<ART>3D-Multiple Object Tracking training task improves passing decision-making accuracy in soccer players
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Authors: Thomas Romeas, Antoine Guldner, Jocelyn Faubert
DOI: 10.1016/j.psychsport.2015.06.002
Year: 2016  |  Pages: 1-9
ASJC codes: 3202
Keywords: Athletes, Perceptual-cognitive training, Small-sided games, Transfer

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<h>ABSTRACT</h>
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Objectives: The ability to perform a context-free 3-dimensional multiple object tracking (3D-MOT) task has been highly related to athletic performance. In the present study, we assessed the transferability of a perceptual-cognitive 3D-MOT training from a laboratory setting to a soccer field, a sport in which the capacity to correctly read the dynamic visual scene is a prerequisite to performance. Design: Throughout pre- and post-training sessions, we looked at three essential skills (passing, dribbling, shooting) that are used to gain the upper hand over the opponent. Method: We recorded decision-making accuracy during small-sided games in university-level soccer players (n = 23) before and after a training protocol. Experimental (n = 9) and active control (n=7) groups were respectively trained during 10 sessions of 3D-MOT or 3D soccer videos. A passive control group (n = 7) did not received any particular training or instructions. Results: Decision-making accuracy in passing, but not in dribbling and shooting, between pre- and post-sessions was superior for the 3D-MOT trained group compared to control groups. This result was correlated with the players' subjective decision-making accuracy, rated after pre- and post-sessions through a visual analogue scale questionnaire. Conclusions: To our knowledge, this study represents the first evidence in which a non-contextual, perceptual-cognitive training exercise has a transfer effect onto the field in athletes.

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<h>INTRODUCTION</h>
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In dynamic sports such as soccer (Association Football), the ability to ‘read the game’
distinguishes skilled from less skilled players (Williams, 2000). However, athletes are
not characterized by superior vision (Abernethy, 1987; Helsen & Starkes, 1999) and visual
training programs have not shown any evidence of transfer to the field (Wood & Abernethy,
1997). Rather, sport scientists identified a number of abilities that are tightly related
to superior anticipation and decision-making to better explain the ability to ‘read the
game’. Anticipation and decision-making represents the human brain's ability to extract
meaningful contextual information from the visual scene and are essential for high-level
performance in sports (Casanova, Oliveira, Williams, & Garganta, 2009). They are typically
referred to as perceptual-cognitive skills, illustrating the role played by both
perceptual and cognitive processes. Two main approaches have been proposed to identify
athletes' perceptual-cognitive superiority. The first and most common theory that supports
athletic expertise relies on the expert performance approach. It reflects comparisons
between elite, sub-elite and/or novice performers in tasks that are domain specific and,
in some cases representative of the behavioral requirements of the competitive setting. In
essence, experts have been shown to be superior to sub-elite and/or novices in sports-
specific tasks including advance visual cue utilization (Abernethy, Gill, Parks, & Packer,
2001; Ward, Williams, & Bennett, 2002), pattern recall and recognition (Abernethy, Baker,
& Côté, 2005; Smeeton, Ward, & Williams, 2004), visual search strategies (Vaeyens, Lenoir,
Williams, & Philippaerts, 2007; Williams, 2000) and the knowledge of situational
probabilities (North & Williams, 2008; Williams, Hodges, North, & Barton, 2006). Those
abilities have been linked to game intelligence. On the other hand, the cognitive
component skill approach examines whether sport expertise influences fundamental cognitive
and perceptual functions outside the sport-specific domain (Nougier, Stein, & Bonnel,
1991). It relies on more fundamental, sport context-free, paradigms that confer a
cognitive fidelity rather than a physical fidelity with the sport environment. In fact, it
is well accepted that physical activity enhances brain plasticity and improves cognitive
and executive functions (for recent reviews see Erickson, Gildengers, & Butters, 2013;
Vivar, Potter, & van Praag, 2013). For example, a significant correlation has been
demonstrated between the results from the executive functions tests (neuropsychological
assessment tool) versus the number of goals and assists the players had scored two seasons
later (Vestberg, Gustafson, Maurex, Ingvar, & Petrovic, 2012). The authors suggested that
results in cognitive function tests predict the success of top-soccer players.
Furthermore, higher order cognitive function has been suggested to be relevant for talent
identification and development in youth soccer players (Verburgh, Scherder, van Lange, &
Oosterlaan, 2014). In a recent meta-analysis, Voss and colleagues showed that expertise in
sport was related to high levels of performance on measures of processing speed and visual
attention (Voss, Kramer, Basak, Prakash, & Roberts, 2010). Moreover, Alves and colleagues
found that volleyball players differed from non-athlete controls on two executive control
tasks and one visuo-spatial attentional processing task (Alves et al., 2013). Furthermore,
interesting significant differences have recently been found between athletes that
outperformed non-athletes in socially realistic multitasking crowd scenes involving
pedestrians crossing streets (Chaddock, Neider, Voss, Gaspar, & Kramer, 2011) or in
learning complex and neutral dynamic visual scenes through a three dimensional multiple
object tracking (3D-MOT) task (Faubert, 2013). These studies support the claim that the
cognitive component approach captures a fundamental cognitive skill associated with
competitive sport training (Voss et al., 2010). Given the emerging evidence of brain
plasticity following learning or injury (Draganski & May, 2008; Ptito, Kupers, Lomber, &
Pietrini, 2012), Faubert and Sidebottom (2012) introduced a perceptual-cognitive training
methodology for athletes (Faubert & Sidebottom, 2012). The technique used is a “highly
leveled” 3D-MOT perceptual-cognitive task because it stimulates a high number of brain
networks that have to work together during the exercise including complex motion
integration, dynamic, sustained and distributed attention processing and working memory.
In an earlier publication by Faubert (2013), the 3D-MOT training technique revealed
striking superior skills in professional athletes compared to sub-elites and novices when
rapidly learning complex and neutral dynamic visual scenes (Faubert, 2013). The results
showed a clear distinction between the level of athletic performance and corresponding
fundamental mental capacities for learning an abstract and demanding dynamic scene task.
The author suggested that rapid learning in complex and unpredictable dynamic contexts is
one of the critical components required for elite performance. Lately, a study revealed
that 3D-MOT performance was most likely related to the athletes' ability to see and
respond to various stimuli on the basketball court, however the simple visuo-motor
reaction time that was not related to any of the basketball specific performance measures
(Mangine et al., 2014). Furthermore, recent neurological evidence has demonstrated the
role of 3D-MOT in enhancing cognitive function in healthy young adults (Parsons et al.,
2014). In fact, 10 sessions of 3D-MOT training improved attention, visual information
processing speed and working memory recorded through neuropsychological tests and
quantitative electroencephalography. In addition, other evidence has demonstrated that
3D-MOT training can show transfer to socially relevant tasks such as biological motion
perception in the elderly (Legault & Faubert, 2012). In sport science and especially in
perceptual-cognitive training studies, focus on transfer measures is essential to
determine whether any improvements observed in the laboratory may transfer back to a live
game situation. A common hypothesis suggests that transfer can occur if the trained and
transfer tasks engage specific overlapping cognitive processes and brain networks (Dahlin,
Neely, Larsson, Backman, & Nyberg, 2008). Studies supporting the expert performance
approach have raised the question of perceptual-cognitive transfer in athletes (Caserta,
Young, & Janelle, 2007; Gabbett, Carius, & Mulvey, 2008; Hopwood, Mann, Farrow, & Nielsen,
2011; Williams, Ward, & Chapman, 2003), however; to our knowledge, studies from the
cognitive component approach have yet to demonstrate this transfer. For instance, Gabbett
et al. (2008) investigated the effects of video-based perceptual training on decision-
making skills during small-sided games (SSG) in elite women soccer players (Gabbett et
al., 2008). Video-based training yielded on-field improvements in passing, dribbling and
shooting decision-making skills. In addition, the use of SSG as a measure of transfer
seemed to be an efficient strategy in capturing the dynamic and strategic components of
soccer. In fact, a major challenge with transfer settings is to develop objective and
sensitive measures of transfer. Soccer is an invasion game where the main goal is to
invade an opponent's territory (offensive scenario) to score and/or to contain space and
regain ball possession (defensive scenario) to avoid conceding goals (Mitchell, Oslin, &
Griffin, 2013). Players have to make different decisions whether they have to defend or to
attack. During the attack, the offensive aspect is to score a goal (e.g. shooting) while
conservation of the ball (e.g. passing, dribbling) is the defensive aspect (Gréhaigne,
Richard, & Griffin, 2012). Passing and shooting the ball have been recognized as important
factors that contribute to the success or improvement of performance in invasion games
(Hughes & Bartlett, 2002). On the other hand, recovering the ball or putting pressure
(e.g. pressing) on the opposing team to regain possession of the ball is the offensive
aspect of the defense. Defending one's goal (e.g. tackling) consists in the defensive
aspect of the defense. Therefore, soccer presents a complex and rapidly changing
environment where different decisions have to be made under pressure and time constraints.
The quality of response to those decision-making situations is crucial in the success of
the team and to improve performance. SSG allows players to experience similar situations
that they encounter in competitive matches while optimizing training duration. It also
reduces space and therefore the amount of time to respond. This process increases the
number of opportunities for decision-making and thus increases the ratio of players'
participation in decision-making (Aguiar, Botelho, Lago, Maças, & Sampaio, 2012). In the
present study, we assessed the transfer capability of perceptual-cognitive 3D-MOT training
void of sports context on offensive decision-making with soccer players. In a dynamic
sport environment such as soccer, players must be able to correctly read the key
information from a visual scene to make accurate decisions. They are usually confronted
with multiple choices. To score goals, players have to select the best options especially
during an offensive scenario. For example, within a split second, players need to decide
whether they protect the ball, when and where to pass or whether they should take a shot
on net. The decision-making skill refers to the capability of individuals to make a choice
and achieve a specific task goal from a set of possibilities (Bar-Eli, Plessner, & Raab,
2011). Becoming an expert in decision-making is thought to be acquired following sport-
specific deliberate practice (10 000 hour rule) (Ericsson, Krampe, & Tesch-Römer, 1993)
even if there is some speculation about the benefits of the involvement in non-sport-
specific activities during the first years of practice (Baker, Cote, & Abernethy, 2003).
This refers to the general benefits of involvement in any physical activities explained
earlier (cognitive component approach). Decision-making in sport relies on three major
cognitive components such as perception, knowledge and decision strategies (Bar-Eli et
al., 2011). Expert decision-makers depend on advanced perceptual and memory processes to
better execute short term decisions. In particular, they rely on advanced visual search
strategies in their central and peripheral vision (Vaeyens et al., 2007) as well as
selective, focused and divided attention (Bar-Eli et al., 2011). While general visual
training programs hardly improve decision-making in sports, 3D-MOT includes dynamic visual
information that has to be processed actively, which is a crucial part of the perceptual
component involved in decision-making. The 3D-MOT selective attention and processing speed
of multiple moving targets task may be a crucial skill to help execute decision-making.
This is supported by studies showing that performance on multiple target tracking tasks is
superior in different kinds of experts such as professional radar operators, video-gamers
and athletes (Allen, McGeorge, Pearson, & Milne, 2004; Green & Bavelier, 2003; Zhang, Yan,
& Yangang, 2009). To train perceptual and attentional processes involved in decision-
making, we used a highly leveled perceptual-cognitive training task that includes complex
motion integration, dynamic, sustained and distributed attention processing and working
memory. Three-dimensional MOT training has already shown evidence in enhancing cognitive
function by improving attention, visual information processing speed and working memory.
Additionally, this is a task in which has previously highlighted athletes' impressive
learning capabilities in complex and dynamic visual scenes. Recently, the technique has
shown training transfer onto a perceptual-cognitive task, such as biological motion
perception, within a laboratory setting. To assess the role of 3D-MOT in decision-making
accuracy on the field, we looked at three essential skills that are used to gain the upper
hand over the opponent throughout soccer offensive scenarios. We suggested that passing,
dribbling and shooting could be improved in the 3D-MOT trained group compared to control
groups between pre- and post-training sessions.

<hs>  Ethics statement</hs>
  ~~~~~~~~~~~~~~~~

The experimental protocol and related ethical issues were evaluated and approved by the
Comité d’Éthique de la Recherche en Santé of Université de Montréal. All subjects were
given verbal and written information about the study and gave their verbal and written
informed consent to participate.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Twenty-three young males from the Carabins soccer team of Université de Montréal
participated (Table 1). All subjects reported normal or corrected-to-normal vision (6/6 or
better) with normal stereoacuity (50 s of arc or better). None of the subjects had ever
taken part in any previous 3D-MOT or perceptual-cognitive experiment.

        <hss>Laboratory tests</hss>

        The 3D-MOT experiment and 3D soccer videos (active control) were conducted using a
        fully immersive virtual environment thanks to a head-mounted display (Sony HMZ-T2)
        in a room with controlled lighting. The head-mounted display is a 3D-ready system
        that allows image projection on two OLED panels with a resolution of 1280 × 720
        pixels and covering a maximal visual field of 45°. Inter-pupillary distance was
        adjusted for each subject. The 3D-MOT experiment was supported by a Hewlett-
        Packard ProBook 4530s with a Core i5 processor and an Intel HD Graphics 3000
        graphic card. The 3D soccer videos, from the official 2010 FIFA world cup™ blu-
        ray, were played on a Sony PlayStation 3™ system. Both the computer (for 3D-MOT)
        and the Sony PlayStation 3™ (for 3D soccer videos) were connected to the head-
        mounted display to offer an immersive experience.

        <hss>Field test</hss>

        Decision-making assessment was conducted during standardized SSG before and after
        the training period. SSG consisted of standard 5 × 5 soccer matches on a 30 m × 40
        m interior turf soccer field to avoid weather influence. Coaches were positioned
        on the side of the pitch to give their instructions as in a real game situation.
        Players were randomly distributed in five different teams composed of five players
        each including a keeper. The five teams were randomly facing each other two times
        during ten games of 5 min each. Every player was then taking part in eight games
        of 5 min for a total of 40 min during both pre- and post-sessions. Players who
        were waiting for the start of the next game were stretching or exercising with the
        ball. SSG were recorded using two video cameras (Sony, HDR-CX260VW). Cameras were
        positioned in the bleachers of the stadium, approximately 10 m above the field of
        play to cover the entire playing area. Players were identified by jerseys and
        numbers. The video recordings were analyzed using Dartfish Connect v6.0.

        <hss>Decision-making coding</hss>

        On-field decision making ability during SSG was coded using standardized coding
        criteria adapted from previous studies (French & Thomas, 1987; Gabbett et al.,
        2008). Passing, dribbling and shooting were the skills assessed (see Table 2). The
        coding instrument made it possible to separate the cognitive decision-making
        component of performance from the motor skill execution component of performance.
        When initially used by French and Thomas (1987) in basketball players, the coding
        instrument was built to evaluate three aspects of performance: control (e.g. a
        player catches the ball), decision (e.g. a player decides which action is
        appropriate), and execution (e.g. a player then executes the skill). In a recent
        study, Gabbett et al. (2008) adapted the instrument for coding decision-making in
        soccer. They assessed one aspect of performance, the decision, which is central in
        the context of our study. The decision component involves selection of the skill
        (e.g. pass, dribble, shoot), as well as which teammate to pass to, what direction
        to dribble, when to shoot, when to stop dribbling, and so on. The quality of each
        decision was coded as 1 for an appropriate decision and 0 for an inappropriate
        decision according to the criteria (Table 2). Decisions that were neither
        appropriate nor inappropriate were not coded. For instance, when the player made a
        pass that did not: a) directly or indirectly created a shot attempt; b) went to a
        teammate who was in a better position than the passer; c) went to a player who was
        closely guarded; d) being intercepted or cause a turn over; e) reached an area of
        the field where no teammates was positioned or out of the field of play. Moreover,
        where the player did not have time to assess the options (e.g. player was tackled
        as soon as he received the ball) the disposal was not considered for assessment.
        Decision-making coding was assessed by an experienced soccer coach blinded to the
        experimental protocol and trained to use the instrument for coding. Then, the
        total score of each player by session was converted to percentage for analysis.
        Percentage accuracy values were established for each participant by dividing the
        number of points awarded by the total number available and then multiplying by
        100.

        <hss>Assessment of subjective judgements</hss>

        To assess whether perceptual-cognitive learning was directly perceived or related
        to unconscious processes, we used participants' judgments in on-field decision-
        making. Players' confidence levels in decision-making accuracy were assessed
        promptly after pre- and post-sessions using the Sport Performance Scale
        application developed in our laboratory
        (http://vision.opto.umontreal.ca/english/technologies/apps_en.html). In the
        present study, we used a simple visual analog scale (rated from min [0%] to max
        [100%]) to assess players' confidence levels in decision-making. Measurements were
        performed on a ‘10′ Samsung Galaxy Tab II™’ tablet. The following instructions
        were individually given to the players: 1) to rate their ‘decision-making accuracy
        during the last play’ and to do so by 2) scrolling their finger on the visual
        analog scale of the touchscreen tablet until they had reached the appropriate
        score. Decision-making accuracy was described and contextualized on the scale as
        follows: ‘Your level of accuracy in anticipating teammate or opponent movements
        and to deliver a correct response (e.g. assist, shot)’. No time constraint was
        imposed and each player took approximately 15 s to both receive the instructions
        and give an answer.

        3D-MOT

        The 3D-MOT task (Fig. 1) was working under the NeuroTracker™ system licenced by
        the Université de Montréal to CogniSens Athletics, Inc. (Montreal, Canada). The
        CORE mode of the NeuroTracker™ system was used. During the exercise, four of eight
        projected spheres had to be tracked within a 3D virtual volumetric cube space with
        virtual light grey walls, subtending a visual angle of 42°. The spheres followed a
        linear trajectory in the 3D virtual space. Deviation occurred only when the balls
        collided against each other or the walls. In order to support an effective
        distribution of attention, a fixation spot was presented in the center of the cube
        throughout the experimentation. An instructed part of the training task was to
        focus on this green fixation square throughout the tracking phase which serves as
        an anchor point from which to extract information from the visual periphery
        (Ripoll, 1991). In other words, the anchor point is localized in a central
        position where the fovea could be directed while the relative movement of the
        spheres could be monitored using the peripheral visual field which is also able to
        detect movement (McKee & Nakayama, 1984). The effective use of such a strategy has
        already been demonstrated in experts through a variety of sports (e.g. Ripoll,
        Kerlirzin, Stein, & Reine, 1995; Savelsbergh, Williams, Van der Kamp, & Ward,
        2002). Each session, based on a staircase procedure, lasted about 8 min. The
        staircase procedure consists of increasing speed if the subject got all the
        indexed targets or decreasing speed if at least one target was missed. Speed
        thresholds were then evaluated using a 1-up 1-down staircase procedure (Levitt,
        1971). After each correct response, the dependent variable (speed ball
        displacement) was increased by 0.05 log and decreased by the same proportion after
        each incorrect response, resulting in a threshold criterion of 50%. The staircase
        was interrupted after eight inversions and the threshold was estimated by the mean
        of the speeds at the last four inversions.

        3D soccer videos

        The 3D soccer videos consisted of game replay from group and knock-out stages of
        the FIFA world cup 2010. Participants went through the whole blu-ray video once
        during the first four sessions of training. They were asked to watch soccer
        actions during approximately 25 min/session. During the last six sessions of
        training, participants would watch the 3D soccer videos for a second time (20
        min/session) and were challenged by 5 min interviews during which questions about
        decision-making accuracy occurring throughout the soccer videos were raised (e.g.
        Did the scorer make the right decision on the first goal of Brazil against North
        Korea according to the situation? What would you have done in his place: pass,
        dribble, shoot?). The questions only ensured that the players were focusing on the
        videos and reinforced their belief that the training was effective. Importantly,
        no feedback was given to the players after they answered.

<hs>  Procedure</hs>
  ~~~~~~~~~

We used a computer randomization script to allocate players into three separate groups
including an experimental (n = 9), active (n = 7) and passive (n = 7) control group. All
of them completed a pre- and post-on-field session during standardized SSG. Participants
were constrained to not take part in any other training research activities throughout the
duration of the testing period. In addition, the university athletes maintained a similar
weekly routine, which was limited to their academic class schedule, training and soccer
practice.

        <hss>Experimental group</hss>

        Players were actively trained ten times; twice a week for five consecutive weeks.
        During each evaluation, they participated in three CORE sessions of 3D-MOT. All of
        the observers reached a total of thirty sessions at the end of the training. Each
        participant followed the same standard procedure and completed each task while
        seated.

        <hss>Active control</hss>

        Participants focused on 3D soccer videos from the official 2010 FIFA world cup™
        blu-ray twice a week for a five week period and a total of 10 sessions. Players
        were informed that this training was expected to have a positive effect on their
        decision-making performance during soccer games. This procedure was undertaken to
        provide an expectancy set for training benefits comparable to that of the
        perceptual-cognitive training group (cf Williams et al., 2003).

        <hss>Passive control</hss>

        No instruction or training was provided for this group.

<hs>  Analysis</hs>
  ~~~~~~~~

Due to injuries, two players from the experimental and the passive control groups were
removed from the decision-making analysis. As the two (active–passive) control groups
showed no statistical differences and small sample size, they were analyzed as a single
control group. On-field decision-making accuracy in passing, dribbling and shooting was
compared between the experimental and the active–passive control group. To find out
whether the players' performance was different between pre- and post-sessions in the
3D-MOT group compared to the other group, we used a mixed-design analysis of variance
(ANOVA; group × sessions). A Levene test yielded no significant differences in homogeneity
between groups (p > 0.05). We conducted paired Student t-tests to compare pre- and post-
evaluation of players' subjective decision-making accuracy, rated by the Sport Performance
Scale, in the 3D-MOT and the active–passive control group. Athletes' 3D-MOT speed
threshold means analysis between pre and post-training showed a comparable improvement as
previously demonstrated in athletes (Faubert, 2013; Faubert & Sidebottom, 2012).

        <hss>Objective decision-making assessment</hss>

        On-field decision-making analysis revealed a significant improvement in passing
        accuracy only for the 3D-MOT trained group between pre- and post-sessions compared
        to the other groups (F(1, 17) = 4.708, p = 0.044, ɳ2 = 0.162) (Fig. 2A). No
        significant difference was observed in decision-making accuracy for dribbling
        (F(1, 14) = 3.628, p = 0.078, ɳ2 = 0.200) and shooting (F(1, 13) = 0.210, p =
        0.654, ɳ2 = 0.015) between pre- and post-sessions for the experimental compared to
        the other groups. However, there is a clear tendency for improvement in dribbling
        that did not reach the significance threshold (p = 0.078). We suggest that a high
        variance could explain those results. In fact, mean number of dribbles (5.1 ± 0.63
        SEM) and shots (4.0 ± 0.52 SEM) during games were far too small compared to mean
        number of passes (15.5 ± 0.93 SEM) to reach a decisive conclusion on the impact of
        3D-MOT training on the on-field performance for these abilities.

        <hss>Subjective decision-making assessment</hss>

        A general improvement in subjective confidence levels of decision-making accuracy
        between pre- and post-sessions was observed in the 3D-MOT group following a paired
        student t-test analysis (t[6] = −3.547, p = 0.012) while no difference was
        observed in the active–passive control group (t[11] = −1.515, p = 0.158) (Fig.
        2B).

<h>DISCUSSION</h>
----------

This study was designed to assess the transferability of perceptual-cognitive training
void of sports context on decision-making accuracy in soccer players. The main result
demonstrates a significant 15% improvement in passing decision-making accuracy in soccer
players trained with the 3D-MOT technique compared to active and passive controls.
Furthermore, this result was corroborated with a proportional quantitative increase in
subjective decision-making accuracy for the experimental group. Finally, players' 3D-MOT
speed thresholds confirmed their superior capacity for processing a complex and dynamic
visual scene task. It should be noted that even if we observed a trend (p = 0.078) in
favor of an improvement in dribbling decision-making for the 3D-MOT group, no significant
differences were found in dribbling and shooting abilities between groups. However, the
low number of dribbles and shots attempted by the players restrict our ability to firmly
conclude that the 3D-MOT training does not affect these decision-making abilities. For
this reason, we will center the discussion on passing decision-making.

<hs>  Decision-making improvement in passing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the present study, we trained soccer players to track multiple elements through
virtual, dynamic, complex and neutral (sport environment free) visual scenes using a
perceptual-cognitive 3D-MOT technique. Ten training sessions in laboratory were sufficient
to improve players' passing decision-making accuracy by 15% between pre- and post-sessions
of SSG. Meanwhile, the active (10 sessions of 3D soccer matches) and passive control
groups did not show any improvement. Considering 3D-MOT transferability has already been
shown in a biological motion perception laboratory task (Legault & Faubert, 2012), this
study represents the first evidence of 3D-MOT transfer from the laboratory to the field.
Moreover, we argued in the introduction that expertise in athletes has been contextualized
according to both the (sport specific) expert performance skills approach and the (sport
environment free) cognitive component skills approach. While few studies have reported
transfer following perceptual-cognitive training in specific sport contexts, the present
study is, to our knowledge, the first evidence in favor of a non-contextual perceptual-
cognitive training transfer on the sport-field. According to the most accepted theory, it
is suggested that specific overlapping cognitive processes and brain networks were engaged
for the laboratory 3D-MOT task and on-field decision-making process during SSG (Dahlin et
al., 2008). Potential implications of 3D-MOT in decision-making improvement are discussed
below.

        <hss>Attentional tracking of multiple elements</hss>

        One of the critical requirements to allow decision-making is to accurately extract
        meaningful information from the visual scene which is possible by using both
        perceptual and attentional processes. Attention and concentration are crucial
        abilities that affect the decision-making of athletes (Bar-Eli et al., 2011).
        During a soccer action, an athlete has to divide attention on the field (e.g.
        teammates, opponents, ball), to use selective attention (e.g. which player to give
        the ball to) and to focus attention (e.g. staring at the net to score). To this
        purpose, many benefits may arise from the highly leveled 3D-MOT technique. A core
        feature of the 3D-MOT technique relies on distributed attention on a number of
        separated dynamic elements (Cavanagh & Alvarez, 2005). The ability to track
        multiple elements has been reported to be superior with the involvement in sport
        activities in adults and youngsters during laboratory MOT tasks (Barker, Allen, &
        McGeorge, 2010; Trick, Jaspers-Fayer, & Sethi, 2005; Zhang et al., 2009). This
        result is not surprising knowing that the ability to maintain attention on
        multiple stimuli or locations for quite a prolonged period of time is important
        for sport (Memmert, 2009). Importantly the 3D-MOT technique includes speed
        thresholds as a dependent variable which is considered as a crucial part of MOT
        performance by requiring more attentional resources to track at higher speeds
        (Feria, 2012). Recently, neurological evidence has demonstrated the role of 3D-MOT
        in improving attention, visual information processing speed and working memory
        (Parsons et al., 2014). From other imagery studies, the MOT technique has reported
        activation of higher-level brain areas involved in attentional processes (Culham
        et al., 1998; Howe, Horowitz, Morocz, Wolfe, & Livingstone, 2009). These areas
        include parietal and frontal regions of the cortex and are believed to be
        responsible for attention shifts and eye movement. As well, the middle temporal
        complex has, not surprisingly, been implicated during MOT processing for motion
        perception (Culham et al., 1998). These brain pathways could potentially be
        involved during the action of reading the play in soccer players; a perception-in-
        action process which is known to activate both dorsal and ventral streams (Goodale
        & Milner, 1992). Training the brain to simultaneously activate those networks may
        possibly help to enhance perceptual-cognitive execution in athletes. In this
        sense, the attentional tracking of multiple elements during 3D-MOT could overlap
        brain networks required during decision-making. Training on 3D-MOT could serve as
        a tool to help automatize those networks and could lead to superior decision-
        makings abilities. Future imagery or electroencephalography study will help us to
        explain the neural process behind 3D-MOT improvements.

        <hss>Engagement of visual search strategies in peripheral vision</hss>

        Beyond the attentional tracking of multiple elements, the 3D-MOT technique engages
        wide visual field stimulation especially because peripheral vision has been
        suggested to play an important role in the performance of sports teams (Knudson &
        Kluka, 1997). With players spread all along a field of about 60 m in width, soccer
        utilizes a large amount of peripheral vision. Peripheral vision refers to the
        ability to detect and react to stimuli outside of foveal vision. In soccer
        referees, peripheral vision has been showed to be useful in decision-making
        accuracy (De Oliveira, Orbetelli, & De Barros Neto, 2011). To extract meaningful
        information from the visual scene, including the periphery, expert athletes rely
        on advanced visual search strategies (Vaeyens et al., 2007; Williams, 2000). There
        is evidence to support that relative motion information is picked up effectively
        via peripheral vision (Williams, Davids, & Williams, 1999). A common occurrence
        during a game is to use foveal and peripheral vision simultaneously. For instance,
        in ‘time-constrained’ situations (e.g. 5 vs 5 situation), skilled soccer players
        fixate the ball in foveal vision while using peripheral vision to monitor the
        positions of teammates and opponents in the periphery (Williams & Davids, 1997). A
        study by Vaeyens et al. (2007) showed that successful soccer decision-makers use
        the player in possession of the ball as the central point on which to fixate gaze
        to explore and pick up the key information underpinning decision making in
        offensive situations (Vaeyens et al., 2007). Researchers have reported the use of
        those ‘visual pivots’ in other sports (Ripoll et al., 1995; Savelsbergh et al.,
        2002) and is a reason why 3D-MOT includes such an anchor point. On the other hand,
        it has been proposed that athletes from visual demanding sports (e.g. netball) can
        generate more frequent (and shorter) eye movements therefore enabling information
        to be extracted for the visual field more rapidly (Morgan & Patterson, 2009).
        Research on eye movement during MOT experiments have identified viewing strategies
        exercised by observers. When multiple targets (e.g. 3 spheres) were presented,
        participants usually adopted a ‘center-looking’ strategy as if they were grouping
        the targets into a single object (e.g. triangle) and were looking closer to the
        center of the object formed by the targets (Fehd & Seiffert, 2008). This strategy
        is in contrast to a ‘target-looking’ strategy where participants would saccade
        from target to target. However, another study by Fehd and Seiffert (2010)
        demonstrated that participants often engaged in both ‘target-looking’ and ‘center-
        looking’ strategies by switching their gaze from the center to the targets and so
        on (Fehd & Seiffert, 2010). Visual search strategies involved during MOT could be
        closely linked to those engaged by sport experts during the process of extracting
        visual information from the action. By training those strategies, which are part
        of the perceptual component involved in decision-making, could help to improve in
        game decision-making.

        <hss>Virtual reality (3D vision)</hss>

        Another major asset of the 3D-MOT methodology is the involvement of virtual
        reality, a technology that is recognized as an important tool to potentially
        improve sport performance (Bideau et al., 2010; Carling, Reilly, & Williams,
        2009). Immersive environments, such as those afforded by virtual reality, engender
        automaticity and therefore implicit learning – which yields decision-making that
        is robust under pressure (Patterson, Pierce, Bell, Andrews, & Winterbottom, 2009).
        Moreover, virtual reality involves stereoscopy (binocular disparity) which is
        required in situations where fast, complex and dynamic elements collide or
        overlap. For instance, stereoscopy has been shown to help in disambiguating object
        occlusions when processing dynamic visual scenes (Faubert & Allard, 2013). This is
        typically the kind of critical situation that can usually be found in soccer when
        players are close to each other (e.g. an attacker wants to make a deep run from
        behind the defender but needs to stay close until the last moment to avoid being
        called offside). Whether it is fast attentional multiple element tracking, wide
        visual field stimulation or stereoscopy, all those components are involved during
        sport actions. Therefore, previous results revealing athletes' extraordinary
        skills for rapidly learning complex and neutral dynamic visual scenes using the
        3D-MOT technique appear logical (Faubert, 2013). This non-contextual perceptual-
        cognitive training seems to involve higher-level cognitive abilities subserved by
        the central nervous system. Presumably, 3D-MOT may capture the dynamic components
        of soccer actions where players have to maintain focus and attention on teammates,
        opponents or the ball to make the best decisions. In summary, this paradigm, even
        if void of sports context, is in keeping with the complex and dynamic nature of
        strategic sport such as soccer. From a sport performance point of view, the result
        is of particular interest in regards to the implication of decision-making and
        passing in modern soccer. Today's elite soccer players require faster decision-
        making than ever mainly because as a competitive sport, the game of soccer is
        increasing in ball speed (15%) as well as the intensity of play and passing rate
        (35%) according to an analysis on world cup soccer final games from the last 40
        years (Wallace & Norton, 2014). Whereas accurately passing the ball to a teammate
        is an essential and fundamental ability required by soccer players (Ali, 2011), it
        also represents the essence of keeping the ball and the source of scoring
        opportunities (Chassy, 2013). The 3D-MOT technique could play a crucial role in
        improving passing accuracy in elite soccer players and could be implemented in
        training centers.

<hs>  Subjective decision-making assessment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Results of subjective decision-making assessment, collected from the Sport Performance
Scale, support the on-field improvement observed in the 3D-MOT training group. One
possible explanation is that it confirms that players who received the perceptual-
cognitive training were conscious of their on-field improvement in decision-making after
the training. Furthermore, confidence level improvement in decision-making accuracy of
trained players was quantitatively proportional to the improvement in decision-making
accuracy rated during video analysis. These results seem to demonstrate that passing
decision-making accuracy improvement in the 3D-MOT group represents a meaningful training
effect rather than the result of increased familiarity with the test environment or
expectancy set for the training benefits.

<hs>  Athlete skills for learning complex and neutral dynamic visual scenes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The 3D-MOT speed thresholds of soccer players were qualitatively similar to those
previously obtained in professional and elite-amateurs athletes showing superior capacity
for processing a complex and dynamic visual scene task (Faubert, 2013; Faubert &
Sidebottom, 2012). This ability has been argued to be one of the critical components for
elite performance and 3D-MOT performance has been shown to be highly associated with
athletes' performance level (Faubert, 2013; Mangine et al., 2014).

<hs>  Future requirements and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To resolve the issue of whether this training can also transfer to better decision making
in regards to dribbles and shooting decisions, we may have to use a different standardized
SSG situation. For instance, we could reduce pitch size to favor ‘one-on-one’ situations
(increase dribbling ratio) and direct ‘goal-to-goal’ actions (increase shooting ratio). To
underline the potential of non-contextual 3D-MOT training, it will also be interesting to
address the degree of transfer of the technique in other invasion (e.g. hockey) or net
(e.g. tennis) games. Another important aspect is to evaluate perceptual-cognitive skills
in youngsters with the 3D-MOT technique. Using memory recall and structured pattern of
play, Ward and Williams (2003) have previously demonstrated superior perceptual-cognitive
skills in elite compared to sub-elites soccer players as early as 9 years old (Ward &
Williams, 2003). However, little or no studies have compared perceptual-cognitive skills
of elite and novice youngsters using a perceptual-cognitive method void of sports context.
One study has revealed better MOT performance in children involved in physical activity
compared to more sedentary children (Trick et al., 2005). Knowing that rapid learning in
complex and dynamic visual scenes is a critical component for sport performance (Faubert,
2013) and that 3D-MOT performance has been linked to sport specific performance measures
(Mangine et al., 2014), 3D-MOT speed thresholds could serve as a tool to determine a
player's ability. Non-contextual perceptual-cognitive techniques may also have
implications in the screening or detection of new talent.

<h>CONCLUSION</h>
----------

Expertise in athletes has been well characterized using specific as well as non-contextual
perceptual-cognitive paradigms. However, the present study represents the first evidence
of an on-field improvement (transfer) following a laboratory perceptual-cognitive training
void of sports context. In fact, training to process complex and dynamic visual scenes has
not only revealed superior learning ability in soccer players but has led to improvements
in passing decision-making accuracy in the field as well. Future laboratory and in-field
studies will be needed to evaluate the degree of transferability of such training on other
dynamic sports.

<h>CONFLICT OF INTEREST</h>
--------------------

One of the authors is director of Visual Psychophysics and Perception Laboratory at the
University of Montreal and he is the Chief Science Officer of Cognisens Athletics Inc. who
produces the commercial version of the NeuroTracker used in this study. In this capacity,
he holds shares in the company. This does not alter our adherence to your journal policies
on sharing data and materials.


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<ART>A Duet for one
==============

Authors: Karl Friston, Christopher Frith
DOI: 10.1016/j.concog.2014.12.003
Year: 2015  |  Pages: 390-405
ASJC codes: 3204, 3205
Keywords: Active inference, Attention, Bayesian, Communication, Generalised synchrony, Predictive coding, Sensory attenuation, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This paper considers communication in terms of inference about the behaviour of others (and our own behaviour). It is based on the premise that our sensations are largely generated by other agents like ourselves. This means, we are trying to infer how our sensations are caused by others, while they are trying to infer our behaviour: for example, in the dialogue between two speakers. We suggest that the infinite regress induced by modelling another agent - who is modelling you - can be finessed if you both possess the same model. In other words, the sensations caused by others and oneself are generated by the same process. This leads to a view of communication based upon a narrative that is shared by agents who are exchanging sensory signals. Crucially, this narrative transcends agency - and simply involves intermittently attending to and attenuating sensory input. Attending to sensations enables the shared narrative to predict the sensations generated by another (i.e. to listen), while attenuating sensory input enables one to articulate the narrative (i.e. to speak). This produces a reciprocal exchange of sensory signals that, formally, induces a generalised synchrony between internal (neuronal) brain states generating predictions in both agents. We develop the arguments behind this perspective, using an active (Bayesian) inference framework and offer some simulations (of birdsong) as proof of principle.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

One of the most intriguing issues in (social) neuroscience is how people infer the mental
states and intentions of others. In this paper, we take a formal approach to this issue
and consider communication in terms of mutual prediction and active inference (De Bruin &
Michael, 2014; Teufel, Fletcher, & Davis, 2010). The premise behind this approach is that
we model the causes of our sensorium – and adjust those models to maximise Bayesian model
evidence or, equivalently, minimise surprise (Brown & Brün, 2012; Kilner, Friston, &
Frith, 2007). This perspective on action and perception has broad explanatory power in
several areas of cognitive neuroscience (Friston, Mattout, & Kilner, 2011) – and enjoys
support from several lines of neuroanatomical and neurophysiological evidence (Egner &
Summerfield, 2013; Rao & Ballard, 1999; Srinivasan, Laughlin, & Dubs, 1982). Here, we
apply this framework to communication and consider what would happen if two Bayesian
brains tried to predict each other. We will see that Bayesian brains do not predict each
other – they predict themselves; provided those predictions are enacted. The enactment of
sensory (proprioceptive) predictions is a tenet of active inference – under which we
develop this treatment. In brief, we consider the notion that a simple form of
communication emerges (through generalised synchrony) if agents adopt the same generative
model of communicative behaviour. So how do prediction and generative models speak to
theory of mind? The premise here is that we need to infer – and therefore predict – the
causes of sensations to perceive them. For example, to perceive a falling stone we have to
appeal (implicitly) to a model of how objects move under gravitational forces. Similarly,
the perception of biological motion rests on a model of how that motion is caused. This
line of argument can be extended to the perception of intentions (of others or ourselves)
necessary to explain sensory trajectories; particularly those produced by communicative
behaviour. The essential role of inference and prediction has been considered from a
number of compelling perspectives: see (Baker, Saxe, & Tenenbaum, 2009; Frank & Goodman,
2012; Goodman & Stuhlmuller, 2013; Kiley Hamlin, Ullman, Tenenbaum, Goodman, & Baker,
2013; Shafto, Goodman, & Griffiths, 2014). This Bayesian brain perspective emphasises the
role of prediction in making inferences about the behaviour of others; particularly in
linguistic communication. We pursue exactly the same theme; however, in the context of
active inference. Active inference takes the Bayesian brain into an embodied setting and
formulates action as the selective sampling of data to minimise uncertainty about their
causes. This provides a natural framework within which to formulate communication, which
is inherently embodied and enactivist in nature. In brief, we hope to show that active
inference accounts for the circular (Bayesian) inference that is inherent in
communication. The very notion of theory of mind speaks directly to inference, in the
sense that theories make predictions that have to be tested against (sensory) data. In
what follows, we focus on the implicit model generating predictions: imagine two brains,
each mandated to model the (external) states of the world causing sensory input. Now
imagine that sensations can only be caused by (the action of) one brain or the other. This
means that the first brain has to model the second. However, the second brain is modelling
the first, which means the first brain must have a model of the second brain, which
includes a model of the first – and so on ad infinitum. At first glance, the infinite
regress appears to preclude a veridical modelling of either brain’s external states (i.e.,
the other brain). However, this infinite regress dissolves if the two brains are formally
similar and each brain models the sensations caused by itself and the other as being
generated in the same way. In other words, if there is a shared narrative or dynamic that
both brains subscribe to, they can predict each other exactly, at least for short periods
of time. This is basic idea that we pursue in the context of active inference and
predictive coding. In fact, we will see that this solution is a necessary and emergent
phenomenon, when two or more (formally similar) active inference schemes are coupled to
each other. Mathematically, the result of this coupling is called generalised
synchronisation (aka synchronisation of chaos). Generalized synchrony refers to the
synchronization of chaotic dynamics, usually in skew-product (i.e., master–slave) systems
(Barreto, Josic, Morales, Sander, & So, 2003; Hunt, Ott, & Yorke, 1997). However, we will
consider generalized synchrony in the context of reciprocally coupled dynamical (active
inference) systems. This sort of generalized synchrony was famously observed by Huygens in
his studies of pendulum clocks – that synchronized themselves through the imperceptible
motion of beams from which they were suspended (Huygens, 1673). This nicely illustrates
the action at a distance among coupled dynamical systems. Put simply, generalised
synchronisation means that knowing the state of one system (e.g., neural activity in the
brain) means that one can predict the states of the other (e.g., another’s brain). The
sequence or trajectory of states may not necessarily look similar but there is a
quintessential coupling in the sense that the dynamics of one system can be predicted from
state of another. In this paper, we will illustrate the emergence of generalized
synchronization when two predictive coding schemes are coupled to each other through
action. In fact, we will illustrate a special case of generalized synchrony; namely,
identical synchronization, in which there is a one-to-one map between the states of two
systems. In this case, there is a high mutual predictability and the fluctuations in the
states appear almost the same. In short, we offer generalized synchronization as a
mathematical image of communication (of a simple sort) that enables two Bayesian brains to
entrain each other and, effectively, share the same dynamical narrative. This paper
comprises five sections. The first provides a brief review of active inference and
predictive coding, with a focus on the permissive role of sensory attenuation when acting
on the world. In predictive coding, sensory attenuation is a special case of optimising
the precision or confidence in sensory (and extrasensory) information that is thought to
be encoded by the gain of neuronal populations encoding prediction errors (Clark, 2013a;
Feldman & Friston, 2010). This takes us into the realm of cortical gain control and
neuromodulation – that may be closely tied to synchronous gain and the oscillatory
dynamics associated with binding, attention and dynamic coordination (Fries, Womelsdorf,
Oostenveld, & Desimone, 2008; Womelsdorf & Fries, 2006). In the second section, we
introduce a particular model that is used to illustrate perception, action and the
perception of action in the context of communication. This model has been used previously
to illustrate several phenomena in perception; such as perceptual learning, repetition
suppression, and the recognition of stimulus streams with deep hierarchical structure
(Friston & Kiebel, 2009; Kiebel, Daunizeau, & Friston, 2008). In the third section, we
provide a simple illustration of omission related responses – that are ubiquitous in
neurophysiology and disclose the brain’s predictive proclivity. In the fourth section, we
use this model to illustrate the permissive role of sensory attenuation in enabling action
by simulating a bird that sings to itself. The purpose of this section is to show that
song production requires the attenuation of sensory input during singing – that would
otherwise confound perceptual inference due to sensorimotor delays. This leads to the
interesting (and intuitive) notion that the sensory consequences of acting have to be
attenuated in order to act. This means that one can either talk or listen but not do both
at the same time. Armed with this insight, we then simulate – in the final section – two
birds that are singing to themselves (and each other) and examine the conditions under
which generalised synchrony emerges. These simulations are offered as proof of principle
that communication (i.e., a shared dynamical narrative) emerges when two dynamical systems
try to predict each other.

<h>ACTIVE INFERENCE AND PREDICTIVE CODING</h>
--------------------------------------

Recent advances in theoretical neuroscience have inspired a (Bayesian) paradigm shift in
cognitive neuroscience. This shift is away from the brain as a passive filter of
sensations towards a view of the brain as a statistical organ that generates hypotheses or
fantasies (from Greek phantastikos, the ability to create mental images, from
phantazesthai), which are tested against sensory evidence (Gregory, 1968). This
perspective dates back to the notion of unconscious inference (Helmholtz, 1866/1962) and
has been formalised in recent decades to cover deep or hierarchical Bayesian inference –
about the causes of our sensations – and how these inferences induce beliefs, movement and
behaviour (Clark, 2013b; Dayan, Hinton, & Neal, 1995; Friston, Kilner, & Harrison, 2006;
Hohwy, 2013; Lee & Mumford, 2003).

<hs>  Predictive coding and the Bayesian brain</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Modern formulations of the Bayesian brain – such as predictive coding – are now among the
most popular explanations for neuronal message passing (Clark, 2013b; Friston, 2008; Rao &
Ballard, 1999; Srinivasan et al., 1982). Predictive coding is a biologically plausible
process theory for which there is a considerable amount of anatomical and physiological
evidence (Friston, 2008; Mumford, 1992). See (Bastos et al., 2012) for a review of
canonical microcircuits and hierarchical predictive coding in perception and (Adams,
Shipp, & Friston, 2012; Shipp, Adams, & Friston, 2013) for a related treatment of the
motor system. In these schemes, neuronal representations in higher levels of cortical
hierarchies generate predictions of representations in lower levels. These top–down
predictions are compared with representations at the lower level to form a prediction
error (usually associated with the activity of superficial pyramidal cells). The ensuing
mismatch signal is passed back up the hierarchy, to update higher representations
(associated with the activity of deep pyramidal cells). This recursive exchange of signals
suppresses prediction error at each and every level to provide a hierarchical explanation
for sensory inputs that enter at the lowest (sensory) level. In computational terms,
neuronal activity encodes beliefs or probability distributions over states in the world
that cause sensations (e.g., my visual sensations are caused by a face). The simplest
encoding corresponds to representing the belief with the expected value or expectation of
a (hidden) cause. These causes are referred to as hidden because they have to be inferred
from their sensory consequences. In summary, predictive coding represents a biologically
plausible scheme for updating beliefs about states of the world using sensory samples: see
Fig. 1. In this setting, cortical hierarchies are a neuroanatomical embodiment of how
sensory signals are generated; for example, a face generates luminance surfaces that
generate textures and edges and so on, down to retinal input. This form of hierarchical
inference explains a large number of anatomical and physiological facts as reviewed
elsewhere (Adams et al., 2012; Bastos et al., 2012; Friston, 2008). In brief, it explains
the hierarchical nature of cortical connections; the prevalence of backward connections
and explains many of the functional and structural asymmetries in the extrinsic (between
region) connections that link hierarchical levels (Zeki & Shipp, 1988). These asymmetries
include the laminar specificity of forward and backward connections, the prevalence of
nonlinear or modulatory backward connections (that embody interactions and nonlinearities
inherent in the generation of sensory signals) and their spectral characteristics – with
fast (e.g., gamma) activity predominating in forward connections and slower (e.g., beta)
frequencies that accumulate evidence (prediction errors) ascending from lower levels.

<hs>  Precision engineered message passing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

One can regard ascending prediction errors as broadcasting ‘newsworthy’ information that
has yet to be explained by descending predictions. However, the brain has to select the
channels it listens to – by adjusting the volume or gain of prediction errors that compete
to update expectations in higher levels. Computationally, this gain corresponds to the
precision or confidence associated with ascending prediction errors. However, to select
prediction errors, the brain has to estimate and encode their precision (i.e., inverse
variance). Having done this, prediction errors can then be weighted by their precision so
that only precise information is accumulated and assimilated at high or deep hierarchical
levels. As for all expectations, expected precision maximises Bayesian model evidence (see
Appendix). The broadcasting of precision-weighted prediction errors rests on gain control
at a synaptic level (Moran et al., 2013). This neuromodulatory gain control corresponds to
a (Bayes-optimal) encoding of precision in terms of the excitability of neuronal
populations reporting prediction errors (Feldman & Friston, 2010; Shipp et al., 2013).
This may explain why superficial pyramidal cells have so many synaptic gain control
mechanisms; such as NMDA receptors and classical neuromodulatory receptors like D1
dopamine receptors (Braver, Barch, & Cohen, 1999; Doya, 2008; Goldman-Rakic, Lidow,
Smiley, & Williams, 1992; Lidow, Goldman-Rakic, Gallager, & Rakic, 1991). Furthermore, it
places excitation-inhibition balance in a prime position to mediate precision engineered
message passing within and among hierarchical levels (Humphries, Wood, & Gurney, 2009).
The dynamic and context sensitive control of precision has been associated with
attentional gain control in sensory processing (Feldman & Friston, 2010; Jiang,
Summerfield, & Egner, 2013) and has been discussed in terms of affordance in active
inference and action selection (Cisek, 2007; Frank, Scheres, & Sherman, 2007; Friston et
al., 2012). Crucially, the delicate balance of precision at different hierarchical levels
has a profound effect on veridical inference – and may also offer a formal understanding
of false inference in psychopathology (Adams, Stephan, Brown, Frith, & Friston, 2013;
Fletcher & Frith, 2009; Friston, 2013). In what follows, we will see it has a crucial role
in sensory attenuation.

<hs>  Active inference</hs>
  ~~~~~~~~~~~~~~~~

So far, we have only considered the role of predictive coding in perception through
minimising surprise or prediction errors. However, there is another way to minimise
prediction errors; namely, by re-sampling sensory inputs so that they conform to
predictions; in other words, changing sensory inputs by changing the world through action.
This is known as active inference (Friston et al., 2011). In active inference, action is
regarded as the fulfilment of descending proprioceptive predictions by classical reflex
arcs. In more detail, the brain generates continuous proprioceptive predictions about the
expected location of the limbs and eyes – that are hierarchically consistent with the
inferred state of the world. In other words, we believe that we will execute a goal-
directed movement and this belief is unpacked hierarchically to provide proprioceptive and
exteroceptive predictions entailed by our generative or forward model. These predictions
are then fulfilled automatically by minimizing proprioceptive prediction errors at the
level of the spinal cord and cranial nerve nuclei: see (Adams et al., 2012) and Fig. 1.
Mechanistically, descending proprioceptive predictions provide a target or set point for
peripheral reflex arcs – that respond by minimising (proprioceptive) prediction errors.
The argument here is that the same inferential mechanisms underlie apparently diverse
functions (action, cognition and perception) but are essentially the same; for example, in
the visual cortex for vision, the insula for interoception, the motor cortex for movement
and proprioception. Crucially, because these modality-specific systems are organised
hierarchically, they are all contextualised by the same conceptual (amodal) predictions.
In other words, action and perception are facets of the same underlying imperative; namely
to minimize hierarchical prediction errors through selective sampling of sensory inputs.
However, there is a potential problem here:

<hs>  Action and sensory attenuation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If proprioceptive prediction errors can be resolved by classical reflexes or changing
(proprioceptive) expectations, how does the brain adjudicate between these two options?
The answer may lie in the precision afforded to proprioceptive prediction errors and the
consequences of movement sensed in other modalities. In order to engage classical
reflexes, it is necessary to increase their gain through augmenting the precision of
(efferent) proprioceptive prediction errors that drive neuromuscular junctions. However,
to preclude (a veridical) inference that the movement has not yet occurred, it is
necessary to attenuate the precision of (afferent) prediction errors that would otherwise
update expectations or beliefs about the motor plant (Friston et al., 2011). Put simply,
my prior belief that I am moving can be subverted by sensory evidence to the contrary;
thereby precluding movement. In short, it is necessary to attenuate all the sensory
consequences of moving – leading to an active inference formulation of sensory attenuation
– the psychological phenomena that the magnitudes of self-made sensations are perceived as
less intense (Chapman, Bushnell, Duncan, & Lund, 1987; Cullen, 2004). In Fig. 1, we have
omitted the (afferent) proprioceptive prediction error from the hypoglossal nucleus: see
(Shipp et al., 2013) for discussion of this omission and the agranular nature of motor
cortex. This renders descending proprioceptive predictions motor commands, where the
accompanying exteroceptive predictions become corollary discharge. The ensuing motor
control is effectively open loop. However, the hierarchical generation of proprioceptive
predictions is contextualised by sensory input in other modalities – that register the
sensory consequences of movement. It is these sensory consequences that are transiently
attenuated during movement. In summary, to act, one needs to temporarily suspend attention
to the consequences of action, in order to articulate descending predictions (Brown,
Adams, Parees, Edwards, & Friston, 2013). Later, we will see that sensory attenuation
plays a key role in communication.

<hs>  Birdsong and attractors</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

This section introduces the simulations of birdsong that we will use to illustrate active
inference and communication in subsequent sections. We are not interested in modelling
birdsong per se – or the specifics of birdsong communication. Birdsong is used here as a
minimal (metaphorical) example of biologically plausible communication with relatively
rich dynamics: noting that there is an enormous literature on the neurobiology and physics
of birdsong (Mindlin & Laje, 2005), some of which is particularly pertinent to active
inference; e.g., (Hanuschkin, Ganguli, & Hahnloser, 2013). We have used birdsong in
previous work to illustrate perceptual categorisation and other phenomena. Here, we focus
on omission-related responses to illustrate the basic nature of predictive coding of
hierarchically structured sensory dynamics. The basic idea here is that the environment
unfolds as an ordered sequence of states, whose equations of motion induce attractor
manifolds that contain sensory trajectories. If we consider the brain has a generative
model of these trajectories, then we would expect to see attractors in neuronal dynamics
that are trying to predict sensory input. This form of generative model has a number of
plausible characteristics: Models based upon attractors can generate and therefore encode
structured sequences of events, as states flow over different parts of the manifold. These
sequences can be simple, such as the quasi-periodic attractors of central pattern
generators or can exhibit complicated sequences of the sort associated with itinerant
dynamics (Breakspear & Stam, 2005; Rabinovich, Huerta, & Laurent, 2008). Furthermore,
hierarchically deployed attractors enable the brain to predict or represent different
categories of sequences. This is because any low-level attractor embodies a family of
trajectories. A natural example here would be language (Jackendoff, 2002). This means it
is possible to generate and represent sequences of sequences and, by induction sequences
of sequences of sequences etc. (Kiebel, von Kriegstein, Daunizeau, & Friston, 2009). In
the example below, we will try to show how attractor dynamics furnish generative models of
sensory input, which behave much like real brains, when measured electrophysiologically:
see (Friston & Kiebel, 2009) for implementational details.

<hs>  A synthetic songbird</hs>
  ~~~~~~~~~~~~~~~~~~~~

The example used here deals with the generation and recognition of birdsongs. We imagine
that birdsongs are produced by two time-varying control parameters that control the
frequency and amplitude of vibrations of the syrinx of a songbird (see Fig. 2). There has
been an extensive modelling effort using attractor models at the biomechanical level to
understand the generation of birdsong (Mindlin & Laje, 2005). Here we use attractors at a
higher level to provide time-varying control over the resulting sonograms. We drive the
syrinx with two states of a Lorenz attractor, one controlling the frequency (between two
to five kHz) and the other controlling the amplitude or volume. The parameters of the
Lorenz attractor were chosen to generate a short sequence of chirps every second or so. To
give the generative model a hierarchical structure, we placed a second Lorenz attractor,
whose dynamics were an order of magnitude slower, over the first (seconds as opposed to
100 ms or so); such that the states of the slower attractor change the manifold of the
fast attractor. This manifold could range from a fixed-point attractor, where the states
collapse to zero; through to quasi-periodic and chaotic behaviour. Because higher states
evolve more slowly, they switch the lower attractor on and off, generating songs, where
each song comprises a series of distinct chirps (see Fig. 2).

<hs>  Omission and violation of predictions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To illustrate the predictive nature of predictive coding, song recognition was simulated
by integrating the predictive coding scheme above (equations in Fig. 1). These simulations
used a standard integration scheme (spm_ADEM.m) described in detail in the appendix. The
simulations reported in this paper can be reproduced by downloading SPM
(http://www.fil.ion.ucl.ac.uk/spm/) and typing DEM to access the graphical user interface
for the DEM Toolbox (Birdsong duet). A sonogram was produced using the above composition
of Lorentz attractors (Fig. 2) and played to a synthetic bird – who tried to infer the
underlying hidden states of the first and second level attractors. These attractors are
associated with the higher local centre and area X in Fig. 1. Crucially, we presented two
songs to the bird, with and without the final chirps. The corresponding sonograms and
percepts (predictions) are shown with their prediction errors in Fig. 3. The left panels
show the stimulus and percept, while the right panels show the stimulus and responses to
omission of the last chirps. These results illustrate two important phenomena. First,
there is a vigorous expression of prediction error after the song terminates abruptly.
This reflects the dynamical nature of the recognition process because, at this point,
there is no sensory input to predict. In other words, the prediction error is generated
entirely by the predictions afforded by the dynamic model of sensory input. It can be seen
that this prediction error (with a percept but no stimulus) is larger than the prediction
error associated with the third and fourth stimuli that are not perceived (stimulus but no
percept). Second, there is a transient percept when the omitted chirp should have
occurred. Its frequency is too low but its timing is preserved in relation to the expected
stimulus train. This is an interesting stimulation from the point of view of ERP studies
of omission-related responses; particularly given that non-invasive electromagnetic
signals arise largely from superficial pyramidal cells – which are the cells thought to
encode prediction error (Bastos et al., 2012). Empirical studies of this characteristic
response to violations provide clear evidence for the predictive capacity of the brain
(Bendixen, SanMiguel, & Schröger, 2012).

<hs>  Creating your own sensations – a synthetic soliloquy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We now consider the production of birdsong using the same model used for perception above.
In the preceding simulations, descending predictions of exteroceptive (auditory)
sensations were used to construct prediction errors that enabled perceptual inference and
recognition of deep (hierarchical) structure in the sensory stream. However, in Fig. 1,
there are also descending proprioceptive predictions to the hypoglossal region that elicit
action through classical reflex arcs. This means the synthetic bird could, in principle,
sing to itself – predicting both the exteroceptive and proprioceptive consequences of its
action. This was precluded in the above simulations by setting the precision or gain of
efferent proprioceptive prediction errors (that drive motor reflexes) to a very low value
(a log precision of minus eight), in contrast to auditory prediction errors (with a log
precision of two). This means that the precision weighted prediction errors do not elicit
any action or birdsong, enabling the bird to listen to its companion. So what would happen
if we increased the precision of proprioceptive prediction errors? One might anticipate
that descending (multimodal) predictions from the higher vocal centre would cause the bird
to sing – and predict the consequences of its own action – thereby eliciting a soliloquy.
In fact, when the proprioceptive precision is increased (to a log precision of eight)
something rather peculiar happens: Fig. 4 shows that a rather bizarre sonogram is
produced, with low amplitude, high-frequency components and a loss of the song’s
characteristic structure. The explanation for this failure lies in the sensorimotor delays
inherent in realising proprioceptive predictions. In other words, descending auditory
predictions fail to account for the slight delay in self-made sensations. This results in
perpetual (and precise) exteroceptive prediction errors that confound perceptual synthesis
and associated action (singing). This resonates with the well-known disruptive effect of
delayed auditory feedback on speech (Yates, 1963). Put simply, action and perception chase
each other’s tails, never resolving the discrepancy between the actual and predicted
consequences of action. Although it would be possible to include sensorimotor delays in
the generative model – see (Perrinet & Friston, 2014) for an example oculomotor control –
a simpler solution rests on sensory attenuation:

<hs>  Sensory attenuation and action</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If auditory predictions are imprecise, by virtue of sensorimotor delays, then their
precision should be attenuated. This is an example of sensory attenuation or attenuation
of sensory precision (Brown et al., 2013). If we attenuate the auditory precision by a
factor of exp(2) – by reducing the log precision from 2 to 0 – the bird is now able to
produce a well-formed soliloquy that would be recognised by another bird: see Fig. 5. The
attenuation of sensory precision corresponds effectively to attending away from the
consequences of action. A nice example of this is our inability to perceive (attend to)
optical flow produced by saccadic eye movements: when visual motion or flow is produced
exogenously – say by gently palpating the eyeball – they can be perceived but not when
produced by oculomotor action. This simple but remarkable fact was first noted by Bell in
1823 and subsequently Helmholtz in 1866 (Wade, 1978). Put simply, we cannot speak and
listen at the same time (Numminen, Salmelin, & Hari, 1999). From the perspective of the
oculomotor system, this suggests that saccadic eye movements are imperceptible palpations
of the world that are only attended to once complete; c.f., active vision (Wurtz,
McAlonan, Cavanaugh, & Berman, 2011). Heuristically, this suggests that active inference
presents in one of two modes; either attending to sensations or acting during periods of
sensory attenuation. It also suggests that behaviour such as speech (that rests upon
preordained sequences) may only be articulated with open loop control – a loop that is
opened by sensory attenuation.

<hs>  Summary</hs>
  ~~~~~~~

These (and many other) simulations suggest that action and perception depend upon a
delicate balance between the precision of proprioceptive and exteroceptive prediction
errors that orchestrate the perceptual synthesis of sensations (caused by others) or
realising sensory predictions (caused by self). It further suggests that certain
behaviours (such as communication) are mediated by (transient) open loop control, which
depends on sensory attenuation. This seems a plausible perspective on speech, in which
violations or failures are generally recognised post hoc (e.g., slip of the tongue
phenomena). It is interesting to speculate on the psychopathology that might attend a
failure of sensory attenuation. In the first simulation above, we illustrated the failure
to realise intended utterances when the precision of both proprioceptive and exteroceptive
prediction errors were high. This might provide an interesting metaphor for failures of
articulation; e.g., stuttering (Kalinowski, Armson, Rolandmieszkowski, Stuart, & Gracco,
1993). The converse pathology would be when both proprioceptive and exteroceptive
prediction errors had too little precision, leading to psychomotor poverty and
bradykinesia (e.g., Parkinson’s disease). See (Adams et al., 2013) for a more general
discussion of precision in the context of psychopathology. One might ask whether sensory
attenuation means that one cannot hear oneself. In quantitative terms, simulations like
those above suggest the attenuation of sensory position is only quantitative: in other
words, if the precision of prediction errors at extrasensory levels is greater than
sensory precision, then descending proprioceptive predictions can be enacted with impunity
– despite irreducible sensory prediction errors. This means that one can register and
subsequently attend to violations in the consequences of action. Furthermore, it is
possible to simulate talking to oneself by noting that higher levels of the cortical
hierarchy (e.g., area X) are receiving prediction errors from lower areas (e.g., the
higher vocal centre). In this sense, higher areas listen to lower areas, which embody
sensorimotor content that may, or may not be, articulated (depending upon whether
proprioceptive gain or precision is high or low). In the next section, we exploit the
notion of sensory attenuation and model two birds that listen and sing to each other.

<h>A DUET FOR ONE</h>
--------------

Finally, we turn to the perceptual coupling or communication by simulating two birds that
can hear themselves (and each other). Each bird listened for two seconds (with a low
proprioceptive precision and a high exteroceptive precision) and then sang for two seconds
(with high proprioceptive precision and attenuated auditory precision). Crucially, when
one bird was singing the other was listening. We started the simulations with random
initial conditions. This meant that if the birds cannot hear each other, the chaotic
dynamics implicit in their generative models causes their expectations to follow
independent trajectories, as shown in Fig. 6. However, if we move the birds within earshot
– so that they can hear each other – they synchronise almost immediately. See Fig. 7. This
is because the listening bird is quickly entrained by the singing bird to correctly infer
the hidden (dynamical) states generating sensations. At the end of the first period of
listening, the posterior expectations of both parents display identical synchrony, which
enables the listening bird to take up the song, following on from where the other bird
left off. This process has many of the hallmarks of interactive alignment in the context
of joint action and dialogue (Garrod & Pickering, 2009). Note that the successive epochs
of song are not identical. In other words, the birds are not simply repeating what they
have heard – they are pursuing a narrative embodied by the dynamical attractors (central
pattern generators) in their generative models that have been synchronised through sensory
exchange. As noted above, this means that both birds can sing from the same hymn sheet,
preserving sequential and hierarchical structure in their shared narrative. It is this
phenomenon – due simply to generalised (in this case identical) synchronisation of inner
states – we associate with communication. The reason that synchronisation is identical is
that both birds share the same prior expectations. In a companion paper we will illustrate
how they learn each other’s attractors to promote identical synchronisation.

<hs>  Summary</hs>
  ~~~~~~~

In summary, these illustrations show that generalised synchrony is an emergent property of
coupling active inference systems that are trying to predict each other. In this context,
it is interesting to consider what is being predicted. The sensations in Fig. 7 are
continuous and (for both birds) are simply the consequences of some (hierarchically
composed and dynamic) hidden states. But what do these states represent? One might argue
that they correspond to a construct that drives the behaviour of one or other bird to
produce the sensory consequences that are sampled. But which bird? The sensory
consequences are generated, in this setting, by both birds. It therefore seems plausible
to assign these hidden states to both birds and treat the agency as a contextual factor
(that depends on sensory attenuation). In other words, from the point of view of one bird,
the hidden states are amodal, generating proprioceptive and exteroceptive consequences
that are inferred in exactly the same way over time; irrespective of whether sensory
consequences are generated by itself or another. The agency or source of sensory
consequences is determined not by the hidden states per se – but by fluctuations in
sensory attenuation (and proprioceptive precision). In this sense, the expectations are
without agency. This agent-less aspect may be a quintessential aspect of shared
perspectives and communication.

<h>CONCLUSION</h>
----------

The arguments in this paper here offer a somewhat unusual solution to the theory of mind
problem. This solution replaces the problem of inferring another’s mental state with
inferring what state of mind one would be into produce the same sensory consequences:
c.f., ideomotor theory (Pfister, Melcher, Kiesel, Dechent, & Gruber, 2014). Conceptually,
this is closely related to Bayesian accounts of the mirror neuron system – in which
generative models are used to both produce action and infer the intentions of actions
observed in others (Kilner et al., 2007). The basic idea is that internal or generative
models used to infer one’s own behaviour can be deployed to infer the beliefs (e.g.,
intentions) of another – provided both parties have sufficiently similar generative
models. The example of communication considered above goes slightly further than this –
and suggests that prior beliefs about the causes of behaviour (and its consequences) are
not necessarily tied to any particular agent: rather, they are used to recognise canonical
behaviours that are intermittently generated by oneself and another. In other words, the
only reason that the simulations worked was because both birds were equipped with the same
generative model. This perspective renders representations of intentional set and
narratives almost Jungian in nature – presupposing a collective narrative that is shared
among communicating agents (including oneself). For example, when in conversation or
singing a duet, our beliefs about the (proprioceptive and auditory) sensations we
experience are based upon expectations about the song. These beliefs transcend agency in
the sense that the song (e.g., hymn) does not belong to you or me – agency just
contextualises its expression. In this paper, we have focused on establishing the basic
phenomenology of generalised synchrony in the setting of active inference. Interpreting
this inference in terms of theory of mind presupposes that agents share a similar
generative model of communicative behaviour. In a companion paper (Friston & Frith, 2015),
we demonstrate how communication facilitates long-term changes in generative models that
are trying to predict each other. In other words, communication induces perceptual
learning, ensuring that both agents come to share the same model. This is almost a self
evident consequence of learning or acquiring a model: if the objective of learning is to
minimise surprise or maximise the predictability of sensations, then this is assured if
both agents converge on the same model to predict each other. Clearly, we are not saying
that theory of mind involves some oceanic state in which ego boundaries are dissolved.
This is because using generative models to predict one’s own behaviour and the behaviour
of others requires a careful orchestration of sensory precision and proprioceptive gain
that contextualises the inference. This means, the generative model must comprise beliefs
about the deployment of precision; including when to listen and when to talk; c.f., turn
taking (Wilson & Wilson, 2005). We have not dealt with this aspect of communication here.
However, it is clearly an important issue that probably rests on prosocial learning. It is
interesting to note that a failure of sensory attenuation – in particular the relative
strength of sensory and prior (extrasensory) precision – has been proposed as the basis of
autism – whose cardinal features include an impoverished theory of mind (Happe & Frith,
2006; Lawson, Rees, & Friston, 2014; Pellicano & Burr, 2012; Van de Cruys et al., 2014).
Furthermore, we have only considered a very elemental form of communication (and implicit
theory of mind). We have not considered the reflective processing that may accompany its
deliberative (conscious) aspects. This is an intriguing and challenging area (particularly
from the point of view of modelling) that calls on things like deceit: e.g., (Talwar &
Lee, 2008). Finally, we have not addressed non-verbal communication in motor and autonomic
domains. A particularly interesting issue here is interoceptive inference (Seth, 2013),
and how visual cues about the emotional states of others can be interpreted in relation to
generative models of our own interoceptive cues: see (Kanaya, Matsushima, & Yokosawa,
2012). So far, in our discussion of communication, we have emphasised the importance of
turn taking – and how this can lead to alignment of posterior expectations and identical
synchronisation of inner states. However, one of the most important functions of
communication is to enable one person to change another. For example, we can change
another’s behaviour by giving them instructions in an experiment, or we can change their
minds by helping them to understand a new concept (like free energy). For this aspect of
communication there is an obvious asymmetry in the interaction, since the aim is to
transfer information from one mind to another. Nevertheless, the basic features of the
process remain as described above – and the asymmetric exchange will call upon generalised
synchronisation. In this context, the naive speaker may assign greater salience or
precision to predictions errors to update his (imprecise) priors about the nature of the
new concept, while the knowledgeable agent will try to change the state of his listener.
For the knowledgeable speaker, prediction errors indicate that his listener has still not
understood (e.g., what must he be thinking to say that). For the ignorant speaker,
prediction errors indicate that his concept is still not quite right: see Fig. 9 and
(Frith & Wentzer, 2013) for discussion of the implicit hermeneutics. But the end result of
the interaction will be a generalised synchronisation between the speakers. The emergence
of such synchronisation indicates that the concept has been successfully communicated –
and both parties can accurately predict what the other will say. As a result Chris’s
concept (of free energy) will have changed a lot, but Karl’s will have changed a little as
a result of communicating with Chris. From a mathematical perspective, we have promoted
generalised synchrony (or synchronisation of chaos) as a mathematical image of
communication. Furthermore, we have suggested that this synchronisation is an inevitable
and emergent property of coupling two systems that are trying to predict each other. This
assertion rests on the back story to active inference; namely, the free energy principle
(Friston et al., 2006). Variational free energy provides an upper bound on surprise (i.e.,
free energy is always greater than surprise). This means that minimising free energy
through active inference implicitly minimises surprise (or prediction errors), which is
the same as maximising Bayesian model evidence. It is fairly easy to show that any
measure-preserving dynamical system – including ourselves – that possesses a Markov
blanket (here sensations and action) will appear to minimise surprise (Friston, 2013). The
long-term average of surprise is called entropy, which means minimising surprise minimises
(information theoretic) entropy. This is important because it means action (and
perception) will appear to minimise the entropy of sensory samples, which are caused by
external states. In turn, this means internal states will inevitably exhibit a generalised
synchronisation with a system’s internal states. All that we have done in this paper is to
associate the external states with the internal states of another agent. So why is
generalised synchrony inevitable? This follows from the measure-preserving nature of
coupled dynamical systems, which implies that internal states, external states – and the
Markov blanket that separates them – possesses something called a random dynamical
attractor. This attracting set of states plays the role of a synchronisation manifold that
gives rise to generalise synchrony. The synchronisation manifold is just a set of states
to which states are attracted to and thereafter occupy. All other points in the joint
state space of internal and external states are unstable and will eventually end up on the
synchronisation manifold. The simplest example of a synchronisation manifold would be the
X equals Y line on a graph plotting an external state against an internal state (see Fig.
8). This corresponds to identical synchronisation. In other words, external and internal
states track each other or – in the current context – both agents become identically
synchronised. Crucially, the attractor (which contains the synchronisation manifold) has a
low measure or volume. This is usually characterised in terms of the (fractional)
dimensionality of the attractor. For example, in Fig. 8 the synchronisation manifold
collapses to one dimension with the emergence of generalised synchrony. A measure of the
attractor’s volume is provided by its measure theoretic entropy (Sinai, 1959). Although
formally distinct from information theoretic entropy, both reflect the volume of the
attracting set of dynamical states occupied by the systems in question. This means that
minimising free energy (information theoretic entropy) reduces the volume (measure
theoretic entropy) of the random dynamical attractor (synchronisation manifold); thereby
inducing generalise synchrony. In conclusion, if the universe comprised me and you – and
we were measure-preserving – then your states and my states have to be restricted to an
attracting set of states that is small relative to all possible states we could be in.
This attracting set enforces a generalised synchrony in the sense that the state you are
in imposes constraints on states I occupy. It is in this sense that generalised synchrony
is a fundamental aspect of coupled dynamical systems that are measure (volume) preserving.
Furthermore, if we are both trying to minimise the measure (volume) of our attracting set
(by reducing surprise or entropy), then that synchronisation will be more manifest. The
notion of generalised synchrony may lend a formal backdrop to observations of
synchronisation of brain activity between agents during shared perspective taking (Moll &
Meltzoff, 2011). For example, functional magnetic resonance imaging, suggests that
internal action simulation synchronizes action–observation networks across individuals
(Nummenmaa et al., 2014). The arguments above suggest that synchronisation is not only
fundamental for a shared experience of the world – it is a fundamental property of the
world that we constitute.

<h>CONFLICT OF INTEREST STATEMENT</h>
------------------------------

The authors declare no conflicts of interest.


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<ART>A carbon price by another name may seem sweeter: Consumers prefer upstream offsets to downstream taxes
================================================================================

Authors: David J. Hardisty, Alec T. Beall, Ruben Lubowski, Annie Petsonk, Rainer Romero-Canyas
DOI: 10.1016/j.jenvp.2019.101342
Year: 2019
ASJC codes: 3202, 3207

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Several years ago, a friend was visiting some monks. As they were eating together, he
asked “If you don't believe in killing animals, why do you eat meat?” The answer: “Oh, we
don't kill animals, the butcher does that. But everybody hates that guy.” Such deflection
of responsibility in circumstances where an individual or group benefits from an object or
good, in this case meat, that is obtained through an action the individual or group
prefers to avoid, in this case, killing of a animal, is not unusual. Many people today
have similar attitudes towards products and services that they consume, which are produced
through actions that harm the environment. For example, consumers demand energy derived
from fossil fuels and other goods and services entailing emissions of carbon dioxide, even
as they blame energy companies for their emissions, which contribute to climate change.
Yet, in practice, consumers may have fewer choices and their impacts are individually
small and dispersed. If a policy solution is to be implemented to reduce these emissions,
where would it be more acceptable? At the source (the butcher shop) that is blamed for the
problem, or at the point of consumption (the kitchen) where concerned individuals may be
nudged to act on their values? To combat carbon emissions,1 where should a mandatory
emissions tax, permit system, or offsetting requirement be applied? “Upstream” on fossil
fuel production, or “downstream” on consumers? And how do consumers react to these
different policies? This issue – how consumers respond to different carbon pricing policy
descriptions – is directly relevant in the context of policies being developed to reverse
climate change or mitigate its effects (Ivanovich, Ocko, Piris-Cabezas, & Petsonk, 2019;
Lee, 2018). For example, the International Civil Aviation Organization (International
Civil Aviation Organization, 2016) has developed the Carbon Offsetting and Reduction
Scheme for International Aviation (CORSIA), which caps the net carbon dioxide emissions of
flights between participating countries at the average of 2019–2020 levels, and allows
airlines to compensate or “offset” their direct emissions above those levels by paying for
emissions reductions achieved from activities outside of the aviation sector. CORSIA is
voluntary for countries over its first phases (2021–2026). Many countries are still
deciding whether or not to opt-in for these phases and thus impose carbon offsetting
requirements on arriving and departing flights. Airlines and their regulators will also
have to determine how best to communicate (explicitly or otherwise) the associated carbon
costs to their customers. Many countries and airlines are currently looking to make carbon
regulation more attractive to consumers, to garner political support for the regulation
and to maintain consumer demand in competitive markets. In this paper, we explore the
psychological impact of different carbon emissions control approaches on consumers,
depending on whether that extra cost or “price” to consumers is communicated as applied
“upstream” on fossil fuel producers and importers, or “downstream” on consumers, as well
as whether the extra cost or price is communicated to be a “tax” or an “offset”. In the
following two sections, we review the academic literatures on these two dimensions.

<hs>  Upstream vs downstream carbon pricing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In theory, a carbon price may be imposed at different points in the production and usage
of fossil fuels and have equivalent impact on carbon emissions; regulation can be applied
“upstream” on the extraction and importation of fossil fuels, or more “downstream” on the
usage of goods and services such as electricity and air transport (Matthews, 2010).
According to conventional economic theory, in the absence of market power, transactions
costs, or other distortions, regulation of environmental pollutants is most cost-effective
when applied at the point (upstream or downstream) that ensures the greatest flexibility
for reducing emissions (see Mansur, 2011). In the case of fossil fuels, which are the
largest contributor to global greenhouse gas emissions, the carbon dioxide emissions at
the point of combustion are proportional to the carbon content of the fuels, assuming
there is no way to scrub out or remove the emissions before they are combusted (or to
capture and store them after combustion). As a result, upstream or downstream regulations
provide the same chances of reducing emissions, making the two approaches theoretically
equivalent from a conventional economics point of view. Entities regulated upstream will
tend to raise their prices and thus pass the carbon price through to consumers,
transmitting the carbon price downstream. Similarly, if consumers facing a downstream
carbon price respond by reducing their demand, producers will then see the same reduction
in profits as if they had faced the carbon price upstream. Given this theoretical
equivalence of points of regulation, an upstream point of monitoring and regulation for
fossil fuels (for example, requiring permits for the mining and importation of fossil fuel
based on its carbon content) has a number of practical advantages relative to more
downstream monitoring and regulation (such as a tax levied at the point of sale to
consumers). In particular, economists have argued for the value of upstream regulation
based on its administrative simplicity (requiring fewer sources to be monitored) and
ability to ensure a broader economic coverage of all sources consuming fossil fuels in the
economy, improving cost-effectiveness and reducing potential for emissions leakage (e.g.,
Stavins, 2007).2 Despite this practical rationale for an upstream approach, policy makers
in most existing and proposed emissions trading systems to date have chosen to regulate
fossil fuel emissions at more downstream points, despite significantly higher
administrative costs and a reduction of coverage for sources below certain thresholds and
sectors such as transportation. These choices may have a behavioral justification
(Matthews, 2010). One argument is that downstream regulation increases the salience of the
price and has different consequences in terms of managerial attention (Hanemann, 2009).
These will induce greater innovation and behavioral change to reduce emissions, reducing
the costs of the policy, even as the overall cap or price is still maintained under either
type of regulation. These behavioral arguments for downstream regulation are largely
“anecdotal” in the context of carbon pricing policies (Aldy & Pizer, 2009), and systematic
empirical research on this specific issue of upstream vs downstream carbon prices is
lacking. We aim to address this in the current research. What might be predicted from
previous research about the psychological effects of upstream vs downstream pricing on
consumers? The implications are mixed. On one hand, studies in the tax arena have shown
that consumers are in fact more responsive to taxes that are embedded in a product's
price, versus placed on a bill as an-add on to the sticker price (Chetty, Looney, & Kroft,
2009). “Downstream” prices may seem more personally relevant, and therefore more
influential on behavior. On the other hand, motivated reasoning (Kunda, 1990) and self-
serving bias (Campbell & Sedikides, 1999) predict that consumers will tend to hold others
responsible for problems when possible, and that this is especially likely under self-
threat (Campbell & Sedikides, 1999). Climate change is a moral issue for many people, and
as such, it is likely that when this moral dimension is made salient, people will seek to
hold someone accountable. Furthermore, consumers’ self-concept may be threatened if they
are engaging in a carbon polluting activity, and therefore motivate them to blame upstream
parties for the emissions. Likewise, to the extent that consumers believe they have low
self-efficacy to lower carbon emissions, they may make an external attribution of control
(Ajzen, 2002) and hold others responsible for the emissions. If consumers do hold others
responsible for carbon emissions, they may be more likely to support more “upstream”
carbon regulations, as these are perceived to hold the responsible parties accountable for
their actions. In summary, while standard economic theory suggests that consumers would
respond equivalently to “upstream” and “downstream” prices, the psychological literature
suggests that consumers may respond more strongly to one or the other, and this topic
demands empirical study.

<hs>  Product attribute framing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Turning to the formulation of a carbon price as a “tax” or an “offset”: does it make a
difference? Product attribute framing can have a substantial impact on consumers (Levin,
Schneider, & Gaeth, 1998). In a classic study, consumers were willing to pay more for a
burger labeled as 75% meat than one labeled 25% fat, even after tasting it (Levin & Gaeth,
1988). Similarly, costs labeled as “taxes” are more odious to people than other equivalent
financial costs (Ericson & Kessler, 2016; Kessler & Norton, 2016), and this may be
particularly true for political conservatives (Hardisty, Johnson, & Weber, 2010; Sussman &
Olivola, 2011). However, these tax aversion studies have only been conducted with U.S.
participants, and could well be smaller in other countries and cultures around the world
where taxes are less stigmatized, such as in Northern Europe. Why does this carbon “tax”
aversion happen? According to Query Theory (Johnson, Haubl, & Keinan, 2007), when people
consider a novel choice and “construct” their preference, their first thought has undue
influence because it biases subsequent information processing in a confirmatory manner. In
the U.S., “tax” is a “dirty word” for consumers (especially for Republicans) that triggers
an immediate negative evaluation, in turn leading the overall evaluation of the carbon tax
to be negative (Hardisty et al., 2010). In contrast, other terms (such as a carbon
“offset”) do not trigger the same immediate negative reaction and cascade of negative
thoughts. Another psychological factor driving tax aversion could be goal framing
(Lindenberg & Steg, 2007; Steg, Lindenberg, & Keizer, 2016); it may be that taxes trigger
a personal “gain” frame (in the goal framing context, a “gain” frame means “to guard and
improve one's resources”, and thus also applies to personal losses, Lindenberg & Steg,
2007), which focuses consumers on the financial cost they will pay (rather than the
environmental benefit). If this is true, tax framing may influence choices (increasing the
decision weight of personal costs) similarly across countries. Likewise, “downstream”
frames may induce a “gain” goal frame or “hedonic” goal frame (more focused on personal
resources and pain avoidance), whereas “upstream” frames (more distant from the self) may
induce a “normative” goal frame, more focused on morally correct behavior. As such,
upstream carbon pricing policies may induce more pro-environmental behavior than
downstream policies. A third factor driving acceptance of carbon pricing could be the
extent that it focuses consumers on the impact of the policy on climate change. Previous
work has found that a climate change frame (vs a financial cost frame or an energy usage
frame) increases environmental behavior intentions (Spence, Leygue, Bedwell, & O'Malley,
2014). Carbon “tax” frames may focus consumers on the cost, and therefore be less
effective than carbon “offset” frames that draw attention to the environmental impact of
the policy. In short, to the extent these policy descriptions are visible to them, U.S.
consumers ought to support paying for an “upstream” carbon offset system more than an
equivalent “downstream” tax.

<hs>  The present research</hs>
  ~~~~~~~~~~~~~~~~~~~~

We test U.S. consumer perceptions of upstream versus downstream carbon regulation
approaches in the aviation industry, along with two different policies: tax and offset. In
combination, the two point of regulation frames and two policy frames result in four
unique carbon price frames. We compare these four frames with two control conditions: a
“no-fee” control in which there is no carbon price, and a “no-information” control in
which the amount of the carbon cost is embedded into the price but where this is not
broken out or explained to consumers in any way. In Study 1, we compared these six
conditions in an exploratory fashion to determine which combinations were most and least
desirable to consumers. In supplemental Study S1 (reported in the Online Supplement), we
tested a replication of Study 1 with minor variations in the study procedure. In Study 2,
we sought to further replicate the key results, and to uncover the psychological processes
driving consumer psychology in this area: specifically, we measured perceptions of
environmental impact and accountability. We examined whether consumers believe that
certain frames would have a bigger impact on climate change and would ensure that those
responsible for carbon emissions would pay to reduce them, in turn predicting flight
choices and support for policy.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 588 residents of the United States (60% men; M age = 34.82 years [SD =
11.29]) who were recruited through Amazon. com's Mechanical Turk (MTurk) website. While
MTurk represents a broad, diverse sample of U.S. participants, it is generally younger,
more educated, and lower income than the general U.S. population (Paolacci, Chandler, &
Ipeirotis, 2010). A sample size target of roughly 600 was set in advance, aiming for 100
participants per experimental cell, to ensure adequate power for all pairwise comparisons.
Sample sizes in each experimental cell were as follows: no fee control = 94, no info
control = 96, upstream offset = 105, upstream tax = 88, downstream offset = 102,
downstream tax = 103.

<hs>  Experimental manipulation: proposed carbon regulatory policies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

All studies were reviewed and approved by a University ethics board. Participants were
randomly assigned to one of six conditions: “upstream offset”, “upstream tax”, “downstream
offset”, “downstream tax”, “no-information control”, or “no-fee control”. Participants in
the four experimental conditions first read a brief description of the policy (between 35
and 38 words), detailed in Appendix A. Other than varying the stream (“upstream” or
“downstream”) and frame (“tax” or “offset”) of the proposed carbon fee, the content of the
regulatory policy in each of the four carbon-fee labelling conditions was identical.
Participants in the control conditions did not read about any policy.

<hs>  Measure of pro-environmental flight preference</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Next, participants were asked to imagine that they were planning a vacation, and were
presented with five pairs of similarly priced flights to small island vacation
destinations. Flight B always included an additional $14.00 carbon fee which varied in
label depending on condition, as seen in Appendix B. For example, “Flight A to the island
of Nevis for $322.99” or “Flight B to the island of Bequia for $310.99 plus an additional
$14.00 carbon offset [tax] on aviation fuel production and importation [on airplane travel
and cargo]”. The five flight pairs differed only slightly in price difference (in each
case, the price of Flight B differed from that of Flight A by no more than +/− $6). In the
“no-information control” condition, the $14.00 carbon fee applied to Flight B was embedded
into the price of Flight B with no additional information provided. In the “no-fee
control” condition, the $14.00 carbon fee was not applied to Flight B. Our main dependent
variable of interest was how likely participants would be to buy Flight B instead of
Flight A on a 7-point scale (from “1- Definitely Not” to “7- Definitely”), averaged across
the five flight pair items. 3 Finally, all participants provided demographic information.

<h>STUDY 1: RESULTS</h>
----------------

Data is publicly available for download at https://tinyurl.com/y75k6hkm. To test whether
experimental condition affected pro-environmental flight preferences (i.e., preference for
flights which included a carbon fee), we conducted an ANOVA on continuous preference for
Flight B (collapsed across all flight pair choices), with condition as the independent
variable. Results revealed a significant main effect of experimental condition, F (5,582)
= 6.07, η2 = 0.05, p < .001. Fig. 1 shows that the “upstream offset” condition was most
effective at eliciting pro-environmental flight preferences. We followed up the ANOVA with
a series of pairwise comparisons; as this was an exploratory study, we corrected for
family-wise error by using Tukey's HSD. Preference for flights carrying a $14.00 carbon
fee in the “upstream offset” condition was significantly greater when compared to the “no
information” control, meanupoff-noinfo = 0.88, p < .001, CI95 [0.39,1.36], and when
compared to the “downstream tax” meanupoff-downtax = 0.55, p = .01, CI95 [0.07,1.02].
Also, the “no fee” control was preferred to the “no information” control, meanupoff-
downtax = 0.63, p < .01, CI95 [0.14,1.13]. No other pairwise comparisons were
statistically significant. We also ran an additional replication Study S1 (reported in the
Online Supplement), which found the same pattern of results: preference for the “upstream
offset” was greater than preference for the “downstream offset”, “upstream tax”, and
“downstream tax” conditions. As political affiliation of U.S. consumers has previously
found to be a significant moderator of environmental policy support (with stronger framing
effects found for Republicans than Democrats; Hardisty et al., 2010; Hart & Feldman,
2018), we also analyzed political affiliation and found that it did indeed moderate the
results, as detailed in the Online Supplement, Appendix G. Specifically, there is a
significant interaction between political party and carbon pricing condition, F (5,344) =
6.75, p < .001, ηp2 = 0.08, such that Democrats respond particularly well to the “upstream
offset” condition, and Republicans respond particularly badly to the “Downstream Tax” and
“Downstream Offset” conditions.

<h>STUDY 1: DISCUSSION</h>
-------------------

Individuals who had read a brief description of a proposed regulation for a carbon fee
described as a “carbon offset on aviation fuel production and importation” consistently
reported a greater preference to purchase flights carrying a $14.00 carbon fee (versus
similarly priced flights with no carbon fee) than, a) individuals who read other brief
descriptions describing the carbon fee as a “carbon tax on airplane travel and cargo”, and
b) individuals who did not read any description of an additional carbon fee and for whom
this $14.00 fee was embedded in the cost of the flight. In addition, individuals in the
“upstream offset” condition equally preferred flights carrying a $14.00 carbon fee as
compared to those in the “no-fee control” condition in which the $14.00 carbon fee was not
even applied. In a separate study, reported in the web supplement Appendix E, we
replicated these results with lengthier (~140 word) policy descriptions. Study 2 was
conducted to explore some potential psychological mechanisms that might underlie the
preference for an “upstream offset” policy description. Specifically, we aimed to test
whether the noted effects were mediated by participants’ perceptions of an “upstream
offset” having a greater environmental impact and/or better ensuring that those
responsible for carbon emissions pollution are actually held accountable.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 1215 residents of the United States (53% women; M age = 36.99 years [SD
= 11.88]) who were recruited through Amazon. com's Mechanical Turk website. Data was
collected in two waves (n = 406 and n = 809), one month apart, combined with two other
(unrelated) studies. A sample size of roughly 1215 was targeted, with the goal of at least
400 participants per cell, based on the modest sample sizes observed in Study 1 (e.g., d =
0.31) and the need for a larger sample size to test multiple, simultaneously estimated
mediation models. Sample sizes in each between-subjects condition were as follows:
upstream offset = 420, upstream tax = 378, downstream offset = 417.

<hs>  Experimental manipulation: proposed carbon regulatory policies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants were randomly assigned to one of three conditions: “upstream offset”,
“upstream tax”, or “downstream offset” and read a corresponding policy description,
identical to those used in Study 1. Our aim was to focus on the “upstream offset”
condition and learn why it was most preferred (in Study 1 and Study S1), by comparing it
to the two most similar labelling conditions: “downstream offset” and “upstream tax”. (To
increase statistical power, this study did not include the “downstream tax”, “no fee” or
“no information” conditions of study 1.)

<hs>  Measures of pro-environmental flight preference and policy support</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In Study 2 participants’ pro-environmental flight preference was gauged using a single
flight pair choice. How likely participants would be to buy “Flight B to the island of
Bequia for $310.99 plus an additional $14.00 carbon [offset] (or tax) on [aviation fuel
production and importation] (or on airplane travel and cargo)” instead of “Flight A to the
island of Nevis for $322.99” on a 7-point scale (from “1- Definitely Not” to “7-
Definitely”) served as our measure of pro-environmental flight choice. In addition,
participants were asked, “How much would you support the implementation of this carbon
regulatory program on a national level?” Responses on this 7-point scale (from “1-
Strongly opposed” to “7- Strongly support”) served as our measure of policy support.
Participants in the second wave of data collection (n = 809) also reported preference for
Flight B on the additional flight pair choice items that were included in Study 1. For
this subsample we were able to create a 5-flight composite collapsed across flight pair
choices and run identical analyses. The results of these are very similar, and are
reported in the online supplement, Appendix I.

<hs>  Measures of perceived environmental impact and carbon emissions accountability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Next, participants were asked two additional questions: “Would you expect this carbon
regulatory program to have a significant impact on climate change?” and “Does this carbon
regulatory program ensure that those who are responsible for carbon emission pollution are
the ones who pay to reduce it?” Responses on both of these 7-point scales (from “1-
Definitely not” to “7- Definitely” and from “1- Not at all” to “7- Very much”,
respectively) served as our potential mediators of interest. Participants in all three
conditions also provided demographic information (e.g., age, sex, income).

<h>STUDY 2: RESULTS</h>
----------------

Data is publicly available for download at https://tinyurl.com/y75k6hkm. To test whether
experimental condition affected pro-environmental flight preference (i.e., preference for
the flight which included a carbon fee), we conducted an ANOVA on continuous preference
for Flight B, with condition as the independent variable. Results revealed a significant
main effect of experimental condition, F (2,1212) = 4.25, η2 = 0.007, p = .011. Table 1
shows that the “upstream offset” condition appears to be most effective at eliciting pro-
environmental flight preferences. The “upstream offset” condition inspired greater pro-
environmental flight preference than the “upstream tax” and marginally greater pro-
environmental flight preference than the “downstream offset” conditions; t (796) = 3.00, d
= 0.21, p = .003, and t (835) = 1.90, d = 0.13, p = .058, respectively. To test whether
experimental condition affected how much participants would support the policy on a
national level, we conducted an ANOVA on policy support, with condition as the independent
variable. Results revealed a significant main effect of experimental condition, F (2,1215)
= 5.81, p = .003, ηp2 = 0.009. Table 1 shows that the “upstream offset” condition appears
to be most effective at eliciting policy support. Policy support in the “upstream offset”
condition was marginally greater when compared to the “upstream tax”, t (796) = 1.79, d =
0.13, p = .073, and significantly greater when compared to the “downstream offset”
conditions, t (835) = 3.46, d = 0.24, p = .001. To test whether experimental condition
affected how much participants believed that the carbon regulatory program would have a
significant impact on climate change, we conducted an ANOVA on perceived environmental
impact, with condition as the independent variable. Results revealed a significant main
effect of the experimental condition, F (2,1212) = 4.95, ηp2 = 0.007, p = .008. Table 1
shows that the “upstream offset” condition appears to be most effective at eliciting high
perceived environmental impact. Perceived environmental impact in the “upstream offset”
condition was significantly greater when compared to the “upstream tax”, t (796) = 2.79, d
= 0.20, p = .005, and the “downstream offset” conditions, t (835) = 2.70, d = 0.18, p =
.007. To test whether experimental condition affected how much participants believed that
the carbon regulatory program would ensure that those who are responsible for carbon
emission pollution are the ones who pay to reduce it, we conducted an ANOVA on perceived
carbon emissions accountability, with condition as the independent variable. Results
revealed a significant main effect of the experimental condition, F (2,1212) = 8.83, ηp2 =
0.014, p < .001. Table 1 shows that the “upstream offset” condition appears to be most
effective at eliciting perceptions of holding accountable those responsible for the carbon
emissions. Perceived carbon emissions accountability in the “upstream offset” condition
was not statistically different when compared to the “upstream tax” condition, t (796) =
1.27, d = 0.09, p = .21, but was significantly greater when compared to the “downstream
offset” condition, t (835) = 4.14, d = 0.288, p < .001.

<hs>  Mediation analyses</hs>
  ~~~~~~~~~~~~~~~~~~

We conducted two sets of mediation analyses to examine the processes associated with
flight preference and policy support. We now examine each of these in turn.

        <hss>Flight preference</hss>

        Both perceived impact and perceived accountability were correlated with flight
        preference, as seen in Table 2. Furthermore, in a GLM with frame (3-levels:
        upstream offset, downstream offset, and upstream tax), perceived impact, and
        perceived accountability predicting flight preference, both impact, F (1,1210) =
        119.11, p < .001, ηp2 = 0.09, and accountability, F (1,1210) = 26.77.11, p < .001,
        ηp2 = 0.02, remained as significant predictors of preference, while frame was
        reduced to marginal significance, F (2,1210) = 2.31, p = .10, ηp2 = 0.004. We also
        analyzed political affiliation and found that it did indeed moderate the results,
        as described in the Online Supplement, Appendix G. Specifically, Republicans were
        more responsive to policy description differences than Democrats, consistent with
        previous research on U.S. participants (Hardisty et al., 2010; Hart & Feldman,
        2018). Next, we conducted a simultaneous indirect effect analysis of the frame →
        impact → flight preference pathway and the frame → accountability → flight
        preference pathway. As seen in Fig. 2a, each leg of each mediation pathway is
        significant. We used a recommended bias-corrected bootstrapping procedure in R
        (Shrout & Bolger, 2002), with 5,000 bootstrap samples. To test the 3-level
        categorical framing variable, we used two dummy coded variables, and focus on the
        upstream offset condition (coded 1) versus the other two conditions (coded 0).
        This revealed significant mediation via both perceived impact, β = 0.13, CI95
        [0.03,0.24], p < .01, and perceived accountability, β = 0.09, CI95 [0.05,0.16], p
        < .001.

        <hss>Policy support</hss>

        Turning to the processes associated with policy support, it is again apparent that
        both perceived impact and perceived accountability are correlated with policy
        support, as seen in Table 2. As seen in Fig. 2b, each leg of each mediation
        pathway is significant. Again, in a model with frame (3-levels: upstream offset,
        downstream offset, and upstream tax), perceived impact, and perceived
        accountability predicting policy support, both impact, F (1,1210) = 483.98, p <
        .001, ηp2 = 0.29, and accountability, F (1,1210) = 96.13, p < .001, ηp2 = 0.07,
        remained as significant predictors of support, while frame dropped to non-
        significance, F (2,1210) = 1.26, p = .29, ηp2 = 0.002. Next, we conducted a
        simultaneous indirect effect analysis of the frame → impact → policy support
        pathway and the frame → accountability → policy support pathway, as seen in Fig.
        2b, using the same bootstrapping procedure with 5,000 bootstrap samples. This
        revealed significant mediation via both perceived impact, β = 0.19, CI95
        [0.06,0.34], p < .01, and perceived accountability, β = 0.13, CI95 [0.07,0.21], p
        < .001.

<hs>  Political affiliation</hs>
  ~~~~~~~~~~~~~~~~~~~~~

As detailed in the Online Supplement, there was a significant interaction between
political affiliation and carbon pricing condition, F (2,773) = 4.96, p < .01, ηp2 = 0.01,
such that carbon pricing condition had a slightly stronger effect on the policy support of
Republicans than Democrats. In particular, the “upstream tax” pricing condition was
supported by Democrats much more than Republicans.

<h>STUDY 2: DISCUSSION</h>
-------------------

The results of Study 2 are consistent with those of Study 1, while adding important
additional nuances which may hint at the psychological mechanisms underlying the noted
success of the “upstream offset” policy description. When a proposed carbon fee was
described as a “carbon offset on aviation fuel production and importation” (versus other
descriptions), individuals were more likely to purchase a flight carrying the carbon fee
instead of a similarly priced flight with no fee, and were more likely to support the
proposed carbon regulation policy. These individuals were also more likely to perceive the
policy as having a more significant impact on climate change, and believe that the policy
would better ensure that those responsible for carbon emissions pollution were the ones
held accountable for paying the fee. Mediation analyses revealed that participants’
increased pro-environmental flight preference and heightened policy support was driven by
perceptions that the “upstream offset” policy would have a greater impact on climate
change (versus “upstream tax” and versus “downstream offset” conditions) and, would better
ensure that those who are responsible for carbon emissions pollution are actually the ones
held accountable for covering the cost (versus the “downstream offset” condition only).

<h>GENERAL DISCUSSION AND CONCLUSIONS</h>
----------------------------------

Across three studies, U.S. consumers were consistently more likely to choose to purchase a
flight with a carbon price when the additional price was described as a “carbon offset for
aviation fuel production and import” than when it was described using other frames, such
as a “carbon tax for airplane travel”. Notably, this upstream offset frame was popular
enough among consumers that it counteracted the expected preference to avoid the $14.00
additional cost of the fee. In addition to the two studies reported above, we ran another
study (reported in the online supplement, Appendix E) which replicated the flight
preference results. The description of the point of regulation (upstream vs downstream)
does seem to have a notable impact on consumer preferences. A “downstream” carbon offset
was not nearly as popular as an “upstream” carbon offset. Why? The upstream offset is
perceived both to help the environment more and to hold accountable those responsible for
the emissions. In other words, the upstream offset condition addresses both the perceived
causes and consequences of the emissions. This is true even though the cost to consumers
for each policy was held constant in our studies, regardless of whether the price was
described as applying upstream or downstream. Our findings contribute to previous studies
on tax aversion. In addition to replicating the general finding of tax aversion in U.S.
consumers (Hardisty et al., 2010; Sussman & Olivola, 2011) and the effectiveness of
environmental frames (Parag, Capstick, & Poortinga, 2011), we introduce and measure the
psychological dimension of “upstream” vs “downstream” framing: not only are taxes
disliked, but this is particularly true for “downstream” taxes on consumers, as opposed to
“upstream” offsets for producers. We also contribute new explanations for tax aversion in
environmental policy: that taxes are not perceived to be effective for making an
environmental impact, and that taxes may not be seen as holding the right people
accountable. In future research, it would be interesting to see if “upstream” vs
“downstream” descriptions influence the order and balance of thoughts in the way predicted
by Query Theory (Johnson et al., 2007): perhaps “downstream” costs induce a negative
cognitive bias in the same way that taxes do, influencing subsequent information
processing. An additional cost or penalty applied to “me” may be more likely to trigger an
immediate negative evaluation. It would also be interesting to study how “upstream” vs
“downstream” descriptions influence goal framing (Lindenberg & Steg, 2007; Steg et al.,
2016), and whether perhaps the “upstream” and “offset” frames induce a “normative” goal of
doing the right thing, whereas the “downstream” and “tax” goes may induce a “gain” goal of
maximizing resources. The implications for policy are somewhat nuanced. Countries or
states that wish to enact a carbon price may want to use the “upstream offset” frame
(paired with a brief description), especially if competing with other countries without a
carbon fee. Our results suggest that consumers may in fact prefer airline flights with an
upstream carbon offset; this preference may be strong enough to counteract any additional
cost to the country or state that implements it (though this should be tested in future
research in field studies). The implementing country could potentially realize further
benefits if the offset investment helps finance sustainable low-carbon development in that
country. Furthermore, aviation consumers might be more accepting of “upstream offset”
regulation than “downstream tax” regulation. In fact, our findings suggest that customers
may be willing to purchase tickets that include appropriately described carbon offsets
even if the cost is higher; these descriptions may still be effective even when they are
as short as 28 words in length. These findings have policy implications for the new
market-based measure adopted for the international civil aviation sector, which has an
offsetting program as a central feature, with a relatively upstream point of obligation at
the level of airlines. Our research suggests that airlines might wish to highlight their
carbon offset purchases for their customers in order to increase customer receptivity. Our
findings also suggest that participation in CORSIA could thus bring overall economic
benefits rather than costs for participating airlines and that countries may thus benefit
from opting-in to the initial voluntary phase. If the goal of a carbon price is to limit
the aviation sectors’ climate impact, a carefully vetted upstream offset program with
strong offset quality requirements may be an effective solution. Future research could
further examine if customer preferences vary with the type of offset and how best to
communicate about offsets to customers to elicit the most favorable response. The studies
reported here have several important limitations. First, the scenarios and answers are
hypothetical, and therefore participants may have tried to give answers that “look good”,
but that do not represent their real views and behavior. For example, in Study 1, we found
that the flight including a $14 upstream offset was equally preferred (or even slightly
more preferred) as compared to a flight with no carbon fee. When spending actual money,
consumers may weight that $14 cost more heavily, and prefer the “no-fee” flight.
Therefore, these results need to be tested with real flight choices in the future. Second,
we only sampled U.S. consumers, and the results may be different in other regions and
cultures. For example, taxes may be less odious in other countries (such as Northern
European countries), and environmental regulation may be more popular. This should be
explored in future research. Third, the sample population we used, Amazon Mechanical Turk,
is not representative of the U.S. population. Specifically, MTurkers tend to be younger,
more educated, and lower income than the general U.S. population (Paolacci et al., 2010).
As such, this group may be more price sensitive, and also more pro-environmental than the
U.S. population, both of which could affect our results. Fourth, while the key findings of
the present research were replicated across three studies (the two studies in the main
manuscript plus one in the supplemental material), the effect sizes are small. As such,
while framing of carbon prices may be a helpful tool, it should not be considered a
panacea for consumer acceptance of carbon prices, and should be combined with other
measures. Up/downstream framing is a useful new dimension in environmental consumer
psychology. It can readily be applied in the airline industry, as well as in other domains
and contexts more broadly, opening new avenues for research and practice. For example,
when products that include a charitable donation (e.g. “$1 from every purchase is donated
to Green Peace”), who gets the credit for the good deed, the consumer, the firm, or both?
We suspect that “downstream” pricing may be more effective in these contexts, but this
should be tested in future research.


<h>REFERENCES</h>
----------

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<ART>A methodological investigation of the Intermodal Preferential Looking paradigm: Methods of analyses, picture selection and data rejection criteria
================================================================================

Authors: Claire Delle Luche, Samantha Durrant, Silvana Poltrock, Caroline Floccia
DOI: 10.1016/j.infbeh.2015.05.005
Year: 2015  |  Pages: 151-172
ASJC codes: 3204
Keywords: Intermodal Preferential Looking, Methodology, Time course analysis, Word recognition

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The Intermodal Preferential Looking paradigm provides a sensitive measure of a child's online word comprehension. To complement existing recommendations (Fernald, Zangl, Portillo, & Marchman, 2008), the present study evaluates the impact of experimental noise generated by two aspects of the visual stimuli on the robustness of familiar word recognition with and without mispronunciations: the presence of a central fixation point and the level of visual noise in the pictures (as measured by luminance saliency). Twenty-month-old infants were presented with a classic word recognition IPL procedure in 3 conditions: without a fixation stimulus (No Fixation - noisiest condition), with a fixation stimulus before trial onset (Fixation, intermediate), and with a fixation stimulus, a neutral background and equally salient images (Fixation Plus - least noisy). Data were systematically analyzed considering a range of data selection criteria and dependent variables (proportion of looking time towards the target, longest look, and time-course analysis). Critically, the expected pronunciation and naming interaction was only found in the Fixation Plus condition. We discuss the impact of data selection criteria and the dependent variable choice on the modulation of these effects across the different conditions.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Over the last four decades, a considerable amount of energy and creativity has been
devoted to designing and testing numerous experimental methods to investigate early speech
perception and language comprehension in young children. One of the most popular methods
is the head-turn preference paradigm (Polka & Bohn, 1996; Werker, Polka, & Pegg, 1997;
Werker & Tees, 1983, 1984) which is primarily used with infants aged from 5 to 16 months
of age to investigate listening preferences and discrimination. The study of word
recognition or word learning from the age of 12 months (Schafer & Plunkett, 1998) relies
on two paradigms, the Switch task (Stager & Werker, 1997; Werker, Fennell, Corcoran, &
Stager, 2002) and the Intermodal Preferential Looking paradigm (IPL, Bailey & Plunkett,
2002; Golinkoff, Hirsh-Pasek, Cauley, & Gordon, 1987; Swingley & Aslin, 2000), also called
looking-while-listening procedure (Fernald, Zangl, Portillo, & Marchman, 2008). In
principle the IPL procedure is more versatile than the Switch task, whereby a new label is
presented alongside a new visual item until a looking time threshold is reached, followed
by a trial where the label is maintained or replaced by another (this is the switch
trial). Indeed, whereas the Switch task is designed for novel word learning situations,
the IPL allows for the investigation of novel word learning (e.g., Gurteen, Horne, &
Erjavec, 2011; Schafer & Plunkett, 1998; Swingley & Aslin, 2002, 2007) together with
familiar word recognition (e.g., Fernald, Pinto, Swingley, Weinberg, & McRoberts, 1998;
Fernald et al., 2008; Houston-Price, Mather, & Sakkalou, 2007; Mani, Coleman, & Plunkett,
2008; Mani & Plunkett, 2007, 2008, 2011a; Ramon-Casas, Swingley, Sebastián-Gallés, &
Bosch, 2009; White & Morgan, 2008), mutual exclusivity (Houston-Price, Caloghiris, &
Raviglione, 2010) and most recently has been adapted for priming tasks (e.g., Arias-Trejo
& Plunkett, 2009, 2013; Mani, Durrant, & Floccia, 2012; Styles & Plunkett, 2009). The
standard procedure consists in presenting pairs of images horizontally on a screen for
several seconds and, mid-trial, playing a target word or a carrier sentence. A trial is
thus divided in a pre-naming and a post-naming phase (for longer post-naming windows, see
Zangl, Klarman, Thal, Fernald, & Bates, 2005). For the duration of the experiment, eye
movements are recorded by cameras mounted above each image (or eye-tracking when
available). These eye movements are then time-locked onto each trial and traditionally
manually coded frame by frame. With the growing use of eye trackers, gaze coding is now
often automatic. Fernald and colleagues (2008) provided a comprehensive review of the
procedure and improvements added progressively since the first introduction of the
paradigm, and listed factors that need to be controlled: both images have to be matched
for size and visual salience; auditory stimuli have to be controlled for duration across
items; target side has to be counterbalanced overall. One of their recommendations is that
across all participants both objects in a given trial should be used as target and as
distracter, since it is the best control to avoid any preference for one stimulus over
another. Although desirable, such a control is not always possible given the restricted
choice of stimulus items in young children and the need for a sufficient number of trials
per participant. Some experiments have controlled for this possible preference effect
(Mani & Plunkett, 2007; Swingley & Aslin, 2000, 2002), presenting the same visual stimuli
at least twice, while others have not (Durrant, Delle Luche, Cattani, & Floccia, 2014;
Floccia, Delle Luche, Durrant, Butler, & Goslin, 2012; Mani et al., 2008) but still found
comparable results. One possible compromise, as suggested by Fernald et al. (2008), is to
ensure an equal preference for both pictures during the pre-naming phase by monitoring
looking times in silence during a pilot experiment. However, to our knowledge, such a
pretest or control for the absence of a pre-naming image bias is not reliably reported in
the literature (with the exception of the results section in Swingley, Pinto, & Fernald,
1999). Another way of controlling for pre-naming visual preferences is to take into
account looking behaviour in the pre-naming phase in the statistical analyses, which is
frequently reported (e.g., Mani & Plunkett, 2007; Meints, Plunkett, & Harris, 1999).
Finally, Fernald et al. argue that, contrary to adult visual experiments, a central
fixation point right before naming is not necessary as children would not follow such an
implicit instruction (note that White & Morgan, 2008, used a centering stimulus before the
pre- and the post-naming phases, while Gurteen et al., 2011, used a centering light before
post-naming). Despite the excellent review by Fernald et al. (2008) the relatively recent
addition of the IPL paradigm to the field of developmental psycholinguistics means that
researchers often face choices regarding the procedure itself and the methods of analyses,
all of which can have important consequences on the observation of an experimental effect.
For example, as demonstrated by Arias-Trejo and Plunkett (2010), choosing a distracter
image which is perceptually close to the target image (e.g., a balloon paired with an egg)
can result in uninvited interference effects so that 18- to 24-month-olds fail to identify
the target image. The consequences of other methodological choices (such as the use of a
fixation point) on the robustness of the experimental effects are largely unknown. As we
will show below, a review of the recent literature reveals a great deal of variation in
many aspects of the procedure, as well as in the selection of the dependent variables used
for the analysis of looking times. Appendix A provides details on methodological aspects
such as the presence of a central fixation stimulus or the duration of the pre- and post-
naming phases across a range of studies that have used the IPL methodology. The aim of the
current study is to complement and extend Fernald et al.’s review by examining how the
different methodological choices and the different methods of looking time analyses impact
on the observation of significant results. In three experiments testing familiar word
recognition with 20-month-olds, we manipulated the level of visual noise (with saliency as
measured by luminance and the presence of a central fixation point), and provided a
systematic and thorough analysis of looking times using those methods most representative
of the current literature. The main objective of this paper is to provide researchers with
some data-grounded recommendations about the best practices when using the IPL procedure.

<hs>  Central fixation point</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

A review of the literature using the preferential looking paradigm shows that around half
the experiments use a centering stimulus at the beginning of each trial, visual or
auditory (Curtin, 2010; Dittmar, Abbot-Smith, Lieven, & Tomasello, 2008; Meints et al.,
1999; Meints, Plunkett, Harris, & Dimmock, 2002; Meints, Plunkett, Harris, & Dimmock,
2004; Schafer & Plunkett, 1998, see Appendix A) while the other half do not report such a
practice (Bailey & Plunkett, 2002; Ballem & Plunkett, 2005; Mani et al., 2008; Mani &
Plunkett, 2007, 2008). This stands in contrast with ERP studies, and adult experiments
generally, where a fixation stimulus is systematically presented to centre the
participant's attention before trial onset (Kuipers & Thierry, 2011). When a central
fixation point is used, trials are always triggered by the experimenter, but not
systematically when such cue is not used, in which case trials are sometimes automatically
interspaced (Ramon-Casas et al., 2009; Swingley, 2003, 2007). Although it is not possible,
from these studies, to draw direct comparisons between results obtained with and without
fixation points given the variety of investigated topics, one can estimate that centering
attention, even furtively, should benefit the procedure and the quality of the data,
especially since it ensures that the child is attentive to the screen immediately before
trial onset. The presentation of an image in the centre of the screen after termination of
a trial has multiple advantages: (i) since the trial is triggered only if the child is
looking at the centre, it ensures the child is attentive and active; (ii) attention is
attracted back to the middle of the screen, giving the same weight to the probability that
the first look will be at the target or the distracter once the trial begins; (iii)
looking at the centre right before trial onset should encourage the child to explore all
new stimuli that appeared in her peripheral vision. This is of particular importance when
considering that trials where the child does not look at both images in the pre-naming
phase can be discarded in the statistical analyses (e.g., Mani & Plunkett, 2007); and (iv)
by having something to look at for the whole duration of the experiment, the entire
procedure becomes dynamic and eventful, maintaining the child's interest. One of the aims
of this study will be to verify if looking behaviour is affected by the potential noise
reduction provided by a fixation point in a classic IPL task.

<hs>  Quality of visual stimuli</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Fernald et al. (2008) recommended controlling the visual stimuli for size, animacy and
salience (in the sense of visually engaging images, especially by matching objects for
animacy). Regarding saliency, experimenters decide on the pictures without any objective
measures. Visual stimuli are often static colour photographs of objects on a white or grey
background (e.g., Mani & Plunkett, 2007; Swingley & Aslin, 2000), sometimes a mix of
realistic drawings and photographs (Swingley, Pinto, & Fernald, 1999), or quite
exceptionally line drawings, coloured (White & Morgan, 2008; White, Morgan, & Wier, 2005)
or plain (with made up animals, Mather & Plunkett, 2011). So as to enhance interest in the
visual stimuli, pictures sometimes move in synchrony on a vertical axis (Swingley, 2003;
Swingley & Aslin, 2002, 2007). In word learning studies, made up objects (obtained by
editing colour photographs as in Schafer & Plunkett, 1998) are visually comparable to real
objects. To our knowledge, only Gurteen et al. (2011) have presented real objects to the
participating infants. Such variability in the selection of visual stimuli in the
literature has been enabled by the possibility of retrieving images and photographs from
the internet, departing from the perceptually controlled line drawings from Snodgrass and
Vanderwart (1980) or their coloured version (Rossion & Pourtois, 2004) to achieve more
naturalistic representations. One way to control for the quantity of information provided
by photographs is to remove any background, even though the percept is less naturalistic
looking. This practice is supported by Meints et al. (2004) who showed that background
affected word recognition. Younger children (15 months) do not recognize a sheep when it
is pictured with a naturalistic background (e.g., a sheep on grass), while they do when
the sheep is presented without background or on an unusual – or less rich – background.
Older children recognize the sheep regardless of background, although the distracting
effect of the typical background was still observed to a certain extent. Perhaps
estimating the basic visual salience of the stimuli would be another, quantifiable, step
towards ensuring that target images are not more attractive than their corresponding
distracters, to complement experimenter judgments. Note that this is a purely visual
control of salience, away from the subjective salience discussed by Fernald et al. (2008)
or the more cognitive saliency maps (for a review, see Althaus & Mareschal, 2012). This
will be achieved in the current study by performing cross-correlations of the pairs of
images presented (Chinga & Syverud, 2007). Images are transformed into a matrix containing
the luminance of each pixel, then into a vector. The cross-correlation compares then the
two vectorized images: a high correlation score will mean that the two images are similar
in salience. By contrasting a more or less visually noisy set of pictures, we will examine
its effect on looking behaviour.

<hs>  Methods of analysis</hs>
  ~~~~~~~~~~~~~~~~~~~

Regardless of the task the participant is engaged in, all experiments in the IPL
literature divide an experimental trial into a pre- and a post-naming phase, based usually
on the onset of the target word (with the exception of priming studies in which there is
no pre-naming phase, e.g., Arias-Trejo and Plunkett, 2009). The selection of analysable
data as well as the choice of dependent variable varies according to research groups and,
on occasion, differs for a single experiment (see Appendix A). The most typical time
window of interest starts 367 ms after word onset (and less frequently word offset):
indeed it has been established that a minimum of 233 ms is necessary to obtain stimulus-
related saccades, and that this latency depends on age, vocabulary size or task complexity
(Fernald et al., 2008; Fernald, Perfors, & Marchman, 2006; Zangl & Fernald, 2007; Zangl et
al., 2005). This time window usually ends at 2000 ms, as it is generally considered that
later looking behaviour is no longer related to the processing of the auditory stimulus.
When plots of the time course for proportions of looks to the target are included, usually
at end of the result section (Arias-Trejo & Plunkett, 2010; Fernald et al., 2008; Swingley
& Aslin, 2000), the time window can then be justified a posteriori, the visual inspection
confirming that roughly 2000 ms after word onset, looking behaviour resumes to chance
level (that is, equal looks to the target and the distracter). However, since latency is a
function of at least age (Zangl & Fernald, 2007) and vocabulary size (Fernald et al.,
2006), the whole looking behaviour can also be influenced by task difficulty. This is the
case for example when mispronunciations of words are minor (Mani et al., 2008; Mani &
Plunkett, 2011a; Swingley, 2007; Swingley & Aslin, 2002). A systematic time window,
regardless of data distribution in the post-naming phase, may overlook meaningful looks if
children are still looking at the target after 2000 ms. It seems recommendable (see
Fernald et al., 2008) that the first, and not the last, step in data analysis should be
the systematic plot of the unfolding looking behaviour, so as to ascertain that the window
of analysis comprises all the word processing and task related looks. This is common
practice in EEG or MEG experiments, since electrophysiological markers can vary in
location and time period (e.g., Bastiaansen, van der Linden, ter Keurs, Dijkstra, &
Hagoort, 2005; Hagoort & Brown, 2000). Perhaps a way to enhance the precision of the
results would be to determine statistically the exact time window when the two conditions
differ (target vs. distracter in simple naming tasks, correct vs. incorrect pronunciation
in mispronunciation experiments). To our knowledge, with the IPL paradigm, only one
instance of such an analysis has been published so far (von Holzen & Mani, 2012, see Maris
& Oostenveld, 2007 for a detailed explanation); the authors showed that in addition to
standard comparisons of looking times averaged across pre- and post-naming trials, it was
possible to identify accurately a specific time window where performance between
conditions differed (in their case, 1140–1580 ms after target word onset). There are two
advantages for this method: first, representing time course plots gives a dynamic
evaluation of visual/linguistic processing; secondly, this data driven method is objective
and prevents a priori judgement of the data. In relation to the looking behaviour, two
types of dependent variables are usually considered: proportion of target looking (taking
into account, or not, the pre-naming phase, see Appendix A), and latency of shifts to the
target. They are respectively assimilated to a correct response and a reaction time (see
Fernald et al., 2008). Other measures have also been used, and usually provide comparable
direction of results, such as total looking time (that is, the sum of looks to the target
during the post-naming phase minus those to the distracter), or the longest look (longest
single fixation to the target). Data filtering or pre-processing is where the greatest
variation across experiments is observed (see Appendix A). In word recognition tasks, with
or without a mispronunciation element, words are selected so that they are likely to be
known a priori by all participants according to standardized norms (thus reducing
considerably the number of potential stimuli, re. Ramon-Casas et al., 2009; Swingley et
al., 1999), or by at least 50% of children of the corresponding age (e.g., Styles &
Plunkett, 2008). Then, some authors further filter the data by analyzing only trials where
parents report the words as known by the child (e.g., Mani & Plunkett, 2011b). Whether it
is necessary or not to check for infants’ knowledge of distracter will be addressed here.
On the one hand, if the child does not know the distracter, she might be looking more at
the target once it has been named simply because the target object is the only object for
which she has a name, and not because she recognizes the link between the label and this
object; this would artificially inflate the target looking time. On the other hand, a
child who does not know the distracter's name would look longer at its picture in
mispronunciation trials, in the spirit of the study by White and Morgan (2008) whereby
unknown objects were presented as distracters. This may be an advantage for strengthening
mispronunciation effects. The impact of filtering out trials where the child does not know
both the target word and the distracter will be evaluated in the current study. The
criteria used to select the attended trials is also variable, with some considering only
long enough fixations to the images (1500 ms in each phase, Bailey & Plunkett, 2002), or
fixation to both images in the pre-naming phrase or at least, throughout the trial (Mani &
Plunkett, 2007). Finally, data cleaning is achieved by excluding participants not
contributing to all experimental conditions (Fernald et al., 2006; second analysis in
Styles & Plunkett, 2008), or whose data points fall outside normality (Fernald et al.,
2006; see also Mani & Plunkett, 2007). Although all these types of pre-processing or
filtering allow for cleaner datasets, comparability across experiments would benefit from
consistent practice, preferably on the measures that are the most conservative. Falling on
an agreement on exclusion criteria or on the best-suited age-specific time window would be
desirable. Indeed, some analyses only include trials where the child is looking at a
picture (final analysis in Fernald et al., 1998), while others reject children not
contributing to all conditions (e.g., Fernald et al., 2006; second analysis in Styles &
Plunkett, 2008), set a minimum looking time (e.g., Bailey & Plunkett, 2002; Ballem &
Plunkett, 2005) or only include trials were both pictures are fixated (Mani & Plunkett,
2007, 2008). The goal of the present research is to examine how the different methods of
data analyses are resistant to methodological alterations, or noise, such as image quality
and the presence of a central fixation stimulus. For this purpose, we ran three versions
of a classic IPL procedure testing the detection of mispronunciation of familiar words,
varying the pictures’ saliency and background, and the presence of a fixation point. For
each experiment, we evaluated how the degree of visual noise, together with the different
criteria for data selection, modified the different dependent variables. Here, the stimuli
were comparable to those in Mani and Plunkett (2007), in which 15-to-24-month-olds were
presented with two images on both sides of a screen and heard, mid-trial, correctly
pronounced in a carrier sentence such as “Look, dog!” for half of the trials, or as a
mispronounced version of the target word (“Look, bog!”) in the other half of trials. If
children recognize lexical entries of familiar words only if they are pronounced correctly
(as is expected from the age of 18 months, e.g., Mani & Plunkett, 2007), a naming effect
should be observed in correctly pronounced trials, but not (or significantly less) in
mispronunciation trials resulting in an interaction between naming and pronunciation – the
key result in these studies. The participants in the current study are 20 month olds, and
so results comparable to 18 month olds can be expected, if not stronger, because their
lexical repertoire increases steadily and their phonological sensitivity seems stable
around these ages (for a developmental Switch task, see Werker et al., 2002). As presented
earlier, we hypothesize that adding a fixation stimulus between trials should enhance the
quality of the data. Indeed, since experimental trials are then only triggered when the
child is attentive to the screen, post-hoc measures of attentiveness (by checking the
videos, re. Fernald et al., 2008; or excluding trials with looks <1500 ms, re. Bailey &
Plunkett, 2002) are less critical yet desirable. The added advantage of having a centred
fixation stimulus is that it should entice the participants into looking at the two images
that appear in their peripheral vision at trial onset. The second manipulated
methodological choice is the uniformity of picture background and the choice of visual
stimuli. As tested by Meints et al. (2004), a typical background is distracting and
reduces the naming effect in younger children, and to a certain extent in 18-month-olds.
To capitalize on these findings and fully appreciate the extent of any distraction
relating to a naturalistic background on the naming effect, we compared two sets of
images, one where the content was naturalistic (mostly with a background), and one where
there was no background, leaving the stimuli in isolation. In addition, we examined the
effect of image saliency on looking behaviour, especially in the pre-naming phase, which,
to our knowledge, has never been investigated experimentally in infants, despite
recommendations to control for it (Fernald et al., 2008). To sum up, we manipulated the
presence/absence of a central fixation point together with the uniformity of picture
background and picture salience, to evaluate the effect of experimental noise in an
auditory word recognition task. In the first condition (No Fixation), no central fixation
stimulus was used and no attempt was made to control for the picture background colour or
salience. This is the noisiest condition. In the second condition (Fixation, intermediate
noise condition), a central fixation point was added and the same images were used as in
the No Fixation condition. In the third condition (Fixation Plus), the central fixation
point was augmented by a systematic absence of background colour for pictures and target-
distracter pairs were selected so that their salience was highly correlated. This is the
least noisy condition. We expect that adding the fixation stimulus should encourage more
looks to both images in the pre-naming phase, leading to cleaner data in terms of trial
rejection, and more balanced looks towards target and distracter (as seen for example by
shorter “longest look” measures). The adjunction of better controlled image background and
saliency should also contribute to enhance the identification of objects, reducing the
“back and forth” between target and distracter, especially during the post-naming phase.
This would translate into longer “longest look” measures but also in a larger naming
effect in correct trials. To fully estimate the impact of experimental stimuli
manipulations on data quality, and therefore get a clear picture of the robustness of the
method, we will provide different types of analyses. First, we will evaluate results for
the classic 367–2000 ms post-naming time window and will examine effects of conditions on
the different dependent variables used in the literature. We will also look at the impact
of the different criteria used for trial rejection on the results. Then we will present a
newer type of analysis that takes the time course of looking behaviour into consideration
and thus avoids averaging over the whole post-naming window (von Holzen & Mani, 2012).
While time course is seemingly the crucial aspect of the IPL paradigm or other visual
paradigms, it has been rarely exploited in IPL experiments yet should provide with
informative and complementary results.

<h>METHODS</h>
-------

In this experiment the classic mispronunciation IPL paradigm is used: two objects are
presented side by side on a screen and one is named halfway through the trial.
Pronunciation is correct for half the trials (e.g., “Look! Bed!”), and incorrect for the
other half (“Look! Bud!”, for bed). We developed three versions. In the No Fixation
condition, no central fixation stimulus was used and images were simply controlled for
suitability and size but not for background, colour or perceptual saliency (they mostly
had a naturalistic background). In the second, Fixation condition, a fixation stimulus was
added before the start of every trial, and in the last condition, Fixation Plus, this was
augmented by controlling the background colour of the pictures and their relative
saliency.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants from the three conditions were matched for gender, age and vocabulary scores
as measured by the Oxford Communicative Development Inventory (Hamilton, Plunkett, &
Schafer, 2000). Twenty 20-month-olds were successfully tested for the Fixation condition
(mean age 20;07; range 19;19 to 21;13; SD 3 days; 8 females and 12 males). Average OCDI
scores were 241 words (SD = 19.1) in comprehension. One additional participant was
excluded for fussiness. The population in the Fixation condition served as the baseline
for the selection of participants in the two other conditions as they were matched on
their OCDI scores in comprehension. Thus, 20 children out of an initial group of 39
children constituted the No Fixation condition (M = 19;16; range 18;20 to 20;29; SD 4
days; 8 females and 12 males). Their comprehension score was 234 words on average (SD =
17.7). Participants for the Fixation Plus condition (M = 19;27; range 18;14 to 21;5; SD =
5; 8 females and 12 males) were selected from the participants of Durrant et al. (2014, 32
toddlers), with an average comprehension score of 241 words (SD = 15.6).

<hs>  Stimuli</hs>
  ~~~~~~~

The stimuli were 32 monosyllabic consonant initial words taken from the OCDI (see Appendix
B), half targets and half distracters. All are imageable nouns. Target words were judged
as known by at least 40% of 20-month-olds (database from the Oxford Babylab), and they
were paired with a distracter sharing the same onset consonant and phonemic structure
(e.g., dog and duck). Out of the 16 targets, participants heard 8 labels that were
correctly pronounced and 8 that were mispronounced. Following Mani and Plunkett (2007),
mispronunciations were obtained by changing one phoneme on one or more dimension, either
on the onset consonant or the vowel (4 trials each), leading to a pseudoword or a very
rare word in infant-directed speech (e.g., bud). The speech stimuli were recorded in an
enthusiastic child friendly manner by a female native speaker of British English.
Recordings were conducted in a sound-attenuated booth, digitized at a rate of 44.1 kHz and
a resolution of 16 bits. The recorded tokens were matched so that the duration, amplitude
and F0 of the correctly pronounced labels and their mispronunciations did not differ
significantly. The tokens were then spliced onto a carrier sentence “Look! Target word!”,
with onset of the test word starting 2500 ms into the trial. Note that the auditory
stimuli are identical across conditions. The visual stimuli were photographs of the
targets and distracters retrieved from the web and judged by the experimenters as good
exemplars of the chosen categories. For the Fixation and Fixation Plus conditions, a
smiley face was presented between trials at the centre of the screen until fixated by the
participant, and followed by the next trial (triggered by the experimenter). For the
Fixation Plus condition, image quality was manipulated: as exemplified in Appendix C, we
systematically removed background colour and matched pictures (pairs of target and
distracter) for visual saliency. This was checked with Pearson's correlation conducted on
the vectorized image pairs (Chinga & Syverud, 2007). The saliency of target-distracter
pairs presented to the No fixation and Fixation conditions was not well correlated (0.13
on average, for the absolute value of the Rs), whereas a reasonable correlation for the
Fixation Plus condition was found (0.35 on average, which is a good correlation magnitude,
Hemphill, 2003). Images were projected onto a screen 1.20 m away from the child, each of
the stimuli image measured 52 cm diagonally and were separated by 43 cm, so that both
images were comprised within 48° of visual angle with 10° of gap between them. The smiley
face was centred and measured 14 cm diagonally.

<hs>  Procedure</hs>
  ~~~~~~~~~

After written consent was obtained, both the participant and the parent were invited into
the room set up for the IPL. An image was presented on the screen in the dimly lit room so
as to entice the child into sitting in a high chair. A short animated cartoon was played
on the screen to keep her entertained and looking at the screen while the experimenter
adjusted the cameras on her face. The parent sat behind the child and was asked not to
intervene in any way so as not to influence the child. The experimenter could hear the
stimuli being presented (so that she could also hear possible parental intervention) but
could not see the screen. Each of the 16 trials (plus two for training) were started
manually by the experimenter when the child was looking at the screen (anywhere for the No
Fixation condition) or at the centre of the screen, that is, at the smiley face (for the
Fixation and Fixation Plus condition). Participants were presented with 8 correct labels
and 8 mispronounced labels. Order of presentation, pronunciation type and side of the
target were counterbalanced across participants.

<hs>  Scoring</hs>
  ~~~~~~~

The digital scoring system developed by Meints and Woodford (2008) was used to synchronize
videos with trial onsets. Eye movements (left image, right image, middle or away) frame by
frame (40 ms) were scored by skilled coders trained by the first author and naïve to the
items being presented to the participants. Each eye fixation was coded, and an independent
skilled coder scored 10% of the pool of data randomly for each group. Agreement between
coders was high with an intraclass correlation coefficient of 0.936 (Shrout & Fleiss,
1979). Looking times on each image were then automatically extracted for the pre- and
post-naming phases, providing the proportions of looks to the target and the distracter in
the pre- and post-naming phases, as well as longest look measures and frame by frame eye
position for the time-course analysis.

<hs>  Time course plot and windows of analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Following recommendations by Fernald et al. (2008), proportions of looks to the target as
a function of time and pronunciation type were plotted in Fig. 1 for each condition (No
Fixation, Fixation and Fixation Plus). Visual inspection of the plots suggests that the
usual 367–2000 ms window post-naming seemed adequate, although it looks like the naming
effect extended after 2000 ms post-naming for the No Fixation and the Fixation conditions.
The final time course analysis (as in von Holzen & Mani, 2012) will be the best test to
determine when pronunciation effects occur. It can be seen from the plots that at the end
of the pre-naming phase, looks to the target were, on average, below the expected 50%
(corresponding to no preference for targets or distracters) for the No fixation and the
Fixation conditions, while the proportion was more balanced for the Fixation Plus
condition. While Fernald et al. (2006) recommend an average of 50% of looks to the target
in the pre-naming phase to avoid any bias, it is often normalized by subtracting pre-
naming measures from post-naming measures (see, among others, Mani & Plunkett, 2007) or
computing a salience score like in Swingley and Aslin (2007). We will return to this
observation in the discussion.

<hs>  Selection of trials</hs>
  ~~~~~~~~~~~~~~~~~~~

First of all, we only analyzed trials where the target was known to the participant. As
children were matched for vocabulary knowledge across the three conditions, we expected
the proportions retained for each condition to be comparable: 95.0% for the No Fixation
condition (304/320 trials), 87.8% for the Fixation condition (281/320), and 93.4% for the
Fixation Plus condition (299/320). However, a chi-square test run on the raw scores
revealed a significant difference between conditions (χ2(2) = 12.55, p = .002). A general
linear model of the data with vocabulary (target known vs. unknown) and condition (No
Fixation, Fixation, Fixation Plus) as factors confirms that more words were known in the
No Fixation condition compared to the Fixation condition (z = 3.001, p = .003), but not
between the No Fixation and the Fixation Plus conditions (z < 1, n.s.). This was very
likely due to a sampling effect, since the Fixation group is the only one where two
participants did not know 6/16 words, while in the other groups the maximum words that
were unknown did not exceed 4/16. The χ2 test excluding these two participants shows that
then the three groups no longer differed (χ2(2) < 1, n.s.). The second step in data
selection often involves an inspection of looking time distribution trial per trial. The
procedure presented by Fernald et al. (2008) includes a pre-screening of the recorded
videos. Another way of retaining attended trials is to select trials where the child is
looking at both pictures, either necessarily in the pre-naming phase (strict criterion),
or at some point throughout the trial (lax criterion). The strict criterion is likely to
result in cleaner data; however it could be that the lax criterion is preferable: training
trials should be sufficient for the child to understand that pictures appear in the two
corners of the screen. Consequently, upon hearing “Look! Dog!”, shifts to the target in
the post-naming phase when the child did not look at the target picture in the pre-naming
phase can still be considered as a sign of word recognition (re. mutual exclusivity in
monolinguals, Houston-Price et al., 2010). In what follows, we present data based on the
lax criterion, but we also provide in Appendix C.1-3 the analyses based on the strict
criterion. With the lax criterion (looks at the target and distracter at some point
throughout the trial), we retained 98.7% of the known trials in the No Fixation condition
(300/304), 95.4% in the Fixation condition (268/281) and 97.0% in the Fixation Plus
condition (290/299). A Pearson's chi-square test with Yates correction shows that the
rejection rate did not differ across conditions (χ2(2) = 4.52, p = .10). The strict
criterion (looks to both target and distracter during the pre-naming phase) retained 88.8%
of the trials in the No Fixation (270/304), 90.4% of the Fixation trials (254/281) and
88.0% of the Fixation Plus trials (263/299). Again, a chi-square test revealed no main
effect of condition (χ2(2) < 1, n.s.). Note that all children were included in the
analysis as they contributed to all conditions (re. Fernald et al., 2006).

<hs>  Looking behaviour in the pre-naming phase</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Preliminary analysis of the pre-naming phase is meant to control for a potential bias
towards the image that will be named later in the trial. Although averages were close to
50% during the whole pre-naming phase, they were significantly below chance for No
Fixation (M = 44.4%, SD = 6.0%, t(19) = −4.15, p = .001) and Fixation (M = 42.9%, SD =
5.9%, t(19) = −5.34, p < .0001), showing a bias towards the distracter image, which was
similar in both conditions (t(38) < 1, n.s.). In the Fixation Plus condition however this
bias was no longer significant (M = 49.1%, SD = 4.5%, t(19) < 1, n.s.), and differed
significantly from that in the No Fixation condition (t(38) = −2.79, p = .008) and the
Fixation condition (t(38) = −3.72, p = .001).

<hs>  Dependent variables</hs>
  ~~~~~~~~~~~~~~~~~~~

IPL studies in the literature have presented a whole range of different dependent
variables (see Table 1), and included pre-naming as a factor (Mani & Plunkett, 2007;
Styles & Plunkett, 2008) or as a salience score (Swingley & Aslin, 2007; White & Morgan,
2008). In the first case, the two resulting independent variables are naming (pre- vs.
post-naming) and pronunciation (correct vs. incorrect), and in the second case only
pronunciation. Results from the pronunciation effect with the salience score are then
identical to the post-hoc analysis of the naming × pronunciation interaction. As such, we
will not present the salience score analysis. It is worth noticing that sometimes the pre-
naming phase is not explicitly analyzed (Fernald et al., 2008; Ramon-Casas et al., 2009;
Schafer & Plunkett, 1998; Swingley, 2003). The most widely used dependent variables are
either the longest look measure (LLK) or the proportion of total looks towards the target
(PTL). The PTL is usually calculated by dividing the total looking time to the target (T)
by the total amount of looks to the target and distracter, that is T/(T + D), in the pre-
and post-naming phases. A significant increase in the PTL in the post- compared to the
pre-naming phase is taken as evidence of a naming effect. A significant decrease or
absence of difference will show an absence of naming effect, that is, no evidence of word
recognition. The LLK, on the other hand, represents the longest single fixation on the
target (and also distracter). Successful word recognition, or the naming effect, should
lead to an increase of LLK in the post-naming compared to the pre-naming phase.
Descriptive statistics are presented for the analysis where children looked at both images
at some point during the whole trial (lax criterion), with proportion of looks to the
target (PTL, Fig. 2) and longest look (LLK, Table 1) measures for the target and
distracter, in the pre- and post-naming phases. Statistics are reported for the overall
LLK and PTL as dependent variables, with pronunciation (correct, incorrect) and naming
(pre-, post-naming) as within-participant factors, and condition (No Fixation, Fixation,
and Fixation Plus) as between-participant factor. We also report effects and interactions
of pronunciation and naming for each condition separately, as each condition could
potentially constitute a stand-alone experiment. Since the p values appear to be
comparable for both measures (with the exception of the triple interaction, significant
with LLK, and driven by the interaction between naming and pronunciation for the Fixation
Plus condition), in the first following section we only report values for the PTL measure.
Detailed descriptive statistics for the other measure (LLK) can be found in Table 1, and
the corresponding ANOVAs are described in the following sections. Comparisons of measures
will be discussed in the next section.

        <hss>Comparison between dependent measures</hss>

        So far, we ran a first series of analyses with condition, pronunciation and naming
        as factors, followed by a second series of analyses broken down by condition, with
        pronunciation and naming as factors. For the two dependent variables, we observed
        an overall agreement in the statistical tests, in particular for the naming
        variable, where the largest effect was expected overall. The more sensitive
        result, namely the interaction between pronunciation and naming, is clearly absent
        in the No Fixation and Fixation conditions, and robust in the Fixation Plus
        condition. A rerun of all these analyses on trials retained with the strict
        attention criterion (that is, trials where children look at both pictures in the
        pre-naming phase) produced a comparable pattern of results (see Appendix D),
        except for the main effect of pronunciation that became weaker (from marginal to
        non-significant for the No Fixation condition, and from significant to marginal
        for the Fixation Plus condition).

        <hss>Time course analysis</hss>

        Time course plots allowed us initially to visualize the time window where the
        naming effect was most likely taking place, ensuring that using the classic
        367–2000 ms window would not miss out interesting data points. The following tests
        will provide us with a more precise measure as to when the two pronunciations
        elicit quantitatively different looking time behaviour. In order to analyze the
        time course of the proportions of look, we followed the methods advocated by von
        Holzen and Mani (2012), a non-parametric random permutation analysis (Maris &
        Oostenveld, 2007) to test effect of pronunciation across time, so as to identify
        the time period when looking times were significantly different. With this method
        however, and contrary to the classic PTL analysis including naming as a factor,
        pre-naming behaviour is not taken into consideration in relation to post-naming.
        This is why we considered another analysis of the time course, focusing on post-
        naming data corrected by the pre-naming data (PTL during the post-naming phase –
        average PTL in the whole pre-naming phase). In short, we ran two analyses, one
        similar to von Holzen and Mani (2012), and one where the average PTL to the target
        in the pre-naming phase (between 367 and 2000 ms) is subtracted from each data
        point. The latter will reveal any potential pronunciation effect that would have
        been masked by a pre-naming bias. The procedure, best described in Maris and
        Oostenveld (2007), identifies the time period where looking behaviour differs
        between the correct and incorrect pronunciation, that is, the naming effect. In
        the first step of the procedure individual paired sample t-tests were performed at
        each time sample, and used to identify significant (p < .05) t-values. In step-
        two, clusters were identified by finding significant t-values that were contiguous
        across time. For each such cluster, a cluster-level t-value was calculated as the
        sum of all single sample t-values within the cluster. Analysis thereafter was
        based on these clusters and their associated cluster level t-value, rather than
        the individual (and highly non-independent) t-values. Since cluster level t-values
        could not be tested for significance against a standard t distribution, in step
        three of the procedure, the significance of each cluster was calculated by
        comparing its cluster-level t-value to a Monte Carlo distribution of cluster level
        t-values generated from the cluster with the largest cluster-level t-value. To do
        this each of the original paired sample t-tests that were used to generate this
        cluster were repeated, but with the data items of each pair randomly assigned
        between the two conditions. This was performed 1000 times to generate a Monte
        Carlo distribution of 1000 summed t-values corresponding to the null hypothesis.
        The summed t-values of these randomized tests provided a null distribution against
        which the actual cluster-level t statistic of each of the observed cluster could
        be compared. Thus, for each observed cluster, a Monte Carlo p-value was calculated
        as the proportion of the null distribution which had a cluster-level t statistic
        that exceeded the actual cluster-level t-statistic. The first series of analyses
        were conducted on the whole trials (pre- and post-naming phases) and revealed no
        significant difference between correct and incorrect trials for the No Fixation
        condition (identified cluster: 900–1060 ms after target word onset; cluster t
        statistics = 12.13, Monte Carlo p = .50) and the Fixation condition (here, the two
        pronunciation conditions do not differ significantly from each other in any time
        window, therefore no Monte Carlo estimate was calculated) (Fig. 1a and b). For the
        Fixation Plus condition however (Fig. 1c), the two types of pronunciation differed
        significantly between 900 and 1580 ms post stimulus onset (cluster t statistics =
        48.73, Monte Carlo p = .04), with an increase in looks at the target when it was
        correctly named. The second series of analyses was conducted on the post-naming
        phase only, after subtracting the overall PTL to the target in the pre-naming
        phase. This is a similar approach to the inclusion of the salience score by
        Swingley and Aslin (2007), where they analyze PTL in the post-naming phase, minus
        PTL in the pre-naming phase; instead this time it is applied on each time frame.
        Again, no significant difference was obtained in the No fixation condition (all
        t-tests reveal ps > .05). In the Fixation condition a cluster between 2420 and
        2460 ms post word onset was identified but was, however, non significant (cluster
        t statistics = 4.33, Monte Carlo p = .96). For the Fixation Plus condition, we
        found a significant difference window which was comparable to the first series of
        analyses, with more looks to the correctly pronounced target from 740 to 1940 ms
        after stimulus onset (cluster t statistic = 105.34, Monte Carlo p = .002). The
        same analyses conducted on the dataset selected with the strict criterion reveal
        rather comparable results, with perhaps more sensitivity. On the whole duration of
        the trial, the No Fixation condition reveals difference cluster between 980 and
        1700 ms after the word onset, but Monte Carlo simulations failed to confirm that
        this difference is significant (cluster t statistics = 12.76, p = .53). For the
        Fixation condition no cluster was identified (all t-tests reveal ps > .05). For
        the Fixation Plus condition, we replicate the significant effect of pronunciation,
        from 980 to 1700 ms after stimulus onset (cluster t statistics = 54.55, p = .03).

<h>DISCUSSION</h>
----------

The goal of the present study was to evaluate how infants’ looking behaviour in the Inter-
modal Preferential Looking paradigm varies as a function of noise generated by two simple
methodological modifications, and how different methods of analysis best account for the
resulting behavioural changes. Three groups of 20-month-olds were tested for recognition
of correctly and incorrectly pronounced familiar words, in conditions that varied in terms
of level of visual noise. In the first, No Fixation condition, no central fixation
stimulus was used and images were simply equated on size and judged as good exemplars,
with no attempt to control for background and salience. In the second and third conditions
(Fixation and Fixation Plus), a central fixation stimulus appeared between trials to
attract the child's gaze to the centre before the onset of the next trial (and not at the
onset of the post-naming phase as in Portillo et al., 2007, cited in Fernald et al.,
2008). In addition, in the third, Fixation Plus condition, children were presented with
images without any background and target-distracter pairs were matched for visual
salience. To analyze the resulting data we examined the impact of different trial
selection criteria, compared two dependent measures (LLK and PTL) and performed a time
course analysis using a combination of Monte Carlo estimate and cluster analysis, to
identify the time period where mispronunciation affected behaviour. Following numerous
studies using a similar paradigm (e.g., Mani & Plunkett, 2007; Swingley, 2003; Swingley &
Aslin, 2000; White & Morgan, 2008), the expected result at 20 months was a naming effect
restricted to the correctly pronounced targets, that is, an increase in looks to the
target in the post-naming phase as compared to the pre-naming phase, only when the target
word is pronounced correctly. We also expected that each methodological modification
(addition of a central fixation and increased control of images) would contribute to
enhance the quality of the data. The central point of the study was to determine which
method of analysis would prove the most robust across methodological variations, and which
would be the most sensitive. Results overall revealed that all three groups showed a main
effect of naming, that is, children fixated the target image longer after it was named.
However, only the Fixation Plus group behaved as predicted by the literature, they showed
a naming effect restricted to words correctly pronounced, just like in Mani and Plunkett
(2007) or Swingley and Aslin (2000). Our main interpretation of these results is that the
combination of the central fixation point and the selection of better-controlled images
contributed to enhance the quality of data, and to reduce experimental noise, in the pre-
naming phase, which in turn resulted in less variable post-naming data, as will be
discussed below. We suspect that other parameters could act to reduce similarly the level
of unwanted noise, such as the use of the same items to act as targets and distracters (as
recommended by Fernald et al., 2008, see Mani & Plunkett, 2007; Swingley & Aslin, 2000) or
the selection of the most frequent words in a child's vocabulary (e.g., Swingley & Aslin,
2000). By progressively reducing the noise in the visual stimuli in the Fixation Plus
condition, exploration of the visual stimuli during the pre-naming phase was more balanced
with a PTL to the target around the expected 50%, despite a slight bias towards the
distracter across all conditions. This bias must be due to reduced familiarity with the
distracter objects (across all groups, participants were reported knowing the names of the
target in 283 trials, and the name of the distracter in 246 trials), which thus worked as
initial attracters. However, the pre-naming imbalance was not strictly comparable in the
No Fixation (Fig. 1a) and the Fixation (Fig. 1b) conditions: whereas it was observed from
the very onset of the pre-naming phase in the No Fixation condition, in the Fixation
condition children looked equally long at targets and distracters from the onset of the
pre-naming phase, and it is only after about 300 ms that the preference for distracters
emerged. Given that the only methodological difference between the No Fixation and the
Fixation conditions was the adjunction of a central fixation stimulus at the onset of each
trial, it is quite likely that this central fixation point contributed to reducing the
imbalance between target and distracter looks during the pre-naming phase. However,
controlling for the quality of images had a cumulative positive effect, as seen in the
Fixation Plus condition. Not only were pre-naming looks between targets and distracters
more balanced, but the expected naming effect was obtained earlier, and was more robust
than in the Fixation condition. What changed between the two conditions was a
disappearance of the background and a quantitatively controlled balance in visual salience
of the target-distracter pairs. Whether background control contributed more than saliency
control to the sharpening of infants’ behaviour remains undetermined in this study. At
this point, these results allow us to add to the recommendations of Fernald et al. (2008)
and from the literature using the IPL paradigm: a fixation stimulus helps by centring the
child's attention before trial onset, and carefully selected images even out the
probability of looking at both images in the pre-naming phase, enhancing the sensitivity
of the method. Crucially, our central aim was to compare how these different
methodological choices would impact on the robustness of data through the lens of
different analytical choices such as the criteria for data selection and the dependent
variables. The literature shows that the criteria used for data inclusion or rejection in
the pre-processing phase varies substantially across experimenters. A most reasonable
practice – which we did not question – is to include only trials where the target word is
known by the participant, as attested by parental questionnaire. More questionable is the
practice of rejecting trials during which the child has not looked at both the distracter
and the target at some point: does it have to be at some point during the entire trial
(lax criterion), or during the pre-naming phase only (strict criterion)? We have shown
that the two criteria, which measure the level of attentiveness during each trial, do not
lead to fundamentally different results. Unsurprisingly more trials were rejected due to
the application of the strict criterion (2.9% for the lax criterion vs. 11.0% for the
strict criterion), resulting in a loss of experimental power. However, a close inspection
of results in the PTL section in the Results section and Appendix D.2 shows that the size
of the main effect of condition is larger when the strict criterion is applied. In
contrast, applying the lax criterion results in larger sizes for all other effects,
including pronunciation and naming as well as the crucial naming × pronunciation
interaction. This suggests that the overall behavioural adjustments due to methodological
changes may be enhanced with the use of the strict criterion, but not the quality of the
key effects (naming modulated by pronunciation). With the strict criterion, we ensure that
children have seen the target and the distracter during the pre-naming phase. Upon hearing
the label they would know that a mispronounced name does not correspond to any picture;
they can then use a ‘better match’ strategy based on phonological overlap and look
slightly longer at the target. This translates into a relative decrease in the size of the
pronunciation effect as compared to the same data analyzed with the lax criterion. In
contrast, with the lax criterion, we also include trials where the child has only checked
the target during pre-naming,1 and therefore, can reasonably assume that the
mispronounciation can refer to the unchecked item. This results in a slightly higher
number of looks towards the distracter during the post-naming phase. To sum up, data may
suggest that we do not measure the same behaviour or strategy if we apply the strict or
the lax criterion: for the former, we may measure a better-fit strategy based on the
degree of phonological overlap, whereas in the latter, children may produce a response
based on a Mutual Exclusivity-type principle (Halberda, 2003). If this speculative
assumption was corroborated by further research, this should be kept in mind when deciding
for one criterion over the other, depending on the theoretical goals of the experiment. We
have seen that it is common practice to exclude trials in which children do not know the
name for the target object; is it justified to also exclude trials where the child does
not know the distracter (as done by, among others, Swingley et al., 1999)? On the one
hand, this could have some advantage: the children would be more likely to look away from
an incorrectly named target image and attach the mispronounced label to the distracter
(White & Morgan, 2008), strengthening the mispronunciation detection effect. On the other
hand, unknown distracters could result in children showing a familiarity effect rather
than a naming effect (looking at the named target simply because they have a name for it,
not because it has been named with its specific label). Quite pragmatically, excluding
trials in which the child does not know the distracter would possibly result in a loss of
experimental power. This was indeed the case for the No Fixation and Fixation conditions,
but not in the more robust condition where the critical interaction was replicated.
Therefore it appears that the application of this criterion does not substantially modify
the quality of the data, at least not in the current study. It should be kept in mind
however that, similarly to what was discussed above for the use of the lax vs. strict
criteria, knowing, or not knowing, the distracter label may modify the strategy that the
child uses in the procedure. An unknown distracter promotes the use of the Mutual
Exclusivity principle whereas a known distracter encourages the use of a best-match
strategy based on the degree of phonological overlap. Regarding the choice of the
dependent variable, the literature often presents side by side analyses based on the
proportion of looks to the target (PTL) and on the longest look to the target (LLK), as
they usually show similar results. The same conclusion can be applied here, although with
a caveat. A close inspection of statistics in the result section shows that in most
analyses, effect sizes are larger for the LLK measures than for the PTL ones. This could
be due to the fact that in the vast majority of cases, the longest look is also the first
look towards the target, and during that period which lasts about 700 ms (see Table 1),
the child computes all the information that is needed to correctly identify the target.
Possibly all further looks towards the target are either verification or random noise,
which is incorporated in the PTL measure but not in the LLK variable, resulting in less
variable data in the latter than in the former measure. Finally, we questioned the
importance of adjusting the time window of analysis, and investigated the relevance of a
time course analysis. Depending on the age and/or vocabulary size of the participants, it
is common practice to adjust the onset of the post-naming phase to account for variation
in gaze shift latency (Fernald et al., 2008). In addition, many factors can influence the
processing time of the target and distracter pictures, starting with the nature and
complexity of the auditory stimulus, the visual properties of the stimuli (e.g., Arias-
Trejo & Plunkett, 2010), or the type of distracter (familiar vs. unfamiliar; White &
Morgan, 2008). Therefore a time window fixed a priori may not be the most accurate. Of
course, selecting for each experiment a time window based on the visual inspection of the
data would be unacceptable as it would lead to a strong human bias. One way around this is
to generalize the use of the time course analysis as reported here which allows the
identification of time windows where the naming or pronunciation effects are indeed
significant. It seems that the statistical analysis of the time course provided an
accurate estimate of looking behaviour, since it allowed us to distinguish between a very
short lived pronunciation effect (in the No Fixation condition) and an enduring one (with
the Fixation Plus condition). This mirrored the outcome of the classic mean-based looking
times analyses, namely a robust interaction pronunciation × naming in the Fixation Plus
condition and none in the No Fixation condition. While very promising to estimate the
speed of word recognition (like Durrant et al., 2014; Fernald et al., 2006), this approach
needs to evolve to establish the minimal temporal window where pronunciation differences
are meaningful (re. the very short lived pronunciation effect in the No Fixation
condition). In summary, observations based on infants’ behaviour in a classic IPL task can
vary quite substantially depending on the methodological parameters chosen during the pre-
processing period or data analysis. Perhaps the vulnerability of the data are best
illustrated in Fig. 2c which displays the results of the Fixation Plus condition.
Correctly and incorrectly pronounced words produced different looking times for about 700
ms, as revealed by the time course analysis. This is a rather short window of interest as
compared to the entire duration of the trials, for example as compared to head-turn
procedures which typically generate differences of about 2 s of looking times between
conditions (e.g., Mattys, Jusczyk, Luce, & Morgan, 1999; Jusczyk & Aslin, 1995). It can be
argued that IPL is a more direct and precise measure of auditory processing than head turn
paradigms as it does not rely on an experimenter's intervention during the session
(whereas head turn set-ups usually do: Floccia et al., 2012; Nazzi, Jusczyk, & Johnson,
2000; Schmale & Seidl, 2009). Yet this augmented precision perhaps makes the IPL tool more
prone to vary with methodological noise. To borrow an example from physical instruments, a
digital thermometer might be more precise than a mercury one, yet thanks to its inertia
the latter is more likely to give robust repeated measures than the former. It is our hope
that this methodological study will contribute to sharpen the use of this invaluable
paradigm in the quest of infants’ representation and processing of visual and auditory
information.


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<ART>A picture tells a thousand words: What Facebook and Twitter images convey about our personality
================================================================================

Authors: Monica Therese Whitty, James Doodson, Sadie Creese, Duncan Hodges
DOI: 10.1016/j.paid.2016.12.050
Year: 2018  |  Pages: 109-114
ASJC codes: 3200
Keywords: Big Five, Cyberpsychology, Facebook, Personality, Profile images, Social network sites, Twitter

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Researchers have questioned whether there is a relationship between personality and patterns of online self-presentation. This paper examined, more specifically, whether personality predicts profile choices as well as image choice behaviour on two different SNSs: Twitter and Facebook. We found that personality does, to some extent, predict choices regarding profile images; however, not always in the direction we predicted and results differed across sites. We found that participants who scored higher on conscientiousness and lower on extraversion were more likely to change their Facebook profile image. Participants who scored lower on extraversion were more likely to choose a Twitter profile image that included a photograph of themselves compared to participants who scored higher on extraversion. For participants whose Facebook profile image was a photograph of themselves, a greater proportion of participants selected a recent photograph from the past six months. However, this was not the case for Twitter. We conclude that personality can predict some image choices and behaviours that might be useful for future work on authentication and identification, although other predictor variables are potentially also important when considering the types of individual characteristics which might predict online behaviour on SNSs.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Social networking sites (SNSs) have become a popular medium for communication and
networking for individuals of all ages (Nadkami & Hofmann, 2012; Subrahmanyam, Reich,
Waechter, & Espinoza, 2008; Valkenburg & Peter, 2009). These sites can potentially provide
valuable information about a person that could assist in authentication and
identification. Moreover, they might provide the user with rich information (e.g., about
potential dates or employees). In contrast, of course, users can perform different
versions of the ‘self’ on these platforms (e.g., Turkle, 1995) or, as others would
contend, express their ‘true selves’ in this space (e.g., Marriott & Buchanan, 2014;
McKenna & Bargh, 2000). Although researchers are beginning to learn more about what online
personal data presented on SNSs might tell us about a person, there is scope to learn much
more about digital identities and what they reveal about the person behind the profile.
This study focused, in particular, on whether personality predicts profile choices as well
as image choice behaviour on two different SNSs: Twitter and Facebook. Drawing from
Goffman's (1959/1997) work, it has been theorised that SNSs provide an ideal environment
for impression management. SNS users can be very selective in the information they choose
to present on these sites, including, for example, their interests, activities, opinions
and emotions. It has been argued that some users consciously select information to present
in order to convey a certain impression (Wu, Change, & Yuan, 2015). Equally, however, some
details might leak additional personal information about a person, unintended and
sometimes unbeknownst to the user; for example, ethnicity, education or class (Whitty &
Young, 2017). Individuals who score higher on certain types of personality characteristics
might choose to represent themselves in distinct ways (e.g., Back et al., 2010; Krämer &
Winter, 2008). Extraverts, for example, are: more likely to select self-representative
photographs (Wu et al., 2015), less likely to post conservative pictures of themselves,
have a greater number of online friends, and are more likely to use the communication
function on SNSs (Krämer & Winter, 2008; Wang, Jackson, Zhang, & Su, 2012). Neurotic
individuals are more likely to use the status update feature and agreeable individuals are
more likely to write comments on others' profiles (Wang et al., 2012). Women low in
agreeableness are more likely to use the instant messaging features on social networking
sites, while men low in openness play more games via social networking sites (Muscanell &
Muscanell & Guadagno, 2012). Individuals who score high on narcissism are more likely to
select pictures that are more physically attractive (Kapidzic, 2013; Wu et al., 2015).
Images and photographs, in and of themselves, might be used intentionally to convey a
particular identity, including personality features (e.g., Wu et al., 2015). Kapidzic and
Herring (2015), for example, found that females are more likely than males to select a
seductive photograph as their profile picture. Zheng, Yuan, Chang, and Wu (2016) found
that women are more likely to emphasize emotional expression in their profile pictures
compared with men, whilst men were more likely to emphasize having fun. Users, however,
might also unintentionally leak aspects about a person; such as age, ethnicity, hobbies,
relationship status (Lee-Won, Shim, Joo, & Park, 2014). For example and perhaps
unsurprisingly, it has been found that individuals who upload dyadic profile pictures on
Facebook report feeling more satisfied with their relationship and closer to their
romantic partners compared with individuals who do not (Saslow, Muise, Impett, & Dublin,
2012). Tifferet and Vilnai-Yavetz (2014) have found that men were more likely to have
profile pictures which accentuate status and risk taking, while women were more likely to
have photographs which including familial relations and showed emotional expression. The
research presented in this paper builds upon this previous literature by examining whether
personality predicted users' profile image choices on SNSs. We focused on two different
types of SNSs in our study, which serve different social purposes — Facebook and Twitter.
Facebook is more privately oriented with a focus on maintaining connections with existing
friendship groups and communicating with them via multiple methods (Raacke & Bonds-Raacke,
2008). Conversely, Twitter is more publically oriented and users' friends are more likely
to be unknown compared with Facebook friends (Hughes, Rowe, Batey, & Lee, 2012; Marwick,
2011). We investigated whether personality predicts: how often users change their profile
image; if individuals choose to use an avatar (an icon or figure that represents that
person, but is not a photograph of that person) or a photograph of themselves; if users
include a recent photograph of themselves; and if users select a profile image they
believe represents their personality.

<hs>  Hypotheses</hs>
  ~~~~~~~~~~

We employed the Five Factor model (Costa & McCrae, 1992; Goldberg, 1990), which is
commonly employed to measure personality. We hypothesised that those who score high on
extraversion (H1) and conscientiousness (H2) will be more likely to change their images
more frequently compared with those who score low on these two scales. Our first
hypothesis is based on the assumption that because extraverts are outgoing and social they
will be more likely to want to update how they present themselves. Our second hypothesis
is based on the assumption that those who score high on conscientiousness will be more
motivated to keep their profile up-to-date. It was further hypothesised that individuals
who score low on openness to experience (H3) and high on extraversion (H4) will be more
likely choose a photograph than an avatar. These hypotheses are based on the assumption
that people who score higher on openness tend to be more creative and open to new ideas
and therefore an avatar might be perceived as a more creative depiction of themselves,
whilst, introverts might choose an avatar in preference to a photograph to divert
attention away from themselves. The fifth hypothesis (H5) is that those who score high on
conscientiousness will be more likely to include a recent photograph of themselves. Again,
this is based on the assumption that conscientious people might be more likely to keep
their profile up-to-date. The sixth and final hypothesis (H6) is that individuals who
score low on openness to experience will choose an image that more closely represents
their self-concept. This is based on the assumption that because individuals low on
openness to experience are far less likely to be creative and experimental they will chose
an image that more closely represents their self-concept.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

One thousand, two hundred and twenty four individuals were recruited from a ‘Qualtrics’
online panel. Of these individuals, 357 individuals reached the end of the study (29%
completion rate), in the main due to screener questions, which eliminated participants due
to not having a Twitter and a Facebook account (43%). This meant the drop out rate, due to
incompletion of the survey was only fairly small (28%). Another 150 individuals were then
excluded for no longer using their Facebook or Twitter account (136), for withdrawing
their consent for the study (8), for repetitive or inappropriate responding (4), or for
incomplete responses (2). After exclusions, the final sample for this study consisted of
207 participants (115 male; 92 female). The mean age of the sample was 40.1 years (SD =
13.1) ranging from 19 to 77 years. For men, the mean age was 41.0 years (SD = 12.8)
ranging from 19 to 68 years. For women, the mean age was 39.0 years (SD = 13.3) ranging
from 20 to 77 years. All participants had both an active Facebook and Twitter account.

<hs>  Materials</hs>
  ~~~~~~~~~

Data were collected using a questionnaire hosted on the Qualtrics online survey platform.

        <hss>Big 5</hss>

        Personality traits were measured using a Five-Factor Personality Inventory
        validated for use online (Buchanan, Johnson, & Goldberg, 2005). This 41-item
        inventory gives measures of Openness to Experience, Conscientiousness,
        Extraversion, Agreeableness, and Neuroticism. The subscales have high reliability
        and have been successfully used in a range of Internet-mediated studies. In our
        study, Cronbach's α ranged from 0.69 to 0.84.

        <hss>Self-rating items</hss>

        Participants were asked several questions about their Facebook and Twitter
        activities, including: frequency of use (on a 7-point scale from ‘once a year or
        less’ to ‘more than once a day’); how regularly they changed their profile image
        (on a 7-point scale from ‘once a year or less’ to ‘more than once a day’); whether
        the profile image was an avatar or a photograph of themselves (with three
        categories to choose from: ‘yes, the image includes a recent photograph of me from
        the last six months’; ‘yes, the image contains a photograph of me, although is
        more than six months old’; ‘no, the image does not contain a photograph of me’);
        and how closely their profile image represented their personality with three
        categories to choose from (‘not at all representative’; ‘somewhat representative’;
        ‘very representative’) (see Table 1 for correlations between these items). We
        appreciate that the question that asks participants how closely their profile
        image represented their personality might not be interpreted as personality
        representativeness per se. However, by this question we were more interested in
        the participants' perceptions of self-concept. We opted to use this phrasing given
        our piloting of questions suggested that participants felt more comfortable with
        the term personality, as this term was more commonly used in ‘everyday speech’.
        Furthermore, we believed it was important to ask this question to all users (i.e.,
        those who included an avatar or a photograph). This is based on previous research
        that has examined representation of self via the use of photographs (e.g.,
        Fernandez, Stosic, & Terrier, 2017; Leikas, Verkasalo, & Lönnqvist, 2013) and
        avatars (e.g., Dunn & Guadagno, 2012).

<hs>  Procedure</hs>
  ~~~~~~~~~

We commissioned Qualtrics to recruit participants from their online panel. Participants
were required to reside in the UK and have both a Facebook and a Twitter account.
Participants were presented with information about the study and asked to indicate
informed consent before proceeding. On the subsequent pages they were asked to complete a
number of demographic items; self-rating items (described above), and complete the Five-
Factor Personality Inventory.

<h>RESULTS</h>
-------

Our first two hypotheses were concerned with the frequency participants updated their
profile imagine on Facebook and Twitter. To test our hypotheses a forced-entry multiple
ordinal regression was calculated with the frequency of avatar change as the outcome
variable and the Big Five personality traits as the predictor variables. Ordinal
regression was considered appropriate given that the frequency of avatar change measure
was ordered-categorical in nature. Separate regression models were calculated for Facebook
and Twitter (frequency of participants' updates is shown in Table 2). The frequency with
which participants used an online service was also controlled for in the regressions
because participants who more frequently used a service would have more opportunity to
change their profile images compared to those participants that used a service less
frequently. In line with the second hypothesis, participants who scored higher on
conscientiousness more frequently updated their Facebook profile compared with those who
scored lower on conscientiousness. However, although we obtained a significant finding for
our first hypothesis, it was in the opposite direction to what we predicted. Participants
who scored lower on extraversion were more likely to change their profile image compared
with those who scored high on extraversion. None of the Big Five personality measures
predicted how often participants changed their Twitter profile image (see Table 3). The
third and fourth hypotheses predicted that those low on openness to experience as well as
extraversion will be more likely to select a photograph of themselves in preference to an
avatar. A Chi-square test indicated that on Facebook significantly more individuals choose
a photograph to represent themselves (n = 134; 64.7%) than an avatar; n = 73; 35.3%),
χ2(1) = 17.98, p < 0.001. However, there was no statistically significant difference in
the proportion of individuals who chose a Twitter profile image that included a photograph
of themselves (n = 108; 52.2%) compared with an avatar (n = 99; 47.8%), χ2(1) = 0.39, p =
0.532. A forced-entry binary logistic regression was used to explore the relationship
between personality and whether a profile image was a photograph of themselves or an
avatar. Separate models were calculated for Facebook and Twitter (see Table 4). The
logistic regression model for Facebook profile images was not statistically significant
(χ2(5) = 5.63, p = 0.344) and explained a very small proportion of the variance
(Nagelkerke R2 = 0.037). Consequently, the third and fourth hypotheses were rejected for
the Facebook profile images. In contrast, a logistic regression model that predicted the
content of Twitter profile images was statistically significant (χ2 (5) = 11.84, p =
0.037), provided a good fit to the data (Hosmer & Lemeshow χ2(8) = 4.59, p = 0.801) and
explained a small proportion of the variance (Nagelkerke R2 = 0.074). Contrary to the
direction predicted in our fourth hypothesis, participants who scored lower on
extraversion were more likely to choose a Twitter profile image that included a photograph
of themselves compared to participants who scored higher on extraversion (B = − 0.07, S.E.
= 0.03, Wald = 7.38, p = 0.007; ExpB = 0.93) (H4). However, our third hypothesis was not
supported. For participants whose Facebook profile image was a photograph of themselves, a
greater proportion of participants selected a recent photograph from the past six months
(n = 82; 61.2%), in preference to an older photograph that was taken more than six months
ago (n = 52; 38.8%), χ2(1) = 6.72, p = 0.010. For participants whose Twitter profile image
was a photograph, there was no statistically significant difference in the proportion of
participants who used a photograph of themselves from the past six months (n = 51; 47.2%)
and those who used an older photograph (n = 57; 52.8%), χ2(1) = 0.33, p = 0.564. The
relationship between personality and whether the profile contained a recent photograph of
the profile owner was tested using a forced entry binary logistic regression. Separate
models were used for Facebook and Twitter profile images (see Table 5). Only participants
who indicated that their profile image was a photograph of themselves were included in the
model. The frequency with which participants used an online service was controlled for
because participants who more frequently used a service have more opportunity to change
their profile image compared to those who use a service less frequently. The logistic
regression model for Facebook profile images was statistically significant (χ2(6) = 27.63,
p < 0.001), provided a good fit to the data (Hosmer & Lemeshow χ2(8) = 10.46, p = 0.880),
correctly predicted a good number of cases (71.6%), and explained a moderate proportion of
the variance (Nagelkerke R2 = 0.234). The model for Twitter profile images was also
statistically significant (χ2(6) = 23.92, p < 0.001), provided a good fit to the data
(Hosmer & Lemeshow χ2(8) = 7.07, p = 0.529), correctly predicted a moderate to good number
of cases (68.5%), and explained a moderate proportion of the variance (Nagelkerke R2 =
0.265). However, none of the Big Five personality traits predicted whether participants
selected a recent or an older photograph of themselves for either their Facebook or their
Twitter profile images (Table 5). Consequently, our fifth hypothesis was rejected for both
the Facebook and Twitter profile images. The sixth and final hypothesis was that
individuals who score low on openness to experience would choose an image that is closer
to their self-concept (see Table 6). A forced-entry ordinal regression was used to explore
the relationship between personality and the extent that participants selected a profile
image representative of their self-concept. The ordinal regression model for Facebook
profile images failed to reach statistical significance (χ2(5) = 11.36, p = 0.05,
Nagelkerke R2 = 0.067; goodness of fit χ2(371) = 354.98, p = 0.716). The ordinal
regression for Twitter profile images also failed to reach statistical significance (χ2(5)
= 11.27, p = 0.05, Nagelkerke R2 = 0.071; goodness of fit χ2(371) = 343.86, p = 0.358).
Consequently, our sixth hypothesis was rejected.

<h>DISCUSSION</h>
----------

In this paper we were interested in whether personality predicts profile image choices and
behaviours carried out two SNSs: Facebook and Twitter. In line with previous research, we
found personality does, to some extent, predict users' choice of profile images as well as
online behaviours (e.g., Back et al., 2010; Dunn & Guadagno, 2012; Hughes et al., 2012;
Kapidzic, 2013; Kapidzic & Herring, 2015; Lee-Won et al., 2014; Leikas et al., 2013;
Saslow et al., 2012; Wang et al., 2012; Wu et al., 2015; Zheng et al., 2016), but not
always in the direction we hypothesised. Given that the behaviours and the image choices
we examined are not immediately obvious indicators of personality, the work here suggests
that users leak information about themselves online, without necessarily intending to
elucidate particular personality characteristics. These findings could be applied in work
on authentication, identification or pre-screening (e.g., by cybersecurity professionals,
employers) or by organisations that wish to be more selective in the types of information
they target individuals (e.g., organisations wishing to carry out targeted advertising on
SNSs). On the other hand, these findings also suggest that users might want to be wary of
how they behave and what information they present about themselves to avoid personality
characteristics being leaked to others. Our second hypothesis, that people who are more
conscientious are more likely to update their profile images compared with those who are
less conscientious, was the only hypothesis that was supported by our data (although we
note that significant findings were obtained for many of the other hypothesises, but in
the opposite direction to what was predicted). This result might be particularly
interesting to employers who are looking to employ conscientious workers. Given that
employers are increasingly drawing from online sources to assist in employment decisions
(Davison, Maraist, Hamilton, & Bing, 2012), this finding suggests there might be some
utility in carrying out further research to examine other online indicators of
conscientiousness. Our research adds to the research that has found that extraverts behave
on SNSs in distinct ways (e.g., Krämer & Winter, 2008; Wang et al., 2012; Wu et al.,
2015); however, our findings were not in the direction we predicted. In our study,
introverts were more likely than extraverts: to update their profile images (Facebook
only) and use a photograph in preference to an avatar to represent themselves (Twitter
only). Perhaps our findings can be explained by previous work which suggests that
introverts feel protected and safe using the Internet to socially interact with others,
often preferring to communicate with others online (e.g., Amichai-Hamburger & Ben-Artzi,
2000). The introverts in our study might be focusing more of their energy on online
communications and relationships compared to offline, thereby spending more time updating
their profile images and feeling safer to display their ‘real’ image online. In addition
to our significant results, we found that hypothesis three and five were not significant
for either SNSs. Hypothesis three predicted that individuals who score low on openness to
experience will be more likely to select a photograph than an avatar. Perhaps this null
result might be explained by recent research on SNSs. Wu et al. (2015), for example, found
that profile pictures were believed by their users to reflect their personality and that
personality could be reflected in both photographs and avatars. According to their
findings, users believed that a variety of impressions could be made using their profile
pictures, such as: socialising, playing sport, romantic, family, etc. The distinction,
therefore, between photograph and avatar, as we have made in this paper, could be too
limiting and future researchers might wish to categorise images when examining the type of
profile images users with different personality choose to use to represent themselves.
Hypothesis five predicted that users who score high on conscientiousness will be more
likely to include a recent photograph of themselves. The null result for this hypothesis
might be explained in a similar way. In addition, given that those who score high on
conscientiousness were more likely to update their profile image, as we predicted, the
issue of using an updated photograph might not be as a concern. Moreover, these findings
suggests that other predictor variables, in addition to personality, should be considered
when examining how individuals characteristically select profile images and image choice
behaviour on SNSs. Previous studies on predictability of behaviour on SNS, for example,
have examined Narcissism, cultural differences and the true self (see Whitty & Young,
2017, for a more in-depth discussion). Our sixth and final hypothesis that individuals who
score low on openness to experience will choose an image that more closely represents
their self-concept, was not significant for Facebook or Twitter. In fact, none of the
personality traits predicted whether a participant felt their chosen image more closely
represented their self-concept. Perhaps other personality traits are more important to
consider when examining the likelihood of chosen an image that represents one's self-
concept (e.g., self-monitoring). As a further point, our findings were not always
consistent across SNSs. This is an important finding given that many previous studies have
focused on one SNS (typically Facebook), assuming findings can be generalised to other
SNSs. This study found that the same participants behaved somewhat differently across
sites, suggesting that the platform itself plays a fairly substantial role. For example,
individuals were far less likely to change their Twitter profile than their Facebook
profile image (suggesting these platforms serve a different function). While this finding
is perhaps not surprising, they do highlight the importance that future research into
detecting personality online ought to pay attention to platform itself and not just the
behaviours per se. Although our study examined more than one SNS, this narrow focus might
be perceived as a limitation and we would encourage future studies to focus on a wider
selection of SNSs. Our findings, at least, suggest that this is a worthwhile exercise.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

In conclusion, there is a growing interest in academia as well as in lay people's
practices to predict psychological characteristics of a person by examining their online
personal data. Our study suggests that our online behaviours can, perhaps unknowingly,
leak aspects about our personality. Our study provides some evidence that personality
predicts the types of profile photographs/images individuals select as well as the
likelihood of updating profile images. Future research might consider image choices in
more detail and across other types of sites.


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----------

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<ART>A qualitative study of research priorities among representatives of Canadian Provincial Sport Organizations
================================================================================

Authors: Nicholas L. Holt, Kurtis Pankow, Katherine A. Tamminen, Leisha Strachan, Dany J. MacDonald, Jessica Fraser-Thomas, Jean Côté, Martin Camiré
DOI: 10.1016/j.psychsport.2018.01.002
Year: 2018  |  Pages: 8-16
ASJC codes: 3202

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: The overall purpose of this study was to examine Canadian Provincial Sport Organization representatives' research priorities in order to provide directions for future research and knowledge translation initiatives in youth sport. Design: Qualitative description methodology. Method: Interviews were conducted with 60 representatives of Canadian PSOs from five provinces. Analysis followed the process of data condensation, data display, and drawing conclusions. Results: The most frequently reported research priorities were athlete development systems, participation and retention, parenting, benefits of sport, and coaching. Conclusions: Research that addresses the priorities of stakeholders may increase the adoption of research evidence in practice, program, and policy contexts. This study provides directions that may help inform future research agendas in youth sport. Conversely, the study also revealed that extensive previous research exists in several of the priority areas identified. These findings suggest that knowledge translation research is required in these areas. Knowledge tailoring may be a useful strategy for improving knowledge translation in these areas. Ultimately, it appears that efforts to increase connections between researchers and other stakeholders in youth sport are important.

--------------------------------------------------------------------------------


<hs>  Qualitative description</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Qualitative description methodology was used in this study, which is suited to obtaining
“answers to questions of special relevance to practitioners and policy makers”
(Sandelowski, 2000, p. 337). Consistent with a pragmatic philosophy, qualitative
description is a tradition of research that can be used to describe participants'
perceptions of phenomena and is suitable for problem identification (Neergaard, Olesen,
Andersen, & Sondergaard, 2009). Qualitative description focuses on providing ‘straight’
descriptions of events or perceptions with low inference interpretation (Sandelowski,
2000; 2010). Given the purpose of the current study, qualitative description was an
appropriate methodological selection because we wanted to depict participants' views about
their priorities for future research.

<hs>  Participant sampling and recruitment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In order to purposefully sample participants (Milne & Oberle, 2005; Sandelowski, 2000;
2010), we approached PSOs in five Canadian provinces via an e-mail explaining the purpose
of the study. We explained that we wanted to speak with a PSO representative who was
primarily responsible for youth sport policies and programming, emphasizing that the focus
of our project was to examine issues relating to research priorities and the use of
research evidence. We estimated, a priori, that approximately 10 participants per province
would enable us to attain adequate data saturation (with the exception of Ontario, which
is the province with the largest population, and as such we sought 20 participants from
two locations in Ontario). A total of 60 PSO representatives (39 male, 21 female, M age =
43.5 years, SD = 12.6 years) participated in this study. Twelve participants were from
Alberta, nine from Manitoba, 20 from Ontario, 10 from Québec, and nine from Prince Edward
Island. Twenty-one participants were executive directors, 12 were presidents/CEOs, and the
remainder were technical directors or held similar roles (e.g., youth program manager,
sport program manager). Six participants held a high school diploma, 44 held undergraduate
degrees, and 10 held graduate degrees as their highest level of education. They
represented a range of team and individual sports, including soccer, football, lacrosse,
volleyball, ice hockey, curling, athletics, tennis, gymnastics, and golf. They had, on
average, 8.8 years of experience working for the PSO (SD = 8.5 years, range 1–30 years).

<hs>  Interviews</hs>
  ~~~~~~~~~~

Consistent with qualitative description (e.g., Neergaard et al., 2009), individual semi-
structured interviews with open-ended questions were conducted. An interview guide was
developed following guidelines proposed by Rubin and Rubin (2012) and piloted via an
interview with a former executive from a PSO, which led to very minor modifications. The
interview guide commenced with a preamble explaining the study and some demographic
questions. The main questions included: What types of research would be most helpful for
you/your organization? What types of research would you like to see people at universities
doing? What types of studies in youth sport would be particularly useful for you/your
organization? What are the opportunities you see in using research? Participants were also
asked some questions about the use of research evidence, data from which were not used in
the current study. Finally, in a summary section, participants were asked: If you had
total control over research, what project would you like to see us complete? Trained
interviewers (n = 5) completed the interviews in each province. The interviewers attended
a three-day qualitative methods workshop conference that included sessions on principles
of qualitative interviewing and training specific to the current study. When the five
interviewers returned to their home provinces to undertake data collection, they remained
in regular contact with each other via e-mail to discuss and debrief after interviews.
Interviews in Québec were conducted in French. Other interviews were conducted in English.
Interviews lasted, on average, 45 min.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

A professional transcription company transcribed the audio files of the interviews
conducted in English. The researcher who conducted the interviews in Québec transcribed
those interviews in French and translated them into English. Participants were assigned a
number and any identifying information (e.g., names of sport, names of individuals) was
removed from the transcript. The principal investigator led data analysis with the
assistance of one of the interviewers. Data from one province (Alberta) were analyzed
first, and the process was repeated for data collected from each of the other provinces.
Analysis followed the process of data condensation, data display, and drawing conclusions
(Miles & Huberman, 1994; Miles, Huberman, & Saldaña, 2014). The first step, data
condensation, is the process of selecting and simplifying data contained in the
transcripts. This involved the principal investigator reading and re-reading transcripts
and coding meaningful segments of information (meaning units) and assigning labels
(codes). A ‘long list’ of codes was initially produced and rules of inclusion (i.e.,
descriptions of the meaning of the code and the data coded therein) were written for each
code. Then, pattern coding was completed, which is a process of grouping codes into a
smaller set of themes. The long list of codes was condensed into themes by comparing and
combining data that reflected similar ideas (e.g., codes reflecting different ideas around
the notion of athlete development were grouped into the theme of ‘athlete development
systems’). Data coded into each theme were checked and re-checked by the principal
investigator and one of the interviewers. The themes depict common patterns shared across
the ‘cases.’ Data displays are visually formatted representations that systematically
portray information and, according to Miles et al. (2014), “are a major avenue to robust
qualitative analysis” (p. 13). A content analysis summary table was created (Table 1)
depicting specific examples of research topics (i.e., the sub-themes) that were combined
to form each theme. A summed indices data matrix was also created to illustrate
participants' responses in each theme (Table 2). This matrix also provided an indication
of the extent to which participants’ perspectives were shared and facilitated descriptive
conclusion drawing about the patterns in the data (Miles et al., 2014). The numerical
reduction and display of data (i.e., Table 2) is an acceptable approach when using
qualitative description, but numerical summaries should be considered as a supplement to
the textual results of the content analysis (Neergaard et al., 2009; Sandelowski, 2010).
Hence, the final step involved creating a written description of themes.

<hs>  Methodological rigor</hs>
  ~~~~~~~~~~~~~~~~~~~~

Consistent with Neergaard et al.’s (2009) suggestions, our approach to methodological
rigor for this qualitative description study followed guidelines provided by Milne and
Oberle (2005), which focus on authenticity and credibility, along with criticality and
integrity. Authenticity and credibility require purposefully sampling an adequate number
of participants and conducting an analysis that is driven by their responses rather than
pre-determined ideas. It is about ensuring participants' ‘voices’ are reported with
relatively low inference (an emic perspective), probing for clarification and depth during
interviews, accurate transcription, inductive analysis, and demonstrating an understanding
of context. The extensive interviewer training also added to authenticity and credibility.
Criticality requires the critical analysis of research decisions, which were discussed
during regular meetings. Integrity involves reflecting on the role and influence of the
researchers, which was addressed via regular debriefing among the interviewers and the
principal investigator maintaining a journal of the research decisions. For instance, one
factor that involved extensive reflection was the principal investigator's previous work
in youth sport and the fact that he has conducted several studies on some of the topics
identified by participants. It was important his research not unduly influence the focus
on providing the participants' accounts of their priorities for future research (i.e., the
emic perspective).

<h>RESULTS AND DISCUSSION</h>
----------------------

Table 1 provides a summary of the analysis depicting specific examples of research topics
(i.e., the sub-themes) that were condensed to form each theme. These sub-themes are
identified in italics in the following sections, where we describe the main themes
reported by the majority of participants and discuss the pertinent findings in relation to
previous research. Table 2 depicts the prevalence of all the themes identified across the
cases.

<hs>  Athlete development systems</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

A total of 49 of 60 participants (81.7%) reported preferences for more research examining
issues related to the athlete development systems for their sport. Examples coded in this
theme referred to a desire to understand more about the effectiveness of the long-term
athlete development (LTAD) models. Some participants specifically questioned the research
evidence-base for the Canadian LTAD model. For example, Alberta PSO#7 (AB_PSO7) argued
that “we have our LTAD models but I think a lot of it isn't really based on research, it's
based on experience, people that are [sport] experts, but based more on their experience.
I think we need more research.” Similarly, Ontario PSO (site A) #5 (ON_A_PSO5) said: OK,
I'm not a big fan of LTADs. I don't believe that there is any documented evidence for a
lot of what we say in LTADs … Where [is there evidence] that says that you're actually
gonna create an Olympian or longevity [of participation]? … I don't know if there are any
[research] groups that their sole purpose is to look at LTAD and evaluate it. I don't know
if Sport Canada has a team that works with LTAD and evaluates it … Other participants,
while generally having a favorable view of LTAD, also highlighted the need to evaluate its
effectiveness. As ON_A_PSO2 said, “I think it's maybe a little too early to know whether
or not it's successful but I guess it's good to have a good model that everybody can
integrate with.” Manitoba PSO#4 (MB_PSO4) highlighted a need for studies examining the
long-term impact of LTAD on athletes and coaches, explaining: It's been 10 or 12 years
since LTAD became a buzzword and it would be interesting to see if that program in and of
itself is having any impact on athlete and coach development … I think looking at the
impact of LTAD from a longitudinal perspective would be useful. And I think it would be
interesting to see if the changes to programs have yielded the results that we anticipated
or if it's just an approach that doesn't really result in changes in the long term. There
is, of course, a large body of research on the psychological, social, and physiological
aspects of talent development in sport (see Gledhill, Harwood, & Forsdyke, 2017; Rees et
al., 2016 for reviews) and, to a lesser extent, talent development environments (see
Henrikson, Stambulova, & Roessler, 2010; Martindale et al., 2005 for reviews). However, it
is possible that much of this research may not directly address the needs of the
participants in the current study because they specifically expressed a desire for
research examining LTAD models (which are not based on this body of talent development
research). Studies of LTAD are scarce and, of the few published studies, there has been a
focus on coaches’ perceptions of LTAD (e.g., Black & Holt, 2009; Chevrier, Roy, Turcotte,
Culver, & Cybulski, 2016) and their views of its adoption and implementation (Beaudoin,
Callary, & Trudeau, 2015). Ford et al. (2011) suggested that LTAD models are fundamentally
based on physiological principles. However, in reviewing some principles associated with
LTAD, specifically in terms of physical literacy, aerobic performance, and anaerobic
performance (speed, strength, power), they concluded “there is little evidence to support
the LTAD claims” (p. 398). Ford and colleagues further suggested that coaches should be
better educated about how to interpret the recommendations of the model. The participants
in the current study appeared to appreciate some of the limitations of the LTAD model, and
their comments reinforce the need for more empirical examination of the foundational
principles contained with LTAD models. It may be that sport organizations themselves could
conduct (or commission) LTAD research. In fact, we did find some examples of sport
organizations conducting their own evaluations of LTAD (in the absence of partnerships
with university researchers). ON_A_PSO9 explained: What's happening right now is our NSO
is rolling out an LTAD program. A year ago, they were rolling out a pilot for the LTAD
program and they invited clubs across the country to volunteer to be part of the pilot
program. So in terms of evaluation and ongoing assessment, they definitely are trying to
do it in a very deliberate manner and make sure they're collecting all that information.
We suspect that perhaps it is neither the sole responsibility of a PSO or NSO, nor that of
research teams, to evaluate LTAD models. Rather, partnerships between sport organizations
and researchers would seem to be a fruitful avenue for examining the effectiveness of LTAD
models.

<hs>  Participation and retention</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

A total of 42 participants (70%) reported preferences for research examining athlete
participation and retention. There was a need for research to track athlete participation
rates. A participant from Prince Edward Island, PSO#3 (PEI_PSO3) highlighted some of the
challenges in this respect: I don't think we have a very good handle on participation
rates in this province. We have self-reporting from our member sport organizations but
you've got overlap with that because there's kids that play multiple sports that you're
duplicating the count … From our perspective, I would love a robust way of truly tackling
our participation rates. In a similar vein, participants highlighted a need for research
tracking athlete retention rates. AB_PSO6 said: I don't think we've done a lot on
retention on any sport. No one can really tell you what their retention rates are … why
are they quitting? Stuff like that would be beneficial, if you knew your population. You
[can] just do it by postal code, you know if you're hitting those guys or not … No one can
really tell you what their retention rates are. Some sport participation tracking data are
available. For example, one national survey in Canada showed that 51% of children aged
5–14 years (approximately 2 million children) regularly took part in sport in the previous
12 months in 2005, compared to 57% of children in 1992 (Clark, 2008). Another Canadian
survey showed that an estimated 77% of 5–19 year olds participated in organized sport or
physical activity programs, and participation rates were relatively stable compared to the
previous eight years in which this survey had been conducted (CANPLAY, 2015). A recent
Australian survey showed that the participation of Australian children aged 5–14 years
remained relatively stable at 64% participation in 2000 to 62% participation 2012 (Vella
et al., 2016). However, as Both, Rowlands, and Dollman (2015) observed, sport
participation research is littered with methodological issues such as differences in
questionnaire design, sample age, study period, and definition of participation that make
it difficult to compare participation trends over time. Nonetheless, the key issue for
participants in the current study was not sport participation trends at a national level,
but rather participation trends in their own sport and/or province. Presumably this issue
could be addressed by building tracking mechanisms into their registration systems (e.g.,
assigning participants an identification number which is used each time they register for
a program). In fact, while it would present a logistical challenge, all children in a
province could be assigned a ‘sport identification number’ that would produce data
regarding their movement between different sports, which would eliminate “duplicating the
count” as PEI_PSO3 put it. As the quote from AB_PSO6 (above) alluded to, participants also
highlighted the need to understand more about participation and retention of individuals
from specific demographic sections of the population. For instance, ON_B_PSO8 said: Yeah,
I think dwindling participation. I would say to try to figure out why. I think most sports
are experiencing a bit of atrophy. I would say you wanna figure out what motivates each
age and stage of the general population to participate in sport so that I would have more
appropriate information to know how to target certain demographics. So I would say that
would be very useful, something that our general membership could learn from, and we could
learn how to adapt and innovate as a sport to remain viable. Functionally, sport
participation requires two intertwined types of resources: opportunities to engage in
sport and motivation to engage in those opportunities (Balish, McLaren, Rainham, &
Blanchard, 2014). However, individuals from various demographic groups face numerous
barriers that restrict their opportunities to engage in sport. For instance, in countries
that use a ‘pay-to-play’ privatized model of youth sport, financial costs are a barrier to
participation among children from low-income families (e.g., Holt, Kingsley, Tink, &
Scherer, 2011). Further reflecting the idea of targeting particular groups, MB_PSO8
commented on two primary (related) issues: First of all, I think because the majority of
our high performing athletes in Manitoba are male. And I think the second reason is
because I think girls are up to six times more likely to drop out of sport than are boys
in Canada. I think that there's a lot of reasons for it, but definitely some psychological
issues that are attached to that, or some social stigmas that are attached to being a
female athlete. And so it would be nice to see what we could do to combat that. Girls are
generally less likely than boys to participate in sport (Clark, 2008). Reasons associated
with reduced participation and dropout among girls are multifaceted. For example, Eime et
al. (2015) showed that intrapersonal barriers (lack of time, lack of energy, and perceived
competence), interpersonal factors (family and friend/peer support), and
environmental/organizational (access, opportunity and resources) were associated with
reduced physical activity and sport participation among adolescent girls. Such evidence
notwithstanding, researchers have recently acknowledged that evidence gaps in this area
still include a lack of participation information (e.g., with regards to dropouts and
commencers of sport participation), lack of surveillance data, and measurement differences
(Vella et al., 2016). Our participants, as well as recent commentaries by researchers,
suggest a need for on-going research to track sport participation and retention in
specific sports and across population subgroups.

<hs>  Parenting</hs>
  ~~~~~~~~~

In total, 42 participants (70%) reported preferences for research examining various
aspects of parental involvement in sport. Some participants expressed concerns about
parents exerting too much pressure on their children to achieve and parents interfering
with coaching. ON_B_PSO9 said, “You know every parent would like the best for themselves
and they're too eager to interfere, and parents' interference [is] one of the biggest
challenges.” Furthermore ON_B_PSO10 said: I don't know what the hell we do with parents.
If we could find a way, something to get into the psyche of the parents, I mean we
mandated Respect in Sport [an online parent and coach education module] because we just
don't wanna have poor parent behavior … The parents are a huge problem … I think if we
could resolve the parental problems, and that's the biggest problem with our club teams,
that's the biggest complaint I get from them, is the parents are killing my coaches. They
coach for a year, they quit. There is an extensive body of research examining parenting in
youth sport (see Holt & Knight, 2014; Knight, Berrow, & Harwood, 2017 for recent reviews).
Indeed, researchers have examined the effects of parental pressure on young athletes for
many years (e.g., Brustad, 1988; Leff & Hoyle, 1995). It appears that much of the research
on parental pressure had not reached the participants in the current study, which suggests
a knowledge translation issue. Participants focused on ways to enhance parent education to
address concerns about parents. ON_A_PSO4 highlighted that: The parents are key … That to
me would be very useful information because then that could be something that we could
then turn around and give to the clubs in order to inform the parents that some of the
things they're doing are not beneficial. Québec PSO#4 (QC_PSO4) said that “Educating the
parents is a big challenge … What is the right attitude to have with your child for them
to be happy? For them not to feel overwhelmed? For them to have a good self-esteem?”
Similarly, PEI_PSO5 said: On the parenting side, helping to educate parents on how they
can help their children, not only after a game or before a game, that kind of stuff, but
even that they can be reaching out to professionals to help make them better in their
sport …. I would love more research or guidance on how to deal with parents. Participants
also expressed concerns about parent-coach relationships. QC_PSO 7 said: Yes. That's it.
Sometimes it can happen. It's very, very close. If I give a lesson, of course, if the
parent is behind me, he/she will hear everything that is going on during the lesson.
Sometimes it can be good, but sometimes they can misunderstand things. [ Research] might
be something about knowing how to deal with parents like that. There are only a small
number of studies examining parent education approaches (e.g., Dorsch, King, Dunn, Osai, &
Tulane, 2017; Thrower, Harwood, & Spray, 2017) and parent-coach relationships (e.g.,
Barber, Sukhi, & White, 1999). Hence, while there may be a research to practice gap in
terms of research on the effects of parental pressure in sport, our findings also
highlight important future directions for research examining parent education and parent-
coach relationships. Such research would likely be highly relevant to sport organizations.

<hs>  Benefits of the sport</hs>
  ~~~~~~~~~~~~~~~~~~~~~

A total of 39 participants (65%) reported preferences for research that could demonstrate
the personal and social benefits of the sport. By and large, participants wanted to know
more about the specific benefits of participating in their sport, often in comparison to
other sports. For example, PEI_PSO6 said there should be more research on: The social
benefits of [name of sport]. It is kind of a unique sport in the fact that it’s a team
sport with an individual [performance focus] in a team context. It's not like [ice] hockey
where in order to win, the team moves the puck and passes. Like in [name of sport] you
have to do one skill by yourself. ON_B_PSO6 highlighted the need for more research into
and promotion of “the benefits of team sports off the court or off the ice or whatever it
happens to be.” Similarly, AB_PSO4 said: … it would be neat from our perspective to have
someone dig a little deeper into the specifics of the game and what it offers and why to
choose [our sport]. So what's different about [our sport]? And what are the benefits? …
What are the benefits of the intangible part that will hopefully enable you to be
successful in a career or business or understanding team dynamics? Although researchers
have questioned the assumption that sport participation leads to positive developmental
outcomes (e.g., Coalter, 2013), and some research has revealed sport participation has
been associated with negative outcomes (e.g., increased substance use; Veliz, Schulenberg,
Kloska, McCabe, & Zarrett, 2015), there is a growing body of evidence depicting the
reported benefits of sport participation (see Eime, Young, Harvey, Charity, & Payne, 2013;
Holt et al., 2017 for reviews). For example, studies have revealed that compared to non-
participants, youth sport participants score better on markers of physical health outcomes
(Pate, Trost, Levin, & Dowda, 2000), educational attainment (Fredricks & Eccles, 2006),
and – when sport participation is combined with participation in other youth development
activities – positive psychological functioning (e.g., Zarrett et al., 2009). Research in
the area of positive youth development (PYD) suggests that developmental benefits are not
gained merely by participating in sport; rather, they appear to be largely dependent on
social interactions that occur within sport settings (e.g., empathetic relationships with
adult coaches and leaders, positive interactions with peers, and the supportive
involvement of parents; Holt et al., 2017). Comparing the participants' desire for more
research on the benefits of their sport with existing literature in this area, a plausible
implication is that research efforts could focus on examining the contextual conditions
that exist within the programs offered by particular sports and the extent to which they
may contribute to, or detract from, participants' acquisition of positive developmental
outcomes. Put differently, it is not a question of whether participation in a particular
sport leads to positive outcomes, but rather a question of what contextual conditions
exist with these sports that contribute to or detract from participants’ acquisition of
positive outcomes. There may be some unique traditions and characteristics in some sports
(e.g., certain martial arts; Chinkov & Holt, 2016) that contribute to participants
obtaining benefits, and evidence from a systematic review showed that team sport
participation was associated with improved mental health outcomes compared to individual
activities, which the authors attributed to the social nature of team sport participation
(Eime et al., 2013). Evans et al. (2016) suggested that sport types (e.g., amount of
interdependence among teammates, physical contact), sport settings (e.g., community
leagues, levels of competitiveness) and individual patterns of sport involvement (e.g.,
amount of organized sport, specialization or sampling pathways) may shape the psychosocial
experiences of young athletes in different ways. Furthermore, outcomes may vary depending
on the type of participation in said sport (e.g., at lower versus higher levels of
competition) or the dimensions of involvement in terms of breadth, intensity, duration and
engagement at different ages (Bohnert, Fredricks, & Randall, 2010; Côté & Hancock, 2016).
Whereas it may be an oversimplification to merely study the benefits of a particular
sport, more sophisticated studies that involve examining the effects of context and type
of participation appear to be important future research directions that would also be
relevant to the participants in the current study.

<hs>  Coaching</hs>
  ~~~~~~~~

A total of 39 participants (65%) reported preferences for research on coaching. Some PSOs
wanted to know more about the effects of particular coaching approaches. MB_PSO2 said: It
would be fascinating to see the direct impact of coaching. I know we see it first-hand in
results, you know Olympic medals. But we'd like to have it at the youth levels. What kind
of impact coaching has at a youth level? … Is there a correlation between a coach being
really ethical and is his team being the same? Is there a correlation between really
practicing good skills at an early age and those athletes continuing on? This finding was
somewhat surprising, given that PSOs are responsible for providing coach education
training schemes (which, presumably, are informed by research to some degree).
Furthermore, there is an extensive body of research on coach education and coaching
practices spanning several decades. Over 25 years ago Smith and Smoll's research showed,
for example, that children with low self-esteem responded more positively to coaches who
were reinforcing and encouraging and provided technical instruction, while they responded
more negatively to coaches who were low on these dimensions (Smith & Smoll, 1990). More
recently, research suggests that transformational leadership behaviors among coaches can
have positive effects on participant outcomes by helping them to think more positively
about themselves and their tasks, enhancing the quality of their relationships by creating
environments that are fair, respectful, and supportive (Turnnidge & Côté, 2017). Thus, it
appears that research on coaching effectiveness has not adequately reached the sport
organization representatives sampled in the current study. This finding suggests a
knowledge translation issue. The need for research examining on-going coach education was
also highlighted. For instance, ON_A_PSO8 told us “[athletes] say they need better
coaching, then obviously what kind of research can we do that would make sure that they're
getting better coaching?” Similarly, AB_PSO12 said: Coaching in general. Any research on
that would definitely be beneficial, how our coaches can become better coaches, what to
stay away from, what to kinda strive to go towards type of thing would be all good stuff
…. We're like a sponge we want to soak as much as we can in some of these areas and apply
it to [name of sport] if possible. Here, the issue seems to reflect the continuing
professional development of coaches (in the participants' words, are coaches getting
“better”?). Griffiths, Armour, and Cushion (2016) claimed that there is a lack of
“conclusive evidence” about the effectiveness of different types of coach education on
coach learning and changes to practice, meaning that little is known about “what works”
(p. 1). More specifically, researchers have tended to focus on specific learning
activities and individuals, rather than institutional or organizational factors that
mediate learning. In their evaluation of a sport organization's youth coach education
program in the UK, Griffiths et al. (2016) found that a clear understanding of the
‘transmission model’ for education was missing and the different ‘communities’ that could
support learning were not connected within the organization. From the perspectives of
participants in the current study, it would appear that important future research
directions could involve examining sport-specific coach education and development programs
and their impact on both coaches and young athletes. Other participants talked about coach
retention. MB_PSO7 suggested it would be important to learn more about: What motivates
people to become coaches because becoming a coach, there's not a lot of money in it but it
takes a lot of time and energy, so it's challenging to keep volunteer coaches involved. So
what motivates people to become coaches and continue in sport coaching volunteer role? The
retention of volunteer coaches is a critical issue for youth sport delivery systems in
many countries. In a focus group study, Rundle-Thiele and Auld (2009) found enjoyment,
success, and support from parents, clubs, and the league were key factors that contributed
to Australian youth coaches’ decisions to stay involved as a volunteer coach. Results from
a survey conducted in the United States showed that 94% of youth sport coaches from a
municipal parks and recreation soccer program were motivated to stay involved because they
wanted to instill positive values in children through their coaching (Busser & Carruthers,
2010). However, there does not appear to be extensive evidence on factors that influence
coach retention over time, and this could represent a valuable area for future research.
Finally, several participants highlighted the need for more research with parent-coaches.
ON_A_PSO4 shared the following specific example: We have one parent in particular who's
now star of the club and his son is one of the best [athletes] in Canada, but the kid has
no break because his dad is coaching him. And his dad was not an athlete. So you've got
that kid who's under so much stress 24-h and I think that they're practicing 15–18 hours a
week. That's a lot of time. That's a lot of their free time. The rest of the time they
should be home being a kid. It is noteworthy that there is very little previous research
on parents as coaches (e.g., Weiss & Fretwell, 2013), despite the fact that parents often
appear to fulfill a coaching role on their children's youth sport teams (Holt & Knight,
2014). The participants' priority for future research examining parent-coaches may
represent an important area for future research that would be beneficial to Canadian PSOs
and other sport systems that rely on parent-coaches.

<h>GENERAL DISCUSSION</h>
------------------

The overall purpose of this study was to examine Canadian PSO representatives’ research
priorities in order to provide directions for future research and knowledge translation
initiatives in youth sport. The most frequently identified areas were athlete development
systems, participation and retention, parenting, benefits of sport, and coaching. There
was an underpinning preference for sport-specific research in several of these areas. We
then compared findings to the existing youth sport literature, revealing future research
directions that may be valuable for stakeholders in youth sport. Conversely, the results
also revealed some of the reported priorities have already received extensive attention in
the youth sport literature, which is instructive information for future knowledge
translation initiatives. A promising feature of this study is that there does appear to be
some enthusiasm and appreciation for the adoption of research evidence among the 60 PSO
representatives sampled. These participants were able to articulate a wide range of
research topics that would assist their work in youth sport. Hence, it appears that
collaborative approaches that include involving stakeholders in the generation of research
agendas are fruitful endeavors for pursue in the future, which may reduce ‘waste’
(Chalmers et al., 2014) and increase the adoption of research evidence in practice,
program, and policy contexts (Innvaer et al., 2002; Straus et al., 2013). Returning to the
KTA model (Graham et al., 2006) that guides our larger project, the current study was
located at the start of the action cycle and focused on identifying problems and searching
for existing relevant research knowledge. Similarly, the small body of previous knowledge
translation research in sport can be located in the ‘early stages’ of knowledge
translation models, given that the focus has been on identifying barriers to the use of
evidence (a type of problem identification itself). Though the evidence base is small, a
‘picture’ is beginning to emerge; people who work in the sport sector (e.g., coaches,
sport organization representatives) face numerous barriers that restrict their ability to
access and use research evidence (Holt et al., 2018; Pain & Harwood, 2004; Reade et al.,
2008b, 2008a; Williams & Kendall, 2007). Researchers themselves may face barriers to
engaging in knowledge translation research. Traditional academic graduate training models
may not adequately prepare researchers for effective knowledge translation (Gould, 2016;
Greenwood & Abbott, 2001). Fully embracing knowledge translation in youth sport may
require major training initiatives. Engaging stakeholders in the development of research
agendas will be an important starting point. Other important steps include considering
what knowledge should be disseminated, to whom, by whom, how, and with what effects?
(Lavis, Robertson, Woodside, McLeod, & Abelson, 2003). By integrating such dissemination
topics into graduate training and emphasizing the need to collaborate with stakeholders in
all stages of the research process (especially in the generation of ideas), important
steps toward creating a generation of researchers dedicated to enhancing the use of
research evidence in youth sport will be made. These suggestions for future research and
training notwithstanding, we also wish to critically reflect on the very premise of using
research evidence to inform decisions in youth sport. To draw an illuminating historical
comparison, evidence-based medicine (EBM) became a paradigm for medical practice in the
early 1990s (Montori & Guyatt, 2008). EBM emphasizes the examination of evidence from
clinical research, requiring physicians to have skills in formulating questions, searching
and retrieving the best available evidence, and critically appraising studies to establish
the validity of results (Evidence-Based Medicine Working Group, 1992). Yet, whatever the
evidence, value and preference judgments are implicit in every clinical decision, not only
in relation to patients' preferences but also physicians’ evaluations of the relative
benefits/harms or costs of treatment (Guyatt et al., 2008). Enduring concerns in the
adoption of EBM in medical and allied health professions have included excessive reliance
on easily obtained but potentially misleading evidence and the increase in commercial
interests to produce and interpret evidence for physicians (Als-Nielsen, Chen, Gluud, &
Kjaergard, 2003; Montori & Guyatt, 2008). Some of these challenges may also apply to
sport. For example, commercial entities often make unsubstantiated claims about the
performance benefits of their products or services, a recent example being the use of
genetic testing for talent identification (Vlahovich, Fricker, Brown, & Hughes, 2016).
More recently, the notion of practice-based evidence has been introduced in the health
care field as it begins to advance beyond the EBM paradigm. As Green (2008) remarked, “if
we want more evidence-based practice, we need more practice-based evidence” (p. 23).
Practice-based evidence acknowledges that efficacy or effectiveness research is just one
of several sources of information needed to improve health care, and that understandings
of the challenges faced by people who both receive and deliver interventions are needed
(Green, 2008). Ammerman, Woods Smith, and Calancie (2014) suggested community-based
participatory research approaches, whereby research and interventions are informed by the
views of different stakeholders, as a useful strategy for developing practice-based
evidence. Furthermore, they argued that systems-based models that consider dynamic,
complex, and multilevel factors and include the views of multiple stakeholders hold great
promise for generating practice-based evidence. Working collaboratively to set research
agendas with appropriate stakeholders in youth sport may provide a useful way forward for
bridging research to practice gaps, and there are some examples from public health that
could provide models for future endeavors in this regard (e.g., Lenaway et al., 2006).
Another useful concept to consider is evidence-based policy. Essentially, evidence-based
policy is an extension of evidence-based practice, suggesting that if practitioners are
expected to base their work on evidence then the same expectations should be placed on
policy-makers (Ham, Hunter, & Robinson, 1995). Evidence-based policy is sometimes viewed
as a linear process, whereby a problem is defined and then research evidence is amassed to
provide policy options (Black, 2001). However, this linear process, whereby evidence leads
to the development of policy, may be problematic. Policy change is not simply made based
on the availability of evidence; it may depend on an appraisal of what is scientifically
plausible, what is politically acceptable or achievable, and what is practical at a given
point in time (Nutbeam & Milat, 2017). Indeed, representatives of sport organizations have
expressed a preference for using research that supports the programs they are already
planning, rather than using evidence as a starting point to inform new programs (Holt et
al., 2018). One concept underlying several of the themes (most notably athlete development
systems, participation and retention, and benefits of the sport) was a preference for
sport-specific research. In this respect, the health care literature can again provide
some guidance for future knowledge translation research in youth sport. Within the KTA
framework (Graham et al., 2006) knowledge tailoring is a critical issue for youth sport
researchers to consider, because ‘generic’ knowledge that is not specifically
contextualized is “seldom directly taken off the shelf and applied without some sort of
vetting or tailoring to the context” (Graham et al., 2006, p. 20). That is, the
implications of relevant research, even when it is accessible, must be adapted to local
contexts (e.g., sport systems). Our results regarding the preference for sport-specific
research highlight the need to tailor ‘generic’ knowledge to local contexts (cf. Straus et
al., 2013). From here, from a knowledge translation perspective, future projects that
involve adapting implications to local contexts will provide opportunities for primary
studies that monitor knowledge use, evaluate the outcomes of using knowledge, and examine
sustained ongoing knowledge use (Graham et al., 2006). A key strength of this study was
the sample, specifically that we were able to recruit 60 people from five provinces. This
facilitated a high degree of data saturation. The thorough approach to training the
interviewers was another strength. Nonetheless, several limitations of this study must be
considered. Qualitative description, while an appropriate methodological selection for
this study, is perhaps one of the most simplistic forms of qualitative research (Neergaard
et al., 2009). Another limitation is that sport organizations are merely one type of
stakeholder in the world of sport. There is a need for further research with other
stakeholders (e.g., coaches, athletes, parents). Additionally, in considering the
implications of this study, the extent to which the findings would apply to youth sport in
other jurisdictions is unknown. However, it is quite likely the findings go beyond the
Canadian context. For example, the most frequently reported theme, LTAD, is not only a
fundamental feature of the Canadian sporting landscape; iterations of LTAD are used in
numerous countries (including, but not limited to, the United Kingdom, Ireland, South
Africa, and New Zealand) and, of course, other countries have some form of athlete
development models in place. Thus, some of the current findings may well apply beyond the
Canadian context. In addition to highlighting a need for more LTAD research, other
implications for generating future research arising from this study include finding ways
to track athlete participation and retention, working with sport organizations to develop
parent education initiatives, understanding the contextual conditions and participation
factors that may contribute to or detract from the acquisition of positive developmental
outcomes in particular sports, examining the effects of on-going coach development, and
studies of coach retention and parents as coaches. By identifying these topics our study
may help inform the development of future programs of study that would be highly relevant
to sport organizations. Implications for knowledge translation include the need to develop
programs of research dedicated to knowledge translation, which involve engaging
stakeholders from the beginning rather than merely developing dissemination strategies.
Studies that examine the complexities surrounding the implementation and adoption of
research evidence, and the evaluation of knowledge translation initiatives, are important
next steps. Finally, our findings suggest that knowledge tailoring strategies (Graham et
al., 2006) will be important in the future in order to contextualize the implications of
‘generic’ knowledge for particular sport organizations. We hope that the views of the
participants in this study may help inform future research agendas, increase the
applicability of findings, and ultimately their translation into the policies, programs,
and practices of youth sport.


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<ART>Accounting for the phenomenology and varieties of auditory verbal hallucination within a predictive processing framework
================================================================================

Authors: Sam Wilkinson
DOI: 10.1016/j.concog.2014.09.002
Year: 2014  |  Pages: 142-155
ASJC codes: 3204, 3205
Keywords: Auditory-verbal hallucination, Predictive processing, Psychosis, Schizophrenia

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Two challenges that face popular self-monitoring theories (SMTs) of auditory verbal hallucination (AVH) are that they cannot account for the auditory phenomenology of AVHs and that they cannot account for their variety. In this paper I show that both challenges can be met by adopting a predictive processing framework (PPF), and by viewing AVHs as arising from abnormalities in predictive processing. I show how, within the PPF, both the auditory phenomenology of AVHs, and three subtypes of AVH, can be accounted for.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The positive symptoms of schizophrenia include delusions of control (“somebody else is
controlling my actions”), thought insertion (“somebody is putting their thoughts into my
head”) and auditory verbal hallucination (AVH) (hearing voices in the absence of a
speaker). Perhaps the most popular theories for understanding these disparate symptoms are
self-monitoring theories, which attempt to explain them as the product of one abnormality,
namely, a problem with self-monitoring. According to these theories, our nervous systems
distinguish self-generated from externally generated stimuli, through a process of self-
monitoring. When this monitoring goes awry, self-generated stimuli are erroneously
attributed to an external cause. The various positive symptoms all involve faulty
monitoring and simply differ insofar as that which is failing to be properly monitored
differs. In delusions of control it is bodily action, whereas in AVH and thought insertion
it is widely thought to be inner speech (Feinberg, 1978; Frith, 1992; Jones & Fernyhough,
2007; Seal, Aleman, & McGuire, 2004). Although ingenious, the breadth of application of
SMTs has recently been questioned by several theorists (Gallagher, 2004; Jones, 2010;
Stephens & Graham, 2000; Wu, 2012). Such criticisms tend not to take issue with the
application of SMTs to symptoms involving bodily action, like delusions of control and
(their merely experiential analogue) illusions of passivity. Rather, they claim that SMTs
struggle to account for AVH and thought insertion. In this paper, I will focus on AVH, and
on two challenges in particular. They are: The Auditory Phenomenology Challenge – How do
you explain the auditory phenomenology of AVH if it is misattributed inner speech? The
Varieties of AVH Challenge – How do you account for the varieties of AVH if it is (always)
misattributed inner speech? In this paper, I suggest that both challenges can be met if we
adopt a recently popular general framework for thinking about what the brain does (e.g.
Clark, 2013; Friston, 2005, 2010; Hohwy, 2013) which we could call the predictive
processing framework (PPF). It is worth mentioning that the application of predictive
processing to psychosis is not new. Indeed, Chris Frith, perhaps the best-known proponent
of SMTs, has suggested something along these lines in Fletcher and Frith (2009). Since
then, Adams, Shipp, and Friston (2013) have also suggested accounts of psychosis within
the PPF. This work, however, does not focus on AVHs to the extent that I do, nor does it
focus on the two challenges that I address here. I proceed as follows. I start by
presenting SMTs and show why they have been found attractive and plausible. I present the
two challenges facing the application of SMTs to AVHs. I then introduce, motivate and
clarify the PPF. I then present evidence suggesting that predictive processing might be
disrupted in psychosis. Finally, I end by applying the PPF to voice-hearing, and show how
it can, first, address the auditory phenomenology challenge, and second, nicely account
for the three subtypes of AVH I present.

<h>SELF-MONITORING THEORIES</h>
------------------------

In this section I characterise SMTs, and describe the evidence that has been used to
support them.

<hs>  Introducing self-monitoring theories (SMTs)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Perhaps the first theorist to make use of self-monitoring was Helmholtz (1866). His
concern, however, was not with psychopathology, but with the following problem presented
by healthy visual cognition. When an image moves across the retina, how does our brain
know whether it is the world moving across our eyes or our eyes moving across the world?
Helmholtz suggested that our brain can tell the difference because when our eyes move
there is a motor command. More specifically, information about the motor command, which
Sperry (1950) later dubbed the “corollary discharge”, is used by the brain to predict the
sensory consequences that would be produced by the eye movement. If the predicted and
actual sensory consequences match then the brain infers that the change was self-generated
and the conscious percept is adjusted accordingly. We can see exactly what happens when
there is no such motor command, and hence no such adjustment, when we press on our eye
with our finger. When we do this, the world itself seems to tilt and shake. It took more
than a hundred years for Helmholtz’s ideas to be applied to psychosis (Feinberg, 1978).
Although Feinberg’s initial paper was on thought (which he took to involve ‘motor
mechanisms’) and thought insertion, the easiest symptoms for which to introduce the
account are delusions of control, since it is clear that, if anything involves motor
commands, bodily actions do.1 In delusions of control, a subject may perform actions that
are in keeping with her plans and intentions (for example, she might brush her hair), but
she claims that somebody else is controlling her. Frith and Done (1989) took this to be a
problem with self-monitoring. In particular, there is a mismatch between the predicted and
actual sensory consequences of the bodily movement and so (as with Helmholtz’s ocular
example) the movement is attributed to an external source. This, in principle, could be a
problem with the generation of the prediction itself (e.g. the corollary discharge) or
with the mechanism that compares expected and actual sensory (including proprioceptive)
input, what became known as “the comparator”. Later manifestations of the self-monitoring
theory (Frith, Blakemore, & Wolpert, 2000) saw comparator-based self-monitoring as the
human body’s way of meeting a computational challenge, in particular, involving skilled
reaching and online correction (see Wolpert, 1997 for a review of these computational
approaches to motor control). This connection, in the late nineties, between the
computational neuroscience of healthy cognition and the neuropsychology of schizophrenia
undoubtedly contributed to the credibility of SMTs.

<hs>  Support for SMTs</hs>
  ~~~~~~~~~~~~~~~~

Whereas in Helmholtz’s example, the recognition by the nervous system that a certain
stimulus is self-produced causes a correction of the conscious percept, in more typical
bodily motor control, it results in sensory attenuation. The evolutionary benefit of this
is clear enough: your nervous system needs to pay attention to stimuli that come from the
outside, not the endogenous stimuli that (in a well-functioning system) will be harmless
and irrelevant. Various data suggest that something goes wrong with this monitoring and
subsequent attenuation (Blakemore, Smith, Steel, Johnstone & Frith, 2000). The most
striking such datum is the reported finding that subjects with diagnoses of schizophrenia
can tickle themselves. The postulated explanation for this is that there is a mismatch
between expected and actual sensory consequences and the sensory consequences are not
attenuated: the tickling sensation is like being tickled by somebody else. Typical
subjects can’t tickle themselves because their nervous systems accurately monitor, and
successfully attenuate, the sensory consequences of the tickling movements (Blakemore,
Wolpert & Frith, 1999). It is not only with bodily action that support has been shown for
the claim that self-monitoring goes awry in schizophrenia. Studies showed that patients
with diagnoses of schizophrenia are more likely to misattribute their own voices than
healthy controls (Cahill, 1996; Johns et al., 2001). For example, Johns et al. (2001) got
subjects to read words aloud and played them feedback of their voices with mild acoustic
distortions. The subjects with diagnoses of schizophrenia were considerably more likely
than healthy controls to claim that the voice they heard was someone else’s. Indeed,
support that this was directly related to the production of hallucinations was supported
by the result that, within the “schizophrenia” group, those who experienced hallucinations
were more likely to misattribute their voice than those who did not hear voices.

<hs>  Applying SMTs to AVH</hs>
  ~~~~~~~~~~~~~~~~~~~~

Several theorists (Feinberg, 1978; Frith, 1992; Jones & Fernyhough, 2007; Seal et al.,
2004) have attempted to explain AVHs in terms of inner speech misattribution, based on
self-monitoring abnormalities. Although from a pre-theoretical standpoint it is not
obvious that inner speech involves motoric elements, this has been empirically supported
by several electromyographical (EMG) studies (which measured muscular activity during
inner speech) some of which date as far back as the early 30s (e.g. Jacobsen, 1931). Later
experiments made the connection between inner speech and AVH, showing that similar
muscular activation is involved in healthy inner speech and AVH (Gould, 1948; McGuigan,
1966). The involvement of motoric elements in both inner speech and in AVH is further
supported by findings from Gould (1950), who showed that when his subjects hallucinated,
subvocalisations occurred which could be picked up with a throat microphone. That these
subvocalisations were causally responsible for the inner speech allegedly implicated in
AVHs, and not just echoing it (as has been hypothesised to happen in some cases of verbal
comprehension (cf. e.g. Watkins, Strafella, & Paus, 2003)), was suggested by Bick and
Kinsbourne (1987), who demonstrated that if people experiencing hallucinations opened
their mouths wide, stopping vocalisations, then the majority of AVHs stopped. To recap,
SMTs have been presented as a unifying model for understanding the positive symptoms of
schizophrenia. The idea is that there is one deficit concerning the monitoring of self-
produced stimuli, and the symptoms differ because there are different kinds of self-
produced stimuli. In delusions of control it is physical action, whereas in AVH and
thought insertion it is inner speech.

<h>TWO CHALLENGES FACING THE APPLICATION OF SMTS TO AVH</h>
----------------------------------------------------

As mentioned, criticisms of SMTs tend not to take issue with the role of self-monitoring
deficits in delusions of control, but rather concern the aforementioned extension of self-
monitoring to symptoms that don’t involve bodily action, namely, AVH and thought
insertion. In this paper, I specifically focus on two challenges facing the application of
SMTs to AVHs.

<hs>  The Auditory Phenomenology Challenge</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

How are we to account for the distinctly auditory phenomenology of certain AVHs? As Cho
and Wu (2013) put it, if a theory claims that AVHs are misattributed inner speech, it must
explain how we get a transformation from the experience of the subject’s own inner voice
[…] often lacking acoustical properties such as pitch, timbre, and intensity into the
experience of someone else’s voice with acoustical properties. (p.2) As Wu (2012) puts it
in an earlier paper, “we must explain this ‘transformation’ from the normal to the
pathological” (p.94). Although one can question the premise that inner speech lacks
auditory phenomenology (McCarthy-Jones and Fernyhough, 2011; Moseley & Wilkinson, 2014),
even granting that this is the case, the PPF makes this ‘transformation’ less perplexing.2

<hs>  The Varieties of AVHs Challenge</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Jones (2010) emphasises the heterogeneity of AVHs: The term AVH encapsulates a diverse
phenomenological experience, which may involve single and/or multiple voices, who may be
known and/or unknown, speaking sequentially and/or simultaneously, in the first, second,
and/or third person and which may givecommands, comments, insults, or encouragement.
(2010, p.566) In particular, Jones presents two models for understanding AVHs and argues
that both are promising for understanding different subtypes of AVH. The first model he
examines is the “memory-based” model proposed by Waters, Badcock, Michie, and Maybery
(2006), which he suggests fits well with the phenomenological features of AVHs that appear
to be the upshot of a traumatic experience. In these AVHs you often find, for example,
instructions to self-harm in a voice that is recognisably that of the abuser. Even more
strikingly, the contents of these AVHs “can be related to what was said during or
surrounding these events (e.g. if you tell anyone I’ll kill you)” (Jones, 2010, p.568).
However, these form only a relatively small subset of AVHs (e.g. 4 out of 24 in Fowler et
al., 2006). A larger subset of AVHs seem to serve the function of regulating or commenting
on current events (e.g. Nayani and David (1996) reported that for 46% of their sample, the
voice had replaced their “voice of conscience”). For these, Jones (2010) suggests that his
second candidate model is a better option. This model is precisely the inner-speech-based
SMTs that we introduced in Section 1. The moral of this is that it is very difficult to
account for all this variety within a model that explains AVHs in terms of misattributed
inner speech. I am in complete agreement with Jones that we need different models for
different subtypes.3 I would simply add to Jones’s suggestion, however, that we
distinguish frameworks, theories, and models. Roughly, the distinction is as follows.
Frameworks are very broad; they are ways of approaching a particular domain of inquiry
(e.g. the brain and cognition). It is within them, whether implicitly or explicitly, that
theories are built.4 Theories are falsifiable claims (rather than ways of approaching
something) at a high level of generality that explain a phenomenon or class of phenomena
by elucidating the fundamental nature of the phenomenon, or by postulating certain rules
or principles that govern or define the phenomenon (e.g. a self-monitoring theory of
schizophrenia). Models are at a lower level of generality; they explain how a particular
kind of phenomenon arises, sometimes in terms of other, hopefully better understood,
phenomena (e.g. a misattributed inner speech model of AVH). Theories might suggest
candidate models. So a self-monitoring theory of the primary symptoms of schizophrenia
might suggest a misattributed inner speech model for AVHs occurring in the context of
schizophrenia. Models should be applicable to individual cases. Thus, given a theory that
posits one kind of deficit, different models could well be needed for different
symptomatic manifestations of that underlying deficit. In a nutshell, I will suggest that
the different subtypes need (as Jones, 2010 suggests) to be explained in terms of
different aetiological models. However, these models are to be built within the same
framework, the predictive processing framework that I will present now.

<h>THE PREDICTIVE PROCESSING FRAMEWORK (PPF)</h>
-----------------------------------------

I’d like to put psychosis to one side, and focus, in this section, on presenting a
framework for understanding the brain and cognition generally. We will later see how this
might apply to AVH. I will start with an initial presentation of the PPF, and then present
some conscious effects that are suggestive that the brain is engaged in predictive
processing.

<hs>  An initial presentation: “inference” and efficiency</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

According to the PPF, the brain’s main task is to “infer” from incoming signals, what the
causes of those signals are, in other words, settle on a hypothesis about what is “going
on”.5 However, the incoming signal, namely, the proximal stimulus on sensory receptors,
underdetermines distal causes. Since inputs are noisy and ambiguous, there is no one-to-
one mapping: the same stimulation can be brought about by two very different distal causes
(and different stimulation in different circumstances can be caused by the same distal
cause). Given that more than one hypothesis is compatible with the incoming signal, how
does the brain settle on one hypothesis rather than another? It needs to take two things
into account: first, the fit of the input with the hypothesis, and, second, how
statistically likely that hypothesis is (the “prior probability”), at least as far as the
brain is concerned (this is subjective rather than objective probability). A hypothesis
could fit the input extremely well, but its prior probability could be so low that it
isn’t even considered. Conversely, a hypothesis could have such a high prior probability,
that, even though it doesn’t fit the input well, it is settled upon. Although this is a
picture of what the brain has to do in order to do a good job of “inferring” what is going
on, it is abstracted from the temporal dynamics of the brain’s functioning. In reality,
the inputs, hypotheses and prior probabilities (priors) are in constant hierarchical
interaction with each other. This is where the notion of prediction comes in. What the
selection of a hypothesis does is that it determines a set of predictions about subsequent
inputs, namely, inputs that are compatible with the hypothesis. If the hypothesis does a
good job of predicting inputs, it will be kept. If it does a bad job, it will be tweaked
or abandoned altogether in favour of another hypothesis. In other words, one hypothesis is
selected rather than another if it better minimises prediction error. Some theorists (e.g.
Hohwy, 2013) sum up the PPF by saying, for example, that the brain is in the business of
minimising prediction error.6 This prediction error minimisation is not only taken to
account for perception and cognition, but for action as well (see e.g. Adams et al.,
2013). Instead of there being motor commands, as on the standard picture, what you have
are predictions, which are then fulfilled by the subsequent bodily movement, thereby also
being a case of prediction error minimisation. This is often called “active inference”
(Friston, 2009), which Pickering and Clark (2014) helpfully gloss as follows: “the
combined mechanism by which perceptual and motor systems conspire to reduce prediction
error using the twin strategies of altering predictions to fit the world and altering the
world (including the body) to fit the predictions” (p.1). This picture has interesting
consequences for how we are to view the role of input on sensory receptors and its impact
on higher cortical regions. According to the PPF, the only information that gets passed on
up the hierarchy is prediction error. Indeed, as some recent theorists nicely put it: an
expected event does not need to be explicitly represented or communicated to higher
cortical areas which have processed all of its relevant features prior to its occurrence.
This stands in sharp contrast to the standard (and admittedly intuitive) view of
perception (what might be called a “bottom-up feature-detection view”). On such a view,
inputs come in, are processed, and passed on. On the PPF, only the prediction error gets
passed on, and therefore the vast majority of what determines your perceptual experience
is what your brain has already predicted, your brain’s best hypothesis. In short, on the
PPF, the role of the incoming signal in determining conscious perception is much less
great than on standard bottom-up views.

<hs>  Precision weighting, second-order prediction and “attention”</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although incoming signals are ambiguous, in different contexts, the degree of ambiguity
will differ. To maximise its predictions, the brain needs to accurately estimate how much
ambiguity (uncertainty) there will be. In contexts where low ambiguity is expected, higher
precision will be demanded, and vice versa. This is called “precision weighting” in the
literature (Feldman & Friston, 2010; Friston, 2009; Hohwy, 2012), and is taken to be
modulated by neurotransmitters such as dopamine (Corlett, Taylor, Wang, Fletcher, &
Krystal, 2010).7 Recently, theorists (Feldman & Friston, 2010; Hohwy, 2012) have equated
this precision weighting with what we often call “attention”. As is well known, attention
can be brought about endogenously or exogenously, namely, either because the subject is in
a state of wanting to attend to something (endogenous attention), or because something in
the environment attracts attention (exogenous attention). Suppose I’m talking to someone
in a crowded bar. By using information from seeing the person’s lips move, my brain has
certain expectations about what sounds are likely to be produced. That part of my visual
field, and the corresponding part of my “auditory field”, now has relatively high
precision attributed to it, largely because I am interested in what’s going to be said
(endogenous focal attention). Everything else around that, both visual and auditory, has
relatively low precision. My brain has a very gist-like hypothesis about what is going on
there, and, any prediction error regarding that has low weighting. Of course, a loud
peripheral bang or camera flash can grab my attention (a case of exogenous focal
attention). That would constitute a strong enough input to overcome whatever down-
modulation my brain has placed on that peripheral prediction error. To sum up, then, we
can think about the directing of attention as “turning up” the expected precision of an
incoming signal, which amounts to turning up the “gain” on any prediction error. This can
be viewed normatively. That is to say, not only can your brain get its predictions wrong,
it can also get the expected precision of its predictions wrong, i.e. its second-order
predictions. Your brain can wrongly think that it is in a more or less ambiguous
environment than it actually is in. And this will mean too much or too little weighting on
prediction error.

        <hss>Binocular rivalry</hss>

        This is perhaps the most common example used in support of the PPF. It speaks
        strongly against a bottom-up view in favour of a more predictive or “inferential”
        view. Under experimental conditions, each eye is presented with a different, but
        meaningful, stimulus. One standard example involves presenting one eye with a
        picture of a house, and the other with a picture of a face. Subjects do not report
        visually experiencing, as one might expect, a mixture of face and house. Rather,
        they experience a “bi-stable” switching, from face to house, and back, and so on
        (the switching is often reported as a gradual “breaking through” of the other
        image). As Hohwy, Roepstorff, and Friston (2008) point out, this can be nicely
        explained within the PPF, as a reasonable response to highly un-ecological
        circumstances. In a nutshell, you experience the bi-stable state because your
        brain is switching between hypotheses about what is out there. When it settles on
        one hypothesis, say, the face hypothesis, inputs from the house image fail to
        accord with this hypothesis and prediction error is sent up the hierarchy. When
        enough prediction error accumulates, the hypothesis switches (and with that, what
        the subject consciously experiences) to the house hypothesis, but then the input
        from the face image doesn’t accord, and so on, and so forth. The fact that this
        bi-stable switching only occurs with certain well-chosen stimuli, suggests the
        operation of what might be called a “hyperprior”: an expectation about the world
        that is stable, and often at a high degree of abstraction. The “hyperprior” in
        this case is that faces and houses, being at different scales, cannot occupy the
        same region of the visual field at the same time. As a result, the “face-house”
        hypothesis about what is out there never presents itself. Note how binocular
        rivalry puts pressure on a “bottom-up” view of perceptual experience. As Hohwy
        (2013) puts it: During rivalry, the physical stimulus in the world stays the same
        and yet perception alternates, so the stimulus itself cannot be what drives
        perception (p.20) One might think that binocular rivalry could result from the
        operation of a different principle, and one that is compatible with a largely
        “bottom-up” view, namely the principle: “If your eyes each have coherent but
        incompatible inputs, don’t receive input from both at once.” This nicely
        illustrates how predictive processing concretely differs from a bottom-up view
        such as this one. When the subject experiences a house, on the bottom-up eye-
        selection hypothesis, this means that the eye being presented a house is passing
        on a signal, whilst the eye being presented a face is not. On the predictive
        processing view, it is the opposite: the eye being presented the face is passing
        on a signal, namely a prediction error signal. One reason for rejecting the eye-
        selection account is that it doesn’t (unlike the build-up of prediction error)
        explain the stable switching back-and-forth. A second, more striking, reason is
        that this account was falsified by Diaz-Caneja (1928) who discovered that if each
        stimulus picture is cut in half and swapped over, so that each eye is being
        presented with a half-face half-house image (split down the middle) there is the
        same experience as before, namely, a rivalry between a complete percept of a face
        and a house.

        <hss>The Hollow Mask Illusion</hss>

        When you are presented with a rotating mask that is slowly turned to present you
        with the concave back of the mask, your brain “corrects” the concave stimulus into
        a convex stimulus. (You yourselves can experience this illusion on several sites
        on the internet.) You experience the concave back of the mask, as convex. Again,
        this is due to a very strong prior (perhaps worthy of being called a hyperprior),
        that over-rides the incoming signal. The prior in question is that the faces you
        will encounter will always be convex (a fair expectation!). This prior is so
        strong that even though the “concave face” hypothesis would better match the
        input, it is never selected. Given the highly specialised processing that faces
        receive in human cognition, this is perhaps hardly surprising.

        <hss>The McGurk Effect</hss>

        Moving away now from uni-modal priors, there is an effect that deals with highly
        flexible, concrete, cross-modal priors. This is the fact that what you see will
        affect your brain’s expectations about what it hears. If a subject is played a
        video of someone appearing to say “ga, ga”, but you play them a synchronous audio
        track of someone saying “ba, ba”, you aurally experience “da, da” (something “in
        between”). This is called the McGurk Effect. The visual input changes your brain’s
        expectation concerning the auditory input, and interprets it differently. We can
        see the same cross-modal predictive processing (vision having an effect on
        audition) at work in more everyday cases. If you look across a crowded bar at
        someone ordering a drink, by looking at her lips, you can actually hear her order.
        Your brain uses the visual input to inform its priors about what is being said. If
        you had tried to hear her order with your eyes closed, there is no way you would
        have been able to single out her voice from the noise of the crowded room. Your
        brain just wouldn’t have had the visual cues to inform its expectations.8
        Furthermore, since what she says is what matters to you at that moment, you “turn
        up the gain” on prediction error that is relevant to hypotheses concerning what
        she says.

<hs>  Clearing up potential confusion: what the brain does and what the person does</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although this predictive processing is extremely relevant for our conscious experience, we
need to be very careful to distinguish what our brains do from what we do. One nice way of
seeing this distinction is by distinguishing “surprisal” (Tribus, 1961) and “surprise”,
where the former is what is surprising to your brain (as signalled by prediction error),
and the latter is what is surprising to you.9 These two come apart. If you look out of
your window and see an elephant on the lawn, you might be very surprised. However, the
fact that you see straight away that it is an elephant shows that your brain has already
minimised the prediction error and settled on the elephant-on-lawn hypothesis. Conversely,
when you are attempting a binocular rivalry task, and you’ve done it before, the switching
doesn’t surprise you, however, your brain is switching between hypotheses precisely
because it is struggling to keep “surprisal” to a sufficiently low level. Since we are
concerned with AVHs, a conscious phenomenon, it is vital to understand this relationship
between what the brain does, and what the person does, and, analogously, predictive
processing on the one hand, and conscious experience on the other. Roughly, your conscious
percept is determined by the overall hypothesis that your brain has adopted in order to
minimise prediction error.

<h>PREDICTIVE PROCESSING AND PSYCHOSIS</h>
-----------------------------------

Now that I have presented the PPF, we can see what relevance it has for psychosis in
general, and for AVH in particular. Two sources of evidence that support the hypothesis
that predictive processing abnormalities might be implicated in psychosis are, first, that
the conscious effects that have been taken to be suggestive of predictive processing are
altered in subjects with diagnoses of schizophrenia, and, second, that there are
behavioural results from eye tracking that are nicely explicable in terms of predictive
processing.

<hs>  Conscious effects are altered in patients with diagnoses of schizophrenia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Suppose that psychosis can be understood, in part, at least, as a breakdown in normal
predictive processing. And suppose that, as we have suggested, the conscious effects just
mentioned are the product of normal predictive processing. One would expect patients with
schizophrenia diagnoses to experience these effects differently from the normal
population. This is exactly what the evidence suggests. Schneider, Leweke, Sternemann,
Weber, and Emrich (1996), Schneider et al. (2002) and Emrich, Leweke, and Schneider (1997)
demonstrate that subjects with schizophrenia diagnoses do not experience the Hollow Mask
Illusion. They see the mask, correctly, as hollow. Their brain does not “correct” the
input. Pearl et al. (2009) showed that patients with diagnoses of schizophrenia experience
the McGurk Effect less. In other words, the visual stimulus corrects the auditory input
less, or not at all. Pearl et al. (2009) put this in terms of a “decreased reliance” on
visual cues. Results with similar implications are reported by Ross et al. (2007) with
regards to visual enhancement of speech comprehension in noisy environmental conditions.
In other words, subjects with diagnoses of schizophrenia showed an impairment in their
ability to enhance their auditory perception with visual cues. Within a PPF this would be
put in terms of either decreased efficacy of auditory priors informed by the visual
information, or in terms of excessively weighted bottom-up prediction error (or both). As
for binocular rivalry, Heslop (2012) showed that switching rates in binocular rivalry
were, on average, significantly slower in subjects with schizophrenia (0.28 switches per
second, versus 0.54 in the non-clinical population).

<hs>  Evidence from eye tracking</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Following Adams, Perrinet, and Friston (2012), I distinguish three eye-tracking tasks
where the performance of patients with diagnoses of schizophrenia differs significantly
from healthy controls. First, there are cases of impaired tracking during visual occlusion
(Hong, Avila, & Thaker, 2005; Thaker et al., 1998). In other words, when a moving target
is temporarily occluded from view, controls are much better than subjects with diagnoses
of schizophrenia at keeping track of the target when it comes back into view. Second,
patients with diagnoses of schizophrenia show impaired “repetition learning.” When a
target trajectory is repeated, healthy controls achieve optimal performance whereas
subjects with schizophrenia diagnoses do not (Avila, Hong, Moates, Turano, & Thaker,
2006). Thirdly, there are cases of what, in the literature, is called “paradoxical
improvement”, namely, where patients with a supposed illness or deficit perform better at
a particular task than healthy controls (the fact that patients with schizophrenia do not
experience the Hollow Mask Illusion might be thought of as a “paradoxical improvement”
since their percept is more veridical). The task in question involves keeping track of a
target that rapidly and unexpectedly changes direction. Subjects with schizophrenia are
better at keeping track of the target than healthy controls (but only very shortly after
the change in direction). Working within the PPF, Adams et al. (2012) explain these three
discrepancies in terms of differing reliance on predictions (priors) and prediction error
respectively. The first two tasks are improved by reliance on prediction, whereas the
third task, being deliberately unpredictable, is hindered by prediction, and would be
improved by a higher weighting on the prediction error. Note, however, that, like the
Hollow Mask Illusion, the “paradoxical” improvement is shown on a stimulus that is
statistically un-ecological. Just as we encounter convex faces and never concave ones, the
world is full of statistical regularities and it is more adaptive to be able to exploit
those regularities efficiently than to slightly outperform others in the rare instances
when stimuli are totally unpredictable.

<h>ADDRESSING THE TWO CHALLENGES</h>
-----------------------------

I will start by showing how the PPF addresses the Auditory Phenomenology Challenge. In
particular, I will show how it circumvents the issue of explaining the “transformation”
from the healthy phenomenon (e.g. inner speech) to the pathological phenomenon (i.e. AVH).
I will then present three subtypes of AVH and show how the PPF accommodates different
aetiological models for each.

<hs>  Dissolving the Auditory Phenomenology Challenge</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Viewed from within the PPF, this challenge is based on a mistaken understanding of how the
brain works, and the relationship that this has to conscious experience. The PPF changes
how one thinks of perceptual experience, and, by extension, radically changes one’s
explanatory focus in trying to account for hallucinations. On a standard framework, where
front-line sensory stimuli get gradually processed and passed on up the hierarchy,
hallucinations make one wonder, “Where does this erroneous sensory stimulus come from?”
Indeed, we can see SMTs as making attempts to answer this within a standard framework.
Their answer is: they come from the quasi-sensory stimulation of inner speech, which is
then misattributed. However, when, instead, we adopt the PPF, incoming stimuli play a much
smaller role in determining the conscious percept, even where veridical perception is
concerned. Given that a conscious percept is constituted by the hypothesis that best
minimises prediction error, we don’t ask, “Where does the input come from?”, since the
input alone doesn’t (and can’t) determine the percept. Rather we ask, “Why does this
hypothesis minimise prediction error?” This general approach makes hallucinations both
less perplexing, and less different from veridical perception.10 The point is that on the
PPF, your conscious experience at any given time is the hypothesis that your brain has
selected in order to minimise prediction error. Applied to AVHs, your experience will have
auditory phenomenology if your brain has had to adopt the hypothesis that you are hearing
something in order to minimise prediction error. This isn’t really a “transformation”
because, on the PPF, it makes no sense to talk of inner speech as a “raw material” that
needs transforming. Either you have an experience that is inner speech, because your brain
has adopted the hypothesis that that is what is going on, or you have a different
experience, corresponding to a different hypothesis. There is no experience of inner
speech first, which is somehow then transformed. The question about whether inner speech
is relevant for AVHs is not one of transformation. It is about whether relevant elements
involved in the production of the inner speech experience are also involved in the
production of some AVHs.11 It seems fairly clear, given all of the evidence in its support
(some of which we have already seen, some of which we will touch upon below), that the
answer to that is: yes. However, it is worth noting that on the PPF, all action will be
couched in terms of active inference, namely, in terms of (hopefully) self-fulfilling
sensory predictions (cf. Adams et al., 2013). How we are to think of inner speech within
this framework is a fascinating direction for future inquiry. Given the plausible view
that inner speech is developmentally derived from overt, private, speech (Berk, 1992;
Vygotsky, 1934; Winsler, 2004), this could involve activating a prediction (as for any
overt action), but over time somehow managing to dispense with many of the features of the
action in question. This could involve learning to lower the weighting on the prediction
error, or to make the prediction itself less demanding, or a combination of the two.
Either way, prediction error could be minimised without having to go through with all
aspects of the action (or, rather, its developmental precursor, private speech), although
some aspects (e.g. subvocalisations, muscular activations) will remain. How this could
lead to AVH is something that we will come to shortly. The key idea, roughly, is that
inner speech is stripped down outer speech, but that this is built back up in AVH.
However, it is not simply built back to overt speech, but to something different that
involves the hearing of speech, but not its production.

<hs>  Accounting for three subtypes of AVH</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Jones (2010) expressed a concern that one model is unlikely to explain the various
subtypes of AVH. He presented two subtypes. I will add a third but then gesture towards
how the PPF provides a framework against which all three can be explained through
different aetiological models.

        <hss>Inner speech hallucinations</hss>

        As we mentioned, the most popular model for understanding AVHs involves
        misattributed inner speech, where the misattribution results from an abnormality
        in self-monitoring. Although I want to abandon the framework within which SMTs
        tend to function, following Jones (2010), I think it is important to emphasise
        that there is great deal of empirical support for the view that a subset of AVHs
        implicate mechanisms involved in inner speech. There is support for the idea that
        inner speech might be relevant, other than the experiments we noted earlier in
        support of SMTs. Ford and Mathalon (2004) used EEG findings to suggest that during
        the production of healthy inner speech, corollary signals from speech production
        areas seem to suppress activation in speech processing areas. As Bentall and
        Varese (2013) nicely put it, “it might be said that when we talk to ourselves, the
        frontal language production areas of the brain tell the posterior areas not to
        bother listening” (2013, p.71). This attenuation should remind us of the support
        from bodily effects of monitoring, namely, the attenuation of sensation in
        (attempted) self-tickling. Both the attenuation pertaining to self-tickling and to
        inner speech can be accounted for within the PPF. Within the PPF, the fact that we
        cannot tickle ourselves is explained rather differently from how it is explained
        in SMTs that rely on motor commands and self-monitoring mechanisms. Brown and et
        al. (2013) have done work within the PPF that accounts for this in terms of a more
        general dampening of weighting on prediction error. The reason for this dampening
        is that movement involves implementing a currently false hypothesis (“I am
        moving”) in favour of the currently true hypothesis (“I am not moving”). The
        dampening swings the balance in favour of the false hypothesis, which then becomes
        true when the action is initiated.12 In inner speech, there is the prediction that
        you will speak, but the precision weighting will be turned right down,
        circumventing the need to minimise prediction error by actually overtly speaking
        (although, as we saw, some vestiges of the overt speech will remain). This will
        correspond to the suppression of activation in “speech processing areas” which are
        reported in both inner speech and in hearing oneself speak aloud (Ford & Mathalon,
        2004). On the PPF there would be less activation in these areas, even when hearing
        oneself speak aloud, since there would be less prediction error (better
        predictions) than hearing someone else speak. The fundamental principle of
        prediction-error minimisation is the same whether the activity to be predicted is
        self-generated or not. One important difference, however, is that, if the activity
        is self-generated, the expected precision will be higher. Given this, only a
        relatively slight error in prediction would result in highly weighted prediction
        error, which would subsequently result in a more erroneous hypothesis to explain
        it away. This could account for cases where there are delusions of control and
        inner speech-based hallucinations in the absence of more outwardly directed
        perceptual abnormalities.

        <hss>Memory-based hallucinations</hss>

        Waters et al. (2006) distinguish their view from “standard cognitive accounts”, by
        which they mean SMTs, and which they call “single deficit accounts”, by proposing
        that: at least two cognitive deficits must be present to explain auditory
        hallucinations: (1) a fundamental deficit in intentional inhibition which leads to
        auditory mental representations intruding into consciousness in a manner that is
        beyond the control of the sufferer; and (2) a deficit in binding contextual cues,
        resulting in an inability to form a complete representation of the origins of
        mental events. This talk of “auditory mental representations”, “inhibition” and
        “binding of contextual cues” is nicely illustrative of how removed this is from
        the sort of framework that I am suggesting in this paper. However, this is not to
        say that they are incompatible, and cannot both be helpful. Using a couple of
        tasks (the Hayling Sentence Completion Task (Burgess & Shallice, 1996) and the
        Inhibition of Currently Irrelevant Memories Task (Schnider & Ptak, 1999)) Badcock,
        Waters, Maybery, and Michie (2005) demonstrated that hallucinating patients with
        diagnoses of schizophrenia have lower inhibition (more intrusion) of irrelevant
        associations and memories. The second deficit is needed to explain why these
        memories, which are failing to be inhibited, aren’t being recognised as memories.
        In research on episodic memory, there is a distinction between content (what is
        remembered) and context (e.g. temporal and “source” features of what is
        remembered). Waters et al. (2006) suggest that, although the content is
        remembered, there is a deficit in “context memory”, and, more specifically, “an
        impairment in combining contextual cues together to form an integrated
        representation of an event in memory”. Thus, the memory will present something
        that happened in the past, usually something traumatic, but it will not be
        experienced as a memory. It will be taken as a voice from the present. Let us look
        at what might be going on here through the lens of the PPF. In a case of an
        episode of healthy episodic memory, whether deliberate or unbidden, what is
        involved is the activation of relevant imagery, which within the PPF (in a way
        somewhat similar to our earlier discussion of inner speech) is not some kind of
        inner sensation, but a prediction. However, unlike the predictions at play in
        perception and action, this prediction is not answerable to – malleable in the
        light of – inputs. How is this “decoupling” from the environment achieved? What
        needs to happen is that the prediction need not to be “taken too seriously”, and
        so this will mean turning the precision right down on prediction error (this is
        similar to what happens in inner speech, minus the articulatory component). That
        way the “prediction” can be maintained even though the system is fully aware that
        it is not really predicting anything, that there is nothing really corresponding
        to the localised hypothesis generating the prediction. The general, overarching,
        hypothesis, is still that the subject is where she is (e.g. at a desk), but she is
        simply remembering something (e.g. that time when her father shouted at her). Now
        suppose that this prediction is activated, but there is a problem with keeping the
        weighting on prediction error low. This generates erroneous amounts of prediction
        error for which the brain has to adopt a hypothesis: this is perception, not
        memory. In a sense, then, if predictive processing, and, in particular the upwards
        and downwards modulation of precision on prediction error, goes badly awry then we
        get a blurring between mere imagery (as involved in episodic memory, imagination
        and, with relevant qualification, inner speech) and perception. The clever trick
        of decoupling, which enables us to remember episodically, or to imagine vividly,
        is disrupted. However, if this is correct, then we don’t need to appeal to
        integration of contextual cues (except insofar as there is a de facto failure to
        realise that this is not happening now). The recollective episode is not
        recognised by the subject as a memory, not because of some cognitive failure to
        remember the temporal or “source” context in which this happened, but because it
        doesn’t feel phenomenologically like remembering something: it feels like hearing
        something. Indeed, failure to remember temporal or source context cannot suffice
        to explain AVHs since there are cases where the voices are recognised by the
        subject as being exact replays of the past (12% in McCarthy-Jones et al., 2012),
        but they are still not experienced as memories, but as perceptual experiences.
        Indeed Wu’s Auditory Phenomenology Challenge applies to memory-based context-
        monitoring views almost as much as to inner-speech-based self-monitoring views. I
        say “almost as much” since perhaps (and we know very little about whether this is
        actually the case) episodic auditory memories have more phenomenological features
        in common with auditory perceptual experiences than episodes of inner speech
        (which arguably have an active, articulatory component). But, in any case, they
        certainly do not share all of them. So the challenge goes: How does one account
        for the auditory phenomenology of AVH if they are simply mis-identified memories?
        How does one account for the “transformation” from auditory-memory phenomenology
        to auditory-experience phenomenology? On the PPF account, since the conscious
        experience is a product of prediction-error minimisation, this question doesn’t
        arise. The initial event, the explanatorily relevant genesis of the experience,
        may be (as with the inner speech hallucinations) the same initial event as for a
        recollection in episodic memory, however, the erroneous prediction error causes
        the brain to hypothesise that something very different is going on.

        <hss>Hypervigilance Hallucinations</hss>

        The two varieties I have just elaborated on were introduced earlier in the paper
        through a consideration of Jones’s Varieties Challenge. This third kind has not
        yet been presented in this paper. Perhaps the first step towards an appreciation
        of the existence of hypervigilance hallucinations was made in a paper by
        Delespaul, DeVries, and Van Os (2002), who conducted an investigation into the
        contextual influences on AVHs. They found that the context where voice hearing is
        most likely to occur is either in the presence lots of people or alone. Building
        on this, Dodgson and Gordon (2009) suggested, on grounds of clinical case-studies,
        a kind of AVH called a “hypervigilance hallucination.” Here is a description of
        hypervigilance hallucinations from their paper: Michael was experiencing a series
        of stressors including break up with a girlfriend and exclusion from seeing their
        child, heavy street drug use, including amphetamine, and a pending court case for
        arson. He began to experience auditory hallucinations, hearing people calling him
        a “nonce”. Michael began to believe that people could read his thoughts, and that
        people thought he was a paedophile. The existence of hypervigilance hallucinations
        as a separate subtype was subsequently supported by Garwood, Dodgson, Bruce, and
        McCarthy-Jones (2013) who, based on a cluster analysis, showed that AVHs tend to
        occur when: attention is directed inward in quiet contexts attention is directed
        outward in noisy contexts They took (i) to suggest that inner speech
        hallucinations were occurring, and (ii) to suggest that hypervigilance
        hallucinations were occurring. Attention seems like a key factor here. So let’s
        view this notion of hypervigilance from within the PPF and its gloss on attention
        as precision-weighting. Let us contrast vigilance, with an illustratively opposing
        state: total calmness and lack of threat. Compare two cases of walking down a
        familiar woodland path at dusk. In the one case, you are walking home after an
        agreeable dinner party at a friend’s house, and you are feeling happy and relaxed.
        Because it is getting dark, you will find that your brain is forming rather vague
        hypotheses about what is out there, but since you are relaxed, and you have no
        reason to think that anything might be a threat, this is fine: precision-weighting
        (“attention”) is kept low. You get home safely having represented your environment
        in a vaguer, more coarse-grained way than you would have done in broad daylight,
        but this served your navigational purposes. Now suppose, instead, that you are
        walking home after having watched a horror movie. You are no longer relaxed, but
        in an emotional state of vigilance. As a result, you will be more likely to
        interpret something as looking like a person lurking amongst the trees. If this
        startles you, your attention will focus on that part of your visual field, and the
        precision-weighting of prediction error in that area will be turned right up. You
        may, due to this upwards-modulation, see that it is, in fact, only a tree trunk.
        Although as you look more closely, you get more incoming visual information
        suggesting the tree-trunk hypothesis, interoceptive information, namely, the fear
        that you feel, which is residual from the horror movie you saw, counts in favour
        of the lurking-person hypothesis (Pezzulo, 2013). You (or, perhaps more
        accurately, your nervous system) roughly think: “Why am I scared? There must be
        something to be scared of”, and then you get even more scared. In sharp contrast,
        in the first case, when you are happy and relaxed, the lurking-person hypothesis
        doesn’t even present itself. This fits nicely with hypervigilance hallucinations.
        In a state of hypervigilance, ambiguous inputs will be given a threatening
        interpretation; hypothesis selection will be biased towards something threatening,
        because this will also serve the purpose of explaining the interoceptive state
        (Seth, 2013). For the subject, this will give rise to experiences which
        misrepresent reality: from the ticking clock or the muffled sound of neighbours
        talking will emerge the experience of a voice telling the subject exactly what the
        subject, in his state of hypervigilance, is afraid of hearing (e.g. “nonce!”).
        Unlike the two other subtypes, hypervigilance hallucination have their genesis in
        the external world. One might of course claim that, since hypervigilance
        hallucinations do, strictly speaking, have some kind of worldly stimulus, then
        they are not, strictly speaking, hallucinations; they are rather illusions. I see
        this as a mainly terminological point, however, so will not go into it.13 A more
        important point is that, because of this, SMTs cannot account for hypervigilance
        hallucinations whereas the PPF can. The point is that, according to SMTs, normal
        monitoring exploits mechanisms (e.g. motor commands) linked to the production of
        self-generated events, and it is this that goes wrong and is misattributed. Thus,
        although it has a story to tell about how bodily actions, inner speech, and
        perhaps even episodic memories, can be badly monitored, and hence misattributed,
        it must remain silent about hypervigilance hallucinations, which are precisely not
        a case of a self-generated stimulus being misattributed, but rather an external
        stimulus being misinterpreted. To put it another way, unlike with SMTs, in the
        PPF, all stimuli, not just the self-generated ones, need to be predicted.

<hs>  Multiple models within one framework: personal history and attentional focus</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

I have gestured towards how these three subtypes could be accounted for within the PPF,
but why would a given subject, at a given time, experience one subtype rather than
another? This is an unavoidably difficult question. Although I cannot answer it in full, I
think that two things are of particular explanatory relevance within the PPF. The first is
the personal history of the subject; the second is the subject’s attentional focus, which
will probably often be the accompaniment of certain moods, emotions and contexts. Personal
history, for example, whether a subject underwent some form of traumatic abuse as a child,
is likely to have an impact on whether a subject hears voices, and, as we have suggested,
these voices are perhaps likely to be memory-based. Similarly, if a subject (like Michael,
in Dodgson and Gordon’s case-study) has a history of amphetamine use, coupled with other
so-called “stressors”, this might well lead to heightened risk of AVH, but probably not
memory-based ones, since there is no single traumatic event to form the basis of the
relevant episodic memory. Of course there could be interaction between the different
factors that contribute to the (perhaps unrealistically clear) delineations of the
subtypes. Thus childhood trauma and substance abuse could contribute to someone being at
heightened risk of AVH. These might be, for example, hypervigilance hallucinations whose
content could in some way be tied to past trauma. What, then, would make an individual
more likely to experience AVHs that have an internal (viz. inner speech or memory) or an
external (viz. hypervigilance) genesis? In answer to this question it may be useful to
appeal to attentional focus. We saw that, within the PPF, following Hohwy (2012), we can
think of attention as turning up the precision-weighting, and hence potential prediction
error, on the attended stimulus. Attention can be directed outward, at incoming stimuli,
or it can be directed inward, at thoughts, feelings and memories. Thus, if attention is
directed outward in a state of anxious hypervigilance, there is more likely to be
excessively weighted prediction error from the outside. This would correspond to
hypervigilance hallucinations. As a result, traffic noise, or a ticking clock, or the
sound of a group of people talking, might be embellished into the experience of a voice
saying something. Alternatively, if attention is directed inwards, and the subject is
socially isolated, ruminating in a state of shame or guilt, then there is more likely to
be excessively weighted prediction error from the inside. This would correspond to inner
speech or memory-based hallucinations. This nicely fits the findings by Garwood et al.
(2013), concerning the prevalence of hallucinations in quiet and noisy contexts. It also
allows that one patient, in different contexts and different moods, may experience
different AVH subtypes. Indeed all three of the subtypes presented here may occur in one
subject at different times. Of course, the picture is more complicated, but the framework
is precisely the sort that is capable of accommodating such complications on a case-by-
case basis.

<h>SUMMARY AND CONCLUSION</h>
----------------------

I have suggested that we view AVHs through the lens of a predictive processing framework
as a way of addressing two challenges, the first of which, in particular, plagues orthodox
SMTs, the second of which is problematic for any single model of AVHs. The first
challenge, of how the auditory phenomenology of AVHs can be accounted for, or at least
rendered less perplexing, is addressed by the fact that the subject’s conscious percept is
not determined by incoming stimuli, but by the brain’s best hypothesis as selected on the
basis of how well it minimises prediction error. The question is not: Where does this
erroneous stimulus come from? Rather the question is: Why does the brain adopt such a
strange hypothesis? The answer to this question is (at least partially): erroneous
precision weighting on prediction error. The second challenge, concerning the varieties of
AVH, is addressed by realising that a new framework can accommodate elements of pre-
existing models, but views the contribution of, for example, episodic memory or inner
speech, in a way that is somewhat different. They are not “raw materials” to be
transformed. Rather, mechanisms that are implicated in generating healthy experiences of
episodic memory and inner speech, can generate erroneous prediction error that will result
in erroneous hypotheses being adopted to minimise it. A major advancement of the PPF over
SMTs is the realisation that, since prediction lies at the heart of cognition (broadly
construed to include emotion and action), both internally and externally produced stimuli
need to be predicted. SMTs had to be silent regarding external stimuli, since only self-
generated stimuli can be monitored. Adopting the PPF, like adopting any framework, is only
a first step. Not only is there, first of all, work to be done on better understanding
predictive processing; for example, its neurobiological underpinnings and how it might go
wrong at that level (see Corlett et al., 2010 for advancements in this direction). There
is also exciting work to be done within the PPF with specific case-studies. It is a
flexible framework within which we can better understand unique individuals, with
different histories, problems and conditions.14


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<ART>Acquiescence response styles: A multilevel model explaining individual-level and country-level differences
================================================================================

Authors: Beatrice Rammstedt, Daniel Danner, Michael Bosnjak
DOI: 10.1016/j.paid.2016.11.038
Year: 2017  |  Pages: 190-194
ASJC codes: 3200
Keywords: Acquiescence, Country-level determinants, European Social Survey, Individual-level determinants, Multilevel model

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Acquiescence has been found to distort the psychometric quality of questionnaire data. Previous research has identified various determinants of acquiescence at both the individual and the country level. We aimed to synthesize the scattered body of knowledge by concurrently testing a multilevel model encompassing a set of presumed predictors of acquiescence. Based on a representative sample comprising almost 40,000 respondents from 20 European countries, we analyzed the effects of the country-level indicators economic wealth, corruption level, and collectivism and the individual-level indicators age, gender, educational attainment, and conservatism. Results revealed that 15% of the variance in acquiescence was due to country-level variations in corruption levels and collectivism. Differences among individuals within countries could be partially explained by conservatism and educational attainment.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Acquiescence—that is, the tendency to respond to descriptions of conceptually distinct
attributes or attitudes with agreement/affirmation (agreement acquiescence) or
disagreement/opposition (counter-acquiescence) regardless of their content—has been widely
recognized as a threat to the validity of questionnaire-based data (e.g., Rammstedt,
Goldberg, & Borg, 2010; Soto, John, Gosling, & Potter, 2008). Specifically, acquiescence
can affect mean levels in item responding, thereby yielding misleading mean differences.
For example, Van Vlimmeren, Moors, and Gelissen (2015) showed that country-level
differences in trust in NATO differed substantially before and after controlling for
acquiescence. Such effects of acquiescence on mean-level differences can occur if
acquiescence differentially affects item responding across countries. Moreover,
acquiescence may blur the intended factorial structure of a questionnaire by biasing item
variances and covariances (Rammstedt et al., 2010). Finally, it has been shown that
acquiescence can substantially bias the associations between personality items and
behavioral criteria, thereby attenuating predictive validity (Danner, Aichholzer, &
Rammstedt, 2015). Given the threats that acquiescence poses to the validity of
questionnaire-based data, the overall aim of the study reported here was to summarize and
integrate the available body of knowledge with regard to central socio-demographic and
social indicators into one single conceptual model encompassing the presumed determinants
of acquiescence. In what follows, we begin by summarizing the reported evidence on
individual-level determinants and then address country-level predictors.

<hs>  Individual-level predictors of acquiescent responding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Numerous studies have revealed that individuals differ systematically in their tendency to
acquiesce. However, the empirical evidence is not univocal. While some studies have
suggested that age is positively related to acquiescence (e.g., Meisenberg & Williams,
2008; Weijters, Geuens, & Schillewaert, 2010), others have failed to find evidence in
support of this notion (e.g., Eid & Rauber, 2000). Findings with regard to possible
effects of gender on acquiescent responding are even more heterogeneous. Some studies have
suggested that women show, on average, a higher tendency toward acquiescent responding
than men (e.g., Weijters et al., 2010), whereas others have found no gender effect (e.g.,
Marin, Gamba, & Marin, 1992). However, a broad consensus exists that educational
attainment is a source of systematic differences in the tendency to acquiesce. Results of
several studies have indicated that acquiescence appears to be more frequent among persons
with a lower level of educational attainment (e.g., Narayan & Krosnick, 1996; Rammstedt et
al., 2010; Rammstedt & Kemper, 2011). It has been suggested that persons with relatively
low education have less clear self-concepts, smaller vocabularies, and less developed
verbal comprehension skills than more highly educated persons. This may make them
relatively uncertain when it comes to responding to questionnaire items, and may thus
leave more room for the influence of systematic response biases (e.g., Goldberg, 1963).
For some countries (e.g., Germany), this inverse effect of education on acquiescence has
been widely replicated. Moreover, there is evidence to suggest that this effect can be
replicated in several other countries, albeit with some exceptions (Danner et al., 2015;
Rammstedt, Kemper, & Borg, 2013). However, results do not indicate a simple
generalizability of the inverse effect of education on acquiescence across all countries
(Meisenberg & Williams, 2008; Rammstedt et al., 2013). Rather, countries appear to differ
systematically in this regard. Moreover, Smith and Fischer (2008) were able to show that
individual-level interdependence, used as a proxy for a collectivistic cultural
orientation, was positively related to acquiescence. Taken together, the literature on
individual-level determinants of acquiescence partially supports the role of age, gender,
level of educational attainment, and degree of conservatism in acquiescent responding.

<hs>  Country-level predictors of acquiescent responding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In addition to individual differences in acquiescent responding, recent research has
identified cross-national differences in the tendency to acquiesce, as reflected by mean-
level differences (e.g., Javeline, 1999; Johnson, Kulesa, Cho, & Shavitt, 2005). For
example, Van Herk, Poortinga, and Verhallen (2004) investigated acquiescent response
tendencies in six European countries. The results revealed that respondents in the
Mediterranean countries scored higher on acquiescence than those in the Northwestern
European countries. A worldwide investigation of acquiescence was conducted by Meisenberg
and Williams (2008). Based on the World Value Survey conducted in 80 countries, they
showed that response styles were most prevalent in less developed countries and that—at
the country level—acquiescence could best be explained by the country's corruption level.
The authors interpreted their findings by suggesting that people who live in corrupt
societies tend to be subservient to powerful others—a tendency that carries over into
their survey responses. A similar effect was reported by Smith (2004), suggesting that
acquiescence is significantly less pronounced in certain European countries than in
countries with lower levels of economic development such as Panama, Nigeria, or the
Philippines. In addition, there is a broad consensus that response styles are
systematically related to cultural variables (Hofstede, 2001; Schwartz, 1994) and that
they tend to be more pronounced in traditional cultures (Javeline, 1999). Specifically,
several studies have suggested that the prevalence of acquiescence differs across
countries and depends on cultural orientations. For example, a study by Johnson et al.
(2005) indicated that collectivistic cultures were especially prone to acquiescent
responding. The authors hypothesized that members of collectivistic nations experienced
greater cultural pressure to acquiesce (Smith & Fischer, 2008). Support for this
association was also provided by Harzing (2006), who investigated 26 countries from all
major cultural clusters in the world. However, Grimm and Church (1999) could not confirm
the effect of collectivism on acquiescence response style. In sum, the results of cross-
national comparative research suggest that there are systematic differences between
countries with regard to the mean tendency to acquiesce and that these differences are a
function of the country's social and economic situation and its cultural orientations—in
particular, the degree to which collectivistic values are endorsed. Thus, we expect that
individual differences at the country level can be explained by these variables.

<hs>  Assessing acquiescent responding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Even though the nature of, and the reasons for, acquiescence are still unclear, different
approaches are used to investigate a person's tendency toward acquiescence. Some
studies—especially those that use only positively keyed items—use the percentage or ratio
of items agreed with (e.g. Harzing, 2006). For this approach, too, different methods of
including and weighting the responses are employed across studies. Instead of using only
positively keyed items, recent studies (e.g. Johnson et al., 2005, Rammstedt & Kemper,
2011; Rammstedt & Farmer, 2013; Rammstedt et al., 2010, 2013; Soto et al., 2008) have
used, whenever possible, pairs of positively and negatively coded items assessing the same
construct (e.g., Prefer to be with others and Like to be all by oneself). Persons with a
high tendency toward acquiescence should have comparatively higher mean scores across
these item pairs than those with a lower tendency to acquiesce. Even though some studies
report only a weak consistency of acquiescence across different scales in general (e.g.
Ferrando, Condon, & Chico, 2004), other studies report latent correlations r > 0.71
between acquiescence indicators of such pairs of negatively and positively keyed items
(Danner et al., 2015).

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

As summarized above, past research has yielded evidence of individual-level determinants
(age, gender, and educational attainment) and country-level predictors (economic
development, degree of collectivism, corruption level) of the tendency to acquiesce.
However, previous studies have yielded inconsistent findings with regard to these
characteristics. These inconsistencies may be due to the fact that most of these studies
used highly selective samples that were not representative of the respective populations.
In addition, to date no study has concurrently and systematically investigated these
country-level and individual-level characteristics, taking into account the multilevel
interrelationships between them. The present study aimed to fill this gap by investigating
potential determinants of acquiescence by simultaneously analyzing the different country-
level and individual-level characteristics and by relying on data that were representative
of the population in 20 European countries. Specifically, we investigated the impact on
the tendency toward acquiescent responding of the country-level characteristics economic
wealth (GDP), corruption level, and level of collectivism in combination with the
individual characteristics age, gender, educational level, and degree of conservatism.
Individual-level and country-level predictors can be combined in one multilevel model
where respondents (i) are nested within countries (j), and differences in acquiescence at
the respondent level are modeled as acquiescence ij = β0j + β1(age) + β2(gender) +
β3(education) + β4(conservatism) + εij, and differences at the country level are modeled
as β0j = γ00 + γ01(wealth) + γ02(corruption) + γ03(collectivism) + υ0j.

<hs>  Data source</hs>
  ~~~~~~~~~~~

The present analyses are based on data of the European Social Survey (ESS;
www.europeansocialsurvey.org/data). The ESS is a cross-national survey that investigates
changes in social structure, conditions, and attitudes in Europe. A key aim of the ESS is
to implement high quality standards in its methodology. These high quality standards are
especially relevant for the translation and adaptation of the questionnaires to guarantee
comparability across the different countries. The survey has been conducted every two
years since 2001. To test our conceptual multilevel model, we selected Round 1 of the ESS
(European Social Survey Round 1 Data, 2002) as a data source because it included several
contrasting item pairs that had already been used in an earlier study as an indicator for
acquiescence (Johnson, Mohler, Harkness, & Braun, 2010).

<hs>  Samples</hs>
  ~~~~~~~

The 2002 round of the ESS collected data from 22 European countries. For the present
analyses, only those countries for which all relevant indicators were available were
included. Therefore, Italy and Luxembourg were excluded from our analyses because
conservatism was not assessed in these countries. A list of the countries included in our
analyses can be found in Table 1. In each country, a sample representative of the
population aged 15 years and over was drawn. Design weights provided in the data set were
applied to adjust for different selection probabilities. The number of interviews
conducted ranged between 1360 in the Czech Republic and 2919 in Germany, with a total
sample size of 39,600 respondents. ESS questionnaires are administered as face-to-face
interviews. Participation is voluntary and not usually incentivized—although some
countries offer small incentives in order to increase participation. (For a detailed
description of the samples and the assessment design, see European Social Survey Round 1
Data, 2002).

            <hss>Demographics</hss>

            Respondents' age was assessed in ESS Round 1 via the year of birth. Gender was
            assessed in ESS Round 1 with a dichotomous variable (1 = men, 2 = women).
            Levels of educational attainment were assessed in all countries on the basis
            of the national education system. Later, the ESS researchers harmonized these
            national data into one variable with reference to the International Standard
            Classification of Education (ISCED) 1997 levels, which yielded five
            categories: (1) “Less than lower secondary education (ISCED 0–1)”; (2) “Lower
            secondary education completed (ISCED 2)”; (3) “Upper secondary education
            completed (ISCED 3)”; (4) “Post-secondary, non-tertiary education completed
            (ISCED 4)”; (5) “Tertiary education completed (ISCED 5)”.

            <hss>Conservatism</hss>

            As a supplement to the ESS, the Portrait Values Questionnaire (PVQ; Schwartz,
            Melech, Lehmann, Burgess, & Harris, 2001) was administered, allowing, among
            other things, the assessment of the higher order value dimension conservatism,
            which overlaps strongly with the cultural orientation collectivism as defined
            by Hofstede (see, e.g., Schwartz & Ros, 1996). The conservatism dimension
            includes the lower order scales conformity, tradition, and security. It
            includes items such as “She/he believes that people should do what they're
            told” (conformity). All items are to be answered on a six-point scale ranging
            from not like me at all to very much like me. Cronbach's alpha ranged between
            0.67 (Hungary) and 0.78 (Austria).

            <hss>Economic wealth</hss>

            As an indicator for the economic wealth of each country, the logarithm of its
            gross domestic product (GDP, adjusted for purchasing power) averaged across
            the years 1990 to 2002 (as suggested by Meisenberg & Williams, 2008), was
            used. Information was retrieved from the World Development Indicators of the
            World Bank (data.worldbank.org/data-catalog/world-development-indicators).

            <hss>Corruption level</hss>

            A measure of the corruption level per country was obtained based on averaged
            scores of Transparency International's Corruption Perceptions Index for the
            years 1999–2005 (transparency.org).

            <hss>Collectivism</hss>

            Country-level scores on an individualism-collectivism scale for the 20
            countries investigated in the present study were taken from Hofstede (2001).

        <hss>Acquiescence</hss>

        As an indicator of acquiescent responding, an acquiescence measure was constructed
        on the basis of eight pairs of survey responses from the ESS questionnaire. These
        item pairs, which constituted sets of statements that clearly represented opposing
        opinions, stem from different question blocks within the ESS questionnaire and are
        intended to measure different constructs ranging from socio-political evaluations
        to attitudes toward migrants. A full list of these item pairs can be found in
        Table S1. All items were to be answered on a five-point Likert scale ranging from
        agree strongly to disagree strongly. In line with earlier research (Aichholzer,
        2014; Billiet & McClendon, 2000; Danner et al., 2015; Rammstedt et al., 2010;
        Rammstedt & Kemper, 2011; Rammstedt & Farmer, 2013), we scored the acquiescence
        scale by averaging all 16 items. Given that eight items were positively keyed and
        eight items were negatively keyed, the resulting mean score does not reflect any
        construct variance but rather only acquiescence (and random measurement error). We
        estimated the reliability of the acquiescence index by subtracting each item from
        its opposing item and subsequently calculated Cronbach's alpha. Cronbach's alpha
        was 0.47 on average and varied between 0.39 (Denmark) and 0.58 (Greece).1 Table 1
        provides an overview of the distribution of the different indicators investigated
        in the 20 countries.

<h>RESULTS</h>
-------

In a first step, we investigated whether the 20 countries differed in their tendency
toward acquiescent responding. We specified a baseline multilevel model with respondents
(i) being nested within countries (j), acquiescenceij = β0j + εij that allowed
acquiescence differences between countries, β0j = γ00 + υ0j. The model parameters were
estimated using the residual maximum likelihood estimator implemented in SAS 9.3. The
model revealed an intra-class correlation of ICC = 0.15, which indicates that 15% of the
total acquiescence variance can be explained by systematic country differences. Hence, the
20 European countries investigated differed systematically in their mean tendency toward
acquiescent responding. On average, the highest acquiescence scores were found in Greece,
followed by Portugal and Poland; the lowest mean acquiescence scores were found in Norway,
the Netherlands, and Denmark (see Table 1). In a second step, we concurrently investigated
different possible determinants of these between-country and within-country differences in
acquiescent responding: We conducted a second multilevel analysis with age, gender,
educational level, and the degree of conservatism as individual factors: acquiescenceij =
β0j + β1(age) + β2(gender) + β3(education) + β4(conservatism) + εij. At the country level,
we investigated economic wealth, corruption level, and degree of collectivism: β0j = γ00 +
γ01(wealth) + γ02(corruption) + γ03(collectivism) + υ0j. The intercorrelations between the
individual-level predictor variables and between the country-level predictors are shown in
Table S2. They indicate that GDP and collectivism, in particular, are moderately
interrelated (− 0.42). The results of the second multilevel model fitted to the data are
shown in Table 2. With the exception of GDP, all country-level predictors contributed
significantly to explaining the tendency to acquiesce. The highest—and following Cohen
(1992) a large — effect on acquiescence was estimated for the country's corruption level
(η = 0.473): The higher the level of corruption, the greater was the tendency toward
acquiescence in that country. A country's level of collectivism also had a large effect on
acquiescence (η = 0.187): The more collectivistic the country, the higher was the overall
tendency to acquiesce. In addition to the country's cultural orientation, the individual's
degree of conservatism was the strongest predictor of acquiescence at the individual level
(η = 0.045) although this effect was small to moderate in size. Further variance in
acquiescence could be explained by the individual's level of education (η = 0.029). Thus,
at the individual level, respondents with a low degree of conservatism and with a lower
level of educational attainment exhibited a higher tendency toward acquiescent responding.
Most likely due to the large sample size, the effect of age and gender was also
statistically significant. However, age contributed only marginally (η = 0.004) to
explaining the variance in our model, and gender did not explain a substantial portion of
the variance at all. Overall, at respondent level, education, age, gender, and degree of
conservatism explained 10% of acquiescent responding, and at country level, wealth, degree
of collectivism, and corruption level explained 74% of acquiescent responding. To ensure
that our results were not due to capitalizing on chance and that they were not biased by
the correlation between GDP, collectivism, and conservatism at the country level, in
particular, we conducted a set of robustness checks. First, we cross-validated the results
of the multi-level analyses by randomly splitting each country sample into two subsamples
and then replicated the analyses for both splits. The pattern of results was very similar
for both splits, which suggests no effect of capitalization on chance (see Table S3). In
addition, we investigated the biasing effect of the intercorrelations of our predictors at
the country level. We therefore excluded each of these three variables in turn from the
analyses. The pattern of the results was highly comparable to that originally found (see
Table S4). We also investigated whether the association between acquiescence and age,
gender, education, or conservatism differed between countries and specified the
associations as random effects which did not change the pattern of results (all ∆ β <
0.002). Finally, we also investigated whether our measure of acquiescence and our
conservatism measure were invariant across countries. In particular, we investigated
configural invariance (same factor structure), metric invariance (same factor loadings),
and scalar invariance (same factor loadings and same intercepts) with multi-group
structural equation models. The metric invariance models showed acceptable model fits
(RMSEA < 0.07, SRMR ≤ 0.05), whereas the scalar invariance model revealed a poor model fit
for both scales (RMSEA > 0.11, SRMR > 0.10). Likewise, the change in RMSEA (∆ RMSEA <
0.015) and SRMR (∆ SRMR < 0.030) also suggest accepting metric invariance for both scales
(Chen, 2007).2

<h>DISCUSSION</h>
----------

The aim of the present study was to develop and test a comprehensive model encompassing
individual-level determinants and country-level predictors of the tendency toward
acquiescent responding in surveys. Our results corroborate systematic differences in
acquiescence between countries: 15% of the variance in acquiescence could be explained by
country differences, while the remaining 85% was due to individual variations among the
respondents within countries. Thus, the European countries included in our study differed
substantially in their tendency toward acquiescence. With our set of predictors we were
able to explain three-quarters of the country-level differences. The most central
indicator explaining these differences in acquiescence between countries was the
corruption level of the respective countries, followed by differences in their respective
cultural orientations. The higher the corruption level and the level of collectivism of a
country, the greater was the overall tendency to acquiesce. By contrast, the economic
wealth of the country had no significant additional effect on acquiescence. These results
support Meisenberg and Williams' (2008) assumption that people living in corrupt societies
are more subservient to powerful others. However, it has to be kept in mind that the
present study investigated only European and thus comparatively wealthy countries. It
needs, therefore, to be investigated in future studies if economic wealth has an
additional effect on acquiescence based on a more heterogeneous set of countries.
Individual indicators such as educational level and degree of conservatism differed
systematically across the countries and thus contributed to the explanation of the
between-country differences in this response style. Moreover, besides these differences
between countries, our results revealed systematic differences between subpopulations:
Some subpopulations within countries were more prone to acquiescence than others. Ten
percent of these individual differences could be explained by our set of predictors. In
line with previous research (e.g., Narayan & Krosnick, 1996; Rammstedt et al., 2010), our
results revealed that—across all countries—individuals with lower levels of educational
attainment and less conservative individuals were more prone to acquiescent responding
than higher educated and more conservative individuals. In contrast, the effect reported
in earlier studies (see Weijters et al., 2010) that females have, on average, a higher
tendency toward acquiescence could not be replicated. Rather, we found a statistically
significant but not substantial effect of gender that indicated a slightly greater
tendency toward acquiescence on the part of males compared to females. Earlier findings
with regard to the effects of age on acquiescence were inconsistent. While some studies
suggested that older individuals have a greater tendency toward acquiescence (e.g.,
Meisenberg & Williams, 2008; Weijters et al., 2010), others identified no substantial
effect of age (e.g., Eid & Rauber, 2000). Our results support these albeit somewhat
contradictory findings insofar as we found a small statistically, but not practically,
significant effect of age in the suggested direction. In sum, our results support the
notion that the corruption level and the cultural orientation of a country, in particular,
explain cross-national differences in acquiescent responding. Taking these indicators into
account, the economic wealth of a country was not found to contribute to the explanation
of cross-national differences. This contrasts with findings of previous studies that did
not control for other indicators. Overall, our study substantially contributes to an
understanding of cross-national differences in acquiescent responding. Systematic cross-
national response artifacts, as detected in our study, may be misinterpreted as
substantive differences across countries or cultures. Therefore, before drawing any
conclusions from cross-national surveys, due caution should be taken to reduce
acquiescence ex ante (e.g., by using balanced scales; Billiet & McClendon, 2000) or to
control for acquiescence ex post (e.g., by using ipsatized data; Brown & Maydeu-Olivares,
2011). Typical areas of application for such ex-ante or post-hoc measures aimed at
reducing acquiescence are all questionnaire-based data collections performed in
multinational, multicultural, and multiregional contexts. Examples include, but are not
limited to, international employee surveys (e.g., Johnson et al., 2005), cross-national
media usage studies (e.g., Kuru & Pasek, 2016), and cross-cultural health surveys (Shavitt
et al., 2016). In all these areas, variations in acquiescence carry the danger of being
misinterpreted as differences in organizational commitment, media exposure habits, or
health-related compliance. Therefore, mindfully considering and correcting for
acquiescence should yield a more accurate picture about ‘true’ differences, and help to
prevent deriving inappropriate subsequent measures.


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<ART>Affective facial expression in sub-clinically depressed and non-depressed mothers during contingent and non-contingent face-to-face interactions with their infants
================================================================================

Authors: Hanne Cecilie Braarud, Siv Skotheim, Kjartan Høie, Maria Wik Markhus, Marian Kjellevold, Ingvild Eide Graff, Jan Øystein Berle, Kjell Morten Stormark
DOI: 10.1016/j.infbeh.2017.05.004
Year: 2017  |  Pages: 98-104
ASJC codes: 3204
Keywords: Affective facial expression, Double video study, Maternal depression, Mother-infant interaction

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background Depression in the postpartum period involves feelings of sadness, anxiety and irritability, and attenuated feelings of pleasure and comfort with the infant. Even mild- to- moderate symptoms of depression seem to have an impact on caregivers affective availability and contingent responsiveness. The aim of the present study was to investigate non-depressed and sub-clinically depressed mothers interest and affective expression during contingent and non-contingent face-to-face interaction with their infant. Methods The study utilized a double video (DV) set-up. The mother and the infant were presented with live real-time video sequences, which allowed for mutually responsive interaction between the mother and the infant (Live contingent sequences), or replay sequences where the interaction was set out of phase (Replay non-contingent sequences). The DV set-up consisted of five sequences: Live1-Replay1-Live2-Replay2-Live3. Based on their scores on the Edinburgh Postnatal Depression Scale (EPDS), the mothers were divided into a non-depressed and a sub-clinically depressed group (EPDS score ≥ 6). Results A three-way split-plot ANOVA showed that the sub-clinically depressed mothers displayed the same amount of positive and negative facial affect independent of the quality of the interaction with the infants. The non-depressed mothers displayed more positive facial affect during the non-contingent than the contingent interaction sequences, while there was no such effect for negative facial affect. Conclusions The results indicate that sub-clinically level depressive symptoms influence the mothers’ affective facial expression during early face-to-face interaction with their infants. One of the clinical implications is to consider even sub-clinical depressive symptoms as a risk factor for mother-infant relationship disturbances.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The caregiver displays multimodal emotional expressions during early social interaction
with the infant, such as affective facial expression, gaze, physical touch, and
vocalization (Stern, 1974). The affective quality and contingency are important components
during early face-to-face interaction (Bornstein & Manian, 2013). The infant is, through
her/his intersubjective awareness (Trevarthen, 2011), receptive to the caregiver’s
affective expressions, as well as attuning his/her internal state for emotional sharing
with the caregiver during early interactions (Trevarthen, 1980, 2001; Trevarthen & Aitken,
2001). An increasing body of research have shown how the infant is intuitively social, and
how this shapes the affective relations with shared meaning between the caregiver and the
infant (for a review see Trevarthen and Delafield-Butt, 2017). Postpartum depression, both
in mothers (Goodman et al., 2011) and fathers (Ramchandani, Stein, Evans, & O'Connor,
2005), is associated with adverse child outcomes. Based on a meta-analysis of 193 studies
Goodman et al. (2011) found that maternal depression was significantly related to higher
levels of internalizing- and externalizing behavioral problems and general psychopathology
in children, and that these associations were strongest for younger children. The
mechanisms that explain these associations are not clear, but regulation of emotions in
the early transactions between the mother and the infant is suggested as possible
mechanisms (Field, Healy, Goldstein, & Guthertz, 1990). Maternal depression is associated
with impairment in the mother’s capacity to synchronize with the infant’s positive
affective state, as well as increased negative affect and irritation or intrusiveness
during face-to-face interaction (Cohn, Campbell, Matias, & Hopkins, 1990). Based on
findings from their meta-analytic review, Lovejoy and colleagues suggested that the
parenting difficulties experienced by depressed mothers may not be associated with
depression per se, but rather to more general distress associated with having
psychological problems (Lovejoy, Graczyk, O'Hare, & Neuman, 2000). Thus, even sub-clinical
levels of depression may influence the early mother-infant interaction negatively. It has
been suggested that a mild-to-moderate depression has a more selective impact on maternal
behavior during early mother-infant interaction, in terms of the mothers contingent
responsiveness and affective availability (Hoffman & Drotar, 1991). In an earlier
experimental perturbation study with sequences of real-life contingent interactions and
with sequences where the interactions were set out of phase, we found that infants of sub-
clinically depressed mothers were less sensitive to the interruptions of the contingency
than were infants of non-depressed mothers (Skotheim et al., 2013). A possible explanation
of this finding is that the infants of the sub-clinically depressed mothers were more
accustomed to non-contingent interaction. The purpose of the present study was to
investigate if even sub-clinical levels of depression may impact maternal behavior and
affective responsiveness during sequences of mutually face-to-face interaction with their
infants and when the interaction are set out of phase, using the double video (DV) set-up.
Field et al. (2005) found in a similar perturbation DV design that clinically depressed
mothers displayed the same amount of positive affect both before and after the interaction
with their infant was set out of phase, while the non-depressed mothers displayed reduced
positive affect after the perturbation of the interaction. Nadel et al. (2005) found, also
using the same design, that both the non-depressed and the clinically depressed mothers
evidenced a similar decrease in positive affect after the perturbation of the interaction.
However in both studies (Field et al., 2005; Nadel et al., 2005), the mothers were told in
advance about of the perturbation, which may have influenced the interactions with their
infants. In addition, the clinically depressed mothers in Field et al’s (2005) study
displayed less positive affect than the non-depressed mothers already from the start of
the experiment, which suggests that the results may be attributable to an effect of
maternal depression and not the manipulation of contingency. In the present study the
mothers focus of gaze and facial expression of affect were examined in groups of sub-
clinically depressed and non-depressed mothers during face-to-face interaction with their
infants. This was examined, drawing on the same sample of sub-clinically and non-depressed
mothers as in Skotheim et al. (2013). In the present study, we examined the mothers’
responses to live (contingent) and non-contingent interaction with their infants. More
specifically, we investigated if sub-clinically depressed mothers would change their focus
of gaze and facial expression of affect in response to shifts between contingent
interaction and non-contingent interaction in a DV-experiment.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Fifty-one mothers and their three months old infants took part in this study. The
participants were drawn from a prospective longitudinal population-based study on
nutrition, mental health and infant development (Markhus et al., 2013) where all the
mothers (n = 105) were asked to participate in the current study. Informed consent was
obtained from 51 mothers. Twelve mother-infant dyads had to be excluded from the analyses,
either because of excessive infant crying (n = 5), or because the mother and the infant
did not manage to establish mutual gaze contact at the start of the experiment (n = 7).
Thus the final sample comprised 39 mothers (mean age = 32 years, range 21–41 years) and
their three months old infants (mean age = 13 weeks, range 9–20 weeks; Boys = 16 (41%).
None of the mothers fulfilled the DSM-IV criteria for major depression, based on the
clinical interview with the Norwegian version of the MINI International Neuropsychiatric
Interview (MINI; Leiknes, Malt, & Malt, 2007; Sheehan et al., 1998). The mothers were
divided into two groups, based on their levels of self-reported depressive symptoms on a
validated Norwegian version of the Edinburgh Postnatal Depression Scale (EPDS; (Berle,
Aarre, Mykletun, Dahl, & Holsten, 2003), using an EPDS total cut-off score ≥6 (Nadel et
al., 2005). Twenty-four mothers were categorized as non-depressed (mean EPDS score 3.26,
range 0–5) and 15 mothers were categorized as sub-clinically depressed (mean score of
8.26, range 6–13). There were no significant differences between the two groups, neither
for infant age or gender nor maternal marital status, parity, educational level or yearly
income. All the mothers received written information about the study prior to giving their
written consent on behalf of themselves and their infant. The study was approved by the
Regional Committee for Medical and Health Research Ethics and the Norwegian Social Science
Data Services. The procedures followed were in accordance with the Helsinki Declaration of
1975 (revised in 2008).

        <hss>The double video set-up</hss>

        The double video set-up and equipment were identical to the Skotheim et al. (2013)
        study. The mother and the infant were placed in two separate sound-proof rooms,
        where they were seated in front of a one-way mirror that enabled them to see a
        life size image of each other’s faces/upper bodies (see Fig. 1). Each one-way
        mirror was positioned in a 450 gradient in front of both the mother and the
        infant, with a LCD-monitor lying flat below. A SONY HDR-HC7E digital video camera
        was placed behind each of the two one-way mirrors, allowing the infant and the
        mother to have direct eye contact with each other while they were looking straight
        into the camera. The cameras in each room recorded the video stream with 25
        frames-per-second. The video was transmitted over firewire to the two computers
        PC1 and PC2 respectively and further in an uncompressed format over a high speed
        wired network to a control-PC (PC3). During piloting the DV set-up, calculation of
        the length between each sequence showed a pause from 150 to 250 ms. The partners
        could not be aware of this pause when interacting together. The mothers and the
        infants vocalizations were captured by microphones integrated in the video cameras
        and was embedded in the video stream. The mothers used earplugs to avoid audio
        feedback. At PC3, the researcher (SS) could monitor the video captured by the two
        computers. This design enabled the researcher to monitor the mother- infant
        interaction and start and stop the experiment. All recorded videos were stored on
        PC1 and PC 2 during the experiment, and then copied to an external hard disk for
        further analyses. As in our previous studies (Braarud & Stormark, 2006, 2008;
        Skotheim et al., 2013; Stormark & Braarud, 2004), the DV experiment comprised five
        sequences in a fixed Live1-Replay1-Live2-Replay2-Live3 order. All five sequences
        consisted of a 60 s interval, in which video-recordings were made of the mother’s
        and the infant’s behavior. The three live sequences all consisted of uninterrupted
        face-to-face interaction. In the first replay sequence, the mother saw and heard
        the infant live while the infant was responding to a replay of the mother from the
        previous live sequence. In the second replay, the mother received a replay of the
        infant’s behavior from the first live sequence. These modifications enabled us to
        control for possible memory bias, since the replay sequences represented two
        different types of non-contingency. The mothers in the present study were naive
        with respect to the experimental manipulation, in contrast to Nadel et al. (2005)
        and Field et al. (2005).

<hs>  Measures</hs>
  ~~~~~~~~

Before entering the study, the mother’s level of depressive symptoms had been assessed
with the Norwegian version of The Edinburgh Postnatal Depression Scale (EPDS; Berle et
al., 2003; Cox et al., 1987), as part of their visit to the well-baby clinic. The EPDS is
a 10-item self-report scale that assesses current (last week) postpartum depressive
symptomatology. Each item is rated on a 4-point scale (0–3), yielding a total score
ranging from 0 to 30, with higher scores indicating increased symptomatology of postpartum
depression. A Norwegian (Leiknes et al., 2007) version of MINI (Sheehan et al., 1998) was
administrated as part of the study to determine if any mothers fulfilled axis I diagnoses
in the Diagnostic and Statistical Manual of Mental Disorders (DSM IV).

<hs>  Procedure</hs>
  ~~~~~~~~~

When arriving at the laboratory, the mothers were first interviewed with the Norwegian
version of MINI 5.0.0. After the interview, the mothers were explained that the purpose of
the study was to investigate face-to-face interaction between mothers and infants, using a
closed-circuit video and computer system. The mothers were told to engage with their
infant as during normal interaction. When the mother and the infant had adjusted to the
laboratory setting, they were seated in each of the rooms where they could see and hear
each other through PC1 or PC2, respectively. When the experimenter (SS) judged that the
mother and the infant had established a stable eye-to-eye contact, the experiment started.

<hs>  Coding and reliability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The mothers’ gaze foci and facial affective expression were scored independently, using
The Observer XT 9. The mutually exclusive categories were Focus of gaze (looking at
partner, looking away from partner, indefinite focus; see Stormark and Braarud (2004)).
For Facial expression, the mutual exclusive categories were positive affect (smiling;
simultaneous raising of lip corners), negative affect (frowning; lowering of eyebrows, eye
squeeze and deepening of the nasolabial furrow) and neutral facial expression (in
accordance with Nadel et al. (2005)). Two independent coders were trained to score the
mothers’ focus of gaze and facial expression of affect. They were blind to which sequence
they were scoring, and blind to the clinical assessment of the individual mother.
Calculation of inter-rater reliability based on eight mothers gave a Cohen’s kappa for
gaze focus (k = 0.97) and facial affective expression (k = 0.67).

<hs>  Statistics</hs>
  ~~~~~~~~~~

The data on maternal gaze focus was subjected to a separate two-way split-plot ANOVA
involving Group (non-depressed mothers vs. sub-clinically depressed mothers) x Sequence
(Live1, Replay1, Live2, Replay2, Live3). The data on positive and negative facial
affective expression was subjected to separate three-way split-plot ANOVAs involving Group
(non-depressed mothers vs. sub-clinically depressed mothers) x Affect (positive vs
negative affect) x Sequence (Live1, Replay1, Live2, Replay2, Live3). To investigate if the
mothers behavior were related to shifts between contingent and non-contingent infant
behavior, rather than general fatigue, the number of live sequences had to exceed the
number of replay sequences. As a result, the research question could not be fully
evaluated in an omnibus ANOVA. Therefore the dataset was examined in a priori comparisons
(planned comparisons of contrast variables (Hays, 1988), so the live and replay sequences
could be weighted equally. The statistical analyses were carried out with STATISTICA 64,
StatSoft, Inc.

<hs>  Mothers’ gaze focus</hs>
  ~~~~~~~~~~~~~~~~~~~

There was a significant main effect of gaze focus (F(1.37) = 23618, p< 0.001), independent
of Sequence and Group, which reflects that the mothers looked at their infants almost
exclusively during the experiment (see Fig. 2). There were no main effect of Sequence and
no interaction effect between Group and Sequence. However, planned comparisons revealed a
non-significant (p = 0.06) linear trend reflecting an increased maternal gaze focus at the
infants during the experiment in the sub-clinically depressed mothers.

<hs>  Mothers’ facial expression of positive and negative affect</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There was no main effect of Group, but there was a significant main effect of Affect,
reflecting that the mothers, independent of group and sequence displayed significantly
more positive than negative affect during the experiment (F(1.37) = 409.98, p < 0.0001),
see Fig. 3 and Fig. 4. There was also a main effect of Sequence (F(4148) = 5.66, p <
0.001), and an interaction effect of Affect and Sequence (F(4148) = 6.55, p < 0.001),
reflecting that there was overall more positive affect during the Replay than the Live
sequences (F(4, 144) = 4.64, p < 0.05), while there was no such sequential effect of
negative affect. Planned comparisons revealed further that there was a linear decrease in
positive affect across sequences, in both the sub-clinically depressed (F(1, 37) = 9.75, p
< 0.01), and the non-depressed mothers (F(1, 37) = 4.72, p < 0.05). There were no
significant differences for negative affect, neither for groups nor across sequences.
Further planned comparisons revealed that the non-depressed mothers displayed
significantly more positive affect during the Replay sequences (Replay 1–2 averages) than
during the Live sequences (Live1-3 averages; F(1, 37) = 5.28, p < 0.05), while there was
no such difference in the sub-clinically depressed mothers. There were no differences in
positive and negative affect between the two groups, neither for the Live nor the Replay
sequences.

<h>DISCUSSION</h>
----------

The main findings in this study were first that the sub-clinically depressed mothers did
not discriminate with respect to the manipulation of the contingency, but expressed the
same amount of facial affect during contingent and non-contingent interactions with their
infants. The non-depressed mothers evidenced significantly higher amount of positive
affect during the replay sequences compared to the live sequences. Both groups of mothers
showed a high amount of gaze focus at their infant, and both groups of mothers showed a
linear decrease in positive affect during the experiment. In line with earlier studies
that focus on the interactive behavior of depressed mothers (Cohn et al., 1990; Field,
1984), we could expect that the sub-clinically depressed mothers, compared to the non-
depressed mothers, would express less positive and more negative affect during the
experiment. Instead, our results show that the sub-clinically depressed mothers expressed
the same amount of positive affect as the non-depressed mothers, but without
discriminating between the sequences that allowed for contingent interaction and the
sequences that did not. In fact there were no overall differences in amount of positive
affect between non-depressed and sub-clinically depressed mothers, which accords with
Nadel et al.’s (2005), but not with Field et al.’s (2005) study. However, while the sub-
clinically depressed mothers in the present study did not discriminate between contingent
and non-contingent interactions with their infants, the non-depressed mothers were
affected by the subtle experiential differences between live- and replay sequences. While
earlier studies have shown a decrease in infant directed speech in the replay-sequences
(Braarud & Stormark, 2008; Murray & Trevarthen, 1986), we found more positive affect in
the replay than the live sequences during this double video experiment. Pechtel et al.
(2013) suggested that sensitive and attuned mothers would be able to continue with
maternal engagement and sensitive regulation of the infant, even in emotional arousing
caregiving situations evoked by infant distress. The non-depressed mothers behavior
responses could therefore be related to their infants affective display during the replay
sequence, and not necessarily to the lack of contingent responses from the infants. Thus,
when the non-depressed mothers experienced a reduction of smiling from their infants in
Replay 1, the mothers could respond with sensitive regulation in an attempt to regulate
the infants toward a more positive state (Feldman, 2003). However, since the replay-
sequences impede on establishing mutual synchrony, one may speculate if the non-depressed
mothers decrease in smiling in the following live-sequence could be understood as a
response to the failure of regulating their infants. Replay2 would represent yet another
and equal perturbation as the mothers received a replay of the infants behavior from
Live1. The mothers saw and heard the infants behavior from what was an optimal social
situation, but where the contingency was interrupted. An alternative and more general
explanation could be that the mothers are used to a greater degree of variability in
infant responsiveness, and need more time before they detect the perturbation of
contingency in the replay sequences (Henning & Striano, 2011). Results from earlier double
video studies (Field et al., 2005; Nadel et al., 2005; Stormark & Braarud, 2004) accords
with the present finding that both groups of mothers in the present study expressed high
amount of gaze at their infants independent of the quality of contingency. However,
mothers infant-directed speech (content, stylistic features and the fundamental frequency
(F0)) seems to be modulated according to changes in social contingency during mother-
infant face-to-face interactions (Braarud & Stormark, 2008; Murray & Trevarthen, 1986). If
one considers that the internal processes of reactivity and regulation in the caregiving
system are related to the infant’s affective cues, one could speculate whether the
mothers’ affective facial responses, gaze focus and infant-directed speech have different
meaning during early social interactions. Van Egeren et al. (2001) found that maternal and
infant vocalization was the primary response in their microanalyses of mother-infant
responsiveness when the infants were 4 months old. The results accentuate that maternal
sub-clinical depression influence sensitivity to social contingency and affective behavior
during mother-infant face-to-face interaction, which is in line with Hoffman and Drotar
(1991). The unexpected high amount of positive affect in the group of sub-clinically
depressed mothers may be attributed to the experimental setting. Even if the mother and
the infant are physically separated during the experiment, the DV set-up optimizes face-
to-face interaction, without any disturbances found in natural circumstances. This
interpretation is supported by the fact that the mothers had nearly 100% amount of gaze
focus at their infants in all sequences. So, even if the mothers and the infants in the
sub-clinically depressed group may have more dyadic difficulties in their daily
interactions (Reck et al., 2004), the DV set-up could have been a positive interactional
experience for the mothers. However, the lack of sensitivity to social contingency found
in this study highlights the selective impact of maternal sub-clinical depressive symptoms
on early face-to-face interaction. One limitation of the study concerns the DV design and
ecological validity. Three months old infants and their caregivers spend most of their
awakening hours in physically close contact during normal situations (Trevarthen, 1979).
In this study, the infant and the mother sat in two separate rooms where they can interact
via PCs, which might be experienced as artificial. The linear decrease in positive affect
for both groups of mothers could be understood as a sign of minor, but increasing distress
during the experimental procedure. Still, even in this artificial environment, the
experiment also demonstrated three-month-olds interest in face-to-face communication,
which also could explain why only five recordings had to be stopped because of excessive
crying. We also acknowledge that there are factors that affect the mother-infant
interaction and dyadic regulation that are not addressed in this study. Infant temperament
is one such factor, even though we have earlier reported that there was no significant
difference in temperament between the two groups of infants (Skotheim et al., 2013).

<h>CONCLUSION</h>
----------

To sum up the sub-clinically depressed mothers displayed the same amount of positive
affective facial expression independently of the quality of the interactions with their
infants, while the non-depressed mothers displayed a decrease in positive affect after the
sequences where the interaction with their infants were set out of phase. There was a
linear decline in positive affect across the five sequences for both groups of mothers,
which suggests that both groups experienced an increase in distress during the experiment.
These results strengthen the findings in Skotheim et al.’s (2013) study, where the infants
of the sub-clinically depressed mothers were less sensitive to the quality of the
affective interaction with the mothers than the infants of the non-depressed mothers were.
Both studies illustrate the importance of the mother’s well-being for early mother-infant
interactions and optimal infant development.


<h>REFERENCES</h>
----------

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<ART>Age attenuates noise and increases symmetry of head movements during sleep resting-state fMRI in healthy neonates, infants, and toddlers
================================================================================

Authors: Kristina Denisova
DOI: 10.1016/j.infbeh.2019.03.008
Year: 2019
ASJC codes: 3204
Keywords: Human brain development, Movement, Neonate cognition, Sleep, rs-fMRI

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Newborns produce spontaneous movements during sleep that are functionally important for their future development. This nuance has been previously studied using animal models and more recently using movement data from sleep resting-state fMRI (rs-fMRI)scans. Age-related trajectory of statistical features of spontaneous movements of the head is under-examined. This study quantitatively mapped a developmental trajectory of spontaneous head movements during an rs-fMRI scan acquired during natural sleep in 91 datasets from healthy children from ∼birth to 3 years old, using the Open Science Infancy Research upcycling protocol. The youngest participants studied, 2–3 week-old neonates, showed increased noise-to-signal levels as well as lower symmetry features of their movements; noise-to-signal levels were attenuated and symmetry was increased in the older infants and toddlers (all Spearman's rank-order correlations, P < 0.05). Thus, statistical features of spontaneous head movements become more symmetrical and less noisy from birth to ∼3 years in children. Because spontaneous movements during sleep in early life may trigger new neuronal activity in the cortex, the key outstanding question for in vivo, non-invasive neuroimaging studies in young children is not “How can we correct head movement better?” but rather: How can we represent all important sources of neuronal activity that shape functional connections in the still-developing human central nervous system?

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

A complex process helps human newborns experience a structured world. This mechanism is
supported in part by the neuronal substrates with early-onset myelination, innately-driven
sensitivities as well as pre- and post-natal learning playing an important role in
development. Currently, little is known about the character and the contribution to this
process by the spontaneous, endogenous head movements produced during rest or sleep, even
though newborns naturally spend the majority of their time sleeping (Roffwarg, Muzio, &
Dement, 1966)—an important knowledge gap in our understanding about how the central
nervous system (CNS) develops in humans during early critical time period (early postnatal
life). Importantly, diverse types of motility occur throughout sleep, across the different
state epochs according to Prechtl (1974). Movements, including startles and mouthing,
occur during quiet sleep, QS (corresponding to the behavioral state 1) as well as active
sleep, AS (state 2), and twitches occur particularly during AS sleep (see, e.g. p. 209 in
Prechtl, 1974). Developmental or maturational character of spontaneous, endogenous
movements during sleep has not been mapped in human infants. An insight from biology is
that spontaneous, endogenous movements are a source of cortical stimulation in early life
and trigger, or are associated with, neuronal activity (Khazipov et al., 2004). In
anesthetized neonatal rats, the majority of the bursts in the primary somatosensory cortex
are “associated with overt movement, including isolated muscle twitches, limb and whole-
body jerks, crawling and sucking” (Khazipov et al., 2004). Recent work has focused on the
role of spontaneous movements during sleep for the developing CNS. Subtle, abundant, and
functionally highly important movements during sleep have been detected and described in
sleeping infant rats (Blumberg et al., 2015; Tiriac, Del Rio-Bermudez, & Blumberg, 2014).
It has been argued that twitches or jerky spontaneous movements in newborn rats, measured
during REM sleep (Rapid Eye Movement; corresponds to AS stage), lack corollary discharge
during sleep (compared to wakefulness), and as such, these movements would be expected to
affect the sensory system, generating concurrent neuronal bursts, and aiding in building
environment-appropriate sensorimotor maps for the developing infant (Blumberg et al.,
2015; Tiriac & Blumberg, 2016; Tiriac et al., 2014). Neuronal spiking increases after
twitches (Sokoloff, Uitermarkt, & Blumberg, 2015). It can be briefly noted that newborn
(P0, Postnatal day 0) or neonatal rats’ maturational stage corresponds to the second half
of gestation in humans, including the pre-term and near-term periods (Colonnese &
Khazipov, 2012). Generally, P10 in rodents corresponds to the third trimester in humans
and P13 corresponds to term, although variation in the maturational correspondence exists
for different brain regions. For example, term in humans is P5–7 for the hippocampus and
P12–14 for the visual cortex (Colonnese & Khazipov, 2012). Tiriac et al.’s studies
included P8–P10 infant rats, a range which approximately corresponds to near-term or term
in humans. Intriguingly, because new neuronal events may accompany spontaneous, endogenous
movements (whether such movements occur during quiet or active sleep in human neonates),
these neuronal events may assist with synapse formation and help build cortical
connectivity maps in the developing human CNS, in particular, the sensorimotor maps. None
of the non-invasive, in vivo functional neuroimaging approaches in use today with human
neonates, infants, and toddlers consider the importance of endogenous, self-generated
spontaneous movements while resting or sleeping for the developing mind and brain. Why is
this significant? The relevant caveat is that head or body movements have a deleterious
impact on the homogeneity of the magnetic field, and researchers use motion correction
strategies to correct high-movement volumes acquired during MRI scans, albeit with
downstream consequences for functional connectivity metrics and inference (Denisova,
2018). The problem is that such a motion correction strategy is incompatible with
extensive knowledge on the role of sensory inputs from spontaneous movements that are
triggers for neuronal bursts and synapse formation in early development (Khazipov et al.,
2004), the drivers of hemodynamics and hence functional connectivity measures that
developmental researchers seek to investigate. That is, functional connectivity studies,
which acquire data during natural sleep or rest in human neonates, infants, and toddlers,
set out to investigate correlations in subtle hemodynamic fluctuations between different
regions, but these studies suppress data acquired while subjects are moving before
applying statistical metrics. In summary, despite knowledge from animal work that neuronal
events of substantial importance to the maturing central nervous system occur due to
spontaneous movements, the potential functional role of these movements and of the new
neuronal events they generate, at least very early in infancy, is not given due
consideration in MRI research with human children. For instance, spontaneous movements in
humans could contribute significantly toward nascent functional connectivity. Do such
movements play a generative, rather than auxiliary or inconsequential, role in the
developing human CNS? Considering this problem in the context of biology while using real
rs-fMRI datasets permits us to meaningfully pose questions when studying how the mind and
brain develop in humans. Biology also provides a pertinent framework to seriously evaluate
and to revolutionize the methods used to answer questions about the neurobiological
underpinnings of cognitive development in children. As a first step toward this goal, the
aim of this study is investigate how one important variable for developmental studies, the
age of the child, has an effect on statistical features of head movements while children
between birth and 3 years of age underwent resting-state fMRI (rs-fMRI) scan during
natural sleep. In humans, recent research has detected informative differences in infants’
spontaneous head movements during a resting-state functional Magnetic Imaging Resonance
(rs-fMRI) scan acquired during natural sleep. Researchers studied infants from two
cohorts: at high vs low familial risk for developing Autism Spectrum Disorder (ASD; high
risk, HR is defined by virtue of having a biological sibling with a confirmed ASD
diagnosis) (Denisova & Zhao, 2017). In particular, Denisova and Zhao (2017) found that
relative to low risk (LR) infants, HR infants as young as 1–2 months old have more random
and less symmetric features of head movements during an rs-fMRI scan obtained during
natural sleep. Atypical head movements of the HR cohort at 1–2 months stayed abnormal at
9–10 months and these features were associated with flatter or delayed future early
learning developmental trajectory (Denisova & Zhao, 2017). It remains unknown whether the
statistical character of subtle movements of the head during sleep is expected to
normalize with age during the first few years of life in normal, healthy children at a low
genetic risk for atypical development, since the study by Denisova and Zhao (2017)
considered neither participants at the intervening ages, nor neonates and older toddlers.
One question to ask is: do spontaneous head movements during sleep in humans change as
children age? Here it may be noted that the capacity to respond flexibly, whether or not
the behavior is accompanied by higher noise (here, “higher noise” refers to higher
variance relative to mean) levels, at least in early infancy, seems paramount for later
normative development. Behavior at either end of the ‘normative’ spectrum, that is, either
excesses (for example, high levels of motor noise: e.g., (Therrien, Wolpert, & Bastian,
2018)) or conversely, a lack thereof (for example, pertaining to culture-specific rearing
practices, e.g., (Adolph, Hoch, & Cole, 2018)), may be detrimental for normative
functioning. Further, investigators have argued for the importance of variability for
normative human behaviors (Latash, 2016). In early life, this issue is complex and depends
on whether movements are considered during wakefulness vs. sleep, in infants at low vs.
high risk for autism, and on the age of the child. For example, the study by Denisova and
Zhao (2017) found that infants’ head movements differ depending on the experimental
condition during the neuroimaging scan, such as whether they were sleeping or awake, while
native language speech was presented to them, and on the age of assessment (Denisova &
Zhao, 2017). The goal of this study is to investigate the developmental pattern of
spontaneous head movements during sleep in a normative sample of children between birth
and 3 years of age, as children underwent an rs-fMRI scan during natural sleep.
Quantitative characterization of an age-related trajectory of spontaneous head movements
during sleep in a sample of healthy children can inform our understanding of sensorimotor
development in humans and would provide context for studies of young children who are not
developing normally. In addition, given that researchers often acquire neuroimaging data
in young children during sleep, a characterization of a developmental trajectory can
inform future brain imaging work in children. Thus, this work quantitatively mapped
statistical features of head movements in neonates, infants, and toddlers in a new cohort
of 86 children, 5 of whom provided longitudinal data, for a total of 91 datasets from
National Database for Autism Research (NDAR). Of note, researchers can distinguish between
genetic and environmental contributors to development in humans (McGue & Bouchard, 1998).
The current work excludes datasets from subjects at known genetic risk for atypical
development; datasets include those from healthy children, who were deemed to be free from
severe medical concerns and who are free of genetic risk for atypical development.
Assessments at all study-sites used a strictly standardized protocol required for MRI
acquisitions, such that all children lay supine on the scanner bed, with head and body
movements minimized using cushioning and blankets during the 5-minute session. The main
questions for the current study are as follows: whether spontaneous head movements during
sleep in young healthy children are (i) qualitatively and quantitatively different among
individual children even when the head is relatively stable and well-cushioned during a
sleep rs-fMRI scan, (ii) whether there is a cross-sectional maturational pattern from
birth to 3 years old, such that neonates show the noisiest and least symmetrical movements
relative to older children, and (iii) whether the maturational pattern is robust, that is,
somewhat independent of the absolute magnitudes of head movements.

<hs>  Datasets</hs>
  ~~~~~~~~

Data used in the preparation of this study were obtained from the NIH-supported National
Database for Autism Research (NDAR). NDAR is a collaborative informatics system created by
the National Institutes of Health to provide a national resource to support and accelerate
research in autism. Dataset identifier(s) (along with Submitters): NDARCOL0002329 (Scott
Holland & Jennifer Vannest), NDARCOL0001890 (Claudia Buss & Pathik Wadhwa), and
NDARCOL0002340 (Mary Phillips). As NDAR is part of the NDA (NIMH Data Archive), available
child datasets include those from research studies that do not solely focus on children at
risk for atypical development, such as autism. The inclusion criteria for selecting
specific collections (#2329, 1890, and 2340) that contributed datasets in the current
study consisted of (i) availability of at least 1 resting-state functional Magnetic
Resonance Imaging (rs-fMRI) scan, with data in original format with no motion correction
or other post-scan processing applied, (ii) a wide age of infants, ranging from birth up
to approximately 3 years old (36 months) during the scan, and (iii) healthy infants, in
particular those who were not known to be at high familial risk for autism or atypical
development. These inclusion criteria yielded the three study-sites above. Study-sites
were excluded if scans did not have comparable temporal resolution relative to the current
datasets (2 s; please see below for details), and/or if participants were at high risk for
atypical neurodevelopment. Specifically, researchers can distinguish between genetic and
environmental risk factors as potentially affecting behavior (McGue & Bouchard, 1998). The
current work excludes datasets known to belong to infants at a genetic risk for atypical
development; no datasets known to be from infants at high familial risk for autism are
part of the current sample. Additional collection-specific inclusion and exclusion
criteria are listed below. All data are de-identified in compliance with U.S. Health
Insurance Portability and Accountability Act (HIPAA) guidelines. Signed, written informed
parental consent was obtained by original study investigators in accordance with U.S. 45
CFR 46 and Declaration of Helsinki for participation and study procedures, including
neuroimaging protocols, were approved by the IRB of each institution. Analyses of these
de-identified data were reviewed and approved by, and a waiver of informed consent was
obtained from, the Institutional Review Board of Columbia University Medical Center. The
current study includes datasets from the May 2017 NDAR data release. The total sample
included 91 datasets (including N = 86 unique participants, with N = 5 who were scanned
longitudinally for a total of 2 times). This sample includes neonates, infants, and
toddlers. All children underwent an rs-fMRI scan during natural sleep (no sedation was
used). For N = 86 unique participants, the Male to Female ratio (M/F) is 40M/46F. Overall
for this dataset (N = 91), the age ranged between 2 and 3 weeks and 35 months. Note that
NDAR provides ages in months; for #1890, ages were available in weeks for participants
less than 1 month old. Birthweight data were available for 63 (including the five children
who contributed longitudinal datasets) out of 86 children. The average birthweight (mean
and standard deviation) was 3282.69 (442.78) grams. Of these children, only four had
birthweights below 2500 g (these infants’ birthweights are: 2410 g, 2410 g, 2380 g, and
2350 g).

<hs>  Additional information on inclusion and exclusion criteria at the three study-sites</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Considering datasets by each of the three study-sites (collections), datasets from
collection #2329 comprised N = 35 participants (14M/21F), infants and toddlers (1–36
months; N = 5 with longitudinal scans). For N = 5 participants who were scanned
longitudinally, their ages at first relative to second scan were: 3 months/14 months
(Male), 13 mo/27 mo (Male), 17 mo/31 mo (Female), 17 mo/31 mo (Female), 20 mo/32 mo
(Female). Thus, together with the longitudinal participants, there were N = 40 datasets
(16M/24F) from this site. All were required to meet inclusion criteria of low-risk,
healthy pregnancy and to have no siblings who were diagnosed with ASD, following
recruitment procedures of the Cincinnati MR Imaging of Neurodevelopment (C-MIND) study.
All participants underwent a single resting-state scan. Datasets from collection #1890
dataset comprised N = 22 healthy, typically developing neonates and infants (10M/12F)
meeting inclusion criteria of a low-risk pregnancy as per original study protocol during
recruitment at University of California, Irvine. Out of these N = 22, N = 14 participants
were 2–3 weeks old (7M/7F), N = 4 were 1 month old (2M/2F) and N = 4 were 11–13 months old
(1M/3F). All participants underwent a single resting-state scan. Datasets from collection
#2340 comprised N = 29 participants (2–5 mo-old infants, 16M/13F) who underwent 2 resting-
state scans each during a single visit to Pitt. All infants met inclusion criteria for
normal pregnancy, but infants were recruited into the Pitt study if they were at risk for
atypical maternal care. However, this dataset was not excluded from the current study,
because the goal of the current work was to characterize a representative and relatively
large cross-sectional sample of young, healthy children. Both genes and environment can
influence behavior (McGue & Bouchard, 1998). In the current work, the important exclusion
criteria pertained to excluding known genetic risk factors that place children at risk for
atypical development, such as familial risk due to having an older biological sibling
diagnosed with ASD. To ensure that total scan time is comparable among all datasets from
all sites, only the first resting-state scan from this dataset is analyzed in the current
study. Thus, all available rs-fMRI datasets from all infants were analyzed, except for
participants from #2340 who were scanned 2 times; only the 1st scan was used to ensure
that the total scan time is comparable among all datasets.

<hs>  MRI acquisition parameters</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Resting-state MRI (rs-fMRI) Blood Oxygenation Level-Dependent (BOLD) data were acquired at
3 Tesla at all three sites, on an Achieva (Phillips Medical Systems, Best, The
Netherlands) MR scanner (C-MIND #2329) or on Tim Trio Siemens (Siemens Healthcare,
Erlangen, Germany) MR scanners (#1890 and #2340). At C-MIND (#2329), rs-fMRI EPI
parameters were: [TR/TE: 2000/35 ms, flip angle = 90°, FOV = 240 × 240 mm, 80 × 80 matrix,
35 axial 4 mm slices], with scan duration of 5 min (150 volumes). At UC Irvine (#1890) rs-
fMRI scan EPI parameters were: [TR/TE: 2000/30 ms, flip angle = 77°, FOV = 220 × 220 mm,
64 × 64 matrix, 32 axial 4 mm slices], with scan duration of 6.5 min (195 volumes). At
Pitt (#2340), rs-fMRI EPI parameters were: [TR/TE: 2020/32 ms, flip angle = 80°, FOV = 256
× 256 mm, 64 × 64 matrix, 32 axial 4 mm slices], with scan duration of 5.05 min (150
volumes) of each run. Thus, all scan sessions lasted about 5 min. Data were acquired
during natural sleep, with eyes closed. During assessment, all children (neonates,
infants, toddlers) lay supine on the scanner bed, with the head cushioned to minimize
movement. Datasets from #1890 were truncated (only the 1st 150 volumes were used) in order
to ensure that the number of samples per se does not affect statistical measures. This
procedure ensured that the number of volumes in this dataset is equivalent to the number
of acquired volumes in the other two datasets. Thus, exactly N = 150 data samples (N = 149
speed data points; please see below for details) per each participant from each of the
datasets were used in the current study.

        <hss>Estimating head movements during the scan</hss>

        Well-established techniques (Friston, 2008; Friston et al., 1995) to estimate head
        movements during resting-state scans were followed and are presented in detail
        elsewhere (Denisova et al., 2016). Image volumes were pre-processed using
        Statistical Parametric Mapping (SPM8), a free open-source software to process
        neuroimaging data (http://www.fil.ion.ucl.ac.uk/spm/software/spm8/) running MATLAB
        version 8.3 (R2014a) (The MathWorks, Inc., Natick, MA). Briefly, realignment of
        scanned volumes in SPM involves estimating the six parameters of an affine ‘rigid-
        body’ transformation (b-splines interpolation using least-squares approach) that
        minimizes the differences between each successive scan and a reference scan
        (Friston, 2008; Friston et al., 1995). The linear (affine) position
        transformations specified for some portion of the image hold for all other
        portions of the image (Friston et al., 1995) by virtue of the treatment of this
        problem as one involving rigid body transformations (Denisova & Zhao, 2017). For
        each participant, rs-fMRI volume image files in NIFTI format were pre-processed,
        producing an output with the six motion parameters (3 linear translations in x, y,
        z directions, and 3 rotations: pitch (about x-axis), roll (about y-axis), and yaw
        (about z-axis)) which is recorded as an rp_%s.txt file in SPM8; rotational
        coordinates were in radians and converted to degrees (*180/pi) (Denisova & Zhao,
        2017).

        <hss>Statistical analyses</hss>

        Overall, a similar analytic strategy—estimating realignment parameters of head
        movements during an fMRI or rs-fMRI scan, calculating a summary metric, and
        applying distributional analyses on the movement time series—was used in several
        recent studies (e.g., Denisova & Zhao, 2017; Denisova et al., 2016), and is
        referred to as an ‘upcycling’ strategy in the context of Open Science Infancy
        Research protocol. Thus, Gamma fits were performed on individual participants’
        speed data, and because Gamma has two parameters, each fit yielded 2 parameter
        estimates per dataset, the shape and the scale. In addition, mean, variance,
        skewness, and kurtosis were also calculated for each individual dataset. Quality
        checks performed for all individual fits included checking that MATLAB's maximum
        likelihood estimation (MLE)-based fitdist algorithm converged on a solution for
        every participant; successful convergence occurred for all fits reported. For non-
        parametric Spearman's rank-order rho analyses (two-tailed) of parameter estimates
        and age, I performed 5000 random bootstrap samples (with replacement) to obtain
        the uncertainty of the rho estimate (95% Confidence Intervals, CIs). Engle's ARCH
        test was used to assess for violations of homoscedacity. Linear fits for parameter
        estimates vs. age are plotted with a Working-Hotelling 95% confidence band
        covering the entire range of values. The functions and tools including the cftool
        in the Statistics and Machine Learning and Curve Fitting Toolboxes in MATLAB 8.3
        (R2014a) (MathWorks, Natick, MA, USA) were used for all statistical analyses.

<h>RESULTS</h>
-------

Young children—from neonates to 3 year olds—show diversity in their spontaneous head
movements during a sleep resting-state fMRI. Fig. 1 presents individual parameter
estimates for shape (a parameter, denoting whether the distribution is best characterized
by Exponential or skewed-to-Gaussian) and scale (b parameter, denoting noise-to-signal
levels) for each participant; the mean, variance, skewness and kurtosis are presented in
Supplementary Figure 2). When inspecting individual parameter estimates on shape (a) and
scale (b) parameters shown in Fig. 1, note that infants with higher levels of noise-to-
signal levels (b parameter) also have more random, noisy signatures (a parameter, tending
toward Exponential distributions) in their spontaneous head fluctuations, following a
power–law relation f(x) = a*xb (consistent trend for normalized peaks data: Supplementary
Figure 3). Supplementary Table 1 and Supplementary Table 2 present goodness-of-fits for
Power and Exponential fits for raw time series and normalized peaks, respectively). Taken
together, these results illustrate the presence of substantial variability in these cross-
sectional data. Can maturational processes account for some of the diversity in the
patterns we observed thus far? The prediction is that infants with the highest shape
values and the lowest scale parameter estimate values (datasets in the right-most lower
location in Fig. 1) are overall older relative to those showing reverse pattern (i.e.,
those datasets with the lowest shape and the highest scale values that are located toward
the left-most upper location in Fig. 1).

<hs>  Age-related patterns in spontaneous head movements</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For sample individual data from several participants, including a neonate, several
infants, and older toddlers, please see Supplementary Figure 4 and also Fig. 2a (data
shown are for male children; both the number of speed data samples (n = 149) per dataset
as well as the sampling rate are equal across all participants). Note that the youngest
child's (neonate; 2–3 weeks old) movements shown in Supplementary Figure 4 have more peak
maxima and a more skewed distribution (Fig. 2a) relative to movements of a 28 mo-old
toddler. Significant associations are detected between statistical features of spontaneous
head movements and the age of participants. While no evidence of heteroscedacity was
detected (P > 0.05), linear fits in all plots are shown with Working-Hotelling 95%
Confidence bands. Spontaneous angular head movements in older children are significantly
less skewed in older children, located toward more symmetric values (lower data points on
the y-axis) (non-parametric Spearman's rank-order correlation: rs(89) = −0.4901 (−0.632 to
0.322, 95% Confidence Intervals, CIs), P = 8.1892e−07) (Fig. 2b, left panel) (Consistent
pattern is found for skewness of linear spontaneous movements and age, rs(89) = −0.3805
(−0.556 to 0.176, 95% CIs), P = 1.9902e−04). Congruent with this pattern, spontaneous
angular head movements in older children are quantified by a significantly higher a-shape
parameter, located toward more Gaussian parameter values on the y-axis on the Gamma
parameter plane (non-parametric Spearman's rank-order correlation: rs(89) = 0.4611
(0.261–0.635, 95% CIs), P = 4.2389e−06) (Fig. 2b, right panel). This association with age
is consistent for parameter estimates obtained from normalized angular peaks data (P =
0.0086) (Supplementary Figure 5a; Supplementary Results). When considering parameter
estimates of linear speed, a significant pattern of higher a-shape parameter with age is
detected: rs(89) = 0.3376 (0.120–0.542, 95% CIs), P = 0.0011 (consistent for normalized
peaks linear speed, P = 0.0424; Supplementary Figure 5a; Supplementary Results). Further,
significantly lower b-scale (noise-to-signal level) parameter estimates (angular speed)
are associated with increasing age: rs(89) = −0.2878 (−0.487 to 0.060, 95% CIs), P =
0.0057) (Supplementary Figure 5b; Supplementary Results) (consistent results for
normalized angular peaks, P = 0.0080). For linear speed, a significant decrease in b-scale
parameter with age is detected: rs(89) = −0.2169 (−0.425 to 0.005, 95% CIs), P = 0.0354
(Supplementary Figure 5b; Supplementary Results) (association is consistent for normalized
linear peaks, P = 0.0464). Thus, older toddlers have a significant increase in the
symmetry as well as a decrease in noise-to-signal levels in their spontaneous head
movements during a sleep resting-state fMRI (Fig. 2; Supplementary Figure 5) (Note that
this finding is particularly robust for parameters derived from angular speed, and is
consistent for analyses using linear speed). This developmental pattern is uncoupled from
peak amplitudes of movements during the scan per se. Specifically, the overall trend for
increased symmetry and reduced noise levels with age remains when using normalized peaks
data (right panels in Appendix A).

<h>DISCUSSION</h>
----------

The current work quantitatively describes, for the first time, the developmental progress
of a set of parameters of spontaneous speed of head movements during sleep rs-fMRI scans
in 91 children's datasets with ages ranging from ∼birth to about 3 years old. The
signatures of spontaneous head movements, even when the head is relatively well-stabilized
during a neuroimaging scan, are diverse among a group of neonates, infants, and older
toddlers, up to approximately 3 years old. The youngest participants studied, 2–3 week-old
neonates, showed less symmetric and more noisy structure in their movement signatures,
tending toward more Exponential distributions and away from more symmetrically Gaussian
distributions shown by older toddlers. The current findings strongly suggest that the
developmental pattern of head movements during sleep rs-fMRI scan in healthy infants is
different from the one to be found in a sample of infants at a familial or genetic risk
for atypical development. The role of spontaneous movements during sleep in early life in
humans is not well-understood, and several implications and interpretations of the current
findings are considered. There are two ways to think about spontaneous head movements
during sleep in early life. First, the traditional view is that head movements are a
nuisance for neuroimaging data acquisition and analyses. Continued research efforts are
still needed to understand the impact of head movements, as well as of motion correction
itself, on MRI analyses and inference, especially in studies with young children. Second,
the new view is that head movements are actually an important source of neuronal activity
in the developing cortex, that this activity builds synapses and functional connections
between the different regions in the developing brain, and thus new, transformative
research is urgently needed to incorporate all major drivers of nascent functional
connections into new methods and studies that measure functional connectivity in early
life.

<hs>  Implications for brain imaging work in young children</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In particular, variations in participant movement during MRI acquisition have unintended,
deleterious consequences (Friston, Williams, Howard, Frackowiak, & Turner, 1996) on image
quality and inference in MRI research (cf. (Denisova, 2018)) and in this case would
confound higher-level age-related hypotheses. In this regard, these findings extend recent
study reporting significant differences in head movement in infants during MRI as a
function of familial autism risk (Denisova & Zhao, 2017). Because the child's age alone is
a significant factor in the extent of movement shown by the participant, age-related
trajectories of head movements during the scan need to be accounted for in neuroimaging
analyses and inference with neonates, infants and toddlers.

        <hss>Age and head motion correction</hss>

        Based on the current findings, we can expect that children of different ages will
        have different patterns of movement spikes and periods of stillness, such that
        neonates will have the most variable patterns relative to older children. This
        effect could be due to differences in how different spontaneous movements,
        including startles and twitches, naturally occur during sleep at younger vs. older
        ages. Since removing volumes exhibiting motion, in order to correct for the
        deleterious impact of movement on acquired EPI data (i.e. via zeroing out or
        scrubbing; (Power, Barnes, Snyder, Schlaggar, & Petersen, 2012)) affects spectral
        features of the remaining time series, a less veridical, and more variable, input
        for functional connectivity analysis is available at the youngest ages. Put
        simply, due to motion correction strategies, the spectral features of the new
        (i.e. motion-corrected) EPI time series would vary systematically across age. For
        this reason, age-related rs-functional connectivity MRI (rs-fcMRI) analyses and
        inferences are problematic. Increasing scanning duration while obtaining EPI data
        for rs-fcMRI analyses, as well as multi-echo EPI acquisitions, are among realistic
        strategies available today for acquiring more good quality data in young children.
        Nevertheless, the outstanding question is not, “How can we correct movement
        better?”, but a more serious and compelling one: How can we measure and represent
        all important sources of neuronal activity that generate functional connections in
        the developing CNS?

        New questions for the study of functional connections in the developing human brain

        Even if it turns out that spontaneous head movements trigger or associate with
        neuronal activity in a different way than what has been shown by animal
        researchers, a significant and important issue remains for rs-fcMRI studies with
        humans in early life. Zeroing out and/or scrubbing EPI volumes with high movement
        means that researchers do not take into account co-occurring neuronal activity,
        which could contribute toward building synapses and functional connectivity in the
        still-developing CNS, during periods of spontaneous movements during sleep (A
        different problem occurs, as noted earlier, if high movement volumes are not
        removed, because EPI time series used in the analyses will exhibit age-driven
        differences in movement, which could lead to spurious age-related functional
        correlations and could be misinterpreted as brain maturational effects). Existing
        approaches and methods that aim to non-invasively measure functional connectivity
        fall short because an important contributor to neuronal activity, for example, for
        sensorimotor development, is missing from data analyses. The unique, transient
        biology of the developing CNS must be taken into account as we develop new non-
        invasive imaging approaches and methods when aiming to reveal nascent functioning
        of the developing human CNS.

<hs>  Interpretations of age-related movement patterns and targets for future research directions in early brain development</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The key finding of an association between age and improvement in spontaneous movement
signatures should be considered with respect to the special needs of neonates for sleep.
Because neonates sleep more than older toddlers and may also produce more frequent
spontaneous movements than toddlers, this may explain, in part, the finding of more
variable signatures in neonates’ spontaneous movements. As noted in the Introduction,
spontaneous movements during sleep in children include twitches and startles and these
movements occur throughout sleep, that is, during AS sleep as well as quiet sleep (QS)
stages which correspond to behavioral state 2 and 1, respectively (Prechtl, 1974). One
potential interpretation that is consistent with the current data is that as infants
successfully build sensorimotor maps of their world (Blumberg et al., 2015; Tiriac et al.,
2014), their requirements for such movements would decrease over time. Another way to
understand these findings is to consider that spontaneous movements permit the neonate to
gain a sense of physical space in the extrauterine environment. Fetuses have been argued
to show proto-predictive capacity and ability to control their movements (Zoia et al.,
2007), prenatal learning and perception occurs in-utero (DeCasper & Spence, 1986; Reid et
al., 2017), and there is decrease in movements before birth womb (Myowa-Yamakoshi &
Takeshita, 2006); there is also the availability for symmetric, non-chaotic
movements—while swimming—in newborns (McGraw, 1939)). The change in the statistical
character of movements with age observed here may reflect in part the gradual adaptation
to the differing physical constraints of the extra-uterine world. It is warranted, in
future work, to direct greater research focus to probe the maturation of brain structures
that are involved in both cognition and movement, such as the cerebellum. Perhaps
unexpectedly, the cerebellum has not received substantial attention in infancy research
relative to the cerebral cortex and subcortical structures, even though this structure
contains 80% of the neurons in the human brain (Herculano-Houzel, 2010) with evidence of
microscopic myelination already present at birth (Kinney, Brody, Kloman, & Gilles, 1988).
With regard to the specific features of the neuronal architecture available early in life,
although axonal myelination (the sheathing or covering of neurons’ axons in the nervous
system that supports neuronal conduction speeds) is initially weak at birth in humans,
postmortem studies indicate that the onset, rate, as well as the direction of myelination
varies (Paus et al., 2001) not only by a specific brain structure (e.g., the cerebellum is
the first major structure to myelinate, before the cerebral cortex (Kinney et al., 1988))
but also locally within the cerebral cortex. Recent work detected structural abnormalities
in the cerebellar cortex in boys with ASD diagnoses relative to typically developing
children (Zhao, Walsh, Long, Gui, & Denisova, 2018). As such, it would be instructive to
investigate the relation between the improvement of movement signatures with age relative
to the anatomical maturation of the cerebellum in order to better understand the important
anatomical brain-based and developmental behavior-based contributions to cognition.
Finally, advancing knowledge about early sensorimotor development is very important for
understanding normative brain development. In particular, normal development of
sensorimotor systems and their connections are important for normative development of
vocal learning and speech (e.g., (Bruderer, Danielson, Kandhadai, & Werker, 2015)).
Atypical functioning of these systems and connections could herald neurodevelopmental
disorders in children, including ASD. Further, different systems (e.g., auditory, visual,
limbic) and structures (e.g., cerebellum) could interact in different ways, exactly during
the critical time when synapses and connections are being built within and across these
systems.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

During MRI scans, young infants are swaddled and their heads are well-cushioned, in order
to restrict their movements during signal acquisition. Considering that these constraints
are in place during acquisition of sleep rs-fMRI scans, infants’ spontaneous head
movements may be likely different from movements that would be produced by these infants
during ‘normal’, non-constrained sleep. For example, one may expect that there would be
increased movement, such as increases in terms of magnitude, during unconstrained sleep.
In future work it would be helpful to measure statistical features during unconstrained
sleep in natural environments using motion capture systems as well as using
polysomnography (PSG) and electroencephalography (EEG) methods. Nevertheless, the current
study established an age-driven pattern of reduced noise-to-signal and increased symmetry
also using normalized data, meaning that this developmental pattern holds after accounting
for magnitude of movements per se in individual infants.

<h>CONCLUSIONS</h>
-----------

This cross-sectional study revealed an age-related pattern in statistical features of head
movements during a sleep rs-fMRI scan in a sample comprised of healthy children between 0
and 3 years of age, including neonates, infants, and toddlers. Specifically, a significant
attenuation of noise-to-signal and an increase in symmetry in head movements during sleep
rs-fMRI was detected in older infants and toddlers, relative to the youngest participants
studied. The current quantitative characterization of a functionally important and
heretofore under-examined aspect of normative development during sleep establishes that
statistical features of spontaneous head movement signatures during rest or sleep are
expected to become less noisy and more symmetrical in ∼3 year old children. For in vivo,
non-invasive neuroimaging studies that aim to reveal how young brains work and learn, the
key outstanding question is not “How can we correct head movement better?” but rather: How
can we represent all important sources of neuronal activity that shape functional
connections in the still-developing human CNS?

<h>COMPETING INTERESTS</h>
-------------------

I have no competing interests, including any financial interests, activities,
relationships, and affiliations that could have influenced decisions or work on this
manuscript.

<h>AUTHOR CONTRIBUTIONS</h>
--------------------

KD conceived and designed study, performed analyses, and wrote paper.

<h>FUNDING</h>
-------

This work is supported by the Sackler Award in Developmental Psychobiology to KD. The
sponsor had no role in study design; in the collection, analysis and interpretation of
data; in the writing of the report; and in the decision to submit the article for
publication.


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<ART>Alexithymic traits, independent of depression and anxiety, are associated with reduced sleep quality
================================================================================

Authors: Jennifer Murphy, Katharina Wulff, Caroline Catmur, Geoffrey Bird
DOI: 10.1016/j.paid.2018.03.023
Year: 2018  |  Pages: 175-178
ASJC codes: 3200
Keywords: Alexithymia, Anxiety, Depression, Sleep, Sleep quality

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Disrupted sleep is a transdiagnostic factor characterising a multitude of psychiatric conditions. Although this is well-recognised, the cause of poor sleep across conditions is unclear. One possibility is that poor sleep is driven by traits which also co-occur with multiple conditions. Previous research suggests that alexithymia (an inability to identify and describe one's emotions) is a candidate trait, as it is linked to poor sleep quality and elevated levels of alexithymia are seen across multiple diagnostic groups. The association between alexithymia and poor sleep quality has been questioned however, with studies arguing that it is depression and anxiety, rather than alexithymia, which impact sleep quality. Problematically, such studies typically utilise measures of depression and anxiety which include items relating to sleep – meaning that apparent associations between depression and anxiety may be due to measurement issues, rather than to depression and anxiety per se. Study 1 confirmed the relationship between alexithymia and subjective sleep quality, whilst Study 2 utilised an independent sample to replicate the association between alexithymia and sleep quality, and to demonstrate that it is not a product of co-occurring depression or anxiety. Results therefore support the suggestion that alexithymia may explain disrupted sleep across multiple psychiatric conditions.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Poor sleep quality is reported across multiple psychiatric conditions (e.g., Freeman et
al., 2017) including depression (see Tsuno, Besset, & Ritchie, 2005) and certain subtypes
of anxiety disorders (see Papadimitriou & Linkowski, 2005). Given the importance of sleep
for wellbeing (Freeman et al., 2017), identifying factors responsible for poor sleep
across the disorders in which it is experienced is an important research aim. In recent
years there has been a growing appreciation that transdiagnostic symptoms, including poor
sleep, may be explained by traits that co-occur with multiple disorders, rather than by
the disorders themselves. In particular, the contribution of alexithymia, a sub-clinical
condition characterised by difficulties identifying and describing one's own emotions and
an externally orientated thinking style, has begun to be appreciated (Sifneos, 1973).
Alexithymic individuals often exhibit poor emotional functioning in a number of domains
outside their defining inability to identify and describe their own emotions, including
emotion recognition (Brewer, Cook, Cardi, Treasure, & Bird, 2015; Cook, Brewer, Shah, &
Bird, 2013; Grynberg et al., 2012; Heaton et al., 2012) and empathy (Bird et al., 2010).
Perhaps as a consequence, individuals with alexithymia also experience problems with
interpersonal relationships and exhibit increased rates of mental and physical ill-health
(Taylor, Bagby, & Parker, 1999). Importantly, increased rates of alexithymia are observed
across many psychiatric conditions (e.g., Brewer, Cook, & Bird, 2016; Murphy, Brewer,
Catmur, & Bird, 2017), and alexithymia has been demonstrated to be responsible for a range
of symptoms across these conditions (e.g., Brewer et al., 2015; Cook et al., 2013). With
respect to sleep, previous studies have identified an association between alexithymia and
poor sleep quality using both subjective (e.g., Bauermann, Parker, & Taylor, 2008) and
objective measures of sleep quality (e.g., Bazydlo, Lumley, & Roehrs, 2001). For example,
using subjective measures alexithymia has been associated with sleep-related problems in
community samples (e.g., Bauermann et al., 2008; Hyyppä, Lindholm, Kronholm, & Lehtinen,
1990) as well as in clinical groups such as men with depression (e.g., Honkalampi,
Saarinen, Hintikka, Virtanen, & Viinamäki, 1999) and individuals with depression (e.g.,
Aydin, Ozdemir, & Selvi, 2012); and rates of alexithymia are reported to be higher in
those with insomnia (e.g., Engin, Keskin, Dulgerler, & Bilge, 2010). Whilst few studies
have employed objective measures, there are also reports that alexithymia is associated
with increased light sleep (Bazydlo et al., 2001; but see De Gennaro et al., 2002).
Furthermore, recent evidence links alexithymia to atypical interoception (perception of
one's internal bodily state; Brewer et al., 2016; Herbert, Herbert, & Pollatos, 2011;
Shah, Hall, Catmur, & Bird, 2016; Murphy, Catmur, & Bird, 2018), and poor interoception
has also been linked to poor self-reported sleep quality in clinical conditions (Ewing et
al., 2017). These studies are therefore consistent with the proposal that heightened
levels of alexithymia may confer risk of disrupted sleep. Although a body of evidence
links alexithymia to poor sleep, it should be acknowledged that individuals with higher
levels of alexithymia are more likely to report increased symptoms of depression and
anxiety (e.g., Hendryx, Haviland, & Shaw, 1991; Honkalampi, Hintikka, Tanskanen, Lehtonen,
& Viinamäki, 2000), which have both been associated with poor sleep (see Tsuno et al.,
2005; Papadimitriou, & Linkowski, 2005). As a consequence, it is possible that it is
depression or anxiety, and not alexithymia, that is responsible for poor sleep quality.
Indeed, previous studies examining the specific contribution of alexithymia, depression
and anxiety to poor sleep quality have produced mixed results, with some studies
suggesting that the relationship between alexithymia and sleep disturbance is driven by
anxiety (Lundh & Broman, 2006; with anxiety quantified using the Karolinska Scales of
Personality; KSP; Gustavsson, Weinryb, Göransson, Pedersen, & Åsberg, 1997) or depression
(De Gennaro, Martina, Curcio, & Ferrara, 2004; with depression assessed using the Center
for Epidemiological Studies Depression scale; CES-D; Radloff, 1977), and some not
(Kronholm, Partonen, Salminen, Mattila, & Joukamaa, 2008; with depression assessed using
the Beck Depression Inventory; BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961).
Problematically, however, many measures of depression and anxiety include items relating
to sleep, and all of the previous studies investigating the relationship between
alexithymia, anxiety, depression and sleep have utilised measures that include items
assessing sleep. For example, the most commonly used measure of depressive traits, the BDI
(Beck et al., 1961) includes items relating to both sleep (e.g., “I don't sleep as well as
I used to”) and tiredness (e.g., “I get tired more easily than I used to”). The same is
true for other routinely-used measures such as the CES-D (Radloff, 1977) which also
includes items relating to sleep (e.g., “My sleep was restless”); and measures of anxiety
that include items relating to tiredness (e.g., “Quite often, especially when I am tired,
I get the feeling that either I or the world around me is changing - a feeling of
unreality”; KSP; Gustavsson et al., 1997). The association between depression and anxiety
and sleep, and whether anxiety and depression are responsible for the association between
alexithymia and sleep quality, may therefore depend on the degree to which items relating
to sleep contribute to assessment of depression and anxiety on a particular measure.
Specifically, studies utilising depression or anxiety measures that have a greater focus
on sleep quality than other measures may inflate relationships between anxiety, depression
and sleep, which in turn obscure, or reduce, associations between alexithymia and sleep
quality (De Gennaro et al., 2004; Kronholm et al., 2008; Lundh & Broman, 2006). The degree
to which the association between alexithymia and sleep quality is suppressed will, in
turn, depend on the proportion of individuals in a particular sample with co-occurring
clinical symptoms and sleep problems. These factors make it very difficult to determine
whether alexithymia contributes to poor sleep quality independent of its relationship with
depression and anxiety when measures of depression and anxiety are utilised that include
items relating to sleep. Consequently, the aim of the present set of studies was to 1)
confirm the relationship between alexithymia and poor sleep quality and 2) examine whether
these associations are driven by anxiety or depression using measures which do not include
items that assess sleep quality.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were recruited via pre-existing databases of individuals who had indicated an
interest in taking part in psychological research and via social media advertisements.
Participants were informed that the study aimed to investigate links between emotional and
bodily awareness, and physical health. 86 participants took part in Study 1. Of these, 70
participants fully completed the questionnaires, had English as their first language and
identified their gender as male or female (Mage = 42.93, SDage = 21.80, range 18–91, 26
Males) and were included in analyses. 13.95% were removed as they had English as their
second language, 3.49% were removed for a failure to complete all measures and 1.16% were
removed as they identified as a non-binary gender. Ethical approval was granted by the
local ethics committee, all participants gave informed consent, and were fully debriefed
upon completion.

<hs>  Method</hs>
  ~~~~~~

Participants completed the Toronto Alexithymia Scale (TAS-20; Bagby, Parker, & Taylor,
1994) and the Pittsburgh Sleep Quality Index (PSQI; Buysse, Reynolds, Monk, Berman, &
Kupfer, 1989) in a randomised order online via Qualtrics (Provo, UT). High scores on these
measures indicate elevated alexithymic traits and poor sleep quality, respectively. The
TAS-20 is comprised of three subscales, difficulties describing feelings, difficulties
identifying feelings and externally orientated thinking.

<h>RESULTS</h>
-------

Where directional predictions are made, one-tailed tests are utilised. Alexithymia scores
ranged from 21 to 79 (M = 46.90, SD = 13.55). As predicted, total alexithymia scores were
associated with reduced sleep quality (r(68) = 0.462, p < .001; one-tailed). Analysis of
the TAS-20 sub-factors indicated a significant association between reduced sleep quality
and each sub-factor (all p < .006; one-tailed). As the relationship between alexithymia
and sleep quality may vary across genders (e.g., Honkalampi et al., 1999; Kronholm et al.,
2008), and levels of alexithymia have been reported to vary across the lifespan (e.g.,
Mattila, Salminen, Nummi, & Joukamaa, 2006), additional analyses were conducted
controlling for these variables. Regression analyses predicting sleep quality from age
(years), gender (0 = female, 1 = male) and alexithymia total scores suggested that both
alexithymia (standardised β = 0.534, t = 4.903, p < .001; one-tailed) and age
(standardised β = 0.265, t = 2.408, p < .010; one-tailed) were predictive of poor sleep
quality and the overall model was significant (F(3,66) = 8.420, p < .001). To uncover
whether the relationship between alexithymia and sleep varied as a function of gender, the
regression analysis was re-run including the interaction term between gender (−1 = female,
and 1 = male) and mean-centred alexithymia scores. The interaction term did not predict
sleep quality (standardised β = 0.154, t = 1.302, p > .05; two-tailed). An adequate range
of alexithymia (Mage = 50.19, SDage = 12.16, Range 24–79), depression (Mage = 10.77, SDage
= 10.0, Range 0–38) and anxiety scores (Mage = 8.27, SDage = 7.62, Range 0–30) were
obtained, with scores on the anxiety and depression DASS subscales ranging between normal
and extremely severe (Lovibond & Lovibond, 1995) and scores on the TAS-20 ranging from
very low to high alexithymic traits (Bagby et al., 1994). Likewise, a large range of PSQI
scores were obtained (Mage = 6.49, SDage = 3.60, Range 0–18). As expected, significant
correlations were observed between these variables (all p < .001; one-tailed; Table 1.).
As in Study 1, all three subscales of the TAS-20 were correlated with poor sleep quality
(p < .05; one-tailed). Analysis of the data was carried out using hierarchical regression.
Participant age (years), gender (0 = female, 1 = male) and anxiety scores were entered
into the first step, depression into the second step, and alexithymia total scores into
the third step of a regression model predicting sleep quality. Visual examination of the
residuals confirmed a normal distribution and no multicollinearity (all VIF < 1.88). At
step one only anxiety scores predicted sleep quality (standardised β = 0.408, t = 3.513, p
< .001; one-tailed) and the overall model was significant F(3,69) = 5.041, p = .003. At
step two only depression scores predicted sleep quality (standardised β = 0.428, t =
3.328, p < .001; one-tailed), and the overall model was significant (F(4,68) = 7.103, p <
.001). Anxiety no longer predicted sleep quality (standardised β = 0.131, t = 0.959, p >
.15; one-tailed). When alexithymia was added (step three), both alexithymia (standardised
β = 0.261, t = 2.133, p < .02; one-tailed) and depression predicted sleep quality
(standardised β = 0.338, t = 2.561, p = .007; one-tailed). The inclusion of alexithymia
significantly increased the variance accounted for by the model (by 4.5%; F(1, 67) =
4.551, p = .037), and the overall model was significant (F(5,67) = 6.889, p < .001).
Although residuals appeared normally distributed, the Kolmogorov–Smirnov test indicated
that the residuals were not normally distributed (D = 0.183, p < .001). Accordingly, the
analysis was re-run using robust regression (entry method), which is less sensitive to
departures from normality (Field & Wilcox, 2017). This analysis confirmed the same pattern
of results, whereby depression (standardised β = 0.107, t = 2.353, p = .011; one-tailed)
and alexithymia (standardised β = 0.096, t = 2.753, p = .004; one-tailed) were the only
predictors of poor sleep quality. The original regression analysis was repeated including
the interaction between gender (−1 = female, 1 = male) and mean centred alexithymia scores
in step four. This had little effect on the results obtained, and the interaction term was
not a significant predictor of sleep quality (standardised β = 0.065, t = 0.554, p >
.250).

<h>STUDY 2</h>
-------

Having confirmed an association between alexithymia and poor sleep quality, the aim of
Study 2 was to determine whether this association was driven by depression or anxiety
using measures which do not include items relating to sleep quality.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A power analysis using the effect size observed in Study 1 for the correlation between
alexithymia and sleep quality indicated an N of 27 would provide 80% power to detect an
effect at α = 0.05 (one-tailed). Participants were recruited as per Study 1 and the same
ethical guidelines were adhered to. 108 participants completed the online questionnaires
anonymously via Qualtrics (Provo, UT). Of these, 73 fully completed the surveys, had
English as their first language and identified as male or female (Mage = 38.84, SDage =
15.82, Range 18–79, 26 Males). 26.9% of the sample were removed as they had English as
their second language, 2.8% of the sample were removed for non-completion and 2.8% of the
sample were removed as they identified as a non-binary gender.

<hs>  Method</hs>
  ~~~~~~

Participants completed the TAS-20 and PSQI as well as the Depression, Anxiety and Stress
Scale (DASS-21; Lovibond & Lovibond, 1995) online. The DASS-21 provides separate subscales
for depression and anxiety, and no items relating to sleep are present in either subscale.
As is typical, scores from the DASS-21 were doubled to equate to the DASS-42 to allow ease
of comparison with studies using this measure (Lovibond & Lovibond, 1995), with higher
scores indicative of greater depression or anxiety.

<h>DISCUSSION</h>
----------

The present set of studies sought to examine the association between alexithymia and sleep
quality. Consistent with previous evidence, Study 1 confirmed that alexithymia is
associated with poor sleep quality and, in this sample, the impact of alexithymia on sleep
quality did not vary across genders. In Study 2, the association between alexithymia and
poor sleep quality was replicated, and analyses confirmed that the association was not a
product of co-occurring depression or anxiety. As expected, anxiety, depression and
alexithymia were all associated with reduced sleep quality (e.g., Tsuno et al., 2005;
Papadimitriou, & Linkowski, 2005; Bauermann et al., 2008). However, no relationship
between anxiety and sleep quality was observed once depression was controlled for,
suggesting that the relationship between anxiety and sleep quality may be driven in part
by the high comorbidity between depression and anxiety (see Papadimitriou, & Linkowski,
2005). It remains a possibility, however, that a unique effect of anxiety on sleep quality
may be observed for distinct subtypes of anxiety disorders. In contrast to previous
evidence suggesting associations between alexithymia and sleep quality are driven by
heightened rates of anxiety and depression (De Gennaro et al., 2004; Lundh & Broman, 2006)
in the alexithymic population, this study found an independent effect of alexithymia on
sleep quality. Such findings are consistent with data from Kronholm et al. (2008), who
found an independent effect of alexithymia on sleep not explained by depression despite
using a depression measure that included items relating to sleep (the BDI). Whilst these
findings conflict with some previous reports (e.g., De Gennaro et al., 2004; Lundh &
Broman, 2006), as previously noted it is possible that the measures of depression and
anxiety used in previous studies that specifically ask about sleep quality or refer to
tiredness (e.g., the BDI, CES-D, and KSP) masked the relationship between alexithymia and
sleep in samples with particular patterns of covariance between clinical symptoms and
sleep quality. These data therefore underscore the importance of ensuring independence of
measurement when selecting measures of depression and anxiety, and highlight the
usefulness of the DASS-21 (which does not include items that assess sleep-related factors)
when assessing correlations between depression, anxiety, and sleep quality. The finding
that heightened alexithymia is associated with poor sleep suggests that alexithymia may
contribute towards the often-observed sleep disturbances across a range of disorders
(e.g., Freeman et al., 2017) that are also characterised by heightened rates of
alexithymia (e.g., Murphy et al., 2017). Whilst the mechanism by which alexithymia confers
risk of disrupted sleep remains unclear, suggestions include increased nocturnal arousal
as a result of poor verbalisation of emotions (Hyyppä et al., 1990), and increased light
sleep (e.g., Bazydlo et al., 2001; see Bauermann et al., 2008). More recent associations
between alexithymia and interoception (e.g., Brewer et al., 2016; Herbert et al., 2011;
Murphy et al., 2018; Shah et al., 2016), and evidence that low interoceptive accuracy is
associated with poor sleep quality in certain disorders (Ewing et al., 2017), also raise
the possibility that poor interoception may be the mechanism by which alexithymia confers
risk of disrupted sleep. However, the direction of causality remains unclear (see also
Ewing et al., 2017); it is also possible that poor interoception results in heighted
alexithymia which in turn results in poor sleep quality and a greater risk of psychiatric
disorders, or that poor sleep may impact upon interoception which results in increased
alexithymia and risk of poor mental health. As is clear from this speculation, future
studies using longitudinal designs should examine the relationship between alexithymia,
interoception, and sleep, using both subjective and objective measures of interoception
and sleep quality. It is important to acknowledge certain limitations of these studies.
First, although several potential confounds were controlled for, body composition (e.g.,
obesity), often associated with both sleep (Beccuti & Pannain, 2011) and alexithymia
(Pinna et al., 2011), was not controlled for. However, given that associations between
alexithymia and sleep quality have been reported when body composition is controlled for
(Kronholm et al., 2008), it is unlikely this would have changed the pattern of results.
Second, although sleep quality is often quantified using self-report measures (e.g., the
PSQI), discrepancies between objective and subjective measures of sleep quality have been
reported, with some suggestion that PSQI scores may be influenced by general negativity
(Grandner, Kripke, Yoon, & Youngstedt, 2006). However, as previous reports suggest that
alexithymia is associated with objective measures of poor sleep even when depression
(CES-D) is controlled for (Bazydlo et al., 2001), it is likely that alexithymia also makes
a contribution to objective measures of sleep disturbance. Future research, therefore,
should investigate the association between alexithymia, depression, anxiety, and sleep
quality, using complementary measures of both subjective and objective sleep quality.
Third, in the present study, depression and anxiety were assessed over the previous week
whereas sleep quality was rated over the previous month. Whilst this method has been
utilised previously (e.g., De Gennaro et al., 2004), it is possible that these differing
time frames may influence the relationship between these measures. It is therefore
important that future studies equate the measurement period for each factor assessed.
Finally, in comparison to previous work, the sample size recruited for the present study
was small. However, it is important to note that an adequate range of scores was present
for all key variables, the association between alexithymia and sleep quality was
replicated across independent samples, and sample sizes were above those determined using
formal power analyses. In summary, these data demonstrate that alexithymia is an
independent predictor of poor self-reported sleep quality, raising the possibility that
alexithymia may contribute towards sleep problems observed across a number of psychiatric
disorders.


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<ART>Altering movement parameters disrupts metacognitive accuracy
============================================================

Authors: E. R. Palser, A. Fotopoulou, J. M. Kilner
DOI: 10.1016/j.concog.2017.11.005
Year: 2018  |  Pages: 33-40
ASJC codes: 3204, 3205
Keywords: Confidence, Metacognition

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<h>ABSTRACT</h>
--------

Correctly estimating the confidence we should have in our decisions has traditionally been viewed as a perceptual judgement based solely on the strength or quality of sensory information. However, accumulating evidence has demonstrated that the motor system contributes to judgements of perceptual confidence. Here, we manipulated the speed at which participants’ moved using a behavioural priming task and showed that increasing movement speed above participants’ baseline measures disrupts their ability to form accurate confidence judgements about their performance. Specifically, after being primed to move faster than they would naturally, participants reported higher confidence in their incorrect decisions than when they moved at their natural pace. We refer to this finding as the adamantly wrong effect. The results are consistent with the hypothesis that veridical feedback from the effector used to indicate a decision is employed to form accurate metacognitive judgements of performance.

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<h>INTRODUCTION</h>
------------

Humans are unique amongst animals in being able to provide explicit reports on the
reliability of, or confidence in their decisions. Previous studies have demonstrated that
our confidence in our decisions or opinions plays a key role in group interactions
(Bahrami et al., 2010; Koriat, 2012). Whenever people express an opinion, they are likely
to also communicate their confidence in that opinion, be this explicitly through what they
say or implicitly in their movements and facial expressions (Aitchison, Bang, Bahrami, &
Latham, 2015). Accurate understanding of confidence has obvious implications for high-risk
decision making domains such as financial investment (e.g. Broihanne, Merli, & Roger,
2014), medical diagnosis (e.g. Berner & Graber, 2008), jury verdicts (e.g. Tenney,
MacCoun, Spellman, & Hastie, 2007), and politics (Johnson, 2004). Theoretical models of
perception have proposed that confidence is related to the quality or strength of sensory
processing (Barthelmé & Mamassian, 2010; Kepecs, Uchida, Zariwala, & Mainen, 2008; Kiani &
Shadlen, 2009; Vickers, 1979; Zylberberg, Barttfeld, & Sigman, 2012; see Yeung &
Summerfield, 2012, for a review) and speak to a domain-specific formation of confidence
judgements. However, there is increasing evidence that perceptual-decision signals are
also seen in neural circuits specialised for motor actions (Cisek & Kalaska, 2005;
Freedman & Assad, 2011; Hernández, Zainos, & Romo, 2002; Romo, Hernández, & Zainos, 2004;
Shadlen & Newsome, 2001), suggesting a contribution of the motor system to estimates of
confidence, and supporting the idea of metacognition as a domain-general process. Indeed,
it has recently been shown that disruption of the motor system, specifically the dorsal
premotor cortex, reduces metacognitive ability when performing a perceptual discrimination
task (Fleming et al., 2014). In addition, Allen et al. (2016) report the results of an
interoceptive priming manipulation where autonomic arousal modulates subjective confidence
on a motion-discrimination task. Thus, it is has been suggested that movement parameters
proprioceptive and interoceptive states may also serve as a useful cue for the inference
of confidence in our own decision-making. Indeed, previous research has shown that the
speed at which a participant makes a forced choice decision is correlated with their
confidence, with faster reaction times associated with more confident decisions (Fleming,
Weil, Nagy, Dolan, & Rees, 2010). Moreover, subjects are able to infer the subjective
confidence of another person simply by the observation of their actions (Patel, Fleming, &
Kilner, 2012), with faster movements rated as more confident and vice versa. This is
reliant on the motor system as subjects with movement disorders have difficulty inferring
the confidence of others moving at speeds very different from their own (Macerollo, Bose,
Ricciardi, Edwards, & Kilner, 2015), and disrupting activity in the motor system reduces
healthy individuals sensitivity to infer confidence from the kinematics of others (Palmer,
Bunday, Davare, & Kilner, 2016). These findings suggest that an individual may in part
infer their confidence in their decisions from their own movement parameters. Here, we
tested this hypothesis using a behavioural priming task to alter movement speed, while
participants performed a perceptual contrast discrimination task. We recorded the speed at
which the participant made their decisions. After each trial of the perceptual decision
task, we asked the participant to rate their confidence in their performance, and
calculated their metacognitive ability, as a measure of the relationship between their
confidence and accuracy.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Forty-eight healthy participants with normal or corrected-to-normal vision were recruited
(31 female, 17 male), with a mean age of 27 (range 18–53, median 24). Forty-four reported
being right-handed, four reported being left-handed. The experiment was fully explained to
participants, apart from the aim of the project and the true aim of the priming task,
which were not disclosed until debriefing to prevent bias. The experiment was approved by
the University College London Ethics Review Board. Informed written consent was obtained
from all participants and procedures were conducted in accordance with the Declaration of
Helsinki.

<hs>  Equipment</hs>
  ~~~~~~~~~

Participants were seated at a table, 60 cm in front of a Dell laptop computer, and
responded using the standard QWERTY keyboard, a marble and three touch-sensitive
containers (Fig. 1). Stimulus display and response collection were controlled by MATLAB
7.8.0 (Mathworks Inc., MA, USA) using the Cogent 2000 toolbox
(http://vislab.ucl.ac.uk/cogent.php).

<hs>  Stimuli and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~

The experiment was carried out at the Institute of Neurology, University College London.
All participants were tested individually, in the presence of the experimenter.
Participants completed two blocks of a metacognition task described below (50 trials per
block), followed by a movement speed prime (50 trials), a third block of the metacognition
task, a second movement speed prime, and finally a fourth block of the metacognition task
(Fig. 2a). The first block of the metacognition task was used as a practice session and
was not included in the analyses.

        <hss>Metacognition task</hss>

        The metacognition task was a perceptual contrast discrimination task used in
        previous studies (Fleming et al., 2010; Patel et al., 2012). The stimuli were
        comprised of two images shown in quick succession on the laptop computer screen.
        Each image comprised a circular clock-face with six Gabor gratings (circular
        patches of light and dark bars) arranged around a central fixation point (Fig.
        2b). The background was uniform grey, with a luminance of 3.66 cd/m2. In one of
        the two images, all the Gabor gratings were set to the same contrast, that is, a
        ‘baseline’ Gabor grating. In the other image, one of the Gabor gratings was set to
        a higher contrast than the other five baseline gratings, causing it to appear as a
        ‘pop-out’. Pop-out gratings were drawn from a stimulus set that varied in contrast
        between 23 and 80% in increments of 3%. The pop-out Gabor grating would appear at
        random in either the first or second image and at a random spatial position
        orientated around a central fixation point. After viewing both images,
        participants were prompted to make a decision as to which image (first or second)
        contained the pop-out grating by the appearance of the message “1 or 2” on the
        screen. Participants made their response by moving a marble from the ‘homepad’,
        positioned centrally on the table, to one of two containers, marked “1” and “2”.
        The container marked “1” was always located on the right of the homepad, and “2”
        on the left. After indicating their decision, participants returned the marble to
        the homepad. A red square framed their selection on the screen and participants
        were then prompted to indicate their confidence in their decision by typing a
        number between 1 and 99. A lower value indicated low confidence and a higher value
        indicated high confidence. No feedback was given to participants about the actual
        accuracy of their decision. Reaction times were recorded from participants while
        they indicated their decision on the contrast discrimination task, allowing us to
        operationalise movement speed as the time between the marble being removed from
        the homepad and placed in a response container. The contrast of the pop-out Gabor
        grating was varied throughout the experiment using a two-up, one-down staircase
        procedure to keep accuracy consistent (Fleming et al., 2014; Patel et al., 2012).
        The staircase operated such that after two consecutive correct decisions the
        contrast was decreased by one increment, whereas after one incorrect decision the
        contrast was increased by one increment. A correct response would thus be made on
        approximately 70% of trials, ensuring that the analysis of movement speed and
        confidence was not affected by performance. In addition to movement speed and
        confidence rating, we also recorded accuracy (correct or incorrect response) and
        signal strength (pop-out Gabor grating contrast strength) on each trial.

        <hss>Movement prime</hss>

        During this task, participants were prompted to move the marble from the homepad
        to either of the two containers marked “1” and “2”, and then return it to the
        homepad. The desired location was instructed on a trial by trial basis, by the
        appearance of a 1 or 2 on the screen. On completing the movement, participants
        were given visual feedback on the screen about their movement speed (“just
        right”/“too slow”/“too fast”) (Fig. 2c). Movement speed was calculated from the
        same reaction time parameters as those used in the metacognition task. The fast
        prime was designed to increase movement speed above natural average parameters,
        while the slow prime was designed to decrease movement speed below natural
        parameters. In the fast prime task, the goal was for participants to remove the
        marble from the homepad container and move it to the indicated container as fast
        as possible. A message of “just right” appeared on the screen if the time it took
        to complete the task was less than 1500 ms. If the time between the marble being
        removed from the homepad container and being placed in another container was
        greater than 1500 ms, a message of “two slow” appeared. In the slow prime task,
        participants were required to complete the movement of the marble from the homepad
        container to the indicated container in over 2300 ms. If they accomplished this, a
        message of “just right” appeared on the screen. If their movement speed was less
        than 2300 ms, a message of “too fast” was presented. To prevent participants
        simply delaying the onset of the movement, a message of “start time too slow” was
        presented if the participant did not remove the marble from the homepad container
        in under 1600 ms. The order in which participants completed the movement prime
        task (fast or slow first) was counterbalanced.

<hs>  Analyses</hs>
  ~~~~~~~~

As the first block of the metacognition task was used as a practice session, the analyses
presented here were conducted on blocks two through four. All trials with a recorded
movement time of zero were removed from analyses. Greenhouse-Geisser was used to correct
for violated sphericity and a more stringent alpha criterion of p = .01 was used to
correct for multiple comparisons, where required.

        <hss>Analysis 1: Relationship between movement speed and confidence</hss>

        We conducted a bivariate correlation analysis of confidence and movement speed at
        baseline (second block of the metacognition task). Movement speeds and confidence
        ratings were mean-corrected and then ranked by movement speed from fastest to
        slowest. These values were then divided into ten equal sized bins in order of
        increasing magnitude. Each bin was then averaged to produce ten mean values for
        confidence and ten mean values for movement speed. A significant negative
        relationship would replicate previous findings of an inverse interdependence
        (Baranski & Petrusic, 1998; Fleming et al., 2010; Patel et al., 2012), whereby
        higher confidence is associated with faster movement.

        <hss>Analysis 2: Effect of movement prime on movement speed</hss>

        An analysis of variance (ANOVA) was used to determine if the movement primes had
        worked. That is, was there was a significant effect of movement prime on movement
        time, in the expected direction. In other words, had the fast prime made
        participants move faster and had the slow prime made participants move slower?

        <hss>Analysis 3: Effect of movement prime on confidence</hss>

        An analysis of variance (ANOVA) was used to determine if the movement primes had
        produced a significant effect on confidence ratings.

        <hss>Analysis 4: Effect of movement prime on metacognitive accuracy</hss>

        Thus, the area below the major diagonal in an individual’s ROC curve is a measure
        of their ability to link confidence to perceptual performance (AROC), in other
        words, their metacognitive accuracy. Analysis of variance (ANOVA) was used to
        determine if the movement primes had produced a significant effect on
        metacognitive accuracy. Secondly, analysis of variance (ANOVA) and nonparametric
        permutation were used to determine if there was an interaction effect between
        correct and incorrect responses and movement primes on confidence.

<hs>  Analysis 1: Relationship between movement speed and confidence</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A bivariate correlation analysis revealed a significant negative correlation between
confidence and movement speed [r2 = −0.870, p = .001, df = 47], before the application of
any movement prime tasks (Fig. 3). This replicates previous findings of a negative
relationship between confidence and movement speed (Baranski & Petrusic, 1998; Fleming et
al., 2010; Patel et al., 2012).

<hs>  Analysis 2: Effect of movement prime on movement speed</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A one-way repeated-measures ANOVA with three levels (baseline, fast, slow) revealed a
significant effect of condition on movement speed [F(1.62,76.11) = 8.720, p = .001, ηp2 =
0.156]. Pairwise comparisons revealed significantly faster movement speeds after the fast
prime (mean = 706.394, SD = 145.070) compared to baseline measures (mean = 745.460, SD =
165.241) [t(47) = 3.161, p = .002, d = 0.469] and slower movement speeds after the slow
prime (mean = 776.829, SD = 203.351) compared to after the fast prime [t(47) = 3.948, p <
.001, d = 0.638] (Fig. 4a). The difference in movement speed after the slow prime relative
to baseline measures was not significant [t(47) = 1.597, p = .117, d = −0.239]. The
difference between movement speeds post fast prime and post slow prime was confirmed to be
significantly different with a nonparametric sign test (p < .001). One large outlying
data-point (>500 ms) can be seen in the Slow condition (Fig. 4a). Removing this
participant’s data from the analysis revealed the same result, with a main effect of
condition [F(2,92) = 13.542, p < .001, ηp2 = 0.227], driven by significant differences
between baseline and fast conditions [p = .007] and fast and slow conditions [p < .001].

<hs>  Analysis 3: Effect of movement prime on confidence</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A one-way repeated-measures ANOVA with three levels (baseline, fast, slow) revealed no
significant main effect of condition on confidence [F(1.79,84.32) = 0.070, p = .916, ηp2 =
0.001] (Fig. 4b). One large outlying data-point (>15) can be seen in the Slow condition
(Fig. 4b). Removing this participant’s data from the analysis revealed the same result,
with no significant main effect of condition [F(1,46) = 0.057, p = .812, ηp2 = 0.001].

<hs>  Analysis 4: Effect of movement prime on metacognitive accuracy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A one-way repeated-measures ANOVA with three levels (baseline, fast, slow) revealed no
significant main effect of condition on [F(1.56,73.50) = 2.389, p = .111, ηp2 = 0.048] on
AROC. Specifically looking at the difference in metacognitive accuracy between the two
primed conditions revealed significantly higher AROC after the slow prime (mean = 0.756,
SD = 0.080) than after the fast prime (mean = 0.725, SD = 0.089) [t(47) = 2.659, p = .011,
d = 0.385) (Fig. 4c). Neither of these values was significantly different to baseline
(mean = 0.747, SD = 0.105) (Baseline vs Slow [t(47) = 0.534, p = .596, d = −0.077],
Baseline vs Fast [t(47) = 1.611, p = .114, d = 0.239]). One large outlying data-point
(>0.2) can be seen in the Slow condition (Fig. 4c). Removing this participant’s data from
the analysis revealed the same result, with no main effect of condition [F(1.637,75.298) =
2.296, p = .117, ηp2 = 0.048, Greenhouse-Geisser corrected]. As AROC has previously been
found to be influenced by both Type-I accuracy/d′ and criterion (Maniscalco & Lau, 2012;
Fleming & Lau, 2014), Spearman’s correlation analyses were conducted to confirm that
changes observed in AROC were not the result of conditional changes in these measures.
There was no significant correlation between AROC and d′ [rs = 0.175, p = .234] or AROC
and criterion [rs = −0.077, p = .602] after the fast prime or between AROC and d′ [rs =
−0.123, p = .407] or between AROC and criterion [rs = 0.189. p = .199] after the slow
prime (see Supplementary Fig. 1). (See also Supplementary Fig. 2 for subject wise Type-II
ROC curves for each condition). As we had found a significant difference in metacognitive
accuracy between the primed conditions in the absence of significant changes in
confidence, we investigated whether changes in confidence were dependent on participant’s
accuracy. To this end, a two-way repeated-measures ANOVA was conducted with a factor of
response (2 levels, correct or incorrect) and a factor of condition (3 levels: baseline,
fast prime, slow prime) was performed. This revealed a significant main effect of
response, with significantly higher confidence on correct trials than incorrect trials
[F(1,47) = 169.559, p < .001, ηp2 = 0.783]. There was no significant main effect of
condition [F(1,47) = 0.823, p = .369, ηp2 = 0.005]. There was a significant interaction
between the two [F(1.99, 93.66) = 5.487, p = .006, ηp2 = 0.188]. To investigate the
location of the interaction effect, we removed the main effect of response by mean-
correcting the confidence data. Confidence ratings for correct and incorrect responses
were mean-corrected separately. As a result, the main effect of response was no longer
significant [F(1,47) = 0.823, p = .269, ηp2 = 0.021] but the results of the main effect of
condition and interaction effect remained identical [F(1,47) = 0.823, p = .369;
F(1.99,93.66) = 5.487, p = .006, ηp2 = 0.188, respectively]. Pairwise comparisons revealed
significantly higher confidence for incorrect responses (mean = 1.519, SD = 5.068) than
correct responses (mean = −1.523, SD = 4.455) after a fast prime [p = .002, d = 0.469]
(Fig. 5). All other comparisons were insignificant after correcting for multiple
comparisons. Furthermore, we tested whether this interaction effect was also significant
using non-parametric analysis. To this end, we ran a permutation test on the interaction.
We simulated 10,000 permutations to determine the distribution of values for the
interaction of interest. In each simulation, the average confidence ratings for each of
the four conditions were randomly assigned to the four conditions: Fast Prime correct,
Slow Prime incorrect, Fast Prime Incorrect, Slow Prime correct. This was performed for
each participant independently. The average interaction value was then calculated across
participants as above. Once this had been repeated 10,000 times, the distribution of the
interaction terms could be plotted, and the point of the true interaction value on this
distribution was calculated. This test also revealed a significant interaction effect
(less than 0.1% of the data had permutations at a higher value than the true value, i.e. p
< .001). In other words, this interaction effect occurred by chance in less than 0.1% of
circumstances, indicating this to be a robust effect.

<h>DISCUSSION</h>
----------

Here we tested the hypothesis that altering participants’ movement speed will disrupt
their ability to form accurate confidence judgements of their performance. The results
supported this hypothesis by indicating that after being primed to move faster than they
would naturally, participants report higher confidence in their incorrect decisions than
their correct ones. Overall, metacognitive accuracy was significantly higher when
participants were slowed than when they were quickened. These findings suggest that the
metacogntive ability to match confidence to accuracy relies on a veridical signal from the
motor system. These data are consistent with previous findings on the role of the motor
system in judgements of perceptual confidence. We replicated the finding that the speed at
which an individual makes a forced choice decision is correlated with their confidence,
with faster reaction times associated with more confident decisions (Fleming et al.,
2010). Consistent with the finding that disrupting activity in the motor system reduces an
individual’s ability to form accurate judgements of confidence (Fleming et al., 2014) and
to infer confidence from the kinematics of others (Palmer et al., 2016), here we find that
altering an individual’s kinematics behaviourally reduces their ability to infer their own
confidence. The absence of a significant direct effect of movement time on confidence in
the presence of a relationship between confidence, accuracy and movement, suggests that
the relationship between metacognition and movement is not a simple linear one. In this
study, moving faster does not increase confidence and moving slower does not decrease
confidence directly. However, moving faster when you are incorrect raises your confidence
above and beyond what it is following a correct response. It is important to note that
feedback on performance was not provided to participants in the research reported here.
Thus, the only information participants had to use in their judgement about their
confidence was the decision making process itself, including the movement made to indicate
their response. It is possible that if participants possess an internal model of their
decision making, including the movement made to indicate that decision, modifying movement
parameters may disrupt the learnt relationship between how movement time relates to
confidence. In effect, participants are no longer able to successfully ‘read out’ their
confidence from their movement time. As a result, their metacognitive ability can no
longer be predicted. The results presented here point towards a role of kinematics in
higher-order cognitive functions, such as the metacognitive monitoring of performance.
Previous research had shown that cognition has a top-down influence on an individual’s
motor behaviour, i.e. that we move faster when we’re feeling more confident (Audley, 1960;
Baranski & Petrusic, 1998; Henmon, 1911; Johnson, 1939; Patel et al., 2012; Volkmann,
1934), but the results of the current research also suggests that we may need an accurate
and veridical representation of our motor behaviour in order to form accurate and
veridical cognitive judgements. This supports a more ‘closed-loop’ view of action and
cognition, whereby there are bottom-up influences on cognition from the body, in addition
to the more closely studied top-down cogntive influences on behaviour. As such, the
present findings hold implications for traditional views of cognition, as operating on a
distinct plane from the motor system. While the results of the current research do suggest
a trial by trial correspondence between confidence and accuracy that is influenced by
ascending information from the effector about the movement speed used to indicate the
decision, the present design does not allow us to comment on whether continued processing
of this information takes place. According to decision-locus models of metacognition
confidence is solely based on evidence available at the point of the judgement (Kiani &
Shadlen, 2009; Vickers, 1979). Alternatively, according to postdecisional-locus models,
metacognitive evidence continues to be accumulated after the decision has been made
(Pleskac & Busemeyer, 2010). Evidence from transcranial magnetic stimulation (TMS)
indicated that stimulation applied after the decision affected confidence judgements and
does support the latter hypothesis (Fleming et al., 2014). The time course of this effect,
however, is not known. Further research might investigate for what length of time after
movement modulation metacognitive disruption is seen. In this study we demonstrated a
causal role of the motor system in metacognition, specifically, that how an individual
moves when they make a decision impacts their ability to relate their feelings of
confidence to their performance. This finding suggests that humans obtain information
about their confidence levels by monitoring their movement kinematics and that these
inferences can be manipulated by changing how subjects move. It would be interesting for
future research to investigate the role that organic changes in movement speed, such as
that seen in Parkinson’s disease, play in metacognitive ability and estimates of
subjective states, such as confidence. This research suggests that highlights the need for
researchers should to consider the inclusion of kinematic information in subsequent models
of metacognition. One such model is presented by Fleming and Daw (2017), which accounts
for action in self-evaluation judgements proposes that individuals form confidence
estimates by applying an analogous computation to their own actions.

<h>FUNDING</h>
-------

This work was supported by a PhD studentship awarded to E.R.P. from the Economic and
Social Research Council (ESRC) and the Medical Research Council (MRC). A.K. was supported
by a ‘European Research Council Starting Investigator Award’ [ERC-2012-STG GA313755].


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<ART>An examination of writing pauses in the handwriting of children with Developmental Coordination Disorder
================================================================================

Authors: Mellissa M. Prunty, Anna L. Barnett, Kate Wilmut, Mandy S. Plumb
DOI: 10.1016/j.ridd.2014.07.033
Year: 2014  |  Pages: 2894-2905
ASJC codes: 3203, 3204
Keywords: Detailed assessment of speed of handwriting (DASH), Developmental coordination disorder (DCD), Handwriting, Handwriting speed, Pausing

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Difficulties with handwriting are reported as one of the main reasons for the referral of children with Developmental Coordination Disorder (DCD) to healthcare professionals. In a recent study we found that children with DCD produced less text than their typically developing (TD) peers and paused for 60% of a free-writing task. However, little is known about the nature of the pausing; whether they are long pauses possibly due to higher level processes of text generation or fatigue, or shorter pauses related to the movements between letters. This gap in the knowledge-base creates barriers to understanding the handwriting difficulties in children with DCD. The aim of this study was to characterise the pauses observed in the handwriting of English children with and without DCD. Twenty-eight 8-14 year-old children with a diagnosis of DCD participated in the study, with 28 TD age and gender matched controls. Participants completed the 10. min free-writing task from the Detailed Assessment of Speed of Handwriting (DASH) on a digitising writing tablet. The total overall percentage of pausing during the task was categorised into four pause time-frames, each derived from the literature on writing (250 ms to 2 s; 2-4 s; 4-10 s and >10 s). In addition, the location of the pauses was coded (within word/between word) to examine where the breakdown in the writing process occurred. The results indicated that the main group difference was driven by more pauses above 10 s in the DCD group. In addition, the DCD group paused more within words compared to TD peers, indicating a lack of automaticity in their handwriting. These findings may support the provision of additional time for children with DCD in written examinations. More importantly, they emphasise the need for intervention in children with DCD to promote the acquisition of efficient handwriting skill.

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<h>INTRODUCTION</h>
------------

Developmental Coordination Disorder (DCD) is the term used to refer to children who
present with motor coordination difficulties, unexplained by a general medical condition,
intellectual disability, sensory or neurological impairment (American Psychiatric
Association [APA], 2013). Handwriting difficulties are mentioned in the formal diagnostic
criteria for DCD (APA, 2013), are frequently mentioned in parent and teacher reports and
are the most common reason for referral to occupational therapy services for this
population (Asher, 2006). While a knowledge base surrounding their handwriting deficits
has emerged in recent years (Jolly & Gentaz, 2013; Prunty, Barnett, Wilmut, & Plumb, 2013;
Rosenblum & Livneh-Zirinski, 2008), the underlying mechanisms of the handwriting deficits
are still unclear. In particular, there is a limited understanding of the excessive
pausing during handwriting reported in this population (Rosenblum & Livneh-Zirinski,
2008). This creates barriers for healthcare professionals in terms of prescribing
intervention, as it is unclear what the pausing behaviour in the handwriting process
actually represents. In a recent study we found that children with DCD produced less text
than their typically developing (TD) peers in four handwriting tasks from the Detailed
Assessment of Speed of Handwriting (DASH; Barnett, Henderson, Scheib. & Schulz, 2007;
Prunty et al., 2013). However, closer inspection of the handwriting process through the
use of a digital writing tablet revealed that the slowness in production was not due to
slower movement of the pen, but due to a higher percentage of the task spent pausing (with
the pen either in the air, or resting on the page) (Prunty et al., 2013). This ‘pausing
phenomenon’ in the handwriting of children with DCD was initially revealed in a study in
Israel by Rosenblum and Livneh-Zirinski (2008), where children with DCD were found to
spend considerably more time than controls with the pen in the air. However, beyond the
findings of these studies, little is known about the behaviour of pausing and the possible
cognitive or physical explanations for why they occur in the handwriting of children with
DCD. It is imperative to understand this pausing behaviour, as it has been shown to
significantly impact on the production of text in children with DCD (Prunty et al., 2013).
The concept of ‘pausing’ during writing is complex in nature and cannot be considered
without recognising handwriting as a component of the writing process. Handwriting is
‘language by hand’ (Berninger & Graham, 1998; Berninger, Abbott, Abbott, Graham, &
Richards, 2002) and there are many cognitive processes which occur before, during and
after the pen is placed on the page (Kandel, Soler, Valdois, & Gros, 2006; Van Galen,
1991). Van Galen's (1991) psychomotor model of handwriting which informs the current
investigation illustrates this, by describing the process from the transformation of
language into the sequencing of handwriting movements. At the highest level of the model
is the activation of the intention to write followed by semantic retrieval, syntactical
construction and spelling. The first step in the motor process is to select the
appropriate allograph, which according to Van Galen (1991) is the activation of the motor
programme (retrieval of an allograph action pattern from long-term motor memory).
Following the activation of the motor programme the module of size control and speed is
activated (Van Galen, 1991). The muscle synergies from both the agonist and the
antagonistic muscles are then recruited during the muscular adjustment module, which
results in the real time movement of the pen (Van Galen, 1991). Van Galen's model of
handwriting, although the most complete in the literature, is not without limitations.
According to Kandel and Spinelli (2010) it fails to account for parallel processing at
different levels of the model, which results in an increased duration of the handwriting
movements. In addition, research by Kandel, Soler, Valdopis and Gros (2006) in French
writers has demonstrated that letters are not programmed individually, but rather in
chunks, and the temporal profile is determined by the number of syllables in the word.
This emphasises the relationship between the production of handwriting and the cognitive
and linguistic aspects of writing and must be accounted for when examining pausing
behaviour in more detail. The definition of a pause in writing is inconsistent in the
literature. Rosenblum and Livneh-Zirinski (2008) defined a pause as a pen lift from the
writing tablet. However, it was not clear as to how long the pen needed to be raised from
the surface in order to be classified as a pause. In the writing literature Alamargot,
Chesnet, Dansac, and Ros (2006) and Alamargot, Plane, Lambert, and Chesnet (2010) defined
a pause as a period of 15 ms or more with the pen not in contact with the tablet. The
rationale for such a short pause threshold was to include all writing events that
occurred; including raising the pen to think of an idea or briefly to dot an ‘i’. Other
authors have omitted to define a pause and made reference only to the fact that pauses
occurred during the writing task (Accardo, Genna, & Borean, 2013). In addition to the
debate on how pauses are classified, it is also unclear even in the literature on writing
what exactly a pause represents. Thus, the pause thresholds used in the current study are
grounded in evidence where possible, while some aspects of the analysis are exploratory in
nature. In relation to pausing in children with DCD, Rosenblum and Livneh-Zirinski (2008)
proposed anomalies in the lower level processes of handwriting, such as between stroke
muscular adjustments, as reasons for excessive pausing. Alternative explanations for the
excessive pausing include physiological factors such as fatigue (Rosenblum & Livneh-
Zirinski, 2008). However, none of these theories have been tested and it remains unclear
whether children with DCD pause excessively for short periods of time (i.e. <1 s), or
whether they pause for longer periods possibly as an indication of fatigue or higher-level
writing processes such as planning (i.e. >4 s). In a study by Alamargot et al. (2010) on
French writers it was found that longer pauses possibly reflected processes such as
planning. In their study, five participants with varying levels of writing expertise were
asked to compose a text by extending a narrative provided to them. There were no time
constraints and they were asked to write as much as they felt was necessary to finish the
story. The participants included three school students, one in grade 7 (12 years old), one
in grade 9 (14 years old) and the third in grade 12 (17 years old). The remaining two
participants included a university graduate student (22 years old) and an established
expert author. The writing task was completed on a writing tablet and eye-tracking was
used to infer processes that occurred during pauses in the writing. Alamargot et al.
(2010) analysed four types of pausing activity for each writer which they labelled as
‘quartiles’. The quartiles consisted of pauses between 78 and 189 ms, 129 and 416 ms, 194
and 624 ms, 695 and 23,248 ms. The participant in grade 7 had the most pauses in quartile
4 (longer pauses) compared to the other four writers. In fact, the 7th grade writer had
pauses as long as 13–18 s at times. According to Alamargot et al. (2010) the longer pauses
were due to a strategy known as step-by-step production of text, where the child switches
between planning and formulation of the text to cope with the cognitive demands of
handwriting. Indeed as the level of writing expertise increased, the number of longer
pauses decreased substantially. Using eye-tracking Alamargot et al. (2010) were able to
investigate the longer pauses based on gaze fixations. These were classified based on
whether the participant was looking back at text, looking at the handwriting area or
looking away from the task. They found that the least experienced writers were inclined to
look away from the task, which according to Alamargot et al. (2010) was an indication of
planning. Despite the detailed analysis of pausing in typically developing children, the
nature of pausing has not been investigated in the handwriting of children with DCD and
knowing whether the pauses are driven by many pauses of small duration or a few of longer
duration is needed to inform approaches to intervention. Another issue alongside the
duration of pauses is their location within text. Previous research by Kandel et al.
(2006) on children found that words tend to be programmed prior to execution, followed by
online processing during the execution phase. According to Alamargot et al. (2010) if the
cognitive demands of handwriting exceed working memory capacity, the word cannot be
processed online, therefore a pause occurs within the word. The pause would allow the
information to be processed before completing the next word segment (Alamargot et al.,
2010). Indeed issues with word level pausing have been found in other developmental
disorders, where children with dyslexia paused for greater periods within words and
particularly around misspellings (Sumner, Connelly, & Barnett, 2012; Sumner, 2013).
According to Sumner (2013), this was indicative of difficulties at the word level due to
the constraints that spelling difficulties had on word processing. Although spelling
difficulties are distinctly different to motor difficulties, both spelling and handwriting
form the basis of transcription skills in models of writing and handwriting (Berninger &
Amtmann, 2003; Van Galen, 1991). According to Kandel et al. (2006) both spelling and motor
planning for handwriting are processed prior to writing the word and online thereafter. It
is therefore plausible that the motor difficulties associated with DCD would manifest in a
within word pause, similar to that of dyslexia, as the child would be unable to plan words
online given the strain of the handwriting on cognitive resources. Prunty et al. (2013)
hypothesised that a lack of automaticity in the handwriting of children with DCD
contributed to the lack of production of text. Indeed examining whether children with DCD
pause within words would be a method of examining automaticity of handwriting and their
ability to manage cognitive processes in parallel. Exploring this area in more detail
would provide a better description of the handwriting process in children with DCD and in
doing so inform an evidence base to support the provision of intervention in this group.
Therefore the aim of this study was to investigate the pausing behaviour demonstrated by
the same group of children with DCD in Prunty et al. (2013) compared to their TD peers. To
do so, their pausing behaviour on a 10 min free-writing task was analysed and categorised
using four time-frames chosen from the available literature on handwriting in DCD and
writing. Since children with DCD have motor difficulties, it was hypothesised that the DCD
group would pause for a greater percentage of time within smaller time-frames due to
possible difficulties manipulating the pen to form the letters. In addition, it was
anticipated that the DCD group would also pause more within-words as a result of the lack
of automaticity in their handwriting. Additional measures of pause frequency and mean
pause duration were also examined separately to compare findings from previous studies on
the handwriting process in children (Alamargot et al., 2010; Rosenblum & Livneh-Zirinski,
2008).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Twenty eight children with DCD (27 boys, 1 girl) and 28 age (within 4 months) and gender
matched typically developing (TD) controls were included in the study.

        <hss>DCD group</hss>

        All children met the DSM-5 diagnostic criteria for DCD (APA, 2013) and a
        diagnostic assessment was in line with recent European guidelines (Blank, Smits-
        Engelsman, Polatajko, & Wilson, 2012). The children had significant motor
        difficulties, with performance below the 10th percentile (24 below the 5th, 4
        below the 10th) on the Movement Assessment Battery for Children 2nd edition Test
        (MABC-2; Henderson, Sugden, & Barnett, 2007) which examines three components of
        motor competency; manual dexterity, ball skills and balance. These motor
        difficulties had a significant impact on their activities of daily living, as
        reported by their parents and evident on the MABC-2 Checklist (Henderson et al.,
        2007). A developmental, educational and medical history was taken from the
        parents, which confirmed that there was no history of neurological or intellectual
        impairment and no medical condition that might explain the motor deficit. The
        British Picture Vocabulary Scale 2nd edition (BPVS-2, Dunn, Dunn, Whetton, &
        Burley, 1997) was used to give a measure of receptive vocabulary, which correlates
        highly with verbal IQ (Glenn & Cunningham, 2005). This was in at least the average
        range for all children, confirming the absence of a general intellectual
        impairment. The Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997) was
        also used to note other behavioural difficulties reported by the parent, which
        commonly occur with DCD such as attention deficit hyperactivity disorder (ADHD)
        (Miller, Missiuna, Macnab, Malloy-Miller, & Polatajko, 2001). No child had a
        diagnosis of ADHD, but hyperactive behaviour was noted on the SDQ for seven
        children. The children were also assessed on the reading and spelling components
        of the British Ability Scales 2nd Edition (BAS-II; Elliott, 1996). These revealed
        that eight children with DCD had literacy difficulties (1 in reading, 7 in
        spelling), as defined by a standard score of less than 85 on the BAS-II
        components, although none had a formal diagnosis of dyslexia or other language
        impairment.

        <hss>Typically developing (TD) control group</hss>

        The control group was recruited through local primary and secondary schools in
        Oxfordshire, England. Teachers were asked to use their professional judgement to
        identify children without any motor, intellectual or reading/spelling
        difficulties. To ensure the children identified were free of these difficulties,
        they were individually tested on the MABC-2 Test (Henderson et al., 2007), BPVS-2
        (Dunn et al., 1997) and the reading and spelling components of the BAS-II
        (Elliott, 1996). Children were included in the control group if they scored at
        least at the level expected for their age on all measures. Children from both
        groups with a diagnosis of dyslexia, and/or those who had English as a second
        language were excluded from the study. Children in both groups who had a reported
        physical, sensory or neurological impairment were also excluded. This was to
        ensure that handwriting difficulties could not be attributed to other disorders.
        See Table 1 for performance profiles of both groups. The study was approved by the
        University Research Ethics Committee at Oxford Brookes University. Parents were
        required to sign a consent form and children were asked to either assent (below 11
        years), or counter sign the parent consent form (over 11 years). The handwriting
        component of this study took place over one 60-min session.

            The detailed assessment of speed of handwriting (DASH; Barnett et al., 2007)

            The free-writing task from the DASH (Barnett et al., 2007) was chosen for an
            extended analysis of pausing data presented in Prunty et al. (2013). This is
            an ecologically valid task in terms of its similarity and relevance to
            handwriting demands in the classroom. Free-writing involves the integration of
            all aspects of the writing process including idea generation, production of
            language, spelling and handwriting. Examining the pauses in the context of a
            free-writing task provides an overall view of the child's ability to cope with
            the demands of the writing system at work. It also provides an opportunity to
            examine whether the writing process is forced to succumb to high cognitive
            loading by imposing pauses where text would have otherwise been processed
            online. The DASH free-writing task requires the child to write about the topic
            of ‘my life’ for 10 min using their everyday handwriting. They are presented
            with a spider diagram prior to the beginning of the task which provides topics
            that they could write about. They are then given 1 min to plan their writing
            and are asked to write continuously once the task starts (Barnett et al.,
            2007). The handwriting product scores for the DCD and TD groups on this
            measure have been previously reported by Prunty et al. (2013). The DASH has UK
            norms for children aged 9–16 years. The internal reliability of the total
            score is between α = .83–.89 and the inter-rater reliability for all four
            tasks is .99, as reported in the test manual.

            <hss>Procedure</hss>

            When completing the DASH free-writing task the participants wrote with an
            inking pen on paper placed on a Wacom Intuos 4 digitising writing tablet
            (325.1 mm × 203.2 mm) to record the movement of the pen during handwriting.
            The writing tablet transmits information about the spatial and temporal data
            of the pen as it moves across the surface. The data was sampled at 100 Hz via
            a Celeron Dual Core CPUT3500@2.10GHz laptop computer. Eye & Pen version1 (EP1)
            software (Alamargot et al., 2006) was used to analyse the pauses. The pauses
            were examined in three separate analyses in order to address independent
            questions. The rationale for the three analyses is provided below and included
            the following: The categorisation of pauses into time-frames and taken as a
            percentage of the overall pause time. An analysis of the location of pauses to
            ascertain where in the writing process the pauses occurred. An examination of
            the frequency and duration of pauses. 1. Categorising the pauses The first
            analyses included the categorisation of pauses into time-frames to examine the
            pauses which attributed to the overall percentage of pause time. The analyses
            included an examination of the following. Pausing at the letter level The
            first analysis in categorising the pauses examined short pauses of between 30
            and 250 milliseconds (ms). This time-frame was chosen from the literature, as
            it is thought to represent the graphomotor component of handwriting. Alamargot
            et al.’s (2010) study mentioned above established a link between short pauses
            and graphomotor execution, particularly in pauses between 78 and 189 ms.
            However, it is not clear from the literature exactly what is meant by
            ‘graphomotor’ activity. It could include for example, the transition between
            individual letters, or a split second pause between letter strokes.
            Nevertheless, short pauses are thought to represent the pauses that occur
            specifically at the letter level. Since the study by Alamargot et al. (2010)
            included a small sample size of five participants ranging from a novice, grade
            6 writer to an expert published author, the time-frame for letter level pauses
            was adjusted to 30–250 ms for the current analysis to capture variation in the
            writing process of children. The second time-frame used to examine between
            letter pauses was 250 ms to 2 seconds (s). This was chosen based on previous
            research by Rosenblum and Livneh-Zirinski (2008), where children with DCD were
            found to pause for longer between letter strokes. Rosenblum and Livneh-
            Zirinski (2008) reported in-air time (pause time) ranging from .37 s to 1.27 s
            on the alphabet task, suggesting that this was the pause time which occurred
            between letters. Given the difference in the production of Hebrew and Latin
            based letters a 250 ms to 2 s time-frame was used to capture any variation due
            to kinematic differences in the production of Latin based letters. The pauses
            between 250 and 2 s were analysed and calculated as a percentage of the
            overall pause time. Pausing at the word-level To examine word level pauses,
            the time frame for analysis was between 2 and 4 seconds (s). This was chosen
            from the literature on writing, where a 2 s pause in typically developing
            (Alamargot et al., 2010; Alves et al., 2007; Wengelin, 2007) and atypically
            developing (Sumner, 2013) writers is considered to represent a pause from
            formulating the text in order to access a higher-level writing process such as
            planning It was important to capture pauses at or above 2 s to examine pauses
            at the word level. However, it was also important to restrict the pause time-
            frame to below 4 s, so lengthy pauses possibly due to fatigue could be
            measured separately. Two time-frames were analysed for the longest pauses in
            writing. A pause that was between 4 and 10 s was considered to represent a
            higher level writing process (generating ideas) or resting due to fatigue. A
            pause above 10 s was considered to be a significant halt in the writing
            activity, possibly due to fatigue or a lack of writing ideas. Alamargot et al.
            (2010) found that the younger, 6th grade writer paused at times for over 10 s
            which they hypothesised as representative of planning during writing. 2.
            Location of pauses The second set of analyses examined the location of pauses
            in order to evaluate the breakdown in the writing process in greater detail.
            The analyses included an examination of the following. All pauses above 2 s
            were analysed to examine pauses at the word level. This is the threshold
            previously used to explore the issue of word level pausing in relation to
            spelling difficulties in children with dyslexia (Sumner, 2013). For the
            calculation of between-word pauses, the total number of opportunities to pause
            between words was always one less than the total words produced. For example,
            if a child produced 60 words, there were 59 opportunities to pause between
            words. Since the children with DCD produced fewer words (M = 119.60 SD =
            59.59) than the TD group words (M = 156.53 SD = 43.65) (see Prunty et al.,
            2013), the between-word pauses and within-word pauses were analysed as a
            percentage of each participants’ word count. When coding a between word pause,
            if a child paused twice between two words, only one of them was coded as a
            between-word pause ‘1′, the other was labelled as miscellaneous ‘−1’. This was
            to differentiate between pauses due to programming the following word versus
            those used to revise or edit previously written text. Pauses that occurred at
            or above 2 s were examined and coded as within word pauses where appropriate.
            Not every pause was coded. For example, if a child paused more than once in a
            word then only one pause was coded, the rest were coded as miscellaneous,
            ‘−1’. Similar to between word pausing, this was to differentiate between
            pauses due to programming the remainder of the word versus those used to edit
            previously written text. Equally if a child finished writing a word and paused
            to go back and dot an ‘i’ this was also coded as ‘−1’ as it was not considered
            to be a between word or within word pause (i.e. it was not considered to be
            planning the execution of the next word). Also, if a child paused within a
            word to go back and edit a previous word and then paused within the previous
            word during the edit, only one pause was coded, the rest were coded as ‘−1’.
            The pauses within words were also coded based on the accuracy of spelling and
            legibility. Pauses within correctly spelled words were coded as ‘2’, pauses
            within misspelled words were coded as ‘3’ and pauses within illegible words
            (identified by DASH scoring instructions) were coded as ‘4’. The amount of
            time spent over 2 s within these locations were calculated as a percentage of
            overall pause time (Fig. 1). Longer 10 s pauses The longer pauses were divided
            into two categories to distinguish between those related to fatigue and those
            related to a lack of ideas for writing. To do so, the pauses over 10 s that
            occurred within a sentence or writing topic/idea were identified and were
            coded as ‘1’, suggesting that the child had already generated ideas to write
            about. In this instance, having to stop within a sentence may indicate
            fatigue. The code ‘2’ was assigned to a pause over 10 s that occurred between
            the end of a writing topic and the beginning of a new one. A pause before a
            new topic of writing would perhaps suggest that the pre-writing pause was due
            to planning. Fig. 2 illustrates an example of code ‘1’ and ‘2’. 3. Frequency
            and duration of pauses The third and final set of analyses included an
            examination of behaviours reported in the literature on writing and to report
            their presentation in children with DCD. The analyses included an examination
            of the following. The frequency of pausing was also considered here as
            Alamargot et al. (2010) found no difference in the frequency of pausing
            between a novice writer and an expert author. However, it is not known whether
            children with DCD demonstrate similar frequencies of pausing compared to TD
            children. It remains unknown whether their pausing behaviour is driven by the
            length of their pauses rather than the frequency. Therefore, the frequency of
            pauses was calculated for three time-frames, those over 250 ms (letter level
            based on Rosenblum & Livneh-Zirinski, 2008 and above), between 4 and 10 s
            (longer pauses possibly due to planning) and those over 10 s (longer pauses
            possibly due to planning or fatigue). The mean pause duration over 2 s was
            examined in order to ascertain whether children with DCD paused for longer on
            average during a word level pause compared to their TD peers. This analysis
            was based on Rosenblum and Livneh-Zirinski (2008) where children with DCD
            demonstrated a longer mean pause duration than TD peers. However, it is not
            known whether this is the case within English children with DCD.

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

For comparisons between the DCD group and TD group, tests of normality were conducted
initially and descriptive statistics for the dependent variables examined. T-tests were
used to examine the differences in the mean values between the groups for all normally
distributed measures. Those measures which did not meet the normal distribution
assumptions were compared using the nonparametric Mann–Whitney-U test. Since age was often
a significant co-variate for the handwriting product measures in our previous work (Prunty
et al., 2013) and many variables in the pausing analysis violated normal distribution,
Spearmans bivariate correlations were used to examine the relationship between age and the
pausing measures. Both groups were analysed together and separately with a significance
level set at p < .05. Regression analyses were undertaken for children with DCD to
ascertain what factors best predict pausing behaviour. In order to ensure that any
difficulties with reading and/or spelling did not influence the results, a sub analysis of
the DCD group was undertaken prior to the main analyses. Results for the 20 children from
the DCD group with at least average reading and spelling scores were compared to the eight
children with poor reading and/or spelling (standard scores below 85). There was no
significant difference between these two groups in any of the pausing analyses; therefore
the two groups were combined to form one DCD group for all subsequent analyses. A similar
sub-analysis was completed for those children who demonstrated slightly raised profiles on
the SDQ for attention. However there was no significant effect of group for any of the
pause analysis therefore the children were combined into one DCD group (n = 28).

<h>RESULTS</h>
-------

1. Categorising the pauses Table 2 illustrates the total overall pause time for each group
during the 10-min free-writing task along with the breakdown of each pause time-frame for
both groups. The total pause time and breakdown of pauses within specific time-frames are
reported in minutes. There was a significant group difference for the overall total pause
time (t(54) = 2.34, p < .023), as previously reported by Prunty et al. (2013). Pausing at
the letter level There was no effect of group for the amount of time (U = 387.0, Z =
−.082, p = .935) or percentage of pause time spent pausing within the 30–250 ms range
(t(54) = .359, p = .721). For the 250 ms to 2 s time-frame there was no effect of group
for the amount of time spent pausing within this time-frame (t(54) = −.887, p = .380).
However, there was a significant effect of group for the percentage of overall pause time,
with a greater percentage of pausing for the TD group (t(54) = −2.21, p = .032). Pausing
at the word-level There was no significant group difference for the time spent pausing at
the word level (U = 380.0, Z = −.197, p = .844) or the percentage of overall pause time
attributed to pauses between 2 and 4 s (U = 325.0, Z = −1.09, p = .272). There was no
significant group difference for the amount of time spent pausing between 4 and 10 s,
(t(54) = .420, p = 676) or for the percentage of pausing within this time frame (t(54) =
−.160, p = 874). The DCD group paused for significantly longer over 10 s (U = 323.5, Z =
−2.19, p = .029) and a greater percentage of their pausing occurred above 10 s compared to
the TD group (U = 265.5, Z = −2.14, p = .032). Fig. 3 highlights all pauses above 250 ms
in the writing of a 13 year old male participant with DCD. Fig. 4 highlights the same
pauses but in a typically developing male participant. The figures illustrate that both
participants have a high frequency of pauses. The difference is in the size of the
circles, as larger circles indicate longer pauses. Fig. 3 illustrates a higher percentage
of longer pauses. 2. Location of pauses There was no significant group difference in the
time spent pausing between words (U = 303.5, Z = −1.45, p = .147) or the percentage of
between word pauses (U = 326.0, Z = −1.08, p = .279). The DCD group paused within 22% of
the words produced during the free-writing task, compared to 16% for the TD group.
However, this difference was not statistically significant (U = 299.0, Z = −1.52, p =
.127). In terms of the duration of time spent pausing, there was a significant group
difference in within word pausing when all three categories were combined (within
correctly spelled words, misspelled words and illegible words) (t(54) = 2.28, p = .026).
Individually, there was no significant effect of group for the duration of time spent
pausing within correctly spelled words (U = 363.5, Z = −.468, p = .640) or misspelled
words (U = 322.0, Z = −1.55, p = .121), but there was a significant effect of group for
within illegible word pauses (U = 270.0, Z = -2.08, p = .037). Table 3 illustrates the
duration of pauses within words and also shows the percentage of overall pause time spent
within words and the locations of word level pausing. Longer 10 s pauses Sixty-eight
percent of children with DCD had pauses of over 10 s compared to 50% of the TD group.
There was a significant effect of group for the location of pauses, as the DCD group
paused more frequently within an idea compared to the TD group (U = 230.5, Z = −2.885, p =
.004). In terms of pausing to think of new ideas, there was no significant effect of group
for 10 s pauses before a new topic of writing (U = 342.0, Z = −.948, p = .343). A Wilcoxon
signed-rank test revealed that the DCD group produced more of their 10-s pauses within an
idea (Z = 2.78, p = .006), whereas there was no distinction between pause locations within
the TD group (Z = −.162, p = .871). 3. Frequency and duration of pauses There was no
effect of group for frequency of pausing above 250 ms (U = 363.5, Z = −.467, p = .640) or
above 4 s (U = 265.0, Z = −1.12, p = .260) but there was a significant group difference
for frequency of pausing over 10 s (U = 258.0, Z = −2.27, p = .023). For mean pause
duration, there was a significant group difference, as children with DCD paused for longer
with a mean pause duration of 5.33 s (SD = 1.90) (Mdn = 5) compared to 4.15 s (SD = 1.16)
(Mdn = 4) (U = 265.0, Z = −2.081, p = .037).

<hs>  Correlations between age and pausing measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 4 shows the Spearmans bivariate correlations that examined the relationship between
pausing and age (years and months). As can be seen, for children with DCD and their TD
peers, pause time over 4 s, mean pause duration and frequency of pausing over 10 s were
all significantly negatively related to age. In addition, for children with DCD a
significant negative correlation was found between age and the time spent pausing within
misspelled words. A significant positive relationship was found between age and time
pausing between 250 ms and 2 s for the TD group only indicating that as TD children
increase in age, the amount of time pausing within 250 ms to 2 s increases. The measure of
frequency of pauses over 250 ms revealed no significant correlations for either of the two
groups.

<hs>  Regressions</hs>
  ~~~~~~~~~~~

Regression analyses were undertaken for children with DCD to ascertain what factors best
predict the frequency of pausing over 10 s. Spelling ability was included due to the close
relationship between spelling and handwriting in models of writing (transcription skills).
Although the participants were closely matched for age, age was entered into this
regression due to the wide age range of participants and the correlation shown between age
and frequency of 10 s pauses. In addition, manual dexterity as measured by the manual
dexterity component of the M-ABC-2 test was included to see if this explained any of the
variance. The regression model was a predictor of frequency of pauses above 10 s in the
DCD group, R2 = .32, adjusted R2 = .27, F(2, 25) = 5.98, p = .008. It was found that age
significantly predicted frequency of 10 s pauses (β = −.372, p = .034), as did manual
dexterity (β = −.387, p = .028) indicating that better manual dexterity was associated
with a decrease in the frequency of pauses. Coefficients can be found in Table 5.

<h>DISCUSSION</h>
----------

Until now, the most detailed studies on handwriting in children with DCD were those of
Rosenblum and Livneh-Zirinski (2008) and Prunty et al. (2013), where children with DCD
were found to spend considerable extra time pausing, compared to their typically
developing peers. However, information was lacking on the exact nature of the pausing in
children with DCD. The aim of this study was to pinpoint and characterise the pausing
behaviour by locating the exact time-frames and locations of pauses in the handwriting of
children with DCD. This type of analysis was the first of its kind in the field of DCD and
was developed in an attempt to form a greater understanding of the pausing behaviour and
its impact on the writing process. While debates continue to surround the categorisation
and interpretation of pauses, where possible the different pause categories in this study
were selected in line with the available literature on writing. The first two research
questions investigated pausing at the grapho-motor level of the handwriting process to
examine whether children with DCD spent a greater amount of time than their TD peers
pausing at the letter level. The justification for this analysis lay in previous research
in the field of DCD where Rosenblum and Livneh-Zirinski (2008) proposed three possible
reasons for pausing, including difficulties with the perceptual aspect of the movement,
difficulties with motor memory for letter formation and/or difficulties in visualising the
letters prior to forming them. While there may well be difficulties in these areas in
children with DCD, they did not appear to contribute to the excessive pausing in this
study, as there were no group differences in the amount of time spent pausing between 30
and 250 ms and they were not shown to pause more than the TD group in the time frame of
250 ms to 2 s. This finding was also supported in our previous study (of which this is a
more detailed analysis) through the lack of group differences that emerged on the alphabet
writing task (involving writing the alphabet from memory as quickly as possible for 60 s)
(Prunty et al., 2013). In-fact the alphabet task in the previous study was the only
handwriting task that did not reveal group differences in pausing. However, it is
important to note that there may be separate issues that occur at the letter level, as the
DCD group spent more time pausing within illegible words. This calls into question the
quality of the movement and the possibility that although the children with DCD were able
to transition between letters as quickly as their TD peers, they produced poorer quality
letters. Legibility is a crucial element of handwriting performance that needs to be
examined in more detail empirically in the future. Meanwhile, it may be necessary for
clinicians to examine both speed and legibility in children with DCD given their behaviour
of pausing within illegible words. In terms of the behaviour of pausing, the group
difference did not appear to be represented at the letter level. The second time-frame
that was analysed focused on word level pauses and whether the excessive pausing in
children with DCD lay within a 2–4 s time-frame. The 2-s threshold has been previously
used in the writing literature, where a boundary of 2 s is thought to represent higher
units of processing rather than letter production (Alamargot et al., 2010; Alves et al.,
2007; Wengelin, 2007). Word level pausing was also of interest here, as previous research
by Kandel et al. (2006) has shown that spelling and motor programming of words occur prior
to the execution phase and online thereafter. This suggests that children with DCD might
be forced to pause within a word to cope with the excessive cognitive load imposed by
handwriting. However, the findings revealed no group differences in the amount of time or
percentage of time pausing within a 2–4 s time-frame. With regards to the location of word
level pausing, there was also no group difference for between-word pausing, which may
suggest that the DCD group did not take longer than their TD peers to programme words
prior to executing them. However, a lack of fluency in the writing process did emerge in
the DCD group through within word pausing, as they spent a greater amount of time pausing
within words compared to their TD peers. Therefore, although there were no differences
prior to executing the words, there were halts within words indicating difficulties with
processing information on-line (Kandel et al., 2006). Figs. 3 and 4 provide a visual
representation of this behaviour, as the sample of writing from the child with DCD clearly
exhibits pauses within-words compared to the behaviour of the TD child in Fig. 4. This
finding is in contrast to studies on other developmental disorders, where it was found
that children with dyslexia paused more both between and within-words compared to TD peers
(Sumner, 2013; Wengelin, 2007). In dyslexia, within-word pausing occurred in correctly
spelled and misspelled words (Sumner, Connelly, & Barnett, 2014). However, this was not
found to be the case here, as the DCD group did not pause more within correctly or
incorrectly spelled words, but did pause more within illegible words. Although
difficulties with spelling are distinctly different from difficulties with motor skill, it
may be that within word pausing occurs in dyslexia and DCD as a means of coping with
difficulties in transcription. In the case of DCD, this study found that the within word
pausing occurred within illegible words, a concept which should be considered in more
detail in the future. The analysis of longer pauses between 4 and 10 s was addressed in
order to distinguish between shorter, letter-level pauses and those of longer duration
attributed to higher-level writing processes. In Alamargot et al.’s (2010) study it was
found that the grade 7 (12 year old) writer had the longest pause times of the five
writers and paused for as long as 13–18 s at times. According to Alamargot et al. (2010)
the longer pauses were due to a strategy known as step-by-step production of text, where
the child switches between planning and formulation of the text to cope with the cognitive
demands of handwriting. Indeed as the level of writing expertise increased (22+ years),
the number of longer pauses decreased substantially. In the current study, this was also
found to be the case, as a relationship was found between age and duration of pauses above
10 s. However using eye-tracking Alamargot et al. (2010) were able to investigate the
longer pauses based on gaze fixations. These were classified based on whether the
participant was looking back at text, looking at the handwriting area or looking away from
the task. They found that the least experienced writers were inclined to look away from
the task, which according to Alamargot et al. (2010) was an indication of planning. In the
current study, there was a significant group difference in longer pauses above 10 s, as
children with DCD not only had more pauses above 10 s, but also paused for longer than the
TD group when doing so. This could suggest that the difference in the groups lay in the
fact that the handwriting skill in the children with DCD was not automatic enough to
concurrently process higher-level writing components. Instead, the DCD group may have been
forced to take longer pauses to plan the next phase of text. However, Chang and Yu (2010)
suggested that a decrease in strength and endurance was a possible contributor to poorer
handwriting control in children with DCD. This is possibly supported by our finding that
the children with DCD paused more above 10 s within ideas, particularly a sentence, rather
than before starting a new topic. If they were planning the content in a similar way to
that of the 7th grader in Alamargot et al.’s (2010) study, they perhaps would have been
more inclined to pause before a new topic rather than within a sentence or current idea.
Further research needs to be done to investigate this in more detail in an effort to rule
out physiological factors such as fatigue. However, practical implications follow from
this particular finding as it provides some empirical evidence to support additional time
for students with DCD to complete examinations. This type of support is termed ‘access
arrangements’ in the UK, where schools are allowed to offer the child extra time to
complete exams, if they satisfy specific criteria, usually in relation to handwriting
(Department for Education (DfE), 2013). Another interesting finding was that the TD group
spent 46% of their pause time within a time-frame of 250 ms to 2 s compared to 37% in the
DCD group. In the TD group a positive relationship between age and pausing within this
time-frame was found, possibly indicating that as TD children become more experienced at
writing, they are able to manage most of the lexical and spelling processes within this
time. However, this relationship was not found in the DCD group. This suggests that the
DCD group may need longer to process this information given that 14% of their pause time
was above 10 s compared to 5% in the TD group. This difference in the distribution of
pauses suggests that while the TD group had the ability to process the lexical and
spelling components within a range of 250 ms to 2 s, the DCD group were unable to do so
and were forced to take longer pauses as a result. From a practical perspective this
highlights the need for handwriting intervention in children with DCD, where they are
given an opportunity to acquire competency in the skill of handwriting so they can process
information on-line, in a similar way to that of their TD peers. Another area addressed in
this study was the overall frequency of pausing. According to Alamargot et al. (2010) the
frequency of pauses was not an indication of a less experienced writer. In fact, in their
study the expert author exhibited the greatest number of pauses, but the key factor lay in
their duration. The excessively frequent pausing in the expert author did not have a
costly effect on the writing, as they were short pauses allowing for on-line processing to
occur quickly. In the current study there were no group differences in the frequency of
pauses above 250 ms indicating that the costly effect of the pausing was not attributed to
pausing frequency, but due to their duration. The only exception for this was in pauses
over 10 s, where the DCD group did pause more frequently in this time-frame. Regression
analyses indicated that the frequency of pauses over 10 s was predicted by both the age of
the child and the manual dexterity score. Given the role of manual dexterity in the
frequency of pauses over 10 s, the role of fatigue should be investigated in future
research. The final area for consideration was the overall mean-pause-duration. Rosenblum
and Livneh-Zirinski (2008) found that children with DCD had a longer mean-pause-duration
than TD peers. However, without knowing how a pause was defined it is difficult to
interpret their findings. In a more specific instance, Alamargot et al. (2010) found that
less experienced writers exhibited a longer mean-pause-duration than the more experienced
authors. In the current study, the DCD group had a longer mean-pause-duration than their
TD peers. However, it seems that this may have been driven by the pauses over 10 s.
Similarly to Alamargot et al. (2010) a negative relationship with age was found for mean-
pause-duration for both groups, indicating that as children get older and possibly more
experienced at handwriting, the duration of the pauses decrease. The possible limitations
of the current analysis lay in the lack of clarity in the writing literature to justify
using particular time-frames to examine pauses. Although this study went some way in
categorising the pauses into timeframes, it is still unclear given the novel nature of
pausing analysis what the pauses actually represent. Further research needs to be
conducted in the field of writing to support this type of analysis. Within the available
research on pauses in writing, it is generally accepted that longer pauses are capturing
higher-level writing processes (Alamargot et al., 2010; Olive et al., 2009), while shorter
pauses reflect transcription (Alamargot et al., 2010). In the present study a range of
time-frames were used to capture the pausing patterns of children with DCD in an attempt
to characterise them in a way that has not been done before. Further research is needed on
handwriting in DCD to provide insight into the longer 10 s pauses in children with DCD,
which seems to be the more influential time-frame emerging from this study.


<h>REFERENCES</h>
----------

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<ART>Are you watching me? The role of audience and object novelty in overimitation
=============================================================================

Authors: Lauren E. Marsh, Danielle Ropar, Antonia F.de C. Hamilton
DOI: 10.1016/j.jecp.2018.12.010
Year: 2019  |  Pages: 123-130
ASJC codes: 3204, 3205
Keywords: Audience effect, Causal reasoning, Object Novelty, Ostracism, Overimitation, Social signalling

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study tested whether overimitation is subject to an audience effect, and whether it is modulated by object novelty. A sample of 86 4- to 11-year-old children watched a demonstrator open novel and familiar boxes using sequences of necessary and unnecessary actions. The experimenter then observed the children, turned away, or left the room while the children opened the box. Children copied unnecessary actions more when the experimenter watched or when she left, but they copied less when she turned away. This parallels infant studies suggesting that turning away is interpreted as a signal of disengagement. Children displayed increased overimitation and reduced efficiency discrimination when opening novel boxes compared with familiar boxes. These data provide important evidence that object novelty is a critical component of overimitation.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Children are predisposed to copy the actions of others with high fidelity even when they
are visibly unnecessary (Lyons, Damrosch, Lin, Macris, & Keil, 2011; Lyons, Young, & Keil,
2007). Strikingly, this “overimitation” is pervasive, occurring when children are directly
instructed to complete only necessary actions (Lyons et al., 2007) and when unnecessary
actions are performed on simple familiar objects (Marsh, Ropar, & Hamilton, 2014). Despite
a decade of research, there is little consensus on why children engage in overimitation.
Social signaling theory suggests that overimitation is akin to mimicry and serves as a
signal to others, conveying likeness or willingness to interact. Consistently, children
overimitate more in scenarios that have increased social relevance to them (Marsh et al.,
2014; Nielsen, 2006; Nielsen & Blank, 2011; Nielsen, Simcock, & Jenkins, 2008; Over &
Carpenter, 2009). However, evidence suggests that overimitation also occurs in the absence
of social drivers (Whiten, Allan, Devlin, Kseib, & Raw, 2016) and regardless of whether
irrelevant actions are demonstrated communicatively or noncommunicatively (Hoehl,
Zettersten, Schleihauf, Grätz, & Pauen, 2014). Failures in causal encoding may also play a
role in overimitation (Lyons et al., 2007, 2011), and overimitation increases with task
opacity (Burdett, McGuigan, Harrison, & Whiten, 2018). However, causal misunderstanding is
unlikely to be the sole determinant given that overimitation increases with age and into
adulthood when causal reasoning is fully matured (Marsh et al., 2014; McGuigan, Makinson,
& Whiten, 2011; Whiten et al., 2016). Alternatively, overimitation could reflect a bias to
generate and defer to normative rules when observing intentional actions (Kenward, 2012;
Kenward, Karlsson, & Persson, 2011; Keupp, Behne, & Rakoczy, 2013; Schmidt, Rakoczy, &
Tomasello, 2011). However, it remains unclear whether children defer to norms because they
are driven to signal their similarity to others or because they find it intrinsically
rewarding to do so regardless of whether a social signal is sent. Evolutionary accounts
propose that overimitation is adaptive; by copying when uncertain and refining one’s
behavioral repertoire later, imitation serves dual functions of learning about the causal
properties of objects in addition to learning social conventions (Burdett et al., 2018;
Wood et al., 2016). Each of these theories is supported by a strong set of studies but is
also refuted by others, leading to an empirical impasse. A potential explanation for this
lack of consensus is that two key features of experimental paradigms used to study
overimitation have varied between studies: the audience during the response phase and the
complexity of objects used in overimitation tasks. This study sought to systematically
manipulate these factors within a single study to examine their impact on overimitation.
People change their behavior under conditions in which they feel like they are being
observed, and this audience effect has been linked to a change in self-focus or reputation
management (Bond & Titus, 1983). Audience effects have been studied in many domains, but
recently there has been an increased focus on audience effects as a marker of reputation
management (Izuma, Matsumoto, Camerer, & Adolphs, 2011) or social signaling (Hamilton &
Lind, 2016). If overimitation is a signaling phenomenon, then it should be modulated by
the presence of an audience because it is not worth sending a signal if there is no
audience available to perceive it. However, if overimitation reflects a learning process
(either causal or normative rules), then the demonstration phase of the study when
children gain new information about the task is critical. If children extract a causal or
normative rule from the demonstration, then they will faithfully replicate the
demonstration regardless of their audience. There are methodological differences in
previous overimitation studies regarding whether the participants are observed during the
response phase. In some studies children were directly observed by the demonstrator
(Nielsen, 2006; Nielsen & Blank, 2011) or by a separate experimenter (Burdett et al.,
2018; Marsh et al., 2014; Wood et al., 2016), but in other studies the demonstrator turned
his or her back on the children during their response (Keupp et al., 2013) or left the
children entirely alone (Hoehl et al., 2014; Kenward et al., 2011; Lyons et al., 2007,
2011; Schleihauf, Graetz, Pauen, & Hoehl, 2018). To date, no single study has directly
compared these conditions. In this study, we directly compared the rates of overimitation
when children are alone, when they are in the presence of a demonstrator who turns his or
her back on the participants, or when their actions are directly observed. A second
research question relevant to overimitation is the extent to which the type of object used
in a given study influences our estimates of overimitation. Tasks used to elicit
overimitation vary with regard to the type of objects and tools that are used, ranging
from simple familiar objects to complicated puzzle boxes (see Marsh et al. (2014) and
Taniguchi & Sanefuji (2017) for discussions), although the puzzle box designed by Horner
and Whiten (2005) has dominated the field. Traditionally, overimitation was demonstrated
by comparing rates of imitation on transparent and opaque puzzle boxes under the
assumption that the causal properties of a puzzle box are apparent if it is transparent.
Indeed, research suggests that imitation is more prevalent when interacting with an opaque
puzzle box compared with an otherwise identical but transparent box (Burdett et al., 2018;
Horner & Whiten, 2005), although manipulating the opacity of the reward container had no
effect (Schleihauf et al., 2018). These studies used novel puzzle boxes, but we posit that
encountering any novel object is likely to cause some uncertainty about the way in which
it is operated regardless of its physical transparency. This uncertainty may lead to
increased overimitation (Rendell et al., 2011; Wood et al., 2016). Here we examined the
effects of object novelty on overimitation and uncertainty by directly comparing
overimitation on matched novel and familiar boxes while also examining children’s
understanding of the efficiency of the actions the children witness. If a “copy when
uncertain” bias is present, then we predict reduced efficiency discrimination for novel
objects and a corresponding increase in overimitation.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A sample of 86 4- to 11-year-old children were randomly assigned to one of three
experimental conditions (see Table 1). The sample was recruited and tested at the
University of Nottingham Summer Scientists event, which attracts middle-class families
from a mid-sized city in England.

<hs>  Stimuli</hs>
  ~~~~~~~

Two sets of six puzzle boxes were used: a novel set and a familiar set. Each box was a
simple transparent container with a removable lid; there were no hidden mechanisms or
latches. In the familiar set, the boxes were not modified further. In the novel set,
identical boxes were slightly modified to create a simple box that participants had not
encountered before. Buttons, switches, or additional decorations were added to each box
(see Fig. S1 in online supplementary material). Importantly, none of these decorations
changed the function of the boxes, but we anticipated that these decorations would affect
children’s certainty about how the objects should be operated. A small toy was put inside
each box for children to retrieve.

<hs>  Design</hs>
  ~~~~~~

This study adopted a 3 × 2 mixed design, with children randomly assigned to one of three
between-participants audience conditions: Act Alone, Disengagement, or Audience. Object
novelty was manipulated within participant. To rule out poor memory as an explanation for
why young children overimitate less, a memory control task was included. Four of the six
boxes were selected to be the overimitation trials (two novel and two familiar), and two
boxes were selected to be memory trials (one novel and one familiar). Boxes were
counterbalanced for novelty and task between participants.

<hs>  Procedure</hs>
  ~~~~~~~~~

Testing took place in a partitioned section of a room introduced to children as a “den.”
Poster boards and colored fabric were arranged such that the den was not visible to anyone
waiting outside. A hidden camera was positioned behind a hole in the fabric wall to record
the sessions without children’s awareness (see Fig. S2). Children were tested alone, with
parents waiting in the room outside. They sat at a small table, opposite the experimenter,
and completed a warm-up task (see supplementary material) before completing three
experimental tasks in a fixed order.

        <hss>Overimitation task</hss>

        The experimenter demonstrated a sequence of three actions (two necessary and one
        unnecessary) to open the box and retrieve the object (see supplementary material
        for verbatim instructions and details of the actions). The experimenter then reset
        the box behind a screen and handed it to the child with this instruction: “When I
        say ‘GO,’ I would like you to get the [duck] out of the box as quickly as you
        can.” In the Act Alone condition, the experimenter left the den, shut the door
        behind her, and called “GO” to the child to signal the start of his or her turn.
        In the Disengagement condition, the experimenter turned around in her seat, called
        “GO,” and sat still facing away from the child until the box had been opened. In
        the Audience condition, the experimenter called “GO” and continued to sit and
        watch the child while he or she retrieved the object. This sequence of events was
        repeated for four overimitation trials.

        <hss>Memory task</hss>

        Children completed a warm-up copying task before watching the experimenter open
        two more boxes (see supplementary material). The memory trials were completed
        under the same audience conditions as the overimitation trials, so the child was
        instructed, “When I say ‘GO,’ can you get the [duck] out of the box. Remember to
        copy me exactly.”

        <hss>Efficiency discrimination task</hss>

        Children rated the efficiency of one necessary action and one unnecessary action
        from each trial on a scale from 1 (very sensible) to 5 (very silly) as described
        in Marsh et al. (2014) (see also supplementary material). Efficiency
        discrimination scores were calculated by subtracting the unnecessary action rating
        from the necessary action rating on each trial. This score could range from −4
        (poor efficiency discrimination) to +4 (good efficiency discrimination), with a
        zero (0) score indicating no discrimination.

<hs>  Data coding and analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

All responses were coded from video. Overimitation on each trial was coded as 1 if the
child made a definite and purposeful attempt to replicate the unnecessary action described
in Table S1 in the supplementary material or was coded as 0 otherwise. The same criterion
was applied to the memory trials, and a total memory score was calculated for each child.
Preliminary analyses showed that overimitation did not vary as a function of trial order,
F(3, 343) = 1.85, p = .138, or puzzle box, F(5, 343) = 0.421, p = .834), so these
variables are not considered further. Mixed-effects models were run using the lme4 package
(Bates, Mächler, Bolker, & Walker, 2015) and the MuMIn package (Barton, 2013) in R
(Version 3.4.2). Separate models were used to predict propensity to overimitate and
efficiency discrimination scores. For overimitation, a full model was constructed that
included predictors of interest (audience, novelty, and efficiency discrimination) and
control predictors (age, gender, and memory) as fixed effects plus an audience by novelty
interaction. Random intercepts for child ID were included to account for the nested
structure of the data. The full model was compared with a null model that included only
control predictors and random effects using a likelihood ratio test. If the full model
outperformed the null model (i.e., a significant difference in model fit), then a reduced
model (full model minus the interaction term) was compared with the full model to
ascertain whether the interaction term significantly contributed. Efficiency
discrimination scores were analyzed using the same protocol. The full model included
predictors of interest (age and novelty), control predictors (gender and memory), and
random effects (child ID). The full model was compared with a null model (control
predictors + random effects) using a likelihood ratio test.

<h>RESULTS</h>
-------

Children in each of the three experimental conditions were matched for age (see Table 1).
The rate of overimitation was high, with 80.2% of children overimitating on at least one
trial. Memory scores were also high, with 73.3% of children performing at ceiling. Only
3.5% of children scored 0 (see Table 1). The reduced model was the best fit to the
overimitation data, explaining 12.0% of the variance by fixed effects and 69.3% of the
variance by random effects (see Tables S3 and S4 for model summaries and comparisons).
Audience was a significant predictor of overimitation, χ2(2) = 7.85, p = .020. Children in
the Disengagement condition (M = 1.83, SD = 1.64) overimitated less than those in the
Audience condition (M = 2.77, SD = 1.43, odds ratio = 7.82, 95% confidence interval [CI] =
[1.63–50.66]) and Act Alone condition (M = 2.77, SD = 1.42, odds ratio = 6.34, 95% CI =
[1.23–42.68]). There was no difference between the Audience and Act Alone conditions (odds
ratio = 1.23, 95% CI = [0.22–7.51]). Novelty also significantly predicted overimitation,
χ2(1) = 6.04, p = .014, such that unnecessary actions on familiar objects (M = 1.13, SD =
0.88) were imitated less frequently than unnecessary actions on novel objects (M = 1.31,
SD = 0.88, odds ratio = 0.46, 95% CI = [0.24–0.86]) (see Fig. 1). Age, gender, efficiency
discrimination, and memory did not predict overimitation (see Table S3). There was no
interaction between audience and novelty, χ2(2) = 0.20, p = .905, indicating that novelty
had the same effect on overimitation behavior regardless of audience. The full model best
predicted the efficiency discrimination data, explaining 10.6% of the variance with fixed
effects and 54.2% with random effects (see Tables S4 and S5 for model comparisons and
model summaries). Age predicted efficiency discrimination, χ2(1) = 13.33, p < .01, such
that the older children were better at discriminating necessary and unnecessary actions
compared with the younger children (odds ratio = 1.68, 95% CI = [1.28–2.20]). Novelty also
predicted efficiency discrimination, χ2(1) = 4.30, p = .038. Children were worse at
discriminating the efficiency of necessary and unnecessary actions when objects were novel
(M = 2.20, SD = 1.85) compared with when they were familiar (M = 2.44, SD = 1.88, odds
ratio = 1.26, 95% CI = [1.01–1.57]). There was no effect of gender or memory on efficiency
discrimination scores (see Table S5).

<h>DISCUSSION</h>
----------

The effect of audience on overimitation was assessed for novel and familiar objects across
a broad developmental spectrum. We demonstrate a clear effect of audience, but not an
increase with increasing level of observation (i.e., Audience > Disengagement > Act
Alone). Instead, we report similar levels of overimitation when children were observed and
when they were alone, but reduced imitation when the demonstrator turned away. This
intriguing set of results can be explained in two ways. First, we could argue that an
audience effect was found in the Audience > Disengagement comparison but that some
distinctive feature of the Act Alone condition disrupted this pattern. High levels of
overimitation in the Act Alone condition could be explained by an “omniscient adult
phenomenon” or “Monika effect,” whereby children falsely attribute knowledge to unseen
adults (Wimmer, Hogrefe, & Perner, 1988). When children were left alone, perhaps they were
uncertain about whether they were being observed and, by default, acted as though they
were. This mirrors other findings in developmental psychology (Meristo & Surian, 2013;
Rubio-Fernández & Geurts, 2013). Children expect a third party to act consistently with
the children’s knowledge even if there is no evidence that the third party shares this
knowledge. However, if children are provided with direct evidence that a third party does
not share the same knowledge, they will predict behavior based on the agent’s knowledge.
For example, Rubio-Fernández and Geurts (2013) demonstrated that 3-year-olds passed a
standard false-belief task when the protagonist turned her back (giving direct evidence
that the protagonist could not see the location change) but failed when the protagonist
left the scene entirely (see also Meristo & Surian, 2013). Perhaps this bias extended to
the children in our study. When children had direct evidence that they were not being
watched (Disengagement condition), they reduced their overimitation. However, when there
was no such evidence (Act Alone condition), they assumed that they were observable and
acted similarly to those children who were directly observed (Audience condition). These
findings hint toward an interesting distinction in our processing of others’ minds when
those individuals are physically present, but not watching, and when they are completely
absent. An alternative interpretation is that there was a reduction in overimitation in
the Disengagement condition because the experimenter’s actions caused the children to feel
less rapport or motivation to engage. By turning her back on the children as they acted
without excusing herself, the experimenter gave a strong signal of disinterest that could
be interpreted as ostracism (Wirth, Sacco, Hugenberg, & Williams, 2010). As a result, the
children may experience reduced rapport with the experimenter and, thus, a reduced drive
to overimitate (Nielsen, 2006). This is contrary to several other findings indicating that
children actually increase their imitative fidelity following exposure to third-party
experience of ostracism (Over & Carpenter, 2009; Watson-Jones, Legare, Whitehouse, &
Clegg, 2014) and first-person experience of ostracism (Watson-Jones, Whitehouse, & Legare,
2016). However, previous work primed ostracism indirectly via computer animations, which
do not directly depict the demonstrator, prior to the imitation task. It is possible that
disengagement from a live model during the interaction has the opposite effect on
imitation due to either the proximity or time course of ostracism. Further work is needed
to disentangle these effects. A neater direct test of the ostracism account could be to
compare rates of imitation when the experimenter excuses herself and turns around to
complete a task with those when the experimenter simply disengages without excuse (as in
this study). Both interpretations are consistent with the signaling theory of
overimitation, in which children are motivated to send a signal to people who are watching
and with whom they have a rapport. The data may also be consistent with a normative
account in which children opt to disregard the newly learned norm following ostracism,
although further research examining the flexibility of norm adherence is required to
support this argument. However, it is not clear how causal encoding can account for the
differences among the three social conditions in this study. Another striking finding was
that children were more likely to overimitate and were less able to discriminate the
efficiency of actions when interacting with a novel box compared with a familiar box.
Thus, it seems that altering the perceived novelty of the boxes reduced children’s
certainty about the causal properties of the objects, leading children to overimitate more
even though only very minor decorative changes distinguished familiar and novel boxes.
This is consistent with emerging work that illustrates increased overimitation when task
complexity increases (Taniguchi & Sanefuji, 2017). These results reflect an element of
causal understanding in any overimitation task, and using novel objects can contaminate
social effects. Alternatively, it is possible that the children in this study interpreted
the novel boxes in this task as more playful, which led them to copy more and rate the
unnecessary actions as less “silly.” However, given that the object novelty manipulation
was presented within participant and in a randomized order, it is unlikely that the
children interpreted the exact same instructions differently on each trial. Regardless,
previous studies have varied in the use of transparent and opaque puzzle boxes, with some
including redundant mechanisms, hidden catches, and superfluous decorations. This lack of
consistency increases response variability and could account for the disparity in results
from different labs. We stress that future work examining the social effects of
overimitation should carefully evaluate the findings with regard to the type of objects
that have been used to elicit overimitation. To conclude, this study provides evidence
that observation of participants during their response and stimulus familiarity can affect
overimitation. These factors may account for discrepancies among previous studies. The
finding that children reduce overimitation when the experimenter disengages is consistent
with social signaling and social rapport accounts of overimitation, and we look forward to
further studies that distinguish these motivating factors.


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<ART>Associations of insecure attachment with extreme pro-group actions: The mediating role of perceived marginalisation
================================================================================

Authors: Nelli Ferenczi, Tara C. Marshall, Katharina Lefringhausen, Kathrine Bejanyan
DOI: 10.1016/j.paid.2015.11.057
Year: 2016  |  Pages: 84-88
ASJC codes: 3200
Keywords: Attachment, Extreme pro-group actions, Intragroup marginalisation, Perceived rejection

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Can personality traits predict willingness to fight or even die for one's heritage culture group? This study examined insecure attachment dimensions - avoidance and anxiety - as predictors of perceived rejection from heritage culture members and, in turn, greater endorsement of extreme pro-group actions. Expressing extreme commitment for the heritage culture may represent an attempt by insecure individuals to reduce their perceived marginalisation and reaffirm their heritage culture membership and identity. Participants completed measures of attachment dimensions, intragroup marginalisation, and endorsement of extreme pro-group actions. Individuals who were high in anxiety or avoidance reported heightened intragroup marginalisation from family and friends. In turn, friend intragroup marginalisation was associated with increased endorsement of pro-group actions. Our findings provide insight as to why insecurely attached bicultural individuals may be drawn to endorse extreme pro-group actions.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

At approximately 8:50 am on July 7th, 2005, a series of explosions in London killed 52
people and left more than 800 injured. For the first time in modern terrorism, the threat
was not wholly external – all four men responsible were British citizens who had been
integrated into the mainstream culture. On the surface, they did not appear excluded from
the mainstream culture, as one might expect from their radicalisation (Silber & Bhatt,
2007). While there has been much speculation about their attitudes towards their British
mainstream culture, comparatively little attention has been given to their interactions
and identification with their heritage cultures (BBC News, 2005). By the same token, the
heritage culture experiences of the estimated 3000–4000 bicultural individuals with an EU
nationality who have travelled to Syria to fight with ISIS as part of their radicalisation
have also received little attention (Traynor, 2014). These examples suggest that
radicalised individuals who are citizens of Western countries may be motivated in part by
the struggle to find an identity (Silber & Bhatt, 2007). This struggle may stem from the
extent to which one feels accepted by their mainstream and heritage cultures. Mainstream
culture is defined as the dominant culture where one currently lives (Berry, 2001).
Heritage culture is defined as the culture of one's birth or upbringing, or the culture
that had a significant impact on previous generations of one's family. Conceptualisations
of marginalisation remain focused on exclusion by members of the mainstream culture and an
enforcement of culture loss (e.g., Kosic, Mannetti, & Sam, 2005); fewer studies have
examined the influence of perceived exclusion by heritage culture friends and family, in
spite of its importance for maintaining one's identity. Our study aimed to address this
research gap by investigating the association of perceived marginalisation from heritage
culture members with extreme pro-group actions, defined as willingness to commit, fight,
or even die in aid of one's heritage culture. Thus, this research may shed light on some
of the reasons why Westernised bicultural individuals might be drawn to joining extremist
groups as a compensatory reaction in response to perceived rejection from their heritage
culture. What role does perceived rejection play in the construction of our identity?
Humans share a fundamental need to form meaningful interpersonal attachments (Baumeister &
Leary, 1995). Rejection from other heritage culture members – defined as intragroup
marginalisation – can occur when individuals develop ties to two or more cultures, and as
a result, no longer conform to the expectations of the heritage culture identity
(Castillo, Conoley, Brossart, & Quiros, 2007). These detrimental impacts and experiences
of intragroup marginalisation may be shaped by personality; those who are insecurely
attached and chronically perceive rejection report increased intragroup marginalisation
(Ferenczi & Marshall, 2014). A compensatory response to intragroup marginalisation may be
to reaffirm one's heritage culture identity through endorsing pro-group actions. In an
effort to gain acceptance and avoid rejection, do insecurely attached individuals endorse
pro-group actions that are extreme?

<hs>  Attachment</hs>
  ~~~~~~~~~~

Attachment is conceptualised as an internal working model of self and others that informs
their interactions over the course of their life (Bowlby, 1969). Views of self and other
are essential for constructing bicultural identity and perceived rejection from in-group
members. Secure attachment is typified by an internalised positive model of the self; that
is, one feels worthy of love, and also a positive model of ‘other’, as significant others
are thought of as being available and trustworthy (Bartholomew & Horowitz, 1991). Secure
attachment is conceptualised as low anxiety and avoidance (Mikulincer, Shaver, Sapir-
Lavid, & Avihou-Kanza, 2009). Anxious individuals have a negative model of self, and tend
to be preoccupied with winning affection from others (Mikulincer, 1998). They endorse
positive models of other, which results in the individual feeling unworthy of love
(Mikulincer, 1995). For those high in anxiety, the attachment system is hyper-activated in
response to perceived rejection threats (Campbell & Marshall, 2011). Anxious individuals
are sensitive to rejection, recalling emotionally painful memories with ease whilst unable
to repress the resulting negative effects (Mikulincer & Orbach, 1995). Their difficulty in
recovering from past experiences of rejection (Marshall, Bejanyan, & Ferenczi, 2013) may
generalise to intragroup marginalisation. Conversely, individuals who are avoidant
perceive others as untrustworthy and unreliable, and hold positive views of their self,
resulting in exaggerated self-reliance (Li & Chan, 2012). Avoidant individuals engage in
deactivating strategies in response to threat, such as moving away from attachment figures
and suppressing emotions to pre-empt the frustration and pain arising from rejection
(Shaver & Mikulincer, 2002). Although they may appear to have high self-esteem
(Mikulincer, 1998), it may be little more stable than a house of cards. Highly distressing
events can unearth anxiety (Mikulincer & Orbach, 1995) and result in difficulties coping
with rejection (Birnbaum, Orr, Mikulincer, & Florian, 1997). Although they may be adept at
suppressing negative impacts of mild threats, they nonetheless experience heightened
psychological distress in response to stress (Stanton & Campbell, 2013). Despite their
defences, they report a need to belong to close others (Carvallo & Gabriel, 2006). We
argue that perceiving rejection from close others qualify as severe threats. Thus, we
expected that individuals high in avoidance would also perceive greater intragroup
marginalisation from close others such as family and friends.

<hs>  Intragroup marginalisation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Social rejection can be conceptualised as a social death (Williams & Nida, 2011). The
negative effects of rejection remain even if it is merely perceived (Smith & Williams,
2004). Individuals who perceive rejection in the form of intragroup marginalisation may
face accusations of betraying their heritage culture, such as by assimilating into the
mainstream culture (Castillo, Zahn, & Cano, 2012). They may perceive that family and
heritage cultural friends view them as threatening the distinctiveness of the cultural
group through deviating from the prescribed social identity (Castillo et al., 2007). Thus,
no longer meeting the expectations of the heritage culture, individuals may feel rejected,
regardless of their own wishes to maintain their heritage culture identity (Ferenczi &
Marshall, 2014). We hypothesised that those individuals high in anxiety or avoidance, who
have a heightened sensitivity to rejection (Shaver & Mikulincer, 2002), would report
greater intragroup marginalisation (Ferenczi & Marshall, 2014). In turn, what compensatory
actions would they endorse in striving for acceptance and positive perceptions of their
self from their heritage culture in-group?

<hs>  Extreme pro-group actions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Individuals strive for others to perceive them as they do themselves (Swann, 1983). In
fact, we engage in a continuous construction of ourselves that draws the feedback from
close others (Swann & Brooks, 2012). Reflected appraisals – perceptions of how others
perceive oneself – play an important role in constructing identity, in particular for
individuals who may experience ambiguity resulting from a dual identity (Khanna, 2004). If
there is an indirect threat to one's opportunity to self-verify, then they may engage in
compensatory self-verification to re-establish coherence (Swann & Brooks, 2012). Self-
verification can occur at the level of the collective self – the evaluation of the self in
relation to one's in-group (Chen, Chen, & Shaw, 2004). In the context of the current
study, if a British Asian woman perceives herself as Punjabi, yet finds her family
criticising her Punjabi language skills, then she might come to question her knowledge of
herself. To avoid threats to the very foundation of her identity, what can she do? We
hypothesised that those who experience intragroup marginalisation will self-verify by
endorsing extreme pro-group actions, in the hope of reaffirming their heritage culture
identity. Thus, by supporting attitudes which are extreme, individuals can demonstrate
their loyalty and commitment. Our study is, to our knowledge, the first to link
attachment, intragroup marginalisation, and extreme pro-group actions. We hypothesised
that insecure attachment would be linked with intragroup marginalisation, and, in turn,
with greater endorsement of extreme pro-group actions.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

208 participants (Mage = 30.29, SD: 11.74; female: 105, male: 100; missing: 2,
transgender: 1) completed the measures. Inclusion criteria for the study required each
participant to have a different heritage and mainstream culture (i.e., they were a first-
or later-generation migrant). 49% of participants reported that they were first-generation
migrants (Myears residing in mainstream culture = 11.27, SD: 8.47); 51% were born and
raised in a mainstream culture that was different to their heritage culture (second- or
later-generation migrants). Participants reported the following heritage cultures:
European (23%), Latin American (18%), East Asian (17%), South Asian (9%), Southeast Asian
(9%), Middle Eastern/North African (8%), African (7%), Jewish (3%), Native American/First
Nations (3%), Caribbean (1%), Mixed (1%), and North American (1%). The majority of
participants reported living in a North American mainstream culture (83%); they also
reported living in Europe (15%), East Asia (1%), and the Middle East (1%). The majority of
participants reported being in a relationship (65%). Participants were recruited online
via Amazon MTurk (paid $0.30), or through the Social Psychology Network (no reward). As an
attention-check measure, we asked participants to report the date, and compared this with
their timestamp. All materials were in English.

        <hss>Berkeley personality profile</hss>

        Neuroticism refers to emotional instability and correlates with increased insecure
        attachment (Shaver & Brennan, 1992). We included seven items from the neuroticism
        subscale (Harary & Donahue, 1994; α = .82; e.g., “I worry a lot”; 1 = Disagree
        strongly, 5 = Agree strongly) to establish that the association of insecure
        attachment with intragroup marginalisation could not be attributed to neuroticism.

        <hss>Experiences in close-relationships – short form (ECR-S)</hss>

        The ECR-S (Wei, Russell, Mallinckrodt, & Vogel, 2007) is a twelve-item scale (1 =
        Strongly disagree, 5 = Strongly agree) that measures general attachment style to a
        partner. It is composed of two subscales: anxious (α = .69; “My desire to be very
        close sometimes scares people away”) and avoidant attachment (α = .80; “I am
        nervous when partners get too close to me”).

        <hss>Intragroup marginalisation inventory (IMI)</hss>

        We included two subscales from the IMI (Castillo et al., 2007): one focused on
        rejection from family members (11 items, α = .84; “Family members laugh at me when
        I try to speak my heritage/ethnic culture group's language”), and one focused on
        rejection from heritage culture friends (16 items, α = .91; “Friends of my
        heritage culture group tell me that I am a ‘sell-out’”; 1 = Never/Does not apply,
        7 = Extremely often). Perceived rejection can be in the form of criticism,
        mocking, or perceived differences between the self and family/friends on
        dimensions that are important to heritage identity.

        <hss>Extreme pro-group actions</hss>

        Swann, Gómez, Seyle, Morales, and Huici (2009) developed this scale to investigate
        participants' willingness to endorse extreme pro-group actions, using it as a
        proxy for extreme pro-group behaviour (Swann, Jetten, Gómez, Whitehouse, &
        Bastian, 2012). By measuring the level to which individuals endorse such actions,
        we could highlight one of the ways in which individuals may choose to self-verify
        in the face of rejection. The subscale measuring willingness to fight for the
        group was composed of five items (e.g., “I would fight someone insulting or making
        fun of my heritage country as a whole”). A two-item subscale centred on
        participants' willingness to die for their heritage culture (e.g., “I would
        sacrifice my life if it gave the heritage culture group status or monetary
        reward”). We created three items to extend the range of pro-group actions to
        include increased commitment to the heritage culture (“The needs of my heritage
        culture group come before my own”, “I would be willing to attend a protest if my
        heritage culture group were threatened”, and “I would be willing to donate money
        to organisations promoting interests of my heritage culture group if need be”). We
        collapsed the ten items into one overall measure of extreme pro-group actions (α =
        .91; 1 = Totally disagree, 7 = Totally agree).

<hs>  Descriptive statistics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Descriptive statistics and Pearson's correlations are reported in Table 1. We ran
preliminary hierarchical regressions controlling for gender (− 1 = male, 1 = female), age,
cultural background (− 1 = 2nd/+ generation migrants, 1 = 1st generation migrants), and
neuroticism. Results revealed that neuroticism was positively correlated with
marginalisation from family, β = .28, p < .005. Over and above the control variables,
avoidant and anxious attachment were linked with increased marginalisation from friends (β
= .27, p < .001 and β = .19, p < .05, respectively) and family (β = .23, p < .005, and β =
.15, p = .05, respectively). Anxious and avoidant attachment were correlated with greater
endorsement of extreme pro-group actions, (β = .19, p < .05 and β = .19, p = .05,
respectively). Friend intragroup marginalisation positively correlated with extreme pro-
group actions, β = .35, p < .005. We then used structural equation modelling to
investigate the pathways between anxious and avoidant attachment, family and friend
intragroup marginalisation, and endorsement of extreme pro-group actions.1 Hu and Bentler
(1999) recommended that for an acceptable model fit, the following requirements must be
met: the chi-square statistic should be non-significant, the comparative fit index (CFI)
should be .95 or greater, and the root mean square error of approximation (RMSEA) should
be .06 or less. We used item parcelling as it requires estimation of fewer parameters and
thus results in a more parsimonious and stable model (Little, Cunningham, Shahar, &
Widaman, 2002). Items were assigned to one of two parcels at random for each latent
variable (Little et al., 2002); this method provides a superior model fit in comparison to
others (Landis, Beal, & Tesluk, 2000).

<hs>  Measurement model</hs>
  ~~~~~~~~~~~~~~~~~

We conducted a Full Information Maximum Likelihood (FIML) procedure in AMOS to include
partially missing data. The measurement model provided a good fit to the data [χ2(25) =
33.41, p > .05, CFI = .99, RMSEA = .04 (CI = .00, .07)]. All of the indicators loaded
significantly onto their respective latent variables (all βs ≥ .58, p < .001).

<hs>  Structural model</hs>
  ~~~~~~~~~~~~~~~~

A fully saturated structural model was tested initially; we included structural
covariances between anxious and avoidant attachment, and family and friend intragroup
marginalisation. Two structural coefficient pathways were non-significant: the pathway
between avoidant attachment and extreme pro-group actions, and the pathway from family
intragroup marginalisation to extreme pro-group actions. To create a more parsimonious
model, we removed these pathways in order of lowest standardised regression weights. Chi-
square difference tests did not yield significant differences in model fit, respectively:
[χ2D(1) = .09, p > .05], and [χ2D(2) = .65, p > .05]. The final model (see Fig. 1)
provided a good fit [χ2(27) = 34.06, p > .05, CFI = .99, RMSEA = .04 (CI = .00, .07)].2

<hs>  Tests of indirect effects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Bootstrap procedures in AMOS3 were used to test the indirect effects of anxious and
avoidant attachment on endorsement of extreme pro-group actions via friend intragroup
marginalisation. Inspection of 95% bias-corrected confidence intervals (CI) from 1000
bootstrap samples found support for the indirect effects of anxious [β = .09, p < .005
(CI: .03, .15)] and avoidant [β = .14, p < .005 (CI: .18, .25)] attachment on endorsement
of extreme pro-group actions via increased friend intragroup marginalisation.

<hs>  Attachment and intragroup marginalisation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our findings contribute to understanding the wide-reaching impact of attachment dimensions
on chronic tendencies of perceiving rejection from others. Anxious individuals may
perceive greater intragroup marginalisation because they are sensitive to rejection
(Campbell & Marshall, 2011) and perceive themselves as having poor capabilities
(Mikulincer & Florian, 1995) in their heritage culture. For example, they may feel that
they are not proficient in their heritage culture language. The parallel findings for
individuals high in avoidance provide further support for the fragility of their positive
self-view (Mikulincer, 1995). Although avoidant individuals claim to be highly self-
reliant, they still experience the need to belong (Carvallo & Gabriel, 2006). They too may
perceive pressure and rejection from those in their closest social circle on the basis of
their heritage culture identity. The current findings provide a link between the
rejection-sensitivity of insecurely attached individuals to endorsement of extreme pro-
group actions, partially through experiences of friend intragroup marginalisation.

<hs>  Intragroup marginalisation and extreme pro-group actions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

One reason why only rejection from friends was linked to greater endorsement of pro-group
actions may be because of the more fragile nature of friendships compared to family bonds
(Allan, 2008). Whilst individuals may feel rejected from their family on the basis of
their heritage cultural identity, they may nonetheless perceive acceptance on binding
cultural conceptions of ‘blood’. As friendships are largely voluntary and based on
equality (Hays, 1988), intragroup marginalisation may be more detrimental for their
maintenance. Close friendships are often considered a ‘chosen’ family, fulfilling an
individual's needs for belonging and closeness (Wrzus, Wagner, & Neyer, 2012). Thus,
individuals may endorse extreme pro-group actions to reaffirm their heritage cultural
identity, and in doing so, realign balance in the friendship after perceiving rejection.
Through measuring endorsement of, as opposed to actual pro-group actions, we could
investigate the responses of individuals who have ostensibly not engaged in extreme
actions. Indeed, many of the EU citizens who joined ISIS are young, often well-educated,
bicultural individuals with no prior history of criminal offences. Research needs to shift
from conceptualising terrorism as a result of personality disorders or irrationality
removed from the general populace (Crenshaw, 2000; Kruglanski & Fishman, 2006). Our
findings indicate that individuals sampled from a broad demographic may indeed endorse
actions that appear extreme. Individuals are more likely to identify with radical groups
when they perceive uncertainty in the form of threat to their values and behavioural
practises (Hogg, Meehan, & Farquharson, 2010). We posit that individuals who report
intragroup marginalisation experience uncertainty in terms of their heritage culture
identity. Thus, they may shift to endorse more radical ideas as a method of alleviating
uncertainty and re-establishing their membership within the heritage culture group.

<hs>  Limitations and further research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Future research should seek to further validate these relationships in several ways.
First, additional research should focus on priming rejection from one's heritage culture.
Second, research should investigate whether the process outlined here is unique to
bicultural individuals, or whether monocultural individuals may also perceive generalised
rejection from the mainstream culture and, in turn, endorse extreme pro-group actions.
However, this process would be different to intragroup marginalisation as monocultural
individuals would not experience a tension between two cultural identities. Third, other
antecedents of intragroup marginalisation should be measured, such as general negativity
towards others. Fourth, future research should investigate the direct association of
intragroup marginalisation with attitudes towards militant organisations, such as Al-
Qaeda, as well as with overt pro-group behaviours. Finally, although we measured
endorsement of extreme behaviour, in part because of the ethical difficulties of measuring
actual extreme behaviour, attitudes can predict intentions and behaviour according to the
theory of reasoned action (Ajzen & Fishbein, 1980).

<hs>  Concluding remarks</hs>
  ~~~~~~~~~~~~~~~~~~

Malik (2015) reports that the Westernised individuals who join ISIS are as removed from
Muslim communities as from the mainstream cultures in which they live. Our findings
provide support that measures which encourage biculturalism are crucial on both the parts
of mainstream cultures and of heritage cultural communities to prevent individuals who are
struggling to find an identity in perceiving rejection from their heritage culture.
Clinical and community interventions which focus on individuals' heritage identities
alongside their integration to the mainstream society could ameliorate experiences of
rejection which may lead to detrimental attitudes and, ultimately, to tragedies similar to
the London bombings.


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<ART>Audience gaze while appreciating a multipart musical performance
================================================================

Authors: Satoshi Kawase, Satoshi Obata
DOI: 10.1016/j.concog.2016.09.015
Year: 2016  |  Pages: 15-26
ASJC codes: 3204, 3205
Keywords: Audience, Audiovisual, Ensemble performance, Eye tracking, Gaze, High-voice effect, Joint attention, Multipart music, Musical communication, Singing

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Visual information has been observed to be crucial for audience members during musical performances. The present study used an eye tracker to investigate audience members’ gazes while appreciating an audiovisual musical ensemble performance, based on evidence of the dominance of musical part in auditory attention when listening to multipart music that contains different melody lines and the joint-attention theory of gaze. We presented singing performances, by a female duo. The main findings were as follows: (1) the melody part (soprano) attracted more visual attention than the accompaniment part (alto) throughout the piece, (2) joint attention emerged when the singers shifted their gazes toward their co-performer, suggesting that inter-performer gazing interactions that play a spotlight role mediated performer-audience visual interaction, and (3) musical part (melody or accompaniment) strongly influenced the total duration of gazes among audiences, while the spotlight effect of gaze was limited to just after the singers’ gaze shifts.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

What do audiences look at when they watch and listen to an ensemble music performance?
Many studies have explored what factors attract visual attention, when they attract the
attention, and how (reviewed in Carrasco, 2011). In particular, gaze has been observed as
an indicator of visual attention. However, the gaze of the audience of a musical
performance remains unclear even though visual information has a great impact on an
audience appreciating an audiovisually presented musical performance (e.g., Platz &
Kopiez, 2012). Investigations of gaze in various situations thus contribute to a holistic
understanding of human behavior. Taking into account auditory attention, while
appreciating audio-visually presented music, a complicated audience gaze is likely to
emerge. This assumption is supported by findings that visual attention interacts with
auditory attention. For example, in brain activity, the circuit related to auditory
attention is linked with the circuit related to vision (Winkowski & Knudsen, 2006). In
Driver and Spence’s review of crossmodal attention, auditory stimuli affect visual
attention, while visual stimuli do not influence auditory attention (Driver & Spence,
1998). These findings suggest that visual attention is associated with the cognition of
musical sound. In the present study, we particularly focused on the gaze of the audience
while the audience is appreciating an ensemble performance in order to explore the
psychological process of music appreciation as audiovisual experience. An ensemble
performance involves multiple musical parts and performers that can potentially divide or
integrate the audience’s attentions, as well as inter-performer interaction cues (reviewed
in Keller, 2014) that could influence performer-audience visual interactions. Despite such
intriguing aspects, fundamental perspectives on audience gaze are insufficient. What
attracts the gaze of an audience during the appreciation of a musical performance? Do
audiences evenly look at the whole of an ensemble, or do they look at specific performers?
If so, why? To find out, we explored gazing behavior during ensemble music appreciation.
First, in accordance with the dominance of a musical part in auditory attention when
listening to multipart music that contains different melody lines, we hypothesize that
auditory attention, depending on the musical part (melody or accompaniment, namely soprano
or alto in the present study), influences visual attention. Soprano is the highest female
voice (Jander, 1980), while alto is lower than soprano. Ensemble performance often
involves multipart that could potentially yield a bias of auditory attention. For example,
prior studies have shown a higher-pitched effect, in which higher voices attracted
listeners’ attention in multipart music (e.g. Fujioka, Trainor, Ross, Kakigi, & Pantev,
2005). Nevertheless, in audiovisual music appreciation, no study has examined whether such
auditory attention corresponds to visual attention. Second, we hypothesized that inter-
performer gazing affects an audience’s visual attention. In accordance with the joint-
attention theory, we highlighted, in particular, one potential function of the gaze as
spotlight, as suggested by Kawase’s study (Kawase, 2009a), in which a singer in a pop band
directed her gaze toward a co-performer who played a solo part. Since previous studies
have mostly focused on performer-audience visual interactions in solo performances, this
hypothesis regarding ensemble performances differs from available findings. In light of
the reciprocal interaction model including performer-audience communication flows during
musical performances (Hargreaves, MacDonald, & Miell, 2005; Kawase et al., 2007), gaze
interactions between performers (Davidson, 2005; Kawase, 2009a; Kawase, 2014a; Kawase,
2014b; Moran, 2010) can influence audiences’ visual attention. This hypothesis is also
supported by the joint attention theory that revealed that a person’s visual cue can
attract other person’s visual attention (e.g. Baron-Cohen, 1995; Frischen, Bayliss, &
Tipper, 2007). If this theory is applicable to musical performances, gazing interactions
between performers could influence the visual attention of audiences. Data of audiences’
gazes during musical performances could shed light on additional aspects of joint
attention. Third, in the context of audiovisual interactions during multimodal music
appreciation (e.g. Platz & Kopiez, 2012), it would be beneficial to investigate how audio
and visual attention are associated with each other. We hypothesized that certain
audiovisual interactions alter the audience’s gaze. Therefore, we investigated how the
audience’s visual attention reacted when auditory attention (e.g. dominance of a musical
part) and visual attention (joint attention between the performer and the audience)
simultaneously emerge. Given that ensemble musical performance potentially causes
attention allocation in both auditory (multipart) and visual (multi-party) aspects, this
attempt could lead to an understanding of attention in simulated multimodal situations in
the real world. To investigate these issues, we used eye tracking to analyze audience
members’ gaze when watching an actual performance by a singing duo. Given that multipart
music is often played in an ensemble, and that gaze between performers naturally emerges
in music performance, our attempt would be in agreement with ecological validity. Factors
that support our hypotheses are reviewed below.

<hs>  Auditory attention in multipart music</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Prior studies have explored how listeners recognize each melody in multipart music. In
terms of auditory attention, higher-pitched parts have been observed to attract more
listeners’ attention. Gregory’s (1990) study of melody recognition in multipart music
found that participants could recognize each melody in multipart music with significant
accuracy and that factors such as the relationships and distances between keys and pitches
affected recognition; specifically, higher melodies were better recognized than lower ones
when there were significant gaps in pitch between melodies. With respect to the
relationship of melody and accompaniment part, Uhlig, Fairhurst, and Keller (2013)
examined the influence of structural and temporal aspects on auditory attention in
multipart music and showed that the melody part was perceived as leading compared to
accompaniment part. Furthermore, cognition research has elucidated high-voice superiority
in polyphonic music, meaning that listeners pay more attention to higher pitches (Fujioka
et al., 2005; Trainor, Marie, Bruce, & Bidelman, 2014), even among very young (three-
month-old) children (Marie & Trainor, 2014). By demonstrating the model, Trainor et al.
(2014) suggested that such high voice superiority was derived from characteristics of the
auditory nervous system. Other studies have explored how ensemble performers integrate
multipart melodies by measuring behavioral (Bigand, McAdams, & Forêt, 2000) and brain
activity (Ragert, Fairhurst, & Keller, 2014). Although these findings yield important
perspectives on perceptions of multipart music, it remains unclear how musical parts
(melody and accompaniment) affect the visual attention of audiences during ensemble
performances. Thus, the present study examined the influence of musical parts on the gaze
of audience members.

<hs>  Joint attention as one of the functions of gazing in everyday communication</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Joint attention represents the sharing of attention among other person(s) in communication
when the other person(s) are referring to something. This function’s tendancy to alter
attentions has been investigated in daily communication (e.g., Frischen et al., 2007),
child development (e.g., Tomasello, 1995), and human-robot communication (Staudte &
Crocker, 2011). Before discussing the validity of focusing on joint attention between
performers and audience members, joint attention in daily life should be reviewed. Joint
attention, one of the fundamental functions of gaze, has been described as a phenomenon in
which a person’s gaze direction shifts another person’s attention (e.g., Baron-Cohen,
1995; Frischen et al., 2007). Langton, Watt, and Bruce’s meta-analysis of gaze functions
(2000) suggested that joint attention is a phenomenon in which eye information provides
substantial cues for another’s gaze direction, and that gaze direction causes reflexive
shifts in an observer’s visual attention based on neural mechanisms. Other studies have
also reported the “following gaze.” For example, adults attend to objects that others
attend to and switch others’ attention through gazing (Shepherd, 2010). Such phenomenon of
joint attention can be examined by measuring gaze. Previous studies explored gaze through
observation (e.g., Tomasello & Farrar, 1986), eye tracking via a head mount eye tracker,
(e.g., Hayhoe & Ballard, 2005), or measurement of gaze on a monitor (e.g., Schilbach et
al., 2010). In the present study, we observed gaze on a monitor through an eye tracker.
This joint attention theory could predict gaze as a spotlight between performers in
ensemble music performance. Kawase (2009a) measured the gazes of a popular music band’s
members during a concert and found that the performer’s gaze differed according to
instrument and musical structure. Kawase (2009a) suggested that the gaze of the vocalist—a
frontwoman performing a central role in the band—functioned to spotlight soloists by
attracting joint attention from audience members. In the present study, we examined this
assumable function of gaze.

<hs>  The influence of audio-visual interactions on audiences during music performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Visual information such as gaze (Antonietti, Cocomazzi, & Iannello, 2009; Kawase, 2009a;
Kurosawa & Davidson, 2005), body movement (Broughton & Stevens, 2009), facial expression
(Thompson, Russo, & Livingstone, 2010), clothing (Griffiths, 2008), and physical
appearance (Wapnick, Mazza, & Darrow, 1998) strongly influence the way audiences decode
music performances (Platz & Kopiez, 2012). Visual information has also been observed to
influence audience perceptions of expression (Davidson, 1993), emotion (Dahl & Friberg,
2007), tone duration (Schutz & Lipscomb, 2007), and performance proficiency (Tsay, 2013)
during musical performances. Audiences also attempt to ensure good visibility of the
performers when selecting seats in a concert hall (Kawase, 2013). Meanwhile, the influence
of auditory information in audiovisually presented music has been reported for audience
judgments of tension during a clarinet performance (Vines, Krumhansl, Wanderley, &
Levitin, 2006), emotions evoked by drums and saxophone (Petrini, McAleer, & Pollick,
2010), portrayed age and gender of characters in Gidayubushi, traditional Japanese
performing arts (Kawase, 2009b), and expression in opera (Silveira & Diaz, 2014). Given
most of these findings of the dominance of audio or visual cues during the appreciation of
audiovisually presented music focused on a solo music performance, it would be beneficial
to investigate ensemble performance that potentially causes complications in the attention
of audience due to its multifaceted auditory and visual factors.

<hs>  Aims and research questions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The present study aimed to quantitatively investigate audience members’ gaze data during
an audiovisually presented performance by focusing on the auditory (melody or
accompaniment) and visual aspects (joint attention) of singers. The main research
questions were as follows: (1) Do singers’ musical parts (melody or accompaniment, namely
soprano or alto in the present study) affect audience members’ visual attention? (2) Does
gazing between performers affect audience’s visual attention? (3) How does the audience’s
visual attention react when auditory attention (e.g. dominance of the part) and visual
attention (joint attention) simultaneously emerge?

<hs>  Research design</hs>
  ~~~~~~~~~~~~~~~

We showed participants a videotaped performance and analyzed their gaze points using an
eye tracker.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Thirty people participated in the experiment. We analyzed data for 20 (Mage = 20.8; 12
female and 8 male) due to low data clarity for the other 10 (e.g., the duration of
measurement was extremely short due to obstacles such as eyeglass frames). All
participants were non-music majors.

<hs>  Materials</hs>
  ~~~~~~~~~

We selected a performance by a singing duo as audiovisual stimulus. We made this selection
for the following reasons: (1) a duo is the simplest form of multipart (i.e., melody and
accompaniment) ensemble, (2) the absence of instruments makes it easy to control gazing in
the experiment, and (3) vocal performance is not accompanied by additional body
movements—such as hand movements for instrument manipulation—that could potentially
attract visual attention. Six audiovisual stimuli of the female duo singing (two singing
parts: soprano and alto, in three gaze conditions: unreciprocated gaze, one from each
singer, and a third with absence of eye contact) that were generated in the recording
experiment were used. To generate audiovisual stimuli, we recorded a two proficient female
singing duo that utilized both melody and accompaniment (Mage = 28.5). The singers sang
the Spanish ballad “Juanita” (Norton, 1951), which was separated into melody (soprano) and
accompaniment (alto). The singers used “na” vocalizations without instrumental
accompaniment. The average total duration of each stimulus was about 26 s, which
incorporated the first half for 13 s and the latter half for 13 s. To examine gaze shifts
according to musical parts, in the middle of the piece where the first half (approximately
13 s from the onset of the performance) has passed and the latter half (the rest of
approximately 13 s of the performance) began, the melody and accompaniment parts switched.
Thus, the singer assigned the melody part switched to accompaniment after the first half
and vice versa. To avoid attracting visual attention, we prepared the experimental
condition as follows: First, we put a blackout curtain behind the singers to conceal any
other objects. Second, the singers were instructed to deliver a natural performance but
maintain a stationary position to avoid any significant movements that might attract
visual attention. Third, both singers wore white shirts and adopted modest hairstyles
(i.e., they did not adopt the showy style one might see at a live concert). The stimuli
were created by combining videotaped images (GZ-MG40, Victor) with sounds recorded through
two microphones (SM57, Shure) with a multitrack recorder (SX-1, TEAC). One microphone was
placed in front of each singer, and the recorded sounds were presented as stimuli (Fig.
1a). In presenting the stimuli to the participants, the voices were panned left and right:
the right speaker presented the recording of the singer on the right, and the left speaker
presented the singer on the left. The images were videotaped by a single camera placed in
front of the singers. To examine whether a bias of visual attention exists toward one side
of the singer, on another day, we conducted a supplemental experiment in which other
participants rated the stimuli used in the main experiment in the visual-only mode
(Appendix A). The result showed no differences between the two singers in terms of
attracting visual attention from the participants in 9 of 12 stimuli presented in the
visual-only mode. The singers’ gaze conditions were manipulated as follows: four gaze
conditions (unreciprocated gaze from each singer, absence of eye contact, and existence of
eye contact) × two musical conditions (melody in the first half of the performance or vice
versa). The results for the eye-contact condition were eliminated since that condition was
not established for the purposes of the present study, although they were included in the
appreciation experiment. Under the unreciprocated gaze condition, at the moment the parts
were switched, the singer looked once toward the co-performer for approximately 2 s. The
reasons for using such a brief gaze were that (1) a long duration would have required the
performer to sing with her head turned toward her co-performer, which discords with
ecological validity, and (2) an observer’s attention shifts with shifts in the face of the
person being looked at, even if the duration is less than 1 s (Langton, Watt, & Bruce,
2000). We regarded the singer’s face direction as similar to gaze direction because (1) in
terms of ecological validity, singers are likely to directly face co-performers, (2) it
could be difficult for participants to perceive gaze shifts through singers’ gazes alone
since the video stimuli focused not on the singers’ faces but on most of their bodies
(Fig. 1b), (3) head direction plays a crucial role in the directional attention of others
(Langton et al., 2000), and (4) head or nose direction has also been observed to affect
joint attention, which is the topic of the present study (Langton, Honeyman, & Tessler,
2004). Accordingly, we checked the videotape frame by frame and determined the duration of
the gaze toward the co-performer from its onset until the performer returned to a front-
facing orientation. To examine whether participants clearly discerned the melody and
accompaniment parts, after the experiment, four audio-only stimuli were presented. Twenty-
eight participants were asked how the melody and accompaniment parts switched between the
right and left speakers. Twenty-six participants correctly responded in all four trials,
recognizing the soprano part as the melody. One participant correctly responded to 3 of
the 4 stimuli, and another responded that he did not understand the meaning of “melody
part.” Two of the 30 participants did not participate in this listening test because the
duration of the setting of the experiment became so long that it would exceed the duration
of the experiment. Overall, the stimuli used in the experiment were perceived as
sufficiently separated. Because participants recognized soprano as the melody part,
hereinafter, the soprano part represents the melody part. Although Fig. 3 portrayed the
appearance of the singers through line drawing, the participants saw recorded actual
singing of a real female duo in front of a blackout curtain.

<hs>  Procedure</hs>
  ~~~~~~~~~

The experiment was conducted in a quiet room. Each participant was rewarded with a book
token for 500 Japanese yen. After providing informed consent, the experiments began.
Participants sat approximately 65 cm away from a 15.6-in. monitor (Fig. 2). As a dummy
task, after watching the stimuli, they rated their preference on an 11-point scale, from
very undesirable (0) to very preferable (10). The stimuli were presented randomly to each
participant using a display and two loudspeakers (SB-CH150, Panasonic), and each
participant’s gaze points were recorded using a noninvasive eye tracker (GP3 Eye Tracker,
Gazepoint). Each participant’s gaze-point coordinates on the monitor were analyzed. After
two practice trials, we conducted the experiment. The singing was presented through two
speakers on either side of the monitor. The right speaker presented sounds recorded by the
microphone pointed at the right-side singer, while the left speaker presented those
recorded by the microphone pointed at the left-side singer. Accordingly, participants
predominantly heard the right-side singer from the right and the left-side singer from the
left. After this experiment, another experiment was conducted. The whole experiment took
about 40 min, including a short break.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

We used the eye tracker to measure participants’ gaze points. As shown in Fig. 3,
participants’ gazes concentrated on the faces, on the bodies, or around the bodies of the
singers. When participants looked at 40% of either side of the display (i.e., left or
right side of the display), we regarded them as watching near around the singer on that
side. There were three reasons for this criterion. First, since the present study aimed to
examine approximately which singer participants looked at, namely, the direction of gaze
was important, a detailed analysis of precise gaze points on areas such as singers’ eyes,
heads, or bodies in the stimuli was not required. Second, accuracy of gaze point was
likely to slightly differed among participants. Third, given that the background was
blackout curtain, there was nothing to attract visual attention. Taking account of these
reasons, this measurement was adopted. We eliminated data for 20% of the gaze points
around the center of the display because those points represented participants shifting
between left and right. We also eliminated data for gazing beyond the monitor. The
sampling rate for the gaze data was 60 Hz.

<h>RESULTS</h>
-------

Fig. 4 shows the results for the directions of participants’ gazes when watching stimuli
in which both singers sang facing forward throughout the piece. When the right-side singer
sang the melody in the first half of the piece, two-way ANOVA on the duration of gaze
(switch of musical part × first or second half) revealed interaction, a trend that
approached significance (F(1, 19) = 3.730, p = 0.068, ηp2 = 0.164). The main effect was
not significant. When the left-side singer sang the melody in the first half, two-way
ANOVA on the duration of gaze (switch of musical part × first or second half) did not show
interaction. The main effect was significant (F(1, 19) = 6.026, p = 0.024, ηp2 = 0.241).
Participants gazed significantly longer at the right-side singer than the left-side one,
regardless of assignment of musical part (melody or accompaniment). Fig. 5 showed the
directions of participants’ gazes at the point of the largest pitch interval and the
highest pitch of the score. Fig. 5a and b show participants’ gaze durations at two points,
during which the pitch interval between the melody and the accompaniment was the largest
(hereinafter, PI1 and PI2). The t-test results showed that participants significantly
looked at the left-side singer longer at PI1 when that singer sang the melody in the last
half (t(19) = 2.346, p = 0.030, Cohen’s d = 0.525, n.s. at PI2), and participants
significantly looked at the right-side singer at PI2 when that singer sang the melody in
the latter part of the piece (t(19) = 4.117, p = 0.001, Cohen’s d = 0.921) and at PI1, a
trend that approached significance (t(19) = 1.998, p = 0.060, Cohen’s d = 0.447). Fig. 5c
and 4d shows participants’ average gaze duration when the highest tone (F5, i.e. 698 Hz)
was sung (hereinafter, HP1 and HP2). The t-test results showed that gaze duration toward
the left side at HP2 was longer than that of the right side when the left-side singer sang
the melody (t(19) = 2.283, p = 0.034, Cohen’s d = 0.511; t(19) = 0.768, n.s. at HP1), and
gaze duration toward the right-side singer at HP2 was longer than that of the left side
when the right-side singer sang the melody (a trend that approached significance: t(19) =
1.825, p = 0.084, Cohen’s d = 0.408; t(19) = 1.704, n.s. at HP1). To examine the influence
of singers’ gaze shifts on participants’ gazes, we conducted three-way ANOVA (switch of
musical part × gaze direction × first or second half) by subtracting the duration
participants gazed toward the left from the duration they gazed toward right. Fig. 6 shows
the participants’ gazes under each stimulus condition. Three-way interaction was not
significant. Simple interaction (switch of musical part × first or second half) was
significant (F(1, 19) = 13.474, p = 0.002, ηp2 = 0.415). In the case where the left-side
singer looked toward the right, two-way ANOVA (switch of musical part × first or second
half) showed that interaction was significant (F(1, 19) = 9.907, p = 0.005, ηp2 = 0.343).
The main effect of the first/s half was significant (F(1, 19) = 5.639, p = 0.028, ηp2 =
0.229). The main effect of the switch of musical part was marginally significant (F(1, 19)
= 3.837, p = 0.065, ηp2 = 0.168). In the case where the right-side singer looked toward
the left, two-way ANOVA (switch of musical part × first or second half) showed that
interaction was significant (F(1, 19) = 9.525, p = 0.006, ηp2 = 0.334). The main effect of
the switch of musical part was marginally significant (F(1, 19) = 3.325, p = 0.084, ηp2 =
0.149). Thus, in terms of the whole duration of gazes throughout the piece, participants’
gazes toward the singer assigned the melody part increased when the shift in the melody
part occurred. Fig. 7 shows the average duration of participants’ gazes when each singer
shifted her gaze toward her co-performer. For example, as the white circle in Fig. 7
represents, while watching the stimulus in which the left side singer looked at the right
singer, and then the melody part switched from the left singer to the right singer,
participants looked at the left singer. Subsequently, 3–5 s after this gaze shift,
participants’ gaze did not concentrate on either side of the singer, and 6 s after this
gaze shift, participants looked at the right singer for a longer period. To investigate
participants’ visual attention while the singers looked at each respective co-performer,
we conducted a two-way ANOVA on the duration of gaze (switch of musical part × gaze
direction) by subtracting the duration participants gazed toward the left from the
duration they gazed toward the right. The result showed that interaction was not
significant, while the main effect of the gaze-shift factor was significant (F(1, 19) =
18.544, p < 0.01, ηp2 = 0.494). Thus, participants looked longer at the singer who shifted
gaze direction toward her co-performer than the singer who did not, regardless of the
assignment of the melody part. To analyze participants’ time-lapse gazing behavior, we
conducted a three-way ANOVA (time (from “during gazing” to 2 s) × gaze direction × switch
of musical part) by subtracting the duration participants gazed toward the left side from
the duration they gazed toward the right. Three-way interaction was not significant.
Simple interaction (time × gaze direction) was significant (F(2, 38) = 12.153, p < 0.001,
ηp2 = 0.390). In the case where the right-side singer sang the melody in the first half,
the two-way ANOVA (time × gaze direction) showed that the interaction effect was
significant (F(2, 38) = 9.138, p = 0.001, ηp2 = 0.325). The main effect was not
significant. In the case where the left-side singer sang the melody in the first half,
two-way ANOVA (time × gaze direction) showed that the interaction effect was significant
(F(2, 38) = 7.311, p = 0.002, ηp2 = 0.278). The main effect was also significant (F(1, 19)
= 5.372, p = 0.032, ηp2 = 0.220). Thus, the singers’ gaze shifts influenced the time-
series alternation of the participants’ gazes. The overall tendency in participant gaze
shifts was as follows: First, participants looked at the singer who shifted gaze.
Subsequently, participants shifted their gaze toward the singer who was looked at by her
co-performer. Finally, participants looked at the singer assigned the melody part.

<h>DISCUSSION</h>
----------

The present study investigated the gazing of audience members when watching an audiovisual
presentation of a duo-singing performance by focusing on the dominance of the musical part
in auditory attention and visual joint attention. The main results were as follows: (1)
regardless of whether it was the left or right singer, the one assigned the melody part
(soprano part) attracted more visual attention throughout the piece, with the exception of
two stimuli, (2) joint attention emerged when each singer shifted her gaze toward her co-
performer, suggesting that inter-performer gazing interaction, when playing a spotlight
role, mediated performer-audience visual interaction, and (3) the musical part strongly
influenced the total duration of participants’ gazes, while the spotlight effect of gaze
was limited to just after the singers directed their gazes toward the co-performer. First,
the present study obtained quantitative evidence that musical parts—namely, melody
(soprano) or accompaniment (alto)—significantly affect where audiences direct their gaze
during an ensemble performance. Overall, the singer assigned the melody part attracted
longer durations of gazing. Even when the singer’s gaze shifted toward her co-performer,
participants were still totally inclined to look at the singer assigned the melody. While
prior studies have yielded findings regarding auditory factors in multipart music (Bigand
et al., 2000; Ragert et al., 2014; Uhlig et al., 2013), the results of the present study
provide a new perspective suggesting that the visual attention of audience members depends
on musical parts. At the same time, the present result aligns with Gregory’s (1990)
finding that melody parts attract attention from listeners. Why did audiences allocate
more visual attention to the singer attracting auditory attention? As our hypothesis, the
effect of high-pitched voices could account for this visual attention to melody (soprano)
parts. When the singer assigned the melody sang the highest pitch in the piece, which was
also the highest pitch in relation to the pitch of the accompaniment (alto) part,
participants looked toward the performer singing the higher part. Similarly, at the points
in which pitch interval between melody and accompaniment part was largest, the singer
assigned the melody attracted the gaze of the audiences. These results correspond to other
findings showing that music listeners pay more auditory attention to higher pitches
(Fujioka et al., 2005; Gregory, 1990; Marie & Trainor, 2014; Trainor et al., 2014). If
such high voice superiority was derived from characteristics of auditory system (Trainor
et al., 2014), it can be inferred that the processing of auditory information influenced
the visual attention toward the soprano part in the present results. Still, careful
consideration is necessary to argue the dominance of the melody part in visual attention,
because the melody part that is generally assigned as a higher pitch part is not always
higher than the accompaniment part in all ensemble performances. Owing to the fact that
participants in the present study recognized the soprano part as the melody part through
the listening experiment, the dominance of the melody part in visual attention in the
present results was proved. However, given that the aim of the present study was not
designed to examine whether the effect of high-pitched voices is coincides with the
dominance of melody part, it remains unclear whether an accompaniment part involving
higher pitch would also attract visual attention. If an implication that the melody part
in western music dominates the accompanying harmony in auditory aspects (Uhlig et al.,
2013) can be applicable to visual aspects, a melody part incorporating a lower pitch could
attract more visual attention than the accompaniment part did. Thus, further research
would be useful in examining whether the melody part always attracts visual attention from
audiences, especially in cases where the pitch is lower than that of the accompaniment.
Second, joint attention emerged when the singers shifted gaze directions. Thus, gaze shift
between the singers played a role as a temporary spotlight. Participants first looked at
the singer who looked toward her co-performer and then (approximately 2 s after the gaze
shift) looked at the singer who was being looked at by her co-performer. After that,
(approximately 6–7 s after the gaze shift), participants looked at the singer assigned the
melody part. This phenomenon can be explained as follows: Participants first gazed at the
singer who looked at her co-performer because the singer, who had been facing frontward,
suddenly took a new action. The participants’ second gaze shift toward the singer being
looked at by her co-performer can be explained in terms of joint attention, in which
gazing attracts the visual attention of observers (Baron-Cohen, 1995; Frischen et al.,
2007; Langton et al., 2000). The present results thus provided evidence of joint attention
during musical performance, while previous findings focused on daily communication (e.g.
Carrasco, 2011), child development (e.g. Tomasello, 1995), or human-robot communication
(e.g. Staudte & Crocker, 2011). The present result also confirms Kawase’s (2009a)
implication that a performer’s gaze attracts visual attention from audience members, like
a spotlight. Over all, the present results provided an implication for the cognitive
function of paying attention to performers during an actual musical performance. For both
performers and audiences, gaze can be a useful interaction cue. Performers can employ gaze
as an effective spotlight that leads an audience to direct attention toward certain
performer(s) or objects. Audiences also can use the spotlight of a performers’ gaze as a
cue for what they should direct attention to or for notification of performance process,
e.g. the boundary of solo part, especially when upcoming events are unpredictable in
performances such as improvisation. Yet, it is necessary to consider the situational
differences between our results and ensemble concerts in the real world. In the present
study, the duration of joint attention was short (approximately 2 s), which could have
been caused by the singer’s immediate gaze shift from her co-performer back to the front.
In Kawase’s (2009a) field study, the singer directed her gaze toward the guitarist playing
a solo for a longer duration (approximately 20 s), suggesting that a longer gaze duration
between performers affects audience fixation on the performer being gazed at by co-
performers. Thus, further research is needed to explore the relationships between the
duration of inter-performer gazing and the duration of audiences’ joint attention. Third,
in terms of audiovisual interaction, the present results point to the strong influence of
auditory information on the total duration of participant gazing, regardless of shifts in
the singer’s gaze direction. The present result is supported by the supplementary
experiment in Appendix A, which found no differences between the two singers in terms of
attracting visual attention from the participants in 9 of 12 stimuli presented in the
visual-only mode. In summary, the process of audio-visual interactions that influenced an
audience’s gaze in the present study is as follows: Musical parts (melody or
accompaniment) predominantly affected the gaze of audiences throughout the performances.
The singer assigned the melody part attracted longer durations of gazing. Meanwhile, gaze
shift between performers induced the joint attention of audiences. However, this spotlight
effect of gaze was limited to just after the singers directed their gaze toward the co-
performer, subsequently, the effect of musical parts returned. A combination of two
different pitch parts, the existence of two singers, and gazing between the singers in the
present study provided additional aspect of crossmodal attention, because we may hardly
ever see these factors simultaneously occur in daily communication, e.g. conversation. The
present results that auditory attention toward the dominant musical part corresponded to
visual attention toward the singer who was assigned as that part support previous findings
that auditory attention affect visual attention (Driver & Spence, 1998), or that circuit
that is related to auditory attention is linked with the circuit related to vision in the
brain (e.g., Winkowski & Knudsen, 2006). Given that music appreciation often occurs in
daily life, the present results provided evidence of more natural attentional behavior in
crossmodal situations, in accordance with ecological validity. In terms of audience
attention during audiovisually presented music, the present results yielded another
perspective by focusing on an ensemble music performance that potentially causes attention
allocation in both auditory and visual aspects, while previous studies have mostly focused
on performer-audience visual interactions in solo performances. During a singing duo
performance containing not only two musical parts and two performers, but also inter-
performer interactions through multiple cues (e.g. Keller, 2014), for example gaze,
(Davidson, 2005; Kawase, 2009a; Kawase, 2014a; Kawase 2014b; Moran, 2010) which often
occur, it makes audiences’ attention more complicated. The present result revealed aspects
of this complicated attention of audiences and confirmed an assumable relationship between
inter-performer interactions and performer-audience interactions (Kawase et al., 2007).
Meanwhile, the present result for joint visual attention supports other findings regarding
the powerful impact of visual information on audience members who judge audiovisual music
performances (Platz & Kopiez, 2012). However, since the visual cues were controlled to
focus on gaze effect, the influence of visual information on participants’ visual
attention was limited. The singers in the present study were instructed to restrict
salient visual expressions such as body movement (Broughton & Stevens, 2009), facial
expressions (Thompson et al., 2010), clothing (Griffiths, 2008), and overall physical
appearance (Wapnick et al., 1998). In addition, they were not instructed to manipulate
performance aspects such as manner of expression (Davidson, 1993), emotion (Dahl &
Friberg, 2007), tone duration (Schutz & Lipscomb, 2007), and performance proficiency
(Tsay, 2013). Such control of visual information helps to highlight the influence of
auditory information on the audience’s gaze, while audiences at concerts actively try to
receive visual information (Kawase, 2013). Conversely, the present result accords, to some
degree, with other studies showing the strong influence of auditory information upon
audience members when judging music performance elements in audiovisual presentation
(Kawase, 2009b; Petrini et al., 2010; Silveira & Diaz, 2014; Vines et al., 2006). Further
study would be useful to explore whether, and if so, how, visual information, apart from
gaze such as body movement, facial expressions, or physical appearance, that was employed
in previous studies also attracts audiences’ gaze. Future studies should investigate
whether these results can be applied to larger ensembles, such as orchestras, that might
involve more complicated interactions between performers. The absence of inter-performer
gazing due to instrument manipulation or performance etiquette should be examined as well.
In such cases, visual attention of audience members could differ from the present results.
A field study would also be fruitful for exploring audience gazing in real concerts since
performer-audience interactions in ensemble concerts involve multifaceted nonverbal cues
other than gazing (Kawase et al., 2007; Kurosawa & Davidson, 2005) that might attract
visual attention. Such an attempt could contribute to the elucidation of a holistic
perspective on musical communication.

<h>AUTHOR NOTE</h>
-----------

We would like to thank Dr. Hiroshi Kinoshita, Dr. Kenji Katahira, Kei Eguchi and all the
performers. Furthermore, we are grateful for the valuable comments from the anonymous
reviewers. This research was funded by JSPS KAKENHI Grant Number 26870735 and Yamaha Music
Foundation.


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<ART>Auditory awareness negativity is an electrophysiological correlate of awareness in an auditory threshold task
================================================================================

Authors: Rasmus Eklund, Stefan Wiens
DOI: 10.1016/j.concog.2019.03.008
Year: 2019  |  Pages: 70-78
ASJC codes: 3204, 3205
Keywords: Auditory, Auditory awareness negativity, Awareness, Consciousness, Electroencephalography, Late positivity, Threshold

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

One theory of visual awareness proposes that electrophysiological activity related to awareness occurs in primary visual areas approximately 200 ms after stimulus onset (visual awareness negativity: VAN) and in fronto-parietal areas about 300 ms after stimulus onset (late positivity: LP). Although similar processes might be involved in auditory awareness, only sparse evidence exists for this idea. In the present study, we recorded electrophysiological activity while subjects listened to tones that were presented at their own awareness threshold. The difference in electrophysiological activity elicited by tones that subjects reported being aware of versus unaware of showed an early negativity about 200 ms and a late positivity about 300 ms after stimulus onset. These results closely match those found in vision and provide convincing evidence for an early negativity (auditory awareness negativity: AAN), as well as an LP. These findings suggest that theories of visual awareness are also applicable to auditory awareness.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

How does the brain enable us to experience seeing a picture or hearing a tone? This
question has been studied extensively in vision. A common strategy has been to use
threshold tasks: If a single, weakly visible image is shown repeatedly at the awareness
threshold, subjects typically report that they are aware of the image on half of the
trials, even though the image remains constant. The differences in associated neural
activity between images that subjects report that they are aware of versus images that
they are unaware of represent the neural correlates of visual awareness (Aru, Bachmann,
Singer, & Melloni, 2012; Crick & Koch, 1998).

<hs>  Electrophysiological correlates of visual awareness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To understand visual awareness, the location and timing of its neural mechanisms are
presumed to be critical. Some theories suggest that awareness is mediated by early
recurrent processing in the visual cortex (Lamme, 2010), whereas other theories suggest
that it is mediated by late activation in the fronto-parietal network (Dehaene & Changeux,
2011; Lau & Rosenthal, 2011). Because of their excellent temporal resolution,
electrophysiological measures derived from electroencephalography (EEG) have been
immensely useful in addressing this issue (Eklund & Wiens, 2018; Koivisto & Grassini,
2016; Koivisto, Salminen-Vaparanta, Grassini, & Revonsuo, 2016). In several
electrophysiological studies, a threshold task was used, and awareness was measured with
subjective ratings. Critically, these studies did not use objective measures of
performance (such as those used in a detection task) because these may not capture
awareness equally well, as subjects may detect a stimulus without being aware of it. For
example, subjects with blindsight can perform visual detection tasks well while claiming
not to have any visual awareness (Stoerig, 2006; Weiskrantz, 1996). In these
electrophysiological studies, awareness ratings were used to separate images into those
that subjects reported that they were aware of and those that subjects reported that they
were unaware of. An event-related potential (ERP; the average EEG response across images)
was computed for each awareness rating, and a difference ERP was computed between them.
Results of these studies suggest two ERP correlates of visual awareness: visual awareness
negativity (VAN) and late positivity (LP; Koivisto & Revonsuo, 2010). VAN is a negative
wave at occipital electrodes that occurs about 200 ms after stimulus onset. LP is a
positive wave at parietal electrodes that occurs at least 300 ms after stimulus onset
(Koivisto & Revonsuo, 2010). VAN has been suggested as the earliest electrophysiological
correlate of visual awareness (Koivisto & Grassini, 2016), and this claim has been
corroborated with magnetoencephalography (MEG; Andersen, Pedersen, Sandberg, & Overgaard,
2016). However, it is unclear whether LP is correlated with awareness (Dehaene & Changeux,
2011; Salti, Bar-Haim, & Lamy, 2012), post-perceptual processes (Andersen et al., 2016;
Koivisto et al., 2016), or both. In terms of mechanisms, the current understanding is that
during visual processing, activity from lower visual areas is fed forward to higher areas
and then fed back to form recurrent loops. The early recurrent loops occur in lower areas
(Lamme & Roelfsema, 2000) and are captured by VAN (Koivisto & Revonsuo, 2010). As later
recurrent loops involve higher areas, including the fronto-parietal network, global
recurrent processing ensues. This process may be captured by LP (Koivisto & Grassini,
2016), and it enables subjects to report their awareness (Lamme, 2006).

<hs>  Neural correlates of auditory detection</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

According to recurrent processing theory (Lamme, 2010), the processes that result in
auditory awareness might be similar to those that result in visual awareness. Previous
electrophysiological studies with threshold sounds have mainly used detection tasks with
and without confidence ratings (Hillyard, Squires, Bauer, & Lindsay, 1971; Parasuraman &
Beatty, 1980; Squires, Hillyard, & Lindsay, 1973). These studies provide some evidence for
neural correlates of auditory detection in an early interval (i.e., N1) and a late
interval (i.e., P3). In the first study, subjects (N = 3) were asked to detect threshold
tones in white noise (Hillyard et al., 1971). Correctly detected tones (hits) were
associated with an N1 (an early negativity at vertex, at about 100 ms) for one subject and
a P3 (a late positivity at vertex, at about 300 ms) for all three subjects. In contrast,
undetected tones (misses) were not associated with any N1 or P3. In a follow-up study, the
task was similar, but subjects also rated their confidence regarding each reported
detection (Squires et al., 1973). When subjects correctly detected tones and rated their
confidence in the detection as high, these tones were associated with an N1 and a P3.
Undetected tones were not associated with an N1 or P3. Similar effects were observed when
subjects were asked to detect and identify tones with different frequencies and also
provide a confidence rating (Parasuraman & Beatty, 1980). More recently, the neural
correlates of informational masking were studied with MEG (Gutschalk, Micheyl, & Oxenham,
2008). The task was to detect target tones within series of tones that were masked by
background tones (multitone masking). Compared with undetected tones, detected tones
resulted in a negativity in the MEG between 50 and 250 ms after tone onset. This
negativity was localized in the same area as the N1. These findings have been corroborated
in subsequent studies with MEG (Dykstra & Gutschalk, 2015; Giani, Belardinelli, Ortiz,
Kleiner, & Noppeney, 2015) and electrocorticography (Dykstra, Halgren, Gutschalk,
Eskandar, & Cash, 2016). Similarly, studies that recorded EEG in a change deafness task
found an enhanced N1 and P3 to detected changes versus undetected changes (Gregg & Snyder,
2012; Puschmann et al., 2013). Taken together, previous studies support the idea that
detection is correlated with both early and late activity. However, these studies used
methods that are not optimal for measuring awareness. Although awareness is largely
captured in a detection task, awareness may be misclassified if subjects have only two
ratings to choose from (Hillyard et al., 1971). For example, subjects may categorize tones
as not heard even though they heard the tone faintly. Although tasks with confidence
ratings allow for graduated ratings (Parasuraman & Beatty, 1980; Squires et al., 1973),
they remain an indirect measure of awareness. Thus, they do not reflect subjects’
experiences as well as asking subjects directly about their experience does. Therefore,
awareness should be measured directly with a rating scale that has several alternatives to
allow subjects to rate their level of awareness (Sandberg, Timmermans, Overgaard, &
Cleeremans, 2010).

<hs>  Neural correlates of auditory awareness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The goal of the present study was to establish ERP correlates of auditory awareness. The
study was modelled after previous studies (Hillyard et al., 1971; Parasuraman & Beatty,
1980; Squires et al., 1973) with the addition of using explicit awareness ratings, similar
to previous studies in vision (Eklund & Wiens, 2018; Koivisto & Grassini, 2016; Koivisto &
Revonsuo, 2010). Tones were presented at each subject’s awareness threshold, and subjects
reported their auditory awareness of the tones by using an awareness rating scale with
three levels while EEG was recorded. In vision, this approach has found VAN. We expected a
similar correlate in hearing, the auditory awareness negativity (AAN).

<h>METHOD</h>
------

The method and analyses were preregistered in detail before any data were collected.
Deviations from the preregistration are noted below. All data and scripts are available
elsewhere (Wiens & Eklund, 2019). We collected data from two groups of subjects (group A,
doi: 10.17605/OSF.IO/HN8KJ; group B, doi: 10.17605/OSF.IO/SHVZD). For group A, we
preregistered an interval for the AAN on the basis of the responses to louder tones
(control trials). However, as explained in Section 3.2.1, the data suggested that this
preregistered interval preceded the AAN. Therefore, we preregistered a later interval and
used a new sample (group B) to test for AAN in this interval.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

We preregistered to recruit at least 20 subjects in each group. If the Bayes Factor (BF)
exceeded 3 or was below ⅓ for our hypotheses, recruitment would end. Otherwise, subject
recruitment would continue for another week. This process was repeated until the BF
reached the criterion, a maximum of 60 subjects were tested, or a predetermined end date
was reached. Group A consisted of 24 healthy subjects (age: M = 25.63 years, SD = 4.43),
of whom 11 were male and 22 were right-handed. Group B consisted of 25 healthy subjects
(age: M = 26.52 years, SD = 6.18), of whom 10 were male and 24 were right-handed. Subjects
had normal or corrected-to-normal vision and were recruited from local universities and
through online billboards. They were compensated with either movie vouchers or course
credits. Before starting the experiment, subjects provided written consent in accordance
with the Declaration of Helsinki. The research was conducted in accordance with the
principles of the regional ethics board. Although we preregistered several exclusion
criteria (e.g., noisy EEG data), only three subjects from group B were excluded because
they did not show a negativity in the N1 interval in the ERP extracted from aware control
trials, as defined below. Critically, the decision to exclude these subjects was made
before the ERPs from the critical trials were analyzed. The final samples consisted of 24
subjects in group A (11 male; age: M = 25.63, SD = 4.43) and 22 subjects in group B (8
male; age: M = 26.32, SD = 6.38).

<hs>  Apparatus and stimuli</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Stimuli were 100-ms tones (f = 1000 Hz, 5 ms fade-in and fade-out). Tones were presented
binaurally through in-ear tubephones (ER2; Etymotic Research Inc., IL; www.etymotic.com).
Instructions were displayed on a BenQ XL2430T, 24-inch gaming monitor (at 144 Hz, 1920 ×
1080 resolution). PsychoPy v 1.85.3 (Peirce, 2007) was used to generate tones and to
collect behavioral data. A Cedrus StimTracker (Cedrus Corporation, San Pedro, CA) was used
to generate triggers to the actual tones. These triggers were used to define tone onsets
and served to compensate for any timing errors between the actual presentation of the
tones and their event markers from the presentation computer.

<hs>  Procedure</hs>
  ~~~~~~~~~

Subjects performed a tone-detection task while seated in front of a computer screen with
their chin in a chinrest. Fig. 1 shows the time course of a trial. On each trial, a black
fixation cross (0.5 visual degrees) was shown for 1000 ms. Critical trials contained a
tone at the individual subject’s auditory awareness threshold (see below), and control
trials contained a tone at 10 dB above the calibrated threshold level. On critical and
control trials, a tone was played binaurally 500 ms after trial onset. On catch trials, no
tone was played. The fixation-cross remained visible for the duration of the trial.
Afterwards, subjects rated their subjective awareness of the tone by using one of three
buttons (“1,” “2,” and “3,” corresponding to “I did not hear any stimulus,” “I heard the
stimulus weakly,” and “I heard the stimulus clearly,” respectively). Subjects were
instructed to focus on rating their awareness accurately rather than responding quickly.
The task comprised 800 trials (640 critical, 80 control, and 80 catch). The trials were
divided into eight blocks of 100 trials each (80 critical, 10 control, and 10 catch), with
a short break between each block. For each subject in group A, the order of critical,
control, and catch trials were randomized within each block. For each subject in group B,
the order of trials was randomized within each set of 10 trials (with 8 critical, 1
control, and 1 catch trial per set). Before the experiment began, subjects performed a
short practice task. This task was identical to the main task but with clearly audible
stimuli. After the practice task was completed, an interleaved staircase was used to
calibrate the tone to a level at which the subject reported being aware (weakly or
clearly) on approximately 50% of the trials (i.e., individual auditory awareness
threshold). The staircase procedure consisted of three interleaved staircases with 40
trials each (36 tone present trials and 4 catch trials). One staircase started at the
threshold estimate obtained from pilot subjects (4 dB), another started 20 dB above this
estimate, and another started 20 dB below. The staircase procedure was as follows: If the
subject reported awareness when a tone was presented, the level decreased. If the subject
reported no awareness when a tone was presented, the level increased. For each staircase,
reversal steps were 8, 8, 4, 4, 2, and 2 for the first six reversals, and 1 dB for
subsequent reversals. After the calibration, a validation block was run with 100 trials
(80 critical, 10 control, and 10 catch trials). The level of the critical tone in the
validation block was determined from both the convergence of the three staircases (from
visual inspection) and the mean of the final six reversals for each staircase. If 45–55%
of the critical trials in the validation block were rated as aware, the experiment began.
If a subject reported awareness on less than 45% of the critical trials, another
validation block was run at a higher sound level. Similarly, if a subject reported
awareness on >55% of the critical trials, another validation block was run at a lower
sound level. This validation was repeated until the 45–55% aware criterion was met. If
this criterion was not met within five validation blocks, subjects were tested at the
level that was closest to their awareness threshold. However, all subjects met the
criterion within five validation blocks.

<hs>  EEG recording</hs>
  ~~~~~~~~~~~~~

EEG data were recorded from six electrodes at standard 10/20 positions (Fpz, Fz, Cz, Pz,
P9, and P10) and two additional electrodes (one on the tip of the nose, and one on the
cheek) with an Active Two BioSemi system (BioSemi, Amsterdam, Netherlands). Fpz, Fz, Cz,
Pz, P9, and P10 were recorded with pin electrodes in a 64-electrode EEG cap; the tip of
the nose and the cheek were recorded with flat electrodes attached with adhesive disks.
Because the left and right mastoids (M1 and M2) were not available in the EEG cap, we used
the nearby positions P9 and P10 for convenience. Two additional, system-specific channels
were recorded with pin electrodes in the EEG cap: The common mode sense (CMS; between PO3
and POz) served as the internal reference electrode, and the driven right leg (DRL;
between POz and PO4) was used as the ground electrode. Data were sampled at 1024 Hz and
were filtered with a hardware low-pass filter at 104 Hz.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

The data were processed and analyzed with Matlab (The MathWorks, Inc.) and R (R Core Team,
2016). Physiological data were processed offline with the toolbox FieldTrip (version
20181003) in Matlab (Oostenveld, Fries, Maris, & Schoffelen, 2011). The behavioral
analyses included all trials, whereas in the EEG data analyses, some trials were excluded
(see below). In the EEG data analyses, tone onset was indexed by the Cedrus StimTracker,
which eliminated any timing errors in tone onset. Offline, continuous EEG data were high-
pass filtered with a 0.1 Hz Butterworth fourth degree two-pass filter. Fpz, Fz, Cz, Pz,
and the mastoids were re-referenced to the tip of the nose, and Fpz was re-referenced to
the cheek electrode (for a combined measure of vertical and horizontal
electrooculography). Epochs were extracted from 100 ms before tone onset to 600 ms after
tone onset. Each epoch was baseline corrected to the mean of the 100-ms interval before
tone onset (−100 to 0 ms). For each subject, maximum amplitude ranges were extracted for
individual epochs, and the distribution of these amplitude ranges was inspected.
Individual trials that were apparent outliers (such as eyeblinks) were excluded. The
exclusion thresholds were set for each individual because subjects showed substantial
variability in these amplitude ranges. Critically, inspection of trials was blinded to
trial type (critical, catch, and control) and awareness ratings to avoid bias (Keil et
al., 2014).

<hs>  ERP analysis</hs>
  ~~~~~~~~~~~~

Two event-related potentials (ERPs) were derived from critical trials: Aware trials were
tones rated as “I heard the stimulus clearly” or “I heard the stimulus weakly,” and
unaware trials were tones rated as “I did not hear any stimulus.” Note that for aware
trials, clearly and weakly heard tones were combined because subjects rarely rated their
awareness as clear (<1%, see Section 3.1), similar to studies in vision (Eklund & Wiens,
2018; Koivisto & Grassini, 2016). Difference waves were calculated by subtracting the ERP
to unaware trials from the ERP to aware trials. We predicted that this difference wave
would be negative in the N1 interval (AAN) and positive in the P3 interval (LP). Because
in vision VAN overlaps in latency with the visual N1 interval (Eklund & Wiens, 2018;
Koivisto & Revonsuo, 2010), we initially expected to observe AAN in the auditory N1
interval. Because we expected N1 at centrally located electrodes (Parasuraman & Beatty,
1980), we combined Fz and Cz electrodes (after 30-Hz low-pass filtering). For group A, the
relevant interval for AAN was preregistered as the peak (±50 ms) of the N1 in the grand
mean ERP of the control trials. This definition of the N1 interval was independent from
the critical trials and thus did not bias the main results. However, as discussed in
Section 3.2.1, this interval preceded an apparent negative difference wave between aware
and unaware trials. Therefore, we preregistered this later interval for group B. For both
groups, mean AAN amplitudes were computed for the N1 interval across Fz and Cz electrodes,
and mean LP amplitudes were computed for the P3 interval between 350 and 550 ms for the Pz
electrode. We selected the Pz electrode based on previous findings in vision (Eklund &
Wiens, 2018). We conducted Bayesian hypothesis testing to determine the degree of evidence
for or against the alternative hypothesis (Dienes, 2008). The Bayes Factor (BF10)
expresses the likelihood of the data given the alternative hypothesis relative to the
likelihood of the data given the null hypothesis, whereas the BF01 shows the reverse
(Dienes, 2008, 2016; Wagenmakers, Marsman et al., 2017; Wiens & Nilsson, 2017). Although
the BF is a continuous measure of evidence, we adopted a common interpretation scheme
(Wagenmakers, Love et al., 2017). The BF was calculated with Aladins Bayes Factor in R
(Wiens, 2017). These scripts compute and plot the BF for mean differences in raw units if
the alternative hypothesis is modelled as a normal, t, or uniform distribution, and the
likelihood is modelled as a normal or t distribution (Dienes & McLatchie, 2018). For group
A, the alternative hypotheses for AAN and LP were modelled as uniform distributions with
the limits of −2 µV to +2 µV. For group B, the alternative hypothesis for AAN was modelled
as a t distribution derived from group A. Specifically, we preregistered the following t
distribution: M = −0.58 (SEM = 0.22, df = 22, 2-tailed). We note that the preregistration
states a positive mean value (i.e., 0.58), but the reason is that the R scripts (Wiens,
2017) require the theoretical effect to be positive. Further, we note that when we checked
our analyses after the preregistration, we realized that one subject was missing from this
previous analysis. With this subject included, the correct t distribution should have been
as follows: M = −0.67 (SEM = 0.25, df = 23, 2-tailed). Although we report the results for
the preregistered analysis, results were similar with this corrected alternative
hypothesis. These and other additional analyses are available elsewhere (Wiens & Eklund,
2019). Although we meant to use the specific t distribution (i.e., M = −0.58) only for the
alternative hypothesis with regard to AAN, the wording of the preregistration suggests
that we intended to use it also for the LP. However, this would be incorrect, because LP
amplitudes are positive and much larger than AAN amplitudes. For simplicity, the Bayesian
analyses reported below use the same alternative hypothesis for LP as in group A (i.e., −2
µV to +2 µV). Note that results are comparable if the alternative hypothesis for LP is
modelled as a t distribution derived from the LP results from group A (Wiens & Eklund,
2019).

<hs>  Behavior</hs>
  ~~~~~~~~

Table 1 shows the descriptive statistics for the behavioral data. Subjects performed the
task as intended: At the individual awareness threshold, close to fifty percent of the
critical tones were rated as aware (of these, 99.7% were rated as weakly heard in both
groups). Most control tones were rated as aware, and most catch trials were rated as
unaware. The average level of the critical tone was 4.7 dB (SD = 4.1) for group A and 6.7
dB (SD = 7.9) for group B.

        <hss>Auditory awareness negativity</hss>

        Table 2 shows the descriptive and inferential statistics for the mean amplitudes.
        Fig. 2 shows the mean ERPs across subjects in group A. In the left panel, a clear
        negativity (N1) to control trials (black line) can be seen with its peak at 150 ms
        after stimulus onset. Our initial, preregistered hypothesis for AAN was that a
        negative difference wave of aware minus unaware critical trials would occur in the
        same interval as the N1 to control trials, as in vision (Eklund & Wiens, 2018;
        Koivisto & Revonsuo, 2010). However, for this interval (94–194 ms), the Bayesian
        one-sample t test provided anecdotal evidence against a negativity (BF10 = 0.37,
        which corresponds to BF01 = 2.70). Nonetheless, the left panel in Fig. 2 suggests
        that there is an apparent negative difference wave (green line), but its peak
        occurred later, about 190 ms after stimulus onset. On the basis of these findings,
        we preregistered this interval (140–240 ms) and tested it on a new sample. Fig. 3
        shows the mean ERPs across subjects in group B. In the left panel, a clear
        negativity for the difference wave (green line) is visible with its peak around
        200 ms after stimulus onset. This peak closely matched that of group A, as
        confirmed by the Bayesian one-sample t test that supported a negativity in the
        revised interval (BF10 = 5.90). These findings provide moderate evidence for AAN.

        <hss>Late positivity</hss>

        Table 2 shows the descriptive and inferential statistics for the mean amplitudes.
        The right panels in Figs. 2 and 3 show the mean ERPs for the two groups. A
        positive difference wave of aware minus unaware critical trials (green line) was
        apparent for both groups after 300 ms. For the preregistered interval (from 350 to
        550 ms), evidence for LP was very strong to extreme (group A: BF10 > 45,000, and
        group B: BF10 = 81.10).

<h>DISCUSSION</h>
----------

When tones were presented at the individual awareness threshold, subjects reported being
aware of about 50% of these tones. From the electrophysiological recordings, a difference
wave was computed for these aware minus unaware tones. This wave showed a central
negativity in the early interval (140–240 ms after tone onset) and a central positivity in
the late interval (350–550 ms after tone onset). Bayesian hypothesis testing provided
moderate evidence for the early negativity (AAN) and very strong evidence for the late
positivity (LP).

<hs>  Auditory awareness negativity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our initial, preregistered hypothesis for AAN was that a negative difference wave of aware
minus unaware tones would occur in the same interval as the N1 to control tones, as in
vision (Eklund & Wiens, 2018; Koivisto & Revonsuo, 2010). For this interval, the Bayesian
analysis provided anecdotal evidence against a negativity, opposite to our predictions.
However, visual inspection of the data suggested an apparent negative difference wave at a
later latency (see green line in Fig. 2A). In hindsight, this finding of a delayed
negativity may not be surprising: Because the latency of the N1 peak is delayed for
quieter tones (Picton, Woods, Braun, & Healey, 1977) and the tones at the awareness
threshold were quieter than the control tones, it is reasonable that the N1 was delayed to
tones at the awareness threshold. Because this N1 delay made theoretical sense, we used
the obtained interval for the N1 to preregister a new interval (140–240 ms). In the new
sample, the Bayesian analysis provided moderate evidence for a negativity and thus AAN.
Specifically, the BF = 5.90 implies that the presence of AAN is almost six times more
likely than the absence of AAN. Because few electrodes were used in the present study, no
source localization is possible with the present data. However, previous studies that
recorded MEG during a multitone-masking task suggest that the main sources may be in
auditory cortex (Gutschalk et al., 2008).

<hs>  Late positivity</hs>
  ~~~~~~~~~~~~~~~

For both data collections, our preregistered hypothesis for LP was that a positive
difference wave for aware minus unaware trials would occur between 350 and 550 ms after
stimulus onset. Indeed, Bayesian analyses provided very strong to extreme evidence for LP.
In vision research, the P3 was larger to aware than to unaware trials; thus, there have
been consistent reports of an LP as a positive difference wave (Dehaene & Changeux, 2011;
Koivisto & Revonsuo, 2010). In hearing research, similar results were obtained when
subjects provided binary detection responses or rated their confidence (Dykstra, Cariani,
& Gutschalk, 2017; Hillyard et al., 1971; Parasuraman & Beatty, 1980; Squires et al.,
1973). In the present study, subjects were required to rate their awareness explicitly.
Therefore, our findings of an LP extend previous findings and demonstrate that the late
neural correlates of hearing are similar to those in vision.

<hs>  Implications for theories of awareness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the philosophical debate about what awareness or consciousness is, two concepts are
central: phenomenal consciousness, which refers to “what it is like” to have an
experience, and access consciousness, which refers to the state of introspection or
reporting about an experience (Block, 1995). It remains unclear if and how the early
process (VAN in vision, AAN in hearing) and the later process (LP in both modalities) map
onto these concepts. According to recurrent processing theory (Lamme, 2006), local
recurrent processing is necessary and sufficient for phenomenal consciousness. Therefore,
if VAN and AAN are indirect measures of local recurrent processing, they index phenomenal
consciousness (Lamme, 2018). Furthermore, global recurrent processing enables reporting
and introspecting on an experience (Koch, Tononi, Massimini, & Boly, 2016; Lamme, 2006)
and thus indexes access consciousness. This is a post-perceptual process according to
recurrent processing theory (Koivisto & Grassini, 2016; Lamme, 2010). Therefore, if LP is
an indirect measure of global recurrent processing, it indexes access consciousness
(Koivisto & Grassini, 2016). According to global workspace theory, local recurrent
processing is a preconscious process (Dehaene, Changeux, Naccache, Sackur, & Sergent,
2006; Naccache, 2018). Thus, VAN and AAN may at best index only preconscious processing.
In contrast, if LP is an indirect measure of global recurrent processing, it indexes
access consciousness, which subsumes phenomenal consciousness according to global
workspace theory (Cohen & Dennett, 2011; Naccache, 2018). Although non-response tasks may
be a promising approach to separating neural correlates of awareness from those of post-
perceptual processes (Tsuchiya, Wilke, Frässle, & Lamme, 2015), the present findings do
not resolve this discussion. Nonetheless, they provide convincing evidence that the ERP
correlates of auditory awareness (AAN) are analogous to those in visual awareness (VAN).

<h>CONCLUSION</h>
----------

In terms of neural correlates of auditory awareness, very little empirical research has
been done previously (for reviews, see Dykstra et al., 2017; Snyder, Yerkes, & Pitts,
2015). The present results expand on previous studies that used a detection task (Hillyard
et al., 1971) or detection and confidence ratings (Parasuraman & Beatty, 1980; Squires et
al., 1973) to investigate the neural correlates of detection in hearing. To capture
awareness in hearing, our study used awareness ratings, because they have been shown to
capture subjective experiences accurately in vision (Sandberg et al., 2010). The present
findings show that AAN is an early neural correlate of awareness in hearing, similar to
VAN in vision.


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<ART>Autobiographical memory and well-being in aging: The central role of semantic self-images
================================================================================

Authors: Clare J. Rathbone, Emily A. Holmes, Susannah E. Murphy, Judi A. Ellis
DOI: 10.1016/j.concog.2015.02.017
Year: 2015  |  Pages: 422-431
ASJC codes: 3204, 3205
Keywords: Episodic, Identity, Older adults, Self, Semantic

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Higher levels of well-being are associated with longer life expectancies and better physical health. Previous studies suggest that processes involving the self and autobiographical memory are related to well-being, yet these relationships are poorly understood. The present study tested 32 older and 32 younger adults using scales measuring well-being and the affective valence of two types of autobiographical memory: episodic autobiographical memories and semantic self-images. Results showed that valence of semantic self-images, but not episodic autobiographical memories, was highly correlated with well-being, particularly in older adults. In contrast, well-being in older adults was unrelated to performance across a range of standardised memory tasks. These results highlight the role of semantic self-images in well-being, and have implications for the development of therapeutic interventions for well-being in aging.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The way we remember our past is thought to influence both our sense of self and our
general well-being. However, the mechanisms underpinning the links between memory, self
and well-being are little understood. This study aimed to investigate the relationships
between well-being and two types of autobiographical memory: semantic self-images (e.g.,
autobiographical knowledge about the self, comprising traits, family roles and group-
membership) and episodic autobiographical memories (detailed memories of specific,
personally-experienced events). Furthermore, in light of established age-related changes
in memory function (e.g., Levine, Svoboda, Hay, & Winocur, 2002; Piolino, Desgranges,
Benali, & Eustache, 2002), we tested younger and older adult groups in order to examine
whether these relationships differ between age groups. A better understanding of the role
that different types of memory play in well-being has important implications. People with
higher levels of well-being benefit from more than simply positive mood and good social
relationships (Diener, 2013), they also have increased life expectancies and better
physical health (Diener & Chan, 2011; Kok et al., 2013). Crucially, this study took the
novel approach of comparing the roles of semantic and episodic autobiographical memory,
addressing the recent call for more detailed investigation of the function of semantic
components of autobiographical memory (e.g., Haslam, Jetten, Haslam, Pugliese, & Tonks,
2011; Prebble, Addis, & Tippett, 2013; Thomsen, 2009). Traditionally, the main focus of
autobiographical memory research has been on episodic, rather than semantic, memories (see
Thomsen, 2009). Episodic autobiographical memories relate to a specific moment in time and
typically include sensory-perceptual details (e.g., visual imagery and sensory
information) and are characterised by a sense of ‘mental time travel’ (Tulving, 1983,
2002). In contrast, semantic autobiographical memories involve simply knowing about an
event or fact, without a sense of mentally travelling back and re-living a specific event
(Tulving, 1983, 2002). These semantic autobiographical memories include knowing the
locations of countries visited on holiday and names of family members. They also include
the sets of traits, roles and beliefs that form semantic self-images, such as knowing one
is a retired accountant and a mother of two children. Semantic self-images are thus a
particularly self-relevant subsection of semantic autobiographical memory. Research
suggests that as we get older, sensory-specific episodic memories become less accessible,
whilst semantic autobiographical memories are retained (e.g., Levine et al., 2002; Piolino
et al., 2002). Specific episodic autobiographical memories arguably play a range of
important roles, including promoting social intimacy (Pillemer, 1998), acting as landmark
events marking transitions in the life story (Shum, 1998; Thomsen, Pillemer, & Ivcevic,
2011), and engaging people with their long-term goals (Singer & Salovey, 1993). However,
recent work (e.g., Haslam et al., 2011; Thomsen, 2009) has emphasised the important role
of semantic autobiographical memory. Key to the present study, Piolino et al. (2006)
proposed that the retention of semantic autobiographical memories may play a central role
in enabling older adults to maintain a sense of diachronic unity. Haslam et al. (2011)
suggest semantic self-knowledge is a bi-directional mediator between episodic
autobiographical memory and identity. They proposed that episodic autobiographical
memories provide the basis for semantic autobiographical memories, and it is these
semantic “facts” that support the self. Prebble et al. (2013) developed this idea further,
proposing that semantic autobiographical memories may help form a scaffold for both
episodic recollection and imagination of future events (e.g., Irish, Addis, Hodges, &
Piguet, 2012). Prebble et al. suggest that self-continuity in older adults is maintained
by semantic autobiographical memory. Semantic autobiographical memories may provide a more
efficient means of promoting narrative continuity, possibly by virtue of the fact that
they can be used to synthesise and organise large amounts of information into a coherent
life story (Prebble et al., 2013). In support of this organisational account, Thomsen
(2009; Thomsen et al., 2011) proposed that people use semanticised life story chapters
(e.g., time at university X) to organise autobiographical retrieval and shape a narrative
life story. Semantic facts structure the way we remember the past and also the way
children imagine the future (Bohn & Berntsen, 2011). In short, a growing number of
researchers have emphasised the role that semantic autobiographical memory plays in
organising memory and promoting a coherent sense of self. Semantic autobiographical memory
is the most resilient form of autobiographical memory, preferentially preserved in healthy
aging (Levine et al., 2002; Piolino et al., 2002) retrograde amnesia (Klein & Lax, 2010;
Rathbone, Moulin, & Conway, 2009), depression (Dalgleish et al., 2007), autism (Crane &
Goddard, 2008) and Alzhiemer’s disease (Martinelli, Anssens, Sperduti, & Piolino, 2013).
In addition to highlighting the dissociation between episodic and semantic memory, these
studies also raise the possibility that semantic self-images might be a useful starting
point for rehabilitation in a range of clinical groups. The present study was particularly
focused on the emotional valence of semantic self-images and episodic autobiographical
memories. This is because there are established age-related changes in the emotional
ratings of autobiographical memory (e.g. the positivity effect; Kennedy, Mather, &
Carstensen, 2004), but little is known about how these might relate to well-being. Well-
being can be conceptualised at both the eudaimonic and hedonic level. Eudaimonic well-
being is associated with viewing one’s life with meaning, purpose and a sense of growth
(Bauer, McAdams, & Pals, 2008) and using and developing the best aspects of oneself (Huta
& Ryan, 2010). Eudaimonic well-being is often conceptualised as “psychological well-being”
(e.g. Ryff & Keyes, 1995), although other conceptualisations exist (for a review, see
Huta, 2013). Hedonic well-being focuses on both the experience of pleasure and a more
cognitive evaluation of life satisfaction (Diener, 2013). Recent empirical work suggests
that hedonic and eudaimonic well-being may overlap, with greatest overall well-being
perhaps stemming from the pursuit of both hedonic and eudaimonic aims (Huta & Ryan, 2010).
We suggest that semantic self-images play a crucial role in supporting the self. The
present study aimed to explore the role of semantic self-images in well-being in aging,
and centred on three main research questions, which will be explored in detail below: (1)
How does the emotional valence of episodic autobiographical memories and semantic self-
images differ between younger and older adults; (2) is well-being correlated more strongly
with the valence of semantic self-images or episodic autobiographical memories and does
this differ between younger and older adults; (3) in older adults, is the valence of
semantic self-images more strongly correlated with well-being than objective measures of
memory performance. The first research question focused on the phenomenological ratings of
episodic autobiographical memories and semantic self-images in the two age groups. Older
adults tend to rate their episodic autobiographical memories more positively than younger
adults (the “positivity effect”; Kennedy et al., 2004; Schlagman, Schulz, & Kvavilashvili,
2006; Schryer, Ross, St-Jaques, Levine, & Fernandes, 2012). Compared to younger adults,
older adults tend to reappraise negative memories in a more positive light (Comblain,
D’Argembeau, & Van der Linden, 2005) and report a larger proportion of positive than
negative autobiographical memories (e.g., Mather & Carstensen, 2005). The first
prediction, in line with the positivity effect (e.g., Kennedy et al., 2004), was that
older adults would rate both their semantic self-images and episodic autobiographical
memories more positively than younger adults. The second research question centred on the
relationships between well-being and the emotional valence of episodic autobiographical
memories, and semantic self-images. In particular, it aimed to elucidate the role that
semantic self-images play in well-being. Swann and Buhrmester (2012) suggest that stable
self-representations are vital for social interactions, making goals, and enabling a sense
of belonging. The present study sought to ascertain whether the valence of semantic self-
images was more closely related to well-being than the valence of episodic
autobiographical memories. Well-being may be associated with the way that autobiographical
memories are framed (Philippe, Koestner, Beaulieu-Pelletier, Lecours, & Lekes, 2012). For
example the presence of ‘growth’ memories (e.g., goal-related memories that lead to a
richer understanding of oneself and one’s life) has been associated with increased ratings
of well-being (Bauer et al., 2008; Bauer, McAdams, & Sakaeda, 2005; Philippe et al.,
2012). Whilst there is a general consensus that judgements of mood and well-being are
affected by the emotions associated with autobiographical memories (e.g., Hart, 2013), it
is unclear which level of autobiographical memory (e.g., semantic or episodic) is
involved. This question has particular relevance to aging, as research suggests that older
adults may use semantic self-images to buffer against the negative effects of aging
(Heidrich & Ryff, 1993). Older adults with negative self-perceptions of aging tend to show
a decline in physical (Sargent-Cox, Anstey, & Luszcz, 2012) and psychological well-being
(Mock & Eibach, 2011). Indeed, the self-system has been conceptualised as a “coping
resource in the aging process” (Diehl, Hastings, & Stanton, 2001, p. 644). The present
study thus sought to elucidate the relationship between the emotional valence of semantic
self-images and well-being. Based on recent work suggesting that semantic autobiographical
memories support identity and organise autobiographical retrieval (Prebble et al., 2013;
Thomsen, 2009), the second prediction was that in both younger and older adults, the
emotional valence of semantic self-images would correlate more closely with measures of
well-being than the emotional valence of episodic autobiographical memories. The third
research question focused only on the older adult group. We aimed to establish whether
memory performance on a range of standardised cognitive tasks was related to well-being.
Previous work has suggested that cognitive decline in aging is associated with decreased
well-being (Llewellyn, Lang, Langa, & Huppert, 2008; Wilson et al., 2013). However, well-
being in older adults tends to be rated relatively highly, in spite of declines in
physical and cognitive health (Scheibe & Carstensen, 2010). Research testing older adults
with dementia indicated that identity (measured as strength of personal identity) mediated
the effects of memory loss on well-being, suggesting that it is not memory loss per se
that leads to lower well-being (Jetten, Haslam, Pugliese, Tonks, & Haslam, 2010). The
design of the present study enabled a clear comparison between the roles of both episodic
autobiographical memories and semantic self-images, and the role of standardised memory
performance, in well-being. This question has implications for our aging population. In
essence, do the changes in memory associated with aging necessarily relate to how positive
people feel about themselves and their lives? It was predicted that well-being would
correlate more closely with how positively participants viewed themselves (e.g. emotional
valence of semantic self-images) than how well they performed in standardised memory
tasks.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants consisted of 32 younger adults (26 female; mean age = 20.25; SD = 2.99; range
= 18–28) and 32 older adults (19 female; mean age = 70.22; SD = 3.02; range = 65–75,). The
younger adults were psychology students at a UK university who received credits for
participating. The older adults were recruited from a database of local adults interested
in participating in research projects. All participants were community-dwelling and
provided details of mental and physical health and any previous history of substance
abuse. Five of the older and five younger adults reported a history of anxiety and/or
depression. Cognitive function was measured using the Trail Making Tests A and B
(completion time in seconds; Reitan, 1958), vocabulary sub-test of WAIS-R (Wechsler,
1981), and category (animal) and letter (F) fluency (Tombaugh, Kozak, & Rees, 1999). For
details of participant characteristics see Table 1.1 In line with previous research,
compared to younger adults, the older adults performed better on the vocabulary task
(Verhaeghen, 2003) but worse on the trail making tasks (Kennedy, 1981) and category
fluency task (Tomer & Levin, 1993).

<hs>  Materials and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

All participants completed the IAM task (Rathbone, Moulin, & Conway, 2008), three measures
of cognitive function (described above), and five measures of well-being in one lab-based
session that lasted between 1.5 and 2 hours. The older adult group also attended a second
1-hour session in which they completed an additional set of memory and cognitive function
tests. This second session took place within two weeks of session 1.

        <hss>IAM task</hss>

        Participants generated up to 10 ‘I am’ statements and then selected their two most
        important statements as cues for up to five episodic autobiographical memories per
        statement (generating up to 10 memories in total).2 All episodic autobiographical
        memories were dated for age at event, and rated on an 11-point scale for vividness
        (0 = not at all vivid, 10 = very vivid), emotional valence (−5 = very negative, +5
        = very positive), personal significance (0 = not at all personally significant, 10
        = very personally significant), rehearsal (0 = never think about it, 10 = think
        about it all the time) and on a dichotomous scale for imagery perspective
        (observer or field). Memories were rated in two ways for episodic specificity.
        First, participants were provided with standardised Remember/Know/Guess
        instructions (Gardiner, 1988) and asked to rate whether each memory was something
        they remembered (R), knew (K) or guessed (G). All responses rated as R were probed
        for episodic details, and were rated as Justified Remember (JR) if such details
        were provided (following Piolino et al., 2003). Memories were also rated for
        specificity by the researcher using a 0 to 4 scale (Baddeley & Wilson, 1986), in
        which 4 = a specific event with details and situated in time and space, 3 = a
        specific event without any detail but situated in time and space, 2 = a repeated
        or extended event situated in time and space, 1 = a repeated or extended event not
        situated in time and space, and 0 = no memory given/only general information about
        the topic. All ‘I am’ statements (e.g. semantic self-images) were rated by the
        participant for emotional valence (−5 = very negative, +5 = very positive), age of
        identity formation, and importance (0 = not at all important, 10 = very
        important). Thus, the emotional valence scores for both semantic self-images and
        episodic autobiographical memories were based on comparable participant-reported
        rating scales.

        <hss>Well-being scales</hss>

        A range of scales were employed to assess eudaimonic, hedonic, and clinically-
        relevant measures of well-being. Eudaimonic well-being was measured using the
        42-item Psychological Well-being Scale (PWB; Ryff & Keyes, 1995; total scale
        score). Hedonic well-being was measured with scales that tapped into emotional
        experience (e.g., The Positive and Negative Affect Schedule, PANAS trait version
        [participants rated to what extent they “generally feel this way…on average”]
        Watson, Clark, & Tellegen, 1988), evaluation of how positive or negative one’s
        life has been (Satisfaction with Life Scale, SWLS; Diener, Emmons, Larsen, &
        Griffin, 1985), and optimism (Life Orientation Test-Revised Optimism Scale; LOT-R;
        Scheier, Carver, & Bridges, 1994). Finally, the Hospital Anxiety and Depression
        Scale (HADS; Zigmond & Snaith, 1983) provided a more clinically-relevant measure
        of well-being.

        <hss>Additional measures for older adult group</hss>

        The Autobiographical Memory Interview (AMI; Kopelman, Wilson, & Baddeley, 1989)
        assessed episodic and semantic autobiographical memory, the Rey-Osterrieth Complex
        Figure Test (Osterrieth, 1944; Rey, 1941) assessed visuospatial memory, the
        Logical Memory Test (LMT; subtest of Wechsler Memory Scale, Wechsler, 1997)
        assessed recall and recognition for narrative memory, the Graded Naming Test (GNT;
        McKenna & Warrington, 1983) measured semantic memory for object names, and the
        Everyday Memory Questionnaire (EMQ; Sunderland, Harris, & Gleave, 1984) was a
        self-report measure of participants’ day-to-day memory problems. General cognitive
        function was assessed using the Montreal Cognitive Assessment (MOCA; Nasreddine et
        al., 2005).

        <hss>Statistical procedures</hss>

        Comparisons of episodic autobiographical memory and semantic self-image ratings
        between younger and older adults were based on ANOVAs with ‘age group’ as a
        between subjects factor. In order to examine the relationships between well-being
        scales, and episodic autobiographical memory and semantic self-images ratings
        within each age group, Pearson product-moment correlation coefficients were
        calculated.

<h>RESULTS</h>
-------

The first aim of this study was to examine whether the phenomenological ratings for
semantic self-images and episodic autobiographical memories differed between younger and
older adults. Mean ratings and ANOVA results for older and younger adults are shown in
Table 2. For completeness, we also include comparison of well-being scores between groups.
Results suggest that age has no effect on the emotional valence, importance, or frequency
of semantic self-images generated. In contrast, older adults’ episodic autobiographical
memories were significantly more positive, and rehearsed less frequently, than those of
younger adults. As one would expect, older adults’ episodic memories were dated at a
higher mean age at event, and were rated as containing less episodic detail than younger
adults’ memories. There was also an age effect for proportion of memories viewed from a
field perspective; older adults were more likely to remember events from a field
perspective than younger adults, but both age groups used a field perspective for the vast
majority of their memories. There were no significant differences in well-being measures
between age groups. To examine whether gender had any effects on these data, it was
included as covariate in the ANOVAs shown in Table 2. Gender had no significant effects on
any of the key variables in this study (well-being scales and valence of episodic
autobiographical memories and semantic self-images). The second aim was to explore the
relationships between the emotional valence of semantic self-images and episodic
autobiographical memories and participants’ well-being scores. Semantic self-image valence
scores were calculated using participants’ mean emotional valence ratings for all self-
images generated in the IAM Task. Episodic autobiographical memory valence scores were
calculated using participants’ mean emotional valence ratings for all episodic memories
generated in the IAM Task. To better understand how these relationships might differ
between age groups, correlational analyses were run within groups for younger and older
adults (see Table 3). As one would expect, both age groups showed multiple significant
correlations between well-being measures, but of particular interest were the correlations
between well-being and semantic self-image valence, as well as well-being and episodic
autobiographical memory valence. All correlations were in the expected direction, with
higher (i.e. more positive) emotional valence ratings for semantic self-images associated
with increased well-being (e.g., higher scores on the PWB Scale, PANAS positive, SWLS, and
LOT-R, and lower scores on the PANAS negative and HADS). There were no significant
correlations between episodic autobiographical memory valence and well-being in the older
adult group, whilst episodic autobiographical memory valence correlated with only the
PANAS positive measure in the younger adult group. In contrast, the valence of younger
adults’ semantic self-images correlated with three well-being measures and in the older
adult group significant correlations were shown between semantic self-image valence and
all measures of well-being. This critical finding suggests that, in both younger and older
adults, semantic self-image valence is more closely correlated with well-being than
episodic autobiographical memory valence. To examine this further, the correlation co-
efficients in Table 3 were entered into Hotelling William method t tests. This tested
whether there was a significant difference between the correlations for well-being and
valence of episodic autobiographical memories compared to between well-being and valence
of semantic self-images. Results (shown in summary in Table 4) indicated that, within the
older adult group, five out of the six measures of well-being were more significantly
correlated with valence of semantic self-images than valence of episodic autobiographical
memories. In contrast, within the younger adult group there were no significant
differences between correlations for well-being and episodic autobiographical memory
valence compared to semantic self-image valence. The final aim was to examine whether
increased well-being scores were associated with better cognitive performance in the older
adult group. For this purpose, correlational analyses were run on scores obtained on a
battery of cognitive tasks, including objective memory measures (e.g., AMI, LMT, GNT) and
the subjective self-report EMQ, alongside well-being scores (see Table 5). The EMQ was
significantly negatively correlated with the PWB Scale and PANAS positive, and
significantly positively correlated with the PANAS negative and HADS. High scores on the
EMQ indicate self-reported experience of a high number of everyday memory problems, thus
these correlations are in the expected direction. None of the objective measures of memory
were correlated with any of the measures of well-being, suggesting that (at least within
this non-clinical group) there was no relationship between memory performance and well-
being.

<h>DISCUSSION</h>
----------

The findings of this study suggest that well-being is more closely linked to how
positively people view themselves at a semantic level, rather than at an event-specific
level – an effect that was particularly pronounced in older adults. The first aim of this
study was to examine how the emotional valence of semantic self-images and associated
episodic memories might differ between younger and older adults. There were few
differences between age groups on the measures of episodic memory, and no differences
between age groups in semantic self-image or well-being scores. As predicted, older adults
rated their episodic autobiographical memories more positively than younger adults. In
contrast, counter to predictions, semantic self-images were rated equally positively by
adults in both age groups. This suggests that the positivity effect in ageing established
for episodic autobiographical memories (e.g. Kennedy et al., 2004) may not extend to
semantic self-images, replicating recent work by Chessell, Rathbone, Souchay,
Charlesworth, and Moulin (2014). The second aim was to examine the correlations between
well-being and the emotional valence of both semantic self-images and episodic
autobiographical memories. As predicted, the emotional valence of semantic self-images was
significantly related to participants’ well-being. This effect was shown in both younger
and older adults, but was particularly pronounced in the older adult group, for whom
semantic self-image valence correlated with all six measures of well-being. In contrast,
the emotional valence ratings for episodic autobiographical memories were not correlated
with any measures of well-being in older adults, and were only correlated with one measure
of well-being in the younger adult group. When correlations between well-being and
episodic autobiographical memory valence were compared to those between well-being and
semantic self-image valence, we found – counter to our predictions – pronounced aging
effects. In younger adults, there was no difference between the correlations for well-
being and episodic autobiographical memory valence compared to well-being and semantic
self-image valence. However, in older adults, well-being was significantly more related to
semantic self-image valence than episodic autobiographical memory valence in five of the
six measures of well-being. This may reflect enhanced emotional-regulation processes
associated with aging (Carstensen, 2006) – a point we discuss later in this section. This
key finding suggests that, in older adults, well-being is more closely linked to the
emotional valence of semantic self-images, rather than episodic autobiographical memory.
The final aim was to examine the relationship between well-being and memory performance in
older adults. In line with predictions, objective memory performance across a range of
standardised tasks bore little relation to measures of well-being. In contrast, self-
reported memory problems showed multiple correlations with well-being. These results
suggest that poor memory performance per se does not necessarily equate with diminished
well-being. The current findings add to a growing body of research highlighting the
important role of semantic autobiographical memory (e.g., Bohn & Berntsen, 2011; Klein &
Lax, 2010; Prebble et al., 2013; Thomsen, 2009). Previous theorists have emphasised the
role that this form of autobiographical memory might play in structuring retrieval of past
and construction of future events (Bohn & Berntsen, 2011; Irish et al., 2012; Prebble et
al., 2013), structuring a life story (Thomsen, 2009) and maintaining identity in the face
of episodic deficits (Klein & Lax, 2010; Rathbone et al., 2009). Here we suggest that this
factual knowledge about the self might play an additional role, through its close
relationship to our judgements of well-being. Further experimental research is needed to
unpick the causal mechanisms between semantic self-image valence and well-being. However,
the results of this study suggest that there are very close ties between perceptions of
well-being and the semantic facts that comprise self-knowledge. This finding relates to
current theories on the central role that imagery plays in emotion (e.g., Holmes &
Mathews, 2010). Indeed, recent studies suggest that positive imagery acts to scaffold
positive affect (Blackwell et al., 2013; Torkan et al., 2014). Within the autobiographical
memory literature, imagery is more typically a hallmark of episodic, rather than semantic,
autobiographical memory (e.g., Tulving, 1983, 2002). However, there is a wide literature
on the clinical relevance of many different forms of imagery (Holmes & Mathews, 2010),
including the construction of negative semantic images of the self (e.g. Conway, Meares, &
Standart, 2004; Hirsch, Clark, Mathews, & Williams, 2003; Ng & Abbott, 2014). More
research is needed to understand the nature of mental imagery associated with semantic
self-images. Semantic self-images, by definition, reflect a particularly self-relevant
form of imagery. Although they represent an amalgam of semantic information (e.g. being
confident, sociable, keen on attending football matches), rather than discrete episodic
events, the emotional valence of these semantic self-images appears to be closely linked
to well-being. Future work based on cognitive bias modification paradigms may shed more
light on the potential therapeutic benefits of modifying semantic self-images, in light of
the success of using this approach with mental images that are episodic in nature (e.g.,
Torkan et al., 2014). The present findings support the results of previous research.
Firstly, across both age groups, participants’ emotional ratings for both episodic
autobiographical memories and semantic self-images were predominantly positive,
replicating previous work (e.g., Chessell et al., 2014; Thomsen, 2009) and supporting the
theory that most people tend to view themselves and their memories in a positive light
(Walker, Skowronski, & Thompson, 2003). Socioemotional selectivity theory (SST;
Carstensen, 2006) may explain why, for older adults in particular, more positive views of
the self were associated with increased well-being. According to SST, the age-related
decrease in subjective sense of future time (e.g. how much time one has left to live)
leads to increased emotional regulation. Furthermore, the fact that well-being showed
strong associations with the emotional valence of semantic self-images is of particular
relevance to older adults, as well as various clinical groups who demonstrate episodic
deficits (e.g., Dalgleish et al., 2007; Klein & Lax, 2010; Martinelli et al., 2013). The
older adults in this sample represented a healthy community-based sample, none of whom
demonstrated severe memory deficits. It is thus possible that more advanced memory loss
would have a greater impact on well-being (e.g., Llewellyn et al., 2008; Wilson et al.,
2013). The question of how memory, well-being, and identity are inter-related in dementia
is complex, and recent papers on the topic have highlighted the importance of studying
identity using a range of approaches (e.g., Caddell & Clare, 2013). The results of the
present study also extend previous findings. Although we found few relationships between
ratings of episodic autobiographical memories and well-being, other researchers describe
significant relationships between well-being and episodic memory. For example, Philippe et
al. (2012) found that young adults who retrieved memories that were rated more highly for
need satisfaction tended to demonstrate increased levels of well-being. However, Philippe
et al. analysed a specific component of episodic memory, related to achieving growth-
related goals, whereas in the current study (in order to allow comparison of self-images
and episodic memories) we used an emotional valence scale to analyse the relationship
between memory and well-being. It is thus possible that other measures of the content and
affective properties of episodic memories, such as redemption and contamination themes
(McAdams, Reynolds, Lewis, Patten, & Bowman, 2001) or intrinsic versus integrated themes
(Bauer et al., 2005), would yield significant relationships with well-being. Crucially,
few studies that measure the relationship between episodic memory and mood or well-being
(e.g., Gillihan, Kessler, & Farah, 2007; Philippe et al., 2012) also include measures of
semantic autobiographical memory, such as self-images. Thus it is possible that when
memories have been shown to have an impact on well-being, they may have done so via their
relationship with semantic facts about the self. This mediating role of semantic
autobiographical memory has been proposed in models of memory and identity (e.g., Haslam
et al., 2011). It is possible, therefore, that semantic self-images play a similar
mediating role in promoting well-being, and this again would be an interesting avenue for
future research. The present research was subject to several limitations and suggests
multiple avenues for future work. First, the study employed a correlational design and as
such it cannot speak to the causal direction between the constructs of semantic self-image
valence and well-being. Whilst it is possible that viewing the self in a positive light
promotes well-being, it is equally possible that higher levels of well-being lead people
to take a more positive view of themselves. Future studies employing experimental designs
will be needed to unpick the direction of effects, however it seems likely that a bi-
directional relationship exists between semantic self-image and well-being (as would be
predicted by models such as the self-memory system; Conway, 2005). Indeed, the self-system
is widely regarded to be dynamic and likely to change depending on mood and context (e.g.,
Markus & Kunda, 1986; Showers, Abramson, & Hogan, 1998). What the present research clearly
indicates is that the emotional appraisal of semantic self-images is closely related to a
range of well-being measures. Regardless of bi-directional effects, if focusing on
positive self-images could be shown to raise levels of well-being this would have
important therapeutic implications. A second point relates the lack of counter-balancing
between the set of well-being measures and the memory tasks. To avoid priming particular
aspects of identity, the semantic self-image generation task was completed first. Thus,
future studies will be required to rule out potential order effects.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

In their recent review, Prebble et al. (2013) suggested that research needs to explore the
semanticised summaries of life narratives, as well as specific event memories, in order to
develop a more complete picture of the roles of episodic and semantic autobiographical
memory. The present paper addressed this aim and found that the valence of semantic self-
images may be more fundamental to conceptions of well-being than that of episodic
autobiographical memories. In essence, we found clear relationships between how positively
people perceive themselves and their overall well-being. This relationship was
particularly pronounced in older adults, for whom a wide range of well-being measures
correlated with ratings of semantic self-image valence. In addition, older adults’
performance on standardised measures of cognition and memory bore no relation to ratings
of well-being. These findings have implications for promoting well-being in aging. It
seems that well-being does not depend on what you remember, or even how good your memory
is – what is key is how you conceptualise your sense of self in the present moment.


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<ART>Bayesian inferences about the self (and others): A review
=========================================================

Authors: Michael Moutoussis, Pasco Fearon, Wael El-Deredy, Raymond J. Dolan, Karl J. Friston
DOI: 10.1016/j.concog.2014.01.009
Year: 2014  |  Pages: 67-76
ASJC codes: 3204, 3205
Keywords: Active inference, Free energy minimisation, Other-representation, Paranoia, Personality disorder, Self-representation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Viewing the brain as an organ of approximate Bayesian inference can help us understand how it represents the self. We suggest that inferred representations of the self have a normative function: to predict and optimise the likely outcomes of social interactions. Technically, we cast this predict-and-optimise as maximising the chance of favourable outcomes through active inference. Here the utility of outcomes can be conceptualised as prior beliefs about final states. Actions based on interpersonal representations can therefore be understood as minimising surprise - under the prior belief that one will end up in states with high utility. Interpersonal representations thus serve to render interactions more predictable, while the affective valence of interpersonal inference renders self-perception evaluative. Distortions of self-representation contribute to major psychiatric disorders such as depression, personality disorder and paranoia. The approach we review may therefore operationalise the study of interpersonal representations in pathological states. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION: AGENCY AND THE INTERPERSONAL SELF</h>
-----------------------------------------------

The sense of self may be experienced at many levels – from the elementary, pre-verbal
‘minimal self’ that accompanies all conscious perception, to the purposeful, historically
constructed ‘narrative’ self who takes action under the conscious guidance of goal and
context. Research based on the idea of the brain as a probabilistic inference device has
seen great advances in recent years (Chater & Oaksford, 2008; Friston & Stephan, 2007),
allowing important aspects of the minimal and narrative self during perception and action
to be considered in the light of how probabilistic prediction interacts with sensory
evidence. The computations that brains perform to predict and hypothesis-test underlie
what it is like to be an I who expects the consequences of acting and perceiving – now and
through time (Hohwy, 2007). In this article, we extend this work to self-perception in the
interpersonal domain, while acknowledging that the sense of self is important, even in the
absence of interactions with others. Simple observation suggests that the interpersonal
self is as complicated in its detailed mechanics as it is blatant about its presence.
While the minimal self at the core of near-instantaneous perception is difficult to put
into words, there is, in the first instance, nothing difficult about putting the
interpersonal self into words: ‘am a kind person’, ‘am not as good as her’. The English
language describes this powerful self-perception with expressions such as ‘he is a
terribly self-conscious’. We claim that the interpersonal self is actively inferred during
social exchanges and that many of its properties correspond to the means and ends of a
machinery of probabilistic inference. Inferring self-representations may thus help achieve
desirable ends (social outcomes). The evidence that we marshal to develop this argument
comes from a wide variety of sources, including computational neuroscience, brain imaging,
psychiatry, social and clinical psychology. We develop our claim as follows. First, we
provide evidence that some high-level, affectively coloured (pain) perception is well
described in terms of basic Bayesian reasoning. Second, we describe an extended framework
of approximate Bayesian reasoning, namely active inference, which encompasses agency and
decision-making. Third, we review the kinds of psychological construct upon which active
inference may operate – and show that inferring about these constructs subserves important
goals. Fourth, we suggest a model of interpersonal exchange that could form the basis for
empirical study. Finally, we examine the psychiatric relevance of making affectively
charged inferences, especially about the self. We conclude by discussing the limitations
of our approach and the implications for future research.

<hs>  Using Bayesian inference to make sense of experience</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Bayesian approach considers probabilities to be degrees of belief, so that Bayesian
inference has the following form. If I make an observation o, what should become of my
belief P (S = s) that some relevant aspect of the world is in state s? For example,1 if o
= ‘Emil gave me a present’, what should become of my belief ‘I am a bad person’? If the
new observation is surprising – with respect to the existing belief framework – the
framework is poor at predicting the observation. It therefore needs to be updated if it is
to describe the world more adequately. This updating of beliefs is the essence of Bayesian
inference, which adjusts the agent’s model of the world so as to render new observations
(data) less unpredictable. Although a full description of this well-established formal
approach is outside the scope of the present article, the interested reader is referred to
(Chater & Oaksford, 2008; Friston & Stephan, 2007; Friston et al., 2013; King-Casas et
al., 2008). The claim we make in this paper is that this inferential framework applies to
all beliefs – including beliefs about the self. In a Bayesian framework what the brain
minimises as it makes inferences, including inferences about the self, is unpredictability
and not, for example, proximal discomfort. We will consider an example of this below, in
the case of perception of pain. We reformulate the principle of psychological economy as
follows: the primary gain of a representation is its power to predict outcomes that matter
under some prior beliefs. Maximising predictability is equivalent to minimising surprise.
Clearly, surprising outcomes rest upon prior beliefs. In our case, these beliefs will be
about the self (and others). Crucially, surprise can be quantified as the negative log
(Bayesian) evidence for a model. This means that minimising surprise maximises the
evidence for a model or representation of interpersonal exchange. We now turn to a simple
but informative application of the Bayesian framework, the understanding of placebo
responding. Placebo responding crucially depends on an interaction between prior beliefs
about analgesia and sensory evidence (Morton, El-Deredy, Watson, & Jones, 2010). This case
study will help structure further discussion in two ways: on the one hand, its limitations
will motivate the need for goal-directed, active inference; but on the other, placebo-
responding provides important lessons for inference about self-representations.

<hs>  The Bayesian model of pain perception</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Bayesian model of pain perception2 (El-Deredy, Trujillo- Barreto, Watson, & Jones,
2010; Watson, El-Deredy, Bentley, Vogt, & Jones, 2006) provides proof-of-principle that
humans perform high-level Bayesian inference to form affectively charged percepts. These
researchers modelled pain perception in two groups of healthy people, ‘placebo responders’
and ‘placebo non-responders’. Pain ratings were collected through three phases. In both
groups: Painful (‘active’) stimuli were initially administered in the absence of any
treatment, establishing an expectation of stimulus – pain perception. Placebo analgesia
was then administered while stimulation was covertly switched to sham stimuli. These were
visually identical but non-painful, giving the impression that the ‘treatment worked’.
Stimulation was finally covertly switched back to active stimuli. The above Bayesian
updating model of pain rating allows one to address the following question: given beliefs
subjects already entertained (priors) about how painful percepts are generated, how are
current percepts integrated into new beliefs (posteriors)? Crucially, ‘new beliefs’
include the precision or the weight that should be attached to past reports. The role of
precision is crucial, because agents come to rely more on cues that have the greatest
precision. Notice that the previous response enters as a new observation in this Bayesian
updating scheme – in other words, the model is observing and trying to explain its own
responses. The authors found that the full model explained the pain-perception data of
placebo non-responders, but a reduced model – which neglects sensory information (ot) and
makes predictions based only on past reports – best accounted for the data from placebo-
responders.3 In other words, one’s inference about the causes of nociceptive input can be
based purely upon previous reports or, equivalently, behaviour that belies one’s own
inferences. Bayesian updating thus provides a good account of behaviours involving high-
level beliefs about analgesic properties. This example also provides proof-of-principle
that apparently irrational, affectively charged human beliefs can be described
quantitatively in terms of the balance of prior beliefs relative to sensory evidence.
Interpersonal interactions also involve apparently irrational, affectively charged beliefs
and the related negative affect is neurally and subjectively related to pain (Eisenberger,
2012). Neither physical pain nor social ‘pain’ stand in a one-to-one relation with damage:
people have widely varying sensitivities to the same physical manipulation (Eisenberger,
Jarcho, Lieberman, & Naliboff, 2006). The experience of physical pain is not unrelated to
self-awareness (‘Pinch me, am I dreaming?’) but interpersonal ‘pain’ is quite directly
related to self- and other- representation. When I am deceived, for example, beliefs like
‘I am a fool’ and ‘he is devious’ immediately gain weight. Much as inferences about pain
relate to the risk posed by stimuli (and, more subtly, my own physical vulnerability), so
during interpersonal inference the self and others are vividly experienced as vulnerable
(or not), noxious (or safe), etc. We will consider examples of inferring aspects of the
self to be noxious, when we consider psychiatric conditions later on. This brings us to a
key limitation of this Bayesian model of pain perception, which is its silence as to the
functional role of inference about pain (or, in our case, about the self). In fact the
optimal readiness with which pain is to be inferred depends on context: organisms can tune
their own pain perception according to both their prior beliefs and the specific
biological goals they believe are attainable in that context (Boureau, 2005). This would
be an irrational anomaly if pain were a raw datum, but not if pain was a motivational
force: if there is little of biological use that can be done, it is better to reduce pain
sensitivity. We therefore need a Bayesian framework that explicitly represents the
person’s agency and goals, namely active inference (Friston et al., 2013). In order to
study self-awareness as inference, we need to quantify the relevant aspects of self-
representation. We will consider this in more detail below; for now, suffice it to say
then we can cast traits like ‘fairness’ or ‘jealousy’ as social preferences: how much
another’s pain or gain can act as a motivating force (Camerer, 2003). We propose that such
sensitivities (preferences) may stand to social outcomes as pain sensitivity stands to
somatic ones. That is, their usefulness may lie in helping the agent reach their goals.

<hs>  Using active inference to reach desirable goals</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

During perceptual inference, we infer those descriptions of the world that are most
consistent both with our sensory data and with our prior beliefs about what the world
should be like. During active inference, however, we can entertain beliefs about
alternative scenarios that lie ahead – scenarios that depend on our own fictive choices in
the future. Policies are then chosen in a Bayes optimal fashion that depends upon these
prior beliefs. Our ‘prior beliefs’ are not just about what we believe the world to be
like, but which alternative outcomes we realistically expect (hope) that we can reach: our
goals. From now on we will refer to prior beliefs about goals simply as ‘goals’.
Conversely, once a subject has experienced part of the scenario, but has not as yet
reached the final outcome, they can be said to hold empirical priors about their policy
(i.e. the choices that are shaped by their goals). These empirical priors pertain to (a)
goal attainability from the current state and (b) beliefs about future choices (Friston &
Stephan, 2007; Friston et al., 2013). Empirical priors are a necessary aspect of inference
in hierarchical models. Technically speaking, they are prior beliefs that are conditioned
on (i.e. depend on) other unknown variables. In our case, beliefs about the policy depend
upon beliefs about hidden states of the world, where beliefs about future states depend
upon the goal. Whether I have to get off the bus may not just depend on whether I see a
park from the bus window, it also depends on which bus I took! In this sense, beliefs
about the policy entail beliefs about hidden states in a hierarchical sense and are
therefore empirical priors. They are essentially prior beliefs about prior beliefs. To
make the distinction between goals and empirical priors over policies clearer, consider
going to the pub for a drink. My favourite drink is actually fairtrade hot chocolate; I
also like Guinness, but less so. If they were in front of me I would choose fairtrade
chocolate ¾ of the time, Guinness ¼ of the time, so these are my goals: [0.75, 0.25]. This
illustrates how – in our framework – all utilities are necessarily relative: the utility
of a particular outcome is always defined in relation to allowable alternatives. The
computational purpose of defining goal priors can be seen as separating out the various
task-dependent probabilities used in active inference from probabilities that do not
depend on where we are in the task or on the agent’s behaviour during the task. In other
words, we separate state-dependent beliefs about what we will do next from the goals that
define beliefs about the final outcome. In contrast to goals, empirical priors entail
beliefs about the dynamics of the task or, more simply, the consequences of a particular
action in terms of the transition from one state to another: where will I end up if I take
this sequence of actions? And how does the disparity between that outcome and my goals
influence my choice of a subsequent policy? If I take a bus towards Barnet (action), am I
likely to get to a nice pub (state) and look for hot chocolate there (policy)? In short,
empirical priors entail the agent’s knowledge about the dynamics of her/himself in the
world. They are ‘priors’ in the sense that the actual policy that we will choose (shall I
look for hot chocolate?) will depend on observations about where we are and where we can
go. Crucially, in the active inference framework, these choices will also depend on the
confidence we have in reaching our goals from the current state. This is because action
depends upon beliefs over policies and beliefs always have a precision. Our inference
framework is thus able to decide about actions motivated by goals that embody the raw
power of gain and loss, contentment and pain. The key device to achieve this, introduced
in this review, is to convert the utilitarian formulation of classical economic theory, in
which choices are assumed to maximise expected utility, into a pure (Bayesian) inference
problem. One can do this by representing the utility of outcomes as prior beliefs about
final states. This means that instead of making choices to maximise expected utility, one
simply minimises surprise – under the prior belief that one will end up in desirable
states. Practically, replacing utilities with prior beliefs means that one can appeal to
well-established inference schemes such as (variational) free-energy minimisation in order
to prescribe normative behaviour. Casting utility functions as prior beliefs means that
one can understand utility – which depends on interpersonal factors – in terms of beliefs
about oneself and others. As an example, assigning high utility to gains acquired by a
partner who resembles me translates into holding a higher prior belief that the partner
will be of a similar type to me and that they will gain from the exchange. So far we have
only used common-sense examples; in order to apply the formalism of active inference to
self- and other- representation, we must determine – at least roughly – the categories of
belief about self and others that people actually use.

<hs>  The nature of beliefs about the self (and others)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

During self- and other-perception, empirical evidence suggests that people form beliefs
about both the states and traits, of both self and others (Bem, 1972; Bentall, 2003;
Fowler et al., 2006). Traits are characteristic patterns of emotion, behaviour or thinking
that subjects engage across many situations. People naturally infer such traits in each
other, in order to anticipate intentional mental states. Psychological research suggests
that people independently score ‘positive attributes’ and ‘negative attributes’ of both
‘self’ and ‘other’. A modern clinical research instrument, used to assess such
representations, is shown in Table 1. The items relate to (i) (social) outcomes; e.g.
‘respected’, ‘a failure’; (ii) Capabilities; e.g. ‘weak’, ‘talented’ and (iii) Preferences
for acting according to social values; e.g. ‘good’, ‘fair’, ‘trustworthy’. Note that the
instrument is asymmetric: ‘other’ attributes relate more to social-value preferences, such
as fairness, harshness, etc.; whereas ‘self’ attributes relate more to social outcomes and
abilities. This division is likely to be an artefact of the clinical focus of this scale;
namely, depression and paranoia. If people are asked to describe ‘what kind of person’
they desire to be and ‘what kind of person they try to avoid being’, they give a mixture
of success-, motivation- and ability-related traits for themselves too (Francis, Boldero,
& Sambell, 2006). We will call a ‘type’ the traits of a person that are relevant to the
current context (e.g. an interpersonal task). Building on the work on inferring an other’s
type (Ray, King-Casas, Montague, & Dayan, 2008), we hypothesize that people harvest
observations to update their beliefs about their own type for good reason: Self (and
other) representations are tools facilitating the efficient computation of interpersonal
behaviour. An important psychological theory that makes contact with these issues is the
‘sociometer theory of self-esteem’ (Leary, Tambor, Terdal, & Downs, 1995). According to
the sociometer account, self-esteem has an important functional role, which is to indicate
one’s likely evaluation by the social milieu. The crucial corollary is that actions that
improve self-esteem are rewarding because – if all goes well – they subserve socially
sanctioned goals. We generalise the ‘sociometer theory of self-esteem’ is to a ‘sociometer
theory of self-representation’. Type-based interpersonal representations, of which (trait)
self-esteem is only a subset, serve to optimise context-dependent social computations.4
Aspects of self-representation important for prediction may be: (i) how successful I have
been in a given context so far; (ii) an appraisal of my capabilities; and (iii) what my
(interpersonal) preferences are. Constructs such as ‘a bad person’ or ‘fair’, can inform
optimal decision-making in a formal and fundamental fashion, despite the emotive and
informal nature of these concepts. Our contention that (interpersonal) preferences should
be the object of inference parallels Hohwy’s hypothesis that desires are inferred in the
process of applying generative models of ourselves (Hohwy, 2007). The coherence of these
models would be important for the construction of the ‘narrative self’. In an
interpersonal context, traits such as ‘talented’, ‘harsh’ etc. can feed directly into the
outcomes that a person wants to reach (or indeed to avoid). In terms of active inference,
agents can inform goals by the desirable self-representations that they are likely to
reach as outcomes. An example is: “If the outcome of this exchange is that I cooperate and
my partner runs off with the money, this would be evidence that I am a fool. This is
highly undesirable – I’ll attach very low probabilities to outcomes implying that I’m a
fool”. We hypothesise that different people are equipped with different prior beliefs,
acquired during their upbringing and built on a base of genetic preparedness. This allows
modelling of individual variation, including variation in psychopathology. It provides a
simple and graceful way to account for different types (phenotypes) in a quantitative and
formal sense. Clearly, people may have a vast lexicon of potential traits to consider. We
expect the ensuing paradigm could the used to inform those traits that are inferred,
especially in clinical applications.

<hs>  Self-representation and desirable goals of social interaction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Type-based representations provide a simple and formal belief space that people may use in
categorising themselves and others – a belief space that can be tested empirically. These
representations can be linked to the returns (e.g. utilities or prior beliefs) that people
expect themselves and others to derive from social actions. An agent’s task is then to
infer, or estimate, ‘types’ linked to utilities. If, for example, I infer that my partner
is a ‘fair person’, this summarises an expectation: that they will avoid actions leading
to inequitable returns for all involved – finding such actions aversive. If I estimate
myself to be ‘highly competitive’, I expect to derive high utility from actions that lead
to me doing better than others, even if my material returns are somewhat lower than under
some other outcome (e.g., where I come second). But why bother using person-
representations as heuristics? Why not just calculate out how everyone should behave based
on their self-interest? The tractability of optimal Bayesian inference is a key issue
here; real agents must perform the requisite computations, which can be very hard. Type-
based interpersonal representations can be likened to heuristics that facilitate
approximate Bayesian inference. Here type-based representations can be a shortcut to
tracing out a complex tree of possible future states and outcomes. In the ‘stag hunt’
game, for example, agents with limited depth-of-thought but equipped with ‘prosocial’
preferences make decisions equivalent to having greater depth-of-thought but no social
biases (Yoshida, Dolan, & Friston, 2008). In such cases, explicit optimal solutions are
often prohibitively complicated to compute. When framed in terms of heuristics or prior
beliefs, approximate Bayesian inference provides a tractable and – in some instances –
neuronally plausible scheme for optimisation. This approach marks a significant departure
from the traditional (normative) behavioural-economic approach, where an agent’s beliefs
about their own type do not depend on their actions and vice versa. It also differs from
traditional psychological approaches, where self-representations – including theories
based on self-esteem or on unconscious representations – are seen as the object of a more-
or-less self-contained homeostasis, rather than an explicit heuristic of how to behave
optimally in social exchanges.

<hs>  Self- and other-representation in a model Trust Task</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Game-theoretical paradigms can induce people to infer traits in others and express their
own traits in beliefs and behaviour. The ‘Trust task’ is a prototypical paradigm (King-
Casas et al., 2008; Ray et al., 2008). In each of several rounds one of the participants,
in the role of the Investor, is given a certain ‘wage’. They can invest any fraction fI of
that ‘wage’ with the Trustee. The Trustee makes a profit, which is usually taken to be
200%. They then keep as much of this as they want and return to the Investor any fraction
fT of the ‘wage’. How much will the Investor entrust to the Trustee? Repeated rounds allow
each player to try to deduce the ‘type’ of their partners. Are they disposed to cooperate
(fT > fI), or maybe ‘grab the money and run’ (fT ≪ fI)? Behavioural studies demonstrate
healthy people often ‘repair cooperation’ that falters, but patients with borderline
personality drift towards the Nash equilibrium, suppressing overall incomes (King-Casas et
al., 2008). The Nash equilibrium has a paranoid flavour: in this game, it says that in the
last round the Trustee will ‘take the money and run’, and therefore should not be trusted.
The same logic holds for the penultimate round, and so on through a process of iterative
backward inference to the very first one. Therefore the Investor should never trust any
money to the Trustee. The Trust Task has been extensively studied, and is attended by a
large amount of psychological and neurobiological data (Xiang, Ray, Lohrenz, Dayan, &
Montague, 2012). However, existing models do not make adequate contact with clinical
psychology. Here, we consider a framework for modelling this task that is equipped with
minimal clinically relevant self- and other-representations. This can be used to analyse
the behaviour of people who might hold unstable or distorted interpersonal
representations. Our framework extends classical models (Camerer, 2003; Ray et al., 2008)
that lack flexible, computationally functional self-representations. Let us consider
agents who think about alternative future scenarios to a limited depth-of-thought (‘one,
two steps …’) and then consider how they and their partners would ‘come across’ in the
long term (‘… infinity’). This gives interpersonal representations a functional role.
Unlike classic neuroeconomic models – and closer to clinical psychology – at the end of
each round subjects have to update their own self-image based upon their actions and those
of their partner. We therefore have a Bayesian Attribution – Self-Representation (BASR)
model, formalising the attribution theory suggested by Bentall (2003). In the BASR model,
working out each possible scenario two moves into the future enables the ‘type’ of each
partner at that future point to be estimated (Fig. 1). There are at least two interesting
ways in which the estimated types of self and other may be useful. First, people may have
intrinsic preferences as to the type of person they want to be, and the type of person
they want their partner to be. The framework of active inference allows us to think about
‘wanting the partner to be’ as ‘believing that the partner will indeed turn out to be’.
The preferences inform goals over the sort of person they are. We could, furthermore,
hypothesize that such goal preferences are context specific: contexts may, for example, be
labelled as competitive or cooperative, and stronger priors attached to corresponding
person types. Second, types can be exploited in explicit approximations of the
consequences of behaviour. An expectation that long-term behaviour will be consistent, on
average, with the inferred player ‘types’ would lead to an estimate of long term returns.
This would then be absorbed into appropriate goal priors. Overall, the BASR model of a
simplified Trust Task would run as follows. First, agents know what actions are available.
Let’s allow them just two options in each round of 30 rounds, a high (cooperative) or low
(uncooperative) contribution fhigh or flow. Second, agents hold beliefs about how
‘cooperative’ each player is, i.e. the player’s types. We can think of ‘cooperative’ being
a positive, high-esteem trait in this context. Third, agents estimate the likely evolution
of the game a small number of moves into the future – e.g. ‘I play X, she plays Y, then I
play Z’. This evolution may be more or less likely according to the agents’ empirical
priors. It may also be more or less compatible with their goal priors, as we saw. Agents
also have a sense of how precise their prediction of reaching their goals may be; this
‘precision’ is important for the mechanics of active inference but outside the scope of
this review. The interested reader is referred to our technical exposition (Friston et
al., 2013). Finally, the player whose turn it is to play infers an updated view of the
interaction. This maximises the consistency between their prior beliefs about the world,
their observations, their goals, their confidence (precision) in reaching those goals –
and of course their policy. Their action then flows from their preferred policy, and it’s
the other player’s turn.

<hs>  The interpersonal self in psychiatric disorders</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Severe psychiatric disorders often illustrate terrible distortions and deficits in self-
perception. Let us consider two examples: “I cannot live and I cannot die, because I have
failed so much, I shall bring my husband and children to hell ... I shall go to the
convict prison and my two girls as well, if they do not make away with themselves because
they were born in my body.” This extract is from a letter written by a severely depressed
patient of Emil Kraepelin – the patient who failed to update her self-image in response to
being given a nice present. It expresses a nihilism that remains familiar to contemporary
clinicians, who are all too aware that a distorted representation of the self can be a
debilitating symptom in severe depression. In the second example, self-perception is
deficient: “Isn’t America supposed to be the land of the free? How come, if I’m free, I
can’t deprive a stupid f∗∗∗ing dumbs∗∗t of his possessions if he leaves them on the front
seat of this f∗∗∗ing van out in plain sight...? Natural selection. F∗∗∗er should be shot.”
This is a quote from Mr. E. Harris, a mass murderer who attracted a diagnosis of
psychopathic disorder (Cullen, 2009). It illustrates how he both talked and acted as if
his representations of other people carried no value. This was most striking when the
prospect of their suffering seemed to hold no aversive value for him. Moreover, he was
devoid of any concern that his beliefs and behaviour would devalue him as a person, de
facto rendering him despicable in any community. Contemporary psychiatric practise
acknowledges the importance of self-representation. Descriptive diagnostic criteria, such
as the DSM-5, define a disturbance of the representation of self and the evaluation of
others as core features of Personality Disorders (Skodol et al., 2011). Moreover, several
empirically validated therapies assume that self-representations are important links in a
causal chain that leads to psychiatric disorders. For example, cognitive-behavioural
therapy postulates that ‘core beliefs’ related to the self, such as “I am unworthy”,
underpin depression (Waller, Shah, Ohanian, & Elliott, 2001). Many mentalization-based
therapies propose that infants internalise representations that caregivers make available
to them – a process which, if it goes awry, may lead to conditions such as borderline
personality disorder (Allen, Fonagy, & Bateman, 2008). The less evidence-laden approach
adopted by psychoanalysis posits fragmented representations of others (part-objects) as
underlying severe mental disorders. In Borderline Personality disorder, patients often
fail to predict the damage that their actions cause, in terms of the way they are
perceived by other people and the ruinous consequences this has for the person themselves
(Allen et al., 2008).

<hs>  When self and others are perceived as noxious entities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Many psychiatric conditions might be described as ‘nocebo states’. In nocebo states
physiologically inert stimuli have aversive effects, e.g. an inert tablet causing nausea.
This is a mirror image of the placebo effect. In psychiatry, features of the self or the
environment that most outsiders would regard as innocuous are often perceived as toxic. A
common example of perceiving a facet of the self as toxic is as follows. A patient with
borderline personality quarrels with a relative about an everyday matter. This activates
loathing of the self to such a degree that the patient hides away and carves insults on
her skin with a razor. However most common, distressing ‘nocebo’ perceptions in psychiatry
are unwarranted (to the outside observer) versions of everyday concerns – such as that
others are devious and the self is worthless, as exemplified by the study by quoted in
Table 1 (Fowler et al., 2006). In many clinical accounts it is not only self-
representations that are dysfunctional: efforts to bolster specific aspects of self-
representation are also seen as maladaptive. However, the precise role of self-
representation is highly controversial, partly due to the fact that it is difficult to
quantify and access in a strictly empirical manner. This highlights the fact that despite
a focus on self-representation over recent years, its normative function is poorly
understood. There is obvious value for interpersonal exchange in asking “what sort of
person is the Other?” However, the value of healthy inference about “what sort of person
do these actions make Me” has not being addressed so thoroughly. The subtle clinical
concept of ‘mind-blindness’ is relevant here. Clinicians mean by this that borderline
patients, especially under stress, show an inability to reflect about other people’s minds
or indeed their own. Increasing this ability through gradual learning is the basis of
Mentalization Based Therapy (Allen et al., 2008). As we saw, placebo responders are
characterised by the absence of a term reporting sensory information about the outside
world (no term in ys,t−1 in Eq. (1)). There are indications that people with borderline
personality disorder may have an analogous but more subtle deficit in interpersonal
interaction. When interpersonal Trust falters they fail to ‘signal’ to their opponent, by
risking part of their income, that they are trustworthy. This leads to an unravelling of
trust. In addition, healthy people playing borderline partners display a reduced level of
theory-of-mind, as would be expected if the borderline partner were deficient in higher-
order theory-of-mind terms (Xiang et al., 2012). The ‘missing term’ in these patients’
model of the world would be exactly “what sort of person would these actions make Me?” We
thus have a computational neuroscience counterpart of the clinical concept of ‘mind-
blindness’. Estimation of social threat and opportunity using active inference requires
not only prior beliefs about self and others, but also their approximate Bayesian updating
– including the evaluation of alternative future scenarios. Several cognitive deficits and
biases, such as mildly reduced IQ and working memory or a ‘jumping to conclusions’
cognitive style, are associated with paranoid psychosis (Bentall et al., 2009). How such
non-specific cognitive deficits may contribute to the aetiology of abnormal beliefs is the
subject of much debate. Affective biases are likely to involve prior beliefs about the
nature and likelihood of noxious states in self and others. Could nonspecific cognitive
deficits shift interactions from cooperative to suspicious in the presence of a specific
distributions of prior beliefs? The cognitive-deficit part of this would be analogous to
the way that play can shift from cooperative to non-cooperative under the influence of
reduced depth-of-thought (Yoshida et al., 2008). Paranoia may result from prior beliefs
about self and others that are activated by specific, aversive contexts – and maintained
by a reduced cognitive ability to consider more complicated but benign scenarios. An
important factor in generative models of paranoia may be the belief that persecutors do
not attach aversive motivational value to the persecuted person’s distress. Such a model
is actually true if one’s partner has psychopathy. The hallmark of this is that the
partner is unable to attach aversive motivational value to the suffering of others (like
Mr. Harris above) despite being able to infer its presence.

<hs>  The embarrassment of Bayesian riches</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Active inference assumes that subjects optimise a probabilistic representation of the
environment. This assumption is not one of perfect or rational behaviour but of a type of
bounded rationality based upon a potential universe of prior beliefs or heuristics.
Previous research has also used this philosophy, of perfect optimisation within a
suboptimal cognitive model (Moutoussis, Bentall, El-Deredy, & Dayan, 2011). When it comes
to psychopathology, however, we encounter a difficult problem: Is ‘deviant’ behaviour the
result of inefficient model optimisation or due to an ‘inefficient’ model of the world? In
other words, are prior beliefs (the model) abnormal, or is psychopathology the result of
‘broken’ active inference? This is a particularly important and challenging question as on
the one hand, any behaviour can be explained as optimal Bayesian inference given some set
of priors and utility function; while some behaviours are undoubtedly the result of what
we may call ‘broken’ active inference. Examples of the latter are likely to include drug-
induced psychosis or dementia.

<hs>  How can one’s type be unknown?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If, as we maintain, a person’s type enters into their decisions, isn’t that person’s type
tautologically the one which determined those decisions? In what sense can such a type be
unknown to the subject, and have to be inferred? At least three alternatives should or
could be tested. First, there may be separate decision-making and self-evaluating parts of
the self, something akin to an actor-critic architecture in reinforcement learning (Sutton
& Barto, 1998). Parenthetically, no self-deception needs to be invoked here. Beliefs
posterior to observing the world, including the self, need not accord with the maximum
likelihood of observations: other constrains enter inference too, as we have seen in some
detail. Second – in a related vein – there may be no well-defined ‘type’. The history of
psychology and psychiatry is littered with abandoned models of personality traits and
types, while stereotypes about groups have little predictive value. Like these models,
people’s self-representations (e.g. ‘I am a music-lover’) may simply be instances of the
fundamental attribution error. In this case, the approach suggested above might help
delineate stable patterns of interactions and attributions, including self-fulfilling
prophesies, which describe the situation at hand but have no deeper explanatory power.
Third – and most interesting – types may have to be inferred and applied in relation to
social norms. How much work a person has to do for others to be considered ‘kind’, or what
offers a ‘fair’ person might make in an ultimatum game? (Xiang, Lohrenz, & Montague,
2013). If ‘kind’ or ‘fair’ people are treated on average better than ‘unkind’ or ‘unfair’
ones, then inferring one’s own type becomes even more important, and more challenging, for
each social partner.

<h>CONCLUSIONS: A PROGRAM FOR CHARACTERISING INTERPERSONAL REPRESENTATIONS</h>
-----------------------------------------------------------------------

In conclusion, we have reviewed two key hypotheses. First, that people make inferences
about themselves – and others – to minimise interpersonal surprise enabling them to make
decisions that are most consistent with their model of the interpersonal world. Second, we
suggest that the framework of active inference can capture the iterative dynamic of ‘where
do I desire to get’, ‘what do I decide’ and ‘what do my actions make me’. The programme of
research that this analysis speaks to is to characterise different prior beliefs (about
contingencies, utilities, prosocial utilities and types) in relation to choice behaviour,
under the assumption that subjects engage in approximate Bayesian inference. Bayesian
subjects are assumed to update of models of their world, while Bayesian researchers infer
models of individual variability of choice behaviour (we could call the latter meta-
Bayesian fitting). Both can be implemented through free energy minimisation. The updating
of self-representations by subjects could then be mapped onto neurobiological substrates,
e.g. via functional neuroimaging. This approach could help advance our understanding of
distorted self- and other-representations in many conditions – including depression,
personality disorder and paranoia. Practically, we envisage that the first step will
entail characterising the updating of beliefs over other people’s type, which in turn
results from exposure to others’ actions, under the simplification that only the immediate
returns matter. One could then consider prior beliefs about outcomes in the long-term
future, and their influence on self-representation. Finally, one might simulate and study
the behaviour of interacting self-representing agents that can even exert choice over the
types of ‘games’ they engage in. We hope to pursue these studies and the ideas reviewed
above to help contextualise and motivate a formal focus on how we represent ourselves and
how these representations determine our behaviour.


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<ART>Behavioural markers for autism in infancy: Scores on the Autism Observational Scale for Infants in a prospective study of at-risk siblings
================================================================================

Authors: Isobel Gammer, Rachael Bedford, Mayada Elsabbagh, Holly Garwood, Greg Pasco, Leslie Tucker, Agnes Volein, Mark H. Johnson, Tony Charman, Simon Baron-Cohen, Patrick Bolton, Susie Chandler, Janice Fernandes, Teodora Gliga, Kristelle Hudry, Andrew Pickles
DOI: 10.1016/j.infbeh.2014.12.017
Year: 2015  |  Pages: 107-115
ASJC codes: 3204
Keywords: ASD, Autism, Autism observation scale for infants (AOSI), Early behavioural markers, High-risk siblings

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We investigated early behavioural markers of autism spectrum disorder (ASD) using the Autism Observational Scale for Infants (AOSI) in a prospective familial high-risk (HR) sample of infant siblings (N= 54) and low-risk (LR) controls (N= 50). The AOSI was completed at 7 and 14 month infant visits and children were seen again at age 24 and 36 months. Diagnostic outcome of ASD (HR-ASD) versus no ASD (HR-No ASD) was determined for the HR sample at the latter timepoint. The HR group scored higher than the LR group at 7 months and marginally but non-significantly higher than the LR group at 14 months, although these differences did not remain when verbal and nonverbal developmental level were covaried. The HR-ASD outcome group had higher AOSI scores than the LR group at 14 months but not 7 months, even when developmental level was taken into account. The HR-No ASD outcome group had scores intermediate between the HR-ASD and LR groups. At both timepoints a few individual items were higher in the HR-ASD and HR-No ASD outcome groups compared to the LR group and these included both social (e.g. orienting to name) and non-social (e.g. visual tracking) behaviours. AOSI scores at 14 months but not at 7 months were moderately correlated with later scores on the autism diagnostic observation schedule (ADOS) suggesting continuity of autistic-like behavioural atypicality but only from the second and not first year of life. The scores of HR siblings who did not go on to have ASD were intermediate between the HR-ASD outcome and LR groups, consistent with the notion of a broader autism phenotype.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Younger siblings of children with an autism spectrum disorder (ASD) represent a high-risk
group for ASD, with recent estimates of the recurrence rate in siblings as high as 18.7%
(Ozonoff et al., 2011). This allows prospective study of development from the first few
months of life in infants who will later go on to receive a diagnosis of ASD. Within such
prospective infant sibling designs, identifying the earliest differences or markers in
those who go on to develop autism is a research priority (Zwaigenbaum, Bryson, & Garon,
2013). Current aetiological models of autism propose that typical developmental
trajectories are derailed by complex interactions between underlying genetic and
neurological vulnerabilities, environment and behaviour, with cascading developmental
effects (Gliga, Jones, Bedford, Charman, & Johnson, 2014). However, the details of these
developmental processes are poorly understood. It is hoped that understanding the ordering
and interactive influences of the earliest biological and behavioural perturbations will
elucidate developmental mechanisms that lead to the pattern of symptoms and impairments
that characterise the clinical phenotype, as well as protective mechanisms that
differentiate those at familial risk who go on to have non-ASD outcomes. This may in turn
point to targets for treatment as well as improving identification of those infants at
highest risk for the disorder in infancy, allowing very early intervention to be put in
place (Green et al., 2013, in press).

<hs>  Early behavioural signs of autism in high-risk studies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Recent reviews of high-risk (HR) sibling studies find convergent evidence for the
emergence of overt behavioural markers between 12 and 18 months of age that distinguish,
at a group level, those infants who go on to receive an ASD diagnosis from other HR
infants and low-risk (LR) groups (Jones, Gliga, Bedford, Charman, & Johnson, 2014;
Zwaigenbaum et al., 2013). At this age, clinically relevant behavioural differences span
both social communication (e.g. gaze following (Bedford et al., 2012); social referencing
(Cornew, Dobkins, Akshoomoff, McCleery, & Carver, 2012)) and stereotyped/repetitive
behaviour (e.g. repetitive play (Christensen et al., 2010); repetitive movement (Loh et
al., 2007) domains, as well as motor (Flanagan et al., 2012) and attentional atypicalities
(Elsabbagh et al., 2013), appearing to represent early manifestations of later ASD
symptoms. However, there is considerable heterogeneity at the individual level in the
pattern of symptom emergence. Prior to 12 months of age, however, few overt behavioural
markers for autism have been identified (Jones et al., 2014). In a recent report, Jones
and Klin (2013) found that in a small sample of HR infants who went on to an ASD
diagnosis, fixation on the eyes declined between 2 and 6 months of age. Other behavioural
signs in the first year of life have included reduced gaze to people (Chawarska, Macari, &
Shic, 2013) and vocal atypicalities (Paul, Fuerst, Ramsay, Chawarska, & Klin, 2010).
Experimental studies have detected atypical neural response to social stimuli such as
dynamic eye gaze from as young as 6 months of age (Elsabbagh et al., 2012).

<hs>  The Autism Observation Scale for Infants (AOSI)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Whilst the research reviewed above and elsewhere (Gliga et al., 2014; Jones et al., 2014;
Zwaigenbaum et al., 2013) has mostly used experimental tasks/paradigms and observational
and parent-report methods, there is also a clinical need for an instrument that allows
systematic observation of early-emerging atypicalities in infants at-risk for ASD. The
Autism Observational Scale for Infants (AOSI; Bryson, Zwaigenbaum, McDermott, Rombough, &
Brian, 2007) is a semi-structured, experimenter-led behavioural assessment designed to
measure early behavioural markers of ASD in infants aged between 6 and 18 months. These
include atypicalities or delays in social communication behaviours (e.g. anticipatory
social response, social babbling, orientation to name, eye contact) and non-social
behaviours (e.g. disengagement of visual attention, motor control and behaviour, atypical
sensory behaviours) as well as aspects of temperament (e.g. reactivity, ease of
transitions between activities). Preliminary findings from the instrument's authors’ HR
sibling cohort suggested that AOSI scores by 12 months but not at 6 months were promising
as a predictor of later ASD outcomes based on 24 month ADOS classification (Zwaigenbaum et
al., 2005). The same group have reported that whilst many individual AOSI items across
domains (e.g. orients to name, eye contact, reactivity) at both age 6 and 18 months
differentiated the group of HR siblings who go on to have an ASD classification at 36
months and LR controls, only atypical motor behaviour differentiated HR siblings who go on
to have ASD from HR siblings who do not at both timepoints (Brian et al., 2008, 2013).
Early behavioural atypicalities measured by the AOSI at 12 months have also been shown to
characterise nearly one fifth of HR siblings who do not go on to have ASD (Georgiades et
al., 2013), consistent with the notion of sub-clinical manifestations of ASD being present
at an enhanced rate in family members of individuals with ASD, referred to as the broader
autism phenotype (BAP; Bolton et al., 1994).

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

The present study sought to replicate in an independent sample whether predictive
associations exist between AOSI scores in early (at around 7 months) and later infancy
(around 14 months) and ASD outcome at 36 months. In the present study we analysed AOSI
data from both 7 and 14 month timepoints in a cohort of HR siblings and LR controls
subsequently followed up at 24 and 36 months to answer the following questions: Do scores
on the AOSI differ between HR siblings and LR controls at 7 and 14 months? Do scores on
the AOSI differ between those HR siblings who go on to have a diagnosis of ASD from those
HR siblings who do not? Within the HR group are there associations between AOSI scores at
the 7 and 14 month timepoint and later scores on the Autism Diagnostic Observational
Schedule (ADOS-G; Lord et al., 1999) at 24 and 36 months?

<h>METHODS</h>
-------

Ethical approval for the BASIS study was obtained from NHS NRES London REC (08/H0718/76).
One or both parents gave informed, written consent for their child to participate.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

One hundred and four children (54 HR, 50 LR) were recruited as part of the British Autism
Study of Infant Siblings (BASIS; www.basisnetwork.org). They were seen on four visits when
aged 6–10 months (mean = 7.35, SD = 1.21; hereafter 7 m), 11–18 months (mean = 13.79, SD =
1.46; hereafter 14 m), and then around their 2nd birthday (mean = 23.9 months, SD = .95;
hereafter 24 m), and third birthday (mean = 37.93 months, SD = 3.02; hereafter 36 m). Each
HR infant had an older sibling (in 4 cases, a half-sibling) with a community clinical ASD
diagnosis (hereafter, proband), confirmed on the basis of information in the Development
and Wellbeing Assessment (DAWBA; Goodman, Ford and Richards 2000) and the Social
Communication Questionnaire (SCQ; Rutter, Bailey and Lord 2003) by expert clinicians on
our team (TC, PB). Most probands met ASD criteria on both measures (n = 44). While a small
number scored below threshold on the SCQ (n = 4), no exclusions were made due to meeting
the DAWBA threshold and expert opinion. For two probands, data were only available on one
measure, and for four probands, neither measure was available (aside from parent-confirmed
local clinical diagnosis). Parent-reported family medical histories were examined for
significant conditions in the proband or extended family members (e.g., Fragile X
syndrome, tuberous sclerosis) with no such exclusions deemed necessary. LR controls were
full-term infants (gestational ages 37 to 42 weeks; 3 born 32 to 36 weeks) recruited from
a volunteer database at the Birkbeck Centre for Brain and Cognitive Development. Medical
history review confirmed lack of ASD within first-degree relatives. All LR infants had at
least one older sibling (in three cases, only half-siblings). The SCQ was used to confirm
absence of ASD in these older siblings, with no child scoring above instrument cut-off
(≥15; n = 1 missing data).

<hs>  The Autism Observational Scale for Infants (AOSI)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Autism Observation Scale for Infants (AOSI; Bryson et al., 2007; revised version used
in this study; Brian et al., 2008) is an experimenter-led, semi-structured observational
assessment, developed to study the nature and emergence of ASD-related behavioural markers
in infancy (6–18 months). A standard set of objects and toys are used across five
activities – each with a specified series of presses for a particular behaviour – and two
periods of free-play. Responses to presses and observations made throughout the assessment
are used to code nineteen items (see Brian et al., 2008; Bryson et al., 2007; for full
description of presses, items and coding; items listed in the Appendix). Each item is
coded on a scale from 0 to 2 or 0 to 3. A rating of 0 denotes typical behaviour and higher
scores denote increasing atypicality. In the current study the 19 item version of the AOSI
reported by Brian et al. (2008) was used. The AOSI yields a Total Score (sum of all codes;
max score 44). The AOSI is administered by a trained examiner who sits at a table opposite
the infant who is held on the parent's lap. AOSIs were administered by research-reliable
research staff and the majority of administrations were double-coded by the examiner and
an observer. Agreement between the two coders was excellent at both 7 months (n = 92,
intraclass correlation coefficient = .97) and 14 months (n = 85, intraclass correlation
coefficient = .95). When codes differed between researchers, they discussed and agreed on
a consensus code, where no observer codes were available the examiner's code was used.

<hs>  Developmental assessments and outcome groups</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

All participants were assessed at all visits on the Mullen Scales of Early Learning (MSEL;
Mullen, 1995)—a measure of developmental abilities yielding an Early Learning Composite
(ELC) standardised score (mean = 100; SD = 15). In order to explore the association
between verbal and nonverbal developmental abilities and AOSI scores we calculated mean
T-scores from the two Verbal (Receptive Language, Expressive Language) and two Nonverbal
(Fine Motor, Visual Reception) Mullen subscales. Of the 54 HR infants recruited, 53 were
retained to the 36 m visit when comprehensive diagnostic assessment was undertaken. At 36
m parents of HR siblings completed the Autism Diagnostic Interview—Revised (ADI-R; Lord,
Rutter, & Le Couteur, 1994) and the SCQ (Rutter et al., 2003), and both HR and LR toddlers
were assessed with the Autism Diagnostic Observation Schedule (ADOS-G: Lord et al., 1999;
24 m module 1N = 50, module 2N = 2; 36 m module 2N = 50 toddlers, module 1N = 3) and the
revised Social Affect and Repetitive and Restrictive Behaviours subtotal and calibrated
severity scores computed (Gotham et al., 2007). Assessors were not blind to risk-group
status. Assessments were conducted by or under the close supervision of clinical
researchers (i.e., psychologists, speech therapists) with demonstrated research-level
reliability. Different teams of researchers saw participants at the first two visits and
the second two visits. Those assessing developmental outcomes were blind to infants’
performance on the AOSI. In determining diagnostic outcome status, four clinical
researchers (KH, SC, GP, TC) reviewed information across the 24 m (including an ADOS-G
assessment for the HR siblings) and 36 m visit (including both ADOS-G and ADI-R
administration for the HR siblings). Seventeen toddlers (11 boys, 6 girls) met ICD-10
(World Health Organisation, 1993) criteria for an ASD (combining ICD-10 childhood autism
and pervasive developmental disorder (hereafter, HR-ASD subgroup)). The remaining 36
toddlers (10 boys, 26 girls) did not meet diagnostic criteria for ASD (HR-No ASD). For the
LR control group, in the absence of a full developmental history (no ADI-R was
administered) no formal clinical diagnoses were assigned but none had a community clinical
ASD diagnosis at 36 months. It is worth noting that the recurrence rate reported in the
current study (32.1%) is higher than that reported in the large consortium paper published
by Ozonoff and colleagues (18.7%; Ozonoff et al., 2011). This is likely to reflect the
modest size at-risk sample in the current study (N = 53). Whilst recurrence rates
approaching 30% have been found in other moderate size samples (Landa & Garrett-Mayer,
2006; Paul et al., 2010) these rates are sample specific and will likely not be
generalizable as findings from larger samples where autism recurrence rates converge
between 10% and 20% (Constantino et al., 2010; Sandin et al., 2014). Similar procedures
combining all information from standard diagnostic measures and clinical observation and
arriving at a ‘clinical best estimate’ ICD-10 diagnosis was used in the present study in
line with other familial at-risk studies and was conducted by an experienced group of
clinical researchers. HR siblings and LR controls did not significantly differ from each
other in age at any visit (t-tests, all ps > .34), nor did the HR outcome groups or LR
controls differ from one another in age at any visit (all ps > .20; see Table 1 for
descriptive statistics on all measures). Whilst the ELC scores of the HR siblings were in
the average range, at each visit their scores were lower than those for the LR controls
(t-tests, all ps < .01). The HR-ASD group had lower ELC scores than the LR group at all
four visits (all ps < .05) and lower ELC scores compared to the HR-No ASD group at the 14
m and 36 m visits (both p < .05) but not the 7 m and 24 m visits.

<hs>  Analysis</hs>
  ~~~~~~~~

Due to the skewed distribution of the AOSI Total Score a square root transformation was
applied and the transformed data met assumptions of normality, with the exception of the
LR group at 14 m of age (p < .05). HR versus LR scores were compared using ANOVA and HR-
ASD, HR-No ASD and LR scores were compared using a one-way ANOVA and post-hoc Tukey HSD
tests. Cohen's d effect sizes are reported (Cohen, 1988). Following this in order to
control for verbal and nonverbal developmental level the Mullen mean Verbal and Nonverbal
T-scores were covaried and post-hoc least significant difference (LSD) tests conducted.
For individual AOSI items, HR versus LR scores were compared using Mann–Whitney tests and
HR-ASD, HR-No ASD and LR scores were compared using Kruskal–Wallace tests and significant
differences followed-up using post-hoc Mann–Whitney tests. Given the larger number of
items but also allowing for the exploratory nature of the analysis, a moderately
conservative significance level of p < .01 was used. Correlations between AOSI scores and
the total scores on the ADOS (Social Affect and Restricted and Repetitive Behaviour
subtotals combined) at 24 months and 36 months in the HR group only were examined using
Pearson's product moment correlations.

<hs>  HR versus LR group differences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As shown in Table 2, at 7 m the HR group had a higher AOSI score than the LR group F(1,
102) = 4.10, p < .045 (d = .39). At 14 m the HR group had a higher AOSI score than the LR
group but the difference was not statistically significant F(1, 99) = 3.36, p = .07 (d =
.36). However, when Mullen Verbal and Nonverbal T-score at each age point was covaried,
the difference between the HR and LR groups was no longer significant (7 m: F(3, 99) =
.66, p = .37; 14 m: F(3, 96) = 2.24, p = .14). At 7 m but not 14 m the covariate effect
for Mullen Verbal T-score was significant (F(3, 99) = 4.48, p < .05).

<hs>  HR outcome group differences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Comparing AOSI scores for the HR-ASD and HR-No ASD outcome groups and the LR group, at 7 m
the one-way ANOVA just missed significance F(2, 98) = 2.94, p = .058 (see Table 2 and Fig.
1). At 14 m, the three outcome group comparison was significant F(2, 96) = 4.43, p = .014.
Post-hoc Tukey tests showed that the HR-ASD group scored higher than the LR group (p =
.01; d = .81). The HR-ASD group also had a marginally but not significantly higher AOSI
score than the HR-No ASD group (p = .07; d = .65). These analyses were repeated covarying
for Mullen Verbal and Nonverbal T-score at each age. The HR outcome groups and LR group
did not differ from each other at 7 m of age, F(4, 95) = .61, p = .47 but did differ from
each other at 14 m of age, F(4, 93) = 3.85, p = .03. Post-hoc LSD tests showed that at 14
m the HR-ASD group scored higher than both the LR group (p < .01) and the HR-No ASD group
(p = .03) and that the HR-No ASD group and LR group did not differ from each other (p =
.53). At 7 m but not 14 m the covariate effect for Mullen Verbal T-score was significant
(F(4, 95) = 4.31, p < .05).

<hs>  Individual AOSI items</hs>
  ~~~~~~~~~~~~~~~~~~~~~

In terms of individual items, at 7 m the HR and LR groups did not differ on any items but
the HR group scored higher than the LR controls on one item at 14 m (orientation to name;
U = 931.00, p < .01). In terms of HR-ASD vs. HR-No ASD outcome groups vs. LR group
differences, at 7 m there were significant differences for the following items: visual
tracking (χ2 = 9.99, p < .01; HR-No ASD > LR: U = 634.50, p < .01) and Social Referencing
(χ2 = 10.78, p < .01; HR-ASD > LR: U = 206.50, p < .01). At 14 m there were significant
differences for the following items: orientation to name (χ2 = 11.50, p < .01; HR-No ASD >
LR: U = 596.00, p < .01; HR-ASD > LR: U = 282.50, p < .01), Engagement of Attention (χ2 =
9.75, p < .01; no significant post-hoc tests) and Social Referencing (χ2 = 9.75, p < .01;
no significant post-hoc tests).

<hs>  Associations between AOSI scores at 7m and 14m and ADOS scores at 24m and 36m</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To examine associations over time between behavioural atypicality as measured by the AOSI
in infancy and the ADOS in toddlerhood correlations were examined in the HR group. Since
the AOSI measures attentional disengagement and atypical motor behaviours, as well early
social communication behaviours, AOSI scores were compared to the ADOS ‘total score’. AOSI
score at 7 m was not associated with ADOS score at either 24 m (r = .23, p = .10) or 36 m
(r = .16, p = .27). However, AOSI score at 14 m was significantly associated both with
ADOS score at 24 m (r = .30, p = .03) and at 36 m (r = .38, p = .005).

<h>DISCUSSION</h>
----------

Consistent with previous reports (Brian et al., 2008, 2013; Georgiades et al., 2013)
behavioural atypicalities as measured by the AOSI differentiated the HR and LR groups in
the first year (7 months) and (marginally) early in the second year (14 months) of life.
At 14 months (but not 7 months) these behavioural markers also discriminated between those
HR infants who went on to an ASD diagnosis and LR controls and marginally between HR who
did and did not go on to an ASD diagnosis. The HR versus LR group comparisons were
attenuated when verbal and nonverbal developmental level was controlled but the HR-ASD
outcome group differences remained significant. The HR-No ASD outcome group scored
intermediate between the HR-ASD outcome group and the LR control group. Several aspects of
this pattern of differences are worthy of comment. First, the HR versus LR group
comparisons are modest only in effect size (.39 at 7 months and .36 at 14 months).
However, in those HR infants who went on to meet diagnostic criteria for ASD at 36 months
by the 14 month timepoint the effect sizes were large (.81 compared to the LR controls;
.65 compared to HR infants who did not go on to meet criteria for ASD at 36 months. The
current sample is modest in size but, notwithstanding this, significant sub-group
differences were still found because of the relatively large behavioural differences on
this observational measure of early autistic atypicality. Although the AOSI combines
developmental abilities (e.g. imitation) and the presence of atypical or unusual
behaviours (e.g. atypical motor and sensory behaviours) the effects of developmental level
as measured by the Mullen verbal and nonverbal subscales did not predominate, with only
verbal ability at 7 month being significantly associated with the AOSI total score.
Finally, the HR-No ASD group performed intermediate between the HR-ASD group and LR group,
both on overall total scores (Table 2) and on individual items (see below). The boxplots
in Fig. 1 show that the interquartile range of this group span across those of both the
HR-ASD and LR groups, suggesting that characteristics that might be considered as aspect
of the early ‘broader autism phenotype’ (BAP) are seen in some but not all of the infants
at familial high-risk who do not go onto an ASD presentation at 36 months of age (see also
Georgiades et al., 2013).

<hs>  Individual items</hs>
  ~~~~~~~~~~~~~~~~

Although the initial report on the AOSI found that scores were predictive of a diagnosis
at 12 months but not 6 months (Zwaigenbaum et al., 2005), subsequent studies have found
that some behaviours at 6 months differentiate HR siblings and LR controls (e.g. eye
contact, social referencing) and also those HR siblings who go on to have an ASD diagnosis
from both LR controls (e.g. reactivity, disengagement of attention) and HR siblings who do
not go on to have an ASD (e.g. atypical motor control) (Brian et al., 2013). In terms of
individual AOSI items we found no HR vs. LR group differences at 7 m and HR siblings only
scored higher than LR controls on one item at 14 m (orientation to name). We found that
social referencing at 7 m and orientation to name also at 14 m differentiated the HR
siblings who went on to have an ASD from LR controls. Furthermore, in line with the BAP
concept (Georgiades et al., 2013; Ozonoff et al., 2014), HR siblings who did not go on to
have an ASD also showed higher levels of atypical behaviour at 7 m (visual tracking) and
14 m (orientation to name), compared to LR controls. However, these item-level findings
should be considered exploratory given that a strict correction for multiple testing was
not undertaken and require replication in other samples. In contrast to previous reports
(Brian et al., 2008, 2013; Georgiades et al., 2013), we conservatively adjusted for the
differences in verbal and non-verbal developmental ability between the groups. It is
increasingly apparent, consistent with the phenotype of ASD, that both developmental and
language delays are part of the BAP at a group level (Messinger et al., 2013; Ozonoff et
al., 2014) and, whilst covarying for these differences one might be taking out some of the
variance of interest, early atypical behaviours still discriminated between the infants
who went on to have ASD and those who did not.

<hs>  Associations between the AOSI and later ADOS scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Within the HR sibling group we examined the association between early behavioural
atypicalities as measured by the AOSI and later early symptoms of autism as measured by
the ADOS. AOSI scores at 7 months were not associated with later ADOS scores but AOSI
scores at 14 months were moderately associated with ADOS scores at 24 and 36 months.
Although the two instruments are not identical there is a considerable overlap in the
concepts, behaviours and scoring systems, and this suggests a moderate degree of
continuity of autistic-like behavioural atypicality from the beginning of the second year
of life into the toddler years. However, as has been found with many experimental measures
(Jones et al., 2014), with a few exceptions, this continuity is not apparent from as early
as 6 to 8 months of age. As such, it appears that the AOSI is successfully capturing very
early emerging autistic behaviours. Larger samples will be required in order to test both
how predictive such early behavioural markers are at an individual, as opposed to a group,
level and in order to trace the longitudinal trajectory of the emergence of such
behaviours over this early time course (Landa et al., 2012, 2013). This work is much
needed as increasingly in some communities concerns about possible autism are raised about
some children in the second year of life, in particular younger siblings of a child with
an ASD given the now well-established recurrence rate of between 10% and 20% (Constantino
et al., 2010; Ozonoff et al., 2011; Sandin et al., 2014).

<hs>  Limitations</hs>
  ~~~~~~~~~~~

We consider these findings preliminary due to the modest sample size and they will require
confirmation in larger and other independent samples. However, it is the first independent
report on the AOSI and replicates some of the findings from the instrument's originators
(Brian et al., 2008, 2013; Zwaigenbaum et al., 2005). We also note several limitations in
the design, including non-blind assessment (to risk status) at both the infancy and
toddler assessments, although the team conducting the toddler visits were blind to infant
AOSI scores.

<h>CONCLUSIONS</h>
-----------

The current findings confirm the emerging picture that early behavioural atypicalities in
emergent ASD include both social and non-social behaviours (see Jones et al., 2014; for a
review). Some of these atypicalities are found only in HR siblings who go on to have ASD
but others are also found in HR siblings who do not, supporting the notion of an early
broader autism phenotype (Georgiades et al., 2013; Ozonoff et al., 2014). Understanding
the interplay between different neurodevelopmental domains across the first years of life
and the influences on these will be important both to understand the developmental
mechanisms that lead to the ASD behavioural phenotype and to inform approaches to
developing early interventions (Green et al., 2013, in press; Wallace & Rogers, 2010).


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<ART>Can evolution get us off the hook? Evaluating the ecological defence of human rationality
================================================================================

Authors: Maarten Boudry, Michael Vlerick, Ryan McKay
DOI: 10.1016/j.concog.2014.08.025
Year: 2015  |  Pages: 524-535
ASJC codes: 3204, 3205
Keywords: Adaptation, Cognitive bias, Ecological rationality, Error management, Evolutionary psychology, Fallacies, Fast & frugal heuristics, Irrationality, Locus shifts

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This paper discusses the ecological case for epistemic innocence: does biased cognition have evolutionary benefits, and if so, does that exculpate human reasoners from irrationality? Proponents of 'ecological rationality' have challenged the bleak view of human reasoning emerging from research on biases and fallacies. If we approach the human mind as an adaptive toolbox, tailored to the structure of the environment, many alleged biases and fallacies turn out to be artefacts of narrow norms and artificial set-ups. However, we argue that putative demonstrations of ecological rationality involve subtle locus shifts in attributions of rationality, conflating the adaptive rationale of heuristics with our own epistemic credentials. By contrast, other cases also involve an ecological reframing of human reason, but do not involve such problematic locus shifts. We discuss the difference between these cases, bringing clarity to the rationality debate.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Like any other biological organ, the human brain is a product of evolution by natural
selection: The brain secretes thought as the liver secretes bile, wrote the 18th century
French physiologist Pierre Cabanis in his Des Rapports du Physique et du Morale de
l’Homme. But does the brain’s biological provenance suggest it must be successful at
producing true beliefs and making rational judgments? Several generations of psychologists
have suggested otherwise, documenting the myriad flaws and foibles of human reasoning
(Gilovich, Griffin, & Kahneman, 2002; Kahneman, 2011; Kahneman, Slovic, & Tversky, 1982).
Especially in popular summaries of this research, humans come off rather badly – prone to
all sorts of biases and fallacies, woefully inadequate at dealing with probability and
uncertainty, and inclined to persist in making errors of social judgment, even after these
have been clearly spelled out (Ariely, 2009; Piattelli-Palmarini, 1996; Shermer, 2011;
Singer & Benassi, 1981; Sutherland, 2007). The psychologist John Kihlstrom (2004) has
called this the ‘People are Stupid’ school of psychology (PASSP). Recently, however, a new
wave of research, inspired by evolutionary ideas, has posed a challenge to this bleak
picture of human reason. This school of thought heralds an ecological conception of
rationality, aligning itself with research in evolutionary psychology. If we approach the
human mind as a collection of cognitive heuristics, tailored to the structure of the
ecological environment, many alleged biases and fallacies arguably emerge as artefacts of
narrow norms and artificial set-ups. After introducing this ‘ecological rationality’
research program, we identify a ‘locus shift’ in some attributions of rationality. In
these cases, individual reasoners are being praised as rational simply because the
heuristics employed in their reasoning show adaptive design (i.e. are “rational” from an
evolutionary perspective). In other words, the adaptive rationale of cognition
(evolutionary locus) is conflated with our own epistemic credentials (personal locus). We
then evaluate whether the normative categories of (ir)rationality can still be applied at
the evolutionary level of analysis, and conclude that this facet of the ‘ecological
defence’ is confusing: (a) human reasoners do not deserve the “credit” for the adaptive
designs they have been equipped with, and (b) evolution cannot exculpate human
irrationality. Finally, we discuss cases in which the program of ecological rationality
has succeeded in rehabilitating human reason, showing that earlier charges of
irrationality had been premature. These cases also involve a form of ecological reframing,
but they do not involve adaptive locus shifts. The aim of this paper is to provide some
much needed clarification to the debate about rationality. In particular, by clarifying
which ‘defences’ of putative irrationality are legitimate and which illegitimate, we hope
to provide a robust conceptual framework within which to situate and evaluate future
empirical evidence. The debate about rationality is not merely of academic interest:
irrationality is a topic of critical personal and social import. Biased beliefs about the
self and the future may promote individually harmful behaviours like smoking, unsafe sex
and overspending, as well as potentially precipitating global catastrophes such as
sectarian violence, world wars, exploding financial bubbles and environmental disasters
(Johnson & Fowler, 2011; Sharot, 2011). Given these wide-ranging outcomes, getting clear
about the nature and extent of human irrationality is a critical philosophical and
psychological project.

<hs>  Recasting rationality in the environment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the heuristics and biases program instigated by Daniel Kahneman and Amos Tversky in the
80s (Kahneman, 2011; Kahneman et al., 1982), heuristics are viewed as mental short-cuts
leading to imperfect and often outright irrational inferences. Though Kahneman and Tversky
pointed out that even fallible heuristics often lead to successful inferences, over time
this sense of balance was lost, and a negative slant began to dominate the research
program they founded (Krueger & Funder, 2004).1 The program of ecological rationality, by
contrast (Fawcett et al., 2014; Gigerenzer, Hertwig, & Pachur, 2011; Gigerenzer & Todd,
1999; Hertwig & Hoffrage, 2013; Todd & Gigerenzer, 2012), aims to effect a gestalt switch,
urging us to rethink the norms of what counts as rational. The canons of ‘classical’
rationality, to which Kahneman & Tversky’s subjects were held accountable, consist of a
general, formal, content-free framework for valid reasoning (e.g. modus ponens). Advocates
of ‘ecological rationality’, by contrast, uphold a radically different view of heuristic
reasoning. Heuristics, they argue, provide us with an ‘adaptive toolbox’ (Gigerenzer,
2008; Gigerenzer & Todd, 1999), each suited to a particular set of challenges endemic to a
particular environment. In contrast with unbounded models of classical rationality, which
typically assume unlimited resources both with regard to information gathering and
computational processing, ecological rationality is ‘fast and frugal’. According to
Gigerenzer and Todd (1999, p. 13), a heuristic is ecologically rational ‘to the degree
that it is adapted to the structure of an environment’. Heuristics are quick and
computationally cheap, requiring few and simple computational steps, and operating on a
limited input domain. For example, when confronted with two objects, only one of which is
recognized, people infer that the familiar one will be more important or have a greater
value. Although this so-called ‘recognition heuristic’ – on which more later – leads us
astray in artificial set-ups, it appears to be a surprisingly accurate guide to real world
problems (Goldstein & Gigerenzer, 2002). Proponents of ecological rationality claim that
many apparent demonstrations of irrationality in the heuristics and biases program are
artefacts of inappropriate standards and narrow norms, such as coherence criteria and the
axioms of probability theory. Indeed, many experiments are expressly designed to mislead
or distract participants, placing them in situations where their usually successful
strategies and heuristics lead them astray. If one canvasses the same phenomena in a
broader framework, however, taking into account the structure of real environments,
computational limitations and various trade-offs, the human mind emerges as more rational
than many psychologists suppose.

<hs>  Two strands</hs>
  ~~~~~~~~~~~

We detect two major strands in the re-appreciation of (apparent) human irrationality as
ecologically rational. On the one hand, as the ecological rationalist points out,
traditional cognitive psychologists have too often delighted in tripping up their subjects
with artificial set-ups that truncate the complexity of real life and human intelligence
(first strand). On the other hand, ecological rationalists have argued that heuristics are
not designed to perform well in artificial (non-ecologically valid) environments. If
putatively ‘irrational’ subjects were tested in an ecologically relevant context, the kind
to which their evolved heuristics are attuned, they would behave rationally (second
strand). In both strands, ecological rationality focuses our attention on the match
between our reasoning and the real world. The sensible argument behind this is that we
should evaluate heuristics in their ‘proper’ context. You should not use a screwdriver as
a crowbar and be surprised that it breaks.2 Whereas the first strand focuses on artificial
set-ups and uncharitable experimenters, the second strand invokes evolutionary rationales.
In the latter case, advocates of ecological rationality point out that heuristics are
crafted by evolution to deal with particular adaptive problems in an ancestral
environment. Therefore, they have a “proper domain” of application (Sperber, 1996) – what
Millikan (1984) termed “Normal conditions” – outside of which we should not expect them to
perform well. Blaming them for “malfunction” in unnatural contexts, without proper
appreciation of their design features, is like blaming the screwdriver. Nevertheless, as
we will argue, while the former approach is (often) warranted, the latter involves
problematic locus shifts.

<hs>  Evolutionary psychology</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

This second evolutionary strand runs through much of the literature on ecological
rationality, (Gigerenzer & Selten, 2002). And indeed, the program connects with work in
the field of evolutionary psychology on the adaptive value of cognitive bias (Aktipis &
Kurzban, 2004; Cosmides & Tooby, 1994; Haselton & Nettle, 2006; Haselton, Nettle, &
Andrews, 2005; Mercier & Sperber, 2011; Nesse, 2001), the main thrust of which is also to
show the ecological validity of human reason. As Haselton & Nettle write: Some cognitive
illusions disappear or greatly attenuate when the task is presented in an ecologically
valid format (Cosmides & Tooby, 1996; Gigerenzer & Hoffrage, 1995). Ecological validity, a
long-standing but undertheorized term in psychology, may in effect be equated to the task
format approximating some task that humans have performed recurrently over evolutionary
time. Apparent biases and illusions are recast in an evolutionary light, as serving some
adaptive rationale. From an adaptationist point of view, human reason is not the botched
and bias-riddled device many psychologists take it to be, but emerges as an extremely
effective, highly specialized set of adaptive tools for dealing with recurring problems in
the Environment of Evolutionary Adaptedness (EEA). In an overview of the research program
of ecological rationality, Gerd Gigerenzer wrote that ‘what appears to be a fallacy can
often also be seen as adaptive behaviour, if one is willing to rethink the norms’
(Gigerenzer, 2008, p. 13). In a similar vein, Haselton and Nettle (2006, p. 59) have
argued that ‘bias in cognition is no longer a shortcoming in rational behaviour, but an
adaptation of behaviour to a complex, uncertain world’. Elsewhere, Haselton and colleagues
wrote ‘an adaptationist perspective suggests that the mind is remarkably well designed for
important problems of survival and reproduction, and not fundamentally irrational.’ These
assessments seem to provide solace for the pessimistic view of human reason voiced by many
psychologists. But can evolution really get us off the hook?

<hs>  Minimal conditions for rationality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In order to assess what exactly ecological/adaptive rationality amounts to, we need a
serviceable conception of rationality. While attempting to formulate a full blown
definition seems doomed to fail, given the loose and varied use of the term, some
constraints on the meaning of ‘rationality’ will guide us through this treacherous
terrain. In this paper, we will be mainly concerned with epistemic rationality (belief
formation that is accurate and truth-tracking) and not so much with instrumental
rationality (actions that maximize the probability of success, according to some
standard). According to De Sousa (2009, p. 289), rationality presupposes intentionality.
An inanimate object or mere mechanism cannot be rational. It would be absurd to claim that
a rock falling to the ground is rationally obeying the laws of gravity, much as it would
be strange to call a calculator rational because it yields correct answers. Likewise,
irrationality is a concept that can be meaningfully applied only to intentional creatures
– entities capable of full-blown rationality (de Sousa, 2007). Irrationality is a term of
epistemic disapprobation, used when someone fails to live up to some expected normative
standard. As ought implies can, it makes no sense to blame a mindless process: It makes
sense to criticize a person, but not a cell, for having made a mistake in computation, or
with having failed to foresee what should have been foreseen, or with having acted on
reasons that fell short of the best set of reasons. In an extended, metaphorical sense,
however, standards of rationality can be fruitfully applied to the domain of
functionality, including biological adaptations and artefacts, even when no intentionality
is involved. Although natural selection is a mindless process, it can produce an
appearance of intentionality by crafting design solutions to recurring adaptive problems
(Williams, 1966/1996). Evolution by natural selection gives rise to what Dennett coined
‘free-floating rationales’ (Dennett, 1983, p. 351). In this extended sense of rationality,
the relevant measure of success is equated with reproductive success or inclusive fitness
(Over, 2000), and standard frameworks of rationality such as game theory (Maynard Smith,
1974) or expected utility theory (see Section 3.2) can be applied (Kacelnik, 2006).
Because of the absence of intentionality, however, not all dimensions of full-blown
rationality can be transferred to evolution. Whereas individual reasoners are capable of
foresight, evolution cannot look into the future. For example, selection can easily get
stuck on local peaks in an adaptive landscape, unable to reach nearby higher summits. If
evolution had the capacity of foresight, it would backtrack and make a detour, as a human
reasoner would. Evolution, therefore, provides a mere ‘simulacrum of rationality’ (de
Sousa, 2009, p. 298).

<hs>  Locus shifts</hs>
  ~~~~~~~~~~~~

Given that rationality (in the literal sense) can only be attributed to person-level
decision making (see above), we question whether the ecological reframing succeeds in
dispelling the charge of irrationality. In order to get clear about the notion of ‘locus
shifts’, we first discuss an example from evolutionary psychology in which a similar
calculus of rationality may be implemented either at the individual level or on an
evolutionary scale: error management. This will allow us to pull apart the two loci of
rationality, while holding the measure of success (e.g. protection from bodily harm)
constant. Expected utility theory is one of the hallmarks of classical rationality: it
describes how to maximize utility under uncertainty, as a function of the probability of
different outcomes and their associated costs and benefits. Normally, the model is used to
describe individual choices, for example betting preferences. In recent years, however,
the logic of expected utility theory has been extended to evolutionary adaptations, under
the guise of error management theory (Haselton & Buss, 2000; Haselton & Nettle, 2006;
Nesse, 2001).3 In a range of different situations, organisms need to process ambiguous
stimuli that may or may not signal adaptively relevant situations, such as the presence of
a predator or pathogen. If the costs associated with the respective errors, measured in
terms of (inclusive) reproductive fitness, are asymmetric, then expected utility theory
can be applied to predict optimal behaviour. If the costs associated with one type of
error are larger than those associated with the opposite kind, then a strategy biased in
favour of making the less costly error may pay off in the long run, even if that increases
the absolute numbers of errors (Arkes, 1991). As Haselton et al. put it: ‘it is better to
make more errors overall as long as they are of the relatively cheap kind’ (Haselton et
al., 2005, p. 731). Error management is displayed in a range of biological adaptations
that are clearly beyond our voluntary control, such as inflammation, disgust, fever and
coughing. In all of these cases, the locus of rationality is clearly evolution by natural
selection, not the individual subject. Things get more interesting when considering
applications of error management theory to human cognition. In such cases, the locus of
rationality may reside either at the individual level or at the evolutionary level. In
most discussions of error management, human behavioural biases are interpreted in terms of
biased belief, with evolution as the rational bookkeeper. For example, people buy into
various superstitions because they evolved pattern detection modules that err on the side
of caution. In order not to miss out on any important causal patterns in the world,
evolution has ‘decided’ to run the risk of occasional false positives, which are mostly
relatively harmless. In a commentary on error management theory, however, McKay and
Efferson (2010) argued that human behavioural bias does not automatically entail biased
belief. In principle, the same behavioural bias may be arrived at through accurate belief
formation combined with judicious action policies, based on expected utility theory. If I
react to a rustle in the leaves as if there is a predator lurking in the bushes, I do not
need a strong belief that a predator is there. Likewise, when approaching a girl that I
like, I do not need to be certain that she fancies me. I may decide to act upon an
admittedly remote possibility, in light of the high opportunity costs associated with
false negatives (ending up as lunch, or missing a romantic – read reproductive –
opportunity). As McKay & Efferson noted, ‘there are infinitely many ways to accomplish the
required behavioural change … inferences about cognition can be radically underdetermined
when one observes an interesting behavioural bias.’ (see also Marshall, Trimmer, Houston,
& McNamara, 2013; McKay & Efferson, 2010, p. 312). The logic underlying the behavioural
bias is the same, but our normative appraisal of human reasoners depends on where the
locus of rationality resides. If the behavioural bias is the outcome of a prudential
action policy, without the involvement of biased belief, we should not accuse reasoners of
irrationality. For example, people fasten their seatbelts before starting the car not
because they strongly believe they will crash into other cars, but just because they would
rather be safe than sorry: the cost of a false negative (being flung through the
windscreen) is orders of magnitude larger than that of a false positive (the energy
expended in fastening one’s seatbelt and the mild discomfort of being strapped in it),
large enough to offset the small probability of a serious car accident. This is a case of
full-blown (intentional) rationality, situated at the level of individual decision making.
An alien scientist interpreting this prudential human behaviour as a symptom of irrational
paranoia would be very uncharitable indeed. On the other hand, if a behavioural bias stems
from some attendant belief distortion, the charge of irrationality may be apposite. For
example, if an unattractive man approaches every woman at the bar, believing that he is
irresistible to the opposite sex, we may be justified in calling him irrational. If biased
behaviour translates to bias in belief formation, however, with evolution keeping the
books of fitness costs and benefits, we think our assessment should be different (for a
discussion, see Galperin & Haselton, 2012). From the adaptationist point of view, the
ecological ‘problem’ of exploiting causal regularities in an organism’s environment can be
solved by different means: a fixed and genetically encoded action sequence, the capacity
to form conditional reflexes and make associations, a belief formation system with a pre-
programmed belief bias, or the genuine capacity for causal thought and expected utility
reasoning (Dennett, 1996; Lorenz, 1941/2009). Only in the latter case is rationality
displayed at the locus of the individual decision-maker. For example, many people engage
in superstitious rituals because they strongly believe in the causal connection. If error
management theorists are right, there is indeed method in the madness of such
superstition, since the fitness cost of overlooking causal links outweighs the fitness
cost of detecting non-existent causal relationships. In such cases, however, the locus of
‘rationality’ pertains to the adaptive design of our reasoning faculties. Although it is
tempting to collapse both levels of rationality, as though the adaptive rationale of our
superstitious behaviour redounds to the human reasoner, the ‘method’ of natural selection
does not obviate – indeed it requires – the ‘madness’ of the individual. Accordingly, we
defend the following claims: We should not credit human reasoners simply because the
adaptive design of their reasoning faculties conforms to some standard principles of
rationality.4 We do not congratulate people for their sophisticated immune systems or
ingenious thermoregulation, nor do we credit cicadas for having discovered prime numbers,5
or spiders for the beautiful geometry of their webs. There is neither cognitive
transparency – the organism has no clue why it behaves as it does – nor intentional
action. According to Dennett, If we discover that an animal is too simple-minded to
harbour an adaptive rationale, we do not discard the rationale but are simply forced to
‘pass the rationale from the individual to the evolving genotype’ (Dennett, 1983, p. 351).
Conversely, if we have good grounds for calling someone’s beliefs irrational (see
further), then merely pointing out the larger evolutionary rationale of the faculties
generating those beliefs will not get him off the hook. Having biologically adaptive
cognition is not an alibi where the charge of irrationality is concerned. If superstitious
belief is adaptive, because it motivates ‘better safe than sorry’ behaviours, that does
not make superstitious people rational. For example, while people who believe that black
cats are harbingers of bad luck may be heeding to the ‘wisdom’ of time-honoured cognitive
adaptations, that does not make their belief rational or truth-tracking.

        <hss>Statistical rationales</hss>

        In the classical heuristics-and-biases framework, heuristics are perceived as
        imperfect shortcuts in an uncertain world, strategies that execute a trade-off
        between cost and accuracy. Gigerenzer and his colleagues, however, have documented
        several cases where this trade-off can be escaped, and ‘less information and
        computation lead to more accurate judgments’ (Gigerenzer & Sturm, 2012, p. 261).
        The showpiece of these ‘less is more’ effects is the recognition heuristic, where
        people take advantage of their own ignorance to make intelligent inferences. In
        judging which out of two cities has a larger population, for example, people use
        name recognition as a cue for population level. When the task consists of German
        cities, American subjects perform better than their German colleagues, because the
        latter recognize too many cities to exploit their own ignorance. A measure of
        ignorance turns out to be profitable in this case (Goldstein & Gigerenzer, 2002),
        while knowing too much is a burden. Apparently, everyday life presents us with
        many situations in which the recognition heuristic proves successful. It provides
        us with a powerful and accurate tool for making inferences about the environment.
        Fast and frugal heuristics escape a trade-off between accuracy and speed because
        ‘they make a trade-off on another dimension: that of generality versus
        specificity’ (Gigerenzer & Todd, 1999, p. 18). In later work, Gigerenzer and
        Brighton (2009) have explored another dilemma (between bias and variance) for
        explaining when and why such ‘less-is-more’ effects occur. The upshot of this
        statistical analysis is that the simplicity of fast and frugal heuristics (few
        computational steps and few parameters) protects them against overfitting (i.e.
        mistaking noise for underlying patterns) and hence ensures robustness in the face
        of environmental change. The success of the recognition heuristic derives from a
        probabilistic rationale. In order for the trick to work, there needs to be a
        correlation between the probability that an item is recognized and the value of
        interest. This ‘recognition validity’ needs to outweigh the ‘knowledge validity’,
        which is the probability of giving the correct answer when both items are
        recognized (Goldstein & Gigerenzer, 1999, 2002). In other words, your ignorance
        must be more valuable than your knowledgeability. In addition, success depends on
        the degree of uncertainty, the number of alternatives, and the size of the
        learning sample. Goldstein & Gigerenzer conclude: [M]any scholars, psychologists
        included, have mistrusted the power of these heuristic principles, and saw in them
        simple-mindedness and irrationality. This is not our view. The recognition
        heuristic is not only a reasonable cognitive adaptation because there are
        situations of limited knowledge in which there is little else one can do. It is
        also adaptive because there are situations … in which missing information results
        in more accurate inferences than a considerable amount of knowledge can achieve.
        Now what should we make of this contrast between simple-mindedness and ‘reasonable
        cognitive adaptation’? Can we attribute rationality to heuristic-wielding human
        thinkers when their heuristics yield accurate inferences?

        <hss>Cognitive transparency</hss>

        The answer to this question depends on the criteria of cognitive transparency and
        intentionality. As pointed out, attribution of (literal) rationality requires
        intentional deliberation on the part of the actor, not just the execution of hard-
        wired action patterns or mindless heuristics. (cf. 3.1 Minimal conditions for
        rationality). To avoid regress of justification, of course, we should not require
        that the agent has contemplated every step in the chain of belief-formation.
        Perceptual beliefs may arise automatically, without deliberation and thus without
        rationality, but more complex beliefs can be formed consciously on the basis of
        basic perceptual beliefs. On the latter level, attributions of rationality and
        irrationality can be meaningfully made.6 Without delving into empirical details,
        we can be confident that many people are ignorant of the statistical principles
        underlying the success of the recognition heuristic. This is hardly surprising if
        the heuristic is a ‘cognitive adaptation’, as Goldstein and Gigerenzer (2002)
        suggest. Many cognitive modules in our brain perform their proper function without
        us having the slightest awareness of their operation, let alone their design
        features and the reasons for their success. If the recognition heuristic is an
        evolved adaptation, activated under appropriate circumstances by a mechanism to
        which human cognizers have no access, it would be strange to credit people for its
        success. The locus of rationality, in this case, is at the level of adaptation.
        Evolution, rather than human cognizers, has exploited recurrent statistical
        correlations in the environment. However, recent research shows that some people
        who use the heuristic articulate a justification that captures the ecological
        validity (Gigerenzer, 2007, pp. 125–126), and they will suspend the use of the
        heuristic if they have good counter-indications (Pachur, Todd, Gigerenzer,
        Schooler, & Goldstein, 2011). Even if such reasoners have no full understanding of
        the statistical principles involved, it seems that the criterion of transparency
        is satisfied, and it would be uncharitable to deny them rationality at the
        personal level. In general, however, the evidence points in the other direction
        Research suggests that people hardly ever make conscious decisions about which
        heuristic to use but that they quickly and unconsciously tend to adapt heuristics
        to changing environments, provided there is feedback. In another striking example
        from the catalogue of fast and frugal heuristics, both humans and dogs use the
        following rule of thumb to catch a ball in flight: keep your gaze fixed at the
        ball, and adjust your running speed such that the angle of the ball in your visual
        field remains constant (Gigerenzer & Todd, 1999). If baseball players are asked to
        predict where a ball will land, but are not allowed to run towards it, they
        perform very poorly (Babler & Dannemiller, 1993). However, when asked how they
        proceed to catch a ball on the fly, people are typically oblivious of using the
        heuristic: ‘most fielders are blithely unaware of the gaze heuristic, despite its
        simplicity’ (Gigerenzer, 2007, p. 11). This, it should be emphasised, does not
        mean that heuristic-wielding humans are irrational, but that the normative
        categories of (ir)rationality simply do not apply insofar as humans are working on
        automatic pilot. Interestingly, on some occasions, Gigerenzer & Todd explicitly
        credit evolution for the design of heuristics: ‘evolution would seize upon
        informative environmental dependencies such as this one and exploit them with
        specific heuristics if they would give a decision-making organism an adaptive
        edge’ (Gigerenzer & Todd, 1999, p. 19). Such statements, however, are in tension
        with the main thrust of their research programme, which is to dispel accusations
        of ‘simple-mindedness’ and irrationality by pointing to the larger ecological
        picture. As we saw in the example of error management, adaptive design is
        perfectly compatible with dumbness. In this regard, the novel insights gleaned
        from Gigerenzer et al.’s research program conflict with their aspiration to
        rehabilitate human reason. Indeed, if the rationale of the recognition heuristic
        or the gaze heuristic were transparent to those profiting from it, the results of
        Gigerenzer et al. would not have been so informative. The effectiveness of these
        heuristics is surprising even to the researchers themselves. For example, another
        deceptively simple heuristic, ‘take the best’, which takes the first
        discriminative cue between two items and ignores the other cues, has outperformed
        weighted statistical decision procedures such as multiple regression. This is how
        Gigerenzer & Goldstein relate their amazement at their own result: ‘When we first
        obtained these results, we could not believe them.’ (Gigerenzer & Todd, 1999, p.
        89). Because people use their heuristics without cognitive transparency, they are
        also often insensitive to local conditions where their heuristics lead them
        astray.7 For example, many advertisers exploit the recognition heuristic by
        investing in brand recognition rather than product quality, thereby undermining
        the ecological validity of the correlation between renown and product quality and
        fooling consumers. In the ‘overnight fame’ experiments by Jacoby, Kelley, Brown,
        and Jasechko (1989), people who had been presented with unknown names the day
        before were tricked into believing that those names were famous. This should not
        come as a surprise. Evolution exploits recurring statistical properties of the
        environment of evolutionary adaptiveness (EEA), but it is not responsive to any
        environmental contingency. For evolution it is ‘rational’ to implement the
        recognition heuristic in an organism as long as overshooting or misfiring has been
        sufficiently rare or inconsequential in the EEA. Error management on the
        evolutionary scale abstracts away from local contingencies.

<hs>  Why adaptive ‘rationality’ does not align with personal rationality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the section on error management, we noted that adaptively ‘rational’ cognition may
translate into irrational belief, such as superstition. There are two additional reasons
why evolutionary rationality and personal rationality may diverge. The first is the so-
called problem of adaptive mismatch. If heuristics are evolved adaptations for managing
cost asymmetries in the EEA, there is no guarantee that the same balance sheet still
applies to modern environments. Probabilities may have changed over time, as may have the
respective costs and benefits. This mismatch hypothesis is one of the main tenets of
evolutionary psychology (Pinker, 1997; Tooby & Cosmides, 1994).8 A heuristic may succeed
in the EEA but fail in modern environments, or only match some limited aspects of modern
environments (e.g. to predict which city will have the largest population). A second
reason concerns the issue of who – or rather what – is the ultimate beneficiary of natural
selection (cui bono? see Dennett, 1995). As Dawkins (1976) has pointed out, following up
on pioneering work by Williams and Hamilton (Hamilton, 1963; Williams, 1966/1996), genes
can be seen as the ultimate beneficiaries of evolutionary adaptation. Individual organisms
are best seen as ‘vehicles’ for genetic propagation (Dawkins, 1982). Take, for instance,
the suicidal sting of a bee. Such behaviour is ‘rational’ from the point of the
evolutionary processes that gave rise to such behaviour, because the bee shares 75% of its
genes with its sisters. Sacrificing its life to enhance the survival chances of the hive
therefore makes sense from a gene-centric perspective. But it certainly does not benefit
the individual bee. Evolutionary rationality – which is situated at the level of the
replicators – therefore does not always coincide with rationality at the level of the
vehicle (Skyrms, 2000; Stanovich & West, 2000; Stanovich & West, 2003).

<h>GENUINE FALLACIES</h>
-----------------

Let us now have a closer look at two famous examples from the irrationality literature,
where advocates of ecological rationality have performed a locus shift: the gambler’s
fallacy and the hot hand fallacy. The former refers to the belief of roulette players that
numbers which have not turned up yet are more likely to win in the next round, because
they are ‘overdue’. In reality, of course, each turn of the roulette wheel is independent
of the next. The wheel has no memory, so the probability distribution remains the same at
every trial. More generally, the gambler’s fallacy describes the belief that statistical
deviations in a given direction will soon be counterbalanced by deviations in the opposite
direction. The hot hand fallacy can be seen as the mirror image of the gambler’s fallacy.
To commit the hot hand fallacy is to believe that, if some deviation from chance has been
observed, further deviations in the same direction are more likely on subsequent trials.
The name derives from basketball, where there is a widespread belief among players and
fans that players score in streaks (Gilovich, 1983; Gilovich, Vallone, & Tversky, 1985).
If one player has already scored well, he has a ‘hot hand’ and is more likely to make
further points during the rest of the game. If he makes a bad start, however, there is a
jinx on him and he will be less likely to perform well during the rest of the match.
Statistical analyses of basketball scoring data have revealed no such clustering (but see
Raab, Gula, & Gigerenzer, 2012, for evidence of streakiness in volleyball), but belief in
the hot hand persists.9 The fact that each of these forms of inference has been bestowed
its proper label in the literature, despite their being one another’s mirror image, is a
source of amusement to Gigerenzer and his colleagues. For them, it exemplifies the bad
habit of psychologists to label any observed deviation from accepted rationality models as
a ‘fallacy’ or ‘bias’, without any understanding of the underlying cognitive mechanisms
(Gigerenzer & Brighton, 2009). Are these unflattering labels justified? Steven Pinker has
argued that the gambler’s fallacy is not really a fallacy, because in most natural
environments, a succession of events is not statistically independent: the probability of
an event changes in function of earlier occurrences. Many events work like that. They have
a characteristic life history, a changing probability of occurring over time which
statisticians call a hazard function. An astute observer should commit the gambler’s
fallacy and try to predict the next occurrence of an event from its history so far …
Roulette wheels, with their smooth and radially symmetric design, are expressly designed
to foil this heuristic, according to Pinker: ‘in any world without casinos, the gambler’s
fallacy is rarely a fallacy’ (Pinker, 1997). Indeed, our ability to spot statistical
dependencies between events in real-life may often prove very useful. That morale even
holds for chance games outside the idealized world of casinos. If I play a dice game at a
fair and the dice land on 12 a couple of times in a row, it is not unreasonable to predict
that they will do so the next time too – because they are probably rigged. In general, as
Bennis et al. have written, ‘casino games [are] exquisitely designed to exploit otherwise
adaptive heuristics to the casino’s advantage’ (Bennis, Katsikopoulos, Goldstein,
Dieckmann, & Berg, 2009, p. 421). Taleb (2008) has referred to the inappropriate
application of pure and simplified models of probability to real life as the ‘ludic
fallacy’. Intuitions that lead us astray in the rarefied and idealized world of casinos,
may prove very useful in real-life situations. If I am presented with some strange device
that churns out black and white balls, and I do not have access to its inner working, I
may be forgiven for thinking that there is a statistical dependence between different
trials. I may even be perfectly justified in doing so, extrapolating from earlier
experience. An experienced gambler in a casino, by contrast, possesses all the requisite
evidence he needs to conclude that this is not a machine to which his pattern detection
heuristics will apply. If even a crash course in statistics and a careful inspection of
the roulette wheel fail to cure him of his habit of thought, then we may, pace Pinker,
call his reasoning fallacious. The natural way to construe Pinker’s argument is as a point
about adaptation. Given that pure randomness is rare in the EEA (as it most probably still
is today in natural environments), it made sense for evolution to endow us with a knack
for spotting patterns, with the minor side-effect of making us vulnerable to (fair) dice
games and roulette wheels. After enduring five straight days of rainy weather, as Pinker
notices, it would have made sense for the optimistic early hominid to expect a sunny
spell. As weather fluctuation often follows statistical patterns, the sun can really be
‘overdue’. For evolution, it makes sense to ‘gamble’ on the kind of environments with a
specific hazard function, and to disregard the abstractions of casino wheels, which did
not feature in ancestral environments. In a similar vein, the hot hand fallacy may arise
from a heuristic adapted to environments with positive temporal autocorrelation or
‘clumping’ (Fawcett et al., 2014; Wilke & Barrett, 2009). But what does that say about us?
Are we forgiven for using the heuristic anyway, even in the face of countervailing
information? Personal-level rationality involves the ability to use contingent information
about the problem task in order to understand which strategies are conducive to success. A
rational person should reflect upon the deliverances of her intuitions and rules of thumb,
and disregard them when she has good reasons to believe that they lead her astray (Over,
2000). Irrationality often stems from what Fiedler and Wänke (2004, 2013) have called
‘meta-cognitive myopia’, or the inability to critically evaluate intuitive heuristics and
use them in appropriate settings. In the case of casinos, there is indeed an alternative
course of action available. Many experienced gamblers, though still feeling the intuitive
pull of the pattern-seeking heuristic, suppress or resist it in practice, because they
realize that the wheel has no memory and every turn is independent of all the others.
Surely (Dennett, 2013) such players are more ‘rational’ than the ones who succumb to the
gambler’s fallacy, in all of the senses we explored: they understand the justification of
their beliefs, they intentionally aim for a specific goal, and they will be more
successful in attaining it. Indeed, one of the hallmarks of (human) rationality is our
ability to reflectively evaluate and cross-validate the output of our cognitive modules,
and to overrule their intuitive hunches when the context calls for it. In this regard,
whereas Pinker emphasises that the gambler’s fallacy is not a fallacy in a world without
casinos, we emphasise that it is nevertheless a fallacy in a world with casinos. As de
Sousa points out, the rational ‘strategies’ attributed to natural selection are conceived
in the most general terms, on the basis of phylogenetic ‘experiences’ and without precise
reference to the circumstances under which they may be implemented. By contrast,
individual rational agents face particular problems in possibly unique circumstances (de
Sousa, 2007, p. 137). Rationality, in this perspective, consists of using our reasoning
abilities appropriately to deal with the situation at hand, not blindly following
heuristics of which – with hindsight – we can appreciate the adaptive rationale.

<hs>  Conjunction fallacy?</hs>
  ~~~~~~~~~~~~~~~~~~~~

Does the program of ecological rationality always involve locus shifts, and their
attendant problems of transparency and intentionality? No. The second strand of the
program of “ecological rationality” (Section 2.2), does not depend on adaptive
considerations, and hence does not involve locus shifts. The ‘ecological’ dimension of
rationality, in this strand, concerns the real-life contexts of human reasoning, which are
typically truncated in artificial lab experiments. To illustrate this difference, we will
briefly consider two examples of alleged human bias that have been reinterpreted under the
banner of “ecological rationality”, but which do not involve adaptive locus shifts and
which satisfy the minimal requirements of personal-level rationality. Consider the
following classic test: Linda is 31 years old, single, outspoken, and very bright. She
majored in philosophy. As a student, she was deeply concerned with issues of
discrimination and social justice, and also participated in anti-nuclear demonstrations.
Which is more probable? Linda is a bank teller. Linda is a bank teller and is active in
the feminist movement. In their original research on what became known as the ‘Linda
problem’, Kahneman & Tversky held human reasoners accountable to the conjunction rule: B
cannot be more probable than A, because it is an accepted rule of probability theory that
the conjunction of two events can never be more probable than either of its members.
Still, the majority of subjects answered B. Gigerenzer, however, pointed out that terms
such as ‘and’ and ‘probable’ are polysemous. ‘Probable’ can also mean plausible, sensible,
or supported by evidence (Gigerenzer, 1996; Hertwig & Gigerenzer, 1999). Kahneman &
Tversky expect subjects to interpret ‘probable’ in the sense of mathematical probability.
As a number of researchers have pointed out, however (Adler, 1984; Dulany & Hilton, 1991;
Hilton, 1995), this construal violates pragmatic rules of conversational inference, in
particular the maxim of relevance (Grice, 1989). According to this maxim, it makes little
sense to adopt the notion of mathematical probability in answering the Linda problem,
given all the additional (and hence presumably relevant) information presented. If
subjects interpret the task as Kahneman & Tversky want them to, the little vignette about
Linda is rendered completely irrelevant to the task, and the ‘correct’ answer depends
solely on the logical operator ‘AND’ and the mathematical meaning of ‘probable’. Why would
the researcher present such an elaborate description of Linda’s character and background,
if it were completely irrelevant? In addition, subjects can reasonably interpret the first
statement as implying that Linda is not active in the feminist movement. These ambiguities
can be ruled out by presenting the task in terms of natural frequencies, or by including
another question that makes the description of Linda relevant, so that the (overall) task
does not violate the maxim of relevance. After such modifications, as it turns out,
subjects reason in accordance with the conjunction rule (Hertwig & Gigerenzer, 1999).10
Given that simple application of the conjunction rule glosses over the conversational
subtleties and ambiguities of the situation, a number of critics have argued that Kahneman
& Tversky’s interpretation is uncharitable (e.g. Margolis, 1987), and even that they, and
not their subjects, have failed to grasp the logic of the Linda problem (Hertwig &
Gigerenzer, 1999): ‘human intelligence reaches far beyond narrow logical norms. In fact,
the conjunction problems become trivial and devoid of intellectual challenge when people
finally realize that they are intended as a content-free logical exercise’ (Gigerenzer,
2008, p. 73).

<hs>  Base rate fallacy?</hs>
  ~~~~~~~~~~~~~~~~~~

Another case of alleged irrationality that (at least partly) disappears when cast in an
appropriate real world environment, instead of an artificial and misleading set-up, is the
infamous base rate fallacy (Casscells, Schoenberger, & Graboys, 1978; Kahneman et al.,
1982, p. 154). For example, when estimating the probability that a patient has contracted
a particular disease, physicians are (sometimes) found to ignore the base rate of the
disease in question. Information about the reliability of the test appears to be the sole
determinant of their judgment, while the statistical prevalence of the disease in the
population group is ignored.

<hs>  However, as Gigerenzer noted, real life is more complicated</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Clinicians, however, know that patients are usually not randomly selected—except in large
survey studies—but rather ‘select’ themselves by exhibiting symptoms of the disease. In
the absence of random sampling, it is unclear what to do with the base rates specified. If
patients are not randomly sampled, Gigerenzer notes, physicians cannot be accused of
committing the base rate fallacy. Indeed, given that real world environments, as opposed
to convenient mathematical idealizations, do not typically proffer random samples, the
judgment of the clinicians is perfectly defensible. In a series of experiments conducted
by Gigerenzer and et al. (1988), people were found to be capable of factoring in base
rates, provided they were ‘convinced’ that the sample was randomly drawn from the
population. Inviting subjects to blindly draw patients’ names from an urn proved effective
in overruling their prior beliefs, whereas merely pointing out random sampling in the
problem description did not. Even though non-random sampling appears to be an intuitive
default assumption, these experiments show that people can and will – given sufficient
commitment – account for base rates when necessary. Indeed, as Gigerenzer points out, with
Tooby and Cosmides (1994), the neglect of base rate information is by no means a
systematic defect of human reasoning, as the label ‘base rate fallacy’ suggests. If
Bayesian problems are couched in terms of frequencies, as opposed to abstract mathematical
probability, it turns out that the ‘fallacy’ largely disappears (but see Kahneman &
Tversky, 1996; Sloman, Over, Slovak, & Stibel, 2003). In other words, it is not that most
people lack the requisite skills to integrate base rate information (Zhu & Gigerenzer,
2006). Provided that there is sufficiently strong indication of random sampling, and that
base rate information is presented in a concrete, accessible way, people’s reasoning
approximates Bayesian theory (Cosmides & Tooby, 1996; Gigerenzer & Hoffrage, 1995). Once
again, Gigerenzer and colleagues argue that the ‘fallacy’ is elicited by the artificial or
experimental set-ups, and evaporates when transferred to real life. It is important to
note that whether and to what extent the conjunction and base rate fallacies disappear
when problems are presented in ecologically valid formats is still hotly debated. This,
however, is a matter of experimental psychology. The point we are making is merely that
the approach taken in these cases does not involve a problematic locus shift.

<hs>  Analysis</hs>
  ~~~~~~~~

Wherein lies the difference between the latter cases and the problematic ones we discussed
earlier, given that both involve a form of ‘ecological’ reframing? In Gigerenzer’s
deflation of the ‘conjunction fallacy’ or the ‘base rate fallacy’, the gestalt switch also
involves adopting a broader view, casting human inference-making in a rich and real world
environment. In these examples, however, the force of the ecological gestalt switch
derives not from any shift to the adaptive rationale of their heuristics, but from the
fact that human reasoners had not been given sufficient information to disambiguate the
problem at hand and to home in on the interpretation intended by the experiments. In
particular, subjects did not know – or were not properly committed to the belief – that
they were dealing with an artificial situation in which the normal richness and ecological
complexity of problem solving should be ignored. How were Kahneman & Tversky’s subjects
supposed to know that their experimenters were interested in a ‘silly’ question that
violates an accepted rule of sensible conversation? Why should they have interpreted the
problem in the sense of mathematical probability, contra their intuition that this made
the whole story about Linda irrelevant? Similarly, why should the physicians have realized
they were expected to take a step back from their regular practice, considering an
unrealistic case in which a subject is randomly drawn from the population at large.
Remember that, when Gigerenzer (1991) committed subjects to the mathematical
interpretation, their reasoning conformed to the conjunction rule. The force of the
argument from ecological rationality here is not that ‘we can design experiments in which
cognitive illusions disappear’ (Kahneman, 2003, p. 711), as Kahneman construes
Gigerenzer’s point, but that there was no illusion in the first place.

<h>CONCLUSION</h>
----------

In order to understand the strengths and frailties of human reason within a naturalized
framework, an evolutionary perspective is invaluable. We applaud the program of ecological
rationality for taking the evolutionary roots of (human) cognition seriously. If one tries
to dispel apparent instances of human irrationality, however, one should not take recourse
to ultimate, evolutionary alibis. The foibles of reason cannot be exculpated simply
because they display some evolutionary rationale, whether arising from error management,
adaptive bias, or some mismatch between evolved heuristics and modern environments. It is
no criticism of a screwdriver (or its human designer) to note that it makes a poor crowbar
– but this does not exculpate the DIY enthusiast who uses a screwdriver as a lever.
Likewise, we can admire the adaptive or functional design of a heuristic while still
impugning the rationality of individuals who blindly misapply it – and should know better.
Conversely, evidence of adaptive cognitive design is not evidence of human rationality. We
cannot fully congratulate ourselves on our ‘rational’ behaviour unless we have some
cognitive access to the goal we want to achieve, our strategy for attaining it, and our
reasons for thinking this strategy is or might be successful. Insofar as humans are
working on automatic pilot, profiting from (or being misled by) the wisdom of their
evolved heuristics, the normative categories of (ir)rationality do not apply. Genuine
rationality presupposes an intentional striving for success. The program of ecological
rationality has pursued two distinct projects, although the distinction between these has
been underappreciated. In its best moments, it has convincingly demonstrated that the
rigid application of content-blind logical norms as a benchmark of rationality produces an
uncharitable view of human cognition, a view insensitive to the subtlety and richness of
human reasoning. On the other hand, advocates of ecological rationality, together with
evolutionary psychologists, have also pointed out the adaptive rationale of some of our
cognitive biases. That research is certainly fascinating, but we should remain wary of
subtle locus shifts between different levels of rationality. In some cases (e.g.
superstition, gambler’s fallacy), having an adapted mind is compatible with misbelief and
irrationality. Even sheer stupidity.


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<ART>Carer-led health interventions to monitor, promote and improve the health of adults with intellectual disabilities in the community: A systematic review
================================================================================

Authors: Rosalyn Hithersay, André Strydom, Gwen Moulster, Marta Buszewicz
DOI: 10.1016/j.ridd.2014.01.010
Year: 2014  |  Pages: 887-907
ASJC codes: 3203, 3204
Keywords: Carer-led intervention, Carers, Health checks, Health intervention, Health promotion, Health services, Intellectual disability, Learning disability

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Using carers to help assess, monitor, or promote health in people with intellectual disabilities (ID) may be one way of improving health outcomes in a population that experiences significant health inequalities. This paper provides a review of carer-led health interventions in various populations and healthcare settings, in order to investigate potential roles for carers in ID health care. We used rapid review methodology, using the Scopus database, citation tracking and input from ID healthcare professionals to identify relevant research. 24 studies were included in the final review. For people with ID, the only existing interventions found were carer-completed health diaries which, while being well received, failed to improve health outcomes. Studies in non-ID populations show that carers can successfully deliver screening procedures, health promotion interventions and interventions to improve coping skills, pain management and cognitive functioning. While such examples provide a useful starting point for the development of future carer-led health interventions for people with ID, the paucity of research in this area means that the most appropriate means of engaging carers in a way that will reliably impact on health outcomes in this population remains, as yet, unknown. © 2014 The Authors.

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<hs>  Health inequalities in ID</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Physical and mental health inequalities have been well documented for people with
intellectual disabilities (ID) (Cooper, Smiley, Morrison, Williamson, & Allan, 2007;
Emerson, 2011; Emerson, Baines, Allerton, & Welch, 2010; Janicki et al., 2002; Kerr et
al., 2003; Servais, 2006; Straetmans, van Schrojenstein Lantman-de Valk, Schellevis, &
Dinant, 2007; Underwood et al., 2012). Although there have been substantial increases in
life expectancy for people born with ID over the past 60 years (Bittles et al., 2002;
Hollins, Attard, von Fraunhofer, McGuigan, & Sedgwick, 1998; Puri, Lekh, Langa, Zaman, &
Singh, 1995; Yang, Rasmussen, & Friedman, 2002), their median age at death remains far
below that of those without ID, with the disparity increasing with the severity of the ID
(Bittles et al., 2002; Glover & Ayub, 2010; Thomas & Barnes, 2010). The most recent data
published on life expectancy comes from a confidential inquiry into the premature deaths
of people with ID in the UK (Heslop et al., 2013). The review covered all deaths (N = 247)
between 1st June 2010 and 31st May 2012, of people with ID aged 4 years or older, who were
registered with a GP in one of 5 areas in South West England. The median age at death for
men with ID was 13 years below that of men in the general population – for women the
difference increased to 20 years. Just under half (48%) of these deaths were deemed to
have been ‘avoidable’, meaning they could have been avoided through good-quality
healthcare (‘amenable’ deaths) or through public health interventions (‘preventable’
deaths) (Heslop et al., 2013).

<hs>  Health checks</hs>
  ~~~~~~~~~~~~~

In light of the increasing awareness of health inequalities, and of the barriers to
accessing good quality healthcare often experienced by people with ID (Alborz, McNally, &
Glendinning, 2005; Backer, Chapman, & Mitchell, 2009; Krahn, Hammond, & Turner, 2006;
Redley, Banks, Foody, & Holland, 2012), several countries have in recent years introduced
primary care health checks for this population (Barr, Gilgunn, Kane, & Moore, 1999; Lennox
et al., 2007; NHS, 2008; Webb & Rogers, 1999). Research has found that health check
programmes for adults with ID identify unmet health needs (Baxter et al., 2006; Lennox et
al., 2007), however their longer-term impact on health outcomes remains to be established.

<hs>  Carer-led interventions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

For those adults who have difficulty recognising and gaining treatment for their health
needs, carers, whether paid or voluntary staff, family, or spouse carers, may be in a
position to monitor illness symptoms, promote healthy lifestyles, or advocate between the
adults they care for and their healthcare providers (Langan, Whitfield, & Russell, 1994).
By holding such a key role in the daily lives of people with ID, carers could potentially
provide a useful resource in terms of more formally assessing and monitoring health needs
and promoting positive health outcomes in the person they care for. Certain existing ID
health checks include carers in the health check process, to provide support, advocacy and
information about the patients’ past and present health status (Lennox et al., 2007; Turk
et al., 2010), however the impact of such interventions on health outcomes is unclear, and
adherence tends to be poor. The primary aim of this study was to conduct a rapid,
systematic literature review of existing health interventions led by carers. We conducted
a broad search, across age-groups which was not limited to the ID population, in order to
find examples of, and outcomes from, carer-led health interventions in a variety of
settings. The results of this review may inform future research to develop and evaluate
carer-led interventions to improve the primary care and health outcomes of individuals
with ID.

<hs>  Search strategy</hs>
  ~~~~~~~~~~~~~~~

We used rapid review methodology (Ganann, Ciliska, & Thomas, 2010; Watt et al., 2008).
Literature was identified via four main sources: the Scopus database, citation tracking,
hand-searching reference lists and expert input. Several people working and publishing in
the field of health care provision and ID were asked to identify any evidence-based carer-
led interventions that they were aware of. Scopus was chosen as the search database, as it
is currently the largest abstract and citation database of peer-reviewed literature, and
has 100% Medline coverage (“SciVerse Scopus Facts & Figures,” 2010). Initial searches were
conducted in February 2013. Citation tracking included following ‘cited by’ links in
Scopus searches, and setting up the searches themselves such that any articles meeting the
search criteria that were published after our initial search, would automatically be added
to the list. 31 May 2013 was deemed the end date for adding new literature. We included
the following search terms: TITLE-ABS-KEY (“carer-led” OR “caregiver-led” OR “carer-
assisted” OR “caregiver-assisted” OR “carer-directed” OR “caregiver-directed” OR “parent-
led” OR “parent-assisted” OR “parent-directed” OR “spouse-led” OR “spouse-assisted” OR
“spouse-directed”) AND health AND (“intervention” OR “check” OR “monitor*” OR “program” OR
“review”).

<hs>  Criteria for selection</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Inclusion criteria were: original research; published in English-language, peer-reviewed,
academic journals; concerning carer-led interventions for improving, monitoring, screening
or promoting physical or mental health, in healthy or clinical populations. Adult and
child participants older than 2 years were included. ‘Carers’ included paid or voluntary
care staff, family or spouses/partners. Review papers were excluded from the final list,
but they were used for hand-searching original research articles. Additional exclusion
criteria were single case studies, method papers not reporting outcomes from the
intervention, infant participants (less than two years old), interventions not led by a
carer, carer-led interventions not targeting physical or mental health, grey literature
and papers published in languages other than English. The titles and abstracts of all
articles were initially assessed for inclusion by the lead researcher (RH). Potentially
qualifying papers were read in full to extract details about the study design and method,
participants, carer group, intervention, controls used and main findings. Final decisions
on inclusion of the studies were agreed by the review team (RH, AS and MB) and all authors
contributed to interpretation and integration of the findings. The reviewers were not
blind to the authors, institutions or journal of publication when assessing the
eligibility of the papers.

<hs>  Quality assessment</hs>
  ~~~~~~~~~~~~~~~~~~

The level of evidence provided by each study was agreed by two researchers (RH and AS),
using the levels of evidence hierarchy published by the Centre for Evidence-Based Medicine
(Howick et al., 2011). The scale runs from 1A to 5, where 1A is the highest level of
evidence possible (i.e. a systematic review of randomised controlled trials (RCTs)) and 5
the lowest (expert opinion without explicit critical appraisal). These ratings were used
to help describe the evidence found, with greater attention given to those studies that
provided a higher level of evidence. The interventions themselves, and the methodology and
outcomes used to assess them, varied widely. It was not possible to quantitatively assess
the efficacy of carer-led interventions, thus results will be presented in the form of a
narrative review, with studies combined by common themes.

<hs>  Overview of the included studies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fig. 1 shows the results of the search process and reasons for excluding studies. 24
papers were included in the final review. An overview of these studies, including the
carer group, patient group, setting, study method, main findings and evidence rating is
provided in Table A1.

        <hss>Summary of results</hss>

        The interventions included in the final list were divided into the following
        themes (number of papers; total number of participants included): carer-led pre-
        health check questionnaires and patient-held records (3; N = 503), carer-led
        interventions for health promotion (12; N = 3498), carer-led symptom monitoring
        and management (4; N = 445), carer-led interventions for mental health (4; N =
        267), screening delivered by carers (1; N = 108).

<hs>  Carer-led pre-health check questionnaires and patient-held records</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Comprehensive Health Assessment Programme (CHAP) and Advocacy Skills Kit Diary (ASK
Diary) were developed in Queensland, Australia, by Lennox and Colleagues (Lennox, Rey-
Conde, & Faint, 2008; Lennox et al., 2010). The CHAP includes an extensive pre-check
questionnaire that is completed by a carer, followed by a GP-led health check. The ASK
diary combines a physical health record and information for GPs working with people with
ID, with advocacy skills training provided for the person with ID if able to self-
advocate, or those advocating on behalf of someone in their care. The intention is to
improve communication between health professionals, people with ID and their carers and
the diary has been designed for continual use in all healthcare environments. An initial
feasibility study with 30 adolescents with ID found that the CHAP was effective at
identifying unmet health needs and increasing health-related activity. However the ASK
diary, although popular with the participants, their parents and their teachers, did not
lead to improved communication levels: despite initially stating their intention to ‘speak
up’ in the health check, not one of the adolescents in the study reported asking a
question, or requesting further information, during medical visits (Lennox et al., 2008).
A later four-arm cluster RCT compared the effects of the CHAP and ASK Diary with care as
usual in adults with ID (Lennox et al., 2010). This trial provides strong evidence for the
efficacy of the CHAP in identifying previously unmet health needs and increasing health-
related activity. However, neither this RCT nor the earlier pilot study considered the
impact of the initial carer-led questionnaire in isolation from the GP-led section of the
CHAP. As such, conclusions about the effect of including carers in the health check
process are difficult to draw. The RCT found that the ASK diary had no quantifiable impact
on measured health outcomes, which included vaccination rates and clinical activity such
as vision checks or weight monitoring. However, exit interviews with 94 carers revealed
that 19% of them had never used the diary: any effects could therefore have been under-
estimated. Poor adherence was also a key concern for Turk and colleagues, who developed
and trialled a personal health profile (PHP) for adults with ID in London, UK (Turk et
al., 2010). The PHP aimed to improve health knowledge in the individual with ID, their
carers and health professionals, and could be updated by anyone involved in the
individual's care. Despite more than 90% of adults with ID and their carers expressing
satisfaction in having the PHP and 87% saying it helped them know more about their health
or the health of the person they cared for, in exit interviews only 66% of adults with ID
and 55% of carers reported actually using the profile. Furthermore, when adults with ID or
their carers were asked whether they had a particular condition, there was no difference
in valid responses between the PHP group and controls during the follow-up assessments.
This indicated that the PHP did not lead to significant increases in personal or general
health knowledge, in either adults with ID or their carers. The profile did not lead to
significant increases in attendance at GP or other healthcare services. Taken together,
these three studies provide little support for the use of carer-completed health records
as a means of improving communication with health professionals or short-term health
outcomes for people with ID.

        <hss>Parent-led interventions for managing childhood overweight and obesity</hss>

        In a pilot RCT involving 50 families, Moens and Braet (2012) found that a
        combination of healthy lifestyle, behaviour change and parenting training for
        parents of overweight children led to significant reductions in their child's BMI.
        The BMI in a wait-list control group (WLC) did not change significantly.
        Comparisons with a reference group, composed of children whose parents had chosen
        not to take part in the main study, found that members of the reference group were
        no different to the intervention group in terms of the child's gender, age or BMI
        at baseline, but showed significant increases in BMI 12 months later. While
        showing that developing a variety of skills in parents can lead to positive health
        outcomes for their children, this research did not consider how the different
        components of the intervention might have impacted on BMI reduction. Two earlier
        RCTs were more comprehensive: Golley, Magarey, Baur, Steinbeck, and Daniels (2007)
        randomised the parents of 111 overweight pre-pubertal children to parenting skills
        plus lifestyle education (PS + LE), parenting skills (PS) alone, or WLC.
        Participants in the PS + LE and PS groups both showed significant reductions in
        BMI Z-score and waist circumference over the 12-month study period, whereas those
        in the WLC showed a smaller reduction in BMI, and no significant change in waist
        circumference. Magarey et al. (2011) composed their groups in the converse
        fashion: parenting skills training was combined with healthy lifestyle training (N
        = 85) and compared to lifestyle training alone (N = 84). Participants achieved an
        average 10% weight loss in both groups, indicating no additional benefit from
        combining the healthy lifestyle training with parenting skills. A further RCT from
        Golley, Magarey, and Daniels (2011) on overweight pre-pubertal children, used the
        same three conditions (PS, PS + LE and 12-month WLC) with the child's food intake
        and activity levels reported by parent completed questionnaires as the outcome
        measures. Mean daily consumption of ‘extra’ food (defined as energy-dense,
        nutrient-poor foods) significantly reduced in both intervention groups, with
        reductions being maintained for up to 6 months. Food intake was unchanged in the
        WLC group and there were no significant differences between the groups in terms of
        activity levels, at any stage of the study. Resnick et al. (2009) randomly
        assigned 46 parents to a health education intervention, delivered through the
        post, or via contact with a health worker. Intervention materials included a
        cookbook, physical activity book, pedometer and information about making healthy
        eating and activity choices. Although parent-report measures showed no significant
        increase in parental knowledge after the intervention, their children's BMI
        percentile reduced by an average of 5 points over the 41-week period. No
        significant difference in BMI percentiles was seen between the groups, indicating
        that the materials had a similar effect whether read alone by the parents or
        delivered by a health worker. A non-randomised contemporaneous control group was
        found to have no change in BMI during the same period. Small and colleagues
        conducted a pilot study of an educational intervention for 45 mothers of 4–6 year
        old children (Small et al., 2012) and found that their educational intervention,
        consisting of nutritional information and practical serving tips, also failed to
        increase parental nutrition knowledge, but did lead to reductions in the average
        amount of calories served to, and consumed by, the children. These combined
        results show that targeting parents can lead to improvements in health promotion
        and healthier lifestyles in their children. Parenting or healthy lifestyle skills
        training may lead to reductions in children's food consumption and BMI and can be
        achieved by providing parents with appropriate educational materials, even when
        these materials do not appear to be improving the parents’ knowledge. However, in
        the current studies such improvements have been small and the mechanisms behind
        such health improvements, in the absence of a clear impact on parental knowledge,
        remain unexplored.

        <hss>Parent-led interventions to improve feeding problems</hss>

        A pilot study by Dovey and Martin (2012) targeted problem feeding in 17 children
        whose problems resulted from sensory defensiveness. Following a 6-month, parent-
        led, contingent reward desensitisation intervention, which included children
        receiving reward tokens after trying problem foods, the children's population-
        corrected height and weight had increased significantly, although BMI changes did
        not reach significance. A previous RCT of 156 parents of 2–6 year old healthy
        children by Wardle et al. (2003) had found that children whose parents were taught
        to lead a 14-day, graduated food exposure programme showed greater increases in
        liking, ranking and consumption of target vegetables than children whose parents
        only received nutritional advice or WLC. In the exposure group, these increases
        were all significant. The control group showed small, but significant increases in
        liking and ranking of the target food, but decreased their consumption, whereas
        those whose parents had only received nutritional advice showed no significant
        increases in any of the measures. These results suggest that parent-led graduated
        exposure techniques can be successfully used to increase their children's
        consumption of healthy foods.

        <hss>Parent-led drug and alcohol education interventions</hss>

        Beatty, Cross, and Shaw (2008) assessed their parent-focused, tobacco and alcohol
        education intervention using a school group randomisation procedure. 1201 parents
        of 10–11 year old children were randomised to the intervention that consisted of
        five sets of learn-at-home drug education materials and activities, or to the
        control group. Post-intervention questionnaires revealed that intervention group
        parents were more likely to have recently spoken to their child about the hazards
        of tobacco and alcohol, covering more of the essential topics outlined in the
        educational materials and to have reported higher levels of engagement when
        talking with their child, than control parents. However, no behavioural outcome
        measures were included, thus the relationship between improved communication and
        the children's alcohol or tobacco use remains unclear. Jackson and Dickinson
        (2011) randomised 1183 non-smoking parents to either an anti-smoking parenting
        programme or a control group who received basic factsheets. Their original
        unpublished results found no significant group differences in smoking-specific
        outcomes in the children. Additional analyses reported in the current paper,
        however, revealed a dose–response pattern: greater parental engagement with the
        materials led to their children recalling more of the 14 behaviours targeted by
        the programme, and experiencing fewer pro-smoking risk factors (such as perceiving
        easy access to cigarettes, or feeling that there would be no negative consequences
        if their parents found them smoking) when interviewed both six months and three
        years following the initial intervention. This increased awareness of anti-smoking
        advice and pro-smoking risk factors were not, however, sufficient to change
        smoking behaviour: the children's likelihood to start smoking three years later
        showed no association with the amount their parents engaged with the study
        materials. Parent-led educational interventions appear to be a potentially
        effective way of improving parent–child communication and increasing children's
        knowledge of substance-use associated risk, but in the studies described, such
        improvements did not lead to positive changes in behaviours.

        <hss>Spouse-assisted lifestyle change interventions</hss>

        Voils et al. (2013) conducted an RCT comparing a telephone-delivered spouse-
        assisted lifestyle change intervention, with treatment as usual, for 255 adult
        patients with high cholesterol. Their intervention included information about
        hypercholesterolemia and joint goal setting to improve the healthiness of their
        lifestyle. Cholesterol levels did not change post-intervention, however patients
        in the intervention group had significantly lower self-reported caloric intake
        than those in the control group. The intervention group also reported 10% longer,
        and 20% more frequent, physical activity sessions than the controls.

<hs>  Carer-led symptom monitoring and management</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Porter and colleagues’ RCT (Porter et al., 2011) compared caregiver-assisted Coping Skills
Training (CST) to an educational control, for patients with early stage lung cancer and
their carers. Caregiver-assisted CST involved 14 telephone sessions, over 8-months, which
taught caregivers how to help patients acquire and maintain coping skills over the illness
trajectory. The control condition provided patients and caregivers with information about
lung cancer and treatment options. Significant improvements in ratings of worst pain,
physical and functional well-being, lung cancer symptoms, depression and self-efficacy
were seen in the patients in both groups, with no significant differences between them.
Thus in this study, caregiver-assisted CST was no more beneficial than providing patients
and their carers with helpful information. Keefe et al. (1996, 1999) conducted a three-arm
RCT with patients with osteoarthritis of the knee, comparing spouse-assisted CST with
conventional CST with no spousal involvement and also with a control group receiving a
spousal support arthritis education package). At the end of the 10-week study period,
patients in the spouse-assisted CST condition had significantly lower levels of pain,
psychological disability, and pain behaviour, and higher scores on measures of coping
attempts, marital adjustment, and self-efficacy, than controls. There were no significant
post-intervention differences between those receiving spouse-assisted CST and conventional
CST (Keefe et al., 1996) and after 12 months, patients in both CST groups had had lower
levels of physical disability and higher levels of self-efficacy than the controls (Keefe
et al., 1999). Abbasi et al. (2012) compared a spouse-assisted multi-disciplinary pain
management programme (SA-MPMP), consisting of seven weekly two-hour group sessions
covering dyadic pain coping and couple skills, with a conventional patient-oriented pain
management programme (MPMP) and standard medical care (SMC), for 36 patients with chronic
lower back pain. All groups showed significant improvements in disability scores post-
intervention, however at the 12 month follow-up, while both intervention groups’ scores
remained lower than baseline levels, those who received SMC had higher levels of
disability than at the start of the study. Taken together, these studies suggest that
including carers in health monitoring and symptom management in long-term physical health
conditions offers little benefit over and above that obtained through existing
interventions or educational packages.

<hs>  Carer-led interventions for mental health</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Quayhagen and Quayhagen (2001) reported on two RCTs assessing 12 and 8 week versions of
their caregiver-led cognitive stimulation intervention (CSI) for people with dementia.
This involved hour-long sessions five times a week, focussing on memory, problem solving
and communication skills. Controls included placebo (watching TV with a carer) and WLC.
The first study (N = 56) showed improvements in immediate memory following the 12-week
intervention, whereas the second (N = 30) found improved problem-solving after 8 weeks of
CSI. In both studies, CSI groups also showed improved verbal fluency, whereas performance
across all measures declined in both control groups. An RCT of 156 dementia patients
currently receiving the dementia medication Donepezil compared the effects of a carer-led
reality orientation programme, with treatment as usual (Onder et al., 2005). The programme
involved three 30-minute sessions per week, during which the caregiver directed attention
to the current date, time and location. This was followed by discussing topics such as
historical events, and exercises designed to target attention, memory and visuospatial
skills. Following the 25-week intervention period, significant group differences were seen
in the patients’ cognitive functioning. Mini mental state examination (MMSE) scores and
scores in the cognition subscale of the Alzheimer's disease Assessment Scale (ADAS-Cog)
showed slight improvements in patients receiving the programme, compared to substantial
decline in those receiving care as usual. Although such improvements were small, the
authors argue that a difference in just one point in the MMSE is enough to substantially
change the cost of caring for that patient. There were no significant differences in
caregiver burden, anxiety, or depression after the study (Onder et al., 2005) and a recent
feasibility study by Milders, Bell, Lorimer, MacEwan, and McBain (2013) reported that
delivering a cognitive stimulation intervention was beneficial not only to the dementia
patient, but to carers as well. Finally, a small single group pilot study assessed a
parent-led cognitive behavioural therapy (CBT) programme for 26 young children with
anxiety disorder (van der Sluis, van der Bruggen, Brechman-Toussaint, Thissen, & Bögels,
2012). This small single group pilot study found that parent-led CBT decreased both
parent- and teacher-reported measures of child anxiety and behavioural inhibition, and
increased mothers’ use of positive parenting methods. This group of studies suggests that
carers are capable of delivering psychological interventions that lead to significant
mental health improvements in those that they care for.

<hs>  Screening delivered by carers</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A two-part study by Paysse, Camejo, Hussein, and Coats (2004) assessed parents’
reliability when delivering visual acuity testing to their children. In the initial stage,
parents used an electronic visual acuity tester (EVA) to assess the visual acuity of their
child (N = 64), with reliability assessed by comparison with an ophthalmic technician's
results. In the second stage, 44 children were randomly assigned to either group ‘A’ who
had their parents assess their visual acuity prior to the technician confirming the
result, or group ‘B’ in which visual acuity was assessed using the full protocol by the
technician. The researchers found that parents could not only reliably assess their
child's visual acuity using the EVA, but that by doing so, the amount of time required
with a qualified health professional was significantly reduced. This study provides a
positive example of carers reliably performing an essential part of an eye exam, which
could set a precedent for including carers in other health check situations.

<hs>  Summary of findings</hs>
  ~~~~~~~~~~~~~~~~~~~

This review summarises the findings from a broad range of carer-led health interventions.
Our initial aim was to identify successful intervention models that involved carers in
screening, monitoring, or promoting health in adults with ID. However, with such a paucity
of research in this field, more general examples were also sought. In non-ID populations,
we found examples of carer-led interventions for health promotion, symptom monitoring and
management, mental health and health screening procedures. Such diverse interventions and
findings make generalisation difficult, however these studies do allow an insight into
some aspects of carer-led interventions that do, and do not, seem to have a positive
impact on health outcomes for the person being cared for. Such details may prove helpful
for developing future carer-led interventions for people with ID and will be explored in
more depth. Of the three papers involving participants with ID, all assessed health
outcomes following the use of a health diary or profile completed by carers. Despite such
records being apparently well received by people with ID, their carers and health
professionals, they were not used by a significant minority of those they were designed
for and none of the studies found quantifiable improvements in health outcomes following
their use (Lennox et al., 2008, 2010; Turk et al., 2010). With such poor adherence to
these interventions, it is unclear whether this type of intervention is ineffective, or
whether the reported lack of improvement in communication and health related outcomes
reflects the fact that too few in the intervention groups engaged with the materials.
Authors for all three papers also noted that health outcomes from such interventions may
take much longer to come to light than the timescale of these studies allowed (Lennox et
al., 2008, 2010; Turk et al., 2010). In terms of health promotion, a series of studies
found that developing parenting and/or healthy lifestyle skills could lead to reductions
in both BMI and the consumption of unhealthy foods in children (Golley et al., 2007, 2011;
Magarey et al., 2011; Resnick et al., 2009). In two studies where parental knowledge of
nutrition and health were assessed before and after the intervention, there appeared to be
no significant improvement in what they knew (Resnick et al., 2009; Small et al., 2012).
Nevertheless, in both studies, positive health outcomes were recorded in their children.
One could therefore conclude that some other aspect of the interventions was leading to
behavioural change. These findings link well with those of Davison, Jurkowski, Li, Kranz,
and Lawson (2013). Their paper reported on the process of including parents as equal
collaborators in the development and evaluation of a family-led childhood obesity
intervention and they explored factors impacting on the families’ health from their
perspective. In analysing their intervention, nutritional knowledge was not felt to be an
important factor; rather the parents felt that they needed improved skills in social
networking, advocacy, communication skills and conflict resolution. It was a lack of these
skills rather than a lack of knowledge that they felt prevented them from providing a
healthy lifestyle for their children. When considering the mechanisms that could lead to
improvements in patient outcomes following carer interventions, it may therefore be that a
focus on skills, rather than knowledge acquisition, is key. Further evidence that
improving knowledge is ineffective at modifying behaviour comes from a study assessing a
parent-led tobacco education programme (Jackson & Dickinson, 2011). Variation in
engagement with the study materials predicted children's knowledge, such that the children
whose parents engaged most with the materials, had the highest knowledge of smoking risks
and the lowest experience of particular risk factors. However, increased engagement with
the programme had no impact on the child's likelihood to have started smoking three years
later. In terms of symptom monitoring and management, none of the studies included found
that carer-led interventions were any more effective than existing interventions (Keefe et
al., 1996, 1999; Porter et al., 2011; Voils et al., 2013). However, one argument for
including carers in the healthcare of those they support is that it may help them to use
health resources more appropriately. Although these studies suggest that using carers
offers no additional benefit to the interventions that already exist, the results
indicated that they were no worse. As such, training carers to deliver interventions may
be a cost-effective way of ensuring that patients (such as those with severe ID) get the
care they need. We also found one promising example of health screening. Parents of
children awaiting an optician's appointment were found to be capable of accurately and
reliably assessing their child's visual acuity (Paysse et al., 2004). This is a positive
example of carer input successfully reducing the need for clinician time, without
negatively impacting on the reliability of the procedure. When considering the inclusion
of carers in the health check process for people with ID, examples such as these may work
as a precedent, highlighting the ability of carers to perform basic health screens,
potentially increasing the effectiveness of interventions and health services. For
patients with dementia, we found that carers were not only capable of delivering
interventions that led to positive improvements in the patient's cognitive functioning
(Onder et al., 2005; Quayhagen & Quayhagen, 2001), but that delivering such interventions
did not increase caregiver burden or anxiety (Onder et al., 2005) and in many cases, was
felt to be beneficial to the carer as well (Milders et al., 2013).

<hs>  Limitations of existing research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Several studies reported here were small scale, with short follow-up periods and varying
levels of quality in their study control. Future studies need to be fully powered to test
efficacy. As already noted, poor adherence to, or engagement with, interventions was a
relatively commonly reported issue in these studies (Jackson & Dickinson, 2011; Lennox et
al., 2010; Turk et al., 2010). Such variability in engagement with an intervention will
inevitably impact on the results. Developing interventions in collaboration with carers
may be one way of ensuring that the interventions are acceptable to those delivering them,
and in turn, improve engagement (Davison et al., 2013). A further limitation highlighted
by Turk et al. (2010) was the high turnover of carers experienced by adults with ID in
their study. The authors argued that this in itself highlighted a need for a patient-held
health record, to ensure that necessary information was readily available, regardless of
how well care staff knew the individual in question (Turk et al., 2010). In many of the
examples we found from outside the field of ID, the carer in question was either a parent
or spouse. While this may too be the case for some people with ID, others will rely on
paid or voluntary care staff. The studies presented here have provided good support for
being able to train carers to deliver health interventions, but in contexts where care
staff may change frequently the acceptability of the intervention from carers’ and
patients’ points of view, and time and financial costs involved in training new staff when
required, would need to be incorporated into the research programme. Participant attrition
was a significant problem for many of the studies. The centre for evidence-based medicine
argues that retention of less than 80% in a study reduces the quality of the study (Howick
et al., 2011). Where it was investigated, for example by Jackson and Dickinson (2011) on
their anti-smoking programme, differential attrition occurred, such that those who dropped
out were more likely to be from the BME community, and to have high school education or
lower, than those who chose to continue. Identifying factors involved in participants
discontinuing with a study is important as such factors would need to be addressed and
improved in order to make the intervention generalisable if successful. A final limitation
is that none of the studies included a cost analysis of the interventions presented. Using
carers to deliver health interventions could save clinician time, and therefore money
(Paysse et al., 2004). However, the cost effectiveness of such interventions will depend
on the cost of training carers, and ensuring that they maintain reliability and accuracy
in the intervention. In a context of frequently changing care staff, such costs could
accumulate more quickly than in contexts where carers are more consistent.

<hs>  Strengths and limitations of this review</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As far as the authors are aware, this is the first review to consider carer-led health
interventions as a means of improving the health of the people they care for, including
those with intellectual disabilities. Our intention was to focus on adults with ID,
however a lack of existing research led to the inclusion of carer-led health interventions
from a variety of patient populations, with different medical conditions, of differing age
groups and in different settings. Such variation in the samples, the interventions
themselves, and the outcome measures used to assess their efficacy, meant that a
quantitative review of carer-led interventions was not possible. As such, over-arching
conclusions concerning the efficacy of carer-led health interventions as a means of
improving health are difficult to make. Our research was time-limited, thus rapid review
methodology was used. To reduce search time, we used just one database (Scopus), which may
have resulted in missing some papers. This review also excluded studies that were not in
English, and did not include interventions published in the grey literature. It is likely
that other carer-led interventions exist, and are in use, but have yet to be evaluated.
Nevertheless, several successful models have been presented, and barriers to research,
such as high carer turnover and a lack of engagement with the interventions have been
identified. This review may therefore help future development of carer-led health
interventions in general, not just in the ID population.

<hs>  Directions for future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

With such a broad range of studies presented here, future research needs to aim to define
the elements of carer-led interventions that are most likely to make a positive impact on
a person's health. We need to establish how best to involve carers to ensure that high
quality interventions are delivered, and that the interventions are acceptable to both
those who are delivering, and those who are receiving them. Identifying factors that would
improve participant adherence and engagement with any given intervention is essential for
improving the quality of future interventions. Including carers and the people they care
for in the planning and development stages may be one way of producing interventions that
are better adhered to. Most crucially, it is essential that future interventions have a
positive impact on health outcomes in the target population. Future studies must include
sufficiently long follow up periods, to assess longer-term impacts, and health outcomes
should be presented in ways that allow the reader to assess their impact in terms of
noticeable changes for the patients, in addition to statistically significant results.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

Carers have successfully delivered healthcare interventions, including screening,
monitoring and health promotion, in a range of health settings. Nevertheless, for people
with ID, there remains a lack of research in this area. With such varied interventions and
outcomes found in the studies described in this review, it is hard to draw clear
conclusions as how best to use carers to impact positively on the health of the person
they care for in the ID community. In addition, engagement with the intervention appeared
to be a common issue. Involving carers and the people they care for in the research
process may lead to better adherence to, and engagement with, carer-led interventions and
should be an integral part of future research.

<h>CONFLICT OF INTEREST</h>
--------------------

The authors declare that there are no conflicts of interest.

<h>FUNDING</h>
-------

This article presents independent research funded by the National Institute for Health
Research (NIHR) under its Programme Development Grants programme (Reference Number RP-
DG-0611-10003). The views expressed are those of the authors and not necessarily those of
the NHS, the NIHR or the Department of Health.


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<ART>Causal knowledge and the development of inductive reasoning
===========================================================

Authors: Aimée K. Bright, Aidan Feeney
DOI: 10.1016/j.jecp.2013.11.015
Year: 2014  |  Pages: 48-61
ASJC codes: 3204, 3205
Keywords: Category-based induction, Causal asymmetry, Causal knowledge, Inductive selectivity, Knowledge over-generalization, Taxonomic knowledge

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey. →. predator) or diagnostic (predator. →. prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. © 2013 Elsevier Inc.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Children make category-based inductions when they infer properties and features in novel
categories based on what they know to be true about familiar related categories (for
reviews, see chapters in Feeney & Heit, 2007, and Hayes, Heit, & Swendson, 2010). Many
different types of relations between categories can support such inferences. For example,
the fact that tigers have a property or that antelopes have a property may be equally good
evidence that lions have the property. The first inference might be strong because lions
and tigers are taxonomically related, whereas the second may be strong because lions eat
antelopes and this food chain relation provides a plausible causal mechanism for property
transmission. This example is consistent with claims based on structured Bayesian
approaches to inductive reasoning (see Kemp & Tenenbaum, 2009) that our knowledge about
the relations that hold between categories of objects can be structured in a variety of
ways. One of our aims in this study was to examine whether causal or taxonomic relations
are more privileged in young children’s category-based inductive reasoning. It was unclear
which knowledge structure might serve as the default because some researchers suggest that
taxonomic reasoning is a default strategy (e.g., Kemp & Tenenbaum, 2009; Shafto & Coley,
2003), whereas others emphasize the primacy of causal knowledge (e.g., Rehder, 2006;
Rehder, 2009). Because they are inductive, category-based inferences are probabilistic,
but they effectively reduce uncertainty about the world. Understanding the constraints
placed on inductive inferences by the underlying structure of different knowledge sources
is crucial if we want to understand the processes that allow inductive inferences to be
flexible yet effective. Several recent studies (Kemp & Tenenbaum, 2009; Shafto, Kemp,
Bonawitz, Coley, & Tenenbaum, 2008) show that adults’ inferences are especially sensitive
to knowledge about how causal relations are structured. However, little is known about
whether children and adults use causal knowledge in similar ways to support their
inductive inferences. Our second aim of this study was to examine whether, like adults
(see Rehder, 2009; Shafto, Coley, & Baldwin, 2007; Shafto, Coley, & Vitkin, 2007; Shafto
et al., 2008), children are sensitive to the direction of the causal relation that holds
between categories. Thus, in addition to examining when children’s inductive inference
becomes sensitive to causal relations, we examined how sophisticated children are in their
use of such knowledge for reasoning.

<hs>  Causal knowledge in inductive reasoning</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The effects of causal knowledge on reasoning are not very well captured by older models of
category-based induction that emphasize featural similarity (Sloman, 1993) and/or class
membership (Osherson, Smith, Wilkie, Lopez, & Shafir, 1990). Such similarity-based models
are powerful at accounting for patterns of inductive reasoning about taxonomic properties
(i.e., properties such as genes whose distribution in the population may depend on
taxonomic relations) and about blank properties (i.e., properties that participants
possess no knowledge about). However, they fail to capture induction across a broader
variety of properties and in expert populations (see Medin, Coley, Storms, & Hayes, 2003;
Rehder & Hastie, 2001; Shafto & Coley, 2003), especially when there is a causal
explanation for the occurrence of shared properties (Rehder, 2006). Causal knowledge plays
a vital role in cognition from infancy onward (Sobel & Kirkham, 2007). The ability to
understand causal structures provides children with tools that help them to successfully
predict future events and understand the outcome of active intervention, allowing them to
gain increasing control over their environment (Gopnik et al., 2004). By 4 years of age,
children are capable of understanding simple causal mechanisms across the domains of
biology (Wellman, Hickling, & Schult, 1997) and psychology (Flavell, Green, & Flavell,
1995) as well as causal explanations in social and physical domains (Hickling & Wellman,
2001). Similarly, children use causal knowledge to classify objects (Ahn, Gelman,
Amsterlaw, Hohenstein, & Kalish, 2000) and natural kinds (Meunier & Cordier, 2009). The
fact that children make use of causal information across diverse domains and tasks
underscores its potential importance in children’s category-based reasoning. Indeed,
evidence suggests that children can use causal knowledge when making inductive inferences.
For example, Hayes and Thompson (2007) taught children (5- and 8-year-olds) and adults
about features of two artificial base creatures, followed by a target that was more
similar to one base but shared a causal antecedent with the other base. Results indicated
that when the causal link was explicit, all age groups preferred to make causal rather
than similarity-based inductions. That is, they preferred to project a property to the
target from the causally related base creature than from the more similar base creature.
When the causal relation was implicit, 5-year-olds did not yet show a preference for
choosing the causally related items, unlike the older children and adults who made
predominantly causal choices. Similarly, Opfer and Bulloch (2007) demonstrated that
5-year-olds were capable of ignoring perceptual similarity in favor of relational
similarity when the latter had a causal antecedent but not when it was non-causal. Both of
these studies suggest that children’s category-based inductive reasoning may be affected
by knowledge about causal relations, although they do not allow us to conclude that causal
knowledge structures are the default. Moreover, such studies do not address the extent to
which children’s inductive reasoning is sensitive to the underlying structure of causal
knowledge (e.g. Pearl, 2000; Sloman, 2005). Consequently, we cannot know whether
children’s use of causal knowledge in induction is mediated by the same underlying
processes as in adults.

<hs>  Structure of causal knowledge: Causal asymmetry effects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

An important feature of causal knowledge is that it is directional, with causes always
preceding or at least co-occurring with their effects (Waldmann, 2000). There is evidence
that adults take such structural features into account because their causal reasoning
tends to display distinctive asymmetry effects (Fenker, Waldmann, & Holyoak, 2005;
Fernbach, Darlow, & Sloman, 2011; Sloman, 2005). Reasoning in line with how we experience
cause–effect relations (predictive causal reasoning) appears to be less effortful than
reasoning backward (diagnostic causal reasoning), suggesting that computational complexity
is a key determinant of the causal asymmetry effect (Kahneman & Tversky, 1973). For
example, when people are asked to verify whether two words are causally related, they
respond faster when the words are presented in a predictive order compared with a
diagnostic order (Fenker et al., 2005). Causal direction also affects inductive
inferences. Thus, people find category-based inductive arguments more convincing when
reasoning in a predictive direction from cause to effect than when reasoning
diagnostically from effect to cause (Medin et al., 2003; Shafto et al., 2008). To
illustrate, people are more confident in the conclusion that bees have an unknown property
given that it is present in the premise category flowers than when the roles of the two
categories are reversed. People’s judgments appear to accord well with the causal
asymmetry effects that are predicted by formal models of causal-based property
generalization (Rehder, 2009; Shafto et al., 2008), although there are arguments that,
relative to a normative standard, people have too much confidence in arguments with a
predictive structure (Fernbach et al., 2011). Despite the convincing evidence that the
causal asymmetry effect is a robust phenomenon in adults’ category-based reasoning, and
evidence that children’s predictive reasoning about novel mechanical systems is better
than their diagnostic reasoning (see Bindra, Clarke, & Shultz, 1980; Hong, Chijun, Xuemei,
Shan, & Chongde, 2005), it is unknown whether children display similar asymmetry effects
when they use causal knowledge to support their inductive inferences. Our study was
designed to answer this question.

<hs>  Context-sensitive reasoning</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although it is clear that causal knowledge is important in induction, adults are adept at
tailoring their inferences to the particular reasoning context. Consider the example with
which we opened this article. If we ask a participant to decide whether lions have a
certain gene on the basis that tigers have that gene, then the taxonomic relation that
holds between lions and tigers is relevant. On the other hand, if we ask whether lions
have a disease on the basis that antelopes have that disease, then the causal mechanism
for disease transmission from antelope to lions via predation is relevant. There is much
evidence that adults, and sometimes children, can show inductive selectivity by selecting
the appropriate knowledge with which to evaluate category-based inductive arguments. For
example, Heit and Rubinstein (1994) showed that people make stronger inferences about
shared properties when the nature of the property is in accord with the nature of the
relationship between two categories. According to Shafto, Coley, and Baldwin (2007);
Shafto, Coley, and Vitkin (2007), changes in context affect the acute availability of
different knowledge structures. Thus, when reasoning about properties such as diseases,
people are more inclined to use knowledge about causal or ecological relations, whereas
taxonomic knowledge tends to be invoked when reasoning about anatomical properties. There
is some evidence that children are also sensitive to the nature of the property that they
are reasoning about (for a full review, see Hayes, 2006). Nguyen and Murphy (2003), for
example, showed that by 7 years of age, children reason taxonomically about biochemical
features but use thematic relations to guide inferences about situational properties.
However, in their study younger children’s use of different relations was heavily
influenced by task format, making it difficult to evaluate the degree to which these
children were using different knowledge structures in a systematic manner. Coley (2012)
demonstrated that there are environmental influences on the age by which children show
inductive selectivity; by 10 years of age, children raised in urban environments
selectively project disease properties between categories that are ecologically related
and so suggest a causal mechanism for disease transmission, whereas rural children show
the same pattern as early as 6 years of age. In an open-ended category generation task,
Vitkin, Coley, and Hu (2005) also showed that children’s inferences are constrained by the
nature of the property that they are asked to reason about. Thus, when told that the two
categories share “stuff inside,” children generated categories based on similarity,
whereas they gave interaction-based responses when reasoning about shared diseases. In
this study we manipulated the nature of the property that participants were asked to
reason about. Although we expected adults to show property effects, our aim in this study
was not to assess the age by which children demonstrate inductive selectivity because any
answer to this question will depend on the paradigm employed. Indeed, inductive
selectivity effects have been demonstrated in young children (Heyman & Gelman, 2000a;
Heyman & Gelman, 2000b) and even infants (see Mandler & McDonough, 1998; Rakison & Hahn,
2004). Instead, we wanted to examine, in the domain of folk biology, how children reason
before selectivity emerges and whether a particular knowledge structure is more important.
On the basis of the literature, it is very difficult to answer questions about default
knowledge structures. There appears to be reason for assuming that taxonomic knowledge
structures are the default; for example, using a speeded response paradigm, Shafto and
colleagues (2007) showed that access to knowledge about causal mechanisms for disease
transmission due to ecological relations between categories is restricted when adults are
asked to respond quickly, whereas taxonomic knowledge seems unaffected by response time
manipulations. This finding, that taxonomic knowledge is primary, is consistent with
suggestions that taxonomic knowledge structures are the default (Kemp & Tenenbaum, 2009).
However, there is also reason to believe that taxonomic knowledge structures are not the
default; Rehder (2006), Rehder (2009) emphasized the primacy of causal knowledge over
taxonomic knowledge, and there is evidence that young children prefer to use thematic
knowledge rather than taxonomic knowledge when reasoning about categories (see Greenfield
& Scott, 1986; Nguyen & Murphy, 2003; Smiley & Brown, 1979). Because the developmental
literature is divided on the question of how young children reason inductively, there are
also important theoretical questions about the development of inductive reasoning to which
questions of default knowledge are relevant. Sloutsky (2010) theorized that inductive
selectivity depends on a maturationally late learning system. Sloutsky suggested that,
prior to the emergence of inductive selectivity, children rely on knowledge acquired
through a simple learning system that exploits co-occurrences and similarity. He cited
evidence that before 7 years of age children rely largely on such similarity between base
and target category to guide their inferences (Fisher & Sloutsky, 2005; Rakison & Lupyan,
2008; Sloutsky & Fisher, 2004). This would suggest that prior to the emergence of
inductive selectivity, children ought to rely heavily on superficial similarity or
category membership rather than on causal knowledge. However, there is evidence that even
children as young as 5 years can ignore featural similarity when explicit causal knowledge
is available (Hayes & Thompson, 2007; Opfer & Bulloch, 2007). Here we examined whether
children as young as 5 years prefer to reason on the basis of taxonomic or causal
relations. This group was younger than the youngest participants that Coley (2012) found
to display inductive selectivity. The contradictory findings in the literature made it
hard to predict whether these children will prefer arguments with taxonomic or causal
relations and whether they will be sensitive to causal structure. If young children’s
inductive inferences are dominated by taxonomic relations, then we would except to see few
effects of causal knowledge. If, on the other hand, causal knowledge dominates early in
reasoning development, then the question arises as to whether young children will exhibit
causal asymmetry effects.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

In total, 44 Year 1 primary school children (Mage = 5.4 years), 40 Year 4 primary school
children (Mage = 8.4 years), 54 Year 8 secondary school children (Mage = 12.6 years), and
a control group of 26 adults from Durham University (Mage = 24.6 years) in the United
Kingdom took part in the experiment. Year 1 and Year 4 students were recruited from a
suburban state primary school in the North East of England. Year 8 students were recruited
from a suburban state secondary school in the same geographical area. There were
approximately equal numbers of male and female participants in the various age groups.

<hs>  Design</hs>
  ~~~~~~

The experiment had a 4 (Age Group: 5-year-olds, 8-year-olds, 12-year-olds, or adults) × 2
(Property: disease or cells) × 2 (Direction: predictive or diagnostic) × 2 (List: A or B)
mixed design, with repeated measures on the direction variable only.

<hs>  Materials</hs>
  ~~~~~~~~~

Participants reasoned about 12 trials, each consisting of a triad of categories: a base
and two targets. On each trial, participants were presented with a base category, were
told that it possessed a feature, and were asked which of the target categories they
thought was most likely to share that feature. One of the targets was causally related to
the base in the form of a food chain relation. This causally related target category
always belonged to a different superordinate category from the base. The other target
category was taxonomically related to the base category and was from the same
superordinate category as the base. In the predictive condition, the causal direction was
ecologically consistent. For example, the base category might be a banana and the causally
related target might be a monkey. In the diagnostic version of this example, the
directionality of the causal link was reversed so that the monkey served as the base and
the banana served as the target. To ensure that children understood the causal mechanisms
by which two categories might be connected, the nature of the causal relationship was
limited to transparent food chains. An example with pictures, all of which were selected
from Rossion and Pourtois (2004) database, is shown in Fig. 1. The direction of the causal
link was counterbalanced across items. For List A, the causal direction was predictive for
Items 1 to 6 and was diagnostic for Items 7 to 12; for List B, the opposite was the case.
Thus, although direction was a within-participants factor, participants never saw any of
the causal pairs twice. The task was self-paced and run on a laptop using purpose-built
software. So that the causally related pairs could be presented in either a predictive
direction (e.g., carrot → horse) or a diagnostic direction (e.g., horse → carrot),
different categories served as the base (e.g., carrot or horse). Because the taxonomically
related target category belonged to the same superordinate category as the base category,
this meant that the taxonomically related target category was different on diagnostic and
predictive trials. Thus, it was crucial to equate the similarity between the base instance
and the taxonomic alternative targets across predictive conditions (e.g., carrot → onion)
and diagnostic conditions (e.g., horse → sheep). A group of 18 Durham University students
rated the similarity on a scale from 1 (not at all similar) to 9 (highly similar) between
pairs of categories presented verbally in a pretest. Only triads in which the similarity
ratings were approximately equal across both conditions were selected (all paired-sample t
tests had ps > .05), resulting in 12 triads. Mean similarity ratings by triad are
presented in Appendix Table A1). Although we did not collect similarity ratings from
children, there is evidence that children and adults perceive similarity relations in
similar ways. For example, using materials pretested for similarity with adults by
Osherson and colleagues (1990), López, Gelman, Gutheil, and Smith (1992) showed effects of
similarity on reasoning in 5-year-olds that were identical to the similarity effects
originally found in adults by Osherson and colleagues. The strength of the causal relation
between the base and target categories was examined in a separate pretest on 19 Durham
University students who rated the extent to which properties might be transmitted between
the base and both target categories in each triad on a scale from 1 (not at all) to 9 (a
great deal). In all cases, ratings were stronger for causally related categories than for
taxonomically related categories. These differences were statistically significant (p <
.05) in 9 of 12 cases and were marginally significant in the remaining 3 cases (see
Appendix Table A2 for ratings).

<hs>  Procedure</hs>
  ~~~~~~~~~

Parents received written information about the study with an opt-out form in case they did
not want their children to take part. Children gave their assent at the beginning of the
session. Participants were randomly allocated to either the cell or disease condition. The
task was explained verbally, and written instructions were presented on-screen.
Participants completed 2 practice trials before commencing the main task. They saw a base
picture at the top of the screen and were told that the animal, plant, or object had an
unfamiliar disease or special cells (e.g., “This horse has a disease called talio/has
talio cells inside”). A different artificial cell or disease name was used for each trial.
The base picture was followed by two arrows pointing to two target pictures. Participants
decided which of the two pictures was more likely to share the disease or special cells
with the base category. The location of the causally and taxonomically related targets on
the screen was randomized. Participants pressed 1 if they thought that the left-hand
picture was more likely to share the property and pressed 9 if they chose the right-hand
picture.

<h>RESULTS</h>
-------

For each individual, the proportion of causally related targets that were chosen was
calculated for the six predictive and six diagnostic triad items. These were analyzed
using a 2 (Direction) × 4 (Age Group) × 2 (Property) × 2 (List) mixed-design analysis of
variance (ANOVA) with direction as the only within-participants variable. For the item
analysis, proportions of causal choices were averaged across items rather than
participants. All effects involving the counterbalancing list variable were nonsignificant
(all ps > .10), so there is no further reference to this variable. As predicted, there was
a main effect of direction, Fs(1, 146) = 20.8, p < .0005, effect size f = .38, Fi(1, 11) =
21.4, p = .001, and a significant main effect of age group, Fs(1, 146) = 6.5, p < .0005,
effect size f = .37, Fi(1.9, 21.3) = 22.56 (Greenhouse–Geisser adjustment for non-
sphericity), p < .0005. Participants made significantly more causal inferences when the
link between the causally related categories was predictive (M = .60, SE = .026) than when
it was diagnostic (M = .47, SE = .028). Despite the significant main effects, the
interaction between age group and direction did not approach significance, Fs(2, 146) =
0.21, p = .89, effect size f = .006, Fi(3, 33) = 0.55, p = .66. Rather, as may be seen in
Table 1, children were as strongly influenced by the structure of causal knowledge as were
adults. Post hoc comparisons using Bonferroni adjustments on the means involved in the
significant effect of age group showed that 8-year-olds made more causal choices than both
12-year-olds (p = .05) and adults (p < .0005). There was no significant difference in the
proportion of causal choices made by 12-year-olds and adults (p = .17), and 5-year-olds
made significantly more causal choices than adults (p = .014). Both 5-year-olds, t(43) =
2.69, p = . 001, and 8-year-olds, t(39) = 3.91, p < .0005, made more causal choices than
predicted by chance alone. The trend line in Fig. 2 suggests that causal induction shows a
curvilinear development in the shape of an inverted U, which was confirmed with a
polynomial contrast. This involves starting with the linear contrast and then sequentially
carrying out higher power contrasts until the highest-power contrast is nonsignificant.
There was a significant linear trend (p < .0005) as well as a significant quadratic term
(p = .014). The cubic contrast was nonsignificant (p = .18). The quadratic effect across
age group was also highly significant across items, Fi(1, 11) = 15.7, p < .0005. This
pattern confirms that the use of causal knowledge in inductive reasoning follows a
curvilinear developmental trajectory, peaking at 8 years and decreasing thereafter. The
results of the ANOVA contained a significant main effect of property, Fs(1, 146) = 8.6, p
= .004, effect size f = .24, Fi(1, 11) = 60.9, p < .0005. Causal choices were
significantly more frequent when participants reasoned about diseases (M = .60, SE = .033)
than when they reasoned about cells (M = .47, SE = .033). However, this was qualified by a
significant interaction between property and age group, Fs(2, 106) = 6.2, p = .001, effect
size f = .36, Fi(3, 33) = 62.7, p < .0005. As Fig. 2 shows, both 4- and 8-year-olds made a
similar number of causal inductions in both the cell and disease conditions (ps > .25,
effect size d < 0.2), suggesting that they are not exhibiting strong inductive selectivity
effects. In contrast, both adults (p = .031, effect size d = 0.8) and 12-year-olds (p =
.0005, effect size d = 1.2) showed strong inductive selectivity effects, making
significantly more causal inductions in the disease condition than in the cell condition.
Furthermore, the proportion of causal choices was similar across all age groups when
reasoning about diseases (all pairwise comparison ps > .20). In contrast, when reasoning
about cells, 4- and 8-year-olds made significantly more causal choices than both 12-year-
olds and adults (ps < .022). The latter two age groups were not significantly different
from each other (p = .64). Thus, it appears that the increased selectivity is driven by a
developmental decrease in causal choices when reasoning about cells rather than a change
in the application of causal knowledge when reasoning about diseases. There was no
significant interaction between direction and property, Fs(1, 146) = 2.26, p = .13, effect
size f = .12, Fi(1, 11) = 2.94, p = .11, and no three-way interaction among age group,
property, and direction, Fs(3, 146) = 0.93, p = .43, effect size f = .13, Fi(3, 33) =
0.89, p = .46. In this equation, P(w1 & w2) represents the probability that a text
contains both words w1 and w2, and P(w1) represents the probability that it contains w1 on
its own. To calculate the conditional probability, one can simply count the number of
times w1 and w2 co-occur and divide this by the number of times w1 occurs by chance in the
same text sample. This is repeated for w2. We took the mean of the two conditional
probabilities for each pair and calculated z scores. Using an independent-samples t test,
we compared the mean co-occurrence index for the causally related category pairs (mean z
score = −0.3, SD = 0.4) with the mean co-occurrence index for the taxonomically related
category pairs (mean z score = 0.15, SD = 1.2). This showed that there was no significant
difference between the two co-occurrence indexes, t = 1.68, df = 31.3 (adjusted for
unequal variances), p = .10, effect size d = 0.5. However, as indicated by the medium
effect size, if anything the taxonomic category pairs co-occurred slightly more
frequently, strengthening our claim that children and adults were drawing on structured
causal knowledge rather than simple associative knowledge. Another possible alternative
explanation of our results is that the youngest participants preferred causally related
targets because they did not possess the knowledge about taxonomic relations required to
recognize the strength of arguments based on such relations. To rule out this possibility,
we checked taxonomic and causal knowledge levels in a separate sample of the same age as
our youngest age group. A group of 20 5-year-olds were shown the color pictures of the
category pairs used in the main experiment and were asked about biological group
membership (“Do this [name of first category] and this [name of second category] belong to
the same group?”) and causal relatedness (“Does this [name of first category] eat this
[name of second category]?”). Paired-samples t tests across the 20 children and by items
showed that there was no difference between the causal relatedness endorsement proportion
(M = .78, SD = .13) and the biological group membership endorsement proportion (M = .79,
SD = .17), ts(19) = −0.68, p = .51, effect size d = 0.15, ti(11) = −0.037, p = .97. Thus,
it is unlikely that the 5- and 8-year-olds in the main experiment preferred causal targets
because, relative to their causal knowledge, they lacked taxonomic knowledge.

<h>DISCUSSION</h>
----------

We had two aims in carrying out this study. First, we wanted to examine whether causal or
taxonomic knowledge is the default prior to the age at which children develop inductive
selectivity. Second, we wanted to see whether children are sensitive to aspects of causal
structure when evaluating category-based inductive arguments. In showing that 5- and
8-year-old participants preferred arguments that were strong because of a causal mechanism
for transmission via a predation relation even when the property reasoned about was a
cell, our findings suggest that causal knowledge structures are the default in children’s
reasoning prior to the emergence of inductive selectivity. In addition, 5-year-olds are
just as sensitive to causal direction as are adults. In fact, all age groups in our
experiment endorsed significantly more predictive arguments than diagnostic arguments.
Interestingly, causal reasoning seems to show a curvilinear development, peaking at 8
years of age and decreasing thereafter due to the emergence of inductive selectivity.
Although we did not anticipate this last finding, as we show below, it has parallels in
the literature on children’s understanding of folk biology. The pattern of results we
observed has very interesting implications for theories about how inductive reasoning
develops. Sloutsky (2010) suggested that “adult-like” inductive reasoning depends on a
maturationally late learning system. This suggestion can explain why we did not observe
inductive selectivity until the age of 12 years, driven by an increase in taxonomic
inferences when reasoning about cells. Under Sloutsky’s account, reasoning about cells
might require more abstract conceptual knowledge about mechanisms that are not
perceptually observable such as genetics and inheritance. However, this account also seems
to suggest that prior to the emergence of inductive selectivity children ought to rely
heavily on superficial similarity or category membership rather than on causal knowledge.
Our data suggest otherwise, with 5- and 8-year-olds making the most causal inductions
regardless of context. Alongside recent evidence from Hayes and Lim (2013), who showed
that inductive selectivity even in relatively transparent contexts depends on conscious
awareness of the relevance of contextual clues, the current findings cast doubt on the
claim that early category-based induction is driven exclusively by simple learning
mechanisms based on co-occurrence and perceptual similarity. At the very least, it
requires a substantial downward revision of the age at which conceptual knowledge such as
simple causal structures can support category-based inductive reasoning. In addition to
their tendency to prefer causal relations rather than taxonomic relations as the basis for
inference, 5- and 8-year-old participants, like older participants, made more causal
inferences when the causal relation between the categories was predictive than when it was
diagnostic. The influence of different kinds of knowledge seems to be fundamentally
related to the way in which this knowledge is organized in long-term memory (Fenker et
al., 2005). Although causal knowledge itself does not have a homogeneous structure and can
vary in complexity from direct cause–effect links to more complex common cause relations
(Sloman, 2005), one might expect the abstract organization of knowledge about food chains
involving simple causal transmission to be similar in adults and children. For example,
children as young as 3 years show an understanding of the importance of causal order in
which effects follow or co-occur with their causes (Bullock & Gelman, 1979; Bullock,
Gelman, & Baillargeon, 1982). Reasoning about relations that are in line with this
ordering of events might be cognitively simpler than needing to reason about possible
causes given an outcome (Kahneman & Tversky, 1973). Shafto and colleagues (2008) suggested
that causal asymmetry effects are driven by a multilevel understanding of causal
knowledge—concrete knowledge about the existence of causal relations and more conceptual
knowledge about how and when causal relations are most likely to warrant an inference from
one agent to another. The simple causal structure used in the current task might explain
why some of our findings are different from previous results. For example, whereas the
current study showed no age-related changes in the frequency of causal reasoning about
diseases, work on ecological reasoning by Coley, Vitkin, Seaton, and Yopchick (2005)
demonstrates a clear developmental trend in the use of non-taxonomic knowledge. They
argued that this is driven by an experiential increase in ecological knowledge. It is
conceivable that the structure of the causal relations underlying the ecologically related
categories in Coley and colleagues’ study (e.g., between tiger and parrot) was more
complex, involving indirect causal pathways and common causes rather than simple and
direct cause–effect relations. Thus, increased complexity may render non-taxonomic
knowledge less available to reasoning processes in younger children. There may be a number
of reasons why the younger children in our experiment relied on causal knowledge rather
than taxonomic knowledge when reasoning. The properties used required knowledge about two
quite distinctive biological domains: (a) food chain relations and disease contagion and
(b) taxonomic relations and genetics. One likely possibility is that knowledge of the
genetic basis of shared properties, inheritance, and biological processes is less
elaborate in 5- and 8-year-olds compared with 12-year-olds and adults (Au & Romo, 1999;
Hatano & Inagaki, 1994; Hatano & Inagaki, 1997). Indeed, educational research suggests
that children have conceptual gaps and erroneous concepts in their explanations for
genetics (Lewis & Kattmann, 2004; Smith & Williams, 2007) that become more elaborate and
accurate only with explicit instruction (Venville & Donovan, 2007). On the other hand, the
mechanism by which members of a common food chain may transmit diseases is obvious and
observable and constitutes a central part of the science curriculum for 8-year-olds. In
line with other work showing that children like to have an explanation for phenomena
(Callanan & Oakes, 1992), the children in our study may have preferred to base their
reasoning on relations for which they have a mechanistic explanation and a more coherent
theory (Gutheil, Vera, & Keil, 1998). Children as young as 3 years have a basic
appreciation that invisible agents can cause illness (Kalish, 1996) and understand simple
mechanisms by which contamination may come about (Siegal & Share, 1990; Springer & Belk,
1994), suggesting that children do have some naive but systematic theory about biological
disease transmission. One striking aspect of our results was that younger participants
over-generalized their knowledge of disease transmission mechanisms. A relevant example of
knowledge over-generalization comes from Keil and colleagues (1999), who showed that
increases in knowledge about the mechanisms of disease transmission simultaneously led to
more accurate inductions for physical illness contagion but less accurate reasoning about
the causes of mental illness. Interestingly, the 8-year-old participants in Keil and
colleagues’ study made the most inaccurate transmission choices. This over-generalization
parallels our current finding in which simple causal transmission is also seen as a basis
for sharing physiological properties such as cells. Thus, inaccurate beliefs or
inappropriate causal explanations seem to be supplanted only when children have more
appropriate coherent explanatory systems at their disposal. Because they show that causal
knowledge dominates taxonomic knowledge in young reasoners, our results are contrary to
the claim made by proponents of the structured Bayesian approach that taxonomic knowledge
structures are the default (see Kemp & Tenenbaum, 2009; Tenenbaum, Kemp, & Shafto, 2007).
Nonetheless, theory-driven Bayesian approaches have the potential to explain developmental
changes in patterns of inductive reasoning. The domain-specific theories captured in
Bayesian knowledge structures are minimalist and open to revision, both on encountering
direct evidence and through verbal instruction. These characteristics of the Bayesian
account, in conjunction with the observation that children are likely to have less well-
developed domain-specific theories, may allow the Bayesian approach to account for the
divergence between 8-year-olds’ and adults’ patterns of inductive selectivity. However, it
aims to explain inference at a computational level rather than in terms of process; the
Bayesian approach does not address the issues of availability and processing effort
(Shafto, Coley, & Baldwin, 2007; Shafto, Coley, & Vitkin, 2007) that are likely to be
important when explaining developmental changes in reasoning ability. Finally, our
research made use of non-blank properties such as cells and diseases, with inductive
selectivity driven by the decrease in the use of causal relations when reasoning about
cells. A future interesting question will be to explore the developmental use of causal
knowledge for inductive problems that use blank properties. It seems likely that changes
in the application of causal knowledge would be driven by cultural factors and expertise
with causal choices likely to decrease in Western and/or urban samples, whereas the use of
causal knowledge is likely to persist in non-Western and more rural samples (e.g., Coley,
2012; Lopez, Atran, Coley, Medin, & Smith, 1997). To summarize, young children strongly
prefer inductive arguments where there is a plausible causal mechanism for property
transmission, even where older children and adults appear to judge that mechanism
irrelevant to the property to be generalized. Recruitment of this salient source of
knowledge may be supplanted only by more contextually appropriate knowledge when formal
education offers children an alternative feasible mechanism by which two categories come
to share properties. In addition, even 5-year-olds are influenced by the directional
nature of causal relations. All of this suggests that causal relations are at least as
important to young children’s reasoning as they are to adults’ reasoning and that, in some
respects, the manner in which causal reasoning influences reasoning is similar across
development.


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<ART>Children's humor types and psychosocial adjustment
==================================================

Authors: Claire L. Fox, Simon C. Hunter, Siân E. Jones
DOI: 10.1016/j.paid.2015.09.047
Year: 2016  |  Pages: 86-91
ASJC codes: 3200
Keywords: Children, Cluster analysis, Humor styles, Psychosocial adjustment, Types

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Attempting to understand how humor styles relate to psychological adjustment by correlating these two constructs fails to address the emerging understanding that individuals use combinations of humor styles, and that different combinations may be differentially associated with psychosocial adjustment. Indeed humor types have been identified in adult samples (Galloway, 2010; Leist & Müller, 2013). The main aim of the study was to explore whether similar humor types are evident at a younger age and whether these types can be distinguished in terms of children's psychological and social well-being. Participants were 1234 adolescents (52% female) aged 11-13 years, drawn from six secondary schools in England. Self-reports of humor styles and psychosocial adjustment were collected at two time points, 6 months apart. A cluster analysis was performed using the child humor styles scores at Time 1. Four humor types were identified: 'Interpersonal Humorists' (high on aggressive and affiliative humor, low on self-defeating and self-enhancing humor), 'Self-Defeaters' (high self-defeating humor, low on the other three), 'Humor Endorsers' (high on all four humor styles), and 'Adaptive Humorists' (high on self-enhancing and affiliative humor, but low on aggressive and self-defeating humor). 'Self-Defeaters' scored highest in terms of maladjustment across all of the outcomes measured. Our analyses support the presence of distinctive humor types in childhood and indicate that these are related to psychosocial adjustment.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Over the past two decades, there has been a steady accumulation of research on the topic
of humor. Far less research has focused on the social/emotional functions of humor in
children or the way that these functions develop through childhood/adolescence (Martin,
2007). It is recognised that among children and adults, there are four main types of humor
style, and these reflect the use of humor in everyday life (Fox, Dean, & Lyford, 2013;
Martin, Puhlik-Doris, Larsen, Gray, & Weir, 2003). Self-enhancing humor is the ability to
maintain a humorous perspective in the face of stress and adversity; it is closely aligned
to coping humor (e.g. ‘My humorous outlook on life keeps me from getting too upset or
depressed about things’). Aggressive humor also enhances the self, at least in the short-
term, but is done at the expense of others (e.g. ‘If someone makes a mistake I often tease
them about it’). Affiliative humor enhances one's relationships with others and reduces
interpersonal tensions (e.g. ‘I enjoy making people laugh’). Finally, self-defeating
humor, largely untapped by previous humor scales, is used to enhances one's relationships
with others, but at the expense of the self (e.g. ‘I often try to make people like or
accept me more by saying something funny about my own weaknesses, blunders and faults’).
The ability to distinguish between different components of humor has brought with it a
clearer picture of the relationships between humor and adjustment. This is evidenced by
the stronger correlations between humor and psycho-social adjustment which are reported
when using the adult Humor Styles Questionnaire (HSQ) as compared to previous research
using unidimensional measures (Martin et al., 2003). Among adults, affiliative and self-
enhancing humor are negatively correlated with anxiety, depression, and suicidal ideation,
and positively correlated with self-esteem and life satisfaction. In contrast, self-
defeating humor is associated with high levels of anxiety, depression, and suicidal
ideation, and lower self-esteem and lower life satisfaction (Dyck & Holtzman, 2013;
Kuiper, Grimshaw, Leite, & Kirsh, 2004; Martin et al., 2003; Tucker et al., 2013).
Aggressive and self-defeating humor styles are both associated with hostility and
aggression (Martin et al., 2003). In addition, aggressive humor is not associated with
psychological adjustment but is strongly negatively correlated with social adjustment
measures (Yip & Martin, 2006). Whether such associations can be generalised to adolescent
populations is not yet clear, and data relating to this would clarify the ways in which
humor as a coping strategy develops across the lifespan. Using a series of studies, the
HSQ was adapted for use with children and young people aged 11–16 years (Fox et al.,
2013). An adaptation of the HSQ was needed to enable the examination of all four styles of
humor styles in children and adolescents. The HSQ could not be used in its adult form as
prior administration with adolescents aged 12–15 (Erickson & Feldstein, 2007) demonstrated
unsatisfactory internal reliability for the two maladaptive sub-scales (α = .65 and .58).
When used with 11–16 year olds, there were acceptable levels of reliability for all four
sub-scales (all α > .70), and both principal components analysis and confirmatory factor
analysis identified a clear four-factor structure. In addition, it was found that
affiliative humor was positively correlated with global self-worth and self-perceived
social competence, and negatively correlated with anxiety and depressive symptoms.
Conversely, self-defeating humor was negatively correlated with global self-worth and
self-perceived social competence, and positively correlated with anxiety and depressive
symptoms. In a more recent longitudinal study using the child HSQ, self-defeating humor
was associated with an increase in depressive symptoms and loneliness and a decrease in
self-esteem. In addition, depressive symptoms predicted an increase in the use of self-
defeating humor over time, thus suggesting a bi-directional relationship. Self-esteem was
associated with an increase in the use of affiliative humor over the school year but not
vice-versa (Fox, Hunter, & Jones, unpublished manuscript). This was the first study to
examine the longitudinal relationships between the four humor styles and aspects of
psychosocial adjustment. While such studies can be more difficult to implement, it is
important that they are utilised more frequently so that we can better understand the
development of humor and its potential negative consequences. Indeed, it could be that
particular styles of humor (e.g. adaptive) lead to improved psychological adjustment or
that better mental health and well-being facilitates the greater use of adaptive styles of
humor. More recently researchers have begun to consider the combination of humor styles
characteristic of any given person (Galloway, 2010; Leist & Müller, 2013). These analyses,
it is believed, can extend knowledge about the four humor styles beyond what we already
know from examining them individually. By identifying different humor types or profiles,
new associations might emerge and advance understanding of the four humor styles and the
ways in which they are related to psychological well-being. Indeed, as stated by Martin et
al. (2003), the four humor styles are closely interrelated, but not equally adaptive for
well-being. Using a sample of 318 Australian adults, Galloway (2010) identified four
clusters: 1) Those who scored above average on all four humor styles; 2) Those who scored
below average on all four; 3) Those who scored above average on the adaptive humor styles
and below average on the maladaptive humor styles, and 4) Those who scored above average
on the maladaptive humor styles and below average on the adaptive humor styles.
Differences between the groups were identified, for example, those in Cluster 1 scored
above average for extroversion and openness and below average for conscientiousness and
agreeableness. Cluster 3 scored highest for self-esteem and agreeableness, and those in
Cluster 4 were below average for self-esteem, extroversion, openness, and agreeableness.
However, the study was limited by the small sample size and the cross-sectional nature of
the design. A similar study by Leist and Müller (2013) with a German sample identified
three, not four clusters: 1) Those who scored above average on all four; 2) Those who
scored below average on all four, and 3) Those who scored above average on the adaptive
humor styles and below average on the maladaptive humor styles. Those in the third cluster
reported higher self-esteem in comparison to the other two clusters. In addition, those in
Cluster 2 reported poorer life satisfaction in comparison to the other two clusters. The
same limitations that apply to Galloway's study (2010) apply here, namely, the small
sample size (N = 348) and the lack of longitudinal data. Moreover the sample was two-
thirds female, which is potentially problematic given that gender differences in the four
humor styles have been consistently identified (Fox et al., 2013; Führ, 2002; Martin et
al., 2003; Saraglou & Scariot, 2002). Thus, the main aim of the current study was to
identify humor types in children and improve on some of the limitations identified in
previous studies, by using a large sample size and a longitudinal design (drawing on the
same data set as used by Fox et al., unpublished manuscript). Differences between the
humor types were examined based on measures of psychosocial adjustment: depressive
symptoms, loneliness and self-esteem. As well as looking at cross-sectional associations
we used residual scores to compare the clusters in relation to changes in adjustment
across time. We also looked at the distribution of gender across the clusters.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

We recruited 1234 pupils aged 11–13 years (school years 7 and 8; 680 children aged 11–12
years, and 554 children aged 12–13 years), from six state secondary schools in the
Midlands, UK. In terms of gender, 599 participants were male and 620 female (with missing
data for 15 participants). The mean age of the sample at Time 1 was 11.68 years (SD =
0.64). The ethnic composition of each school (M = 93% white) was a reflection of the
region in which the research was located; the sampling strategy took into account both
rural/urban and SES profile to achieve a range of schools representative of the area from
which they were recruited. Parents or carers of all children in the relevant year group at
each school were invited to allow their child to participate, using the opt-out method of
consent. Pupils who did not participate in the first session of data collection at Time 1
were not permitted to take part in the second session of data collection at Time 1. Across
the time points of the study, the participation rate ranged from 70% to 85% of eligible
young people registered in the schools. Participant recruitment and data collection were
conducted during school hours. Participants assented to take part in the study during
class time. Classes varied in size from 10 to 31 with a modal class size of 24 pupils.
Participants who were not taking part completed an alternative activity.

<hs>  Materials</hs>
  ~~~~~~~~~

Students completed an answer booklet at each session in which they recorded their name,
age, school class, gender and ethnicity, prior to completion of the measures pertinent to
that session.

        <hss>Humor styles</hss>

        Participants completed the self-report child Humor Styles Questionnaire (child
        HSQ; Fox et al., 2013), which is an adapted version of the adult HSQ (Martin et
        al., 2003). Using a 4-point response scale (1 = strongly disagree to 4 = strongly
        agree), participants rated their agreement with the 24 statements. There are six
        items per sub-scale with four sub-scales in total: Self-Defeating (e.g. ‘I often
        put myself down when I am making jokes or trying to be funny’), Aggressive (e.g.
        ‘When I tell jokes I'm not worried if it will upset other people’), Affiliative
        (e.g. ‘I don't have to try very hard to make people laugh — I seem to be a
        naturally funny person’) and Self-Enhancing (e.g. ‘I find that laughing and joking
        are good ways to cope with problems’). When used with 11–16 year olds, Fox et al.
        (2013) found acceptable levels of internal reliability for all four sub-scales
        (all α > .70), and confirmatory factor analysis identified a very clear four-
        factor structure. The child HSQ also has acceptable levels of test re-test
        reliability (rs range from .65 to .75 across one week). For the present study,
        reliability coefficients were all above .70, apart from aggressive humor at Time 1
        (Time 1: αaggressive = .66; αself-defeating = .73; αself-enhancing = .75,
        αaffilitative = .85; Time 2: αaggressive = .71; αself-defeating = .81; αself-
        enhancing = .82, αaffilitative = .88). In addition, the four-factor structure was
        confirmed. Mean scores were calculated for each sub-scale, with higher scores
        reflecting greater use of that form of humor.

        <hss>Depressive symptoms</hss>

        The 10-item, self-report Children's Depression Inventory — Short Form (Kovacs &
        Beck, 1977) for ages 7–17 years was administered. For each symptom, participants
        are required to indicate which of three items best describes them over the
        preceding two weeks, and responses were scored from 0 (no symptom), 1 (mild
        symptom), or 2 (moderate/severe symptom). An example item is: “I am sad once in a
        while”, “I am sad many times”, and “I am sad all the time.” Sum scores were then
        calculated, with higher scores reflecting the presence of greater symptomatology.
        This measure showed acceptable internal consistency with the current sample (α =
        .86, and α = .88, at T1 and T2 respectively).

        <hss>Loneliness</hss>

        This was assessed using the four-item, self-report Loneliness and Social
        Satisfaction scale (Asher, Hymel, & Renshaw, 1984; Rotenberg, Boulton, & Fox,
        2005). A 5-point Likert scale ranging from 1 = not at all true to 5 = really true
        was used and a mean score was calculated such that higher scores reflected greater
        loneliness. An example item is ‘I am lonely.’ In the current study, this measure
        showed acceptable internal consistency (α = .86, and α = .88, at T1 and T2
        respectively).

        <hss>Self-esteem</hss>

        Rosenberg's (1965) 10-item, self-report self-esteem measure for adolescents and
        adults was used with participants judging each item on a 4-point scale from 1 =
        strongly disagree to 4 = strongly agree. An example item is “I am able to do
        things as well as most people”. With the current sample, reliability coefficients
        were α = .87 and α = .89 at T1 and T2 respectively. Sum scores were calculated
        with higher scores reflecting higher self-esteem.

<hs>  Procedure</hs>
  ~~~~~~~~~

Prior to data collection, the study was approved by the relevant University Ethics
Committee. Data collection took place in the Fall (Time 1) and Summer (Time 2) terms of
the school year, in school classrooms with a class teacher present. Data collection took
approximately half an hour. A range of other variables were measured but are not the
central focus of this paper. Sessions began with the researchers introducing themselves
and explaining the measures that would be collected that day, and explaining the
confidential nature of the questionnaires. Pupils were asked to complete the questionnaire
booklets in silence; they were asked to keep their answers private and not look at what
other children were doing. Following data collection pupils were thanked and fully
debriefed as to the aims and purpose of the study.

<hs>  Descriptive statistics and intercorrelations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Descriptive statistics for all the Time 1 and Time 2 variables can be seen in Table 1.
Table 2 shows the intercorrelations for all the T1 and T2 variables. As might be expected
there are significant correlations between the four humor styles and depression,
loneliness and self-esteem, at Time 1 and Time 2 and from Time 1 to Time 2. For example,
the adaptive styles of humor (affiliative, self-enhancing) are positively correlated with
self-esteem and negatively correlated with depression and loneliness. In contrast, self-
defeating humor is negatively correlated with self-esteem and positively correlated with
depression and loneliness.

<hs>  Cluster analysis</hs>
  ~~~~~~~~~~~~~~~~

We decided to use a series of K-mean cluster analyses as used by Galloway (2010) with an
adult sample. When using cluster analysis, the investigator typically has to decide how
many clusters to extract from the data. A degree of trial and error is often used to
identify the most optimal solution. Normally this is done taking into account the
interpretability and parsimony of the different solutions being considered. First, the
child HSQ scores were transformed to Z scores to help with the interpretation of the
results. A series of K-mean cluster analyses were conducted with the four-cluster solution
being the one considered the most appropriate. The Z-scores for the four humor styles
within the four clusters can be seen in Table 3 and in Fig. 1. The first cluster, which we
have called the ‘Interpersonal Humorists’ includes those who scored above average on
aggressive and affiliative humor, but below average on the other two humor styles. Cluster
2 represents the ‘Self-Defeaters’ who scored high on this style of humor, but low on the
other three. Thirdly, the ‘Humor Endorsers’ scored above average on all four humor styles,
and finally, the ‘Adaptive Humorists’ scored high on the two adaptive styles of humor, but
low on aggressive and self-defeating humor. These clusters were replicated when performing
a cluster analysis on the Time 2 data (see Table 3).

<hs>  Group differences</hs>
  ~~~~~~~~~~~~~~~~~

A Chi-square analysis to test for gender differences across the four clusters was
significant (χ2 = 35.30, df = 3, p < .001). The percentage of males and females in
Clusters 1 and 2 were roughly equivalent. However, there were more males then females in
Cluster 3 (‘Humor Endorsers’) and more females than males in Cluster 4 (‘Adaptive
Humorists’) (Table 4). A series of one-way ANOVAs tested for differences between the
groups in terms of the measures of psychosocial adjustment at Time 1 and using
standardised residual change scores from Time 1 to Time 2 (by regressing the T2 scores on
respective T1 scores). Table 5 shows that the main differences were between Cluster 3 (the
‘Self-Defeaters’) and the other three clusters. Those in Cluster 3 scored highest for
depressive symptoms, loneliness, self-esteem and change in loneliness, compared to the
other three clusters. In addition, those in Cluster 3 showed a greater change in
depressive symptoms, in comparison to the ‘Interpersonal Humorists’ (Cluster 1) and the
‘Adaptive Humorists’ (Cluster 4). For the self-esteem change scores there were no
differences between the four clusters. When looking at the cross-sectional data only, some
other group differences emerged. The ‘Adaptive Humorists’ (Cluster 1) scored highest for
self-esteem in comparison to the ‘Self-Defeaters’ (as above) but also in comparison to the
‘Interpersonal Humorists’ (Cluster 1) and the ‘Humor Endorsers’ (Cluster 3). There was
also a significant difference in depressive symptoms between the ‘Adaptive Humorists’ and
the ‘Humor Endorsers’. For loneliness, the ‘Humor Endorsers’ (Cluster 3) reported
significantly less loneliness then the Self-Defeaters (Cluster 2), but significantly more
loneliness than the ‘Adaptive Humorists’ (Cluster 4) and the ‘Interpersonal Humorists’
(Cluster 1) (Table 5).

<h>DISCUSSION</h>
----------

This is the first study to identify humor types using a large sample of adolescents and a
longitudinal design. It builds on the research by Galloway (2010) and Leist and Müller
(2013) who were the first to explore combinations of humor styles with adult samples. In
the same way, the current study extends knowledge beyond what we already know about humor
styles from examination of simple correlations between the four humor styles and measures
of psychosocial adjustment. Indeed, our findings suggest that simple correlations can be
misleading. Of note is that self-defeating humor, when used in combination with other
humor styles, is not necessarily maladaptive. Of all the clusters identified, those in
Cluster 2 (the ‘Self-Defeaters’) scored highest in terms of psychosocial maladjustment.
They scored highest for depressive symptoms, loneliness, self-esteem and change in
loneliness, compared to the other three clusters. For change in depressive symptoms, the
‘Self-Defeaters’ scored the highest in comparison to the ‘Interpersonal Humorists’
(Cluster 1) and the ‘Adaptive Humorists’ (Cluster 4). However, there was no difference
between the ‘Self-Defeaters’ and the ‘Humor Endorsers’ (Cluster 3), who appeared to show
no change. In contrast, those in Cluster 4 (the ‘Adaptive Humorists’) scored highest for
self-esteem in comparison to the three other clusters. They were also less lonely than the
‘Self-Defeaters’ and the ‘Humor Endorsers’; these two groups were also more lonely than
the ‘Interpersonal Humorists’. This suggests that the negative effects of using self-
defeating humor can be offset to some extent when it is used in combination with other
humor styles, but not always. Future research could examine a wider range of adjustment
variables over time to explore the similarities and differences between these two groups.
Crucially though, the ‘Humor Endorsers’ were not found to be more maladjusted than the
‘Adaptive Humorists’ and the ‘Interpersonal Humorists’ when examining change in adjustment
across time. However, future studies could extend this research to see whether any
differences do emerge over a longer period of time. In the same way it would be
interesting to examine the ‘Interpersonal Humorists’ over a longer time period. Our
findings seem to suggest that aggressive humor is not typically used in isolation, and
when it is used with affiliative humor, it could be viewed as adaptive, at least for the
protagonist. The ‘Interpersonal Humorists’ were less lonely in comparison to the ‘Self-
Defeaters’ and ‘Humor Endorsers’, although this effect disappeared when we looked at the
data across time. Dyck and Holtzman (2013) noted that of all the four humor styles,
aggressive humor has the weakest and most inconsistent findings, with many studies that
have used the adult HSQ failing to find significant associations between aggressive humor
and measures of psychological adjustment. As argued by Martin (2007), over the long-term,
aggressive humor may be detrimental to the self because it tends to alienate others.
Studies over a longer time-frame may be able to identify significant associations between
aggressive humor types and psychosocial maladjustment. There are some similarities between
these findings and those of Galloway (2010) and Leist and Müller (2013). Similar to the
present study, both studies identified a group scoring high on all four humor styles and a
group who scored above average on the adaptive humor styles, but below average on the
maladaptive humor styles. However, these previous studies also identified a group who
scored low on all four. In addition, Galloway (2010) identified a group who scored above
average on the maladaptive humor styles and below average on the adaptive humor styles. In
contrast, for the present study, aggressive humor and affiliative humor were combined,
leaving a group of children who scored high on self-defeating humor and low on the other
three humor styles. This may be due to the difference in age between the samples, the
different cultures and/or it may cast some doubt on the findings of these previous studies
which drew on relatively small samples of participants (300–400). There is a need to
replicate these humor types using similar samples but in different contexts and countries.
The adult HSQ has received cross-cultural validation among European (Saraglou & Scariot,
2002), Chinese (Chen & Martin, 2007) and Arabic samples (Kazarian & Martin, 2004). It
demonstrates good psychometric properties and the findings provide support for the four-
factor structure. In addition, there is cross-cultural stability in terms of the
associations between the four humor styles and measures of psychosocial adjustment; gender
differences are also consistent. However, there are differences when looking at the
interrelations between the sub-scales. Unlike with North American samples (Martin et al.,
2003), there is typically no correlation between affiliative and aggressive humor in other
cultures (Chen & Martin, 2007; Kazarian & Martin, 2004; Saraglou & Scariot, 2002). Given
that Cluster 1 with the current sample includes those who scored high on affiliative and
aggressive humor, it is important that these types are investigated further in other
cultures. One of the main limitations of the study is the use of self-reports to measure
humor styles and children's psychosocial adjustment, which raises the possibility that
many of the associations were confounded by shared method variance. Further research
should consider gathering data on children's adjustment from different sources, such as
teachers and parents. There is also a need to examine associations between humor types and
a wider range of adjustment variables. However, it is not clear that shared method
variance necessarily leads to inflated estimates (Conway & Lance, 2010). In addition, the
use of humor types to some extent does guard against this claim though because we are not
examining simple correlations between positive/negative humor styles and positive/negative
aspects of psychosocial adjustment; instead we are looking at differences between humor
types, which involve combinations of adaptive and maladaptive humor styles. A potential
useful way forward would be to test some of these hypotheses experimentally, similar to
the studies by Kuiper, Kirsh, and Leite (2010) and Ziegler-Hill, Besser, and Jett (2013).
For example, Ziegler-Hill et al. (2013) provided evidence that adult targets displaying
the more benign styles of humor are perceived more positively by others. Similarly, Kuiper
et al. (2010) found that both adolescents and adults are less willing to continue an
interaction with someone displaying maladaptive humor (i.e. aggressive or self-defeating
humor). For example, it would be useful to know how others perceive those who use all four
styles of humor, in comparison to those who use only self-defeating humor. Results from an
experimental approach such as this could advance our understanding, possibly identifying
perceived motives behind the different uses of humor. In conclusion, the current study has
extended knowledge beyond what we already know about the simple correlations between the
four humor styles and aspects of psychosocial adjustment in children. Furthermore, it is
the first study to examine differences in humor types across time. The findings suggest
that the negative effects of self-defeating humor could be offset if it is used in
combination with other humor styles. However, further research is needed to examine
children's humor types in other cultures as well as differences between humor types over a
longer period of time.


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<ART>Children's inference generation: The role of vocabulary and working memory
==========================================================================

Authors: Nicola Kate Currie, Kate Cain
DOI: 10.1016/j.jecp.2015.03.005
Year: 2015  |  Pages: 57-75
ASJC codes: 3204, 3205
Keywords: Global coherence, Inference, Local coherence, School-aged children, Vocabulary, Working memory

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<h>ABSTRACT</h>
--------

Inferences are crucial to successful discourse comprehension. We assessed the contributions of vocabulary and working memory to inference making in children aged 5 and 6. years (n = 44), 7 and 8. years (n = 43), and 9 and 10. years (n = 43). Children listened to short narratives and answered questions to assess local and global coherence inferences after each one. Analysis of variance (ANOVA) confirmed developmental improvements on both types of inference. Although standardized measures of both vocabulary and working memory were correlated with inference making, multiple regression analyses determined that vocabulary was the key predictor. For local coherence inferences, only vocabulary predicted unique variance for the 6- and 8-year-olds; in contrast, none of the variables predicted performance for the 10-year-olds. For global coherence inferences, vocabulary was the only unique predictor for each age group. Mediation analysis confirmed that although working memory was associated with the ability to generate local and global coherence inferences in 6- to 10-year-olds, the effect was mediated by vocabulary. We conclude that vocabulary knowledge supports inference making in two ways: through knowledge of word meanings required to generate inferences and through its contribution to memory processes.

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<h>INTRODUCTION</h>
------------

Skilled comprehenders make sense of written and spoken language by constructing a coherent
memory-based representation of the state of affairs described by the text, commonly
referred to as a situation model (Kintsch, 1988). The text does not always explicitly
state all of the information needed for coherence. Therefore, readers and listeners
regularly make inferences to integrate information within the text and to fill in details
that are only implicit. These inferences are incorporated into the situation model that
the comprehender constructs and result in a more accurate and complete understanding of
the text (Graesser, Singer, & Trabasso, 1994). Although children make inferences from an
early age, they do not typically make as many as do older children and adults (e.g.,
Ackerman, 1986; Casteel, 1993). Our focus in this study was to understand better why this
is the case by examining the role played by two critical factors related to young
children’s inference generation: vocabulary and working memory. Furthermore, we explored
whether these factors make different contributions to distinct types of inference. A
greater understanding of the factors that support early inference making will inform
models of comprehension development and also the literacy curriculum and targeted
intervention programs for children with weak inference-making and comprehension skills.
When considering different types of inference, one of the key distinctions that can be
made is between inferences that establish local coherence and those that establish global
coherence (Graesser et al., 1994). Inferences that are necessary for local coherence
typically involve the integration of separate propositions within the text and are usually
cued by a pronoun, synonym, or category exemplar; for example, “He finished the orange
juice quickly. The drink was very refreshing.” Local coherence inferences often require a
mapping between related words, for example, between synonyms or category exemplar pairings
as in the example above. In contrast, inferences necessary for global coherence can
involve inferring goals that motivate particular actions or establishing an overall theme
of a text, and this often relies on the ability to connect ideas that are not explicitly
signaled by a single word and that can be distributed throughout the text. For example,
readers can infer the likely setting of a story through links between semantically related
concepts such as “building sandcastles,” “paddling in the water,” and the presence of a
“pier” (which together indicate that the setting is the seaside). In this way, inferences
that are necessary for global coherence typically draw more heavily on information that is
external to the text than do local coherence inferences (Cain & Oakhill, 1999, in press).
We note that it is likely that local and global coherence inferences are not truly
categorical distinctions and that, rather, different inferences draw on information in the
text and background knowledge to differing degrees (Florit, Roch, & Levorato, 2011).
Furthermore, some authors distinguish local and global coherence inferences in terms of
distance between elements of the text (e.g., McKoon & Ratcliff, 1992), but we did not
manipulate this feature of our texts. Critically, both local and global coherence
inferences are necessary for a full understanding of the text, in line with Cain and
Oakhill’s (1999) study of children and Long and Chong’s (2001) study of adults. Adults
routinely make inferences to establish local and global coherence (e.g., Albrecht &
O’Brien, 1993; Bloom, Fletcher, van den Broek, Reitz, & Shapiro, 1990; Nicol & Swinney,
1989; Sanders & Noordman, 2000). With regard to local coherence inferences, children are
capable of making them from an early age, but developmental improvements are clear.
Ackerman (1986) found that 6-year-olds were as sensitive as 9-year-olds to the need to
establish local coherence in short texts but made fewer local coherence inferences than
did 9-year-olds when required to support comprehension. Barnes, Dennis, and Haefele-
Kalvaitis (1996) demonstrated substantial developmental improvements in the ability to
make local coherence inferences between 6 and 11 years of age, with smaller gains
thereafter up to 15 years (the oldest age group in their study). Likewise, research
examining children’s ability to generate inferences to establish global coherence
demonstrates early sensitivity as well as developmental gains, with 4-year-olds making
fewer inferences about narrative themes and characters’ goals than 6-year-olds (Lynch et
al., 2008). These studies provide clear evidence that, despite early sensitivity to the
need to establish both local and global coherence when processing text, significant gains
in inference-making ability occur during early to middle childhood. When we examine the
wider literature on inference making in adults, as well as in children, we find evidence
that vocabulary and working memory influence an individual’s inference-making ability. We
next turn our attention to a consideration of these skills and how they might be related
to developmental improvements in inference making. Obviously, text comprehension could not
occur without knowledge of individual word meanings, and for that reason vocabulary is
routinely shown to be related to general measures of reading (Oakhill & Cain, 2012) and
listening comprehension (Florit, Roch, Altoe, & Levorato, 2009). Vocabulary is also
significantly correlated with measures of inference making in both children (Lynch et al.,
2008; Oakhill & Cain, 2012) and adults (Dixon, LeFevre, & Twilley, 1988). For local
coherence inferences, knowledge of word meanings may be particularly important when a
synonym, paraphrase, or category member refers back to an earlier mentioned object
(Perfetti, Yang, & Schmalhofer, 2008). In addition to knowledge of specific word meanings,
the production of some inferences also draws heavily on background knowledge and the
interrelations between words (Cain & Oakhill, 2014; Casteel, 1993). In the case of global
coherence inferences, one cannot infer that a furry animal that barks and likes going for
walks is a dog unless one possesses the requisite knowledge about dogs and their
characteristics. Thus, not just knowledge of individual word meanings but also rich
semantic networks with robust connections between the meanings of words associated by
topic may be important for easy and accurate inference making. Therefore, there are clear
mechanisms through which vocabulary may support both local and global coherence inference
making. Working memory refers to the memory systems used for the simultaneous storage and
processing of information (Baddeley & Hitch, 1974). Measures of verbal working memory
(sometimes referred to as verbal complex memory span) are more strongly related to reading
comprehension in young children than are measures that simply tap storage of verbal
information (or short-term span) (Leather & Henry, 1994). Furthermore, working memory
explains unique variance in general measures of listening and reading comprehension after
controlling for vocabulary in children between 4 and 10 years of age (Cain, Oakhill, &
Bryant, 2004; Florit et al., 2009; Seigneuric & Ehrlich, 2005). Working memory may be
particularly important for inference generation because a reader or listener needs to
maintain activation of previously processed information while relating this to the piece
of text currently being processed. Younger children might routinely fail to do so if their
working memory capacity limits the amount of information that they can store when
processing text. This may account for the observation that younger children tend to
process text in a piecemeal manner, not always making connections between ideas,
particularly if they are not presented in succession (Schmidt & Paris, 1983). However,
studies that have included assessments of working memory and either inference making or
more general reading comprehension within a developmental framework report contradictory
results. Chrysochoou and Bablekou (2010) found a reduction in the influence of working
memory on inference making between 5 and 9 years of age, whereas other work suggests that
the relation between working memory and reading comprehension either stays constant
between 7 and 10 years of age (Seigneuric & Ehrlich, 2005) or increases during that period
(Cain et al., 2004). One factor influencing the strength of any relation between inference
and working memory may be the nature of the materials; the influence of working memory on
inference making for 9- and 10-year-olds is strongest when the pieces of information
supporting the inference need to be integrated over large units of text (Cain, Oakhill, &
Lemmon, 2004). In the current study, we were interested in the contributions made by both
vocabulary and working memory to local and global coherence inferences in different age
groups. Recent work supports this focus by showing that from as young as 4 to 6 years,
higher level comprehension skills such as text integration (particularly relevant for
local coherence inferences) and knowledge accessibility (important for both inference
types but particularly for global coherence inferences) emerge as separate skills (Hannon
& Frias, 2012). To date, there is only one published study that has explored the relative
influences of both working memory and vocabulary to different types of inference making
(Chrysochoou, Bablekou, & Tsigilis, 2011). The two inference types studied by Chrysochoou
and colleagues (2011) were required to establish coherence in the text. They broadly map
onto the local and global coherence distinction that we focused on here. We note that the
authors referred to the latter as elaborative inferences, but on examination these appear
to be necessary to ensure a full and coherent understanding of the text as intended by the
authors of the original article (Cain & Oakhill, 1999). Chrysochoou and colleagues (2011)
found small, but significant, associations between complex working memory span and
inferences that were required for local coherence in their sample of 9-year-olds. However,
they found a much stronger association between working memory and inferences required to
establish global coherence. The relations between their measures of short-term span (e.g.,
measures of the phonological loop) and both types of inference were weak. Critically,
Chrysochoou and colleagues (2011) demonstrated that vocabulary fully mediated the
relations between working memory and the inferences required for local coherence but only
partially mediated the relations between working memory and the inferences required to
establish global coherence. One possible reason for this distinction is the way in which
vocabulary can support memory. The theory is that children and adults with richer
vocabulary knowledge have more accurate and available representations of words in their
long-term memory than those with poorer vocabulary knowledge, and this better knowledge
supports accurate maintenance of information in verbal working memory (Nation, Adams,
Bowyer-Crane, & Snowling, 1999; Walker & Hulme, 1999). Thus, vocabulary may be important
for inference making in two ways. First, vocabulary knowledge is important because
inferences involve word knowledge; local coherence inferences involve mapping between
synonyms and category exemplars, and global coherence inferences tap knowledge about the
interrelations between word meanings. Second, vocabulary knowledge may support inference
making because it can provide a boost to accurately maintain the contents of working
memory, necessary to aid the integration of information from different parts of the text.
In relation to the findings of Chrysochoou and colleagues (2011), the full mediation of
working memory by vocabulary for local coherence inferences may reflect the lower memory
demands associated with this type of inference, which involve integration between
successive sentences, and the partial mediation for global coherence inferences may
reflect the higher memory demands of global coherence inferences, which involve
integration of ideas throughout the text and also with background knowledge external to
the text. Another possibility for this distinction is that Chrysochoou and colleagues
(2011) used a single measure of receptive vocabulary, which is regarded by some as a
measure of the number of words known and which does not tap deeper knowledge of the
interrelations between words (Tannenbaum, Torgesen, & Wagner, 2006). We assessed
vocabulary in two ways to achieve a more complete assessment of this complex construct; we
used the same single word comprehension measure as Chrysochoou and colleagues and also a
measure that assessed knowledge of word networks (semantic fluency). We believed that this
broader conceptualization of vocabulary knowledge would provide a robust test of its
relation to inference making. The current study sought to build on previous research on
children’s inference making by looking specifically at the distinction between inferences
required to establish local and global coherence (a distinction that has not been examined
in previous work with younger age groups of children) with the aim to determine how
vocabulary and working memory influence this ability in 6- to 10-year-olds. Our review of
the literature indicates that both vocabulary and working memory will be associated with
inference making in this age range. We predicted that vocabulary would be more strongly
associated with global coherence inferences than with local coherence inferences because
the former rely on richer and better connected semantic networks, in line with Cain and
Oakhill (2014). We also predicted that memory would be more strongly associated with
global coherence inferences than with local coherence inferences because global coherence
inferences involve maintaining activation of a larger amount of text. Regardless of their
age, all children in our sample were presented with the same texts, which were read aloud
to them by the assessor. It is widely believed that the same skills underpin comprehension
of written and spoken text (Hoover & Gough, 1990). This is supported by research
demonstrating the role of inference for each (Barnes et al., 1996) and strong relations
between performance on reading and listening comprehension tasks when word reading ability
is suitably controlled (Cain, Oakhill, & Bryant, 2000; Kendeou, van den Broek, White, &
Lynch, 2009; Stothard & Hulme, 1992). Because we used the same texts, we expected to find
developmental improvements in inference making and the strongest relation between memory
capacity and inference making in the youngest age group, where the processing demands
would be greatest. In general, we expected stronger associations between inference making
and measures of complex memory span (tasks that tap both storage and processing) than
between inference making and short-term memory span measures (which tap only storage),
similar to the results found for 8- and 9-year-olds by Chrysochoou and colleagues (2011).
There are contradictory findings for the roles of vocabulary and memory; studies of 8- to
11-year-olds find a unique role for working memory in the prediction of concurrent reading
comprehension that is independent of vocabulary (Cain et al., 2004; Seigneuric & Ehrlich,
2005), whereas other work suggests that working memory has a unique role in the prediction
of reading comprehension, over and above vocabulary knowledge, for 5- and 7-year-olds but
not for 9-year-olds (Chrysochoou & Bablekou, 2010; Florit et al., 2009). A key aim of this
study was to determine whether vocabulary and working memory predicted unique variance in
inference making or whether any relation between working memory and inference making was
mediated by vocabulary as found by Chrysochoou and colleagues (2011; see also Dixon et
al., 1988, for work with adults). This finding is in contrast to studies of discourse
comprehension that identify a unique contribution for working memory on reading and
listening comprehension independent of vocabulary (Cain et al., 2004; Florit et al., 2009;
Seigneuric & Ehrlich, 2005). Full mediation would indicate that the relation between
working memory and inference making is due to the support that vocabulary provides for
maintaining activation of relevant information in memory. Thus, our analyses were
constructed to determine whether this relation exists across all ages for both types of
inference.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The participants were 130 children from schools in the northwest of England. Of this total
sample, 44 children were enrolled in Year 1 classrooms (5–6 years of age, M = 6;2
[years;months], SD = 4 months, range = 5;7–6;8; 26 boys and 18 girls), 43 were from Year 3
classrooms (7–8 years of age, M = 8;3, SD = 3 months, range = 7;9–8;8; 21 boys and 22
girls), and 43 were from Year 5 classrooms (9–10 years of age, M = 10;2, SD = 4 months,
range = 9;8–10;8; 24 boys and 19 girls). Consent was obtained from headteachers and
parents, and assent was received from children, prior to each assessment session. The
schools served socially mixed catchment areas. All children spoke British English as their
first language, and children with a statement of special educational needs did not take
part in the study.

<hs>  Materials and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

All children completed assessments of inference making, vocabulary, and memory. They were
assessed individually over four sessions, with each session lasting no longer than 15 min.

        <hss>Local and global coherence inferences</hss>

        Each child listened to four short stories modified from materials developed for
        another project (Language and Reading Research Consortium, in press) that were
        read aloud by the experimenter. The stories were 148 to 161 words in length. Each
        story had an episodic structure that began with a setting (to introduce
        characters, time, and/or place) and had categories of story units, including
        events, goals, attempts, outcomes, and/or reactions (Stein & Glenn, 1982). The
        Coh-Metrix Text Easability Assessor (Graesser, McNamara, & Kulikowich, 2011)
        metrics showed that the texts had high narrativity (the extent to which the text
        is story-like, M = 63%), had a high number of concrete and imageable content words
        (M = 94%), and were syntactically simple (M = 94%) but had low referential
        cohesion (M = 35%). The latter was to be expected because the texts were
        constructed to require inferential processing for adequate comprehension. Children
        were instructed to listen carefully to the stories so that they could answer the
        memory questions after each one. At the end of each story, children were asked
        four questions that tapped the ability to make local coherence inferences and four
        questions that tapped global coherence inferences. For each story, the four local
        coherence inferences required the listener to integrate information from two
        sentences in the text and the four global coherence inferences required the
        listener to understand motivations and infer themes, settings, or central
        character identity. Examples are provided in Table 1. A second rater categorized
        each of the 32 questions. There was 94% agreement for the local versus global
        coherence distinction. The two questions categorized differently were resolved
        through discussion. Cronbach’s alpha on this task for this sample of children was
        adequate (α = .77). The order of the questions followed the order of information
        presentation in the story.1 If a child gave an incomplete or vague answer, the
        experimenter prompted the child. This was either a repetition of the question or
        encouragement to be more specific (see Table 1 for examples). Each inference
        question was scored as correct, correct after a prompt, or incorrect. Correct
        responses were awarded 2 points for a full response and 1 point for a partial
        response. When a child did not provide an acceptable response to a global
        coherence question, the child’s background knowledge for that information was
        checked with a follow-up question (see Table 1). Although both local and global
        inferences draw on relevant background knowledge, the global coherence inferences
        examined in the current study were more knowledge dependent in that they drew on a
        range of facts to work out a setting or a character’s identity. Therefore, we made
        additional checks that children possessed the necessary background knowledge for
        this inference type so that we could determine whether knowledge differences were
        the source of any developmental differences found. There were very few instances
        where children did not have the required background knowledge; only one child in
        each year group answered one background knowledge question incorrectly (<0.3%). An
        adjusted total score was calculated taking into account only those items for which
        the child possessed the relevant background knowledge. This was a proportionate
        score based on the child’s actual score and the maximum possible score (for only
        those items where the background knowledge was known). To enable ease of
        comparison, the raw correct scores for the local coherence questions are reported
        as proportions correct.

        <hss>Vocabulary</hss>

        Each child completed two measures of vocabulary, one that tapped breadth of
        vocabulary knowledge and one that tapped depth of vocabulary knowledge, in order
        to obtain a more complete assessment of this construct. The British Picture
        Vocabulary Scale–Third Edition (BPVS; Dunn et al., 2009) provided a measure of
        breadth of vocabulary knowledge. Each child was asked to select one of four
        pictures that best showed the meaning of a word spoken aloud by the experimenter.
        The test was administered and scored according to the guidelines in the manual.
        Internal consistency was not reported in the manual. Therefore, Cronbach’s alpha
        was calculated for this sample of children (α = .97). The Word Associations
        subtest from the Clinical Evaluation of Language Fundamentals–Fourth Edition
        (CELF-IV; Semel, Wiig, & Secord, 2006) tapped semantic fluency and depth of
        vocabulary knowledge. In each trial, the child was asked to provide as many words
        as possible in 1 min from a specified category (items of clothing that people
        wear, animals, foods that people eat, or jobs that people do). The first category
        was a practice trial. The test was administered and scored according to the
        manual. We could not calculate internal consistency for this task, but the
        test–retest reliability value reported in the manual for this age range is good
        (.96–1.00).

        <hss>Working memory measures</hss>

        Each child completed four assessments of verbal working memory. There were two
        measures of the ability to store information (simple span) and two measures of the
        ability to store and process information (complex span). Internal consistency was
        not reported in the manual for the working memory measures, so it was calculated
        for the current sample.

            <hss>Simple span measures</hss>

            Each child completed the Word List Recall and Digit Recall subtests from the
            Working Memory Test Battery for Children (WMTB-C; Pickering & Gathercole,
            2001). In these tasks, children were asked to recall either lists of words or
            strings of digits spoken by the experimenter. The tasks were administered and
            raw scores were calculated according to the test manual. There were six trials
            at each level of difficulty. Once a child had correctly completed four of the
            trials on a level, the assessor moved on to the next level, as directed by the
            manual. The child received credit for any trials not completed on the previous
            level. The assessor stopped testing once three trials on a level were answered
            incorrectly. Raw scores (total number of trials correct, including those given
            credit for as a result of moving on to the next level) and standardized scores
            are presented in Results. Cronbach’s alpha based on the current sample of
            children was good (α = .85) for the word span and excellent (α = .90) for the
            digit span.

            <hss>Complex working memory span</hss>

            Each child completed the Listening Recall and Counting Recall subtests from
            the WMTB-C (Pickering & Gathercole, 2001). In the Listening Recall task,
            children listened to short sentences, made a true/false judgment about each
            one, and then recalled the final word in each one. This test began with one
            sentence and increased in difficulty by the addition of sentences in each set
            (two sentences, three sentences, etc.). In the Counting Recall task, children
            counted the number of dots on a page and recalled the total. The test
            increased in difficulty in that children were required to count more than one
            pattern of dots over successive pages and then to recall the totals in the
            correct order. Both tests were administered according to the manual and
            followed the same progression and discontinuation rules as described above.
            Cronbach’s alpha based on the current sample was good (α = .88) for both the
            listening span and counting span (α = .90).

<h>RESULTS</h>
-------

The results are reported in two sections. The first section concerns developmental
comparisons of performance on all tasks. The second section concerns analyses that explore
the interrelations between vocabulary, working memory, and inference performance. Before
analysis, the “Q–Q plots” for all measures were examined separately for each year group.
Q–Q plots provide a means of assessing deviation from a normal distribution (Cohen, Cohen,
West, & Aiken, 2003). The plots indicated that the data were normally distributed. The
data distributions were also checked for outliers. All analyses were run on the original
dataset and also on a dataset that was adjusted to remove outliers following the
recommendations of Tabachnick and Fidell (2007), whereby outlier data points are changed
to the next highest/lowest (non-outlier) number. Less than 1% of datapoints were replaced
in this way. The patterns of analyses were the same for both analyses, and so the analyses
reported here were those conducted on the original data.

<hs>  Developmental comparisons on all measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First we report the performance on the inference task, followed by performance on the
vocabulary and memory measures.

        <hss>Performance on local and global inference questions</hss>

        The proportion of total correct items (adjusted to take general knowledge into
        account, as described above) for local and global coherence inferences were the
        dependent variables in the analyses reported in this section. Before analysis, the
        data were arcsine transformed, as is recommended to stabilize variance and
        normalize proportional data (Sheskin, 2003). The pattern for the analyses of the
        raw scores was the same as that of the arcsine-transformed scores, so the analyses
        reported here are those conducted on the raw proportionate scores. Two analyses
        are reported below. In the first analysis, the dependent variable is performance
        when the question was first asked. In the second analysis, the dependent variable
        is performance that includes correct responses provided after a prompt. The mean
        proportions of correct responses on the local coherence and global coherence
        inference questions are shown in Table 2.

            <hss>Performance on local and global inference questions: First responses</hss>

            A mixed factor ANOVA with age (6, 8, or 10 years) as a between-participants
            factor and inference type (local or global) as a within-participants factor
            was conducted. There was a significant main effect of age, F(2, 127) = 14.78,
            p < .001, ηp2 = .19. Post hoc Tukey tests (p < .05) indicated that the 6-year-
            olds obtained significantly lower scores than the 8- and 10-year-olds and that
            the 8-year-olds obtained significantly lower scores than the 10-year-olds (Ms
            = .58, .65, and .74 in order of increasing ages). There was also a significant
            main effect of inference type, F(1, 127) = 106.89, p < .001, ηp2 = .46,
            because the children performed best on the global inference questions (Mlocal
            = .58, Mglobal = .73). The interaction was not significant, F(2, 127) < 1.0,
            ns.

            <hss>Performance on local and global inference questions: After prompts</hss>

            As is evident from Table 2, performance improved with the use of prompts. The
            difference between unprompted and prompted scores (collapsed across age group)
            was significant for both types of inference: local, t(129) = 15.72; global,
            t(129) = 12.08; ps < .001. A mixed factor ANOVA with the same design as before
            was conducted on the scores that included prompted responses. The pattern of
            results was the same as for the analysis of unprompted scores, with main
            effects of age, F(1, 127) = 14.21, p < .001, ηp2 = .18, and inference type,
            F(1, 127) = 127.82, p < .001, ηp2 = .50, and no interaction between the
            factors, F(2, 127) < 1.0, ns.

        <hss>Performance on vocabulary and working memory measures</hss>

        The mean raw scores (total number of items correct for the vocabulary measures and
        total number of trials correct for the word, digit, listening, and counting
        working memory measures) for each age group are reported in Table 3. The mean
        standardized scores were available for all measures with the exception of the Word
        Associations task, for which standardized scores are not reported in the manual.
        The standardized scores were all within an age-appropriate range. Criterion
        reference scores were available for each age group on the Word Associations task,
        and all children met the minimum criterion score for their age. A small number of
        children (n = 10) had missing data due to absence at a testing session. A one-way
        ANOVA on the raw scores for each measure was conducted with age group as a
        between-participants factor. As predicted, there were age differences for all
        measures shown by significant F values (see Table 3; all ps < .001). Post hoc
        Tukey tests (p < .05) revealed that for most measures there were significant
        differences in performance between each successive age group in the following
        order: 6 < 8 < 10 years. The two exceptions were the Word Associations and
        Counting Recall tasks. Here, both the 8- and 10-year-olds obtained significantly
        higher scores than the 6-year-olds, but these two older groups did not differ from
        each other. The 6-year-olds performed poorly on both complex span measures of
        working memory, with 27.3% of these children not passing the first level of the
        Listening Recall task and a further 61.4% not progressing beyond the one-span
        level. For the Counting Span task, 22.7% did not progress beyond the one-span
        level. This is in line with Gathercole, Pickering, Ambridge, and Wearing’s (2004)
        observation that the task demands for these complex span measures are too high for
        very young children and that these complex span measures might not be sensitive to
        individual differences. On that basis, the complex span tasks were not included in
        further analyses for this age group.

<hs>  Correlations between inference, vocabulary, and working memory</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First, zero-order correlations were conducted for each age group separately to examine the
interrelations between variables. Composite scores were produced to ensure a broad and
comprehensive indicator of the vocabulary and memory constructs: vocabulary (BPVS and Word
Associations), simple memory span (Word List Recall and Digit Recall), and complex memory
span (Listening Recall and Counting Recall). The working memory composites support the
distinction between tasks tapping short-term storage in the phonological loop and those
tapping the central executive (Pickering & Gathercole, 2001). Reducing the number of
measures to form composites also met the requirement of 10 data points per predictor for
the multiple regression analyses reported next (as recommended by Tabachnick & Fidell,
2007). The scores on the first response to the inference questions were used. All scores
were converted to z scores (for each age group separately) to ensure that measures were on
a comparable scale (see Table 4). A small number of children (n = 10) had missing data on
one of the two subtests used to produce the composites. In these cases, the mean
performance on the missing subtest for the relevant age group was used so that a composite
could still be calculated for each of these children. This amounted to 18 data points in
total (2.36% of all data points).2 Because of the small sample size, we discuss
correlations both in terms of statistical significance and in relation to effect sizes
where .10 represents a small effect, .30 a moderate effect, and .50 a large effect (Field,
2005). In all age groups, the two inference measures were significantly correlated and the
effects were moderate to large. Of note, vocabulary was more strongly related to inference
making than was memory. The vocabulary composite was significantly correlated with local
coherence inference making for the 6- and 8-year-olds and with global coherence inference
making for all age groups. All effect sizes were large. For the youngest age group, simple
span was significantly correlated with local coherence inference making, with a moderate
effect size, but a significant relation was not found for the older age groups. The simple
and complex working memory measures (where used) were significantly correlated with global
coherence inference making for all age groups, where the effects were moderate (with the
exception of simple span for the 8-year-olds, where the effect was small and did not reach
significance).

<hs>  Do working memory and vocabulary each explain independent variance in inference making in different age groups?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A series of multiple regression analyses were conducted to determine the relative
contributions of memory and vocabulary to the two types of inference. Fixed-order
hierarchical multiple regression analyses were conducted for each inference type and each
age group separately. Vocabulary, simple span, and complex span (8- and 10-year-olds only)
were entered as predictors in the analyses. Simple span was added at the first step,
followed by complex span (8- and 10-year-olds only) and vocabulary. Previous research has
found that vocabulary mediates the relationship between memory and inference generation
(Chrysochoou et al., 2011); therefore, the influence of the memory measures before the
inclusion of vocabulary could be determined using this order of variables. In addition,
complex span tasks have been found to be more highly related to reading comprehension than
simple span tasks (Daneman & Merikle, 1996). Therefore, this order of memory variables
also ensured that any influence of simple span could be identified. Table 5 shows the
results for the multiple regression analyses for the local coherence inferences. For local
coherence inferences, simple span and vocabulary explained variance in performance for the
6-year-olds, although (as indicated by the beta values) only vocabulary was a significant
predictor when both variables were included in the model (see Table 5). For the 8-year-
olds, only vocabulary significantly accounted for significant variance in local coherence
inference making. In contrast, for the 10-year-olds, none of the measures significantly
explained variance. For global coherence inferences, simple span and vocabulary explained
additional variance in performance for the 6-year-olds, although (similar to the local
coherence analyses) only vocabulary predicted unique variance when both variables were
taken into account (see Table 6). For the 8-year-olds, complex span and vocabulary
significantly accounted for additional variance in global coherence performance, although
(again) only vocabulary was a significant predictor when all variables were taken into
account. For the 10-year-olds, simple span and vocabulary explained additional variance in
global coherence performance, but only vocabulary significantly predicted unique variance.

<hs>  Does vocabulary mediate the influence of working memory on inference making in different age groups?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As outlined in the Introduction, the literature indicates that vocabulary may mediate the
influence of memory on inference making. The data in Tables 5 and 6 demonstrate that both
vocabulary and short-term memory made significant contributions to local inference making
in the 6-year-olds and that vocabulary and memory (short-term span for 6- and 10-year-olds
and complex span for 8-year-olds) predicted global inference making in all age groups. The
analyses reported next assess whether or not vocabulary mediated the influence of memory
on inference making. The total effect of working memory on inference making is presented
in Fig. 1, the mediation path assessed is presented in Fig. 2, and the labels used to
denote each path are also referred to in Tables 7 and 8. A set of mediation analyses was
conducted based on the causal steps strategy (see Baron & Kenny, 1986) and Preacher and
Hayes’s (2008) bootstrap (1000) resample procedure using an SPSS macro for this procedure,
which gives point estimates (PEs) and bias-corrected confidence intervals (BC CIs) for the
indirect effect. Where zero is not included in the 95% confidence interval for the
mediated effect, the effect is statistically different from zero and mediation is
confirmed. For local coherence inferences, simple span predicted significant variance in
local coherence inference making for the 6-year-olds (see Table 5). The mediation analyses
demonstrated that vocabulary mediated its effect; the effect of working memory on
inference making (c′ path) was not significant after taking vocabulary into account.
Critically, mediation was confirmed because zero was not included in the 95% confidence
interval for the mediated effect (see Table 7). Mediation analyses were not conducted for
the 8- and 10-year-olds because the working memory measures did not predict unique
variance in local coherence scores (see Table 5). For global coherence inferences,
vocabulary mediated the relationship between working memory and inference for all age
groups. As shown in Table 6, although simple span predicted inference for the 6- and
10-year-olds, the effects of working memory on inference were mediated by vocabulary at
both ages because the path coefficient for the regression of this working memory measure
on inference was no longer significant when vocabulary was entered into the equation (c′
path). Mediation was confirmed because zero was not included in the 95% confidence
interval for the mediated effect (see Table 8). For the 8-year-olds, complex span was
related to global coherence inference making (see Table 6). However, as for the analysis
for the two other age groups above, vocabulary mediated this effect because the path
coefficient for the regression of complex span on inference was no longer significant when
vocabulary was entered into the equation (c′ path). The mediated effect of complex span
via vocabulary was significant because zero was not included in the 95% confidence
interval (see Table 8).

<h>DISCUSSION</h>
----------

The main aims of this study were to explore developmental differences in local and global
coherence inference making and to determine the extent to which vocabulary and working
memory influenced performance. In line with expectations and previous research, the
6-year-olds were able to generate these inferences from short narrative text, but
significant improvements were found with age. Critically, our work indicates that
vocabulary and working memory differed in the extent to which they predicted performance
on both types of inference between age groups. Specifically, there was evidence that
vocabulary knowledge was critical both independently and through its role in supporting
the memory processes required for global inference making in particular. First, let us
consider performance on the local coherence inferences. In line with previous research,
performance improved with age (Ackerman, 1986). To integrate information between sentences
in order to establish local coherence, children needed to understand and make use of
pronouns and also synonyms. The previous literature on pronoun and synonym comprehension
has focused on individual differences in relation to measures of reading comprehension
skill in general. This body of work finds that children who differ in reading
comprehension skill differ in their understanding and use of pronouns and synonyms to
integrate different propositions in a text (Ehrlich & Remond, 1997; Megherbi & Ehrlich,
2005; Oakhill, 1983; Oakhill & Yuill, 1986; see also Cain & Nash, 2011, for developmental
improvements in knowledge of other cohesive devices). We propose that poorer use of these
signaling cues may have limited local coherence inference making for the children in our
study and could, in part, explain the developmental differences. The source of the poorer
use of these signals appears to be different for the 6-, 8-, and 10-year-olds. Vocabulary
was a particularly important predictor of local coherence inference making for the two
youngest age groups, a finding supported by previous research on inference making
(Chrysochoou & Bablekou, 2010; Chrysochoou et al., 2011) and reading comprehension in
general (Seigneuric & Ehrlich, 2005). The current study is the first to show that
vocabulary knowledge is specifically related to 6- to 10-year-olds’ ability to make
inferences to establish local coherence. We cannot determine whether children lacked the
category-relevant knowledge, failed to activate this, and/or failed to use this
information during text processing from our data. However, we believe that a lack of
relevant knowledge per se is an unlikely source of these developmental differences because
few children failed the background knowledge check questions for the global inference
measures. Thus, we propose that speed of knowledge retrieval and integration during text
presentation are more likely sources of failure to establish local coherence (as proposed
by Perfetti et al., 2008, for adults). We are currently exploring online text processing
in these age groups to examine these possibilities. Although the zero-order correlations
and regression analyses indicated that working memory played a role in the determination
of the youngest children’s local coherence inference performance, working memory was not a
unique predictor after taking vocabulary knowledge into account. The youngest children’s
poorer memory skills may have limited their ability to retain the information from two
successive sentences in order to integrate their meanings when constructing their
situation model of the text. However, the mediation analysis confirmed that for the
6-year-olds the influence of memory was fully mediated by vocabulary, similar to the
findings in other work with older children (Chrysochoou et al., 2011). Children with
richer vocabulary knowledge will be better able to retain information in verbal working
memory (Cain, 2006; Nation et al., 1999), which supports our finding of a mediation
effect. A complex interaction between vocabulary and verbal working memory may underpin
developmental differences in this type of inference making, and further work is needed to
test the proposal that speed of knowledge retrieval and/or maintenance of accurate
representations of meaning were the source of local coherence inference difficulties. In
contrast to the pattern of prediction for the youngest age groups, neither vocabulary nor
working memory explained performance on the local coherence inferences for the oldest age
group. The older children had superior memory and vocabulary skills, which may have been
sufficient for them to establish local coherence. However, the 10-year-olds were not at
ceiling on the task, so this explanation is unsatisfactory. One possibility is that they
had sufficient vocabulary and working memory skills to perform the task, but additional
gains on these questions could come from strategic processing. For example, older children
may have greater awareness of which information in a text is critical for the generation
of local and global inferences. We are currently investigating developmental differences
in children’s use of text information in the generation of both inference types to explore
this issue further. Work with poor comprehenders (Yuill & Oakhill, 1988) also shows that
children can be taught how to make inferences and that this boosts both inference making
skill and reading comprehension. We now turn to a discussion of the findings on global
coherence inferences. As predicted, and in line with other work, there were developmental
improvements on the global coherence inferences (Chrysochoou & Bablekou, 2010; Schmidt &
Paris, 1983). It has been suggested that younger children tend to view statements in a
text as independent pieces of information and do not always link successive ideas
together, particularly if they are not presented in succession (Schmidt & Paris, 1983).
The local coherence inferences were signaled, indicating when successive pieces of text
should be linked. In contrast, the global coherence inferences were not signaled and
typically required the listener to link information across a number of different
nonconsecutive sentences. Thus, one reason for failing to generate these inferences is a
piecemeal processing style. Another reason is the processing demands of this type of
inference. The global coherence inferences required the integration of information
presented in different nonconsecutive sentences. The association between working memory
and performance on this type of inference probably arose because of this demand on memory.
Age differences in global coherence inference ability persisted even when differences in
the necessary background knowledge were controlled (indeed, there were only three
instances where a child failed to correctly answer a global coherence inference and lacked
the necessary knowledge). Thus, this study adds to a growing body of work demonstrating
that the ability to make coherence inferences is not solely dependent on having the
relevant background knowledge (Barnes et al., 1996; Cain & Oakhill, 1999; Cain, Oakhill,
Barnes, & Bryant, 2001). The findings support the idea that children need to know when and
how to draw on background knowledge during text comprehension and that this ability might
improve with age (Cain & Oakhill, 1999). Our work advances our understanding of the
development of inference making by demonstrating that at all three ages, vocabulary was
the most important factor explaining performance on the global coherence measures and
vocabulary fully mediated the relationship between global coherence inference making and
working memory. This finding is supported by previous work assessing this inference type
with older children (Chrysochoou et al., 2011). Thus, although children demonstrated
relevant background knowledge when assessed, they did not always use this to generate or
encode the inference. Furthermore, the information to be linked was typically presented in
words that were semantically associated; for example, “pet,” “furry,” “playful,” and
“kennel” were all used to indicate that the story was about a dog. It may be that, for
some children, the associations between these links were not sufficiently strong to
activate the concept to which they were all related. The developmental improvements found
in vocabulary knowledge and the richness of semantic networks, in which the associations
between co-occurring concepts are encoded (Metzger et al., 2008), may assist in inference
making that relies on background knowledge. Future work, using online measures to assess
whether children use successive pieces of information, may help to further our
understanding of the production of this inference type. In this study, children made a
greater number of global coherence inferences than local coherence inferences, in contrast
to other work that has compared the generation of these inference types during reading
(Cain & Oakhill, 1999). Although the questions tap different elements of the story and,
therefore, are not directly comparable, this finding requires consideration. One
explanation could be that the global coherence inferences (particularly those that were
thematic in nature, e.g., the setting of a story or a character’s identity) were more
foregrounded because the text made a number of references to these elements. Support for
this explanation comes from work on the centrality effect, which finds that information
that is more central to the overall story meaning is more likely to be remembered than
information that is peripheral to overall story meaning (e.g., see Albrecht & O’Brien,
1993; Miller & Keenan, 2009). Future work comparing these inference types should consider
this difference. There are several educational implications that stem from this work.
First, performance for all age groups on both types of inference improved after prompting
underspecified responses. This finding identifies prompting as a useful means to
demonstrate a child’s potential (or competence) and also as a tool to indicate the
standard of coherence required of comprehension (van den Broek, Risden, & Husebye-Hartman,
1995). Second, the finding that all age groups made both global and local coherence
inferences indicates that children of this age engage in the processing required to
construct a representation of the entire text rather than engaging in piecemeal line-by-
line processing. Third, the importance of vocabulary knowledge to inference making and the
way in which vocabulary mediated the relations between working memory and inference making
supports the critical role of background knowledge in text comprehension (Eason, Goldberg,
Young, Geist, & Cutting, 2012). It also lends weight to other research proposing that
children need to be taught how to use both the text and background knowledge as sources of
information to guide inference generation and text comprehension (Brandão & Oakhill, 2005;
Raphael & Wonnacott, 1985). There are several limitations to this work that need to be
addressed in future work in order to understand fully the roles of vocabulary and working
memory in children’s inference making. First, although our sample size had adequate
statistical power to detect the contributions of key skills, replication with a larger
sample size is required to confirm the developmental differences. Second, we did not
include independent assessments of strategic knowledge, so we do not know to what extent
different age groups were aware of different sources of knowledge and strategies that may
influence language comprehension (Brandão & Oakhill, 2005). Third, although we drew on a
large literature indicating that the same processes underpin the comprehension of written
and spoken text, we note the evidence for a greater influence of attention on listening
comprehension (Cain & Bignell, 2014). Future work should consider the extent to which this
might specifically affect inference making. Finally, all of our measures were offline.
Language comprehension is a dynamic process. Thus, it is essential to investigate how both
vocabulary and memory (both short-term and working memory) interact during online language
processing to identify when and where they influence the inference-making process. We are
pursuing this line of inquiry in ongoing work. In summary, few studies have experimentally
contrasted children’s ability to generate different types of inference, and none has
developmentally explored the unique roles of vocabulary and working memory in local and
global inference making. This study has highlighted different roles for vocabulary and
working memory in relation to these two types of inference at different ages. This not
only adds to our understanding of inference development but also indicates factors that
may limit language comprehension in the classroom.


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<ART>Children's understanding of first- and third-person perspectives in complement clauses and false-belief tasks
================================================================================

Authors: Silke Brandt, David Buttelmann, Elena Lieven, Michael Tomasello
DOI: 10.1016/j.jecp.2016.03.004
Year: 2016  |  Pages: 131-143
ASJC codes: 3204, 3205
Keywords: Complement clauses, Epistemic modality, False belief, First-language acquisition, Mental verbs, Theory-of-mind development

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

De Villiers (Lingua, 2007, Vol. 117, pp. 1858–1878) and others have claimed that children come to understand false belief as they acquire linguistic constructions for representing a proposition and the speaker's epistemic attitude toward that proposition. In the current study, English-speaking children of 3 and 4 years of age (N = 64) were asked to interpret propositional attitude constructions with a first- or third-person subject of the propositional attitude (e.g., “I think the sticker is in the red box” or “The cow thinks the sticker is in the red box”, respectively). They were also assessed for an understanding of their own and others’ false beliefs. We found that 4-year-olds showed a better understanding of both third-person propositional attitude constructions and false belief than their younger peers. No significant developmental differences were found for first-person propositional attitude constructions. The older children also showed a better understanding of their own false beliefs than of others’ false beliefs. In addition, regression analyses suggest that the older children's comprehension of their own false beliefs was mainly related to their understanding of third-person propositional attitude constructions. These results indicate that we need to take a closer look at the propositional attitude constructions that are supposed to support children's false-belief reasoning. Children may come to understand their own and others’ beliefs in different ways, and this may affect both their use and understanding of propositional attitude constructions and their performance in various types of false-belief tasks.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

A large number of studies have shown that language plays a facilitative role in children’s
development of false-belief understanding (for overviews, see Astington & Baird, 2005;
Milligan, Astington, & Dack, 2007). However, it is still unclear which aspects of language
are responsible. Some researchers have looked to discourse because children must
constantly confront mismatches between what they and their interlocutor know or do not
know for pragmatically appropriate communication (e.g., Harris, 1996, 1999; Peterson &
Siegal, 2000; Tomasello & Rakoczy, 2003). Others have looked to the more representational
aspects of language, in particular (a) children’s mastery of mental state terms, such as
think and know (e.g., Bartsch & Wellman, 1995; Olson, 1988; Ruffman, Slade, & Crowe,
2002), and (b) children’s mastery of propositional attitude constructions in which these
mental state terms prototypically occur, such as I think that he will be late again (e.g.,
de Villiers & de Villiers, 2000; Hale & Tager-Flusberg, 2003; Lohmann & Tomasello, 2003;
Low, 2010). In the remainder of this article, we use linguistic terminology and refer to
these propositional attitude constructions as complement-clause constructions or just
complements. These complement-clause constructions contain a main clause expressing the
attitude toward a proposition (e.g., I think) and a subordinate clause expressing that
proposition (e.g., he will be late again). In the current study, we took a closer look at
children’s understanding of these complement-clause constructions and the parallel
development of their false-belief understanding. Around the age of 4 years, children
typically start to pass explicit tests of false belief (Wellman, Cross, & Watson, 2001).
To investigate whether this developmental achievement is equally supported by different
kinds of complement-clause constructions, we compared 3- and 4-year-olds’ comprehension of
complement-clause constructions with first- and third-person subjects in the main clause
(henceforth, first-person complements, such as “I think the sticker is in the red box”,
and third-person complements, such as “The cow thinks the sticker is in the red box”). We
further investigated how the same children perform in tasks testing their understanding of
their own and others’ false beliefs. Our main hypothesis was that third-person complements
are more tightly related to false belief because they are more likely to encode genuine
references to mental states. Linguistic research suggests that whereas first-person
complements can refer to mental states, they are also regularly used as epistemic
parentheticals, which are produced to alert the listener to the relative (un)certainty of
a proposition. Phrases like I think can be translated as maybe (e.g., Thompson & Mulac,
1991; Verhagen, 2005). In other words, first-person complements are ambiguous because they
can either refer to mental states or function as (un)certainty markers (see also Manson,
2002). Moreover, even when used as epistemic parentheticals, first-person complements are
ambiguous on another level. That is, a phrase like I think in I think it’s in the red box
can express either certainty or uncertainty, and it has been suggested that children up to
the age of 5 years treat I think as if it means I know (e.g., Bassano, 1985; Miscione,
Marvin, O’Brien, & Greenberg, 1978; Naigles, 2000). Therefore, first-person complements
are highly ambiguous, and this ambiguity may affect the way in which children interpret
them and the way in which they are related to their false-belief understanding.

<hs>  Production of complement-clause constructions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The idea that first-person complements do not necessarily refer to mental states is
supported by studies of spontaneous speech demonstrating that children produce first-
person complements considerably before they typically show an explicit understanding of
false belief. When Diessel and Tomasello (2001) looked at young English-speaking
children’s production of complement clauses, they found that at around the age of 3 years
children used many mental verbs only in the first person, as in I think it’s in there (see
also Bloom, Rispoli, Gartner, & Hafitz, 1989). Following functional linguists (e.g.,
Thompson & Mulac, 1991; Verhagen, 2005), they argued that in this case the I think phrase
is not being used to refer to a mental state or mental activity but rather is being used
as a kind of epistemic marker to alert the listener to the speaker’s relative uncertainty
(for similar findings in German children’s spontaneous speech, see Brandt, Lieven, &
Tomasello, 2010).

<hs>  Comprehension of complement-clause constructions and false belief</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To investigate the developmental gap between children’s production of first-person
complement-clause constructions at around the age of 3 years (e.g., Diessel & Tomasello,
2001) and their successful performance in explicit false-belief tests at around the age of
4 years (Wellman et al., 2001), Moore, Bryant, and Furrow (1989) and Moore, Pure, and
Furrow (1990) tested whether and when young English-speaking children correctly
interpreted first-person complements and whether they understood them before they passed
explicit false-belief tests. Moore and colleagues (1989) developed a hidden-object task
where two puppets indicated which of two boxes contained some candy. The puppets produced
first-person complements only. For example, one puppet said I think it’s in the red box,
and then the other puppet said I know it’s in the blue box. In this case, children who
understood these verbs and sentence types were expected to pick the blue box. Moore and
colleagues (1989) contrasted three mental state verbs: guess, think, and know. Overall,
3-year-olds performed at chance level, whereas 4-year-olds tended to perform at above
chance level but still performed worse than 6- and 8-year-olds. Looking at the think–know
contrast in particular, the 3-year-olds, on average, went for the correct box in 2 of 4
trials (M = 2.07), whereas the 4-year-olds, on average, went for the correct box in 3 of 4
trials (M = 3.14). Moore and colleagues (1990) showed that, in addition, 4-year-olds’
performance in this hidden-object task was strongly correlated with their performance in
various explicit tests of false belief. These findings suggest that, even though children
produce first-person complements with mental verbs before they show an explicit
understanding of false belief, their comprehension of first-person complements develops at
the same time as they start to show an explicit understanding of false belief. A similar
developmental pattern and dissociation between production and comprehension has been
observed in children’s use and understanding of epistemic modals. Like first-person
complements, modal verbs, such as must and will, are ambiguous. For example, must can
express necessity (e.g., you must go to bed now) or epistemic modality (e.g., saying that
must be the postman on hearing the doorbell). Studies looking at children’s production and
comprehension of modal verbs suggest that children first use them to express notions like
necessity (e.g., Wells, 1979). At around the age of 3 years, they start using the same
verbs to express epistemic modality in apparently appropriate contexts. However, when
children are tested on their comprehension of the epistemic meaning of modal verbs, they
do not seem to understand them in any systematic way until the age of 4 or 5 years, and
Papafragou (1998) suggested that children’s full understanding of the epistemic functions
of modal verbs depends on their theory-of-mind understanding (see also Moore, Pure, &
Furrow, 1990). For mental verbs and complement clauses, it has been suggested that
children’s comprehension and correct use of the more complex (i.e., mental state)
functions do not just depend on, but also support, their theory-of-mind development (e.g.,
Astington & Baird, 2005; de Villiers, 2007; Milligan et al., 2007). In the current study,
we explored the possibility that children’s theory-of-mind development is mainly
associated with children’s understanding of third-person complements. This assumption is
suggested by a number of studies that found that caregivers’ talk about their own mental
states (e.g., I think this is a golf ball) shows weaker links to children’s false-belief
understanding than their talk about others’ mental states, including those of the children
(e.g., you think this is a golf ball) (Adrián, Clemente, & Villanueva, 2007; Booth, Hall,
Robison, & Kim, 1997; Howard Gola, 2012; Taumoepeau & Ruffman, 2006). Howard, Mayeux, and
Naigles (2008) also found that mothers’ use of first-person complements does not support
children’s ability to systematically distinguish between the epistemic functions of I
think, expressing relative uncertainty, and I know, expressing certainty. This is probably
due to the fact that, when used with first-person subjects, mental verbs (such as think
and believe) can express either certainty or uncertainty. For example, when a child hears
an utterance like I think it’s bedtime now from their mother, the mother is pretty certain
that it indeed is bedtime (cf. Howard et al., 2008; Naigles, 2000). In this case, the
meaning of I think cannot easily be distinguished from the meaning of I know (see also
Bassano, 1985; Miscione et al., 1978). Howard and colleagues (2008) found that in the
linguistic input of 3- and 4-year-old English-speaking children, more than half of the
phrases containing the verb think were used to express certainty rather than uncertainty,
that think was most often used with first-person subjects, and that these phrases did not
directly support children’s understanding of false belief and the epistemic functions of
mental verbs. To summarize, previous research suggests that first-person complements do
not necessarily refer to mental states, and thus their use in children’s own language and
in their input does not directly support children’s false-belief understanding. Neither
does the everyday use of first-person complements seem to support children’s understanding
of the semantics of mental verbs and the complement-clause constructions in which these
verbs are used (Howard et al., 2008). What has not been investigated yet is (a) whether
young children find it easier to distinguish the semantics and epistemic functions of
mental verbs when they are used in third-person complements (e.g., she thinks the sticker
is in the red box vs. she knows the sticker is in the blue box) as opposed to first-person
complements and (b) how young children’s understanding of third-person complements is
related to their false-belief understanding.

<hs>  First-person versus third-person complements and false-belief understanding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the current study, we modified the hidden-object task (cf. Moore, Bryant, & Furrow,
1989) to directly compare 3- and 4-year-olds’ comprehension of first- and third-person
complements. For example, in the first-person version, one puppet said I think the sticker
is in the red box, and the other puppet said I know the sticker is in the blue box. In the
third-person version, the experimenter spoke for the puppets: The cow thinks the sticker
is in the red box. The pig knows the sticker is in the blue box. In addition, we used a
more balanced set of false-belief tasks that allowed us to directly compare children’s
understanding of their own and others’ false beliefs and how this relates to their
understanding of first- and third-person complements. Based on the assumption that phrases
like I think in first-person complements can express either certainty or uncertainty
(e.g., Howard et al., 2008), we expected children to perform worse on the first-person I
think–I know contrast than on the third-person the cow thinks–the pig knows contrast.
Based on the assumption that first-person complements can either refer to mental states or
function as (un)certainty markers (e.g., Diessel & Tomasello, 2001), we also expected
stronger developmental associations between third-person complements and false-belief
understanding than between first-person complements and false belief.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The children were recruited through a child participant database and tested in a quiet
room at the university of a medium-sized English city. In total, 32 young 3-year-olds (M =
3 years 4 months, range = 3;1 [years;months] to 3;5, 17 girls) and 32 young 4-year-olds (M
= 4 years 4 months, range = 4;1 to 4;4, 15 girls) participated in the study. One
additional 3-year-old was tested but needed to be excluded from the analyses because she
failed the pretest (described below). All children were English-speaking monolinguals.
None of the participants had any known language impairment.

<hs>  Design and materials</hs>
  ~~~~~~~~~~~~~~~~~~~~

All children started with the hidden-object task (cf. Moore et al., 1989) and did four
false-belief tests afterward. As described in more detail below, we used the classic
unexpected content and change of-location tests (Perner, Leekham, & Wimmer, 1987; Wimmer &
Perner, 1983) as well as a new version of the change-of-location test, which tests
children’s understanding of their own false belief (Buttelmann, 2016). In the hidden-
object task, we had two conditions that were tested between participants. In each age
group, 16 children (8 girls) were tested in each condition. In the first-person condition,
for each trial children heard two contrastive statements from two hand puppets (a cow and
a pig). The complement clauses were used with one of two mental verbs and a first-person
singular subject in the main clause (e.g., pig: I think the sticker is in the blue box;
cow: I know the sticker is in the red box). As in one of Moore and colleagues’ (1989)
conditions, the two mental verbs that were contrasted were think, marking relative
uncertainty, and know, marking certainty. In the first-person condition, the test
sentences were prerecorded and played from little speakers hidden under the hand puppets.
In the third-person condition, the experimenter spoke for the puppets and the children
heard, for example, The pig thinks the sticker is in the blue box; The cow knows the
sticker is in the red box. Each child received eight trials. Across trials, we
counterbalanced the order of the statements (whether the first statement contained think
or know in the main clause), the assignment of the statements to the hand puppets (whether
the pig or cow knew or thought), and the assignment of the statements to the boxes
(whether it was known or thought that the sticker was hidden in the red or blue box).

<hs>  Procedure</hs>
  ~~~~~~~~~

All children were tested by a female experimenter who sat opposite them at a small table.
For each trial, the child saw two opaque boxes on the table—always a red one and a blue
one. The red box was always placed to the left of the child. The experiment started with a
pretest. The experimenter told the child that she, the pig, and the cow had hidden many
stickers in the boxes and that the pig and cow would help the child to find these
stickers. She also told the child that the pig and cow might not remember all the hiding
places. For each of four trials a new pair of boxes was placed on the table in front of
the child. After the experimenter put the two boxes on the table, she asked the puppets,
Can you help X [child’s name] find the sticker? Which box is the sticker in? In the
pretest, the child heard two non-contrastive statements about the location of the sticker
from the two hand puppets. One statement was affirmative and the other was negated (e.g.,
pig: The sticker is in the red box; cow: The sticker is not in the blue box). Whether the
cow or the pig used the affirmative or negated statement, and which statement came first,
was counterbalanced. In the pretest, children were allowed to choose and open one of the
two boxes right away. Children who picked the right box in at least three of four trials
continued with the experiment. Children who scored lower than three of four trials
received two additional trials. If they then picked the right box in four of six trials,
they also continued with the experiment. As indicated above, we needed to exclude one
3-year-old because she did not reach this criterion. In each experimental trial, children
needed to choose one box but were not allowed to look into any of the boxes before they
were finished with all eight trials. In the first-person condition, the hand puppets
uttered the prerecorded test sentences. In the third-person condition, the hand puppets
first whispered into the experimenter’s ear, and the experimenter then uttered the test
sentences. The whispering did not contain any actual words, and the experimenter produced
the third-person complements right after the whispering. No additional instructions were
given to the child. Because the task was quite demanding, after four experimental trials
there was a break during which the experimenter played a puzzle game with the child. They
played this game for approximately 5 min and then continued with the second set of
experimental trials. Before they did the false-belief tests, children were allowed to look
into the boxes they chose and collect their stickers. Note that, finally, all boxes
contained stickers so that children were not differently rewarded before they began the
subsequent false-belief tests. For testing children’s understanding of false belief, we
presented participants with four different tasks. In the classic change-of-location test
(Wimmer & Perner, 1983), children needed to answer a test question about another person’s
false belief. The experimenter told the story and acted it out with two little dolls and
props: Sally puts a ball into her basket, Sally leaves the room, Ann transfers the ball
from Sally’s basket into her box, and Sally returns. The experimenter then asked three
questions: (a) the test question (Where will Sally look for her ball?), (b) the reality
control question (Where is the ball really?), and (c) the memory control question (Where
did Sally put her ball in the first place?). The change-of-location own-belief test is
based on the classic change-of-location paradigm but tests children’s understanding of
their own false belief (Buttelmann, 2016). For this, things were arranged such that
children searched in the incorrect location for a small toy. The experimenter placed two
boxes (a green one and a pink one) on the table and told the child that she was going to
hide a small toy ball in one of them. She then put an occluder on the table to block the
child’s view and put the toy ball into one of the boxes (the pink one in Fig. 1A and B).
At the same time, she slightly manipulated the position and the cover of the other box
(the green one in Fig. 1). So, after the occluder was removed, it looked like the
experimenter had manipulated one box, but had not touched the other one (see Fig. 1C and
Buttelmann, 2016, for details regarding the procedure of this test). She then asked the
child (a) the manipulation control question (Where is the ball?). Except for one 3-year
old, all children pointed to the box that looked like it had been manipulated and thus
held a false belief concerning the location of the ball. The experimenter then showed the
child that this box was actually empty and that the ball was hidden in the other box. She
then put the ball back in the same box (i.e., the one that did not look like it had been
manipulated) and asked (b) the test question (Where did you first think the ball was?). As
in the classic change-of-location test, the experimenter also asked (c) the reality
control question (Where is the ball now?). The unexpected content (or “Smarties”) test
included questions about both children’s own false belief and another person’s false
belief (Perner et al., 1987). We followed the original procedure of the task and used a
Smarties tube that was filled with crayons. The experimenter first asked the child what he
or she thought was is in there. After the child said Smarties, chocolate, sweets, or
something similar, the experimenter showed the child the actual content of the box
(crayons). She then put the crayons back into the tube, closed it, and asked the child
three questions: (a) the memory control question (Can you remember what’s inside here?),
(b) the own-belief test question (What did you first think was inside here?), and (c) the
other-belief test question (What will pig think is inside this box?). The order of the
own-belief test question (b) and the other-belief test question (c) was counterbalanced
across children. Thus, we were able to test children’s understanding of their own and
others’ false beliefs in scenarios involving unexpected contents and the change of an
object’s location. The unexpected content and change-of-location tests were presented as
blocks, and the order was counterbalanced. Within these blocks, we also counterbalanced
the order of own and others’ false-belief questions. Test sessions lasted 20 to 25 min.

<hs>  Scoring</hs>
  ~~~~~~~

Children’s choices in the hidden-object task were scored as correct when participants
chose the box marked by I know in the first-person condition and the box marked by the pig
knows or the cow knows in the third-person condition. For each false-belief task, children
got a score of 1 (pass) if they correctly answered both the test question and the
corresponding control question(s). Overall, eight 3-year-olds failed to correctly answer
the reality control question (about the actual location of the object) in the change-of-
location task (five in the change-of-location own-belief test and three in the change-of-
location other-belief test). In addition, six 3-year-olds did not give a correct answer to
the memory control question (about the actual content of the Smarties tube) in the
unexpected content task. Among the 4-year-olds, only two gave incorrect answers to the
reality control questions (about the actual location of the object) in the change-of-
location own-belief test. Trials in which children did not answer the control question(s)
correctly were dropped from the analyses. That is, for that specific false-belief test,
children did not get a score of either 0 (fail) or 1 (pass). For the unexpected content
task, this means that they did not get a score for either the own- or other-false-belief
test question. However, no child failed all control questions. So, each child got a score
of 0 (fail) or 1 (pass) for at least one false-belief measure and was considered in the
subsequent analyses.

<h>RESULTS</h>
-------

First, we analyzed children’s performance in the hidden-object task. A 2 (Age: 3- vs.
4-year-olds) by 2 (Condition: first- vs. third-person complements) analysis of variance
(ANOVA) suggested that there was a significant interaction between age and condition, F(1,
60) = 10.56, p = .002. Therefore, we ran separate analyses for the two age groups. The
3-year-olds performed at chance in both the first- and third-person conditions (first-
person: M = 52.3% of trials, SD = 13.1; Wilcoxon test: Z = .577, N = 16, p = .564; third-
person: M = 50.0% of trials, SD = 12.9; Wilcoxon test: Z = .054, N = 16, p = .957) (see
Fig. 2). Similarly, there was no significant difference between the younger children’s
performances in the first- and third-person conditions (Mann–Whitney U-test: U = 117.0, Z
= .443, Nfirst-person = 16, Nthird-person = 16, p = .657). The 4-year-olds, in contrast,
performed above chance in both conditions (first-person: M = 58.6% of trials, SD = 16.3;
Wilcoxon test: Z = 2.08, N = 16, p = .038; third-person: M = 79.7% of trials, SD = 15.1;
Wilcoxon test: Z = 3.434, N = 16, p = .001). Unlike the 3-year-olds, the older children
also performed significantly better in the third-person condition than in the first-person
condition (Mann–Whitney U-test: U = 46.0, Z = 3.157, Nfirst-person = 16, Nthird-person =
16, p = .002) (see Fig. 2). When we directly compared the two age groups, we found that
the 4-year-olds performed better than the 3-year-olds in the third-person condition
(Mann–Whitney U-test: U = 238, Z = 4.23, N3-year-olds = 16, N4-year-olds = 16, p < .001).
For the first-person condition, however, we did not find any significant age differences
(Mann–Whitney U-test: U = 148, Z = .793, N3-year-olds = 16, N4-year-olds = 16, p = .468).
Table 1 shows the number and percentage of children who passed each false-belief test in
each age group. Remember that we had to exclude a number of 3-year-olds and two 4-year-
olds from some trials because they did not answer the corresponding control question(s)
correctly. In addition, one 3-year-old did not have a false belief in the own-false-belief
version of the change-of-location test. Therefore, depending on the task, the total number
of 3-year-olds included in the analyses ranged from 26 to 29 and the number of 4-year-olds
included in the analyses ranged from 30 to 32. The 4-year-olds performed better in the
own-false-belief tests than in the other-false-belief tests. No significant differences
were found between the own-false-belief versions of the unexpected content test and the
change-of-location test (McNemar test: N = 50, p = .804). Similarly, there was no
significant difference between the other-false-belief versions of the two tasks (McNemar
test: N = 56, p = .839). Therefore, both tasks were combined for percentages of trials
passed in the own- and other-false-belief tests. The 4-year-olds performed above chance in
the own-false-belief tests (M = 84.4% of trials, SD = 29.6; Wilcoxon test: Z = 4.315, N =
32, p < .001) and at chance in the other-false-belief tests (M = 56.3% of trials, SD =
39.7; Wilcoxon test: Z = .894, N = 32, p = .371). The 3-year-olds performed below chance
in both the own- and other-false-belief tests (own: M = 31.3% of trials, SD = 37.6;
Wilcoxon test: Z = 2.558, N = 32, p = .011; other: M = 25.8% of trials, SD = 31.3;
Wilcoxon test: Z = 3.441, N = 31, p = .001). In accordance with these results, we found
that the 4-year-olds performed better than the younger group in both own-false-belief
tests (Mann–Whitney U-test: U = 857, Z = 4.98, N3-year-olds = 31, N4-year-olds = 32, p <
.001) and other-false-belief tests (Mann–Whitney U-test: U = 704, Z = 3.06, N3-year-olds =
31, N4-year-olds = 32, p = .002). The pairwise comparisons presented so far suggest that
between the ages of 3 and 4 years, children develop a better understanding of third-person
complements and of their own false belief. Their understanding of others’ false beliefs
also develops, but even the 4-year-olds still performed at chance in tasks testing the
understanding of others’ false beliefs. To further investigate whether there is a
relationship between children’s understanding of first- and third-person complements and
their understanding of false belief, we ran two regression models in R (R Core Team,
2014). In the first model, we entered children’s performance in the hidden-object task
(percentage trials correct), condition (first- vs. third-person complements), and age (3-
vs. 4-year-olds) to predict their performance in own-false-belief tasks. Condition and age
were coded as categorical variables (third-person and 4-year-olds, respectively).
Performance in the hidden-object task was coded as a continuous numerical variable. We
found main effects for age, performance in the hidden-object task, and condition as well
as a three-way interaction among all the factors (see Table 2). Together with the pairwise
comparisons presented above, these main effects and complex interaction suggest that it is
the older children’s growing understanding of third-person complements that is related to
their improved understanding of their own false belief. When we entered the same variables
to predict children’s performance in other-false-belief tasks, we found a main effect for
their performance in the hidden-object task and a two-way interaction between age and
performance in the hidden-object task. Together with the pairwise comparisons presented
above, this suggests that only the 4-year-olds’ understanding of complement clauses was
positively related to their understanding of others’ false beliefs (see Table 3).

<h>DISCUSSION</h>
----------

In the current study, we found developmental differences between 3- and 4-year-old
English-speaking children’s understanding of third-person complements and between 3- and
4-year-olds’ understanding of false belief. In particular, the older children performed
above chance level and also significantly better than the younger age group in the third-
person condition of the hidden-object task (with third-person complements) and in the own-
false-belief tests. Unlike the younger age group, the 4-year-olds also performed just
above chance in the first-person condition of the hidden-object task (with first-person
complements), but their performance in this condition did not significantly differ from
that of the 3-year-olds. In addition, the 4-year-olds performed at chance level in the
other-false-belief tasks, whereas the 3-year-olds were below chance and significantly
worse than the older age group. Together with these pairwise comparisons, the main effects
and complex interactions in the regression analyses suggest that the older children’s
understanding of own false belief was positively related to their understanding of third-
person complements. Their developing understanding of others’ false beliefs seems to be
related to their understanding of both first- and third-person complements. These findings
support our main hypothesis that the developmental link between third-person complements
and false-belief understanding should be stronger than the relation between first-person
complements and false belief because third-person complements are more likely to encode
genuine reference to mental states and mental processes (e.g., Diessel & Tomasello, 2001;
Howard et al., 2008; Manson, 2002). In addition, the older children found it easier to
distinguish the semantics of the mental verbs think and know in a third-person context
than in a first-person context, which supports the assumption that the semantics of mental
verbs is less ambiguous when used with third-person subjects (cf. Howard et al., 2008). We
found no clear developmental links between first-person complements and false-belief
understanding. In the hidden-object task, the 4-year-olds did not perform significantly
better with first-person complements than their younger peers. However, we did find
developmental differences for children’s understanding of false belief in the sense that
the 4-year-olds were significantly better than the 3-year-olds despite the older group
being only at chance on others’ false beliefs. It could also be possible that the
understanding of first-person complements was linked to children’s understanding of their
own false beliefs. But the regression analysis and pairwise comparisons suggest that only
the third-person complements, not the first-person complements, were positively linked to
children’s understanding of their own false beliefs. These findings provide further
support for the assumption that it is third-person complements that are intrinsically
related to children’s development of false-belief reasoning. We suggest that first-person
complements show weaker links to children’s false-belief development because they do not
necessarily refer to mental states and are ambiguous even when they are used as epistemic
markers (cf. Diessel & Tomasello, 2001; Howard et al., 2008). However, previous studies
did find correlations between children’s understanding of first-person complements and
false belief as well as developmental differences between 3- and 4-year-olds’
understanding of first-person complements with mental verbs (e.g., Howard et al., 2008;
Moore et al., 1989, 1990). The discrepancies between the current study and previous
studies might be due to methodological differences. For example, Moore and colleagues’
(1989) finding that there were developmental differences for children’s understanding of
first-person complements might be due to the fact that the age ranges applied in that
study were much wider than those applied in the current study (i.e., the 4-year-olds were
between the ages of 4 and 5). Therefore, the effect might have been driven by the older
participants. Another possible explanation is that in Moore and colleagues’ original study
the experimenter produced all test sentences, whereas we used prerecorded test sentences
in the first-person condition. However, when we did a similar study with German-speaking
children, the test sentences were produced live in both conditions of the hidden-object
task as in Moore and colleagues’ study. The pattern of results was similar to that in the
current study; we found developmental differences only for third-person complements and
false-belief understanding (Brandt & Buttelmann, 2015). As mentioned before, previous
studies also found correlations between children’s understanding of first-person
complements and their general understanding of false belief (Howard et al., 2008; Moore et
al., 1990). However, unlike the current study, previous investigations have not
systematically distinguished between children’s understanding of their own and others’
false beliefs. For example, Howard and colleagues (2008) also used the unexpected content
test but gave children a combined score for their answers to the questions about their own
and someone else’s false beliefs. When we systematically distinguished between children’s
understanding of their own and others’ false beliefs, we found a positive relation between
the older children’s developing understanding of others’ false beliefs and their
comprehension of both first- and third-person complements (see regression analysis in
Table 3). However, the older children’s understanding of their own false beliefs was more
advanced than their understanding of others’ false beliefs and was positively related only
to their understanding of third-person complements (see regression analysis in Table 2).
The relationship between first-person complements and false-belief understanding is
probably due to the fact that although phrases like I think and I know are often used just
like adverbials expressing (un)certainty (e.g., Diessel & Tomasello, 2001; Thompson &
Mulac, 1991; Verhagen, 2005), this function is not completely independent of the more
complex meanings of these mental state verbs. Most of the time, we do not use these
phrases to explicitly refer to mental states. Still, even using them to express different
degrees of certainty requires some concept of mind. Indeed, recent proposals suggest that
even if first-person complements are not used to refer to mental states directly, their
mastery may bootstrap young children into understanding true reference to mental states.
This might be because children notice that the verbs they use and comprehend as a signal
of, for example, (un)certainty are being used in a slightly different way and might be
used and comprehended as more or less explicit reference to mental states (Gordon, 1995;
Tomasello & Rakoczy, 2003). Children’s comprehension of mental verbs in first-person
contexts is also likely to be informed by their understanding of mental verbs in other
contexts, such as third-person complements, where these verbs are more likely to refer to
mental states. However, as has been shown for a variety of linguistic terms and
constructions (for an overview, see Tomasello, 2003), developing a more abstract, context-
independent representation of mental verbs takes time. And, as our current and previous
findings suggest, the acquisition of an abstract representation of mental verbs also
interacts with children’s false-belief development. A similar developmental story has been
put forward for the acquisition of modal verbs and other forms of epistemic markers and
evidentials, such as sentence-final particles, where children use apparently semantically
and/or syntactically complex terms and structures appropriately before they understand the
full range of concepts behind these terms and structures (e.g., Aksu-Koç, Ögel-Balaban, &
Alp, 2009; Matsui, Yamamoto, & McCagg, 2006; Papafragou, 1998; Papafragou, Li, Choi, &
Han, 2007). For example, children start using the modal auxiliary will at around the age
of 2.5 years (Wells, 1979). However, early in development, this modal auxiliary is most
likely to be used to communicate intention. Only at around the age of 5 years do children
use will to express how certain they are about something (e.g., saying that will be the
postman on hearing the doorbell) (Wells, 1979). This latter use is referred to as
epistemic modality, and Papafragou (1998) argued that children’s comprehension and correct
use of modal verbs with an epistemic function depends on their theory-of-mind development.
To grasp the epistemic function of modal verbs, children need to have developed a
“representational model of mind” (Forguson & Gopnik, 1988, as cited in Papafragou 1998, p.
383). However, Papafragou also suggested that this epistemic function is related to other,
more basic functions of modal verbs and that it is, indeed, not always easy to distinguish
between epistemic and other kinds of modals when looking at spontaneous speech. It seems
possible that once children have acquired a theory of mind, they extend the more basic
root functions of modal verbs expressing intention, ability, obligation, and so on to the
more complex epistemic functions of modal expression. For mental verbs and complement
clauses, it has been suggested that children’s comprehension and correct use of the more
complex functions not only depend on but also support their theory-of-mind development
(e.g., Astington & Baird, 2005; de Villiers, 2007; Milligan et al., 2007). When children
start using mental verbs and complement clauses, they tend to use first-person complements
with restricted phrases and fixed discourse functions (Köymen, Lieven, & Brandt, 2016).
Most important, it has been claimed that children’s first uses of mental verbs and
complements do not refer to mental states (e.g., Bartsch & Wellman, 1995; Diessel &
Tomasello, 2001; Shatz, Wellman, & Silber, 1983). Nevertheless, children start to talk
about their own mental states at around the age of 3 years (Bartsch and Wellman, 1995).
Results from the current study and previous research suggest that this talk about own
mental states might be related to children’s developing understanding of (others’) false
beliefs. However, third-person (and possibly also second-person) complements show a
stronger developmental link with children’s understanding of false belief. As has been
suggested by de Villiers (2007), complement clauses serve as representational tools for
children’s (and adults’) false-belief understanding because “the complement is embedded
under the verb and takes the particular perspective or point of view of the subject, not
the speaker, licensing also the subject’s terms of reference even when these are not the
speaker’s” (p. 1868). In other words, third-person complement-clause constructions (e.g.,
she thinks he’ll be late) allow us to distinguish between our own and someone else’s
perspective (e.g., she). First-person complements, on the other hand, express only one
perspective because the subject (e.g., I in I think he’ll be late) refers to the speaker
herself. The current data do not allow us to make substantial claims about the causal
relationship between developments in language and theory of mind, but previous studies
suggest that language supports explicit false-belief understanding rather than the other
way around (see meta-analysis by Milligan et al., 2007). Results from the current study
allow more detailed hypotheses, which need to be tested in follow-up training and
longitudinal studies. Our findings suggest that even though first-person complements also
play a role in children’s developing understanding of false belief, it is the
understanding of third-person complements that shows a parallel development with that of
false belief. In particular, children’s understanding of their own false belief develops
together with their understanding of third-person complements. A more general and explicit
understanding of both own and others’ false beliefs might develop out of children’s
understanding of own beliefs, very likely supported by their understanding of first- and
third-person complements. In both linguistic and sociocognitive development, children
develop more abstract representations of mental verbs and belief as they discover
commonalities across different discourse contexts.


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<ART>Children's use of interventions to learn causal structure
=========================================================

Authors: Teresa McCormack, Neil Bramley, Caren Frosch, Fiona Patrick, David Lagnado
DOI: 10.1016/j.jecp.2015.06.017
Year: 2016  |  Pages: 1-22
ASJC codes: 3204, 3205
Keywords: Active learning, Bayesian modelling, Causal learning, Causal structure, Scientific learning, Self directed learning

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Children between 5 and 8. years of age freely intervened on a three-variable causal system, with their task being to discover whether it was a common cause structure or one of two causal chains. From 6 or 7. years of age, children were able to use information from their interventions to correctly disambiguate the structure of a causal chain. We used a Bayesian model to examine children's interventions on the system; this showed that with development children became more efficient in producing the interventions needed to disambiguate the causal structure and that the quality of interventions, as measured by their informativeness, improved developmentally. The latter measure was a significant predictor of children's correct inferences about the causal structure. A second experiment showed that levels of performance were not reduced in a task where children did not select and carry out interventions themselves, indicating no advantage for self-directed learning. However, children's performance was not related to intervention quality in these circumstances, suggesting that children learn in a different way when they carry out interventions themselves.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Most developmental studies of causal learning (e.g., Bullock, Gellman, & Baillargeon,
1982; Gopnik, Sobel, Schulz, & Glymour, 2001; Shultz, 1982) have required children to
judge whether an event is causally efficacious. However, in learning about the world, what
is at issue is often not just whether a specific variable has a particular causal power
but also the structure of the causal relations between a set of variables. You might
observe that Events A, B, and C tend to co-occur (e.g., that when you feel stressed you
are likely to drink more heavily and also that your blood pressure is raised). This co-
occurrence is consistent with a variety of different causal structures; for example, the
structure may be a common cause in which A independently causes both B and C, B ← A → C
(stress causes heavier drinking and also independently causes raised blood pressure), or a
causal chain in which A causes B which causes C, A → B → C (stress causes heavier drinking
which raises blood pressure). How do we distinguish between these possibilities?
Intervening on a causal system potentially provides very important information (Hagmayer,
Sloman, Lagnado, & Waldmann, 2007; Sloman & Lagnado, 2005; Steyvers, Tenenbaum,
Wagenmakers, & Blum, 2003). Observing what happens if we intervened on B only would allow
us to distinguish between the two suggested causal structures; if, assuming no background
causes, we make B occur on its own (engage in heavy drinking when not stressed), and C
does not occur (blood pressure is not elevated), we can rule out the A → B → C causal
chain. A variety of studies have required adults to infer the structure of the relations
between sets of variables (e.g., Fernbach & Sloman, 2009; Kushnir, Gopnik, Lucas, &
Schulz, 2010; Lagnado & Sloman, 2004, 2006; Sobel & Kushnir, 2006; Steyvers et al., 2003).
In several of these studies, participants learned the causal structure by deciding what
interventions to make on elements in the system, carrying out these interventions and
observing their effects (Bramley, Lagnado, & Speekenbrink, 2015; Lagnado & Sloman, 2004,
2006; Sobel & Kushnir, 2006; Steyvers et al., 2003). Such interventions are assumed to
reveal conditional dependencies or independencies between variables, and adults’ success
on these tasks has been interpreted as being consistent with the causal Bayes net approach
to causal learning (e.g., Glymour, 2001; Gopnik et al., 2004) that captures causal
learning in terms of the construction of causal models based on conditional probability
information. A major advantage of this approach is that it specifies how and why
interventions on a system yield richer information about the causal (in)dependencies
between variables than that which is available through observation of patterns of
covariation (Hagmayer et al., 2007; Steyvers et al., 2003; Waldmann & Hagmayer, 2005). The
causal Bayes net approach has been extensively adopted by developmental psychologists
interested in explaining children’s learning about causation (Gopnik, 2012; Gopnik &
Wellman, 2012; Gopnik et al., 2004). The majority of studies in this tradition have
involved children learning whether an object possesses a particular causal power, usually
on the basis of observing the experimenter’s actions (e.g., whether an object makes a box
light up and play a tune; Gopnik & Sobel, 2000; Kushnir & Gopnik, 2007; Sobel, Tenenbaum,
& Gopnik, 2004). Relatively few studies have used tasks in which children themselves
decide which interventions to carry out in order to discover the causal structure of a
system (e.g., whether it has a causal chain or common cause structure). Such studies are
particularly important because they can be used to assess young children’s effectiveness
in generating and testing hypotheses about the causal relations between sets of variables.
Moreover, a key advantage of the causal Bayes net approach over most other accounts of
causal learning is that it can capture this more complex type of learning, distinguishing
between different causal paths as well as identifying variables’ ultimate effects. One
study that did examine children’s ability to learn causal structure by means of making
interventions on a system is that of Schulz, Gopnik, and Glymour (2007, Experiment 3), in
which 4- and 5-year-olds intervened on a causal system involving a box with two gears.
Children needed to decide whether each gear moved by itself or whether one of the gears
caused the other one to move. Children could remove each gear in turn from the box to
examine whether the other gear worked on its own when the box itself was switched on. They
gave their answers about the relations between the gears by selecting from a set of
anthropomorphized pictures of the two gears that depicted different possible relations
between them. Performance on this task was mixed. Children did not all reliably generate
the right interventions to distinguish between the different possible relations that might
hold between the gears. Even among those who did make appropriate interventions, children
were not successful at identifying instances in which one of the other gears caused the
other one to move. Schulz and colleagues’ (2007) study provides limited support for the
claim that children will generate informative interventions and use this information to
distinguish between different causal structures. Not only was performance relatively weak,
but children were only required to make judgments about the dependencies between pairs of
variables rather than to distinguish among three-variable causal structures. Children gave
their responses by pointing to pictures of the two gears that showed whether they turned
themselves or one turned the other. There was a third variable—a switch—that was important
in the system, but children did not need to represent how its relation to the gears varied
for the different causal systems, and it did not feature in the pictures depicting causal
relations between the gears. Thus, this study does not allow us to draw firm conclusions
about whether children can use interventions to distinguish between, for example, common
cause and causal chain structures. However, the findings of some other studies suggest
that we should expect even very young children to be good at crafting appropriate
interventions and using them to learn about causal systems (Bonawitz, van Schijndel,
Friel, & Schulz, 2012; Cook, Goodman, & Schulz, 2011; Schulz & Bonawitz, 2007). Indeed,
Schulz (2012) argued that the ability to select appropriate interventions and use the
evidence generated from such interventions may be developmentally basic. In various
studies, she and her colleagues showed that young children will appropriately explore a
causal scenario when given ambiguous information (Cook et al., 2011; Schulz & Bonawitz,
2007). In these scenarios, children’s behavior did suggest that children were trying to
figure out whether an object possessed a certain causal property. However, children did
not need to make interventions to disambiguate the structure of the relations between
different variables and then use this information to decide, for example, whether a system
was a common cause or causal chain. A further study by Sobel and Sommerville (2010) tried
to address this specific issue. Children viewed a box with four colored lights—A, B, C,
and D—and were told that some of the lights could make other lights turn on. The box was
configured so that the relations between the lights took the form of either a common
cause, B ← A → C, or a causal chain structure, A → B → C. Children could interact freely
with the box by switching on lights and observing their effects. They were then asked a
series of questions about the relation between pairs of lights. Sobel and Sommerville
found that children performed above chance on these questions, which could be interpreted
as indicating that they were able to use the information generated from their
interventions to decide on the structure of the causal relations. There are, however, two
difficulties with this interpretation. First, before children answered the questions, the
experimenter pressed each of the buttons in turn and narrated what it did; arguably, this
provided children with the answers to the test questions (indeed, children performed above
chance, although less accurately, when given just this narration). Second, it was not
clear that to answer correctly children needed to have an integrated representation of how
the three variables in the system were related to each other rather than just knowledge of
pairwise relations. Indeed, Sobel and Sommerville did not include in their analyses the
answers that children gave to the question of whether A makes C go in the case of the
causal chain, arguing that answers to this question are hard to interpret. However, by
questioning children only about the other pairwise relations between A and B and between B
and C, it is impossible to know whether children actually understood the nature of the
overall causal structure. The general point here is that we can distinguish between
learning structurally local pairwise links and integrating such links to form a
representation of causal structure. This distinction is important because learning
localized pairwise relations is likely to be easier than learning global structure
(Fernbach & Sloman, 2009). Moreover, learning local pairs only is often liable to lead to
the wrong global model; for example, when one connection “explains away” the dependence
between two others, a pairwise learning strategy would still attribute a connection
between these two variables, whereas a global strategy would not. A number of other
studies of children’s causal learning can also be interpreted as studying children’s
learning of pairwise relations rather than global causal structure (e.g., Schulz, Goodman,
Tenenbaum, & Jenkins, 2008; Sobel & Sommerville, 2009), meaning that we still have limited
evidence about children’s ability to learn causal structure. Uncertainty as to whether
children are adept at appropriately generating interventions and using them to learn
causal structure comes from two sources. First, research on children’s scientific learning
has for many years suggested that younger children may have great difficulty in generating
appropriately informative interventions and learning the nature of relations between
variables from the evidence generated by these interventions (e.g., Klahr & Dunbar, 1988;
Klahr, Fay, & Dunbar, 1993; Kuhn, 1989; Schauble, 1996; Zimmerman, 2000, 2007). On the
face of it, this body of findings seems at odds with recent findings from the causal Bayes
net tradition. One possible explanation of the differing findings lies in the role of the
knowledge base in scientific learning studies. For example, preexisting, and sometimes
erroneous, beliefs can hamper children’s ability to generate appropriate interventions and
interpret statistical data (e.g., Amsel & Brock, 1996; Kuhn et al., 1988). Indeed, Schulz
and colleagues suggested that this type of factor, along with task complexity, may mask
children’s basic learning skills (Bonawitz, van Schijndel, Friel, & Schulz, 2012; Cook et
al., 2011), which may be better demonstrated in the tasks used in the causal Bayes net
tradition where domain-specific knowledge is of limited importance and statistical
evidence is simple. However, the findings of a recent study by McCormack, Frosch, Patrick,
and Lagnado (2015) provide a second reason for being unsure about children’s ability to
learn from interventions on a causal system. This study, like most of those in the causal
Bayes net tradition, involved children learning about a novel mechanical system. The only
relevant data for causal learning were supplied by two types of domain-general cues:
statistical information provided through interventions on the system and the temporal
patterns of event occurrence. Children needed to learn the causal structure of the
system—a box with three separate shapes (A, B, and C) on its surface that rotated. Across
two experiments, children watched while the experimenter intervened on components of the
system. In one experiment, the experimenter carried out interventions in which she
disabled one of the shapes by preventing it from moving before moving each of the other
shapes in turn. Children did not find it straightforward to use the patterns of evidence
provided by these interventions to discriminate between causal structures even when the
system operated deterministically. Although 6- and 7-year-olds were able to use the
evidence from the more complex interventions to accurately infer when the system was one
of the causal chains, children younger than this could not do so, and even 7- and 8-year-
olds were unable to use information from these interventions to accurately judge when the
system was a common cause. McCormack and colleagues argued that children’s difficulties
may stem from integrating pieces of evidence provided across a number of separate
observations of the causal system. At first sight, McCormack and colleagues’ (2015)
findings seem to be more consistent with the conclusions stemming from research on
children’s scientific learning that has emphasized its limitations. It might be argued,
however, that this study did not provide children with an optimal opportunity to
demonstrate their abilities. Children watched while the experimenter made a series of
interventions rather than making the interventions themselves. Sobel and Kushnir (2006)
argued that participants find it easier to learn causal structure when they decide what
interventions to conduct, largely because this provides an opportunity for them to engage
in more active hypothesis testing (but see Lagnado & Sloman, 2004). In particular, they
suggested that when participants craft interventions themselves, they obtain evidence in a
structured way that makes it more apparent whether it supports specific hypotheses.
Moreover, children might be particularly likely to benefit from being allowed to explore
how a system operates in that hands-on interventions may ensure they stay engaged with the
task. In this study, we used a task very similar to that of McCormack and colleagues
(2015) in which children needed to decide whether a three-element causal system was a
common cause, B ← A → C, an A → B → C causal chain, or an A → C → B causal chain. Children
intervened on the system themselves in order to learn its structure. Shapes on top of a
box rotated when children moved them by hand, or shapes could be moved by rotating another
shape that was causally connected to them. For example, for the A → B → C causal chain,
spinning A initiated the rotation of both B and C, and spinning B rotated C; all of the
shapes always moved simultaneously in the tasks to minimize temporal cues. Children needed
to select and carry out a series of interventions; these could be simple interventions in
which they made one of the three shapes spin, or they could be more complex interventions
in which children prevented one of the three shapes from moving by disabling it and then
spun one of the other two shapes. Note that we were not attempting to faithfully recreate
a free-play situation because it was important for our analyses that we were able to
exhaustively categorize children’s actions on the system. Although they were completely
free to choose their interventions, the only actions children could carry out were
interventions on the system. Furthermore, it was made clear to children that their job was
to learn the causal structure of the system and that they could not make an unlimited
number of interventions. This allowed us to look in our modeling work at the efficiency
with which children produced informative interventions. We examined two aspects of
performance: the nature of the interventions that children selected and children’s causal
structure choices. Not all interventions provided useful information to discriminate among
the three possible causal structures, which allowed us to examine whether the tendency to
choose informative interventions changes with age. We also examined whether there was any
relation between the quality of children’s interventions and the likelihood that children
chose the correct causal structure at test. It is possible to try to examine these issues
without formal modeling (see Sobel & Kushnir, 2006) by, for example, simply distinguishing
between two broad classes of informative and non-informative interventions. However, we
chose to model children’s learning in a Bayesian framework. Doing so has two key
advantages. First, it allows us to properly assess whether there are developmental changes
in the extent to which children resemble idealized Bayesian learners. This is important
because, within the currently dominant causal Bayes net tradition, young children’s
learning is often characterized as approximating to such an ideal, particularly with
regard to causal learning from statistical information (e.g., Gopnik, 2012; Gopnik &
Wellman, 2012). Formal modeling allows us to assess the extent to which this
characterization is appropriate by assessing children’s performance against the standards
set by the Bayesian tradition itself. Second, although in this study we can (and do)
classify interventions broadly as informative or non-informative, the learning task itself
is sequential. This means that how informative an intervention is depends on what children
have already observed and what they can remember about such observations. However,
figuring out the informativeness of each intervention that a participant makes on a trial-
by-trial basis would be a formidable task without a formal model. Indeed, without such a
model, it is hard to see how one would operationalize the notion of informativeness under
such circumstances. Our Bayesian model allowed us to capture the sequential nature of the
learning task by assuming that the most informative interventions were those that
maximally reduced uncertainty about which was the correct hypothesis at any particular
point in the learning sequence given some level of forgetting.

        <hss>Participants</hss>

        Children were from three different school years: 21 5- and 6-year-olds (M = 72
        months, range = 64–80), 31 6- and 7-year-olds (M = 86 months, range = 80–93) and
        25 7- and 8-year-olds (M = 98 months, range = 93–103). Children were tested
        individually in their schools.

        <hss>Materials</hss>

        The study used a wooden box, 41 cm (long) × 32 cm (wide) × 20 cm (high), which had
        an on/off switch at the front. There were three different colored lids for the
        box. Two of these had three colored/patterned shapes (e.g., circle, rectangle,
        star) inserted on their surface that rotated independently on the horizontal
        plane; a separate lid was used in pretraining and had only two shapes (see Fig.
        1). The colors and shapes of the components were varied across participants and
        causal structures. On each of the two lids used in testing, the three shapes
        formed an equilateral triangle of 24-cm sides. Each shape had a small hole that
        aligned with a hole in the lid of the box. There was a miniature red-and-white
        “Stop” sign affixed to a metal rod that could be inserted through the hole on any
        shape into the corresponding hole in the box, preventing it from moving. Each of
        the shapes could be rotated by hand; the rotation of the other shapes was
        controlled by a laptop hidden inside the apparatus that participants were unaware
        of. A set of photographs was used during the learning phase that participants used
        to indicate which intervention they were going to make; these photographs depicted
        each shape on the box, and in addition there were photographs of each of the
        shapes alongside the stop sign. Photographs of the whole box with its shapes
        depicting three possible causal structures were used at test for children to
        indicate their judgment of the causal structure: one common cause and two causal
        chains (i.e., depicting B ← A → C, A → B → C, or A → C → B). The photographs for
        use at test were overlaid with pictures of hands to indicate causal links
        (following Frosch, McCormack, Lagnado, & Burns, 2012).

        <hss>Procedure</hss>

        Children completed two test trials: one common cause and one causal chain (order
        counterbalanced). There was a pretraining phase to ensure that children knew what
        their task was and how to give their answer at test. The pretraining procedure
        used a lid on the box that had only two colored shapes inserted on its surface;
        its purpose was to demonstrate that some shapes caused others to move but that the
        stop sign could be used to prevent a shape from moving. Children were initially
        asked to name the colors of the shapes to ensure that they would know which shapes
        the experimenter was referring to, and the experimenter drew children’s attention
        to the on/off switch at the front set at the “off” position. She then switched the
        box on and manually rotated one of the two shapes (X). This had no effect on the
        other shape (Y), which remained stationary, and the experimenter pointed this out
        to children. She then rotated the other shape (Y), which resulted in the first
        shape (X) simultaneously rotating. She explained to children, “Some shapes are
        made to move by others.” The experimenter then switched the box off and introduced
        children to the stop sign, which she inserted into X to stop it from moving,
        saying, “See this stop sign, it can be used to stop a shape from moving. See the
        [color of X] one cannot move now.” She then switched the box on again and rotated
        Y, which this time had no impact on the movement of X because it was prevented
        from moving by the stop sign. Following this, the lid was removed from the box and
        replaced by a different colored lid with three different shapes for the first test
        trial. Children were asked to name the colors of the three shapes and were told
        that their job was to figure out how the box worked. They were introduced to the
        three test pictures depicting the three different causal structures, with the
        experimenter saying, “In a moment I will ask you to figure out how the box works,
        but first I want to show you some pictures of the box which show different ways in
        which the box may be working. Only one of them is right, and you’ve got to work
        out which is the right one. It won’t change halfway through, and it is definitely
        only one of the pictures. You’ll have to use your detective skills to work out
        which picture shows what the box does.” The experimenter described each of the
        three pictures (e.g., “In this picture, the red one makes the blue one go, and the
        blue one makes the white one go, and the hands show that”). Following these three
        descriptions, children were then asked a set of three comprehension questions. For
        each causal chain picture, the experimenter asked, “Can you show me the picture
        where the [color of A] one makes the [color of B/C] one go and the [color of B/C]
        one makes the [color of B/C] one go?” For the common cause picture, the
        experimenter asked, “Can you show me the picture where the [color of A] one makes
        both the [color of B] one and the [color of C] one go?” The majority of children
        answered these questions correctly the first time, but if they did not answer all
        three questions correctly, the experimenter repeated the initial descriptions and
        asked the comprehension questions again. This procedure was repeated again if
        necessary. Following this pretraining, the experimenter said, “I am going to
        switch the box on now, and I want you to figure out how the box works.” Children
        were told that they could do one of two things (order counterbalanced): either
        “You can move a shape to see if it makes other shapes move” or “You can stop a
        shape from moving by putting the stop sign in and then see what happens when you
        move another shape.” It was explained to children that before they carried out
        each intervention, they needed to point to a card indicating what they intended to
        do. The experimenter said, “Before you try anything on the box, I want you to
        point to one of these cards. This card means you want to spin the [color] one, and
        you point to this card if you want to stop the [color] one. See, we also have the
        cards for spinning and stopping the [color and color] ones. So, each time you want
        to do something, you point to one of these cards first.” Children were told that
        they had 12 “goes” to start with and that each time they moved a shape counted as
        1 “go.” It was made clear that using the stop sign did not count as a go by
        itself; children needed to then in addition move one of the other shapes. The
        procedure with cards was used to ensure that children interacted with the box in a
        controlled way and to make clear that they could not make an unlimited number of
        interventions. It also ensured that all children made a fixed minimum number of
        interactions before attempting to answer the test question. Children were told
        that they did not need to keep track of the number of goes that they had with the
        box because the experimenter would count this for them. Before children began, the
        experimenter said, “Remember, you’ve got to figure out which picture shows how
        this box really works.” She then demonstrated what happened when the A shape was
        moved, which was that the other two shapes also moved simultaneously, and pointed
        out that they did not know yet “which ones make other ones go.” Participants were
        subsequently allowed to make interventions on the box by first selecting the
        appropriate card and then making the intervention. So, for example, if they wanted
        to see what happened when C was moved if B was disabled, they needed to point to
        the card depicting B with the stop sign in it and then to the card depicting C.
        They then carried out their intervention. After participants completed 12
        interventions, the experimenter said, “You have had your 12 goes now. Do you want
        to choose which picture you think shows what the box did, or do you want to have
        another 6 goes?” The majority of participants opted to choose after 12
        interventions. Children completed a short filler task (a paper-and-pencil maze) in
        between the common cause/causal chain trials. It was made clear that the second
        box might work in the same way as the first box or it might work in a different
        way. The second box always had a lid of a different color and different shapes.

<hs>  Results</hs>
  ~~~~~~~

In both trials, 69 of the 77 participants stopped after 12 interventions. The remaining 8
opted for an additional 6 interventions in one or the other trial. Of these, 4
participants opted for the additional 6 interventions on both trial types. Initial data
analyses examined participants’ responses for each of the two trial types. Fig. 2 shows
the percentage of participants who chose each response type for each trial type. The
majority of participants in each group, except for the youngest group, chose the correct
answer for the causal chain trial. The majority of participants in all groups chose the
common cause response for the common cause trial. Binomial analysis showed that each group
of participants chose the correct response more often than chance (all ps < .01) except
for the 5- and 6-year-olds who did not select the correct causal chain more often than
chance. This group tended to select the common cause response for both structures.
Performance on the causal chain structure was associated with age, χ2(2) = 6.91, p < .05,
with the number of correct responses improving with age. Performance on the common cause
structure was marginally significantly associated with age, χ2(2) = 5.66, p = .056,
although in this case the 6- and 7-year-olds gave more correct responses than each of the
other groups.

        <hss>Analysis of interventions</hss>

        Subsequent analyses examined the nature of participants’ interventions on the
        system. We initially discriminated between whether an intervention was informative
        or not given the three possible causal structures. There were three interventions
        that were never informative: A+, B+C–, and B–C+, adopting the notation of “+” to
        mean that a particular shape was moved by the participant and “–” to mean that a
        shape was disabled. Potentially informative interventions were A+B–, A+C–, B+, C+,
        A–B+, and A–C+. We also classified interventions as simple or complex; A+, B+, and
        C+ were classified as simple, and those involving initially disabling one of the
        components before moving another component were classified as complex. Table 1
        shows the percentage of times that participants in each age group chose each of
        these interventions. The most popular intervention tended to be A+, which,
        although it was uninformative, did make all of the three shapes spin. Propensity
        to select a complex intervention increased significantly with age, F(2, 74) =
        7.22, p < .002, η2 = .16, with 7- and 8-year-olds being the most likely to pick
        the complex interventions (65% of the time vs. 46% for 5- and 6-year-olds and 45%
        for 6- and 7-year-olds). We examined whether participants chose informative
        interventions more often than chance by conducting a one-sample t-test with a test
        value of .67 given that two thirds of the nine possible interventions were
        informative. Only the 7- and 8-year-olds were significantly more likely than
        chance to select informative interventions, t(24) = 2.83, p < .01, both ps > .10
        for the younger groups. A logistic regression showed that the proportion of
        informative interventions significantly predicted the probability of a participant
        getting the chain trial correct (z = 2.73, p < .01) (see Table 2), but this was
        not the case for the common cause trial (z = −0.62, p > .50). One potential
        explanation for the latter finding is that the children were overall more likely
        to select the common cause, doing so 56% of the time. Thus, some of the correct
        responses on the common cause test trial are likely to have been made by the
        weaker participants purely by virtue of their favoring the common cause structure.

        <hss>Modeling interventions</hss>

        So far, we have looked at proportion of informative intervention choices without
        considering the sequential nature of the task or whether and how efficiently
        children produced a set of informative interventions sufficient to discriminate
        between causal structures. A child who did not produce such a set but repeatedly
        produced a single informative intervention would score 100% on this measure.
        Moreover, how useful an intervention is depends on what learners already know (in
        this case what they have already learned from their previous interventions). For
        example, A+B– and C+ are both informative interventions in this task provided that
        you do not know anything yet. But suppose that you have already performed A+C– and
        observed that this made B spin. This evidence effectively rules out the ACB chain,
        leaving only the ABC chain and the common cause as possibilities. Now, on
        subsequent trials, performing C+, or repeating A+C–, will not tell you anything
        new because both of these interventions simply distinguish the ACB chain from the
        other two. To capture how efficiently children’s intervention choices allow them
        to home in on the true structure, we can analyze the interventions sequentially by
        looking at how effectively these interventions reduce uncertainty, assuming that
        initially children are perfectly able to remember past outcomes and integrate new
        information. For all age groups, for both structures, children’s interventions
        were significantly much more efficient than the chance level (mean efficiencies
        for chain and common cause, respectively: 5- and 6-year-olds = .71 and .66, 6- and
        7-year-olds = .79 and .63, and 7- and 8-year-olds = .82 and .80; all ts > 6, ps <
        .0001). Children’s efficiency for the common cause changed significantly with age,
        F(2, 74) = 4.47, p ⩽ .02, η2 = .11, but there was no effect of age on efficiency
        on the causal chain trials, F(2, 74) = 1.14, p = .32, η2 = .03. Unlike proportion
        informative interventions, efficiency did not predict accuracy on the chain (see
        Table 2) and was in fact negatively related to accuracy on the common cause (z =
        –2.62, p < .01). Whereas proportion informative interventions did not take into
        account the sequential nature of the task, arguably interventional efficiency has
        the opposite shortcoming. By assuming, implausibly, that children have a perfect
        memory for the outcomes of their previous interventions and perfect ability to
        make inferences from this information, it ignores what they do on subsequent
        interventions once they have, in principle, enough information to potentially
        identify the correct structure. An inspection of the modeled data found that
        children obtained sufficient information for certainty after an average of only
        2.75 interventions; this means that our measure of efficiency ignores a large
        proportion of the data and makes no allowances for noise, forgetting, or
        uncertainty in learning. A more balanced way to assess the quality of
        participants’ interventions is achieved by adding some noise, encapsulating the
        idea that learning is likely to be somewhat leaky or error prone. The exact level
        of “forgetting” in the model turned out not to be particularly important. We found
        qualitatively the same results setting it to 10%, 25%, 50%, 75%, and 90%, although
        the results were clearer for the lower levels of forgetting. Here we report
        results assuming 25% forgetting after each test. We established chance levels of
        intervention quality, again through simulation over 1000 trials. The 5- and
        6-year-olds’ intervention quality was not significantly above chance on either the
        chain or common cause; the 6- and 7-year-olds were above chance on the chain,
        t(30) = 2.88, p < .01, and marginal on the common cause, t(30) = 1.73, p = .09;
        and the 7- and 8-year-olds’ intervention quality was above chance for both trials
        (chain: t(24) = 2.46, p < .02; common cause: t(24) = 4.87, p < .001). Averaged
        over trial types, we found that intervention quality improved with age, F(2, 74) =
        4.03, p < .03, η2 = .10, with 7- and 8-year-olds significantly more efficient that
        5- and 6-year-olds (p < .01), but no significant difference between 5- and 6-year-
        olds and 6- and 7-year-olds. Breaking this into responses for the two structures,
        regardless of forgetting rate, intervention quality was a significant predictor
        for correct identification of the chain structure (z = 2.61, p < .01), but not for
        the common cause structure (see Table 2).

<hs>  Discussion</hs>
  ~~~~~~~~~~

Our findings provide important information about developmental changes in children’s
ability to learn causal structure through intervention. Children’s ability to learn a
causal chain structure improved developmentally, with the youngest children not managing
to learn this structure at above-chance levels. However, we need to consider why the 5-
and 6-year-olds correctly identified the common cause structure as accurately as the 7-
and 8-year-olds. Our view is that the good performance on this second trial type is due to
a tendency even among the youngest children to assume that, when events happen
simultaneously, the underlying structure is a common cause. Previous studies have found
that both children and adults make use of this simple temporal heuristic when they observe
a three-variable system with this sort of temporal schedule (Burns & McCormack, 2009;
Fernbach & Sloman, 2009; Lagnado & Sloman, 2006; McCormack et al., 2015). Indeed,
McCormack et al. (2015) demonstrated that children will use this type of temporal
heuristic even when faced with contradictory statistical information provided either
through observing the operation of a probabilistic causal system or through observing the
effects of interventions on a deterministic system. Thus, the good performance of the
younger children on the common cause structure is likely to reflect use of this heuristic
rather than use of statistical information derived from interventions on the system. This
would also straightforwardly explain the lack of a relation between intervention quality
and performance on the common cause structure. The analyses of children’s intervention
choices provide insights into why performance improved developmentally on the causal chain
trial. Interventions could be initially classified as informative or non-informative given
the three possible causal structures. Over all trials, unlike the oldest group, younger
groups of children did not choose informative interventions more often than chance. It
proved to be fruitful, however, to further examine intervention choices and how these
related to performance in more detail by means of our modeling work. The initial analysis
of how efficient participants were at producing a set of interventions that could in
principle discriminate between the different hypotheses showed that all groups of children
produced such a set more quickly than would be expected if they were simply choosing
between interventions at random. This means that even the youngest children had the
evidence available to them to make the appropriate causal inferences. However,
intervention efficiency was not a predictor of performance. This demonstrates that good
performance does not hinge on simply initially choosing interventions that are as a matter
of fact disambiguating. Children may forget or fail to make use of what they have
observed, and the subsequent interventions they make may also influence their judgments.
Our modelling work suggested that this was indeed the case because our measure of the
quality of children’s interventions that took into account the complete sequence of
interventions predicted performance on the causal chain structure, under the assumption
that there was some degree of forgetting. Moreover, unlike efficiency, intervention
quality improved with age, with older children being more likely to consistently choose
interventions that would help to disambiguate the causal structures given what they had
already observed. These results indicate that with development children become more
discerning in their choice of interventions, and this has an impact on their causal
structure learning. How do our findings fit with what is already known about developmental
changes in children’s use of interventions to learn about causal systems? In designing our
study, we sought to ensure that domain-specific knowledge was not relevant for task
performance. However, this did not rule out children exploiting a type of preexisting,
albeit domain-general, heuristic about the nature of the causal system, namely that when
multiple events occur immediately following an intervention, the underlying structure is
likely to be a common cause (McCormack et al., 2015). When the evidence generated from
interventions was consistent with this assumption (i.e., in the common cause trial), even
young children performed well. However, younger children had difficulty in discarding this
assumption on the basis of the contradictory evidence provided by their interventions.
This is consistent with evidence from the scientific learning literature indicating that
children have difficulty in discarding a preexisting hypothesis and may routinely ignore
statistical evidence that fails to support such a hypothesis (Amsel & Brock, 1996; Kuhn et
al., 1988). Furthermore, an inspection of developmental changes in the pattern of
children’s intervention choices (Table 1) yields some further interesting additional
parallels with findings from the scientific learning literature. Our task is very
different from those used in research on children’s scientific learning; it is simpler,
and the children we tested are younger than those typically used in such studies (but see
Koerber, Sodian, Thoermer, & Nett, 2005; Piekny, Grube, & Maehler, 2014). Nevertheless,
some of our findings confirm broad developmental patterns that are well established in
that research. Younger children tended to prefer making the A+ intervention and did so
repeatedly. This intervention is the most causally effective (it makes all of the events
happen) but does not discriminate among the three available hypotheses. However, it
reinforces any existing hypothesis that the causal structure is a common cause by
providing the temporal pattern of all events happening simultaneously. Young children’s
preference for this intervention has parallels with demonstrations in the scientific
learning studies showing that children attend most to the variable already believed to be
causal, focus more on producing an effect than on generating disambiguating evidence, and
produce evidence that is consistent with their existing hypothesis rather than seeking to
disconfirm it (e.g., Klahr & Dunbar, 1988; Klahr et al., 1993; Kuhn, 1989; Schauble, 1990,
1996). Although younger children’s patterns of interventions led to poorer performance, it
is interesting to note that recent formal analyses have demonstrated that whether their
type of approach should be viewed as inefficient depends on the learning context. First,
the tendency to intervene on variables already believed to be causal in order to confirm
an existing hypothesis is not necessarily always the wrong strategy. This type of strategy
has been shown to be rational under the assumption that causal connections in the world
are sparse (Navarro & Perfors, 2011), meaning that competing causal hypotheses do not
generally share the same effect variables. In such circumstances, “positive tests,”
operationalized as intervening on the variable thought to be the root cause (Coenen,
Rehder, & Gureckis, 2015), are highly diagnostic. Hence, younger children’s pattern of
interventions could be interpreted as due to a tendency to act in a way that has proved to
be an effective general-purpose method for learning causal relationships in the past but
is not appropriate given the specific learning context in which they find themselves.
Second, we also found that younger children were less likely than older children to
produce the more complex interventions that involved disabling one of the components in
the system. This type of intervention can be particularly informative because it can be
used to exclude a variable as being necessary for production of an effect. However,
separate Bayesian modeling work with adults has demonstrated that producing simple rather
than complex interventions is not always an inefficient strategy. Bramley, Lagnado, et al.
(2015) showed that simple interventions tend to be more informative than complex
interventions with respect to a broader hypothesis space (e.g., all possible three-
variable causal models), with more complex interventions becoming more useful once the
space of possibilities narrows to favor only a few overlapping causal hypotheses. In our
task, children needed to discriminate among just three competing hypotheses, so it is one
in which complex interventions are likely to be useful. In summary, the observed
developmental changes can be interpreted as supporting the idea that whereas younger
children used simple strategies that may have proved to be effective in other contexts,
older children were more able to adjust their learning strategy in a way that was
appropriate for the task—that is, to use a control of variables strategy (Chen & Klahr,
1999; Dean & Kuhn, 2007) in which confounding variables are experimentally controlled.

<h>EXPERIMENT 2</h>
------------

Experiment 1 showed that by 6 or 7 years of age children can generate informative
interventions and use these to derive the structure of a three-variable causal system and
that the quality of their interventions predicts their performance. What we have not yet
shown, however, is that children benefited from generating interventions themselves.
Following Sobel and Kushnir’s (2006) study with adults and Sobel and Sommerville’s (2010)
related study with children, we might predict that being able to self-generate
interventions facilitates active hypothesis testing. In our second experiment, we tested
additional groups of children using a “yoking” procedure similar to Sobel and Kushnir’s
procedure. Children did not select interventions themselves; rather, each child was
individually matched with one of the children from Experiment 1 and saw the outcomes of
the set of interventions made by that child. There were two conditions; children in the
yoked–self condition carried out a series of interventions on the system but did not
select which interventions to make, and children in yoked–observe condition simply watched
interventions being carried out by the experimenter. If children benefit from selecting
interventions themselves, we would expect performance to be worse in the yoked conditions
compared with the self-generated interventions in Experiment 1. If there are benefits from
simply carrying out interventions oneself, even if one has not selected them, we would
expect performance in the yoked–self condition to be better than performance in the
yoked–observe condition. In addition to comparing performance across conditions, we
examined whether our measures of intervention quality, taken from the interventions made
by the yoking participants from Experiment 1, were predictive of performance even in the
yoked conditions. It is important to note that all participants in Experiment 2 received
sufficient information to disambiguate the causal structures. Because all children in
Experiment 1 obtained sufficient information to make correct inferences, the relation
between intervention quality and performance found in that experiment can be explained in
two potentially independent ways. It may be that this relation was obtained because higher
quality interventions resulted in a larger quantity of useful information that was
obtained in a sequence that facilitated learning. Alternatively, it may be that this
relation was obtained because children who were engaged in productive hypothesis testing
selected useful interventions that allowed them to assess these hypotheses. If the former
is the case, we might expect to see a relation between intervention quality and
performance in the yoked conditions of Experiment 2 because children in those conditions
received identical sequences of information to the children who selected the interventions
themselves. However, if this relation hinges on the role of active hypothesis testing, it
might not be obtained in circumstances where children do not select interventions
themselves.

        <hss>Participants</hss>

        Three groups of children took part in this part of the study: 28 5- and 6-year-
        olds (M = 75 months, range = 70–81), 62 6- and 7-year-olds (M = 87 months, range =
        81–93), and 50 7- and 8-year-olds (M = 99 months, range = 91–105), who were
        recruited from the same year groups and from schools in the same area as the child
        participants in Experiment 1. Half of the children were assigned to the yoked–self
        condition and half to the yoked–observe condition.

        <hss>Materials</hss>

        These were identical to those used in Experiment 1.

        <hss>Procedure</hss>

        The procedure for each of the conditions was identical to that of Experiment 1 up
        until the learning stage of the task. In the yoked–self condition, the
        experimenter explained that she was going to ask children to do things to the
        shapes in the box in order to figure out how the box worked, using cards to give
        instructions. She explained that when she pointed to a picture of a specific
        shape, children needed to move that shape to see what happened to the other
        shapes, and when she pointed to a picture of a shape with a stop sign in it,
        children needed to initially put the stop sign in that shape and then see what
        happened when they moved whichever shape was depicted in the next picture that she
        pointed to. Children were told that the experimenter would give them 12
        instructions of this sort to start with. During the learning phase, the
        experimenter then instructed children to carry out the interventions in the same
        order as their yoked participants from Experiment 1. For those children who were
        yoked to children from Experiment 1 who completed 12 interventions (the majority
        of children), after those interventions were completed the experimenter said, “You
        have had your 12 goes now. Which picture do you think shows how the box works?”
        For the remaining children, after 12 interventions the experimenter said, “We have
        6 more things to try before you give your guess about how the box works,” and then
        showed the remaining 6 interventions before asking the test question. The
        procedure for the yoked–observe condition was very similar except that the
        experimenter explained that she would point to the pictures of the shapes herself
        before moving them. During the learning phase, the experimenter then pointed to
        the appropriate pictures before each intervention and carried out all
        interventions herself with children observing.

<hs>  Results</hs>
  ~~~~~~~

Fig. 4A shows the distribution of responses for each trial type for the yoked–self
condition, and Fig. 4B shows the distribution for the yoked–observe condition. As can be
seen from the figure, correct responses were relatively similar to those in Experiment 1,
although the 7- and 8-year-olds seemed to perform less well on the causal chain. We
compared performance in these conditions with performance from the yoked participants from
Experiment 1; Table 3 shows the percentages of correct responses for the causal chain and
common cause trials as a function of condition. There was no significant association
between condition and numbers of correct responses for the causal chain trial, χ2(2) =
1.48, p = .48, or for the common cause trial, χ2(2) = 3.89, p = .14; the association
between condition and numbers of correct responses for each trial type was also not
significant if each age group was examined separately or if each condition was compared
separately with the other two conditions. We then examined whether the factors that were
predictive of performance in Experiment 1 predicted performance in the yoked conditions.
Neither the proportion of informative interventions presented to participants, the
efficiency of the sequences of interventions for identifying the true structure, nor their
overall quality (assuming 25% forgetting) predicted performance for either the yoked–self
or yoked–observe groups on either trial type (all ps > .05). The relation between these
measures of interventions and performance on the causal chain identified in the 77
participants in Experiment 1 were still significant for the 70 whose data were yoked to
the yoked–self and yoked–observe groups (informative interventions: z = –2.69, p < .005;
intervention quality: z = –2.50, p < .01), indicating that the fact that the measures do
not predict performance in the yoked groups is not a problem of slightly reduced
statistical power.

<h>GENERAL DISCUSSION</h>
------------------

Experiment 1 examined children’s causal structure learning under circumstances in which
they selected and carried out interventions on a simple three-variable causal system. To
the best of our knowledge, the analyses reported here of its data constitute the first
attempt to model the quality of children’s interventions when learning causal structure
within a Bayesian framework. Our findings regarding children’s interventional learning
varied depending on whether children were learning a causal chain or a common cause
structure. With regard to the former, there were clear developmental improvements not only
in terms of accuracy of structure learning but also in terms of the quality of the
interventions that children produced, as assessed in our Bayesian modeling. The key
advantage of the modeling is that it provided us with a quantitative measure of the
quality of children’s interventions, allowing us to formally examine the extent to which
children’s interactions with the system were optimal. This Bayesian measure of
intervention quality predicted performance. Put simply, the findings suggest that with
development children increasingly resemble idealized Bayesian learners, although we note
that the best predictor of performance from our modeling results was a measure of
interventional quality that assumed some degree of noise in the Bayesian learning process.
The same pattern of findings was not obtained for the common cause structure, and the most
plausible interpretation of this is that younger children’s inferences in this task were
based on a simple temporal heuristic (“assume a common cause if effects happen
simultaneously”) rather than on use of statistical information provided from
interventions. Use of such temporal heuristics is widespread in both children’s and
adults’ causal structure learning (Burns & McCormack, 2009; Fernbach & Sloman, 2009;
Lagnado & Sloman, 2004, 2006; White, 2006), with McCormack et al. (2015) demonstrating
that younger children’s causal structure inferences are highly influenced by the temporal
pattern of events. Their findings are consistent with those from the current study insofar
as those authors also found no developmental improvements in the likelihood that children
would give a common cause judgment under circumstances in which all events happened
simultaneously. Children’s tendency to recruit temporal heuristics is likely to be due to
the heuristics’ low demands on information processing in comparison with using statistical
information (Fernbach & Sloman, 2009). For example, in the current study, use of such a
heuristic would have been based on the observation of a single intervention—the temporal
pattern of events following A+. This intervention was the most common one made by the
younger groups; we interpreted this as suggesting that these children focus on producing
an effect rather than systematically testing the competing hypotheses and in doing so are
provided with evidence (i.e., the temporal pattern of events) that they take to be
consistent with their existing hypothesis. Younger children were also less likely to
disable components in the system, suggesting that they were less likely to try to exclude
any variables. Although younger children’s interventions in the system had these
characteristics, all children produced a set of interventions that could in principle have
allowed them to correctly judge the causal structure. However, the Bayesian analysis
proved to be useful in establishing that simply initially producing interventions that
could potentially disambiguate the causal structure was not predictive of good
performance. Rather, children’s performance was related to how informative their
interventions were as they moved through the task sequentially, with the Bayesian modeling
making it possible to operationalize the informativeness of sequential intervention
choices. In general, as we argued above, our developmental findings are broadly consistent
with some well-established findings in the literature on scientific learning. One of the
aims of the scientific learning literature is to explore the wide variety of cognitive and
metacognitive processes that are important at each stage of the reasoning process, from
formulating initial questions, generating and evaluating evidence, to constructing and
revising theories. Our aim in this study was not to match such studies in the breadth of
cognitive processes that they explore or in the depth of analysis that they typically
provide regarding, for example, the range of strategies that participants recruit. For a
start, although we have described children as deciding between hypotheses, we do not
believe that it is helpful to consider children to be engaged in theory construction in
our task. Nevertheless, our findings are valuable in terms of what they add to our
knowledge specifically about basic aspects of causal structure learning. As already
emphasized, in many instances scientists must uncover not just which variables are causal
but also the overall structure of a causal system. Most studies of children’s causal and
scientific learning have focused on their ability to learn whether specific variables are
causally efficacious. Although in scientific learning studies such variables sometimes
have additive or interactive effects (e.g., Kuhn & Pease, 2008; Kuhn, Pease, & Wirkala,
2009), typically participants do not need to distinguish between, for example, common
cause and causal chain structures. It is an important strength of the causal Bayes net
approach that, unlike more traditional models of causal learning, it can model this sort
of learning of structure. Our modeling work demonstrates the utility of examining such
learning within a broadly Bayesian framework, albeit to allow us to conclude that younger
children might not be the idealized Bayesian learners they are sometimes assumed to be
within the causal Bayes net tradition.

<hs>  Active versus passive learning</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our use of a yoking procedure in Experiment 2 provided insights into whether active
participation assists children’s causal learning. We found no clear learning benefits of
either selecting or carrying out interventions oneself, a finding that contrasts with that
of Sobel and Kushnir’s (2009) adult study but is consistent with the findings of Lagnado
and Sloman (2004). We note that there is a long-standing debate in the literature on
children’s scientific learning over whether “hands-on” learning is more beneficial than
more passive learning (e.g., Bruner, 1961; Kirschner, Sweller, & Clark, 2006; Mayer,
2004). The debate regarding active versus passive learning is multifaceted, encompassing
both cognitive and motivational issues, but in the context of children’s scientific
learning the central question has been whether children show benefits in terms of the
amount, depth, and persistence of knowledge gained when allowed to engage in self-guided
discovery learning. So, for example, Klahr and Nigam (2004) compared how well children
learned a control-of-variables strategy in two conditions: either direct instruction or a
condition in which they designed and carried out experiments themselves. On the basis of
their findings, these authors argued that direct instruction is more beneficial than
discovery learning. Unsurprisingly, such a conclusion has attracted much attention because
it is believed to have important consequences for how children should be taught science
(Hmelo-Silver, Duncan, & Chinn, 2007; Kuhn, 2007). In interpreting the contribution of our
findings to this debate, it is important to remember that our task is much simpler than
those typically used in studies of the benefits of active learning. Moreover, children did
not need to learn a theory or generalize from their learning, and the task was not one in
which we could contrast hands-on learning with, for example, teacher instruction.
Nevertheless, our task provided a context in which we could examine whether there were
measurable benefits to actively selecting one’s own interventions in circumstances where
children need to decide between different hypotheses. In the self-select condition, unlike
in the other two conditions, children freely decided what information to sample and when
to sample that information; this freedom with regard to information sampling can be seen
as the most important difference between active and passive learning conditions (Gureckis
& Markant, 2012). We found no evidence that such freedom yielded benefits. This suggests
that, at least on the face of it, in learning causal structure, children do not benefit
from being able to actively generate interventions in order to test specific hypotheses
that they may be entertaining, as opposed to either just observing such interventions or
carrying out interventions that were decided by another person. However, the results also
indicate a more nuanced conclusion because we examined not just whether levels of
performance differed depending on learning condition but also whether the quality of
interventions predicted performance even in yoked conditions. Interestingly, we found that
this predictive relation did not hold in our yoked conditions. This finding is reminiscent
of the results of correlational analysis conducted by Sobel and Kushnir (2006) on their
adult data. They calculated the proportion of interventions that participants self-
generated (or were exposed to in yoked conditions) that would provide information that was
critical for learning a particular causal structure (i.e., a simple measure of
intervention quality). They found that the correlation between the proportion of critical
interventions and accuracy in causal structure judgments was significant only in
conditions where participants generated the interventions themselves, not in yoked
conditions. Their interpretation of this finding is that participants who generate
critical interventions are better placed to interpret the outcome that results from an
intervention and use it to distinguish between hypothesized structures. Although we did
not find that self-generating interventions boosted learning, our findings are at least
compatible with Sobel and Kushnir’s (2006) suggestion that learning may proceed in a
different way under such conditions. When selecting interventions themselves, children who
were testing hypotheses in an effective way were able to select informative interventions
specifically to test particular hypotheses (consistent with Sobel & Kushnir’s
characterization of learning under this condition), and this may have underpinned the
relation between quality of interventions and performance. Gureckis and Markant (2012)
argued that when participants are selecting for themselves, they can preferentially select
information that reduces their current uncertainty. Indeed, the measure of quality of
interventions produced in our Bayesian modeling can be seen as a formal measure of the
extent to which participants are adept at selecting interventions to reduce uncertainty,
and it is this that predicted performance in the self-select condition. However, this mode
of learning was not available to children in the yoked conditions, which may be why there
was no relation between quality of interventions and performance in these conditions.
Note, however, that the unavailability of this mode of learning in the yoked conditions
did not significantly impair performance. It is possible that the benefits of active
hypothesis testing were outweighed in our study by the information processing demands of
selecting and implementing interventions, demands that were reduced in the yoked
conditions. Such a possibility is consistent with suggestions that there may be
disadvantages associated with self-directed learning (for discussions, see Gureckis &
Markant, 2012; Kirschner et al., 2006; Markant & Gureckis, 2014). Moreover, as Gureckis
and Markant (2012) pointed out, active learning might not necessarily be beneficial under
circumstances where learners are biased in their information seeking and focus, for
example, on confirming preexisting erroneous hypotheses. As we have discussed, there is
evidence that the younger children adopted such an approach to their intervention choices.
There may be other circumstances, however, where children’s causal learning would benefit
from the opportunity to engage in active hypothesis testing, but the broader literature on
self-directed learning has yet to clearly identify the situations where any advantages may
outweigh potential disadvantages (Gureckis & Markant, 2012).

<h>CONCLUSIONS</h>
-----------

The findings of this study point to two clear directions for future work in this area.
First, the fact that children become increasingly Bayes-efficient information seekers in
their causal learning raises the question of what cognitive changes underpin this
developmental shift. There has been considerable discussion over the role of Bayesian
modeling not only in a developmental context but also in providing an explanatory
framework within cognitive psychology more generally (e.g., Bowers & Davis, 2012; Jones &
Love, 2011; Schlesinger & McMurray, 2012). Here, we have used a Bayesian approach simply
to provide a more formal analysis of how the quality of children’s interventions improves
developmentally. Questions regarding the developmental changes that account for these
improvements cannot be directly addressed by the modeling reported here, which does not
model cognitive processes (although we note that directly inspecting the patterns of
children’s interventions suggested that some developmental changes have parallels to those
shown in the scientific learning literature). It is possible, however, that in the future
models based on approximate Bayesian inference that attempt to be more psychologically
plausible (Bramley, Dayan, et al., 2015; Kemp, Tenenbaum, Niyogi, & Griffiths, 2010;
Sanborn, Griffiths, & Navarro, 2010; Shi, Feldman, & Griffiths, 2008) may play a role in
addressing this question. Importantly, the developmental improvements found in our study
highlight the need for Bayesian models that not only capture idealized learning but also
can accommodate, and potentially explain, developmental changes in the quality of
children’s causal learning. Explaining developmental changes will require additional
research that builds on the current findings but also tries to examine in more detail the
role of particular types of cognitive processes such as children’s strategies. The second
direction for future research stems from our finding that although active learning, in the
form of self-selecting interventions, did not seem to benefit children’s causal structure
learning (beyond simply observing someone else’s interventions), our modeling raised the
possibility that learning may proceed in a qualitatively different way when children do
not have the opportunity to choose interventions themselves. This finding demonstrated the
potential benefits of examining not just whether causal learning is affected by whether or
not individuals can engage in more active learning but also how it may be differentially
related to the sort of information generated in active learning. Further examination of
potential qualitative differences looks like an important goal for future empirical and
modeling work on causal structure learning.


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<ART>Chinese sex differences in intelligence: Some new evidence
==========================================================

Authors: Jianghong Liu, Richard Lynn
DOI: 10.1016/j.paid.2014.11.002
Year: 2015  |  Pages: 90-93
ASJC codes: 3200
Keywords: China, Chinese, IQ, Intelligence, Sex differences, Variability, WISC-R

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Sex differences on the WISC-R in Chinese children were examined in a sample of 788 aged 12. years. Boys obtained a higher mean full scale IQ than girls of 3.75 IQ points, a higher performance IQ of 4.20 IQ points, and a higher verbal IQ of 2.40 IQ points. Boys obtained significantly higher means on the information, picture arrangement, picture completion, block design, and object assembly subtests, while girls obtained a significantly higher mean on coding. The results were in general similar to the sex differences in the United States standardisation sample of the WISC-R. Boys showed greater variability than girls.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The question of sex differences in intelligence has been debated from the early years of
the twentieth century. The almost unanimous consensus has been that there is no sex
difference in “general intelligence” defined as the average of the major cognitive
abilities and measured by tests like the Wechslers and the Binets. There are, however, sex
differences in a number of specific abilities. The conclusion that there is no sex
difference in “general intelligence” was reached in the second decade of the twentieth
century by Terman (1916, pp. 69–70) on the basis of his American standardisation sample of
the Stanford–Binet test. In recent decades this conclusion was endorsed by many leading
authorities. Thus “it is now demonstrated by countless and large samples that on the two
main general cognitive abilities – fluid and crystallized intelligence – men and women,
boys and girls, show no significant differences” (Cattell, 1971, p. 131); “gender
differences in general intelligence are small and virtually non-existent” (Brody, 1992, p.
323); “there is no sex difference in general intelligence worth speaking of” (Mackintosh,
1996, p. 567); and “sex differences have not been found in general intelligence” (Halpern,
2000, p. 218). The only challenge to this consensus has come from Lynn (1994, 1998, 1999),
who has argued that males have larger average brain size than females, that brain size is
positively correlated with intelligence at a magnitude of approximately .40 (Vernon,
Wickett, Bazana, & Stelmack, 2000), and hence that there is a theoretical expectation that
males should have higher average intelligence than females. To examine this theoretical
expectation, Lynn (1994) proposed that the Wechsler intelligence tests could be taken as
among the best measures of general intelligence on the grounds that they provide measures
of the major cognitive abilities of verbal, numerical, perceptual, reasoning, spatial,
immediate memory, perceptual speed and general knowledge. He then examined the sex
difference in eight standardization samples of the Wechsler intelligence tests for
children aged 6–16 and showed that boys obtained a higher mean Full Scale IQ by an
advantage of 2.25 IQ points. He also showed that in six standardization samples of adults,
men obtained a higher mean Full Scale IQ by an average of 3.08 IQ points. Despite these
results, it has continued to be asserted that “females and males score identically on IQ
tests” (Halpern, 2012, p. 233) and that “there is no evidence, overall, of sex differences
in levels of intelligence” (Sternberg, 2014, p.178). However, Ellis et al. (2008) recently
argued in their book that studies have shown that, although small, there are significant
sex differences in intelligence over the years throughout the world. It has also been
consistently asserted for approximately a century that while males and females have the
same average intelligence, males have greater variability of intelligence than females. An
early first statement of this proposition was made by Ellis (1904, p.425): “It is
undoubtedly true that the greater variational tendency in the male is a psychic as well as
a physical fact”. This sex difference in variability was reaffirmed by Thorndike (1910)
and by many subsequent authorities including Penrose (1963, p. 186) “the consistent story
has been that men and women have nearly identical IQs but that men have a broader
distribution…the larger variation among men means that there are more men than women at
either extreme of the IQ distribution”. Others who have asserted this conclusion include
Herrnstein and Murray (1994, p. 275), Lehrke (1997, p. 140), Jensen (1998, p. 537), and
Ceci and Williams (2007, p. 223): “all sides in the gender wars agree that there is
greater variability in male distributions of many abilities.” This conclusion has recently
been affirmed once again by Deary, Penke, and Johnson (2010): “Males have a slight but
consistently wider distribution than females at both ends of the range.” There is a large
research literature on sex differences in various cognitive abilities. Kimura (1999, 2002)
lists five abilities on which males obtain higher average means than females: spatial
orientation, visualization, line orientation, mathematical reasoning, and throwing
accuracy; and five abilities on which females obtain higher average means than males:
object location memory, perceptual speed, verbal memory, numerical calculation, and manual
dexterity. In this paper we examine sex differences in intelligence in China with a view
to determining how far these are consistent with those found in studies in the United
States and other western countries on which most of the conclusions have been based.

<h>METHOD</h>
------

A Chinese sample of 788 children in the sixth grade aged 11–13 years with a mean age of
12.5 was tested with the Chinese version of the Wechsler Intelligence Scale for Children-
Revised (WISC-R) in 2011–13. The sample was obtained from the Jintan Child Cohort Study.
The Wechsler (1974) original sample in this study comprised 1656 Chinese children (55.5%
boys, 44.5% girls) consisting of 24.3% of all children in this age range in the Jintan
region, which is located in Jiangsu, China. This sample includes children from city, town,
and village populations; in addition, the demographics of Jiangsu are similar to those
found on the national level, making this sample likely to be fairly representative in
terms of sex ratio, urban versus rural population ratio, ethnic majority, and others. The
Jintan Child Cohort Study is an on-going prospective longitudinal study with the aim of
exploring early health risk factors in the development of child cognition and behavior.
Details of this study have been described in a previous publication (Liu, McCauley, Zhao,
Zhang, & Pinto-Martin, 2010). The cohort took their first IQ test (the WPPSI) at age 6
years and the sex differences have been given by Liu and Lynn (2011, 2013) and Liu, Yang,
Li, Chen, and Lynn (2012). The Chinese version of the Wechsler Intelligence Scale for
Children-Revised (WISC-R) with which the children were tested was standardized in China in
1985 and has shown good reliability in Chinese children (Yue & Gao, 1987). The WISC-R
consists of six verbal subtests, namely Information, Comprehension, Arithmetic, Vocabulary
Similarities and Digit Span, that are summed to give the Verbal IQ, and of six non-verbal
subtests, namely Picture Arrangement, Picture Completion, Object Assembly, Block Design,
Coding and Mazes tests, that are summed to give the Performance IQ. The Verbal IQ and
Performance IQs are combined to give a Full-Scale IQ. The WISC-R IQs of the 2011–13
Chinese sample were collected between spring 2011 and summer 2013 when the participants
were in sixth grade or had just graduated from sixth grade. Participants were invited to
the laboratory, where research assistants, who participated in an intensive training
course, administered the Chinese WISC-R. Ten of the subtests were used, Digit Span and
Mazes being omitted. The research assistants were supervised by a Ph.D. trained clinical
psychologist who specializes on cognitive brain assessment at Nanjing Brain Hospital. The
same training procedure as described in detail in Liu and Lynn (2013) was followed. The IQ
test was administered over the course of one hour in a quiet room in Jintan Hospital. Each
test was scored by two individuals to minimize scorer bias. This procedure for data
collection was approved by the research ethics committee of Jintan Hospital and the
University of Pennsylvania. Written consent was obtained from parents and written assent
from children was collected prior to initiation of the study.

<h>RESULTS</h>
-------

Table 1 gives the mean scaled scores and standard deviations for boys and girls on the
subtests, and the verbal, performance and full scale IQs on the Chinese WISC-R of the
2011–2013 Jintan sample. Also given are the differences between the means of the boys and
girls expressed as ds (the difference between the means divided by the pooled standard
deviation, with minus signs showing that girls obtained higher means than boys), the t
values using independent sample t-tests for the statistical significance of the
differences between the means of the boys and girls, and the variance ratios (VR) as a
measure of the sex differences in variability calculated as the standard deviation of the
males divided by the standard deviation of the females. Thus, a VR greater than 1.0
indicates that males had greater variance than females. Table 2 gives sex differences on
the WISC-R in China and in the standardization sample (N = 2200) in the USA given by
Jensen and Reynolds (1983).

<h>DISCUSSION</h>
----------

The results provide six points of interest. First, it is shown in Table 1 that in the
present Chinese sample boys obtained a significantly higher Full Scale IQ than girls by
0.25d, the equivalent of 3.75 IQ points. This figure is higher than the average boys’
advantage of 2.25 IQ points on the Wechsler Full Scale IQ in eight standardization samples
of the Wechsler tests for children noted in the introduction. In the present Chinese
sample boys obtained a significantly higher Performance IQ than girls by 0.28d, the
equivalent of 4.2 IQ points, and a significantly higher Verbal IQ than girls by 0.16d, the
equivalent of 2.40 IQ points. These results provide additional evidence that modest but
significant sex differences exist in intelligence, thus refuting continued assertions that
no differences exist (e.g., Halpern, 2012, p. 233; Sternberg, 2014, p. 178) Second, there
are six statistically significant sex differences on the subtests of the WISC-R in the
present Chinese sample shown in Table 1. Boys obtained significantly higher means than
girls on Information, Picture Arrangement, Picture Completion, Block Design and Object
Assembly, and girls obtained a significantly higher mean than boys on Coding. Third, on
several of the subtests, the sex differences in the present Chinese sample were consistent
with those in the American standardization sample shown in Table 2. The advantage of boys
in the present Chinese sample on Information is virtually identical to that in the United
States with statistically significant ds of .44 and .37, respectively. These results
confirm those of several studies of the Wechsler information tests among adults and of
other studies finding that among adults men have significantly higher means than women on
information and general knowledge (Lynn & Irwing, 2002; Lynn, Irwing, & Cammock, 2002).
The advantage of boys in the present Chinese sample on Picture Arrangement is consistent
with that in the American standardization sample with statistically significant ds of .19
and .11, respectively. The advantage of boys on Object Assembly in the present Chinese
sample is also consistent with that in the United States with statistically significant ds
of .38 and .18, respectively. Boys obtained higher scores on Picture Completion in the
present Chinese sample (.19) and in the U.S. (.15) and on Block Design with ds of .19 and
.15, respectively. The higher means obtained by boys in both China and the United States
on Picture Arrangement, Object Assembly, Picture Completion and Block Design are
explicable because these are all measures of visual–spatial abilities on which males
typically obtain higher means than females (Linn & Peterson, 1985; Voyer, Voyer, & Bryden,
1995). The statistically significant advantage of girls on Coding in the present Chinese
sample is consistent with the higher mean obtained by girls in the United States with ds
of .41 and .53, respectively. Fourth, on Comprehension and Similarities the sex
differences in the present Chinese sample, where both boys and girls score similarly at
.00 and −.01, is consistent with those in the American standardization sample with ds of
.01 and .07. Fifth, there is some inconsistency in the sex difference in Vocabulary, where
there was no significant difference between boys and girls in the Chinese sample (d =
−.03) but boys obtained a significantly mean in the American sample (d = .14). Sixth, the
frequent assertion that males have greater variability of intelligence than females is
generally confirmed in the present Chinese sample. Boys had greater variability than girls
on the Verbal, Performance and Full Scale IQs and in six of the ten subtests. However,
girls had greater variability than boys in Comprehension, Vocabulary and Block Design, and
there was no difference in the variability of boys and girls on Similarities. Future
studies might consider controlling for sociodemographic variables to further validate this
finding.


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<ART>Comparing methods for measuring peak look duration: Are individual differences observed on screen-based tasks also found in more ecologically valid contexts?
================================================================================

Authors: Sam V. Wass
DOI: 10.1016/j.infbeh.2014.04.007
Year: 2014  |  Pages: 315-325
ASJC codes: 3204
Keywords: Attention, Infant, Naturalistic attention, Peak look duration, Sustained attention

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Convergent research points to the importance of studying the ontogenesis of sustained attention during the early years of life, but little research hitherto has compared and contrasted different techniques available for measuring sustained attention. Here, we compare methods that have been used to assess one parameter of sustained attention, namely infants' peak look duration to novel stimuli. Our focus was to assess whether individual differences in peak look duration are stable across different measurement techniques. In a single cohort of 42 typically developing 11-month-old infants we assessed peak look duration using six different measurement paradigms (four screen-based, two naturalistic). Zero-order correlations suggested that individual differences in peak look duration were stable across all four screen-based paradigms, but no correlations were found between peak look durations observed on the screen-based and the naturalistic paradigms. A factor analysis conducted on the dependent variable of peak look duration identified two factors. All four screen-based tasks loaded onto the first factor, but the two naturalistic tasks did not relate, and mapped onto a different factor. Our results question how individual differences observed on screen-based tasks manifest in more ecologically valid contexts. © 2014 The Authors.

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<h>INTRODUCTION</h>
------------

Research is increasingly suggesting that early-developing, domain-general aspects of
attentional control may mediate subsequent skill acquisition in a variety of areas (e.g.
Heckman, 2006; Karmiloff-Smith, 1998; Wass, Scerif, & Johnson, 2012). For example, aspects
of domain-general attentional control have been shown to predict, on starting school,
children's’ subsequent learning on literacy and numeracy tasks (e.g. Welsh, Nix, Blair,
Bierman, & Nelson, 2010). And research into the development of attentional control within
clinical disorders suggests that early disruption to attentional control may play a key
role in impairing early learning in social settings, for example during word learning,
leading to subsequent catastrophic developmental cascades (e.g. Karmiloff-Smith, 1998).
This suggests the importance of researching the ontogenesis of attentional control during
the first few years of life. Cohen suggested that infant attention involves at least two
different mechanisms: an attention-getting process which determines whether an individual
will orient towards a stimulus presented in his periphery, and an attention-holding
process which determines how long his attention will be maintained once he fixates (Cohen,
1972). This second phase, the attention-holding process, is commonly described as
‘sustained attention’ (Richards, 2011). However, although individual differences in
attention are frequently reported in applied and developmental psychology, the terms used
are rarely precisely defined and are conventionally assessed using a variety of methods.
Historically, the most widely used technique for measuring infants’ looking behaviour
involves presenting static stimuli using a slide projector or computer screen across a
number of discrete but contiguous trials; the infant's viewing behaviour is coded either
live by an experimenter viewing the infant on a video feed, or post hoc (Colombo &
Mitchell, 2009). Two variables are typically derived: peak look duration, the duration of
the longest unbroken look to the screen, and habituation rate, i.e. the rate of change of
looks over time. Colombo and Mitchell argued in favour of peak look duration as the better
metric of individual and developmental differences in visual attention during infancy
because it is more reliable, and shows more robust relationships with long-term cognitive
outcomes (Colombo & Mitchell, 1990). Previous research has demonstrated that peak look
duration to novel, static, screen-based stimuli show a U-shaped trajectory over the first
year of life (Colombo & Mitchell, 2009; Colombo & Cheatham, 2006; Courage, Reynolds, &
Richards, 2006). Research has also robustly demonstrated that peak look duration to novel
stimuli during the first year of life relates negatively with long-term cognitive
outcomes: shorter look duration during the first year is associated with better
performance on later IQ and language measures (Colombo, 1993; McCall & Carriger, 1993;
Tami-LeMonda & Bornstein, 1989) and recognition memory (Rose, Feldman, & Jankowski, 2003a,
2003b). Shorter looking is also associated with higher pre-existing knowledge bases and
general arousal levels (de Barbaro, Chiba, & Deak, 2011; Dixon & Smith, 2008). An
alternative technique for assessing looking durations during infancy involves presenting
dynamic stimuli on a computer screen (Courage et al., 2006; Shaddy & Colombo, 2004; see
Richards, 2010 for a review). This work has generally used either TV clips (e.g. Richards
& Anderson, 2004) or specially filmed naturalistic or semi-naturalistic dynamic scenes
(Wass, Porayska-Pomsta, & Johnson, 2011). These techniques have been used to investigate
how autonomic indices change in different attention states (Richards, 2011; Richards &
Cronise, 2000), how looking behaviour towards the screen changes over time (Anderson,
Choi, & Lorch, 1987; Richards & Anderson, 2004), and how these changes are different in
children with Attention Deficit Hyperactivity Disorder (ADHD) (Lorch et al., 2004). To our
knowledge, no research has investigated whether individual differences in look duration
are consistent across static vs. dynamic looking time paradigms. A third paradigm that has
been used to assess looking durations involves presenting a number of unfamiliar objects
consecutively or concurrently in a table-top setting, and performing video coding post hoc
to analyse looking behaviour. For example, Kannass and Oakes (2008) videoed 9-month-old
and 31-month-old infants playing with toys, in both single-object (objects presented
consecutively) and four-object (objects presented concurrently) conditions; they also
measured 31-month language performance in the same children (see also Sarid & Breznitz,
1997). They found that shorter look durations in the single-object task correlated with
larger vocabularies at 31 months (Kannass & Oakes, 2008). For the multiple object
condition, however, they found the opposite relationship: longer durations at 9 months
correlated with larger vocabularies at 31 months (see also Choudhury & Gorman, 2000).
Despite the strong face similarities between these paradigms, no previous research has
assessed whether individual differences using one type of looking time paradigm are
consistent across different assessment techniques. A number of studies have addressed this
indirectly, but none directly. Kagan and Lewis (1965) examined the relationship between
looking behaviour towards static stimuli at 6 and 13 months and the amount of free-play
locomotor activity at 13 months, and found that infants with long fixation times at 6 and
13 months were more sedentary during free play. Coldren found that infants’ attention to
stimuli in laboratory tasks correlated with the attention to their caregiver in face-to-
face interactions at 3- and 4-month-olds but not at 6 months (Coldren, unpublished data,
described in Colombo & Mitchell, 1990). Pêcheux and Lécuyer (1983) found with 4-month-olds
that fixation time towards static stimuli was positively correlated with their visual
exploration of a toy (Fig. 1). This gap in the literature is important for a number of
reasons. As we note in Part 2, there are a number of marked differences between these
different looking time paradigms, such as: the size of the target towards which attention
is being directed, the presence or absence of movement in the target or periphery of the
visual field of the child, and the relative luminance of the target relative to other
elements within the infants’ field of view (Fig. 2). In the absence of data showing cross-
paradigm consistency, we cannot be sure how individual differences in attention as
assessed using screen-based tasks might relate to individual differences in attention in
naturalistic settings. Are the dissimilarities between screen-based and naturalistic
attention tasks documented in Fig. 2 incidental to the individual differences that are
assessed on these tasks? Or are they central to them? Within the habituation literature,
shorter looking to static stimuli during the first year is frequently described as an
index of ‘faster processing speed’; this is frequently posited as an explanation for the
negative correlations noted between look duration during the first year and long-term
outcomes (Colombo & Cheatham, 2006). One question that follows from this is: does ‘faster
processing’ as assessed using screen-based attention tasks also manifest as different
(‘better’, or ‘more efficient’) orienting in naturalistic contexts? Or is shorter looking
to screen-based stimuli associated with better long-term outcomes because both measures
tap some underlying, ‘pure’ aspect of cognition that is entirely independent of
naturalistic orienting? The present study is intended as a small step towards addresing
these questions.

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

As described above, there exists to our knowledge no previous research that has addressed
whether individual differences in peak look duration are consistent across different
assessment techniques. The present study was conducted in order to address this question.
We presented four screen-based assessments, namely: (i) looking behaviour towards
‘interesting’ (complex) static stimuli, (ii) ‘boring’ (non-complex) static stimuli, (iii)
mixed static and dynamic stimuli and (iv) to videos under conditions of distraction
(during the recording of EEG data). We also presented two semi-naturalistic looking
assessments involving the presentation of novel objects in a table-top setting, in (i) a
single-object condition (novel objects presented one by one) and (ii) a four-object
condition (four novel objects presented concurrently) (following (Kannass & Oakes, 2008).
The six measures were presented in different testing rooms and inter-leaved in order, to a
single cohort of typically developing 11-month-old infants. 11-months was chosen as the
age for the present study because this has been characterised as an age that shows the
first emergence of endogenous attentional control (Colombo & Cheatham, 2006; Courage et
al., 2006). Across all six paradigms, the single dependent variable we assessed was peak
look duration. This was selected because it has previously been argued to be the most
stable assessment of looking behaviour during infancy–in comparison for example to
habituation rate (the rate of change of looks over time), which is less reliable, and
shows less robust relationships with long-term cognitive outcomes (Colombo & Mitchell,
1990). As far as possible, peak look duration was assessed identically across the six
paradigms we administered. From reviewing the literature we were able to find no
discussions suggesting that different factors might influence peak look duration
differentially between screen-based and semi-naturalistic settings. Therefore we predicted
that individual differences in peak look duration would be consistent across all the
paradigms administered.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

42 typically developing 11-month-old infants participated in the study. Mean age at
testing was 337 days (range 312–259, standard deviation 9). Gender ratios were 26 male/16
female. Of note, other aspects of these data have already been published elsewhere (Wass
et al., 2011; Wass & Smith, 2014). The current data contain, however, completely novel
analyses which do not overlap with previous publications.

<hs>  Apparatus and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

The six peak look assessments were administered in three sections. Section A consisted of
the ‘static non-complex’ assessment, the ‘static complex’ assessment and the ‘mixed
dynamic/static’ assessment. Section B consisted of the ‘structured free play’ assessment.
Section C consisted of the ‘videos during EEG’ assessment. Presentation order. All three
sections were administered during a single visit, which generally lasted c. 90 min with
breaks. Section A was presented in two halves (‘A1’ and ‘A2’). The order in which the
sections were administered was: Section A1, then Section B, then Section A2, then Section
C. The naturalistic ‘structured free play’ assessment (Section B) was therefore presented
between the other screen-based tasks. This design was chosen in order to preclude the
possibility of order effects being responsible for the results observed. Testing rooms.
Sections A–C were each presented in different rooms. Of note, therefore, the screen-based
tasks included in Section C were presented in a different room to the screen-based tasks
in Section A. In the detailed descriptions of the methods that follows, materials are
described section by section, together with the data processing techniques that were used.

<hs>  Section A – ‘static non-complex’/‘static complex’/‘mixed dynamic/static’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Materials. For the three peak look assessments contained in section 1 infants were seated
on their caregiver's lap while the viewing material was presented on a Tobii 1750
eyetracker subtending 24° of visual angle. The three assessments were presented
interleaved with each other. Static non-complex images. Two different still images were
presented at different stages of the testing protocol. The two ‘non-complex’ images were
both monochromatic objects presented against a white background (see Fig. 1 for example).
Trials were presented concurrent with child-friendly music, such as songs from Sesame
Street. Four different songs were used that were paired randomly with the different
images. All infants heard the same four songs over the course of all experiments. Trials
were presented using a gaze-contingent infant-controlled habituation protocol procedure:
images were presented and remained on-screen for as long as the infant looked to the
screen. Following cessation of a look, the image was re-presented until two successive
looks had taken place that were less than 50% of the longest look so far. In order to
confirm eyetracker contact, a small (c. 0.4°) re-fixation target was briefly presented
every 15 s; subsequent analyses (described in the Supplementary Materials) suggested that
this did not influence the timing of peak look duration measure. Peak look was calculated
independently for each image and then averaged. Static complex images. The two ‘complex’
images were polychromatic scenes (see Fig. 1 for example). The testing procedures used
were identical to those used for the static non-complex assessment. For practical reasons,
individual trials were capped at 120 s; 11 out of the 152 individual trials included
reached this cap (see Fig. S1). To confirm our classification of images into ‘complex’ and
‘non-complex’ feature congestion was calculated for each image using Matlab scripts from
Rosenholtz, Li, and Nakano (2007). Feature congestion quantifies local variability across
different first-order features such as colour, orientation and luminance; see SM for a
more detailed description. For the two ‘non-complex’ images, average feature congestion
across the whole frame was found to be 1.7 and 1.6; for the two ‘complex’ images, average
feature congestion was 7.6 and 5.1 (see Fig. S2). This confirmed our classification of the
stimuli into ‘complex’ and ‘non-complex’. Mixed static/dynamic images. 3 blocks of mixed
static and dynamic images were presented at different stages of the testing protocol. Each
block lasted 65 s. Each block consisted of a mixture of: head shots of actors (single and
in groups) reciting nursery rhymes, still images of actors’ faces, and shots of toys and
birds accompanied by background music (see Fig. 1 for example). The individual stimuli
within each 65-s block each lasted 4–12 s. As with the static images, a small re-fixation
target was briefly presented c. every 15 s in order to confirm eyetracker contact (see
analyses in SM). Data processing. Infants’ looking behaviour was coded from a camera on
top of the monitor. Gaze was coded in 1-s bins, as either looking at the screen or not.
Total percentage looking time and the length of each unbroken look to the target were
calculated. Instances in which the participant looked away from and then back to the
screen within 1 s were treated as constituting one continuous look rather than two
discrete looks. Coder 1 coded 76%, coder 2 48%; 25% of the videos were double coded.
Cohen's kappa was calculated to assess inter-rater reliability and was found to be 0.71.

<hs>  Section B – ‘structured free play’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Materials. The two peak look assessments contained in Section 2 were conducted in a puppet
theatre with attractive surrounds, and a stage behind which experimenter and the camera
were visible. Infants sat on their caregiver's lap, close enough to the stage so that they
could reach to and touch the objects on it. Between each trial, the curtains of the puppet
theatre were closed and new objects were placed on the stage; reopening them marked the
start of the next trial. The two assessments were presented consecutively: Free play –
1-object condition. In the single-object condition, five objects (an plastic figure/a
basting pipette/a glitter lamp/a lion mask/a rabbit mask) were presented in randomised
order consecutively for 30 s each. Fig. 1 shows an example of the objects used; Fig. S3
shows images of all the objects used. The objects used varied in size from 5–20 cm. Free
play – 4-object condition. The four-object condition was presented immediately after the
one-object condition. Four objects (a rubber duck, a plastic train, a plastic teddy bear,
a tiger finger puppet) were presented concurrently in a line across the stage, in a
randomised order, for 90 s. The objects used varied in size from 5 to 10 cm. Data from 10
participants was unusable for the four-object condition due to changes made to the
experimental protocol during testing. Data processing. Infants’ looking behaviour was
recorded from a camera positioned behind the stage. The coding protocol used was based on
that used by Kannass and Oakes (2008). Infants’ looking behaviour was coded for whether
the infant was looking at the object or not. Sections where the object was not on the
stage (because the infant had knocked or thrown it off) were excluded. All coding was
conducted in 1-s bins. Data were triple coded. Coder 1 coded 70%, coder 2 50% and coder 3
24%; 40% were double coded by coders 1 and 2 and 24% by coders 1 and 3. Cohen's kappa was
calculated to assess inter-rater agreement. This was found to be 0.72 between coders 1 and
2 and 0.78 between coders 1 and 3.

<hs>  Section C – ‘videos during EEG’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Materials. The peak look assessment contained in Section 3 was presented with infants
sitting on their caregiver's lap while viewing materials were presented on a cathode ray
TV subtending 30° of visual angle. Simultaneously with the administration of this task,
infants were having EEG data recorded using a 128-channel EGI hydrocel net (Wass, 2011).
Only one assessment was presented in this section: Videos during EEG. Three videos were
presented sequentially in rotation during EEG recording. These videos were: (i) a series
of actresses reciting nursery rhymes to camera; (ii) videos of toys spinning; (iii) a
short TV clip. Videos lasted 32–44 s each. Each video was presented twice. Data
processing. Infants’ looking behaviour was recorded from a camera positioned below the
monitor. Videos were coded according to whether the infant was looking to or away from the
screen, using an identical coding scheme to that used in sections and 2. Coder 1 coded
76%, coder 2 48%; 24% were double coded. Cohen's kappa was calculated to assess inter-
rater reliability and was found to be 0.88.

<h>RESULTS</h>
-------

The results section is in two parts. Firstly, descriptive statistics of the looking time
data obtained from the different paradigms are presented. Secondly, analyses are presented
that examine the inter-relationships in looking time across the different assessments
administered. Specifically we wished to evaluate the hypothesis that individual
differences in looking time would be consistent across the six assessments.

<hs>  Part 1 – Descriptive statistics of looking time data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Descriptive statistics for the entire data set are shown in Table 1. For each assessment,
mean peak look oberved across all infants has been reported, together with the Standard
Error of the Mean (S.E.M.) and range. Additionally, for comparison, identical data have
been reported for mean look duration (i.e. the average of all looks recorded towards the
stimuli). For each assessment, the number of participants who provided usable data is
shown in the final column. With the exception of the free-play 4 object task, for which
(as described above) changes were made to the experimental protocol during testing, drop-
out rates are acceptable (maximum 4/42). These were due to fussiness and non-compliance
during testing. Fig. 3a–f shows histograms of all the individual looks collected on the
different tasks. Fig. 3g shows plotted lognormal fittings. Lognormal distributions were
calculated as these are generally reported to be the best fit on infant looking time data
(Pempek et al., 2010; Richards & Anderson, 2004). Marked differences in the patterns of
look durations observed on different tasks can be seen: both peak and mean look duration
were higher for all of the screen-based tasks than for the structured free play tasks.
Within the screen-based tasks, markedly longer peak looking times were observed in the
static complex and mixed dynamic-static categories than in the other categories. The
between-participant distributions of peak look durations were found to be positively
skewed, in common with all looking time assessments (see e.g. Richards & Anderson, 2004);
therefore all subsequent analyses have been calculated based on log-transformed data
(following e.g. Frick, Colombo, & Saxon, 1999).

<hs>  Part 2 – Analyses to examine the inter-relationships in looking time across the different assessments administered</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We wished to evaluate the hypothesis that individual differences in looking time would be
consistent across the six assessments we administered. In order to examine this, two
analyses were conducted. First, zero-order correlations were calculated. Second, a factor
analysis was performed. First, histograms and scatterplots were calculated to assess
whether per-participant peak look values derived from the log-transformed data were
parametrically distributed, and whether any bivariate relationships observed were robust.
Fig. 4 shows these scatterplots. All parameters were found to be normally distributed.
Zero-order correlations. Fig. 4 shows the zero-order bivariate correlations that were
observed between the variables entered into the factor analysis. The four screen-based
tasks (static complex, static non-complex, mixed dynamic-static, videos during EEG) all
show significant correlations (r = .33 to .56, all ps < 05) with the exception of the
static complex to dynamic during EEG (r = .24, p < .10). Inspection of the scatterplot
(Fig. 4) suggests that this relationship is weakened by an outlier. In comparison the two
FP tasks do not correlate with any of the screen-based tasks (negative in 5 of the 9
comparisons conducted, and r < = .12 in the remaining 4). The scatterplots in Fig. 4
suggest that this not attributable to the presence of outliers. One explanation that was
considered for the low zero-order correlations observed with the free play data was that
these data were inherently more ‘noisy’ than the screen-based looking time data. In order
to evaluate this possibility, data were examined from an overlapping dataset that has been
published previously (Wass, 2011; Wass et al., 2011). In this paper, an identical task to
that presented here was presented twice at fifteen days’ interval to a smaller cohort (N =
21) of infants. Analyses assessed the number of total attentional reorientations and
attentional shifts from object to person. Test-retest reliability between the two testing
sessions was r = .53, p < .01 for total attentional reorientations, and r = .52, p < .05
for attentional shifts from object to person. This suggests that these measures are
relatively stable as indices of individual differences. Factor analysis. Factor analyses
were conducted to examine the factorial structure underlying our data in more detail. Our
analytical approach was based on that used in previously published research (Rose,
Feldman, & Jankowski, 2004, 2005). First, the sample size was examined. The ratio of
participants to variables for the factor analysis was found to be 6.3, which is above the
prescribed ratio of 5 suggested by Hair, Tatham, Anderson, and Black (1998). To maximise
the sample size for factor analysis, missing values were imputed based on the mean of the
subscale to which that item belonged (following Blair & Razza, 2007). The factor analysis
yielded a two-factor solution (Eigenvalues >1.0) representing 59% of the total variance
(see Table 2). These two factors were submitted to a principal axis rotation (oblimin) and
the scree plot was inspected, supporting a two-factor solution. Thresholds were set at
0.70 for principal loading and 0.50 for secondary loading (Guadagnoli & Velicer, 1988).
The first factor, which had an Eigenvalue of 2.29 and accounted for 38% of the variance,
was defined by three of the screen-based tasks, with the fourth screen-based task allotted
a secondary loading. The second factor, with an Eigenvalue of 1.23, was loaded onto by the
two FP variables (4-object as primary loading and 1-object as secondary loading), and
(negatively) by the static complex variable (primary loading).

<h>DISCUSSION</h>
----------

Our analyses were designed to assess whether individual differences in peak look duration
are consistent across different looking time measurement paradigms. To 42 typically
developing 11-month-old infants we administered six assessments of peak look duration,
including four screen-based assessments and two free-play based assessments. We predicted
that results obtained would be consistent across all paradigms. The results were not as
predicted. The factor analysis suggested a two-factor solution. The first factor was
defined by the four screen-based tasks (‘static non-complex’, ‘mixed dynamic-static’ and
‘videos during EEG’, with ‘static complex images’ as a secondary loading). The second
factor was defined by the two free play tasks (one as a secondary loading) and also (with
a negative loading) by the static complex screen task. The four screen-based tasks were
administered across different testing rooms, and interspersed with the free play tasks,
which precludes the possibility of room or order effects being responsible for our
results. Looking time to static screen stimuli and to dynamic screen stimuli showed strong
correlations. Strikingly, we also found that looking behaviour towards a TV screen during
recording of EEG data, which has the additional variance of tightness of fit of the EEG
net, reactivity to testing and so on, mapped onto the same factor as the other three
screen-based tasks, that were administered using a different screen in a different room.
In contrast the two FP assessments mapped onto a separate factor, and showed non-
significant (max r = .12) zero-order correlations with each of the screen-based tasks. The
zero-order correlations observed between the FP and screen-based tasks were negative in 5
out of 8 comparisons. In the factor analysis, the only screen-based task (static complex)
that loaded on to the second factor loaded on negatively (higher looking time to static
complex images associated with lower looking time during structured free play). Further
analyses were conducted to assess the possibility that these findings might be
attributable to other factors such as increased measurement error during the
administration of the free play tasks, with negative results. There are a number of
limitations to this study. The sample size was relatively small (N = 42), and a number of
techniques used by other researchers to complement looking time measures (such as heart
rate measurement and focused attention coding) were not applied. Furthermore, measurements
were only taken with one age group (11-month-olds), whereas the limited data available
suggests that different results may have been observed if the experiment were repeated
with younger infants (Coldren, unpublished data; discussed in Colombo & Mitchell, 1990).
Nevertheless, our results suggest that, in 11-month-old infants, individual differences in
peak look duration are constant across different screen-based tasks but not between
screen-based and semi-naturalistic tasks. We were able to find no discussion in the
literature suggesting that different factors might influence peak look duration between
screen-based and semi-naturalistic settings. What kinds of differences might these be? The
following discussion is structured around a number of factors commonly thought to
influence peak look duration. The first factor commonly associated with peak look duration
is processing speed. Sokolov argued that the initial presentation of a novel stimulus
produces a conflict between a “neural model” of the current environment and the sensory
processes occurring in the brain; prolonged exposure to that stimulus allows the viewer to
form an internal representation of it, which is why looking durations decline over time
(Sokolov, 1963). ‘Faster processors’ are thought to require less time to form an internal
representation; this is frequently linked to the finding that shorter peak look duration
to static stimuli during the first year correlates negatively with long-term cognitive
outcomes (e.g. Rose et al., 2002; Rose, Feldman, Jankowski, & Van Rossem, 2008). Advocates
of the importance of processing speed in influencing peak look duration might predict that
individual differences would not be stable between looking time to static screen and
dynamic screen stimuli, since one involves static visual information and the other
constantly changing information. They might also suggest that individual differences might
be stable between static screen and our free play task, since both require forming
internal representations of static targets (on-screen pictures and ‘real-world’ objects).
In fact we found the opposite pattern: individual differences in peak look duration were
consistent across the static screen and dynamic screen stimuli but not with the free play
task. A second factor related to peak look duration is ease of disengaging of visual
attention. Frick and colleagues measured the relationship between experimentally assessed
attentional disengagement latencies and spontaneous looking behaviour to static screen
stimuli in typically developing 3- and 4-m-os (Frick et al., 1999). They found that long-
looking infants showed greater variability in their response latencies. This suggests
that, at least in younger infants than the 11-month-olds studied here, attentional
disengagement may play a role in mediating spontaneous looking behaviour. This is one area
where differences can be noted between our screen-based and semi-naturalistic paradigms
(see Fig. 2). Screen-based paradigms tend to be designed with the screen occupying a
relatively large proportion of the infant's visual field (typically c.25° of visual angle,
as here), whereas in FP paradigms the target is generally much smaller (c. 5° in our
case). In screen-based tasks the target is generally much more luminant than the surrounds
(which are typically dark); in our free play paradigms, in contrast, this was not the case
(see Fig. 2). Lastly, in screen-based tasks there are sharp luminance contrasts between
the edge of the screen and the surrounds; again, these were not present in the FP task
(see Fig. 2). These differences may be important because previous research has noted that
viewers tend to dwell on areas of high luminance contrasts such as object boundaries.
Although this effect has been reported at all ages from 6-week-old infants (Bronson, 1994)
through to adults (Henderson & Smith, 2009) its effect has been reported to decline with
increasing age (Frank, Vul, & Johnson, 2009; Karatekin, 2007). The high-contrast and
prominent luminance contrasts present in our screen-based but not in our naturalistic
tasks may influence behaviour in the current study, and perhaps more for some infants than
others. A third factor that may relate to peak look duration is autonomic arousal. This
can be assessed in both phasic (i.e. event-related) and tonic contexts (de Barbaro et al.,
2011; Richards, 2011). Richards and colleagues explored changes in heart rate variability
and peak look during object examination; they found a decrease in variability during
attention, which was interpreted as consistent with a model of phasic parasympathetic
vagal influence on the heart during sustained attention phases (Richards & Casey, 1991;
Richards, 2011). Of note, our screen-based tasks (particularly the static screen stimuli)
contained abrupt changes in luminance coincident with the onset of each trial: the screen
transitioned from dark to bright in an otherwise darkened room and an auditory stimulus
was presented; such changes were completely absent in the naturalistic task. It is
possible that these abrupt changes in luminance are associated with phasic changes in
sympathetic/parasympathetic nervous system balances, and that some infants are more
susceptible to these changes than others (Alkon et al., 2006). This factor would influence
looking behaviour in the screen-based but not the naturalistic looking time tasks. Aston-
Jones and colleagues suggested a role for brainstem, Norepinephrine modulated arousal
systems in shifting between attention states; they distinguish between a ‘scanning’ mode,
in which look durations are short and the focus of visual attentiveness is wide, and a
‘focused’ mode, in which look durations are longer and the spatial distribution of
attention is narrower (Aston-Jones, Rajkowski, & Cohen, 1999; Aston-Jones, Iba, Clayton,
Rajkowski, & Cohen, 2007; cf. Pannasch et al., 2008). In our semi-naturalistic tasks,
other targets (objects and people) are present within the peripheral visual field of the
infant, whereas attempts were made to ‘black out’ all peripheral objects for the screen-
based tasks (as is typical in other labs) (see Fig. 2). The shifting between attention
states that Aston-Jones and colleagues describe may therefore be a factor in our semi-
naturalistic tasks but not in our screen-based tasks. A fourth factor that may relate to
peak look duration is executive control. Aspects of executive control have been reliably
associated with sustained attention in older children (e.g. Reck & Hund, 2011). (Note
however that sustained attention in these studies with children is assessed not using
looking time measures but with tasks such as the Continuous Performance Task, whose
relationship with peak look duration has, to our knowledge, not been studied.) Colombo and
Cheatham point out that positive correlations are observed between long-term cognitive
outcomes and peak look to static stimuli after the first year of life, whereas negative
correlations are observed between the same two variables during the first year. They
suggest that this may be attributable to the emergence of effortful control as a factor
mediating behaviour at about the 12-month boundary (Colombo & Cheatham, 2006; see also
Courage et al., 2006). Note, however, that Kochanska and Aksan (2006) found that focused
attention (not peak look duration) during the second half of the first year correlated
positively with effortful control at 22 months. One difference between our screen-based
and our semi-naturalistic tasks may be relevant here. This is that, for the semi-
naturalistic tasks, a number of other informative gaze targets (such as the experimenter)
are within the field of view of the child – whereas the screen-based tasks were conducted
in a darkened room. There are a variety of reasons why looks away from the object may have
an adaptive value in our free play paradigm but not in our screen-based paradigm (e.g.
Rueda, Posner, & Rothbart, 2005; Sheese, Rothbart, Posner, White, & Fraundorf, 2008). It
may be therefore that executive control relates more strongly to peak look duration in the
free play than in the screen-based tasks, although future work is required to investigate
this in more detail (cf. Rothbart, Ellis, Rueda, & Posner, 2003; Sheese et al., 2008).

<h>CONCLUSIONS</h>
-----------

To a cohort of typically developing 11-month-old infants we presented several assessments
of peak look duration, including some that assessed looking behaviour on screen-based
tasks and others that assessed behaviour on semi-naturalistic tasks. We found that the
four screen-based tasks (looking to static non-complex, to static complex, to mixed
dynamic/static and to dynamic stimuli during EEG recording) all mapped onto a single
factor, whereas the two free play assessments mapped onto a separate factor. In our
discussion we noted a number of ways in which factors such as susceptibility to high
luminance contrasts and abrupt stimulus onset–offset changes may be key factors mediating
individual differences on screen-based tasks, but relatively unimportant in more
naturalistic contexts. Future research should exploit recent technological advances such
as head-mounted eyetrackers (e.g. Aslin, 2009) to increase our understanding of how
individual differences in naturalistic attention relate to individual differences in
infant attention as assessed using screen-based paradigms.


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<ART>Comparison of children diagnosed with cerebral palsy in a private cord blood bank to an epidemiological sample
================================================================================

Authors: Peter Mazonson, Mark Kane, Kelin Colberg, Heather Harris, Heather Brown, Andrew Mohr, Chris Santas, Adrian Sandler
DOI: 10.1016/j.ridd.2018.06.011
Year: 2018  |  Pages: 153-160
ASJC codes: 3203, 3204
Keywords: Cerebral palsy, Hematopoietic stem cells, Private cord blood bank, Regenerative medicine, Umbilical cord blood, Web-based research

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Although cord blood (CB) stem cell research is being conducted for treatment of cerebral palsy (CP), little is known about children with CP and stored CB. Aims: To compare demographic and clinical characteristics of children with CP and stored CB to children with CP identified in a population-based study. Methods and Procedures: The Longitudinal Umbilical Stem cell monitoring and Treatment REsearch (LUSTRE®) Registry recruited children from the largest US private CB bank. Demographics, co-morbidities, and gross motor function (GMFCS level and walking ability) were collected and, where possible, compared with the CDC's Autism and Developmental Disabilities Monitoring (ADDM) Network. Outcomes and Results: 114 LUSTRE participants were compared to 451 ADDM participants. LUSTRE participants were more likely to be white, but sex distribution was similar. Co-morbidities (autism and epilepsy) and functional mobility were also similar. Conclusions and Implications: The results of this analysis suggest that while children diagnosed with CP and with access to stored CB differ from a broader population sample in terms of demographics, they have similar clinical severity and comorbidity profiles. As such, LUSTRE may serve as a valuable source of data for the characterization of individuals with CP, including individuals who have or will receive CB infusions.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPER ADDS?</h>
---------------------

To date, little research has been done on families that choose to privately bank their
children’s cord blood (CB) and whose children are subsequently diagnosed with cerebral
palsy (CP). This analysis was performed to help understand the extent to which the results
of research within the private CB-storing population might be relevant to broader
populations of children with CP. The study compared children with CP who were enrolled in
the Longitudinal Umbilical Stem cell monitoring and Treatment REsearch (LUSTRE®) registry
at the largest private, US cord blood bank to children with CP identified in the CDC’s
Autism and Developmental Disabilities Monitoring (ADDM) Network. While the demographics of
children with CP differed, these samples were similar when compared across several
measures of functional mobility and for the prevalence of co-occurring medical conditions.
Based on these results, LUSTRE may be useful for the characterization of children with CP,
including individuals who have or will receive CB infusions.

<h>INTRODUCTION</h>
------------

Umbilical cord blood (CB) contains a mixed cell population and is a rich source of
hematopoietic stem cells (Gluckman et al., 1989). CB derived cellular therapy has been
used for decades to treat pediatric and adult patients with hematologic malignancies and
disorders (Butler & Menitove, 2011; Gluckman et al., 1989; Prasad & Kurtzberg, 2009).
Based on evidence that CB cells may have the capacity to facilitate repair of damaged
tissues outside of the blood and immune system, it is also in early phases of research as
a treatment for a number of additional conditions, including cerebral palsy (CP) (Chez et
al., 2018; Dawson et al., 2017; Kurtzberg, Durham, Laskowitz, Balber, & Bennett, 2016; Sun
et al., 2015; Sun et al., 2016; Sun et al., 2017). The collection and private storage of
umbilical cord blood, recently estimated at approximately 4 million units worldwide, has
become an increasingly popular choice for parents of newborn children (Ballen, Verter, &
Kurtzberg, 2015). However, little is known about the medical conditions that affect
families that choose to privately store their newborns’ CB. The Longitudinal Umbilical
cord blood Stem cell monitoring and Treatment REsearch (LUSTRE®) Registry identifies and
follows families that have both stored their children’s CB in the largest US CB bank and
have children with conditions that are currently treated with, or under research for
treatment with, CB. Over time, LUSTRE is designed to help better understand the clinical
characteristics and disease severity of these children, describe the treatments they
receive, compare the long-term clinical and quality of life outcomes associated with these
treatments, and characterize the types of participants who are receiving stem cell
therapy. CP, one of several neurological conditions currently being studied for potential
treatment with CB, is a LUSTRE target condition. Little research exists regarding the
characterization of children diagnosed with CP who also have access to privately stored
CB; nor is there published research on how this population compares to the broader CP
population. This study was undertaken to describe the LUSTRE-CP cohort and to assess, in
terms of demographics and disease severity, how children in LUSTRE with CP compared to a
nationally representative sample of children with CP. We used data from the Autism and
Developmental Disabilities Monitoring (ADDM) Network for this comparison group. ADDM is
funded by the U.S. Center for Disease Control and Prevention (CDC) to estimate the number
of children with autism spectrum disorder and other developmental disabilities living
across the United States. The ADDM Network has routinely provided valuable insight into
the epidemiology of various developmental disabilities, including CP (Christensen et al.,
2014; Kirby et al., 2011; Yeargin-Allsopp et al., 2008). In order to determine how
children with CP and stored CB compare to children with CP in the general public, we
compared children in LUSTRE to children captured in the most recent assessment of CP
conducted by ADDM in 2008.

<hs>  Study design</hs>
  ~~~~~~~~~~~~

LUSTRE is an observational disease registry open to all families who have stored CB in the
largest, U.S.-based, private cord blood bank, CBR Systems, Inc. LUSTRE assembles data in
three distinct phases, each collecting more detailed information from a more targeted
group of families (Fig. 1). The Surveillance Phase (Phase I) collects data on the
prevalence of medical conditions among all families storing CB in the bank. It uses a
cross-sectional survey to identify whether families have any of 32 conditions currently
treated with CB or under investigation for treatment with CB. The Monitoring Phase (Phase
II) collects detailed data annually on children with selected target conditions identified
in Phase I, including disease severity, medical and treatment history, comorbidities,
demographics, and quality of life. This phase of the registry consists of an
observational, prospective, longitudinal cohort study that collects data on children with
target medical conditions and with access to their own (autologous) stored CB. Finally,
the Infusion Phase (Phase III) collects additional clinical details on Phase II patients
who receive a CB infusion. LUSTRE participants are followed over time, regardless of
whether their families ever elect to use their stored CB.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The initial participants in Phase I of LUSTRE have been described previously (Mazonson et
al., 2017). Briefly, in the original cohort, over 94,000 families provided information
about whether their child with stored CB, or that child’s first-degree relatives, had been
diagnosed with any of 32 conditions of interest. By offering the survey to more families
as they store CB in the bank, new observations are added to the Phase I dataset, which now
contains information on more than 120,000 families. Once families identified an eligible
family member with one or more LUSTRE conditions, they were invited via email to join the
Monitoring Phase of the registry. The Monitoring and Infusion Phases began enrollment in
January of 2014 for children whose own CB had been stored and who had a CP diagnosis.
LUSTRE’s study protocol was approved by Ethical and Independent Review Services (E&I
#13-130). Informed consent was obtained before administering the Phase II study
questionnaire.

<hs>  Selection of the Autism and Developmental Disabilities Monitoring Network comparison cohort</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The ADDM Network offers the largest cross-sectional assessment of children living with CP
in the US (Christensen et al., 2014). These data are frequently referenced for CP
prevalence rates in the US (Christensen et al., 2014). In 2008, 451 children with CP were
identified via data abstracted from organizations that diagnosed, treated, and provided
services to developmentally disabled children served by one of four ADDM surveillance
sites in Alabama, Georgia, Missouri, and Wisconsin. Children were eligible if they were 8
years old at the time of case ascertainment. The ADDM Network surveyed 8-year-old children
because it focused heavily on ASD and other developmental disabilities and previous work
showed that, by this age, most children with ASD had been identified for health care
services. Although all ADDM Network study subjects were 8 years of age, GMFCS level and
walking ability category were abstracted based on available descriptions of study subjects
at or after 4 years of age, when their motor functioning levels were believed to have
stabilized. To maximize available data points but minimize the chance of misclassifying
motor functioning, we, similarly, compared the GMFCS-derived study measures from LUSTRE
children of at least 4 years of age with data published by the ADDM Network. Wider and
narrower LUSTRE age groupings were also compared to the ADDM cohort to see if our findings
were affected.

<hs>  Assessment of functional mobility and other clinical characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To optimize the collection of parent-reported data when designing the Phase II
questionnaire, LUSTRE used existing, validated instruments and methodologies where
possible. To assess functional mobility, primary caregivers of study subjects were asked
to select which of five age-appropriate descriptions of functional mobility best described
their child, using the Parent Report Gross Motor Functioning Classification System (GMFCS)
(Palisano, Rosenbaum, Bartlett, & Livingston, 2008). Similarly, the ADDM Network
abstracted GMFCS level based on available descriptions of study subjects. GFMCS level
determinations were then used to classify study subjects into three aggregate categories
describing walking ability: walks independently, walks with handheld mobility device, or
limited or no walking ability. Specifically, in ADDM, GMFCS levels I and II were
classified as “walks independently;” level III as “walks with handheld mobility device;”
and levels IV and V as “limited or no walking ability.” To maintain concordance with the
ADDM Network, LUSTRE reported data on both GMFCS levels as well as the aggregate walking
ability categories used in ADDM. In addition to assessing their child’s functional
mobility, primary caregivers with children enrolled in LUSTRE provided information
regarding demographics and the presence of co-occurring medical conditions. For this
study, we focused on co-occurring autism spectrum disorders (ASD) and epilepsy/seizures to
make clinical comparisons since these were the only comorbid conditions publicly available
from ADDM Network data.

<hs>  Statistical methods</hs>
  ~~~~~~~~~~~~~~~~~~~

Frequency distribution of characteristics in the LUSTRE data set, such as age at
enrollment, parental education, and family income level were calculated for all
participants with a CP diagnosis for whom CB was stored at birth. Additionally, Pearson χ2
tests were used to examine differences in characteristics of children enrolled in the
LUSTRE and ADDM Network cohorts, including sex, ethnic group, co-occurring ASD, co-
occurring epilepsy, walking ability, GMFCS level, and ambulatory status. Participants < 4
years of age (28.9%) were excluded from the LUSTRE cohort when comparing clinical
characteristics and comorbidities, in order to focus on children with more stable
condition diagnoses and gross motor function. A p-value of <0.05 was considered
significant. All data analyses were performed using STATA statistical software program
(version 13.0, STATA Corp LP, College Station, TX).

<hs>  Identification of children with CP in bank</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As of November 2016, 121,411 families had completed a LUSTRE surveillance questionnaire.
429 families (0.35%) indicated a possible CP diagnosis in a child with access to their own
stored CB. 221 families chose to enroll in Phase II of LUSTRE, 158 (71.5%) were identified
via the surveillance questionnaire and 63 (28.5%) were previously identified by the CB
bank. Of the 221 enrolled families, 114 of these families reported a formal CP diagnosis.
Data on the 114 subjects with CP are presented here.

<hs>  Demographic and SES overview of LUSTRE participants with CP</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As displayed in Table 1, slightly over half of LUSTRE subjects with CP were male (56.1%).
The average age of LUSTRE children was 5.7 (SD 3.5), with a range at time of enrollment of
1–17 years. In addition, the majority of LUSTRE children were white (79.8%). The majority
of fathers (64.0%) and mothers (60.5%) of children with CP had at least a four-year
college degree (Table 1). 55.4% of LUSTRE households providing income information reported
household incomes greater than or equal to $100,000. Of note, 35% of the LUSTRE cohort did
not provide financial information.

<hs>  Demographic comparison of LUSTRE and ADDM network subjects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 presents data on the 114 LUSTRE subjects compared to the 451 ADDM Network
subjects. Both cohorts were majority male. (56.1% vs 60.8%, p = 0.369). However, the
ethnic profile of the LUSTRE population showed a significantly higher percentage of white
subjects compared to the ADDM Network cohort (78.8% vs. 51.6%, p < 0.001). Parental
education and income levels were not available from the ADDM Network cohort for comparison
with LUSTRE.

<hs>  Disease severity comparison of LUSTRE and ADDM network subjects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The frequency of co-occurring ASD among LUSTRE participants was 10.3% (95% CI 3.4–17.1%)
and among ADDM participants was 6.9% (95% CI 4.9–9.6%). The frequency of co-occurring
epilepsy/seizures was 34.2% (95% CI 23.5–44.9%) in LUSTRE versus 41.0% (95% 36.4–45.7% CI)
in ADDM (Table 2). The prevalence of ASD and epilepsy was not significantly different
between ADDM and LUSTRE (p = 0.291 and 0.252, respectively). In addition, LUSTRE and ADDM
Network subjects did not differ significantly on the GMFCS, measured across all 5 levels
(p = 0.354), collapsed into walking ability categorization (p = 0.610) or summarized as
ambulatory (GMFCS levels I-III) and non-ambulatory (GMFCS levels IV-V) (p = 0.473). No
clinical differences were found when comparing LUSTRE participants across subgroups of
ages (ages 4–8 or 6–10) to the ADDM participants (Table 3).

<hs>  Demographic comparison of respondent and non-respondent families</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The participation rate among families responding to Phase I of LUSTRE was 33.3%. After
adjusting using inverse proportional weighting of characteristics available for both
responders and non-responders, no material differences in condition prevalence rates were
observed (Mazonson et al., 2017; Seaman & White, 2013). Among families invited to
participate in Phase II, 41.9% enrolled. No significant differences in the available
characteristics of participating and non-participating families were observed (e.g., mean
age of primary parent, mean age of children with stored cord blood, mean CB units stored)
(Table 4).

<hs>  Missing data</hs>
  ~~~~~~~~~~~~

Missing data were rare among LUSTRE participants. Two participants did not provide GMFCS
level data. In contrast, due to ADDM Network’s reliance on medical records, clinician
reviewers were unable to assign GMFCS levels or walking ability categories for 142 out of
451 children. However, efforts were made to maximize the number of children with a gross
motor function assessment. For 28 of these 142 children, enough information was available
for study clinicians to assign a walking ability category without a formal GMFCS level,
reducing the number of observations missing a gross motor function assessment to 114
(25.3%).

<h>DISCUSSION</h>
----------

LUSTRE is a unique registry of children with privately stored CB who have conditions
treatable with, or undergoing research for treatment with, CB. When compared, subjects
with CP in LUSTRE had similar clinical profiles to those of the ADDM Network’s CP sample.
Specifically, the two CP cohorts displayed similar motor functioning levels and prevalence
of comorbidities. Both LUSTRE and the ADDM Network reported that just over half of
children walked unaided while just over a quarter were unable to walk. When comparing
GMFCS levels, over two-thirds were ambulatory (GMFCS I-III) in both LUSTRE and the ADDM
Network. In addition, the prevalence of co-occurring ASD and epilepsy/seizures were
similar between the two samples. Both cohorts reported approximately 10% of children with
CP had been diagnosed with co-occurring ASD, while over a third of children with CP had
been diagnosed with epilepsy/seizures (Christensen et al., 2014). The LUSTRE cohort was
less ethnically diverse than ADDM Network’s population-based sample. No significant
difference in sex distribution was observed. While we were not able to compare parental
education levels or household income directly, if the ADDM Network sample represented the
average US population, LUSTRE families were likely to be significantly more educated and
affluent than the ADDM Network sample. Specifically, 55.4% of LUSTRE CP households
providing income information reported greater than or equal to $100,000 in family income,
whereas, 26.4% of US households had equivalent income according to 2015 census data
(United States Census Bureau, 2015a). Furthermore, among all US adults, only 32.3% of
males and 32.7% of females have at least a college bachelor’s degree, whereas, among the
parents of the LUSTRE cohort, 64.0% of fathers and 60.5% mothers reported this level of
education (United States Census Bureau, 2015b).

<hs>  Limitations</hs>
  ~~~~~~~~~~~

There are potential limitations to this analysis related to both the ADDM Network and the
LUSTRE data. With regard to the ADDM Network, limitations have been reported elsewhere
(Christensen et al., 2014). Most notably, 25% of children with CP did not have sufficient
information on gross motor functioning to classify them according to the GMFCS or walking
ability categorization. To address this concern, ADDM Network investigators used a
multiple imputation model to infer children’s walking ability based on other data
available in their medical records. The distribution of walking ability among children
with imputed data for missing values was similar to what was found for children with
observed data. Thus, it is likely that data was missing at random, unrelated to severity
level (Christensen et al., 2014; Maenner et al., 2012). With regard to LUSTRE, as
previously published, the participation rate among families responding to Phase I of
LUSTRE was 33.3% and the participation rate among families invited to take part in Phase
II was 41.9%, raising the possibility of selection bias among the respondents. However,
further analyses did not show evidence of selection bias in either group of participants.
Nonetheless, some degree of selection bias could have occurred. Sampled populations also
differed between LUSTRE and ADDM. While ADDM was limited to four sites, primarily in the
south (Alabama, Georgia, Missouri, and Wisconsin), LUSTRE is open to families across the
US. In addition, families participating in LUSTRE must pay to store cord blood at a
private cord blood bank. This potential financial barrier to private cord blood banking
likely results in a less socio-economically diverse LUSTRE cohort. A previous study of a
Canadian-based CP cohort showed that lower socioeconomic status may be associated with
lower GMFCS level (Oskoui, Messerlian, Blair, Gamache, & Shevell, 2016). This study also
suggested that socioeconomic status is positively correlated with full-term pregnancies,
which might suggest different etiologies of CP in full term pregnancies. Interestingly,
despite differences in socioeconomic factors, we didn’t detect differences in functional
mobility between the LUSTRE and ADDM cohorts. An additional, potential limitation of
LUSTRE is its use of parent-reported data, which could have introduced some
misclassification of conditions and comorbidities. However, many widely cited, peer-
reviewed epidemiological studies utilize parental report in place of clinical report to
provide descriptions of neurodevelopmental and other clinical conditions (Blanchard,
Gurka, & Blackman, 2006; Gurney, McPheeters, & Davis, 2006; Kogan et al., 2009; Russ,
Larson, & Halfon, 2012). In addition, evidence is growing that parents can accurately
report diagnoses on web-based surveys (Daniels et al., 2012). Another potential limitation
in both studies was in GMFCS level assignment. Traditionally clinicians determine these
levels, but LUSTRE used parent report while the ADDM Network used chart review by
clinicians who did not meet or examine the child. The validity of the parent-reported
method has been documented as very high (ICC> = 0.9) in similar studies, and the author of
the GMFCS supported the use of the one-page version for caregiver reporting in this study
(Dietrich, Abercrombie, Bartlett, & Fanning, 2005; McDowell, Kerr, & Parkes, 2007; Morris,
Galuppi, & Rosenbaum, 2004; Morris, Kurinczuk, Fitzpatrick, & Rosenbaum, 2006). Similarly,
the ADDM Network has validated its “arm’s length” GMFCS level assignment method
(Christensen et al., 2014). In further support of these findings of similar clinical
severity levels within the two cohorts, as discussed above, the relationships held when
the comparisons were made across different LUSTRE age subgroups.

<h>CONCLUSION</h>
----------

Based on the findings from this study, it appears that children with CP and access to
their own stored CB are less socio-economically diverse than the broader CP population.
This is likely a result of the fact that families that choose to privately store CB must
have the necessary financial resources to pay for private storage. However, because
clinical severity and co-morbidity prevalence are similar, these groups may be more
comparable than they first appear. LUSTRE may serve as a valuable source of data for the
study and characterization of individuals with CP, including individuals who have or will
receive CB infusions.

<h>CONFLICT OF INTEREST</h>
--------------------

HH and HB are both employees of CBR Systems, Inc. PM, MK, KC, AM and CS received financial
support from CBR Systems, Inc. to carry out this study. AS received compensation from CBR
Systems, Inc. for consultation services.

<h>FUNDING</h>
-------

This work was supported by CBR Systems, Inc.


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<ART>Conscious awareness is required for holistic face processing
============================================================

Authors: Vadim Axelrod, Geraint Rees
DOI: 10.1016/j.concog.2014.05.004
Year: 2014  |  Pages: 233-245
ASJC codes: 3204, 3205
Keywords: Holistic face processing, Unconscious processing, Visual awareness

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Investigating the limits of unconscious processing is essential to understand the function of consciousness. Here, we explored whether holistic face processing, a mechanism believed to be important for face processing in general, can be accomplished unconsciously. Using a novel "eyes-face" stimulus we tested whether discrimination of pairs of eyes was influenced by the surrounding face context. While the eyes were fully visible, the faces that provided context could be rendered invisible through continuous flash suppression. Two experiments with three different sets of face stimuli and a subliminal learning procedure converged to show that invisible faces did not influence perception of visible eyes. In contrast, surrounding faces, when they were clearly visible, strongly influenced perception of the eyes. Thus, we conclude that conscious awareness might be a prerequisite for holistic face processing. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Most people are good at recognizing faces, which is a capacity that is usually taken for
granted. Yet, given that all faces are essentially very similar (e.g., all faces have a
nose, eyes, and mouth; relative position of features is largely the same), the cognitive
task of face recognition is far from straightforward. A key component of efficient facial
processing is considered to be holistic processing (Farah, Wilson, Drain, & Tanaka, 1998;
Richler, Cheung, & Gauthier, 2011) – the ability to perceive a face as a whole and not as
a set of independent features. Probably the most spectacular demonstration of this
phenomenon is the composite face effect (Young, Hellawell, & Hay, 1987) – that is, when a
facial image is composed of the bottom and top halves of two different faces, where
recognition of one half of a face (e.g., the top part) is modulated by that of the other
half (e.g., the bottom part). Holistic face processing in general, and the composite face
effect in particular, has been extensively explored in healthy populations using
behavioral measures (for review: Rossion, 2013), functional MRI (e.g., Andrews, Davies-
Thompson, Kingstone, & Young, 2010; Axelrod, 2010; Axelrod & Yovel, 2010, 2011; Schiltz,
Dricot, Goebel, & Rossion, 2010; Schiltz & Rossion, 2006) and event-related potentials
(e.g., Jacques & Rossion, 2009; Wiese, Kachel, & Schweinberger, 2013) as well as in
participants with impaired face recognition (prosopagnosia) (Avidan, Tanzer, & Behrmann,
2011; Busigny & Rossion, 2011). However, whether conscious awareness is required for
holistic face processing is not known. Understanding the role of consciousness and
conscious awareness is one of the fundamental challenges of the cognitive sciences (Baars,
1993; Dennett, 1993; Koch, 2004). Empirically, the level of conscious awareness is usually
evaluated by an introspective, “subjective report” (whether a participant was aware of a
stimulus) and “objective measure” (forced-choice discrimination, even for subjectively
unaware stimulus) (Merikle & Daneman, 1998). While qualitative differences between
conscious and unconscious perception have been debated for years (e.g., Cheesman &
Merikle, 1986; Peremen & Lamy, 2014; Vorberg, Mattler, Heinecke, Schmidt, & Schwarzbach,
2003), numerous behavioral (e.g., Marcel, 1983; Mudrik, Breska, Lamy, & Deouell, 2011;
Sklar et al., 2012) and neuroimaging (e.g., Axelrod, Bar, Rees, & Yovel, 2014; Dehaene et
al., 2001; Fahrenfort et al., 2012; Sterzer, Haynes, & Rees, 2008) studies demonstrate
that information can be processed unconsciously. Unconscious face processing is one of the
widely explored types of unconscious processing. A large body of evidence suggests that
emotional aspects of face processing (for reviews: Pessoa & Adolphs, 2010; Tamietto & de
Gelder, 2010), gaze (Chen & Yeh, 2012; Stein, Peelen, & Sterzer, 2012; Stein, Senju,
Peelen, & Sterzer, 2011) and face familiarity (de Gardelle, Charles, & Kouider, 2011;
Henson, Mouchlianitis, Matthews, & Kouider, 2008; Kouider, Eger, Dolan, & Henson, 2009)
can be processed without conscious awareness; however, several studies have shown that
facial identity (Moradi, Koch, & Shimojo, 2005; Stein & Sterzer, 2011; Stone & Valentine,
2005) and face gender/race (Amihai, Deouell, & Bentin, 2011) cannot be processed
unconsciously. In the present study, we addressed the question of unconscious face
processing from another angle, while asking whether holistic face processing can take
place unconsciously. Based on the previous negative results of unconscious face
identity/gender processing, and given that face recognition and holistic processing might
share common underlying mechanisms (Richler, Cheung et al., 2011; Wang, Li, Fang, Tian, &
Liu, 2012), one possibility is that holistic face processing cannot be accomplished
without conscious awareness. Alternatively, it is also possible that holistic face
processing is a more basic type of processing than face recognition, which implies that
holistic processing might still occur unconsciously. In addition, given that holistic
processing has been suggested to be an automatic process (Richler, Wong, & Gauthier,
2011), it therefore possibly could be executed unconsciously (Hasher & Zacks, 1979). In
the present study, we devised a novel “eyes-face” composite stimulus that was composed of
a pair of eyes plus the remaining part of the face [c.f., top and bottom image face parts
(Young et al., 1987)]. Participants had to discriminate between pairs of eyes in two
consecutively presented composite images while the rest of the face was either the same or
different (Fig. 1A and B). Critically, in the subliminal version of the paradigm, while
the eyes were always visible, the rest of the face was rendered invisible using Continuous
Flash Suppression (CFS; Fig. 1B) (Harris, Schwarzkopf, Song, Bahrami, & Rees, 2011;
Tsuchiya & Koch, 2005). We asked whether invisible faces influenced discrimination of the
visible eyes.

<h>EXPERIMENT 1</h>
------------

In this experiment, we used three different sets of composite faces. The first set was
comprised of five male composite faces (examples of faces: Fig. 1B left side). To increase
the perceptual differences between images, a second set included three male and three
female composite faces (examples of faces: Fig. 1C, top). The third set of images was
comprised of three female faces, either with or without eyebrows (examples of faces: Fig.
1C, bottom). The motivation to include this third composite image set was that eyebrows
are the closest facial feature to the eyes and, consequently, have a higher chance of
being attended to when the task is eyes discrimination. Participants were presented with
two consecutive composite faces that contained visible eyes and faces. The face part of
each image was rendered invisible by CFS (Fig. 1B). The pairs of eyes in the two images
were always the same, and the invisible faces were either the same or different. The task
was to report whether successive pairs of visible eyes were the same or different.
Participants were told that this eyes discrimination task was very difficult, and were
encouraged to look out for the smallest differences between the two stimuli. Notably,
because the stimuli did not appear in the exact same screen position (a small amount of
spatial jitter was added; see Methods) and the eyes were surrounded by a constantly
changing CFS mask, it was not evident that sequential eye stimuli were actually identical.
Effect size was defined in percent units as the percent of trials answered “eyes same”
when the invisible faces of the two images were the same minus the percent of trials
answered “eyes same” when the invisible faces of the two images were different. An effect
size larger than zero was taken as evidence of a subliminal influence of the invisible
faces on judgments of the visible eyes.

        <hss>Participants</hss>

        Fifteen healthy volunteers (age 20–27 years, 10 females) participated in this
        experiment: all participants participated in the experiment with image set 1 (male
        faces), 14 of the same set of participants participated in the experiment with
        image set 2 (male and female faces), and 12 of the same set of participants took
        part in the experiment with image set 3 (faces with and without eyebrows). Two
        participants were excluded from the analysis of all three experiments because they
        reported that they could see the masked face. The experiment was approved by Tel-
        Aviv University ethics committee, and all participants gave informed consent to
        participate in the experiment.

        <hss>Apparatus</hss>

        For stimuli presentation, a CRT 17-in. color monitor was used. Screen resolution
        was 1024 × 768, and refresh rate was 85 Hz. Stimuli were presented using MATLAB
        7.6 with Psychtoolbox (Brainard, 1997). Participants sat in a comfortable chair at
        a distance from the monitor of 30 cm. During the experiment, the room lights were
        turned off.

        <hss>Stimuli</hss>

        All image manipulations were performed in Adobe Photoshop CS2. Face stimuli
        (neutral face expressions) were taken from the Karolinska Directed Emotional Faces
        (Lundqvist & Litton, 1998). Image set 1 consisted of five male face identities
        (examples of faces: Fig. 1B, left side), and image set 2 consisted of three male
        and three female face identities (examples of faces: Fig. 1C, top). Image set 3
        consisted of three female face identities – three original images and three images
        where the eyebrows were removed using Adobe Photoshop program (examples of faces:
        Fig. 1C, bottom). Five pairs of eyes (rectangle with the eyes, Fig. 1B) were
        cropped from different face images (not used in image sets 1–3) and integrated
        into each face image of the experimental image sets 1–3. The same pairs of eyes
        were used for all image sets. The size of the rectangle containing the eyes was
        identical for all pairs of eyes (see below). The resultant image sets included 25
        stimuli each (five face identities with five pairs of eyes) for image set 1, and
        30 stimuli each (six face identities with five pairs of the eyes) for image sets 2
        and 3. None of the composite faces had original (“native”) eyes. The images were
        in color. Face images were positioned in the center of the rectangular background
        image frame, which was a light grey color (RGB: 97, 97, 97) (see Fig. 1B).
        Dimensions of the stimuli were as follows (in degrees of visual angle): background
        square frame (vertical: 27, horizontal: 27); face image (vertical: 21, horizontal:
        16.5); eyes rectangle (vertical: 3.3, horizontal: 14.5).

        <hss>Invisibility manipulation</hss>

        To render stimuli invisible, we used Continuous Flash Suppression (CFS) (Tsuchiya
        & Koch, 2005). The paradigm was designed in such a way that the eyes rectangle was
        fully visible with both eyes, whereas the remaining part of the face was invisible
        (Harris et al., 2011). During the experiment, participants wore cardboard anaglyph
        red/cyan glasses. The visible part of the stimulus was projected using all three
        RGB colors. The invisible part of the stimulus was projected using the red color
        channel (visible using red filter), while a Mondrian mask was projected using
        green/blue channels. The Mondrian mask appeared over the whole background
        rectangle frame with the exception of the visible stimulus part (see Fig. 1B). The
        position of the visible eyes rectangle was fixed relative to the Mondrian image.
        In addition, on the Mondrian masks, we drew an elliptic contour line at the
        location of the invisible face (see Fig. 1B, right side). The motivation for
        adding this contour ellipse was to urge participants to make eye judgments as
        though the eyes were part of a face. The elliptic contour line was created by
        increasing the brightness of the corresponding mask pixels by 20%. The ellipse
        contour was created at the same position for all mask images and was at a fixed
        position relative to the eyes rectangle. Mondrian masks were prepared by randomly
        scrambling a kaleidoscope image. Our preliminary pilots showed that use of this
        pattern achieved higher invisibility effects than the geometrical shapes usually
        used (e.g., Tsuchiya & Koch, 2005). Mondrian masks were replaced continuously at a
        frequency of 10 Hz (every 100 ms). During the invisible part of Experiment 1, the
        face composite stimuli were always projected to the non-dominant eye of the
        participant while the CFS mask was presented to the dominant eye. Eye dominance
        was tested by asking participants to view a distant object through a hole made by
        the fingers of their two hands (“Miles test”) (Mendola & Conner, 2007; Miles,
        1930). In the visible sessions, the participants wore specially prepared glasses
        with two red lenses (stimuli visible through both eyes and mask invisible through
        both eyes). Using this approach, we preserved the same quality of stimulation for
        visible and invisible sessions.

        <hss>Experimental design</hss>

        For each one of three image sets, there were three experimental sessions: eyes
        discrimination session with invisible face images, awareness invisibility test of
        discriminating invisible face images, and eyes discrimination session with visible
        face images. To minimize the number of switches between tasks, participants first
        performed three sessions of eyes discrimination with invisible face images (all
        three image sets), then three sessions of awareness invisibility (all three image
        sets; explained below), and finally three sessions of eyes discrimination with
        visible face images (all three image sets). The order of the image sets within
        these three sessions was counterbalanced across participants. From the side of
        stimuli presentation (computer code), all three experimental sessions were exactly
        the same for each image set. A trial consisted of two consecutively presented
        stimuli (each stimulus duration = 0.3 s, interstimulus interval [ISI] = 0.1 s)
        (Fig. 1A). There was a random position jitter between two stimuli (2% of stimulus
        size). The eyes in two images of a trial were always the same, whereas the faces
        were either the same (50% of the trials) or different (50% of the trials). For
        image set 1 (males only set), the different faces were of different male face
        identities. For image set 2 (males and females set) the different faces were each
        composed of different identities from opposite genders (either male–female or
        female–male, counterbalanced). For image set 3 (with and without eyebrows), the
        different faces were the same identity presented twice with and without eyebrows
        (either no eyebrows – eyebrows or eyebrows – no eyebrows). In the “invisible”
        sessions, only the eyes were visible; in the “visible” sessions (at the end of the
        experiment), both the eyes and faces were visible. Participants were asked to make
        their response after the second stimulus disappeared. In the eyes discrimination
        experiment, participants had to press ‘1’ if the two pairs of eyes were the same
        and ‘2’ if the two pairs were different. The fact that the pairs of eyes were
        always the same was not known by participants. Participants were told before the
        experiment that the task would be very difficult and that any slight difference
        that they perceived between the two eye pairs should be taken as an indication of
        the presence of a difference between the eyes. Our preliminary pilot tests showed
        that presenting the two stimuli with a slight spatial jitter and a constant change
        in CFS mask around the eyes created an impression that the eyes were not actually
        identical. Indeed, at the informal debriefing after the experiment, participants
        indicated that they had seen differences between the pairs of eyes. Awareness test
        sessions were very similar to the eyes discrimination sessions; the only
        difference was that participants had to discriminate between invisible faces (‘1’:
        same faces, ‘2’: different faces); since the participants admitted seeing nothing,
        they were encouraged to guess. Participants were asked not to use the visible eyes
        in the discrimination; instead, they were encouraged to try to discriminate based
        on the non-eye part of the image (inside the ellipse). Each session consisted of
        50 trials (25 trials with the same faces and 25 with different faces). At the
        beginning of the experiment, before the first session with invisible face images,
        participants underwent a short training session (10 trials) of eyes discrimination
        with invisible faces. As face stimuli, we used two male identities that were not
        used afterwards in the experimental sessions.

        <hss>Data analysis</hss>

        Data were analyzed using MATLAB and SPSS 17 software. The effect size for the eyes
        discrimination task was calculated as the percent of trials answered “same” when
        the face identities of the two images were actually the same minus the percent of
        trials answered “same” when the face identities were different. An effect size
        larger than zero provided evidence that a change in face influenced perception of
        the eyes. Significance at the group level was established using non-parametric
        Wilcoxon Signed Rank test (signrank MATLAB function). In the visual awareness
        tests, the individual d-prime values [signal detection theory (Macmillan, 2002)]
        of discrimination invisible stimuli (correct/incorrect) were assessed using non-
        parametric Wilcoxon Signed Rank test vs. zero. For all the parametric tests
        (ANOVAs and correlations), the data was first tested for normality using
        Lilliefors test (lillietest MATLAB function). Reaction times of participants were
        not analyzed since the participants were asked to respond only when the second
        stimulus of the trial disappeared, and they were asked to maximize accuracy and
        not to minimize response time. To calculate the Bayes factor, we used the online
        calculator of Zoltan Dienes
        (http://www.lifesci.sussex.ac.uk/home/Zoltan_Dienes/inference/Bayes.htm).

<hs>  Results: Experiment 1</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Judgment of visible eyes was not influenced by invisible faces in any of the image sets
(Fig. 2, left side) [males only set 1: effect size: −3.4%, MSE: 3.7%, p = .26, Wilcoxon
sign-rank = 29.5, one Sample Wilcoxon Signed Rank test vs. 0; males and females set 2:
effect size: 4.1%, MSE: 3.7%, p = .29, Wilcoxon sign-rank = 27; with and without eyebrows
set 3: effect size: −6.4%, MSE: 4.8%, p = .19, Wilcoxon sign-rank = 11.5]. For raw
response rates of “same eyes” answers, see Table 1, first row. Invisibility of faces was
tested in separate sessions, with stimulus configurations identical to the main
experiment, but the participants were required to discriminate between the invisible
faces. Discrimination of faces did not differ significantly from chance for all three
image sets [males only set 1: d-prime: 0.082, MSE: 0.11, p = .47, Wilcoxon sign-rank = 25;
males and females set 2: d-prime: 0.15, MSE: 0.2, p = .50, Wilcoxon sign-rank = 25.5;
males and females set 3: d-prime: 0.028, MSE: 0.13, p = .95, Wilcoxon sign-rank = 22] (raw
response rates, Table 1, second row). Contrarily to invisible faces, judgment of visible
eyes was strongly influenced by visible faces in all image sets (Fig. 2, right side)
[males only set 1: effect size: 51.7%, MSE: 7%, p = .001, Wilcoxon sign-rank = 0; males
and females set 2: effect size: 54.2%, MSE: 7.2%, p = .002, Wilcoxon sign-rank = 0; with
and without eyebrows set 3: effect size: 42.8%, MSE: 7.6%, p = .005, Wilcoxon sign-rank =
0] (raw response rates, Table 1, third row). The difference between invisible and visible
faces was confirmed by the two-way repeated measured ANOVA analysis with image set and
face visibility as factors: there was a highly significant main effect of face visibility:
F(1, 9) = 118.425, p < .001 but non-significant main effect of image set [F(2, 18) = 3, p
= .075] and non-significant interaction between image set and face visibility [F(2, 18) <
1]. Experiment 1 found no evidence that invisible faces influence the perception of
visible eyes. Notably, the “null effect” for invisible faces may stem either from a lack
of sensitivity or, alternatively, from the phenomenological absence of unconscious
processing (Dienes, 2011, in press). Since the orthodox (Neyman and Pearson) statistical
approach is unable to distinguish between these two possibilities, we adopted a Bayesian
approach (Dienes, 2011). That is, the Neyman and Pearson approach, by definition, might
only find support for the alternative hypothesis (rejecting H0 and accepting H1), but
cannot provide support for the H0 hypothesis (when H1 is not accepted). A Bayesian
approach (Bayes factor), in contrast, can provide support for either H0 or H1 (Dienes, in
press). As the data input parameters, we used effect size and mean square error (Jiang et
al., 2012). To model the expectation parameters, following the recommendation of Dienes
(Dienes, 2011), we consulted previous studies that also explored unconscious face
processing using the CFS paradigm (Amihai et al., 2011; Moradi et al., 2005; Yang, Hong, &
Blake, 2010). In particular, the effect size during unconscious face processing in these
studies was at least two times smaller compared to that during conscious processing (Yang
et al., 2010), whereas in some cases it was five to ten times smaller (Amihai et al.,
2011; Moradi et al., 2005). Therefore, given that the effect size in the conscious
condition of our study was on average 50%, the unconscious mean prediction was defined as
7.5% and the standard deviation was set to 5% (two-tailed normal distribution). The
results of the analysis revealed the following: for the males-only set 1, the Bayes factor
was 0.07; for the males-and-females set 2, the Bayes factor was 0.95; and for the eyebrows
set 3, the Bayes factor was 0.23. Thus, the Bayes factor values in sets 1 and 3 provide
strong support for the phenomenological absence of unconscious processing (Bayes factor <
0.33); the results of set 2 should be interpreted as a “lack of sensitivity” (0.33 < Bayes
factor < 3) (Dienes, 2011).

<h>EXPERIMENT 2</h>
------------

In the current experiment, we asked whether there was a way to improve unconscious
holistic processing by means of subliminal learning with feedback (e.g., Atas, Faivre,
Timmermans, Cleeremans, & Kouider, 2014; Di Luca, Ernst, & Backus, 2010; Nishina, Seitz,
Kawato, & Watanabe, 2007; Rosenthal & Humphreys, 2010; Watanabe, Náñez, & Sasaki, 2001).
Participants underwent half an hour of subliminal learning with feedback, which was based
on same/different invisible faces (see Methods). We hypothesized that by means of
learning, we could induce the invisible face to modulate perception (discrimination) of
the visible eyes. The flow of this experiment is shown in Fig. 3. This experiment used the
image set with five male faces (two versions: intact and shifted eyes; described below).
To verify that, as a result of repetitive exposure during learning, the invisible part of
the stimulus (face) did not become visible (e.g., Atas, Vermeiren, & Cleeremans, 2013;
Schwiedrzik, Singer, & Melloni, 2009, 2011), participants underwent an invisible face
awareness test before and after learning. In addition, unrelated to subliminal learning,
participants were tested with a set of stimuli in which the original five male stimuli
were manipulated in such a way that the rectangle of the eyes in all images was shifted
(Fig. 4A). Similar manipulations are effective in disrupting holistic face processing
(e.g., Axelrod & Yovel, 2010; Maurer, Grand, & Mondloch, 2002; McKone, Kanwisher, &
Duchaine, 2007). Our plan was to compare the magnitude of any influence of invisible faces
between an intact and shifted eyes stimuli set. Critically, in order to conclude that any
effect, if found, was related to holistic processing, the magnitude of this effect must be
higher for the intact eyes than for the shifted eyes stimuli set.

        <hss>Participants</hss>

        Eighteen healthy volunteers (ages 19–30, 13 females) participated in this
        experiment. Two participants were excluded from the analysis because they reported
        consciously seeing the masked face. The experiment was approved by Tel-Aviv
        University’s ethics committee, and all participants gave informed consent to
        participate.

        Apparatus

        The same as in Experiment 1.

        <hss>Stimuli</hss>

        The image set with five male identities from Experiment 1 was used in this
        experiment. In addition, based on this image set, we created a second image set
        where the eyes rectangle was shifted to the left 6.5 degrees of a visual angle
        (see Fig. 4A). The empty eye position was filled with a uniform average color
        taken from the surrounding facial features (RGB: 217, 112, 67). The horizontal
        size of the background rectangle frames for both intact and shifted eye sets were
        increased to 35° of a visual angle.

        Invisibility manipulation

        The same as in Experiment 1.

        <hss>Experimental design</hss>

        The flow of the experiment is presented in Fig. 3. For each of the two image sets
        (intact and shifted eyes), there were five experimental sessions: two sessions
        with invisible face images, where eyes had to be discriminated (one before and one
        after learning), two awareness invisibility tests of discriminating invisible face
        images (one before and one after learning), and an eyes discrimination session
        with visible face images. The awareness invisibility tests always followed the
        eyes discrimination sessions with invisible face images. The eyes discrimination
        session with visible face images was always the last session of the experiment.
        The order of intact and shifted eyes sessions was counterbalanced between
        participants. All sessions of this experiment (including the learning sessions;
        see below) consisted of 30 trials (15 trials with same faces and 15 with different
        faces). The learning procedure included 14 sessions. These learning sessions had
        the same design as the testing sessions (eyes discrimination test) with the
        exception of a correct/incorrect indication after each trial (feedback) and
        overall score at the end of the session. While participants’ task was to
        discriminate between pairs of eyes, the correct/incorrect answer indication was
        based on same/different invisible faces. In particular, the answer was defined as
        correct if the participant answered “same” when the two invisible identities were
        the same or answered “different” when the two invisible identities were different.
        At the end of each learning session, participants received their session scores
        (percentage of correct answers). At the informal debriefing after the experiment,
        participants were asked based which parameters had served as the basis for their
        development of the ability to discriminate between the pairs of eyes. All
        participants indicated that their decision had been based on either eye shape,
        distance between the eyes, or eye color.

        <hss>Data analysis</hss>

        The analysis procedure of non-learning sessions was the same as in Experiment 1.
        The significance of a learning effect was evaluated using linear regression
        analyses, which were applied for group (averaged) and individual data. The
        procedure for the group-level linear regression analysis was as follows: (1)
        effect size values for each session were averaged across participants resulting in
        averaged effect size values (Fig. 4C); (2) these effect size values were submitted
        to linear regression; and (3) a regression line slope coefficient significantly
        different from zero was used to support the learning effect (Weisberg, 2005). The
        procedure for the individual-level linear regression analysis was as follows: (1)
        for each participant, the effect size values were submitted to linear regression;
        (2) the individual linear regression slope coefficients were obtained and
        submitted to Wilcoxon Signed Rank test (slope coefficients vs. zero test).

<hs>  Results: Experiment 2</hs>
  ~~~~~~~~~~~~~~~~~~~~~

In line with the results of Experiment 1, before learning, invisible faces did not
influence the judgment of visible eyes for both intact and shifted eye sets (Fig. 4B,
leftmost bars) (intact eyes: effect size: −2.1%, MSE: 3.9%, p = .69, Wilcoxon sign-rank =
60.5; shifted eyes: effect size: −5%, MSE: 4.3%, p = .25, Wilcoxon sign-rank = 29) (raw
response rates, Table 2, first row). The Bayes factor, modeled with the same parameters as
in Experiment 1, was 0.23 for the intact eyes set and 0.21 for the shifted eye set. Thus,
for both image sets, the results of the Bayesian analysis (Bayes factor) suggested the
absence of unconscious processing. Participants then completed a subliminal learning task
with feedback using the intact eyes image set. Average learning results across
participants are shown in Fig. 4C; as seen, performance gradually improved across sessions
(slope coefficient = 1.12, significantly different from zero: t(13) = 5.56, p < .001). To
examine the effect of learning at an individual level, a linear regression model was
estimated for each participant; the resultant individual slope coefficients were
significantly above zero [Wilcoxon Signed Rank test: p = .0086, Wilcoxon sign-rank = 5.5].
After learning, participants were tested again (sessions without feedback), and we
observed a significant effect of the invisible face on visible eyes judgments for both
intact and shifted eyes sets (Fig. 4B, middle bars) [intact eyes: effect size: 10.4%, MSE:
4.3%, p = .029, Wilcoxon sign-rank = 26; shifted eyes: effect size: 11.2%, MSE: 3.4%, p =
.013, Wilcoxon sign-rank = 7.5] (raw response rates, Table 2, second row). Repeated-
measures ANOVA, with eye position (intact/shifted eyes) and time of test (before/after
learning) as factors, revealed a highly significant main effect of time of test [F(1, 15)
= 11.826, p = .004]; however, no significant effect of eye position [F(1, 15) < 1] and no
significant interaction [F(1, 15) < 1] were found, which confirms the similar effect size
for intact and shifted eyes. In addition, using the Bayesian approach, we tested whether
the absence of difference between unconscious processing for intact and shifted eyes
should be interpreted as an insufficient experimental sensitivity or as positive evidence
in support of the absence of unconscious holistic processing. The data mean value was the
difference in effect size between intact and shifted eyes (equal to 0.83%), and the mean
standard error of difference was 0.7%. The modeling parameters were estimated based on the
reduction of the effect for unconscious processing compared to conscious processing (as in
Experiment 1) and the effect size for intact vs. shifted visible faces (around 50%). Thus,
the model’s mean was set to 5% and the standard deviation was set to 5% (two-tailed normal
distribution). The Bayes factor we found was 0.16, unequivocally suggesting the absence of
unconscious holistic processing. Interestingly, as can be seen in Table 2 (second vs.
first raw), the learning effect was associated with an increase in the proportion of
“same” responses for the “same” invisible faces (but no major change for “different”
invisible faces). To test this statistically, for raw responses (“same” responses), we ran
three-way repeated-measures ANOVA with eyes position (intact/shifted eyes), time of test
(before/after learning) and invisible stimulus type (same/different faces) as factors. We
found significant two-way interaction between time of test and invisible stimulus type
F(1, 15) = 11.826, p = .004]. The follow-up repeated-measures ANOVA only for “same”
invisible faces with eyes position (intact/shifted eyes) and time of test (before/after
learning) as factors revealed a significant main effect of time of test [F(1, 15) = 6.025,
p = .027], no significant effect of eye position [F(1, 15) = 2.596, p = .128] and no
significant interaction [F(1, 15) < 1]. Similar repeated-measures ANOVA only for
“different” invisible faces revealed no significant effects (insignificant main effect of
time of test [F(1, 15) < 1], eye position [F(1, 15) = 2.163, p = .162] and interaction
between them [F(1, 15) < 1]). Thus, we conclude that the learning was associated with
increasing the number of “same” responses for “same” invisible faces, but no change for
“different” invisible faces. To ensure that faces were genuinely invisible, we ran
awareness tests before and after learning (Fig. 3). These awareness tests confirmed that
the faces were invisible before [intact eyes: d-prime: 0, MSE: 0.1, p = .84, Wilcoxon
sign-rank = 36.5; shifted eyes: d-prime: 0.023, MSE: 0.1, p = .97, Wilcoxon sign-rank =
45] and after [intact eyes: d-prime: 0.069, MSE: 0.096, p = .43, Wilcoxon sign-rank = 46;
shifted eyes: d-prime: 0.097, MSE: 0.12, p = .39, Wilcoxon sign-rank = 45] training. For
both types of eyes, no differences existed in visibility level before or after learning
[intact eyes: p = .63, Wilcoxon sign-rank = 51.5; shifted eyes: p = .68, Wilcoxon sign-
rank = 60] and no significant correlation existed across participants between the level of
face discrimination (awareness test) and level of eyes influence effect (eye judgment main
task) [intact eyes: r(15) = 0.15, p = .56; shifted eyes: r(15) = 0.28, p = .28]. Taken
together, these results suggest that because of learning, participants’ judgment of eyes
was influenced by invisible faces. Critically, because the results for intact and shifted
eyes were similar, we conclude that the effect is not related to unconscious holistic face
processing [the classical composite face effect (Young et al., 1987)]. Finally, we tested
the “eyes-face” stimulus but now with visible faces (Fig. 4B, rightmost bars). The
findings revealed that, while in the intact eyes condition, faces influenced the
perception of the eyes significantly [effect size: 48.3%, MSE: 6.6%, p < .001, Wilcoxon
sign-rank = 1.5], the effect was completely abolished for the shifted eyes [effect size:
2.9%, MSE: 3.5%, p = .44, Wilcoxon sign-rank = 34.5]. This finding confirms that the
shifted eyes manipulation disrupted holistic face processing. To examine the difference
between visible and invisible perception (after learning), we ran a two-way repeated-
measures ANOVA with visibility level (visible/invisible) and eye position (intact/shifted)
as factors. The results showed a significant main effect of visibility level [F(1, 15) =
11.7, p = .004], a significant main effect of eye position [F(1, 15) = 26.5, p < .001],
and a significant interaction [F(1, 15) = 22.9, p < .001]. To explore different patterns
of visible and invisible processing further, we ran a post hoc non-parametric Wilcoxon
Signed Rank test, which revealed a larger effect size for visible compared to invisible
for intact eyes [p < .0012, Wilcoxon sign-rank = 5.5] and a trend for a larger effect size
for invisible compared to visible for shifted eyes [p < .077, Wilcoxon sign-rank = 24.5].

<h>DISCUSSION</h>
----------

The objective of the current study was to test whether holistic face processing can occur
outside of conscious awareness. We used a novel “eyes-face” stimulus, where discrimination
between sets of eyes was affected by the presentation of a visible congruent or
incongruent face. Using different sets of composite face stimuli, we showed that visible
but not invisible faces influenced perception of visible eyes. Moreover, even after
subliminal learning, when invisible faces biased judgments of visible eyes, this effect
was not found to be related to holistic face processing. Thus, we conclude, conscious
awareness may be necessary for holistic face processing. The question of whether face
recognition and face identity-related processing can be accomplished unconsciously has
been at the focus of research in recent years. In particular, several studies have shown
that neither facial identity (Moradi et al., 2005; Stein & Sterzer, 2011; Stone &
Valentine, 2005) nor face gender/race (Amihai et al., 2011) is processed unconsciously. In
the current study, we hypothesized that, if holistic processing is a more basic component
of face recognition, then it might be possible to find evidence for unconscious holistic
face processing. To increase the chances of identifying this effect, several steps were
taken. First, the “eyes-face” stimulus used was optimized to generate a strong effect for
visible faces. That is, studies with a classical composite face illusion stimulus (top and
bottom face halves) often use response time to index holistic processing because response
accuracy measures are often not sensitive enough (e.g., de Heering & Rossion, 2008; Wang,
Li et al., 2012). Here, given the strong response accuracy effect for visible faces (Fig.
4B), relatively large amount of room is left for a potential effect with invisible faces.
Second, in Experiment 1, we used different sets of faces while aiming to maximize
perceptual differences between the faces (e.g., male and female faces). Third, by using
the image set in Experiment 1 with and without eyebrows, we ensured that the facial
features (eyebrows) which were essential for inducing the effect were as close as possible
to the visible eyes rectangle. Finally, we employed a subliminal learning procedure, which
was successful in the sense that, as a result of learning, invisible faces influence
responses regarding visible eyes (discrimination of visible eyes). However, the fact that
similar effects were found for intact and shifted eyes ruled out the interpretation that
the effect was related to holistic face processing. Thus, given that despite all
aforementioned steps, no unconscious holistic face processing effect could be found, we
suggest that this process might not be processed unconsciously, at least for the condition
of dichoptic stimulation employed here. The absence of holistic face processing outside
conscious awareness is also interesting to consider in light of the recent proposal that
the holistic phenomenon, as it is measured in a composite task (e.g., Young et al., 1987),
is a result of automatic processing with a failure to allocate covert attention (Richler,
Cheung et al., 2011). Accordingly, given that some define automatic processes as
unconscious (e.g., Hasher & Zacks, 1979), one could have expected that face holistic
processing might be executed unconsciously. Several lines of evidence can reconcile our
result with these expectations. First, the link between automatic and unconscious
processing is frequently made for the highly learned processes, like car driving (e.g.,
Charlton & Starkey, 2011), which might involve awareness mechanisms different from the
sensory (un)awareness for masked stimuli used in our study. Second, the relationship
between attention and consciousness is highly debated (for reivews: Koch & Tsuchiya, 2007;
Marchetti, 2012; Van Boxtel, Tsuchiya, & Koch, 2010) and it has been shown, for example,
that two processes can be dissociated (e.g., Naccache, Blandin, & Dehaene, 2002). Yet, it
is not clear whether a failure to allocate covert attention, which might be a result of
automatic processing (Richler, Cheung et al., 2011), can occur for invisible, unconscious
stimuli. Finally, a similar hypothesis had been proposed with regard to the Stroop task
(Stroop, 1935), which is also automatic (MacLeod, 1991) and therefore can be processed
unconsciously (Marcel, 1983). Yet, the empirical support for this hypothesis is rather
controversial: while some studies do find an unconscious Stroop effect (e.g., Marcel,
1983), others claim that such an effect can be explained by conscious awareness (Tzelgov,
Porat, & Henik, 1997) or partial awareness (Kouider & Dupoux, 2004). Thus, in light of the
evidence provided, the absence of unconscious holistic face processing might not be that
surprising. The results reported here are interesting to consider in the context of
unconscious processing of visual context in general. The invisible surroundings can
influence the orientation of a centrally presented visible grating (Clifford & Harris,
2005), and the invisible surrounding luminance can modulate the perceived brightness of
the centrally presented visible circle (Harris et al., 2011). In addition, two studies
have explored the perception of illusory contours surrounded by an invisible context, and
reported mixed results. One study found, using breaking continuous flash suppression
(Jiang, Costello, & He, 2007) that an invisible Kanizsa triangle emerged into awareness
faster than did a control stimulus (Wang, Weng, & He, 2012). The second asked participants
to indicate the direction of the Kanizsa triangle induced by the invisible surroundings
and reported only chance performance (Harris et al., 2011). Notably, the invisible context
and the stimuli explored in the studies described above were relatively simple stimuli,
which are known to be processed at a relatively low level within the visual hierarchy
(e.g., V1 for line orientation, V4 for color processing). In contrast, faces are processed
within high-level regions of the occipito-temporal cortex (Haxby, Hoffman, & Gobbini,
2000); therefore, it is plausible that low-level, but not high-level, context can be
processed unconsciously. Finally, Mudrik and colleagues recently demonstrated an
interesting example of invisible context processing (Mudrik et al., 2011), where the
authors showed that invisible scenes containing incongruent invisible objects emerged into
awareness faster than did congruent scenes (see also: Mudrik & Koch, 2013). Yet, as the
invisible context in this study was semantic and not purely visual, there is no
straightforward way to relate their findings to ours. What might be the possible
underlying neural mechanisms of the effect we observed? The neural network of face
processing is well characterized (Haxby et al., 2000), while the commonest and the most
reproducible region across participants is the Fusiform Face Area (FFA) (Kanwisher,
McDermott, & Chun, 1997). The FFA exhibits various properties pertinent to face
processing, such as partial view-invariance (e.g., Axelrod & Yovel, 2012; Grill-Spector et
al., 1999; Kietzmann, Swisher, König, & Tong, 2012) and discrimination between face
identities (e.g., Gilaie-Dotan & Malach, 2007; Nestor, Plaut, & Behrmann, 2011; Rotshtein,
Henson, Treves, Driver, & Dolan, 2005). More critical for the current discussion, however,
is that the FFA has been suggested to be responsible for holistic face processing (Andrews
et al., 2010; Axelrod & Yovel, 2010, 2011; Schiltz & Rossion, 2006; Zhang, Li, Song, &
Liu, 2012). If this is indeed the case, and assuming that unconscious information can
reach the FFA (e.g., Fahrenfort et al., 2012; Moutoussis & Zeki, 2002; Sterzer et al.,
2008), then our result suggests that the FFA operations responsible for holistic
processing are associated with awareness; however, one should also consider that the
network of face-processing regions is distributed (Gobbini & Haxby, 2007) and spans not
only the occipito-temporal cortex (Op de Beeck, Haushofer, & Kanwisher, 2008) but also the
frontal lobes (Axelrod & Yovel, 2013; Ishai, Schmidt, & Boesiger, 2005). As such, holistic
processing might also require interactive processing between several different brain
regions – the type of distributed, long-range processing that was proposed to be
associated with awareness (e.g., Dehaene & Changeux, 2011; Dehaene, Kerszberg, & Changeux,
1998). Overall, future research will be needed to gain a deeper understanding of the
underlying neural correlates. A special note should be made regarding the subliminal
learning procedure employed here. As discussed, the fact that, during and after learning,
invisible faces influenced both intact and shifted eyes suggests that the effect was not
related to holistic processing. We also found that the learning was associated with a more
frequent “same” answer for the “same” invisible faces, but no change for “different”
invisible faces. Yet, as the goal of the current study was not to explore the mechanisms
of subliminal learning but rather to use this type of learning as a tool, it is not
possible to clearly determine exactly what type of information was learnt and how the
learning occurred. It is plausible that, in the course of learning, participants
unconsciously learnt to associate between the “change” or “no change” of invisible images
(faces) and the required response for visible eyes. In other words, the same/different
faces were treated as just same/different images. In addition, it is also possible that
motor response mapping associative learning occurred (Damian, 2001) while participants
learnt to press ‘1’ when two invisible images were the same and ‘2’ when they were
different. Notably, the learning procedure did not influence face awareness, which was
equally invisible before and after learning. Finally, it should be noted that according to
an alternative view of holistic processing, the effect that is measured by a composite
task might not be of a perceptual but rather a decisional nature (e.g., Richler, Gauthier,
Wenger, & Palmeri, 2008; Richler, Palmeri, & Gauthier, 2012; Rossion, 2013). In our study,
to increase the sensitivity of the design, we included only the pairs of the same eyes.
That is, by requiring participants to discriminate between the same eyes, we imposed the
participants to set the same-different decision boundary at a low level. Indeed, this
design was very sensitive, as we found that context had large effects on eye perception
for visible faces. Yet, this design had its downside as well; since no different pairs of
eyes were included, our ability to estimate potential response bias was limited (e.g.,
Richler et al., 2012; Rossion, 2013). Critically, the main goal of the present study was
to explore whether invisible faces influence the discrimination of visible eyes,
regardless of the nature of holistic processing. To conclude, in the current study we
explored the question of whether holistic processing can take place outside of conscious
awareness. Using three different sets of face images and applying a procedure of
subliminal learning, we demonstrated that conscious visual awareness might be a
prerequisite for holistic processing.


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<ART>Consciousness as a concrete physical phenomenon
===============================================

Authors: J. Jylkkä, H. Railo
DOI: 10.1016/j.concog.2019.102779
Year: 2019
ASJC codes: 3204, 3205
Keywords: Constitutive mechanisms of consciousness, Empirical observation, Epistemic gap, Hard problem of consciousness, Model-dependent realism, Neural correlates of consciousness, Philosophy of science, Russellian Monism, Scientific models

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<h>ABSTRACT</h>
--------

The typical empirical approach to studying consciousness holds that we can only observe the neural correlates of experiences, not the experiences themselves. In this paper we argue, in contrast, that experiences are concrete physical phenomena that can causally interact with other phenomena, including observers. Hence, experiences can be observed and scientifically modelled. We propose that the epistemic gap between an experience and a scientific model of its neural mechanisms stems from the fact that the model is merely a theoretical construct based on observations, and distinct from the concrete phenomenon it models, namely the experience itself. In this sense, there is a gap between any natural phenomenon and its scientific model. On this approach, a neuroscientific theory of the constitutive mechanisms of an experience is literally a model of the subjective experience itself. We argue that this metatheoretical framework provides a solid basis for the empirical study of consciousness.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The current scientific view about the relationship between consciousness and neural
activity is ambivalent. On the one hand, the enterprise to solve the mystery of
consciousness using neuroscience is built on the physicalistic idea that consciousness is
identical with neural activity: We know that the brain is necessary for consciousness, and
neuroscience has begun to unravel the neural mechanisms that enable subjective, conscious
experience (Dehaene & Changeux, 2011; Koch, Massimini, Boly, & Tononi, 2016; Laureys,
2005). On the other hand, scientists and philosophers often assume that science can merely
observe correlations between neural activity and consciousness, not consciousness per se.
After all, how could neural activity be identical with consciousness given that the two
appear so different? For this reason, neuroscientists search for the neural correlate of
consciousness (NCC), which has been defined as the minimal set of neural processes that
are together sufficient for a specific conscious experience (Crick & Koch, 1990). Here, we
attempt to shed light on this discrepancy. The present article is an attempt to formulate
a plausible and solid metatheoretical foundation for the neuroscientific study of
consciousness. This is, in our view, an imperative objective for consciousness science.
While consciousness science has established itself as a specific field of empirical
science, it seems to be still searching for its identity: Arguably, it is a field that
does not yet have a clearly defined explanandum. This is likely to foster false
disagreements between theories of consciousness, and contribute to the perception that
consciousness science is a less rigorous field than other fields of science (Michel et
al., 2018). In this paper, we defend a form of physicalistic monism, which holds that all
concrete phenomena are physical—this is typically the starting point in modern science.
Complex phenomena, such as those studied by chemistry, biology, or neuroscience, belong to
the same ontological category as fundamental physical processes (those studied by fields
such as particle physics), and are based on them. We could say that “physical” denotes the
set that contains all concrete phenomena, and terms like “biological” or “neural” denote
subsets of that all-encompassing set. By the term “physical” we mean the ontological
category of phenomena studied by physics—thus, on our reading “physical” is a placeholder
for whatever is the fundamental nature of phenomena studied by physics. As we will argue
below, we take subjective experiences or consciousness to be concrete natural phenomena
(Revonsuo, 2006; Searle, 2002; Strawson, 2008b). If we endorse the physicalistic premise
that all concrete natural phenomena are physical, it follows that our experiences are
physical phenomena. This might appear to be a contradictory claim, given that the term
“physical” is often defined in opposition to “mental”. For instance, according to the
Oxford Dictionary, “physical” is something “relating to the body as opposed to the mind”,
or as “relating to things perceived through the senses as opposed to the mind” (emphasis
added) (Physical, n.d.). Here we do not adhere to this standard usage of “physical”,
because it a priori commits us to dualism. On our reading, terms like “experiental” or
“conscious” denote certain natural phenomena which belong to the class of physical
phenomena. The challenge for physicalists who consider experiences to be identical with
some neural processes is to explain why the two appear so different, or why there is an
epistemic gap between the two. For instance, a person with total congenital achromatopsia
arguably cannot know what it is like to see the vivid colors of a sunset on a clear
evening, even if she perfectly knew all the details of how the human brain works. It
appears that science cannot tell us anything about the qualitative or subjective aspects
of experiences—the colors of the sunset, the bitterness of coffee, or the pain of having a
manuscript rejected—and thus cannot completely capture their nature (e.g. Chalmers, 1996;
Jackson, 1986; Nagel, 1979). The difficulty of conceiving subjective experiences—or
“qualia”, to use the philosophical term referring to the “qualitative feelings” associated
with experiences—as an object of scientific study has led some empiricists to explicitly
avoid referring to them (Dehaene, 2014), or to claim that such aspects do not exist
(Dennet, 1991; Dennett, 2018). Many attempts in philosophy have been made to explain where
the epistemic gap stems from, and the so-called phenomenal concepts strategy is probably
the most popular alternative (for a good overview, see Balog, 2012). It aims to reduce the
gap into differences between how phenomenal and non-phenomenal concepts refer. Non-
phenomenal concepts have a mode of presentation that is distinct from their referent
(e.g., we recognize water based on its perceptual features, but not everything that
appears to be water is water), but phenomenal concepts are suggested to be more intimately
tied with their referent. For instance, it is claimed that phenomenal concepts are
recognitional concepts whose mode of presentation is identical with their referent (e.g.
Loar, 1990); that phenomenal concepts are similar to indexicals like “here” and “now”
(e.g. Ismael, 1999); or that they are quotational concepts, so that e.g. “pain” refers to
“that state:___”, where the blanks are filled in with pain itself (e.g. Papineau, 2002).
Our main focus in this paper is not on differences between how phenomenal and scientific
concepts refer, but instead on the question of how, and to what extent, science can model
consciousness. In this paper we take it as our premise that experiences, in all their
qualitative richness, are concrete physical phenomena (Strawson, 2008a). To emphasize that
empirical explanations of consciousness aim to characterize the causal physical processes
that are identical with consciousness—not processes that merely correlate with it—we use
the concept “constitutive mechanisms of consciousness” (CMC; Revonsuo, 2006). As discussed
later in detail, by CMC we mean all those physical processes that together make up
consciousness. Similar to biologists who try to describe the hierarchical physical
processes that constitute, for example, a living cell or an amoeba, consciousness science
aims to describe the hierarchical constitution of the processes that constitute
consciousness. This approach is superficially similar to the aim of describing the NCC.
The NCC and CMC approach share the idea that consciousness can be described as a
hierarchical process: lower level phenomena (molecules, neurons, their activity) combine
to produce a system-level phenomenon (a network of neurons and brain areas), which
corresponds to consciousness. The crucial difference between these two views is that the
CMC approach implies that the physical phenomenon the scientific theories describe is
consciousness. The NCC approach, in contrast, suggests that the theories describe a
physical phenomenon that merely correlates with consciousness. This brings us back to the
aim of the present paper: What does it mean to claim that certain neural activation
patterns are identical with experiences, given that the two appear so different? As a
summary, we aim to characterize how subjective experiences are related to empirical
observations and models about their constitutive mechanisms, and why there appears to be
an epistemic gap between the two. We propose that the epistemic gap is distinctness
between the scientific CMC-model and the concrete experience. A scientific model is always
distinct from the concrete phenomenon it models, and in this sense there is an epistemic
gap between any phenomenon and its model, not just experiences. As suggested by Hawking
and Mlodinow (2010), through science we can never know the nature of the world in itself,
we can only model it based on observations. This is because scientific models (like our
everyday models of the world) are phenomena in the scientists’ brains: they are mental
models that aim to explain and predict scientific observations of external phenomena.
Thus, scientific models of subjective experiences are themselves conscious phenomena in
the minds of scientists. Our framework implies that our subjective experiences are
different from other natural phenomena solely because they are the only phenomena in the
universe that constitute our subjective realm. If we assume that all the properties of
experiences (including what they feel like) are physical and causally efficacious, then
they can causally interact with measuring devices. Thus, it is possible to observe and
model consciousness itself, not just its correlates. We call our approach Naturalistic
Monism, because it shares some key components with Russellian Monism (RM), but is
completely naturalistic: it does not postulate the existence of properties beyond the
scope of natural science. This article is structured as follows. In the second part, we
explain how our approach is motivated in particular by Strawson's (2008a, 2008b) version
RM, but also how our view significantly differs from it. In the third part of the article,
we describe in what sense scientific theories are distinct from the phenomena they model,
and what implications this has for consciousness research. In the fourth section, we
discuss the implications of Naturalistic Monism from the perspective of science of
consciousness, and conclude that neuroscience can study consciousness, not just its
correlates. Finally, in the fifth section we briefly discuss the philosophical
implications of our approach.

<h>CONSCIOUSNESS AS A PHYSICAL PHENOMENON</h>
--------------------------------------

Among philosophers, RM has recently gained popularity as an explanation of how experiences
are related to their neural mechanisms (e.g. Alter & Nagasawa, 2012; Chalmers, 2016; Goff,
2017; Montero, 2015; Schneider, 2017). It promises to account for why science appears to
have trouble in explaining the subjective aspects of experiences, while maintaining that
experiences are nevertheless identical with their neural mechanisms. Naturalistic Monism
shares two premises with RM: First, it holds that experiences are concrete natural
phenomena; Second, it accepts that science has in some sense limited access to their
nature. The crucial difference between Naturalistic Monism and RM concerns how the second
premise should be interpreted. Strawson (2008a, 2008b) calls his version of RM “Real
Materialism”, because it is both materialistic (or physicalistic; Strawson uses the terms
interchangeably) and realistic about experiences. He writes: “Realistic physicalists,
then, grant that experiential phenomena are real concrete phenomena—for nothing in life is
more certain—and that experiential phenomena are therefore physical phenomena. It can
sound odd at first to use ‘physical’ to characterize mental phenomena like experiential
phenomena, and many philosophers who call themselves materialists or physicalists continue
to use the terms of ordinary everyday language, that treat the mental and the physical as
opposed categories. It is, however, precisely physicalists (real physicalists) who cannot
talk this way, for it is, on their own view, exactly like talking about cows and animals
as if they were opposed categories. Why? Because every concrete phenomenon is physical,
according to them. So all mental (experiential) phenomena are physical phenomena,
according to them; just as all cows are animals.” (Strawson, 2008c) Naturalistic Monism
endorses this premise, as it is formulated in the above quote. The existence of
consciousness is the most certain thing in the world: we can doubt the existence of the
whole external world, but not our own experiences. If we are physicalists and take it that
experiences feel like something, then we must admit that there exist at least some
physical phenomena in the universe that feel like something. However, this is where our
agreement with Strawson and other Russellians largely ends. For Strawson continues: “I am
happy to say, along with many other physicalists, that experience is ‘really just neurons
firing’ […] But when I say these words I mean something completely different from what
many physicalists have apparently meant by them. I certainly don’t mean that all
characteristics of what is going on, in the case of experience, can be described by
physics and neurophysiology or any non-revolutionary extensions of them. That idea is
crazy. It amounts to radical ‘eliminativism’ with respect to experience, and it is not a
form of real physicalism at all.” (ibid) Strawson’s idea is probably the following: if it
was possible to characterize the nature of experiences completely in terms of science, no
room would be left for phenomenal qualities or what-it-is-likeness, because science
appears to say nothing about such properties. Strawson appears to claim that if
experiences could be perfectly characterized scientifically, we would be philosophical
zombies (Chalmers, 1996). We strongly disagree with this claim: as we will argue, it
conflates experiences with their scientific models. Strawson’s view is based on a
metaphysical distinction between extrinsic (roughly: relational, structural, and
dispositional) and intrinsic (non-relational, non-structural, and non-dispositional)
properties (for a useful discussion of the distinction, see Seager, 2006). On this view,
science is only concerned with extrinsic properties—how objects behave, which causal
dispositions they have, which relations they stand in, what is their structure, and so on.
For instance, in Newtonian physics, force is defined in relation to mass and acceleration.
For Russellians, this leaves open the question: what is the non-relational, non-
dispositional, and non-structural nature of a phenomenon? Russell (1927) himself argued
that this intrinsic nature is ontologically “neutral” (that is, neither mental nor non-
mental; see Stubenberg, 2016), but Strawson takes it that the intrinsic nature of all
physical phenomena is (proto)mental (see also Goff, 2017). To use the current terminology,
Strawson would argue that what an experience feels like is part of the intrinsic (science-
transcendent) nature of the experience, but CMC characterizes the extrinsic
(scientifically observable) nature of the same phenomenon. The intrinsic-extrinsic
distinction could be criticized in many ways (see e.g. Hiddleston, 2019; Howell, 2015;
Kind, 2015), but here we simply note that the postulation of intrinsic properties is
metaphysically promiscuous and unscientific. If we suppose that there is an unobservable
and causally impotent intrinsic property corresponding to each observable, causally
efficacious property, we double the number of physical properties in the universe solely
based on armchair reflection. Moreover, as argued by Ellis (2001), among others, there may
be no need to postulate any categorical properties to “ground” causal dispositions or
relational properties, because all natural phenomena can be considered as essentially
causal-dispositional, or processes. For instance, scientifically it makes no sense to
speak of the nature of quarks independently of how they interact with other subatomic
particles. According to the standard version of quantum chromodynamics, it is impossible
for quarks to exist in isolation, so it is nomologically impossible for them to possess a
non-relational nature. Because RM implies that experiences are beyond the scope of
science, it renders the scientific study of consciousness impossible in principle: science
can only study the extrinsic correlates of consciousness, not consciousness per se. This
resembles the dualistic notion that “conscious experience involves properties of an
individual that are not entailed by the physical properties of that individual, although
they may depend lawfully on those properties” (p. 110; Chalmers, 1996). This type of
reasoning in part underlies the use of the term “correlate” to describe the neural
mechanisms that underlie consciousness. If we could account for the epistemic gap without
assuming an ontological gap between different types of properties, we should do so.1 This
is the aim of Naturalistic Monism. It holds that experiences are just like any other
physical phenomena in that they can be observed and scientifically modelled. The epistemic
gap between experiences and their scientific models does not reflect the existence of any
separate types of properties, but instead simply the distinctness between a phenomenon and
its scientific model.

<h>NATURALISTIC MONISM: PHENOMENA AND THEIR SCIENTIFIC MODELS</h>
----------------------------------------------------------

Naturalistic Monism shares with Russellian Monism (RM) the Kantian assumption that science
has in some sense limited access to the nature of the phenomena it studies. However, as
explained above, whereas RM holds that there exist two distinct types of properties
(extrinsic and intrinsic), Naturalistic Monism takes it that there exists only one class
of physical phenomena. The limits of science are not due to the existence of ontologically
distinct types of properties, but instead to the fact that we can only know the world
through observations and scientific models. Schneider (2017), a proponent of RM, motivates
the existence of science-transcendent intrinsic properties by quoting the theoretical
physicist Stephen Hawking, who famously asked: “What is it that breathes fire into the
equations and makes a universe for them to describe? The usual approach of science of
constructing a mathematical model cannot answer the questions of why there should be a
universe for the model to describe.” (Hawking, 1988, 174). Strawson (2008b), in turn,
quotes the astrophysicist Arthur S. Eddington, who noted that “[…] science has nothing as
to the intrinsic nature of the atom. The physical atom is, like everything else in
physics, a schedule of pointer readings. The schedule is, we agree, attached to some
unknown background.” (Eddington, 1929, 259) But do Hawking and Eddington intend that there
would exist some properties of physical phenomena completely beyond the scope of science,
as Russellians would have it? Or did they simply mean that we cannot know the nature of
physical phenomena without relying on observation (“pointer readings”) or without
utilizing scientific models and equations? The former claim is metaphysical, the latter is
purely epistemological. At least Hawking intended to make a purely epistemological claim,
which he and Mlodinow formulated more explicitly when they introduced the notion of Model-
Dependent Realism (MDR) (Hawking & Mlodinow, 2010). According to MDR, we can never know
the nature of the world as it is in itself, but instead we can only know it through how it
affects our senses. Based on observations, we can formulate models of the world in our
minds, but we can never step outside the models and compare them to model-independent
reality. We can never be certain if our models are true in a strict sense of the word; we
can only evaluate whether they are elegant, can predict observations, or can be used to
manipulate phenomena. Hawking and Mlodinow consider scientific models on par with our non-
scientific, everyday models of the world: both are in the mind/brain of the organism and
based on constant causal interaction between the organism and its environment.
Consciousness itself can be considered as an internal model of the world, which affords us
to predict and explain what happens in our surroundings, increasing our chances of
survival (Friston, 2010; Hobson & Friston, 2014; Revonsuo, 2006). In this sense, there is
only a matter of degree between a person forming an inner representation of the world
based on their everyday interaction with it, aided by nothing but naked senses and their
body, and a researcher building a scientific model based on more sophisticated,
instrumentally aided, and theoretically-driven observations and manipulations of the
phenomena. In both cases, the model is a natural phenomenon in the brain of the modeler,
and can itself be an object of scientific inquiry (more about this in Section 5.1.). It is
a philosophical question whether a model can ever be considered as “true”, but from a
purely naturalistic perspective we can judge to what extent an organism’s internal model
of the world affords it to interact with its environment efficiently. A mouse has a valid
internal model of its surroundings if the model affords the mouse to seek shelter from the
approaching cat in the nearest burrow. Likewise, our scientific atomic model can be
considered as valid if it affords us to build functioning nuclear reactors. Thus, internal
models—irrespectively of whether they are of a scientific or everyday variety—can be
minimally considered as valid or even “true” in a pragmatic sense. Whether they are true
in some stricter sense is a philosophical problem that is beyond the scope of the present
paper. According to Naturalistic Monism, the epistemic gap between a subjective experience
and its scientific description is distinctness between two phenomena: the experience in
the mind of a participant and the scientific model in the mind of the researcher.
Naturalistic Monism implies that an experience is the concrete phenomenon that a
scientific model of its constitutive mechanism describes; it is what underlies scientific
observations of its constitutive mechanisms. Scientists can model experiences, but the
participants’ experiences are always distinct from their scientific models, which are in
the minds of researchers. Whereas the participant has “immediate” or first-person access
to their experiences, the researcher can know them “mediately” through observations and
models. The researcher does not have direct access to the participant’s experiences; they
can only access the participant’s consciousness indirectly by causally interacting with it
(and directly experiencing a model of it in their own consciousness). In this respect,
consciousness is an exceptional object of research: it is the only phenomenon that we can
at least partly know or experience directly, not only based on observations and models.
Thus, in the case of experiences, we can directly compare the model and the concrete
phenomenon that is modeled—something we can never do in the case of, say, atoms. Science
can model all the aspects of experiences—including what they feel like—but only model. For
instance, suppose that subjective pain could be modelled as T-type interaction between
neural modules M1 and M2 (or T-interaction, for short). “T-interaction” is just pain’s
scientific model, formed in the mind of a scientist based on observations, such as which
neural events are correlated with reports of pain, avoidance behavior, certain facial
expressions, and so on. Even a scientific realist, who assumes that scientific theories
can truthfully capture the nature of natural phenomena, cannot hold that pain is literally
nothing but “T-interaction”, because “T-interaction” is a theoretical model of pain, and
distinct from pain itself. Instead, the realist should be interpreted as claiming that
pain can be truthfully modelled as “T-interaction”. This is compatible with the fact that
when the concrete process scientifically modelled as “T-interaction” happens in a subject,
the occurrence of the process feels like something for her. Crucially, the subjective feel
of pain is nothing distinct from the process described by the model; it is the happening
of the concrete process itself. Accordingly, a scientific realist can accept that pain has
a qualitative feel; what their realism implies is only that the feel of pain can be
truthfully modelled as “T-interaction”. In this sense, we can eliminate the theoretical
notion of “qualia”, conceived of as a non-dispositional, non-relational, and non-
structural property, without claiming that experiences would not feel like anything (in
the everyday sense of “feeling like something”) (cf. Dennett, 2018). A neuroscientific
CMCE-model of an experience E is never identical with E; it only refers to E. Whereas
science can only model experiences through observation, we know our own experiences
immediately. My pain is not something outside of me that I observe, it is part of my
subjective realm. It constitutes the physical process that is my consciousness, which
could be observed and modelled by a scientist as CMCpain. To paraphrase Edelman and Tononi
(2000), “Unlike any other entity, […] with consciousness we are what we describe
scientifically” (p. 14, italics in the original). The reason why we easily think that
there is an epistemic gap only for experiences is because our experiences constitute us,
and thereby we have non-empirical access to their nature—access that is not mediated
through observations and models. Naturalistic Monism implies that there is an epistemic
gap between any concrete phenomenon and its scientific model, due to the distinctness
between the model and the phenomenon. As discussed later in the article (Section 5.2.),
how wide we take the gap to be depends on which philosophy of science we endorse.
Naturalistic Monism implies that what an experience feels like is part of its nature in
itself, independently of observations, scientific models, or other theoretical
characterizations. In fact, describing an experience as “feeling like something” is
already a conceptualization, and it could be debated whether it adequately or truthfully
captures the nature of the experience. Descriptions of consciousness typically depend on
the person’s favorite philosophical theory, religion, culture, or level of education.
Consciousness could be said to be “neural activation”, “qualitative”, “phenomenal”,
“feeling like something”, “non-relational”, “non-structural”, consisting of “qualias”,
“soul”, “Brahman”, and so on. All such definitions of experiences could be questioned, but
that does not amount to questioning the nature of experiences themselves. If you take René
who believes in an immaterial soul, David who believes in qualia, and Daniel who denies
the existence of qualia, and stick them with a needle, the same kind of natural phenomenon
is instantiated in all of them. The concrete phenomenon that occurs in them is of the same
type, even if they define it in very different ways—nature does not care about our
definitions.2 The qualitative feel of experiences is often considered as problematic or
even impossible to model scientifically. Naturalistic Monism implies that it is possible
to model what experiences feel like—but only model. The discrepancy between what, say,
pain feels like for a subject S and how a scientific model characterizes it is simply
distinctness between pain and its scientific model. Pain is a natural process happening in
S, whereas its scientific model is a highly complex conceptual representation in the minds
of scientists. What pain feels like for S is not something over and above the process
described by the model; instead, it is the happening of the described process in S. When
pain happens in me, I can minimally say it feels like “this”, referring to the happening
of my pain experience (Ismael, 1999; Papineau, 2002). Consciousness science aims to model
such processes, and can in this sense model what experiences feel like. In the form of an
argument: What pain feels like for S = the happening of pain in S. The happening of pain
in S is a concrete physical process. Science can model all concrete physical processes.
Thus, science can model what pain feels like. It is common to suppose that knowing a
scientific model of pain does not give knowledge of what pain feels like. In contrast,
according to Naturalistic Monism, knowing the pain-model does give knowledge of what pain
feels like, but only knowledge in terms of the scientific model, which is distinct from
concrete pain. What concrete pain feels like is simply the happening of pain in us, a
process that science aims to model with the pain-model. We can say that pain is nothing
but “T-interaction” (in a de re sense, meaning that “T-interaction” refers to pain), but
this does not amount to reducing concrete pain into the theoretical T-interaction-model.
Instead, pain, including what we call its “what-it-is-likeness”, is the concrete
phenomenon that science models as T-interaction. The take-home message is that we need not
postulate the existence of any properties (“qualia”) for the what-it-is-likeness of pain
over and above the properties described by the scientific pain-model. Once we have a
scientific model of pain that is perfectly isomorphic with pain as experienced, we have a
scientific model of pain’s phenomenology. For instance, the experienced intensity or
sharpness of pain could be modelled as parameters in the pain-model that correspond to
such qualities—any change in the experienced sharpness of pain corresponds to a change in
the corresponding parameter (see Section 4.1.). However, this does not mean that pain
itself would be just the theoretical parameters; it is what the parameters model.3

<h>STUDYING CONSCIOUSNESS SCIENTIFICALLY</h>
-------------------------------------

We have argued, first, that consciousness should be viewed as a concrete physical process
in the world in the same sense as lightning, photosynthesis, and life—experiences are of
the same ontological type as all physical phenomena, there is only difference in
complexity. Second, we have stressed that scientific models are themselves mental
phenomena and always distinct from the phenomena they model. Because experiences are
concrete phenomena, they can causally interact with other physical phenomena, including
observers and their measuring devices. Science can model experiences as CMCs. For a
neuroscientist, the experience of a subject is the “external” phenomenon that affects the
scientist’s measuring devices, and which they aim to describe with the CMC-model. From the
subject’s perspective, their experience is an “internal” phenomenon, part of their
subjective realm. We will next illustrate Naturalistic Monism with the help of a
neuroscientific example. Consider a visual experience of a cat (Fig. 1). On our approach,
a subjective cat experience is the physical process in the world that underlies
neuroscientific observations that we interpret in terms of the CMCcat-model (a model of
the constitutive mechanisms of a cat experience). Thus, the terms “cat experience” and
“CMCcat” refer to the same concrete phenomenon.4 Whereas the term “experience of cat” is
typically used to refer to an experience when it is part of a subject’s consciousness, the
neuroscientific term “CMCcat” is used in scientific contexts, where it refers to the
experience as the external phenomenon that causes scientific observations. Experiences are
complex physical processes that are composed of lower-level phenomena, and the composition
can be described scientifically. Science can describe how experiences are composed of
lower level processes in the same way as it explains how hydrogen and oxygen form water.
This framework is summarized in Fig. 1. The cat-experience is depicted in Fig. 1 as a
complex physical process that is composed of lower-level constituent processes. This can
be empirically modelled by defining how the CMCcat-process is related to its constituent
processes. It is often argued that consciousness cannot be fully explained by analyzing
the interactions between its lower-level constituents (this is the so-called “combination
problem” that RM faces; see Chalmers, 2017). This argument conflates phenomena with their
scientific models: one can never “reduce” any phenomenon to its description or
descriptions of its lower level processes (reduce Xn to Yn or Yn-1 in Fig. 1); one can
only reduce descriptions to other descriptions (reduce Yn to Yn-1). To give an example,
one can explain how the functioning of an amoeba is based on the interactions between the
molecules that constitute it, and in this sense reduce the scientific model of the living
amoeba to models of lower-level phenomena, such as interactions between proteins, enzymes,
and so on. This does not mean that the actual, concrete amoeba is “reduced” to anything
else; the concrete amoeba is the complex system composed of the interaction between
molecules, enzymes, and so on. In the same way, one can model how an experience is based
on lower level processes (how Yn is based on Yn-1), but this does not amount to “reducing”
the concrete experience (Xn) into a description. When we explicate how a cat-experience is
composed of lower level processes (the lower axis in Fig. 1), we do it in terms of
describing how the CMCcat is composed of lower-level processes, such as the activation of
individual neurons (the upper axis in Fig. 1). Crucially, when we scientifically reduce an
experience into lower-level processes, we do so only descriptively. “Reducing” the
concrete experience—literally tearing it to parts—would amount to destroying it. The
crucial point here is that if we accept that scientific models of experiences are
literally models of experiences, then it is possible to scientifically model how
subjective experiences are based on lower-level processes. The black boxes in Fig. 1 might
appear to motivate some kind of mysticism about the nature of (non-mental) physical
phenomena, similar to Strawson’s “intrinsic nature” that cannot be empirically captured.
However, this mysticism is inherent to all science: we can never know the nature of the
world as it is in itself, we can only model it based on how it affects our senses. In Fig.
1, the lower level boxes are mostly black to emphasize that the phenomena exist
independently and outside of how we scientifically model them, but this does not imply
that they are completely epistemologically opaque to us: we can know their nature, but
only through observations and models. Moreover, it is important to notice that whether a
box is black or not depends on perspective: my consciousness is not a black box for me,
but it is for you, because your knowledge of my consciousness is based solely on
observations and models (your model of my mind).

<hs>  Towards an empirical model of consciousness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Because Naturalistic Monism implies that an experience is a concrete physical phenomenon,
and that all the properties of experiences are physical properties, it must be possible to
observe and scientifically model all the characteristics of an experience. Hence, based on
the current framework, empirical science can study consciousness, not just its correlates.
This is an important upshot, as it collapses the problem of consciousness into a standard
problem of science. Specifically, we suggest that scientific models of consciousness
should describe the following5 (Fig. 2): Constituents. Because consciousness is a complex
physical process, science should describe its constituents. This explanation describes
what consciousness is “made of”. Isomorphy. A complete model of consciousness should
accurately describe all the details about the contents of consciousness, including its
phenomenology. Etiology. Understanding the etiological basis of consciousness, from
immediately preceding causes to its phylogenetic basis, is crucial for understanding
phenomenology. Causal power. Being a concrete physical phenomenon, consciousness can
causally interact with other physical processes inside the brain. A key part of explaining
consciousness is explaining what it can do.

        <hss>Lower-level constituents</hss>

        According to Naturalistic Monism, a successful empirical theory of consciousness
        must specify the constituent processes that are necessary for consciousness, but
        which are not themselves conscious until they interact in some specific way to
        form the CMC. The constituents are for CMC what hydrogen and oxygen are for water:
        hydrogen and oxygen do not cause water, they constitute it. The constituents of
        consciousness are often called the “mechanism of consciousness”: Which neural
        processes determine whether an individual is conscious or unconscious? Which
        neural processes determine whether a visual stimulus will be consciously
        perceived? Examples of theoretical attempts to answer such question include the
        global workspace model (GWT; Baars, 1988; Dehaene & Changeux, 2011), integrated
        information theory of consciousness (IIT; Oizumi, Albantakis, & Tononi, 2014), and
        higher-order thought theory of consciousness (Lau & Rosenthal, 2011). These
        theories aim to describe how consciousness “emerges” from neural activity.
        According to Naturalistic Monism, these theories aim to describe the CMC.
        Crucially, because the CMC is a model of consciousness, explaining the
        constituents of CMC amounts to explaining the constituents of consciousness
        itself—not just something that correlates with consciousness. Consider the GWT,
        for example. According to the theory, consciousness is a process where a large
        number of individual modules share their information with each other to enable
        flexible behavior and maintenance of information (Baars, 1988). According to the
        neural model of the theory, this corresponds to synchronous interactions between
        specific neural populations in frontal, parietal and sensory cortical areas
        (Dehaene & Changeux, 2011). These individual processes are not conscious alone,
        but become conscious when they interact in the way that the theory describes.
        These constituent processes are further based on lower-level processes:
        oscillatory activity requires a certain balance of excitatory and inhibitory
        neurons, neural activity requires a resting membrane potential, neurons are made
        up of specific molecules, and so on. The constituents can, in principle, be traced
        to fundamental physical entities; in this sense, the CMC (the experience) is
        continuous with other physical phenomena. GWT does not make claims about how the
        subjective aspects of consciousness (phenomenology) are enabled by activation of
        the global workspace, but according to Naturalistic Monism, the concrete
        phenomenon whose functional aspects GWT models is consciousness and has a certain
        phenomenology for the subject in whom it happens. Accordingly, the functional
        properties modelled by GWT are not independent of phenomenal consciousness; they
        are the functional aspects of phenomenal processes (causal power of consciousness
        is discussed further in Section 4.1.4.).

        <hss>Isomorphism</hss>

        Because the phenomenology of an experience is a concrete physical process, any
        change in phenomenology can in principle be observed and modelled by a specific
        change in the model. Thus, a complete CMCE- model of an experience E must be
        perfectly isomorphic with the experience: there must be a one-to-one
        correspondence between the empirically observed physical phenomenon (CMCE) and the
        subjective experience E (Fingelkurts & Fingelkurts, 2004; Revonsuo, 2000). This
        means that an empirical theory of consciousness, if sufficiently detailed, can
        provide a complete scientific description of an experience and its phenomenology.
        To do this, the theory must be able to define which empirically observed physical
        processes correspond to different contents of experiences, and how these contents
        combine to form complex experiences. For instance, from the perspective of
        conscious vision, the requirement of isomorphy means that the model must predict
        the phenomenology of vision from the egocentric perspective, not from the
        retinotopically-centered frame of reference (Land, 2012). According to the
        integrated information theory of consciousness (Oizumi et al., 2014) the structure
        of recurrent networks (“qualia space”, to use IIT’s terminology) defines
        phenomenology. According to Naturalistic Monism, such models are descriptions of
        the concrete physical phenomenon that is consciousness. The reader may, at this
        point, insist that isomorphic descriptions of CMCs would not explain the
        “qualitative feelings” of experiences, or answer why certain neuronal activity
        feel like something, and hence the description would not be an explanation of
        phenomenology. Such counter-arguments are ill-posed, because they conflate
        concrete phenomena with their scientific models. For instance, what blue feels
        like for S is the happening of CMCblue in S, a concrete process that can be
        perfectly modelled scientifically—but just modelled. Grasping the CMCblue-model
        affords knowledge of how an experience of blue can be scientifically described,
        whereas what blue feels like is just the happening of the concrete phenomenon,
        which is distinct from the scientific model. No description alone can ever cause
        the happening of the concrete phenomenon it describes, but this does not imply
        that it could not perfectly describe the phenomenon and its happening in a
        subject. Science can model the constituents, etiology, etc. of blue experiences,
        and there is no further question of why blue (or the corresponding neural process)
        feels like blue. Feeling like blue is part of the nature of blue experiences,
        determined by their constituent processes, just like having a certain molar mass
        is part of the nature of helium. Science can model what blue feels like and how
        that feel is determined by lower-level processes, just like it can model the molar
        mass of helium and its constituent processes.

        <hss>Etiology</hss>

        In trying to explain what must happen in the brain so that, for instance, visual
        information crosses the threshold to consciousness, neuroscience examines the
        causal chain of events that lead to it (Dehaene & Changeux, 2011; Railo, Koivisto,
        & Revonsuo, 2011). In other words, they describe the etiology of conscious vision.
        The aim is to disentangle the CMC from other processes that correlate with
        conscious perception, but do not constitute it (e.g. Aru, Bachmann, Singer, &
        Melloni, 2012). For example, neural processes that precede the presentation of a
        stimulus help to predict whether or not the stimulus is consciously perceived – in
        other words, prestimulus activity correlates with the subsequent conscious
        perception (e.g. Iemi, Chaumon, Crouzet, & Busch, 2016). However, these
        prestimulus correlates of conscious vision are obviously “just correlates”, and
        the neural processes that constitute the conscious perception of the stimulus
        happen later. One of the challenges of empirical science is to characterize this
        etiological chain of events that leads to conscious vision, that is, the formation
        of the CMC that corresponds to experience of that stimulus. In addition to
        explaining the immediately preceding causes that lead to consciousness, science
        can describe longer time scales such as individual development, or evolution (see
        Revonsuo, 2006). A theory of consciousness should explain how consciousness has
        evolved from earlier products of evolution. For example, the phenomenology of
        visual perception could be accounted in empirical terms by characterizing how
        frequently different stimulus combinations have been encountered during the
        evolution (Purves, Wojtach, & Lotto, 2011). Similarly, pain can be considered as a
        complex biological adaptation that has helped organisms to avoid potentially
        damaging stimuli, and whose bio-chemical basis could possibly be traced back to
        single celled organisms (Bray, 2009). According to Naturalistic Monism, this does
        not mean that only the functional aspects of pain (or visual perception) would be
        products of evolution, but also that the different types of subjective unpleasant
        sensations we call “pain” (or visual phenomenology) are products of evolution.
        This view is built on the assumption that consciousness is not an epiphenomenon
        (cf. Jackson, 1982), but instead that it has power to influence other physical
        processes.

        <hss>Causal power</hss>

        The idea that experiences are something different from other physical phenomena is
        deep-rooted in philosophy and science. For instance, Edelman (2003), who builds an
        elegant theory of consciousness on a bio-physical foundation, argues that
        conscious states are “informational even if not causal” (p. 5523). This way,
        consciousness easily appears epiphenomenal, which is strongly at odds with our
        subjective experience as well as the empirical scientific assumption that human
        consciousness is a product of evolution, and plays a causal role in behavior.
        Naturalistic Monism ties together the phenomenal and functional aspects of
        consciousness. Because consciousness is a physical process, it can causally
        interact with other phenomena in the brain and drive the organism’s behavior. We
        propose that Naturalistic Monism may help to dismantle some stubborn conflicts
        about whether consciousness should primarily be described in functional or
        phenomenal terms (Block, 1995; Carter et al., 2018; Dehaene & Changeux, 2011).
        While it is an empirical question to find out whether specific cognitive functions
        (e.g. global access or error detection; Dehaene, Lau, & Kouider, 2017) are
        necessary for consciousness, our framework implies that experiences never take
        place in a causal void. An experience E (CMCE) always causally interacts with
        other processes in the brain, both conscious and non-conscious: it can cause, for
        instance, thoughts, emotions, bodily states, or actions, and interact with the
        outside world. One of the goals of empirical science of consciousness is to
        explain what gives conscious processes their power to potentially elicit fast and
        accurate actions, and flexible voluntary behavior6. Theories such as the Global
        Workspace theory are explicitly built around this foundation (Dehaene & Changeux,
        2011). According to Naturalistic Monism, such “functional explanations” can
        provide key insights into the phenomenal qualities of experiences as well (cf. the
        example about pain, in previous subsection).

<h>PHILOSOPHICAL IMPLICATIONS</h>
--------------------------

In this section, our aim is to briefly address the main philosophical implications of
Naturalistic Monism. The discussion is not intended as exhaustive, but rather as pointing
towards future research.

<hs>  Relativity of “subjective” and “objective”</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Naturalistic Monism implies that terms like “subjective”/”objective”, or “first-
person”/”third-person” are relative. When a subject S1 perceives an apple, the apple is
objective and third-person observable. The experience of the apple in S1 is subjective or
first-person observable for S1, but because it is a natural phenomenon, it is third-person
observable for a neuroscientist (S2). The neuroscientist’s observations and theoretical
models of the neural mechanisms of S1’s apple-experience, in turn, are phenomena in the
scientist’s mind/brain and (at least partly7) subjective or first-person observable for
the neuroscientist—the scientist is aware of grasping the model. The scientist’s model is
in principle objectively or third-person observable for a “metaneuroscientist” (S3), and
so on ad infinitum. In short: any subject’s experience is another subject’s external
phenomenon. Husserl’s notions of phenomenological and natural attitude can be used to
illustrate this relativity. In everyday life, we typically endorse the natural attitude,
focusing on external objects instead of our experiences of them. When I perceive an apple,
my consciousness is directed at the apple and I am not necessarily aware of the details of
my experience per se, such as what the greenness of the apple feels like. In Hurssel’s
terminology this is called the natural attitude. In contrast, when I endorse the
phenomenological attitude, I focus on my apple-experience as an experience. A scientist,
in turn, is concerned with the external phenomena they study and thus automatically
endorse the natural instead of the phenomenological attitude—they rarely focus on the
nature of their scientific models as conscious phenomena in their minds. However, even the
conceptual aspects of a scientific model—e.g. that the helium atom has two protons—are
conscious phenomena in the mind of the scientist when they grasp the model. As such, the
scientist can endorse the phenomenological attitude towards them and consider them as
experiences. This illustrates that we can never escape our own point of view: even a
scientific model is only a representation in the scientist’s mind. However, even though a
scientist S1 cannot themselves “step outside” their model, an external observer S2 can: in
principle, such a “meta-observer” could investigate the relationship between an object X
and the scientist S1’s mental model of it from an external perspective, treating both the
object and the model as external phenomena (“noumena” in Husserl’s terms). But the meta-
observer S2 would then be confined to their own perspective (and so on for any further
meta-observer).

<hs>  Philosophies of science and consciousness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If we consider consciousness as a concrete physical phenomenon, then the question about
the relationship between an experience and its mature scientific model comes at least
partly down to which philosophy of science we endorse (in addition to the details of the
model itself). A scientific model is always distinct from the concrete phenomenon it
models, and there is always a gap between the two in this sense. How wide we take the gap
to be depends on whether we endorse realism or antirealism about science. Roughly,
according to realism, mature scientific theories can be true, and truthfully describe the
nature of the world (Psillos, 1999). Thus, the epistemic gap between a phenomenon and its
mature scientific model is non-existent or narrow.8 According to antirealism, on the other
hand, we always have to remain agnostic about the truth of scientific models. For
instance, according to constructive empiricism (van Fraassen, 1980), scientific theories
can be considered as empirically adequate if they are isomorphic with observations, but we
can never say whether they are literally true. We could say that, on this view, there is
always an indefinitely wide epistemic gap between a phenomenon and its model, or that it
makes no sense to speak of such a gap. Scientific realism implies that if we said that our
experiences involve purely qualitative aspects that cannot be modelled structural-
relationally, we would be mistaken. According to scientific realism, all natural phenomena
can be truthfully modelled structural-relationally. On this view, what we call a
“qualitative feeling” can be truthfully modelled as a structural-relational process.
Importantly, this approach does not deny that experiences feel like something; it only
holds that the feel can be modeled purely structural-relationally. If we characterized the
feel as something purely qualitative, we would be mistaken—not about the feel itself, but
instead about how to describe it. Importantly, terms like “qualitative” or “feeling” are
only concepts which refer to certain concrete processes that happen in us. The processes
are the way they are, no matter how we refer to them. Scientific realists would hold that
experiences can be truthfully modelled completely in structural-relational terms, but this
does not, and cannot, amount to eliminating any aspects of the experiences themselves. It
may be difficult to see how, say, the redness of red could be a structural-relational
process, given that introspection about redness does not reveal that it has such nature.
However, from the fact that a model M applies to an experience E, it does not follow that
a subject experiencing E would introspectively see that M applies to it (cf. Dennet,
1991). If we endorse antirealism, such as van Fraassen’s empiricism, we can only say
whether a neuroscientific theory of consciousness is compatible with observations, not
whether it “captures the nature” of what it models. It could be said that, for the
antirealist, there is always an indefinitely wide epistemic gap between any concrete
phenomenon and its scientific model, and that experiences are not different in this
respect. It is noteworthy that Naturalistic Monism is not committed to either realism or
antirealism; this is an independent question. Naturalistic Monism minimally implies that
there is always distinctness between a phenomenon and its model, but whether we take there
to be an epistemic gap may depend on which philosophy of science we endorse. Detailed
discussion of how consciousness is related to different philosophies of science is beyond
the scope of this paper. The main point is that if we consider experiences as being of the
same (ontological) type as any other physical phenomenon, then the question about the
relationship between an experience and its scientific model boils down to the general
question about the relationship between any phenomenon and its model.

<hs>  Panpsychism</hs>
  ~~~~~~~~~~~

According to Naturalistic Monism, experiences are concrete physical phenomena that are
based on lower-level physical processes, and thereby ontologically continuous with them.
Does it follow that all physical phenomena are of an “experiential nature”, because they
are of the same ontological type as experiences (cf. the black boxes in Fig. 1)? In our
view, this is not a necessary conclusion. An experience E can be scientifically modelled
as CMCE, a system-level phenomenon in the brain that is based on the activity of
individual neurons. In this sense, consciousness is continuous with other physical
phenomena, all the way down to subatomic particles. However, insofar as individual neurons
(not to speak of quarks) alone do not realize the CMCE-process, they are not conscious, at
least in the same sense as we are. On this line of argumentation, it is possible for
consciousness to emerge from something that is not conscious, and it is the task of
empirical theories of consciousness to describe exactly how this happens (but see
Strawson, 2008b). On the other hand, we have no non-empirical or non-model-mediated access
to the nature of other physical phenomena besides our experiences. We can extrapolate from
our own case and infer that at least cats and cows are likely to have similar experiences
as us, given that they show similar behaviors and have similar neuroanatomy. It is more
difficult to say anything about the possible inner lives of insects, amoebas, or quarks.
This difficulty, however, stems from the limits of science, not from consciousness being a
special type of phenomenon.

<hs>  Zombies, Mary, and the “hard problem”</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Philosophical zombies (Chalmers, 1996) are creatures that appear just like normal human
beings in every functional and observable respect, but for whom “the lights are out”: it
does not feel like anything to be a zombie. When we imagine zombie-pain, we imagine
something that would cause pain-observations and fit our scientific model of pain, but
which would not be real pain. If such fake-pains are conceivable, then arguably we could
conceive of any fake natural phenomena. For instance, we can imagine that we live in a
massive computer simulation, where our observations of electrons are not caused by real
electrons, but instead by computer algorithms. If such imaginings are possible at all,
what they teach us is that our scientific models and observations are always distinct from
the concrete phenomena that underlie them. It does not tell us anything about the nature
of experiences or electrons, except for that they are concrete phenomena and independent
of their scientific models and observations. The same reasoning can be applied to the Mary
case, a neuroscientist who has never experienced colors (Jackson, 1986). Mary knows
everything about the visual color system in the brain, but she does not know what it is
like to see red. The conclusion that the thought experiment is supposed to demonstrate is
that there are some facts about experiences that cannot be described by scientific models.
But the conclusion is false: Mary does know what it is like to see red, but only in terms
of a scientific model. What it is like for S to see red is the happening of a red
experience in S. Because science can model such processes, it can thereby model what it is
like to see red. When Mary sees red for the first time, the concrete phenomenon whose
model she already knew happens in her. What the Mary case teaches us is that a concrete
phenomenon can be quite different from what a scientific model says it is. But this does
not imply that there would be some properties (“qualia”) that cannot be scientifically
modelled, it only shows that a concrete phenomenon is distinct from its model.

<h>CONCLUSIONS</h>
-----------

We have argued that once we clearly distinguish between concrete phenomena and their
scientific models, the epistemic gap – why our experiences appear so different from neural
activity – dissolves into distinctness between the model and the phenomenon. From the
perspective of Naturalistic Monism, science can observe and model consciousness, not just
its correlates. We hope that our proposal helps to establish a solid ground for the
empirical science of consciousness, as it collapses the problem of consciousness into a
standard problem of science. Scientific explanation never affords us knowledge of the
nature of phenomena in themselves. However, if we accept that our subjective experiences
are concrete physical phenomena, then science can provide a complete and exhaustive model
of experiences, including what they “feel like”.


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<ART>Considering self or others across two cultural contexts: How children's resource allocation is affected by self-construal manipulations
================================================================================

Authors: Sandra Weltzien, Lauren Marsh, Patricia Kanngiesser, Bobby Stuijfzand, Bruce Hood
DOI: 10.1016/j.jecp.2019.04.002
Year: 2019  |  Pages: 139-157
ASJC codes: 3204, 3205
Keywords: Generosity, Priming, Self-construal, Self-focus, Sharing development, Societal differences

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Most humans share to some degree. Yet, from middle childhood, sharing behavior varies substantially across societies. Here, for the first time, we explored the effect of self-construal manipulation on sharing decisions in 7- and 8-year-old children from two distinct societies: urban India and urban United Kingdom. Children participated in one of three conditions that focused attention on independence, interdependence, or a control. Sharing was then assessed across three resource allocation games. A focus on independence resulted in reduced generosity in both societies. However, an intriguing societal difference emerged following a focus on interdependence, where only Indian children from traditional extended families displayed greater generosity in one of the resource allocation games. Thus, a focus on independence can move children from diverse societies toward selfishness with relative ease, but a focus on interdependence is very limited in its effectiveness to promote generosity.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Sharing of resources is vital and common in all human societies (Henrich et al., 2010).
Yet, young children across societies tend to maximize their own outcomes and only from
middle childhood begin to conform to the sharing norms of their respective societies
(e.g., Cowell et al., 2017; House et al., 2013; Rochat et al., 2009). Children’s sharing
behavior is influenced by social information such as explicit normative instructions
(House, 2018; McAuliffe, Raihani, & Dunham, 2017) and demonstrations by adult models
(Blake, Corbit, Callaghan, & Warneken, 2016; Over & Carpenter, 2013). Whereas children
from different societies behave more selfishly if selfish behavior is modeled by an adult,
Western children appear to be less flexible in adopting more generous behavior (Blake et
al., 2016; Weltzien, Marsh, & Hood, 2018). For example, children in both urban United
States and rural India reduced their giving when stingy behavior was modeled, but only
Indian children increased their giving when generous behavior was demonstrated (Blake et
al., 2016). Children’s abilities to copy others and follow instructions have been widely
documented (Blake et al., 2016; House, 2018; McAuliffe et al., 2017; Over & Carpenter,
2013). What remains puzzling is why children from Western societies respond less to social
influences aimed to increase generosity compared with children from other populations. An
emphasis on child autonomy and independence in Western middle-class families (Blake et
al., 2016; Grossmann & Na, 2014; Keller, Borke, Chaudhary, Lamm, & Kleis, 2010) may make
children more reluctant to go against their self-interest. In contrast, children from
societies that emphasize child obedience and interdependence (Clegg & Legare, 2016; Keller
et al., 2010) may respond more readily to social influences even when they contravene
children’s self-interest. Recent studies applying priming of self-construals in children
offer tentative support for these claims. Experimentally manipulated self-focus reduced
British children’s willingness to relinquish personal possessions (Hood, Weltzien, Marsh,
& Kanngiesser, 2016) and their sharing and helping behavior (Weltzien et al., 2018),
whereas focusing on others or close friends was ineffectual. These findings may reflect a
relative strength of independent versus interdependent self-construals in British
children. Yet, cross-cultural evidence from populations with predominantly interdependent
self-construals is lacking. The United Kingdom and India are two countries that have
traditionally differed along the dimension of individualism versus collectivism (Santos,
Varnum, & Grossmann, 2017; Verma, 1999). The consensus across the cross-cultural
literature is that Western middle-class families socialize their children toward autonomy,
individuality, and self-sufficiency (Greenfield, Keller, Fuligni, & Maynard, 2003;
Kärtner, Crafa, Chaudhary, & Keller, 2016; Keller et al., 2010). Indian middle-class
families, on the other hand, emphasize interpersonal responsibilities, interdependence,
and shared experiences to a larger degree (Kärtner et al., 2016; Keller et al., 2010;
Miller, Bersoff, & Harwood, 1990). These differences also manifest in the extent to which
the self is defined in relation to others. Arguably, in individualistic societies, people
have more independent self-construals, defined largely in terms of internal attributes
such as attitudes and abilities (Grossmann & Na, 2014; Markus & Kitayama, 1991).
Conversely, in collectivistic societies, people have more interdependent self-construals,
mainly defined in terms of group membership and close relationships (Markus & Kitayama,
1991). Although independent and interdependent self-construals coexist in all individuals,
their prominence and accessibility vary due to different cultural conventions and
socialization practices (Singelis, 1994). Across societies, middle childhood has been
identified as an important phase in prosocial development where children begin to conform
to societal norms (Cowell et al., 2017; House et al., 2013; Rochat et al., 2009).
Therefore, the current study investigated the influence of independence and
interdependence priming on the sharing behavior of 7- and 8-year-old children from urban
locations in the United Kingdom and India. In the current study, children took part in one
of three self-construal manipulations in the form of semistructured interviews:
independence focus, interdependence focus, or a control condition. Sharing was
subsequently assessed in a task that is commonly used to explore sharing behavior in the
current age group (e.g., Fehr, Bernhard, & Rockenbach, 2008; House et al., 2013; Sheskin,
Bloom, & Wynn, 2014). Each child completed four repetitions of three different sharing
games. In each game, the child needed to choose between two mutually exclusive options
that distributed stickers between the child and an anonymous recipient. We used a forced-
choice sharing procedure with preset ratios to reduce the problem of individual biases in
decision making (Green & Swets, 1966). Moreover, retaining the anonymity of the recipient
avoided possible confounds due to reputation management, reciprocity, and/or differing
relationships between the participant and the recipient. In the “other-advantage” game,
the choice was between an equal split and an unequal split favoring the recipient: low
stake (1:1 vs. 1:2) or high stake (2:2 vs. 2:4). In the “self-advantage” game, the choice
was between an equal split and an unequal split favoring the participant: low stake (1:1
vs. 2:0) or high stake (2:2 vs. 4:0). The other-advantage and self-advantage games have
been used to measure disadvantageous inequity aversion and advantageous inequity aversion,
respectively (Blake et al., 2015; Fehr et al., 2008; Sheskin et al., 2014). In addition,
we introduced a new game category, termed “that’s life,” where no fair option was
available and self-advantage was pitted directly against other-advantage: low stake (1:0
vs. 1:2) or high stake (2:0 vs. 2:4). Specifically, a child could either maximize or
minimize the other child’s payoff without incurring a cost to himself or herself. This
dilemma has not previously been studied but presents an ecologically valid predicament
given that inequality in real life is often difficult to avoid. We predicted that both
British and Indian children would be less generous in the independence condition (as
compared with the control condition) in all three games (e.g., Blake et al., 2016; Hood et
al., 2016; Weltzien et al., 2018). In other words, we expected an increase in 1:1 (2:2)
choices in the other-advantage game, an increase in 2:0 (4:0) choices in the self-
advantage game, and an increase in 1:0 (2:0) choices in the that’s life game. Moreover,
based on the differences in self-construal orientation that exist between these two
societies, we predicted that Indian children, but not British children, would be more
generous in the interdependence condition (as compared with the control condition) in all
three games (Blake et al., 2016). That is, we predicted an increase in 1:2 (2:4) choices
in the other-advantage game, an increase in 1:1 (2:2) choices in the self-advantage game,
and an increase in 1:2 (2:4) choices in the that’s life game.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The Indian sample consisted of 90 7- and 8-year-old children enrolled in an English-
speaking middle- to upper-class private school in Pune, India (Mage = 97.29 months, SD =
3.86, range = 91–105; 51 boys). The British sample consisted of 90 7- and 8-year-old
children enrolled in middle- to upper-class schools in Bristol, United Kingdom (Mage =
92.68 months, SD = 6.46, range = 94–107; 40 boys). The sample size was specified a priori
in accordance with previous research that used a similar design and procedure (Weltzien et
al., 2018). An additional 12 Indian children and 15 British children were tested but
excluded from the analyses because they failed to pass one or more of the control trials.
All Indian participants had a high level of English language proficiency. Testing in both
societies, therefore, was conducted in English by the first and second authors. All
children were tested individually in suitable locations at their respective schools.
Informed consent was obtained in written form from the parents of all children who
participated in this study. All children provided verbal agreement that they wished to
partake in the research.

        <hss>Interview procedure</hss>

        Each child took part in one of three interview conditions: an independence
        interview, an interdependence interview, or a control interview. Questions asked
        during independence and interdependence interviews were constructed and adapted
        for children based on the list of independent and interdependent self-construal
        primes developed by Kühnen and Hannover (2000). During the independence interview,
        the experimenter asked a series of questions about the child himself or herself,
        aimed at focusing attention on the child’s uniqueness and individuality (e.g.,
        “What makes you special?” and “How are you different from other people?”). The
        experimenter also used second-person singular pronouns (e.g., you, your, yours,
        [child’s name]) whenever apt in order to further steer the child’s attention
        toward his or her self. During the interdependence interview, the experimenter
        asked questions about the child’s relationships with family and friends to focus
        attention on relatedness and closeness to others (e.g., “Is there anyone in your
        life that you feel close to?” and “Why is it important to have a family?”). In
        addition, the experimenter used second-person plural pronouns (e.g., you, your
        [together]) whenever apt in order to further steer the child’s attention toward
        relationships with and dependence on others. In the neutral control interview, the
        experimenter asked questions about animals and was careful to avoid the use of
        personal pronouns (see Appendix A for full interview scripts).

        <hss>Distribution game</hss>

        The experimental design was adapted from previous studies (Fehr et al., 2008;
        House et al., 2013; Sheskin et al., 2014). Across 12 trials, children decided
        between two mutually exclusive options for distributing tokens to the self and to
        “another child” (recipient). First, two opaque boxes were presented: one for the
        participant and one for “another child from a different school” (recipient). Next,
        the experimenter explained that tokens would be used in the task and that at the
        end of the task the tokens would be exchanged for stickers. The child was then
        introduced to two identical boards. On each board, there were two circles with
        arrows. The boards were placed so that one arrow pointed toward the child’s box,
        illustrating that the tokens in that circle would go to the child, whereas the
        other arrow pointed to the recipient’s box, illustrating that the tokens in that
        circle would go to the recipient (see Fig. B1, top and bottom, in Appendix B).

        <hss>Training</hss>

        Each child was given two training trials. The first training trial presented the
        child with a 1:1 versus 2:2 decision. Thus, one board delivered only one coin to
        the participant and one coin to the recipient, whereas the second board delivered
        two coins to each of them. This trial functioned as a control and assessed how
        often the child would choose the highest payoff when both options provided equal
        outcomes for both the participant and the recipient. The second training trial
        presented the child with a 1:0 versus 2:0 decision and assessed how often the
        child would choose the highest self-benefit. The two training trials were designed
        to introduce children to two important features of the game, namely that payoffs
        are influenced by the child’s decision and the recipient does not always need to
        obtain payoffs. Additional control questions ensured that all children had fully
        understood the training trials (see Appendix C for full testing script).

        <hss>Test trials</hss>

        The next 12 test trials were split into three games with two identical low-stake
        trials and two identical high-stake trials for each game: Other-advantage game
        (1:1 vs. 1:2 or 2:2 vs. 2:4): This game explored children’s propensity to choose a
        fair distribution over a distribution that provides a benefit to the recipient at
        no cost to the self. Self-advantage game (1:1 vs. 2:0 or 2:2 vs. 4:0): This game
        explored children’s propensity to choose a fair distribution at a cost to the
        self. That’s life game (1:0 vs. 1:2 or 2:0 vs. 2:4): This game explored whether
        children would opt to maximize or minimize the recipient’s payoff when there was
        no difference to the child’s own payoff. The 12 test trials were divided into two
        blocks that contained two repetitions of each game. Within each block, three low-
        stake trials were followed by three high-stake trials presented in a random order.
        After the first block, the control trial (1:1 vs. 2:2) was repeated to ensure that
        the child was still paying attention to the task (see Table D1 in Appendix D). The
        entire procedure lasted approximately 20 min per child (interview: approximately 4
        min; distribution game: approximately 15 min).

<hs>  Data coding and statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Time spent on the interviews did not differ significantly across societies or interview
conditions (see Appendix E and Table E2 for analysis and summary statistics). Therefore,
this factor was not considered further. All sessions were videotaped, and children’s
behavior was coded live and from videotape.

        <hss>Sharing data</hss>

        Statistical analyses of sharing behavior were run in R Version 3.0.2 (R
        Development Core Team, 2013), using the lme4 package (Bates, Maechler, Bolker, &
        Walker, 2013) and the lsmeans package (Lenth, 2016). Because there were multiple
        trials per participant, observations could not be considered independent of each
        other. To account for this, the data were analyzed using generalized linear mixed
        models (multilevel logistic regressions), permitting the inclusion of random
        effects to model the nested structure of the data (Baayen, 2008; Bates, Maechler,
        Bolker, & Walker, 2013). Data from the three games were analyzed separately. In
        all models, sharing decision was entered as a binary response variable (other-
        advantage trials: fairness = 1, other-advantage = 0; self-advantage trials:
        fairness = 1, self-advantage = 0; that’s life trials: self-advantage = 1, other-
        advantage = 0). All full models included the predictor variables of interest
        (society and condition), their two-way interaction, and the control variables
        gender (male or female), stake (high or low), block (1 or 2), and age in months (Z
        transformed) as fixed effects. Reduced models were identical to the full models
        but without the interaction term. Null models included only control variables and
        random effects. Initially, likelihood ratio tests were used to explore to what
        extent including random effects to model between participant variation would
        significantly improve each of the model’s fit to the data. We compared three types
        of models: no random effects, only random intercepts, and random intercepts and
        random slopes for block and stake. For all three games, the inclusion of random
        intercepts significantly improved the model fit, whereas the inclusion of random
        slopes did not. Consequently, all analyses reported contain random intercepts but
        no random slopes. The following analytical procedure was carried out for each
        game. First, the fit of the full model was compared with the null model with a
        likelihood ratio test to determine whether the inclusion of the complete set of
        predictor variables (main effects and interaction) significantly improved model
        fit. Second, the fit of the full model was compared with that of the reduced
        model. Subsequent analyses were conducted on either the full or reduced model,
        conditional on whether inclusion of the two-way interaction significantly improved
        model fit (for all model comparisons, see Appendix F). To assess the significance
        for the remaining predictors in the model with the best fit to the data (either
        full or reduced model), likelihood ratio tests were used. Interpretation of
        predictors was done by examining model coefficients and, in the case of
        categorical predictors with more than two levels, by conducting pairwise
        comparisons using the lsmeans package. An exploratory analysis of the family
        structure data was also included for a subset of the data (self-advantage game,
        Indian sample; see Results for rationale). The procedure for this analysis was
        identical to the procedure described above. However, instead of including society
        as a predictor variable, this analysis included family structure (joint or
        nuclear).

        <hss>Interview data</hss>

        To explore children’s verbal responses to independence and interdependence
        questions, interviews were transcribed verbatim. From the British population, 4
        independence interviews could not be transcribed due to faulty video recordings.
        From the Indian population, 12 independence interviews and 9 interdependence
        interviews could not be transcribed due to poor audio quality. All remaining
        scripts were coded by the first author using two coding categories: self-
        references and social relationship references. The self-reference category
        included the words I, me, mine, myself, and my own. In addition, the word my was
        included when related to personal possessions (i.e., my car, my house) but not
        when related to personal relationships (i.e., my mum, my friend). The social
        relationship reference category included the words he, him, himself, she, her,
        herself, his, hers, we, us, our, ourselves, they, them, their, each other, dad,
        mum, sister, and brother as well as name(s) of friend(s). See Table G3 in Appendix
        G for mean self-references and social relationship references by condition and
        society. For reliability, a second coder, blind to the purpose and predictions of
        the study, coded 25% of the transcripts (balanced by gender, condition, and
        society). Agreement between the first and second coders was excellent (κ = .96).
        The responses from the control interview were not included in this analysis
        because the questions were specifically designed to steer children away from
        speaking about themselves or their social relationships. Indeed, the authors
        intended to exclude data from children who made such references in the control
        interview, although this was not necessary because no references to self or social
        relationships were made in this condition. To account for individual variability
        in the overall number of self-references and social relationship references used
        by children, a proportional self-reference score was calculated for each child.
        This was done by calculating the proportion of self-references from the total
        number of self-references and social relationship references. Self-reference
        scores were analyzed in SPSS using an analysis of covariance (ANCOVA) with
        condition (independence or interdependence) and society entered as between-
        participant factors and age in months entered as a covariate.

        <hss>Other-advantage game (1:1 vs. 1:2 or 2:2 vs. 2:4)</hss>

        Children predominantly selected the fair option (72.9%) over the generous option
        (27.1%). Model comparisons showed that the reduced model had the best fit to the
        data (see Table H4 in Appendix H for model outputs). This model revealed that
        sharing decisions were significantly predicted by society, χ2(1) = 29.64, p < .001
        (see Fig. 1). Irrespective of condition, British children were more likely to
        choose the fair (1:1 or 2:2) option (predicted probability = .90) compared with
        Indian children (predicted probability = .64), odds ratio = 4.85, 95% confidence
        interval (CI) = 2.86–9.03. In addition, sharing decisions were significantly
        predicted by condition, χ2(2) = 6.17, p = .046, although pairwise comparisons
        revealed no significant differences between the conditions after Tukey corrections
        for multiple comparisons (ps > .058). Sharing decisions were also significantly
        predicted by block, χ2(1) = 8.85, p = .003. Specifically, children were more
        likely to choose the generous (1:2 or 2:4) option in the first block (predicted
        probability = .26) compared with the last block (predicted probability = .16),
        odds ratio = 1.78, 95% CI = 1.23–2.59. This pattern is consistent with previous
        findings showing that repeated trials reduce generosity over time, although the
        reasons for this remain unknown (Kogut, 2012).

        <hss>Self-advantage game (1:1 vs. 2:0 or 2:2 vs. 4:0)</hss>

        Children predominantly selected the selfish option (75%) over the fair option
        (25%) in this game. The full model had the best fit to the data (see Table H5 in
        Appendix H for model outputs). First, the results revealed a significant
        interaction between society and condition, χ2(2) = 6.90, p = .031 (see Fig. 2).
        Pairwise comparisons (Tukey corrected) showed that British children were
        significantly more likely to choose the selfish (2:0 or 4:0) option in the
        independence condition (predicted probability = .99) than in the control condition
        (predicted probability = .82), odds ratio = 16.63, Z = 2.93, p = .038. Conversely,
        Indian children were significantly more likely to choose the fair (1:1 or 2:2)
        option in the interdependence condition (predicted probability = .39) than in the
        control condition (predicted probability = .03), odds ratio = 0.05, Z = −3.31, p =
        .012. In other words, British children were nudged toward selfishness after
        talking about their independence, whereas Indian children were nudged toward
        costly sharing after talking about their connectedness with others. Sharing
        decisions in the self-advantage game were also significantly predicted by age,
        χ2(1) = 5.88, p = .015, suggesting that older children were more likely to choose
        the fair (1:1 or 2:2) option compared with younger children, odds ratio = 1.99,
        95% CI = 1.13–4.14. Moreover, sharing decisions were predicted by block, χ2(1) =
        7.47, p = .006. Children chose the fair (1:1 or 2:2) option more often in the
        first block (predicted probability = .10) compared with the last block (predicted
        probability = .05), indicating that children in both societies gradually increased
        their selfishness over the course of the experiment, odds ratio = 0.50, 95% CI =
        0.28–0.82. Finally, sharing decisions were significantly predicted by stake, χ2(1)
        = 15.56, p < .001. Specifically, children chose the fair (1:1 or 2:2) option more
        often in low-stake trials (predicted probability = .12) than in high-stake trials
        (predicted probability = .05), odds ratio = 2.72, 95% CI = 1.67–5.16, suggesting
        that across societies children found it harder to resist a self-benefit when the
        payoffs were higher.

        <hss>That’s life game (1:0 vs. 1:2 or 2:0 vs. 2:4)</hss>

        Children predominantly chose the selfish option (61%) over the generous option
        (39%) in this game. The reduced model had the best model fit (see Table H6 in
        Appendix H for model outputs). In this game, there was no effect of society, χ2(1)
        = 2.55, p = .11. However, sharing decisions were significantly predicted by
        condition, χ2(2) = 23.11, p < .001 (see Fig. 3). Pairwise comparisons (Tukey
        corrected) showed that children were more likely to choose the selfish (1:0 or
        2:0) option in the independence condition (predicted probability = .83) than in
        the control condition (predicted probability = .59), odds ratio = 0.30, Z = −3.57,
        p = .001. Thus, activating children’s independent self-construals reduced
        generosity in both British and Indian children. There was no significant
        difference in sharing behavior between children in the control condition and
        children in the interdependence condition (predicted probability = .50). Sharing
        decisions were again predicted by block, χ2(2) = 21.49, p < .001. An examination
        of the model coefficients revealed that children were more likely to choose the
        generous (1:2 or 2:4) option in the first block (predicted probability = .44)
        compared with the last block (predicted probability = .25), odds ratio = 2.36, 95%
        CI = 1.62–3.60. Finally, sharing decisions were predicted by stake, χ2(1) = 10.28,
        p = .001, such that children chose the selfish (1:0 or 2:0) option more often in
        high-stake trials (predicted probability = .72) compared with low-stake trials
        (predicted probability = .59), odds ratio = 0.55, 95% CI = 0.39–1.25.

        Exploratory analyses of self-advantage game, Indian sample (1:1 vs. 2:0 or 2:2 vs. 4:0)

        Why did we find an effect of interdependence focus only in Indian children in the
        self-advantage game? One possibility that became apparent from the demographic
        data was that, unlike the British sample, many of the Indian children lived in
        joint (extended) families. Traditional Indian families typically harbor three or
        more generations, including members of the extended family. In such families,
        “collective responsibility” is highly valued, with the needs of the family
        superseding the needs of the individual (Chadda & Deb, 2013). Living in a large
        family unit also fosters the pooling of resources, with family members sharing
        everything from food to property (Chettiar, 2015). Self-construals begin to form
        during early childhood (Singelis, 1994). Children from joint families, as opposed
        to Western-style nuclear families, may have more salient interdependent self-
        construals and, thus, may be more susceptible to the interdependence manipulation.
        Of the current Indian participants, 54 children lived in joint families, whereas
        36 children lived in nuclear families. This allowed us to carry out an exploratory
        analysis to investigate whether family structure might influence Indian children’s
        sharing decisions in the three conditions in this game. The full model had the
        best fit to the data (see Table H7 in Appendix H for model outputs). There was a
        significant interaction between family structure and condition, χ2(2) = 9.69, p =
        .008 (see Fig. 4). Pairwise comparisons (Tukey corrected) revealed that in the
        interdependence condition Indian children from joint families were significantly
        more likely to choose the fair (1:1 or 2:2) option in the interdependence
        condition (predicted probability = .73) than in the control condition (predicted
        probability = .07), odds ratio = 37.55, Z = 4.07, p < .001. Conversely, Indian
        children living in nuclear families were significantly less likely to choose the
        fair (1:1 or 2:2) option (predicted probability = .13) than children living in
        joint families (predicted probability = .73) in the interdependence condition,
        odds ratio = 0.06, Z = −3.05, p = .027.

<h>DISCUSSION</h>
----------

Here, for the first time, we demonstrated that children from two societies with different
self-construal orientations varied in their sharing behavior following a focus on
independence or interdependence. In both societies, activating children’s independent
self-construals reduced their generosity in two games (other-advantage and that’s life),
where they could provide a benefit to recipients at no cost. This is consistent with
previous findings that children from diverse societies will readily adjust their behavior
toward selfishness following stingy modeling by adults (Blake et al., 2016). Moreover, the
current results extend previous evidence of reductions in trading, sharing, and helping
behavior following self-priming in British children (Hood et al., 2016; Weltzien et al.,
2018) to a different population. Interdependence priming had an effect on Indian children
in the self-advantage game (1:1 vs. 2:0 or 2:2 vs. 4:0) exclusively. In comparison with
the other two games, sharing in the self-advantage game came at a cost to participants.
Past work has shown that societal differences in sharing behavior are pronounced in costly
sharing contexts (House et al., 2013). Here, we expanded on this finding by demonstrating
societal differences in susceptibility to interdependence primes within these contexts.
Enhanced reactivity of Indian children to interdependence primes is likely attributable to
a relatively greater societal emphasis on interpersonal responsibilities (Kärtner et al.,
2016; Keller et al., 2010; Miller et al., 1990). Moreover, our exploratory analysis
revealed that the effect of interdependence primes in the Indian sample was qualified by
family structure. Specifically, Indian children living in traditional extended families
were significantly more likely to choose the fair option over the selfish option than
children living in Western-style nuclear families. This suggests that growing up in an
extended family may lead children to be more susceptible to interdependence primes. Over
the past few decades, the sociocultural milieu of India has been going through a rapid
change, with a gradual disintegration of the traditional extended family system and a
corresponding increase in nuclear families, particularly in urban areas (Singh, 2014).
This transformation has led to changes in family functions and values, with a growing
emphasis on privacy and independence (Singh, 2014). As a consequence, parents in nuclear
families may be more likely to instill individualistic values in their children. This
could explain why no effects of interdependence primes were found for Indian children from
nuclear families, who responded similarly to the British children. Our findings have
implications for cross-cultural researchers because they suggest that it is critical to
consider the appropriate level of analysis. Here, societal differences were apparent, but
a closer look at family structure within our Indian sample provided a more nuanced
picture. There are many other factors that could covary with family structure in India.
These include but are not limited to parental income, level of education, and degree of
foreign travel. Future work could be more informative not only by considering societal
differences but also by paying attention to family-level factors. This could include a
focus on measuring independent and interdependent beliefs at the family level. The results
also revealed some societal differences in sharing behavior irrespective of priming
condition. Specifically, in the other-advantage game (1:1 vs. 1:2 or 2:2 vs. 2:4), Indian
children were more likely than British children to benefit the recipient even though a
fair option was available. This finding contradicts previous research showing that
children from the United States and India display similar levels of generosity (Blake et
al., 2016) and are equally averse to receiving less than others (Blake et al., 2015).
Instead, the current results support evidence that children from more collectivistic
societies tend to share resources more generously than children from more individualistic
societies (e.g., Scharpf, Paulus, & Wörle, 2016; Stewart & McBride-Chang, 2000). Previous
studies using the self-advantage game have found an aversion to receiving more than others
(advantageous inequity aversion) from 7 or 8 years of age in children from Switzerland,
the United States, Canada, and Uganda (Blake et al., 2015; Fehr et al., 2008) but not in
children from rural India (Blake et al., 2015). We found, however, that neither British
nor Indian children showed such an aversion (control condition of self-advantage game).
These divergent findings may be due to methodological differences between studies. It is
well documented that the presence of a recipient or sharing with a known other influences
sharing behavior (e.g., Leimgruber, Shaw, Santos, & Olson, 2012; Martin & Olson, 2015;
Schäfer, Haun, & Tomasello, 2015). Whereas previous studies used either peer-to-peer
encounters or a photograph of in-group recipients (e.g., Blake et al., 2015; Fehr et al.,
2008), children in the current study shared with an unidentified child “from a different
school.” Virtually all cross-cultural sharing studies, including the current study, have
used tasks where sharing takes place in view of the experimenter (e.g., Blake et al.,
2015; House et al., 2013; Rochat et al., 2009; Schäfer et al., 2015). There is evidence
that both adults and children employ reputation-enhancing strategies and behave more
generously when others witness their sharing (Alpizar, Carlsson, & Johansson-Stenman,
2008; Haley & Fessler, 2005; Leimgruber et al., 2012). In addition, reputational concerns
may differ between societies (Callaghan & Corbit, 2018; Gächter & Herrmann, 2009). In the
current study, the experimenter’s presence may have influenced both sharing decisions in
general and the effects of the focus manipulations. For example, interdependence primes
may have triggered a stronger awareness of being observed in the Indian participants than
in the British participants. Future studies could investigate this possibility by using
the current paradigm and comparing sharing in a fully anonymous sharing task that also
controls for the presence of the experimenter. In conclusion, the current findings reveal
that subtle self-construal manipulations have striking effects on children’s sharing in
different societies. A focus on independence easily moved children in the United Kingdom
and India toward selfishness, but a focus on interdependence was very limited in its
effectiveness to promote generosity. Specifically, a focus on interdependence increased
generosity only in Indian children living in traditional joint families during a costly
sharing game. Our findings indicate the importance of considering other levels of analysis
beyond broad societal comparisons.


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<ART>Consistency of maternal cognitions and principles across the first five months following preterm and term deliveries
================================================================================

Authors: A. Winstanley, R. G. Sperotto, D. L. Putnick, S. Cherian, M. H. Bornstein, M. Gattis
DOI: 10.1016/j.infbeh.2014.09.005
Year: 2014  |  Pages: 760-771
ASJC codes: 3204
Keywords: Caregiving, Cognitions, Infancy, Parenting, Prematurity, Principles

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The aims of this study were to examine and compare the development of parenting cognitions and principles in mothers following preterm and term deliveries. Parenting cognitions about child development, including thinking that is restricted to single causes and single outcomes (categorical thinking) and thinking that takes into account multiple perspectives (perspectivist thinking), have been shown to relate to child outcomes. Parenting principles about using routines (structure) or infant cues (attunement) to guide daily caregiving have been shown to relate to caregiving practices. We investigated the continuity and stability of parenting cognitions and principles in the days following birth to 5 months postpartum for mothers of infants born term and preterm. All parenting cognitions were stable across time. Categorical thinking increased at a group level across time in mothers of preterm, but not term, infants. Perspectivist thinking increased at a group level for first-time mothers (regardless of birth status) and tended to be lower in mothers of preterm infants. Structure at birth did not predict later structure (and so was unstable) in mothers of preterm, but not term, infants and neither group changed in mean level across time. Attunement was consistent across time in both groups of mothers. These results indicate that prematurity has multiple, diverse effects on parenting beliefs, which may in turn influence maternal behavior and child outcomes.

--------------------------------------------------------------------------------


CONSISTENCY OF MATERNAL COGNITIONS AND PRINCIPLES ACROSS THE FIRST FIVE MONTHS FOLLOWING PRETERM AND TERM DELIVERIES
--------------------------------------------------------------------------------

A large literature documents the importance of parenting beliefs about infants and
caregiving (Bornstein, 2015; Bornstein et al., 2007; Dichtelmiller et al., 1992; Goodnow,
1988; Miller, 1988; Miller-Loncar, Landry, Smith, & Swank, 2000; Moorman & Pomerantz,
2008; Pomerantz & Dong, 2006). However, few studies have examined the parenting beliefs of
parents of preterm infants, despite preterm deliveries occurring in around 12–13% of live
births in the United States and around 5–9% in Europe and other developed countries
(Goldenberg, Culhane, Iams, & Romero, 2008). This gap in the literature is significant
because infants born prematurely may be at risk due to early non-optimal caregiving
environments (e.g., Clark, Woodward, Horwood, & Moor, 2008; Feldman & Eidelman, 2006;
Forcada-Guex, Pierrehumbert, Borghini, Moessinger, & Muller-Nix, 2006). The current study
compared two types of maternal beliefs–cognitions about child development and principles
of caregiving–in comparable mothers of term and preterm infants and did so across two time
points during infancy. Therefore, this study was able to examine both the nature, as well
as the effect, of prematurity on the developmental trajectories of parenting cognitions
and principles.

<hs>  Continuity and stability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

One aim of developmental research is to understand how constructs develop across time
(Bates & Novosad, 2006; Wohlwill, 1970). In this study, we focused on two approaches to
measure the development of parenting cognitions and principles: continuity and stability
(Bornstein, 2002). Continuity is defined as consistency in group mean level performance
across time. A continuous construct is one in which group means do not differ from one
time point to a later time point, whereas changes in mean group performance across time
would demonstrate that a construct is discontinuous. Individual differences have a
complementary focus on variation around the mean. Stability in individual variation is
defined as consistency in the relative rank or standing of individuals within a group
across time. A stable construct is one on which some individuals rank at relatively high
levels at one point in time and again display at relatively high levels at a later point
in time, whereas other individuals display lower levels at both times. An unstable
construct is one in which individuals do not maintain their rank order across time.
Studying the continuity and stability of variables provides both a descriptive and
explanatory account of development. Continuity and stability not only tell us about
individual differences but also about the developmental origins, nature, and future of
constructs (Bornstein & Putnick, 2012). Stability and continuity are mainstay concepts in
developmental science and represent statistically and theoretically independent spheres of
development (Bornstein & Bornstein, 2008). Developmental scientists are not only
interested in how constructs manifest themselves but also in group and individual
development across time and, therefore, in continuity and stability.

<hs>  Parenting cognitions and principles</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We chose to study the continuity and stability of both maternal cognitions and principles
because parenting is multidimensional, modular, and specific (Bornstein, 2002, 2006). That
is, different parental behaviors and beliefs serve different functions, have different
developmental trajectories, and have different effects on children, with different domains
not necessarily related. We selected the cognitions and principles described below based
on their documented relations with parenting behavior and practices as well as child
outcomes that may be particularly important for preterm infants (see Section 1.3). First,
we studied the complexity of mothers’ thinking about development. Specifically, we focused
on two levels of reasoning – categorical and perspectivist thinking – as well as an
additional summary variable that reflects the balance between these two levels –
complexity of thought (Sameroff & Feil, 1985). Perspectivist thinking reflects flexible
reasoning that involves multiple perspectives and takes into account reciprocal influences
and transactional perspectives on development, and is therefore more complex. Categorical
thinking reflects reasoning that attributes behavior to a single cause and views the child
as an extension of parents without individual needs and is therefore less complex. These
two levels of complexity of thought describe the broader context of how mothers conceive
of children and the parenting role (Miller-Loncar et al., 2000). A parent's ability to
think complexly has been shown to relate to both parental behavior and child outcomes.
Parents who think more complexly about child development show more sensitive and
responsive parenting behaviors (Landry, Garner, Swank, & Baldwin, 1996; Miller-Loncar et
al., 2000; Pratt, Hunsberger, Pancer, Roth, & Santolipo, 1993). The preterm and term
infants of these parents, in turn, show higher levels of social responsiveness during
childhood (Miller-Loncar et al., 2000). However, parents who rely on lower levels of
thinking, who have fewer conceptual resources and perspectives to draw on, tend to show a
more rigid and authoritarian behavioral style (Deković & Gerris, 1992). Second, we
measured parenting principles of caregiving, which are specific personal codes that guide
caregiving during infancy (Winstanley & Gattis, 2013) rather than the general level
parents can think about development (as described above). Caregiving principles reflect
how parents make decisions about infant care. Specifically, we focused on two principles:
structure and attunement. Structure reflects mothers’ support of schedules and routines to
guide their infants’ day-to-day lives. Attunement reflects mothers’ attention to and
reliance on their infants’ cues to guide daily caregiving. These two caregiving principles
are independent, and therefore some parents support attunement and oppose structure (or
vice versa), whereas others support or oppose both principles. Structure and attunement
are related to parenting practices. For example, attunement is positively related to bed-
sharing, breastfeeding, and holding in parents of infants under 18 months (Winstanley &
Gattis, 2013).

<hs>  Prematurity</hs>
  ~~~~~~~~~~~

There are several reasons to hypothesize that complexity of thought and caregiving
principles could be important to understanding the social environment of infants following
prematurity. First, the behaviors that have been documented in interactions between
mothers and their preterm infants are the same as those that are related to lower
perspectivist and higher categorical thinking. That is, mothers of preterm infants have
been described as more intrusive and controlling and less sensitive and responsive
(Feldman & Eidelman, 2006; Feldman & Eidelman, 2007; Forcada-Guex et al., 2006). The
increased intrusiveness and reduced sensitivity seen in mother-preterm infant interactions
could therefore reflect differences in maternal cognitions about development (such as,
higher levels of categorical thinking). One study did show that mothers of 4-year-olds
born preterm tended to score higher on categorical thinking (Pearl & Donahue, 1995).
However, we do not yet know how early these differences appear and how categorical and
perspectivist thinking develop. An additional reason to study complexity of thought and
caregiving principles following prematurity is that parenting beliefs could be
particularly meaningful for preterm infants’ development. For example, using preterm
infants’ cues and states (sleepiness, arousal, hunger) to guide caregiving is crucial to
ensure that such care is developmentally appropriate, as evidenced by the focus of many
NICU-based interventions on new parents learning to use infants’ cues about hunger,
distress, and sleepiness (Browne & Talmi, 2005; Graven & Browne, 2008; Kaaresen, Ronning,
Ulvund, & Dahl, 2006; Landry, Smith, Swank, & Guttentag, 2008). NICU-based interventions
have been developed on findings that parents who attend to the behavioral cues of their
preterm infants to provide supportive early interactions have infants, and later children,
with more positive outcomes (Bozzette, 2007; Landry, Smith, Miller-Loncar, & Swank, 1997).
Support of the use of infants’ cues in this way is a central focus in the caregiving
principle of attunement. In addition, the parenting practices of breastfeeding and holding
(in particular, skin-to-skin touch) are advocated when caring for preterm infants (e.g.,
Flacking, Ewald, & Wallin, 2011; Tessier et al., 1998), and breastfeeding and holding
practices are related to stronger support of attunement (Winstanley & Gattis, 2013).
Therefore, parents’ support of attunement (with or without structure) could be important
for positive infant outcomes following prematurity. Parenting cognitions and principles
have generally been found to be stable in samples of parents of term infants of middle-SES
European American background (Cote & Bornstein, 2003; Holden & Miller, 1999; Rubin &
Mills, 1992). However, less is known about the stability and continuity of maternal
complexity of thought and caregiving principles following preterm deliveries. Measuring
complexity of thought and caregiving principles at one time point provides a static
picture of how mothers approach and think about caregiving and their child. Looking at
just one time point is inadequate because complexity of thought and caregiving principles
are likely to change with time as early caregiving moves from the hospital to the home,
and as children develop. Very early caregiving of preterm infants often occurs in the
hospital, and during this time some parents report feelings that the medical staff are
more capable of caring for their preterm infant than they are (Cleveland, 2008; Goldberg &
DiVitto, 1983; Howson, Kinney, & Lawn, 2012). In addition, because preterm birth is often
unexpected, parents are suddenly forced, ill-prepared, into parenthood, and so they may
not have had ample opportunity to attend antenatal classes, read books about parenting and
child development, or develop principles about how to care for their infants (Goldberg &
DiVitto, 2002). It is therefore important to examine how complexity of thought and
caregiving principles change or remain consistent from the days following a premature
delivery into later infancy once caregiving routines have been established. As such,
prematurity offers the interesting opportunity to understand how parenting complexity of
thought and caregiving principles develop under different circumstances.

<hs>  Methodological issues</hs>
  ~~~~~~~~~~~~~~~~~~~~~

This study aimed to chart maternal beliefs following preterm birth, and so child
chronological age (calculated from date of birth) was used to schedule visits. This
decision was based on our plan to equate amounts of extrauterine experience across dyads
at both time points. By contrast, using corrected age (calculated from the due date) to
ensure equivalent biological maturity, mothers of preterm and term infants would
necessarily differ in the quantity of postnatal and dyadic experience. Corrected age is
problematic when studying social development and, in particular, the effects of preterm
birth on early parent-infant interactions (Brachfeld, Goldberg, & Sloman, 1980; Wilcox,
Weinberg, & Basso, 2011). When studying parenting following premature delivery, it is also
imperative to distinguish between prematurity itself and the other factors associated with
prematurity (Anderson & Doyle, 2008). For example, preterm birth occurs more often among
mothers of low socioeconomic status, who are under 15 years of age, or who have had many
pregnancies close together in time (Behrman & Butler, 2006). These demographic factors,
without the consideration of premature deliveries, may be related to maternal cognitions
and principles. Therefore, differences in beliefs between mothers of preterm and term
infants may be ascribable to reasons other than the birth status of their infant. For
example, modest relations between complexity of thought and maternal education have been
reported (Gutierrez & Sameroff, 1990; Pratt et al., 1993), and lower educational
attainment is a risk factor for premature delivery (Behrman & Butler, 2006). In addition,
biological risk and neonatal experience of infants (for example, 5-minute Apgar score or
days on ventilation) can affect outcomes for children and their social interactions
(Aylward, 2002; Hintz et al., 2005; Landry et al., 1997; Vohr et al., 2000). Confounding
variables must therefore be carefully explored (Aylward, 2002). To isolate the impact of
prematurity on maternal complexity of thought and caregiving principles, we examined
multiple demographic and medical covariates for the developmental trajectories of
complexity of thought and caregiving principles following preterm and term deliveries.

<hs>  This study</hs>
  ~~~~~~~~~~

This study examined how maternal complexity of thought and caregiving principles develop
from the days following a premature or term delivery to a time when the parenting role is
more established, 5 months later. Therefore, we assessed the continuity and stability of
complexity of thought and caregiving principles in mothers of preterm vs. term infants.
Our first aim was to examine whether the continuity and stability of maternal complexity
of thought and caregiving principles differed by birth status when measured at birth and
again 5 months later. We chose to schedule the follow-up data collection at 5 months to
ensure parents had become established in the parenting role and infants were settled (St
James-Roberts et al., 2006). We expected to see differences in the developmental
trajectories of preterm and term mothers’ complexity of thought and caregiving principles
from birth to 5 months. Such results would demonstrate that the dynamics of complexity of
thought and caregiving principles look different for mothers of preterm and term infants.
Our second aim was to examine potential predictors of any observed change in complexity of
thought and caregiving principles. To do this, we determined whether medical and
demographic factors accounted for any changes observed. Few studies have systematically
examined basic developmental properties of maternal complexity of thought and caregiving
principles following premature deliveries. These assessments will increase our
understanding of the development of maternal complexity of thought and caregiving
principles in general and specifically in response to premature deliveries. Furthermore,
this study examined whether prematurity had uniform or differentiated effects on
complexity of thought and caregiving principles.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total sample of 105 mothers completed questionnaires within the first month from
delivery and 5 months later as part of a study about mothers’ and their preterm (n = 41)
or term (n = 64) infants’ development. Parents of infants born between 30 and 42 weeks
gestational age were recruited. Mothers were divided into two groups by the birth status
of their infant based on infant's gestational age; infants below 37 completed weeks of
gestation were in the preterm sample (up to and including 36 weeks and 6 days; Howson et
al., 2012) and those 37 weeks and above were in the term sample. The majority of
participants were recruited during the hospitalization period following delivery through
the Department of Child Health at University Hospital Wales (UHW, n = 90), with the
remaining 15 parents recruited through the Cardiff city registry office and other
community links, such as the National Childbirth Trust (recruited either soon after
delivery or prenatally but completed the questionnaires soon after delivery). An
additional 3 dyads were excluded due to a history of maternal depression or placement on
the child-in-need register by local authorities to monitor the child due to concerns about
the social environment of the child—for example, exposure to domestic abuse. Families were
not approached if their infants had serious medical conditions beyond prematurity alone or
congenital abnormalities that could affect growth and development, including requiring
surgical intervention during hospitalization. Additionally, multiple births and parents
under 16 years old were excluded. Suitable infants were identified as fitting inclusion
and exclusion criteria through discussions with medical staff (midwife, nurse, or doctor)
responsible for their care. At birth, 148 mothers completed questionnaires. Attrition
between birth and 5 months was 29% resulting in the final sample of 105 dyads at 5 months.
The majority of parents who did not participate were not contactable at 5 months (53%);
others had difficult life circumstances (27%), their infant had developed health problems
(10%), or no longer wished to participate (10%). Table 1 compares health and demographic
information about participating mothers and their preterm or term infants. The preterm and
term samples did not differ on any of the demographic variables (infant birth order,
maternal age, ethnicity, marital status, maternal education, and family income) or on
5-min Apgar scores. The samples naturally differed on medical status—preterm infants were
born at younger gestational age and lower birthweight and spent more days on ventilation
and in the hospital after birth. These variables were all checked as potential covariates
and predictors of change in complexity of thought and caregiving principles.

<hs>  Procedures</hs>
  ~~~~~~~~~~

All study procedures were reviewed by the Cardiff University School of Psychology's
research ethics committee, the National Health Service's Research & Development, and Local
Research Ethics Committee. Mothers consented to participate soon after delivering their
baby at which time they completed the Baby Care Questionnaire (BCQ; Winstanley & Gattis,
2013) and Concepts of Development Questionnaire (CODQ; Sameroff & Feil, 1985) for the
first time. Mothers completed these two questionnaires again 5 months later. Health and
demographic information was collected from a combination of a self-report measure
completed by the mother and inspection of medical records by research assistants. Five-
month study visits were scheduled based on postnatal chronological age with a window of
±15 days. Gifts were given to infants and parents for participation (worth approximately
USD $10).

        <hss>The Baby Care Questionnaire (BCQ)</hss>

        The BCQ (Winstanley & Gattis, 2013) asks parents to rate 30 statements about
        caregiving on a 4-point Likert scale ranging from strongly disagree (1) to
        strongly agree (4). The BCQ contains 2 subscales—structure and attunement.
        Subscale scores were calculated by averaging across relevant items (17 items for
        structure and 13 items for attunement). Structure represents parent support of
        regularity and routines in their infant's daily life. For example, It is important
        to introduce a sleeping schedule as early as possible. Structure showed adequate
        internal consistency at birth (preterm: α = 0.81; term: α = 0.87) and 5 months
        (preterm: α = 0.79; term: α = 0.84). Attunement represents parent trust and
        attention to their infant's cues and support of close physical contact. For
        example, Responding quickly to a crying baby leads to less crying in the long run.
        Three items for the attunement subscale had poor distributions and did not relate
        with overall attunement or other items making up the attunement subscale and so
        were not used in calculating the average attunement score. The resulting 10-item
        attunement scale showed adequate internal consistency at birth (preterm: α = 0.60;
        term: α = 0.75) and 5 months (preterm: α = 0.68; term: α = 0.75).

        <hss>Concepts of Development Questionnaire (CODQ)</hss>

        The CODQ (Sameroff & Feil, 1985) asks parents to rate 20 statements about child
        development on a 4-point Likert scale ranging from strongly disagree (0) to
        strongly agree (3). The CODQ measures parent cognitions about child development,
        in particular parent ability to think complexly about children. The CODQ contains
        two subscales – categorical and perspectivist – and a summary scale of complexity.
        For each subscale an average score is calculated. At the categorical level, parent
        cognitions are restricted to single determinants and single outcomes. For example,
        Parents must keep to their standards and rules no matter what their child is like.
        Three items for the categorical subscale had poor distributions and did not relate
        with the subscale overall or with the other items making up the subscale and so
        were not used to calculate the categorical subscale score. The remaining 7-item
        categorical subscale showed adequate internal consistency at birth (preterm: α =
        0.68; term: α = 0.77) and 5 months (preterm: α = 0.65; term: α = 0.53). At the
        perspectivist level, child development is viewed from multiple perspectives,
        allowing parents to understand that multiple factors can interact and change over
        time to result in different outcomes. For example, Parents change in response to
        their children. Cognizing at the perspectivist level allows parents to view and
        evaluate a large range of developmental possibilities. Three items for the
        perspectivist subscale had poor distributions and did not relate with the subscale
        overall or with the other items making up the subscale, so were not used to
        calculate the perspectivist subscale score. The remaining 7-item perspectivist
        subscale showed adequate internal consistency at birth (preterm: α = 0.60; term: α
        = 0.65) and 5 months (preterm: α = 0.60; term: α = 0.67). Previous studies have
        found similar internal consistency coefficients when using the CODQ (e.g.,
        Benasich & Brooks Gunn, 1996; Landry et al., 1996; Lee, 2005; Manlove, Vazquez, &
        Vernon-Feagans, 2008). Complexity is calculated as (perspectivist − categorical +
        3.0)/2. Therefore, complexity represents the balance between categorical and
        perspectivist thinking and also ranges from 0 to 3. To ensure the BCQ and CODQ
        used equivalent scales, after calculating complexity, all subscales of the CODQ
        were transformed to range from 1 to 4 (by adding 1 to all scores). Therefore, a
        complexity score of 4 means that parents strongly agree with items related to the
        perspectivist subscale and strongly disagree with items related to the categorical
        subscale. Conversely, a complexity score of 1 means that parents strongly disagree
        with items related to the perspectivist subscale and strongly agree with items
        related to the categorical subscale. Correlations among maternal structure,
        attunement, categorical, perspectivist, and complexity for birth and 5-month
        variables by birth status indicated that structure was not related to any of the
        cognitions, but attunement was positively related to perspectivist scores and to a
        smaller extent complexity scores. However, the correlation coefficients did not
        indicate singularity for any of these measures (shared variance = 0–28%) and so
        were treated independently.

<hs>  Descriptive and explanatory variables</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mothers completed a demographic questionnaire after delivery that collected information
about demographic variables, previous pregnancies, and the current or most recent
pregnancy and delivery. In addition, researchers accessed the medical records of the
infant after discharge and created records of the infants’ health during their
hospitalization.

<hs>  Analysis plan</hs>
  ~~~~~~~~~~~~~

Prior to data analysis, distributions of categorical thinking, perspectivist thinking,
complexity of thought, structure, and attunement at both time points were examined for
normality, homogeneity of variance, and influential outliers. All variables met
assumptions for parametric tests. The first aim was to assess the continuity and stability
of complexity of thought and caregiving principles in mothers of preterm and term infants.
Therefore, the effects of child age (birth vs. 5 months) and birth status (preterm vs.
term) were tested using repeated-measures Analysis of Variance (RM-ANOVA). Child age
(birth vs. 5 months) was treated as a within-subjects variable and birth status (preterm
vs. term) was treated as a between-subjects variable. In addition, stability estimates
were reported across ages for maternal complexity of thought and caregiving principles by
birth status using correlation. Table 2 presents means and standard deviations for
maternal complexity of thought and caregiving principles by infant age and birth status.
Table 2 also presents correlations between subscales at birth and 5 months by infant birth
status. Follow-up analyses were run to control for mothers’ previous experience of having
a child (birth order: firstborn vs. laterborn) and having previously had a preterm
delivery (no vs. yes). The uncontrolled analyses are reported below as all results
controlling for experience of mothers with previous children were the same as uncontrolled
analyses except where noted. The next aim was to identify what variables may account for
any developmental changes observed in complexity of thought and caregiving principles.
Multiple regression analyses were used to examine predictors of differential stability
across groups, and RM-ANCOVAs were used to examine predictors of discontinuity. The
predictors of change in mean level or discontinuity were examined using RM-ANCOVAs. First,
the main effects of infant age (birth vs. 5 months) and birth status, and the effect of
the infant age × birth status interaction on cognitions or principles at 5 months were
examined. Then, covariates were included to examine their effect on the significance of
the main effect of age and the infant age × birth status interaction. Reducing either the
main effect of age or the infant age × birth status interaction to nonsignificance would
indicate that the covariates, at least in part, accounted for the discontinuity of
maternal cognitions or principles. For the predictors of differential stability of
cognitions or principles, we used a similar process with multiple regressions. In the
first step, cognitions or principles at birth (centered), birth status (preterm vs. term),
and the interaction between cognitions or principles at birth and birth status were
included as predictors, and cognitions or principles at 5 months was the outcome variable.
Covariates were then included in the second step to examine whether their inclusion
attenuated the cognitions or principles at birth or interaction term to nonsignificance.
Potential health and demographic covariates were selected by examining zero-order
correlations with 5-month scores for cognitions or principles of interest.

<hs>  Complexity of thought</hs>
  ~~~~~~~~~~~~~~~~~~~~~

For categorical thinking, there was a main effect of age, F(1, 103) = 12.28, p < 0.001,
ηp2 = 0.107, no main effect of birth status, F(1, 103) = 0.00, p = 0.960, ηp2 = 0.002, and
a significant interaction between infant age and birth status, F(1, 103) = 4.34, p =
0.040, ηp2 = 0.040. Simple effects analyses examined the interaction between infant age
and birth status on categorical thinking. A main effect of age was found for mothers of
preterm, F(1, 40) = 15.36, p < 0.001, ηp2 = 0.277, but not term infants, F(1, 63) = 1.17,
p = 0.283, ηp2 = 0.018. Categorical thinking was continuous in mothers of term, but not
preterm, infants. Mothers of preterm and term infants did not differ in their categorical
thinking at birth, F(1, 103) = 1.03, p = 0.312, ηp2 = 0.010, or 5 months later, F(1, 103)
= 1.61, p = 0.208, ηp2 = 0.015. Mothers of preterm infants increased their categorical
thinking with age, whereas mothers of term infants did not change with age. We examined
possible explanations for the discontinuity of categorical scores in mothers of preterm
infants. Apgar scores at 5 min, number of siblings, and whether the mother was living with
a partner (no vs. yes) were included as covariates because these variables were related to
categorical thinking at 5 months. Apgar scores at 5 min were not recorded in medical
records for 11 infants (2 preterm and 9 term), and therefore these dyads were excluded,
resulting in a final sample of 94 (39 preterm and 55 term). Table 3 presents the F, p, and
ηp2 values for step 1—infant age, birth status, and infant age × birth status interaction
– and step 2—adding covariates – in predicting categorical thinking. In step 1, there was
a significant main effect of age, F(1, 92) = 11.83, p < 0.001, ηp2 = 0.114, but no main
effect of birth status, F(1, 92) = 0.32, p = 0.573, ηp2 = 0.003, and a trend level
interaction between infant age and birth status, F(1, 92) = 3.77, p = 0.055, ηp2 = 0.039,
on categorical scores. Adding covariates attenuated the main effect of age to
nonsignificance, F(1, 89) = 0.15, p = 0.705, ηp2 = 0.002 (a 0.112 reduction in the ηp2),
but only very slightly reduced the interaction between age and birth status, F(1, 89) =
3.46, p = 0.066, ηp2 = 0.037 (a 0.002 reduction in the ηp2). None of the covariates
independently predicted discontinuity in categorical thinking. The RM-ANCOVAs for mothers
of preterm and term infants individually showed that the main effect of age was
nonsignificant for both groups (preterm: F(1, 35) = 0.97, p = 0.332, ηp2 = 0.027; term:
F(1, 51) = 0.41, p = 0.523, ηp2 = 0.008). The only difference in the RM-ANCOVAs was that
Apgar scores at 5 min independently predicted categorical scores at 5 months for mothers
of preterm infants, F(1, 35) = 4.43, p = 0.042, ηp2 = 0.112 (higher Apgar scores related
to higher categorical thinking), but not term infants, F(1, 51) = 0.01, p = 0.932, ηp2 =
0.000. Together, Apgar at 5 min, number of siblings, and mother living with a partner
accounted for discontinuity in categorical thinking for both groups, but only Apgar scores
at 5 min independently predicted categorical scores at 5 months in mothers of preterm
infants. For perspectivist thinking, there was a main effect of age, F(1, 103) = 12.53, p
< 0.001, ηp2 = 0.108, a main effect of birth status at a trend level, F(1, 103) = 3.70, p
= 0.057, ηp2 = 0.035, but no significant interaction between infant age and birth status,
F(1, 103) = 0.48, p = 0.491, ηp2 = 0.005. Mean differences demonstrated that perspectivist
thinking was lower, on average, at birth (mean difference = −0.12, SE = 0.03, p < 0.001)
and in mothers of preterm infants (mean difference = −0.11, SE = 0.06, p = 0.057). When
controlling for previous children and previous preterm birth, the main effect of age
remained, F(1, 99) = 17.39, p < 0.001, ηp2 = 0.149, as did the main effect of birth
status, F(1, 99) = 4.00, p = 0.048, ηp2 = 0.039. However, there was also a significant
interaction between age and birth order, F(1, 99) = 5.11, p = 0.026, ηp2 = 0.049. Simple
effects analyses indicated that the main effect of age was only significant for mothers of
firstborns, F(1, 61) = 20.39, p < 0.001, ηp2 = 0.251, and not mothers of laterborns, F(1,
36) = 0.02, p = 0.894, ηp2 = 0.000. Mothers of firstborns increased in their perspectivist
thinking from birth to 5 months (birth: M = 2.78, SD = 0.35; 5 months: M = 2.96, SD =
0.35) but perspectivist thinking did not change for mothers of laterborns (birth: M =
2.92, SD = 0.35; 5 months: M = 2.94, SD = 0.35) for both groups of mothers. In addition,
mothers of preterm infants were lower on perspectivist thinking than mothers of term
infants. We examined potential explanations for the discontinuity of perspectivist scores
in the mothers of firstborn preterm and term infants. Mother's highest educational
qualification, attending antenatal classes (no vs. yes), and breastfeeding at birth (no
vs. yes) were included as covariates because these variables were related to perspectivist
thinking at 5 months. Only first-time mothers were included, and one dyad was excluded due
to missing data for breastfeeding at birth, resulting in a final sample of 63 (22 preterm
and 41 term). Table 3 presents the F, p, and ηp2 values for step 1—infant age, birth
status, and infant age × birth status interaction – and step 2—adding covariates – in
predicting perspectivist thinking. In step 1, there were main effects of age, F(1, 61) =
16.20, p < 0.001, ηp2 = 0.210, but no significant main effect of birth status, F(1, 61) =
2.19, p = 0.144, ηp2 = 0.035, or interaction between infant age and birth status, F(1, 61)
= 0.84, p = 0.364, ηp2 = 0.014, on perspectivist scores. Adding covariates attenuated the
main effects of age, F(1, 58) = 2.83, p = 0.098, ηp2 = 0.046 (a 0.164 reduction in the
ηp2) to nonsignificance. None of the covariates independently predicted perspectivist
thinking. Therefore, highest maternal qualification, attending antenatal classes, and
breastfeeding together accounted for the discontinuity of perspectivist thinking. Finally,
there were no main effects of age, F(1, 103) = 0.01, p = 0.937, ηp2 = 0.000, or birth
status, F(1, 103) = 1.82, p = 0.181, ηp2 = 0.017, or interaction between infant age and
birth status, F(1, 103) = 0.93, p = 0.336, ηp2 = 0.009, for complexity of thought.
Complexity of thought did not differ by infant age or birth status and was therefore
continuous for mothers of preterm and term infants. Stability was found for all three CODQ
variables in mothers of term and preterm infants (Table 2). Z-tests indicated that the
stability coefficients did not differ between mothers of preterm and term infants for
categorical scores (z = 1.02, p = 0.308, two-tailed test), perspectivist scores (z =
−0.33, p = 0.741, two-tailed test), or complexity scores (z = 0.00, p = 1.00, two-tailed
test).

<hs>  Caregiving principles</hs>
  ~~~~~~~~~~~~~~~~~~~~~

For structure, there was no main effect of age, F(1, 103) = 0.12, p = 0.729, ηp2 = 0.001,
or birth status, F(1, 103) = 3.28, p = 0.073, ηp2 = 0.031, or interaction between infant
age and birth status, F(1, 103) = 0.18, p = 0.671, ηp2 = 0.002. When controlling for
previous children and previous preterm birth, there was a significant main effect of birth
status, F(1, 99) = 3.96, p = 0.050, ηp2 = 0.038, but still no main effect of age, F(1, 99)
= 0.83, p = 0.364, ηp2 = 0.008, or interaction between infant age and birth status, F(1,
99) = 0.07, p = 0.789, ηp2 = 0.001. The main effect of birth status reflected that mothers
of preterm infants (M = 2.77, SD = 0.30) supported structure more, on average, than
mothers of term infants (M = 2.65, SD = 0.30). For attunement, there was no main effect of
age, F(1, 103) = 0.89, p = 0.349, ηp2 = 0.009, or birth status, F(1, 103) = 2.06, p =
0.154, ηp2 = 0.020, or interaction between infant age and birth status, F(1, 103) = 0.04,
p = 0.838, ηp2 = 0.000. Therefore, structure and attunement did not differ across age or
birth status and were continuous for mothers of preterm and term infants. However, when
controlling for previous experience of caregiving, mothers of preterm infants were higher
on structure than mothers of term infants. Stability was found for structure for mothers
of term infants but not mothers of preterm infants (Table 2). Z-tests indicated that the
stability of structure was significantly lower for mothers of preterm infants than term
infants (z = −2.50, p = 0.012, two-tailed test). Stability was also found for attunement
for mothers of preterm and term infants (Table 2). The stability of attunement did not
differ between mothers of preterm and term infants (z = −0.45, p = 0.653, two-tailed
test). We examined potential explanations for the differential stability of structure in
mothers of preterm and term infants. Family income was included as a covariate because
this variable was related to structure at 5 months. Three dyads were missing data on
family income and therefore were excluded from these analyses resulting in a final sample
of 102 (40 preterm and 62 term). Table 4 presents the regression coefficients for step
1—structure at birth (centered), birth status, and structure at birth × birth status
interaction – and step 2—adding family income – in predicting structure at 5 months. Step
1 accounted for 34% of the variance in structure scores at 5 months, R2 = 0.34, F(3, 98) =
16.72, p < 0.001. Neither structure at birth nor birth status predicted structure at 5
months, but the interaction between structure and birth status predicted structure at 5
months. This result reflects the earlier finding that structure was only stable in mothers
of term infants and not in mothers of preterm infants. Step 2 did not account for
significantly more variance than step 1, ΔR2 = 0.00, F(1, 97) = 0.53, p = 0.467. Adding
family income as a covariate attenuated the interaction term to nonsignificance (model 1:
β = −0.21, p = 0.037; model 2: β = −0.19, p = 0.065) but only just (a 0.02 absolute
reduction in the β). Family income did not independently predict instability in structure.
Therefore, family income accounts for some of the differential stability in structure
between mothers of preterm and term infants but only to a limited degree.

<h>DISCUSSION</h>
----------

The first aim of the study was to examine developmental trajectories of maternal
complexity of thought and caregiving principles following preterm and term deliveries in
the first 5 months of their infant's life. We found prematurity had a differentiated
effect on complexity of thought and caregiving principles, with different levels of
complexity of thought and caregiving principles affected differently. The second aim was
to examine demographic and medical variables that might explain changes in complexity of
thought and caregiving principles. Below we first discuss the findings related to
complexity of thought and then caregiving principles.

<hs>  Complexity of thought</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Categorical thinking was continuous for mothers of term, but not preterm, infants. Mothers
of preterm infants showed increasing levels of categorical thinking from the delivery of
their infant to 5 months later (and therefore an increase in less complex thinking). In
combination, Apgar scores at 5 min, number of siblings, and whether mothers were living
with a partner accounted for the discontinuity of categorical thinking in mothers of
preterm infants. The only independent predictor of categorical thinking was 5-min Apgar
scores for mothers of preterm, but not term, infants. For mothers of preterm infants,
higher 5-min Apgar scores were related to higher categorical thinking scores at 5 months
but not at birth. However, it must be noted that 5-min Apgar scores of the preterm infants
reflected the low-risk nature of the sample, as scores ranged from 7 to 10 (but around 86%
scored 9 or 10). Therefore, this finding needs to be further examined in a higher risk
sample with a wider range of Apgar scores. For both groups of mothers of firstborn
infants, perspectivist thinking increased over time and overall levels were lower in all
mothers of preterm infants regardless of parity. The discontinuity of perspectivist
thinking for first-time mothers was accounted for by a combination of highest maternal
qualification, having attended antenatal classes, and breastfeeding at birth (however,
none of these variables independently predicted perspectivist thinking). Finally,
complexity of thought was continuous for both birth status groups. Stability was found at
equal levels for all three complexity of thought variables across birth status groups.
Despite equal levels of complexity of thought, prematurity had an impact on categorical
and perspectivist thinking. Categorical thinking increased in mothers of preterm infants
from birth to 5 months but remained continuous in mothers of term infants. In addition,
mothers of preterm infants were less able (at trend levels) to demonstrate perspectivist
thinking. However, complexity of thought did not differ by the birth status or age of the
infant. Despite being able to think as complexly about child development as mothers of
term infants, mothers of preterm infants appear to increasingly rely on lower levels of
thinking. This result could have important implications because lower levels of thinking
have been shown to relate to more rigid and authoritarian parenting (Deković & Gerris,
1992), and more complex levels of thinking have been shown to relate to warm and sensitive
parenting (Landry et al., 1996; Miller-Loncar et al., 2000; Pratt et al., 1993).
Furthermore, this result could inform the design of NICU interventions. That is, early
interventions could focus on helping mothers to take multiple, flexible perspectives when
thinking about children and development (and so become less reliant on lower levels of
thinking). Further work needs to examine whether the similar levels and trajectories of
complexity of thought for mothers of preterm infants can prove protective despite
differences in categorical and perspectivist thinking (compared to mothers of term
infants). Therefore, relations between complexity of thought (both overall level and
trajectories) with later parenting behaviors and child outcomes need to be studied.

<hs>  Caregiving principles</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Structure and attunement were both stable and continuous in mothers of term infants. In
contrast, structure was continuous but unstable, and attunement was continuous and stable,
for mothers of preterm infants. Therefore, only the caregiving principle of structure
appeared to be affected by premature birth. In mothers of preterm infants, structure at
birth did not predict structure 5 months later. Therefore, mothers of preterm infants
appeared to change their support of structure over the first 5 months but not in a uniform
way (i.e., no mean increase or decrease). The differential stability of structure by birth
status was reduced to nonsignificance by controlling for family income. However, the
reduction of the interaction term of structure at birth × birth status was small, and
family income did not add to the variance accounted for in the regression model.
Therefore, this result should be considered with caution. Perhaps characteristics of the
infant (for example, sleep state stability or clarity of cues) would provide a better
explanation of the differential stability of structure than demographic or medical
factors. For example, it could be that the lower stability of structure following preterm
delivery reflects that these mothers are more willing to be flexible in structure and base
that principle on their infant's willingness or ability to fit into a schedule.
Alternatively, as preterm birth is often unexpected and accompanied by periods of
hospitalization, mothers’ support of structure at birth may not be a representation of
their true principles but instead reflect the structure of the hospital and medical staff.
As such, mothers of preterm infants may only develop their own principles about structure
on leaving the hospital and becoming fully responsible for their infants’ daily care. Both
of these hypotheses fit with findings that, when controlling for previous experience with
children, structure appeared to be higher in mothers of preterm, as compared to term,
infants. Future work should examine such hypotheses. Attunement, in comparison, did not
appear to be affected by premature deliveries as attunement showed stability and
continuity for mothers of preterm and term infants. Many interventions implemented
following premature deliveries or during NICU stays focus on teaching parents to respond
to the cues and unique characteristics of their infant (Browne & Talmi, 2005; Kaaresen et
al., 2006; Landry et al., 2008). In addition, more optimal outcomes have been found for
children who had parents who followed their interests and cues as infants (Landry et al.,
1997). Understanding a parent's support of attunement at the start of one of these
interventions or following a premature delivery may prove useful in planning how to best
approach helping parents. For example, parents who already support the principle of
attunement may only require guidance in identifying their infants’ unique cues, whereas
parents who show little or no support of attunement may first need the significance of
using their infants’ cues to guide caregiving explained. Therefore, this finding of
similar levels and trajectories of attunement demonstrates that mothers of preterm
infants, at least in principle, do not differ from mothers of term infants in the value
they place in using and trusting infant cues and signals to guide caregiving. Therefore,
attunement may reflect an enduring caregiving principle of parents that is less affected
by external forces, whereas structure is more responsive to environmental factors. More
work is needed to examine the predictors of these principles.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

There were relatively high levels of attrition between data collection at delivery and at
5 months. Loss of participants was primarily due to difficulties contacting families when
attempting to schedule the 5-month visit. In addition, this sample relied on families
consenting to take part in the study and as such was not representative of all preterm
infants born in UHW. The subscales of the CODQ showed relatively low internal consistency;
however, these consistency estimates are similar to those reported previously with samples
of parents of term, as well as preterm, infants (e.g., Benasich & Brooks Gunn, 1996;
Landry et al., 1996; Lee, 2005; Manlove et al., 2008). Future work might include a larger,
more heterogeneous sample. The current sample was relatively homogeneous, including
primarily white mothers of higher income and education. Furthermore, we excluded three
families due to a history of depression or concerns about the social environment of the
child. We were unable to include these families in the sample because the small number
meant that we were not able to control for these social risk factors. Future studies, with
larger, more diverse samples, should include such variables in analyses. This study is,
however, an important first step to examining the effects of infant prematurity on the
development of maternal cognitions and principles.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

This study demonstrates differences in the trajectories of some of the studied cognitions
and caregiving principles following preterm, as compared to term, deliveries. The studied
maternal cognitions and caregiving principles were not affected equally by prematurity.
Mothers increasingly relied on categorical thinking in establishing the caregiving role
for their preterm infants and were less stable in reports of structuring their caregiving.
However, both structure and categorical thinking showed similar levels for mothers of
preterm and term infants at both time points. This study highlights the need to examine
developmental trajectories of cognitions and principles. In addition to differences in the
trajectories of complexity of thought and caregiving principles, mothers of preterm
infants tended to report lower perspectivist thinking than mothers of term infants
following delivery and after 5 months of caring for their infant. These results provide
insight into the development of complexity of thought and caregiving principles following
premature deliveries and tell us about the broader context in which cognitions about child
development and caregiving principles develop in parents. For example, first-time mothers
(at a group level) increased in their perspectivist thinking as their infants grew older,
while mothers of laterborns showed consistency across time. In addition, given that
different cognitions about child development and caregiving principles showed different
trajectories these results further highlight that parenting is multidimensional (Bornstein
& Cote, 2004; Bornstein & Tamis-LeMonda, 1990; Bornstein, Tamis-LeMonda, Hahn, & Haynes,
2008). Further work needs to examine the change and consistency of these cognitions about
child development and caregiving principles later in infancy, as well as their impact on
parenting behaviors and child outcomes.

<h>AUTHOR NOTE</h>
-----------

Alice Winstanley, Department of Psychology, University of Cambridge; Rebecca G. Sperotto
and Merideth Gattis, School of Psychology, Cardiff University; Diane L. Putnick and Marc
H. Bornstein, Eunice Kennedy Shriver National Institute of Child Health and Human
Development; and Shobha Cherian, Department of Child Health, University Hospital of Wales.


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<ART>Context, control and the spillover of energy use behaviours between office and home settings
================================================================================

Authors: Clare Littleford, Tim J. Ryley, Steven K. Firth
DOI: 10.1016/j.jenvp.2014.06.002
Year: 2014  |  Pages: 157-166
ASJC codes: 3202, 3207
Keywords: Behaviour, Energy use, Household, Office, Organisational, Spillover

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This paper examines how office-based lighting and computer use behaviours relate to similar behaviours performed by the same individuals in a household setting. It contributes to the understanding of energy use behaviour in both household and organisational settings, and investigates the potential for the 'spillover' of behaviour from one context to another. A questionnaire survey was administered to office-based employees of two adjacent local government organisations ('City Council' and 'County Council') in the East Midlands region of the UK. The analysis demonstrates that the organisational or home setting is an important defining feature of the energy use behaviour. It also reveals that, while there were weak relationships across settings between behaviours sharing other taxonomic categories, such as equipment used and trigger for the behaviour, there was no evidence to support the existence of spillover effects across settings. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In recent years, concern about environmental impacts and the cost, availability and
security of energy supplies has led to heightened interest in ways to reduce energy use
within buildings. For psychologists, work in this area has frequently focused on
understanding the determinants of energy use behaviours, or on testing the effectiveness
of intervention strategies aimed at changing behaviours (Abrahamse, Steg, Vlek, &
Rothengatter, 2005). Much of the research into the determinants of energy use behaviours
has focused on household settings (Abrahamse, Steg, Vlek, & Rothengatter, 2007; Owens &
Driffill, 2008; Steg, Dreijerink, & Abrahamse, 2005). However, non-domestic buildings
account for around one quarter of total UK energy use (Brown, Wright, Shukla, & Stuart,
2010), with local government buildings alone estimated to consume 26 billion kWh of energy
annually (Carbon Trust, 2007). Interest is now growing in understanding energy use
behaviours in non-domestic, organisational settings such as offices and other workplaces
(Lo, Peters, & Kok, 2012; Matthies, Kastner, Klesse, & Wagner, 2011; Murtagh et al., 2013,
in press; Scherbaum, Popovich, & Finlinson, 2008). At the same time, many behaviour change
interventions include, explicitly or otherwise, the notion of ‘spillover’ – that
encouraging people to take up one pro-environmental behaviour may lead them to take up
further pro-environmental behaviours (Thøgersen & Ölander, 2003). By exploring how office-
based lighting and computer use behaviours relate to similar behaviours performed by the
same individuals in a household setting, this paper contributes to the understanding of
energy use behaviour in both household and organisational settings, and investigates the
potential for ‘spillover’ of behaviour from one context to another. Energy saving
behaviours such as turning off equipment when it is no longer in use are not necessarily
motivated by pro-environmental intentions; they may be the result of, for example, habit
or routine, organisational practice, a personal dislike of waste, or a fear of electrical
faults. Literature exploring these behaviours from an environmental standpoint can
nevertheless provide insights. Stern (2000) identifies and describes four classes of pro-
environmental behaviour: environmental activism such as involvement in environmental
organisations; non-activist public behaviour such as support for or acceptance of public
policies; private-sphere environmentalism including the purchase, use and disposal of
household products; and other environmentally-significant behaviour including behaviour
within organisations. This classification distinguishes behaviours performed in household
settings from those performed in organisational settings. In particular, it identifies
that individuals may affect the environment by influencing organisations to which they
belong, or by how they carry out their role within an organisation. Much of the literature
examining individual environmentally-significant behaviour focuses on behaviours that
could be classed as private-sphere environmentalism: waste and recycling (e.g. Barr, 2007;
Tudor, Barr, & Gilg, 2007), energy demand (e.g. Abrahamse et al., 2005) and travel mode
choice (e.g. Anable & Gatersleben, 2005; Bamberg & Schmidt, 2003). For much of this
research, the context of the behaviour is a household setting, where individual control
over the performance of behaviours is likely to be relatively high. While even in
households individuals do not have complete autonomy (their behaviour may be influenced or
constrained by the people they live with, or by the finances, time or facilities available
to them) it is still likely that an individual will have greater control over these
behaviours in their own home than in an organisational setting such as an office. In
offices, behaviours are shaped by the physical context of the office (the presence of
controls over building systems or equipment), but also by the social context (the needs,
expectations or norms of the people they share the office with) and by the organisational
context (the policies and expectations of the organisation that employs them). However,
many pro-environmental behaviours within organisational settings could fit into more than
just Stern's (2000) fourth category of ‘other behaviour including within organisations’.
Non-activist public behaviour within an organisation could include support for a company's
environmental policies, while private-sphere environmentalism choices could affect an
employee's actions within the workplace. For such behaviours to be classified separately
to similar behaviours performed in a household setting, the setting that the behaviour
occurs within would need to be a defining feature of that behaviour. A number of
researchers have considered how environmentally-significant behaviours in one setting
relate to similar behaviours in different settings. Barr, Shaw, Coles, and Prillwitz
(2010) found that people tend to behave in a less pro-environmental manner when on holiday
than when at home, often finding it difficult to transfer commitment to environmental
action into other, more problematic contexts. The problematic aspects of other contexts
are likely to vary according to the nature of the context in question. This is an area
that has not yet been fully explored by researchers. However, it has been identified that
the influencing factors most relevant to a particular behaviour are specific to each
context (Stern, 2000). For example, Siero, Bakker, Dekker, and Van Den Burg (1996) argue
that it is not possible to generalise from household energy saving behaviour to workplace
energy saving behaviour because expenditure is experienced more directly by the household,
while employees only benefit indirectly from financial benefits of energy saving at work.
However, this suggests that cost is an overriding factor in the decision-making process,
while other research has identified a wide range of factors that may influence
environmentally-significant behaviour, including situational characteristics, prior
awareness and experience of the behaviour, habits and routines, environmental beliefs and
values, social and personal norms, and perceptions of behavioural control and self-
efficacy (Bamberg & Möser, 2007; Barr, 2007; Clayton & Brook, 2005). Who pays for the
energy used, then, is only one difference between the home and workplace settings, and not
necessarily the decisive difference. Where connections have been found between behaviours
performed in household and organisational settings, prior experience of the behaviour has
been shown to be important. Studies of waste and recycling behaviour found that office
workers who actively recycled at home were more likely to recycle paper (Lee, De Young, &
Marans, 1995) and textiles (Daneshvary, Daneshvary, & Schwer, 1998) at work than
colleagues who did little home recycling, while a sample of hospital workers reported
recycling similar items in the workplace to those they recycled at home (Tudor et al.,
2007). Tudor et al. (2007) suggest that similarities between specific recycling items may
act as a cue to prompt the behaviour in each location. Barr (2007) suggests that the link
identified by Daneshvary et al. (1998) between behavioural experiences in one setting and
action in another implies a ‘behavioural snowball effect’, with participation in one
behaviour leading to uptake of others. This has also been identified as a ‘spillover’
effect in the context of behaviour change interventions (Thøgersen & Ölander, 2003). Much
of the evidence suggesting the existence of a spillover effect is correlational (Barr,
Gilg, & Ford, 2005; Poortinga, Whitmarsh, & Suffolk, 2013; Thøgersen & Noblet, 2012;
Whitmarsh & O'Neill, 2010), with evidence that correlations between behaviours increase
with the similarity (Bratt, 1999) and the perceived similarity (Thøgersen, 2004) of the
behaviours. Thøgersen and Noblet (2012) argue that behaviours in the same taxonomic
categories (time and place of behaviour, skills employed etc.) tend to be more strongly
correlated than behaviours within different taxonomic categories. For similar behaviours
in household and organisational settings, however, it is not clear whether prior
experience of the behaviour in one setting will encourage the performance of the behaviour
in the other setting, leading to spillover effects, or whether differences between the
household and organisational contexts will lead to differences in the performance of the
behaviour. This question is important because the concept of spillover is influential in
the design of many public behaviour change campaigns, which encourage people to take small
steps to mitigate environmental impacts in the hope that small actions will lead to more
and larger pro-environmental actions (Thøgersen & Crompton, 2009). If such an effect does
exist and can be encouraged across contexts, this could add to the potential influence of
behaviour change campaigns, with workplace-based campaigns able to influence home
behaviours and vice versa. However, Nye and Hargreaves (2010) argue that different
mechanisms drive behaviour change in workplace and household settings, with normative
influences particularly influential in the workplace. Furthermore, the notion of spillover
is problematic. Thøgersen and Noblet (2012) criticise behaviour change programmes and
policies that attempt to trigger spillover, arguing that there is little evidence that
‘wedge’ or ‘catalyst’ behaviours lead to large behavioural changes, beyond a weak ‘foot in
the door’ effect. This effect suggests that performing pro-environmental behaviours can
‘prepare the ground’ for acceptance of more far-reaching pro-environmental changes, but
that this is likely to only work when the original behaviours are considered pro-
environmental, rather than common, socially mandated or providing individual benefits
(Poortinga et al., 2013; Thøgersen & Noblet, 2012). This is problematic in organisational
settings such as offices, where other considerations such as carrying out tasks related to
the job role, meeting the expectations of the employing organisation or interacting with
colleagues in a shared environment may lead to multiple or competing motivations. This
paper, then, addresses two questions: Is there a fundamental difference between energy use
behaviours performed in the organisational setting of an office and energy use behaviours
performed in a household setting? Does the performance of an energy use behaviour in the
organisational setting of an office spill over to influence the performance of related
behaviours in a household setting? These questions are addressed by examining responses to
a questionnaire survey on lighting and computer use in office and household settings. This
allows the connections between the performance of similar behaviours by the same
individuals across organisational and household settings to be examined.

<hs>  The study</hs>
  ~~~~~~~~~

This paper discusses responses to a questionnaire survey administered to office-based
employees of two adjacent local government organisations (‘City Council’ and ‘County
Council’) in the East Midlands region of the UK. The independence of the study from the
Councils and the confidentiality of responses given were emphasised in the invitation to
take part and in the questionnaire's introductory text. Results of the study were shared
with the Councils, but only at an aggregate level once the analysis was complete.
Responses were examined in two stages. Stage one investigated whether there was a
fundamental difference between energy use behaviours performed in an office setting and in
a household setting. Stage two investigated whether there was evidence for the spillover
of energy use behaviours from the office to the household setting. Respondents from the
City Council (n = 337) were based in a single modern open-plan office building with
predominantly centrally-controlled or automated lighting (hereafter ‘City Central
Building’). Respondents from the County Council (n = 296) were based in 32 separate office
buildings, but with 226 respondents concentrated in four main buildings. The remaining
respondents were mostly based in small offices within specialist buildings such as
libraries and children's centres. Most of the County Council respondents (259 of 296)
reported that they had some individual-level control over lighting within their office
building. In stage one, all respondents were included. In stage two, the 337 responses
from the City Central Building (19% of the 1785 occupants) were compared with the largest
group of responses from a single building within the County Council sample (n = 144, 32%
of the 450 occupants). This building (hereafter ‘County Individual Building’) was an older
office building where occupants had a higher level of individual control over lighting
than in the City Central Building. While occupants of the City Central Building were only
able to turn lights off in meeting rooms, occupants of the County Individual Building were
able to turn lights off in meeting rooms, toilets, and open plan offices (using light
switch cords hanging from ceilings above the desks). Including the full County Council
sample for stage one rather than just those included in stage two gave a larger sample
(296 rather than 144), which was better for conducting Principal Components Analysis
(Field, 2009). Limiting the County Council sample in stage two to those from the County
Individual building meant that levels of individual control over energy use were
consistent across the whole of each sample.

<hs>  Survey design</hs>
  ~~~~~~~~~~~~~

The questionnaire was administered as a web-based survey, with respondents invited to take
part via all-staff emails and through advertising on each organisation's intranet. The
wording of these invitations was provided by the researchers and emphasised their
independence from the Councils, although the all-staff emails themselves were sent by an
employee from each Council's Sustainability team. Sections in the questionnaire covered
socio-demographics, self-reported lighting and computer use in the office and in the home
setting, and a selection of attitude-behaviour items. This included items measuring
constructs taken from the Theory of Planned Behaviour (Ajzen, 1991). In this paper, these
were used to identify how variables measuring different aspects of behaviours in the
office and home settings grouped together; an investigation of the relationships between
constructs proposed by the Theory of Planned Behaviour is not presented here (Littleford,
2013). Office behaviours examined relate to lighting and computer use. These behaviours
had quite a small impact in terms of the amount of energy the appliances consumed, or the
potential energy savings that could be made through changes in individual behaviour.
However, individual office occupants had a greater level of control over the use of
computers and lighting than they did over other building systems that consumed more
energy, particularly heating and cooling. In the City Central building, temperature was
controlled by a Building Management System, with no opportunity for individual control. In
the County Individual building, the heating system could be controlled on each floor but
worked poorly, with large fluctuations in internal temperature in different parts of the
building making this a contentious issue. These circumstances meant that no comparisons
could be drawn between office and home heating behaviours for participants from the City
Central building as they could not control heating in the office, while participants in
the County Individual building's heating behaviours were dominated by experiences of
discomfort, making it unlikely that meaningful comparisons could be drawn with their
heating behaviours at home. Furthermore, the agreement reached with the two Councils
participating in the study was to focus on behaviours within the office buildings, so
other energy intensive behaviours such as driving were outside the scope of the study. The
study aimed to develop insights into behaviour in the office and home settings, and
behaviours that were commonly performed in both settings, such as using lighting and
computer equipment, allowed the study to identify processes and relationships across
settings, even if the behaviours in question were not the most energy intensive behaviours
performed in each setting. Respondents from the County Council were asked to report their
performance of three lighting behaviours: turning office lights off when they were not
needed, turning meeting room lights off when they leave the room empty, and turning toilet
lights off when leaving them unoccupied. In the City Central Building, office and toilet
lights were controlled centrally by the Building Management System, but occupants were
able to turn off lights in meeting rooms, so were only asked about these. All respondents
had the same level of individual control over their computer use, and were asked about
three computer-related behaviours: turning off the computer when they finished for the
day, turning off the computer monitor when they finished for the day, and turning off the
computer monitor when away from their desk for more than ten minutes. Respondents were
asked how often they performed each behaviour, with five response categories: Never,
Rarely, Half the time, Frequently, and Always. Home behaviours examined in the
questionnaire were chosen for their similarities to the office behaviours. All were asked
how often they performed two lighting-related and two-computer related behaviours, and
again were given five response categories. The two lighting behaviours were turning off
lights in a room when they weren't needed, and turning off lights in a room when leaving
the room empty; these matched the wording of the office lights and meeting room lights
questions respectively. The two computer-related behaviours were turning off the home
computer when finished using it, and turning off the computer monitor when away for more
than ten minutes. The first question referred to ‘when finished using it’ rather than
‘when finished for the day’ used in the office setting, reflecting that in the office
context the occupant left the vicinity of the computer at the end of the working day (by
going home), but in the home context was more likely to remain in the same environment.
The question about turning off the computer monitor when away for more than ten minutes
matched the wording in the office setting. An additional item in the Home setting stated
‘I turn the main TV off fully instead of leaving on standby’; while this was similar to
the computer-related behaviours (turning off the equipment when it was finished with),
there was no direct comparison in the Office setting. Respondents were also asked to state
their level of agreement with a range of attitudinal statements, on a five-point scale
(‘Strongly disagree’ to ‘Strongly agree’). These included items measuring constructs
within the Theory of Planned Behaviour (Ajzen, 1991), and additional items relevant to the
household and organisational settings. The constructs from the Theory of Planned Behaviour
were Attitude towards the behaviour (ATT), Subjective Norm (SN) and Perceived Behavioural
Control (PBC). These were measured at a behaviour and setting-specific level, with six
items measuring ATT for each behaviour in the Office setting, six in the Home setting, six
measuring SN in the Office setting and four in the Home setting, and two measuring PBC in
each of the Office and Home settings. Further attitude statements related to the
respondent's sense of their own responsibility for saving energy at work and at home,
their sense of moral obligation to save energy in each setting, and whether they saw
reducing the Council's energy use as ‘good’ or ‘important’. Additional items addressed the
respondent's perceptions of the organisation's expectations of its employees, the
organisation's commitment to energy conservation, and the importance placed on energy
conservation by senior management.

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

In stage one, Principal Components Analysis (PCA) was conducted on reported behaviours in
both settings, and on responses to items measuring constructs within the Theory of Planned
Behaviour. Direct Oblimin rotation, an oblique rotation method, was used, as it could not
be assumed that the variables were fully independent. The analysis was conducted
separately on the City Council (n = 337) and County Council (n = 296) samples; as the non-
normal distribution of the results for many variables limited the generalisability of the
findings from a single sample, results from two separate samples helped to confirm the
findings (Field, 2009). Stage two used the whole of the City Council sample (n = 337)
based in the City Central Building, and a sub-set of the County Council sample (n = 144)
based in the County Individual Building. A non-parametric correlation technique,
Spearman's rho, was utilised to identify significant associations between office and home
based attitudes and behaviours within each sample. Subsequently, hierarchical multiple
regression was used to identify significant differences between the two samples in both
the office and home settings. This allowed differences in the gender make-up of each
sample to be controlled for, enabling the analysis to better identify effects resulting
from differences in the office buildings the respondents were based in. If such
differences existed in the office setting but not in the home setting, this could indicate
that behaviour was not spilling over between the two settings.

<hs>  Characteristics of the samples</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 1 presents demographic details about the samples (including for the sub-sample of
the County Individual Building, taken from the County Council sample). For most
demographic items, the proportions of respondents in each category were similar across all
of the samples. Most respondents were full time employees who were not in a managerial
role and were owner-occupiers of their home. The largest difference between samples was in
the gender split, with females making up 57.9% of the City Council/City Central Building
sample, but only 39.6% of the County Individual Building sample, possibly reflecting a
difference in the kinds of departments based in each building. While the City Central
Building housed the majority of the City Council's office-based employees, the County
Individual Building housed a sub-section of the County Council's office-based employees
and included some technical services (highways, transport) which have been noted
nationally to be dominated by men, with women making up only 5% of senior local government
roles in highway services and 9% in transport across the UK (LocalGov.co.uk, 2008).

<hs>  Stage one: the distinction between behaviour in the office and home settings</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 presents summary statistics for each of the self-reported behaviours included in
the questionnaire for respondents from both Councils. High levels of performance were
reported for all behaviours apart from turning off computer monitors when away in both the
office and home settings. The highest reported performances of behaviours came in the
office setting. There was a near-universal performance of turning off a computer at the
end of the day, with 97.3% (City Council) and 96.8% (County Council) of respondents
reporting that they ‘Frequently’ or ‘Always’ performed this behaviour. These high levels
of reported enactment are a useful finding but resulted in too little variance in results
to be used in stage two of the analysis. Reported performance of turning meeting room
lights off was slightly lower, with 93.8% (City Council) and 90.6% (County Council)
selecting ‘Frequently’ or ‘Always’. Turning office lights off when they were not needed,
which only the County Council respondents were able to perform, was reported much less
frequently (74.1% ‘Frequently’ or ‘Always’). Respondents from the County Council
consistently reported a more frequent performance (albeit to a small extent) of each
office-based computer-related behaviour, while respondents from the City Council reported
slightly higher frequencies of performance of turning off meeting room lights. However,
the overall patterns of computer-related behaviours in the office setting were similar for
both Councils, with high reported frequencies of turning off computers and monitors at the
end of the day, but low reported frequencies of turning off monitors when away for more
than ten minutes. Turning off monitors when away for more than ten minutes was performed
less frequently in the office than at home, with 14.1% (City Council) and 16.8% (County
Council) reporting that they ‘Frequently’ or ‘Always’ turned off their monitor when away
more than ten minutes in the office, but 32.8% (City Council) and 36.0% (County Council)
reporting the same in the home setting. However, turning off the computer when finished
using it at home was performed less often than the equivalent, near-universal office
behaviour of turning off the computer at the end of the day, with 83.9% (City Council) and
79.5% (County Council) reporting that they ‘Frequently’ or ‘Always’ turned off the home
computer. This suggests that there is a difference in reported performance between similar
behaviours in the office and home settings. To explore this further, Principal Components
Analysis (PCA) was conducted to identify how the reported behaviours grouped together.
Table 3 presents the results of the first PCA, conducted on the reported performance of
nine behaviours (four in the office and five at home) in the County Council sample. All
factor loadings above .3 (or below −.3) are presented, with loadings used in factor
identification in bold. Data was excluded pairwise to minimise losses due to missing
responses, providing a sample of between 216 and 285 for each behaviour. The PCA was
conducted using Direct Oblimin rotation, and identified three components with eigenvalues
above 1, explaining 29.3%, 14.8% and 12.6% of the variance respectively. The items
clustering on the same components suggest that component 1 represents Home behaviours,
component 2 represents Computer Monitor behaviours, and component 3 represents Office
Lighting behaviours. The Home behaviours component had a reasonably strong reliability, α
= .644, but the components for Monitor behaviours (α = .598) and, particularly, Office
lighting behaviours (α = .421) were weaker. These components are made up of a small number
of items, which has been noted to weaken the results of Cronbach's α tests for the
internal reliability of a scale (Field, 2009). PCA was also conducted on items measuring
behaviour in the City Council sample, using the same parameters. Initial testing revealed
low levels of correlation and communality for three variables in this sample: turning off
meeting room lights, turning off the home computer, and turning the main TV of fully
instead of leaving on standby. These were excluded from the analysis, leaving only four
items to test. Despite this, the City Council sample provided some support for the factor
structure identified in the County Council sample, identifying components representing
Home behaviours (Home lights when not needed and Home lights when leave room empty,
eigenvalue 1.938, 48.5% of variance, α = .843) and Monitor behaviours (Office monitor when
away from desk and Home monitor when away from desk, eigenvalue 1.204, 30.1% variance, α =
.575). The results of these PCA support the presence of a stable factor structure and
identify that behaviours group together at a specific level, based on the type of
equipment (lighting, computer monitor). For the lighting behaviours, these also grouped
according to the setting that the behaviour occurs within, providing some evidence that
energy demand behaviours performed in an office setting are different to energy demand
behaviours performed in a home setting. However, it was not possible to see whether this
was also true for the computer monitors as there were too few items to form separate
components in each setting. For this reason, further PCA (again using Direct Oblimin
rotation) were conducted using responses to items measuring constructs within the Theory
of Planned Behaviour. Using these statements gave a larger number of measured items for
each behaviour. Statements measured ATT Attitude towards the behaviour, SN Subjective Norm
and PBC Perceived Behavioural Control, using multiple statements tailored to each
behaviour in each setting. Each sample was asked about four behaviours. As the City
Council sample had no individual control over office lighting, they were asked about
turning off meeting room lights when leaving the room empty, while the County Council
sample was asked about turning off office lights when they weren't needed. The other
behaviours were the same for both samples: turning off computer monitors when away for
more than ten minutes in both the office and home settings, and turning off home lights
when they were not needed. Table 4 presents the results of the PCA conducted on the City
Council sample. The analysis identified 11 components with eigenvalues over 1, explaining
between 2.7% and 21.5% of the variance. Most components clustered around items relating to
the same equipment, Theory of Planned Behaviour construct and setting for the behaviour.
Where the components were not consistent with this (components 7, 8, 10 and 11), they
reflected a weakness in the measurement of the Perceived Behavioural Control construct,
which was only measured with two items for each behaviour, with one of those items being
reverse-worded. The greater number of items relating to each specific behaviour in this
analysis reveals a distinction between monitor behaviours in the office and home setting
that could not be identified in the PCA of behaviours. For all of the behaviours presented
here, then, setting is a defining feature on which the components cluster. The analysis
also reveals similarities between behaviours performed in the same setting. Component 4
combines items measuring the Subjective Norm (SN) for both switching off home monitors and
switching off home lighting, although the factor loadings form distinct groupings by
equipment within that component. This suggests that the relationship between the
Subjective Norm and the reported performance of the behaviours is similar for both pieces
of equipment in the home setting. However, the influence of SN in the office setting
appears to be different, with SN statements for computer monitor and lighting behaviours
in the office setting clustering separately from each other and from their equivalents in
the home setting. A Principal Components Analysis was also conducted using responses from
the County Council sample, and the results supported those found for the City Council
sample. In the County Council sample, 9 components were identified, accounting for between
3.0% and 17.4% of the variance, with similar patterns of clustering according to
construct, equipment and setting for each specific behaviour. The results of Principal
Components Analysis for both samples support the contention that behaviours in the office
and home setting are different, even when the other taxonomic categories relating to those
behaviours (e.g. equipment, action, trigger for the action) are very similar.

<hs>  Stage two: connections and spillover between office and home settings</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Stage one of this analysis identified that the setting in which an energy use behaviour
occurs is an important factor in defining that behaviour. Stage two examines relationships
between energy use behaviours in the office and home setting, and explores whether there
is evidence of the spillover of behaviour between the two settings. The analysis focuses
on two specific buildings, the City Central Building with high levels of centralised
control over lighting through a Building Management System, and the County Individual
Building with a higher level of individual occupant control over lighting, including light
switch cords hanging from ceilings above individual desks. Correlations were calculated
using the non-parametric Spearman's rho. Table 5 presents the results of the correlations
for the samples from both buildings. A large number of significant correlations (r) were
identified, reflecting the high levels of reported performance for most behaviours. There
was a greater number of significant correlations (p < .05) between behaviours in the same
setting (17) than in different settings (12); of the most highly significant (p < .01), 13
were in the same setting and five in different settings. However, the setting was not the
only distinguishing feature. There were also a greater number of significant correlations
between behaviours in the office and home settings for the County Individual Building (9)
than for the City Central Building (3). Excluding the office lighting behaviour that only
the County Individual occupants could perform reduced this to a difference of seven to
three. The relationships between the office-based behaviour of turning off meeting room
lights and the four home behaviours were the clearest difference between the two samples,
with all four correlations for the City Central Building non-significant and for the
County Individual Building highly significant. The meeting room lighting behaviour in
County Individual Building correlated with all of the home-based behaviours, while the
meeting room lighting behaviour in City Central Building did not correlate significantly
with their performance of the home behaviours. Effect sizes were calculated using r2,
indicating the proportion of variance in the ranked data explained by the correlation. The
effect sizes for the correlations for County Individual Building were small, explaining
between 3% (Home lights when not needed) and 9% (Home computer when finished) of shared
variance in the ranks. Nevertheless, this highlights the lower level of individual control
over lighting in the City Central Building than in the County Individual Building.
However, the correlations for turning office lights off when not needed, which only
respondents in County Individual Building could perform, were only significant for two of
the four home-based behaviours (Home lights when not needed, and Home computer when
finished). The correlation with the other home lighting behaviour, Home lights when empty,
was not significant. This suggests that the correlation is not only related to the type of
equipment (lights, computer monitors), but also to the triggers for behaviour (when not
needed, when leaving a room empty). Given this, it is of no surprise that the strongest
correlation between behaviours in different settings in both samples was between the
office-based and home-based versions of turning off the computer monitor when away for
more than ten minutes, explaining 12.2% of the variance for City Central Building and 9.6%
of the variance for County Individual Building. These effect sizes are quite small, but
nevertheless significant. In both locations, the behaviours share the type of equipment
and the triggers for the behaviour. The second biggest effect size between locations for
County Individual Building (explaining 9% of the variance) was between turning meeting
room lights off when leaving the room empty, and turning the home computer off when
finished using it. These are different types of equipment, but could arguably share a
trigger of their use having finished. However, this relationship is non-significant for
the City Central Building, suggesting that other differences between the samples are
influencing reported behaviour. To investigate some possible differences between the
samples from each building, responses to a number of statements measuring attitudes and
organisational factors were examined using hierarchical multiple regression. As the gender
make-up of each sample was markedly different, this method of analysis allowed the effects
of gender to be controlled for when identifying relationships with the building that
respondents were based in. Table 6 presents the results of the regression analysis,
revealing that, once gender was controlled for, significant differences between the two
samples were found for two of the three office-based behaviours and for three of the four
office-based attitude statements. Once gender was controlled for, the building that the
respondent was based in did not have a significant relationship with any of the three
organisational variables measured. Significant differences were seen for nine of the ten
variables examined, although all were small effects; the largest, for the attitude item
‘Reducing the Council's energy use is a good thing’, accounted for just 5% of the
variance. Significant relationships between reported behaviours and the building that the
respondents were based in were found for two of the three office-based behaviours.
Respondents in the County Individual Building were significantly more likely to report
turning off their monitor at the end of the day than respondents in the City Central
Building (explaining 4% of the variance). Conversely, respondents in the City Central
Building were significantly more likely to report turning off meeting room lights,
although this only accounted for 1% of the variance. Significant relationships were also
found between the building the respondents were based in and their responses to three
attitude statements. Respondents in the City Central Building were more likely to agree
that reducing the Council's energy use was ‘a good thing’ (explaining 5% of variance) and
‘important’ (2%), while respondents in the County Individual Building were more likely to
agree that they ‘should do what they can’ to help the Council save energy (2%). The
remaining attitude statement, ‘I should do what I can to help the Council save energy’,
was significantly related to both gender and the building the respondent was based in; the
building alone explained 2% of variance, rising to 3% once gender was accounted for,
revealing that women and respondents in the County Individual Building were more likely to
agree. These results distinguish between an assigned responsibility to act (‘not my
responsibility’), a moral sense of obligation to act (‘should do what I can’), and an
assessment of the value of acting (‘important’ and ‘a good thing’). Differences in
behaviours across the two buildings were accompanied by differences in the respondents'
sense of moral obligation to act (with respondents in County Individual Building feeling
this more strongly) and their assessment of the value of acting (with respondents in City
Central Building feeling this more strongly). Gender alone accounted for differences
between the samples found in three variables, with women being significantly more likely
to agree that Council employees were expected to try to conserve energy (explaining 1% of
variance), that the organisation was committed to saving energy (2%), and that senior
management saw this as a priority (3%). As the two samples originate from different
organisations, these three statements were designed to examine whether organisational
differences accounted for differences between the samples, measuring respondents'
perceptions of organisational commitment to energy saving. The first, ‘People who work for
the Council are expected to try to conserve energy’, measured perceptions of the
expectations placed on respondents by the organisation. The second, ‘The Council is
committed to saving energy’, measured perceptions of the organisation's commitment to
saving energy. The third, ‘Senior management see conserving energy as an important
priority’, measured perceptions of the importance of energy saving to the organisation's
leadership. Responses to these statements were not as positive as for attitudes and
behaviours. For the first two statements, most respondents selected either ‘3 = Neither
agree nor disagree’ (City Central Building, 36.2% and 26.1%; County Individual Building,
35.3% and 39.1%) or ‘4 = Tend to agree’ (City Central Building, 39.9% and 44.2%; County
Individual Building, 35.3% and 39.1%). For the third statement, responses were even more
ambivalent, with 46.3% (City Central Building) and 42.0% (County Individual Building)
selecting ‘3 = Neither agree nor disagree’. While the results did identify small
differences relating to gender, the results did not distinguish between the two buildings,
suggesting that the respondents' perceptions of their organisation's commitment to energy
saving did not explain differences between the two samples' office-based attitudes and
behaviours. To test whether differences between responses from each building carried over
into the home setting, respondents were also asked to report on home-based behaviours and
respond to home-based attitude statements. Hierarchical multiple regression was again
conducted on the results to test whether the building the respondent was based in or their
gender was related to their responses (Table 7). Only one variable was found to be
significantly related to either the building or gender. Women and those based in the
County Individual Building were significantly more likely to agree with the attitude
statement ‘I should do what I can to save energy at home’, explaining 3% of variance.
However, gender had a greater effect than the building, which alone accounted for just 1%
of variance. The results reveal that, while there were significant differences between the
two samples for attitudes and behaviours in the office, there were no significant
differences for behaviours at home, and only one small difference on attitudes at home. If
there had been significant differences in behaviours reported in the home setting
consistent with those seen in the office setting, this would have provided some evidence
of factors influencing behaviour across different settings. Instead, no evidence has been
found to support the existence of spillover effects between behaviours reported in the
office and home settings, beyond weak correlations between behaviours, and only small
evidence of consistency in attitudes across settings.

<h>DISCUSSION AND CONCLUSIONS</h>
--------------------------

This paper addressed two questions that explore the relationships between energy use
behaviours performed in office and home settings. Firstly, the paper examined whether
there was a fundamental difference between energy use behaviours performed in the
organisational setting of an office and in the home. Using Principal Components Analysis
(PCA), it was found that factor loadings grouped energy use behaviours according to
similarities in the equipment involved, the trigger for the behaviour, and the setting
that the behaviour took place within. Furthermore, even where the energy use behaviours in
each setting involved the same action and the same trigger for performing the action, the
factor loadings still clearly distinguished between settings. This suggests that the
organisational or home setting is an important defining feature of the energy use
behaviour. The second stage of the paper examined relationships between the energy use
behaviours performed in the office and the home setting, and whether this provided any
evidence for the spillover of energy use behaviours between settings. A greater number of
correlations between behaviours were found within the same setting than was found across
different settings. Correlations were found between behaviours that shared the same type
of equipment (lighting, computer monitors) and triggers for the behaviour (leaving a room,
finishing using the equipment) as well as the setting for the behaviour. The strongest
correlation across settings was found for turning off a computer monitor when away more
than ten minutes, with the behaviours sharing the same type of equipment and trigger for
the behaviour in each setting. The correlations identify that relationships between
behaviours are strongest when they share defining features; the PCA analyses identify that
setting is a particularly important defining feature. This suggests that spillover effects
across settings would be most likely to occur where other taxonomic categories (equipment,
trigger for the behaviour) were similar. However, this study did not identify evidence of
such an effect. Indeed, differences between the behaviours reported by respondents across
the two buildings provided a further opportunity to identify connections between
behaviours in different settings, but again did not find evidence of spillover.
Respondents from the City Central Building were significantly more likely to report
turning off meeting room lights than respondents from the County Individual Building,
while those from the County Individual Building were significantly more likely to report
turning off their computer monitor at the end of the day. However, no significant
differences were found between the two samples for reported behaviours in the home
setting; the causes of differences in reported behaviour in the office setting did not
carry over into the home setting. The correlations revealed further differences between
the behaviours reported by respondents from each office building. There was a greater
number of correlations between all behaviours reported by respondents from the County
Individual Building than by respondents from the City Central Building. Across settings,
this difference was particularly marked, with the office behaviour of turning off meeting
room lights correlating significantly with all four home behaviours for County Individual
respondents, but with no home behaviours for City Central respondents. The main difference
identified between these buildings was the level of individual control that occupants had
over lighting, with those in the County Individual Building having a higher level of
control. The greater number of correlations between office and home behaviours for
respondents from the County Individual Building suggests that people behave more
consistently across settings when they have greater control over their own behaviour.
However, in settings such as offices, individual control is more than just physical
control; it is also normative, reflecting the influence of an environment shared with
colleagues and shaped by the expectations of the employing organisation. Connections
between behaviours across settings, then, depend on the features of the behaviours in
question (equipment, trigger for the behaviour) and on the nature of the context, both
physical and normative. With setting an important defining feature of behaviour, and with
the different constraints created by different types of setting shaping the behaviours
reported, any spillover effects between behaviours in different settings seem likely to be
weak at best. This has implications for the design of behaviour change interventions,
suggesting that they will be most effective when they recognise the specific features of
the target behaviours – the equipment involved, the triggers for the performance of the
behaviour, and most importantly, the nature of the setting that the behaviour occurs
within. Interventions within organisational settings such as offices, this suggests,
cannot be expected to result in behaviour change within households (and vice versa),
unless other defining features of the target behaviours (equipment, trigger for the
behaviour) are very similar. One reservation about these findings does need to be noted,
however. The level of performance of each behaviour reported by respondents was very high,
resulting in data that was skewed and low levels of variance in the data. This limits the
level of variance in the home setting that could be explained using the data from the
office setting, and could potentially have masked further effects between settings. The
high levels of correlation between behaviours in different settings could be a sign of the
existence of such effects. Further research in this area could address some of the
limitations of this study, by identifying behaviours with greater variance that may reveal
effects not seen in the data presented here. Further research could also compare
behaviours in different office buildings within the same organisations rather than between
two similar organisations to eliminate any effects originating from differences in
organisational culture that have not been identified here. Research that compared the
results of behaviour change interventions in different settings would also be able to
identify further evidence for the existence, or otherwise, of a spillover effect between
contexts. There is also potential for research to usefully focus on how similar behaviours
need to be in each setting for influences on the performance of one behaviour to also
influence the performance of a behaviour in a different context. The research presented in
this paper has highlighted the importance of identifying the defining features that make
behaviours similar. Further work is needed to understand how such defining features
interact with context and action to create triggers for the performance of behaviours, in
order to understand the influence that the type of setting has on the performance of
individual energy demand behaviours.


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<ART>Cooperation is in our nature: Nature exposure may promote cooperative and environmentally sustainable behavior
================================================================================

Authors: John M. Zelenski, Raelyne L. Dopko, Colin A. Capaldi
DOI: 10.1016/j.jenvp.2015.01.005
Year: 2015  |  Pages: 24-31
ASJC codes: 3202, 3207
Keywords: Cooperation, Mood, Nature, Nature relatedness, Social dilemma, Sustainability

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Theory and correlational research suggest that connecting with nature may facilitate prosocial and environmentally sustainable behaviors. In three studies we test causal direction with experimental manipulations of nature exposure and laboratory analogs of cooperative and sustainable behavior. Participants who watched a nature video harvested more cooperatively and sustainably in a fishing-themed commons dilemma, compared to participants who watched an architectural video (Study 1 and 2) or geometric shapes with an audio podcast about writing (Study 2). The effects were not due to mood, and this was corroborated in Study 3 where pleasantness and nature content were manipulated independently in a 2×2 design. Participants exposed to nature videos responded more cooperatively on a measure of social value orientation and indicated greater willingness to engage in environmentally sustainable behaviors. Collectively, results suggest that exposure to nature may increase cooperation, and, when considering environmental problems as social dilemmas, sustainable intentions and behavior.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

We clearly face significant environmental challenges (e.g., climate change, pollution,
accelerating extinctions). Although the causes and solutions are obviously multifaceted
and complex, many have suggested that modern lifestyles contribute to environmental
destruction—not only via excessive consumption, but also by disconnecting people from
nature. This scholarship often draws on Wilson's (1984) biophilia hypothesis, which posits
that humans have an innate need to associate with other living things due to our
evolutionary history. We evolved in natural environments and, thus, they still support
optimal human functioning (Kellert, 1997). We do not need to accept the specific innate
need posited by biophilia to see a gap between humans' evolutionary environments and the
current living conditions of people in modern societies. This gap may be a source of
suboptimal well-being. Consistent with this idea, living near greenspace predicts higher
happiness (White, Alcock, Wheeler, & Depledge, 2013) and longevity (Mitchell & Popham,
2008), and spending time in nature seems to provide a variety of cognitive, mood, and
physiological benefits (reviewed by Hartig, Mitchell, de Vries, & Frumkin, 2014 and Selhub
& Logan, 2012). Despite nature's apparent benefits, most people spend the majority of
their time indoors away from nature (MacKerron & Mourato, 2013). This physical
disconnection may also foster a problematic psychological disconnection. That is, when
humans do not feel like they are part of larger ecosystems, they may be less inclined to
protect the natural environment (Schultz, 2000). Supporting this idea, individual
differences in subjective connectedness with nature consistently predict pro-environmental
attitudes and behaviors, as well as happiness (Capaldi, Dopko, & Zelenski, 2014; Mayer &
Frantz, 2004; Nisbet, Zelenski, & Murphy, 2009; Tam, 2013). Ironically, our threatened
natural environments may be critical to fostering the deep concern that would protect
them. Although suggestive, past research linking nature with sustainable behavior is
mostly correlational, qualitative, or relies on subjective self-reports. In this research
we take an experimental approach by manipulating exposure to nature and observing effects
on a laboratory analog of sustainable behavior: a fishing-themed commons dilemma (Gifford
& Gifford, 2000). Dawes (1980) described environmental problems as social dilemmas with
two key features: individuals benefit by behaving selfishly (e.g., over-harvesting
resources, polluting) regardless of others' choices, and where all would benefit if
everyone cooperated instead of pursuing immediate or narrow self interest (see also Parks,
Joireman, & Van Lange, 2013). Said another way, broad participation and cooperation are
essential to resolving many environmental problems. We hypothesize that participants
exposed to nature will make more cooperative, and thus sustainable, choices. We view
cooperative behavior as that which contributes to collective benefits (not necessarily
without simultaneous personal benefit), and, in this context, sustaining resources. This
prediction is similar to ideas prevalent in environmental psychology—that time in nature
and strong subjective connections with nature promote sustainable attitudes (Gifford,
2014). Nonetheless, it departs from most research in the area by suggesting that these
effects can be observed over the course of a few minutes in the laboratory. The processes
involved in a lifetime of accumulated nature experience may well differ, but we
nonetheless draw on the personality-level correlations as part of the rationale for our
prediction. Fleeson (2001) has suggested that associations at the trait level often apply
at the state level too (e.g., trait extraversion predicts high positive affect and most
people experience positive emotions when they behave in extraverted ways). Regarding
nature and sustainability, part of the link has been established. Brief exposures to
natural settings increase momentary feelings of nature relatedness (Mayer, Frantz,
Bruehlman-Senecal, & Dolliver, 2008; Nisbet & Zelenski, 2011; Schultz & Tabanico, 2007).
Because trait nature relatedness is strongly associated with sustainable attitudes (Tam,
2013), state nature relatedness, caused by nature exposure, may be too. Research on the
short-term consequences of nature exposure also suggests some reasons that nature could
promote sustainability, particularly when we think of sustainable behaviors that are also
cooperative behaviors. For example, nature exposure is often associated with good moods
(Mayer et al., 2008; Nisbet & Zelenski, 2011). Intuitively, and generally consistent with
the ‘broaden and build’ view of positive emotions (Fredrickson, 2001), good moods may
facilitate cooperative or prosocial behavior, actions that would also be sustainable in
resource dilemmas. Research on mood and cooperation, however, suggests that the link may
be complex and depend on context (Hertel, Neuhof, Theuer, & Kerr, 2000). Considering
another route, Kaplan and Berman (2010) reviewed nature's effects on attention
restoration, crime reduction, subjective energy, frustration tolerance, etc., and
suggested that they share the common core of improved self-control. Nature may facilitate
cooperation in commons dilemmas by improving self-control, thus curtailing temptations to
cheat or overharvest. Perhaps even more relevant, Weinstein, Przybylski, and Ryan (2009)
manipulated nature exposure with photographs (nature vs. built environments) or plants
(present or absent) and found that nature increased participants' intrinsic aspirations
and generosity, and decreased extrinsic, materialistic aspirations. That is, nature caused
people to report valuing others and prosocial behavior more, and wealth and fame less.
This extended to actual behavior in the ‘trust game’; participants exposed to nature gave
more actual money to another person that they could have kept for themselves without
negative consequence. These effects were mediated by feelings of (state) nature
relatedness and autonomy, and were strongest among participants who felt most immersed in
the nature. Similar effects may not require deep immersion, however. Mazar and Zhong
(2011) found that participants merely exposed to green products in a consumer study gave
away more money than participants who viewed more conventional products. Such effects
contrast with findings that money primes make people more self-sufficient and less
prosocial (Vohs, Mead, & Goode, 2006); nature may function oppositely (Nisbet & Zelenski,
2009). Although suggestive, none of this research has examined sustainability attitudes or
behaviors. Commons dilemmas provide a link between nature effects and sustainability
because they channel cooperation, trust, and prosocial motivations into sustainable
behaviors. To be clear, cooperative behavior is not always sustainable. Humans often
cooperate in ways that ultimately threaten natural environments; most current
environmental crises result from economic activity that requires some cooperation among
individuals and groups. Moreover, not every sustainable behavior requires cooperative
intentions. The environmental benefits may be diffuse (e.g., a reduction in greenhouse
gasses benefits all), but the intentions may be completely local and selfish (e.g.,
thinking, ‘a tree would look nice in my backyard’). Said another way, altruism is not
required for cooperation or sustainable behaviors. Our primary focus is the confluence of
cooperation and sustainability. Environmental problems are classic examples of commons
dilemmas, and, thus, research on commons dilemmas has much potential to inform
environmentally sustainable behavior and decision making. We have focused on an
environmentally themed commons dilemma because it allows us to bridge different
literatures in suggesting nature exposure as a potential aid to cooperative or sustainable
behavior. We extend the theory and mostly correlational research that suggests a strong
link between connecting with nature and sustainability by adding experimental
manipulations that speak to causal direction more directly. We extend experimental
studies' suggestive hints about nature's effects on mood, self-control, prosocial
motivation, and trust by testing them in contexts more relevant to sustainability. In sum,
there are theoretical and empirical reasons to suspect that exposure to natural (vs.
built) environments may promote cooperative, sustainable behavior. To test these ideas, we
conducted three studies. In the first, we randomly assigned participants to view videos of
almost exclusively natural or built environments. Participants were later asked to ‘play a
fishing game’, an iterative, fishing-themed commons dilemma where they were paid for each
fish harvested. We also included measures of mood, state nature relatedness, and state
trust (as possible mediators), and trait measures of nature relatedness and trust as
exploratory predictors or moderators. Study 2 reports a close replication. Study 3
provides a conceptual replication and extension; it begins to disentangle cooperation from
sustainability by measuring these outcomes independently. We report how we determined our
sample size, all data exclusions, all manipulations, and all measures in all studies
(Simmons, Nelson, & Simonsohn, 2012).

        <hss>Participants</hss>

        Undergraduate students (n = 111) were recruited for a study titled ‘Personality
        and Media’ via our department online subject pool system. Our goal was n = 120 for
        an exploratory study, and we collected data to the end of a semester. The sample
        was 70.3% female with a mean age of 20.81 (SD = 3.10). Participants received
        course credit as compensation. They were also paid based on fishing performance,
        but learned this only after arriving for the study.

        <hss>Materials</hss>

        Videos. To manipulate exposure to natural vs. built environments, participants
        viewed one of two 12-min videos that included educational narration and background
        music. The nature video excerpted BBC's Planet Earth series, beginning in tundra
        forest with images of trees and animals. It then proceeded to areas around the
        world and showcased the plants and animals native to those areas, ending in a
        jungle. We chose this particular excerpt because there are no mentions of marine
        life or fish, as well as to avoid explicit appeals for conservation. Planet Earth
        is easily described as a ‘nature documentary.’ It represents nature as
        environments relatively untouched by humans (lack of buildings), with abundant and
        beautiful fauna and flora (see Vining, Merrick, & Price, 2008). The built video
        excerpted Landmark Media's Walks with an Architect series, and featured in-depth
        looks at buildings, their history, and locations in New York City. The buildings
        in New York City arguably include some of the world's finest architecture, and we
        chose this video to contrast with the nature in Planet Earth while still conveying
        impressive content. The fact that nearly every part of the video contains human-
        built spaces makes it antithetical to common conceptions of nature (Vining et al.,
        2008). Thus, these excerpts were relatively ‘pure’ representations of nature and
        non-nature (cf., a cultivated garden). No pilot data were collected on the effects
        of these videos, yet some of their impacts (e.g., on mood and subjective
        connection with nature) are described by this study. Participants viewed videos on
        desktop computers with 17-inch screens and received sound via headphones. Commons
        dilemma. To assess cooperation, participants engaged in a fishing-themed commons
        dilemma, specifically FISH 3.1 (Gifford & Gifford, 2000; see
        http://web.uvic.ca/∼rgifford/fish/). In this microworld simulation, participants
        make choices about how many fish to harvest across multiple ‘seasons’. In our
        application, participants harvested from an ocean shared by three other fishers
        who were, unbeknownst to participants, actually simulated. Between each season,
        fish regenerated at a rate of 1.5, and fishing continued until fish were gone or
        15 rounds had passed, but participants were not informed of this limit. The ocean
        began with 50 fish, and participants were paid $.10 per fish harvested. A fee of
        $.05 was charged to go to, and return from, sea, thus making it necessary to catch
        at least two fish to profit in any one season (though participants could stay ‘on
        shore’ for free). Information about the number of fish harvested, fish remaining
        in the ocean, profits, and other fishers' catches were all displayed continuously
        on the screen. Simulated fishers were programmed to behave relatively
        cooperatively (an average of .5 on the 0 to 1 ‘greed’ setting). FISH yields
        measures of fish harvested, total seasons, profits, as well as calculated indexes
        of efficiency and restraint (see Gifford & Gifford, 2000). The indexes were
        calculated in each season, and then averaged across seasons so each participant
        received a single score. Restraint tracks the raw number of fish harvested while
        accounting for group size (but not regeneration rate); higher numbers (between 0
        and 1) are necessary for a sustainable resource. Efficiency tracks the number of
        fish taken relative to the current size of the fish population and the
        regeneration rate. Scores above 1 indicate ‘unnecessary’ efficiency, i.e., taking
        less than would regenerate, whereas scores below 1 indicate that more fish were
        taken than could be regenerated in the next season, thus shrinking the population.
        State Scales. To assess state nature relatedness, participants completed the
        single-item Inclusion of Nature in Self measure (INS; Schultz, 2002). Participants
        were presented with seven pairs of circles labeled self and nature that differ in
        the degree of physical overlap. Participants choose the pair that represented, “…
        your relationship with the natural environment at this point in time. How
        interconnected are you with nature right now?” As distractors, participants also
        rated pairs of circles labeled “self” and “people, family, friends, community, an
        urban center, and to all humanity.” A mood questionnaire included the Positive and
        Negative Affect Scales (PANAS; Watson, Clark, & Tellegen, 1988). Participants
        rated adjectives on a Likert scale of 1 (very slightly or not at all) to 5
        (extremely) to describe their feelings “in the moment”. Because the 10-item
        positive affect (α = .85) and negative affect (α = .81) scales assess only high
        arousal affects (e.g., enthusiastic, proud, interested, and afraid, nervous,
        distressed, respectively), we added adjectives that were lower in arousal, yet
        still pleasant, and intuitively associated with nature experiences: fascination,
        peaceful, content, in awe, curious, and relaxed. Although this scale is admittedly
        ad hoc, it may capture aspects of the ‘soft fascination’ described by Kaplan
        (1995). Nature is also a prototypical trigger of awe (Keltner & Haidt, 2003). This
        pleasant affect scale had good internal consistency (α = .79). Following a
        practice round of the FISH simulation, participants also completed a 3-item ad hoc
        measure of trust in other fishers (α = .79). They rated items like, “I expect that
        my group members will be trustworthy” on a 5-point scale of agreement. Trait
        Scales. Participants completed the 5-item Faith in People Scale (trust; Rosenberg,
        1957), and the 6-item Short Nature Relatedness Scale (Nisbet & Zelenski, 2013).
        These were embedded in the 44-item Big Five Inventory (John & Srivastava, 1999), a
        broad measure of personality traits, to avoid suggesting our interest in specific
        individual differences.

        <hss>Procedure</hss>

        Participants arrived at the lab and were ushered to a small testing room. One or
        two participants were tested simultaneously, but the lab layout suggested the
        possibility of more. After informed consent and a brief description of the study
        (framed as being about personality and perceptions of media), participants
        completed the trait measures. They were then randomly assigned to watch the Planet
        Earth or Walks with an Architect video. Following the video, they completed a
        brief questionnaire about their liking of the video (cover story), the INS, and
        mood questionnaire. Next, participants received detailed written and verbal
        instructions about FISH, including a three-season practice session. They then
        completed the state trust measure and began the actual FISH simulation of up to 15
        seasons. Following FISH, participants completed a brief questionnaire about their
        impressions of the ‘fishing game’ (cover story), a demographics questionnaire, and
        a questionnaire that probed for suspicion.1 Finally, participants were debriefed
        and paid according to their FISH performance.

<hs>  Results</hs>
  ~~~~~~~

Our primary hypothesis was that exposure to natural (vs. built) environments,
operationalized as Planet Earth (vs. architecture) videos, would produce higher rates of
cooperative and sustainable behavior. We tested this hypothesis across various FISH
indicators. Many had substantial skew, kurtosis, and outliers, so we present comparisons
in two ways: as t-tests with 15 outliers2 excluded from all tests, and nonparametric
Mann–Whitney's U with all participants (see Table 1). Results generally supported
hypotheses. Participants who watched the Planet Earth video harvested significantly fewer
fish per season and had commons pools that lasted more seasons than those who watched the
architecture video. These differences are mirrored in the indices of restraint and
efficiency with the Planet Earth condition showing more of both. Participants who viewed
the architecture video made significantly more money, suggesting that this scenario
favored a short-term, unsustainable strategy (i.e., large harvests across a few rounds).
By season 15, 49.09% of the architecture condition's oceans went extinct, compared to
28.57% in the Planet Earth condition, χ2 (1, N = 111) = 4.92, p = .03. We anticipated that
the Planet Earth video might produce better moods and more feelings of nature relatedness
and trust compared to the architecture video. These suspicions were only partially
confirmed (see Table 2). Participants who saw the Planet Earth video reported
significantly more pleasant affects and less negative affect, but groups did not differ
significantly on (high arousal) positive affect, state nature relatedness, or trust. Given
that the Planet Earth video produced somewhat more pleasant states, we conducted
exploratory bootstrapping mediation analyses (Preacher & Hayes, 2008) with all FISH
indicators as dependent variables. In no case was negative affect or pleasant affect a
significant mediator. (Said another way, controlling for mood made no difference.) In
other exploratory analyses, we tested whether relevant personality variables (nature
relatedness and trust) predicted FISH behavior or moderated the effect of our experimental
manipulation, but results were almost uniformly not statistically significant.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The results of Study 1 provide preliminary evidence that exposure to nature can promote
cooperative or sustainable decisions. Participants who viewed the Earth video harvested
more sustainably (i.e., fewer fish per season and extinctions) than participants who
watched the architecture video. Although the mechanisms of this effect are not clear, data
suggest that mood, trust, and subjective feelings of nature relatedness do not account for
differences.

<h>STUDY 2</h>
-------

In Study 2 we attempted a close replication with minor alterations. First, we adjusted the
FISH parameters slightly to see whether results would extend to a context that did not
favor a short-term strategy (in terms of profits). That is, we reduced the cost of going
out to sea so each fish was more profitable, especially in small catches. We also
increased the maximum number of seasons, giving fishers more time to benefit from a
sustainable, long-term strategy—small profits in each season add up when there are more
seasons. In addition, we added another more neutral control condition to confirm that the
action of the effect was not entirely due to the architecture video. Finally, we omitted
some of the exploratory measures from Study 1.

        <hss>Participants</hss>

        With procedures identical to Study 1, 121 students (71% female) were recruited and
        randomly assigned to either the nature, built, or neutral conditions. Our goal was
        40 subjects per condition, allowing good power to detect the effect sizes observed
        in Study 1. All received course credit (and money) as compensation.

        <hss>Materials and procedure</hss>

        The study was identical to Study 1 with the following exceptions: A new control
        condition consisted of watching the iTunes visualizer (full screen) while
        listening to the Grammar Girl podcast, The Rules of Story. In FISH, the cost of
        going out to, and returning from, sea was reduced to $.02, and the maximum number
        of seasons was increased to 25. Trait nature relatedness and both trust measures
        were omitted. A Big Five personality measure remained (recall the cover story
        about personality and media), but was changed to the 40-item ‘mini markers’
        (Saucier, 1994) as this was helpful to an unrelated project.

<hs>  Results</hs>
  ~~~~~~~

As in Study 1, our primary hypothesis was that the Planet Earth video would produce more
cooperative and sustainable FISH decisions compared to the architecture video and grammar
podcast. Skew, kurtosis, and outliers were again concerns with FISH variables, so we
conducted parametric analyses with three outliers excluded and nonparametric analyses with
no exclusions. (See Supplementary Materials for more Study 2 analysis details.) When
comparing omnibus tests across the three conditions, we found differences that were often
marginally significant (e.g., ANOVA ps from .06 to .14 and Kruskal-Wallace ps from .03 to
.08), with the exception of profits where there were somewhat smaller differences (ps =
.27 and .15). Across indicators, the architecture and grammar conditions were most similar
(comparisons produced ps all > .26), and both tended to differ from the Earth condition.
Table 3 provides means, SD, and an indication of where differences between two conditions
are statistically significant. Unless one is rigid about the p < .05 criterion, results
replicate Study 1's finding that Planet Earth produces more sustainable fishing behavior,
though effect sizes are somewhat smaller. Also, as anticipated, adjustments to FISH
parameters resulted in better outcomes for a sustainable strategy; the Planet Earth
condition now harvested more fish than architecture or grammar conditions. Mood
differences were also similar to Study 1 with nature somewhat more pleasant; the new
grammar control produced moods similar to the architecture condition. Exploratory
mediation analyses again failed to provide any evidence that mood was responsible for the
effects of videos on FISH outcomes.

<h>STUDY 3</h>
-------

To build on two studies with very similar methods and findings, Study 3 addressed some
issues of generalizability (e.g., going beyond the particular Planet Earth clip) and took
a stronger approach to ruling out mood as a possible (yet increasingly unlikely)
explanation for nature's effect on cooperation. To accomplish this, we created a new video
manipulation that independently varied pleasantness and nature content with a 2 × 2
design. In addition, we replaced FISH, as a measure of cooperation, with social value
orientation, a conceptually similar and empirically related measure (Balliet, Parks, &
Joireman, 2009) that includes no environmental connotations, followed by some more
explicit questions about sustainable behaviors.

        <hss>Participants</hss>

        Undergraduate students were recruited via our department online portal until 250
        had completed the study. To ensure valid responses, analyses excluded participants
        who finished in less than 10 min (median time was 21 min) and who did not comply
        with two requests to leave items blank; thus, n = 228.

        <hss>Materials</hss>

        Videos. Drawing on videos from YouTube, we created 2 min clips designed to
        independently manipulate pleasantness and natural (vs. built) context. We used
        criteria similar to Study 1 to determine nature and built contexts. To enhance the
        valence manipulation, we replaced original sound with upbeat, pleasant music or
        minimalist, foreboding music. Visual content included: Las Vegas strip (pleasant,
        built) which included images and video from this street at night with neon signs
        and edited in a fast, ‘upbeat’ way; old-growth forest (pleasant, nature) which
        showed a time lapse clip of undergrowth sprouting and aerial shots of large,
        mature trees; abandoned, decrepit house (unpleasant built) which slowly toured a
        clearly abandoned and distressed building with minimal furnishings; a flood
        (unpleasant nature 1) which showed expansive and fast moving water in a clearly
        flooded landscape that included some occasional damaged houses; a wolf pack
        (unpleasant nature 2) which showed wolves antagonizing a bison and bear, and
        hunting and killing an elk. The ‘extra’ unpleasant nature video was included as a
        comparison because the flood video included brief built elements, i.e., houses
        being washed away. They are sometimes combined in results for efficiency, but
        yield similar results individually. Questionnaires. Cooperation was assessed with
        the social value orientation slider measure (SVO; Murphy, Ackermann, & Handgraaf,
        2011). Across six items, participants allocated points (imagined as money) to
        themselves and a hypothetical other via a forced choice of nine alternatives that
        vary benefits to self vs. other. Although typically conceptualized as an
        individual difference measure, instructions do not imply anything trait-like, and
        similar measures are sensitive to context (Bekkers, 2004). High scores indicate
        more pro-social choices. SVO scores were missing for two otherwise complete cases.
        Willingness to behave sustainably was assessed with a 30-item questionnaire
        developed by Ferguson, Branscombe, and Reynolds (2011). Participants indicated
        their willingness to engage in a variety of sustainable behaviors, such as,
        “Reduce the amount of warm and hot water used” on a 7-point Likert scale ranging
        from 1 (extremely unwilling) to 7 (extremely willing). Items cover transportation,
        energy and water use, social advocacy, tax support, and regulation support. Scores
        reflect mean ratings, α = .94. Similar to Study 1, mood was assessed with the
        20-item PANAS (PA and NA αs = .91) interspersed with 6 vitality items; state
        nature relatedness was assessed with the INS (plus family and society as foils).
        The full 21-item trait nature relatedness scale (α = .90) was embedded in a
        100-item IPIP (ipip.ori.org) Big Five personality questionnaire, and, as a
        validity check, “Please leave this item blank” was inserted twice.

        <hss>Procedure</hss>

        Participants were directed to a Qualtrics webpage that administered the study.
        Following consent, they completed the personality measures and were then randomly
        assigned to view one of five videos. Following the video, they completed measures
        of mood, INS, cooperation, and willingness.

<hs>  Results</hs>
  ~~~~~~~

Manipulation checks suggested that videos altered pleasantness and nature exposure
relatively independently. In 2 × 2 (valence by environment) ANOVAs, we found significant
effects of valence on positive affect, F(1, 224) = 12.61, p < .001, ηp2 = .053, and
negative affect, F(1, 224) = 33.70, p < .001, ηp2 = .13 (see Table 4 for means).
Corresponding effects of environment were null for positive affect, F(1, 224) = .01, p =
.92, ηp2 < .01, and marginally significant for negative affect, with built videos
producing slightly higher ratings, F(1, 224) = 3.49, p = .06, ηp2 = .015. We also observed
a marginally significant effect of environment on INS, F(1, 224) = 3.46, p = .06, ηp2 =
.015, with nature videos producing higher levels of subjective nature relatedness. Thus,
manipulations functioned largely as expected. Our primary hypothesis was that nature
videos (forest, wolves, and flood) would produce more cooperative choices than built
videos (Las Vegas and old house). A 2 × 2 ANOVA with SVO as the dependent variable
revealed that environment had a significant effect, F(1, 222) = 4.43, p = .04, ηp2 = .020,
with nature videos producing more pro-social responses (and no effect of valence or
interaction).3 We also tested whether this extended to willingness to engage in
environmentally sustainable behaviors, and found a similar effect of environment, F(1,
224) = 4.51, p = .04, ηp2 = .020. However this was qualified by an interaction with
valence, F(1, 224) = 3.96, p = .05, ηp2 = .017.4 Essentially, the built, pleasant, Las
Vegas video produced particularly low levels of willingness compared to the other groups,
which were similar (see Table 4). Exploratory bootstrapping analyses suggested that state
nature relatedness (INS) mediated the effect of videos (nature vs. built) on SVO (95% CI:
.002, 1.45) and willingness (.01, .25; see Fig. 1), though ‘significance’ depended
somewhat on using this approach (cf. Baron & Kenny) and combining the negative nature
videos (see Supplement). Thus, state nature relatedness may account for nature's effects
on cooperation and sustainability, but the evidence is somewhat inconsistent. There was
also a significant correlation between SVO and willingness in this study (r = .28). Thus,
we tested the possibility that SVO mediated the effect of videos on willingness.
Bootstrapping indicated a possible mediation path when negative nature conditions were
combined (95% CI: .002, .16; see Fig. 1), though ‘significance’ again depended somewhat on
this particular approach (see Supplement). The films' effect on sustainability may be due
to shifts in cooperation, but evidence is again somewhat inconsistent. Finally, we also
explored the role of trait nature relatedness and found that it correlated significantly
with SVO (r = .28), INS (r = .61), willingness (r = .64), and positive affect (r = .23),
but typically did not interact with manipulations in predicting these things. In sum, this
study provides a conceptual replication supporting the idea that exposure to nature (in
this case forest, flood, and wolf videos) promotes cooperative decisions, even absent an
environmental context. These effects did not depend on nature's pleasantness, and also
extended to explicit statements about environmental behavior under some circumstances.

<h>GENERAL DISCUSSION</h>
------------------

After finding that short walks in nature produced both pleasant moods and feelings of
nature relatedness, Nisbet and Zelenski (2011) suggested nature as a ‘happy path to
sustainability’. This research takes the critical next step by explicitly testing the link
between nature exposure and sustainable behaviors, rather than inferring this from the
trait–level association between nature relatedness and sustainable behavior. Across three
studies, we found consistent evidence for the idea that exposure to nature (videos) can
produce cooperative behavior, which was also sustainable behavior in the context of
commons dilemmas. Viewing environmental problems as social dilemmas underscores the link
between cooperation and sustainability. Environmental issues are classic examples of
social dilemmas, and cooperation is essential in solving them. In our lab analog, exposure
to nature increased sustainable fishing and helped determine whether or not fish stocks
collapsed. These effects appear to be due to nature per se as both built and neutral
control comparisons produced similar results. Moreover, although pleasant moods are
typically associated with nature, they did not explain its effect on cooperation. Results
held using statistical mood controls, and when we directly manipulated pleasant and
unpleasant representations of nature. The mediation results for state nature relatedness
were inconsistent across studies (significant only in Study 3), and not robust enough to
provide strong evidence for this as the only path. Although it remains plausible that time
in nature fosters connectedness and sustainable attitudes over the long term (Schultz,
2000), different processes may explain nature's effect on cooperative or sustainable
behavior in the moment. That is, repeated experiences in nature, especially pleasant ones,
may foster a more stable sense of nature relatedness, and then a desire to protect nature,
habits of spending more time in nature, associating with individuals and groups that value
nature and sustainable practices, etc. (e.g., Bragg, 1996; Kals, Schumacher, & Montada,
1999; Mayer & Frantz, 2004; Nisbet et al., 2009; Orr, 1993). Such connections likely
develop over time. A single exposure to nature will probably not permanently change a
person's attitudes or behavior, and it is entirely possible that momentary feelings of
connectedness with nature do not cause sustainable choices in the same way that a more
stable sense of a nature related self does. Previous correlational research on these
topics likely speaks more to the stable contents of personality, whereas the studies we
report here deal more with shifts in processing. Momentary nature exposure may produce a
set of changes in emotion and cognition that are temporary and relatively distinct from
personality-level processes. Our studies found little support for improved mood or trust
as reasons that nature influences momentary cooperation or sustainability. Other research
has shown that nature exposure can help restore attention or self-control resources (see
Kaplan & Berman, 2010). Perhaps related to this, two recent articles have found that
nature reduces temporal discounting (Berry, Sweeney, Morath, Odum, & Jordan, 2014; van der
Wal, Schade, Krabbendam, & van Vugt, 2013). That is, nature appeared to shift people's
preferences from immediate gratification to larger but more distant payoffs. Nature's
ability to improve self-control in this way seems very consistent with the more
sustainable strategies we observed in the FISH studies (though our studies did not
guarantee a higher payoff with a long-term strategy). Additional research is needed,
however, to determine which of these, or other, changes are more fundamental to nature
exposure. Said another way, the improvements in sustainable behavior that we observed in
these studies may be due to (mediated by) more basic shifts in delay of gratification. On
the other hand, the measures in Study 3 suggest that there is more than temporal
discounting at stake. The SVO measure is about immediate allocations and seems to measure
prosociality more than self-control (see also Guéguen & Stefan, 2014). In addition, Study
3 included self-reported willingness to perform sustainable behaviors. Nature seemed to
increase these, but the effect was qualified by an unexpected interaction. In addition,
the effect of nature on willingness appeared to be mediated by SVO (prosociality or
cooperation). Thus, we suggest a cautious interpretation of possible momentary changes in
explicit environmental attitudes. Said another way, it is possible that nature's ability
to promote sustainable behavior ‘in the moment’ applies primarily to cooperative contexts
or commons dilemmas (or possibly even an explicit understanding of the choice as a social
dilemma). Nature may shift cooperation more than sustainability per se when the two are
dissociated. As with all meditation claims, determining the exact mechanism(s) of nature's
effect on sustainability and cooperation will take considerable (more) research (see
Bullock, Green, & Ha, 2010). This research bridged gaps between experimental studies of
nature exposure that have not considered sustainable behavior, and correlational studies
that suggest a link between nature relatedness and sustainable attitudes. Like most
experimental studies, our methods trade apparent external validity for methodological
control. Although we argue that they maintain psychological realism, testing
generalizability is clearly an issue for future research. Our participants were all
Canadian students exposed to representations of (not actual) nature, ‘fishing’ in a
simulation for relatively low stakes and in relatively cooperative contexts, or completing
questionnaires in Study 3. In addition, studying the effects and active ingredients of
‘nature’ is tricky given its nearly infinite exemplars and the absence of clear or direct
controls. We began to deal with this issue of stimulus sampling (Wells & Windschitl, 1999)
by comparing four nature videos with four comparison conditions across our studies (i.e.,
Planet Earth, forest, wolves, and flood vs. architecture, grammar podcast, Las Vegas, and
decrepit house). One could develop hypotheses about why, for example, Las Vegas or wolves
might have particular effects beyond the natural-built distinction (indeed, we believe
they must in some ways), but given a 4 vs. 4 comparison, the more parsimonious explanation
seems to be an effect of nature—this is the consistent theme across all stimuli. Still,
despite some breadth across these studies, this research begs for future conceptual
replications, falsification attempts, and search for boundary conditions. Collectively our
results suggest that nature may increase cooperation and sustainable choices, yet
additional exemplars should be tested in future work before considering the matter
settled. As one specific and potentially important example, our nature videos may have
primed the idea of conservation, thus creating demand. Although possible, some design
choices argue against this particular problem: 1) we chose nature videos that excluded
marine life and pro-environmental messages that might make the link obvious; 2) we paid
our research participants for each fish harvested, giving them an incentive inconsistent
with pleasing the experimenter; 3) we used a between-subjects design so that the video
content could not be compared across conditions or become an obvious cue; 4) we crafted a
plausible cover story about the study's purpose (i.e., about personality and reactions to
media) that included distracting measures to support that story. In addition, Study 1
included a funneled debriefing for suspicion, and even with a liberal criterion, less than
10% of participants could identify the study's purpose, and removing these participants'
data had little effect on the results. Finally, there is nothing ‘environmental’ about the
SVO measure in Study 3 where nature again produced cooperative responses. Thus, narrow
priming or demand (i.e., nature videos to conservation) seems like an incomplete
explanation for our results. It seems more plausible that nature could prime cooperation
broadly, similar to, but opposite, the self-sufficiency primed by money (Vohs et al.,
2006). With these caveats in mind, we turn to more speculative implications. As a
methodological note for researchers, nature images or videos are often used as ‘neutral’
stimuli in control conditions. Our results suggest that nature can produce psychologically
meaningful effects, and, thus, its ‘neutrality’ may be unwisely assumed in some research
contexts. For example, a recent registered trial of ‘brain training’ failed to find much
benefit for the cognitive exercises, but participants in a control condition, which
consisted of watching short nature videos, reported significant improvements in
psychological well-being and decreased stress over time (Borness, Proudfoot, Crawford, &
Valenzuela, 2013). Also, three of nine studies in the money priming article just mentioned
included control conditions that seem like nature (e.g., images of fish, a flower poster,
and a seascape poster; Vohs et al., 2006). Appropriate comparison conditions depend on
context, but nature may be appropriate less often than many assume. Outside the lab,
conservation activists have long used nature imagery in persuasive appeals, but recent
messaging around climate change often prefers economic or security arguments. Given the
effects of priming money vs. nature, nature imagery may produce more persuasive appeals or
better reminders to behave sustainably–environmental problems are social dilemmas, and
cooperation is key to sustainable solutions. Future empirical work could compare the
relative efficacy of such appeals more directly. Our research also contributes to a
growing body of work that suggests nature's benefits extend beyond individual well-being,
for example, to prosocial aspirations (Weinstein et al., 2009) and behavior (Guéguen &
Stefan, 2014) and reduced aggression and crime (Kuo & Sullivan, 2001). Such findings,
combined with nature's salubrious effect on socioeconomic health disparities (Mitchell &
Popham, 2008), suggest that societies might consider investing more in nature. Similar to
arguments for public education, providing nature access to all citizens could possibly
provide a net social or financial benefit.


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<ART>Corticospinal excitability is facilitated by combined action observation and motor imagery of a basketball free throw
================================================================================

Authors: David J. Wright, Greg Wood, Daniel L. Eaves, Adam M. Bruton, Cornelia Frank, Zoë C. Franklin
DOI: 10.1016/j.psychsport.2018.08.006
Year: 2018  |  Pages: 114-121
ASJC codes: 3202
Keywords: Mental practice, Motor evoked potentials, Motor simulation, Sport, Transcranial magnetic stimulation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: This experiment investigated the extent to which independent action observation, independent motor imagery and combined action observation and motor imagery of a sport-related motor skill elicited activity within the motor system. Design and method: Eighteen, right-handed, male participants engaged in four conditions following a repeated measures design. The experimental conditions involved action observation, motor imagery, or combined action observation and motor imagery of a basketball free throw, whilst the control condition involved observation of a static image of a basketball player holding a basketball. In all conditions, single pulse transcranial magnetic stimulation was delivered to the forearm representation of the left motor cortex. The amplitude of the resulting motor evoked potentials were recorded from the flexor carpi ulnaris and extensor carpi ulnaris muscles of the right forearm and used as a marker of corticospinal excitability. Results: Corticospinal excitability was facilitated significantly by combined action observation and motor imagery of the basketball free throw, in comparison to both the action observation and control conditions. In contrast, the independent use of either action observation or motor imagery did not facilitate corticospinal excitability compared to the control condition. Conclusions: The findings have implications for the design and delivery of action observation and motor imagery interventions in sport. As corticospinal excitability was facilitated by the use of combined action observation and motor imagery, researchers should seek to establish the efficacy of implementing combined action observation and motor imagery interventions for improving motor skill performance and learning in applied sporting settings.

--------------------------------------------------------------------------------


<hs>  Participants</hs>
  ~~~~~~~~~~~~

An a priori power analysis was conducted using G*Power software to determine the number of
participants required for this experiment. The power analysis was based on the data
reported by Wright et al. (2014), who compared differences in corticospinal excitability
between AO, MI and AOMI of an index finger abduction-adduction movement against a static
hand control condition, and obtained effect sizes ranging from d = 0.68–1.78. Based on the
lowest effect size (d = 0.68) and α set at 0.05, the power analysis indicated that in
order to find significant differences between the experimental conditions and the control
condition, at least 15 participants would be required to achieve a power of 80%. In order
to allow for possible participant dropout or other loss of data, 18 participants were
recruited to participate in this experiment. All 18 participants were male and aged
between 19 and 32 years (mean age 22.61 ± 3.45 years). They were all right-handed, as
assessed by the Edinburgh Handedness Inventory (Oldfield, 1971), and all had at least
moderately good imagery ability, as assessed by the Vividness of Movement Imagery
Questionnaire-2 (Roberts, Callow, Hardy, Markland, & Bringer, 2008; See Table 1). All
participants were novice basketball players, in that they had some experience of playing
the sport in practical physical education lessons at school, but had never played
competitively. Furthermore, none of the participants were susceptible to possible adverse
side-effects of transcranial magnetic stimulation, as assessed by the TMS Adult Safety
Screen (Keel, Smith, & Wassermann, 2001). All participants provided written informed
consent to take part in the experiment, which had been granted ethical approval by the
University Ethics Committee at the host institution.

<hs>  Electromyography and transcranial magnetic stimulation procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

EMG was recorded throughout the experiment using a Delsys Bagnoli 2-channel EMG system
(Delsys Inc, Boston, MA). Prior to electrode attachment, participants were asked to
repeatedly flex and extend their right wrist, mimicking the action of shooting a
basketball free throw, whilst the experimenter felt the participants' right forearm to
identify the flexor carpi ulnaris (FCU) and extensor carpi ulnaris (ECU) muscles. Once
identified, the sites were cleaned using alcohol wipes and surface EMG electrodes were
attached over the belly of both muscles, and a reference electrode was placed on the
olecranon of the ulna bone. Recordings were taken from the FCU and ECU muscles as they are
both active when flicking the wrist to release the ball from the hand during the execution
of a basketball free throw. The EMG signal was recorded using Spike 2 (version 6.18)
software, with a sampling rate of 2 kHz, bandwidth of 20–450 kHz, 92 dB common mode
rejection ratio and >1015 Ω input impedance, received by a Micro 1401–3 analogue-to-
digital converter (Cambridge Electronic Design, Cambridge, UK). Single-pulse TMS was
delivered to the left primary motor cortex using a figure-of-eight shaped coil (two 70 mm
diameter loops), orientated at a 45° angle to the central line between the nasion and
inion landmarks of the cranium (Brasil-Neto et al., 1992), and connected to a Magstim 2002
magnetic stimulator (Magstim, Whitland, Dyfed, UK). The optimal scalp position (OSP) was
identified as the scalp location that produced MEPs of largest amplitude in both muscles,
using a stimulation intensity of 60% maximum stimulator output (e.g., Clark et al., 2004;
Williams et al., 2012; Wright et al., 2014). Once identified, the OSP was marked on a
tightly fitting polyester cap worn by the participants by drawing around the coil with a
marker pen. The coil was held fixed against the OSP using a mechanical arm, and accuracy
of coil placement was ensured throughout the experiment by checking the coil position
frequently in relation to the marking and adjusting the positioning if necessary. Resting
motor threshold (RMT) was then determined for each participant by gradually reducing or
increasing the stimulation intensity, until the minimum intensity capable of producing
MEPs with peak-to-peak amplitudes in excess of 50 μV in five out of 10 trials was
identified (Rossini et al., 1994, 2015). This stimulation intensity, plus 1% of the
maximum stimulator output was identified as the RMT (see Rossini et al., 2015 for
guidelines on TMS procedures). Based on the recommendations of Loporto, Holmes, Wright,
and McAllister (2013) the stimulation intensity for the experiment was set at 110% of each
participant's RMT to reduce the likelihood of direct wave stimulation. Modal values for
the location of the OSP, and mean values for the RMT and experimental stimulation
intensity can be found in Table 1.

<hs>  Experimental procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Participants were seated at a desk in front of a 32-inch Samsung flat-screen TV,
positioned at eye-level at a distance of 90 cm. Their head was placed comfortably in a
custom-built head-and-chin rest, and their hands and forearms rested in a pronated
position on the desktop. The lighting in the room was dimmed and blackout curtains were
drawn along either side of the desk to eliminate any potentially distracting visual
stimuli in the surrounding area. Whilst seated in this position, participants took part in
four experimental conditions within a single testing session on the same day. As shown in
Fig. 1, the four conditions were termed: static observation (control), action observation
(AO), motor imagery (MI) and combined action observation and motor imagery (AOMI). Each
condition required participants to complete a block of 30 repetitions of a 10-s duration
video. One stimulation from the TMS device was delivered per video, resulting in a total
of 30 stimulations per condition. Thirty stimulations per condition were administered as
this is recommended as a sufficient number of stimulations to provide a reliable measure
of corticospinal excitability (Cuypers, Thijs, & Meesen, 2014; Goldsworthy, Hordacre, &
Ridding, 2016). Each stimulation was delivered 4640 ms after the onset of each video, as
this corresponded with the point at which the model flicked their wrist to release the
ball in the action observation video. There was a 3 s rest period between each video,
resulting in a 13 s inter-stimulus interval between trials. This duration inter-stimulus
interval is consistent with TMS safety guidelines and is sufficient time for the effects
of previous stimulations to have subsided (Chen et al., 1997). The total duration of each
experimental condition was 6 min 30 s. Following each condition participants were given a
rest period of approximately 3 min before starting the next condition. This duration rest
period between conditions was appropriate as MEP amplitudes return the baseline levels
after 1 min (Baldi, Perretti, Sannino, Marcantonio, & Santoro, 2002), and it is also
consistent with previous TMS experiments exploring AO or MI processes (e.g., Loporto,
McAllister, Edwards, Wright, & Holmes, 2012; Wright et al., 2014). The entire experiment,
including participant familiarization, completion of consent forms and questionnaires, EMG
preparation, OSP and RMT procedures, experimental conditions and participant debriefing,
lasted approximately 90 min.

<hs>  Static observation (control) condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the static observation condition, participants were shown a silent video, filmed from a
third-person visual perspective (see Fig. 1), depicting a male basketball player standing
still on a basketball free throw line and holding a basketball. Participants were
instructed to observe the videos and were reminded of this instruction verbally every 10
trials.

<hs>  Action observation (AO) condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the AO condition, participants were shown a video of the same male basketball player
shooting a successful basketball free throw. In this video, filmed from the same third-
person visual perspective as the static observation condition, the model bounced the
basketball twice before shooting a right-handed free throw that went straight through the
hoop without hitting the rim or backboard. The sounds of the ball being bounced twice
during the model's pre-performance routine, the ‘swish’ of the ball going through the net,
and the ball bouncing after the shot landed were all audible in the video. Participants
were instructed to observe the videos and were reminded of this instruction verbally every
10 trials.

<hs>  Motor imagery (MI) condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the MI condition, participants were shown a video of a black screen, but heard the same
audio recording as in the AO condition. Participants were instructed to actively imagine
themselves shooting a successful basketball free throw in time with the audio recording.
No specific instructions were provided regarding which perspective participants should
image from, but they were instructed to focus specifically on imagining the feelings and
sensations associated with flicking the wrist as they released the ball. Kinesthetic
imagery instructions were emphasized explicitly as these have been shown to facilitate
corticospinal excitability to a greater extent than visual imagery (Stinear, Byblow,
Steyvers, Levin, & Swinnen, 2006). Participants were reminded of this instruction verbally
every 10 trials. In addition, prior to beginning this condition, participants were asked
to keep their eyes open during their imagery to maintain consistency across conditions.
They were also reminded that they could refer to their mimicking of the wrist flick action
during the EMG preparation procedures to recall the kinesthetic sensations associated with
executing the movement.

<hs>  Combined action observation and motor imagery (AOMI) condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the AOMI condition, participants were presented with the same visual and auditory
stimuli they had seen in the AO condition, but were instructed to actively imagine
themselves shooting a successful basketball free throw in time with the video. As in the
MI condition, participants were instructed to focus specifically on imagining the feelings
and sensations associated with flicking the wrist as they released the ball. Participants
were reminded of this instruction verbally every 10 trials.

<hs>  Order of conditions</hs>
  ~~~~~~~~~~~~~~~~~~~

Experimental conditions were always presented in the following fixed order: static
observation, AO, MI, AOMI. The decision to utilize a fixed order of conditions was taken
for several reasons. The static observation condition was always presented first to
acquire a baseline MEP amplitude value before any action observation or motor imagery had
taken place. This was important to reduce the chance of participants engaging in
spontaneous or deliberate motor imagery during control trials, by virtue of having already
being exposed to imagery instructions or the action observation stimuli. Similarly, the AO
condition was presented next, before any imagery instructions were provided, in an attempt
to reduce the likelihood of knowledge of prior imagery instructions eliciting forms of
imagery in this condition. The MI condition was then presented as the third condition,
after AO, as it was deemed necessary to have first exposed participants to basketball free
throw stimuli to allow them to image the action, due to their novice status. The AOMI
condition was then presented last as it was important for participants to have experienced
both AO and MI conditions independently to allow them to be combined effectively. This
approach to ordering conditions is consistent with previous TMS research using a similar
experimental design (Wright et al., 2014, 2016).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

An increase in EMG activity at the time of stimulation can result in an increase in the
amplitude of the subsequent MEP (Devanne, Lavoie, & Capaday, 1997; Hess, Mills, & Murray,
1987). As such, the amplitude of each participant's EMG activity in the 200 ms prior to
each stimulation was measured in both muscles. Any trials in which this value was greater
than 2.5 SD above the mean of that participant's baseline EMG for that muscle were removed
from the analysis (Loporto et al., 2013; Wright et al., 2014). This resulted in a mean of
2.35 (±0.86) trials being removed per participant from each muscle in each condition, and
so no participants were removed from the experiment due to excessive loss of data. The
peak-to-peak amplitude of MEPs in the remaining trials was then measured. Due to large
intra- and inter-participant variability in MEP amplitude, these data were normalized
using the z-score transformation commonly used in TMS action observation and imagery
research (e.g., Aglioti, Cesari, Romani, & Urgesi, 2008; Fadiga et al., 1995; Wright et
al., 2014). The normalized MEP amplitude data were then analyzed with a 2 (muscle) x 4
(condition) repeated measures analysis of variance (ANOVA), using the IBM SPSS Statistics
21 software package. Whilst no significant differences were predicted between muscles due
to both muscles having similar involvement in the execution of a basketball free-throw,
muscle was included as a factor in the ANOVA as it was prudent to first examine whether
differences between muscles existed before exploring differences between conditions. Where
Mauchly's test indicated that the assumption of sphericity had been violated, the degrees
of freedom were corrected using the Greenhouse-Geisser method. The alpha level for
statistical significance was set at α = .05 and effect sizes are reported as Cohen's d.
Post-hoc pairwise comparisons with the Bonferroni adjustment were used to explore
significant effects.

<h>RESULTS</h>
-------

Table 2 shows the raw MEP amplitude data obtained from each muscle in each condition. Due
to the large variability both within and between participants in the raw MEP amplitudes,
this data was normalized using the z-score transformation. Fig. 2 shows the normalized
z-score MEP amplitude data. In this figure, a value of zero indicates the mean MEP
amplitude across all conditions, with the positive and negative values indicating by how
many standard deviations a particular condition was above or below the mean of all
conditions, respectively. The 2 (muscle) x 4 (condition) repeated measures ANOVA performed
on the z-score MEP amplitude data showed no significant main effect for muscle, F(1, 17) =
0.59, p = .45. There was, however, a significant main effect for condition, F(3, 51) =
6.21, p = .001. Post-hoc pairwise comparisons with the Bonferroni adjustment showed that
MEP amplitude in the AOMI condition was significantly larger than in both the static
observation (p = .03, d = 0.75) and action observation (p = .05, d = 0.71) conditions (see
Fig. 2). No other pairwise comparisons were statistically significant. The muscle ×
condition interaction was not significant, F(1.8, 30.61) = 0.07, p = .91.

<h>DISCUSSION</h>
----------

The aim of this experiment was to establish the effects of different action observation
and motor imagery conditions on corticospinal excitability for a sport-related motor
skill. Specifically, the amplitude of MEPs obtained during AOMI, independent AO and
independent MI of a basketball free throw task were compared against a control condition.
MEP amplitudes were significantly larger during AOMI, compared to both the control
condition and the independent AO condition. There was no difference in MEP amplitude
between either the independent AO or independent MI conditions and the control condition.
As the amplitude of the MEP provides a marker of corticospinal excitability (Naish et al.,
2014), these results indicate that in the current experiment corticospinal excitability
was only facilitated by AOMI, but not by independent AO or MI. This finding of increased
activity in the motor system during AOMI supports previous research showing increased
neurophysiological activity in various motor regions of the brain during AOMI conditions
using TMS (e.g., Mouthon et al., 2015; Ohno et al., 2011; Sakamoto et al., 2009; Wright et
al., 2014; Wright et al., 2016), EEG (e.g., Berends et al., 2013; Eaves, Behmer, et al.,
2016) and fMRI (e.g., Nedelko et al., 2012; Taube et al., 2015; Villiger et al., 2013).
The findings of the current experiment add to this body of literature by demonstrating
this effect in a sport-related motor skill, as opposed to simple hand movements or
activities of daily living. The facilitation of corticospinal excitability during AOMI is
likely to reflect increased activity in the premotor cortex in this condition. Meta-
analyses of neuroimaging data have shown that the primary motor cortex, to which TMS was
delivered in this experiment, is not reliably activated during MI or AO (Caspers, Zilles,
Laird, & Eickhoff, 2010; Hardwick et al., 2017; Hétu et al., 2013). The primary motor
cortex, however, is linked to the premotor cortex by strong cortico-cortical connections
(Fadiga, Craighero, & Olivier, 2005). Hardwick et al. (2017) recently demonstrated that
the dorsal (PMd) and ventral (PMv) premotor cortices are activated consistently by both AO
and MI. Although both simulation states can evoke activity in the premotor regions, multi-
voxel pattern analysis has shown that AO and MI produce activity in topographically
distinct regions of the premotor cortex. For example, Filimon, Rieth, Sereno, and Cottrell
(2015) reported that anterior regions of PMd and posterior regions of PMv are more active
during MI, whilst lateral and posterior regions of PMd and anterior regions of PMv are
more active during AO. It is therefore possible that instructing participants to engage
simultaneously in AOMI would produce increased and more widespread activity throughout the
premotor cortex than independent AO or MI. This would manifest in an elevated MEP response
via cortico-cortical connections linking the premotor and motor cortices (Fadiga et al.,
2005) and would explain why the greatest facilitation in corticospinal excitability in
this experiment was found during the AOMI condition. Based on this finding, it is
conceivable that greater improvements in the performance and learning of motor skills may
be obtained through AOMI interventions, compared to the more established use of
independent AO or MI (Holmes & Wright, 2017). Specifically, the increased activity
obtained during AOMI may promote functional connectivity and plasticity within the brain,
facilitating a more efficient motor execution as learning progresses (O'Shea & Moran,
2017; Ruffino, Papaxanthis, & Lebon, 2017). Although longitudinal research incorporating
both neurophysiological and performance measures is required to verify this claim, some
preliminary evidence indicates that AOMI interventions can modulate behavioral outcomes
(see Eaves, Riach, et al., 2016). For example, Romano-Smith, Wood, Wright, and Wakefield
(2018) reported that AOMI interventions can improve aiming performance in a dart throwing
task. In addition, AOMI has been shown to influence automatic imitation effects (Bek,
Poliakoff, Marshall, Trueman, & Gowen, 2016; Eaves, Behmer, et al., 2016; Eaves,
Haythornwaite, & Vogt, 2014) and improve balance (Taube, Lorch, Zeiter, & Keller, 2014),
grip strength (Sun, Wei, Luo, Gan, & Hu, 2016) and hamstring strength (Scott, Taylor,
Chesterton, Vogt, & Eaves, 2017). Whilst further research is required to examine the
effect of AOMI on the performance and learning of motor skills, there are possible
explanations for why AOMI interventions may provide an effective tool for sport
psychologists and athletes. One possibility is that AOMI interventions may contribute to
improvements in motor performance and learning by developing athletes' mental
representation of a skill. Mental representations are cognitive representations for motor
actions comprising a compilation of body postures and associated sensory consequences,
known as basic action concepts, that are related functionally and biomechanically to the
successful execution of a motor skill (Frank, Land, & Schack, 2013; Schack, 2012). These
mental representations are encoded in long-term memory and guide motor skill execution
(Land, Volchenkov, Bläsing, & Schack, 2013; Schack & Mechsner, 2006). According to Schack
and Mechsner (2006), expert performers have mental representations that are highly
organized and closely related to the functional demands of the skill, whereas the mental
representations of novices are comparatively less organized and less closely related to
the functional demands of the skill. Frank et al. (2013) demonstrated that mental
representations of novices became functionally more organized as performance improved
following physical practice. Recent research indicates that the structure of novices'
mental representations can also be developed through both AO (Frank, Kim, & Schack, 2018;
Kim, Frank, & Schack, 2017) and MI (Frank, Land, Popp, & Schack, 2014; Kim et al., 2017)
interventions. Although both AO and MI contribute to the development of mental
representations of action, it is possible that they do so through different mechanisms
(Kim et al., 2017). AO provides a visual representation of an action, typically without
the deliberate generation of associated kinesthetic sensations. As such, AO may enhance
the structure of mental representations primarily through developing the sequencing and
timing of different basic action concepts. In contrast, MI involves the generation of
visual and kinesthetic aspects of a movement and so may enhance an individual's mental
representation primarily by developing the sensory consequences associated with different
basic action concepts. By combining the two techniques, AOMI interventions may develop the
mental representation of a skill by enhancing both the sequencing between basic action
concepts and the associated sensory consequences, and this in turn may lead to
improvements in motor skill performance and learning. In this experiment, corticospinal
excitability was not facilitated by either independent AO or independent MI. This finding
was somewhat unexpected as it is well-established in the TMS literature that both AO
(e.g., Naish et al., 2014) and MI (e.g., Grosprêtre et al., 2016) usually facilitate
corticospinal excitability, relative to control conditions. This effect has been
demonstrated in sport-related tasks for both AO (e.g., Aglioti et al., 2008; Wrightson,
Twomey, & Smeeton, 2016) and MI (e.g., Fourkas, Bonavolontà, Avenanti, & Aglioti, 2008;
Wang et al., 2014). Although this finding conflicts partially with our hypothesis and with
previous TMS research on this topic, it could be explained by the choice of stimuli used
for the control condition in this experiment. There are inconsistencies in the choice of
control conditions used across experiments exploring AO, MI or AOMI with TMS (Loporto,
McAllister, Williams, Hardwick, & Holmes, 2011). Rest (e.g., Wang et al., 2014),
observation of blank screens (e.g., Wrightson et al., 2016), fixation crosses (e.g.,
Sakamoto et al., 2009) or static images of the body or a body part (e.g., Aglioti et al.,
2008; Wright et al., 2014) are all common choices of control stimuli. Loporto et al.
(2011) suggest that the use of a static image of a body or body part as the control
condition is the most appropriate as it ensures that any facilitation of corticospinal
excitability during observation or imagery conditions is related to the observation or
imagery of biological movement. In contrast, when using a fixation cross or blank screen
it is not possible to determine whether a facilitation effect is due to the observation or
imagery of biological movement per se, or rather just the presence of some form of visual
stimuli on screen or the involvement of some form of cognitive activity (Loporto et al.,
2011). The use of a static image of the body was, therefore, chosen deliberately for this
experiment to provide a more stringent control condition against which the effects of the
three different interventions could be compared. The fact that only AOMI produced a
facilitation of corticospinal excitability relative to this stricter control condition
provides justification for the use of AOMI, rather than independent AO or independent MI
interventions. Although this experiment is the first to demonstrate the effects of AOMI of
a sport-related motor skill on corticospinal excitability, it is important to acknowledge
several possible limitations associated with the experiment. First, the four conditions
were presented in a fixed order, rather than being randomized or counterbalanced
throughout the experiment. As participants always completed the AOMI condition last, it is
possible that the enhanced MEP amplitude in this condition was due to either increased
familiarity with the stimuli, or a carry-over effect whereby MEP amplitude was enhanced
during the final condition due to residual corticospinal activity from the previous
conditions. Although these explanations are plausible, Loporto et al. (2012) showed in two
experiments that MEP amplitude did not change over the course of observing five blocks of
the same action observation stimuli. In addition, the current experiment utilized a 3 min
rest period between conditions as Baldi et al. (2002) showed that MEP amplitudes return to
baseline levels after only 1 min. Taken together, it is therefore unlikely that the
increased effect reported in the AOMI condition is due to familiarity with the stimuli or
carry-over effects. Instead, the finding for the AOMI condition is likely to reflect
increased activity in the premotor cortex resulting from combining the two simulation
states. Second, imagery perspective may have differed between the MI and AOMI conditions.
Participants were told to image the feelings and sensations associated with executing the
free throw, but were not instructed to use a specific imagery perspective in either
condition. The third-person perspective of the video in the AOMI condition may have
encouraged imagery from this perspective, whereas first- or third-person perspectives may
have been used in the MI condition, depending on an individual participant's perspective
preference. Imagery from a third-person perspective may produce MEPs of larger amplitude
(Fourkas, Avenanti, & Aglioti, 2006), although it may also be more difficult to generate
kinesthetic imagery from this perspective (Callow & Hardy, 2004). Given this conflict,
future research should provide a stricter control of imagery perspective. It may also be
worthwhile to investigate the effects of manipulating different AO and MI perspective
combinations within AOMI interventions on various neurophysiological and behavioral
measures. A final issue to be acknowledged is that the present experiment used novice
participants rather than experienced basketball players. Neurophysiological activity
during AO and MI differs between experts and novices. Specifically, expert performers in a
variety of skills typically exhibit increased neurophysiological activity during AO and MI
compared to novices (Aglioti et al., 2008; Calvo-Merino, Glaser, Grezes, Passingham, &
Haggard, 2005; Fourkas et al., 2008; Mizuguchi & Kanosue, 2017). As such, the direction of
the effects reported here would likely replicate in an expert sample, although the
magnitude of the effects may be enhanced. This would be a worthwhile area for future
research investigating the neurophysiological effects of AOMI interventions. In
conclusion, the main finding of this experiment is that AOMI of a basketball free throw
facilitated corticospinal excitability relative to the control condition, but independent
AO or MI had no such effect. This finding has important implications for the design and
delivery of sport psychology interventions aimed at improving sport performance and
enhancing motor skill learning. Independent AO (Ste-Marie et al., 2012) and independent MI
(Cumming & Williams, 2012) are well-established techniques that are used widely for
improving motor skill performance and learning. The mechanism by which these methods are
effective is through producing activity in brain regions that are involved in motor
execution (Jeannerod, 2001). The findings of the current experiment indicate that greater
activity in the motor system occurs when AO and MI are combined into a single intervention
strategy. As such, implementing AOMI interventions may offer a more effective method for
improving motor skill performance and learning than the independent use of either
technique. There is, however, currently a lack of research examining the effects of AOMI
interventions on the performance and learning of motor skills. Future research should
therefore first attempt to identify the efficacy of AOMI interventions for improving
movement outcome and technique across a range of skill types, for both novice and expert
performers. Research could then explore optimal methods for delivering AOMI interventions
by, for example, establishing the efficacy of different visual perspectives for AOMI or
the effects of introducing MI alongside AO gradually in a layered manner.


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<ART>Costs and Benefits of Imperfect Cognitions
==========================================

Authors: Lisa Bortolotti, Ema Sullivan-Bissett
DOI: 10.1016/j.concog.2015.03.013
Year: 2015  |  Pages: 487-489
ASJC codes: 3204, 3205

--------------------------------------------------------------------------------


<h>WHAT ARE THE BENEFITS OF EPISTEMICALLY FLAWED BELIEFS?</h>
------------------------------------------------------

Lisa Bortolotti is interested in the potential benefits of irrational beliefs, and she
focuses on pathological beliefs. In particular, she discusses those delusions that have
been construed as playing a defensive function, such as Reverse Othello syndrome,
erotomania, and anosognosia. Such delusions are wildly implausible, but at the time at
which they are endorsed, they may carry both psychological and epistemic benefits. They
act as a defence protecting agents from low self-esteem and the potentially disruptive
consequences of overwhelming negative emotions. In virtue of such benefits, they also
allow agents to avoid depression and continue interacting with the surrounding physical
and social environment in a way that may be conducive to feedback from social exchanges
and to the acquisition of useful information. To characterise cognitions that are
typically false and irrational but may also carry benefits of this sort, Bortolotti
introduces the notion of epistemic innocence which captures the status of cognitions that
have some significant epistemic benefit and whose benefit could not be attained by other
means. To show that at least in some circumstances there may be no alternatives to a
delusional belief, Bortolotti argues that in anosognosia people do not have direct
evidence of their impairments and are unable to integrate indirect evidence about their
impairments in their concept of themselves. This means that one plausible alternative to
the delusional belief that they are not impaired, that is, the belief that they are
impaired, may not be available to them. Bortolotti concludes that, in the case of
motivated delusions, psychological benefits can turn into epistemic ones. In their paper,
Maarten Boudry, Michael Vlerick, and Ryan McKay revisit the contribution of the friends of
ecological rationality to the rationality debate in cognitive science. The rationality
debate concerns the implications of people failing simple inductive and deductive
reasoning tasks in experimental settings. The friends of ecological rationality correctly
point out that failure in solving the reasoning tasks may be explained in some
circumstances by the fact that the tasks are presented in a misleading way. But they also
defend a more general and stronger claim, the claim that heuristics regarded as
epistemically flawed or biased can be shown to be ecologically rational. This is the claim
Boudry and colleagues find problematic. Some of the heuristics responsible for reasoning
mistakes can be adaptive, but they cannot be redeemed as rational. Boudry and colleagues
illustrate the difference between adaptiveness and rationality with the example of
superstitious beliefs and fast-and-frugal heuristics. Superstitious beliefs may be
adaptive (as in some environments genetic fitness may be enhanced in organisms that avoid
risks) but this does not make them rational (as they are badly supported by the evidence
and fail to track the truth). A fast-and-frugal heuristic such as the recognition
heuristic is useful when people are asked to make a choice in a situation of ignorance.
They select better-known versus less well-known items, and this can lead them to making
the right choice in some environments. But in advertising the recognition heuristic is
exploited: the presence of a known brand determines a consumer’s choice, and other
relevant factors such as product quality are not taken into account. Heuristics are
effective in some domains, and misfire in others. Their local adaptiveness is definitely a
benefit, but it is not a good indication of their epistemic rationality.

<h>WHAT ARE THE BENEFITS OF DISTORTED MEMORIES?</h>
--------------------------------------------

Jordi Fernandez argues that memories have (at least) two types of functions and two types
of benefits. They preserve information about the past (narrative function) and they are
reconstructions of events that engage the same capacities involved in imagination and are
aimed to build a narrative (reconstructive function). They can provide good evidence about
the past, thereby allowing the subject to represent the past accurately (which is
epistemically beneficial); and they contribute to the formation of beliefs about the past
that have an instrumental value for the agent, thereby allowing the agent to satisfy some
of her goals (which is adaptively beneficial). Depending on the agent’s goals, the
epistemic benefits and the adaptiveness of memories can be related. In the paper,
Fernandez asks whether two forms of memory distortions—observer memories and fabricated
memories—can be adaptive. In the context of trauma, observer memories enable agents to
obtain some affective relief in the short term, but may hinder their capacity to develop a
coherent and healthy self-concept in the long term. In the context of false memories of
abuse, memories can respond to a need for explanation thereby relieving internal tensions,
but can cause emotional damage and compromise personal relationships. The interesting
result is that, if we take memory to have only a narrative function, then observer
memories and fabricated memories are not distorted. They have been produced to further the
goals of the agent, not to represent the past correctly. But if we take memory to have
only a preservative function, then observer memories and fabricated memories have no
benefits, because the only benefits that count are epistemic ones. Fernandez argues that
both conclusions are unattractive and that the case of beneficial memory distortions
suggests that we should take an inclusive approach to the functions of memory. Martin
Conway and Catherine Loveday reach a similar conclusion to Fernandez, that false memories
can have significant benefits for an agent, but start from a more radical position in that
they downplay the preservative function of memory, based on empirical investigations of
how memory works. Memories and imagined events are constructed in a similar way,
inferentially, via the so-called “remembering–imagining system”, and the accuracy of
autobiographical memories is understood in terms of the relationship between
correspondence (how the memory captures an experienced event) and coherence (how the
memory coheres with other beliefs about the self). Whereas a memory can succeed in its
coherence, it can never fully succeed in its correspondence as it will always be partial
and to some extent distorted. No memories represent events “literally” and maybe they are
not supposed to do so. The main function of memory is to “generate personal meanings”,
that is, to provide an understanding of the world that allows agents to successfully adapt
to it.

<h>WHAT IS PATHOLOGICAL IN DELUSIONAL BELIEFS?</h>
-------------------------------------------

Aikaterina Fotopoulou argues that, just as the past self is known via inference from
autobiographical memory, so the present self is known via perceptual inference. Due to its
indirect nature, representations of the past and present self are imperfect, both in the
context of normal perceptual inference and of pathological conditions such as anosognosia
for hemiplegia. Consistent with the prediction–error model, in Fotopoulou’s account the
brain predicts the hidden causes of sensory inputs and revises such predictions in order
to minimise errors. There some delusional beliefs emerging in anosognosia, such as the
illusion of movement and the adherence to the denial of paralysis even after the paralysis
has been acknowledged. How can these beliefs be explained? A temptation is to rely on a
multiplicity of distinct factors, where the hypothesis is that both perception and
reasoning are damaged. But Fotopoulou argues instead that we should just focus on
perceptual inference. In anosognosia prediction errors are absent or unreliable and this
results in patients making inferences from out-of-date models of their motor abilities.
More specifically, in Fotopoulou’s account, anosognosia is due to an inability to update
bodily awareness in the light of new information about the affected body parts and to
integrate first- and third-person perspectives on the body. Anosognosia for hemiplegia is
just an exaggeration of the imperfection of bodily awareness. Kengo Miyazono also
considers the costs of delusional beliefs, and attempts to account for their pathological
nature. What is the difference between everyday irrational beliefs, such as the
unjustified belief in the infidelity of one’s spouse or common instances of self-
deception, and delusional beliefs that are symptoms of schizophrenia and delusional
disorders? Miyazono critically assesses several answers provided in the literature and
dismisses them: delusions are not necessarily more bizarre, more irrational, or less
understandable than non-delusional beliefs. Moreover, it is not always the case that a
person with delusions lacks responsibility for the actions guided by her delusional
beliefs. Miyazono’s positive account is that delusions are pathological because they
involve a harmful biological malfunction. Delusions are harmful because they disrupt good
functioning and often negatively affect the quality of life of people who report them.
Delusions are malfunctioning beliefs because the processes by which they are formed are
abnormal in some important respect (that is, in some respect other than statistical
normality), where the respects in which the process malfunctions vary according to one’s
preferred aetiological account of delusions. In the person who forms delusions, either
experience is abnormal or, additionally, there are deficits concerning attention and
reasoning.

<h>WHAT ARE THE COSTS AND BENEFITS OF IMPLICIT COGNITIONS?</h>
-------------------------------------------------------

Jules Holroyd investigates responsibility for implicit biases and the actions resulting
from them. Holroyd considers three epistemic conditions for responsibility for implicit
bias, endorsing the third, which is that one should have observational awareness of the
effects of implicitly biased behaviour. Observational awareness is being aware that one’s
behaviour has some morally undesirable property, for example, the property of being
discriminatory. According to Holroyd, we should not be asking whether agents do, as a
matter of fact, have observational awareness of their biased behaviour, but rather,
whether they ought to have this awareness, and whether they are culpable for not having
it. Drawing on empirical work, Holroyd argues that agents can have observational awareness
of their discriminatory behaviours that are based on implicit attitudes. She also argues
that agents ought to have this awareness, and resists the claim that agents are not
responsible for behaviours manifesting biases because biased actions are guided by
implicit cognitions. Finally, Holroyd considers the role of other imperfect cognitions in
relation to implicit biases, specifically, failures of attentiveness, and self-deception.
She suggests that an investigation into whether agents are responsible for actions guided
by implicit biases may in part depend on the relationship between implicit biases and
other imperfect cognitions. Ema Sullivan-Bissett is interested in the epistemic status of
confabulatory explanations of decisions or actions guided by implicit bias. She is keen to
resist the trade-off view of imperfect cognitions; that a cognition enjoys pragmatic
benefits at the expense of epistemic ones. To this end, she too appeals to the notion of
epistemic innocence. She focuses on two imagined cases of decisions or actions guided by
implicit biases. Via an analysis of these cases, she argues that at least sometimes,
confabulatory explanations of decisions or actions guided by implicit bias are
epistemically innocent. First, they may be epistemically beneficial. They fill an
explanatory gap, potentially leading to the acquisition and retention of true beliefs and
knowledge, and they also help to maintain consistency between an agent’s beliefs. Second,
alternative (more epistemically worthy) explanations that could confer these benefits are
unavailable. Sullivan-Bissett concludes that when we are in the business of epistemic
evaluation, we should consider both the epistemic benefits of an imperfect cognition, and
the context in which it occurs.

<h>CONCLUSIONS</h>
-----------

We believe that the eight papers in this issue initiate a much needed interdisciplinary
dialogue on imperfect cognitions, and make substantial progress in answering key research
questions about the types of costs and benefits that such cognitions in the clinical and
non-clinical population may have. Hopefully the ideas presented here will also stimulate
further empirical research and conceptual investigation into different forms of imperfect
cognitions, and help sketch a more psychologically realistic account of human agency and
cognition.
<ART>Creativity and personality in classical, jazz and folk musicians
================================================================

Authors: Mathias Benedek, Barbara Borovnjak, Aljoscha C. Neubauer, Silke Kruse-Weber
DOI: 10.1016/j.paid.2014.01.064
Year: 2014  |  Pages: 117-121
ASJC codes: 3200
Keywords: Creativity, Divergent thinking, Music genre, Music learning, Personality

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The music genre of jazz is commonly associated with creativity. However, this association has hardly been formally tested. Therefore, this study aimed at examining whether jazz musicians actually differ in creativity and personality from musicians of other music genres. We compared students of classical music, jazz music, and folk music with respect to their musical activities, psychometric creativity and different aspects of personality. In line with expectations, jazz musicians are more frequently engaged in extracurricular musical activities, and also complete a higher number of creative musical achievements. Additionally, jazz musicians show higher ideational creativity as measured by divergent thinking tasks, and tend to be more open to new experiences than classical musicians. This study provides first empirical evidence that jazz musicians show particularly high creativity with respect to domain-specific musical accomplishments but also in terms of domain-general indicators of divergent thinking ability that may be relevant for musical improvisation. The findings are further discussed with respect to differences in formal and informal learning approaches between music genres. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Within the field of music, jazz is commonly considered as a particularly creative
discipline (e.g., Barrett, 1998). This appraisal is related to the fact that jazz music
involves a high degree of improvisational playing. Jazz improvisation can range from the
simple embellishment of the melody of the theme to e.g. the continuous extemporization of
entirely new melodies that fit to the sequence of chords (Johnson-Laird, 2002; Pressing,
1988). Jazz musicians who are highly skilled in improvising hence may possess traits that
are different from those of musicians in other disciplines such as classical music. So
far, only little is known about the individual differences between musicians devoted to
different music genres. Therefore, this study compared jazz musicians with musicians of
classical and folk music with respect to their musical activities, creativity and
personality. Only few studies have investigated specific differences in attitudes, and
learning approaches of musicians specialized in different music genres (e.g., Bézenak &
Swindells, 2009; Creech et al., 2008; Papageorgi, Creech, & Welch, 2013; Welch et al.,
2008). Classical musicians are reported to acquire musical skills mainly in formal
educational settings involving one-to-one instruction and by practicing alone, whereas
non-classical musicians devote more time to extra-curricular activities such as playing
music for fun with others or having professional conversations (Bézenak & Swindells, 2009;
Welch et al., 2008). Additionally, classical musicians attach greater importance on
technical proficiency involving sight-reading, notation, and quality of tone, whilst non-
classical musicians appear to attach greater importance to skills such as memorization or
improvisation (Bézenak & Swindells, 2009; Creech et al., 2008). Bézenak and Swindells
(2009) found that jazz musicians show higher intrinsic motivation and experience more
pleasure in musical activities than classical musicians. In contrast, classical musicians
report higher levels of performance anxiety than other non-classical musicians (Papageorgi
et al., 2013). These findings already suggest important differences in the general
approach towards learning and playing music between different genres such as jazz and
classical music. Research also addressed the question what factors lead to expert
performance in music and more specifically in improvisational skills. It is now widely
accepted that the cumulative amount of deliberate practice but also the quality of
practice is highly predictive of mastery in the domain of music (Ericsson, Krampe, &
Tesch-Römer, 1993; Williamon & Valentine, 2000). Additionally, there is evidence that
individual differences in domain-general cognitive abilities also contribute to expert
performance (Hambrick et al., in press). Beaty, Smeekens, Silvia, and Kane (in press)
report a study where ten jazz students were video-taped during improvisation performances
on a piece unknown to them, which then was rated for creativity by three professors of
jazz studies. They found that creativity of improvisation was independently predicted by
practice hours and divergent thinking ability (i.e., a common indicator of creative
potential) of the jazz students. The findings suggests that divergent thinking, commonly
defined as the ability to fluently generate original and appropriate ideas, may represent
a relevant ability supporting improvisational creativity. This notion is in line with
formal models of jazz improvisation stating that improvisation requires the continuous
generation and evaluation of musical ideas (Pressing, 1988). Similarly, divergent thinking
is considered as a central factor underlying creative thinking in music according to
Webster’s model (2002), together with certain differences in personality and motivation.
As a consequence, jazz musicians who are highly skilled in improvisation may differ in
their creativity and personality from musicians of other genres. The aim of this study is
to formally test this hypothesis by comparing Jazz musicians with musicians specialized in
classical and folk music.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 120 students enrolled in the study of instrumental pedagogy at the University
of Music and Arts in Graz participated in this study. They majored in various different
musical instruments (e.g., piano, violin, voice), but were enrolled in one of three tracks
related to a specific genre of music: classical music, jazz music, or folk music. The
study curriculum is largely the same for all three genres, but classical and folk
musicians have more courses on analyzing theoretical aspects of music as compared to Jazz
musicians, who attend more courses focused on improvisational skills, ensemble playing and
developing practical musical skills. The curriculum of folk musicians specifically
requires the playing of at least two folk instruments and offers supplementary classes on
folk dance or yodeling. We excluded seven participants who were enrolled in more than one
music program and hence could not be attributed unambiguously to one music genre.
Moreover, we included only students who indicated to have good to excellent language
skills, leading to the exclusion of another 14 participants. The remaining sample
consisted of 99 students, including 52 students of classical music, 25 students of jazz
music, 21 students of folk music. On average, students had an age of 24.8 years (SD =
5.6), and have been studying music for 2.6 years (SD = 1.8). The sex distribution was
fairly balanced with 47% females. The music groups did not differ in their age (F[2,95] =
2.25, p = .11), nor sex ratio (χ2[2] = .08, p = .96), but jazz students on average
reported a longer duration of study (F[2,84] = 9.69, p = .001, partial-η2 = .19; classical
music: 2.1 years; jazz music: 3.9 years; folk music: 2.4 years). For analyses involving
speeded creativity tests we only included participants with German as mother tongue,
resulting in 70 students (30 classical music, 22 jazz music, 18 folk music).

        <hss>Study and practice activities</hss>

        We assessed relevant socio-demographic information including age, sex,
        nationality, selected study programs, and students gave a self-assessment of
        language skills (“excellent”, “good”, “fair”, or “bad”). They were asked how many
        hours they typically practiced their instruments at every single day of the week.
        This data was used to compute a reliable estimate of the practice hours per week.
        Finally, participants indicated how many concerts they play per semester, and how
        many competitions they had participated, how often they had won competitions, and
        how many productions they had published so far.

        <hss>Creativity assessment</hss>

        Creative cognitive potential in the verbal domain was assessed with four divergent
        thinking tasks taken from a well-known German creativity test (Verbaler-
        Kreativitätstest; VKT; Schoppe, 1975). The tasks included two alternate uses tasks
        asking participants to generate different creative uses for a “tin can” and a
        “simple string”, and two instances tasks which asked to generate many things that
        could be used “for faster locomotion” or that are “bendable”. In all tasks,
        participants were instructed to find as many and as creative ideas as possible
        within the given time (120s, or 90s for the alternate uses and the instances task,
        respectively). The performance in the divergent thinking tasks was scored for
        ideational fluency (i.e., number of ideas), and ideational creativity. For the
        scoring of ideational creativity we created lists of pooled, alphabetically
        sorted, non-redundant responses for each task. Four experienced raters rated each
        idea for creativity on a four-point scale (“0, uncreative”, “1, somewhat
        creative”, “2, fairly creative”, and “3, very creative”). We then computed a top-3
        creativity score by averaging the creativity ratings of the three top-most
        creative ideas within each task (Benedek, Mühlmann, Jauk, & Neubauer, 2013). This
        scoring method was found to yield valid scores that show to discriminant validity
        with regard to fluency measures (Benedek, Franz, Heene, & Neubauer, 2012; Benedek
        et al., 2013; Silvia et al., 2008). We averaged scores of the two alternate uses
        tasks and the two instances tasks to obtain one fluency score and one creativity
        score per task type. Additionally, creative potential in the figural domain was
        assessed with a picture completion task taken from the imagination subscales of
        the Berliner-Intelligenz-Test (Jäger, Süß, & Beauducel, 1997). Participants were
        shown a series of abstract lines which had to be completed in an original way to
        form meaningful objects. This task was scored for ideational fluency following the
        instructions of the test manual. Besides creative potential, we also assessed
        real-life creative activities and achievements of the students using the inventory
        of creative activities and achievements (ICAA; described in Jauk, Benedek, &
        Neubauer, 2014). This inventory assesses creative activities and achievements in
        eight domains, including literature, music, arts and crafts, creative cooking,
        sports, visual arts, performing arts, and science and engineering. In the
        activities scale, participants report on a 5-point scale how often they carried
        out certain activities within the last 10 years. In the achievements scale,
        participants marked achievements they had already attained in each domain ranging
        from “I have never been engaged in this domain” (0 points) to “I have already sold
        some of my original work in this domain” (10 points), and values of all
        achievements are summed. Activities and achievements scores can be analyzed
        separately for each domain or as a composite score, after summing across domains.

        <hss>Personality assessment</hss>

        Personality was assessed with respect to the Big Five using the NEO-FFI (Borkenau
        & Ostendorf, 1993). We assessed schizotypy using the German 17-item version of the
        Schizotypical Personality Questionnaire (SPQ; Klein, Andresen, & Jahn, 1997).
        Participants also completed the Error Orientation Questionnaire (EOQ; Rybowiak,
        Garst, Frese, & Batinic, 1999). This questionnaire contains 37 items asking about
        individual attitudes towards errors at work. In this study work was defined as
        practicing and performing activities as a musician. The EOQ consists of eight
        scales, including error competence, learning from errors, error risk taking, error
        strain, error anticipation, covering up errors, error communication and thinking
        about errors. Further questionnaires include the German version of the Frost
        Multidimensional Perfectionism Scale (FMPS; Stöber, 1998), the German Achievement
        Motivation Scale (AMS; Lang & Fries, 2006), rumination scale of the Perfectionism
        Inventory (PI; Hill et al., 2004), the student version of the SELLMO (a German
        questionnaire on learning and achievement motivation; Spinath, Stiensmeier-
        Pelster, Schöne, & Dickhäuser, 2012), and a set of self-devised questions on error
        behavior.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants were tested in groups of 10–25 people in lecture rooms. First, they provided
general information on their person, studies and practicing habits. They then worked on
the divergent thinking tasks, the NEO-FFI, the SPQ, the EOQ, completed a self-devised
questionnaire on error behavior, the ICAA, the FMPS, the AMS, the PI rumination scale and
the SELLMO. The total session took about 90 min.

<h>RESULTS</h>
-------

Potential group differences between musical genres (classical music, jazz, or folk music)
were analyzed by means of ANOVAs with the between-subject factor music genre. In case of
significant group effects, LSD posttests were employed to further examine differences
between group means.

<hs>  Genre-related differences in general musical activities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Students of folk music devote on average 12 h per week on practice, which is significantly
less than the typical practice periods of students of classical music (p = .01) or jazz
music (p = .08), who spend about 18 h a week (F[2,92] = 3.39, p = .04, partial-η2 = .07;
see Table 1). Jazz musicians played significantly more concerts per semester than
classical musicians (p = .001) and folk musicians (p = .001; F[2,92] = 10.78, p = .001,
partial-η2 = .19). On the other hand, jazz musicians participated in a lower number of
music competitions (F[2,92] = 4.16, p = .02, partial-η2 = .08) than classical (p = .01)
and folk musicians (p = .02), and also won a lower number of competitions (F[2,92] = 4.60,
p = .01, partial-η2 = .09). Finally, folk musicians published a significantly higher
number of works than classical musicians (p = .03; F[2,92] = 3.08, p = .05, partial-η2 =
.06).

<hs>  Genre-related differences in creativity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Students of classical, jazz and folk music were compared in their levels of creative
potential, creative musical activities and creative musical achievements. As can be seen
in Table 2, the three groups differed significantly in ideational creativity as measured
by the alternate uses task (F[2,67] = 3.61, p = .03, partial-η2 = .10) and the instances
task (F[2,67] = 3.96, p = .02, partial-η2 = .11). In both tasks, Jazz musicians showed
higher ideational creativity than folk musicians (p = .01, and p = .01) and classical
musicians (p = .09, and p = .02). No additional group differences were observed with
respect to ideational fluency in the divergent thinking tasks (alternate uses task:
F[2,67] = 0.34, p = .71; instances task: F[2,67] = 1.97, p = .15; picture completion task:
F[2,67] = 0.17, p = .85). We then analyzed potential group differences in creative
activities and achievements with a focus on the musical domain. Jazz musicians reported to
have engaged in a significantly higher number of creative musical activities over the last
years (F[2,94] = 20.20, p < .001, partial-η2 = .30) than classical musicians (p < .001)
and folk musicians (p < .001). Moreover, jazz musicians also showed higher creative
achievements in the musical domain (F[2,94] = 15.03, p < .001, partial-η2 = .24) than
classical musicians (p < .001) and folk musicians (p = .003). Notably, these group
differences remained highly significant even after statistically controlling for
differences in age and duration of study. As a side analysis, we also looked for group
differences in other domains measured by the ICAA. The only significant finding was that
folk musicians showed higher creative achievements in the domain of arts and crafts
(F[2,94] = 8.92, p < .001, partial-η2 = .16) than classical musicians (p = .02) and jazz
musicians (p = .02).

<hs>  Genre-related differences in personality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Analyses of group differences in personality structure revealed a significant effect for
extraversion (F[2,96] = 3.88, p = .02, partial-η2 = .08) and an effect by trend for
openness (F[2,96] = 2.42, p = .06, partial-η2 = .05), but not effects for neuroticism,
agreeableness, or conscientiousness (see Table 3). Specifically, folk musicians were found
to be more extraverted than classical musicians (p = .007) and jazz musicians (p = .05).
Classical musicians tend to be less open to new experiences than jazz musicians (p = .06)
and folk musicians (p = .11). The music genre groups did, however, not differ in
schizotypy (F[2,96] = 0.34, p = .72). No further significant group differences were
observed in the motivational measures of this study, including all sub-facets of error
orientation and perfectionism, and indicators of achievement motivation, learning
motivation and rumination.

<h>DISCUSSION</h>
----------

The analysis of general musical activities revealed that the participants, although still
studying at the Arts College, already were very accomplished musicians, completing a high
weekly pensum of practice, playing a considerable number of concerts per year, regularly
participating in music competitions, and having a substantial number of music productions
published. Moreover, the music students already have attained very high levels of creative
achievement in the domain of music, with 8% having accomplished every single musical
achievement listed in the employed inventory. Interestingly, students of different music
genres differed substantially in the relative amount of engagement in these activities.
Classical musicians practice a lot and participate in a high number of competitions, but
do not publish as many music productions as non-classical musicians. In contrast, jazz
musicians perform a larger number of concerts per year but do not participate as often in
music competitions. This confirms recent research showing that classical musicians are
more focused on achievements related to solo professional work, whereas jazz musicians are
more engaged in informal ways of practice by playing lots of concerts (Bézenak &
Swindells, 2009; Creech et al., 2008; Welch et al., 2008). Finally, folk musicians showed
a lower amount of weekly practice but have many performances in concerts, competitions and
music productions. Taken together, these findings support the view that music learning is
not only the product of formal educations systems but also includes different informal
ways of practice (Green, 2002), and that approaches to music learning may differ between
music genres (e.g., Welch et al., 2008). Besides differences in musical activities, music
genre was also related to individual differences in psychometric creativity. As expected,
Jazz musicians showed higher divergent thinking ability (i.e., creative cognitive
potential) in terms of ideational creativity than classical and folk musicians. The
ability to fluently generate original ideas can be considered highly compatible with the
improvisational skills that are required and trained in jazz music, and they may be of
relatively lower significance in classical music or folk music (Pressing, 1988; Webster,
2002). Interestingly, Fink and Woschnjak (2011) reported a similar finding from the domain
of dance. They found that modern/contemporary dancers, who are often required to improvise
on stage, showed higher creative potential than ballet dancers who are normally obliged to
adhere to well-structured choreographies. Of course, one can only speculate about the
causality in the relationship between divergent thinking and improvisation abilities: Is
high divergent thinking ability a precondition for becoming a good jazz musician, or does
continuous improvisation training implicitly increase divergent thinking ability? There is
evidence in support of both perspectives. On the one hand, divergent thinking was shown to
predict improvisational creativity beyond the mere amount of practice (Beaty et al., in
press). On the other hand, extensive engagement in divergent thinking can increase
divergent thinking performance (Benedek, Fink, & Neubauer, 2006) and even have effects on
relevant brain activation patterns (Fink, Grabner, Benedek, & Neubauer, 2006). Thus, both
perspectives may apply to some extent. It would, however, need longitudinal studies to
properly disentangle the relative effects in the causal relationship of creative potential
and improvisation training. As another result, jazz musicians reported to engage in a much
larger number of creative activities in the domain of music than classical or folk
musicians. In this context, it is important to point out that the employed measure of
creative musical activities specifically reflects activities that involve creating
something new but it does not consider playing music as a creative activity per se. Sample
items of this scale include “I reinterpreted a piece of music in a creative way”, “I made
up a melody”, “I made up a rhythm”, or “I artificially created sounds”. These creative
activities are very common during jazz improvisation, whereas classical music usually
involves a flawless reproduction with focus on technical excellence (Bézenak & Swindells,
2009; Creech et al., 2008). To be sure, playing e.g. a Bach sonata also involves
individual expression by giving it a personal note in terms of temper and atmosphere, but
this individuality usually does not go as far as changing the rhythm or melody of the
piece in a substantial way. A similar argument may also explain why jazz musicians showed
much higher creative achievements in the domain of music. Again, the scale explicitly
focuses on achievements related to original pieces of work (e.g., musical compositions or
rearrangements). We also observed differences in personality between musicians of
different genres of music. First of all, folk musicians are more extraverted than
classical and jazz musicians. This finding may be related to the fact that folk music is
commonly played at sociable events involving regular interactions with the audience.
Therefore, the genre of folk music may more likely attract extraverted musicians that
enjoy social interactions as an integral part of their performance. As an interesting
additional finding, folk musicians were more achieved in the domain of arts and crafts.
This may refer to stronger bonds of folk musicians to traditions and related skills in
arts and crafts. We also observed a weak group effect for openness suggesting that jazz
and folk musicians are more open to new experiences than classical musicians. Openness to
new experiences reflects a preference for variety and the readiness to leave beaten paths.
It is consistently related to creativity in the literature (e.g., Feist, 1998; Jauk et
al., 2014) and may also promote the readiness to seek variation in musical play as
required during improvisation. Finally, we did not observe group differences in error
orientation or motivational variables between music genres in this study. This is an
interesting finding as one might have expected that jazz musicians e.g. are more
comfortable with risk taking during their improvisational play. It should be noted,
however, that the EOQ does not differentiate between errors occurring during practice or
performance (Kruse-Weber & Parncutt, 2013). It hence is possible that the questions were
rather attributed to the process of learning rather than to stage performances and thus
errors were conceived as equally important.

<h>CONCLUSIONS</h>
-----------

This study revealed evidence that jazz musicians show higher divergent thinking ability,
and a higher number of creative activities and achievements in the musical domain as
compared to musicians from other genres such as classical music or folk music. These
findings support the view that the music genre of jazz is highly associated with
creativity, both in terms of musical activities and psychometric aspects of musicians. The
observed differences may be related to differences in the formal and informal ways of
practice and learning, with Jazz musicians attaching more importance on informal practice
and playing for fun and lower value on technical perfection and competitions. Finally, the
findings add to the evidence that individual differences in domain-general abilities
(i.e., creative potential) may be relevant for the realization of domain-specific creative
activities and achievements (Jauk et al., 2014; Kaufman & Beghetto, 2009).


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<ART>Creativity on tap? Effects of alcohol intoxication on creative cognition
========================================================================

Authors: Mathias Benedek, Lisa Panzierer, Emanuel Jauk, Aljoscha C. Neubauer
DOI: 10.1016/j.concog.2017.06.020
Year: 2017  |  Pages: 128-134
ASJC codes: 3204, 3205
Keywords: Alcohol, Creativity, Disinhibition, Executive function

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Anecdotal reports link alcohol intoxication to creativity, while cognitive research highlights the crucial role of cognitive control for creative thought. This study examined the effects of mild alcohol intoxication on creative cognition in a placebo-controlled design. Participants completed executive and creative cognition tasks before and after consuming either alcoholic beer (BAC of 0.03) or non-alcoholic beer (placebo). Alcohol impaired executive control, but improved performance in the Remote Associates Test, and did not affect divergent thinking ability. The findings indicate that certain aspects of creative cognition benefit from mild attenuations of cognitive control, and contribute to the growing evidence that higher cognitive control is not always associated with better cognitive performance.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Can alcohol consumption support creative thought by inducing disinhibition, or will it
just impair cognitive control and similarly affect creative cognition? The idea about a
positive relationship between alcohol and creativity has been popularized by reports
associating eminent creativity with excessive alcohol consumption (Knafo, 2008). But
empirical evidence is sparse, and the association between alcohol and creativity seems at
odds with the relevance of cognitive control for creative thought (e.g., Benedek, Jauk,
Sommer, Arendasy, & Neubauer, 2014). Therefore, this study examined the effect of alcohol
on executive control and on standard measures of creative cognition. Creative cognition is
assumed to rely on both controlled, goal-directed and spontaneous, undirected cognitive
processes (Beaty, Silvia, Nusbaum, Jauk, & Benedek, 2014; Benedek & Jauk, in press;
Sowden, Pringle, & Gabora, 2015). Pertinent research mostly focused on divergent thinking
(viz. creative idea generation) and creative problem solving (i.e., problems that can be
solved either analytically or insightfully, which typically implies a restructuring of the
problem representation). The relevance of cognitive control for divergent thinking is
evidenced by consistent correlations with intelligence (Kim, 2005; Silvia, 2015),
particularly with fluid intelligence (Jauk, Benedek, Dunst, & Neubauer, 2013; Nusbaum &
Silvia, 2011) and broad retrieval ability (Avitia & Kaufman, 2014; Benedek, Franz, Heene,
& Neubauer, 2012; Silvia, Beaty, & Nusbaum, 2013). At the level of executive abilities,
divergent thinking has been associated with working memory capacity and cognitive
inhibition (Benedek et al., 2012, 2014; De Dreu, Nijstad, Bass, Wolsink, & Roskes, 2012;
Zabelina, Robinson, Council, & Bresin, 2012). Divergent thinking requires overcoming
prepotent, uncreative response tendencies and involves cognitive strategies (Gilhooly,
Fioratou, Anthony, & Wynn, 2007), which was shown to be facilitated by intelligence (Beaty
& Silvia, 2012; Nusbaum & Silvia, 2011; Nusbaum, Silvia, & Beaty, 2014). While much of the
empirical evidence on creative cognition and cognitive control is based on divergent
thinking, similar evidence also exists for creative problem solving. Creative problem
solving tasks like Duncker’s candle problem or the Remote Associates Test can be achieved
in a strategic way (Fleck & Weisberg, 2004; Smith, Huber, & Vul, 2013), and higher
performance again has been related to intelligence and executive control (Gilhooly &
Fioratou, 2009; Lee, Huggins, & Therriault, 2014). Creativity has also been associated
with disinhibition and spontaneous insight (Eysenck, 1995; Kounios & Beeman, 2014).
Empirical evidence for the relevance of spontaneous, undirected cognitive processes in
creative thought mostly comes from research on incubation processes. Creative problem
solving sometimes leads to an impasse of thought, also known as mental fixation, were
goal-directed solving attempts are no longer fruitful. Incubation research has
demonstrated that breaks from deliberate problem solving can benefit creativity by
refreshing inadequate mindsets while leaving room for unconscious work (Hélie & Sun, 2010;
Sio & Ormerod, 2009). Similarly, while expertise typically supports problem solving by
guiding search through problem space, it can also be detrimental when misdirecting search
efforts to salient but inadequate concepts (Wiley, 1998). Together, these findings suggest
that cognitive control generally supports creative cognition by facilitating the effective
implementation of goal-directed processes, but focused attention may sometimes be
ineffective and potentially even harm creative problem solving (Wiley & Jarosz, 2012). The
role of cognitive control in creative cognition has also been addressed by experimental
studies examining the effects of low to moderate doses of alcohol (i.e., usually inducing
a blood alcohol concentration <0.08) on different measures of creative ability. One study
reported that the fluency of idea generation was reduced in both an alcohol group and a
placebo group compared to the control group (Gustafson, 1991). Another investigation found
that intoxicated writers and non-writers showed reduced idea flexibility but an increased
number of non-obvious, original ideas (Norlander & Gustafson, 1998). Yet another study
observed no notable effects of alcohol on divergent thinking performance, but participants
evaluated their performance as more creative when they thought that they had received
alcohol (Lang, Verret, & Watt, 1984). A more recent study demonstrated that moderate
alcohol intoxication impaired working memory performance, but the intoxicated group showed
higher performance in the Remote Associates Test (RAT) compared to a control group not
receiving any drinks (Jarosz, Colflesh, & Wiley, 2012). Together, the available research
provides partial support for a positive effect of alcohol on creative cognition, but
evidence is still sparse and inconsistent. Part of the inconsistency might be attributed
to missing placebo control groups, and the focus on single measures of creative potential.
People tend to overestimate their creative performance and even become more creative when
they think they have consumed alcohol, which points to the importance to include placebo
control groups in order to dissociate pharmacological effects from expectation effects
(Lang et al., 1984; Lapp, Collins, & Izzo, 1994). Moreover, findings may be specific to
certain aspects of creative cognition such as insight problem solving and divergent
thinking, and even the scoring of divergent thinking tasks can be an issue when focusing
on summative uniqueness, which is known to be severely confounded with response fluency
(Silvia et al., 2008). The present study thus tested the effects of mild alcohol
intoxication in a placebo-controlled design using alcoholic and non-alcoholic beer. We
examined the effects of alcohol on objective and subjective levels of intoxication,
executive control, and two standard tasks of creative potential: creative problem solving
in the Remote Associates Task and divergent thinking ability, scored for rated creativity,
fluency, flexibility and novelty. Reduced cognitive control via mild alcohol intoxication
could be expected to attenuate fixation effects (Smith & Blankenship, 1991) and thus
support cognitive flexibility in the Remote Associates Test (Jarosz et al., 2012). The
available research allows no clear prediction regarding the effect of alcohol on divergent
thinking ability (Gustafson, 1991; Norlander & Gustafson, 1998). On the one hand,
divergent thinking is known to involve executive processes similar to intelligence tasks
(Benedek et al., 2014; Silvia, 2015). On the other hand, lower cognitive control might
increase disinhibition and unusualness of thought (e.g., Babor, Berglas, Mendelson,
Ellingboe, & Miller, 1982; Eysenck, 1995; Field, Wiers, Christiansen, Fillmore, & Verster,
2010), and thereby support the exploration of new and unusual parts of the idea space in
the given problem (as measured by fluency, flexibility and novelty). Together, these
mechanisms might facilitate the generation of unusual and potentially even creative ideas.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

132 people participated in an online screening, which aimed to identify those eligible for
participation in the main study. The online screening asked about age, potential
pregnancy, heart or liver diseases, psychiatric disorders, and included the Alcohol use
disorders identification test (AUDIT; Saunders, Aasland, Babor, De la Fuente, & Grant,
1993). 89 people from the screening met all criteria for participation, as they were at
least 18 years old (the local age limit for legal consumptions of any type of alcoholic
drinks), reported no pregnancy or relevant disease, and were casual drinkers of alcohol
but with an AUDIT level < 8 reflecting no risk for alcohol-related problems. A total of 70
young adults (54 % female), aged between 19 and 32 years (M = 23.3; SD = 2.8), finally
participated and completed all measures.

<hs>  Experimental design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This study investigated the effect of alcohol on cognition in a randomized placebo-
controlled pretest-posttest design. We used beer as experimental intervention, because it
is available in alcoholic and non-alcoholic form and represents a highly popular drink
among male and female University students. Participants of the alcohol group received
Gösser Zwickl® (5.2% alcohol by volume) and participants of the non-alcoholic group
received Gösser Naturgold® (<0.5% alcohol by volume). These two beers were selected
because they are very similar in taste and visual appearance (i.e., golden, naturally
cloudy). The amount of beer was individually adjusted for weight, age and gender (Watson,
Watson, & Batt, 1980; Widmark, 1932) targeting at a blood alcohol concentration (BAC) of
0.03 (in case of alcoholic beer). For a male with 22 years, 75 kg and 182 cm this results
in about 500 ml of beer, whereas a female with 22 years, 65 kg and 165 cm received about
350 ml beer. Drinks were cooled and prepared in a separate room and served in neutral
drinking glasses. Participants were asked not to consume alcohol or other drugs 24 h
before the experiment and not to eat and drink caffeinated drink 2 h before the
experiment. They were tested in groups of two people, who were randomly assigned to the
experimental groups (1 alcohol and 1 placebo). The participants were blind to the
experimental condition, and the employed group setting was intended to avoid any
experimenter effects. After a general instruction, participants signed informed consent. A
first measurement of alcohol concentration with the alcohol tester ACE Neo (ACE Handels- &
Entwicklungs GmbH; Freilassing, Germany) confirmed that all participants were sober at the
start of the experiment. In the pretest, participants completed an executive function test
(2-back task), two measures of creative potential (Remote Associates Test and divergent
thinking test), and a test of creativity evaluation skills. Then participants were given
their drinks and they watched a documentary about South Africa for half an hour to allow
the BAC level to reach its maximum. In the posttest, participants worked on different
versions of the same tests as in the pretest. The BAC was measured right after the
executive function test, with the result being concealed from the participants.
Additionally, all participants were asked indicate their subjective level of alcohol
intoxication on a four-point rating scale (0 = not at all, 1 = a little, 2 = quite a bit,
3 = very much). After the experiment, the participants were informed about the existence
of the placebo-control group and what group they had been assigned to. The total
experiment took about two hours. The procedure had been approved by the ethics committee
of the local university.

        <hss>Self-reported alcohol use</hss>

        The alcohol use disorders identification test (AUDIT; Saunders et al., 1993) is a
        10-item screening of individual drinking behavior. It asks for the frequency of
        alcohol consumption, and for indicators of alcohol dependence and harmful alcohol
        use. Total scores of 8 or more are recommended as indicators of potentially
        hazardous and harmful alcohol use (Babor, Higgins-Biddle, Saunders, & Monteiro,
        2001).

        <hss>Executive control</hss>

        Executive control was measured with a verbal 2-back task (Baddeley, 2003). The
        computer-based task presented a sequence of single white letters (K, M, R, or T)
        on black background with an inter-trial-interval of 1.5 s (inter-stimulus-interval
        = 0.2 s). Participants had to decide whether the current letter is identical with
        the one presented two stimuli ago by pressing a button for each target.
        Participants completed 20 practice trials, followed by the actual test with 100
        trials (25% targets). The final score reflected the total number of correct
        responses to targets and non-targets.

        <hss>Creativity measures</hss>

        Creative thinking was assessed with the Remote Associates Test (RAT; Mednick,
        1962) and divergent thinking tasks (Guilford, 1967), two common measures of
        creative potential (Kaufman, Plucker, & Baer, 2008). The RAT presents three
        unrelated words (e.g., cottage, blue, cake) and ask for a solution word that
        provides an unexpected connection between them (cheese: cottage cheese, blue
        cheese, cheesecake). Pretest and posttest used different sets of 10 items with
        increasing difficulty, but matched for item difficulty across tests (Landmann et
        al., 2014). The items were presented on a computer and participants entered the
        solution via a keyboard (timeout: 30 s). Divergent thinking (DT) was assessed with
        a computer-based version of the alternate uses task, which asks to find creative
        uses for common objects within 2.5 min (pretest: umbrella, shoe; posttest: car
        tire, fork). Task performance was scored for rated creativity as well as for
        fluency, flexibility, and novelty. All responses were evaluated for creativity (a
        holistic rating reflecting the novelty and usefulness of ideas) by six independent
        judges on a 4-point Likert-like scale ranging from (0 = uncreative, to 3 very
        creative). Inter-rater-reliability ranged from 0.75 to 0.81. DT creativity was
        defined as the average creativity evaluation of the three most creative ideas per
        task according to judge’s ratings. This top-3 creativity score was shown to avoid
        confounds with the fluency of responses (Benedek, Mühlmann, Jauk, & Neubauer,
        2013). DT fluency reflected the number of ideas per task. DT flexibility was
        defined as the number of categories into which ideas fall. To this end, two judges
        classified all responses for the 28 categories provided by the manual of the
        Torrance Test of Creative Thinking (Torrance, 1974). The inter-rater-reliability
        of the flexibility assessments ranged from 0.86 to 0.95. Finally, DT novelty was
        defined as the average statistical infrequency across ideas. We computed the
        novelty of each idea as the inverse of its frequency within our sample (e.g.,
        ideas generated by five people get a score of 0.2, whereas unique ideas get a
        score of 1). For all DT scorings, pretest and posttest scores represented the
        average performance in the two respective DT tasks. Creativity evaluation skills
        were assessed with a short-version of the creativity evaluation test (CET; Benedek
        et al., 2016). The CET presents different ideas that have to be judged as either
        common, inappropriate, or creative. Short versions for pretest and posttest were
        defined by selecting 8-item task blocks from the original CET. CET performance was
        scored by the informedness of judgements, a standard index from signal detection
        theory that equally accounts for sensitivity and specificity of judgements
        (Powers, 2011).

<hs>  Manipulation check and control analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The alcohol and the placebo groups each consisted of 35 participants, with a similar ratio
of females (49% and 60%, respectively; χ[1] = 0.92, p = 0.47). Participants who had
consumed alcoholic beer had an average BAC of 0.026 (SD = 0.08), which is close to the
targeted BAC level of 0.03. As expected, participants who had consumed non-alcoholic beer
had a BAC of 0 (SD = 0.00; t[66] = −19.5, p < 0.001). Importantly, however, the two
experimental groups did not differ in the level of subjectively perceived intoxication (U
= 711.5, p = 0.13); drinkers of alcoholic and non-alcoholic beer all predominantly
indicated to feel a little bit intoxicated (both groups: mode = 1, median = 1). We
observed no significant differences between gender groups: In the alcohol group, the BAC
was largely similar between females (0.028; SD = 0.08) and males (0.025, SD = 0.08; t[33]
= 1.64; p = 0.11). Moreover, gender groups did not differ in the subjective level of
intoxication, neither in total (U = 565, p = 0.51), nor within experimental groups
(alcohol group: U = 121.5, p = 0.30; placebo group: U = 149.5, p = 0.93; all modes and
medians = 1).

<hs>  Effects of alcohol intoxication on cognition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We analyzed effects of time (from pretest to posttest, i.e., T1 to T2) and experimental
group (alcohol versus placebo) on cognitive performance with two-way mixed ANOVAs. In the
2-back task, participants showed practice effects (time: F[1, 68] = 20.81, p < 0.001,
partial-ɳ2=0.23), but this effect tended to be moderated by the experimental group
(interaction: time ∗ group: F[1, 68] = 3.95, p = 0.05, partial-ɳ2 = 0.06): only the
placebo group significantly increased their performance from T1 to T2 (t[34] = −4.40, p <
0.001), whereas the intoxicated group showed only a trend towards improvements (t[34] =
−1.93, p = 0.06; see Fig. 1); yet, the groups did not differ significantly at T1 (t[68] =
−1.37, p = 0.18) or T2 (t[68] = −0.43, p = 0.57). In the Remote Associates test (RAT),
participants also showed increased performance at T2 (time: F[1, 68] = 24.47, p < 0.001,
partial-ɳ2 = 0.27), and this effect was again moderated by experimental group (time ∗
group: F[1, 68] = 4.76, p = 0.03, partial-ɳ2 = 0.07): groups did not differ in performance
at T1 (t[68] = 0.14, p = 0.89), but following the intervention, intoxicated participants
showed higher RAT solution rates than those from the placebo control group (t[61.82] =
−2.50, p = 0.02, d = 0.59; see Fig. 1). Regarding divergent thinking (DT) performance, we
observed no time effects and, importantly, no significant moderation by experimental group
for all DT scores, including DT creativity (time: F[1, 68] = 2.13, p = 0.15; time ∗ group:
F[1, 68] = 1.73, p = 0.19; see Fig. 1), DT fluency (time: F[1, 68] = 3.77, p = 0.06; time
∗ group: F[1, 68] = 1.50, p = 0.22), DT flexibility (time: F[1, 68] = 1.01, p = 0.32; time
∗ group: F[1, 68] = 0.23, p = 0.63), or DT novelty (time: F[1, 68] = 0.89, p = 0.35; time
∗ group: F[1, 68] = 0.55, p = 0.46). Finally, creativity evaluation performance showed a
significant time effect (time: F[1, 68] = 5.78, p = 0.02, partial-η2 = 0.08; T1: M = 0.53,
SD = 0.49; T2: M = 0.69, SD = 0.29), but no significant interaction with experimental
group (time ∗ group : F[1, 68] = 2.17, p = 0.24).

<h>DISCUSSION</h>
----------

This study investigated the effect of low alcohol intoxication on creative cognition in a
placebo-controlled design. Consumption of a low dose of alcohol tended to impair executive
control, but facilitated creative problem solving (viz. insight problem solving), and did
not affect divergent thinking ability. These findings replicate and extend recent research
in this field. For example, Jarosz et al. (2012) also reported reduced working memory
capacity and increased performance in the Remote Associates Test after moderate alcohol
consumption. As a difference, Jarosz and colleagues did not include a placebo control
group, because this may not be credible for moderate to high doses of alcohol (Martin &
Sayette, 1993). However, assuming to have consumed alcohol can lead to higher evaluations
of one’s creative output, and potentially even to more original performance (Lapp et al.,
1994). Therefore, this study used a lower dosage (target BAC of 0.03, versus 0.07 in
Jarosz et al., 2012), which effectively induced similar levels of subjectively experienced
intoxication in alcohol and placebo groups. We found that intoxicated participants
actually improved their performance in the RAT beyond the level of the placebo group,
which rules out the possibility that performance gains were caused by expectancy effects
alone. This study thus replicated effects of alcohol on creative problem solving for a
lower BAC level, while more clearly attributing them to the (additional) pharmacological
effect of alcohol. Alcohol intoxication neither improved nor harmed divergent thinking
(DT) performance. This is consistent with some previous findings (Lang et al., 1984),
while other studies found reduced idea fluency, flexibility, and increased originality at
higher levels of intoxication (Gustafson, 1991; Norlander & Gustafson, 1998). Given the
important role of executive control for divergent thinking ability (e.g., Benedek et al.,
2014), it seems possible that negative effects on controlled processes are compensated by
positive effects on spontaneous processes at low levels of alcohol, but one might expect
reduced DT creativity for higher alcohol levels. We also observed no effect of alcohol
intoxication on creativity evaluation skills, which is in line with the idea that
intoxicated people do not differ in their creativity evaluation from people who assume to
have consumed alcohol (Lang et al., 1984). Finally, it is interesting to mention that the
employed N-back task proved to be a sensitive indicator of mild intoxication effects on
cognitive control. Previous studies have often used complex span tasks (Colflesh & Wiley,
2013; Jarosz et al., 2012), but findings do not always align between these tasks (Redick &
Lindsey, 2013). Therefore, it is useful to note N-back and complex span tasks both appear
to reliably capture effects of mild to moderate alcohol intoxication on cognitive control.
Considering the findings together, a moderate attenuation of cognitive control seems to
benefit creative problem solving but not divergent thinking. Creative cognition is
generally assumed to rely on the interaction of controlled and spontaneous processes, but
the optimal balance may differ between tasks (Benedek & Jauk, in press). While most
cognitive activities usually benefit from high cognitive control, some may actually suffer
from too much focus (Chrysikou, Weber, & Thompson-Schill, 2014; Radel, Davranche,
Fournier, & Dietrich, 2015; Wiley & Jarosz, 2012). Our findings suggest that high
cognitive control is relatively more important to divergent thinking than to creative
problem solving. This interpretation is consistent with the observation that creative
problem solving tasks are often solved by spontaneous insight and accompanied by
“Aha”-experiences (Kounios & Beeman, 2014). While attentional control typically supports
the cued search of memory (Unsworth & Engle, 2007), looking for remote associations may
benefit from by a slightly reduced attentional focus and more flexible integration of
semantic concepts (Rowe, Hirsh, & Anderson, 2007; Wiley, 1998). Alcohol may particularly
play a role in mitigating fixation effects. In creative problem solving, problems can
often only be solved after a restructuring of the problem representation. When initial
solution attempts get on the wrong track, this can cause blocks to immediate problem
solving, which is known as mental fixation (Smith & Blankenship, 1991). These fixations
typically fade with time, which is considered a central mechanism behind incubation
effects (Storm & Koppel, 2012; Vul & Pashler, 2007). In a similar way, alcohol may reduce
fixation effects by loosening the focus of attention and hence impeding the building and
maintenance of dominant but inappropriate mental representations. Thereby, alcohol may
facilitate a broader associative search and the effective solving of creative tasks that
are prone to fixation effects.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

Our study corroborates the notion that small attenuations of cognitive control may
facilitate certain aspects of creative cognition while not affecting others. It
contributes to our understanding of the interplay between controlled and spontaneous
processes in creative thought and of their relative importance in different types of
creative cognition. The findings, however, should not be overgeneralized by assuming that
creativity is generally supported by alcohol. Beneficial effects are likely restricted to
very modest amounts of alcohol, whereas excessive alcohol consumption typically impairs
creative productivity (Kerr, Sheffer, Chambers, & Hallowell, 1991). Moreover, positive
effects appear limited to specific phases in the creative process that are not fully
tractable by goal-directed thought, while other phases such evaluation and implementation
of ideas usually suffer from reduced cognitive control (Norlander, 1999). Our findings
thus add to the increasing evidence suggesting that higher cognitive control is not always
equivalent to better cognitive performance (Amer, Campbell, & Hasher, 2016; Beilock, Carr,
MacMahon, & Starkes, 2002; Chrysikou, et al., 2014; Wiley & Jarosz, 2012).


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<ART>Creature of Habit: A self-report measure of habitual routines and automatic tendencies in everyday life
================================================================================

Authors: Karen D. Ersche, Tsen Vei Lim, Laetitia H.E. Ward, Trevor W. Robbins, Jan Stochl
DOI: 10.1016/j.paid.2017.04.024
Year: 2017  |  Pages: 73-85
ASJC codes: 3200
Keywords: Automaticity, Compulsivity, Daily routines, Eating, Questionnaire, Sensation-seeking, Stimulant drug exposure, Stress

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Our daily lives involve high levels of repetition of activities within similar contexts. We buy the same foods from the same grocery store, cook with the same spices, and typically sit at the same place at the dinner table. However, when questioned about these routine activities, most of us barely remember the details of our actions. Habits are automatically triggered behaviours in which we engage without conscious awareness or deliberate control. Although habits help us to operate efficiently, breaking them requires great effort. We have developed a 27-item questionnaire to measure individual differences in habitual responding in everyday life. The Creature of Habit Scale (COHS) incorporates two aspects of the general concept of habits, namely routine behaviour and automatic responses. Both aspects of habitual behaviour were weakly correlated with underlying anxiety levels, but showed a more substantial difference in relation to goal-oriented motivation. We also observed that experiences of adversity during childhood increased self-reported automaticity, and this effect was further amplified in participants who also reported exposure to stimulant drugs. The COHS is a valid and reliable self-report measure of habits, which may prove useful in a number of contexts where discerning individuals' propensity for habit is beneficial.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Global challenges such as poverty, obesity and climate change require large parts of the
general population to change the way we behave in order to make steps towards addressing
these problems. Thus far, educational approaches and attempts to appeal to individuals'
insight into the pressing need for change have largely failed (Webb & Sheeran, 2006). One
reason for the lack of success may be that the targeted behaviours are largely habitual in
nature, occurring outside conscious awareness. A better understanding of the mechanisms
underlying habitual responses and individual variations in forming and breaking habits is
needed in order to develop more effective strategies to address these global challenges
(Marteau, Hollands, & Fletcher, 2012). Habits constitute response patterns that a person
repeatedly exhibits in a specific situation (Lally & Gardner, 2013; Wood & Runger, 2016).
These responses are learned and become automatically activated when the individual enters
the associated environment. Examples could be making breakfast on coming into the kitchen
in the morning, or putting the mobile phone onto charge when coming home from work. Such
automatic responses are generally triggered by environmental cues, allowing us to perform
routine actions highly efficiently whilst focussing our attention on other things.
Meanwhile, the original motivation for these habitual actions becomes increasingly
irrelevant and, once initiated automatically without intention, habits continue without
conscious control. As habits are highly stable, they are difficult to change or break
altogether. However, within a different environment (e.g. in a friend's kitchen), the same
actions involved in making breakfast may suddenly run less smoothly, requiring conscious
attention, and we may likewise run the risk of forgetting to charge the phone at the end
of a day off work. Substantial experimental evidence has shown that habits develop though
instrumental learning (Thorndike, 1898). The repetition of reinforced actions, if
performed within the same environment, results in contextual stimulus-response
associations in memory that trigger the behaviour automatically within that environment
(Dickinson, 1985). These stimulus-response associations seem to overshadow the purpose
that initially motivated the behaviour, rendering the behaviour insensitive to changes in
the value or the contingency of the consequences. When habits are formed, control over the
behaviour gradually shifts away from being guided by our intentions to being automatically
triggered by cues in the environment. Consequently, once formed, habits are no longer
motivated by a goal, and are thus difficult to break with goal-oriented intentions or
knowledge of the consequences of habitual actions (Wood & Neal, 2007). There is
significant variation in the degree to which different individuals show a propensity for
developing habits. While some people delight in novelty and change in their lives, others
go so far as to even describe themselves as ‘creatures of habit’, an expression that
reflects their appreciation of routine and regularity in their lives. What underlies these
individual differences in habit formation is still largely elusive, but may provide
important insight into differences in the strategies needed to change habits in different
people. Nevertheless, a number of factors have already been identified that can influence
the switch of initially goal-directed actions into habitual responses. These include
prolonged practice (Boakes, 1993; Dickinson, Balleine, Watt, Gonzalez, & Boakes, 1995;
Neal, Wood, & Quinn, 2006), experiences of acute or chronic stress (Dias-Ferreira et al.,
2009; Schwabe & Wolf, 2011), or exposure to stimulant drugs (Nelson & Killcross, 2006;
Corbit, Chieng, & Balleine, 2014). By contrast, strong executive functions seem to promote
goal-directed behaviours (Otto, Raio, Chiang, Phelps, & Daw, 2013), and possibly
facilitate the regain of control over behaviours that have become habitual. A core
question meriting consideration revolves around the extent to which ‘creature of habit’
traits might represent a vulnerability marker for the development of clinical conditions
in which habitual behaviours have spiralled out of control, such as drug addiction,
gambling, obsessive-compulsive disorder, or eating disorders. Indeed, a number of mental
health problems involve rigid and inflexible routines, and actions performed in response
to particular triggers regardless of negative consequences (American Psychiatric
Association, 2013). Clarification around a role for proneness to habits in these
conditions may shed light on more successful treatments than those currently available.
Habitual behaviour can be assessed by experimental paradigms that manipulate the value or
contingencies of the outcome to identify behaviour patterns that persist irrespective of
such manipulations (Ersche et al., 2016; de Wit, Niry, Wariyar, Aitken, & Dickinson, 2007;
Mckim, Bauer, & Boettiger, 2016; Gillan et al., 2013). Evidently, self-report measurements
of behaviours that largely occur without awareness is not without criticism (Sniehotta &
Presseau, 2012). The self-reported habit index (SRHI) is one of the few questionnaires
that evaluate individuals' perception of a particular behaviour with respect to frequency,
automaticity, efficiency, and self-reference using a 12-item rating scale (Verplanken &
Orbell, 2003). The focus of the SRHI lies on a specific recurring behaviour that has been
identified by the researcher, not by the scale. This presents a major drawback of the
SRHI, as it excludes individuals who, due to a different lifestyle, do not engage in the
behaviour in question. To the best of our knowledge, there are currently no tools
available to assess more generally how individuals differ in their engagement in habits in
daily life. The aim of the present study, therefore, was to develop a scale that reflects
variations in individuals' tendencies towards responding in a habitual manner in everyday
life. Variations in proneness to habit may be driven by a need for structure and
predictability, which may reassure anxious individuals who worry about uncertainty and the
possibility of things going wrong in novel situations (Evans et al., 1997; Connors,
Bisogni, Sobal, & Devine, 2001). We therefore hypothesized that increased habitual
tendencies are associated with higher levels of anxiety and obsessive-compulsive traits.
Conversely, sensation-seeking traits and goal-striving personalities are likely to run
counter to regularity and repetition (Dunn, 2000). We therefore predicted that low levels
of habitual behaviours in daily life are associated with high levels of sensation-seeking
and goal pursuit. An ancillary aim of the study was to examine whether exposure to stress
or stimulant drugs, which have been shown to promote habitual responding in experimental
settings, also affect participants' self-reported habitual tendencies.

<hs>  Scale development</hs>
  ~~~~~~~~~~~~~~~~~

For the first step in developing a scale measuring characteristic behaviours and attitudes
for ‘creature of habit’ traits, we generated a pool of 59 items based on a thorough review
of the literature, and interviews and discussions with experimental and health
psychologists. On compiling the questionnaire, we noticed that half of the generated items
related to tendencies describing regular behaviours (e.g. I park my car always in the same
place), mental attitudes surrounding the minimisation of effort (e.g. I quite happily work
within my comfort zone), or the establishment of safety/predictability (e.g. I rely on
what is tried and tested), as well as emotional reactions when faced with irregularity
(e.g. I hate it when the grocery store re-arranges the aisles). The other half of the
items were behaviours occurring in the context of eating, such as describing behaviour
motivated by preferences (e.g. I have a preferred sandwich), automatic responses (e.g. I
always follow a certain order when preparing a meal), and behaviours characterised by a
lack of planning (e.g. I tend to cook more than I eat). Participants were required to
indicate for each statement their level of agreement on a 5-point Likert scale, ranging
from strongly disagree (1) to strongly agree (5). We extensively piloted the questionnaire
within the local community and conducted face-to-face interviews about the meaning of the
items. Items that were consistently misunderstood were either reworded or removed. Further
piloting showed that administering the entire 59-item questionnaire presented a challenge
to participants, so that we subsequently divided it into two parts. Although the
categorisation of general habits and food-related habitual responses was initially
unintended, it provided a rationale for splitting the COHS into two parts with similar
numbers of items (see Appendix A).

<hs>  Study sample</hs>
  ~~~~~~~~~~~~

We used Amazon's Mechanical Turk (MTurk), a crowdsourcing internet marketplace, to collect
data from 406 individuals in the online community. Forty-four participants (11%) were
excluded due to either incompletion, invalid responses or duplication of data, leaving a
total sample of 362 participants (47% male), whose identity remained anonymous to the
research team. Participants had to be at least 18 years of age [mean age 39.7 years ± 11.5
standard deviation (SD)] and based in the United States of America. All participants
received $2.00 for completion of the study, which included the two parts of the COHS with
the items in each part being presented in random order, and a selection of validated
questionnaires to assess personality traits of anxiety, compulsivity, sensation-seeking,
and goal-pursuit. We also collected background information, including ethnicity, native
language, education level, and employment status. Moreover, we asked participants to
indicate whether they have ever had any experience with stimulant drugs (either for
recreational purposes or as medication) and to complete the Childhood Trauma Questionnaire
(CTQ, Bernstein et al., 2003). The characteristics of the full study sample and the
subgroups are shown in Table 1. As recommended by Meade and Craig (Meade & Craig, 2012),
we also included two attention check items to safeguard against careless participants. The
study was approved by the Psychology Research Ethics Committee (Pre.2015.124; PI:KDE).

<hs>  Personality measures</hs>
  ~~~~~~~~~~~~~~~~~~~~

Anxiety personality traits: The trait version of the Spielberger State-Trait Anxiety
Inventory (STAI, Spielberger, Gorsuch, Lushene, & Jacobs, 1983) assesses variations in
trait anxiety of a long-standing nature. It consists of 20 questions surrounding worry,
tension, apprehension, and nervousness that are rated on a 4–point scale ranging from
almost never (1) to almost always (4). Obsessive-compulsive Personality Traits: The
Obsessive-Compulsive Inventory–Revised (OCI-R, Foa et al., 2002) is an 18-item
questionnaire to assess obsessive-compulsive symptoms in both clinical and non-clinical
samples. Participants rate the degree to which they have been bothered or distressed by
obsessive-compulsive symptoms in the past month on ranging from not at all (0) to
extremely (4). Sensation-Seeking Personality Traits: The Sensation-Seeking Scale Form-V
(SSS-V, Zuckerman, 1996) is a widely-used psychological instrument for measuring
individuals' need for novel and complex sensations along with the willingness to take
risks for the sake of having such experiences. It is composed of a series of 40 pairs of
dichotomous statements from which one must be selected. Goal-Oriented Personality Traits:
The Habitual Self-Control Questionnaire (HSCQ, Schroder, Ollis, & Davies, 2013) is a
14-item instrument measuring variations in people's commitment to completing tasks and
their self-perceptions around their drive for goal-pursuit. Participants express their
level of agreement to each item on a 5-point Likert scale, ranging from disagree strongly
(1) to agree strongly (5).

<hs>  Psychometric analysis of the creature of habit scale (COHS)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We first applied graph theory networks (Harary, 1969) to the correlation matrix to
visualise the structure of the item pool. We then used the Mokken Homogeneity Model (MHM,
Mokken, 1971), a non-parametric method based on Item Response Theory, to identify
redundant items, meaningful subscales and summary scores (Stochl, Jones, & Croudace,
2012). The goal of this method is to cluster the items into scales that meet the three key
assumptions of MHM: unidimensionality, monotonicity, and local independence. The summary
scores of the items within a subscale should then allow to order people with respect to
severity of the measured trait. Unidimensional subscales from the original item pool
(meaning that all items measure the same latent trait) were identified using Loevinger's
scalability coefficients (Loevinger, 1947) to assess scalability of a single item in
relation to the other items of the scale as expressed by Hi, and the scalability of the
total scale, as expressed by H. To meet the unidimensionality assumption of MHM, none of
the Hi's should drop below 0.30 (Hemker, Sijtsma, & Molenaar, 1995). Monotonicity was
assessed using methods available in R package mokken (van der Ark, 2007, 2012). Local
independence assumption states that an individual's responses to items are independent of
each other and is usually only examined by critical review of item wording. Items
violating any assumption of MHM were discarded from the final set. Structure and construct
validity of the final set of items in the COHS was subsequently assessed by confirmatory
factor analysis. Reliability of subscales was assessed by McDonald's omega (McDonald,
1999). For reasons of convention, we also computed Cronbach's alpha (Cronbach, 1951) and
estimated the graded response model (Samejima, 1969) in order to examine measurement error
in detail. Finally, we evaluated convergent and discriminant validity using Pearson's
correlations with personality traits that have been linked to variations in habitual
tendencies. The aforementioned analyses were conducted using R (R Core Team, 2016) and the
packages qgraph (Epskamp, Cramer, Waldorp, Schmittmann, & Borsboom, 2012), mokken (van der
Ark, 2007, 2012) and ltm (Rizopoulos, 2006).

<hs>  Effects of childhood adversity and stimulant drug exposure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Depending on whether participants had been exposed to stimulant drugs, they were allocated
into two categorical subgroups (no stimulants, stimulant exposure), since no further
information with respect to amount and duration of use was available. We also divided the
sample based on the CTQ scores into participants with no or mild type of adversity
experiences and those with moderate to severe adversity experiences, following the method
described by Bradley et al. (2008). Possible adverse experiences included verbal assault,
humiliation, intimidation, domestic violence, or sexual abuse. We used t-tests and chi-
square to explore differences in demographics between the subgroups. We also assessed
moderating and mediating effects of stimulant drug use between childhood adversity and the
two COHS scales (automaticity, routine). Gender, ethnicity and education were included as
covariates to control for subgroup differences in these variables.

<hs>  Data structure and item correlations of the COHS</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Item correlations and structure are shown in Fig. 1 and suggest that items can be roughly
divided into two clusters. Mokken scaling indicates that 39 of the 59 items grouped into
seven subscales and 20 items failed to either cluster with any subscale or create a
subscale on their own. The largest subscale consisted of 16 items, describing behaviours
and attitudes that favour order, familiarity and regularity, which we consequently termed
routine. The second largest subscale included 11 items, creating a relatively separate
cluster of items describing automatic behaviour patterns, which we consequently termed
automaticity. Although the items within the remaining scales 3–7 were strongly correlated,
each scale only consisted of just two to three items, which was considered insufficient
for a meaningful measurement (Thissen & Wainer, 2001). These items were therefore
discarded from the final set, in addition to the 20 items that did not fit into any
subscale.

<hs>  Psychometric properties of the COHS</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 provides additional results from Mokken Scale Analysis on the assessment of
homogeneity of subscales. For both scales, homogeneities (H coefficients) were calculated
at 0.35 (routine) and 0.41 (automaticity), suggesting medium strength (Sijtsma & Molenaar,
2002). We did not detect any significant violations of monotonicity in either scale,
suggesting compliance with the Mokken MHM for all items. Consequently, we ascertained that
individuals should be assessed on the basis of the score of each scale separately, rather
than by an overall score of both scales (Molenaar, 1982). Both dimensionality of the final
item set and construct validity of the items were evaluated using confirmatory factor
analysis. Considering the results of the Mokken Scale Analysis and network approach, we
hypothesized a 2-factor (correlated) structure for the final item set. The path diagrams
of the model are shown in Fig. 2. Model fit was good (Comparative fit index = 0.966,
Tucker-Lewis index = 0.963, Root Mean Square Error of Approximation = 0.057 (95% CI
0.051–0.062)). All standardized factor loadings were significant and, with the exception
of item COHS_16, higher than 0.5, suggesting good construct validity of items. Factor
analysis also confirmed that the two scales, routine and automaticity, were only weakly
correlated domains (r = 0.14, p < 0.001), which further justified separate scoring of the
two scales.

<hs>  Reliability, measurement error, and validity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

McDonald‘s omega and Cornbach's alpha for the COHS routine (ω = 0.92, α = 0.89) and
automaticity (ω = 0.91, α = 0.86) suggest satisfactory reliability for both scales.
Detailed examination of measurement error can be found in Fig. 3, showing that both scales
have reasonably small measurement error across a wide range of score distributions. As
shown in Table 3, the COHS routine scale was significantly inversely correlated with
sensation-seeking (SSS-V) and weakly correlated with trait levels of anxiety (STAI-T) and
compulsivity (OCI-R). COHS automaticity, on the other hand, showed a significant inverse
relationship with goal-pursuit (HSCQ), in addition to weak correlations with trait-anxiety
and compulsivity. We further correlated both subscales with age to examine whether older
individuals show a preference for routines (Bergua et al., 2006), but the results were
non-significant (both p > 0.1).

<hs>  Effects of childhood adversity and stimulant drug exposure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants who reported previous exposure to stimulant drugs were predominantly male (χ2
= 5.1,p = 0.024) and of white ethnic origin (χ2 = 11.2,p = 0.047), but were not different
from stimulant-naïve participants in terms of education level or employment status. The
ANCOVA model, which included gender and ethnicity as covariates, did not reveal any
significant subgroup differences in terms of routine behaviour (F1,358 = 0.1,p = 0.921) or
automaticity (F1,358 = 0.8, p = 0.365). For childhood adversity, significantly more women
than men reported traumatic experiences during childhood (χ2 = 9.7,p = 0.002).
Participants without adverse childhood experiences were more likely to attend university
compared with participants who had such experiences (χ2 = 9.0,p = 0.011), but they did not
differ with respect to ethnicity or employment status. When the two subgroups for
childhood adversity were compared, with gender, ethnicity and education included as
covariates, participants with childhood adversity showed significantly higher levels of
automaticity compared with their counterparts without such traumatic experiences (β =
0.126,p = 0.019) (Fig. 4). The two subgroups did not, however, differ in terms of routine
behaviours (β = − 0.018,p = 0.746). The comparison of participants with and without
stimulant drug exposure, again accounting for covariates, revealed no group differences
either for automaticity (β = − 0.001,p = 0.982) or routine (β = − 0.049,p = 0.362).
However, we did identify a significant interaction effect between stimulant drug exposure
and childhood adversity on automaticity (β = 0.172, p = 0.035) and an interaction effect
at trend level for routine (β = 0.145,p = 0.082) suggesting that stimulant drug exposure
further exacerbated the increased levels of automaticity observed in those individuals
with childhood adversity. We did not find any mediation effect of stimulant drug exposure
on the relationship between childhood adversity and either automaticity (total
standardized indirect effect = − 0.004,p = 0.671) or routine (total standardized indirect
effect = − 0.007, p = 0.426).

<h>DISCUSSION</h>
----------

We present a novel questionnaire to assess individual variations in habitual tendencies in
everyday life. The COHS is theoretically sound and has shown good psychometric properties.
As identified by mokken scaling, the COHS differentiates two distinct features of habits:
routine behaviours and automatic responses. Questionnaire items that were associated with
volition, such as personal preferences or lack of planning, did not survive the analysis,
further supporting the notion that habits are not mediated by a goal (Wood & Neal, 2007).
The two scales for routines and automaticity both constitute forms of habits: they share
with habits their implicit nature, in the sense that within daily life, they may both be
initiated without conscious awareness. Habits are behaviours learned by repetition, not by
insight (Boakes, 1993) - another critical feature shared by both routines and
automaticity. The regular nature of routines involves repetition, and repeated practice is
likewise a prerequisite for the transformation of purposeful behaviour into an automatism
(Orbell & Verplanken, 2010). Yet, routine and automaticity also distinctly differ from one
another, specifically in terms of their function and control over behaviour, as reflected
by the weak correlation between the two COHS scales. This differentiation is further
supported by the influence that adverse life events and stimulant drug exposure appear to
have on the degree to which individuals express automaticity, whilst not affecting routine
behaviours.

<hs>  How routines and automaticity relate to habits</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Routines are generally described as familiar action patterns that involve regularity,
which are likely to be performed on a daily basis (Gallimore & Lopez, 2002). Routines have
a relatively fixed temporal pattern of sequenced actions that are executed voluntarily in
order to make daily life more orderly and efficient (Clark, 2000). This functional purpose
and their relative independence from the immediate environment are critical features of
routines, which may explain why routines are maintained as long as they deliver the
desired outcome. Once this is no longer the case, e.g. due to changing circumstances, a
conscious decision is typically made to either drop or amend the routine (Clark, 2000;
Denham, 2002). Likewise, meaningful routines may also be deliberately combined and turned
into rituals in order to increase cohesion between members of a group (Doherty, 1997;
Denham, 2003). Although routines fall within the realm of habits, their inherent
functionality (either implicit or explicit) and their strong link with a time frame, may
explain why routines and habits are not synonymous. Habits thus only include those routine
behaviours that are performed automatically without serving a specific purpose and are no
longer restricted to a fixed temporal pattern. One possibility is that the degree to which
people are inclined to apply routines in their daily lives might be one factor underlying
their proneness to form habits. Personality traits associated with seeking or avoiding
situations of novelty and excitement may further explain the spread of individual
variations in routine practices (Dunn, 2000). Clearly, individuals with high sensation-
seeking traits would be less inclined to engage in rituals, which would make them feel
bored and stuck in a rut, whilst those more prone to anxiety in novel situations may
relish the predictability and comfort of routine. Just as routine behavioural patterns can
reduce effort and cognitive load, so can automatic behaviours, thereby enhancing
functional efficiency of daily activities. However, in contrast to routines, automaticity
neither has to be sequential in nature nor does it involve any kind of deliberation,
cognitive direction or dependency on utility of the outcome (Saling & Phillips, 2007). In
fact, automatic actions are initiated by environmental cues without a deliberate
intention, and they may even continue without the involvement of conscious control (Bargh,
1994). Habits, by contrast, extend beyond simple automatic reactions, involving complex
patterns of behaviours that are performed repeatedly and relatively automatically with
very little variation (Clark, 2000). Environmental cues not only trigger the behavioural
response but also the mental representation of the habit (Aarts & Dijksterhuis, 2000; Wood
& Runger, 2016). This may also explain the inverse relationship between automaticity and
goal-striving in the COHS. As such, goal-striving individuals manage their behaviour with
consideration for the consequences of their actions in mind, and are less inclined to
allow environmental stimuli to take over control. Given that automatic actions are
dependent on the context that triggers them, automatic action patterns necessarily vary
enormously with respect to individuals' lifestyles. This poses a particular challenge for
self-report measures, which require questionnaire items that capture the specificity of
the environment while applying to a large number of people. As the consumption of food is
largely automatic (Cohen & Farley, 2008), it is not surprising that many automaticity
items are related to eating. Yet, this should not detract from the fact that other non-
food related behaviours are equally likely to be automatic but are just more difficult to
assess by questionnaire. It is of further note that eating habits also involve routines,
as traditionally exemplified by the eating pattern of three meals a day (Jastran, Bisogni,
Sobal, Blake, & Devine, 2009). The involvement of the routine component of habit in food-
related behaviour is also captured by a number of items in the routine subscale of the
COHS.

<hs>  The benefits and risks of habits</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A major hallmark of habits is that they are not mediated by a goal (Dickinson, 1985; Wood
& Neal, 2007). Although goal pursuit might have motivated the behaviour initially, once
the habit has been acquired, the goal is no longer required to motivate or guide the
actions, thereby making habits less effortful and cognitively demanding than goal-
orientated behaviours. Habits thereby allow individuals who are affected by cognitive
decline or impaired motivation, such as older adults or drug-addicted individuals, to
behave highly efficiently despite their deficits (Bergua et al., 2006; de Wit, van de
Vijver, & Ridderinkhof, 2014; Ersche et al., 2016), albeit at the expense of flexibility.
Furthermore, as habits are decoupled from goal-orientated motivation, habitual behaviour
is less susceptible to motivational urges, offering therapeutic opportunities for
individuals who particularly struggle with resisting temptations and cravings (Lin, Wood,
& Monterosso, 2016). This critical component of habits, namely their insensitivity to
reinforcement contingencies or outcome, is, however, not captured by the COHS, but may be
explored by studies using the COHS together with experimental paradigms. Importantly,
although habits continue even though these actions are no longer needed, they do not
necessarily continue in an uncontrolled manner; for example, they will not be carried out
in exactly the same way when there is a change in the environment or temporal
configuration of the situation (Lombo & Gimenez-Amaya, 2014). However, if habits lose the
specific link to the context and co-occur with compromised inhibitory control, an
increased risk arises of habitual patterns being repeatedly practised over and over again,
becoming more and more deeply entrenched, which is the case in clinical conditions
involving maladaptive habits such as obsessive-compulsive disorder and addiction (White,
1997; Mishkin, Malamut, & Bachevalier, 1984; Graybiel & Rauch, 2000). Accordingly, both
COHS factors were positively correlated with OCI-R scores, a clinical measure of
compulsive symptoms (Foa et al., 2002). Although the present sample was not drawn from a
clinical population, the positive relationship suggests that both aspects of habits
captured in the COHS lend themselves to susceptibility for development of compulsivity.
The underlying causes for the development of compulsivity are still elusive, but
investigation into them is of critical importance given their apparent relevance to a
number of disorders.

<hs>  Neural substrates of the creature of habit components</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The differentiation of routine behaviour and automaticity, as assessed by the COHS, might
also be reflected in distinct neural substrates underpinning different components of
habits. Hitherto, the basal ganglia have been considered to play a key role in the
formation of habits (Ashby, Turner, & Horvitz, 2010; Yin & Knowlton, 2006; Graybiel,
2008). During the initial phases when a behaviour is learned, the associative part of the
striatum (caudate nucleus and anterior putamen) and the adjunct limbic structures and
medial prefrontal cortex are critically involved (Doyon et al., 2009; Ashby et al., 2010).
In as much as these brain systems are critical for both learning and memorising the
instrumental contingencies as well as the differential effects of action-outcomes
(Liljeholm, Tricomi, Doherty, & Balleine, 2011; Tanaka, Balleine, & O'Doherty, 2008),
goals remain relevant during this phase and might still be involved in the development of
routines. However, with prolonged practice, sensorimotor regions of the striatum (putamen)
that are primarily connected to sensory and motor cortices take over control (Tricomi,
Balleine, & O'Doherty, 2009), resulting in behaviour patterns becoming more automatic and
eventually taken over by the cerebellum, possibly contributing to automaticity (Lang &
Bastian, 2002; Doyon et al., 2009). Whether the processes for developing routines and
automatic response are reflected in variations in connectivity in cortico-striatal and
cortico-cerebellal pathways, respectively, are hypotheses to be tested using the COHS in
combination with neuroimaging technology.

<hs>  Creature of habit: Moderator effects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants who reported adverse childhood experiences scored significantly higher on the
COHS automaticity scale than those who did not report such experiences. This effect was
further exacerbated in individuals who also reported using stimulant drugs at least once
in their lives. These results are in keeping with prior preclinical work suggesting that
the development of automatic responses could be accelerated by exposure to stress and
psychostimulant drugs. Our findings are consistent with preclinical work showing that both
stress and stimulant drugs induce sensitisation of dopaminergic systems, thereby promoting
a more rapid transition to stimulus-response action patterns (Dias-Ferreira et al., 2009;
Nelson & Killcross, 2006; Nordquist et al., 2007). From a psychological perspective, a
predominance of automatic responses under stress is clearly beneficial. As long as the
context is stable, the individual may rely on cerebellar circuits, ensuring that complex
actions are performed efficiently even under stressful conditions, (Doyon et al., 2009).
In light of the role automaticity plays during stress, it is noteworthy that most of the
COHS automaticity items are food-related, which might point to the stress-induced
neuroendocrine functions that have also been linked with automatic eating patterns
(Kandiah, Yake, & Willett, 2008; Tryon, DeCant, & Laugero, 2013). This further supports
our finding of higher automaticity scores in people who report having experienced
stressful childhoods.

<h>CONCLUSIONS</h>
-----------

The 27-item COHS is a measure of habitual tendencies in daily life that demonstrates good
validity and reliability (Appendix B). The questionnaire has been designed to measure
creature of habit traits, but the findings also point to sub-dimensions of habits related
to automatic responses and routine behaviours. This differentiation sheds light on
habitual behaviours and may inform interventions to break habits in populations with
abnormal maladaptive habits. For example, it is conceivable that individuals with highly
expressed routine behaviours would particularly benefit from training alternative routines
to replace maladaptive habits. Conversely, for individuals with a particular affinity for
automaticity, interventions would be more effective if they were to focus on breaking the
maladaptive stimulus-response relationships by linking the triggering stimulus to a more
desirable response and practising this new stimulus-response relationship. A shortcoming
of the current questionnaire is that it does not assess the critical feature of habits
concerning insensitivity to reinforcer devaluation – a feature that would be difficult to
assess by self-report. Thus, further benefit could be derived from administering the COHS
in combination with other diagnostic tools, specifically instrumental learning tasks.
Moreover, cross-validation of the COHS in an independent sample is also warranted.
Generally, the potential usefulness of this questionnaire may be better appraised when the
measure has been used in further empirical studies. The use of neuroimaging methods may be
of particular benefit in elucidating the different neural pathways involved. Specifically
in populations with dysfunctional habit formation, the COHS may help to clarify which
aspects of the construct are abnormal, and may then help to determine the most appropriate
therapeutic strategy.

<h>CONFLICT OF INTEREST</h>
--------------------

All authors declare that they have no competing or potential conflicts of interest in
relation to this work.


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<ART>Decision-making of English Netball Superleague umpires: Contextual and dispositional influences
================================================================================

Authors: Adele M. Burnett, Daniel T. Bishop, Kelly J. Ashford, A. Mark Williams, Noel P. Kinrade
DOI: 10.1016/j.psychsport.2017.04.003
Year: 2017  |  Pages: 52-60
ASJC codes: 3202
Keywords: Avoidance, Bias, Pressure, Referee, Reinvestment, Rumination

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives The decisions made by officials have a direct bearing on the outcomes of competitive sport contests. In an exploratory study, we examine the interrelationships between the decisions made by elite netball umpires, the potential contextual and environmental influences (e.g., crowd size), and the umpires’ dispositional tendencies – specifically, their propensity to deliberate and ruminate on their decisions. Design/Method Filmed footage from 60 England Netball Superleague matches was coded using performance analysis software. We measured the number of decisions made overall, and for home and away teams; league position; competition round; match quarter; and crowd size. Additionally, 10 umpires who officiated in the matches completed the Decision-Specific Reinvestment Scale (DSRS). Results Regression analyses predicted that as home teams’ league position improved the number of decisions against away teams increased. A model comprising competition round and average league position of both teams predicted the number of decisions made in matches, but neither variable emerged as a significant predictor. The umpire analyses revealed that greater crowd size was associated with an increase in decisions against away teams. The Decision Rumination factor was strongly negatively related to the number of decisions in Quarters 1 and 3, this relationship was driven by fewer decisions against home teams by umpires who exhibited higher Rumination subscale scores. Conclusions These findings strengthen our understanding of contextual, environmental, and dispositional influences on umpires’ decision-making behaviour. The tendency to ruminate upon decisions may explain the changes in decision behaviour in relation to the home team advantage effect.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In competitive sports, officials are required to make rapid and complex decisions, often
in a highly pressured environment (Helsen & Bultynck, 2004). Moreover, their decisions
often directly affect the outcome of competitions (Plessner & MacMahon, 2013). For
example, during the final minutes of the 2015 Rugby World Cup quarter-final between
Scotland and Australia, referee, Craig Joubert, decided to award a controversial penalty
to Australia for a deliberate knock-on, resulting in a 35–34 victory for Australia, which
enabled them to progress to the semi-final of the competition. Such decisions invariably
attract negative evaluations by aggrieved players, coaches, spectators and the media, so
the importance of consistent and impartial officiating is unquestionable (Stulp, Buunk,
Verhulst, & Pollet, 2012). Decision-making can be influenced by a variety of factors
(MacMahon et al., 2015), such as home advantage and crowd noise (e.g., crowd noise
contribution to the home advantage effect, Nevill, Hemingway, Greaves, Dallaway, &
Devonport, 2016; Unkelbach & Memmert, 2010), competition level (Souchon, Cabagno, Traclet,
Trouilloud, & Maio, 2009; Souchon et al., 2016), reputation (e.g., expectation bias in
gymnastics, Plessner, 1999) and time (e.g., decision accuracy and frequency thoughout
games, Emmonds et al., 2015; Mallo, Frutos, Juárez, & Navarro, 2012). In the current
paper, we employ an exploratory approach to examine the decisions made by netball umpires
and the influences of contextual and environmental factors on the number of decisions
made. Moreover, we investigate umpires' self-reported tendency to reinvest in, and
ruminate upon, their decisions. Many researchers have focused upon the home advantage in
sports – a phenomenon whereby there is an apparent advantage conferred to the home team.
Four major determinants have been suggested to cause the home advantage effect namely,
familiarity, territoriality, travel fatigue, and crowd noise (Pollard, 2008). It has been
suggested that home advantage fluctuates throughout the game. For example, in basketball,
Jones (2007) demonstrated that the home advantage (difference in points scored by the home
and away teams) was greatest in the first quarter. In volleyball, home teams had a greater
advantage at the beginning (1st set) and towards the end of the game (4th and 5th sets);
this effect has been attributed to familiarity with the venues and crowd effects
(Marcelino, Mesquita, Palao, & Sampaio, 2009). In relation to the referee's influence on
the home advantage, Boyko, Boyko, and Boyko (2007) examined data from 5244 English Premier
League soccer matches involving 50 referees. They found that referees differed in their
susceptibility to the home advantage effect; hypothesising this was due to variations in
the referees' ability to deal with social pressure. However, Johnston (2008) replicated
Boyko et al.’s (2007) approach and found no evidence of such individual differences when
removing referees who only officiated a few matches. To investigate this discrepancy
further, Page and Page (2010) analysed footage from 37,830 national and international
soccer matches across 58 competitions, between 1994 and 2007. Their analyses showed that
not only did the size of the home advantage differ significantly between referees, but
also, in line with Boyko et al. (2007), their decisions were moderated by crowd size –
lending support to the notion that referees cope differently with the social pressure
exerted by home crowds. Using a video-based protocol, Nevill, Balmer, and Williams (2002)
manipulated crowd noise presence (“loud” or none) and found that soccer referees made more
decisions in favour of the home team, and in line with the original match referee.
Unkelbach and Memmert (2010) identified the inherent limitation of testing crowd noise
(“natural conditions”) versus no crowd noise (“unnatural conditions”). The authors
highlighted that Nevill et al.'s (2002) findings merely indicate that home crowd noise
biases decisions compared to no crowd noise, rather than crowd noise influencing referee
decisions in favour of the home team. Subsequently, Unkelbach and Memmert (2010) tested
the hypothesis that louder crowd noise would lead to more yellow cards awarded compared to
low crowd noise. Twenty referees viewed 56 foul scenes, in which 50% led to the award of a
yellow card and 50% did not. The high-volume crowd noise led to substantially more yellow
cards than low-volume crowd noise. Further evidence in soccer indicates that home teams
were awarded more penalties (e.g., Nevill, Newell, & Gale, 1996; Scoppa, 2008; Sutter &
Kocher, 2004), and fewer yellow and red cards (Buraimo, Forrest, & Simmons, 2010) with the
size of the attending crowd moderating these effects (Boyko et al., 2007). The mediating
effect of competition level has received scant attention, whilst stage of competition
(e.g., Round 1, playoffs, finals, etc.) has yet to be investigated. Souchon et al. (2009)
proposed that the level of competition is a stereotyping heuristic used by referees to
form their decisions, interpreting fouls differently according to their preconceptions
regarding the standard of play. Souchon et al. (2009) investigated this notion in handball
(e.g., lower versus higher standard), predicting the level of competition effects would be
greater for more difficult, ambiguous handball transgressions (“pushing offences”, opposed
to clearer “holding back” offences) and anticipating that referees would be more lenient
in higher-standard competition. They reported that referees intervened less frequently at
higher levels of competition and allowed play to continue without intervention more
frequently following more ambiguous transgressions (pushing offences compared to holding
offences). Similarly, Souchon et al. (2016) observed that referees intervened less often
when higher-level players transgressed. The authors suggested that a reduction in
decisions made may be the culmination of a number of factors: referees trying to maintain
the flow of a match; referees making fewer calls to maintain the game's value as a
spectacle (e.g., Mascarenhas, O'Hare, & Plessner, 2006); that a greater number of fouls
may be more ambiguous in high-level competition, due to the high speed of play; that
greater levels of player aggressiveness may make it more difficult to identify
transgressions; or that referees may assume that certain players can continue their
actions despite the seriousness of the foul committed (e.g., gender stereotype and males
superior physical ability, Souchon et al., 2010). In this study, we aim to examine
potential changes in the number of decisions made across progressive competition rounds
(perceived match importance arguably increases as the rounds progress). Few researchers
have focused on the effect of the competing teams' abilities on sports officials'
judgements. However, Plessner (1999) examined the idea of an expectation bias in team
gymnastics, where gymnasts normally perform in a ranked order, worst to best. Plessner
predicted that when the same routines, placed in either first or fifth position, will
score higher when the judges view them in the latter position. Forty-eight gymnastic
judges, with prior expectations of coaches' rank order of the gymnasts, judged videotapes
of a men's team competition. Their results supported the notion of an ability expectation
bias, whereby, for difficult tasks (e.g., pommel horse, vault, and horizontal bar) the
judges awarded greater scores when the target routines were presented fifth than if they
were presented first. Findlay and Ste-Marie (2004) explored athlete reputation bias in
figure skating judgments. Twelve judges evaluated performance of 14 skaters, half of whom
were known to the judges. The performance of skaters with a pre-existing positive
reputation were scored more highly than those of the unknown skaters. It is possible that
similar unconscious biases relating to perceived athlete ability may also exist in team
sports; hence, we also took the competing teams' pre-eminence (i.e., their league
position) into account in this study. To date, a limited body of research has investigated
the effect of the match period on sports officials' decision-making. Mallo et al. (2012)
assessed the soccer referees' decision quality and quantity in relation to match periods.
Mallo et al. reported that a greater number of incidents occurred in the last 15- minute
period of matches – but the lowest referee decision accuracy (77%) was also observed
during this period. They suggested that physical and mental fatigue occurs during the
final stages of a match leading to impaired decision-making. Similarly, Emmonds et al.
(2015) found a drop in penalty judgement accuracy in rugby league referees in the last 10
min of matches. Conversely, Mascarenhas, Button, O'Hare, and Dicks (2009) reported that
soccer referees were less accurate in the opening 15 min of each half than they were at
any other period. They attributed poorer decision-making to warm up decrements, whereby
their physical warm-up was not accompanied by any mental warm up techniques. Finally,
Elsworthy, Burke, and Dascombe (2014) investigated decision-making demands of Australian
Football referees, and reported that the number of free kicks awarded and free kick
accuracy did not differ across each quarter of the match. Accordingly, in the present
study, we analysed differences in the number of decisions made by netball umpires across
each of the four match quarters. Published reports using qualitative methods have
identified several sources of pressure and anxiety for sports officials (such as game
importance, Hill, Matthews, & Senior, 2016; time, Morris & O'Connor, 2016; social
pressure, Schnyder & Hossner, 2016). Morris and O'Connor (2016) found that National Rugby
League (NRL) referees identified the time during a match as an influence on their game
management strategies and decision-making ability. For example, one referee stated
“certain decisions can have a greater impact at different stages in a game which can
increase media scrutiny” (Morris & O'Connor, 2016, p. 854). Schnyder and Hossner (2016)
interviewed high-level soccer referees regarding decision-making and the difficulties they
face. Several of the referees identified social pressures, including pressure from the
media, teams, football associations and even themselves. Hill et al. (2016) interviewed
seven expert rugby referees and noted that avoidance coping behaviours were regularly
employed to deal with multiple stressors that influence their performance including:
unfamiliarity (e.g., new situations); performance errors (e.g., mistakes that ‘harm’
players, coaches and own career prospects); interpersonal conflict (e.g., manging player
hostility); game importance (e.g., when the match outcome held significant consequence for
players such as a final, or for themselves such as games close to renewal of contracts)
and self-presentational concerns (e.g., fear of negative evaluation by selectors, avoiding
criticism that could damage their confidence and reputation). The avoidance behaviours
manifested themselves as denial after performance errors, rushing or withdrawal during the
game, and a lack of preparation leading into games. Similarly, overt and maladaptive
changes in behaviour under anxiogenic conditions have been observed in soccer (Jordet &
Hartman, 2008) in climbing (Nieuwenhuys, Pijpers, Oudejans, & Bakker, 2008), dart throwing
(Nibbeling, Oudejans, & Daanen, 2012), golf (Hill, Hanton, Matthews, & Fleming, 2010), and
police arrest procedures (Renden et al., 2014). Decision avoidance has been described as
“a tendency to avoid making a choice, by postponing it or by seeking an easy way out that
involves no action or no change” (Anderson, 2003, p. 139). Selection difficulty has been
identified as a major contributor to decision avoidance including factors such as:
reasoning; preference uncertainty; attractiveness of options; attentional focus; time
limitation; negative emotion (associated with blame and regret); and conflict type
(Anderson, 2003). Researchers have shown that decision averseness occurs when situations
have inequitable outcomes for others – particularly when the decision maker is held
accountable (Beattie, Baron, Hershey, & Spranca, 1994); and the likelihood of negative
outcomes also increases negative emotions associated with such decisions (Luce, Bettman, &
Payne, 1997). In this study, we explored the notion that withdrawal of decisions (fewer
decisions made) may be an example of decision avoidance behaviour. Several theories have
been proposed to explain performance decrements under pressure. A prominent example is
Reinvestment Theory (Masters, 1992). Reinvestment is defined as the “propensity for
manipulation of conscious, explicit rule based knowledge, by working memory, to control
the mechanics of one's movements during motor output” (Masters & Maxwell, 2004, p.208).
Consequently, the use of explicit knowledge to consciously control normally automatic
movements typically results in performance decrements or outright failure. Researchers
have demonstrated that, when performing well-learnt motor skills or complex cognitive
tasks, individuals who have a strong tendency to reinvest (as measured by the Reinvestment
Scale, Masters, Polman, & Hammond, 1993) (as measured by the Reinvestment Scale) are more
susceptible to poor performance under pressure (Jackson, Kinrade, Hicks, & Wills, 2013;
Kinrade, Jackson, & Ashford, 2010). To address potentially differential effects of
reinvestment on motor skill execution and decision-making, Kinrade, Jackson, Ashford, and
Bishop (2010) modified the original scale to create a decision-specific version focusing
on individuals' propensity to deliberate, and ruminate, on their decisions – the Decision-
Specific Reinvestment Scale (DSRS). Kinrade et al. (2010) proposed two explanations for
the breakdown of decision-making under pressure. First, that conscious processing of
explicit information results in poor decision-making, by interfering with normal automatic
processes (Decision Reinvestment; e.g., “I'm aware of the way my mind works when I make a
decision”). Secondly, ruminative thoughts (e.g., over past poor decisions) lead to poor
decision-making by drawing processing resources away from the task at hand (Decision
Rumination; e.g., “I remember poor decisions I make for a long time afterwards”). Kinrade
et al. (2010) described rumination as a thought process that typically involves repetitive
negative thoughts about past events or current mood states. Higher decision reinvesters
and ruminators tend to exhibit poorer working memory task performance (Laborde, Furley, &
Schempp, 2015), and poorer decision-making performance in complex tasks (Kinrade, Jackson,
& Ashford, 2015). Kinrade et al. (2015) suggested that ruminative thoughts may occupy
working memory capacity at a time when executive functions are already in great demand to
complete the primary task. Poolton, Siu, and Masters (2011) used the DSRS to examine
soccer referees' susceptibility to the home advantage effect. Twenty-eight experienced
referees were asked to make decisions when viewing game footage of two opposing players
competing for the ball, by stating which player committed the foul. Referees that emerged
as ‘high decision ruminators’ disproportionately made decisions in favour of the home
team. We aim to explore this link further in the present study, in the context of netball
officiating. In order to more fully understand contextual and dispositional influences on
the decision-making of netball umpires, we used performance analysis to examine decisions
made by umpires during matches in the England Netball Superleague – the highest echelon of
competitive netball in the UK. We explored not only environmental and contextual
influences such as crowd size, but also the umpires' self-reported tendency to reinvest
in, and ruminate upon, their decisions. The number of decisions made provided an overt
manifestation of the observed umpires' behaviour, a technique previously used to
categorise observational data into approach- and avoidance-type behaviours (Jordet &
Hartman, 2008). In accordance with previous research (Anderson, 2003; Hill et al., 2016;
Jordet & Hartman, 2008; Nevill et al., 2002; Poolton et al., 2011; Souchon et al., 2016),
we tentatively hypothesised that umpires' decision frequency would be mediated by
environmental/contextual influences such as home team status, crowd size, match
prominence, league position, and time during the match. More explicitly, we predicted
that, home teams in the presence of larger crowds, greater match significance, more
prominent teams, and early match quarters would each be associated with lower decision
frequencies (i.e., avoidance behaviour). We also predicted that a tendency to reinvest and
ruminate would be associated with inhibited decision-making.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Altogether, 15 umpires officiated in the Superleague during the 2014 season, umpiring
approximately eight matches each (M = 8.067, SD = 3.77). From this original sample 10
umpires (M age = 39.6 yrs, SD = 9.38 yrs) with a mean total years' experience of 14.5
years (M = 14.5 yrs, SD = 7.66 yrs), qualified at international (International Umpire
Award) or national level (A-award), completed the DSRS. On average, they officiated almost
nine matches each throughout the season (M = 8.80, SD = 2.859).

        <hss>Data acquisition</hss>

        Video footage from sixty Netball Superleague 2014 season matches was obtained.
        Crowd size (number of people present in the crowd) data were collected from the
        individual teams for their home fixtures and from England Netball for all
        ‘neutral’ venues (i.e., those for which there was no home team). League table data
        for each round were obtained from England Netball. Approval was obtained from the
        lead institution's local ethics committee.

        <hss>Variables</hss>

        All coded variables were derived from discussions with a panel of experts (an
        England Netball Officiating Manager, a retired international umpire and assessor,
        a current national level umpire and tutor) and in accordance with variables
        previously shown to be pertinent with regard to sports officials' decision-making
        (e.g., match importance, Hill et al., 2016; Decision Rumination and the home
        advantage effect, Poolton et al., 2011). The primary dependent variable was the
        number of observable decisions made (NoD), split into three subcategories:
        overall; those against the home team; and those against the away team. Other coded
        variables included: infringement type (contact, obstruction, offside, breaking,
        out of court, and other infringement); and sanctions imposed (penalty pass,
        advantage, throw in, advantage goal, other sanction.). Additionally, we recorded
        six variables that were hypothesised to have a potential influence on umpires'
        decision-making: crowd size; competition round number (e.g., 1 = 1st round);
        league positions (of home teams, of away teams, and average; 1 = top of the
        league); and match quarter (e.g., Q1 = 1st quarter).

        <hss>Decision specific Reinvestment Scale</hss>

        Altogether, 10 umpires completed the Decision-Specific Reinvestment Scale (DSRS,
        Kinrade et al., 2010), a 13-item scale, comprising two subscales (Decision
        Reinvestment and Decision Rumination). Participants responded to each of the 13
        items using a 5-point Likert scale anchored by 0 (“extremely uncharacteristic”)
        and 4 (“extremely characteristic”). The Decision Reinvestment subscale comprises 6
        items, assessing the individual's propensity to consciously monitor their
        decision-making processes, with scores ranging from 0 to 24. The Decision
        Rumination subscale comprises 7 items, assessing tendency to negatively evaluate
        previous poor decisions, with scores ranging from 0 to 28. Kinrade et al. (2010)
        reported an internal consistency of 0.89 for the Decision Reinvestment subscale
        items and 0.91 for the Decision Rumination subscale items.

<hs>  Procedure</hs>
  ~~~~~~~~~

The matches were analysed using digital performance analysis software (Sportscode Elite
Version 9, Sportstec, Australia). A self-devised code window was designed to collect the
number of observable decisions, based on arm signals and vocalisations made by the umpires
during the matches. Observable decisions were infringements that were registered and acted
upon by the official by either a whistle blow or signalling advantage (this did not
include time calls e.g., injury, blood). Also, umpires can decide not to interfere with
play (Helsen & Bultynck, 2004) and these non-observable decisions were not recorded.
Situations in which decisions were unclear were coded separately (accounting for 1.4% of
total decisions made). Two researchers independently coded all the footage; intraclass
correlation coefficients were used to test for inter and intra-observer reliability (ICC
>0.90 for all).

<hs>  Data analyses</hs>
  ~~~~~~~~~~~~~

Preliminary screening of all data, using univariate z-scores (>± 3.29) and multivariate
Mahalanobis distance values revealed one outlier from both the match and umpire data set
which were removed. The data were normally distributed. A repeated-measures ANOVA was
completed to compare differences in the NoD made across quarters. The relationships
between contextual/environmental influences, dispositional tendencies, and decision-making
were examined using two different analyses: one in which matches were treated as cases (n
= 59), and another in which umpires were cases (n = 15 [all umpires] or n = 10 [DSRS
completer's only, accounting for 72% of all matches, n = 42]). Pearson's product moment
correlation coefficient was calculated for all bivariate combinations of the following
variables in the match analyses: NoD; per match and per quarter; overall, in favour of
home teams and in favour of away teams; crowd size; competitive round number; and home,
and away team league positions, and their average. For the umpire analyses, bivariate
correlations included total years of experience, Reinvestment, Rumination and number of
games umpired. For the match-level analysis, all variables that were significantly related
to NoD were entered as predictors into two stepwise multiple regression analyses and one
linear regression, in which backward elimination was used in order to find a model that
best explained the data. NoD, NoD Away, and NoD Home were the criterion measures for each
of the three models. Alpha was set at 0.05 for all statistical tests. Due to the
exploratory nature of the study, and accordingly tentative but directional nature of the
hypotheses, we made no correction for multiple comparisons.

<hs>  Descriptive statistics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The descriptive statistics are presented in Table 1. On average, umpires made 120
observable decisions per game (M = 120.41, SE = 4.07). A repeated-measures ANOVA indicated
that more decisions were made in the first quarter (M = 33.02, SE = 1.14) than in the
third (M = 29.63, SE = 1.16) and fourth (M = 27.72, SE = 1.61) quarters, (F (3, 39) =
4.811, p = 0.006, ηp2 = 0.270). The most common infringement type was contact (M = 45.69,
SE = 1.04), and the most frequently awarded sanction was a penalty (M = 48.77, SE = 1.37).
Descriptive statistics revealed that DSRS scores ranged from 15 to 35 (DSRS Global M =
25.50, SD = 6.67), and Reinvestment subscale score from 7 to 16 (Reinvestment M = 12.8, SD
= 2.82), and Rumination subscale score from 4 to 20 (Rumination M = 12.7, SD = 5.42).

        <hss>Total NoD</hss>

        All match-level bivariate correlations are presented in Table 2. NoD decreased as
        the average league position of the two teams increased (r = -0.269, p = 0.040);
        that is, the higher the positions of the two teams, the greater the NoD.
        Similarly, the higher the home team league position (NB: top position in the
        league = 1), the greater the NoD (r = -0.259, p = 0.047). As the teams progressed
        through the competition rounds, NoD increased (r = 266, p = 0.042). A backward
        stepwise regression was completed to identify the best predictors for NoD
        (variables entered: average league position, round, and home league position). The
        model that best predicted NoD included round and average team position (F (2, 58)
        = 3.919, p = 0.026, R2Adjusted = 0.091), although, when considered individually,
        neither predictor contributed significantly; they only approached significance
        (round p = 0.078, average team position p = 0.074) (see Table 3).

        <hss>NoD home</hss>

        NoD Home increased with the away team's league position (r = -0.340, p = 0.008). A
        linear regression indicated that away league position was a significant predictor
        of NoD (Home) (F (1, 54) = 6.255, p = 0.016, R2Adjusted = 0.089) (see Table 3).

        <hss>NoD away</hss>

        NoD Away increased as home teams' positions improved (r = -0.424, p = 0.001). As
        away teams progressed through rounds (r = 0.344, p = 0.008) or played in front of
        larger crowds (r = 0.312, p = 0.023) the NoD against them increased. A multiple
        regression was run to identify the best predictors for NoD Away (variables entered
        crowd size, round, and home league position) using the backward method. After the
        exclusion of crowd size and round, home team league position was shown to best
        predict NoD Away (F (1, 48) = 7.940, p = 0.007, R2Adjusted = 0.126). (See Table
        3).

        <hss>Total NoD</hss>

        The total number of match decisions was not significantly correlated with any of
        the influences. As the average league position improved the number of decisions
        were greater (r = -0.573, p = 0.032).

        <hss>NoD home</hss>

        NoD Home increased as the competition progressed (i.e. later rounds, r = -0.618, p
        = 0.018) and the away team's league position became more prominent (r = -0.603, p
        = 0.022).

        <hss>NoD away</hss>

        As crowd size increased so did the NoD Away (r = 0.560, p = 0.037) (see Table 4).

        <hss>DSRS</hss>

        The correlations completed with the DSRS subscales include only the data from the
        ten umpires who completed the scale. The Rumination subscale score was
        significantly negatively associated with NoD Q1 (r = -0.795, p = 0.006), NoD Q3 (r
        = -0.709, p = 022), NoD Home Q1 (r = -0.717, p = 0.020) and NoD Home Q3 decisions
        (r = -0.660, p = 0.038); that is, higher Rumination subscale scores were
        associated with fewer decisions. Reinvestment subscale scores were not
        significantly correlated with any NoD variables.

<h>DISCUSSION</h>
----------

In an exploratory study, we examined the influence of contextual and dispositional
differences on decision-making of umpires in actual match settings. We hypothesised, based
on existing literature, that environmental and contextual influences (i.e., larger crowds,
more prominent teams, greater match significance, and early quarters) would be associated
with lower decision frequencies. Furthermore, we predicted that inhibited decision-making
would be associated with a dispositional tendency to reinvest and ruminate. In line with
our hypotheses, match prominence and league position were associated with a reduction in
the number of decisions. The Decision Rumination factor was linked with inhibited decision
making; but contrary to our hypothesis, the Reinvestment factor was unrelated. In contrast
to our hypotheses, increasing crowd size was associated with a greater number of
decisions, particularly against away teams; and the number of decisions diminished
throughout a match. Our data indicated that more decisions were made in Q1 (33 decisions)
than in Q3 (29 decisions) and Q4 (27 decisions), incongruent to our hypothesis and the
findings by Mallo et al. (2012) and Elsworthy et al. (2014). These differences could be
related to physical fitness and fatigue of umpires; for example, Paget (2015) found that
the distance covered by netball umpires was significantly reduced in the fourth quarter.
It is possible that, if umpires are physically fatigued and not covering the same
distances as they did in the early stages of a match, the fewer decisions later in the
game could be those missed or avoided as a result of incorrect positioning. Multiple
researchers have highlighted the link between position (distance and angle) of soccer
referees and decision performance (e.g., Gilis, Helsen, Catteeuw, & Wagemans, 2008; Mallo
et al., 2012; Oudejans et al., 2000, 2005). For example, Mallo et al. (2012) demonstrated
referees had a lower number of incorrect decisions when the referees were positioned in
the central area of the field. Research in medical and military settings has shown that
fatigue and physical exertion have a detrimental effect on decision-making (e.g., Kovacs &
Croskerry, 1999; Larsen, 2001). However, in sport contexts, decision-making performance
was shown to be unaffected by physical exertion in Australian football umpires (Elsworthy,
Burke, Scott, Stevens, & Dascombe, 2014; Paradis, Larkin, & O'Connor, 2015), fatigue in
English Premier League assistant referees (Catteeuw, Gilis, Wagemans, & Helsen, 2010) or
physical performance of New Zealand Football Championship referees (Mascarenhas et al.,
2009). Thus, it is possible the change in the number of decisions is in response to the
reducing work rate of the players or level of performance. For example, Weston and
colleagues (Weston, Bird, Helsen, Nevill, & Castagna, 2006; Weston et al., 2012) found
that soccer referees and players high intensity running distance, ball travel, and total
distance covered were correlated. However, further research is required to understand the
link between player and referee physical performances and their impact on referee
decision-making. As suggested by Poolton et al. (2011), higher Rumination subscale scores,
and not Reinvestment scores, were strongly associated (r > -0.7) with fewer decisions in
Q1 and Q3. Notably, higher ruminators made fewer decisions against home teams during those
quarters. Burke, Joyner, Pim, and Czech (2000) demonstrated that basketball officials'
cognitive anxiety was higher pre-game, and at half time when compared to post-game. It is
possible that prior to the start of the game, where officials arrive at the venue early
and watch the teams' warm-up pre-game, and during the half-time break, there is greater
potential for officials to engage in ruminative thoughts than during the smaller breaks
taken between Quarters 1 and 2, and 3 and 4. To our knowledge, no researchers have
investigated the timing of sports officials' decision ruminations. However, Roy et al.
(2016) explored the timing of rumination by asking hockey players to rate on a 5-point
scale whether they would continue to think about the play when it was over and their role
in the play (past play), and how the team and individual would perform in the rest of the
match (future play). Their results indicated that participants were unlikely to think
about previous play after it was over, or about how the game would unfold; however, they
were more likely to think about past play than future play. The authors suggested that the
low rumination observed in successful field hockey players could reflect that people low
in rumination do best in tasks requiring quick shifts of attention (such as dynamic team
sports). Alternatively, a possible explanation might be that umpires engage in avoidance
behaviours to reduce the chance of scrutiny of their decisions (Anderson, 2003). Contrary
to our hypothesis, but consistent with Poolton et al. (2011), Reinvestment subscales
scores were not related to the number of decisions. A home advantage effect was observed;
the descriptive statistics indicated that more decisions were awarded against away teams,
supporting findings in soccer, that home teams were awarded more penalties (Nevill et al.,
1996) and that more yellow cards were awarded to away teams (Goumas, 2014). Factors
purported to contribute to the home advantage include travel (i.e. greater time and
distances for the away team), referee bias, familiarity and crowd size (Pollard, 2008).
Furthermore, the correlations suggested that for matches in later rounds, where there is
often greater importance due to more matches influencing final placings, play-offs and
finals, fewer decisions were awarded against home teams. One explanation could be that
officials exhibit avoidance-type behaviours to cope with the increases in anxiety
resulting from increased perceived importance. Hill et al. (2016) found that rugby
referees highlighted the importance of the game as one of the stressors affecting their
performance, and that some referees use avoidance coping methods (e.g., Jordet & Hartman,
2008) to manage this stressor. It is possible that umpire experience could have confounded
these figures, however a correlation between round and the umpires years of experience,
where you might expect the most experienced umpires to officiate the latter rounds, was
non-significant (r = 0.126, p = 728). Our results are consistent with previous research
(e.g., Boyko et al., 2007; Page & Page, 2010) where increases in crowd size were
associated with an increase in the number of decisions against away teams. One possible
explanation is that when faced with a difficult decision, officials draw on other salient
cues (e.g., crowd noise), particularly when placed under time constraints (Balmer et al.,
2007). In order to reduce the complexity of a decision (Souchon et al., 2010) umpires' may
use simple heuristics (Raab, 2012). For example, if two opposing players contested a ball
and the umpire was unsure of the penalty decision, they may place equal weight on the
auditory crowd cues as they do their visual information. Crowd noise typically favours the
home team, resulting in more decisions against away teams (Nevill & Holder, 1999). This
finding is reflected in our data, with larger crowd sizes associated with more decisions
against away teams. Alternatively, researchers have reported that crowd noise induces a
reluctance to penalise the home team (Nevill et al., 2002) (i.e., an absence of crowd
noise indicates to the referee that no serious offence has been committed). The number of
years' experience was not associated with the number of decisions made. This may be due to
the number of years' experience umpiring at Superleague level (which was not recorded) or
that there was little to no difference in qualification (Hancock & Ste-Marie, 2013). Other
researchers have found the referee's experience to influence decision -making. Nevill et
al. (2002) found as referees experience increased, that more fouls were awarded against
home players, until a peak of 16 years, where upon a decline was then observed. However,
the number of games umpired was positively associated with Reinvestment subscale scores.
Potentially, those umpires who deliberate more on their decisions are deemed more
effective and are therefore requested to umpire more often. League position predicted
fewer decisions against home teams when playing lower positioned away teams, and for away
teams playing lower positioned home teams. This finding may be similar to the reputation
bias of judges found by Findlay and Ste-Marie (2004) and Plessner (1999) whereby teams
with a better performance reputation may be sanctioned less. Alternatively, it is possible
that the results of this study could be explained by the differences in players (e.g.,
lower ability teams or less competitive matches), or players' susceptibility to pressure,
and not that of the officials. Previously, researchers have reported that yellow cards
against away players in soccer could be a consequence of a poorer psychological state when
compared with playing at home (Bray, Jones, & Owen, 2002; Terry, Walrond, & Carron, 1998).
There were several limitations that need to be acknowledged. First, we had incomplete data
for crowd size, resulting in six matches being excluded from the crowd size analyses.
Similarly, not all umpires who officiated the season completed the DSRS and were therefore
excluded from the correlational analyses. However, those who did complete the DSRS
officiated 72% of the matches analysed. Second, the accuracy of decisions was not
recorded, preventing insight into the performance change of umpires exposed to different
contextual and environmental conditions or comparisons between those with greater or
lesser disposition to ruminate. However, it was not practically possible to obtain
objective assessments of every decision made by the officials across the season. We also
acknowledge that rumination is often seen as a negative process (referring to passive
self-critical worrisome or anxious thinking, Trapnell & Campbell, 1999; Treynor, Gonzalez,
& Nolen-Hoeksema, 2003), whereas self-reflection (considered to be a motivated process
aimed at understanding in the self and overcoming problems and difficulties, Trapnell &
Campbell, 1999; Treynor et al., 2003) on performance is an important post-game learning
tool used by sports officials (MacMahon et al., 2015). Although the DSRS items refer to
negative ruminative thoughts, our study design did not allow us to collect data on the
types or timings of rumination/reflection. Further investigation is required to examine
the relationship between rumination and performance in sports officials, with reference to
the types (rumination versus reflection) and timings (before, during, and after
performance) of ruminations officials' make through self-report or stimulated recall.
Third, we cannot isolate the influence of each potential bias using the current study
design. The number of decisions umpires make may be a result of a combined effect of crowd
sizes, league position, round, and time. For example, you might expect later rounds to
have greater crowd sizes, which could have confounded our data. However, a correlation
between round and crowd size, was not significant (r = 0.136 p = 0.326). It would be
beneficial to investigate these effects in isolation in a controlled environment in order
to draw clearer conclusions regarding the potential influence of these factors.
Furthermore, we cannot be certain that the players' performance was not affected by the
same contextual, environmental or dispositional influences, leading the umpires to adjust
their decision-making accordingly. Finally, we used observational data and descriptive and
correlational analyses. An advantage of the use of observational data is the high external
validity, making the results easily interpretable and applicable in the real world. While
our approach is novel and the study presents the first empirically based analysis of
netball officiating behaviour we cannot infer causality from the findings. In future,
controlled experiments are required to establish any causal links that may be implied in
our data. For example, future research should examine the specific crowd factors that lead
to changes in decision-making behaviour such as examining the impact of volume on
decision-making, where crowd size has been linked to crowd noise (Hayne, Taylor, Rumble, &
Mee, 2011); or investigating the semantics of crowd members (e.g., relevant or irrelevant
to the decision, Bishop, Moore, Horne, & Teszka, 2014). In summary, we explored putative
contextual/environmental and dispositional influences on netball umpires' decision-making.
We observed a home advantage effect, whereby more decisions were awarded against away
teams when crowd sizes were greater. We found a reduction in the number of observable
decisions made, against teams with higher status, in more important matches, as the time
played in a match decreased and as a function of increasing levels of Decision Rumination.
Our study presents the first empirically-driven task analysis of the demands of refereeing
in netball and highlights a number of key areas for which follow-up research comprising
experimental designs and manipulations may be employed.


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<ART>Delusions as harmful malfunctioning beliefs
===========================================

Authors: Kengo Miyazono
DOI: 10.1016/j.concog.2014.10.008
Year: 2015  |  Pages: 561-573
ASJC codes: 3204, 3205
Keywords: Delusion, Harmful dysfunction analysis of disorder, Malfunction, Schizophrenia, Teleosemantics

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Delusional beliefs are typically pathological. Being pathological is clearly distinguished from being false or being irrational. Anna might falsely believe that his husband is having an affair but it might just be a simple mistake. Again, Sam might irrationally believe, without good evidence, that he is smarter than his colleagues, but it might just be a healthy self-deceptive belief. On the other hand, when a patient with brain damage caused by a car accident believes that his father was replaced by an imposter or another patient with schizophrenia believes that "The Organization" painted the shops on a street in red and green to convey a message, these beliefs are not merely false or irrational. They are pathological. What makes delusions pathological? This paper explores the negative features because of which delusional beliefs are pathological. First, I critically examine the proposals according to which delusional beliefs are pathological because of (1) their strangeness, (2) their extreme irrationality, (3) their resistance to folk psychological explanations or (4) impaired responsibility-grounding capacities of people with them. I present some counterexamples as well as theoretical problems for these proposals. Then, I argue, following Wakefield's harmful dysfunction analysis of disorder, that delusional beliefs are pathological because they involve some sorts of harmful malfunctions. In other words, they have a significant negative impact on wellbeing (=harmful) and, in addition, some psychological mechanisms, directly or indirectly related to them, fail to perform the jobs for which they were selected in the past (=malfunctioning). An objection to the proposal is that delusional beliefs might not involve any malfunctions. For example, they might be playing psychological defence functions properly. Another objection is that a harmful malfunction is not sufficient for something to be pathological. For example, false beliefs might involve some malfunctions according to teleosemantics, a popular naturalist account of mental content, but harmful false beliefs do not have to be pathological. I examine those objections in detail and show that they should be rejected after all.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Delusional beliefs are typically pathological.1 Being pathological is clearly
distinguished from being false or being irrational. Anna might falsely believe that her
husband is having an affair but it might just be a simple mistake. Again, Sam might
irrationally believe, without good evidence, that he is smarter than his colleagues, but
it might just be a healthy self-deception. On the other hand, when DS, a patient with
brain damage caused by a car accident, believes that his father was replaced by an
imposter (Hirstein & Ramachandran, 1997) or Peter with schizophrenia, believes that “The
Organization” painted the shops on a street in red and green to convey a message
(Chadwick, 2001), these beliefs are not merely false or irrational. They are pathological.
What makes delusional beliefs pathological? This paper explores the negative features
because of which delusional beliefs are pathological. In Section 2, I critically examine
the proposals according to which delusions are pathological because of (1) their
strangeness, (2) their irrationality, (3) their resistance to folk psychological
explanations or (4) impaired responsibility-grounding capacities of people with them. I
present some counterexamples as well as theoretical problems for these proposals. In
Section 3, I argue, following Wakefield’s harmful dysfunction analysis of disorder, that
delusional beliefs are pathological because they involve some sorts of harmful
malfunctions. In other words, they have a significant negative impact on wellbeing
(=harmful) and, in addition, some psychological mechanisms, directly or indirectly related
to them, fail to perform the jobs for which they were selected in the past
(=malfunctioning). An objection to the proposal is that delusional beliefs might not
involve any malfunctions. For example, they might be playing psychological defence
functions properly. Another objection is that a harmful malfunction is not sufficient for
something to be pathological. For example, false beliefs might involve some malfunctions
according to teleosemantics, a popular naturalist account of mental content, but harmful
false beliefs do not have to be pathological. I examine those objections in detail in
Section 4 and show that they should be rejected after all. The central question of this
paper is about what makes delusional beliefs pathological. Before starting, I have several
remarks on the idea that delusional beliefs are pathological. First, when I use the term
“pathological” in talking about mental states, I refer to the property of the mental
states in virtue of which they constitute, together with other symptoms, mental disorders.
Delusional beliefs, together with other positive and negative symptoms, constitute
schizophrenia, for example. Second, the idea that a belief is pathological is different
from the idea that it is delusional. Unfortunately, there is no uncontroversial definition
of delusionality. According to DSM-5, a delusion is “a false belief based on incorrect
inference about external reality that is held despite what almost everyone else believes
and despite what constitutes incontrovertible and obvious proof or evidence to the
contrary” (American Psychiatric Association, 2013, p. 819). This definition is, however,
very controversial. Delusions might be accidentally true. Some delusions are not about
external reality but rather about internal mental states. Some delusions might not be
based on inference of any sort, and so on. In this paper, I simply stipulate that a belief
is delusional if sufficient psychiatrists regard it as delusional. Third, I assume that
delusionality and pathology can come apart, at least, in principle. First, some delusional
beliefs might not be pathological. For example, it is often argued that healthy
individuals can have delusional beliefs or delusion-like ideas.2 A person without any
psychiatric diagnosis might have a paranoia belief that his colleagues are trying prevent
him from being promoted. The belief is delusional (i.e. regarded as delusional by
psychiatrists) but not pathological (i.e. does not constitute a mental disorder). Again,
some pathological beliefs might not be delusional. For example, some instances of
confabulations or obsessive thoughts might involve non-delusional pathological beliefs. It
is conceivable that a person has obsessive thoughts about being contaminated by gems, but
the thoughts are not delusional because he perfectly recognizes their implausibility. The
thoughts in such a case are pathological (i.e. constitute a mental disorder, such as OCD)
but not delusional (i.e. not regarded as delusional by psychiatrists).3

<h>SOME UNSUCCESSFUL ANSWERS</h>
-------------------------

(1) Strangeness: Anna’s belief that his husband is having an affair is false but it is not
very strange. Many married women can have the same belief at some point. DS’s belief that
his father was replaced by an imposter, on the other hand, is not only false but also
strange.4 The same thing is true about Peter’s belief that The Organization painted the
shops to convey a message. This observation motivates the first proposal, according to
which delusions are pathological because their strange content. In other words, the
pathology of delusion comes from the abnormality of the content. A problem of this
proposal is that it is not obvious that all delusions are significantly stranger than
healthy beliefs. Peter’s belief is certainly strange. But, there are some healthy beliefs
that are as strange as his. For example, Murphy (2013) discusses a community in Sudan
where it is believed that ebony trees provide important social information. The belief
about ebony trees is culturally normal and hence not pathological. Nonetheless, it seems
to be as strange as Peter’s delusional belief. One might think, however, that this problem
can be solved by introducing a culture-relative notion of strangeness. The idea, for
example, is that the belief about ebony trees is not strange relative to the culture in
the community. Peter’s belief, on the other hand, is strange relative to the culture in
the western, modern community to which he belongs. But, this response does not solve all
the problems, because pathological delusions and healthy beliefs with similar content can
exist in the same cultural contexts. For example, it can be difficult to distinguish
Anna’s belief from the delusional jealousy in Othello syndrome by content alone.
Presumably, the main difference between healthy beliefs about the partner’s infidelity and
delusional jealousy is not about the content but rather about the sensitivity to the cues.
As Easton, Schipper, and Shackelford noted, delusional jealousy “can be thought of as
hypersensitive jealousy, as these individuals experience jealous reactions at a much lower
threshold than normal individuals” (Easton, Schipper, & Shackelford, 2007, p. 399).
Another problem is that being strange is not sufficient for a belief to be pathological.
Philosophers seriously believe very strange things. But, typically, these philosophical
beliefs are not the expressions of a mental disorder, but rather of remarkable insights
and argumentative skills. For example, there are some philosophers who seriously believe
that every single object in the universe is conscious (panpsychism), that, for any
objects, however arbitrary they are chosen, there is a further object that is composed by
them (unrestricted composition), that there are facts about the boundaries of a vague
predicate which we can never discover (epistemicism about vague predicates), and so on.
(2) Irrationality: Sam’s belief that he is smarter than his colleagues is irrational but,
presumably, DS’s belief that his father was replaced by an imposter and Peter’s belief
that The Organization painted the shops to convey a message are more irrational. Maybe,
they are too irrational. According to the second proposal, delusion is pathological
because of their extreme irrationality.5 However, it is not obvious that delusional
beliefs are extremely irrational. According to empiricist accounts of delusion formation,
which is very influential recently, delusions are formed in response to abnormal
experience. Given the fact that the abnormal experience can be understood as a kind of
evidence for delusional beliefs, it is not obvious at all that, according to empiricism,
delusions are extremely irrational. Indeed, a number of empiricist researchers support the
view that a delusion is a reasonable response to abnormal experience. Maher famously
argued that delusions “are derived by cognitive activity that is essentially
indistinguishable from that employed by non-patients, by scientists, and by people
generally” (Maher, 1974, p. 103). Coltheart, Menzies, and Sutton (2010) support this claim
and argue that it is perfectly Bayesian rational for a Capgras patient to adopt the
imposter hypothesis rather than the competing, realistic hypotheses given the abnormal
data. (They do not use the term “experience” because they think that the “data” are not
consciously accessible.) The imposter hypothesis actually gets a higher posterior
probability than the competing hypotheses. Similarly, Corlett and colleagues argue that it
is hard for a Capgras patient to avoid the imposter hypothesis given the abnormal
experience they have; “the phenomenology of the percepts are such that bizarre beliefs are
inevitable; surprising experiences demand surprising explanations” (Corlett, Taylor, Wang,
Fletcher, & Krystal, 2010, p. 360). Still, the view that a delusion is a rational response
to abnormal experience is controversial. Stone and Young (1997), for instance, argue that
delusional beliefs are produced not only by abnormal experience but also by the irrational
reasoning with the bias toward observational adequacy; people with delusion irrationally
put more emphasis on incorporating new observations into belief system (observational
adequacy) than keeping existing beliefs as long as possible (doxastic conservatism). McKay
(2012) follows this suggestion and argues, in response to Coltheart et al. (2010) that
delusional beliefs are produced through the Bayesian-irrational reasoning process with the
bias of discounting prior probabilities of the hypotheses; people with delusion
irrationally put more emphasis on likelihoods (which summarize how nicely hypotheses
explain the observation) than prior probabilities (which summarize how probable the
hypotheses are prior to the observation). But, even if one of those views is correct, it
is still not obvious that delusional beliefs are extremely irrational. Similar irrational
biases might be found in healthy beliefs as well. For example, the famous study by
Kahneman and Tversky on the base-rate neglect (1973) shows that normal people have the
strong tendency to neglect the base-rate information that is relevant for given
hypotheses. Here, the base-rate information gives the prior probabilities of the
hypotheses at issue. Thus, the tendency to neglect the base-rate information can be
understood as the tendency to neglect prior probabilities. One of the basic principles of
statistical prediction is that prior probability, which summarizes what we knew about the
problem before receiving independent specific evidence, remains relevant even after such
evidence is obtained. Bayes’ rule translates this qualitative principle into a
multiplicative relation between prior odds and the likelihood ratio. Our subjects,
however, fail to integrate prior probability with specific evidence. [ …] The failure to
appreciate the relevance of prior probability in the presence of specific evidence is
perhaps one of the most significant departures of intuition from the normative theory of
prediction (Kahneman & Tversky, 1973, p. 243). Experimental studies revealed some “biases”
in judgment processes of people with delusion. However, the studies do not necessarily
support the idea that delusions are very irrational. The term “bias” can be used in, at
least, two different ways. It might refer to the deviation from the norm of (logico-
mathematical) rationality. When we say that the tendency to neglect the base-rate
information is “biased”, the term is used in this sense. It deviates from the Bayesian
norm of rationality. Alternatively, the term might refer to the deviation from the
performance of normal people. In the context of the delusion research, the term “bias” is
often used in the second way. So, it is perfectly possible that the “biased” performance
of people with delusion does not actually deviate from the norm of rationality. This
possibility is nicely illustrated by the well-known study of the “jumping-to-conclusion
bias” (Huq, Garety, & Hemsley, 1988). It was found in the study that people with delusion
have the tendency to “jump to conclusion”; they require less evidence before coming to
conclusions than people in control groups (healthy people and non-delusional people with
schizophrenia). At the same time, though, it was also found that the performance of people
with delusion is more rational from a mathematical point of view than that of people in
control groups. People with delusion reach the conclusion when the probability of the
hypothesis is reasonably high, while people in control groups do not reach the conclusion
until the probability is unnecessarily high. So, Huq et al. wrote; “[i]t may be argued
that the deluded sample reached a decision at an objectively ‘rational’ point. It may
further be argued that the two control groups were somewhat over cautious” (Huq et al.,
1988, p. 809). (3) Understandability: Sam’s belief that he is smarter than his colleagues
is irrational, but it is “understandable” in the sense that we can give a simple folk
psychological account of it. Sam comes to believe it because he wants it to be the case
that he is smarter than his colleagues. In other words, his belief is driven by the desire
to be smarter than the colleagues. On the other hand, DS’s belief that his father is
replaced by an imposter and Peter’s belief that The Organization painted the shops to
convey a message are not “understandable” in this way. There are no easy folk
psychological explanations of those delusional beliefs. According to the third proposal,
delusions are pathological because of the “ununderstandability” or the resistance to folk
psychological explanations. But, this view is not fully satisfactory. First, it is not
clear that the all delusions resist folk psychological explanations. Sam’s belief is
“understandable” because we can identify the motivational factors that play crucial roles
in the formation of the belief. But, then, when motivational factors play crucial roles
for some delusions, at least those delusions are “understandable” by identifying those
motivational factors.6 Butler (2000) reported the case of B.X. who had the delusion about
the fidelity of his former romantic partner (reverse Othello syndrome). B.X. was a gifted
musician who had been left quadriplegic following a car accident. One year after his
injury, he developed delusional beliefs about the continuing fidelity of his former
romantic partner, N., who had in fact severed all contact with him soon after the
accident. A pretty straightforward folk psychological explanation of this case would is
that B.X. formed his delusional beliefs because he desperately wanted it to be the case
that N. still loved him. In other words, his delusional beliefs were driven by the desire
that N. still loved him. Second, resisting folk psychological explanation does not seem to
be sufficient for beliefs, or mental states in general, to be pathological. The so-called
“twisted self-deception” is a good example. Twisted self-deceptive beliefs are, roughly
speaking, the unwelcome irrational beliefs. For example, if it turns out that Anna’s
belief about the husband’s affair is not supported by the available evidence at all, it is
a twisted self-deceptive belief. Presumably, there is no straightforward folk
psychological explanation of twisted self-deceptive beliefs. Mele (1999) provides an
influential account according to which twisted self-deceptive beliefs are produced by the
people’s tendency to avoid costly errors. If, on one hand, Anna falsely believes that her
husband is having an affair, then the falsity is not very costly. For example, it just
annoys the husband. If, on the other hand, she falsely believes that the husband is not
having an affair, then the falsity is very costly. The relationship is seriously
threatened in that case. This account is not purely folk psychological. The idea that
people choose their beliefs so that they can avoid costly errors does not seem to be a
part of folk psychology. Indeed, the idea comes from the scientific, not folk,
psychological theory by Friedrich (1993). Another example comes from Gendler (2008). Many
people experience an extreme fear when they walk on the horseshoe-shaped transparent
walkway on the 4000 feet above the floor of the Grand Canyon. There is nothing abnormal or
pathological in this experience. As Gendler noted, “the basic phenomenon—that stepping
onto a high transparent safe surface can induce feelings of vertigo—is both familiar and
unmysterious” (Gendler, 2008, p. 635). The people who walk on the walkway seem to believe
that the walkway is safe. But, then, why do they feel the extreme fear? The fear seems to
be ungrounded if they seriously believe that the walkway is safe. Are they, then, somewhat
sceptical about the safety? But, in that case, we cannot explain the fact they step onto
the walkway in the first place. Presumably, there is no easy folk psychological
explanation of the fear. Gendler argues that they feel the extreme fear because they
alieve that the walkway is not safe, although they believe that it is safe. Alief is,
roughly speaking, “a mental state with associatively linked content that is
representational, affective and behavioral, and that is activated—consciously or
nonconsciously—by features of the subject’s internal or ambient environment” (Gendler,
2008, p. 645). Although alief sounds like another folk psychological state, Gendler’s
account of the case is not purely folk psychological. After all, alief is not a part of
the conceptual repertoire of folk psychology. Presumably, it is best understood as an
extended folk psychological account.7 (4) Responsibility: Suppose that Anna, on the basis
of her belief, acts violently to the woman who is mistakenly regarded as the affair
partner. The falsity of the belief does not change the fact that Anna is responsible for
what she does. Anna is clearly responsible for her violence. On the other hand, if DS,
because of his delusional belief, had acted violently to his father, he would not have
been fully responsible for the violence. People with Capgras delusion sometimes act
violently on the basis of their delusional beliefs. In a tragic case in Louisiana in 2011,
for instance, a father beheaded his disabled son because he believed that the son was had
been replaced by a CPR dummy. Following the testimony by forensic psychiatrists, he was
ruled not guilty by reason of insanity. The forth proposal is that delusions are
pathological because of responsibility-grounding capacities, such as decision-making
capacity or autonomous agency, are significantly impaired in people with delusion. It is,
however, not obvious that responsibility-grounding capacities are always impaired in
people with delusion. Certainly, it is very likely that belief-forming or belief-checking
capacities are impaired somehow in them. But, the impairment in belief-forming/checking
capacities might be dissociated from the impairment in responsibility-grounding
capacities. A possible response to this challenge is that belief-forming/checking
capacities are relevant to the attribution of responsibility. In other words,
responsibility-grounding capacities include belief-forming/checking capacities. For
example, according to M’Naghten rules, a person is not responsible for what he does when
he is ignorant of “the nature and quality of the act he was doing.” Presumably, people
with delusion are ignorant of the nature and quality of their acts because of impaired
belief-forming/checking capacities and, hence, they are not responsible for the acts.
However, this response is not very convincing. Certainly, there is a sense in which a
violent Capgras patient is ignorant of the nature and quality of his act; he thinks that
he is attacking the imposter, which is false. But, this is also true about Anna; she
thinks that she is attacking the affair partner, which is false. So, if “being ignorant”
means “having the false belief” or “not having the true belief”, then Anna is as ignorant
as violent Capgras patients. The phrase might be interpreted in different ways, but it is
not clear that there is an interpretation according to which violent Capgras patients are
significantly more ignorant than Anna. Another response is that delusion is just a tip of
iceberg. People with delusion often have other kinds of abnormalities at the same time and
these abnormalities impair responsibility-grounding capacities. For instance, delusions in
the context of schizophrenia are accompanied by other positive and negative symptoms that
directly or indirectly impair responsibility-grounding capacities. However, we cannot
assume a priori that responsibility-grounding capacities are compromised in people with
schizophrenia in general. There might be serious individual differences about the quality
of responsibility-grounding capacities of people with schizophrenia given the fact that
schizophrenia is an extremely heterogeneous condition. Maybe, the fact that one gets the
diagnosis of schizophrenia in itself does not tell us much about his responsibility-
grounding capacities. As Bortolotti, Broome, and Mameli (2013) pointed out, “[t]he
assumption that people who have psychotic symptoms or have received a diagnosis of
schizophrenia lack responsibility or have reduced responsibility for action is especially
problematic, as the behavior of two people with psychosis or schizophrenia can differ
almost entirely. Some people with schizophrenia are able to function well, cognitively and
socially, and to control their delusions to some extent.”

<h>HDA AND DELUSION</h>
----------------

I believe that the main problem of the previous proposals is that they are detached from
the considerations about what, in general, makes a condition pathological. In order to
explain why a condition X is pathological, first, we need to have a general account of the
features that make conditions pathological and, then, show that X has the features as
well. But, the previous proposals skip the first step and simply point out some remarkable
negative features of delusion. This invites all sorts of counterexamples and difficulties.
Wakefield (1992a, 1992b) presented a general account of disorder, which is very
influential and, in my view, more plausible than its rivals. It is often called “Harmful
Dysfunction Analysis of Disorder.” I will call it “HDA.” According to HDA, disorders are
“harmful malfunctions” or “harmful dysfunctions.” Being “harmful” means having a negative
impact on wellbeing. The harmfulness condition is important because “disorder is in
certain respects a practical concept that is supposed to pick out only conditions that are
undesirable and grounds for social concern” (Wakefield 1992b, p. 237). A “malfunction” is,
roughly speaking, the failure to perform an etiological function,8 where the etiological
function of something is the performance for which it was selected in the past.9 For
instance, a heart malfunctions when it fails to pump blood, a kidney malfunctions when it
fails to filter metabolic wastes from blood, a corpus callosum malfunctions when it fails
to facilitate interhemispheric communications, and so on. My proposal, which relies on
HDA, is that delusions are pathological because (1) they are harmful and (2) they involve
some etiological malfunctions directly or indirectly. I will call (1), and (2) “the
harmfulness thesis” and “the malfunction thesis” respectively. There are many objections
to HDA. It should be noted, however, that most (if not all) objections are aiming at
refuting the necessity claim of HDA, namely, the claim that a harmful etiological
malfunction is necessary for a disorder. This means that those objections are not very
serious for my purpose. What is crucial for my account is that a harmful etiological
malfunction is sufficient for a disorder. We can say that delusions are pathological
because they involve harmful etiological malfunction as long as a harmful etiological
malfunction is sufficient for a disorder. For example, Tengland (2001) argues that viral
infection is a counterexample to HDA. Viral infection is a disorder but its symptoms (e.g.
fever, cough, sneezing) are very often biological defences, not malfunctions. Again,
Murphy and Woolfolk (2000) argue that appendicitis is another counterexample. Appendicitis
is clearly a disorder, but vestigial organs such as appendix cannot fail to perform its
etiological functions because they do not them in the first place.10 Wakefield argues, in
response to Tengland, that viral infection involves etiological malfunctions at the level
of cell (Wakefield, 2011) and, in response to Murphy and Woolfolk, that appendicitis
involves etiological malfunctions at the level of tissue (Wakefield, 2000). In my opinion,
Wakefield’s responses are convincing. But, even if they are not, those counterexamples are
not very serious for my account, because they are the counterexamples to the necessity of
a harmful etiological malfunction for a disorder.

<hs>  The harmfulness thesis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Delusions seem to be harmful in all sorts of ways. Delusions do not only cause
psychological stress and anxiety but also harmful consequences in the life of the people
with them, such as losing a job or failing to maintain relationship with other people.
McKay and colleagues propose the following definition of delusions, which explicitly
mentions the harmfulness of delusions; “A person is deluded when they have come to hold a
particular belief with a degree of firmness that is both utterly unwarranted by the
evidence at hand, and that jeopardises their day-to-day functioning [emphasis added]”
(McKay, Langdon, & Coltheart, 2005, p. 315). Delusions can be especially harmful when
people act on them. There are many reported cases where people perform harmful actions on
the basis of their delusions. The case in Louisiana that I already mentioned, for example,
a father killed his disabled son on the basis of his Capgras delusion, which is not only
harmful to the son (being killed), but also to the father (killing his own son without
knowing).11,12 Some clarifications are in order. First, the “harm” at issue does not have
to be the harm to people with delusion themselves. It might be the harm to people around
them, such as family members, friends, colleagues, or neighbours. It is conceivable that
some people with delusions are happy because of them at some point. For example, the
grandiose delusion about special abilities given by God might make some people happy at
some point. Still, the delusion might be harmful overall because of the serious troubles
it causes for other people. Second, the harmfulness thesis is not about hedonistic pains
or pleasures. The life on the experience machine (the machine that produce the perfect
illusion of leading whatever kind of life one desires, while one floats about in a tank)
is extremely pleasurable from the hedonistic point of view. But, typically, we do not find
the life very attractive. Nozick argues that the life is not attractive because “we want
to be a certain way, to be a certain sort of person. Someone floating in a tank is an
indeterminate blob. There is no answer to the question of what a person is like who has
long been in the tank. Is he courageous, kind, intelligent, witty loving? It’s not merely
that it’s difficult to tell; there’s no way he is” (Nozick, 1974, p. 43). Similarly, it is
conceivable that the life with the grandiose delusion about special abilities is really
pleasurable from the hedonistic point of view. But, again, it does not mean that the life
is really attractive. It is not attractive because, as a matter of fact, the person with
the delusion fails to be the person he really wants to be. He wants to have some special
abilities that distinguish him from others. However, he does not have such abilities. His
real life might not be less miserable the one in the tank. Third, there is an implicit
ceteris paribus clause in the harmfulness thesis. Delusions are ceteris paribus harmful.
For example, we can imagine the case where Peter avoided a fatal plane crash because he
had changed the reservation due to his delusional belief that The Organization wants him
to do so. In this case, his delusional belief is beneficial rather than harmful. Actually,
the same thing is true about disorders in general. For example, we can easily imagine the
case where Peter avoided the plane crash because he had changed his reservation due to his
flu. But, of course, the case does not show that flu is not harmful. The claim that flu is
harmful has an implicit ceteris paribus clause and these tricky cases do not contradict
the ceteris paribus claim.

<hs>  The malfunctioning thesis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

According to the malfunctioning thesis, delusions involve some etiological malfunctions.
What kinds of malfunctions are they exactly? A fully satisfactory answer to this question
is not available yet because the process of delusion formation and maintenance has not
been fully understood. Still, the current understanding of the process is informative
enough to help us to identify good candidates.13 First, according to the empiricist
theories, delusions are formed in response to abnormal experience. In this view, there
might be some etiological malfunctions in the mechanisms that are responsible for the
abnormal experience. For example, Ellis and Young (1990) argue that Capgras delusions are
formed in response to the abnormal experience of seeing familiar faces which is caused by
the disconnection between autonomic nervous system and face recognition system.14 This
hypothesis is supported by the finding that people with Capgras delusion do not show the
asymmetrical autonomic responses between familiar faces and unfamiliar faces (Ellis,
Young, Quayle, & De Pauw, 1997). The experience of Capgras patient is abnormal in that it
lacks the affective component that is usually a part of the experience. A Capgras delusion
is formed as an explanation of this abnormal perceptual-affective experience. Second,
there might be some etiological malfunctions in attention mechanisms. According to
prediction-error theories (Corlett et al., 2010; Fletcher & Frith, 2009), people with
delusion have problems in the allocation of attention caused by aberrant prediction-error
signals. Prediction-error signals are the indicators of the mismatch between expectations
and actual inputs. They guide the process of attention allocation in such a way that
attention is paid to the things or events that defy expectations. Due to aberrant
prediction-error signals, people with delusion pay attention to the things or events that
are not actually important. A delusion arises as the explanation of the apparent
significance of these things and events. The study by Corlett et al. (2007) supports this
hypothesis. In the study, two groups of participants (people with and without delusion)
were tested with a task involving learning the association between certain foods and
allergic reactions, while the activity of the right prefrontal cortex (which was
identified as a reliable marker of prediction-error processing in previous studies) was
monitored with fMRI. In the delusional group but not in the control group, the magnitude
of the activity of the right prefrontal cortex was not significantly different between the
cases where expectations about allergic reaction were confirmed and the cases where they
were violated. In other words, in the delusional group, the right prefrontal cortex fails
to distinguish prediction-error from prediction-confirmation.15 Third, the two-factor
theories (Coltheart, 2007; Davies, Coltheart, Langdon, & Breen, 2001) posit the so-called
“second factor”, namely, the factor that explains the adoption and/or maintenance of
delusional hypotheses. The second factor is often associated with the damage to right
frontal lobe. If the second factor really exists, then there can be some etiological
malfunctions that are responsible for it. The main reason for positing the second factor
is that it explains the difference between people with delusions and people without
delusions who are experientially equivalent. For example, patients with the damage to the
ventromedial prefrontal cortex do not adopt imposter hypotheses but are often regarded as
experientially equivalent to people with a Capgras delusion. Unfortunately, there is no
agreement on the nature of the second factor. Here is a recent proposal. Coltheart et al.
(2010) argue that the second factor is the bias of neglecting contradictory evidence after
adopting delusional beliefs.16 After a Capgras patient adopts the imposter hypothesis, he
will be exposed to contradictory evidence such as the behavior of the “imposter”, the
testimony of trustworthy friends, and so on. The contradictory evidence however is
neglected because of the bias and, consequently, the delusional hypothesis is
maintained.17,18

<hs>  Delusions might not be malfunctional</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There are at least two kinds of possible objections to the claim that delusions are
pathological because of X. First there might be some objections according to which it is
not the case that all delusions are X.19 For example, an objection to the view that
delusions are pathological because of their strangeness is that it is not the case that
all delusions are strange. Delusional jealousy is not. Second, there might be some
objections according to which X is not sufficient for a belief to be pathological. For
example, an objection to the view that delusions are pathological because of the
resistance to folk psychological explanations is that resisting folk psychological
explanations is not sufficient for a belief to be pathological. Twisted self-deceptive
beliefs resist folk psychological explanations, but they are not pathological. In this
section, I examine these two kinds of objections to my own proposal. According to the
first group of objections (4.1), it is not the case that all delusions are malfunctional.
Some of them are perfectly functional. According to the second (4.2), a harmful
malfunction is not sufficient for a belief to be pathological. There are some beliefs that
are harmful and malfunctional but are not pathological.

<hs>  Psychological defence</hs>
  ~~~~~~~~~~~~~~~~~~~~~

One might think that some delusions are not malfunctional but rather are successfully
performing a function, namely, the psychological defence function. In the case of B.X.
that I mentioned earlier, for instance, his delusion about the fidelity of N. plays the
psychological defence function. It defends B.X. from the stark reality that his body is
paralyzed and N. does not love him anymore. Indeed, the idea that some delusions have
defensive roles is popular recently (Bentall & Kaney, 1996; McKay, Langdon, & Coltheart,
2007). For instance, it has been suggested that persecutory delusions are produced by the
so-called “externalizing attribution bias,” which is the bias of attributing negative
events to other agents rather than themselves in order to defend self-esteem.
Psychological defence objection, however, is not very persuasive. I do not rule out the
idea that some delusions play psychological defence roles. The problem of this objection
is rather that even if they play such roles, it does not imply that they are successfully
playing biological, etiological functions. Certainly, defending self-esteem is a good
thing for us. It brings psychological comfort. But it is not obvious that it is not only
psychologically good, but also biologically good. In other words, it is not obvious that
defending self-esteem does not just bring psychological comfort, but also brings
reproductive success. Stich famously argues that, “natural selection does not care about
truth; it cares only about reproductive success” (Stich, 1990, p. 62). Similarly, we can
also say that natural selection does not care about psychological comfort; it cares only
about reproductive success. Etiological functions and psychological comfort do come apart
in some cases. For example, the negative emotions, such as fear or anxiety, are
psychologically negative, but they play important biological functions, such as the
function of avoiding dangers or threats. Presumably, we can even say that they play those
functions exactly because they are psychologically negative, in the same way that pain
plays the function of defending body from damage exactly because it is psychologically
negative. (Pain would fail to defend body if it were psychological positive.) Furthermore,
there are some conditions that are psychologically positive, but etiologically
malfunctional. Nesse (1998) argues that insufficient anxiety, which is psychologically
positive, is etiologically malfunctional. Anxiety has important etiological functions, and
insufficient anxiety is the failure of performing these functions. People with
insufficient anxiety never visit psychiatric clinics. They do not think they have to do
so. Nonetheless, their anxiety mechanisms are etiologically malfunctioning and,
presumably, they should be medically treated in some cases.

<hs>  Doxastic shear pin</hs>
  ~~~~~~~~~~~~~~~~~~

McKay and Dennett (2009) consider an interesting hypothesis according to which delusions
are “doxastic shear pins.” A shear pins is a metal pin installed in complex mechanistic
systems, and it is designed to break in certain circumstances in order to protect other,
more expensive parts of the systems. It is conceivable that some delusions play similar
roles. A possible hypothesis is that there is a mechanism whose function is to prevent
motivational factors from influencing belief forming processes. But, in the situation
where one faces extreme psychological stress, the mechanisms is designed to break and let
motivational factors influence belief forming processes in order to protect more important
cognitive mechanisms. For example, in the case of B.X., the mechanism is broken, in
accordance with the design, in the face of the extreme psychological stress and,
consequently, his desire for the continuing fidelity of N. has a significant impact on
belief forming processes, which leads to his delusion. Mishara and Corlett (2009) propose
another version of shear pin hypothesis on the basis of the prediction-error theory.
According to the theory, a delusion is formed in response to prediction-error signalling
abnormalities. Due to aberrant prediction-error signals, trivial things or events become
abnormally salient and attention-grabbing. This is the stage of the so-called “delusional
mood.” A delusion in the end arises as the explanation of the abnormal salience attached
to the things and events. A delusion, according to Mishara and Corlett, can be understood
as a kind of doxastic shear-pin; The delusions appear as an Aha-Erlebnis, or “revelation”,
concerning what had been perplexing during delusional mood. [ …] The delusions are not
primarily a defensive reaction to protect the self, but involve a “reorganization” of the
patient’s experience to maintain behavioral interaction with the environment despite the
underlying disruption to perceptual binding processes. At the Aha-moment, the “shear-pin”
breaks, or as Conrad puts it, the patient is unable to shift “reference-frame” to consider
the experience from another perspective. The delusion disables flexible, controlled
conscious processing from continuing to monitor the mounting distress of the wanton
prediction error during delusional mood and thus deters cascading toxicity. At the same
time, automatic habitual responses are preserved, possibly even enhanced (Mishara &
Corlett, 2009, p. 531). Now, I do not have a priori reasons to rule out these hypotheses.
What is crucial for me is that they are perfectly compatible with my proposal. They are
compatible because there might still be some etiological malfunctions that are directly or
indirectly related to delusional beliefs in those hypotheses. This is very likely in the
hypothesis by Mishara and Corlett. In the hypothesis, it is assumed that prediction-error
signalling is abnormal and it causes abnormalities in attention allocation processes. The
role of delusions is to help people to maintain behavioral interactions with the
environment despite these abnormalities. They do not eliminate the abnormalities. In the
hypothesis by McKay and Dennett, the mechanism that normally constrains the influence of
motivational factors on belief formation fails to perform one of its functions. It is
broken. Certainly, it successfully plays another function, namely, the function of
defending more important mechanisms. Presumably, the mechanism is best understood as
having two incompatible functions. On one hand, it has the function of constraining the
influence of motivational factors on belief formation processes. On the other hand, it has
the function of defending more important cognitive mechanisms. Those functions are
incompatible because the mechanism successfully performs the latter function only by
failing to perform the former and vice versa. In the case where the “shear pin” breaks,
the mechanism is functional in the sense that it successfully performs the latter
function, but it is malfunctional in the sense that it fails to perform the former.

<hs>  The error management theory</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The error management theory (Haselton & Buss, 2000) is the view recurrent asymmetries in
the costs of false alarms shaped varieties of cognitive and behavioral biases over
evolutionary history. For example, it is well-established that, compared with women, men
have the stronger tendency to overperceive sexual interest. According to the error
management theory, this tendency is explained by the recurrent asymmetry in the costs of
errors. Smoke detectors are designed to be activated more often than they really need to
be. This is because false positives are not very costly (i.e. some unnecessary
evacuations), while false negatives are extremely costly (i.e. the building will be burnt
down). Similarly, natural selection designed the men’s sexual perception system so that it
is activated more often than it really needs to be. This is because “false alarms
typically result in trivial expenditures of wastes courtship effort for men: Although
rejected men may experience social embarrassment, women generally do not respond
antagonistically to men’s overperception of sexual interest. The costs of missed mating
opportunities, on the other hand, were substantial for men over the course of human
evolution, because men’s reproductive success can be directly affected by the access to
fertile mates” (Perilloux, Easton, & Buss, 2012, p. 146). The error management theory
might cause some problems for my proposal. Maybe, some delusions are produced by the
biases that evolved due to recurrent cost asymmetries. Those biases are not malfunctional.
Rather, they come from the very design of relevant mechanisms. Delusional jealousy is a
good candidate. False positives about the infidelity of partners do not seem to be very
costly (i.e. partners will be annoyed), while false negatives are very costly (i.e. the
partners might leave the subjects). So, the error management theory predicts that that
jealousy is, by design, activated more often than it is really needs to be. In other
words, people are designed to be oversensitive to the infidelity of partners. It is
conceivable that this bias does not only explain normal jealousy but also delusional
jealousy. Consistent with this hypothesis, delusional jealousy has some important
characteristics in common with normal jealousy. For instance, men with delusional jealousy
are especially upset about the partner’s sexual infidelity, whereas women with delusion of
jealousy are especially upset about the partner’s emotional infidelity, which is
consistent with the pattern that is seen in normal jealousy (Easton et al., 2007). If it
is true that delusional jealousy is the product of the error management theoretic bias,
then there is nothing malfunctional about it. As Easton and colleagues suggested, “morbid
jealousy does not meet the dysfunction criterion and therefore should not be considered a
mental disorder” (Easton, Schipper, & Shackelford, 2006, p. 412). Error management theory
in itself is a very plausible view. Still, I do not think that it causes serious troubles
for my account. First, delusional jealousy might be pathological in the same sense that
fever as the symptom of viral infection is pathological. Fever as the symptom of viral
infection itself is not malfunctional. It is rather a designed defensive response. When we
regard fever as pathological, we do so in virtue of the fact that it is a symptom of viral
infection which involves etiological malfunctions. In other words, fever indirectly
involves etiological malfunctions even though it is perfectly functional in itself. The
same thing might be true about delusional jealousy. Indeed, delusional jealousy often
occurs as a symptom of the conditions that are expected to involve some etiological
malfunctions. It occurs, for example, in the contexts of schizophrenia, bipolar disorder,
Parkinson’s disease, brain injuries, and so on. When we regard delusional jealousy as
pathological in those cases, we do so presumably in virtue of the fact that it is a
symptom of the conditions that involve etiological malfunctions. Delusional jealousy,
thus, indirectly involves etiological malfunctions even if it is perfectly functional in
itself. Second, even if normal people have the error management theoretic bias of being
oversensitive to the infidelity of partners, the bias might not be sufficient to explain
delusional jealousy. A possibility is that the bias is pathologically exaggerated in
people with delusional jealousy. As McKay and Dennett suggested, “the most that can
presently be claimed is that delusions may be produced by extreme versions of systems that
have evolved in accordance with error management principles, that is, evolved so as to
exploit recurrent cost asymmetries. As extreme versions, however, there is every chance
that such systems manage errors in maladaptive fashion” (McKay & Dennett, 2009, p. 502).
Indeed, if delusional jealousy is just an expression of an error management theoretic
bias, then we cannot explain the fact that it is often seen in the contexts of
schizophrenia or bran injuries. Presumably, delusional jealousy is more similar to
rheumatoid arthritis, which is the product of pathologically exaggerated immune responses,
than to the fever in viral infection. Another possibility is that the designed bias is
only a factor of delusional jealousy. There is the second factor, which might be the bias
of neglecting contradictory evidence after adopting delusional hypotheses (Coltheart et
al., 2010). Maybe, the bias explains the fact that delusional jealousy is maintained,
after adopted, in the absence of supportive evidence. Indeed, the two-factor theorists
tend to think that the second factor is shared in all types of delusions. If so, again, it
is likely that there are some malfunctions that underlie the second factor.20

<hs>  Harmful malfunction is not sufficient</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

According to the second objection, a harmful etiological malfunction is not sufficient for
a belief to be pathological. For example, it is sometimes said that the fundamental idea
of teleosemantics is that misrepresentations, such as non-veridical perceptions or false
beliefs, involve the failures of etiological functions. The basic idea behind teleological
theories of content is that this normative notion – and its distinction between proper
functioning and malfunctioning – might somehow underwrite the normative notion of content
– and its distinction between representation and misrepresentation. (Neander, 1995, p.
112). Much of the original appeal of teleosemantics was its ability to employ teleo-
functional notions of purpose in order to deal with apparently normative aspects of
semantic phenomena. In particular, the biological notion of failure to perform a proper
function was used to attack the problem of misrepresentation, which had caused a lot of
trouble for information-based theories (Godfrey-Smith, 2006, p. 62). If it turns out that
all misrepresentations involve etiological malfunctions, then, according to my proposal,
all harmful misrepresentations are pathological. All harmful non-veridical perceptions and
false beliefs are pathological. But, this creates too many mental disorders! Obviously, it
is not the case that all harmful misrepresentations are pathological. One might falsely
believe that he is not as smart as his colleagues, and the false beliefs might have a
negative impact on wellbeing (e.g. the loss of self-esteem, psychological stress amnesia,
etc.). This can happen to a perfectly healthy person (although it could lead to
pathological conditions such as depression). This seems to show that my proposal is wrong.
More precisely, it shows that a harmful etiological malfunction is not sufficient for a
mental state to be pathological. Healthy harmful misrepresentations involve harmful
etiological malfunctions, according to teleosemantics, but they are not pathological.
There are some possible responses to this objection. First, I might simply reject
teleosemantics. However, I do not find this option very attractive because the
incompatibility with teleosemantics, which is a popular account of mental representations
among naturalist philosophers of mind, is a disadvantage of my proposal. Second, I might
argue that healthy harmful misrepresentations are not harmful enough to be pathological.
For example, the healthy false belief that I am not as smart as my colleagues is not a
counterexample my claim because it is not harmful enough. This option is committed to the
view that the difference between healthy false beliefs and delusions is about the
harmfulness condition of HDA. Both involve some kinds of etiological malfunctions. Thus,
they are equivalent in terms of the malfunction condition. On the other hand, they are
different in the degree of harmfulness. Delusions are harmful enough to be pathological.
Healthy false beliefs are not. This response might or might not work. But I do not agree
with the idea that delusions and healthy false beliefs are different only in terms of the
harmfulness condition. I do believe that they are also different in the malfunction
condition. Teleosemantics, properly understood, does not imply that all misrepresentations
involve etiological malfunctions. It is a misunderstanding of teleosemantics that all
misrepresentations involve etiological malfunctions according to the theory. Thus, even if
we accept teleosemantics, we do not have to accept the view that all false beliefs involve
etiological malfunctions. There are different versions of teleosemantics and they need
different discussions. In the following, I will talk about two notable examples; Millikan
(1984), Millikan (1989) consumer-based teleosemantics and Neander (1995, 2013)
informational teleosemantics. Let us begin with the following famous example by Dretske.
Some marine bacteria have internal magnets, magnetosomes, that function like compass
needles, aligning themselves (and, as a result, the bacterium) parallel to the Earth’s
magnetic field. Since the magnetic lines incline downward (toward geomagnetic north) in
the northern hemisphere, bacteria in the northern hemisphere, oriented by their internal
magnetosomes, propel themselves toward geomagnetic north. Since these organisms are
capable of living only in the absence of oxygen, and since movement toward geomagnetic
north will take northern bacteria away from the oxygen-rich and therefore toxic surface
water and toward the comparatively oxygen-free sediment at the bottom, it is not
unreasonable to speculate, as Blakemore and Frankel do, that the function of this
primitive sensory system is to indicate the whereabouts of benign (i.e. anaerobic)
environments (Dretske, 1991, p. 63). What does the state of magnetosome represent? Does it
represent magnetic north or the oxygen-free sediment? Millikan thinks that it represents
the oxygen-free sediment, not magnetic north. In Millikan’s view, what the state of
magnetosome represents is determined by what the state needs to correspond to in order for
the consumer of the state to perform its function successfully in its normal way. For the
successful performance of the consumer (i.e. motor mechanism), the state needs to
correspond to the oxygen-free sediment. After all, what is crucial for the successful
functioning of the motor mechanism is to lead the bacteria to the oxygen-free sediment.
Then, Millikan’s account actually allows for misrepresentations without etiological
malfunctions. Suppose that I use a bar magnet to lead a bacteria upward and, consequently,
the bacteria dies because of the exposure to oxygen-rich surface water. In this case, the
state of the magnetosome misrepresents without etiological malfunctions. The state
misrepresents because, on the one hand, it represents the oxygen-free sediment and, on the
other hand, it is tokened when the oxygen-rich surface water is there instead. It does not
involve any etiological malfunctions because nothing is wrong about the bacteria itself.
Rather, it is just unlucky. Still, Millikan insists that the magnetosome in the case fails
to perform its function in a certain sense. […] Dretske is right that the magnetosome that
directs that bacterium in the wrong direction because someone holds a bar magnet overhead
is not broken or malfunctioning. In that sense, it is functioning perfectly properly. But
it doesn’t mean that it is succeeding in performing all of its functions, any more than a
perfectly functional coffeemaker is performing its function when no one has put any coffee
in it. Very often things fail to perform their functions, not because they are damaged,
but because the conditions they are in are not their normal operating conditions
(Millikan, 2004, p. 83). The magnetosome fails to perform its functions in the same way
that a coffee maker fails to perform its function (of making coffee) when nobody puts
coffee beans in it. Millikan carefully distinguishes the cases where something
malfunctions or, in other words, it fails to perform its function due to the intrinsic
damage from the cases where something fails to perform its function doe to the
environmental misfortune. For the sake of avoiding confusion, I will use the term
“misfunction” for the second type of failures. The coffee maker does not malfunction but
misfunctions when nobody puts coffee beans in it. The magnetosome does not malfunction but
misfunctions when it is fooled by my bar magnet. What is crucial here is that it might be
the case that all misrepresentations involve some etiological misfunctions in Millikan’s
version of teleosemantics (Millikan, 1997), but it is not the case that all
misrepresentations involve etiological malfunctions. Unlike Millikan, Neander seems be
committed to the idea that all misrepresentations involve etiological malfunctions. She
discusses the example of a frog (Rana pipiens) that catches and eats flies. The frog,
however, responds not just to fries, but to other small, dark, moving things that are not
flies, such as BBs. Let us call the frog’s representation of its target “R.” Neander
thinks that R represents small, dark, moving things rather than flies. This means that R
does not misrepresent as long as it is caused by small, dark, moving things. It does not
misrepresent, for instance, when it is caused by a BB. When does R misrepresent, then? It
misrepresents, according to Neander, when it is caused by something which is not a small,
dark, moving thing. It misrepresents, for example, when it is caused by a snail. Neander
discusses a challenge according to which this view does not allow for the possibility of
misrepresentation at all. After all, it is very unlikely that R is caused by a snail. In
response, she argues that R will never be caused by a snail as long as perceptual systems
of the frog are healthy, but “[a] sick frog might R-token at a snail if it was
dysfunctional in the right way. Damaging the frog’s neurology, interfering in its
embryological development, tinkering with its genes, giving it a virus, all of these could
introduce malfunction and error” (Neander, 1995, p. 109). These are the cases where R
misrepresents, according to Neander. Then, it looks as though all misrepresentations
involve some malfunctions in this account after all. This commitment, however, is
problematic. Obviously, one can have a false belief without having any neurological or
genetic abnormalities. Neander recognizes this problem. Her answer to it is that the claim
that misrepresentations always involve malfunctions is true only for primitive
representations in the early stages of visual processing. Consider the case where we see a
skinny cow in the dim distance and mistakenly represent it as a horse (Fodor’s example).
Here, we may suppose, we misrepresent without malfunctioning, and clearly the content of
our perceptual representation goes beyond the physical parameters of the environmental
features measured. But this sophisticated representation occurs after much visual
processing has already taken place, at least, this is so on computational theories of
vision. In such theories, early visual processing does not represent the cow as a horse
(or as a cow) but as something which looks a certain way – as having a certain outline
texture, color and so on. That is, according to conventional computational theories of
perception, initially there is a representation of the physical parameters of the
environment as measured by the visual system. It is much plausible that there is no
misrepresentation without malfunction at this level (Neander, 1995, p. 132). The claim
that misrepresentations always involve etiological malfunctions is true only in the early
stages of visual processing. It is not true for sophisticated representations such as
beliefs or the perceptual representations in the later stages of visual processing. In
sum, both versions of teleosemantics, Millikan’s and Neander’s, are actually free from the
view that all misrepresentations involve etiological malfunctions. Misrepresentations
might involve etiological misfunctions in Millikan’s account. But, they do not always
involve etiological malfunctions. In Neander’s theory, misrepresentations involve
etiological malfunctions in the early stages of visual processing. But, it does not
generalize to other kinds of misrepresentations.

<h>CONCLUSIONS</h>
-----------

I have argued that delusions are pathological because they are harmful and malfunctional.
They have significant negative impacts on wellbeing. And, some psychological mechanisms,
or the connections between them, that are directly or indirectly related to delusions fail
to perform their etiological functions due to intrinsic problems. In Section 2, I
discussed some possible explanations of the pathology of delusional beliefs. The
explanations are not fully satisfactory primarily because they are detached from the
considerations about what, in general, makes a condition pathological. My explanation, on
the other hand, is an application of a general account of disorders by Wakefield, which
successfully explains various kinds of physical and mental disorders. Two types of
objections were critically examined in Section 4; (1) it is not the case that all
pathological delusions are malfunctional and (2) involving harmful malfunctions are not
sufficient for a belief to be pathological. The first type of objections come from the
ideas that delusions are playing psychological defence functions, that they are doxastic
shear pins, and that they are produced by error-management theoretic biases. In response,
I argued that those ideas are perfectly compatible with the claim that delusions involve
some etiological malfunctions. The second type of objection comes from the worry that all
misrepresentations involve some etiological malfunctions if teleosemantics is correct. In
response, I showed that the objection is based upon a misunderstanding about
teleosemantics. If we are careful enough about the distinction between malfunction and
misfunction, it is not very difficult to see that notable teleosemantics theories are free
from such a commitment about misrepresentations.


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<ART>Development of online use of theory of mind during adolescence: An eye-tracking study
================================================================================

Authors: Irene Symeonidou, Iroise Dumontheil, Wing Yee Chow, Richard Breheny
DOI: 10.1016/j.jecp.2015.11.007
Year: 2016  |  Pages: 81-97
ASJC codes: 3204, 3205
Keywords: Adolescence, Eye-tracking, Inhibition, Perspective taking, Social cognition, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We investigated the development of theory of mind use through eye-tracking in children (9–13 years old, n = 14), adolescents (14–17.9 years old, n = 28), and adults (19–29 years old, n = 23). Participants performed a computerized task in which a director instructed them to move objects placed on a set of shelves. Some of the objects were blocked off from the director's point of view; therefore, participants needed to take into consideration the director's ignorance of these objects when following the director's instructions. In a control condition, participants performed the same task in the absence of the director and were told that the instructions would refer only to items in slots without a back panel, controlling for general cognitive demands of the task. Participants also performed two inhibitory control tasks. We replicated previous findings, namely that in the director-present condition, but not in the control condition, children and adolescents made more errors than adults, suggesting that theory of mind use improves between adolescence and adulthood. Inhibitory control partly accounted for errors on the director task, indicating that it is a factor of developmental change in perspective taking. Eye-tracking data revealed early eye gaze differences between trials where the director's perspective was taken into account and those where it was not. Once differences in accuracy rates were considered, all age groups engaged in the same kind of online processing during perspective taking but differed in how often they engaged in perspective taking. When perspective is correctly taken, all age groups’ gaze data point to an early influence of perspective information.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Over the last couple of decades, cognitive neuroscience research has shown that brain
areas involved in theory of mind (the “social brain”)—our ability to attribute the
beliefs, thoughts, desires, intentions, and feelings of others—undergo changes not only
during childhood but also during adolescence (Burnett, Sebastian, Cohen Kadosh, &
Blakemore, 2011). A substantial number of studies have now provided evidence for
structural and functional changes in the social brain during childhood and adolescence. In
addition, there is a body of evidence that theory of mind (ToM) is applied more robustly
or accurately with age through middle childhood (Devine & Hughes, 2013; Epley, Morewedge,
& Keysar, 2004; Lecce, Bianco, Devine, Hughes, & Banerjee, 2014; Surtees & Apperly, 2012;
Wang, Ali, Frisson, & Apperly, 2016) and adolescence (Dumontheil, Apperly, & Blakemore,
2010; Vetter, Altgassen, Phillips, Mahy, & Kliegel, 2013). Previous studies have shown
that children’s performance on paradigms such as false-belief tasks reaches ceiling at
around the age of 5 years (Surian, Caldi, & Sperber, 2007; Wellman, Cross, & Watson,
2001). The question arises as to what factors affect older children and adolescents’
successful application of such abilities. The Director paradigm has been used to
investigate the ability to take the perspective of another individual into account in a
communicative context (Apperly, Back, Samson, & France, 2008; Brown-Schmidt & Hanna, 2011;
Fett et al., 2014; Keysar, Barr, Balin, & Brauner, 2000; Keysar, Lin, & Barr, 2003). In
these studies, the participant interacts with another agent (a “director”) to act on a set
of objects (Director paradigm; Fig. 1). Crucially, some of the objects are blocked off
from the director’s point of view and are visible only to the participant. Thus, when the
director talks about an object (e.g., “the large ball”; Fig. 2), the participant should
ignore any object that is not visible to the director and instead select a referent from
what is in the “common ground,” that is, what is visible to both the participant and the
director. This paradigm requires the participant to infer the speaker’s referential
intention (a mental state) based on beliefs that differ from his or her own due to the
speaker’s ignorance of the presence of an object that would be a potential referent for
the instruction given. For example, in the setup shown in Fig. 2, the participant, but not
the director, sees a third ball that best fits the description “the large ball” (the
basketball) and needs to discount it as the intended referent because the director does
not know about that ball. The Director paradigm is useful for the study of the development
of the social brain because it can be used to measure the application of aspects of ToM
without asking participants to make an explicit judgment about their own or someone else’s
perspective or thoughts. Given that even adults manifest less than ceiling performance on
the Director paradigm (Brown-Schmidt & Hanna, 2011; Keysar et al., 2000), it is well
suited for exploring how ToM abilities develop across childhood and adolescence. Early
visual world eye-tracking studies using the Director paradigm demonstrated that adult
participants are not able to ignore objects to which they have privileged visual access
and that they are less accurate in choosing the object that is visually available to both
participants and the director compared with control conditions (Epley et al., 2004; Keysar
et al., 2000, 2003). Keysar and colleagues explained these results by suggesting that
participants have an initial bias to take an egocentric perspective and that their initial
interpretation of the instruction is later adjusted according to the speaker’s knowledge
state by a second process that corrects any manifest errors. In contrast, studies using
very similar paradigms have found evidence that participants are able to integrate
information about the speaker’s beliefs immediately (Hanna, Tanenhaus, & Trueswell, 2003;
Heller, Grodner, & Tanenhaus, 2008). This is comparable to findings that individuals may
rapidly and automatically compute what other people see (Samson, Apperly, Braithwaite,
Andrews, & Bodley Scott, 2010). It seems clear that adults are able to integrate
information to some extent about what their interlocutor knows from the earliest stages of
referential language processing even though they are liable to attend to objects that are
not known to the speaker (Brown-Schmidt & Hanna, 2011). Among adults, performance on
perspective-taking tasks has been shown to be affected by factors such as the nature of
the verbal stimulus (Barr, 2008), the extent to which the interaction offers information
about the interlocutor’s mental state (Brown-Schmidt, 2009a), cultural background (Wu &
Keysar, 2007), inhibitory control (Brown-Schmidt, 2009b; Nilsen & Graham, 2009), and mood
(Converse, Lin, Keysar, & Epley, 2008). Dumontheil and colleagues (2010) tested 7- to
27-year-old female participants’ performance using a computerized version of Keysar and
colleagues’ (2000) Director task. Participants were presented with a 4 × 4 grid that
contained various objects in different slots. A director (an avatar) gave participants
instructions about which objects to move and where to move them. As in the original
design, some of the slots on the shelves were occluded so that the director could not see
what was present on those shelves. The study also included a No-Director condition where
participants performed the same task in the absence of a director. In this condition, they
were told that the instructions would not refer to items in slots with a gray background.
According to Dumontheil and colleagues (2010), the difference between the two conditions
is that whereas only executive function processes are required for participants to perform
well on the task in the No-Director condition, both ToM processes and executive function
processes are required in the Director condition because participants need to take someone
else’s perspective into account in order to perform well. Dumontheil and colleagues (2010)
found that error rates were higher in the late adolescent group (14- to 17-year-olds) than
in the adult group in the Director condition but that they did not differ between the late
adolescent and adult groups in the No-Director condition, which relies on executive
functions only. This suggests that late adolescents differ from adults in their
application of ToM inference when controlling for certain executive function demands. In
contrast to the error rates, Dumontheil and colleagues (2010) reported that reaction times
on the critical trials in the Director condition remained the same across all age groups.
Furthermore, they found that reaction times were longer in the No-Director condition than
in the Director condition. According to the authors, this difference suggests that
participants approach the Director task in a way that is more efficient than just applying
an arbitrary rule. They proposed that the difference in accuracy between the late
adolescent and adult groups might stem not from how efficiently or rapidly they can make
referential inferences but rather from their propensity to integrate information about the
speaker’s beliefs in making those inferences. These suggestions point to a response to the
question raised above as to what factors are responsible for the better application of ToM
abilities during this stage of development. The current study used visual world eye-
tracking measures on a variant of the Director task employed by Dumontheil and colleagues
(2010). It is widely accepted that eye fixations can indicate how we process information
during spoken language comprehension (Altmann & Kamide, 1999; Tanenhaus, Spivey-Knowlton,
Eberhard, & Sedivy, 1995). By measuring when participants fixate their gaze on an object,
we can identify which object they are considering as a possible referent at a given point
in time. Although eye-tracking has previously been used in variants of the Director task,
samples of these studies have been limited to either adults (Keysar et al., 2003; Lin,
Keysar, & Epley, 2010; Wu & Keysar, 2007) or younger children (5- and 6-year-olds in Nadig
& Sedivy, 2002; 4- to 12-year-olds in Epley et al., 2004). The current study afforded an
opportunity to examine and compare how children, adolescents, and adults apply ToM in real
time through monitoring their eye gaze while they were performing the task. Specifically,
the aim was to explore the time course of the decision process that yields both correct
and incorrect responses in participants. Furthermore, the current study also aimed to
understand whether ongoing development of executive function processes, specifically
inhibition, plays a role in perspective taking. Previous studies have found a correlation
between inhibition and the application of ToM inference in children (3- and 4-year-olds in
Carlson, Moses, & Claxton, 2004; 4- to 10-year-olds in Hansen Lagattuta, Sayfan, & Harvey,
2014; 4- to 9-year-olds in Lagattuta, Sayfan, & Blattman, 2010; 2- to 5-year-olds in
Nilsen & Graham, 2009) and in adults (Brown-Schmidt, 2009b). A meta-analysis of 100
studies with 3- to 6-year-olds by Devine and Hughes (2014) highlighted the association
between executive function and ToM. Inhibitory control, like other executive skills, is
still maturing during adolescence (Leon-Carrion, García-Orza, & Pérez-Santamaría, 2004;
Luna, Padmanabhan, & Hearn, 2011). A study by Vetter and colleagues (2013) found that
inhibitory control, as measured with an anti-saccade task, predicted age-related variance
in affective ToM during adolescence. No other study, however, has looked at the role of
inhibitory control in adolescents’ ability to inhibit one’s perspective and consider
someone else’s perspective. Therefore, we measured participants’ inhibitory control
through two variants of the Go–NoGo task in order to investigate whether individual
differences in inhibitory control can account for their performance on the Director task.
Based on the evidence of ongoing functional development of neural processes related to ToM
and the results of Dumontheil and colleagues (2010), we expected that age-related
differences in participants’ accuracy would be greater in the Director condition than in
the No-Director condition. We also expected to see age-related differences in inhibitory
control, which may partially account for participants’ performance on the Director task.
We measured the extent to which participants considered the target object relative to the
distractor by computing the target advantage score, which is the average probability of
looks at the target object minus the average probability of looks to the distractor
(Brown-Schmidt, 2009b; Kronmüller & Barr, 2015). This allowed us to examine and compare
how each age group used ToM to identify the referent. According to the perspective
adjustment model proposed by Keysar and colleagues, participants have an initial
egocentric bias, which is then adjusted, during a second process, to the speaker’s
perspective. Therefore, this theory predicts that participants will fixate on the
distractor first and, if the second process of adjusting is successful (i.e., on correct
trials), then participants will fixate their gaze on the target object and give a correct
response. However, if the second process fails and perspective taking does not occur, then
we would expect participants’ gaze to remain on the distractor, not to fixate on the
target, and participants to eventually give an incorrect response. As such, it is
predicted that although both adolescents and adults would fixate on the distractor object
initially, demonstrating an initial egocentric bias, adults would then be more likely to
switch to fixating their gaze on the target object and do so more quickly than
adolescents. In other words, both adolescents and adults would have a smaller target
advantage initially, but adults would have a bigger target advantage score than
adolescents in earlier time regions. Other models of perspective taking found in Hanna and
colleagues (2003) and Brown-Schmidt, Gunlogson, and Tanenhaus (2008) suggest that
perspective information is available from the outset but that the extent to which it is
integrated online depends on how sensitive participants are to such information (Brown-
Schmidt, 2012) or on participants’ ability to integrate that information with linguistic
and visual contextual information (Hanna et al., 2003). According to these proposals, an
incorrect response may reflect a simple failure to integrate perspective from the start of
a trial. If this is the case, then patterns of eye gaze may differ from the onset of the
critical phase of the instruction between correct and incorrect trials.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 65 participants took part in this study, constituting three age groups: child
(n = 14, 9–13 years old, M = 11.2 years, SD = 1.2), adolescent (n = 28, 14–17.9 years old,
M = 16.2 years, SD = 1.1), and adult (n = 23, 19–29 years old, M = 23.0, SD = 2.8). The
age groups were divided to match the age groups of Dumontheil and colleagues (2010). Adult
participants were recruited from the University College London (UCL) Psychology
participant pool, whereas children and adolescents were recruited from London schools. All
participants were native English speakers. Data from three adults were excluded due to
technical errors. We also excluded data from two adolescents who did not understand the
instructions of the No-Director condition. Verbal ability was measured in all participants
using the vocabulary subtest of the Wechsler Abbreviated Scale of Intelligence (WASI;
Wechsler, 1999). Average verbal IQ scores were 124 (SD = 8.0) for adults, 118 (SD = 6.9)
for adolescents, and 123 (SD = 10.2) for children. A one-way analysis of variance (ANOVA)
showed a significant difference in verbal IQ scores between groups, F(2, 57) = 5.97, p =
.03. Bonferroni-corrected post hoc comparisons showed that adolescents performed worse
than adults (p = .04), but verbal IQ did not significantly differ between children and
adolescents (p = .22) or between children and adults (p = 1.00). Parents/guardians of all
child and adolescent participants as well as the adult participants were given information
sheets prior to the study. Informed consent was obtained from the parents/guardians for
all child/adolescent participants and from all adult participants. This study was approved
by the UCL research ethics committee.

        <hss>Director task</hss>

        The current experiment had two within-participant factors: condition (Director or
        No Director) and trial type (Control or Experimental). It had one between-
        participants factor: age group (child, adolescent, or adult). The task design and
        stimuli were based on a previous study by Dumontheil and colleagues (2010; see
        also Apperly et al., 2010). Participants were presented with a visual scene of a 4
        × 4 set of shelves containing eight different objects and were asked to move one
        of the objects in each trial. In the Director condition, a “director” was shown
        standing behind the shelves, viewing the shelves from behind (Fig. 1).
        Participants were asked to listen to the director’s instructions to move one of
        the objects (e.g., “Move the large ball up”) and respond. Participants were told
        that they should take the director’s viewpoint into account when following the
        director’s instructions. They were told that objects in slots with a gray
        background were visible only to them, whereas the other objects could be seen from
        either side of the shelves. In Experimental trials, the instruction referred to
        one object (“target”) given the director’s point of view but would refer to
        another object (“distractor”) if one assumed participants’ perspective (Fig. 2A).
        As such, participants needed to take the director’s perspective into account in
        order to respond correctly in an Experimental trial. In Control trials, the
        distractor object was replaced by an irrelevant object and the instruction
        referred to an object that was visible to both participants and the director (Fig.
        2B). In Filler trials, instructions referred to single objects that were visible
        to both participants and the director (e.g., the turtle in Fig. 2). In the No-
        Director condition, the only difference was that the director was removed from the
        stimuli (Fig. 2C and D). Participants were told that the auditory instructions
        would refer only to items in clear slots and not items that were in slots with a
        gray background. A total of 48 pairs of shelf configurations were created as
        Experimental and Control trials. All shelf configurations depicted eight objects
        and included either three (Experimental trials) or two (Control trials) exemplars
        of the same object that differed in position (top/bottom) or size (large/small).
        In Experimental trials, the exemplars were distributed such that the distractor
        object (the top-most, bottom-most, smallest, or largest object) was in a slot with
        a gray background, whereas the target object (the second top-most, bottom-most,
        smallest, or largest object) and the third object (“Object 2”) were in a clear
        slot (Fig. 2A and C). In the Control trials, the distractor was replaced by an
        irrelevant object (Fig. 2B and D). The rest of the objects were unique objects
        distributed among three slots with a gray background and two clear slots. Another
        48 pairs of shelf configurations were created for the Filler trials, in which the
        instructions referred to single objects that were in a clear slot. Taken together,
        the stimuli were divided such that half were presented in the Director condition
        and the other half were presented in the No-Director condition (counterbalanced
        across participants), and each participant saw 12 Experimental trials, 12 Control
        trials, and 24 Filler trials in the Director and No-Director conditions. The order
        of stimulus presentation was counterbalanced between participants. The materials
        and design of the current study differed from those Dumontheil and colleagues’
        (2010) study in three ways. First, we included a greater number of Experimental
        and Control trials to increase statistical power and allow eye-tracking data
        analysis. Second, whereas each shelf configuration was used with three successive
        instructions in Dumontheil and colleagues’ study, a different shelf configuration
        was used in each trial in the current study to minimize participants’ learning
        strategies. Third, whereas participants needed to pretend to drag the object in
        the previous study, they were able to click and drag any object on the grid in the
        current study.

        <hss>Inhibitory control tasks</hss>

        To measure participants’ inhibitory control, we used two different Go–NoGo tasks,
        both of which had one within-participant factor trial type (Go or NoGo). The
        Simple Go–NoGo task was based on the standard Go–NoGo paradigm (Simmonds, Pekar, &
        Mostofsky, 2008). A colored square was presented on the left or right side of the
        screen in each trial. Participants needed to indicate which side of the screen it
        appeared on if the square was green (a Go trial) and to inhibit their response if
        the square was red (a NoGo trial). The Complex Go–NoGo task was identical except
        that it used yellow and blue squares and included a 1-back working memory (WM)
        requirement (see Simmonds et al., 2008), such that participants needed to indicate
        on which side of the screen the square was shown (Go trials) except when a blue
        square was preceded by a yellow square (NoGo trials).

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants were tested individually in one session lasting approximately 45 min. They
completed the various tasks in the following order: (1) the Director task (Director
condition and then No-Director condition), (2) the inhibitory control tasks (Simple
Go–NoGo task and then Complex Go–NoGo task), and (3) the vocabulary subtest of the WASI.
Eye movements during the Director task were recorded using a Tobii TX300 eye-tracker at a
sampling rate of 60 Hz. Stimuli for the Director task were presented using E-Prime 2, and
the Go–NoGo tasks were programmed in Cogent
(http://www.vislab.ucl.ac.uk/Cogent/index.html) running in Matlab 7.0 (MathWorks).
Standardized instructions were read to participants prior to the Director task. For the
Director condition, participants were told that the director had a different view of the
shelves (Fig. 1) and that the director’s point of view must be considered when following
the director’s instructions to move objects. We asked participants to give an example of
an object that both they and the director could see as well as an object that the director
could not see to ensure that participants understood the task. For the No-Director
condition, participants were told that the director was no longer present and that
instructions would refer only to items in clear slots, such that they should ignore items
in slots with a gray background when performing the task. The Director condition was
always presented prior to the No-Director condition in order to prevent participants from
applying the rule provided in the No-Director condition (Dumontheil et al., 2010).
Participants were presented with two Filler practice trials before each condition. In each
trial, the visual stimulus and auditory instructions were presented over a period of 2.2
s. The visual stimulus remained on the screen for another 3.8 s, during which participants
responded by clicking an object and dragging it to a different position. A response was
considered correct if the target object had been selected. Response times (RTs) were
measured from the onset of the display. In the Go–NoGo tasks, each square was presented
for 400 ms, with a 600- to 800-ms jittered fixation cross intertrial interval (ITI).
Participants responded by pressing the left or right key using their right index or middle
finger, respectively (adapted from Watanabe et al., 2002). Participants performed two
practice blocks prior to each task; the first practice block presented 10 Go trials to
establish a habitual response, and the second one presented 6 Go trials and 4 NoGo trials.
Practice was repeated if participants made two or more errors. Each participant performed
80 test trials on each task (25% NoGo).

        <hss>Behavioral data analyses</hss>

        All analyses were processed in SPSS and R. Statistical significance was set at p <
        .05. Bonferroni-corrected post hoc t-tests were performed to explore significant
        main effects and interactions further.

            <hss>Director task</hss>

            Mixed repeated measures ANOVAs with two within-participant factors (condition
            and trial type) and one between-participant factor (age group) were performed
            on participants’ mean accuracy (percentage errors) and reaction times (RTs).
            Data for Filler trials were not analyzed; participants made fewer than 2%
            errors on these trials on average. Because verbal IQ differed among groups, we
            conducted an additional mixed repeated measures ANOVA that included verbal IQ
            as a covariate.

            <hss>Inhibitory control tasks</hss>

            For both the Simple and Complex Go–NoGo tasks, mean accuracy (percentage
            errors) was calculated for each participant in each trial type (Go or NoGo)
            and median RT was calculated for correct Go trials. A 2 × 3 mixed ANOVA with a
            within-participant factor trial type (Go or NoGo) and a between-participant
            factor age group (child, adolescent, or adult) was performed for each task.
            One-way ANOVAs were performed to examine the effect of age group on
            participants’ RTs in Go trials in each task.

            <hss>Association between Director and inhibitory control tasks</hss>

            Regression analyses were performed to investigate whether age-related changes
            in Director task performance were associated with performance on the
            inhibitory control tasks. The difference in percentage errors between Director
            and No-Director Experimental trials, which is the critical measure of
            interest, was entered as the dependent variable. In a first step, age was
            entered as a continuous variable. In a second step, the four percentage error
            measures of the Simple and Complex Go–NoGo trials were entered in a stepwise
            regression. Finally, in a third step, IQ was entered to assess whether it
            accounted for variance associated with age in this model.

        <hss>Eye-tracking data analyses</hss>

        Eye movements were analyzed by computing a target advantage score, which is the
        average probability of looks at the target object minus the average probability of
        looks at the distractor (Kronmüller & Barr, 2015). A look to the target was
        defined as a look to the object or the slot in which the object was located.
        Likewise, a look to the distractor (or the irrelevant object in Control trials)
        was defined as a look to the object or the slot in which the object was located.
        Note that because the distractor was an irrelevant object in the Control trials,
        target advantage scores in the Control trials represented the difference between
        looks to the target and looks to the irrelevant object. Target advantage scores
        were calculated over 50-ms time bins for the figures where 0 ms was the noun
        onset. For statistical analyses, the target advantage scores were calculated for
        five different time windows (regions) during a trial. The five regions were time-
        locked to the onset of words in the auditory stimuli. Region 1 was the verb
        (“move”), Region 2 was the article (“the”), Region 3 was the modifier (“large”),
        Region 4 was the critical noun region (“ball”), and Region 5 was the directional
        preposition (“up”). Analyses of data in these regions were offset by 200 ms to
        account for the time required for planning and launching an eye movement (Hallett,
        1978). Data in each region were analyzed for the Director and No-Director tasks
        separately. Because we did not have predictions regarding participants’ eye gaze
        prior to the modifier (e.g., “large”), we focused our analyses on data in Regions
        3 to 5 only. First, 2 (Condition) × 2 (Trial Type) × 3 (Age Group) mixed ANOVAs
        were performed on correct trials for each region. Data from 2 participants in the
        child group were excluded from this analysis because they did not have enough
        correct trials. Second, 2 (Accuracy) × 3 (Age Group) mixed ANOVAs were performed
        separately for correct and incorrect Director Experimental trials, the key trials
        of interest, for each region. Because children and adolescents did not have many
        correct trials (in some cases only one or two), and some adults did not have any
        incorrect trials, some participants (5 children, 5 adolescents, and 9 adults)
        needed to be omitted from this analysis due to the lack of eye gaze data. Given
        the clear differences in accuracy between groups, we believe that it was not
        suitable to combine correct and incorrect trials in the analysis. However,
        interested readers can find the results of such analyses in the online
        supplementary material.

            <hss>Accuracy</hss>

            Fig. 3 shows participants’ percentage error as a function of age group, and
            Table 1 shows the results of the statistical analysis. There were significant
            main effects of condition (ηp2 = .591), trial type (ηp2 = .675), and age group
            (ηp2 = .220), which were qualified by significant Age Group × Trial Type and
            Age Group × Condition two-way interactions and a significant three-way
            interaction (p = .013, ηp2 = .142). We explored this interaction further by
            analyzing the Experimental and Control trials separately. No significant
            effects were found in the Control trials (all ps > .08). In contrast, in
            Experimental trials there was a main effect of condition, F(1, 57) = 83.57, p
            < .001, ηp2 = .595, a main effect of age group, F(2, 57) = 8.10, p = .001, ηp2
            = .221, and a significant interaction between condition and age group, F(2,
            57) = 3.67, p = .032, ηp2 = .114. Follow-up analysis examining Experimental
            trials in the Director and No-Director tasks separately revealed a significant
            effect of age group in Director Experimental trials, F(2, 57) = 8.10, p =
            .001, ηp2 = .221, but not in No-Director Experimental trials, F(2, 57) = 1.85,
            p = .167. Follow-up t-tests for the Director Experimental trials showed that
            both the child and adolescent groups made significantly more errors than the
            adult group (child: t(32) = 3.73, p = .001, d = 1.321; adolescent: t(44) =
            2.94, p = .005, d = 0.887), but there was no difference between the child and
            adolescent groups, t(38) = 1.36, p = .183. Because the age groups
            significantly differed in terms of their verbal IQ, we repeated the 2 × 2 × 3
            mixed repeated measures ANOVA with standardized IQ (z-score) as a covariate.
            The same main effects and interactions were found. To summarize, children and
            adolescents made more errors than adults only in the Director Experimental
            trials, which required taking the perspective of the director into account, in
            contrast to the rule-based control condition (No-Director Experimental
            trials). This replicated the behavioral results reported in Dumontheil and
            colleagues (2010).

            <hss>Reaction time</hss>

            Analysis of RT showed that children responded more slowly than the adolescents
            and adults in all trial types except for the Director Experimental trials,
            which showed no difference among age groups (see supplementary material for
            analyses). These results are also in line with those reported in Dumontheil
            and colleagues (2010).

            <hss>Simple Go–NoGo</hss>

            The repeated measures ANOVA revealed significant main effects of trial type,
            F(1, 57) = 50.34, p < .001, ηp2 = .469, and age group, F(2, 57) = 5.29, p =
            .008, ηp2 = .156 (Fig. 4). More errors were made in NoGo trials than in Go
            trials and the child group made more errors than the adolescents (p = .027)
            and adults (ps < .03), who did not differ (p = 1.00). The interaction between
            age group and trial type was not significant (p > .20).

            <hss>Complex Go–NoGo</hss>

            We found significant main effects of trial type, F(1, 57) = 108.87, p < .001,
            ηp2 = .656, and age group, F(2, 57) = 11.44, p < .001, ηp2 = .286, in the
            Complex Go–NoGo task and no interaction between these factors (p > .10) (Fig.
            4). Here, the child and adolescent groups did not differ (p > .10), but they
            both made more errors than the adult group (ps < .01).

            <hss>Simple and Complex Go RT</hss>

            Analyses of median RT in correct Go trials revealed that, in both the Simple
            and Complex Go–NoGo tasks, the child group was significantly slower than the
            adolescent and adult groups, who did not differ from each other (see
            supplementary material for RT analyses).

            <hss>Association between inhibitory control tasks and Director task</hss>

            Regression analyses showed that age significantly accounted for 14.4% of
            variance in the difference in percentage error between Director and No-
            Director Experimental trials (Table 2). Inhibitory control, as measured by the
            Simple NoGo percentage error, accounted for an additional 9.2% of variance,
            with more errors on Simple NoGo trials predicting more errors in Director
            versus No-Director Experimental trials. The other three measures of Go–NoGo
            percentage error were not significant predictors (all βs < .124 and ps >
            .370). The effect of age was still significant in the second model, suggesting
            partially independent effects of age and inhibitory control. Finally, entering
            verbal IQ as an additional regressor did not improve the model, and both the
            independent effects of age and Simple NoGo percentage error remained
            significant (Table 2).

<hs>  Eye-tracking results</hs>
  ~~~~~~~~~~~~~~~~~~~~

Table 3 shows mean target advantage scores across conditions, and Table 4 shows the
results of the statistical analyses. Fig. 5A–D show plots of average target advantage over
time. No significant effects were found in Region 3 (“large”) (all ps > .20). Main effects
of condition and trial type were marginal in Region 4 (“ball”) (ps < .10) and were
significant in Region 5 (“up”) (condition: ηp2 = .042; trial type: ηp2 = .234). The
Condition × Trial Type interaction was significant in both Region 4 (ηp2 = .031) and
Region 5 (ηp2 = .035). Follow-up analyses revealed no significant effects in Control
trials in either region (ps > .30), whereas the target advantage in Experimental trials
was significantly smaller in the No-Director task than in the Director task in both Region
4, F(1, 57) = 8.22, p < .01, ηp2 = .055, and Region 5, F(1, 57) = 10.84, p = .002, ηp2 =
.090. No significant effects involving age group were observed in any of the regions (all
ps > .15). To summarize, in correct trials, participants showed a smaller target advantage
in No-Director Experimental trials than in Director Experimental trials on hearing the
noun. Crucially, their eye movement patterns did not vary across age groups in any of the
regions. We conducted additional analyses to examine the differences in eye gaze between
correct and incorrect Director Experimental trials, the key trials of interest in the
Director paradigm (Tables 5 and 6). We included an additional region (pre-response region)
to check whether participants looked at the object they chose. This region was defined as
the 200 ms before response time in a given trial. Graphs of target advantage again
indicate a similar pattern across age groups (Figs. 5B and 6). Mixed 2 (Accuracy) × 3 (Age
Group) ANOVAs revealed a main effect of accuracy across Regions 3 to 5 and the pre-
response region (Region 3: ηp2 = .240; Region 4: ηp2 = .271; Region 5: ηp2 = .224; pre-
response: ηp2 = .118). Participants had a bigger target advantage in incorrect trials than
in correct trials in Regions 3 to 5; conversely, they had a bigger target advantage in
correct trials than in incorrect trials in the pre-response region. No significant effects
involving age group were observed (all ps > .30). To summarize, analyses of eye movement
data in the Director Experimental trials revealed clear differences between correct and
incorrect trials, but there was no significant effects involving age group in any of the
regions. In other words, there were no significant age-related differences in
participants’ eye gaze patterns in both correct and incorrect Director Experimental
trials. Furthermore, the effect of accuracy observed in Regions 3 to 5 was reversed in the
pre-response region, such that participants initially showed a greater target advantage in
the incorrect trials than in the correct trials, and it was only right before they
responded that they showed a greater target advantage in correct trials than in incorrect
trials.

<h>DISCUSSION</h>
----------

In this study, we collected behavioral and eye-tracking data to investigate online use of
ToM during perspective taking in children, adolescents, and adults. Experimental trials of
the Director task required participants to take into account the director’s perspective to
determine the intended referent in the instructions (e.g., “large ball”). The No-Director
condition required participants to follow an explicit avoidance rule to determine the
correct referent. Whereas both the Director and No-Director conditions involved executive
function, in particular inhibition, only the Director condition required an inference
about the speaker’s intentions given the speaker’s ignorance of certain objects
(Dumontheil et al., 2010). The current study had three main objectives: (a) to replicate
the behavioral findings of Dumontheil and colleagues (2010), (b) to assess the role of
inhibitory control in this task across age groups, and (c) to compare the time course of
information processing among children, adolescents, and adults through eye-tracking in
order to determine in what ways the deployment of ToM differs across age groups.

<hs>  Behavioral data</hs>
  ~~~~~~~~~~~~~~~

We found that in the Director Experimental condition, the child and adolescent groups
performed worse than the adult group, but participants’ accuracy did not differ across
groups in the No-Director Experimental condition. These results are in line with
Dumontheil and colleagues (2010) findings and provide further evidence for age-related
differences between adolescents’ and adults’ tendency to take someone else’s perspective
into account. Conversely, response times decreased with age in all conditions except in
Director Experimental trials, which did not vary with age, and are again similar to those
observed by Dumontheil and colleagues.

        <hss>Inhibitory control</hss>

        We observed age-related differences in participants’ performance on both
        inhibitory control tasks. In the Simple Go–NoGo task, the child group made
        significantly more errors and was significantly slower than the adolescent and
        adult groups. These results are in line with previous studies suggesting that with
        a low-level cognitive load inhibitory control performance reaches adult level
        performance by approximately 14 years of age (Lamm, Zelazo, & Lewis, 2006; Leon-
        Carrion et al., 2004; Luna, Garver, Urban, Lazar, & Sweeney, 2004). In the Complex
        Go–NoGo task, the child and adolescent groups performed worse than the adult
        group. Because the Complex Go–NoGo task included a 1-back WM requirement, these
        results are also in line with studies investigating WM that found age-related
        differences between adolescents and young adults (Conklin, Luciana, Hooper, &
        Yarger, 2007; Luna et al., 2004).

        <hss>Association between inhibitory control tasks and Director task</hss>

        What was novel in this study was the investigation of the relationship between the
        inhibitory control tasks and the Director task. The results show that inhibitory
        control as measured by Simple NoGo accuracy accounted for some of the variance in
        accuracy difference between Director and No-Director Experimental trials.
        Critically, inhibitory control accounted for only some of the variance due to age
        given that age remained a significant predictor, suggesting that some additional
        factors are behind age-related changes. These results are in line with a previous
        study by Vetter and colleagues (2013), who found that 15% of the variance of
        affective ToM performance was uniquely explained by age, indicating independent
        effects of age and inhibition. Interestingly, no relationship was found between
        participants’ performance on the Complex Go–NoGo task and the Director task. This
        is surprising because performance on the Complex Go–NoGo task showed age-related
        differences between the adolescent and adult groups. This could be because the
        Complex Go–NoGo task placed greater WM demands than the Director task. A study
        that explored the relationship between WM and perspective taking (Lin et al.,
        2010) found that participants with lower WM capacity performed more poorly on the
        Director task than participants with greater WM capacity and that participants’
        performance on the Director task was worse during high-WM load trials than during
        low-WM load trials. However, Lin and colleagues’ (2010) study did not include a
        No-Director condition with matched general executive function demands, whereas the
        current study used the difference in accuracy between Director Experimental and
        No-Director Experimental trials as the measure of interest. Future research might
        shed light on these differences in results by using separate measures of WM and
        inhibition (Vetter et al., 2013). A possible limitation for the interpretation of
        the behavioral results is the difference in verbal IQ among age groups. However,
        the significant interactions with age observed in the Director task were still
        present when verbal IQ was added as a covariate. Moreover, adding verbal IQ as a
        predictor in the multiple regression did not affect the results given that both
        the independent effects of age and Simple NoGo accuracy remained significant.

<hs>  Eye-tracking data</hs>
  ~~~~~~~~~~~~~~~~~

Through eye-tracking, we were able to investigate additional underlying factors in
Director task performance. Examining correct and incorrect trials separately indicated
that adults, adolescents, and children did not differ in their online processing of the
task (Fig. 5). Analyses of Director Experimental trials data showed opposite effects of
accuracy in the earlier regions (Regions 3–5) and the pre-response region, such that
participants initially showed a greater target advantage in the incorrect trials than in
the correct trials. They showed a greater target advantage in correct trails than in
incorrect trials only right before they responded. These results seem inconsistent with
the perspective adjustment model (Keysar et al., 2000, 2003), according to which one would
expect that on both the correct and incorrect trials participants first attend to the
distractor, the best-fit referent from an egocentric perspective. On correct trials
participants would adjust to considering the director’s perspective and attend to the
target, whereas on incorrect trials the second adjustment process would fail because it is
costly and participants would remain focused on the distractor. However, as is evident
from the incorrect trials for all age groups, participants appear to consider the target
early on in the trial and then, before responding, their eye gaze shifts to the
distractor. Based on the eye-tracking results, it seems that at the point where the
director indicates which object should be moved (Region 4), participants on correct trials
are already on a path to correctly considering the director’s perspective. However,
participants’ strategy seems to be to first look at the objects that participants are not
going to choose (or the objects they should not pick) as a process of elimination before
focusing on the object that they will ultimately choose. This pattern has not been
reported before. Other studies, such as Hanna and colleagues (2003), Heller and colleagues
(2008), and Barr (2008), showed that bias in participants’ eye gaze builds steadily toward
the target after initial interference from the distractor. What sets our study apart from
these eye-tracking studies is the fact that the distractor is the best fit for the
description, making the task of ignoring the privileged object particularly challenging.
In addition, the description itself contains a relational modifier (e.g., “big,” “bottom”)
that implicitly refers to a contrast set. Given these two factors, it should not be
surprising that participants adopt a strategy of checking all objects of the same type
(e.g., all balls on the display) to ensure that they choose the correct one. Our eye gaze
data of Object 2 (e.g., the second commonly viewable ball) suggests this also. It shows
that prior to focusing on the object they chose, participants paid similar attention to
each of the other two objects they eliminated (see Figs. S3–S5 in supplementary material).
The only other studies that used a setup similar to ours are those reported in Keysar and
colleagues (2000) and Wu and Keysar (2007). Neither of those articles reported eye gaze
data in full, but their results are consistent with ours in that they found more looks to
the distractor overall and first looks to the distractor were earlier than first looks to
the target. Adults, adolescents, and children in the current study seemed to follow a
process of elimination strategy in control trials as well, where only the two commonly
viewable objects denoted by the noun (e.g., “ball”) were present and only one fit the full
description (“large ball”). We propose that participants focus first on the second object
to exclude it before looking at the target (see Figs. S3–S6 in supplementary material).
Therefore, there may be a consistent strategy across all conditions, and all age groups,
of looking at the objects that are not going to be chosen prior to focusing on the object
to be chosen. If we accept that participants adopt a process of elimination strategy, then
our results suggest that the eye gaze pattern on correct trials is influenced by the
actual beliefs of the director early on, as we see the pattern emerge in Region 4 when
participants process the modifying adjective (“large”). The idea that eye gaze data
reflect an influence of the speaker’s perspective at an early stage is in line with a
number of previous perspective-taking studies mentioned above (Brown-Schmidt et al., 2008;
Hanna et al., 2003; Heller et al., 2008). The results are also consistent with Nadig and
Sedivy’s (2002) observation that 5- and 6-year-old children showed early sensitivity to a
speaker’s perspective in a much simplified director task. These articles proposed an
alternative to the perspective adjustment model, claiming that mental state information,
like any other relevant information, is potentially available to be integrated into
referential decision processes from the outset. On this constraint-based view, the extent
to which mental perspective information is used depends on the extent to which other
constraints are conflicting and how salient or available the perspective information is
(Brown-Schmidt & Hanna, 2011; Samson et al., 2010). Hanna and colleagues (2003) argued
that the Director paradigm used in Keysar and colleagues (2000) and in this article makes
conflicting cues related to the linguistic form particularly strong because the occluded
object (the distractor) is in fact the best fit for the description. Other studies such as
Brown-Schmidt (2009b) have suggested that varying the strength (or quality) of cues to the
speaker’s mental perspective can affect online referential processes. If varying cues to
mental perspective can have an impact on ToM integration, it seems plausible from this
constraint-based perspective that individuals may differ in the extent to which their
referential processes exploit a given cue. Thus, an explanation of the age-related
differences that are not accounted for by inhibitory control may lie in differences in
participants’ sensitivity of online processes to mental perspective information. This is a
hypothesis that requires further exploration. If we assume that accuracy differences in
our Director task are a product of varying abilities to integrate perspective information
in incremental referential processes, rather than at a later corrective stage, then we can
make sense of the reaction time results reported here and in Dumontheil and colleagues
(2010). These results showed shorter RTs in the Director task compared with the No-
Director task and also no RT difference in the Director condition between age groups. The
observation made about these results is that the Director task engages a more efficient or
rapid process than simple explicit rule following and does so to the same extent across
age groups. Taken together, the current results provide evidence for age-related
differences between adolescents and adults in their online use of ToM. Contrary to
perspective adjustment accounts of the Director task, our results suggest that all age
groups appear to engage in the same kind of online processes during perspective taking but
differ in how often mental state information informs incremental decision processes.
Taking our results in the wider context of research into online use of ToM, we see one
possible source of the difference between age groups as being their sensitivity to
available cues to mental state information.


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  [44] Shali Wu, Boaz Keysar. The effect of culture on perspective taking. doi:10.1111/j.1467-9280.2007.01946.x
<ART>Discovering cultural differences (and similarities) in facial expressions of emotion
================================================================================

Authors: Chaona Chen, Rachael E. Jack
DOI: 10.1016/j.copsyc.2017.06.010
Year: 2017  |  Pages: 61-66
ASJC codes: 3200

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Understanding the cultural commonalities and specificities of facial expressions of emotion remains a central goal of Psychology. However, recent progress has been stayed by dichotomous debates (e.g. nature versus nurture) that have created silos of empirical and theoretical knowledge. Now, an emerging interdisciplinary scientific culture is broadening the focus of research to provide a more unified and refined account of facial expressions within and across cultures. Specifically, data-driven approaches allow a wider, more objective exploration of face movement patterns that provide detailed information ontologies of their cultural commonalities and specificities. Similarly, a wider exploration of the social messages perceived from face movements diversifies knowledge of their functional roles (e.g. the ‘fear’ face used as a threat display). Together, these new approaches promise to diversify, deepen, and refine knowledge of facial expressions, and deliver the next major milestones for a functional theory of human social communication that is transferable to social robotics.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Are facial expressions of emotion universal across cultures or are they culture specific?
That is, can Chileans understand the emotions of the Chinese from reading their facial
expressions, and vice versa? Such questions (and more) have been at the center of one of
the longest standing debates in Psychology — whether facial expressions of emotion are
hard-wired and universal, or learned and thus subject to cultural variability. By virtue
of the dichotomous nature of the debate — that is, nature versus nurture, essentialism
versus constructivism — the direction and focus of the field has followed a cyclic, back-
and-forth seesaw pattern for over a century (e.g. see [1,2]). Several major milestones
have marked this era: Darwin's revolutionary theory of the biological and evolutionary
origins of facial expressions that supported views of universality [3]; later
counteractions by rising cultural relativism (e.g. [4]); Ekman's pioneering work showing
the pan-cultural recognition of six face movement patterns as basic emotions (e.g. [5])
that cemented the recent dominant view that facial expressions of emotion are universal.
Indeed, most introductory Psychology textbooks — a litmus test for the main thinking in
the field — tend to report that six specific face movement patterns universally convey six
basic emotions across all cultures, with cultural variance often consigned to a footnote
(if at all). Consequently, research in the past 50 years or so has focused almost
exclusively on these six facial expressions with little exploration of the cultural
diversity in face movement patterns and the social messages they convey. Yet, in the last
decade or so the emergence of an interdisciplinary scientific culture using new, imported
methods and concepts is now pushing research boundaries toward a broader, deeper, and more
refined understanding of facial expression communication. Consequently, several
significant new advances have questioned the true universality of facial expressions of
emotion, instead revealing a more complex account that combines traditionally distinct
views (e.g. nature versus nurture). Such an approach sharply contrasts with the cyclic,
seesawing patterns of past research, and mark the beginning of a new research culture that
has the potential to deliver significant new milestones that cut across fundamental (e.g.
Anthropology and Psychology) and applied (e.g. Computing Science and Social Robotics)
disciplines of social communication. In this review, we will highlight two recent pieces
of research that have used creative, out-of-the-box thinking to advance knowledge of
facial expressions of emotion across cultures, and generate new questions that will guide
future research directions. To appreciate the relevance and scope of these new approaches,
it is first useful to outline the classic methods used to understand facial expressions
across cultures.

CLASSIC APPROACHES TO UNDERSTANDING FACIAL EXPRESSIONS OF EMOTION ACROSS CULTURES
--------------------------------------------------------------------------------

Since the inception of the universality debate, a central goal has been to identify which
face movement patterns are common across cultures and which are culture-specific. However,
doing so is genuinely challenging because the human face can generate an incredible
diversity of facial expressions. To illustrate, consider that the face can produce over 40
individual movements, measured as Action Units (AUs) [6], such as Upper Lid Raiser (AU5),
Nose Wrinkler (AU9), and Lip Stretcher (AU20), each of which can be combined in different
numbers to create a vast array of complex patterns. Each AU can also be activated with a
specific movement pattern across time based on, for example, different acceleration, peak
latency, and amplitude, which further magnifies the number of movement combinations the
face can generate. Indeed, due to these complex variations Ekman noted that ‘it is
exceedingly difficult to observe the common facial expressions of emotion across cultures’
([7], p. 234). One of the most popular approaches to understanding facial expressions
across cultures has involved selecting images of facial movement patterns thought to
convey specific basic emotions based on theory and naturalistic observation, and testing
their recognition across cultures (e.g. [8–10]). Most notably, Ekman and colleagues used
this approach to show that six specific face movement patterns thought to represent basic
emotions of happy, surprise, fear, disgust, anger, and sad elicited above chance
recognition accuracy across several distinct cultures (e.g. [5]). Consequently, these six
face movement patterns, each represented as a specific combination of AUs — for example,
‘happy’ involves Cheek Raiser (AU6) and Lip Corner Puller (AU12), whereas ‘sad’ involves
Inner Brow Raiser (AU1), Brow Lowerer (AU4) and Lip Corner Depressor (AU15) — became
widely considered as the gold standard in universal displays of emotions thought to be
basic. However, the classic approach of using top-down, theory-driven methods to select
and test specific face movement patterns (i.e. the AU patterns proposed by Ekman and
colleagues) and the social messages they convey (i.e. six emotion categories) has
substantially restricted knowledge of how the face communicates emotion messages.
Specifically, such methods are typically grounded in the experimenter's culture and can
thus reflect culture-specific intuitions and observations more than human behavior more
broadly (i.e. a bias of cultrocentrism) — for example, see [11•,12–14]. Perhaps
unsurprisingly then, numerous cross-cultural studies have shown that these ‘universal’
face movement patterns are in fact not universally recognized across cultures, at least in
terms of equal performance levels (see [15,16] for recent reviews. See also Gendron in
this special issue). Instead, these face movement patterns are best recognized by
Westerners and elicit significantly lower performance in other cultures particularly for
‘fear,’ ‘disgust’ and ‘anger.’ Thus, while this approach has delivered recognizable
representations of Western facial movement patterns of emotion, equivalents in other
cultures remain largely unknown. Knowledge has been further restricted by limiting the
exploration of the social messages that face movement patterns can convey. For example,
classic approaches have focused primarily on only six emotion categories, which, in
addition to representing a small proportion of the nuanced emotion messages required for
the complex social exchanges of daily life, could instead reflect the main emotion
concepts of Western culture (e.g. see [17•,18]). Furthermore, classic approaches have
focused mostly on the inner emotional states of the transmitter — for example, a lowered
brow with tightened lips and eyes indicates that ‘he is angry’ — rather than their
predicted behaviors toward others — for example, ‘he will attack me’ — which overlooks key
aspects of human social communication and interaction ([19]; see also [20]). Finally, face
movements are complex dynamic information patterns (see [21] for a review) where the
temporal order and activation of different AUs provide important diagnostic information
for emotion categorization (e.g. [22] see also [23]). Classic approaches have mostly used
static displays such as images of posed face movements, or created the illusion of
movement by progressively morphing between two different static images (e.g. happy and
sad). Yet, neither method can capture nor explore how the dynamic parameters of face
movements — for example, AU amplitude, acceleration, or peak latency — influence the
interpretation of face movement patterns. Classic approaches have undoubtedly advanced
understanding of how face movements can convey different emotions, but knowledge remains
limited to only a small and (Western) specific set of facial patterns and social messages.
Consequently, substantial knowledge gaps remain both in the characterization of face
movement patterns (in terms of AU composition and their respective timings) and the
messages they convey within and across cultures. Rather, revealing the true diversity of
dynamic face patterns along with their cultural commonalities and specificities first
requires a broader understanding of the face movements used in different cultures and the
messages they convey (see also [24] for further discussions). We will now outline two key
studies that have made significant advances toward this goal.

<h>CHARACTERIZING DYNAMIC FACE MOVEMENT PATTERNS USING DATA DRIVEN METHODS</h>
-----------------------------------------------------------------------

In recent work, Jack and colleagues [25••] diversified and deepened knowledge of how face
movements convey emotions across cultures using a novel data-driven approach to
objectively and mathematically model dynamic face movement patterns. Figure 1(a)
illustrates this approach. On each experimental trial, a dynamic face movement generator
[26] creates a random facial animation by randomly selecting a subset of individual face
movements (i.e. AUs; see colored labels on left) and applying a random dynamics to each AU
(see color-coded curves). The cultural observer categorizes the facial animation by
emotion (e.g. disgust) and rates its intensity (e.g. strong) when the face movement
pattern correlates with their prior knowledge of that face movement pattern and its
associated message (e.g. ‘strong disgust’). If the pattern does not correspond to one of
the response options (here, the six classic emotions) the observer selects ‘other.’ After
many such trials, measures of statistical association (e.g. regression, correlation,
mutual information) are used to build a relationship between the dynamic patterns
presented on each trial and the observer's responses. The analysis thus produces, for each
observer independently, a mathematical model of the dynamic face movement patterns that
convey these specific emotions to individuals in a given culture. These mathematical
models can then be submitted to rigorous analyses to extract patterns that are common
across cultures and those that are culture-specific. Such an approach provides several
advantages, particularly in relation to the debate about the universality of facial
expressions of emotion. First, data-driven methods typically make few a priori assumptions
about which stimulus patterns will convey which messages to whom, thereby allowing a much
broader and agnostic exploration of face movement patterns as carriers of relevant
information. This approach also makes intuitive sense for the purposes of objective study,
particularly of groups for which there may be little existing knowledge (e.g. Sentinelese
society). Second, building detailed, quantitatively characterized facial movement patterns
(i.e. an information ontology) enables precise and objective analyses and comparisons to
show how face movement patterns are similar or different across cultures. Third, such
methods are generic and can be used to sample any objectively measureable information
space (e.g. face morphology and complexion, body movements [27], vocalizations [28,29]) to
test against almost any perceptual category (e.g. attractive, trustworthy [30,31],
interested, confused [32], delighted, embarrassed [25••]). Such methods therefore have
significant potential to advance understanding of how the human face conveys different
messages because they impose fewer (subjective) restrictions on empirical investigation
(see also [33•] for further discussion). Jack and colleagues [25••] used this approach to
explore cultural commonalities and specificities in facial expressions of emotion by
modeling the dynamic face movement patterns associated with over 60 different emotions
across two cultures — Western and East Asian. Using a multivariate data reduction
technique applied to the resulting culturally valid face movement models, they revealed
four latent and culturally common Action Unit (AU) patterns each associated with a
specific combination of valence, arousal, and dominance. Figure 1(b) summarizes the
results. Color-coded face maps show the four latent face movement patterns with red
indicating stronger AU presence and blue indicating weaker AU presence (see also AU labels
above each face map). Emotion words below each face show a sub-sample of the face movement
models that the latent pattern contributes most to (see [25••] for full list of emotion
words). Plots below each face show the distribution of average ratings of valence,
arousal, and dominance for each emotion word associated with each latent movement pattern.
Extracting these latent patterns from the set of 60+ culturally valid face movement models
also revealed the specific face movements that accentuate each latent pattern to create
complex facial expressions of emotion in each culture (see also [34] for discussion on
cultural accents). Together, these data question the widely held view that six facial
movement patterns universally convey the six emotions of happy, surprise, fear, disgust,
anger, and sad, and instead suggest that four latent patterns are common across cultures.
Furthermore, the combination of culturally common face movement patterns and culture-
specific accents also suggests a symbiosis (not opposition) of biology and culture,
thereby generating new predictions about the bio-cultural phylogeny and ontogeny of facial
expressions. The projection of latent face movement patterns onto broad dimensions (e.g.
valence, arousal) with specific accents that map more closely to specific categories (e.g.
rage, disgust) also suggests a specific synergy between the dimensional and categorical
perception of face movements [35,36].

<h>BEYOND SIX EMOTIONS—UNDERSTANDING THE MESSAGES THAT FACE MOVEMENTS CONVEY</h>
-------------------------------------------------------------------------

In addition to characterizing the specific face movement patterns that are used for social
interaction in different cultures, a central and related goal is to understand their
communicative aspects. That is, what messages do face movements convey to others? While
psychologists have typically focused on messages that reflect the inner states of the
transmitter (e.g. ‘he feels angry’), behavioral ecologists have tended to consider face
movement patterns as tools to influence the receiver's behavior (e.g. ‘I should submit’)
[37]. Since mouting evidence now questions the traditional psychological view that
specific face movement patterns are pan-cultural transmitters of ‘basic’ emotions (e.g.
[38–40]), new opportunities now emerge to explore the broader range of messages that face
movements convey within and across cultures. In a recent cross-cultural study [41••]
Crivelli and colleagues stepped beyond the traditional set of six emotion categories to
explore the social motives that could be attributed to face movement patterns. Across two
complementary experiments, Trobriand Islanders of Papua New Guinea matched the classic
face movement patterns of emotion with classic emotion labels (i.e. ‘happy,’ ‘surprise,’
‘fear,’ ‘disgust,’ ‘anger,’ and ‘sad’) and with different social motives such as ‘social
invitation,’ ‘protection,’ ‘threat,’ ‘submission’ and ‘rejection.’ Contrary to the view
that these face movement patterns primarily convey emotions, Trobriand Islanders matched
them with emotions and social motives. In further contrast to widely held views of
universality, Trobriand Islanders consistently associated the classic ‘fear’ face movement
pattern — that is, knitted brows, wide-open eyes, laterally stretched mouth — with ‘anger’
and ‘threat.’ Examination of the Trobriand Islanders’ material culture [11•] and
observation of their traditional rituals and social interactions [42] further corroborated
these findings by showing that classic ‘fear’ face movement patterns are consistently used
as threat displays in their own culture as well as others (e.g. Maori, ! Kung Bushmen,
Himba, Eipo). Together, these results show that face movements convey multi-component
messages including behavioral intentions rather than a fixed set of emotion categories
[43].

<h>CONCLUSIONS</h>
-----------

Here, we have highlighted two recent studies that have moved beyond the boundaries of
traditional approaches to make significant new discoveries on how face movement patterns
convey social messages across cultures. In doing so, each study demonstrates the power and
potential of interdisciplinary approaches to access the corners of knowledge that have so
far been overlooked or have remained inaccessible. In particular, mature data-driven
methods imported from visual psychophysics combined with state-of-the-art dynamic 3D
computer graphics can now characterize face movement patterns with unprecedented detail to
deliver precise information ontologies and reveal how face movement patterns differ (or
are similar) across cultures. Similarly, integrating perspectives from separately evolving
fields (e.g. social face perception of emotions, personality, conversational messages,
e.g. [44]) or across dichotomous debates (e.g. nature versus nurture) boosts progress in
understanding the functional (e.g. see [45–47]) and perceptual ontologies of face movement
patterns (e.g. personality traits [30,48], intelligence [49]. See also Niedenthal in this
special issue). Applications of advanced technologies, interdisciplinarity, and creative
thinking now mark the emergence of a new scientific culture that holds great potential to
make significant new milestones, and to raise the profile and impact of Psychology to
realize its potential in other fields (e.g. computer vision, social robotics; see [50]).

<h>REFERENCES AND RECOMMENDED READING</h>
----------------------------------

Papers of particular interest, published within the period of review, have been
highlighted as: • of special interest •• of outstanding interest


<h>REFERENCES</h>
----------

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<ART>Distortions of temporal integration and perceived order caused by the interplay between stimulus contrast and duration
================================================================================

Authors: Elkan G. Akyürek, Ritske de Jong
DOI: 10.1016/j.concog.2017.02.011
Year: 2017  |  Pages: 129-142
ASJC codes: 3204, 3205
Keywords: Missing element task, Stimulus contrast, Temporal integration, Temporal order judgment

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Stimulus contrast and duration effects on visual temporal integration and order judgment were examined in a unified paradigm. Stimulus onset asynchrony was governed by the duration of the first stimulus in Experiment 1, and by the interstimulus interval in Experiment 2. In Experiment 1, integration and order uncertainty increased when a low contrast stimulus followed a high contrast stimulus, but only when the second stimulus was 20 or 30 ms. At 10 ms duration of the second stimulus, integration and uncertainty decreased. Temporal order judgments at all durations of the second stimulus were better for a low contrast stimulus following a high contrast one. By contrast, in Experiment 2, a low contrast stimulus following a high contrast stimulus consistently produced higher integration rates, order uncertainty, and lower order accuracy. Contrast and duration thus interacted, breaking correspondence between integration and order perception. The results are interpreted in a tentative conceptual framework.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Human perceptual awareness has some paradoxical properties. We are able to detect flashes
of light that last only 1 ms, but we cannot reliably estimate just how brief that is
(Efron, 1967). It has also long been known that despite our apparent sensitivity, rapid
sequences of brief visual stimuli can outpace the visual system relatively easily. This
difficulty does not seem to rest with any particular stimulus being too brief to process
perceptually, but rather with the speed at which one stimulus is followed by the next. It
has long been known that in extremis, at high succession speeds, stimuli are simply
perceived as simultaneous (Exner, 1875). Before that unified state is reached, two
presumably related phenomena occur: Confusion arises about which stimulus came first, and
also, the identities of individual stimuli may get blended to the extent that they are
perceived as parts of a single composite stimulus, which comprises all the features of its
multiple constituents. Evidence for the first phenomenon comes from temporal order
judgment (TOJ) tasks, in which observers are presented with two almost simultaneous
stimuli, and are asked to decide which of the pair came first: When the stimulus onset
asynchrony (SOA) between them falls from approximately 100 to 20 ms, observers drop from
near-perfect order judgments to effectively guessing (e.g., Jaśkowski & Verleger, 2000).
The accuracy of order judgments is thought to depend on a central, cognitive function,
rather than modality-specific factors, since TOJ tasks involving visual, auditory, and
tactile stimuli, all produce similar estimates of the critical interval (Hirsh & Sherrick,
1961; Sternberg & Knoll, 1973). The second phenomenon, the temporal integration of
successive stimuli, is typically found in tasks that test the observer’s ability to
respond to a feature that is only apparent from the combination of two individually shown
stimulus displays. One exemplary procedure is the missing element task (MET; Akyürek,
Schubö, & Hommel, 2010; Hogben & Di Lollo, 1974), which presents two brief, successive
displays of simple stimuli such as dots or small squares within a regularly spaced grid of
5 by 5 positions, such that the first display contains 12 of these stimuli, and the second
display another 12. One position in the grid is thereby left empty, for the observer to
find. Trying to mentally compare the two partial displays from memory is not a feasible
strategy in this task, but the missing element is easily found if the observer is able to
perceptually integrate the two displays. Such temporal integration becomes increasingly
difficult as the total display duration increases, particularly beyond 100 ms. Like
temporal order judgments, it appears that integration is similar across modalities,
suggesting it has a central source also (Saija, Andringa, Başkent, & Akyürek, 2014).
Intuitively, it seems likely that temporal integration and order judgment are closely
related. If two successive stimuli are temporally integrated, and perceived as a unitary
event, surely a temporal order can no longer be assigned between them. Vice versa, if the
stimuli appear to occur so close together in time that their order can only be guessed at,
that would suggest a degree of simultaneity that would be associated with integration. The
timing of the stimuli obviously strongly governs both the ability to assign order and the
tendency to integrate. However, although a strong correlation between integration and
order perception may indeed exist (for a demonstration in a rapid serial visual
presentation [RSVP] task, see Akyürek et al., 2012), it may not always be perfect. In the
MET, observers often report a sense of having seen multiple stimuli (i.e., they detected a
temporal gap), which implies a minimal awareness of some order, even if the stimuli still
appeared to ‘fall in line’, and integration succeeded. When Kinnucan and Friden (1981)
measured MET performance (% correct localization) with stimuli of varying brightness, and
subsequently asked observers to rate the degree to which the successive MET displays
appeared as one, the outcomes differed as a function of their brightness manipulation. The
authors suggested that actual temporal integration and the subjective appearance of unity
may rely on different mechanisms, and the latter on discontinuity detection in
particular—a function that is presumably central also to temporal order judgments. Further
hints for a possible dissociation between integration and TOJ may be found in studies of
stimulus intensity effects in integration tasks. Many studies report inverse intensity
effects, that is, integration is found to be enhanced by less intense stimuli (e.g.,
Bowling & Lovegrove, 1981; Di Lollo & Bischof, 1995). A similar phenomenon of “inverse
effectiveness” has also been found in multisensory integration tasks, where less salient
stimuli are more easily integrated between modalities (Meredith & Stein, 1983). In TOJ
tasks it has also been found that higher stimulus intensity facilitates temporal
separation (Jaśkowski & Verleger, 2000), which reflects the same dynamics. Yet, there have
been reports of an opposite relationship as well, in which higher stimulus intensity
impedes separation (e.g., Ueno, 1983; Wilson, 1983). A complicating factor in the
interpretation of many of these collective studies is the possible role of retinal
afterimages, elicited by using bright stimuli on a dark background. Nonetheless, one
account for the discrepant effectiveness that has been offered is that task
characteristics vary, namely whether observers are (implicitly) asked to judge stimulus
offset or total duration (Nisly & Wasserman, 1989; Wasserman & Nisly-Nagele, 2001,
although see also Di Lollo & Bischof, 1995). It is conceivable that such characteristics
may similarly underlie possible differences between integration (in the MET) and TOJ
tasks. In line with this notion, Jaśkowski (1996) has argued that because stimulus
intensity effects found on visible persistence are not necessarily mirrored in TOJ
performance, TOJ may not strongly rely on perceived duration. When the strength of the
first and second display is independently manipulated, such that a brighter stimulus
follows a dimmer stimulus, or vice versa, the outcomes are even less uniform. In a TOJ
task, Bachmann, Põder, and Luiga (2004) found that when the relative contrast of a pair of
stimuli was manipulated, observers tended to report the stimulus with the lowest contrast
as the first. Performance was thus best when the first stimulus was dim, which does not
point to inverse effectiveness. Inverse effectiveness would predict higher perceptual
latency and more integration with the second stimulus, and thus lower TOJ performance. In
line with these findings, however, are reports by Kinnucan and Friden (1981; Experiment 1)
and Johnson, Nozama, and Bourassa (1998), who found increased integration when the first
stimulus was stronger than the second in a MET paradigm, again suggesting direct rather
than inverse effectiveness. Johnson and colleagues nonetheless also showed that inverse
effectiveness was again obtained when the two displays were matched in luminance. In a
similar vein, Long and O’Saben (1989) also observed inconsistent intensity effects on
integration. Finally, it is conceivable that temporal integration and temporal order
judgments are differentially affected by the deployment of exogenous (stimulus-driven) and
endogenous (volitional) modes of attention.1 Exogenous attention is engaged by stimulus-
related manipulations, such as intensity, while endogenous attention responds to (learned)
contingencies, such as predictable stimulus timing. Lawrence and Klein (2013) recently
demonstrated that exogenous and endogenous factors can have different, dissociable effects
on performance (reaction time and accuracy) in temporal attention tasks. Exogenous and
endogenous factors are typically not explicitly controlled for in temporal integration and
order tasks, but it is conceivable that they are differentially involved in these two
tasks, which might lead to different response profiles. Summarizing, even though
conceptually temporal integration and order judgment would appear to be two sides of the
same coin in perceptual awareness, the collective body of studies on these phenomena shows
relatively little consistency. The relationship between temporal integration and order
judgment thereby remains underspecified. A closer examination of the correspondence
between these measures of rapid visual perception seems called for, and to do so was the
aim of the present study. To thus investigate whether temporal integration and order
judgments are similarly affected by relative stimulus strength, the present study measured
both integration performance and the accuracy, as well as the associated uncertainty of
order judgments by means of a single, uniform task, in which stimulus contrast and
duration were varied systematically. The inclusion of a measure of uncertainty in the TOJ
task was motivated by a previous study by Ulrich (1987), who demonstrated that perceptual
moment and triggered moment models do not account well for TOJ performance in a classic
ternary task, in which the third response option is that of indicating simultaneity. Since
the idea of a perceptual moment, whether it is externally triggered or not, is
conceptually close to an interval during which temporal integration takes place, this may
be taken as evidence for a dissociation between integration and order judgments. However,
indicating simultaneity corresponds to a rather specific percept, while it is conceivable
that within a particular range of SOA close to actual simultaneity, the perception of
simultaneity is not elicited (e.g., because flicker is detected), but order still remains
ambiguous. In other words, in this range there may be an interval during which a gap is
detected, that is, some implicit order is recognized, but it may yet be impossible to
determine what the order actually was. Temporal integration might still occur in this SOA
range. To examine whether such impressions are indeed experienced, and whether these might
correlate with integration frequency, observers were presently given the option to
indicate uncertainty with regard to order. Finally, in the present study stimulus strength
was not manipulated directly as a function of brightness or luminance, but by means of
relative contrast, which entailed that when the first stimulus was high contrast, the
second stimulus was low contrast, and vice versa. Individual stimulus contrast was
furthermore defined such that high contrast corresponded to lower stimulus luminance (and
vice versa), which made the stimulus contrast more strongly with the white background,
thereby removing possible low-level confounds related to stimulus intensity, such as
retinal afterimages, which can vary for both visual latency and persistence measures
(Allik & Kreegipuu, 1998; Coltheart, 1980).

<h>EXPERIMENT 1</h>
------------

Experiment 1 examined the effect of stimulus contrast on temporal integration performance
and the accuracy of temporal order judgments under task conditions commonly used in MET
paradigms. To this end, an MET based on an existing paradigm (Akyürek et al., 2010), was
designed to include two different stimulus onset asynchronies (SOAs) that were determined
by the duration of the first stimulus display (cf. Di Lollo, 1977, 1980). These were
furthermore crossed with two different contrast conditions. Either the first or the second
stimulus display had higher contrast, while the other display had lower contrast. Finally,
the duration of the second stimulus display was varied as well. Next to accuracy measures
in both tasks, the frequency of uncertain responses in the ternary temporal order judgment
task was also measured.

        <hss>Participants</hss>

        Twenty-one Psychology students (19 female) at the University of Groningen
        participated in the experiment. They could earn a small monetary compensation in
        exchange for good task performance (detailed below), and were informed about this
        opportunity beforehand. The study was conducted in accordance with the Declaration
        of Helsinki, and approved by the departmental ethical committee prior to its
        execution. All participants reported normal or corrected-to-normal visual acuity
        and gave written informed consent. The data of two female participants were
        excluded, because their overall task performance did not meet a minimum level of
        10% correct in either task. In the final sample, mean age was 20 years (range
        18–25 years).

        <hss>Apparatus and stimuli</hss>

        Participants were seated individually in sound-dampened testing cabins, at a
        viewing distance of approximately 60 cm (not fixed) to the screen. Cabin lighting
        was dimmed. Stimuli were shown on a 22″ CRT screen, refreshing at 100 Hz, using a
        display resolution of 800 by 600 pixels and a color depth of 16 bit. The screen
        was driven by a standard Windows XP personal computer. The experiment was
        programmed in E-Prime 2.0 Professional, and logged responses that were entered by
        means of a standard PS/2 keyboard and mouse. As shown in Fig. 1, a white
        background (157 cd/m2) was maintained throughout the experiment. Stimuli consisted
        of colored squares of 10 by 10 pixels, centered in an invisible 20 by 20 field.
        These fields were arranged in a grid of 5 by 5 positions (25 total), which itself
        was centered on the screen. On each trial, one of these positions remained empty.
        The others were filled such that on each of the two successive stimulus displays,
        12 squares appeared in the one color, with the squares in the other display having
        the second color. The order of these colors was randomly drawn, but equally
        distributed. The same logic was applied to the contrast of the squares in either
        display, which was either low or high. Thus, a high contrast stimulus in the one
        color would be followed by a low contrast stimulus in the other color, or vice
        versa. The four possible colors were high contrast red (RGB 213, 0, 0; 23 cd/m2),
        low contrast red (RGB 255, 159, 159; 71 cd/m2), high contrast blue (RGB 0, 0, 213;
        12 cd/m2), and low contrast blue (RGB 170, 170, 255; 64 cd/m2). On the response
        screen in the temporal order judgment task, a brief text in black 18 point bold
        Courier New font prompted participants to enter which color had come first, using
        the z or c key for either color, or the x key if they were unsure. On the response
        screen in the temporal integration task, a full grid of black outlined squares
        appeared. Participants could use the mouse to click where no colored square had
        previously appeared.

        <hss>Procedure</hss>

        There were 1152 experimental trials in the experiment, divided across the two
        tasks in two successive blocks of 576 trials each. The order of blocks was
        counterbalanced between participants, and each block was preceded by 24 practice
        trials that were discarded prior to analysis. Each task block was further
        subdivided in 6 trial blocks, after which a summary of performance was given, and
        at which point participant could take a short break. Participants could initiate a
        new block by pressing the right mouse button, but within each trial block the
        trials continued without interruption. Good performance was rewarded such that a
        correct answer in the integration task yielded 10 points, while an incorrect or
        missing answer subtracted 5. In the temporal order judgment task a correct answer
        yielded 5 points, an incorrect answer cost 10 points, and participants had a third
        option: By indicating that they were unsure of the temporal order, a loss of
        points could be avoided (but nothing could be gained either). After the
        experiment, the count was settled such that €1 was paid per 500 points earned.
        Each trial started with a blank screen that lasted 600–1200 ms (600 + a ∗ 30 ms,
        where a was randomly varied between 0 and 20). The first stimulus display (S1)
        followed, with a duration of 30 or 70 ms, depending on the experimental condition.
        After a brief interstimulus interval of 10 ms, the second stimulus display (S2)
        followed in turn, lasting 10, 20, or 30 ms, again dependent on the condition. The
        response screen then appeared after a blank interval of 600 ms, and terminated
        upon user input, or when 1200 ms had passed by. The design featured three
        variables that were analyzed by means of repeated measures analysis of variance
        (ANOVA). The first variable was Contrast, with two levels (S1 high & S2 low or S1
        low & S2 high). The second two-level variable was SOA (40 or 80 ms; S1 duration +
        10 ms fixed ISI duration). The third variable was S2 duration, which had three
        levels (10, 20, or 30 ms). The full design thus comprised 12 cells (2 × 2 × 3).
        Analyses were performed separately for integration and order judgment tasks, and
        frequencies computed relative to all trials in the respective tasks. When a
        significant test of sphericity occurred, degrees of freedom were adjusted with the
        Greenhouse-Geisser epsilon correction.

<hs>  Discussion</hs>
  ~~~~~~~~~~

In line with expectations, temporal integration frequency as well order judgments showed
some clear common effects. Among these were the straightforward changes brought about by
SOA: Shorter SOA increased integration and uncertainty with regard to temporal order, and
decreased the accuracy of order judgments. S2 duration had comparable effect on temporal
integration and temporal order uncertainty, although the effect on the former was mostly
limited to the condition in which S2 was 30 ms. Furthermore, there was no overall S2
duration effect on temporal order judgment accuracy. Stimulus contrast, however, produced
some unexpected outcomes, even though the observed trends seemed straightforward
initially. Overall, there was a trend indicating that a high contrast S1 followed by a low
contrast S2 increased integration, and there was reliable evidence for a decrease in the
number of uncertain responses. Yet, contrary to what might be expected, high contrast at
S1 was also associated with a trend towards increased temporal order accuracy. Stimulus
contrast furthermore proved to depend on the duration of the shorter stimulus (i.e., S2)
quite markedly. At 10 ms S2 duration, contrary to the overall trend in the present data
described above, integration frequency and TOJ uncertainty were lower when S1 was high
contrast, compared to when it was low contrast, while temporal order judgment accuracy was
higher. However, at 20 and 30 ms S2 duration, both integration and temporal order accuracy
were higher when S1 was high contrast; contrary to the reciprocal relationship between
these measures that was observed at 10 ms S2 duration. Furthermore, temporal order
uncertainty no longer clearly differed. Taken together, the results of Experiment 1
indicated that temporal integration and temporal order judgments can vary in different
ways, depending on the interplay between stimulus contrast and duration. These findings
support the notion that even when the stimulus material is identical, the integration and
order judgment task may not tap fully identical cognitive processes, at least for the
presentation conditions currently tested. It is similarly conceivable that different modes
of attention (endogenous or exogenous) were being engaged. However, the discrepancy
between tasks seemed to rest primarily with the accuracy of order judgments. The frequency
of uncertain responses in the TOJ task showed a (mirrored) pattern that was quite similar
to that of correct integrations, showing a correlation between the means of r = 0.875.
This suggests that uncertainty with regard to order may thus rely more on sensory signals
that also enable temporal integration, while the judgment that is otherwise made may
include other, more top-down driven aspects.

<h>EXPERIMENT 2</h>
------------

Although having a variable and relatively long duration of the first stimulus display is
common in temporal integration tasks, it is conceivable that the manipulations in
Experiment 1 were specifically driven by the inequality in stimulus strength between the
first and second stimulus display. The relatively long duration of the first stimulus
presumably made it much more prominent than the second stimulus, if only because it is
known that for near-threshold stimuli, perceived brightness and duration are related
(Bloch, 1885). To investigate whether the relative strength of the first stimulus in
Experiment 1 might have played a role in the outcomes, in Experiment 2 the duration of
that stimulus was reduced so that it always matched the second stimulus, thereby
equalizing their comparative strength.

        <hss>Participants</hss>

        Twenty-five new participants (21 female) took part in the experiment. Following
        the same criterion as in Experiment 1, the data of 6 participants (5 female) were
        excluded. Mean age was 20.3 years (range 18–28 years) in the final sample.

        <hss>Apparatus and stimuli</hss>

        The experimental setup was identical to that of Experiment 1.

        <hss>Procedure and design</hss>

        The procedure and design were similarly unchanged, with the exception of S1
        duration. Rather than 30 or 70 ms, S1 duration was either 10, 20, or 30 ms, equal
        to the duration of S2 on the same trial. SOA remained the variable of interest,
        and was preserved at either 40 or 80 ms, being equal to S1 duration + ISI. Thus,
        when S1 was 10 ms, the ISI was either 30 or 70 ms, when S1 was 20 ms, the ISI was
        either 20 or 60 ms, and when S1 was 30 ms, the ISI was either 10 or 50 ms.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The results of Experiment 2 were straightforward: Integration was facilitated by a high
contrast S1 and a low contrast S2, while temporal order judgments were less accurate in
this condition. Uncertainty with regard to order again followed the opposite pattern; with
more uncertainty resulting from the high contrast S2 condition. There was evidence from
all three response measures that contrast effects were more pronounced when SOA was short.
Since the temporal intrusion is obviously higher at short SOA, these effects confirm that
contrast does not generically affect the perception of stimuli, but specifically affects
the perceptual process of temporal integration and/or separation. There were furthermore
several marginal trends suggesting that longer S2 duration might also enhance contrast
effects, to a more limited degree. These trends might have been observed since S2 was not
followed by a mask, providing more opportunity for S2 (and its contrast) to leave an
impression.

<h>GENERAL DISCUSSION</h>
------------------

Temporal integration rate and order uncertainty varied similarly as a function of stimulus
contrast and duration in both experiments, suggesting that these perceptual states may be
similarly driven by sensory information. Temporal integration rate and order judgment
accuracy also showed similar patterns in several of the presently tested conditions, yet
there were also notable exceptions, in which wholly opposite effects were observed. In the
following, a tentative account for the findings will be presented. To start with the most
straightforward outcome: The results of Experiment 2 consistently showed that a high
contrast S1 followed by a low contrast S2 resulted in more temporal confusion. Integration
as well as uncertain temporal order responses were higher, while order accuracy was lower,
in comparison with the reversed contrast. These results follow the same trend that has
been observed for stimulus intensity in integration tasks (e.g., Eriksen & Collins, 1968;
Kinnucan & Friden, 1981), and fit with previous observations that a low contrast stimulus
tends to be perceived as having occurred earlier in time (Bachmann et al., 2004). This
outcome seems compatible with the idea that low stimulus contrast evokes less brain
activity than high contrast (e.g., Sclar & Freeman, 1982), based on which a conceptual
model of temporal perception can be specified. In Panel A of Fig. 4, using as few
additional assumptions as possible, resultant neural activity distributions are visualized
as a function of time for each of the contrast conditions. Neural activity is plotted in
arbitrary units, as the model is principally neutral with regard to the nature of such
activity (e.g., firing rate or phase locking). Activity in the model is thought to have an
exponential property, such that activity accelerates towards peak activity levels, but
also drops back to baseline (the horizontal axis) more readily. This assumption of non-
linear scaling is motivated by the idea that it would help efficient representation
(Baddeley et al., 1997), but is not essential for the model to function. Although it is
not essential for the model either, it is assumed that a certain degree of activity is
needed for the brain to become perceptually aware of a stimulus; this is visualized by
means of a threshold level (t). The idea of a (dynamic) threshold is shared with the
influential Global Neuronal Workspace model developed by Dehaene and Changeux (2011) and
Dehaene, Sergent, and Changeux (2003). In this model, once activity passed the threshold,
the global workspace is “ignited” and self-amplifying recurrent activity occurs,
constituting conscious awareness. The current model is nevertheless principally agnostic
with regard to the question of whether awareness should involve wide-spread (non-specific)
recurrent activity across brain regions, or whether more local activity would suffice (cf.
Bachmann, 2007; Dehaene, Changeux, Naccache, Sackur, & Sergent, 2006; Lamme, 2006). It is
furthermore reasonable to assume some time is needed before the threshold is reached,
which is typically estimated to be around 100 ms (e.g., Wu, Busch, Fabre-Thorpe, &
VanRullen, 2009). Critically, the model couples a degree of persistence with the contrast-
induced difference in the magnitude of activity. The idea that the neural signal lingers
after stimulus offset, and that it has perceptual consequences, is supported by classic
behavioral experiments and remains uncontested (e.g., Hogben & Di Lollo, 1974; Sperling,
1960). Persistence is modeled by having neural activity subside more slowly than it rises.
This produces the dynamics visualized in Panel A of Fig. 4 (by the solid lines; the dotted
lines reflect an additional assumption further detailed below). When a high contrast
stimulus is followed by a low contrast stimulus (solid lines, top plot), it differs in
three ways from when a low contrast S1 is followed by a high contrast S2 (solid lines,
bottom plot): The activity peaks are closer together, the interval in-between during which
neither stimulus is above threshold is shorter, and there is more overlap between the
activity distributions of the stimulus pair. These differences all point towards the same
perceptual outcome, namely that the perceived temporal separation between the stimuli is
lower when a high contrast S1 is followed by a low contrast S2, as expressed in increased
integration rates, increased TOJ uncertainty, and reduced TOJ accuracy. It may be noted
here that previously advanced formal models of persistence would presumably generate
similar predictions (Dixon & Di Lollo, 1994; Loftus & Irwin, 1998). The present model not
only shows which assumptions are necessary to produce the observed behavior, but also
highlights at least one other candidate assumption that would actually be
counterproductive, namely that brain activity associated with low contrast not only
produces lower peak amplitude, but also takes longer to build than for high contrast
stimuli. Panel B of Fig. 4 shows the resultant distributions. Including this assumption
would appear to be justified on the basis of previous findings. For instance, Alpern
(1954; see also Roufs, 1963) demonstrated that observers had more difficulty judging
temporal order with lower stimulus intensity, and Kelly (1961) showed that flicker
sensitivity increased when luminance was higher, suggesting that the visual system ‘speeds
up’. A similar result was obtained for stimulus contrast in both flicker and motion tasks
(Stromeyer & Martini, 2003). However, when this assumption is added to the model, it only
counteracts the observed behavior. As shown in Panel B of Fig. 4 (solid lines), when a
high contrast S1 is followed by a low contrast S2, S2 would have reached threshold
relatively late, while the high contrast S1 would not have been delayed (top plot). In
this case, maximal temporal separation should have been observed, resulting in more
accurate and less uncertain TOJ, and less integration, and the reverse when a low contrast
S1 is followed by a high contrast S2 (bottom plot). Neither of these predictions were
confirmed by the present data, suggesting that task performance did not depend on such
latency differences. Thus, these differences are best omitted from the model if it is to
account for temporal integration and order judgment as a function of relative stimulus
contrast.

<hs>  Relationship to brain electrophysiology</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There is some prior evidence from event-related potential (ERP) studies of temporal
integration that supports the model dynamics advocated here. Akyürek et al. (2010; Akyürek
& Meijerink, 2012) measured component amplitude during both early (N1, N2) and late (P3)
phases of the ERP during temporal integration in a typical MET, similar to the current
paradigm. In their task, SOA was determined mainly by S1 duration, as in Experiment 1 of
the present paper. The authors found that increased component amplitude across N1, N2, and
P3 was associated with successful integration of the two successive displays. By contrast,
there was no indication that the latency of any of these components changed
systematically. If component amplitude can be related to representation strength
(assumption 1), this pattern of results would match the predictions of the model depicted
in Fig. 4, provided that the ERP was driven mainly by the (onset of the) first stimulus
(assumption 2). Some evidence for both assumptions may be found in the Appendix Figure
published by Akyürek and Meijerink (2012), the relevant panel of which is reproduced here
as Fig. 5. Here, the ERPs of different S1 duration conditions of their MET were overlaid
(40, 70, and 100 ms, with 10 ms ISI). The figure firstly shows that increased component
amplitude was elicited by the longer-lasting (stronger) S1s, at least as far as the
earlier components are concerned. Secondly, it is apparent from this figure also that
there was no consistent time-shift in the ERP, despite the varying SOA between the
contrasted conditions. These findings held not only when the participants were doing an
actual integration task, but also for another experimental condition in which no temporal
integration, but only singleton detection was required, with identical stimulus timing
(not shown). At a conceptual level, the ERP observed in this MET thus aligns well with the
neural activation dynamics predicted by the current model. Similar direct ERP evidence for
TOJ tasks under conditions comparable to those in the MET paradigm is not yet available.
Such evidence would provide a further validation check of the assumptions underlying the
present model. Eventually, a direct test of the effects of stimulus duration and relative
contrast on the ERP in these tasks will be essential to further support theorizing on the
underlying neural dynamics. Further research is thus clearly needed here. Some relevant
results are nevertheless available from a previous ERP study of a different TOJ task in
which attention was also modulated (McDonald, Teder-Sälejärvi, Di Russo, & Hillyard,
2005). An amplitude change, spanning the P1, N1, and P2 components, was also implicated in
this study. Stimulus and task differences may affect the components that are modulated,
but the activity dynamics were in line with the current model, even though other authors
have additionally observed component latency shifts in a bimodal TOJ task (Vibell, Klinge,
Zampini, Spence, & Nobre, 2007).

<hs>  Differences between tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Can the model depicted in Panel A of Fig. 4 be further modified to account for the deviant
results obtained in Experiment 1? In this experiment, SOA was directly determined by S1
duration, as is common in temporal integration tasks (e.g., Akyürek et al., 2010; Di
Lollo, 1977, 1980). Even though the present study used negative contrast (i.e., relatively
dark stimuli on a white background), it seems likely that the impression made by the
stimuli increases in strength as duration increases (cf. Bloch’s Law for perceived
brightness; Bloch, 1885). Previous research furthermore suggests that the relatively long
duration of S1 may have made its offset in particular more noticeable (Wilson, 1983). Two
notable observations resulted in the present study. First, at 10 ms S2 duration, a pattern
of performance was observed that was opposite to that found in all conditions of
Experiment 2. A low contrast S1 followed by a high contrast S2 facilitated integration,
decreased the accuracy of order judgments, and increased TOJ uncertainty, compared to the
reverse contrast condition. Second, the accuracy of order judgments at 20 and 30 ms S2
duration remained higher for a high contrast S1 followed by a low contrast S2 than for the
reverse contrast condition, even though integration performance reverted to match
Experiment 2 at those S2 durations. In the following, possible explanations for these
discrepant results will be offered, interpreting the results within the framework of the
model. Primarily, to account for the deviance in temporal integration frequency and order
judgments in the 10 ms S2 condition of Experiment 1, an additional assumption is required
to alter the model dynamics. This assumption is that stimulus contrast and duration
interact in some cases, such that a particularly weak stimulus not only attains lower peak
activity, but also takes longer to get there. This may (only) happen in the most extreme
condition currently tested in Experiment 1, when a brief (10 ms), low contrast S2 is
preceded by a strong, and relatively long-lasting S1. The hypothesized role for S1 here is
justified because the combination of its contrast and duration is likely to intensify
forward masking of S2 (cf. Kirschfeld & Kammer, 2000). It may also cause S1 to be
perceived as if it occurred later, due to its delayed offset (Jaśkowski, 1991), increasing
the ambiguity of the stimulus sequence. In line with the above, it must also be assumed
that when S1 has low contrast, and S2 has high contrast, the hypothesized slowing of
S2-related activity does not, or only to a much lesser extent, occur. The resultant
distributions are visualized with the dotted lines in Panel A of Fig. 4. Because the low
contrast S2 (top plot) suffers more from short duration than the high contrast S2 (bottom
plot), it gets delayed to the point where the temporal separation perceived between the
stimuli is greater in the former case than in the latter. This would cause the observed
reversal of performance seen at 10 ms S2 duration in Experiment 1. Note that applying the
same transformations on the distributions in Panel B, which assume task performance should
reflect a ‘main effect’ of contrast on activity rise time, does not as easily produce a
reversal in outcomes, again suggesting that this assumption is less likely to be correct.
Here, even though the slowing of a low contrast S2 might be less (because of the already-
present slowing for low contrast stimuli), this would only reinforce the temporal
distinctiveness advantage of the condition in which a high contrast S1 precedes it (top
plot). The comparatively small delay that might occur for a high contrast S2 would be
hard-pressed to overcome the temporal proximity caused by the slow rise of the low
contrast S1 that precedes it (bottom plot). With regard to the observed facilitation of
temporal order judgment accuracy in all S2 duration conditions when it followed a high
contrast S1 in Experiment 1, the most parsimonious account appears to assume that when
confronted with a relatively long S1 the observers relied on a different signal to judge
order. Since the activity associated with S1 is expected to be high overall, the total
area of its activity distribution above the detection threshold may also become quite
large. This may demarcate the stimulus from the weaker S2 to such an extent that it is
consequently seen (correctly) as having come first. Such an effect is reminiscent of prior
entry (Spence & Parise, 2010; Titchener, 1908), an attention-related latency illusion in
which stronger stimuli are seen as having occurred earlier in time (though see Jaśkowski,
1996, for an opposing view on prior entry in TOJ). It seems conceivable that while order
judgments may normally rely on perceived temporal separation, it may be overruled by the
strong discrepancy in stimulus (offset) clarity, as elicited by the relatively long
duration of S1 in Experiment 1. The decision level that is needed to judge order, beyond a
state of mere uncertainty, may provide the opportunity to take such additional evidence
into account. This idea fits with previous evidence against an account of TOJ performance
on the basis of perceptual latency (Ulrich, 1987), and a similar proposal that was fielded
by McDonald et al. (2005), who studied attentional biases in temporal order judgments. The
authors observed attentional amplitude enhancement over visual cortex, in the absence of
latency change, suggesting that (attentional modulation of) TOJ in their task relied on
signal strength. A similar reliance may have occurred in the present study. It has indeed
been suggested previously that attentional involvement in temporal order judgment may
primarily affect decision mechanisms (Aghdaee, Battelli, & Assad, 2014). Thus, if the
relatively long duration of S1 caused differential involvement of exogenous and endogenous
modes of attention (cf. Lawrence & Klein, 2013), that might be expected to result in a
change at the decision level, thereby causing TOJ accuracy to deviate from the other
measures. In view of previous evidence implicating parietal cortex in perceiving stimulus
on-/offset and temporal order (Battelli, Cavanagh, Martini, & Barton, 2003; Davis,
Christie, & Rorden, 2009), it might be a fruitful avenue for further neurophysiological
research to assess the relative involvement of this area as a function of stimulus
contrast and duration in both order and integration tasks, which might provide converging
evidence for differential functional involvement. Taken together, not one single mechanism
based on either perceived stimulus strength or latency seems able to account for all
aspects of the present results. Behavior in trials in which a TOJ decision was made in
particular seems to involve processing beyond what underlies both temporal integration and
the experience of order uncertainty. A similar conclusion was reached by Di Lollo, von
Mühlenen, Enns, and Bridgeman (2004), based on an examination of metacontrast masking as a
function of target-mask (∼S1-S2) SOA and mask duration. These authors obtained evidence
that different mechanisms might underlie the effects on task performance caused by these
two factors. Although the tasks in the present study were different, and although the
duration of S1, rather than S2, seemed the critical variable in these tasks, the outcomes
do seem to converge on the idea that not all aspects of the perception of brief,
successive stimuli follow uniform rules. As previously alluded to, the current results
suggest that this non-uniformity might be attributed to the need for more (conscious)
evidence weighing to reach a perceptual decision (beyond being uncertain about order) in
the TOJ task than in the integration task, which might imply reliance on recurrent
pathways in the brain, and possibly increased top-down control in the former task. This
could be accounted for in models of perceptual awareness through interactions between
stimulus-specific and top-down activations, as previously proposed by Bachmann (1997),
which might specifically trigger deviations in some cases, such as when a relatively long
S1 is presented.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

Although temporal integration and temporal order judgments were presently found to change
consistently with relative stimulus contrast in most conditions of the present study, this
was clearly less the case when the duration of the first stimulus was relatively long.
Thus it must be concluded that when it comes to perceiving simultaneity and episodic
unity, relative stimulus contrast interacts with stimulus duration, such that at a given
contrast level facilitation as well impedance can result. The present results also
underscore that in the perception of rapid successive stimuli, seeing integrated percepts
and temporal order do not always perfectly align, resulting in a ‘two-sided’ perceptual
experience: It seems that sometimes perceived stimulus strength can be used, possibly post
hoc, to infer order between a pair of stimuli that make an integrated impression.


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<ART>Dizziness—A Resource: Dizziness and the compossible space in research-creation
==============================================================================

Authors: Ruth Anderwald, Karoline Feyertag, Leonhard Grond
DOI: 10.1016/j.emospa.2017.07.001
Year: 2018  |  Pages: 122-130
ASJC codes: 3205, 3207
Keywords: Compossible space, Dizziness, Moving-image art, Philosophy, Research-creation

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

This article summarises part of the findings of our research-creation Dizziness––A
Resource (2014-17) funded by the Austrian Science Fund and hosted at the Academy of Fine
Arts Vienna. We will introduce the two underlying key concepts, related practice examples,
and tell the story of experimental filmmaker Oskar Fischinger's wax-slicing machine.
Furthermore, we will give insight into the philosophical background of the methodology
that we have developed throughout the research process. This article underlines the
creative potential of dizziness by introducing new ways it may be conceptualised, thinking
with and through the frames of emotions and space. Dizziness is understood as a phenomenon
of embodied knowledge (Manning, 2009; Varto, 2013), blurring categorisation between the
perception and conception of dizziness. Taumel, German for ‘dizziness’, implies a broader
semantic field including medical indications of vertigo and further notions of physical
and emotional disequilibrium, exhilaration, confusion, uncertainty, disorientation, and
turmoil. Taumel therefore includes positive, negative, and ambiguous connotations.
Mirroring the research trajectory, this jointly written text oscillates between cross-
disciplinary conceptualisation and practice, approaching dizziness in a metaphorical sense
as object and method. Research-creation as the combination of arts-based research and
research-based art (Loveless, 2015; Manning, 2008) allows for manifold approaches,
heterogeneous formats, diverse outcomes, and contradicting methods as modes of ‘curiosity,
sustained questioning, and analysis’ (Green, 2012: 272). As in dizziness, we believe that
the strength of research-creation resides in its ambiguous, wide-stretched and diversity-
affirming nature. The first key concept we introduce in this paper relates to dizziness as
a possible resource for creativity. The second explores ‘compossibility’ as an actual and
theoretical space for the experience of, and reflection on, dizziness. Both concepts are
mutually dependent if they are to bring about their creative potential. Dizziness––A
Resource started from the assumption that feelings of dizziness – of being lost or
disoriented (Solnit, 2005; Ladewig, 2016) – are not only a part of the artistic and
philosophical, but also of any creative process (Anderwald et al., 2013; Anderwald and
Grond, 2015; Feist, 1998; Feyertag, 2015; Jullien, 2012; 2015; Montuori, 1994).
Consequently, we inquired when, where, and how dizziness arises and how the experience of,
and reflection on, dizziness and its conceptualisation can lead to a better understanding
of inherent creative processes. Relating to the first key concept, our proposition is that
the notion of dizziness could provide a critique of simplistic views on creative processes
that describe them as logical circuits, e.g. ‘break in, break down, break through’
(Anderwald and Grond, 2015; Deleuze, 2003; Katzmair, 2015; Marks, 1998). Moreover,
dizziness as a ‘concept in motion’ needs a mode of thinking infused by movement, not
relying on fixed points but on moving relations and shifting anchor points (Strong, 2004).
Our critique underlines the importance of the creation of ‘compossible spaces’ by the
interaction and collaboration of persons who feel affected by dizziness in different or
even conflicting ways, experiencing it as fear and/or pleasure. Within these ‘compossible
spaces’ dizziness as movement becomes a resource, shaking and swiping away long-
established oppositions and making room for the unfolding of seemingly contradictory
feelings, processes, theories, matters, and disciplines.

<h>FALLING INTO DIZZINESS</h>
----------------------

Dizziness arises locally and combines various elements: theory and emotion, momentum and
disorientation, time and space. It can clear, cause a great stir, or move heaven and earth
– it destabilises. According to Plato, dizziness constitutes all philosophical thought by
destabilising the basis of knowledge to a state of uncertainty: as an ontological state it
can prompt transformation and innovation (Plato, Timaeus: 49e; Echterhölter et al., 2010).
The dizzy individual experiences an emotional rollercoaster ride involving feelings of
exhilaration, anxiety, and disorientation. Exposure to dizziness increasingly reduces
predictability and our ability to exercise control. From a medical perspective, dizziness
is considered a symptom, not a sign. Similar to vertigo, it can only be described by the
experiencing subject and cannot be measured objectively. As a medical symptom, dizziness
is ambiguous and can lead to a multitude of diagnoses. The vestibular system is the
sensory apparatus that signals the coordinates of our spatial position to the brain,
affording our sense of balance and spatial orientation. Together with the cochlea, it
constitutes the labyrinth of the inner ear. As our movements consist of rotations and
translations, the vestibular system comprises two components: the semi-circular canal
system that indicates rotational changes in velocity and the otoliths that indicate linear
changes in velocity. The vestibular system sends signals primarily to the neural
structures that control our eye movements and to the muscles that keep us balanced.
Psychobiologist Matti Mintz's research suggests a connection between our ability to
maintain emotional and corporeal equilibrium and flexibility. His research particularly
indicates comorbidity between anxiety disorders and a poor sense of orientation and
balance (Mintz, 2016; Erez et al., 2002). Working on his film Failed States (2008)
filmmaker Henry Hills literally used dizziness as his resource. Spinning around and
becoming dizzy with his camera in hand enabled him to overcome a severe crisis in his
work. Not only had the vertiginous perception of the world matched his uncertainties about
his work, but his becoming dizzy also stimulated new sensations and brought back a
childhood memory – spinning and falling into the grass while watching the world turning
around him. Speaking of filmmaking, dizziness in its corporeal sense can be transmitted by
unstable or rotating camera movements of which abundant examples exist in art films such
as Stan Brakhage's Scenes Before Under Childhood (1967-70), Michael Snow's La Région
Centrale (1971), Steve McQueen's Static (2009), or Catherine Yass' Lighthouse (2011).
Moreover, dizziness in its metaphorical sense has been employed in cinema from its very
beginning, as in the Lumière's gravity-defying first special effect in film (La démolition
d'un mur, Auguste and Louis Lumière, 1896) or Georges Méliès’ early film Un homme de tête
(1898) and was later elaborated in surrealist films such as Teinosuke Kinugasa's A Page of
Madness (1926) or Hans Richter's collaborative film Dreams That Money Can Buy (1947).
Furthermore, dizziness can be produced by abundant visual input such as the flickering of
light, as used in Tony Conrad's film Flicker (1965) or Joachim Koester's This Frontier is
an Endless Wall of Points (after the mescaline drawings of Henri Michaux) (2007). But
dizziness can also be produced by a deprivation of visual stimuli, as seen in the
‘prisoner's cinema’ phenomenon reflected in, for instance, Melvin Moti's eponymous video
work (2008). When a person – a prisoner for example – is subjected to prolonged visual
deprivation, hallucinations in the form of colours and shapes might occur (Sacks, 2012).
Therefore, dizziness indicates a situation in which the possibilities of reality can no
longer be grasped in a habitual manner because of a lack or overload of stimuli,
knowledge, or input. Whether frightening or enjoyable, by falling into dizziness we enter
a stage of uncertainty, disorientation, and heightened vulnerability where we are unsure
of our abilities, perceptions, and processing – uncertain of ourselves (Butler et al.,
2016). This manifests through feelings of excitement caused by a distorted perception of
time and space, loss of proportion, and an increasing feeling of lack of control and/or
temporary loss of memory and self (Katzmair, 2015; Montuori, 1994). Dizziness can affect
us as an individual, group, or society (Koller, 2014a,b) and the ensuing insecurity
affects interaction with our environment (Lorey, 2015). To different degrees, these
conditions of loss and feelings of insecurity are present in all dizziness processes, from
crisis to flow experiences (Csikszentmihalyi, 1996), aporia to ecstasy, immersion in a
film or book to philosophical pondering, or the creation of an artwork (Montuori, 1994).
Moreover, the emotional spectrum of dizziness must be considered in order to comprehend
its potential as a resource. The experience of dizziness contains ambiguous and even
contradictory feelings. This inherent unpredictability makes clear why dizziness cannot be
seen as a means of ‘self-design’ (Groys, 2008). In its reflection, dizziness exposes
related emotions as movements propelling the individual into a certain direction or
perspective. For the aforementioned filmmaker Henry Hills, memories of being dizzy
generated a positive reminiscence of childhood, which helped him come to terms with a
creative crisis. However, not all recollections of dizziness necessarily need to be
positive to have a constructive effect on navigation through dizziness. Therefore, the
combination of the physical, emotional, and metaphorical experience of dizziness with the
more reflexive and theoretical framework of compossibility proved essential for this
research if dizziness was to be seen as a resource for creativity. Dizziness represents
the limit state of the challenged subject experiencing the vacillation between loss of
control (staggering) and gain of control (equilibrium) (Echterhölter et al., 2010). In its
metaphorical sense, dizziness starts with teetering and staggering at the limitations of
knowledge, for instance when faced with a central problem or crisis (Alon, 2014) or aimed
towards the creation of a new work of art (Anderwald et al., 2013). The compossibility of
precipitancy and precision is what German philosopher Marcus Steinweg suggests for a
situation involving dizziness in artistic or philosophical practice (2013). He further
indicates a connection between the processes of thinking and art creation, both grounded
in the groundless and the abyssal, starting from inherently aporetic moments (Kofman,
1988) and aiming at the impossible, in contrast to the self-reduction to the possible
exemplified by politics (Steinweg, 2013). As Steinweg quotes Heiner Müller: ‘Something new
can only develop when you are doing something you cannot do […] Art is what you want to
do, not what you can do’ (2013: 48). Describing this movement as headless or blind,
Steinweg uses the practice of writing as an example in which the author develops a
distance from the universe of facts without ever fully detaching from it. This striving to
‘develop something new’ by ‘doing what you cannot do’ is further reflected in the
following story about seminal filmmaker Oskar Fischinger that influenced our
methodological approach.

<h>APPLYING FISCHINGER'S WAX-SLICING MACHINE TO DIZZINESS—A RESOURCE</h>
-----------------------------------------------------------------

Between 1918 and 1921, filmmaker Oskar Fischinger – literature aficionado and at the time
an apprentice – prepared a lecture for his literary club in Frankfurt. He set out to
analyse and compare the structure of two theatre plays: Fritz von Unruh's Platz and
William Shakespeare's Twelfth Night. To supplement his talk, he drew graphic charts that
illustrated the plays' dramatic developments as lines that collide, swirl, and break as
the action unfolds. Trying to express his findings, he remembered: ‘In preparing this
speech I began to analyse the works in a graphic way. [ …] On large sheets of drawing
paper, along a horizontal line, I put down all the feelings and happenings, scene after
scene, in graphic lines and curves […] that showed the dramatic development of the whole
work and the emotional moods very clearly’ (Fischinger, 2006: 110). However, this graphic
exposition of the dramas' content seemed to baffle his audience. Fischinger understood
that he needed to add the element of temporal movement in order to express his thoughts
more clearly. After being introduced to Walter Ruttmann's work by a fellow member of his
literature club, he felt encouraged to explore the possibilities of moving images.
Following his precursory experiments with coloured liquids and wax, Fischinger invented a
compelling apparatus: the wax-slicing machine. First, coloured wax threads were cast into
a block, which the machine pushed towards a revolving, fan-shaped blade. The blade would
cut thin slices from the block as the film camera shot single frames through an apparatus
in the blade, to which the camera shutter was synchronised (see Figs. 1 and 2). Fischinger
explains: On a 2-dimensional plane, plastic forms were build up [sic] and formed in a
block of colour wax—all kinds of forms and shapes and colour were imbedded in such a block
of wax forms like pyramids or kegels [cones] or fantastic shaped forms like spirals etc.
[…] [A]fter such a wax block [was] finished squarely, [it] was put in a machine, which cut
fine thin slices off the surface of the block. After each slice was cut off, a motion
picture camera placed before the machine photographed the surface of the wax plane. Then
the next slice was cut off and again one frame was photographed with the camera … Imagine
the beauty of a polished cut through a wonderful stone […] somehow the camera records the
cutting of the full stone from the beginning to the end. The camera would, so to speak,
wander through and through the stone, the wonderful pattern would grow. (undated
typescript) The methodology and research process of Dizziness––A Resource is inspired by
the wax-slicing machine's animation process. Each cut in the wax block generates a shot
from Fischinger's camera and thus the cut becomes a film frame. Setting these frames in
motion animates the wax block's inherent dynamics. With every slice, Fischinger's abstract
film expands, involving the viewer in its dramatic evolution. In contrast, the
metaphorical wax block of our research-creation – a ‘block of sensations’ – grows by
gradually incorporating different conceptual, emotional, and disciplinary approaches
towards dizziness. According to Deleuze and Guattari: What is preserved – the thing or the
work of art – is a bloc of sensations, that is to say, a compound of percepts and affects.
Percepts are no longer perceptions; they are independent of a state of those who
experience them. Affects are no longer feelings or affections; they go beyond the strength
of those who undergo them. Sensations, percepts, and affects are beings whose validity
lies in themselves and exceeds any lived. (1994: 163-64). Moreover, these percepts and
affects are the slices or ‘snapshots’ of our research-creation created through giving the
research process a momentarily distinct form through writing, making art, or staging
cross-disciplinary events (Coleman and Ringrose, 2013). Like single film frames, these
artworks and texts are preserved and recorded on our project blog. Comparable to animating
the snapshots on film, the blog's visitor then animates the accumulated ‘snapshots’ of the
research process and creates his or her own ‘animation’ by choosing what to see, hear, or
read (http://on-dizziness.com). Moving through the blog, the viewer is able to experience
artworks, animate knowledge, and gain a new perspective on dizziness. Fischinger's
animation process inspired this methodology: describing and applying movement in order to
connect and convey meaning or knowledge that cannot be exposed otherwise.

<h>DIZZY MOTIONS IN COMPOSSIBLE SPACE</h>
----------------------------------

‘ … because in the end, dizziness, which I call ambiguity, is compossibility.’ (François
Jullien, Interview, Paris, May 26, 2015) Falling into dizziness is a gradual process and
enabling the experience of, and reflection on, dizziness requires a specific spatial and
temporal setting. French philosopher François Jullien compares this process to passing
through the ‘sas’ (French for ‘lock’, ‘sluice’, or ‘compression chamber’), a space of
exchange and transformation, passage through which results in a change in motion and
velocity (2015). The sas is the metaphorical space-time of the in-between (things, views,
feelings, situations, definitions, theories, matters) where compossibility sets in
(Bachelard, 1969; Jullien, 2012; Game and Metcalfe, 2011; Simmel, 1994). According to
Jullien, the term ‘compossibility’ means the possible and inclusive togetherness of
contradictory elements (2015). Out of this confrontational togetherness, an in-between
space can emerge, creating the possibility of dissolving and/or re-arranging what has been
so far. Evidence for such a compossible space is already found in Plato's notion of the
chôra: a space, the formless form, literally the maternal womb or matrix (Burchill, 2011;
Pechriggl, 2006). Chôra is neither being nor non-being but an interval in which ‘forms’
were originally held (Plato, Timaeus: 52d-53a). Another historical reference to
compossible space is found in Leibniz's concept of possible worlds, constituted of
compossible substances. These substances are only able to create a possible world when
they do not contradict or exclude each other (Messina and Rutherford, 2009). However, by
Jullien's contemporary definition, compossibility involves creating a space of ambiguity
where established oppositions possibly collide, dissolve, and mix anew (2015). Compossible
space may be used to describe a situation and condition that an individual, group, or
society can transgress and designates the possible and inter-relational existence of
several mutually exclusive and contradictory worlds or states, as in simultaneous
experiences of fear and pleasure evoked by dizziness. Therefore, compossibility can be
understood as a paradoxical space where established opposites and ideas are still
recognisable but tend to dissolve. The different motions assigned to dizziness – falling
into, passing through, and coming out – disturb and unbalance the constituting components
of the compossible space, allowing for their re-combination. Fischinger's animation of the
wax block may represent this passing through the compossible space. As motion, dizziness
gradually becomes independent of the initial experience, still preserving it, but
necessarily transforming the experience and ensuing emotions by reflecting on them,
transforming thrill into fear into pleasure for instance. To reflect always means to
create ruptures and pauses in the continuum of time and space; at the same time,
reflection also requires cohesion in order to take the experience a step further towards
understanding (Arendt, 2006). This reflexive process builds upon plateaus, it ‘slices the
wax block’ of experience. Visualised in Fischinger's work, the slicing of the wax block
and ensuing snapshots engender cohesion through their animation on screen and thus
establish the compossible space for the passage through dizziness. In this sense,
dizziness does not solely pertain to a theoretical concept, but also a physical sensation
and an ambiguous emotional experience, shaking convictions and habits. At the same time
ontological concept and symptom, method and object, sensation and metaphor, dizziness is
apt to animate its contradicting constituting components, and this requires a space to
unfold. The inclusion of feelings into the philosophical concept of dizziness – feelings
preserved as affects like despair, fear, enjoyment or exaltation – contributes to the
transformation of a static philosophy of being into a dynamic philosophy of becoming made
of percepts, affects and concepts (Deleuze and Guattari, 1994). With the following example
from our research-creation, we introduce artworks created through the experience of, and
reflection on, dizziness. The perception of spinning, transformed into a photo-sculpture
model, provided first insight into the interdependence of dizziness and compossible space.
Concerning the sensation of spinning, the simple percept of dizziness proved insufficient,
demanding a supplementary transformation of the subjective experience into an affect, as
we will explain in the following chapter.

<h>BACK TO THE DIZZY BODY</h>
----------------------

To elaborate on compossibility and dizziness, we became particularly interested in
constituting the ephemeral moment of a spinning person's simultaneous standing and
falling. It appears to be the turning point, the superposition of keeping upright and
falling, the precise temporal moment of the compossibility of motion and standstill
(Feyertag, 2015). Moreover, while falling we might believe we are suddenly falling from
safety to uncertainty. But the basis on which we fall plays a significant part in our
staggering and falling. The supposition that one is stable before falling is misleading;
the staggering begins while we still feel safe and in control. To elucidate on these
thoughts in practice, every morning for the first few weeks of the research-creation
project we spun in turn until falling down in a dizzy state and noted our observations in
a research diary. Soon it became clear that one can see the other person stumbling or
falling, but no outward signs indicate the quality of the other's experience of dizziness
or when or if the other will fall. The individual's experience of staggering and falling
is peculiar. From an evolutionary point of view, staggering triggers reflexes that are
very old, located in the lower region of the spinal cord rather than the brain. When
staggering, we instantly relax the unsteady leg and tense the other in an effort to regain
balance (Bähr and Frotscher, 2009). As adults unaccustomed to falling, we were hardly able
to predict whether we will regain balance or fall. At times, we experienced our staggering
and falling down as if it was happening in slow motion – we even felt detached from
ourselves. The dizziness we encountered in our daily spinning was sometimes so strong that
it impeded us to go on with our daily chores. Our notes describe that the dizziness felt
slightly different every day, at times rather brief, at times a lingering experience. We
felt particularly overshadowed by the ensuing dizziness when we were full of energy and
eagerness to start the day. In the course of this self-experiment, the anticipation of
feeling unwell after spinning resulted in a very unpleasant start of the day. Due to this,
and the fact that we usually needed quite some time to recover after spinning, we stopped
these proceedings after a few weeks. In lieu we started riding a merry-go-round whenever
in a difficult spot in our research-creation, as we found that the uncomfortable memories
of being dizzy increasingly impacted the actual experience. Clearly, our emotional
conditions influenced our experience of dizziness, pointing to the situational and
conditional character of experiencing dizziness. Conversely, whether pleasant or
unpleasant, dizziness as an out-of-the-ordinary experience extracts the individual from
the day-to-day and thus may present a freeing experience. Furthermore, within the
experience of dizziness the compossibility of simultaneously standing (certainty) and
falling (uncertainty) can be stated but not really observed except with still photography.
Intrigued by the sensations of dizziness and the observation of our dizzy bodies, we began
work on data for 3D models to compare the expressions of the dizzy body to the sensation
of dizziness. Using photogrammetry, we tried to translate subjective sensations into
percepts and affects with the help of ‘iconic’, a leading 3D studio in Istanbul.
Surrounded by the studio's cage of cameras, we spun one after the other to the point of
falling. After quite a few failed efforts, ‘iconic’ was finally able to record snapshots
of us in the moment of simultaneously falling and standing, the data from which was used
to print two photo-sculpture models (see Figs. 3, 4, & 5). These were created through the
combination of a full-body colour photograph superposed on a 3D rendering of the body in
motion. Anderwald's figurine depicts her staggering, precisely at the moment of falling.
The statue cannot stand, velocity solely stabilised the moving body into an upright
position in the captured moment, exposing one's illusion of control of the body's
movements while already falling. Both statues visualise the unpredictability of the body's
expression when the subject is dizzy. Indeed, Grond was falling backwards the moment his
photo was taken. However, his figurine's poise seems balanced and stable because his
movements before and after the snapshot cannot be anticipated from his composure. Both 3D
snapshots designate a compossible point, a threshold where standing and falling are
momentarily coinciding (Feyertag, 2015; Jullien, 2016). Nevertheless, the statues cannot
transmit the feelings the individuals experienced. As a symptom, dizziness needs
individual expression and cannot be sufficiently explained or understood by objective
measurements or visualisation from/of the outside.

<h>TRANSFORMING DIZZINESS TOGETHER</h>
-------------------------------

Dizziness––A Resource aims at a more holistic understanding of the potential of dizziness
by describing it through cross-disciplinary practice, analysis, and reflection. In our
conversations with artists, scientists, and experts in fields related to dizziness we
realised that describing dizziness is dependent on the use of metaphorical language. We
intensified the collaboration with philosopher Feyertag, with who we started co-authoring
texts including an artistic text lending voice to a personification of dizziness. In this
chapter we will provide an overview of the processes leading us to the creation of a sound
installation that treats the exhibition Dizziness. Navigating the Unknown (Kunsthaus Graz
and Ujazdowski Castle CCA Warsaw) as a film animation, including the works of fellow
artists as snapshots that form a compossible space animated by the voice of personified
dizziness. After capturing and analysing the dizzy body's expression, we shifted our
attention to the feelings involved in experiencing dizziness using the generated 3D data
as an artistic and reflective tool, considering this moment from different perspectives.
Clearly, dizziness could not be sufficiently described from the outside alone, even if the
data is cast into a sculpture and forms what Deleuze and Guattari term a ‘percept’.
Studying dizziness as a symptom and process requires the consideration of individual
expression and time. Therefore, we reanimated the captured data from the ‘iconic’ sessions
as a series of still images and simultaneously searched for a narrative to translate the
feelings of dizziness into another artistic language. In cooperation with graphic designer
Christian Hoffelner, we produced The Bend (2015), a booklet that combines the still images
from these sessions with a poetic text of the same name that emulates a spinning motion –
walking in uncertainty – as it is written in a loop. This writing process transformed the
percept of dizziness into an affect by adding a poetic narrative. (see. Fig. 6).
Translating the research involving the 3D figurines further into creative writing, we
started imagining dizziness as an archaic and hermaphroditic being, soliloquising its
distress and desire. Now generated by the polyphony of the project's artistic and
philosophical voices, our writing gave an account of the feelings that affected us while
exposed to dizziness at various stages of the research process. Integrating narrative and
personal forms of dizziness, we continued by producing the film Dizziness is My Name,
using footage of the animated statues in addition to the co-authored monologue of
‘Dizziness’ in which the persona states: ‘Dizziness is my name and I am a pendulum without
rope or gravity. My gravity is movement.’ This artistic work eventually led to the
eponymous sound installation that guides viewers through the compossible space of the
exhibition Dizziness. Navigating the Unknown (Kunsthaus Graz and Ujazdowski Castle CCA
Warsaw). The narrating voice of ‘Dizziness’ entices the visitor to move erratically
through the exhibition space, setting in motion the animation of dizziness exposed in the
selected artworks. Our cooperation with Katrin Bucher Trantow, chief curator of Kunsthaus
Graz, was not as much a search for a common vocabulary as it was a search for common
ground in the work process. Our exchange over the research trajectory was continuous and
lively, involving other artists, scientists, and curators. We discovered that we had to
adapt our improvisational attitude, while Bucher Trantow adjusted her strategic approach.
The resulting process of co-curating the aforementioned exhibition mirrored the research-
creation's findings in historical and contemporary artworks. Bucher Trantow brought a
focus on emotion to the research process, emphasising the importance of viewers' feelings
towards individual artworks and their emotional journey through the exhibition space.
Correspondingly, we divided the exhibition into three intersectional fields: falling into
dizziness, navigating through dizziness, and coming out of dizziness. These specific foci
are inspired by a conversation with artist Joachim Koester, who insisted on the importance
of coming into and getting out of dizziness as the defining moments for future feelings
towards this experience of dizziness (unpublished interview by Anderwald and Grond,
09/14/2014).

DIZZINESS IN ARTISTIC WORK PROCESSES – COOPERATION WITH CREATIVITY RESEARCH AND KUNSTHAUS GRAZ
--------------------------------------------------------------------------------

In cooperation with Mathias Benedek and Emanuel Jauk, creativity researchers at the
University of Graz, we addressed dizziness' potential and what it might entail for
creativity research. The first challenge was, as it is often in cross-disciplinary
research, finding a common language. Merleau-Ponty's metaphor describing the search for
creative expression as ‘a step taken in the fog’ (Merleau-Ponty, 1964: 3) was the starting
point of discussion with Benedek and Jauk when explaining our understanding of dizziness
as a possible resource. In our experience as artists, we have regarded dizziness as a
resource for creating new artistic work (Anderwald et al., 2013), whereas the creativity
researchers considered states of dizziness as unproductive. Therefore, we questioned a
relevant group of artists on their experience. But how could their experience of dizziness
be measured for creativity research? We decided to develop a survey on dizziness in
creative work processes connected to an art competition in order to gather empirical
insight and quantitative and qualitative data on artists' work processes in a valid
setting as well as encourage new ideas and artworks on the topic. Together with Bucher
Trantow, we designed ‘Living in a Dizzying World’, the competition that was tied to the
survey for inclusion in the final exhibition of this research-creation at Kunsthaus Graz.
Standardised surveys, personality tests (Rammstedt and John, 2005; Tubes and Christal,
1992), and divergent thinking tests (Nusbaum et al., 2014) were examined and, by updating
some of the questions, a questionnaire applicable to artists in their studio environment
was created. Another challenge was to establish a language that did not put the artists
enrolled in the survey under additional stress, but at the same time was still valid for a
creativity research sampling investigation. Despite our efforts, six of the forty-four
artists dropped out of the competition and survey because they felt pressure responding to
daily questions about their work process. Other artists found it advantageous, as this
participant explains: Somehow I was comforted by the idea that other artists were
reflecting on their process at the same time I was. It made me realize that the challenge
of art making is not unique—it is difficult for all of us and can lead to different
emotional states, etc. I thought that the survey was really beneficial for me in terms of
paying attention to my process in an objective way. (Benedek et al., 2017: no pagination)
Most artists appeared to have mixed feelings about their respective creative process,
partially because the competing participants only had two weeks to create and submit their
artwork to be judged by an international jury (Katrin Bucher Trantow, Sergio Edelzstein,
Anna Jermolaewa). The daily questionnaire included seventeen recurring questions and an
open section for comments and could be filled out via an app or online form. At the end,
the artists were asked to upload their finished work to a university server. In order to
re-start the applicants' work process at the beginning of the competition, a quote from
David Bowie's song ‘Changes’, ‘turn and face the strange’ (1971), was sent to the
participants as an additional inspiration for the work. Indeed, finding a timespan that
was reasonable for the artists' work processes, but also accord with experience-sampling
methods for the investigation of extended creative work was yet another methodological
challenge. For two years of close cooperation, we gained insight into the emotions and
experiences of dizziness in artists’ work processes. Our first conclusion is that how
artists deal with states of dizziness is related to their personality structure, momentary
condition, and past experience. Some artists stated that they never experience anything
like dizziness in their work process, while others related the opposite. Between-person
analysis revealed that artists with lower levels of agreeableness, higher levels of
openness and a history of high artistic achievements generated artworks the jury found to
be of superior quality (Benedek et al., 2017). The artworks in the competition examined
dizziness mainly from an aleatoric or destructive perspective. The winning artwork Fractal
Crisis (2016) by Viktor Landström and Sebastian Wahlforss follows a woman having a nervous
breakdown, a situation of internal and external crisis (Bucher Trantow et al., 2017).
Furthermore, the personality trait of openness allows for a greater ability to perceive
two contradicting images simultaneously as separate and combined images (Antinori et al.,
2017). This research-creation contextualises said ability with John Keats' notion of
‘negative capability’ coined in 1918 (Keats, 2014). It designates the capability of
staying open and flexible when confronted with unknown, uncategorised or unpredictable
knowledge or situations, – or in context with our research – the ability to enter and
endure compossibility (Jullien, 2015). Within the compossible space the ability to use the
movement of dizziness as creative potential becomes decisive. Philosophically speaking,
this means opening up to the indefinite and shaping this opening that can be equated with
defining the indefinite (Steinweg, 2013). In this sense the creative work process is
considered oblivious to the aspects of impossibility. Creative processes therefore lean
towards the aporetic and experimental, towards situations of unexpectedness and
experiences of groundlessness and despair (Kofman, 1988; Alon, 2014). When we arrive at a
dead end, with no possibility to carry on or through, are we forced to recombine all
impossibilities – all which seems contradictory, exclusive, senseless, and disparate – in
order to transform them into a compossible space and make for a yet unknown possibility.

<h>CONCLUSION</h>
----------

In this article we defined the term ‘dizziness’ applied in Dizziness––A Resource and
reflected on the concepts of dizziness and compossibility in theory and practice. The
cross-disciplinary research-creation process of Dizziness––A Resource has led to the
development of a methodology that draws from Fischinger's invention of the wax-slicing
machine for film animation, an approach mirrored in the conception of the exhibition
Dizziness. Navigating the Unknown. The experience of dizziness contains ambiguous and even
contradicting feelings. In its reflection, dizziness exposes related emotions as movements
that propel the individual in a certain direction or perspective. Moreover, understanding
the emotional and spatial movements that constitute dizziness, requires a mode of thinking
based on movement. If we are able to conceptualise dizziness as constant movement through
spatial, emotional, and social surroundings, we may gain new perspectives on the affects
and effects of thought. Therefore, we base dizziness, as well as this adapted process of
research-creation, on ‘the idea of “movement”, movement conceived both as object and
method, as syntagma and paradigm, as a characteristic of works of art and a stake in a
field of knowledge claiming to have something to say’ (Didi-Huberman in Michaud, 2007) and
relate it to Fischinger's animation process. We conclude that movement is at the core of
our experience of, and reflection on, dizziness. Furthermore, only through movement that
describes dizziness can the pure modal logic of compossibility be set in motion. As
addressed artistically and philosophically over the research process, thinking-in-motion
holds the potential to overcome the traditional oppositions of motion and standstill,
certainty and uncertainty, knowing and not-knowing, because there is space and movement
‘in between’ professed opposites, which can become productive in moving towards new
knowledge and meaning (Arendt, 2006). The concept of dizziness introduces an element of
movement and openness to the ‘in between’ that could enable us to think the compossibility
of opposites and acknowledge this grey zone or blandness for its creative and innovative
potential (Bey, 1985; Deleuze and Guattari, 1994; Jullien, 2007; Manning, 2008). Therefore
the development of ‘negative capability’ and enabling social and spatial surroundings are
germane for transforming the ambiguity of dizziness into a resource. Hence, the experience
of dizziness is never purely enjoyable, as anyone who has set foot on a rollercoaster can
concur, but it can provide new sensations, stimulus, and input. This out-of-the-ordinary
experience brings about feelings of excitement and exhilaration that can oscillate between
elation and exasperation, and thus its concomitant unpredictability has to be dealt with
on an individual and interpersonal scale. Encouraged by our cross-disciplinary
cooperation, we plan to continue this research-creation to provide a more holistic
understanding of how dizziness affects togetherness. The research-creation Dizziness––A
Resource was supported by the Austrian Science Fund (AR-224), FWF-PEEK, AR 224. We are
very grateful to Mathias Bendek and Emanuel Jauk, Institute of Psychology, University of
Graz, and Katrin Bucher Trantow and Kunsthaus Graz (Universalmuseum Joanneum) for their
valuable contributions to this research-creation. We are also thankful for the important
comments of the peer reviewers that helped sharpen the focus of this contribution to ESS.


<h>REFERENCES</h>
----------

  [11] Mathias Benedek, Emanuel Jauk, Kevin Kerschenbauer, Ruth Anderwald, Leonhard Grond. Creating art: An experience sampling study in the domain of moving image art. doi:10.1037/aca0000102
  [15] Gregory J. Feist. A meta-analysis of personality in scientific and artistic creativity. doi:10.1207/s15327957pspr0204_5
  [18] Ann Game, Andrew Metcalfe. 'My corner of the world': Bachelard and Bondi Beach. doi:10.1016/j.emospa.2010.10.002
  [31] Sarah Kofman. Beyond Aporia?. doi:10.4324/9781315537597
  [38] Anna Antinori, Olivia L. Carter, Luke D. Smillie. Seeing it both ways: Openness to experience and binocular rivalry suppression. doi:10.1016/j.jrp.2017.03.005
  [46] Emily C. Nusbaum, Paul J. Silvia, Roger E. Beaty. Ready, set, create: What instructing people to "be creative" reveals about the meaning and mechanisms of divergent thinking. doi:10.1037/a0036549
  [49] Beatrice Rammstedt, Oliver P. John. Short version of the Big Five Inventory (BFI-K): Development and validation of an economic inventory for assessment of the five factors of personality. doi:10.1026/0012-1924.51.4.195
  [52] Georg Simmel. Bridge and Door. doi:10.1177/026327694011001002
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<ART>Does executive function mediate the path from mothers' depressive symptoms to young children's problem behaviors?
================================================================================

Authors: Gabriela D. Roman, Rosie Ensor, Claire Hughes
DOI: 10.1016/j.jecp.2015.09.022
Year: 2016  |  Pages: 158-170
ASJC codes: 3204, 3205
Keywords: Executive function (EF), Externalizing problems, Internalizing problems, Longitudinal analysis, Maternal depression, Mediation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study investigated the mediation role played by children's executive function in the relationship between exposure to mild maternal depressive symptoms and problem behaviors. At ages 2, 3, and 6. years, 143 children completed executive function tasks and a verbal ability test. Mothers completed the Beck Depression Inventory at each time-point, and teachers completed the Strengths and Difficulties Questionnaire at child age 6. Longitudinal autoregressive mediation models showed a mediation effect that was significant and quite specific; executive function (and not verbal ability) at age 3 mediated the path between mothers' depressive symptoms (but not general social disadvantage) at the first time-point and children's externalizing and internalizing problems at age 6. Improving children's executive functioning might protect them against the adverse effects of exposure to maternal depressive symptoms.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Among parents of young children, symptoms of depression are common and often chronic
(Field, 2011), such that McLennan, Kotelchuck, and Cho (2001) found that nearly a quarter
(24%) of 17-month-olds were exposed to maternal depression, with a third of these children
still exposed to depression a year later. This early exposure to maternal depressive
symptoms predicts a plethora of negative child outcomes. Compared with children of
nondepressed mothers, children of depressed mothers show elevated rates of both
externalizing problems, such as hyperactivity (Ashman, Dawson, & Panagiotides, 2008),
conduct disorder (Leschied, Chiodo, Whitehead, & Hurley, 2005), and violence (Hay, Pawlby,
Waters, Perra, & Sharp, 2010), and internalizing problems, such as depression (Hammen &
Brennan, 2003; Murray et al., 2011), anxiety (Gartstein et al., 2010), and social phobia
(Biederman et al., 2001). Studies of the mechanisms underpinning these associations have,
to date, focused on aspects of maternal functioning such as maternal regulatory processes
(Dix & Meunier, 2009). Child functioning has received much less attention, which is
surprising given that exposure to maternal depressive symptoms is related to cognitive
abilities that are relevant for behavioral adjustment such as executive functions (Hughes,
Roman, Hart, & Ensor, 2013) and language development (e.g., Quevedo et al., 2012).
Research into the cognitive and neural mechanisms that may underlie childhood antisocial
behaviors has highlighted the higher order processes associated with the prefrontal cortex
that underpin flexible goal-directed action, collectively known as executive function (EF)
(Hughes, 2011). The protracted development of the prefrontal cortex has led theorists to
posit that EF might be particularly susceptible to environmental factors (e.g.,
Mezzacappa, 2004; Noble, Norman, & Farah, 2005). Studies of risk factors indicate that
exposure to extreme adversity (i.e., maltreatment or neglect) has profound consequences
for the functioning of the prefrontal cortex (for a review, see Belsky & De Haan, 2011).
Until recently, however, few studies considered less extreme adversity such as exposure to
mild maternal depressive symptoms (Odgers & Jaffee, 2013). The current study addressed
this gap by focusing on children’s exposure to maternal depressive symptoms in a normative
sample and by examining the relationship between exposure to maternal depressive symptoms
and child EF over the course of early childhood (ages 2–6 years). The development of the
prefrontal cortex is marked by growth spurts, with the first 3 years of life representing
a time when the majority of myelination occurs and is paralleled by peaks in synaptic
formation and dendritic growth (e.g., Spencer-Smith & Anderson, 2009). This heightened
brain development translates into important EF developments through both refinements of
acquired skills (e.g., Alloway, Gathercole, Willis, & Adams, 2004) and initial attempts to
integrate and coordinate multiple functions (Garon, Bryson, & Smith, 2008). The emergence
of toddlerhood as a critical period is further supported by research highlighting that
individual differences in EF appear remarkably stable over time (Carlson, Mandell, &
Williams, 2004; Fuhs & Day, 2011; Hughes & Ensor, 2007; Hughes, Ensor, Wilson, & Graham,
2010), with the implication that effects observed in preschoolers and school-aged children
might simply reflect carry-on effects of early delays. Indeed, the complexity of EF
development, whereby at each point emergent skills are reliant on the mastery of simpler
abilities, lends support to the idea that EF development follows a cascading pathway model
(e.g., Cummings, Davies, & Campbell, 2000). As such, this study focused on whether
exposure to maternal depressive symptoms might translate into behavior problems
specifically through delays in EF skills acquisition at a very early stage (i.e., age 3
years). The current article represents a secondary data analysis. To examine whether poor
early EF is a mechanism through which exposure to maternal depressive symptoms translates
into problem behaviors, the current study builds on several studies involving overlapping
samples. Regarding the first path in this proposed mediation model, these earlier studies
showed that children of mothers who had fewer depressive symptoms at child age 2 years or
who displayed steeper recoveries from depressive symptoms over 4 years typically showed
better EF at age 6 years (Hughes et al., 2013). This was true even when individual
differences in children’s working memory at age 2 and maternal education and positive
control at child ages 2 and 6 were accounted for (Hughes et al., 2013). In contrast, no
relationship between maternal depression and child EF was found by two separate studies of
older children in which maternal depression scores were dichotomized (Klimes-Dougan,
Ronsaville, Wiggs, & Martinez, 2006; Micco et al., 2009). As discussed by Hughes and
colleagues (2013), the most likely explanations for these discrepant findings relate to
differences during the developmental period under focus (adolescence vs. early or middle
childhood) and the sensitivity of the measures used. Regarding the latter, the previous
studies that reported a relationship between maternal depression and child EF used self-
reported continuous measures of depression that differentiated between mothers’ depression
severity at all levels, whereas the studies that found no relationship used rigorous
clinical diagnoses such that mothers with subclinical depression were placed in the
“control” group together with nondepressed mothers. Regarding the second path of the
mediation model, longitudinal analyses of data from the current sample have documented
predictive relations between (a) poor EF at age 3 years and multi-informant ratings of
problem behaviors at age 4 years (Hughes & Ensor, 2008) and (b) poor EF at age 4 years and
low gains in EF from ages 4 to 6 years and teacher-rated problem behaviors at age 6 years
(Hughes & Ensor, 2011). Importantly, even though these earlier studies demonstrated each
of the two paths of the mediation model, they did not examine whether EF is a mechanism
through which exposure to maternal depression transforms into problem behaviors. Indeed,
significant relationships for different segments of a theoretical model of mediation do
not conclusively establish a mediated effect (Kenny, 2012). In this case, elevated
maternal depressive symptoms may independently predict both poor EF and child problem
behaviors (i.e., multifinality of causes; Cicchetti & Toth, 1998). The only study to have
investigated a mediation effect was an analysis of data from an enlarged sample of 235
4-year-olds comprising the study children and their best friends; although this analysis
did show a mediation effect of child EF in the relationship between exposure to maternal
depressive symptoms and child behavior difficulties (sample overlap: 66%; Hughes & Ensor,
2009a), the cross-sectional nature of the data limits the strength of conclusions that can
be reached. To address this gap, the current study aimed to examine whether children’s EF
at age 3 years mediates the relationship between mothers’ depressive symptoms at child age
2 years and children’s externalizing and internalizing problems at age 6 years.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

At study entry, the sample comprised 143 families (out of a total of 192 eligible
families), with a child aged between 24 and 36 months at the first visit and English as a
home language, recruited in Cambridgeshire, United Kingdom. Starting with age 4 years, the
sample was enlarged to include the study children’s best friends, yielding a new sample of
235 children. This implied that analyses focused on toddlerhood involved the core sample,
whereas analyses focused only on preschool and later development involved the enlarged
sample, with a sample overlap of approximately 66%. The current study focused on
toddlerhood; therefore, data analysis was applied to members of the core sample for whom
data were available at ages 2 and 3 years. Face-to-face recruitment was carried out at
support groups for young mothers and at every mother–toddler group in wards within the
highest quartile nationally of deprivation (Noble et al., 2008), thereby resulting in a
socially diverse sample. Informed consent and ethical approval were obtained for all
assessments. As a token of thanks for their participation, families received £20 (i.e., 20
British pounds) for each visit to the home. A copy of the video footage recorded in the
lab and taxi/travel costs were also provided. More than 95% of the children were
White/Caucasian and 56 (39%) were girls. At the study entry, 25% of women were single
parents and 53% of mothers had no education qualifications or had education qualifications
only up to GCSE (general certificate of secondary education) level (usually obtained at
age 16 years). Regarding family size, 12% of children had no siblings, 53% had one
sibling, 22% had two siblings, and the remaining 13% had three or more siblings. This
study focused on data collected when children were 2 years old (Time 1; SDage 2 = 4
months), 3 years old (Time 2; SDage 3 = 4 months), and 6 years old (Time 3; SDage 6 = 4
months).

        <hss>Deprivation</hss>

        Following the example of Moffitt et al. (2002), deprivation at study entry was
        evaluated using eight markers: maximum education level per family was GCSE
        (usually obtained at age 16 years), head of household occupation in elementary or
        machine operation occupation, annual household income under £10,000, receipt of
        public benefits, council house as the home, home reported as crowded by the
        mother, single-parent family, and no access to a car. Of the 127 (89%) families
        without missing data, 31% of families showed no deprivation (zero markers), 32% of
        families showed moderate deprivation (one or two markers), and 37% of families
        showed high deprivation (three or more markers).

        <hss>Mothers’ depressive symptoms</hss>

        Maternal depressive symptoms were self-reported using the Beck Depression
        Inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961) at all time-points.
        The BDI includes 21 questions about affective, somatic, and cognitive symptoms.
        Item response categories range from 0 (minimal) to 3 (extreme). Item intraclass
        correlation was high at all time-points, with a Cronbach’s alpha ⩾ .82. Two-
        parameter logistic item response theory models applied at each time-point revealed
        that the BDI was especially successful in identifying mothers who experienced mild
        to moderate depressive symptoms. Some of the items that showed lowest power to
        discriminate between different levels of depressive symptoms were those about
        “weight loss,” “loss of interest in sex,” and “somatic preoccupation.” Some of the
        items with consistently high discrimination across assessments were those about
        “concentration difficulty,” “past failure,” or “loss of pleasure.” The most
        “difficult” items (i.e., items endorsed only by very depressed mothers) were
        “punishment feelings,” “suicidal ideation,” “somatic preoccupation,” and “past
        failure,” whereas the “easiest” items (i.e., items also endorsed by nondepressed
        mothers) were “tiredness or fatigue,” “irritability,” and “changes in sleeping
        patterns.”

        <hss>Children’s problem behaviors</hss>

        At child age 6 years, 74 teachers completed the Strengths and Difficulties
        Questionnaire (SDQ; Goodman, 1997) for 120 of the children. The SDQ response
        categories range between 0 (not true) and 2 (certainly true), and the 25 items are
        divided into 5-item subscales: a positive subscale (prosocial behavior) and four
        problem subscales (conduct problems, hyperactivity, emotional problems, and peer
        problems). This study focused on the problem subscales. Item intraclass
        correlation was high for the total problem behavior score (Cronbach’s alpha = .82)
        and for the items comprising the externalizing (Cronbach’s alpha = .84) and
        internalizing (Cronbach’s alpha = .74) problems subscales.

        <hss>Verbal ability</hss>

        At ages 2 and 3 years, children’s verbal ability was assessed using the Naming and
        Comprehension subtests of the British Abilities Scales (BAS; Elliott, Murray, &
        Pearson, 1983), which tap expressive and receptive language skills. Scores ranged
        between 0 and 20 for the Naming subtest and between 0 and 27 for the Comprehension
        subtest. At age 6 years, verbal ability was measured using the Revised British
        Picture Vocabulary Scale (BPVS; Dunn, 1997), which taps receptive language. Total
        scores were computed as a sum.

        <hss>Executive function</hss>

        At ages 2 and 3 years, children completed four tasks: Beads, Trucks, Baby Stroop,
        and Spin the Pots. At age 6 years, children completed three tasks: Beads,
        Day–Night, and Tower of London. The tasks were delivered by researchers (PhD
        students and research assistants) trained by the task developer. The Beads task, a
        part of the Stanford–Binet Intelligence Scales (Thorndike, Hagen, & Sattler,
        1986), taps working memory. Four warm-up trials are followed by 10 trials where
        children are shown 1 or 2 beads (for 2 or 5 s, respectively) and must identify
        them in an image of 12 beads sorted by color and shape. In a further 16 trials,
        children are presented with a photographic representation of a bead pattern for 5
        s, which they must reproduce with real beads arranged on a stick. Scores represent
        the number of correct trials and range between 0 and 26 points. The Trucks task
        taps rule learning and switching (Hughes & Ensor, 2005), each tested with an
        8-trial phase. Children must guess which of two pictures of trucks will lead to a
        reward. The first truck chosen by children gives the rule in the first phase; the
        opposite truck gives the rule in the second phase. Scores represent the number of
        correct trials and range between 0 and 16 points. The Spin the Pots task (Hughes &
        Ensor, 2005) assesses working memory. Children are shown eight distinct “pots”
        (e.g., jewelry boxes, candy tins, wooden boxes) placed on a Lazy Susan tray and
        are invited to help the researcher place attractive stickers in six of the eight
        pots. Then, the tray is covered with a cloth and spun, after which the cloth is
        removed and children must choose a pot. The test is discontinued when children
        find all of the stickers or after 16 attempts. The score is 16 minus the number of
        errors made. The Baby Stroop task taps inhibitory control (Hughes & Ensor, 2005).
        Children are presented with a normal-sized cup and spoon and a baby-sized cup and
        spoon. In the control phase, children must name the large cup/spoon “mommy” and
        the small cup/spoon “baby.” In the second phase, children must use the labels
        incongruously. The Day–Night task is a Stroop task designed for older children
        (Gerstadt, Hong, & Diamond, 1994). This task is identical to the Baby Stroop task
        except for the props; the cup and spoon are replaced by two abstract patterns
        representing “Day” and “Night.” The 12 trials are presented in a pseudo-random
        order, with scores ranging from 0 to 12. The Tower of London task (Shallice,
        1982), taps planning abilities. The props include a wooden board with three pegs
        of unequal size and three large spongy balls. The large peg can carry three balls,
        the middle peg can carry two balls, and the small peg can carry only one ball.
        Children must reproduce arrangements presented in an image by moving only one ball
        at a time and using the minimum number of moves needed. Warm-up trials with one-
        move problems are followed by two-, three-, and four-move problems (three problems
        each). Children achieve 2 points for success using the minimum number of moves, 1
        point for success with the use of extra moves, and 0 points for failure to
        complete the problem or when more than 2n + 1 extra moves are necessary. Total
        scores range between 0 and 18 points.

<h>RESULTS</h>
-------

Analyses were conducted using Mplus Version 7.11 (Muthén & Muthén, 1998–2010). Power
analyses were performed using the macro developed by Preacher and Coffman (2006). Little’s
(1998) MCAR tests applied to missing data patterns revealed that data were missing
completely at random for all variables. Specifically, data were missing completely at
random in relation to maternal depressive symptoms, such that depressed mothers were not
more likely to drop out of the study than nondepressed mothers. Maternal depression scores
were based on longitudinal factor analysis; as such, scores were estimated in instances
with missing data. Therefore, factor scores of maternal depressive symptoms were available
for all mothers and at all time-points. The same was true for child EF. Data were also
missing completely at random in relation to child problem behaviors, and further missing
value analysis revealed that missing information about problem behaviors was not more
likely to come from boys than girls or from children of mothers with low education than
other children. Missing data were avoided with regard to problem behaviors for those cases
with data on some of the items through the use of factor analysis in the creation of final
scores. To account for data missingness and skewness, we used robust estimators: WLSMV to
obtain factor scores of depressive symptoms and child problem behaviors (here indicators
were categorical) and MLR to specify factors of EF and mediation models (here all measures
were continuous). Model fit was evaluated using the comparative fit index (CFI), the
Tucker–Lewis index (TLI), and the root mean square error of approximation (RMSEA).
Adequate fit was achieved for CFI and TLI values ⩾.90 and for RMSEA values ⩽.08 (Hu &
Bentler, 1999). Good fit was achieved for CFI and TLI values ⩾.95 and for RMSEA values
⩽.06 (Bentler, 1990). The chi-square is also reported for all models but was not used in
the evaluation of model fit due to the tendency of the chi-square to over-reject true
models for large samples and/or models with many degrees of freedom (Bentler, 1990). Fully
standardized coefficients are presented.

<hs>  Descriptive statistics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Across time-points, 65% to 73% of mothers exhibited no or minimal depression (i.e., scores
< 10), 19% to 24% exhibited mild to moderate depression (i.e., scores of 10–18), and 7% to
12% exhibited moderate to severe levels of depressive symptoms (i.e., scores ⩾ 19). Mean
levels of child problem behaviors (M = 8.07) fell within the normal range (i.e., scores of
0–11), but elevated problem behaviors were also noted (Max = 25), and on average scores
were slightly higher (on all dimensions except peer problems) than a nationally
representative sample of 5- to 10-year-old children in Great Britain (youthinmind, 2012).
Specifically, borderline or abnormal levels of problem behaviors were exhibited by 13.8%
of the children in relation to conduct problems, 34.7% of the children in relation to
hyperactivity, 11% of the children in relation to emotional problems, 14.5% of the
children in relation to peer problems, and 26.1% of the children in relation to total
behavior difficulties. Table 1 summarizes children’s mean levels of EF and verbal
abilities. As expected, children improved in their mean levels of verbal abilities and EF
across time.

<hs>  Data reduction</hs>
  ~~~~~~~~~~~~~~

We created factor scores from the questionnaire-based variables to index mothers’
depressive symptoms at each time-point and child problem behaviors at the final time-
point. We used the procedure described by Ensor, Roman, Hart, and Hughes (2012) to create
factor scores of mothers’ depressive symptoms by dichotomizing BDI items due to low
selection rates of the higher categories and applying single-factor confirmatory factor
analysis with scalar invariance (i.e., equal structure, loadings, and thresholds) to
factors obtained at each time-point. The model achieved good power (α = 1.00) and adequate
fit, χ2(1967) = 2184.025, p < .01, RMSEA = 0.03, 90% confidence interval (CI) [0.02,
0.04], CFI = .92, TLI = 0.92. We used the procedure described by Goodman, Lamping, and
Ploubidis (2010) to create factor scores of child problem behaviors by applying
confirmatory factor analysis with four first-order factors (conduct problems,
hyperactivity, emotional problems, and peer problems) and two second-order factors
(externalizing problems [conduct problems and hyperactivity] and internalizing problems
[emotional problems and peer problems]). The model achieved good power (α = .91) and
adequate fit, χ2(166) = 291.74, p < .01, RMSEA = 0.08, 90% CI [0.06, 0.09], CFI = .91 TLI
= 0.90. All item loadings onto first-order factors (β ⩾ .57, p < .01) and all first-order
factor loadings onto second-order factors were significant (β ⩾ .45, p < .01). In
addition, we used the findings of exploratory factor analyses previously reported by
Hughes and Ensor (2008) at ages 3 and 4 years to specify a single factor of EF at each
time-point. At ages 2 and 3 years, we specified a factor based on children’s scores on the
Beads, Trucks, Baby Stroop, and Pots tasks. At age 6 years, we specified a factor based on
children’s scores on the Beads, Stroop, and Tower of London tasks. To examine stability in
EF over time, we specified regression paths between EF factors at consecutive time-points.
To account for the known association between EF and verbal ability, we included indicators
of verbal ability as time-varying covariates of EF and specified regression paths between
verbal ability indicators at consecutive time-points. The model achieved adequate power (α
= .73) and adequate fit, χ2(73) = 106.54, p < .01, RMSEA = 0.06, 90% CI [0.03, 0.08], CFI
= .93, TLI = 0.91. The range of factor loadings obtained here (βrange = .24–.65, p < .01)
was similar to that reported by studies where EF was constructed using slightly different
tasks (e.g., .17–.63; Espy, Kaufmann, Glisky, & McDiarmid, 2001). Fully standardized
parameter estimates indicated that inter-individual differences in EF (β2–3 = .91 and β3–6
= .80, p < .01) and verbal ability (β2–3 = .79 and β3–6 = .60, p < .01) were stable over
time. In addition, EF and verbal ability were significantly positively related at each
time-point (rage 2 = .84, p < .01, rage 3 = .56, p < .01, and rage 6 = .78, p < .01).

<hs>  Mediation analyses</hs>
  ~~~~~~~~~~~~~~~~~~

To test mediation effects, we specified the autoregressive longitudinal mediation model
presented in Fig. 1. The model showed good fit to the data, χ2(160) = 203.215, p = .01,
RMSEA = 0.04, 90% CI [0.02, 0.06], CFI = .95, TLI = 0.94. The model achieved good power (α
= .95). The power of the model was enhanced by the large number of degrees of freedom of
the model (df = 160 in the mediation model), which offset any power issues related to a
small sample size (143 participants). Relative to girls, boys had poorer EF at age 2 years
(β = −.21, p = .01) and higher externalizing problems at age 6 years (β = .13, p < .05).
Net of these effects, higher maternal depressive symptoms at child age 2 predicted poorer
child EF at age 3 (β = −.20, p < .01) even when accounting for stability in EF from age 2
to age 3 (β = .90, p < .01) and the significant association between EF and verbal ability
at age 3 (β = .71, p < .05). In turn, poorer EF at age 3 predicted higher externalizing
problems at age 6 (β = −.32, p < .01) and higher internalizing problems at age 6 (β =
−.32, p < .01). This was true even given the significant concurrent relationship between
child EF and externalizing problems (β = −.48, p < .01) and between child EF and
internalizing problems (β = −.43, p < .05). Regarding externalizing problems, the indirect
effect was significant (βind = .07, p < .05, 95% CI [0.001, 0.130]). Regarding
internalizing problems, the indirect effect was marginally significant (βind = .06, p =
.059, 95% CI [−0.002, 0.134]). To further probe the robustness of our findings, we tested
two alternative models. The first model (Fig. 2) showed that verbal ability did not act as
an alternative mediator, although higher maternal depressive symptoms at child age 2 years
predicted marginally significantly lower child verbal ability at age 3 years, which in
turn predicted higher externalizing and internalizing problems at age 6 years. The second
model (Fig. 3) showed that the observed effects of depressive symptoms on behavior
adjustment via poor EF did not simply reflect effects of deprivation more generally
because, although exposure to higher levels of deprivation at age 2 directly predicted
higher externalizing problems at age 6 and poorer EF at age 3, and poorer EF at age 3
predicted higher externalizing and internalizing problems at age 6, the indirect effects
were not significant.

<h>DISCUSSION</h>
----------

This study investigated whether the path from maternal depressive symptoms to young
children’s problem behaviors operates, at least in part, through impairments in children’s
EF. Building on a previous model, which tested the long-term associations between
children’s exposure to maternal depressive symptoms during toddlerhood and EF at age 6
years (Hughes et al., 2013), the current findings support Cummings et al. (2000) cascading
pathway model of development in that they demonstrate more immediate associations between
exposure to maternal depressive symptoms and poor EF, which are then carried over time.
Regarding the second path, our findings were consistent with those from a recent meta-
analytic review (Schoemaker, Mulder, Deković, & Matthys, 2013), which showed a weak to
moderate association between preschool children’s externalizing problems and their overall
EF, inhibitory control, working memory, and attention shifting (Schoemaker et al., 2013).
Our findings are also consistent with previous reports of associations between
internalizing problems and overall EF (Riggs, Blair, & Greenberg, 2003), working memory
(Brocki & Bohlin, 2004), and inhibitory control (e.g., Rhoades, Greenberg, & Domitrovich,
2009). Our main study finding was that individual differences in EF at age 3 years
significantly mediated the relationship between mothers’ depressive symptoms at child age
2 years and children’s externalizing problems at age 6 years. To our knowledge, this is
the first study to test such mediation effects within a rigorous autoregressive
longitudinal design, whereby measures (all except child problem behaviors) were assessed
repeatedly at each of the three time-points. The prospective longitudinal design and the
selected time intervals add to the significance of findings; ages 2 and 3 are key periods
when children improve on their EF skills and acquire more advanced types of EF, whereas
age 6 follows the transition to school. Importantly, the current findings indicate that
the mediation role of EF is unlikely merely to reflect associations with other cognitive
abilities that underlie behavior adjustment such as verbal fluency. Verbal ability is
highly related to EF (e.g., Hughes & Ensor, 2007), and until recently tasks measuring
various EF components tended to be verbal in nature (e.g., the backward word span task,
tapping working memory) (Carlson, Moses, & Breton, 2002). It is noteworthy, therefore,
that verbal ability was not a mediator, probably because heightened maternal symptoms only
predicted marginally significantly lower verbal ability. Although conclusions are limited
by the inclusion of a single indicator of verbal fluency, this finding suggests that
different cognitive domains might not be equally important in the relation between
exposure to maternal depressive symptoms and problem behaviors and calls for future
studies of child mediators. Along the same lines, it is also important to note that child
EF did not mediate the relationship between general deprivation and problem behaviors.
Depressive symptoms occur more often in the context of deprivation (Stansfeld, Clark,
Rodgers, Caldwell, & Power, 2011), and previous studies have dealt with this convoluted
relationship by showing that maternal depression mediates the relationship between
deprivation and child problem behaviors (Rijlaarsdam et al., 2013) and that reduced
economic resources mediate the relationship between depressive symptoms and child behavior
(Turney, 2012). Alternatively, measures of deprivation and depressive symptoms have been
combined into a single measure of family risk (e.g., Halligan et al., 2013). Not
surprisingly, we found that greater deprivation at age 2 years predicted poorer EF at age
3 years and heightened externalizing problems at age 6 years. However, the indirect effect
was not significant; this null finding is important because it suggests that the mediatory
role of poor EF is specific to the effects of exposure to maternal depressive symptoms.
Establishing the specificity of risk factors implicated in an EF-mediated pathway to
problem behaviors is theoretically significant. In particular, a significant mediation
effect of EF in the relationship between exposure to deprivation and problem behaviors
would have been consistent with the suggestion that those variations in problem behaviors
that are due to impairments in EF are mostly created by inadequate levels of overall
stimulation and environmental inconsistency, supporting theoretical conceptualizations of
EF as a regulatory process dependent on “optimal” stimulation. In contrast, our findings
of a significant mediation effect of EF in the relationship between exposure to maternal
depressive symptoms and problem behaviors is consistent with the suggestion that
variations in problem behaviors due to impairments in EF might be caused by poor-quality
interpersonal relationships, supporting models of EF development through modeling of adult
behavior and observational learning (Hughes & Ensor, 2009b). Maternal depression has been
associated with impairments in mothers’ own EF skills (e.g., Barrett & Fleming, 2011;
Johnston, Mash, Miller, & Ninowski, 2012). Children are keen observers of adults’ everyday
behaviors (Dunn, 1993) and so may internalize problem-solving strategies that do not rely
on the use of high EF skills. For example, depressed mothers are less likely to use
planning in order to optimize repetitive tasks (Hughes & Ensor, 2009b), which might
translate into fewer opportunities for their children to observe and internalize such
strategies. In addition, depression is known to deplete emotional resources by activating
an oversensitized distress response system and reducing the threshold for what is
considered aversive (for a review, see Dix & Meunier, 2009). Both deficits in maternal EF
(Psychogiou & Parry, 2014) and deficits in emotion processing and emotion regulation (Dix
& Meunier, 2009) have been hypothesized as mechanisms through which depression translates
into low maternal cognitive flexibility. A reduced ability to respond contingently would
adversely affect parental scaffolding of children’s goal-directed activities, which has
been shown to predict EF development (Bernier, Carlson, & Whipple, 2010; Hughes & Ensor,
2009b; Schroeder & Kelley, 2010). Scaffolding also involves showing children how to solve
(a part of) the next step, which children immediately imitate, internalize, and then apply
to further steps in the process until the next stage of difficulty is achieved and the
scaffolding process is repeated. In other words, to a large extent, scaffolding can be
seen as a form of concentrated and focused observational learning. Future studies that
take a close look at how scaffolding unfolds in interactions between children and mothers
in the context of depression could greatly enhance our understanding of the processes that
relate exposure to maternal depressive symptoms and child EF development. Other factors
that might be expected to distort the mediation effect reported here include parenting and
maternal functioning. These have been omitted from the current study due to a focus on
child mediators. However, the inclusion of measures of parenting and the parent–child
relationship is unlikely to have altered the results because previous analyses of data
from this sample showed that including maternal positive control at ages 2 and 6 years did
not weaken the negative effects of mothers’ depressive symptoms at child age 2 on child EF
at age 6 (Hughes et al., 2013); likewise, there was no interaction between observed
mother–child mutuality (at both ages 2 and 6) and mothers’ depressive symptoms at age 2 as
predictors of child problem behaviors at age 6 (Ensor et al., 2012). Another important
environmental factor not included here is the father, an omission largely caused by the
absence of fathers in more deprived families (25% of the mothers were single parents at
study entry). A key strength of this study is the use of independent assessments for each
variable. Mothers’ depressive symptoms were self-reported, children’s EF abilities were
tested through age-appropriate experimental tasks, and children’s externalizing and
internalizing problems were reported by teachers. On the flipside, a limitation of this
study is the use of a single measurement method for each variable. For example, mothers’
self-reported depressive symptoms were not corroborated by clinical interviews. Children’s
EF abilities were measured by multiple measures, but each subcomponent (i.e., working
memory, inhibitory control, or attention shifting) was measured by a single task. This
said, all main constructs were factor analyzed and used either as latent variables or as
resulting factor scores in all analyses, thereby reducing measurement error. The small
sample size and the presence of relatively few mothers with depressive symptoms indicate
that results are preliminary in nature and warrant further validation with larger samples.
The current study has several implications for interventions aimed at reducing children’s
externalizing problems. Combined “two-generation” interventions aimed at improving both
mothers’ depressive symptoms and children’s externalizing problems are a potential avenue
given that improvements in maternal depressive symptoms have been associated with more
successful treatment of child externalizing problems (Van Loon, Granic, & Engels, 2011).
On the downside, such interventions might be more susceptible to failure if the component
aimed at reducing maternal depressive symptoms is not successful, as has been indicated by
research showing that heightened maternal depressive symptoms interfere with the positive
effects of interventions aimed at child adjustment (Beauchaine, Webster-Stratton, & Reid,
2005; Van Loon et al., 2011; but see Rishel et al., 2006, for null findings). From this
point of view, the current study’s implication that interventions that improve children’s
EF could help to reduce externalizing problems in children exposed to maternal depression
(as indicated by the significant longitudinal mediation effect) is particularly
noteworthy. Previous research has shown that children’s EF is improved by a variety of
interventions, some of which can easily be implemented in schools (for a review, see
Diamond & Lee, 2011). In addition, it may be possible to promote children’s EF through
interventions aimed at improving the home environment such as by reducing chaos (e.g.,
Evans, Gonnella, Marcynyszyn, Gentile, & Salpekar, 2005) and encouraging parents to limit
children’s exposure to fast-paced cartoons (Lillard & Peterson, 2011). In sum, despite the
omissions identified above, and within the limitations imposed by the study design, by
demonstrating that individual differences in child EF at age 3 years mediate the
relationship between exposure to maternal depressive symptoms at age 2 years and teacher
ratings of externalizing and internalizing problems at age 6 years, this study adds to our
understanding of the self-regulatory mechanisms through which exposure to maternal
depressive symptoms might translate into child problem behaviors. Moreover, our findings
provide a potential avenue in the quest for factors that may buffer young children from
the adverse effects of exposure to mothers’ depressive symptoms.


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<ART>Does interaction matter? Testing whether a confidence heuristic can replace interaction in collective decision-making
================================================================================

Authors: Dan Bang, Riccardo Fusaroli, Kristian Tylén, Karsten Olsen, Peter E. Latham, Jennifer Y.F. Lau, Andreas Roepstorff, Geraint Rees, Chris D. Frith, Bahador Bahrami
DOI: 10.1016/j.concog.2014.02.002
Year: 2014  |  Pages: 13-23
ASJC codes: 3204, 3205
Keywords: Collective decision-making, Computational, Confidence, Heuristic, Interaction, Metacognition, Perception, Reaction time, Signal detection theory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

In a range of contexts, individuals arrive at collective decisions by sharing confidence in their judgements. This tendency to evaluate the reliability of information by the confidence with which it is expressed has been termed the 'confidence heuristic'. We tested two ways of implementing the confidence heuristic in the context of a collective perceptual decision-making task: either directly, by opting for the judgement made with higher confidence, or indirectly, by opting for the faster judgement, exploiting an inverse correlation between confidence and reaction time. We found that the success of these heuristics depends on how similar individuals are in terms of the reliability of their judgements and, more importantly, that for dissimilar individuals such heuristics are dramatically inferior to interaction. Interaction allows individuals to alleviate, but not fully resolve, differences in the reliability of their judgements. We discuss the implications of these findings for models of confidence and collective decision-making. © 2014 The Authors.

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<h>INTRODUCTION</h>
------------

There is a growing interest in the mechanisms underlying the “two-heads-better-than-one”
(2HBT1) effect, which refers to the ability of dyads to make more accurate decisions than
either of their members (e.g., Hill, 1982). One study (Bahrami et al., 2010), using a
perceptual task in which two observers had to detect a visual target, showed that two
heads become better than one by sharing their ‘confidence’ (i.e., an internal estimate of
the probability of being correct), thus allowing them to identify who is more likely to be
correct in a given situation. Sharing of confidence as a strategy for combining individual
opinions into a group decision has also been established in non-perceptual domains (e.g.,
Sniezek & Henry, 1989). This tendency to evaluate the reliability of information by the
confidence with which it is expressed has been termed the ‘confidence heuristic’ (e.g.,
Thomas & McFadyen, 1995). A recent study has shown that a simple algorithm based on the
confidence heuristic – always opt for the opinion made with higher confidence – can yield
a 2HBT1 effect in the absence of any interaction between individuals (Koriat, 2012).
Intrigued by this finding, we tested whether this algorithm could in practice replace
interaction in collective decision-making. Importantly, such a formula for collective
choice – if effective – would not be susceptible to the egocentric biases that may impair
interaction (e.g., Gilovich, Savitsky, & Medvec, 1998), and could readily be used by
decision makers, such as jurors, medical doctors or financial investors, who have to
combine different opinions in limited time. Indeed, the implementation of heuristics
inspired by individual decision-making has proved very useful within professional contexts
(e.g., Gigerenzer, 2008).

<hs>  Circumventing interaction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Building on Bahrami et al.’s (2010) study, Koriat (2012) asked isolated observers to
estimate the degree of confidence in their perceptual decisions. Participants, all of whom
had received the same sequence of stimuli, were afterwards paired into virtual dyads so
that they matched each other in terms of their ‘reliability’ (i.e., the reliability of
their individual decisions about the visual target). To remove individual biases in
confidence, their confidence estimates were normalised, so that they shared the same mean
and standard deviation, before being submitted to the Maximum Confidence Slating (MCS)
algorithm, which selected the decision of the more confident member of the virtual dyad on
every trial. While circumventing interaction, the MCS algorithm yielded a robust 2HBT1
effect. Interestingly, isolated observers’ confidence estimates are negatively correlated
with their reaction times when responses are given in the absence of speed pressure (e.g.,
Patel, Fleming, & Kilner, 2012; Pleskac & Busemeyer, 2010; Vickers & Packer, 1982),
raising the possibility that a Minimum Reaction Time Slating (MRTS) algorithm may be
sufficient to yield a 2HBT1 effect. In this study, we tested the efficacy of the MCS and
MRTS algorithms without matching dyad members in terms of their reliability, and compared
the responses advised by the algorithms with those reached by the dyad members through
interaction (henceforth ‘dummy’ versus ‘empirical’ dyads/decisions). In particular, we
addressed three questions. First, does the success of the MCS and MRTS algorithms depend
on the similarity of dyad members’ reliabilities? Bahrami et al. (2010) found that the
success of interactively sharing confidence was a linear function of the similarity of
dyad members’ reliabilities. For similar dyad members, two heads were better than one.
However, for dissimilar dyad members, two heads were worse than the better one.
Interestingly, Bahrami et al. (2010) found that these discrepant patterns of collective
performance could be explained by a computational model in which confidence was defined as
a function of the reliability of the underlying perceptual decision. We predicted that the
efficacy of the MCS and the MRTS algorithms would also depend on the similarity of dyad
members’ reliabilities. Second, do the algorithms fare just as well as interacting dyad
members? People vary in their ability to estimate the reliability of their own decisions
(e.g., Fleming, Weil, Nagy, Dolan, & Rees, 2010; Song et al., 2011); this ability is
typically referred to as ‘metacognitive’ ability and, in social contexts, determines the
credibility of people’s confidence estimates. While the algorithms are prone to error when
people misestimate the reliability of their own decisions, interacting individuals may
take such misestimates into account (e.g., Tenney, MacCoun, Spellman, & Hastie, 2007). We
predicted that interacting dyad members would take into account the credibility of each
other’s confidence estimates when making their joint decisions, and that interaction would
be relatively more beneficial than the algorithms for dissimilar dyad members; they have
more to lose from following the more confident but less competent of the two. Third, what
is the effect of normalising confidence estimates before selecting the decision made with
higher confidence? Koriat (2012) reported that the MCS algorithm performed equally well
when using raw and normalised confidence estimates as its input. However, this analysis
was limited to (virtual) dyad members of nearly equal reliability. Even though people vary
in the ability to evaluate the reliability of their own decisions, confidence estimates
are rarely uninformative about underlying performance (e.g., Lau & Maniscalco, 2010). As a
consequence, normalising confidence estimates may remove statistical moments that reflect
actual differences in underlying performance (e.g. differences in average confidence due
to differences in average performance). We therefore predicted that submitting normalised
confidence estimates to the MCS algorithm would be relatively more costly for dissimilar
dyad members.

<hs>  Data and participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~

To test our predictions, we analysed data from an experiment (Bahrami et al., 2012a) in
which dyad members estimated their confidence in individual decisions on every trial, but
were also required to make a joint decision whenever their individual decisions
conflicted. We used data from two experimental conditions: a ‘non-verbal’ condition in
which dyad members made their joint decisions only having access to each other’s
confidence estimates, and a ‘verbal’ condition in which dyad members also had the
opportunity to verbally negotiate their joint decisions (the NV condition and the NV&V
condition in Bahrami et al., 2012a, 2012b). In total, fifty-eight participants (29 dyads)
took part in the non-verbal (14 dyads) and the verbal (15 dyads) conditions. All
participants were healthy adult males (mean age = 23.5 years, SD = 2.8 years) with normal
or corrected-to-normal vision. The members of each dyad knew each other before taking part
in the experiment. We describe the key experimental details below (see Bahrami et al.,
2012a, 2012b, for response, display and stimulus parameters).

<hs>  Experimental details</hs>
  ~~~~~~~~~~~~~~~~~~~~

Dyad members sat at right angles to each other in a dark room, each with their own screen
and response device. For each trial, dyad members viewed two brief intervals, on which six
contrast gratings were presented simultaneously around a central fixation point. In either
the first or the second interval, one of the six contrast gratings had a slightly higher
level of contrast. After the two viewing intervals, a horizontal line with a fixed
midpoint appeared on each dyad member’s screen. The left side of the midpoint represented
the first interval, the right side represented the second. An additional vertical
confidence marker was displayed on top of the midpoint. Each dyad member made his private
decision about which interval he thought contained the oddball target by moving the
confidence marker to the left (first interval) or to the right (second interval) of the
centre. The confidence marker could be moved along the line by up to five steps on either
side, each step indicating higher confidence. There was no response time limit. Next, the
dyad member’s private responses (decision and confidence) were shared. In the case of
agreement (i.e., if dyad members privately selected the same interval), they received
feedback and continued to the next trial. But in the case of disagreement, one of the two
dyad members was randomly prompted to make a joint decision on behalf of the dyad. In the
non-verbal condition, the nominated dyad member made the joint decision only having access
to the declared responses. In the verbal condition, the nominated dyad member also had the
opportunity to verbally negotiate the joint decision with his partner. Dyad members were
free to ignore each other’s confidence estimates at this stage of the experiment. After
one practice block of 16 trials, two experimental sessions were conducted. Each session
consisted of 8 blocks of 16 trials (128 trials in each session and 256 trials in total).
Within each session, one dyad member responded with the keyboard (colour-coded as blue)
and the other dyad member responded with the mouse (colour-coded as yellow). The dyad
member using the keyboard controlled the confidence marker by pressing the ‘n’ (move
left), the ‘m’ (move right), and the ‘b’ (submit response) buttons. The dyad member using
the mouse controlled the confidence marker by pressing the ‘left’ (move left), the ‘right’
(move right), and the ‘scroll’ (submit response) buttons. Dyad members switched places
(and hereby response device) at the end of the first session. See Fig. 1 for a schematic
of an experimental trial.

<hs>  Computing MCS responses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

We used Goodman & Kruskal’s gamma to test whether high (or low) confidence was associated
with correct (or incorrect) decisions. As expected, the gamma coefficients (mean = .16, SD
= .09) were significantly positive across dyad members, t(57) = 14.04, p < .001. For each
dyad, we then derived the joint decisions advised by the MCS algorithm. In line with
Koriat (2012), we first normalised the dyad members’ confidence estimates and then
selected the decision of the more confident dyad member on each trial; the normalised
confidence estimates, cnorm, were related to the raw confidence estimates, c, via cnorm =
(c − μc_dyad)/σc_dyad, where μc and σc were the mean and the standard deviation of the raw
confidence estimates pooled from both dyad members.

<hs>  Computing MRTS responses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Due to a programming error, the experimental code continued to sample the mouse response
time until both mouse and keyboard responses had been registered. This error meant that
mouse response times were either identical to keyboard response times (i.e., those trials
in which the dyad member using the mouse actually made a faster response than the dyad
member using the keyboard) or slower than keyboard response times (i.e., those trials in
which the dyad member using the mouse made a slower response than the dyad member using
the keyboard). Only including those trials in which dyad members responded with the
keyboard (i.e., the first 128 trials for dyad member A and the last 128 trials for dyad
member B – see Section 2.2), we regressed reaction times (milliseconds) against confidence
to test whether faster decisions were associated with higher confidence. As expected, the
unstandardised regression coefficients (mean b = −156.29) were significantly negative
across dyad members, t(57) = −5.13, p < .001. Including all trials, for each dyad, we
derived the joint decisions advised by the MRTS algorithm. As described above, we could
infer which dyad member made the faster decision on each trial. The programming error
meant that we could not test the effect of normalising reaction times.

<hs>  Computing sensitivity</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Psychometric functions were created for each dyad member and for the dyad (empirical or
dummy) by plotting the proportion of trials in which the target was reported to be in the
second interval against the contrast difference between the two intervals (i.e., the
contrast level in the second interval minus the contrast level in the first interval at
the target location). The steepness of the slope provides an estimate of sensitivity. More
sensitive observers were, by definition, more ‘reliable’ in their estimates of contrast.
See Fig. 2 for an example psychometric function. We computed the similarity of dyad
members’ reliabilities as the ratio of the sensitivity of the worse dyad member to that of
the better dyad member (Smin/Smax), with values near zero corresponding to dyad members
with very different reliabilities and values near one corresponding to dyad members of
nearly equal reliability. We computed the collective outcome of the dyad (empirical or
dummy) as the ratio of the sensitivity of the dyad (empirical or dummy) to that of the
more sensitive dyad member (Semp/Smax, SMCS/Smax, and SMRTS/Smax), with values below 1
indicating a collective loss and values above 1 indicating a collective benefit.

<hs>  Normalised versus raw confidence estimates</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To test the effect of normalising confidence estimates before selecting the decision made
with higher confidence, we also submitted raw confidence estimates to the MCS algorithm.
The trials in which dyad members reported the same level of confidence but selected
different intervals were resolved by randomly selecting the decision of one of the two
dyad members; we note that there were no such confidence ties when submitting normalised
confidence estimates to the MCS algorithm. To ensure that the random selection did not
favour one of the dyad members by chance, for each dyad, we generated one hundred dummy
dyads using raw confidence estimates and used their mean sensitivity (SrawMCS) to test the
effect of normalising confidence estimates (SMCS/SrawMCS). See table 1 for a summary of
the strategies for collective choice.

<h>RESULTS</h>
-------

As none of our interest measures showed significant differences between the non-verbal and
the verbal conditions, we only report results based on data collapsed across both
conditions. In addition, as none of these measures changed over time (i.e., from the first
to the second session of the experiment), we only reported data collapsed across both
experimental sessions.

<hs>  The efficacy of the algorithms</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The similarity of dyad members’ sensitivities (Smin/Smax) significantly predicted the
collective outcome of the MCS algorithm (SMCS/Smax), b = .68, t(27) = 5.17, p < .001, and
explained around 50% of the variance, R2 = 49.8, F1,28 = 26.74, p < .001 (see Fig. 4A).
For similar dyad members, the MCS algorithm yielded a collective benefit (SMCS/Smax > 1
when Smin/Smax > 0.6). However, for dissimilar dyad members, the MCS algorithm yielded a
collective loss (SMCS/Smax < 1 when Smin/Smax < 0.6). The similarity of dyad members’
sensitivities also significantly predicted the collective outcome of the MRTS algorithm
(SMRTS/Smax), b = .59, t(27) = 4.69, p < .001, and explained around 45% of the variance,
R2 = 44.9, F1,28 = 22.02, p < .001 (see Fig. 4B). However, the MRTS only yielded a
collective benefit for five dyads. The MCS algorithm was superior to the MRTS algorithm,
both when normalised confidence estimates, t(28) = 4.99, p < .001, and raw confidence
estimates, t(28) = 6.26, p < .001, were used as its input.

<hs>  The relative benefit of interaction over the algorithms</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To test whether interacting dyad members used the credibility of each other’s confidence
estimates to guide their joint decisions, we regressed the fraction of disagreement trials
in which the dyad eventually followed the decision of dyad member A instead of that of
dyad member B (the choice ratio) against the ratio of the AROC for dyad member A relative
to that of dyad member B (the AROC ratio). The AROC ratio significantly predicted the
choice ratio, b = .70, t(27) = 3.58, p < .001, and explained around 30% of the variance,
R2 = .32, F1,28 = 12.78, p < .001 (see Fig. 5). The similarity of dyad members’
sensitivities significantly predicted the performance of the empirical dyads relative to
that of the MCS algorithm (Semp/SMCS), b = −.43, t(27) = −4.21, p < .001, and explained
around 40% of the variance, R2 = .40, F1,28 = 17.73, p < .001 (see Fig. 6A). For similar
dyad members, there was no relative benefit for interaction over the MCS algorithm
(Semp/SMCS ≈ 1 when Smin/Smax > 0.8). However, for dissimilar dyad members, there was a
relative benefit for interaction over the MCS algorithm (Semp/SMCS > 1 when Smin/Smax <
0.8). The similarity of dyad members’ sensitivities also significantly predicted the
performance of the empirical dyads relative to that of the MRTS algorithm (Semp/SMCS), b =
−.651, t(27) = −2.20 p = .037, and explained around 15% of the variance, R2 = .15, F1,28 =
4.83, p = .037 (see Fig. 6B). However, the MRTS algorithm only (marginally) outperformed
two of the empirical dyads.

<hs>  The effect of normalising confidence estimates</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The similarity of dyad members’ sensitivities significantly predicted the effect of
normalising confidence estimates (SMCS/SrawMCS), b = .17, t(27) = 2.70, p = .012, and
explained around 20% of the variance, R2 = .21, F1,28 = 7.31, p = .012 (see Fig. 7). For
similar dyad members, there was a relative benefit for normalising confidence estimates
(SMCS/SrawMCS > 1 when Smin/Smax > 0.6). However, for dissimilar dyad members, there was a
relative cost to normalising confidence estimates (SMCS/SrawMCS < 1 when Smin/Smax < 0.6).
We note that this effect was relatively subtle (cf. change of scale on y-axis in Fig. 7),
and that the relative benefit of interaction over the MCS algorithm was not affected using
raw, instead of normalised confidence estimates, as input to the MCS algorithm.

<h>DISCUSSION</h>
----------

Sharing of confidence as a strategy for combining individual opinions into group decisions
has been established in a wide range of contexts. This tendency to evaluate the
reliability of information by the confidence with which it is expressed has been termed
the ‘confidence heuristic’. In this study, we tested two simple ways of implementing the
confidence heuristic in the context of a collective perceptual decision-making task: the
MCS algorithm, which opts for the decision made with higher confidence, and the MRTS
algorithm, which opts for the faster decision, exploiting a negative correlation between
confidence and reaction time. Our findings have important implications for the use of
heuristics for collective choice and for models of confidence and collective decision-
making.

<hs>  The efficacy of the MCS and the MRTS algorithms</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As expected, the MCS and the MRTS algorithms only yielded 2HBT1 effects for dyad members
of nearly equal reliability. However, despite a negative correlation between confidence
and reaction time, the MCS algorithm markedly outperformed the MRTS algorithm. The
superiority of the MCS algorithm to the MRTS algorithm could be due to differences in the
‘pre-processing’ of their input. While we could submit both normalised and raw confidence
estimates to the MCS algorithm, we could only submit raw reaction times to the MRTS
algorithm because of a programming error (see Section 3.2). Since individuals vary with
respect to their average response speed, pooling raw reaction times from two individuals
might corrupt the link between confidence and reaction time. However, the MCS algorithm
outperformed the MRTS algorithm even when raw confidence estimates were used as its input,
suggesting that reaction time may be a very noisy substitute for confidence. The sign of
the correlation between confidence and reaction time has been found to depend on response
demands, with a negative correlation in the absence of speed pressure and a positive
correlation under speed pressure (see Pleskac & Busemeyer, 2010, for a computational
account of this phenomenon). While no speed pressure was enforced in the current task,
dyad members may have paced their responses on a subset of trials, thus corrupting the
negative correlation between confidence and reaction time. We note that, outside the
context of the MCS and the MRTS algorithms, the normalisation of confidence estimates has
a more straightforward interpretation than the normalisation of reaction times. The
normalisation of confidence estimates is intended to remove biases in the use of a scale –
here, how an internal variable is mapped onto a confidence scale – and could potentially
capture important aspects of collective decision-making (see Section 5.3). It is less
clear how the normalisation of reaction times would translate into other contexts. Taken
together, our findings show that heuristics for collective choice are susceptible to
individual differences in reliability, and suggests that reaction time cannot be
substituted for confidence without incurring a considerable collective accuracy cost. In
this light, we will limit the remainder of the Discussion to the MCS algorithm.

<hs>  The relative benefit of interaction over the MCS algorithm</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If the assumptions of the WCS model were satisfied, the responses advised by the MCS
algorithm should be just as accurate as those reached by dyad members through interaction.
However, the ability to estimate the reliability of one’s own decisions (cf. the level of
noise in one’s perceptual system) shows substantial individual differences (e.g., Fleming
et al., 2010; Song et al., 2011); this ability is typically referred to as metacognitive
ability and quantified as metacognitive accuracy. While the MCS algorithm is prone to
error when people misestimate the reliability of their own decisions, interacting
individuals may take such misestimates into account. For example, one study has shown that
mock jurors find witnesses who are confident about erroneous testimony less credible than
witnesses who are not confident about it (Tenney et al., 2007). We predicted that
interacting dyad members would take into account the credibility of each other’s
confidence estimates when making their joint decisions, and that interaction would be
relatively more beneficial than the algorithms for dissimilar dyad members, because they
have more to lose from following the more confident but less competent of the two. As for
the first prediction, the fraction of disagreement trials in which the dyad followed dyad
member A instead of dyad member B depended on their relative metacognitive accuracy (here
measured as AROC – see Section 3.4), indicating that dyad members used the credibility of
each other’s confidence estimates to guide their joint decisions (see Fig. 5). As for the
second prediction, interaction was more robust than the MCS algorithm to differences in
reliability. For similar dyad members, the decisions reached through interaction were no
more accurate than those advised by the MCS algorithm. However, for dissimilar dyad
members, the decisions reached through interaction were considerably more accurate than
those advised by the MCS algorithm; this was true irrespective of whether normalised or
raw confidence estimates were submitted to the MCS algorithm. While models of collective
decision-making have identified the ‘arbitration’ of confidence estimates as key to
collective performance (e.g., Bahrami et al., 2010; Koriat, 2012), our findings suggests
that the ‘weighting’ of confidence estimates is equally important for collective
performance. Without taking the credibility of confidence estimates into account, the MCS
algorithm cannot fully replace interaction in collective decision-making. Our study
highlights the social heterogeneity of credibility as an interesting avenue for
computational research: how do we estimate the credibility of each other’s opinions, and
how good are we at doing so? We note that the relative benefit of interaction over the MCS
algorithm need not necessarily result from dyad members discounting the opinion of the
dyad member with lower metacognitive accuracy. More specifically, while dyad members may
assign less weight to the opinion of the more confident but less competent member (“bad
but doesn’t know it”), they may also assign more weight to the opinion of the less
confident but more competent dyad member (“good but does know it”). We believe that
computational models of social learning (e.g., Behrens, Hunt, Woolrich, & Rushworth, 2008)
are needed to tease apart such decision strategies.

        <hss>Role of feedback</hss>

        All participants received feedback about the accuracy of each decision, and could
        thus directly evaluate the credibility of each other’s confidence estimates.
        Indeed, previous research has shown that diagnostic feedback helps groups of
        individuals to identify their more accurate members (Henry, Strickland, Yorges, &
        Ladd, 1996). The relative benefit of interaction over the MCS algorithm might
        therefore not persist in the absence of diagnostic feedback. However, using the
        same visual perceptual task, Bahrami et al. (2012b) found that diagnostic feedback
        was not necessary for the accumulation of a 2HBT1 effect – diagnostic feedback
        only appeared to accelerate the process – indicating that individuals may rely on
        other signals when they learn the credibility of each other’s confidence
        estimates. The identification and incorporation of these signals will pose a major
        challenge for dynamic models of collective decision-making.

        <hss>Role of familiarity</hss>

        Here, for each dyad, one participant was recruited, and then asked to bring along
        a friend to the study. Dyad members might thus have used their interpersonal
        history to establish the credibility of each other’s confidence estimates.
        However, using a similar task, but in the domain of approximate numeration,
        Bahrami, Didino, Frith, Butterworth, and Rees (2013) found that familiarity had
        little impact on collective performance, suggesting the dyad members evaluated the
        credibility of each other’s confidence estimates in the context of their current
        task performance. While there is no evidence for a main effect of familiarity on
        collective performance, it may be the case that familiarity matters more for
        dissimilar than similar dyad members.

        <hss>Non-perceptual domains</hss>

        Research has shown that individuals are ‘overconfident’ about the accuracy of
        their knowledge-based judgements but ‘underconfident’ about the accuracy of their
        perceptual judgements (see Harvey, 1997, for a review). These discrepant patterns
        of confidence have led to the hypothesis that different types of information
        determine confidence in knowledge and perception. For example, Juslin and Olsson
        (1997) propose a model of confidence in which perceptual judgements are dominated
        by ‘Thurstonian’ uncertainty, internal noise such as stochastic variance in the
        sensory systems, whereas knowledge-based judgments are dominated by ‘Brunswikian’
        uncertainty, external noise such as less-than-perfect correlations between
        features in the environment. This dissociation raises issues as to whether
        confidence can be used as a proxy for the reliability of decisions in non-
        perceptual domains. However, direct comparison of knowledge-based and perceptual
        judgements has found evidence for a common basis of confidence (e.g., Baranski &
        Petrusic, 1994; Pallier et al., 2002), suggesting that the efficacy of the MCS
        algorithm will generalise to non-perceptual domains (but see Koriat, 2012, for
        exceptional environments).

<h>FUNDING</h>
-------

This work was supported by the Calleva Research Centre for Evolution and Human Sciences
(DB, JYFL), the European Research Council Starting Grant NeuroCoDec 309865 (BB), the
Danish Council for Independent Research – Humanities (KT, RF), the EU-ESF program Digging
the Roots of Understanding DRUST(KT, RF), the European UnionMindBridge Project (DB, KO,
AR, CDF, BB), the Gatsby Charitable Foundation (PEL), and the Wellcome Trust (GR).


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<ART>Effect of variation in noise absorption in open-plan office: A field study with a cross-over design
================================================================================

Authors: Aram Seddigh, Erik Berntson, Fredrik Jönsson, Christina Bodin Danielson, Hugo Westerlund
DOI: 10.1016/j.jenvp.2015.08.004
Year: 2015  |  Pages: 34-44
ASJC codes: 3202, 3207
Keywords: Distraction, Health, Noise, Office type, Open-plan offices, Performance

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Noise has repeatedly been shown to be one of the most recurrent reasons for complaints in open-plan office environments. The aim of the present study was to investigate if enhanced or worsened sound absorption in open-plan offices is reflected in the employees' ratings of disturbances, cognitive stress, and professional efficacy. Employees working on two different floors of an office building were followed as three manipulations were made in room acoustics on each of the two floors by means of less or more absorbing tiles & wall absorbents. For one of the floors, the manipulations were from better to worse to better acoustical conditions, while for the other the manipulations were worse to better to worse. The acoustical effects of these manipulations were assessed according to the new ISO-standard (ISO-3382-3, 2012) for open-plan rooms acoustics. In addition, the employees responded to questionnaires after each change. Our analyses showed that within each floor enhanced acoustical conditions were associated with lower perceived disturbances and cognitive stress. There were no effects on professional efficiency. The results furthermore suggest that even a small deterioration in acoustical room properties measured according to the new ISO-standard for open-plan office acoustics has a negative impact on self-rated health and disturbances. This study supports previous studies demonstrating the importance of acoustics in work environments and shows that the measures suggested in the new ISO-standard can be used to adequately differentiate between better and worse room acoustics in open plan offices.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In relation to other ambient factors, the impact of unwanted sound or noise is probably
the most studied when it comes to office environments (Boyce, 1974; De Croon, Sluiter,
Kuijer, & Frings-Dresen, 2005; Leather, Beale, & Sullivan, 2003; Leder, Newsham, Veitch,
Mancini, & Charles, 2015; Navai & Veitch, 2003; Nemecek & Grandjean, 1973; Pejtersen,
Allermann, Kristensen, & Poulsen, 2006; Sundstrom, Burt, & Kamp, 1980; Sundstrom, Town,
Rice, Osborn, & Brill, 1994; Veitch, Charles, Farley, & Newsham, 2007; Veitch, Farley, &
Newsham, 2002; Warnock, 2004). Noise has been suggested to cause interruption, irritation
and lowered performance among employees (Roelofsen, 2008), and is one of the most common
reasons for complaints in open-plan office environments (Kaarlela-Tuomaala, Helenius,
Keskinen, & Hongisto, 2009). However, this study addresses something that is less known
about noise, namely, how better or worse acoustical conditions in open-plan offices affect
employees' perception of disturbances, cognitive stress, and professional efficacy. Why
noise is a common reason for complaints can be explained by the changing state hypothesis
(Jones, Madden, & Miles, 1992), which suggests that sounds varying over time cause more
disruptions. A sound that is constant in intensity or timbre should therefore cause fewer
disturbances than sounds that constantly change their characteristics. A more uniform
sound source can be created by filtering out high frequency sound, so called low-pass
filtering (Jones, Alford, Macken, Banbury, & Tremblay, 2000) or by introducing new sources
of sound, which either can be competing voices (babble-effect) or speech neutral masking
noises, e.g. from ventilation (Loewen & Suedfeld, 1992). Increasing the number of sounds
beyond a critical level causes the overall degree of variability in sound to drop, hence
the overall result is a more even sound level where peaks and troughs from individual
sound sources are cancelled out (Perham, Banbury, & Jones, 2007). The degree of
variability might also be expected to drop when reverberation time increases. For example,
Beaman and Holt (2007) found that a reverberation time, i.e. the time it takes for sound
to attenuate, of 5 s led to the same low amount of error in conducting an immediate recall
test as in the quiet control condition. However, in an office environment the
reverberation time seldom approaches 5 s but varies in lower ranges (between 0.4 and 1 s).
Perham et al. (2007) investigated if more realistic differences in reverberation time can
affect performance on a cognitive test measuring serial recall. They compared one quiet
condition with two different noisy conditions. The two noisy conditions were comprised of
noise from various sources in an office recorded in a room with a reverberation time of
either 0.7 or 0.9 s. The respondents conducted the test while listening to the noises
through headphones. Although they found an effect on performance between the quiet
condition, where no noise was played, and the two noisy conditions, performance on the
test did not differ between the two noisy conditions. Further analyses revealed that
speech intelligibility did not differ between the two noisy conditions, and the authors
concluded that “at least for typical office reverberation times, lower reverberation times
do not increase intelligibility” (Perham et al., 2007, p. 843). It has also been found
that different noise types, for example speech, music, and office noise in general, in
comparison with quiet conditions, negatively impact different cognitive outcomes, such as
memory performance, reading comprehension, and proofreading (see Hongisto, 2005 for an
overview). Noise has also been extensively studied in field studies. Ringing telephones,
air conditioning, and office machinery have all been suggested to cause disturbances in
office environments. Human speech (Boyce, 1974; Pierrette, Parizet, Chevret, & Chatillon,
2014; Sundstrom et al., 1994) and its intelligibility is another common distracting
factor. It is measured by the Speech Transmission Index (STI), which ranges from 0,
meaning that the speech is not understandable, to 1, meaning that the speech is fully
comprehendible. When STI exceeds 0.2 it begins to cause a decrease in performance with the
highest decrement occurring around 0.6 (Hongisto, 2005). Furthermore, field studies also
show that distractions and noise are present also in cell offices (Seddigh et al., 2015),
even if open-plan office environments usually are associated with more noise and
distractions (Kaarlela-Tuomaala et al., 2009; Seddigh, Berntson, Bodin Danielson, &
Westerlund, 2014). Consequently, it would be more relevant to investigate the impact of
different sound intensities or certain aspects of noise rather than comparing its presence
with absence. In addition, another study by Pierrette et al. (2014) could not find any
association between the A-weighted sound pressure level dBA (LeqA) and the perception of
noise in the office as high or annoying. The authors emphasised the relevance of measuring
behavioural outcomes to appraise the appropriateness of the noise in open-plan office
environment instead of relying overly much on objective acoustical measures. This
conclusion corresponds well with the definition of noise not as the particular type or
magnitude of the sound, but rather as the perception of the sound by the listener, i.e. to
what extent the sound is experienced as noise (Roelofsen, 2008). Additionally, knowledge
workers – that is workers who create, develop, manipulate, disseminate or use knowledge to
provide an outcome – depend to high degree upon processing information (Bosch-Sijtsema,
Ruohomäki, & Vartiainen, 2010; Janz, Colquitt, & NOE, 1997). According to the Load theory
of selective attention and cognitive control (Lavie, Hirst, de Fockert, & Viding, 2004)
unwanted stimuli such as noise need to be first processed and then actively inhibited in
order to not distract the person who is exposed to noise. Therefore, for knowledge workers
noise competes for the same cognitive capacities that process task related information
(see also Diamond, 2013; Seddigh et al., 2014). Hence, lower in comparison to higher noise
levels in office environments should lead to fewer problems for knowledge workers.
Furthermore, another relevant theory concerning supportive design (Ulrich, 1991) suggest
that while certain physical characteristics may not affect employees negatively per se,
they may intensify the negative impact of some other factor in the environment (Evans,
2001). Leather et al. (2003) found such effect and reported that high noise together with
high job strain, in contrast to low job strain, was associated with lower job
satisfaction, lower organisational commitment and increased rate of symptoms of infectious
diseases. Low noise regardless of the level of job strain did not have a large effect on
these measures. A comparable suggestion to the interaction of noise level and job strain
can be made for the joint effect of open-plan office environments and noise levels. That
is, even if the open-plan office environments per se do not affect employee health and
performance, bad acoustical conditions in these environments might. It is important to
investigate the total acoustical condition in the office rather than focussing on any
single aspect that may affect the acoustical condition. Namely even if wall panels can
affect the acoustical condition in an office environment, in research settings it is
important to focus on the actual acoustical condition in the office instead of the
presence or absence of panels per se. In fact in a recent study Leder et al. (2015) found
that larger workstations in open-plan offices were associated with greater satisfaction
with privacy, however the degree of enclosure of the workstation by partial-height
partitions was not associated with the same outcome measure. Furthermore, in order to more
thoroughly understand the impact of noise on office workers health and performance,
different types of measures should be used. Except behavioural outcomes, we believe that a
more comprehensive mapping of the objective sound environment, rather than too much
reliance on a single sound measure, could give a more extensive understanding of how
objectively measured sound is associated with the perception of noise. This idea is in
fact raised in the International Standard of room acoustic parameters (ISO-3382-3, 2012),
which suggests that rather than relying too much on single measures, such as reverberation
time, a combination of measures including STI and background noise levels should be
focused on in order to receive a more complete evaluation. Hence, the purpose of the
present study is to test the effect of different acoustical environments on employee
ratings on indicators of disturbances, health, and performance. This is done by a
crossover design that compares two different types of sound absorbents installed in
contrasting sequences on two similar floors within the same office building. In order to
obtain a comprehensive understanding of the room acoustics, we collected objective
acoustical data in accordance with the international standard regarding room acoustics
parameters (ISO-3382-3, 2012). We also collected behavioural measures, in order to
understand how the acoustical environment impacts on the employees.

<hs>  Aims and hypotheses</hs>
  ~~~~~~~~~~~~~~~~~~~

In this study the aim was to investigate if enhanced or worsened room acoustic
characteristics in open-plan office environments are reflected in changes in the
employees' own perception of disturbances, health and/or performance. The manipulation
consisted of different acoustic elements in the office building, where one condition
enhanced the acoustic environment (better condition) and one worsened the acoustic
environment (worse condition) as compared with a baseline condition. Disturbances are
examined from three different perspectives. Firstly, a broad measure of disturbances was
used in order to understand the impact of our manipulation of the environment on
disturbances in general. The second and third measure of disturbances focused on
disturbances from sounds from nearby and distant sources, respectively. Apart from the
self-rated measures, we also used objective acoustical measures. The respondents'
perception of the environment is followed over three time-points (T1, T2, and T3). Our
overall hypothesis was that the acoustical conditions would have an impact on the
respondents' experiences regarding the outcome variables, that is within each floor: the
better condition is associated with lower disturbances in general, the better condition is
associated with lower nearby disturbances, the better condition is associated with lower
distant disturbances, the better condition is associated with lower cognitive stress, the
better condition is associated with higher professional efficiency.

<hs>  Participating organization and employees</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Two months before the study started the organisation had moved from an old office building
with mostly private office rooms to a new renovated building with 6 floors, which was
where this study was conducted. Two out of the six floors were used for the study (floors
4 and 5) as they had identical layouts, were similarly furnished, and the employees on
these floors had similar work assignments. Each floor was highly open, with limited or no
partitions, carpeted and with ceilings furbished with highly sound absorbent tiles. Each
employee had his/her own designated desk. The sample consisted of 151 employees in a
municipality office outside of Stockholm, Sweden. The improvements in acoustics were
partly made through installation of wall absorbents. However, the wall absorbers had not
been aired before they were set up and during the initial days three employees felt
irritation in the form of smell and headaches. These three employees were excluded from
the analyses. A number of randomly selected employees were asked if they had noticed any
smell or symptoms, but no one else had. During data collection a fourth employee received
a screen that would protect against glare. Because her acoustic environment may have
changed due to the screen she was also excluded from the analyses. Further, two employees
on the managerial level had been informed about the design of the study and were also
excluded. After exclusion of these individuals the sample size consisted of 145 persons.
77% (n = 117) of the total sample completed the baseline survey in its entirety (T0), 70%
(n = 106) the first survey (T1), 62% (n = 94) the second (T2), and 64% (n = 97) the third
(T3). In total around 40 individuals had a full set of data for T1, T2 and T3.

<hs>  Study design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

This study employed a crossover design in an office environment to investigate if enhanced
and worsened acoustical environment impact employees' perception of disturbances, self-
rated health and performance. Before data was collected the employees were invited to a
meeting where they were informed about the purpose and procedure of the study. They were
told that four electronic surveys would be sent out and that during the total time of the
study, we might change the acoustics of the office several times. They were also told that
at the end of the study they would be given full information about the results of the
study and what changes we had made. The baseline survey was collected just before any
manipulations were made to the office environment. Each manipulation resulted in one of
two conditions: In the better condition, sound absorbing wall panels were set up and the
pre-existing, highly sound absorbent ceiling tiles were kept. In the so called worse
condition, there were no sound absorbing wall panels and highly sound reflective ceiling
tiles were installed, replacing 55% of the original highly absorbent tiles. Both types of
tiles had similar colour and form and could not easily be distinguished from each other
(See Zalyaletdinov, 2014 for the full acoustical report). During the weekend after the
baseline survey (T0) had been collected, changes were made on floor 4 to create the better
condition, and on floor 5 to create the worse condition. Two weeks after the first
manipulations had been made the first survey was sent out. The surveys were always sent
out on Mondays. During the weekend after, floor 4 was changed to create the worse
condition and vice versa. After two weeks of exposure to the new conditions, the second
survey was sent out. The three weeks following after the second survey contained many
national holidays. In order to ensure that most employees had been exposed to the sound
environment for two full weeks, the third survey were sent out six weeks after the second
survey had been completed (see Fig. 1).

<hs>  Survey measures</hs>
  ~~~~~~~~~~~~~~~

All respondent data was collected by means of an electronic survey. Disruption in general
was measured by four items. The questions were “To what extent have you in the past seven
days been disturbed by ventilation sounds”; “… by sounds from computers”; “… by ringing
phones”; and “… by colleagues' phone calls”. All questions concerning disruptions were
measured by using a five-point rating scale (1 = “to a small extent”, 5 = “to great
extent”). Cronbach's α for internal reliability from the first survey was 0.71, indicating
satisfactory consistency. Nearby disturbances were measured by the question “To what
extent have you in the past seven days been disturbed by speech and laughter from
colleagues sitting near you (within a radius of 10 m)”. Distant disturbances were measured
by the question “To what extent have you in the past seven days been disturbed by speech
and laughter from colleagues who sit further away (beyond a radius of 10 m)”. Cognitive
stress was measured by the cognitive stress scale (4 items) from the Swedish version of
the Copenhagen Psychosocial Questionnaire (COPSOQ) (Kristensen, Hannerz, Høgh, & Borg,
2005). Sample question: How much of the time during the past week have you found it
difficult to think clearly? All items were scored on a 5-point rating scale (1 = never, 5
= always). Cronbach's α for internal reliability from the first survey was 0.88,
indicating satisfactory consistency. The professional efficacy subscale (6 items) of the
Swedish version of the Maslach Burnout Inventory – General Survey (MBI-GS) was used to
assess self-rated performance (Schutte, Toppinen, Kalimo, & Schaufeli, 2000). All items
were scored on a 7-point rating scale (ranging from 1 = never, 7 = daily). Cronbach's α
for internal reliability from the first survey was 0.85, indicating satisfactory
consistency. See Table 1 for a correlation matrix between the dependent variables at T0.
The covariates included in the model were age (continuous: ranging from 21 to 69), gender
(0 = male, 1 = female), and educational level (dichotomized: 0 = low for those without an
academic degree, 1 = high for those with an academic degree; see Tables 2a and 2b).

<hs>  Acoustic measurements</hs>
  ~~~~~~~~~~~~~~~~~~~~~

We included several acoustical measures in accordance with ISO 3382-3 guidelines
(ISO-3382-3, 2012). These are D2,s, Lp,A,S,4 m, and radius of comfort (rc). D2,s is a rate
of spatial decay of A-weighted sound pressure level of speech per distance doubling. D2,s
is therefore a measure of how fast the decibel level has been attenuated at a certain
point from the sound source. Lp,A,S,4 m is a nominal A-weighted sound pressure level of
normal speech at a distance of 4.0 m from the sound source. In other words Lp,A,S,4 m
shows how much normal speech sound has been attenuated at a distance of 4 m from the sound
source. Radius of comfort (rc) is the distance from the sound source where the sound
pressure level of speech meets 48 dBA, which is the targeted value of Lp,A,S,4 m according
to (ISO-3382-3, 2012). The radius of comfort formula was suggested at EuroNoise 2012 with
background from the field study report made by Nordic Innovation (Hellström & Nilsson,
2010). The formula for calculating rc is rc = 4 × 100.3(Lp,A,S,4m−Lc)/D2,s. These
measurements were carried out for each condition in furnished rooms without staff along
four measurement paths, two paths on each floor (please see Appendix for a more detailed
description of the objective measurements). In addition, dBA levels were recorded from
four points by two microphones on each floor. Point 1 and 2 on floor 5 and point 3 and 4
on floor 4. These microphones registered the equivalent dBA for every 30 min interval from
06.30 until 18.00 h. Our intention was to register dBA levels for the total period,
however, technical difficulties prohibited us from collecting data at point 1 during the
first period and at point 2 during the third period. The length of the data collection for
the dBA levels were 11 days for the first period, 4 complete days for the second period,
and 15 days for the third period. Weekends were not included in the analysis. At each
point for each period, an equivalent dBA was calculated for every past half an hour
starting from the first registration at 7 AM to the last at 6 PM. All objective acoustical
data were gathered in order to confirm that the manipulations we had made to the physical
environment had led to two distinguishable acoustical conditions on each floor. The
acoustic conditions for each path were the same for T1 and T3, hence the objective
measures concerning D2,s, Lp,A,S,4 m, and rc measured at T1 were assumed being the same at
T3.

<hs>  Data analyses</hs>
  ~~~~~~~~~~~~~

39 employees had at one or several time points worked in the open-plan office environment
less than 15 h the latest 7 weekdays before answering the survey. The answers of these
employees at the specific time point(s) were removed. That is, if an employee had worked
less than 15 h the latest 7 days before answering the survey at T1 and T3 but more than 15
h the latest 7 days before answering the survey at T2, the responses at T1 and T3 were
removed while the responses at T2 were kept. First, five 3 × 2 repeated ANCOVA analyses
were carried out for each of the five outcome variables for T1, T2, and T3 in order to
test if the different order of the better versus worse conditions generated a different
development of the outcome measures over time. By investigating if the quadratic function
of time and floor was significant, the repeated ANCOVAs test if the repeated manipulations
to the different floors affected the outcome measures in the supposed direction. That is,
the exposure for each floor either went from better to worse to better (floor 4), or from
worse to better to worse (floor 5) which was hypothesised to yield approximately
symmetrically different U-shape curves of the outcome variables for the two floors that
significantly differed in their direction. Employees on floor 4 should rate Disruption in
general, Nearby disturbances, Distant disturbances, and Cognitive stress as low (in the
better condition) – high (worse condition) – low (better condition) creating a ∩-shaped
pattern, while employees on floor 5 should rate the same outcomes as high (worse
condition) – low (better condition) – high (worse condition) creating a U-shaped pattern.
For professional efficiency employees on floor 4 should rate as high (better condition) –
low (worse condition) – high (better condition) creating a U-shaped pattern, while
employees on floor 5 should rate professional efficiency as low (worse condition) – high
(better condition) – low (worse condition) creating a ∩-shaped pattern. A significant
quadratic function of time and floor would mean that the better and worse conditions
affected the employees according to intentions, which will allows us to conduct further
analyses to test if the manipulations between the better and the worse conditions differed
meaningfully within each floor. Second, on floor 4 and 5 separate repeated ANCOVAs were
carried out. For floor 4 these tested if the first better condition (T1) significantly
differed from the worse condition (T2) (the first contrast analysis) and if the second
better condition (T3) significantly differed from the worse condition (T2) (the second
contrast analysis). For floor 5 these tested if the better condition (T2) differed
significantly from the first worse condition (T1) (the third contrast analysis), and if
the better condition (T2) differed significantly from the second worse condition (T3) (the
fourth contrast analysis). These additional analyses were carried out only for the
outcomes that were significant in the first set of analyses investigating the quadratic
interaction effect of time and floor on the outcomes. The analyses were conducted in SPSS
version 21 by means of the General Linear Model. Sex, age, and educational level were
included as covariates. The repeated ANCOVA analyses rely on non-missing-data for each
respondent for T1–T3. Hence, for each ANCOVA analyses missing answers at T1, T2 and/or T3
for each outcome variable lead to case-wise deletion.

<h>RESULTS</h>
-------

The difference between the better and the worse acoustical condition for the active parts
of the working days and for each floor are shown in Fig. 2, which illustrates that in
general throughout the days during data collection, both floors had a lower dBA level
during the better condition in comparison to the worse. Floor 5 had a larger variation
than floor 4. The figure also shows a trend that the dBA levels seem to increase from
morning to the late afternoon. For the other objective measures please see Table 3.
According to expectations, and as shown in Table 3, the condition with both absorbing
tiles and wall absorbents, absorbed noise better than the condition with reflective tiles
and no wall absorbents according to the latest ISO standard.

<hs>  Disruption in general</hs>
  ~~~~~~~~~~~~~~~~~~~~~

According to Wilks' criterion there were no significant main effects of time or floor. The
interaction effects between time and the covariates were not significant. The time and
floor interaction was significant for the hypothesised quadratic function (F[1, 38] =
7.29, p = 0.01, partial η 2 = 0.16). The manipulations on each floor yielded symmetrically
different U-shaped curves for disruption in general which suggested lower disturbances in
the better conditions in comparison to the worse. Contrast analyses comparing the
conditions within each floor where carried out to test the first hypothesis. On floor 4
the change from the better (T1) to the worse (T2) condition was significant while the
change from the worse (T2) to the better (T3) condition was not. On floor 5 the change
between the worse (T1) to the better (T2) condition was not significant but the change
between the better condition (T2) to the worse (T3) was significant (all p < 0.05; please
see Fig. 3a). To conclude, the first hypothesis was supported in that the better
acoustical condition is related to less reported disturbances in general.

<hs>  Nearby disturbances</hs>
  ~~~~~~~~~~~~~~~~~~~

With the use of Wilks' criterion there was no significant main effect of time or floor.
The interaction effects between time and the covariates were not significant. The time and
floor interaction was significant between time and floor for the hypothesised quadratic
function (F[1, 40] = 16.69, p < 0.001, partial η 2 = 0.29). The manipulations on each
floor yielded symmetrically different U-shaped curves for nearby disturbances, which
suggested lower disturbances in the better conditions in comparison to the worse. Contrast
analyses comparing the conditions within each floor showed that on floor 4 the change from
the better (T1) to the worse (T2) condition was significant while the change from the
worse (T2) to the better (T3) condition was not. On floor 5 the change between the worse
(T1) to the better (T2) condition was significant which also was the change between the
better condition (T2) to the worse (T3) (all p < 0.05; please see Fig. 3b). To conclude
the second hypothesis was supported in that the better acoustical condition is related to
lower reported nearby disturbances.

<hs>  Distant disturbances</hs>
  ~~~~~~~~~~~~~~~~~~~~

With the use of Wilks' criterion there was no significant main effect of time or floor.
The interaction effects between time and the covariates were not significant. The time and
floor interaction was significant between time and floor for the hypothesised quadratic
function (F[1, 40] = 5.42, p = 0.025, partial η 2 = 0.12). The manipulations on each floor
yielded symmetrically different U-shaped curves for distant disruption suggested lower
disturbances in the better conditions in comparison to the worse. Contrast analyses
comparing the conditions within each floor where carried out to test the first hypothesis.
On floor 4 neither the change from the better (T1) to the worse (T2) condition nor the
change from the worse (T2) to the better (T3) condition was significant. On floor 5 the
change between the worse (T1) to the better (T2) condition was not significant but the
change between the better condition (T2) to the worse (T3) was significant (all p < 0.05;
please see Fig. 3c). To conclude, the third hypothesis was supported in that the better
acoustical condition is related to less reported disturbances from distant sources.

<hs>  Cognitive stress</hs>
  ~~~~~~~~~~~~~~~~

With the use of Wilks' criterion there was no significant main effect of floor. However,
the main effect of time was significant (F[2, 36] = 3.48, p = 0.042, partial η 2 = 0.16).
The interaction effect between time and covariates were not significant. The time and
floor interaction was significant between time and floor for the hypothesised quadratic
function (F[1, 37] = 7.59 p = 0.009, partial η 2 = 0.17). The manipulations on each floor
yielded symmetrically different U-shaped curves for cognitive stress, which suggested
lower stress in the better conditions in comparison to the worse. Contrast analyses
comparing the conditions within each floor where carried out to test the fourth
hypothesis. On floor 4 neither the change from the better (T1) to the worse (T2) condition
nor the change from the worse (T2) to the better (T3) condition were significant. On the
other hand on floor 5 both the change between the worse (T1) to the better (T2) condition
and the change between the better condition (T2) to the worse were significant (all p <
0.05; please see Fig. 3d). To conclude, the fourth hypothesis was supported in that the
better acoustical condition is related to less cognitive stress.

<hs>  Professional efficiency</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

With the use of Wilks' criterion there was no significant main effects of floor or time.
The interaction effects between time and the covariates were not significant. Further, the
hypothesized quadratic function between time and floor was not significant (see Fig. 3e),
meaning that the employees on each floor did not report significantly higher or lower
efficiency depending on the different conditions. Given that the overall quadratic
function of time and floor was not significant, no further analyses within each floor were
carried out. Therefore the fifth hypothesis could not be supported (see Fig. 3e).

<h>DISCUSSION</h>
----------

This study investigated if better and worse acoustic environments, created by less or more
absorbing tiles and wall absorbents, affect employees' perception of disturbances,
cognitive stress, and professional efficacy. In line with our expectations, the acoustical
measures showed a lower overall noise level during the working day and also lower D2,s,
Lp,A,S,4 m, and rc in conditions where tiles and wall panels that absorbed more sound
energy had been installed. In addition, also supporting our expectations, the acoustical
measures showed a higher overall noise level during the working day and higher D2,s,
Lp,A,S,4 m, and rc in conditions where the more reflective tiles where installed and wall
panels removed. Our results are in line with previous studies (Kaarlela-Tuomaala et al.,
2009) and suggest that employees' perception of disturbances and health are affected
negatively when exposed to increased noise levels. However, in contrast to previous
research findings (Perham et al., 2007; Pierrette et al., 2014), the results from the
present study showed that improved room acoustics was associated not only to lower
objective noise levels, but also to lower perceived disturbances and lower cognitive
stress. Consequently, the results imply that employees perceived better possibilities to
make decisions, concentrate, and reported having lower amount of memory loss. These
findings may be explained by that decreased general noise level in the office environment
decrease the interference of noise on higher cognitive functions, which are important for
knowledge workers ability to carry out their tasks (Diamond, 2013; Lavie et al., 2004;
Seddigh et al., 2014, 2015). These findings can also be related to the findings of Leather
et al. (2003) who reported that high noise levels in contrast to low noise levels interact
with job strain and impact employees' job satisfaction, organisational commitment and
symptoms of infectious diseases. Hence, the acoustical condition of the open-plan office
seems to have a direct relationship to indicators of both health and performance of
employees. Interestingly, these effects were evident despite the short exposure time to
the new condition, suggesting that the effect of a change in room acoustics is quite
immediate. However, the short exposure time might also explain why not all contrast
analyses where significant, even if the effects went in the expected direction (i.e.
better acoustics leading to less problems, for our measures of disturbances and health).
As evident in Fig. 1, the manipulations between the two conditions had a larger impact on
floor 5 in forms of differences in dBA-levels. Although the employees on both floors had
similar tasks, one possible explanation to these differences was revealed during the
feedback session to the employees. Employees on floor 5 had more conversations and
meetings around their desks and in the open space compared to employees on floor 4 who
either did not have as many meetings or conducted the meetings in separate meeting rooms.
Therefore, the acoustical differences between the two acoustical conditions likely had
greater consequence for floor 5 than for floor 4, as Fig. 1 illustrates. In fact it is
possible to discern a similar pattern in employees' rating by looking at Fig. 3a–e. Also
in these figures it is apparent that the differences between the better and worse
condition is larger on floor 5 as compared to floor 4, meaning that manipulations on floor
5 had a larger effect on the employees. Nevertheless, also for the significant findings
the survey responses have a low variation around the middle of the scale. Therefore it
seems that even if noise has a significant impact it does not seem terribly disturbing to
most respondents. Given the small variation in the objective measures between the
conditions, our results might also indicate that quite large changes to the physical
environment are needed to substantially improve the acoustical conditions in the office.
In this study we conducted acoustical measurement according to the new ISO-standards for
open-plan offices (ISO-3382-3, 2012). With these measurements and radius of comfort (rc)
we could find differences which corresponded to the manipulations done to the acoustical
environment. Although the acoustical measures showed quite small differences between our
two conditions within each floor, a comparison of effect sizes for the sought quadratic
function between time and floor reveal small effects approaching medium sized effects (η 2
between 0.15 and 0.29) (Cohen, 1988). This would suggest that even a minor improvement
made to room acoustics could impact employees perceived health and disturbances.

<hs>  Strengths and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

One of the main strengths of this present study is that it was carried out in the field
addressing regular office employees. Given that the social and other organisational
structure within the organisation had not changed, we believe that our finding is highly
relevant for the effect that noise has on employees' perception of cognitive stress and
disturbances. Another strength of this study is its crossover design. By having two groups
that constantly were exposed to the opposite condition than the other and by changing back
and forth between the conditions, we created a highly controlled field experiment
increasing the reliability of our findings. In addition, we also gathered objective data.
The objective measurements ensured that the manipulations we carried out had an impact on
the acoustical environment and further strengthened our findings by corresponding to the
survey responds. By so doing we were able to show that improvements in acoustics have a
direct impact on measures of both health and disturbances. The ceiling tiles of both
conditions looked the same, but the wall absorbent installed during the better condition
could have indicated to the respondents sitting near the wall absorbents that an
improvement had been made. In turn this signal could have systematically affected the
employees to respond more positively when the absorbents were present. Nevertheless, there
are some aspects that speak against that our results mainly would be due to such a placebo
effect. Before any manipulations were made employees on both floors were asked to answer
the survey (T0). At T1 floor 5 had the worse condition – that is the condition without any
wall absorbent and with reflective ceiling tiles. As we compare the result of T0 with T1
we see that these employees generally report more problems during T1 (compare Table 2a
with Fig. 3a–e or with Table 2b). If our result would be due to placebo we should not have
seen such pattern given that no visual manipulations had been made on floor 5 between T0
and T1. On the other hand on floor 4 and during T1 in comparison to T0, the employees
rated only small improvements in disturbances and cognitive stress. This corresponds well
with the minor improvements measured by the acoustical measurements conducted between T0
and T1. Therefore, all in all it seems that the employees' answers correspond well with
the acoustical measurements conducted rather than the presence or absence of the wall
absorbents. Another concern that could be raised as a limitation is the short exposure
period for each condition before we collected the survey data. If people after some
passage of time learn to adapt to an increased noise level then our findings might not be
as relevant as they might suggest. However, a study by Banbury and Berry (2005) could not
find any lasting habituation to office noise, which speaks against any major adaptation to
increased noise levels taking place among employees.

<h>CONCLUSIONS AND IMPLICATIONS FOR PRACTICE</h>
-----------------------------------------

By means of a crossover design, we investigated the effect of two different room acoustics
on employees' perception of disturbances, cognitive stress, and professional efficacy.
Although the acoustical measurements showed that the manipulations between our two
conditions in general were quite small, the better acoustical condition nevertheless had a
more positive effect on employees' perception of disturbances and cognitive stress. It was
also shown that manipulations in the acoustical environment measured by measurements
suggested in ISO 3382-3(ISO-3382-3, 2012) correspond well with employees' self-reported
measures of health and disturbances. The study shows the importance of focussing on the
acoustical conditions in open-plan offices in order to improve employees' well-being and
through means of that also organisational efficiency.

<h>AUTHORS' CONTRIBUTION</h>
---------------------

AS designed and made the preparation for the study. AS anchored the project in the
participating organisation and also collected the data. AS conducted the analysis and
wrote the first and successive draft including introduction, method, result, and
discussion sections. HW, FJ, EB, and CBD have contributed with substantial suggestions and
comments to the manuscript. AS have changed the manuscript according to relevant
suggestions and comments, and prepared the final manuscript. AS submitted the manuscript
and is the corresponding author in the review process. HW, FJ, and EB have been
supervising AS in every part of the study, contributed to the writing of the paper, and
have also been involved in the design process. HW is overall project leader.


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<ART>Effects of age on metacognitive efficiency
==========================================

Authors: Emma C. Palmer, Anthony S. David, Stephen M. Fleming
DOI: 10.1016/j.concog.2014.06.007
Year: 2014  |  Pages: 151-160
ASJC codes: 3204, 3205
Keywords: Aging, Awareness, Development, Lifespan, Metacognition

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Humans have a capacity to become aware of thoughts and behaviours known as metacognition. Metacognitive efficiency refers to the relationship between subjective reports and objective behaviour. Understanding how this efficiency changes as we age is important because poor metacognition can lead to negative consequences, such as believing one is a good driver despite a recent spate of accidents. We quantified metacognition in two cognitive domains, perception and memory, in healthy adults between 18 and 84. years old, employing measures that dissociate objective task performance from metacognitive efficiency. We identified a marked decrease in perceptual metacognitive efficiency with age and a non-significant decrease in memory metacognitive efficiency. No significant relationship was identified between executive function and metacognition in either domain. Annual decline in metacognitive efficiency after controlling for executive function was ~0.6%. Decreases in metacognitive efficiency may explain why dissociations between behaviour and beliefs become more marked as we age. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Metacognition refers to ‘thinking about thinking’ (Flavell, 1979), or the ability to
become aware of thoughts and behaviours. Metacognition is a fundamental aspect of higher
cognition in humans (Dunlosky & Metcalfe, 2009) and may support conscious awareness
(Koriat, 2007), social interaction (Frith, 2012), and be impaired in neuropsychiatric
disorders (David, Bedford, Wiffen, & Gilleen, 2012). Metacognition comprises both
monitoring and control (Koriat & Goldsmith, 1996; Nelson, 1996). Intuitively, a person has
good metacognitive monitoring if their subjective appraisals track their objective
behaviour on a trial-by-trial basis. For example, an individual who is metacognitively
efficient will report high confidence when they are objectively correct, and low
confidence when they are objectively incorrect; conversely an individual with poor
metacognitive efficiency has poor awareness, manifested by subjective reports that are
unrelated to task performance. Different cognitive domains give rise to different types of
metacognitive judgment. For example, in the perceptual domain one might have variable
confidence about seeing or hearing a particular stimulus. Metacognitive judgments about
memory may refer to whether one’s recall or recognition is likely to have been correct (a
retrospective confidence rating) or whether a stimulus is likely to be remembered or
recognised in the future (“judgments of learning”, JOLs; and “feelings of knowing”, FOK).
Overall, metacognitive judgments are thought to be based on a combination of perceptual or
mnemonic strength and additional analytic factors (Busey, Tunnicliff, Loftus, & Loftus,
2000; Koriat & Goldsmith, 1996; Vickers, 1979). Previous research has established that
metacognitive efficiency in different domains can be isolated and studied independently of
primary cognitive capacity (see Fleming & Dolan, 2012, for a review). However, there is
some debate as to whether metacognition changes as we age. On the one hand, we might
expect greater life experience leads to more accurate self-knowledge and greater
metacognitive efficiency. On the other hand, convergent evidence has revealed a specific
neural basis for metacognitive efficiency in human prefrontal and parietal cortex
(Fleming, Huijgen, & Dolan, 2012; Fleming, Weil, Nagy, Dolan, & Rees, 2010; McCurdy et
al., 2013; Rounis, Maniscalco, Rothwell, Passingham, & Lau, 2010; Yokoyama et al., 2010)
regions which are also highly susceptible to aging-related atrophy (Raz et al., 2005;
Resnick, Pham, Kraut, Zonderman, & Davatzikos, 2003) and therefore metacognitive
efficiency may be expected to decrease as we age. Such a hypothesis is consistent with
reports that lack of awareness of cognitive, physical and perceptual abilities in healthy
older adults can be problematic in everyday life. (Hertzog & Hultsch, 2000) demonstrated
that there are notable changes in self-appraisal as we age, and these tend to centre on
inaccuracies regarding beliefs about cognitive ability and control over cognition. Older
adults tend to demonstrate increased over-confidence compared to actual performance when
compared to younger adults (Dodson, Bawa, & Krueger, 2007; Hansson, Rönnlund, Juslin, &
Nilsson, 2008). For example when older adults between the ages of 65–91 years old were
asked about their driving abilities, 85% of the drivers in this age range rated themselves
as ‘good’ or ‘excellent’ drivers despite an increased frequency of accidents (Ross,
Dodson, Edwards, Ackerman, & Ball, 2012). However, the literature on laboratory measures
of metacognition such as confidence judgments and JOLs has shown mixed results. Some
studies reveal stable or even improved accuracy of confidence ratings with age for general
knowledge (Dodson et al., 2007; Pliske & Mutter, 1996), problem solving (Vukman, 2005), or
memory recall tasks (Lachman, Lachman, & Thronesbery, 1979). Similarly, studies
investigating JOLs, FOKs and “judgments of forgetting” have found that older adults’
predictions of recall or recognition were as good as those of younger adults (Eakin,
Hertzog, & Harris, 2014; Haber, 2012; Halamish, McGillivray, & Castel, 2011). In contrast,
other studies report significant age differences in the accuracy of confidence judgments
about recall and recognition (Bender & Raz, 2012; Dodson et al., 2007; Huff, Meade, &
Hutchison, 2011; Kelley & Sahakyan, 2003; Pansky, Goldsmith, Koriat, & Pearlman-Avnion,
2009; Perrotin, Isingrini, Souchay, Clarys, & Taconnat, 2006; Soderstrom, McCabe, &
Rhodes, 2012; Souchay, Isingrini, & Espagnet, 2000; Souchay, Moulin, Clarys, Taconnat, &
Isingrini, 2007; Toth, Daniels, & Solinger, 2011; Wong, Cramer, & Gallo, 2012) learning of
emotional information (Tauber & Dunlosky, 2012), and study-time allocation (Froger,
Sacher, Gaudouen, Isingrini, & Taconnat, 2011). In addition, the neural correlates of
metacognitive judgments have been found to differ between younger and older adults (Chua,
Schacter, & Sperling, 2009). In many of these studies it has proven difficult to decouple
metacognitive accuracy from age-related changes in performance. Common measures of
metacognitive accuracy such as the gamma correlation are affected by task performance
(Masson & Rotello, 2009), potentially confounding changes in metacognition with age with
changes in performance. For example, if two individuals A and B have identical
metacognitive ability, but A performs better than B on the primary task, A’s metacognition
score will appear higher than B’s due to this performance confound. Accordingly, Daniels,
Toth, and Hertzog (2009) found that older adults had lower accuracy of immediate JOLs for
predicting old/new item recognition, but reasoned that this may reflect age-related memory
deficits as opposed to deficits in metacognition. In the present study we employ a
recently developed signal detection theoretic measure, meta-d′/d′ (Maniscalco & Lau,
2012), to circumvent this problem. Meta-d′/d′ quantifies the efficiency with which
confidence ratings discriminate between correct and incorrect trials in each task domain
(perception and memory). Importantly, meta-d′/d′ is a relative measure: given a certain
level of processing capacity (d′), meta-d′/d′ quantifies the extent to which a
metacognitively optimal observer is aware of their performance. Previous literature has
also drawn conceptual similarities between characteristics of memory metacognition and
executive functions (Fernandez-Duque, Baird, & Posner, 2000; Pannu & Kaszniak, 2005;
Shimamura, 1995; Souchay et al., 2000). In particular it has been suggested that any age-
related decline in metacognition may be due to executive limitations associated with aging
(Souchay & Isingrini, 2004). Again, however, results from initial studies examining this
issue are mixed. FOK but not JOL accuracy has been shown to significantly correlate with
executive function (Souchay, Isingrini, Clarys, Taconnat, & Eustache, 2004), indicating
that perhaps only some forms of metacognitive judgement require intact executive function
to be completed accurately. Perrotin, Belleville, and Isingrini (2007) compared patients
with mild cognitive impairment (MCI) to healthy age-matched controls in their FOK
abilities. FOK accuracy was primarily related to primary memory performance in MCI
patients, whereas in control participants it was linked to executive function. In the
present study we therefore examined the effects of both age and executive function on a
performance-controlled measure of metacognitive efficiency (meta-d′/d′). We studied
retrospective confidence judgments in two domains, perception and memory, following recent
evidence that metacognition across different domains may draw upon dissociable neural and
cognitive processes (Baird, Smallwood, Gorgolewski, & Margulies, 2013; McCurdy et al.,
2013).

<hs>  Recruitment</hs>
  ~~~~~~~~~~~

Participants were recruited via two distinct sampling methods as part of a larger clinical
research study. A copy of the Royal Mail Postal Address File (PAF), containing all
residential addresses in the boroughs of Lambeth and Southwark (London, UK), was obtained,
and approach letters for participation in the study were sent out to a random selection of
184 addresses. A total of 28 participants were recruited using this method. Participants
verbally confirmed an absence of mild cognitive impairment (MCI) or memory disorder.
Participants were also recruited using the MindSearch database, available to researchers
based at King’s College, London. Participants who had registered their details with the
database and met the inclusion criteria (n = 585) for this study were selected. All
potential participants were contacted via email twice in a 6 month period, with a total of
32 participants responding positively and being included in the study. Our inclusion
criteria required participants to be over the age of 18 and have no previous or current
presentation of a psychosis related disorder, MCI, memory disorders or Alzheimer’s
dementia. We compared our healthy older adult sample to a sample of confirmed MCI patients
who were screened as part of a larger clinical study (criteria = scoring > 20 on the MMSE
and failing at least one section of the Consortium to Establish a Registry for Alzheimer’s
Disease (CERAD) neuropsychological battery). The PAF and MindSearch participants performed
significantly better on the Wechsler Memory Scale (immediate and long term recall, long
term recognition) and Trails B-A executive function test than the clinical sample.
Therefore we can be confident that the majority of the participants included were not
suffering from undiagnosed MCI. There was no significant difference between the two
recruitment methods regarding mean group age (t = .27, p = .79), years in education (t =
−.49, p = .63) or BDI score (t = −.52, p = .61). The sample was recruited using
opportunity sampling within the two methods with no set age/gender cells filled. Two
subjects with Beck Depression Inventory (BDI; (Beck & Steer, 1984) scores greater than 20
were excluded from further analysis. All participants had normal or corrected to normal
vision.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Our sample consisted of 60 participants, 33 of whom were female. The mean age was 40.28
years old, with a minimum of 18 and maximum of 84 years old, with no difference in age
between males and females (t(58) = 0.76, p = 0.45). The mean depression score was 6.03 (SD
= 4.32) out of a possible 64 indicating that the sample was not depressed. A subset of
participants completed the memory metacognition and neuropsychological tests; therefore
for each test the relevant N is stated (Table 1).

<hs>  Metacognition measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Perceptual metacognitive ability was investigated using a computerised visual perceptual
task similar to that used previously (Fleming et al., 2010). Each trial required
participants to perform a perceptual task. The stimuli used were Gabor patches: circular
patches of alternating light and dark vertical bars (2.8 visual degrees in diameter,
spatial frequency of 2.2 cycles per visual degree). The contrast between the vertical
lines in each standard Gabor patch was 20%, where 0% indicates no difference between the
light and dark bars and 100%, the maximum difference (black to white). Six such Gabor
patches were arranged in a circle (eccentricity of 6.9 visual degrees) around a central
fixation point set on a uniform grey background (see Fig. 1a). One of the six Gabor
patches was made to pop-out from the others by increasing the contrast in that patch. The
contrast of the pop-out Gabor patches varied from 23% (little effect of pop-out) to 80%
(pop-out very clear). The task required participants to view two stimulus arrays, each
presented for 200 ms, separated by an interval of 300 ms. The interval between stimuli was
filled by a uniform grey screen without the Gabor patches. A single Gabor patch in one of
the two intervals was designated as a pop-out. Which of the six Gabor patches popped-out
varied randomly between trials. Participants were prompted by a computer display to
respond ‘1’ or ‘2’ as to whether they thought the pop-out Gabor patch appeared during the
first or second presentation. Participants responded by pressing the numerical keys on the
top left-hand side of the laptop keyboard with their left hand. Participants had 2 s in
which to make their decision, after which a red box surrounded their selection. No
feedback was given as to whether they were right or wrong. Participants then indicated
confidence in their decision on a scale of 1–6 (1: relatively low confidence; 6:
relatively high confidence; see Fig. 1a.). Participants were encouraged to use the full
range of the scale, thinking carefully about how confident they were after each decision.
Participants responded by pressing numerically marked keys on the top left-hand side of
the laptop keyboard with their left hand, with a red box again surrounding this selection.
Participants had 3.5 s to complete this metacognitive judgement. Performance on the task
was maintained at around 70% using a 2-down, 1-up staircase procedure (Levitt, 1971). Two
consecutive correct visual judgments led to a one step (3%) decrease in contrast of the
pop-out Gabor patch in the next trial, whereas one incorrect visual judgment led to a one
step increase in contrast of the pop-out patch. This procedure ensures all participants
perform with approximately the same accuracy on the primary perceptual task, allowing us
to measure metacognitive ability independent of task performance. This was especially
useful in the present study as the range of participant ages may otherwise have led to
performance bias. Older participants who struggled to make manual responses gave verbal
answers to a researcher who made manual responses. The task comprised 5 blocks of 8 min
with short breaks between each block, taking approximately 50 min to complete. A standard
task instruction sheet was read through by participants on their own, followed by the
opportunity to ask the task administrator questions. Participants were seated in a
darkened room approximately 60 cm from a laptop computer screen (Sony Vaio, PCG-71614 M
laptop; 17 in display; 1280 × 800 pixels). Stimulus display and responses for the tasks
were programmed in MATLAB 7.8 (Mathworks Inc., Natick, MA, USA) using the COGENT 2000
toolbox (http://www.vislab.ucl.ac.uk/cogent.php). A practice session of two blocks of
eight trials was given at the start to familiarise participants with the task.
Participants were tested individually in a quiet room. Memory metacognitive ability was
investigated using the 2-alternative forced choice (AFC) memory confidence task devised by
McCurdy et al. (2013) (see Fig. 1b). There were three learning and testing blocks, with a
different learning time assigned to each block. At the beginning of each block, 50 English
words (Calibri font, size 24) were presented simultaneously on the screen for either 0.5,
1, or 1.5 min to create three levels of difficulty in which participants performed at
neither chance nor ceiling. English words were generated using the Medical Research
Council Psycholinguistic Database (Wilson, 1988). These standard nouns were four to eight
letters long, had one to three syllables, and had a familiarity, concreteness, and
imagability rating of 400–700 each. Participants were instructed to memorize as many words
on the list as possible during the study period. A small notice appeared at the bottom of
the screen to inform them when there was 10 s left to study the list. After the study
period, a series of trials probing memory for the word list was presented. In each trial,
two words were presented to the left and right of fixation. One of these words had been
presented on the study list (“old”), and the other word had not been presented previously
(“new”). First, participants had 3s to provide a 2-AFC judgment with regard to which word
was ‘old’, where pressing ‘1’ referred to the left hand word and ‘2’ referred to the right
hand word. Participants then had 3 s to press one of four keys (“7,” “8,” “9,” or “0”)
using their right hand to indicate their confidence in being correct on the 2-AFC judgment
(signifying “not at all confident” to “very confident” respectively). Older participants
who struggled to make manual responses gave verbal answers to a researcher who made manual
responses. The task comprised 3 blocks of approximately 5 min each with short breaks in
between each block.

        <hss>Calculating metacognitive efficiency</hss>

        Metacognitive efficiency was quantified using the meta-d′ measure developed by
        Maniscalco and Lau (2012). Meta-d′/d′ is a relative measure: given a certain level
        of processing capacity (d′), meta-d′/d′ quantifies the extent to which a
        metacognitively optimal observer is aware of their performance. A meta-d′/d′ value
        of 1 is equivalent to metacognitively “ideal”, whereas meta-d′/d′ < 1 indicates a
        failure of metacognitive awareness. Values of meta-d′/d′ greater than 1 indicate
        that awareness is more accurate than task performance, which may occur for
        instance if the initial judgment is made under time pressure (Charles, Opstal,
        Marti, & Dehaene, 2013). Meta-d′ was calculated using MATLAB code available at
        http://www.columbia.edu/~bsm2105/type2sdt (Maniscalco & Lau, 2012) for both
        perceptual and memory metacognition.

<hs>  Neuropsychological measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

IQ was measured using the shortened Wechsler Adult Intelligence Scale-III (WAIS-III;
Wechsler, 1997a, 1997b) which comprises the Digit Symbol Coding, Arithmetic, Information
and Block Design sub-components of the full WAIS assessment; 39 participants completed
this assessment. Executive function (EF) was measured using the “Trail Making” test
(Reitan, 1986), which measures ‘set-shifting’, or the ability to shift attention between
one task to another. This test consists of two parts in which the subject is instructed to
connect a set of 25 dots as fast as possible while still maintaining accuracy. The first
task (A) requires participants to connect numbers in ascending order and the second task
(B) requires participants to connect the dots, alternating between numbers and letters (in
alphabetical order). Time taken to complete both tasks is recorded and a ‘B-A’ score is
calculated by subtracting the time taken in task A from time taken in task B. The longer
the composite time (B-A) the worse the set-shifting ability. 44 participants completed
this assessment. The Wechsler Memory Scale (WMS) ‘logical memory’ sub-task (Wechsler,
1997a, 1997b) was used to gauge short-term, long-term and recognition memory. The logical
memory task is a sub-test within the whole WMS battery, designed to detect attention and
memory deficits, and asks participants to listen to and remember two spoken stories. After
hearing each story participants are asked to immediately recount the story to the
researcher (Immediate test), where a higher score is obtained by recalling more key facts.
30 min after the stories are initially heard participants are asked again to recount the
stories to the researcher (Delayed test). Finally, a recognition task is then carried out,
where participants are asked 15 questions about each story and required to give ‘Yes’ or
‘No’ answers (Recognition test). 34 participants completed the short-term recall
(Immediate) test, and 33 participants completed the long-term recall (Delayed) and
recognition (Recognition) tests.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Correlations between metacognitive efficiency (meta-d′/d′), age and neuropsychological
measures were computed using Pearson’s product-moment correlations implemented in R 3.0.1.
5 subjects who performed lower than 65% in the perceptual task (indicating a failure of
the staircase procedure to appropriately control performance) were excluded from analyses
of perceptual task data. Regression analyses were carried out using the lm function in R
and un-standardised regression coefficients are reported.

<h>RESULTS</h>
-------

The mean percentage of trials answered correctly on the perceptual task was 70.8% (range
65.7–73.6%), with no significant relationship between age and percentage of trials
answered correctly (r = −0.16, p = 0.25; n = 53). The mean percentage of trials answered
correctly on the memory task was 67.8% (range 49–87%). Performance on the memory task was
lower in older adults leading to a negative correlation between age and performance (r =
−0.36, p = 0.03; n = 38). We calculated a metacognitive efficiency score (meta-d′/d′) for
each participant on both perceptual and memory tasks. The average efficiency score was
1.08 (SD = 0.34) for the perceptual task and 0.73 (SD = 0.81) for the memory task. In the
subset of subjects who completed both tasks (N = 32), metacognitive efficiency tended to
be greater for perception than for memory (t(31) = 2.19, p = 0.04). Consistent with
previous findings (McCurdy et al., 2013) we found a positive association between
metacognitive efficiencies across domains (r = 0.40, p = 0.02; n = 32; see Fig. 2a.)
However, when two memory metacognition outliers were removed (greater than 2 standard
deviations beyond the group mean; see Fig. 2a) this relationship failed to reach
significance (r = 0.25, p = 0.19; n = 30). No significant relationships were identified
between IQ and metacognitive efficiency (perceptual: r = 0.12, p = 0.51, n = 33; memory: r
= 0.11, p = 0.60, n = 27) or years of education and metacognitive efficiency (perceptual:
r = 0.016, p = 0.25, n = 53; memory: r = 0.003, p = 0.98, n = 38), consistent with
previous reports of a lack of correlation between IQ and metacognition in younger adults
(Fleming et al., 2012; Weil et al., 2013). Significant relationships were identified
between WMS scores and memory metacognitive efficiency (immediate, r = .37, p = .05, n =
28; delayed, r = .59, p = .01, n = 27; recognition, r = .37, p = .05, n = 27), but not
perceptual metacognitive efficiency (immediate, r = .12, p = .54, n = 29; delayed, r =
.05, p = .79, n = 28; recognition, r = .07, p = .73, n = 28). We next turned to the
relationship between metacognition and age. We found a significant negative relationship
between perceptual metacognitive efficiency (meta-d′/d′) and age (r = −0.38, p = 0.005; n
= 53; see Fig. 2b). Thus, despite our measure of metacognition controlling for differences
in task performance, older adults showed lower awareness of their perceptual task
performance than younger adults. The relationship between age and memory metacognitive
efficiency (meta-d′/d′) was negative but was non-significant (r = −0.064, p = 0.70; n =
38). We cannot however draw conclusions regarding a differential effect of age on
perceptual compared to memory metacognition as the difference between the domain-specific
metacognitive efficiency-age correlations in the subset of subjects who completed both
perceptual and memory tasks was itself not significant (Hotelling’s t = 0.66, p = 0.51).
As meta-d′/d′ is a ratio between two quantities, changes in either or both of its
components may contribute to an overall decrease in metacognitive efficiency in the
perceptual task. Examining each component separately, in the perceptual task we found a
significant increase in d′ with age (r = 0.47, p < 0.001; n = 53) and a non-significant
decrease in meta-d′ (r = −0.17, p = 0.22; n = 53). Under the ideal observer model, d′
should be equal to meta-d′. Thus both an increase in performance and a decrease in the
ability to appraise this performance (given a particular level of d′) contributed to the
observed decrease in overall efficiency (Fig. 2c). For the memory task, there were no
significant changes in either d′ (r = 0.016, p = 0.92; n = 38) or meta-d′ (r = −0.15, p =
0.36) with age. Finally, we considered that the relationship between metacognitive
efficiency and age may be mediated by changes in executive function. In order to assess
this hypothesis we constructed a general linear model (GLM) that predicted metacognitive
efficiency from age and executive function as measured by the Trail Making Test. This
analysis was restricted to a subset of participants who conducted the Trail Making Test (N
= 44). We found that the relationship between age and perceptual metacognitive efficiency
remained significant after controlling for changes in executive function (β = −0.0058, p =
0.02), and increased executive function was not associated with better metacognitive
efficiency (β = 0.0042, p = 0.26).

<h>DISCUSSION</h>
----------

The primary aim of this study was to investigate the effects of age on metacognitive
efficiency in healthy adults between the ages of 18 and 84. We found that perceptual
metacognitive efficiency declined with age, despite task performance being controlled to
ensure all participants performed with the same accuracy. In other words, older adults
were less efficient at introspecting about whether they are performing well or badly on a
perceptual task than younger adults. This result is consistent with previous observations
of a weaker match between beliefs and abilities in older adults (Hultsch, MacDonald,
Hunter, Levy-Bencheton, & Strauss, 2000; Ross et al., 2012) and age-related differences in
the accuracy of confidence judgments (Bender & Raz, 2012; Dodson et al., 2007; Huff et
al., 2011; Kelley & Sahakyan, 2003; Pansky et al., 2009; Audrey Perrotin et al., 2006;
Soderstrom et al., 2012; Souchay et al., 2000, 2007; Toth et al., 2011; Wong et al.,
2012). However, many previous studies did not control for the influence of task
performance on measures of metacognition. This is particularly critical when studying
aging as metacognitive ability may be difficult to distil from other age-related changes
in cognitive abilities. In the current study we employ a measure of metacognition,
meta-d′/d′, that controls for the influence of task performance and response bias
(Maniscalco & Lau, 2012). Our results extend those of Weil et al. (2013) who took a
similar approach to study the development of metacognitive efficiency during adolescence.
In a sample of 28 adolescents and 28 adults it was found that perceptual metacognitive
efficiency increased with age during adolescence (11–18 years old), with a non-significant
decrease with age in adulthood. However the maximum age in Weil et al’s sample of older
adults was 41, precluding the study of metacognitive efficiency in older age. Here we
extend this age range to 84, finding that efficiency continues to decline despite task
performance remaining stable. A subset of subjects additionally completed a recognition
memory task that allowed us to calculate a metacognitive efficiency score in the memory
domain. We found a positive correlation in efficiency scores across domains that was
weakened after removal of two outliers. Our result provides some support for the notion
that there is a global correlation in metacognitive ability across domains (McCurdy et
al., 2013), but also is consistent with a large proportion of domain-specific variance
that may be linked to separate brain systems underpinning perceptual and memory
metacognition (Baird et al., 2013; McCurdy et al., 2013). There was no effect of age on
memory metacognition, but we are cautious about over-interpreting this null result for two
reasons: first, fewer subjects completed the memory task, reducing our power to detect an
effect of age; and second, there was no statistical support for a differential effect of
age on perceptual vs. memory metacognition. Further work is required to ascertain whether
may be different trajectories for age-related changes in domain-specific metacognitive
functions. Mixed results were obtained for the effect of age on measures of basic task
performance (% correct and d′). In the perceptual task, effects of age on these two
measures had opposite sign (negative for% correct and positive for d′). Dissociations
between% correct and d′ are possible if the decision criterion is also changing (Macmillan
& Creelman, 2004). However such differences in the current study are difficult to
interpret, because performance was controlled in the perceptual task such that% correct
varied over a narrow range, and poorly performing subjects were excluded prior to
analysis. It is possible that increases in d′ with age reflect an overcompensation in
difficulty adjustment that made the task slightly easier for older adults. In the memory
task, % correct declined with age, whereas this effect was not seen in an analysis of d′.
The meta-d′ approach estimates the subject’s metacognitive accuracy in units directly
comparable to d′, a measure of primary task performance (Maniscalco & Lau, 2012). For a
metacognitively ideal observer, meta-d′ = d′, and meta-d′/d′ = 1. Closer examination of
the relationship between these quantities and age revealed an increase in perceptual d′
and a decrease in perceptual meta-d′, leading to an overall decrease in metacognitive
efficiency (Fig. 2c). As noted above, the narrow range of performance levels in the
perceptual task precludes strong interpretation of changes in d′. However, the relative
values of d′ and meta-d′ are informative. In younger adults, meta-d′ is similar to or
slightly above d′ (meta-d′/d′ ∼ 1), whereas in older adults, meta-d′ drops below d′,
leading to metacognitive efficiency scores less than expected on an ideal observer model.
One might expect that age-related changes in metacognitive processes would be related to
neuropsychological measures of executive function (Fernandez-Duque et al., 2000),
following evidence that perceptual metacognitive efficiency is linked to frontal lobe
function (Fleming et al., 2010; Hoerold, Pender, & Robertson, 2013; Persaud et al., 2011;
Rounis et al., 2010). Previous studies have found evidence for a link between the use of
metacognitive information in the control of behaviour and executive function as measured
by Wisconsin Card Sorting Test performance (Pansky et al., 2009; Souchay & Isingrini,
2004), but the relationship between executive function and metacognitive monitoring is
less well understood. In particular, it is difficult to rule out an indirect effect of
executive function on measures of metacognition via effects on primary task performance,
highlighting the need to distil a measure of metacognitive efficiency that controls for
differences in performance. In the current study, we did not find evidence for a
relationship between perceptual metacognitive efficiency and performance on the Trail
Making Test, a measure of set-shifting. Indeed, in a regression analysis explicitly
controlling for changes in set-shifting performance, we observed an annual decline of 0.6%
in metacognitive efficiency. Of course, executive function is a very broad construct, and
the relationship between metacognitive efficiency and other components such as inhibition
and updating (Miyake et al., 2000) remain to be determined. The perceptual and memory
metacognition tasks were adapted from those used in recent structural and functional
imaging studies of healthy participants (Baird et al., 2013; Fleming et al., 2010; McCurdy
et al., 2013). However a limitation of this design is that there are differences between
tasks that are potentially orthogonal to the domain in question. For example, our
recognition memory task involved verbal stimuli; we cannot rule out the possibility that a
different pattern of results would be obtained with memory tasks using nonverbal stimuli
such as faces. Indeed, an important goal for future work is the development of perceptual
and memory metacognition paradigms that are more closely matched for stimulus
characteristics. Similarly it is unclear whether the observed decrease in metacognitive
efficiency is specific to visual perceptual metacognition, or may extend to other
perceptual modalities or other aspects of decision-making. An additional difference
between domains is that the perceptual task used a staircase procedure to control task
difficulty for each individual participant whereas this was not feasible with the current
word recognition task. By adjusting stimulus selection online such performance control
could be built into a memory paradigm in future studies. Finally, a small minority of
older individuals struggled to input confidence ratings manually using the keyboard
response, and their verbal ratings were instead entered by the experimenter. We cannot
rule out effects of changes in response modality on our results, but we note that even in
older individuals metacognitive efficiency did not decline to floor levels (meta-d′/d′ ∼
0), indicating that confidence ratings tracked task performance in a meaningful way
regardless of adjustments in response modality. In summary, we reveal an age-related
decline in perceptual metacognitive efficiency whilst controlling for age-related
differences in task performance and executive function. Our study is cross-sectional, and
it is possible that other factors differing across the age range affected metacognitive
ability. It will therefore be very informative in further work to investigate longitudinal
changes in metacognitive efficiency with age. Quantifying changes in metacognition with
age is critical for our understanding of higher-order cognitive functions in an aging
population, especially as deficits in metacognitive monitoring may lead to impaired
control of behaviour (Koriat & Goldsmith, 1996). Aging-associated diseases such as
Alzheimer’s are accompanied by metacognitive deficits that may lead to non-adherence to
treatment and impaired decision-making (Cosentino, 2014). Our results, when combined with
previous research in adolescents (Weil et al., 2013), reveal a non-linear relationship
between age and perceptual metacognitive efficiency, increasing during adolescence,
plateauing in early adulthood, and declining in older age.

<h>AUTHOR CONTRIBUTIONS</h>
--------------------

E.C.P, A.S.D and S.M.F. designed research; E.C.P performed research; E.C.P. and S.M.F.
analysed data; E.C.P, A.S.D and S.M.F. wrote the paper.


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<ART>Emotional Mental Imagery as Simulation of Reality: Fear and Beyond—A Tribute to Peter Lang
================================================================================

Authors: Julie L. Ji, Stephanie Burnett Heyes, Colin MacLeod, Emily A. Holmes
DOI: 10.1016/j.beth.2015.11.004
Year: 2016  |  Pages: 702-719
ASJC codes: 3203
Keywords: behavior therapy, cognitive therapy, emotion, mental imagery, visual imagery

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<h>ABSTRACT</h>
--------

This article pays tribute to the seminal paper by Peter J. Lang (1977; this journal), “Imagery in Therapy: Information Processing Analysis of Fear.” We review research and clinical practice developments in the past five decades with reference to key insights from Lang's theory and experimental work on emotional mental imagery. First, we summarize and recontextualize Lang's bio-informational theory of emotional mental imagery (1977, 1979) within contemporary theoretical developments on the function of mental imagery. Second, Lang's proposal that mental imagery can evoke emotional responses is evaluated by reviewing empirical evidence that mental imagery has a powerful impact on negative as well as positive emotions at neurophysiological and subjective levels. Third, we review contemporary cognitive and behavioral therapeutic practices that use mental imagery, and consider points of extension and departure from Lang's original investigation of mental imagery in fear-extinction behavior change. Fourth, Lang's experimental work on emotional imagery is revisited in light of contemporary research on emotional psychopathology-linked individual differences in mental imagery. Finally, key insights from Lang's experiments on training emotional response during imagery are discussed in relation to how specific techniques may be harnessed to enhance adaptive emotional mental imagery training in future research.

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Mental imagery refers to perceptual experience in the absence of sensory input, commonly
described as seeing with the “mind’s eye,” hearing with the “mind’s ear,” and so on
(Kosslyn, Ganis, & Thompson, 2001). In this paper we consider mental imagery both as an
emotion-evoking stimulus that can be manipulated (e.g., during therapeutic techniques such
as imaginal exposure; Foa, Hembree, & Rothbaum, 2007), and as a symptom of psychopathology
(e.g., distressing intrusive memories/flashbacks in posttraumatic stress disorder; cf.
Holmes & Mathews, 2010). In his bio-informational theory of emotional imagery, Lang (1977,
1979) postulated that a mental imagery representation of an emotionally charged stimulus
(e.g., a spider) activates an associative network of stored information that overlaps with
that activated during actual experience of the stimulus in reality (e.g., encountering a
live spider). This associative network of information is said to consist of perceptual
information about the stimulus (color, shape, size, texture of spider), semantic
information about what it means (insect, danger, bite), somatovisceral response
information about what it feels like to encounter the stimulus (fear, racing heart), and
preparatory motor responses evoked by the encounter (e.g., muscles tensing to flee from
the spider). According to this theory, mental imagery differs from verbal thought in that
only mental imagery has the capacity to activate physiological and behavioral response
systems (Lang, 1987). Research pertaining to this assertion will be discussed in Section
III. Lang's (1977, 1979) associative-network information processing definition of mental
imagery was influenced by Pylyshyn's (1973) propositional theory of mental imagery, which
construed mental imagery as conceptual representations describing reality, rather than as
pictorial representations depicting reality. Historically, the debate concerning whether
mental imagery involves conceptual representations (Pylyshyn, 1973) or pictorial
representations (Kosslyn, 1981) has been the subject of heated debate. Neuroimaging and
psychophysics evidence gathered in the past 50 years has largely resolved the debate in
favor of the latter view (see Pearson, Naselaris, Holmes, & Kosslyn, 2015, for a review).
Although this appears to refute the grounds of Lang’s bio-informational theory, closer
inspection reveals that the validity of this theory stands irrespective of whether mental
imagery is conceptual or pictorial in nature. As Lang (1987) explicated, the bio-
informational theory was developed not as a theory on the nature of mental imagery, but as
a functional theory concerning the impact of mental imagery on emotional processing. Due
to the overlap in perceptual information between imagined and real stimuli, Lang (1977,
1979) proposed that imagined interaction with a stimulus can evoke corresponding emotional
responses associated with real interaction with that stimulus. As such, imagined
interaction with stimuli can function as an “as-if real” template for rehearsing and
modifying emotional and behavioral responses to the same stimuli in real life. Lang (1977,
1979) proposed that this function of mental imagery could be harnessed in clinical
treatment to facilitate fear-extinction learning and habituation via the rehearsal and
learning of new adaptive responses during imaginal exposure therapy. Indeed, numerous
studies using a range of associative learning paradigms have shown that mental imagery can
produce conditioned responses in the same way as real stimuli (cf. Dadds, Bovbjerg, Redd,
& Cutmore, 1997; Lewis, O'Reilly, Khuu, & Pearson, 2013). Crucially, Lang proposed that
the elicitation of a fear emotional response during mental imagery of the feared stimuli
(simulation of both perceptual representations and autonomic and behavioral responses) is
required for learning to occur, and is therefore necessary in order for imaginal exposure
to be effective (Lang, 1977; Wolpe, 1958). Interestingly, Lang’s conception of mental
imagery as an “as-if real” template parallels contemporary functional perspectives on
mental imagery. These contemporary accounts view mental imagery as a core component of the
"prospective brain," which enables the simulation of hypothetical future events based on
prior knowledge and memories of past experience for the purposes of prediction and
planning (Moulton & Kosslyn, 2009; Schacter, Addis, & Buckner, 2008; Suddendorf &
Corballis, 2007). Of particular relevance to Lang’s (1977, 1979) functional theory is
Moulton and Kosslyn's (2009) theory of mental imagery as emulation. Emulation is defined
as the episodic construction of a hypothetical scenario that simulates not only perceptual
information about an event, but also rich semantic and affective information about
plausible causes and consequences of the imagined scenarios (Moulton & Kosslyn, 2009). As
such, both Lang (1977, 1979) and Moulton and Kosslyn (2009) postulate that mental imagery
has the capacity to evoke cognitive and emotional responses, enabling the individual to
not only “try out” one or more versions of what might happen (Schacter et al., 2008, p.
40), but to also “try out” the emotional consequences of alternative courses of action
(Lang, 1987, p. 412; Moulton & Kosslyn, 2009, p. 1278). By providing a pivotal testable
framework linking mental imagery to emotion, Lang’s (1977, 1979) bio-informational theory
paved the way for much subsequent research concerning the functions of mental imagery.
While Lang focused on the role of imagery in fear extinction learning, contemporary
theorists point to the wider role of mental imagery in planning, problem solving, and
self-regulation (Gilbert & Wilson, 2007; Suddendorf & Corballis, 2007; Taylor, Pham,
Rivkin, & Armor, 1998). The first half of this review will evaluate evidence pertaining to
Lang’s key proposal, that mental imagery has the capacity to evoke emotional responses,
and explore how this capacity has been exploited therapeutically in clinical treatment.
The second half of the review will consider how subsequent research has built on Lang’s
initial work concerning individual differences to illuminate how variability in imagery
may relate to emotional dysfunction, and highlight neglected insights from Lang’s research
on emotional imagery training that could potentially contribute to future treatment
innovation.

<h>SECTION I: MENTAL IMAGERY-EVOKED EMOTIONAL RESPONSE</h>
---------------------------------------------------

Developments in clinical psychology over the past 50 years have shown that unwanted and
distressing mental imagery is a symptom present in a wide range of anxiety and mood
disorders (Holmes & Mathews, 2010). In anxiety disorders, mental imagery phenomena include
the intrusive flashbacks that define posttraumatic stress disorder (Brewin & Holmes, 2003;
Ehlers et al., 2002), and imagery of feared stimuli or distorted images of one’s own
physical appearance in the case of phobias or social phobia, respectively (Hirsch &
Holmes, 2007). Depression and bipolar disorder symptomology also feature mental imagery of
past failures and trauma (Kuyken & Brewin, 1994), as well as possible future events, such
as suicidal acts (Holmes, Crane, Fennell, & Williams, 2007). While clinical presentation
suggests that negative mental imagery symptomology can have emotionally distressing
consequences for patients, researchers have noted a relative paucity of studies designed
to directly evaluate this assumption (Holmes & Mathews, 2010; Watts, 1997). Lang (1977,
1979) was one of the first investigators to empirically examine the capacity for mental
imagery to evoke emotional response. Much of Lang’s experimental work on mental imagery
was devoted to assessing psychophysiological reactivity to mental imagery cued by verbal
scripts depicting emotional scenarios and bodily responses (e.g., “your face is flushed as
your muscles strain to continue the pace”). In this section, we review evidence resulting
from the work of Lang, and others, that mental imagery does indeed have an impact on
emotion, as indexed by physiological, neurological, and subjective measures. Furthermore,
response information measured at these levels has also revealed biases in emotional
processing in individuals suffering from emotional psychopathology, such as mood and
anxiety disorders.

<hs>  The Impact of Emotional Mental Imagery on Physiological Activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It is widely accepted that emotional experience involves activation of the central and
peripheral nervous systems (Gross & Barrett, 2011). Thus, if mental imagery
representations of emotional scenarios are capable of eliciting emotional responses in an
“as-if real” manner (Kosslyn et al., 2001; Kreiman, Koch, & Fried, 2000; Lang, 1979), this
may be observable at a physiological level. Using verbal scripts depicting emotionally
negative or neutral information, Lang’s (1977, 1979) experimental work measured peripheral
nervous system responses while participants imagined the content of the scripts. The
central hypothesis was that physiological effects would arise during emotional imagery as
a result of activation of perceptual memories, triggering somatovisceral responses
associated with experience of the stimuli in reality. In terms of autonomic arousal, Lang
and colleagues observed greater heart rate acceleration during mental imagery of high
versus low arousal scenarios. In healthy participants, imagery of fear and anger-related
scenarios led to greater heart rate acceleration than did imagery of neutral scenarios
(Cook, Hawk, Davis, & Stevenson, 1991; Vrana, 1995; Vrana, Cuthbert, & Lang, 1986;
Witvliet & Vrana, 1995). Similarly, skin conductance response (SCR) levels also indicated
elevated emotional arousal during mental imagery of emotional scenarios, such that scripts
depicting highly arousing pleasant and unpleasant experiences produced larger increases in
SCR relative to those depicting neutral experiences, in healthy populations (Lang, Levin,
Miller, & Kozak, 1983; Weerts & Lang, 1978). Research has shown that respiratory responses
are also influenced by mental imagery in healthy populations. Specifically, imagery evoked
by scripts depicting high arousal scenes (fear and action-related) compared to low arousal
scenes (relaxation and depression-related) produced greater drops in end-tidal fractional
carbon dioxide concentration, likely reflecting hyperventilation (Van Diest et al., 2001).
Importantly, this hyperventilation during emotional imagery was more pronounced in
individuals with higher relative to lower imagery generation ability, as assessed using
the Questionnaire Upon Mental Imagery (QMI; Sheehan, 1967). This individual differences
dimension in imagery has also been explored in Lang’s work, and will be considered in more
detail in Section III. In addition to autonomic indices, mental imagery has been shown to
modulate other indices of physiological arousal, such as the startle blink reflex. Vrana
and Lang (1990) required healthy participants to first learn and then recall six pairs of
sentences depicting fear-related and neutral scenarios. During recall, participants were
instructed either to relax and ignore the sentence (control condition), to silently
articulate the sentence (verbal condition), or to imagine the sentence content as a
personal experience (imagery condition). As expected, startle blink reflexes evoked by
acoustic probes were found to be greater during recall of fear relative to neutral
sentences. Importantly, this effect was greater in the imagery condition than in either
the control condition or the verbal condition (Cuthbert et al., 2003). Finally, mental
imagery of food stimuli has been shown to modulate the gustatory salivary reflex. Research
in the field of brain computer interfaces (BCI) has found increases and decreases in
salivary pH levels compared to baseline as a result of a healthy participant imagining
consuming a lemon versus drinking milk, respectively (Vanhaudenhuyse, Bruno, Bredart,
Plenevaux, & Laureys, 2007). This finding has also been harnessed to demonstrate conscious
awareness in clinical patients with complete locked-in syndrome (LIS), individuals who
cannot otherwise indicate the presence of conscious awareness (Wilhelm, Jordan, &
Birbaumer, 2006). In addition to appetitive salivary responses, repetitive mental imagery
of food consumption (eating M&Ms) has also been shown to lead to food item-specific
satiation effects (Morewedge, Huh, & Vosgerau, 2010). Although no physiological measures
were included in the study, consumption of that food item was reduced in the high-
repetition imagery group (30 repetitions) relative to the low-repetition imagery group
(three repetitions), indicating satiation effects (Morewedge et al., 2010). Together, the
above evidence provides support for Lang’s (1977, 1979) contention that mental imagery has
the capacity to activate the peripheral nervous system and evoke somatic responses, be it
in the form of “fight or flight” sympathetic system response during fear- or anger-related
imagery, or “rest and digest” parasympathetic response during gustatory imagery. However,
one limitation associated with using physiological indicators of autonomic nervous system
(ANS) activation is that these can be employed only to index high arousal emotions, such
as anger, fear, disgust, or elation. In contrast, both high and low arousal emotional
responses can be assessed using neurological measures, such as those provided by
neuroimaging. Furthermore, the studies reviewed in this section have not explicitly
contrasted mental imagery representations of emotional stimuli to an alternative mode of
representation of the same information, and therefore one cannot conclude based on the
evidence that the physiological effects observed reflect the impact of mental imagery per
se, rather than the impact of emotional information processing in general. Research
addressing this limitation will be discussed in Section III.

<hs>  The Impact of Emotional Mental Imagery on Neural Measures of Emotional Response</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

According to Lang's (1979) bio-informational theory, emotional imagery is hypothesized to
be able to elicit similar physiological responses in both peripheral and central systems
as would be evoked during actual experience (Lang & McTeague, 2009). Since the 1970s,
developments in brain imaging technology have enabled assessment of the impact of
emotional imagery on central nervous system (CNS) structures involved in coordinating
peripheral nervous system (PNS) responses. Neural indices of emotion processing during
emotional mental imagery can be evaluated in comparison to activity observed during
veridical perception of emotional stimuli, or to emotionally neutral mental imagery. Meta-
analytic reviews of neuroimaging studies on healthy participants show that the brain
regions most consistently associated with emotional processing are the dorsomedial
prefrontal cortex (mPFC), anterior cingulate cortex (ACC) and amygdala (Murphy, Nimmo-
Smith, & Lawrence, 2003; Phan, Wager, Taylor, & Liberzon, 2002), and the insular cortex
(Craig, 2009), all of which are involved in the coordination of ANS activity. Activation
of these same emotion-processing regions has been observed during emotional mental
imagery. Early hemodynamic neuroimaging studies using positron emission tomography (PET)
showed that mental imagery of emotional relative to neutral information elicited increased
regional cerebral blood flow (rCBF) to the mPFC, ACC and anterior insula (Kosslyn et al.,
1996; Partiot, Grafman, Sadato, Wachs & Hallett, 1995; Schaefer et al., 2003). This effect
has been found in PET studies not only for mental imagery evoked by scripts depicting
negative scenarios (aggression and guilt-related) (Shin et al., 2000), but also for mental
imagery evoked by scripts depicting positive scenarios (success and affection-related)
(Schaefer et al., 2003). More recent studies have used script-driven emotional imagery to
examine the specificity of neural circuits for the processing of emotional valence versus
arousal. Costa, Lang, Sabatinelli, Versace, and Bradley (2010) used functional magnetic
resonance imaging (fMRI) to examine negative, positive, and neutral script-driven imagery,
and found that activation of the amygdala was enhanced during emotional relative to
neutral imagery, irrespective of emotional valence. However, activation of the nucleus
accumbens (NAc) and mPFC were selectively enhanced during positive relative to neutral
imagery, not negative relative to neutral imagery (Costa et al., 2010). Results from this
script-driven imagery study are also consistent with a previous fMRI study where
participants viewed positive and neutral pictures (Sabatinelli, Bradley, Lang, Costa, &
Versace, 2007). Studies using fMRI have also compared neural responses to real versus
imagined emotional stimuli in the same participants. Kim et al. (2007) found comparable
magnitudes of left hemisphere amygdala activity between when participants viewed faces
with negative and positive emotional expressions and when they generated mental imagery of
such faces. In fMRI studies using real-time neural activation feedback (“neurofeedback”),
over successive trials participants were able to use self-generated visualization of
positive and negative scenarios to regulate the activation of emotion processing regions
such as the insula (S. Lee et al., 2011). In addition to face stimuli, mental imagery of
positive and negative events in the past and future has been shown to activate the
amygdala and ACC (Sharot, Riccardi, Raio, & Phelps, 2007). In another study examining
negative and positive mental imagery in the same participants, Damasio et al. (2000) found
different ACC subregions were differentially activated by fear, anger, happiness, and
sadness imagery. Finally, direct evidence that visual imagery and visual perception share
common neural systems implicated in emotional response comes from a single-cell recording
study on human epileptic patients. Kreiman et al. (2000) found that 75% of the 89 recorded
cells in the amygdala selectively altered their firing rates in comparable patterns during
both visual perception and visual imagery recall of emotional faces, whereas 4% and 10%
responded selectively to imagery or veridical perception, respectively (Kreiman et al.,
2000). As such, results from neuroimaging and single cell recording studies provide
converging evidence that mental imagery has the capacity to evoke an emotional response by
activating neural networks involved in emotional processing and response coordination with
the autonomic nervous system. However, as with the physiology studies reviewed earlier,
the neuroimaging studies reviewed here have not explicitly contrasted mental imagery
representations of emotional stimuli to an alternative mode of representation of the same
information, and therefore one cannot conclude based on the evidence that the
physiological effects observed reflect the impact of mental imagery per se, rather than
the impact of emotional information processing in general.

<hs>  Disruption of Emotional Mental Imagery Reduces Emotional Impact</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

If mental imagery-based representation of emotional information serves to elicit emotional
responses to this information, then it follows that disruption of such imagery should
reduce the intensity of such emotional responding. This hypothesis has been investigated
using dual task paradigms that reduce the availability of cognitive resources required for
mental imagery generation. Typically, in such studies, participants attempt to generate
mental imagery while undertaking a concurrent task that consumes working memory resources,
such as sequenced finger tapping on a number pad, or mental arithmetic. Across several
experiments, Andrade, Kavanagh, and Baddeley (1997) asked healthy participants to generate
visual imagery from emotionally negative versus neutral cues (photographs and personal
memories) while concurrently tapping a spatial pattern with a finger, engaging in lateral
eye movements, or performing no concurrent task. Results showed lower vividness of mental
imagery in the concurrent spatial tapping and lateral eye movement conditions, relative to
the no-concurrent task control condition. Critically, this reduction in the imagery
vividness was accompanied by a corresponding decline in the intensity of participants’
emotional responding to the negative, compared to neutral, cues. This result was
replicated by Kavanagh, Freese, Andrade, and May (2001) using a within-subjects design in
which participants generated both positive and negative autobiographical episodic memory
imagery at three time points. At the first and third time points, imagery generation took
place without a concurrent imagery interference task, whereas at the second time point,
imagery interference was produced by concurrent performance of a lateral eye-movement task
and viewing of dynamic visual noise, in counterbalanced order. Concurrent imagery
interference was successful in reducing the vividness ratings for negative (but not
positive) memories, as compared to the no-interference condition. Again, the critically
important finding was that performance of the concurrent task also served to dampen the
emotional impact of these memories. Clinical researchers have also begun to harness the
potential for concurrent tasks to reduce the emotional impact of processing affectively
toned mental imagery. The use of a concurrent mathematics task during recall of real-life
collective trauma has been shown to reduce the emotional impact of recalling the traumatic
event in the general population (Engelhard, van den Hout, & Smeets, 2011). Likewise, it
has been shown that performance of a concurrent capacity-consuming task reduces the
emotional impact of thinking about feared future events in healthy participants
(Engelhard, van den Hout, Janssen, & van der Beek, 2010), in students who report high
frequency of intrusive future fear imagery (Engelhard, van den Hout, Dek, et al., 2011),
and in clinical patients with PTSD (Lilley, Andrade, Turpin, Sabin-Farrell, & Holmes,
2009). Lilley et al. (2009) asked a group of patients with PTSD to generate trauma-related
mental imagery while engaging in concurrent lateral eye movements, counting out loud, or
performing no concurrent task. Participants in the eye-movement condition reported the
lowest levels of imagery vividness, followed by those in the phonological counting
condition, while participants in the no-concurrent task control condition reported the
highest levels of imagery vividness. The intensity of negative emotion experienced by
participants during this procedure followed this exact same function, being lowest in the
participants who performed the concurrent eye movement task, intermediate in those who
performed the concurrent phonological counting task, and highest in those who performed no
concurrent task. Thus, manipulating the vividness of mental imagery through the use of
this concurrent task approach served to influence the emotional impact of processing
trauma-relevant information. In addition to voluntarily generated imagery, researchers
investigating intrusive flashbacks in PTSD have also begun to evaluate the possibility
that capacity-consuming concurrent tasks may also be capable of reducing the frequency and
emotional impact of involuntary mental imagery. There is growing evidence that playing the
visuospatial computer game “Tetris” following exposure to analogue trauma reduces the
frequency of subsequent involuntary memory imagery. Holmes, James, Coode-Bate, and
Deeprose (2009) had healthy participants view film clips depicting traumatic scenes, then
either play the visuospatial game Tetris after film viewing, or not. Participants used a
diary to report intrusive imagery of the film clip content over the following week.
Participants who played Tetris after film viewing reported experiencing fewer such imagery
intrusions, relative to those who had not. This effect appears to be modality-specific, as
playing a predominantly verbal “pub quiz” game after film viewing did reduce subsequent
imagery intrusions to the same degree as playing Tetris (Holmes, James, Kilford, &
Deeprose, 2010). Subsequent studies have also found Tetris game play to be effective in
reducing intrusive memory frequency when memories were reactivated 24 hours after initial
film viewing (James et al., 2015). Future research could profitably investigate whether
Tetris alleviates imagery intrusions in PTSD symptoms specifically because of visuospatial
disruption (James et al., 2015) or as a result of more general working memory taxation
(Van den Hout & Engelhard, 2012), as investigators remain divided in their views
concerning this issue.

<h>SECTION II: MENTAL IMAGERY-EVOKED EMOTIONAL RESPONSE IN PSYCHOPATHOLOGY</h>
-----------------------------------------------------------------------

Mental imagery-evoked emotional responses have been used to study emotional
psychopathology, primarily in anxiety research. Evidence has revealed variations in neural
and physiological responses across anxiety disorder subtypes. For example, while there is
evidence that, overall, anxiety patients exhibit greater amygdala and insula activity
during aversive imagery and picture viewing relative to healthy controls, this
hyperactivation is more evident in social anxiety disorder and specific phobias compared
to PTSD (cf. Etkin & Wager, 2007). Similarly, during fear relative to neutral memory
imagery, specific and social phobics showed greater increases in heart rate and startle
reflex response (but not skin conductance) compared to healthy participants (Cuthbert et
al., 2003). However, those with panic disorder and PTSD showed hyporeactivity relative to
healthy controls, even when baseline heart rate and startle potentiation were taken into
account (Cuthbert et al., 2003). Using the same paradigm, McTeague et al. (2010) found
that while PTSD patients generally exhibited greater increases in heart rate and startle
reflex response (but not in skin conductance) compared to healthy controls, more severe
multitrauma PTSD patients showed blunted heart rate, skin conductance, and startle reflex
responses compared to single-trauma PTSD patients (McTeague et al., 2010). Indeed, reduced
neural fear responding has been linked to the dissociative subtype of PTSD, characterized
by symptoms of depersonalization and derealization, symptoms associated with higher trauma
severity and chronicity (Lanius, Brand, Vermetten, Frewen, & Spiegel, 2012). Blunted
neurophysiological reactivity to aversive imagery is hypothesized to be attributable to
the effects of chronic stress and depression comorbidity, which appears to be more evident
in individuals with pervasive anxiety-based disorders rather than focal fear-based phobias
(for a review, see Lang & McTeague, 2009).

<hs>  Concordance Between Subjective and Physiological Response to Emotional Mental Imagery in Psychopathology</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Variations in the level of concordance between subjective emotional distress and
physiological arousal during aversive mental imagery have also been investigated as an
indicator of emotional psychopathology. This section will review studies that have
assessed the level of concordance between self-report, physiological and neural measures.
In healthy volunteers, there is evidence of concordance between self-report and
physiological indicators of emotional responding. For example, in a study with healthy
volunteers reporting high fear of snakes or public speaking, Lang et al. (1983, Experiment
2) found concordance between self-report and physiological indicators of arousal during
fear-imagery, though only when participants had been trained beforehand to focus on their
own somatic responses during imagery, and not when participants instead had been trained
to focus on visual perceptual information about the stimuli. Similarly, Dalgleish et al.
(2013) found concordant variation in subjective reports and physiological indicators (skin
conductance and heart rate) of emotional responses during imagery of personal memory
imagery of fear, anger, happiness and sadness, in 41 out of 53 participants. In anxiety
disorders, Lang and colleagues found enhanced self-reported distress and heart rate and
skin conductance reactivity during imagery of personal phobic stimuli relative to personal
non-phobia-related stimuli and standardized stimuli (Cook, Melamed, Cuthbert, McNeil, &
Lang, 1988). Interestingly, the congruence between levels of subjective distress and
physiological fear response was greatest in participants with simple phobias, followed by
those with social phobia, with the least congruence found in those with agoraphobia (Cook
et al., 1988). Similarly, McNeil, Vrana, Melamed, Cuthbert, and Lang (1993) assessed
aversive imagery in volunteers and clinically anxious patients with simple and social
phobias, and found that subjective reports of imagery vividness and emotional distress
were positively related to heart rate reactivity in those with simple phobias (e.g.,
dental surgery) but not in those with social (speech) phobia. As reviewed in Lang and
McTeague (2009), subjective reports of emotional distress in anxiety disorders are not
always accompanied by concordant levels of physiological fear response, at least for
startle potentiated reflex responses. Whereas exaggerated startle reflex response is found
in patients with specific and social phobia during phobic imagery and picture-viewing,
blunted startle response is found in patients with more severe anxiety profiles, such as
those with agoraphobia, panic disorder, generalized anxiety disorder (GAD), and comorbid
depression (Lang & McTeague, 2009). Indeed, physiological response to aversive mental
imagery appears to be negatively related to disorder chronicity, severity, and depression-
comorbidity, possibly reflecting suppressed defensive reactivity due to long-term stress
(McTeague & Lang, 2012). However, the view that chronic anxiety is associated with
negative emotional suppression is inconsistent with the Contrast Avoidance Model of worry
(Newman & Llera, 2011). This model postulates that individuals with GAD defensively
recruit a perpetuated negative emotional state to emotionally prepare for unexpected
negative events. Preliminary evidence in support of this model is provided by the finding
that worry-induction in healthy volunteers and GAD patients increases negative emotional
states at both subjective and physiological (skin conductance) levels, preventing further
increases during exposure to negative imagery (Peasley-Miklus & Vrana, 2000) and film
clips (Llera & Newman, 2014). The presence of ceiling effects in negative emotional
reactivity to imaginal and real aversive stimuli should be further investigated in GAD and
other anxiety-disorder subtypes.

SECTION III: THE IMPACT OF MENTAL IMAGERY ON EMOTION—A COMPARISON WITH VERBAL REPRESENTATION
--------------------------------------------------------------------------------

Section I reviewed evidence that mental-imagery-based representations of emotional
information elicit emotional responses at physiological, neurological, and subjective
levels. However, as noted earlier, such studies did not contrast mental imagery to an
alternative mode of representation of the same information, and therefore it is unknown
whether the effects observed during emotional imagery reflect an impact of emotional
information processing in general or mental imagery per se. This section reviews studies
that have attempted to answer this question by contrasting mental imagery to verbal
representations of emotional information. In several studies, Lang and colleagues compared
the impact of mental imagery versus verbal information processing of fear-related and
neutral sentences (Cuthbert et al., 2003; Vrana et al., 1986). Participants were
instructed either to generate mental imagery based on previously memorized fearful
sentences, or to verbally repeat the sentences in silence without generating accompanying
mental imagery. Results showed significant and sustained heart rate acceleration relative
to baseline during mental imagery, but not during verbal repetition of fearful scenarios
(Cuthbert et al., 2003; Vrana et al., 1986). This suggests that mental-imagery-based
processing of emotional information has a greater impact on emotion than verbal
processing. However, several experimental design issues constrain the interpretation of
these results. First, self-reported emotional impact was elicited only following mental
imagery of scenarios in Vrana et al. (1986), but not following verbal repetition of
scenarios. Thus, it is unclear whether imagery-based processing led to greater subjective
emotional response compared to verbal-based processing of the same information (Holmes &
Mathews, 2005). Second, due to prior memorization of the cue sentences, participants
necessarily engaged in verbal processing of the scenarios prior to completing both mental
imagery and verbal repetition conditions. Thus, it is difficult to determine whether
differences in emotional response between the imagery and verbal processing conditions
simply reflect the recruitment of an additional representational system in the imagery
condition (Holmes & Mathews, 2005). Finally, while participants in the imagery condition
elaborated on sentence content by simulating them as a personal experience, those in the
verbal condition simply repeated the sentences. Thus, it is possible that differences in
the level of semantic elaboration between the conditions contributed to differences in
observed physiological response. Following Vrana et al. (1986), a series of studies
conducted more controlled comparisons of the subjective emotional impact of mental imagery
versus verbal processing of emotionally negative information. A commonly used experimental
paradigm has involved exposing participants to scenarios that, while initially ambiguous,
ultimately resolved in a manner that produces an emotionally valenced representation of
the described situation. Experimenters have contrasted the emotional impact of
manipulating whether these representations are imagery-based or verbal in nature. Thus,
for example, Holmes and Mathews (2005) instructed healthy participants to either generate
imagery or focus on the semantic meaning of 100 such initially ambiguous auditory
scenarios that always resolved negatively (“You are at work when you hear the fire alarms
go off. You run to the exit to discover that it is . . . for real”). Holmes and Mathews
(2005) found that participants in the imagery condition reported greater increases in
self-reported anxiety as measured using the Spielberger State Anxiety Inventory (STAI-S;
Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983) (Experiment 1: M = 7.3; Experiment 2:
M = 5.67), relative to the verbal condition (Experiment 1: M = 1.9; Experiment 2: M =
1.55). Importantly, the enhanced emotional impact of mental imagery relative to verbal
processing is not restricted to negative material. Using a similar experimental approach,
but employing initially ambiguous auditory sentences that always resolved positively,
Holmes, Mathews, Dalgleish, and Mackintosh (2006) found healthy participants in the mental
imagery generation condition reported greater increases in positive affect (M = + 7.15, SD
= 10.30) than those in the verbal condition (M = -6.08, SD = 9.63), as measured using the
Positive and Negative Affect Schedule (PANAS-X; Watson & Clark, 1994). This effect of
greater emotional impact of imagery relative to verbal processing has since been
replicated in several studies (Holmes, Coughtrey, & Connor, 2008; Holmes, Lang, & Shah,
2009; Nelis, Vanbrabant, Holmes, & Raes, 2012; Pictet, Coughtrey, Mathews, & Holmes,
2011). In addition to transient effects on positive emotion, the impact of positive mental
imagery has been shown to persist in the short term. Holmes, Lang, & Shah (2009) asked
healthy participants to complete the task described above, and subsequently exposed these
participants to a negative mood induction procedure. Participants in the imagery condition
experienced a less severe decrement in positive mood following the negative mood induction
procedure (PANAS M = -4.90, SD = 6.88) than did those in the verbal condition (PANAS M =
-10.90, SD = 8.33). Consistent with research on the buffering effects of positive mood on
negative mood (Fredrickson, 1998), Holmes, Lang, & Shah (2009) results suggest that
positive mental imagery may have a greater potential to buffer the emotional impact of a
negative mood induction than does positive verbal thought. The experimental approach
adopted by Holmes and colleagues differs from that employed by Vrana et al. (1986) in two
important ways. First, participants in the verbal representation condition were instructed
to form meaningful representations of the auditory scenario, requiring them to engage in
semantic processing rather than simply engage in verbal repetition of the information, as
was the case in Vrana et al.’s approach. Second, subjective emotional response to the
information was compared when this was represented in an imagery format and in a verbal
format. Thus, while Vrana et al. (1986) were able only to conclude that imagery-based
representations exert an impact on subjective emotional experience, Holmes and colleagues
have been able to demonstrate that imagery-based representations exert a greater impact on
subjective emotional experience than do verbal representations. In the studies described
above, the information that participants were required to represent was always presented
in a verbal format. Thus, it could be the case that the greater emotional impact of the
imagery condition reflects the fact that the information is represented in two modalities,
both verbal and imagery, while in the verbal condition the information is represented in
only a single modality (Pictet & Holmes, 2013). To address this issue, an alternative
experimental paradigm, the Picture-Word Task (PWT), was developed (Holmes, Mathews,
Mackintosh, & Dalgleish, 2008). In the PWT, cue items consist of both a visual image and a
negative or benign word caption (e.g., a picture of a person in a lake accompanied by the
word sink or swim). Participants are asked to combine the picture and the word using
either imagery (“form a mental image that combines the next picture and word”) or verbal
statement (“form a sentence that combines the next picture and the word”). Thus, in this
design, the stimulus materials are comprised of image-based and verbal information.
Results from the PWT were consistent with the previous finding that imagery-based
representation evoked a stronger impact on subjective emotional experience than verbal
representation of the same information. Specifically, Holmes, Mathews, Mackintosh, &
Dalgleish, 2008 found that using mental imagery to combine negative picture-word cues
resulted in greater increases in anxiety (M = + 7.06, SD = 5.84) than did the use of
verbal processing to combine these cues (M = + 2.43, SD = 3.01); and using mental imagery
to combine benign picture-word cues resulted in a greater reduction in anxiety (M = -3.81,
SD = 5.94) than did the use of verbal processing to combine these cues (M = + 1.0, SD =
2.22). Therefore, on the basis of the reviewed evidence, it is appropriate to conclude
that imagery-based processing of emotional information has a greater impact on subjective
emotional experience than does verbal processing of the same information. In relation to
Lang’s original postulation that only mental imagery has the capacity to activate
physiological and behavioral response systems, evidence from studies on anxiety suggests
that more verbal forms of thinking, such as worry, can also impact cardiovascular
(Brosschot, Pieper, & Thayer, 2005; Llera & Newman, 2010) and neural activity consistent
with a negative emotional response (Oathes et al., 2008). We also note here that worry has
been defined as “a chain of thoughts and images, negatively affect-laden and relatively
uncontrollable” (Borkovec, Robinson, Pruzinsky, & DePree, 1983).

SECTION IV: HARNESSING MENTAL IMAGERY’S POWERFUL EMOTIONAL IMPACT IN CLINICAL PRACTICE
--------------------------------------------------------------------------------

When Lang's (1979) bio-informational theory of emotional imagery was developed,
behaviorism was the dominant approach within clinical psychology. At this time, mental
imagery was used to evoke emotion during imaginal exposure treatment of anxiety disorders
to help clients learn new emotional and behavioral responses and train self-control
(Goldfried, 1971) via graded imaginal desensitization (Wolpe, 1958) or rapid flooding to
feared stimuli (Wolpe, 1973). Developments in cognitive and social psychology in
subsequent decades has shown that an individual’s thoughts can exert a strong influence on
his/her behavior and wellbeing. As a result, the content and phenomenology of an
individual’s mental imagery-based thoughts have themselves become the subject of analysis
and modification (A. T. Beck, 1970; Lazarus, 1968). Building upon Judith Beck’s cognitive
therapy imagery formulations (J. S. Beck, 1995), new mental imagery techniques have been
brought into the clinic. The following section will briefly review contemporary cognitive
and behavioral (CBT) therapeutic techniques that have built upon the legacy of Lang’s
early work, which include: (a) imaginal exposure, (b) the direct modification of the
content of aversive imagery-based thoughts, (c) the promotion of adaptive imagery, (d)
metacognitive reappraisal of imagery, and (e) imagery-based cognitive modification of
maladaptive thinking habits. Imaginal exposure (IE) treatments are still widely used in
contemporary clinical practice, with a strong evidence base for treating anxiety disorders
ranging from specific phobias (Craske, Antony, & Barlow, 2006), obsessive-compulsive
disorder (Abramowitz, Franklin, & Foa, 2002), generalized anxiety disorder (Zinbarg,
Craske, & Barlow, 2006), to PTSD (Foa et al., 2007). Seminal advances in mechanistic
understandings of fear extinction learning and habituation have been informed by the
legacy of Lang’s bio-informational theory and experimental work (e.g., Lang, Melamed, &
Hart, 1970). Specifically, it has been proposed that for extinction learning and
habituation to occur in imaginal exposure therapy, the imagined feared stimulus itself
must evoke fear processing structures in the brain, including both stimulus and response
networks (Foa & Kozak, 1986). Evidence for this central mechanism of change comes from the
numerous subsequent studies showing that patients who exhibit initial physiological fear
responses and subsequent habituation of such responses benefit more from imaginal exposure
therapy than those who do not (Craske, Sanderson, & Barlow, 1987; Jaycox, Foa, & Morral,
1998; Kozak, Foa, & Steketee, 1988; Mueser, Yarnold, & Foy, 1991). There is increasing
evidence that the efficacy of IE, at times combined with other behavioral or cognitive
treatments, is superior to psychopharmacology for OCD (Foa et al., 2005) and PTSD (Van
Etten & Taylor, 1998). For GAD, IE-based CBT has been found to be more effective than
nondirective and relaxation-based techniques (Borkovec & Costello, 1993). Interestingly, a
growing body of research has used virtual reality simulations during exposure therapy to
treat a range of anxiety disorders (for reviews see Opriş et al., 2012; Morina, Ijntema,
Meyerbröker, & Emmelkamp, 2015). Preliminary evidence suggests that exposure treatments
using mental imagery simulations (IE) versus virtual reality simulations of feared stimuli
have comparable efficacy for fear of flying (Rus-Calafell, Gutiérrez-Maldonado, Botella, &
Baños, 2013) and public speaking (Wallach, Safir, & Bar-Zvi, 2009). In addition to anxiety
disorders, researchers have also successfully used IE to reduce intrusive mental imagery
in major depression, with promising results in terms of therapeutic benefits (Kandris &
Moulds, 2008). Imagery rescripting techniques designed to directly modify the content of
emotion-inducing mental imagery have been developed, helping clients transform their
unwanted distressing imagery into more benign forms (Hackmann, Bennett-Levy, & Holmes,
2011). Such techniques have been combined with exposure treatment for a range of
disorders, from PTSD and personality disorders (e.g., Arntz & Weertman, 1999; Butler &
Holmes, 2009; Long & Quevillon, 2009; Smucker & Dancu, 1999/2005), to snake and social
phobia (Hunt & Fenton, 2007; Wild, Hackmann, & Clark, 2007). For PTSD, evidence suggests
that imaginal exposure therapy combined with imagery rescripting is more effective than
imaginal exposure therapy alone (Arntz, Tiesema, & Kindt, 2007; Grunert, Weis, Smucker, &
Christianson, 2007). Imagery rescripting has also been used to reduce intrusive mental
images in healthy populations (Rusch, Grunert, Mendelsohn, & Smucker, 2000) and in people
with depression (Brewin et al., 2009). Rescripting of intrusive imagery associated with
negative memories has shown initial promise as a stand-alone treatment for major
depression (Brewin et al., 2009). For a detailed review of imagery rescripting treatments,
see Arntz (2012) and Holmes, Arntz, and Smucker (2007)). In addition to the development of
clinical techniques intended to attenuate negative imagery, clinical investigators have
also sought to develop methods of fostering the generation of positive imagery, to help
clients build more adaptive relationships between self, others, and the world (Hackmann et
al., 2011). Symbolic positive imagery has been used to help clients access adaptive
emotional states, in interventions such as Compassion Mind Training (CMT; P. Gilbert,
2009), which was inspired by work on the perfect nurturer image by D. A. Lee (2005). Other
positive imagery techniques include guiding clients to construct and road test ideal ways
of being in personality disorders (Mooney & Padesky, 2000) or to form mental images of
positive scenarios to counter the types of negative beliefs observed in personality
disorders, eating disorders, and obsessive-compulsive disorder (Korrelboom, de Jong,
Huijbrechts, & Daansen, 2009). Positive imagery can also be used to attenuate or replace
negative imagery in vivo. In social anxiety, generating and holding in mind positive
images of one’s own appearance, to displace negative images of oneself appearing red and
sweaty, has been shown to reduce anxiety and improve social performance (Hirsch, Mathews,
Clark, Williams, & Morrison, 2003). Positive imagery has also been shown to function as an
effective distractor for chronic pain patients (Fors, Sexton, & Gotestam, 2002). A third
category of imagery-focused interventions aims not to directly alter potentially
distressing negative mental imagery but rather to change how the patient thinks about
these images, in ways that reduce their emotional impact. Metacognitive strategies aim to
down regulate the impact of distressing mental imagery via reappraisal (Gross, 2002).
Techniques include encouraging patients to perceive mental images as subjective phenomena
(Wells, 2003) rather than meaningful premonitions or signs that one’s mind is out of
control (Starr & Moulds, 2006; Williams & Moulds, 2007). Another approach is mindfulness-
based cognitive therapy, in which clients are trained to regard their verbal thoughts and
mental images as mere passing mental phenomena that do not require a response (Segal,
Teasdale, & Williams, 2002). More recent developments in experimental clinical research
have begun to develop mental imagery-focused cognitive training informed by cognitive bias
modification (CBM) paradigms. CBM aims to reduce maladaptive imagery styles and boost
adaptive imagery via computer-based training (Blackwell et al., 2015; Williams et al.,
2015). Such mental imagery training approaches are informed by research that has
illuminated psychopathology-linked individual differences in imagery, which will be
discussed in more detail with the next section of this review. Hence, clinical practice is
increasingly harnessing the power of mental imagery to facilitate adaptive emotional
functioning. The efficacy of such approaches may be further enhanced by future research
designed to illuminate the potentially critical role of variability in the strength of the
emotional response, observed during imagery in the clinic, in determining treatment
outcomes. Given that the elicitation of both subjective and physiological emotional
responses during imaginal exposure is a central mechanism of change in the successful
treatment of fear, the effectiveness of other treatments that use mental imagery to
optimize emotional functioning may also depend on the client’s emotional response during
imagery. In our view, research investigating differences between treatment responders
compared to nonresponders in the emotional impact of mental imagery may prove fruitful in
informing future translational research in this field.

SECTION V: INDIVIDUAL DIFFERENCES IN MENTAL IMAGERY AND EMOTIONAL PSYCHOPATHOLOGY
--------------------------------------------------------------------------------

So far, this review has discussed mental imagery in terms of its capacity to evoke
emotional responses, the presence of disorder-linked variations in this emotional
response, and the ways that clinical practice has harnessed mental imagery to facilitate
emotional processing. However, one relatively neglected aspect of mental imagery that is
of potential clinical significance is differences across individuals in the ability and
tendency to experience emotional imagery. Here, “ability” is simply defined as the
deliberate generation of imagery, and “tendency” as the nondeliberate (i.e., spontaneous)
generation of imagery. This section will review research on individual differences in
emotional mental imagery tendency and ability in both healthy and clinical populations. An
interesting finding from Lang’s experimental work on the emotional impact of mental
imagery is the observation that the level of emotional response experienced during imagery
is related to how vividly an individual can generate mental imagery in general (imagery
generation ability). Lang and colleagues found that, in healthy participants, heart rate
acceleration during fearful imagery was more pronounced in individuals with high imagery
ability, relative to those with low imagery ability, as assessed by a self-report
questionnaire (Miller et al., 1987). However, such a relationship between self-reported
imagery ability and physiological arousal during fear imagery is not always observed.
McTeague, Bradley, and Lang (2002) found no association between imagery ability and
physiological reactivity during emotional imagery, whether such reactivity was indexed by
autonomic responses (heart rate, skin conductance), facial EMG (corrugator and
orbicularis), or startle blink reflex. Relatively few studies have examined individual
differences in mental imagery and its relationship to imagery-based treatment outcomes in
clinical populations. McNeil et al. (1993) found that physiological reactivity and
subjective reports of distress were greater in individuals with higher relative to lower
self-reported imagery generation ability. However, this effect was only observed in
individuals with specific phobias (e.g., dental), and not in those with social anxiety. In
chronic PTSD patients undergoing prolonged imaginal exposure treatment, Rauch, Foa, Furr,
and Filip (2004) found that participants’ self-reported anxiety and imagery vividness were
correlated, and both decreased significantly during treatment. However, while subjective
anxiety change was related to treatment outcome, imagery vividness change was not
significantly related to treatment outcome (Rauch et al., 2004). Given these mixed
results, it presently remains uncertain how robust a difference there exists in the
intensity of emotional responding to imagery, between people who exhibit good and poor
imagery ability, and how these differences relate to imagery-based treatment outcomes. The
resolution of issue clearly requires further research. In recent years, researchers have
begun to investigate whether bias in the relative ability to generate mental imagery of
emotionally negative compared to emotionally positive scenarios may be associated with
emotional psychopathology. Several studies have used the Prospective Imagery Task (PIT;
Holmes, Lang, Moulds, & Steele, 2008; Stöber, 2000) to assess imagery vividness. In this
task, participants are required to generate mental imagery cued by negative and positive
sentences depicting self-referential future scenarios (e.g., negative scenario: “You will
be the victim of crime”; positive scenario: “You will have lots of energy and
enthusiasm”). Results from such studies indicate that, compared to healthy controls,
individuals with depressed mood (Holmes, Lang, Moulds, & Steele, 2008), and those with a
diagnosis of clinical depression or anxiety (Morina, Deeprose, Pusowski, Schmid, & Holmes,
2011) report lower imagery vividness (i.e., visual clarity) for positive scenarios.
Participants with depressed mood (Holmes, Lang, Moulds, & Steele, 2008) and anxiety
disorders (Morina et al., 2011) also report greater vividness of imagery for negative
scenarios compared to healthy controls, though this latter effect is not observed in
clinically depressed participants (Morina et al., 2011). In addition, researchers have
begun to move beyond cross-sectional data and to examine temporal relationships between
imagery vividness and emotional psychopathology. Blackwell et al. (2015) conducted a
randomized controlled trial in which 150 depressed adults received either a positive
imagery intervention involving repeated generation of mental imagery involving pleasant
daily activities, or a nonimagery “sham training” control condition, both delivered via
the Internet over 4 weeks. Results indicate that the more vividly participants in the
positive imagery condition could imagine the positive training scenarios at baseline, the
greater their reduction in depression symptoms over the course of the intervention
(Blackwell et al., 2015). Future studies should more directly assess the relationship
between changes in imagery vividness and changes in symptomology. Researchers have also
started to explore disorder-linked individual differences in the tendency to spontaneously
experience emotional mental imagery in daily life. Negative self-concept in unselected
undergraduate students has been found to be positively associated with the frequency of
retrospectively reported negative spontaneous cognitions, consisting predominantly of
imagery-based memories of past negative experiences (Krans, de Bree, & Moulds, 2015). It
has also been shown that, compared to formerly-depressed and never-depressed individuals,
depressed individuals report experiencing spontaneous imagery-based memories, which were
predominantly negative in content, as more vivid, evoking greater subjective distress, and
causing greater disruption to daily life (Newby & Moulds, 2011). Future emotional
psychopathology-linked individual differences research may benefit from obtaining
convergent measures of emotional response during mental imagery, such as measures of
physiology and hemodynamic neural activity. In addition to indices of emotional response
during imagery, electroencephalography (EEG) measures of cortical brain electrical
activity may provide indices of the level of cognitive resources expended during imagery
as an additional measure of the impact of emotional imagery. One recent study from Lang
and colleagues examining alpha-band activity during emotional mental imagery suggests EEG
may provide an objective measure of neural activity involved in semantic, motor, and
perceptual representations of emotional stimuli. Bartsch, Hamuni, Miskovic, Lang, and Keil
(2015) found that while mental imagery elicited by pleasant and unpleasant verbs prompted
equivalent levels of alpha amplitude, both were higher than that observed during imagery
of emotionally neutral verbs. Alpha-band (8-12 Hz) activity is associated with internally
directed attention and may be used to index individual differences in emotional imagery-
related brain activity in translational and clinical research. Could it be that individual
differences in imagery-based processing of verbal information causally underpins
vulnerability to emotional psychopathology, and/or functionally contributes to its
maintenance? So far, research linking individual differences in emotional mental imagery
generation and emotional psychopathology has been correlational in nature. More
experimental research is required to investigate if and how the ability and tendency to
experience emotional mental imagery is causally related to emotional wellbeing and
dysfunction. Several mechanisms have been proposed and require further investigation. One
hypothesis is that mental imagery acts as an emotional amplifier and exacerbates states of
mood instability, such as in bipolar disorder (Holmes, Geddes, Colom, & Goodwin, 2008).
From a treatment perspective, enhancing the ability to mentally simulate positive
scenarios may causally relate to improved emotional functioning via cognitive and
behavioral mechanisms such as enhanced negative mood repair, and/or increased anticipatory
pleasure and approach motivation for daily activities. The outcomes of such future
research will inform how best to exploit our increasing understanding of individual
differences in mental imagery in ways that can enhance the efficacy of our therapeutic
interventions for clinical anxiety and depression.

SECTION VI: NEGLECTED INSIGHTS FROM LANG’S WORK ON MENTAL IMAGERY EMOTIONAL RESPONSE TRAINING
--------------------------------------------------------------------------------

A critical yet largely overlooked finding from Lang’s (1977, 1979) experimental work is
the demonstration that the emotional impact of imagery can be modulated via training.
Lang’s psychophysiology studies provided reliable evidence that physiological arousal
during mental imagery of fearful scenes can be increased in two ways. One is via the
inclusion of somatovisceral response information in the verbal scripts used to cue imagery
(e.g., “your heart is pounding”). The other is via the positive reinforcement of
participants’ verbal reports of mental imagery containing somatovisceral response during
an initial training phase (e.g., “I felt myself running down the hill fast . . . my heart
was beating”). Several studies by Lang and colleagues have demonstrated that such imagery
training amplified participants’ ability to elicit physiological responses during imagery
(Lang, Kozak, Miller, Levin, & McLean, 1980; Lang et al., 1983; Miller et al., 1987). As
discussed earlier, the effectiveness of imaginal exposure therapy rests partly on the
presence of initial emotional arousal to the imaginal feared stimuli. Thus, training that
enhances emotional response during negative imagery may improve fear-extinction treatment
outcomes. Furthermore, training that can increase the emotional impact of mental imagery
may serve to enhance the effectiveness of positive imagery interventions for clinical
patients who exhibit deficits in positive imagery. As described earlier, the cognitive
bias modification approach has recently been combined with mental imagery training to
target interpretation bias in both mood and anxiety disorders. Imagery-based
interpretation bias modification (IBM) training involves repeatedly generating imagery in
response to verbal sentences and picture-word pairs depicting hypothetical everyday
scenarios that resolve positively. Experimental studies have shown that imagery-based IBM
training of this nature improves mood to a greater degree than does verbal-based IBM
training (Holmes, Lang, et al., 2009; Holmes et al., 2006; T. Lang, Blackwell, Harmer,
Davison, & Holmes, 2012). To date, several randomized-controlled clinical trials have been
conducted, with mixed preliminary findings. While results from two such trials indicate
positive imagery IBM training to be a promising and accessible Internet intervention for
improving mood and alleviating symptoms in depression (Williams, Blackwell, Mackenzie,
Holmes, & Andrews, 2013; Williams et al., 2015), another trial found no support for the
positive IBM imagery condition being better than a non-imagery-focused, noninterpretation
training, control condition (Blackwell et al., 2015). It seems reasonable to suppose that
the efficacy of this imagery-based IBM training would be further enhanced by increasing
the positive emotional impact of the trained pattern of positive imagery. This objective
may be served by integrating the somatovisceral response amplification techniques,
developed by Lang and colleagues, into imagery-based IBM programs designed to increase the
occurrence of positive imagery, which represents an important avenue for future research
in this area.

<h>SECTION VII: CONCLUSION AND FUTURE DIRECTIONS</h>
---------------------------------------------

Charting the progress of emotional mental imagery research across the past five decades
since Lang’s (1977) seminal paper has clearly illustrated the major impact of his bio-
informational theory and experimental research on this field. Following Lang’s footsteps,
both experimental and translational researchers have continued to be fascinated by the
special relationship that exists between mental imagery and emotion. In emphasizing mental
imagery’s capacity to activate perceptual stimulus representations as well as
physiological and behavioral responses, Lang’s theory and experimental work provided
crucial insights into the field of behavior therapy. Specifically, physiological fear
response during imagery of feared stimuli has been identified as the marker of successful
learning during imaginal exposure and habituation. In light of this finding, evidence
reviewed in Section I showing blunted physiological fear response in patients suffering
more chronic anxiety and mood dysfunction represents a serious concern in the clinical
field. Specifically, it suggests that such individuals may require additional support to
enhance physiological responding in order to maximally benefit from the corrective effects
of imaginal (or in vivo) exposure therapy. Given that the success of imaginal exposure
therapy in facilitating fear-extinction hinges upon the patient exhibiting initial
physiological arousal to the imagined fear stimuli, the efficacy of other CBT treatments
using mental imagery to facilitate emotional processing may also be enhanced by taking
steps to ensure that emotional responses to mental imagery are maximized. Future clinical
translational and treatment efficacy research may well benefit from using training
techniques pioneered by Lang to keep affect “hot” during critical moments in therapy.
Recent individual differences research has begun to illuminate how bias in the relative
ability to voluntarily generate emotional imagery, and bias in the tendency to
spontaneously experience emotional imagery, differentiates those experiencing emotional
disturbance from healthy individuals. This line of experimental research has important
clinical implications, as an excess of unwanted emotional mental imagery requires
therapeutic alteration. Further, the inability to generate positive imagery, or inability
to respond to negative imagery, has treatment implications for depression and exposure
therapy. Particularly promising is experimental research that investigates how the
relationship between mental imagery and emotion can be exploited for clinical benefit via
cognitive bias modification training. Future research on positive mental imagery training
could be enhanced by incorporating Lang’s method of emotional imagery response training,
using imagery-eliciting scripts that contain both stimulus and response information,
combined with training procedures that positively reinforce emotional responding during
mental imagery. Furthermore, measuring both subjective and neurophysiological indices of
emotional response during positive mental imagery training may provide additional
information in identifying treatment responders in future research. Nearly 40 years ago,
Lang’s seminal work on emotional imagery laid the foundation for a new era of experimental
and clinical research on this fascinating topic. While subsequent researchers have been
able to build upon this firm foundation in ways that have greatly expanded knowledge and
understanding, it is remarkable that Lang’s original questions, and the findings produced
by Lang and his collaborators, have remained of such central importance within the
burgeoning contemporary literature. We are confident that this will continue to be the
case across the years that lie ahead, and we are honored to have been given this
opportunity to celebrate, and pay tribute to, Lang’s extraordinary scientific and clinical
legacy.

<h>CONFLICT OF INTEREST STATEMENT</h>
------------------------------

The authors declare that there are no conflicts of interest.


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<ART>Emotional and behavioural problems in children with Developmental Coordination Disorder: Exploring parent and teacher reports
================================================================================

Authors: Laura Crane, Emma Sumner, Elisabeth L. Hill
DOI: 10.1016/j.ridd.2017.08.001
Year: 2017  |  Pages: 67-74
ASJC codes: 3203, 3204
Keywords: Developmental Coordination Disorder (DCD), Emotional symptoms, Hyperactivity, Motor impairment, Strengths and Difficulties Questionnaire (SDQ)

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<h>ABSTRACT</h>
--------

Background Although characterised by motor impairments, children with Developmental Coordination Disorder (DCD) also show high rates of psychopathology (anxiety, depression, low self-esteem). Such findings have led to calls for the screening of mental health problems in this group. Aims To investigate patterns and profiles of emotional and behavioural problems in children with and without DCD, using the Strengths and Difficulties Questionnaire (SDQ). Methods and procedures Teachers and parents completed SDQs for 30 children with DCD (7–10 years). Teacher ratings on the SDQ were also obtained from two typically-developing (TD) groups: 35 children matched for chronological age, and 29 younger children (4–7 years) matched by motor ability. Outcomes and results Group and individual analyses compared parent and teacher SDQ scores for children with DCD. Teacher reports showed that children with DCD displayed higher rates of emotional and behavioural problems (overall, and on each subscale of the SDQ) relative to their TD peers. No differences were observed between the two TD groups. Inspection of individual data points highlighted variability in the SDQ scores of the DCD group (across both teacher and parent ratings), with suggestions of elevated hyperactivity but comparably lower levels of conduct problems across this sample. Modest agreement was found between teacher and parent ratings of children with DCD on the SDQ. Conclusions and implications There is a need to monitor levels of emotional and behavioural problems in children with DCD, from multiple informants.

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<h>WHAT THIS PAPER ADDS</h>
--------------------

In this study, we present a detailed investigation of emotional and behavioural problems
in children with Developmental Coordination Disorder (DCD), using parent- and/or teacher-
report versions of the Strengths and Difficulties Questionnaire (SDQ). We used both group
and individual analysis, which enabled us to compare teacher-ratings of children with DCD
to typically developing children (those who were matched for age, as well as younger
children matched for motor ability), and to each other. Results demonstrated that there
was variability in the SDQ scores of DCD children (across both parents and teacher
ratings), but also some broad patterns; for example, individually, children with DCD
tended to show high levels of hyperactivity, but comparably lower levels of conduct
problems. For children with DCD, levels of agreement between parent and teacher ratings on
the SDQ were modest. This suggests that information on emotional and behavioural problems
in DCD should be collected from multiple informants.

<h>INTRODUCTION</h>
------------

Developmental Coordination Disorder (DCD, sometimes referred to as dyspraxia) affects
between 2 and 6% of children (American Psychiatric Association [APA], 2013; Lingam, Hunt,
Golding, Jongmans, & Emond, 2009) and is characterised by motor skills that are
significantly below age-expected levels, persisting despite opportunities to acquire and
develop these skills. These motor impairments must: have a significant impact on
activities of daily living and academic achievement; occur early in development; and not
be better accounted for by an alternative explanation (e.g., general medical conditions,
intellectual disabilities, visual impairments) (APA, 2013). There are several reasons why
children with DCD may present with emotional and behavioural difficulties. Despite being
of average or above average intelligence (APA, 2013; Sumner, Pratt, & Hill, 2016),
children with DCD often experience problems with school-related tasks (e.g., handwriting,
organising their workload, completing tasks on time) (Zwicker, Missiuna, Harris, & Boyd,
2012). DCD also negatively affects leisure participation (Zwicker et al., 2012), meaning
that children may become less likely to engage in group activities with peers (Chen &
Cohn, 2003), potentially leading to social isolation and loneliness (Missiuna, Moll, King,
Stewart, & MacDonald, 2008; Poulsen, Ziviani, Cuskelly, & Smith, 2007). Further, high
rates of psychopathology – including anxiety (Pratt & Hill, 2011) as well as depression
and low self-esteem (Lingam et al., 2012; Piek et al., 2007) – have been reported in
children with DCD. DCD also commonly co-occurs with other conditions, such as attention-
deficit-hyperactivity disorder (ADHD), which is often associated with emotional and
behavioural problems (Missiuna et al., 2014). There have been calls for the screening of
mental health problems in children with DCD (Rigoli & Piek, 2016), with the Strengths and
Difficulties Questionnaire (Goodman, 1997) being suggested as a suitable tool for
assessing possible psychosocial problems; both generally (Goodman, Ford, Simmons, Gatward,
& Meltzer, 2000) and in the DCD population (Rigoli & Piek, 2016). Using the parent-report
version of the SDQ in a sample of 47 children with DCD, Green, Baird, and Sugden (2006)
found that 62% of children with DCD showed ‘clinical’ levels of emotional and behavioural
difficulties (13% = ‘borderline’, 15% = ‘normal’).1 Further, 85% of the sample showed
‘significant’ problems in at least one of the five SDQ subscales (Emotional symptoms,
Conduct problems, Hyperactivity, Peer problems, Prosocial behaviours). Using the teacher-
report version of the SDQ, Van den Heuvel, Jansen, Reijneveld, Flapper, and Smits-
Engelsman (2016) reported children with DCD (n = 23) to have significantly greater
emotional and behavioural problems than typically developing (TD) (chronological age
matched) children. However, the proportion of children showing ‘clinical’ levels of the
Total difficulties scores (36%) was much lower than the 62% reported by Green et al.
(2006). Indeed, mean scores across all subscales of the SDQ were lower in Van den Heuvel
et al.’s (2016) sample, relative to Green et al.’s (2006) sample. This could be due to
Green et al. (2006) recruiting their sample from a clinic, whereas Van den Heuvel et al.
(2016) recruited their sample by screening large numbers of children and identifying those
with significant motor impairments (from a community-based school sample). Alternatively,
it could be due to the studies differing in their use of parent- versus teacher-report,
with teachers potentially rating the children’s difficulties as less severe. This may be
because teachers are less familiar with each child’s capabilities (relative to the
parents), therefore underestimating the child’s difficulties. Or, it could be because
teachers have a greater understanding of what typical performance is (due to working with
a large range of children) and are, therefore, less likely to overestimate any
difficulties. Indeed, a review of the psychometric properties of the SDQ highlighted only
modest agreement between parent- and teacher-reported scores on the SDQ (Stone, Otten,
Engels, Vermulst, & Janssens, 2010). The aim of the current investigation was to explore
emotional and behavioural difficulties using the SDQ in a sample of children with a
confirmed clinical diagnosis of DCD. First, we sought to confirm previous reports of high
levels of emotional and behavioural difficulties amongst children with DCD by comparing
teacher SDQ ratings of children with DCD to two groups of TD children: (1) a group matched
by chronological age (hereafter ‘CA’ group); and (2) a group matched based on motor
ability (motor-match, hereafter ‘MM’ group). The latter group was comparable to the DCD
group in terms of performance on a motor task but was, inevitably, younger than the DCD
group. Comparisons between these two groups provide an indication of whether the observed
profile of children with DCD reflects a level of immaturity, to some extent. The second
aim, focusing on the DCD group only, was to investigate levels of agreement between
parent- and teacher-report on the SDQ (unfortunately, we were not able to collect parent-
reported SDQ data from the TD children, to also explore this comparison in the CA and MM
groups). A meta-analysis comprising 14,811 children between the ages of 3–17 years (from a
range of typical and clinical populations), reported correlations between parent and
teacher SDQ ratings to be between 0.26 and 0.47 (Stone et al., 2010). As such, only
“modest” agreement was predicted in the current study. However, adopting group and
individual analyses to explore this research question allowed more detailed analyses than
has been undertaken in previous research. Further, it enabled us to explore individual
profiles of emotional and behavioural problems across the DCD group.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

As part of a broader study exploring the cognitive and behavioural profiles of children
with DCD (see Sumner, Hutton, Kuhn, & Hill, 2016; Sumner, Leonard, & Hill, 2016), 30
children with a diagnosis of DCD (21 boys, 9 girls, all aged 7–10 years) were recruited
through primary schools, as well as advertisements via a charitable organization (the
Dyspraxia Foundation, UK). Prior to taking part in the study (and independent of the
research study itself), children had received a diagnosis of DCD from a multi-disciplinary
team of clinicians who were external to the research team. The second edition of the
Movement Assessment Battery for Children (MABC-2; Henderson, Sugden, & Barnett, 2007) was
used to confirm a DCD diagnosis, and all children scored at or below the 16th percentile
on this measure. Additionally, on an initially screening questionnaire, parents confirmed
that there was no history of additional diagnoses or medical conditions that might explain
the child’s motor difficulties. The CA group comprised 35 children (26 boys, 9 girls, aged
7–10 years), whilst the MM group comprised 29 children (19 boys, 10 girls, aged 4–7
years), all recruited from primary schools in South London. In a screening questionnaire,
their parents reported no identified diagnosis of a neurodevelopmental condition,
including DCD. The MM group were screened based on the time taken to complete a peg
placing task as part of the MABC-2 (in which they had to place 12 pegs into a board as
quickly and accurately as possible, using both their preferred and non-preferred hands);
as reported in Sumner, Hutton et al. (2016) and Sinani, Sugden, & Hill (2011), who have
adopted similar approaches to matching. Raw scores were used for the motor matching
process (i.e., number of seconds taken) of children in the MM and DCD groups. After
screening peg placing time, all children in the MM group completed a standardised
assessment of their fine and gross motor skills to determine age-appropriate motor skills
(at or above the 25th percentile on the MABC-2), detailed below. Similarly, all children
in the CA group had to score at or above the 25th percentile on the MABC-2. Background
characteristics of the groups are presented in Table 1. This included a measure of
parental education, which has been used as a measure of socio-economic status in similar
studies (Fernald, Marchman, & Weisleder, 2013; LeBarton & Iverson, 2013), and was found to
be comparable across the groups.

        Wechsler intelligence scale for children (WISC-IV) and wechsler preschool and primary scale of intelligence (WPPSI-IV)

        The WISC-IV (Wechsler, 2003) and WPPSI-IV (Wechsler, 2012) were used to determine
        inclusion in the study, which required a Full-Scale IQ (FSIQ) >70 for all groups.
        FSIQ calculated from the WISC-IV comprises four indices and ten subtests (items
        per index shown in brackets): verbal comprehension (3 items), perceptual reasoning
        (3 items), working memory (2 items), and processing speed (2 items). From the
        WPPSI-IV, FSIQ is calculated from five indices and 6 subtests: verbal
        comprehension (2 items), visual spatial (1 item), fluid reasoning (1 item),
        working memory (1 item) and processing speed (1 item). Participants completed all
        subtests. The DCD and CA groups completed the WISC-IV, while the younger MM group
        completed the WPPSI-IV. The psychometric properties of these tests have been
        established from large, representative samples which confirm good reliability
        (including internal consistency above 0.88 for the four indices of the WISC-IV,
        and above 0.89 for the WPPSI-IV indices; and test-retest stability above 0.86 for
        the WISC-IV, and above 0.84 for the WPPSI-IV).

        <hss>Movement Assessment Battery for Children (MABC-2)</hss>

        Children completed the age-appropriate assessments (age band 1: 4–6 years; age
        band 2: 7–10 years) of the second edition of the MABC-2 (UK norms; Henderson et
        al., 2007). Each age band comprises three components: manual dexterity (3 items),
        aiming and catching (2 items), and static and dynamic balance (3 items). Scores
        from the eight items are summed to provide a total standard score (Mean = 10, SD =
        3) and percentile rank. The MABC-2 was used to confirm the diagnostic status of
        the DCD (i.e., at or below the 16th percentile) and to confirm age-appropriate
        abilities in both TD (i.e., at or above the 25th percentile) groups. Across
        studies that have addressed the psychometric properties of the MABC-2, reliability
        is considered good. Intra class correlations (ICCs) for test-retest reliability
        are reported between 0.77 and 0.95, and for inter-rater reliability ICCs have been
        reported at 0.95 and above (see Henderson et al., 2007, for details).

        <hss>Strengths and Difficulties Questionnaire (SDQ)</hss>

        The SDQ (Goodman, 1997) is a 25-item questionnaire that can be completed by
        parents or teachers (note: the questions asked are the same in both formats but
        the opening statement differs very slightly from ‘your child’ to ‘the child’,
        respectively). It comprises five scales (of five items each): Emotional symptoms
        (e.g., “Often unhappy, down-hearted or tearful”); Conduct problems (e.g., “Often
        has temper tantrums or hot tempers”); Hyperactivity (e.g., “Constantly fidgeting
        or squirming”); Peer problems (e.g., “Rather solitary, tends to play alone”); and
        Prosocial behaviours (e.g., “Considerate of other people’s feelings”). Ten of the
        questions are designed to tap the child’s strengths; 14 represent difficulties;
        and 1 item is neutral. Parents or teachers (depending on the informant) rate each
        question on a three-point scale (“Certainly True”, “Somewhat True”, “Not True”)
        and scores of 0, 1 or 2 are assigned (depending on whether the items are
        positively or negatively phrased). A ‘Total Difficulties’ score (ranging from 0 to
        40) is generated by summing scores from all of the scales except the Prosocial
        behaviours scale (as this reflects positive behaviours). As well as using SDQ
        scores as continuous variables, scores can be classified into ‘normal’,
        ‘borderline’ and ‘clinical2’ categories, and risk factors can be determined
        regarding Emotional disorders, Behavioural disorders and Hyperactive disorders
        (‘low risk’, ‘medium risk’, and ‘high risk’) (see www.sdqinfo.org). Data from a
        large, representative sample has confirmed satisfactory reliability (mean Cronbach
        α = 0.73; mean cross-informant correlation = 0.34; mean retest stability after 4–6
        months = 0.62) and validity (as assessed by comparing SDQ scores against
        independent psychiatric diagnoses) (Goodman, 2001).

<hs>  Procedure</hs>
  ~~~~~~~~~

Ethical approval was obtained from Goldsmiths, University of London. Written informed
consent was provided by all schools and parents/carers, while verbal assent was obtained
from the children that took part in the study. Children completed the cognitive and motor
assessments in two separate sessions either in their school (for the TD groups) or during
a visit to the research lab (for the DCD group). They were seen individually in a quiet
room. Parents of children with DCD completed the questionnaire during the visit to the
research lab, while teachers of children with DCD were sent a copy of the questionnaire
and asked to post the completed copy back to the research team. Teachers of the TD groups
completed the questionnaires during school time and returned them to a member of the
research team.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Tests of normality and homogeneity were conducted prior to test selection. Parametric
(paired samples t-test, ANOVA) and non-parametric equivalents (Kruskall-Wallis) were used
to investigate differences at the group level and when comparing teacher and parent
responses. Intra class correlations (ICCs) were also used, when comparing agreement
between teacher and parent ratings on the SDQ.

<h>RESULTS</h>
-------

Relating to the inclusion criteria for the study, Table 1 presents the background
characteristics of the three groups. The DCD and CA groups were significantly older than
the MM group. No significant differences were found between the CA and MM groups on FSIQ,
but the DCD were shown to have slightly lower FSIQ scores (although still scoring within
the average range for this test). FSIQ was not found to be correlated with any of the SDQ
measures (ps > 0.18) and, therefore, is not included in subsequent analyses. Finally, the
inclusion criteria for motor abilities were met for all three groups. Of note, 2 (7%)
children with DCD scored on the 16th percentile, while the remaining DCD participants
scored on the 9th (n = 6, 20%) or at or below the 5th percentile (n = 22, 73%).

<hs>  Teacher ratings of emotional and behavioural difficulties in children with and without DCD</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Data screening highlighted that SDQ Total Difficulties scores, as well as three SDQ
subtest scores (Emotional symptoms, Conduct problems, and Peer problems), were not
normally distributed (skewness values >1). Applying transformations to these data did not
result in the assumptions of normality being met, so non-parametric (Kruskall-Wallis)
tests were used. For the normally distributed variables (Hyperactivity, and Prosocial
behaviour), one way ANOVAs were used. Results demonstrated that teachers rated the DCD
group as showing greater levels of emotional and behavioural problems than their TD peers
(CA and MM matched) on all subscales of the SDQ, and in their overall scores (see Table
2). As can be seen in Table 2, the TD average scores were low in each subtest, except for
in the Prosocial behavior ratings where a higher score reflects more positive, prosocial
behaviour. Notably, none of the children in the two TD groups (CA or MM) scored in the
‘borderline’ or ‘clinical’ ranges on the SDQ Total Difficulties component (all scoring in
the ‘normal range’). Further, in relation to the subtest scores, teacher ratings
demonstrated only one ‘borderline’ case from the CA group in each of the following
categories: Emotional symptoms, Hyperactivity and Prosocial behaviour; in addition to, two
‘clinical’ scores on the Hyperactivity scale, three ‘borderline’ scores on the Prosocial
behaviour and one on the Peer problems scale from the MM group. Analyses of borderline and
clinical cases in the DCD group are discussed below.

<hs>  Comparing parent and teachers SDQ scores in children with DCD</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Focusing on the DCD group only, group analyses compared parent and teacher reports on the
SDQ before examination of individual data points allowed us to: (a) look more closely at
concordance between parent and teacher ratings on the SDQ; and (b) determine whether
children with DCD presented with a specific profile of emotional and behavioural
difficulties on the SDQ. As seen in Table 3, a paired samples t-test revealed no
significant difference between parent and teacher scores when considering the Total
difficulties scores of children with DCD on the SDQ. However, paired samples t-tests
exploring SDQ subscale scores indicated two key differences between parent and teacher
ratings of the children with DCD. First, parents reported their DCD children’s
hyperactivity to be more problematic than teachers did. Second, parents rated the
prosocial behaviours of their children with DCD more highly (i.e., less problematic) than
teachers did. There was also a non-significant trend towards parents rating their DCD
children’s conduct problems to be more severe than teachers did. Across the other
subtests, there was general agreement between parent and teacher ratings. Significant
correlations between parent and teacher ratings were found for three of the five subscales
(Emotional symptoms, Conduct problems and Peer problems), with correlations approaching
significance for the Total difficulties score (see Table 3). Classifying DCD children’s
scores (overall, and for each subtest) into ‘normal’, ‘borderline’ or ‘clinical’
categories, we explored individual children’s scores on the SDQ for those who had both
parent and teacher reported scores (n = 26; one teacher and three parents did not return
the SDQs). Table 4 presents the classification for each individual child, on each subtest
and overall, as rated by both their parent and teacher: unshaded cells reflect ‘normal’
scores, grey cells reflect ‘borderline’ scores, and black cells reflect ‘clinical’ scores.
For Total difficulties scores, as well as scores on each subtest, a tick after the parent
and teacher ratings reflects agreement between the informants’ classifications (with
‘agreement’ being classed as both parent and teacher reporting the child’s behaviour to be
either ‘normal’ or in the ‘borderline/clinical’ range) and a cross denotes disagreement
(i.e., a parent rating the child’s behaviour in the ‘normal’ range and the teacher
reporting the child’s behaviour to be in the ‘borderline/clinical’ range, or vice versa).
A tally at the end of each row or column indicates the number of parent-teacher
classification agreements for each child or across the subscales (including the overall
total). Inspection of Table 4 serves to further demonstrate the modest level of agreement
between parent and teacher ratings of children with DCD on the SDQ. For example, on the
Total difficulties SDQ scores, parents and teachers classified children similarly in 15
out of 26 cases (57.7%). Likewise, classification agreements across the other subtests
ranged from 15 to 20 out of 26 (57.7%–76.9%), and classifications for risk of Emotional,
Behavioural or Hyperactive disorders ranged from 15 to 19 out of 26 (57.7%–73.1%). A
further feature of Table 4 is that it illustrates the variability in the scores of
children with DCD across the different subscales of the SDQ. Visual inspection of Table
highlights that no discernable pattern emerges amongst the group, aside from fairly severe
levels of hyperactivity across the sample (with only 2/26 DCD children showing ‘normal’
levels of hyperactivity, as rated by both parents and teachers), as well as a relative
lack of children with the presence of conduct problems (16/26 DCD children showed ‘normal’
levels of conduct problems, as rated by both parents and teachers). DCD children were also
rated as having a slightly raised profile of peer problems and emotional difficulties;
only 12 DCD children (46.1%) were rated as having ‘normal’ levels of peer problems by both
parents and teachers, with this figure falling to just eight children (30.8%) in relation
to emotional difficulties.

<h>DISCUSSION</h>
----------

We used teacher and parent versions of the SDQ to explore reports of emotional and
behavioural problems in children with DCD. Teachers reported that children with DCD
displayed a higher number of emotional and behavioural difficulties than their TD peers
(both those of a similar CA, and those with similar motor abilities). Further, exploring
the profiles of emotional and behavioural problems in children with DCD more closely
(using individual and group analyses), yielded two key findings. First, variability was
noted amongst the SDQ profiles of individual children with DCD; there was a range of
different combinations of typical and atypical presentations of emotional and behavioural
problems, with some overarching themes (e.g., high levels of hyperactivity, comparatively
lower levels of conduct problems). Second, agreement between parent and teacher reports of
children’s emotional and behavioural difficulties was modest (as found by Stone et al.,
(2010), highlighting the need for clinicians to collect information from multiple
informants when assessing a child with DCD. The results are consistent with other studies
that have used the SDQ in this population; finding high rates of difficulties overall, as
well as on the individual subscales (e.g., Green et al., 2006; Van den Heuvel et al.,
2016). The present study was unique in that it compared teacher-report SDQ scores of
children with DCD against two TD comparison groups – those matched on CA, as well as
younger children matched on motor ability (MM). Consideration of the profiles of the two
TD groups from teacher ratings demonstrated that all children fell in the ‘normal’
boundary for the SDQ Total Difficulties score, with very few TD children from these two
groups showing ‘borderline’ or ‘clinical’ profiles in the subtests. This is in stark
contrast to a high number of children with DCD showing the latter profiles. The finding
that the CA and MM groups scored equivalently – and showed lower levels of emotional and
behavioural problems than the DCD group – suggests that the emotional and behavioural
profile of the DCD group is not simply due to motor immaturity. Instead, it may be a
repercussion of the core diagnostic characteristics: difficulties experienced in the motor
domain (e.g., problems with acquiring proficient fine and gross motor skills having
consequences for the development of other aspects of functioning such as social and
emotional development). Individual analyses (using SDQ data collected from both parents
and teachers) highlighted variability between the SDQ scores of the DCD group, with a
range of combinations (of typical and atypical) emotional and behavioural problems noted.
Wide variability is perhaps not so surprising in a group often shown to be heterogeneous
in nature (Biotteau et al., 2016). Therefore, this method of exploring individual
differences is an important approach when interpreting the performance of the DCD group.
Despite this variability, there was some suggestion that children with DCD have elevated
levels of hyperactivity, with only 2/26 children (7.69%) showing ‘normal’ levels of
hyperactivity (as rated by both parents and teachers). This is consistent with studies
suggesting a high degree of overlap between DCD and ADHD (Kadesjo & Gillberg, 1998) and
highlights that clinicians should be astute to hyperactivity in children with motor
difficulties. Individual analyses also showed that nearly two thirds of children with DCD
demonstrate no conduct problems – 16/26 children (61.54%) showed ‘normal’ levels of
conduct problems (as rated by both parents and teachers), which is consistent with
previous research (Gustafsson et al., 2014). Yet, it should be noted that conduct problems
were reported in just over a third of this group. Finally, the slightly raised profile of
emotional difficulties and peer problems in the children with DCD also confirms previous
findings (e.g., King-Dowling, Missiuna, Rodriguez, Greenway, & Cairney, 2015; Wagner, Bös,
Jascenoka, Jekauc, & Petermann, 2012). Group and individual analyses demonstrated modest
agreement between parent and teacher scores on the SDQ for children with DCD. Whilst
previous studies have reported high levels of emotional and behavioural problems in
children with DCD, findings from SDQ studies using parent or teacher reports have not
yielded equivalent results; for example, teacher-reported SDQ scores of children with DCD
(Van den Heuvel et al., 2016) have been reported to be lower than those reported by
parents (Green et al., 2006). These previous studies have each used parent or teacher
reports in isolation, whereas the present research compared parent and teacher ratings
across the same group of children. Adopting this approach provides further, more solid
evidence for subtle disparities between parent and teacher ratings on the SDQ. They also
confirm previous studies (outside the field of DCD) showing only modest agreement between
parent- and teacher-reported scores on this measure (Stone et al., 2010). Analysis of
parent and teacher reports also revealed that parents often rated their children with DCD
to be more hyperactive than teachers did; however, the opposite was true for prosocial
behaviours (with parents often reporting higher levels of prosocial behaviour than
teachers). This could be accounted for by children behaving differently in school and at
home, or could be related to teachers having a broader (and potentially more accurate)
benchmark against which to compare the children. Irrespective of the reasons underlying
these differences, it illustrates the importance of professionals obtaining reports from
both teachers and parents when using the SDQ with children with DCD. In doing so, any bias
ought to be removed, as well as ensuring no information is missing. This, in turn, will
lead to a more comprehensive picture of the child’s difficulties. Although a strength of
this study is the inclusion of a younger MM comparison group, it is noted that the
procedure of matching on a single measure of fine motor skill has its limitations. Future
research may consider extending this approach to a larger sample of participants and to
consider matching on fine and gross motor skill. In selecting samples, care was taken to
exclude children with known co-occurring difficulties (based on parent and clinical
reports) so that conclusions related to the core motor difficulty could be made. However,
it is recognised that further screening of possible co-occurring difficulties would help
further categorise the profiles seen here. In taking this research forward, direct
comparison of both parent and teacher SDQ ratings in the TD (CA and MM) groups would be
fruitful, to align to the present findings. Interestingly, our data show that teachers do
not rate the TD children particularly highly on any aspect of the SDQ; nevertheless,
parent perspectives would be valuable here. Overall, the current findings highlight that a
large proportion of children with DCD present with problems with attention
(hyperactivity). In addition, albeit to a lesser extent, a number of DCD children had a
raised profile of emotional difficulties and peer problems. As the sample did not have any
confirmed co-occurring diagnoses (e.g., ADHD), it highlights the importance of exploring
emotional and behavioural problems in a DCD population, to fully support these
individuals. The findings also flag inconsistencies across parent and teacher ratings,
stressing the importance of considering both perspectives. Moreover, the variability in
SDQ scores across the DCD sample suggests that a tailored approach to intervention is
necessary to support the emotional and behavioural needs of this group.


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<ART>Emotional intelligence and performance in a stressful task: The mediating role of self-efficacy
================================================================================

Authors: Shagini Udayar, Marina Fiori, Elise Bausseron
DOI: 10.1016/j.paid.2019.109790
Year: 2020
ASJC codes: 3200
Keywords: GERT, STEM, STEU, Self-efficacy, Stress, TEIQue, Task performance, Trait and ability emotional intelligence

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Emotional intelligence (EI) is argued to predispose individuals to better apprehend and accomplish stressful tasks. Research produced to date has nevertheless mostly neglected the processes that render EI situationally advantageous. In this study, we used path analysis to explore how ability and trait EI relate to delivering a presentation under stress by distinguishing subjective and objective performance. We also proposed self-efficacy as a potential mediator of the trait EI-performance relationship. One hundred and twenty university students completed the STEU, STEM, and GERT (for ability EI) and the TEIQue (for trait EI); then they performed an oral presentation task in front of two evaluators. Students’ self-ratings and evaluators’ scores composed subjective and objective performance. Results indicated that: (a) self-efficacy fully mediated the relationship between trait EI and both subjective and objective performance; (b) ability EI, in particular emotion understanding (STEU), directly predicted objective performance. These findings highlight one way in which the two leading EI approaches may both contribute to performance under stress, but through distinctive paths.

--------------------------------------------------------------------------------


<h>EMOTIONAL INTELLIGENCE AND PERFORMANCE</h>
--------------------------------------

Past results are mixed, and yet both trait EI and ability EI appear to predict various
forms of performance such as cognitive task performance (e.g., Hui-Hua & Schutte, 2015;
Lam & Kirby, 2002), academic performance (e.g., Perera, 2016; Song et al., 2009),
workplace performance (e.g., O'Boyle et al., 2011), and performance under pressure (e.g.,
Laborde, Lautenbach, Allen, Herbert, & Achtzehn, 2014; Lyons & Schneider, 2005). Trait EI
appears to predict performance when performance is assessed via both subjective and
objective ratings (O'Boyle et al., 2011). One rationale advanced for the positive
association between trait EI and objective performance/outcomes is the overall
characterization of high trait EI individuals as being less implicitly prone to
impulsiveness and more self-controlled (Petrides, 2011). Trait EI thus should cultivate
attitudes and behaviors that are normally crucial for facilitating productive persistence
in stressful situations. The role of ability EI in predicting performance has been
investigated especially in the domain of workplace behavior, with evidence mainly
supporting its utility for objective performance (O'Boyle et al., 2011). Being
conceptualized as a ‘performance’ measure of EI and hence not linked to subjective
perceptions of one's abilities—as also proven by the low correlation between trait and
ability EI (e.g., Vesely Maillefer et al., 2018)—ability EI should be associated with
objective, rather than subjective, performance. In reviewing the extant literature, we
identified three major limitations. First, only few studies have investigated both trait
and ability EI as predictors of the same final outcome (e.g., Davis & Humphrey, 2012).
This empirical hole makes it hard to ascribe reliably a precise situational utility to
each single construct. Second, most frequently, subjective and objective indicators of
performance–with a disproportionate emphasis on job performance–have been counted as
equivalent (Joseph et al., 2015). Third, while a rationale for a possible mediation effect
of self-regulatory process standing between EI and performance outcomes has been theorized
(Zeidner & Matthews, 2018), past research has largely neglected its testing (for an
exception regarding coping as a potential mediating mechanism, see MacCann, Fogarty,
Zeidner, & Roberts, 2011). Consistent with the above critiques, we considered: (a) both
trait and ability EI as predictor of performance in a task expected to demand high
emotional involvement; and (b) both subjective (self-reported) and objective (other-rated)
ratings of performance; and (c) the mediating role of a particular self-regulatory
process, namely self-efficacy, in the relationship between trait EI and performance in a
stressful task.

<hs>  Self-efficacy, a potential mediator</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Self-efficacy refers to people's judgments of their own capabilities to organize and carry
out actions and behaviors required to attain a certain performance (Bandura, 1986). The
basic idea is that one's personal dispositions affect one's behavior by activating self-
regulatory processes such as self-efficacy (Lent, Brown, & Hackett, 1994). Some EI experts
have suggested that trait EI may positively impact performance because of its links to
emotional self-efficacy (e.g., Dacre Pool & Qualter, 2012; Joseph et al., 2015). However,
to our knowledge there exists no full investigation of the relationship between the three
concepts. A few studies only have reported a positive correlation between trait EI and
self-efficacy (e.g., Mouton, Hansenne, Delcour, & Cloes, 2013), and another has shown that
trait EI predicted self-efficacy perceptions in a condition of stress as compared to a
neutral one (Mikolajczak & Luminet, 2008). Yet, ‘subjective’ beliefs about one's
capability to perform, we argue, is the most plausible mechanism through which trait EI
may impact performance. In contrast, the ability EI-self-efficacy beliefs relationship
appears less straightforward. Individuals high in ability EI use their emotional skills to
effectively adapt to the situation and ultimately outperform. Performance seems to depend
directly on one's actual ability to deal with an emotional situation.

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

We aimed to test the EI-performance link and our assumption for self-efficacy to act as a
unique mediator in two hypotheses Hypothesis 1. The relationship between trait EI and
objective and subjective performance will be mediated by perceived self-efficacy in
dealing with the task. Hypothesis 2. Ability EI will have a direct effect on objective
performance, but not on subjective (self-rated) performance. We did not have specific
hypotheses regarding which EI ability would better predict performance, although emotion
understanding and emotion management would be more relevant for the task chosen involving
high stress.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A mixed group of 120 students enrolled at a University in Switzerland (55 female; 80% of
undergraduate, age range: 19-31; Mage = 21.63 and SD = 2.22) were pooled from a larger
research sample collected a year earlier. All received 20 CHF in compensation for
participation.

<hs>  Design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

Upon arrival in the lab, participants were instructed to prepare, in 10 min, a 3 min oral
presentation that they would need to perform immediately after in front of two neutral
evaluators. Participants randomly allocated to a high stress condition (n1 = 60, 26
females) were asked to synthetize a complex philosophical text, and those allocated to a
low stress condition (n2 = 60, 29 females) to discuss professional experiences and career
aspirations. In both conditions, they needed to speak until the end of the 3 min in front
of a camera and were recorded. The evaluators seated behind a desk as they listened and
rated independently the presentations using an online assessment form. Participants
finally completed a post-questionnaire before being debriefed. The experiment lasted about
45 min.

<hs>  Measures</hs>
  ~~~~~~~~

The Trait Emotional Intelligence Questionnaire-Short Form (TEIQue; Cooper & Petrides,
2010) measured trait EI, while the Situational Test of Emotional Understanding-Short Form
(STEU; MacCann & Roberts, 2008), the Situational Test of Emotion Management-Short Form
(STEM; MacCann & Roberts, 2008), and the Geneva Emotion Recognition Test-short version
(GERT; Schlegel & Scherer, 2016) assessed ability EI. A single-item indicator evaluated
self-efficacy belief (SE) about coping with the task. Single item measures have been used
to assess self-efficacy in previous studies (e.g., Hoeppner, Kelly, Urbanoski, &
Slaymaker, 2011). As a measure of subjective performance (Perf-S), participants indicated
how well they thought they performed on the task. For objective performance (Perf-O), the
evaluators rated each presentation overall based on the criteria: clarity, organization,
and coherence of the argument presented; inter-rater reliability calculated using the
intra-class correlation coefficient (ICC) was good: .91. The Brief HEXACO Inventory (BHI;
De Vries, 2013) and the Verbal Reasoning test from the Kit of Factor-Referenced Cognitive
Tests (VR; Ekstrom, French, Harman, & Dermen, 1976) assessed personality and cognitive
ability and were employed as controls1 (see supplementary materials 1 for details).

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

We used the Statistical Package for Social Sciences version 22 (IBM SPSS Statistics 22;
SPSS Inc., Chicago, IL) to compute scores on the variables of interest, perform
descriptive analyses, and calculate ICC and Cronbach reliabilities. Monte Carlo power
analysis for indirect effects was conducted through a modern online application
(Schoemann, Boulton, & Short, 2017). To test the fit of the data, path analysis with
maximum likelihood estimation was performed with Stata 14 (StataCorp, 2015); path
coefficients of direct and indirect effects were estimated using Z-tests for mediation
analysis. A model testing both hypotheses 1 and 2 was fitted with the total score of the
TEIQue, STEU, STEM, GERT as independent variables, confidence in the ability to cope with
the situation as mediator (only for the TEIQue), and subjective and objective performance
as outcomes (see Fig. 1). A trimmed model was then created removing the non-significant
paths for the sake of parsimony. This model was compared with two full mediation models
linking trait EI with each performance type. Only the control variables displaying
significant correlations with the mediator or the outcomes were retained for the analyses.
We let the error terms of the outcomes correlate in the model. We requested standardized
solutions, thus the reported values are beta coefficients. Overall R2 was also computed.
The fit indices used were: chi-square test statistic (χ2), the comparative fit index
(CFI), the Tucker-Lewis index (TLI), the root mean square error of approximation (RMSEA),
and the Standardized Root Mean Residual (SRMR). If the CFI value was .90 or above, the TLI
values were above .95, the SRMR and RMSEA values were .08 or less, we considered the model
to have a good fit.

<h>RESULTS</h>
-------

In the two conditions, participants rated how stressed they felt before, during, and after
performing. Participants assigned to the high stress condition felt more stressed after
the task (M = 2.05 SD = 1.02) than those in the low stress condition (M = 1.68 SD = 0.93),
F (1, 118) = 4.26, p = .041. Stress felt before and during performance did not differ in
the two conditions, with participants reporting quite high levels of stress overall across
the two conditions while performing (M = 3.54, SD = 0.99). Due to the similarity of
effects of high and low stress conditions, and to low power to conduct mediation analyses
with each condition treated separately, we dummy coded experimental condition (0-low
stress condition, 1 high stress condition) and added it as a control variable in all
models.

<hs>  Descriptive analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Table 1 presents the means, standard deviations, and correlations among the variables.
Trait EI positively correlated with self-efficacy and subjective performance but not with
objective performance, only the STEU did. The STEU, STEM and GERT were correlated with
each other, suggesting a common latent variable assessing ability EI. Self-efficacy in
coping with the situation was positively correlated to subjective and objective
performance. Verbal reasoning, gender, emotionality, agreeableness, and conscientiousness
showed no significant relationship with either the mediator or the performance outcomes
and were excluded from analysis.

<hs>  Mediation analyses</hs>
  ~~~~~~~~~~~~~~~~~~

The Monte-Carlo power analysis indicated power of 94% for detecting the indirect effect of
trait EI on subjective and objective performance. Confirmatory factor analysis (CFA) using
maximum likelihood estimation to assess the structural validity of ability EI using the
STEU, STEM, and GERT further showed satisfactory fit indices and/or factor loadings >.45,
confirming that each scale is indeed an indicator of ability EI.

<h>DISCUSSION</h>
----------

We experimentally explored how ability and trait EI relate to subjective and objective
performance under task-induced stress and proposed self-efficacy as a potential mediator
of the trait EI-performance relationship. Self-efficacy mediated the relationship between
trait EI and both subjective and objective performance (Hypothesis 1), and ability
EI–albeit only in the case of emotion understanding–directly and strictly predicted
objective performance (Hypothesis 2). While we did not hypothesize the exact nature of the
mediation for trait EI, we note that a full mediation emerged for both objective and
subjective performance.

<hs>  The mediating role of self-efficacy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our findings suggest that the perceived capacity to understand and use emotions is
cardinal in mobilizing self-regulatory processes that are powerful enough to influence
both subjective and objective performance. In this respect, they corroborate the results
of a recent study where trait EI was found to impact human behavior through a similar
mechanism (Udayar, Fiori, Thalmayer, & Rossier, 2018). Our findings also reveal that, at
least with respect to performance under stress, the contribution of trait EI on subjective
and objective performance is fully accounted for by self-efficacy beliefs about being
capable to deal with the situation's emotional and stressful components, further
corroborating the path through which trait EI may exert positive outcomes.

<hs>  Utility of EI in predicting performance under stress</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ability EI had a direct effect, and on objective performance only. Among the three ability
EI components, only emotion understanding was a significant predictor. Although we
expected that emotion management could have played a role given the stressful situation,
the finding regarding the prominent role of emotion understanding within the ability EI
framework was not particularly surprising based on a number of studies showing its
relevance in predicting important outcomes (e.g., Qualter et al., 2019; Yip & Côté, 2013).
Factor analysis approaches have also highlighted higher factor loadings for this ability
EI component (e.g., MacCann, Joseph, Newman, & Roberts, 2014). Individuals high in emotion
understanding received a better external score for their presentation but, as self-raters,
they did not judge their individual performance significantly higher than their
counterparts lower in emotion understanding. Perhaps this denotes the presence of a form
of self-doubt in high ability EI scorers, and/or one of overconfidence in those less
skilled in the construct. More certainly, the results indicate that actual abilities and
subjective perceptions of performance have little to do with each other. This aligns in
logic with the typical low correlation found between intelligence scores and self-reported
measures of intelligence (Paulhus, Lysy, & Yik, 1998 cited in Brackett & Mayer, 2003). Our
findings also show that like in Lyons and Schneider (2005), high ability EI individuals
seem to have used their emotional skills to adapt to the presentation situation and to
ultimately outperform. In contrast, trait EI seems to be a better predictor of subjective
performance as ability EI had no effect on it. All in all, our results speak in favor of
considering ability EI as an asset for elevating performance regardless of the subjective
beliefs the person has about such performance. Still, EI training programs promoting
either the trait or ability approach could benefit from incorporating the finding that
self-mastery beliefs about one's ability to deal with a stressful situation (such as
performing well at a job interview) are of practical help for thriving. Our findings,
however, support the conclusions of previous studies for envisaging the utility of EI
mostly in jobs high in emotional labor (e.g., Joseph & Newman, 2010) as, we speculate, it
is in these where task-induced stress would be most exacerbated.

<h>LIMITATIONS TO CONSIDER FOR FUTURE RESEARCH</h>
-------------------------------------------

We assessed performance on one task and under the special state of stress. Our findings’
generalizability is thus limited to individuals subjected to similar performance
challenges and conditions (Matthews et al., 2006). This being said, many school or work
situations require to deliver presentations on subjects the person is not necessarily
familiar with, and to articulate a position in front of others with often the quite
stressful risk of being judged. Hence, we believe that the experimental condition employed
in our study had good ecological validity. We also measured self-efficacy after the task
was performed. In principle, how people performed on the task might have affected self-
efficacy perceptions. Although the measurement of self-efficacy before performance would
have been more effective for showing its mediational effect, we believe that performing
the task did not substantially affect self-efficacy perceptions for two reasons: (a) the
experimenters were instructed to remain neutral and to not provide any cue about how
participants were performing and (b) both conditions were perceived to be rather stressful
and therefore difficult (the average level of stress during the task across conditions was
3.54 out of 5); hence, participants did not have a clear sense of how well they performed
after the task. Finally, we made the choice to use performance indicators explicitly
tailored to our presentation task; an alternative for future research would be to use
standardized questionnaires assessing subjective and objective performance, which might
increase the validity of our findings.

<h>CONCLUDING NOTES</h>
----------------

As research on possible primary (e.g., inability to exploit/express one's full potential)
and secondary (e.g., demotivation, poor decision-making) negative effects stress could
have on performance continues to advance and gain importance in a plethora of domains
(e.g., health care, sport; Lea, Davis, Mahoney, & Qualter, 2019), our findings bring
reasonable optimism in revealing, through trait and ability EI, two possible paths that
might aid to minimize such detrimental effects. Of course, moving forward, one big
question is: how can knowledge about the virtues of each construct be most effectively
diffused and strategically implemented in action?

<h>FUNDING</h>
-------

The contribution of the authors was financed by the Swiss National Science Foundation
(grant no 100014_165605 awarded to Marina Fiori). +


<h>REFERENCES</h>
----------

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<ART>Emotional responses to world inequality
=======================================

Authors: Anna Barford
DOI: 10.1016/j.emospa.2016.10.006
Year: 2017  |  Pages: 25-35
ASJC codes: 3205, 3207
Keywords: Discussion groups, Emotion, Inequality, Kenya, Mexico, UK

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Drawing on discussions with Kenyan, Mexican and British teachers, this paper reports on emotional responses to international socio-economic inequality. Emotional regimes are explored to identify what ‘appropriate’ responses to inequality are in a variety of local and national contexts. These include rural and urban settings, and social milieus ranging from elite to deprived. Politeness, hand-wringing and humour can create a protective distance; while sadness, anger and hope for change connect with the issue of inequality and challenge the associated injustices. Distancing and connecting emerge as central themes in the analysis. The spatial patterns of emotions align with participants' socio-economic positions, in more disadvantaged settings unapologetic anger about inequality was expressed, as was humour in the face of group or national misfortune. These emotional regimes can be understood within the wider context of participants' socio-economic position; their senses of injustice; and their views on the possibility of social change. I argue that social norms surrounding justice and distribution can influence levels of inequality, and vice versa. This is of particular importance given the societal damage caused by inequality, which is now widely acknowledged.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Emotions are central to how people are positioned in relation to a topic or situation.
Being emotionally engaged may amplify attitudes and provide an impetus for action. In
contrast, denial of something being morally problematic may mean not feeling disturbed
(Cohen, 2000). Connecting to or distancing from an issue is a key theme in this analysis
of secondary school teachers' and trainee teachers’ attitudes towards socio-economic
inequality. Emotions are important for understanding the interconnected yet unequal social
world, to the extent that neglecting the vocabulary of emotions “leaves a gaping void in
how to both know, and intervene in, the world.” (Anderson and Smith, 2001, p.7). Emotions
are active elements of public debate on world issues. Emotions, such as fear of terrorism,
may be provoked to justify political manoeuvres (Pain, 2009). Negative emotions
surrounding inequality may be roused by unmet expectations. These expectations are based
on experience of norms of remuneration, capacity to meet basic needs, and level of
disposable income, amongst other factors (Hegtvedt et al., 2008). I am interested here in
understanding how local socio-economic positioning and norms influence emotional responses
to inequality. In particular, I consider the emotional regimes surrounding inequality in
three countries that differ markedly in terms of national wealth. It is widely argued that
current levels of world inequality, normally taken to imply income or wealth inequality,
are unacceptable (Amin, 2006; Dorling, 2010; Ghosh, 2008; Roy, 1999; Sutcliffe, 2005).
Economic inequality is closely associated with health, social and educational inequality.
It has been argued that greater economic equality would enable a fuller use of human
resources, create larger markets for goods, and reduce costs of managing society, such as
policing costs (Sutcliffe, 2005; Wacquant, 2010). Many negative outcomes of national
inequality in richer countries have been identified, which impact upon the wealthy as well
as poorer groups (e.g., Wilkinson and Pickett, 2009). Being richer than others can even
lead to feelings of vulnerability and depression. This may be partly due to searching for
fulfillment in objects of social status (James, 2007). Thomas Pogge takes a Rawlsian
approach to poverty, arguing that we have a responsibility not to cause harm (Pogge,
2008a). Bob Sutcliffe, on the other hand, emphasizes that redistribution is desirable for
social justice independent of consequences (Sutcliffe, 2005). These authors provide some
responses to inequality embedded in academic debate, a debate that provokes emotional and
moral statements in addition to discussion about evidence and theory. This paper presents
comparative research on attitudes to world socio-economic inequality. It focuses on how
secondary school teachers and trainee teachers from Kenya, Mexico and the UK talk about
such inequality. I emphasize the emotional stances imbued in discussions about inequality,
and pay attention to how participants position themselves in relation to inequality. The
three countries were selected to span a wide range of levels of international inequality,
whilst having broadly comparable national inequality (the UK is the more equal society of
the three, reflecting a trend of richer countries being more equal than poorer countries;
Barford, 2010). The research locations also capture diversity in terms of the countries’
roles in the world economy, geographical location, and regional influences. Exploring how
emotional regimes are interrelated with the local, national and international socio-
economic positions of research participants offers insight into spatial patterns of
emotions surrounding inequality. Characterising the emotional regimes concerning world
inequality is important for understanding how people create connections and distances
across social and physical divides.

<h>LITERATURE ON POLITICS, EMOTIONS AND INTERCONNECTIVITY</h>
------------------------------------------------------

Since the mid-1990s, there has been increased interest in emotions within the disciplines
of sociology, psychology, philosophy, and geography (Reddy, 2005; Thien, 2005). More
recent interest in emotions within the social sciences stems from the recognition of their
political importance. The idea that emotions are regarded as separate from the public
sphere and essentially private has been widely critiqued across feminist (or emotional)
geography literature, since they are tied up with power relations. For example, social
hierarchies are associated with psychosocial stress and status anxieties (Anderson and
Smith, 2001; Wilkinson and Pickett, 2009; Routledge, 2012). Social constructionists view
emotions as “culturally relevant, public performances, reflecting power relations and
mediating between subjective experiences and social practices” (Zembylas, 2007, p.58).
Understandings of politics, policies, experiences and attitudes can be improved by
considering their emotional dimensions. Emotions can motivate people to act against
injustices (Routledge, 2012). In recognition of the active role of emotions, William Reddy
coined the term emotives, a word similar to performative, to express how emotions
influence the world (Reddy, 2005). He describes how emotional information is conveyed in
responses to others in words and facial expressions. Reddy argues that communities
establish norms resulting in an ‘emotional regime’, where conformity to preferred emotions
is endowed with authority. Social interactionist Arlie Hochschild (Hochschild, 2008) uses
a similar concept of ‘feelings rules’. For Hochschild, emotions are based on cultural
‘prototypes’. Particular reactions are expected in response to certain events: one should
be thrilled to win a prize, one should be furious when mistreated. As cultures are fluid
and interconnected, feeling rules can be interpreted as having local, national, and
international influences. These expectations vary between cultures and contexts due to
local differences in general standards (Hegtvedt et al., 2008). A constellation of feeling
rules contributes to emotional regimes, and both terms are employed in this paper.
Attitudes to world inequality are likely to be influenced by spatial variations in
emotional regimes and feeling rules. Emotional regimes, which make some responses
acceptable and others distasteful or inappropriate, are partly influenced by material
conditions. This is because material conditions underlie the procurement of essential
goods and luxuries (and social norms of wealth influence what is deemed essential or
luxurious). Economic position also influences the cultural norms and values to which
people are exposed. Thus, geographies of inequality could bear some similarities to the
spatial patterns of emotional responses to inequality. Reddy's and Hochschild's views of
the social conditioning of emotions counter the common impression that emotions are
involuntary (Anderson and Smith, 2001), and several researchers have documented how
emotional expression is consciously controlled. For instance, protesters may avoid angry
and violent responses to social injustices so as not to provide an excuse for others to
delegitimize their objections (Routledge, 2012). Similarly, in Mexico and the USA, media
accusations of being ‘crazy’ or ‘emotionally craven’ have undermined and silenced protest
against injustices to women (Wright, 2008). In both cases, dominant groups have encouraged
emotional control in an effort to maintain social control. Yet channeling rather than
suppressing anger and aggression has enabled protests to persist, whilst conforming to
wider emotional expectations (Thrift, 2004). However, a strong response is sometimes
necessary to initiate social change. Roland Barthes distinguishes between punctum, as an
emotionally charged response that ruptures complacency, and the more common studium, which
is a general, polite interest in something (Barthes, 2000). Emotion demonstrates
engagement, whereas polite interest suggests an emotional distance. Those carefully
managing their emotional responses in order to maintain legitimacy, whilst acting upon
strongly held views, negotiate conflicting demands. Norms for emotional performance have
been identified as governing emotional labour. This ‘surface acting’ requires people to
display emotions that they do not feel (Moore, 2008). For example, retail workers are
expected to be cheerful and friendly, whereas judges should be emotionally neutral (Kiely
and Sevastos, 2008). Emotional labour at work strains employees (e.g. Nylander et al.,
2011) due to dissonance between actual and performed feelings. Some people resolve this
dissonance by aligning their own feelings with expected behavior referred to as ‘deep
acting’ (Moore, 2008). There is less need for such emotional labour for people of higher
status. Generally, people who are powerful and of high status have more positive emotional
experiences than people with lower status (Collins, 1990 in Moore, 2008). My interest in
the socio-economic context of emotions resonates with a feminist approach that binds
everyday emotions to networks of power and privilege within which they are located (Pain,
2009). Economic and other social inequalities are widely understood to be instances of
injustice, and so have the potential to cause anger and frustration amongst those
experiencing these injustices. Other researchers have demonstrated that those suffering
disadvantages experience more distress and anger, and those whose advantages are
associated with injustices are more likely to experience feelings of guilt (Hegtvedt et
al., 2008). The type and extent of emotional response may reflect how much someone is
influenced by an experience or observation, as well as by dominant feeling rules.
Distancing is of particular interest given that people and places are now generally
understood to be relational and connected to others, which affects their identities and
capabilities. The uneven development of places is partly due to their interconnectedness:
“The ‘gap’ between the ‘first’ world and the ‘third’ is not just a gap; it is also a
connection.” (Massey and Jess, 1995, p.225). Through time, humans have empathised with
increasingly large groups, from families to the nation state and beyond (Rifkin, 2010). At
a smaller scale, a South African Xhosa proverb ‘umuntu gumuntu ngabantu’ (a person is a
person through persons) acknowledges the importance of society to individuals' identities
(Raghuram et al., 2009; Shutte, 1993 in Smith, 2000; Therborn, 2009). Given these
interrelations and expanding geographical imaginations, distancing other people and places
in our imaginations may constitute denial, whereas emphasizing connections may stress
responsibility. Anglo-American culture has a propensity to suppress emotion and avoid
discussion of responsibility. Emotional suppression was exemplified when ecologist Page
Spencer, writing about her grief at the destruction caused by the 1989 Exxon-Valdez oil
spill in Alaska, was criticized for her “unprofessional and embarrassingly emotional”
accounts (Button, 2010). Similarly, geographer Melissa Wright (2008) received criticism
for her protests against injustices to women. It seems more usual for the privileged to
address injustice and inequality from an emotional distance. Judging their wealth to be
deserved and in the national interest (Pogge, 2008a,b; Rowlingson and Connor, 2010), and
denying the severity of poverty (Swaan, 2005) enables the wealthy to approach inequality
in an apparently rational and unemotional manner. Misperceiving poverty, perhaps by
constructing the poor as lazy and the rich as hardworking (Reis and Moore, 2005; Bamfield
and Horton, 2009), also facilitates an emotionally disengaged approach to inequality.
Income and life expectancy distances between people are increasing at the world and often
country levels (Therborn, 2009). Yet the porous boundaries of places mean that these basic
inequalities cannot be understood in isolation (Massey and Jess, 1995). Instead,
contemporary inequalities are geographical expressions of the contradictions of capitalism
(Smith, 1990). The feelings of the relatively wealthy towards the global poor are better
documented than those who are more disadvantaged by inequality. This research aims to
access multiple understandings of inequality to enhance appreciation of “the lives that
others live partly because of us” (Cook, 2006, p.660). It is within this relational
understanding of people and places that emotions towards world inequality are of
particular interest. The emotions surrounding these international connections and
injustices are central to this paper. Key questions are: How do people feel about their
position in an unequal global system? How do physical distance and feelings of
connectivity play out in the emotional regimes associated with increasing inequalities?
Does one's position within this system influence the form of appropriate emotional
responses, and how? What is the geography of the feeling rules concerning world
inequality?

<hs>  Country context</hs>
  ~~~~~~~~~~~~~~~

The countries selected for this research are distinctly positioned in terms of national
income, meaning that these three countries intersect with world inequality from divergent
material situations. On the spectrum of Gross Domestic Product per capita, Kenya has a
relatively low income, Mexico is towards the middle, and the UK has a relatively high
income. The distribution of income within the three countries is comparatively unequal
(poorer countries generally have higher income inequality than wealthier countries). See
Table 1 for details. All three countries included in this study enacted neo-liberal
policies since the late 1970s. In 1985, Mexico signed the General Agreement on Trade and
Tariffs, which opened the economy and removed state subsidies. This was followed by
further liberalisation or ‘Salinisation’ under President Carlos Salinas (Hamnet, 2006).
This privatization in the 1990s enabled the Mexican Carlos Slim Helú to enter the ranks of
the world's richest people (Harvey, 2007). In the 1980s and 1990s, private enterprise
strategy and Kenyan capitalists acting as agents of foreign capital seemed to make Kenya
an exception to sub-Saharan African poverty (Himbara, 1994). At the same time, under
Margaret Thatcher, the UK transformed from a social democratic state, then comparable to
Sweden, to one of increased service privatization (Harvey, 2007). Each country connects to
a regional identity with distinctive cultures, politics and institutions. Kenyans share in
a pan-African identity (Thiong’o, 2009); Mexico and the rest of Latin America are set in
contradistinction to the United States along linguistic, economic and political lines
(Paz, 2005); and the UK is half-heartedly engaged in European economic and political
consolidation. Still, these countries also stand out from their region. Kenya is the East
African hub; all three countries have close but dissimilar relationships with the United
States. Trends in values and attitudes do vary between world regions, as shown by global
values surveys (Pew Research Centre, 2015), so wider regional context is worth
considering.

<hs>  Discussion groups</hs>
  ~~~~~~~~~~~~~~~~~

Discussion groups were used to shed light on how inequalities are addressed in social
situations, and thereby access the social nature of human knowledge (Goss and Leinbach,
1996). The group setting invites discussion and accommodates open-ended questions that
encourage people to talk in their own terms. Working with groups also emphasizes locality
(Holbrook and Jackson, 1996), which is especially relevant to research into geographical
variations. In order to capture the co-production of emotions in specific contexts, I have
employed extended quotations, where appropriate, to show group interaction. Table 2
provides further detail on group composition and setting. The discussion groups were one-
off meetings lasting roughly 90 min, a relatively low time-commitment compared to
approaches that run multiple meetings with the same group (Burgess, 1996; Kneale, 2001).
The discussion guide included seven questions, starting with what inequality means, in
order to develop a working definition. Next participants were asked about their awareness
of inequalities at the world scale, and then about the causes of inequality. They were
asked about the importance of inequality as a world issue. Four visualizations of
inequality were used to provoke discussion. Of these, two cartograms are shown in Figs. 1
and 2. Then, positive and negative aspects of inequality were discussed. To conclude the
discussion participants were asked to comment on the frequency with which they discuss
inequality, and with whom. This gave a sense of how much the ideas that arose during the
groups extend into participants’ daily lives (Bedford and Burgess, 2001). Group sizes
departed from the standard number of discussion group participants, which is often in
double figures (Goss and Leinbach, 1996; Hennick, 2007). Instead, groups ranged from 2 to
8 people. Small group sizes allow more time for each person to speak, and reduce the
likelihood of simultaneous conversations that are hard to facilitate and transcribe. With
smaller groups it is also easier to recruit participants and gain head teachers’ approval.
Discussion groups were recorded and subsequently transcribed. The words spoken (or their
English translation), and how they were said, were noted. This included the stress on
certain words (indicated by italicized text), tone of voice and other sounds such as sighs
and laughter. The discussion groups in Mexico used Spanish. Those in the UK and Kenya were
conducted in English (which is the medium of secondary education in Kenya). In Kenya,
Kiswahili words were often inserted into English sentences. Learning languages for
fieldwork can deepen understandings of different perspectives and increase cultural
sensitivity more generally (Watson, 2004). Having studied both Spanish and Kiswahili in
preparation for this research, I was able to conduct the groups and translate the
recordings myself, checking meaning with others when appropriate.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

School teachers were chosen for four main reasons. Firstly they have a wider influence on
society, through their potential to expand pupils' sensitivities and awareness.
Educational institutions also play a central role in reproducing social structures
(Bourdieu, 1996). One teacher referred to her role as teaching children to be responsible
citizens: “… You're also teaching them for a wider world in which that inequality will
exist, and it will change if they have a different mindset” (urban private school, UK).
Secondly, teachers often interact with pupils from diverse socio-economic backgrounds and
may deal with inequalities between their students on a daily basis. Thirdly, although
teachers are a heterogeneous group whose professional experiences vary considerably,
working with participants with a shared occupation renders findings more comparable
between countries. Lastly, as ‘global social dialogues’ of social movements and
international institutions are already well documented (Yeates, 2009), new insights into
global dialogues could come from research into teachers' perspectives given their unique
positions in relation to education and schooling. In most cases, discussion groups were
recruited from the same school or teacher training college, and most discussion groups
took place within the school building. The professional context of the discussion, in
terms of the social and physical setting, influenced the roles played by participants.
School hierarchies and professional desirability influenced the views and emotions
expressed, and probably minimized the number of disagreements that arose between
participants, requiring emotional labour from some group members. Recruiting people who
know one another can reduce anxiety about involvement and debate, as well as facilitate
the telling of shared stories (Holbrook and Jackson, 1996). Table 2 details the
participants in each group. I mainly recruited teachers of geography, history, languages
and social sciences. These teachers had varying levels of experience: from trainees to
retirees. They worked in towns and cities as well as rural areas; in schools serving
richer and poorer students; in government and private schools. I conducted nine groups in
Kenya, eight in Mexico and seven in the UK.

<hs>  The social position of participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Local context, such as being in a rural or urban area, or public or private schools,
influences both teachers’ experiences and their socio-economic status. Particularly in
rural areas of poorer countries there may be a lack of electricity, poor school buildings,
minimal support and book shortages, amongst other challenges (Iredale, 1993). In Mexico,
teachers are more respected in a rural setting than in cities, due to the status and
remuneration compared to other skilled jobs available locally. Rural and urban teachers
will be aware of divergent forms of inequality in their daily lives. A state-private
divide exists in education systems in all three countries. Private school teachers are
likely to accept dominant elites, given their choice of school. Many state school teachers
will have some experience of poverty amongst pupils. Since the 1990s, Mexico opened its
education system to the private sector due to World Bank pressure to reduce “non-
productive expenditure”. Private schools taught 13.4% of lower secondary and 21.4% of
upper secondary pupils by 1999 (Delgado-Ramos and Saxe-Fernández, 2009; Marchant, 2005).
In the UK, the Conservative governments from 1979 to 1997 framed parents and pupils as
consumers of education. ‘Consumer choice’ has led to prioritisation of good results over
pupils' needs (Hill et al., 2009).

<hs>  Analysis</hs>
  ~~~~~~~~

To analyse discussion group data in a discourse analysis tradition I focused on what words
allow the speaker to do, how some topics are prioritised, and considered the grammar and
word choices (Wood and Kroger, 2000). Self-definition implicit in discussion was used to
evaluate how interviewees positioned themselves and others in terms of socio-economic
inequality. This is because there are multiple possible interpretations of status
depending on reference group. It is almost always possible to find someone better or worse
off than oneself, and to feel relatively privileged or disadvantaged as a result. Emotions
were analysed according to how participants related to a privileged or disadvantaged self-
categorisation. Status and emotions were identified by the words used and manner of
expression, in order to identify the geography of the emotional regimes employed and the
logic behind them. I worked with emic themes arising from the data, to make less expected
findings possible (Goss and Leinbach, 1996). A reading, re-reading and cross-group
comparison formed the basis for analysis. Codes were formed, altered and merged
throughout. At times I mapped themes diagrammatically to create an overview of conceptual
interconnections (Burgess, 1996; Kneale, 2001; Miles and Huberman, 1994). Ultimately, I
collapsed emotional responses into those that emphasize connectivity between socio-
economic groups, and those that create a distance. These responses infer something about
spatiality and intimacy. Distance is physical, with apparent barriers, as well as a
personal disentanglement from other people and places. By contrast, connection emphasizes
political, economic, social or other forms of proximity, even over large physical
distances. Descriptions of connection also express a level of personal engagement with the
experiences of others. These approaches were analysed in relation to how respondents
expressed their socio-economic status. Comparison between groups highlighted absences and
presences and I identified several discursive repertoires and emotional treatments of
inequality and considered how the groups relate to such repertoires (Jackson, 2001). These
findings are best understood as case studies that illustrate variations and patterns of
understandings of inequalities in particular locales, positioned differently in the same
world order. Due to the small and unrepresentative sample, the findings cannot be
considered representative of the countries in which the research was undertaken (Creswell,
2007). It is possible that cultural context or variations in sense of humour, amongst
other things, could lead to my misinterpretation of some emotions. Nevertheless, multiple
types of information from a discussion group can be used to aid a good interpretation of
feelings. Respondents’ words, body language, tone, and other sounds such as giggling or
sighing can be read in conjunction to triangulate the emotions expressed.

<hs>  Researcher positionality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Postcolonial responsibility requires acknowledging the partial, embedded, political and
messy nature of research and writing (Noxolo, 2009; Jazeel and McFarlane, 2010). This
research was carried out within the context of the global inequalities that it seeks to
challenge. On leaving the UK, my home country became a more significant part of my
identity. Like others (Skelton, 2001), I tried to disassociate myself from British
transnational politics, immigration laws and trade policies. Inequalities often existed
between me as the researcher and the participants. Some teachers working in poorer
contexts could well have found it insensitive for a privileged British student to ask
about inequality, although this reaction was not openly communicated during the discussion
groups. Some of the teachers working in richer contexts, where inequality usually is not
openly critiqued, probably thought me to be radical due to the same questions. On first
sight I was assumed to be a Gringo in Mexico, due to my physical appearance. I am white,
female and undertook this research aged 26–27. Being British may have freed me from
negative stereotypes of United States Americans whose holiday homes have proliferated in
towns such as Chapala in Jalisco. On the other hand, the UK's foreign policies have often
met with controversy. In Kenya I was a Muzungu, a racial and economic category. Typically,
Muzungus receive a warm welcome, always pay for their Kenyan friends, and enjoy going on
safari. In Kenya and Mexico there was surprise at my age and occupation: in both countries
PhD students are usually over 30 years old and already have families (I had no children at
the time). Within the UK, my accent gives away my middle-class background and often
(mistakenly) leads people to think I come from the South of England. I attempted to manage
facets of my identity whilst recognising Rose's (1997) point that we cannot fully
understand, control or redistribute power. My identity influenced participants’ responses
to my questions, as well as my analysis and interpretation of the data. Responses were
influenced partly by a wish to maintain social desirability in front of me, the
researcher, as well as other group members. Further, ideas and attitudes may have been
expressed in particular ways in order that I would understand. Especially in Kenya and
Mexico, it is likely that participants gave more explicit explanations to ensure my
understanding. The themes that interested me, and the patterns that I discovered in the
transcripts, were influenced by my own interest in and understanding of the causes of
inequality. Thus aspects of my identity combined with my sensitivities as a researcher to
influence the results produced by this research.

<h>RESULTS & DISCUSSION</h>
--------------------

Below I demonstrate and discuss how emotional regimes relate to socio-economic inequality.
My analysis shows how respondents tend either to connect or distance themselves from the
issue of inequality. Connection and distancing have emotional and conceptual implications.
Emotional distancing is being more cut off from an issue, whereas connecting is being
emotionally engaged. Conceptually it means whether respondents describe themselves as
being interconnected with others. These associated responses are influenced by whether the
respondents consider themselves to be comparatively privileged or disadvantaged. Speaking
of the global and local poor generally led the teachers to position themselves as
privileged. Reference to wealthier nations, or the rich within their own society, resulted
in participants self-defining as disadvantaged. UK groups rarely position themselves as
disadvantaged. Certain emotions were associated with these positions and distancing
approaches, and these intersecting themes structure the results section (see Table 3).
Generally there was agreement within groups, illustrating the co-production of emotional
responses. Sometimes emotional responses were led by a dominant group member with
especially strong views. In Mexico Group 6 (rural government school) there was one
dominant, politicized and critical male teacher. His discourse was followed with approval,
e.g.: “He's taken the words from our mouths. We totally agree with our colleague.”

<hs>  Disadvantaged, connecting</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Sometimes being disadvantaged whilst connecting with inequality took the form of outrage
or disgust, and a sense of manipulation. Sometimes hope was expressed, at other times
powerlessness and resentment were the dominant emotions. In many cases there was a strong
emotional engagement with inequality, akin to Barthes’ concept of punctum (2000). “At the
world level there are countries that are supposedly the powerful ones, and they are the
ones that are almost moving the world. The smaller countries are those that are doing
nothing more than depending on other countries. So, there is a lot of inequality.” “We're
nothing more than their game of chess!” (Mexico 7, small rural school) The outrage at
world inequality communicated is evident in word choice. The last quote here suggests
disempowerment and resentment, but these words were spoken boldly and critically. The
speaker challenges this situation by emphasizing the nature of this unequal relationship.
The teachers in this Mexican village school saw few opportunities for themselves. One
teacher suggested marriage to a foreigner as a way to progress socially. I found that
rural groups within Mexico were particularly emotionally engaged with inequality. In small
communities poverty and insecurity are not anonymous, but experienced by friends, family,
neighbours and pupils. Thus socio-economic disparities may be more conspicuous and felt
particularly deeply. The term ‘feeling inferior’ was mentioned three times by Kenya 2
(high-achieving urban government school). Kenya 2 and Mexico 6 (rural government school)
use the terms “inferior”, “unequal”, and “terrible” to describe inequality. This differs
from the qualified, apologetic tone of the later quotations from privileged groups. Kenya
2 positioned themselves as being disadvantaged at the world scale. “I think something else
which also brings up world inequalities, is lack of finance. … other countries have a lot
of finance to exploit all the resources that they have. So we are left behind and we feel
as if there is no equality. But if we could have finance to exploit the resources at times
we might be on a par with the others …” “and even issues of political ideologies, you see
like we always adopt, if you look at the world, even like the developing countries the
kind of political ideologies are foreign. They try to adopt them and try to use them to
run their own affairs in those countries. And some of these things brings about a serious
problem of inequality because some of the ideologies for instance, look at the way Kenya
got its independence, we inherited a British kind of system, and this was a colonial
system and so we had our own people come in and continue to perpetuate the system of
colonialism and that creates inequality in the country.” (Kenya 2, high-achieving urban
government school) The speakers object to poorer countries’ lack of financial and
political control. The second speaker builds on the first. Both argue that uneven
connections between places reinforce inequality and disempower poorer nations. Colonialism
is blamed for causing national level inequality; this was a common theme in the Kenyan
discussion groups. The explanation that lack of finance creates inequality paradoxically
gives some hope. Through identifying the structural cause of the problem a possible
solution becomes apparent. The first speaker is able to imagine a way in which greater
equality could be achieved. Hope is the most positive emotion identified in relation to
inequality: “I live in the slum, and I don't like that kind of life … I keep thinking,
‘how can I change things? How can I move out of this you see, and have that?’ What, I talk
about it with people, ‘for how long shall we continue living in this situation?’ … ‘So
what can I do to change this?’ Not just for me but for all of the other people who are
living around me.” (Kenya 6, NGO-funded slum primary teachers) The speaker, in their mid-
twenties, is dissatisfied but hopeful about the future. The speaker is a slum dweller who
engages with inequality through talk of improving things for others as well. Solidarity
and optimism are evident. The deprived setting meant that school meals might be the only
food pupils receive. Following the focus group I was shown sacks of food donated by
international organisations. This teacher's emotional expression, of hope for the future
and dissatisfaction with the present, may be a well-practised interaction with
international visitors (especially those involved in aid or charity work), a performance
of emotional labour by a recipient of aid. This quotation contrasts with the politicized
engagements cited earlier, yet still engages seriously with inequality whilst following a
set of feeling rules. Anger and outrage at the structural causes of inequality are not
appropriate responses to the donor community, not part of the role of being a grateful
recipient. Emotional labour is needed to construct such politically acceptable responses,
which perform the function of easing interactions between the privileged and
disadvantaged, and facilitating a beneficial transfer of resources.

<hs>  Privileged, connecting</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Privileged participants also engaged with inequality as a serious and important issue.
Emotional work was involved in acknowledging the difficulties of others, whilst not
offending other group members in the privileged social context. This balancing is
demonstrated below, where one female participant recovers her composure after an outspoken
criticism of inequality. “But I do have moments when I think ‘God, this is, I cannot live
with this, this is awful, how can this be’, you know. And then obviously you do, you're
not actually affected by it, and I think maybe I'm just being a middle class white woman
having a little bit of a worry, and then I'll buy something Fairtrade and it will be ok.
But you know I do feel it personally to be quite difficult.” (UK 5, urban private school)
This teacher has a strong emotional reaction against inequality. She emphasizes the
necessity of change, describing inequality as awful. She then qualifies her own views
using her white middle-class and female position to imply that she may be more emotional
(female) and perhaps less in touch with local social conditions (white and middle class).
Dismissing her feelings as “a little bit of a worry” tones down her response. This softens
her response, bringing it closer in line with a more emotionally neutral approach. Perhaps
this is a defensive move based on previous criticism for strong emotional responses. This
speaker was not challenged for her feelings about inequality during the group discussion,
instead her self-regulation appears to be a response to wider social norms and feeling
rules governing how inequality is discussed. How some respondents express their critical
and emotionally engaged approach, knowing that this is unconventional in their society,
reminds us of the partial authority of feeling rules. Another British participant, with a
strong interest in inequality, represents a small but vocal minority arguing against
inequality within the UK. “If the problem is inequality, which I think it is, you can't
just look at the third world and say, you know, ‘we've got to do something about the third
world’. No, we've got to do something about the first world and the second world as well.
Because they're, for me, they're equally problematic. … if I have to walk through
Manchester and see somebody scrabbling around in the dustbin to find food, my life is
worse. I mean I know that their life is worse (said quickly), but my life is worse. We've
got to get to recognise that.” (UK 4, retired urban teacher) This participant emphasizes
connections between people. This is achieved partly by identifying that the problems of
inequality need to be addressed worldwide. Inequality, referred to here in terms of
poverty, is engaged with emotionally. When speaking her voice rose, and she was insistent
when stating “my life is worse”. By commenting that poverty is bad for all of society,
this respondent conceptually positioned herself within inequality. That she did not
qualify her criticisms or soften her opinions may be due to her lifelong commitment to
tackling inequality desensitizing her to dominant feeling rules. Over the years she will
have co-constructed an alternative set of emotional responses, building a critical culture
to challenge inequality. In the following quotation a teacher describes how privileged
pupils responded to the disadvantage of others. “… I took a group of students, year 11, 12
and 13 to, er, Mother Theresa Centre, missionaries of charities, she rescues the lowest of
the low in society, people who have been abandoned by families, people that are paralysed,
people that are deformed, mentally challenged and so on, and when the kids went there I
assumed at that level they were psychologically ready to go in. But when we went in, they
broke down and were totally disorientated …. So, yes, they know there is inequality, but
they don't digest, but yeah, they don't get, they've got to be in contact with it to
understand what it means.” (Kenya 7, urban British-system private school) The privileged
pupils at this school are a mixture of international and home students. They are wealthy
in the Kenyan context, and some will join a global elite. The initial obliviousness to the
reality of poverty and disadvantage illustrates how wealthy people buffer themselves from
other social groups. This participant recommends ‘being there’ to disrupt complacency,
using a language of embodied understanding. Not understanding is described corporeally (or
physically) as not “digesting” or incorporating new information, implying a superficial
awareness. This relates to my earlier observation that the two rural Mexican groups were
particularly emotionally engaged in the discussion of inequality. Nairobi has a broader
spectrum of income groups than rural Mexico, yet this urban environment separates pupils
from many other city dwellers. The teacher positioned herself as privileged. During the
discussion she gave examples of how she connects across social distance. This included
providing meals for a poor community and highlighting disadvantage to her pupils. The
sense of privilege and connection resulted in tangible actions, a demonstration of
Routledge's (2012) description of emotional engagement with injustices leading to action.

<hs>  Disadvantaged, distancing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

The main way in which disadvantaged people emotionally distanced themselves from the
inequality was through humour. Several participants in Kenya joked about poverty and the
challenges experienced at the local or at national level. “And why are we living in this
situation while the other people have enough so that they can even throw it? Like the
politicians who come with the helicopter and just throws money [giggles]” Followed by
group laughter (Kenya 6, teachers in poor urban area) The brazen behavior described was of
some politicians flying over the Kibera slum, throwing money in an attempt to win votes.
Group laughter confirms that these comments were funny, and demonstrates that humour is an
appropriate emotional response in this context. Laughter releases tension, keeping the
discussion light-hearted. This laughter may stem from two causes. Firstly, having such
wealth and poverty together is so preposterous that it becomes funny. Secondly,
participants feel powerless to change such entrenched wealth differences. The helplessness
provokes a reaction and laughter is often easier than anger to handle socially. These
teachers live and work in a particularly poor community, so have first-hand experiences of
the injustices associated with inequality. Collective laughter creates an emotional
buffer. Another example comes from comments about the world cartogram showing the
distribution of people earning over US$ 200 per day (Fig. 1). On this map most of Africa
shrinks into a thin black line. South Africa is visible due to the very high earners
living there. The following dialogue is about this map: “[Chuckles] we're in real
problems.” “There's a strip, a black one” [chuckles] “A black strip, of Africa” [laughs]
Anna: “That's where Kenya is, in the black line” Anna: “Why are you laughing?” “Because it
is not there [laugh], it is not seen.” (Kenya 8, rural government school) Like the
previous quotation, this humour is not derisive of others, but is a response to the
group's circumstances. Kenya is described using the personal pronoun ‘we’. Laughter builds
throughout this dialogue, with almost every speaker chuckling or laughing as they describe
the map. That Kenya is not visible on a map of high earnings could be funny due to a
similar combination of ridiculousness and powerlessness. Firstly, seeing one's country
missing from a world map is bizarre. Unexpected occurrences or actions are often used to
provoke laughter, and this map had the same effect (albeit unintentionally). Secondly,
that Kenya is ‘in real problems’ is well-established, the map authoritatively reinforces
this point. Laughing is a protective response.

<hs>  Privileged, distancing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Humour featured as a way of emotionally distancing the privileged from inequality:
“Without inequality, I mean I, we would, we would all be the same, we'd all be the same
[yes] who's going to do, you know, different types of jobs, [yes] you know, what it is
that you aspire to.” “Actually that's a REALLY good point, like in Aldous Huxley's Brave
New World, everyone's actually, so what they do is they actually engineer people so that
they are equal [particularly] because if you have an entire society made up of incredibly
bright, intelligent but nobody, nobody wants to clean the toilets.” “Well I think that's
it really isn't it, and society, and economy need [Yeah.] variation.” “See in intelligence
and in the things, in the things that, well let's face it, you want inequality in
intelligence so that you can con some people into cleaning the toilets” “I mean my mum is
a cleaner and she gains, she is honestly one of the people who is most satisfied with her
job.” (UK 6, urban teachers at a private girls school) This conversation depoliticises
inequality by using supposed differences in intelligence to justify some people doing
undesirable jobs. These teachers distanced themselves from menial work, by asserting their
own superior intelligence. The raucous laughter released tension in the discussion, which
had grown whilst building an argument against equality. In the context of an elite school,
intelligence justifying social disparities offers a socially acceptable explanation. One
group member recovers from this laughter, by drawing on the trope of the happy poor. She
states that cleaning is a fulfilling job. There were two other noteworthy instances of
laughter distancing privileged British participants from inequality (UK 1, UK 3). In both
instances the laughter followed statements of their own privilege, expressing uneasiness
about this position. Awkwardness about privilege, rather than catalysing a social critique
or expression of guilt, followed a pattern of diffusion by humour when group members were
of a similar social position. It is likely that the emotional regime would have been
altered by a different group composition. Distancing by those who consider themselves
comparatively privileged often took the form of non-confrontational interactions.
Apparently balanced responses, noting the disadvantages and benefits associated with
inequality, emotionally and politically distanced groups from the poverty and injustice
associated with inequality. The following responses are to a question about awareness of
world inequality: “Obviously people are living in absolute poverty. They don't have
anything, don't have enough food and other things they need such as water. And obviously
that's not nice and that's what aid charities are trying to tackle I think.” “Saying good
things to inequality is difficult because they're WRONG. But at the same time you've got
things like cheap clothing that people, you know they want cheap clothing. And I know it's
wrong to say, but due to inequality we do get cheaper clothes and things. And it feels
wrong but then it's there, it's a fact.” (UK 1, trainee teachers, urban location) After
acknowledging the existence of economic inequality and its serious consequences, both
speakers distance themselves from the possibility of change. Both comments have similar
narrative forms, expressing regret about inequality and distancing themselves from
inequality. Locating the possibility for change away from themselves offers a neat
solution to the problem, and presents it as self-contained. The second speaker focuses on
the present, implying that inequality is immutable. Distancing the causes of inequality
from the relatively privileged trainee teachers avoids confrontation, the associated
feeling rule is: do not challenge those who benefit most from inequality. Emotions that
others might find it hard to respond to, such as guilt, anger or sorrow, are not
expressed. Acknowledging the problem and distancing themselves from it positions these
trainees as both globally aware yet not accountable for how their lives intersect with
those of others. Studying at a University in a wealthy British city could mean these
respondents were rarely confronted with deep disparities. Inequality probably felt
distant, making distancing easy. The trope of the ‘happy poor’ was used by groups in all
three research countries. In Mexico and Kenya, this referred to the rural poor within that
country. The argument is that rural subsistence lifestyles require little money. Kenya 1
(urban trainee teachers) suggested that $2 is too much in the countryside. UK 1 (urban
trainee teachers) respondents referred to a generalised global poor, warning against
patronizing pity when poor people might be happy. The quotation below shows how one
Mexican group presented the idea of the happy poor within the district of Chiapas. “The
geography of Mexico is one of internal differences. In Chiapas there are people who are
happy with $2 per day.” (Mexico 1, urban teachers from different schools) The happy poor
are constructed as distant by the urban, privileged groups cited above. The speakers live
at a physical and social distance from the poor to whom they refer. This distancing is
inconsistent with their claims to know about the emotional well-being of these distant
poor. The distance allows poorer people to be imagined as having fundamentally different
needs and desires from the research participants. The Mexican quote above refers to the
relatively poor Chiapas district, which is home to many indigenous people. Emotions are
contained and participants reason that poverty is not always a problem (see Barford, 2011
for further discussion). Following an emotionally neutral regime, research participants
avoid challenging one another's socio-economic position and political stance by curtailing
discussion of the difficulties associated with poverty, discussion which could otherwise
prompt strong emotional reactions such as anger or shame. The effect of living amidst
urban poverty was described by a British teacher working in Nairobi, Kenya. She had become
accustomed to seeing slum living conditions: “I don't blink, so you do become a little bit
immune to it, because it becomes so normal” (Kenya 7, urban British-system private
school). She had adjusted to living surrounded by poverty by accepting it. This created an
emotional buffer and protected her from thinking through the implications of poverty.
Observing severe poverty on a daily basis and not intervening requires a form of
distancing, to block the possible shame, pity or anger that might otherwise occur.
Emotional regimes surrounding inequality play several roles: limiting discord, requiring
politically correct responses, and protecting the group and speaker from emotional upset.
Participants' socio-economic positions influence the way in which calls for social change
are expressed, and the appropriate level of emotional commitment to such views. Those who
distanced themselves from inequality also tended to justify it; conversely those who
connected with the topic and connected with others across social divides were inclined to
challenge inequality. In all three countries there were instances of connection and
distancing. One's perceived socio-economic position depends upon choice of reference
group, and more privileged groups in each country recognised this status. In the UK no
groups considered themselves to be disadvantaged, whereas some groups in poorer and rural
areas of Kenya and Mexico did identify with poorer segments of society. Perceived socio-
economic position, combined with connecting or distancing, influenced whether and how
research participants challenged global inequality.

<h>CONCLUSION</h>
----------

Emotions are said to be “intensely political” (Anderson and Smith, 2001, p.7). Inequality
itself is intensely political, because if inequality in resource distribution is
understood as problematic, the logical response is redistribution. Politics arise because
those with more than their equal share of resources may be unwilling to share what they,
and others, consider to be deserved wealth (Rowlingson and Connor, 2010). Whilst some
research participants defended and justified inequality, others felt it was unacceptable.
As others have argued (e.g., Raghuram, Madge and Noxolo, 2009; Therborn, 2009), a more
public and emotionally engaged appreciation of connectivity and relationality could
diminish the conceptual, and ultimately socio-economic, distances between people. Future
research might explore how changes in feeling rules associated with inequality come about,
and how these changes relate to societal change. Self-defined socio-economic position
(disadvantaged/privileged) and political approach to inequality (connecting/distancing)
influence emotional regimes (see Table 3). An emotional regime guides whether anger,
humour, or hope (amongst other options) is an appropriate response to the highly political
and morally sensitive topic of inequality. Country context had some influence on whether
research participants self-defined as being comparatively privileged or disadvantaged. It
was more common for Kenyans and Mexicans to self-define as disadvantaged than UK groups,
reflecting disparities in national wealth. However, it is not possible to distill these
findings to a list of emotional regimes by country because of the importance of sub-
national variations in socio-economic status. The more privileged participants softened or
excused their confrontational views and laughter about inequality; in disadvantaged
settings unapologetic anger and humour at group or national misfortune about inequality
were acceptable responses. Whether research participants appeared connected to, or
distanced from, inequality and its consequences is partly influenced by group dynamics;
this is evident in the tendency towards consensus within the discussion groups which were
composed pre-existing groups of colleagues. The emotional labour of some participants was
observable, for example as they followed feeling rules of being concerned, whilst
expressing their own anger or distance in a socially acceptable way. The geography of
these distancing or confronting emotional techniques varies between people located at
different points within the worldwide distribution of resources, and possibly relates to
how much people feel they have to gain/lose from redistribution. At the beginning of the
Millennium it was asked, “What possibilities are there for developing a geographical
agenda sensitive to the emotional dimensions of living in the world?” (Anderson and Smith,
2001, p.8). The findings presented here offer an international perspective on the feeling
rules that influence how teachers discuss inequality. Comparing emotional expressions
about inequality from diverse social, economic, political and geographical settings offers
insight into multiple perspectives on the same topic. Going beyond one-way analyses of how
one socio-economic group makes sense of another, the work presented here helps to piece
together a more holistic picture of how inequality is understood from multiple vantage
points. This research has made space for both the similarities and differences between
disparate groups to emerge. Paying attention to emotional expressions, whether people are
connecting or distancing themselves from an issue, and how geographical distance and
socio-economic inequality intersect with physical distance and relationality, offers
purchase on the role that emotions play in our interconnected social, economic and
political lives. This methodological approach could be productively applied to other
global issues, such as the debate surrounding climate change.


<h>REFERENCES</h>
----------

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<ART>Empowering interventions to promote sustainable lifestyles: Testing the habit discontinuity hypothesis in a field experiment
================================================================================

Authors: Bas Verplanken, Deborah Roy
DOI: 10.1016/j.jenvp.2015.11.008
Year: 2016  |  Pages: 127-134
ASJC codes: 3202, 3207

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study tested the habit discontinuity hypothesis, which states that behaviour change interventions are more effective when delivered in the context of life course changes. The assumption was that when habits are (temporarily) disturbed, people are more sensitive to new information and adopt a mind-set that is conducive to behaviour change. A field experiment was conducted among 800 participants, who received either an intervention promoting sustainable behaviours, or were in a no-intervention control condition. In both conditions half of the households had recently relocated, and were matched with households that had not relocated. Self-reported frequencies of twenty-five environment-related behaviours were assessed at baseline and eight weeks later. While controlling for past behaviour, habit strength, intentions, perceived control, biospheric values, personal norms, and personal involvement, the intervention was more effective among recently relocated participants. The results suggested that the duration of the 'window of opportunity' was three months after relocation.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Promoting environmentally friendly behaviours is arguably one of the most difficult
behaviour change targets. When people are asked opinions on environmental issues such as
global warming, many will express concerns and pro-environmental attitudes (e.g.,
Eurobarometer, 2014; Ipsos MORI, 2015; Verplanken & Roy, 2013). But when asked what the
most important issues are today, the environment usually ends up low in these rankings
(e.g., BBC, 2015; Gallup, 2015). Even if events such as hurricanes, flooding, or
pollution, happen on the doorstep, the environment remains a distant and nebulous entity
for most people (e.g., Lorenzoni, Nicholson-Cole, & Whitmarsh, 2007, Whitmarsh, 2008).
Consequently, as is predicted by construal-level theory of psychological distance (Trope &
Liberman, 2010), mental representations of “the environment” are not conducive to taking
pro-environmental action (Spence, Poortinga, & Pidgeon, 2012). Environmental issues can
also be framed as social dilemmas, that is, conflicts between immediate self-interest and
longer-term collective interest, which also weaken an individual's motivation to act
(e.g., Biel & Thøgersen, 2007; Lorenzoni et al., 2007). Some barriers to pro-environmental
action are straightforward, in particular when people are restrained in their options, for
instance due to inadequate public transport or limited financial resources. Gifford (2011)
discussed a variety of psychological barriers to pro-environmental behaviour, such as
judgemental biases, social comparison processes, psychological investments in current
behaviours, and mistrust in authorities. In this article we focus on habit as a particular
barrier to change. We will argue that while habits are hard to break, finding
opportunities where existing habits are temporarily broken may make a behaviour change
intervention more effective. Many behaviours that are considered as potential targets for
behaviour change in a more sustainable direction, such as transportation, shopping,
leisure activities, or water usage, are strongly habitual. Habits are learned dispositions
to repeat past responses (Wood & Neal, 2007; Wood & Rünger, 2016). These behaviours are
conducted frequently, usually at the same location and time, and are less guided by
conscious intent (e.g., Danner, Aarts, & de Vries, 2008; Gardner, 2009; Ji & Wood, 2007;
Neal, Wood, Labrecque, & Lally, 2012; Ouellette & Wood, 1998; Triandis, 1977; Verplanken,
Aarts, van Knippenberg, & Moonen, 1998; Wood, Quinn, & Kashy, 2002). While the prevalent
socio-cognitive models suggest that control of behaviour is anchored in an individual's
motivation or willpower (e.g., Ajzen, 1991), when habits are forming some of that control
shifts to the environment, that is, to the cues that elicit the habit (e.g., Neal, Wood, &
Drolet, 2013; Neal, Wood, Wu, & Kurlander, 2011; Orbell & Verplanken, 2010; Wood & Neal,
2007; Wood, Tam, & Guerrero Witt, 2005). Habits are thus highly automatised behaviours
(e.g., Aarts & Dijksterhuis, 2000; Verplanken & Orbell, 2003), or patterns of behaviour
(e.g., Kurz, Gardner, Verplanken, & Abraham, 2015; Roy, Verplanken, & Griffin, 2015). This
comes with a degree of ‘tunnel vision’, that is, a lack of choice awareness, superficial
decision making, and little interest in new information, even if decision makers are
explicitly asked to make deliberate choices (Aarts, Verplanken, & van Knippenberg, 1997;
Verplanken, Aarts, & van Knippenberg, 1997). The features which thus characterise habit –
lack of conscious intent, a shift of behavioural control from willpower to cues, and
‘tunnel vision’ – are making existing habits resistant to change and thus do not bode well
for behaviour change interventions. However, it is not always possible to execute a habit.
Circumstances may arise or contexts may change which limit or block a habit, perhaps
temporarily, and thus require considering alternative courses of action (e.g., Jones &
Ogilvie, 2012). For instance, Fujii, Gärling, and Kitamura (2001) studied the effects of a
temporary freeway closure on commuters. While habitual car users were likely to take a
longer route rather than switching to a more efficient public transport option, some car
users did try public transport and, finding out they had overestimated the travel time,
continued to do so during the freeway closure. Brown, Werner, and Kim (2003) observed how
car users switched to a light-rail option due to temporary parking shortages, and for some
this remained a long-run choice maintained by the positive experiences. Verplanken,
Walker, Davis, and Jurasek (2008) found that university employees who had recently moved
house and were concerned about the environment were commuting more sustainably than those
who were equally concerned, but had not relocated, suggesting that the relocation might
have temporarily activated important environmental values (cf., Gatersleben, Murtagh, &
Abrahamse, 2014; Verplanken & Holland, 2002). These studies suggest that when habits are
broken, this may create a “window of opportunity” for behaviour change. Change may occur
spontaneously, for instance by discovering better options than the old habits, as
supposedly was the case in the studies cited above. But this window may also be used
strategically to promote behaviour change. Behaviour change interventions may thus be more
effective when delivered in the context of major habit disruptions, such as those related
to life course changes. This has been put forward as the habit discontinuity hypothesis
(Bamberg, 2006; Verplanken et al., 2008; Walker, Thomas, & Verplanken, 2015). Major
discontinuities may involve transitions to new phases in life (e.g., from education to a
job), geographical or physical changes (e.g., residential or work-related relocations), or
changes in the environment where habits are executed (e.g., infrastructural changes). Such
discontinuities may force people to renegotiate ways of doing things, create a need for
information to make the new choices, and a mind-set of being ‘in the mood for change’.
Interventions that capitalise on these conditions may thus be more effective compared to
interventions under default conditions. A number of studies have investigated the effects
of behaviour change interventions that were intentionally delivered in the context of a
discontinuity. Bamberg (2006) provided residents who recently had relocated with a 1-day
free public transport ticket and information about the available public transport
services. The intervention induced a significant increase in the use of public transport
compared to a control group of relocated residents who did not receive an intervention.
Thøgersen (2012), in a secondary analysis of an intervention study in which participants
were given a free one-month public transport pass, found that the intervention was only
effective among participants who had recently moved house or work place. Walker et al.
(2015) followed workers of an organisation which had relocated and initiated a sustainable
travel plan in the wake of it, and demonstrated how old habits decayed and new habits
established. While the studies cited in the previous paragraph produced results that are
in line with the habit discontinuity hypothesis, they did not provide a test whether the
discontinuity itself had a distinct role. In other words, these studies demonstrated that
interventions delivered in the wake of a discontinuity were effective, but did not
contrast the effects with a default condition in which participants did not go through a
discontinuity. The present study aimed to provide such a test in a field experiment in a
middle-large city in the east of England. The study included participants who had, versus
had not, recently relocated, as well as an intervention versus no-intervention control
group in both segments. The intervention consisted of face-to-face interviews and the
provision of information about sustainable choices. The outcome consisted of self-reported
frequencies of twenty-five environmentally relevant behaviours, which were assessed at
baseline and eight weeks later. The hypothesis was tested that higher frequencies of
behaviour are reported in the intervention versus control group eight weeks later, but
that this effect is stronger when participants had recently relocated. The effects were
controlled for key determinants of environmental behaviour at baseline; past behaviour,
habit strength, behavioural intention, perceived behavioural control, biospheric values,
personal norms, and personal involvement (e.g., Steg, van den Berg, & de Groot, 2014; Steg
& Vlek, 2009). Past behaviour obviously served as benchmark for change. Existing habit
strength was included, as this might influence the resistance to change (Lewin,
2008/1946). Intention and perceived control represented the most proximal predictors of
behaviour in the theory of planned behaviour (e.g., Ajzen, 1991), and thus covered the
motivation to behave environmentally friendly and the perceived ability to do so,
respectively. Biospheric values, personal norms, and personal involvement represented
broader motivational, normative and identity-related factors which have been found related
to related to pro-environmental behaviour and behaviour change (e.g., Göckeritz et al.,
2010; Sparks & Shepherd, 1992; Stern, 1992; Thøgersen & Ölander, 2002; Verplanken &
Holland, 2002; Whitmarsh & O'Neill, 2010).

<hs>  Participants and design</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Participants were recruited among residents of Peterborough, a city in the east of England
with approximately 186,000 citizens. A total of 1612 individuals were cold-contacted at
the doorstep; 800 (49.6%) were willing to participate in the study.1 Half of the
participants were known to have relocated within the previous 6 months (“movers”). These
households had been identified through property websites and contacts with developers who
had been active in the recruitment areas. The remaining 400 participants were recruited
from the same areas (“non-movers”). Movers and non-movers were matched on house size
(number of bedrooms), home ownership, recycling facilities, and access to public
transport. Participants were assigned to an intervention or a control condition. In order
to avoid neighbours being assigned to different conditions, a clustered randomisation
procedure was applied, in which geographical units were designated as intervention and
control areas, respectively. The study comprised two measurements (T1 and T2,
respectively), which were approximately eight weeks apart. The measurements consisted of
questionnaires, which were handed out upon recruitment and sent by post, respectively.
From the original 800 participants at T1, a total of 521 (65%) submitted a completed
questionnaire at T2. The final sample contained 330 females (63%) and 191 males (37%).
Ages ranged from 19 to 85 years, M = 41 years. Participants received a £10 cash voucher
and a lottery ticket for a £250 a prize draw for submitting the final T2 questionnaire.
The study received approval from the Ethics Committee in the authors' department.

<hs>  Procedure and the intervention</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The field work (recruitment, delivery of the intervention and data collection) was
conducted by the Peterborough Environment City Trust. This organisation had developed an
intervention to promote sustainable behaviours among residents who had recently relocated.
This intervention was adapted and delivered in the intervention condition. Participants in
the control condition only completed the T1 and T2 questionnaires. The intervention
consisted of a Personal Interview; a selection of sustainable items (“Sustainable Goodie
Bag”); tailored and general information (“Green Directory”); a Newsletter. The
intervention was targeted at a wide range of environmentally relevant behaviours,
including water conservation, waste reduction, reducing car use, and saving gas and
electricity. The intervention contained individualised as well as generic information.
Multiple motives were addressed, which concerned ecological values such as preserving
natural resources, as well as individual benefits such as financial savings (cf., Steg,
Bolderdijk, Keizer, & Perlaviciute, 2014; Whitmarsh, 2009). The individualised information
was tailored in the Personal Interview, and partly tailored in the Green Directory, which
also contained generic information. The Sustainable Goodie Bag and the Newsletter conveyed
generic information.

        <hss>Personal Interview</hss>

        Upon agreement to participate, participants were asked to fill out a
        questionnaire, which formed the T1 baseline assessment. The project assistant then
        conducted a personal interview. The responses provided in the questionnaire were
        used as the basis for this conversation. The purpose of the interview was to
        identify behaviours the interviewees were interested in changing, potential
        barriers to change, and possible solutions. The project assistants were trained to
        use one or more of the following intervention tools: (1) addressing perceived
        obstacles and barriers, such as lack of information or skills; (2) providing
        details of obtaining financial benefits, for example by saving water, electricity,
        gas or fuel; (3) emphasising long-term environmental benefits for humans and the
        environment; (4) setting and committing to behavioural goals; (5) emphasising a
        “green identity”; (6) emphasising pro-environmental injunctive and descriptive
        norms; (7) enhancing or maintaining engagement with and attention to the
        ecological agenda. The project assistants kept notes of which behaviours were
        addressed specifically during the interview.

        “Sustainable Goodie Bag”

        Participants were offered a free re-usable shopping bag containing sustainable
        products. The bag contained eco-washing liquid, vegetable and flower seeds, a bus
        timetable, a shower timer, and a set of brochures on environmentally friendly
        choices.

        “Green Directory”

        An information booklet was sent out shortly after the Personal Interview.
        Information for each participant was selected on the basis of their expressed
        interest and/or lack of awareness of issues during the Personal Interview. The
        Directory also provided generic information by referring to websites on how to
        live sustainably, and emphasised both environmental as well as the financial
        benefits of saving resources.

        <hss>Newsletter</hss>

        Participants received twice a Newsletter from the Peterborough Environment City
        Trust. The Newsletters contained a variety of information about sustainable
        solutions and provided links to relevant websites.

<hs>  Assessments</hs>
  ~~~~~~~~~~~

Behaviours were assessed both at T1 and T2, while all other measures were taken at T1.

        <hss>Relocation status</hss>

        Participants were asked how long ago they had moved to their current address. This
        was recorded in terms of weeks, months, and/or years. The time participants lived
        at the current address varied from one week to 32 years. A variable indicating
        relocation status was constructed by applying a log transformation on the number
        of weeks participants had lived at their current address.

        <hss>Behaviours</hss>

        Participants were asked how frequently they had performed twenty-five
        environmentally relevant behaviours during the last year (T1). These items were
        presented again eight weeks later (T2) with reference to the same time frame. The
        choice of behaviours was informed by behavioural goals formulated by the UK
        Department for Environment, Food, and Rural Affairs (Defra, 2008). The behaviours
        broadly covered the domains of water (e.g., taking less than 10 min in the shower;
        using the toilet dual flush), waste (e.g., using re-usable shopping bags; using
        leftover food for other meals), transportation (e.g., walking or cycling short
        journeys; ecologically friendly driving), and energy use (e.g., turning down the
        heating; washing clothes at cooler temperatures).2 Frequencies of performing these
        behaviours were reported on 5-point scales, which were labelled “never” (1),
        “seldom” (2), “sometimes” (3), “often” (4), “always” (5), respectively. Because
        the internal reliabilities of the four behavioural domains were unacceptable
        (i.e., Cronbach Alpha < 0.50), the twenty-five behaviours were aggregated.
        Cronbach Alpha for the collective behaviours was 0.77 and 0.84 for the T1 and T2
        assessments, respectively. For each participant the behaviours were thus averaged
        into a T1 and T2 aggregated behaviour index, respectively. High scores indicate
        high frequencies.

        <hss>Habit strength</hss>

        Habit strength was assessed by a shortened version of the Self-Report Habit Index
        (SRHI; Verplanken & Orbell, 2003). In order to keep the response load within
        acceptable limits, the SRHI was applied to the four behavioural domains, which
        were labelled as, “Using less water”, “Producing less waste”, “Reducing the car
        less for short journeys”, and “Reducing gas and electricity use”, respectively.
        For each of these categories six items from the original twelve items contained in
        the SRHI were presented, Each set of items started with the stem “[Behaviour X] is
        something …”, which was followed by the six items; “… I do frequently”, “… I do
        automatically”, “… I do without thinking”, “… that is part of my daily routine”,
        “… is typically me”, and “… I have been doing for a long time”. The items were
        chosen such that the key features of habit (the experience of repetition and
        automaticity) were represented (Orbell & Verplanken, 2015). Responses were
        reported on 5-point scales labelled as “strongly disagree” (1), “disagree” (2),
        “undecided” (3), “agree” (4), “strongly agree” (5), respectively. Cronbach Alpha
        for the four behavioural domains varied between 0.96 and 0.97. Across all items
        Cronbach Alpha was 0.94. For each participant the SRHI responses were averaged
        into an aggregated habit index. High scores indicate strong habits.

        <hss>Behavioural intentions</hss>

        For each of the four main behavioural categories participants were presented with
        three intentions, e.g., “In the next six months I intend to conserve water”; “I
        expect that I will conserve water in the next six months; “I am not really
        intending to conserve water in the next six months” (reverse scored). Responses
        were reported on 5-point scales, which were labelled “strongly disagree” (1),
        “disagree” (2), “undecided” (3), “agree” (4), “strongly agree” (5), respectively.
        Cronbach Alpha for the four behavioural domains varied between 0.75 and 0.82.
        Across all items Cronbach Alpha was 0.86. For each participant the behavioural
        intention responses were averaged into an aggregated intention index. High scores
        indicate strong intentions.

        <hss>Perceived behavioural control</hss>

        For each behavioural category participants were presented with three items
        assessing perceived behavioural control (e.g., “I would find it easy to conserve
        water”; “Cutting back on my water consumption would not be hard to do”; “I don't
        really know how I could conserve water” – reverse scored). Responses were reported
        on 5-point scales, which were labelled “strongly disagree” (1), “disagree” (2),
        “undecided” (3), “agree” (4), “strongly agree” (5), respectively. Cronbach Alpha
        for the four behavioural domains varied between 0.63 and 0.77. Across all items
        Cronbach Alpha was 0.82. For each participant the perceived behavioural control
        responses were averaged into an aggregated perceived control index. High scores
        indicate strong perceptions of control.

        <hss>Personal norms</hss>

        For each behavioural category participants were presented with three items
        assessing personal norms with respect to the environment (e.g., “Conserving water
        is something that everyone should do”; “Because of my values and principles, I
        feel it is important to try and conserve water”; “I feel a moral obligation to
        save water for the sake of the environment”). Responses were reported on 5-point
        scales, which were labelled “strongly disagree” (1), “disagree” (2), “undecided”
        (3), “agree” (4), “strongly agree” (5), respectively. Cronbach Alpha for the four
        behavioural domains varied between 0.78 and 0.84. Across all items Cronbach Alpha
        was 0.91. For each participant the personal norm responses were averaged into an
        aggregated personal norm index. High scores indicate strong personal norms.

        <hss>Biospheric values</hss>

        Biospheric values were assessed by four items taken from De Groot and Steg (2008).
        Respondents rated the importance of “Preventing pollution: protecting natural
        resources”, “Respecting the earth: harmony with other species”, “Unity with
        nature: fitting into nature“, and “Protecting the environment: preserving nature”
        in terms of the extent to which they were “a guiding principle in their lives”.
        The response scale used was ‘‘not at all important” (1) to “of supreme importance”
        (5).’ Cronbach Alpha was 0.91. For each participant the responses were averaged.
        High scores indicate strong values.

        <hss>Personal involvement</hss>

        Personal involvement was assessed by eight items, which were developed for the
        present study. The items covered emotional involvement (e.g., “I feel anxious
        about what climate change will do to us”), interest in the environment (e.g.,
        “There are more important things to worry about than the environment” - reverse
        scored), and empowerment (e.g., “I feel that I can really make a contribution to a
        better environment”). Responses were reported on 5-point scales, which were
        labelled “strongly disagree” (1), “disagree” (2), “undecided” (3), “agree” (4),
        “strongly agree” (5), respectively. Cronbach Alpha was 0.81. For each participant
        the responses were averaged into a personal involvement index. High scores
        indicate strong personal involvement.

<h>RESULTS</h>
-------

All variables were screened on distribution normality, and were found satisfactory.
Skewness and kurtosis values were between −0.05 and + 0.05 for all variables, except
personal involvement, for which these values were −0.98 and 1.50, respectively, suggesting
some degree of deviation from normality. In Table 1 means, standard deviations, and
correlations of the behaviour indices at T1 and T2 and the determinants of behaviour at T1
are presented. All determinants assessed at T1 were statistically significantly correlated
with the behaviour indices. The correlations were as can be expected on the basis of the
literature, that is, in the range of 0.30–0.40.

<hs>  Testing the habit discontinuity hypothesis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In order to test the main hypothesis, a multiple regression analysis was conducted.
Behaviour at T2 was regressed on age, sex, behaviour at T1, the determinants of behaviour
at T1 (habit, intention, perceived control, biospheric values, personal norm, and personal
involvement), the intervention, relocation status, and the intervention x relocation
status interaction. The intervention was coded as −1 (control group) and +1 (intervention
group), and relocation status was z-transformed before calculating the interaction term.
The adjusted R-square was 0.46, Cohen's f2 = 0.85. The variance inflation factors varied
from 1.02 to 2.28, indicating that there were no multicollinearity problems. Details of
the analysis are presented in Table 2. While all determinants at T1 correlated
statistically significantly with behaviour at T2, only behaviour at T1, habit, and
personal involvement retained statistically significant regression weights.
Unsurprisingly, the main effect of relocation status was non-significant. The intervention
effect was statistically significant, suggesting the intervention was effective in
changing behaviour in a sustainable direction. Importantly, this effect was qualified by a
statistically significant intervention x relocation status interaction, beta = −0.08, t =
−2.37, p < .02. In order to inspect the nature of the interaction, simple slope analyses
were conducted at the mean minus one standard deviation of relocation status, the mean,
and the mean plus one standard deviation, respectively. The dependent variable was the
behaviour index at T2, controlled for the behaviour index at T1 and the determinants.
These analyses revealed that the intervention was most effective when participants had
relocated relatively recently. The slopes showed a statistically significant effect of the
intervention on behaviour change at the mean minus one standard deviation of relocation
status, beta = 0.20, p < .001, 95% CI between 0.08 and 0.32, and at the mean, beta = 0.09,
p < .04, 95% CI between 0.01 and 0.18, while there was no significant effect at the mean
plus one standard deviation, beta = −0.01, 95% CI between −0.14 and 0.11. Because part of
the information provided during the intervention was individualised, the multiple
regression was re-run with the behavioural composites of participants in the intervention
condition being replaced by composites of only the behaviours that were specifically
addressed during the Personal Interview. Using these tailored scores, the results were
very similar to those reported above, and included again the statistically significant
intervention x relocation status interaction, beta = −0.08, t = −2.43, p < .02.

<hs>  Investigating the ‘window of opportunity’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Tentatively, we investigated the actual time frame during which the intervention was most
effective after participants had relocated. In other words, given that a habit
discontinuity effect was present, how wide was this ‘window of opportunity’? While
relocation status had been log-transformed in the previous analyses, in this case the raw
number of weeks since relocation was used. As half of the total sample was recruited to
have relocated within the previous 6 months, the sample was split as closely as possible
into quartiles, i.e., participants who relocated less than 3 months previously, 3–6
months, 6–200 months and over 200 months, respectively. In Fig. 1 the mean behaviour
composite scores at T1 and T2 in the intervention and control conditions are graphically
presented for the four groups. The figure also provides the test of the intervention
effect in each group.3 This breakdown suggests that the intervention was effective during
the first three months after relocation, after which no effects could be detected.

<h>DISCUSSION</h>
----------

This study tested the hypothesis that an intervention delivered in the wake of a major
discontinuity (residential relocation) is more effective than if the intervention is
delivered under default conditions. The rationale behind the hypothesis is that when old
habits are temporarily disturbed, people may be more sensitive to new information and
adopt a mind-set that is conducive to behaviour change. The results of the study gave
support to this hypothesis. While controlling for baseline levels of past behaviour, habit
strength, intentions, perceived control, biospheric values, personal norms and personal
involvement, and pitted against a no-intervention control group, participants who received
an intervention and had recently relocated reported more change eight weeks later on a
composite of twenty-five environment-relevant behaviours compared to participants who had
not recently relocated. Although other studies have produced results that were in line
with the habit discontinuity hypothesis (Bamberg, 2006; Brown et al., 2003; Fujii et al.,
2001; Jones & Ogilvie, 2012; Thøgersen, 2012; Verplanken et al., 2008; Walker et al.,
2015), the field experimental design of the present study provided a more rigorous test of
the hypothesis. Unlike the above mentioned studies, which were either correlational and/or
included samples in which all participants had been subjected to a discontinuity of some
sort, the present study was thus able to demonstrate the effect of the discontinuity per
se. There are a number of caveats to consider. The effect size of the extent to which
relocation boosted intervention effects was small. More than anything else, the results
should be considered as ‘proof of concept’. Two conditions made the present test very
conservative. The first is that for an individual participant not all behaviours were
relevant, and only a selection of these were addressed in the Personal Interview.
Secondly, the discontinuity effect was controlled for major determinants of behaviours,
that is, past behaviour, habit, perceived behavioural control, and a set of motivation
variables, which, as can be expected, explained most of the variance in T2 behaviour. The
test of the discontinuity effect was thus confined to the mere additional contribution of
relocation. The discontinuity effect was evident when using the highest level of
aggregation of behaviour and the corresponding aggregates of habit, intention, perceived
control and personal norm.4 First, the intervention was partly tailored, and thus focused
on different behaviours for different participants, which provided a compelling argument
for aggregation. Second, aggregation makes sense from a reliability point of view. In a
seminal paper, Weigel and Newman (1976) showed that when single behavioural criteria were
aggregated into an overall behavioural index, this measure correlated 0.62 with a general
environmental attitude measure, compared to an average of 0.29 when single criteria were
used. While that paper focused primarily on the issue of attitude-behaviour consistency,
it demonstrated that, in line with the principles of test theory, combining multiple
indicators provides a more reliable instrument. In order to provide the most rigorous test
of the discontinuity effect, we thus also aggregated the behaviour-specific determinants
(habit, intention, perceived control, personal norm) at the highest level. A fair question
can be posed about the psychological meaning of these aggregates, as these do not have
one-to-one connections to specific behaviours. Our view is that, if anything else, the
aggregates might be considered as behavioural, motivational, and normative representations
of higher order sustainability or ecological values. One of our reviewers suggested that
the aggregated habit variable might capture variation in self-identity, in this case a
“green” identity (e.g., Sparks & Shepherd, 1992; Stern, 1992; Thøgersen & Ölander, 2002;
Verplanken & Roy, 2013; Whitmarsh & O'Neill, 2010), which would thus also elucidate why
habit retained a significant regression weight (Table 2). The latter suggested that
variations in existing habit strength modulated behaviour change over and above the
discontinuity effect. While the results undoubtedly have theoretical significance, the
practical implications are limited unless circumstances are found or created under which
larger effect sizes can be realised. The latter may be accomplished in a variety of ways.
For instance, larger effect sizes can be expected when interventions focus on single or
small sets of behaviours (e.g., recycling, eco-driving, saving water; e.g., Abrahamse,
Steg, Vlek, & Rothengatter, 2005). Effect sizes may increase by selecting and/or combining
treatments. On the basis of a meta-analysis of 253 intervention studies in the domain of
pro-environmental behaviours, Osbaldiston and Schott (2012) found that interventions that
included cognitive dissonance, goal setting, social modelling and the use of prompts
showed the largest effect sizes. Combining such tools with a discontinuity approach may
thus lead to more powerful interventions. Finally, interventions may be more effective
when these are carried forward by groups or communities which generate social support
(e.g., Abrahamse et al., 2005; Staats, Harland, & Wilke, 2004; Weenig & Midden, 1991).
Interventions and behaviour change cannot be seen in isolation from wider systems in which
they occur (e.g., Hawe, Shiell, & Riley, 2009; Lewin, 2008/1946). A ‘system’ may be
defined by geographical location, such as a residential area. This comes with an
infrastructure and bundles of behaviours, such as driving children to school or shopping
in that area. Relocation thus unfreezes such patterns. It is therefore interesting to
focus on relatively large-scale discontinuities, which are confined to a specific location
and time frame, such as when a new residential area is being built. These situations
provide easy access to relatively large groups of residents, who are all undergoing the
same life course change in the same time period. Other ‘systems’ may be culturally
defined, such as social practices, for instance those involving hygiene or leisure
activities (e.g., Kurz et al., 2015; Reckwitz, 2002; Shove, Pantzar, & Watson, 2012).
Social practices also involve infrastructures and bundles of habits, and are empowered
with a shared meaning (e.g., hygiene standards). When individuals move into a new phase,
such as a transition from school to work, starting a family or entering retirement, the
habits defined by a social practice are subject to change, and may thus be interesting
targets for interventions. Habit discontinuities may also be considered from a stage model
perspective (e.g., Bamberg, 2013; Dahlstrand & Biel, 1997; Gollwitzer, 1990; Prochaska &
Velicer, 1997). Stage models of behaviour change distinguish a motivational phase and a
volitional or execution phase. The motivational phase is characterised by deliberation,
prioritising goals, and forming intentions. In the volitional phase goals and intentions
are subsequently enacted. One of the issues in these models is why, how, and when an
individual moves from a motivational to a volitional phase. A habit discontinuity may be
conducive to instigating such a transition, and may thus facilitate the transition from
contemplation to action (e.g., Gollwitzer, 1990; Holland, Aarts, & Langendam, 2006). A
prerequisite is that a motivation to adopt the new behaviours is present in the first
place, which needs to be genuine and self-related in order to have the potential to
translate into action (e.g., Bamberg, 2006; Verplanken & Holland, 2002; Walker et al.,
2015; Whitmarsh & O'Neill, 2010). The present study has a number of limitations. An
obvious limitation is that behaviours were assessed by means of self-reports, which are
vulnerable to social desirability and consistency biases. We opted for investigating a
broad spectrum of behaviours. This put constraints on the types of measurements that were
feasible. However, even if the self-reports contained a degree of bias, this cannot
explain why a habit discontinuity effect was found. In other words, it is difficult to
argue that biases would be stronger among those who recently relocated. The choice for
breadth (many behaviours) also put restrictions on the assessments of behaviour-specific
determinants (habit, perceived control, intention, personal norm), which could only be
measured at the level of behaviour category (e.g., saving water). This introduced a lack
of correspondence. Another limitation was that we had no a-priori foundation for defining
what exactly a “recent” relocation is, and the chosen cut-off period of six months was
arguably arbitrary. This points to a wider issue with respect of discontinuity hypothesis,
namely the question what determines the size of what we referred to as the ‘window of
opportunity’, and the time when discontinuity effects can be expected to occur (cf., Jones
& Ogilvie, 2012). A disruption is a temporary condition, and once a person has settled
into the new situation, old habits may easily be re-activated (e.g., Walker et al., 2015;
Wood & Rünger, 2016; Wood et al., 2005). The present results suggest that in this case the
‘window’ was approximately three months wide. It can be argued that the dynamics of a
discontinuity effect may not be confined to a period after the event itself. For instance,
in the case of relocations, behaviours such as more efficient commuting may be the very
reason for a relocation. The window of opportunity may thus open before the actual
discontinuity takes place.

<h>CONCLUSION</h>
----------

Prevalent models of behaviour and behaviour change may lead to the suggestion that people
change attitudes and behaviour only if the alternatives offered are sufficiently
convincing or beneficial. This leaves the context in which interventions are delivered out
of the equation, and reflects a rather static view of human behaviour. The habit
discontinuity approach focuses on contexts in which people are undergoing life course
changes. Those moments of change, when minds and behaviours temporarily unfreeze, may
provide precious opportunities for adopting healthier and more sustainable lifestyles.


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<ART>Enhanced latent inhibition in high schizotypy individuals
=========================================================

Authors: Kiri T. Granger, Paula M. Moran, Matthew G. Buckley, Mark Haselgrove
DOI: 10.1016/j.paid.2015.11.040
Year: 2016  |  Pages: 31-39
ASJC codes: 3200
Keywords: Latent inhibition, Schizophrenia, Schizotypy, Within-participants design

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Latent inhibition refers to a retardation in learning about a stimulus that has been rendered familiar by non-reinforced preexposure, relative to a non-preexposed stimulus. Latent inhibition has been shown to be inversely correlated with schizotypy, and abnormal in people with schizophrenia, but these findings are inconsistent. One potential contributing factor to this inconsistency is that many tasks that purport to measure latent inhibition are confounded by alternative effects that also retard learning and co-vary with schizotypy (e.g. learned irrelevance and conditioned inhibition). Here, two within-participant experiments are reported that measure the effect of familiarity on learning without the confound of these alternative effects. Consistent with some of the clinical literature, a positive association was found between the rate of learning to the familiar, but not the novel, stimulus and the unusual-experiences dimension of schizotypy - implying abnormally persistent latent inhibition in high schizotypy individuals.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

For many years, experimental designs have been translated from the study of animal
learning to abnormal psychology in an attempt to understand the symptoms associated with
schizophrenia. One of these symptoms is a disruption of attentional function (e.g.
Hemsley, 1987; McGhie & Chapman, 1961), and latent inhibition (Hall & Honey, 1989; Lubow,
1973; Lubow & Moore, 1959) has been one of the most common designs used to model abnormal
attention in schizophrenia. Here, a stimulus is rendered familiar by mere non-reinforced
exposure, before being established as a cue for an outcome. Latent inhibition is observed
when participants learn more slowly about the preexposed cue than a non-preexposed control
cue during a subsequent test of learning (Lubow & Moore, 1959). Theoretical analyses of
latent inhibition have focused upon an attentional explanation — proposing that during
preexposure, attention diminishes to the preexposed stimulus so that, subsequently,
participants take longer to learn the association between this stimulus and the outcome
(Lubow & Gewirtz, 1995; Mackintosh, 1975; Pearce & Hall, 1980) than the non-preexposed
cue. Consistent with the idea that individuals with schizophrenia have a deficit in
attention is the observation of an attenuation of latent inhibition in these individuals,
which is reflected as the absence of slower learning to the preexposed cue. This effect is
typically seen in individuals with acute schizophrenia, rather than individuals with
chronic schizophrenia (e.g. Baruch, Hemsley, & Gray, 1988a; Gray, Fernandez, Williams,
Ruddle, & Snowden, 2002; Gray, Hemsley, & Gray, 1992; Rascle et al., 2001; Vaitl et al.,
2002, but see also: Cohen et al., 2004; Swerdlow, Braff, Hartston, Perry, & Geyer, 1996;
Williams et al., 1998), and this relationship has been suggested to account for the
presence of spurious associations being formed between stimuli in the environment from
which unusual thought patterns and positive symptoms may emerge (i.e., hallucinations,
delusions) (Kapur, Mizrahi, & Li, 2005; Moran, Owen, Crookes, Al-Urzi, & Reveley, 2008).
However, the relationship between attenuated latent inhibition and positive symptomatology
has been challenged. Gray et al. (1992) suggested that a reduction in latent inhibition
was associated with the acute stage of schizophrenia rather than the positive symptoms per
se. When acute and chronic patients with schizophrenia were matched for their level of
positive symptoms, an attenuation of latent inhibition was only observed in acute, not
chronic patients. Later studies have provided mixed findings: normal latent inhibition has
been observed in both acute medicated (Swerdlow et al., 1996) and un-medicated (Williams
et al., 1998) patients. More recent studies have shown that acute patients with
schizophrenia do show an attenuation of latent inhibition, but that this was correlated
with their negative rather than their positive symptoms (Rascle et al., 2001), whereas
Cohen et al. (2004) found latent inhibition in schizophrenia patients with high levels of
positive symptoms did not differ from that of healthy controls (for a review see: Schmidt-
Hansen & Le Pelley, 2012). One possible explanation for the inconsistencies in the
literature may be because the effect has an additional pole of expression — an enhanced,
or abnormally persistent, latent inhibition effect with the chronic stage of schizophrenia
(Weiner, 2003). To the best of our knowledge, only three studies have shown that latent
inhibition is abnormally persistent in chronic patients with schizophrenia. Rascle et al.
(2001), Cohen et al. (2004) and Gal et al. (2009) all report enhanced latent inhibition in
patients in a chronic stage of their illness. Although enhanced latent inhibition has been
tentatively associated with negative symptoms, this effect appears more specific to
illness chronicity (Gal et al., 2009). It thus seems accurate to suggest that
schizophrenia is associated with an abnormal expression of latent inhibition. Whether an
attenuation or enhancement of the effect is observed, depends on the stage of the illness.
As has been noted elsewhere (e.g. Haselgrove & Evans, 2010) comparisons of the cognitive
abilities of schizophrenic patients with controls can introduce a number of confounds,
notably the medication state of the different groups. To overcome this issue, a
dimensional approach can be adopted in which variations in schizotypal personality
characteristics are measured in a normal population and correlated with performance on
cognitive tasks. A number of studies have now indicated that attentional mechanisms are
similarly disrupted in high psychometrically-defined schizotypal individuals and people
with schizophrenia (e.g. Baruch, Hemsley, & Gray, 1988b; Evans, Gray, & Snowden, 2007;
Granger, Prados, & Young, 2012; Gray et al., 2002; Le Pelley, Schmidt-Hansen, Harris,
Lunter, & Morris, 2010; Schmidt-Hansen, Killcross, & Honey, 2009). However, like the
schizophrenia literature (e.g. Baruch et al., 1988a; Gray et al., 1992; Rascle et al.,
2001), previous studies that have investigated the relationship between schizotypy and
latent inhibition have revealed mixed results. Baruch et al. (1988b) were the first to
report a relationship between latent inhibition and schizotypy in the normal population;
reporting reduced latent inhibition in participants who scored high, but not low (as
determined by a median split) on the Psychoticism dimension of the Eysenck psychoticism
questionnaire (EPQ; Eysenck & Eysenck, 1975 see also; Allan et al., 1995; Lubow, Ingberg-
Sachs, Zalstein-Orda, & Gewirtz, 1992). Similarly, Gray, Snowden, Peoples, Hemsley, & Gray
(2003) reported measures of schizotypy to be correlated with reduced latent inhibition,
but only when using a between-participant latent inhibition task (see also: Braunstein-
Bercovitz & Lubow, 1998; Burch, Hemsley, & Joseph, 2004). However, another between-
participants latent inhibition task used by Lipp, Siddle, and Arnold (1994) reported no
significant association of the effect with the EPQ (Eysenck & Eysenck, 1975), and an
association between latent inhibition and the schizotypal personality questionnaire
(Claridge & Broks, 1984) that only approached statistical significance (see also: Lipp &
Vaitl, 1992). Furthermore, this trend was due to differences in the non-preexposed control
group, with high scorers tending to learn faster than low scorers, rather than the
theoretically more interesting, preexposed group. The between-participant tasks used by
Baruch et al. (1988b) showed no association between latent inhibition and scores on the
Launey–Slade Hallucination Scale (Launay & Slade, 1981). Other studies have shown that,
given sufficient preexposure, individuals high in schizotypy can in fact demonstrate a
latent facilitation effect (De la Casa, Ruiz, & Lubow, 1993) (but see Burch et al., 2004).
Therefore, where some authors report a reduction in latent inhibition with higher levels
of schizotypy, others do not, and with some authors suggesting a reversal of latent
inhibition with schizotypy (see also: De la Casa & Lubow, 2002; Kaplan & Lubow, 2011;
Lubow & Kaplan, 1997; Lubow, Kaplan, & De la Casa, 2001; Lubow & Weiner, 2010; Shira &
Kaplan, 2009). More recent studies have tended to employ a within-participant procedure
for detecting latent inhibition in which learning about a novel and familiar stimulus is
measured in the same participant. Evans et al. (2007), Schmidt-Hansen et al. (2009) and
Granger et al. (2012) argue their results support a deficit in latent inhibition, related
to the positive dimension of the Oxford-Liverpool Inventory of Feelings and Experiences
(O-LIFE) (Mason, Claridge, & Jackson, 1995). However, the attenuated latent inhibition
effect with unusual experiences reported by Evans et al. and Schmidt-Hansen et al. did not
reach the conventional cut-off point for statistical significance. A significant reduction
in latent inhibition was attained by Granger et al., but this was a result of an
association between the difference between the preexposed and non-preexposed stimuli and
unusual experiences. This latter observation is problematic, because any correlation
between schizotypy and a composite constructed from these two scores does not reveal which
of its components is, or is not, contributing to the overall effect. As such it is
entirely possible that it is a difference in performance to the non-preexposed stimulus,
not the preexposed stimulus, that contributes to the co-variation of the composite measure
with schizotypy. In support of this possibility, Granger et al. did not see any
significant relationship between the unusual experiences dimension and learning about the
preexposed stimulus alone. A number of studies of latent inhibition in humans have
modified its basic procedure in order to ensure that participants engage with the
experiment during preexposure. First, the outcome from the second stage of the experiment
might also be included in the first stage of the experiment — unpaired with the cue (e.g.
Cohen et al., 2004; De la Casa & Lubow, 2001; Gal et al., 2009; Lubow & De la Casa, 2002;
Lubow & Kaplan, 1997; Swerdlow et al., 1996). Second, a secondary, masking, task may be
presented concurrently with the preexposed cue. For example, a list of nonsense syllables
may be presented and participants required to count the number of times one syllable
appears during preexposure (e.g. Baruch et al., 1988a; Gray et al., 1992). The use of
either of these modifications undermines the comparability of human latent inhibition to
animal models that do not require such procedures to observe latent inhibition (Lubow,
2005). But, more importantly, they also generate procedures that align themselves with
other learning phenomena, rather than latent inhibition. For example, by exposing the
target outcome during the pre-exposure stage of the experiment in an uncorrelated (or
unpaired) fashion with the pre-exposed cue, may result in the establishment of learned
irrelevance or conditioned inhibition to the pre-exposed cue; both of these effects are
known to retard the acquisition of later learning (e.g.: Baker & Mackintosh, 1977;
Rescorla, 1969) and are known to co-vary with schizotypy (Le Pelley, Schmidt-Hansen, et
al., 2010; Migo et al., 2006; Schmidt-Hansen et al., 2009). Evans et al. (2007) have
described a within-participant latent inhibition procedure that, they suggest, circumvents
the inclusion of a masking-task during preexposure. In this task participants were
presented with a series of letters, presented one after the other in the centre of the
screen and instructed to press the spacebar as quickly as possible when the letter X was
presented. The letter X was either preceded on some trials by a letter (e.g., S) that had
been preexposed amidst the filler letter earlier in the experiment or by a letter (e.g.,
H) that had not been preexposed. This task showed a latent inhibition effect —
participants were slower to respond to presentations of X when it was cued by the
preexposed letter rather than the non-preexposed letter, and a trend for a reduction in
latent inhibition with the positive symptom dimension of schizotypy was observed. As this
procedure did not include a concurrent masking task during the preexposure stage of the
experiment, it is difficult to explain this result in terms of learned irrelevance.
Furthermore, at first blush, it seems difficult to explain this result in terms of
conditioned inhibition, as the target outcome was not presented to participants during the
pre-exposure phase either. However, as Evans et al. note, an expectation of the target-
stimulus was established prior to the preexposure phase through instruction. Thus,
conditioned inhibition might be generated because the target outcome was expected to
appear (but did not) at a time when the preexposed (but not the non-preexposed) stimulus
was presented. Consequently, standard associative models of learning (e.g. Rescorla &
Wagner, 1972) predict that during the preexposure stage an inhibitory association will
form specifically between the preexposed stimulus and the target X, slowing later learning
with this stimulus. Importantly, this slower learning is not a consequence of an
attentional mechanism — such one that might generate latent inhibition. Here we introduce
a procedure that examines variations in latent inhibition with schizotypy under conditions
where the contribution of conditioned inhibition and learned irrelevance are minimised in
order to provide a less ambiguous measure of the impact of learned variations in
attention. However, removing the masking task altogether would result in an experimental
paradigm that participants have no requirement to engage in. An alternative strategy then
is to keep the masking task in place during preexposure but in such a way as to establish
it as task-relevant. The two experiments reported here explored this possibility.

<h>EXPERIMENT 1</h>
------------

The first aim of Experiment 1 was to create a within-participant latent inhibition task
that minimises the possibility of observing conditioned inhibition and learned
irrelevance. The second aim was to examine how this task co-varies with schizotypy.
Presented here are two variations of a task by Evans et al. (2007; itself modified from
that designed by Young et al., 2005). The first version constituted a replication of the
task described by Evans et al., to demonstrate latent inhibition, predominantly as a
positive control. The second version constituted a modification of this task where no
expectation of the target was established during the preexposure stage either through
instruction or explicit exposure to the target outcome — thus removing the contribution of
conditioned inhibition. Instead, as suggested by Evans et al., during the preexposure
stage participants were simply asked to count the number of instances of one of the filler
letters (M). This manipulation also establishes all of the stimuli in stage 1 as task
relevant as participants must process each letter in order to determine whether it is a
letter M or not. Consequently, this task is also less amenable to an explanation in terms
of learned irrelevance. In the subsequent test stage of both versions of the task,
participants continued to be presented with a series of letters, one after the other in
the centre of the screen, but were now instructed to make a response as quickly as
possible when the letter X appeared. On some occasions the letter X was preceded by a non-
preexposed cue, whereas on other trials it was preceded by a cue that had been rendered
familiar by being presented during the preexposure stage. Based on the results of Evans et
al. it was expected that response-times would be shorter to X when it had been preceded by
the non-preexposed, rather than the preexposed cue. We are interested in assessing whether
the same effect was evident in the modified version of the task, as this would suggest the
operation of a mechanism during stimulus preexposure that is not sensitive to learned
irrelevance or conditioned inhibition.

        <hss>Participants</hss>

        Fifty-seven healthy Nottingham University participants and members of the general
        public (35 males and 22 females) took part, in exchange for course credit or a £4
        inconvenience allowance. The age range was 18–54. Twenty-eight participants
        completed the replicated version of the Evans et al. (2007) LI task (‘replicated-
        task condition’), and twenty-nine completed a modified version of this task
        (‘modified-task condition’).

        <hss>Apparatus</hss>

        All experimental stimuli appeared on a standard desktop computer running Windows
        XP, and were programmed using Psychopy (Peirce, 2007; www.psychopy.org). Stimuli
        were white capital-letters in Arial-font (7 mm × 5 mm; h × w) presented for 1 s
        each on a computer-screen (28 cm × 35 cm; h × w) with a gray background. The
        stimulus-letters were S and H, one of the letters served as the preexposed
        stimulus and the other was the non-preexposed stimulus, counterbalanced across
        participants. The target was the letter X, with filler-letters D, M, T and V; see
        Fig. 1.

            <hss>Replicated-task condition</hss>

            The task had two stages: preexposure and test. After reading an information
            sheet and signing a consent-form, the following instructions were presented to
            participants on the computer monitor prior to the task: “In this task I want
            you to watch the sequence of letters appearing on the screen. Your task is to
            try and predict when a letter ‘X’ is going to appear. If you think you know
            when the ‘X’ will appear then you can press the space bar early in the
            sequence, that is before the ‘X’ appears on screen. Alternatively, if you are
            unable to do this please press the spacebar as quickly as possible when you
            see the letter ‘X.’ There may be more than one rule that predicts the ‘X.’
            Please try to be as accurate as you can, but do not worry about making the
            occasional error. If you understand your task and are ready to start press the
            spacebar to begin.” During the preexposure stage the preexposed stimulus was
            presented 20 times, intermixed in a random order with presentations of filler
            letters each of which was presented 15 times; each stimulus was presented for
            1000 ms separated by a 50 ms inter-stimulus interval. The non-preexposed
            stimulus and target letter X were not presented during the preexposure stage.
            The test stage followed the preexposure stage, without interruption. In the
            test stage, the preexposed stimulus and the non-preexposed stimulus were each
            presented 20 times followed by a 1000 ms presentation of the target stimulus
            X. There were also 20 non-cued presentations of X during which the target was
            preceded by one of the 4 filler letters, each of which preceding the target 5
            times. In total there were 64 presentations of the filler letters throughout
            the test phase. The whole task lasted 7 min. Participants were required to
            press the space-bar, either when X appeared on screen, or if they could
            predict when the X would appear as the next letter in the sequence.

            <hss>Modified-task condition</hss>

            The procedure for the modified version of the task was as described for the
            replicated version of the Evans et al. (2007) latent inhibition task (Section
            2.1.3.1), with the exception that participants received 2 sets of
            instructions, one set appeared on screen prior to the preexposure stage,
            instructing the following: “In this task I want you to watch the sequence of
            letters appearing on the screen. Your task is to count how many times the
            letter ‘M’ appears. This task will last about 3 mins. When this task ends, you
            will be given a new set of instructions. Press any key when you are ready to
            start the experiment.” Thus for the modified-task condition participants were
            not aware that the target stimulus would appear until after the preexposure
            phase. A second-set of instructions (identical to those administered at the
            outset of the replicated-task condition) were then presented prior to the test
            stage. A computer-based version of the O-Life (Mason et al., 1995) was
            administered to assess individual schizotypy. This questionnaire assesses four
            dimensions of schizotypy. The unusual experiences (UnEx) subscale measures
            auditory hallucinations, magical thinking and perceptual aberrations
            reflecting positive symptoms of schizophrenia (e.g., “Have you ever felt you
            have special, almost magical powers?”). The Introvertive Anhedonia (IntAn)
            subscale reflects anhedonia (inability to experience pleasure); analogous to
            the negative symptoms of schizophrenia (e.g., “Do you feel lonely most of the
            time, even when you're with people”). The Cognitive Disorganisation (CogDis)
            subscale assesses disruptions in attention/concentration; consistent with the
            disorganized symptoms of schizophrenia (e.g., “Do you ever feel that your
            speech is difficult to understand because the words are all mixed up and don't
            make sense?”). Lastly, Impulsive Nonconformity (ImpNon) measures recklessness,
            impulsivity and antisocial behavior (e.g., “Do you often have an urge to hit
            someone?”) ; similar to the Psychoticism scale of the Eysenck Personality
            Questionnaire (Eysenck & Eysenck, 1975).1 The OLIFE questionnaire has good
            validity as it maps on to the same multi-dimensional structure as
            schizophrenia; assessing positive, negative and disorganized symptoms (Mason
            et al., 1995).

        <hss>Scoring</hss>

        Reaction times (RT's) in stage 2 were recorded from the onset of the preexposed
        and non-preexposed stimulus that preceded the target (X) for each participant. As
        each stimulus was presented for 1000 ms separated by a 50 ms inter-stimulus
        interval, participants' RT could range from 0 to 2050 ms. If participants' RT was
        less than 1050 ms they predicted the X; whereas if their RT was between 1050 and
        2050 ms, they responded to the X. Median RTs for responses to the PE stimulus and
        NPE stimulus were calculated for each participant as it is less biased by extreme
        values compared to the mean. RT's to both the PE stimulus and NPE stimulus across
        the 20 test trials were between 1050 and 2050 ms, excluding one NPE trial which
        had an RT less than 1050 ms for the modified-task version; thus the majority of
        responses to both stimuli were responses to the X. The scores derived for the
        four-schizotypy subtypes (complete for Experiment 1 and the subsequent Experiment
        2) are presented in Table 2.

        <hss>Latent inhibition</hss>

        Fig. 2 shows the group mean of individual median reaction times to X across the 20
        test trials2 with the PE and NPE stimuli. Both the replicated-task and the
        modified-task groups showed faster RTs to the non-preexposed stimulus than the
        preexposed stimulus — latent inhibition. A 2 (condition: replicated-task,
        modified-task) × 2 (stimulus: preexposed, non-preexposed) mixed analysis of
        variance (ANOVA) of individual median reaction times revealed a significant main
        effect of stimulus F(1,55) = 16.626, p < .001, partial η2 = .23, but no main
        effect of condition or interaction (Fs < 1), suggesting reaction times were
        similar for participants in both the replicated-task and the modified-task
        irrespective of target expectation during preexposure. On this basis, and to
        increase statistical power, the data were combined from the two test conditions
        for subsequent analyses.

        <hss>Latent inhibition and schizotypy</hss>

        A standard multiple regression analysis was carried out using the four schizotypy
        subscales taken from the O-Life: UnEx, IntAn, ImpNon and CogDis as the predictor
        variables, and individual median reaction times to the preexposed and non-
        preexposed stimuli as the dependent variables. If any of the predictor variables
        are associated with latent inhibition it would be expected that a relationship
        would be found with the preexposed stimulus, but not with the control non-
        preexposed stimulus. When reaction time to the preexposed stimulus was entered as
        the dependent variable, UnEx was a significant predictor of RTs (β = .36, p =
        .021), reflecting slower learning to the preexposed stimulus with individuals high
        in UnEx, i.e. enhanced latent inhibition. ImpNon was also a significant predictor
        of reaction time to the PE stimulus (β = −.36, p = .014), reflecting faster
        learning to the preexposed stimulus for individuals high in ImpNon, i.e. an
        attenuation of latent inhibition. Neither of the remaining schizotypy subscales
        (CogDis and IntAn) were significant predictors of reaction time to the preexposed
        stimulus (ps > .05). When reaction time to the non-preexposed stimulus was entered
        as the dependent variable, the only significant predictor of reaction time was
        ImpNon, which again was negatively correlated with RT (β = −.32, p = .035). None
        of the remaining schizotypy dimensions were significant predictors of reaction to
        the non-preexposed stimulus (ps > .05). All standardized regression coefficients
        and R2 values can be seen in Table 1. The results indicate that individuals high
        in UnEx are slower to learn the association between the preexposed stimulus and
        the target than individuals low in UnEx. This, in conjunction with the finding
        that UnEx was not a significant predictor of reaction time to the non-preexposed
        stimulus, indicates that individuals high in this subtype are exhibiting an
        enhancement of latent inhibition. A relationship between ImpNon and RTs to both
        the preexposed and non-preexposed stimuli was also found, showing that individuals
        high in ImpNon make faster responses irrespective of whether the stimulus is
        familiar or novel. The enhancement of latent inhibition with high UnEx, does not
        agree with a number of schizotypy studies (Evans et al., 2007; Granger et al.,
        2012; Schmidt-Hansen et al., 2009). However, the reported attenuation of latent
        inhibition with high UnEx, failed to reach the conventional level of significance
        in the studies reported by Evans et al. (2007) and Schmidt-Hansen et al. (2009).
        Furthermore, it cannot be ruled out that the latent inhibition task employed in
        each of these studies was not a consequence of alternative learning phenomena
        instead of latent inhibition, due to the limitations previously described. Before
        we can draw any further conclusions, however, it is important to acknowledge the
        possibility that we still might be observing a co-variation of schizotypy with
        learned irrelevance in the current study, as opposed to latent inhibition. Whilst
        the modified-task condition successfully minimised the contribution of conditioned
        inhibition, it still included a masking task (count the letter M). Although this
        procedure — which requires continuous monitoring of the experimental stimuli —
        establishes a situation in which all of the experimental stimuli are task
        relevant, it is conceivable that it still establishes learned irrelevance. In this
        task, participants are required to respond (albeit covertly) to the letter M,
        rather than any other stimulus. In this sense, then, the preexposed stimulus is
        irrelevant to the task in hand, thus learned irrelevance may still be the cause of
        the slower learning to the preexposed stimulus, rather than latent inhibition. As
        previously discussed, learned irrelevance is an effect which has been shown to
        influence human learning (Le Pelley & McLaren, 2003) and also co-vary with
        schizotypy (Le Pelley, Schmidt-Hansen, et al., 2010; Schmidt-Hansen et al., 2009).
        However, as previously outlined, it would be problematic to remove the masking
        task altogether as participants would have no requirement to engage in the task
        during the preexposure stage. Therefore, the aim of Experiment 2 was to design a
        procedure that examined latent inhibition under conditions where the contribution
        of both learned irrelevance and conditioned inhibition were minimised, but keep
        the masking task in place during preexposure but in such a way as to establish it
        as directly relevant (as opposed to irrelevant) to the preexposed stimulus. If
        latent inhibition is still observed under these circumstances, it would permit an
        evaluation of the effect in terms of models of attention that do not emphasise the
        importance of learned irrelevance (e.g. Esber & Haselgrove, 2011; Pearce & Hall,
        1980).

<h>EXPERIMENT 2</h>
------------

To minimise the contribution of learned irrelevance (as well as conditioned inhibition),
the purpose of Experiment 2 was to adjust the parameters of the modified-task condition
from Experiment 1. In the preexposure stage, participants were now asked to say out loud
each of the letters that appeared on the screen. This manipulation directly establishes
all of the stimuli in stage 1 as task relevant as participants must process each letter by
reading each of them aloud. Consequently, this version of the task rules out an
explanation of any subsequent attenuation of learning to the preexposed stimulus with an
appeal to learned irrelevance. Furthermore, as no expectation of the target stimulus (X)
is established prior to, or during, preexposure the task is also not amenable to an
explanation in terms of conditioned inhibition. The test stage of the task remained the
same as the modified-task condition from Experiment 1: participants were required to make
a response as quickly as possible when the letter X appeared on screen. We are first
interested in assessing whether an effect of stimulus preexposure is still observed under
these different circumstances and second, to assess whether the task co-varies with
schizotypy. This being the case would suggest a relationship between schizotypy and of
stimulus preexposure that goes beyond learned irrelevance.

        <hss>Participants</hss>

        Sixty healthy Nottingham University participants and members of the general public
        (10 males and 50 females) took part, in exchange for course credit or a £4
        inconvenience allowance. The age range was 18–33 years.

        <hss>Apparatus</hss>

        The apparatus were the same as described in Experiment 1.

        <hss>Procedure</hss>

        The procedure for Experiment 2 was as described in the modified-task condition in
        Experiment 1 with the exception that the instructions received prior to the
        preexposure stage asked participants to say aloud each letter that appeared on the
        screen. A second-set of instructions (identical to those administered at the
        outset of the test stage of the modified condition from Experiment 1) were
        presented prior to the test-phase. As per the previous experiments, participants
        completed the O-Life (Mason et al., 1995) questionnaire. All scoring was performed
        in the same manner as described in Experiment 1. In keeping with Experiment 1, the
        majority of RT's to both the PE stimulus and NPE stimulus across the 20 test
        trials were between 1050 and 2050 ms, excluding 3 NPE trials which had RTs that
        were less than 1050 ms, indicating that participants were predicting the
        occurrence of the X on these trials.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The scores derived for the four schizotypy subtypes (complete for Experiments 1 and 2) are
shown in Table 2. Unpaired t test analyses were carried out to assess if the reported
schizotypy means differ from the population norms for each subscale. While the means for
CogDis and IntAn do not differ significantly from the normative values, the means for UnEx
and ImpNon are both significantly lower than the normative values for the modified-task
version of Experiment 1, and for Experiment 2. Significant differences are highlighted in
bold in Table 2. Previous studies have also obtained mean schizotypy scores that are below
Mason et al.'s (1995) normative values, and similar to those reported here (e.g. Evans et
al., 2007; Granger et al., 2012; Sellen, Oaksford, & Gray, 2005).

        <hss>Latent inhibition</hss>

        Fig. 3 shows the median reaction times to X across the test trials of Experiment 2
        (shown in two-trial blocks) with the preexposed and non-preexposed stimuli. It can
        be seen that reaction times were faster during the non-preexposed than the
        preexposed stimulus. This impression was confirmed with a 2 (stimulus: non-
        preexposed, non-preexposed) × 10 (trial block: 1–10) ANOVA of individual reaction
        times, which revealed a significant main effect of stimulus, F(1,59) = 25.691, p <
        .001, partial η2 = .303 and a significant main effect of trial number, F(9,51) =
        7.949, p < .001, partial η2 = .584, but no significant interaction between these
        variables, F < 1. In line with both conditions from Experiment 1, Experiment 2
        successfully generated an effect of preexposure on reaction times during
        subsequent learning — latent inhibition. The task presented in Experiment 2
        however, produced latent inhibition when the target was not expected during
        preexposure, and importantly, when using a masking-task that was not irrelevant to
        stimulus preexposure. These results encourage the suggestion that that an effect
        of exposure on learning is being observed here — that is to say latent inhibition
        rather than conditioned inhibition or learned irrelevance.

        <hss>Latent inhibition and schizotypy</hss>

        In keeping with Experiment 1, a standard multiple regression was carried out using
        the four schizotypy subscales from the O-Life (UnEx, IntAn, ImpNon and CogDis) as
        the predictor variables, and reaction time to the preexposed and non-preexposed
        stimuli as the dependent variables. Again, when reaction time to the preexposed
        stimulus was entered as the dependent variable, UnEx was a significant predictor
        of reaction times to the preexposed stimulus (β = .40, p = .021), reflecting
        slower learning to the preexposed stimulus with individuals high in UnEx —
        replicating the enhanced latent inhibition effect observed in Experiment 1. Unlike
        Experiment 1, however, ImpNon was not a significant predictor of reaction time to
        the preexposed stimulus, nor were the remaining schizotypy subtypes. When median
        reaction time to the non-preexposed stimulus was entered as the dependent
        variable, none of the schizotypy subtypes were significant predictors of reaction
        time to the non-preexposed stimulus (ps > .05). Standardized regression
        coefficients and R2 values can be seen in Table 3. In keeping with Experiment 1,
        the results of Experiment 2 show that individuals high in UnEx are slower to learn
        the association between the preexposed stimulus and the target than individuals
        low in UnEx. In both Experiments 1 and 2, we observed facilitation in RTs in
        individuals high in UnEx that was specific to the preexposed stimulus. These
        results encourage the suggestion that we are observing an enhancement of latent
        inhibition, rather than a more general effect of schizotypy on learning to both
        stimuli. Whilst the findings from both experiments presented here are comparable,
        the task employed in Experiment 2 is particularly notable as it comprises a
        relatively ‘pure’ demonstration of latent inhibition, as it minimises the
        contribution of both conditioned inhibition and learned irrelevance to stimulus
        preexposure.

<h>GENERAL DISCUSSION</h>
------------------

Two experiments revealed slower learning of a stimulus-target association with a stimulus
that had been rendered familiar through prior non-reinforced preexposure than a stimulus
that had not — latent inhibition. In both experiments learning about the preexposed, but
not the non-preexposed stimulus was related to the unusual experiences dimension of the
O-LIFE — revealing an enhancement of latent inhibition in individuals scoring higher on
the positive dimension of schizotypy. Experiment 2, in particular, arranged preexposure in
a manner that resulted in the subsequent retardation of learning to be explicable in terms
of the effects of mere exposure but not the confounding effects of conditioned inhibition
or learned irrelevance. This is in contrast to other studies in the latent inhibition
literature (e.g. De la Casa & Lubow, 2001, 2002; Evans et al., 2007; Granger et al., 2012;
Lubow & De la Casa, 2002; Schmidt-Hansen et al., 2009; Swerdlow et al., 1996), which can
be explained in terms of these alternative learning phenomena. To the best of our
knowledge, the current data constitute the first observation of enhanced latent inhibition
in sub-clinical high-schizotypy individuals. Three studies (Cohen et al., 2004; Gal et
al., 2009; Rascle et al., 2001) have reported enhanced latent inhibition in schizophrenia
patients. The first study by Rascle et al. (2001) used a between-participants design in
which chronic schizophrenia patients in the preexposed group showed slower learning in
comparison to controls, resulting in an enhancement of latent inhibition. The remaining
studies, by Cohen et al. (2004) and Gal et al. (2009), like the current study, employed a
within-subject manipulation of stimulus familiarity to demonstrate latent inhibition and
were able to show an abnormality in learning that was specific to the preexposed stimuli.
Both Cohen et al. and Gal et al. showed that latent inhibition enhancement was associated
with the negative symptoms experienced by adolescents with schizophrenia. These results
are what would be predicted based on Weiner's (2003) model that suggests enhanced latent
inhibition is associated with depleted levels of glutamate (see Javiit, 2007; Javiit,
2010), which may be related to the prevalence of negative symptoms. On the other side of
the coin, is the reported relationship between the positive symptoms of schizophrenia and
attenuated latent inhibition (e.g. Baruch et al., 1988a; Gray et al., 1992, 2002; Rascle
et al., 2001; Vaitl et al., 2002). This latter pattern of results is consistent with Gray
et al.'s (1991) model for cognitive and neural associates of positive acute schizophrenia
symptoms: that a loss of loss of latent inhibition is due to over-activity in the
mesolimbic dopaminergic system. At first glance, the results presented here, an
enhancement of latent inhibition with the positive UnEx dimension of schizotypy, conflict
with these analyses. There has been considerable disagreement about the relationship
between the attenuation of latent inhibition in schizophrenia and positive symptomatology:
some authors have found a relationship between latent inhibition and positive symptoms
(Baruch et al., 1988a; Gray et al., 1992, 2002; Rascle et al., 2001; Vaitl et al., 2002),
others have not (Cohen et al., 2004; Gal et al., 2009; Rascle et al., 2001; Swerdlow et
al., 1996; Williams et al., 1998; for a review see: (Schmidt-Hansen & Le Pelley, 2012). In
particular, Rascle et al. (2001) reported an attenuation of latent inhibition was
associated with low levels of negative symptoms in patients with schizophrenia, rather
than with levels of positive symptoms. Whereas Cohen et al. (2004) reported no difference
in the magnitude of latent inhibition between high levels of positive symptoms in
schizophrenia patients, and healthy controls. These findings, along with the current
results, do not support the relationship between latent inhibition attenuation and
positive symptomatology. On the other hand, the proposition by Weiner (2003) — that
enhanced latent inhibition is related to negative symptoms, refers mainly to chronic
patients. However, the findings reported by Cohen et al. and Gal et al. (2009) were able
to show an association between enhanced latent inhibition and clinical condition (chronic
schizophrenia), but not with the level of negative symptoms per se. The discrepancy
between these findings, and the results reported here are possibly due to the nature of
the tasks employed by Cohen et al. and Gal et al.; as previously highlighted, these
existing tasks confound learned irrelevance with latent inhibition itself. How the refined
latent inhibition task reported here covaries with individuals with schizophrenia, is the
focus of future research. One possible shortcoming of employing the multiple regression
analysis that we have used in Experiments 1 and 2 is that the observed correlations
between UnEx and RT to the non-preexposed stimulus could have been caused by any processes
that impact upon the RTs to the preexposed stimulus, including those which also impact on
RTs to the non-repexposed stimulus; that is to say, the common variance components
affecting RTs to both preexposed and non-preexposed conditions. In order to evaluate this
possibility, we pooled the data across Experiments 1 and 2 and conducted a hierarchical
multiple regression in which RTs to the non-preexposed stimulus were added in the model in
step 1 to act as a covariate, and examined the subsequent relationships between UnEx,
CogDis, IntAn and ImpNon (as predictor variables), and RTs to the pre-exposed stimulus (as
the dependent variable) in step 2. UnEx remained as a significant predictor of RT to the
pre-exposed stimulus in step 2, β = .23, t = 2.61, p = .01, as did CogDis now, β = −.18, t
= 2.07, p = .041. The remaining sub dimensions of the OLIFE were not significant however,
βs < −.01, ts < 1.2, ps > .23. It therefore appears that the relationship that we observed
between schizotypy and RT in the current studies is specific to the pre-exposed stimulus.
For the purposes of completeness, we also repeated the previous regression but this time
with RTs to the preexposed stimulus entered as a covariate in step 1, and examined the
subsequent relationships between UnEx, CogDis, IntAn and ImpNon (as predictor variables),
and RTs to the non-preexposed stimulus (as the dependent variable) in step 2. None of the
beta coefficients were significant. βs < .03, ts < 1.0, ps > .39. In order to ensure that
participants were engaged with the task during the preexposure stage of Experiment 2, a
secondary task was employed in which participants were required to repeat, out loud, each
stimulus that was presented on the screen. We have argued that immersing preexposure
within such a procedure precludes the current results from being explained in terms of
learned irrelevance — as the preexposed stimulus was established as task relevant. This
raises the question, then, of whether the current results are a demonstration of latent
inhibition or, instead, a circumstance in which establishing a stimulus as task relevant
in stage 1 might hinder learning in stage 2 when the same stimulus is established as an
explicit cue for a target stimulus. On balance, this possibility seems unlikely. A number
of studies have now shown that when a stimulus is established as relevant to the solution
of one task, the same stimulus is subsequently better, not worse, than a control stimulus
at serving as a cue in a different task (e.g. Bonardi, Graham, Hall, & Mitchell, 2005; Le
Pelley, Turnbull, Reimers, & Knipe, 2010). Furthermore, tasks of these sort have been
shown to have a negative, not a positive, correlation with schizotypy (e.g. Le Pelley,
Schmidt-Hansen, et al., 2010). To the best of our knowledge there is only one
demonstration, in humans, of a stimulus being established as task relevant then going on
to show a subsequent retardation in learning (Griffiths, Johnson, & Mitchell, 2011).
However, this "negative-transfer" effect was demonstrated under circumstances in which the
task type was the same between pre-exposure and learning (only the magnitude of the target
outcome was changed). Furthermore, to date, there is no evidence of this effect having any
relationship with schizotypy. The two experiments presented here show an effect of
schizotypy on learning about a preexposed stimulus using a refined latent inhibition
procedure. Both Experiments 1 and 2 show a comparable and novel effect of enhanced latent
inhibition in individuals high in UnEx. We advocate the use of the task described in
Experiment 2, as this task successfully minimised the contribution of both conditioned
inhibition and learned irrelevance on the preexposure effect, and could be a useful tool
for assessing attentional dysfunction in schizophrenia, as well as other clinical and sub-
clinical populations.

<h>CONFLICT OF INTEREST</h>
--------------------

No conflicts of interest declared.


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<ART>Events associated with stability and change in adult locus of control orientation over a six-year period
================================================================================

Authors: Stephen Nowicki, Genette Ellis, Yasmin Iles-Caven, Steven Gregory, Jean Golding
DOI: 10.1016/j.paid.2018.01.017
Year: 2018  |  Pages: 85-92
ASJC codes: 3200
Keywords: ALSPAC, Life stressors, Longitudinal cohort, Parental locus of control, Stability over time

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Although locus of control (LOC) has been the focus of thousands of studies we know little about how or if it changes over time and what is associated with change. Our lack of knowledge stems in part from the past use of cross-sectional and not longitudinal methodologies to study small numbers of participants from non-representative populations. The purpose of the present study was to use a longitudinal design with a large representative population to provide relevant information concerning the stability and change of adult LOC. Before the birth of their child, and again six years later, mothers and their partners participating in the Avon Longitudinal Study of Parents and Children (ALSPAC) completed LOC tests and structured stressful events surveys. Analyses revealed that stresses experienced in relationships with spouses, friends and family, financial stability and job security, and illness/smoking were associated with changes in LOC. Results suggest substantial variation of LOC within spousal/parent dyads and moderate stability of LOC over time for both men and women. Stressors associated with change in LOC may be possible candidates when considering interventions to modify LOC expectancies.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The purpose of this project was to examine the stability and change of locus of control
(LOC) orientation in adult men and women over a 6 year period, and to identify events
associated with LOC stability or change. LOC refers to individuals' generalized expectancy
regarding the connection between their behavior and reinforcements received in a problem-
solving context (Rotter, 1966). Individuals who fail to see a connection between what they
do and what happens to them and view what happens as the result of luck, fate, chance, or
powerful others are externally controlled. Conversely, those who tend to perceive a
connection between their efforts and what happens to them are internally controlled.
Rotter's article stimulated a remarkable amount of research. A search of PsychInfo
resulted in 17,812 articles with a keyword “locus of control” as of summer 2015 and with
6600 of these appearing after 1996 (1425 dated 2010–2015). LOC has sustained itself as a
concept for psychological study for more than a half century (Nowicki & Duke, 2016). As
there are >100 different definitions of “locus of control” throughout the literature
(Skinner, 1996), researchers need to clearly state and define which LOC concept and
measure is being used (e.g. Reich & Infurna, 2016). Peterson and Stunkard (1992) have
noted potential problems that could result from using similar appearing cognates, like
efficacy (e.g. Infurna & Mayer, 2015; Lachman & Weaver, 1998) or attribution (Peterson &
Seligman, 1983; Seligman, 1975) interchangeably with locus of control of reinforcement as
described by Rotter (1966). Rotter defined LOC within his social learning theory (1954,
1966) emphasizing that it is an expectancy that has the capacity to affect behavior
differently from situation to situation and has its greatest impact in circumstances that
are novel, ambiguous or transitory. LOC has been related to an ever-growing number of
important and significant aspects of human life including personality characteristics
(e.g. Judge & Bono, 2001; Nowicki & Duke, 1974), social adjustment difficulties (e.g.,
Cheng, Cheung, Chio, & Chan, 2013), academic achievement (e.g. Flouri, 2006), health
outcomes (e.g. Conell-Price & Jamison, 2015), and business success (e.g. Kormanik & Rocco,
2009). However, surprisingly little research has been completed concerning the origins of
control orientations or their trajectories over time. Using data gathered from the Avon
Longitudinal Study of Parents and Children (ALSPAC), Golding, Iles-Caven, Gregory, and
Nowicki (2017), Golding, Gregory, Iles-Caven, and Nowicki (2017), and Golding, Ellis,
Iles-Caven, Gregory, and Nowicki (2017), identified antecedent characteristics of the
childhoods that were common to internality in both men and women; these included maternal
warmth, being breast fed, having a stable home, and recollection of childhood as happy.
Antecedents like these describe a home situation in which children feel comfortable and
safe enough to explore their environments and learn more about the possible contingencies
existing between their behavior and outcomes. Lefcourt (1976) had earlier theorized a
similar set of circumstances underlying the development of appropriate internal control
expectancies. Antecedent information may be helpful in suggesting what might underlie the
learning of generalized internal or external control expectancies as well as to offer
possible insights into what may be associated with changes in or maintenance of LOC.
Unfortunately, since most of the antecedent data have been obtained from studies using
cross-sectional methodologies they are inappropriate for objectively describing how
individuals' LOC changes over time or, if changes do take place, with what they are
associated. Longitudinal data would be valuable in supporting or refuting cross-sectional
results describing the development of control expectancies. The purpose of this
investigation was to identify events associated with LOC changes over time by analyzing
longitudinal LOC data gathered over a 6 year period beginning when the women and their
partners were expecting a baby. Some LOC studies with adults have used LOC pre-post scores
as an outcome measure to evaluate the impact of interventions. Unfortunately, in these
cases researchers rarely report correlations between pre-post testing of the group not
receiving the intervention, as this would be valuable in determining the stability of LOC
over time in typical participants. For example, Sørlie and Sexton (2004) studied the
effects of psychosocial medical and treatment related factors upon change in the
Multidimensional Health Locus of Control scale (MHLC) (Wallston, Wallston, & DeVellis,
1978). The MHLC was administered to surgical patients prior to surgery and again four
months following discharge. They found a positive relationship with physicians' predicted
internality, while severity of illness and subjective feelings of stress were associated
with externality. Similar findings were obtained with patients who had undergone heart
surgery (Sørlie & Sexton, 2004). They too became more internal with the passage of time
and involvement with rehabilitation. Though researchers using the perceived control
construct have produced results consistent with those found by Rotter, orientated LOC
investigators have primarily studied older rather than younger adults. They used a variety
of ways to assess “perceived” control, and not offered construct validity evidence in
support of the perceived control measures they used or how they may have related to LOC.
For example, in one study (Turiano, Chapman, Agrigoroaei, Infurna & Lachman, 2014)
“perceived” control was measured using a 4-item test with a 7-point Likert Scale while in
another (Infurna & Okun, 2015) it was assessed by a 6-item scale with a 4-point Likert
scale. Because there is an absence of information of how the different perceived control
measures correlate with one another or with Rotter's scale, it is difficult to determine
if what they are measuring is similar to or different from what researchers have found
using Rotter-based LOC scales. Rather than assessing “perceived” control in middle-aged
and older adults, Schneewind (1997) was one of the few researchers to gather test–retest
information from younger adults using a scale based on Rotter's definition. The initial
test was administered to parents when their child was 10 years old; the retest took place
16 years later. Parents and their children completed German adaptations of LOC scales
(Adult and Child Nowicki-Strickland Internal-External scales). LOC was part of a more
comprehensive longitudinal study of personality in the context of family development
(Schneewind, Ruppert, & Harrow, 1998). Initial data were gathered from a sample of
mother–father-child triads recruited from six different German states. The mean age of the
children was 12, mothers 39, and fathers 42. Sixteen years later Schneewind and his
colleagues contacted former participants and had 197 triads volunteer to participate in a
second assessment. In this paper we are primarily interested in what Schneewind found
regarding parent LOC. At both testing times, mother and father LOC scores were positively
correlated, but low (time one, r = 0.19; time two, r = 0.21). Pre-post LOC correlations
for mothers and fathers across the 16 years were what Schneewind called “moderate” and
ranged between 0.35 and 0.44.

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

Little is known about how LOC expectancies develop and change in adulthood. We lack
information about what the LOC association is within spousal or parental dyads, the
trajectory of adult LOC over time or what life events are associated with LOC changes over
time. Our goal here is to provide such LOC information. The ALSPAC data set is unique in
that it contains LOC scores from both mothers and fathers before the child was born and
six years later. Thus we can assess the stability of parents' LOC during a critical period
of their lives. The absence of previous research made prediction difficult. Relationship
theories offer competing predictions. Complementary theorists (e.g., Kiesler, 1982)
suggest a negative association between mother and father LOC scores, with one individual
being external and the other internal. Similarity perspectives (e.g., Byrne, 1969)
suggests that the LOC scores would be similar; internals liking internals and externals
liking externals. Based on Schneewind's findings, we predict parents' own pre-post LOC
scores would be moderately related to one another over time, but relatively unrelated to
one another at pre- and post-times. Although Schneewind obtained valuable data regarding
adult LOC stability and change, he failed to provide any information about what might be
associated with changes. The ALSPAC data set includes data concerning the stressors
encountered by adults during the six years between the first and second LOC
administration. Rotter (1966) and Lefcourt (1976) theorize that internality thrives when
individuals are in warm, supportive, relatively stress free environments in which they can
learn to perceive the connection between their behavior and outcomes. We predict that
greater stress will be related to greater externality.

<hs>  The ALSPAC study</hs>
  ~~~~~~~~~~~~~~~~

This pre-birth cohort was designed to determine the environmental and genetic factors that
were associated with health and development of children and their parents (Golding and
ALSPAC Study Team, 2004; Boyd et al., 2013). As part of the study design, and in order to
determine the parents' backgrounds prior to the birth of the child, there was a concerted
effort to obtain details of their personalities, moods and attitudes, including a measure
of their LOC, before the birth of the child. ALSPAC recruited 14,541 pregnant women
resident in Avon, UK with expected dates of delivery 1st April 1991 to 31st December 1992.
Enrolment strategies included encouragement through the local media, general
practitioners, midwives, health services and obstetric hospitals; women then contacted the
study center for further information; they were then sent a series of questionnaires to be
completed at home. 14,541 is the initial number of pregnancies for which the mother
enrolled in the ALSPAC study. Of these there were 14,062 livebirths, of which 13,988
survived to at least 12 months. For full details of all the data collected see the study
website: www.bristol.ac.uk/alspac/researchers/data-access/data-dictionary/. Uniquely among
the major UK cohort studies at the time it was decided to include the fathers of the
children. To this end questionnaires were sent to the mother to pass to her partner if she
was happy for him to take part. This strategy was approved by the ALSPAC Ethics and Law
Committee (Birmingham, 2018). Consequently, there was no immediate way in which the study
administrators knew the identity of the study fathers. Given the uncertainty of this
approach, it is striking how many took part during the pregnancy (10,000 compared with
13,867 pregnant women (Fraser et al., 2013)). Follow-up used a variety of techniques
including questionnaires, hands-on examinations, assays of biological samples and details
of the environment at various stages of life. Questionnaires included detailed history of
events, occupations and life styles of each parent. Loss to follow-up occurred when the
child died, the mother refused, or moved away and could not be traced. As in all
longitudinal studies, attrition increased as the study continued (Fraser et al., 2013).
This is illustrated by the numbers of parents who completed the LOC questions at the two
time points 6 years apart. For the women the numbers fell from 10,565 to 8378 (79% of the
original), and for the partners the change was from 7365 to 3891 (53%). From Supplementary
Table 1 it can be seen that the proportion of parents with LOC scores 6 years after the
study child's birth had proportionately fewer families who (a) resided in public housing,
(b) were young mothers, (c) were of manual social class or (d) who smoked. These factors
need to be born in mind when generalizing the results. Follow-up used a variety of
techniques including questionnaires, hands-on examinations, assays of biological samples
and details of the environment at various stages of life. Questionnaires included detailed
history of events, occupations and life styles of each parent. Loss to follow-up occurred
when the child died, the mother refused, or moved away and could not be traced. As in all
longitudinal studies, attrition increased as the study continued (Fraser et al., 2013).
This is illustrated by the numbers of parents who completed the LOC questions at the two
time points 6 years apart. For the women the numbers fell from 10,565 to 8378 (79% of the
original), and for the partners the change was from 7365 to 3891 (53%). From Supplementary
Table 1 it can be seen that the proportion of parents with LOC scores 6 years after the
study child's birth had proportionately fewer families who (a) resided in public housing,
(b) were young mothers, (c) were of manual social class or (d) who smoked. These factors
need to be born in mind when generalizing the results.

<hs>  Measures of LOC</hs>
  ~~~~~~~~~~~~~~~

The LOC measure used in the present study is a shortened form of the adult version of the
Nowicki-Strickland Internal-External locus of control scale (ANSIE) which comprises 40
items in a yes/no format to assess perceived control (Nowicki & Duke, 1974). This was
chosen over other scales more specifically related to perceived control over health, as it
was considered that this more generalized scale would relate to other factors in addition
to health outcomes. Construct validity for the scale has been found in the results of over
1000 studies (Nowicki, 2016). The version used here comprises 12 of the original 40 items,
which were chosen after factor analysis of the ANSIE in a pilot of 135 mothers in the USA.
An Anglicized version of these 12 items was included in the questionnaires sent to the two
parents in pregnancy (Golding, Iles-Caven, et al., 2017) and again six years after the
child was born, with identical wording. From the responses LOC scores were derived for men
as well as for women, the higher the score the more external the LOC. The scores ranged
from 0 to 12. Classification into external and internal parents in pregnancy, using the
definition for externality of greater than the median LOC score (>4 for women, >3 for
men), identified 40.3% of mothers and 38.8% of their partners as externally-oriented in
pregnancy. Because of increasing internality in the women over time, their median LOC
score changed to 3, whereas their partners stayed at 3.

<hs>  Identification of events</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

From 8 months post-birth, each parent was sent a questionnaire concerned with life events
in the preceding period, at approximately yearly intervals. The life events inventory
comprised 42 items, which were derived for the ALSPAC study using previous inventories as
a basis for selection of items. Three main sources were used in this way: Brown and Harris
(1978), Barnett, Hanna, and Parker (1983) and Stanley (1988). In order to develop a
summary of variables to determine whether each specific event had occurred over the
preschool period of the study child, we created a variable for each event that used all
available questions (i.e. those sent to the parents at 8, 21, 33 and 47 months). We did
not sum the number of times an event occurred as there was often overlap between ages.
Rather than look at the number of the events occurring, we have deliberately looked at
each separately using the hypothesis that some types of event will result in increasing
internality, and some externality, a pattern that we found when considering the
relationship between the events in childhood and the LOC of the adult (Golding, Ellis, et
al., 2017).

<hs>  Other variables considered</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Other variables investigated here were chosen because they were associated with parental
LOC as well as with differential response rates. They were included to determine whether
they were associated with any change in LOC orientation across the 6 years. They include:
(1) housing tenure – which is an accepted socio-economic indicator in the UK – divided
into owner-occupied (includes having a mortgage), rented public housing, and other rented
property; (2) age of the mother at the child's conception; (3) social class (based on
occupation of the mother's partner classified into manual and non-manual (Standard
Occupational Classification, 1990); (4) presence of mother's partner in the home
(identified by questionnaire at 8 months); (5) maternal education level (based on the
actual qualifications attained and divided into three levels of attainment); (6) the
mother's parity (number of previous pregnancies resulting in either a live or stillbirth);
(7) the smoking habit of each parent at 8 months of age (categorized in two ways – any
regular smoking and regular smoking of ≥10 cigarettes/day).

<hs>  Statistical techniques</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The statistical strategy was to determine the pattern of factors that were associated with
the change in LOC orientation in each parent, with a focus on events that occurred after
the initial measure. The study was hypothesis free. Based on the findings from a study of
the childhoods of these individuals we anticipated that some of the events might result in
a change toward internality, and some toward externality. Results were descriptive, and
compared individuals who changed from those who did not, using logistic regression. No
account was taken of the number of tests undertaken, to avoid type I errors.

<hs>  Correlation of parents' LOC scores with one another and across time</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As demonstrated in Table 1, both mother and father LOC scores were positively and
moderately correlated between the two-time points (mothers = 0.57; fathers = 0.56); cross-
sectional correlations between parents at each of the two time points were positively
correlated, but low (in pregnancy r = 0.33; 6 years later r = 0.29).

<hs>  Additional findings concerning parents' LOC</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The ‘change score’ was calculated as the difference between the LOC score in pregnancy and
that obtained 6 years later. Mothers' and fathers' LOC change scores ranged from −9 to +8,
with mode and median at 0 with a mean difference of −0.30 [SD 1.89; n = 8302] points for
mothers and +0.037 [SD 1.98; n = 3968] points for fathers. Thus, mothers on average were
getting more internal while their partners were tending to become more external. The
correlation coefficient between the parents change scores was positive but low (0.11).

<hs>  Lifestyle and social conditions associated with changes in LOC over time</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In Tables 2a and 2b we consider certain lifestyles and social conditions at 8 months post-
delivery: for life-style we consider the changes in LOC associated with the smoking habits
of each parent; social conditions were demonstrated by the tenure of the home in which the
family were living and whether the mothers' partner was part of the household. Smoking of
the parents bore very strong associations with the likelihood of the parents changing
their orientation (Table 2a). Of the women who stayed externally oriented 30.7% were
smoking when the offspring was 8 months old, whereas 24.7% of those who had become
internal had this history (P = .002); for women who stayed internal, only 11.9% smoked,
but 20.0% of those who became external did so (P < .0001). Similar patterns were shown for
women who were heavy smokers as well as when the partner smoked (Table 2a). Changes in the
partners' orientation were equally associated with the smoking habits of the woman as well
as of the partner himself (Table 2b). Mothers who lived in public housing were
considerably more likely to stay external, and those in owner-occupied accommodation less
likely to do so. Conversely mothers who were internally oriented in pregnancy were more
likely to become external if in public housing (Table 2a). A similar pattern was shown for
the mothers' partners (Table 2b). Most of the women who answered the relevant
questionnaires had live-in partners (Table 2a), but those mothers who were externally
oriented were more likely to become internal if the partner was present. Conversely the
women who were internal but became external were less likely to have a live-in partner.
Partners were less likely to be given (or complete) a questionnaire if they were not
living with the mother 6 years post-birth; even so, among those who answered the
questionnaire, there was some evidence that those who became internal were more likely to
be living with the mother, and those who did not were more likely to become external
(Table 2b).

<hs>  Stressful life events associated with changes in LOC over time</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 3a presents variations in the potentially stressful events occurring to parents and
ways in which they were associated with maternal changes in the LOC orientation. The first
two columns compare proportions of women who had a history of the stressor between those
who stayed external and those who became internally-oriented. Of the 42 stressors
occurring, just four showed a significant association: the women were more likely to
become internal if (a) they went back to work and/or (b) they had problems at work; they
were more likely to stay external if they had (i) separated from a partner, or (ii) argued
with family or friends. The last two columns compare the occurrence of the events among
those who stayed internal and those who were internal but became external. In this case,
25 of the 42 stressors were significant at the 5% level or higher, with 16 of the 25 at
the .005 level and 9 of the 25 at the <.001 levels or better. We find 4 of the 16
significant events associated with staying internal: (i) having a partner who was very
ill, (ii) having a partner who had problems at work, (iii) mother returning to work, and
(iv) having problems at work. In contrast, three times as many stressful events, 12 in
all, were associated with becoming external: (a) becoming divorced, (b) having a partner
who rejected the child, (c) having a partner who was in trouble with the law, (d)
separating from the partner, (e) arguing with family and friends, (f) becoming homeless,
(g) having major financial problems, (h) getting married, (i) being physically abused by
her partner, (j) being emotionally abused by her partner, (k) having a partner who
emotionally abused her children, and (l) attempting suicide. As was found for mothers,
partners had more stressful events associated with externality than internality (Table
3b). Only one event was significantly associated with changing from an external to an
internal orientation: starting a new job. Four were associated with him being
significantly less likely to become internal; (a) losing his job, (b) arguing with his
partner, (c) arguing with family and friends, and (d) having major financial problems.
Similar to the mothers, partners had more stressors, 11 in all, associated with becoming
external. Four of the 11, were associated with being less likely to become external – (a)
a friend or relative was ill, (b) he moved home, (c) he had a burglary, and (d) his
partner became pregnant. Seven were associated with becoming external; (i) having been
very ill himself, (ii) losing his job, (iii) reduction in his income, (iv) arguing with
family and friends, (v) having major financial problems, (vi) being emotionally abused by
his partner, and (vii) his partner starting a new job.

<hs>  LOC between spouses and over time</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This study is among the few that has obtained LOC scores from a large representative
population composed of parental dyads at two time points, but is unique because the
initial test took place prenatally, and the second six years later Hajek and Konig (2017)
collected LOC information from a large representative cohort of adults over a five year
period from 2005 to 2010, but did not delineate where participants were in regards to
family or examined factors that were associated with changes in LOC. On the other hand,
Schneewind (1997) did focus on LOC in parents of children who were first tested when
children were aged 10 and tested again 16 years later. However his participants were a
select group of nearly two hundred family members whose initial LOC test was not obtained
before the child was born. By obtaining mother and father LOC scores prenatally we have
the unique advantage of being able to describe parents' LOC perspectives before the
arrival of the child and to evaluate the future impact of their prenatal orientations on
their own and their children's behavior. Studies have already begun to show the benefit of
this approach by revealing that the degree of externality in the parent dyad was
associated with (1) negative outcomes in children's eating, sleeping and emotion
regulation behaviors during their first 5 years of life (Nowicki, Iles-Caven, Gregory,
Ellis, & Golding, 2017a) and (2) the number of teacher-rated emotional and behavioral
difficulties when children were 9 and 11 years old (Nowicki, Iles-Caven, Gregory, Ellis, &
Golding, 2017b). The design of the ALSPAC study and the data set it produced not only
allowed us to evaluate the associations between parent prenatal LOC and child outcomes but
also (1) to gather heretofore nonexistent normative data regarding the nature and
stability of the spouses' LOC within their dyads prior to their child's birth and 6 years
later, as well as (2) to obtain indicators of the stability of adult male and female LOC
scores from before a child was born to a time 6 years later. We know of no other study
that has obtained extensive normative LOC information from a large and representative
population of adult women and men who were in a relationship with one another over time.
Our results favor the similarity prediction (Byrne, 1969), but just barely. Correlations
were positive but low at both testing times. While mothers and their partners tend to
share a similar LOC perspective, it is only that, a tendency, and the reality is that for
most parent dyads, various LOC combinations exist. To examine associations that might
arise from different combinations with child outcomes, Nowicki et al. (2017a) created four
combinations of prenatal LOC; internal/internal; mother internal/father external; mother
external/father internal; and external/external. They found that as externality increased
in the parental dyad so did associations with negative children's adjustment outcomes.

<hs>  Associations with stability and change in LOC over six years</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Moderate positive correlations between pre- and post-test scores indicate that many
individuals were changing their LOC orientation over time. We predicted and found that LOC
changes, especially toward externality, were associated with lifestyle, social, and
stressful event variables. What is clear from the findings is that greater stress and less
stability in personal relationships, health, and financial matters are related to
remaining or becoming external for both mothers and their partners. In terms of
relationships perhaps none are more important than the one between the parents themselves.
Externality was associated with stressful spousal issues in the relationship including
physical or emotional abuse of one another or other indicators of relationship failure
such as divorce, trouble with the law or rejection of the child. Although mothers had more
relationship stressors associated with externality than their partners, the direction of
the association was the same. Besides their own relationship difficulties being related to
externality, both parents indicated that “arguing with family and friends” added to the
potential to remain or become external. If mothers and their partners didn't get along
then an inability to relate to family and friends would probably increase the likelihood
of being associated with feelings of externality. The importance of the spousal
relationship was further substantiated by the finding that living together or living apart
was related to stability and change in LOC. External mothers were more likely to move
toward internality if they had a live-in partner in contrast to prenatally internal
mothers who, if they did not have a live-in partner, moved toward externality; the same
association was found for mothers' partners as well. Financial matters and “work” were
also associated with externality for both mothers and their partners. For mothers,
externality was associated with “having major financial problems” and “not going back to
work” while for men it was “losing a job”, “reduction of income”, and “partner starting
new job”. “Work” may be especially important for men's LOC as suggested by the finding
that “starting a new job” was the only event associated with internality for them. Illness
was associated with LOC differently for mothers and their partners. For men, “having been
very ill himself” was significantly related to externality while for women “having a
partner who was very ill” was associated with internality. In this regard, it is
noteworthy that the four events endorsed by women who stayed internal (having had a
partner who was very ill; having had a partner who had problems at work; having to go back
to work herself; and having problems at work) involved problems in their spousal and work
relationships. Perhaps meeting challenges and responding successfully to them facilitated
internality in women. Unfortunately, we do not have access to what exactly the problems
were or what the women thought, felt and did while experiencing them, but we might learn
much from interviewing such women to obtain this information. Lifestyle differences were
also related to LOC stability and change. Clearly, smoking was a significant marker of
externality in the ALSPAC population. As smoking increased so did externality. While we
cannot establish cause and effect with our design, the fact that smoking is associated
with externality and externality in turn is associated with negative outcomes in
personality, health, achievement, and adjustment suggests it would be worthwhile having a
closer look at how those variables affect one another. Past research suggested a
connection between smoking and LOC (Wallston & Wallston, 1978). Because of the association
between smoking and externality, it might be helpful to see if stop-smoking programs had
any effect on participants' LOC. Unfortunately, research has focused on determining who is
more likely to successfully complete a stop-smoking program; not surprisingly most often
it is the internals and not the externals (e.g. Kaplan & Cowles, 1978). One potential way
around the fact that externals do not respond as well to more general smoking cessation
programs is to use individualized interventions favoring those with external as opposed to
internal control expectancies (e.g. Steffy, 1975) to see if externals who were successful
changed toward internality. Having a choice about where we live is important, so it is not
surprising that ALSPAC participants who had less choice of where to live and found their
only choice was to live in public housing rather than renting or owning other dwellings
are more external. To offset a lack of choice in where to live, it might be useful to give
those in public housing opportunities to exercise some “control” over their living
situation. Researchers have found that institutionalized individuals who were given
control over small decisions in their lives responded by changing toward internality (e.g.
Aasen, 1987). Perhaps pilot programs in which housing authority personnel and those living
in public housing could work together to generate lists of ways in which public housing
occupants would have the power to make more of their own choices; this might lead to
changes toward internality over time.

<hs>  Strengths and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Among the strengths of this study are the following: (i) it is based on a whole
population, defined geographically and consequently not biased by particular selection
(e.g. college students). Comparison with census data from 1991 show that the study
participants are broadly representative (Fraser et al., 2013). (ii) The numbers considered
are far larger than in any other study of LOC over time. (iii) Data on life events were
obtained at times between the measures of the LOC orientation of the parents, and
consequently cannot have been influenced by the LOC response. (iv) It is the only study to
be able to compare the pairs of parents across time with respect to their LOC orientation.
The disadvantages concern: (1) the attrition rate in this study, which was particularly
high for the mothers' partners; (2) other modes of statistical analysis, choice of
confounders and/or unobserved time-constant variables may provide different results; and
(3) the fact that we are unable to confirm our results by comparing results with another
study, since there is no (to our knowledge) study that has similar longitudinal data
available. In consequence these results should be considered as hypothesis generators.
Hopefully they will generate further studies over time.

<h>CONCLUSIONS</h>
-----------

Thousands of studies confirm the importance of LOC, yet we have learned little from them
about true stability and/or change of LOC over time or what is associated with change when
it occurs. The present study provides data to begin to better understand LOC, although it
is important to note the paternal attrition over time. We found that: (1) LOC in parent
dyads is correlated in a low, positive manner; (2) adult LOC is moderately correlated
across time; (3) women become more internal from pregnancy to motherhood, whereas their
partners become slightly more external; and (4) greater stress especially in
relationships, finances, and health, is associated with increasing externality. Future
designs need to build in techniques to gather information that would allow for the
assessment of the short-term changes that may have been obscured by adaptation/habituation
processes over a 6-year span. In this way we can gather additional information to help us
to eventually identify variables that may be linked to change in LOC orientations.
Hopefully our findings will help to elucidate the role of stressors in the development of
internal and external LOC and bring us closer to being able to construct intervention
programs to foster the development of appropriate internality, especially in expectant
parents. The following is the supplementary data related to this article. Availability of
parental LOC data in pregnancy for whole sample and for the parents 6 years after the baby
was born, showing distributions of background factors. Supplementary data to this article
can be found online at https://doi.org/10.1016/j.paid.2018.01.017.


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<ART>Evidence for semantic involvement in regular and exception word reading in emergent readers of English
================================================================================

Authors: Jessie Ricketts, Robert Davies, Jackie Masterson, Morag Stuart, Fiona J. Duff
DOI: 10.1016/j.jecp.2016.05.013
Year: 2016  |  Pages: 330-345
ASJC codes: 3204, 3205
Keywords: Context, Lexical phonology, Mixed-effects models, Semantic, Vocabulary, Word reading

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We investigated the relationship between semantic knowledge and word reading. A sample of 27 6-year-old children read words both in isolation and in context. Lexical knowledge was assessed using general and item-specific tasks. General semantic knowledge was measured using standardized tasks in which children defined words and made judgments about the relationships between words. Item-specific knowledge of to-be-read words was assessed using auditory lexical decision (lexical phonology) and definitions (semantic) tasks. Regressions and mixed-effects models indicated a close relationship between semantic knowledge (but not lexical phonology) and both regular and exception word reading. Thus, during the early stages of learning to read, semantic knowledge may support word reading irrespective of regularity. Contextual support particularly benefitted reading of exception words. We found evidence that lexical–semantic knowledge and context make separable contributions to word reading.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Knowledge of the meaning of words and phrases (semantic knowledge) has an important role
to play in reading. Logically, a child needs to understand the meaning of the words and
phrases contained within a text in order to fully understand it. The simple view of
reading (e.g., Gough & Tunmer, 1986), an influential framework for understanding reading
comprehension, posits that successful reading comprehension is underpinned by oral
language comprehension (including semantic knowledge) as well as word reading abilities.
Indeed, studies adopting longitudinal and experimental (randomized controlled trial)
designs (e.g., Clarke, Snowling, Truelove, & Hulme, 2010; Nation & Snowling, 2004) have
yielded convincing evidence that semantic knowledge is causally related to reading
comprehension ability. There is also evidence that oral language ability contributes to
the development of word reading in children, with influences from both phonology and
semantics (e.g., Duff & Hulme, 2012; Nation & Cocksey, 2009; Nation & Snowling, 2004;
Ouellette & Beers, 2010; Ricketts, Nation, & Bishop, 2007). We concentrated here on
semantic influences. Nation and Snowling (2004) showed that semantic knowledge at age 8
years predicted later word reading at age 13 years after accounting for decoding ability,
phonological skills, and the autoregressor (word reading at age 8 years). In an extension
of this research, Ricketts and colleagues (2007) demonstrated a more specific
relationship—that oral vocabulary knowledge was more closely associated with exception
word reading than with regular word reading. Exception words are words with unusual
mappings between spelling and sound (e.g., <yacht>, <pint>), whereas regular words contain
only predictable spelling–sound mappings. Importantly, regular words can be readily
decoded using knowledge of the usual relationships between spelling patterns (graphemes)
and sounds (phonemes), whereas exception (or irregular) words cannot (e.g., using such a
strategy would result in <yacht> being pronounced to rhyme with “matched” rather than
“cot”). Regular words are usually read more accurately than exception words by typically
developing children (e.g., Nation & Cocksey, 2009). In the literature outlined above,
receptive and/or expressive oral vocabulary measures have typically been used to assess
semantic knowledge. It is worth noting that the acquisition of oral vocabulary or
lexical–semantic knowledge is incremental rather than an all-or-nothing process, with
individuals adding to existing lexical–semantic representations, as well as acquiring new
representations, throughout the lifespan. Studies conducted by Ouellette and colleagues
(e.g., Ouellette, 2006; Ouellette & Beers, 2010) have acknowledged this by making a
distinction between breadth (number of words known) and depth (what is known) in
vocabulary knowledge. Ouellette and Beers (2010) found that for children aged 5 to 7 years
a depth measure was a significant predictor of exception word reading, whereas a breadth
measure was not; the reverse pattern was observed for older readers (11–12 years). Oral
vocabulary is an important part of semantic knowledge. However, semantic knowledge also
encompasses an understanding of the meaning-based relationships between words, the meaning
of phrases, and so on. As far as we have ascertained, the study by Nation and Snowling
(2004) is unique in investigating the relationship between semantic knowledge and word
reading by using not only the usual measure of oral vocabulary (in this case an expressive
measure) but also a measure that goes beyond such lexical–semantic knowledge—a composite
of “semantic skills” comprising semantic fluency and synonym judgment. In regression
analyses, Nation and Snowling found that their two measures of semantic knowledge made
equivalent contributions to explaining variance in word reading, as measured concurrently
and longitudinally by a well-established standardized test. However, their analysis of
exception word reading, more specifically, showed that oral vocabulary at age 8 years was
a significant predictor of exception word reading 4 years later, whereas the semantic
composite was not. A number of mechanistic accounts for the relationship between semantic
knowledge and word reading have been proposed. Walley, Metsala, and Garlock (2003)
suggested that the relationship between semantic knowledge and word reading is indirect.
According to their lexical restructuring hypothesis, oral vocabulary development serves to
specify phonological representations, which in turn are critical for word reading
development (e.g., Bishop & Snowling, 2004; Brady & Shankweiler, 1991; Goswami & Bryant,
1990). Computational models of word reading assume a more direct relationship. In the
triangle model, words can be read aloud via two pathways, including one that maps
indirectly from orthography to phonology via semantics (Harm & Seidenberg, 2004; Plaut,
McClelland, Seidenberg, & Patterson, 1996). The dual route cascaded (DRC) model
(Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001) also makes reference to a semantic
route; however, this route has not been implemented in its simulations, and the activation
of semantics is not necessary for word reading. In the triangle model, semantic knowledge
is necessary and has a particularly important role to play in the reading of exception
words and for poor readers. Similarly, in his developmental account, Share (1995) argued
that top-down support from semantic information helps readers to resolve decoding
ambiguity (for similar proposals, see Bowey & Rutherford, 2007; Tunmer & Chapman, 2012).
According to this view, when a word is encountered that cannot be readily decoded, either
because it is an exception word or because the reader does not possess the requisite
reading ability, semantic information relating to the context or the word can be combined
with a partial decoding attempt to successfully read the word. In most studies, the
relationship between semantic knowledge and word reading has been investigated by
measuring both constructs and testing whether these constructs are correlated across
participants, showing that there is a general relationship between some index of the
semantic knowledge that individuals can access and the number of words that they can read
on an unrelated measure. However, theoretical positions proposing a direct and necessary
relationship between semantics and word reading (e.g., Harm & Seidenberg, 2004) motivate a
more precise hypothesis of the relationship between these variables. Specifically, that
knowledge of an individual word should aid reading of that particular word. This
hypothesis is corroborated by evidence from semantic dementia patients, some of whom
experience difficulty in reading exception words alongside their semantic impairments but
who are more likely to successfully read exception words for which they know the meanings
(Graham, Hodges, & Patterson, 1994; Woollams, Ralph, Plaut, & Patterson, 2007; but see
Schwartz, Saffran, & Marin, 1980, for a contrasting case). In what follows, we summarize
pertinent data from studies with children. Nation and Cocksey (2009) probed item-level
relationships between semantic knowledge and word reading in children. Participants aged 7
years read lists of regular and exception words and completed auditory lexical decision
and definitions tasks as indexes of phonological and semantic lexical knowledge,
respectively. Nation and Cocksey found that children demonstrated phonological and
semantic knowledge of the majority of words that they read correctly, and this
relationship was stronger with exception words than with regular words, although a small
percentage of words were read correctly without being recognized in the auditory lexical
decision task or defined correctly. Across-items performance in both auditory lexical
decision and definitions tasks showed equivalent correlations with word reading. In
further analyses, both auditory lexical decision performance and definitions knowledge
were entered into by-items regression analyses predicting exception word reading. Auditory
lexical decision performance explained unique variance in exception word reading after
accounting for the variance explained by definitions performance. However, definitions did
not explain unique variance in exception word reading after accounting for the variance
explained by auditory lexical decision. This led the authors to conclude that lexical
phonology (familiarity with a word’s phonological form) is sufficient to support word
reading and that possessing deeper semantic knowledge does not predict more successful
reading. However, they interpreted their findings with caution due to the small sample
size and the recognition that by-items performance on their auditory lexical decision task
was skewed toward ceiling. Two training studies conducted by Duff and Hulme (2012,
Experiment 2) and McKague, Pratt, and Johnston (2001) showed that pre-exposing children to
the phonological forms of words facilitates learning to read those items, as does pre-
exposure to phonology plus semantics (see also Ouellette & Fraser, 2009; Wang, Nickels,
Nation, & Castles, 2013). In Duff and Hulme (2012) and McKague and colleagues (2001), pre-
exposure to phonology plus semantics did not confer an additional advantage beyond pre-
exposure to phonology alone, resonating with Nation and Cocksey’s (2009) claim that
lexical phonology is sufficient to support word reading. In contrast, adult studies have
indicated that semantic pre-exposure supports learning to read exception words over and
above pre-exposure to phonology alone (McKay, Davis, Savage, & Castles, 2008; Taylor,
Plunkett, & Nation, 2011), consistent with data from semantic dementia patients (for a
review of relevant research, see Taylor, Duff, Woollams, Monaghan, & Ricketts, 2015).
Taken together, findings are mixed. In relation to ideas put forward by Share (1995) and
others (Bowey & Rutherford, 2007; Tunmer & Chapman, 2012), knowing a word’s phonological
form may be sufficient to support partial decoding attempts, but knowledge of semantics
may also be important. Resolving this issue was one motivation for our study.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

We investigated whether semantic knowledge predicts word reading in 6- and 7-year-old
children, bringing together two approaches that have been used to explore this
relationship. In the first approach, we measured semantic knowledge and word reading using
standardized tests and also asked children to read lists of regular and exception words to
assess whether there is a general relationship between semantic knowledge and word reading
(cf. Nation & Snowling, 2004; Ouellette & Beers, 2010; Ricketts et al., 2007). As in
Nation and Snowling (2004), we measured both lexical–semantic knowledge (expressive
vocabulary) and broader semantic knowledge (semantic relations between words). Our measure
of lexical–semantic knowledge was an expressive oral vocabulary measure that captured
depth as well as breadth; such measures have been found to predict exception word reading
more strongly than measures of breadth alone in children of this age (Ouellette & Beers,
2010). Our measure of broader semantic knowledge assessed awareness of meaning-based
relationships between words. In our second approach, we investigated item-specific
relationships between word knowledge and word reading (after Nation & Cocksey, 2009). We
exposed children to lists of regular and exception words in tasks assessing word knowledge
(auditory lexical decision and definitions) and reading (reading in isolation and reading
in sentence context) to probe whether knowledge of a word’s phonological form or semantic
attributes would predict the ability to read that particular word. Our study builds on
previous work by assessing reading in a more naturalistic contextualized task in addition
to the reading in isolation approach adopted by the majority of studies. Notably, children
typically read words, particularly exception words, more accurately in context (Archer &
Bryant, 2001; Nation & Snowling, 1998). We also extend previous research by using mixed-
effects models to estimate item-specific relationships between word knowledge and word
reading while accounting for error variance due to participants and items. In sum, we took
a novel approach to probing the mechanisms underpinning the relationship between word
knowledge and word reading by (a) investigating general and item-specific relationships in
the same study with the same children, (b) measuring richer semantic knowledge using the
semantic relationships task as well as oral vocabulary, and (c) measuring word reading in
context as well as in isolation. Our hypotheses were as follows. First, we hypothesized a
general relationship between semantic knowledge (both vocabulary and semantic
relationships) and word reading (Nation & Snowling, 2004) that would be stronger for
exception words than for regular words (Ricketts et al., 2007). Second, we predicted an
item-specific relationship between word knowledge (as indexed by auditory lexical decision
and definitions) and word reading, again expecting that this relationship would be
stronger for exception words (Nation & Cocksey, 2009). We further predicted that auditory
lexical decision might be an equivalent or stronger predictor of word reading compared
with definitions (Nation & Cocksey, 2009). Finally, we expected that regular words would
be read more accurately than exception words (Nation & Cocksey, 2009), words would be read
more accurately in context than in isolation (Archer & Bryant, 2001), and this contextual
facilitation effect would be more pronounced for exception words than for regular words
(Nation & Snowling, 1998; Share, 1995).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A sample of 27 children (10 boys) aged 6 and 7 years participated in this study (M = 6.50
years, SD = 0.26). All children from one year group attending two schools serving socially
mixed catchment areas in Birmingham, United Kingdom, were invited to take part provided
that they spoke English as a first language and did not have any recognized special
educational need. Data were collected and analyzed from all children for whom informed
parental consent was received. Children had experienced 2 years of formal literacy
instruction. Ethical approval was provided by the ethics committee at the Institute of
Education, University of London.

        <hss>Standardized tasks</hss>

        Children completed standardized tasks in two sessions, each lasting approximately
        30 min. Sessions were separated by approximately 1 week (mean amount of time
        between testing sessions = 5.26 days, SD = 1.58). All background measures were
        published standardized tasks and were administered according to manual
        instructions in a fixed order across the two sessions. Nonverbal reasoning was
        measured using the Matrix Reasoning subtest of the Wechsler Abbreviated Scale of
        Intelligence (WASI; Wechsler, 1999), which is a pattern completion task. Word-
        level reading was assessed using the Phonemic Decoding Efficiency (PDE) and Sight
        Word Efficiency (SWE) subtests of the Test of Word Reading Efficiency (TOWRE;
        Torgesen, Wagner, & Rashotte, 1999). In each subtest, children are asked to read a
        list of nonwords (PDE) or words (SWE) of increasing length and difficulty as
        quickly as they can. Efficiency was indexed by the number of nonwords or words
        read correctly in 45 s. Semantic knowledge was indexed by the Vocabulary and
        Similarities subtests of the WASI (Wechsler, 1999). The Vocabulary subtest is a
        measure of expressive vocabulary that requires children to verbally define words.
        The Similarities subtest measures knowledge of the semantic relationships between
        words; children are presented with two semantically related words and are asked to
        describe how these words are related in meaning.

        <hss>Experimental tasks</hss>

        Children were exposed to 40 words in the context of four tasks: two assessing
        reading (reading in isolation and reading in context) and two indexing lexical
        knowledge (auditory lexical decision and definitions). Tasks were completed in the
        following fixed order: auditory lexical decision, reading in isolation,
        definitions, and reading in context. Tasks were presented in this order to limit
        contamination across tasks. Nonetheless, repetition effects were possible and were
        confounded with the isolation versus context manipulation. However, the first
        three tasks were completed during the first session, and the final task was
        completed during the second session. Thus, the reading tasks were completed on
        separate days. All tasks were separated by time and interleaved with filler tasks
        to minimize children’s awareness of the repetition of items. The auditory lexical
        decision task was included to assess children’s familiarity with the phonological
        forms (lexical phonology), and the definitions task was administered to tap item-
        specific lexical–semantic knowledge (lexical semantics).

            <hss>Stimuli</hss>

            Stimuli are included in the Appendix and comprised 20 regular words and 20
            exception words, taken from longer lists in the Diagnostic Test of Word
            Reading Processes (DTWRP; Forum for Research in Literacy & Language, 2012).
            Regular words included only graphemes that were pronounced according to
            grapheme–phoneme correspondence (GPC) rules (Rastle & Coltheart, 1999),
            whereas exception words included one or more graphemes with pronunciations
            that deviated from these rules (e.g., the <s> in <sugar> has an atypical
            pronunciation). The stimuli included monosyllabic and multisyllabic words.
            Because stress patterns affect pronunciation in multisyllabic words, during
            DTWRP design an expert panel of psychologists, linguists, and psycholinguists
            provided consensus that the regular multisyllabic words were pronounceable
            using usual grapheme–phoneme mappings. All words selected for the current
            study could be used as nouns. Regular and exception word lists were closely
            matched (all ps > .05) on length measured in phonemes, letters, or syllables
            and on printed word frequency, where available from the Children’s Printed
            Word Database (Masterson, Dixon, Stuart, & Lovejoy, 2003), otherwise from the
            CELEX Lexical Database (Baayen, Piepenbrock, & van Rijn, 1993). In addition,
            lists were matched (all Fs < 1) for bigram token frequency, bigram type
            frequency, trigram token frequency, trigram type frequency, and number of
            orthographic neighbors (data from N-Watch; Davis, 2005). See Table 1 for a
            summary of the stimulus characteristics of the regular and exception words.

            <hss>Reading tasks</hss>

            In the first reading task, children read each word aloud in isolation. In the
            second reading task, children read each word in a sentence context, with each
            word appearing at the end of a sentence stem ranging in length from four to
            nine words. In each trial of the contextualized reading task, a sentence stem
            was presented on the screen first. Following this, the target word was
            presented. Children were asked to read sentence stems and target words aloud.
            Sentence stems and target words were presented separately to minimize
            differences between the two reading tasks. In addition, the examiner corrected
            any errors made while reading sentence stems to maintain comprehension for the
            context. Errors made while reading target words were not corrected. To develop
            sentence stems, regular and exception words were paired according to
            difficulty (using the difficulty order from the DTWRP; Forum for Research in
            Literacy & Language, 2012) so that sentence stems could be matched in pairs
            for overall printed word frequency (Masterson et al., 2003) and for length in
            words, letters, and syllables (all Fs < 1). A series of cloze procedures was
            conducted with adults to develop contexts that were not overly constraining
            such that participants could not readily guess the target from the sentence
            stem and, therefore, would need to read it. For each cloze procedure, adults
            were asked to complete each sentence stem (with target words missing). For the
            sentence stems used in this study, a maximum of 2 of 25 adults inserted the
            target in any one case, showing that children were unlikely to guess the
            target word from the sentence stem. Within isolation and context reading
            tasks, trials were blocked by type (exception then regular). Stimuli were
            presented in random order within blocks using the E-Prime program (Schneider,
            Eschman, & Zuccolotto, 2002a, 2002b). Words and sentences were presented in
            Arial 25-point font, and the approximate viewing distance was 40 cm. Words
            subtended an approximate mean visual angle of 4.37° to 10.82° for 4- and
            10-letter words, respectively. Accuracy was calculated for each child in each
            task (i.e., number of words read correctly). The maximum score was 20 for each
            list (regular or exception) within each task.

            <hss>Auditory lexical decision</hss>

            The auditory lexical decision task was administered to determine whether
            children were familiar with the phonological form of each word (lexical
            phonology). The 40 words were presented along with an equal number of nonwords
            from the ARC database (Rastle, Harrington, & Coltheart, 2002) that were
            matched to the words for number of letters and, in most cases (80%), for
            initial phoneme. Items were recorded by a native speaker of English. Stimuli
            were presented one at a time through headphones, and children were required to
            make a manual key-press response to indicate whether the item was a word or
            not. Children completed four practice trials at the beginning of the task to
            ensure that they understood the task demands. Stimuli were presented in random
            order, and response accuracy (max = 20 for each word list) and latencies were
            recorded using E-Prime.

            <hss>Definitions</hss>

            Children were asked to describe what each word meant, yielding a measure of
            lexical–semantic knowledge. All 40 words were administered in a single random
            order. Items were blocked such that children responded to items from the
            exception word list first and then items from the regular word list. The
            resulting definitions (N = 1080) were scored by two independent coders as 0
            (no definition/incorrect definition), 1 (partial definition), or 2 (full
            definition). Criteria for scoring a 0, 1, or 2 for each word were agreed to by
            the first author and coders beforehand. The coders then scored each definition
            without any consultation. There was a high degree of inter-rater reliability,
            r(1080) = .96. Nonetheless, the coders discussed each discrepant score in turn
            (with advice from the first author), reaching consensus in all cases. A total
            definitions score (max = 40 for each list) was calculated for each child.

<h>RESULTS</h>
-------

Mean normative scores were at or near the average range on standardized assessments of
nonverbal reasoning, semantic knowledge, and word-level reading (see Table 2 for a
summary). High reliability estimates are reported for all tasks. Table 3 summarizes
performance by participants and by items, as well as reliability estimates (Cronbach’s
alpha), for experimental word tasks. Reliability estimates were acceptably high for most
tasks but were relatively low for auditory lexical decision. We next present findings on
(a) correlation and regression analyses exploring general relationships between semantic
knowledge and word-level reading (with scores calculated by participants in the more
traditional way) and (b) mixed-effects models that probe effects of regularity (regular
vs. exception) and reading task (isolation vs. context), as well as item-specific
relationships between semantic knowledge and word-level reading (taking into account
random effects due to participants or items).

<hs>  General relationships between semantic knowledge and word-level reading</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 4 presents bivariate parametric correlations (by participants) between raw scores on
standardized measures of semantic knowledge (vocabulary, similarities) and all reading
tasks (TOWRE PDE, TOWRE SWE, and regular and exception word reading in both isolation and
context). Pertinent to our hypotheses, Table 4 indicates medium to large correlations
between each measure of semantic knowledge and each measure of word-level reading.
Contrary to our expectations, semantic variables were not more closely related to
exception word reading than to regular word reading, and across word reading tasks
performance was less highly correlated with scores on the vocabulary task than with scores
on the similarities task. For nonword reading (measured by the TOWRE PDE), scores showed a
higher correlation with vocabulary than with similarities, although coefficients were
similar. A series of regression analyses (see Table 5) was then conducted to probe whether
semantic knowledge explains additional variance in word reading after accounting for
variance explained by phonological decoding ability (measured by TOWRE PDE score), which
was entered at the first step. Separate analyses were conducted with performance on each
word reading measure (number of words read correctly by each participant) as the outcome
variable. Decoding was a significant independent predictor of each word reading measure in
each analysis. After accounting for the variance that decoding explained, similarities but
not expressive vocabulary explained additional variance in each outcome variable. These
models explained between 62% and 79% of the variance in word reading. Models with
similarities explained more variance (67%–79%), with similarities explaining approximately
5% to 10% of that variance. In summary, there was a clear relationship between semantic
knowledge and word reading ability; this was more marked for the similarities task.

<hs>  Mixed-effects models</hs>
  ~~~~~~~~~~~~~~~~~~~~

In generalized linear mixed-effects models (GLMMs), we examined the factors that
influenced the log odds of response accuracy, including fixed effects due to item
regularity (regular vs. exception), experimental reading task (in isolation or in
context), and word knowledge (auditory lexical decision or word definitions scores), as
well as random effects due to variation in overall accuracy (random intercepts) or in the
slopes of the fixed effects (random slopes) associated with differences between sampled
participants or stimuli (Baayen, Davidson, & Bates, 2008). This approach allowed us to
avoid the problems associated with analyzing dichotomous outcomes using linear models
(discussed by, e.g., Baayen, 2008; Dixon, 2008; Jaeger, 2008). We analyzed 2160
observations—27 children reading 20 regular and 20 exception words, once in each of the
isolated and context conditions—using the glmer function in the lme4 package (Bates,
Maechler, Bolker, & Walker, 2014) in R (R Core Team, 2014). We tested the relative utility
of including hypothesized fixed effects or potential random effects in our models by
performing pairwise likelihood ratio test (LRT) comparisons (Barr, Levy, Scheepers, &
Tily, 2013; Pinheiro & Bates, 2000) of simpler models with more complex models, where the
former are nested within the latter. In the following, we outline the results of the model
comparisons but report only estimates of fixed and random effects for the final model.
Interested readers are invited to contact the first author for supplementary material,
including the data, code used in analyses, and estimates associated with intermediate
models. First, we tested our hypotheses by progressing through a series of models with
varying fixed effects but the same random effects, starting with a model of the log odds
of response accuracy with no fixed effects and just the random effects of participants and
items on intercepts (average accuracy)—an “empty model.” Compared with the empty model, a
model including terms corresponding to regularity, reading task, auditory lexical
decision, and definitions significantly improved model fit: LRT, χ2 = 41.08, 4 df, p <
.001. In this main-effects model, there were significant effects of reading task and
definitions only (both ps < .001). Our remaining hypotheses were addressed by adding
interaction terms. Compared with the main-effects model, a model also including the
regularity by reading task interaction improved model fit: LRT, χ2 = 5.30, 1 df, p = .021.
Adding regularity by auditory lexical decision and regularity by definitions terms did not
further improve model fit: LRT, χ2 = 0.47, 2 df, p = .789. Thus, we adopted a final model
that included the main-effects and regularity by reading task terms. Following Baayen
(2008; see also Pinheiro & Bates, 2000), we examined whether both random intercepts terms
were required by performing pairwise LRT comparisons of models with the same fixed effects
as the final model but varying random effects as follows: (i) a model with both random
effects of participants and items on intercepts, as in the models detailed in the
forgoing; compared with (ii) a model with just the random effect of participants on
intercepts; and compared with (iii) a model with just the random effect of items on
intercepts. We found that both random intercepts terms were warranted by improved model
fit to data (inclusion of a random effect of participants on intercepts: LRT, χ2 = 754.85,
1df, p < .001; inclusion of a random effect of items on intercepts: LRT, χ2 = 585.05, 1df,
p < .001). In Models (ii) and (iii), the pattern of significant effects remained largely
the same, with significant effects of reading task and definitions and a regularity by
reading task term that was nearly significant (Model ii: p = .058; model iii: p = .094).
However, in each model, the auditory lexical decision effect was also significant (both ps
< .001). Thus, when variation relating to either participants or items alone was taken
into account, both auditory lexical decision and definitions showed a significant
relationship with word reading. However, after simultaneously accounting for variation
relating to both, only the definitions effect remained. Following Barr and colleagues’
(2013) recommendations, we examined the importance of random slopes (random differences
between participants or between items in the slopes) of the fixed effects due to reading
task, word knowledge, or the regularity by reading task interaction. We did this by
testing whether model fit was improved by the inclusion of terms corresponding to random
effects of participants or items on the slopes of the fixed effects. We found that a model
including terms corresponding to random effects of participant differences on the slopes
of word regularity and reading task effects, and corresponding to random effects of item
differences on the slopes of both word knowledge measures (definitions and auditory
lexical decision), significantly fit the data better than a model including the same fixed
effects and just random intercepts: LRT, χ2 = 34.46, 10 df, p < .01. Thus, including the
observed variability between participants in the slopes of both regularity and reading
task effects, and between responses to different items in the slope of the word knowledge
effect, improved model fit. Table 6 summarizes the final model, with fixed effects due to
regularity, reading task, the regularity by reading task interaction, and word knowledge
(scores on auditory lexical decision and definitions tests) as well as random effects of
participants and items on intercepts and on the slopes of the fixed effects. The estimated
coefficients for the final model show that reading accuracy was higher for the context
(vs. isolation) task and for words that had been defined more accurately. Furthermore, the
model revealed a regularity by reading task interaction. Inspection of Table 3 indicates
that a regularity effect was more evident when words were read in isolation rather than in
context and that the influence of context was greater for exception words than for regular
words. Contrary to our hypotheses, we found that (a) semantic knowledge showed equivalent
relationships with regular and exception word reading and (b) auditory lexical decision
performance was not associated with word reading.

<h>DISCUSSION</h>
----------

The results support our primary hypothesis that variation in semantic knowledge is
associated with variation in word reading performance. Indeed, we have provided robust
evidence for this by observing this association, for the first time, across both general
and item-specific analyses. We have extended previous findings on reading words in
isolation by assessing word reading in context, which is more akin to how children
encounter words naturally. We observed an interaction between context and word type such
that sentence context particularly facilitated reading of exception words, in line with
previous studies (Nation & Snowling, 1998). It is worth noting that the reading in
isolation task was always administered before the reading in context task; thus, any
contextual benefit must be interpreted with caution because some improvement might be
attributable to practice effects. However, tasks were separated by approximately 1 week.
Furthermore, the order of the tasks does not invalidate our finding of an interaction
between context and word type, nor does it affect our key findings that semantic knowledge
(as measured by the similarities task) predicted reading in context as well as reading in
isolation in regression analyses and that lexical–semantic knowledge and contextual
effects were independently predictive of word reading in our mixed-effects analyses.
Theories of word reading focus almost exclusively on reading in isolation. Nonetheless,
our findings are consistent with developmental theories that highlight the importance of
contextual support for word reading (Share, 1995) and with the triangle model’s (yet to be
implemented) assumption that semantics and context exert separable but interacting effects
on reading aloud (Bishop & Snowling, 2004; Seidenberg & McClelland, 1989). We hope that
the current study, along with other empirical studies of word reading in context (Martin-
Chang & Levesque, 2013; Nation & Snowling, 1998), will pave the way for research that aims
to probe the mechanisms that underpin word reading as it occurs naturally. An important
first step will be to specify how context supports word reading, why this might be more
beneficial for exception word reading than for regular word reading, and why this effect
was separable from that of item-specific semantic knowledge in our analyses. In the
current study, context was provided at the sentence level and may have conveyed useful
semantic information along with other cues (e.g., grammar). Thus, one plausible
interpretation of our findings would be that semantic information from the context
supported word reading, and this was more effective for exception words than for regular
words. However, this interpretation is premature; our data do not address whether this
effect was driven by semantic information or other cues provided by context. We found that
semantic knowledge showed equivalent relationships with regular and exception word
reading, a finding that we replicated across by-participants regression analyses and
mixed-effects models. To the extent that our measures of semantic knowledge map onto the
way in which semantic representations are activated in the triangle model, this finding
contrasts with the triangle model, where semantic knowledge is seen as more important for
exception word reading than for regular word reading (e.g., Harm & Seidenberg, 2004;
Strain, Patterson, & Seidenberg, 1995; but see Woollams et al., 2007, for effects of
semantics on regular word reading within a triangle model framework). Notably, it is also
at odds with pertinent developmental findings that semantic knowledge shows a closer
relationship with exception word reading than with regular word reading in English-
speaking children (Nation & Cocksey, 2009; Ricketts et al., 2007), whereas it is in accord
with emergent findings from English-speaking children indicating relationships between
semantic variables and both regular and exception word reading (Duff & Hulme, 2012;
Mitchell & Brady, 2013; see also findings from Spanish-speaking adults reported by Davies,
Barbón, & Cuetos, 2013, and from English-speaking adults reported by Strain & Herdman,
1999). It remains to be seen whether this finding is predicted by the DRC model (Coltheart
et al., 2001) given that current instantiations have not yet simulated the role of
semantics in word reading development (see Taylor, Rastle, & Davis, 2013). There are a
number of possible explanations for discrepancies between our observations and previous
findings. Marked ceiling effects on regular word reading could explain weaker
relationships between semantic knowledge and regular word reading in previous studies
(Nation & Cocksey, 2009; Ricketts et al., 2007). Another possibility concerns the age and
reading ability of participants. Semantic knowledge may contribute more indiscriminately
to word reading during the early stages of reading development when children have limited
knowledge of orthography-to-phonology mappings (as in our study; for a similar argument,
see Duff & Hulme, 2012). With reading experience, the role of semantics in regular word
reading may decrease such that a closer relationship between semantic knowledge and
exception word reading emerges. In addition, the impact of semantic knowledge on word
reading may be influenced by item-level characteristics such as length, frequency,
familiarity, and meaning (Mitchell & Brady, 2013). Indeed, our set of regular words were
harder to define than our set of exception words. This could go some way to explaining the
finding that semantic knowledge contributes to both regular and exception words. Future
research should aim to explore the conditions under which semantic knowledge affects
regular word reading, adopting developmental designs and varying stimulus characteristics.
In correlation analyses (by participants), all standardized measures of semantic knowledge
and word-level reading were inter-correlated. However, knowledge of semantic relationships
(similarities) was consistently more highly correlated with word reading than with oral
vocabulary knowledge. After controlling for decoding skill, regression analyses showed
that similarities, but not expressive vocabulary, predicted word reading. One possible
explanation for this finding is that scores on the similarities measure were more varied
than scores on the vocabulary measure such that the similarities measure may have captured
more fully the variability in semantic knowledge in our sample. The hypothesis that
performance on the similarities measure was systematically more varied than performance on
the oral vocabulary measure could be explored in future research. Previous studies that
have investigated general relationships between more than one semantic measure and word
reading have shown that the semantic predictors of word reading (after controlling for
decoding) vary according to the age of the participants and the outcome measures used in
analyses. In Ouellette and Beers (2010), both depth and breadth of vocabulary knowledge
were measured. In younger participants (5–7 years) depth but not breadth predicted
irregular word reading, whereas in older participants (11 and 12 years) the opposite
pattern was observed. Nation and Snowling (2004) employed a measure of vocabulary and a
“semantic composite” (semantic fluency and synonym judgment). Both measures predicted word
reading concurrently, but only oral vocabulary was a longitudinal predictor of exception
word reading. The finding that oral vocabulary did not predict word reading in our
regression analyses also contrasts with the item-specific effects detected in our mixed-
effects models. This seems surprising given that the definitions task was designed to
parallel the standardized expressive vocabulary measure that we used by asking children to
define words and adopting a three-point scoring approach. Plausibly, this discrepancy
could be explained by differences in the variables included in the models. We controlled
for decoding ability in our by-participants analyses so that we could examine the
relationship between semantic knowledge and word reading after accounting for the
substantial variance in word reading explained by decoding skill (this is a standard
approach; see, e.g., Ouellette & Beers, 2010; Ricketts et al., 2007). However, we did not
include decoding ability in our mixed-effects analyses because the models were specified
as confirmatory analyses (following, e.g., Barr et al., 2013) of the effects of the
following experimental factors: reading task, regularity, and word knowledge type.
Nevertheless, the addition of decoding ability to the final model did not change the
pattern of results. Different findings across our analytical approaches could instead
reflect the way in which our mixed-effects models capture a specific relationship between
knowledge of an item and reading that same item, whereas the by-participants regressions
explore a more general relationship between a measure of children’s lexical–semantic
knowledge, which could act as a proxy for their item-specific semantic knowledge or their
ability to use context, and their ability to read a separate set of words. Arguably, this
general relationship could be weaker. Taken together with the mixed findings discussed in
the preceding paragraph, it is clear that although the relationship between semantic
knowledge and word reading is robust, the precise pattern of findings observed varies
across analyses and data sets. Notably, however, our observations show that semantic
knowledge is predictive of word reading ability. Mixed-effects models demonstrated that
correctly defining a word was a significant predictor of accurately reading that word,
whereas accepting it as a word in our lexical decision task was not. This result was
unexpected given that in Nation and Cocksey (2009) performance on definitions and auditory
lexical decision tasks showed equivalent (significant) correlations with word reading and
that auditory lexical decision was the stronger predictor in by-items regression analyses
(for similar findings, see Duff & Hulme, 2012, Experiment 2; McKague et al., 2001). Thus,
we did not replicate Nation and Cocksey’s (2009) finding that auditory lexical decision
predicts word reading, nor did we provide support for their proposal that lexical
phonology is enough to support word reading (i.e., lexical–semantic knowledge provides no
additional benefit). Instead, our findings indicate that it is lexical–semantic rather
than lexical–phonological knowledge that supports word reading. Other investigations of
the relative importance of lexical phonology and semantics for word reading have indicated
that semantic knowledge is a better predictor of reading success than phonological
knowledge (Duff & Hulme, 2012, Experiment 1; McKay et al., 2008; Taylor et al., 2011),
resonating with our findings. One plausible explanation for the discrepancy between our
study and that of Nation and Cocksey (2009) relates to the different analytic approaches
adopted in the studies. In Nation and Cocksey’s study, correlations and regressions were
conducted across items (an F2 by-items analysis), thereby taking into account random error
variance due to the items. In contrast, our final mixed-effects model incorporated random
error variance due to both participants and items. Thus, accounting for both sources of
error variance could have “washed out” the effect of auditory lexical decision. Indeed,
when our model accounted for either error variance due to participants (akin to F1 by-
participants analyses) or error variance due to items (akin to F2 by-items analyses), we
replicated Nation and Cocksey’s finding; both definitions and auditory lexical decision
performance predicted word reading. Analyses reported by Baayen and colleagues (2008)
indicate that fixed effects are better estimated in repeated measures studies when both
random participants and item effects are taken into account (see also Barr et al., 2013).
Essentially, these models specify, rather than assume, the random variation in the data
that is due to participants (in this case variation in children’s reading accuracy) and
items (in this case variation in performance in response to individual words). It is
possible that our findings would be replicated in Nation and Cocksey’s data if mixed-
effects models were applied, supporting a conclusion that lexical semantics, but not
lexical phonology, affects word reading. Caution is warranted in interpreting our auditory
lexical decision results. Reliability for this task was low, and post hoc consideration of
its stimuli has highlighted its limitations. Following Nation and Cocksey (2009), we
selected nonwords that matched our words in terms of letter length and initial letter (or
phoneme). However, we should have explicitly matched words and nonwords for number of
syllables and phonemes. We checked this retrospectively, discovering that our words had
approximately one more phoneme (M = 5.50, SD = 1.68 vs. M = 4.45, SD = 1.11) and one more
syllable (M = 2.13, SD = 0.79 vs. M = 1.03, SD = 0.16). It is possible that this made the
nonwords superficially distinctive from the words, making the task easier and reducing the
extent to which lexical knowledge was used to make decisions (they could instead have been
made on the basis of shallower processing). By participants, there is no indication of
ceiling effects, and performance showed good variability. By items, performance again
showed good variability, but scores were closer to ceiling (this is also the case in
Nation & Cocksey, 2009), providing some evidence that discriminating between particular
words and nonwords was fairly easy. Ceiling effects by items may also explain poor
reliability (Cronbach’s alpha) on the auditory lexical decision task. Our choice of
nonword distracters, therefore, may have restricted relationships between auditory lexical
decision performance and reading because auditory lexical decision performance did not
consistently reflect lexical knowledge or because scores on this task showed poor
reliability (for further discussion of the impact of poor reliability on correlational
analyses, see Vul, Harris, Winkielman, & Pashler, 2009). The nature of the nonwords used
in the auditory lexical decision task has important implications for how performance on
this task should be interpreted (e.g., Ernestus & Cutler, 2015). As mentioned above,
superficial differences between our word and nonword stimuli may have reduced the use of
lexical knowledge in making decisions. Equally, however, in tasks where nonwords are very
word-like, lexical decisions are commonly assumed to reflect greater reliance on semantic
processing (Binder et al., 2003). An important goal for future research will be to
investigate the relative contributions of lexical phonology and semantic knowledge to word
reading using more carefully controlled auditory lexical decision stimuli and/or other
tasks designed to tap lexical phonology. In sum, our findings provide robust and novel
support for the idea that semantic knowledge and sentence context independently support
word reading (cf. Bishop & Snowling, 2004). In addition, they add to emergent evidence
that lexical or semantic knowledge supports reading of regular words as well as exception
words (Davies et al., 2013). If semantic knowledge is causally related to word reading
success, then training knowledge of word meanings should benefit word reading. Findings
from such training studies have so far been inconclusive, with some suggesting that
training lexical-level phonological knowledge is sufficient to support word reading (Duff
& Hulme, 2012, Experiment 2; McKague et al., 2001) and others indicating that semantic
knowledge exerts an effect beyond phonology (McKay et al., 2008; Taylor et al., 2011).
Future empirical and theoretical studies that adopt psychologically plausible approaches
to learning and development should aim to advance our understanding of how the
relationship between lexical knowledge and word reading changes with age and development
and whether semantic knowledge is causally related to word reading.


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<ART>Exploring early communicative behaviours: A fine-grained analysis of infant shows and gives
================================================================================

Authors: Laura Boundy, Thea Cameron-Faulkner, Anna Theakston
DOI: 10.1016/j.infbeh.2016.06.005
Year: 2016  |  Pages: 86-97
ASJC codes: 3204
Keywords: Caregiver responsiveness, Communicative behaviours, Giving gestures, Joint attention, Micro-behaviours, Pre-linguistic communication, Showing gestures

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The ability to share and direct attention is a pre-requisite to later language development and has been predominantly studied through infant pointing. Precursors to pointing, such as showing and giving gestures, may display similar communication skills, yet these gestures are often overlooked. This may be due to difficulty in discerning these gestures in interaction. The current study had two aims; firstly, to identify the micro-behaviours associated with showing and giving gestures in infants under 12 months, in order to ascertain whether these form two discrete communicative behaviours. Secondly, to examine whether these micro-behaviours predicted caregiver responses to these gestures. Fine-grained coding of show and give gestures, their micro-behaviours and caregiver responses was conducted through secondary analysis of naturalistic, triadic interactions between 24 infants, caregivers and a selection of toys. Findings suggested that the micro-behaviours arm position, hand orientation and eye-gaze, were significant predictors of infant gesture type, however only arm positioning was a significant predictor of caregiver response. This suggests that early showing and giving gestures can be classified based on some associated micro-behaviours, however caregiver's responses may not be contingent on these same cues, potentially resulting in difficulty understanding infant gestures. Our findings enhance our understanding of infant communication before 12 months, provide guidance to both researchers and caregivers in the identification of infants' early shows and gives, and highlight the need for greater study of these early pre-linguistic behaviours.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Between 9–12 months, infants experience a transition in their interaction with the world.
Systematic patterns emerge in their communicative behaviours as they begin to use deictic
gestures combined with eye-gaze, vocalisations, body movements and facial expressions to
engage in social interaction with a communicative partner (Bates, 1979; Igualada, Bosch &
Prieto, 2015; Liszkowski, Brown, Callaghan, Takada, & De Vos, 2012). The presence of these
multimodal communicative behaviours is believed to be an indicator of an infant’s joint
attention abilities, and a considerable body of evidence links these skills to later
language development (Kristen, Sodian, Thoermer, & Perst, 2011; Laakso, Poikkeus,
Katajamäki, & Lyytinen, 1999). Generally, these early communicative skills have been
studied mainly through the pointing gesture (Carpenter, Nagell, & Tomasello, 1998; Cochet
and Vauclair, 2010; Tomasello, Carpenter & Liszkowski, 2007). Pointing is perceived as a
tool used to initiate joint attention between the infant and adult and pointing
declaratively (i.e. pointing with a motive to share or direct attention onto a specific
object or event) is a good predictor of later language outcomes (Colonnesi, Stams, Koster,
& Noom, 2010; Tomasello et al., 2007). Infants begin to use pointing with a communicative
intent at around 11–12 months of age (Fusaroa, Vallotton, & Harris, 2014) and both
experimental and non-experimental studies consistently highlight a relationship between
this type of pointing and skills in both the production and comprehension of language,
particularly verbal naming (see Colonnesi et al., 2010 for a review). Pointing is
generally perceived as a landmark communication skill at around 12 months of age
(Colonnesi et al., 2010; Liszkowski, 2010). There is evidence however to suggest that
infants can engage in communicative behaviours prior to the emergence of pointing. Bates,
Camaioni, and Volterra (1975) found that showing and giving behaviours emerged around 10
and 11 months respectively, whereas pointing with communicative intent did not appear
until 12–13 months. The shift from showing and giving to pointing indicates the infant’s
understanding of the difference between the self and objects. Pointing is believed to be
more cognitively complex as it exists outside of the object context and draws attention to
more distal referents (Bates, Thal, Whitesell, Fenson & Oakes, 1988). However, both
showing and giving behaviours also reflect the ability to initiate joint attention and
demonstrate an understanding that the adult is an agent separate from the environment and
capable of engaging with an object. Support for the claim that shows and gives are
precursors to pointing is presented in Cameron-Faulkner, Lieven, Theakson, & Tomasello
(2015). In their study of 10–12 month old infants, shows and gives emerged prior to
pointing behaviours and also had a strong association with the later use of points but not
reaches (the latter of which are associated with imperative behaviours and are not deemed
to be as cognitively complex in nature). Beuker, Rommelse, Donders & Buitelaar (2013)
examined the developmental trajectory of specific joint attention skills and their
interrelations with later vocabulary size. They found that infants who developed joint
attention skills at an earlier age, specifically gestures which involved directing
attention (such as showing, giving and pointing) displayed larger receptive and expressive
vocabulary growth earlier in life. Thus, showing and giving gestures may be good
candidates for studying the foundations of early communication and the skills that make us
uniquely human. To date pre-linguistic showing and giving behaviours have been under-
researched, particularly when compared to studies on pointing. A potential reason for this
absence is the lack of a clear definition of the two constructs. Bates et al. (1975, 1976)
highlighted the difficulty in distinguishing showing and giving behaviours, suggesting
that their function is often ascertained by how others react to the social context and
that often, infant intentions are misinterpreted by caregivers. They referred to shows and
gives as an extension of the arm towards the adult and distinguished between the two
behaviours based on whether the infant gave the toy to the adult or kept it for
themselves. Clements and Chawarska (2010) built on these definitions in their study of
shows, gives and points in 9 and 12 month olds with autism. Shows were defined as “a
person’s arm extending toward another person’s face while holding an object” (p. 48)
whereas giving behaviours were described as “placing an object in another person’s hand or
pushing an object at least halfway toward another person” (p. 48). Even with these more
detailed definitions, the authors noted that pointing gestures were more salient than
showing gestures due to their specific hand form (i.e. an outstretched arm with the index
finger extended). The lack of salience of many showing gestures creates problems from a
methodological viewpoint. Typically, naturalistic research on gesture development is
conducted through observation or parental diaries. Although this provides an ecologically
valid measure of infants’ spontaneous gestures (Capirci, Iverson, Pizzuto & Volterra,
1996; Woodward, 2009, Crais, Douglas, and Campbell (2004) highlighted the concern
researchers often have over parental report methods, (i.e. through parental diaries) as
the reliability of their interpretations is questioned. Whilst researchers may be trained
to recognise behaviours in infants, parents may find it difficult to recognise “researcher
defined” gestures or their functions, potentially jeopardising the validity of
communicative development research (Woodward, 2009). The difficulty in identifying these
gestures extends to caregivers in the home environment too. Bates et al. (1975, 1979)
highlighted the problem of caregivers misinterpreting these gestures as instrumental acts
or overlooking this action completely. Early pointing studies have already established
that children rely on verbal feedback to determine connections between their pointing
gestures and intentions, and adults who respond promptly, contingently and appropriately
to infant actions tend to improve infants’ subsequent production and comprehension of
words (Colonnesi et al., 2010; Rowe & Goldin-Meadow, 2009). Furthermore, observation of
the responses of others facilitates not only social learning, but enables the
understanding of intentional communication (i.e. awareness of other people’s goals during
interaction) which plays a fundamental role in language development (Elsner, Bakker,
Rohlfing, & Gredebäck, 2014). Theoretically, being able to distinguish these gestures
would provide greater insight into the emergence of intentional communication in pre-
linguistic infants. Towards the end of their first year, infants’ communicative
competencies increase and they begin to use gestures with a number of accompanying
behavioural characteristics, such as systematic hand shapes and vocalisations, to help
more directly express their social intentions. Exploration of these behaviours could
provide insight into the different motives underlying early pre-linguistic gestures. It
would also help determine whether these gestures are fully ambiguous and so interpretable
only from the context of the shared interaction and preceding actions. The difficulty in
pinpointing infant intentions outside of adults’ responses raises the question of whether
infants formulate an intention before they hold out a toy, or if their behaviours are
contingent on the adult’s response. If this were the case, it may be impossible to
distinguish between early showing and giving gestures without relying on caregiver
feedback. If, however, in a typical interactional context, shows and gives involved
distinct behavioural cues (e.g. a particular hand position) it would allow for greater
examination of the role of caregiver responses in forming and developing these gestures
(Bates et al., 1975; Liszkowski, 2005). Identifying and understanding these behavioural
cues is an important step in the understanding of the origins of language and social
cognition in humans. Research on the pointing gesture has managed to overcome the issue of
ambiguity to some extent by providing objective associated micro-behaviours to help study
the development of this gesture in greater detail (Bates et al., 1975; Brooks & Meltzoff,
2008; Cochet & Vauclair, 2010; Gullberg, de Bot, & Volterra, 2008; Krause & Fouts, 1997;
Liszkowski, Carpenter, & Tomasello, 2008; Woodward, 2009). Cochet et al. (2014) used a
frame by frame video analysis to describe the differences between infant’s early pointing
gestures versus reaching. Features such as arm extension, hand-shape and body posture were
all found to demonstrate different functions of infants’ gestures. Arm extension was found
to be greater with pointing gestures, and these were often accompanied by an outstretched
index finger. In contrast, infants leaned further forward when reaching whereas pointing
was characterised by a ‘sitting back’ posture (Lock et al., 1990). A number of other
studies have looked at the impact of vocalisations and gaze alternation on early social
interaction and language development (Franco & Butterworth, 1992; Grünloh & Liszkowski,
2015; Liszkowski & Tomasello, 2011). Infants tend to produce different types of
vocalisations when they are engaged in social interaction compared to when they are alone
(Goldstein, Schwade, Briesch, & Syal, 2010). Furthermore, vocalisations are more likely to
accompany declarative pointing gestures compared to imperative reaching (Grünloh &
Liszkowski, 2014). These differences suggest that declarative, communicative gestures are
more closely interconnected to the vocal system and thus later language development
(Cochet & Vauclair, 2010). The co-occurrence of gaze alternation with a gesture is often
considered evidence of intentional communication (e.g. Cochet & Vauclair, 2010; Franco &
Butterworth, 1996). Previous studies have found that gaze alternations with pointing were
produced more frequently in a declarative context, particularly one that requested
information (Cochet & Vauclair, 2010). All of these micro-behaviours provide a number of
important developmental functions; they are a means of expressing infants’ intentions and
feelings, they help engage a social partner in interaction and allow infants to display
their affective experiences (Bates et al., 1975; Bates, 1979). They also provide
quantitative measures to allow researchers to categorise different gestures and clarify
differences based on various features. To our knowledge, these precise definitions for
coding have not been looked at for early showing and giving gestures. Exploration of the
associated micro-behaviours of showing and giving would allow researchers to examine these
gestures to the same extent as pointing and reaching, and could provide parents with
information to aid in their identification of these early gestures. The current study
addresses this gap in the literature by conducting a fine-grained analysis of these early
communicative gestures in naturally-occurring play, documenting early showing and giving,
their associated micro-behaviours and caregiver responses to these gestures. The study has
two specific research aims: Firstly, to examine whether shows and gives are two distinct
behaviours by documenting associated micro-behaviours. From this we would hope to provide
standardised behaviour codes to help identify and distinguish between these gestures.
Secondly, to examine whether caregiver’s responses are predicted by the patterns of micro-
behaviours associated with infants’ gestures. From this we hope to examine whether
caregivers’ linguistic and non-linguistic responses to infants’ gestures are contingent on
specific infant micro-behaviours displayed when they gesture.

<hs>  Dataset</hs>
  ~~~~~~~

The data from the current study was taken from pre-existing video corpus of pre-linguistic
interaction between infants aged 10–13 months and their caregivers. The data was collected
as part of a larger, longitudinal study on the emergence of proto-declarative gestures
(Cameron-Faulkner et al., 2015).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

24 infants (10 girls: mean age 313 days, range 267–356 days) and their mothers were
recruited from the centre database at the University of Manchester Child Study Centre. All
dyads were monolingual English-speakers from the north-west of the UK with no reported
language delay. Families that participate at our Study Centre typically come from middle
class backgrounds, though demographic information was not collected for the current study.
The mothers were given travel expenses and the children were presented with a book for
their participation.

<hs>  Procedure</hs>
  ~~~~~~~~~

Infants had to attend three monthly sessions which took place within a controlled
environment in a child study lab. Two video cameras were used to capture the body
movements and facial expressions of both the infants and caregivers. Infants engaged in
20–25 min of natural free-play sessions with their caregiver and a selection of age-
appropriate toys (e.g. plastic cups, rattles, blocks, brushes etc.) with a variety of
shapes, sizes and textures, supplied by the experimenter. All toys were picked with the
aim of eliciting a declarative motive (i.e. a motive to share attention and interest)
rather than an imperative. Specifically, all toys could be fully manipulated by the
infants without requiring any assistance from the caregiver. The naturalistic play
sessions were also established to encourage sharing interest in the toys and in terms of
the target object behaviours. Infants and caregivers sat on the floor on a play rug
without other distractions around them. Caregivers were asked to let their infants lead
the play so that the maximum amount of infant initiated behaviours could be elicited.
Sessions were divided into two 10 min phases. During phase 1, the experimenter left the
room and the infant and caregiver were recorded playing together. At the end of phase 1,
the experimenter returned to the room, collected the toys, and replaced them with a
different selection of toys. Phase 2 repeated the social play session but with the new
toys. Infants participated in these sessions once a month for 3 months. Each session was
the same duration and had the same procedure.

        <hss>Gestures</hss>

        All coding was conducting using the video recordings of the original larger study
        (Cameron-Faulkner et al., 2015). For the original study, two trained research
        assistants coded the data for instances of infant showing and giving gestures
        based on the definitions in Table 1, as well as infant reaches and points. The
        coding criteria for shows and gives were broad and did not include any specific
        detail on the more fine-grained aspects of the gestures. The two research
        assistants were blind to the hypotheses of the original study. In addition to
        coding the infant gestures, the research assistants also categorised the
        interactional sequences following each instance of these communicative behaviours
        (i.e. shows, gives, reaches and points) with respect to eye gaze and object
        manipulation or maternal comment. For the current study, the first author began by
        recoding the data using the same broad definitions of show and gives as used in
        the larger study. These codes were then compared with those of the original study.
        We examined whether the current and previous coders identified the same behaviours
        as infant initiated show and give behaviours. Of the 112 instances identified by
        either coder, agreement was k = 0.70 (79%). Behaviours which could not be agreed
        upon were labelled ambiguous and removed from subsequent analyses. Of the 92
        instances of communicative gestures identified by both coders, agreement was k =
        0.76 (87%) for type of gesture (a show vs. a give) indicating good reliability
        between the categorisation of the original coders and the first author. Following
        the initial identification phase we established a coding scheme for the micro-
        behaviours by drawing on existing studies of prelinguistic communicative behaviour
        (see below). For each infant, only the first session to display shows and gives
        was coded, as we were interested in the earliest display of these gestures. The
        type of gesture was categorised using binary codes of 1 for a showing gesture and
        0 for a giving gesture.

        <hss>Micro-behaviours</hss>

        The first author established a coding scheme for potentially relevant micro-
        behaviours. Micro-behaviours were selected based on previous codes used for the
        classification of more established gestures such as points and reaches (e.g.
        Brooks & Meltzoff, 2008; Cochet & Vauclair, 2010; Elsner et al., 2014). Table 2
        displays the micro-behaviours coded for each show and give. The video-recordings
        were then re-examined and the micro-behaviours for each identified communicative
        gesture were coded. The micro-behaviour analysis was conducted on the data after a
        sufficient time lag from the identification phase and in addition the show/give
        categorisation was hidden. Also all show and gives which were identified during
        both the original and current study (as mentioned above) were included in the
        analysis.

            <hss>Vocalisation</hss>

            Vocalisation was scored as a binary code of 1 if the gesture was accompanied
            by vocalisation and 0 if it was not. These codes were then compared to the
            original coding. Agreement for this behaviour with the previous coding was
            good k = 0.73 (84%).

            <hss>Eye gaze</hss>

            Eye gaze was coded as 1 if the infant looked to the caregiver first when
            displaying a gesture and 0 if they primarily looked at the toy. Again these
            codes were compared to the coding from the original study. Coders agreement
            for the location of eye-gaze was k = 0.64 (66%) indicating moderate
            reliability. Similarly gestures that were accompanied by gaze alternation were
            scored as 1 if there was evidence of gaze alternation and 0 if the eye gaze
            was fixed, agreement between coders was again good k = 0.78 (81%).

            <hss>Morphological features</hss>

            Arm positioning was given a code of 1 if the arm was raised and 0 if it was
            straight out/lowered slightly. Body posture was given a code of 1 if the
            infant leaned forward and 0 if they did not move. Hand-orientation was split
            into “inverted” hand-shape (i.e. palm facing downwards) and “upwards” hand-
            shape (i.e. palm facing up or towards the caregiver) as these had been
            suggested in past literature as indicators of infant gives (Elsner et al.,
            2014). Codes which were difficult to define due to camera angles or the
            positioning of the dyads were coded as ambiguous.

        <hss>Caregiver responses</hss>

        Caregiver linguistic and non-linguistic responses to infants’ shows and gives were
        classified. These definitions were based on codes used in the larger study which
        in turn were based on pre-established categories used in the classification of
        caregiver contingent talk and follow-in behaviour towards infant’s gestures
        (Cameron-Faulkner et al., 2015; McGillion et al., 2013; Tomasello & Farrar, 1986).
        Table 3 displays the caregiver responses coded for each show and give gesture.
        These responses were split into ‘show’ responses (look and comment contingently on
        the object) and ‘give’ responses (reaches towards toy and asks for it). Caregiver
        responses were given a score of 1 for a perceived ‘show’ response and 0 if it
        involved for a perceived ‘give’ response. Agreement between coders for caregiver’s
        non-linguistic responses was k = 0.85 ‘Ignore’ responses from the caregivers were
        also coded whenever they failed to respond linguistically and non-linguistically
        to the infants' target gestures.

<hs>  Analysis</hs>
  ~~~~~~~~

To examine whether the observed micro-behaviours were linked to (1) categorisations of
infant gesture type, and (2) caregivers’ interpretations of these gestures, a multiple
correspondence analysis, followed by a mixed-effects logistic regression was performed in
R (R Core Team, 2012). Results are organised as follows. Firstly, descriptive statistics
are presented for the proportion of infant showing and giving behaviours, the associated
behavioural cues and caregiver interpretations of these gestures across the selected
sessions. Secondly, the graphical results of the multiple correspondence analyses are
displayed and described. Finally, the mixed-effects logistic regression is reported for
both infant gesture classification and caregiver response outcomes.

<hs>  Frequencies of shows, gives and associated micro-behaviours</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Overall, 20 participants displayed some form of showing or giving in at least one of their
three sessions. Four participants were excluded due to a lack of shows and gives. There
were a total of 92 episodes of gesturing across all participants. Of these 54% were
classified as shows (n = 50) and 46% were labelled as gives (n = 42). There were instances
of individuals who displayed only shows or only gives in their session. Infants produced
an average of 2.5 shows (range: 0–8) and an average of 2 gives within their sessions
(range: 0–10). Age of first use of gestures was not significantly correlated with overall
number of showing and giving gestures produced (r = −0.1; p = 0.3) nor was it correlated
with the type of gesture produced (r = −0.04; p = 0.7). This suggests that the age of
onset for these gestures within these sessions did not predict the frequency of gestures
or the type of gesture. Vocalisation accompanied just 17% of infants’ gestures whereas
gaze alternation was present with gestures on average 64% of the time. Infant gaze focused
primarily on the caregiver 46% of the time. Regarding the form of the gestures, 35% of
gestures were characterised by the infant leaning forward and 45% of gestures displayed an
‘inverted’ hand-shape compared to a ‘palm up’ hand orientation. Gestures with a raised
arm, as opposed to a straight out position also accompanied 45% of infants’ gestures. Fig.
1 displays the frequencies of the associated behaviours for both infant shows and gives.
When broken down, there were clear differences in the numbers of these behaviours for
infants’ showing vs. giving.

<hs>  Multiple correspondence analysis: associations between gesture categorisations, micro-behaviours and caregiver responses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To visually examine the pattern of relationships of the variables, a Multiple
Correspondence Analysis (MCA) was conducted using the FactoMineR function in R (R Core
Team, 2012). Firstly, we looked at associations between the micro-behaviours and the
researcher classified shows and gives. Fig. 2 displays clusters for the micro-behaviours
and the showing and giving gestures. Two fairly clear clusters of associations are
apparent. In the top left quadrant, the behaviours classified as ‘show’ are highly
associated with a ‘palm up’ hand position and a raised arm. In the bottom right quadrant,
the behaviours classified as ‘give’ are highly associated with a ‘straight arm’ position
and ‘inverted hand’ shape. We then looked at the associations between the micro-behaviours
and caregivers’ responses to infant gestures (see Fig. 3). Again, there are two clusters,
however these are not as distinct compared to the researcher’s classifications of infants’
showing and giving in Fig. 2. In the top left quadrant, both non-linguistic and linguistic
responses classified as ‘show responses’ are clustered near to the ‘palm up’ hand position
and a raised arm. In the bottom right quadrant, both non-linguistic and linguistic
responses classified as ‘give responses’ are clustered near to the ‘straight arm’ position
but actually are most closely associated with the infant’s lack of vocalisations.
Furthermore, although these responses are positioned in the same quadrant as the
researcher’s classifications of shows and gives, they are not as closely associated,
suggesting a level of ambiguity when interpreting these gestures.

<hs>  Regression model 1: behavioural cues and infant gestures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We then carried out two analyses to investigate whether these micro-behaviours
significantly predicted (1) the classification of infants’ gestures and (2) caregivers’
linguistic and non-linguistic responses. Regression models were fitted using the lme4
function in R (Bates, Maechler & Bolker, 2012) with the two outcome variables; gesture
(show vs. give) and caregiver response (show response vs. give response) used in two
separate models. The following predictor variables; ‘vocalisation’, ‘gaze alternation’,
‘eye-gaze to caregiver, “arm raised”, ‘inverted hand-shape’ and ‘lean forward’ were
entered as fixed effects and ‘participants’ and ‘age of first use’ as a random intercept
effects. Overall fit of the model was tested using a likelihood ratio test, comparing the
models with predictor behaviours entered to a baseline model (with no effects of interest)
(Field et al., 2012). Before considering the main predictor variables of interest, we
compared models with and without the random effect of age of first use. The addition of
infant age did not provide a significantly better fit to the data (χ2 (1) = 0.92, p = 0.6)
thus only ‘participant’ was retained to control for differences accounted for by
individuals. Consequently, model 1 included all of the predictor variables to establish if
any of the infant micro-behaviours were significant predictors of the categorisation type
(show/give) assigned to infants’ gestures. Model 1 was then compared to a baseline model
without the predictor variables to assess the fit of the data. Table 4 displays the
coefficients and standard error results for all the micro-behaviours entered into model 1.
The results showed that gaze alternation, infant posture and infant vocalisation were not
significant predictors of the classification of infant gesture. In contrast, the location
of infants’ eye-gaze significantly predicted gesture type classification, as eye-gaze
primarily directed to the caregiver was associated with infant showing gestures.
‘Inverted’ hand-shape was also found to have a significant, negative association with
infant showing, indicating that it was a significant predictor of infant gives. Likewise,
in positioning was found to be a significant predictor of gesture type, as a raised arm
was associated with infant showing. ‘Inverted’ hand-shape was found to have a significant,
negative association with infant showing, indicating that it was a significant predictor
of infant gives. When comparing model 1 to the baseline model, the predictive behaviours
significantly improved the fit of the model (χ2 (9) = 53.0, p < 0.001). This suggests that
there are specific micro-behaviours associated with each global behaviour type.

<hs>  Regression model 2: behavioural cues and caregiver responses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To test whether caregivers’ linguistic and non-linguistic responses to infant gestures
were also predicted by the micro-behaviours present with the infants’ gestures, a further
mixed effects logistic regression was conducted, with caregiver response (show response,
characterised by shared orientation and comment vs. give response, characterised by
reaching for and/or requesting the toy) as the outcome variable. Again, the inclusion of
infant age as a random effect within the model did not provide a significantly better fit
to the data (χ2 (1) = 0.05, p = 0.9) thus only ‘participant’ was retained to control for
differences accounted for by individuals. Model 2 again included the following predictor
variables; ‘vocalisation’, ‘gaze alternation’, ‘eye-gaze location’ (eye-gaze to hearer)
‘arm positioning’ (raised arm), ‘hand orientation’ (inverted hand-shape) and ‘body
posture’ (lean forward) as fixed effects and ‘participants’ as random intercept effects.
Again, fit of the model was obtained by likelihood ratio tests, comparing model 2 (with
the predictors of interest) to a baseline model (with no effects of interest). Table 5
displays the coefficients and standard error results for vocalisation, gaze alternation
and all the other behavioural cues entered into model 2. Like the previous model,
vocalisation, gaze alternation and infants’ posture changes were not significant
predictors of the type of caregiver response to infant gestures. However, infants’ eye-
gaze was also not a significant predictor of caregiver responses. Infants’ hand-
orientation also did not reach statistical significance indicating that infants’ body,
hand-shape, vocal and visual behaviours were not predictors of caregiver’s responses. Arm
positioning was again found to be a significant and indeed the only predictor of caregiver
responses, with a raised arm displaying a significant and positive association with
caregiver’s shared orientation and comment (show response). When comparing model 2 to the
baseline model, the predictive behaviours significantly improved the fit of the model (χ2
(9) = 17.34, p = 0.008). Fig. 4 displays a summary of the variance explained by each
predictor for both infant behaviour classifications (show vs. give) and caregiver
responses (show response vs. give response). Positive values indicate a stronger
association with behaviours classified as shows/caregivers’ shared orientation/commenting
(show responses) whereas negative values imply a greater association with infant
behaviours classified as gives/caregivers’ reach/request (gives responses) behaviour.

<h>DISCUSSION</h>
----------

This study set out to address the gap in the literature concerning infants’ early showing
and giving gestures, by conducting a fine-grained analysis of these gestures and their
associated micro-behaviours. The aims of the study were (1) to investigate both showing
and giving gestures in infants and to characterise them in terms of vocalisation, hand-
shape, arm and body position, eye gaze location and gaze alternation (2) to investigate
the predictive value of these micro-behaviours on caregivers’ responses to infant
gestures. We used naturalistic video-data from a larger study to identify instances of
showing and giving, the associated micro-behaviours and caregiver responses. Our results
suggest a distinction between the micro-behaviours associated with showing and giving
gestures and also a contrast in the predictive value of these behaviours for researcher
classifications of these gestures compared to caregiver responses. Below we discuss some
of the key findings and areas for future study.

<hs>  The type of gesture was not associated with age</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The current findings support the view that from 9 to 10 months, infants begin to use
gestures as a way to communicate and interact with a social partner (Bates, 1979; Cameron-
Faulkner et al., 2015; Cochet & Vauclair, 2010;). Overall, 83% of the infants demonstrated
evidence of self-initiated shows and gives which displayed some evidence of communicative
function (i.e. a motivation to share attentions and interest). Interestingly, the age of
onset for these behaviours did not significantly predict the overall number of shows and
gives observed or the type of gesture produced. A possible explanation for this is that
before 12 months, infants are still learning how their gestures can achieve specific
communicative goals and so do not yet use them consistently within social play (Carpenter
et al., 1998). If this was the case, it is possible that the type of gesture produced at
this stage may be contingent on the caregiver’s response rather than a previously
formulated intention. Indeed, our findings revealed that individual infants often
displayed a tendency to use one type of gesture over the other during the social play
session. The identification of specific micro-behaviours for shows versus gives provides
researchers with the opportunity to analyse the earliest instances of these gesture and
examine how each is shaped by caregiver responses.

<hs>  Vocalisation and gaze alternation were not significant predictors of infant shows or gives, however eye-gaze location was</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Vocalisation only accompanied 17% of infants’ gestures and was not a significant predictor
of gesture type. A possible explanation for this is that the infants in our study were
still quite young to be consistently vocalising as a means of communication. Gros-Louis &
Wu (2012) noted an increase in pointing gestures and vocalisation only after 12 months of
age, and also found that infants produced vocalisations concurrently with gestures to
orient the adults’ attention to the object. In our study, the adults were generally
attentive to the infant throughout the interaction, which may have decreased the need for
vocalisation when the adult was not attending. Further research is required to determine
whether caregiver’s attentional focus dictates the frequency and type of vocalisation with
showing and giving gestures, and to explore the developmental trajectory of this behaviour
into the infants’ second year. Gaze alternation was also not a significant predictor of
showing or giving, although it accompanied a higher proportion of gestures (64%). A
possible explanation for this is that gaze alternation highlights the presence of general
intentional communication rather than acting as a predictor of the type of gesture
displayed. Research consistently highlights the presence of gaze alternation in
conjunction with gestures such as giving, showing, reaching and pointing (Bates et al.,
1975; Cochet & Vauclair, 2010; Gros-Louis, West & King, 2014). However, previous studies
have noted that gaze alternation is often not a reliable predictor of infant communicative
intentions and often can be influenced by the specific contexts in which the child was
recorded (Cameron-Faulkner et al., 2015; Liszkowski & Tomasello, 2011). Clearly, the
relation between the use of eye gaze to direct attention, and its relation to specific
communicative behaviours and developments requires greater clarification, and so the
conclusions we can draw from this behaviour should be interpreted with caution.
Interestingly, although gaze alternation did not significantly predict the type of gesture
used by infants, eye-gaze location did. Infant eye-gaze to the caregiver was associated
with a showing gesture. Previous studies have suggested that early pointing in infants
emerges from a shared practice of looking at things with a social partner (Liszkowski &
Tomasello, 2011). Pointing with communicative intent is generally accompanied by visual
checking, particularly eye gaze to the caregiver, to establish common ground (e.g.
Dimitrova, Moro, & Mohr, 2015; Haynes et al., 2004). The significant association between
eye-gaze to the caregiver and the showing gesture supports the idea that this gesture may
be a precursor to communicative pointing, and reflect a similar motive to share that
interest and attention with others (Liszkowski, Carpenter, Henning, Striano, & Tomasello,
2004; Tomasello et al., 2007). The presence of this behaviour alongside early infant
showing gestures could provide greater insight into the developmental trajectory of pre-
linguistic communication.

<hs>  Arm positioning and hand-shape were significant predictors of infants’ shows and gives</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Differences in arm position were a significant predictor of infant gesture categorisation;
a raised arm was more frequently associated with a showing gesture than a giving gesture.
This is an interesting finding as although arm positioning has been used to define
pointing and reaching gestures (e.g. Franco & Butterworth, 1996) the relationship between
this behaviour and other deictic gestures has yet to be studied in great detail. Another
interesting observation was the significance of hand-shape variability in predicting
infant gesture categorisation; an ‘inverted’ hand-shape was more frequently associated
with a giving gesture. Previous studies suggested that hand-shape variability was a
significant indicator of infants’ motives when pointing at an object or event (e.g. Brooks
& Meltzoff, 2008; Franco & Butterworth, 1996) and a recent study reported that infants as
young as 12 months displayed abilities to differentiate between goal-directed gestures
based on their hand-shape (Elsner et al., 2014). Replication of the current findings (i.e.
that a raised arm is a significant predictor of infant showing gestures whereas an
inverted hand-shape helps predict the likelihood of a giving gesture) could establish
these as salient indicators of shows and gives and aid in their identification in both
research and social situations.

<hs>  Caregiver responses were not contingent on infants’ behaviours, with the exception of arm position</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

From our initial observations, it seemed that caregivers sometimes found it difficult to
understand their infant’s gestures, for example responding to the infants with a question
like “Is that for me?” when the infant held out a toy. This suggests that at this age, the
intent of infants’ emerging gestures is sometimes unclear to the recipient. This
assumption would support the recent finding of Dimitrova et al. (2015) who also found that
the communicative status of prelinguistic gestures was often overlooked or misinterpreted
by caregivers. Our second aim was therefore to investigate whether caregiver responses
were contingent on infants’ micro-behaviours displayed when gesturing. Caregivers
responses were divided into ‘show’ responses (looks and/or comments) and ‘give’ responses
(extends hand and/or asks for toy) to the infants’ gestures (Cameron-Faulkner et al.,
2015). With the exception of arm position, none of the behaviours produced by the infants
significantly predicted the likelihood of particular caregiver responses. Rather than
concluding that these behaviours have little relevance, one possibility is that there are
complex multimodal interactions between the various behavioural cues that influence their
interpretation. For example, it could be that infant vocalisations have particular
significance that is contingent on the presence or absence of shared eye contact with the
caregiver. To examine these more complex interactions, a much larger sample of infant show
and give behaviours would be needed. Although further work is needed to investigate
possible interactions between cues and caregivers’ abilities to utilise this information
to interpret infant gestures, one additional cue was predictive of researcher
categorisations of infant behaviours. Thus, there is still the possibility that the lack
of significant associations between infant micro-behaviours and caregiver responses can be
explained by caregiver failure to utilise all the available behavioural cues produced by
the infant (Cochet & Vauclair, 2010). A number of studies indicate that when an infant
uses clear communicative cues during a joint attention episode, the caregiver provides
more contingent responses overall (Vallotton, 2009). This sharing of information helps the
infant to gain an understanding of their social world and adults who respond contingently
to infant gestures aid in the advancement of their social and language repertoire
(Colonnesi et al., 2010). The current study provides a set of standardised behaviours to
help identify showing and giving gestures not only for research purposes, but to inform
caregivers in the home about the presence of infant behavioural cues during social
interaction. This is a first step in the investigation of caregiver responsiveness to
these early gestures and the potential factors that may influence this contingency.

<h>CONCLUSIONS</h>
-----------

Taken together, the results of this study provide valuable insight into infants’
communicative patterns before 12 months and question the assumption that infant pointing
is the first communicative milestone achieved (Colonnesi et al., 2010; Liszkowski, 2010).
Infants’ showing and giving gestures display evidence of differing behaviours and
demonstrate infants’ ability to initiate these early gestures during triadic play,
engaging the adult in the object of interest. This ability to adapt their behaviours may
reflect earlier instances of communicative intentions, and the emergence of more
sophisticated communicative abilities (Liszkowski, 2010). The research calls for future
studies to explore these gestures and associated behavioural cues using more controlled
experimental methods and longitudinal studies, to further determine their significance as
a window onto infants’ intentional communication and to explore the relationship between
early showing and giving gestures and later language acquisition. Furthermore, the current
findings highlight the need for researchers to focus on a number of features in infant
gesture, including arm positioning, hand shape, and eye-gaze reference when coding
infants’ early shows and gives, in order to fully ascertain the functions of early
communicative gestures. Clear documentation of behavioural cues associated with early
shows and gives may not only aid in parental reports of infants’ gestures, but generally
provide parents with clearer indications of their child’s intentions, potentially reducing
the number of misinterpretations, which could be beneficial to both infant language
development and social interaction (Dunham & Dunham 1992).


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<ART>Exploring the autistic and police perspectives of the custody process through a participative walkthrough
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Authors: Chloe Alice Holloway, Nell Munro, John Jackson, Sophie Phillips, Danielle Ropar
DOI: 10.1016/j.ridd.2019.103545
Year: 2020
ASJC codes: 3203, 3204
Keywords: Access to justice, Autism spectrum conditions, Criminal justice system, Police and Criminal Evidence Act 1984, Police custody, Vulnerable detainees

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<h>ABSTRACT</h>
--------

Background: Research suggests that autistic individuals may be more likely to come into contact with police and have more negative experiences in police custody. However, limited information about the difficulties they experience during the custody process is available. Aims: This study explores the experiences of autistic individuals and officers during a walkthrough of the custody process to identify specific difficulties in these encounters and what support is needed to overcome these. Methods and procedures: A participative walkthrough method was developed to provide autistic individuals and officers an interactive opportunity to identify areas where further support in the custody process was needed. Two autistic participants and three officers took part in the study. Outcomes and results: Autistic participants reported negative experiences due to: i) the emotional impact of the physical setting and custody process ii) communication barriers leading to increased anxiety and iii) exposure to sensory demands. Officers highlighted three factors which limit their ability to support autistic individuals effectively: i) the custody context ii) barriers to communication and iii) knowledge and understanding of autism. Conclusions and implications: Adjustments are needed to the custody process and environment to support interactions between autistic individuals and officers and improve the overall wellbeing of autistic individuals.

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<h>WHAT THIS PAPER ADDS?</h>
---------------------

There has been little in-depth research into the lived experiences of autistic individuals
throughout the custody process. Previous research has not explored the difficulties which
autistic individuals might experience at specific points of the custody process or what
adjustments might support the interactions between autistic individuals and officers to
improve overall wellbeing. This study is one of the first to examine the experiences of
autistic individuals during the custody process. A novel walkthrough technique using a
combination of qualitative methods was employed to gain an insight into police and
autistic interactions and experiences of the custody process. It builds upon the evidence
that autistic individuals have negative experiences in police custody by identifying
specific parts of the custody process that create difficulties for autistic detainees. The
research also further explores the factors which may affect the ability of officers to
support autistic detainees effectively.

<h>INTRODUCTION</h>
------------

Research suggests that autistic individuals are more likely to come into contact with
police than the general population (Debbaudt & Rothman, 2001). For example, Tint, Palucka,
Bradley, Weiss, & Lunsky (2017) reported that 16 % of 284 autistic participants had
experienced police contact over a 12–18 month period (Tint et al., 2017). Some studies
have suggested that this could be due to autistic individuals being more likely to commit
a criminal offence or engage in certain types of criminal behaviour (see Allely & Creaby-
Attwood, 2016 for discussion). However, other studies have disputed this, reporting that
autistic individuals are in fact no more likely than the general population to commit an
offence (see King & Murphy, 2014 for review). Alternative explanations for the increased
risk of autistic individuals coming into contact with police have been reported by other
studies. For instance, it has been suggested that autistic individuals are at greater risk
of being victims of a crime (Brown-Lavoie, Viecili, & Weiss, 2014). In addition, another
study has also reported that autistic individuals may be at greater risk of their
behaviour being misinterpreted by police, resulting in an increased likelihood that they
may be arrested for a criminal offence (Dickie, Reveley, & Dorrity, 2018). Police custody
plays an integral role in the criminal justice system in responding to and dealing with
individuals who have been arrested in connection with offending behaviour. In England and
Wales, when an individual has been arrested by a police officer on reasonable suspicion
that they have committed, are committing, or about to commit a criminal offence, they may
be brought to police custody (see s 24 Police and Criminal Evidence Act 1984 ('PACE'))
until a decision is made about whether they are to be charged with the offence. A suspect
may be detained in police custody for up to 24 hours without charge for the purposes of
investigating the offence (see s 37(1) and s 41 PACE). Many decisions made in the custody
context can influence the personal and legal outcomes of individuals. For instance, the
detainee can decide to exercise the right to legal representation or the right to silence,
or they may choose to admit guilt and/or accept a police caution. The custody officer
oversees many of these decisions as they are responsible for ensuring detainees are
treated according to the main legislative safeguards (see s 39(1)(a) PACE). In particular,
the custody officer is responsible for informing detainees of their rights and ensuring
the welfare of individuals whilst in custody. To some extent, all individuals will
experience difficulties in police custody as suspects will be subject to a series of
intrusive processes including booking-in, fingerprinting, DNA swabbing, drugs testing and
police interview (see Skinns, 2011 for discussion). They may also be detained in a cell
for a significant period of time while the investigation takes place and they may
experience a loss of privacy, isolation and a loss of control (see Skinns, 2011 for
discussion). This can sometimes result in adverse outcomes (see Skinns, 2011 for
discussion). However, the addition of sensory and communication differences in autism may
exacerbate the impact of these factors further, making them more vulnerable to adverse
outcomes (Chown, 2010; Crane, Maras, Hawken, Mulcahy, & Memon, 2016; Woodbury-Smith &
Dien, 2014). Specifically, if important legal information is not conveyed in an accessible
way, this could lead to autistic detainees making ill-informed decisions in custody. In
addition, barriers to communication between neurotypical and autistic individuals may
prevent adjustments to the custody process or environment from being made which could
further impact negatively on their welfare. Despite the increased likelihood of coming
into contact with the criminal justice system, police officers and other criminal justice
professionals report feeling ill-equipped to adequately support autistic individuals
(Crane et al., 2016; Dickie et al., 2018). But few studies have explored autistic
individuals’ experiences in the system. Working in partnership with autistic individuals
to gain their views on how to enhance service provision (Robertson, 2010), and to ensure
research is both meaningful and valuable to the autistic community (Fletcher-Watson et
al., 2019) can lead to better translation of the research findings to real-world settings,
improving outcomes for autistic individuals. Of the few studies that have explored the
criminal justice system from an autistic perspective, all report that autistic individuals
have negative experiences in police custody and are generally dissatisfied with their
interactions with police (Allen et al., 2008; Crane et al., 2016; Helverschou, Steindal,
Nøttestad, & Howlin, 2018). As part of a larger study into the prevalence of offending
behaviour among autistic individuals in South Wales, Allen et al. (2008) conducted
interviews with six autistic individuals who had experience of the criminal justice
system. They documented several difficulties including “not being able to take everything
in; feeling in the spotlight; not knowing what was going to happen next, and feeling
uncomfortable with the other people at the police station ...” (Allen et al., 2008: 754).
Following an online survey of both police officers (n = 394), autistic individuals (n =
31) and their families (n = 49) in England and Wales, Crane et al. (2016) also reported
that autistic individuals experienced emotional stress and breakdowns in communication in
custody. In part, this was attributable to the inappropriateness of the physical setting
of the interview room and custody suite and a lack of appropriate support. This study also
found that some autistic individuals may not disclose their diagnosis due to a fear of
being victimized or discriminated against. Helverschou et al. (2018) interviewed nine
autistic individuals who had been convicted of a criminal offence. Although the majority
of the research focused on reasons underlying the offending behaviour and experience in
prison in Norway, some questions touched on their experiences during the custody process.
While the processes in Norway may be different to England and Wales, it is interesting
that the individuals reported similar negative experiences to those reported by
participants in the UK. Specifically, they reported being confused about the reasons for
their arrest or concerns about the lack of a legal representative that understood them.
While these studies provide evidence for the need of greater support for autistic
individuals within the criminal justice system, there are some limitations to the
methodological approaches used. Interviews and surveys conducted after a period of time
has passed may fail to capture important details about specific parts of police procedures
that are significant barriers to participation in the criminal justice system. The sample
of participants who complete online surveys may also not fully reflect the broader range
of experiences as they may be disproportionately completed by those who are most
dissatisfied by their experiences. Furthermore, these studies explored autistic
experiences of the criminal justice system more broadly. They did not ask participants to
reflect on specific aspects of the custody process or identify what support may be
required to allow them to participate effectively. To address this, the current research
will investigate the custody process to gain detailed information about potential changes
that could make the process more accessible for autistic individuals. Crane et al. (2016)
suggested it would be valuable to carry out direct observations of how police procedures
are conducted with autistic individuals. This would allow the researcher to note specific
areas of difficulty and when they occur, which might be missed in subsequent interviews
with participants. This approach has further value in that it would allow researchers to
obtain perspectives from both autistic individuals and the officers interacting with them.
This allows us to address the double empathy problem (Milton, 2012; Milton, Heasman, &
Sheppard, 2018; Sheppard, Pillai, Wong, Ropar, & Mitchell, 2016) which argues that
breakdowns in communication are a two-way process. Specifically, just as neurotypical
individuals may struggle to understand the intentions of non-autistic people, difficulties
may also stem from an inability of neurotypical individuals to infer what autistic
individuals are thinking (Sheppard et al., 2016). Therefore, it was the aim of this
research to carry out a participative walkthrough which used a combination of direct
observation and interview techniques to identify barriers that might affect an autistic
individual’s participation in the custody process. Two autistic individuals and three
officers took part in the study. The objectives were to: i) identify specific points in
the custody process where adaptations are needed, ii) assess how autism impacts upon the
custody process, and iii) identify recommendations for changes to the custody
process/environment that would improve the experiences of autistic individuals.

<hs>  Participative walkthrough</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Due to the practical, ethical and legal limitations associated with carrying out an
observation of autistic individuals detained in police custody (see Demarée, Verwee, &
Enhus, 2013), it was considered more appropriate to simulate this process using a
walkthrough method. The participative walkthrough is an experimental method adopted for
the purposes of this research. It builds on the basic principles of the ‘go-along’ method
which is typically used by researchers to learn more about a neighbourhood or place, or
experimentally, to explore new and unfamiliar situations (Carpiano, 2009; Kusenbach,
2003). This method combines two different qualitative methods: field observation and
interviewing (Carpiano, 2009). During observations, people do not usually provide a verbal
commentary on their activity, making it difficult to access their concurrent experiences
and interpretations (Kusenbach, 2003). Similarly, interviews keep informants from engaging
in their usual activities in the environments where they naturally occur meaning important
aspects of that lived experience may be overlooked (Kusenbach, 2003). In contrast, by
using a go-along approach researchers can observe an individual’s responses in context and
simultaneously access their experiences at a specific time or location (Kusenbach, 2003).
Researchers are therefore able to explore the informant’s experiences, interpretations,
and practices using a combined approach of asking questions and observation (Carpiano,
2009). The participative walkthrough goes beyond the traditional ‘go-along’ to recreate an
interactive process. This study was designed to provide officers and autistic individuals
the opportunity to actively engage in the custody process and with each other, rather than
simply being passive observers to what would take place in custody. Another layer was
added by the researchers who observed the walkthroughs assessing the participants’
behavioural and emotional responses. These observations also helped guide the subsequent
interviews and provide additional context to themes identified in the data, allowing the
researchers to identify points to discuss in the interview and verify the accuracy of what
was reported. The researcher also served a supportive role for the walkthrough and was
there to guide the process and intervene, if needed.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Ethical approval for the study was granted by the ethics committee at the School of Law,
University of Nottingham. Autistic participants were recruited on the basis they: i) were
resident in the UK, ii) were over the age of 18, iii) had a diagnosis of an Autism
Spectrum Condition (including Asperger’s Syndrome), iv) did not have previous experience
of being detained in police custody, and v) had sufficient communication skills to take
part in the research. Two autistic individuals, one female aged 24 (referred to as Anne)
and one male aged 33 (referred to as Ben), took part. Both were British nationals with
English as their first language. One participant lived independently and both had
educational attainment through to University level. Nottinghamshire police were the focus
of the study because of their proximity to the University and interest in developing their
vulnerability strategy further. One custody sergeant and two detention officers were
recruited via internal email sent by the custody and development officer to assist with
the walkthrough. The officers were not required to have any training or experience of
autism, although one reported having personal experience of interacting with autistic
individuals outside custody. Informed consent was obtained from all participants prior to
the study.

<hs>  Procedure</hs>
  ~~~~~~~~~

The walkthrough focused on three parts of the custody process: i) booking-in ii)
processing and iii) cell detention. The walkthrough was carried out in an operating police
station on an overflow floor which was not currently in use. Two walkthroughs were
conducted. The walkthroughs lasted 51 and 53 min, respectively. These were audio recorded
with the consent of participants. Two officers, the autistic participant and CH were
present during each walkthrough. DR was also present during one walkthrough to provide
additional support to the autistic participant. CH took notes on the quality of
interactions between individuals (i.e. ease of communication), and recorded any visual
emotional and behavioural cues (e.g. self-stimulatory behaviour) showed by the
participants in response to what was happening, and provided support to both participants
throughout the process. Prior to the walkthrough, participants read an information sheet
and consent form which they signed and returned to the researcher. They were also given an
overview of what would happen during the study and informed that each process was
optional. Consent was verbally confirmed at each stage. Participants were allocated a
scenario to contextualise the study (theft or criminal damage) which was explained to
them.

        <hss>Booking-in</hss>

        Each autistic participant was asked to answer a series of background questions set
        out by standard police procedures. The officers answered any queries raised by the
        participants and explained the purpose of the booking-in process. Participants
        were then asked to undergo a personal search. The officers explained what would
        happen and showed them the items used in this process. Where the participants
        consented, the search was then carried out by an officer of the same gender.

        <hss>Processing</hss>

        The autistic participant was then taken to the processing room located in an
        operating part of the station. No other detainees were present at this time. The
        different processing procedures were explained accordingly: i) UV Smartwater test,
        ii) fingerprinting, iii) DNA test, iv) drug test and v) photographs. The custody
        sergeant also explained what safeguards would be in place and any legal
        implications. The officers simulated the Smartwater test, fingerprinting and
        photographs where the participant consented.

        <hss>Cell detention</hss>

        Finally, the autistic participant was taken to look around a holding cell,
        interview room and shower room. They were specifically asked to talk about how
        they felt about the cell. The officers demonstrated how the intercom in the cell
        operated, what it would be like if the door was closed and what would happen
        during a routine check.

        <hss>Interviews</hss>

        The participant interviews were semi-structured and conducted following an
        interview schedule to allow for consistency between individuals. All interviews
        were audio recorded and notes were taken throughout. DR conducted interviews with
        each autistic participant. One interview lasted 47 min and the other was 64 min
        long. Questions were divided into sections: i) overall study ii) booking-in iii)
        processing iv) cell detention and v) final comments. All questions were open-ended
        asking the participants to describe their experiences of each process and identify
        any difficulties with or ways of improving these processes (see Appendix A). CH
        also carried out a joint interview with the custody sergeant and one detention
        officer. The other detention officer was unavailable for interview after the
        study. The interview was 25 min long. General open-ended questions were asked
        about the officers’ experiences of taking part in the study and interacting with
        the autistic participants (see Appendix B). Upon completion, all participants were
        de-briefed and invited to discuss any concerns. Researchers maintained contact
        with the participants for a limited time after the study to check if they had
        further questions and ensure they were not experiencing any negative consequences
        from their participation.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

The walkthrough and interviews were transcribed in full and analysed by CH using a
combination of inductive and deductive approaches to thematic analysis (Braun & Clarke,
2006). This allowed the researchers to identify themes relating specifically to the
officers or autistic participants and better compare their perspectives. Initially an
inductive approach was taken due to the novelty of the walkthrough method and the
exploratory nature of the research questions, which allowed us to code directly from the
data to reflect the actual experiences of the participants. Each transcript was read line
by line and colour coded according to identify specific themes. These initial codes were
then reviewed, adapted and categorised into overall themes to better describe what was
happening in the data. The second stage of analysis involved a more deductive approach as
the transcripts and field notes were considered alongside each other to compare the
experiences of the participants and allow the researcher to draw inferences from the data
that were not explicitly articulated. Specifically, we drew upon the theoretical construct
of “double empathy” (Milton, 2012; Milton et al., 2018) to help us better frame
relationships between the data. To verify the accuracy of the final analysis, the data was
subsequently reviewed and interpreted independently by NM and DR. A few discrepancies were
resolved prior to the identification of final themes.

<hs>  Autistic perspective</hs>
  ~~~~~~~~~~~~~~~~~~~~

Three core themes were identified: i) impact of the custody environment ii) the
contribution of communication difficulties to anxiety and iii) impact of sensory
sensitivities on autistic individuals’ experiences in custody (see Table 1 for summary).

<hs>  Impact of the custody environment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Both participants were concerned about what it would be like to be detained longer in
police custody. This was linked with the physical surroundings and the emotional impact of
experiencing the custody process.

            <hss>Unfamiliarity</hss>

            The unfamiliarity of the custody environment was a concern: “(…) it’s mainly
            the novelty of the environment - the unfamiliarity of it” (Ben interview).
            This was partially attributable to the fact it was the participants first time
            in police custody.

            <hss>Small spaces</hss>

            The lack of space was also identified as a potential difficulty: “very
            claustrophobic” (Anne interview). Ben shared concerns about the small space
            particularly over a longer period of time with nothing to do: “I think if I
            was in there for a whole day… I think I’d be very claustrophobic… (…) I
            wouldn’t have been doing much constructive activity. (…) I’m worried about
            perhaps the space to move (…) perhaps, the exercising (..” (Ben interview).
            These concerns extended to the interview room: “a bit… boxy, a bit dingy in
            places, a bit (…) claustrophobic” (Ben walkthrough). Conversely, the
            processing room was viewed more positively: “(…) was quite spacious and I’m
            thinking that others might be tighter, so that helped in there (..” (Ben
            interview).

            <hss>Sleep</hss>

            The custody environment was also connected to the potential inability to
            sleep. This was due to the lighting in the cell which is always turned-on:
            “This doesn’t get any darker at night. This is what it’d be like at 2 a.m.”
            (Ben walkthrough). It was suggested this would cause difficulties sleeping
            which, combined with having nothing to do, would heighten the impact of
            detention: “if I’d been in here for… what, let’s say, a few hours… I think I’d
            probably start getting bored (…)” (Ben walkthrough).

            <hss>Privacy</hss>

            Both participants also discussed potential difficulties created by the lack of
            privacy in custody. The open toilet was a key issue: “(…) the toilets I think,
            I find most intimidating!” (Ben walkthrough). Both participants stressed they
            would not have used the toilet unless they were “desperate” (Ben interview).
            This was because they thought they would be visible on the CCTV camera. But
            this is not always the case: “(…) it’s not constantly being watched - but it’s
            constantly being filmed in case something happens and the toilet areas greyed
            out, so you can’t see people on the toilet.” (Anne walkthrough).

            <hss>Feeling overwhelmed</hss>

            Both autistic participants highlighted the emotional impact detention would
            have had on them if they had actually been taken into custody: “I think what
            realistically [would] happen is… probably start stimmi..”, “(…) hand flapping
            and things” (Anne interview). Anne reported how this would have been “[a] way
            of copi..” with detention, “trying to (…) calm the autism down..” (Anne
            interview).

            <hss>Concern about long-term consequences</hss>

            The long-term emotional impact was also discussed: “I’d probably felt self-
            destroyed, perhaps cause, you know, what could be the consequences of an
            arrest? (…) particularly if I was to lose my job as a result. And… if I was to
            go from being… doing well to, perhaps years of being unemployed (…) and I
            think I’d be very anxious - would I be worse off afterwards?” (Ben interview).

            <hss>Understanding of custody staff</hss>

            It was stressed that the manner and response of custody staff can help to
            minimise the emotional impact of custody: “(…) I felt a lot easier about it
            than I initially thought… and, the officers who we, dealt with today, were…
            very… understanding, (…) overall, I didn’t feel overly intimidated, but (…)
            specific points (…) could have been a little bit… intimidating.” (Ben
            interview). Importantly, it was suggested knowledge of autism was crucial:
            “(…) although they… seemed to… uh, try to be understanding they actually…
            appeared to have not that much knowledge. And so… probably being under more
            stress… if you were (…) in custody for real. (…) it (…) might be even harder
            to… feel comfortable to tell them, like, what was wrong. And especially some
            of the questions, which were key” (Anne interview).

<hs>  The contribution of communication difficulties to anxiety</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Both participants reported feeling less anxious when the officers explained what was
happening as it helped them understand the custody process. In contrast, they reported
feeling anxious when this was not fully explained, or the language was not clear.

        <hss>The need for more information about police procedures</hss>

        Not knowing what was going to happen was a key source of anxiety. This was
        illustrated during the walkthrough when the Smartwater test was conducted by
        switching off the normal lighting and turning on the ultraviolet light. It was
        observed by the researcher that the “sudden change startled [Anne]” (Field notes).
        This was because the detention officer did not explain what they were doing: “(…)
        I didn’t know what - was gonna happen. (…) all they said was ‘Stick your hands
        out’ (…) I didn’t know if they were gonna suddenly search me or what.” (Anne
        interview). It was mentioned that in some situations this might cause some
        autistic individuals to “lash out at someone” (Anne interview). Anne emphasised
        that it helped when the officers provided a context for what was happening by
        explaining what they were going to do and why they had to do each thing. Ben
        concurred that this helped reduce his anxiety: “(…) it just removed some of the
        fear about it. You know, when you know what’s actually being done… you don’t have
        the anxiety about something that’s… impending that isn’t.” (Ben interview). Anne
        also felt it might help to be kept informed about what is happening later on in
        the process and receive regularly updates of any changes if they were detained for
        longer periods of time. Ben agreed that additional information about what might
        happen would be useful: “I think the foresight of what would happen next and
        possibly when it’s likely to happen… (…), step-by-step what’s likely to happen and
        (…) if you’re charged, what happens if you’re not charged and um… you know, …
        perhaps explaining some of the (professionals) roles – you know have some
        literature, because reading material’s always good.” (Ben interview). It was also
        suggested that more accessible forms of information should be provided. For
        example, “visual prompts of what was gonna happen” or “a visual timetable” (Anne
        interview) and a booklet outlining the custody process.

            <hss>Ambiguous questions</hss>

            The autistic participants often found it difficult to understand some of the
            questions asked by the police officers. Open and ambiguous questions played an
            integral part of this. For example, it was noted by the observer that when
            Anne was asked “Where do you live?” in the booking-in stage, she only gave the
            name of the city where she lived. When further prompted by the officer with
            “Where in (city name)?”, Anne only gave the specific area rather than the
            address. Anne commented in interview “(…) they asked me (…) where I lived. (…)
            they could’ve easily just said ‘What’s your address? ’” (Anne interview).
            There was further evidence that the phrasing of other questions during the
            booking-in led to a failure to disclose important medical information or
            clinical diagnoses. For instance, when Ben was asked “do you have any injury
            or illness currently?” he did not disclose a medical condition due to the
            wording of the question. This was only picked up several questions later when
            he was asked about whether he was taking any current medication (Field notes).
            Both participants also reported that they found it difficult to know when it
            was appropriate to disclose they were autistic: “I wouldn’t have mentioned
            autism… (…) Had they not already known” (Anne interview). This was because
            there was no direct question on autism, only questions asking “do you suffer
            from any mental health problems or depression?” and “do you have any learning
            disabilities that we need to provide any help or support for?”. The phrasing
            of questions was also mentioned in relation to asking for food and drink. It
            was explained that standard protocol is to regularly check on the detainee in
            the cell to check they are okay. Anne stressed that: (…) ‘Are you okay?’ could
            be answered in general … I just say yes.” (Anne interview). She further
            commented in interview: “I think, being asked specifically if you want a drink
            or food [would help] … ‘cause it’s something I find difficult to ask for (…)
            in a strange situation” (Anne interview). It was suggested communication
            between the autistic individuals and officers could be better supported by
            making “open questions effectively into closed questions” (Anne interview).
            Prompt sheets would also have helped: “could have had like, prompt sheets (…)
            so when they say ‘How does autism affect you?’, be able to say (…) things that
            are quite common”; “like lighting, sound. “(Anne interview). This would make
            it easier for autistic individuals to communicate what specific support they
            might need and minimise the risk that they may not disclose this information.

            <hss>Legal jargon</hss>

            Technical language (i.e. solicitor) caused additional confusion. This was a
            specific concern for Anne: “added some anxiety because… (…) I had to re-ask…
            what it was”; “they didn’t seem to understand (…) why I didn’t understand”
            (Anne interview). It was observed that this encouraged her to waive her legal
            rights during the study (Field notes).

            <hss>Communicating in the cell</hss>

            There were also concerns about using the intercom to contact the officers: “I
            wouldn’t feel comfortable using it. ‘cause it’s like a phone… I don’t like
            phones...”;“‘cause you can’t see who you’re talking to. (…) it’s like the
            anxiety of waiting for someone to pick up”; “there’s no body language, (…) you
            have to rely on… words..”, “you can’t sign or anything” (Anne interview).

<hs>  The impact of sensory sensitivities on autistic individuals’ experiences in custody</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Several aspects of the custody environment were identified as creating sensory
difficulties.

        <hss>Noise</hss>

        As the study was conducted on a quieter floor, there was minimal background noise.
        However, Ben commented on how he would have felt if the walkthrough had been
        conducted in busier surroundings: “(…) there wasn’t a lot of noise there, but if
        there was… if there was lots clattering, lots of loud noises, it could have been
        quite difficult.” (Ben interview). Anne also reported hearing “buzzing” coming
        from the lights and described the cell as “quite echoey” (Anne interview). She
        emphasised these noises would have been difficult to cope with: “you’re already
        anxious going in. And I would say all of those, sort of, aspects are heightened…
        and so it’s harder to deal with them”; “you can’t block them out as easily.” (Anne
        interview). To minimise exposure to noise, it was suggested that it would be
        better to use a quieter part of the station, if possible (Ben interview).
        Alternatively, it was thought that people might benefit from “ear-muffs” or ear
        defenders (Ben interview).

        <hss>Visual</hss>

        A potential source of visual sensory stress was the artificial lighting: ““it
        could throw a few (…) sensory issues after prolonged exposure” (Ben interview).
        Being able to dim the lighting would have minimised the impact of this. It was
        also suggested that the lighting should be replaced with “softer lights” or
        “different colours of lighting” (Ben interview). Colour was also a concern: “a lot
        of people with autism can be colour sensitive as well - so certain colours.” (Ben
        interview). Duller colours were preferred: “(…) you wouldn’t want a cell to be red
        for instance… because that could, you know, make people… quite angry? (…)” (Ben
        interview) In addition, it was felt that “softer floor colours” and “more matt”
        paint would be less demanding (Ben interview).

        <hss>Tactile</hss>

        Lastly, Anne and Ben referred to the tactile demands of the custody process.
        During the study, Ben took part in the search, fingerprinting and photographs.
        While the search did not create problems at the time, in different circumstances
        this could have raised sensory issues: “(…) if it wasn’t in a such a consensual
        nature it would have felt a little bit intrusive.” (Ben interview). In contrast,
        Anne opted for a description of this process because she was concerned about the
        sensory demands involved. Tactile demands were perhaps most evident during the
        processing stage for both participants who raised concerns about the invasiveness
        of the procedure. For example, they referred to the forcefulness of the
        fingerprinting: “(…) in a busy situation I’d imagine it might have been slightly
        more forceful, which might have been more irritating. (…)” (Ben interview). This
        was amplified by the fact that “they said that they could do it against your will
        (…) Feel sort of forced to do it.” (Anne interview). The DNA swab would raise
        similar issues: “Very uncomfortable. Having stuff in my mouth that I don’t want.”
        (Anne interview). It was noted that a further concern was having to wear different
        fabrics for the photographs, as this may be a “potential sensory trigger” (Field
        notes).

        <hss>Officer perspective</hss>

        Three main themes were identified in relation to how officers perceived and
        experienced the walkthrough process with autistic detainees: i) the custody
        context ii) barriers to communication and iii) training and experience (see Table
        2). These factors also affected the identification of autistic individuals in
        police custody.

<hs>  Restrictions of the custody context</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The custody sergeant and detention officer described the demands of the custody
environment and their role in custody.

        <hss>Time pressure</hss>

        The officers identified competing pressures in their day to day roles which could
        prevent them from spending more time with detainees than they would wish: “(…)
        some - like me - need to spend more time with some people as opposed to others.
        (…) ‘cause of custody and the beast that it is (…) the fact that we may want to
        spend some time with this particular person, but because, this other person’s come
        in and caused – (…) a bit of a rucus, it - it causes no end of problems. (.. ″
        (Officer interview). The need to process detainees quickly especially during
        busier periods was also a factor: “it’s a time thing isn’t it as well? (…) It’s
        bang, bang, bang, bang, the next person. (…)” (Officer interview).

        <hss>Lack of alternatives to custody</hss>

        Another factor which influenced their ability to respond to autistic detainees was
        the limited alternatives to detention: “Doing this job of criminalising people
        when we don’t need to. Arresting them and being in custody when they don’t need to
        be here. And especially if it causes - like, I could see with [Ben] it was causing
        him that much hassle and grief (…)” (Officer interview). While the custody
        sergeant referred to the possibility of diversion, he described how this occurred
        at the end of the process. He also emphasised how it was important for arresting
        officers to consider the necessity of bringing individuals to custody in the first
        place.

        <hss>The impact of custody design on detention processes</hss>

        Finally, the custody environment itself was considered to play a role in the way
        officers were able to respond to detainees. In particular, the lack of privacy was
        highlighted as a factor that might discourage detainees from sharing important
        medical information: “(…) it’s difficult. ‘cause sometimes a lot of people hide
        things. Er, and a lot of people do not want to tell you (…) it’s not very private
        is it? (…)” (Officer interview).

<hs>  Barriers to communication</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Communication between the custody staff and the autistic participants was difficult for
both parties, not only for Anne and Ben: “(…) it was harder with [Anne] than it was with
[Ben]. (…) much harder to get the answers and responses from her (…) I’ve booked a couple
of people in who’ve, um, said they’re on the autistic spectrum – (…) and normally get more
interaction with them (…) So it’s quite difficult… (…) I’d ask them… um… what affects
them, and… how do you feel, and how can I make your stay better – (…) and they normally
tell us (…)” (Officer interview) One key barrier to communication was the question
structure, particularly with regard to disclosure. This is because there is no flexibility
to adjust what is asked according to the needs of the detainee: “(…) all our questions,
everything that I went over, are pre-set.” (Officer interview). In particular, the custody
sergeant suggested it would help them if there was a set question about autism in the
system: “it’s probably be better if it was a set question, because it does depend how you
ask the question. (…) ‘cause [Ben] presents very well. (…) unless he told you, you
wouldn’t think (…) - there was any issue at all? (…) ‘Do you require any help with reading
or writing? Or have any learning disabilities the police can provide help or support
with?’, I don’t know whether that’s enough (..” (Officer interview)

<hs>  Knowledge and understanding of autism</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It was suggested that the response of officers was also influenced by their knowledge and
understanding of autism. This was linked to two factors - prior experience with autistic
individuals and training.

        <hss>Prior experience</hss>

        Having personal experience with autistic individuals was thought to influence
        officers’ responses to autistic detainees: “(…) I only ask certain questions
        [beyond the pre-set questions] because of my life experiences (…) if I’d not had
        that experience, I wouldn’t ask certain questions. (…) Or I wouldn’t be prepared
        to treat them any different (…)” (Officer interview). It was also observed that
        prior experience with autistic detainees in their role may improve their
        responses. During the walkthrough, it was noted that the officers may have adapted
        their interactions with Ben (the second participant) according to what they
        learned with Anne (Field notes). In contrast, their overfamiliarity with the role
        may prevent them from understanding an individual’s needs: “I think sometimes we
        take it for granted (…) the experiences of people coming to custody - especially
        when they’re brand new. (…) we don’t quite understand their anxieties. (…) ‘cause
        (…) we see people coming in all the time. (…)” (Officer interview).

        <hss>Training</hss>

        It was also implied that the training they receive may play a role. However, they
        referred to a lack of specific autism training: “We do get a little bit but (…) in
        email form, really. (…) we do have training - training is good [but] … it’s more
        mental health based (…)” (Officer interview). The custody officer suggested
        providing specific information to help them support autistic detainees better,
        such as “quick [reference] cards” (Officer interview).

<h>DISCUSSION</h>
----------

This study was conducted to learn more about the experiences of autistic individuals and
the officers interacting with them during the custody process. It aimed to identify
potential barriers that might prevent autistic individuals from participating in the
custody process and limit the ability of custody staff to support them. The data from the
autistic participants showed three overarching themes: i) impact of the custody
environment ii) the contribution of communication difficulties to anxiety and iii) impact
of sensory sensitivities on autistic individuals’ experiences in custody. These themes
partly overlapped with those from the officer data: i) restrictions of the custody context
ii) barriers to communication and iii) knowledge and understanding of autism. However, the
reasons underlying some of the common themes were different. This reflects the differing
perspectives of the autistic individuals and the officers who participated in the
walkthrough, illustrating how a “double empathy” problem (Milton, 2012; Milton et al.,
2018; Sheppard et al., 2016) may present itself in a real-world context.

<hs>  Custody environment/context</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

A key issue identified from the data was how the custody environment impacted upon the
well-being of the autistic participants. The physical layout of the custody suite
increased anxiety due to its unfamiliarity, small/closed-off spaces, bright lights and
lack of privacy. Interestingly, lack of privacy was also mentioned in the officer
interview but in relation to disclosure of personal information, rather than the impact on
detainee wellbeing. The emotional impact of the custody environment, although lessened by
the conditions of the walkthrough, was clearly explained as a concern by the autistic
participants. Feeling overwhelmed and worried about the consequences of arrest (e.g.
losing job) were all highlighted as emotions they would feel quite intensely if they were
taken into custody as a suspect. These findings are similar to those made by Skinns’
research which discussed the general experiences of non-autistic suspects in police
custody (Skinns, 2011). However, the additional sensory sensitivities and communication
barriers autistic individuals face are likely to amplify the intensity of these issues,
making the custody environment particularly challenging. The officers highlighted other
issues relating to the custody context which they felt restricted their ability to better
support autistic individuals in custody. Specifically, time constraints and the lack of
available alternatives to detention. These findings are consistent with Crane et al.’s
(2016) study which surveyed a large number of police officers and highlighted time
pressure and frustration in relation to other legislative restrictions. This emphasises
the organisational and procedural constraints operating within police environments and
suggests there may be a need for higher level organisational or policy changes.

<hs>  Communication / anxiety</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Communication was perhaps the strongest theme. For the officers, the primary concern was
their ability to obtain sufficient information from autistic individuals to help support
them. However, the data suggests that the reliance on gathering this information solely
through verbal exchange can be a substantial barrier to communication. The key issue for
autistic participants was the ambiguity or vagueness of the questions which had
implications for disclosure of important medical information or their autism diagnosis.
Both the officers and the autistic individuals felt the pre-set questions did not
adequately allow individuals to disclose their autism. This was due to the autistic
individuals not considering their diagnosis to be an illness, injury, medical condition,
learning disability, or mental health condition. While some autistic individuals may have
associated learning difficulties (Emerson & Baines, 2010) or mental health conditions (Lai
et al., 2019), autism is not classified as either. Furthermore, there has been a movement
away from a medical model of autism towards the social model, specifically with regard to
understanding autism as another layer of diversity within society (Robertson, 2010). The
concept of neurodiversity has gained popularity among some autistic individuals who feel
that autism is a part of their identity (see den Houting, 2019 for discussion). This
indicates a risk that some autistic individuals may not be identified in police custody.
Therefore, the issues in this research with disclosure suggest some changes may be needed
at a procedural or policy level to incorporate a question about autism, or at least about
needs arising from neurodiversity (i.e. alternative communication support). An important
finding in relation to the theme of communication for the autistic participants was how
strongly it was linked with anxiety. Specifically, being informed about what was going to
happen was key to helping reduce feelings about uncertainty. It was suggested the addition
of visual support (i.e. a toolkit) to convey information in a more accessible way could be
valuable.

<hs>  Sensory sensitivities</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Sensory sensitivities were highlighted as having the potential to negatively affect
experiences of autistic individuals during the custody process. Tactile sensitivities were
emphasised most, particularly in relation to the search and processing procedures. The
visual glare from the lighting and glossy colours used in the station also added to their
difficulties. Interestingly, smell was not mentioned during the walkthrough. Similarly,
auditory sensitivities were not as strongly highlighted. This may have been due to using
the training suite rather than the actual custody suite which was always in use. Thus, the
impact of these factors may be areas for further investigation.

<hs>  Knowledge and understanding of autism</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The officers highlighted how previous experience with autistic or other vulnerable
detainees prompted them to ask additional questions to better support them during the
walkthrough. However, although officers have a good awareness and sensitivity to
vulnerable detainees, they may be lacking in knowledge of autism specific support. This
was clearly illustrated by the quote in section 3.1.2 (above) which conveyed that the
officers showed compassion but lacked specific knowledge about how autism affected them.
As mentioned by the officers, this may be due to the limited autism training they receive.
This is consistent with previous research which raised concerns about the adequacy of
autism training for police (Crane et al., 2016).

<hs>  Recommendations for support</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

In light of these findings, several recommendations can be made to improve the support of
autistic individuals in police custody (see Table 3). These are divided into those that
could be implemented by police officers on the ground immediately and those that require a
change in policy or practice at a higher level. Notably, many of these recommendations
would also benefit suspects more generally or those with other developmental conditions
(i.e. sensory processing disorder). Therefore, it would be extremely valuable to consider
how some of these changes could be incorporated as part of standard custody procedure, and
not only for detainees who disclose a diagnosis of autism. This is particularly important
as some individuals with autism may be undiagnosed or fail to disclose they have autism
during the booking in process as evidenced in our current findings and in previous work
(Crane et al., 2016). While this study provides valuable insight into the experiences of
autistic individuals during the custody process, it also has limitations. The findings are
limited to two autistic participants who both had attended University and only required
moderate support in their daily lives. Given the heterogeneity of autism, it will be
important to replicate this work with other autistic individuals representing a greater
diversity of the population. Furthermore, although many of the custody processes will be
the same in other police stations (at least in England and Wales), it is important to note
that the facilities or environment may differ across police stations. The study is also an
example of a ‘best case scenario’ and various forms of support were in place to help
safeguard the welfare of the participants. As the findings do not reflect the heightened
stress experienced by detainees in real life, they may not reflect the full range of
difficulties some individuals may experience in police custody or the impact this may have
on them. Moreover, this study did not include neurotypical individuals. This prevents
further comparison of the experiences of autistic individuals with those from the general
population. Nonetheless, the autistic participants did report a considerable number of
issues that would likely only be amplified under real-world conditions. To gain further
insight into these experiences, further research across different settings with a range of
participants should be conducted.

<h>CONCLUSIONS</h>
-----------

The effects of communication barriers and sensory stress illustrated by this study
indicate that autistic individuals are at greater risk of being adversely affected when
detained in police custody. When combined with the typical difficulties suspects already
experience, these additional factors are likely to affect how autistic individuals
participate in the custody process. Adaptations to custody procedures and greater
provision of accessible information are crucial as a lack of understanding can exacerbate
anxiety levels. Taking steps to minimise sensory demands by adapting or better designing
custody suites is also important to prevent sensory overload and reduce overall stress. In
summary, these findings emphasise the need to implement a range of additional support in
police custody and to make changes to the custody environment, police procedures and
current policies.

<h>FUNDING</h>
-------

This work was supported by the Economic and Social Research Council [grant number
ES/J500100/1], by a PhD studentship to CH.


<h>REFERENCES</h>
----------

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<ART>Externalising behaviour from infancy to mid-adolescence: Latent profiles and early predictors
================================================================================

Authors: Anne Kjeldsen, Harald Janson, Mike Stoolmiller, Leila Torgersen, Kristin S. Mathiesen
DOI: 10.1016/j.appdev.2013.11.003
Year: 2014  |  Pages: 25-34
ASJC codes: 3204
Keywords: Adolescence, Developmental trajectories, Early predictors, Externalizing problems, Infancy

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The overall aim of the current study was to identify typical trajectory classes of externalising behaviour, and to identify predictors present already in infancy that discriminate the trajectory classes. 921 children from a community sample were followed over 13. years from the age of 18. months. In a simultaneously estimated model, latent class analyses and multinomial logit regression analyses suggested a five-class solution for developmental patterns of externalising problem behaviours: High stable (18% of the children), High childhood limited (5%), Medium childhood limited (31%), Adolescent onset (30%), and Low stable (16%). Six risk factors measured at 18. months significantly discriminated among the classes. Family stress and maternal age discriminated the High stable class from all the other classes. The results suggest that focusing on enduring problems in the relationship with the partner and partners' health may be important in preventive and early intervention efforts. © 2013.

--------------------------------------------------------------------------------


<hs>  Sample and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

We used data from the Tracking Opportunities and Problems Project (TOPP), a population-
based prospective longitudinal study focusing on development of well-being, good mental
health, and mental disorders in children, adolescents, and their families. More than 95%
of Norwegian families with children attend public health services in infancy, which
include 8–12 health screenings during the first 4 years of the child's life. Every family
who visited a child health clinic within six select municipalities in eastern Norway
(comprising 19 different health care regions) in 1993 for the scheduled 18 month
vaccination visit, were invited to complete a questionnaire. Of the 1081 eligible
families, the parents of 939 children (87%) participated at Time 1 (t1). These parents
received a similar questionnaire when the children were 2.5 years of age (Time 2: n = 804,
86% of t1), 4.5 years (Time 3: n = 760, 81%), 8.5 years (Time 4: n = 535, 57%), 12.5 years
(Time 5: n = 610, 65%) and 14.5 years (Time 6: n = 481, 51%). The questionnaires were
administered by health-care workers at t1 to t3. In subsequent waves questionnaires were
sent by mail. The parents chose whether the mother or father completed the questionnaire
at t1–t4, at t5 the mothers were encouraged to answer, and at t6 separate maternal and
paternal questionnaires were sent. The number of questionnaires completed by mothers at
each wave included 921 (t1), 784 (t2), 737 (t3), 512 (t4), 594 (t5) and 481 (t6). Since so
few fathers participated across time, the paternal questionnaires were not included in the
current study. The 19 health care regions were chosen on the basis of their overall
representativeness of the diversity of social environments in Norway: 28% of the families
lived in large cities, 55% in small towns or other densely populated areas, and 17% in
rural areas. The gender of the children in the sample was nearly evenly divided, with
48.9% (n = 450) boys. Maternal age ranged from 19 to 46 years at t1, with a mean of 30
years (SD = 4.7). At t1, 49% of the families had only one child, 37% had two, and 15% had
three to ten children. The participating families were predominantly ethnic Norwegian. In
1993 only 2.3% of the Norwegian population came from non-Western cultures, therefore, this
sample was largely representative of ethnicity in Norway at the time of data collection
(Statistics Norway, 2013). Data from the child health clinics showed that nonparticipants
at t1 did not differ significantly from the study participants with respect to maternal
age, education, employment status, number of children, or marital status. Analyses of
sample attrition from t1 to t7 (i.e., child age 16.5 years) showed that the families who
had dropped out were not significantly different at t1 from the families who completed
questionnaires at t7 in terms of child externalising behaviour, maternal depression,
maternal age, financial status, number of children, negative life events, chronic stress,
or social support. However, the dropout sample was significantly different from the
remaining sample at t1, in that a greater proportion of mothers with low education had
left the study. This is commonly found in longitudinal studies (Gustavson, Soest,
Karevold, & Røysamb, 2012). Steps taken to minimize the impact on statistical analyses of
this non-random attrition are addressed in the analyses section.

        <hss>Externalising behaviour problems</hss>

        Core aspects of mother-reported child and adolescent externalising behaviours were
        measured at all six waves with items rated on a three point scale: 0 (no
        difficulties), 1 (moderate difficulties), or 2 (substantial difficulties). At ages
        18 months, 2.5 years, and 4.5 years the average of three items from the Behaviour
        Checklist (Richman & Graham, 1971) was used to measure temper tantrums,
        manageability, and irritability. Internal consistency (Cronbach's alpha) was .41,
        .46, and .49, at t1, t2, and t3, respectively, for the three-item scale. The
        average inter-item correlation was .21, .23, and .25 at the three time points,
        comparable to the average inter-item correlation of .25 for the 24-items of the
        Externalising syndrome grouping of the CBCL for 1.5–5 years (Achenbach & Rescorla,
        2000) in a large study with a Norwegian sample of 4-year-olds — the Trondheim
        Early Secure Study (L. Wichstrøm, personal communication, June 10, 2011). This
        suggests that the low alphas reflect that few items are used to measure a broad
        construct rather than fundamental deficits in scale reliability. At age 8.5 years
        the Conduct Problem subscale from the Strengths and Difficulties Questionnaire
        (SDQ; Goodman, 1994) was used to measure tempers, obedience, fighting, lying, and
        stealing. The reliability and construct validity of the SDQ has been established
        in a Norwegian sample (Van Roy, Veenstra, & Clench-Aas, 2008). Internal
        consistency for the five item scale was .48. The alpha for the Conduct Problem
        subscale is similar to the findings from other studies (Van Roy et al., 2008). At
        age 12.5 and 14.5 years we used the TOPP Scale on Antisocial Behaviour (TSAB) as a
        measure of externalising behaviours in adolescence. The reason for the change of
        measures was the need for a broader and more comprehensive measure of
        externalising, covering a wider range of behaviours than the five-item SDQ
        subscale. The 18-item scale was constructed for the current project given the
        absence of an age and culture sensitive measure of problem behaviours ranging from
        relatively normative to serious (illegal) through adolescence. The TSAB is
        presented in Table 1. The specific behaviours are included with reference to
        Loeber and colleagues' model of three developmental pathways in child disruptive
        behaviours (Loeber et al., 1993). The items measuring inter-personal aggression
        refers to “overt behaviours” in the Loeber et al. model, stealing and vandalism to
        “covert behaviours”, and loitering to “authority conflict/avoidant behaviours”.
        The TSAB combines items from other Scandinavian scales (Bendixen & Olweus, 1999;
        Mahoney & Stattin, 2000; Rossow & Bø, 2003). The alpha coefficients were .69 and
        .77 at t5 and t6 respectively. Due to a change of wording for three items at t6
        (excluding aggressive behaviours among siblings) the measure of physical
        aggression at t6 may be underestimated compared to t5. Time-to-time correlations
        (i.e., t1 to t2, t2 to t3, etc.) were .46, .50, .32, .29, and .43 for the
        externalising measures, with the lowest correlations corresponding to the longest
        intervals between waves. These time-to-time correlations between the six
        externalising measures across childhood are at about equal magnitude as the alphas
        for the BCL and the SDQ. Again, this supports the interpretation of a measure
        comprising few items covering a broad construct area as opposed to fundamental
        deficits in measure reliability.

        <hss>Temperament</hss>

        At age 18 months child temperament was assessed by the EAS Temperament Survey for
        Children: Parental Ratings (Buss & Plomin, 1984), which contains four dimensions:
        (a) Emotionality — the tendency to become aroused easily and intensely (often
        called Negative Emotionality); (b) Activity — preferred levels of activity and
        speed of action; (c) Sociability — the tendency to prefer the presence of others
        to being alone; and (d) Shyness — the tendency to be inhibited and awkward in new
        situations. The EAS for children aged 1–9 years was used. Because of ambiguity in
        translation, one item was deleted from each dimension. The items were scored on a
        Likert scale from 1 (very typical) to 5 (very untypical). Cronbach's alphas for
        the four items in each dimension were .66, .68, .52, and .75, respectively.

        <hss>Maternal mental health</hss>

        At child age 18 months maternal symptoms of anxiety and depression were measured
        by a 23-item version of the Hopkins Symptom Check List (HSCL-25; Hesbacher,
        Rickels, Morris, Newman, & Rosenfeld, 1980). The reliability of the HSCL has been
        well established in a Norwegian sample (Tambs & Moum, 1993). Two items, “thoughts
        of ending your life” and “loss of sexual interest or pleasure”, were excluded from
        the current version of the questionnaire because some mothers who participated in
        a pilot study had perceived the questions as offensive. The items were scored on a
        4-point Likert scale, from 1 (not at all) to 4 (very much). The alpha coefficient
        was .90.

        <hss>Family stress</hss>

        At child age 18 months mothers were asked to indicate whether they had experienced
        enduring problems during the last 12 months in the following areas: housing,
        employment, financial status, their partner's health (somatic and mental), and
        their relationship with their partner, each scored 0 (no problem) or 1 (problem).
        The sum of the scores in the five stress areas formed the composite score of
        family stress, with a range of 0 to 5. The alpha coefficient was .56.

        <hss>Social support from partner</hss>

        At child age 18 months a social support from partner index was formed by taking
        the mean of three items, each on a Likert-scale from 1 (completely disagree) to 5
        (completely agree), measuring closeness and contact, respect and responsibility,
        and a feeling of belonging (Dalgard, Bjork, & Tambs, 1995; Mathiesen, Tambs, &
        Dalgard, 1999). The alpha coefficient was .59.

        <hss>Social support from friends and family of origin</hss>

        Corresponding to the social support from partner index, this questionnaire
        targeted the same three qualities (closeness and contact, respect and
        responsibility, and a feeling of belonging) to describe the mothers' relationships
        to friends and members of her family of origin. This measure was also completed at
        child age 18 months. A social support from friends and family of origin index was
        computed by summing the mean value of the 6 items. The alpha coefficient was .72.

        <hss>Family demographics</hss>

        Maternal education at child age 18 months was measured using eight response
        categories, and was recoded to represent the approximate total years of education.
        Additional variables included: Maternal birth year; Mothers living without spouse
        or partner; Siblings, a dichotomous variable of 0 (no siblings) and 1 (one or more
        siblings); and Child gender, all values were reported by mothers at child age 18
        months. See Table 2 for a description of sample characteristics.

        <hss>Analytic strategy</hss>

        Latent class analyses refer to modelling with categorical latent variables to
        represent subpopulations. The latent classes explain the relationships among the
        observed dependent variables, similar to factor analysis, but sort individuals
        into latent classes rather than producing continuous latent factor scores. Child
        externalising mean scores at each assessment (age 18 months and 2.5, 4.5, 8.5,
        12.5 and 14.5 years), rescaled to have approximately equal variance at every time
        point to eliminate possible estimation problems due to different scales of
        measurement, were used in the latent class analyses. The rescaling was done by
        multiplying the variable by 10 (at t1, t2 and t3, respectively), 14.29 (at t4),
        and 26.67 (at t5 and t6). After rescaling, mean externalising was 4.2, 4.6, 4.7,
        3.1, 1.9, and 1.9 at age 1.5, 2.5, 4.5, 8.5, 12.5 and 14.5 years respectively.
        Latent Class Growth Analysis (LCGA) is a popular latent class analyses method for
        longitudinal measures that produces classes that are similar in terms of
        development. Latent Profile Analysis (LPA) is similar to LCGA but it does not
        impose a parametric form to growth (e.g. linear growth) and is, therefore, more
        general than LCGA. LPA captures developmental change just as LCGA, but in the form
        of a profile of change rather than as slopes and intercepts. Because we did not
        want to restrict a priori the possible shape of developmental patterns to
        estimate, we considered this a sound choice. We allowed the residual time specific
        variances to be different across classes but forced them to be equal across time
        to minimize the number of variance parameters and potential convergence problems.
        Child and family factors measured at child age 18 months were used as predictors
        of the longitudinal latent classes, including emotionality, shyness, activity,
        sociability, maternal symptoms of anxiety and depression, family stress, social
        support from partner, social support from family of origin and friends, maternal
        education, maternal age, mothers living without spouse/partner, siblings, and
        child gender. Multinomial logit regression was used to test for group
        discrimination by the 18 month predictors one at a time. The predictors were then
        combined in one multi-predictor model to compare their relative strength in
        discriminating the latent classes; those that were not significant in the multi-
        predictor model were removed. Models were estimated by using the full information
        maximum likelihood estimator in Mplus, which allows for the inclusion of
        participants with partial data in the trajectory variables (externalising), but
        not participants with missing predictor data, under the assumption that
        missingness is at random, conditional on variables included in the model (MAR).
        Thus, the sample size varies somewhat across models depending on which t1
        variables are included. The amount of missing data at t1 was minimal, however,
        with less than 2% for any particular predictor, and less than 3% for the multi-
        predictor models. It is not possible to test the MAR assumption unless the missing
        data can somehow be recovered, but even if the MAR assumption is not completely
        true, MAR based likelihood estimation performs well under most circumstances and
        is superior to obsolete methods based on including only subjects with complete
        data (Graham, 2009).

<hs>  Optimal number of latent classes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Externalising scores from all waves were first included in a series of latent class
analyses in order to decide on the optimal number of latent classes. For models with 3 or
more classes, the data drove the models toward solutions that included one or two classes
with virtually no externalising in adolescence. This was due to skewness of the TSAB
scores at t5 and t6, as 173 mothers reported that their adolescents had no externalising
behaviours at both t5 and t6 combined. Since subgroups with means and variances of zero
are known to produce estimation challenges and model nonconvergence (Hipp & Bauer, 2006),
we thus fixed the model variance-parameters for these two groups at a small value near
zero (0.22). (Another commonly used approach to the class variation problem, i.e., forcing
the residual variance terms to be the same across all the classes, was not appropriate for
these data, as the assumption that a low externalising class would have just as much
variability as a high externalising class was not plausible and did not describe the
observed data well.) Solutions with two to six classes were examined. We used the BIC and
sample size adjusted BIC (SSA-BIC) fit statistics, and the Vuong-Lo-Mendell-Rubin (VLMR)
test to decide on the optimal number of latent classes. The BIC's were 19,313, 18,983,
18,805, 18,743, and 18,767, respectively, for the two to six-class solutions, while the
SSA-BIC's were 19,256, 18,895, 18,688, 18,594, and 18,590. The VLMR test indicated that
three classes were the best solution but this solution did not include a low externalising
class. There is an inherent uncertainty regarding the optimal class enumeration in
exploratory LPA. However, BIC fit statistics are the most commonly used and accepted
criterion for deciding on the optimal number of latent classes. We chose the model with
five trajectories, as it had the lowest BIC fit statistic among models with two to six
classes. Although the SSA-BIC did not show the same clear minimum, it is known that the
BIC imposes a higher per parameter penalty then the SSA-BIC and the SSA-BIC usually
indicates more classes than the BIC (Nylund, Asparouhov, & Muthen, 2007). Inspection of
the profile forms, problem levels, and proportions of the various classes also supported
the five-class solution. We tracked the (re)allocation of individuals as the number of
classes increased, and the underlying heterogeneous data structure became apparent. We
were thus able to inspect the meaningfulness of the various solutions in terms of the
balance between model complexity and simplicity when depicting this heterogeneity. Both
the BIC and the meaningfulness of the solution were supportive of the five-class solution.
The five-class solution consists of a “High stable” class (a group with a stable high
level of externalising through the study period that emerged in the solutions with three,
four, and five classes, suggesting that the identification of the “High stable” class is a
robust finding), a “High childhood limited” class (characterised by a very high level of
externalising in the early epoch and a low level in adolescence), a “Medium childhood
limited” class (characterised by high levels of externalising in early childhood), an
“Adolescent onset” class (with the second lowest level of externalising early on and the
second highest externalising level in adolescence), and finally a “Low stable” class. We
present class proportions later when discussing results for models that included
predictors.

<hs>  Single-predictor model results</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A second series of latent class analyses was conducted by including the 18 month
predictors into the five-class model, one predictor at a time to test for the effect of
separate predictor variables on the classification results. Including the early variables
in the model increased the model stability without substantially changing the shape of the
trajectories and the proportions of children in the classes. We used a nested chi-square
test (likelihood ratio test or LRT) to compare all class contrasts (the H1 model) versus a
model where all class contrasts were forced to zero (the H0 model). The nested chi-
squares, resulting from a 4 df test of the null hypotheses that the predictors had no
effect on class discrimination, were significant for all 18 month variables except three.
Latent class membership was significantly predicted by child emotionality, LRT (4) =
169.4; p < .001, maternal depression, LRT (4) = 83.9; p < .001, family stress, LRT (4) =
54.8; p < .001, support from family and friends, LRT (4) = 23.6; p < .001, maternal
education, LRT (4) = 23.4; p < .001, maternal age, LRT (4) = 23.4; p < .001, child gender,
LRT (4) = 20.8; p < .001, and support from partner, LRT (4) = 17.2; p < .001. Child
temperamental shyness, mothers living without partners, and having siblings were not
significant predictors. Models with child temperamental activity and sociability had
severe convergence problems, did not give meaningful results, and were excluded from
further analyses.

<hs>  Multi-predictor model results</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Finally, in order to identify the most influential predictors differentiating the five
trajectory classes, we included a multi-predictor, multinomial logit regression analysis
in the latent class model. We entered all of the 18 month predictors, and successively
eliminated variables that were not significant in the total model. Again, this
significance was evaluated by comparing a 4 df nested chi-square test for a model with all
class contrasts (the H1 model) versus a model where all class contrasts were forced to
zero (the H0 model). Six predictors remained in the final model and had significant
effects in discriminating among classes. The individual class contrasts, the four that
were actually estimated (classes 1–4 vs. 5) and the other six that can be derived from
those four along with the 4 df nested chi-squares for these six variables are presented in
Table 3. Estimating all four class contrasts for each of six predictors, 24 estimated
effects in all, with no restrictions on any of the effects, makes the solution difficult
to interpret and tends to inflate the standard errors of the estimates. To make the model
more interpretable, we constrained class contrasts that were about the same magnitude to
be equal with possibly different signs and forced two class contrasts to zero that were
very close in magnitude to zero. This constrained model had nine estimated class contrasts
as opposed to 24, yet the fit of the model was not significantly worse (nested chi-square
= 13.27 with 15 df, p = .58) and the standard errors for the nine effects were
considerably better estimated, although the actual magnitudes of the effects were about
the same as the unconstrained model. The class regression effects for the constrained
model are shown in Table 4. In general, classification quality improves when more
information, such as class predictors, are included in the model. Interestingly, the “High
stable” class remained almost identical across models, while the other classes changed
only moderately. Boxplots with pseudo-class and fitted trajectories for the five-class
solution based on the multi-predictor model are presented in Fig. 1. As can be seen, there
is a close correspondence between the two, indicating a reasonable solution. For three of
the five groups there is a shift in externalising level between t3 and t4 and between t4
and t5, which may partly be a result of a change in measures. The five LCA classes varied
both in level and pattern over time. The class with the highest level of externalising
behaviours in the three first waves had a low level of externalising at the adolescent
end-point. This “High childhood limited” (HCL) class was the smallest with 5% of the
sample. The class with the second highest level of externalising in infancy continued to
have high scores throughout the entire measurement period. This “High stable” (HS) class
comprised 18% of the sample. The class with the median level of externalising in infancy
declined to a near zero level at the adolescent end-point. This “Medium childhood limited”
(MCL) class was the largest, including 31% of the sample. The class with the second lowest
level of externalising in infancy was the second highest group at the adolescent end-
point. This “Adolescent onset” (AO) group constituted 30% of the sample. Finally, 16% of
the sample was assigned to a “Low stable” (LS) group. Due to change in measures and
rescaled variables, note that only relative change across groups and not absolute
(developmental) change can be interpreted (Fig. 1). As can be seen by the 4 df nested chi-
squares at the bottom of Table 3, child negative emotionality made the strongest class
discrimination, followed by maternal symptoms of depression, child gender, family stress,
maternal age, and siblings. Turning now to the class regressions (Table 4), we start with
the two variables, family stress and maternal age that had the hypothesized pattern of
uniquely discriminating the high stable class (class 5) from the other classes (class
1–4). The fact that all four class regressions for family stress can be constrained to be
equal without degrading model fit, − .29, and are significantly different from zero
indicates that family stress uniquely discriminates the HS class from classes 1–4 but does
not discriminate among classes 1–4. Higher levels of family stress were associated with
lower log odds of membership in classes 1–4. The estimated class regressions can be
exponentiated to determine the effect of a 1 unit shift in the predictor on the odds of
being in one class vs. another, and for family stress this value is .75, indicating that
each 1 unit increase in family stress lowers the odds of belonging to classes 1–4 by 25%.
To appreciate the range of risk from family stress in the population we can consider the
10th percentile family stress score of 0 as low risk and the 90th percentile score of 3 as
high risk. Going from low to high risk in the population would increase family stress by 3
units and thus increase the odds of belonging to the HS class by a multiplicative factor
of 2.4 or 140%. Maternal age also had the same pattern of effects as family stress such
that increasing birth year (i.e. younger age) was associated with lower log odds of being
in classes 1–4 vs. the HS class. Going from low to high risk increased the birth year
variable by 1.2 units (it was linearly rescaled to prevent convergence problems in the
model, on the raw scale it was 12 years, age 36 compared to age 24), which corresponds to
an increase in the odds of being in the HS class by a factor of 3.7. Because family stress
and maternal age are the only two predictors that uniquely discriminated the HS class, it
makes sense to consider the range of risk from both risk factors simultaneously. This
entails comparing a family with both risk factors at the 10th percentile value to a family
with both risk factors at the 90th percentile, all else being equal. Such a comparison
yields an 8.8 fold increase in the odds of being in the HS class vs. classes 1–4, which is
a very substantial increase in risk. The next two variables with relatively simple class
discrimination patterns were female gender and children with siblings. Siblings increased
the odds of being in the HS class vs. the MCL, HCL and AO classes by 2.1 but had no effect
on discriminating the LS class and the HS class. Female gender increased the odds of being
in the MCL, HCL, and in the LS classes vs. the HS class by 1.7 but decreased the odds of
being in the AO class vs. the HS class by 0.6. Finally, maternal depression and child
emotionality had a similar but more complicated pattern of effects on class
discrimination. Both variables increased the odds of being in the HCL class vs. the HS
class by very substantial amounts, but both variables also increased the odds of being in
the HS class vs. the AO and LS class by substantial amounts. Maternal depression also
increased the odds of being in the HS class vs. the MCL class, but child emotionality had
no effect on this contrast. Child emotionality appears to discriminate largely based on
early externalising in the first three time points. Maternal depression also fits this
pattern, except for the significant discrimination of the HS and MCL classes, which have
similar levels of early externalising, but quite different levels of adolescent
externalising. In fact, for low vs. high risk on maternal depression, a shift of 0.8 units
on the maternal depression scale, the odds of being in the HS class vs. the LS class
increases by 2.0.

<h>DISCUSSION</h>
----------

The overall aim of the current study was to identify typical trajectory classes of
externalising behaviours, and to identify predictors already present in infancy that
discriminate among the trajectory classes. A latent profile model with five classes was
chosen as the best to capture the heterogeneity in the 13-year course of externalising
behaviour development from infancy to mid-adolescence. The model identified a class of
children following a developmental trajectory with a HS level of externalising behaviours.
Identification of this HS class is a robust finding, in that the class emerged early in
the analytic process and remained consistent across models. While most predictor variables
discriminated between trajectory classes in the single-predictor models, six variables
were the most influential (multi-predictor model). Two variables, family stress and
maternal age, discriminated uniquely between the HS class and all other classes. Comparing
families with both of these risk factors simultaneously at the 10th percentile value to
families with both risk factors at the 90th percentile, all else being equal, yields an
8.8 increase in the odds of being in the high stable class versus the other classes. The
other four significant variables in the multi-predictor model – child gender, siblings,
maternal depression, and child emotionality – had less clear patterns of class
discrimination. The finding that maternal age and family stress, measured in infancy,
seems to have strong impact on externalising development from infancy to mid-adolescence
has potential to inform preventive and early intervention efforts. There is an inherent
uncertainty regarding class enumeration in exploratory LPA, and deciding on the optimal
number of latent classes cannot be done based on test-based criteria alone. For our
results, however, the BIC fit statistics clearly suggested that five classes were better
than four or six. We fixed several model variance parameters at a small value near zero
for two classes at t5 and t6 in order to avoid estimation difficulties due to no variance
in externalising scores. In preliminary attempts at modelling the data without fixing the
class variances, the BIC statistic never hit a clear minimum and just continued to
decrease for four, five, and six class solutions. The longitudinal five-class solution
that was chosen for the current study is in line with theory and earlier findings. As
postulated by Moffitt's taxonomy (1993), an early-onset and an adolescent-onset type
emerged. Childhood limited types were found as in other longitudinal studies (Moffitt,
2006). Among studies that have covered longer developmental periods starting from before
the age of three years, the solutions vary between three, four, and five trajectory
classes. Similar to our five-class solution, results from the NICHD study based on
aggression ratings (Campbell et al., 2006; NICHD ECCRN, 2004) and on ratings based on a
broader externalising construct (Fanti & Heinrich, 2010) suggested five trajectory
classes. Further, two different classes with externalising behaviour problems limited to
childhood were also found in studies starting at a very early age (Fanti & Heinrich, 2010;
Côté et al., 2006; Shaw et al., 2005). For instance, Fanti & Heinrich (2010) identified a
High Desister class as well as a Moderate Desister class, which seems to correspond well
with our solution with two different childhood limited classes. The LS class consisted of
16% of the sample. In trajectory studies that begin from preschool or later, the LS
externalising class tends to be the largest class (e.g., Campbell et al., 2010; Odgers et
al., 2008). In infancy and toddlerhood, however, child misbehaviour is highly normative
(Tremblay et al., 1999; Wakschlag et al., 2010). A small LS externalising class is in line
with findings from other studies that have measures from infancy and onwards, like 10% in
the Shaw et al., study (2005) and 5% in the Côté et al., study (2007). The HS
externalising class comprised 18% of the sample, which is substantial in comparison to
most previous studies. For example, 7% of the sample used by Shaw et al. (2005) was
classified as having high stable externalising behaviour, and 3% fell into a similar class
in the NICHD ECCRN (2004) study. The only study to identify a similar proportion is Côté
et al. (2006), with 16.6%, although the Côté study identified three and not five groups as
did the current study. Post-hoc analyses indicated that the HS class in the present study
was characterized by a wide array of externalising behaviours. As the construct of
externalising used in the TOPP cohort is broader, encompassing common oppositional and
disruptive behaviour in early childhood and vandalism, status violations, and physical
aggression from mid childhood onwards, the larger high stable class is an expected finding
compared to the studies that have had a limited focus on overt conduct problems and
physical aggression. The problem scores of the HS class are labelled “high” as they are
compared to the other classes in the model, but are these scores exceptionally (deviant)
high? The proportion of children in comparable populations expected to meet criteria for a
disruptive disorder diagnosis is estimated at between 3% and 8% (e.g., Heiervang et al.,
2007; Kessler et al., 2012; Wichstrom et al., 2012), thus for the majority of the children
in the HS class (18%) the scores are probably not clinically high. When comparing the mean
HS problem levels, however, to the means in comparable studies across childhood, it is
clear that the HS class is substantially elevated in comparison to average children.
First, we compared the BCL scores at age 4.5 to data from an epidemiological study of
approximately 2000 Norwegian 4-year-olds in Vestfold county (Wefring, 2001). Means and SDs
across the complete datasets were similar, and the mean problem score of the HS class
corresponds to the 88th percentile value in the Vestfold data (K. K. Lie, personal
communication, November 8, 2013). Further, we do not have Norwegian norms for SDQ, but we
compared the age 8.5 score on SDQ Conduct Problems Scale to data from two large Norwegian
population-based samples of 9-year-olds (Obel et al., 2004). Means and SDs across the
three complete datasets are very similar, and the mean problem score of the HS class
corresponds to a score between the 87th and 95th percentile value in the Akershus data (J.
Clench-Aas, personal communication, November 8, 2013). Finally, to our knowledge, the only
other project that has collected parent-reports at ages 12 and 14 with items identical to
those in TSAB is the Swedish “10 to 18” study (Mahoney & Stattin, 2000). In that study,
four items comparable to TSAB items no. 2, 3, 9, and 15 (see Table 1) were administered.
It should be noted that the response format in that study differed from the one applied in
our study, in that responses referred to lifetime involvement (“ever”) and not involvement
during “the last 12 months”. These four items in the “10 to 18”-study, measured at ages 12
and 14 (H. Stattin, personal communication, November 1st, 2013) have close to identical
means, SDs, and 95th percentile values as compared with the corresponding four items in
the TOPP-study measured at ages 12.5 and 14.5 years. The problem score levels of the HS
class correspond to a score between the 94th and 98th percentiles and between the 92nd and
98th percentiles in the “10 to 18”- data in early and mid-adolescence, respectively. More
details on the comparisons are available by request from the first author. Concerning
class-differentiating predictors measured at 18 months, one noteworthy result was that the
LS class was uniquely different from all the other classes on low maternal depression and
low child emotionality. The HS problem trajectory class was uniquely and strongly
differentiated by young maternal age and higher levels of family stress from all the
remaining developmental pathways identified in the study, including the HCL group, which
started with an even higher externalising level in infancy. Given the need to extend
knowledge about normative versus high-risk early externalising behaviour, the
identification of these two family factors which can discriminate between the HS and other
groups (odds ratio of 8.8 for high on both vs. low on both risk factors) is an important
finding, with potential to inform prevention and early intervention efforts. Early family
adversity is a well-established predictor of externalising development (Aguilar, Sroufe,
Egeland, & Carlson, 2000; Shaw et al., 2001). Despite this, the current study is to our
knowledge, the first trajectory study over the period from infancy to mid-adolescence to
document this. The results suggest that support to young mothers and families under
stress, especially those whose toddlers are exhibiting noncompliant acting-out behaviour,
may interrupt a pathway of externalising behaviour which may otherwise continue into
adolescence. The current study included a population based sample where the youngest
mother gave birth at age 17. Young motherhood is identified as a risk for externalising
development in both high-risk samples in the U.S. and Canada (Nagin & Tremblay, 2001; Shaw
et al., 2005), and in nationally representative samples (Côté et al., 2007). Our results
are in line with these previous findings, while we note that young motherhood was not a
significant predictor in a U.S. general population sample (NICHD ECCRN, 2004). The measure
of family stress that discriminated the HS class from all the other classes at 18 months
covered problems experienced during the previous 12 months in areas including
socioeconomic difficulties and relationship issues. Living condition stressors constituted
important parts of this index, and were measured with three items covering enduring
problems with housing, employment, and financial status. Our finding on living condition
stressors is in line with results on low income from general population samples in the
U.S., Canada, and the U.K. (Barker & Maughan, 2009; Côté et al., 2006; NICHD, 2004),
underlining that living condition stressors are an important predictor of the development
of chronic high externalising from early childhood onwards. The current findings suggest
that other aspects of stress are also important. An exploratory post-hoc analysis
suggested that the variables within the overall stress construct which were most closely
related to class membership were problems in the relationships between mothers and their
partners and partners' health problems. Regarding the mothers' experience of enduring
problems in their relationship with their partners, studies are scarce, and we have
located only one trajectory study from early childhood onwards with which to compare our
results. The Avon Longitudinal Study (Barker & Maughan, 2009) measured grave parental
relationship problems in the form of partner cruelty towards the mother (defined as any
indication of emotional and/or physical abuse from the mother's partner), and found that
partner cruelty between child ages 0 and 4 predicted chronic conduct problems from ages 4
to 13. Our findings expand upon the Avon study results by indicating that parental
relationship problems do not need to include cruelty to have significance for early-onset
externalising development. The last topic within the early family stress index is mothers'
experience of enduring problems related to partners' somatic and/or mental health. Here,
as well, we have located only one early starting trajectory study with a measure that was
somewhat similar to ours. A Canadian population based study measured depressive symptoms
in fathers at child age 5 months and found paternal depression to be a unique predictor of
chronic disregard for rules between ages 29 to 74 months (Petitclerc et al., 2009). The
Canadian finding, in combination with our results, point toward the importance of health
issues in fathers (mothers' partners) for chronic high externalising development from
early childhood onward. As these last issues within the family stress index were measured
with only one item each, and given the overall scarcity of studies on these two topics,
there is a need for more studies to shed light on the impact of enduring difficulties in
mother's relationship to her partner and to partner's health, as early predictors of a
chronic high externalising profile across childhood. Child negative emotionality measured
in infancy had the strongest impact on the final model as a whole; this variable
contributed to the discrimination of most of the classes. Child emotionality appears to
discriminate largely based on early externalising in the first three time points. Since
for all five trajectory classes the mean levels of negative emotionality and externalising
were parallel to each other at t1, it is possible that parents did not differentiate
clearly between externalising behaviour and temperamental negative emotionality at this
early age. Furthermore, it may be that there is conceptual overlap between the items
tapping negative emotionality and externalising at this age (both of which are related to
child manageability), an issue that is common in the field (Sanson et al., 2011). However,
studies suggest that confounding of measures does not fully account for the predictive
role of emotionality, which has consistently emerged in the literature as a risk for
externalising behaviour problems (Sanson, Hemphill, Yagmurlu, & McClowry, 2011). Parents
raising a child high in negative emotionality may need support in helping the child to
regulate a temperamental disposition, and in avoiding a punitive style of discipline and
‘coercive cycles’ of interaction with their child (Reid et al., 2002). Maternal anxiety
and depressive symptoms when children were 18 months old had the second strongest impact
on the final (multi-predictor) model as a whole, and similar to child emotionality, this
predictor appears to discriminate largely based on early externalising in the first three
time points. Unlike child emotionality, however, it discriminated the HS class from the
MCL class (odds ratio of 2.0), two classes which have similar levels of externalising at
the three earliest time points but quite different levels of externalising at adolescence.
This finding points toward maternal symptoms of anxiety and depression as an early risk
factor for all the pathways towards some level of externalising problems in adolescence.
Once again, these findings suggest a need for early intervention for mothers showing signs
of mental health problems. More of the children in the HS class had siblings compared to
all the other classes except the LS class. Parenting two or more children simultaneously
creates higher demands on parents and family resources. A mother who is exposed to the
risk factors of family stress, young age, and the presence of siblings in the family has a
16 fold increase in the odds of having a child in the HS class compared to the MCL, HCL,
and the AO classes. The substantial increase in risk due to siblings could be because
multiple siblings may exacerbate each other's antisocial behaviour in a negative cycle of
so-called deviancy training (Patterson, 1986). In support of this notion, sibling
aggression has previously been found to have a unique contribution to externalising
development in a genetic sensitive study (Natsuaki, Ge, Reiss, & Neiderhiser, 2009).
Contrary to expectations, the HS profile had an even split between the genders, rather
than mostly consisting of boys. The even split between the genders in a high externalising
class is not in line with previous research (e.g. Côté et al., 2006). Previous findings
have suggested that robust gender differences are typical for overt externalising
behaviour types, as well as for a wider construct that includes overt types (Broidy et
al., 2003; Moffitt, Caspi, Rutter, & Silva, 2001). To our knowledge, gender differences
are not equally robust in other facets of externalising behaviours. For stealing and
lying, the frequency may be equal between the genders (Tiet, Wasserman, Loeber,
McReynolds, & Miller, 2001). The use of a broad measure of externalising in the current
study, which includes oppositional and disruptive behaviour in early childhood and covert
and authority avoidant behaviour from mid-childhood onwards, may have resulted in more
girls included in the HS class. The post-hoc analyses of gender differences within the HS
class suggest that the HS boys were on average more involved in overt externalising
behaviours than the HS girls, while for the remaining externalising items there were no
gender differences within the HS class. Furthermore, the size of the HS class identified
in the current study is substantial in comparison to other studies (NICHD ECCRN, 2004;
Shaw et al., 2005). Thus, the inclusion of externalising behaviours that were non-
confrontational at all time points in addition to overt behaviours, may have resulted in a
higher proportion of children in general, and also a higher proportion of girls, included
in the HS profile. Maternal education level discriminated in the HS and LS groups in the
single-predictor models, but failed to do so when all predictors were entered
simultaneously. This is in contrast with findings from the U.S., Canada, and England, for
example Nagin and Tremblay's (2001) study, in which low maternal education was one of two
factors discriminating between “chronics” and “high decliners” in physical aggression. One
possible explanation for why maternal education was not significant in the complete model
of this study may be that education is not a strong marker of social class in Norway given
that Norway is a relatively homogeneous society. Overall, this study produces
substantially important findings, and adds to the literature in notable ways. To our
knowledge, no latent class trajectory study has included such an array of simultaneously
estimated early predictors of class membership, with the earliest externalising measure
taken before child age of 2 years and continuing to mid-adolescence. The results suggest
that preventive and early intervention efforts should have a broader focus and pay special
attention to children's externalising behaviours in the context of young motherhood and
higher levels of family stress, as well as child temperament, maternal distress, male
gender, and presence of siblings in the family. It is possible that family support
intervention programmes focusing on supporting a stable, low stress family environment
would reduce the numbers of adolescents likely to engage in delinquency. What may the
mechanisms be that link the identified factors in infancy with membership in a stable high
trajectory pattern? A young mother may be less experienced as a caregiver and have poorer
parenting skills, while at the same time she may be more vulnerable to the frustration of
her own developmental needs. Additionally, when experiencing enduring strains in a
relationship with a romantic partner, with health issues, with living condition related
issues, and/or when having symptoms of depression and anxiety, these factors are likely to
result in reduced sensitivity, contingency, and time available during day to day
interactions with the child. While this study benefited from six waves of data with a
community sample, it has some limitations. Attrition analyses showed that some of the less
educated mothers had left the study by t7. This maternal factor is known to be associated
with externalising problems in the child. Thus, the results may be underestimating the
effects of low education on externalising trajectories. All analyses, however, were
carried out using full information maximum likelihood estimation which includes subjects
with partial data and minimizes biases due to attrition. Another limitation is the use of
different measurement instruments to assess externalising behaviour in the trajectory
model, meaning that the externalising construct is not identical through all developmental
phases. Three out of five groups show a shift in trajectory shape with changing
instruments, and the physical aggression component may be underestimated at t6. Our
measures, however, are still appropriate for identifying different patterns of
externalising development even if specific mean levels of externalising are not directly
comparable across time. It has also been shown that children's development differs over
the various domains within the broad construct of externalising (Bongers, Koot, van der
Ende, & Verhulst, 2004). The current study focused on the broader construct, and not on
its sub-domains. The current study's strength of using a developmentally appropriate broad
measure to identify and compare trajectory groups should be weighed against the
disadvantage of not considering sub-domain development. Furthermore, the early predictors
measured in this study are likely to change over time in ways that are likely to continue
to impact development. Future studies should address a broader view of potential
predictors throughout development. Findings may have been weakened by the modest internal
consistency of some predictor measures, which is likely to have attenuated some
relationships. Internal consistency was also low for the outcome, but the latent class
model accounts for imperfect reliability in the outcome and hence it is not likely that
the modest internal consistency of the t1–t4 indicators has biassed the class solution,
even though it may have contributed to weaker classification accuracy for some
individuals, particularly in the first set of analyses before predictors were added to the
model. In addition, because the mothers reported on themselves as well as their children,
single-informant bias may have influenced the results. A reasonable case has been made,
however, that maternal reports provide valid and useful information (Janson & Mathiesen,
2008; Rothbart & Bates, 2006). However, replication with multi-source data is needed.
Also, although the study has tapped a range of important influences on children's
development, there are other potential sources of influence such as children's peer
relationships and genetic variation, on which more information is needed to fully
understand the development of externalising problems. Finally, our findings may also be
more easily generalised to Western European societies that are more similar to Norway with
respect to social welfare systems including family and youth support systems as opposed to
findings from for example the United States. This study contributes to the literature with
data from a developing general population sample followed over a long time span. We have
used a broad and developmentally appropriate measure of externalising, and taken advantage
of a wide range of risk factors measured very early in development. The results add to the
literature with unique and practically important findings that may be useful for
prevention or early intervention efforts in minimizing the long term negative effects of
early externalising behaviours. Although replication of these findings is necessary, they
point towards the need for preventive interventions to start very early in life and to
address multiple aspects of children's family life.


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<ART>Eye gaze as a means of giving and seeking information during musical interaction
================================================================================

Authors: Laura Bishop, Carlos Cancino-Chacón, Werner Goebl
DOI: 10.1016/j.concog.2019.01.002
Year: 2019  |  Pages: 73-96
ASJC codes: 3204, 3205
Keywords: Attention, Body gestures, Communication, Coordination, Eye gaze, Joint action, Visual interaction

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

During skilled music ensemble performance, a multi-layered network of interaction processes allows musicians to negotiate common interpretations of ambiguously-notated music in real-time. This study investigated the conditions that encourage visual interaction during duo performance. Duos recorded performances of a new piece before and after a period of rehearsal. Mobile eye tracking and motion capture were used in combination to map uni- and bidirectional eye gaze patterns. Musicians watched each other more during temporally-unstable passages than during regularly-timed passages. They also watched each other more after rehearsal than before. Duo musicians may seek visual interaction with each other primarily, but not exclusively, when coordination is threatened by temporal instability. Visual interaction increases as musicians become familiar with the piece, suggesting that they visually monitor each other once a shared interpretation of the piece is established. Visual monitoring of co-performers’ movements and attention may facilitate feelings of engagement and high-level creative collaboration.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

When people interact, eye gaze serves as a means of giving, as well as obtaining
information. The direction of a person’s gaze can indicate their focus of attention –
which might be on another person, a salient environmental stimulus, or the direction they
intend to move. Indeed, some researchers have hypothesized that the human eye evolved its
current structure (specifically, the contrast between the coloured iris and white sclera)
because people benefitted from the ability to track each other’s gaze direction
(Tomasello, Hare, Lehmann, & Call, 2007). When eye gaze is directed towards another
person, it often indicates an intention to interact. Imaging studies have shown that
direct eye gaze activates the “social brain”, a network of structures involved in human
communication and social interaction (Senju & Johnson, 2009). It follows that eye gaze can
be a valuable means of communicating during joint action tasks, such as playing team
sports or performing with a music ensemble. Our study assessed the communicative functions
of eye gaze during music ensemble performance, a form of joint action that requires
precise and multi-layered coordination between participants. Individual note onsets and
offsets, as well as expressive nuances (e.g., changes in patterns of loudness and
articulation) have to be aligned in time, even though the information provided by the
score (if there is one) may be limited and subject to interpretation. During ensemble
performance, visual communication between musicians is secondary in importance to auditory
communication, but can become more relevant when performers are uncertain of each other’s
interpretations (Bishop & Goebl, 2015). Prior research has shown that temporal
instability, such as happens at piece entrances, long pauses, and sudden tempo changes
(Bishop & Goebl, 2017; Davidson, 2012; Kawase, 2014a, 2014b), and disruptions to the
clarity (e.g., loudness) of inter-performer audio feedback (Fulford, Hopkins, Seiffert, &
Ginsborg, 2018) can prompt an exchange of visual cues. These are sometimes deliberately
integrated into a performance plan across rehearsals (Williamon & Davidson, 2002). The
current study was designed to build on these findings by examining patterns of uni- (one-
way) and bidirectional (two-way or mutual, see Emery (2000)) eye gaze as they unfolded
across the course of piano and clarinet duo performances. Our aim was to identify the
conditions that prompt performers to interact visually. Based on theoretical
understandings of the mechanisms that support musical interaction (discussed in the next
section), we hypothesized that differences in playing conditions would encourage different
degrees of visual interaction.

<hs>  Functions of eye gaze in musical interaction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We defined two functions of interperformer eye gaze, both of which we expected to see
evidence of during duo performance. Our definitions of these functions are theoretically-
motivated, which we describe below, and demonstrate our attempt to reconcile the
sometimes-contrasting predictions that derive from different perspectives on musical
interaction. By defining these functions and seeking measurable behavioural evidence of
them, we aimed to highlight the variable nature of musical interaction and shed some light
on which processes support duo performance as playing conditions change. Our underlying
argument was that, as a performance unfolds, musicians are at some moments in time drawn
to engage deliberate planning and communication processes to ensure that coordination is
achieved or maintained. They might exchange gestural cues, facial expressions, or make
audible inhalations to facilitate synchronization following a long pause, for example.
Outside of these moments, they allow coordination to “emerge” from the subtle, pre-
reflective accommodations that they make to each other’s audiovisual feedback. Of course,
successful emergent coordination at note and expressive levels is contingent on performers
attending closely to each other and their combined musical output.

        <hss>Engagement-driven eye gaze</hss>

        Engagement-driven eye gaze is used by musicians to monitor each other’s attention
        and engagement in the joint performance task, as well as to indicate their own
        attention and engagement. This information can be provided by musicians’ gaze
        direction, facial expressions, and body movements. For example, eye gaze directed
        towards the observing co-performer might indicate a focus on the interperformer
        interaction, while a particular pattern of body sway might indicate focus towards
        an aspect of expression. It is important for musicians to be aware of each other’s
        focus of attention (e.g., whether it is directed to the score, or to the co-
        performer, signalling an intent to interact, or elsewhere, signalling potential
        distraction), because their attentiveness relates to how responsive they are
        likely to be to subtle fluctuations in each other’s audiovisual signals. In the
        context of the current study, evidence of engagement-driven gaze would include the
        occurrence of bidirectional gaze that does not occur exclusively at moments of
        temporal ambiguity (though perhaps at other structurally significant points; e.g.,
        piece ending). Bidirectional gaze between duo performers allows visual signals to
        flow in both directions and signifies that both performers are monitoring each
        other. In particular, bidirectional gaze that occurs during periods of temporal
        stability, when visual communication is not necessary for performers to maintain
        coordination (Bishop & Goebl, 2015; Fulford et al., 2018; Kawase, 2014a), is
        suggestive of performers’ attempts to confirm each other’s attention.

        <hss>Intention-driven eye gaze</hss>

        Intention-driven eye gaze is used by musicians to communicate their individual
        intentions and learn their co-performers’ individual intentions. By “individual
        intentions”, we refer to action-based plans that are known to one performer, but
        not necessarily to others (e.g., a performer may intend to play a particular
        passage softly). These are to be distinguished from “shared intentions”, which are
        action-based plans that overlap between performers (e.g., all performers may
        intend to play the passage softly). In particular, musicians are known to
        communicate visually to align their intended timing, and their cueing gestures
        often take the form of an exaggerated nod (Bishop & Goebl, 2017). In the context
        of the current study, evidence of intention-driven gaze would include the
        occurrence of unidirectional gaze at moments of temporal ambiguity (e.g., piece
        onset), particularly when directed from follower to leader. Musical passages with
        ambiguously or imprecisely notated timing may be interpreted differently by
        different performers; thus, uncertainty about each other’s interpretation might
        prompt performers (especially those in a leading role) to communicate their own
        intentions or (in the case of followers) seek out information about their co-
        performer’s intentions. In such cases, the leader might watch the follower while
        performing a gestural cue to ensure that the follower is paying attention. While
        the follower’s gaze is intention-drive, the leader’s follower-directed gaze is
        engagement-driven. In the next section, we discuss the theoretical underpinnings
        of these definitions.

<hs>  Cognitivist and enactive perspectives on musical interaction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Some forms of joint action involve deliberate collaboration between group members with the
aim of achieving a particular goal. Tasks such as coordinating a pass between people on
the soccer field, lifting a table into a truck, or playing a piano duet according to a
particular style fall into this category. In the literature, this is referred to as
planned coordination, and defined in contrast to emergent coordination, which occurs
unintentionally as people make (largely) automatic accommodations to low-level features in
each other’s audio and visual signals (e.g., people who are walking together may find
themselves stepping in sync; van der Wel, Sebanz, & Knoblich, 2016). It is important to
note that planned and emergent coordination are not mutually exclusive, and during
ensemble performance, occur in parallel. According to the cognitivist account of joint
action, during planned coordination, shared intentions and shared attention to the task
are necessary for group members to achieve their desired goal (Keller, 2014; Knoblich &
Sebanz, 2008). The term intentions refers broadly to a dynamic, action-based process of
representing or anticipating upcoming actions or events. This process is flexible –
intentions are constantly evolving as performers monitor their own and their co-
performers’ output. Flexibility in action planning is important because it allows group
members to compensate for variability in each other’s performance, which might arise
because of errors, environmental disturbances, or the spontaneous introduction of new
ideas (Loehr, Kourtis, Vesper, Sebanz, & Knoblich, 2013; Noy, Dekel, & Alon, 2011; for an
overview see Bishop, 2018). Shared intentions comprise overlapping, but not identical,
representations of how individual efforts should contribute to the overall outcome. In
essence, each member of the group understands their own contribution in the terms of how
it will combine with others’ contributions (Gallotti & Frith, 2013). Another perspective
on the processes underlying interpersonal coordination derives from embodied, enactive,
and distributed cognition and dynamical systems theories (Geeves & Sutton, 2014; Leman &
Maes, 2014). By this account, entrainment between individuals occurs spontaneously as a
result of low-level sensory (auditory and visual) couplings, or accommodation (Maes,
2016). For ensemble musicians, this process potentially enables coordination at both local
(note) and global (expressive) levels. Some researchers argue that shared intentions, as
defined by cognitivists, may not be needed for musicians to coordinate their performance
in this way, because coordination can arise independently of such top-down control as
musicians engage in cycles of small-scale responses to the joint output (Schiavio &
Høffding, 2015). Evidence of coordinated improvised performance in the absence of
preplanned structures has been observed in both music (Canonne & Garnier, 2015) and dance
domains (Kimmel, Hristova, & Kussmaul, 2018), suggesting that emergent coordination can
indeed occur in artistic contexts. MacRitchie, Varlet, and Keller (2017) propose that
representational and entrainment processes may run in tandem, with one or the other
exerting a dominant influence on behaviour depending on the performers’ familiarity with
each other’s roles in the performance. For example, in the early stages of rehearsal,
ensemble members may be unsure of how each other will interpret an unfamiliar piece, and
representational processes may dominate as they try to establish a shared interpretation.
Jointly rehearsing a new piece was the task given to participants in the current study. As
they rehearsed, their familiarity with each other’s playing increased and they established
shared intentions for how the piece should sound, potentially reducing the likelihood that
they would have to communicate individual intentions in order to coordinate their
performance. One of the specific hypotheses we tested was whether performers would spend
less time watching each other as the rehearsal progressed. Such a finding would suggest
that gaze is largely intention-driven during the early stages of rehearsal, and decreases
once performers are more certain of how each other intends to play. The opposite finding –
an increase in partner-directed gaze across the rehearsal (already observed in trios; see
Vandemoortele et al., 2018) – would suggest that familiarity with the music and with a
shared, practiced interpretation encourages the use of engagement-driven gaze.

<hs>  Influences on gaze behaviour</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

With these perspectives in mind, our study considered the possibility that eye gaze serves
multiple communicative functions during ensemble performance – specifically, that it is
primarily a means of affirming co-performers’ attention and engagement, and secondarily a
means of ascertaining co-performers’ intentions. Engagement-driven gaze, which allows for
the exchange of subtle attention, expressive, and movement-related signals, may help to
support entrainment processes. Intention-driven gaze, in contrast, which reflects a drive
to exchange intentions that would not otherwise be shared, may help to support
representational processes. Much of the research on visual interaction during ensemble
performance focuses on musicians’ body gestures. The questions addressed include how
timing information might be encoded in these gestures, and how well other musicians are
able to synchronize their own gestures with those they observe (Bishop & Goebl, 2017,
2018; Wöllner & Cañal-Bruland, 2010; Wöllner, Parkinson, Deconinck, Hove, & Keller, 2012).
The assumption behind these studies is that musicians choose to attend to each other’s
gestures to obtain information that might facilitate coordination. In particular, a
performer who is assuming a “follower” role might monitor the performer who is assuming a
“leader” role for gestural cues. The current study investigated whether patterns of
partner-directed gaze relate to performers’ assumption of leader/follower roles. Research
has already shown that leader-follower relationships emerge among ensemble members
(Badino, D’Ausilio, Glowinski, Camurri, & Fadiga, 2014; Timmers, Endo, Bradbury, & Wing,
2014), and that these relationships are reflected in the amount of time that performers
spend looking towards one another – when leader/follower roles are assigned, followers
look more towards leaders than vice versa (Kawase, 2014a). Many factors contribute to the
emergence of leader-follower relationships in musical duos, some relating to genre
conventions (e.g., in Western classical music, the performer playing the solo or melody
typically leads) and others relating to social factors (e.g., relative skill levels of the
performers, personality traits, etc.). As a contrast to previous studies in which
leader/follower roles were assigned, we tested specifically whether leader-follower
relationships that are implied by piece structure (i.e., melody vs. accompaniment
assignments) influence gaze patterns. If performers were to watch their partner more when
following (playing accompaniment) than when leading (playing the melody), it would suggest
the use of gaze as a means of obtaining information about the leader’s intended
interpretation. Our hypothesis was that leader/follower relationships might be reflected
in gaze behaviour during some parts of a performance (e.g., during periods of high
temporal instability), but not during others (e.g., during periods with regular timing),
indicating an interaction with musical structure. Musicians’ tendency to visually monitor
each other’s attention and engagement was likewise expected to rise and fall across the
course of a performance. To assess this tendency, we tested whether performers tended to
look more towards their partners’ face than towards their partners’ bodies or instruments.
In cases where instrument motion is likely to be informative (e.g., during clarinet
performance), a preference for looking at the face would suggest that gaze is being used
to communicate information about attention. We also considered how often partner-directed
gaze was bidirectional, rather than unidirectional. During moments of bidirectional gaze,
information flows both ways simultaneously – from primo to secondo and from secondo to
primo – which, in addition to giving both performers visual access to each other’s body
gestures and facial expressions, communicates to each performer that they are the focus of
their partner’s attention. Direct eye gaze is treated specially by the human brain,
affecting the way people perceive others and judge their mental capabilities. Faces with
direct gaze are judged as belonging to people with more sophisticated mental faculties
than faces with averted gaze, for instance, possibly because direct gaze acts as a cue to
impending social interaction and prompts people to expend more effort in considering
others’ internal experiences (Khalid, Deska, & Hugenberg, 2016). In certain types of
interaction, gaze is drawn to others’ eyes and faces. For example, deaf viewers have been
found to focus mostly on signers’ faces when watching sign language video clips,
processing hand and arm movements largely with their peripheral vision (Muir & Richardson,
2005). Face-directed gazing during signing allows the viewer to detect facial expressions
and lip movements, and it allows the signer see that the viewer is paying attention. Along
the same lines, studies of spoken conversation have shown that speakers expect listeners
to confirm their attention through auditory or visual backchannelling, and will
periodically pause and look towards their listeners, seeking such a response (Bavelas,
Coates, & Johnson, 2002). Direct eye gaze may likewise contribute to backchannelling
during music ensemble performance. More broadly, in non-musical forms of interaction,
perceived gaze direction has been shown to help people track each other’s attention. A
study by Khoramshahi, Shukla, Raffard, Bardy, and Billard (2016) provides a clear example.
In this study, human participants collaborated with an avatar on the “mirror game”, a task
in which two participants, while facing each other directly, move a pair of sliders along
horizontal tracks to produce creative but synchronized patterns of motion. Participants
were told to follow the avatar’s lead. When the avatar provided anticipatory gaze cues
(i.e., began looking in the direction of its next movement just before initiating the
movement), leader-follower synchronization was better than when the avatar visually
tracked its hand movements (i.e., always looked directly at its moving hand). Anticipatory
gaze cues, therefore, allowed participants to account for the avatar’s intentions in their
own action planning. We hypothesized that ensemble musicians monitor each other’s gaze
direction when it is possible to do so, possibly because tracking fluctuations in each
other’s attention – as well as receiving backchannelling signals – helps to support
emergent coordination.

<hs>  Current study</hs>
  ~~~~~~~~~~~~~

This study investigated patterns of eye gaze during duo piano and clarinet performance.
Motion capture and eye tracking were used to map musicians’ body gestures and gaze
patterns as they rehearsed and performed a new duet piece. The piece was composed
specifically for this study and contained a number of potential challenges for
coordination (see Section 2.3). Duos recorded four full performances of the piece between
periods of free joint rehearsal. The final performance was given with no visual contact
between performers; the other performances and free rehearsal periods were completed under
normal visual contact conditions. Eye gaze data were analysed to determine when and how
much musicians looked towards their co-performers. Motion data are presented in Bishop and
Goebl (submitted for publication). Patterns of partner-directed eye gaze were expected to
distinguish conditions that encourage the use of visual interaction for confirming co-
performers’ attention and engagement (engagement-driven gaze) from the use of visual
interaction for communicating individual intentions (intention-driven gaze). To this end,
we assessed the potential effects of rehearsal, leader/follower relations, and musical
structure on the amount of time that musicians spent watching their partners. It should
also be noted that glances from one performer to another can be multifunctional, enabling
a performer to gain information about their co-performer’s attention and intentions
simultaneously. For this reason, the manipulation of musical structure was particularly
important, as we expected temporal uncertainty resulting from imprecisely notated timing
to encourage intention-driven gaze in particular. Engagement-driven gaze, in contrast,
could occur at any time, and was not expected to account for heightened tendencies for
partner-directed gaze at moments of temporal instability. As evidence of engagement-driven
gaze, periods of bidirectional gaze were expected to occur throughout performances.
Musicians were expected to look at each other even during temporally stable passages and
during performances that followed the rehearsal period. For clarinet duos, partner-
directed gaze was also expected to target the face more often than the instrument/body,
even though clarinet bell movements are known to carry information relevant to expression
and timing (Wanderley, Vines, Middleton, McKay, & Hatch, 2005). As evidence of intention-
driven gaze, musicians were expected to look towards their partner when uncertain of their
partner’s intentions – for example, at piece onset, during periods of temporal instability
in the music, and at the start of the rehearsal period. They were also expected to look
more towards their partner when playing an accompaniment passage (i.e., when following)
than when playing a melody passage (i.e., when leading).

<hs>  Design</hs>
  ~~~~~~

The effects of three main within-subject independent variables were tested: (1) piece
structure, (2) rehearsal time, and (3) leader/follower roles. The structure of the duet
piece is outlined below (see Section 2.3). As part of the analysis procedure, the piece
was segmented into windows of interest, and performers’ behaviour was compared between
windows (piece structure variable). The three performances recorded with normal visual
contact were given before, partway through, and immediately following a rehearsal period
(rehearsal time variable). Instrument pairing (piano-piano or clarinet-clarinet) was
manipulated between subjects. Our primary dependent variable was the amount of time (i.e.,
percentage of recorded gaze samples) that performers spent looking at their partner. For
clarinettists, as a secondary dependent variable, we also compared the percentage of time
dedicated to face-directed versus body/instrument-directed gaze.

<hs>  Stimuli and equipment</hs>
  ~~~~~~~~~~~~~~~~~~~~~

A duet was composed for the experiment by the second author, a pianist and composer with
14 years of musical training. Some excerpts from the piece are given in Fig. 1. Though
primo and secondo parts were not technically very difficult, the piece was meant to be
challenging for a duo to coordinate. There were several changes in meter and tempo, some
unusual meters (e.g., 5 + 7/8), one unmetered section, and sections with accent patterns
that the primo and secondo were intended to synchronize. The piece was initially written
as a piano duet, then arranged for two clarinets with the aid of a professional
clarinettist. See the Appendix for the full piano score. Performers wore SMI ETG 2
wireless glasses, through which eye gaze was tracked at 120 Hz (Fig. 2). These glasses
track gaze with up to 0.5° accuracy over all distances (SensoMotoric Instruments (SMI),
2017). The glasses cannot be worn over normal prescription glasses, which create too much
interference; however, magnetic snap-on corrective lenses were available for participants
requiring a distance correction (within the prescription range of −4.0 to +4.0). The
glasses were fitted with markers for detection by the motion capture system. Two markers
were placed on top of the glasses frame, at the corner of each lens. The third marker was
placed on a small stick, which was attached to the glasses frame with dental putty and
extended down from the left arm of the glasses. A 10-camera (Prime 13) OptiTrack motion
capture system was used to track performers’ upper body movements, recording at a rate of
240 frames per second. Each performer was fitted with 25 reflective markers. Additional
markers (3) were fixed to the eye tracking glasses, the corners of the music scores (4),
and, in the case of clarinet duos, both performers’ instruments (4). Eye gaze data for the
two performers were collected with separate laptops, both of which were connected to an
OptiTrack eSync 2 device (see Fig. 2), which transmitted TTL triggers from the motion
capture software to the eye tracking software at the start and end of each motion capture
recording. These triggers were logged in the gaze data files as a numerical variable,
allowing us to retrospectively align eye gaze and motion capture data by trimming data
files to exclude observations outside the trigger range. Pianists performed on Yamaha
Clavinovas, from which audio and MIDI data were collected via a Focusrite Scarlett 18i8
sound card and recorded on separate tracks in Ableton Live. Clarinettists performed on
their own instruments, and their audio was likewise recorded in separate tracks, using DPA
d:vote 4099 clip-on microphones. A clapboard was placed within range of an additional room
microphone and within view of the OptiTrack and SMI cameras and struck once at the start
and end of each recording. This provided a synchronization stimulus, recorded on all
devices, that allowed us to align audio/MIDI with motion capture and eye gaze data.

<hs>  Procedure</hs>
  ~~~~~~~~~

At the start of the session, performers were presented with the piece and randomly
assigned either the primo or secondo part. They were told that our aim was to investigate
performer interaction during rehearsal of unfamiliar music. Duos were asked to practice
the piece in preparation for making some high-quality recordings at the end of the
session. They were not required to memorize the music. Performers were positioned so that
they faced each other, roughly 1.5 m apart. Clarinettists played standing without any
specific instruction on how to orient themselves, so they had more freedom to move around
than did pianists (e.g., see how the clarinettists’ scores ended up at an angle to each
other in Fig. 3b). An initial (sight-read) performance was recorded first, with performers
encouraged to ignore errors and play through as much of the piece as possible without
stopping. This performance was followed by up to 20 min of free joint rehearsal. (Some
duos required more practice time than others. To prevent duos from reaching peak
performance by the end of the first rehearsal, duos who were progressing quickly were
asked to stop when the experimenters could hear that they still had some passages to work
out.) A second full performance was then recorded, followed by up to 20 more minutes of
rehearsal. Finally, two “polished” performances were recorded, one with visual contact
between performers, and then one without (always in that order). Musicians also completed
a short questionnaire on their musical background and answered a few debriefing questions
about their perceptions of the experiment.

        <hss>Note onsets</hss>

        Note onsets in clarinet performances were identified manually using waveform and
        spectrogram information. For piano performances, MIDI data collected from the
        Clavinovas were matched to the score using the score-performance matcher developed
        by Flossmann, Goebl, Grachten, Niedermayer, and Widmer (2010). This system pairs
        performed pitches with score notes based on pitch sequence information,
        disregarding the timing. Incorrectly performed pitches (additions and
        substitutions) are omitted, so the resulting matched performance profile includes
        only correctly performed notes.

        <hss>Eye gaze</hss>

        Vectors indicating direction of gaze for the right eye of each participant were
        exported from the eye tracking software. For each sample of eye gaze data, a “gaze
        target” was identified. For pianists, gaze targets took one of three values,
        indicating whether the participant was looking towards the score (“score”), the
        other performer’s face (“face”), or elsewhere in the room, including towards the
        piano keys (“other”). For clarinettists, gaze targets could take an additional
        value, indicating whether the participant was looking at the other performer’s
        upper body/instrument (“instrument”) (Pianists were only able to see each other’s
        faces over their scores, and clarinettists’ views of each other’s lower bodies
        were largely occluded by the music stands). It was necessary to allow for small
        degrees of imprecision in the gaze vector coordinates obtained by the glasses
        resulting from calibration errors, which sometimes occurred over the course of the
        1-h recording session (e.g., if participants bumped or shifted the glasses
        following the initial calibration step). To account for such errors, we expanded
        the region of each gaze target by a small amount so that gaze vectors that fell
        slightly outside a region would be counted as intersecting that region. For all
        duos, markers indicating the sides of the head were adjusted outwards by 1.4 times
        the length of the vector between them; the same was done for the markers
        indicating the left and right shoulders, and for the markers outlining the
        clarinets. The assumption here was that participants were unlikely to spend time
        watching anything but each other, the score, and their instruments, given their
        unfamiliarity with the music. Thus, a participant who appeared to be staring at a
        spot on the wall just to the left of their co-performer’s head was most likely
        actually looking at their co-performer’s face. We developed an automated procedure
        for identifying gaze targets, which involved remapping gaze vector coordinates
        into the motion capture space. As a first step, motion capture and eye tracking
        data were temporally aligned using the recorded trigger values (see Section 2.3),
        and linear interpolation was used to resample gaze vector profiles at 240 Hz, the
        sampling rate of the motion capture recordings. Finally, we tested whether the
        corrected gaze vector intersected with the score, the other performer’s face, or,
        for clarinettists, the other performer’s body or instrument. Fig. 3 provides
        visualizations of these tests. Scores were defined as four-sided polygons using
        markers that had been placed in the corners. Performers’ faces were defined as
        four adjacent triangles using markers located on the top and sides of the head, on
        the chest, and on the shoulders. Clarinettists’ upper bodies were designated by
        five adjacent triangles, using markers located on the shoulders, chest, upper
        arms, and waist. Clarinets were defined as four-sided polygons, using markers
        placed near the mouthpiece and near the bell. A sample video showing the gaze
        behaviour of two pianists during a final performance can be viewed in the
        supplementary files.

        <hss>Missing data</hss>

        Eye gaze data are not reported for two pianists and two clarinettists, for whom we
        were unable to get reliable recordings. (The glasses are sometimes unable to track
        pupil position; for example, if the participant is squinting, has swelling around
        the eyes, or has a flatter nose/narrower eyes than are typical for people of
        European descent.) Motion capture data was also lost for one clarinet duo and
        partially lost for a second clarinet duo, due to file corruption.

<hs>  Differences in temporal stability across piece sections</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

One of our primary hypotheses was that the percentage of time that performers spent
watching each other would increase in passages where timing information was loosely-
defined by the score (and the chances of performers’ interpretations diverging was
greater) and decrease in passages with less temporal ambiguity. We refer to passages with
loosely-defined timing information as “temporally unstable”, because variability in
performance timing was expected to increase. To confirm, analyses of (1) tempo variability
and (2) primo-secondo note asynchronies were conducted for piano duo performances. The
analyses were only run on the MIDI data acquired from pianists since note onsets in
clarinet performances were identified manually, and therefore less precise. The piece was
divided a priori into sections, with boundaries placed where they made musicological sense
(i.e., when meter and texture changed). The first 8 bars (“entrance”), the final 10 bars
(“ending”), and the unmetered section from the middle of the piece (“unmetered”) were
expected to invoke greater temporal instability than the other, more regularly-timed
sections (“regular”). Interbeat intervals (IBIs) were taken as a measure of performance
tempo using averaged primo-secondo note onsets. As a measure of within-performance tempo
variability, the series of IBIs was differenced once (Fig. 4). The resulting series
indicated how IBI durations changed across the course of the piece: high values reflected
large note-to-note changes in tempo, while small values reflected a more consistent tempo
over time. The increased tempo variability and note asynchrony that occurred in the
unmetered section of the piece confirms our expectation that timing would be less stable
during this passage. In the following sections, we test for effects of piece structure on
eye gaze behaviour with the expectation that this section in particular will prompt visual
interaction between performers.

<hs>  Effects of piece structure, rehearsal time, and instrument on unidirectional partner-directed eye gaze</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fig. 6 shows the percentage of time per beat, averaged across individual performers, that
gaze vectors intersected with a co-performer’s face, body, or instrument – that is, the
average percentage of time for which unidirectional partner-directed gaze occurred.
Results are given separately for clarinettists and pianists, as some differences were
observed between instrument groups (see below). Thus, performers spent more time looking
at each other during periods of temporal instability than during periods of regular
timing, in line with the hypothesis that uncertainty about co-performers’ intended timing
would prompt visual interaction. On the other hand, they spent more time watching each
other after rehearsing than before, indicating an increase in visual interaction once they
had established shared intentions regarding how the piece should sound. Differences
between sections were stronger for clarinettists than for pianists.

<hs>  Effects of leader/follower roles on unidirectional partner-directed eye gaze</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Sections of the piece in which leader/follower roles were implied by a
melody/accompaniment structure were identified a priori. Primos led a total of 27 bars,
distributed across entrance (4 bars), unmetered (half of the section, counted as 1 bar),
regular (12), and ending (10 bars) sections, while secondos led a total of 14 bars,
distributed across entrance (4 bars), unmetered (half of the section, again counted as 1
bar), regular (1 bar), and ending (8 bars) sections.

<hs>  Effects of piece structure and rehearsal time on face- versus body/instrument-directed eye gaze among clarinettists</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Pianists in this experiment were only able to see each other’s faces over the top of their
music stands, but clarinettists were standing and able (at least partially) to see each
other’s upper bodies and instruments. So, for clarinettists, we tested for differences in
how much time they spent looking at their partner’s face versus their partner’s
body/instrument (Fig. 9).

<hs>  Effects of piece structure, rehearsal time, and instrument on bidirectional partner-directed eye gaze</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fig. 10 shows the average percentage of time per beat that both performers’ gaze vectors
simultaneously intersected each other’s face, body, or instrument – the average percentage
of time for which bidirectional partner-directed gaze occurred. Thus, bidirectional gaze
occurred rarely, but varied according to piece structure and rehearsal time similarly to
unidirectional gaze – occurring more often during moments of temporal instability, and
increasing as performers became more certain of how they wanted the piece to sound. As was
the case for unidirectional gaze, differences between piece sections were greater for
clarinettists than for pianists.

<h>DISCUSSION</h>
----------

This study assessed the patterns of unidirectional and bidirectional eye gaze that
occurred during duo performance of an unfamiliar piece, before and after brief periods of
rehearsal. Piano and clarinet duos recorded four performances of a piece – one before, one
partway through, and two at the end of a 20–40 min rehearsal session. Piece structure and
rehearsal time were found to influence the percentage of performance time during which
uni- and bidirectional gaze occurred. Specifically, musicians looked more often at their
partners during periods of temporal instability than during periods of regular timing,
suggesting the use of intention-driven gaze. They also spent more time watching each other
after rehearsing than before, suggesting an increasing role for engagement-driven gaze as
they learned the music. Clarinettists, finally, exhibited a preference for face-directed
rather than body-directed gaze during the entrance section of the piece. Each of these
observations is discussed in greater detail below. One of our central hypotheses regarding
intention-driven gaze was that moments of temporal instability would prompt performers to
interact visually, and this hypothesis was confirmed. Performers spent a greater
percentage of their time watching each other during the unmetered section than during
regularly-timed sections. This finding is in line with the idea that ensemble musicians
exchange visual signals when temporal coordination is threatened by ambiguity in the
timing information given by a musical score (Bishop & Goebl, 2015; Kawase, 2014a, 2014b).
More broadly, it aligns with research suggesting that, on interpersonal coordination
tasks, people draw flexibly on information from different modalities, depending on which
modality seems most reliable at a given moment (Elliott, Wing, & Welchman, 2010; Hove,
Iversen, Zhang, & Repp, 2013). During the unmetered section of the piece, temporal
ambiguity came from both the absence of a notated meter – which encouraged high note-to-
note variability in tempo – and the presence of long held notes, including the notes with
fermatas shown in Fig. 1. As a side note, we should mention that several (though not all)
duos deliberately integrated visual cues into their performance routine during this
section of the piece, following verbal discussion (e.g., “watch me here, and I’ll give the
cue”). This observation is in line with findings reported by Williamon and Davidson
(2002), who also found musicians to deliberately integrate visual cues into a performance
plan in this way. During the entrance section, the primary instance of temporal ambiguity
came at the moment of piece onset, which the primo and secondo were intended to
synchronize. Both uni- and bidirectional gaze peaked during the seconds just prior to
piece onset. On one hand, it is unsurprising that performers watched each other closely as
they prepared to coordinate the first chord of the piece, given the absence of prior
audio. On the other hand, it is interesting to note the peak in bidirectional gaze at this
point. A peak in uni- but not bidirectional gaze would have suggested that one performer
visually monitored the other for information about when to begin. The peak in
bidirectional gaze that we observed instead suggests that performers monitor each other.
In doing so they may exchange a range of information about their shared focus of
attention, their joint willingness to interact, and their intended timing of the first
notes of the piece. Uni- and bidirectional gaze both also peaked in the beats leading up
to the final chord of the piece. This was particularly the case for clarinettists. Many
duos gradually slowed their tempo in the last notes of the piece, employing the well-known
expressive device referred to as the “final ritard” (Friberg & Sundberg, 1999; Honing,
2003), but overall, there was less temporal ambiguity in this section of the score than,
for example, in the unmetered section. We would therefore suggest that the increase in
visual interaction at the end of the piece reflects performers’ attempts to monitor each
other’s attention, rather than exchange specific information about their intended timing.
For pianists, there was also an unexpected uptake in unidirectional gaze during one of the
regularly timed sections of the piece. This uptake occurred in the third bar (53) of the
line shown in Fig. 1b (around beat 380 in Figs. 6 and 10). It seems unlikely that
performers would be prompted to look to each other for timing cues during this passage, as
the timing is relatively unambiguous. Rather, we would speculate that the uptake in
partner-directed gaze relates to the positioning of the passage on the score: this line
appeared at the top of the page that stood in the center of the music stand, only a short
vertical distance away from the co-performer’s face. It would have been easier for
performers to glance at their partners while playing this line than while playing most
other parts of the piece, which would have required the eyes to traverse a greater
distance. The piano score spanned six pages, which we fixed together as two groups of
three, so that there was only one page turn at the end of page 3. Beat 380 fell at the top
center of page 5. A corresponding, though smaller, uptake can be seen at the start of the
second regularly-timed section on score page 2 (see third dotted vertical line in Fig. 6),
which likewise fell at the top center of the music stand, though this uptake could also be
attributed to the change in meter that occurs at this spot. Uptakes in partner-directed
gaze did not occur for clarinettists at either location, likely because they were free to
reposition themselves (since they were standing), and often ended up at an angle rather
than facing each other directly (as in Fig. 3b). The fact that pianists chose to glance at
their partner when it became easier to do so is telling – it suggests a propensity to
engage visually even when coordination does not depend on it. We also tested the
hypothesis that performers would look less at their partners after rehearsing than before.
This is what we would expect to see if visual interaction were primarily a means of
communicating individual intentions. Performers’ familiarity with each other’s intentions
would increase as they established a shared interpretation of the piece, reducing their
reliance on visual cues. Challenging this hypothesis, however, the results showed an
increase in partner-directed gaze with rehearsal. It seems that performers chose to engage
visually with each other once they were familiar enough with the score to be able to
glance away from it. Note synchronization was maintained in the final performance, even
though performers could not see each other, indicating that duos do not require visual
contact in order to coordinate temporally – in line with prior research (e.g., Bishop &
Goebl, 2015; Fulford et al., 2018). The increase in partner-directed gaze that occurred
across the first three performances thus indicates a desire to interact visually when
doing so is not necessary to maintain coordination. Such a finding is in line with the
hypothesis that gaze can be engagement-driven – that musicians interact visually in order
to monitor each other’s attention and engagement. It might also be that performers seek
additional means of interaction to ensure coordination once they have specific
expectations for how the piece should sound, and what each performer should contribute.
For clarinettists, we found a preference for face- over body-directed gaze only in the
entrance section of the piece. We had hypothesized that clarinettists would spend more
time looking at each other’s faces than each other’s bodies if their aim was to monitor
each other’s facial expressions and gaze direction; in contrast, greater focus on the
body/instrument might indicate an attempt to monitor gestures involved in sound-
production, including fingering and breathing. Our observations suggest that clarinettists
were compelled to monitor each other’s expressions and attention as they coordinated the
entrance of the piece. The lack of meaningful results in other conditions could be
partially attributable to imprecision in the identification of gaze vectors that
intersected near the borders of the face and instrument regions. A possible consequence is
that performers who were watching their partner’s instrument close to the mouthpiece might
sometimes have been categorized as watching their partner’s face. The best fix to this
issue would have been periodic recalibration of the glasses throughout the 1-h recording
session. Another likely explanation is the way clarinettists were positioned in the
recording space in relation to each other. Their view of each other was partially blocked
by the music stand and score, and depending on how they chose to stand (e.g., close to the
music stand vs. further away; facing their partner directly vs. at an angle), how high
they had adjusted the music stand, how tall they were compared to their partner, and how
much they and their partner moved, their views of each other were sometimes (variably,
throughout the performance) partially occluded. We chose to prioritize naturalistic
playing conditions by giving performers some freedom of movement, but a more controlled
recording setting might yield a clearer identification of which cues (face or body)
clarinettists attend to while performing. We had hypothesized that performers might spend
more time watching their partner when playing accompaniment passages (following) than when
playing melody passages (leading). This hypothesis was not confirmed; partner-directed
gaze was not reliably influenced by the leader/follower roles implied by
melody/accompaniment relationships in the score (though there was a nonsignificant
tendency for performers to watch their partners more when following than when leading, in
all but the ending section). This lack of effect is in contrast to the idea that followers
visually monitor leaders for cues indicating how to play. Instead, it seems that both
leaders and followers have reason to watch each other. The lack of effect here is at odds
with prior research that has shown followers to look more towards leaders than vice versa
(Kawase, 2014a, 2014b), possibly because of differences in experimental design. Kawase’s
participants were assigned leader and follower roles, while our participants were not
given any explicit instruction regarding who should lead or follow. We were instead
interested in whether gaze patterns would be affected by the leader/follower relationships
that emerge naturally during duo performance, with the acknowledgement that these
relationships vary within and between performances and are influenced by numerous factors,
including piece structure, performance conventions, and the social and personality
dynamics that arise between the performers. Future research might investigate whether some
of these other factors have a stronger influence on gaze behaviour. It is important to
acknowledge limits to the generalizability of our results. We tested a specific type of
performance situation: participants were rehearsing, not performing for an audience; the
music was unfamiliar, not previously practiced; and participants were positioned in the
recording space in a way that encouraged visual contact. Changes to any one of these
factors would likely influence gaze behaviour. Skilled musicians are flexible in their
abilities to draw cues from their co-performers’ audio/visual signals, and readily adapt
to changes in playing conditions (Bishop & Goebl, 2015; Glowinski, Bracco, Chiorri, &
Grandjean, 2016). As such, there is no single pattern of interactive or communicative
behaviours that could be said to enable duo performance across different playing
conditions. The patterns of gaze behaviour that were observed here are interesting
primarily because of what they imply about how musical interaction unfolds. Our results
imply that duo musicians who have full access to each other’s audio signals are prompted
to supplement their audio interaction with interaction via a second modality (vision) when
they want confirmation of piece timing or their partner’s focus. Future research might
investigate how interaction techniques differ across performance conditions. The design of
this experiment rests on the assumption that musicians who are learning a new piece from
the score will have to focus their visual attention on the score most of the time. The
fact that they have few opportunities to look elsewhere makes their partner-directed
glances meaningful – they would not divert their gaze away from the music unless they had
reason to do so. Without such a demand on their visual attention (e.g., if the music were
memorized or the task was to improvise), it would not be possible for us as experimenters
to deduce meaning from their partner-directed gaze. In this paper, we have attributed
meaning to participants’ partner-directed glances according to the conditions in which
they occur. First, we have argued that partner-directed glances occurring in moments of
potential temporal variability likely reflect an effort to confirm shared expectations
regarding performance timing. In such moments, performers may be watching for cues
indicating their partner’s intended timing. In interpreting some of our other findings, we
have suggested that performers keep track of each other’s attention and engagement by
visually monitoring gaze direction, body movements, and facial expressions. The frequency
of bidirectional gaze and the increase in partner-directed gaze that occurred with
rehearsal were observations that we took as evidence that performers choose to visually
monitor each other even when coordination is not threatened by uncertainty over timing.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

The results of this study suggest that duo musicians seek visual interaction with their
co-performer, particularly – but not exclusively – when coordination is threatened by
temporal instability. Performers seem to monitor each other for timing cues when uncertain
of whether temporal coordination will be successful. Visual interaction also increases as
performers grow more familiar with the piece, which may reflect an attempt to engage with
each other in a way that enables higher levels of collaboration. Gestural cues are an
important source of information as performers interact visually, but a characterization of
performers’ communicative gestures is still missing from the literature. Our ongoing
investigation of the motion data collected as part of this study examines how performers
move when they know that a co-performer is watching, where in the performance explicit
cueing gestures are given, and how performance gestures evolve across rehearsals. In the
literature, it has been hypothesized that emergent coordination between ensemble members
is supported by low-level sensory couplings (e.g., Maes, 2016). Visually monitoring co-
performers should facilitate such couplings by relaying information about body movement
and facial expressions. Furthermore, performers who are able to visually confirm each
other’s attention and engagement might feel more engaged in the collaborative task
themselves, and perhaps more willing to take creative risks. Along these lines, an
interesting continuation of this research would be to test the contribution of visual
interaction to the quality of ensemble musicians’ performance experiences and,
importantly, to the occurrence of group flow. The term group flow describes an
intrinsically-rewarding state of intense focus, effortlessness, and perceived success that
is shared among collaborating members of a group (Cochrane, 2017; Hart & Di Blasi, 2015;
Sawyer, 2006). Reports from ensemble musicians suggest that a feeling of deep
connectedness between co-performers is critical to group flow (Hart & Di Blasi, 2015).
Visual interaction could help to support such feelings of connectedness.


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----------

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<ART>Family-centered practices and the parental well-being of young children with disabilities and developmental delay
================================================================================

Authors: Joana Maria Mas, Carl J. Dunst, Anna Balcells-Balcells, Simon Garcia-Ventura, Climent Giné, Margarita Cañadas
DOI: 10.1016/j.ridd.2019.103495
Year: 2019
ASJC codes: 3203, 3204
Keywords: Family-centered practices, Parenting beliefs, Psychological well-being, Self-efficacy beliefs, Structural equation modeling

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Research evidence from studies in North America on the relationships between family-centered practices, parents’ self-efficacy beliefs, parenting confidence and competence beliefs, and parents’ psychological well-being was used to confirm or disconfirm the same relationships in two studies in Spain. Aims: The aim of Study 1 was to determine if results from studies in North America could be replicated in Spain and the aim of Study 2 was to determine if results from Study 1 could be replicated with a second sample of families in Spain. Methods and procedures: A survey including the study measures was used to obtain data needed to evaluate the relationships among the variables of interest. The participants were 105 family members in Study 1 and 310 family members in Study 2 recruited from nine early childhood intervention programs. Structural equation modeling was used to test the direct and indirect effects of the study variables on parents’ well-being. Outcomes and results: Results showed that family-centered practices were directly related to both self-efficacy beliefs and parenting beliefs, and indirectly related to parents’ psychological well-being mediated by belief appraisals. Conclusion and implications: The pattern of results was similar to those reported in other studies of family-centered practices. Results indicated that the use of family-centered practices can have positive effects on parent well-being beyond that associated with different types of belief appraisals.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPER ADDS?</h>
---------------------

This paper adds to our understanding of how the effects of family-centered practices can
be traced to more positive and less negative parent psychological well-being.
Specifically, the results showed that how early childhood intervention practitioners
interact with families and provide support is directly related to both parents’ self-
efficacy beliefs and parenting beliefs and indirectly related to parent well-being
mediated by self-efficacy beliefs. In turn, positive parenting beliefs were related to
parents' psychological well-being. This research illustrates how the complex relationships
among the variables in the study could be identified as evidenced by the direct, indirect,
and total effects of the predictor variables on both belief appraisals and parent well-
being. This complexity has implications for both developmental disabilities researchers
and ECI practitioners in order to understand how professional practices have positives
consequences for improving family functioning.

<h>INTRODUCTION</h>
------------

The birth of a child with an identified disability or condition, and the rearing of a
child with a developmental delay, is two life events that can and often do have
deleterious effects on parental psychological health and well-being (Koehler, Fagnano,
Montes, & Halterman, 2014; Schwarzer & Schulz, 2003; Weekes, 1999). Research indicates
that parents of young children with disabilities or delays often experience increased
stress (Innocenti, Huh, & Boyce, 1992; Smith, Oliver, & Innocenti, 2001) and attenuated
psychological well-being (Barlow, Cullen-Powell, & Cheshire, 2006; Raina et al., 2005) in
the absence of effective coping mechanisms and social support (Hassall, Rose, & McDonald,
2005; Krakovich, McGrew, Yu, & Ruble, 2016; Trute, Benzies, Worthington, Reddon, & Moore,
2010). In addition to the adverse effects on parental psychological health and well-being,
raising a child with a disability or developmental delay can also have negative effects on
parents’ beliefs about their child-rearing confidence and competence (Gowen, Johnson-
Martin, Goldman, & Applebaum, 1989; Hassall et al., 2005). The more difficult child-
rearing entails, the more parenting confidence and competence is likely to be compromised
(Dempsey, Keen, Pennell, O’Reilly, & Neilands, 2009; Mas, Giné, & McWilliam, 2016). One of
the coping mechanisms that lessen stress and bolsters well-being is self-efficacy beliefs
(D’Amico, Marano, Geraci, & Legge, 2013; Hall, Neely-Barnes, Graff, Krcek, & Roberts,
2012). Self-efficacy refers to “people’s beliefs about their capabilities to exercise
control over events that affect their lives” (Bandura, 1994, p. 71) including efficacy
beliefs about rearing a child with a disability or developmental delay (Hassall & Rose,
2005; Maclnnes, 2009). The stronger perceived self-efficacy, the less negative are the
consequences of adverse life events (Lightsey & Sweeney, 2008). The weaker perceived self-
efficacy, the more negative are the consequences of adverse life events (D’Amico et al.,
2013; Dunning & Giallo, 2012). In addition, the stronger perceived self-efficacy, the more
positive the effects on parenting beliefs (Dunst & Dempsey, 2007) whereas the weaker
perceived self-efficacy, the more negative are the effects on parenting beliefs (Dunning &
Giallo, 2012; Kuhn & Carter, 2006). Two types of self-efficacy beliefs were the focus of
investigation in the study described in this paper: (a) family member control over the
resources and supports from ECI practitioners and (b) parenting beliefs of control over
affecting changes in child behavior. A considerable amount of research indicates that
self-efficacy is related to a host of different psychological and physical health benefits
(DeVellis & DeVellis, 2001; Grob, 2000; O’Leary, 1985), including parenting belief
appraisals and psychological well-being (Nelson, Kushlev, & Lyubomirsky, 2014). Bandura
(1997), for example, noted that “Research…shows that a strong sense of parenting efficacy
yields dividends in the emotional well-being of mothers raising children who present
special difficulties” (p. 191, emphasis added). Parents of young children with
disabilities and developmental delays often come in contact with many professionals as
part of participation in early childhood intervention (ECI) (e.g., Affleck, Tennen, &
Rowe, 1991; Bailey, Hebbeler, Scarborough, Spiker, & Mallik, 2004; Swick, 2004; Woods &
Lindeman, 2008). The ways in which professionals interact with, treat, and provide support
to parents and their children can influence self-efficacy and parenting beliefs in either
positive or negative ways depending on how help is provided. Research indicates that
professionals’ use of family-centered practices (FCPs) is positively related to both self-
efficacy beliefs and parents’ sense of competence and confidence (Dunst, Trivette, &
Hamby, 2007). Practitioners who employ FCPs treat families with dignity and respect; share
information so parents can make informed decisions; acknowledge and build on family member
strengths; actively engage family members in obtaining resources and support; and are
responsive to each families’ changing life circumstances (Dunst & Espe-Sherwindt, 2016;
Dunst, 2002). Dunst and Espe-Sherwindt (2016), in their review of FCPs measures, found
that different measures tend to include two sets of indicators: relational practice
indicators and participatory practice indicators. Relational practices emphasize the use
of relationship-building strategies, active and reflective listening, and practitioner
beliefs about family member strengths and capabilities. Participatory practices emphasize
informed family choice and decision making, active family member involvement in achieving
desired goals and outcomes, and practitioner use of capacity-building help-giving
practices. Research reviews of FCPs studies indicate that this type of help-giving is
related to a host of positive parent, family, and child outcomes, including self-efficacy
beliefs, parents’ sense of confidence and competence, and parent and family psychological
health and well-being (Dempsey & Keen, 2008; Dunst, Trivette, Trivette et al., 2007;
Rosenbaum, King, Law, King, & Evans, 1998). The relationships between FCPs and self-
efficacy beliefs, however, have been found to differ as a function of the targets of
belief judgments (Bugental, Johnston, New, & Silvester, 1998). Family-centered practices
are more highly related to parent belief appraisals of control over practitioner and
program practices and are less strongly related to belief appraisals over life events not
directly influenced by early childhood practitioners (Dunst, Trivette, Trivette et al.,
2007; Dunst, Trivette, & Hamby, 2008). The same is the case for the relationships between
FCPs and parents’ beliefs about their parenting confidence and competence (Dunst,
Trivette, & Hamby, 2006, 2008). Results from these meta-analyses indicate that FCPs are
indirectly related to parenting confidence and competence mediated by belief appraisals of
control over program and practitioner responsiveness to family concerns and priorities.
Based on the relationships among family-centered practices, self-efficacy beliefs,
parenting confidence and competence beliefs, and parental psychological well-being
described above, investigators have developed path analytic models for exploring the
relationships among these variables where hypothesized relationships have been tested
using structural equation modeling (Dunst & Trivette, 2009; Dunst, Hamby, & Brookfield,
2007; King, King, Rosenbaum, & Goffin, 1999; Raina et al., 2005; Trivette, Dunst, & Hamby,
2010). Close inspection of the results in these investigations indicates that FCPs have
positive effects on self-efficacy beliefs where positive self-efficacy beliefs are
associated with positive parenting belief appraisals (confidence and competence) and
psychological well-being. Findings from structural equation modeling (SEM) studies by
Dunst et al. (e.g., Dunst, Hamby et al., 2007, 2009, Dunst, Espe-Sherwindt, & Hamby, 2019;
Dunst, Hamby, & Raab, 2019; Trivette et al., 2010) were used as the foundation for the
studies described in this paper. We used the relationships in those studies to (1) test
the fit of the relationships among the study measures to the model in Figs. 1 and 2
evaluate the pathways of influence in two structural equation modeling studies. Both
studies were conducted in Spain where we determined whether the pattern of relationship
found in structural modeling studies conducted mostly in North America could be replicated
with families in another country. The study was conducted as part of a line of research
and practice on factors facilitating practitioner use of FCPs and the outcomes of these
practices (e.g., Costa, Serrano, Dunst, Mas Mestre, & Cañadas, 2017; Mas et al., 2018;
Serrano, Mas, Canadas, & Gine, 2017). The study hypotheses, and prior research that are
the basis for the pathways of influence, were: Family-centered practices would be directly
related to both self-efficacy beliefs and parenting (confidence and competence) beliefs
(Dempsey & Dunst, 2004; Dunst, Trivette, Trivette et al., 2007; Dunst, Hamby et al., 2007)
and be indirectly related to parenting beliefs mediated by self-efficacy beliefs (2008,
Dunst et al., 2006b). Self-efficacy beliefs of control over practitioner family-centered
practices would be directly related to parenting beliefs (Dunst et al., 2006b) and be
indirectly related to parental well-being mediated by parenting beliefs (Dunst, Hamby et
al., 2007). Parenting confidence and competence beliefs would be directly related to
parental well-being (Young, Karraker, & Lesley, 2006). Family-centered practices would be
indirectly related to parental well-being mediated by both self-efficacy beliefs and
parenting beliefs (Dunst & Trivette, 2009; Trivette et al., 2010). Results from the
different sets of analyses were expected to determine if the pattern of relationships
among the study variables could be replicated between countries and within countries. Our
primary interests were the indirect effect of FCPs on parent well-being mediated by the
different belief appraisals and the extent to which the direct and indirect effects of
FCPs and efficacy beliefs on parent well-being could be replicated as the sine qua non of
scientific research (Francis, 2012; Simons, 2014).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Study participants were recruited from different ECI centers in Spain: three ECI centers
for Study 1 and six ECI centers for Study 2. Tables 1 and 2 show the characteristics of
the study participants, their children and families, and the ECI the children and families
received. Study 1. A convenience sample of 105 family members of children with identified
disabilities and developmental delays receiving ECI and who responded to an invitation to
complete a survey were the Study 1 participants. Most participants were mothers (70%) and
married or living with a partner (87%). Sixty-five (65) percent were between 31 and 40
years of age. A majority of the participants (70%) completed at least a secondary
education. The children’s mean chronological age was 3.73 years (Range = 1–8) where 73%
were boys. The most frequently reported child diagnoses were developmental delays (30%),
Autism Spectrum Disorders (18%), and intellectual disabilities (13%). Study 2. A
convenience sample of 310 family members of children with identified disabilities and
developmental delays receiving ECI and who responded to an invitation to complete a survey
were the Study 2 participants. Most participants were the children’s mothers (80%) who
were married or living with a partner (86%). Fifty-eight (58) percent were between 31 and
40 years of age. Eighty (80) percent of the respondents completed at least a secondary
education. The children’s mean chronological age was 3.42 years (Range 1–6) and 66% were
boys. The most frequently reported child diagnoses were speech and language disorders
(23%), developmental delays (16%), and Autism Spectrum Disorders (13%).

<hs>  Measures</hs>
  ~~~~~~~~

A survey was used to obtain information needed to describe the study participants and
obtain measures of the variables of interest. The survey included both investigator-
developed items and scales previously validated in other studies (e.g., (Trivette & Dunst,
2004) including a study investigating the psychometric properties of Spanish versions of
the scales (Mas et al., 2018). The latter was modeled after instruments used by other
investigators interested in both the psychometric properties of the scale items the
relationships among the variables that were the focus of investigation (e.g., Dunst,
Trivette, & Hamby, 2006).

        <hss>Background information</hss>

        Investigator-developed questions were used to obtain information about the person
        completing the survey, and their child and family receiving ECI. This included
        child age, gender, and their primary diagnosis; the respondent’s age, gender,
        relationship to the child, level of education, employment status, and marital
        status; and family monthly income and number of adults and children in the nuclear
        family. The survey also included questions about the frequency of intervention and
        the number of months of receiving ECI. Each child’s primary caregiver completed
        the survey so that there was only one survey for each household.

        <hss>Family-centered practices</hss>

        We used the Spanish version (Mas et al., 2018) of the Family-Centered Practices
        Scale (Dunst & Trivette, 2003) to assess practitioners’ use of FCPs. This scale is
        a parent-completed instrument that assesses the degree to which professionals with
        whom they work employ FCPs. The scale includes six relational FCPs items and six
        participatory FCPs items. The relational FCPs items measure the interpersonal
        relationships between a family member and practitioner (e.g., “The practitioner
        really listens to my concerns and requests”). The participatory FCPs items measure
        practitioner use of capacity-building practices (e.g., “The practitioner helps me
        be an active part of obtaining desired resources and supports”). Participants
        indicate for each item the extent to which ECI staff interacts with and treats
        them and their families on a 5-point scale ranging from 1 = never to 5 = all the
        time. Coefficient alpha for the total scale score was .91 in Study 1 (relational
        subscale alpha = .81 and participatory subscale alpha = .83) and .89 in Study 2
        (relational subscale alpha = .78 and participatory subscale alpha = .83).

        <hss>Self-efficacy beliefs</hss>

        Self-efficacy was measured in terms of the participants’ beliefs about control
        over the types of resources and supports provided by the ECI practitioners. Four
        items were used to measure the respondents’ self-efficacy beliefs where the
        participants were asked to indicate on a 5-point Likert scale the degree to which
        they agreed with different belief statements (e.g., “I am able to decide with
        staff which aspects I want to work for my children and family”). The items were
        obtained from Dunst et al. (2006a). Coefficient alpha was .72 in Study 1 and .75
        in Study 2.

        <hss>Parenting competence and confidence beliefs</hss>

        Parenting beliefs were measured in terms of participants’ judgment of their
        ability to execute childrearing practices. Four items were used to measure the
        respondents’ parenting competence and confidence beliefs. Participants were asked
        to indicate on a 5-point Likert scale the degree to which they agreed with
        different parenting belief statements (e.g., “I am able to provide my children
        activities that help them learn”) (competence) (e.g., “I feel confident in my
        ability to help my son or daughter’s development”) (confidence). The items were
        obtained from Dunst et al. (2006a). Coefficient alpha was .64 in both Study 1 and
        2.

        <hss>Psychological well-being</hss>

        Five items were used to measure the respondents’ psychological well-being.
        Participants were asked to indicate, on a 5-point Likert scale, the degree to
        which they agreed with different well-being statements. Three items asked about
        positive well-being (e.g., “I think that things are going well for my family”) and
        two items asked about negative well-being (e.g., “I feel anxious or upset”). The
        items were obtained from Dunst et al. (2006a). Coefficient alpha for positive
        well-being was .60 in Study 1 and .58 in Study 2. Coefficient alpha for negative
        well-being was .63 in Study 1 and .56 in Study 2.

<hs>  Procedure</hs>
  ~~~~~~~~~

The researchers first contacted three ECI center directors in Study 1 and six ECI center
directors in Study 2 to request their participation in this study and to obtain permission
to contact the families of the children enrolled in this centers. ECI centers were
selected via a criterion of convenience (i.e., centers that had already collaborated in
previous or current projects developed by the same research group). After their approval,
a meeting was held with the practitioners at the centers to explain the study, request
their assistance in terms of explaining the importance of the study to the families,
describe the aim and expected results, and to provide them the study measures to
distribute to families receiving ECI on this services. The information provided to the
parents included the following: A letter describing the study, an informed consent letter,
and the survey described above. They were also provided a telephone number and email
address they could use to contact the investigators if they had any questions or concerns
about the study or if they wanted to withdraw their consent and participation. It was
requested that only one family member (father, mother or other primary caregivers)
complete the FCPs scale and other survey measures within 15 days and return completed
survey and informed consent letter to the center in a sealed envelope to ensure
confidentiality. Once the center had collected the sealed envelopes, the directors sent
the completed scales and surveys to the researchers who prepared the responses for
subsequent analysis.

<hs>  Method of analysis</hs>
  ~~~~~~~~~~~~~~~~~~

Structural equation modeling (SEM) was used to evaluate the effects of family-centered
practices on parental well-being mediated by self-efficacy and parenting belief appraisals
(Jöreskog & Sörbom, 2014). SEMs were used in both Study 1 and Study 2 with both measured
and latent variables to identify the best fitting model. The measured variables were the
sums of the scores for the (a) two family-centered practices measures (relational and
participatory), (b) two parenting belief measures (confidence and competence), and (c) the
two well-being measures (positive and negative). The latent variables included the two
subscale measures for family-centered practices, parenting beliefs, and parental well-
being. SEMs for all combinations of measured and latent variables were run. The fit of the
models to the pattern of relationships among the variables in the models was evaluated
using the root mean square error of approximation (RMSEA), standardized root mean residual
(SRMR), comparative index (CFI), incremental fit index (IFI), and normed fit index (NFI).
The closer RMSEA and SRMR are to zero, and the closer CFI, IFI, and NFI are to one, the
better the fit of the model to the data (Hu & Bentler, 1995). A preponderance of indices
reaching recommended levels was used as the criterion for establishing an acceptable model
fit (Hooper, Coughlan, & Mullen, 2008). Both SEMs included tests for the direct, indirect,
and total effects of the study variables on parental well-being. Effects decomposition
(Kline, 2005) was used to identify the pathways of influence in the models. Standardized
coefficients between contiguous variables were used to test for direct effects and the
products of these coefficients were used to test for indirect effects (Bollen, 1987;
Sobel, 1988). Total effects were determined by the sums of direct and indirect effects.

<h>RESULTS</h>
-------

Table 3 shows the correlations among both the Study 1 and Study 2 measures. All of the
correlation coefficients in both sets of data are statistically significant. The
directions of the effects are also all as expected. Both family-centered practices
measures were positively correlated with the three belief measures (self-efficacy beliefs,
parenting competence beliefs, and parenting confidence beliefs) and positive parental
well-being and negatively correlated with negative parental well-being. The pattern of
relationships between the three belief measures and parental well-being was much the same.
The correlation matrices in both studies were imputed in LISREL for the SEMs.

<hs>  Study 1 analyses</hs>
  ~~~~~~~~~~~~~~~~

The best fitting SEM is shown in Fig. 2. RMSEA was .00 (90% CI = .00–.10), SRMR was .03,
CFI was .99, IFI was .99, and NFI was .95. All five indices met generally agreed upon
thresholds and indicate a good fit of the model to the relationships among the variables
in the model. Three of the five structural coefficients for the direct effects were
statistically significant. The patterns of relationships among the variables in the model
are generally consistent with the study hypotheses as evidenced by effects decomposition.
Table 4 shows the effects decomposition results for the direct, indirect, and total
effects of family-centered practices, self-efficacy beliefs, and parenting beliefs on
parental well-being. As expected, FCPs were directly related to both self-efficacy beliefs
and parenting beliefs. Family-centered practices were also indirectly related to parental
well-being mediated by both self-efficacy beliefs and parenting beliefs. Self-efficacy
beliefs were directly related to parenting beliefs, and indirectly related to parental
well-being mediated by parenting beliefs. Parenting beliefs were directly related to
parental well-being.

<hs>  Study 2 analyses</hs>
  ~~~~~~~~~~~~~~~~

Fig. 3 shows the SEM for the fit of the Study 1 model to the data. RMSEA was .11 (90% CI =
.08–.14), SRMR was .05, CFI was .97, IFI was .97, and NFI was .96. The indices indicate a
reasonably good fit of the model to the data. All of the path coefficients in the model
were statistically significant except for the direct effect between self-efficacy beliefs
and parental well-being. The patterns of relationships were consistent with expectations.
The complete set of direct, indirect, and total effects are shown in Table 4. Family-
centered practices were directly related to both self-efficacy beliefs and parenting
beliefs, and indirectly related to parental well-being mediated by both the self-efficacy
and parenting belief measures. Self-efficacy beliefs were directly related to parenting
beliefs, and indirectly related to parental well-being mediated by parenting beliefs.
Parenting beliefs were directly related to parental well-being.

<hs>  Model comparisons</hs>
  ~~~~~~~~~~~~~~~~~

A comparison of the results from the two sets of analyses found that the indices for the
fit of the models to the data a were more similar than different, and that the indirect
effects of FCPs on parental well-being mediated by both kinds of belief measures (self-
efficacy beliefs and parenting beliefs) were almost identical (β = .37, p <  .001, and β =
.38, p <  .001, respectively in Studies 1 and 2). Closer inspection of the pathways of
influence, however, indicates a few differences in the two sets of analyses. In Study 1,
the influence of FCPs on parenting beliefs was direct (β = .41, p <  .01) but only
marginally indirectly related to parenting beliefs mediated by self-efficacy beliefs (β =
.73 × .21 = .15, p <  .10). In contrast, the relationship between FCPs and parenting
beliefs in Study 2 was both direct (β = .24, p <  .005) and indirect mediated by self-
efficacy beliefs (β = .70 × .54 = .38, p <  .001). There were also differences in the
pathway of influence of family-centered practices on parental well-being. Whereas the
indirect effect of family-centered practices on parental well-being mediated by parenting
beliefs was similar in both Study 1 (β = .41 × .58 = .24, p <  .02), and Study 2 (β =.24 ×
.78 = .19, p <  .005), the indirect effect of family-centered practices on parental well-
being mediated by self-efficacy beliefs through parenting beliefs was significant in Study
2 (β = .70 × .54 x .78 = .29, p <  .001) but not in Study 1 (β = .73 × .21 x .58 = .09, p
>  .10). The patterns of relationships among the variables in Study 1 indicate that the
influence of FCPs on parental well-being is primarily through parenting beliefs. In Study
2, the patterns of relationships among the variables indicate two pathways of influence
between FCPs and parental well-being; one through parenting beliefs, and one through self-
efficacy beliefs and parenting beliefs. Despite the few differences in the sizes of effect
for the relationships among the variables in the two SEMs, the results were more similar
than different as evidenced by the fit indices and effects decomposition results.

<h>DISCUSSION</h>
----------

The studies described in this paper examined the manner in which practitioners’ use of
FCPs was related to parent psychological well-being. More specifically, we evaluated the
relationships between family-centered relational and participatory practices, self-
efficacy beliefs, parenting confidence and competence beliefs, and families’ positive and
negative psychological well-being. Structural equation modeling was used in both studies
to test the fit of a model based on results from previous research on the relationships
among the variables in the model (e.g., King et al., 1999; Thompson et al., 1997; Trivette
et al., 2010). The findings for families in Spain were the same or very similar to those
reported in other studies mostly in North America (e.g., Dunst, Hamby et al., 2007; King
et al., 1999; Thompson et al., 1997). The Study 1 model was used to evaluate the fit of
the data to the SEM in Study 2 for replication purposes. The results provided support for
both the hypothesized direct and indirect effects shown in both Fig. 3 and Table 5. The
findings showed that how practitioners interact with families is directly related to
parents’ self-efficacy beliefs and parenting beliefs and indirectly related to parenting
beliefs mediated by self-efficacy beliefs (Bailey, Nelson, Hebbler, & Spiker, 2007; King
et al., 1999; Trivette et al., 2010). More specifically, our results showed that the more
parents judged the practices of the ECI practitioners as family-centered, the more control
they reported over the supports and assistance received from the practitioners with whom
they worked in a manner identical to that found in other studies (e.g., Dunst, Trivette,
Trivette et al., 2007). Likewise, the more parents perceived control over FCPs, the more
competent and confident was their parenting beliefs (Dunst, Trivette, Boyd, & Brookfield,
1994; Dunst & Dempsey, 2007; Dunst, Hamby et al., 2007). Positive parenting beliefs, in
turn, were related to parents' psychological well-being in a manner similar to what has
been found in other studies (Dunst & Trivette, 2009; Dunst, Hamby et al., 2007; Dunst,
Trivette & Raab, 2013; Trivette et al., 2010). That is, the pathways of influence found in
our study illustrate how the effects of family-centered practices could be traced to more
positive and less negative parent well-being in a manner similar to that found in other
studies (Dunst & Trivette, 2009; Dunst, Hamby et al., 2007; King et al., 1999). The
indirect effects found in Study 2 are consistent with findings in previous research where
the relationships between FCPs and child, parent, and family outcomes have been found to
be mediated by different kinds of belief appraisals in a manner consistent with self-
efficacy theory (Bandura, 1997). Parental attributions -like those investigated in the
present research-have been found in other studies to mediate the relationship between FCPs
and parent well-being (King et al., 1999), child well-being (Dunst & Trivette, 2009),
parent-child interactions (Dunst, Espe-Sherwindt et al., 2019; Dunst, Hamby et al., 2019),
and child behavior and development (Graves & Shelton, 2007; Trivette et al., 2010). The
research described in this paper adds to this evidence base by demonstrating how the
complex relationships among the variables in the study could be identified as evidenced by
the direct, indirect, and total effects of the predictor variables on different mediator
and outcome variables. The manner in which we found FCPs to be directly and indirectly
related to parent psychological well-being illustrate how practitioner help-giving
practices are related to belief appraisals and in turn are related to health-related
outcomes similar to what has been found in other studies (Bailey et al., 2007; Dunst et
al., 2008). This was expected since the use of both relational and participatory FCPs has
been found to have capacity-building characteristics and consequences (Dunst & Espe-
Sherwindt, 2016). The characteristics include, but are not limited to, practitioner
beliefs about existing family member strengths and the capacity to become more competent;
informed family choice and decision-making; active family member involvement in achieving
desired goals and outcomes; family member use of existing capabilities; and the
development of new skills for obtaining desired resources and supports and achieving
desired goals (Dunst & Espe-Sherwindt, 2016). The consequences include, but are not
limited to, parents’ beliefs about their ability to exercise control over important life
events (e.g., Skinner & Greene, 2008), including parenting beliefs about their
childrearing practices (Coleman, 1999; Newland, 2015). The results add to “the knowledge
base regarding the role active help-receiver participation plays in people achieving
desired life circumstances that in turn produce positive behavioral consequences in other
domains of functioning” (Dunst et al., 2006a, p. 48). We therefore conclude that the
results found in our studies provide evidence for the generalized effects of FCPs in
samples in Spain in a manner similar to that found in other studies. The belief appraisals
that were the focus of this investigation have been used in other studies as measures of
individual empowerment (Woodall, Raine, South, & Warwick-Booth, 2010) and psychological
empowerment (Zimmerman & Rappaport, 1988). According to Singh (1995), individual
empowerment is defined as "a process by which families access knowledge, skills, and
resources that enable them to gain positive control over their own lives as well as
improve the quality of their lifestyles” (p. 13, emphasis added). Self-efficacy beliefs
have been used as a measure of control over practitioner help-giving practices (Trivette,
Dunst, Boyd, & Hamby, 1995) and parenting beliefs have been used as a measure of control
over executing parenting roles (Paczkowski & Baker, 2007). An empowerment perspective of
efficacy beliefs helps explain how experiences afforded families (e.g., practitioner use
of FCPs) “equip people with the requisite knowledge, skills, and resilient self-beliefs of
efficacy to alter aspects of their lives over which they can exercise some control (Ozer &
Bandura, 1990, p. 472, emphasis added). These types of control belief appraisals influence
families’ abilities to cope, deal with, and affect life circumstances (Bandura, Caprara,
Barbaranelli, Regalia, & Scabini, 2011; Skinner, 1995). Placed within the context of
empowerment theory, FCPs include capacity-building experiences that provide family members
opportunities to use existing abilities and acquire new abilities in ways that positively
affect their beliefs about control over important life events in ways that influence
health-related outcomes. As noted by both empowerment (Rappaport, 1987) and self-efficacy
(Bandura, 1997) scholars, belief appraisals function as mechanisms for explaining how
competency-enhancing experiences afforded people are manifested in terms of improved
psychological functioning (Diener & Biswas-Diener, 2005; Woodall et al., 2010). According
to Tensky (2005), this necessitates a paradigm shift in terms of how we conceptualize and
operationalize the ways in which professionals go about their work with help seekers.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

There are at least three limitations that must be considered as part of the data
interpretation. The first limitation has to do with the use of self-report measurement
instruments, which may account for the nature of the relationships among the variables in
both studies, and the fact that the data are cross-sectional and not longitudinal. This
limitation concerns the degree of confidence for asserting causal relationships between
the study measures (Asher, 1983; Kenny, 2004). This limitation is partly mitigated by the
fact that the pattern of results in both studies are nearly identical to those reported in
studies where there was time precedence between the belief appraisals and well-being
measures (Dunst & Trivette, 2009; Dunst, Hamby et al., 2007). A second limitation is the
failure to include other measures in the analyses that might better explain the nature of
the relationships among the variables in the SEMs (e.g., parenting styles of interaction;
see especially Trivette et al., 2010). As noted by Tomarken and Waller (2005), such
omissions may present a misleading depiction of how FCPs are directly and indirectly
related to other variables of interest (see especially Trivette et al., 2010). A third
limitation relates to the fact that only one model was the focus of investigation where
the model was informed by results from previous investigations. It could be the case that
there are other models that better explain the relationships among the variables in the
model. However, as noted by MacCallum (1995), “In a strictly confirmatory [SEM] strategy,
the researcher constructs one model of interest and evaluates that model by fitting it to
appropriate data. If the model yields interpretable parameter estimates and fits the data
well, it is supported and considered a plausible model (p. 31, emphasis added).

<h>CONCLUSION AND IMPLICATIONS FOR PRACTICE</h>
----------------------------------------

The pattern of results in the SEMs provided empirical support for the contention that the
way in which help is provided can either enhance or impede the intended outcomes of that
help (Dunst, Trivette, & Hamby, 2007). The findings showed how the effects of FCPs on
parent psychological well-being are indirect and mediated by self-efficacy beliefs and
parenting competence and confidence beliefs. These results have a number of implications
for practice. The first implication has to do with an understanding of and the need to be
clear about how FCPs are related to health-related outcomes. Parental well-being is
recognized as an important family outcome of ECI (Bailey et al., 1998; Krauss & Jacobs,
1990). The effects of FCPs on parent psychological well-being, however, are primarily
indirect and not direct, and it is important that practitioners have a clear understanding
of how FCPs influence outcomes of interest, including, but not limited to, health-related
outcomes (see e.g., Dunst et al., 2008). The second implication has to do with the
importance of using both relational and participatory FCPs and especially the use of
participatory help-giving practices, if FCPs are going to have capacity-building
consequences. The latter is the case because practices that actively involve parents in
ECI are more likely to promote a sense of competence and confidence as hypothesized by
Bandura (1997). Accordingly, ECI programs and practitioners that focus on the empowerment
of families will need to place primary emphasis on using participatory practices that
strengthen existing capabilities and promote the acquisition of new family member
competencies (Dunst, 2010). The third implication is not to assume that ECI programs and
practitioners that claim to use FCPs, in fact, use these practices on a routine basis.
Research has shown that ECI programs, organizations, and practitioners face many
challenges and obstacles as part of adopting and using FCPs, and especially participatory
practices (Dempsey & Keen, 2017; Dunst & Espe-Sherwindt, 2017). It is therefore hardly
surprising that Dempsey and Keen (2017) noted that “effective implementation is the next
major challenge for family-centered practices” (p. 65). Effective implementation includes,
but is not limited to, the use of evidence-based professional development practices.
Findings from a recently published study indicate that professional development specialist
use of capacity-building professional development practices was related to practitioners’
use of capacity-building FCPs (Dunst, Espe-Sherwindt et al., 2019; Dunst, Hamby et al.,
2019). This demonstrates an empirical relationship between evidence-based implementation
practices and evidence-based FCPs.

<h>FUNDING</h>
-------

This research has been carried out through funds from the Ministry of Universities and
Research of the Department of Enterprise and Knowledge of the Generalitat de Catalunya.


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<ART>For better or for worse: The moderating effects of personality on the marriage-life satisfaction link
================================================================================

Authors: Christopher J. Boyce, Alex M. Wood, Eamonn Ferguson
DOI: 10.1016/j.paid.2016.03.005
Year: 2016  |  Pages: 61-66
ASJC codes: 3200
Keywords: Adaptation, Life satisfaction, Marriage, Personality, Subjective well-being

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

On average, marriage tends to lead to temporary increases in life satisfaction, which quickly return to pre-marital levels. This general pattern, however, does not consider the personality of individuals entering into marriage. We examine whether following marriage pre-marital personality predicts different changes to life satisfaction in a sample of initially single German adults (N = 2015), completing life satisfaction measures and indicating their marital status yearly for 8 years (during which 468 married). We find that conscientious women experience greater life satisfaction following marriage than less conscientious women. Our data also indicate that introverted women and extraverted men experience longer-term life satisfaction benefits following marriage. Our results refute the claim of limited life satisfaction effects from marriage and caution against relying on average effects when examining the influence of life events on well-being.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Considerable research has aimed at testing whether marriage leads to increases in life
satisfaction. Married individuals robustly have higher average levels of life satisfaction
than non-married individuals (Haring-Hidore, Stock, Okun, & Witter, 1985), but this
relation is partially explained through social selection effects, whereby those with
higher life satisfaction are more likely to marry (Mastekaasa, 1992). Nevertheless
research that controls for selection effects suggests that any life satisfaction benefits
of marriage are at best transitory. There are short-term life satisfaction increases
following marriage but life satisfaction returns fairly rapidly to pre-marital levels
(Yap, Anusic, & Lucas, 2012). However, this general pattern of results is unlikely to be
true for everyone, with some people being more likely to experience greater life
satisfaction benefits following marriage, whilst others may find the experience less
beneficial. Here we explore whether a person's pre-marital personality predicts life
satisfaction change following marriage. Personality represents basic individual tendencies
and, as conceptualized by the Five Factor Model, (FFM; McCrae & Costa, 2008), comprises
agreeableness, conscientiousness, extraversion, neuroticism, and openness-to-experience.
Individuals can infer and express accurately what these basic tendencies are from their
own behaviors and experiences (McCrae & Costa, 2008). The FFM traits relate to an
individual's life satisfaction (Steel, Schmidt, & Shultz, 2008), which may be through a
direct relation, capturing an individual's predisposition to experience positive or
negative emotions (as with the positive or negative affective components of extraversion
or neuroticism). Alternatively, the relationship between personality and life satisfaction
may be indirect (as with agreeableness, conscientiousness, and openness) through
orientating individuals toward positive situations (McCrae & Costa, 1991). However,
evidence is emerging for a third pathway, in that there are differences in how personality
influences response to life events. Specifically, personality has been shown to predict
how life satisfaction is influenced following adverse life events such as disability
(Boyce & Wood, 2011) and income loss (Boyce, Wood, & Ferguson, in press), as well as
protecting against depression during widowhood (Pai & Carr, 2010). Importantly such
studies have utilized personality measures before the events took place, thus preventing
confounding any effects with the possibility that personality traits develop in response
to these events (Boyce, Wood, Daly, & Sedikides, 2015). Only two studies have assesed
whether personality moderates the extent to which individuals' life satisfaction changes
following marriage (Anusic, Yap, & Lucas, 2014; Yap et al., 2012). However, owing
potentially to limited statistical power Yap et al. (2012) obtained null effects, whilst
Anusic et al. (2014) did not utilize personality traits measured before marriage. Since
research in this area is limited we hypothesize that any of the FFM personality traits may
be important. In accordance with our exploratory approach the literature on relationship
satisfaction suggests an important role for agreeableness, conscientiousness,
extraversion, and neuroticism (Malouff, Thorsteinsson, Schutte, Bhullar, & Rooke, 2010).
Personality traits tend to influence relationship satisfaction via ongoing relationship
dynamics (Solomon & Jackson, 2014), which may ultimately lead to the dissolution of the
relationship (Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007). Since the attainment of a
satisfying relationship is a near universal goal (Roberts & Robins, 2000) factors that
enhance the quality of a relationship are also likely to influence life satisfaction.
Given there are personality differences across men and women with regard to relationship
satisfaction (Solomon & Jackson, 2014) we also explore personality differences across men
and women. Since we make no specific predictions we consider statistical corrections for
multiple comparisons (Nakagawa, 2004).

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

We used the German Socio-Economic Panel (SOEP) study, an ongoing longitudinal study of
German households. The SOEP began in 1984 with a sample of adult members from private
households in West Germany, initially over-representing immigrants. Since 1984, the SOEP
has expanded to include East Germany and various sub-samples to ensure a broadly
representative sample of the entire German population (Wagner, Frick, & Schupp, 2007). We
focused on SOEP participants, regardless of their origin in the sample, who answered
personality questions in 2005 and were single. Participants also responded to questions
about their life satisfaction in every year from 2005 to 2012 and we ensured that their
marital status was recorded in each of these years. We then observed the marital status
across this period to determine whether individuals had married. Participants' current
marital status is recorded in the SOEP as either married (living together with spouse),
married (but permanently separated), single, divorced, or widowed. We concentrate only on
those individuals that are initially single, got married and stayed married (remaining
living together with spouse) in the study period. All individuals that marry in our sample
therefore marry for the first time. We included a control group of individuals who
remained single throughout the study period such that we could account for life
satisfaction selection effects and to ensure life satisfaction changes were the result of
marriage rather than some national event that affected the entire sample. Our final sample
consisted of 2015 (986 females, 1029 males) participants of which 1547 remained single
throughout the study period and 468 (248 females, 220 males) participants married for the
first time at some point in the study and remained married. In 2005, when all individuals
were single, age ranged from 17 to 88 (M = 30.99, SD = 12.53).

        <hss>Life satisfaction</hss>

        Life satisfaction was measured with one item each year for all 8 years.
        Participants responded to the question “How satisfied are you with your life, all
        things considered?” from 0 (completely dissatisfied) to 10 (completely satisfied).
        Participants' responses were standardized (M = 0, SD = 1) across the sample.
        Single item scales, although typical for large data sets, can have a low
        reliability resulting in an underestimation of the true effect size (inflating
        Type II, but not Type I, error). Lucas and Donnellan (2007) estimate the unstable
        state/error component of life satisfaction in the SOEP and show that approximately
        33% of the variance in responses can be attributed to the unstable state/error
        component over a 1 year period. They infer that the life satisfaction has an
        acceptable reliability of at least r = .67. Although reliability diminishes with
        an increased time interval the reliability is approximately r = .45 across 7
        years. This is higher than normally observed for single item measures.

        <hss>Big Five personality measures</hss>

        A 15-item (3 per trait) shortened version of the Big Five Inventory (Benet-
        Martínez & John, 1998) was administered in 2005. This version was developed
        specifically for use in the SOEP, where there is limited space for survey
        questions (Gerlitz & Schupp, 2005). Participants responded to 15 items (1 = “does
        not apply to me at all”, 7 = “applies to me perfectly” scale), with three items
        assessing each of the FFM domains of agreeableness (e.g., “has a forgiving
        nature”), conscientiousness (e.g., “does a thorough job”), extraversion (e.g., “is
        communicative, talkative”), neuroticism (e.g., “worries a lot”), and openness
        (e.g., “has an active imagination”). Across each personality dimension all three
        scores were aggregated after appropriate reverse coding and then standardized (M =
        0, SD = 1). Life satisfaction and personality scores for the entire SOEP sample,
        as well as for each marriage category and by an individual's age group, are found
        in Tables A1 and A2 respectively in the Appendix A. These scores are broadly
        comparable to SOEP sample wide scores. The SOEP scale has comparable psychometric
        properties to longer FFM scales. For example, the short-item scale produces a
        robust five factor structure across all age groups (Lang, John, Lüdtke, Schupp, &
        Wagner, 2011). Donnellan and Lucas (2008) demonstrated that each of the scales in
        the SOEP correlates highly (r > .88) with the corresponding scale in the full Big
        Five Inventory. Although Lang (2005) illustrates that the retest reliability
        across 6 weeks is acceptable (r > .75) this reliability measure is insufficient as
        our study takes place over 7 years and may not apply to our specific marriage sub-
        sample. Since the shortened Big Five Inventory was administered 4 years later in
        the SOEP we estimate the retest reliability in our sample. It was at least r = .52
        across this time period and similar for those that married and those that did not
        (see Table A3). These values are comparable to longer scales over this time frame
        (r = .55; see Roberts & DelVecchio, 2000). Table A4 shows the correlations between
        each of the FFM personality traits and life satisfaction in our sample.
        Neuroticism has a strong negative relationship with life satisfaction, whereas the
        remaining traits are less strongly positively related to life satisfaction,
        conforming with previous research (Steel et al., 2008).

        <hss>Covariates</hss>

        Marriage is correlated with a number other factors which may be associated with
        life satisfaction. We control for an individual's age, the presence of children in
        the marriage, education level, and an individual's satisfaction with family life.
        We also include time-period dummies to allow for time-period specific differences
        in life satisfaction. Since age and education also correlate with personality
        (Srivastava, John, Gosling, & Potter, 2003) any personality interactions may be
        driven by these factors. For example, older individuals (or analogously those more
        highly educated) may have a higher life satisfaction during marriage than those
        younger. Since age (or education) is also likely to be associated with
        personality, not appropriately controlling for the interaction of these variables
        with marriage may lead to a spurious interaction between personality and marriage.
        Thus we include interactions of both age and education (recorded in 2005) with our
        marriage variables. We dealt with missing data in education (15.9%) and family
        satisfaction (2.2%) using multiple imputation. We used multiple imputation chained
        equations (MICE; White, Royston, & Wood, 2011) using predictive mean matching and
        obtained 5 imputations (based on five sequential iterations using MICE). We also
        imputed the missing education–marriage interaction terms to ensure these variables
        had the correct means and covariances.

<hs>  Data analytic strategy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

To examine whether personality predicts life satisfaction differences in how individuals
respond to marriage we carried out an interaction analysis within a multilevel framework.
We analyze the Level 1 effect of marriage on life satisfaction (LS) across all time points
(t) from 2006 to 2012 for men and women separately. Since we were interested in life
satisfaction over the course of the marriage we coded individuals at each time-point
according to the number of years they had been married up to that time-point. Since the
years before marriage are often associated with benefits to life satisfaction we include
dummy variables to indicate that an individual will get married in the next year or
alternatively that they will get married at some point in the study. At a given time-point
participants were classified as either never experiencing marriage throughout the study,
not yet married but would at some point during the study (Mt + > 1), experienced marriage
in the following year (Mt + 1), or married for 1 to 7 years (Myrs). Our analysis allowed
us to establish, and control for, any life satisfaction selection effects, and also
determine the effect on life satisfaction at different years of marriage. To determine
non-linear effects we included the square and cube of the number of years that the
participant had been married (Myrs2, Myrs3). Person-specific slopes and intercept errors
are captured by the σ terms and ε captures the overall model error. By controlling for
life satisfaction in 2005, γ01 and γ02 are interpretable as marriage selection effects,
and γ03, γ04, and γ05 signify changes in life satisfaction by year of marriage. The
coefficients γ13, γ14, and γ15 represent the personality-marriage interaction effects.
Since our analysis is largely exploratory we consider our results in light of possible
Type 1 error through multiple comparisons (Nakagawa, 2004).

<h>RESULTS</h>
-------

To test whether there is an interaction between personality and marriage in predicting
life satisfaction we carried out multilevel regressions separately for both women and men,
initially including no controls. Table 1 Regression 1 provides the results for women. The
coefficients on the marriage main effect variables suggest that on average women that will
marry during the study are 0.13 SD (coefficient on Mt + > 1) higher in life satisfaction
than those who don't marry. In the year directly preceding marriage women on average have
life satisfaction levels 0.29 SD (coefficient on Mt + 1) higher than those who never
marry. The first year of marriage is then associated with a life satisfaction level of
0.21 SD, with each additional year of marriage changing life satisfaction according to
0.30 ∗ Years Married − 0.10 ∗ Years Married2 + 0.01 ∗ Years Married3. Thus the effect of
marriage on life satisfaction is initially positive but eventually reduces. Regression 1
illustrates that the effect of marriage on life satisfaction is also dependent upon pre-
marriage personality. There are significant interaction terms for both conscientiousness
and extraversion. This suggests that women with basic underlying tendencies (see McCrae &
Costa, 2008) that result in them endorsing behaviors reflective of conscientiousness or
low extraversion experience higher life satisfaction during marriage. This is illustrated
in Fig. 1. In the left-hand panel we observe that women who score themselves moderately
high on conscientiousness (+ 1 SD) experience sustained life satisfaction benefits,
whereas women who score themselves as moderately low on conscientiousness (− 1 SD) quickly
experience falls in life satisfaction. After some years the life satisfaction levels of
those moderately low in conscientious are similar to those that remained single throughout
the study. The middle panel in Fig. 1 shows the effect of marriage on life satisfaction
for women who score themselves moderately low (− 1 SD) and moderately high (+ 1 SD) on
extraversion. There is significance only on the linear interaction but the curvature
remains owing to the main effect coefficients and the interaction only changing the
trajectory of the curvature. Initially there are no satisfaction differences by
extraversion. However, after a few years of marriage women that endorse behaviors
reflective of extraversion begin to experience reductions in life satisfaction, whilst
those that don't endorse behaviors reflective of extraversion (i.e. intraversion) maintain
their level of life satisfaction. Thus women who score low on extraversion appear to
experience long-term life satisfaction benefits following marriage. We note the sudden
spike in life satisfaction in years 6 and 7 but we suggest caution since only a small
number of participants in our sample experienced 6 or 7 years of marriage. Table 1
Regression 3 provides the results for men. On average men that marry during the study
experience life satisfaction increases in the year directly preceding the marriage, where
life satisfaction rises to 0.18 SD. The first year of marriage is then associated with a
life satisfaction of 0.17 SD higher than those who remain single, with each additional
year of marriage changing life satisfaction according to 0.25 ∗ Years Married − 0.09 ∗
Years Married2 + 0.01 ∗ Years Married3. The effect of marriage on life satisfaction is on
average positive but returns to pre-marital levels of life satisfaction quickly.
Regression 3 suggests, however, that men who endorse behaviors reflective of extraversion
experience higher life satisfaction during marriage. The right-hand panel in Fig. 1 shows
the effect of marriage on life satisfaction for men that score themselves moderately low
(− 1 SD) and moderately high (+ 1 SD) on extraversion. Whilst all men experience a pre-
marital increase in their life satisfaction, men that are extraverted seem to experience
longer-term benefits to their life satisfaction during marriage. Introverted men, however,
experience significant drops in their life satisfaction that result in them being
approximately 0.20 SD lower in life satisfaction than those who never marry. Due to the
possibility of Type 1 errors owing to multiple comparisons we re-evaluate our results
after making a Bonferroni-type correction (p = 0.05/α, where α represents the number of
comparisons made which is 10 here). Only the conscientious interaction in women survives
this correction (joint significance on both conscientiousness interaction terms; p =
.004). Although Bonferroni-type corrections minimize the possibility of Type 1 errors they
have been criticized for increasing the likelihood of Type 2 errors (Nakagawa, 2004). Thus
we suggest that the other interactions, rather than being rejected, should be simply
treated with caution. Further a number of other factors may correlate not only with
marriage and life satisfaction but also with personality. We account for these by
including additional controls including age, the presence of children, education level,
and an individual's satisfaction with family life, as well as the interaction of the
individual's pre-marital age and education with the marriage variables up to the quadratic
term of years spent married. The conscientiousness interaction effects are still evident,
whereas for extraversion these effects are significant only at the 10% level. There is now
a linear effect on neuroticism. These changes are driven by the inclusion of family
satisfaction, which is strongly correlated with life satisfaction. This suggests further
caution for the extraversion result in both men and women.

<h>DISCUSSION</h>
----------

Although individuals may experience initial life satisfaction increases following marriage
these effects on average return quickly to pre-marital levels. However, we show that an
individual's reaction depends on their pre-marital personality. Specifically, women who
reported being conscientious experienced sustained increases in their life satisfaction
following marriage whereas those less conscientious experienced small transitory life
satisfaction increases. Such a result might be explained by the tendency for conscientious
individuals to place more value on relationship goals (Roberts & Robins, 2000) and
therefore conscientious individuals may strive harder to ensure success (Duckworth,
Peterson, Matthews, & Kelly, 2007). This result is consistent with conscientious
individuals being more satisfied with their relationships (Malouff et al., 2010). This
conscientiousness effect, however, was not found in men. Although we expected some
differences between men and women it is not clear why this was the case and we
speculatively suggest that this could be due to differences in how men and women value
life goals (Roberts & Robins, 2000). We also found effects that differed across men and
women for extraversion, with introverted women but extraverted men experiencing long-term
benefits to their life satisfaction. Extraversion generally predicts enhanced relationship
satisfaction (Solomon & Jackson, 2014) and although it is not clear why we observed
inconsistent effects it has been suggested that the importance of extraversion for
relationship satisfaction may be cultural (Malouff et al., 2010). Some caution is,
however, recommended with our results on extraversion since the effects were dependent on
the inclusion of certain controls and further the effect did not pass the more stringent
significance level to account for multiple comparisons. One reason for our limited power
to detect some of the effects might be due to our scales for personality and life
satisfaction being shorter than ideal. This may have also resulted in our effects being
under-estimated. Our research nevertheless demonstrated a test–retest stability in a
short-item personality scale over 4 years that was comparable to longer scales, adding to
the literature on personality stability whilst being consistent with the literature on
personality change (Boyce et al., 2015). Our exploratory approach to understanding how
personality moderates the influence of marriage on life satisfaction was an attempt to
establish initial research in this area. Now that the basic relationship has been
established we hope that this opens up possibilities for future research to explore
mechanistic pathways. We suggest that our results might be driven by specific personality
types valuing or not valuing certain features of their new environment, such as different
social opportunities that arise following marriage. Alternatively, life satisfaction may
increase following marriage not due to the direct effect of marriage per se but via the
indirect effect marriage has in protecting an individual when they encounter life
stressors. Personality may both increase the likelihood of other life stressors occurring
during marriage and/or moderate the impact of such life stressors. It is also possible
that partner personality may have an important effect in explaining why some marriages
yield more satisfaction than others (Solomon & Jackson, 2014). Since most of our sample
did not include partners from the same marriage we were unable to examine the influence of
partner personality. We recognize this limitation and future research should therefore
explore the role of partner personality. Although more work is needed in understanding and
testing precise mechanisms behind our results, our research is the first to demonstrate
that personality moderates the effect of marriage on life satisfaction and adds to a
growing literature illustrating the importance of personality traits for generating higher
or lower well-being following commonly occurring life events.


<h>REFERENCES</h>
----------

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<ART>From Likert scales to images: Validating a novel creativity measure with image based response scales
================================================================================

Authors: Franziska Leutner, Adam Yearsley, Sonia Cristina Codreanu, Yossi Borenstein, Gorkan Ahmetoglu
DOI: 10.1016/j.paid.2016.10.007
Year: 2017  |  Pages: 36-40
ASJC codes: 3200
Keywords: Creativity, Image-based measure, Openness, Psychological assessment

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The use of image-based testing to assess individual differences has increased substantially in recent years, with proponents arguing that they offer a more engaging alternative to text-based psychometric tests. Yet research examining the validity of these tests is near to non-existent. Traditional image-based formats have been little more than an adaptation of self-reports, with images replacing questions but not response options. The current study develops a novel image-based creativity measure, where images replace conventional response scales, and scores on the measures are obtained using a linear regression scoring algorithm to predict three self-reported creativity measures. Using sequential forward selection on a set of 77 image-based items, an optimal solution of 14 items that were valid predictors of self-reported creativity scores were identified. The image-based measure had good test-retest reliability. Implications are discussed in terms of the usefulness of image-based testing for practitioners seeking engaging and short test formats.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The assessment of individual differences in psychological traits, such as personality,
intelligence, and creativity, stretches back more than a century (Chamorro-Premuzic,
2007). The most common way of measuring differences between people is through psychometric
tests (Ahmetoglu & Chamorro-Premuzic, 2013). Psychometric tests are used extensively in
settings from selection (Rothstein & Goffin, 2006) to psychiatric diagnosis (Gilbody,
Richards, Brealey, & Hewitt, 2007), and consumer profiling (Matz, Gladstone, & Stillwell,
2016). Despite their widespread use, psychometric tests are criticised for their inability
to engage the test taker (Krosnick, 1991), the ease of faking responses (Morgenson et al.,
2007), and adverse impact (Hough, Oswald, & Ployhart, 2001). Perhaps in response to these
criticisms, and fuelled by technological advances, recent years have seen mounting
interest in more engaging forms of assessment (Attali & Arieli-Attali, 2015), including
gamification (Chamorro-Premuzic & Steinmetz, 2013; Landers & Callan, 2011; Reeves & Read,
2013) and social media analytics (Kosinski, Matz, & Gosling, 2015; Pennebaker, 2011).
However, innovative assessment tools often serve entertainment purposes, with little
indication to their validity (Naglieri et al., 2004). The increase in the quantity of
these instruments has not been synonymous with an increase in research into their quality,
that is, their reliability and validity. Indeed, the desire to use innovative assessment
by professionals has outpaced the peer-reviewed literature (e.g., Roth, Bobko, Van
Iddekinge, & Thatcher, 2013). This gap between research and practise is problematic if
tests are used to make hiring decisions or provide clinical diagnosis. Consequently,
developing scientific evidence for the validity and utility of image-based tests is
critical, not only from an academic, but also an applied perspective. The current study
takes a step in this direction. Specifically, an image-based creativity assessment and a
predictive scoring algorithm are developed. The test-retest reliability, as well as its
concurrent validity in relation to three text-based, self-report creativity measures are
assessed, so that practitioners may better understand how such image-based tests compare
to traditional tests.

<hs>  Advantages of image-based formats</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

One of the most common innovations in psychological assessment formats has been to replace
item questions with visual representations, thereby increasing user engagement (Barrett &
Ebbeling, 2003; Downes-Le Guin, Baker, Mechling, & Ruylea, 2012; Hamari, Koivisto, &
Sarsa, 2014; Lugtigheid & Rathod, 2005). Beyond engagement, image-based formats could
provide theoretical and practical advantages over text-based psychometric tests. First,
they may be more suitable for culturally and linguistically diverse test takers, and
remove misunderstanding of text items (Paunonen, Jackson, & Keinonen, 1990). Second,
responding to image-based items may require less attention, reducing test taker fatigue.
Finally, image stimuli evoke stronger preferences in respondents than verbal stimuli,
providing for reduced length of image-based tests (Lugtigheid & Rathod, 2005; Meissner &
Rothermund, 2015).

<hs>  Past research on image-based tests</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Despite being innovative, image-based formats in assessment are not new. Geist's (1959)
Pictorial Interest Inventory pictures a person engaged in three activities, of which
respondents pick the most appealing one. More recent image-based tests adapt text-based
personality measures such that the question is replaced with an image: The Nonverbal
Personality Questionnaire (Paunonen et al., 1990) measures Murray's (1938) psychological
needs such that participants report the likelihood that they would engage in visually
displayed behaviours. A version of the test measuring the Big Five also exists (Paunonen,
Ashton, & Jackson, 2001). These adaptations of verbal personality tests have gained
support in the academic literature for their internal reliabilities and validities (Hong,
Paunonen, & Slade, 2008; Moore, Schermer, Paunonen, & Vernon, 2010; Paunonen, 2003;
Paunonen, Jackson, Trzebinski, & Forsterling, 1992; Paunonen, Zeidner, Engvik, Oosterveld,
& Maliphant, 2000). However, research examining the validity of image-based tests is
scarce, and their use is mostly limited to special populations, such as children or
illiterates. In addition, the use of response scales and scoring methodologies developed
for verbal formats is not ideal: by using images to replace the question stem, questions
are limited to those that can be visually represented.

<hs>  Assessment of creativity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Creativity encompasses both personality and cognitive aspects related to the production of
unique and useful ideas (Runco & Jaeger, 2012; Simonton, 2000). Three of the many
components associated with creativity are: Cognitive Flexibility, the ability to switch
cognitive sets to adapt to changing environmental stimuli (Scott, 1962); Curiosity, the
recognition, pursuit, and intense desire to explore novel and uncertain events (Kashdan &
Silvia, 2009) and Openness to Experience, the Big Five personality trait considered as a
proxy of creativity (Feist, 1998; Furnham & Bachtiar, 2008; Martindale, 1989). Because of
the broadness of the construct, multi-trait, multi-method approaches have been proposed as
most suitable (Cropley, 2000; Plucker & Makel, 2010). An image-based measure of creativity
may add to this array of measurement methodologies available for creativity testing. In
addition, image-based response scales may be particularly effective in measuring
creativity because images elicit aesthetic preferences, such as preferences for
complexity, which in turn are indicative of self-reported creativity and aesthetic styles
(Barron, 1953; Chamorro-Premuzic, Reimers, Hsu, & Ahmetoglu, 2009; Rawlings, 2003; Swami,
Stieger, Pietschnig, & Voracek, 2010; Wiersema, van der Schalk, & van Kleef, 2012). A
preference for complex polygons is associated with higher self-reported creativity, such
that Eisenman and Robinson (1967, 1968) suggested the use of polygons varying in their
level of complexity as measures of creativity. Accordingly, the present research aimed to
a) develop a novel format image-based creativity measure, b) investigate its concurrent
validity in relation to three text-based measures of creativity, and c) assess its test-
retest reliability.

        <hss>Curiosity and Exploration Inventory-II (CEI-II; Kashdan et al., 2009)</hss>

        A 10-item, five-point Likert self-report scale. The CEI-II measures two traits:
        stretching (e.g., ‘I actively seek as much information as I can in new
        situations’) and embracing (e.g., ‘I am the type of person who really enjoys the
        uncertainty of everyday life’). The CEI-II demonstrates reliability estimates of
        0.85, construct validity, discrimination, desirable breadth of difficulty (Kashdan
        et al., 2009), and predictive validity for task performance (Kashdan, Rose, &
        Fincham, 2004).

        <hss>Cognitive Flexibility Inventory (CFI; Dennis & Vander Wal, 2010)</hss>

        A 20-item, seven-point Likert scale, self-report measure of adaptive thinking in
        stressful situations. Thirteen items assess behaviours related to alternatives
        (e.g., ‘I consider multiple options before making a decision’), and seven items
        behaviours related to control (‘When I encounter difficult situations, I feel like
        I am losing control’). The CFI shows a reliable factor structure, internal
        consistency, test-retest reliability, and concurrent validity (Dennis & Vander
        Wal, 2010).

        <hss>Openness to experience (Goldberg, 1999)</hss>

        Measured on a five-point Likert scale (‘very inaccurate’ to ‘very accurate’) using
        the 10-item Openness scale from the International Personality Item Pool (e.g. ‘I
        enjoy hearing new ideas’).

<hs>  Item design</hs>
  ~~~~~~~~~~~

The question stem of image-based items retained its verbal format, but the response scale
presented a range of images (see Fig. 1). Each item consisted of a text-based question and
between two and eight image response options. The image response options took one of two
forms: they either assessed varying levels of the same trait, or they represented
different traits. Seventy-seven items were designed to reflect Cognitive Flexibility,
Curiosity, and Openness.

<hs>  Scoring</hs>
  ~~~~~~~

The scoring algorithm was developed on a sample of 964 participants, recruited using a UK
panel company, and compensated for their participation. The panel had an equal
distribution of males and females, and participants were UK residents. Approximately half
of the users were 18–25 and the other half 25–36 years old. Participants completed the
three creativity measures as well as all 77 image-based items. Rather than stipulating
which responses were indicative of which underlying trait, responses to image-based items
were scored in relation to standard measures. This method is commonly used in measure
validation procedures when testing concurrent validity between new and existing measures
(Rust & Golombok, 2009), as well as for predictive personality measures (Bachrach,
Kosinski, Graepel, Kohli, & Stillwell, 2012; Boyd et al., 2015; Lambiotte & Kosinski,
2014; Youyou, Kosinski, & Stillwell, 2015; Schwartz et al., 2013; Wang, Kosinski,
Stillwell, & Rust, 2014). Responses to all 77 items were dummified, with each image
response option being transformed into a binary variable. This resulted in 321 dummy
variables. Dummified responses were used as the independent variables (predictors) and the
creativity scores as the respective dependent (predicted) variables in linear regression
models to estimate the creativity scores.

        <hss>Item selection</hss>

        As the large number of dimensions resulting from 321 dummy variables can cause
        over-fitting, two methods of feature selection were used. The first method, LASSO
        (Least Absolute Shrinkage and Selection Operator) regression with 10-fold cross
        validation was applied to reduce the number of image response options. LASSO is a
        regularized regression, which penalizes variables with large coefficients and
        discounts variables with inconsistent performance across the sample. Thereby LASSO
        selects response options that are most indicative of creativity. LASSO cannot take
        into account that some image response options were taken from the same question.
        In order to account for the contribution of single questions, a second feature
        selection method, Sequential Forward Selection, was used (Devijver & Kittler,
        1982). Starting with an empty set of questions, LASSO regression with 10-fold
        cross validation was used to estimate the relevant scale. The predicted and
        measured scores were correlated, and additional questions added at each step until
        no new question improved the correlation by > 0.1. Questions with individual
        correlations higher than 0.2 were also retained. This resulted in a final set of
        14 questions, or 64 dummy variables.

<hs>  Results</hs>
  ~~~~~~~

With the selected 14 questions as predictor variables, LASSO regression with 10-fold cross
validation was performed to predict creativity scores. Coefficients for the models
predicting Cognitive Flexibility, Curiosity, and Openness, are presented in Table 1.

<hs>  Validation</hs>
  ~~~~~~~~~~

1071 participants (605 females) were recruited using Amazon's Mechanical Turk (MTurk).
Participants completed the text-based creativity measures and the 14-item image-based
measure, which is part of the Red Bull Wingfinder assessment. To assess test-retest
reliability, a subset of 162 participants retook the test after 60 days. MTurk panellists
were US citizens paid for their participation. 15% were aged 18–24, 47% aged 25–34, 24%
aged 35–44, and 14% aged 45 to 59. Responses to the image-based measure were scored using
the algorithm described in Section 2.3. Creativity scores were normally distributed on the
text- and image-based measures (see Table 2). The three text-based creativity scores had
moderate intercorrelations (average r = 0.47, with p < 0.001), as had the three image-
based scores (average r = 0.5, with p < 0.001) (see Table 2). Correlations between text-
and image-based scores were moderate to high. Concurrent validity was higher for Curiosity
and Openness than for Cognitive Flexibility (see Fig. 2). The average test-retest
reliability of the image-based measures was r = 0.63 (p < 0.001) (see Fig. 2).

<h>DISCUSSION</h>
----------

The aim of this study was to examine the psychometric properties of a newly developed
image-based creativity measure. Results obtained from two large samples provided
preliminary evidence for the test-retest reliability and concurrent validity of the
14-item measure. The developed scoring algorithm accurately predicted creativity scores on
two of the three existing scales. This finding is in line with studies demonstrating the
use of predictive models for measuring personality (Chen, Hsieh, Mahmud, & Nichols, 2014;
Lambiotte & Kosinski, 2014; Yarkoni, 2010) and indicates that predictive scoring
algorithms are suitable for scoring image-based response scales. Moderate correlations
between the image-based and the text-based measures for Curiosity and Openness
demonstrated good concurrent validity of the image-based format (r = 0.5, p < 0.001).
Furthermore, the measure exhibited good test retest reliability (r = 0.65, p < 0.001),
indicating that the selected image-based items are able to reliably measure aspects of
creativity. On the other hand, the concurrent validity for Cognitive Flexibility was
relatively low (r = 0.35, p < 0.001), suggesting that the selected images may not assess
this particular aspect of creativity equally well. The predictive scoring algorithm used
fewer items than established text-based measures, assessing all three creativity aspects
with 14 items, compared to 40 items on the text-based measures. Both the predictive
scoring algorithm and stronger associations evoked by images may be reasons for achieving
shorter length (Meissner & Rothermund, 2015). The image-based measure demonstrated good
test-retest reliability (average r = 0.63, p < 0.001), in particular taking into account
factors that might have reduced the correlation including the small number of items, long
interval between test and retest (six weeks), and the small to moderate sample size.
Indeed, the observed test-retest reliability for the image-based Openness measure was
higher than that reported in other studies for the ten-item, text-based Openness measure
(reported r = 0.55 in Kosinski, Stillwell, & Graepel, 2013). Participants were more likely
to consistently select the same image than they were to consistently select the same point
on a Likert scale. This could be due to the relatively broader construct of creativity as
compared to Openness (i.e. broader constructs tend to display better reliability;
Chamorro-Premuzic, 2011). In addition, some image-based items had only two images as
response options, compared with five to seven response options on Likert scales, which
could lower the probability of changing responses.

<hs>  Implications</hs>
  ~~~~~~~~~~~~

The current study has a number of implications for the development of image-based
assessments, particularly those focusing on creativity, but also beyond. For researchers
and practitioners interested in alternatives to traditional self-report Likert response
scales, this study provides preliminary support for the validity and reliability of an
image-based measure. Although additional research is needed to replicate and extend these
findings, this study takes a step towards providing evidence for the utility of innovative
psychological assessments. The image-based measure has a number of advantages in practice.
The measure is shorter than both existing text- and image-based creativity measures. Image
response scales may be less obvious in what they are measuring than Likert scales. As a
consequence, image-based scales could be less prone to faking and appear less intrusive to
the test taker.

<hs>  Limitations and future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The current study has a number of limitations. It assessed the concurrent validity of
image-based measures in relation to text-based, self-report inventories only. Although
this provides initial evidence of the validity of image-based measures, additional studies
are needed to investigate its relationship to non-self-report measures of creativity, such
as divergent thinking tests. In addition, reliability of the image-based measure should be
improved by identifying additional image-based items, in particular if the measure is to
be used in selection contexts. The incremental validity of the image-based measures in
predicting creative performance, beyond existing tests, should be established. This
research would be necessary for demonstrating the value of using image-based measures
alongside, in addition to, or as a replacement of, current creativity measures. There has
been a call for a multi-method, multi-trait approach to the study of creativity (Batey &
Furnham, 2006; Cropley, 2000; Park, Chun, & Lee, 2016; Plucker & Makel, 2010). Image-based
measures may tap into the same performance variance as other creativity measures. But
provided that image-based measures are more engaging than self-reports and easier to
administer than divergent thinking tests, they could provide an alternative to existing
creativity measures. Otherwise, image-based tests may predict distinct performance
variance from current measures. In this scenario, they could be used alongside traditional
tests. Accordingly, the purpose of developing an image based assessment is not only to
provide more engaging alternatives for established (self-report) methods, but to provide
an optional methodology for a valid multi-method approach to assessing creativity (and
perhaps other personality traits like the Big Five).

<hs>  Conclusion</hs>
  ~~~~~~~~~~

This study supports the proposition that creativity can be measured via preferences for
image-based stimuli. It may encourage research into innovative assessment formats and help
practitioners in applying alternative assessments in settings where evidence of validity
and reliability is required. Image-based assessments may provide a solution to an evolving
need for alternative assessments, and this study was one of the first to attempt to bridge
the gap between practise and research.


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<ART>Further evidence of the heterogeneous nature of impulsivity
===========================================================

Authors: Amy J. Caswell, Rod Bond, Theodora Duka, Michael J. Morgan
DOI: 10.1016/j.paid.2014.11.059
Year: 2015  |  Pages: 68-74
ASJC codes: 3200
Keywords: Factor analysis, Human, Impulsivity, Inhibitory control, Laboratory measures, Motor impulsivity, Reflection impulsivity, Temporal impulsivity

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

'Impulsivity' refers to a range of behaviours including preference for immediate reward (temporal-impulsivity) and the tendency to make premature decisions (reflection-impulsivity) and responses (motor-impulsivity). The current study aimed to examine how different behavioural and self-report measurements of impulsivity can be categorised into distinct subtypes.Exploratory factor analysis using full information maximum likelihood was conducted on 10 behavioural and 1 self-report measure of impulsivity.Four factors of impulsivity were indicated, with Factor 1 having a high loading of the Stop Signal Task, which measures motor-impulsivity, factor 2 representing reflection-impulsivity with loadings of the Information Sampling Task and Matching Familiar Figures Task, factor 3 representing the Immediate Memory Task, and finally factor 4 which represents the Delay Discounting Questionnaire and The Monetary Choice Questionnaire, measurements of temporal-impulsivity.These findings indicated that impulsivity is not a unitary construct, and instead represents a series of independent subtypes. There was evidence of a distinct reflection-impulsivity factor, providing the first factor analysis support for this subtype. There was also support for additional factors of motor- and temporal-impulsivity. The present findings indicated that a number of currently accepted tasks cannot be considered as indexing motor- and temporal-impulsivity suggesting that additional characterisations of impulsivity may be required.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Impulsivity encompasses a range of behaviours that include making premature decisions,
preferring immediate gratification and having difficulties inhibiting motor responses.
Impulsivity functions as a dimension of normal behaviour, and it is thought that it can be
adaptive in certain situations (Dalley, Everitt, & Robbins, 2011). However, it is also
well established that it is associated with a number of negative outcomes (Aichert et al.,
2012; Schweizer, 2002; Vigil-Colet & Morales-Vives, 2005) and is elevated in many clinical
populations (e.g. de Wit, 2009; Winstanley, Dalley, Theobald, & Robbins, 2004; Winstanley,
Eagle, & Robbins, 2006). There is growing consensus that impulsivity is heterogeneous and
should not be considered a unitary construct and should instead reflect a variety of
behaviours and processes (Evenden, 1999). In laboratory-based research, investigators have
focused on two subtypes of behavioural impulsivity: ‘motor’-impulsivity (MI), as a failure
to inhibit a behavioural response (also termed inhibitory control) and the failure to
delay gratification (which we will term ‘temporal’-impulsivity [TI], also referred to as
delay discounting). A third subtype of ‘reflection’-impulsivity (RI), i.e. the tendency to
make decisions without gathering or evaluating necessary information, has also been
suggested although it received comparatively little attention. Multiple tasks have been
designed to index each subtype including the Stop Signal Task (SST), Go/NoGo (GNG) and
Immediate Memory Task (IMT) for MI, the Matching Familiar Figures (MFF20) and Information
Sampling Task (IST) for RI, and pen-and-paper measures such as the Monetary Choice
Questionnaire (MCQ) and experiential tasks including the Single Key Impulsivity (SKIP) and
Two Choice Impulsivity Paradigm (TCIP) for TI. Impulsivity can also be indexed using self-
report measures (e.g. Kirby & Finch, 2010; Whiteside & Lynam, 2001), including the Barratt
Impulsiveness Scale (BIS-11, Patton, Stanford, & Barratt, 1995). However, despite
agreement that impulsivity comprises of multiple subtypes, they are rarely investigated
concurrently and multiple tasks are seldom simultaneously administered to the same
participants. Researchers typically select a single measure and refer to it as
‘impulsivity’, disregarding the wide array of processes and subtypes contributing to
impulsive behaviour. This practice has led to poor characterisation of the structure of
impulsivity, and the relationship of the subtypes to one another. Of the small number of
studies attempting to address this, investigators typically find correlations between
dependent variables of a task and have also found relationships between tasks indexing the
same subtype (e.g. Broos et al., 2012; Dougherty et al., 2009; Reynolds, Penfold, & Patak,
2008), suggesting that the subtypes may be well-defined. In contrast, relationships
between subtypes are not uniformly found (e.g. Broos et al., 2012; de Wit, 2009; Messer,
1976; Reynolds et al., 2008) and investigators employing factor analysis procedures have
found that measures of TI and MI load onto different factors of impulsivity, providing
evidence that these two subtypes may be distinct (Broos et al., 2012; Lane, Cherek,
Rhoades, Pietras, & Tcheremissine, 2003; Reynolds, Ortengren, Richards, & de Wit, 2006).
Collectively these studies provide preliminary evidence that the subtypes of impulsivity
may be well-defined and differentiated. However these studies are limited by including too
few tasks (e.g. Broos et al., 2012; Lane et al., 2003; Reynolds et al., 2006) despite
evidence that more detailed classifications of impulsivity are required. The SST, GNG and
IMT are used interchangeably as measures of MI in spite of evidence that the tasks index
distinct processes: ‘action cancellation’, i.e. the inhibition of a response during its
execution, on the SST (Dalley et al., 2011; Winstanley, 2011) and ‘action restraint’, i.e.
the inhibition of a response before it has started, on the GNG and perhaps the IMT (Dalley
et al., 2011, 2009; Eagle, Bari, & Robbins, 2008; Reynolds et al., 2008; Winstanley, 2011;
Winstanley, Olausson, Taylor, & Jentsch, 2010). There is evidence that different
neurotransmitters may contribute to the two processes (Eagle et al., 2008; Winstanley et
al., 2010) and factor analysis has indicated two distinct factors of MI (Dougherty et al.,
2009; Reynolds et al., 2008). With regards to TI, participants respond differently to
experiential versus pen-and-paper measures (Winstanley, 2011), hypothetical versus real
rewards (Hinvest & Anderson, 2009; Madden, Bickel, & Jacobs, 1999), monetary versus point
rewards (Frederick, Loewenstein, & O’Donoghue, 2002) and also to short versus longer
delays (Odum, 2011). However, these paradigms are used interchangeably despite there being
no evidence to validate the assumption that they all index the same underlying process.
Research suggests that self-report measures of impulsivity are not analogous with
behavioural tasks (Dick et al., 2010). The BIS-11 has been found not to correlate with
measures of MI or TI (Lane et al., 2003; Lansbergen, Schutter, & Kenemans, 2007; Reynolds
et al., 2006) and investigators predominantly find distinct factors of self-report and
behavioural impulsivity (Broos et al., 2012; Havik et al., 2012; Lane et al., 2003; Malle
& Neubauer, 1991; Meda et al., 2009). However, there is some evidence that self-report
impulsiveness is related to GNG performance (Aichert et al., 2012; Reynolds et al., 2006).
Importantly, no factor analysis studies have included measures of RI despite evidence that
it is clinically significant and distinct from other subtypes (e.g. Caswell, Morgan, &
Duka, 2013a, 2013b; Morgan, Impallomeni, Pirona, & Rogers, 2006; Morgan, McFie, Fleetwood,
& Robinson, 2002). The IST was designed to minimise some of the potential shortcomings of
the MFF20 that include confounding by other cognitive processes (Clark, Robbins, Ersche, &
Sahakian, 2006; Messer, 1976; Zelniker & Jeffrey, 1976) but although both tasks have been
proposed to be analogous measures of RI, there are no factor analysis studies to validate
this. As such, current literature discusses three subtypes of behavioural impulsivity, RI,
MI and TI. There is evidence that MI and TI are distinct, although available literature is
hampered by limited selection of tasks. This limited selection of tasks is a cause for
concern as there is evidence of task differences within proposed subtypes that may have
implications for their factor loadings and call into question their validity as indexes of
the subtypes. Previous studies have also failed to incorporate RI into factor analysis
models of impulsivity, despite evidence of its importance (e.g. Caswell et al., 2013a,
2013b; Morgan et al., 2006; Morgan et al., 2002). The current study aims to address these
issues by investigating the structure of impulsivity using exploratory factor analysis,
including measures of RI, to confirm whether impulsivity can be categorised into distinct
subtypes. We will include a greater number of putative measures of different subtypes of
impulsivity than has been attempted previously, encompassing the three proposed
behavioural subtypes of MI, TI and RI (the previously unexplored subtype). The tasks will
also include the BIS-11 as a self-report index of impulsivity although it is expected that
separate facets of self-report and behavioural impulsivity will be identified.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

160 (80 m, 80f) student participants at the University of Sussex were recruited, providing
informed consent. They were required to be 18–45 years of age, not suffering from any
mental illness, not be a heavy smoker (<20 per day), not taking any medication (excluding
the contraceptive pill). Participants were instructed to abstain from the use of illicit
recreational drugs for at least 1 week prior to the experiment and from the use of alcohol
for at least 12 h prior to the experiments.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants completed the BIS-11 and the National Adult Reading Task, Alcohol Use
Questionnaire and Drug Use Questionnaire followed by a battery of behavioural impulsivity
tasks. Tasks were computerised and completed in a random order.

        <hss>Self-report and demographic measures</hss>

        National Adult Reading Task (NART; Nelson & O’Connell, 1978): The NART gives an
        estimate measure of verbal IQ. Participants did not complete the NART if they were
        dyslexic or second language English (n = 23). Alcohol Use Questionnaire (AUQ;
        Townshend & Duka, 2002): Participants estimate the number of alcohol units they
        consume per week. Drug Use Questionnaire (see Townshend & Duka, 2005):
        Participants give details of use for main drug categories. Participants were given
        a score where 0 = no use; 1 = use of cannabis/hash/marijuana; 3 = use of
        ecstasy/other drugs.

            <hss>Self-report impulsivity</hss>

            Barratt Impulsiveness Scale, Version 11 (BIS-11; Patton et al., 1995): The
            BIS-11 is a 30-item checklist measuring impulsivity. The questionnaire gives a
            total impulsivity score as well as three subscales of motor-, attentional- and
            nonplanning-impulsivity.

            <hss>Behavioural impulsivity</hss>

            Information Sampling Task (IST; Clark et al., 2006): Participants open a
            matrix of boxes to reveal two colours underneath before selecting the colour
            in the majority. There are two conditions available, each consisting of 10
            trials, treated as separate tasks: Fixed win (FW): Participants win/lose 100
            points regardless of number of boxes opened. Reward conflict (RC): For every
            box opened, participants lose 10 points from a bank of 250. The task gives the
            probability of being correct that the participant tolerates at the point of
            decision-making [P(correct)]. Matching Familiar Figures Task (MFF20; Cairns &
            Cammock, 1978; Kagan, Rosman, Day, Albert, & Phillips, 1964): Participants
            select the one of six visually presented stimuli which is identical to an
            original image. Participants complete 20 trials. The task gives a composite
            Impulsivity score (I-score). Stop Signal Task (SST; Logan, 1994): Participants
            respond to the direction of visually presented green arrows withholding this
            response whenever the arrow turns red (the Stop Signal, occurs 25% of trials).
            Participants complete 120 trials. The task gives a measure of Stop Signal
            Reaction Time (SSRTi). Go/NoGo (GNG; adapted from Kim, Iwaki, Imashioya, Uno,
            & Fujita, 2007): Participants respond whenever a visually presented triangle
            is pointing upwards (Go trials, occur 60% of trials) withholding this response
            if a triangle is pointing in another direction (Stop trials, occur 40% of
            trials). Participants complete 120 trials. The task gives a measure of the
            percentage of commission errors to Stop signals. Immediate Memory Task (IMT;
            Dougherty, Marsh, & Mathias, 2002): Participants press the mouse-button if a
            5-digit number string is identical to the preceding string. Participants
            complete two blocks of 180 s, with a 20 s rest period between blocks. The task
            gives a measure of commission errors occurring when a participant makes a
            premature Go response to a Catch trial (occur 33% of trials). Single Key
            Impulsivity Paradigm (SKIP; Dougherty, Mathias, Marsh, & Jagar, 2005):
            Participants press the mouse-button to obtain a point reward. The magnitude of
            the reward is dependent on the delay between consecutive responses.
            Participants complete a four-minute trial. The task gives a measure of average
            inter-response time. Two Choice Impulsivity Paradigm (TCIP; Dougherty et al.,
            2005): Participants choose between two shapes representing a smaller-sooner (3
            points after 3 s) and larger-later (9 points after 9 s) point rewards.
            Participants complete 30 trials. The task gives a measure of the number of
            smaller-sooner choices. Monetary Choice Questionnaire (MCQ; Kirby, Petry, &
            Bickel, 1999): A pen-and-paper task on which participants choose between
            hypothetical large delayed rewards, and smaller more immediate rewards.
            Participants complete 27 items. The task gives a measure of discounting of
            delayed rewards (k). Delay Discounting Questionnaire (DDT): The DDT is a
            variation on the MCQ. The pen-and-paper procedure is identical to the MCQ;
            participants complete 212 items. Stimuli are presented in a fixed random
            order. The task gives a measure of discounting of delayed rewards (k).

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

Exploratory factor analysis was conducted using Mplus 7,2 (Muthén & Muthén, 1992–2012).
Participant demographics and correlations were analysed using Statistical Package for
Social Sciences (SPSS) version 22.

        <hss>Participant demographics characteristics</hss>

        Participant demographic information including age, average IQ and alcohol and drug
        consumption are reported. Gender differences on the tasks were calculated to
        ensure that there were no differences that may affect the factor structure.
        Pearson’s correlation coefficient was calculated to identify the relationship
        between age and impulsivity.

        <hss>Variable selection</hss>

        One primary dependent variable was selected per task for the factor analysis. This
        selection was made in part due to the comparatively small sample size; had the
        sample been larger, multiple measures from each task could have been included. The
        selection of one variable per task was also made to maintain consistency between
        tasks as each task contains a varying number of outcome variables and it is known
        that factor analysis depend heavily on the number of indicators included per
        expected factor– including multiple from a select number of measures would have
        caused imbalances in the factor structure by increasing shared variance (Russo,
        Leone, Lauriola, & Lucidi, 2008). Variables included in the factor analysis model
        were: DDT mean k value. MCQ mean k value. TCIP number of impulsive choices. IMT
        percentage commission errors. GNG percentage commission errors. Data were checked
        to ensure that any participant who did not understand the task, or displayed
        inconsistent responding, was excluded from that measure – see Section 3.1 for
        details of included participants. The SST, SKIP, DDT and MCQ were log 10
        transformed to correct issues of non-normality. All variables were coded so that
        large values indicate increased impulsivity.

        <hss>Correlations between task</hss>

        Pearson’s correlation coefficient was calculated to identify the correlations
        between impulsivity measures selected for the factor analysis. In an additional
        exploratory analysis, as a variables of interest not included in the primary
        analysis, correlations between the BIS-11 subscales and the behavioural measures
        of impulsivity were calculated to identify the relationship between self-report
        and behavioural measures of impulsivity.

        <hss>Factor analysis</hss>

        Exploratory factor analysis (EFA) was conducted to identify the factor structure
        of impulsivity. The sample size of 160 participants for the 11 items exceeds the
        suggested minimum ration of 5 participants per item (Gorsuch, 1983). EFA was
        carried out using full information maximum likelihood with Geomin oblique
        rotation. χ2, comparative fit index (CFI), a root mean square error of
        approximation (RMSEA), and standardized root mean square residual (SRMR) were used
        to evaluate the fit between the model and the data. CFIs of ⩾0.90 indicate a good
        fit to the data (Browne & Cudeck, 1993). A RMSEA value <0.05 indicate a good fit
        to the data (Browne & Cudeck, 1993). Well-fitting models obtain SRMR values <0.05
        (Cooke et al., 2013). As measures of appropriateness of factor analysis, a
        Kaiser–Meyer–Olkin (KMO) value >.5 indicates acceptable sampling adequacy. A
        significant result for Bartlett’s test of sphericity indicates that the null
        hypothesis that the correlation matrix is an identity matrix can be rejected.

<hs>  Missing data and exclusions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

BIS-11 Data were missing for one participant. SST Data were missing for 3 participants; a
further 9 were excluded for GoRTs > 1000msecs, or 100% Stop accuracy as it was assumed
that participants had not understood task instructions. GNG Data were missing from 2
participants, one participant was excluded for failing to stop to any Stop signals as it
was assumed that they had not understood task instructions. IMT Data were missing for 3
participants. SKIP Data for 3 participants were missing. DDT Data were missing for 1
participant, 14 participants were excluded according to the inclusion criteria (see
Johnson & Bickel, 2008). MCQ Data for 3 participants were missing. Full information
maximum likelihood (FIML) was used to handle missing data for the factor analysis and
therefore all 160 participants were included in the factor analysis (Enders, 2010).
Correlational analysis was performed on all included data.

<hs>  Participant characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The age of participants ranged from 18 to 45 (M 20.85; S.D. 3.79). Estimated verbal IQ
ranged from 90 to 124 (M 108; S.D. 7.19). Participants drank on average 17 units of
alcohol/week (range 0–72, S.D. 14.39). 40% of participants reported no drug use, 31%
reported marijuana use, 29% reported other drug use. There were no gender differences on
any impulsivity measure, see Table 1. There were significant associations between age and
the Two Choice Impulsivity Paradigm (r(160) = −.173, p = .029) and the Delay Discounting
Task (r(145) = .182, p = .029). There were no other correlations between age and any other
impulsivity measures [BIS-11, r(159) = .067, p = .40; SST, r(148) = .149, p = .07; GNG,
r(157) = −.017, p = .83; IMT, r(157) = −.046, p = .57; ISTfw, r(160) = .135, p = .09;
ISTrc, p(160) = .074, p = .35; MFF20, p(160) = .043, p = .59; SKIP, p(157) = −.036, p =
.65; MCQ, p(157) = .082, p = .31].

<hs>  Correlations between tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

The correlation matrix between primary variables of each task is presented in Table 2a.
Correlations between the BIS-11 subscales and each of the behavioural impulsivity measures
are presented in Table 2b.

<hs>  Factor analysis</hs>
  ~~~~~~~~~~~~~~~

A four-factor model was indicated and appeared to fit the data well [χ2(17) = 15.736, p =
0.5426; CFI = 1.000, RMSEA = 0.000, 90%CI = 0.000–0.660; SRMR = 0.031]. The KMO value was
.511. Bartlett’s test of sphericity was significant, x2(55) = 156.06. The scree plot (Fig.
1) was uninformative and indicated no clear number of factors. Four factors were retained
in the analysis. Factor 1 contained a high loading of the SST. Factor two represents RI
with loadings of the IST and MFF20. Factor 3 represents performance on the IMT. Factor 4
represents performance on the DDT and the MCQ. The SKIP, TCIP, GNG and the BIS-11 did not
load onto any factors. There were no significant correlations between factors. See Tables
3 and 4 for factor loadings and correlations.

<h>DISCUSSION</h>
----------

The current study provides important new insights into the structure of impulsivity. The
results indicate that impulsivity should not be considered a unitary construct and instead
represents a series of independent subtypes. Importantly, the results provide the first
factor analysis support for the suggestion of a distinct, well-defined factor of RI. There
was also support for the characterisation of behavioural impulsivity into additional
factors of MI and TI. The current findings indicated that a number of currently accepted
tasks as measurements of MI and TI cannot be considered as indexing these two subtypes and
therefore suggest that additional characterisations of impulsivity may be required.
Overall, there does not appear to be a strong underlying factor structure; instead,
measures purported to index impulsivity typically do not correlate other than in small
independent clusters. The study is the first to implement RI in factor analysis protocols.
The results indicated that all putative measures of RI loaded onto a single factor thereby
validating these measures and suggesting that, in addition to its clinical significance,
RI is distinct from other subtypes of impulsivity. The MFF20 has been criticised as being
confounded by other cognitive processes (Block, Block, & Harrington, 1974; Clark et al.,
2006; Southgate, Tchanturia, & Treasure, 2008) with the IST developed to circumvent these
issues (Clark et al., 2006). However, despite their procedural differences the current
study provides the first validation that the two measures index the same primary
underlying process. The results provide evidence that MI can be considered independent
from RI and TI; however, it appears that tasks purported to measure MI do not index the
same underlying processes. Whilst the SST, IMT and GNG are often used interchangeably, the
results indicate that they index different forms of inhibitory control. The SST loaded
onto a distinct factor, providing evidence that ‘action cancellation’ (Winstanley, 2011)
is dissociable from other forms of inhibitory control. While it has been proposed that the
GNG and IMT both index ‘action restraint’ (Winstanley, 2011) the two tasks loaded
separately suggesting that the tasks measure different processes. The IMT loaded onto the
third factor; on the task, participants must refrain from responding until the correct cue
is presented (Winstanley, 2011) and it has been noted that responding on the task is self-
generated where participants regulate their behaviour in anticipation of a ‘go’ signal
(Winstanley et al., 2010). The results suggest that this form of self-generated responding
may be an independent facet of impulsivity, distinct from action cancellation on the SST.
The GNG did not load onto any factor suggesting it should be treated with caution as a
measure of impulsivity. Overall, the data indicate that types of motor-impulsivity are
behaviourally characterisable and are dissociable. Investigators have developed pen-and-
paper and experiential tasks to measure TI, however there has been little research
validating the assumption that they index the same process. Our results indicate that pen-
and-paper measures (the DDT and MCQ) are analogous and that participants respond
consistently despite differences in reward and delay values. However, neither experiential
task loaded onto the factor indicating that they do not index TI as currently understood.
Ostensibly, the TCIP and pen-and-paper measures both require participants to select
between smaller-sooner and larger-later rewards. However, the tasks differ in the
magnitude and type of reward- and delay-values. The comparatively short delays on the TCIP
may not have been sensitive to individual differences (Winstanley et al., 2006). The point
rewards are received in the laboratory, removing expectations of inflation, future income
and the probability of receiving the delayed reward (Frederick, Loewenstein, & O’Donoghue,
2002). The SKIP is methodologically distinct, utilising a free-operant procedure – the
longer participants wait between consecutive responses, the more points they receive. The
underlying processes are relatively unexplored; the task correlated with the GNG
suggesting that the two may share underlying processes. The results provide evidence that
the SKIP and TCIP do not index TI processes as they are currently understood, and that
neither are analogous to pen-and-paper measures. Self-reported impulsivity on the BIS-11
did not load onto any factor. This supports evidence that self-report impulsivity loads
separately from behavioural tasks (Broos et al., 2012; Lane et al., 2003; Malle &
Neubauer, 1991; Meda et al., 2009) and suggests that the two are heterogeneous.
Interestingly, although self-reported impulsivity did not load onto any factor,
performance on the IMT was related to BIS-11 total score as well as the nonplanning
subscale, the MCQ also correlated with the nonplanning subscale whilst the SST was the
only task that correlated with the BIS-11 motor subscale. No behavioural task correlated
with the attentional subscale. These correlations suggest that there may be some limited
associations between self-reported impulsivity and performance on behavioural tasks. There
were no gender differences in impulsivity indicating that the model applies to both
genders, and age did not correlate with any of the measures except for the TCIP and DDT
indicating that for the most part impulsivity does not differ with age amongst our sample.
All participants were university students however we did not take a measure of income
which may have been an important demographic factor of interest. There are further
limitations to the analysis which should be discussed. Despite each of the impulsivity
tasks providing multiple outcome measures, only the primary impulsivity index was selected
from each. Including multiple measures may have provided a more nuanced profile of the
constructs under study. For example, the BIS-11 can be categorised into three sub-scores
of self-report impulsivity; as these were not included we cannot identify whether any
would have loaded onto any of the identified factors, although the lack of consistent
correlations between the subscales and the behavioural tasks suggest that they would not.
There were two primary reasons for this selection – to address the limited sample size and
to avoid imbalances in the number of variables included from each task. The number of
subjects is adequate based on our reduced selection of only one variable per task, and
selecting multiple variables from each task would have jeopardised this; a larger sample
size would have permitted more refined analysis of multiple outcome variables and future
studies with greater power are needed to evaluate the sub-scores for each task. The
selection of one variable per task was also made to maintain consistency between tasks.
Each of the tasks provide a differing number of outcome variables and had we selected
multiple from one task (e.g. the BIS-11) we would also have had to select multiple from
every other tasks to prevent imbalances in the factor structure (it is known that factor
analysis depend heavily on the number of indicators included per expected factor). In
light of this we made the decision to select only one per task. Unfortunately, in reality
such imbalances are unavoidable, with the Fixed Win and Reward Conflict versions of the
IST, and the two pen-and-paper measures of TI being very similar; these methodological
overlaps may have implications for the observed factor structure by increasing shared
variance. In summary, the results provide evidence that impulsivity should not be
considered a unitary construct, instead consisting of a series of independent subtypes.
The data provide compelling support for the suggestion of a distinct, well–defined factor
of RI. There was also support for the categorisation of behavioural impulsivity into
additional factors of MI and TI. However, the results suggest that a number of currently
accepted tasks cannot be considered as indexing these two subtypes, instead indicating
that additional characterisations of impulsivity may be important. The results indicate
that the IMT represents an additional facet of impulsivity. The data suggest that a number
of tasks purported to index impulsivity should be treated with caution, and the results
should be used as a basis for investigators in selecting tasks. It is hoped that the
results encourage more researchers to implement multiple tasks to index ‘impulsivity’, as
opposed to tasks in isolation.


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<ART>Goal conflict, ambivalence and psychological distress: Concurrent and longitudinal relationships
================================================================================

Authors: Nicholas J. Moberly, Joanne M. Dickson
DOI: 10.1016/j.paid.2018.03.008
Year: 2018  |  Pages: 38-42
ASJC codes: 3200
Keywords: Ambivalence, Anxiety, Conflict, Depression, Goals, Motivation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Conflict between goals (inter-goal conflict) and conflicting feelings about attaining particular goals (ambivalence) are believed to be associated with depressive and anxious symptoms, but have rarely been investigated together. Kelly et al. (2011, Personality and Individual Differences, 50, 531-534) reported that inter-goal conflict interacted with ambivalence to predict concurrent depressive symptoms in undergraduates, with ambivalence being more strongly associated with depressive symptoms for persons reporting less inter-goal conflict. We sought to replicate and extend this finding in a larger sample, using separate measures of inter-goal conflict and facilitation, and a longitudinal follow-up. Undergraduates (N = 210) rated their goal strivings for ambivalence, inter-goal conflict and facilitation, and completed measures of depressive and anxious symptoms that were repeated after one month. Inter-goal conflict (but not facilitation) and ambivalence were both uniquely positively associated with depressive and anxious symptoms concurrently, but did not predict symptom change. Inter-goal conflict and ambivalence did not interact to predict concurrent symptoms, but inter-goal conflict was associated with greater reductions in anxious symptoms for people reporting low ambivalence. Findings suggest that different forms of motivational conflict across the goal hierarchy are associated with symptoms, but do not exacerbate symptoms over time.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Making progress on personal goals imbues life with meaning and contributes to well-being
(Brunstein, 1993; Klinger, 1977; Klug & Maier, 2015), so it is unsurprising that goal
conflict has long been considered to be associated with psychological distress (Higginson,
Mansell, & Wood, 2011). This article examines how two different forms of conflict (inter-
goal conflict and goal ambivalence) contribute to anxious and depressive symptoms. A
person experiences inter-goal conflict when one of their goals makes it more difficult to
pursue their other goals (Emmons, 1986; Riediger & Freund, 2004). For example, a person's
goal to ‘spend more time with my family’ may conflict with their goal to “get promoted at
work”. Conversely, a person may experience inter-goal facilitation if one of their goals
makes it easier to pursue their other goals (e.g., “spend more time with family” may
facilitate the goal to “deepen my relationships”). Inter-goal conflict is associated with
negative affect and lower life satisfaction (Emmons, 1986) and more psychiatric symptoms
among undergraduates (Perring, Oatley, & Smith, 1988) and adolescents (Dickson & Moberly,
2010). However, some studies using undergraduate samples have not found associations
between inter-goal conflict and depressive (Emmons & King, 1988, Study 2; King, Richards,
& Stemmerich, 1998; Segerstrom & Solberg Nes, 2006) or anxious symptoms (Emmons & King,
1988, Study 2). In community samples, no significant correlations emerged between inter-
goal conflict and depressive symptoms (Wallenius, 2000) or negative affect (Kehr, 2003;
Romero, Villar, Luengo, & Gómez-Fraguela, 2009). Equivocal results may reflect the use of
bipolar measures that conflate inter-goal facilitation and conflict. Riediger and Freund
(2004) found that unipolar measures of inter-goal conflict and facilitation loaded on
distinct factors, with only inter-goal conflict being significantly associated with
negative affect at the between- and within-person level. Boudreaux and Ozer (2013) found
that inter-goal conflict, but not inter-goal facilitation, was positively correlated with
anxiety and negative affect in undergraduates; the correlation with depressive symptoms
was not significant. In their meta-analysis, Gray, Ozer, and Rosenthal (2017) revealed
that goal conflict was positively associated with psychological distress (weighted effect
size: r = 0.34), with studies using unipolar scales yielding larger effect sizes. Inter-
goal conflict may be less distressing if it represents competition among goals for a
shared limited resource (e.g., time or money) rather than inherently incompatible outcomes
(Riediger & Freund, 2004; Segerstrom & Solberg Nes, 2006). However, conflicted motives
about attaining specific goals, i.e., ambivalence (Bleuler, 1911; Sincoff, 1990), may
illustrate more profound motivational conflict that is more strongly associated with
psychological symptoms. Goal ambivalence has been conceptualised as an approach-avoidance
conflict about the pursuit of a particular goal (Emmons, King, & Sheldon, 1993) that is
generated by conflict between relevant goals at a higher level in the goal hierarchy
(Kelly, Mansell, & Wood, 2015). For example, a student may feel ambivalent about an essay-
writing goal because it is relevant to a higher-level goal conflict between excelling
academically and maintaining interpersonal relationships. Higher-level goal conflict may
be more irresolvable because such goals are self-defining (Powers, 1973). Goal ambivalence
has indeed been found to be associated with anxious and depressive symptoms among
undergraduates (Emmons, 1986; Emmons & King, 1988; King et al., 1998; but see Romero et
al., 2009, for null results). Other research has examined the association between
psychological symptoms and ambivalence about goals relevant to particular life stages. For
pregnant women, ambivalence about childbirth was associated with concurrent depressive
symptoms and increasing symptoms post-partum (Koletzko, La Marca-Ghaemmaghami, &
Brandstätter, 2015). In another sample, daily fluctuation in ambivalence about having the
child was associated with negative affect. In another study, ambivalence about attaining a
degree was associated with lower life satisfaction both concurrently and longitudinally
(Koletzko, Herrmann, & Brandstätter, 2015). Inter-goal conflict and ambivalence may
overlap because people will often feel ambivalent about conflicting goals (Emmons & King,
1988). Indeed, modest positive correlations have been reported between goal ambivalence
and inter-goal conflict at the within-person level (Emmons, 1986; King et al., 1998), if
not at the between-person level. Few studies have examined whether inter-goal conflict and
ambivalence have independent or interactive associations with symptoms (Kelly et al.,
2015). Although Emmons (1986) found that ambivalence but not inter-goal conflict explained
unique variance in psychological symptoms, this study was underpowered. Kelly et al.
(2011) reported that goal ambivalence was positively associated with concurrent depressive
and anxious symptoms, whereas inter-goal conflict did not predict significant additional
variance. Moreover, these forms of conflict interacted such that ambivalence was more
strongly associated with depressive symptoms for participants reporting less inter-goal
conflict. The authors speculated that ambivalence may be more distressing if it is not
attributable to the pursuit of conflicting lower-level goals, suggesting that the
ambivalence is generated by higher-level goal conflict. A person who strives to run
marathons and learn guitar may report inter-goal conflict due to limited leisure time, but
may experience no ambivalence if these pursuits are consistent with higher-level goals
(Kelly et al., 2015). Conversely, a person who strives to care for the vulnerable and
provide childcare may report no inter-goal conflict, but may experience ambivalence if
these pursuits conflict with a higher-order goal of being independent. A combination of
low inter-goal conflict and high ambivalence may indicate a distressing lack of
integration across levels of the goal hierarchy. However, Kelly et al.’s (2011) result
requires replication, and it is unclear whether the relationship between ambivalence and
depressive symptoms is moderated by lower levels of inter-goal facilitation and/or higher
levels of inter-goal conflict. To further illuminate the unique and interactive
relationship between inter-goal conflict, ambivalence and psychological distress, we
extended Kelly et al.’s (2011) research using a larger sample and distinct measures of
inter-goal conflict and facilitation (Riediger & Freund, 2004). We also examined whether
inter-goal conflict, goal ambivalence and their interaction would predict symptom change
over one month, consistent with the notion that inter-goal conflict actively contributes
to psychological distress. Boudreaux and Ozer (2013) found that inter-goal conflict
predicted increases in depressive and anxious symptoms over five weeks in undergraduates.
Similarly, Koletzko, La Marca-Ghaemmaghami, and Brandstätter (2015) found that ambivalence
about having a child in women was associated with worsening depressive symptoms after
birth. Based on the notion that conflict is deleterious at all levels of the goal
hierarchy (Powers, 1973), we hypothesised that inter-goal conflict and goal ambivalence
would each predict unique variance in anxious and depressive symptoms. Inter-goal
facilitation was included as a covariate, but was not expected to be associated with
anxious or depressive symptoms (Riediger & Freund, 2004). We sought to replicate Kelly et
al.’s (2011) interaction between ambivalence and inter-goal conflict, such that anxious
and depressive symptoms would be highest for individuals reporting high level of goal
ambivalence and low levels of inter-goal conflict. Prospectively, we expected that higher
levels of ambivalence and inter-goal conflict would each predict increases in anxious and
depressive symptoms. More tentatively, we predicted that the interaction between inter-
goal conflict and ambivalence would explain additional variance in symptom change.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Two hundred and ten undergraduate students (169 women, 41 men; M = 20.0 years, SD = 2.5,
range = 18–35) were recruited from the University of Exeter campus via online
advertisements. Participants were remunerated with course credit or £15.

<hs>  Materials and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Participants attended an initial 1 h session in which they provided informed consent,
before completing a personal strivings assessment, inter-goal conflict and facilitation
matrices, and depressive and anxious symptom scales.

        <hss>Personal goal strivings (Emmons, 1986)</hss>

        Participants first read instructions asking them to list at least ten personal
        goals, defined as “things that you typically or characteristically are trying to
        do”, by completing the stem: “I typically try to…” Examples were provided (e.g.,
        “Convince others that I am intelligent”) and participants were told that they
        should list goals that identified them as individuals, rather than goals that
        other people thought they should have. Participants who generated more than ten
        goals were asked to choose the ten that represented them most accurately. Allowing
        for minor wording changes, Emmons (1986) found that 82% of goals were consistent
        over one year.

        <hss>Goal ambivalence (Emmons, 1986)</hss>

        Participants rated their ambivalence about each of their goals on a 6-point scale
        from 0 (none at all) to 5 (extreme) in response to the following question:
        “Sometimes even though we successfully reach a goal, we are unhappy (e.g., if
        you're “trying to become more intimate with someone” and you succeed, you might
        also feel concern about being tied down). How much unhappiness do you or will you
        feel when you are successful in this striving?” Mean ambivalence scores across
        goals were calculated for each participant (α = 0.79). Goal ambivalence has
        previously shown a one-year stability correlation of 0.65 (Emmons & King, 1988).

        <hss>Inter-goal conflict and facilitation (Riediger & Freund, 2004)</hss>

        Participants next completed two 10 × 10 matrices to rate inter-goal conflict and
        facilitation respectively. In each matrix, each of the participant's ten goals was
        listed in both rows and columns. In the conflict matrix, participants rated the
        extent to which pursuing each of their goals in the rows “makes it more difficult
        to pursue” each of the other strivings across the columns. In the facilitation
        matrix, participants were asked to rate the extent to which pursuing each of the
        goals in the rows “makes it easier to pursue” each of the other goals across the
        columns, on a 6-point scale from 0 (not at all) to 5 (extremely). Thus,
        participants rated the extent to which each of their goals both conflicted with
        and facilitated each of their other goals (bidirectionally). Mean inter-goal
        conflict (α = 0.91) and facilitation ratings (α = 0.90) were calculated for each
        participant.

        <hss>Beck Depression Inventory–II (BDI-II; Beck, Steer, & Brown, 1996)</hss>

        Participants completed the BDI-II, a validated 21-item scale assessing depressive
        symptoms over the past two weeks. Each item is rated on a scale from 0 to 3,
        yielding a total score from 0 to 63 (α = 0.90).

        Generalized Anxiety Disorder–7 (GAD-7; Spitzer, Kroenke, Williams, & Löwe, 2006)

        Participants completed the Generalized Anxiety Disorder–7, a seven-item scale
        assessing the frequency of anxious symptoms over the past two weeks. Each item is
        rated on a four-point scale from 0 to 3, yielding a total score from 0 to 21 (α =
        0.85). Participants completed further goal measures not relevant to the current
        study, before making an appointment for a follow-up session one month later (M =
        35.0 days, SD = 5.4).

        <hss>Follow-up session</hss>

        One hundred and ninety-four (92.3%) participants returned for the follow-up, when
        they completed the BDI–II (α = 0.91) and the GAD–71 (α = 0.85), together with
        other measures irrelevant to the current study, before being remunerated.

<hs>  Cross-sectional analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Table 1 presents correlations and (untransformed) descriptive statistics for all
variables. Inter-goal facilitation scores clustered around the scale midpoint but two-
thirds of the sample reported mean inter-goal conflict and ambivalence scores below 1 on
the 0–5 scale. Sample means were below recommended cut-offs for mild depressive (Beck et
al., 1996) and mild anxious symptoms (Spitzer et al., 2006), and these variables were
highly correlated. Due to small means, depressive and anxious symptom scores, inter-goal
conflict and goal ambivalence were positively skewed so were log-transformed to improve
normality. Men reported less inter-goal facilitation than did women, t(208) = 1.99, p =
0.048, d = 0.35, but no other significant gender differences emerged. Inter-goal conflict
and ambivalence were each significantly positively correlated with depressive and anxious
symptoms at both time points. At Time 1, inter-goal facilitation was modestly positively
associated with anxious symptoms. Inter-goal conflict and facilitation were positively
correlated between persons: people reporting more conflict among their goals tended to
report more facilitation, perhaps reflecting a general response tendency. However, multi-
level models (accounting for clustering of goals within persons) revealed that inter-goal
conflict and facilitation were negatively correlated at the within-person level: goals
that conflicted more with other goals tended to be less mutually facilitative. Inter-goal
conflict and ambivalence were positively correlated at both levels of analysis. Inter-goal
facilitation and ambivalence were not significantly correlated at the between-person level
but were modestly negatively correlated at the within-person level. To assess unique and
interactive relationships, inter-goal conflict, facilitation and ambivalence were each
standardised before entry into a multiple regression model as predictors of Time 1
depressive symptoms in the first step, followed by the interactions between (i) inter-goal
conflict and goal ambivalence and (ii) inter-goal facilitation and goal ambivalence in the
second step.2 When entered together in the first step, inter-goal conflict, facilitation
and goal ambivalence jointly explained 12.1% of depressive symptom variance, F(3, 206) =
9.44, p < 0.001. Goal ambivalence was independently associated with depressive symptoms at
Time 1, β = 0.22, p = 0.002, as was inter-striving conflict, β = 0.20, p = 0.007, but
inter-striving facilitation was not a significant predictor, β = −0.00, p = 0.99.
Critically, when entered in the second step, the interactions between (i) inter-goal
conflict and goal ambivalence, and (ii) inter-striving facilitation and goal ambivalence,
jointly failed to explain significant additional variance in depressive symptoms at Time
1, ∆F(2, 204) < 1, p = 0.84, with neither individual interaction reaching significance, ps
> 0.54. An equivalent multiple regression analysis was conducted to predict Time 1 anxious
symptoms. When standardised and entered simultaneously in the first step, inter-goal
conflict, facilitation and ambivalence explained 14.0% of anxious symptom variance, F(3,
206) = 11.14, p < 0.001. Striving ambivalence was independently associated with anxious
symptoms at Time 1, β = 0.23, p = 0.001, as was inter-striving conflict, β = 0.19, p =
0.009, but inter-striving facilitation was not a significant predictor, β = 0.10, p =
0.13. Critically, when entered in the second step, the interactions between (i) inter-
striving conflict and goal ambivalence, and (ii) inter-striving facilitation and goal
ambivalence, jointly failed to explain significant additional variance in Time 1 anxious
symptoms, ∆F(2, 204) < 1, p = 0.81, with neither individual interaction reaching
significance, ps > 0.51.

<hs>  Longitudinal analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Paired t-tests revealed a small, statistically significant decrease in depressive symptoms
from baseline to follow-up, t(193) = 3.42, p = 0.001, d = 0.20, but no statistically
significant difference in anxious symptoms over this period, t(192) = 1.45, p = 0.15, d =
0.05. Further multiple regressions investigated whether inter-goal conflict and
ambivalence predicted change in depressive and anxious symptoms from Time 1 to Time 2
respectively. In the multiple regression predicting Time 2 depressive symptoms, Time 1
depressive symptoms was entered first, followed by standardised inter-goal conflict,
inter-goal facilitation, and goal ambivalence in the second step. Finally, the
interactions between (i) inter-goal conflict and goal ambivalence and (ii) inter-goal
facilitation and goal ambivalence were entered in the third step. Controlling for Time 1
depressive symptoms, inter-goal conflict, inter-goal facilitation and goal ambivalence
jointly failed to explain significant additional variance in Time 2 depressive symptoms,
F(3, 189) = 1.06, p = 0.37, ∆R2 < 0.01. Goal ambivalence, β = 0.10, p = 0.09, inter-goal
conflict, β = −0.05, p = 0.38, and inter-goal facilitation, β = −0.00, p = 0.97, were not
significant predictors. The interactions entered in the third step failed to explain
significant additional variance in Time 2 depressive symptoms, F(2, 187) = 1.35, p = 0.26,
∆R2 < 0.01, with neither interaction being significant, ps > 0.19. Thus, inter-goal
conflict, facilitation and goal ambivalence did not predict change in depressive symptoms,
independently or interactively. In the parallel multiple regression predicting Time 2
anxious symptoms, after entering Time 1 anxious symptoms, simultaneous entry of inter-goal
conflict, facilitation and goal ambivalence failed to explain additional variance in
anxious symptoms at Time 2, F(3, 188) < 1, p = 0.82, ∆R2 < 0.01. Goal ambivalence, β =
0.04, p = 0.43, striving conflict, β = −0.04, p = 0.45, and striving facilitation, β =
0.00, p = 0.97, were not significant predictors. The interactions entered in the third
step failed to explain additional variance in depressive symptoms at Time 2, F(2, 186) =
2.47, p = 0.09, ∆R2 = 0.01. However, because the crucial interaction between inter-goal
conflict and ambivalence was significant (β = 0.11, p = 0.03; the other interaction was
not, p = 0.77), we proceeded to explicate it. Fig. 1 plots (log) T2 anxious symptoms for
persons scoring one standard deviation above and below the mean on inter-goal conflict and
ambivalence, calculated at mean levels of T1 anxious symptoms and inter-goal facilitation.
Tests of simple slopes revealed that higher levels of inter-goal conflict at Time 1 were
associated with reductions in anxious symptoms at Time 2 for persons with lower goal
ambivalence (β = −0.15, p = 0.04). However, levels of inter-goal conflict at Time 1 were
not significantly associated with levels of anxious symptoms at Time 2 for persons with
higher goal ambivalence (β = 0.04, p = 0.53).

<h>DISCUSSION</h>
----------

Our results support theoretical perspectives and empirical research suggesting that goal
conflict is associated with psychological distress (Higginson et al., 2011). The positive
association between inter-goal conflict and concurrent psychological symptoms mirrors the
results of a recent meta-analysis (Gray et al., 2017). As hypothesised, inter-goal
facilitation was not uniquely significantly associated with anxious or depressive
symptoms, consistent with distinct relationships for inter-goal conflict and facilitation
(Riediger & Freund, 2004). The relationship between inter-goal conflict and symptoms is
unlikely to be due to a general tendency for distressed people to make more pessimistic
goal ratings, because no negative correlation emerged between inter-goal facilitation and
symptoms. Inter-goal facilitation may be more relevant to psychological well-being than to
distress symptoms (Riediger & Freund, 2004). Consistent with previous research (Emmons &
King, 1988; King et al., 1998), goal ambivalence was associated with greater anxious and
depressive symptoms. Ambivalence was moderately positively associated with inter-goal
conflict at both the between-person and within-person level of analysis, but was uniquely
associated with both anxious and depressive symptoms, suggesting that they are not
mutually redundant. Our study had greater statistical power (0.80 to detect a small-medium
effect size f2 = 0.05) than those reported by Emmons (1986) and Kelly et al. (2011), which
may explain why they did not find that goal ambivalence and inter-goal conflict had unique
associations with symptoms. Goal ambivalence and inter-goal conflict may reflect
motivational conflict at higher and lower levels of the goal hierarchy respectively (Kelly
et al., 2015). Furthermore, whereas inter-goal conflict must be consciously reported,
ambivalence towards goals could suggest higher-level goal conflict that is outside
conscious awareness. The unique contributions of inter-goal conflict and ambivalence
observed here support the utility of using distinct measures to capture motivational
conflict associated with distress throughout the goal hierarchy. We found no evidence for
an interaction between ambivalence and inter-goal conflict in predicting concurrent
distress symptoms. Using a larger sample and a unipolar measure of inter-goal conflict, we
did not replicate Kelly et al.’s (2011) finding that inter-goal conflict buffered the
relationship between ambivalence and depressive symptoms. These authors speculated that
ambivalence may be more closely associated with psychological distress at lower levels of
inter-goal conflict because this combination implicates unconscious higher-order goal
conflicts that are difficult to resolve. Instead, our results suggest that ambivalence is
associated with psychological symptoms at high and low levels of inter-goal conflict.
Thus, psychological distress is associated with both mid-level conscious conflict and
higher-level goal conflict that generates ambivalence (Kelly et al., 2015). This
combination is illustrative of a low level of motivational integration across the goal
hierarchy, which may be consistent with goal blockage and negative affect (Emmons & King,
1988). It is noteworthy that people with more depressive (and to a lesser extent, anxious)
symptoms report proportionately more abstract goals (Dickson & MacLeod, 2004; Dickson &
Moberly, 2013; Emmons, 1992). Abstract goals are rated as more difficult (Emmons, 1992),
and their centrality to the self may make goal conflicts at this level appear
irresolvable. Counter to expectations, neither inter-goal conflict nor goal ambivalence
predicted change in anxious or depressive symptoms over one month. Nevertheless, a
significant interaction revealed that people with high levels of inter-goal conflict and
low levels of ambivalence experienced reductions in anxious symptoms. Although it would be
inappropriate to over-interpret this unexpected finding, which did not emerge for
depressive symptoms, moderate conflict or differentiation among goal pursuits may protect
against anxiety in the absence of ambivalence. Previous longitudinal studies have not
examined the longitudinal interaction of inter-goal conflict and ambivalence, and should
seek to replicate this result. Our longitudinal results are contrary to Boudreaux and
Ozer's (2013) finding that goal ambivalence predicted change in depressive symptoms among
undergraduates, and Koletzko, Herrmann, and Brandstätter’s (2015) finding that mothers'
ambivalence about the specific goal of having a child predicted increased depressive
symptoms post-partum. It could be concluded that our longitudinal results suggest that
inter-goal conflict is a concomitant rather than a cause of distress. However, depressive
and anxious symptoms were highly stable over the one month period, such that it was
difficult for other predictors to predict change. Furthermore, we elicited goals as
enduring strivings that are relatively stable (Emmons, 1986), while ambivalence and inter-
goal conflict ratings demonstrate considerable stability (Emmons & King, 1988). Therefore,
any long-established pattern of motivational conflict may not predict further increases in
psychological distress. Consistent with this, Kehr (2003) found that emerging but not
enduring inter-goal conflict predicted changes in affect over eight weeks in managers.
Studies indicate that within-person fluctuations in motivational conflict are correlated
with state affect (Koletzko, La Marca-Ghaemmaghami, & Brandstätter, 2015; Riediger &
Freund, 2004), suggesting that changes in inter-goal conflict or ambivalence that are
associated with the adoption of new strivings might predict increases in psychopathology.
Although our findings illuminate the role of distinct forms of motivational conflict in
contributing to psychological distress, this study has limitations. First, we used a
single item to measure goal ambivalence that asked participants to what extent they would
experience negative emotions after goal attainment. Koletzko, Herrmann, and Brandstätter
(2015) argued that this measure does not capture the contradictory motives entailed in
ambivalence, and developed a new scale for this purpose. Second, we were unable to
determine whether the association between inter-goal conflict and symptoms was related to
inherent incompatibility between goals or competition between goals for a limited
resource, although these dimensions correlate positively (Riediger & Freund, 2004). Some
studies (e.g., Segerstrom & Solberg Nes, 2006) have recruited independent judges to rate
inter-goal conflict to obtain more objective judgements, which risks failing to capture
idiosyncrasies relating to personal goal strivings. We used an undergraduate sample whose
strivings may be more homogenous than older adults who have a more consolidated identity.
Finally, it is unclear to what extent our findings are influenced by the probable
inclusion of participants who would meet diagnostic criteria for mood disorders.
Nevertheless, the association between goal conflict and well-being is relatively
consistent across samples (Gray et al., 2017). In conclusion, our results suggest that
both inter-goal and intra-goal conflict are uniquely associated with psychological
distress, such that goal ambivalence is associated with anxious and depressive symptoms
for individuals reporting high and low levels of inter-goal conflict. Although our results
suggest that chronic goal conflict may not exacerbate symptoms, future research could
usefully concentrate on examining cross-lagged relationships between different forms of
motivational conflict and psychological distress in periods when goal strivings are
adopted or discarded.


<h>REFERENCES</h>
----------

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<ART>Going the extra green mile: When others' actions fall short of their responsibility
================================================================================

Authors: Kathryn Buchanan, Riccardo Russo
DOI: 10.1016/j.jenvp.2015.03.002
Year: 2015  |  Pages: 82-93
ASJC codes: 3202, 3207
Keywords: Action, Responsibility, Self-reported energy conservation behaviors, Shortfall

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The present research examined whether the environmental responsibility and actions attributed to large scale organizations, such as the government, can influence people's environmental efforts. In particular, we examined whether people increase or decrease their willingness to enact energy conservation behaviors (ECB) when there is a shortfall between others' actions and their responsibility. In Studies 1 and 2 we found that willingness to enact ECB was positively correlated with judgements about each of the organizations' eco-responsibility but not their eco-actions. Interestingly, each of the organizations' actions were perceived as falling short of their responsibility and this shortfall was positively associated with willingness to enact ECB. In Study 3, we found that manipulating respondents perceptions of government shortfall increased participants' willingness to enact ECB. Overall our findings provide support for social compensation theory as when others actions fall short of their responsibility people are prepared to "go the extra green mile".

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Environmental campaigns and policy initiatives often attempt to influence people's
behaviors (DEFRA, 2008; Owens, 2000). For example, a discussion paper from the UK cabinet
office argued that in striving for green behaviors, “the eventual aim is to entrench a
habit of personal responsibility” (2004, p.5). However, while the onus appears to be on
individuals there are other key actors or agents who also have a role to play in energy
conservation such as firms, communities, governments, and international organizations (see
Stern, 1992). Yet, to date, this wider social context has typically been overlooked in
psychological research. Consequently, it remains to be seen if people's willingness to
enact Energy Conservation Behaviors (ECB) is influenced by (a) the responsibility ascribed
to others to conserve energy, (b) the actions others are seen to be taking and, (c)
incidences in which other agents' responsibility to conserve energy falls short of their
perceived eco-actions.

<hs>  The influence of other organizations on individual environmental efforts</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We propose that people's actions are influenced by collective dynamics, such that
individuals look to others (including larger organizations) when setting their own
behavior standards. We suggest this on the basis that people do not operate in a social
and political vacuum; rather they are aware that other organizations and entities have a
role to play in energy conservation. Indeed, in several qualitative studies it has emerged
that people consider a number of organizations to be responsible for environmental efforts
(Barr, Gilg, & Shaw, 2011; Hargreaves, Nye, & Burgess., 2013; Hinchlifffe, 1996;
Lorenzoni, Nicholson-Cole, & Whitmarsh, 2007). Interestingly, such findings emerged
despite the fact that the majority of these qualitative studies did not seek to examine
the role of other agents in environmental behaviors - which suggests that such perceptions
may be pervasive. Moreover, it is likely that these perceptions are fostered by the media
which frequently provides commentary on the environmental efforts of a variety of agents
and institutions. For example, in April 2014 the UK was hit by high levels of air
pollution caused by a combination of local emissions, light winds, pollution from the
continent, and dust from the Sahara. News articles were quick to acknowledge that such
pollution could bring further attention to the, “government's long-term failure to reduce
air pollution” (BBC, 2014). As such it is clear that a person's environmental action is
situated in a broader set of social relations that need to be taken into consideration
(see also Catney et al., 2013).

<hs>  Responsibility</hs>
  ~~~~~~~~~~~~~~

The link between personal responsibility and willingness to enact or support ECB has been
established in a multitude of research studies (e.g., Guagnano, Dietz, & Stern, 1994;
Hines, Hungerford, & Tomara, 1987; Hunecke, Blobaum, Matthies, & Hoger, 2001; Jansson,
Marell, & Nordlund, 2010; Kaiser, Ranney, Hartig, & Bowler, 1999; Kaiser & Shimoda, 1999;
Nordlund & Garvill, 2002; Steg, Dreijerink, & Abrahamse, 2005). In contrast, far less is
known about the relationship between ascriptions of environmental responsibility to other
agents and personal willingness to enact ECB. Yet, it is apparent from both quantitative
and qualitative studies, that individuals are aware that other agents, such as their
neighbours, the government, corporate bodies (e.g., city council, offices) and
multinationals, have a role to play in energy conservation (e.g., Hargreaves, Nye, &
Burgess, 2010; Hinchliffe, 1996; Lorenzoni et al., 2007; Stern, Dietz, & Black, 1985).
However, it remains to be seen how these perceptions of others' environmental obligations
influence people's own environmental efforts. According to the bystander effect, we might
expect a diffusion of responsibility to occur and individuals to be less inclined to help
by enacting ECB when responsibility is distributed among several others (Darley & Latané,
1968; Latané & Darley, 1970; Latané & Nida, 1981). Yet, on the other hand, if individuals
consider both themselves and others responsible for energy conservation this may foster a
sense of shared responsibility, such that willingness to enact ECB is positively
influenced by ascriptions of responsibility to others.

<hs>  Action</hs>
  ~~~~~~

Past research suggests that social norms play a pervasive role in an individual's
willingness to enact ECB (e.g., Barr et al., 2011; Cialdini, Reno, & Kallgren, 1990,
Goldstein, Cialdini, & Griskevicius, 2008; McDonald, Fielding, & Louis, 2013; Nolan,
Schultz, Cialdini, Goldstein, & Griskevicius, 2008; Schultz, Nolan, Cialdini, Goldstein, &
Griskevicius, 2007). Typically, marketing campaigns use social norms to try and influence
people's behaviors by changing perceptions of what is considered normal (descriptive
norms) or socially acceptable (injunctive norms). For instance, researchers found that
hotel guests were significantly more likely to re-use their towels when presented with the
following normative appeal, “Join your fellow guests in helping to save the environment”,
than when presented with the message, “Help save the environment” (Goldstein et al.,
2008). Social norms can also lead people to act in ways that are detrimental to the
environment. For example, people are more likely to litter in littered environments, and
this effect is even more pronounced if they have witnessed another person drop litter
(Cialdini et al., 1990 Experiment 1). As such, there is substantial support for the idea
that people may enact either more or less ECB depending on what others are (or are not)
doing. However, typically norms have been examined at the individual level and, to the
best of our knowledge; there is currently no research that examines if the norms of larger
social organizations (e.g., the government, energy suppliers) influence personal
environmental efforts. On the one hand, the environmental actions that an organization
takes (or does not take) may set an important precedent (i.e., it may act as a norm),
especially given the position of power these organizations may hold. Yet, on the other
hand, people may not consider the actions of larger organizations as relevant if they
perceive that they are operating on a substantially different level from themselves.

<hs>  Considering responsibility and action together</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We propose that in order to understand if the wider social context contributes to
intentions to enact eco-behaviors it is necessary to consider both perceptions of others'
eco-responsibilities, and others' eco-actions. This is because while responsibility and
action are distinct and separable from one another they are also clearly related. This
relation stems from their definition. Specifically, responsibility is defined as, “the
state or fact of having a duty to deal with something …”, while action is defined as, “the
fact or process of doing something”. In other words, responsibility is about “what we
ought to be doing” whereas action is about “what we are actually doing”. Thus when people
think about responsibility it is likely that they also consider action. Of course, this
does not mean that the two inevitably co-occur in an applied setting. Rather, it is
possible to be responsible for something but not to take action and vice versa. However,
given the operational links between responsibility and action there are two good reasons
for considering the dual influence of both factors on intentions to enact ECB. First,
considering action without responsibility may render the influence of action irrelevant.
If an agent is not considered responsible for conserving energy then their actions or
inactions are irrelevant and may have little bearing on our own actions. Second,
considering action alongside responsibility provides the basis for moral judgements to be
made about whether other agents are meeting their environmental responsibilities. As such,
considering both responsibility and action together enables us to address an important and
hitherto unanswered research question: to what extent are others' actions seen as matching
their responsibility and in cases where others' action are perceived as falling short of
their responsibility how does this influence personal willingness to enact ECB? In the
present paper we refrain from making specific predictions about whether perceptions of
others' shortfall will lead to either an increase or decrease in willingness to enact ECB.
We argue that to do so would be inappropriate given that there are psychological
mechanisms that can be used to infer support for either possibility. Specifically, when
confronted with others' shortfall, the sucker effect and feelings of personal inefficacy
may explain why people will decrease their efforts; whereas social compensation theory may
explain why people will increase their efforts.

        <hss>Doing less: running a mile</hss>

        The ‘sucker effect’ describes a phenomenon that occurs when individuals experience
        motivation loss when they suspect that capable others are not contributing (Kerr,
        1983). There is some indication from qualitative studies that the sucker effect
        may occur in response to perceptions that powerful organizations are failing to
        meet their environmental responsibilities (Barr et al., 2011; Hinchliffe, 1996).
        For example, one interviewee observed, “But it is discouraging when you hear …
        that places like America won't sign up to the Kyoto agreement … That's just
        pushing us into thinking, ‘well, why should we bother? ’” (Barr et al., 2011,
        p.716), while another interviewee commented, “I am one person and you think, well
        why am I going to change my lifestyle if all these other people aren't? It's human
        nature” (Lorenzoni et al., 2007, p.451). Diminished feelings of personal efficacy
        or perceived helplessness may also lead individuals to do less when others'
        actions fall short of their responsibility. Personal efficacy refers to “the
        belief in one's capabilities to organize and execute the courses of action
        required to manage prospective situations.” (Bandura, 1995, p.2). We suggest that
        individuals' personal efficacy may be undermined in the face of powerful global
        entities failing to live up to their environmental responsibilities. Indeed, there
        is some suggestion of this in qualitative research: “I'm impotent in a way because
        America didn't sign up to the Kyoto agreement” (Lorenzoni et al., 2007, p.450) and
        in quantitative research findings that show perceived behavioral control is a
        strong predictor of environmental behaviors (e.g., Heath & Gifford, 2002; Kaiser &
        Gutscher, 2003).

        <hss>Doing more: going the extra green mile</hss>

        Social compensation theory (SCT) proposes that in a collective setting people may
        work harder or contribute more effort to group tasks to compensate for others when
        they expect their co-workers to perform poorly on a meaningful task (Williams &
        Karau, 1991). As such, if extrapolated from a small group context (where SCT has
        previously been studied) to a more societal context, SCT provides a theoretical
        basis for why people may be more likely to increase their own environmental
        efforts if they perceive a discrepancy between others' actions and their
        responsibility. Notably, for social compensation to occur in an environmental
        setting three conditions need to be met. First, individuals would need to
        attribute responsibility for energy conservation both to other agents and to
        oneself to ensure energy conservation is considered an important shared goal.
        Second, participants would need to perceive that the actions others were taking to
        conserve energy were minimal or ineffective. Third, as social compensation theory
        is grounded in the collective effort model (Karau & Williams, 1993), individuals
        would need to perceive that their environmental efforts could make at least some
        difference to the goal of energy conservation.

<h>CURRENT RESEARCH</h>
----------------

In Studies 1 and 2 we utilized a correlational design to examine if willingness to enact
ECB were associated with perceptions of others environmental responsibilities, actions,
and the discrepancies between others responsibility and actions. In Study 3, we employed
an experimental design and manipulated the extent to which the government's actions were
seen as falling short of their responsibility to examine the effects on willingness to
enact ECB.

<h>CORRELATIONAL STUDIES: STUDIES 1 AND 2</h>
--------------------------------------

In both Studies 1 and 2, we administered a questionnaire measuring participants'
willingness to enact ECB, perceptions of others responsibility, actions, and the
discrepancies between others responsibility and actions (i.e., the shortfall). In Study 1,
shortfall was calculated by subtracting actions scores from responsibility scores. In
Study 2 we aimed to replicate the results obtained in Study 1 and to extend the findings
from Study 1, by administering measures of shortfall to ensure that the results we
obtained were not the product of measurement biases.

<hs>  Procedure</hs>
  ~~~~~~~~~

In Study 1, participants were presented with a list of six agents displayed in a
randomized order and were asked to rate the extent to which each agent was responsible for
conserving energy and was taking action to conserve energy. We presented these rating
tasks to participants on two different pages because we aimed to avoid highlighting any
discrepancies between others' eco-responsibility and eco-actions (i.e., others' shortfall)
lest this affected ECB ratings. Having completed the rating tasks, participants then
indicated their willingness to enact ECB. All measures are detailed below in the order
they were presented. In Study 2, we followed the same procedure. However, this time
participants were randomly assigned to complete either (a) measures where shortfall was
computed by subtracting action ratings from responsibility ratings (as per Study 1) or (b)
bipolar measures of shortfall (ranging from “action is less than responsibility” to
“action is more than responsibility”). Participants then completed the Environmental
Government Judgement Scale (EGJS). This is a 15 item scale that we developed to measure
perceptions that the governments environmental actions were (i) less than, (ii) in line
with, or (iii) exceeding their responsibility. We developed and included this measure to
avoid relying on scales comprised of the difference score calculated between two single
items. After completing the EGJS, participants then indicated their willingness to enact
ECB before providing their responses to a scenario where governments' environmental
actions were described as falling short of their responsibility. We focused on the
government, as opposed to other organizations, because, in principle, the government has
the most control via legislation. In asking participants explicitly for their responses to
the shortfall scenario we were able to see if their self-reported responses to shortfall
would be in line with the correlations between shortfall and willingness to enact ECB.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

In Studies 1 and 2 we recruited participants using a convenience sampling method via
Amazon's Mechanical Turk1 to respond to an online survey entitled, “Social Issues and Your
Opinions”. All participants were USA citizens. In Study 1, a total of 197 participants
(103 males, 94 females) aged from 18 to 73 (M = 33.32, SD = 12.99) completed the survey.
In Study 2, 212 participants (128 males, 84 females), aged from 19 to 72 (M = 34.34, SD =
11.98) completed the survey. Of these 212 participants, 108 completed shortfall ratings by
providing action and responsibility ratings and 104 completed judgements of the bipolar
shortfall measures.

        <hss>Responsibility and action judgements</hss>

        Participants provided their own judgements about the extent to which they
        agreed/disagreed that each of the six agents were (a) responsible for conserving
        energy and (b) taking action to conserve energy. All judgements were completed
        using 7-point scales from 1 (‘Strongly Disagree’) to 7 (‘Strongly Agree’). The
        agents listed were: myself, other consumers apart from me, the government, the
        energy suppliers, the big countries that use the most energy (hereafter referred
        to as industrial countries), and industrial factories. We selected these 6 agents
        based on the findings from a pilot study in which 10 participants (3 males, 7
        females aged between 18 and 60, Mage = 31, SD = 12.27) responded to the open-ended
        question: ‘In your opinion who does the responsibility lie with to conserve
        energy?’ We computed a mean score of ‘Other Agents’ Shortfall’ comprised of
        shortfall ratings of the following agents: the government, the energy suppliers,
        industrial factories and countries. We excluded “other consumers” from this mean
        score because we reason that participants will likely perceive “other consumers”
        as more similar to themselves than to the other agents. In Study 1, we always
        measured responsibility first and action second. In Study 2, we administered
        action ratings first and responsibility ratings second. In administering these
        measures in a different order we aimed to rule out the possibility that our
        results were influenced by ordering effects2

        <hss>Shortfall judgements (subtracting action from responsibility)</hss>

        Shortfall judgements were calculated by subtracting action ratings from
        responsibility ratings. Hence, a positive figure indicates a perception that the
        actions that others are taking to conserve energy fall short of the responsibility
        that others have to conserve energy.

        <hss>Shortfall judgements (a bipolar scale, Study 2 only)</hss>

        In Study 2, half of the participants were randomly assigned to complete shortfall
        judgements using a bipolar scale. Specifically, they were asked to indicate for
        each agent, ‘if the action they take to conserve energy measures up to the
        responsibility they have to conserve energy’ using a 13 point bipolar scale
        ranging from −6 (“action is less than responsibility”) to 6 (“action is more than
        responsibility”). The midpoint of 0 was labelled “action is equal to
        responsibility”. We used a 13 point scale to ensure that results were comparable
        with the shortfall scores that we obtained by subtracting action ratings from
        responsibility ratings as this previous method allowed scores to range −6 and 6.
        In subsequent analyses, we reverse scored all responses so that a positive score
        equated to more shortfall.

        <hss>The Environmental Government Judgement Scale (EGJS, Study 2 only)</hss>

        In Study 2, we developed our own measure to assess the relationship between
        perceptions of government's responsibility to conserve energy and perceptions of
        the government's energy conservation actions. Logic dictates that there are only
        three possible relationships between these two variables. Accordingly, we
        generated a pool of statements intended to reflect beliefs that the government's
        actions (i) fell short of its responsibility, (ii) were in line with its
        responsibility, and (iii) exceeded its responsibility. In total we generated 15
        statements, 5 for each of the possible three relationships. Participants were
        asked to indicate their agreement/disagreement with each statement using a 7-point
        scale ranging from 1 (‘Strongly Disagree’) to 7 (‘Strongly Agree’). All items are
        listed below in the results section in Table 3.

        <hss>Government shortfall scenario (Study 2 only)</hss>

        We asked participants to report what they would do if the government's action to
        conserve energy fell short of its environmental responsibility. Responses were
        made using a 5-point scale ranging from 1 (‘Decrease my environmental efforts a
        lot’) to 5 (‘Increase my environmental efforts a lot’). The midpoint of the scale
        (i.e., 3) represented ‘make no change to my environmental efforts’. Participants
        were then asked to provide qualitative explanations for the answer they had given.

        <hss>Willingness to enact ECB</hss>

        In both Studies 1 and 2, participants indicated the likelihood that they would
        make a concerted effort to enact each ECB using a 7-point scale ranging from 1
        (very unlikely) to 7 (very likely). Six out of eight of these items were adapted
        from the Student Environmental Behavior Scale (Markowitz, Goldberg, Ashton, & Lee,
        2012, p.99). We avoided selecting items that may be dependent on people's
        circumstances (e.g., the extent to which they have the opportunities to use public
        transport, carpool, replace CFL light bulbs, etc.) and instead focused on energy
        conservation behaviors that in theory most people could enact. Both exploratory
        and confirmatory factor analysis performed on Studies 1 and 2 revealed a two
        factor structure (see Supplementary Materials). Factor 1 consisted of items
        representing effortful ECB: ‘Donate money to research projects designed to reduce
        carbon emissions’, ‘Start a petition to support environmental protection efforts’
        and ‘Tell others about ways in which they can be environmentally friendly’. Factor
        2 consisted of items representing easier ECB: ‘Turn my thermostat down by one
        degree’, ‘Switch off lights in unoccupied rooms’, and, ‘Avoid leaving electronic
        appliances in stand by modes’. In both Studies 1 and 2 both subscales had good
        internal reliability (Study 1: Easy: α = .74, Effortful: α = .76. Study 2: Easy: α
        = .70, Effortful: α = .80) and were significantly positively correlated (Study 1:
        r = .44, p < .01, Study 2: r = .62, p < .01).

        <hss>Responsibility and action and shortfall judgements</hss>

        Means, standard deviations, and standard errors indicating respondents'
        perceptions of each agent's responsibility to conserve energy and the actions each
        agent is perceived to be taking to conserve energy are shown in Table 1.

        <hss>Responsibility ratings</hss>

        In both Studies 1 and 2, respondents' responsibility ratings indicate that each of
        the agents is perceived to be at least somewhat responsible for conserving energy
        (means ranged from 5 to 6). Overall, participants tended to rate their own
        responsibility to conserve energy as less than the other agents' responsibility.
        To examine if these differences were statistically significant, we conducted a
        series of pairwise comparisons where the significance level adopted for the
        results was adjusted to .01 to control for the Familywise error rate. In Study 1,
        the results showed that participants rated their own responsibility for conserving
        energy as significantly less than other agents' responsibility, although the
        effect sizes obtained were small (the government: t(196) = −2.77, p < .01, 95% CI
        = −.46 to −.08, d = −0.20, industrial countries t(196) = −4.25, p < .01, CI =
        −0.58 to −0.21, d = −0.31, energy suppliers: t(196) = −2.44, p < .01, 95% CI =
        −0.47 to −0.05, d = −0.20, industrial factories: t(196) = −3.87, p < .01, 95% CI =
        −0.60 to −0.19, d = −0.32, and other individual consumers: t(196) = 1.90, NS, 95%
        CI = 0.02 to 0.39, d = 0.11)3 In Study 2, participants again tended to rate their
        own responsibility as slightly less than other agents' responsibility, although
        these differences were not large enough to reach significance and the effect sizes
        were negligible (the government: t(107) = −79, NS, 95% CI = −0.42 to 0.18, d =
        −0.08, industrial countries t(107) = −1.91, NS, 95% CI = −0.58 to 0.01, d = −0.21,
        energy suppliers: t(107) = −0.71, NS, 95% CI = −0.39 to 0.18, d = −0.07,
        industrial factories: t(107) = −.24, NS, 95% CI = −0.34 to 0.27, d = −0.02 and
        other individual consumers: t(107) = 1.31, NS, 95% CI = −.04 to 0.21, d = 0.07).
        Perceptions of other agents' responsibility did not appear to diminish
        participants judgements of their own responsibility, in fact the more participants
        felt other agents were responsible the more they also felt they too were
        responsible (Study 1: r = .57 and Study 2: r = .55, both ps < .01).

        <hss>Action ratings</hss>

        In both Studies 1 and 2, the data show that participants were less inclined to
        agree that other agents are taking action to conserve energy with mean ratings for
        each agent typically falling between 3 and 4. This was with the exception of
        respondents own actions for which the mean score was higher at 5.21 in Study 1,
        and 5.17 in Study 2. This suggests that participants believe they are taking at
        least some action to conserve energy and that the action they are taking is more
        than that of both other individual consumers and other agents (Study 1: other
        individual consumers: t(196) = 7.84, p < .01, 95% CI = 0.56 to 0.94, d = .54, d =
        0.75, the government: t(196) = 8.37, p < .01, 95% CI = 0.86 to 1.38, d = 0.75,
        industrial countries: (t(196) = 10.75, p < .01, 95% CI = 1.23 to 1.77, d = 0.96,
        energy suppliers: t(196) = 8.84, p < .01, 95% CI = 0.99 to 1.55, d = 0.84, and
        industrial factories: t(196) = 11.09, p < .01, 95% CI = 1.28 to 1.84, d = 1.00).
        Study 2: other individual consumers: t(107) = 3.72, p < .01, 95% CI = 0.24 to .79,
        d = 0.41, the government: t(107) = 5.43, p < .01, 95% CI = 0.69 to 1.49, d = 0.76,
        industrial countries: (t(107) = 7.95, p < .01, 95% CI = 1.25 to 2.08, d = 1.08,
        energy suppliers: t(107) = 5.99, p < .01, 95% CI = 0.79 to 1.57, d = 0.77 and,
        industrial factories: t(107) = 9.27, p < .01, 95% CI = 1.43 to 2.21, d = 1.23)).

        <hss>Shortfall ratings: responsibility minus action</hss>

        There were significant differences between each of the agents' eco responsibility
        ratings and their corresponding eco-actions, such that others' eco-actions fell
        short of their responsibility (other individual consumers: t(196) = 7.07, p < .01,
        95% CI = .62 to .1.10, d = .65, the government: t(196) = 11.80, p < .01, 95% CI =
        1.35 to 1.90, d = 0.65, industrial countries: (t(196) = 13.96, p < .01, 95% CI =
        1.83 to 2.43, d = 1.40, energy suppliers: t(196) = 12.47, p < .01, 95% CI = 1.48
        to 2.05, d = 1.19, and industrial factories: t(196) = 14.35, p < 01, 95% CI = 1.90
        to 2.50, d = 1.45). Study 2: other individual consumers: t(107) = 5.67, p < .01,
        95% CI = 0.56 to .1.18, d = 0.68, the government: t(107) = 9.89, p < .01, 95% CI =
        1.32 to 1.98, d = 1.12, industrial countries: (t(107) = 11.07, p < .01, 95% CI =
        1.97 to 2.82, d = 1.55, energy suppliers: t(107) = 9.17, p < .01, 95% CI = 1.35 to
        2.09, d = 1.12, and industrial factories: t(107) = 11.55, p < 01, 95% CI = 1.91 to
        2.69, d = 1.46)). Interestingly, participants perceived even their own eco-actions
        as falling short of their eco-responsibility (Study 1: t(196) = 2.54, p < .01, 95%
        CI = 0.05 to 0.42, d = 0.18, Study 2: (t(107) = 3.67, p < .01, 95% CI = 0.20 to
        0.67, d = 0.32)). Nonetheless, participants own shortfall was still seen to be
        significantly smaller than others' shortfall (Study 1: other individual consumers:
        t(196) = −5.96, p < .01, 95% CI = −0.82 to −0.42, d = −0.41, the government:
        t(196) = −10.05, p < .01, 95% CI = −1.66 to −1.11, d = −0.84, industrial
        countries: (t(196) = −12.65, p < .01, 95% CI = −2.19 to −1.59, d = −1.06, energy
        suppliers: t(196) = −10.41, p < .01, 95% CI = −1.82 to −1.23, d = −0.91, and
        industrial factories: t(196) = −12.70, p < .01, 95% CI = −2.26 to −1.65, d =
        −1.10). Study 2: other individual consumers: t(107) = −3.09, p < .01, 95% CI =
        −.72 to −0.16, d = −0.31, the government: t(107) = −5.91, p < .01, 95% CI = −1.61
        to −.81, d = −0.81, industrial countries: (t(107) = −8.48, p < .01, 95% CI = −2.41
        to −1.49, d = −1.08, energy suppliers: t(107) = −6.04, p < .01, 95% CI = −1.71 to
        −.87, d = −0.89, and industrial factories: t(107) = −9.01, p < .01, 95% CI = −2.27
        to −.87, d = −1.10)).

        <hss>Shortfall ratings (a bipolar scale, Study 2 only)</hss>

        The descriptive statistics for the shortfall ratings obtained using the bipolar
        measure are listed in Table 2 along with the results obtained from the series of
        one-sample t-tests which we conducted for each agent to examine if their shortfall
        scores were significantly different from 0. The findings show that each of the
        other agents' eco-actions is perceived to fall significantly short of their eco-
        responsibility (apart from Government that did not reach the Familywise corrected
        .01 significance level). In contrast, participants tended to report that their own
        eco-actions were either in line with, or marginally surpassed their eco-
        responsibility. Respondents own shortfall was rated as significantly smaller than
        each of the others' shortfall (other consumers: t(103) = −3.43, p < .01, 95% CI =
        −1.41 to −0.38, d = −0.41, government: t(103) = −2.50, p < .01, 95% CI = −1.83 to
        −0.21, d = −0.35, industrial countries: t(103) = −3.95, p < .01, 95% CI = −2.45 to
        −0.81, d = −0.54, energy suppliers: t(103) = −3.53, p < .01, 95% CI = −1.97 to
        −.0.55, d = −0.46, and industrial factories: t(103) = −4.78, p < .01, 95% CI =
        −2.65 to −1.10, d = −0.65).

        <hss>The Environmental Government Judgement Scale (Study 2 only)</hss>

        To assess the structural integrity of the EGJS we first conducted parallel
        analysis (PA; Horn, 1965) using the SPSS syntax developed by O'Connor (2000) to
        determine how many factors to extract.4 Previous studies have found that PA is one
        of the most accurate methods for deciding how many factors to retain (e.g., Zwick
        & Velicer, 1986). Only the first two eigenvalues were greater than the subsequent
        values, suggesting a two-factor structure solution. Accordingly, we conducted
        exploratory factor analysis specifying a two-factor solution. Given that we
        expected our subscales to be negatively correlated we selected an oblimin
        rotation. Bartlett's test (X02 (105) = 2718.04, p < .01) suggested that there was
        an adequate sample size for this analysis and the Kaiser-Meyer-Olkin (.95) test
        indicated that the data were suitable for factor analysis. The eigenvalue for the
        first factor was 9.31 and accounted for 62.07% of the variance. The eigenvalue for
        the second factor was 1.41 and this accounted for an additional 9.36% of the
        variance. All items loadings are shown in Table 3. Factor 1 is comprised of items
        representing the perception that the government's action either in line with or
        exceeds its responsibility. Factor 2 is comprised only of items representing
        perceptions that the government's environmental actions fall short of its
        responsibility. Both subscales had acceptable reliability (Actions in line with or
        exceeding responsibility: α = .95, Shortfall: α = .88). As predicted, the two
        factors were significantly negatively correlated (r = −.37, p < .01). Moreover,
        there was some indication of convergent validity as the government shortfall scale
        comprised of 5 items was significantly positively correlated with the government
        shortfall scale that we calculated by subtracting government action from
        government responsibility (r = .49, p < .01). Similarly, the subscale containing
        items indicating government actions were either in line with or exceeded its
        responsibility were significantly negatively correlated with the government
        shortfall scale comprised by subtracting government action from government
        responsibility (r = −.49, p < .01). We computed the means for each subscale and
        found that they were in line with our previous findings. Specifically, the mean
        score for government shortfall was 5.22 (SD = 1.16), indicating that respondents
        perceive that the government's actions fall short of its responsibility.
        Conversely, the mean score for the other subscale was 2.89 (SD = 1.16) indicating
        that the majority of participants do not tend to believe that the government's
        actions are either in line with or exceed its responsibility.

        Associations of willingness to enact ECB to responsibility, action, and shortfall

        The Pearson product–moment correlation coefficients between participants'
        willingness to enact ECB and eco-responsibility and eco-action ratings are shown
        in Table 4.

            <hss>Associations of willingness to enact ECB to responsibility</hss>

            In both Studies 1 and 2, willingness to enact both easy and effortful ECB was
            significantly positively correlated with perceptions of other agents as
            responsible for conserving energy (Study 1: rs ranged from .15 to .38, with rs
            >.20 being significant at p < .01. Study 2: rs ranged from .32 to .47, ps <
            .01).

            <hss>Associations of willingness to enact ECB to action</hss>

            The extent to which others agents were perceived to be taking action to
            conserve energy was not consistently associated with willingness to enact
            either easy or effortful ECB. Although, in Study 2, we found that both the
            ratings of government action and the ratings of industrial factories action
            were negatively correlated with willingness to enact easy ECB, albeit these
            findings did not reach statistical significance after applying the Familywise
            corrected significance level of .01).

            Associations of willingness to enact ECB to shortfall (responsibility minus action)

            Overall the mean score of other agents' shortfall (i.e., when their
            responsibility to conserve energy did not measure up to their actions taken to
            conserve energy) was significantly positively correlated with willingness to
            enact easy (Study 1: r = .26 and Study 2: r = .38, both ps < .01) but not
            effortful ECB (Study 1: r = .09 and Study 2: r = .16, both NS). In both
            Studies 1 and 2, the shortfall ratings for the government, industrial
            countries, energy suppliers, and factories were positively correlated with
            willingness to enact easy, but not effortful, ECB. Further analyses revealed
            positive correlations between each agent's shortfall and willingness to enact
            easy ECB (Study 1: rs ranged from .17 to .26, with rs >.20 being significant
            at p < .01, Study 2: rs ranged from .23 to .39, with rs >.25 being significant
            at p < .01). We then conducted further analyses excluding anyone with a score
            of 0 to see if this would influence the association of shortfall ratings to
            willingness to enact ECB. Notably, those with a score of 0 believe that the
            agents' actions are in line with their responsibility (i.e., they are doing
            what they should be). However, the obtained correlations were comparable to
            those displayed in Table 4.5

            <hss>Associations of willingness to enact ECB to shortfall (bipolar scale)</hss>

            The mean score of other agents' shortfall obtained using the bipolar measure
            administered in Study 2 was also positively correlated with willingness to
            enact easy, but not effortful, ECB (r = .24, p = .016). Notably, this
            correlation was comparable to the correlation we obtained between other
            agents' shortfall as computed by subtracting action ratings from
            responsibility (Study 2: r = .24 vs. r = .38, Z = 1.12, NS). Further analyses
            revealed that the correlations between each of the agents' shortfall and
            willingness to enact easy ECB were positive (rs ranged from .14 to .27, albeit
            only those greater than .25 were significant at the after applying the
            Familywise corrected significance level of .01).

            Associations of willingness to enact ECB to environmental government judgement scale

            The 5-item government shortfall scale was significantly positively correlated
            with willingness to enact both easy and effortful ECB (respectively, rs = .43
            and .45, both ps < .01). Conversely, the subscale comprised of items
            indicating that government's actions were either in line with or in excess of
            its responsibility was significantly negatively correlated with willingness to
            enact both easy and effortful ECB (respectively, rs = −.30 and −.21, both ps <
            .01). Controlling for personal responsibility did not substantially change the
            correlations between government shortfall and willingness to enact either easy
            or effortful behaviors (respectively, r(1056) = .35 and .31, both ps < .01).

        <hss>Government shortfall scenario (Study 2 only)</hss>

        The majority of participants reported that if the government's actions fell short
        of its responsibility they would make no changes to their environmental efforts (N
        = 75, 35.4%), increase their efforts a little (N = 98, 46.2%) or a lot (N = 37,
        17.5%). Only 2 respondents reported that they would decrease their efforts a
        little (N = 1) or a lot (N = 1). Such findings replicate the positive correlations
        we obtained between government shortfall and willingness to enact ECB. We used the
        qualitative responses participants gave for their reactions to the government
        shortfall scenario to conduct thematic analysis using the five step process
        outlined by Braun and Clarke (2006) in which analysts (1) familiarize themselves
        with the data, (2) code it, (3) generate initial themes, (4) review these themes,
        and (5) define and name them. We employed an inductive approach consistent with an
        essentialist/realist method whereby the themes identified were strongly linked to
        the data. Hence, themes were largely identified at the semantic level. Table 5
        shows the themes that emerged from our qualitative analysis for people that
        indicated they would increase, decrease or make no changes to their environmental
        efforts. The following themes emerged for participants who said that they would
        increase their efforts either a little or a lot: compensation, obligation
        (personal and collective), efficacy (personal and collective), importance of the
        environment, moral high ground, and setting an example. The following themes
        emerged for people who said they would make no change: limits to personal
        environmental contribution, belief that the environmental issues are not
        important, and disconnection between personal actions and the government. Of the
        two people who stated they would decrease their environmental efforts, both
        questioned why they should do more when the government was doing less. In other
        words, the sucker effect appeared to account for these two people's decreased
        environmental motivation.

        <hss>Perceptions of others' responsibility, actions, and shortfall</hss>

        Studies 1 and 2 present a first attempt to examine the wider contextual
        associations of ECB. The results indicate that both individuals and other agents
        are perceived to be at least somewhat responsible for conserving energy. Yet,
        other agents are seen to be taking significantly less action to conserve energy
        than individuals. Both other agents and individuals' eco-actions are seen as
        falling short of their responsibility to conserve energy and persisted
        irrespective of whether we measured responsibility first (as in Study 1) or action
        first (as in Study 2). Moreover, we consistently found that regardless of which
        measures of shortfall are employed there is still a perception that other agents
        actions are falling short of their responsibility. Notably, this discrepancy
        between eco-responsibility and eco-actions was significantly larger for other
        agents than for oneself.

        Associations of willingness to enact ECB to responsibility, action, and shortfall

        Across both Studies 1 and 2 the data show that the responsibility ascribed to
        others to conserve energy is associated with willingness to enact both easy and
        effortful ECB. In contrast, perceptions of others' eco-actions were not
        consistently and significantly related to either willingness to enact easy or
        effortful ECB. Interestingly, when other agents' actions to conserve energy were
        seen as falling short of their environmental responsibility, individuals were
        somewhat more likely to report willingness to enact easy ECB.

        <hss>Shortfall and willingness to enact ECB</hss>

        Importantly, the positive association between shortfall and willingness to enact
        ECB emerged consistently, despite our use of several different measures of
        shortfall which included (i) subtracting action ratings from responsibility
        ratings, (ii) using a bipolar scale (iii) measuring government shortfall using a 5
        item scale, and (iv) asking participants to respond to a government shortfall
        scenario. As such, it seems that the findings are relatively robust and are not
        vulnerable to differences in measurement style. Moreover, a thematic analysis of
        the explanations revealed some insight into why individuals may increase their
        efforts when confronted with shortfall. Indeed, the themes that emerged were
        compatible with the conditions needed to prompt social compensation – i.e., that
        the goal to be obtained is both important and shared, and that any personal
        actions they undertake will contribute towards achieving the goal. Specifically,
        participants appeared to consider “caring for the environment” to be an important
        goal and one that they had a collective and personal obligation to help fulfill.
        Moreover, they believed that the environmental actions that they undertook could
        help make a difference. As such, the data provide some support for the idea that
        when others' actions are seen to be falling short of their responsibility people
        are more likely to be inclined to compensate for the discrepancy by increasing
        their own willingness to enact ECB. Of course, given that the magnitude of these
        correlations was generally small and only emerged between others' shortfall and
        willingness to enact easy (but not effortful) ECB, it seems that respondents may
        compensate for others' shortfall but only to a certain extent.

<h>AN EXPERIMENTAL STUDY: STUDY 3</h>
------------------------------

In both Studies 1 and 2, we found that participants appear willing to compensate for other
agents' shortfall by personally enacting more easy to perform ECB. However, given the
correlational design of Studies 1 and 2 we cannot infer causality. Hence in Study 3, we
aimed to manipulate shortfall and examine the effect on willingness to enact ECB. We
manipulated shortfall by first asking participants to provide their responsibility
ratings, and then randomly assigning them to view either 10 government actions or 10
government inactions. Notably, we deliberately presented the materials in this order in an
attempt to manipulate shortfall. Specifically, by presenting participants with the
responsibility rating task first and then showing them the actions/inactions we intended
to bring responsibility to the forefront of participants' minds. This was done to ensure
that those participants who subsequently encountered the 10 government inactions perceived
a shortfall to occur between ascribed responsibility to the government and its actions. We
manipulated action on the basis that in Studies 1 and 2 participants typically rated the
government as at least somewhat responsible for conserving energy (i.e., mean ratings were
always between 5 and 6 out of a maximum of 7). Given the stability of this score we
anticipated that it might be difficult to manipulate participants' responsibility
perceptions. In contrast, we expected that it might be easier to manipulate participants'
perceptions of government's action as we suspect that only those with a specialist
interest in the environment would be familiar with environmental policies and legislation.
To manipulate actions we randomly assigned participants to view either 10 environmental
actions the government has taken or 10 environmental actions the government has not taken.
We expected that participants in the inaction condition would score more on the government
shortfall measures. Given the results of Studies 1 and 2 we hypothesized that participants
that were induced to perceive high levels of government shortfall (i.e., in the inaction
condition) would be significantly more willing to enact ECB than participants that were
induced to perceive low levels of government shortfall (i.e., those in the action
condition). While we predicted that our experimental procedure would manipulate
participants' perceptions of government's shortfall we also considered it likely that in
each condition there would be some people that were unaffected by the manipulation. In
order to maximize the effect of our manipulation, we removed participants whose scores on
our 5-item measure of government shortfall were discordant to the manipulation condition
they had been allocated to, namely, (a) those participants who scored highly on government
shortfall in the action condition and, (b) those participants who scored low on government
shortfall in the inaction condition. Further details on this procedure are presented in
the result section.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants first rated the extent to which they believed the government is responsible
for conserving energy. They were then randomly assigned to view either 10 statements
emphasizing the action the government has taken to reduce carbon emissions/greenhouse
gases or 10 statements emphasizing issues where the government has not taken action (see
Appendix A). An example of a government action was, ‘The environmental actions the
government has taken caused carbon pollution to fall to its lowest level in nearly 20
years’ and an example of a comparable government inaction was, ‘Recent data found that
energy related carbon dioxide emissions in 2013 were 2% above the 2012 level, largely
because the government has not implemented effective environmental policies.’ Each
statement was displayed on a single page and the order in which the pages were presented
was randomized. To ensure that participants read the statements we instructed them to
‘read this information carefully as you will be asked questions about it later’. To check
if our manipulation had worked we asked participants to complete a measure of government
action so that we could compute shortfall by subtracting action ratings from
responsibility ratings (as in Studies 1 and 2) as well as our 5-item government shortfall
judgement scale (as in Study 2). Finally, participants were asked to indicate how willing
they would be to engage in ECB.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 125 participants (71 males, 54 females) were recruited via Amazon's Mechanical
Turk to complete the online questionnaire. All participants were USA citizens. Their ages
ranged from 19 to 81 (M = 3.76, SD = 13.81). 63 participants were randomly allocated to
the high shortfall (government inaction) condition and 62 participants to the low
shortfall (government action) condition.

        <hss>Government shortfall</hss>

        We measured government shortfall using two methods. First, as in Studies 1 and 2,
        we subtracted action ratings from government ratings and second, as in Study 2, we
        administered the 5-item measure of government shortfall. The 5-item measure of
        government shortfall had excellent reliability (α = .90).

        <hss>Willingness to enact ECB</hss>

        As in Studies 1 and 2 participants completed a measure of their willingness to
        enact ECB. Each subscale had acceptable reliability (easy: α = .68, effortful: α =
        .79).

        <hss>Manipulation checks</hss>

        We expected that participants who were exposed to 10 government actions would rate
        government shortfall as low while participants who were exposed to 10 government
        inactions would rate government shortfall as high. To examine if this expectation
        was correct we used a median split to categorize participants' scores on the 5
        item government shortfall scale as low (scores of 5 or less) or high (scores of
        5.2 or more) to see whether the obtained scores were discordant to the condition
        participants had been allocated to (i.e. low shortfall scores to participants in
        the high shortfall condition and high shortfall scores to participants in the low
        shortfall condition). While this expectation held true for the majority of
        participants (N = 100), it seems that the manipulation did not work as intended
        for a fifth of our sample. Specifically, in the no-shortfall condition (i.e.,
        where participants were shown 10 government actions) 12 participants still
        reported perceiving high levels of government shortfall. In the shortfall
        condition (i.e., where participants were shown 10 government inactions) 13
        participants did not report perceiving high levels of shortfall. Hence, following
        the exclusion of these participants, the mean score of the 5-item government
        shortfall was 6.14 (SD = .55) in the shortfall (or inaction) condition and 3.42
        (SD = .98) in the non-shortfall (or action) condition7 As an additional test of
        our manipulation we conducted a one way ANOVA to examine if the conditions had
        produced significantly different perceptions of government shortfall as assessed
        by subtracting government action ratings from government responsibility ratings.
        As intended, there was a significant effect of condition on the Shortfall
        difference score: F (1, 98) = 169.77, p < .01. η2 = .63) such that participants in
        the shortfall (or inaction) condition scored higher on government shortfall
        measures than participants in the non-shortfall (or action) condition (M = 3.37,
        SD = 1.73 vs. M = −.92, SD = 1.55).

        <hss>Effect of condition on willingness to enact ECB</hss>

        Findings from two one-way ANOVAs revealed that there was a significant effect of
        condition on willingness to enact both easy and effortful ECB (respectively, F (1,
        98) = 3.98, p < .05. η2 = .04 and F (1, 98) = 5.29, p < .02. η2 = .05), such that
        those in the shortfall (or inaction) condition reported more willingness to enact
        ECBs than those in the non-shortfall (or action) condition (easy ECB: M = 5.97, SD
        = 0.96 vs. M = 5.55, SD = 1.15, effortful ECB: M = 4.44, SD = 1.46 vs. M = 3.84,
        SD = 1.11). These findings suggest that participants may be more willing to enact
        ECB when they are induced to believe that the government's environmental actions
        fall short of its responsibility.

<hs>  Study 3 discussion</hs>
  ~~~~~~~~~~~~~~~~~~

The data from Study 3 demonstrate that it is possible to manipulate shortfall by
highlighting discrepancies between responsibility and action by first having participants
rate an agent's responsibility and then varying the information participants have about an
agents actions. Our findings show that participants that are induced to perceive high
levels of government shortfall are more willing to enact both easy and effortful ECB than
participants that perceive lower levels of government shortfall. Importantly the data show
the direction of causality between shortfall and willingness to enact ECB.

<h>GENERAL DISCUSSION</h>
------------------

The present research presents a first attempt to examine some of the wider contextual
variables that surround environmental issues, namely, how perceptions of other agents'
responsibility and action contribute to individuals own environmental efforts. Moreover,
by considering these variables in relation to one another we were able to make a novel
contribution to the literature regarding how people react when others' eco-actions are
seen as falling short of their responsibilities. In summary our findings show that several
other agents are seen as responsible for conserving energy but are not perceived as taking
action to do so. Respondents' willingness to enact ECB is positively correlated with other
agents' responsibility ratings but not perception of their environmental actions. In
circumstances where others' actions are seen as falling short of their responsibility
people appear prepared to compensate for this shortfall by increasing their willingness to
enact ECB.

<hs>  Willingness to enact ECB: why eco-responsibility matters</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We replicated findings from past research showing that (a) individuals consider themselves
to be responsible for conserving energy, and (b) that this responsibility is positively
associated with willingness to enact ECB (e.g., Hines et al., 1987; Kaiser & Shimoda,
1999). Our findings also complement existing quantitative and qualitative findings by
showing that aside from themselves people attribute responsibility to several other agents
(e.g., Lorenzoni et al., 2007; Hargreaves et al., 2010; Hinchliffe, 1996; Stern et al.,
1985). Beyond replicating past research, we found that judgements about others eco-
responsibilities are positively correlated with willingness to enact ECB. These findings
present an important contribution to the literature, as they suggest that, when it comes
to environmental issues, responsibility is shared but not diffused, leaving people willing
to enact ECB. Indeed, the correlations of .57 and .55 between personal responsibility and
others' responsibility obtained in both Studies 1 and 2 provide some support for the
notion of shared environmental responsibility.

<hs>  Willingness to enact ECB: why others' eco-actions do not seem to matter</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In both Studies 1 and 2 our findings suggest that others are not perceived as taking much
action to conserve energy, and that others' eco-actions are not significantly associated
with willingness to enact ECB. Therefore, little support was provided for the effects of
social norms, at least when considering other agents in the form of high-level
institutions or organizations. Such results may be explained by the fact that the average
person may have relatively little knowledge of the environmental actions' that
organizations are taking/not taking. Equally, people may find it difficult to clearly
envisage an entire organization's environmental actions rather than a singular person's
actions. Indeed, on average participants neither agreed nor disagreed that others were
taking action to conserve energy, thus suggesting that they were unsure about their
responses. It is possible then that a positive correlation may have been found between
willingness to enact ECB and other agents actions if respondents were more inclined to
believe these other agents were taking action to conserve energy either because they had
knowledge of such actions and/or could envisage them. It is also possible that we did not
find significant correlations between other agents actions and willingness to enact ECBs
because the others agents were not considered by participants to be similar to themselves.
Indeed, appeals involving social norms appear to be more effective when their content
involves a more similar referent group such as guests in this room rather than guests in
this hotel (e.g., Goldstein et al., 2008; Reese, Lowe, & Steffgen, 2013; but see Bohner &
Schlüter, 2014; Study 1 for conflicting results). In summary the null relations between
other organizations' actions and willingness to enact ECB could be explained by at least
three factors – knowledge of others environmental actions; difficulty of envisaging an
organization's environmental actions; and perceived similarity of the organizations to
oneself. Future research could independently manipulate these factors to establish if they
affect the influence of an organization's actions on individuals own environmental
efforts.

<hs>  Willingness to enact ECB: when others' actions fall short of their responsibility</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In Study 1, we found that other agents' responsibility to conserve energy was seen as
falling short of their action and that this shortfall was significantly positively
correlated with willingness to enact easy to perform ECB. In Study 2, we replicated these
findings using several different measures of shortfall. Moreover, correlations between
shortfall and willingness to enact easy to perform ECB were corroborated as almost two
thirds of respondents reported that they would increase their environmental efforts should
the government's actions fall short of its responsibility. Finally, in Study 3
participants who were manipulated to experience high perceptions of government shortfall
were more willing to enact both easy and effortful ECB than participants who were
manipulated to experience low perceptions of government shortfall. We suggest these
findings are best explained by social compensation theory. Indeed, the three conditions
necessary for compensation to occur were present in our data sets. First, respondents
attributed responsibility to everyone including themselves, indicating that energy
conservation is seen as a collective or shared goal. Second, respondents appeared
unconvinced that other agents were taking sufficient action as evidenced by their
relatively low action ratings. Third, participants appeared to perceive that their own
efforts could go some way in compensating for other shortfall. Indeed, in Study 2, the
qualitative explanations provided support for the conditions needed for social
compensation to occur.

<h>CONCLUSIONS AND FUTURE DIRECTIONS</h>
---------------------------------

Past research has typically identified ways in which individuals can be encouraged to
enact ECB. However, it has done so without taking into consideration individuals'
perceptions of the “external” world. Our findings show that it is important to consider
the broader social context as the extent to which other organizations' actions were seen
to fall short of their environmental responsibility increased personal willingness to
enact ECB. In our research, we focused on one organization in particular – the government.
We consistently found that perceptions of the governments' shortfall were related to
increased willingness to enact ECB. Notably, although significant, in both Studies 1 and 2
many of the correlations we obtained between others' shortfall and ECB were small in
magnitude. Similarly, in Study 3, manipulating shortfall did influence ECB but the effect
sizes obtained were medium rather than large. This suggests that perceptions of others'
shortfall may only explain a small percentage of the variance in willingness to enact ECB.
However, this does not mean that our findings are of little importance or interest.
Rather, encouraging people to act in environmentally friendly ways constitutes a complex
challenge involving a multitude of factors. Thus to identify an additional and previously
unconsidered factor still presents an important step towards gaining a more complete
understanding of people's willingness to enact ECB. Nonetheless, although the present
research offers an important and novel contribution there is ample scope for future
research that could improve upon and extend our findings. First, future correlational
research should counterbalance the order in which the measures are presented to
participants. While we varied the order in which participants completed responsibility and
action judgements, in both Studies 1 and 2 we always measured ECB after participants had
completed the responsibility and action judgements. While this enabled us to compare the
findings from the correlational studies to Study 3 (in which the experimental design meant
that we had no choice but to measure ECB after responsibility and action) it is important
to establish whether this ordering had a bearing on our results. Second, to ensure that
the results obtained here are not attributable to self-report biases, future research
should utilize an objective measure of ECB that captures participants physically enacting
a meaningful and personally costly behavior. Given the vague information participants
received about each study it is unlikely that they guessed the aim of our research and
influenced their answers accordingly. Nonetheless, indicating a willingness to enact ECB
is different from actually enacting ECB and establishing a relationship between shortfall
and an objective measure of ECB would demonstrate ecological validity. Third, while our
results are in line with social compensation theory it is likely that there are additional
theories that may also explain the relationship between shortfall and willingness to enact
ECB. Indeed, in Study 2 participants mentioned several other reasons for increasing their
efforts in response to government shortfall including taking the moral high ground or
setting an example to others. Future research could examine the validity of these
explanations by operationalizing them and establishing their role as mediator between
others shortfall and willingness to enact ECB. Finally, there is ample scope for further
research to explore the links between the public goods dilemma and the findings we
obtained. Indeed, there are some parallels between both the public goods dilemma and the
perception of others' actions as falling short of their responsibility. Namely, in both
scenarios, in the absence of everyone involved working together (i.e., co-operating) it is
still in an individual's best interest to contribute even when others do not (i.e., they
defect) because the payoff is still greater than doing nothing at all. Considering our
findings in this vein may help illuminate other relevant research questions. For instance,
participants that initially co-operate in public good games tend to reduce their
contribution in subsequent rounds when others repeatedly defect. Are the same findings
likely to occur in the shortfall scenario or will people continue to compensate for
“repeat offenders” shortfall? In summary, while as an explanation of the outcome we favor
social compensation theory, undoubtedly further research may be required to discount
alternative theories. Nevertheless, the present research indicates that perceived
shortfall induces a willingness to enact energy conservation behaviors.


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<ART>Habitual physical activity and cardiometabolic risk factors in adults with cerebral palsy
================================================================================

Authors: Jennifer M. Ryan, Vivion E. Crowley, Owen Hensey, Julie M. Broderick, Ailish McGahey, John Gormley
DOI: 10.1016/j.ridd.2014.03.051
Year: 2014  |  Pages: 1995-2002
ASJC codes: 3203, 3204
Keywords: Cardiometabolic risk factors, Cerebral palsy, Physical activity, Sedentary behavior

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Adults with cerebral palsy (CP) are known to participate in reduced levels of total physical activity. There is no information available however, regarding levels of moderate-to-vigorous physical activity (MVPA) in this population. Reduced participation in MVPA is associated with several cardiometabolic risk factors. The purpose of this study was firstly to compare levels of sedentary, light, MVPA and total activity in adults with CP to adults without CP. Secondly, the objective was to investigate the association between physical activity components, sedentary behavior and cardiometabolic risk factors in adults with CP. Adults with CP (n= 41) age 18-62. yr (mean. ±. SD. = 36.5. ±. 12.5. yr), classified in Gross Motor Function Classification System level I (n= 13), II (n= 18) and III (n= 10) participated in this study. Physical activity was measured by accelerometry in adults with CP and in age- and sex-matched adults without CP over 7 days. Anthropometric indicators of obesity, blood pressure and several biomarkers of cardiometabolic disease were also measured in adults with CP. Adults with CP spent less time in light, moderate, vigorous and total activity, and more time in sedentary activity than adults without CP (p<. 0.01 for all). Moderate physical activity was associated with waist-height ratio when adjusted for age and sex (β= -0.314, p<. 0.05). When further adjustment was made for total activity, moderate activity was associated with waist-height ratio (β= -0.538, p<. 0.05), waist circumference (β= -0.518, p<. 0.05), systolic blood pressure (β= -0.592, p<. 0.05) and diastolic blood pressure (β= -0.636, p<. 0.05). Sedentary activity was not associated with any risk factor. The findings provide evidence that relatively young adults with CP participate in reduced levels of MVPA and spend increased time in sedentary behavior, potentially increasing their risk of developing cardiometabolic disease. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Although cerebral palsy (CP) is a non-progressive disorder, it is well reported that
adults with CP experience a number of secondary conditions with age. These include pain,
fatigue, stiffness, and poor balance (Opheim, Jahnsen, Olsson, & Stanghelle, 2009; Van Der
Slot et al., 2012), and can lead to a decline in physical functioning and loss of mobility
from early adulthood. Between 30% and 52% of adults with CP reported experiencing
deterioration in walking function (Bottos, Feliciangeli, Sciuto, Gericke, & Vianello,
2001; Opheim et al., 2009). Loss of mobility is most commonly observed between the age of
20 and 40 years (Bottos et al., 2001). Deterioration in physical functioning over time may
lead to difficulties performing everyday activities and potentially an inactive lifestyle.
Only two studies have objectively measured physical activity in adults with CP to date,
with conflicting results (Nieuwenhuijsen et al., 2009; van der Slot et al., 2007). Adults
with unilateral spastic CP were reported to be as active as their able-bodied peers (van
der Slot et al., 2007), whereas adults with bilateral spastic CP were less active than
their able-bodied peers (Nieuwenhuijsen et al., 2009). Gross motor function was a strong
predictor of physical activity in adults with bilateral CP (Nieuwenhuijsen et al., 2009).
Differences in the gross motor function between samples may therefore explain the
discrepancy in results. Although these studies reported levels of total physical activity
in adults with CP, information about time spent in individual domains of activity, such as
sedentary behavior, light activity (LPA) and moderate-to-vigorous activity (MVPA), is not
available. Decreased levels of MVPA and increased sedentary behavior are independently
associated with risk factors for cardiovascular disease (CVD) and type II diabetes
mellitus (T2DM), including obesity, dyslipidemia, hypertension, insulin resistance,
hyperglycemia, and inflammatory markers (Healy, Matthews, Dunstan, Winkler, & Owen, 2011;
Loprinzi et al., 2013; Luke, Dugas, Durazo-Arvizu, Cao, & Cooper, 2011; Nelson et al.,
2013). The current American College of Sports Medicine (ACSM) guidelines recommend that
adults accumulate 150 min of moderate activity (MPA) or 75 min of vigorous activity (VPA),
in bouts of at least 10 min, per week to reduce their risk of CVD and premature mortality
(Garber et al., 2011). The potentially increased risk of adults with CP developing T2DM or
CVD, as a result of inactivity, has led to comparisons to people with spinal cord injury –
a population known to have insulin resistance, dyslipidemia, and an elevated presence of
T2DM (Bauman, 2009). Furthermore, a recent study reported that reduced MPA and increased
sedentary behavior are associated with an increased risk of the metabolic syndrome in
adults with impaired mobility (Peterson, Al Snih, Stoddard, Shekar, & Hurvitz, 2013).
Despite this, no study has investigated habitual levels of MVPA and their association with
cardiometabolic risk factors in adults with CP. The purpose of this study was two-fold.
The first objective was to compare levels of physical activity and sedentary behavior
between adults with and without CP. The second objective was to examine the relationship
between physical activity components, sedentary behavior and cardiometabolic risk factors
in adults with CP.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Adults with CP (n = 41), age 18–62 yr (mean ± SD = 36.5 ± 12.5 yr), classified in level
I–III of the Gross Motor Function Classification System (GMFCS) participated in this
study. This study was limited to ambulatory individuals only as accelerometers are unable
to quantify physical activity in wheelchair users (Hiremath & Ding, 2011). Participants
were recruited from a national centre that provides services to people with a disability
and through general practitioners (GPs) nationwide. The database of the centre was
searched for eligible adults, resulting in 263 letters and study invitations being sent to
potential participants. Letters were sent to 1367 GPs asking them to pass on information
leaflets and study invites to clients who were eligible to participate. Physical activity
data from age- and sex-matched adults without CP was obtained from an institutional
database of physical activity control data that was collected between 2009 and 2013.
Adults with a severe intellectual disability and pregnant women were excluded from
participating in this study. Participants were informed of the testing procedures before
written informed consent was obtained. In the case of participants with a mild to moderate
intellectual disability, their guardians also provided written informed consent. Ethical
approval for this study was granted by the University of Dublin's Faculty of Health
Sciences’ ethics committee and the Central Remedial Clinic's ethics committee.

<hs>  Procedures</hs>
  ~~~~~~~~~~

Participants were classified according to the GMFCS and according to type of motor
abnormality and anatomical distribution as defined by the Surveillance of Cerebral Palsy
in Europe (Rosenbaum et al., 2007). Information was also obtained from participants
regarding their history of CVD and T2DM and current use of medication. Height, body mass,
body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), and waist-height
ratio (WHtR) were measured in participants. WC was measured, on bare skin, to the nearest
0.1 cm midway between the lower rib margin and the iliac crest at the end of gentle
expiration. HC was measured to the nearest 0.1 cm at the end of gentle expiration around
the maximum circumference of the buttocks. The mean of two measurements was used for both
WC and HC. Overweight and obesity were identified as a BMI ≥ 25 kg m−2 and ≥30 kg m−2,
respectively. Central obesity was defined as WC ≥ 80 cm for women and ≥94 cm for men.
Blood pressure was measured from the right arm or the least affected side, in the case of
significant asymmetry, using the Omron 705 IT BP monitor. The Omron 705 IT has
demonstrated excellent validity in adults under the British Hypertension Society criteria
(El Assaad, Topouchian, & Asmar, 2003). The appropriate cuff size was selected for the
participant based on their mid-arm circumference and placed so that the lower edge was 3
cm above the elbow crease and the bladder was centred over the brachial artery.
Participants rested in a seated position with their back supported for at least 5 min
before three measurements were taken at a 1–2 min interval. The average of the last two
measurements was used in data analysis. Blood was drawn following an overnight (10 h) fast
and processed according to standard procedures in the Biochemistry Department, St. James's
Hospital, Dublin. Participants were allowed to drink water during the fast and medications
for cardiovascular stability were permitted (i.e. anti-hypertensive medications). Insulin
was measured by electrochemiluminescence immunoassay (Elecsys Insulin Assay, Roche
Diagnostics GMBH). Enzymatic, colorimetric assays (Roche/Hitachi cobas c systems) were
used to measure fasting glucose, total cholesterol (TC), high-density lipoprotein
cholesterol (HDL-C) and triglycerides. TC/HDL-C ratio was calculated as TC divided by
HDL-C. Low-density lipoprotein cholesterol (LDL-C) was calculated using the Friedewald
equation (Friedewald, Levy, & Fredrickson, 1972). High performance liquid chromatography
(Arkray/Adams A1c HA-8160 Analyser System) was used to measure glycated haemoglobin
(HbA1c) and c-reactive protein (CRP) was measured by particle enhanced immunoturbidimetric
assay (Roche/Hitachi cobas c systems). High risk CRP was categorized as >0.3 mg dL−1
(Pearson et al., 2003). 25-Hydroxy vitamin D (25OHD) was measured on the API 4000 LC/MS/MS
system (Norwolk, Connecticut). The Homeostasis Model Assessment index (HOMA-IR) (Matthews
et al., 1985) was used to evaluate insulin resistance. The metabolic syndrome was defined
according to the most recent joint interim statement (Alberti et al., 2009), i.e. the
presence of three or more of the following: (1) central obesity, (2) elevated
triglycerides (≥150 mg/dL [1.7 mmol L−1]) or drug treatment for elevated triglycerides,
(3) reduced HDL-C (<40 mg/dL [1.0 mmol L−1] in men; <50 mg/dL [1.3 mmol L−1] in women) or
drug treatment for reduced HDL-C, (4) elevated blood pressure (systolic ≥ 130 and/or
diastolic ≥ 85 mm Hg) or antihypertensive drug treatment, and (5) elevated fasting glucose
(≥100 mg/dL) or drug treatment for elevated glucose. Physical activity was measured using
the RT3 accelerometer (Stayhealthy, Inc.). The following procedure was used to collect
physical activity data in adults with and without CP. All participants were asked to wear
the RT3 for 7 days on their right hip (or least affected side in the case of significant
asymmetry) in the midaxillary line. Participants were told to wear the RT3 for waking
hours and to remove it only for bathing and swimming. Participants were asked to record
the times that they removed the monitor and the activities they completed while not
wearing the monitor. Vector magnitude count data was collected in 1-min epochs. Valid
activity data was defined as having at least four days data, of at least 10 h wear time
per day (Ward, Evenson, Vaughn, Rodgers, & Troiano, 2005). Sedentary activity was defined
as <100 counts·min−1, light activity (LPA) was defined as 100–984 counts·min−1, moderate
activity (MPA) was defined as 984–2341 counts·min−1, vigorous activity (VPA) was defined
as >2341 counts·min−1 (Rowlands, Thomas, Eston, & Topping, 2004). Data is presented as
time spent in light, moderate and vigorous activity accumulated in 1-min intervals,
percentage time spent in sedentary activity (i.e. minutes spent in sedentary
activity/total wear time), and mean activity counts per minute (counts·min−1). Time spent
in MVPA accumulated in 10-min bouts was also calculated. One minute of activity below the
moderate activity count threshold was allowed for before the bout was considered to be
ended. Finally the percentage of adults with and without CP meeting the ACSM
recommendation was calculated.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Statistical analysis was performed using IBM SPSS Statistics (version 19). The
distribution of the data was checked for normality by the Kolmogorov–Smirnov test. The
logarithm function was applied to HOMA-IR, TC/HDL-C ratio and 25OHD to transform this data
to a normal distribution. Means and standard deviations were computed for each of the
normally distributed continuous variables. Medians and interquartile ranges were computed
for skewed data. Prevalence data is presented as percentages. Differences between
continuous variables with a normal distribution were determined by independent t-tests and
one-way analysis of variance (ANOVA). Differences between continuous variables with a
skewed distribution were determined by Mann–Whitney U tests and Kruskal–Wallis one-way
analysis of variance. Pearson's χ2 test was used for comparison of independent groups of
categorical data. Multiple linear regression was used to investigate the association
between cardiometabolic risk factors (i.e. BMI, WC, WHtR, WHR, systolic blood pressure,
diastolic blood pressure, TC, HDL-C, TC/HDL-C ratio, LDL-C, triglycerides, plasma glucose,
HbA1c, HOMA-IR, 25OHD) and physical activity components (percentage time in sedentary
behavior, LPA, MPA, VPA, MVPA, mean counts·min−1). Collinearity was examined using
variance inflation factors. All analyses were controlled for age and sex. To avoid
multicollinearity, each independent variable (i.e. percentage time in sedentary behavior,
LPA, MPA, VPA, MVPA, and mean counts·min−1) was entered in separate analyses. When
systolic or diastolic blood pressure was the dependent variable of interest the analysis
was additionally controlled for anti-hypertensive medication (i.e. self-report of taking
any hypertension lowering medication coded as 1 if yes or 0 if no). When TC, HDL-C, LDL-C,
or TC/HDL-C ratio was the dependent variable of interest the analysis was also
additionally controlled for drug therapy (i.e. self-reported taking of any cholesterol
medication coded as 1 if yes or 0 if no). These analyses were repeated additionally
controlling for total physical activity (mean counts·min−1). Variance inflation factors <5
suggested that multicollinearity was not an issue. Logistic regression was conducted to
investigate the association between the metabolic syndrome, high risk CRP (dependent
variables) and each physical activity component (independent variables). Analyses were
initially controlled for age and sex before additionally controlling for total activity.
Statistical significance was set at p < 0.05.

<h>RESULTS</h>
-------

The characteristics of participants with CP are presented in Table 1. Both groups (i.e.
adults with and without CP) wore the RT3 for a median (IQR) of 7.0 (1.0) days. Adults with
CP wore the RT3 for a median (IQR) time of 840.5 (88.5) min per day; adults without CP
wore the RT3 for a mean time of 841.2 (59.3) min per day. There was no significant
difference in wear time between groups.

<hs>  Physical activity and sedentary time in adults with and without CP</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Time spent in MPA, VPA, and MVPA, and mean counts·min−1 differed across GMFCS levels I, II
and III, respectively (see Table 2). Post hoc pairwise comparisons revealed that adults in
level I spent more time in VPA and MVPA than adults in level II, and more time in MPA,
VPA, MVPA and total activity (mean counts·min−1) than adults in level III (p < 0.01 for
all). Adults in level II spent more time in MPA than adults in level III (p < 0.05).
Adults in level III spent more time in sedentary behavior than adults in level II (p <
0.05). There were no other differences in physical activity components between GMFCS
levels. Adults with unilateral spastic CP spent less time in sedentary behavior and more
time in MPA, VPA, MVPA and total activity than adults with bilateral CP. Data from adults
with non-spastic forms of CP were excluded from analyses due to the small numbers of
adults in this group (n = 4). Overall, adults with CP spent more time in sedentary
behavior (p < 0.001) and less time in LPA (p < 0.001), MPA (p < 0.001), VPA (p < 0.01),
MVPA (p < 0.001), and total activity (mean counts·min−1) (p < 0.001) than adults without
CP (see Fig. 1). When analyzed according to GMFCS level, however, there was no difference
in any physical activity outcome between adults in GMFCS level I and age- and sex-matched
control participants. A trend towards a significant difference was observed for VPA (p =
0.057). Adults in level II spent more time in sedentary behavior (p < 0.001), and less
time in LPA and total activity than control participants (p < 0.01). Time spent in MPA,
VPA and MVPA did not differ between adults in GMFCS level II and control participants.
Adults in level III spent more time in sedentary behavior and less time in LPA, MPA, VPA,
MVPA, and total activity than control participants (p < 0.01 for all).

<hs>  Adherence to physical activity guidelines among adults with and without CP</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ten adults with CP (24.4%) and 22 adults without CP (53.7%) met the ACSM guideline of 150
min of MVPA per week (χ2 = 7.38, p < 0.01). The number of adults meeting the guideline was
significantly less across worsening gross motor function [GMFCS level I: n = 7 (53.8%);
GMFCS level II: n = 3 (16.7%); GMFCS level III: n = 0 (0.0%); χ2 = 9.92, p < 0.01].
Adherence to the guideline for vigorous activity was not calculated because of the small
quantity of VPA accumulated by adults with CP.

<hs>  Cardiometabolic risk factors in adults with CP</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Two adults (5%) were taking antihypertensive medication. Three adults (7.3%) were taking
cholesterol medication. One person reported a pre-diagnosis of type I diabetes mellitus.
This person was removed from all analyses of blood biomarkers of glucose metabolism (i.e.
plasma glucose, HOMA-IR, HbA1c). A value for plasma glucose was missing for one person and
the HbA1c assay was missing for one person due to processing errors. Cardiometabolic risk
factors across GMFCS level are presented in Table 3. The prevalence of overweight/obesity
was 41.5%, the prevalence of central obesity was 36.6%, the prevalence of the metabolic
syndrome was 20.5% and the prevalence of high risk CRP was 14.6%. Regression models to
show how physical activity components were associated with cardiometabolic risk factors
are presented in Table 4. Regression analysis revealed that when age and sex were adjusted
for MPA was associated with WHtR. When total activity was additionally controlled MPA
remained associated with WHtR. Significant associations were also observed between MPA and
WC, systolic blood pressure and diastolic blood pressure when adjusted for age, sex and
total activity. Logistic regression analysis revealed that neither physical activity nor
sedentary behavior was associated with the metabolic syndrome or high risk CRP.

<h>DISCUSSION</h>
----------

The results of the current study indicate that adults with CP spend more time in sedentary
behavior and less time in light, moderate, vigorous and total physical activity than
adults without CP. Although previous studies have similarly reported reduced levels of
total activity among adults and children with CP (Maher, Williams, Olds, & Lane, 2007;
Nieuwenhuijsen et al., 2009) this is the first study to quantify the time that adults with
CP spend in each component of physical activity. In addition, this is first study to
demonstrate that a significantly smaller proportion of adults with CP meet physical
activity guidelines compared to adults without CP. MPA was negatively associated with a
number of cardiometabolic risk factors, suggesting that this population is at increased
risk of developing chronic disease as a result of reduced levels of activity. Similar to
previous studies of adults and children with CP (Bjornson, Belza, Kartin, Logsdon, &
McLaughlin, 2007; Nieuwenhuijsen et al., 2009), adults in level I accumulated comparable
levels of physical activity to able-bodied adults. In fact they accumulated a mean of 27.4
min of MVPA per day, resulting in over half of these adults meeting the guideline. Adults
in GMFCS level II, however, spent more time in sedentary behavior, and less time in LPA
and total activity than adults without CP. Interestingly, they accumulated similar levels
of MPA, VPA and MVPA as control participants. It is possible that adults with mild to
moderate impairments participate in MVPA while attempting to keep up with their able-
bodied peers during everyday life. The combination of trying to balance the activity
involved in daily life and the greater energetic cost of locomotion associated with CP
(Brehm, Becher, & Harlaar, 2007) may, however, result in an energy imbalance and chronic
fatigue, a primary complaint among adults with CP (Van Der Slot et al., 2012). Adults in
level II may therefore reduce light activity and increase sedentary behavior in an attempt
to preserve energy. Despite achieving similar levels of MVPA as able-bodied participants,
it should be noted that, of concern, only 16.7% of adults in GMFCS level II met the
physical activity guideline. As expected, adults in GMFCS level III participated in the
least amount of physical activity; no adults in this group met the physical activity
guideline. As well as accumulating little or no MVPA they spent a large proportion of the
day in sedentary behavior. There is evidence in the general adult population that
sedentary behavior is strongly associated with T2DM and cardiometabolic risk factors,
independent of time in MVPA (Healy et al., 2011; Stamatakis, Hamer, Tilling, & Lawlor,
2012). In the current study however, sedentary behavior was not associated with any
cardiometabolic risk factor. This may be because the relationship between objectively
measured sedentary behavior and cardiometabolic risk factors is less consistent than that
between self-reported sedentary behavior and risk factors (Stamatakis et al., 2012). Some
research suggests that the type of sedentary behavior, in particular TV-viewing, rather
than the volume of sedentary behavior is associated with cardiometabolic risk factors
(Carson & Janssen, 2011; Stamatakis et al., 2012). This information was not captured by
accelerometry in the current study. Although no association was observed between sedentary
behavior and cardiometabolic risk factors, MPA was negatively associated with a number of
risk factors. This is in contrast to a recent study in Dutch adults with CP that was
unable to find an association between physical activity and cardiovascular risk factors
(van der Slot et al., 2013). This is likely because the association between individual
components of physical activity and risk factors was not investigated. The association
between physical activity and risk factors may be mediated through the effect of excess
adiposity on cardiometabolic disease. In the current study MPA was associated with
measures of central adiposity but not BMI. Similarly, anthropometric measures of central
obesity, but not BMI, are associated with cardiometabolic risk factors in adults with CP
(Peterson, Haapala, & Hurvitz, 2012), probably because BMI is unable to identify excess
adiposity in adults with impaired mobility (Peterson et al., 2013). Future studies
investigating the effect of exercise interventions in adults with CP should evaluate
changes in abdominal adiposity, which can occur in the absence of changes in BMI even in
the general population (Kay & Fiatarone Singh, 2006), and subsequent changes in
cardiometabolic risk.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

There are a number of limitations to this study including the cross-sectional design, the
inability to generalize the results to non-ambulatory adults with CP, and the lack of
dietary assessment. The studied sample was also relatively small. There is currently no CP
register in the Republic of Ireland and the majority of rehabilitative services are only
provided up until age 18 years. International research reported that less than one-third
of adults with CP are under the regular control of a rehabilitation physician (Hilberink
et al., 2007). Despite every effort being made to recruit adults for this study the
relatively low participation may have resulted in selection bias. In particular adults
with an interest in preventive health and being physically active may have been more
likely to participate. As information was not available on adults who did not respond to
the study invite, comparisons cannot be made between responders and non-responders. The
accelerometer used in this study was also not water-proof and therefore was unable to
measure physical activity accumulated during water sports. Only 6 participants (14.6%)
however, reported swimming for between 1 and 3 h per week.

<h>CONCLUSION</h>
----------

The results of this study suggest that a large proportion of adults with CP do not meet
physical activity guidelines. As well as spending less time in total physical activity
adults with CP spent less time in MPA and VPA, and more time in sedentary behavior than
their able-bodied peers. The negative association between MPA and cardiometabolic risk
factors suggests that policy and intervention should be implemented to increase MPA in
adults with CP in order to reduce cardiometabolic disease risk in this population.

<h>CONFLICT OF INTEREST</h>
--------------------

No external funding was received for this work. An honorarium, grant, or other form of
payment was not given to anyone to produce this manuscript. The authors declare no
conflicts of interest.


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<ART>Hans Eysenck's interface between the brain and personality: Modern evidence on the cognitive neuroscience of personality
================================================================================

Authors: Rachel L.C. Mitchell, Veena Kumari
DOI: 10.1016/j.paid.2016.04.009
Year: 2016  |  Pages: 74-81
ASJC codes: 3200
Keywords: Cognition, Emotion perception, Extraversion, Neuroticism, Personality traits

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<h>ABSTRACT</h>
--------

In this review, incorporating functional and structural MRI and DTI, with evidence gathered over the last 15 years, we examine the neural underpinnings of extraversion and neuroticism, the two major personality dimensions in Eysenck's (1967) biological model of personality. We present clear evidence that, as proposed by Eysenck nearly half-a-century ago, these traits relate meaningfully to the functioning and structure of various cortical and limbic brain regions. Specifically, there is a robust relationship between neuroticism and the functioning of several emotion processing networks in the brain, particularly during exposure to negative stimuli. The brain regions showing this association include a number of cortical regions implicated in emotion regulation, depression and anxiety, in addition to many sub-cortical/limbic regions. Currently, there are few studies directly assessing the relationship between extraversion and the cortical arousal system in the context of varying stimulations but data available so far are remarkably consistent with Eysenck's model. Future neuroimaging studies guided by relevant personality and cognitive theories, and with sufficient power to allow application of sophisticated analysis methods (for example, machine learning) are now needed to improve our understanding of the biological basis of individual differences and its application in the promotion of well-being and mental health.

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<h>INTRODUCTION</h>
------------

Well before the advent of modern human brain imaging, Hans Eysenck, the visionary
psychologist and the most influential personality researcher in recent history, proposed a
theory (Eysenck, 1967) that went beyond description and measurement of personality and,
for the first time, provided the neurophysiological causes of personality. It was unique
in trying to explain extraversion and neuroticism, the two major personality dimensions in
Eysenck's model (the third dimension, psychoticism, added formally later in 1975), in
terms of individual differences in the functioning of aspects of the central nervous
system (Eysenck, 1967). Here, we review neuroimaging evidence, gathered mainly over the
last 15 years, examining the association between extraversion and/or neuroticism and brain
activation/connectivity patterns elicited by a wide range of cognitive and affective
tasks. We have included relevant functional magnetic resonance imaging (MRI), structural
MRI and diffusion tensor imaging (DTI) studies generated in the context of Eysenck's
three-factor factor model as well as Costa and McCrae's five-factor personality model
(Neuroticism, Extraversion, Openness to Experience, Agreeableness & Conscientiousness).
There is a reasonable correspondence between the two models for extraversion and
neuroticism (Costa & McCrae, 1995). We have also considered findings relating to the
remaining three factors of the five-factor model as well as those relating to
psychoticism, the third dimension in Eysenck's revised model (Eysenck & Eysenck, 1975),
were examined within the same study, for completeness.

<hs>  Cognitive processing</hs>
  ~~~~~~~~~~~~~~~~~~~~

Eysenck's theory proposed that the extraversion–introversion dimension (extraversion =
positive affectivity, marked by pronounced engagement with the external world and
characterized by high sociability, talkativeness, energy and assertiveness) is caused by
variability in cortical arousal (Eysenck, 1967). Those who score low for extraversion
(introverts) have lower response thresholds and are consequently more cortically aroused
than those who score high for extraversion (extraverts). It further postulated an inverted
U-shaped relation between cognitive performance and ‘level of arousal’, jointly determined
by environmental arousal potential (defined in terms of a range of environmental
manipulations and task parameters) and subject arousability as reflected in extraversion.
These postulates jointly predict that, at low environmental arousal potential, extraverts'
performance would be lower than that of introverts'. As environmental arousal increases,
performance of extraverts should improve and they should catch up with introverts; and, at
high levels of environmental arousal, extraverts should out-perform introverts with a
decline in introverts' performance, until it becomes so arousing as to evoke transmarginal
inhibition (TMI) (Eysenck, 1994; Gray, 1964). With evocation of TMI, introverts may
experience lower arousal increments than extraverts. There is considerable support for
these predictions from behavioral studies (Eysenck, 1981). Eysenck's model further
postulated that level of arousal, resulting from a combination of environmental arousal
and subject arousability, is mediated by activity in a ‘cortical arousal system’,
modulated by reticulo-thalamic-cortical pathways (Eysenck, 1967, 1981). A circuit that
seemingly corresponds to this cortical arousal system, including the dorsolateral
prefrontal cortex (dlPFC) and anterior cingulate regions, has been identified in studies
applying fMRI to a wide range of cognitive tasks (Duncan & Owen, 2000). Importantly,
findings of an fMRI study (Kumari, ffytche, Williams, & Gray, 2004), the only one so far
to test the predictions concerning extraversion and cortical activity at different
cognitive loads (or stimulation levels), are remarkably consistent with Eysenck's model.
Specifically, this study showed that the higher the extraversion score, the greater the
change in fMRI signal in the dlPFC and anterior cingulate from rest (through 1- and
2-back) to the 3-back working memory load condition. Furthermore, also consistent with
Eysenck's model, which treats neuroticism and psychoticism dimensions as independent of
extraversion, the relationship between extraversion and dlPFC and anterior cingulate
activity was not found for neuroticism or psychoticism in Kumari et al.’s (2004) study.
Concerning neuroticism, Eysenck proposed that the neuroticism-stability dimension
(neuroticism = negative affectivity, marked by emotional instability and low tolerance for
stress or aversive stimuli, and characterized by anxiety, fear, moodiness, worry, envy,
frustration, jealousy, and loneliness) is explained by differences in the level of
activity primarily in the limbic system (Eysenck, 1967). Perhaps not surprisingly, most
existing fMRI studies have examined the effects of neuroticism in implicit or explicit
affect processing, emotion regulation, fear/anxiety stress induction paradigms (reviewed
and discussed in the next section) rather than with pure cognitive paradigms. A very
recent study, which examined the effects of personality using the five-factor model, found
that decreased and increased effective connectivity within the working memory network,
activated by a 3-back working memory task, were associated with high neuroticism and high
conscientiousness, respectively (Dima, Friston, Stephan, & Frangou, 2015). Although these
findings show a significant effect of personality in neuroplasticity, their interpretation
is rather difficult because neuroticism and conscientiousness had opposite effects. The
effects of conscientiousness, however, appear consistent with possible extraversion
effects, since conscientiousness correlates positively with extraversion when assessed
using the Eysenckian scales (Costa & McCrae, 1995). Notably, extraversion itself, as in
the five-factor model, did not have any influence in this study. An important line of
enquiry in relation to fMRI of neuroticism using cognitive (and other) paradigms is
indicated by experimental evidence showing greater trial-to-trial variability in cognitive
performance (particularly reaction time) of high neuroticism scorers, relative to low
neuroticism scorers (Robinson & Tamir, 2005). This behavioral effect may reflect task-
irrelevant cognitions such as worries and preoccupations in neurotic individuals. Moment-
to-moment brain signal variability is also known to be present in neuroimaging studies and
has important implications for fMRI activation and connectivity studies (Garrett et al.,
2013). Interestingly, moment-to-moment brain signal variability correlates with less,
rather than more, reaction time variability across various paradigms and samples (Garrett,
Kovacevic, McIntosh, & Grady, 2011; McIntosh, Kovacevic, & Itier, 2008; Misic, Mills,
Taylor, & McIntosh, 2010; Raja Beharelle, Kovacevic, McIntosh, & Levine, 2012). Despite a
highly likely influence of neuroticism in this phenomenon, given its known association
with reaction time variability, no published study has yet examined the effect of
neuroticism in moment-to-moment/trial-to-trial variability in brain activations.

<hs>  Affect</hs>
  ~~~~~~

One of the great challenges faced by the human mind is the need to comprehend the content
of other minds. Thus a rapidly increasing literature has sought to explore the
psychological and neural mechanisms behind “the mental operations that underlie social
interactions, including perceiving, interpreting, and generating responses to the
intentions, dispositions, and behaviors of others” (Green et al., 2008), namely ‘social
cognition’. One of the most fundamental means we have of making these inferences is the
emotion cues that other people display. However, individual differences associated with
personality traits are a key influence on the way we perceive and respond to emotion cues
(Britton, Ho, Taylor, & Liberzon, 2007). Indeed, our personality, whether we tend to be
shy or outgoing, anxious or contented, has a major influence on our lives and the way we
interact with the world around us (Hamann & Harenski, 2004). For example, highly neurotic
individuals preferentially respond to negative emotion cues, and highly extravert
individuals preferentially respond to positive emotion cues (Canli et al., 2001).
Personality has these effects because it comprises an integrated pattern of thinking,
feeling and behaving that varies between individuals but is relatively stable within
individuals over time (Suslow et al., 2010). These chronic affective styles associated
with personality tune the affective system to be more sensitive towards one class of cues
than to another (Cunningham, Arbuckle, Jahn, Mowrer, & Abduljalil, 2010; Fruhholz, Prinz,
& Herrmann, 2010). Beyond their everyday implications for understanding normal socio-
cognitive behavior, neuroticism and extraversion are of great importance as trait
dimensions, because of the implications for individual vulnerability for emotion-related
psychopathologies such as anxiety and mood disorders (Brandes & Bienvenu, 2006; Foster &
MacQueen, 2008; Gale et al., 2011; Keller, 2004; Klein, Kotov, & Bufferd, 2011; Wright,
Kelsall, Sim, Clarke, & Creamer, 2013). Adoption of cognitive neuroscience techniques
undoubtedly facilitates a clearer understanding of how personality influences the way
people react to emotion cues. It has even been said by some that neuroimaging might prove
superior to behavioral or cognitive paradigms in characterising the effects of personality
dimensions on reactivity to emotion cues (Harenski, Kim, & Hamann, 2009). The thinking
here is that whereas behavioral and cognitive indices represent the combined effects of
all brain activity components during a task, neuroimaging can isolate specific aspects of
neural reactivity as being influenced by specific personality dimensions. Although some
psychological determinants of individual variability in emotional reactivity have been
determined at the behavioral level, research has only recently begun to explore the brain
mechanisms that might enable this individual variability (Canli et al., 2001). This is
because most prior neuroimaging studies have taken a group-based approach, in which the
mechanism that determines emotional reactivity is studied in a group of healthy
individuals not preselected for any specific criteria (Calder, Ewbank, & Passamonti, 2011;
Hamann & Canli, 2004). Here the effect of individual differences on emotion perception at
the neural level is frequently ignored or dismissed as statistical noise (Calder et al.,
2011; Canli, 2004; Hamann & Canli, 2004). Yet these individual differences can exhibit
remarkable stability within participants, suggesting that they are not random
fluctuations, and that they relate to traits that are different between, but consistent
within, individuals (Canli, 2004). With a correlational approach, individual differences
in neural reactivity do not represent noise, rather they represent valuable signal that
can reveal much about aspects of brain function of fundamental value to the study of
social cognition (Canli & Amin, 2002; Hamann & Canli, 2004). Since the trait of
neuroticism involves enhanced processing of negative emotion cues (Canli et al., 2001),
one way of establishing the influence of neuroticism on patterns of brain activity is to
study the neural response to negative emotions (Haas, Constable, & Canli, 2008). In the
original study of neuroticism, extraversion and neural reactivity to emotion cues, Canli
et al. observed that neuroticism correlated positively with neural reactivity to negative
scenes in the middle frontal and temporal gyri, whilst extraversion correlated with
reactivity to positive scenes in the inferior, middle and superior frontal gyri, the
cingulate, the inferior and middle temporal gyri, the basal ganglia and amygdala (Canli et
al., 2001). These correlations were both robust; and in the expected direction, that is
greater neural reactivity to positive emotion cues was associated with high extraversion,
whilst greater neural reactivity to negative emotion cues was associated with high
neuroticism. Since this original study, subsequent research has confirmed and extended
these findings in the visual modality, using symbols, faces or scenes. Thus, neuroticism
has been associated with activity in the middle frontal gyrus (‘negative’ upsetting
scenes) (Canli et al., 2001), medial PFC (sad faces) (Haas et al., 2008), anterior
cingulate (‘negative’ upsetting scenes) (Haas, Omura, Constable, & Canli, 2007), temporal
pole (sad faces) (Jimura, Konishi, & Miyashita, 2009), amygdala (‘negative’ upsetting
scenes) (Cunningham et al., 2010; Harenski et al., 2009), and the basal ganglia
(‘negative’ non-smiling/sad emotion symbols) (Bruhl, Viebke, Baumgartner, Kaffenberger, &
Herwig, 2011), when perceiving facial emotion cues. Beyond passive viewing of visual
emotion cues or forced-choice labelling tasks, other research on personality and affective
reactivity has sought to actively direct participant's view towards or away from emotion
cues, by manipulating their attention. In this line of research, neuroticism has been
shown to influence activity in brain regions such as the caudate and supramarginal gyrus
even before a negative emotion cue is visible, that is through directing attention towards
its mere anticipation (Bruhl et al., 2011), activation of the former having also been
demonstrated more broadly for the anticipation of emotional music (Salimpoor, Benovoy,
Larcher, Dagher, & Zatorre, 2011). Increasing the evaluative attentional processing
demands by introducing emotion-related conflict has demonstrated that in such
circumstances, neuroticism is typically associated with increased amygdala activity
(Fruhholz et al., 2010), which makes sense given the role of the amygdala in vigilance
(Davis & Whalen, 2001), and the aforementioned association of neuroticism with a
predisposition towards negative emotion cues. Indeed, according to Eysenck's own
biological theory of personality, high levels of neuroticism were hypothesized to reflect
increased reactivity of the limbic system (of which the amygdala is part), which then
predisposes highly neurotic people to react strongly to emotionally arousing experiences
and take longer to return to pre-arousal states (Eysenck, 1967, 1994). Elsewhere in the
limbic system, neuroticism has also been observed to associate with degree of activity in
the medial PFC in response to emotional arousal, the authors in this study suggesting that
neuroticism influences emotional reactivity by enhancing neural sensitivity to high levels
of emotional arousal, predisposing highly neurotic individuals to react strongly to
arousing experiences (Kehoe, Toomey, Balsters, & Bokde, 2012). Some emotion-relevant brain
regions show increased or decreased activity in association with neuroticism depending
upon specific emotional response/processes involved. For example, highly neurotic
individuals show increased activity during anticipation of painful stimulation (possibly
reflecting higher vigilance, anticipatory anxiety and emotional over-arousal) and
decreased activity during painful stimulation (possibly reflecting emotional blunting,
avoidance/passive coping strategy, learned helplessness, etc.) in the anterior cingulate,
thalamus, parahippocampal gyrus and thalamus regions (Coen et al., 2011; Kumari et al.,
2007). In the temporal domain, evidence has shown that higher degrees of neuroticism are
associated with a sustained haemodynamic response across time in the medial PFC to
negative stimuli, not just with an instantaneous response (Haas et al., 2008). Such a link
might thereby create a mechanism whereby rumination over time could facilitate the
association of neuroticism with increased vulnerability for depression. The importance of
taking temporal dynamics into account when using neuroimaging to study the influence of
personality on affective reactivity is further underscored when distinguishing between
initial reactivity to an emotional stimulus, and subsequent recovery once an emotion cue
terminates or ceases to be relevant. Closer examination of the time course of neural
response in the amygdala in one study demonstrated that whilst initial amygdala reactivity
did not predict trait neuroticism, slower amygdala recovery from negative images after
their offset did predict greater neuroticism (Schuyler et al., 2012). Because neuroticism
is associated with greater perseveration of emotional events (Robinson, Wilkowski,
Kirkeby, & Meier, 2006), this link between greater neuroticism and slower amygdala
recovery might form the basis of the inability to alter negative mood state once
established, thereby enabling another important element of the increased vulnerability for
depression associated with neuroticism. Following the same logic as for neuroticism, one
way of establishing the influence of extraversion on patterns of brain activity is to
study the neural response to positive emotions. Thus a high degree of extraversion has
been linked in this way with a greater response to positive visual emotion cues e.g.,
happiness, in the amygdala (Suslow et al., 2010), the basal ganglia (Canli et al., 2001),
and anterior cingulate cortex (Canli, Amin, Haas, Omura, & Constable, 2004; Canli, Sivers,
Whitfield, Gotlib, & Gabrieli, 2002; Haas, Omura, Amin, Constable, & Canli, 2006). These
brain regions are all known for their generic roles in emotion perception (Etkin, Egner, &
Kalisch, 2011; Kringelbach & Berridge, 2009; Phan, Wager, Taylor, & Liberzon, 2002;
Phillips, Drevets, Rauch, & Lane, 2003; Sabatinelli et al., 2011). Functional connectivity
between the anterior cingulate and inferior parietal lobule, middle frontal gyrus and
right orbitofrontal gyrus may also increase with degree of extraversion during reactivity
to positive emotion cues (Haas et al., 2006), which is consistent with the known
functional neuroanatomy of this region (Bush, Luu, & Posner, 2000), and likely reflects
increased attentional input to monitoring for positive emotion cues among other functions
(Ptak, 2012; Vandenberghe & Gillebert, 2009). Subcortical regions such as the thalamus
have also been implicated as enabling the influence of extraversion on the neural response
during (anticipation of) positive emotion cues (Bruhl et al., 2011). In the context of the
protective influence of high extraversion on psychological well-being (Abbott et al.,
2008), a relationship with emotional reactivity in such a deep brain structure might be
particularly difficult to modify in people with low extraversion, for example by
psychotherapy (Wang et al., 2013). Beyond the confines of the supposed link between
extraversion and positive emotional reactivity, other research suggests that extraversion
in fact reflects a generic increase in social engagement irrespective of emotional valence
(Ponari, Trojano, Grossi, & Conson, 2013). Along these lines, one study demonstrated a
link between emotional reactivity in the fusiform gyrus to both positive and negative
emotion cues in an attentional dot-probe task (Amin, Constable, & Canli, 2004), which
would be consistent with that region's known role as an alerting mechanism to emotional
content in social communications (Schindler, Wegrzyn, Steppacher, & Kissler, 2015).
Historically, literature on the relationship between personality traits and emotion
perception mechanisms has focused on visual cues, yet beyond facial cues, another crucial
means of transmitting emotion cues is through prosody. By manipulating features of speech
such as pitch, duration, loudness, voice quality and spectral properties (Ross, 1993), we
can alter our tone of voice and thereby alter the emotion that we convey. It is an
especially effective means of conveying emotional meaning in everyday contexts (Scherer,
1986), because the ability to produce, coordinate, and understand emotion signals in
speech in this way is a prerequisite for fundamental attributes of social cognition
including, ‘negotiating claims to power, respect, or equality, defining degrees of
intimacy, showing affiliation or non-affiliation, avoiding threats, repairing
interpersonal misunderstandings and so forth’ (Arndt & Janney, 1991). Indeed, in some
situations, it may be the only means of expressing nonverbal emotion cues. Thus far, there
has been only one prior report on the effect of individual differences in personality on
the neural response to prosodic emotion cues (Bruck, Kreifelts, Kaza, Lotze, & Wildgruber,
2011). In this study, for explicit emotional prosody identification relative to control
tasks (task driven activity), positive correlations were observed between neuroticism and
neural responsivity in the amygdala and anterior cingulate. During prosody identification
for emotional vs. neutral trials (stimulus-driven activity), a correlation was observed
with the neural response in medial frontal cortex, to happy prosody. Perhaps reflecting
the clearer trends for neuroticism-linked than for extraversion-linked patterns of
emotional reactivity with visual emotion cues, no correlations were observed between brain
activity patterns and extraversion for prosodic cues in this study. Overall, there is no
doubt that existing studies provide strong support for a brain basis of individual
differences in extraversion and neuroticism, and the findings of many of these studies,
despite them not being specifically formulated to test (in fact many conducted in a
theoretical vacuum), can be considered broadly in line with Eysenckian predictions.

<h>STRUCTURAL MRI</h>
--------------

That personality is biologically-based as proposed by Eysenck immediately becomes apparent
when considering evidence from structural MRI. One particular overview study was able to
demonstrate associations with the volume of different brain regions and four out of the
‘big five’ personality traits (DeYoung et al., 2010). Specifically, extraversion covaried
with volume of medial orbitofrontal cortex, a brain region involved in processing reward
information (Noonan, Kolling, Walton, & Rushworth, 2012). Neuroticism covaried with the
volume of brain regions associated with threat, punishment, and negative affect, such as
the dorsomedial PFC and portions of the left medial temporal lobe (Kalisch & Gerlicher,
2014; Strange & Dolan, 2006). However, greater levels of neuroticism have also been linked
to reduced overall ratio of brain to intracranial volume across the brain as a whole,
particularly the element of neuroticism relating to chronic experience of arousing
negative emotions (Knutson, Momenan, Rawlings, Fong, & Hommer, 2001), which might possibly
reflect the cumulative effects of stress reactivity (McEwen, 2006). Agreeableness (which
correlates negatively with Psychoticism; Costa & McCrae, 1995) in the DeYoung study,
covaried with volume in regions that process information about the intentions and mental
states of other individuals, including the posterior cingulate cortex and superior
temporal gyrus (Nummenmaa & Calder, 2009; Schlaffke et al., 2015). Finally,
conscientiousness covaried with volume in lateral PFC in the De Young study, a region
involved in planning and the voluntary control of behavior (Tanji & Hoshi, 2008). Often
the seat of functional associations with personality (see Section 5), the PFC cortex may
further exhibit separable patterns of association dependent on the particular personality
trait in question. Specifically, extravert people may have a thinner layer of cortical
gray matter ribbon in regions of the right inferior PFC and fusiform gyrus, compared to
introvert people, whereas neurotic people may have a thinner cortex mantle in anterior
regions of the left orbitofrontal cortex (Wright et al., 2006). The difference in
hemispheric lateralization for these effects was significant in this study, perhaps
reflecting literature that greater left-sided activity of the PFC has classically been
associated with positive affect as found in extraversion, whereas greater right-sided PFC
activity has classically been associated with negative affect as found in neuroticism
(Davidson, 2003; Spielberg, Stewart, Levin, Miller, & Heller, 2008). Perhaps the greatest
body of research on the structural bases of the five major personality traits has come
from Voxel-Based Morphometry (VBM), a technique with two distinct advantages relative to
traditional tracing methods. Firstly, it allows detection of subtle morphometric
differences in brain structure that may not be discernible by visual inspection, and
secondly, it allows investigation of the entire brain rather than a particular structure,
in an automatic and objective manner (Scarpazza, Tognin, Frisciata, Sartori, & Mechelli,
2015). In the body of research using VBM to examine personality-related differences, one
major area of focus has been the amygdala. In one of the early studies, neuroticism
appeared to negatively correlate with gray matter density in the right amygdala, whereas
extraversion was positively correlated with gray matter density in the left amygdala
(Omura, Todd Constable, & Canli, 2005). Given what we know about the affective style of
extraversion and neuroticism, this laterality pattern would again be consistent with a
model of affect that posits left-lateralized hemispheric specialization for positive
affect or approach-oriented behavior, and right-lateralized hemispheric specialization for
negative affect or withdrawal-oriented behavior (Maxwell & Davidson, 2007; Shackman,
McMenamin, Maxwell, Greischar, & Davidson, 2009). However, subsequent research has not
confirmed these results for neuroticism. In later literature, correlations with
neuroticism have either been positively rather than negatively correlated, and the foci of
the volumetric correlation has concerned the left/bilateral rather than right amygdala
(Koelsch, Skouras, & Jentschke, 2013; Mincic, 2015). Nevertheless, amygdala volume
differences in one form or another might therefore be indicative of an individual's risk
of depression (Whittle et al., 2014), which would certainly fit with this structure's role
in detecting emotional saliency and social relevance (Adolphs, 2008, 2010; Murray, Brosch,
& Sander, 2014). Other gray matter volume differences reportedly linked to degree of
neuroticism have included increased volume in the cerebellum, and decreased volume in the
superior frontal gyrus (Lu et al., 2014), which have been linked to negative affect
coordination and regulation of negative emotions respectively (Baumann & Mattingley, 2012;
Becker & Stoodley, 2013; Falquez et al., 2014; Mak, Hu, Zhang, Xiao, & Lee, 2009;
Mothersill, Knee-Zaska, & Donohoe, 2016). As a whole, this body of evidence suggests that
neuroticism is related to several brain regions involved in regulating negative emotions.
Regarding extraversion, the major finding seems to concern personality-dependent volume
differences in the orbitofrontal cortex and other PFC brain regions. Thus increasing
extraversion appears to correlate positively with increased/decreased orbitofrontal cortex
gray matter density/volume (Coutinho, Sampaio, Ferreira, Soares, & Goncalves, 2013;
Cremers et al., 2010; Omura et al., 2005). As mentioned above, changes in amygdala volume
or density have also been observed to depend on the degree of extraversion an individual
exhibits (Cremers et al., 2010; Lu et al., 2014; Omura et al., 2005). Given that
extraversion acts as a protective factor against development of anxiety disorders and
depression, one possible explanation is that the reduced likelihood of highly extravert
individuals developing an affective disorder relates to modulation of emotion processing
through the orbitofrontal cortex and the amygdala, two structures often implicated in
concert in patients with diagnoses of affective disorders (Blackmon et al., 2011; Kanske,
Heissler, Schonfelder, & Wessa, 2012; Zald et al., 2014; Zhang et al., 2014). Other
frontal lobe structures which have evidenced a relationship between extraversion and
personality-dependent changes in gray matter density or volume have included the anterior
cingulate cortex, inferior frontal gyrus, middle frontal gyrus, superior frontal gyrus,
all of which are known to be involved in emotional and socio-cognitive processes (Coutinho
et al., 2013; Cremers et al., 2010; Forsman, de Manzano, Karabanov, Madison, & Ullen,
2012; Lu et al., 2014). Taken as a whole, the structural evidence from VBM suggests that
one aspect of personality differences may be individual variation in the organization of
brain networks for evaluation of socially relevant stimuli, including regions involved in
recognition of social-affective stimuli and social judgment.

<h>CONNECTIVITY</h>
------------

Whilst the evidence presented in the previous sections has revealed important initial
insights into the structural and functional neural correlates of personality, current
knowledge of relationships between brain function and structures and personality traits is
still rather limited. White matter mediates communications in the brain and is critical
for the integrity of brain function. As noted above, neuroticism indexes the tendency to
experience negative effect, and functional imaging has evidenced the importance of the
relationship between functioning of the amygdala and PFC in response to negative emotion
cues (Haas et al., 2007; Harenski et al., 2009; Hooker, Verosky, Miyakawa, Knight, &
D'Esposito, 2008). It is perhaps not surprising therefore that subsequent research with
Diffusion Tensor Imaging (DTI) has evidenced a positive correlation between neuroticism
and a measure of loss of white matter integrity in the anterior cingulum and uncinate
fasciculus, tracts that connect the PFC and amygdala (Xu & Potenza, 2012). This modulatory
effect of neuroticism on the connectivity of the PFC and amygdala is in line with similar
demonstrations with functional MRI measures in the context of affective reactivity
(Cremers et al., 2010). However, other DTI evidence has suggested that the breakdown in
white matter integrity associated with neuroticism may be more widespread, and include
fibres connecting frontal, occipital, parietal and temporal lobes, tracts connecting
orbitofrontal regions with limbic regions, fibre tracts connecting thalamic nuclei with
the frontal lobes, and cross-hemispheric pathways including the corpus callosum
(Bjornebekk et al., 2013). It was speculated by the authors that the more widespread
relationship between neuroticism and white matter integrity observed in this second study
might reflect its greater methodological sensitivity. The wide distribution of effects in
the latter study further suggests that general rather than regionally specific processes
might be driving the effects, and emphasizes the importance of collecting white matter
integrity measures throughout the brain. Evidence for personality-linked patterns of
functional connectivity independent of performance of a given task, comes from the
analysis of resting state data, that is from the patterns of spontaneous activity
observed, that are intrinsic and stable across time. Identifying brain correlates of a
situation-independent personality structure requires evidence of a stable ‘default’ mode
of brain functioning (Sampaio, Soares, Coutinho, Sousa, & Goncalves, 2014). Thus in terms
of low-frequency fluctuations, neuroticism has been observed to correlate negatively with
regional activity of the middle frontal gyrus and precuneus, whilst extraversion has been
observed to correlate positively with regional activity of the striatum, precuneus and
superior frontal gyrus (Kunisato et al., 2011). The former might reflect the association
of neuroticism with the role of the precuneus in anticipatory fear (Kumari et al., 2007),
and an inbuilt mechanism to attempt emotional regulation in order to deal with the
predisposition to negative affectivity (Pan et al., 2014; Seo et al., 2014). For
extraversion, the striatal correlation observed more likely reflects the importance of
reward processing (Schultz, 2015), but the positive involvement of the precuneus may this
time reflect a reduced need for emotion regulation. The link between low frequency
oscillations in the precuneus in the resting state and degree of extraversion has
subsequently been confirmed by another group (Wei et al., 2014). Seed-based correlation
analysis has continued this theme of differences between neuroticism and extraversion in
reward processing and need for socio-emotional regulation. Thus higher neuroticism scores
have been observed to correlate with increased amygdala resting state functional
connectivity with the precuneus, and decreased amygdala resting state functional
connectivity with the temporal poles, insula, and superior temporal gyrus (Aghajani et
al., 2014). Conversely, higher extraversion scores in this study correlated with increased
amygdala resting state functional connectivity with the putamen, temporal pole, insula,
and occipital cortex. These changes in amygdala resting state functional connectivity
associated with neuroticism perhaps reflecting the less adaptive perception and processing
of self-relevant and socio-emotional information frequently seen in neurotic individuals
(Robinson, Moeller, & Fetterman, 2010), whereas the amygdala resting state functional
connectivity pattern associated with extraversion perhaps reflecting the heightened reward
sensitivity and enhanced socio-emotional functioning in extraverts. Placing the seed
region in the precuneus or anterior cingulate has revealed that neuroticism predicts
resting state functional connectivity with brain areas involved in self-evaluation and
fear, whilst extraversion predicts resting state functional connectivity with brain areas
involved in reward and motivation (Adelstein et al., 2011). Given that neuroticism is
known to be associated with anxiety and self-consciousness (Montag, Reuter, Jurkiewicz,
Markett, & Panksepp, 2013), and extraversion is implicated in gregariousness and
excitement-seeking (Li et al., 2010), it seems that the major contribution of this
literature is the clear consistency it evidences with known qualities about each
personality domain. At a more general level, compared with less neurotic individuals,
highly neurotic individuals may exhibit a whole-brain network structure resembling more of
a random network, with weaker functional connections. In such highly neurotic individuals,
Servaas et al. (2015) demonstrated that functional sub-networks could be delineated less
clearly and the majority of these showed lower efficiency. The authors concluded that the
‘neurotic brain’ has a less than optimal functional network organization and that it shows
signs of functional disconnectivity. Moreover, in high compared with low neurotic
individuals, emotion and salience sub-networks seemed to have a more prominent role in the
information exchange relative to the sensorimotor and cognitive control sub-networks
(Servaas et al., 2015).

<h>FUTURE DIRECTIONS: WHAT MIGHT EYSENCK HAVE WANTED FOR THE FUTURE?</h>
-----------------------------------------------------------------

If we could go back to the 1990s, the easiest way to answer this question would have
required going to the canteen of the Institute of Psychiatry (now known as the Institute
of Psychiatry, Psychology and Neuroscience) around 10.30 am and approach Hans Eysenck. We
believe he would have given insightful suggestions with a smile, just as he did when
approached by the second author when she first arrived, an unknown hopeful post-doc from
India, at the Institute of Psychiatry. Nonetheless, we identify some areas, which we
believe will advance our understanding of the neural basis of individual differences. We
believe that there is a great need to understand why some people are better at
interpreting emotion cues than others, and we believe that personality effects are one
such mechanism by which these individual differences occur. If we are able to demonstrate
clear personality-linked differences in the way people's brains shape their response to
emotion cues, a myriad of future applications will likely ensue (Bruck, Kreifelts, &
Wildgruber, 2011). Can brain activation patterns be used to classify normal and
dysfunctional emotional reactivity with machine learning classifiers? Can we distinguish
the types of people (i.e., personality types) skilled in decoding nonverbal emotion cues
from those with difficulties interpreting such cues based on typical patterns of brain
activation? Pursuing an individual differences approach in the study of emotional
reactivity not only holds the potential to further advance current models of social
cognition; it may also guide the way to a better understanding of individual disturbances
of emotion perception associated with psychiatric disorders. Here it is worth noting that
in the latest incarnation of current diagnostic guidelines (Diagnostic and Statistical
Manual of Mental Disorders; DSM-V), there is much greater emphasis on dimensional
approaches to describing mental ill health than in previous editions (Kraemer, 2007). From
a clinical perspective, a clear demonstration of a relationship between personality and
emotional reactivity could be used to argue that changes in emotion perception could be
harnessed as a reasonable alternative way of monitoring clinical improvement among
individuals receiving treatment for personality disorders, as a ‘surrogate marker’.
Pursuing other cognitive and affective functions which relate to individual differences in
behavioral studies (but not considered so far by personality neuroscience researchers),
and also found to be aberrant in certain psychiatric disorders, would be just as valuable.
We suggest that future studies are also sufficiently powered to examine personality
effects, in particular trait interactions (e.g., extraversion with/without high
neuroticism), in brain responses at rest, to varying cognitive demands and emotional
challenges, and rule out the influence of other factors such as gender, age and IQ (which
also affect brain properties). Most existing studies of extraversion, neuroticism
(reviewed earlier) and related traits (reviewed by McNaughton, Corr, & DeYoung, 2015) have
been too small to examine such effects and mostly ignored them. It may be possible to
achieve larger samples sizes with increased co-operation between research groups, without
much additional cost (Mar, Spreng, & Deyoung, 2013). We further suggest that personality
neuroscience researchers, wherever possible, utilize relevant personality theories (e.g.,
reinforcement sensitivity theory) (Corr, 2008) and cognitive psychology (e.g., to
determine task properties, cognitive processes involved, time on task etc.) to guide their
neuroimaging experiments and interpretations. Finally, we suggest that future studies
should examine the influence of personality traits in trial-to-trial variability in brain
signals. If confirmed, personality influences in these signals have implications for our
understanding of brain basis of individual differences in personality but also for the
neuroimaging community at large.

<h>CONCLUSIONS</h>
-----------

The findings reviewed above provide compelling support that, as proposed by Eysenck,
individual differences in extraversion and neuroticism are related to the functioning and
structure of various brain regions. Our review suggests a strong relationship between
neuroticism and emotion processing neural networks, particularly during exposure to
negative emotion cues, and suggests a relationship between some of the same emotion
processing regions and extraversion in response to positive emotion cues. These regions
include some cortical regions implicated in emotion regulation, depression and anxiety, in
addition to most sub-cortical/limbic regions. At present, there are few data directly
assessing the relationship between extraversion and cortical arousal system in the context
of varying stimulation levels (e.g., by increasing cognitive load), but they are
remarkably consistent with Eysenck's model.


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<ART>Helping as an early indicator of a theory of mind: Mentalism or Teleology?
==========================================================================

Authors: Beate Priewasser, Eva Rafetseder, Carina Gargitter, Josef Perner
DOI: 10.1016/j.cogdev.2017.08.002
Year: 2018  |  Pages: 69-78
ASJC codes: 3204, 3205
Keywords: Early false belief understanding, Helping paradigm, Replication, Teleology, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This article challenges the claim that young children's helping responses in Buttelmann, Carpenter, and Tomasello's (2009) task are based on ascribing a false belief to a mistaken agent. In our first Study 18- to 32-month old children (N = 28) were more likely to help find a toy in the false belief than in the true belief condition. In Study 2, with 54 children of the same age, we assessed the authors’ mentalist interpretation of this result against an alternative teleological interpretation that does not make the assumption of belief ascription. The data speak in favor of our alternative. Children's social competency is based more on inferences about what is likely to happen in a particular situation and on objective reasons for action than on inferences about agents’ mental states. We also discuss the need for testing serious alternative interpretations of claims about early belief understanding.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Buttelmann’s helping paradigm plays an important role in the discussion about when infants
or children come to understand belief (Buttelmann, Carpenter, & Tomasello, 2009: BCT). In
the standard false belief test children are asked to predict where an agent, who is
mistaken about an object’s location, will look for it. Quite reliably only by about 4
years children answer this question correctly (Wimmer & Perner, 1983; Wellman, Cross, &
Watson, 2001). In contrast, children’s looking behavior that indicates their anticipations
about where the agent will search for the object provides evidence for sensitivity to
false beliefs in infants as young as 18 months (Clements & Perner, 1994; Southgate, Senju,
& Csibra, 2007; Thoermer, Sodian, Vuori, Perst, & Kristen, 2012). In violation of
expectation paradigms evidence was found at an even younger age around 14–16 months
(Onishi & Baillargeon, 2005; Surian, Caldi, & Sperber, 2007). Prolonged looking when an
agent’s belief does not match the child’s own belief showed sensitivity to the agent’s
belief as young as 7 months and similar ages are reported for neural signatures of
representing belief (Kampis, Parise, Csibra, & Kovacs, 2015; Kovacs, Teglas, & Endress,
2010; Southgate & Vernetti, 2014). BCT provide an importantly different kind of evidence
for early understanding of belief because they used helping behavior, an intentional
action, as an indicator of understanding. Before expanding on the ongoing debate about the
nature of young children’s false belief understanding and on our alternative
interpretation of BCT’s findings we start by describing their procedure and interpretation
in detail. Two experimenters E1 and E2 (E2 being the agent to be helped) engage with the
child C. After a short warm up E2 discovers two boxes of different color (A and B) and
opens and closes the lids of both with interest. In E2’s absence E1 shows C how the boxes
can be locked and opened with a pin. E1 leaves the boxes unlocked and E2 returns excitedly
with a caterpillar toy. She plays for a while with it, introducing it also to E1 and C,
and puts it into box A. In the false belief (FB) condition E2 leaves again to get her
keys. E1 and C “play a trick” on E2 and E1 sneakily moves the toy to box B, continuously
checking on the door, and then locks both boxes with the pin. E2 returns and tries to open
box A (where she thinks the toy still is). In the true belief (TB) condition E2 stays in
the room and watches how E1 moves the toy to box B with mutual eye contact with E2 and C.
E2 looks briefly away when E1 locks the boxes with the pin. After going to check whether
the door was properly shut, E2 approaches box A and unsuccessfully tries to open it. If
the child does not respond immediately, E1 suggests to C to help E2 and if needed, several
prompts follow. BCT tested one group of 18-month- and another group of 30–32-month-old
children and found that in each age group children in the FB condition tended to go to box
B to retrieve the toy for E2, while in the TB condition they tended to help E2 to open box
A. The mentalistic interpretation preferred by BCT is as follows: When E2 tries to open
the locked box A the child has to figure out the reason for E2’s action. Since in the FB
condition E2 thinks that the toy is still in box A she most likely is looking for her toy.
Since she does not know where the toy really is the children help her find it in box B. In
the TB condition E2 knows that the toy is in box B, therefore she cannot be after the toy
when trying to open box A. She must be trying to open A for some other (unknown) reason.
BCT’s results play a central role for theories about the cognitive basis of early theory
of mind competences. Two lines of explanation are particularly prominent. The first one
distinguishes between an implicit and explicit understanding (Clements & Perner, 2001;
Onishi & Baillargeon,2005). Children’s looking is an indirect measure of their knowledge.
They look as a consequence of their expectations and not in order to serve a purpose (They
look there because the agent will go there, not in order that the agent will go there, nor
in order to tell the experimenter what they are thinking). Whereas, they answer the test
question posed in the traditional false belief task in order to answer the question.
Appropriate responses on an indirect measure (looking) in the absence of correct
responding to a direct measure (answer to question) is taken as a sign of implicit
knowledge in the consciousness literature (Reingold & Merikle, 1993; applied to false
belief studies: Clements & Perner, 2001). Children’s helping behavior in BCT’s study is
highly relevant evidence, since it is a direct measure: children do it in order to help
the experimenter. So their data speak against the implicit knowledge explanation
(Carruthers, 2013, p. 145). The second main explanation of the discrepancy in when
children take belief into account assumes that children have explicit knowledge from early
on but cannot show it in the standard task due to processing limitations. Baillargeon,
Scott, and He (2010) distinguish between spontaneous and elicited test responses. Looking
time and gaze direction are spontaneous responses, while the answers to the traditional
test questions are elicited responses. In particular the additional processing required by
the test question is supposed to exceed younger children’s processing capacity. BCT’s
finding thus poses a problem for this theory since children’s helping is elicited by E1’s
verbal suggestion to help E2 (the relevant agent to whom a belief is supposed to be
attributed). Hence it should be as difficult as the standard test, which it is not. To
account for BCT’s data Carruthers (2013, p. 152), for instance, saw the need to amend
Baillargeon et al.’s theory with assumptions from language pragmatics as proposed by
Helming, Strickland, and Jacob (2014) and Helming, Strickland, and Jacob (2016). When
being asked a question by the experimenter in the traditional test, children have to
coordinate their third-person perspective as a listener to the story with their second
person perspective when interacting with the experimenter. It is this coordination of
perspectives that makes the traditional task so difficult and helping in BCT’s procedure
easy since this does not necessitate such coordination. In contrast, Setoh, Scott, and
Baillargeon (2016, also Scott, 2017) argue that despite requiring elicited responses BCT’s
task is easier than the standard false belief task because it lacks the need for
inhibiting a prevalent (reality oriented) response. Evidently, BCT’s results are of great
theoretical importance for the field. For this reason we decided to have a closer look at
their replicability and interpretation. Although there are quite a few demonstrations of
early sensitivity to belief, hardly any of them have been replicated by different
laboratories (e.g., for BCT’s task Fizke, Butterfill, & Rakoczy, 2013 found similar
results but they used a noticeably different procedure). Another question, of course,
concerns the interpretation of the results. Again, although there are many demonstrations
of infants’ sensitivity to belief in different situations, no study that we are aware of,
has yet specifically tested the more recently suggested alternative interpretations for
several of the VOE and AL studies (e.g., Ruffman, 2014; Wellman, 2014, chp 8). To our
knowledge the only study that tested an alternative explanation for BCT’s findings was run
by Allen (2015). Allen (2015) contrasted the FB condition with a new clairvoyance
condition, which was the same as the FB condition except that E2 tried to open box B,
where the toy is but E2 thinks it is empty. If, so Allen reasoned, children take E2’s
false belief into account E2 must be intending to open an empty box, so they should direct
E2 to box A, which is empty. Children did not do this. They helped E2 find the toy as
often in the clairvoyance as in the FB condition. However, Allen’s argument is not very
persuasive, since trying to open a box of which one thinks that it is empty, does not mean
one wants to open box A because one thinks it is empty. One might have plenty other
reasons for opening it. To gain experience with BCT’s paradigm we started with a straight
replication of the original TB and FB conditions.2 We soon noticed that with the FB-TB
manipulation not only E2’s belief changed but the conditions had a quite different feel.
One very obvious difference is the trick which E1 plays on E2 only in the FB condition. As
already pointed out by Allen (2015, p.66):“Hiding the toy in the context of playing a
trick not only makes the toy particularly salient but it also creates an expectation that
the adult is going to return and look for the toy”. Two further potentially confounding
factors pertain to ownership of the toy and to E2’s projected interest in the toy. The
procedure of the FB condition (1) confirms the initial impression that the toy belongs to
E2 because, for example, E1 only dares move it secretively in E2’s absence. Children this
age have already an acute sense of ownership (Nancekivell, Van de Vondervoort, & Friedman,
2013). (2) The condition also leaves unquestioned that E2 takes great interest in her toy.
In contrast, E2’s behavior in the TB condition signals that (a) it may not be E2’s toy
since he watches E1 move the toy without complaining that they have not asked for
permission and (b) that E2’s enthusiasm and interest for the toy must have waned towards
the end since E2 watches as a bystander while E1 moves the toy. Ownership and interest
therefore are further possible common sense reasons which could explain children’s
different behavior in the two conditions. Taken together we proposed three possible
factors (i.e., ownership, interest and playing a trick, but there could be many more) that
provide teleological reasons for children to show a distinct helping pattern in the two
conditions that are not based on belief reasoning. However, the purpose of the study is
neither to investigate the specific reasons that might motivate children’s behavior nor
the general nature of early pro-sociality. What we want to test is whether their responses
in this task are based on belief reasoning or on some kind of teleological reasoning (as
understood by Perner & Roessler, 2010). Perner and colleagues (Perner & Esken, 2015;
Perner & Roessler, 2010) argue that by 9–18 months children become ‘teleologists’ able to
derive an agent’s reason for an action without concern for the subjective views provided
by mental states. The important feature of teleology is to see objective facts as
providing the reasons for action. For instance: it starts to rain at the birthday party.
The teleologist naturally perceives the need for a shelter for the birthday cake (the cake
being under a shelter is preferable/more-desirable/better than it being left in the rain,
which makes it a potential action goal) and uses her knowledge of where to find a shelter
to bring the cake there. Although the evaluation of the cake being under a shelter as
‘better’ (or desirable) and the ‘facts’ of the shelter’s location are based on the
teleologist’s subjective view, the teleologist treats these ‘subjective facts’ as
objective. For the teleologist it is a simple fact that it is better to shelter the cake
than leave it in the rain; it is not a matter of being considered better by some people
depending on their subjective views of what is good or bad. This subjectivity is inherent
in the mentalist concepts of desire (subjective view of what would be a better state,
i.e., a goal) and belief (subjective view of what the facts are). To illustrate how
teleology applies to BCT’s scenario we use the suggestion from above that children
perceive the agent’s (E2’s) continued interest in playing with the toy. In the FB
condition E2 is continuously playing with the toy (which makes her happy and thus for a
pleasant, desirable situation). That E2 has to interrupt her play in order to fetch a key
suggests that she will continue to play with the toy on her return. Hence, enabling her to
do so will make for a better situation (she’ll be happy; a goal to be achieved) than
preventing her from doing so (she’ll be nervous and grumpy). Consequently, when she is
looking for the toy in the wrong box children have good reason to help her find the toy in
box B to achieve a better situation (a goal). In the TB condition the agent interrupts her
play with the toy and watches the child and E1 play with it and then briefly moves away to
close a door. This gives less clear indication that the agent is likely to resume her play
with the toy. So when she tries to open the empty box the teleologist child perceives no
compelling reason to direct her to the box with the toy. To note: this explanation of the
results by BCT does not depend on children making use of E2’s belief about the content of
the boxes to infer what E2 wants, as BCT suggested. There is no need for mentalizing; a
basic concern about what purpose (goal) E2 pursues is directly indicated by her different
behavior in the early stages of the TB and FB conditions. With these assumptions outlined
above BCT’s data can be explained without children having to concern themselves with E2’s
beliefs or knowledge. When in the FB condition E2 returns it is very likely that she is
coming back for her toy. When she is trying to open box A children recognize her error and
correct her by redirecting her to her toy in box B. In the TB condition it is not so clear
what E2 wants. When she tries to open box A she is likely to want to open this box – for
whatever reasons – and thus children help her do so. We tested our teleological
alternative against BCT’s mentalistic explanation of their data using three boxes, A, B,
and C in four conditions. Two conditions, the old-FB and old-TB condition, corresponded to
BCT’s FB and TB conditions, except for the presence of the third box that was not used in
the test procedure, only in the training phase. The new-FB condition conformed the
original FB condition except that E2 tried to open the third and empty box C. In the new-
TB condition E2 behaved as in the original TB condition except for trying to open the
empty box C rather than the empty box A, into which E2 had originally placed the toy. We
expect that the presence of the third box will not influence children’s helping behavior
and that we will replicate BCT’s original results in the old-FB and old-TB conditions. For
the new-FB condition the two theories make different predictions. If children use E2’s
belief and knowledge to infer what E2 wants (BCT’s theory) then children should behave in
the new-FB condition in the same way as in the original TB condition: they should help
open box C, since E2 knows that box C never contained her toy and she cannot be looking
for it. Our teleological alternative predicts that since E2’s behavior in the early phases
of the new-FB condition was the same as in the original FB condition, this should signal
directly that E2 is interested in getting her toy. So children should help her find it by
directing her to box B that contains the toy. For the new-TB condition the two theories
make the same behavioral prediction. BCT predict that children help open C because E2
knows that it is empty. The teleological alternative predicts that children help open C
because E2, who lost interest in the toy, is now interested in opening box C. One should
point out, though, that teleology by itself does not yield a strict prediction of how
interested children should be in opening box C. Only because we know from the results of
BCT that they are under these conditions that we make this prediction. Table 1 provides an
overview of the four conditions and each theory’s predictions.

<h>STUDY 1</h>
-------

The objective of this study was not primarily to see whether BCT’s result can be
replicated but whether we would manage to replicate it using – within our possibilities –
the same materials and procedure before we proceeded to test an alternative interpretation
of the data in Experiment 2.

        <hss>Participants</hss>

        Overall, 45 children between 18 and 32 months (Mage = 24.47, SD = 4.08, 20 girls)
        participated in the study. The age range was chosen to cover the range between
        BCT’s youngest in their sample of 18 month olds in Study 2 and their oldest in
        Study 1. These two groups showed about the same size of effect, which we try to
        replicate. A third group of 16 month olds did not show a significant effect and so
        we did not include this age in our study. Data were collected in the Theory of
        mind Child Lab of the University of Salzburg (n = 20), the Parent-Toddler Group of
        the University of Stirling, (n = 17) and in the Little Stars Nursery (n = 8).
        Seventeen children had to be excluded because of parental/teacher error (3),
        fussiness (10), unclear responses (2), or because they did not respond to any
        helping request by opening or at least touching one of the boxes (2). Compared to
        BCT, who excluded 23% of the 2,5-year-olds and 54% of 18–16 month-olds, our
        overall dropout rate was similar (35%). For child centered reasons only (fussiness
        and no response) BCT excluded 6.5% of the 2,5 year olds and 26% of the 16–18
        months olds while we excluded 13% of the older children (26–32 months) and 41% of
        the younger children (18–25 months olds) of our sample. The 28 children of the
        final sample had a mean age of Mage = 25.64 months, (SD = 3.64, range = 20–32
        months, 12 girls).

        <hss>Materials</hss>

        Materials were produced according to the description in Buttelmann et al. (2009).
        Boxes were identical in size, virtually identical in locking mechanism, handlebars
        and color; for the stuffed toy we also used a caterpillar which was roughly the
        same size (48 cm). Following David Buttelmann’s advice, the locking mechanisms of
        the boxes were loosened so that they would make a noise when E2 tries to open them
        and the caterpillar was stuffed especially with plastic foil so that it made
        sizzling noises when being moved. Both features may be important for grabbing
        children’s attention during the procedure. For the warm up and instruction phase a
        wooden pegboard game was used.

        <hss>Procedure</hss>

        For a detailed description of the procedure see Buttelmann et al. (2009). To
        replicate the original procedure we prepared transcripts (English and German) of a
        video provided by David Buttelmann. We then videotaped our procedure and received
        written feedback from him for both, the English and the German version. We
        implemented his detailed feedback on the protocol as well as on our realization of
        the procedure. As in BCT children participated either in a TB or in a FB
        condition. Position and color of the boxes as well as where the toy was placed
        first were counterbalanced. E2’s eye gaze before attempting to open a box was also
        counterbalanced. Test-sessions were videotaped and coded by two independent
        raters. As in the original study, it was coded which box a child opened or touched
        first. Our coding and exclusion criteria followed closely that of BCT. However, in
        the FB condition two children showed an interesting response pattern that was not
        reported by BCT but also occurred in Allen’s (2015) study with 3–5-year olds; they
        responded by opening the old toy box first but not to help E2 to open it but only
        to gleefully show E2 that the box is now empty. Immediately after doing so they
        opened the current toy box to show E2 that the caterpillar had been hidden there.
        Both children additionally verbalized “Here it is!” Although these children
        touched the old box first, we interpret this behavior in BCT’s favor as an
        understanding that E2 did not know the new location of the caterpillar. In order
        to avoid false negatives a “re-coding” according to this interpretation was added
        to the “original coding” by BCT and we will report results for both. Overall, two
        raters disagreed only on two trials. As a result, one child was excluded due to an
        unclear response. For the other child agreement could be reached through
        discussion with a third rater.

<hs>  Results & Discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~

The 28 children needed different amounts of prompting to either touch or open a box.
Eleven children spontaneously responded to E2’s nonverbal request, nine children responded
to one of E1’s prompts, four children responded to one of E2’s verbal prompts and four
children helped only when their parent or teacher prompted (3) or assisted (1) them. The
center panel of Table 2 shows the number of children choosing either box B with the toy
(two of them re-coded in the FB condition) or the empty box A. The right panel shows the
original results by BCT in comparison. As one can see the proportion of children helping
to open box B that contained the toy in the FB condition in our study is very high
(recoded: 93%, original coding: 79%) and comparable to the original study (76%) and
differs from a uniform distribution (Binomial test: re-coded: p = .002; original: p =
.057). In contrast, the distribution of responses in the TB condition looked different.
The proportion of the expected empty-box response was not even half (43%) in our study as
opposed to the original study (81%) and the responses did not differ significantly from a
uniform distribution (Binomial test: p = .79 in our case). If we compare our results in
the TB condition directly with BCT’s the difference is highly significant (χ2 = 7.15, p <
.01). We have no good explanation to offer for this difference except for the observation
that most children appeared to be at a loss of what is being asked of them in this
condition. Despite this different performance in the TB condition, we nevertheless find a
trend of a different proportion of B (box with toy) responses in the two conditions:
Fisher’s exact test p = .038 (relying on the recoded responses, with original coding: p =
.21, both one-tailed) but two-tailed p = .077 (relying on the recoded responses, with
original coding: p = .42). Hence, the data do not clearly speak against the null-
hypothesis. We will take up this point again in the General Discussion. Since our study
supported children’s strong tendency to help the agent in the FB condition of the original
study we thought to be in a good enough position to venture a test of our alternative
explanation for that condition.

<h>STUDY 2</h>
-------

The prime objective of this study was to assess how children in the FB condition infer
from E2’s attempt to open an empty box that E2 must be looking for her toy. Is it critical
for their inference that the agent is trying to open that box, in which she mistakenly
thinks her toy is located or is their inference based on some other information? We have
suggested at least three other factors that may lead to that inference: in the FB
condition – in contrast to the TB condition – children are primed by the initial part that
(1) the toy belongs to E2, (2) E2 has great interest in playing with her toy, and is
likely to engage in a hide and seek routine (Allen 2015). Any one of these factors make
children expect that E2 will look for her toy on her return. When E2 returns and tries to
open the now empty box children help her find the toy, without any concern for her false
belief about where the toy now is. Children do not show the same helping behavior in the
TB condition since the TB condition strongly suggests that the toy does not belong to E2,
that she has lost interest in the toy, and because no hide and seek routine is indicated.
Hence when she tries to open the empty box fewer children assume that she is still looking
for the toy and that she tries to open the empty box for some unknown reason.
Consequently, fewer children direct her to the toy and, instead, help open the empty box.
A new version of the FB task (new-FB) with three boxes can distinguish between the
different explanations. Instead of trying to open the box that she believes contains her
toy, E2 tries to open the third box which is also empty and has never contained the toy.
If children rely on E2’s false belief to figure out that she is likely looking for her toy
– as BCT suggested – then they should come to the conclusion that she must have some other
reason for trying to open this box since she knows that it does not contain her toy. If,
however, children assume that the agent is keen to play with her toy again, as we
surmised, then they should also help her to find the toy in this new-FB condition. In
order to tie in the results with the 2-boxes version, there will be an old-FB and an old-
TB condition identical to the two boxes experiment in Study 1, except for the presence of
a third box (which is involved in the training but not in the transfer in the test phase).
For these two conditions we anticipate to replicate the results from Study 1. What differs
in the new-TB condition is that instead of attempting to open box A the agent tries to
open the third box C (as in the new-FB condition). Both theories predict the same
behavior, that is, children will show the same response pattern in the new-TB as in the
old-TB condition. Its purpose is to check whether the active involvement of the third box
creates any deviation from what is expected.

        <hss>Participants</hss>

        Overall, 126 children between 18 and 32 months were tested either in the Theory of
        mind Child Lab of the University of Salzburg (n = 20), in different childcare
        institutes in the city of Salzburg (n = 87) and in Scotland (n = 19). Testing in
        institutes took place in a separate room and in the presence of the child’s
        teacher or parent. Thirty-six children (28%) had to be excluded due to
        parental/teacher (4) or experimenter error (4), fussiness (20), unclear responses
        (3) or because they did not respond to any helping request (5). Overall, 29.1% of
        children (20,6% of the older (28–32 months) and 37.5% of the younger (18–27
        months) ones) were excluded. The final sample consists of 90 children between
        18.04 and 32.82 months (M = 27.15 months, SD = 3.65, 40 girls). Thirty-seven
        children participated in the replication conditions (Mage = 27.17 months, SD =
        3.69). Six children spontaneously responded to E2’s nonverbal request, 13 children
        responded to E1’s prompts, five children responded to E2’s verbal prompts, 11
        children responded to their parents/teachers prompt and one child needed
        parental/teacher assistance. Fifty-three children participated in the new
        conditions (Mage = 27.13 months, SD = 3.66). Seven children spontaneously
        responded to E2’s nonverbal request, 26 children responded to one of E1’s prompts,
        eight children responded to one of E2’s verbal prompts, 10 children responded to
        their parents/teachers prompting and one child needed parental/teacher assistance
        (unfortunately, for one child video recording is missing and therefore amount of
        prompts cannot be reported).

        <hss>Materials & Procedure</hss>

        In this study we added a third, differently colored but otherwise identical, box.
        All remaining materials were the same as in Study 1. The three boxes were set up
        in a semi-circle in equal distance (80 cm) to each other. The distance between the
        child and each box was 1 m. As in Study 1 the experiment started with E2
        discovering the boxes. She opened and closed the lids of all three boxes several
        times before leaving the room so E1 could explain the locking mechanism to the
        child. By doing that E1 treated all boxes identically and according to the
        protocol of Study 1. The procedure in the test-phase was also identical to Study
        1, with the exception that E1 locked the third box with the pin without attracting
        the child’s attention to it and that E2 was sitting in some distance behind the
        three boxes in the decision-phase. Further details can be found in the
        supplementary materials.

        <hss>Design & Coding</hss>

        Children participated in one of the four conditions. We had two TB conditions and
        two FB conditions that differed according to which of the three boxes E2 tried to
        open (see Table 1). In neither condition the third box C was involved in the
        transfer of the toy from box A (old) to box B (current). Two of the conditions
        (old-FB and old-TB) were a replication of the original study, with the only
        exception that the third box was also present in the setting. In these conditions,
        E2 always tried to open the now empty box A. In both of the new conditions (new-FB
        and new-TB), E2 always tried to open the third, non-involved box C. Colours of
        boxes were assigned to position according to a Latin Square Design within each
        condition. So the location of the boxes was fully counterbalanced, as was where
        the toy was put first. This makes for 36 different combinations to which children
        were randomly assigned without using a combination twice. The direction of
        transfer was varied such that the toy was always transferred from box A to the box
        to the right, if A was the box on the right the toy was transferred to the box on
        the left. Eye gaze was varied such that E2 always looked at box B first, then at
        the left empty box (which could either be box A or C), then at the right empty box
        (which could again either be box C or A). Test-sessions were videotaped and coded
        by two raters. Again, it was coded which box a child opened or touched first. Two
        raters agreed on 87 of 90 trials and the disagreements were resolved through
        discussion with a third rater. Again, three children in the FB conditions showed a
        response as described in Study 1: after opening the box that E2 tried to open they
        showed her that it was empty and immediately proceeded to show her where the
        caterpillar was hidden. We re-coded these children as directing their response
        (primarily) at box B. We will again report results according to this re-coding as
        well as for the original coding.

<hs>  Results & Discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~

Table 3 shows children’s responses in the four conditions. Children practically ignored
the third box C (with the exception of one child) and showed a preference for box B,
containing the toy, in both conditions but not significant in either (Binomial Test both
ps > .11). However, the pattern of results for A-responses and B-responses is not
significantly different from the results of Study 1 (χ2 (3) = 3.212, p > .36). The results
of the old FB and TB conditions, which we hoped would replicate the results of the two box
conditions in Study 1, indicate that the use of three boxes flattened the distribution of
chosen boxes. This suggests increased error responding. Closer inspection of the data
showed that children had a strong preference for approaching the center box, the one
closest to E2. The choices of boxes for all four conditions were 26% left, 53% center, and
21% right box. This differed from the expected uniform distribution (χ2 (2) = 9.8, p >
.007), which should have occurred since assignment of A, B, and C to box location was
counterbalanced. Evidently the center box attracted children, which increased error
trials. So we excluded this source of error by looking only at responses directed at the
left or right box, shown in Table 4. Now the picture becomes much more accentuated. The
response frequencies for the old conditions now resemble closely those of Study 1. Without
the distraction of the center box Study 2 replicates Study 1, which is reassuring as it
shows that the use of the third box does increase error but does not distort the results.
We now turn to our core concern, children’s responses in the new-FB condition with our
focus on children’s response directed at the box with the toy (B) in relation to the box,
which E2 tries to open (C). According to BCT’s theory children will know that E2 believes
that the toy is in box A and should therefore show the same preference for the box E2 is
trying to open (C), as they do in the original TB condition. Our theory predicts, however,
that children assume that E2 is looking for her toy and, therefore, direct her to the box
with the toy (B), as they do in the original FB condition. The data confirm that more
responses were directed at B than at C. To see whether this refutes one and supports the
other theory we calculated a Bayes Factor (BF). Each theory is tested against the null
hypothesis H0 of no preference between the two boxes. We use Rouder’s Bayes calculator for
binomial data: http://pcl.missouri.edu/bf-binomial. For specifying the model of H1 for
BCT’s theory we use the observed proportions from BCT’s original TB condition (see Table
2) since their theory lets us expect similar results to their TB condition in our new-FB
condition. The model thus specifies the proportion of 30/37 for C (which the agent tries
to open) vs 7/37 for B (where the toy is). The corresponding observed proportions in the
new-FB condition of 6/24 for C and 18/24 for B result in BF = 0.00076, very strong
evidence against BCT’s theory3 (Dienes, 2014; Lee & Wagenmakers, 2014). In contrast, our
explanation predicts that children should behave in the new-FB condition as in BCT’s FB
condition. Thus we use the data from their FB condition with 28/37 for B (where the toy
is) vs. 9/37 for C (which the agent tries to open) to specify H1. Given the observed
proportions this yields BF = 17.86 substantial evidence for our hypothesis. The same
result is obtained for the reduced data set excluding middle box responses (see Table 4)
with BF = .005 for BCT’s theory and BF = 9.09 for our theory. Moreover, there were
significantly more B responses in the new-FB condition than in the new-TB condition in
relation to C responses (Fisher’s Exact p = .031). One can argue that what matters for
BCT’s mentalist claim is that the original FB condition should lead to more B-directed
responses because E2 is trying to open the box she mistakenly thinks her toy is in.
Whether children direct their helping at the box E2 is trying to open in the TB condition
is not really of essence. In fact our data suggest that children do not have much idea of
what they are supposed to do in the TB condition. Hence a fairer test might be to contrast
the number of B-directed responses with responses directed at any one of the other boxes
(A or C). In this case we get a highly significant difference between conditions: Fisher’s
exact test p = .006.4

<hs>  4 General discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~

The overarching aim of this paper was to test an alternative interpretation of Buttelmann
et al. (2009). Study 1 was a direct replication attempt to build a fundament for testing
this alternative hypothesis. Like in the original study, children’s responses in the FB
condition were much more often directed at the box that contained the toy than at the
empty box. We could also show that this tendency was stronger in the FB than in the TB
condition, albeit children not showing the expected preference for the empty box in the TB
condition in our study. The theoretical thrust of our data comes from our new-FB condition
in Study 2 designed to distinguish BCT’s original mentalistic explanation from our
teleological alternative. BCT claimed that in order to be able to help the agent children
must infer in the FB condition that the agent wants her toy as she is trying to open the
box where she believes her toy to be. Whereas in the TB condition, the agent tries to open
a box, which she knows is empty, she probably wants to open that box for unknown reasons.
In our new-FB condition the agent tries to open box C, which she knows to be empty.
Therefore, on BCT’s reasoning, she cannot be looking for her toy but must intend to open
that box for some other reason. Consequently children should direct their response to this
box the agent is trying to open, in analogy to the original TB condition. Our data speak
strongly against this explanation. Our suggestion is that children infer what the agent
wants without concern for her mental states. The procedure in the FB condition signals
that she is still highly interested in her toy or is likely to engage in a hide and seek
routine when she returns, therefore children will help her find her toy when she makes an
error of looking into box A instead of box B. For our new-FB condition this theory, as
opposed to BCT’s theory, predicts the same behavior as for the old-FB condition since the
pre-test procedure is exactly the same. Children – according to our hypothesis – are
fairly sure that the agent is coming back to look for her toy. However, she goes to the
wrong box (A in the original and C in the new-FB condition), which provides children with
a good reason to help her find the toy in box B. The data speak for this explanation much
more strongly than for the one advanced by BCT. Our explanation has potential relevance
for how we should look at infants’ impressive social competence. An important issue
concerns the question of why such young children are so keen to help others. Paulus (2014)
outlined several different classes of models of what motivates pro-social behavior in very
young children. (1) Emotion-sharing-models assume that helping behavior arises as a result
of emotional contagion in combination with the development of self-other-differentiation
and the arising ability to respond to others’ negative emotions in a solution oriented
manner, for example comforting (Hoffman, 2000; Preston & De Waal, 2002). (2) Social-
interaction-models propose that children act pro-socially merely because they enjoy
interacting with other people without a specific motivation to be of benefit to others
(Over & Carpenter, 2009; Reingold & Merikle, 1993). (3) The social-normative-model
emphasizes the role of the social environment and characterizes the emergence of helping
behavior as a process of internalizing the rules of their environment (in support of this
model see e.g., Hammond & Carpendale, 2012). (4) Proponents of goal-alignment-models
(e.g., Kärtner, Keller, & Chaudhary, 2010; Kenward & Gredebäck, 2013) agree upon the idea
of a goal contagion process by which children take over the other’s goal and consequently
act as if it was their own. Goal-alignment-models are the most similar to the (5)
teleological account as both propose that an understanding of goals, and not an
understanding of others’ mental states, is the driving factor for helping. In Perner and
Roessler’s account, however, there is no need for a process of goal contagion because
teleological reasoning is based on objective facts and seeing the possibility of a
desirable state should give anyone reason to make this the goal of their action. Although
these models differ about children’s motivation for engaging in helping behavior, they all
presuppose that children in our study know what the purpose/goal of the other person’s
action is. On all five accounts children need to know this in order to (1) respond
adequately to other’s emotional state, to (2) engage in behavior apt to promote good
interaction, to (3) show that one is willing to help, or to (4) take on the other’s goal.
The central question tested in our new conditions is whether children need a belief-desire
theory to do so, or whether they can do it on the basis of what they observe the agent
doing. This question is most explicitly addressed in teleology which is particularly
explicit that no mental states are needed. This stands in stark contrast to how Tomasello
(2014) describes the cognitive basis of cooperation and helping. Tomasello (2014) argues
that an early inclination for helping stems from a specific human genetic trait, a
cooperative turn in human evolution, which consists of the ability to engage in higher
order mentalizing. For instance in the object choice task, where children or apes are
faced with several up-side down buckets, one of which is baited, when the experimenter
marks or points to one of them, very young children spontaneously look for the bait under
this bucket while chimpanzees need excessive training to learn this. According to
Tomasello (2014, p. 57) “the key point is that the inferences used in cooperative
communication are socially recursive… In the object choice task…, the recipient infers
that the communicator intends that she knows that the food is in that bucket – a socially
recursive inference that great apes apparently do not make.” Our finding put into question
whether such intricate, recursive mentalizing abilities are needed to explain young
children’s cooperative inclinations. But, if not recursive mentalizing, what does give
children this cooperative knack? Roessler and Perner (2015) and Perner and Esken (2015)
have argued that an understanding of the reasons for acting (teleology) provides a more
direct, hence less vulnerable, basis for cooperation than recursive mentalizing. Reasons
for action consist of non-mental, objective facts including value facts, that is, what is
good or bad to have. Our explanation of BCT’s results implements this approach even though
we cannot be sure exactly how the children interpret the interactions. We have mentioned
several possibilities. For instance, we proposed that children notice E2’s interest and
emotional engagement with the toy and therefore see her playing with it as desirable (a
goal). Since it is a ‘good’ thing it provides reason – not just for the agent – for
everyone, who can contribute to help bring it about. So when the agent does something
inadequate for achieving this goal the child teleologist has a natural inclination to
help—without any need to engage in reasoning about each other’s desires and beliefs. Allen
(2015) has pointed out another plausible possibility. The secretive cue in the FB
condition may give children the impression that this is a game of hide and seek, in which
the seeker is to find the hidden target. We know that children at this age tend to help by
directing the seeker to the target. From an adult’s point of view this helping is
counterproductive and misses the point of the game; yet that is what children tend to do
(Gratch, 1964; Theo Wimmer anecdote in Perner, 1991, p. 153). From a teleologist’s point
of view this counterproductive help makes perfect sense. The overall goal, when everybody
is happy, thus a desirable, good state to be in, is for the seeker to find the target. So
the teleologist child chips in to get to that goal by helping the seeker. Our result has
also implications for how we should view other supposed demonstrations of early belief
understanding. Of these – there are many by now – only few, if any, have been replicated
in a strict sense and some, as this journal issue attests, are not easily or perhaps not
at all replicable A recent number of studies report severe replication issues (see e.g.,
Dörrenberg, Liszkowski, & Rakoczy, 2017; Powell, Hobbs, Bardis, & Carey, 2017; Schuwerk,
Priewasser, Sodian, & Perner, 2017; Yott & Poulin-Dubois, 2016). Even the data of our
Study 1 did not reach the same significance criterion (two-sided p-value below .05) as the
original study. But one should not conclude from that that our data provide evidence
against the existence of BCT’s effect, that is, the difference between the two conditions.
To see this we carried out a Bayes analysis which shows a BF = 2.81 in favor of BCT’s
finding, but a BF below 3.0 is regarded as inconclusive evidence (Dienes, 2014; Lee &
Wagenmakers, 2014). Nevertheless, by the sheer weight of numbers of other kinds of
demonstrations, early belief understanding is widely accepted as a fact. For many of the
findings alternative explanations have been proposed (e.g., Apperly & Butterfill, 2009;
Fenici, 2015; Perner & Roessler, 2010; Ruffman 2014; Wellman, 2014, chp 8), but few of the
pithier ones have been tested.5 Peter Carruthers (2013, p. 150), in a recent evaluation of
the evidence, concluded with soothing caution: “…at present we seem warranted in
tentatively endorsing the infant-mindreading hypothesis, based on its record so far,” and
he added wisely: “But if it should turn out that these existing studies cannot be
replicated, or if additional control experiments provide evidence of non-mentalizing
mechanisms underlying the results, then the situation may yet reverse itself.” The present
study heralds this reversal.


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<ART>Hidden hypotheses in ‘hypothesis-free’ genome-wide epigenetic associations
==========================================================================

Authors: Edward D. Barker, Susanna Roberts, Esther Walton
DOI: 10.1016/j.copsyc.2018.07.009
Year: 2019  |  Pages: 13-17
ASJC codes: 3200

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The recent interest in epigenetics within mental health research, from a developmental perspective, stems from the potential of DNA methylation to index both exposure to adversity and vulnerability for mental health problems. Genome-wide technology has facilitated epigenome-wide association studies (EWAS), permitting ‘hypothesis-free’ examinations in relation to adversity and/or mental health problems. In EWAS, rather than focusing on a priori established candidate genes, the genome is screened for DNA methylation, thereby enabling a more comprehensive representation of variation associated with complex disease. Despite their ‘hypothesis-free’ label, however, results of EWAS are in fact conditional on several a priori hypotheses, dictated by the design of EWAS platforms as well as assumptions regarding the relevance of the biological tissue for mental health phenotypes. In this short report, we review three hidden hypotheses — and provide recommendations — that combined will be useful in designing and interpreting EWAS projects.

--------------------------------------------------------------------------------


HIDDEN HYPOTHESIS 1: EWAS COVERAGE IS SUFFICIENT FOR COMPLEX PSYCHIATRIC PROBLEMS
--------------------------------------------------------------------------------

Array-based platforms have become widespread in psychology research, largely due to their
ease of use, relatively high through-put, and well standardised and validated pipelines
for processing, quality control, and analysis techniques. In particular, the Illumina 450k
and EPIC arrays feature 480 000–850 000 probes targeting nearly 99% of RefSeq genes, as
well as a range of other genomic categories, such as CpG islands, shores and shelves,
miRNA promoters and enhancers, where DNAm can be influenced by and/or impact transcription
in distal genomic regions [11••]. Compared with the Ilumina 450k, the newer Illumina EPIC
850k array provides much greater coverage of ENCODE and FANTOM5 enhancers [12••], and
shows higher genetic influence underlying DNAm probes [13]. Nevertheless, these
microarrays are limited in the number of sites they can assess, and thus lack true genome-
wide measurements [14]. Furthermore, during the design process of the 450k and EPIC
arrays, CpG sites were chosen as potentially biologically informative based on
consultation with a consortium of DNA methylation experts [15]. Whilst the coverage of
genes and CpG islands on these microarrays are comprehensive, it does not represent a
complete picture of methylated cytosines across the genome. Selection was, in part, based
on data from a number of phenotypes (some medical in nature such as cancer), and thus is
not specifically targeted to brain-based, stress-related complex mental health phenotypes.
This is an important point: if a sizeable proportion of the CpG sites tested are not
relevant to the phenotype of interest, the likelihood of detecting relevant results is
reduced.

HIDDEN HYPOTHESIS 2: PERIPHERAL TISSUE IS MEANINGFUL FOR MENTAL HEALTH PROBLEM(S)
--------------------------------------------------------------------------------

The second hidden hypothesis relates to the tissue that is used to quantify DNAm. The
majority of mental health research is based on DNAm profiles obtained from peripheral
tissues from living persons, such as blood and saliva. When investigating outcomes such as
conduct disorder or depression, however, the brain is often the main tissue of interest
when it comes to mechanistic interpretations of results [16••]. To this end, research
suggests that the correspondence of methylation profiles from blood and saliva to the
brain is in fact quite limited, but can be higher with cross-tissue genetic influence
[13,17]. This presents a critical disadvantage if the investigator would like to use the
peripheral tissue as a surrogate of the central nervous system (CNS; the brain). One
promising avenue is to establish DNAm as a biomarker for mental illness. A biomarker does
not have to be mechanistic (i.e. CNS surrogate). Indeed, blood-based biomarkers have been
used for diagnostics, predictive risk, disease monitoring and/or treatment response in
cancer, cardiovascular and infectious disease [18,19]. However, even within a biomarker
framework, the assumption is often that distinct peripheral tissues are interchangeable
and equally suited for biomarker detection, when in fact it is highly probable that
peripheral tissues themselves correspond differently to environmental adversity and/or
disease state [14]. For instance, biomarkers for mental health traits (e.g. depression)
may be more detected in blood than saliva, as blood is more central to inflammatory
processes related to stress and disease [16••].

<h>HIDDEN HYPOTHESIS 3: BIOLOGICAL RELEVANCE FOR THE PHENOTYPE OF INTEREST</h>
-----------------------------------------------------------------------

The last hypothesis relates to the assumption that biology can be informative to the
phenotype itself. Focal phenotypes (e.g. oppositional defiant disorder, anxiety) in mental
health research are often complex and multiply determined [20]. The lack of established
robust biomarkers for mental health problems (e.g. [19]) may suggest that some of these
traits might not strongly associate with detectable biological processes. Furthermore,
effect size associations in EWASes are often very small suggesting that — while
significant — distinguishing the importance of DNAm in the aetiology of the mental health
phenotype may prove difficult [21••]. Perhaps unsurprisingly then, most EWAS in mental
health include some form of gene ontology analysis, which queries the role of larger
biological systems based on existing databases [22]. These analyses result in general
statements such as ‘neurodevelopment’ or the ‘immune system’ being involved in the
aetiology of a given phenotype. Whether these broad categories play indeed a substantial
role in the aetiology of the mental health problem is often hard to determine given the
post hoc nature of the interpretation. Relatedly, many EWASes have tried to infer
downstream effects of observed variation in DNAm such as differences in gene expression.
Many of these studies find very little in terms of functional relationships, but a small
number do report downstream biological associations (e.g. [21••]). In general, it has
proven difficult to pinpoint EWAS-related biological relevance of observed DNAm changes,
even if they are in genes which seem ‘plausible’ based on reported functionality and
previous literature.

<h>RECOMMENDATION FOR HIDDEN HYPOTHESIS 1: EWAS COVERAGE</h>
-----------------------------------------------------

An alternative to using arrays with limited coverage is to use next-generation sequencing-
based approaches to interrogate the whole methylome [21••]. However, these methodologies
are high in cost and time intensive. Despite the limitations described above, pragmatic
and strategic study design can maximise utility and interpretation of results of the
Illumina 450k and EPIC arrays. For example, for researchers interested in targeting CpGs
likely to associate with ‘brain-based’ mental illnesses, an a priori set of CpGs (e.g. a
‘systems approach’) could be isolated from the array data, which could still span
thousands of loci. The suggestion is to prioritize CpGs within biological systems that are
known to associate with variation in post-mortem brain samples [23••] or even structural
or functioning brain imaging [24] if this is of primary interest to the investigator. The
second recommendation for optimising the use of EWAS CpGs is to target those probes with
underlying genetic influence — methylation quantitative trait loci (mQTLs). This approach
may have the advantage that cross-tissue concordance (e.g. blood, saliva, post-mortem
brain) appears higher for CpGs that show cross-tissue genetic influence [13]. Another
advantage of mQTLs is that CpGs under considerable genetic influence are less affected by
confounds [11••,13,25]. However, while mQTLs are a worthwhile approach, it is a relatively
new area and at present, there is a small proportion of methylation sites with
consistently reported mQTLs [11••,13]. Furthermore, large-scale and detailed information
on tissue-specific mQTLs is still sparse.

<h>RECOMMENDATION FOR HIDDEN HYPOTHESIS 2: PERIPHERAL TISSUE AND PHENOTYPE</h>
-----------------------------------------------------------------------

One strategy to maximise the interpretability of EWAS projects is to examine DNAm as a
biomarker for mental health problems that have mechanistic underpinning in tissues other
than the brain, such as blood. A wide-range of psychiatric disorders have been associated
with immune function as measured by peripheral inflammation [26]. Furthermore, there is
good evidence from animal studies, and increasing evidence in humans, that peripheral
inflammatory markers can affect brain areas implicated in certain psychiatric disorders
[27]. Consequently, adversity-related immune processes and DNAm may be well measured in
blood samples (see [28••]). For biomarkers to be useful, they must be cost effective,
drawn from accessible tissue and predictive of future risk [29]. Biomarkers for brain-
based disorders (e.g. depression) have proven more difficult to establish [19]. Liu et al.
[30] performed an EWAS on blood tissues across 13 population-based cohorts and reported
that a composite biomarker (consisting of 144 CpGs) discriminated drinkers from non-
drinkers. It was thus suggested that a blood-based DNAm diagnostic test could be
developed. It is important to note, however, that in addition to methodological
considerations [31], the Liu et al. study was cross-sectional, thus it may prove difficult
to use this specific biomarker as a predictor of future alcohol use, as the variation in
DNAm may be the result of chronic drinking (i.e. reverse causality [32]). Importantly,
large-scale meta-analyses based on new and growing consortia (e.g. PACE [33•]) are
beginning to report consistent epigenetic effects on traits such as schizophrenia or
smoking behaviour (e.g. [34,35]) which suggests that we may begin to be able to utilise
this information to further optimize DNAm biomarker approaches.

<h>RECOMMENDATION FOR HIDDEN HYPOTHESIS 3: PHENOTYPE AND BIOLOGY</h>
-------------------------------------------------------------

Several suggestions have been put forward to address the complex nature of the biology
that may underlie mental health problems. Most notably, the Research Domain Criteria
(RDoC) initiative has proposed alternative approaches to study mental illness by
integrating many different levels of information including genetics, neurocircuits and
behaviour [36]. Methylation-based research can be integrated into an RDoC perspective.
Here, researchers could employ a two-stage analysis, first investigating epigenetic
effects on intermediate dimensions of mental health and then, using the results as
biomarkers to query the more complex phenotypes. For, example, if externalising
difficulties (e.g. ADHD, aggression) are the focal phenotype, rather than performing an
EWAS directly on the disorder(s), the researchers could instead, as the first step,
perform an EWAS on brain imaging endophenotypes of the externalising phenotype (e.g.
[24]). In the second step, the results of the EWAS could be used to create poly-epigenetic
genetic biomarker score (e.g. [28••]) to be (potentially) associated with the disorder.
This type of two stage of EWAS may examine the epigenetic changes associated with
antecedents of diagnosable mental health conditions, which would be could be more useful
as a risk biomarker than a biomarker of the actual diagnosis.

<h>CONCLUSION</h>
----------

The recent interest in epigenetics, from a developmental perspective, stems from the
potential of DNA methylation to index both exposure to adversity and vulnerability for
mental health problems [2••]. To this end, there has been substantial activity in
examining EWASes of adversity-related disorders, such as conduct disorder [37] and
psychosis [38]. Of interest, from these EWAS, DNAm in genes that underlie stress response,
neurotransmitter activity and immune regulation have been identified. These preliminary
findings may provide a useful framework for more in-depth investigations — potentially as
CNS surrogates or biomarkers — of the biological pathogenesis of a mental health problem.
However, we argue that understanding hidden hypotheses within the EWAS is an important
first step in interpreting the results in relation to mental health phenotypes.

<h>REFERENCES AND RECOMMENDED READING</h>
----------------------------------

Papers of particular interest, published within the period of review, have been
highlighted as: • of special interest •• of outstanding interest


<h>REFERENCES</h>
----------

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<ART>How anxiety induces verbal hallucinations
=========================================

Authors: Matthew Ratcliffe, Sam Wilkinson
DOI: 10.1016/j.concog.2015.11.009
Year: 2016  |  Pages: 48-58
ASJC codes: 3204, 3205
Keywords: Anticipation, Anxiety, Inner speech, Verbal hallucination

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Verbal hallucinations are often associated with pronounced feelings of anxiety, and it has also been suggested that anxiety somehow triggers them. In this paper, we offer a phenomenological or 'personal-level' account of how it does so. We show how anxious anticipation of one's own thought contents can generate an experience of their being 'alien'. It does so by making an experience of thinking more like one of perceiving, resulting in an unfamiliar kind of intentional state. This accounts for a substantial subset of verbal hallucinations, which are experienced as falling within one's psychological boundaries and lacking in auditory qualities.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In this paper, we offer an account of the relationship between a substantial subset of
verbal hallucinations (VHs) and feelings of anxiety.1 It is widely acknowledged that VHs
are heterogeneous. Variables include volume, auditory quality, number of voices, degree of
personification, emotional tone, thematic content, mode of address (second- or third-
person), level of control over voices, and level of distress associated with them (Larøi,
2006; McCarthy-Jones et al., 2014; Nayani & David, 1996). We focus specifically on VHs
that have repeated insults, threats and terms of abuse as their thematic contents. Many
studies report that the majority of ‘voice hearers’ report such contents, and often only
such contents.2 Although frequently associated with schizophrenia diagnoses, these
experiences also arise in several other psychiatric conditions, including post-traumatic
stress disorder, psychotic depression, bipolar disorder and borderline personality
disorder, as well as in non-clinical subjects (Johns et al., 2014). First-person reports
of abusive, insulting or threatening voices in these populations have much in common
(Aleman & Larøi, 2008, p. 78), and we offer an account of VHs that is consistent with
their diagnostic non-specificity. We propose that certain VHs arise due to pronounced and
pervasive social anxiety, of a kind that is common to several psychiatric conditions. We
begin by presenting the view that anxiety is not merely a consequence of VHs: it both
triggers them and shapes their content. Then we examine a model of how this happens,
according to which VHs result from an anxiety-induced failure to anticipate thoughts. We
argue that lack of anticipation is neither necessary nor sufficient for VHs. Instead, we
introduce the notion of an ‘emotional style’ of anticipation and focus on one such style:
anxious anticipation. Our central claim is that anxious anticipation of one’s own thought
contents generates VHs by making an experience of thinking that p more like one of
perceiving that p.3 We will show how this serves to clarify what Stephens and Graham
(2000) call the “alien quality” of VHs, something that is not always attributable to their
seeming to originate in the external environment or to their having sensory properties
much like those of veridical perceptions. Our account captures those VHs that are
experienced as internal in origin and as lacking in auditory properties. Others, we
concede, require different explanations. We conclude by briefly examining how our
personal-level account ties in with subpersonal theories. Our case throughout is
principally philosophical. We develop a phenomenological account of anxious anticipation,
one that is both independently plausible and compatible with various empirical findings
concerning VHs. However, we also draw upon first-person testimonies, in order to
illustrate and provide further support for some of our claims. The main source of
testimony is an Internet questionnaire study, which we conducted in collaboration with
colleagues.4 Participants were invited to provide open-ended, free-text responses to
questions that included “Please try to describe your voice(s) and/or voice-like
experiences”, “How, if at all, are these experiences different from hearing the voice of
someone who is present in the room?” and “What kinds of moods or emotions are associated
with your voices?” All respondents quoted here had psychiatric diagnoses.5 Our intention
is not to suggest that the phenomenology can simply be ‘read off’ first-person reports,
thus comprising straightforward empirical evidence for our account. Rather, these are
testimonies to be interpreted.6 The account that we offer is not only consistent with
their content but aids in their interpretation, helping to make sense of otherwise
puzzling experiences that people struggle to describe. It is corroborated by its ability
to do so.7

<h>VERBAL HALLUCINATIONS AND ANXIETY</h>
---------------------------------

VHs, especially those with unpleasant contents, are generally accompanied by depression
and anxiety. It is easy to see how such an experience might cause anxious distress.
However, anxiety and depression frequently arise before the onset of VHs, and anxiety is
particularly prevalent among ‘voice-hearers’ in both clinical and non-clinical populations
(Allen et al., 2005; Kuipers et al., 2006; Paulik, Badcock, & Maybery, 2006). It is
important to distinguish two findings: (a) generalised anxiety is present before voices
arise, and (b) there is heightened anxiety immediately before and during the VH
experience. We focus on (b), but will also suggest a role for (a). According to Delespaul,
de Vries, and van Os (2002, p. 97), anxiety is the “most prominent emotion during
hallucinations and reports of anxiety intensity exceeded baseline levels before the first
report of auditory hallucinations”. It has also been hypothesised that increased anxiety
both triggers VHs and shapes their content, although the mechanism remains unclear
(Freeman & Garety, 2003, p. 923). This view is consistent with first-person descriptions
of the emotional states that immediately precede VHs: “It’s worse when I’m stressed,
anxious or scared.” (#3) “When I am feeling anxious they grow stronger. When I am alone as
the day goes on they get stronger.” (#6) “Fear, unsafety, scare, not knowing” (#19)
“Loneliness, depression, anxiety, feeling unloved, deserted, uncared for” (#28) What is
described is not simply ‘anxiety’ but ‘social anxiety’. Hence the individual often
withdraws from others and may complain of feeling socially isolated and estranged
(Hoffman, 2007).8 Romme, Escher, Dillon, Corstens, and Morris (2009) provide fifty
detailed first-person accounts by voice hearers, which include numerous references to
social vulnerability, anxiety, fear, social isolation, shame and feeling lost. Many add
that their feelings of anxiety, depression and estrangement originated in distressing
social relationships and traumatic events, including neglect and abuse during childhood.
All of this is consistent with the prevalence of abusive and insulting voices; the content
of VHs is usually mood-congruent (Larøi, 2006, p. 165). That many VHs arise in a context
of social anxiety and are immediately preceded by heightened anxiety does not, in itself,
imply a causal relationship. However, the fact that treating the anxiety often leads to a
reduction in VH frequency and severity lends further support to the hypothesis that
anxiety is causally implicated in VHs (Kuipers et al., 2006, p. 28). Even so, how anxiety
might cause VHs remains thoroughly unclear. In what follows, we will offer a personal-
level account of how this happens.

<h>ANXIETY AND ANTICIPATION</h>
------------------------

We think that the notion of ‘anticipation’ is central to understanding how anxiety induces
VHs. However, contrary to the received view, we will argue that VHs are not attributable
to a lack of anticipation but to how one anticipates. A recent phenomenological account
that attributes VHs to anxiety and to a consequent lack of anticipation is offered by
Gallagher (2005), who seeks to accommodate both VHs and thought insertion. (He does not
say whether or how the two differ, an issue we will return to later.) We take this account
as a starting point from which to develop our own position. Gallagher’s approach is
premised on the view that acts of thinking incorporate experiences of anticipation. It is
not that one anticipates thinking something before one thinks it. That would fall foul of
an infinite regress objection: anticipating the thought that p is itself a thought with
the content ‘the thought that p’, which would be anticipated by a further thought with the
content ‘the thought that the thought that p’, and so on.9 What one anticipates is less
determinate in content. Gallagher offers the analogy of listening to a melody, where one
might not anticipate hearing a particular note before one hears it, but one has at least
some sense of what will come next, as illustrated by the surprise one feels when a note is
out of tune.10 By analogy, one might anticipate the thematic “gist” of a thought, the
content of which is more determinate (Hoffman, 1986). According to Gallagher, if a thought
were not anticipated at all, it would arrive fully formed, rather than crystallizing out
of something that is congruent with it but less determinate in content. This would amount
to a sense of its coming from elsewhere, like the unanticipated and fully-formed
communications we receive from other people. He further proposes that such experiences
could occur due to “unruly emotions such as anxiety”. In brief, anxiety disrupts
anticipation and, were it to immediately precede a particular thought, that thought would
“appear as if from nowhere”; it would be “sudden and unexpected” (Gallagher, 2005, pp.
194–200). This is consistent with a widespread emphasis in the VH literature on prediction
failure (e.g. Frith, 1992). Of course, the breakdown of a subpersonal mechanism that
predicts (or, more specifically, ‘monitors’) the generation of thoughts is distinct from a
personal-level prediction failure. However, the personal-level correlate of sub-personal
prediction failure is often taken to be an experience of one’s thoughts as unanticipated.
As Fletcher and Frith (2009, p. 56) put it, “an inner voice is unpredictable and therefore
feels alien”.11 However, Gallagher’s account faces a serious problem, as does any other
account that appeals to a lack of conscious anticipation. First of all, it is arguable
that lack of conscious anticipation is not sufficient for VHs. Many thoughts appear to
arise unanticipated, such as a song that suddenly starts ‘playing in one’s head’ or a
seemingly random thought that does not cohere with the gist of one’s thinking and may also
disrupt one’s train of thought. In response, perhaps even these thoughts are anticipated
to at least some degree and therefore differ from VHs. It is difficult to arbitrate
between conflicting phenomenological claims here. But, whatever the case, it can be added
that lack of anticipation is clearly not necessary for VHs. In short, many voice-hearers
do anticipate their voices, to the extent that they may be able to solicit a voice,
dialogue with it and predict the thematic content of what it will ‘say’ next. In fact, it
has been claimed that a majority of voice-hearers are able to converse with their voices
(e.g. Garrett & Silva, 2003, p. 449). In one influential study, 51% reported that they had
at least some control over their voices, 38% that they could initiate a voice, and 21%
that they could stop a voice (Nayani & David, 1996, p. 183). Some also describe a feeling
of ‘personal presence’ preceding a voice. Hence we suggest that the simple contrast
between anticipating and failing to anticipate is an unhelpful one; VHs do not arise due
to lack of anticipation. Indeed, having a thought that is completely unanticipated might
well be a fairly mundane experience, one that does not involve the relevant sense of
externality. Instead, VHs arise when thoughts are anticipated in a distinctive way. All
instances where one anticipates that p can be qualified in terms of the following:
Determinacy of content: p can be more or less specific. Mode of anticipation: p can be
anticipated as certain, uncertain, probable, improbable, doubtful, and so forth. Emotional
style of anticipation: the prospect of p can be the object of a range of different
emotions, such as excitement, curiosity, hope or fear. By appealing to a combination of
[1] and [3], we will argue that VHs arise due to a distinctive emotional style, that of
anxious anticipation. We will assume that the mode of anticipation, [2], is usually that
of certainty or high probability.

<h>ANXIETY AND THE ALIEN QUALITY</h>
-----------------------------

We accept, as a premise, that many emotions either are intentional states or at least
incorporate intentional states: R is afraid of p; S is guilty about q. This is not to
imply that the intentionality of emotion is a matter of cognitive ‘judgment’ or
‘appraisal’ rather than ‘affect’ or ‘feeling’. There are various ways of arguing that some
or all emotional feelings are themselves intentional, and that their objects are not
restricted to one’s own bodily states (see, for example, Goldie, 2000; Prinz, 2004;
Ratcliffe, 2008). We further maintain that types of emotion are not just commonly but
properly associated with only certain other types of intentional state. For instance,
feeling guilty about something is properly associated with remembering it but not with
imagining it or anticipating its occurrence. And fearing something is properly associated
with anticipating its occurrence but not with remembering that it has already occurred.
One might feel guilty about something that has not happened, in a situation where one has
already set the wheels in motion such that it almost certainly will happen. Even so, the
guilt remains past-directed: one feels guilty about p in virtue of the fact that one
remembers doing q, where q is likely to cause p. It is not psychologically impossible to
fear what has already happened or to feel guilty about a merely imagined state of affairs.
Nevertheless, the experience would be a strange one. In the case of guilt, one might then
think ‘I am wrong to feel guilty about this’ or, alternatively, ‘maybe I am not just
imagining doing it; maybe I actually did do it’. When remembering that p is associated
with feeling guilty about p, it is debatable how the two relate. Perhaps there is a
singular kind of intentional state, that of ‘guiltily remembering that p’. Alternatively,
a distinction might be drawn between two distinct and simultaneous intentional states with
the content p. Or it could be that one first remembers p and then feels guilty about p; so
guilt borrows its content from a preceding intentional state. The same applies to fearing
and perceiving that q. However, even if the two experiences are – according to some
criterion – distinct, it is plausible to maintain that they affect each other. Were one to
feel persistent, intense, recalcitrant guilt about something merely imagined, one’s
imagining having done p might take on some of the qualities of memory; p would start to
feel like something one had actually done. More generally, we propose the following: where
‘emotion x with content p’ is properly associated with ‘intentional state y with content
p’ but not with ‘intentional state z with content p’, its association with z can result in
z’s taking on some of the phenomenological characteristics of y. In extreme cases, the
result is a novel kind of experience, one that is of neither y nor z. This, we will argue,
is how anxiety induces VHs. It is not properly associated with one’s own thought contents
and, when it is associated with them, they are experienced as the contents of a
perception-like intentional state that also retains some of the features of thought. Our
proposal requires further clarification. It is commonplace to think something and also
feel anxious about it. Hence one might object that thoughts clearly are proper objects of
anxiety. However, what we are ordinarily anxious about is p, not having the thought that
p. For example, where p is ‘I might lose my job’, I am anxious about actually losing my
job, not about having the thought that I might. Feeling anxious about ‘the thought that p’
is a more unusual experience. But how could this account for VHs? There is a sense in
which anxiety is intrinsically ‘alienating’ or ‘externalising’. It presents its object –
however determinate – as something unpleasant that one is confronted with. The object of
anxiety is something that threatens, something that one feels helpless in the face of. It
is important to distinguish different senses of ‘externality’ here. To say that an object
of anxiety is essentially external is not to insist that it be experienced as physically
external to one’s bodily boundaries. Our own bodily experiences can be objects of anxiety.
A person who fears she has a serious medical condition may become increasingly anxious
about certain persistent bodily sensations. And chronic illness can involve more
widespread feelings of alienation from one’s body. It is encountered in a way that is
strange and previously unfamiliar, as an actual or potential impediment to one’s
activities and an object of anxiety, rather than something in which one has implicit
‘trust’ (Carel, 2013; van den Berg, 1966). Where an object of anxiety is physically
external to oneself, one feels ‘alienated’ from it in a similar way. One could feel
comfortably immersed in or uncomfortably separate from one’s physically external,
interpersonal surroundings. When suffering from pronounced social anxiety, one does not
simply feel physically separate from others. One experiences a different kind of
separation from them; one is estranged from them, threatened by them, vulnerable and
helpless. In this respect, anxiety is comparable to some experiences of pain. Consider an
intense, lingering pain in one’s hand that persists independently of any external
stimulus. The painful hand is not experienced as something ‘external’ to one’s body. But
one feel alienated from it all the same, in the sense that one is confronted by something
unpleasant, something one seeks to avoid but can do nothing about. Hence something can be
experienced as external and alien or, alternatively, as internal and alien. The sense of
alienation that we are concerned with here has nothing to do with perceived physical
location.12 And neither does that which many voice-hearers describe, since the voices are
often reported as internally located, and yet alien. We suggest that certain VHs arise
when one’s own thought contents become objects of anxiety and are thus experienced as
‘alien’. This is consistent with the observation that many voice-hearers dread their
voices and, more specifically, what it is that the voices ‘say’. The distressing content
is something the voice-hearer is confronted with, something she might try unsuccessfully
to resist, to avoid: “it’s mocking me, I hate that one […] I am left in a state of fear
[…]. They don’t sound like me. They are angry most of the time. I don’t like to think of
mean things, I try hard not to, but the more I try not to think the more the voices get
nasty” (#22). Of course, it could be that the person experiences p and is subsequently
anxious about it, due to the unpleasantness of p and also to p’s seeming to originate from
elsewhere. We acknowledge this, but propose that causation goes both ways: anxious
anticipation of content p can also generate an experience of p as alien. To illustrate how
this happens, consider various familiar experiences that involve an indeterminate,
affectively charged thought content coalescing into something more determinate. Take the
realisation that you have left your bag on the train. As you depart from the station, this
might begin as a surge of anxiety, the content of which can be roughly characterised as
‘something is wrong’; ‘I’ve not done something’ or ‘something important is missing’. This
becomes ‘I’ve left something on the train’ and then ‘I’ve left my bag on the train’, after
which the repercussions of what has happened becomes progressively clearer. Indeterminate
content p arises, eliciting anxiety, and one anxiously anticipates the dawning of q, where
q is a more determinate form of p. (The initial experience can also arise when nothing is
wrong, in which case the content sometimes remains indeterminate, and the feeling fades
upon recognition that all is well.) The view that thought contents can increase in
determinacy as they form is consistent with various proposed explanations of VHs. For
instance, Fernyhough (2004) suggests that inner speech is more usually condensed and
fragmented, and that the experience of externality is attributable to its anomalous re-
expansion. And, according to the influential theory proposed by Hoffman (1986, p. 503),
VHs are generated by disruption of a discourse planning process, which involves “abstract
planning representations that are linked to goals and beliefs”. These give one a broad
sense of what is coming next and precede more determinate contents. More generally, the
emphasis that much of the VH literature places on ‘inner speech’ suggests a process of
some kind whereby thoughts are converted into inner speech (Stephens & Graham, 2000, p.
81). The received view is that VHs involve experiencing one’s own ‘inner speech’ as non-
self-produced, rather than one’s thoughts per se, where inner speech is construed as a
medium in which only some of our thoughts appear. Hence thought content could provoke
anxiety, the object of which is the subsequent content of inner speech. For current
purposes, we do not need to endorse a specific theory of what happens or how it happens.
All we need commit ourselves to is the claim that thought content p precedes thought
content q, where q is a more determinate form of p. Now, it could be argued that the
content of the thought remains the same throughout such a process, that it is simply
‘translated’ into inner speech. However, whatever the process we are referring to might
turn out to consist of, we suggest that it does at least involve differing degrees of
content determinacy. That this is so becomes clearer once we emphasise the emotional
content of VHs. Many emotions are intentional states with contents that can be conveyed in
linguistic form. However, even if one were to insist that they incorporate some kind of
‘propositional content’ from the outset, this is not the same as their incorporating inner
speech. It has been argued that spoken language does not just serve to convey pre-formed
emotional states but also to individuate or even partly constitute them, at least in some
instances (e.g. Campbell, 1997; Colombetti, 2009). Amongst other things, language can
gives an emotion a more specific content. Similar points are made by the phenomenologist
Maurice Merleau-Ponty (1962, pp. 177–182), for whom speech increases the determinacy of
thought (and emotion): “the most familiar thing appears indeterminate as long as we have
not recalled its name”; “the clearness of language stands out from an obscure
background”.13 It is informative to revisit Hoffman (1986) in the light of these
reflections. His approach has a cognitive emphasis throughout. The abstract plans and
goals that enable discourse planning have – it appears – a propositional structure,
although their content is less specific than that of inner speech. But consider an example
Hoffman uses to illustrate his point. When asked to describe where she lives, a patient
says the following: Yes, I live in Connecticut. We live in a 50-year-old Tudor house. It’s
a house that’s very much a home…. ah…. I live there with my husband and son. It’s a home
where people are drawn to feel comfortable, walk in, let’s see…. a home that is furnished
comfortably – not expensive – a home that shows very much my personality. (Hoffman, 1986,
p. 506) The overall theme that constitutes a sense of ‘where things are heading’ is a
consistently emotional one.14 Utterances are not just ‘mood-congruent’; what we have is
the articulation of an emotion or mood, something that renders its content increasingly
specific. Now, let us assume that ‘inner speech’ can play a similar role to spoken
language. Thus, in the case of an abusive ‘voice’, there is an unpleasant emotional
content p, which provokes anxious anticipation of a more determinate linguistic content q,
one that is elicited by p and consistent with p. Anxiety is intrinsically alienating and
so its object, the thought that q, is experienced as alien, as something unpleasant that
one faces and is unable to avoid. Whatever forms of anticipation our thinking more usually
involves, anxious anticipation of thought content is not one of them. That style of
anticipation is more typical of certain affectively charged perceptual experiences. So an
unfamiliar, perception-like experience of thought content arises. It might be objected
that the thought content ‘I’ve left my bag on the train’ is not experienced as alien and
that the process sketched here therefore fails to account for the ‘alien quality’ of VHs.
But there is a crucial difference between the two. In the train case, one is anxious about
the fact that one has left one’s bag on the train, not about the thought content ‘I’ve
left my bag on the train’. However, in the case of a VH with the content ‘you’re a
worthless piece of filth’, the thought content is itself an object of anxiety. The way it
is anticipated as it coalesces thus renders it alien, something unpleasant before which
one feels helpless. Hence an emphasis on lack of anticipation is misleading.15 To revisit
the melody analogy, consider listening to a piece of music that involves a build-up of
tension (an opera by Wagner, perhaps). One senses that something intrusive will blast in;
it is on its way. And yet, when it arrives and conforms to the indeterminate expectation
one had of it, it is still encountered as disruptive, as arising from elsewhere, set apart
from the music that preceded it.

<h>INTERPRETING FIRST-PERSON ACCOUNTS</h>
----------------------------------

The approach we have outlined is consistent with empirical findings concerning (i) the
thematic content of many VHs, (ii) the prevalence of anxiety, and (iii) the occurrence of
similar kinds of VH experience in several psychiatric conditions and in non-clinical
populations. In addition, it is consistent with many first-person testimonies and serves
to further illuminate those testimonies. VH contents are sometimes explicitly described as
linguistic manifestations of negative, self-directed emotional appraisals that are
themselves sources of anxiety. For example: “It’s hard to describe how I could ‘hear’ a
voice that wasn’t auditory; but the words used and the emotions they contained (hatred and
disgust) were completely clear, distinct and unmistakeable, maybe even more so that if I
had heard them aurally. [ …]. I heard the voices of demons screaming at me, telling that I
was damned, that God hated me, and that I was going to hell”. (#9) This person further
describes how the contents of his VHs “reflected all the judgmental attitudes I had heard
from my family and church”. The emotional judgments are themselves feared; they are met
with “anxiety/panic and incapacitating depression” (#9). Another questionnaire respondent
remarks, “I hate everything about myself. [ …] I hear a voice that confirms everything I
think about myself and sometimes it feels as if it is the only one that will tell me the
real truth about myself”. She adds, “I can never concentrate on anything but how I am
feeling and the voice I hear”. Thus, there is a combination of distressing, self-directed
emotional appraisals and heightened attentiveness towards them; she waits for them to
arrive.16 The content of her ‘voice’ is specifically associated with that of negative,
self-directed emotions: “I took an anti-psychotic to stop the voice and it helped a bit as
I don’t have something that seems so real confirming my feelings so outrightly”17.
Reference to a voice ‘confirming’ one’s feelings indicates that it not only expresses pre-
formed feelings but also adds to them in some way. This is plausibly construed in terms of
its giving them a more determinate content, one that is an object of anxious anticipation.
Feelings of inadequacy and the like are at first indeterminate, but can take on a more
determinate linguistic guise that ‘confirms’ the emotional appraisal it is congruent with
and out of which it arises. Some first-person accounts further indicate a process of
exactly the kind that we have described. An experience induces anxious anticipation, which
then proceeds to shape the experience in question: “Due to the murmuring voice experiences
being so distressing with each successive occurrence however, I grew to dread ever more
either whenever another experience would appear to possibly be forthcoming or, once in the
midst of an actual ongoing experience, what would come next; waiting for the next shoe to
drop.” (#31) “It’s very difficult to describe the experience. Words seem to come into my
mind from another source than through my own conscious effort. I find myself straining
sometimes to make out the word or words, and my own anxiety about what I hear or many have
heard makes it a fearful experience. I seem pulled into the experience and fear itself may
shape some of the words I hear.” (#32) “I have come to recognise the voices as expressions
of anxiety, perhaps even a recognition of a fear I have about myself that I am not
prepared to entertain as being part of my personality.” (#34) There is anxious
anticipation of what is coming next, rather than a lack of conscious anticipation (#31),
which affects what is then experienced (#32). And, as indicated by (#34), anxiety about
one’s own thought contents is also associated with a sense of their being alien; the
anxiety is constitutive of one’s ‘disowning’ something distressing. One might object that
inner speech does not have auditory properties, regardless of whether or not its content
is experienced as alien, whereas VHs are auditory experiences (e.g. Wu, 2012).
Furthermore, VHs are often experienced as originating in the external environment. Nothing
we have said explains their auditory properties or the fact that they are physically
‘external’, as well as ‘alien’ in our sense. We acknowledge that some VH experiences most
likely conform to orthodox definitions of hallucination, according to which verbal
hallucinations are auditory experiences that arise in the absence of appropriate external
stimuli (e.g. Frith, 1992, p. 68; Halligan & Marshall, 1996, p. 242). Several accounts of
VHs emphasise such an experience (e.g. Garrett & Silva, 2003, p. 445; Leudar et al., 1997,
p. 888; Wu, 2012, p. 90). However, others suggest that VHs are generally lacking in
auditory qualities (e.g. Moritz & Larøi, 2008; Stephens & Graham, 2000, p. 104). As Frith
(1992, p. 73) suggests, a VH can involve something more abstract than hearing a voice, “an
experience of receiving a communication without any sensory component”. The two views can
be reconciled by acknowledging that VHs come in both guises. David (1994) states that most
but not all subjects experience voices as arising “inside the head”, while Nayani and
David (1996) report that 49% of their subjects heard voices through their ears, 38%
internally and 12% in both ways. Leudar et al. (1997, p. 889) state that 71% of their
subjects heard only internal voices, 18% heard voices “through their ears”, and 11% heard
both. Internal VHs are not always described as bereft of auditory properties but, whatever
auditory properties they might have, there is a substantial phenomenological difference
between these two types. This is readily apparent when we turn to first-person
descriptions by individuals who experience both: “The voice inside my head sounds nothing
like a real person talking to me, but rather like another person’s thoughts in my head.
The other voices are to me indistinguishable from actual people talking in the same room
as me.” (#1) “There are two kinds – one indistinguishable from actual voices or noises (I
hear them like physical noises, and only the point of origin (for voices) or checking with
other people who are present (for sounds) lets me know when they aren’t actually real. The
second is like hearing someone else’s voice in my head, generally saying something that
doesn’t ‘sound’ like my own thoughts or interior monologue.” (#17) Hence we suggest that
it is fruitful to draw a broad, over-arching distinction between two subsets of VHs: (i)
those that are experienced as external in origin and auditory in character; (ii) those
that are experienced as internal in origin and lacking in auditory properties. Our account
applies specifically to (ii). One might worry that what we have proposed conflicts with
the observation that even internal VHs are usually described in terms of audition, rather
than other kinds of perceptual experience. However, information of the relevant kind is
usually received through auditory channels, at least in the absence of visual stimuli such
as reading materials. So, even when it is bereft of the relevant sensory qualities, it
lends itself to description in those terms. Furthermore, talk of hearing is often
qualified. For example, references to the ‘sound’ of a voice and to ‘hearing’ might appear
in scare quotes. Some of these internal ‘voices’ may not have any auditory qualities at
all, a view that is consistent with reports of VHs in congenitally deaf subjects (e.g.
Aleman & Larøi, 2008, pp. 48–9). Nevertheless, it is plausible to suggest that some of
them do have audition-like properties. The claim that inner speech is sometimes or always
wholly bereft of auditory properties is by no means uncontroversial. For example, Hoffman
(1986) takes it to involve ‘auditory imagery’, and there may be considerable interpersonal
variation too.

<h>AN UNFAMILIAR KIND OF INTENTIONAL STATE</h>
---------------------------------------

Even though anxiety about one’s own thought contents is unusual, one might object that it
is plausibly more widespread than the kind of VH experience we seek to account for. There
could well be many people with disruptive, intrusive and self-directed thought contents
that provoke anxiety but are not experienced as VHs. However, up to this point we have
only emphasised one of two roles played by social anxiety, that of an immediate trigger
for VHs. Generalised anxiety and social isolation are also disposing factors (which is not
to rule out others). One experiences heightened anxiety about something specific in a
context of already feeling more generally anxious and estranged. Depression and anxiety
are both associated with what we might call ‘diminished agency’. One’s personal and
interpersonal surroundings are globally oppressive and no longer invite effortless
responses to meaningful possibilities in the way they once did. So there is a pervasive
sense of being incapable of action, and even thoughts may seem sluggish, effortful, bereft
of the kind of active anticipation that is involved when one is drawn into and absorbed in
a theme (Benson, Gibson, & Brand, 2013; Ratcliffe, 2013). If the person feels more
generally passive, helpless and incapable in the face of a threating world, the
phenomenological distance between actively initiating something and receiving it from
elsewhere may already be lessened. This could render her more vulnerable to a blurring of
the phenomenological boundary between thinking that p and perceiving that p. This is
consistent with the observation that voices are generally “perceived as being
extraordinarily powerful” (Birchwood, Meaden, Trower, Gilbert, & Plaistow, 2000; Chadwick
& Birchwood, 1994, p.191). The individual’s relationship with her voices corresponds to
her relationship with the social world; she feels passive and vulnerable in the face of
interpersonal threat. There are also reports of inner dialogue becoming “more pronounced”
before the onset of voices in some cases, with “subtle pre-psychotic distortions of the
stream of consciousness – such as abnormal sonorization of inner dialogue and/or
perceptualization of thought” (Raballo & Larøi, 2011, p. 163). This suggests a more
general blurring of the experienced difference between kinds of intentional state, which
would render one more prone to experiencing anxiety-inducing thought contents as alien. It
also points to a gradual process, whereby the person becomes anxious about certain
thematic contents, with raised anxiety leading to their progressive alienation, sometimes
culminating in an experience of the voices as “almost personified” (Raballo & Larøi, 2011,
p. 165).18 What we have outlined here also complements an approach to delusions proposed
by Currie (2000) and Currie and Jureidini (2001), according to which a delusion is not a
recalcitrant false belief but an imagining that is mistaken for a belief. In the case of
VHs, there is similarly confusion between two kinds of intentional state: perceiving and
thinking. Currie and Jureidini (2001) construe this as an epistemic problem, where one
actually imagines something but mistakes one’s imagining that p for the belief that p.
However, they later reject a categorical distinction between imagination and belief,
allowing for the possibility of intentional states that fall somewhere between the two
(Currie & Jureidini, 2004).19 Whether or not our account of the blurring between thought
and perception is an epistemic or constitutive one depends on which definitions of
‘perception’ and ‘thought’ one is working with. Our emphasis is on the phenomenology of
VHs. We have suggested that an experience of perceiving differs from one of thinking, and
that anxious anticipation can lead to a perception-like experience of thought content.20
We grant that non-phenomenological conceptions of thought and perception could be adopted,
which would re-cast the situation in epistemic terms. For example, if perception is
defined as necessarily involving receipt of information from a sensory source, then a VH
of the kind we have described is non-perceptual, pure and simple, and any first-person
impression to the contrary is mistaken. However, in purely phenomenological terms, one
does not mistake an experience of type x for one of type y; one has an intentional state
that is neither x nor y: “it definitely sounds like it is from inside my head. It’s at
some kind of border between thinking and hearing” (#18). The view that VHs involve an
unfamiliar kind of experience, one that falls between thinking and perceiving, is
supported by the observation that people frequently struggle to describe them. VHs are
often described as ‘almost like’ something; it is ‘as though’ something were the case. For
example, they might be described as ‘like’ telepathy: “The commentary and the violent
voices I heard as though someone was talking to me inside my brain, but not my own
thoughts. Almost like how telepathy would sound if it were real. I don’t know how else to
explain it.” (#4) “.. there are things I ‘hear’ that aren’t as much like truly hearing a
voice or voices. [ ….] Instead, these are more like telepathy or hearing without hearing
exactly, but knowing that content has been exchanged and feeling that happen.” (#7) Given
this, it is interesting to consider the possibility that certain kinds of VHs and what is
called ‘thought insertion’ – which are traditionally treated as separate kinds of symptom
– are in fact the same phenomenon (Ratcliffe and Wilkinson, 2015). It could be that there
are varying degrees of ‘perceptualisation’, which lend themselves to description in terms
of either VH or thought insertion. And it could also be that much the same experiences are
described in different ways. A quasi-perceptual experience of thought content could be
related in terms of (a) a perception with an anomalous content or (b) a thought content
that is not one’s own.21 Acknowledging that VHs involve an unfamiliar kind of intentional
state also casts light on the phenomenon of ‘double bookkeeping’. Many who voice
delusional beliefs and describe hallucinatory experiences also speak and act in ways that
distinguish their delusions from other beliefs and their hallucinations from veridical
perceptions, thus suggesting different kinds of experience. Sass (1994, p. 3) describes
this as follows: Many schizophrenic patients seem to experience their delusions and
hallucinations as having a special quality or feel that sets these apart from their ‘real’
beliefs and perceptions. [ …] Indeed, such patients often seem to have a surprising, and
rather disconcerting, kind of insight into their own condition. With specific reference to
VHs, van den van den Berg (1982, p. 105) observes that voices are often given a “special
name” to set them apart from perceptual experiences, due to their having a “recognizable
character of their own which distinguishes them from perception and also from
imagination”. This is complemented by our view that VHs are not quite like perceptions or
thoughts, a view that also explains why the majority of clinical and non-clinical voice-
hearers are readily able to distinguish their ‘voices’ from veridical auditory perceptions
(Moritz & Larøi, 2008).

<h>VARIETIES OF VH</h>
---------------

As we have emphasised, our account is intended to accommodate only some of those
experiences that are labelled as ‘VHs’. Furthermore, it could be that ‘internal VHs that
are bereft of at least some auditory properties’ are themselves heterogeneous. While we
have emphasised anxious anticipation of inner speech, Michie, Badcock, Waters, and Maybery
(2005) propose that VHs involve memory intrusions. Now, McCarthy-Jones et al. (2014)
report that only 39% of their subjects acknowledged VH contents resembling memories and
fewer still said that their VHs were memories. Even so, it could be that some internal VHs
are like this. Indeed, internal VHs could encompass experiences of inner speech, memories
and imaginings, as well as some contents that blend memories with imaginings. And the
predominance of one form or another may reflect individual differences, different life
histories and different diagnostic categories. For instance, we might find a predominance
of alienated memory contents in cases where there is past trauma. However, inner speech
VHs with less pronounced auditory qualities may be more common in schizophrenia, thus
accounting for more frequent reports of ‘thought insertion’ in schizophrenia. However,
this is not a problem for our account, given that what we have proposed need not be
specific to the experienced boundaries between perception and inner speech. The alienating
role of anxiety could be easily extended to the anticipation of distressing memories and
imaginings, both of which may have more pronounced auditory qualities. It is also worth
keeping in mind that ‘social anxiety’ is not a singular phenomenon but something that
would benefit from further analysis. Some first-person accounts emphasise shame and
humiliation, others interpersonal threat and helplessness, and others guilt and self-hate.
Different variants of social anxiety are likely to be associated with different thematic
contents, given that VH contents are mood-congruent. Again, some of these differences may
correspond to different psychiatric categories. For example, a person with a diagnosis of
psychotic depression might hear voices that mock her and criticise her for her failures
(Larøi, 2006). Hence the account we have offered has the potential to accommodate
considerable phenomenological diversity, and to distinguish VH characteristics that are
more typical of one or another diagnosis. What about external VHs? If first-person
accounts are to be taken at face value, they are sometimes much like veridical auditory
perceptions. Hence they are unlike what we have described and also arise in a different
way. However, social anxiety is implicated here too. Extreme social anxiety could dispose
a person towards the anticipation of interpersonal communications with negative, self-
directed contents. Delespaul, deVries and Van Os (2002) found that VHs are most likely to
occur either when one is in the presence of lots of people or when one is alone. Building
on this, Dodgson and Gordon (2009) propose, on the basis of clinical case-studies, a kind
of VH called a ‘hypervigilance hallucination’ which occurs especially in ‘noisy’
environments where stimuli are susceptible to multiple interpretations. This, they
suggest, accounts for a “substantial subset of externally located voices”.22 The existence
of hypervigilance hallucinations as a separate subtype was subsequently supported by
Garwood et al. (2013) who, based on a cluster analysis, showed that VHs tend to occur when
(i) attention is directed inward in quiet contexts, and (ii) attention is directed outward
in noisy contexts. This finding fits nicely with our account. In both internal (inner
speech or memory-based) VHs and external, hypervigilance VHs, anxious anticipation shapes
and distorts the experience. In instances of anxious hypervigilance, out of external
stimuli (such as a ticking clock or the muffled sound of neighbours talking) will emerge
the experience of a voice telling the subject exactly what the subject is afraid of
hearing. Thus anxiety could also be the underlying cause of at least some external VHs,
even though internal and external VHs are generated in different ways. Our account also
allows for in-between cases. For example, a perceptual stimulus might trigger an
imagining, which is then experienced as an object of pronounced anxiety, and therefore as
alien and perception-like. The same applies to inner speech: an external stimulus with
auditory qualities could trigger an increasingly determinate linguistic content that is
experienced as alien. Unlike an internal VH, this would seem to originate in the external
environment, given its association with a perceived environmental cause. In such a case,
auditory properties might also be ‘interpreted’ in such a way that they are consistent
with the content of the communication. Even so, our emphasis on anxiety cannot do justice
to all VH experiences. Some VHs do not have distressing contents (Copolov, Mackinnon, &
Trauer, 2004). Indeed, some voice-hearers obtain consolation, support and/or guidance from
their voices. This applies to many of those VHs that arise in the context of grief. In a
study of nearly 300 widows and widowers in Wales, Rees (1971) found that nearly half had
hallucinations of the deceased spouse, sometimes lasting many years. Feelings of presence
were most common, but VHs were also reported by 13%. Most of these people found their
hallucinations comforting and helpful. We do not claim to have dealt with such cases, and
we concede that the phenomenology of grief – in all its complexity – needs to be addressed
separately. The same goes for various other kinds of VH experience. However, it may be
possible to extend our general approach to VHs without the specific emphasis on anxiety.
We have not claimed that anxious anticipation is the only way of anticipating one’s own
thought contents that blurs the boundaries between intentional state types. A further
limitation of our account is that we have addressed only the ‘phenomenological’ or
‘personal’ level of description and have not postulated any associated mechanisms. What we
have supplied here can, however, operate as an explanandum for neurobiological approaches.
If one wants to provide a subpersonal account of how x is generated, where x is
phenomenological in character, it helps to have a good account of what x consists of. That
is what we have tried to provide, and there are clearly implications for accounts of the
subpersonal mechanisms involved in VHs. According to a popular family of approaches, our
nervous systems distinguish endogenous from externally produced stimuli through a process
of self-monitoring. In particular, when a motor command is sent, a copy of that motor
command is used to predict the sensory consequences of the action. When the actual sensory
consequences match the predicted sensory consequences, the nervous system ‘judges’ that it
is self-produced and sensory attenuation occurs (as if it were ‘saying’: ‘don’t worry
about this: it’s only you’). When monitoring goes awry, sensory attenuation fails to occur
and endogenous stimuli are erroneously attributed to an external cause (e.g. Campbell,
1999; Frith, 1992; Frith, Blakemore, & Wolpert, 2000; Jones & Fernyhough, 2007; Seal,
Aleman, & McGuire, 2004). It is not clear how anxiety might fit into a self-monitoring
story, as a cause rather than an effect of VHs. Furthermore, our anxiety-based account
does not appeal to motor processes. Indeed, one might sense a tension between our account
and the self-monitoring approaches, given that we emphasise a change in the style of
anticipation, rather than a lack of anticipation. Of course, personal- and subpersonal-
level explanations are to be distinguished from each other. And it could be that our
anticipating p in style x rather than y involves the breakdown of certain subpersonal
prediction mechanisms, while others continue to operate or perhaps operate differently.
But, until a more specific account along such lines is developed, the claim that personal
level anticipation in style x rather than y involves a breakdown of subpersonal prediction
lacks explanatory power.23

<h>CONCLUSION</h>
----------

We have argued that anxiety induces VHs in the following way: anxious anticipation of
thought contents as they become increasingly determinate results in a quasi-perceptual
experience of thought content. This is because anxiety is not properly associated with
‘the thought that p’; anxiety alienates us from its objects in a way that we are not
ordinarily alienated from our own thought contents. Insofar as the person faces something
that she seeks to avoid and is confronted by something that she feels helpless to resist,
the resulting experience resembles an affectively charged perception more so than a
mundane episode of thought. This account fits in well with subjective reports to the
effect that anxiety triggers or aggravates VHs, that the voices confirm negative self-
evaluations, and that the voices fall somewhere in between experiences of hearing and
thinking. However, we also made clear that our account applies only to a subset of VHs,
those with negative content, and most clearly to those that are experienced as internal in
origin and lacking in auditory qualities.


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<ART>How much does emotional valence of action outcomes affect temporal binding?
===========================================================================

Authors: Joshua Moreton, Mitchell J. Callan, Gethin Hughes
DOI: 10.1016/j.concog.2016.12.008
Year: 2017  |  Pages: 25-34
ASJC codes: 3204, 3205
Keywords: Emotional expressions, Emotional valence, Replication, Self-serving bias, Temporal binding, Time interval estimation, Voluntary action

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Temporal binding refers to the compression of the perceived time interval between voluntary actions and their sensory consequences. Research suggests that the emotional content of an action outcome can modulate the effects of temporal binding. We attempted to conceptually replicate these findings using a time interval estimation task and different emotionally-valenced action outcomes (Experiments 1 and 2) than used in previous research. Contrary to previous findings, we found no evidence that temporal binding was affected by the emotional valence of action outcomes. After validating our stimuli for equivalence of perceived emotional valence and arousal (Experiment 3), in Experiment 4 we directly replicated Yoshie and Haggard's (2013) original experiment using sound vocalizations as action outcomes and failed to detect a significant effect of emotion on temporal binding. These studies suggest that the emotional valence of action outcomes exerts little influence on temporal binding. The potential implications of these findings are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Temporal binding refers to the compression of the perceived time interval between
voluntary actions and their sensory consequences (Haggard, Clark, & Kalogeras, 2002). More
specifically, an outcome (e.g., a tone) is experienced earlier when it is triggered by a
voluntary action compared to when it occurs in isolation or is triggered by an involuntary
movement. Similarly, actions that trigger an event are experienced later than actions with
no discernible outcome (see Moore & Obhi, 2012, for a review). For example, Haggard et al.
(2002) examined judgements of the onset time of both a voluntary action and a resulting
tone using the Libet clock method (Libet, Gleason, Wright, & Pearl, 1983), where one
estimates the time of onset of an action or outcome via the position of a rotating clock-
hand around a clock-face. These judgements were compared to those made when only the
action was performed (i.e., with no outcome) and when a sound was heard in isolation
(i.e., without a prior cause). Haggard et al. found that the perceived time of an action
was later when the action produced a tone compared to when there was no outcome. Moreover,
the perceived time of a sound was earlier when the sound had been produced by an action
compared to when it was heard in isolation. In other words, temporal binding means that
the time interval between an action and its outcome becomes perceptually compressed when
we think there is a causal relationship between action and outcome. Temporal binding has
also been observed with methods other than the Libet task, such as verbal or numerical
estimates of the interval between action and outcome (Buehner & Humphreys, 2009; Humphreys
& Buehner, 2010). Temporal binding has been shown to occur for both self- and other-
generated actions (Moore, Teufel, Subramaniam, Davis, & Fletcher, 2013; Poonian &
Cunnington, 2013) and may be a general phenomenon linking causally related events
(Buehner, 2012). To date, researchers have mostly investigated the conditions required for
temporal binding and the mechanisms that underpin it (Hughes, Desantis, & Waszak, 2013),
and they have done so using experimental tasks that often involve basic actions, such as a
button press, producing sensory feedback, such as an auditory tone (David, Newen, &
Vogeley, 2008; Sato & Yasuda, 2005). These temporal binding tasks arguably lack any real-
world complexity with which humans perform goal-directed actions to produce meaningful
outcomes in everyday life (Moretto, Walsh, & Haggard, 2011). Researchers have started to
examine the generalizability of temporal binding effects to stimuli beyond simple and
arbitrary outcomes, such as priming social cues (Aarts et al., 2012), authorship of action
cues (Desantis, Weiss, Schütz-Bosbach, & Waszak, 2012), leader-follower cues (Pfister,
Obhi, Rieger, & Wenke, 2015) and economic and pain cues (Caspar, Christensen, Cleeremans,
& Haggard, 2016). For example, Aarts et al. (2012) found that, when primed with a positive
picture (taken from the International Affective Picture System; Lang, Bradley, & Cuthbert,
1999) that indicated a reward, temporal binding during the Libet clock task increased
compared to neutral primes. Takahata et al. (2012) trained participants to associate two
tones with either financial gain or loss. Using the Libet task, they found that the
temporal interval between judgements of onsets for actions and outcomes of financial loss
was significantly larger than for judgements of financial gain. In other words, negative
outcomes reduced the effect of temporal binding. This points towards the possibility that
the effect of valence on temporal binding might be driven by self-serving biases, where
one is more inclined to associate positive events with the self compared to negative
events (Mezulis, Abramson, Hyde, & Hankin, 2004; Miller & Ross, 1975). Yoshie and Haggard
(2013) directly tested this idea by investigating whether temporal binding differed
between outcomes that varied in terms of their intrinsic emotionality. They asked
participants to make voluntary actions (a key-press) that produced auditory sounds that
were either of positive or negative emotional vocalizations (e.g., laughter or disgust).
Participants made temporal estimations of their actions and the ensuing sound via the
Libet clock method. They found that positive sounds produced shorter estimations of onset-
time between the action and sound compared to negative sounds (Experiment 1), with this
effect being mostly driven by decreased binding to negative outcomes (Experiment 2).
Yoshie and Haggard’s (2013) research provided promising evidence that negative emotional
outcomes reduce temporal binding, which occurs presumably because people are less inclined
to attribute negative outcomes to themselves. However, despite the potential importance of
Yoshie and Haggard’s (2013) findings, they have yet to be replicated using other temporal
binding tasks and different emotionally-valenced action outcomes. Thus, answering
Christensen, Yoshie, Di Costa, and Haggard’s (2016) call for more research exploring the
emotional modulation of temporal binding using alternative methods, the goal of the
current research was to conceptually replicate Yoshie and Haggard’s (2013) temporal
binding effects using an interval estimation procedure (vs. the Libet task; Moore & Obhi,
2012) and images of faces conveying positive and negative emotions (vs. emotional
vocalizations; experiments 1 and 2). Moreover, we conducted a separate study to validate
the perceived valence of the face stimuli we used in Experiments 1 and 2 (Experiment 3),
and we conducted a highly-powered direct replication of Yoshie and Haggard’s first
experiment (Experiment 4). On the basis of Yoshie and Haggard’s findings, we expected that
temporal binding would be smaller for negative outcomes (faces or vocalizations conveying
negative emotions) than for positive outcomes (faces or vocalizations conveying positive
emotions).

<h>EXPERIMENT 1</h>
------------

We used an interval estimation procedure to gauge temporal binding (Ebert & Wegner, 2010;
Engbert, Wohlschläger, & Haggard, 2008; Moore, Wegner, & Haggard, 2009). In this
procedure, participants are asked to judge the time interval between an action and its
sensory outcome (e.g., a button press and a sound). Using this procedure, Engbert et al.
(2008) found that the interval between voluntary actions and visual, auditory, and somatic
outcomes were compressed compared to the interval between passive actions and similar
outcomes. For our task, participants were asked to press the space bar, which was followed
by emotionally valenced action-outcomes—namely, emoticons depicting positive, neutral, or
negative emotions (see Fig. 1). Emoticons are prevalent throughout modern technological
communication, and frequently used to convey emotion (Derks, Bos, & Von Grumbkow, 2008;
Hudson et al., 2015). Research has shown that emoticons elicit similar cortical responses
to real faces (Churches, Nicholls, Thiessen, Kohler, & Keage, 2014) and that emotions
conveyed in emoticons are subject to similar behavioural biases (Öhman, Lundqvist, &
Esteves, 2001) and neural processing disruptions (Jolij & Lamme, 2005) as real faces.

        <hss>Participants</hss>

        We recruited 80 native English-speaking participants (51 males, Mage = 33.91,
        SDage = 11.27) through prolific.ac, an online crowdsourcing platform. Participants
        received monetary compensation. We screened participants for the following
        inclusion criteria: an approval rating of above 90% on prolific.ac (based on prior
        experiment performance/approval scores) and aged between 18 and 65. The required
        sample size was fixed ahead of data collection, and a power analysis showed we had
        90% power to detect a small effect (Cohen’s f = 0.10) of emotional valence on
        temporal binding (α = 0.05).

        <hss>Materials and procedures</hss>

        Experiment 1 consisted of 100 trials: 10 practice and 90 experimental trials. We
        used an interval estimation procedure to measure temporal binding (see Moore &
        Obhi, 2012). For each trial, participants saw a fixation cross on the screen, and
        in their own time, pressed the spacebar. In the practice block participant actions
        produced a neutral stimulus, which was a green circle with a diameter equal to the
        emoticon images. During practice trials, the green circle appeared after a
        randomly selected time interval from either 0 ms or a multiple of 100 ms up to 900
        ms. We used all intervals in the practice block, to encourage participants to
        expect the full range of durations in the experimental block. During the practice
        block, feedback was provided to participants after they made their time
        estimations. Feedback consisted of both the participant’s estimated time and the
        actual time of stimulus onset to enhance familiarity with estimating time in
        milliseconds. In the experimental condition, an emoticon appeared after either
        100, 400 or 700 ms (Moore et al., 2009), which remained on the screen for a
        further 400 ms. We varied the delay intervals to increase participants’
        uncertainty regarding the interval between action and outcome to allow for
        variation in judgement times (cf. Ebert & Wegner, 2010). The emotional expressions
        of the emoticons were manipulated by orienting the lines representing the mouth:
        curved upwards for positive, curved downwards for negative, and a straight line
        for neutral. The emoticons were genderless, varied only in the shape of the mouth,
        and were presented on a white background in the center of the screen (see Fig. 1).
        Participants underwent two blocks of 45 trials, allowing for 30 presentations of
        each emoticon image in total. Participants were instructed that they would not
        receive feedback for their time estimations during the experimental trials. A
        schematic display of the sequence of trial events is shown in Fig. 2. Both the
        time intervals and emoticons (either positive, negative or neutral) were pseudo-
        randomised across trials, such that there was the same number of trials in each
        condition at each time interval. A blank screen then followed the emoticon for 400
        ms, replaced by a horizontal time estimation scale in the center of the screen
        (see Fig. 3). The scale ranged from 0-1000 ms, with demarcation lines every 100
        ms. Participants were instructed to scroll the slider along the bar to the time
        that they believed it took the image to appear since their action (in multiples of
        100 ms). Once selected, participants confirmed their selections by clicking on a
        ‘finish’ button, and proceeded to the next trial.

<hs>  Results</hs>
  ~~~~~~~

Participants’ mean time estimations for each of the three onset times (100, 400 and 700
ms) and the three emoticons (positive, neutral and negative) were subjected to a 3
(emotional valence: positive, neutral, and negative) × 3 (temporal delay: 100, 400 and 700
ms) fully within-subjects ANOVA (see Fig. 4). Analysis revealed a significant main effect
of Temporal Delay, F(2, 158) = 56.54, p < 0.001, ηp2 = 0.77, showing that even under less
controlled experimental contexts (i.e., within an online testing platform), participants
perceived distinct time intervals corresponding to their actual length (see Dewey &
Knoblich, 2014, for comparable findings within a laboratory context). There was no
statistically significant effect of emotional valence on time estimations, F(2, 158) =
0.22, p = 0.80, ηp2 = 0.003, nor was there an interaction between temporal delay and
emotion, F(4, 316) = 1.47, p = 0.21, ηp2 = 0.018.

<hs>  Discussion</hs>
  ~~~~~~~~~~

In Experiment 1, the emotional valence of action outcomes did not affect temporal binding.
One potential limitation of Experiment 1 is that although previous research has shown that
emoticons can have the same affective consequences as real faces do (Öhman et al., 2001),
the emoticons we used might not have elicited enough of an emotional response to modulate
temporal binding. Thus, rather than using emoticons for action outcomes, in Experiment 2
we replicated our Experiment 1 procedure using images of real human faces expressing
either negative or positive emotions.

<h>EXPERIMENT 2</h>
------------

In Experiment 2, we used real-face images as the outcomes to participants’ actions. Real
face images have been well-documented to elicit electrocortical responses, and emotional
expressions are typically rated along the dimensions of valence and arousal: Smith,
Weinberg, Moran, and Hajcak (2013), using the NimStim collection of face-images (NimStim,
Tottenham et al., 2009), found that emotional expressions (e.g., happy, fearful, sad),
elicited greater cortical responses than neutral face images. Generally, both negative and
positive emotions invoke stronger emotional responses than faces with neutral expressions
(Ito, Cacioppo, & Lang, 1998), however the current literature suggests negative emotions
elicit stronger cortical responses than positive emotions (Leppänen, Kauppinen, Peltola, &
Hietanen, 2007; Smith, Cacioppo, Larsen, & Chartrand, 2003).

        <hss>Participants</hss>

        We recruited 89 participants (55 males: Mage = 33.73, SDage = 10.74) through
        prolific.ac.uk. An additional participant was excluded due to a technical problem.
        Participants received monetary compensation. A power analysis showed that we had
        95% power to detect a small effect (Cohen’s f = 0.10) of emotional valence on
        temporal binding (α = 0.05).

        <hss>Materials and procedures</hss>

        Experiment 2 consisted of 110 trials: 30 practice trials, and 80 experimental
        trials. To prepare participants for the experimental procedure, we asked
        participants to initially perform a practice task consisting of 10 trials where
        their actions produced a neutral stimulus (the green circle). Similar to
        Experiment 1, during practice trials the time interval for the stimuli to appear
        was randomly selected from either 0 ms, or a multiple of 100 ms, up to 900 ms.
        Participants were provided with feedback about the accuracy of their time
        estimations. Outcome stimuli consisted of 80 face images of young adults either
        portraying positive or negative expressions, taken from a widely used and
        validated set of face stimuli (NimStim, Tottenham et al., 2009). The facial images
        were balanced for gender, such that 10 males and 10 females were randomly chosen
        from the set (see Fig. 5). Four facial images per male/female were chosen: two
        depicting positive facial emotions, and two depicting negative facial emotions (80
        images in total, 4 × 20). The positive facial emotions included 40 images of a
        happy expression comprised the positive facial emotions, and 36 images of disgust
        and 4 images of fear expressions for the negative. Images were presented on a
        white background in the center of the screen. For the initial practice trials, we
        used the same neutral stimulus (green circle) as Experiment 1. Participants
        underwent two experimental task blocks of 40 trials each, with a break between
        blocks. Each block was dedicated to either solely positive expressions or negative
        expressions, and the order of task blocks was counterbalanced between
        participants. Therefore, action-effects were predictable within their own blocks.
        Furthermore, participants were instructed that they would not receive feedback for
        their time estimations. The time interval for face images to appear was randomised
        at 100 ms, 400 ms, or 700 ms (Moore et al., 2009), with the same number of trials
        in each condition at each time interval. A practice block of 10 trials that
        contained stimuli of the related task block preceded each experimental block. Upon
        block completion, participants were instructed that they would be asked to
        complete another practice task where they would see a different set of images,
        receiving feedback with their time estimations. To incentivize participant to
        attend to the face stimuli, we also implemented catch-trials by informing
        participants that they would also be occasionally asked a question about the image
        they had just seen (specifically, “Was the previous face male or female?”). If
        they were correct, then they would be awarded an extra 10 pence per correct
        question. There were six catch trials in total – three trials per experimental
        condition. Seventy-six participants (84%) scored correctly on all catch trials, 8
        participants (9%) scored correctly on 5 catch trials, and the remaining 6
        participants scored correctly on 4 catch trials.

<hs>  Results</hs>
  ~~~~~~~

We averaged time estimations for each of the three onset times (100, 400 and 700 ms) and
for each of the two levels for face-expressions (happy and disgust). We conduced a 2
(emotional valence: positive and negative) × 3 (temporal delay: 100, 400 and 700 ms) fully
within-subjects ANOVA. Analysis revealed a significant main effect of temporal delay, F(2,
176) = 225.75, p < 0.001, ηp2 = 0.72 (see Fig. 6). Consistent with Experiment 1, there was
no statistically significant effect of emotional valance on time estimation, F(1, 88) =
0.092, p = 0.76, ηp2 = 0.001. There was also no significant interaction between temporal
delay and emotion, F(2, 176) = 0.63, p = 0.53, ηp2 = 0.007.

<hs>  Discussion</hs>
  ~~~~~~~~~~

Similar to Experiment 1, the findings from our second experiment indicated no modulation
of negative versus positive emotions on temporal binding. This is despite the use of real
facial images depicting emotional expressions (as opposed to emoticons), and the
predictability of which emotion-expression (either positive or negative) would result from
the participant’s action. For both Experiments 1 and 2, we failed to find any meaningful
effect of emotion on temporal binding, which seems inconsistent with earlier findings. One
potential issue with our first two experiments, however, is that the stimuli we used for
the positive and negative action outcomes (emoticons and real faces) might be perceived as
less positively and/or negatively valenced than the sound vocalizations that Yoshie and
Haggard (2013) used and therefore produced weaker temporal binding effects. To validate
our stimuli, in Experiment 3 participants rated the emotional valence and arousal of the
emoticons and faces we used in Experiments 1 and 2 and the positive and negative sound
vocalizations that Yoshie and Haggard used.

        <hss>Participants</hss>

        Forty-nine participants were recruited via Amazon’s Mechanical Turk (25 males,
        Mage = 34.80, SDage = 11.56). To ensure data independence, one additional
        participant was not included in the analyses because they had a duplicate IP
        address.

        <hss>Materials and procedures</hss>

        Participants were informed that they would rate several images of faces and sound
        vocalizations in terms of how negative-to-positive and emotional arousing they
        appeared or sounded, respectively. Participants first performed a sound check that
        asked them to identify three different sounds (e.g., a cow mooing) from three
        choices (e.g., a pig’s oink, a cow’s moo, or a chicken’s cluck) in order to ensure
        participants both could hear the sounds properly and were paying attention. All
        respondents saw the emoticons used in Experiment 1, all 80-face expressions used
        in Experiment 2, and heard 24 sounds (three repetitions of the 8 different
        sounds). The sounds were the same as those used by Yoshie and Haggard (2013),
        which were a selection of 8 different non-verbal emotional vocalizations: four
        negative vocalizations (screams expressing fear or retches expressing disgust,
        each with both male and female voices) and four positive vocalizations (cheers
        expressing achievement or laughs expressing amusement, each with both male and
        female voices). The block order of which type of stimulus the participants rated
        was randomly determined, and the stimuli presented within those blocks was
        randomised. Using the same rating scales as Yoshie and Haggard, after
        seeing/hearing the stimulus, participants judged the extent to which each stimulus
        looked (for the images) or sounded (for the vocalizations) negative-to-positive,
        on a 7-point scale ranging from 1 (highly negative) to 7 (highly positive).
        Participants also rated the extent to which they believed each stimulus sounded or
        looked emotionally arousing (1 = not arousing at all to 7 = highly arousing).

<hs>  Results</hs>
  ~~~~~~~

Ratings of valence and emotional arousal were averaged across the different positive and
negative faces and sounds. Because we were primarily interested in determining whether the
different stimuli were perceived to be of equivalent valence, we conducted a one-way ANOVA
with stimulus type on three levels (emoticons, faces, and vocalizations) separately for
positive and negative stimuli. Shown in Table 1, there was a significant main effect of
stimulus type in terms of perceived valence for both positive stimuli, F(2, 96) = 15.21, p
< 0.001, ηp2 = 0.24, and negative stimuli F(2, 96) = 22.44, p < 0.001, ηp2 = 0.32. Paired
sample t-tests revealed that the happy emoticon was rated as significantly more positive
than the positive vocalizations, t(48) = 3.52, p = 0.001; there was no significant mean
difference between the positive faces and positive vocalizations in terms of perceived
valence, t(48) = 1.95, p = 0.057. For the negative stimuli, the negative vocalizations
were rated as more positive (less negative) than both the sad emoticon, t(48) = 5.76, p <
0.001, and the negative faces, t(48) = 2.70, p = 0.01. Thus, the emoticon and face stimuli
we used in Experiments 1 and 2 were perceived as either the same or more emotionally-
valenced than the sound vocalizations used by Yoshie and Haggard (2013). We also conducted
a one-way ANOVA with stimulus type on three levels (emoticons, faces, and vocalizations)
separately for positive and negative stimuli for perceived emotional arousal. There were
no significant differences among the types of positive stimuli for the ratings of
emotional arousal, F(2, 96) = 1.44, p = 0.24, ηp2 = 0.03. For the negative stimuli, F(2,
96) = 3.70, p = 0.028, ηp2 = 0.07, the negative vocalizations were rated as more arousing
than the sad emoticon, t(48) = 2.31, p = 0.025, but were no more arousing than the
negative faces, t(48) = 0.79, p = 0.43.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The findings of Experiment 3 indicate that the visual stimuli used within Experiments 1
and 2 and the audio stimuli of Yoshie and Haggard (2013) were by and large rated similarly
across dimensions of perceived valence and emotional arousal. More specifically, the
positive emoticon was rated as more positive and more emotionally arousing than those of
real faces and emotionally valenced vocalizations. Similarly, the negative emoticons and
the negative faces were rated as more negative than the vocalizations. As such, the
failure to find the predicted modulation of temporal binding by emotion in Experiments 1
and 2 does not seem to be driven by differences in the emotional appraisal of the stimuli.

<h>EXPERIMENT 4</h>
------------

Because we did not find an effect of emotion on temporal binding in Experiments 1 and 2,
we conducted a direct replication of Yoshie and Haggard (2013) to investigate the
replicability of their findings.

        <hss>Participants</hss>

        We recruited 24 participants to achieve 95% power to detect Yoshie and Haggard's
        reported effect size for their Experiment 1 (dz = 0.77): 12 males and 12 females
        (aged 18–23: Mage = 21.75, SDage = 3.11), one for each of the 8 (2 × 2 × 2)
        possible orders of conditions (agency/baseline, action/sound and positive/negative
        vocalizations), counterbalanced between participants. Participants were paid for
        their time. Following Yoshie and Haggard (2013), we screened for the following
        exclusion criteria: native language other than English, left handedness, recent
        use of illicit drugs, uncorrected visual or auditory impairment, and history of
        psychiatric or neurological illness.

        <hss>Materials and procedures</hss>

        Experiment 4 used the exact same auditory stimuli as Yoshie and Haggard (2013).
        The stimuli were a selection of non-verbal emotional vocalizations, previously
        validated in the native English population to significantly differ in perceived
        valence, but not in perceived arousal (Sauter, Eisner, Calder, & Scott, 2010). In
        the negative condition, each participant’s keypress was followed by one of four
        negative vocalizations (screams expressing fear or retches expressing disgust). In
        the positive condition, these were replaced by positive vocalizations (cheers
        expressing achievement or laughs expressing amusement). The auditory stimuli in
        each condition were carefully matched for pitch (peak frequency) and duration.
        This experiment faithfully replicated the same procedure used by Yoshie and
        Haggard (2013). We presented the experiment via Macintosh computers (OS X 10.9.5),
        and used a customised program running in Inquisit v4.01 (Draine, 1998; Millisecond
        Software) to present participants with the temporal binding task on a 27-inch flat
        screen. We used the Libet clock task to measure the perceived timing of actions
        and sounds. During the experiment, participants viewed a Libet clock. In agency
        conditions, the participant was instructed to press a key on a computer keyboard
        with the right index finger at a time of his/her choosing, which caused a sound to
        appear 250 ms later. The participant was then prompted to report where the clock
        hand was at the onset of their key-press or (agency action condition), in a
        separate block, at the onset of the sound (agency sound condition). In the single-
        event baseline action condition, the participant pressed a key at a time of
        his/her choosing. This keypress did not cause a sound, and the participant was
        asked to judge the time of his/her keypress. In the single-event baseline sound
        condition, the participant heard sounds at random intervals, which mimicked time
        intervals of participant key-presses, and judged the times of sound onsets. To
        make sure that participants understood the task, we asked participants to perform
        5 practice trials before each condition. Participants underwent four task blocks
        of 32 trials each (baseline action, baseline sound, agency action, and agency
        sound) for both the negative and positive conditions, or 256 (32 trials × 8
        blocks) trials in total. In each block four different sounds of an emotional
        condition were presented in a randomised order (4 sounds × 8 repetitions). Since
        each block contained only positive or negative sounds, the four different
        vocalizations consisted of either the disgust and fear sounds, or the achievement
        and amusement sounds (each in both male and female voices). Each block was further
        divided into two sub-blocks of 16 trials each, with the stimuli randomised across
        the two sub-blocks, such that each sub-block could contain an uneven distribution
        of sounds. To ensure attention to the auditory stimuli, at the end of every sub-
        block we asked participants which of the four sounds they heard most frequently
        during that sub-block. Participants gained a reward of 25 pence for each correct
        answer to this question. The whole experiment was divided into two sessions of
        four blocks each. Each session was devoted to action judgments (baseline action
        and agency action) or sound judgments (baseline sound and agency sound) only. Half
        of participants (n = 8) judged the times of action in the first session and of
        sound in the second session, while in the other half (n = 8) the order was
        reversed. A 10-min break was inserted between the two sessions. To maximize the
        effects of emotional valence, within each session the baseline and agency blocks
        of one emotional condition (e.g., negative) were presented successively, and after
        a 5-min break the blocks of another emotional condition (e.g., positive). Thus,
        there was an additional 5-min break within each session. Both the order of
        emotional conditions (negative first or positive first) and the order of task
        types (baseline first or agency first) were consistent across the two sessions for
        each participant, and counterbalanced between participants (see Yoshie & Haggard,
        2013).

<hs>  Results</hs>
  ~~~~~~~

We used Yoshie and Haggard’s (2013) protocol for extracting binding scores. Judgement
errors were calculated individually for each block by subtracting the actual onset of the
event with the perceived onset. Positive values reflect a delayed judgement, and negative
outcomes reflect an anticipatory (early) judgement. Action binding (shift) was calculated
by subtracting the mean judgement error of the action in the baseline condition from the
mean judgement error in the agency condition. Similarly, sound binding (shift) was
calculated by subtracting the mean judgement error of the sound in the baseline condition
from the mean judgement of the sound in the agency condition. Composite binding was
calculated by subtracting the mean shift in sound judgements from the mean shift in action
judgements. Per Yoshie and Haggard (2013), paired t-tests (negative vs. positive) were
used to assess the effects of emotional valence on temporal binding. We performed a Grubbs
test for outliers (Grubbs, 1950), and no participant met the criteria for exclusion (all
ps > 0.05). Additionally, we compared scores between positive and negative vocalizations
on an attention task asking participants to state the most frequent sound within the
preceding sub-block. A paired-samples t-test revealed no difference in participants’
attention to sounds between negative (M = 3.83, SD = 1.34) and positive (M = 3.63, SD =
1.21) vocalizations, t(23) = 0.96, p = 0.35; dz = 0.20. Table 2 shows the mean judgment
errors and shifts relative to baseline conditions for different emotional conditions. The
presence of action binding was confirmed by a shift in judgement errors that was
significantly different from zero for action judgements in both the negative, t(23) =
2.94, p = 0.007, dz = 0.60, and positive conditions, t(23) = 3.78, p = 0.001, dz = 0.77.
Similarly, sound binding was also significant for both negative, t(23) = 5.47, p < 0.001,
dz = 1.12, and positive vocalizations, t(23) = 5.27, p < 0.001, dz = 1.08. Composite
binding did not differ significantly between the negative (M = −234.68, SD = 174.71) and
positive conditions (M = −280.38, SD = 134.20), t(23) = 1.20, p = 0.24, dz = 0.24.
Similarly, paired t-tests revealed no significant difference in sound binding, t(23) =
0.64, p = 0.53; dz = 0.13, or action binding, t(23) = 1.16, p = 0.26, dz = 0.24, between
the positive and negative conditions.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The findings of Experiment 4 suggest that temporal binding, as measured using the Libet
clock method, was not significantly modulated by positive versus negative sound
vocalizations as action outcomes. It is worth noting that although we did not find
significant modulation of temporal binding by emotional valence, the effect we observed
was nonetheless in the same direction as Yoshie and Haggard’s (2013) effect. Thus, if
there is an effect of emotional valence on temporal binding using the Libet task and sound
vocalizations, it is smaller than previously thought. Moreover, given the results of our
Experiments 1 and 2, the effect of emotional valence of action outcomes on temporal
binding does not seem to generalize using emotionally valenced visual stimuli and time
interval estimation tasks.

<h>GENERAL DISCUSSION</h>
------------------

The objective of this series of experiments was to investigate the degree to which
temporal binding is modulated by emotional valence. Studies 1 and 2 found no significant
difference in temporal binding between positive and negative emoticons (Study 1) or
positive and negative real facial expressions (Study 2). Study 3 revealed that the stimuli
used in Studies 1 and 2 were equivalent in valence and arousal to stimuli that have
previously been observed to modulate temporal binding (Yoshie & Haggard, 2013).
Furthermore, in a highly powered replication study (Study 4), we observed no significant
modulation of temporal binding by emotionally valenced vocalizations (Yoshie & Haggard,
2013). Taken together, these finding cast doubt on whether temporal binding is influenced
by outcome valence. Despite showing no significant modulation by valence, temporal binding
itself was clearly present in Study 4. Indeed the binding scores were overall somewhat
larger than Yoshie and Haggard’s (2013). This suggests that the absence of a valence
effect in our study was not due to reduced sensitivity to detect emotional modulation.
Although not significant, the effect of valence on binding was in the predicted direction
in the current study. However, it is worth noting that this was largely driven by greater
action binding to positive tones, whereas Yoshie and Haggard’s (2013) effect was more
strongly localised on outcome binding. More recently Christensen et al. (2016)
investigated the effect of outcome valence on prospective and retrospective components of
action binding (see Moore & Obhi, 2012) with the same vocalizations used here and in
Yoshie and Haggard (2013). They observed significantly increased retrospective action
binding only when the valence of the outcome was unpredictable. However, for predictable
outcomes (as used in the current study) there was reduced action binding for both positive
and negative outcomes compared to neutral outcomes. Taken together with the current
findings, a complex picture emerges whereby the precise effect of emotion on temporal
binding cannot be clearly attributed to a simple self-serving bias such that positive
outcomes increase binding. This may reflect a genuine complexity in the precise mechanisms
driving the emotional modulation of binding, or it might reflect the fact that the
underlying effect is small or unreliable. The absence of an effect of valence in
Experiments 1 and 2 suggest that any effect, if present in the population, does not
generalize to other measures of binding. Future work should attempt to replicate and
extend other examples of self-serving bias in temporal binding (Aarts et al., 2012;
Takahata et al., 2012) and sensory attenuation (Gentsch, Weiss, Spengler, Synofzik, &
Schütz-Bosbach, 2015; Hughes, 2015) to further advance our understanding of how (or if)
outcome valence influences implicit agency. Assessing the degree to which binding is
modulated by factors that also modulate explicit agency reports is important to determine
the relationship between implicit and explicit agency. Recent evidence suggestions that
neither sensory attenuation (Dewey & Knoblich, 2014) nor temporal binding (Dewey &
Knoblich, 2014; Saito, Takahata, Murai, & Takahashi, 2015) correlate with explicit reports
of agency. While explicit and implicit measures will never show total convergence,
positive evidence of covariation is important to argue that conscious reports and
unconscious biases are indeed measuring the same underlying process. The current studies
provide new evidence that questions the degree to which temporal binding is modulated by
self-serving biases.

<h>AUTHORS’ NOTE</h>
-------------

This research was supported by studentship ES/J500045/1 from the Economic and Social
Research Council.


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<ART>Human Lie-Detection Performance: Does Random Assignment versus Self-Selection of Liars and Truth-Tellers Matter?
================================================================================

Authors: Karl Ask, Sofia Calderon, Erik Mac Giolla
DOI: 10.1016/j.jarmac.2019.10.002
Year: 2020  |  Pages: 128-136
ASJC codes: 3202, 3203, 3205
Keywords: Deception, Detection strategy, Lie detection, Random assignment, Self-selection

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Deception research has been criticized for its common practice of randomly allocating senders to truth-telling and lying conditions. In this study, we directly compared receivers’ lie-detection accuracy when judging randomly assigned versus self-selected truth-tellers and liars. In a trust-game setting, senders were instructed to lie or tell the truth (random assignment; n = 16) or were allowed to choose to lie or tell the truth of their own accord (self-selection; n = 16). In a sample of receivers (N = 200), we tested two alternative hypotheses, predicting opposite effects of random assignment (vs. self-selection) on receivers’ lie-detection accuracy. Accuracy rates did not differ significantly as a function of veracity assignment, failing to support the claim that random assignment of liars and truth-tellers alters the detectability of deception. Equivalence tests indicated that, while a small effect of random assignment cannot be ruled out, moderate (or larger) effect sizes are unlikely.

--------------------------------------------------------------------------------


<h>GENERAL AUDIENCE SUMMARY</h>
------------------------

General Audience Summary In everyday communication, people typically decide whether to lie
or to tell the truth of their own accord. In most studies on lie detection, however,
researchers instruct individuals to lie or tell the truth on a random basis. This approach
has received critique from experts in the field, because it does not reflect what happens
in real life. Since self-selected and instructed liars and truth-tellers differ in several
ways (e.g., motivation, proficiency of lying), the two modes of veracity assignment may
give rise to different cues to truth and deception. In the current study, we tested
whether random assignment, as compared with self-selection, improves or impairs people's
ability to detect deception. Liars and truth-tellers (senders) tried to convince
participants (receivers) to trust them with their money, promising cooperation and
financial gain in return. Half of the senders had been randomly assigned to lie or tell
the truth, whereas the other half had chosen to lie or tell the truth of their own accord.
We tested two competing hypotheses: First, on the assumption that it prevents good liars
from choosing to lie (and poor liars from choosing not to lie), random assignment would
improve receivers’ ability to detect lies. Second, on the assumption that there are
detectable differences between senders who are likely to lie when given the opportunity
and those unlikely to lie, random assignment would make such differences uninformative and
impair receivers’ ability to detect lies. Our results did not support any of the
hypotheses (lie-detection accuracy was near chance level in all experimental conditions),
thus failing to support the claim that random assignment of liars and truth-tellers alters
the detectability of deception. Instead, they indicate that the widely documented poor
ability of humans to detect lies holds for both self-selected and instructed liars.

        <hss>Participants</hss>

        Seventy-two male economy students at the University of Gothenburg, Sweden, were
        recruited for a study on economic decision making. Video messages from 32 of these
        (age range: 19–32 years, Mage = 24.03, Mdnage = 23, SD = 3.19) were used as
        stimulus material in Phase 2. The decision to specifically recruit male economy
        students was based on research showing that economists are more likely to act
        self-interestedly compared to non-economists (Carter & Irons, 1991; Frank,
        Gilovich, & Regan, 1993). Of particular interest, male economy students have been
        found to act more self-interestedly than female economy students in a trust-game
        dilemma (James, Soroka, & Benjafield, 2001). Considering our aim to elicit
        voluntary lies in a trust game dilemma, only male economy students were recruited.

        <hss>Procedure</hss>

        Upon arrival, participants were seated in front of a computer and introduced to a
        trust-game dilemma. The scenario was an amended version of that used by Holm and
        Nystedt (2008). Participants were told they had been randomly paired with another
        participant, referred to as “X”, and that they had been given 50 SEK each to a
        total sum of 100 SEK. Participants were further told that this amount could be
        doubled to 200 SEK on the condition that X trusted the participant with the
        decision how to distribute the money between them. If they did not convince X they
        would, however, only receive the 50 SEK. Participants were told that they were
        going to send a video message to X, expressing why they are altruistic and can be
        trusted, in order to convince him/her to pass the decision over to them.
        Participants were presented with two distribution options: (a) X gets 0 SEK and
        the participant gets 200 SEK (egoistic option), and (b) X gets 80 SEK and the
        participant gets 120 SEK (altruistic option). The instructions stated that both
        parties would be better off if X chose to hand over the decision to the
        participant, provided that the participant would choose the altruistic option (b).
        Participants in the random-assignment condition were instructed, through
        randomization, either to select the egoistic alternative (a) or to select the
        altruistic alternative (b). Thus, they needed to lie about having altruistic
        intentions if they were assigned the egoistic alternative (n = 20), and tell the
        truth if they were assigned the altruistic alternative (n = 17). Participants in
        the self-selection condition were instead instructed to choose the distribution
        option they personally preferred. Thus, they needed to lie if they chose the
        egoistic alternative (n = 8), and to tell the truth if they chose the altruistic
        alternative (n = 27). When participants had been informed about their randomly
        assigned choice or had made their own choice, they were given 5 min alone to
        prepare their message. They were told that they could say whatever they wanted in
        order to convince X to pass the decision over to them, and that they had to keep
        within the upper and lower time limits of 30 s and 1 min, respectively. After
        having prepared what to say, an assistant entered the room and asked the
        participant to take a seat in a chair in front of the camera and to look straight
        into the camera, whereupon the assistant started the video recording. The camera
        was placed straight in front of the participants and was slightly higher than eye-
        level. The image was cropped slightly above their heads and just below their
        knees. If participants talked for longer than 1 min the assistant, who was seated
        in the corner of the room, signaled by standing up that they should end the
        message. When the video recording was finished, participants were shown to a
        second room while the experimenter allegedly brought the message to X to watch. In
        reality, the experimenter waited for 5 min before re-entering the room. All
        participants were then told that X trusted them after having viewed the message.
        After this, participants were asked to divide the 200 SEK in accordance to their
        distribution choice and to place the money in each of two envelopes marked “for
        you” and “X.” Finally, participants brought the envelopes back to the first room,
        after which they left with the compensation that they had put in their own
        envelope. The experimenter subsequently verified that all participants had left
        the correct amount of money in the “X” envelope (i.e., corresponding to the chosen
        distribution option).

        <hss>Participants and design</hss>

        Sample size was determined before data collection, based on an a priori power
        analysis using the G*Power 3.1.9.2 software (Faul, Erdfelder, Lang, & Buchner,
        2007). As no previous tests of the current hypotheses are available in the
        literature, we computed the necessary sample size to achieve 80% power, with a 5%
        Type-I error rate, to detect the average effect size of social cognition studies
        (r = .20) reported by Richard, Bond, and Stokes-Zoota (2003). The analysis
        indicated a sample size of 199 participants. To allow for attrition, 215
        participants were recruited for a study on social judgments. They were recruited
        from a research participant pool, consisting mainly of university students and
        people from the general public, at the Department of Psychology, University of
        Gothenburg, Sweden. They received 50 SEK (∼6 USD) as compensation for
        participating in the study. Fifteen participants were excluded from analyses—five
        knew someone in the videos, four did not follow the instructions, two had language
        difficulties, two experienced technical problems, one was disturbed while
        performing the test, and one had impaired hearing—which resulted in a final sample
        size of 200 participants. One hundred and thirty-seven participants were female,
        60 were male, and three did not specify their gender. Ages ranged between 18 and
        72 years (M = 30.03, Mdn = 26, SD = 11.26). Participants were randomly assigned to
        one of four conditions in a 2 (veracity assignment: random vs. self-selection) × 2
        (detection strategy: feeling focus vs. detail focus) factorial design. The exact
        number of participants per design cell is reported in Table 1. Sender veracity was
        varied within participants (see Procedure section below).

        <hss>Procedure</hss>

        Participants were seated in front of a computer where they read and signed an
        informed consent form. They were informed about the procedure of the trust game in
        Phase 1. Specifically, they were told that participants in a previous study had
        made a choice about how to distribute 200 SEK between themselves and another
        participant (referred to as “X”). There had been one egoistic decision alternative
        (take 200 SEK and give 0 SEK to X) and one altruistic decision alternative (take
        120 SEK and give 80 SEK to X). Importantly, participants in the previous study had
        been instructed to try to convince X to trust them with the decision, because
        otherwise they would get only 50 SEK each. To this end, the participants in the
        previous study had recorded a persuasive video message to X. Participants were
        further told that they were going to watch a series of these video messages, while
        assuming the role of X, imagining that each message was directed toward
        themselves. They were also informed that some of the persons in the videos lied
        about choosing the altruistic distribution option, while some told the truth about
        choosing the altruistic distribution option. Participants were told that their
        task was to judge the veracity of each of the video messages. Four video sets were
        created, each containing eight videos (four true and four deceptive messages). Two
        of the video sets contained only senders who had been randomly assigned to lie or
        tell the truth (random assignment) and the other two contained only senders who
        had voluntarily chosen to lie or tell the truth (self-selection).1 Participants
        were randomly assigned to one of the two sets in their respective veracity-
        assignment condition. Each participant thus watched and judged eight video
        messages, the order of which was randomized for each participant. To manipulate
        detection strategy, participants in the feeling-focus condition were instructed to
        base their veracity judgments on how they felt about the sender and the message:
        “When watching the following video clips and making your judgments, we want you to
        focus on how you feel about the person and what he is saying. Does your gut
        feeling tell you that the person is lying or telling the truth?” Participants in
        the detail-focus condition were instructed to base their judgments on details in
        the verbal content of the message: “When watching the following video clips and
        making your judgments, we want you to focus on analyzing the details in what the
        person is saying. Do these details indicate that the person is lying or telling
        the truth?” A reminder of the detection strategy was presented on the screen
        immediately before the presentation of each video message.

        <hss>Dependent measures</hss>

        Immediately after watching each video clip, participants made a dichotomous
        veracity judgment by answering the following question: “Do you think that the
        person told the truth or lied (i.e., did he choose to share the money or not)?”
        For the purpose of statistical analysis, participants’ veracity judgments were
        converted, using the procedures described in Stanislaw and Todorov (1999), into
        signal-detection measures of discrimination accuracy (d′) and response bias (c).2
        Participants also indicated how confident they were that their veracity judgment
        was correct (1 = not at all confident, 7 = very confident). Participants in the
        feeling-focus condition further indicated how strongly they felt that the person
        was lying or telling the truth (1 = strongly feel that the person is lying, 7 =
        strongly feel that the person is telling the truth). Participants in the detail-
        focus condition instead indicated how strongly they perceived that the details in
        the person's statement suggested that he was lying or telling the truth (1 =
        strongly suggest that the person is lying, 7 = strongly suggest that the person is
        telling the truth). The latter two measures were included to strengthen the
        manipulation of detection strategy, by repeatedly drawing participants’ attention
        to their affective impression of the sender or to the verbal details of the
        messages. Hence, they were not included in any statistical analyses.

        <hss>Manipulation checks and control variables</hss>

        In order to check the effectiveness of the detection-strategy manipulation,
        participants were asked to rate on 7-point scales the extent to which they (a)
        based their veracity judgments on their gut feeling and (b) based their veracity
        judgments on the details of what the individual was saying (1 = not at all, 7 =
        completely). Participants’ accuracy motivation was also assessed by asking how
        important they thought it was to make correct veracity judgements (1 = not at all
        important, 7 = very important). In addition, participants’ general trust was
        measured using the General Trust Scale (Yamagishi & Yamagishi, 1994). The scale
        consists of six items measuring peoples’ propensity to trust others (e.g., “most
        people are basically honest”), using 5-point rating scales (1 = strongly disagree,
        5 = strongly agree). A general trust index was created by averaging participants’
        ratings on the six items (Cronbachs's α = .64). Given a previous finding that
        higher scores on the General Trust Scale are associated with better lie-detection
        performance (Carter & Weber, 2010), we included the general trust index as a
        covariate in the analyses of the lie-detection measures to account for variance
        due to individual differences.

<hs>  Preliminary Analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Participants in all four conditions were highly motivated to make correct veracity
judgments, with means varying between 5.38 and 5.69 on 7-point Likert-scales. A 2
(veracity assignment: random vs. self-selection) × 2 (detection strategy: feeling focus
vs. detail focus) ANOVA showed no significant main or interaction effects (Fs < 0.94, ps >
.335), indicating that the four groups did not differ significantly from each other in
level of motivation. A second ANOVA on participants’ general trust also did not reveal any
main or interaction effects (Fs < 3.05, ps > .082).

<hs>  Main Analysis</hs>
  ~~~~~~~~~~~~~

Means and standard deviations for the variables related to lie detection are reported in
Table 1. Participants’ average detection accuracy was 48.3%, which did not differ
significantly from chance performance (50%) as indicated by a one-sample t-test, t(199) =
−1.33, p = .186, Hedges’ g = −0.09, 95% CI [−0.23, 0.04]. On average, participants judged
51.1% of the messages as truthful. There was not a significant truth or lie bias, as the
proportion truth judgments did not differ significantly from 50%, t(199) = 1.10, p = .271,
Hedges’ g = 0.08, 95% CI [−0.06, 0.22].

<hs>  Additional Analyses</hs>
  ~~~~~~~~~~~~~~~~~~~

Given the null finding regarding the effect of veracity assignment on discrimination
accuracy (d′), we ran tests of statistical equivalence to examine the informativeness of
the result. The procedure recommended by Lakens (2017) involves running two one-sided
tests (TOST) to test whether the observed effect size differs significantly from the
smallest effect size of interest, defined by a lower (e.g., d = − 0.20) and an upper
(e.g., d = 0.20) equivalence bound. If the observed effect is significantly higher than
the lower bound and significantly lower than the upper bound, it is deemed equivalent to
the absence of an effect that is worth examining (Lakens, 2017). A first TOST with
equivalence bounds set at d = ±0.20 was non-significant, t(203.95) = 0.06, p = .522 (one-
tailed), indicating that our result is not equivalent to the absence of a small effect (by
conventional standards; Cohen, 1988). In the current experiment, an effect of d = 0.20
translates into a difference in lie-detection accuracy of 3.73% (0.20 × 18.63 [SDpooled]).
A second TOST, with equivalence bounds set at d = ±0.50 was significant, t(203.95) =
−2.10, p = .019 (one-tailed), indicating that our results are equivalent to the absence of
a medium-sized or larger effect (by conventional standards). In the current experiment, an
effect of d = 0.50 translates into a difference in lie-detection accuracy of 9.32% (0.50 ×
18.63 [SDpooled]). In sum, these analyses show that while our findings do not provide
evidence for the absence of a minor effect, they do indicate that a moderate or large
effect of veracity assignment on discrimination accuracy is unlikely.

<h>DISCUSSION</h>
----------

In the current study, we pitted two competing hypotheses against each other, predicting
that receivers’ lie-detection accuracy would increase (H1) or decrease (H2) as a result of
the random assignment (vs. self-selection) of lying and truth-telling senders. The
observed results did not provide support for any of the hypotheses. In fact, participants
across the experimental conditions performed similarly to what would be predicted by
chance. Moreover, we found no indication that the effect of random assignment on detection
accuracy differs as a function of receivers’ basing their veracity judgments on verbal
content details or on intuitive feelings. When interpreting null results, it is important
to consider the possibility of a false negative finding. Our study was powered to detect
effects as small as r = .20 (d = 0.41) at 80% power. Moreover, follow-up tests indicated
that our results are statistically equivalent to the absence of a medium-sized or larger
(d ≥ 0.50) effect of veracity assignment. The current findings, thus, indicate that medium
or large effects of our manipulation, as studied under the current paradigm, likely do not
exist. However, a few caveats should be noted before generalizing our findings further.
First, our results cannot rule out the existence of a small effect. The meta-analysis by
Bond and DePaulo (2006) indicates that most moderators of lie-detection accuracy are,
indeed, quite weak, and such effects are difficult to detect in an individual experiment,
unless very large samples are used. Second, our relatively modest stimulus material (32
senders) may have restricted the range of detectable differences between self-selected
liars and truth-tellers. Provided that such differences exist, they should emerge more
reliably when larger samples of stimuli are used (Wells & Windschitl, 1999). Third, our
study produced null findings in a trust-game paradigm, but their replicability in other
deception contexts is unknown. Therefore, the role of veracity assignment procedures in
other domains (e.g., criminal, relational) should be examined. Finally, manipulation
checks indicated that the manipulation of detection strategy was only moderately
effective. It is thus questionable whether we achieved the intended separation of
participants who focused predominantly on verbal details and those who focused
predominantly on feelings. We also do not know whether the manipulation shifted receivers’
relative attention to verbal and nonverbal cues, as we did not measure this directly.
These limitations would have been particularly problematic had the effect of detection
strategy been the main focus of the study. However, given that we explored detection
strategy only as a potential moderator of any effect of veracity assignment, the weak
manipulation of detection strategy is less consequential. These caveats notwithstanding,
however, the current findings indicate that veracity assignment and detection strategy, as
operationalized in the current experiment, have at most a modest influence on human lie-
detection performance. We unexpectedly found an interaction effect between veracity
assignment and detection strategy on participants’ response bias. Specifically,
participants relying on a feeling-focused (vs. detail-focused) strategy were significantly
more likely to judge senders as truthful, but only when senders had self-selected to lie
or tell the truth. Given the effect's modest size, and the fact that it emerged from
exploratory analyses, we refrain from a lengthy attempt at an explanation. The result may
be an indication, however, that senders attuned to feeling-based intuitive impressions
(vs. verbal content details) are more receptive to cues that signal high believability,
which may in turn be more prevalent among self-selected (vs. randomly assigned) senders.
This possibility could be tested in future confirmatory research. Another notable finding
is that we were unable to replicate Carter and Weber's (2010) finding on the relationship
between receivers’ general trust and lie-detection ability. They concluded, based on a
very small sample (N = 29), that “high trusters” are better lie detectors than “low
trusters.” In the current study, however, we found no correlation between general trust
and lie-detection accuracy in a sample almost seven times as large (N = 200). Instead, we
found the more intuitive result that high trusters displayed a stronger truth bias than
did low trusters. The current finding casts serious doubt on the replicability of the
original finding reported by Carter and Weber (2010) and calls for further replication
attempts. Moreover, compared with Carter and Weber's result, ours is more compatible with
the established finding that individual differences in lie-detection ability are very
small, and that there is considerably more individual variation in people's inclination to
regard statements as truthful (Bond & DePaulo, 2008). In conclusion, the current study was
the first to fully compare the detectability of self-selected versus randomly assigned
truth-tellers and liars. We found no evidence that the mode of veracity assignment,
separately or in conjunction with receivers’ detection strategy, influences lie-detection
accuracy. This finding fails to support, and provides some evidence against, the concern
that random assignment would substantially alter the detectability of truths and lies
(Levine, 2018). This should not be taken as evidence that the method of veracity
assignment is of little consequence to deception researchers. Rather, the choice of
veracity assignment should be informed by the focal research question. If the aim is to
examine differences between truthful and deceptive messages, independent of senders’
propensity to lie, then random assignment is appropriate. If, however, the researcher is
interested in differences that correlate with senders’ propensity to lie, then allowing
liars and truth-tellers to self-select is necessary.

<h>AUTHOR CONTRIBUTIONS</h>
--------------------

K.A. conceived and designed the studies and collected the data. K.A., S.C., and E.M.G. all
contributed to analyzing and interpreting the data, writing the manuscript, and approving
the final version of the manuscript for submission.

<h>CONFLICT OF INTEREST</h>
--------------------

The authors declare no conflict of interest.


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<ART>Implicit bias, awareness and imperfect cognitions
=================================================

Authors: Jules Holroyd
DOI: 10.1016/j.concog.2014.08.024
Year: 2015  |  Pages: 511-523
ASJC codes: 3204, 3205
Keywords: Awareness, Implicit bias, Moral responsibility

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Are individuals responsible for behaviour that is implicitly biased? Implicitly biased actions are those which manifest the distorting influence of implicit associations. That they express these 'implicit' features of our cognitive and motivational make up has been appealed to in support of the claim that, because individuals lack the relevant awareness of their morally problematic discriminatory behaviour, they are not responsible for behaving in ways that manifest implicit bias. However, the claim that such influences are implicit is, in fact, not straightforwardly related to the claim that individuals lack awareness of the morally problematic dimensions of their behaviour. Nor is it clear that lack of awareness does absolve from responsibility. This may depend on whether individuals culpably fail to know something that they should know. I propose that an answer to this question, in turn, depends on whether other imperfect cognitions are implicated in any lack of the relevant kind of awareness.In this paper I clarify our understanding of 'implicitly biased actions' and then argue that there are three different dimensions of awareness that might be at issue in the claim that individuals lack awareness of implicit bias. Having identified the relevant sense of awareness I argue that only one of these senses is defensibly incorporated into a condition for responsibility, rejecting recent arguments from Washington & Kelly for an 'externalist' epistemic condition. Having identified what individuals should - and can - know about their implicitly biased actions, I turn to the question of whether failures to know this are culpable. This brings us to consider the role of implicit biases in relation to other imperfect cognitions. I conclude that responsibility for implicitly biased actions may depend on answers to further questions about their relationship to other imperfect cognitions.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Are individuals responsible for behaviour that is implicitly biased? Implicitly biased
actions are those which manifest the distorting influence of implicit associations. That
they express these ‘implicit’ features of our cognitive and motivational make up has been
appealed to in support of the claim that, because individuals lack the relevant awareness
of their morally problematic discriminatory behaviour, they are not responsible for
behaving in ways that manifest implicit bias. However, the claim that such influences are
implicit is, in fact, not straightforwardly related to the claim that individuals lack
awareness of the morally problematic dimensions of their behaviour. Nor is it clear that
lack of awareness does absolve from responsibility. This may depend on whether individuals
culpably fail to know something that they should know. I propose that an answer to this
question, in turn, depends on whether other imperfect cognitions are implicated in any
lack of the relevant kind of awareness. In Section 2 clarify our understanding of
‘implicitly biased actions’ and then argue that there are three different dimensions of
awareness that might be at issue in the claim that individuals lack awareness of implicit
bias. Having identified the relevant sense of awareness, in Section 3, I argue that only
one of these senses is defensibly incorporated into a condition for responsibility,
rejecting recent arguments from Washington & Kelly for an ‘externalist’ epistemic
condition. Having identified what individuals should – and can – know about their
implicitly biased actions, I turn in Section 4 to the question of whether failures to know
this are culpable. This brings us to consider the role of implicit biases in relation to
other imperfect cognitions. I conclude that responsibility for implicitly biased actions
may depend on answers to further questions about their relationship to other imperfect
cognitions.

<h>IMPLICIT BIAS, AND AWARENESS OF IT</h>
----------------------------------

What are the phenomena at issue when we talk of implicit biases? Amodio and Mendoza (2010)
describe them as ‘associations stored in memory’ (364).1 These associations can influence
behaviours and judgements. For example, implicit associations have been posited as
explaining differential evaluations of the same CV whose only difference was race,
indicated by the name at the top (Dovidio & Gaertner, 2000); as implicated in shooter
bias, whereby in a computer simulation individuals were more likely to ‘shoot’ black men
with weapons than white men with weapons (Glaser & Knowles, 2008); and as playing a role
in the seating distances between experimental participants and stigmatised group members
(Tidswell, Sheeran, & Webb, in preparation). But what is it about the associations
involved in producing such varied behaviour that makes them implicit, and how do we
delineate which of the many associations of this sort constitute biases?

<hs>  ‘Implicit’</hs>
  ~~~~~~~~~~

Some have suggested that associations are implicit simply because the measure used to
access them is an implicit one; namely, one that does not rely on self-report measures,
nor the voluntary offering of information about one’s attitudes. An implicit measure might
involve a prime of which the agent is not aware, then a measure of how being so primed
influences behaviour or judgement. But why use an implicit measure to access these
associations? One reason is that individuals may not be forthcoming or frank about
associations they would rather they did not have. Another reason is that the associations
are characterised by features of automatic processes which render them difficult for the
agent to identify and report on. DeHouwer, Teige-Mocigemba, Spruyt, and Moors (2009) pick
out the following features as ones taken to be characteristic of implicit associations:
operation without the guidance of proximal goals (that would enable the agent to initiate,
intervene or stop the processes); operation without substantial cognitive resources (such
as when one’s attention is occupied with some other task); and operation with very limited
time (such as when one is required to respond very quickly); or without awareness.
Notably, some philosophers and psychologists have taken this latter feature as
characteristic or even definitional of implicit bias (see e.g. Kelly & Roedder, 2008;
Washington & Kelly, in press; Greenwald & Banaji, 1995; Saul, 2013). I will say much more
about this characteristic in the following. What is important is that these features are
not specified as necessary for an association to be implicit, which leaves considerable
scope for variation in the properties of the associations being measured in such studies,
and discussed in subsequent philosophical literatures.2

<hs>  ‘Bias’</hs>
  ~~~~~~

What is it about some implicit associations that should lead us to characterise them as
‘biases’? We can think of such associations as biases when they are disposed to exert a
distorting influence on judgement. The influence at issue can be characterised as
distorting in that it leads to a judgement which departs from the norms of rationality.
This can be most clearly seen in the CV studies mentioned above: the name at the top of a
CV does not provide a reason for judging it to be better or worse than an otherwise
identical CV. It is less clear how this analysis explains the behavioural outputs, such as
increased seating distance from stigmatised groups. One possibility would be to extend the
definition to include not only distortions of judgement but also undesired or undesirable
influences on action. Another would be to suppose that these behaviours are preceded by
(tacit) judgements, which are distorted (judgements about the suitable place to arrange
the seat say; or about the level of danger posed by an individual). Perhaps either way of
proceeding is adequate, but for the sake of providing a simple contrast with explicit
bias, I will work with the model that sees all implicitly biased action as involving a
distortion of judgement. This judgement is sometimes the output measured; in other cases
it informs the behavioural output which is measured.3 We can proceed, then, with the
following understanding of implicit bias: it is operative when implicit associations
produce a distorting influence on judgement and hence behaviour informed by that judgement
(this leaves room for some implicit associations which are not implicit biases).

<hs>  Responsibility</hs>
  ~~~~~~~~~~~~~~

What are we asking when considering whether or not an agent is responsible for implicit
bias? One dimension of responsibility is forward-looking: is this something an agent can
be asked to take responsibility for, and bring about changes in her cognition? This is an
important sense of responsibility when considering implicit biases, where one of the
primary aims is to bring it about that individuals act in ways that are less biased.4 But
this is not the only sense of responsibility I am concerned with here. The question here
is whether an individual can be held responsible, in the sense of liable to praise or
blame, for the manifestation of implicit bias. If an individual acts in ways that express
bias, is this something that they are blameworthy for (there is, of course, a further
question about whether expressing blame would be appropriate)? To say that the agent is
blameworthy, then, is to say that they have intentionally done something that violated a
moral standard that we expected them to maintain, and as a result certain responses would
be warranted: disapprobation or other forms of informal sanction on the part of others;
resentment on the part of the wronged party; guilt on the part of the wrong-doer, and
resolution to avoid such behaviours or actions in future (indeed, to take responsibility
for that).5 Whether individuals are responsible in this sense is the question with which I
am concerned.

<hs>  Awareness</hs>
  ~~~~~~~~~

Authors who have addressed the question of responsibility for implicit bias have argued
that to the extent that individuals are not (Saul, 2013) or could not reasonably be
expected to be (Washington & Kelly, in press) aware of their implicit biases, they are not
responsible for action influenced by these biases. However, there are different senses of
‘awareness’ at work in this debate. In the next sub-section I articulate three different
senses of awareness that are circulating in the literatures (philosophy and psychology)
about implicit biases. This will enable us to identify more precisely the sense in which
individuals have or lack awareness, such that we can evaluate whether being in such an
epistemic situation exculpates from moral responsibility.

<hs>  Three kinds of awareness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

What do individuals lack awareness of, in the case of implicit bias? In the literature
from empirical psychology and from philosophy, we find different views on this. For
example, in making the claim that individuals should not be blamed for implicit biases,
Saul writes that ‘a person should not be blamed for an implicit bias of which they are
completely unaware’ (Saul, 2013 p. 55), where what is at issue is that individuals are not
aware of the operation of the bias in the production of action. (We might also interpret
Saul as claiming that individuals are not aware of the presence of the bias, but let us
restrict our focus to the operation of the bias, in relation to which our concern with
responsibility arises most pressingly). The sense of awareness at issue here seems to be
introspective awareness; awareness that might yield knowledge of one’s cognitive processes
simply by reflecting on one’s internal states and processes. This sense of awareness is
also in play in Kelly & Roedder’s description of implicit measures as accessing aspects of
cognition ‘not easily accessible or readily available to introspection’ (Kelly & Roedder,
2008, p. 524), and in Anderson’s discussion of ‘unconscious stereotypes’; representations
of which the agent is introspectively unaware (2010, p.74, 48).6 One might have
introspective awareness with respect to whether certain beliefs or feelings are playing a
role in one’s decisions: one can ask oneself, and on reflection give an answer. But, the
claim goes, one cannot simply introspect and discern if an implicit bias is operating in
the production of action. Alternatively, we might be concerned with whether individuals
are aware of a set of propositions about implicit bias, which are likely to be true of
themselves. This is a second sense of awareness at issue in Saul’s claims: when she writes
that individuals may ‘become aware that they are likely to have implicit biases’ (2013,
p.55), the awareness at issue is of the body of knowledge concerning the disposition of
individuals to be biased. Similarly, Washington and Kelly (in press) focus on whether some
individuals in fact know, or should know, certain empirical facts about their probable
susceptibility to implicit biases. In attempting to explain their divergent intuitions
about the responsibility of an egalitarian on a hiring committee who manifests implicit
bias in the 1980s, and a similarly placed contemporaneous egalitarian, they observe that
‘in 1980, no one knew the creepy psychological facts about implicit biases; the
psychological research had not yet been done, and so today’s wealth of empirical evidence
simply did not exist’ (in press). This fact (about what individuals can reasonably be
expected to know) figures in their explanation of why they seek to exculpate the 1980s
discriminator, but not the contemporaneous one. It is unreasonable to expect the 1980s
discriminator to be aware of facts about implicit bias as yielded by empirical psychology:
those facts were not part of our epistemic milieu then. But now, those on hiring
committees have epistemic responsibilities, which include familiarising themselves with
that body of knowledge. At issue in these claims, then, is not some particular aspect of
one’s cognition, nor some observed behavioural effects, but rather some body of knowledge
pertaining to individuals’ general tendencies to manifest implicit biases. Knowledge of
this would be achieved through what we might call inferential awareness; awareness reached
through inferences made about this body of empirical knowledge, and one’s own behavioural
dispositions in light of that. Finally, other authors are concerned with whether
individuals have awareness of the manifestation in behaviour of implicit bias: in
particular, their focus is on an individual’s awareness of discrepant behavioural
responses on tests for biases, and their willingness to attribute such responses to
implicit prejudice. For example, Monteith, Voils, and Ashburn-Nardo (2001) undertook
studies on implicit race associations, in which they measured different response times to
pairing tasks (black names with unpleasant [congruent] or pleasant [incongruent] terms,
and white names with unpleasant [incongruent] or pleasant [congruent] terms. The congruent
pairings are those that individuals are expected to respond more quickly on, insofar as
they are informed by stronger, more accessible, associations. So, a faster
‘black/unpleasant’ response than ‘black/pleasant’ response indicates a stronger
association between the former, negative, construct than the latter. Following the study,
Monteith et al. ‘identified participants who recognized that they were slower on
incongruent [contra-implicit association] than on congruent [consistent with implicit
association] IAT trials’ (2001, p.405), and found that a significant portion of these
individuals were able to attribute their differential response times to implicit
prejudice. The striking claim here is that a considerable number of individuals (64% of
the study participants) were able to recognise, on the basis of observations of their own
behavioural responses, that they were responding differently to the different stimuli. At
issue here, then, is whether individuals are aware of their differential or discriminatory
behavioural outputs. As a matter of fact, it turns out that at least some individuals are.
Individuals at least sometimes have observational awareness of the extent to which their
own actions are biased; and sometimes they additionally have what we can refer to as
attributional awareness: awareness that some feature of their cognition – implicit
prejudice – can be attributed as causally producing that influence.7,8 We have three
candidate senses of awareness, then: introspective awareness of the implicit association
itself, or its operation; inferential awareness of the body of knowledge about people’s
tendencies to harbour, and display, implicit bias; observational awareness of the effects
of the implicit associations on behaviour (sometimes alongside attributional awareness of
the cause of these effects). Because these distinct senses of awareness have not been
distinguished in either the empirical or philosophical literatures, we should be cautious
in our claims about the relationship between these different senses of awareness;
considerably more conceptual (and empirical) work is needed to understand their
relationship than is possible here. However, some preliminary remarks can be made.
Firstly, if one denies that introspective awareness of implicit biases (or indeed any
mental state, cf. Levy, 2014) is possible, then acquiring knowledge of the other kinds
(inferential or observational) will not garner that sort of awareness. Secondly, gaining
inferential awareness (of the fact one is likely to be biased) may well aid observational
awareness, if it can prompt reflection on one’s behaviours that might yield evidence of
subtle discrimination. Finally, inferential and observational awareness of facts about
implicit bias may also generate attributional awareness, in that one may be able to
attribute one’s discriminatory behaviour to the probable presence of implicit bias, even
if one is unable to introspect on such biased processes.

<hs>  A normative epistemic condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Each of these senses of awareness of implicit bias has been used in the literature
regarding whether individuals meet the epistemic conditions for responsibility. How should
we think of these different senses in relation to the epistemic conditions for
responsibility? When considering whether lack of awareness, or ignorance, exculpates, we
have to ask not merely what an individual does or does not have awareness of, in some
relevant sense of awareness.9 Some failures of awareness are themselves culpable. For
example, ignorance of the harm one is perpetrating may not exculpate if one can reasonably
be expected to check that one’s actions are not harmful in that way. Similarly, forgetting
– being unaware of – a meeting one had promised to keep does not exculpate, and may itself
be culpable, in the usual course of things (setting aside excessive pressures or stresses
or distractions). Not being aware of a motive of cruelty or jealousy that shapes one’s
interactions with friends does not excuse actions that are cruel or express jealousy. This
is because, in all these cases (bar exceptional circumstances) we think that the agent
should be aware of the morally relevant facts – whether they are causing harm, or are
forgetting a commitment, or expressing a cruel motive – and their failures of awareness or
knowledge are themselves culpable. (See Sher (2009) for a recent articulation and defence
of the epistemic conditions for responsibility in these terms. The reasons for this
culpability need further unpacking; something we return to in Section 4.). So rather, we
should proceed by asking not whether individuals are in fact aware, in the (to be
determined) relevant sense, of their implicitly biased actions; but rather, whether an
individual should be aware in this sense, and whether their failures of awareness are
culpable.10 We are asking what individuals should know qua responsible agents.11 This
approach is consistent with the idea, defended in legal philosophy, that negligence does
not require that an individual in fact be aware of the harm caused by her action; only
that a reasonable person would have been.12 So our question is now more well focused: do
the epistemic requirements that apply to responsible individuals include awareness of the
kinds identified above? In the next section, I consider each requirement in turn in order
to identify the relevant epistemic conditions for responsibility for implicitly biased
actions.

<h>EPISTEMIC CONDITIONS AND RESPONSIBILITY FOR IMPLICIT BIAS</h>
---------------------------------------------------------

We are interested, then, in whether the following claims are true as conditions for
responsibility: individuals should be aware, introspectively, of the operation of implicit
associations individuals should be aware of, or know about, the body of knowledge about
people’s tendencies to harbour and display implicit biases, and make the relevant
inferences about their own tendencies to express implicit biases. individuals should have
observational awareness, or knowledge, of the effects of implicit associations on their
behaviour. How might we proceed in evaluating which kinds of knowledge individuals should
have? There is a methodological difficulty here, in that we have quite a few moving parts.
The conditions for moral responsibility are in question, but the mental phenomena,
processes, and actions they influence are in some respects unfamiliar – they are states
about which we are learning ever more from the findings of empirical psychology. What
should be held fixed, in trying to understand how we should think about the role of these
unfamiliar processes in our agency? In question is not whether we are ever morally
responsible for anything; that we are, at least sometimes, is a starting assumption of the
argument.13 Those who argue that we are not responsible for actions influenced by implicit
biases (or for the implicit associations themselves) are not seeking to vindicate general
scepticism about responsible agency. At issue, rather, is whether certain aspects of our
agency fall into the remit of those things for which we are responsible. One strategy we
can employ is to consider other more familiar aspects of agency, and our judgements about
responsibility regarding these. Should the same be said of implicit biases? Another
strategy is to consider where a certain condition for moral responsibility would set the
bar if it ruled out holding individuals responsible for a certain kind of state or
behaviour: would it set the bar implausibly high, and lead us to general scepticism about
responsibility? I will deploy each of these strategies in proceeding. In asking whether we
should consider each epistemic condition as specifying a requirement for responsibility,
we should ask whether it is a) desirable, and if so, b) possible, to meet the norm. For if
it is impossible to gain awareness of some sort, then it would be unreasonable to require
that individuals have such knowledge as a condition of responsibility. So our evaluation
will require attention both to philosophical questions about the defensibility of certain
conditions, and empirical questions about what sorts of awareness are possible, as far as
the findings of empirical psychology reveal.

<hs>  Individuals should be aware, introspectively, of the operation of implicit associations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Is this a requirement on responsible agency that we should endorse? If so, then the non-
culpable failure of individuals to have introspective awareness of the activation and
operation in their cognitions of implicit biases would indeed mitigate from
responsibility. My inability to detect the activation of an implicit association, or the
extent to which it is influencing my cognitive processes, would suffice to absolve me from
responsibility for any influence that association exerts on behavioural outputs. It should
be noted that any failure of this kind would, seemingly, be non-culpable. Many have
claimed that the operation of implicit associations – their activation and role in our
cognitive processes – is not something to which we have access simply by reflecting, or by
introspectively checking (see e.g. Saul, Washington & Kelly). And these assertions are
borne out by empirical studies also. Indeed, various studies rely on the opacity of
various aspects of our cognition. For example, the ‘evaluative priming test’ operates by
presenting a prime (e.g. a black or white face, a picture of a prominent Republican or
Democrat) and then measuring how long it takes individuals to recognise and categorise a
negative or positive word. The idea is that if an individual is faster to categorise the
negative terms as bad, than positive words as good, this reveals a negative association
with the prime (because negative constructs were made more accessible by the prime).14 The
idea is that individuals do not have introspective access to the ways in which the prime
(of which they may or may not be aware) activates certain associations which influence
their ease of categorisation. Such implicit processes in general do not appear to be
‘operationally transparent’ to us, such that it is not possible to have introspective
awareness of their operation. If so then any failure to have such introspective awareness
would be non-culpable. But should we endorse this requirement as a condition for
responsible agency, such that non-culpable failure to meet it does exculpate? This
requirement does not seem to me to be defensible. Firstly, it is not a standard we apply
to other aspects of our cognition. Secondly, were such a standard to be applied, it would
lead to radical scepticism about the possibility of responsible agency. On the first
point: we should note that with respect to other aspects of cognition, it is not a
condition on responsibility that individuals be aware of the cognitive processes that
produce action. Here are two examples that help us to see this. Consider a case discussed
by Nancy Snow (2006), of an individual instinctively making an intervention when she
observes an elderly woman being cheated by a sales clerk (556–557). A central feature of
Snow’s example is that the agent does not recognise that her sense of justice is activated
(her justice related goals, in Snow’s terms); there are important aspects of her
cognitions, then, in relation to which she lacks introspective awareness. But that she
lacks awareness of this aspect of her cognition does not mean that she cannot be held
responsible and praised for her actions. Likewise with blameworthy actions. Cases of
forgetting are clear candidates of instances in which individuals might be blamed, despite
lack of awareness of whatever processes led them to forget (indeed, awareness of this
might alleviate the forgetting!). Consider Sher’s discussion of forgetting for which the
agent is responsible: a distracted parent forgets that a dog is languishing in an
overheating car. The parent lacks awareness of the cognitive processes whereby various
competing demands crowd out the relevant belief; this leads her to act in a negligent and
harmful way. But Sher asks us to share the intuition that the agent is still responsible
for this failure, despite the lack of awareness of the processes (the failures of
attention) that produced the action. Here are two cases, then, in which it is plausible
that we hold an agent responsible (for creditable action, and for blameworthy action) even
whilst they fail to be aware of the cognitive processes that play a role in producing the
actions for which we hold them accountable. Thus, it seems that we do not require
introspective awareness of the processes involved in the production of action as a
condition on responsibility. My contention is not, of course, that these examples are
exactly the same as cases of implicitly biased actions. There might ultimately be
different judgements to be made about the two kinds of cases. However, what these cases
show is that merely lacking introspective awareness of the processes involved in
deliberation and action does not suffice to exculpate, and is consistent with praiseworthy
and blameworthy action. Nonetheless, the more familiar processes described above are
similar in some important respects (whilst of course dissimilar in others) to those
involving implicit associations that produce implicitly biased actions: they are fast,
automatic, not readily under the agent’s deliberative control, unreflective, and (in the
latter case) processes the agent would not endorse, and productive of morally undesirable
outcomes. Unless a case can be made for implicit associations being treated differently,
then the fact that an agent lacks awareness of the operation of implicit associations
would not be grounds for exemption from responsibility.15 For in general, we do not
maintain that individuals should have this kind of knowledge of their cognitive processes;
we do not require ‘operational transparency’ for individuals to be held responsible for
actions that result from these processes. Indeed, if we did, very many of our actions –
perhaps all of them? – would be exempt from responsibility, insofar as we are never aware
of all of the processes that input into the production of action. Lack of awareness of
this kind, then, does not exempt from responsibility. Even if it is not possible to secure
this kind of awareness, that is irrelevant: because introspective awareness is not a
requirement for morally responsible action.

<hs>  Individuals should be aware of, or know about, the body of knowledge about people’s tendencies to harbour and display implicit biases, and make the relevant inferences about their own tendencies to express implicit biases</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Let us turn, then, to the second formulation of the epistemic condition for responsibility
in relation to implicit biases: that individuals should be aware of the relevant facts
about the tendencies to express implicit biases in action. This is the sort of condition
that Washington & Kelly argue for, in developing their ‘externalist’ account of the
epistemic conditions for responsibility. The condition on responsibility here is one which
maintains that individuals should, in some contexts, have an awareness of the facts
uncovered by empirical studies about tendencies to discriminate as a result of implicit
bias; inferences can then be made about one’s own propensity to do so. (Ultimately, steps
to avoid biased actions can then be taken). There are two distinctive moves made by
Washington & Kelly in advancing this condition: first, Washington & Kelly argue that what
individuals should know (with respect to bodies of knowledge such as that about implicit
bias) is role dependent in a significant sense. For example, a football commentator is
required to keep up with changes to team composition in the seasonal transfer market; a
heart surgeon is required to have up to date knowledge of aortic valve technologies; I am
not required to have knowledge of either. The second key move is to point out that the
possibility of meeting this requirement is dependent upon one’s epistemic environment.
Accordingly, individuals could not meet the requirement to know about implicit biases in
1980, when the findings of empirical psychology about implicit cognition were less well
established and less readily available. In this way the epistemic conditions for
responsibility are ‘externalist’ in a significant sense – depending not on facts about the
agent, but on facts about her epistemic environment – what is known, and what is available
to be known. This leads Washington & Kelly to conclude that we should endorse this
condition for moral responsibility, (b), in the case of individuals who (i) need to have
information about implicit biases because of the social role they occupy; and (ii) have
that information available in their epistemic environment, such that they are responsible
for not availing themselves of that knowledge. Thus they maintain that responsibility
‘accrues first, or at least more quickly and disproportionately, to occupiers of specific
social roles. These include those involved in hiring decisions, obviously, but also
teachers, social workers, and those in other “gate keeper” positions whose activities can
have the most amplified effects on various institutions and population level outcomes’ (in
press). This issue speaks to the extent to which failure to meet this epistemic condition
is culpable – is such ignorance itself a culpable failure to fulfil one’s epistemic
responsibilities? For the contemporaneous hiring committee member, according to Washington
& Kelly, it is; they can be held responsible (and perhaps blamed) for not knowing what
they should – given the availability of the relevant information, and the role they occupy
– be aware of. An implication of this is that for other individuals – the proverbial
‘person on the street’ – the lack of awareness of this knowledge is not culpable; her
failure to meet this epistemic requirement does not mean she fails to grasp something she
should grasp – so she, unlike the ‘gatekeepers’, can be exculpated from responsibility.
This, Washington and Kelly maintain, is due to the fact that our epistemic environment is
one in which knowledge about implicit bias ‘has still not risen to the level of common
knowledge, and it probably will not any time in the immediate future. … and the percentage
of people who have not heard of implicit bias at all is probably still quite high’ (in
press). Accordingly, the extent of this exculpation depends on the ‘availability’ in the
epistemic environment of the relevant knowledge. When it is pervasively known, and not
just within the remit of academic researchers, this failure will be more widely
culpable.16 Should we agree with Washington & Kelly’s statement of this epistemic
condition for responsibility? To start, we should ask ourselves what motivates the move to
restrict the normative requirement (should know) to those in ‘gatekeeper’ roles. Why
should such individuals know about implicit biases? The answer is presumably that
individuals in such roles are more likely to manifest implicit biases in ways that we can
reasonably foresee to have deleterious effects on those who are stigmatised by or
discriminated against by those biases, or in ways that affect population level
distributions of benefits and burdens. But this motivating assumption seems to me
implausible. Many people make decisions about who to hire, who to fire – literal
‘gatekeeper’ decisions – but also about who to grant a loan to, where to live, who to stop
and search, who to give a lift to, what news stories to report (and how), who to write
prescriptions for, who to sit by on a train, how to evaluate co-workers, who to smile at,
what grades to assign or references to write, who to cross the road to avoid, who to
believe, who to befriend …and so on. These kinds of interactions can all be affected by
implicit biases (see Jost et al., 2009 for an overview).17 And it seems to me to be
difficult to substantiate the claim that the reasonably foreseeable cumulative effects of
these interpersonal interactions are not greater than those of the gatekeepers who make
decisions with population level effects. The widespread impact of ‘informal’
discrimination and segregation in sustaining patterns of disadvantage is described in
detail in Anderson’s work on racial inequality (2010). Valian (1999) also emphasises that
population level discrepancies in the distribution of advantages can often be traced to
the accumulation of small instances of differential treatment. Accordingly, it seems to me
implausible to restrict the realm of ‘responsibility to know’ to some few individuals
charged with hiring decisions or other population level outcomes, especially given what we
know about the pervasiveness of implicit bias and its effects. If this is right, then the
epistemic requirement to be familiar with the findings of empirical psychology will apply
very widely indeed. Almost everyone will be subject to the requirement that they are aware
of the relevant body of empirical findings about the nature of implicit biases, which of
their actions are likely to be susceptible to it (and ultimately, how to avoid this). This
knowledge is available in their epistemic environment, and it is knowledge that they
should acquire. This seems like a very demanding epistemic condition! Washington & Kelly
might appeal to the idea that such knowledge, whilst available, is not readily accessible
as ‘common knowledge’, so failure to grasp it is not culpable.18 But the general epistemic
requirement cannot be that the knowledge is ‘common’ in this way – otherwise the hiring
committee members would also fail to be culpable (these gatekeepers, too, are making
decisions where knowledge of implicit bias is not common knowledge). Moreover, if the
potential and cumulative damage foreseeable as a result of the biased actions of, for
example, loan-makers (and prescription-writers, testimony-takers, stop-and-searchers, and
so on) is commensurate with that of hiring committee ‘gatekeepers’, there is no reason to
subject them to different epistemic standards. But if the same epistemic standards apply
more broadly it looks like we are committed to maintaining that very many individuals in
fact are responsible for acting in an implicitly biased way, because they are culpably
blameworthy for not knowing what they should know (namely, about a body of knowledge in
empirical psychology). This seems rather implausible: not because it involves maintaining
that very many individuals might be responsible for acting in implicitly biased ways (I
think we may be); but that the grounds for this are the failures to engage with the
findings of empirical psychology.19 To summarise: plausibly, very many of us play a role
in sustaining and perpetuating patterns of disadvantage by acting in ways that are
implicitly biased; also plausibly we have a responsibility to avoid doing so. But
Washington & Kelly seem to be committed either to denying this, or to the claim that,
therefore, almost everyone has a responsibility to engage with the findings of academic
research.20 This is an implausibly demanding epistemic requirement, and one that
accordingly, we should reject.21 One of the reasons we should reject this condition is
because it supposes that the only access individuals might have to knowledge about
implicit bias is via (some perhaps mediated) academic research. But there is reason to
believe that this is not the case. This brings us to the third epistemic condition for
moral responsibility.

<hs>  Individuals should have observational awareness, or knowledge, of the ways their behaviours are influenced by implicit associations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Let us now turn, then, to the third sense of awareness identified earlier. I have
suggested that individuals cannot, and ought not to, have awareness of all of their (or
the relevant) cognitive processes prior to acting; and that it is unreasonable to demand
of almost everyone that they engage with complex bodies of academic knowledge about
implicit biases. But there remains the question of whether individuals can, and should be
expected to, have knowledge of the morally relevant features of the actions they perform.
In this context, the morally important features include the property of being
discriminatory, or treating differentially on the basis of some arbitrary feature (such as
race, gender, or age). Do we in general require that individuals have awareness of these
properties as a condition of responsibility? Do we require that individuals should have
this knowledge? And to what extent is failure to have that knowledge culpable? Let us
again consider two cases that will help us to think about this condition in general,
before we turn to consider it in relation to our concern with implicit bias. Let us
consider a variant of a case presented by Adams (1985), in which an individual acts in a
way that expresses ingratitude; perhaps she is insufficiently warm in accepting a favour,
say. This individual has not confronted the fact that she harbours this attitude of
ingratitude, Adams tells us. And this is because she cares more about having a good
opinion of herself than confronting unsavoury truths about herself. In being unaware of
the presence of this attitude in her cognitions, the agent will therefore be unaware of
her action manifesting this attitude; so unaware that her behaviours manifest the morally
undesirable characteristic of being ungrateful. But we should nonetheless hold the agent
responsible for the actions that are inflected by this attitude, Adams claims, because she
should be aware of the fact that her actions are inflected by this attitude. If we share
Adams’ judgements, then we should hold that it is not a condition for responsibility that
the agent is in fact aware of the morally relevant features of their behaviour. A failure
to know that one’s action is expressive of ingratitude does not absolve one of
responsibility for acting ungratefully. This is something the agent should be aware of. In
Adams’ version of the story, the agent’s failure of awareness is due to some further
agential fault (the desire to have a good opinion of herself). Moreover, in this case, it
seems clear that this is something that, with a bit of reflective work, the agent could
become aware of. Observing that her action manifests ingratitude, then, is something we
can reasonably expect the agent to do. Let us consider a second case, this time from Sher
(2009). Sher presents an individual who tells an anecdote, failing to notice that in doing
so she is being insensitive to her audience (an anecdote about a financial failure that is
not well received by the individual who has recently experienced financial failure, say).
Her behaviour has the property of insensitivity, but this is something of which she is
not, at the time of her remarks, aware. Nonetheless, Sher urges us to share his intuition
that this individual is responsible and blameworthy for her insensitivity. This is because
she should be aware of her insensitivity, he claims, even if she is not.22 If we agree
with Sher, then, again, we should not hold that it is a condition for responsibility that
the agent is in fact aware of the morally relevant features of her behaviour (in this
case, insensitivity). The agent should be aware of this feature, and we can suppose that
this is something that, with sufficient reflection, it would have been possible for her to
notice about her behaviour. Given this, it is a reasonable expectation to hold the agent
to. These cases seem far from controversial, and are instances of common parts of our
practice of holding each other responsible. So far, then, the epistemic condition I have
described in this section is far from revisionary. Finally, then, let us consider whether
the same considerations apply to the case of actions that express implicit bias – such as
the differential evaluation of CV whose only difference is the racialised name at the top.
These actions have the morally undesirable characteristic of being discriminatory. If we
treat this case as a direct analogue to those considered above, then the mere fact that an
agent is not aware that her action is discriminatory will not suffice to exculpate.
Ignorance alone does not excuse. So we turn to our next question: is awareness of the
discriminatory nature of her action something that we think the agent should have
knowledge of? Certainly we should strongly affirm the desirability of this: insofar as
agents are expected to bring their behaviour into conformity with moral norms, we should
insist that they ought to self-monitor, and be aware of ways in which their behaviour may
depart from these moral standards. But whether this expectation is reasonable in the case
of implicit bias depends on whether it is possible for agents to have this awareness.
Given the implicit nature of the biases at issue, shouldn’t we suppose that this is not
something that individuals can reasonably be expected to be aware of? As we have already
seen (1.5 above), the empirical evidence does not provide support for that claim, and
rather indicates the contrary. First, it is worth noting that whilst some authors have
characterised implicit associations as attitudes of which the agent is unaware (Saul,
Washington & Kelly, see above), DeHouwer et al. (2009, 357–358) point out that there is in
fact little reason to endorse this claim. Whilst in some implicit measures the way in
which the association is activated is something that the agent is not aware of (because
the association is primed) this does not mean that the effects of the bias on behaviour
are not something that the agent can be aware of. Likewise, that an attitude is measured
with an implicit measure (a measure that does not require self-report or reflective
articulation of one’s attitude) does not mean that the behavioural manifestation of the
attitude cannot be reported on. Recall the studies by Monteith et al. (2001), which I
mentioned earlier in introducing the notion of observational awareness. In this study,
participants undertook a race IAT (pairing white or black names with pleasant or
unpleasant terms). The participants were then asked to evaluate their performance on the
IAT, and the interesting finding for present purposes was that a significant number of
participants (64%) were able to report on the basis of observational awareness of their
own responses that they responded more slowly when pairing black names with pleasant terms
(than with unpleasant terms, and than white names with pleasant terms). These findings
garner support from more recent experimental studies.23 Hahn, Judd, Hirsh, and Blair
(2013) examined individuals’ accuracy of predictions regarding the expression of implicit
biases. They found that individuals were, when asked to carefully reflect, able to
accurately predict this, both in experimental terms: ‘My sorting of [the congruent
pairings] will be very/moderately/slightly easier...’ (p.5) and in conceptual terms: ‘My
true implicit attitude is a lot/moderately/slightly more positive towards white’ (p.8).
This was so even where individuals showed discrepancies between recorded implicit
attitudes, and reported explicit attitudes, such that predictions were not being made on
the basis of explicit attitudes of which the participants were aware and alert to the
possibility of their subtle influence on behaviour.24 We might think that the participants
made their predictions on the basis of general knowledge of social context rather than on
the basis of awareness of their own behavioural dispositions. But the experimenters ruled
this out by asking participants to predict both their own, and the average responses.
There was divergence between these predictions, with predictions about their own behaviour
more closely matching biases measured (p. 10). Or, we might think that reports of explicit
attitudes are unreliable, such that individuals in fact had explicitly biased attitudes,
and made reports in anticipation of these attitudes influencing their behaviour. This
possibility seems unlikely, given that the effect was found in the condition in which
participants were told that the results did not reveal their ‘true attitudes’, but merely
cultural associations (manipulation checks revealed that these participants accepted this
story) (p.7). This study is important, because it indicates that individuals are not only
able to detect morally relevant features of their actions post hoc; they were also able to
predict morally undesirable features ex ante.25 In a way, this should not seem surprising
given the remarks above: there is nothing about the manifestation of an implicit
association or attitude in behaviour that prevents it from being accessible to report on.
But it is surprising in the context of philosophical discussions that have supposed that
implicitly biased behaviour is something of which individuals are not (in some sense)
aware, and have elided the different notions of awareness at issue. But these assumptions
are not supported: there is evidence that supports the claims that, with reflection,
individuals are at least sometimes able to detect and predict discrepant responses. These
are tentative findings: we might wonder whether the possibility of detecting and
predicting biased responses extends to the full range of behaviours that might be
influenced by bias. This is particularly so where the biased actions are identified in
studies that observe statistical tendencies across groups, rather than in intrapersonal
differences in responses. And we should want to know more about the functioning of this
awareness ‘outside the lab’. Nonetheless, the present findings provide reason to examine
how widespread observational awareness of ones actions as biased is, given that it is at
least possible sometimes to have such awareness.26 The key points, then, are as follows:
firstly, individuals should have knowledge of the morally relevant features of their
actions, such as that they are discriminatory. It is only if individuals non-culpably lack
knowledge of this sort, then, that they should be absolved of responsibility for
discriminatory, implicitly biased behaviour. One way of non-culpably lacking this
knowledge would be if it were not possible to have such awareness. But the evidence
suggests that this sort of awareness is not ruled out; and moreover, sometimes individuals
are able to gain this sort of awareness.27 This raises the question, then, of whether
there are other grounds for supposing that individuals who lack awareness of the ways in
which their actions are inflected with bias are culpable for this lack. I suggest two
possible (non-exhaustive, non-exclusive) explanations that might implicate other imperfect
cognitions in our responsibility for implicitly biased behaviour.

<h>IMPLICIT BIAS AND OTHER IMPERFECT COGNITIONS</h>
--------------------------------------------

We have arrived at the following question: when individuals lack the awareness that it
appears possible for them to have, with respect to the morally relevant properties of
their implicitly biased behaviour, is this lack a culpable one? Not all failures to know
what should be known are culpable failures. What might be said about the failure to have
the relevant kind of awareness of one’s own actions as implicitly biased? Here are two
possible answers that yield different judgements about the extent of an individual’s
blameworthiness for their actions.

<hs>  Failures of attentiveness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

It might be tempting to suppose that the kind of awareness at issue requires some
revisionary moral understanding, such that the culpability of any failure to meet the
epistemic condition is considerably mitigated. Not knowing what one should know may be
less culpable if it is harder to gain that knowledge, because it is not yet normalised and
nor accessible to all as moral knowledge (it is rather at a ‘frontier’ of moral knowledge)
(Calhoun, 1989, cf. Washtington & Kelly, above); or if the pervasive tendency is not even
to think of an issue as ‘morally charged’, so that moral reflection is not focused upon
that action or its consequences at all (Isaacs, 1997). Examples of this include the
failure of many to know that the supposedly gender-neutral use of the pronoun ‘he’
perpetuates sexism. Such sexist language use may be less blameworthy if the knowledge of
this that we all should have is not yet normalised, or requires some imaginative leap to
access; or if it is not yet clear that this domain of our activity is even morally
scrutable.28 Analogously, we might think that the common sense view of discrimination
involves the explicit intention to treat differently, or the explicit intention to harm
others or manifest ill will (Garcia, 1996). Given this, the failures of awareness with
respect to implicitly biased actions may be candidates for a kind of moral ignorance that
is mitigated in the ways described above. Perhaps the knowledge that one’s actions can be
discriminatory, even if not intentionally so, is not yet ‘normalised’ so as to make this
knowledge readily accessible; or perhaps such behaviour does not prompt reflection, as it
is not on the radar as a ‘moral issue’ at all. In this respect we can see how inferential
awareness of the findings about implicit bias may make it considerably easier to possess
observational awareness of one’s actions as biased. Knowing that one is likely to be
biased, given the body of empirical evidence we now have, can introduce pressures to
reflect that might generate observational awareness. To the extent that one lacks
inferential awareness, then, it may be harder to know what one should know. Moreover, we
might think culpability is mitigated further if this moral ignorance is compounded by
misleading introspective evidence, which seems to suggest to us that our motives are good,
and without discriminatory content. However, these remarks do not seem quite right as a
full diagnosis of the failing, because what is at issue is not simply whether a certain
behaviour is morally problematic or would fall under the rubric of ‘discrimination’; but
rather whether the fact that a behaviour displays differential treatment is noted at all.
The lack of awareness at issue here is not whether the situation is a ‘morally charged’
one; it is surely accepted that one’s behaviour would be morally questionable if it were
known to involve such differential treatment. Rather, the lack of awareness pertains to
the behaviour manifesting differential treatment itself. There is some lack of
attentiveness, a failure to notice, that means the morally relevant feature of behaviour
is not something of which the agent is aware (irrespective of how it would, once noticed,
be labelled). It might be that this failure of attention is driven by the mistaken beliefs
that, since one is not intentionally discriminatory, it is simply not possible for one’s
actions to have discriminatory effects. But on the other hand, some failures to notice
morally important things can be indicative or expressive of an agent’s evaluative stance –
what they care about, and how much. Lacking the motive to reflect can indicate what one
takes to be worthy of moral scrutiny. Such lacks are ones that it is feasible to hold
individuals responsible, and blameworthy, for (Sher, 2009; Smith, 2005). The extent to
which an individual is culpable for the failures of awareness with respect to implicitly
biased actions, then, will depend on answers to further questions about the role of
implicit associations in our broader agential structures, and how their expression is
related to the values we hold.29

<hs>  Self-deception</hs>
  ~~~~~~~~~~~~~~

It is one thing to lack a motive to reflect; another to be motivated not to reflect, as
Calhoun points out: ‘self-interest can motivate the suppression of reflection ... self-
deception is a matter of not being motivated to examine one’s actions or reasoning too
carefully, lest something unpleasant turn up’ (399).30 Whilst it might be possible to
detect in one’s actions differential treatment – or to predict it – when specifically
prompted to do so, these are difficult truths to confront. Acknowledging not only one’s
complicity in but perpetuation of patterns of discrimination, albeit in subtle and
unintended ways, is something that no doubt many of us find hard to accept. The belief
that one’s actions are implicitly biased, and other implied beliefs about one’s role in
sustaining patterns of discrimination, are clearly beliefs that, for a range of reasons,
agents might be motivated not to confront. Conversely, the belief that one’s actions are
consistent with one’s moral ideals (of non-discrimination, of being evidence sensitive and
unbiased) is one that agents are motivated to maintain. That we are motivated to avoid the
sort of moral reflection that might overturn those desirable beliefs, and turn up these
undesirable facts about our propensity to bias, is a plausible explanation of this lack of
awareness. After all, there is ample evidence from empirical psychology that we are
motivated to maintain a positive self-concept (Brown, 1986; Suls, Lemos, & Stewart, 2002).
Indeed the motive to present a positive view of ourselves is what raises concerns about
the validity of self-report measures (we do not want to see ourselves, or let others see
us, as prejudiced), and makes access to attitudes via implicit measures so valuable.31
Moreover, recent studies indicate that such a motivation has a role in sustaining our view
of ourselves as immune to bias: Pronin and Kugler (2007) found individuals to over-rely on
on misleading introspective evidence of propensity to bias (introspection revealing –
surprise! – no bias). Meanwhile participants ignored behavioural evidence of their own
bias that they were willing to take as evidence of bias in others: ‘actors … preferred to
see themselves as bias free’ where it was possible to ignore evidence to the contrary
(576). This form of self-deception could explain the failure of individuals to have
awareness that their actions manifest implicit bias.32 Would this explanation yield the
judgement that such ignorance is culpable? Whilst pervasive, such self-deceptions are not
so overwhelming as to be insurmountable: in Pronin and Kugler’s study, when experimenters
reminded subjects of the unreliability of introspection (in contrast to observed
behaviour) as a guide to their own bias, the participants no longer denied their
susceptibility to bias. Insofar as the motivated lack of reflection is serving to bolster
a misleadingly positive view of oneself, and serving to cover up morally undesirable
aspects of one’s actions that are not otherwise impossible to detect, a case can be made
that failures of awareness resulting from such mechanisms are culpable. In this case, such
ignorance would be culpable, and the lack of awareness of one’s actions as implicitly
biased would not serve to exculpate from responsibility.

<h>SUMMARY</h>
-------

I have argued that there three different claims that need teasing apart when thinking
about whether individuals have awareness in relation to implicit bias: whether we have
introspective awareness of its operation in influencing behaviour; whether we are aware of
the relevant bodies of knowledge about implicit bias that enable us to infer our likely
susceptibility to such biases; whether we are observationally aware of the fact that our
behaviours have the morally undesirable property of being discriminatory. In each case,
the relevant question is not whether an individual has this awareness, but whether they
should have such awareness, and whether lacking it is culpable. I argued that lacking
introspective awareness of the operation of implicit associations, or lacking inferential
awareness of the propensity to display implicit bias, does not in itself exculpate.
Rather, I argued that we should have observational awareness of the morally relevant
features of our behaviour, namely, their discriminatory nature. And indeed the empirical
studies on implicit bias do not entail that such knowledge is impossible to gain; in fact,
some show that sometimes individuals do have this kind of awareness. When we lack it, are
we culpably ignorant? Perhaps so, if this lack is due to failures of attention that
express our values, or self-deception that narrowly serves our interests. In this way, our
responsibility for implicitly biased actions may be bound up with imperfect cognitions of
other kinds.


<h>REFERENCES</h>
----------

  [2] Elizabeth Anderson. The imperative of integration
  [10] Jan De Houwer, Sarah Teige-Mocigemba, Adriaan Spruyt, Agnes Moors. Implicit Measures: A Normative Analysis and Review. doi:10.1037/a0014211
  [12] John F. Dovidio, Samuel L. Gaertner. Aversive racism and selection decisions: 1989 and 1999. doi:10.1111/1467-9280.00262
  [13] Chloë Fitzgerald. A Neglected Aspect of Conscience: Awareness of Implicit Attitudes. doi:10.1111/bioe.12058
  [14] Miranda Fricker. The relativism of blame and Williams's relativism of distance. doi:10.1111/j.1467-8349.2010.00190.x
  [15] Bertram Gawronski, Wilhelm Hofmann, Christopher J. Wilbur. Are "implicit" attitudes unconscious?. doi:10.1016/j.concog.2005.11.007
  [16] Jack Glaser, Eric D. Knowles. Implicit motivation to control prejudice. doi:10.1016/j.jesp.2007.01.002
  [17] Anthony G. Greenwald, Mahzarin R. Banaji. Implicit Social Cognition: Attitudes, Self-Esteem, and Stereotypes. doi:10.1037/0033-295X.102.1.4
  [19] Jules Holroyd. Responsibility for implicit bias. doi:10.1111/j.1467-9833.2012.01565.x
  [22] Tracy Isaacs. Cultural Context and Moral Responsibility. doi:10.1086/233765
  [23] John T. Jost, Laurie A. Rudman, Irene V. Blair, Dana R. Carney, Nilanjana Dasgupta, Jack Glaser, Curtis D. Hardin. The existence of implicit bias is beyond reasonable doubt: A refutation of ideological and methodological objections and executive summary of ten studies that no manager should ignore. doi:10.1016/j.riob.2009.10.001
  [25] Matt King, Peter Carruthers. Moral responsibility and consciousness. doi:10.1163/174552412X625682
  [26] Neil Levy. Consciousness, implicit attitudes and moral responsibility. doi:10.1111/j.1468-0068.2011.00853.x
  [29] Margo J. Monteith, Corrine I. Voils, Leslie Ashburn-Nardo. Taking a look underground: Detecting, interpreting, and reacting to implicit racial biases. doi:10.1521/soco.19.4.395.20759
  [30] Brian A. Nosek. Moderators of the relationship between implicit and explicit evaluation. doi:10.1037/0096-3445.134.4.565
  [31] Brian A. Nosek. Implicit-explicit relations. doi:10.1111/j.1467-8721.2007.00477.x
  [33] Emily Pronin, Matthew B. Kugler. Valuing thoughts, ignoring behavior: The introspection illusion as a source of the bias blind spot. doi:10.1016/j.jesp.2006.05.011
  [34] George Sher. Who Knew?: Responsibility Without Awareness. doi:10.1093/acprof:oso/9780195389197.001.0001
  [35] Angela M. Smith. Responsibility for attitudes: Activity and passivity in mental life. doi:10.1086/426957
  [36] Nancy E. Snow. Habitual virtuous actions and automaticity. doi:10.1007/s10677-006-9035-5
  [37] Ema Sullivan-Bissett. Implicit bias, confabulation, and epistemic innocence. doi:10.1016/j.concog.2014.10.006
  [38] Jerry Suls, Katherine Lemos, H. Lockett Stewart. Self-esteem, construal, and comparisons with the self, friends, and peers. doi:10.1037/0022-3514.82.2.252
  [45] J. L.A. Garcia. The heart of racism. doi:10.1111/j.1467-9833.1996.tb00225.x
  [46] Kate A. Ranganath, Colin Tucker Smith, Brian A. Nosek. Distinguishing automatic and controlled components of attitudes from direct and indirect measurement methods. doi:10.1016/j.jesp.2006.12.008
<ART>Implicit bias, confabulation, and epistemic innocence
=====================================================

Authors: Ema Sullivan-Bissett
DOI: 10.1016/j.concog.2014.10.006
Year: 2015  |  Pages: 548-560
ASJC codes: 3204, 3205
Keywords: Confabulation, Epistemic benefit, Epistemic evaluation, Imperfect cognitions, Implicit bias

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

In this paper I explore the nature of confabulatory explanations of action guided by implicit bias. I claim that such explanations can have significant epistemic benefits in spite of their obvious epistemic costs, and that such benefits are not otherwise obtainable by the subject at the time at which the explanation is offered. I start by outlining the kinds of cases I have in mind, before characterising the phenomenon of confabulation by focusing on a few common features. Then I introduce the notion of epistemic innocence to capture the epistemic status of those cognitions which have both obvious epistemic faults and some significant epistemic benefit. A cognition is epistemically innocent if it delivers some epistemic benefit to the subject which would not be attainable otherwise because alternative (less epistemically faulty) cognitions that could deliver the same benefit are unavailable to the subject at that time. I ask whether confabulatory explanations of actions guided by implicit bias have epistemic benefits and whether there are genuine alternatives to forming a confabulatory explanation in the circumstances in which subjects confabulate. On the basis of my analysis of confabulatory explanations of actions guided by implicit bias, I argue that such explanations have the potential for epistemic innocence. I conclude that epistemic evaluation of confabulatory explanations of action guided by implicit bias ought to tell a richer story, one which takes into account the context in which the explanation occurs.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In this paper I explore the nature of confabulatory explanations of action guided by
implicit bias in the non-clinical population. My aim is to highlight the potential
epistemic benefits of some confabulatory explanations and tell a richer story about the
overall epistemic status of such explanations. Although confabulation is characterised and
often even defined on the basis of its epistemic costs, I argue that some confabulations
can play a positive role, not just because they act as a psychological defence by
enhancing coherence, stability, self-confidence, and well-being (Ramachandran, 1996: 351;
Fotopoulou, 2008: 542), but also because they bestow epistemic benefits which are
otherwise unavailable. In section one I describe two imagined cases of confabulatory
explanations of actions guided by implicit bias.1 In section two, I characterise non-
clinical confabulation by identifying some common features of the phenomenon, features
shared by my two imagined cases. In section three, I introduce the notion of epistemic
innocence to capture the status of those cognitions that have obvious epistemic faults,
but also have some significant epistemic benefits that could not be otherwise obtained. In
section four, I argue that confabulatory explanations of actions guided by implicit bias
have the potential to deliver epistemic benefits, insofar as they maximise the acquisition
of true beliefs in the long run by filling an explanatory gap, and they help the agent
maintain consistency among her cognitions. I also argue that, at the time of the
confabulatory explanation, no alternative explanations are available—in a sense to be
explained—to the subject. I conclude that epistemic evaluation of confabulatory
explanations should be indexed to context, taking into account the (un)availability of
alternatives and potential epistemic benefits. This allows us to resist a kind of trade-
off view about the epistemic status of confabulatory explanations: the view that pragmatic
benefits come at the expense of epistemic ones. A closer focus on the potential epistemic
benefits of these cognitions, as well as the context in which they occur, can result in a
more careful epistemic evaluation of them.

<h>EXPLANATIONS OF ACTIONS DRIVEN BY IMPLICIT BIAS: TWO CASES</h>
----------------------------------------------------------

In this section I describe two imaginary cases of confabulatory explanations that could
occur in the non-clinical population. I will assume Jules Holroyd’s definition of implicit
bias in the discussion which follows, according to which: ‘[an] individual harbors an
implicit bias against some stigmatized group (G), when she has automatic cognitive or
affective associations between (her concept of) G and some negative property (P) or
stereotypic trait (T), which are accessible and can be operative in influencing judgment
and behavior without the conscious awareness of the agent’ (Holroyd, 2012: 275). Implicit
biases then can be understood as ‘largely unconscious tendencies to automatically
associate concepts with one another’, such tendencies can result in judging ‘members of
stigmatized groups more negatively’ (Saul, 2012b: 244). Care is needed when using the term
‘unconscious’ with respect to implicit bias. Gawronski, Hofmann, and Wilbur (2006)
distinguish three types of awareness: source, content, and impact awareness. If a subject
has source awareness of some attitude of hers, she has awareness of the origin of that
attitude. If a subject has content awareness of some attitude of hers, she has awareness
of the attitude itself. Finally, if a subject has impact awareness of some attitude of
hers, she has awareness of the influence of that attitude on other psychological processes
(Gawronski et al., 2006: 486). Gawronski and colleagues’ review of empirical evidence
suggests that implicit attitudes only differ from explicit attitudes with respect to
impact awareness. They conclude that the term “unconscious” is adequate for indirectly
assessed attitudes only with regard to one particular aspect: impact awareness. However,
the term “unconscious” is inadequate when it is assumed to imply a lack of source
awareness or content awareness. Note that though the evidence suggests that source and
content awareness of implicit attitudes is possible, that is not to say that subjects
always have such awareness in ordinary settings. We can be cautious here and take a lesson
from the nearby literature: in her discussion of moderating automatic stereotypes, Irene
Blair claims that though ‘the evidence is compelling with regard to the possibility of
moderating automatic stereotypes, the likelihood of such moderation in everyday social
encounters is not yet known’ (Blair, 2002: 249). Similarly then, though the work Gawronski
and colleagues reviewed showed evidence that content and source awareness is possible,
that is not to say that ‘unconscious’ used in this way is always inappropriate. Empirical
work has shown that implicit biases are held by most people, even those who avow
egalitarian positions, or are members of the targeted group. Results from Implicit
Association Tests (IATs) support this. IATs work by measuring the speed at which subjects
pair two categories of object with, for example, pleasant and unpleasant stimuli (e.g. the
words ‘wonderful’ and ‘awful’) or stereotypical and unstereotypical stimuli. The idea
behind the tests is that we can discover which categories a subject associates with one
another. This is done by measuring the categorisation performance of combinations of
categories (De Houwer, Teige-Mocigemba, Spruyt, & Moors, 2009: 347). In a review of over
2.5 million IAT results across seventeen topics, Brian Nosek and colleagues report that
‘[i]mplicit and explicit comparative preferences and stereotypes were widespread across
gender, ethnicity, age, political orientation, and region’ (Nosek et al., 2007: 40). In
the rest of the paper, I will follow Holroyd in understanding implicit biases as operative
when they ‘produce a distorting influence on judgement and hence behaviour informed by
that judgement’ (Holroyd, 2015). The cases I introduce in the next two sections are ones
in which implicit biases are operative in this sense.

<hs>  Implicit gender bias and the case of Roger</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In a study on the influence of the gender of an applicant on reviewing CVs, both male and
female participants were more likely to vote in favour of hiring a male applicant than a
female applicant when the CVs presented were otherwise identical (Steinpreis, Anders, &
Ritzke, 1999: 509). The authors of the study suggest that the results ‘indicate a gender
bias for both men and women in preference for male job applicants’ (Steinpreis et al.,
1999: 510). Both male and female participants were ‘significantly more likely to hire a
potential male colleague than an equally qualified potential female colleague’, and were
‘more likely to positively evaluate the research, teaching, and service contributions of a
male job applicant than a female job applicant with an identical record’ (Steinpreis et
al., 1999: 522). Corinne A. Moss-Racusin and colleagues found that when assessing
application materials of a student applying for a Laboratory Manager position, ‘[f]aculty
participants rated the male applicant as significantly more competent and hireable than
the (identical) female applicant’, as well as ‘select[ing] a higher starting salary’
(Moss-Racusin, Dovidio, Brescoll, Graham, & Handelsman, 2012: 16,474). Monica Biernat and
Diane Kobrynowicz predicted that ‘it would be more difficult for women than men […] to
document their ability in a competence-related domain’ (Biernat & Kobrynowicz, 1997: 554).
They ran two studies which confirmed this prediction showing that women were required by
participants to ‘jump through more hoops’ in order to show that they were able to fill a
position (Biernat & Kobrynowicz, 1997: 554). These studies suggest that ‘[w]ithout any
intention of bias, once we have categorised someone as male or female, activated gender
stereotypes can colour our perception’ (Fine, 2010: 56). Having pointed to empirical work
showing the presence and effects of gender bias, here is the case of Roger: Roger is on a
hiring panel deciding from a stack of CVs which candidates to invite to interview. Roger
thinks of himself as an egalitarian, and not as somebody who is sexist. The CVs are not
anonymous with respect to gender. Roger chooses not to invite any female applicants to
interview. Katie is one of the female candidates who Roger chooses not to invite to
interview. Katie’s CV is of equal or better quality than at least some of her male
competitors who did get invited to interview, and had Katie’s CV been headed with a male
name, Katie would have been invited to interview. The case might be made more plausible if
the job were a traditionally male one, say, an ‘executive chief of staff’ position
(Biernat & Fuegen, 2001: 711). As Madeline Heilman points out, ‘research has repeatedly
demonstrated sex bias in employee selection processes […] with male applicants generally
recommended for hire and seen as more likely to succeed than female applicants with the
identical credentials when jobs are male in sex-type’ (Heilman, 2001: 660). Let us say
that Roger’s decision not to invite Katie to interview was guided by his implicit bias
against women. I will not worry too much about how exactly to cash out the guided by
locution here, the thought is only that Roger’s implicit bias was efficacious in his
decision not to invite Katie to interview, and the appropriate counterfactuals are true
(if Roger did not have an implicit bias against women, Katie would have been invited to
interview, and if Katie’s CV was headed with a typically male name, Katie would have been
invited to interview). Let us ask Roger to explain his decision. He claims that Katie’s CV
indicates that she is not good enough for the job, and so she ought not to be interviewed.
Later I will argue that Roger’s explanation of his decision not to invite Katie to
interview is a confabulatory one (Section 2.6).

<hs>  Implicit race bias and the case of Sylvia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Empirical work has shown that implicit race bias is exhibited by many people. Such biases
may affect not only our beliefs, but also the way we perceive the world. A study by Keith
B. Payne (2001) showed that participants were able to more quickly identify guns (as
opposed to non-gun tools) when they were primed with a Black face, as compared to when
they were primed with a White face. In this experimental set up, the ‘presence of Black
faces facilitated the identification of guns relative to the presence of White faces’
(Payne, 2001: 185). When a time condition constraint was introduced into an otherwise
identical experiment, participants more often mistakenly identified tools as guns when
they had been primed with a Black face as compared to when they had been primed with a
White face. Payne identifies as the ‘critical finding’ that ‘priming participants with a
Black rather than a White face was sufficient to make them call a harmless item a gun’
(Payne, 2001: 188). In a similar experiment in which participants were instructed to shoot
at subjects holding a gun, and not shoot at subjects not holding a gun, participants were
found to shoot an armed subject quicker if that subject was African American than if he
was White, and the decision to not shoot an unarmed subject was made more quickly when the
target was White and not African American (Correll, Park, Judd, & Wittenbrink, 2002:
1317). Finally, behaviour which is ambiguously aggressive committed by a black person is
more likely to be perceived as hostile than the same behaviour committed by a white person
(see for example Duncan, 1976; Sagar & Schofield, 1980). Implicit bias then is ‘getting to
us even before we get to the point of reflecting upon the world—it affects our very
perceptions of that world’ (Saul, 2012b: 246). In summarising a body of work on this Tamar
Gendler claims that ‘[h]undreds of studies conducted in dozens of laboratories over nearly
two decades have shown that—for most twentieth and twenty-first-century American
participants in most circumstances’ the White-or-positive and Black-or-negative pairing
‘is more natural’ than the White-or-negative and Black-or-positive pairing. Gendler claims
that this suggests ‘that the former categories are, for most participants, more readily
constructed or more easily accessed, and hence experienced as more “natural” than the
latter’ (Gendler, 2011: 52). Here is the case of Sylvia: Sylvia is walking down the road
on her way to work. Sylvia thinks of herself as an egalitarian, and not as somebody who is
racist. She sees a black man walking towards her. Sylvia crosses the road. The man is not
acting in a threatening manner. Had the man not been black, Sylvia would not have crossed
the road. Let us say that Sylvia’s decision to cross the road was guided by her implicit
bias against black people. Again, what I mean by the guided by locution here is just that
Sylvia’s implicit bias against black people was efficacious in the production of her
behaviour, and that the appropriate counterfactuals hold (if Sylvia did not have an
implicit bias against black people, she would not have crossed the road, had the man not
been black, she would not have crossed the road).2 Let us ask Sylvia to explain her
behaviour. She claims that the man was behaving in a threatening way, and so she crossed
the road out of fear for her safety. I have built into the case that the black man is not
behaving in a threatening way, and let us suppose that if one did not hold an implicit
bias towards black people, no threat would be felt. In the next section I will argue that
Sylvia’s explanation of why she crossed the road is a confabulatory one (Section 2.6).
Next I will look at the explanations offered by Roger and Sylvia in the light of five
features of confabulatory explanations, to support the claim that at least sometimes,
explanations of decisions or actions guided by implicit bias are confabulatory.

<h>COMMON FEATURES OF NON-CLINICAL CONFABULATION</h>
---------------------------------------------

Here I do not aim to solve the thorny issue regarding how best to define confabulation,
rather, I will just highlight what the two cases described in the previous section have in
common, focusing in particular on those features that are relevant to their epistemic
status. As we will see, these features appear in popular accounts of confabulation. I will
consider five common features of confabulatory explanations, they (1) are false or ill-
grounded; (2) are offered as the answer to a question; (3) have a motivational component;
(4) fill a gap, and (5) are reported without any intention to deceive. These are not
necessary and sufficient conditions, rather, they have been thought to be common features
of confabulatory explanations, and they are features which characterise the cases of Roger
and Sylvia.

<hs>  False or ill-grounded</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Confabulatory explanations are epistemically faulty. Generally speaking, they are false
explanations, their being so has been identified as a key or defining feature of them (see
for instance Berrios, 2000: 348; McKay & Kinsbourne, 2010: 289). However, someone might
confabulate and hit on something true (see for example William Hirstein’s discussion of
subjects with Korsakoff’s syndrome—a form of amnesia caused by alcohol abuse or severe
malnutrition—who happen to confabulate correctly (2009: 3), or Ryan McKay and Marcel
Kinsbourne’s example of a subject who lacks ‘access to his biographical information, yet
by chance may confabulate the correct answer when asked his age’ (2010: 289)). We cannot
then, rule out by definition the possibility of true confabulatory explanations. But even
when confabulatory explanations are not false, they are epistemically poor in other
respects. A key epistemic feature of confabulations then is that they are ill-grounded or
poorly supported by evidence (Hirstein, 2005: 33–4). In confabulation, the explanation
offered for a decision or action does not reflect what caused that decision or action and
also poorly matches the details of the situation at hand. For example, the participants in
Johnathan Haidt’s experiment were presented with a scenario in which two siblings engage
in incest. Asked how they felt about the scenario, most of the participants claimed that
it was wrong, and justified that attitude on the basis of the risks of inbreeding, even
when the case of incest they were presented with explicitly excluded the possibility of
reproduction after sexual intercourse (Haidt, 2001). Explanations of actions guided by
implicit bias look to share the same features as the classical cases of non-clinical
confabulation reported by Haidt. They are false explanations, since they do not map on to
what was efficacious in guiding the subjects’ decisions or actions. They are ill-grounded,
insofar as they misrepresent important features of the situations. Roger chooses not to
invite Katie to interview, when her CV is of equal or better quality than at least some of
her male competitors. Sylvia crosses the road upon seeing a black man, when the black man
is not acting in a threatening way. Roger offers an explanation of his decision by
claiming that Katie’s CV was not as strong as the CVs of the (male) candidates who were
invited to interview. Sylvia explains her action by claiming that the black man was
behaving in a threatening way. The reasons given in these explanations were not the
reasons which were actually in play with respect to Roger’s decision and Sylvia’s action,
and they are not supported by evidence, and therefore the explanations are both false and
ill-grounded.

<hs>  Provoked</hs>
  ~~~~~~~~

In the psychological literature there is a recurrent distinction between two types of
confabulation. A confabulation is spontaneous when it is not elicited by questioning, and
it is provoked when it is offered as a response: the person is asked to offer an
explanation for something, and she provides a confabulation (Kopelman, 1999: 197–8;
Hirstein, 2005: 20). Provoked confabulations can occur in people ‘who are fully in
possession of most of their cognitive faculties, and able to respond correctly to all
sorts of requests and questions’ (Hirstein, 2005: 21). In the two cases of confabulation I
considered in the previous section and in many other instances of non-clinical
confabulation, the explanation is likely to be generated as a response to a specific
question, such as ‘Why did you not invite this candidate to interview?’ or ‘Why did you
cross the road?’ The second feature of confabulation then, which is shared by the cases of
Roger and Sylvia, is that they can be provoked as responses to questions.

<hs>  Motivated</hs>
  ~~~~~~~~~

A third feature common to many instances of confabulation is that they involve a
motivational element, which means that they are goal-directed states or processes (Bayne &
Fernandez, 2009). This is something ‘many accounts of confabulation’ have recognised
(Bortolotti & Cox, 2009: 954, see also Zangwill, 1953: 700). This motivational element
might be a causal factor for the explanation’s being provided at all (for example, to
cover a gap in memory, Bonhoeffer, 1901, cited in McKay & Kinsbourne, 2010: 291), or as a
factor with respect to the content an explanation has (Fotopoulou, Conway, & Solms, 2007;
Fotopoulou et al., 2008; Metcalf, Langdon, & Coltheart, 2010). So disagreement with
respect to the role of motivational factors in confabulation concerns whether they play a
role in the very existence of a confabulation, or whether they play a role additionally in
the content of a confabulation. Confabulatory explanations are then, at least in part,
motivated explanations, that is, some pro-attitude plays a role in either the very
formation of a confabulation, or more specifically, the content of a confabulation. We can
distinguish between a motivation to offer an explanation as opposed to no explanation
(type-a), and a motivation to offer an explanation with a specific content as opposed to
an explanation with a different content (type-b). In the non-clinical context of
confabulatory explanations of decisions or actions guided by implicit bias, confabulatory
explanations may be motivated in both senses. In some cases, they allow the person to
avoid the appearance of ignorance or incompetence. In response to a question to which a
person does not know or cannot know the answer, she may confabulate when admitting that
she does not know the answer would be costly. This typically occurs when ‘the provoking
question touches on something people are normally expected to know’ (Hirstein, 2005: 30),
(we might think that someone on a hiring panel ought to be able to give reasons for
rejecting candidates, and someone crossing a road ought to be able to give reasons for so
doing). Thus, confabulatory explanations may protect a person from claiming not to know
why they decided or acted as they did. Equally, there are cases in which the motivational
component plays a role in the very content of the explanation. Perhaps the most obvious
motivational component guiding the content of a confabulation is the desire a subject
might have to maintain coherent beliefs about the self or a good self-concept. It looks
like both kinds of causal work are being done by confabulatory explanations offered in the
cases of Roger and Sylvia. In the first place, the explanation might be motivated by a
desire not to be dumbfounded, or the desire not to fail to offer an explanation at all for
one’s decision or action. In the second place, the content of the explanation might be
motivated by one’s desire not to appear sexist or racist.

<hs>  Filling a gap</hs>
  ~~~~~~~~~~~~~

Related to the last point, and especially with regards to type-a motivation, confabulatory
explanations have been thought to, in some sense, fill a gap. According to the classic
conception of clinical confabulation as a consequence of a memory impairment—that best
applies to the phenomenon when it occurs in the context of amnesia and
dementia—confabulations are ‘stories produced to cover gaps in memory’ (Hirstein, 2005:
32). But confabulation plays a gap-filling role in more cases than those in which there is
a memory deficit (I do not think that Roger and Sylvia offer the explanations they do
because they fail to remember why they acted as they did3). The gap-filling claim needs to
be construed more broadly and not couched only with respect to a gap in memory. We might
instead think of confabulatory explanations as filling gaps ‘at a certain level in the
cognitive system’, insofar as they help produce ‘complete, coherent representations of the
world’ (Hirstein, 2005: 30). In the cases I have given of explanations of actions guided
by implicit bias, the person may not be aware of having a bias, or at the very least, may
not be aware of that bias’s influence, (recall that this is what Gawronski and colleagues
term impact awareness (2006: 486)). This is the gap that might be filled by the
confabulatory explanation. Arguably, explanations of decisions or actions guided by
implicit bias fill a gap which could not be otherwise filled—I will discuss the idea of
alternative explanations being in some sense unavailable to subjects who confabulate later
(Section 4.2).

<hs>  No intention to deceive</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

My talk of a motivational component and of gap-filling may be suggestive of an intention
to deceive (even if it is an intention to deceive oneself) when subjects offer
confabulatory explanations. There is an interesting literature on the potential overlap
between confabulation and self-deception which I cannot address here (see, for example
Bayne & Fernandez, 2009; Hirstein, 2000, 2005; Ramachandran, 1996). For my purposes it
suffices to say that the ‘orthodox position’ is that people who confabulate should not be
understood as lying (Hirstein, 2005: 28), and this follows from there being no intention
to deceive in confabulation.4 This is made very clear in the epistemic concept of
confabulation, according to which a confabulation is ‘a certain type of epistemically ill-
grounded claim that the subject does not know is ill-grounded’ (Hirstein, 2005: 33).
According to this conception, when a person confabulates she offers an ill-grounded claim
and she is not aware of that claim as being ill-grounded, and she does not believe
contrary to it. If a necessary condition on intending to deceive another is that the
deceiver believes contrary to what she avows, then she who confabulates does not so
intend, because she does not recognise her confabulation as epistemically ill-grounded.
People offering confabulatory explanations of decisions or behaviour guided by implicit
bias have no intention to deceive: subjects can lack impact awareness of the operations of
implicit biases, and so it would be strange to understand the subjects in my examples as
seeking to deceive in order to cover up their implicit sexism or racism which is operative
when they act. Given that their attitudes are implicit ones and are not recognised by the
subjects as attitudes they have (or at least, not recognised as attitudes which are
influencing their decisions or behaviour), subjects should not be construed as
intentionally seeking to cover up those attitudes (see Holroyd, 2015, for more discussion
on this point).

<hs>  Do Roger and Sylvia confabulate?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Are the explanations given by Roger and Sylvia genuine cases of confabulation? I have
outlined five features common to confabulation, these are their being false or ill-
grounded, provoked in response to questioning, motivated, filling a gap, and there being
no intention to deceive on the part of the confabulator. In my outline of each of these
features, I have suggested that they are ones which characterise the cases of Roger and
Sylvia. Care needs to be taken though with respect to how the cases of Roger and Sylvia
are described, since under a certain kind of description, Roger and Sylvia are not
confabulating. In the cases as I have described them Roger genuinely (and falsely)
believes that Katie’s CV is of inferior quality, and Sylvia genuinely (and falsely)
believes that the black man is behaving in a threatening way. If this is the
interpretation of the circumstances—that the subjects have false beliefs and base their
decisions and actions upon those beliefs—we would not be in the presence of confabulatory
explanations. Our subjects would be explaining their behaviour by appealing to a belief of
theirs for which the evidence was poor. Under the hypothesis I am currently discussing,
Roger believes that Katie has a worse CV than her male competitors and he offers a true
explanation of his action when he explains why he did not choose to invite her to
interview. His belief about the quality of the CV is not supported by the evidence, but
instead is guided by an implicit bias, the belief is false but the explanation of the
choice is not confabulatory. The explanation is one which is both true and well-grounded.
This is not how I want to understand these cases. Rather, let us ask Roger why he has the
belief that Katie’s CV is of inferior quality. Now Roger claims that he has the belief
because the CV is inferior. Now we are in the presence of confabulatory explanations since
the reason Roger has the belief that the CV is inferior is not because it is, it is rather
because of some implicit bias he has. My cases then ought to be understood as ones in
which the subject is asked to explain why they acted in the way that they did, and they
give an explanation in which they cite what they take to be a fact about the world which
both informs the belief and explains the decision or action. When Roger says that he did
not invite Katie to interview because her CV was inferior he confabulates, because he
cites something which was not efficacious in the making of his decision. This is not to
say that it is sufficient for confabulation that one is wrong about the cause of one’s
belief, and it is for this reason only that Roger’s explanation is a confabulatory one. As
we have seen, Roger’s explanation exhibits many other features typical of confabulatory
explanations. Note also the way the cases were described: these are not cases of explicit
sexism or racism, rather, they are cases of subjects who explicitly take egalitarian
positions, but have implicit biases against certain groups, which guide their decisions or
actions. It is possible (indeed common) for a subject to have no explicit sexist or racist
beliefs and yet still have implicit biases towards these groups. According to the most
common reading of the IAT results, subjects have implicit biases, even though such biases
are not always reflected in explicit judgements.

EPISTEMIC INNOCENCE5THANK YOU TO LISA BORTOLOTTI, WITH WHOM I DEVELOPED THE NOTION OF EPISTEMIC INNOCENCE AS I AM UNDERSTANDING IT HERE (SEE BORTOLOTTI, 2015, FOR AN EXPLANATION OF WHY WE USE THE TERM ‘INNOCENCE’ IN THIS WAY).5
--------------------------------------------------------------------------------

I am interested in the epistemic status of confabulatory explanations of decisions or
actions guided by implicit bias, and whether they have the potential for epistemic
innocence. I will understand the notion of epistemic innocence in the following way: an
epistemically faulty cognition is epistemically innocent if, at a given time, it endows
some significant epistemic benefit (Epistemic Benefit) onto the subject, which could not
be otherwise had, because alternative, less epistemically faulty cognitions are in some
sense unavailable to her at that time (No Alternatives). I will further elucidate the
notion of epistemic innocence in the rest of this section.

<hs>  Which benefits?</hs>
  ~~~~~~~~~~~~~~~

A cognition being epistemically innocent does not imply that that cognition is free from
epistemic faults, perhaps very few cognitions are innocent in that sense. The claim is
only that such cognitions can confer epistemic benefits which are otherwise unavailable,
in some contexts. If confabulatory explanations of the kind I have in mind here have
epistemic benefits, might we be better off to call them epistemically good rather than
epistemically innocent? No, since saying this would be to ignore or deny the obvious
epistemic faults of confabulation. My aim here is to highlight the potential epistemic
benefits of some confabulatory explanations. One way of doing this without polarising the
debate is to claim some sort of inbetween status for confabulations. An ideal agent would
not need to confabulate explanations, but human agents have significant limitations that
lead to confabulatory explanations. Now, this is not always or not entirely a bad thing.
Confabulatory explanations can sometimes play a positive epistemic role.

<hs>  Which unavailability?</hs>
  ~~~~~~~~~~~~~~~~~~~~~

What I mean by unavailable in the No Alternatives condition on epistemic innocence will
differ depending on the kind of cognition under investigation. Here is a first pass at
three ways we might think about the notion of unavailability: alternative cognitions might
be strictly unavailable, motivationally unavailable, or explanatorily unavailable. An
alternative explanation is strictly unavailable if it is based on information that is
opaque to introspection, or otherwise irretrievable. We might understand this sense of
unavailability in terms of alternative cognitions being inaccessible to the subject. For
example, consider the case of a subject with dementia who suffers from severe memory
impairment. She claims to remember going to the beach with her parents that morning, but
the trip she recalls occurred when she was a teenager, sixty years ago. A memory of the
trip which included the correct time at which it took place, or information which would
suggest to the subject that she had made a mistake with respect to the time of the trip,
is inaccessible to her, and so strictly unavailable, due to the severe memory impairment
she suffers as a result of her dementia. An alternative explanation is motivationally
unavailable if it is inhibited or not accessed due to motivational factors. It is
generally agreed upon in the literature that self-deception includes a motivational
element, which makes it a good case to refer to in explicating the notion of motivational
unavailability.6 This motivational element might make less epistemically faulty cognitions
unavailable to the subject. Take the case of the cuckholded husband who self-deceptively
believes that his wife is faithful. Evidence that she is unfaithful may be available to
him (insofar as it is perceptually available—he sees that his wife returns home late,
dishevelled, and uninterested in him), but an alternative cognition, such as the belief
that his wife is having an affair, is motivationally unavailable, due to the husband’s
very strong motivation for it to be the case that his wife is faithful (wishful self-
deception) or for it to be the case that he believes that his wife is faithful (willful
self-deception) (see Van Leeuwen, 2007: 331–2, for further elucidation of the distinction
between wishful and wilful self-deception). An alternative explanation might be
unavailable in a weaker sense, such that it is strictly speaking available for
consideration by the subject, but it is not regarded as a genuine contender. It is
explanatorily unavailable to the subject insofar as it is dismissed due to its apparent
implausibility. For example, a subject may come to have a cognition which explains some
experience she has. If alternative cognitions which might also be candidate explanations
for her experiences are such that they strike her as seriously implausible or
explanatorily inadequate, these alternative cognitions are explanatorily unavailable.
Suppose there are bite marks in my cheese, I hear scratching at night, and my cat is
agitated. I come to the conclusion that I have mice in my house. An alternative
explanation might be that a cheese-eating, cat-irritating, noisy fairy is infiltrating my
home at night. This explanation is not available to me in the sense I have in mind here
due to the incredulity I would feel towards it. It is either not considered by me, or it
is such that I rule it out on grounds of implausibility or poor explanatory power,
relative to the preferred and adopted cognition.

<h>EPISTEMIC INNOCENCE AND CONFABULATORY EXPLANATIONS</h>
--------------------------------------------------

In order for confabulatory explanations of decisions or actions guided by implicit bias to
be epistemically innocent in the way described above, it would need to be the case that
they are epistemically beneficial as per the Epistemic Benefit condition, and that less
epistemically faulty alternative explanations delivering the same epistemic benefit are in
some sense unavailable to the subject at the time, as per the No Alternatives condition.
In this section, I will argue that at least in some cases, confabulatory explanations of
this sort meet both conditions on epistemic innocence.

<hs>  Epistemic benefit and confabulatory explanations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As in my earlier characterisation, confabulatory explanations are epistemically poor
insofar as they are false, or at the very least ill-grounded. Here I want to focus on
whether confabulatory explanations have any epistemic benefits notwithstanding their
epistemic faults. I claim that there are two potential epistemic benefits: in the context
of epistemically imperfect agents, confabulatory explanations of decisions or actions
guided by implicit bias may maximise the acquisition of true beliefs in the long run by
filling an explanatory gap, and they may help the epistemic agent maintain consistency
among her cognitions. Sometimes confabulations will be epistemically innocent and overall
good, for example, viewed from a consequentialist framework this might be when the
benefits outweigh the costs. In other cases, they will be epistemically innocent, and
epistemically bad, from the same framework, as when such benefits are counteracted by the
epistemic costs of confabulation. Importantly, epistemic innocence does not stand or fall
with epistemic goodness.

        Maximising the future acquisition of true beliefs by filling explanatory gaps

        Here I will argue that there are epistemic benefits in providing a confabulatory
        explanation to the question ‘Why did you do this?’ This is because filling an
        explanatory gap allows people to consider their reasons for their actions which
        may otherwise remain unexplored and unchallenged. Earlier I suggested that one of
        the characteristics of confabulatory explanations was their filling a gap, where
        this was to be understood not just in terms of memory gaps, but rather, more
        broadly. The performance of the function of gap filling may be pragmatically
        beneficial in different ways depending on the case. In the non-clinical case,
        explanations of decisions or actions guided by implicit bias may fill a gap which
        gives the illusion of competence, and prevents people from having to claim that
        they do not know or cannot remember why they formed an attitude, made a choice, or
        performed an action (see Dalla Barba, 1993, cited in Van Damme & d’Ydewalle, 2010:
        221). McKay and Kinsbourne identify two types of motivational account which apply
        to confabulations. According to the first, subjects who confabulate offer the
        explanations they do ‘in order to conceal embarrassing gaps in their memories’
        (McKay & Kinsbourne, 2010: 291). McKay and Kinsbourne reject this account as one
        having ‘very little evidence’ in support of it, and I have already said that
        confabulations are doing more than filling gaps in memory. We might understand
        this kind of account more broadly though, as one which claims that people who
        confabulate do so in order to conceal gaps more generally (for example,
        explanatory gaps regarding why they decided or acted in a certain way). If this
        kind of account were correct, at least for confabulatory explanations in the non-
        clinical population, such explanations could be seen as conferring a pragmatic
        benefit with respect to the prevention of embarrassment which may have indirect
        positive epistemic consequences (perhaps my not suffering the discomfort of
        embarrassment might mean I am more willing and able to investigate my environment
        and participate in the exchange of information). According to the second type of
        motivational account, confabulations are ‘purposive constructions that function to
        embellish the situation of the patient’, meaning that confabulatory explanations
        are compensatory in virtue of their content (not merely their very existence)
        (McKay & Kinsbourne, 2010: 291). If the second type of account were right, there
        would be additional pragmatic benefits, due to the confabulation enhancing the
        concept of the self or the situation of the person, and potentially enhancing
        self-confidence and wellbeing. This matches with my description of the cases Roger
        and Sylvia. But is there room for epistemic, as well as pragmatic, benefits? My
        claim here is that by having an explanation and endorsing a position, one can
        receive feedback and the problematic things that are believed (I did not invite
        Katie to interview because her CV was of poorer quality or I crossed the road
        because the black man was behaving in a threatening way) become available to
        introspective reflection, and open to feedback and revision. Jeanette Kennett and
        Cordelia Fine argue that when we become aware of our biases and are committed to
        not being prejudiced, then we can counteract or compensate for our biases and
        achieve better consistency between explicit attitudes and behaviour: research
        demonstrates that when people become aware that they have a tendency to make
        certain types of judgments in a biased way (for example, due to the activation of
        negative stereotypes about a racial group) then, if they are motivated to be
        unprejudiced, they will effortfully over-ride their intuitively-based judgments,
        so long as they have the cognitive resources to do so. If becoming aware of our
        biases and being motivated to not be prejudiced can lead to trying to overcome the
        judgements we make on the basis of bias, confabulatory explanations may be
        indirectly epistemically beneficial, insofar as they might contribute to our
        becoming aware of our biases. We might think that a much better way to become
        aware of our biases would be to fail to offer an explanation at all. In Roger’s
        case for example, if he claimed not to know why he did not invite Katie to
        interview, this might be a better way of encouraging him to reflect on what was
        guiding that decision. However, I will argue later (Section 4.2) that this
        dumbfounding response is unavailable to Roger, and so the confabulatory
        explanation here confers a benefit which is not otherwise obtainable. Related to
        this, research has shown that individuals who avow low prejudice but recognise
        that they are prone to behaviour which is inconsistent with this—so-called ‘low-
        prejudice discrepancy-prone’ subjects—are more likely to feel guilt when
        expressing biased behaviour (as measured by the IAT for race), and more likely to
        interpret such behaviour as being related to race factors (Monteith, Voils, &
        Ashburn-Nardo, 2001: 411). Speculatively, if subjects become aware that they are
        discrepancy-prone, the guilt felt when expressing biased behaviour, and their
        interpreting it in this way, might be instrumental in seeking to achieve better
        consistency between their explicit attitudes and their behaviour. There are
        reasons to think such awareness is possible. For example, in a study looking at
        the relationship between self-report scores on the Modern Racism Scale (MRS) and
        implicit racial attitudes, Jason Nier found that: when participants believed their
        ‘true attitudes’ were being accurately assessed, there was a significant
        relationship between an implicit measure of racial attitudes (the IAT) and an
        explicit measure of racial attitudes (the MRS). When participants did not believe
        that their self-reported explicit attitudes could be accurately corroborated with
        an implicit measure, there was no association between implicit and explicit
        attitudes. One way to become aware of our biases is to observe our own behaviour
        (see Holroyd, 2015) compare them with our explanation of our actions, and identify
        discrepancies. Giving reasons (even confabulatory ones) contributes to becoming
        aware of one’s own attitudes (and conflicts in attitudes), priorities and values
        and offers people the opportunity to construct a coherent narrative of themselves
        where behaviour aligns with explicit commitments as opposed to implicit biases
        (Bortolotti, 2009). By reporting a false explanation, we make some (confabulatory)
        explanation for our decisions or actions available, and we may initiate a process
        by which we acquire a new true belief, whereas if we did not have any explanation
        to offer we may have been stuck with an implicit bias that is not detected and
        does not get challenged. The flip side to this benefit is that offering a
        confabulatory explanation might serve to mask the discriminatory nature of the
        behaviour, which might otherwise be observed if the explanation were an accurate
        one or one indicating dumbfounding. I will argue later though that alternative
        explanations such as these are unavailable to the person confabulating, given
        certain other conditions (Section 4.2). I do not deny the epistemic costs of the
        confabulatory explanation—that it might mask the discriminatory nature of the
        behaviour being one such cost—the idea is only that there may also be some
        epistemic benefits, including the confabulatory explanation initiating a process
        by which the subject acquires a new true belief. So confabulatory explanations are
        epistemically beneficial insofar as in offering them as explanations they become
        open to attack. This might then start a thinking process, where I might end up
        with a less epistemically faulty explanation. So the confabulation is
        epistemically good insofar as it acts as an enabling condition for further
        reflection. Discussing and justifying one’s decisions or actions, specifically,
        reflecting on the potential role played by stereotypes can reduce the effects of
        such stereotypes (Saul, 2012a: 259). This does not require the subject to have any
        kind of conscious control over her implicit biases, the idea is rather that when
        she engages in this kind of discussion, it ‘may help to flag up at least some
        cases in which there is no defensible reason for a judgment. And some of these may
        be cases of bias’ (Saul, 2012a: 259). This can be epistemically beneficial insofar
        as if one discovers that the decision or action is not carried out for a
        defensible reason this might initiate a process whereby the subject comes closer
        to a true explanation of their decision or action. The subject may come to have
        impact awareness of their bias, and seek to reduce its influence which might have
        positive epistemic consequences. One worry is that the benefit I have outlined is
        one had by a lot of things, and that now my just saying anything false is
        epistemically beneficial insofar as it might prompt someone to suggest I think
        again, which might in turn bring about my doing so, and then I might come to have
        a more epistemically worthy belief. There are two things to say in response to
        this kind of worry. Firstly, this is an epistemic benefit which is had in a
        context in which alternatives are not available, whereas not all cases of avowed
        false belief are going to be cases where less epistemically faulty cognitions are
        unavailable. So though avowing false beliefs might be epistemically beneficial,
        the context in which this benefit comes is important for judgements of epistemic
        innocence. Secondly, it is not on this benefit alone that I suggest that
        confabulatory explanations of decisions or actions guided by implicit bias are
        epistemically beneficial.

        <hss>Maintaining consistency</hss>

        Here I will argue that there are epistemic benefits in providing a confabulatory
        explanation in response to a question such as ‘Why did you do this?’ because it
        allows one to maintain a coherent self-concept. The epistemic benefit here comes
        from the explanation’s having a particular content, and so this maintaining of
        consistency is only had by explanations with certain contents. Not having
        unexplained gaps with respect to one’s decisions or actions may be instrumental to
        maintaining a coherent set of beliefs about oneself. In the case of implicit bias,
        Roger has to make consistent his belief that he is egalitarian, and his belief
        that he did not invite Katie to interview. Similarly, Sylvia has to make
        consistent her belief that she is egalitarian, and her belief that she crossed the
        road when she saw a black man. Given our subjects’ lack of impact awareness that
        an implicit bias is playing a role here, their confabulatory explanations maintain
        consistency between their beliefs about the values they are committed to, and
        their beliefs that they made some decision or performed some action.7 In addition
        to this, the explanation may fill a gap in the sense that it provides a reason for
        the action that is more desirable than the (true) alternative. In the
        confabulatory explanations of actions driven by implicit bias, Roger’s decision
        not to invite Katie to interview, or Sylvia’s action of crossing the road to avoid
        a black man, is explained by appeal to something external (the inferior quality of
        Katie’s CV, and the threatening behaviour of the black man, respectively). The
        subjects make an attribution error but in doing so they maintain their positive
        self-concept. In the true explanations, the action would be caused by something
        internal, a bias against women, and a bias against black people, respectively. The
        limitations of this potential epistemic benefit lie in the fact that the
        confabulation achieves consistency at the expense of truth. This may lead to a
        revision of the self-image such that in confabulation, ‘coherence trumps
        correspondence’ (Bortolotti & Cox, 2009: 962).8 We might wonder then why
        consistency here should be considered as epistemically beneficial, might it make
        the acquisition of true beliefs less likely in the long run? If we conceive of
        consistency being a benefit only when it tends towards truth or when it adds to
        the overall coherence of belief, perhaps the maintaining of consistency had here
        is not epistemically beneficial. For those who feel the force of this worry I say
        this: at the very least the apparent maintaining of consistency might be
        indirectly epistemically beneficial. Not experiencing an inconsistency might have
        indirect epistemic consequences. Just like the prevention of embarrassment (see
        Section 4.1.1), perhaps by not suffering the discomfort which an inconsistent set
        of cognitions might bring, I might be more willing and able to investigate my
        environment and participate in the exchange of information.

<hs>  No alternatives and confabulatory explanations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

I have argued that confabulatory explanations can have epistemic benefits. Here I will
argue that such benefits are only attainable via the confabulatory explanation, because
less epistemically faulty cognitions which deliver the same epistemic benefits are in some
sense unavailable to the subject who confabulates. We have seen that confabulatory
explanations of decisions or actions guided by implicit bias can be sincerely and
confidently avowed, and offered with no intention to deceive on the part of the subject
confabulating. Given this, as well as the third-person implausibility of the explanations
offered, it looks like subjects who confabulate do not recognise the poor epistemic status
of the explanations they give. This claim is supported further by accounts of
confabulation which postulate a deficit in the confabulator’s ability to evaluate
hypotheses. On Hirstein’s view, two errors are involved in confabulation. The first is the
creation of a false response, and the second is a failure by the subject to ‘check,
examine it and recognize its falsity’ (Hirstein, 2005: 15). The thought is that a non-
confabulator might have the first error, the generation of a false response, but they
would recognise the falsity or absurdity of it. So the person who confabulates ‘should
either not have created the false response or, having created it, should have censored or
corrected it’ (Hirstein, 2005: 15). The mechanisms by which this failure is achieved is
suggested by Hirstein to result from the fact that the ability to construct plausible
responses and the ability to verify such responses are separate in the brain, and
confabulators retain the first ability, but the second has been compromised by brain
damage (Hirstein, 2005: 16–7). My focus has been on confabulation as it occurs in the non-
clinical population, specifically, in explanations of actions guided by implicit bias.
Hirstein states that young children have been reported to confabulate when reporting on
their (false) memories (see for example Ackil & Zaragoza, 1998), and subjects of hypnosis
can confabulate (Hirstein, 2005: 16), as well as ordinary people in experimental settings
(for example, in choice blindness experiments, see Hall & Johansson, 2008). In these
cases, people do not have the kind of brain damage which would make the particulars of
Hirstein’s account plausible in such a way that it has general application across all
cases of confabulation. The etiology of confabulatory explanations may not be shared
across the board; we cannot give an account which cites brain damage when we are
explaining why non-clinical subjects offer confabulatory explanations in certain contexts.
What we can say in general though is that—for whatever reason—when people confabulate,
they do not experience doubt, which results in a failure to check on the plausibility of
hypotheses when they are occur. Perhaps this failure is realised in different ways across
cases. In a case of explanations of decisions or actions guided by implicit bias, for
example, the failure might be caused by some motivational component of the agent’s
cognitive economy. The motivational component of explanations of actions guided by
implicit bias is straightforward to spell out. In terms of type-a motivation (that is,
motivation to offer an explanation as opposed to no explanation), subjects are asked to
justify their decision or action but because their decision or action was guided by an
implicit bias, the true causal explanation of their decision or action is not strictly
available to them (unless they are well-read in psychology and they suspect that their
decision or action may be influenced at least to some extent by biases they are not aware
of). As we have seen, this lack of impact awareness with respect to implicit attitudes is
a distinguishing feature of them (Gawronski et al., 2006: 486). Given that failing to give
reasons for one’s decision or action may be costly, such subjects have a reason to provide
an explanation. In terms of type-b motivation (that is, motivation to offer an explanation
with a particular content), our subjects are motivated to think of themselves as persons
of egalitarian persuasion, who do not have gender or racial prejudices. Thus, it is easy
to see that the explanations they offer for their decisions and actions are influenced by
motivational factors. We might think that motivational factors are playing a role in the
content of the explanation offered by running the appropriate counterfactual: if Roger
were explicitly sexist or Sylvia were explicitly racist, and the subjects were not ashamed
by this or did not have the desire to conceal such prejudices, and they decided or acted
in the above ways and were asked for explanations of their decisions or actions, we might
expect Roger to claim that he did not invite Katie to interview because women make for bad
colleagues, and Sylvia to claim that she crossed the road to avoid the black man because
black men are dangerous. If a subject’s decision or action is guided by an implicit bias
pertaining to some group, there is a sense in which explanations citing that bias are
unavailable to her, given certain other conditions. Such other conditions may include the
subject considering herself a person who does not hold sexist or racist prejudices, or at
the very least having the desire to be perceived as such by her peers: The belief that
one’s actions are implicitly biased, and other implied beliefs about one’s role in
sustaining patterns of discrimination, are clearly beliefs that, for a range of reasons,
agents might be motivated not to confront. Conversely, the belief that one’s actions are
consistent with one’s moral ideals (of non-discrimination, of being evidence sensitive and
unbiased) is one that agents are motivated to maintain. This kind of story is supported
empirically. In their review article, Gawronski and colleagues found evidence that
correlations between self-reported attitudes and indirect attitudes are ‘often higher when
the impact of motivational factors is controlled’ (Gawronski et al., 2006: 489).
Confabulatory explanations of actions driven by implicit bias are sometimes such that less
epistemically faulty alternative cognitions are motivationally unavailable to the subject
insofar as they cite implicit biases against certain groups, biases which she is motivated
not to recognise in herself or have others recognise in her.9 Thinking in terms of one’s
attitudes being regulated for truth, we might say that the truth regulation present in the
cases when a motivational component is in play is sufficiently different from the truth
regulation present in cases where motivational factors are not playing a role, such that
in the former case, the content of the explanation offered is distorted away from a true
explanation. Once the subject is motivated to think of herself as someone who does not
have sexist or racist attitudes, or motivated for other people to not think of her in that
way, the regulation for truth in her belief formation with respect to her explanation for
her decision or action is weakened. We might think then, that without the motivational
component, the explanation offered for decisions and actions guided by implicit biases,
would not be confabulatory, since studies have shown that controlling for the motivational
components results in a higher correlation of explicit and implicit attitudes (Gawronski
et al., 2006: 489). What cases of confabulation share is that something is going on such
that where doubt should be cast on the confabulatory story, it is not. My claim is that
whatever this component is—whether it has a neurological basis (as in many clinical
cases), or a motivational one—it indicates that other, less epistemically faulty
cognitions are unavailable to the subject. When an explanation is presented to the subject
upon which doubt is not cast, alternative cognitions are unavailable insofar as the
confidence which comes with the confabulation, and the motivational factors which are
driving both the presence and content of it, close off alternatives such that they are not
sought or entertained.

<h>CONCLUSIONS</h>
-----------

In this paper I characterised confabulation in terms of five features which are common to
them: their being false, their being offered in response to a question, their involving a
motivational component, their filling a gap, and their being produced and avowed without
any intention to deceive. After outlining two possible cases of confabulatory explanations
of decisions or actions guided by implicit bias, I introduced the notion of epistemic
innocence. This notion was intended to capture those cognitions which deliver some
epistemic benefit which could not have been otherwise had in virtue of alternative
cognitions being in some sense unavailable. I then argued that confabulatory explanations
of this sort have the potential for epistemic innocence. So what should we conclude from
these considerations about the epistemic status of confabulatory explanations in the non-
clinical population? What might my analysis mean for the epistemic evaluation of non-
clinical confabulation, specifically confabulatory explanations of decisions and actions
guided by implicit bias? As I noted earlier, epistemic innocence does not track epistemic
goodness. The benefits I identified though should not be neglected. These were filling an
explanatory gap which cannot be otherwise filled, which may lead to the acquisition and
retention of true beliefs or knowledge, as well as helping to maintain consistency between
a subject’s other beliefs (which might be directly or indirectly epistemically
beneficial). In some cases, less epistemically faulty cognitions with the same epistemic
benefit are in some sense unavailable to the subject, and so the confabulatory explanation
delivers some epistemic benefit which is otherwise unobtainable. I conclude then that at
least in some cases, confabulatory explanations of decisions or actions guided by implicit
bias can be epistemically innocent, and that epistemic evaluation of confabulatory
explanations ought to take into account the context in which the cognition occurs. If we
do this we are able to provide a richer account of the epistemic status of confabulatory
explanations, and we can resist the view that pragmatic benefits come at the expense of
epistemic ones. If we focus on the context in which confabulatory explanations occur, and
their potential epistemic benefits, we can give a richer epistemic evaluation of them.


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<ART>Impulsivity and compulsivity are differentially associated with automaticity and routine on the Creature of Habit Scale
================================================================================

Authors: Karen D. Ersche, Laetitia H.E. Ward, Tsen Vei Lim, Roderick J. Lumsden, Steven J. Sawiak, Trevor W. Robbins, Jan Stochl
DOI: 10.1016/j.paid.2019.07.003
Year: 2019
ASJC codes: 3200
Keywords: Frequency, Goal-directed, Mediation, Personality trait, Questionnaire, Suppression

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Habits may develop when meaningful action patterns are frequently repeated in a stable environment. We measured the differing tendencies of people to form habits in a population sample of n = 533 using the Creature of Habit Scale (COHS). We confirmed the high reliability of the two latent factors measured by the COHS, automaticity and routines. Whilst automatic behaviours are triggered by context and do not serve a particular purpose or goal, routines often have purpose, and because they have been performed so often in a given context, they become automatic only after their action sequence has been activated. We found that both types of habitual behaviours are influenced by the frequency of their occurrence and they are differentially influenced by personality traits. Compulsive personality is associated with an increase in both aspects of habitual tendency, whereas impulsivity is linked with increased automaticity, but reduced routine behaviours. Our findings provide further evidence that the COHS is a useful tool for understanding habitual tendencies in the general population and may inform the development of therapeutic strategies that capitalise on functional habits and help to treat dysfunctional ones.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Habits are repetitive, meaningful actions in our daily lives, which often go unnoticed due
to their automatic nature (Robbins & Costa, 2017). The scientific interest in habits has
increased in recent years, not least because habits can make behaviour either highly
efficient or severely dysfunctional and distressing. Understanding the factors that
influence habit formation for the better and for the worse may thus have implications both
for enhancing performance when habits are to our benefit, and developing treatments for
habits that have become maladaptive. People also differ in their readiness to form and
engage in habits in their daily lives, which we refer to as habitual tendencies. There is
widespread agreement that habits form over time when behaviour is repeated regularly in
the same context. Meanwhile, control over this behaviour gradually shifts from being
guided by intentions to being automatically triggered by cues in the environment (see Wood
& Runger, 2016). An example would be a person's tendency to take their shoes off
automatically by the front door when returning from work. Importantly, habits are not
restricted to single actions but may also involve sequences of actions, as exemplified by
a night time routine to always prepare one's clothes for the next day before going to bed.
Although this deferral of control to environmental stimuli can make habits highly
functional by providing structure, reducing uncertainty and freeing up cognitive
resources, it also makes behaviour less flexible, since much more effort is required to
break or adjust a habit (Wood & Runger, 2016). In people with problems of regulatory
control, habits may run the risk of spiralling out of control. A prime example is
obsessive-compulsive disorder (OCD), where rather mundane habitual behaviour patterns such
as washing one's hands or locking the front door when leaving the house become problematic
for the afflicted individual. Patients with OCD find themselves unable to stop performing
certain routines, even when they become dysfunctional and negatively affect their lives
(American Psychiatric Association, 2013). Another example is drug addiction, where
individuals lose control over the initiation, amount and duration of their habitual drug
use, and pursue their drug-taking routines even in the face of extremely adverse
consequences (American Psychiatric Association, 2013). Experimental research in both
animals and humans has been trying to elucidate the mechanisms underlying habit formation,
and to identify factors that may precipitate the development of habits. External factors
such as exposure to stimulant drugs (Corbit, Chieng, & Balleine, 2014; Ersche et al.,
2016; Gourley, Olevska, Gordon, & Taylor, 2013; Nelson & Killcross, 2006), excessive
training (Colwill & Triola, 2002; Holland, 2004; Thrailkill, Trask, Vidal, Alcala, &
Bouton, 2018) and stress (Dias-Ferreira et al., 2009; Schwabe & Wolf, 2009) have all been
shown to facilitate the formation of habits. Thus, behaviour that is regularly performed
in a state of either acute or chronic stress is more prone to become habitual and
controlled by environmental stimuli (Dias-Ferreira et al., 2009). For example, individuals
with a history of stressful life events who also use drugs recreationally, are highly
likely to develop a drug-taking habit when they use drugs regularly in the same context
(e.g. always in a club on a Friday night). Even if these individuals do not have the
intention to use drugs, going to a club on a Friday night increases the likelihood that
they will be using drugs that night. As habitual behaviour is triggered by the context, it
is the environment that prompts their drug use, overriding their intentions. Habitual drug
use does not, however, equate to addiction, but internal factors such as impulsive
personality traits have been shown to precipitate – at least in animal models of addiction
– the transition of initially adaptive habits into maladaptive ones (Belin, Mar, Dalley,
Robbins, & Everitt, 2008). Impulsive individuals are thus at risk of their drug-taking
habits spiralling out of control and becoming compulsive. This means that they may
continue using drugs even if this poses an acute threat to their health, professional or
social life, such as by risking myocardial infarction, job loss, or relationship
breakdown. The exact mechanism underlying the transition from functional to dysfunctional
habits is, however, still unclear, but as there is a great need for effective treatments
for individuals who have lost control over their habits, as well as for strategies to
promote habit formation in individuals affected by cognitive decline or dementia who
struggle to manage their daily lives, the interest in understanding habitual behaviours
will continue to increase. Healthy individuals in the general population who describe
themselves as ‘creatures of habit’ are therefore of particular interest for research as
they show an increased propensity to develop habits without them becoming pathological. We
recently developed the Creature of Habit Scale (COHS, Ersche, Lim, Ward, Robbins, &
Stochl, 2017) to measure individual variation in habitual tendencies in the general
population. We confirmed modulatory effects of stimulant drug use and life adversity on
habitual tendencies, as assessed by the COHS. We also identified positive relationships
between compulsivity and habitual tendencies, but at the time we did not examine
relationships with impulsivity (Ersche et al., 2017). Impulsivity and compulsivity are two
personality traits associated with a lack of control over behaviour, which might explain
why in some people automatic habits risk spiralling out of control. Whilst impulsivity
reflects a failure to inhibit the initiation of behaviour, compulsivity characterizes a
failure to stop an ongoing behaviour that is becoming inappropriate to the situation (see
Robbins, Gillan, Smith, de Wit, & Ersche, 2012). Although both constructs reflect
distinctly different deficiencies in the regulatory process, they may occur together. We
also did not investigate at the time the influence of participants' prior experience with
each situation referred to in the questionnaire items. This is a fair concern given that
habits develop gradually through associative learning and repetition (Wood & Neal, 2007),
suggesting that the more often action patterns are performed in a given context, the
greater the likelihood of the context triggering the actions automatically irrespective of
the goal (Verplanken & Orbell, 2003). In the aforementioned example of drug-taking, it
would be important to know whether it really matters how often people take drugs before
their drug use becomes habitual, or whether predisposing personality factors that
precipitate the development of habits are more important. In experimental settings,
overtraining of an instrumental action is commonly used to induce stimulus-response habits
(Adams & Dickinson, 1981; de Wit & Dickinson, 2009; Tricomi, Balleine, & O'Doherty, 2009).
However, whilst in animal models the extent of training seems to be directly related to
the predominance of the stimulus-response habit (Dickinson, 1985), such a relationship
does not seem to hold for humans, according to the findings of experimental work (for
review de Wit et al., 2018). It is therefore conceivable that the strength of human habits
is not proportional to the extent of prior practice. The aim of the present study was
therefore to assess the extent to which the self-reported frequencies with which habitual
actions have been performed accounts for habitual tendencies, as assessed by the COHS. We
also aimed to investigate the effects of impulsivity and compulsivity on habitual
tendencies in daily life. As the COHS is a relatively new measure, we used the opportunity
to re-evaluate its psychometric properties in this new sample.

<hs>  Sample</hs>
  ~~~~~~

We recruited study participants through the online platform Amazon MTurk to examine
variations in regular behaviours, since this platform has been regarded as suitable for
obtaining data from the general population (Mortensen & Hughes, 2018). Participation
requirements were a minimum age of 18 years and current residency within the United States
of America. There were no restrictions with respect to gender, ethnicity or employment
status. We also collected background information, including ethnicity, native language,
education level, and employment status. A total of 565 participants completed the study,
but data of 32 participants (6%) had to be excluded post hoc due to invalid responses or
inattentive responding [assessed through recommendations by Meade & Craig, 2012]. Excluded
individuals did not differ from the remaining sample on any demographic variable. The
final sample included 533 participants with a mean age of 36.8 years [±10.8 standard
deviation (SD), age range 18–71 years]. The sample was almost evenly split between male
(50.8%) and female (49.2%) participants, of whom 81% identified as Caucasian, 9% as
African American, 4% as Asian, 4% as Hispanic, and 2% as Multiracial. The overwhelming
majority of participants were native English speakers (99%), who were at the time of the
study in full-time employment (70%) [15% in part-time employment, 13% not in paid work,
and 2% studying].

<hs>  Procedures</hs>
  ~~~~~~~~~~

The study was approved by the School of Biological Sciences Research Ethics Committee
(PRE.2015.124; PI: KD Ersche). Participants received $3.00 for the completion of the
study, which included the assessment of functional habits using the COHS questionnaire
(Ersche et al., 2017), which includes 27 statements to which participants indicate their
level of agreement on a 5-point Likert scale, ranging from strongly disagree (1) to
strongly agree (5). Once participants completed the COHS, they were asked to indicate how
often they engage in the behaviour described by each item by selecting one of the
following response options: never, once a month, twice a month, three times a month, once
a week, twice a week, three times a week, four times a week, five times a week, six times
a week, once a day, twice a day, three times a day, four times a day, five times a day, or
more than five times a day. These responses were then coded respectively from 0 (never) to
15 (five times a day). This fine-grained scale was deliberately selected to capture the
wide spread of individual lifestyles as it had been previously used to quantify habitual
behaviours (Verplanken & Orbell, 2003). In order to determine participants' levels of
trait impulsivity, we administered the Barratt Impulsiveness Scale (BIS-11, Patton,
Stanford, & Barratt, 1995). The BIS-11 is a widely-used 30-item questionnaire that
measures impulsive personality traits in three dimensions: attention (inattention and
cognitive instability), motor behaviour (spontaneous actions), and non-planning (lack of
forethought). As a personality trait, impulsivity covers the spectrum from normal to
maladaptive behaviour, and it can be assessed using the same tool in both healthy people
and patients. The following cut-off scores have been suggested to differentiate variation
in trait-impulsivity: BIS-11 total scores between 52 and 71 are indicative of the normal
range of impulsivity (n = 296, 56%), scores below 52 reflect individuals who are extremely
over-controlled (n = 176, 33%), and scores above 72 signify highly impulsive individuals
(n = 61, 11%) (see Stanford et al., 2009). For the assessment of compulsive tendencies, we
administered the Obsessive-Compulsive Inventory–Revised (OCI-R, Foa et al., 2002), which
requires participants to rate 18 common obsessive-compulsive symptoms in terms of the
degree to which they have been bothered or distressed by them in the past month on a
5-point scale, ranging from not at all (0) to extremely (4). Whilst subclinical levels of
obsessive-compulsive symptoms are common in the general population (Sher, Martin, Raskin,
& Perrigo, 1991), an OCI-R score of 21 or more suggests obsessive-compulsive symptoms of
clinical severity (Foa et al., 2002). In the present sample, the vast majority of
participants (n = 425, 80%) scored within the normal range, whilst the scores of 20% of
participants (n = 108) pointed toward particularly high levels of compulsivity.

<hs>  Factor structure of the Creature of Habit Scale (COHS)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We used confirmatory factor analysis to verify that the COHS structure consists of two
latent factors (automaticity and routine) as reported in our previous study (Ersche et
al., 2017). Means and variances adjusted Weighted Least Squares (WLSMV) were used as
estimators in all presented models. Fit was evaluated using traditional indices such as
Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI) and Tucker-
Lewis Index (TLI). Reliability of subscales was assessed by McDonald's omega (McDonald,
1999), and for reasons of convention, we also computed Cronbach's alpha (Cronbach, 1951).
We extended our factor analytic model by regressing each COHS item onto the corresponding
frequency item. The conceptual path diagram of this model is shown in Fig. 1. The
rationale for this approach was two-fold: firstly, it allowed us to quantify the influence
of frequency on COHS items (by using difference in R-squares of COHS items between
frequency-adjusted and non-adjusted factor analytic models). Secondly, we evaluated
whether the constructs of automaticity and routine hold whilst taking into account the
frequency with which participants previously engaged in these behaviours.

<hs>  Relationship between impulsivity and compulsivity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We further extended the CFA model by including self-reported impulsivity (BIS-11) and
compulsivity (OCI-R) levels as predictors of the latent factors for automaticity and
routine. We used participants' individual responses on the COHS without any adjustments
for frequency. Our aim was to investigate how levels of impulsivity and compulsivity
relate to participants' responses with respect to automaticity and routine. We estimated
the models using the statistical software Mplus, version 8 (Muthén & Muthén, 2018) and
standardized the results. Solely for descriptive purposes, we divided the sample into
three subgroups reflecting the three categories of impulsivity, as measured by the BIS-11.
For illustrative purposes only, we compared these subgroups with respect to compulsivity
(OCI-R) and habitual tendencies (COHS automaticity and routine) using the Kruskal-Wallis
and the Jonckheere's trend tests to identify differences and trends respectively (Fig. 2).

<hs>  Factor structure of the Creature of Habit Scale (COHS)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The two-factor structure of the COHS fitted the data well (Chi-square(df) = 1169(323), p
≤0.001, RMSEA = 0.070, 90%CI for RMSEA = (0.066, 0.075), CFI = 0.977, TLI = 0.975),
supporting the notion of automaticity and routine being two subscales of COHS. Both
factors were also moderately correlated with each other (r = 0.296, p < 0.001). The
loading of both factors was high, indicating high factorial validity of items. Likewise,
the reliability of the coefficients for both factors was high as well, i.e. COHS routine
(Cronbach's alpha: 0.90; McDonald's omega: 0.94) and COHS automaticity (Cronbach's alpha:
0.87; McDonald's omega: 0.92), providing support for satisfactory measurement precision of
both subscales (Fig. 3).

<hs>  The influence of frequency on the COHS scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The inclusion of the frequency ratings in the model also fitted the data well (RMSEA =
0.032, CFI = 0.93, TLI = 0.93). In this model, factor loadings were adjusted for the
influence of frequency ratings. Model estimates are shown in Table 1. In brief, the
loadings were smaller compared to the model without frequency, but remained high enough to
support the existence of two underlying factors. This suggests that habits, as
conceptualised in the COHS, cannot be fully explained by how frequently the corresponding
activities have previously been carried out. Standardized regression coefficients
(adjusted for relationships between items and the corresponding factors) between the COHS
items and the corresponding frequency ratings ranged from 0.09 to 0.65. Except item 13 (I
rely on what is tried and tested rather than exploring something new.), all COHS items
were statistically significant, suggesting that participants' responses can be partially,
but not fully, explained by the self-reported frequency with which the behaviour in
question has been repeated. The average difference between R-squares for frequency-
adjusted and non-adjusted factor models was 0.15 for automaticity items and 0.11 for
routine items, suggesting that frequency explains slightly more variance for automaticity
than for routine.

<hs>  The effects of deficient regulatory control on habitual tendencies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fig. 4 depicts the model we used to evaluate the effects of insufficient regulatory
control, as reflected by self-reported measures of impulsivity and compulsivity. All
factor loadings, regressions and correlations included in this model were statistically
significant (all p-values <0.001). Automaticity was positively related to both impulsivity
and compulsivity, suggesting that participants with higher levels of impulsivity and/or
compulsivity are more likely to report increased tendencies for automaticity. It is
noteworthy that the effect of impulsivity (β = 0.345) on automaticity was larger than the
effect of compulsivity (β = 0.155). For routine behaviours, we observed relationships of
approximately the same magnitude but of different directions with respect to impulsivity
and compulsivity (βimpulsivity = −0.270 versus βcompulsivity = 0.273). This may indicate
that more compulsive individuals are more prone to routine behaviours. This effect is,
however, attenuated in individuals who are also impulsive, as impulsivity prevents the
occurrence of routines.

<h>DISCUSSION</h>
----------

Habitual responses are part of everyday life, but the propensity to form habits differs
substantially across individuals. Here we provide evidence for the validity of the two-
factor model underlying the COHS for assessing habitual tendencies in the general
population. We further confirm that the COHS is consistent with the theoretical concept of
habits, which explains the formation of habits through a process of context-dependent
repetition (Robbins & Costa, 2017; Wood & Runger, 2016). Both scales of the COHS were
significantly influenced by the frequency of past behaviour but, importantly, they were
not fully explained by it. Our findings thus not only concur with prior experimental work
in humans (de Wit et al., 2018), they also have important implications for the use of the
COHS, making it a potentially useful psychometric instrument for investigating habitual
tendencies in the general population. Our data further suggest that habitual tendencies
are related to personality traits, specifically those that characterise an individual's
disposition in regulating behaviour. Whereas both impulsivity and compulsivity were
positively related to automaticity, they had conflicting associations with the tendency to
routine. Impulsivity was negatively associated with routine behaviours, perhaps because of
impaired behavioural regulation with respect to timing. By contrast, compulsivity, perhaps
unsurprisingly, was positively associated with both routine and automaticity.

<hs>  Frequency of past behaviour and habitual tendencies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There is widespread agreement that habit formation is a process, rather than an event,
which implies that the repetition of behaviour is to some degree necessary for it to
become habitual. This notion is also reflected in our data suggesting that habits are
dependent on repetition but are not fully explained by it. What may seem self-evident has,
however, not always been seen in this way. A decade ago, habits were understood as a
combination of both frequency (as defined by repetition) and automaticity (as defined by a
lack of control and awareness) (Verplanken & Orbell, 2003). Whilst repetition was deemed
critical in the early stages of habit formation, automaticity was thought to play a more
prominent role in the final stages of habit formation by implicitly ensuring that
behaviour will be repeated once the habitual response has been established (Gardner, 2012;
Verplanken, 2006). Clearly, repetition of behaviour through practice is needed for habit
formation, but well-practised behaviours are not necessarily habits. Our two-step approach
of composing the COHS questionnaire, first to select items of sufficiently general nature,
and subsequently to collect frequency information for each of them, has allowed us to
control statistically for the effects of repetition. As this study shows, both COHS scales
clearly survived the corrections for different frequencies between individuals, thereby
further supporting the notion that habitual tendencies are more than merely the frequency
of their occurrence. Therefore, as recommended by Ajzen (2002), we should not solely rely
on behavioural frequencies as the defining criterion for habits, but rather focus on the
qualitative characteristics of habits, such as the declining influence of cognitive
factors and the increasing control of stimulus cues over behaviour.

        <hss>Personality and proneness to habit</hss>

        As habit formation is characterised by a devolution of control from intentions to
        the contextual cues, individuals with problems in self-regulation run the risk of
        automatic habits getting out of control. Our data suggest that trait impulsivity
        promotes habitual behaviour by facilitating this regulatory imbalance between the
        goal-directed and the habit system. Impulsivity seems to selectively enhance
        automatic stimulus-driven, goal-independent actions whilst diminishing the
        occurrence of routine behaviours. Our findings seem to complement previous
        findings in regular smokers, whose levels of trait impulsivity predicted how
        likely they would pick up a cigarette if they were craving for one (Hogarth,
        2011). Conscious cravings predicted smoking only in less impulsive smokers,
        whereas in highly impulsive individuals smoking was more habitual since it was
        decoupled from the conscious desire for a cigarette. This subtle difference
        between goal-independence, as reflected by the COHS automaticity scale, and some
        relatedness of routines to a goal, appears to be critical in defining the
        influence of trait impulsivity on habit formation. Given that impulsive actions
        are spontaneous, premature, lack forethought, and have previously been described
        as an ‘inability to control automatic reactions to stimuli’ (Kopetz, Woerner, &
        Briskin, 2018), the positive relationship with stimulus-driven behaviours captured
        by the COHS automaticity scale may thus seem intuitive. The negative influence of
        impulsivity on routine behaviours, however, might be less obvious. Clearly,
        routines such as going to church on Sunday morning or brushing your teeth before
        going to bed are not fully independent from a goal, but are meaningful familiar
        action patterns, which have been performed many times in the same context so that
        they become automatic once the action sequence has been activated by the cognitive
        representation of the goal (Aarts & Dijksterhuis, 2000). Consequently, the
        difficulty that impulsive individuals have in adjusting the optimal timing for an
        action (as they initiate actions prematurely) is opposed to adhering to regularity
        and developing routines. In fact, the implementation of family routines is
        explicitly recommended to parents of impulsive children as routines provide them
        with a stable context in which consequences become more predictable, encouraging
        them to act less impulsively (Lanza & Drabick, 2011). Compulsivity, by contrast,
        was positively associated with both aspects of habits, routine behaviours and
        automaticity, albeit to a lesser degree than impulsivity. The positive
        relationship is not surprising given that routines, at least those routines that
        have an almost ritualistic nature, may run the risk of developing into compulsive
        behaviours, as exemplified in obsessive-compulsive disorder (Mell et al., 2005).
        Likewise, the unconscious, stimulus-driven nature of compulsions has often been
        described by patients with compulsive disorders (McCusker & Gettings, 1997). It is
        thus conceivable that compulsive personality traits may enhance habitual
        tendencies under conditions of insufficient inhibitory control.

<hs>  Habit formation from a neuroscientific perspective</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our findings also agree well with the substantial work in both animals and humans that has
been defining the neural circuit architecture underlying the neuroadaptive processes of
habit formation (Balleine & Dickinson, 1998; Tricomi et al., 2009; Yin, Knowlton, &
Balleine, 2006). There is now broad consensus that habitual responding develops through
the progressive engagement of different striatal subsystems along a ventral to dorsal
gradient (Burton, Nakamura, & Roesch, 2015). During the early stages of habit formation,
behavioural control relies heavily on dopaminergic pathways modulating interactions of the
associative striatum and the lateral and medial prefrontal cortices, which encode the
value of expected outcomes (Haber & Knutson, 2009). As during this stage behaviour is
mainly goal-directed and performed on purpose, actions are selected on the basis of their
anticipated consequences. With prolonged practice, however, the regulation of these
actions is reorganised as behaviour becomes increasingly automatic and less dependent on
dopaminergic neurotransmission in the aforementioned regions (Ashby, Turner, & Horvitz,
2010). This change is hypothetically underpinned by devolution of behavioural control to
the sensorimotor striatum (Ashby et al., 2010). During this transition, information about
action sequences is clustered together to form units of behavioural repertoires (or
‘chunks’), which can be quickly and more efficiently implemented (Graybiel, 1998). In
other words, the sensorimotor system acts on the signals it receives from the prefrontal
cortex and does not further evaluate how appropriate they are. Consequently, behaviour is
executed irrespective of its potential consequences. Experimental evidence further shows
that the extent of training (or repetition) is directly linked to changes in dopamine
signalling, which induces the transition of control from the associative system to the
sensorimotor system (Choi, Balsam, & Horvitz, 2005). Thus, from a neuroscientific point of
view, the repetition of behaviour is not equivalent to habit, but represents an essential
ingredient for its development. With respect to the influence of impulsive and compulsive
traits on habit formation, there is also growing evidence of impulsivity being associated
with deficits in goal-directed control (Gillan, Kosinski, Whelan, Phelps, & Daw, 2016;
Hogarth, Chase, & Baess, 2012). Consequently, reduced prefrontal involvement during goal-
directed choices may facilitate habitual responding (Deserno et al., 2015). The neural
substrates of compulsivity have been associated with dysregulation of control functions
implemented by frontostriatal and corticostriatal circuitries (van den Heuvel et al.,
2016). Subclinical levels of compulsivity in healthy volunteers seem to be associated with
a volume enlargement of the putamen (Kubota et al., 2016), a structure that is
significantly enlarged in patients with compulsive disorders (Chamberlain et al., 2008;
Ersche et al., 2011, 2012; Pujol et al., 2004), suggesting a highly active sensorimotor
system (Kwon et al., 2003) that facilitates habit formation.

<hs>  Strengths, weaknesses and outlook for further research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Strengths of the study include the relatively large sample size, the re-evaluation of the
COHS's psychometric properties (given that it is a relatively new tool), and our aim to
address the theoretically important question about the influence of frequency on habit
formation. The latter is particularly pressing for assessing habitual tendencies by
questionnaire given the discrepancies between animal and human experimental work. Due to
practical constraints of this online study, the occurrence of habitual behaviours and
their frequencies could only be assessed by self-report and not verified objectively,
which should be addressed by future studies. We used a 15-point frequency scale to allow
for the variation in lifestyles in our sample. We acknowledge that for some COHS items,
frequency data are more difficult to collect than for others. For example, items such as
‘I like routines’, may not spark an obvious answer but our pilot work suggests that
participants understood this item in terms of the frequency with which they generally
obtain gratification when engaging in their routines, which is consistent with the item's
meaning. Our finding that frequency is important but not sufficient for the formation of
habits is critical for the assessment of habits by questionnaire more generally, given
that habits are dependent on people's lifestyles, which determine how frequently they
engage in a behaviour. The COHS items were therefore carefully chosen, and as suggested by
the present study, are not compromised by how frequently respondents report having
previously engaged in the behaviour in question. Our findings are thus in keeping with
both the theoretical concept of habits and the neuroscientific evidence of their
development. The COHS has not been designed to measure habit strength in terms of how
persistently an individual pursues a particular habit, but rather to assess individual
variation in readiness to engage in habitual behaviours in daily life. It should therefore
not be mistaken with the Self-Reported Habit Index (Gardner, De Bruijn, & Lally, 2011;
Verplanken & Orbell, 2003), which requires individuals to rate their experience with the
regular behaviour in question. Further work is, however, warranted to investigate how
proneness to habits expresses itself during habit learning in an experimental paradigm. It
would be of particular interest to test whether high COHS scores are predictive of
enhanced acquisition of stimulus-response habits and the (in)ability to adjust them
according to changing circumstances. The present study does not necessarily indicate that
the proneness to form functional habits is a risk marker for the transition to
dysfunctional habits; however, we would welcome research in patients with dysfunctional
habits to investigate whether the COHS might inform preventative or therapeutic strategies
for these patients.

<h>CONCLUSIONS</h>
-----------

This present study examined the inter-relationships between three potentially related
traits: impulsivity, compulsivity and the proneness to habits, defined according to two
distinct criteria, automaticity (goal-independent) and routine (goal-related), and not
dependent on their frequency of occurrence. Whereas both impulsivity and compulsivity are
associated with increased automaticity of behaviour, they may thus exert opposite effects
on routine habitual behaviour, impulsivity being negatively correlated. These findings may
be relevant for identifying vulnerability to certain mental health disorders and for
understanding how learning may become aberrant and produce psychopathology.


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<ART>Infants' performance in spontaneous-response false belief tasks: A review and meta-analysis
================================================================================

Authors: Pamela Barone, Guido Corradi, Antoni Gomila
DOI: 10.1016/j.infbeh.2019.101350
Year: 2019
ASJC codes: 3204

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Evidence obtained with new experimental paradigms has renewed the debate on the development of theory of mind in general and false belief ascription in particular. Namely, several studies contend to prove that infants already have the capacity to attribute false beliefs. The aim of the current meta-analysis is to review and summarize the empirical evidence about spontaneous-response false belief tasks in infants younger than 2 years old. Fifty-six false belief conditions using the violation-of-expectation, the anticipatory looking and interactive paradigms were included in this meta-analysis, including 1469 infants. The role of several moderators was examined, following Wellman et al.ös meta-analysis (2001). Results show that correct performance on spontaneous-response false belief tasks was about 1.76 times more likely than incorrect performance (β = 0.57, 95% CI 0.33; 0.80, p <.0001). Mediator analyses revealed that (i) year of publication had a significant influence on performance, reducing the average log odds of successful performance (β = -0.11, 95% CI: -0.16; -0.06, p <.0001); and (ii) correct performance was more likely than incorrect performance when the task was conducted in the violation-of-expectation paradigm (β = 0.75, 95% CI: 0.25; 1.26, p =.003). However, heterogeneity was high across the studies and the funnel plot revealed an asymmetric distribution suggesting that studies with small effect sizes were not published. These results cast doubt on the alleged robustness of the phenomenon: its effect size decreases as time passes, it seems to depend on the type of paradigm employed, and the variance across studies is not well understood yet.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In our everyday social interactions, we frequently attribute mental states (e.g., beliefs,
desires and intentions) to other people in order to predict or explain their behavior. For
example, if you know that Ben wants to drink orange juice, and you know that Ben believes
that the orange juice is in the fridge, you can predict that he will search for the orange
juice in the fridge. This ability to impute mental states to others (and also to oneself)
to make predictions about the future behavior of other agents is called theory of mind
(Premack & Woodruff, 1978, p. 515). Competence in theory of mind consists of understanding
agents as holders of beliefs and desires, which jointly give rise to intentions and goals,
carried out in action. False-belief ascription was chosen as diagnostic of theory of mind
capacity (Bennett, 1978; Dennett, 1978; Harman, 1978) because an agent with a false belief
holds an informational state incongruent with reality. Then, this ability requires that an
individual understands the situation in the terms of the agent, which are necessarily
different from how the individual himself conceives of it. As a result, developmental
psychologists devised the false belief task (FBT) to investigate children’s ability to
represent another person’s mistaken belief (Wimmer & Perner, 1983). There are two main
versions of the classical FBT: the “change of location” or the “unexpected transfer”
version (Baron-Cohen, Leslie, & Frith, 1985; Wimmer & Perner, 1983), and the “unexpected
contents” variant (Gopnik & Astington, 1988; Hogrefe, Wimmer, & Perner, 1986; Perner,
Leekam, & Wimmer, 1987). In the former, the child is told (or shown) a story in which the
main character puts an object in location x and then, while the character is absent, the
participant witnesses how the object is transferred from location x to location y. Upon
the character’s return, the participant is asked, “Where the character will look for the
object?” In the unexpected contents task, the child is shown a box whose content is not
what the cues depicted on its surface suggest, and is asked, “What do you believe is in
the box?” After revealing what is in fact inside, the participant is asked “What did you
believe was in the box?” and “What another child will think is in the box when he first
encounters it?” To pass the test, the child has to distinguish between her current and
former perspective of the situation as well as the character’s perspective. Correct
performance on any version of the FBT indicates that the child understands that the agent
will behave according to her beliefs about the reality (i.e., her perspective) which
diverge from the reality itself (i.e., these beliefs are false) and from the child’s true
beliefs about the situation. Using multiple variations of this basic test, a huge amount
of converging evidence supported the conclusion that children consistently pass the FBT by
the age of 4 (Wellman, Cross, & Watson, 2001). Interestingly, younger children
consistently give the wrong answer in every version of the FBT, responding from their own
point of view, not from the agent’s (Apperly, 2011). However, doubts remained that passing
the classical FBT involved additional abilities than just theory of mind, both in terms of
linguistic abilities and executive control requirements (Ozonoff & McEvoy, 1994; Russell,
Mauthner, Sharpe, & Tidswell, 1991). Further support for this suspicion came from an
experiment in which 35-month-old children, who were allowed to answer by looking instead
of verbally answering a question, passed the test (Clements & Perner, 1994). More
recently, Rubio-Fernández and Geurts (2013), who also used the classical change of
location task but required the participants to move the puppet character themselves
instead of verbally answering questions, found that 36 months old passed the test. In
addition, Setoh, Scott, and Baillargeon (2016) revealed that 30 months old also succeeded
in the change of location task if they received two previous practice trials resembling
the structure of the test question and if the target object was removed from the scene, so
the child was uncertain about the object’s last location. As the structure of the
classical FBT is made simpler, in terms of verbal competence and executive control
requirements, attribution of false beliefs is found earlier than previously thought.
During the last decade, this suspicion gave rise to a new set of simpler, spontaneous-
response FBT, developed in order to find out how early attribution of false beliefs, and
therefore, theory of mind, can be said to appear in development (Scott, Baillargeon, Song,
& Leslie, 2010). These new experimental paradigms involve violation-of-expectation (VOE)
(Onishi & Baillargeon, 2005), and anticipatory looking (AL) measures (Southgate, Senju, &
Csibra, 2007), as well as a variety of interactive designs (Buttelmann, Carpenter, &
Tomasello, 2009). The VOE paradigm exploits the fact that when an individual’s
expectations are violated, she is surprised and surprise involves looking longer at the
spot where the relevant event is taking place. Accordingly, it involves two steps: first,
a habituation or familiarization phase, in which the infants are experimentally induced to
form context-dependent expectations by being repeatedly exposed to the same event.
Secondly, in the test trials, they are presented with either an expected or an unexpected
event, given the induced expectation. The prediction is that infants will look longer to
unexpected events as a sign of surprise. By experimentally modifying the event, authors
try to determine the content of the infants’ expectations formed during the habituation
trials (Jacob, 2013). Onishi and Baillargeon (2005) designed the first spontaneous-
response study applying this paradigm in false belief understanding as a variation of the
classical change of location task. In the familiarization phase, infants first watched as
an actor hid a slice of watermelon in a green box and retrieved it from there twice. Next,
a sort of magic change occurred. In one false belief (FB) condition, the watermelon moved
by itself (in fact, the agent moved it using a magnet under the table) from the green to a
yellow box while the agent was absent (FB-green condition). In another FB condition, the
agent was present while the watermelon moved to the yellow box but then it returned to its
original position as soon as the agent disappeared from the scene (FB-yellow condition)1 .
In the experimental trials, infants watched the actor searching in one of the two boxes.
The authors predicted that infants would look for a longer period of time when the agent
acted unexpectedly (according to her false belief): if she went to the yellow box in the
FB-green condition or to the green box in the FB-yellow condition. After this seminal
paper, the VOE paradigm has spread over the field as a measure of belief understanding2 .
On the other hand, other researchers have chosen infants’ first look in the test trial as
the dependent variable. This first look generally takes place before the display is shown.
This anticipatory looking method is a measure of what an infant expects to happen, given
what happened before in his/her presence (Heyes, 2014). Clements and Perner (1994) were
the first in using the AL measure in the context of a standard change of location FBT.
Instead of directly asking where the agent would look for her toy upon her return,
participants heard the experimenter say to himself “I wonder where she’s going to look?”.
Most 35 month-old children correctly anticipated the spot where the agent would search
according to her belief looking first at that location. Southgate et al. (2007) updated
the AL methodology using an eye-tracker and removing any verbal interaction in order to
test 25-month-old infants in a spontaneous-response FBT. They predicted that infants would
look in anticipation where an agent with a false belief will search for an object, on the
grounds of the visual information previously available to both. Interestingly, the object
was not just changed of location but removed from the scene. After Southgate and
colleagues’ positive results, other authors started to use infants’ first look as a
dependent measure of false belief understanding. In addition, a new set of spontaneous-
response FBT emerged that took advantage of infants’ intentional interaction abilities,
such as active helping and referential communication. These tasks typically involve simple
language and introduce participants to a scene in which an agent does or does not witness
an event. Children are then given a verbal prompt –but one that only indirectly taps their
representation of the agent’s epistemic state. Authors measure young children spontaneous
behaviors in response to the prompt, such as helping and pointing, as a proxy for belief
understanding. In the first FBT using the interactive paradigm, infants watched as an
agent placed a toy inside a box, and later as another person switched the toy from one box
to a second one while the agent either witnessed the switch (true belief condition) or not
(false belief condition). Then, the agent unsuccessfully attempted to open the box that
originally contained the toy and infants, who were previously instructed on how to open
the boxes, spontaneously helped her. Buttelmann et al. (2009) expected that infants helped
the agent to open the other box, where the toy is actually hidden, only in the false
belief condition. So far, many other studies have employed infants’ helping or pointing
behavior to measure false belief ascription. Each of the previous studies on early false
belief understanding provided positive results showing that infants, from 15 months old,
can attribute false beliefs to another agent. This new picture of young children tracking
another agent’s false beliefs gave rise to a paradox in development: on the one hand,
infants succeed in different non-verbal and spontaneous versions of the FBT but, on the
other hand, children cannot reliably pass the verbal, explicit versions of the FBT until
they are 4 years old. Different theoretical approaches tried to explain this developmental
paradox. For instance, advocates of a nativist or an early, full mentalistic capacity
account take the results of spontaneous-response FBT at face value, claiming that they
prove genuine false belief understanding (Carruthers, 2013; Jacob, 2013; Leslie, 1994;
Leslie, Friedman, & German, 2004; Scott & Baillargeon, 2017). They argue that 3 year-olds’
difficulties with the explicit FBT are related to processing demands but not to their
understanding of beliefs, thus applying the strategy first proposed by Fodor (1992) of an
innate, full competence but limited performance due to the task’s requirements. Working
memory and related executive control abilities change throughout children’s development
but not their ability to understand propositional attitudes in general, which is assumed
to be complete, universal, and innate or it appears very early in ontogeny. In other
words, 2 year-old children do attribute full-blown beliefs –beliefs with propositional
contents– as part of their understanding of others as intentional agents. Empiricists, on
the other side, deny that infants’ performance on spontaneous-response FBT show that they
attribute beliefs in first place. From their point of view, infants’ behavior can be
explained by low-level processes such as a novelty preference (Heyes, 2014) or simpler
behavioral rules (Perner & Ruffman, 2005). For example, Heyes (2014) has forcefully argued
that the novelty generating the surprise in the VOE and the AL procedures appears at a
lower representational level than the true or false belief representations. Infants'
looking behavior is a function of the degree to which the observed (perceptual novelty)
and remembered or expected (imaginal novelty) low-level properties of the test stimuli
–their colors, shapes, and movements– are novel with respect to the earlier events encoded
by the infants in the experiment. On Perner’s view, on the other hand, infants’
performance in these tasks can be accounted in terms of learned or innate behavioral
rules, such as that “people tend to look for an object where they last saw it and not
necessarily where the object actually is” (Perner & Roessler, 2012). More recently,
though, a two-systems account of belief-ascription has been put forward (Apperly &
Butterfill, 2009; Butterfill & Apperly, 2013; Low, Apperly, Butterfill, & Rakoczy, 2016).
According to this dual-system view, overcoming the spontaneous-response FBT depends on a
fast and implicit but inflexible system. Such system reasons about “belief-like” states,
called “registrations”, and develops early in ontogeny. A registration is a non-
propositional, extensional state that holds relations to objects and properties and has
its effects directly on action. Someone who reasons about registrations would track
beliefs, true and false, but in a limited range of situations. For example, infants can
attribute registrations regarding the location of an object and thus succeed in many
spontaneous-response FBT (Apperly & Butterfill, 2009). However, they cannot track beliefs
that involve quantifiers, indefinitely complex combinations of properties, or
aspectuality, that is, situations in which a protagonist refers to an object under one
aspect in contrast to another (Apperly & Butterfill, 2009; Rakoczy, Bergfeld, Schwarz, &
Fizke, 2015; Rakoczy, 2017). The fact that registrations have signature limits explains
why young children fail spontaneous tasks in which the protagonist was mistaken about the
identity of an object (Fizke, Butterfill, van de Loo, Reindl, & Rakoczy, 2017). Since
registrations are relational states, they fail to capture the intensionality
characteristic of propositional attitudes and the aspectuality of the agent’s mental state
(Rakoczy, 2017). On the other hand, a late-developing and flexible system supports the
attribution of genuine beliefs. This system is effortful and explicit, but also
inefficient, and supports children’s success in explicit FBT. Beliefs, unlike
registrations, are propositional, intentional states, which engage in holistic and complex
interactions with other propositional attitudes. Such a flexible system allows children to
overcome the limitations posed by the early system and track more complex beliefs. Lately,
Tomasello (2018) has argued that insofar as the previous theories are based on individual
cognition, the developmental puzzle will not be solved. The key to understanding beliefs
requires an account of the processes of social and mental coordination with other agents
and their perspectives. According to Tomasello (2018), the origins of this coordination
lie in infants’ join attentional activities around their first birthdays, in which they
relate two perspectives. To pass the spontaneous-response FBT, infants just need to
display their ability to triangulate, the same one that they use in joint attention, which
involves tracking what the agent sees or has seen in the test, and how this information
will affect the agent´s behavior. But such epistemic tracking does not imply that the
child should understand that the agent´s belief is incorrect; in other words, the infant
does not need to compare the agent’s perspective with his own view of the situation or
with the objective situation (Tomasello, 2018). While three-year-old children answer the
false belief question focusing on the objective perspective, 4- to 5-year-old children
pass the FBT because they come to coordinate the three perspectives involved: the child’s,
the agent’s and the objective perspective. Much social and communicative interaction with
others is required before such achievement, which is mainly characterized by communicative
exchanges involving joint attention to mental content (Tomasello, 2018). Almost fifteen
years after the seminal study from Onishi and Baillargeon, there is no consensus about the
capacities displayed by the infants in the non-verbal tasks. After the positive evidence
obtained in the pioneer studies, new tasks either confirmed a similar pattern of results
or failed to replicate the original findings (most of them were not published; see Kulke &
Rakoczy, 2018). Given the mixed pattern of the accumulated evidence, it is time for a
meta-analysis of the literature on implicit theory of mind. Specifically, this meta-
analysis explores how correct performance in spontaneous-response FBT has revealed and
whether (and how) other variables mediate this effect.

<hs>  Inclusion and exclusion criteria</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We used the following criteria to select studies to include in the meta-analysis. We only
included studies testing participants’ capacity to attribute false beliefs in which their
mean age was 26 months old or younger. Thus, we excluded all false belief conditions
testing older children. We only included tasks that employed one of these three paradigms
for implicit false belief ascription: the violation of expectation methodology, the
anticipatory looking and the interactive paradigms (grouping both tasks that require
infants’ helping and pointing behaviors). We only included implicit false belief
conditions; thus, we excluded true belief, ignorance and control conditions that might be
present in the studies as well. We only included false belief conditions in which typical-
developmental infants were tested. Then, we excluded false belief tests carried out on
samples with atypical development. We included all the tasks published from Onishi and
Baillargeon seminal paper (2005) until 4th February 2019. Although we checked for
unpublished data in the overview of studies done by Kulke and Rakoczy (2018), most of
these data are now published and we have already included in the current meta-analysis3 .

<hs>  Moderator and mediator analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Each condition included in the meta-analysis was coded for the following dependent
variables, most of them following Wellman et al. (2001)4 : Paradigm: the paradigm employed
in each condition, that is, the violation of expectation (VOE), the anticipatory looking
(AL) or the interactive paradigm. Age: the mean age of participants in each condition
(expressed in months). In some cases, the authors reported the mean age of participants
from the whole group (grouping together either true and false belief conditions or two
false belief conditions). Sample size: the number of participants in a condition. Dropped
participants: the number of participants excluded from each condition. In many cases, the
authors reported the total amount of excluded participants in the whole study, grouping
together false and true belief conditions, or two false belief conditions. Familiarization
trials: the number of familiarization trials performed in each condition. When the authors
employed warm-up trials, instead of familiarization trials, we coded the familiarization
trials as 0. Belief: the type of belief attributed to the agent. We coded four levels,
distinguishing beliefs about: an object location (L); a non-obvious property of an object
(NP); the identity of an object (I); or Agent: three levels that described the nature of
the agent as: a real present person; a videotaped person; or a virtual agent (including
cases of a human-like individual, a geometric shape or an animal). Real presence of the
target object: whether, at the test trial, the target object was: real and present (i.e.,
the object was inside one of the boxes); or absent (i.e., the object had been removed from
the scene). Object movements: the number of displacements of the object that the agent did
not see before the object arrived at its final position. Motive of the transformation: two
levels capturing whether the key transformation (e.g., the change of location or the
substitution of unexpected contents) was done: to trick: to explicitly trick the agent, or
for other reason: for some other reason including no explicit reason at all. Salience of
the agent’s mental state: we distinguished four levels: absence: the false belief state
had to be tracked from the agent’s absence during the key events; back turned: the false
belief state had to be tracked due to the agent’s back turned during the key
transformation; first-person experience: the false belief experience was demonstrated
initially on the children themselves; and blindfold: the agent used a blindfold during the
transformation. Interaction: we coded whether there was interaction between the child and
the agent during the test or not. Design: indicates the design employed in each condition.
We distinguished between: a within-subjects design (WS): participants were tested in both
test events (congruent and incongruent events in the VOE case) or in both conditions
(false and true belief conditions); and a between-subjects design (BS): participants were
tested in only one test event (in the VOE case) or in only one false belief condition.
Test trials: the number of test trials that were conducted with each child. Depending on
the paradigm employed, we coded the dependent variable in each case. In the VOE paradigm,
we coded the mean looking time (in seconds) that infants spent looking to (a) the expected
event, that is, when the agent acted according to her false belief; and (b) the unexpected
event, that is, when the agent acted in a way that was not according to her false belief.
In the AL and the interactive paradigms, we coded the percentage of passers, that is, the
number of infants that showed the correct anticipatory behavior (in the AL paradigm)5 or
the correct helping or pointing behavior (in the interactive paradigms).

<hs>  Search strategies & coding procedures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The literature on implicit false belief tasks is relatively recent (the first study was
published in 2005), so new studies are known in the area and are cited as new articles
appear. However, we checked the databases EbscoHost – PsycINFO, SCOPUS, and Web of Science
(WoS) to ensure we were taking into account all the studies published up to date. The
search terms employed were false belief, implicit false belief tasks, false belief +
infants, spontaneous response false belief tasks, violation of expectation + false
beliefs, looking paradigm + false beliefs, theory of mind. We addressed studies published
in English and we only included published studies. All the studies were coded by the first
author, after agreement on the codes with the third author. Table 1 shows the final list
of references included in the current meta-analysis.

<hs>  Statistical methods</hs>
  ~~~~~~~~~~~~~~~~~~~

We calculated the effect sizes based on the data described in the articles and on the
responses from the authors to requests for further information6 . For within-subjects
designs, in which infants were tested on both congruent and incongruent test trials, the
standardized mean change was calculated. Its formula is equal to (m1i - m2i)/Sdif, where
m1i and m2i refer to the observed means at the two measurement occasions. To calculate the
standard deviation of the paired differences, the corresponding standard deviations of the
two measurement occasions and the correlation coefficient between both should be reported.
No condition that employed a within-subject design reported the correlation between
participants’ two measures. Then, we fixed a medium correlation of 0.5 for these cases7 .
On the other hand, studies conducted with the AL and the interactive paradigms provide
data for single groups with respect to a dichotomous dependent variable: correct
anticipatory look (it means, looking in anticipation to the place where the agent should
go according to her false belief), or incorrect anticipatory look; or correct helping or
pointing behavior (i.e., opening the correct box, giving the appropriate object, or
pointing to the correct location), or incorrect helping or pointing behavior. Therefore,
we used the logit transformed proportion (log odds) as an outcome measure for the studies
from both paradigms. The log odds for single groups is equal to the
log((xi/ni)/(1-(xi/ni))) where xi denotes the number of individuals experiencing the event
of interest and ni refers to the total number of individuals in the group. The variance of
log odds is equal to 1/xi + 1/(ni-xi). Finally, we converted d scores into log odds by
applying the formula d · (π/√3); and the variance of d into the variance of log odds
following the formula v(d) · (π2/√3). Then, we calculated the effect size standard error
(SE) which is equal to the square root of the variance. 95% confidence intervals were
calculated in the statistical program R Core Team (2013). The lower bound of the
confidence interval results from applying the formula log odds – (1.96 · SE), while the
upper bound of the interval is determined by log odds + (1.96 · SE). We employed a random
effects model in which we assume that the true effects are normally distributed
(Borenstein, Hedges, Higins, & Rothstein, 2009). Under this model, two sources of
variability are assumed: intra-study variability (due to sampling error) and inter-study
variability (each study estimates its own parametric effect) (Ausina & Meca, 2015).
Heterogeneity was assessed by calculating different statistics. First, we used the Q
statistic, which is the weighted sum of squares (WSS) on a standardized scale, and its
p-value as a test of significance. As a standard score, it can be compared with the
expected WSS (on the assumption that all studies share a common effect) to yield a test of
the null and also an estimate of the excess variance (Borenstein et al., 2009). We also
quantify T2 that reflects the variance of the true effects; and I2 that reflects the
proportion of observed dispersion that is due to true heterogeneity and is expressed as a
ratio. Higgins, Thompson, Deeks, and Altman (2003) suggest that values on the order of
25%, 50%, and 75% might be considered as low, moderate, and high, respectively. Finally,
when we add moderators to the model, we report R2 which reflects the amount of
heterogeneity accounted for the variables included in the model. Possible publication bias
was assessed with a funnel plot. The funnel plot is a graphical display of effect sizes
against their standard errors and shows that, in the absence of publication bias, studies
will be symmetrically distributed around the mean effect size, since the sampling error is
random. In the presence of publication bias, the studies are expected to follow the model,
with symmetry at the top, a few studies missing in the middle, and more studies missing
near the bottom (Borenstein et al., 2009, p. 284). We used the metafor package
(Viechtbauer, 2010) in R Core Team (2013) to calculate effect sizes, heterogeneity
estimates, to run the meta-analysis, and to perform the forest, the funnel, and the meta-
regression plots.8

<hs>  Description of studies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

A PRISMA flow diagram illustrates the search strategy and study selection (see Fig. 1).
The search procedure yielded 44 references for which additional information was obtained.
Two of these references were duplicates (the VOE task with 18-months-old from Poulin-
Dubois & Yott, 2018 with the one from Yott & Poulin-Dubois, 2016; and the AL study of
Sodian et al., 2016 with the one of Thoermer, Sodian, Vuori, Perst, & Kristen, 2012), thus
we removed them. Of these 42 papers, 2 studies were carried out with another paradigm
(Kovács, Téglás, & Endress, 2010; Southgate & Vernetti, 2014) and, in 5 of them, the
target group was constituted by older children (Burnside, Ruel, Azar, & Poulin-Dubois,
2017; Burnside, Wright, & Poulin-Dubois, 2018; Grosse Wiesmann, Friederici, Singer, &
Steinbeis, 2017; Oktay-Gür, Schulz, & Rakoczy, 2018; Wang & Leslie, 2016), thus we
excluded them. Out of them, 2 additional articles were eliminated because of insufficient
reported data to calculate the effect sizes (Song & Baillargeon, 2008; Träuble, Marinovi,
& Pauen, 2010). Finally, the data from 33 articles were included in the meta-analysis.
From these definitive 33 papers, we additionally excluded some conditions in which authors
tested older children (Fizke et al., 2017; Grosse Wiesmann, Friederici, Disla, Steinbeis,
& Singer, 2018; Kulke, Reiß, Krist, & Rakoczy, 2018; Priewasser, Rafetseder, Gargitter, &
Perner, 2018; Schuwerk, Priewasser, Sodian, & Perner, 2018) or deaf participants (one
condition from Meristo et al., 2012), and other conditions due to insufficient data to
calculate the effect sizes (two VOE conditions from Powell, Hobbs, Bardis, Carey, & Saxe,
2018). The final selection of articles amounted to 56 false belief conditions in which a
total of 1469 infants were tested. Table 2 reports the descriptive information of each
false belief condition included in the meta-analysis like the year of publication, the
sample size, infants’ mean age, the paradigm employed, the effect size and the 95%
confidence intervals. Table 3 provides a descriptive summary of the database grouped by
the variables coded. The mean age of all the participants of the database was 19.55 months
and, from the 56 false belief conditions, 19 employed the VOE paradigm, 15 used the AL
procedure and 22 the interactive methodology.

        <hss>Model 1</hss>

        We built a random effects meta-analytic model with maximum likelihood estimation
        on infants’ performance in spontaneous-response false belief tasks. This first
        model (model 1) included no covariate. The results showed that the estimated
        average effect size (calculated in log odds) is equal to β = 0.57, 95% CI [0.33;
        0.80] (see Fig. 2). It, therefore, suggests that the average log odds corresponds
        to an odds of 1.76, meaning that correct performance on spontaneous-response false
        belief tasks was about 1.76 times more likely than incorrect performance9 . In
        terms of probabilities, the probability of correct performance was 64%10 . The
        null hypothesis can be rejected (z = 4.69, p <  .0001). The total set of studies
        was heterogeneous as evidenced by significant Q-values (Q[1,55] = 163.81, p <
        .001). T2, which reflects the amount of true heterogeneity (i.e., the variance of
        the true effects), is 0.50 (SE = 0.15). The proportion of observed dispersion in
        the data that is due to heterogeneity is specified by I² = 71.5%, which indicates
        a medium-high proportion of variance due to heterogeneity rather than chance. The
        funnel plot showed that all the effect sizes falling within the grey area would be
        statistically non-significant in a two-tailed test (Fig. 3). We can see an
        asymmetrical distribution of the effect sizes, with more studies on the right part
        of the plot -showing larger effect sizes- that have less precision (smaller
        samples). This graphical display suggests a publication bias: some studies with
        non-significant results were not published.

        <hss>Model 2</hss>

        Part of the heterogeneity found may be due to the influence of moderators
        (Viechtbauer, 2010). We examined this possibility by fitting a mixed-effects model
        including theoretically relevant predictors as the year of publication, infants’
        age, the paradigm employed, the type of belief, the type of agent, the motive of
        the transformation, the design of the study, and the presence of the target object
        as moderators. This second model 2 includes 8 predictors. We performed a multiple
        meta-regression on model 2 using the restricted maximum likelihood method. Table 4
        shows the results. In this model, the estimated amount of residual heterogeneity
        is equal to T2 = 0.23, suggesting that 53.80% (R2) of the total amount of
        heterogeneity can be accounted for the eight moderators included in the model. The
        proportion of observed dispersion due to heterogeneity (I²) is reduced to 52.14%.
        We can reject the null hypothesis based on the omnibus test (QM = 49.67, df = 12,
        p < .0001). Before analyzing the implication of each moderator, a statement of
        caution is crucial. Given the large number of moderators considered and their
        confounds with one another, we need to be circumspect in the interpretation of the
        results about the influence of these variables on children’s performance.
        Examining the predictors of model 2, we find that year of publication (z = -4.54,
        p <  .0001), infants’ age (z = 2.26, p = .02) and the motive of transformation (to
        trick the agent; z = 0.32, p = .04) have a significant influence on performance.
        The test for residual heterogeneity is significant (QE = 87.20, df = 43, p <
        .0001), indicating that other moderators, not considered in the model, are
        influencing children’s performance. These results indicate that as time passes,
        the probability of passing the test diminishes -0.15 units (95% CI: -0.22; -0.09)
        in terms of the average log odds of successful performance. This means that
        incorrect performance on spontaneous-response false belief tasks is 0.86 times
        more likely than correct performance as the year of publication is higher,
        suggesting that null results or children’s incorrect performance on the task are
        currently being published. On the other hand, when older infants are tested, the
        log odds of successful performance increase 0.08 units (95% CI: 0.01; 0.15),
        meaning that correct performance is 1.08 times more likely than incorrect
        performance as infants get older. When the motive of the transformation is to
        trick the agent, it results in an increase of 0.65 (95% CI: 0.02; 1.29) units in
        the log odds of correct performance. This indicates that correct performance is
        1.91 times more likely than incorrect performance. Anyway, the confidence
        intervals of the effect sizes of these two predictors almost touch zero. Then, we
        should cautiously interpret them. The effects of all other predictor were not
        significant (all p values > .05).

        <hss>Model 3</hss>

        Lastly, we examined a simpler model by fitting a mixed-effects model only
        including the year of publication and the paradigm as moderators. The results of
        the multiple meta-regression for model 3, that includes two predictors, are
        presented in Table 5. The estimated amount of residual heterogeneity is equal to
        T2 = 0.19, suggesting that 61.30% (R2) of the total amount of heterogeneity can be
        accounted for the inclusion of these two moderators in the model. The proportion
        of observed dispersion due to heterogeneity (I²) is 48.19%. We can reject the null
        hypothesis based on the omnibus test (QM = 40.12, df = 3, p < .0001). A closer
        inspection of the predictors shows that year of publication appears to have a
        significant influence on performance (z = -4.32, p <  .0001) as well as the VOE
        paradigm (z = 2.92, p =  .003). Results indicate that as the year of publication
        is higher, there is a reduction of -0.11 (95% CI: -0.16; -0.06) in the average log
        odds of successful performance. This result indicates that incorrect performance
        on spontaneous-response false belief tasks is 0.90 times more likely than correct
        performance as time passes, in the same vein as the result of model 2. On the
        other hand, performing the task in the VOE paradigm implies a change of 0.75 (95%
        CI: 0.25; 1.26) in increasing the log odds of successful performance in the task.
        This means that correct performance is 2.12 times more likely than incorrect
        performance when the test is run with the VOE paradigm.

        <hss>Models’ comparison</hss>

        The models were compared using the Akaike information criterion (AIC) and the
        Bayesian information criterion (BIC). Table 6 contains the values of each
        criterion for the three models. Comparing model 2 with model 1, both AIC and BIC
        decrease: AIC is reduced from 160.26 to 123.74, and BIC decreases from 164.28 to
        148.40. This shows that the fit of the second model is improving. If we then
        consider model 3, in comparison with model 2, AIC increases (AIC = 129.09) while
        BIC considerably decreases (BIC = 138.84). BIC penalizes for each additional
        variable included in the model, thus, the fit of model 3 –with only two
        parameters– improves in comparison to model 2 that possesses eight predictors. As
        the AIC for model 2 and model 3 are not substantially different, the fit of the
        third model is better than the fit of the first one and therefore it is preferable
        over the other two models.

<hs>  A meta-analysis per paradigm</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We also run separate meta-analysis per each of the paradigms employed (see Fig. 2).
Results show that the VOE paradigm had a significant mean effect size β = 1.28, 95% CI
[0.86; 1.69], implying that correct performance on the task was about 3.58 times more
likely than incorrect performance (see Table 7). The results from the interactive
paradigms also indicate a significant mean effect size β = 0.31, 95% CI [0.01; 0.61],
suggesting that correct performance on the task was about 1.36 times more likely than
incorrect performance. However, this is a lower probability and the confidence interval
almost reach zero. On the other hand, the meta-analysis for the AL paradigm provided no
significant mean effect size (β = 0.16, 95% CI: -0.24; 0.57). Results from the VOE and the
interactive paradigm suggest that the average effect size found when all paradigms were
included as moderators come from these methodologies.

<hs>  Main effects analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~~

We also inspected the main effects of all the variables we have coded. We will first
consider the effect of the year of publication and we will then analyze the other
methodological moderators separately. Year of publication might have a special status,
likely indexing publication bias rather than methodological differences11 .

        <hss>Year of publication</hss>

        The year of publication, on its own, has a significant influence on performance (z
        = -5.32, p <  .0001). Insofar as the year of publication is higher, the
        probability of passing the test falls -0.14 units (95% CI: -0.19; -0.09) in terms
        of the average log odds of successful performance (see Fig. 4). This result
        suggests that children’s incorrect performance on spontaneous-response false
        belief tasks is 0.87 times more likely than correct performance as the year of
        publication increases, in the same direction as we found in models 2 and 3.

        <hss>Methodological moderators</hss>

        We found that the following variables produced a significant main effect: the
        paradigm, the type of agent, the object’s movements, the salience of the agent’s
        mental state and the sample size. Each of them has, on its own, a significant
        influence on young children’s performance. All the remaining methodological
        moderators produced non-significant main effects. Table 8 presents the estimates,
        the p values and the confidence intervals for all the significant predictors. The
        effect of the paradigm was already analyzed in model 3. On the other hand, when
        the agent was a videotaped person, there was a change of -0.62 (95% CI: -1.15;
        -0.08) in reducing the average log odds of successful performance.12 Regarding the
        object’s movements, when it was moved twice outside the view of the agent, there
        was a change of -1.16 (95% CI: -1.90; -0.42) in reducing the average log odds of
        successful performance. Then, when the agent’s false belief was induced because
        she was turned back during the key events, there was a change of -0.77 (95% CI:
        -1.31; -0.24)13 . The sample size also seemed to influence performance: when
        bigger the sample size, lower the probability of finding a correct performance in
        the task (β = -0.01, p =  .02, 95% CI: -0.02; 0.00). However, the confidence
        interval for this effect size includes zero. Finally, the following Figs. 5–7 show
        how the variables are distributed in the conditions recruited for the meta-
        analysis. Fig. 5a shows how all the studies that found big effect sizes were run
        with small samples. When bigger sample sizes were employed, the effect sizes
        tended to decrease. Fig. 5b, on the other hand, shows the relation between dropped
        participants and the effect sizes found in each condition: only a few studies
        excluded more than 20 participants. In addition, when all infants were included in
        the sample, the resulting log odds of correct performance was low (it only
        happened in two studies). Effect size as a function of infants’ age is shown in
        Fig. 6. We can see that, as infants become older, correct performance tended to
        decrease although it was a non-significant trend (p =  .06)14 . Interestingly,
        most of the tests were carried out with 18-month-old infants. This age group,
        however, showed an uneven performance on the task: they correctly passed the VOE
        tests but showed all possible results in the other two paradigms considered
        (above, at chance and below chance performance). Interestingly, there were no
        studies carried out in the specific age range from 19 to 23 months old. Also,
        there was only one study employing the VOE paradigm with older infants (24 months
        old) and interactive tests were consistently conducted from 18-month-old. Fig. 7
        shows the dispersion of the data in each paradigm according to (a) the design
        employed, (b) the interaction between the child and the experiment, and (c) the
        motive of the transformation. Interactive paradigms mostly employed between-
        subjects designs (by testing the child only in a FB condition), while within-
        subjects designs were used in the other paradigms (although not as often as
        between-subjects ones; Fig. 7a). Fig. 7b shows how interaction overlaps with the
        paradigm: AL and VOE paradigms are non-interactive measures and interaction
        appears in those tasks in which infants should help or point to the agent.
        Finally, Fig. 7c shows that the transformation of the scene (i.e., change of
        location) was mainly done to trick the agent in the interactive tasks. All the
        other changes that provoked a false belief in the agent were done for other
        (including no) reason.

<h>DISCUSSION</h>
----------

This meta-analysis reveals that, on average, correct performance on spontaneous-response
false belief tasks is more likely than incorrect performance, suggesting that the tasks
are tapping a real phenomenon. However, the meta-analysis simultaneously uncovers
important issues: (i) an increase in year of publication implies a decrease in correct
performance; (ii) a considerable heterogeneity is present among studies; (iii) the
asymmetrical distribution of effects sizes in the funnel plot suggests publication bias;
and (iv) correct performance depends on the type of paradigm used. Taken together, these
results indicate that the developmental puzzle is still unsolved. First of all, we saw
that large effect sizes were found at the onset of the research in implicit false belief
attribution, but this outcome could not be replicated in more recent experiments.
Relatedly, those large effect sizes were found with small samples, whereas later studies
used bigger samples. Secondly, the high percentage of heterogeneity found across studies
suggests that, despite the significant effect, we still do not know which factors really
explain the variance across studies. Since two of the parameters (i.e., the year of
publication and the paradigm) considerably reduced such variance among studies -from a
high ratio to a medium ratio of heterogeneity-, there was still much variance in the
dataset that the model could not explain. Thirdly, the skewed distribution of the effect
sizes hints at the presence of publication bias in this literature. Current initiatives to
look for unpublished papers and to replicate previous studies imply that many researchers
become aware of this bias. For example, some journals have invited to submit replications
of the tasks (for instance, the special issue Understanding theory of mind in infancy and
toddlerhood published by the journal Cognitive Development) and the scientific community
is doing an effort to conduct direct as well as conceptual replications (Kulke & Rakoczy,
2018). Especially relevant for the future of the field is the ManyBabies framework (Frank
et al., 2017) which is currently running a large size replication on infants’ theory of
mind. The project ManyBabies 2 aims to run three waves of multi-lab studies developing
tasks to measure VOE, AL and interactive behaviors. In this effort, researchers from
different theoretical point of views will collaborate to devise the experiments and run
them in their own labs. The results of the present meta-analysis, then, constitute a first
step on that direction insofar as it provides an overall picture of the field that would
be comparable with a future overview of the area as new results are accumulated. Fourth,
the type of task employed seems to be relevant. When the year of publication and the
paradigm were included in the model, only the VOE paradigm –among the other two– produced
a significant effect. This consequence implies that infants reliably performed above
chance only within this methodology. But if false belief attribution were achieved at
these ages, then it should take place regardless of the task used, just as it was found
for elicited-response FBT. Studies employing within-subject design are critical to shed
light on this lack of convergence across paradigms (Poulin-Dubois & Yott, 2018; Powell et
al., 2018). In addition, many of the VOE effects are due to a single lab; further,
analytic decision-making varies substantially from paper to paper in this body of work.
These studies combine three looking time measures in different ways. Disruptive looking
and continuous-looking measures (used to end a trial), and a cumulative minimum looking
time (before which a trial could not end) are systematically varied across conditions and
studies without independent justification (Rubio-Fernández, 2019b). This fact certainly
obscures the interpretation of the results in the VOE paradigm. On the other hand, there
is a great variability in the confirmatory looking times across the FB conditions in the
VOE paradigm that it is surprising in itself, because it could not be predicted a priori
(all the looking times for expected and unexpected trials are reported in Table 9).
Looking times considerably varied from one experimental condition to another: they
stretched from 4.52 to 29.5 s when unexpected outcomes are presented and from 3.27 to 18.8
s in the case of expected events. At least part of this variability could be due to the
different materials employed in each task, the setting in which studies were embedded, and
the cultural context in which the studies were run. However, the existing variability
should be pointed out and make researchers to raise the question of how to set and justify
a criterion for expected versus unexpected looking times rather than stipulate them ad hoc
as it seems it is done depending on the times found.15 Anyway, what matters for the VOE
methodology is that longer looking times, in fact, indicate a surprise reaction rather
than duration per se. As it was well established long ago, longer looking may also
indicate a preference for novelty (Fantz, 1967): without surprise, longer looks might
indicate a preference for an event that is seen as new rather than unexpected. This point
brings us to a second consideration, common in the debate about the use of this
methodology to assess conceptual development in first year-olds: the familiarization phase
involved in the VOE paradigm might just induce perceptual expectations instead of the
assumed one in terms of belief and intention attribution. The fact that a long and
constant familiarization phase is required reinforces this possibility, providing the
participants with some anticipation of where the elements involved in the scene are likely
to move around. In other words, the familiarization phase might induce the infant to
attend to a particular location (Falck, Brinck, & Lindgren, 2014) or to a particular
perceptual configuration (Heyes, 2014)16 . However, the studies did not include a measure
of familiarization or habituation. An independent way to assess the generated
expectations, if any, during the familiarization phase would be welcome. The design should
also involve greater perceptual variability in terms of colors, distances, objects and all
the perceptual details of the situation. It could easily be tested in (i) a control
condition in which perceptual changes were introduced in the familiarization phase to
check whether the VOE response also appeared, thereby indicating conceptual understanding;
and (ii) a control condition in which the familiarization phase involved perceptually
different instances of the same intentional event. Additionally, if infants were already
able to ascribe beliefs in the familiarization phase, a very brief familiarization period
would suffice. Main effect analyses showed how multiple aspects, on their own and in
combination, decreased the probability of correct performance in these tasks. We may be
unaware of many other variables that moderate infants’ performance on these tasks.
Although we attempted to codify more parameters, like the separation between locations and
the delay between hiding the object and testing, most authors did not report such
information. For instance, the distance between the two locations (i.e., boxes) was
reported in only 13 out of 56 conditions. In those studies, such distance considerably
varied from 5 cm to 100 cm. On the other hand, the delay between hiding the object on its
last position and testing was not specified. In some cases, it could be estimated but it
was a difficult task since infants controlled the end of the trials in the VOE studies.
Any estimation, then, would be imprecise. The analysis of both parameters could give us a
hint for the explanation of the variability in the data.

<hs>  Study limitations</hs>
  ~~~~~~~~~~~~~~~~~

We remark some potential limitations to the current meta-analysis that simultaneously
constitute venues for new research. First, we only focused on peer-reviewed journal
publications; hence we did not have access to reports that failed to be published. The
present meta-analysis, as we claimed before, is a necessary first step to have a panoramic
view of the evidence published so far. It is also an open invitation to submit non-
published results in order to increase the number of false belief conditions considered
and rerun the analyses. Second, other moderators that we did not code could have
influenced the phenomenon (like nationality, the distance between locations, the delay
between hiding and testing, etc.). Third, although we chose to work with the more prolific
paradigms in the field, new ways to measure implicit false belief ascription are being
developed, like the use of electroencephalography (EEG) to record brain wave patterns
during the task (Southgate & Vernetti, 2014). Four, we selected sample sizes in which
infants were younger than 26 months old. In future work, it would also be compelling to
study the developmental trend of the capacity to attribute beliefs and see what happens in
the transition from two to three years old. But this decision would also imply broadening
the inclusion criteria in order to select verbal spontaneous-response paradigms, like the
verbal AL and the verbal VOE tasks (He, Bolz, & Baillargeon, 2012; Scott, He, Baillargeon,
& Cummins, 2012). Finally, we only included conditions in which infants were required to
attribute false beliefs to another. However, almost all studies include additional
conditions, like true belief as well as ignorance and other control conditions. Then,
infants’ above chance performance on implicit FBT would be doubtful if they, for example,
performed at chance or below chance level in the true belief condition. As Rubio-Fernández
(2019a) correctly pointed out, different kind of criteria have been proposed for passing
the FBT in infants and older children. While a differential performance between true and
false conditions is expected for infants, older children also have to perform above chance
level in both conditions in the traditional task. So, a careful analysis of infants’
performance in spontaneous-response true belief tasks is also needed to get a more
comprehensive view of infants’ mentalistic abilities.

<h>CONCLUSION</h>
----------

In conclusion, this meta-analysis is the first one in proposing an integrative view of all
the published studies on spontaneous-response false belief tasks in children younger than
26 months-old. Infancy is a key developmental period in which implicit methodologies are
being used to test the origins of many psychological constructs, such as theory of mind
and the specific capacity to attribute false beliefs. The emerging picture from this
systematic review, however, is puzzling. Although correct performance on spontaneous-
response FBT was on average more likely than incorrect performance, the analyses revealed
publication bias and high heterogeneity across the data. While several authors have shown
that preschoolers display a robust developmental pattern from a below-chance to an above-
chance performance in the standard FBT (Wellman et al., 2001), infants’ performance on the
nonverbal FBT is equivocal and does not show any clear developmental pattern.
Understanding the behavior of another agent according to her false belief would minimally
require robust attributions. We mean that the attributer, who ascribes a false belief to
an agent, should correctly help or inform her when necessary, look in anticipation to the
location where she will go and look longer when she acts incongruently with her epistemic
state. Experimental settings should move forward in that direction and test the same
children across a battery of implicit tasks that employ different paradigms. In this way,
we could examine individual differences in performance (e.g., infants that show
understanding across all the implicit measures and infants that fail all of them) and
convergent validity of the tests (like Poulin-Dubois & Yott, 2018 who failed to find
convergent validity). Similarly, tasks that concurrently combine two implicit measures are
welcomed, like measuring infants’ anticipatory look and (un)expected looks (e.g.,
Dörrenberg, Rakoczy, & Liszkowski, 2018) or participant’s anticipatory look and
interactive behavior (work in progress).


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<ART>Infants’ perception of goal-directed actions: A multi-lab replication reveals that infants anticipate paths and not goals
================================================================================

Authors: Kerstin Ganglmayer, Manja Attig, Moritz M. Daum, Markus Paulus
DOI: 10.1016/j.infbeh.2019.101340
Year: 2019
ASJC codes: 3204
Keywords: Action understanding, Anticipatory gaze shifts, Eye-tracking, Goal anticipation, Infancy, Replication

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Influential developmental theories claim that infants rely on goals when visually anticipating actions. A widely noticed study suggested that 11-month-olds anticipate that a hand continues to grasp the same object even when it swapped position with another object (Cannon, E., & Woodward, A. L. (2012). Infants generate goal-based action predictions. Developmental Science, 15, 292–298.). Yet, other studies found such flexible goal-directed anticipations only from later ages on. Given the theoretical relevance of this phenomenon and given these contradicting findings, the current work investigated in two different studies and labs, whether infants indeed flexibly anticipate an action goal. Study 1 (N = 144) investigated by means of five experiments, under which circumstances (e.g., animated agent, human agent) 12-month-olds show flexible goal anticipation abilities. Study 2 (N = 104) presented 11-, 32-month-olds and adults both a human grasping action as well as a non-human action. In none of the experiments did infants flexibly anticipate the action based on the goal, but rather on the movement path, irrespective of the type of agent. Although one experiment contained a direct replication of Cannon and Woodward (2012), we were not able to replicate their findings. Overall our work challenges the view that infants are able to flexibly anticipate action goals from early on, but rather rely on movement patterns when processing other's actions.

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<h>INTRODUCTION</h>
------------

During the first year of life, infants start to visually anticipate other people’s actions
(Adam et al., 2016; Ambrosini et al., 2013; Cannon & Woodward, 2012; Daum, Gampe, Wronski,
& Attig, 2016; Falck-Ytter, Gredebäck, & von Hofsten, 2006). For example, 12-month-olds
anticipate the goal of a simple manual reach-and-transport action (Falck-Ytter et al.,
2006). However, infants show difficulties in anticipating actions when situations become
more complex (Gredebäck, Stasiewicz, Falck-Ytter, Rosander, & von Hofsten, 2009). In
addition, it has been suggested that action anticipation depends on whether a human or a
non-human agent is performing the action (Cannon & Woodward, 2012; Daum, Attig, Gunawan,
Prinz, & Gredebäck, 2012; Kanakogi & Itakura, 2011) and that movement characteristics of
actions such as distances, durations and velocities have a strong impact on the
anticipation of the goal of observed actions (Daum, Gampe et al., 2016). In this paper we
present a series of studies conducted in several laboratories that investigated whether
infants and adults are able to visually anticipate an action goal when two goals are
available and whether they differentiate between human and non-human (i.e. animated)
agents. Being able to understand that other people have goals is essential for processing
social information. Understanding the goal-directedness of human actions has been related
to the ability of perspective taking (Krogh-Jespersen, Liberman, & Woodward, 2015) and of
coordinating one’s own actions with others (Sebanz, Bekkering, & Knoblich, 2006).
Influential developmental theories have therefore stressed the role of goal encoding and
anticipation for early social-cognitive development (e.g., Woodward, 2009). In the study
by Falck-Ytter et al. (2006), infants anticipated the action of a hand that placed objects
into a container (for a related setup see also Brandone, Horwitz, Aslin, & Wellman, 2014).
However, movement path and goal were confounded in this paradigm, and for this reason, no
conclusion is possible whether infants’ anticipations were based on the information
provided by the movement or the information about the action goal. The encoding of an
action as goal directed goes beyond the representation of pure physical movements.
Accordingly, a study by Cannon and Woodward (2012) presented a manual reaching action with
not only one but two possible action goals to infants at the age of 11 months. After being
familiarized with the hand always grasping the same of the two objects, the objects’
position changed place for the following test trial. During the test trials, the infants
observed an uncompleted manual movement where the hand stopped before indicating a clear
movement direction. The infants showed anticipations towards the familiarized object in
the now new location. This indicates that infants did not just anticipate the mere
movement pattern but that they encoded the action as being directed towards a specific
goal. This goal attribution served as the basis for the subsequent goal anticipation. As
striking as these results are, different results were obtained by Daum et al. (2012). They
used a similar methodological approach with a slightly modified paradigm. In their study,
participants were familiarized with an animated fish that moved behind an occluder to one
of two goal objects. In the test phase, with the location of the two goal objects being
swapped, only 3-year-olds and adults anticipated the correct goal. Two-year-olds
anticipated both the path and the goal, indicating that they seem to be in a transition
phase. In contrast, 9- and 12-month-olds expected the fish continue to move on the
movement path as in the familiarization phase. These contradictory findings represent a
puzzle, particularly for developmental theories that capitalize on the role of goal
understanding in early development. Notably, a number of studies that used a similar
paradigm as Cannon and Woodward (2012) do not give a clear picture either. These studies
are different from Cannon and Woodward as the human agent sat at a table and was fully
visible to the participants (Krogh-Jespersen & Woodward, 2014, 2018; Krogh-Jespersen et
al., 2015; Krogh-Jespersen, Kaldy, Valadez, Carter, & Woodward, 2018; Paulus, 2011).
Participants observed an agent grasping one of two objects for once, followed by two
consecutive test trials in which the agent performed an uncompleted reaching action.
Again, the objects’ position was swapped for test trials. Krogh-Jespersen and Woodward
(2014) demonstrated with this paradigm that goal-directed fixations of 15-month-olds
needed more time to be initialized, indicating additional cognitive effort when taking an
action goal into account instead of when the mere movement pattern was anticipated.
Interestingly, goal-anticipations were not demonstrated consistently in this paradigm for
older children. Two-year-olds anticipated neither the goal nor the previous location
systematically (Krogh-Jespersen et al., 2018) and 21-month-olds only made goal-directed
anticipations in the first, but demonstrated chance performance in the second test trial
(Krogh-Jespersen et al., 2015). Overall, there is a heterogeneous pattern of results on
whether or not young children show flexible goal anticipations for a human actor. Given
this evidence it is on the one hand unclear from which age on infants anticipate other’s
actions as goal-directed and on the other hand, whether they differentiate between non-
human and human agents. Developmental theories claim that one’s own experiences are
fundamental for understanding others actions. This is also known as the human first-view
(Luo & Baillargeon, 2005; Meltzoff, 1995; Woodward, 2005). Because a human hand performed
the action in the study by Cannon and Woodward (2012), this could have facilitated
infants’ goal encoding. Some suggest that infants use their own motor abilities when
anticipating other’s actions (e.g., Kilner, Friston, & Frith, 2007; Paulus, 2012). For
example Krogh-Jespersen and Woodward (2018) demonstrated that already 8-month-olds
anticipate an action goal, but only after they practiced reaching for an object
themselves. Others suggest that infants are simply more familiar with human hands than
with a non-human agent (Ruffman, Taumoepeau, & Perkins, 2012). This account would imply
that infants are more experienced with hands grasping objects than with moving fish, as
they have probably not often seen an animated fish before. Indeed, previous studies
demonstrated earlier anticipations within infants when actions were more familiar (Cannon
& Woodward, 2012; Filippi & Woodward, 2016; Gredebäck & Kochukhova, 2010; Gredebäck &
Melinder, 2010; Kanakogi & Itakura, 2011). Cannon and Woodward (2012) showed that infants
did not anticipate an action as goal-directed when performed by a mechanical claw (see
also Adam et al., 2016; Kanakogi & Itakura, 2011). In contrast, the so called all agents-
view (Luo & Baillargeon, 2005) proposes that infants attribute goals to any individual
that can be identified as an agent (Leslie, 1995). It has been argued that humans
attribute goals to non-human agents as long as they show specific characteristics, like
self-propelledness (Luo & Baillargeon, 2005), equifinal variations (Kamewari, Kato, Kanda,
Ishiguro, & Hiraki, 2005), or an action outcome produced by the agent (Adam, Reitenbach, &
Elsner, 2017). However, most empirical evidence concerning the all agents-view comes from
looking-time studies (e.g. Gergely, Nádasdy, Csibra, & Bíró, 1995; Luo & Baillargeon,
2005). Thus, it is still an open question whether infants are able to generate online
anticipations when perceiving non-human instead of human actions. However, as it is
neither empirically nor theoretically clear when and to what extent infants are able to
anticipate an action based on the action goal and not on the movement pattern, we report
two studies, assessed in two different labs, that address this question in further detail.
Study 1 contains five experiments, which disentangle the precise methodological issues
between Cannon and Woodward (2012) and Daum et al. (2012). The goal of the first study was
to investigate which aspects are fundamental for infants’ goal encoding abilities within
12 months of age. Two major questions guided this research: First, whether infants show
goal-directed anticipations for non-human as well as for human actions equally, as
proposed by the all agents-view, or whether infants are better in anticipating the goal of
a human action than the goal of a non-human action, as suggested by the human first-view.
Second, whether the seemingly contradictory findings of Cannon and Woodward (2012) and
Daum et al. (2012) are a result of further methodological differences. In the study by
Daum et al. (2012), the agent shortly disappeared behind an opaque occluder. This paradigm
was used to trigger participant’s eye-movements to the position where they expect the
agent to reappear (adapted from Kochukhova & Gredebäck, 2007). However, infants have to
maintain the association between the agent and the object when the agent is not visible,
which might require additional cognitive capacities, such as memory or attention (Hespos,
Gredebäck, von Hofsten, & Spelke, 2009; Jonsson & von Hofsten, 2003). This additional
requirement of cognitive resources could be another reason why infants in the Daum et al.
study (2012) showed goal-directed anticipations only from later on. Further, the two
studies used different designs in providing the stimuli. Cannon and Woodward (2012)
presented infants four blocks, which each contained three familiarization trials, one swap
trial (in which the objects’ position changed place) and one test trial. Daum et al.
(2012) presented participants eight familiarization trials, one swap trial and two test
trials. The more frequent presentation of learning trials in the Daum et al. study (2012)
could have increased the attentional focus to the location of the object. As was
demonstrated by Paulus et al. (2011), already 9-month-olds based their anticipations of an
agent’s choice for a path on the agent’s previous choices. Further, it is also possible
that infants encoded both goal and path of the action simultaneously, thus it is unclear
which aspect dominates infants visual anticipations. The following five experiments of
Study 1 present a step by step approximation of the paradigm from Daum et al. (2012) to
the paradigm of Cannon and Woodward (2012). The last experiment represents a replication
as close as possible to the study by Cannon and Woodward (2012). Initially, we
hypothesized that the type of agent and the presence of an occluder influence infants’
goal anticipations. Following the human first-view, we expected more goal anticipations in
the experiments that contain a human agent. In contrast, the all agents-view predicts no
differences in the goal anticipations between all five experiments, because human and non-
human agents are processed equally from early on. We would further assume that infants
show more goal-directed anticipations in the experiments without an occluder. The second
study, conducted in a different lab, directly compared the two paradigms in a within-
subjects design. That is, Study 2 assessed whether children and adults show systematic
differences in their anticipations when observing human and non-human goal-directed
actions. A second goal of Study 2 was to answer the question whether the two paradigms
assess the same underlying ability regarding their goal anticipations, as proposed by the
all agents-view. Since non-human agents are widely used in studies on social perception
within children (e.g., Hamlin, Wynn, & Bloom, 2007; Kuhlmeier, Wynn, & Bloom, 2003), it is
crucial to find out whether they actually perceive animated stimuli in the same way as
human stimuli. We tested 11-month-olds as our youngest age group, since this age group
showed goal-directed anticipations in the study by Cannon and Woodward (2012). We also
included 32-month-olds, because developmental changes of children’s goal anticipations for
an animated agent between the age of 24 and 36 months were observed by Daum et al. (2012).
Developmental changes were also observed by Krogh-Jespersen et al. (2015, 2018), although
they found a decrease of goal-directed anticipations for a human agent in toddlers. Given
this puzzle, the inclusion of 32-month-olds in Study 2 seems informative. We additionally
wanted to clarify whether and how adults differ in their perceptions of the stimulus
material presented in the two paradigms. Accordingly, stimulus material was presented in a
within design with a human- and a non-human animated agent. One is based on Cannon and
Woodward (2012) and contained a human hand grasping one of two objects; the other is based
on Paulus, Schuwerk, Sodian, and Ganglmayer (2017) and contained an animated agent walking
along a path towards one of two targets (similar to Daum et al., 2012, where an opaque
occluder was used). The human first-view proposes goal encoding for 11- and 32-month-olds
to be more likely in the hand- than in the path-paradigm (Cannon & Woodward, 2012; Daum et
al., 2012). In contrast, the all agents-view proposes goal anticipations in both
paradigms. Either of the theories predicts adults to visually anticipate an action goal
for both human- and non-human agents (Daum et al., 2012; Pfundmair, Zwarg, Paulus, &
Rimpel, 2017). The current effort from two labs is a valuable approach with the aim to
conceptually and partly even directly replicate a finding that is central in a heated
debate in developmental psychology on the early origins of social cognition. It is
essential to know in greater detail to which extent the findings by Cannon and Woodward
(2012) are replicable before drawing strong theoretical conclusions. Thus, one central
point of this endeavor was to examine whether or not we could (conceptually or directly)
replicate Cannon and Woodward (2012) and contribute thus to the theoretical debate by
examining the robustness of a key finding.

<h>STUDY 1</h>
-------

Study 1 investigates whether 12-month-olds are able to make goal-directed anticipations.
Given the contradicting findings of Cannon and Woodward (2012) and Daum et al. (2012), the
aim was to test which aspects are relevant for infants’ ability to anticipate an action
goal. Therefore, the stimuli of Daum et al. (2012) were assimilated step-by-step over five
experiments to the stimulus material used by Cannon and Woodward (2012). In Experiment 1
the animated stimuli of Daum et al. (2012) were used but displayed in the same
presentation order as in Cannon and Woodward’s study (2012). In Experiment 2, the occluder
was removed and the action direction was changed from vertical to horizontal, whereas the
fish still remained as the agent. In Experiment 3, the fish was replaced by a human hand
as the agent. Additional adaptions regarding timing were made in Experiment 4. Finally,
Experiment 5 used newly filmed videos, which were designed to be as comparable to the
stimuli of Cannon and Woodward (2012) because the original stimulus material was not
available. According to the human first-view, one would hypothesize to find anticipations
towards the previously observed movement path or random gaze behavior in conditions using
a non-human agent (Experiment 1 and Experiment 2). In contrast, one would expect
anticipations towards the previously observed goal in the conditions in which a human hand
served as the agent (Experiment 3, 4 and 5). According to the all agents-view infants
should demonstrate in all five experiments goal directed anticipations. We further
expected that experiments without an occluder would facilitate infants processing of the
action, thus we expected to find an increase of goal-directed anticipations in the
conditions that did not make use of an occlusion paradigm.

<hs>  Experiment 1</hs>
  ~~~~~~~~~~~~

In the first experiment, the influence of the design of stimuli presentation on infants’
encoding of the action was tested. Infants were shown the stimulus material as used by
Daum et al. (2012), an animated fish that moved towards one of two goal objects and was
briefly occluded. We combined the stimulus material with the procedure used by Cannon and
Woodward (2012) where the stimuli were presented in four blocks; each block contained
three familiarization trials, one swap trial, and one test trial. Further some criteria
for inclusion (three of four blocks with usable data) and analysis of gaze shifts (gaze
shift from the start-AOI to one of the goal-AOIs with 200 ms fixation) were the same as in
the study by Cannon and Woodward (2012).

        <hss>Method</hss>

        The preprocessed eye-gaze data of both studies is available at
        https://osf.io/bucrv/?view_only=fa9e929fe4524755b38383fd223378f5. To protect
        participants’ data privacy, demographic information is not shared in this data
        set.

            <hss>Participants</hss>

            The sample included 24 healthy 12-month-olds (12 girls, mean age = 12 months
            and 4 days; 11;21–12;15). Ten additional infants had to be excluded due to
            inattention and restlessness (n = 1), crying (n = 4), technical problems (n =
            1) and failure to provide enough eye-tracking data (n = 4; see Measures
            section for details).

            <hss>Stimuli</hss>

            Participants were presented videos of a red-blue fish, that moved by itself
            (self-propelledness) on a blue background. At the beginning of the videos, the
            fish was situated at the bottom in the middle of the screen. The targets were
            a yellow duck and a colored ball placed on the left and right corner at the
            top of the screen (see Fig. 1). In the middle of the screen was a round
            occluder in the color of wooden grain. Infants saw four blocks and each block
            consisted of three familiarization trials, one swap trial and one test trial.
            Before each block an attention getter was presented to direct infants’
            attention to the screen. In the familiarization trial (total duration was
            15.12 s) the fish first jumped up and down (accompanied by a sound) for 3 s
            and then moved towards the occluder (2.44 s). The agent disappeared behind the
            occluder for 0.92 s and reappeared to aim for one target. At the goal object
            (after 2.08 s) the fish poked the target for three times (3 s) and the target
            reacted with small movements, which was combined with a sound. During the swap
            trial, the two targets changed place (4.96 s) and were shown for another
            second after the changeover to the infant. In the test trials, the fish again
            jumped up and down (3 s) before approaching the occluder (2.44 s). The agent
            stayed behind the occluder for the rest of the trial (another 10.12 s). The
            total duration of the whole presentation (all four blocks) was 5 min and 24 s.
            Target object as well as the position of the target object was counterbalanced
            between participants.

            <hss>Setting and procedure</hss>

            For testing, infants were seated in a car safety seat (Maxi Cosi Cabrio) with
            a distance of 60 cm between the eye tracker and the child and stimuli were
            presented on a 17”-monitor (25° × 21°). Gaze was measured through a Tobii 1750
            eyetracker (precision: 1°, accuracy: 0.5° and sampling rate: 50 Hz) and a
            nine-point infant calibration was used. The stimuli-presentation was conducted
            via the software ClearView (version 2.7.1., Tobii).

            <hss>Measures</hss>

            To analyze infants’ eye-movements, three areas of interest were defined based
            on Daum et al. (2012, see Fig. 1). The lower area was the starting area of the
            agent, the other two included the two goal objects. For all measures, we
            analyzed the first fixation participants performed from the start area to one
            of the goal-AOIs (first look analysis). Infants had to fixate the goal-AOI for
            200 ms, within a radius of 50 pixels (based on Cannon & Woodward, 2012). Gaze
            shifts were categorized as anticipatory, when the first fixation was directed
            in one of the goal-AOIs before the agent reappeared from the occluder during
            familiarization trials (occlusion-time plus 200 ms). In the test trials, this
            time interval was extended for another 1000 ms (see Cannon & Woodward, 2012),
            because the agent did not reappear from behind the occluder (occlusion-time
            plus 200 ms plus 1000 ms). Gaze shifts were categorized as reactive, when
            fixations to one of the goal-AOIs occurred after the agent reappeared in the
            familiarization trials. For the test trials, a fixation to one of the goal
            AOIs after the 2120 ms was categorized as reactive. First, we calculated the
            anticipation rate, which is the relation of all anticipations to all gaze
            shifts (anticipatory as well as reactive). This measure indicates how much
            participants generally perform anticipations; it is not including information
            to which specific location infants anticipated. To further analyze the type of
            anticipations, the accuracy rate was calculated. For this, the number of
            anticipations towards the specific target AOI was divided by the total number
            of gaze shifts (anticipatory and reactive). For this analysis, the number of
            anticipations was averaged over all familiarization trials and test trials.
            For familiarization trials the goal-related accuracy rate (ratio of goal
            anticipations and all gaze shifts) and the non-goal-related accuracy rate
            (ratio of anticipations to the other object and all gaze shifts) were defined.
            To analyze infants’ learning performance in the familiarization phase, two
            scores were compared (Daum et al., 2012): The accuracy score of the averaged
            anticipations of the first familiarization trials of all four blocks and the
            accuracy score of the averaged anticipations of the last familiarization
            trials of all four blocks. For test trials the identity-related accuracy rate
            (ratio of anticipations to the goal object in the new location and all gaze
            shifts) and the location-related accuracy rate (ratio of anticipations to the
            other object in the old location and all gaze shifts) were generated. Again,
            the anticipations were averaged over all four test trials for each score. In
            sum, for both the familiarization as well as the test phase, each accuracy
            score consists of four trials. To be included in analysis, infants had to
            watch the screen at least 200 ms from the start of the movie until the agent
            disappeared behind the occluder; and 200 ms after disappearance until the end
            of the movie. Infants were included for final analysis if they had at least
            three of four test trials that fulfilled these criteria (Cannon & Woodward,
            2012). Further they had to look at the swap trial for at least 2000 ms to be
            included. In all experiments of Study 1, we controlled for the possible
            influence of the type of target and position of target on the number of
            anticipations for the first four familiarization trials and test trials. As no
            significant influence could be found in none of the five experiments, the
            following analysis was averaged over these factors. Further, the anticipation
            rate of the first four and last four familiarization trials, as well as test
            trials, were averaged across the four blocks.

            <hss>Anticipation rate</hss>

            The anticipation rate for the whole experiment was 0.79 (SD = 0.15) and 0.74
            (SD = 0.20) for the familiarization phase only. We compared the anticipation
            rate of the last familiarization trials with anticipation rate of the test
            trials with a Wilcoxon signed-rank test and found a significant difference.
            Participants anticipated more in the test trials (M = 0.91, SD = 0.17) than in
            the last familiarization trials (M = 0.72, SD = 0.30), with z = −2.92, p =
            .003, r = .42.

            <hss>Familiarization phase</hss>

            A Wilcoxon signed-rank test was calculated to compare the goal-related
            accuracy rate with the non-goal-related accuracy rate in the last
            familiarization trials. Indeed, children anticipated more to the goal (M =
            0.58, SD = 0.34) than to the non-goal (M = 0.14, SD = 0.25), with z = −3.25, p
            = .001, r = −.47. This indicates that the children learned to correctly
            anticipate the reappearance of the agent from behind the occluder during the
            familiarization phase. A comparison of the first familiarization trials
            averaged across the four blocks (M = 0.51, SD = 0.34) and the last
            familiarization trials did not show a significant increase of goal-directed
            anticipations over time, z = −1.41, p = .16, r = −.20.

            <hss>Test phase</hss>

            The Wilcoxon signed-rank test demonstrated a higher location-related accuracy
            rate (M = 0.60, SD = 0.32) than an identity-related accuracy rate (M = 0.31,
            SD = 0.31), z = −2.14, p = .03, r = −.31. Further, a comparison of the goal-
            related accuracy rate of the last familiarization trials with the identity-
            related accuracy rate in the test trials showed a significant difference, z =
            −2.56, p = .01, r = −.37. In contrast, there was no significant difference
            between the goal-related accuracy rate of the last familiarization trials and
            the location-related accuracy rate of the test phase, z = −0.34, p = .73, r =
            −.05. For the following analysis, only anticipations (and not reactions) were
            used. A Chi-Square-Test was calculated over the number of identity- and
            location-related anticipations in test trials. Infants anticipated the
            reappearance of the agent based on location (n = 51) than on identity of the
            goal object (n = 28), χ²(1) = 6.70, p = .01.

            <hss>Additional analysis</hss>

            Finally, when interpreting these findings, and comparing them to the original
            study, one has to consider that the data was differently analyzed than the
            original study of Cannon and Woodward (2012). The inclusion criteria used are
            stricter than in the original study by Cannon and Woodward (2012). For
            example, infants had to look for a specific time at the swap trial or fixate
            the start area for a certain time before the agent moved behind the occluder,
            etc. Also, gaze shifts that occurred after a certain time were no longer
            defined as anticipatory, but as reactive. The resulting scores were calculated
            different to the original study, which used a proportion score and did not
            include non-anticipations. Although our use of stricter criteria should result
            in a more reliable assessment of true goal anticipation, one could argue that
            the different results are caused by these stricter criteria. To exclude this
            possibility, we additionally analyzed our data as closely as possible to the
            approach by Cannon and Woodward (2012; details can be seen in the
            supplementary material). This additional analysis did not change the pattern
            of results; the mean proportion score of 0.34 (SD = 0.30) was significantly
            different from chance with t(23) = −2.64, p = .015, Cohen’s d = 0.54,
            indicating a significant looking bias towards the location and not the goal.

        <hss>Discussion</hss>

        Experiment 1 aimed to examine whether the different findings reported in Cannon
        and Woodward (2012) and Daum et al. (2012) are the result of differences in the
        procedure of the stimulus presentation. The findings show that 12-month-olds
        learned to correctly anticipate the reappearance of the agent by the end of the
        familiarization phase. However, in the test trials, infants anticipated the action
        based on the location of the goal object and not on its identity. Therefore, it
        doesn’t seem that the more frequent presentation of the action in Daum et al.’s
        study (2012) highlighted the path of the action and caused children’s location-
        related anticipations. Ultimately, the divergent findings are not caused by the
        different presentation order and amount of learning and test trials. The next
        experiment will test whether the occluder has a significant effect on infants’
        anticipations.

<hs>  Experiment 2</hs>
  ~~~~~~~~~~~~

In Experiment 2, the animated stimuli were used without an occluder; the agent was visible
the whole time. Additionally, the direction of the movement was changed from a vertical to
a horizontally movement (as in Cannon & Woodward, 2012). Given the claim that horizontal
movements are easier to anticipate for infants (Gredebäck, von Hofsten, & Boudreau, 2002),
we intended to facilitate anticipations and to test whether a change of the movement
direction increases infants’ identity-related anticipations. Also to draw infants’
attention to the screen at the beginning of the action, an ostensive cue was integrated (a
voice stated “Look”).

            <hss>Participants</hss>

            Again, the sample included 24 healthy 12-month-olds (12 girls, mean age = 12
            months and 4 days, 11;20–12;10). Nine additional infants had to be excluded
            due to inattention and restlessness (n = 2), crying (n = 1) or failure to
            provide enough eye-tracking data (n = 6).

            <hss>Stimuli and procedure</hss>

            The experimental setup was exactly the same as in Experiment 1, only that the
            targets (duck 3.9° × 4.1°, penguin 3.5° × 4.0°) were now situated in the two
            corners at the right side of the monitor (see Fig. 2). Further the starting
            point of the agent (1.9° × 4.0°) was close to the left monitor side. No
            occluder was visible and the background was light blue. Stimuli where similar
            to Experiment 1 with the exception that in the first two seconds of each movie
            a voice stated “Look”, to catch infants’ attention. In the familiarization
            trial the agent jumped up and down (1.96 s, combined with a whistle sound) and
            started to move towards the target objects. After 4.72 s the agent took a turn
            to one of the targets, which he reached after another 2.60 s and poked it (see
            Experiment 1). The whole familiarization trial lasted for 14.92 s. In the swap
            trial the two objects changed position within 5.96 s and the whole trial
            lasted for another 5 s. Test trials were similar to Experiment 1, except that
            the agent, when approaching the target, stopped after 4.72 s just after the
            middle of the scene and remained there for the rest of the trial (another 4.96
            s). The whole presentation time for the movies was 5 min and 2 s. Again goal
            object and position of goal object were counterbalanced between participants.

            <hss>Measures</hss>

            For Experiment 2 the calculation of the measures followed Experiment 1. Areas
            of interest can be seen in Fig. 2. Gaze shifts were defined as anticipatory,
            if anticipations took place from the beginning of the movement towards the
            objects until the agent made a turn to one of the targets (for test trials:
            time of standstill of the agent plus 1000 ms). This results in an anticipatory
            period of 5720 ms for test trials in total. All gaze shifts that occurred
            after the turn of the agent were coded as reactive (in test trial after the
            additional 1000 ms).

            <hss>Anticipation rate</hss>

            For this experiment the anticipation rate was 0.81 (SD = 0.14) for the whole
            experiment, and 0.76 (SD = 0.19) for the familiarization phase. As in
            Experiment 1, we found an increase in anticipations in the test trials (M =
            0.94, SD = 0.13) compared to the last familiarization trials of all four
            blocks (M = 0.74, SD = 0.30), with z = −2.62, p = .01, r = −.38.

            <hss>Familiarization phase</hss>

            Infants showed in the last familiarization trials more anticipations to the
            goal (M = 0.60, SD = 0.35) than to the non-goal (M = 0.14, SD = 0.21), z =
            −3.43, p = .001, r = −.50. The goal-related accuracy rate in the first
            familiarization trials (M = 0.52, SD = 0.33) was not significantly different
            from the goal-related accuracy rate in the last familiarization trials (M =
            0.60, SD = 0.35), z = −0.85, p = .40, r = −.12. The infants quickly learned to
            correctly anticipate the target.

            <hss>Test phase</hss>

            The analysis showed no significant difference between the identity-related
            accuracy rate (M = 0.41, SD = 0.35) and the location-related accuracy rate (M
            = 0.54, SD = 0.33), z = −1.12, p = .26, r = −.16. Further, a comparison
            between the goal-related accuracy rate in the last familiarization trials (M =
            0.60, SD = 0.35) with the identity-related accuracy rate (M = 0.41, SD =
            0.35), z = −1.58, p = .12, r = −.23, and the location-related accuracy rate (M
            = 0.54, SD = 0.33), z = −0.91, p = .36, r = −.13, was not significant. Infants
            anticipated in the test phase towards the goal as well as to the original
            location of the object. Following Experiment 1, only anticipations were
            analyzed. The Chi-Square test over the four test trials between identity- (n =
            37) and location-related gaze-shifts (n = 47) was not significant, χ²(1) =
            1.19, p = .28. The additional analysis, with the same measure and inclusion
            criteria as Cannon and Woodward (2012, see Experiment 1 for details) revealed
            chance performance of the infants’ looking behavior, with t(23) = −0.72, p =
            .482, Cohen’s d = 0.15, M = 0.45, SD = 0.33.

        <hss>Discussion</hss>

        Experiment 2 investigated whether the absence of an occluder and the change in
        movement direction (from vertical to horizontal) had a facilitating effect on
        infants’ goal encoding abilities. Results of the test trials demonstrated that
        anticipations of the 12-month-olds were at chance level. They neither showed a
        significant looking bias towards the goal object, nor to the old location. As they
        demonstrated goal-directed anticipations at the end of the familiarization phase,
        problems in learning the association between the agent and the target are not the
        case. It seems likely that the absence of the occluder facilitated infants’ goal
        anticipations (Hespos et al., 2009; Jonsson & von Hofsten, 2003). It seems easier
        for infants to encode the goal of an action, when the agent is visible for the
        whole time. The additional change from a vertical to a horizontal position and the
        use of a verbal cue at the beginning of the action could have facilitated the task
        as well. For the next experiment we wanted to see whether the type of agent
        influences infants’ anticipations.

<hs>  Experiment 3</hs>
  ~~~~~~~~~~~~

To test whether infants are more likely to flexibly attribute goal-directed behavior to a
human agent, the animated fish was replaced by a human hand that moved to and grasped one
of two goal objects. Timing and procedure of the action, as well as size of the targets
differed from Cannon and Woodward (2012), as they remained the same as in Experiment 1 and
2.

            <hss>Participants</hss>

            The final sample included 32 healthy 12-month-olds (16 girls, mean age = 12
            months and 1 day, 11;15–12;15). The sample size is larger for this and the
            following experiments of Study 2, due to more conditions than in the previous
            experiments (see section Stimuli and Procedure). Eleven additional infants
            were tested but excluded due to inattention and restlessness (n = 4), crying
            (n = 2), or not enough eye-gaze data (n = 5).

            <hss>Stimuli and procedure</hss>

            Stimuli in Experiment 3 are the same as in Experiment 2, except for the
            following differences: Instead of an animated fish, a human hand (4.6° × 7.6°)
            was filmed. The two targets (duck 4.8° × 4.9°, penguin 4.5° × 4.8°) still have
            been animated with CINEMA 4D (Maxon, Version R10). The human hand was inserted
            in the video via a blue screen method (see Fig. 3). For the familiarization
            trials the human hand started to move its fingers and a whistle sound occurred
            (1.92 s). Then the hand moved from the left side in the direction of the
            targets. After 4000 ms the hand crossed the middle and made a turn to one of
            the targets. The hand reached the target after 2 s, grasped it (1.12 s) and
            moved it further to the right (action effect plus sound lasted for 0.92 s).
            The whole familiarization trial took 14 s. The test trials started exactly
            like the familiarization trials. After the hand started to move towards the
            middle, it stopped after 4 s for another 5 s. Duration of the test trial was
            14.12 s in total. The whole presentation lasted 4 min and 48 s. Type of goal
            object and position of the object were counterbalanced between participants.
            Further, the orientation of the hand, that is, thumb pointing towards the goal
            object, as well as left and right hand were counterbalanced within
            participants. This led to four different combinations for the blocks, namely
            1) familiarization: right hand, test trial: right hand, 2) familiarization:
            right hand, test trial: left hand, 3) familiarization: left hand, test trial:
            left hand, 4) familiarization: left hand, test trial: right hand. The order of
            combination was also counterbalanced. For analysis the same scores were
            calculated as in Experiment 1 and 2. Gaze shifts for test trials were defined
            as anticipatory if they occurred within a time period of 5000 ms (from the
            beginning of the reaching action onwards). Also inclusion criteria remained
            the same. AOIs were identical to Experiment 2. To control for an influence of
            hand orientation on the scores, Kruskal–Wallis tests were performed for
            Experiment 3, 4 and 5 and turned out not significant. Therefore, the following
            analysis was averaged over this factor.

            <hss>Anticipation rate</hss>

            For the whole experiment, the anticipation rate was 0.91 (SD = 0.10) and for
            the familiarization phase 0.89 (SD = 0.12). Although participants performed
            more anticipations in the test trials (M = 0.95, SD = 0.11) than in the last
            familiarization trials of all four blocks (M = 0.88, SD = 0.19), the Wilcoxon-
            signed rank test was not significant for this experiment, with z = −1.86, p =
            .06, r = −.23.

            <hss>Familiarization phase</hss>

            The Wilcoxon signed-rank test showed that the goal-related accuracy rate in
            the last familiarization trials (M = 0.60, SD = 0.34) was significantly higher
            than the non-goal related accuracy rate of the last familiarization trials (M
            = 0.28, SD = 0.31), z = −2.58, p = .01, r = −.32. There was no significant
            difference between the goal-related accuracy rate of the first familiarization
            trials (M = 0.53, SD = 0.27) and the goal-related accuracy rate of the last
            familiarization trials (M = 0.60, SD = 0.34), z = −1.21, p = .23, r = −.15.

            <hss>Test phase</hss>

            There was no significant difference between infants’ identity-related (M =
            0.40, SD = 0.31) and location-related (M = 0.55, SD = 0.28) accuracy rate, z =
            −1.41, p = .16, r = −.18. Infants anticipated more to the goal in the
            familiarization phase (M = 0.60, SD = 0.34) than to the same goal in the test
            trials (M = 0.40, SD = 0.31), z = −2.26, p = .02, r = −.28. In contrast they
            did not differ in their anticipations to the goal in the last familiarization
            phase (M = 0.60, SD = 0.34) and their anticipations to the old location in the
            test phase (M = 0.55, SD = 0.28), z = −0.74, p = .46, r = −.09. A further Chi-
            Square-Test with the number of anticipations in all four test trials between
            goal- and identity-related anticipations turned out to be not significant,
            χ²(1) = 3.64, p = .057, although a tendency towards more location-related (n =
            65) than identity-related anticipations (n = 45) could be observed. Again,
            also the additional analysis according to Cannon and Woodward (2012) resulted
            in chance performance of the infants, with t(31) = −1.53, p = .137, Cohen’s d
            = 0.27, M = 0.43, SD = 0.27.

        <hss>Discussion</hss>

        Experiment 3 examined whether the type of agent has an influence on infants’ goal
        anticipations. Therefore, a human hand reaching for one of two objects was
        presented to 12-month-olds. Results showed that infants did not increase their
        goal-related anticipations in this experiment. In contrary, they showed the
        tendency to anticipate the grasping action based on the movement path and not the
        goal object. Theoretically this finding speaks against the claim that experience
        with an action improves infants’ anticipations (Cannon & Woodward, 2012; Gredebäck
        & Melinder, 2010; Kanakogi & Itakura, 2011; Kochukhova & Gredebäck, 2010). Still,
        it is not clear which factors caused the differences between our experiments with
        Daum et al’s findings (2012) and Cannon and Woodward’s (2012). Some differences
        (timing of the action, start of the presentation, effect of the action, type of
        goal objects) have remained in the last three experiments. For example, in
        Experiment 1, 2 and 3, the animated objects visibly swap places in the swap trial
        and are not presented already in their new position like in Cannon and Woodward’s
        (2012) stimuli. It is not clear in what way this could have affected their
        anticipations. Hence changes in the stimuli material have been made on these
        factors for the next experiment.

<hs>  Experiment 4</hs>
  ~~~~~~~~~~~~

Because in Experiment 2 and 3, the anticipations were ambivalent, this could be an
indication for an increase of identity-related gaze shifts caused by the nature of the
agent. To further assess this potential shift of processing caused by the stimulus
material, the stimuli have been changed further in Experiment 4 to increase similarity to
the stimuli of Cannon and Woodward (2012). Therefore, the timing of the action and the
action effect were adapted. Additionally, movements of the hand at the beginning of the
trials were removed and the swapping procedure of the target objects was no longer
presented. Participants only observed a still frame of the already swapped objects. The
rest of the factors, such as blocked design, no occluder, direction of movement, and type
of agent stayed the same as in Experiment 3. Differences to Cannon and Woodward (2012)
remained regarding the target objects (a duck and a penguin here, a green frog and a red
ball in Cannon & Woodward, 2012). Also following Experiment 3, the agent was inserted via
a blue screen method and targets were still animated. Further, type and size of targets
were different than in the original study.

            <hss>Participants</hss>

            The sample included 32 healthy 12-month-olds (16 girls, mean age = 11 months
            and 26 days, 11;12-12;11). Thirteen additional infants were tested but
            excluded due to inattentiveness and restlessness (n = 1), crying (n = 1), not
            enough eye-tracking data (n = 10) or technical problems (n = 1).

            <hss>Stimuli and procedure</hss>

            Movies were similar to Experiment 3 and adapted to the videos of Cannon and
            Woodward (2012). Each movie started with a black still frame for 0.36 s. After
            0.04 s the agent moved into the picture. After another 1.56 s the hand made a
            turn into the direction of a target. The agent reached the target after 1.04
            s. He grasped the object and did not move thereafter (no action effect, only
            sound; 0.4 s). After 0.52 s the black screen was presented for 0.48 s. One
            familiarization trial lasted 4.36 s. For the swap trial a still frame with the
            objects in changed position was presented for 3.56 s. For test trials the
            agent again moved into the picture after 0.04 s. Then the hand moved in the
            direction of the targets and stopped after 1.52 s right after the middle of
            the screen. Movies of test trials lasted each 2.88 s. Presentation time of the
            whole stimuli material over all four blocks was 1 min and 33 s. Goal object,
            position of goal object, orientation of hand, and the order of presentation
            was again counterbalanced across the infants. The analysis remained the same
            as in the previous experiments. However, since the test trial is very short in
            this experiment, the criteria to treat gaze shifts after the standstill of the
            hand plus another 1000 ms as reactive is no longer applicable. Therefore, all
            gaze shifts were treated as anticipatory. Inclusion criteria were identical to
            the other three experiments, except that infants had to watch each movie at
            least for 100 ms from the start until the turn and again from the turn until
            the end of the movie. Also they had to look at the swap trial at least for 700
            ms.

            <hss>Anticipation rate</hss>

            The anticipation rate for the whole experiment was 0.74 (SD = 0.18) and 0.65
            (SD = 0.24) for all of the 12 familiarization trials. Again, the anticipation
            rate of the test trials was higher (M = 1.00, SD = 0.00) than in the last
            familiarization trials of all four blocks (M = 0.61, SD = 0.30), z = −4.32, p
            < .001, r = −.54.

            <hss>Familiarization phase</hss>

            Goal-related accuracy rate of the last familiarization trials (M = 0.49, SD =
            0.29) was significantly higher than the non-goal-related accuracy rate of the
            last familiarization trials (M = 0.12, SD = 0.19), z = −3.98, p < .001, r =
            −.50. Further the goal-related accuracy rate of the first familiarization
            trials (M = 0.47, SD = 0.37) was not significantly different from the goal-
            related accuracy rate of the last familiarization trials (M = 0.49, SD =
            0.29), z = −0.53, p = .60, r = −.07.

            <hss>Test phase</hss>

            Results revealed that the identity-related accuracy rate (M = 0.30, SD = 0.29)
            was significantly lower than the location-related accuracy rate (M = 0.70, SD
            = 0.29) in the test phase, z = −3.23, p = .001, r = −.40. There was also a
            significant difference between the goal-related accuracy rate in the last
            familiarization trials (M = 0.49, SD = 0.29) and the identity-related accuracy
            rate in the test phase (M = 0.30, SD = 0.29), z = −2.14, p = .03, r = −.27.
            Infants showed more anticipations towards the goal in the familiarization
            phase than in the test phase. Moreover, another Wilcoxon signed-rank test
            showed that the location-related accuracy rate in the test phase (M = 0.70, SD
            = 0.29) was significantly higher than the goal-related accuracy rate in the
            last familiarization trials (M = 0.49, SD = 0.29), z = −3.04, p = .002, r =
            −.38. Again, when only the number of anticipations was included, a Chi-Square
            test demonstrated that infants anticipated the action more in relation to the
            location (n = 83) than to the identity of the goal (n = 36), χ²(1) = 18.56, p
            < .001. The same pattern was observed in the additional analysis according to
            Cannon and Woodward (2012), in which infants demonstrated a preference for the
            previous location, with t(31) = −4.05, p < .001, Cohen’s d = 0.72, M = 0.29,
            SD = 0.29.

        <hss>Discussion</hss>

        In the fourth experiment we wanted to discover, whether the changes of the stimuli
        in comparison to Experiment 3 would now enable a replication of Cannon and
        Woodward’s results (2012). Findings indicate that 12-month-olds show more
        anticipations directed towards the location and not the goal object. Even after
        using stimuli that are highly similar to Cannon and Woodward (2012), we could not
        replicate their findings. However, our stimuli still contained subtle differences
        regarding the targets and construction of the stimuli, such as that a human hand
        was overlaid on the animated background with a blue screen method. Hence, we
        performed a last experiment that contains a replication as close as possible to
        the Cannon and Woodward (2012) study.

<hs>  Experiment 5</hs>
  ~~~~~~~~~~~~

To replicate the results of Cannon and Woodward (2012), the stimuli were newly filmed.
Direction, timing, and procedure of the action were as close as possible to the original
study. The two targets, now also a red ball and a green frog, were at the same position of
the screen and had the same size. There should be no to only few differences in the method
used between this experiment and Cannon and Woodward (2012).

            <hss>Participants</hss>

            Thirty-two healthy 12-month-olds were included for the final sample (16 girls,
            mean-age = 11 months; 27 days, 11;16-12;13). Additionally, 22 infants were
            tested but excluded due to inattentiveness and restlessness (n = 7), crying (n
            = 1) or not enough eye-gaze data (n = 14).

            <hss>Stimuli, procedure and analysis</hss>

            Stimuli were identical to Experiment 4 except that the goal objects were now a
            green frog (3.4° × 4.4°) and a red ball (4.3° × 4.1°; see Fig. 4). For the
            action, the human hand (4.9° × 9.4°) reached from the left to the right side
            of the screen. No animations were used anymore. Material was edited and cut
            with Final Cut Pro (Version 7.0.3). To ensure that the action was timed
            accurately, one movie of Cannon and Woodward (2012) was used as a basis for
            cutting the stimuli. As already Experiment 4 followed the timing of Cannon and
            Woodward (2012), there were no other changes made (see Experiment 4 for
            details). Goal-object, position of goal-object, hand orientation and order of
            hand orientation was counterbalanced throughout participants, leading to 16
            different combinations. Analysis of the data and inclusion criteria were
            carried out as in Experiment 4.

            <hss>Anticipation rate</hss>

            For the whole experiment, the anticipation rate amounts to 0.74 (SD = 0.14).
            For the familiarization trials the anticipation rate is 0.65 (SD = 0.18). A
            Wilcoxon signed-rank test revealed a significant difference between the
            anticipation rate of the test trials (M = 1.00, SD = 0.00) and the last
            familiarization trials (M = 0.56, SD = 0.31), with z = −4.40, p < .001, r =
            −.56.

            <hss>Familiarization phase</hss>

            Goal-related accuracy rate in the last familiarization trials (M = 0.39, SD =
            0.31) was significantly higher than the non-goal-related accuracy rate of the
            last familiarization trials (M = 0.18, SD = 0.27), z = −2.03, p = .04, r =
            −.25. There was no significant difference between the goal-related accuracy
            rate in the first familiarization trials (M = 0.50, SD = 0.30) and the goal-
            related accuracy rate in the last familiarization trials (M = 0.39, SD =
            0.31), z = −1.51, p = .13, r = −.19.

            <hss>Test phase</hss>

            A Wilcoxon signed-rank test demonstrated no significant difference between the
            identity-related (M = 0.40, SD = 0.35) and location-related (M = 0.60, SD =
            0.35) accuracy rate in the test phase, z = −1.53, p = .13, r = −.19. Also the
            goal-related accuracy rate in the last familiarization trials (M = 0.39, SD =
            0.31) did not differ from the identity-related accuracy rate in the test phase
            (M = 0.60, SD = 0.35), z = −2.62, p = .009, r = −.23. Nevertheless, the goal-
            related anticipation rate in the last familiarization trials (M = 0.39, SD =
            0.31) was significantly lower than the location-related accuracy rate in the
            test trials (M = 0.60, SD = 0.35), z = −2.62, p = .009, r = −.23. A Chi-Square
            test over the number of anticipations of the test trials showed a significant
            difference, χ²(1) = 4.40, p = 0.036. Infants anticipated more often to the
            location (n = 66) than to the identity of the goal (n = 44). The analysis
            according to Cannon and Woodward (2012) with the same measure and inclusion
            criteria demonstrated chance level of infants’ looking behavior, with t(30) =
            −0.92, p = .363, Cohen’s d = 0.17, M = 0.44, SD = 0.39.

        <hss>Discussion</hss>

        While the previous experiments 1–4 represent conceptual replications of the study
        by Cannon and Woodward (2012), Experiment 5 represents a direct replication.
        Because the original stimuli were not available, the stimuli were newly filmed for
        Experiment 5 and video edited to make them as similar to the original stimuli as
        possible. Nevertheless, the current findings show that 12-month-olds demonstrated
        more anticipations to the location than to the goal. The results of this direct
        replication are in line with the findings of Experiment 1–4 and of Daum et al.
        (2012). The differing findings between the two paradigms can neither be explained
        by the presence of an occluder nor by the type of agent. Detailed implications of
        these findings are discussed in the General Discussion.

<hs>  Discussion Study 1</hs>
  ~~~~~~~~~~~~~~~~~~

The aim of Study 1 was to examine which factors (type of agent, occlusion, order of
trials, timing and procedure of the action, movement direction) effect infants’ goal
encoding and caused the contradictory findings of two previous studies focusing on the
same research question (Cannon & Woodward, 2012; Daum et al., 2012). Based on previous
findings (Cannon & Woodward, 2012; Hespos et al., 2009; Kanakogi & Itakura, 2011), the
hypothesis of Study 1 was that the different results could primarily be attributed to two
factors, namely type of agent (human vs. non-human) and differences in the requirement of
cognitive resources caused by the use of an occlusion paradigm. For this purpose, these
differences were consecutively aligned in Study 1. In 5 experiments, an agent was
presented to 12-month-old infants who moved to one of two goals. Before the test phase,
positions of the target objects were swapped. Results over all 5 experiments showed that
12-month-olds learned the association of the agent and the target during familiarization
phase already after three trials, thus demonstrating fast learning within infants (Krogh-
Jespersen & Woodward, 2014). For test trials, infants showed in four of the five
experiments more location- than identity-related anticipations. In one experiment, infants
anticipated equally often towards the identity and the location of the target. Over all
five experiments, infants demonstrated 311 location-related and 189 identity-related
anticipations. The hypothesis that the different results of the two studies (Cannon &
Woodward, 2012; Daum et al., 2012) could be attributed to the type of agent and the
occluder was not confirmed. Further, our results are neither in line with the human first-
nor with the all agents-view, since we did not find goal anticipations in any of the
experiments. This finding is not in line with previous studies, which highlight the role
of experience (human first-view) for understanding an action as goal-directed in the first
year of life (Cannon & Woodward, 2012; Gredebäck & Melinder, 2010; Kanakogi & Itakura,
2011; Krogh-Jespersen & Woodward, 2018). They are in line with findings demonstrating that
infants anticipate others’ actions based on their previous path (Paulus et al., 2011).
However, results are not in line with looking time studies that demonstrated understanding
of goal-directed actions of non-human agents already within infants, as stated by the all
agents-view (e.g. Kamewari et al., 2005; Luo, 2011; Luo & Baillargeon, 2005; Schlottmann &
Ray, 2010). Nonetheless, it remains an open question, why infants expected the agent to
move to the familiarized location and not to the previous goal. The assumption, that the
occluder could have an influence on infants’ anticipations, was not confirmed either in
Study 1. Infants showed location-related anticipations, independent of the presence of an
occluder. On the one hand, studies have suggested that the use of an occluder requires
extra skills for infants (Hespos et al., 2009; Jonsson & von Hofsten, 2003). On the other
hand, previous findings showed that infants in their first year of life are able to
anticipate the reappearance of a temporarily occluded object (Gredebäck & von Hofsten,
2004; Gredebäck et al., 2002; Rosander & von Hofsten, 2004). Our results are in line with
the latter set of findings. In sum, the current findings suggest that at the age of 12
months, the ability to flexibly anticipate the actions of others based on goal identity
has not yet developed, irrespective of whether the agent was human or not, and therefore,
infants have also shown anticipations based on the location. In Study 2 this issue is
further addressed in another lab and with different stimuli. The inclusion of older age
groups (32-month-olds and adults) in Study 2 will also reveal how stable this effect is
over the course of development.

<h>STUDY 2</h>
-------

The second study analyzed whether children and adults show goal encoding for two different
paradigms, one using a human hand as an agent (e.g., Cannon & Woodward, 2012) and one a
non-human animated animal (e.g., Daum et al., 2012; Paulus et al., 2011). We intended to
find out whether infants use similar processing strategies for both paradigms. Thus, both
tasks were presented to 11-month-olds, 32-month-olds and adults in a within-subject
design. In both paradigms, the agent walked to one of two objects for several times. For
test trials the objects’ position was swapped and participants observed an uncompleted
action. The hand-paradigm is based on the study by Cannon and Woodward (2012), while the
stimuli differed in a few manners. Most notably, the number of trials and the presentation
order of learning and test trials were different. Further details are described below in
the method section. Moreover, to facilitate infants’ encoding of the scenario, we also
decided to familiarize participants with the actor and the targets. Goal-directed
anticipations from 11 months onward in the hand-paradigm would replicate the findings of
Cannon and Woodward (2012). In the path-paradigm, we expected 11-month-olds and 32-month-
olds to anticipate the old path, thus the novel goal, as the action is performed by a non-
human agent (Daum et al., 2012). We hypothesized to find anticipations towards the
familiarized goal within the adult sample in both paradigms (Daum et al., 2012; Pfundmair
et al., 2017). A correlational analysis of the anticipatory looking behavior between the
two paradigms should further clarify whether the different processing mechanisms assessed
by the two paradigms are related to each other. We expected to find at least in the adult
sample a positive correlation, because they showed goal anticipations for human and non-
human agents in previous studies (Daum et al., 2012; Pfundmair et al., 2017). In case we
would find a correlation between the two paradigms within children, as predicted by the
all agents-view, we wanted to make sure that this relation is not mediated by individual
factors of the child (Licata et al., 2014). Hence, we included a measure for temperament
(Infant Behavior Questionnaire revised very short form; Putnam, Helbig, Gartstein,
Rothbart, & Leerkes, 2014; Early Childhood Behavior Questionnaire very short form; Putnam
& Rothbart, 2006) as well as a cognitive measure for pattern recognition. Therefore, items
were adapted from the Bayley-Scales (Bayley, 2006; German version by Reuner & Rosenkranz,
2014; see supplemental material) for the 32-month-olds. As there are, to our knowledge, no
comparable items for 11-month-olds, a task for working memory (Pelphrey et al., 2004;
Reznick, Morrow, Goldman, & Snyder, 2004) was used as an indicator for pattern
recognition. In this task infants had to remember in several trials at which of two
windows the experimenter appeared beforehand.

        <hss>Participants</hss>

        The final sample included 34 11-month-olds (mean age = 11.44 months; SE = 0.15; 15
        girls), 35 32-month-olds (mean age = 32.11 months; SE = 0.09; 23 girls) and 35
        adults (mean age = 23.03 years; SE = 1.04; 30 women). Additionally, 8 children
        were tested but excluded, as they did not want to watch the second movie (n = 4),
        were inattentive (n = 2), or because of measurement failure (n = 2). Three
        additional adults had to be excluded due to technical problems. Participants came
        from a larger city in Germany. The infant population was recruited from local
        birth records and adult participants were recruited from a student population.
        Participants or their caregivers gave informed written consent. The study was
        approved by the local ethics board.

        <hss>Stimuli and procedure</hss>

        Participants were presented with two different paradigms. Both paradigms were
        shown on a 23-inch monitor, which was attached to a Tobii TX300 corneal reflection
        eye tracker with a sampling rate of 120 Hz (Tobii Technology, Sweden). Children
        were either seated on their parent’s lap or in a car-safety seat (Chicco) about 60
        cm away from the screen. For 11- and 32-month-olds, a 5-point calibration was
        performed. Adults were calibrated with a 9-point procedure. Data collection and
        analyzation was carried out with Tobii Studio (Tobii Technology, Sweden). All
        movies had the size of 1920 × 1080 pixels. In the subsequent section, the stimuli
        for the hand-paradigm are described first, the animated path-paradigm second.

            <hss>Hand-paradigm</hss>

            The procedure started with a movie, which introduced the agent. The female
            actor was sitting on a table and waving at the participant (6 s). To
            familiarize participants with the targets, two pictures were shown (each 2 s).
            Each showed one of the two targets, a green ball and a blue cube, accompanied
            by a sound. Next, the learning trials started. Similar to Cannon and Woodward
            (2012), the movies of the learning trials presented the two targets at the
            right side of the screen. The ball was situated in the upper position, the
            cube in the lower position (see Fig. 5). The table was light brown. After 0.10
            s, the hand reached into the picture (supplemented by a subtle, short sound)
            from the left side of the screen towards the targets, until just past midline
            (2.65 s). It then made a curvilinear path towards the ball and grasped it
            (after another 0.85 s) for 0.40 s combined with a squeak-sound. The whole
            learning trial lasted for circa 4 s, and was shown for 5 times in a row. Next,
            participants were presented with the swap trial, which consisted of a picture
            of the objects in swapped position accompanied by a rattle sound (4 s).
            Finally, in the test trials the hand reached in from the left (with the same
            sound as in the familiarization trials) and stopped just past midline (2.80
            s). A still-image of the hand in this position was presented for another 6.10
            s. A test trial lasted for 8.90 s and was presented for three times in a row.
            Between each test trial a black screen with an attention-getting sound was
            presented, to redirect infants’ attention to the screen.

            <hss>Path-paradigm</hss>

            First, participants were familiarized with the setup using an introductory
            movie. It showed a horizontal path that led from the right to the left side of
            the screen. A rabbit was sitting at the right side of the path and a
            transparent occluder was located in the middle of the path. After 0.2 s the
            rabbit started to jump up and down, supplemented by a sound. At the same time
            the occluder turned opaque and the rabbit started to move towards the end of
            the path through the occluder (6.88 s), turned around and went back towards
            the starting point. The whole movie lasted for 12.54 s. Afterwards five
            learning trials were presented. The learning trials contained a path that was
            leading to two different goals (similar to Paulus et al., 2017); a house that
            was situated on the upper path and a wood, situated on the lower path (see
            Fig. 5). The occluder was overlaid at the crossroad where the path divided
            into two options leading to the different goals. The agent was a pig that was
            located at the left side of the path. At the beginning of the movie the
            transparent occluder turned opaque (0.44 s). Afterwards the pig started to
            jump for two times (accompanied by a sound) and moved towards the occluder,
            until it disappeared for 2.37 s. The pig then reappeared on the upper path and
            moved towards the house. When it reached the house a bell sound was played.
            The whole movie took 10.52 s. Following the learning trials, a swap trial was
            shown (total duration 10.03 s). First a frame of the objects in the old
            position was presented; after 3 s both targets disappeared with a sound and
            reappeared in changed position after another 2 s with the same sound. Targets
            in changed position were presented for 5 more seconds. The pig was situated at
            the beginning of the path during the whole trial. The following test trials
            started completely identically to the learning trials, except that the targets
            were now in changed position and the pig did not reappear from the occluder
            for 6 s. The duration of one test trial was 11.52 s and test trials were
            presented three times in a row. Between the three test trials the same black
            screen with the attention-getting sound was inserted, as was done in the hand-
            paradigm. Both paradigms were shown to each participant. Order of paradigms
            was counterbalanced. Between the two eye-tracking movies 11-month-olds and
            32-month-olds did a task for a control measure on the table. A detailed
            description of control measures can be found in the files of the supplemental
            material.

        <hss>Measures</hss>

        The Tobii standard fixation filter with a velocity threshold of 35 pixels/window
        and a distance threshold of 35 pixels was used to define fixations. For the hand-
        paradigm three AOIs were defined: One AOI covered the area of the hand (“starting
        area”, 31.94%), the other two AOIs covered the targets (each 13.67%). Participants
        gaze behavior was measured for the whole test trial. AOIs for the path-paradigm
        were implemented as followed: The “start-AOI” covered the starting point of the
        action, namely the first part of the path, which led to the occluder (5.46%, see
        Fig. 5). The other two AOIs were situated on the area where the paths reappeared
        from the occluder (each 14.53%). The “start-AOI” was active for 1.79 s before the
        agent disappeared behind the occluder. Once the agent disappeared, fixations to
        the other AOIs were measured. For analysis of participant’s gaze behavior, three
        different measures were used for both paradigms, following previous research
        (Paulus et al., 2011; Schuwerk & Paulus, 2015). First we assessed whether
        participants generally anticipated to one of the two targets, irrespective to
        which one. The second measure assesses participants’ expectations based on their
        first fixations to either of the targets. The third measure assessed looking time
        durations to both targets. This measure was included to control for corrective eye
        movements.

            <hss>Frequency Score</hss>

            This score assesses whether all three age groups showed an equal amount of
            general anticipations (irrespective to which of the two targets they fixated)
            in all three test trials for each paradigm. In the hand-paradigm, a fixation
            was counted with 1, when participants first fixated the hand and fixated one
            of the targets after (no matter which of the targets). For the path-paradigm,
            a fixation was counted with 1, when participants first looked at the path
            leading to the occluder before the agent disappeared and fixated on one of the
            target-AOIs after the agent disappeared. A fixation somewhere else or no
            fixation was coded with 0 (Schuwerk, Sodian, & Paulus, 2016).

            <hss>First Fixation Score</hss>

            This score was calculated similar to the Frequency Score, with the only
            difference that now the type of first fixation, namely to which specific
            target was fixated, was considered. To be counted as a first fixation for the
            hand-paradigm, participants had to fixate the hand first and fixate on one of
            the targets after. In the path-paradigm, first fixations were only included
            when participants first looked at the path leading to the occluder before the
            agent disappeared and fixated on one of the other AOIs after the agent
            disappeared. A fixation from the beginning of the path to the correct path was
            coded with 1, a fixation to the incorrect, that is, the familiarized path, was
            coded with −1 and a fixation somewhere else on the screen or no fixation was
            coded with 0 (Schuwerk & Paulus, 2015). The score was averaged over the three
            test trials for analysis. If participants have two or more missing values for
            test trials in each paradigm they were excluded for that score. One 32-month-
            old in the hand-paradigm did not show gaze data for at least two test trials
            and one 11-month-old in the path-paradigm.

            <hss>Differential Looking Score (DLS)</hss>

            A score was calculated that represents the relative amount of time on one AOI
            in relation to the other. This score was additionally included to control for
            corrective eye-movements, as participants could fixate first on one AOI but
            direct most of the following fixations to the other AOI (Schuwerk & Paulus,
            2015; Senju, Southgate, White, & Frith, 2009). Therefore the total looking
            time to the incorrect goal-AOI was subtracted from the total looking time to
            the correct goal-AOI and divided by the sum of total looking time to both
            goal-AOIs in that time. This results in scores between −1 and 1; a value
            towards −1 would indicate a preference for the novel goal, a value towards 1 a
            preference for the old goal.

        <hss>Frequency of anticipations</hss>

        For the hand-paradigm, participants anticipated in 280 out of 312 trials (9.74%).
        For the path-paradigm, participants anticipated in 270 out of 312 trials (6.54%).
        A generalized estimating equations model (GEE; Zeger & Liang, 1986) was calculated
        for each paradigm separately (unstructured working correlation matrix, logit link
        function, binomial distribution) to see whether age group or test trial (first,
        second or third trial) or the interaction of age group and test trial had an
        effect on participants’ frequency of anticipatory first fixations. Results can be
        found in Tables 1 and 2. For both paradigms, neither of the predictors had a
        significant influence on the frequency of anticipations. This means that all age
        groups showed an equal amount of anticipations in all three test trials for both
        the hand- and path-paradigm.

        <hss>First Fixation Score</hss>

        A repeated measures ANOVA with the First Fixation Score was performed with the
        within-subject factor paradigm (hand- vs. path-paradigm) and the between-subject
        factor age group (11-months, 32-months, and adults). No main effect of paradigm
        was found, F(1, 99) = 0.64, p = .427; ηp2 = 0.01, but a significant main effect of
        age group, F(2, 99) = 6.55, p = .002, ηp2 = 0.12. The interaction of paradigm and
        age group was also significant, F(2, 99) = 9.65, p < .001, ηp2 = 0.16.
        Consequently, a one-way ANOVA with the between subject factor age group was
        performed for each paradigm separately. Analysis for the hand-paradigm did not
        reveal significant differences between the age groups, F(2, 100) = 1.93, p = .151,
        ηp2 = 0.04, whereas the ANOVA for the path-paradigm turned out significant, F(2,
        100) = 13.35 p < .001, ηp2 = 0.21. Bonferroni’ post-hoc tests showed a significant
        difference between 11-month-olds (M = −0.34, SE = 0.10) and adults (M = 0.24, SE =
        0.10) with p < .001, Cohen’s d = 0.95, and 32-month-olds (M = −0.45, SE = 0.10)
        and adults, p < .001, Cohen’s d = 1.15. The difference between the two infant
        groups was not significant, p = 1.00, Cohen’s d = 0.19.

        <hss>DLS</hss>

        Results for the DLS showed a similar pattern. The repeated measures ANOVA with the
        between subject factor age group and the within subject factor paradigm
        demonstrated no significant effect of paradigm, F(1, 100) = 0.16, p = .215, ηp2 =
        0.02, and age group, F(2, 100) = 1.30, p = .277, ηp2 = 0.18. The interaction
        effect of paradigm and age group turned out significant, with F(2, 100) = 10.61, p
        < .001, ηp2 = 0.18. One-way ANOVAs were performed for each paradigm separately.
        The ANOVA for the DLS for the hand-paradigm was significant, F(2, 100) = 3.35, p =
        .04, ηp2 = 0.06. Bonferroni’ post-hoc tests showed no significant difference
        between 11-month-olds (M = −0.05, SE = 0.07) and 32-month-olds (M = −0.23, SE =
        0.07), with p = .23, Cohen’s d = −0.44, and between adults (M = −0.30, SE = 0.07)
        and 32-month-olds, p = 1.00, Cohen’s d = −0.17. However, comparison between adults
        and 11-month-olds turned out significant, p = .04, Cohen’s d = −0.59. Similarly,
        analysis for the path-paradigm showed a significant effect with F(2, 101) = 6.60,
        p = .002, ηp2 = 0.12. Bonferroni’ post-hoc tests demonstrated a significant
        difference between 11-month-olds (M = −0.27, SE = 0.08) and adults (M = 0.12, SE =
        0.08), p = 0.003, Cohen’s d = 0.80, and between 32-month-olds (M = −0.20, SE =
        0.08) and adults, p = .020, Cohen’s d = 0.68. Again the difference between the
        11-month-olds and 32-month-olds was not significant, p = 1.0, Cohen’s d = 0.15.

        <hss>Comparisons across paradigms per age group</hss>

        Repeated measures ANOVAs were performed for each age group separately with the
        within-subject factor paradigm. Analysis of the First Fixation Score for the
        11-month-olds revealed no difference in performance for the two paradigms, F(1,
        32) = 3.41, p = .07, ηp2 = 0.10, just as for the 32-month-olds, F(1, 33) = 0.45, p
        = .51, ηp2 = 0.01. In contrast, adults performed in both paradigms differently,
        with F(1, 34) = 16.64, p < .001, ηp2 = 0.33 (see also Fig. 6 for descriptives).
        Adults showed a looking bias towards the novel object in the old location in the
        hand-paradigm, but a looking bias towards the goal in the path-paradigm. The same
        pattern was demonstrated for the DLS: No difference was found for the 11-month-
        olds, F(1, 33) = 3.37, p = .08, ηp2 = 0.09, and 32-month-olds, F(1, 33) = 0.04, p
        = .84, ηp2 = 0.001. However adults showed a significant difference between the two
        paradigms, with F(1, 34) = 3.01, p < .001, ηp2 = 0.43, with the same pattern as
        for the First Fixation Score.

        <hss>Type of anticipated action</hss>

        Further to check whether participants showed a significantly different looking
        bias from chance towards one or the other AOI, one sample t-tests against chance
        level were calculated for each paradigm and each age group separately (indicated
        by the asterisks in Fig. 6). 11-month-olds showed chance performance in the hand-
        paradigm for the First Fixation Score, t(33) = −0.88, p = .39, Cohen’s d = −0.15,
        and the DLS, t(33) = −0.73, p = .47, Cohen’s d = −0.13. For the path-paradigm they
        showed a significant looking bias towards the previous path, for the First
        Fixation Score, t(32) = −3.36, p = .002, Cohen’s d = −0.58, and the DLS, t(33) =
        −3.30, p = .002, Cohen’s d = −0.57. 32-month-olds performed in every paradigm
        above chance. They anticipated that the hand would grasp the novel object in the
        old location, indicated by the First Fixation Score, t(33) = −4.46, p < .001,
        Cohen’s d = −0.77, and DLS, t(33) = −3.44, p = .002, Cohen’s d = −0.59; as well as
        that the agent would reappear on the old path aiming for the novel goal, for First
        Fixation Score, t(34) = −4.63, p < .001, Cohen’s d = 0.78, and DLS, t(34) = −2.59,
        p = .014, Cohen’s d = 0.44. Similarly adults anticipated significantly above
        chance that the hand would grasp the novel object in the old location, with t(34)
        = −2.57, p = .02, Cohen’s d = −0.44 for the First Fixation Score, and t(34) =
        −4.33, p < .001, Cohen’s d = −0.73 for the DLS. In contrast for the path-paradigm,
        adults anticipated the agent’s reappearance on the correct path, with t(34) =
        2.24, p = .032, Cohen’s d = 0.38 for the First Fixation Score. Results of the DLS
        turned out not significant, t(34) = 1.41, p = .167, Cohen’s d = 0.24. To be able
        to compare our results better with Cannon and Woodward (2012) we further analyzed
        only the first test trial of the hand-paradigm. As Cannon and Woodward (2012)
        presented infants four blocks in the design of three learning trials and one test
        trial per block, and given that we presented participants five learning- and three
        consecutive test trials, an analyzation of only the first test trial is closer to
        a replication of the original study (with the difference being that we have five
        instead of three learning trials). One-sample t-test revealed chance performance
        for the 11-month-olds for the DLS (M = 0.05, SE = 0.11), t(32) = 0.49, p = .63,
        Cohen’s d = 0.09, and a First Fixation Score of M = −0.12, SE = 0.17. The
        32-month-olds showed a significant looking bias towards the old location for the
        DLS (M = −0.26, SE = 0.08), t(33) = −3.18, p = .003, Cohen’s d = −0.55, with also
        a negative First Fixation Score (M = −0.53, SE = 0.15). Similarly the t-test was
        also significant for the adults with t(34) = −4.05, p < .001, Cohen’s d = −0.69,
        for the DLS (M = −0.36, SE = 0.09), and a First Fixation Score of M = −0.37, SE  =
        0.15, indicating a looking bias towards the location. In sum, even when we only
        analyzed the first test trial, we did not find goal directed anticipations over
        all age groups for the hand-paradigm.

        <hss>Correlation analysis</hss>

        For each age group the Spearmen’s Roh correlation between scores of the hand- and
        path-paradigm were calculated (see Table 3). All correlations of the control
        measures can be found in the supplemental material. Analysis of the 11-month-olds
        and 32-month-olds revealed no significant correlations between the two paradigms.
        Interestingly, for adults the First Fixation Score did not correlate with each
        other, whereas the DLS turned out significant.

        <hss>Additional analysis</hss>

        Also Study 2 was additionally analyzed as similar as possible to the study by
        Cannon and Woodward (2012). Details of analysis and results can be seen in the
        supplementary material. Results suggest that neither for the hand- nor for the
        path-paradigm, infants anticipated the action goal-directed. Even when looking at
        the three test trials separately for the hand-paradigm (see Fig. 7), participants’
        performance was never above chance level.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The second study investigated two questions: (1) Do children and adults anticipate an
action of a non-human agent and human agent based on the previously observed goal instead
of the previously observed movement path? (2) Do children and adults show similar
processing strategies regarding goal encoding for two different paradigms? To this end
11-month-olds, 32-month-olds and adults were presented with two different paradigms. One
presented a human hand reaching for one of two objects and the other presented an animated
animal walking to one of two goals. Both followed a similar paradigm as described in Study
1 with a previous familiarization phase and a subsequent test phase in which the position
of the goal objects were swapped. Results revealed that when the location of targets had
changed, 11-month-olds and 32-month-olds did not perform goal-directed anticipations for
both types of actions. This is surprising, since we expected goal anticipations for human
actions from early on (Cannon & Woodward, 2012; Meltzoff, 1995; Woodward, 2005). Instead
we observed for 11-month-olds chance performance when presenting the action performed by
the hand. Considering the path-paradigm with the animated agent, 11-month-olds looked
longer towards the familiarized path leading to the novel goal. Hence results are similar
to Study 1 and Daum et al. (2012). Together with the experiments of Study 1, our results
are not in line with those by Cannon and Woodward (2012) and do not support theoretical
claims (e.g., Woodward, 2009) that the ability to flexibly anticipate other’s action goals
emerges in infancy. Rather, they support approaches that assume that early action
understanding is a multi-faceted construct that involve different kinds of processes and
mechanisms (Uithol & Paulus, 2014). 32-month-olds showed a looking bias in both paradigms
towards the old path. On the one hand, this is noteworthy, as not even older children
visually anticipated the goal of a human action. Yet, even previous research reported a
mixed pattern of goal anticipations for human actions in toddlers (Krogh-Jespersen et al.,
2015, 2018). The performance in the path-paradigm is in accordance to previous findings
(Daum et al., 2012) and our hypothesis. Our results imply that 11-month-olds and 32-month-
olds are not able to anticipate goals of non-human actions. This does not support the
theoretical claim that infants understand goal-directed actions of non-human actions from
early on (Luo & Baillargeon, 2005). The correlational analysis confirmed that children do
not use the same processing strategies when observing a human or animated animal, as we
didn’t find any significant correlations between the paradigms. In sum, our results cannot
confirm the widely made assumption that children perceive human actions based on their
goals (Ambrosini et al., 2013; Cannon & Woodward, 2012; Falck-Ytter et al., 2006;
Woodward, 1998). Quite the contrary, the findings suggest that infants process actions
based on visuo-spatial information and represent actions as movement patterns. Thus, our
findings support low-level accounts of social understanding, indicating that infants make
use of simple information when they process actions, such as statistical regularities
(Daum, Wronski, Harms, & Gredebäck, 2016; Ruffman, 2014; Uithol & Paulus, 2014). Further
we did not find any correlations within children between the two paradigms, which speaks
against the claim that children process human und non-human actions similarly from early
on (Leslie, 1995; Luo & Baillargeon, 2005). Adults reacted according to our expectations
in the path-paradigm: They fixated the novel path leading to the familiarized goal first.
Surprisingly adults showed contradicting anticipations in the hand-paradigm; they expected
the hand to grasp the novel object. Thus, they encoded the movement trajectory instead of
the action goal. This is interesting, since the goal of the actor should be clear at least
for adults. However, so far there is only one study that tested the paradigm of Cannon and
Woodward (2012) in adults. Pfundmair et al. (2017) found that adults anticipated the goal
of a grasping hand as well as of a grasping claw, which is in contrast to our findings.
Given this contradiction and lack of prior studies within adults, further investigation is
needed. Maybe this paradigm is not equally suitable for adults as it might be for children
(i.e. measuring the same underlying ability). Interestingly, in our study we found a
positive correlation between adults’ looking times in the two paradigms, which indicates
that they demonstrated related processing strategies for the two types of stimuli. Ramsey
and de C. Hamilton (2010) showed in a fMRI-study that adults process goal-directed actions
of a triangle similar to goal-directed grasping actions of a human hand. They concluded
that the fronto-parietal network, which is often referred to as the human mirror neuron
system, actually encodes goals rather than biological motion (Ramsey & de C. Hamilton,
2010). Similar assumptions have been made by Schubotz and Von Cramon (2004), who found
activity in motor areas for abstract, non-human stimuli. One assumption would be that the
role of experience influences participants’ performance in the two tasks (Ruffman et al.,
2012). Adults probably gained more experience with animations and cartoons throughout
their life, whereas infants are still not well familiarized with them.

<h>META-ANALYSIS</h>
-------------

In the previously described studies, we conducted six similar experiments that measured
whether infants between 11- and 12-months of age anticipate the goal of an action instead
of the movement path. Infants performed in none of the six experiments visual
anticipations towards the goal, questioning the theoretical claim that infants selectively
encode and anticipate other’s action goals (Cannon & Woodward, 2012; Woodward, 1998).
Instead we observed the tendency of infants to anticipate the movement path. In order to
produce a more reliable estimate of the observed looking bias towards the location, a
meta-analysis was conducted. We wanted to find out whether this effect is significant over
all of our six experiments.

        <hss>Effect sizes</hss>

        Effect sizes for the meta-analysis were expressed as correlation coefficients, r.
        This metric was chosen, as correlation coefficients are easier to interpret and
        compared with other metrics (Field, 2001; Rosenthal, 1991). The experiments of
        Study 1 were treated as single studies for the meta-analysis. As we wanted to see
        whether the effect of infants making location- instead of goal-directed
        anticipations is significant over all experiments, we used for each experiment of
        Study 1 the effect size of the comparison between location and goal-directed
        anticipations in test trials. This resulted in five effect sizes for each
        experiment of Study 1 (see Table 2 for effect- and sample sizes). For Study 2 we
        used the mean effect size of both paradigms of the First Fixation Score, following
        Rosenthal’s (1991) suggestion for cases when there are more effect sizes within a
        study. As the effect sizes of Study 1 are based on infants’ first fixations, we
        did not include the Differential Looking Score of Study 2 in this analysis. In
        Study 2, the direction of infants’ looking bias was measured via one-sample
        t-tests, which is why we used the effect-sizes thereof (see Table 2).

        <hss>Method of meta-analysis</hss>

        We assume that our sample sizes come from the same population and expect our
        sample effect sizes to be homogenous, since all our experiments are similar and
        collected from similar populations. According to this we decided on a fixed-
        effects model instead of a random-effects model, as suggested for these
        circumstances by Field and Gillett (2010). For calculating the fixed-effects
        model, the approach by Hedges et al. (Hedges & Olkin, 1985; Hedges & Vevea, 1998)
        was used. The analysis was calculated via written syntax for SPSS (see Field &
        Gillett, 2010).

<hs>  Results</hs>
  ~~~~~~~

The mean effect size based on the model was −0.24 with a 95% confidence interval (CI95)
of’ −0.38 (lower) to −0.09 (upper) and a highly significant z score (z = 3.07, p = .002).
According to Cohen’s criterion (1988) this is a small to medium effect. A chi-square test
of homogeneity of effect sizes was not significant, χ²(5) = 1.51, p = .912. This supports
our previous assumption of a low between-study variance indicating that our participants
are sampled from the same population. To illustrate infants’ looking bias towards the
location instead of the goal over all experiments, the number of anticipations towards the
location versus the goal was summed up over all six experiments. From a total of 681
anticipations, infants directed 423 anticipations towards the location whereas 258
anticipations were performed towards the goal (Table 4).

<hs>  Discussion</hs>
  ~~~~~~~~~~

The meta-analysis aggregated data from 178 participants over all six experiments and
demonstrated that samples of 11- to 12-month old infants show anticipations directed
towards the path of an action and not to its goal, with a small to moderate magnitude.
This result underlines the previous findings of Study 1 and 2, and highlights the
conclusion of our findings: Through all our 6 experiments we were not able to find a goal-
directed looking bias within 11- to 12-month-olds. Rather, we observed anticipations of
infants towards the location indicating that infants encode the movement path instead of
the goal of an action. This is further discussed in the next section.

<h>GENERAL DISCUSSION</h>
------------------

The present work addresses the question of whether and under which circumstances children
and adults flexibly anticipate actions as goal-directed. It has been claimed that infants
show visual goal anticipations earlier for human than for non-human actions (Meltzoff,
1995; Paulus, 2012; Ruffman et al., 2012; Woodward, 2005), whereas others proposed that
infants are able to anticipate goals for non-humans equally well as for humans (Leslie,
1995; Luo & Baillargeon, 2005). Cannon and Woodward (2012) demonstrated that 11-month-old
infants are able to encode an action of a human hand, but not of a mechanical claw as
goal-directed. In contrast, Daum et al. (2012) could only find goal-directed anticipations
within children from 3 years of age and adults, when using an animated agent instead of a
human hand. With the current set of studies, we aimed to contribute to the current debate
on infants’ goal anticipations by exploring whether infants indeed anticipate actions
flexibly based on goals rather than based on movement paths and patterns. Two different
labs collaborated over the attempt to replicate both conceptually and directly the
findings reported by Cannon and Woodward (2012). We hypothesized that infants understand
human actions earlier than actions of a non-human animated agent. Therefore, we expected
to replicate the findings of Cannon and Woodward (2012) in our experiments that used a
human hand as agent but not necessarily in the experiments that used non-human animated
animals as agents. However, despite our systematic variation of any other factors that
could have had an influence on infants’ action perception (such as type of agent, presence
of an occluder or number of learning- and test trials), we failed to replicate the
findings of Cannon and Woodward (2012) across all our experiments and labs. Infants
between 11 and 12 months of age did not anticipate an action in relation to its goal, but
rather to its movement path. This was observed, irrespective of whether the agent was a
human or an animated animal. We even included an experiment that was as close as possible
based on the stimuli of Cannon and Woodward (2012) and were not able to replicate their
finding. A meta-analysis aggregated over all of our data emphasizes our result and
illustrates a consistent effect for a looking bias towards the location and not the goal
within 11- and 12-month-olds. The finding, that infants and young children base their
anticipations on the movement path relates to previous eye-tracking studies (e.g., Paulus
et al., 2011; Schuwerk & Paulus, 2015) and further stresses the role of frequency
information for infants’ action processing. Our results underlie the claim that already
infants are able to detect contingencies and regularities in their environment, as
supposed to be an important learning mechanism (Kirkham, Slemmer, & Johnson, 2002; Ruffman
et al., 2012; Smith & Yu, 2008). Does this mean that infants do never show flexible goal-
directed anticipations? It should be noted that the paradigm by Cannon and Woodward (2012)
presented participants with a scene of two objects placed on a white background and a hand
that appears from the left side to grasp one of them. This scene is filmed from a
birds’-eye view and does not include the whole situation, namely an agent sitting on a
table in front of two targets. Theoretically, it has been proposed by predictive coding
accounts that active perception is informed by environmental features (e.g., Clark, 2013).
Also studies with infants could demonstrate the informative influence of context
information on infants’ action anticipations (Fawcett & Gredebäck, 2015; Stapel, Hunnius,
& Bekkering, 2012). Usual situations in our environment provide us with lots of
information that is already there before an action takes place, and thus open room for
top-down influence before an action is performed (Clark, 2013). Thus, it is possible that
the situation in the Cannon and Woodward-paradigm (2012), as well as in our experiments,
might be too abstract and out of context. The fact that we also couldn’t find goal-
directed anticipations for adults adds additional concern towards this paradigm. However,
adding more ecological cues might help infants. Other studies reported goal anticipations
within infants when they were presented with a movie depicting the entire human agent
grasping for an object (Kim & Song, 2015; Krogh-Jespersen & Woodward, 2014, 2018; Krogh-
Jespersen et al., 2015). Furthermore, there are studies demonstrating goal anticipations
in infants and toddlers when they had the possibility to learn about the agent’s goal
(Paulus, 2011; Paulus et al., 2017). For example, in Paulus et al.’s study (2017),
children observed an agent walking to a goal for several times whereas the goal’s position
changed from time to time. This highlighted the goal object on the expense of the movement
path (see also Ganglmayer, Schuwerk, Sodian, & Paulus, 2019). In sum these findings
suggest that infants might need additional information in order to visually anticipate the
goal and not the movement path. Another possibility relates to cultural factors. While the
study of Daum et al. (2012) and the current studies were implemented in Europe, the study
of Cannon and Woodward (2012) was conducted in the U.S. A comparison of various studies on
children’s TV consumption suggests that infants watch more TV in the U.S. than in Europe
(Feierabend & Mohr, 2004; Zimmerman, Christakis, & Meltzoff, 2007). In an additional pilot
study, we asked 22 parents of 12-month-olds about the average time their infants watch TV.
Results showed that only 23% of the 12-month-olds watch TV and for an average time of 4
min. In comparison, Zimmerman et al. (2007) reported that infants in the US spend on
average an hour per day in front of a TV screen. Given the fact that prior experience with
technology and real objects increases learning through TV (Hauf, Aschersleben, & Prinz,
2007; Troseth, Saylor, & Archer, 2006), it is possible that different experiences with TV
and screens could be a reason for our diverging findings. Yet, on the other hand, since we
did not find goal-related anticipations in 32-month-olds or even adults (Study 2) who
arguably have ample experiences with TV, this factor is rather unlikely to be the central
cause underlying our non-replication. Our work highlights the importance for replication
studies in developmental psychology, as recently researchers warned of false positive
findings and publication biases. Recent attempts to replicate findings of implicit Theory
of Mind tasks turned out difficult as well (e.g., Burnside, Ruel, Azar, & Poulin-Dubois,
2018; Kammermeier & Paulus, 2018; Kulke, Reiß, Krist, & Rakoczy, 2017; Powell, Hobbs,
Bardis, Carey, & Saxe, 2017). Some specifically tried and failed to replicate an implicit
Theory of Mind task based on anticipatory looking measures, questioning the robustness of
these tasks (Kulke, von Duhn, Schneider, & Rakoczy, 2018; Schuwerk, Priewasser, Sodian, &
Perner, 2018). One strength of the present manuscript concerns the integration of work
conducted at two different labs. Such a collaborative effort is not only in line with
suggestions for future best practices (e.g., Frank et al., 2017), but also increases the
conclusiveness of our results. In sum, our findings over various types of stimuli and
across two labs suggest that infants around 11 and 12 months of age do not flexibly
anticipate an action based on its goal, but primarily use the information about the
movement path, when presented with two possible targets that change location for test
trials (following Cannon & Woodward, 2012). This indicates that infants base their
anticipations on frequency information (similar to Henrichs, Elsner, Elsner, Wilkinson, &
Gredebäck, 2014). When they observe an action performed in a certain way, they use this
information to predict that action in the future (Ruffman, 2014). However, infants in
their first years of life seem to process this information in relation to movement paths
(Paulus et al., 2011). Our findings also imply that we need to reflect on what we exactly
mean when we say that infants understand goals, as a goal, in its general meaning, refers
to a desire (Ruffman et al., 2012; Uithol & Paulus, 2014). In conclusion, according to our
six experiments, infants do not flexibly anticipate action goals around 12 months. Rather,
their anticipation of others’ actions might rely on more simple heuristics, such as
movement trajectories.

<h>FUNDING SOURCES</h>
---------------

This work was partly supported by the German Research Foundation (DFG, Nr. PA 2302/6-1).


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<ART>Intentionality and temporal binding: Do causality beliefs increase the perceived temporal attraction between events?
================================================================================

Authors: S. Antusch, H. Aarts, H. Marien, R. Custers
DOI: 10.1016/j.concog.2019.102835
Year: 2020
ASJC codes: 3204, 3205
Keywords: Intentional action, Perceived causality, Temporal binding, Temporal repulsion

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Intentional motor actions and their effects are bound together in temporal perception, resulting in the so-called intentional binding effect. In the current study, we address an alternative explanatory mechanism for the emergence of temporal binding by excluding the role of motor action. Employing a sensory-based Libet clock paradigm, we examined temporal perception of two different auditory stimuli, and tested the influence of beliefs about the causal relationship between the two auditory stimuli, thus simulating a crucial feature of intentional action. In two experiments, we found a robust temporal repulsion effect, indicating that instead of being attracted to each other, the auditory stimuli were shifted away from each other in temporal perception. Interestingly, repulsion was attenuated by causal beliefs, but this effect was fragile. Furthermore, temporal repulsion was unaffected by the intensity of prior learning. Findings are discussed in the context of intentional action awareness research and multisensory integration.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The ability to integrate sensory information into a coherent picture of the world is an
important human trait. It enables people to build a conscious representation of complex
visual scenes and auditory events that are otherwise disconnected in time or space
(Serences & Yantis, 2006; Shamma, Elhilali, & Micheyl, 2011). Apart from integrating
perceptual input, humans also form coherent representations of their own behavior (Aarts &
Custers, 2009; Vallacher & Wegner, 1987). Self-produced actions that predict and result in
sensory feedback, such as pressing keys that result in a sound or light, are perceived as
coherent events of meaningful behavior (e.g., playing a tone on the piano or illuminating
a room), even though action and effect are spatially and temporally separated and do not
form a single entity. This ability to construct a coherent conscious experience of one’s
own behavior has important implications for the understanding of the self and the sense of
agency, i.e. the feeling of causing one’s own action and effects in the external world.
Specifically, people perceive their intentional actions and resulting outcomes as if they
are temporally bound together in conscious awareness; a phenomenon that is referred to as
intentional binding (Haggard, Clark, & Kalogeras, 2002b). It is assumed that this temporal
binding effect is rooted in internal prediction processes resulting from intentionally
selected motor actions, causing the compression of the time interval between action and
effect and the formation of a coherent representation of the action-effect event (Frith,
Blakemore, & Wolpert, 2000). Recent research, however, suggests that this temporal binding
effect might not be the result of intentionality per se (e.g., Desantis, Hughes, & Waszak,
2012; Dogge, Schaap, Custers, Wegner, & Aarts, 2012; Hughes, Desantis, & Waszak, 2013),
but rather a product of other factors that are associated with intentional action. In the
present study, we examine this subject in more detail and raise the question whether the
temporal binding effect is similarly sensitive to events that do not require any form of
action. Building on the notion that intentional actions are associated with beliefs in
causality that might bias the perceptual relation between two events (Buehner & Humphreys,
2010; Desantis, Roussel, & Waszak, 2011; Eagleman & Holcombe, 2002), we tested whether
causality beliefs cause two successive auditory stimuli to be perceptually bound together
in the Libet clock paradigm. The emergence of such a binding effect as a function of
causality beliefs would undermine the validity of the temporal binding task as a read-out
of intentionality and a measure of sense of agency. One central argument that has been put
forward in favor of the central role of intentionality in action concerns the impact of
externally induced action on temporal binding. Some studies employed transcranial magnetic
stimulation (TMS) to induce an involuntary action followed by a tone (Haggard & Clark,
2003; Haggard et al., 2002b). Subjects judged the time of movement onset and tone onset by
using the Libet clock. The time judgments did not reveal a temporal binding effect but a
clear and strong repulsion effect instead, indicating that subjects perceived the motor
movement and subsequent tone as two separate events. While these TMS experiments suggest
that the temporal binding task can distinguish involuntary from voluntary action in
producing a coherent representation of one’s own action, it is important to note that the
magnetic stimulation of motor areas results in an abrupt, reflexive and oddly felt
movement of a limb (here a finger). Clearly, human agents have the capacity to evoke
actions by direct brain stimulation, but such action onset does not fit with everyday
externally induced motor movement where intentionality is ruled out, for example when
someone else pushes or pulls one’s hand into a specific direction. Building on this
notion, recent studies show that temporal binding might be reduced but does not vanish for
actions that are not self-chosen or driven by internal motivation (Antusch, Aarts, &
Custers, 2019; Caspar, Christensen, Cleeremans, & Haggard, 2016) or passively induced in
the agent by another experimenter or a mechanical lever press (Borhani, Beck, & Haggard,
2017; Dogge et al., 2012; Engbert & Wohlschläger, 2007; Moore, Wegner, & Haggard, 2009).
These findings suggest that it is not intentionality per se that drives the temporal
binding effect, as externally induced movement does not cancel out temporal binding in
settings that include clear causal relations between action and outcome. One explanation
for the observed binding between externally induced actions and a tone might be that
participants were able to predict the outcome and believed to have a causal role in
producing it. Causal beliefs impact cognitive processes at several stages, e.g., learning,
judgment and decision-making (Harris, Fiedler, Marien, & Custers, 2019; Lucas & Griffiths,
2010). Moreover, higher-order causal beliefs have been shown to affect low-level processes
of perception (Buehner & Humphreys, 2009, 2010; Cravo, Claessens, & Baldo, 2009). A study
by Buehner and Humphreys (2009), for example, suggests that mentally linking one’s key
press to a subsequent tone following a presumed causal association enhances the
anticipation of the tone. However, not only effects stemming from motor actions are
subject to temporal binding, also external (visual) events can be spatially bound together
when they share a common causal association (Buehner & Humphreys, 2010). Accordingly,
holding a higher-order belief about the causal relationship between two events increases
binding between them, even when action is not actively involved. In a further exploration
of the role of causality beliefs in temporal binding of involuntary movement and effect,
Dogge et al. (2012) subjected their participants to a temporal binding task with the Libet
clock. Participants either executed a voluntary key press or an involuntary key press that
was induced by a lever pulling down their index finger. In the involuntary conditions,
some participants were asked to consider themselves as the agent, construing the resulting
effect (tone) as being caused by their key press. The magnitude of the binding effect
increased between the simple involuntary and involuntary self-causation condition, with
mean judgment errors (indicating a stronger binding effect) being larger in the
involuntary self-causation condition (Dogge et al., 2012). Similarly, it has been shown
that explicit beliefs of being the causal agent resulted in stronger intentional binding
in participants in a joint action task (Desantis et al., 2011). Whereas informative, these
studies do not entirely rule out the role of motor prediction and intentionality in
temporal binding between action and effect. It is for example conceivable that
participants started up their motor system once they noticed a slight movement of the
mechanical lever, causing them to experience a motor prediction signal and/or
intentionality over the key press. Because of the tight link between perception and action
(e.g., Decety & Grèzes, 2006; James, 1890; Prinz, 1997), a similar reasoning might account
for findings that show binding effects as a result of observing others’ action (e.g.,
Desantis et al., 2012; Kirsch, Kunde, & Herbort, 2018). A more stringent test of the role
of causality beliefs in temporal binding is provided by sensory paradigms that do not
employ motor action. In one such study by Haggard and colleagues (2002a), participants
judged the temporal onset of two identical successive auditory stimuli that were separated
by a 250 ms time interval. Results revealed that especially the second stimulus was
temporally repulsed from the first stimulus (Haggard, Aschersleben, Gehrke, & Prinz,
2002a). Similar results were obtained by Desantis et al. (2012) who compared the temporal
perception of two non-motor stimuli separated by a 400 ms time interval against an operant
action condition in a Libet clock paradigm. The findings were such that both, congruent
and incongruent (with precedingly learned associations), tone pairs resulted in temporal
repulsion instead of temporal binding, suggesting that temporal contiguity and identity
prediction were not sufficient for binding to emerge (Desantis et al., 2012). The first
tone was perceived as occurring earlier than in actuality, and the second stimuli was
perceived as occurring later than in actuality, leading to a repulsion instead of a
binding effect. Thus, instead of integrating the two stimuli such as in intentional
binding, participants seemed to detach the two from each other by experiencing them as two
separate entities and shifting them away from each other in temporal perception. It is
important to note that these studies did not investigate the role of causal beliefs and
might have suffered from flaws that reduced the probability of observing a temporal
binding effect. For example, Haggard et al. (2002a) used successive tones of the same
frequency and length. Hence, there might have been little inclination for participants to
integrate the tones into a coherent event and to perceive them as causally related. Thus,
participants perceptually shifted the tones away from each other. Using tones of different
frequencies, Desantis et al. (2012) paired the tones in congruent and incongruent within-
subject blocks and employed an unconventional 400 ms time interval. Because the tones were
sometimes congruent and sometimes incongruent, a stable predictive link could not be
formed. Furthermore, it is unclear how the extended time interval affected the results.
Finally, while suggesting temporal repulsion, comparisons with the baseline tone condition
in the Haggard et al. (2002a) study only suggest temporal repulsion of the second tone,
while the first tone seems to even be bound to the subsequent tone. Desantis et al. (2012)
only tested the temporal perception of the second tone while a comparison baseline
condition was lacking completely. Hence, the interpretation of the findings as
demonstrating temporal repulsion was neither statistically tested nor can it be claimed in
the absence of a comparison baseline condition. Thus, it remains subject to empirical
scrutiny whether external stimuli in successive contexts are repulsed or bound to each
other in temporal perception. The present study therefore aimed to replicate the temporal
binding (repulsion) effect with two different auditory stimuli by employing a unimodal
sensory paradigm based on the Libet-clock. In our task, participants acquired the
associations between two auditory stimuli pairs, such that the first stimulus predicted
the onset of the second one. Each pair consisted of a noise sound (such as a scratch
sound) followed by a sinusoidal tone 250 ms later. The pairings remained constant for each
participant, allowing for participants to perceive the stimuli as being linked and
represented as one event. Furthermore, as an important addition to earlier work, we
examined the role of causality belief in the perceived temporal attraction between the two
auditory stimuli. To that end, we manipulated explicit beliefs about the causal
relationship between the two successively presented auditory stimuli to more stringently
test their influence on temporal binding of the stimuli. The first experiment addresses
the basic role of perceived causality in modulating the temporal binding between two
different auditory stimuli. Experiment 2 was designed to further explore the role of
perceived causality in a context where the association between the first and second
auditory stimulus was strengthened by practice.

<hs>  Participants and design</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

In total, 641 individuals (49 females), with a mean age of 23 years (M = 23.02, SD = 6.15)
participated in the experiment in exchange for course credit or monetary reimbursement.
Participants were randomly assigned to one of two between-subject conditions, resulting in
33 participants in the control condition and 31 participants in the causal belief
condition. The study was carried out in line with the guidelines of the Declaration of
Helsinki and was approved by the Ethics committee of the Faculty of Social and Behavioral
Sciences at Utrecht University as part of a project line (ethics approval code:
FETC17-124). All participants gave written informed consent. A 2 (target: noise vs. tone)
× 2 (type of trial: baseline vs. succession trials) × 2 (condition, between: control vs.
causal belief) mixed design was employed.

<hs>  Procedure</hs>
  ~~~~~~~~~

The experiment consisted of an altered Libet clock paradigm as used by Haggard et al.
(2002) and was programmed using Eprime Software version 2.0. Four different auditory
stimuli of 100 ms length were used: two noise sounds and two sinusoidal tones. The noise
sounds resembled scratch sounds while the sinusoidal tones were of either 300 Hz or 1000
Hz frequency.2 All stimuli were played via a Sennheiser headphone.

        <hss>Acquisition phase</hss>

        The experiment began with an acquisition phase in which participants were
        familiarized with the auditory stimuli and their combinations. At the start,
        participants were told that four different auditory stimuli would be used in the
        experiment and that they would begin with experiencing each stimulus once. While
        participants experienced a stimulus, an on-screen message stated which stimulus
        they were experiencing. By pressing F1, they could advance to hearing the next
        stimulus. Subsequently, to facilitate the distinguishability of the stimuli,
        participants experienced each stimulus four additional times. These trials
        advanced automatically and like in the preceding trials, it was stated on screen
        which stimulus participants were experiencing. After participants were
        familiarized with the different auditory stimuli, they learned that each noise
        sound would be paired with one of the sinusoidal tones during the experiment. In
        the control condition, participants were told that the computer would determine
        the combinations of the noise and tone, and that they would therefore be
        independent of each other. Put differently, the pairs of auditory stimuli would
        not be causally related. They then heard the independent noise – tone
        combinations. In the causal belief condition, participants learned that the
        computer would choose the noise that would cause the second tone to occur. The
        second tone would thus be dependent on the selection of the noise. Put
        differently, the pairs of auditory stimuli would be causally related. They then
        heard the dependent noise – tone combinations. The noise – tone combinations were
        counterbalanced across participants but remained constant for a given participant.
        In both conditions, the noise – tone combinations were presented five times each
        (i.e., ten trials in total). Participants were asked to pay close attention. They
        then completed eight trials in which they heard noise – tone combinations that
        were either congruent or incongruent with the previously learned pairs. In the
        control condition, they were asked to indicate which combinations of tones were
        presented before, whereas in the causal belief condition, they were asked to
        indicate which combinations of tones were causally related. This was done to
        further emphasize and boost the independent (control condition) and the dependent
        nature (causal belief condition) of the stimuli pairs in the respective conditions
        before the start of the actual experiment.

        <hss>Experimental trials (altered Libet clock task)</hss>

        Next, participants commenced with the experimental trials. In both conditions,
        participants completed four blocks in randomized order. The blocks consisted of
        two baseline blocks (baseline noise, baseline tone) and two succession blocks
        (succession noise, succession tone). Each block comprised 24 trials, including
        four practice trials and 20 experimental trials. The practice trials preceding the
        experimental trials of each block were identical to and indistinguishable from the
        experimental trials but were not analyzed. Each trial began with the presentation
        of a dotted clock face consisting of forty grey dots arranged in a circle around
        the center of the screen, with a diameter of six centimeters. A black dot served
        as a clock hand and was moving alongside the grey dots with a speed of 2560 ms per
        rotation. The starting position of the clock hand varied between trials and was
        random. Participants were asked to attend to the clock face and the rotating clock
        hand. Depending on the trial, they then either perceived a single auditory
        stimulus or a stimuli pair in succession. The onset of the stimuli was programmed
        to always occur during the second rotation of the clock hand. In baseline blocks,
        participants either perceived one of the two noise sounds (baseline noise) or
        either of the two sinusoidal tones (baseline tone). In the succession blocks,
        participants always perceived an initial noise sound followed by the paired
        sinusoidal tone at 250 ms. After the presentation of the last stimulus, the clock
        hand continued moving for a duration of 1000 ms before it disappeared.
        Subsequently, the mouse cursor as well as a prompt to make a time judgment
        appeared in the center of the clock face. Participants were required to judge
        either the temporal onset of the noise sound (succession noise trials) or the
        temporal onset of the sinusoidal tone (succession tone trials) by clicking on one
        of the dots to indicate the position of the clock hand at the time of the event.
        In baseline trials, participants always judged the onset of the single presented
        stimulus (noise in baseline noise and sinusoidal tone in baseline tone trials).
        While blocks and trials were identical in both between-subject conditions,
        instructions differed. In the causal belief condition, instructions for the
        individual blocks emphasized the causal and dependent relationship of the two
        stimuli on each other. For example, participants in the causal belief condition
        read that they would hear two stimuli in succession, meaning that the tones were
        dependent on each other and that the first noise would cause the following
        sinusoidal tone. In the control condition, in contrast, the independence of the
        stimuli was emphasized. At the end of the experimental trials, participants filled
        in their age and gender. Moreover, participants also answered a question
        concerning their belief in the causal dependence of the second stimulus on the
        first stimulus (as indicated on a 9-point Likert scale ranging from 1 - absolutely
        not to 9 - very much). This question served as a manipulation check. Finally,
        participants were debriefed and thanked for their participation as well as
        reimbursed.

<h>DATA ANALYSIS PLAN</h>
------------------

Prior to the main statistical analyses, extreme temporal judgments were excluded on a
trial basis. Following Aarts et al. (2012), temporal judgments, which were more than ±640
ms away from the actual temporal onset, were excluded as it can be assumed that
participants either rated the onset of the wrong stimulus or were inattentive in general
on those trials. Overall, the number of judgments excluded based on this criterion was
very small (0.14% of all judgments). Based on earlier research suggesting a temporal
repulsion effect between auditory stimuli (Desantis et al., 2012; Haggard et al., 2002a),
we first aimed to test whether there was a significant overall temporal repulsion effect
independent of condition. First, for each trial a judgment error (in milliseconds) was
calculated as the difference between the judged time of an event and its actual time of
occurrence. A positive judgment error corresponds to delayed awareness of the event, and a
negative judgment error corresponds to anticipatory awareness. Next, for each participant
separate shifts for the first (noise) and second (sinusoidal tone) stimulus were computed
by subtracting the mean baseline judgment errors from the mean judgment errors in
succession trials (noise shift = mean judgment error in succession noise trials – mean
judgment error in baseline noise trials; tone shift = mean judgment error in succession
tone trials – mean judgment error in baseline tone trials). Finally, overall binding
scores were computed by subtracting the shift of the second stimulus from the shift of the
first stimulus (i.e., overall score = noise shift – tone shift). Positive overall binding
scores thus indicated temporal compression of the interval between the stimuli (temporal
binding) while negative scores were indicative of temporal repulsion. See Fig. 1 for the
distribution of the raw data in the full sample. First, we examined the direction of the
overall temporal shift. To that end, we conducted a one-sample t-test of the overall
binding score against zero. As we had no hypothesis pertaining to either a temporal
binding or a temporal repulsion effect, we conducted a two-tailed test. Next, we aimed to
test whether temporal perception of the stimuli in the two conditions was statistically
different. Specifically, we assumed that stimuli in the causal belief condition would be
bound more strongly than in the control condition. In line with that, we conducted a one-
tailed independent samples t-test on the overall binding scores in both conditions.
Finally, we tested the direction and significance of the temporal shift in the two
conditions. That is, we tested whether the perceptual shift was equally present in both
conditions. For that purpose, two one-tailed one-sample t-tests of the overall binding
scores in each condition against zero were conducted. Additionally, to illustrate the
strength of the evidence and confirm the Frequentist analyses, equivalent Bayesian
analyses were performed. For the convenience of the reader, complete Bayesian analyses are
reported.

<hs>  Manipulation check</hs>
  ~~~~~~~~~~~~~~~~~~

Prior to the main analysis, we conducted an independent samples t-test, testing the belief
in causality rating between control and causal belief condition. Confirming our
manipulations, the results revealed that participants in the causal belief condition (M =
6.68, SD = 2.15) believed more strongly in the causal dependency of the second stimulus on
the first stimulus than participants in the control belief condition (M = 5.24, SD =
2.48), t(62) = −2.4688, p = .016, two-tailed, d = 0.61, 95% CI [−1.12, −0.11].

<hs>  Main analyses</hs>
  ~~~~~~~~~~~~~

Next, we proceeded with the main analysis as outlined in the data analysis plan.

        <hss>Overall temporal repulsion</hss>

        To examine the direction of the perceptual shift and its statistical significance,
        a one-sample t-test of the overall binding scores against zero was conducted.
        Results revealed a highly significant repulsion effect equaling 77 ms (M = −77.20,
        SD = 65.94), t(63) = −9.366, p < .001, two-tailed, d = −1.17, 95% CI [−1.49,
        −0.85]. This temporal repulsion effect occurred bi-directionally. That is, noises
        were significantly more anticipated on succession trials (M = 13.12, SD = 46.97)
        as compared to baseline trials (M = 50.97, SD = 47.94), t(63) = 5.949, p < 001,
        two-tailed, dz = 0.74, 95% CI [0.36, 0.80]. Similarly, tones were perceived
        significantly later on succession trials (M = 90.17, SD = 49.34) than on baseline
        trials (M = 40.83, SD = 50.82), t(63) = −6.932, p < .001, two-tailed, dz = −0.87,
        95% CI [−1.31, −0.66].

        <hss>Difference in temporal repulsion between conditions</hss>

        In addition, to test whether temporal perception differed for participants in the
        control and the causal belief condition, overall binding scores were subjected to
        an independent samples t-test based on condition. The results revealed that
        participants in the causal belief condition (M = -52.50, SD = 67.24, N = 31)
        perceived the stimuli as significantly closer to each other in time than
        participants in the non-causal control condition (M = −100.40, SD = 56.35, N =
        33), t(62) = −3.096, p = .0015, one-tailed. The difference of −47.9 ms was of
        moderate effect size, d = −0.77, 95% CI [−1.28, −0.26].3 See Fig. 2 for a
        visualization of the overall shifts for the separate between-subject conditions.

        <hss>Temporal repulsion per condition</hss>

        Following, two one-sample t-tests were conducted to test whether the judgments
        were significantly different from zero. In the control condition (M = −100.40, SD
        = 56.35), judgments showed a statistically significant temporal repulsion effect,
        t(32) = −10.24, p < .001, one-tailed, d = −1.78, 95% CI [−2.33, −1.22]. Similarly,
        also in the causal belief condition (M = −52.50, SD = 67.24), individuals showed a
        significant temporal repulsion effect, t(30) = −4.35, p < .001, one-tailed, d =
        −0.78, 95% CI [−1.18, −0.37]. The separate shifts for the noise and the tone in
        the between-subject conditions are visualized in Fig. 3.

<hs>  Bayesian analyses</hs>
  ~~~~~~~~~~~~~~~~~

To assess the strength of the evidence, we performed Bayesian analyses in JASP (JASP Team,
2018, Version 0.9). In the absence of sufficient information regarding a reasonable effect
size and given the novelty of the paradigm, the default Cauchy prior of 0.707 instead of
an informed prior was used for the Bayesian t-tests (Bartlett, 2018; Quintana & Williams,
2018). To assure the robustness of Bayes Factors, robustness checks were conducted. The
results indicated that the chosen prior did not inflate the Bayes Factors. Hence, the
results of all tests can be assumed to be robust. The results of all robustness checks are
reported in the Supplementary Materials.

        <hss>Bayesian t-test on overall repulsion</hss>

        To test the strength of the temporal repulsion effect, we conducted a Bayesian
        two-tailed one-sample t-test on the overall temporal repulsion score. The
        alternative hypothesis stated that the temporal repulsion effect differed from
        zero (zero meaning no perceptual shift). The results revealed a BF10 = 5.199e + 10
        (=51,990,000,000), 95% CrI [−1.46, −0.84], indicating extreme evidence for the
        alternative hypothesis.

        <hss>Bayesian t-test on temporal repulsion between conditions</hss>

        Next, to test the strength of the difference between the two conditions, a one-
        tailed Bayesian independent-samples t-test was conducted. The alternative
        hypothesis assumed that the temporal judgments in the causal belief condition
        would be smaller than in the control condition, indicating less repulsion. The
        BF+0 was 25.01, 95% CrI [0.19, 1.19], suggesting that the data was 25 times more
        likely to occur under the alternative than under the null hypothesis. Thus, there
        was strong evidence for the idea that temporal repulsion was smaller in the causal
        belief condition than in the control condition.

        <hss>Bayesian t-tests on temporal repulsion in the separate conditions</hss>

        Consecutively, two Bayesian one-sample t-tests were conducted. Both overall
        binding scores were tested against a population mean of zero. For the causal
        belief condition, a BF10 = 183.4, 95% CrI [−1.13, −0.34], was found, indicating
        very strong evidence for the alternative hypothesis. For the control condition, a
        BF10 = 7.136e + 8 (=713,600,000), 95% CrI [−2.36, −1.13], was found, indicating
        even extreme evidence for the alternative hypothesis.

<h>DISCUSSION</h>
----------

In this first experiment, we aimed to replicate the temporal repulsion effect between two
auditory stimuli suggested by existing literature (Desantis et al., 2012; Haggard et al.,
2002a). Employing a sensory based Libet clock paradigm, strictly excluding the possibility
for motor action, for the first time, we empirically tested and statistically demonstrated
this temporal repulsion effect (i.e., corroborated by Frequentist and Bayesian analyses).
Additionally, we found that participants who held an explicit belief about the causal
dependency of the stimuli on each other, perceived the stimuli as being less strongly
repulsed than participants who did not hold such belief. This finding suggests an
increased perceived coherence between the stimuli in the causal belief condition. However,
temporal binding was still absent, indicating that the temporal integration of the two
auditory stimuli was weak and thus did not produce a full coherence experience.

<h>EXPERIMENT 2</h>
------------

To test the reliability of the temporal repulsion effect in the perception of successive
auditory stimuli and the attenuation thereof in the causal belief condition, a second
experiment was set up. It is conceivable that temporal repulsion persisted in the light of
causal belief because of the arbitrary nature of the stimuli and their associations. For
example, recent research using a different paradigm suggests that stimuli that have a
naturalistic link (such as the picture of a hand and a clapping sound) are more easily
bound in temporal perception (Thanopoulos, Psarou, & Vatakis, 2018). Research suggests
that these associative links between stimuli are acquired through learning and repeated
exposure (Turk-Browne, Scholl, & Chun, 2008). Especially in the absence of motor action
such learning might be pivotal for forming a stable predictive link. Hence, in an attempt
to strengthen these associations, we increased the amount of learning trials from ten to
sixty trials in the additional learning conditions.

        <hss>Participants and design</hss>

        The sample of the second experiment consisted of 1004 (66 females) volunteers with
        a mean age of 22 years (M = 22.22, SD = 2.03) who participated in the experiment
        in exchange for course credit or a monetary reimbursement. The study was carried
        out in line with the guidelines of the Declaration of Helsinki and was approved by
        the Ethics committee of the Faculty of Social and Behavioral Sciences at Utrecht
        University (ethics approval code: FETC17-124). All participants gave written
        informed consent. The design of the second experiment resembled the design of the
        first experiment with the addition of another between-subject factor. The complete
        design was a 2 (target: first vs. second tone) × 2 (type of trial: baseline vs.
        succession) × 2 (condition, between: control vs. causal belief) × 2 (additional
        learning, between: no vs. yes) mixed design. The addition of the learning factor
        resulted in two additional between-subject conditions. That is, participants could
        be randomly assigned to either one of the following conditions: control condition
        or causal belief condition (replication of the conditions of Experiment 1),
        control learning condition or causal belief learning condition (resulting from the
        addition of the learning factor to the design).

        <hss>Procedure</hss>

        The general procedure of the experiment resembled that of the first experiment.
        Also the stimuli used were identical to the stimuli in the first experiment. The
        experiment was programmed using Eprime 2.0. The procedural differences between the
        first and the second experiment are outlined below.

            <hss>Acquisition phase</hss>

            The experiment began with an acquisition phase. In the control and causal
            belief condition, the same acquisition phases as in the first experiment were
            employed (for details see Experiment 1). In the additional learning condition,
            after having acquired the stimuli, participants completed extensive learning
            phases of the stimuli pairs. In total, participants completed 60 learning
            trials (2 × 30 trials, separated by a 30 s break). The repeated exposure to
            the stimuli pairs thus would strengthen the association between the stimuli.
            Like in the first experiment, in the causal belief condition, the causal
            relationship between the two stimuli of a pair was emphasized whereas in the
            control condition their independence was emphasized.

            <hss>Experimental trials (altered Libet clock trials)</hss>

            The control and causal belief condition were identical to the first
            experiment. The instructions for experimental blocks in the learning
            conditions were borrowed from the respective control conditions.

                <hss>Data analysis plan</hss>

                As in Experiment 1, we excluded temporal judgments that were more than
                ±640 ms away from the actual temporal onset of the stimulus on a trial
                basis (Aarts et al., 2012). Overall, the amount of excluded trials was
                very small (0.15% of the total amount of judgments). Furthermore, we
                calculated separate shift scores as well as overall binding scores per
                participant using the same formula as in Experiment 1. Upon inspection of
                the overall binding scores, one participant seemed to be an extreme
                outlier with an average mean judgment score of −532.38 ms. As this score
                was more than six standard deviations away from the average overall
                binding score of the remaining participants (M = −67.28, SD = 74.34), we
                decided to remove this person from further analysis. A visualization of
                the raw data including the outlier is provided in Fig. 4. We proceeded
                with testing the significance of the overall temporal perceptual shift.
                Since we had no directional hypothesis regarding the perceptual shift in
                the overall sample (either temporal binding or temporal repulsion), we
                conducted a two-tailed one-sample t-test on the overall temporal binding
                scores. After establishing the significance of the temporal repulsion
                effect in the sample, we subjected the overall binding scores to an ANOVA
                with causal belief and learning as between-subject factors to assess their
                influence on temporal perception. Following, four separate one-tailed one-
                sample t-tests were conducted to test the significance of the temporal
                repulsion shift in the separate between-subject conditions. Finally,
                equivalent Bayesian analyses are reported to give an impression of the
                strength of the evidence.

<hs>  Manipulation check</hs>
  ~~~~~~~~~~~~~~~~~~

To check that the belief in the causal relationship between paired stimuli was indeed
stronger in the causal conditions than in the control conditions, we conducted an ANOVA
with causal belief condition and learning as between-subject factors on causal belief. The
results revealed that, on average, participants in the causal belief conditions (M = 5.6,
SD = 2.24 , assessed on a 9-point Likert scale) believed more strongly in the causal
dependency of the second stimulus on the first stimulus than participants in the control
belief conditions (M = 3.67, SD = 2.17), F(1, 95) = 19.615, p < .001, η2 = 0.17, 95% CI
[0.05, 0.30]. Learning was not found to have an influence on the causal dependency belief,
F(1, 95) = 0.101, p = .751, η2 = 0.00, 95% CI [0.00, 0.04]. Similarly, also the
interaction between the causal belief manipulation and learning was not significant,
F(1,95) = 1.631, p = .205, η2 = 0.01, 95% CI [0.00, 0.10].

        <hss>Overall temporal repulsion</hss>

        A one-sample t-test on the overall binding score across conditions was conducted
        to assess the direction of the perceptual shift and to test its statistical
        significance. The results revealed a significant repulsion effect of around 67 ms
        (M = −67.28, SD = 74.34), t(98) = −9.005, p < .001, two-tailed, d = −0.91, 95% CI
        [−1.14, −0.67]. Simple main effects confirmed that temporal repulsion occurred on
        both sides – the noise and the tone side, meaning that they were both perceptually
        repulsed from each other. While noises were perceived as occurring earlier on
        succession trials (M = 3.49, SD = 39.06) than on baseline trials (M = 35.44, SD =
        41.05), t(98) = 7.805, p < .001, two-tailed, dz = 0.78, 95% CI [0.31, 0.73], tones
        were perceived significantly later on succession trials (M = 64.58, SD = 60.34)
        than on baseline trials (M = 29.25, SD = 44.54), t(98) = −6.018, p < .001, two-
        tailed, dz = -0.60, 95% CI [-0.90, -0.43].

        <hss>Influence of causal belief and learning on temporal repulsion</hss>

        The overall binding scores were then subjected to an ANOVA with condition and
        learning as between-subject factors. Neither the main effect for condition, F(1,
        95) = 0.203, p = .653, η2 = 0.00, 95% CI [0.00, 0.05], nor the main effect for
        learning, F(1, 95) = .061 p = .806, η2 = 0.00, 95% CI [0.00, 0.03], was
        significant. Moreover, also the interaction between condition and learning was not
        significant, F(1, 95) = 0.117, p = .733, η2 = 0.00, 95% CI [0.00, 0.05]. Also the
        planned comparison between the control and the causal belief condition did not
        yield a significant effect, F(1, 95) = 0.331, p = .566, η2 = 0.00, 95% CI [0.00,
        0.06]. The causal belief effect that we found in the first experiment was thus not
        replicated. See Fig. 5 for a visualization of the overall binding scores in the
        four between-subject conditions.

        <hss>Temporal repulsion per condition</hss>

        The scores of all four between-subject conditions were negative, indicating
        temporal repulsion of the two stimuli from each other: control condition (M =
        −74.94, SD = 57.46, N = 27), causal condition (M = −62.90, SD = 68.02, N = 25),
        control learning condition (M = −66.01, SD = 98.73, N = 24) and causal learning
        condition (M = −64.37, SD = 73.30, N = 23). Separate one-sample t-tests were
        conducted to test if temporal repulsion in the conditions was significantly
        different from zero. The results were as follows: t(26) = −6.777, p < .001, one-
        tailed, d = −1.30, 95% CI [−1.81, −0.78] (control), t(24) = −4.624, p < .001, one-
        tailed, d = -0.92, 95% CI [−1.39, −0.45] (causal), t(23) = −3.275, p = .0015, one-
        tailed, d = −0.67, 95% CI [−1.11, −0.22] (control, learning), t(22) = −4.211, p <
        .001, one-tailed, d = −0.88, 95% CI [−1.35, −0.39] (causal, learning). Fig. 6
        provides an overview of the separate temporal shifts for the perception of the
        noise and the tone as compared to baseline.

<hs>  Bayesian analyses</hs>
  ~~~~~~~~~~~~~~~~~

Furthermore, Bayesian analyses were conducted using JASP software (JASP Team, 2018,
Version 0.9). Like in Experiment 1, the default Cauchy prior of 0.707 was used for the
Bayesian t-tests as a lack of existing information regarding a realistic effect size did
not allow for the determination of an informed prior (Bartlett, 2018; Quintana & Williams,
2018). To assure the robustness of the Bayes Factors, robustness checks were conducted.
The results indicated that the chosen prior did not inflate the Bayes Factors and that all
test can be assumed to be robust. The results of all robustness checks are reported in the
Supplementary Materials.

        <hss>Bayesian t-test on overall repulsion score</hss>

        Like in the first experiment, to test the strength of the temporal repulsion
        effect, we conducted a Bayesian two-tailed one-sample t-test on the overall
        temporal repulsion score. The alternative hypothesis stated that the temporal
        repulsion effect differed from a population mean equal to zero. The BF10 = 3.979e
        + 11(=397,900,000,000), 95% CrI [−1.46, −0.84] indicated extreme evidence for the
        alternative hypothesis.

        <hss>Bayesian ANOVA</hss>

        Subsequently, we conducted a Bayesian ANOVA on the overall binding scores with
        causal belief and learning as between-subject factors. The results showed that,
        given the data, there was no evidence that the separate effects of causal belief
        (BF10 = 0.234) and learning (BF10 = 0.219) were a good addition to the null model
        explaining the extent of temporal binding or repulsion. Similarly, neither a model
        including both factors (BF10 = 0.051) nor a model including both factors and the
        interaction term (BF10 = 0.015) was favorable given the data.

        Bayesian t-test on the difference between the control and causal belief condition

        Next, to test the likelihood of decreased temporal repulsion in the normal causal
        belief condition as compared to in the normal control condition (replication of
        Experiment 1) given the data, a one-tailed Bayesian independent-samples t-test was
        carried out. The null hypothesis that there was no difference between the two
        conditions was tested against the alternative hypothesis that the temporal
        repulsion in the causal condition was smaller than in the control condition. The
        BF+0 = 0.497, 95% CrI [0.01, 0.7], suggested no evidence for the alternative
        hypothesis.

        <hss>Bayesian t-tests on temporal repulsion per condition</hss>

        Finally, we conducted separate Bayesian one-sample t-tests to test each group
        judgment against zero. The results were as follows: control condition BF10 =
        47998.34, 95% CrI [−1.75, −0.75], causal condition BF10 = 250.6, 95% CrI [−1.34,
        −0.39], control learning condition BF10 = 12.36, 95% CrI [−1.05, −0.19], and
        causal learning condition BF10 = 87.08, 95% CrI [−1.23, −0.30]. That is, while
        there was extreme evidence in favor of the alternative hypothesis in the control
        and causal condition, the evidence for the alternative hypothesis was (very)
        strong in the two learning conditions. This suggests that the evidence for
        temporal repulsion was strong in all conditions but slightly less strong in the
        learning conditions. In short, we replicated the temporal repulsion effect of the
        first experiment, but we could not replicate the moderating influence of causal
        belief, even when participants received more extensive practice in causally
        linking the two auditory stimuli.

<h>GENERAL DISCUSSION</h>
------------------

Research on action awareness consistently finds voluntary actions and their effects to be
attracted to each other in temporal perception. This temporal binding effect is said to be
rooted in factors inherent to intentional action – hence the name, intentional binding.
Here we explored a potential confound of intentional action in producing temporal binding.
Specifically, we explored the role of beliefs of causality, and cancelled out any role of
action by examining temporal perception of auditory stimuli. Employing an adapted sensory-
based version of the Libet clock paradigm, in two experiments we found a temporal
repulsion effect for the perception of auditory stimuli in the absence of motor action.
This finding supports past research that observed a similar effect (Desantis et al., 2012;
Haggard et al., 2002a). However, we were able to statistically test it with a sufficiently
large sample, and unambiguously demonstrated the existence and robustness of such an
effect. That is, both - the noise and the sinusoidal tone - were significantly shifted
away in comparison to baseline. We also found evidence for a moderating effect of causal
belief on temporal binding of auditory stimuli. Specifically, in Experiment 1 we showed
that making participants believe that the first auditory stimulus is causally related to
the second auditory stimulus reduced the repulsion effect, suggesting an increased form of
temporal integration and perceived coherence. The repulsion effect was not fully reduced,
and we could not replicate the moderating influence of causal belief in a second
experiment, even though we exposed participants to more training in applying causal
beliefs to the auditory stimulus combinations. Hence, while we demonstrated a robust and
clear temporal repulsion effect for sensory stimuli in the absence of motor action, the
influence of higher order beliefs was less robust and not sufficient to cause actual
temporal binding, as would be the case in intentional action. One possible explanation for
the absence of a causal belief effect on temporal binding of auditory stimuli might lie in
the naturalistic character of the stimuli combinations. Recent research on voluntary
action, for example, suggests that naturalistic as compared to non-naturalistic links
between action-events carry an implicit (learned) causality experience which makes them
likely to bind to an effect (Dogge et al., 2012; Dogge, Hofman, Custers, & Aarts, 2019;
Thanopoulos et al., 2018). Following this line of reasoning, the absence of temporal
binding may be due to the lack of a natural association between the two auditory stimuli.
Although previous research showed that spatial binding of visual stimuli could emerge
rather rapidly (Buehner & Humphreys, 2010), auditory sequences might require practice for
temporal binding and perception of coherence to occur (Hsu, Le Bars, Hämäläinen, & Waszak,
2015; Lange, 2009; Turk-Browne et al., 2008). We found that the number of trials that we
used was not enough and that it is unclear how much prior experience is necessary to
induce temporal binding between non-naturalistic stimuli links. While there is research
suggesting that a few trials might suffice (Shimi & Logie, 2018), other research suggests
that more elaborate prior learning is necessary (Ernst, 2007). The failure to replicate
the causal belief effect on temporal binding thus indicates the fragility of building a
coherent representation of a non-naturalistic combination of sounds (Grotheer & Kovács,
2014; Jacobsen & Schröger, 2001), which seems less problematic for intentional action
where one produces sounds by key-presses that might be more naturalistic and more easily
to acquire. All in all, the present finding might give reason to assume that
intentionality has a special status in binding action and effect. As far as the evidence
in the current literature can tell, temporal binding mainly occurs when people perform,
observe and simulate actions (such as key-presses) to produce effects. Despite potential
flaws in experimental designs and testing (Hughes et al., 2013), these overall findings
strongly suggest that sensorimotor processes are vital to conscious experiences of action
coherence and agency. It is unclear, though, whether the predictions involved in this
sensorimotor mechanism stem from intentional action, actual body movement or action
simulation, or whether temporal binding arises from multisensory causal integration that
links physical sensations to predicted sensory effects (Ehrsson, Spence, & Passingham,
2004; Prikken et al., 2019). Future research might therefore design temporal binding
studies that more indirectly operate on the motor-sensory system, possibly ruling out
action simulation and using conditions that resemble sensory experiences (e.g., tactile
stimulation of the finger) that often accompany intentional motor action during
interaction with the world. Finally, the present experiments employed the Libet clock
paradigm to examine how two successive auditory stimuli are temporally bound together in
conscious awareness. A key feature of the Libet clock in a full temporal binding within-
subject design is that one can specifically examine whether repulsion (or attraction) is
caused by a shift away from the first stimulus or from the second stimuli, or both. Our
data suggest that the temporal repulsion effect occurred bi-directionally, such that
subjects perceived the first stimulus earlier and the second stimulus later in time than
actually was the case. Repulsion in the temporal binding task thus represents an instance
in which two successive stimuli are disconnected and separated in conscious experience. It
is important to note that recent research uses alternatives for the Libet clock, in
particular time interval estimations. Whereas these time estimations seem to yield
findings that correspond with a temporal binding effect, the measure does not offer a
clear inspection of the effect: time interval estimations are compared with the actual
time intervals, leading to under- or overestimations of time intervals. Notably, in some
studies underestimations are considered to represent temporal binding, whereas in other
studies overestimations are treated as temporal binding when comparing conditions that are
hypothesized to modulate binding effects (Damen, Van Baaren, Brass, Aarts, & Dijksterhuis,
2015; Kühn, Brass, & Haggard, 2013; Wen, Yamashita, & Asama, 2015). Thus, although the
time interval estimation measure is practical and easy to administer, it is ambiguous in
showing whether attraction or repulsion effects are at stake (for studies on time interval
estimations with respect to auditory and visual stimuli links, see e.g., Humphreys &
Buehner, 2009; Imaizumi & Tanno, 2019). Therefore, whereas the Libet clock paradigm has
downsides on its own (Pockett & Miller, 2007), it allows for reliable assessments of the
relative temporal shifts compared to baseline time perception, which may be preferred over
time interval estimation to examine whether, how and when a positive temporal binding
(attraction) binding or negative temporal binding (repulsion) effect will occur. To
conclude, the present research clearly shows that two auditory stimuli occurring in the
absence of motor actions are not subject to temporal binding but temporal repulsion, even
when people believe that the stimuli are causally related. Understanding the role of
causal beliefs in binding action and effect has received some attention lately, but most
studies still involve motor movement, and hence, it remains unclear whether and how
intentional action shapes coherent representations and a sense of agency of our own
behavior. We believe that ruling out any role of motor movement (albeit overtly or
covertly) might be crucial in examining alternative mechanisms for temporal binding
between action and effect, such as multisensory causal binding that integrates associated
information from different sensory modalities. The current research might serve as a first
step in this enterprise.

<h>AUTHOR CONTRIBUTIONS</h>
--------------------

S. A., R. C. and H. A. conceived the idea and planned the experiment. S. A. programmed the
experiment, supervised data collection and analyzed the data. S. A. and H. M. interpreted
the data. S. A., H. A. and R. C. wrote the manuscript. H. M. provided useful comments.


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<ART>Intentions, efficacy, and norms: The impact of different self-regulatory cues on reducing engine idling at long wait stops
================================================================================

Authors: Lynsey Mahmood, Dominic Abrams, Rose Meleady, Tim Hopthrow, Fanny Lalot, Hannah Swift, Julie Van de Vyver
DOI: 10.1016/j.jenvp.2019.101368
Year: 2019
ASJC codes: 3202, 3207

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Idling engines contribute significantly to air pollution and health problems. In a field study at a busy railway crossing we used the Theory of Planned Behavior to design persuasive messages to convince car drivers (N = 442) to turn off their engines during long wait stops. We compared the effects of three different messages (focusing on outcome efficacy, normative reputation, or reflection on one's intentions) against a baseline condition. With differing effectiveness, all three messages had a positive effect compared with the baseline. Drivers were most likely to turn off their engines when the message focused on outcome efficacy (49%) or reflection (43%), as compared to the baseline (29%). The increased compliance in the normative reputation condition (38%) was not significantly different from baseline. Thus, stimulating self-regulatory processes, particularly outcome efficacy, is demonstrated to have a positive effect on pro-environmental driving behavior. Theoretical and practical implications are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Individuals’ energy use greatly contributes to greenhouse gas emissions (e.g., Druckman &
Jackson, 2016). The behavior of drivers (e.g., engine idling) has been identified as an
important contributor to unnecessary emissions, and hence is a key target for intervention
(Dietz, Gardner, Gilligan, Stern, & Vandenbergh, 2009). These emissions also pose a health
threat. For example, in the Netherlands, car, bus, and bicycle passengers along high
intensity traffic routes were all exposed to significantly more particulate air pollution
than those on low intensity routes (Zuurbier et al., 2010). To address these environmental
and health hazards we developed a field study to test the effectiveness of messages
designed to persuade drivers to switch off their engines to reduce engine idling during
long waits at a railway level crossing.

<hs>  Using Theory of Planned Behavior to encourage pro-environmental behavior</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Theory of Planned Behavior (TPB) asserts that attitudes, norms, and perceived behavioral
control lead to intentions which proximally predict action (Ajzen, 1991, 2002). This TPB
framework is useful for developing interventions aimed at pro-environmental behavior
(PEB). Traffic-related behavior, despite being considered an important category of
research for TPB, is only rarely investigated (Steinmetz, Knappstein, Ajzen, Schmidt, &
Kabst, 2016). We focused here on norms, perceived behavioral control (via outcome
efficacy), and intentions as the basis for messages aimed at encouraging a pro-
environmental behavior (engine switch-off) at a long-wait stop. With respect to Abraham
and Michie's taxonomy (2008), our intervention falls in between a “persuasion” and a
“motivation” behavior change method, which were identified as quite effective methods when
paired with TPB framework (see Steinmetz et al., 2016).

        <hss>Norms and reputation</hss>

        To invoke norms, we designed a persuasive message appealing to social reputation
        (Emler, 1990). Indeed, norms are often invoked by signaling the reputational
        relevance of behavior (Abrams & Hogg, 1990), which plays a key role in determining
        whether the behavior will be adopted by the individual. It has been suggested that
        people are more willing to act in a prosocial (including pro-environmental) manner
        when they can acquire a reputation for doing so (Roberts, 2012). For example,
        participants invested greater sums in a climate protection program when their
        investment was made public, i.e. when they gained social reputation (Milinski,
        Semmann, Krambeck, & Marotzke, 2006). In a similar vein, university students
        reduced their energy consumption on campus when a delegate provided them with, and
        commented on, their consumption feedback, but not when the feedback was provided
        electronically and privately (Emeakaroha, Ang, Yan, & Hopthrow, 2014). Finally,
        avoidance of publicly deviating from ingroup PEB norms can also increase PEB
        (Player et al., 2018; see also; Goldstein, Cialdini, & Griskevicius, 2008). For
        the “normative reputation” condition, we therefore developed a sign that asked
        drivers: “When barriers are down, turn off your engine to show others you care”.
        This designed to subtly induce a reputational motivation (to be caring) to engage
        in PEB.

        <hss>Perceived control and outcome efficacy</hss>

        Our second persuasive message relied on the attitude component of TPB,
        specifically, evaluation of behavioral outcomes. Attitude toward the behavior is
        driven by beliefs about the consequences of performing the behavior, such as
        whether their behavior will have a positive outcome (Hausenblas, Carron, & Mack,
        1997; McEachan, Conner, Taylor, & Lawton, 2011). PEB can often be regarded as a
        ‘drop in the ocean’ (Kerr, 1996; Lorenzoni, Nicholson-Cole, & Whitmarsh, 2007),
        whereby an individual may feel that their single contribution will not have any
        impact, and therefore there is no point in acting. In contrast, outcome expectancy
        highlights the importance of an individual behavior in leading to a particular
        outcome (Doherty & Webler, 2016). Efficacy over the outcome can have direct,
        positive, and significant influences on public behavior about climate change
        (Doherty & Webler, 2016) and recycling behavior (Lindsay & Strathman, 1997).
        Assuming that all drivers are capable of turning off their engines, the relevant
        goal for perceived control is their belief that they can affect air quality (i.e.,
        outcome efficacy), rather than the lower level ability to turn off their engine.
        Using outcome efficacy as the foundation, we therefore developed a message that
        asked: “Please switch off your engine when barriers are down. You will improve air
        quality in this area” (hereinafter labelled ‘outcome efficacy’). This message
        aimed at showing the positive consequence of a simple action that was within the
        drivers' control.

        <hss>Intention to act and self-reflection</hss>

        The third persuasive message addressed intention to act. TPB asserts that
        intention is the closest predictor to behavior, with attitudes, norms, and
        perceived behavioral control as antecedents. However, an intention-behavior gap
        persists (see Sheeran & Webb, 2016), in part because people often forget to
        perform the behavior (Sheeran & Orbell, 1999). In cognitively demanding situations
        that involve multiple goals (such as driving), depleted cognitive resources can
        disrupt the link between an intention and its behavioral implementation, meaning
        that despite pro-environmental attitudes (and intention), the behavior is not
        actioned (Steg, Bolderdijk, Keizer, & Perlaviciute, 2014). Reminding people to
        consider their intentions could foster the enactment of consistent behavior.
        Indeed, studies found that simply questioning people about their behavioral
        intentions increased subsequent adoption of the behavior (mere measurement effect;
        see Godin et al., 2010; Todd & Mullan, 2011). Using a question to focus driver
        attention on their own behavioral intention about a salient action (switch off
        engine) should increase action. For this “reflection on intention” condition, the
        message therefore asked drivers: “When barriers are down do you intend to turn off
        your engine?”.

<h>METHOD</h>
------

The study complied with ethical standards of the British Psychological Society and
American Psychological Association, and was approved by the School of Psychology Ethical
Review Board (# 20122491). We collected data on engine switch-off rates at a busy long-
wait stop at the time of displaying one of three intervention signs (compared to
baseline). We hypothesized that all messages would improve behavior relative to baseline
and additionally explored differences in effectiveness between messages.

<hs>  Sample</hs>
  ~~~~~~

Data collection took place on 14 different days spread on a 6-month period (October 2012
to March 2013). Collection lasted for 1 h at the time, between 8am and 6pm, Mondays to
Saturdays. We randomly varied time of collection in order to reduce the chances that the
same driver would be sampled repeatedly (e.g., while commuting to work), and so that
intervention conditions would not be confounded with time of testing. Overall, 565
vehicles were sampled, a large majority of which were cars (n = 442).1

        <hss>Location and setting</hss>

        Engine idling was observed at a busy level crossing in a medium-size city in the
        UK. The local council had erected a permanent sign asking people to switch off
        their engines that was visible before, and throughout the duration of the study
        (see supplementary material). The intervention messages were printed on a placard
        (420 × 594 mm; font type = Franklin Gothic medium, font size = 100 pt), 2 m above
        ground level. To ensure that all vehicles would pass the sign on their approach to
        the level crossing, the placards, held by stationary research assistants on the
        sidewalk, were positioned facing traffic on each side of the crossing, 75 m before
        the barrier and approximately 5 m from the existing council signs (futher detail
        on the methodology can be found in supplementary materials). While the barrier was
        down and the vehicles were stationary, another research assistant walked along the
        sidewalk from the barrier toward the queuing traffic as far as the sign,
        discreetly recording whether each vehicle's engine was on (coded 0) or off (coded
        1). This was assessed by viewing exhaust activity and listening for engine noise
        emitted from each vehicle (see supplementary materials for interrater
        reliability).

        <hss>Intervention messages</hss>

        We used three intervention messages: Normative reputation, Outcome efficacy, and
        Reflection on intentions, which were compared to a Baseline condition where no
        message was present (see Table 1).

        <hss>Control variables</hss>

        It is possible that drivers' behavior is influenced by the weather (e.g., less
        likely to turn off the engine on a hot day where the car AC is on). To account for
        this, we coded for each observation period the weather (rainy = −1, sunny or
        cloudy but dry = 1) and the visibility (dark or foggy = −1, visible = 1). Since a
        person's behavior can be impacted by the presence of others, we additionally
        recorded the number of people in the vehicle (M = 1.55, SD = 0.76). Most drivers
        were alone (58%) or accompanied by one passenger (32%), and the remaining vehicles
        had three or more people aboard.

<h>RESULTS</h>
-------

We conducted a hierarchical logistic regression to analyse the impact of the intervention
messages on drivers’ idling behavior. In a first step we included only the type of
intervention as a predictor. To test more accurately the effect of the three interventions
against the baseline, we computed the following contrast (hereinafter C1): Baseline = −3,
Outcome efficacy = 1, Reflection = 1, Reputation = 1. We also entered the orthogonal
contrasts in order to better estimate residuals (C2: Baseline = 0, Outcome efficacy = −2,
Reflection = 1, Reputation = 1; C3 = Baseline = 0, Outcome efficacy = 0, Reflection = −1,
Reputation = 1). In a second step, we additionally entered the three covariates: weather,
visibility, and number of people in the car. The analyses revealed a significant effect of
the intervention messages. Relative to the baseline, drivers turned off their engine
significantly more after exposure to any of the three messages. This effect held in the
absence and presence of the covariates, which did not impact engine idling (see Table 2).
Percentages of drivers that turned off their engine per experimental condition are
illustrated in Fig. 1.2 To complement these results, we additionally tested the difference
between each message and the baseline condition. The difference was significant for both
Outcome efficacy, OR = 2.30, 95% CI [1.26, 4.18], Wald's χ2 = 7.42, p = .006, and
Reflection on intention, OR = 1.83, 95% CI [1.02, 3.30], Wald's χ2 = 4.04, p = .045. It
failed to reach significance for Normative reputation, OR = 1.49, 95% CI [0.81, 2.73],
Wald's χ2 = 1.62, p = .20.

<hs>  The present results</hs>
  ~~~~~~~~~~~~~~~~~~~

In this experiment we tested the effectiveness of interventions aimed at encouraging PEB
in a context where they are commonly rare. Drawing from TPB (see Steinmetz et al., 2016,
for a recent meta-analysis), we hence tested the effectiveness of three messages
(normative reputation: “… show others you care”; outcome efficacy: “… you will improve air
quality”; reflection on intention: “… do you intend to switch off? “) to encourage drivers
to turn off their engines at a long wait stop. Our aim was to test whether focusing on
different aspects of behavioral regulation could be effective in triggering more
environmentally positive behavior. Initial results showed that all messages led to higher
compliance (higher rates of engine switch-off) than the baseline. However, analyses also
revealed that not all messages had the same impact: despite descriptively increasing
compliance (by 8.8 points), the reputation message did not significantly differ from
baseline, whereas reflection and outcome efficacy did (by 13.8 and 19.4 points,
respectively). Hence, the study shows that the mere presence of a person carrying a
persuasive sign on the sidewalk is not enough to impact drivers’ behavior: the content of
the message is essential. The normative reputation message aimed to motivate drivers based
on opportunity to enhance their reputation by showing others they care (Steg et al.,
2014). However, our results suggest that this was not enough to elicit behavior change. It
is possible that drivers were not convinced that others would be able to detect their PEB,
and hence that there was in fact little reputational gain to be achieved. Moreover, the
message may have caused some dissonance for drivers with strong self-interest or hedonic
values, and thus reduced the likelihood of action since the messaging opposed their
existing belief system (Kollmus & Ageyman, 2002). This seems consistent with evidence that
PEB messages can be effective when they target self-interest motives (Van de Vyver et al.,
2018) or appeal to drivers with stronger hedonic or egoistic values (Steg et al., 2014).
The reflection on intention message aimed to target drivers with preexisting intentions to
behave pro-environmentally who might not do so in certain settings because they are
distracted or forget to enact their intentions. This message elicited significantly higher
behavioral compliance than baseline, which is consistent with the mere measurement effect
(Godin et al., 2010; Todd & Mullan, 2011). However, the nature of the message does
restrict its impact to receivers who already hold pro-environmental intentions. Drivers
who are relatively unconcerned about the environment would be less likely to harbor
intentions to turn their engines off, and therefore would not be influenced by the
message. This might be especially important in the particular context of this study, since
factors such as status and comfort have been found to influence behavioral choice
(Gatersleben, Steg, & Vlek, 2002), so switching off the engine and losing other functions
(such as heating/AC and radio) may outweigh the PEB. Finally, the outcome efficacy message
aimed to increase drivers' sense of efficacy and remove uncertainty regarding the
effectiveness of their (non-idling) behavior. This message elicited significantly higher
behavioral compliance than baseline and was, descriptively at least, the most effective
message, increasing compliance by 66%. This remarkable effectiveness could be explained by
the fact that the message went beyond the heightening of values and normative behavior by
delivering a specific and positive message that the driver's personal contribution would
make a difference to the environment (Doherty & Webler, 2016; Hine & Gifford, 1996;
Meyerowitz & Chaiken, 1987; Morton, Rabinovich, Marshall, & Bretschneider, 2011; Webb &
Eves, 2007).

<hs>  Limitations, future research and conclusions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This study has some limitations that must be acknowledged. First, observations were
limited to one location. Future studies will need to ensure that the results can be
replicated in different places. Moreover, the procedure relied on the presence of a
research assistant to hold the placard. Even if past studies have ensured that the mere
presence of a person on the sidewalk (holding a blank sign) did not significantly affect
the rated of engine idling (Meleady et al., 2017), it may have somewhat altered the
drivers’ usual behavior. Future studies should therefore investigate the effect of
messages attached to fixed poles. Finally, given the non-intrusive nature of the study, we
assessed behavior but could not measure its psychological antecedents. Hence, we cannot
know of sure whether the messages impacted the targeted cognitions and/or others. It will
be valuable to conduct additional experimental studies that test the impact of the
messages on the relevant cognitions – but this goes beyond the scope of the present field
study. In sum, this study makes a substantial contribution by showing that behavior change
towards PEB is sensitive to the way that persuasive messages tap into particular routes
for self-regulation. It also raises interesting questions for future research about how
different approaches might work in particular contexts and about how different aspects of
self-regulation might feed into one another. The most effective message, outcome efficacy,
led to a decrease of engine idling by 19.4% (corresponding to an increase in compliance by
66%). Relative to the usual traffic at the level crossing where the experiment took place,
this ismpact would prevent the emission of 3538 tons of CO2 per year.3 We believe that
this can still be increased and the message made even more effective, notably by giving
additional, specific details on the efficacy of the behavior (Steg & Vlek, 2009; Webb &
Eves, 2007). For example, adding a specific outcome (e.g. engine switch off would improve
air quality by X%) or by providing some sort of feedback to drivers (e.g. each car that
switches off reduces pollution by X amount) could boost the effectiveness of the efficacy
message still further.


<h>REFERENCES</h>
----------

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<ART>Intergenerational encounters on the metro: Young people's perspectives on social control in the media city
================================================================================

Authors: Päivi Honkatukia, Arseniy Svynarenko
DOI: 10.1016/j.emospa.2018.10.001
Year: 2019
ASJC codes: 3205, 3207

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The formation of urban social order has been studied since the classic accounts of the
modern city (e.g. Park, Simmel, Weber, Goffman; see also Ocejo and Tonnelat, 2014). In
studies inspired by the ‘mobility turn’ in sociology (Brighenti, 2012, 404), public
transportation has been analyzed as a space for conviviality as well as a symbolic
platform for struggles and protests over space and rights, particularly for racialized
minorities (Fleetwood, 2004, 36–37; Mitchell, 2003). This article studies public transport
from the perspective of 15- to 17-year-olds, who are often categorized as teenagers. Their
views have rarely been taken seriously when analyzing urban social order (Ocejo and
Tonnelat, 2014, 494; Tironi and Palacios, 2016), hence leaving us blind to young people's
everyday struggles with their entitlement to belong in the city (Maira and Soep, 2005).
With regard to young people's urban engagements, it is necessary to acknowledge the recent
development and accessibility of mobile technologies and the expansion of social media
platforms. Young people aged 15 to 17, the so-called Post-Millennials (also known as
Generation Z or iGen, who have come of age in the first two decades of this millennium),
are growing up amid ongoing, hectic change shaped by media and information technology
advances. Finland, which is in focus in this article, ranks second only to Japan in terms
of mobile broadband penetration (OSCE, 2017). More than 95 percent of Finns aged 16 to 24
own a smartphone (Statistics Finland, 2016a), and 92 percent of young people regularly use
smartphones to play games online, listen to music and watch videos, while 89 percent use
them to access social networks (compared to 9% of 65- to 74-year-olds; Statistics Finland,
2016b). Despite the widespread use of media technology, very few studies on new media have
focused on young people's media consumption in relation to their mundane engagements in
cities or other youth cultural contexts (Buckingham and Kehily, 2014, 10–11). In general,
the implications of mobile technologies for social interaction in public places have not
yet been thoroughly explored (e.g. Hampton et al., 2010). Considering the above, this
article examines the dynamics of social order in the contemporary digitalized ‘media city’
(Georgiou, 2013) from the perspective of young generations. Social order is formed
interactively in the everydayness of the city and through the processes of social control.
By social control, we refer to forms of social interaction through which norms regulating
human conduct are created, monitored and sanctioned. We conceptualize social control as
being inherently interwoven into young people's intra- and intergenerational relations,
having both formal and informal features (Honkatukia and Keskinen, 2018). In the media
city in particular, social order involves technological mediation and is constituted via
mundane encounters ‘with social diversity in a situation of spatio-temporal proximity’
(Brighenti, 2012, 46). Empirically, we have focused on the Helsinki metro and have
interviewed young people who use it daily. The metro represents for us a highly
technologically driven site where Internet, digital technology and mobile devices are
deeply embedded in the everyday life of the passengers (Hatuka and Toch, 2016). Moreover,
the metro is a site of both formal and informal surveillance and control (CCTV, gates,
security lighting; Gardner et al., 2017; Lianos, 2012). Even if formal surveillance has
been intensified recently in many cities due to the securitization and militarization of
social control (e.g. Hussain and Bagguley, 2012; Franko Aas, 2007, 63–65), the Helsinki
metro, perhaps due to its small size and its globally remote position, lacks many of the
features of formal control that characterize larger cities. In the Helsinki metro, there
are no gates with mechanical barriers as there are in most other metro systems, no
specially dedicated police department (unlike in Washington, D.C. or throughout the
Russian metro network) and no airport-style security with metal detectors and X-ray
scanners as in St. Petersburg or Moscow. In the technological and automated Helsinki metro
system, social control is often manifested through informal and non-verbalized means as
well as voluntary self-control of passengers, deriving either from their willingness to
conform, imitation, learned routines or contagiousness of habits. Some omnipresent
tensions concerning social control become visible in the Helsinki metro due to its
concentration of mechanical and digital technology in the closed spaces of stations and
metro carriages (also Lianos, 2012; Zaporozhets, 2014). A specific feature of this context
is that during transit, social control and norms are often negotiated in interactions with
unknown people situationally and often in short-term encounters. Moreover, in the closed
space of metro carriages moving through tunnels underground, human interaction with
various technological objects (travel card readers and mechanical doors) becomes an
important part of the metro experience (Lianos, 2012). Hence, metro carriages and stations
are anthropological spaces for complex emotional and sensory experiences, social
engagement and symbolic self-expression of which mechanical and digital devices are
essential parts (e.g. Hayward, 2004). We are interested in young people's experiences of
(mainly informal) social control in this technologized context. Our inquiry assumes that
young people's encounters with adults, including those encounters related to social
control, bear importance for creating a sense of belonging, citizenship and being
legitimate members of the city. The article will also shed light on the dynamics behind
earlier research findings from Finland claiming that public transport is seen as an
ambiguous space for young people. Young people's experiences of threatening situations on
public transport are rather common in larger cities (Kivivuori et al., 2014; Ojanen, 2018,
26–27), and it is also common to regard the metro as the least-safe option compared to
other forms of public transport in Helsinki (Tuominen et al., 2014, 36–38). In the
following section we will explore more closely the specificities of the metro as a
technologized form of public transport, and present the theoretical underpinnings of the
study. In the analysis of social order and control, we were inspired by Pierre Bourdieu's
(1977) idea of symbolic violence (as applied by e.g. Bourgois, 2001 and Listerborn, 2015),
as well as by conceptualizations of the digitalization of urban life (e.g. Hatuka and
Toch, 2016; Georgiou, 2013; Brighenti, 2012; Hampton et al., 2010). This framework enables
us to reflect on how everyday life experiences relate both to intergenerational power
structures and the digitalization of urban spaces, and how these two intertwine.
Thereafter, and based on thematic interviews conducted with a sample of young people aged
15 to 17, we will analyze their narration on encounters with adults on the metro,
especially those related to social control and processes of symbolic violence. In the
concluding section we reflect on the nature of the intergenerational social order in a
digitalized media city based on our empirical inquiry.

<h>THE TECHNOLOGICAL METRO SYSTEM AS A SITE OF INFORMAL SOCIAL CONTROL</h>
-------------------------------------------------------------------

On the metro, one is usually unable to choose one's company or the people one is
surrounded by. Events change rapidly, and interaction with others is usually brief.
Compared to trams and buses, a greater number of people share the same space on the metro,
multiplying the possibilities of coming across people with diverse backgrounds in a
physically restricted space and often crowded conditions (Ocejo and Tonnelot, 2014;
Gardner et al., 2017). With larger numbers of passengers on the metro, one is less likely
to meet the same people on the same routes at the same times or to be acquainted with
their habits beforehand. Due to the high level of automation and digitalization,
passengers rarely encounter metro personnel or guards in Helsinki. On buses and trams, by
contrast, contact between passengers and drivers is almost unavoidable. On most buses, for
instance, the drivers check that every passenger who boards has paid the fare, and they
can directly intervene in any situations that may occur. On the metro, formal control is
mediated by technical means such as video surveillance, and there are only random checks
by security workers and ticket inspectors. This setting distinguishes the metro from other
forms of public transport and determines the significance of informal control, which
largely rests on conventions, shared norms, expectations and negotiation. Age, gender and
cultural background exert significant impacts on social order. Accordingly, we approach
the metro not only as a mechanical or technological mode of transport but also as a
social, experienced and affective urban space in which digital devices, and through them
virtual realities, play a part. The metro is not merely a vehicle that takes passengers
from A to B, nor is a metro carriage or station merely a ‘non-place’ (Augé, 1995). On the
contrary, in these spaces, people gain experiences, learn about and take part in public
social order and are socially, virtually and emotionally engaged (see Zaporozhets, 2014;
Thibaud, 2015; Hatuka and Toch, 2016). Their experiences and emotions are deeply
interwoven with interactions with other people of different ages and from diverse
backgrounds.1 We concur with Carina Listerborn (2015, 97), who studied veiled women's
experiences in Malmö, Sweden, and who suggests that ‘encounters between strangers, as
different users of public spaces, are one of the core subjects for discussion in relation
to orders in the public space’. Regarding the metro in particular, we align ourselves with
Richard E. Ocejo and Stéphanie Tonnelat (2014, 494), who regard the metro as a unique
public space in which social order is negotiated with strangers, namely those who are
located spatially close but socially distant from each other (following Simmel's (1964)
notion of ‘the stranger’ as an inherent aspect of city life). The presentation of
strangeness is an essential feature in this context, involving informal norms and their
guidance through social control (Ocejo and Tonnelat, 2014, 495). We study social order and
control in the highly-digitalized metro environment, which is equipped with wireless
infrastructure and provides broadband Internet access to mobile devices. Tali Hatuka and
Eran Toch (2016, 2195–2196) referred to the use of mobile devices as ‘a portable private-
personal territory’, which is characterized by permeable boundaries between the private
and the public or the material and the virtual in daily life places, as smartphones and
devices connect their owners to multiple webs of relations. In the neo-liberal discourse,
the appearance of mobile devices and new media is often celebrated as a means of making a
city more accessible, flexible and smooth for its citizens, providing them with increased
safety through electronic connectivity (Brighenti, 2012, 408; Hampton et al., 2010,
701–702). As alleged digital natives, young people's competencies are often believed to
empower them as they are able to teach the older generations how to use the newest apps or
play popular games (Giddings, 2017; Mäyrä, 2017). Not exclusively adhering to these
discourses, we are interested in young people's subjective understandings of the nature of
social order on the metro, which serves for us as an example of a highly technologized and
digitalized social system of the media city. We understand social control as a necessary
feature of social life that makes social interaction smooth and predictable. Yet at the
same time, it involves power relations and possibilities for oppression as well as conveys
messages on the conditions of belonging versus exclusion (Von Scheve and Von Luede, 2005).
Through addressing social control, we examine what young people's accounts about
travelling on the metro reveal about their entitlements to using urban spaces (Listerborn,
2015; Maira and Soep, 2005). From this perspective, we will focus on young people's
stories about their encounters with adults, primarily those encounters characterized by
ambivalence, and analyze the meanings created within the framework of symbolic violence
(Bourdieu, 1977; Bourgois, 2001). Integral to the notion of symbolic violence is the
premise that dominant views are perceived from a limiting perspective, which portrays
social order as natural and self-evident, thereby concealing the structural power
relations behind it. Our aim is to analyze personal narratives to understand the formation
of the intergenerational order, to determine the role of digital devices in this context
and to provide insights into young people's entitlements in the contemporary media city.

<h>DATA AND METHODS</h>
----------------

This study focuses on 15- to 17-year-olds, who lack many formal rights (in Finland, 18 is
the age of majority and the voting age, while 15 is the minimum age of criminal
responsibility and for other legal actions like concluding an employment contract) but for
whom the metro provides the possibility of exploring the city independently of parents. In
public discourse, the ‘underaged’ are commonly depicted with ambivalent perceptions as
either victims or perpetrators of disruptive acts, especially in public places (e.g.
Fleetwood, 2004). We are distancing the study from these depictions by carefully analyzing
young people's subjective experiences of social control. The empirical material originates
from interviews conducted during the Helsinki City Youth Department project in 2016 and
2017. The City of Helsinki recruited young people for a period of one month each summer to
work on an art project, Ole hyvä Helsinki! (You're Welcome, Helsinki!), which is part of
the city's branding campaign, Brand New Helsinki (http://brandnewhelsinki.fi/). Young
people produced art for metro stations and worked in workshops on city premises (youth
centres, art centres) near several metro stations (in 2016, four groups worked on four
metro stations, and in 2017, the city expanded the project to 10 stations). A total of 31
interviews were conducted in 2016–2017 with 57 young people aged 15 to 17 using semi-
structured individual or group interviews. The interviews were voluntary, and participants
could choose whether they wanted to participate in a group (2–4 participants) or
individually. Only a couple of the young people who had engaged in the city workshops in
the centres we visited declined to participate in the study. The main themes of the
interviews concerned everyday metro experiences, the use of apps and devices in transit,
mobility in the city and neighbourhood identities. The participants represented various
social strata and lived in neighbourhoods near the workshops where they were working. The
majority (80 percent) of workshop participants were young women, with one participant
describing their gender as non-binary, while around 10 percent represented ethnic or
racial minorities. By and large, groups in Helsinki city centre mostly consisted of people
from middle-class backgrounds. We do not, however, regard this as a problem, considering
that many previous studies on youth engagements in the urban sphere have focused on young
people from working-class backgrounds (e.g. Kehily and Nayak, 2014; Skelton, 2001). The
interviewees from eastern neighbourhoods, however, had more diverse socio-economic
backgrounds. Narratives describing encounters with adults were extracted from the
transcribed interview data, and through a process of close reading, we identified themes
including stories and reflections on norms and expectations concerning young people's
conduct on the metro. We also paid attention to young people's descriptions of their use
of digital devices while in transit. The studied accounts represented actual examples of
the formation of social order in the digitalized and technological metro setting as
articulated in the participants' own words (Ocejo and Tannelot, 2014, 499–500).

<h>LIGHT SOCIALITY SHAPED BY THE NORM OF SILENCE</h>
---------------------------------------------

In almost every interview, the participants talked about metro carriages as mundane,
convivial spaces, which hosted very limited social interaction. According to the
interviewees, metro carriages are silent spaces where one is not expected to make a loud
noise, stare at other people or intrude into other people's personal space. This was
termed ‘the norm of silence’ or ‘light sociality’ by our participants, and it has been
theorized by Goffman (1963), for example, as ‘civil inattention’, in which the presence of
others is visually acknowledged without focused interaction or verbal communication (Ocejo
and Tonnelat, 2014, 495, 497). Sometimes it can be like that. For instance, you bump into
a stranger, apologize, everyone smiles and then ‘okay, goodbye’. Or, okay, someone dropped
something, forgot something and then you kind of ‘hey, you dropped your umbrella’, ‘okay,
thanks’ … [you] don't necessarily go to talk to a stranger because you don't know whether
[he/she]2 wants to talk, what kind of person [he/she] is. You don't know whether [he/she]
will look at you strangely if you start talking and everything … This kind of norm of
silence is very hard to break. Even if you are not afraid of embarrassing situations,
somehow it does not feel natural. (Neo, 17, male) The norm of silence, as described by Neo
above, allows the passengers to be ‘in their own bubble’; to lose themselves in thought,
look through the window or daydream. Most of the young people we interviewed admitted to
routinely entertaining themselves in their ‘portable private-personal territory’ (Hatuka
and Toch, 2016) by scrolling social media, chatting with their friends online or watching
their favourite series via streaming services. Some even related to the metro carriage as
‘a space of productivity’ (Hampton et al., 2010, 714), as they described how they used the
metro ride for doing their homework with their devices. Even though some young people were
very critical of the extensive use of smartphones and social media in public places, many
could not imagine a tedious metro journey without engaging in private activities on-
screen, making visible the nature of the metro space as a media city. Sixteen-year-old
Riina, for example, referred to this somewhat self-ironically as she admitted to having
been ‘terrified’ every time her phone ran out of power on the metro. Furthermore,
immersing oneself in virtual realities while travelling was sometimes portrayed as an
actively chosen means of shutting out the ‘background noise’ in order to ‘be somewhere
else’ – as explained by 17-year-old Aino. Hence, the young people's accounts illustrate
the ways in which digital technology is explicitly used to reduce attentiveness to one's
surroundings (Hatuka and Toch, 2016; Ocejo and Tonnelat, 2014, 504). Despite the strong
norm of silence, most of the young people admitted that they had sometimes been approached
by adults or engaged in brief exchanges with them while travelling on public transport. In
the interview accounts, the adults who approached young people were either referred to as
‘oldies’ or ‘different’ in some way, such as alcoholics. By contrast, ‘people like mothers
with small children’ or those going to work were, according to the interviewees, very
task-oriented within public spaces and too preoccupied with their own matters (including
their private digital bubbles) to engage in conversations. The exchanges with ‘grannies’
or ‘grandpas’, as the older passengers were called, were often described neutrally or in
positive terms as amusing encounters or pleasant chats, emphasizing the convivial nature
of travelling. Similarly, listening to intoxicated adults' stories was often seen as funny
and entertaining, and being drunk in public was not regarded as wrongful for the most
part. By contrast, many saw substance users as an inevitable and normal feature of urban
life. In general, the young people felt that they were treated well or at least
‘neutrally’ on the metro compared to everyone else. Some stated that any possibly negative
reactions were caused by the bad behaviour of young people themselves. Notwithstanding
individualized tensions, the interviewees also challenged the strict division between
their generation and adults into two, easily identifiable and inherently oppositional
groups (Kallio, 2017; Fleetwood, 2004, 35; Ocejo and Tonnelat, 2014, 500). Instead, a
distinction was made between well- and badly-behaved people, with the latter including
noisy and unruly people of different ages. This division is visible in the following
account, in which the young man positions himself as an ‘invisible’ rider (Ocejo and
Tonnelat, 2014, 498), hence conforming to the atmosphere shaped by civil inattention
discussed above: There are young people who behave well and there are noisy young people.
[ People] always look angrily at those who are very noisy. I even do it myself. As for me,
no one ever looks at me. I am kind of invisible; I never cause any kind of disorder, so no
one ever looks at me. (Alex, 17, male)

<h>FROM SEXUAL HARASSMENT TO DEROGATORY REMARKS</h>
--------------------------------------------

Aside from the emphasized neutrality of contact with adults, some more ambiguous
situations with adults were mentioned, including experiences of sexual harassment, racism
and being labelled negatively according to stereotypes. The civil inattention discussed
above called for flexibility from passengers as well as the need to overlook norm
violations on occasion (Ocejo and Tonnelat, 2014, 497), which our interviewees were aware
of. At the same time, the problematic nature of this kind of overlooking was perhaps most
vividly apparent when some of the young women discussed their experiences of sexual
harassment on the metro. Several of them admitted to having experienced it, as explained
by the following interviewee: It was precisely on the metro where the incident occurred,
and it was very distressing when someone started to follow me. He followed me for 15
minutes or so, then I kind of … very nice [ironical tone], he shouted after me that I was
really beautiful and everything. Yeah, those are very distressing experiences for me at
least. (Minna, 17, female) These incidents were not regarded as violence, nor were they
seen as particularly scary situations – rather, they were viewed as occasions during which
‘nothing really happened’ (Stanko, 1990). As such, they were acknowledged as an inevitable
part of everyday life for many girls and younger women in the city. One of the young
women, for example, recalled a recent and, according to her, ‘minor’ yet irritating
incident, and commented that it came to mind only because sexual harassment was discussed
in the interview. Some of the young women related how they had grown accustomed to this
kind of conduct as early as age 12 or 13. The self-evident nature of the young women's
experiences of sexual harassment had come as a surprise to some at first, especially when
being among other people in a metro carriage is not perceived as a situation in which one
would expect intrusions into bodily integrity (see also Listerborn, 2015, 110). The
perpetrators were often described as middle-aged men (or those in their 30s) who were
sometimes – but not always – under the influence of alcohol. They were described as
looking for some sort of sexual contact with young girls. Unwanted advances consisted not
only of verbalized messages or touching, but also took the form of intense staring or
sexual gestures. The men's comments about beauty or good looks were generally regarded as
unacceptable and unwanted as opposed to flattering. Once I was going to school, and there
[on the metro] was someone, a sort of, some guy was staring at me and smiling. And when I
was about to leave, he winked at me. I just looked at him in astonishment. I was going to
school! It was kind of amazing [said ironically], yes. (Olivia, 17, female) Reactions to
harassment and boundaries of tolerance are decidedly contextualized. Fifteen-to sixteen-
year-olds are highly sensitive to harassment in urban public places – particularly on
public transport and by older males (Aaltonen, 2017). However, in the social order of the
metro, shaped by civil inattention and passengers' immersion in their private digital
bubbles, these experiences become either invisible or tolerated. According to the
interviewees, nobody intervened as a rule, and unless something very exceptional occurred,
no help could be expected from fellow passengers. Hence, they emphasized that they could
only rely on themselves and develop skills to cope with such situations. The following
incident was recounted by 16-year-old Ruska, who described their gender as neutral (not
adhering to the strict binary division of male or female) and recalled being harassed by
‘lads’. The feeling of being left to cope alone during the incident is aptly summed up by
Ruska below: Ruska: Once, some guy just put his hand on my knee and started to move his
hand, and then I kind of really hit his hand and left. Ruska: And then people sort of
noticed that something had happened, but they did nothing; they kind of said nothing to
this person. Interviewer: So, no one intervened? In addition to sexual harassment, quite a
few interviewees, regardless of gender, mentioned being accused of various issues related
to their age while on the metro, such as loitering, being too noisy or too preoccupied
with their gadgets, or of alleged bad behaviour in general. A frequently mentioned example
was when the young people were watched to ensure that they did not occupy the priority
seats (i.e. seats reserved for the disabled or elderly). These encounters were not always
described as explicitly confrontational but generally consisted of angry gestures or
scowls, thus making visible the norms and general attitudes towards young people in these
situations (Fleetwood, 2004, 36). One of the young women said that she was always a bit
paranoid about this and was constantly prepared to encounter negative comments or
‘shouting’. Hence, her strategy was to avoid carriages occupied by older passengers. A
male respondent regretted not being able to respond with a witty retort to a ‘grandpa’
accusing him of sitting in the ‘wrong seat’. This was because he had been surprised by the
elderly man's reaction, particularly seeing as the carriage had been half empty at the
time. An old man came and tapped me on the back and said, ‘When you're young, it's good
that you can sit [on public transport], so when you get old you'll be able to stand’. Then
I asked, ‘Do you want to sit here?’ He said that he didn't. He told me to go ahead and sit
if it was so important for me. In retrospect, I should have said that yes, I actually
wanted to sit down. But in that kind of situation, witty replies seldom come to mind.
Besides, it's probably better not to start arguing, even if it sometimes crosses your mind
to answer an inappropriate comment in an equally inappropriate way. (Satoshi, 17, male)
Racist insults and comments about young people's personal style or outward appearance were
also mentioned as examples of unpleasant experiences on the metro. In the following
excerpt, the young woman described how she had been upset and angry about the impolite
attitude of an older woman she called ‘granny’, who commented on her looks: Once there was
a granny who started to look at me in a kind way and smiled, so I smiled back. Then she
suddenly said, ‘You have very ugly eyebrows; why did you paint them like that?’ Just like
that; smiles politely and then simply tells me that I look ugly and to go and wipe some of
it off. (Lotta, 17, female) Outward appearance, clothes and makeup are important means of
identity-building for young people (McRobbie, 1997), and while often influenced by the
fashion industry, they are highly personal. Hence, comments concerning one's looks can be
particularly insulting. What was even more upsetting for Lotta above was that the comments
were uttered by a kind-looking person who was smiling at the same time (cf. Listerborn,
2015, 109). Later in the interview, she emphasized her attempts to make a good impression
by being polite and avoiding swearing in public, and regarded the comments by the older
woman as unfair in this respect, too. Like the young man above, Lotta felt unable to talk
back. Responding in an impolite way would have reaffirmed the negative stereotype of young
people as troublesome, as she explained: So, I don't really understand; you can't say
‘mind your own business’ or anything like that because there is still some kind of
authority-politeness kind of position. I was expected to apologize for my ugly eyebrows
and then leave. (Lotta, 17, female) Based on the respondents' accounts, it can be said
that young people are expected to play a part as ambassadors of youth (cf. Listerborn,
2015), which prevents them from defending themselves, as the following story by Olivia
reveals: I was walking out of the metro with friends when a very rough woman just pushed
me for walking too slowly because I didn't want to push the person in front of me. I made
a comment of some sort, and then she began complaining that young people are blah blah
blah. That's what young people get for being nice and giving up their seats to everyone on
the bus, metro and so on but still get blamed for not respecting older people. (Olivia,
17, female) The above examples are revealing when it comes to young people's ambivalent
positions in the social order of the contemporary city (see Ocejo and Tonnelat, 2014,
498). Some participants described using the metro as uncomfortable and stressful because
of the possibility of being treated unfairly, condescendingly or rudely by older
passengers. The respondents seemed to think that a double standard exists in
intergenerational relations: older people are entitled to comment on or even touch young
people, but young people are expected to be well-behaved and polite towards adults (also
Listerborn, 2015, 108). For this reason, the participants felt that their ability to
negotiate was limited, particularly with older people they encountered on the metro.

<h>DIGITAL MEANS OF COPING</h>
-----------------------

Based on the interviews, avoiding conflicts with adults seemed to be a major concern for
some young people on the metro. In the context of a media city, the interviews revealed
several significant patterns in this respect. First, young women in particular seemed to
use their portable devices (smartphones, headphones, tablets) not only for entertainment
and communication but also to secure privacy and to claim and safeguard their personal
space (see Fleetwood, 2004, 38). Some referred to their gadgets or music as ‘a getaway’,
meaning both the ability to distance oneself from one's surroundings and to protect
oneself from unwanted advances, especially from adult males. The following excerpt
exemplifies this: Well, usually I travel on the metro with a phone in my hands. I listen
to music or watch something, check Twitter or apps like that. So, if someone comes and
actually speaks to you, some random dude, then you can just pretend that you aren't
listening to him or haven't noticed him. That's what I always do. It's a kind of safety
issue for me, meaning that I don't necessarily need to encounter people. (Minna, 17,
female) Second, the respondents reported that they resorted to their smartphones or other
gadgets (i.e. headphones to listen to music) especially if they felt that there were
potentially intrusive passengers around or if they were travelling alone. Hence, they used
digital devices as part of their personal safety routines (Stanko, 1990) or ‘street
wisdom’ (Anderson, 1990) on and around public transport. Communicating with someone (on
the other end of the line), for example, was portrayed as one of the tricks young female
travellers used to overcome stressful situations. This is described below by Olivia.
Talking on the phone after leaving the metro station was described in her account as a
safety routine that increased her confidence about travelling in public. I use a bus line
that starts outside the metro station. One Saturday evening at the bus stop, I realized
that a man was staring at me. I thought, okay, now [I] should do something, and I decided
to call a friend. I talked to her during the entire bus trip home. I felt safer since I
could not have been attacked while on the phone, especially seeing as I told my friend
where I was and some other general information just to be on the safe side. (Olivia, 17,
female) Considering the data, it seems that the young women's digitalized coping
mechanisms were individualistic, as they were adopted in an atmosphere shaped by civil
inattention and the travellers' general immersion in their private digital bubbles.
However, in some accounts, digital devices were connected to safety in a more
communitarian way, as some young women emphasized their habits of looking after one
another and making sure that friends arrived safely at their destinations when travelling
later in the evening. Third, digital devices were used by young people as shields against
the adult gaze and for minimizing the opportunities for interaction with them out of fear
of negative comments related to their youth. This is described by 17-year-old Lotta and
Veera in the following exchange. For them, engagement in their private digital bubbles
gave an impression of business as opposed to loitering, which, they claim, young people
are often accused of. Lotta: Yes, it is kind of strange; when you are my age, whatever you
do is just loitering. Like, if I'm waiting for public transport or waiting for a friend
downtown, I always try to look terribly busy so that people would not get an impression
that I'm just hanging around there. Veera: In that situation I usually grab my phone and
pretend to be scrolling something […] Interviewer: […] You said that you take your mobile
out and then what do you do? Veera: Well, I go to Instagram. Even if I have already seen
all the feeds many times, I go there again in the desperate hope that there will be
something new, please, anything new. Fourth, regarding the technologized metro system,
many of the young people we interviewed had expectations of safety from the
representatives of formal control, such as security guards. Despite sometimes being viewed
as possessing stereotypical views of young people (see also Saarikkomäki, 2017), they were
nevertheless regarded as safe adults, sources of help and advice and professionals with
official rights to maintain public safety, thereby representing protective and caring
forms of social control for young people. However, in the digitalized metro system, which
is in itself effective in following passengers everywhere (Brighenti, 2012, 410), one
quite rarely encounters such safe adults and cannot expect help from CCTV cameras, as was
pointed out by our interviewees. Also, some respondents felt that security personnel had
disregarded or overlooked their safety needs on the metro. When asked what they would like
to change in the Helsinki metro system, interviewees most commonly mentioned that they
wished to see more security guards in metro carriages and stations, especially in the
evening and at night.

<h>AMBIVALENT ENCOUNTERS AS SYMBOLIC VIOLENCE</h>
------------------------------------------

As previously mentioned, it was common for the young people we interviewed to portray
metro carriages and stations as neutral spaces with limited social interaction with
unknown people (Goffman, 1963; Augé, 1995), and the tendency for passengers to be in their
private digital bubbles during the metro ride. We have, however, also documented another
side to this story, describing young people's recollections of mundane but ambivalent
encounters in which they felt that their presence on the metro was monitored or challenged
by older generations. Depending on the young person in question, these experiences were
either seen as isolated incidents or as common features of public transport. Hence, these
experiences were not unitary, and their meanings varied depending on contextual factors.
Despite this variability, the ways in which the interviewees made sense of their
experiences can be interpreted in line with conceptualizations of symbolic violence
(Bourdieu, 1977; Bourgois, 2001). Accordingly, sexual harassment, for example in the form
of gestures or staring, makes young women in particular conscious of their visibility and
vulnerability on the metro. They learn to view themselves as self-evident and natural
objects of harassment, especially when performing idealized femininity. They also learn
that, as young women, they are expected to cope with harassment by themselves and to put
up with it without making a big issue of it. What they do not recognize, however, are the
unobserved structural or cultural mechanisms behind the objectifying practices (Bourgois,
2001). At worst, if something happens, the young women might end up blaming themselves for
not having been cautious enough (Pedersen, 2009). While some seemed confident about their
coping strategies and cleverly used technological means to facilitate them, others talked
openly about their fears and worries concerning their personal safety. The possibility of
sexual violence was discussed in some interviews, illustrating the continuum of sexual
violence in the consciousness of at least some young women (Kelly, 1987). Similarly,
experiences of being labelled as misbehaving youngsters can be interpreted as a form of
symbolic violence. The participants seemed to have internalized the fact that they could
be confronted as representatives of the ‘troublesome’ young generation when they travel in
the city. They did not usually portray themselves as victims of these utterances but were
nevertheless irritated that they did not have sensible means of talking back. Experiencing
negative reactions can negatively affect their trust in adults and their confidence while
travelling in the public sphere (Listerborn, 2015, 109). Based on the interviews, it can
be said that the mundane nature of these experiences disguises the intergenerational power
relations that are reproduced in them and that portray young people as immature, deficient
and of less worth than adults. The acts giving rise to ambivalent emotions are not overt
violence but often mundane experiences – situations which may not even be noticed by other
passengers often engaged in their own virtual networks. The rude comments are based on the
negative imaginaries of youth, claiming that young people are in need of education,
discipline or adult guidance. The older people's conduct towards young people can
therefore reflect their genuine fear of youth, which they feel safe uttering only in
certain situations. Despite this, many young people regard this kind of treatment as
insulting as it affronts their dignity as people and categorizes them as deviant youth.
When allowed to continue without intervention, the negative imageries are reproduced, and
both the older people who intrude into young people's privacy and the adults who remain
passive bystanders operate in ways that fail to recognize the harmful consequences of
their actions for young people as users of public transport (Cooper, 2012, 66). As such,
they take part in forming a social order of discriminating patterns that might restrict
young people's movements in the city (Listerborn, 2015, 106–108).

<h>CONCLUSIONS: AMBIVALENT ENTITLEMENTS SHAPED BY DIGITAL BUBBLES</h>
--------------------------------------------------------------

Intergenerational interaction in the Helsinki metro seems to be characterized by young
people's expectations of conviviality and travelling in their private digital ‘bubbles’ on
the one hand, and confusion concerning their position on the other. They feel that they
are required to act like adults, yet they must be prepared to be treated like children
without rights, targets of sexual harassment or intrusive comments, or problematic kids
who should be disciplined or given advice on how to behave or look. In other words, young
people feel that they are expected to behave well, which does not, however, preclude
adversarial encounters with adults. These experiences may arouse feelings of alienation in
the urban public realm, as this condition is often viewed as a self-evident reality that
young people feel they must adjust to without many opportunities for change. It is notable
that the characteristics of social order that we have analyzed here as symbolic violence
are formed in the metro system of Helsinki, which lacks many features of formal
surveillance that exist in larger cities, and where social control mainly entails informal
interaction between strangers. Moreover, the Helsinki metro sociality is characterized by
widespread use of digital devices. Based on our analysis, we claim that the neoliberal
discourses emphasizing the positive aspects of digitalization on urban sociability (see
e.g. Hampton et al., 2010) disregard other, more complex impacts related to intensified
use of digital technology in public spaces. Digital technology is documented to have
created, in addition to new opportunities for city dwellers, new automated forms of
control involving discriminatory restrictions of freedom of movement (Brighenti, 2012,
408; Graham and Wood, 2003). In addition, as we argue here, the contemporary mediatized
and digitalized metro sociality might contribute to the constitution of an oppressive
intergenerational order in the public sphere in which young people are relegated to
subordinated positions and treated according to stereotypical depictions. This is made
possible by the young and middle-aged passengers' extensive immersion in their digital
bubbles when travelling on the metro. Aside from the narratives of our respondents, it is
easy to observe that this is a general mode of conduct on public transport, especially on
the metro. Based on the narration of the participants in this study and on observations in
earlier studies (e.g. Hatuka and Toch, 2016; Hampton et al., 2010), it can be claimed that
the travellers' extensive immersion in their ‘portable private-personal territories’
decreases their attentiveness to social surroundings and less familiar people. It also
seems to reduce the general preparedness of passengers to intervene in problematic
situations between generations, which, according to the interviewees, have occurred
between them and adults who are ‘older’ or somehow ‘different’ from busy, task-oriented
adults. Secondly, young women in particular have adopted mobile technology as part of
their personal safety routines. In that sense, it can be argued that digitalization has
increased their feelings of safety in their personal space amid strangers (Hatuka and
Toch, 2016, 2203–2204). Yet simultaneously, as they expect no support from their fellow
passengers, despite the existence of mobile technology, they still feel vulnerable and
talk about coping mainly as their own responsibility. The implications of mobile
technology for social relations in the urban sphere are hence ambiguous. The digital
revolution has not only liberated teenagers to explore the media city on their own terms,
but internet connectivity and portable digital devices are also involved in processes
based on stereotypical imaginaries of youth, which can have harmful consequences for young
people's capacities to use city spaces. The persistence of these perceptions is of course
only one aspect of the lived realities of young people in urban spheres. Nonetheless, if
not problematized, their continued use will restrict young people's opportunities to
relate to the media city as a safe place to explore.


<h>REFERENCES</h>
----------

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<ART>Internalizing emotions: Self-determination as an antecedent of emotional intelligence
================================================================================

Authors: Dominique Perreault, Lisa Mask, Melinda Morgan, Céline M. Blanchard
DOI: 10.1016/j.paid.2014.01.056
Year: 2014  |  Pages: 1-6
ASJC codes: 3200
Keywords: Emotional intelligence, Psychological well-being, Self-determination

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

An extensive body of literature indicates that people differ in the extent to which they attend to, process, and regulate emotions. The present research sought to build on this knowledge by examining whether general self-determination (GSD) could account for individual variation in emotional intelligence (EI) and psychological well-being (PWB). A simple and multiple mediation model using bootstrap analyses tested these relationships in a sample of students (Study 1, N= 283) and workers (Study 2, N= 265). Results supported the hypothesized mediating role of EI in the relationship between GSD and PWB across both studies. When the inter-related facets of EI were considerately separately, indirect effects emerged for mood regulation/optimism and social skills across both studies as well as for utilization of emotions, albeit negatively, in Study 2. Our findings support and extend past work on the antecedents of EI and have important implications for human functioning across a variety of settings. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

A wealth of scientific evidence indicates that people vary in the extent to which they use
emotion-related information in their day to day lives. Mayer, Salovey, and Caruso (2000)
refer to this capacity as emotional intelligence (EI) which they formally define as “the
ability to perceive and express emotion, assimilate emotion in thought, understand and
reason with emotion, and regulate emotion in the self and in others” (p. 396). To these
authors, EI is therefore a set of abilities and should be assessed with maximum
performance measures much like traditional intelligence tests (e.g., Mayer, Salovey, &
Caruso, 2002; Petrides, 2011; Petrides & Furnham, 2000a). A distinct but complementary
conceptualization of this construct (Schutte, Malouff, & Bhullar, 2009) defines EI as a
set self-perceptions, dispositions, and motivations that are affective in nature and that
share some common variance with major personality traits (Petrides, Pita, & Kokkinaki,
2007; Petrides, Pérez-Gonzalez, & Furnham, 2007). Unlike the ability-model, this trait
model of EI captures the inherent subjectivity underlying one’s emotional experience and
should therefore be assessed via self-report measures (e.g., Petrides & Furnham, 2000a;
Petrides & Furnham, 2000b; Schutte et al., 1998). Notwithstanding these divergent
operationalizations, EI has emerged as a viable and important construct in the literature
evidenced by the accumulation of handbooks, book chapters, review papers, and meta-
analyses on the subject. For instance, those who score high on measures of EI perform
better at work (e.g., O’Boyle, Humphrey, Pollack, Hawver, & Story, 2011) and in school
(e.g., Petrides, Frederickson, & Furnham, 2004); they also report more positive
relationships (e.g., Mavroveli, Petrides, Rieffe, & Bakker, 2007) and better physical
health (e.g. Costa, Petrides, & Tillmann, 2014). However, it’s the enhancement of
emotional health and well-being wherein lies the construct’s greatest potentiality and
interest. For instance, EI is negatively related to several indices of psychopathology
(Malterer, Glass, & Newman, 2008) such as personality disorders (Petrides, Pérez-González,
et al., 2007) and anxiety disorders (Summerfeldt, Kloosterman, Antony, McCabe, & Parker,
2011) as well as self-harm (Mikolajczak, Petrides, & Hurry, 2009) and externalizing
behaviors in adolescents (Downey, Johnston, Hansen, Birney, & Stough, 2010). In non-
clinical samples, EI correlates positively with a variety of well-being indices such as
life satisfaction, happiness, optimism, self-esteem, and decreased negative affect (for
reviews see Brackett, Rivers, & Salovey, 2011; Petrides, 2011) with a meta-analytic
correlation of .34 (Martins, Ramalho, & Morin, 2010). But why do some people attend to,
process, and regulate their emotions with greater ease than others? In other words, what
accounts for the individual variation in EI? Consistent with the trait-model of EI (e.g.,
Petrides, Pita, et al., 2007), higher-order personality factors are purported to shape
people’s affective self-perceptions. For instance, trait EI mediated the relationship
between each of the Big Five personality traits and self-reported mental health and well-
being (e.g., Johnson, Batey, & Holdsworth, 2009). Other research suggests that trait EI
may stem from dispositional differences in quality of attention. Schutte and Malouff
(2011) observed that the relationship between mindfulness and various indicators of
subjective well-being (i.e., positive affect, negative affect, and life satisfaction) were
mediated by trait EI. Significant indirect effects for a specific subcomponent of EI,
namely mood regulation have also been documented. For example, Kämpfe and Mitte (2010)
observed that mood repair accounted for the relationship between extraversion and life
satisfaction as well as between extraversion and happiness. Other research found cognitive
reappraisal of emotion to partially explain the relationship between secure attachment and
well-being (Karreman & Vingerhoets, 2012). Together, these findings suggest that the
ability to perceive and manage one’s emotions is partly due to stable individual
differences such as one’s personality, attachment style (i.e., secure attachment), and
mindfulness. In the present research, we investigated self-determination as a plausible
antecedent of EI that contributes to psychological well-being (Bhullar, Schutte, &
Malouff, 2013). At the core of self-determination theory (Deci & Ryan, 1985) lays a
motivational perspective of the self which is endowed with integrative capacities toward
increasing organization and coherence (Ryan, 1993). The expression of this coalescence is
reflected in the degree of perceived autonomy or self-determination underlying the
regulation of action. For instance, behaviors which are initiated out of inherent interest
and enjoyment for their own sake (intrinsic regulation) are experienced as the most self-
determined followed by reasons to act in accordance with one’s deepest values (integrated
regulation), and then by personal identification with the activity (identified
regulation). However, not all behaviors are experienced as authentic and freely chosen;
many are initiated out of pressure and obligation to bolster or protect one’s sense of
self-worth (introjected regulation), to comply with external demands (external regulation)
or without any intention (amotivation). These behaviors are experienced as controlling and
coercive because the underlying self operates in a fragmented and compartmentalized
manner. These six styles of behavior regulation can be combined into a single index,
whereby higher scores reflect greater self-determination which is linked to healthier
functioning and well-being (e.g., see Deci & Ryan, 2008 for a review). The integrative
capacity for effective and adaptive self-regulation of action is also reflected in the
manner with which one meets their moment to moment experiences. According to Hodgins and
Knee (2002), greater self-determination endows a person with more openness and less
defensiveness toward potentially threatening and difficult events. For instance, when
primed with self-determination, people report less desire to escape and engage in fewer
self-serving attributions in response to failure (Hodgins, Yacko, & Gottlieb, 2006).
Autonomously-oriented individuals also exhibit better emotional regulation and integration
of negative affect after viewing a traumatic film clip (Weinstein & Hodgins, 2009) and
retrospectively recalling negative life events and identities (Weinstein, Deci, & Ryan,
2011). However, little is known on the skills utilized by those with greater self-
determination which promote effective assimilation of emotionally-laden experiences into a
more unified and cohesive self. We propose that these skills are attributed in part to the
inter-related abilities of EI. The objective of the present research was to investigate
individual variation in EI by examining the determining role of self-determination which
was assessed at the dispositional or general level indicative of a more enduring
motivational orientation toward the environment (Guay, Mageau, & Vallerand, 2003). To this
end, the inter-related abilities of EI were hypothesized to mediate the relationship
between general self-determination (GSD) and psychological well-being (PWB). These
relationships were initially tested with a sample of undergraduate students (Study 1) and
then replicated with a sample of working adults (Study 2).

        <hss>Participants and procedure</hss>

        A sample of 283 undergraduate students of which the majority were female (n = 226)
        took part voluntarily in this two-phase study (Mage = 18.95 years, SDage = 1.75).
        Participants were recruited from a campus subject pool and received course credit
        in exchange for their participation. Measures of GSD and EI were completed at the
        beginning of the semester (Phase 1) while a measure of PWB was completed three
        months later (Phase 2).

        <hss>Measures</hss>

        GSD was assessed with the 18-item General Motivation Scale (GMS; Guay et al.,
        2003). The six subtypes of motivation proposed by Deci and Ryan (1985) are each
        represented by three items. Respondents rated the extent to which each item (e.g.,
        “…because I like making interesting discoveries”; intrinsic regulation)
        corresponded to their reasons as to “why they do things in general” on a scale
        from 1 (does not correspond to my reasons at all) to 7 (corresponds exactly to my
        reasons). Internal consistency estimates ranged from .68 to .84 across subscales.
        Mean subscale ratings were combined to form a GSD index whereby higher scores
        indicate greater GSD: +3 * (intrinsic) + 2 * (integrated) + 1 * (identified) − 1 *
        (introjected) − 2 * (external) − 3 * (amotivation). Cronbach’s alpha for the
        entire scale was .81. EI was measured using the Assessing Emotions Scale (AES:
        Schutte et al., 1998) where responses were rated from 1 (strongly disagree) to 7
        (strongly agree). As to its structure, some suggest the existence of a single
        global EI factor (e.g., Schutte, Malouff, Simunek, McKenley, & Hollander, 2002)
        while others propose the existence of four sub-factors (e.g., Petrides & Furnham,
        2000a; Saklofske, Austin, & Minski, 2003). Cognizant of this debate, EI was
        represented by a global EI factor derived by averaging scores across all 33 items
        as well as by four sub-factors derived by averaging scores across each subscale’s
        respective items. The subscales were derived from the work of Petrides and Furnham
        (2000a). Internal consistency estimates ranged from .72 to .84 across subscales (α
        = .91 for the entire scale). PWB was assessed using Ryff’s (1989) short form
        Scales of Psychological well-being (SPWB) which tap six different facets of
        positive psychological functioning. Responses were rated on a scale from 1
        (strongly disagree) to 7 (strongly agree) and then averaged across all 18 items to
        represent PWB (α = .84).

        <hss>Descriptive statistics</hss>

        Descriptive statistics are reported in Table 1. As predicted, positive
        relationships emerged between GSD, EI, and PWB. On the bivariate level, age did
        not correlate with any variable. However, gender differences did emerge for
        certain facets of EI with women scoring higher than men on ‘appraisal of emotions’
        and ‘social skills’. Regardless of these observations, both gender and age were
        controlled for in subsequent analyses for theoretical reasons (e.g., Mavroveli et
        al., 2007; Petrides & Furnham, 2000b).

        <hss>Mediation analyses</hss>

        The hypothesized mediating role of EI in the relationship between GSD and PWB was
        tested using the SPSS macro, INDIRECT (Preacher & Hayes, 2008). The macro relies
        on the resampling method of bootstrapping; a procedure that provides an estimate
        of the indirect effect in the population by resampling the dataset k times in
        order to obtain the indirect effect’s sampling distribution and confidence
        intervals (CI). An estimate is considered statistically significant if its 95% CI
        does not include zero. Testing a simple mediation model, a direct effect emerged
        for GSD on PWB (B = .019, p < .001) as did an indirect effect through global EI
        with a point estimate of .0177, 95% CI [.0111, .0254]. The magnitude of this
        indirect effect was represented by an index of mediation (Preacher & Kelley, 2011)
        which was equal to .171. Thus, for every 1 SD increase in GSD, PWB would increase
        by .171 SDs through global EI. Effect size was estimated using Kappa2; a ratio of
        the obtained estimate over the maximum possible estimate of the indirect effect
        (Preacher & Kelley, 2011). In this case, Kappa2 = .18. Overall, GSD accounted for
        33% of the variance in PWB both directly and indirectly through EI, B = .037, p <
        .001, F(4,278) = 34,86, p < .001. To understand which facet of EI accounts for the
        relationship between GSD and PWB, a multiple mediation model (MMM) was tested with
        each of the four sub-factors of EI. These results are reported in Table 2.
        Indirect effects emerged for ‘mood regulation-optimism’ and ‘social skills’.
        Pairwise contrasts revealed that the former was greater than the latter. The index
        of mediation for each indirect effect indicates that for every 1 SD increase in
        GSD, PWB would increase by.188 and .043 SDs through ‘mood regulation-optimism’
        (Kappa2 = .20) and ‘social skills’ (Kappa2 = .05), respectively. In the MMM, GSD
        accounted for 40% of the variation in PWB both directly and indirectly through the
        four facets of EI, F(7,275) = 25.80, p < .001.

        <hss>Participants, measures and procedure</hss>

        This community sample was comprised of 265 working adults recruited from multiple
        work environments using a snowballing strategy, of which 46% were employed in the
        private sector and the remaining 54 % were employed in the public sector. The
        majority were women (n = 184) and the sample ranged from 18 to 58 years (M =
        32.93, SD = 12.32). Participants took part in this cross-sectional study
        voluntarily and were invited to complete a questionnaire comprised of the same
        self-report measures described in Study 1 with the exception of the SPWB for which
        a mid-length version of the scale was used whereby each factor was represented by
        nine items instead of three (GMS: αs ranged from .66 to .84 across subscales, with
        a Cronbach’s alpha for the entire scale of .82; AES: αs ranged from .69 to .81
        across subscales and was equal to .88 for the entire scale; SPWB: α = .92 for the
        entire scale).

        <hss>Descriptive statistics</hss>

        Descriptive statistics are reported in Table 1. Bivariate relationships between
        all constructs were consistent with predictions with the exception of ‘utilization
        of emotions’ which was not significantly related to GSD (r = .11, p > .05) nor to
        PWB (r = .02, p > .05). Age and gender emerged as significant correlates of GSD
        and EI. Consistent with the results of Study 1, women’s EI scores were higher than
        men’s on the global factor as well as on all facets of EI except ‘mood regulation-
        optimism’. Age and gender were controlled in subsequent analyses.

        <hss>Mediation analyses</hss>

        Testing a simple mediation model, a direct (B = .027, p < .001) and indirect
        effect with a point estimate of .0100, 95% CI [.0065, .0144] emerged for the
        global factor of EI with an index of mediation of .131 (Kappa2 = .14). GSD
        accounted for 36% of the variance in PWB both directly and indirectly through EI,
        (B = .037, p < .001), F(4,260) = 37.59, p < .001. Next, a MMM was tested, the
        results of which are reported in Table 2. Indirect effects emerged for all facets
        of EI with the exception of appraisal of emotions. Pairwise contrasts revealed
        that the indirect effect through ‘mood regulation-optimism’ was the greatest,
        followed by ‘social skills’ and then by ‘utilization of emotions’. The index of
        mediation for these indirect effects indicates that for every 1 SD increase in
        GSD, PWB would increase respectively by .146 and .043 SDs through ‘mood
        regulation-optimism’ (Kappa2 = .16) and ‘social skills’ (Kappa2 = .05).
        Contrarily, for every 1 SD increase in GSD, PWB would decrease by .031 SDs through
        ‘utilization of emotions’ (Kappa2 = .04). In sum, GSD accounted for 46% of the
        variation in PWB both directly and indirectly through the four factors of EI,
        F(7,257) = 33.19, p < .001.

<h>DISCUSSION</h>
----------

The efficiency and effectiveness with which people can identify, process, and manage their
emotions has important implications for their health and well-being. Part of this capacity
is attributed to structural factors such as one’s personality (e.g., Johnson et al.,
2009). Grounded in the framework of self-determination theory (Deci & Ryan, 1985), we
propose that part of this capacity stems from an underlying self that is motivational in
nature, oriented toward greater organization and unity. At the behavioral level, this
integrative propensity is manifested as general self-determination (GSD) which endows a
person with greater openness and receptivity to their environment (Hodgins & Knee, 2002).
The present research tested this proposition by investigating GSD as a plausible
antecedent that may account for individual variation in emotional intelligence (EI)
thereby resulting in differing levels of psychological well-being (PWB). Data obtained
from two different samples (students vs. workers) support these hypothesized
relationships. First, we examined the mediating role of global EI in the relationship
between GSD and PWB. All paths in the model were significant and positive across both
studies suggesting that greater GSD is associated with greater PWB, directly and
indirectly through increased global EI. Therefore, the more people undertake their daily
activities with a sense of volition and autonomy, the more skilled they become in
responding to and using emotion-laden information in their day to day decision making
processes thereby experiencing greater PWB. Consistent with the trait-model of EI, these
findings imply that part of its variability is motivational in nature (Petrides, Pita, et
al., 2007) and therefore suitable for intervention work. Indeed, people who underwent an
‘emotional competence’ training program significantly improved their employability, their
subjective well-being and the quality of their relationships post intervention (Kotsou,
Nelis, Grégoire, & Mikolajczak, 2011; Nelis et al., 2011). Our findings suggest that
intervention efforts might also benefit from targeting people’s GSD. For instance,
participants primed with subtle reminders of GSD (i.e., choice, opportunity, freedom)
evidenced better emotional integration following exposure to a traumatic film designed to
induce negative affect (Weinstein & Hodgins, 2009) and after recalling difficult life
events (Weinstein et al., 2011). Thus, participants undergoing an ‘emotional competence’
training program might experience accrued benefits if primed with GSD beforehand. Second,
we sought to better understand which of the four (if not all) inter-related abilities of
EI accounted for the relationship between GSD and PWB. Both ‘mood regulation-optimism’ and
‘social skills’ emerged as significant mediators suggesting that effective and adaptive
regulation of action is linked to effective and adaptive regulation of emotions, “within
the self and in relation to other people” (Vesely, Siegling, & Saklofske, 2013, p. 222).
These results emerged in both studies, lending strength to their effect and are in line
with the work of Spence, Oades, and Caputi (2004) who noted that mood regulation-optimism
was the strongest predictor of emotional well-being in a sample of students. Our analyses
also yielded one surprising result that warrants further discussion. Contrary to
expectations, the indirect effect of ‘utilization of emotions’ (UE) was negative and
significant in the worker sample but not in the in the student sample. To be specific,
this result suggests that greater GSD is linked to greater UE which in turn is associated
with lower levels of PWB. This particular subscale was designed to tap the extent to which
one is capable of using emotional information in generating ideas and solving problems.
Yet, a closer examination of its individual items (n = 4) suggests some bias toward
neutral and positive emotions (e.g., “When I am in a positive mood, solving problems is
easy for me”). Theoretically, this seems incongruent with the open and non-defensive
disposition of someone with greater GSD who is equipped at meeting and internalizing a
broad spectrum of emotions, even difficult ones. Stated differently, all emotional inputs
(positive and negative) represent potential sources of information in making decisions for
someone who initiates their actions based on well-integrated values. Statistically,
there’s also the possibility that UE acted as a suppressor in the model. When we tested a
simple mediation model linking GSD to PWB through UE, the mediator was not statistically
significant. However, when several MMM were tested that included UE, its indirect path
became significant. This finding may also be inherent to the subscale itself as other
studies noted similar problems (e.g. Gignac, Palmer, Manocha, & Stough, 2005). A few
limitations of the present research are worth noting. First, responses were limited to
self-report data. Future work could examine these relationships using a motivational
priming procedure and behavioral evidence of emotional integration and well-being (Hodgins
et al., 2006). Second, Cronbach’s alphas were low (<.70) for some of the subscales of the
GMS in Study 1 and 2, an issue that has been reported by other researchers (Julien, Guay,
Senécal, & Poitras, 2009). However, the entire scale was used in the creation of GMS
indexes whereby the reliability statistics were respectively .81 and .82. Third, the four-
factor solution documented by Petrides and Furnham (2000a) for the AES did not emerge in
our data. Attempts were made to keep our factor structure consistent with findings in the
literature, but some of the items did not provide the same fit across our samples
suggesting potential instability with respect to a four-factor solution. Future research
is needed to help elucidate sample differences when examining sub-facets of EI with the
AES. Fourth, the longitudinal nature of Study 1 implies that factors other than GSD and EI
assessed during Phase 1 influenced the reporting of PWB assessed at Phase 2. Future
studies should include potential covariates of this relationship (e.g., personality
factors). Despite these limitations, findings from the present research contribute to a
burgeoning literature on the antecedents of EI given the importance of EI for adaptive and
healthy functioning. By investigating the motivational underpinning of EI, our findings
lend credence to the growing interest in programs and workshops aimed at increasing EI.
Moreover, the present research was grounded in self-determination theory; one of the most
validated and comprehensive frameworks of human needs and motivation. Our results support
the predictions of Hodgins and Knee (2002) by linking a motivational orientation with
specific socio-emotional competencies which are conducive to better emotional integration
and therefore enhanced PWB. By uncovering the emotional pathways by which GSD leads to
better adjustment, future work might garner a better understanding of how people with
varying motivational profiles cope with adversity (e.g., Amiot, Blanchard, & Gaudreau,
2008) across a variety of settings (e.g., school, work, sports).


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<ART>Internet-Based Mindfulness Treatment for Anxiety Disorders: A Randomized Controlled Trial
================================================================================

Authors: Johanna Boettcher, Viktor Åström, Daniel Påhlsson, Ola Schenström, Gerhard Andersson, Per Carlbring
DOI: 10.1016/j.beth.2013.11.003
Year: 2014  |  Pages: 241-253
ASJC codes: 3203
Keywords: Anxiety disorder, Internet-based, Mindfulness, Randomized controlled trial, Treatment

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Mindfulness-based interventions have proven effective for the transdiagnostic treatment of heterogeneous anxiety disorders. So far, no study has investigated the potential of mindfulness-based treatments when delivered remotely via the Internet. The current trial aims at evaluating the efficacy of a stand-alone, unguided, Internet-based mindfulness treatment program for anxiety.Ninety-one participants diagnosed with social anxiety disorder, generalized anxiety disorder, panic disorder, or anxiety disorder not otherwise specified were randomly assigned to a mindfulness treatment group (MTG) or to an online discussion forum control group (CG). Mindfulness treatment consisted of 96 audio files with instructions for various mindfulness meditation exercises. Primary and secondary outcome measures were assessed at pre-, posttreatment, and at 6-months follow-up.Participants of the MTG showed a larger decrease of symptoms of anxiety, depression, and insomnia from pre- to postassessment than participants of the CG (Cohen's dbetween= 0.36-0.99). Within effect sizes were large in the MTG (d= 0.82-1.58) and small to moderate in the CG (d= 0.45-0.76). In contrast to participants of the CG, participants of the MTG also achieved a moderate improvement in their quality of life.The study provided encouraging results for an Internet-based mindfulness protocol in the treatment of primary anxiety disorders. Future replications of these results will show whether Web-based mindfulness meditation can constitute a valid alternative to existing, evidence-based cognitive-behavioural Internet treatments.The trial was registered at ClinicalTrials.gov (NCT01577290). © 2013 The Authors.

--------------------------------------------------------------------------------


<hs>  Participants</hs>
  ~~~~~~~~~~~~

The trial was registered at ClinicalTrials.gov (NCT01577290). The regional ethics
committee of Umeå University approved the study protocol. Participants were recruited via
advertisements in regional and national newspapers and on the project’s study website
(www.studie.nu). After registering with their e-mail address, participants obtained
detailed information about the theoretical background, the goals and the design of the
study, and were asked to give written informed consent. They were informed that the study
aimed to compare a mindfulness-based treatment to a control condition and that
participants randomized to the control group would receive access to the active treatment
after post-assessment. The selection of participants followed two steps. Participants were
asked to fill out the outcome questionnaires. These included, among others, the Beck
Anxiety Inventory (BAI; Beck, Epstein, Brown, & Steer, 1988), the Beck Depression
Inventory-II (BDI-II; Beck, Steer, & Brown, 1996), and additional questions regarding
current and past psychological or medical treatment for mental problems. Participants who
indicated at least mild anxiety on the BAI (cutoff > 8) and who did not indicate severe
depression according to the BDI-II (cutoff < 29) or suicidal ideation as assessed by the
suicide item of the BDI-II (item 9 < 2) were then invited to take part in a diagnostic
interview. The interview was conducted via telephone, a procedure with adequate
psychometric properties (Crippa et al., 2008). Four advanced MSc clinical psychology
students conducted the depression and anxiety disorders sections of the Structured
Clinical Interview for DSM-IV Axis I Disorders (First & Gibbon, 2004). The interviewers
had received training in using the interview. The SCID training included sample videos,
role-plays, and supervised training interviews. We applied the following inclusion
criteria: (a) at least 18 years old, (b) access to the Internet, (c) meeting diagnostic
criteria for a primary diagnosis of social anxiety disorder, panic disorder with or
without agoraphobia, generalized anxiety disorder, or anxiety disorder not otherwise
specified, (d) not participating in any other psychological treatment for the duration of
the study, (e) no extensive prior experience with mindfulness meditation, and (f) if on
prescribed medication for anxiety/depression, dosage had to be constant for 3 months prior
to the start of the treatment.

<hs>  Procedure</hs>
  ~~~~~~~~~

After pre-assessment, participants were randomly allocated to the mindfulness treatment
group (MTG) or the discussion forum control group (CG) by an online true random-number
service independent of the investigators. After randomization, participants of the MTG
received access to a website where the mindfulness program was presented. They were asked
to work with the mindfulness program daily for 6 days of the week for 8 weeks.
Participants in the control group received access to an online discussion forum and were
invited to take part in online discussions during 8 weeks. Participants in both groups
received an automated e-mail at the end of Week 4, encouraging them to carry on with the
assigned treatment. Primary and secondary outcome measures were administered over the
Internet prior to the treatment, after the treatment at the end of Week 8, and, for
participants of the MTG, at 6 months follow-up. Participants of the CG were offered the
mindfulness program after post-assessment.

        <hss>Internet-Based Mindfulness Treatment</hss>

        At the core of the unguided, Internet-based mindfulness treatment program were
        brief, instructive audio files presenting mindfulness exercises (Schenström,
        2010). Mindfulness exercises included instructions for sitting meditation,
        mindfulness movement, three different types of body scan, and four different forms
        of breathing anchor. The program was organized into eight modules. At the
        beginning, participants were presented with a 20-minute video that explained the
        concept of mindfulness and its relevance for anxiety disorders and introduced the
        eight modules of the program. The modules were as follows: Stopping and Getting
        Started Managing Your Thought Noise SOAL: Stop, Observe, Accept, and Let Go It Is
        What It Is Sitting With Whatever Comes Up In each module, mindfulness exercises
        were combined with brief psychoeducation and written instructions to apply the
        concept of mindfulness in daily life. Each module included 12 mindfulness
        exercises, each of which lasted 10 minutes, resulting in a total of 960 minutes
        (16 hours) of mindfulness exercises for the 8-week treatment period. Before each
        mindfulness exercise, participants were instructed to reflect on the purpose for
        the exercise. Participants were asked to complete one module each week and to
        conduct mindfulness exercises twice a day on 6 days of the week. Participants only
        gained access to the next module once they had completed the previous one.

            <hss>Online discussion forum</hss>

            Participants in the control group received access to a closed, anonymous, and
            supervised online discussion forum. Each week, a new topic was presented for
            discussion. All topics were related to anxiety or panic but were not
            therapeutic in nature. For example, topics included how participants perceived
            the health care provided for anxiety disorders, how they discussed anxiety
            problems with others, and how they perceived seasonal changes of mental health
            problems. These online dialogues were supervised but the investigators did not
            take active part in the discussions.

            <hss>Outcome measures</hss>

            Our primary outcome measure was the BAI, a 21-item self-report questionnaire
            that assesses the severity of somatic and cognitive anxiety symptoms. Items
            are scored on a 0–3 Likert scale and the total score ranges between 0–63
            points. In addition, as secondary outcome measures, we administered the BDI-
            II, the Quality of Life Inventory (QOLI; Frisch, Cornell, Villanueva, &
            Retzlaff, 1992), and the Insomnia Severity Index (ISI; Morin, 1993). The BDI-
            II measures depression on 21 items, with a total score ranging between 0 to 63
            points (0–3 Likert scale). The QOLI assesses the importance of (0–2 Likert
            scale) and satisfaction with (-3 to 3 Likert scale) 16 life domains on 32
            items (total score -6 to 6). The ISI is a brief questionnaire that assesses
            insomnia on 7 items (0–4 Likert scale; total score 0–28). All outcome measures
            were administered online, a procedure that has demonstrated adequate
            psychometric properties for all applied instruments (Hedman et al., 2010;
            Lindner, Andersson, Öst, Carlbring, 2013; Thorndike et al., 2009, 2011). In
            the current sample, reliability estimates at pre-assessment were as follows:
            BAI: α = 0.82, BDI-II: α = 0.82, QOLI: α = 0.79, and ISI: α = 0.86.

            <hss>Statistical analyses</hss>

            All analyses on change in primary and secondary outcome measures were
            conducted as intention-to-treat analyses using a mixed models approach.
            Analyses were carried out in R Version 2.15 (R Development Core Team, 2010),
            and mixed models were fitted with NLME (Jose, Douglas, Saikat, Deepayan, & R
            Development Core Team, 2012). In this approach, main and interaction effects
            are evaluated on the basis of their contribution to an increase of goodness of
            model fit (Field, Miles, & Field, 2012). The increase of fit is χ2
            -distributed. Within- and between-group effect sizes were calculated using
            Cohen’s formula based on pooled standard deviations (Cohen, 1988). Clinically
            significant change was calculated for the BAI for the completer sample
            according to the criteria suggested by Jacobson and Truax (1991). In order to
            facilitate comparison of the present findings with those of other studies, we
            adopted criteria for improvement and recovery from two previous trials
            (Vøllestad et al., 2011; Westbrook & Kirk, 2005). Reliable improvement or
            deterioration was defined as a pre-post change score of 10 points or more and
            recovery was defined as a post BAI score of 10 or less.

<h>RESULTS</h>
-------

A total of 91 participants met all inclusion criteria and were randomized to one of the
two groups (see flow chart in Figure 1). Seven participants (7.7%) did not complete the
outcome measures at posttreatment. Dropout rates did not differ between the two groups,
χ2(1) = 1.47, p = .267. Ten participants in the mindfulness group (11%) failed to fill out
self-report measures at 6-months follow-up-assessment. Table 1 displays sociodemographic
characteristics and Table 2 depicts pretreatment scores of the outcome measures for the
two groups. There were no significant group differences at pretreatment on any demographic
variable or outcome measure: all χ2(1-3) < 2.33, all p > .31; all t(89) < 1.31, all p >
.19. The computer automatically registered the amount of completed mindfulness exercises
for the MTG. Participants in the mindfulness group completed on average 44 (SD = 33.7) out
of 96 mindfulness exercises, which corresponds to an average of 7.3 hours of mindfulness
practice during the 8-week intervention period. These time specifications can only be
estimators of the real practice time. The program only recorded the amount of started
exercises. It remains unknown whether the mindfulness exercises were not only started but
also conducted for the full intended 10 minutes. In both groups, participants were asked
at post-assessment how satisfied they were with the received treatment. Answers ranged
from 1 (not at all satisfied) to 5 (very satisfied). Participants of the mindfulness group
were on average “satisfied” with the treatment (M = 3.7, SD = 1.0) whereas participants of
the online forum control group were only “somewhat satisfied” (M = 3.0, SD = 1.2). This
group difference in satisfaction was significant, t(80) = 2.88, p < .01.

<hs>  Change in primary and secondary outcomes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Means, standard deviations, and effect sizes for all four outcome measures in both groups
are displayed in Table 2. The mixed models analysis on the BAI revealed that participants
in the mindfulness group showed a larger decrease of anxiety from pre- to post-assessment
than participants of the control group (Group × Time: χ2[1] = 9.71, p = .002). Pre-post
effect sizes were large (d = 1.33) for the mindfulness group and moderate (d = 0.76) for
the control group. The between-group effect size at post-assessment indicated a large
group difference (d = 0.99). Results on the depression scale were similar. The mixed model
analysis using the BDI as dependent variable showed a significant Time × Group
interaction, χ2(1) = 15.60, p < .001. Participants of the active group indicated more
improvement on depression scores from pre- to post-assessment than participants of the
control group (between-group effect d = 0.84). Pre-post effect sizes were large (d = 1.58)
in the mindfulness group and small (d = 0.49) in the control group. The mindfulness group
also improved significantly more than the control group on the ISI. The mixed model
analysis revealed that participants of the active group showed a larger decrease in
insomnia from pre- to post-assessment than did participants of the control group (Time ×
Group: χ2[1] = 5.77, p = .016). Effect sizes indicated large improvements for the active
group (d = 0.82) and small improvements for the control group (d = 0.45), as well as a
small group difference at post-assessment (d = 0.36). The mixed model analysis on the QOLI
also revealed a significant interaction effect of Time × Group, χ2(1) = 6.68, p = .009.
Participants in the mindfulness group reported a moderate increase of life satisfaction (d
= 0.64), whereas participants of the control group showed no change (d = 0.04). Group
differences at post-assessment were small (d = 0.37).

        <hss>Differences Between Diagnostic Groups</hss>

        To examine whether the different diagnostic groups predicted or moderated primary
        treatment outcome, we entered diagnostic group as an additional independent
        variable in the mixed model on the BAI. Results indicated that although the
        different diagnostic groups showed different levels of anxiety across both
        assessment points and both treatment groups (main effect diagnostic group: χ2[3] =
        19.84, p < .001), the specific anxiety diagnosis did not predict change in anxiety
        (Diagnostic Group × Time: χ2[3] = 1.89, p = .596) nor did it moderate the
        treatment effect (Diagnostic Group × Time × Treatment Condition: χ2[6] = 6.83, p =
        .337). In other words, in both treatment conditions, participants with PD, GAD,
        SAD, and ADNOS showed similar rates of anxiety change.

        <hss>Psychotherapy Experience</hss>

        To investigate the impact of former psychotherapy experience on treatment outcome,
        we included experience with psychotherapy (yes/no) as an additional independent
        variable into the mixed model analysis on the BAI. Results showed that the
        experience with psychological treatment did not influence change in anxiety scores
        across both treatment groups (Psychotherapy Experience × Time: χ2[1] = 2.28, p =
        .131). Participants with former experiences with psychotherapy showed similar
        rates of improvement as participants without such experiences. Differences in
        previous psychotherapy experience also did not lead to differential change rates
        of anxiety symptoms in the two treatment conditions (Psychotherapy Experience ×
        Time × Treatment Condition: χ2[2] = 2.12, p = .345).

        <hss>Amount of Exercises</hss>

        We also examined whether the amount of completed mindfulness exercises predicted
        change in anxiety in the mindfulness treatment group (MTG). Amount of mindfulness
        exercises was entered as an independent variable into a mixed model within the MTG
        using the BAI at pre- and post-assessment as dependent variable. Results showed
        that the amount of exercises did not predict treatment outcome (Time × Exercises
        Completed: χ2[1] = 2.54, p = .111).

<hs>  Clinical significance of change</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 3 depicts the rates of clinical significant change on the primary outcome measure
BAI at post-assessment for the two groups (completer sample). Sixteen participants (40%)
of the mindfulness group met the criteria of improvement and recovery compared to 4
participants (9%) in the control group. This difference in response rates was significant,
χ2(1) = 11.04, p = .002.

<hs>  Maintenance of treatment effects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

At 6-month follow-up, the control group had received access to the mindfulness treatment
program, so analyses are based on the MTG only. Means and standard deviations at 6-month
follow-up are included in Table 2. Paired t-tests from pre- to follow-up assessment showed
that there was a significant decline in anxiety scores (BAI: t[34] = 8.54, p < .001, d =
1.44). Similarly, on secondary outcome measures, participants of the MTG showed a
significant reduction of symptoms of depression and insomnia (BDI-II: t[34] = 5.89, p <
.001, d = 1.00; ISI: t[34] = 4.77, p < .001, d = 0.82) and a significant improvement in
quality of life from pre- to follow-up assessment (t[34] = -3.12, p = .004, d = 0.53).
Differences between post and 6-month follow-up indicated stable treatment results for
three out of the four outcome measures. There were no significant post- to follow-up
differences for anxiety, t(34) = -0.95, p = .347, insomnia, t(34) = -1.97, p = .057, and
quality of life, t(34) = 1.67, p = .104. Results showed a significant increase of
depressive symptoms from post- to follow-up assessment, t(34) = -2.18, p = .036.

<h>DISCUSSION</h>
----------

The current trial aimed to evaluate the efficacy of an Internet-based mindfulness
treatment program for persons with anxiety disorders. Pre-post change scores as well as
the comparison to an active control condition indicated that participants of the
mindfulness program benefitted substantially from the treatment and experienced a
significant decrease of anxiety symptoms. Participants of this group also achieved
substantial reductions in symptoms of depression and insomnia, which are very common
comorbid conditions among individuals with anxiety disorders. Most improvements were
stable at 6-month follow-up with the exception of changes in depressive symptoms. Overall,
the present study supports previous results achieved in face-to-face settings on
mindfulness as an effective transdiagnostic treatment approach in heterogeneous anxiety
disorders (Arch et al., 2013; Vøllestad et al., 2011). In contrast to the present study,
Arch and colleagues treated more severely disturbed patients in a more clinically
representative setting and reported only moderate changes on self-report measures. The
selection and recruitment of participants in the study of Vøllestad et al. (2011), on the
other hand, was very similar to the current randomized controlled trial and effects on
primary and secondary measures, as well as clinical change rates, were comparable. Results
of the present study are also in line with findings of recent meta-analyses on
mindfulness-based treatments in anxiety disorders (Hofmann et al., 2010; Vøllestad et al.,
2012). Similar to the current results, Vøllestad and colleagues (2012) reported large
average reductions in depression and anxiety and moderate improvements in quality of life
through stand-alone and combined face-to-face mindfulness treatments. In conclusion,
mindfulness exercises delivered in face-to-face settings or remotely via the Internet seem
to yield similar changes in symptoms. The remote delivery does not seem to lessen the
efficacy of mindfulness interventions. This is surprising as some differences in the
setting are prone to affect common mechanisms of change. The most salient difference
constitutes the lack of contact to a clinician and to other patients in the Internet
setting. As Baer, Carmody, and Hunsinger (2012) point out, the contact with a warm and
empathetic group leader as well as the sharing with fellow participants very likely
stimulate therapeutic changes in face-to-face mindfulness programs, above and beyond the
effects elicited by more specific mechanisms of change. Accordingly, Malpass and
colleagues (2011), who describe the therapeutic process in mindfulness treatments from the
participants’ point of view, highlight the perceived importance of the group as a
therapeutic factor. The proposed specific therapeutic factor in mindfulness-based
interventions is an increase of mindfulness. An increase of mindfulness has repeatedly
been associated with the reduction of symptoms (e.g., Bränström, Kvillemo, Brandberg, &
Moskowitz, 2010; Carmody & Baer, 2008; Vøllestad et al., 2011). Baer and colleagues
demonstrated that an increase in facets of mindfulness, such as observing, nonreactivity,
acting with awareness, and nonjudging, preceded and mediated changes in stress in an MBSR
program. While the beneficial effect of an increase of mindfulness very likely also
applies to Internet-based mindfulness treatments, the effects of more common mechanisms of
change, such as the therapeutic relationship or group therapeutic factors, do not apply to
an Internet-based intervention. In the present study, participants practiced mindfulness
without any contact or support from clinicians or fellow participants. This also applies
to two previous Internet-based mindfulness studies in nonclinical samples (Glück &
Maercker, 2011; Krusche et al., 2012). In effect, the good outcomes of unguided Internet-
based mindfulness studies at least partly question the necessity of interpersonal common
factors in mindfulness treatments. A second important difference between the current
Internet trial and previous trials constitutes the intensity of treatments. The applied
Internet-based program was restricted to 20 minutes of daily mindfulness exercise. The
MBSR treatment program encompasses 30 hours of group treatment paired with instructions to
train in mindfulness daily for 45 to 60 minutes (Kabat-Zinn, 1990). Similarly, in
mindfulness-based cognitive therapy (Segal, Williams, & Teasdale, 2012), patients spend 24
hours in group treatment and train an additional 45 to 60 minutes per day at home.
Unfortunately, most clinical trials on mindfulness-based interventions failed to document
to which extent patients actually adhered to these extensive homework assignments. As an
exception, Vøllestad et al. (2011) reported that their participants practiced mindfulness
for, on average, 34 minutes a day. This constitutes a vast difference to the 7 minutes of
mindfulness practice per day found in the current trial. As both treatment protocols
yielded comparable outcomes in similar patient populations, these findings suggest that
treatment intensity does not crucially affect treatment outcome in mindfulness-based
interventions. Indeed, reviews on mindfulness interventions found no or equivocal results
on the relationship between number of treatment sessions/amount of homework exercise and
treatment outcome (Toneatto & Nguyen, 2007; Vettese, Toneatto, Stea, Nguyen, & Wang, 2009;
Vøllestad et al., 2012). In the present trial, the association between completed
mindfulness exercises and change in anxiety was weak (r = .26, p = .114). Also, the good
results of the present study were paired with a rather low adherence. Participants
completed on average only half of the treatment protocol. There is yet no empirical data
on the necessary and sufficient amount of mindfulness practice. Future studies should
investigate dose-response relations in Internet as well as in face-to-face mindfulness-
based interventions. Previous research on transdiagnostic Internet-based treatments for
anxiety disorders found that tailored or unified cognitive-behavioral programs can be
effective in the reduction of anxiety symptoms (Berger et al., 2013; Carlbring et al.,
2011; Johnston et al., 2011). The reported between- and within-group effect sizes of the
current trial are comparable to those achieved through these CBT trials. Also, the
attrition rate of 8% in the current trial ranges well within the proportions reported in
online CBT trials (4%–10%; Berger et al., 2013; Carlbring et al., 2011; Johnston et al.,
2011). When comparing ratings of satisfaction with the received treatments, participants
in the current mindfulness trial seem a bit less satisfied (average of 4 on a 1–5 scale)
than participants in the two previous transdiagnostic CBT trials that reported
satisfaction ratings (average of 3–4 on a 1–4 scale; Berger et al., 2013; Johnston et al.,
2011). Overall, the Internet-based mindfulness treatment of anxiety disorders seems
equally effective and acceptable as Internet-based CBT approaches. Although totally
different in content, the applied Web-based mindfulness program and online CBT programs
share some common features that have been found to be associated with good therapeutic
outcome. For example, participants in both types of Internet treatments underwent the same
extensive diagnostic process that has been found to promote adherence and therapeutic
change (Barak, Hen, Boniel-Nissim, & Shapira, 2008; Boettcher, Berger, & Renneberg, 2012).
Furthermore, participants in both Internet treatments completed their therapy within a
clear deadline, an additional characteristic of Internet-based treatments that has been
found to be associated with good outcome (Nordin, Carlbring, Cuijpers, & Andersson, 2010).
These shared features and the comparable good results suggest that some characteristics of
the Internet setting per se contribute to therapeutic change, possibly by the stimulation
of positive outcome expectations (Boettcher, Renneberg, & Berger, 2013).

<hs>  Limitations and future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The current trial is, to our knowledge, the first to evaluate an Internet-based
mindfulness treatment program for anxiety disorders. As such, it concentrated on the
examination of efficacy. Nonetheless, the lack of information regarding the proposed
mechanism of change in mindfulness treatments, the increase of mindfulness, is the central
limitation of the present study. Future Internet-based studies should assess likely common
and specific agents of change on a regular basis and relate these to changes in different
outcome domains. A second limitation of the present design constitutes the lack of a
diagnostic interview at post-assessment. Even though rates of clinical change are an
indicator of how many participants benefitted from the treatment, a clinician-rated
reevaluation of diagnostic status would have been helpful to estimate the effects of this
treatment on remission and comorbidity (Johnston et al., 2013). To this end, the
administration of disorder-specific self-report questionnaires also would have been
helpful. The restriction to use the BAI as primary outcome measure makes it harder to
compare the current trial to disorder-specific studies. Furthermore, as the BAI mainly
focuses on the assessment of somatic anxiety symptoms, it may not adequately reflect
changes in cognitive symptoms of anxiety, such as worrying in GAD (Leyfer, Ruberg, &
Woodruff-Borden, 2006). A further limitation of the present study lies in the assessment
of treatment adherence. We only assessed how many exercises were initiated and were unable
to verify whether and for how long these exercises were performed. Clearly, the present
study needs replications and can only be considered as a first step towards the
establishment of online mindfulness programs in the treatment of anxiety disorder. In
order to estimate the comparative efficacy of mindfulness online treatments, future
studies should apply more carefully controlled comparison groups. One limitation of the
current trial is the failure to assess the engagement of the participants in the online
discussion forum control group. We do not know how much time the participants spent in the
forum and how actively they participated in the discussions. Moreover, participants of the
control group were informed beforehand that they would receive the mindfulness treatment
after post-assessment, perhaps inadvertently producing a wait-list quality to the control
group as some participants may have ignored the offer of the online discussion group and
waited for the active treatment. This makes it hard to interpret the between-group effect
sizes. Nevertheless, the results of the current trial suggest that an unguided mindfulness
program can be as effective as established Internet-based CBT programs. Mindfulness-based
treatments could form an alternative to existing online programs. They could offer a valid
choice for persons seeking treatment for anxiety disorders in general and for patients who
do not respond to CBT in particular. Mindfulness and CBT treatments differ substantially
in the demands they pose on participants. Both treatment approaches are participatory and
ask the patient to engage actively in the therapeutic process. However, whereas
mindfulness treatments request the patient to follow repeated meditation instructions, CBT
protocols ask the patient to actively engage in varying exercises (e.g., dysfunctional
thoughts protocol, behavioral experiments). In direct comparisons of mindfulness and CBT
treatments, future studies should investigate patient characteristics and preferences that
are potentially associated with differential treatment outcome. In accordance with face-
to-face multicomponent mindfulness interventions, mindfulness exercises could also
complement cognitive-behavioral treatment protocols. Future studies should seek to explore
reasonable ways to combine both treatment approaches in the Internet-based setting and
empirically evaluate the potential benefits of combined treatments.

<h>SOURCES OF FUNDING</h>
------------------

This study was made possible in part by a generous grant from the Swedish Council for
Working Life and Social Research (FAS 2008-1145). The funding body was not involved in the
study design, in the collection, analysis and interpretation of data, in the writing of
the report, or in the decision to submit the article for publication.

<h>CONFLICT OF INTEREST STATEMENT</h>
------------------------------

Five of the six authors have no competing interests to report. Dr. Ola Schenström has
founded a company that, among other things, markets online mindfulness products.


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<ART>Investigating the efficacy of neurofeedback training for expediting expertise and excellence in sport
================================================================================

Authors: Christopher Ring, Andrew Cooke, Maria Kavussanu, David McIntyre, Rich Masters
DOI: 10.1016/j.psychsport.2014.08.005
Year: 2015  |  Pages: 118-127
ASJC codes: 3202
Keywords: EEG alpha power, Expertise, Golf, Motor performance, Neurofeedback, Performance under pressure

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: This experiment examined whether electroencephalographic (EEG)-based neurofeedback could be used to train recreational golfers to regulate their brain activity, expedite skill acquisition, and promote robust performance under pressure. Design: We adopted a mixed-multifactorial design, with group (neurofeedback, control) as a between-subjects factor, and pressure (low, high), session (pre-test, acquisition 1, acquisition 2, acquisition 3, post-test), block (putts within each training session), and epoch (cortical activity in the seconds around movement initiation) as within-subject factors. Methods: Recreational golfers received three hours of either true (to reduce frontal EEG high-alpha power, N=12) or false (control, N=12) neurofeedback training sandwiched between pre-test and post-test sessions during which we collected measures of cortical activity (EEG) and putting performance under both low and high pressure conditions. Results: Individuals in the neurofeedback group learned to reduce their frontal high-alpha power before striking putts. Despite causing this more "expert-like" pattern of cortical activity, neurofeedback training failed to selectively enhance performance, as both groups improved their putting performance similarly from the pre-test to the post-test. Finally, both groups performed robustly under pressure. Conclusions: Performers can learn to regulate their brain activity using neurofeedback training. However, research identifying the cortical correlates of expertise is required to refine neurofeedback interventions if this training method is to expedite learning. Suggestions for future neurofeedback interventions are discussed.

--------------------------------------------------------------------------------


<h>NEUROFEEDBACK TRAINING IN SPORT</h>
-------------------------------

Neurofeedback training provides individuals with real-time information about their level
of cortical activity via sounds or visual displays (Hammond, 2007). Based on principles
derived from operant learning theory (e.g., Skinner, 1963), rewarding positive
reinforcement, such as a change in the pitch of a tone, is provided when a desired level
of cortical activity is achieved. Electroencephalography (EEG) is perhaps the most common
brain imaging method that is used to provide neurofeedback training (e.g., Vernon, 2005).
In brief, EEG involves the recording of electrical activity on the scalp to detect
voltages generated in the brain. EEG offers exquisite temporal resolution, whereby changes
in activation are detected more or less instantaneously (e.g., Harmon-Jones & Peterson,
2009). Moreover, EEG can be measured while participants stand and perform a range of
movements, which makes the method particularly well suited for providing neurofeedback in
sport (e.g., Thompson, Steffert, Ros, Leach, & Gruzelier, 2008). To this end, there have
been a handful of studies investigating whether EEG neurofeedback training can facilitate
performance in sport, and while the evidence concerning the effectiveness of EEG
neurofeedback is not conclusive, it is certainly encouraging (e.g., Arns, Kleinnijenhuis,
Fallahpour, & Breteler, 2007; Kavussanu, Crews, & Gill, 1998; Landers et al., 1991;
Rostami, Sadeghi, Karami, Abadi, & Salamati, 2012). For instance, the seminal study of
neurofeedback in sport was conducted by Landers et al. (1991), and investigated the
effects of neurofeedback in sixteen experienced archers. Landers et al. (1991) reasoned
that archery performance should be associated with activation of the right-hemisphere of
the brain, which is associated with visual-spatial processing, and deactivation of the
left-hemisphere of the brain, which is associated with verbal-analytic processing (e.g.,
Hatfield, Landers, & Ray, 1984; Landers et al., 1994). Accordingly, they measured EEG
activity and archery performance in pre- and post-test sessions, separated by
approximately 60 min of neurofeedback training during which the archers watched their
relative left- and right-hemisphere activity on a visual display. Results revealed that
performance improved from the pre-test to the post-test in eight archers who were rewarded
when they reduced cortical activity over their left-hemisphere. In contrast, performance
deteriorated in the remaining eight archers, who were rewarded when they reduced cortical
activity over their right-hemisphere. Although this finding implies that neurofeedback
training could be used to expedite learning in archery, it is important to note that left-
hemisphere cortical activity in the pre- and post-test sessions was the same for members
of both neurofeedback groups. This indicates that the neurofeedback training protocol did
not cause members of the left-hemisphere neurofeedback group to suppress left-hemisphere
function. Consequently, the improvement in performance that was achieved by this group may
not be directly attributable to the neurofeedback that they received. A more recent study
of neurofeedback training by Rostami et al. (2012) also adopted a pre- and post-test
design to increase the power of the sensory motor rhythm (i.e., cortical activity between
13 and 15 Hz) over central motor areas (i.e., C3 electrode site) of the brain.
Specifically, twelve experienced marksmen attended 15 h of laboratory sessions spread over
five weeks, and were trained to control their cortical activity by sitting and watching
this activity on a screen. Results revealed that neurofeedback training led to marginal
improvements in shooting accuracy from the pre-test to the post-test, whereas the
performance of a control group who received no neurofeedback training was unchanged. While
this finding is also supportive of neurofeedback as a tool to aid the development of
expertise and excellence in sport, the study was subject to two principal limitations.
First, the choice to train participants to increase the sensory motor rhythm over central
motor areas was somewhat arbitrary, with the authors providing no theoretical or empirical
rationale to support this key methodological feature. Second, no measures of EEG activity
were obtained during the pre- and post-test sessions. Accordingly, it was impossible to
evaluate whether the beneficial effects of neurofeedback training were attributable to
participants having learned to control their patterns of cortical activation. Finally,
perhaps the most informative neurofeedback study in sport was conducted by Arns et al.
(2007). They adopted a crossover design in which six amateur golfers completed 12 blocks
of putts. The golfers putted as normal in the odd-numbered blocks, and putted while
receiving auditory neurofeedback training in the even-numbered blocks. Importantly, the
element of cortical activity that was fed back to participants was partly customised to
the task. Specifically, a comparison of cortical activity associated with the best (i.e.,
holed) and worst (i.e., missed) putts during a baseline session was conducted to customise
the neurofeedback for each participant. This resulted in participants being trained to
reduce a combination of theta (4–8 Hz), alpha (8–12 Hz), sensory motor rhythm (13–15 Hz)
and/or beta (15–30 Hz) power in the final moments preceding putts. It is also important to
note that the auditory neurofeedback tone was played to participants while they stood over
the ball and prepared to execute putts. By adopting these innovative design features, Arns
et al. (2007) were the first researchers to provide customised, concurrent neurofeedback
training during task performance. Their results revealed that participants holed more
putts during the blocks in which they received neurofeedback compared to those in which
they did not. Although this study provides arguably the strongest support for the efficacy
of neurofeedback training as a tool to foster expertise and excellence in sport, it
nonetheless suffers from key limitations, including low sample size and no control group.
Thus, the results of the Arns et al. (2007) study may simply reflect a placebo effect
whereby improved performance was elicited by the presence of the neurofeedback system and
auditory tone, rather than by changes in cortical activity per se.

<h>THE CORTICAL CORRELATES OF EXPERTISE IN GOLF</h>
--------------------------------------------

Since the work of Arns et al. (2007), two studies have systematically examined the
patterns of cortical activity that underpin successful golf putts, and the results of
these studies could form the empirical grounding for new neurofeedback interventions.
Specifically, Babiloni et al. (2008) compared patterns of EEG activity characterising
holed putts and missed putts in a sample of expert golfers. They found a widespread
reduction in EEG alpha power during the four seconds preceding putts. This is consistent
with the well-established finding that voluntary self-paced movements are preceded by a
reduction (i.e., desynchronisation) in EEG alpha power (around 8–12 Hz) in both
hemispheres of the brain during bimanual tasks (e.g., Leocani, Toro, Manganotti, Zhuang, &
Hallett, 1997; Pfurtscheller & Aranibar, 1979). Crucially, Babiloni et al. (2008) also
found that compared to missed putts, holed putts were characterised by a greater reduction
in high-alpha power (10–12 Hz) at sites overlying the premotor and motor cortex (e.g., Fz,
Cz, C4), indicating that these sites and the high-alpha frequency band are ideal
candidates to be targeted by neurofeedback interventions. Second, the study by Babiloni et
al. (2008) was recently replicated and extended by Cooke et al. (2014). Specifically,
Cooke et al. (2014) compared cortical activity preceding holed versus missed putts, in
both experts and novices. The results showed that expert golfers displayed a greater
reduction in high-alpha power than novices, and that holed putts were characterised by
less high-alpha power than missed putts, at frontal and central sites (e.g., Fz, F3, F4,
Cz) in the two seconds preceding movement. In sum, the results of Babiloni et al. (2008)
and Cooke et al. (2014) provide consistent evidence that expertise and optimal golf
putting performance is characterised by a suppression of EEG high-alpha power in the final
moments preceding movement initiation.

<h>THE PRESENT STUDY</h>
-----------------

To address the limitations of previous studies, the present experiment was designed to be
the largest neurofeedback investigation to date, while also being the first to employ
concurrent, empirically grounded neurofeedback along with an active control group. Our
empirically guided neurofeedback was based on the results of Babiloni et al. (2008), and
Cooke et al. (2014), and aimed to teach participants to reduce their frontal high-alpha
power before striking putts. Importantly, we also investigated the effects of
neurofeedback training on performance under pressure. Previous research has demonstrated
that increases in psychological pressure can disrupt patterns of physiological activity
during motor preparation and cause impaired performance (e.g., Cooke, Kavussanu, McIntyre,
& Ring, 2010; Weinberg & Hunt, 1976). Consequently, our experiment is the first to examine
whether neurofeedback training can help performers produce consistent physiological
responses which could ensure robust performances across both low and high-pressure
conditions. We hypothesised a series of interactions in which the neurofeedback group
would display greater reductions in pre-movement high-alpha power, and greater
improvements in performance, from a pre-intervention test to a post-intervention test,
when compared to a control group. We also expected individuals in the neurofeedback group
to produce consistent patterns of cortical activity and robust performances across both
low- and high-pressure conditions during the post-intervention test.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Twenty-four right-handed male golfers volunteered to participate in the experiment, and
were randomly assigned to a neurofeedback training group (N = 12, M age = 23.00, SD = 5.83
years, M golf handicap = 23.00, SD = 6.62) or a control group (N = 12, M age = 21.00, SD =
2.52 years, M golf handicap = 23.33, SD = 4.62). All participants provided informed
consent before taking part.

<hs>  Task</hs>
  ~~~~

Participants used a standard length (90 cm) blade style golf putter (Titleist Scotty
Cameron Circa 62) to putt regular-size golf balls (diameter 4.7 cm) towards a standard-
size hole (diameter 10.8 cm) from a distance of 2.4 m. The hole was located 1.25 m from
the end and 0.75 m from the sides of a flat artificial putting surface (Turftiles), which
had a stimpmeter reading of 3.05 m (i.e., a medium-to-fast paced green).

<hs>  Design</hs>
  ~~~~~~

We adopted a mixed-multifactorial design. Participants attended a pre-test and a post-test
(hereafter referred to as the test phase of the experiment), which included both low- and
high-pressure conditions. They also attended three training sessions following the pre-
test and preceding the post-test (hereafter referred to as the acquisition phase of the
experiment); each session consisted of twelve 5-min blocks of putts. Our design therefore
included group (neurofeedback, control) as a between-subject factor, as well as pressure
(low, high), session (pre-test, acquisition 1, acquisition 2, acquisition 3, post-test),
block (referring to each 5-min block of putts within the training sessions), and epoch as
within-subject factors. Epoch refers to the time-windows around movement in which cortical
activity was assessed (i.e., −4 to −3 s, −3 to −2 s, −2 to −1 s, −1 s to 0 s, 0 s to +1
s). The inclusion of this factor was in keeping with previous studies (e.g., Babiloni et
al., 2008; Cooke et al., 2014). Further details are provided in the data reduction and
statistical analyses sections below.

<hs>  Neurofeedback training protocol</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

During the acquisition phase of the experiment, participants in the neurofeedback group
received three 1-h sessions of neurofeedback training. Cortical activity was recorded from
the Fz site on the scalp using an active electrode connected a DC amplifier (Brainquiry
PET-4), with reference and ground electrodes attached to the right and left mastoids,
respectively. We decided to provide feedback at the Fz site because this site has been
shown to capture the strongest differences in high-alpha power between experts and novices
and successful and unsuccessful outcomes in the moments preceding golf putts (Cooke et
al., 2014). In tandem with cortical recordings, a computer running Bioexplorer software
(Cyberevolution) extracted high-alpha power from the EEG signal, and fed this back to
participants in the form of an auditory tone. Importantly, the tone was programmed to vary
in pitch based on the level of high-alpha power. Moreover, the tone was set to turn off
completely (i.e., be silenced) when the following criteria were met: a) high-alpha power
was reduced (relative to each participant's individual baseline) by 26.8%, 53.6%, and
80.4% in the first, second, and third training sessions, respectively; b) theta power was
reduced (relative to each participant's individual baseline) by 18.2%, 36.4%, and 54.6%,
in the first, second, and third training sessions, respectively; c) impedance was low, as
reflected by <10 μV of 50 Hz activity in the signal (Arns et al., 2007); d) eye-blinks
were absent, as detected by an active electrode that was placed over the orbicularis oculi
muscle of the right eye. Participants were required to reduce theta power alongside high-
alpha power because theta power at the Fz site has been revealed as an additional marker
of expertise in the moments preceding golf putts (Cooke et al., 2014). The high-alpha and
theta power threshold values initially were based on the performance of experts (Cooke et
al., 2014) but subsequently were refined in pilot testing. They were designed to encourage
gradual development of participants' ability to reduce high-alpha power, with the
thresholds in the final training session roughly corresponding to the reductions in power
that characterised the successful putts of experts in previous studies (i.e., Babiloni et
al., 2008; Cooke et al., 2014). In line with the study by Arns et al. (2007), the
neurofeedback tone was turned off completely for 1.5 s once the neurofeedback thresholds
had been reached, except for when high-impedance or an eye-blink was detected within this
dwell-period, in which case the tone re-started immediately. Auditory neurofeedback was
provided to participants in twelve 5-min blocks per training session while participants
practiced putting (i.e., concurrent). Specifically, participants were instructed to
execute putts when they felt ready, but only when the tone was turned off (i.e.,
indicating that high-alpha power had been reduced). Participants in the control group
followed an identical procedure to those in the neurofeedback group, except the tone that
they heard was not based on their brain activity. Instead, participants in this group were
played a recording of the tone from a matched (i.e., yoked) participant in the
neurofeedback group. This feature ensured that the tone was turned off on the same number
of occasions and for the same duration in both groups, and guaranteed that a similar
number of putts were completed by both groups of participants during the acquisition phase
of the experiment.

<hs>  Pressure manipulation</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Two pressure conditions (each consisting of 50 putts) were manipulated in the test phase
of the experiment using social evaluation, competition, and rewards (Baumeister & Showers,
1986), with the order of the conditions counterbalanced across participants. The two
conditions are described below.

        <hss>Low-pressure condition</hss>

        This condition was non-competitive, contained no rewards, and was designed to
        minimise any pressure that may have been elicited by social evaluation.
        Specifically, participants were informed that performance would be assessed by the
        average distance of putts from the hole, with holed putts counting 0 cm in the
        calculation. Crucially, participants were also told that although the accuracy of
        each putt would be recorded, their individual performance would not be analysed.
        Instead, it was explained that the performance of all participants would be pooled
        to generate one accuracy score for the sample as a whole.

        <hss>High-pressure condition</hss>

        The high-pressure condition was set up as a competition that offered rewards, and
        placed an explicit emphasis on social evaluation. Specifically, participants were
        informed that they would be individually evaluated in this block of putts. To this
        end, they were told that all participants would be ranked on a leaderboard based
        on their average distance from the hole in this condition. Moreover, they were
        informed that the leaderboard would be emailed to all participants at the end of
        the study, and that cash prizes of £50, £25, £10 and £5 would be awarded to the
        top four performers (e.g., Wilson, Smith & Holmes, 2007). Finally, they were told
        that twenty-four participants were to be recruited for the study, allowing each
        individual to evaluate their chances of winning a prize (e.g., Cooke et al.,
        2010).

        <hss>Number of putts struck</hss>

        We recorded the number of putts struck during each block in the acquisition phase
        of the experiment. The purpose of this measure was twofold. First, it allowed us
        to identify and control for possible group differences in the number of putts
        (i.e., practice) during skill acquisition. Second, we were able to indirectly
        assess the extent to which participants in the neurofeedback group learned to
        produce the desired high-alpha power profile, with better control of cortical
        activity being indicated by more putts being struck per 5-min block.

        <hss>Performance</hss>

        Mean radial error (i.e., the mean distance of the balls from the hole) was
        recorded as our measure of performance (Cooke et al., 2010; Cooke, Kavussanu,
        McIntyre, Boardley, & Ring, 2011). Zero was used in the calculation of mean radial
        error on trials where the putt was holed (Hancock, Butler, & Fischman, 1995). Mean
        radial error scores were obtained by taking a photograph of the final position of
        each putt using a digital camera (Sony Handycam) suspended above the hole.
        Photographs were then analysed offline using custom developed “ScorePutting”
        software (see Neumann & Thomas, 2008).

        <hss>Pressure manipulation check</hss>

        The 5-item pressure/tension subscale of the Intrinsic Motivation Inventory (Ryan,
        1982) was used to test the effectiveness of our pressure manipulation. Items,
        including “I felt pressured”, were rated on a 7-point Likert scale, with labels of
        1 (not at all true), 4 (somewhat true), and 7 (very true). The item responses were
        averaged to provide one score for the subscale. Cooke et al. (2011) reported
        reliability coefficients ranging from .66 to .90 for this subscale. In this
        experiment, alpha coefficients in the low and high-pressure conditions during the
        pre-test and post-test sessions ranged from .66 to .85, demonstrating acceptable
        internal consistency.

        <hss>Cortical activity</hss>

        We recorded EEG activity during the test phase of the experiment from an array of
        16 silver/silver chloride pin electrodes on the scalp (Fp1, Fp2, F4, Fz, F3, T7,
        C3, Cz, C4, T8, P4, Pz, P3, O1, Oz, O2) positioned in accordance with the 10-20
        system (Jasper, 1958). The BioSemi EEG system replaces the conventional “ground”
        electrode with two separate electrodes placed on either side of the vertex: a
        common mode sense active electrode and a driven right leg passive electrode; the
        “reference” at the time of recording lies somewhere between these two electrodes.
        These electrodes form a feedback loop which serves to reduce common mode voltage
        and thereby increase the signal-to-noise ratio above what would be achieved by
        systems using conventional ground electrodes with the same impedance (e.g.,
        Metting van Rijn, Peper, & Grimbergen, 1990; see also Biosemi website:
        http://www.biosemi.com/faq/cms&drl.htm). Electrodes were also placed at the left
        and right mastoids, to permit offline referencing. All signals were amplified and
        digitized at 512 Hz with 24-bit resolution (Biosemi ActiveTwo) using ActiView
        software (Biosemi). Conductive gel (ECI Electro-gel) was applied to all recording
        electrodes, and all sites were abraded using a blunt needle (for sites on the
        scalp) and a combination of abrasive paste (Nuprep) and alcohol wipes (Mediswab)
        (for the mastoids) prior to electrodes being attached.

        <hss>Performance</hss>

        Mean radial error was used as our measure of performance, as described above.

<hs>  Procedure</hs>
  ~~~~~~~~~

The protocol was approved by the local research ethics committee. Participants attended
five 2-h testing sessions (i.e., pre-test, acquisition 1, acquisition 2, acquisition 3,
post-test) on separate days (to prevent any confounding effects of fatigue), with each
session being an average of 2.3 (SD = 2.7) days apart. In the pre-test session,
participants were briefed, instrumented to allow the recording of cortical activity and
provided with instructions about the golf-putting task. Specifically, they were asked to
try to get all putts “ideally in the hole, but if unsuccessful, to make them finish as
close to the hole as possible.” Next, they performed 20 familiarization putts to become
accustomed to the putting surface and to putting while instrumented for EEG recordings.
After the familiarization block, participants performed two blocks of 50 putts, which
represented the low- and high-pressure conditions. Each block was preceded by its
respective pressure manipulation as described above. After each putt, a photograph was
taken to record the terminal location of the ball, and then the ball was replaced at the
start position by the experimenter. This ensured that participants did not need to move
between trials, thereby keeping movement artefacts to a minimum, while also regulating the
time between putts, which approximately ranged from 15 to 30 s. The manipulation check
(i.e., pressure/tension subscale of Intrinsic Motivation Inventory, as described above)
was administered immediately after the final putt in each of the pressure conditions,
while cortical activity was recorded continuously during each block. On completion of the
pre-test, participants were thanked and reminded of the time and date of their acquisition
sessions. In the acquisition phase of the experiment, participants were welcomed to the
laboratory and instrumented with the neurofeedback system. During the first acquisition
session, they were asked to address and fixate on a golf ball for five seconds. This
procedure was repeated five times in order to calculate their average baseline high-alpha
power. Customized computer scripts were then prepared for each participant in the
neurofeedback group in order to set the neurofeedback tone to silence when high-alpha
power was reduced from their individual baseline by 26.8%, 53.6%, and 80.4%, in
acquisition sessions one, two, and three, respectively. Participants were then issued with
the following instructions: “The computer will play a tone that is linked to your brain
activity. When you reach a prescribed level of brain activity, the tone will turn off. We
would like you to produce this level of brain activity before you putt, so we want you to
address the ball and get ready to putt, and then wait for the tone to turn off before
executing your stroke. You will receive 1-h of neurofeedback training today in the form of
12 blocks of the tone being played for 5-min at a time. During each 5-min block, you will
putt as many balls as is permitted in the time, which will depend on the number of times
that you manage to turn the tone off. It does not matter how many balls you putt.”
Participants then completed the twelve 5-min blocks of putts, interspersed with 2-min
breaks between each block. After each putt a photograph was taken to record the terminal
location of the ball (e.g., Neumann & Thomas, 2008). In acquisition sessions two and
three, participants were instrumented, reminded of their instructions, and immediately
began the 12 blocks of putts (i.e., the baseline high-alpha measure only occurred during
acquisition session 1). At the end of each session participants were thanked and reminded
of the time and date of their next visit. We decided to fix the amount of exposure to the
tone (rather than fix the number of putts) because we wished to standardize the amount of
experience with the feedback stimulus. By standardizing exposure our neurofeedback
training protocol was consistent with other recent neurofeedback studies (e.g., Rostami et
al., 2012). After completing the acquisition phase of the experiment, participants
attended the post-test session, which was identical to the pre-test. On completion of the
post-test, participants were thanked and debriefed. Upon completion of the study,
leaderboards were emailed to participants and competition winners were contacted and paid
their prize money.

<hs>  Data reduction</hs>
  ~~~~~~~~~~~~~~

Individual trials within the continuous cortical recordings were identified using an
optical sensor (Datasensor S51-PA 2-C10PK), which detected the initiation of putts, and a
microphone (Rode NT1) connected to a mixing desk (Studiomaster Club 2000), which detected
the putter-to-ball contacts. These signals were recorded using both Actiview (Biosemi) and
Spike2 (Cambridge Electronic Design) software. Processing of EEG data recorded during the
test phase of the experiment was conducted with EEGLab software (Delorme & Makeig, 2004)
using the following procedure: First, datafiles were resampled (256 Hz), filtered (1–50
Hz) and referenced to the average mastoid. Next, a neutral EEG baseline was identified
(cf., Babiloni et al., 2008). Specifically, we performed a fast Fourier transform (1 Hz
bins, Hanning window taper) spanning 7 s before until 1 s after initiation of each putt.
We then performed exploratory analyses to identify a period within this 8 s window during
which cortical activity was similar across both between (i.e., group) and within-subjects
factors (i.e., session and pressure). Specifically, potential baselines were initially
identified by eye and then subjected to a series of 2 Group × 2 Session × 2 Pressure
ANOVAs to verify the absence of main or interaction effects which, if present in the
baseline, would confound our interpretation of subsequent results. ANOVAs confirmed no
main or interaction effects for high-alpha power in the period from 0 ms to 200 ms around
movement, so we selected this window as a neutral baseline, before proceeding with the
remaining data processing steps as follows: First, we created new epochs spanning 5 s
before until 1 s after each putt (e.g., Babiloni et al., 2008), and performed baseline
removal (i.e., subtracted power during the baseline period from power in the other
epochs). Next, we screened the data to reject any artefacts. Gross artefacts were removed
by rejecting any large deviations in the signal (>100 μV) from the baseline level. This
important pre-processing step (see Onton, Westerfield, Townsend, & Makeig, 2006) was
followed by independent component analyses, which, in combination with the ADJUST
algorithm (Mognon, Jovicich, Bruzzone, & Buiatti, 2011), were used to identify and remove
remaining artefacts including eye blinks, eye movements, and the blood pressure pulse.
Next, we performed a fast Fourier transform (1 Hz bins, Hanning window taper) on the
artefact-free epochs, and averaged the data in successive 1 s epochs from 4 s before
(i.e., preparatory period) until 1 s after (i.e., movement period) the initiation of
putts. Finally, we computed power in the high-alpha (10–12 Hz) frequency band. For brevity
of reporting, only the results from the key Fz electrode, and those in its immediate
surroundings (i.e., F3, F4, Cz) are presented. We selected these electrodes because they
roughly overlie the primary motor cortex, the premotor cortex, and the supplementary motor
areas that are related to movement control (e.g., Ashe, Lungu, Basford, & Lu, 2006), and
which have been implicated in previous EEG-based golf-putting research (Babiloni et al.,
2008). Moreover, these electrode sites captured the strongest effects, and were largely
representative of the other sites.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Performance and number of putts struck in the acquisition phase of the experiment were
subjected to 2 Group × 3 Session × 12 Block Analyses of Variance (ANOVAs). Measures of
cortical activity during the test phase were subjected to 2 Group × 2 Session × 2 Pressure
× 5 Epoch (i.e., −4 to −3 s, −3 to −2 s, −2 to −1 s, −1 s to 0 s, 0 s to +1 s) ANOVAs.
Finally, the pressure manipulation check and performance recorded during the test phase
were subjected to 2 Group × 2 Session × 2 Pressure ANOVAs. These analyses were designed to
assess the three aims of our experiment as explained in the results section. Significant
effects were probed by polynomial trend analyses and planned post hoc comparisons. The
results of univariate tests are reported, with the Huynh-Feldt correction procedure
applied to analyses, which violated the sphericity of variance assumption. Partial eta-
squared is reported as a measure of effect size, with values of .02, .12, and .26
indicating relatively small, medium, and large effect sizes, respectively (Cohen, 1992).

<hs>  Acquisition phase</hs>
  ~~~~~~~~~~~~~~~~~

Analyses of the measures obtained in the acquisition phase of the experiment allowed us to
indirectly assess whether neurofeedback taught participants to produce expert like
cortical activity (i.e., number of putts struck) and promoted expedited learning.

<hs>  Test phase</hs>
  ~~~~~~~~~~

Analyses of the measures obtained in the test phase of the experiment allowed us to
directly assess whether neurofeedback taught participants to produce expert like cortical
activity and promoted expedited learning. They also allowed us to assess whether
neurofeedback encouraged consistent patterns of cortical activity and robust performance
across both low and high levels of pressure.

<h>DISCUSSION</h>
----------

Neurofeedback training offers the exciting possibility of expedited motor skill
acquisition, and, thus, more efficient development of excellence and expertise in sport
(Gruzelier, Egner, & Vernon, 2006). This experiment is one of the first to empirically
investigate the effectiveness of neurofeedback training as a tool to accelerate learning
in sport. Our aims were to: a) examine whether neurofeedback training could teach
recreational golfers to produce the patterns of brain activity that are exhibited by
experts in the moments preceding successful putts; b) evaluate whether neurofeedback
training could improve performance and thereby accelerate the novice to expert evolution;
and c) examine whether neurofeedback training could help produce patterns of cortical
activity and performance levels that would be robust to the potential deleterious effects
of increased psychological pressure. Our results are discussed in the sections that
follow.

<hs>  Effects of neurofeedback training on cortical activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We supported our hypothesis that neurofeedback training would be successful in teaching
recreational golfers to suppress frontal high-alpha power during preparation for putting.
First, in the acquisition phase of the experiment, we revealed an effect of block,
indicating that participants were able to complete more putts in five minutes in those
blocks towards the end of each training session compared to those at the start. This
provides indirect evidence that the neurofeedback group learned to reduce high-alpha power
and thereby turn off the neurofeedback tone more frequently as the blocks in each training
session progressed. Second, we provided the first direct evidence of neurofeedback
training leading to selective changes in cortical activity, as implied by the group by
session interactions for EEG high-alpha power at frontal sites. Specifically, members of
the neurofeedback group reduced their pre-movement high-alpha power from the pre-test to
the post-test, whereas members of the control group did not. This key finding clearly
reveals for the first time that relatively brief neurofeedback training (i.e., 3 h over
three separate days) can teach recreational golfers to regulate their cortical activity
even when the source of neurofeedback (i.e., the auditory tone) has been removed.

<hs>  Effects of neurofeedback training on performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our hypothesis that neurofeedback training would facilitate performance and thereby
expedite the development of expertise was not supported. Although members of the
neurofeedback group learned how to suppress their high-alpha power in the moments
preceding putts, their performance during acquisition and the improvement in their mean
radial error score from the pre-test to the post-test were similar to the improvements
achieved by members of the control group. This separation between cortical activity and
behavioural outcome could indicate that reduced pre-movement high-alpha power is not a key
determinant of golf-putting success. However, based on the evidence provided by Babiloni
et al. (2008) and Cooke et al. (2014), this conclusion seems unlikely. There are three
alternative explanations that could reconcile this discrepancy. First, it must be conceded
that the pattern of high-alpha power that our neurofeedback group learned to produce was
not entirely representative of the activity that is produced before the successful putts
of experts. Specifically, our participants produced a general suppression of high-alpha
power spanning the entire four second preparatory period, whereas experts have been shown
to produce a sharp decline in high-alpha power that is most evident during the final two
seconds before and during movement (Cooke et al., 2014). It is thus possible that a
dynamic reduction in high-alpha power (i.e., event-related desynchronisation) is required
in order to deliver putting success (e.g., Babiloni et al., 2008). However, to counter
this claim, our neurofeedback group produced a dynamic reduction in pre-movement high-
alpha in the pre-test, yet they performed worse than in the post-test, where a dynamic
reduction was absent (Fig. 2). Similarly, the control group produced a dynamic reduction
in high-alpha power in both pre-test and post-test sessions, but this did not yield better
performances than the neurofeedback group. A second alternative is that the method
employed to elicit the pre-movement reduction in high-alpha power is important for putting
success, rather than the reduction in high-alpha power per se. For example, it is well-
established that high-alpha power has an inverse relationship with cortical activity, such
that a decrease in high-alpha power reflects heightened activation (e.g., Pfurtscheller,
1992). Accordingly, it would have been possible for the recreational golfers in our study
to learn that they could reduce their high-alpha power and thereby turn off the
neurofeedback tone by engaging in a number of cognitive activities that are irrelevant to
golf putts (e.g., Nowlis & Kamiya, 1970). In contrast, one may speculate that expert
golfers produce their reduction in high-alpha power by engaging specific working memory
processes in order to programme movement parameters such as direction and force (e.g.,
Cooke, 2013). To counter this suggestion, one could argue that if members of our
neurofeedback group were engaging in irrelevant activities to turn off the neurofeedback
tone, their performance is likely to have been impaired. Nevertheless, it would be useful
for future studies to examine the precise strategies that expert golfers use to produce
reductions in pre-movement high-alpha power. The outcomes of such studies could provide
cues to help ensure that participants regulate their cortical activity by engaging in the
same processes as experts in future neurofeedback interventions. Finally, it is possible
that it is a suppressed absolute level of high-alpha power in those seconds immediately
preceding and during movement (i.e., –2 s to +1 s) that is the key to expertise and
putting success (e.g., Babiloni et al., 2008; Cooke et al., 2014). In the present study,
neurofeedback training led to suppressed high-alpha power early during movement
preparation, but in the final second before and during movement the high-alpha power of
the neurofeedback group and the control group was the same (Fig. 2). This seems the most
likely explanation for the null effect of neurofeedback training on performance in our
experiment. It could be attributed to our neurofeedback tone being silenced for 1.5 s once
the prescribed high-alpha power threshold had been breached (cf. Arns et al., 2007). This
afforded the possibility for participants to begin to increase high-alpha power in the
final moments before and during movement, while the neurofeedback tone remained turned
off. This potential artefact could be remedied in future studies by removing a pre-set
silence duration once the neurofeedback threshold is achieved.

<hs>  Effects of neurofeedback on cortical activity and performance under pressure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our final hypothesis was that neurofeedback training would help promote consistent
preparatory cortical activity and performances under both low and high levels of pressure.
We found that performance levels remained robust for both the neurofeedback and the
control groups, so neurofeedback training failed to yield any selective benefits for
performance during pressured conditions. The null effects of pressure on performance could
be attributed to the high number of trials that were required to generate meaningful EEG
data (e.g., Luck, 2005). Specifically, it is known that multiple trials dilute the
strength of pressure manipulations, in this case providing participants with several
chances to redeem bad putts, and likely eliciting levels of pressure far below those
experienced in real-life (Cooke et al., 2010; Woodman & Davis, 2008). Future studies
should afford special consideration to methods of maximising the impact of the pressure
manipulations, especially when large numbers of trials are planned. Finally, in contrast
to our hypothesis, we found that neurofeedback training failed to inoculate participants
against pressure-induced changes in cortical activity. Elevated pressure served to
increase the change in high-alpha power over time at sites overlying frontal regions of
the cortex (i.e., Fz, F3) in both groups of participants. Given that high-alpha power is
inversely related to cortical activity (e.g., Pfurtscheller, 1992), increased high-alpha
power during the early phases of motor preparation in the high-pressure condition could
reflect worrisome thoughts diverting attentional resources away from the motor planning
(i.e., frontal) regions of the brain (Fig. 3). It is possible that more training sessions
were required in order for the volitional control of cortical activity to outweigh the
involuntary changes that appear to be induced by increases in psychological stress.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In addition to the potential limitations of the neurofeedback protocol outlined above, we
concede that the sample size was relatively small. However, the sample size was larger
than those adopted in relevant previous studies (e.g., Arns et al., 2007 N = 6; Landers et
al., 1991 N = 16). Moreover, our study was sufficiently powered to detect a number of main
and interaction effects as detailed above. Notwithstanding, it may be beneficial for
future studies to replicate and extend our experiment with a larger cohort. Future
research would also do well to investigate other aspects of cortical activity, such as EEG
coherence neurofeedback training. In brief, EEG coherence analyses assess the degree of
linear interrelatedness between signals recorded at two sites, with high coherence
commonly thought to represent functional communication between the two sites (e.g.,
Thatcher, Krause, & Hrybyk, 1986). To this end, it has recently been suggested that a
reduction in coherence between the left-hemispheric verbal-analytic regions (e.g.,
electrode site T3) and the motor planning regions (e.g., electrode site Fz) of the brain
represent a reduction in verbal-analytic information processing, and characterise
successful performance across golf putting, rifle shooting and surgical laparoscopy tasks
(e.g., Deeny, Hillman, Janelle, & Hatfield, 2003; Zhu, Poolton, Wilson, Hu, et al., 2011;
Zhu, Poolton, Wilson, Maxwell, & Masters, 2011). This understanding of what T3-Fz
coherence reflects presents researchers with a first opportunity to supplement
neurofeedback with coaching strategies (e.g., implicit learning techniques – see Masters &
Poolton, 2012; Zhu, Poolton, Wilson, Maxwell, & Masters, 2011; Zhu, Poolton, Wilson, Hu,
et al., 2011) to help ensure that trainees produce the desired “expert-like” coherence
patterns through relevant methods. Such a cross-pollination of training methods could
increase the likelihood of neurofeedback yielding expedited learning and robust
performances under stress (e.g., Zhu, Poolton, Wilson, Hu, et al., 2011; Zhu, Poolton,
Wilson, Maxwell, & Masters, 2011). Finally, future research should also carefully
investigate the mechanisms which underpin the expected beneficial effects of neurofeedback
training on performance. For instance, researchers could conduct source localisation
analyses to more precisely identify the individual brain structures that are responsible
for generating the EEG activity measured at the scalp. This would offer insight into the
physiological mechanisms of excellence. Alternatively, researchers could conduct
statistical mediation analyses to verify proposed causal relationships among cortical,
cardiac, somatic and motor systems. We were unable to perform such analyses here because
neurofeedback failed to produce selective benefits for performance.

<hs>  Conclusion</hs>
  ~~~~~~~~~~

In conclusion, this is the first experiment to show that brief neurofeedback training
(i.e., 3 h) can teach recreational golfers to regulate their cortical activity during a
retention test. Importantly, and in line with the themes of this special issue, these
results provide proof of principle that neurofeedback training can be used to alter
cortical activation, thereby providing further support for the notion that this technique
can help expedite the development of expertise in athletes. Neurofeedback training failed
to yield any selective benefits for performance in the present study. This could be
explained by limitations of our neurofeedback protocol as outlined above. By refining
neurofeedback protocols and furthering our understanding of the cortical correlates of
expertise, future studies could expedite development of expertise and excellence, and
neurofeedback can increasingly feature in motor learning protocols in the years and
decades to come.


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<ART>Investigating the link between trait emotional intelligence, career indecision, and self-perceived employability: The role of career adaptability
================================================================================

Authors: Shagini Udayar, Marina Fiori, Amber Gayle Thalmayer, Jérôme Rossier
DOI: 10.1016/j.paid.2018.06.046
Year: 2018  |  Pages: 7-12
ASJC codes: 3200
Keywords: Career adaptability, Career decision-making, Mediation, Self-perceived employability, Trait emotional intelligence

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Trait emotional intelligence (TEI) is emerging as a useful and promising individual difference in predicting vocational behavior (e.g., Di Fabio & Saklofske, 2014). Little is yet known about the underlying processes that may lead TEI to associate with career related outcomes. This study investigates the role of career adaptability in mediating the association between TEI and career decision-making difficulties and self-perceived employability, in a sample of Swiss university students (N = 400). The results of a series of path analysis in which we controlled for intelligence, sex and personality showed that career adaptability fully mediated the effect of TEI on self-perceived employability and career decision-making difficulties, in particular the subscales of lack of information and inconsistent information. Our findings shed light on the role of regulatory processes in shaping the effects of TEI on career-related outcomes.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Our contemporary globalized world involves managing increasingly uncertain professional
trajectories (Guichard, 2015), and career uncertainty is known to be associated with
higher anxiety (Fuqua, Seaworth, & Newman, 1987). In this context, a better understanding
of one's emotional experience has been found to play an important role in career-related
issues (e.g., Di Fabio & Saklofske, 2014). However, little is still known about the
affective components that may impact the process of career exploration and career
development. The aim of this study is to understand the pathway through which emotional
self-perceptions representing the affective aspects of personality, i.e., trait emotional
intelligence (TEI; Petrides, Pita, & Kokkinaki, 2007), may affect career related outcomes,
such as career indecision and self-perceived employability. TEI, defined as the emotional
traits that reflect self-perceptions regarding one's ability to deal with emotions, is
associated with important career related outcomes including career indecision, career
indecisiveness and career decision-making self-efficacy (Di Fabio & Saklofske, 2014), with
self-perceived employability (Di Fabio & Kenny, 2015), and in predicting career success
(De Haro García & Castejón Costa, 2014). The path through which TEI and career indecision
and self-perceived employability are related, however, remains unexplored in the
literature, with no study to our knowledge yet investigating the mediating paths between
these variables. Social Cognitive Career Theory (SCCT; Lent, Brown, & Hackett, 1994)
posits that the relationship between dispositions and career choice is not direct, but
mediated by internal processes, such as self-efficacy. Similarly, Rossier (2015)
highlights the role of regulatory processes, including career adaptability, in mediating
the relationship between individual dispositions and career behaviors. Interestingly,
regulatory processes have a strong adaptive function in allowing dispositions to fit the
characteristics of the environment.

<hs>  Career adaptability, career indecision and self-perceived employability as career-related outcomes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Studies indicate the potential for TEI to have an indirect effect on career indecision and
self-perceived employability through career adaptability (Coetzee & Harry, 2014; Harry,
2017). Career adaptability refers to a set of personal resources that help individuals
manage career transitions (Savickas & Porfeli, 2012). Some studies have highlighted the
association between career adaptability and career decision-making difficulties (e.g.,
Hirschi, Herrmann, & Keller, 2015). A recent meta-analysis (Rudolph, Lavigne, & Zacher,
2017) showed career adaptability to be significantly associated with employability. Of
note, no studies explored the possible mediator effect of career adaptability on the
relationship between TEI and career related outcomes. We posit that the psychosocial
resources of career adaptability may account for the effect of trait emotional
intelligence on career-related outcomes. To explore the mediating role of career
adaptability we chose two career-related constructs to capture the more negative and more
positive aspects of transition to employment: career decision-making difficulties (Gati,
Krausz, & Osipow, 1996), more generally termed career indecision, and self-perceived
employability. Previous work has primarily emphasized the cognitive aspects of career
indecision (e.g., Gati & Tal, 2008). Some authors have also identified its affective
aspect: Betz and Sterling (1993) found that chronic career indecisiveness was strongly
correlated with fear of commitment to a decision, an affective disposition. Saka and Gati
(2007) found emotional and personality-related factor affecting severe career decision-
making difficulties. Self-perceived employability is defined as the characteristics needed
to secure a job that corresponds to one's interests and goals (Rothwell & Arnold, 2007).
Indeed, self-perceived employability appears to be related to higher job satisfaction,
higher work engagement (Ngo, Liu, & Cheung, 2017), and higher perceived marketability (De
Vos, De Hauw, & Van der Heijden, 2011). Overall, both career indecision and self-perceived
employability capture fundamental aspects of career-related outcomes, and may help
elucidate the role of TEI and career adaptability in contributing to career development.

<hs>  Personality, intelligence and sex</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Big Five personality traits have been shown to associate with TEI (Saklofske, Austin,
& Minski, 2003) and with career adaptability, especially conscientiousness (Rudolph et
al., 2017). Although previous studies have established no significant effects of fluid
intelligence on career decision (Di Fabio & Saklofske, 2014), this variable logically
could affect career adaptability. Sex also may impact TEI (Petrides, Furnham, & Martin,
2004), although previous studies have shown no effects of sex on career adaptability
(Rudolph et al., 2017).

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

Based on the framework delineated above, the present study examined the indirect effect of
TEI on career indecision making difficulties and self-perceived employability through
career adaptability, controlling for personality traits, fluid intelligence, and sex. The
strong association between career indecision and emotional intelligence is widely
acknowledged in the literature, although no study to our knowledge has looked at the
process that may explain this association. Furthermore, self-perceived employability is a
key element for career development and success that has not been much studied in relation
to TEI. We hypothesized that career adaptability would fully mediate the relationship
between TEI and career indecision, including its 3 subscales (H1) and between TEI and
self-perceived employability (H2).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

We recruited 400 participants (46% female), ranging in age from 17 to 48 (Mean = 21.39 and
SD = 3.27) from several universities in the Lausanne area (Switzerland) through the
university subject-pool. Participants were bachelor (69,8%) and master or advance studies
students (30,2%) in various disciplines. They gave written consent to participate in the
study and were compensated for their participation.

        <hss>Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF)</hss>

        The Trait Emotional Intelligence Questionnaire-Short Form (Cooper & Petrides,
        2010) is a 30-item self-report questionnaire that measures TEI using a Likert
        scale ranging from 1 = ‘strongly disagree’ to 7 = ‘strongly agree’. Cronbach
        reliability for the total score in the current sample was 0.83.

        <hss>Career Adapt-Abilities Scale (CAAS)</hss>

        The Career Adapt-Abilities Scale (Savickas & Porfeli, 2012) includes 24 items
        equally divided into 4 subscales measuring resources of concern, control,
        curiosity, and confidence. Participants rate how strongly they have developed
        these resources on a Likert scale ranging from 1 = ‘I don't have this ability’, to
        5 = ‘I have a very strong ability’. We employed the total score for the analysis
        as the literature shows that the 4 subscales load into a single second-order
        factor (Savickas & Porfeli, 2012). Cronbach reliability for the total score in the
        current sample was 0.91.

        <hss>Career Decision-making Difficulties Questionnaire (CDDQ)</hss>

        The Career Decision-making Difficulties Questionnaire (Gati et al., 1996) includes
        34 items, but in this study only 32 were used due to a technical problem with the
        administration of items 27 and 29, which were part of the ‘inconsistent
        information’ subscale. The two missing items did not seem to significantly affect
        the subscale score and reliability. We employed the total score and the scores of
        the three subscales (lack of readiness, lack of information, inconsistent
        information) in the statistical analysis. The Likert scale ranges from 1 = ‘Does
        not describe me’ to 9 = ‘Describes me well’. Cronbach reliability in the current
        sample for the total score was 0.92, 0.61 for lack of readiness, 0.93 for lack of
        information, and 0.83 for inconsistent information.

        <hss>Self-Perceived Employability Scale (SPES)</hss>

        The Self-Perceived Employability Scale for university students (Rothwell, Jewell,
        & Hardie, 2009) is a 16-item scale used to evaluate expectations and self-
        perceptions of employability in university students. An example item is: “The
        skills and abilities that I possess are what employers are looking for”. The
        Likert scale ranges from 1 = ‘strongly disagree’ to 7 = ‘strongly agree’. Cronbach
        reliability in this sample for the total score was 0.87.

        <hss>Raven's Standard Progressive Matrices (RPM)</hss>

        Raven's Standard Progressive Matrices (Raven, 1938) were used to assess cognitive
        abilities, especially to evaluate fluid intelligence. The test is composed of five
        sets (A to E) of 12 multiple-choice, progressively more difficult items (60
        total). The test administration was time-limited to 20 min. Cronbach reliability
        of the total score in the current sample was 0.88.

        <hss>Brief HEXACO Inventory (BHI)</hss>

        The Brief HEXACO Inventory is a 24-item questionnaire that assesses six
        personality dimensions: Honesty, emotionality, extraversion, agreeableness,
        conscientiousness, and openness (De Vries, 2013). The HEXACO model is an
        acknowledged measure of personality that proved to be a valid and reliable
        indicator of the major personality traits (e.g., Ashton & Lee, 2009). The brief
        version of the questionnaire showed adequate levels of test-retest reliability and
        high convergence with the longer HEXACO measure (De Vries, 2013). Participants
        respond to self-reflective items using a Likert scale ranging from 1 = strongly
        disagree to 5 = strongly agree. Alpha reliabilities of the dimensions in the brief
        version of the questionnaire range from 0.43 and 0.72 (De Vries, 2013). The
        Honesty scale was not included in the analytic model as we did not have any
        hypothesis regarding its relationship with TEI.

<hs>  Procedure</hs>
  ~~~~~~~~~

The data presented here were collected as part of a larger project on the investigation of
emotional competencies, intelligence, and performance. Students from several French-
speaking Swiss universities participated by filling out questionnaires both online and in
a lab session. The scores of trait EI and personality were collected through an online
survey filled out up to seven days before the lab session. The scores of career
adaptability, fluid intelligence, career indecision and self-perceived employability were
collected during the lab session. Only 308 participants completed this questionnaire
online, as it was added at a second stage of the data collection.

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

To test the fit of the data, structural equation modeling for path analyses were conducted
using Stata 14 (StataCorp, 2015) with maximum likelihood estimation; path coefficients of
direct and indirect effects were estimated using Z-tests. Five separate path models
testing full mediation were fitted: the first four with trait emotional intelligence as
the predictor, career adaptability as the mediator, and career decision-making
difficulties (total score and scores on the 3 subscales) as the outcome, and the fifth
with the same predictor and mediator, but with the outcome of self-perceived
employability. Each model was compared with a partial mediation model for comparative
purposes. Sex, personality traits, and general intelligence were added as control
variables in both models. Because the mediator was measured and not manipulated in our
study, the mediator and the dependent variables might share some common causes; we
therefore employed the instrumental variable method to account for potential endogeneity
problems (Antonakis, Bendahan, Jacquart, & Lalive, 2010), allowing covariance between the
standard error of the mediator and of the outcome. We requested standardized solutions,
thus the reported values are beta coefficients. Overall R2 was also computed for each
model. The following fit indices were used: chi-square test statistic (χ2), the
comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error
of approximation (RMSEA). If the CFI value was 0.90 or above, the TLI values were above
0.95, the SRMR and the RMSEA values were 0.08 or less, the model was considered to have an
acceptable fit (Cheung & Rensvold, 2002; Hu & Bentler, 1999).

<h>RESULTS</h>
-------

The means, standard deviations, and correlations of the variables used are shown in Table
1. As scores on agreeableness were not correlated with emotional intelligence, we did not
include it as a control variable in the final model. The Shapiro-Wilk normality test
showed that the scores on CAAS, CDDQ (total score and lack of readiness), and SPES were
normally distributed.

<hs>  Results regarding career indecision</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We tested a full mediation model in which career adaptability fully mediated the
relationship between trait emotional intelligence and career decision-making difficulties,
after controlling for the effect of sex, intelligence, and personality traits on TEI and
career adaptability. Overall, the model showed satisfactory fit, χ2(6) = 12.29, p = .056;
RMSEA = 0.058; SRMR = 0.020; CFI = 0.975; TLI = 0.938, R2 = 0.50. Because we observed that
the effects of almost all control variables on career adaptability except
conscientiousness were not significant, we created an alternative full mediation trimmed
model (see Table 2) where only the path from conscientiousness to career adaptability was
retained. A Chi-square test for model comparison indicated that the trimmed model had the
same predictive power as the model including the regression paths from all control
variables, ∆χ2(5) = 6.73, p = .241. We therefore retained the most parsimonious model with
the regression path from conscientiousness to career adaptability only, for the rest of
our analyses and for all tested models (Fig. 1). We tested a full mediation model in which
career adaptability fully mediated the relationship between trait emotional intelligence
and career decision-making difficulties, after controlling for the effect of sex,
intelligence, and personality traits on TEI and career adaptability. Overall, the model
showed satisfactory fit, χ2(6) = 12.29, p = .056; RMSEA = 0.058; SRMR = 0.020; CFI =
0.975; TLI = 0.938, R2 = 0.50. Because we observed that the effects of almost all control
variables on career adaptability except conscientiousness were not significant, we created
an alternative full mediation trimmed model (see Table 2) where only the path from
conscientiousness to career adaptability was retained. A Chi-square test for model
comparison indicated that the trimmed model had the same predictive power as the model
including the regression paths from all control variables, ∆χ2(5) = 6.73, p = .241. We
therefore retained the most parsimonious model with the regression path from
conscientiousness to career adaptability only, for the rest of our analyses and for all
tested models (Fig. 1). The comparison of the Chi-square test between the full mediation
(trimmed) model and the partial mediation model (with a direct path from trait emotional
intelligence and career decision-making difficulties) indicated no significant
differences, ∆χ2(1) = 3.53, p = .060 (see Table 2), and supported a full mediation. This
result highlights the importance of career adaptability in totally accounting for the
relationship between TEI and career decision-making difficulties. TEI had a significant
indirect effect on career decision-making difficulties through career adaptability, β =
−0.39, Z = −8.19, p < .001.

        <hss>Results regarding career indecision's subscales</hss>

        We tested three different models in which career adaptability fully mediated the
        relationship between TEI and each of the CDDQ's subscales (lack of readiness, lack
        of information, and inconsistent information). Overall, the model with lack of
        readiness as dependent variable showed close to acceptable fit, χ2(11) = 28.66, p
        = .003; RMSEA = 0.072; SRMR = 0.032; CFI = 0.919; TLI = 0.890, R2 = 0.46. A Chi-
        square test for model comparison between the full mediation model and the partial
        mediation model (with a direct path from TEI to lack of readiness) indicated a
        significant difference, ∆χ2(1) = 5.49, p = .019—the partial mediation model had
        better predictive power and showed better fit indices. TEI had a direct effect on
        lack of readiness (β = −0.33, Z = −2.46, p = .014), but the indirect effect was
        not anymore significant. The model with lack of information as a dependent
        variable showed a good fit to the data, ∆χ2(11) = 15.19, p = .174; RMSEA = 0.035;
        SRMR = 0.021; CFI = 0.983; TLI = 0.977, with an R2 of 0.47. A Chi-square test for
        model comparison between the full and the partial mediation model (with a direct
        path from trait emotional intelligence to lack of information) showed no
        significant difference between the two, ∆χ2(1) = 3.54, p = .060, supporting a full
        mediation. TEI also had a significant indirect effect on lack of information
        through career adaptability (β = −0.38, Z = −8.03, p < .001). The model with
        inconsistent information as dependent variable showed a good fit to the data,
        χ2(11) = 14.74, p = .195; RMSEA = 0.033; SRMR = 0.022; CFI = 0.983; TLI = 0.977,
        with a R2 of 0.48. A Chi-square test for model comparison between the full and the
        partial mediation model (with a direct path from TEI to inconsistent information)
        showed no significant difference between models, ∆χ2(1) = 0.20, p = .658—the full
        mediation model has the same predictive power as the partial mediation model. TEI
        also had, a significant indirect effect on inconsistent information through career
        adaptability (β = −0.31, Z = −6.69, p < .001).

<hs>  Results regarding self-perceived employability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Similar to the previous model, we tested a model in which career adaptability fully
mediated the relationship between TEI and self-perceived employability, after controlling
for the effect of conscientiousness on career adaptability. Overall, this model showed
satisfactory fit, χ2(11) = 29.30, p = .002; RMSEA = 0.064; SRMR = 0.026; CFI = 0.945; TLI
= 0.924, with an R2 of 0.44. A Chi-square test for model comparison between the full and
the partial mediation model (with a direct path from trait emotional intelligence to self-
perceived employability) showed no significant difference between the models, ∆χ2(1) =
0.14, p = .709. This result further highlights the importance of career adaptability in
the relationship between TEI and self-perceived employability, confirming the full
mediation effect of career adaptability (Fig. 2). A Chi-square test for model comparison
between the full and the partial mediation model (with a direct path from trait emotional
intelligence to self-perceived employability) showed no significant difference between the
models, ∆χ2(1) = 0.14, p = .709. This result further highlights the importance of career
adaptability in the relationship between TEI and self-perceived employability, confirming
the full mediation effect of career adaptability (Fig. 2). TEI also had a significant
indirect effect on self-perceived employability through career adaptability (β = 0.30, Z =
7.56, p < .001).

<h>DISCUSSION</h>
----------

The aim of the current study was to examine the mediating role of career adaptability on
the relationship between: a) TEI and career indecision, and b) TEI and self-perceived
employability. We hypothesized a full mediation for both paths. Our hypotheses were
supported in all cases except for the career indecision aspect of lack of readiness.
Career adaptability acted as a mediator of the relationship between TEI and career
indecision. Indeed, individuals scoring high on TEI obtained higher scores on career
adaptability, which in turn had a positive impact on career indecision scores. These
results suggest that the perceived capacity to understand and use emotions in different
contexts may mobilize individuals' self-regulatory resources, which in turn reduce
difficulties in making career decisions. Career adaptability was shown to be a mediator of
the relationship between personality dispositions and career exploration and engagement
(Li et al., 2015; Nilforooshan & Salimi, 2016). Our study indicates that career
adaptability may also regulate the impact of more emotional dispositions, in particular
trait emotional intelligence, on career decision-making difficulties. Indeed, when
including career adaptability as a mediator, TEI has no anymore a direct effect on career
indecision. This finding highlights the importance of considering the mechanisms through
which a predictor may affect an outcome, and not simply testing the direct effect of the
predictor. Concerning the three categories of career decision-making difficulties, career
adaptability fully mediated the relationship between TEI and lack of information and
inconsistent information, but TEI had only a direct positive effect on lack of readiness
to enter the career decision-making process, the indirect effect through career
adaptability being non-significant. Overall these results suggest that TEI has an
important role in affecting perceived difficulties arising before making career-related
decisions. Thus, individuals with high TEI would have fewer difficulties related to a lack
of willingness to make a decision, to a general difficulty in making decision, or to
dysfunctional beliefs about career decision-making process. Career adaptability seems to
regulate the relationship between TEI and career decision-making difficulties that involve
a lack of information and difficulties utilizing information due to inconsistency
encountered during the decision-making process. TEI had once again no direct effect on
both outcomes. Career adaptability also acted as a full mediator of the relationship
between trait emotional intelligence and self-perceived employability. Indeed, individuals
with high trait emotional intelligence through an activation of their career adaptability
resources showed a better self-perceived employability, indicating that the perceived
capacity to deal with emotions may activate the psychosocial self-regulatory resources,
which in turn raise the confidence in finding a future employment. As for previous models,
TEI had no direct effect on employability. The established relationship between
conscientiousness and career adaptability was also confirmed by our study. Indeed, when
the effect of conscientiousness on career adaptability was not controlled for, all the
models showed poor fit. The meta-analysis conducted by Rudolph et al. (2017) showed that
career adaptability and conscientiousness are strongly associated, which explains the
better model fit once accounting for this link in the analysis.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Limitations of the current study include the use of a cross-sectional analysis to test the
mediation hypotheses. It would be interesting to test them with a longitudinal design to
see if the activation of career adaptability and its impact on career-related outcomes
occurs across different time-lags. An additional limitation to consider is that this study
used a student sample, and the results are not based on real-life career experiences.
Previous research has shown that career adaptability influences job-related outcomes by
affecting positive and negative emotional responses in the workplace (Fiori, Bollmann, &
Rossier, 2015). The current findings add to our understanding of career adaptability by
showing the dispositional affective antecedents that may mobilize the cognitive resources
of career adaptability to support more effective career decision-making and more positive
perceived employability. Ultimately, career adaptability emerges as a self-regulatory
skill that shapes affective reactions (Fiori et al., 2015) and is also shaped by the
perceived capacity to manage emotional experience. Based on the results of the current
investigation, fruitful future directions could involve the development of interventions
for career orientation that address potential deficits in both affective dispositions
(e.g., trait emotional intelligence) and emotional states (e.g., negative affect) and
cognitive self-regulatory resources (e.g., career adaptability). Important to note is that
the affective and cognitive determinants of career-related outcomes may reciprocally
influence each other, thus it would be advisable to intervene on both components at the
same time. Because our results show that both conscientiousness and TEI affected career
adaptability and career-related outcomes, future research might investigate potential
interaction effects of these two personality dispositions. That trait emotional
intelligence exerts positive effects on career indecision and employability is well known
in the literature. Our contribution adds evidence for the path through which such effects
may occur: individuals who are more confident in their capacity to handle emotional
situations, including those generated by the search for an employment, mobilize more
cognitive self-regulatory resources. These in turn positively affect individuals' self-
perceived employability and lower their career indecision. Ultimately, this study helps
provide a more comprehensive picture of the factors affecting career related outcomes. The
following are the supplementary data related to this article. Final models with career
indecision, lack of readiness, lack of information, and inconsistent information. Final
model with self-perceived employability. Supplementary data to this article can be found
online at https://doi.org/10.1016/j.paid.2018.06.046.


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<ART>Judgement utility modulates the use of explicit contextual priors and visual information during anticipation
================================================================================

Authors: N. Viktor Gredin, David P. Broadbent, A. Mark Williams, Daniel T. Bishop
DOI: 10.1016/j.psychsport.2019.101578
Year: 2019
ASJC codes: 3202
Keywords: Bayesian, Decision making, Probabilistic information, Risk, Soccer

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: We examined the impact of judgement utility on the use of explicit contextual priors and visual information during action anticipation in soccer. Design: We employed a repeated measures design, in which expert soccer players had to perform a video-based anticipation task under various conditions. Methods: The task required the players to predict the direction (left or right) of an oncoming opponent's imminent actions. Performance and verbal reports of thoughts from players were compared across three conditions. In two of the conditions, contextual priors pertaining to the opponent's action tendencies (dribble = 70%; pass = 30%) were explicitly provided. In one of these experimental conditions, players were told that an incorrect ‘right’ response would result in conceding a goal, which created imbalanced judgement utility (left = high utility; right = low utility). In the third control condition, no explicit contextual priors or additional instructions were provided. Results: The explicit provision of contextual priors changed players’ processing priorities, biased their anticipatory judgements in accordance with the opponent's action tendencies, and enhanced anticipation performance. These effects were suppressed under conditions in which the explicit contextual priors were accompanied by imbalanced judgement utility. Under these conditions, the players were more concerned about the consequences of their judgements and were more inclined to opt for the direction with the higher utility. Conclusions: It appears that judgement utility disrupts the integration of contextual priors and visual information, which results in decreased impact of explicit contextual priors during action anticipation.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In dynamic and rapidly evolving environments, fast and accurate anticipation of an
opponent’s actions underpins expert performance (Williams, 2000). Researchers have tried
to elucidate the processes by which athletes combine prior knowledge and beliefs relevant
to the specific performance context (i.e., contextual priors) with evolving visual
information during anticipation (see Cañal-Bruland & Mann, 2015; Williams & Jackson,
2018). It has been proposed that athletes may employ Bayesian reliability-based strategies
to weigh up, and integrate, contextual priors with relevant visual information: the
reliance on contextual priors and visual information is modulated by the comparative
reliability of the information at hand, where more reliance is assigned to information of
relatively higher certainty with regard to the to-be-anticipated event (Gredin, Bishop,
Broadbent, Tucker, & Williams, 2018). However, when examining anticipation in sport, a
key, but often overlooked, component of the Bayesian framework is the comparative utility
associated with possible judgements. Judgement utility refers to the potential costs and
rewards associated with the consequences of one’s predictions: high judgement utility is
associated with high rewards (if accurate) and low costs (if inaccurate), and vice versa
for low judgement utility. According to Bayesian theory, people attempt to maximise the
probability of their judgements being accurate while simultaneously maximise the expected
utility of their judgments (Geisler & Diehl, 2003). In the current study, we examined the
impact of judgement utility on the integration of explicit contextual priors and visual
information during anticipation in soccer. It is well-established that expert athletes use
advance visual information, such as opponent kinematics, to predict an opponent’s next
move (e.g., Farrow, Abernethy, & Jackson, 2005; Loffing & Hagemann, 2014; Wright, Bishop,
Jackson, & Abernethy, 2013). However, in recent years, researchers have taken a broader
focus when examining the nature of anticipation in sport, by exploring the importance of
non-visual information, such as contextual priors (Broadbent, Gredin, Rye, Williams, &
Bishop, 2018; Gray & Cañal-Bruland, 2018; Gredin et al., 2018; Navia, Van der Kamp, &
Ruiz, 2013; Runswick et al., 2018a). Due to advances in technology that enable
sophisticated analyses of opponents, an increasingly prevalent component of elite sport
preparation is to provide athletes with contextual priors pertaining to the behaviours of
forthcoming opponents (Memmert, Lemmink, & Sampaio, 2017). Gredin et al. (2018) recorded
gaze patterns and anticipatory judgements while soccer players predicted an opponent’s
imminent actions with the ball in 2-versus-2 defensive soccer scenarios. The players
performed the task both with and without explicitly provided contextual priors pertaining
to the action tendencies of the attacker on the ball – specifically, whether he tended to
dribble or pass the ball to a teammate. When given priors, the players allocated their
visual attention toward the attacking teammate off the ball over the first half of each
trial, as their determination of the teammate’s run trajectory enabled them to inform
their judgements according to the action tendencies of the attacker on the ball. Over the
second half of each trial, closer to the key point of action, the players relied more on
evolving kinematic information of the attacker on the ball to inform their judgements. The
provision of explicit priors biased the players’ judgements toward the most likely action,
given the action tendencies, which resulted in enhanced task performance (see also
Broadbent et al., 2018; Navia et al., 2013). Similarly, the beneficial performance effect
of contextual priors was reported by Runswick et al. (2018a) using a task that required
cricket batters to predict the location of forthcoming deliveries from bowlers. The
batters exhibited superior anticipation when facing the same bowler six times in a row and
when explicitly provided with information about the game state and field setting, compared
to under conditions in which they faced six different bowlers and were not explicitly
presented information about the game state and field setting. In the former condition,
retrospective verbal reports demonstrated that the batters relied more on contextual
priors to inform their judgements when compared to the latter condition. In the quest to
develop an overarching framework that might explain the processes by which athletes
combine contextual priors and visual information during anticipation, Loffing and Cañal-
Bruland (2017) suggested that Bayesian theory may provide a suitable framework to
elucidate these processes. Bayesian models for probabilistic inference assume that people
base their judgements on probabilistic if-then relationships between known informational
variables and unknown to-be-anticipated variables. That is, if ‘X’ (a known informational
variable) occurs, then there is a certain probability that ‘Y’ (an unknown to-be-
anticipated variable) will occur. This process suggests that, if one informational
variable is associated with greater reliability (i.e., higher certainty) than another,
then the individual’s joint estimate should be biased toward the ‘more reliable’
informational variable (Knill & Pouget, 2004). In line with the suggestion by Loffing and
Cañal-Bruland (2017), Gredin et al. (2018) evaluated their findings using a Bayesian
framework for probabilistic inference. In keeping with Bayesian theory, the authors
proposed that players integrated explicit contextual priors and evolving visual
information according to the comparative levels of reliability associated with the
different sources of information (see Vilares & Körding, 2011). That is, the players were
more dependent on priors over the first half of each trial where the reliability of
kinematic information was low, and vice versa (see also Gray & Cañal-Bruland, 2018). A
fundamental aspect of Bayesian theory is that our ultimate judgements are affected by both
the reliability of available information and the potential costs and rewards associated
with inaccurate and accurate judgements. Put in Bayesian terms, the weighted average of
the reliability conveyed by prior and current sources of information is convolved with the
utility values assigned to possible judgements (Geisler & Diehl, 2003). The biasing effect
of judgement utility reflects not only to our desire to gain rewards and avoid costs, but
also our tendency to use current information to confirm the viability of the high-utility
option. As such, we tend to overestimate the likelihood of the outcome in accordance with
its utility (see DeKay, Patiño-Echeverri, & Fischbeck, 2009; Russo & Yong, 2011). The
biasing effect of judgement utility was, for example, shown in a study by Wallsten (1981)
in which physicians judged it to be more likely that a patient had a malignant tumour than
a cyst, despite the higher objective likelihood that the patient had a cyst. It was
proposed that physicians overestimated the chances of a tumour due to its more severe
consequences, relative to a cyst. In other words, a tumour diagnosis would yield greater
rewards (if correct) and lower costs (if incorrect) than would diagnosing a cyst. In line
with this finding, Canãl-Bruland, Filius, and Oudejans (2015) reported that skilled
baseball batters tended to predict that fastballs would be pitched to a greater extent
than change-ups. It was suggested that this strategy enabled them to handle the high speed
of a fastball and, due to the slower nature of change-ups, to adapt their swing if
confronted with this latter pitch type. If expecting a change-up, on the other hand,
batters would not be able to catch up with the speed of a fastball. This finding suggests
that judgement utility (e.g., comparatively higher utility of predicting a fastball than a
change-up in baseball) may influence anticipation in sport. However, the manner in which
judgement utility modulates the impact of contextual priors and processing priorities
during anticipation has yet to be examined empirically. Greater awareness of the effects
of judgement utility on athletes’ use of contextual priors will strengthen our
understanding of action anticipation processes in sport – which will ultimately enhance
coaches’ and performance analysts’ ability to maximise the effectiveness of explicit
contextual priors (see Cañal-Bruland & Mann, 2015). In the current study, we examined the
impact of judgement utility on the integration of explicit contextual priors and visual
information as expert soccer players anticipated an oncoming opponent’s imminent actions.
We employed the same task as used by Gredin et al. (2018): a video-based anticipation task
simulating 2-versus-2 defensive soccer scenarios, in which the players had to predict the
direction (left or right) of the attacker on the ball’s (termed ‘the opponent’ from
hereon) action at the end of each sequence. In addition to conditions with and without
explicitly provided contextual priors pertaining to the opponent’s action tendencies
(dribble = 70%; pass = 30%), an additional condition was added, in which contextual priors
were explicitly provided and judgement utility was explicitly manipulated. Judgement
utility was manipulated by telling the players that an incorrect ‘right’ response would
result in conceding a goal, which created imbalanced judgement utility (left = high
utility; right = low utility). We recorded anticipation judgements and collected
retrospective verbal reports of the thoughts the players engaged in when solving the task.
We predicted that the explicit provision of contextual priors would bias anticipatory
judgements toward the most likely action given the opponent’s action tendencies (i.e.,
dribble) and consequently enhance their anticipation performance (Broadbent et al., 2018;
Gredin et al., 2018). Furthermore, we predicted that the explicit provision of contextual
priors would result in players engaging in more thoughts related to the positioning of the
attacker off the ball (see the Method section for detailed explanation) and the opponent’s
action tendencies, whereas fewer thoughts would be related to the opponent’s kinematics
(cf., Runswick et al., 2018a). However, in keeping with Bayesian theory (see Geisler &
Diehl, 2003), we predicted that these effects would be supressed when the priors were
accompanied with manipulated judgement utility, as players would be more inclined to opt
for the direction associated with the higher utility value (i.e., left). In the condition
where judgement utility was manipulated, it was hypothesised that the players would engage
in more thoughts related to the costs and/or rewards that their responses could bring
about. Based on Bayesian theories of weighted integration of information, we predicted
that this would result in fewer thoughts related to the opponent’s action tendencies and
relevant visual information.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 18 (10 male and 8 female) expert soccer players (Mage = 23 years, SD = 3)
participated. On average, the players had 14 years (SD = 2) of competitive experience in
soccer at university or semi-professional level. At the time of the study, they
participated in an average of 9 h (SD = 4) of soccer practice or match play per week. A
spreadsheet for estimating sample size for magnitude-based inferences (Hopkins, 2006) was
used to calculate the number of participants needed to find a clear performance effects
(i.e., chances of the true effect to be substantially positive and negative < 5%;
Batterham & Hopkins, 2006; see the Data Analysis section for further details). We used
data from the study by Gredin et al. (2018) to calculate the minimum required sample size
(n = 12; Hopkins, Marshall, Batterham, & Hanin, 2009). The study was approved by the
Research Ethics Committee of the lead institution and conformed to the recommendations of
the Declaration of Helsinki. All participants gave their written informed consent before
taking part.

<hs>  Test stimuli</hs>
  ~~~~~~~~~~~~

The test stimuli comprised 30 video sequences of 2-versus-2 counter attacking scenarios in
soccer, viewed from the perspective of one of the defenders. The test stimuli were filmed
on an artificial turf soccer pitch using a high-definition digital video camera (Canon
XF100, Tokyo, Japan) with a wide-angle converter lens (Canon WD-H72 0.8x, Tokyo, Japan).
The camera was attached to a moving trolley, at a height of 1.7 m, to replicate the
perspective of a central defender moving backwards. The final test footage was edited
using Pinnacle Studio software (v15; Pinnacle, Ottawa, Canada). In total, 130 video
simulations were created, but only clips that were independently selected by two qualified
soccer coaches (UEFA A Licence holders), based on their representativeness of actual game
play, were included in the final test footage of 30 clips. In each sequence, there was one
attacking player in possession of the ball (‘the opponent’), a second attacker off the
ball, and one marking defender who was following the second attacker throughout the
sequence (see Figure 1). The videos were projected onto a 3.3 × 1.9 m projection screen
using an Optoma HD20 DLP projector (Optoma, New Taipei City, Taiwan). The participant
viewed the scenarios from a first-person perspective, as if they were the second defender.
At the start of the sequence, the opponent was positioned approximately 7 m in front of
the participant, 10 m to the right of the centre of the pitch, and 3 m inside the
defensive half. The attacker off the ball and the second defender started approximately 3
m behind, either on the left, or the right, side of the opponent. When the sequence
started to unfold, the players approached the participant and, after approximately 1.5 s,
the attacker off the ball made a direction change towards either the left or the right.
The sequences lasted for 5 s and, at the end of each sequence, the opponent could either
pass the ball to his teammate who was positioned either to the left or right of the
opponent (30% of trials) or dribble the ball in the opposite direction of the teammate
(70% of trials).

<hs>  Task design</hs>
  ~~~~~~~~~~~

The participant was required to predict the direction (left or right) of the ball from the
opponent’s final action. At the start of each trial, the participant was standing 3.5 m in
front of the projection screen holding a response device in each hand − one for ‘left’
responses and one for ‘right’ responses. The participant was instructed that they should
respond as soon as they were certain enough to carry out an action based on their
prediction and that they could not change this response. Immediately after the
participant’s response, the trial was occluded and feedback with regard to their response
time and accuracy was displayed on-screen. Feedback for response time and accuracy was
given as pilot testing suggested that receiving this information after each trial
motivated the participant to stay engaged with the test task throughout the test session.
A full 5-s trial was occluded 120 m s after the foot-ball contact of the opponent’s final
action and if the participant responded after this point, then that trial was counted as
incorrect. Since players in a soccer match are normally aware of the position of the ball
and other players each trial started with a frozen frame for 1 s to allow the participant
to detect this information. During the course of a trial, the participant was free to move
as preferred in order to maximise the real-world representativeness of the task (cf.
Gredin et al., 2018).

<hs>  Procedure</hs>
  ~~~~~~~~~

Before testing, the participant undertook 25–40 min of training in how to provide
retrospective think-aloud reports. This training consisted of instructions on how to
report thoughts retrospectively, including practice on a number of generic tasks. The
participant was given feedback on their verbal reports, along with good and bad examples
for these practice tasks (see Eccles, 2012). Throughout the training, the participant was
encouraged to ask the researcher questions if they were unsure about how to articulate
their reports. The aim of the verbal report training was to ensure that the participant
learned how to verbalise only the thoughts that they used during the preceding task
performance and to report them as they were naturally experienced during performance. This
procedure is important to follow, as elaborating or providing commentary on the reported
thoughts, or reporting thoughts that were not used during task performance may influence
performance and violate the natural cognitive processes that occur during the task
(Ericsson & Simon, 1980). Following this training, the participant was fitted with a lapel
microphone and a body-pack transmitter that was wirelessly connected to a compact
diversity receiver (ew112-p G3; Sennheiser, Wedemark, Germany) and a recording device
(Zoom H5; Zoom Corporation, Tokyo, Japan), so that verbal reports could be recorded.
Thereafter, the participant was given an overview of the experimental protocol and
performed eight familiarisation trials to become accustomed to the experimental setup and
response requirements. Verbal reports of thoughts were collected after four of the
familiarisation trials. Following the familiarisation trials, the 30 test trials were
presented in three blocks of ten trials, and under three different conditions (i.e., 90
test trials in total). In the control condition (Control), the participant performed the
task without any additional information. In one of the experimental conditions (EXP), the
participant performed the same task, but before each block, the participant was explicitly
primed (verbally and on-screen) with contextual priors pertaining to the opponent’s action
tendencies (i.e., dribble = 70%; pass = 30%). Due to the nature of the task, the
positioning of the attacker off the ball revealed information that enabled the participant
to use information about the opponent’s action tendencies (i.e., if the attacker off the
ball was on the left, 70% of the opponent’s final actions were to the right, and vice
versa). This meant that the participant had to incorporate the explicit contextual priors
(i.e., the opponent’s action tendencies) with evolving visual information (i.e., the
positioning of the attacker off the ball) in order to use the priors to inform their
judgement. In complex and highly dynamic performance environments, such as in soccer, this
interdependency between contextual priors and visual information may be an important
component when seeking to elucidate the integration of different sources of information
during anticipation (Gredin et al., 2018). In the other experimental condition (EXPJU),
the same task was performed, and the same contextual priors were explicitly provided, but
in this condition, the participant was instructed that if they were incorrect (i.e.,
responded ‘right’) when the opponent passed or dribbled the ball toward the left, their
team would concede a goal. This instruction was given in order to increase the comparative
utility associated with responding ‘left’. In other words, correct and incorrect ‘left’
responses came with greater rewards (stopping a goal) and costs (conceding a goal),
respectively, than ‘right’ responses. This manipulation was based on the fact that in
soccer, possession of the ball in a more central position near the penalty area (i.e., to
the participant’s left in the present task) is more frequently associated with positive
attacking outcomes than possession in a wider position (i.e., to the participant’s right;
Brooks, Kerr, & Guttag, 2016). The participant received this instruction before each
block, both verbally and on-screen, and was informed as to the number of goals they had
conceded after each block. Each condition started with a condition-specific
familiarisation trial, for which retrospective verbal reports were collected. To eliminate
the influence of trial-specific characteristics, the same test trials were used in all
three conditions. Thus, the distribution of trials where the opponent dribbled (70%) and
passed (30%) the ball was identical across all three conditions. Furthermore, these
actions were equally distributed across left and right outcome directions. The order in
which the conditions were presented was randomised and counterbalanced across
participants, which is a commonly used design in order to mitigate potential learning and
carryover effects across various experimental conditions in sport (e.g., Gray, 2009;
Jackson, Ashford, & Norsworthy, 2006; Runswick, Roca, Williams, Bezodis, & North, 2017).
To further avoid any potential familiarity between conditions, the trial order in each
condition was randomised (cf. Gredin et al., 2018). Response time and accuracy were
recorded for each trial and verbal reports of thoughts were collected after six trials in
each condition (cf. Runswick et al., 2018a). The selection of trials for which verbal
reports were given was pseudorandomised in order to counterbalance the number of trials
where the opponent dribbled (n = 3) and passed (n = 3) the ball, as well as the number of
trials where the direction of the final actions was left (n = 3) and right (n = 3). The
same trials were selected for all conditions and participants in order to avoid trial-
specific characteristics from violating the verbal report data. The whole test session was
completed within 90 min.

<hs>  Dependent measures</hs>
  ~~~~~~~~~~~~~~~~~~

Anticipatory judgements. To ascertain whether any systematic speed–accuracy trade-off
effects were evident in the response data, Pearson correlations between response time and
accuracy were determined for each condition. A positive correlation between the two
variables was found in each of the three conditions (Control, r = 0.59 ± 0.28 [90% CI];
EXP, r = .66 ± 0.24; EXPJU, r = 0.68) ±0.23). To account for this speed-accuracy trade
off, anticipation performance was expressed as an anticipation efficiency score, which was
calculated by multiplying the average response time by the proportion of inaccurate
responses in each condition (note: lower efficiency score indicates superior anticipation
performance; cf. Gredin et al., 2018). In addition to the anticipation efficiency score,
anticipation performance was expressed by the change in response accuracy between each
condition, where the change in response time was used as a covariate in order to account
for the covariation in the speed and accuracy measures (cf. Abernethy, Schorer, Jackson, &
Hagemann, 2012). As we predicted that explicit contextual priors would bias the players’
judgements toward the most likely action, given the opponent’s action tendencies, we
calculated the proportion of ‘dribble’ responses in each condition (note: a ‘dribble’
response corresponded to when the participant responded ‘right’ and the attacker off the
ball was on the left side of the opponent or when the participant responded ‘left’ and the
attacker off the ball was on the right side of the opponent). As we predicted that
judgement utility would bias the players’ judgement toward the direction with the
comparatively higher utility, the proportion of ‘left’ responses in each condition was
assessed. Verbal reports. The verbal reports of thoughts were first transcribed verbatim,
and the statements conveyed by each report were then coded into different categories (cf.
Murphy et al., 2016; Roca, Ford, McRobert, & Williams, 2013; Runswick et al., 2018a).
Statements were coded into three categories of visual information: positioning of the
attacker off the ball, statements referring to the horizontal position (e.g., left, right,
inside, outside) of the attacker off the ball relative to opponent; kinematic information,
statements referring to the kinematic cues of the oncoming opponent; other visual
information, statements referring to other kind of visual information not captured by the
previous two categories. Furthermore, statements were coded into two categories of non-
visual information: action tendencies, statements referring to the opponent’s tendency to
pass or dribble the ball; judgement utility, statements referring to the costs and/or
rewards their responses could bring about. Verbal report data from 3 participants, and 9
reports (<4%) from the remaining 15 participants, were excluded from the analyses due to
participants failing to follow the procedure required for providing retrospective think-
aloud reports (see Eccles, 2012). Once statements within each eligible report had been
categorised, the proportion of reports in each condition that contained statements of each
category was assessed (note: each report could contain references to multiple sources of
information; cf. Murphy et al., 2016).

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

Descriptive statistics are reported as means and SDs. Magnitudes of observed effects along
with their 90% CIs are reported as standardised (d) and unstandardised units. The effects
were standardised by dividing the mean difference between conditions by the combined SD
and then interpreted against the following scale: 0.2 > |d|, trivial; 0.2 ≤ |d| < 0.5,
small; 0.5 ≤ |d| < 0.8, moderate; 0.8 < |d|, large (Cohen, 1988; Cumming, 2012). Cohen’s
standardised unit for the smallest substantial effect (0.2) was used as a threshold value
when estimating the uncertainty in true effects. The following scale was used to convert
the quantitative chances to qualitative descriptors: 25–75%, possible; 75–95%, likely;
95–99.5%, very likely; > 99.5%, most likely (Hopkins, 2002). If the lower and upper bounds
of the CI exceeded the thresholds for the smallest substantial negative and positive
effect, respectively, meaning that there is ≥ 5% that the true effect could be
substantially negative and ≥5% that it could be substantially positive, then the effect
was deemed unclear. All other effects were deemed clear and evaluated as per the
description above (Batterham & Hopkins, 2006). The confidence level of the CIs was not
adjusted for multiple comparisons (Hopkins, Marchall, Batterham, & Hanin, 2009; Perneger,
1998; Rothman, 1990). Due to the low number of participants making references to the
sources of non-visual information in their verbal reports, leading to high variability
across participants and skewed data, inferential analyses were not conducted on the verbal
reports of action tendencies and judgement utility. For these reports, descriptive
statistics, including the number of participants referring to each information category,
are presented.

<hs>  Anticipatory judgements</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Table 1 shows the descriptive statistics for the response time and accuracy scores in each
condition1,2. As shown in Figure 2a, the participants exhibited superior performance,
manifested in a lower anticipation efficiency score, in EXP than in Control (d = 0.54 ±
0.35) and EXPJU (d = 0.43 ± 0.35), whereas no substantial effect was obtained when the
anticipation efficiency score in Control was compared to that in EXPJU (d = 0.14 ± 0.34).
The analysis of the adjusted effects for response accuracy between conditions revealed
that response accuracy was higher in EXP than in Control (d = 0.35 ± 0.29) and EXPJU (d =
0.25 ± 0.30), whereas no substantial effect was found between Control and EXPJU (d = 0.12
± 0.27; note: changes in response time were included as a covariate in these analyses).
The proportion of trials in which the participants predicted that the opponent would
dribble was higher in EXP than in Control (d = 0.66 ± 0.47) and EXPJU (d = 0.89 ± 0.46),
whereas no clear effect was found when the proportion of ‘dribble’ responses in Control
was compared to that in EXPJU (see Figure 2a). Figure 2c shows that the proportion of
trials where the participants predicted that the opponent would dribble or pass the ball
toward the left was higher in Control than in EXP (d = 0.33 ± 0.42) and higher in EXPJU,
both compared to Control (d = 0.65 ± 0.44) and compared to EXP (d = 1.03 ± 0.47).
Unstandardised effects for anticipation efficiency, percentage ‘dribble’ responses, and
percentage ‘left’ responses across conditions are presented in Table 2.

<hs>  Verbal reports</hs>
  ~~~~~~~~~~~~~~

The percentage of verbal reports referring to each category of visual information in each
condition is presented in Figure 3. The participants reported a higher proportion of
statements referring to the positioning of the attacker off the ball in EXP than in
Control (d = 0.37 ± 0.34) and EXPJU (d = 0.22 ± 0.39), whereas no substantial difference
was found between Control and EXPJU (d = 0.12 ± 0.28). The percentage of statements
referring to the kinematic information of the opponent was higher in Control than in EXP
(d = 0.59 ± 0.27) and EXPJU (d = 1.03 ± 0.43), and higher in EXP than in EXPJU (d = 0.47 ±
0.27). Regarding other sources of visual information, the participants reported a higher
proportion of statements within this category in Control than in EXP (d = 0.32 ± 0.37) and
EXPJU (d = 0.40 ± 0.27), while no clear difference was obtained between EXP and EXPJU.
Unstandardised effects for the percentage of verbal reports referring to each category of
visual information across conditions are presented in Table 3. In reports containing
statements referring to non-visual information, the proportion containing statements
relating to the opponent’s action tendencies were 1.1% (SD = 4.3) in Control, 32.2% (SD =
28.5) in EXP, and 22.2% (SD = 29.5) in EXPJU. Only one participant mentioned this
information source in Control, whereas eleven and nine participants referred to the
opponent’s action tendencies in EXP and EXPJU, respectively. Statements relating to
judgement utility were reported in 34.2% (SD = 32.5) of the reports in EXPJU, while the
corresponding proportions in Control and EXP were 14.2% (SD = 23.3) and 3.3% (SD = 12.9),
respectively. Statements referring to this category was reported by five participants in
Control, one participant in EXP, and twelve participants in EXPJU.

<h>DISCUSSION</h>
----------

We examined the impact of judgement utility on the integration of explicit contextual
priors and visual information as expert soccer players predicted the direction (left or
right) of an oncoming opponent’s imminent actions. The players performed the anticipation
task under three different conditions: one condition without any explicit contextual
priors; another condition in which contextual priors pertaining to the opponent’s action
tendencies (dribble = 70%; pass = 30%) were explicitly provided; and a third condition in
which these contextual priors were explicitly provided, and judgement utility was
explicitly manipulated (left judgements = high utility; right judgements = low utility).
We recorded anticipatory judgements and collected retrospective think-aloud reports in all
three conditions. In line with our predictions, the explicit provision of contextual
priors biased the players’ anticipatory judgements toward the most likely action, given
the opponent’s action tendencies. This effect was manifested in the fact that the players
predicted the opponent would dribble the ball to a greater extent in the condition with
explicit contextual priors, compared to the condition in which no priors were provided.
This finding supports previous research suggesting that expert soccer players use explicit
contextual priors to inform their judgements when predicting an oncoming opponent’s next
move (Broadbent et al., 2018; Gredin et al., 2018). As we predicted, this biasing effect
of explicit contextual priors resulted in enhanced performance, which was evidenced by
superior anticipation efficiency in the condition with, compared to without, explicit
priors. These findings support the growing body of research demonstrating the performance-
enhancing effect of contextual priors on anticipation in sport (Broadbent et al., 2018;
Gredin et al., 2018; Navia et al., 2013; Runswick et al., 2018a). An important objective
of this study was to examine the impact of judgement utility on the players’ anticipation.
As we hypothesised, judgement utility supressed the impact of explicit contextual priors:
the proportion of ‘dribble’ responses did not increase when priors were accompanied by the
judgement utility manipulation. In line with our predictions, this resulted in
anticipation performance comparable to that in the control condition. As prescribed by
Bayesian models for informational integration, this finding suggests that expert soccer
players base their judgements both on the reliability of the information at hand and the
costs and rewards their responses could generate (see Geisler & Diehl, 2003). In other
words, it appears that judgement utility reduced the impact of contextual priors, as the
players were more inclined to opt for the direction with the comparatively higher utility.
Further support for the impact of judgement utility on anticipatory judgements is apparent
in the comparison made between the proportion of ‘left’ responses across conditions. As
predicted, the proportion of responses where the players opted for a leftward outcome was
higher in the condition where judgement utility was manipulated, compared to the other two
conditions. Such a biasing effect of judgement utility has been demonstrated across
various domains (see Canãl-Bruland et al., 2015; DeKay et al., 2009; Russo & Yong, 2011).
It is noteworthy though, that the players responded ‘left’ more often than ‘right’ in all
three conditions. It may be the case that the players associated the left side with
greater goal threat, due to the position on the pitch (Brooks et al., 2016) even though
this information was not explicitly provided, and hence there were more ‘left’ responses
in all three conditions. This suggestion aligns with the findings reported by Canãl-
Bruland et al. (2015) demonstrating that baseball batters predicted fastballs to a greater
extent than change-ups, even if they were not explicitly instructed that predicting
fastballs came with greater utility. Interestingly, in the two conditions without
manipulated judgement utility, the players were more inclined to respond ‘left’ in the
condition without explicit contextual priors. In keeping with Bayesian theory (see Geisler
& Diehl, 2003; Vilares & Körding, 2011), the perceived imbalance in threat between left
and right outcomes may have been weighted higher in the former condition where less
reliance was placed on the opponent’s action tendencies. To explore the processing
priorities employed by the players during task performance, we collected immediate
retrospective verbal reports of their thought processes. The data provide tentative
support for our prediction that the players would refer to the opponent’s action
tendencies to a greater extent when this information was explicitly provided, relative to
when it was not. Furthermore, when contextual priors were explicitly provided, the players
reported a higher proportion of thoughts relating to the attacker off the ball, compared
to the latter condition. This finding aligns with the gaze data in Gredin and colleagues'
(2018) study, in which expert soccer players shifted their overt visual attention away
from the opponent, and toward the attacker off the ball, when explicit contextual priors
were provided. In the case of that study, and the current one, it is proposed that the
players prioritised the positioning of the attacker off the ball more so when contextual
priors were explicitly provided compared to when they were not. This information enabled
the players to inform their anticipatory judgements in accordance with the opponent’s
action tendencies (i.e., when the attacker off the ball was on the left, 70% of the
opponent’s final actions were to the right, and vice versa). The verbal report data in the
current study also showed that the proportion of thoughts relating to the opponent’s
kinematic information was lower in the condition in which contextual priors were
explicitly provided, relative to in the condition where they were not. This finding
mirrors that of Runswick et al. (2018a), who demonstrated that an increased reliance on
contextual priors came with a decreased reliance on kinematic information, when cricket
batters predicted the location of forthcoming deliveries from a bowler. The previous
research, and the current study, provide support for the Bayesian notion that, when the
reliability of one informational variable increases (e.g., increased reliability of
contextual priors via explicit guidance or sequential pickup), people’s judgements become
less contingent upon other informational variables (e.g., kinematic information; see
Vilares & Körding, 2011). In the condition where judgement utility was manipulated, the
players engaged less in thoughts relating to the positioning of the attacker off the ball
and fewer players referred to the opponent’s action tendencies, compared to when explicit
contextual priors were provided, but judgement utility was not manipulated. Furthermore,
in the former condition, the players engaged less in thoughts relating to the opponent’s
kinematic information, and more players referred to the costs and/or rewards their
responses could bring about, relative to in the other two conditions. In line with our
predictions, these data provide tentative support that the biasing effect of judgement
utility on anticipation was underpinned by changes in the thought processes that the
players employed during task performance; namely, an increased concern about the costs
and/or rewards their responses could bring about (see also DeKay et al., 2009; Russo &
Yong, 2011). The current study lends support to the idea that Bayesian theory may provide
a suitable framework to elucidate the processes by which athletes inform their judgments
during action anticipation (Loffing & Cañal-Bruland, 2017). However, it is important to
note that the experimental design in this study did not allow us to test the predictions
prescribed by Bayesian theory in relation to the impact of contextual priors, visual
information and judgement utility in a fine-grained quantitative manner. Thus, we
encourage researchers to further explore the merits of Bayesian theory in this regard; for
example, by adopting temporal occlusion paradigms to more tightly control the availability
of visual information (e.g., Runswick, Roca, Williams, McRobert, & North, 2018b), by
altering the reliability of priors in a more fine-grained manner (e.g., Gray & Cañal-
Bruland, 2018), and/or by using continuous outcome possibilities, rather than a binary-
choice task (e.g., Tassinari, Hudson, & Landy, 2006). Our findings may prove highly
informative to coaches and performance analysts, who typically use contextual priors to
guide their players’ on-pitch decision making. In situations where inaccurate and accurate
judgements incur varying costs and rewards, it seems like judgement utility disrupts
players’ processing priorities and decreases the effectiveness of explicit contextual
priors. However, it is worth noting that soccer matches are inherently complex, comprising
multiple crossmodal sources of environmental information, priors that relate to multiple
players and/or situations, and a multitude of potential outcomes. Thus, it is possible
that the task in the current study did not evoke behaviours that we might observe under
natural performance conditions (see Cañal-Bruland, Müller, Lach, & Spence, 2018; Müller &
Abernethy, 2012; Vaeyens, Lenoir, Williams, Mazyn, & Philippaerts, 2007). Clearly, the
impact of judgement utility should be further explored, using more naturalistic test
tasks. Another potential limitation of this study was that we did not include a condition
in which we manipulated judgement utility and provided no explicit contextual priors.
Adding such a condition would allow us to assess the moderating effects of judgement
utility with greater certainty. However, pilot work suggested that the effects that would
have been obtained in such a condition would not have been substantially different to
those obtained in the EXPJU. Also, it is worth highlighting that it is possible that the
players in the current study used information acquired in preceding conditions to inform
their task performance in subsequent conditions. Thus, in order to mitigate potential
confounding order effects, we employed a randomised and counterbalanced within-participant
design, which is a well-established approach when comparing the effects of various
informational conditions in sport (cf. Gray, 2009; Jackson et al., 2006; Runswick et al.,
2017). To further avoid any potential familiarity effects across conditions, the trial
order in each condition was randomised (cf. Gredin et al., 2018). Furthermore, it is
possible that the feedback for response time and accuracy provided after each trial
created another source of information that could have facilitated trial-to-trial learning.
However, self-reported pilot data suggest that, without this immediate feedback about
their performance, the players’ motivation to engage with the task would decline over the
course of testing. In the study by Gredin et al. (2018), in which the players performed a
similar task and received feedback for response time and accuracy after each trial, the
authors did not find any substantial performance effect when the initial 24 trials of a
conditions were compared to the final 24 trials of that condition. This finding suggests
that task experience, including feedback on performance after each trial, did not change
the players’ performance on the task. A related issue is the potential risk that the
retrospective verbal reports of thoughts may have disrupted the natural thought processes
in which the players engaged during task performance and, as such, influenced their
behaviours on the task. In order to mitigate this risk, the players undertook 25–40 min of
training on how to only report heeded thoughts in a way that they were naturally
experienced during the task, rather than trying to explain, justify, or qualify their
thoughts or behaviours during the task (see Eccles, 2012; Ericsson & Simon, 1980). In
summary, our findings suggest that the explicit provision of contextual priors biased
expert soccer players’ processing priorities during action anticipation: greater reliance
was placed on the priors and context-relevant visual information, while less reliance was
placed on evolving kinematic information. This, in turn, biased anticipatory judgements
toward the most likely outcome, given the contextual priors, and enhanced anticipation
performance. However, the biasing impact of explicit contextual priors, in regard to both
anticipation and associated thought processes, was supressed when the comparative
utilities associated with potential judgements differed. Under these conditions, the
players became less reliant on the contextual priors and unfolding visual information, and
more inclined to opt for the outcome associated with the highest rewards and the lowest
costs.


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<ART>Knowledge acquisition and research evidence in autism: Researcher and practitioner perspectives and engagement
================================================================================

Authors: Sarah J. Carrington, Mirko Uljarević, Alessandra Roberts, Louise J. White, Lynda Morgan, Dawn Wimpory, Christopher Ramsden, Susan R. Leekam
DOI: 10.1016/j.ridd.2016.01.011
Year: 2016  |  Pages: 126-134
ASJC codes: 3203, 3204
Keywords: Autism Spectrum Disorders, Knowledge sharing, Practice, Research

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Government policy and national practice guidelines have created an increasing need for autism services to adopt an evidence-based practice approach. However, a gap continues to exist between research evidence and its application. This study investigated the difference between autism researchers and practitioners in their methods of acquiring knowledge. Methods: In a questionnaire study, 261 practitioners and 422 researchers reported on the methods they use and perceive to be beneficial for increasing research access and knowledge. They also reported on their level of engagement with members of the other professional community. Results: Researchers and practitioners reported different methods used to access information. Each group, however, had similar overall priorities regarding access to research information. While researchers endorsed the use of academic journals significantly more often than practitioners, both groups included academic journals in their top three choices. The groups differed in the levels of engagement they reported; researchers indicated they were more engaged with practitioners than vice versa. Conclusions: Comparison of researcher and practitioner preferences led to several recommendations to improve knowledge sharing and translation, including enhancing access to original research publications, facilitating informal networking opportunities and the development of proposals for the inclusion of practitioners throughout the research process.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Government policy and national practice guidelines have highlighted an increasing need for
professionals working in autism services to adopt an evidence-based approach in the
delivery of diagnostic methods and clinical and educational interventions. However, a gap
continues to exist between research knowledge and its application in practice (Parsons et
al., 2013; Reichow, Volkmar, & Cicchetti, 2008). One factor that may contribute to this
gap is a difference between academic and non-academic professional groups in their
approach to acquiring knowledge of autism research. Practitioners’ views about what counts
as a credible knowledge source is historically influenced by their training and experience
(Rycroft-Malone et al., 2004). They may, therefore, routinely use different methods from
those used by researchers when updating their specialist professional knowledge and have
different views about how they could potentially benefit from research evidence in the
future. Greater understanding of these perspectives is therefore important for researchers
who are aiming to adapt scientific evidence to meet the needs of the wider, non-academic
community (Lemay & Sá, 2014). Effective knowledge translation into practice depends on
effective facilitation by researchers (Kitson, Harvey, & McKormack, 1998; Rycroft-Malone
et al., 2004), a goal that has been heightened by government policy in recent years by the
impact assessment of academic research (e.g. Research Excellence Framework, 2014;
http://www.ref.ac.uk/). It has been argued that attempts to bridge the research-practice
gap need to involve greater collaboration between autism researchers and research-users,
such that both communities are engaged in the research process from the beginning (Parsons
et al., 2013). Such collaborative activity, or engagement, can facilitate co-participation
in the development of research design and method through reciprocal exchange of knowledge.
Engagement between researchers and the people who use research is a central component of
interactive models of knowledge translation in health policy (Jacobson, Butterill, &
Goering, 2003) and a key facilitator of effective knowledge translation (Huberman, 1990).
It enables the researcher to orient towards the needs of the user group, provides
opportunities for discussion about the values and interpretation of evidence, and helps to
facilitate trust and collaboration between researchers and research-users (Milton, 2014;
Parsons et al., 2013). Recent research studies in the field of autism have highlighted the
importance of developing a research agenda that is oriented towards the research-user.
This work has identified topic areas that research-users prioritize as important areas for
future research (Pellicano, Dinsmore, & Charman, 2013; Pellicano, Dinsmore, & Charman,
2014a). Results showed that although researchers and research-users agreed on some of the
priorities for future research in autism, there was also a mismatch in priorities for
other areas. This research also reported a mismatch in the level of engagement reported by
researchers and research-users in the field of autism (Pellicano et al., 2013; Pellicano,
Dinsmore, & Charman, 2014b). While academic researchers perceive themselves to be engaging
with non-researchers, the same view is not held by non-research users of research. The
findings above emphasize that research should focus on priority areas that meet the needs
of the research-user community, a goal more likely to be fulfilled by improved engagement
between researchers and non-researchers. The focus of the current study was not on
priorities for what should be researched, as previously studied, but on the process of
knowledge acquisition. To investigate this, similarities and differences in the methods
and preferences for acquiring knowledge used by researchers and research-users were
examined, targeting individuals from one sector of the autism research-user community:
professional practitioners working in clinical, educational and policy settings. In this
respect our definition of ‘research-user’ is consistent with the definition used by Lemay
and Sá (2014) in a study of the translation of research evidence into professional
practice. If methods of knowledge acquisition differ, and researchers present evidence in
ways that are incompatible with the preferences of practitioners, communication will be
inhibited and the translation of research evidence impeded. Therefore, greater
understanding of the gap between research and practitioner groups in both their current
practice and future preferences will facilitate conditions for collaborative engagement
that starts from a more common ground and enable reciprocal exchange. The current
questionnaire study formed part of the development work for an online web-based initiative
being designed for the purpose of connecting research, practice, and policy communities.
In a set of three questions, researchers and professionals working in practice communities
were asked about how they use research information. First, both groups were asked how they
currently keep up to date with information in the field of autism. Second, both groups
were asked which methods they thought would be beneficial to increase research access and
research knowledge for research-users. This question necessarily focuses on the
translation of information from researchers to research-users, to help explore issues
about the inadequacy of the communication of research evidence to non-research
professionals. Finally, researchers and practitioners were asked to report on their
current level of engagement with the other community. This question was intended as a
general measure of the extent to which each group felt that they had any form of active
involvement with the other community and was intentionally non-specific, to capture any
form of interaction or engagement. It was expected that the two groups would use different
sources of information to keep up to date with professional knowledge, with researchers
relying more on primary evidence sources and practitioner research-users relying on
alternative evidence sources. However, it was not known if views would differ about the
best methods for increasing research knowledge in the non-academic community. Better
understanding of potential differences between these groups may identify mechanisms by
which knowledge sharing could be improved. Finally, based on previous findings, it was
expected that practitioners would report lower levels of engagement with researchers than
vice versa.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total number of 683 respondents answered at least one of the three questions. Two
hundred and sixty one respondents described themselves as working in the area of practice
or policy. When asked to specify their occupation, of these 261, the two largest
occupational groups represented were professionals working in schools (teachers or
teaching/learning assistants; n = 55), and psychologists, including educational, clinical
and occupational psychologists (n = 47). Other occupational groups included speech and
language therapists (n = 21), psychiatrists (n = 5), nurses (n = 3), support workers (n =
16) and social workers (n = 6). Nine respondents stated that their occupation included
both “policy work” and practice roles, with a further two indicating that their primary
occupation was “policy work”. Eighty-two respondents selected “Other” and a further 26 did
not respond to this question. The title of ‘practitioner’ group was therefore assigned, to
include a range of professionals working in clinical, educational, and policy-based
practice. In the research professional group (n = 422), the majority described themselves
as either established career researchers (including completed a PhD, working in research;
n = 256) or early career researchers (including post-graduate, research assistant or
associate, or PhD student; n = 143). A minority (n = 17) selected “Other”, which included
retired or freelance/independent researcher, and six gave no response. Researchers were
also asked in which country they worked.1 There were 147 researcher responses from North
America, 137 from Australia/New Zealand, and a further 108 from elsewhere in the UK. The
remaining respondents (n = 30) came from a range of countries including Serbia, Japan,
South Korea, Argentina, South Africa, Columbia and Singapore.

<hs>  Design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

The survey questions were first designed for practitioners and trialled on a first ‘wave’
set of 54 local professionals from clinical, educational and policy sectors recruited
through professional contacts in two neighbouring regions of Wales (UK), in order to
identify potential problems. Concurrent with this initial trial of the survey, a separate
sample of eight local autism professionals from teaching, occupational therapy, speech and
language therapy, care work and educational psychology professions were recruited through
professional contacts to take part in 40 minute telephone/face-to-face interviews using a
semi-structured, open-ended interview format. The interviews focused on the topics of
evidence-based practice, research colleagues, and collaboration. Responses from these
interviews revealed broad themes that were consistent with the online survey questions and
response options. The survey was then distributed to the researcher group in addition to
the geographically wider practitioner community without alterations. The survey was
written and distributed only in English. The data for the main survey were collected via
Google Survey over a period of three weeks in August 2013. The online survey was also sent
to UK professionals and two international email lists made up of both practitioners and
researchers who attended face-to-face or online professional conferences. Consistent with
previous online surveys of this type (e.g. Pellicano et al., 2014a, 2014b), a snowball
method of sampling was used. The link was shared extensively via national and
international email contact lists and social media, and recipients were encouraged to
forward it to colleagues, resulting in a ‘cascade’ distribution. Emails were sent out
three times inviting people to respond. The survey was shared on Twitter and Facebook
weekly. The written introduction to the survey explained that the questions formed part of
the planning and design stage for a new knowledge hub initiative aiming to improve
connections between autism researchers and non-academic professionals, and that the survey
aimed to compare the needs and views of different professional groups. Ethical approval
was obtained from the University's School of Psychology Ethics Committee. All participants
gave informed consent on the first online page of the questionnaire prior to
participating. Participants were first asked to indicate if they were a researcher or a
professional working in practice or policy. Both groups were asked about the methods they
use to access information: “At the moment, how do you keep up to date with current
information in the area of autism?” Respondents were asked to select their top three
options out of a possible ten (see Fig. 1 for summarized response options). In a separate
question, respondents were asked to identify methods that they perceived would be
beneficial for increasing research access and research knowledge (see Fig. 2 for response
options). Non-academic professionals were asked “Of the options below, which would help
you benefit most from research knowledge and evidence in your specialist area of autism?”
Respondents were asked to select their top three options out of a possible nine. The
researcher version of the questionnaire asked a similar question, which aimed to elicit
researchers’ views of what would help most to promote engagement, research awareness and
knowledge translation in practice and policy communities: “The [online initiative] aims to
engage researchers with non-academic professionals, promote awareness of research and
create opportunities to translate research knowledge. Which options below do you think
would help achieve this aim? Tick your top three”. The identical response options for both
groups are shown in Fig. 2. Both questions included an ‘other’ option. Finally, both
groups were also asked about their level of engagement with research or non-research
professionals: either “As a practitioner or working in policy in autism, do you currently
engage with researchers?” or “As a researcher in autism, do you currently engage with
practitioners or those working in policy?” To reduce the potential carry-over effect of
responses, the questionnaire design presented the following fixed order: (1) methods for
improving research knowledge question, (2) methods for updating of current information
question, (3) engagement with the other professional group question.

<hs>  Updating of current information</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Each participant was asked to select their three preferred methods of keeping up to date
with current information. Six participants, all researchers, did not endorse any items and
were excluded. Of the remaining participants, 233 (89%) practitioners and 336 (81%)
researchers selected three options. The distribution of choices for the sample selecting
three options is shown in Fig. 1. Two-by-two Chi square analyses compared group
differences for each option, with alpha level set at .005 following Bonferroni correction
for multiple comparisons. The following information options were selected significantly
more frequently by practitioners than researchers: campaigns: χ2(1) = 28.52, p < .001 (20%
practitioners, 5% researchers); non-academic journals: χ2(1) = 15.10, p < .001 (23%
practitioners, 11% researchers); conferences and Continuing Professional Development
(CPD): χ2(1) = 14.26, p < .001 (64% practitioners, 48% researchers); newspapers, online
news, TV and radio: χ2(1) = 7.93, p = .005 (29% practitioners, 19% researchers). In
contrast, the following options were selected more frequently by researchers than
practitioners; colleagues: χ2(1) = 20.94, p < .001 (74% researchers, 55% practitioners);
academic journals: χ2(1) = 142.77, p < .001 (91% researchers, 45% practitioners). The top
three options for each group overlapped, although the order of these differed. The most
frequently endorsed option for practitioners was conferences/CPD courses (64%) followed by
colleagues (55%) and academic journals (45%), while the most frequently endorsed option
for researchers was academic journals (91%), followed by colleagues (74%) and conferences
(48%). No group differences (p > .005) were found for Google searches (31% practitioners,
25% researchers), membership of voluntary organizations (19% practitioners, 11%
researchers), or social media (8% practitioners, 9% researchers) and there was no
difference in the “other” category (7% practitioners, 6% researchers). Analyses were re-
run including participants who failed to endorse all three choices. Results were identical
with the exception of one additional group difference for voluntary organizations, which
was favoured by practitioners (χ2(1) = 9.28, p < .002; 18% practitioners, 10%
researchers).

<hs>  Increasing research knowledge</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Each participant was asked to select the three methods that they considered most
beneficial for increasing research access and knowledge (their top three). The question to
practitioners asked which methods would most benefit their own research knowledge and
evidence in their specialist area of autism (top three choices), while the question to
researchers asked which would help promote research awareness and opportunities for
knowledge translation in non-academic professionals. Eleven respondents (all of whom were
researchers) did not endorse any items and were excluded. Of the remaining participants
228 practitioners (87%) and 389 researchers (95%) endorsed three choices. Fig. 2 compares
the choices of the respondents who selected three choices. As above, 2×2 Chi square
analyses were computed to compare groups for each option, with alpha level set at .006
using Bonferroni adjustment for multiple comparisons. The following options were selected
significantly more frequently by practitioners than researchers: connect directly to
research articles to read original research: χ2(1) = 29.09, p < .001 (58% practitioners,
36% researchers); access to practice based articles that have been based on reliable
research: χ2(1) = 11.47, p < .001 (61% practitioners, 47% researchers). In contrast, the
following options were selected more frequently by researchers: speak to a researcher to
ask questions about specific research findings: χ2(1) = 27.59, p < .001 (35% researchers,
15% practitioners); access a large directory of researchers to find out about research
and/or develop opportunities for collaborating: χ2(1) = 8.72, p < .005 (45% researchers,
33% practitioners). The most frequently endorsed option for practitioners was access to
practice-based articles based on research (61%), followed by connect directly to research
articles (58%) and then learn to apply evidence-based research methods (45%). For
researchers the most frequently endorsed option was non-technical one-page lay summaries
(50%), followed by access to practice-based articles based on research (47%) and access a
large directory of researchers (45%). No group differences were found for researchers’
blogs (16% practitioners, 23% researchers), non-technical one-page summaries (43%
practitioners, 50% researchers), Twitter or news updates (26% practitioners, 23%
researchers) or apply evidence-based research methods to use in practice and policy (45%
practitioners, 40% researchers). Analyses were re-run to include all those participants
who did not endorse the full three choices; the results were identical.

<hs>  Engagement with the other professional group</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Eight practitioners and one researcher did not respond to this question. Table 1 shows the
current level of inter-group engagement reported by the remaining practitioners (n = 253)
and researchers (n = 421). Researchers reported significantly higher levels of engagement
with practitioners than practitioners reported for their level of engagement with
researchers (χ2(3) = 87.03 p < 0.001); the majority of researchers (56.3%) indicated that
they had either “a lot” or “quite a bit” of engagement with practitioners, while the
majority of practitioners (79.1%) reported that they only “occasionally” had engagement
with researchers, if at all.

<h>DISCUSSION</h>
----------

This study presents the first evidence of similarities and differences between researchers
and practitioners working in autism in their preferred methods for acquiring up-to-date
information and gaining research knowledge. The focus on a professional practitioner
research-user group in the current study specifically aimed to facilitate greater
understanding of the incompatibility in preferred methods used by researchers and
professional practitioners. By identifying gaps in the way that researchers communicate
research evidence it may be possibly to highlight potential targets for evidence-based
approaches in clinical, educational and policy-based practice. Multi-dimensional
approaches to knowledge translation (Kitson et al., 1998; Rycroft-Malone et al., 2004)
have emphasized the importance of the nature and accessibility of the research evidence to
be translated. In the current study we examined the evidence sources that practitioners
prefer to use when updating their knowledge and the methods that they consider would help
them benefit from research knowledge and evidence. Previous work on knowledge translation
in areas of health and education indicates that practitioners can be resistant to learning
about and accepting research evidence (Parsons et al., 2013; Russell, Greenhalgh, Boynton,
& Rigby, 2004; Rycroft-Malone et al., 2004), and indicate preferences for accessible,
practitioner-relevant and non-technical sources of evidence information (Graham, Tetroe, &
Gagnon, 2013). Specific work in the area of autism has also emphasized practitioners’
priorities for accessing practitioner-oriented methods in the area of intervention
(Reichow et al., 2008). When both researchers and practitioners were asked about how they
keep up to date with current information, their responses showed that the preferred
current sources of information for practitioners were conferences and continuing
professional development (CPD). There was also evidence that practitioners relied more
than researchers on publicly accessible sources of knowledge such as news media and
campaigns, as well as on non-academic journals. In general, however, more accessible
methods of updating current information, such as social media, Google searches and
news/TV, were of relatively low priority for practitioners. Researchers differed from
practitioners in their methods for keeping up to date with current information due to
their highly frequent use of academic journals compared with practitioners. However they
were similar in their low priority for social media and other accessible evidence sources.
When researchers and practitioners considered what would be beneficial for increasing
their research knowledge, the most notable finding was the high value given by
practitioners to original articles from academic journal articles. Another notable
difference was that researchers gave higher scores than practitioners to the options
relating to direct contact with researchers (access to researcher directory to find out
about research or develop opportunities for collaborating and speak to a researcher).
Finally, both groups were in agreement about their priorities for learning to apply
evidence-based research methods and accessing non-technical research summaries, both of
which were highly rated. Again, more accessible methods such as social media were of
relatively low priority for both groups and showed no difference between the groups.
Finally, when asked about level of engagement with the other group, the results for the
current study supported Pellicano et al.’s (2014b) earlier finding. We found that
practitioners reported relatively lower levels of engagement in comparison to the level of
engagement reported by researchers; that is, researchers identified themselves as more
highly engaged with the practitioner community than vice versa. One potential explanation
for this discrepancy could be the perceived impact of engagement in the two fields; while
researchers may more directly perceive the benefits of involving the practitioner
community in designing and conducting research, the outcome of research and the
implications for practice may be felt only over a longer time-frame. Practitioners may,
therefore, feel less engaged by the research community as the impacts of any involvement
may be less immediately tangible. Alternatively, this discrepancy could reflect
differences in the perceived value of research evidence and practitioner expertise; if
practitioners felt that research evidence was valued more highly than evidence coming from
their own knowledge and expertise, they may be less likely to engage with the research
community. The questionnaire in the current study did not allow us to explore these
issues, but these findings highlight that an important area for further investigation will
be to clarify differences in the definition and value of what counts as evidence and to
facilitate more reciprocal recognition of both research and practitioner expertise. Taking
the results from all three questions together, the findings show a pattern in which
researchers and practitioners not only have mismatched perceptions of engagement with each
other, but also have different views about how to best facilitate the communication and
sharing of research knowledge. For practitioners, direct access to original research
articles in academic journals is prioritized very highly as a beneficial method for
increasing research knowledge, while access to researchers themselves (speaking to a
researcher or accessing a directory of researchers) is prioritized more highly by
researchers. There are also important similarities between the two groups; for example,
both assign relatively low ratings to social media as a mechanism for accessing and
gaining research knowledge. Moreover, the top three options for updating current
information in both groups were conferences or CPD, academic journals, and colleagues.
Although the order of these options differed in the two groups, this overlap suggests that
practitioners and researchers use the same mechanisms to update their current research
knowledge, with a desire by the practitioner group in this study to access original
research articles from academic journals. These findings have important implications for
the effective translation of research knowledge, indicating the ways in which research
evidence may best be made accessible to meet the preferences of practitioners. The
findings also have some limitations and raise issues for both for the design of future
studies and for initiatives directed at researcher-practitioner engagement. With respect
to limitations, the two samples were not completely representative. The practitioner
group, who had responded to a request to complete an online survey may already have been
motivated towards research. Moreover, as recruitment included the use of email contact
lists, some of which originated from conference delegate lists, the sample may have had an
interest in research to some degree. Similarly, researchers who completed the survey were
likely to have an interest in communicating research findings beyond the academic
community. It could also be argued that as respondents were aware that the purpose of the
survey was to inform the development of a new knowledge hub aiming to improve connections
between autism researchers and practitioners, their responses may have been biased,
reflecting a desire to demonstrate good practice both in terms of accessing research
information and engaging with other communities. This potential bias highlights the
limitations of self-report measures, which are dependent not only on the honesty of
respondents but also on the accuracy of their evaluation of their own behaviour. A further
potential limitation of the design of the survey could be that the response options for
all three questions were presented as a list and in a fixed order. However, this did not
appear to affect the results, as when asked which methods would be most beneficial in
increasing access to research knowledge, the top three for both groups included options
from the second half of the list. Moreover, some aspects of the question wording might
suggest that caution should be applied when interpreting some of the responses options.
For example, the relevant question posed to the researcher and non-academic professional
groups regarding methods beneficial for increasing knowledge, differed slightly; however,
this difference was necessary, as the aim in the current study was specifically to
identify methods that would be beneficial for increasing practitioners’ research access
and knowledge. Finally, some missing demographic information limited the potential for a
fuller interpretation of the results. Although researchers were asked to indicate their
current status as either early or established career researcher (or other), thus giving
some indication of their level of experience, the practitioner group were not asked about
their level of experience. Nor was either group asked to indicate their age or gender. It
seems likely that some or all of these characteristics could potentially influence
respondents’ perceptions and use of social media and technology. However, there were no
significant differences in how the research and practitioner groups rated their use, or
the perceived benefits, of social media and technology, suggesting that if there were
differences in age, gender, or experience between the two groups, these differences did
not unduly affect the findings. The relatively low priority placed on social media and
other more accessible methods, however, is perhaps surprising given the prevalence of
blogs and twitter postings from well-established researchers, research organisations, and
charities. Moreover, the survey was advertised using e-mail and social media, and as such,
some role for social media could have been expected. The reported lack of importance
placed on social media and Google searches may have reflected recognition that some media
sources are not necessarily direct scientific sources; that is, they may be brief,
simplified interpretations of the evidence. This issue could be further explored by more
specifically probing dependence on different types of social media, distinguishing between
postings from credible research organisations or charities (e.g. the National Institute
for Health and Care Excellence) and more general postings or comments on research findings
in the mainstream media. In their ethnographic study of professionals working within
Public Health Units, Lemay and Sá (2014) found that practitioners primarily relied on
academic literature accessed through journals or professional training and communications
to update their research knowledge. The group of professionals were actively engaged in
using research to develop and implement evidence-based practice. Given the recruitment of
a research-user group in the current study that was similarly focused on professional
practice, a similar priority placed on more formal sources of research information was
perhaps to be expected. Finally, it might be argued that that asking participants to
indicate only three sources of information in the current questionnaire may have
underestimated the role of more accessible sources such as social media. However, by
constraining participants’ choice in this way, priorities were more clearly identified.
The results from the current study indicate that more accessible methods such as social
media were not given high priority by either group, suggesting that other sources were
considered more informative or reliable. Further research is needed to identify the role
played of social media in knowledge acquisition in this field. Other issues may be
addressed in the design of future studies. For example, the design of the questionnaire
did not allow for identification of differences between distinct practitioner groups
working in either health or education practice who might hold different views. Further
exploration of the preferences and priorities of the groups would also be helpful. For
example, when selecting the top three options that would be beneficial for facilitating
access to research knowledge, ranking of preferences would provide richer data. Another
important future direction for further research is in understanding how both researchers
and practitioners assess the quality of the research that they access. Improving
practitioners’ confidence in their evaluation of the available evidence could empower them
to apply the findings from research in their practice. Practitioners’ preferences
regarding access to academic journals were a key finding. It is possible that very recent
policy changes in open access publishing of academic research articles may be already
reducing barriers to knowledge access. However, practitioners’ needs in this respect
should, be continually reviewed and we recommend that researchers are attentive to the
importance of making their published findings easily accessible for practitioner use.
Another way to address the desire to access and use research is through a scientific
training ‘master-class’ method that has proved to be effective for increasing research
competencies in public health professionals (Jansen & Hoeijmakers, 2013), which also gives
opportunity for direct contact and engagement. These ‘master-classes’ could be further
extended to include training in the application of evidence-based practice, which was one
of the top three options selected by practitioners as being beneficial in translating
research knowledge. Previous commentary on the gap between research knowledge and practice
in autism emphasizes the need to build new research evidence based on collaboration
between research and non-research professionals (Parsons et al., 2013), a view that is
also consistent with interactive models of knowledge translation in health sectors
(Jacobson et al., 2003). Research evidence in the area of autism, however, indicates that
research-users, including practitioners, family members and adults with autism, may
experience low levels of engagement with researchers (Pellicano et al., 2014b).
Differences in reported experiences of engagement by researchers and practitioner groups
reported in this study point to the need to provide direct face-to-face contact and real
world shared activities to improve mutual understanding with stakeholders. Mottron (2011)
has highlighted the considerable insight that can be gained by including individuals with
autism in all aspects of the research process – including the design, implementation, and
interpretation of studies. Similar engagement between academic researchers and
practitioners in clinical, educational and social care professions is also vital. We
recommend that opportunities are increased for informal contact and equitable
collaboration in the design of research studies, from the beginning of the research
process (Parsons et al., 2013). In so doing, it will be possible to build stronger
communication channels, more trusting relationships and a shared interpretation of
research with practice professionals and other users (Milton, 2014; Parsons et al., 2013).
This study investigated just one aspect of the complex pattern of knowledge sharing
relevant for effective translation of research evidence into practice. Its focus was to
explore views about access to research information and levels of engagement experienced.
As such it might be considered as the tip of an iceberg, with a number of other barriers
to evidence based practice still unexplored. The translation of research evidence into
practice is a complex process and the relationship between researchers and research-users
is not simply one of knowledge provider and user. Models that focus on the interactive
nature of knowledge sharing between members of different academic and non-academic
communities, stress the importance of active engagement between members. Yet it is
important to acknowledge the notable lack of work in this area and the need to build
initial foundations for such models. Building these foundations may first require the
study of knowledge translation from researcher to researcher-user, and then trace the
complementary influence of research-user expertise on research as a result of engagement
and collaboration over time. Furthermore, as Mitton, Adair, McKenzie, Patton, and Waye-
Perry (2007) points out, there is remarkably little formal evaluation of the actual
effectiveness of the application of knowledge translation strategies in context. We
recommend a new focus within basic research to ensure better understanding of “what works
for whom and in what circumstances”. The results from the current study support a
recommendation to provide access to a range of research-based information in the
development of an online knowledge platform, from non-technical summaries to access to
original research articles. Our findings also point to the need for improved engagement
and communication, and continual review of user needs and the barriers to research
implementation in practice. However, it is essential that future work should more fully
characterize a range of potential factors that hinder knowledge sharing and translation in
order to best integrate research and practice in autism.


<h>REFERENCES</h>
----------

  [3] Nora Jacobson, Dale Butterill, Paula Goering. Development of a framework for knowledge translation: Understanding user context. doi:10.1258/135581903321466067
  [4] Maria W.J. Jansen, Marjan Hoeijmakers. A masterclass to teach public health professionals to conduct practice-based research to promote evidence-based practice: A case study from the Netherlands. doi:10.1097/PHH.0b013e318225158a
  [5] Alison Kitson, Gill Harvey, Brendan McCormack. Enabling the implementation of evidence based practice: A conceptual framework
  [6] Margaret A. Lemay, Creso Sá. The use of academic research in public health policy and practice. doi:10.1093/reseval/rvt029
  [7] Damian E.M. Milton. Autistic expertise: A critical reflection on the production of knowledge in autism studies. doi:10.1177/1362361314525281
  [8] Craig Mitton, Carol E. Adair, Emily McKenzie, Scott B. Patten, Brenda Waye Perry. Knowledge transfer and exchange: Review and synthesis of the literature. doi:10.1111/j.1468-0009.2007.00506.x
  [9] Laurent Mottron. Changing perceptions: The power of autism. doi:10.1038/479033a
  [10] Sarah Parsons, Tony Charman, Rachel Faulkner, Jude Ragan, Simon Wallace, Kerstin Wittemeyer. Commentary - Bridging the research and practice gap in autism: The importance of creating research partnerships with schools. doi:10.1177/1362361312472068
  [12] Elizabeth Pellicano, Adam Dinsmore, Tony Charman. What should autism research focus upon? Community views and priorities from the United Kingdom. doi:10.1177/1362361314529627
  [13] Elizabeth Pellicano, Adam Dinsmore, Tony Charman. Views on researcher-community engagement in autism research in the United Kingdom: A mixed-methods study. doi:10.1371/journal.pone.0109946
  [14] Brian Reichow, Fred R. Volkmar, Domenic V. Cicchetti. Development of the evaluative method for evaluating and determining evidence-based practices in autism. doi:10.1007/s10803-007-0517-7
  [16] Jill Russell, Trisha Greenhalgh, Petra Boynton, Marcia Rigby. Soft networks for bridging the gap between research and practice: Illuminative evaluation of CHAIN. doi:10.1136/bmj.328.7449.1174
  [17] Jo Rycroft-Malone, Gill Harvey, Kate Seers, Alison Kitson, Brendan McCormack, Angie Titchen. An exploration of the factors that influence the implementation of evidence into practice. doi:10.1111/j.1365-2702.2004.01007.x
<ART>Labels constructively shape object categories in 10-month-old infants
=====================================================================

Authors: Nadja Althaus, Gert Westermann
DOI: 10.1016/j.jecp.2015.11.013
Year: 2016  |  Pages: 5-17
ASJC codes: 3204, 3205
Keywords: Categorization, Cognitive development, Eye-tracking, Infancy, Language acquisition, Language and cognition

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

How do infants’ emerging language abilities affect their organization of objects into categories? The question of whether labels can shape the early perceptual categories formed by young infants has received considerable attention, but evidence has remained inconclusive. Here, 10-month-old infants (N = 80) were familiarized with a series of morphed stimuli along a continuum that can be seen as either one category or two categories. Infants formed one category when the stimuli were presented in silence or paired with the same label, but they divided the stimulus set into two categories when half of the stimuli were paired with one label and half with another label. Pairing the stimuli with two different nonlinguistic sounds did not lead to the same result. In this case, infants showed evidence for the formation of a single category, indicating that nonlinguistic sounds do not cause infants to divide a category. These results suggest that labels and visual perceptual information interact in category formation, with labels having the potential to constructively shape category structures already in preverbal infants, and that nonlinguistic sounds do not have the same effect.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

One of the central questions in early language and cognitive development is how the
emergence of language affects infants’ preverbal understanding of the world. During the
past 20 years, many studies have shown that even very young infants can rapidly form
categories on the basis of the static perceptual features of objects (Behl-Chadha, 1996;
French, Mareschal, Mermillod, & Quinn, 2004; Mareschal & Quinn, 2001; Oakes, Coppage, &
Dingel, 1997; Quinn, 2002, 2004; Quinn & Eimas, 1996) and that during the first year of
life these early categories are gradually enhanced with more sophisticated knowledge such
as feature correlations, sounds, motion, function, and animacy cues (Baumgartner & Oakes,
2011; Burnham, Vignes, & Ihsen, 1988; Pauen & Träuble, 2009; Perone & Oakes, 2006; Younger
& Cohen, 1986). Other research has shown that in older children language can shape object
categories by enabling the grouping together of perceptually dissimilar objects (e.g.,
dogs and whales as mammals) and the separation of similar objects (e.g., bats and birds)
into different categories as well as forming the basis for inferences about hidden object
properties (Graham, Kilbreath, & Welder, 2004; Welder & Graham, 2001). There is also
evidence that labeling aids object individuation by 12 months of age (Xu, Cote, & Baker,
2005), and even younger infants at 9 or 10 months expect different labels to refer to
different kinds of object (Dewar & Xu, 2007, 2009). However, although several studies have
investigated the emerging effect of language on categorization during the first year of
life, they have yielded little agreement and it is not yet clear how linguistic
information interacts with object representations that have developed preverbally. Two
separate questions have been asked about the role of language in infants’ object
categorization during the first year of life. The first is whether labels can facilitate
object categorization, that is, whether the labeling of objects enables infants to form
categories that they would not form without labels. The second question is whether, like
in older children, labels can override nonverbal perceptual information and change the
structure of perceptual categories when visual similarity and category labels are in
conflict with each other. Much of the work exploring early categorization is based on the
familiarization/novelty preference procedure (Fantz, 1964), which relies on the fact that
infants tend to spend more time looking toward novel objects than toward familiar objects.
In a typical study, infants are familiarized with a sequence of objects from one category
and are then tested with two new objects—one a novel member of the familiarized category
and one from a different category. If infants show a looking preference to the object from
the new category, it can be concluded that they have formed a category that includes the
novel within-category object but excludes the object from the different category. The
emerging ability of language to shape categories has been studied in variants of this
paradigm in which the objects presented during familiarization are accompanied by auditory
labels or other sounds and the effect on infants’ looking preferences during test are
investigated. The question of whether labels facilitate category formation has been
addressed in several studies by Waxman and colleagues (Balaban & Waxman, 1997; Booth &
Waxman, 2002; Ferry, Hespos, & Waxman, 2010; Fulkerson & Waxman, 2007; Waxman & Braun,
2005; Waxman & Markow, 1995). For example, in a seminal study, Balaban and Waxman (1997)
showed that infants who were familiarized with a sequence of pig drawings exhibited at
test a looking preference for a rabbit over a novel pig only when the familiarization
items were accompanied by a labeling phrase (“A pig!”) but not a tone sequence.
Unsystematic labeling with different novel words did not lead to category formation in
12-month-olds (Waxman & Braun, 2005). Other studies have aimed to provide evidence that
consistent novel labels facilitate categorization in infants at 6 months of age and even
at 3 or 4 months (Ferry et al., 2010; Fulkerson & Waxman, 2007). This and other work has
led to the claim that words serve as “invitations to form categories,” enabling category
formation by highlighting commonalities between objects with the same label (Waxman &
Markow, 1995). However, two considerations appear to weaken this claim. First, as
described, many studies have shown that preverbal infants as young as 3 months can form
perceptual categories in the absence of any auditory input, and these early categories can
be at the basic or superordinate levels (Behl-Chadha, 1996; Quinn & Eimas, 1996). On this
basis, it seems plausible that, in silence, 9-month-olds may be able to form a perceptual
category of the stimuli used in the studies described above (e.g., a category of pigs that
is different from rabbits). Because the described labeling studies did not involve a
control condition in which the objects were presented in silence, it is difficult to
assess whether labels had an effect above and beyond purely visual information (Plunkett,
Hu, & Cohen, 2008; Robinson & Sloutsky, 2007a). Sloutsky and Napolitano (2003) and
Sloutsky and Robinson (2008) have aimed to reconcile the results from categorization-in-
silence studies and categorization-with-labels studies by arguing that, far from
facilitating categorization, auditory information instead interferes with visual
processing and, therefore, disrupts category formation when categories would have been
formed in silence. According to this “auditory overshadowing hypothesis,” labels disrupt
category formation less than other auditory stimuli because they are highly familiar
auditory signals. Therefore, visual categories that are learned in silence can still be
formed in the presence of labels, but tone sequences usually disrupt visual category
formation (Robinson & Sloutsky, 2007a, 2007b). A second limitation of the described
labeling studies is that they familiarized infants with only a single category. Even if we
assume that labels have a facilitative effect above and beyond presentation in silence,
such a paradigm cannot answer the question of whether labels constructively interact with
preverbal representations to shape category structures. It is a well-known finding that
infants’ attention is maintained longer in the presence of labels compared with silence
(Althaus & Mareschal, 2014; Baldwin & Markman, 1989; Robinson & Sloutsky, 2007a). The
processes involved in this longer looking period may well have to do with more intensive
visual processing, but not necessarily in the sense of using the information given by the
label to adjust category boundaries. In familiarization with a single category, an
increase in novelty preference might simply be the outcome of an effectively prolonged
stimulus exposure. The question of a constructive role of category labels can be addressed
by familiarizing infants with two separate but visually similar categories with two
distinct labels simultaneously. This is similar to word learning studies that test whether
infants can associate words and (individual) objects (Mani & Plunkett, 2008; Schafer &
Plunkett, 1998; Werker, Cohen, Lloyd, Casasola, & Stager, 1998). This paradigm can then be
used to answer the two questions posed above. If infants do not form categories in silence
but are successful under labeling, then labels facilitate category formation. If infants
successfully categorize in silence but form different categories under labeling, then
labels can serve to override visual information. Plunkett and colleagues (2008) reported a
two-category study, using a set of stimuli introduced by Younger (1985). These stimuli
consisted of two sets of line drawings of schematic animals based on the same set of four
distinctive features. In the “broad” set, features were combined such that there were no
discernable clusters of stimuli; the eight stimuli formed a single large category. In the
“narrow” set, the feature values were correlated (e.g., long-necked animals always had
thick tails), and based on these correlations two subcategories of four stimuli could be
formed. In Younger’s study, 10-month-old infants were familiarized with the animal
drawings in silence. Younger found that the infants were sensitive to the feature
correlations and formed a single category for the broad set but formed two distinct
categories for the narrow set. In a separate study, Younger and Cohen (1986) showed that
4-month-old infants were not able to make use of feature correlations, indicating that
this ability develops between 4 and 10 months of age. Plunkett and colleagues (2008)
introduced labeling into Younger’s (1985) paradigm. When 10-month-old infants were
familiarized using the broad stimulus set and were provided with the same label (“Look!
Dax!”) for every stimulus, they formed one category, just like in silence. Likewise, when
infants were familiarized with the narrow stimulus set and heard two different labels
corresponding to the two subcategories, they formed two categories, again like in the
silent case. However, importantly, when infants saw the narrow stimulus set but heard the
same label for each stimulus, they formed a single category. Plunkett and colleagues
argued that in this case the labels served to override visual categorization, leading
infants to merge two perceptually distinct categories when they shared a common label.
However, these results leave open an alternative explanation, namely that forming two
categories in the narrow condition depended on infants’ ability to detect feature
correlations, an ability that develops between 4 and 10 months of age. It is possible that
the added complexity of the condition in which visual information (two categories) and
labels (one label) were in conflict led to overloading the infants, resulting in a more
shallow processing of the visual information. This explanation is compatible with results
showing that when complex stimuli (e.g., conflicting visual and auditory information)
overload the learning system, infants can regress to an earlier level of processing—here,
that of 4-month-olds (Cohen, Chaput, & Cashon, 2002). In this case, instead of infants
constructively using label information to merge two distinct categories, they could merely
have failed to detect the feature correlations that define the two categories in the first
place and, like 4-month-olds, formed a single category of the visual stimuli. One way in
which to exclude the possibility that labels merely lead to shallower object processing is
to conduct a study with a similarly ambiguous visual stimulus set that is in the absence
of labels perceived as a single large category but that is parsed into two subsets when
two distinct labels are presented. In other words, distinct labels cause infants to divide
a large category rather than a single label causing them to merge two sets of objects. In
this case, deeper processing is a prerequisite for the change in category boundary because
a more detailed representation is necessary for subcategory formation. Such a result would
constitute evidence for a constructive effect of labels. This is the approach taken in our
study. In sum, previous work with infants at the transition to language has not provided a
coherent picture of how nonlinguistic and linguistic information interact in category
formation. In particular, the central question of whether labels can guide the structure
of object categories in preverbal infants remains open. Demonstrating such a constructive
role requires the following methodological considerations. First, a labeling condition
should be contrasted with a silent condition to ensure that labels have an effect beyond
the visual information alone. Second, infants should be familiarized with a stimulus set
that allows parsing into one or two categories to show that labels can shape the encoded
category structure in a way that goes beyond merely enhancing attention. Third, the task
should be designed so that category formation in the presence of labels cannot be
explained by the processing of less visual detail than when familiarized in silence. A
fourth point concerns the difficulty of ensuring that looking preferences represent
novelty preference rather than familiarity preference. Previous work has demonstrated that
infants’ mode of preference can change as a function of task complexity or duration of
exposure (Hunter, Ames, & Koopman, 1983; Roder et al., 2000). Because the addition of (one
or more) auditory stimuli arguably changes task complexity, a test trial including a
visually novel test item is necessary to establish whether infants display a novelty
preference (longer looking at the novel test item) or a familiarity preference (shorter
looking at the novel stimulus) (Cohen, 2004; Oakes, 2010). Note that Plunkett and
colleagues (2008) did not include a novel test stimulus, which complicates interpretation
of their results. Here, we describe a study based on these considerations. We presented
infants with a set of objects that we expected to be perceived as a single category when
viewed in silence, and we asked whether pairing half of the objects with one label and
half with another label would lead infants to split the objects into two categories
according to their labels. This would require infants to use more detail for
categorization with labeling than in the silent condition. We constructed a set of stimuli
by morphing a drawing of one novel animal into a drawing of a distinct second animal in a
fixed number of steps, thereby obtaining a set of perceptually equidistant stimuli over
which it was possible to define categories as well as subcategories (at either end of the
morphing continuum) and their averages. The overall logic of our study followed that of
Younger (1985), but here differences between objects were based not on the variation in
distinct features but rather on a holistic difference achieved by the morphing process.
Infants were familiarized with eight objects either in silence, with one label, or with
two labels. If labels serve to constructively shape category structure, infants should
form a single category comprising all stimuli when familiarized in silence or when
accompanied by a single label but should form two categories when two distinct labels are
provided.

        <hss>Participants</hss>

        A total of 63 full-term 10-month-old infants participated in this study (mean age
        = 302 days; 28 girls). Infants were randomly assigned to either a silent condition
        (n = 20), a two-label condition (n = 20), or a one-label condition (n = 23). One
        additional infant was tested but excluded due to technical problems. Infants were
        recruited on a voluntary basis via local advertisements. Informed consent was
        received from the caregivers, and infants received a small gift for their
        participation.

            <hss>Visual stimuli</hss>

            The familiarization and test stimuli are depicted in Fig. 1. All stimuli were
            obtained by morphing Stimulus 1 into Stimulus 19 in 18 steps using the
            software MorphMagic. To ensure discriminability of the individual exemplars,
            only every second morphed image was used in the familiarization set. The gap
            between Stimuli 7 and 13 ensured that there was a visual grounding for a
            division into two separate subcategories (Stimuli 1, 3, 5, and 7 and Stimuli
            13, 15, 17, and 19, respectively). Choice of test stimuli followed the design
            of Younger’s (1985) study. It was assumed that infants forming one broad
            category would find the overall average stimulus (here, Stimulus 10) less
            novel than more peripheral stimuli (here, Stimuli 4 and 16). Conversely,
            infants who form two categories should find the overall average more novel
            because it falls between the categories but should not show preference for the
            peripheral stimuli because they now fall into the center of each of the two
            categories. A novel test animal was constructed to establish whether infants
            were showing novelty or familiarity preference at test. The familiarization
            stimuli were depicted against a white background and presented on either the
            left or right half of the screen (counterbalanced such that no regular
            structure emerged). Stimuli subtended approximately 16 degrees visual angle on
            the screen. Roughly half of the infants saw the stimuli facing left, and the
            other half saw them facing right. The test stimuli were depicted pairwise
            facing in the same direction as the familiarization stimuli, either depicting
            the overall average (10) next to one of the subcategory averages (4 or 16) or
            depicting one of the average objects (10, 4, or 16) alongside the novel
            animal. This novel animal had been constructed to have the same configuration
            as the overall average (10) but different individual features. Features were
            chosen to correspond to those that were relevant to discriminate original
            animal drawings that served as the basis for morphing (e.g., tail, feet,
            ornament on tummy, wings, head shape) but looked different enough to be easily
            discriminable.

            <hss>Auditory stimuli</hss>

            The auditory stimuli were the phrases “Look, a geepee!” and “Look, a boota!”
            recorded digitally from a female native speaker of British English in
            enthusiastic, infant-directed speech. The label (“A geepee!” /“A boota!”) was
            repeated twice, thereby occurring three times per stimulus. The onset of the
            first auditory phrase was at 2000 ms after the onset of the visual stimulus,
            with the labeling phrase (“A geepee!” /”A boota!”) repeated at 5000 and 8000
            ms after stimulus onset. In the two-label condition, half of the infants heard
            the label “geepee” with Stimuli 1, 3, 5, and 7 and heard the label “boota”
            with Stimuli 13, 15, 17, and 19—and vice versa for the other half of the
            infants. In the one-label condition, half (n = 12) of the infants heard
            “geepee” paired with all eight stimuli, and the other half heard “boota”
            paired with all eight stimuli.

        <hss>Procedure</hss>

        After a warm-up phase during which the experimenter explained the procedure and
        obtained written consent, infants were seated on the parent’s lap at a distance of
        approximately 65 cm from a 22-inch screen. A 9-point calibration sequence was used
        to calibrate a Tobii X120 remote eye tracker (sampling frequency = 120 Hz, system
        accuracy = 0.5 degrees). During this procedure, a small animated object with
        accompanying sound was displayed at nine locations (left, center, and right for
        top, middle, and bottom row) on the screen. Calibration was repeated up to three
        times or until all nine points had been calibrated successfully. After the
        calibration procedure, infants were presented with the eight familiarization
        stimuli, shown in a pseudorandomized order for on average 9750 ms (SE = 22) each.
        Individual sequences were obtained by using three Latin squares of three
        pseudorandom sequences, ensuring that no more than three consecutive stimuli were
        from the same subcategory. In the label conditions, infants heard the labels as
        described above. Prior to the first trial, and in between all subsequent trials,
        small animated video clips were shown at the center of the screen to direct
        infants’ attention to this location. Their duration varied between 800 and 1800
        ms. The familiarization phase was followed by a test phase consisting of six
        trials of 10 s each. The first and second, third and fourth, and fifth and sixth
        test trials were identical apart from left/right positioning of the test stimuli.
        The first two test trials always paired the overall average (Stimulus 10) with one
        of the subcategory averages (Stimulus 4 or 16, counterbalanced). The order of Test
        Trials 3/4 and 5/6 was counterbalanced; these presented infants with (a) the novel
        item paired with the overall average and (b) the novel item paired with the same
        subcategory average that was used on Test Trials 1 and 2 (i.e., each child either
        saw the subcategory average, 4, on Test Trials 1, 2, and either 3 and 4 or 5 and
        6, or they saw the subcategory average, 16, on these four trials). The reason for
        always presenting the pair of overall average and subcategory average at the start
        of the test phase was that this is the most sensitive contrast and needs to be
        presented while infants are at the peak of familiarity with the target stimuli. In
        particular, there is the possibility that once the novel stimulus has been
        presented, the overall average and subcategory averages will appear equally
        uninteresting to participants regardless of the category structure established by
        the end of familiarization. The location (left/right) of the items on Test Trials
        1, 3, and 5 was counterbalanced across infants. The test trials were silent in all
        conditions.

        <hss>Looking time during familiarization</hss>

        To assess whether familiarization had occurred, we compared average looking times
        during the first four and last four familiarization trials in all three
        conditions. The data were submitted to a mixed two-way analysis of variance
        (ANOVA) with the between-participants factor condition (silent, two-label, or one-
        label) and the within-participants factor block (Block 1 [Trials 1–4] or Block 2
        [Trials 5–8]). There were significant main effects of condition, F(2, 60) =
        15.357, p < .001, and block, F(1, 60) = 14.563, p < .001. The interaction between
        condition and block was not significant (F = 0.087, p = .917). Post hoc tests
        confirmed that infants in both label conditions had longer looking times than
        those in the silent condition (two-label: M = 8275 ms, SE = 280; one-label: M =
        8274 ms, SE = 271; silent: M = 6249 ms, SE = 271; both ps < .001, Bonferroni-
        adjusted). Looking times between one- and two-label conditions did not differ
        significantly (p = .59). This result is consistent with previous studies showing
        longer looking under auditory input than in silence (Robinson & Sloutsky, 2007a).
        Furthermore, average looking times during Block 1 (M = 7763 ms, SE = 160) were
        higher than those during Block 2 (M = 7113 ms, SE = 189; p < .001, Bonferroni-
        adjusted), as demonstrated by a paired t-test on the collapsed data. This
        indicates that infants across all conditions had become familiarized by the end of
        the familiarization phase.

        <hss>Preferential looking during test trials</hss>

        Test trial results are given in Table 1 (proportions and test results) and Table 2
        (absolute looking times). For the first two test trials, a preference score for
        the overall average object was obtained for each infant by dividing the total
        looking time at the overall average object (Stimulus 10) by the total looking time
        on that trial. For the remaining four test trials, a novelty preference score was
        obtained for each infant by dividing the looking time at the novel object by the
        total looking time on that trial. Preference scores for each pair of test trials
        (1 and 2, 3 and 4, and 5 and 6) were calculated as the average between the two. A
        mixed effects ANOVA with the between-participants factor condition (silent, two-
        label, or one-label) and the within-participants factor test trial (novel vs.
        overall average or novel vs. subcategory average) revealed a significant
        interaction of condition and test trial, F(2, 59) = 4.96, p = .010.1 The main
        effects of condition, F(2, 59) = 0.467, p = .629, and test trial, F(1, 59) =
        0.013, p = .91, were not significant. Planned comparisons against chance (.50)
        were conducted for each test trial in order to test whether infants preferred one
        stimulus over the other. In the silent condition, infants showed no preference for
        either stimulus when the subcategory averages and overall average stimuli were
        paired, t(19) = 0.67, p = .512. Similarly, there was no looking preference in the
        pairing of the novel stimulus and the subcategory average, t(18) = 1.10, p = .27.
        However, infants exhibited a preference for the novel stimulus when it was paired
        with the overall average stimulus, t(18) = 4.36, p < .001, d = 1.00). This looking
        pattern indicates that the overall average, but not the subcategory averages, was
        more familiar than the novel exemplar. These results, therefore, indicate that in
        the silent condition infants formed a single category. In the two-label condition,
        results for Test Trials 1 and 2 again showed no preference for either item, t(19)
        = 0.279, p = .78. For the remaining test trials, the results from the silent and
        one-label conditions were reversed; infants showed no preference when the overall
        average and novel item were paired, t(19) = 0.79, p = .43, but had a preference
        for the novel stimulus when paired with the subcategory averages, t(19) = 4.17, p
        < .001, d = 0.94. These results indicate the formation of two categories in the
        two-label condition, resulting in the subcategory averages being perceived as
        familiar and the overall average stimulus being perceived as novel. Results in the
        one-label condition resembled those in the silent condition; with no preference on
        the first two test trials, t(22) = 0.97, p = .34, infants exhibited a significant
        novelty preference for the novel test item when it was paired with the overall
        average, t(22) = 2.57, p = .017, d = 0.54, but not when it was paired with the
        subcategory averages, t(22) = 0.438, p = .66. As in the silent condition, this
        pattern of results indicates that the infants formed one category when all objects
        were paired with the same label. Taken together, these results indicate that
        infants in the silent condition and in the one-label condition formed a single
        category comprising all eight familiarization items, but they formed two
        categories when the objects were paired with two labels.

<hs>  Discussion</hs>
  ~~~~~~~~~~

Experiment 1 showed that infants formed a single category when objects were presented in
silence and when they were paired with a single label. In contrast, infants split this
category in two when the objects were paired with two distinct labels. Infants who were
familiarized with the visual stimuli in silence appeared to accept a large variety of head
shapes, leg types, and body posture as possible realizations of the target category.
Infants’ preferences during the test phase indicated that in the silent condition they
integrated all of the different familiarization exemplars into a single category
representation whose prototype was the overall average (see also Younger & Gotlieb, 1988,
for evidence that infants form prototype representation for perceptual categories). In
contrast, infants distinguished between the two subsets at either end of the morphing
continuum when the same objects were accompanied by two different labels, forming two more
restrictive exclusive categories. If this result were due to labels merely enhancing
visual processing overall (i.e., the trials simply being more interesting in the presence
of speech), we would expect two categories to be formed regardless of how many different
labels accompanied the visual stimuli. This is not the case; when a single label was
presented with all stimuli, infants formed just one large category. Our results,
therefore, suggest that infants tracked the correspondences between labels and object
features. Furthermore, the current pattern of results is incompatible with the auditory
overshadowing hypothesis, which predicts that visual processing in the presence of labels
is less detailed than in silence; to form two categories, infants needed to process more
detailed visual information to enhance the perceptual difference between the objects in
the two subcategories. In particular, our findings indicate that the condition with the
largest amount of novel auditory stimulation (two novel labels) leads to the most detailed
representation (two separate subcategories). Together, therefore, these results provide
unequivocal evidence that labels can have a constructive role in category formation in
infants prior to their first productive use of language. One open question with regard to
infants’ performance on the test trials is why infants in all three conditions did not
exhibit any preference on the first two test trials contrasting the overall and
subcategory averages. A possible explanation is that novelty preference depends on a sort
of “feature pop-out.” Because the stimuli were obtained using morphing, there were no
clearly identifiable feature differences between stimuli presented side by side, that is,
between the overall average stimulus (10) and the two subcategory averages (4 and 16). It
seems plausible that the lack of clear novelty could have prompted infants to compare
stimuli, resulting in overall similar looking times to both test items. Specifically, none
of the stimuli used here (the overall average, 10, and the subcategory averages, 4 and 16)
violates the familiarized category structure. Even if an infant has formed two categories
during familiarization and, therefore, the overall average (10) is perceived as relatively
novel, the infant could attempt to integrate this stimulus into the previously constructed
category structure by merely extending the category boundaries without needing to
completely re-form the categories. Similarly, if the infant has formed one category, the
subcategory average is not implausible as a category member but merely further away from
the overall category average. Infants’ looking patterns on test trials containing a novel
stimulus suggested competition effects between the two test stimuli presented side by
side; pop-out of the features of the novel stimulus creates a novelty effect, and if the
other stimulus is perceived as highly familiar, it presents no competition to the novel
item. In contrast, if the other item is perceived as less familiar, infants will spend
time exploring the novel stimulus but also scan the other item because more processing is
necessary to incorporate it into the established category. In other words, competition
between the test items here, or lack thereof, reveals how different category boundaries
have been formed. One remaining open question is whether the observed constructive effect
for labels in category formation is specific to language or whether it extends to other
forms of auditory input. In the work by Waxman and colleagues (Balaban & Waxman, 1997;
Ferry et al., 2010; Fulkerson & Waxman, 2007), labels were contrasted with tone sequences
and differential effects were found. However, as discussed above, these differences were
interpreted by Sloutsky and colleagues as being due to the different familiarity of speech
sounds and nonspeech sounds. Even in studies that did not find positive effects for
labels, nonlinguistic sounds had a more detrimental impact than labels (Robinson &
Sloutsky, 2007a). Finally, the study by Plunkett and colleagues (2008), which is so far
the best controlled study, did not involve a nonspeech sound condition. Therefore, to
establish whether labels take a special role in shaping visual categories, we tested an
additional group of infants on a nonlinguistic sound condition.

<h>EXPERIMENT 2</h>
------------

The design and procedure for this experiment were identical to the two-label condition in
Experiment 1 except that instead of auditory labels, nonlanguage sounds were played.

        <hss>Participants</hss>

        A total of 17 10-month-old infants participated in this experiment (mean age = 300
        days; 8 girls). A further 6 infants were excluded due to fussiness (n = 1) or
        technical problems (n = 5).

        <hss>Materials</hss>

        The visual stimuli were the same as in Experiment 1. Two sounds were used: a
        tingling bell sound and a wooden xylophone tone sequence. Each sound lasted 1 s.
        Each sound was played three times during the presentation of a picture, starting
        at 2000, 5000, and 8000 ms after stimulus onset. Half of the infants heard the
        bell sound with Stimuli 1, 3, 5, and 7 and the xylophone sound with Stimuli 13,
        15, 17, and 19—and vice versa for the other half of the infants.

        <hss>Procedure</hss>

        The procedure was identical to that in Experiment 1.

        <hss>Familiarization</hss>

        A paired t-test on average looking times for Blocks 1 and 2 of familiarization
        (Block 1 [Trials 1–4] or Block 2 [Trials 5–8]) revealed that there was a trend for
        infants to begin to habituate by the second block of familiarization (Block 1: M =
        6937 ms, SE = 446; Block 2: M = 5999 ms, SE = 573), t(16) = 2.033, p = .059. An
        ANOVA on the average looking time per trial was conducted to compare looking time
        during familiarization in Experiment 2 with the conditions of Experiment 1. This
        revealed a significant effect of condition, F(3, 76) = 10.13, p < .0005. Post hoc
        comparisons showed that infants in Experiment 2 spent approximately equal amounts
        of time gazing at the stimuli (M = 6468 ms, SE = 336) as those in the silent
        condition of Experiment 1 (p > .99); that is, they exhibited shorter
        familiarization looking times than infants in the labeling conditions (one-label:
        p = .023; two-label: p = .001).

        <hss>Test trials</hss>

        Looking preference scores for all test trials are shown in Table 1. Test trials
        and calculation of looking preferences were the same as in Experiment 1. For Test
        Trials 1 and 2 (overall average vs. subcategory average), the preference score did
        not differ from chance, t(16) = 1.48, p = .16, two-tailed. In test trials pairing
        the novel stimulus with the overall average stimulus, there was a marginally
        significant preference for the familiar item (i.e., the overall average) over the
        novel item, t(16) = 2.01, p = .061, d = −0.49. On the test trials pairing the
        novel stimulus with a subcategory average, infants did not reliably prefer either
        stimulus on these two test trials (t‐test on average preference scores: t(16) =
        1.13, p = .28). In summary, infants’ results differed from those found in
        Experiment 1. The marginal familiarity preference exhibited when the novel
        stimulus was paired with the overall overage stimulus indicates that infants
        formed a single category in the two-tone condition of Experiment 2.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The two-label condition in Experiment 1 revealed that pairing objects from a single
category with two labels led infants to split the category into two separate categories.
Pairing the visual stimuli with two nonlinguistic tones did not have the same effect. The
only (marginal) preference shown by the infants was one for the overall average when it
was paired with the novel item. This looking pattern can only be interpreted as a
familiarity preference. As described above, familiarity preferences can occur when the
familiarization stimuli are complex and/or infants have not become sufficiently
familiarized during training. In line with our interpretation of the results in Experiment
1, we need to interpret the familiarity preference here as indicative of infants forming a
single category over the familiarization stimuli. This means that despite the presence of
two distinct auditory stimuli, infants are not persuaded that there are two visual
categories—in contrast to the label condition, where their category representation was
guided by the structure provided by the labels. This result is compatible with the
auditory overshadowing hypothesis in the sense that infants (a) seem to struggle with
category formation, as indicated by the marginal test preference, and (b) do not use the
auditory stimuli to group the visual objects. Therefore, nonlinguistic tone stimuli,
unlike labels, appear to interfere with infants’ processing of visual material. Although
category formation per se does not appear to be disrupted in Experiment 2, the finding is
consistent with results from previous studies showing that nonlinguistic sounds do not
facilitate category formation (Balaban & Waxman, 1997; Ferry et al., 2010; Fulkerson &
Waxman, 2007; Robinson & Sloutsky, 2007a; Sloutsky & Robinson, 2008).

<h>GENERAL DISCUSSION</h>
------------------

Our aim in this work was to investigate how object labels interact with visual information
during category formation in preverbal 10-month-old infants. Although a body of literature
that has addressed this question exists, we argued that methodological considerations left
the results of these experiments inconclusive. We argued that to investigate whether
labels can constructively guide category formation and override visual similarities in
young infants it is necessary to (a) familiarize infants on a set of stimuli that could be
parsed into one or two categories, (b) test infants under varying labeling conditions
(silence, one label, and two labels), (c) include a novel test stimulus to ascertain
whether at test infants show a novelty or familiarity preference, and (d) construct the
stimulus set so that the effects of labels cannot be explained as processing less visual
detail than without labels. We presented a paradigm that incorporates these
considerations, familiarizing infants on a stimulus set that could be grouped into one
large category or two smaller categories. We found that on presentation in silence or when
all objects were paired with the same label, infants formed a single category. In
contrast, when half of the objects were paired with one label and the other half were
paired with another label, infants formed two separate categories in line with how the
objects had been labeled. Conversely, when the objects were paired with nonlinguistic
sounds, infants formed a single category but exhibited familiarity preference. In infants
at the transition to language, these results present clear evidence that labels interact
with nonlinguistic information to constructively shape categories and that these effects
are specific to linguistic labels and do not extend to nonspeech sounds. The results of
our experiments reconcile arguments that sounds act to overshadow visual processing and
that labels have a constructive effect on category formation. The results of Experiment 2
suggest that nonlinguistic tones indeed interfere with visual processing so that infants
did not form a category in the tone condition, whereas in silence they did. However,
whereas Sloutsky and Napolitano (2003) and Sloutsky and Robinson (2008) argued that labels
merely interfere less with visual processing than nonlinguistic sounds but contribute
nothing to category formation, our Experiment 1 clearly shows that labels do in fact
constructively affect categorization. Therefore, depending on their nature, auditory
signals can both interfere with and shape visual categories. Furthermore, recent results
also indicate that the temporal relationship between presentation of visual and auditory
stimuli matters so that interference is especially strong when visual and auditory stimuli
have a common onset (Althaus & Plunkett, 2015). Some authors have discussed the role of
labels in terms of whether they function as features that increase similarity between
objects in a bottom-up manner (Gliozzi et al., 2009; Sloutsky et al., 2001) or whether
they act in a referential manner, serving as “names” (Waxman & Gelman, 2009). Waxman and
Markow (1995) described the role of labels as “invitations to form categories” by
highlighting common visual features, suggesting a top-down role for labels. Likewise,
Waxman and Gelman (2009) argued that words are “referential” in nature and, as such, are
more than associates or perceptual features. Gliozzi and colleagues (2009), in contrast,
demonstrated that even results such as those presented by Plunkett and colleagues (2008),
which show a change in category formation based on label–object correlations, can be
simulated with a connectionist model that treats labels as features. In our study,
labeling caused infants to use more restrictive criteria for a classification of two items
as “similar,” effectively producing two smaller categories. The label, therefore, serves
not so much as a mere additional feature but instead as a feature that modulates the way
in which visual features are used. As such, our interpretation of the labels’ role is
somewhere between the extremes of “labels as features” and “labels as names”; labeling has
a supervisory function in the sense that it modulates the processing of similarity, but
whether this is enough to establish a “referential” relationship between the labels and
objects in these infants at just 10 months of age remains open. This interpretation is in
line with recent computational models (Althaus & Mareschal, 2013; Westermann & Mareschal,
2014) that simulate the role of words in the context of categorization. Althaus and
Mareschal (2013) demonstrated how early interactions between word learning and learning
about objects led to improved category representations compared with isolated learning,
without labels explicitly acting as supervisory signals. The model by Westermann and
Mareschal (2014) shows how labels can affect the similarity relations between objects in a
top-down manner by warping the perceptual similarity space to increase perceptual distance
between objects that have different labels. Such a mechanism could also account for the
results presented here. Our findings fit well with recent theories about interactions of
language with other domains. Although the strong Whorfian hypothesis of linguistic
determinism (Whorf, 1956) has been largely discounted over the last few decades, newer
research is gradually establishing links between language processing and perception or
cognition in adult processing (Boroditsky, 2001; Lupyan, 2008a, 2008b; Lupyan, Rakison, &
McClelland, 2007). In particular, the “label feedback hypothesis” (Lupyan, 2012) suggests
that language modulates cognitive processes, for example, benefitting visual search or
recognition memory (Lupyan, 2008a, 2008b). It seems likely that the effects we observe in
the experiments presented here reflect early stages of these interactions between language
and cognition. To summarize, the experiments presented in this article show that labels
have a constructive impact on category formation in preverbal infants; when a set of
objects is accompanied by labels, 10-month-old infants adapt their category structure in
correspondence to how the objects are labeled. This ability necessitates a deeper
processing of objects when they are paired with labels than when they are presented in
silence, with different labels highlighting visual differences between objects. Our
results further indicate that the effect of labels is not merely to enhance attention but
that it is also a constructive process in the sense that infants’ categorization behavior
was contingent on the number of labels they heard and that infants aligned their
categories with the labels. Object labels, thus, are powerful stimuli that are able to
direct infants’ attention to different visual dimensions in the construction of visual
categories.


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<ART>Late, but not early, arriving younger siblings foster firstborns’ understanding of second-order false belief
================================================================================

Authors: Amy L. Paine, Holly Pearce, Stephanie H.M. van Goozen, Leo M.J. de Sonneville, Dale F. Hay
DOI: 10.1016/j.jecp.2017.08.007
Year: 2018  |  Pages: 251-265
ASJC codes: 3204, 3205
Keywords: Community sample, Longitudinal study, Second-order false belief, Siblings, Social cognition, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study examined the influence of younger siblings on children's understanding of second-order false belief. In a representative community sample of firstborn children (N = 229) with a mean age of 7 years (SD = 4.58), false belief was assessed during a home visit using an adaptation of a well-established second-order false belief narrative enacted with Playmobil figures. Children's responses were coded to establish performance on second-order false belief questions. When controlling for verbal IQ and age, the existence of a younger sibling predicted a twofold advantage in children's second-order false belief performance, yet this was the case only for firstborns who experienced the arrival of a sibling after their second birthday. These findings provide a foundation for future research on family influences on social cognition.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Individual differences in children’s development of theory of mind (ToM), defined as the
“understanding of mental states, what we know or believe about thoughts, desires,
emotions, and other psychological entities both in ourselves and in others” (Miller, 2009,
p. 749), have traditionally been explored using the false belief task (Perner & Wimmer,
1983). Researchers have noted various sources of individual differences on this task,
including number of siblings (Lewis, Freeman, Kyriakidou, Maridaki-Kassotaki, & Berridge,
1996; McAlister & Peterson, 2007; Perner, Ruffman, & Leekam, 1994; Ruffman, Perner, Naito,
Parkin, & Clements, 1998), family sociodemographic status (Cole & Mitchell, 2000; Cutting
& Dunn, 1999), and maternal education level (Pears & Moses, 2003). Passing false belief
tasks has also been found to be related to children’s language (Astington & Jenkins, 1999)
and executive function (Carlson & Moses, 2001). Although it is well established that
preschoolers with older siblings outperform those without siblings on ToM tasks (Lewis et
al., 1996; Ruffman et al., 1998), the influence of younger siblings on ToM remains
unclear. Piaget (1959) suggested that both younger and older siblings facilitate social
understanding through discussion and reflection. Dunn (1994) claimed that siblings
influence social understanding through talk about causality and internal states,
management of conflict by parents, joint play, shared jokes, and reasoning about moral
issues; both younger and older siblings may equally facilitate ToM (Jenkins & Astington,
1996; Perner et al., 1994; Peterson, 2000). Indeed, in a recent meta-analysis by Devine
and Hughes (2016), the number of child-aged siblings, regardless of birth order, predicted
false belief understanding during early childhood. Despite these findings, the evidence is
mixed. Some studies found no effect of younger siblings on ToM tasks (Calero, Semelman,
Salles, & Sigman, 2013; Farhadian et al., 2010; Ruffman et al., 1998; Shahaeian, 2015),
and in one case younger siblings had a negative effect on ToM (Wright & Mahford, 2012).
Younger siblings may influence ToM development negatively by placing increased demands on
parents’ time, resulting in a decrease in mother–firstborn positive interactions (Baydar,
Greek, & Brooks-Gunn, 1997), including play and conversation with the firstborn child
(Dunn & Kendrick, 1980a, 1980b). It is also possible that parents’ explanations to their
firstborn children are frequently interrupted due to younger siblings’ demands (Wright &
Mahford, 2012). The age threshold model proposes that younger siblings may need to reach a
certain threshold in age before providing a positive influence on ToM (Kennedy, Lagattuta,
& Sayfan, 2015). If so, it is possible that some null findings may be due to the younger
siblings in those studies being too young to provide any advantage. Younger siblings may
become more important in fostering children’s more advanced understanding of minds during
middle childhood, but research on sibling influences on the later development of ToM
remains limited (Devine & Hughes, 2016; Hughes, 2016; Miller, 2009). Most studies
examining younger sibling influence on ToM focused on first-order false belief tasks
(Miller, 2009). However, during middle childhood, second-order false belief tasks are
thought to be more age appropriate (Perner & Wimmer, 1985). Whereas first-order false
belief tasks typically assess children’s understanding that someone may have beliefs that
differ from their own, a second-order task assesses whether children understand that one
story character can have a mistaken belief about another character’s belief. Some children
pass this higher-order test of ToM between 6 and 7 years of age (Perner & Wimmer, 1985).
Findings about sibling influence on ToM in older children are mixed; in some cases both
younger and older siblings facilitated higher-order ToM performance (Kennedy et al., 2015;
McAlister & Peterson, 2007), but in other studies younger siblings had no effect (Calero
et al., 2013; Miller, 2013). It is possible that older siblings begin to benefit from
younger siblings as the latter become more proficient playmates (Lagattuta et al., 2015).
Alternatively, as firstborn children start school and spend less time with family members,
the initial sibling advantage may disappear. Before a more definitive conclusion can be
drawn, larger-scale studies are required to tease apart the benefits of particular kinds
of sibling constellations (Cassidy, Fineberg, Brown & Perkins, 2005). Studies finding no
effect of younger siblings may have lacked sufficient statistical power to detect smaller
effects once samples are separated into sibling constellation groups (i.e., sibling
presence, birth order, age spacing, and gender composition) (see Miller, 2013). “Only
child” subsamples typically are small (Miller, 2013). This not only leads to a decrease in
power to detect an advantage in having a sibling over none but also results in samples
with a very high proportion of children who have siblings—in some studies more than 90%,
which exceeds the estimate that 80% of children in Western families have a sibling
(Volling, 2012). Although previous research on ToM has highlighted covariates that need to
be accounted for in studies of sibling influence, rarely have these all been controlled in
a single study, which may also explain the mixed findings. These covariates include child
age (Wellman, Cross, & Watson, 2001), family context (Lewis et al., 1996),
sociodemographic risk factors (Cutting & Dunn, 1999; Cole & Mitchell, 2000), language
ability (Astington & Jenkins, 1999), and executive function, specifically working memory
and inhibition (Carlson & Moses, 2001; Lagattuta, Sayfan, & Harvey, 2014). Children’s
understanding of second-order false belief is positively associated with their language
and executive function (Astington, Pelletier, & Homer, 2002; Lagattuta, Sayfan, &
Blattman, 2010; Lagattuta et al., 2014; Perner, Kain, & Barchfield, 2002). However, in
studies of sibling influences on ToM, rarely are age, sociodemographic risk, language, and
executive function all controlled (see Kennedy et al., 2015; Miller, 2013); when examined
together in one study, executive function was positively associated with second-order
false belief when age was controlled but not when language ability was partialed out
(Hasselhorn, Mahler, & Grube, 2005). Although correlates of first-order false belief may
also be relevant for second-order false belief, this has not yet been fully established
(Miller, 2012). Some of these correlates, such as executive function, may be most
important during early development of ToM; after children reach a certain threshold of ToM
skills during middle childhood, these relationships may attenuate or disappear (Lagattuta
et al., 2015). To address these issues, we explored the ways in which younger siblings
might influence 7-year-olds’ performance on a second-order false belief task while
controlling for known correlates of ToM in a study of a nationally representative
community sample of firstborn children and their families. Our moderately sized dataset of
firstborn children and their families provided a unique opportunity to examine the effect
of younger sibling constellation factors, including sibling presence, gender composition,
and age spacing.

<hs>  Design</hs>
  ~~~~~~

The Cardiff Child Development Study (CCDS) is a prospective longitudinal study of a
nationally representative sample of mothers and their firstborn children. Data collection
took place during pregnancy and at means of 6, 12, 21, 33 and 84 months postpartum. The
current study focuses on the home visit that took place at a mean age of 84 months. The
CCDS is funded by the Medical Research Council (MRC), and ethical approval was obtained
for the procedures from the National Health Service (NHS) Multi-Centre Research Ethics
Committee and the Cardiff University School of Psychology Research Ethics Committee.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 332 primiparous women and their partners were recruited between November 2005
and June 2008 from NHS antenatal clinics in hospitals and general practitioner (GP)
surgeries in two Health Care Trusts in Wales, United Kingdom. The CCDS is nationally
representative in terms of sociodemographic factors; it did not significantly differ from
families with firstborn children in the large, nationally representative sample in the
Millennium Cohort Study (see Hay et al., 2014). A total of 321 families were seen after
the birth of the first child, with 286 (89.01%) assessed at 7 years; of these, 272 (95%)
were directly observed at home. The current sample comprises 229 of these families (Fig.
1). The participants’ mean age at the time of testing was 83.20 months (range = 67–104).
The demographic characteristics of the children included in this subsample (69.0% of the
original sample) are summarized in Table 1. A child’s exposure to socioeconomic adversity
was indexed by (a) the mother not having achieved basic educational attainments (i.e.,
having no qualifications or fewer than five general certificates of secondary education
(GCSEs) or equivalent attainments), (b) the mother being 19 years of age or younger at the
time of the child’s birth, (c) the mother not being legally married during the pregnancy,
(d) the mother not being in a stable couple relationship during the pregnancy, and (e) the
mother’s occupation being classified as working class according to the Standard
Occupational Classification 2000 (SOC2000; Elias, McKnight, & Kinshott, 1999). A principal
components analysis (PCA) based on the polychoric correlation matrix confirmed that all of
these items contributed to a single component, which explained approximately 77% of the
shared variance in these risk indicators. Summary scores derived from this PCA measured
the family’s exposure to socioeconomic adversity (Perra, Phillips, Fyfield, Waters, & Hay,
2015). In terms of sibling constellation, 172 children (75.1%) had at least one younger
sibling living in the home; of these, 133 (58.1%) had one sibling, 32 (14.0%) had two
siblings, and 7 (3.1%) had three siblings. Gender composition and age spacing were
examined with the younger sibling closest in age to the firstborn. In total, 91 children
(52.9%) were in a same-gender sibling dyad and 81 children (47.1%) were in an opposite-
gender sibling dyad; of these, there were 47 (27.3%) older boy–younger boy dyads, 44
(25.6%) older girl–younger girl dyads; 46 (26.7%) older boy–younger girl dyads, and 35
(20.3%) older girl–younger boy dyads. The firstborn children entered siblinghood at a mean
age of 35.7 months (SD = 16.8). To investigate the influence of sibling birth interval,
children were grouped according to the interval between the firstborn and secondborn
sibling births. Children who entered siblinghood at or below the first quartile (≤24
months) were categorized as having an early arrival sibling (n = 45, 19.7%), children who
entered siblinghood at or above the third quartile (≥43 months) were categorized as having
a later arrival sibling (n = 44, 19.2%), and children with a sibling arriving between
these quartiles were categorized as having an average arrival sibling (n = 83, 36.2%).

<hs>  Procedure</hs>
  ~~~~~~~~~

Research assistants visited each family at home for two 2-h sessions. The caregiver
(typically the mother) was given questionnaires and interviewed by a trained research
assistant to gather information on the caregiver and firstborn’s well-being as well as
family lifestyle arrangements and social network. Where possible, these interviews would
take place in a separate room from the child. During these interviews, the child completed
various cognitive, social, and emotional assessments in a quiet space with a second
trained research assistant. A third research assistant attended to keep any younger
siblings occupied while the assessments took place. A remuneration of £20 was given to the
caregiver, and a book voucher of £10 was given to the child, at the end of the session.

        <hss>Second-order false belief task</hss>

        This task was adapted from second-order belief paradigms (Coull, Leekam, &
        Bennett, 2006; Perner & Wimmer, 1985). Each child was told a story enacted with
        plastic Playmobil figures by the experimenter. The protagonist was gender matched
        to the participant, and the sibling was gender matched to the participant’s
        closest-in-age younger sibling. In cases where the focal child had no siblings,
        the sibling character’s gender was randomly selected. The narrative is shown in
        Fig. 2. Pathways to passing or not passing this task are shown in Fig. 3. Children
        were classified as minimally passing second-order false belief if they correctly
        answered the first location question with an appropriate justification, and they
        were classified as passing second-order false belief with full comprehension if
        they also correctly answered the additional probe questions. An independent
        observer coded transcripts for 32.9% of the participants and established excellent
        agreement for passing second-order false belief (kappa coefficient = 1.00) and for
        appropriate or inappropriate justifications (kappa coefficient = 1.00). There was
        also very good agreement within appropriate and inappropriate justification codes,
        where the kappa coefficients were .89 and .79, respectively.

        <hss>Verbal IQ</hss>

        Each child’s vocabulary knowledge was assessed using the British Picture
        Vocabulary Scale (BPVS; Dunn, Dunn, Whetton, & Pintillie, 1982). In this task, the
        experimenter spoke a word to the child, who was asked to point or say the number
        of the picture that corresponded to the word. Each child’s verbal IQ was
        calculated by age normalizing the data to produce a standardized score. The mean
        score for verbal IQ was 99.54 (SD = 11.99), and the average age children in the
        sample were equivalent to was 84.14 months (SD = 14.66) and ranged from 49 to 150
        months.

        <hss>Executive function</hss>

        Cognitive function was assessed using tasks from the Amsterdam Neuropsychological
        Tasks (ANT) (de Sonneville, 1999). The ANT is a well-validated and sensitive
        instrument to evaluate executive functioning in population-based samples
        (Brunnekreef et al., 2007) and clinical samples (Rommelse et al., 2008). The tasks
        were presented on a laptop computer, and children made responses using a mouse.
        For each task, the experimenter gave verbal instructions while showing examples.
        Following this, children were given a practice trial before starting the test
        trials. The Response Organization Objects (ROO) task was used to measure response
        inhibition via children’s reaction times to stimuli. Children were asked to hold
        the mouse with a forefinger of each hand on each button of the mouse. In Part 1
        (compatible condition), children were presented with a fixation cross in the
        middle of the screen and were asked to respond to a red ball appearing on either
        side of the cross by clicking the same side of the mouse on which the ball
        appeared. In Part 2 (incompatible condition), children were presented with a white
        ball on the screen. Children were instructed to click the opposite side of the
        mouse according to the position of the ball. Response inhibition was
        operationalized as the difference between children’s mean reaction speed times in
        milliseconds (M = 314.32 ms, SD = 195.65) between the incompatible (Part 2) and
        compatible (Part 1) tasks. The Visuo-Spatial Sequencing (VSS) task was used to
        measure visuo-spatial working memory. In this task, children were presented with a
        gray square containing 9 circles symmetrically positioned in a 3 × 3 matrix on a
        computer screen. After a beep, a sequence of circles was pointed at by a computer
        animated hand, and after the sequence children took control of the mouse to
        replicate the sequence of circles. The test consisted of 24 trials and gradually
        increased in difficulty in the number of targets and complexity of the sequence.
        Working memory was assessed using the total number of correct targets in the
        correct order, with a total of 100 possible correct targets. The mean score for
        correct targets in the correct order was 67.24 (SD = 17.94).

<hs>  Children’s understanding of second-order false belief</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Correlations, means, and standard deviations for all variables of interest are presented
in Table 2. In total, 95 children (42.8%) passed the minimal second-order false belief
questions, and 67 children (30.2%) passed the second-order false belief questions with
full comprehension (Fig. 3). Minimal second-order false belief and second-order false
belief with full comprehension were positively associated (Table 2). A Guttman scaling
analysis using the Goodenough–Edwards method revealed a developmental progression from
minimal second-order false belief to second-order false belief with full comprehension (CR
= .99). Despite these two levels of passing second-order false belief being a part of a
single continuum, younger sibling constellation factors were only associated with passing
second-order false belief with full comprehension (Table 2). Therefore, the subsequent
analyses focused on children’s full comprehension of second-order false belief. Prior to
investigating the influence of siblings on this measure of false belief understanding, a
preliminary investigation of its correlates was conducted.

<hs>  Correlates of second-order false belief understanding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Examination of the correlation matrix (Table 2) and the collinearity statistics revealed
no issues with collinearity among predictor variables: firstborn age, firstborn gender,
sociodemographic risk, verbal IQ, response inhibition ANT, and working memory ANT
(variance inflation factor < 10, tolerance > .20) (Menard, 1995; Myers, 1990). Verbal IQ
and sociodemographic risk were significantly associated with passing the second-order
false belief questions with full comprehension, with higher verbal IQ scores associated
with better performance and higher sociodemographic risk scores associated with lower
performance. No relationship was detected between the ANT measures of response inhibition
and working memory and children’s passing second-order false belief with full
comprehension, nor was a relationship detected between age at the time of testing and
second-order false belief (all ps > .19) (Table 2). However, in view of earlier research
suggesting that individual differences exist in performance on false belief tasks across
different ages (Wellman et al., 2001), age was included in the subsequent logistic
regression. In the logistic regression, these potential confounds accounted for 11% of the
variance in second-order false belief with full comprehension, χ2(3) = 18.45, p < .001,
Nagelkerke R2 = .11. Children who were older at the time of testing, Wald statistic =
4.21, p < .05, odds ratio (OR) = 1.08, 95% confidence interval (CI) = 1.00–1.16, and those
who had higher verbal IQ scores, Wald statistic = 7.17, p < .01, OR = 1.04, 95% CI =
1.01–1.07, performed significantly better on second-order false belief; therefore, age and
verbal IQ were used as covariates in the subsequent analysis.

<hs>  Do younger sibling constellation factors influence the firstborn’s second-order false belief performance?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There was no significant association between number of siblings living in the home and
second-order false belief performance (r = .10, p = .15) (Table 2). Therefore, all
subsequent analyses explored sibling constellation factors related to the closest-in-age
sibling.

        <hss>Presence of a sibling in the home</hss>

        To test for variations in second-order false belief as a function of presence or
        absence of siblings in the home, the sample was divided into two groups.
        Preliminary analyses showed no differences between the groups in ratio of boys to
        girls, firstborn mean age, sociodemographic risk, verbal IQ, and working memory
        (all ps > .15) (see Table 3). Children with siblings performed better on the
        response inhibition task, t(76.83) = 2.03, p < .05. Children with a sibling had a
        twofold advantage in passing the second-order false belief task with full
        comprehension, χ2(1) = 5.00, p < .05, OR = 2.33, 95% CI = 1.10–4.97 (see Fig. 4).
        In a subsequent logistic regression analysis (Table 4), the covariates were
        entered into the first step of the model, which accounted for 9% of the variance
        in second-order false belief understanding, χ2(2) = 15.07, p < .001, Nagelkerke R2
        = .09. At the second step, the presence of a younger sibling accounted for
        significant additional variance in understanding second-order false belief, χ2(1)
        = 4.97, p < .05, and the overall model remained significant, χ2(3) = 19.98, p <
        .001, Nagelkerke R2 = .12. Within this model, verbal IQ remained a significant
        predictor of second-order false belief performance. Children with a younger
        sibling were twice as likely as children without siblings to pass second-order
        false belief with full comprehension, Wald statistic = 4.53, p < .05, OR = 2.35,
        95% CI = 1.07–5.15.

        <hss>Gender composition</hss>

        Gender composition was examined in two ways; after same-gender and opposite-gender
        dyads were compared, all four possible gender compositions—older girl–younger
        girl, older girl–younger boy, older boy–younger boy, and older boy–younger
        girl—were explored. Preliminary analyses showed no differences between the groups
        in ratio of boys to girls, firstborn mean age, sociodemographic risk, verbal IQ,
        and working memory or in inhibition across all of the groups (all ps > .10). No
        associations were detected between gender compositions of sibling dyads and
        second-order false belief (ps > .20).

        <hss>Birth interval</hss>

        Although no association was detected between timing of sibling arrival and second-
        order false belief understanding (r = .02, p = .81) (see Table 2), the four
        sibling arrival groups (no-sibling group and early-, average-, and late-arriving
        sibling groups) were investigated. Preliminary analyses showed no differences
        among these groups in ratio of boys to girls, verbal IQ, and working memory (ps >
        .15). Significant differences were detected among groups in sibling age, F(3, 224)
        = 3.16, p < .05, sociodemographic risk, F(3, 225) = 4.13, p < .01, and ANT
        inhibition scores, F(3, 220) = 3.12, p < .05. Post hoc tests were selected in
        accordance with results from tests for homogeneity of variances. Games–Howell post
        hoc tests indicated that children in the late-arriving sibling group were older
        than those in the no-sibling group and that children with an average-arriving
        sibling performed better on the inhibition task than those without a sibling (ps <
        .05). A Tukey post hoc test indicated that children with an average-arriving
        younger sibling had lower sociodemographic risk than those with a late-arriving
        sibling (p < .01). A significant difference was detected among the four sibling
        groups in their passing of the second-order false belief task with full
        comprehension, χ2(3) = 8.97, p < .05 (Fig. 5). This finding was explored further
        while controlling for covariates of second-order false belief. Because late-
        arriving siblings did not significantly differ from the average-arriving sibling
        group in performance on passing second-order false belief with full comprehension,
        these were collapsed into one “average to late”-arriving sibling group. There were
        no significant differences among the groups in ratio of boys to girls, firstborn
        mean age, sociodemographic risk, verbal IQ, and working memory or in inhibition
        when these groups were collapsed (all ps > .06). The three remaining sibling
        status groups were dummy coded, with the no-sibling group assigned as the
        reference category in a logistic regression. Covariates (age and verbal IQ) were
        entered into the first step of the logistic regression model. When entered into
        the model at the second step, early arrival of a younger sibling and average to
        later arrival of a younger sibling accounted for a significant step when entered
        into the model, accounting for an additional 4% of the variance in second-order
        false belief with full comprehension, χ2(2) = 6.57, p < .05. The overall model
        remained significant, χ2(2) = 21.57, p < .001, Nagelkerke R2 = .13. The early
        arrival of younger siblings did not predict firstborns’ passing of second-order
        false belief with full comprehension; however, “average to late”-arriving siblings
        conveyed a significant advantage, Wald statistic = 5.63, p < .05, OR = 2.66, 95%
        CI = 1.19–5.96 (Table 5).

<h>DISCUSSION</h>
----------

When predictors of second-order false belief understanding were controlled, children with
a younger sibling living in the home were twice as likely to succeed on a second-order
false belief task. It was established that this sibling advantage occurred only for
firstborns who did not experience the early arrival of a sibling. Our finding stands in
contrast to the first study of sibling effects on second-order false belief tasks, which
found no effect (Miller, 2013), but is consistent with previous research showing that
presence of a younger sibling in the home is advantageous for ToM (Lewis et al., 1996;
Perner et al., 1994; Peterson, 2000). In contrast to earlier work (Kennedy et al., 2015),
the younger sibling’s influence on a higher-order ToM task in our sample was not limited
to same-sex siblings. There are various mechanisms by which younger siblings could
facilitate their siblings’ social understanding; these might include engaging in joint
pretense (Youngblade & Dunn, 1995), sharing knowledge through teaching (Azmitia & Hesser,
1993; Zajonc & Markus, 1975), or engaging in conflict and resolution (Dunn, 1994; Foote &
Holmes-Lonergan, 2003). Our focus on younger siblings, however, revealed that the
firstborn’s experience of the arrival of a younger sibling before the second birthday did
not provide a similar advantage. The first 2 years of life represent an important time in
ToM development, when evidence for consciousness, pretense, and the use of lexical terms
for mental states emerges (Astington, Harris, & Olson, 1988; Bartsch & Wellman, 1995).
Transition to siblinghood during this time may disrupt this process. Future work should
examine multiple factors in family interactions that explain differential effects of
early- and late-arriving siblings on the oldest child’s social cognitive development.
Children who experienced socioeconomic adversity performed less well on the second-order
task; however, this association did not remain significant when accounting for age and
verbal IQ. This finding stands in contrast to previous research (Cole & Mitchell, 2000;
Cutting & Dunn, 1999), perhaps because our study took into account a number of dimensions
of sociodemographic risk beyond occupational class or income. Although a number of
sociodemographic risk factors have been found to be associated with ToM, such as income,
maternal education (Andersson, Sommerfelt, Sonnander, & Ahlsten, 1996), and parental
occupational class (Cutting & Dunn, 1999), rarely are these factors all controlled in a
single study (Pears & Moses, 2003). Although the effects reported in this study were not
large, it is important to note that the sample size used in the current study provided
sufficient power to enable detection of such small to moderate effects. Thus, the absence
of an association with children’s executive function abilities in this sample is
noteworthy given that there was sufficient power to detect such an effect. Although
executive function abilities and first-order ToM have been found to be positively related
(Carlson, Moses, & Breton, 2002), a finding replicated in the current study with respect
to working memory in particular, there has not been consistent evidence for a correlation
between executive function and second-order ToM (for a review, see Miller, 2009). Indeed,
executive function has been found to be positively associated with second-order false
belief when age was controlled, but not when language ability was controlled (Hasselhorn
et al., 2005). Alternatively, it is possible that the nonverbal measures used in this
study to assess executive function might not be comparable to other verbal measures of
inhibition and working memory such as Bear/Dragon, “Simon Says”–type inhibition tasks or
word/digit span working memory tasks (Carlson et al., 2002). Before a more definitive
conclusion can be made, replication of this finding using other executive function tasks
is warranted. In light of previous research suggesting that some 6-year-olds and the
majority of 7-year-olds are successful at attributing second-order beliefs (Perner &
Wimmer, 1985), it is noteworthy that only a minority of children in this community sample
passed the second-order task. This finding must be interpreted with some caution in view
of the limitations of our study procedures. Data collection took place in the family
homes; therefore the assessment may have been influenced by distractions within the home
environment. However, evidence from this representative community sample may provide a
more accurate estimate of the number of children at this age who understand second-order
false belief. Finally, given our sampling strategy where we recruited firstborn children,
we are unable to determine whether our findings were driven by a general sibling effect,
not just the influence of younger siblings. Therefore, more work is needed to determine
whether older siblings, as well as younger siblings, continue to foster children’s
understanding of minds into middle childhood. In conclusion, the finding that the presence
of a younger sibling in the home facilitated the firstborn’s false belief understanding
draws attention to the unique contribution of the sibling relationship to social cognitive
development during middle childhood. Taken together with evidence from the vast literature
on first-order false belief understanding, our findings contribute to knowledge about the
influence of both younger and older siblings on a child’s development of a ToM during the
middle childhood years.


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<ART>Learning to infer the time of our actions and decisions from their consequences
===============================================================================

Authors: Helena Matute, Carmelo P. Cubillas, Pablo Garaizar
DOI: 10.1016/j.concog.2017.09.009
Year: 2017  |  Pages: 37-49
ASJC codes: 3204, 3205
Keywords: Action, Causal binding, Conscious decision, Conscious will, Intentional binding, Learning

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Research shows that people infer the time of their actions and decisions from their consequences. We asked how people know how much time to subtract from consequences in order to infer their actions and decisions. They could either subtract a fixed, default, time from consequences, or learn from experience how much time to subtract in each situation. In two experiments, participants’ actions were followed by a tone, which was presented either immediately or after a delay. In Experiment 1, participants estimated the time of their actions; in Experiment 2, the time of their decisions to act. Both actions and decisions were judged to occur sooner or later as a function of whether consequences were immediate or delayed. Estimations tended to be shifted toward their consequences, but in some cases they were shifted away from them. Most importantly, in all cases participants learned progressively to adjust their estimations with experience.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

A famous experiment by Benjamin Libet and his colleagues (Libet, Gleason, Wright, & Pearl,
1983) used an oscilloscope clock with a dot rotating around a sphere and asked their
experimental participants to perform a quick movement of their finger or wrist at any time
they felt they wished to. This procedure was repeated for a number of trials, and at the
end of some of those trials participants were asked to indicate on the clock the position
of the dot at the exact moment of their “conscious awareness of wanting to move”. In
addition, electroencephalographic (EEG) activity was recorded in order to assess the exact
time at which the readiness potential (an electroencephalographic component that precedes
the initiation of voluntary actions) occurred. Contrary to what intuition would suggest,
the sequence for self-initiated actions that was recorded did not start with the
participants’ reporting their conscious will to perform the action. Instead, the readiness
potential was recorded first in the temporal chain (around 550 ms before the action), with
participants reporting their conscious will as occurring much later in time (around only
200 ms before the initiation of the action). This seems to suggest that voluntary actions
are initiated unconsciously at a neuronal level, and that the conscious decision to act
occurs much later in time (about 350 ms later). This experiment, along with several others
that confirmed, extended, or discussed the initial findings (Banks & Isham, 2009;
Guggisberg & Mottaz, 2013; Haggard & Eimer, 1999; Rigoni, Brass, Roger, Vidal, & Sartori,
2013; Rigoni, Brass, & Sartori, 2010; Soon, Brass, Heinze, & Haynes, 2008) have fueled
some rather heated debates about consciousness and free will in psychology, law, and
related disciplines (Alquist, Ainsworth, & Baumeister, 2013; Baumeister, Masicampo, &
DeWall, 2009; Guggisberg & Mottaz, 2013; Moore, 2016; Rigoni, Kühn, Gaudino, Sartori, &
Brass, 2012; Vohs & Schooler, 2008). Libet’s clock procedure has also been used in many
experiments studying not only how people become aware of their own decisions but also of
their own actions (Banks & Isham, 2009; Caspar & Cleeremans, 2015; Haggard, Clark, &
Kalogeras, 2002; Moore, Lagnado, Deal, & Haggard, 2009; Rigoni et al., 2010; Tobias-Webb
et al., 2017). A standardized, open source version of Libet’s clock has recently been
published (Garaizar, Cubillas, & Matute, 2016), which should facilitate reproducibility of
these findings. In spite of the many experiments that have pursued this line of research,
there are still many questions that remain unanswered. Perhaps the most obvious problem is
that it is impossible to assess directly the moment at which conscious will actually
occurs. In particular, experimental participants do not have direct access to the time of
their conscious decisions (Banks & Isham, 2009; Fahle, Stemmler, & Spang, 2011; Guggisberg
& Mottaz, 2013; Rigoni et al., 2010). Moreover, we do not even know whether the temporal
order in which the events are recorded in those experiments is the temporal order in which
they actually occur. It might well be that people are poor at estimating the time of their
conscious decision, so that perhaps they simply misjudge this time when asked to report
it. Indeed, the only information that Libet et al.’s (1983) experiment (or, to our
knowledge, any other experiment) can reveal in relation to the time of conscious will is
the subjective report of when participants estimate that it took place. Therefore, one
crucial question is how people estimate the time of their decision. One possibility is
that they directly perceive the moment at which they decide to act, whilst another is that
they infer retrospectively the time at which they decided to act. Preliminary evidence for
this latter possibility exists in the literature. For example, Banks and Isham (2009)
added auditory feedback (i.e. a tone) to the participants’ action and manipulated the time
intervals between action and feedback. If people perceived the time of their decisions
directly, then the time at which the tone occurred after the action should be irrelevant.
However, their participants reported that their conscious decision to act occurred sooner
or later as a function of whether the tone occurred sooner or later after the action. In
other words, participants appeared to retrospectively infer, rather than perceive, the
time at which they decided to act. Banks and Isham concluded that the generation of the
action was largely unconscious, with participants inferring the time of their decision
from observable cues, particularly from the apparent time of their own actions (see also
Lau, Rogers, & Passingham, 2007; Rigoni et al., 2010). But assuming that the time of
decision is inferred from the estimated time of action leads us to another crucial
question: How do people estimate the moment of their actions? Again, they might directly
perceive their own actions or they might infer the occurrence of their actions from their
consequences. This has been a central question in Experimental Psychology since the
nineteenth century. According to the Ideomotor Theory proposed by James (1890), people use
the sensorimotor properties of the action in order to estimate when they performed the
act. It is easy to extend this logic to assume that people use not only the sensorimotor
properties of their action, but also any other consequences of their action, such as a
tone — which an experimenter might introduce into the situation — to infer when they have
acted. Interestingly, this line of research has shown that when the consequences of the
action (e.g. a tone) are delayed, then people estimate that their action occurred later in
time (Banks & Isham, 2011; Haering & Kiesel, 2014; Haering & Kiesel, 2015; Wegner, 2002).
Moreover, a very similar finding has been consistently reported using the so-called
“action-effect binding” paradigm, which shows that actions and their consequences tend to
be perceived as closer to each other in time than they actually are (Haggard et al.,
2002). According to Haggard and his colleagues, the intentionality of the action is the
crucial factor in producing this effect, but it has also been suggested that
intentionality is not always necessary (e.g., Isham, Banks, Ekstrom, & Stern, 2011), and
that it might be the causal relationship between the action and the outcome, rather than
its intentionality, that is critical (Bechlivanidis & Lagnado, 2013; Buehner, 2012;
Buehner & Humphreys, 2009). In any case, the finding that the estimated time of action is
affected by the time of its consequences and it is shifted toward them is a robust result
that has been reported in many different experiments (Buehner, 2012; Cravo, Haddad,
Claessens, & Baldo, 2013; Garaizar et al., 2016; Haering & Kiesel, 2015; Haggard et al.,
2002; Moore & Haggard, 2008; Nolden, Haering, & Kiesel, 2012). Thus, it seems that it is
not only the case that people cannot directly perceive the time of their decisions, they
also seem to have difficulties in estimating the time of their own actions. Indeed, the
estimation of the time of decisions and the time of actions appears to vary in the same
manner and they both seem to be strongly influenced by the time at which the consequences
occur (see also Banks & Isham, 2011). The most basic example of such consequences are
sensorimotor consequences (such as visual and haptic cues that signal, for example, that a
button has been pressed), but additional consequences such as added auditory stimuli can
also be signals that the action (and decision) has occurred. In order to infer the time of
their actions, people appear to discount some time from the time at which the consequences
occur, and then, they possibly discount some extra time from the apparent time of action
in order to infer the time of decisions. But then the question is how they know how much
time they need to subtract in each situation. Do people simply subtract some fixed,
default, time, which is identical in all cases, or do they learn from experience how much
time they need to subtract in each particular case? In daily life, it seems reasonable to
expect that people will constantly need to learn how much time to discount in each
particular situation. People may easily learn that a light of a room will turn on
immediately after they press the correct switch, but they should as readily learn to
predict a long delay for tomatoes to grow after they have planted the seeds. Indeed, it
has been shown that humans and other animals have expectations of when consequences should
occur after the potential cause has occurred, and these expectations affect their learning
and behavior (e.g., Arcediano, Escobar, & Miller, 2003; Buehner & May 2002; Buehner & May
2003; Buehner & May 2004; Matzel, Held, & Miller, 1988; Miller & Barnet, 1993; Savastano &
Miller, 1998). Quite possibly, these expectations can be learned through experience and
are continuously adjusted for each action-outcome pair and context. By the same reasoning,
people will possibly learn to assume that in some cases their action occurred immediately
before its consequences whilst in other cases they might learn that their actions (and
decisions) took place a long time before they observed the consequences. The present study
will test whether people learn to infer the time of their actions and decisions or if, in
contrast, they just subtract a fixed time upon observing their consequences. Although the
majority of research in the area of temporal binding implicitly assumes that learning
plays an important role, we are aware of very few investigations that explicitly examine
such learning. Indeed, most experiments report the dependent variable (e.g., subjective
judgments or estimations of when the action occurred) averaged over the total number of
trials (Haggard et al., 2002; Moore et al., 2009), and so there is typically a lack of
information on what happens on a trial-by-trial basis during the course of learning. Thus,
the possibility exists that action-effect binding might take place during the early trials
due to pre-experimental biases, after which people might progressively learn to correct
their error and improve the accuracy of their estimated time of actions (and perhaps also
their decisions). Alternatively, it is possible that estimations do not improve with
experience and instead show a fixed binding effect throughout the experimental session.
This might occur, for instance, if actions were always, by default, subjectively shifted
toward their effects. This is what most reports on temporal binding seem to suggest, given
that they typically provide only one (averaged) binding value for each group in each
experimental session. We are aware of only two studies looking at learning in the binding
tradition. One of them was reported by Cravo et al. (2013). They used three different
intervals (250, 300, 350 ms) between the action and the outcome (i.e. Action condition),
and between an external event and the outcome (i.e., No Action condition). They observed,
first, that the mean reported interval between the action and the outcome was shorter than
between the external event and the outcome, an effect that was evident from the very early
trials. According to the authors, this implies that action-outcome binding effects are due
to people expecting short intervals between actions and outcomes from the very first
trials, suggesting that pre-experimental biases must be important. In addition, they
observed no differences between the early and later trials when considering the whole
experimental session. Thus, they concluded that previous biases are probably more
important than learning in producing the action-outcome binding effect. Importantly,
however, they also noted that some learning was taking place within each of the
consecutive and independent training blocks of trials in which they had subdivided the
training phase. Thus, although their experiment represents a good starting point, there
are a number of reasons why we are unable to extract any firm conclusions about learning
from this study. First, the fact that learning seemed to take place within each block but
no differences were observed between early and later trials throughout the session
suggests that learning might have occurred but was eroded each time a new training block
started. If this were the case, participants might not have benefited from the entire
learning session and might have started anew each time a new block of trials was
presented. Thus, it is possible that the learning phase might have just been too short to
observe any appreciable differences. In addition, there were two different conditions and
three different intervals in each block (with a total of 20 trials for each interval in
each block), which might also have made the problem too difficult to be learned in the
short time allocated to each block. A potential way to solve these problems might be to
make the task easier and to provide a larger number of learning trials, that is, to ensure
a more effective learning experience. This is one strategy that we will follow to examine
the course of learning in the present research. The other study we are aware of was
reported by Moore et al. (2009). They tested whether contingency learning played a role in
the binding effect. Unfortunately, however, they used a complex design which did not allow
them to observe the course of learning. As they put it: “we averaged our estimates across
several trials because of the high variability of human timing performance. Therefore, we
could not measure the time-course of the learning process but we can infer that causal
learning occurs based on our contingency effects” (p. 282–283). This study also suggests
that reducing the difficulty of the task might possibly be the first step needed to study
the learning curve. The present research will take such steps in order to test whether
people progressively learn to estimate the time of their actions and decisions with
experience.

<h>OVERVIEW OF THE EXPERIMENTS</h>
---------------------------

In order to facilitate the observation of a learning curve, we will use only one
continuous training session (i.e. blocks of trials will constitute a continuous and
incremental training session, rather than independent learning experiences). In addition,
we will use only two different conditions during training (i.e. immediate feedback vs
delayed feedback). A third condition (i.e. no-feedback) will be added as a separate
baseline phase to assess judgments in the absence of feedback, but it will be presented
only after the training phase has already been completed, so that baseline assessment
could not interfere with the critical learning experience.

<hs>  Ethics statement</hs>
  ~~~~~~~~~~~~~~~~

The computer program informed participants that their involvement was voluntary and
anonymous. We did not ask participants for any data that could compromise their privacy,
nor did we use cookies or software in order to obtain such data. The stimuli and materials
were harmless and emotionally neutral, the goal of the study was transparent, and the task
involved no deception. The ethical review board of the University of Deusto examined and
approved the procedure used in this research, and the two experiments were conducted in
accordance with the approved guidelines.

<hs>  Data selection criterion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Data from participants who did not press the key more than 25% of trials on either one of
the three feedback conditions described above (i.e., immediate, delayed, and no-feedback)
were discarded.

<h>EXPERIMENT 1</h>
------------

The purpose of this experiment was twofold. First, we tested whether people estimate the
time of their actions accurately or whether their estimate is affected by the time of
consequences. We expected that a delay in the consequences of the action should produce a
delay in the estimated time of action, thereby reproducing previous reports (e.g., Banks &
Isham, 2011; Garaizar et al., 2016; Haggard et al., 2002). Most importantly, this
experiment aimed to extend previous findings by assessing whether the estimation of the
time of action was subject to learning. That is, we tested whether people will then
progressively learn to correct their estimation errors and improve their reported time of
action with experience.

        <hss>Participants</hss>

        The sample was comprised of 60 Psychology students from the University of Deusto
        who volunteered to take part in the experiment in exchange for academic credit.
        Data from four of the participants were discarded according to the data selection
        criterion described above.

        <hss>Apparatus</hss>

        Participants performed the task on personal computers in a large computer room.
        They were seated approximately 1 m apart from each other. We developed a Visual
        Basic computer program based on Garaizar et al.’s (2016) open source HTML version
        of Libet’s clock. The computers run the program on Microsoft Windows 7. A screen
        capture of this version is shown in Fig. 1. Its accuracy and settings were
        validated using the identical methodology published by Garaizar et al. Auditory
        stimuli were presented via headphones connected through the audio output of the
        PCs.

        <hss>Procedure and design</hss>

        The procedure and design were identical to those described by Garaizar et al.
        (2016). On each trial, participants observed a clock face on the computer screen
        with a dot rotating around the sphere at a constant speed of 2560 ms per cycle.
        There were two cycles of the dot per trial. Participants were asked to look at the
        center of the clock during the first cycle within each trial, and to press the
        space bar anytime they wished to during the second cycle on each trial. Pressing
        the bar did not stop the rotating dot, but was followed by auditory feedback at
        different delays as described below. We used a within-subject design with two
        types of trials during training. On half of the trials (i.e., immediate condition)
        a 1000 Hz 200 ms tone was programmed to occur immediately following the
        registration of the action, using Microsoft Windows Multimedia Timers,1 which have
        a resolution of 1 ms as assessed by popular experimental software packages such as
        SuperLab (Abboud, Schultz, & Zeitlin, 2006) and E-Prime (Schneider, Eschman, &
        Zuccolotto, 2002). On the other half of trials (i.e., delayed condition), the same
        tone was programmed to occur with a 500 ms delay after the registration of the
        action. There were 40 trials for each condition, and they were presented in
        pseudorandom order. Immediately after each one of the 80 trials was completed,
        participants observed an empty clock face and were asked to indicate the location
        at which the dot was when they pressed the space bar during that trial (see Fig.
        1). This was their subjective judgment of their time of action. Participants
        answered this question using the mouse, after which the empty clock face was
        presented again and the inter-trial interval (ITI) began. The ITI lasted between
        1000 and 3000 ms. At the beginning of the ITI, a text prompting participants to be
        prepared for the next trial was presented along with a complex 1000 ms tone (500
        ms at 250 Hz followed by 500 ms at 440 Hz). Then, after a variable interval of
        0–2000 ms the next trial began. Finally, after all 80 trials had been completed a
        screen instructed participants that on the following trials no auditory feedback
        would be presented. Participants were then presented with 20 additional trials
        without auditory feedback in order to assess their baseline judgments without the
        provision of feedback (i.e., baseline condition).

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

For comparison purposes, we will first describe our results as they have typically been
described in previous research. Thus, we will first report the subjective estimates for
the time of action averaged across the training session. Mean estimated time of action is
shown in Fig. 2 against the actual recorded time for action (which is represented as zero
on the Y axis). A positive value means that the action was estimated on average after it
already had taken place, whereas a negative value means that the action was estimated on
average before it had taken place. In addition, it should be noted that baseline judgments
are often subtracted from target judgments in the literature and the data are reported
after this transformation has already been applied (e.g., Moore et al., 2009; Tobias-Webb
et al., 2017). However, in order to facilitate potential comparisons, we decided to depict
the experimental trials and the baseline trials separately (rather than subtract baseline
data from target action-outcome trials). Thus, Fig. 2 shows the raw average estimates for
the time of action (in ms from the actual time of action) for both the action-outcome
trials and the baseline trials separately. Means (and standard errors of the mean) are
−11.16 (4.97), 81.09 (17.98), and −8.45 (8.15) for the immediate, delayed and baseline
conditions, respectively. The subjective estimation of the time of action in the delayed
condition was also significantly longer than the time at which the action actually
occurred (i.e. zero on the Y axis of Fig. 2), t(55) = 4.508, p < 0.001, dz = 0.602.
Interestingly, there was also a discrepancy between the estimated time of the action and
the occurrence of the action in the immediate condition, t(55) = 2.246, p = 0.029, dz =
0.3. In those cases, however, participants reported that their action occurred before,
rather than after, the actual time of the action. We will use the term antibinding to
refer to this effect that occurs in the immediate condition, since the estimated time of
action was shifted away from the outcome. No significant differences were observed during
baseline trials between the estimated time of action and actual time of action, t(55) =
1.037, p = 0.304, dz = 0.138. Subsequent planned comparisons showed that in the delayed
condition there was a significant difference between the first and the last block of
trials, which suggests that learning occurred and participants improved the accuracy of
their estimations through the training session, t(55) = 5.054, p < 0.001, dz = 0.675.
Also, and even though learning and improvement are evident in the delayed condition, the
participants’ estimations are significantly different from the actual time of action, even
on the fourth block of trials, t(55) = 6.511, p < 0.001, dz = 0.87, for the first block;
t(55) = 2.637, p = 0.011, dz = 0.352, for the fourth block. The learning curve in Fig. 3
suggests that the accuracy of judgments could still improve if a more extended learning
experience were provided. The immediate condition also shows the significant difference
between the first and the fourth block which reflects the occurrence of learning, t(55) =
2.409, p = 0.019, dz = 0.321. In this condition, however, the estimation was at first
quite accurate and did not differ from zero (i.e. the actual time of action) on the first
block of trials, t(55) = 0.247, p = 0.785, dz = 0.033, but as learning proceeded,
estimations began to shift away from the outcome (and thus from the action as well) so
that the antibinding effect become evident, and by the fourth block participants came to
believe that they had acted significantly earlier than they had, t(55) = 3.035, p = 0.004,
dz = 0.405. Thus, the observed antibinding effect seems to be a learning effect. The
estimations of the time of action during the baseline phase did not significantly differ
between the first and the last block of trials, t(55) = 0.294, p = 0.77. Moreover, no
significant differences were observed between the estimated time of action and the actual
time of action during baseline, t(55) = 0.896, p = 0.374, dz = 0.119, for the first
baseline block of trials, t(55) = 0.7, p = 0.487, dz = 0.093 for the last block. That is,
the time of action appears to be accurately judged throughout the baseline phase.

<h>EXPERIMENT 2</h>
------------

Experiment 1 showed that participants inferred the time of their actions from the
consequences of those actions, so that when the consequences were delayed participants
estimated that they had acted later than they had. Most importantly, participants learned
progressively to improve their estimations of their action on the delayed trials, possibly
by subtracting some time from the time at which the auditory feedback was presented.
However, as they did so, they also began to subtract some time from the time of feedback
in the immediate condition, so they also began to assume that their action occurred
earlier than it did when feedback was immediate. Our next purpose was to explore whether
those effects would also occur if we asked participants to estimate the time of their
conscious decision to act rather than the time of their actions. If the subjective time of
action can be so easily mislead by the time in which the consequences of the action occur,
then the subjective time of decisions should also be affected. As has been shown
previously, participants should believe that their decision took place sooner or later as
a function of whether the auditory feedback for their actions occurred sooner or later
(Banks & Isham, 2009). This implies that people cannot be certain of when they made a
decision. Instead, they possibly infer their time of decision upon observing the
consequences of their behavior. Investigating whether people infer a fixed time for
decisions as a function of when the outcome occurs or whether, in contrast, this time is
learned and modifiable through experience is the aim of Experiment 2.

        <hss>Participants</hss>

        The sample was comprised of 56 Psychology students from the University of Deusto,
        who volunteered to take part in the experiment in exchange for academic credit.
        Data from seven of them were discarded according to the data selection criterion
        described for Experiment 1.

        <hss>Design, apparatus, and procedure</hss>

        All aspects of the experimental design and procedure are identical to those of
        Experiment 1 except that we asked participants to report the time of their
        decision to act rather than the time of their action.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

As in Experiment 1, we will first report the subjective judgments averaged throughout the
experimental session. In the present experiment, these judgments reflect the estimated
time of decision rather than action. Again, in order to facilitate potential comparisons,
we decided to depict the raw data from the experimental trials and the baseline trials
separately. Fig. 4 shows the raw average estimates for the time of decision in ms from the
recorded time of action (which is shown as point zero on the Y axis) for both the action-
outcome trials and the baseline trials. Means (and standard error of the mean) are −11.33
(6.98), 27.92 (9.25), and −24.06 (6.90) for the immediate, delayed and baseline
conditions, respectively. As can be observed in Fig. 4, when the action was immediately
followed by feedback participants estimated that their decision had occurred slightly
before their action, which seems to be a sensible inference. However, when feedback
following the action was delayed, participants then moved their estimated time of decision
toward the tone. This replicates previous findings (Banks & Isham, 2009) and can also be
regarded as an extension of the standard binding effect, as it shows that the shift of the
subjective estimation toward the outcome occurs not only for actions but also for
decisions. It is interesting to note that the estimated time of decision in the delayed
condition was also significantly delayed when compared with the time at which the action
actually occurred (i.e. zero on the Y axis of Fig. 4), t(48) = 3.017, p = 0.004, dz =
0.431. We refer to this finding as a superbinding effect, as participants came to believe
that their decision occurred after they had already acted, rather than before they acted.
Thus, the mean estimation of the time of decision was shifted toward the tone, and beyond
the action. This suggests that when estimating the time of their decisions, participants
were more strongly influenced by the observation of consequences, which probably signaled
the apparent time of action, that than by their actual decisions (or their actual
actions). There was also a significant difference between the estimated time of decision
and the actual occurrence of the action on the baseline trials, t(48) = 3.486, p = 0.001,
dz = 0.498 (see Fig. 4). In those cases, participants tended to report that their decision
occurred before the action, which is a sensible inference. This temporal priority of the
reported conscious decision over the actual action was not observed in the immediate
condition, t(48) = 1.623, p = 0.111, dz = 0.231, perhaps due to the fact that the delayed
condition was presented during the same block of trials. (Nevertheless, recall that these
are averaged data for the entire session; the analyses of the learning curve are described
below and show a different and interesting pattern). The most critical and newest results
in this experiment are shown in Fig. 5. It shows the learning curves for the subjective
timing of conscious decision throughout the experimental session, depicted in blocks of 10
trials. The learning curves are very similar to those observed in Experiment 1, which
suggests that the course of learning is very similar for actions and decisions. Although
the binding effect for decisions in this experiment appears to be less pronounced than the
effect for actions found in Experiment 1, it should be noted that the estimated time of
decision should be located, at least in principle, before the action. Thus, the fact that
the binding effect is still present, that is, decisions are still shifted toward the
outcome and beyond the action, suggests that the binding effect for decisions is actually
strong. As already mentioned, we are referring to it as a superbinding effect.
Particularly during the early trials, participants seem to infer that their decisions
occurred near the tone, and after their actions had already occurred. Quite possibly, they
misjudged the timing of their actions, as was evident in Experiment 1, and therefore they
also misjudged the location of their decisions. Then, as training proceeds, the
participants appear to progressively learn that their decisions must have occurred earlier
than they thought, so they gradually reduce the superbinding effect. Interestingly, in the
delayed condition decisions are judged to occur much later than the actual actions during
the first block of trials, t(48) = 4.089, p < 0.001, dz = 0.584, but this superbinding
effect is then gradually corrected and by the fourth block of trials decisions are no
longer judged to occur after their actions, t(48) = 0.186, p = 0.853, dz = 0.026.
Nevertheless, by the end of training decisions are not yet judged as preceding the action.
It is quite possible that the estimation of the action is still suffering from some degree
of binding by the end of the training session, which suggests that, like in Experiment 1,
the accuracy of judgments could still improve if a more extended learning experience were
provided. In the immediate condition, however, the estimated time of decisions did not
differ from the actual time of action in the first block of trials, t(48) = 0.625, p =
0.535, dz = 0.089, but by the fourth block participants had learned to locate their
decisions significantly before their actions, t(48) = 5.27, p < 0.001, dz = 0.752. This
suggests that, as should be expected, the immediate condition was easier for them to
learn. The estimations of the time of decision during the baseline trials did not
significantly differ between the first and the last block of trials, t(48) = 0.752, p =
0.456, dz = 0.107, and thus no learning was observed during baseline. Estimated time of
decision was significantly lower than zero (see Fig. 5) from the very first block of
trials, t(48) = 3.381, p = 0.001, dz = 0.483, and remained so through the last block,
t(48) = 3.097, p = 0.003, dz = 0.442. That is, participants inferred that their decisions
occurred before their actions throughout the baseline phase.

<h>GENERAL DISCUSSION</h>
------------------

The two experiments reported here suggest that participants infer the time of their
actions and decisions from their consequences. By manipulating the time of those
consequences we were able to change both the time at which they believed they had acted
(Experiment 1) and the time they believed they had decided to act (Experiment 2). The
results of Experiment 1 extend previous reports in the action-outcome binding literature
(Garaizar et al., 2016; Haering & Kiesel, 2012; Haering & Kiesel, 2015; Haggard et al.,
2002; Moore, 2016); and the results of Experiment 2 extend previous reports in the
conscious will literature (Banks & Isham, 2009; Libet et al., 1983; Wegner, 2002). Taken
together, the two experiments suggest that the subjective estimates of the time of action
and decision are governed by similar processes. That is, both the subjective estimates of
the time of actions and decisions were affected by their consequences and tended to be
shifted toward them. Most importantly, we observed that estimations of the time of action
and decision were subject to learning and were progressively adjusted as learning
proceeded. We believe this is the first time that a learning curve has been reported to
show how people estimate the time of their actions and decisions. Below we elaborate on
these findings.

<hs>  Learning, antibinding, and superbinding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The two experiments showed that inferring the timing of decisions and actions is subject
to learning, since the participants were continuously adjusting their timing inferences.
We believe this is the first time that a clear learning curve has been shown for the
estimation of actions and decisions. Action-outcome binding effects found in previous
studies were replicated in the current experiments for both actions and decisions, and not
only when judgments were averaged across the experimental session (i.e. as they are
typically reported; see Figs. 2 and 4), but were also observed during the early training
trials (see Figs. 3 and 5). Importantly, however, those binding effects were progressively
corrected as learning proceeded (see Figs. 3 and 5). In some cases the binding effects
vanished for both actions and decisions as learning proceeded whilst in other cases this
learning and adjusting process yielded what we have called an antibinding effect: The
reported time of action tended to be progressively shifted away from the outcome, rather
than toward it, and in the immediate condition the action ended up being judged as
occurring significantly earlier than the actual action. Interestingly, as participants
learned to improve their estimations in the delayed feedback condition, they also
overcompensated (erroneously) their subjective inferences in the immediate condition.
Thus, this antibinding effect is also the result of learning. Seemingly, participants
learned that some time interval needed to be subtracted from the apparent time of action
(which was strongly influenced by the time of feedback), and so they subtracted this time
not only in the delayed condition but also in the immediate condition, thereby producing
the antibinding effect on the immediate trials. Thus, this antibinding effect has possibly
been favored by the fact that various intervals were presented in the same block, so that
what was learned for one of them implied an error when applied to the other one. It could
be argued that the antibinding effect might simply be reflecting that the computer program
is registering the time in which the action is completed whereas the participants might be
reporting the time at which they initiated the action. It is true that the time at which
an action is initiated should differ slightly from the time at which it is completed and
registered, but even if participants were using the initiation of the action as the
assessment point, we believe that this could not explain the observed effects. During the
early trials the participants’ estimate of their time of action in the immediate condition
does not differ from the actual time of action recorded by the computer. It is only with
time and experience that participants start to locate their actions away from the outcome
(and from the actual action), and this happens only in the immediate condition. In the
delayed condition the estimated time of action is shifted toward the outcome. If
antibinding were simply due to participants reporting the time of the initiation of their
action, then the learning curves should be identical (and flat) in the immediate and the
delayed conditions. We believe the interpretation in terms of learning is more plausible.
Indeed, effects similar to these ones have also been reported in cases in which, instead
of being trained on several delays simultaneously, participants are trained with one
delay, so that they learn to expect a certain action-outcome interval, and then they are
tested with different delays in a subsequent test phase. When tested with shorter delays,
participants feel that the outcome occurs before their action, and sometimes they even
feel that they have not caused the outcome, because it occurred too early for this to be
the case (Haering & Kiesel, 2012; Haering & Kiesel, 2015; Heron, Hanson, & Whitaker, 2009;
Stetson, Cui, Montague, & Eagleman, 2006). Moreover, in some cases participants may even
distort their perception of temporal order in order to make it consistent with their
causal beliefs. If the outcome occurs slightly before the action, participants will not
realize that it does. They may even reorder the sequence of events so that they come to
believe that the events occurred in the “correct” order, that is, action before effect
(Bechlivanidis & Lagnado, 2013; Bechlivanidis & Lagnado, 2016; Desantis, Roussel, &
Waszak, 2011; Heron et al., 2009). One potential problem of any experiment using Libet’s
clock and related procedures is that participants could preplan their actions. Then the
delayed feedback might be taken as indication of their inaccuracy to press the spacebar
exactly at the planned time during the early trials, which might be the reason why they
typically believe they acted later than they did. Note, however, that even though
preplanning is certainly possible, participants would still be taking the tone as a signal
of when the action (and decision) was performed, so we believe that the possibility of
preplanning does not undermine our main proposal that the time of actions and decisions is
inferred from consequences. Moreover, the role of learning is still evident in the
learning curve and shows that participants learn to gradually correct their estimation
error (regardless of whether their action was planned), and they gradually learn to give
more weigh to cues that are better signals of the action (such as, for instance, haptic
cues) while they progressively give less weight to cues such as auditory feedback, which
in this case is a totally unreliable cue. Also of interest is the effect observed in
Experiment 2 with the estimated time of decision as the dependent variable (Experiment 2).
In this case, participants shifted their estimated time of decision toward the outcome, as
we expected, but quite surprisingly, they even shifted it beyond the action. That is, they
reported that their decision had occurred after they had already acted. Given that the
subjective time of decision should reside, at least in principle, before the action, we
are using the term superbinding to refer to this effect. Importantly, just as participants
learned to reduce their binding effect for the time of actions in Experiment 1, they also
learned to reduce this superbinding effect for the time of decisions in Experiment 2.
Thus, superbinding is also subject to learning. In the immediate condition participants
learned in just a few trials to locate their decisions before their actions. In the
delayed condition, however, they needed more time to progressively locate their decisions
away from the outcomes and closer to their actions. Even so, by the end of the session
they were still estimating that they had decided after they had already acted. This
finding adds support to the idea that the time of decision is inferred from the apparent
time of action, which in turn is strongly affected by the time of its consequences.
Nevertheless, the shape of the learning curve suggests that if training were extended,
then participants would probably learn to estimate their decisions as occurring before
their actions, just as they do in the immediate and in the baseline conditions. In other
words, this superbinding effect should probably vanish with a more prolonged learning
experience. What this experiment clearly shows is that decisions are not directly
perceived, nor are they inferred to occur at a fixed interval prior to actions. Instead,
participants progressively learn to locate their decisions before their actions.

<hs>  How do people learn to adjust their inferences for actions and decisions?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It is worth noting that with respect to decisions (i.e. Experiment 2) there are no
objective parameters to learn from, that is, no parameters that require adjustment. In
other words, there is nothing that can be taken as an objective cue for learning about the
actual time of decisions. In principle, if no cues exist that can facilitate learning,
then learning should not take place, and adjustments would not make sense. Even so,
participants in this experiment are learning to locate their decisions before their
actions, and they are modifying their estimates with experience. We believe that they are
quite possibly learning to improve their estimations of the time of actions, as shown in
Experiment 1, and then they progressively learn to also subtract some time from the
estimated time of action, probably assuming that decisions must precede actions. As
already noted, the action is possibly the most reliable cue that can be used to infer that
a decision has been made and therefore the question of how people learn to infer their
decisions can be substituted, at least in part, by the question of how people learn to
infer their actions. James (1890) Ideomotor Theory posits that associations are formed
between actions and effects, and once they are formed the action will prime the mental
representation of the effect, just as the observation of the effect will also activate the
mental representation of the action. Consistent with this view, Ebbinghaus (1885) had also
suggested that associations between mental representations of events were bidirectional,
so that each event could activate the representation of the other one in either direction.
Although early 20th century research was not conclusive about the bi-directionality of
associations and the idea was generally abandoned (see Asch & Ebenholtz, 1962; Ekstrand,
1966, for review), more recent research has shown that associations can indeed activate
the mental representation of either event upon observation of the other one (Arcediano et
al., 2003; Arcediano, Escobar, & Miller, 2005; Dignath, Pfister, Eder, Kiesel, & Kunde,
2014; Gerolin & Matute, 1999). Recent extensions of James’ Ideomotor Theory (Dignath et
al., 2014; Elsner & Hommel, 2001), as well as the Temporal Coding Hypothesis developed by
Miller and his colleagues in the domain of associative learning with animals (Matzel et
al., 1988; Savastano & Miller, 1998) and humans (Arcediano et al., 2003; Arcediano et al.,
2005), suggest that associations encode not only the representation of the associated
events but also their timing relationship. That is, if a given temporal relationship
exists between the two associated events, each of these events will prompt the mental
representation of the other at the time when it should occur or should have occurred
(Dignath et al., 2014; Matzel et al., 1988; Savastano & Miller, 1998). This view predicts
that whenever an action is performed its effect will be predicted based on previous
learning; and that whenever the effect is observed, the occurrence of the action will be
inferred at its usual time. This proposal is also consistent with the idea that action-
effect binding might be the result of people using the consequences of their actions as
temporal markers in order to reconstruct the time of their actions (and thus their
decisions as well) (Banks & Isham, 2011; Friedman, 1990). These two processes (predicting
the second event from the first and inferring the first event from the second) have often
been regarded in the literature as two alternative hypotheses, but they are perfectly
compatible. Indeed, the two of them have been shown to play a critical role, and it has
been suggested that there is both a predictive and a postdictive (inferential) component
in the subjective estimation of actions and in the action-outcome binding effect (Chambon,
Sidarus, & Haggard, 2014; Moore & Haggard, 2008; Moore et al., 2009; Wenke, Fleming, &
Haggard, 2010). We do not want to mean that these predictions and inferences need be
perfectly explicit, conscious, and verbalized. However, because the action is associated
with its consequence (which includes timing), performing the action involves the
prediction (whether explicit or incidental) that its consequence will occur at its usual
time. Additionally, because of the bidirectionality of the association, the representation
of the action (including its time of occurrence) can also be backwardly activated upon
observation of its consequence. All of the above suggests that continuous adaptation (i.e.
learning) takes place when people infer the occurrence of their actions and decisions from
consequences, a view that is strongly supported by the present findings. According to the
most widely accepted theories of associative learning, learning consists of reducing
prediction errors (Rescorla & Wagner, 1972). Combining traditional learning theories with
the proposals described above concerning temporal coding and bi-directionality of
associations (Dignath et al., 2014; Matzel et al., 1988; Savastano & Miller, 1998), it
seems reasonable to expect that when participants perform an action they will
automatically predict (whether explicitly or not) that a consequence will occur at a given
time (as a function of their previous experience). We should also expect that if the
consequence does not occur at the expected time, then learning will consist of adjusting
those prediction errors until they are minimized. Moreover, from the occurrence of the
consequence, people should also adjust the time at which they believe the action should
have occurred, so that, if the outcome is moved forward, then the action should also have
been moved forward. It is currently a matter of debate as to whether the subjective
action-outcome interval becomes shortened in the action-outcome binding paradigm or
whether the whole subjective interval is not shortened but instead displaced. In other
words, it might be that action-outcome binding effects are due to a reduction in the
subjective interval between actions and outcomes, but it could also be that when the
outcome is delayed on a given trial, then the perception of the entire interval is shifted
in that direction so that the estimated time of action will preserve the length and
synchrony of the original interval (Heron et al., 2009). We believe our results are more
consistent with this second view. The estimation of the action (and decision) tended to be
shifted in the direction of the outcome or in the opposite direction as a function of
whether the outcome occurred later or sooner than the time it was expected to occur. The
estimated time of action and decision were also moved in the forward direction or in the
backward direction as a function of whether learning was in its earlier or more advanced
stages. Initially, the estimations tended to be displaced toward the outcome (which
occurred surprisingly late), but then they moved away from the outcome as participants
learned that the tone was not a reliable cue for the occurrence of action. Thus, it was
not the case that the interval became shorter, it just moved in one or the other
direction. A similar proposal has been advanced by different versions of the Comparator
Theory in the area of sensorimotor research (Frith, 2005; Frith, Blakemore, & Wolpert,
2000; Miall & Wolpert, 1996; Synofzik, Vosgerau, & Newen, 2008; Wolpert, Ghahramani, &
Jordan, 1995), according to which, people compute the difference between the sensory input
that they expect when performing the action and the one they receive, and they use the
output of this sensorimotor comparator process to realign the temporal interval (see also
Heron et al., 2009). Because in the present experiments we presented the consequences of
the action at two different intervals rather than just one, it was impossible for
participants to accurately predict whether a tone would follow the action (and decision)
immediately or whether it would be delayed. Under those uncertain circumstances, we
suggest that participants are likely to have minimized those errors by encoding some
averaged prototype of the intervals rather than (or in addition to) the correct ones.
Participants could then use this averaged interval, both when they predict the outcome of
individual trials and when they infer the time at which their action (or decision) occurs.
In other words, they probably predicted the consequences of their actions at some
intermediate point (e.g., 200 ms) and then, when they observed the consequences of their
actions, they possibly inferred that the actions had occurred at some intermediate time
before the consequences (e.g., 200 ms). We believe this might be important in the
development of the antibinding effect; on trials in which feedback occurred immediately
after the action, participants would still infer that their action should have occurred
earlier, thereby producing the antibinding effect. This view assumes that the whole
interval moves forward (or backward) rather than becoming shortened in binding effects
(see Heron et al., 2009). Learning is, by definition, continuous, and should always
correct errors. This means that one should expect that if changes are introduced in an
already learned situation, then new errors could occur, and then relearning will need to
take place again. Our results suggest that before starting the experiment, participants
already have some expectations about the standard interval between their action and their
consequences, due to their previous experience with the experimental context (typically a
computer). This is consistent with Cravo et al.’s (2013) proposal that pre-experimental
biases play a crucial role in the observation of binding effects with delayed outcomes, an
effect that we replicated here during early trials. If those outcomes are presented later
(or sooner) than expected, then participants assume that the action must have also
occurred later (or sooner). Our results show that those expectancies, or pre-experimental
biases, need to be learned and are continuously adjusted for each action-outcome pair. By
the same reasoning, this adjustment does not always consist of shifting the estimation of
the action toward the outcome (binding); sometimes it consists of shifting the estimation
of the action away from the outcome (antibinding), and sometimes decisions can even be
reported to occur after their actions (superbinding). In any case, and as learning
proceeds, those errors tend to be corrected and people gradually learn to adjust the
estimation of their actions to the occurrence of the actual actions. As they learn to
adjust the estimation of their actions, they also learn to adjust the estimation of their
decisions so that they appear to occur before their actions.


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<ART>Learning to read new words in individuals with Down syndrome: Testing the role of phonological knowledge
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Authors: Silvana E. Mengoni, Hannah M. Nash, Charles Hulme
DOI: 10.1016/j.ridd.2014.01.030
Year: 2014  |  Pages: 1098-1109
ASJC codes: 3203, 3204
Keywords: Down syndrome, Orthographic learning, Phonology, Reading

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<h>ABSTRACT</h>
--------

This study examined the effect of word level phonological knowledge on learning to read new words in Down syndrome compared to typical development. Children were taught to read 12 nonwords, 6 of which were pre-trained on their phonology. The 16 individuals with Down syndrome aged 8-17 years were compared first to a group of 30 typically developing children aged 5-7 years matched for word reading and then to a subgroup of these children matched for decoding. There was a marginally significant effect for individuals with Down syndrome to benefit more from phonological pre-training than typically developing children matched for word reading but when compared to the decoding-matched subgroup, the two groups benefitted equally. We explain these findings in terms of partial decoding attempts being resolved by word level phonological knowledge and conclude that being familiar with the spoken form of a new word may help children when they attempt to read it. This may be particularly important for children with Down syndrome and other groups of children with weak decoding skills. © 2014 Elsevier Ltd.

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<h>INTRODUCTION</h>
------------

Although there is variability between individuals, reading accuracy has been identified as
a relative strength in Down syndrome in comparison to general ability and reading
comprehension (e.g. Boudreau, 2002; Buckley, 1985; Cardoso-Martins & Frith, 2001; Hulme et
al., 2012; Laws & Gunn, 2002; Nash & Heath, 2011). Typically individuals with Down
syndrome show better reading of words than nonwords (Roch & Jarrold, 2008). Further, they
tend to have poor phonological awareness (Lemons & Fuchs, 2010; Næss, Melby-Lervåg, Hulme,
& Lyster, 2012), a skill that is important for decoding in typical development (e.g. Byrne
& Fielding-Barnsley, 1989; Hulme, Goetz, Gooch, Adams, & Snowling, 2007; Wagner et al.,
1997). This relationship is also present in Down syndrome (Fowler, Doherty, & Boynton,
1995; Roch & Jarrold, 2008); indeed a recent meta-analysis found that the deficit in
nonword reading in individuals with Down syndrome is moderated by their performance on
phoneme deletion tasks (Næss et al., 2012). The relative difficulties in nonword reading
and phonological awareness among individuals with Down syndrome suggests that they may be
recruiting compensatory strategies to support the development of word reading, such as
visual skills or vocabulary knowledge (Boudreau, 2002; Buckley, 1985; Kay-Raining Bird,
Cleave, & McConnell, 2000). A recent longitudinal study suggested that vocabulary is a
stronger predictor of reading development in Down syndrome than in typical development
(Hulme et al., 2012). Related to this, Nation and Cocksey (2009) have suggested that
phonological (sound-based) aspects of vocabulary knowledge may be particularly important
for learning to read when decoding is compromised. The aim of the current study was to
investigate the contribution of word level phonological knowledge to reading and
orthographic learning in individuals with Down syndrome. In order to study the mechanisms
behind reading development in Down syndrome, it is useful to consider models of reading in
typical development. The triangle model of reading (Plaut, McClelland, Seidenberg, &
Patterson, 1996) proposes two ways in which the phonology of words can be activated from
their orthography: directly or indirectly via semantics. Semantic information (meaning-
based knowledge) is argued to be most important when the direct phonological pathway is
impaired or compromised such as when reading irregular words (McKay, Davis, Savage, &
Castles, 2008; Taylor, Plunkett, & Nation, 2011) or in disorders such as Down syndrome or
dyslexia. Semantic knowledge is not well-specified in the triangle model and was
conceptualised as additional input to the phonological representation (Plaut et al.,
1996). In studies with children, semantics is typically assessed by vocabulary tasks.
However, these tasks often require both phonological and semantic knowledge about a word
(Johnson, Paivio, & Clark, 1996; Levelt, Roelofs, & Meyer, 1999). Nation and Cocksey
(2009) devised separate measures of phonological knowledge and semantic knowledge and
found that at the item-level, phonological, but not semantic, knowledge uniquely predicted
variations in children's reading of irregular words. They suggested that irregular words
may result in partial decoding attempts, and possession of a whole-word phonological
representation allows children to resolve these attempts and produce the correct response.
Such a process may well be important for learning to read in individuals who have decoding
difficulties, such as individuals with Down syndrome. One method to determine how existing
phonological knowledge affects reading is to conduct training studies with novel words.
This controls what phonological information about a word children have been exposed to. In
such studies, children are taught to read unfamiliar words or nonwords with or without
pre-training. Pre-training can be used to train phonological knowledge of words or
nonwords and may involve individuals hearing and saying the items (McKague, Pratt, &
Johnston, 2001) or discriminating between the target items and phonologically similar
distracters (Duff & Hulme, 2012). It has been found that typically developing children are
more accurate when attempting to read words that have received such phonological pre-
training (i.e. those they have phonological knowledge about), than those words which have
not (Duff & Hulme, 2012; McKague et al., 2001). This supports the idea that knowing the
phonological form of a word is causally related to children's ability to learn to read it.
Training studies can also explore how children establish orthographic (written)
representations of new words. According to Share's self-teaching hypothesis (Jorm & Share,
1983; Share, 1995) when a child encounters an unknown word, they independently convert the
letters into sounds, a process termed phonological recoding. Multiple successful
encounters with a word result in the formation of an orthographic representation.
Orthographic knowledge can be tested using orthographic choice tasks that assess whether
children can discriminate the correct written form of the word from a nonword with the
same pronunciation but a different spelling. If familiarising the child with the
phonological form of a word supports decoding, this should also promote the creation of an
accurate orthographic representation. The aim of the present study was to examine the
effect of phonological knowledge on written nonword learning in individuals with Down
syndrome. A group of typically developing children was matched to the individuals with
Down syndrome on word reading. A subgroup of the typically developing children was also
individually matched to the individuals with Down syndrome on decoding. This two-stage
matching procedure was used to investigate whether individuals with Down syndrome learnt
to read new words at a rate commensurate with their reading or decoding level. It was
predicted that individuals with Down syndrome would show written nonword learning in line
with their decoding skill but below the level expected from their word reading ability.
Phonological pre-training was designed to familiarise individuals with the phonological
form of the nonwords prior to encountering them in print. It was expected that this would
benefit the typically developing children (Duff & Hulme, 2012; McKague et al., 2001). The
individuals with Down syndrome would likely have poorer decoding skills than typically
developing children at the same level of reading and so make more partial decoding
attempts that could be resolved through phonological knowledge. Therefore it was also
predicted that individuals with Down syndrome would benefit more from phonological pre-
training than the typically developing children matched for word reading but that when the
groups were matched for decoding, they would benefit equally from phonological pre-
training.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Sixteen children and adolescents with Down syndrome (mean age of 13;08 (SD = 2;11; range
8–17 years); five males) were recruited through families who were also taking part in a
longitudinal study and all individuals completed the study. All individuals also
participated in a spoken word learning study approximately 12 months previously (Mengoni,
Nash & Hulme, 2013), which trained different nonwords using different methods and none of
the background data were re-used in the present study. All individuals had Trisomy 21
according to parental report and were known from previous testing to have a reading age of
at least five years. Parental consent was obtained for the individuals to participate in
the study. Of the individuals with Down syndrome, ten were in mainstream education: five
in primary schools and five in secondary schools. Four individuals were in special
education: two in secondary schools and two in college. Two individuals had joint
attendance at special and mainstream secondary schools. Thirty typically developing
children (mean age of 6;01 (SD = 0;06; range 5–7 years); 16 males) were recruited from
Year 1 and 2 classes in two primary schools. These year groups were chosen to correspond
to the reading ability of the group of individuals with Down syndrome, and indeed there
was no difference between the two groups on a test of single word reading (see Table 1).
This matching procedure means that any differences in word learning cannot reflect overall
differences in word reading ability, but it means that the typically developing group are
likely to have had more limited reading experience. Consent for the typically developing
children to participate was obtained from the headteachers of the schools and from their
parents. Children who had been identified with special educational needs were excluded.
All participants in both groups were monolingual English speakers.

<hs>  Assessment battery</hs>
  ~~~~~~~~~~~~~~~~~~

Testing for the longitudinal study in which the individuals with Down syndrome were
participating took place at the same time as this study and the tasks reported below were
part of the longitudinal study. It was decided to administer the same tasks to the
typically developing group to keep the procedure the same and to act as filler tasks
before the post-tests. The results of standardised tests are reported later to give an
indication of the relative profiles of the two groups.

        <hss>Nonverbal reasoning</hss>

        The Matrices subtest from the Wechsler Pre-School and Primary Scale of
        Intelligence IIIUK (WPPSI-IIIUK; Wechsler, 2003; reliability coefficient .90) was
        administered to measure nonverbal reasoning skills. In this task, children were
        asked to look at an incomplete matrix and choose the missing section from four or
        five options. Testing was discontinued after four incorrect answers on either four
        or five consecutive items.

        <hss>Word reading</hss>

        The Single Word Reading Test from the York Assessment of Reading for Comprehension
        (YARC) Passage Reading battery (Snowling et al., 2009; reliability coefficient
        .98) was administered. The test consists of 60 words that increase in complexity
        from simple words such as ‘see’ to more complex words such as ‘pseudonym’.
        Individuals were shown all words and asked to read as many as they could.

        <hss>Nonword reading</hss>

        The Graded Nonword Reading Test (Snowling, Stothard, & McLean, 1996; reliability
        coefficient .96) was used to test children's decoding skills. Individuals were
        presented with nonwords that increased in difficulty from ‘hast’ to ‘sloskon’, and
        were asked to read them aloud. There were five practice trials and 20 test items,
        and the task was discontinued after six consecutive errors. Individuals were
        awarded one point for each nonword read correctly.

        <hss>Expressive vocabulary</hss>

        The WPPSI-IIIUK Picture Naming subtest (reliability coefficient .88) was
        administered to test expressive vocabulary ability. Individuals were asked to name
        a series of 30 pictures ranging from car to thermometer, and the test was
        discontinued if five consecutive incorrect responses were made.

        <hss>Phonological awareness</hss>

        To assess phoneme awareness individuals were given an Alliteration Matching task,
        adapted from Carroll (2004). All stimuli were presented to children as spoken
        words and colour pictures. Individuals were asked which word out of a choice of
        two started with the same sound as a target word. The distracters were matched to
        the correct answer for global similarity to the target word. There were two
        practice items and 10 test items, and individuals were administered all items. The
        Sound Deletion subtest from the YARC Early Reading battery (Hulme et al., 2009;
        reliability coefficient .93) was also administered to test phonological awareness.
        Individuals were presented with spoken words and corresponding colour pictures,
        asked to repeat the word and then asked to delete a sound. Some of the items
        resulted in nonwords, e.g. say sheep without the /ʃ/, whereas some items resulted
        in real words, e.g. say boat without the /t/. There were 12 items, which tapped
        deletion of syllables and phonemes in initial, medial and final positions and
        individuals completed all items.

        <hss>Verbal short-term memory</hss>

        The Word Recall subtest from the Working Memory Test Battery for Children (WMTB-C;
        Pickering & Gathercole, 2001; reliability coefficient .72) was used to measure
        verbal short-term memory skills. The individuals heard a sequence of words and had
        to repeat them in the same order. The sequence of words increased in length,
        across trials. The test was discontinued when individuals scored less than four
        out of six items correct at a given list length. The number of correct trials,
        rather than span score, was used in analyses as this score had a greater range and
        therefore was more sensitive to individual differences.

<hs>  Design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

All individuals were taught to read 12 nonwords, and there was phonological pre-training
for six of these nonwords. Individuals were then tested on their phonological and
orthographic knowledge of the taught nonwords. The phonological pre-training condition and
control condition (no pre-training) took place in two separate sessions on different days.
All children were seen individually and the testing sessions lasted 20–30 min each. All
typically developing children were seen at school and the individuals with Down syndrome
were either seen at home or school. In the pre-training condition, the phonological pre-
training occurred first, followed immediately by written nonword learning. In the control
condition, the written nonword learning was the first activity. The background tasks were
then administered, followed by the phonological choice post-test and the orthographic
choice post-test.

        <hss>Training materials</hss>

        Twelve pairs of nonwords were created that had two different but homophonic vowel
        digraphs (e.g. ‘nirp’ and ‘nurp’). All nonwords had four graphemes and three
        phonemes and are shown in Appendix. Within the nonword pairs, there were no
        significant differences between the number and frequency of orthographic
        neighbours of the nonwords according to the ARC database (Rastle, Harrington, &
        Coltheart, 2002). The nonword pairs were separated into two lists ensuring that
        similar vowel patterns were not all in the same list. Within each pair, nonwords
        were randomly assigned to be either a target nonword or pseudohomophone
        distracter, which would be used in the orthographic choice post-test. These
        assignments were the same for all individuals.

        <hss>Learning procedure</hss>

        The individuals were introduced to the training procedure by being told they were
        going to learn some words from an alien planet. The two conditions (phonological
        pre-training vs. control) occurred on different days and the training procedure is
        depicted in Fig. 1. The two lists of target nonwords were counterbalanced across
        the two conditions, as was the order of conditions resulting in four versions of
        the experiment. The learning procedure lasted approximately 5–10 min and the
        children generally enjoyed it and attended well.

        <hss>Phonological pre-training</hss>

        There were four trials in the phonological pre-training procedure, each of which
        consisted of a repetition activity and a phonological consolidation activity.
        These activities were spoken and individuals did not see any written material.
        First, the individuals heard the nonword and repeated it. This was the same across
        each trial. They then did a phonological consolidation activity that was designed
        to familiarise individuals with the sound of the nonword. This increased in
        difficulty throughout the training. For the first trial the individuals heard the
        nonword segmented into its constituent phonemes and repeated this and they also
        heard the first and last sound isolated. The second trial was the same as the
        first but the individuals sounded out the nonword independently. For the third and
        fourth trial, individuals independently isolated the initial sound and the final
        sound, respectively. The six nonwords appeared in a fixed random order within each
        trial and corrective feedback was given, which was either “well done” or “that's
        not quite right” followed by the correct answer.

        <hss>Written nonword learning (reading aloud)</hss>

        There were four trials of written nonword learning, in which the individuals saw
        the written nonwords individually and read them aloud. Individuals were permitted
        one attempt at the answer and were then given corrective feedback, which was
        either “well done” or “that's not quite right” followed by the correct answer. The
        nonwords were printed in size 36 Century Gothic lower-case font-type on sheets of
        A4 paper. All six nonwords appeared in a fixed random order within each trial.
        Individuals were awarded one point for each nonword they read correctly. Problems
        with articulation are common in children with Down syndrome (Kumin, Councill, &
        Goodman, 1994; Roberts et al., 2005) and if a phoneme was pronounced incorrectly
        but with a consistent realisation then this pronunciation was accepted as correct
        in the nonword learning task.

<hs>  Experimental post-tests</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Two computerised post-tests, a phonological choice task and an orthographic choice task,
were administered approximately 10–15 min after the training procedure. The phonological
choice task assessed whether individuals could recognise the phonological forms of the
trained nonwords. The orthographic choice post-test assessed individuals’ recognition of
the nonwords’ spelling.

        <hss>Phonological choice task</hss>

        The phonological choice task was presented on a laptop computer using e-Prime
        version 1.0 (Schneider, Eschman, & Zuccolotto, 2002). Pictures of three children
        were shown sequentially, each accompanied by a spoken nonword that was either the
        target nonword or a distracter. The three pictures of the children then appeared
        simultaneously on the computer screen and the individual was asked who had said an
        alien word that they had learnt earlier. They could respond verbally or non-
        verbally by pointing. For each target nonword, two distracters were devised (see
        Appendix). The first differed by one phoneme; for half of the nonwords, the
        initial phoneme was changed and for the remaining half, the final phoneme was
        changed. The second distracter differed by two phonemes and was based on the first
        distracter but the remaining consonant was also changed, for example the
        distracters for ‘nirp’ were ‘nirt’ and ‘mirt’. Prior to the experimental trials,
        two practice trials with real target words were administered to familiarise the
        individuals with the task demands. These presented the real word ‘bird’ with the
        distracters ‘mird’ and ‘mirg’ and the real word ‘ball’ with the distracters ‘borz’
        and ‘morz’.

        <hss>Orthographic choice task</hss>

        The orthographic choice task was also presented using e-Prime. Three written
        nonwords appeared on the computer screen simultaneously and individuals were asked
        to pick the alien word that they had learnt that day. They could respond verbally
        or non-verbally by pointing. As outlined in Section 2.4.1, all target nonwords had
        a pseudohomophone distracter. A visual distracter was also created by changing the
        last consonant of the target nonword to a visually similar one. Therefore, the
        target nonword ‘nirp’ had the pseudohomophone distracter ‘nurp’ and the visual
        distracter ‘nirg’. All distracter items are shown in Appendix. Prior to the
        experimental trials, two practice trials with real words and pictures were
        administered. These presented the real word ‘bird’ with the distracters ‘berd’ and
        ‘birg’ and the real word ‘door’ with the distracters ‘doar’ and ‘doof’.

<h>RESULTS</h>
-------

Raw scores and a significance level of .05 were used for all analyses. One child with Down
syndrome did not score on the alliteration matching and sound deletion tasks for
behavioural reasons therefore N was reduced for these tasks.

<hs>  Performance on background measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To examine the distribution of scores within the groups the Shapiro–Wilk test was used and
histograms were examined. If the distribution of scores for a task were non-normal for
either or both groups then a Mann–Whitney U test was used to test the differences between
the groups. If the distributions were normal in both groups, then an independent samples
t-test was used. The mean scores, standard deviations and between-group test results are
reported in Table 1. Where possible age-equivalent scores are also reported to indicate
the developmental level of the two groups. As can be seen the two groups were matched on
word reading and from previous research it would be expected that the typically developing
children would perform significantly better than the individuals with Down syndrome on all
other tasks. This was the case for matrices, alliteration matching, sound deletion and
word recall, and there was also a trend for a difference on nonword reading. However the
two groups performed similarly on the picture naming task.

<hs>  Phonological learning</hs>
  ~~~~~~~~~~~~~~~~~~~~~

In order to investigate whether the phonological pre-training improved written nonword
learning, it must first be established that it resulted in increased phonological
knowledge in both groups. The mean scores for the correct response in the phonological
choice post-test are shown in Table 2. For both conditions and both groups, the correct
answer was chosen above chance levels (score of two). The two distracters were chosen at
similarly low levels across groups and conditions.

<hs>  Written nonword learning</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

The written nonword learning scores for both groups in the control and phonological pre-
training conditions across the four learning trials are shown in Fig. 2 and the overall
means are in Table 2. Individuals with Down syndrome generally performed at a lower level
than the typically developing children, with both groups doing better in the phonological
pre-training condition than the control condition. Learning increased across trials,
although this appeared to be greater in the control condition.

<hs>  Summary of results</hs>
  ~~~~~~~~~~~~~~~~~~

The phonological pre-training resulted in better performance on the phonological choice
post-test and improved ability to read the taught nonwords. In comparison to the typically
developing group, the individuals with Down syndrome performed more poorly when reading
the nonwords and there was a marginally significant trend for them to benefit more from
phonological pre-training. However there was no effect of phonological pre-training or
group on orthographic knowledge.

<hs>  Matching for target nonword decoding skill</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To test the prediction that individuals with Down syndrome would show written nonword
learning performance and benefit from phonological pre-training at a level equivalent to
their decoding skill, a subgroup of children from the typically developing group were
individually matched to the individuals with Down syndrome on their scores on the first
written nonword learning trial (first reading aloud attempt) in the control condition.
This criterion was chosen as it reflects ability to decode the nonwords with no previous
exposure to the spoken or written form. This resulted in 16 typically developing children
(seven males) being selected who had a mean age of 6;02 matched to the 16 individuals with
Down syndrome.

        <hss>Performance on background measures</hss>

        The performance of the typically developing subgroup on the background cognitive
        measures is shown in Table 3 along with the individuals with Down syndrome for
        comparison purposes. Matching on target decoding also resulted in the groups
        having similar scores on the standardised nonword reading test. Due to the uneven
        profile in individuals with Down syndrome, with word reading generally being a
        strength compared to nonword reading, the individuals with Down syndrome performed
        significantly better on the word reading measure than the typically developing
        subgroup. The two groups had similar scores on the picture naming task, but the
        typically developing subgroup performed significantly better on the remaining
        tasks of alliteration matching, sound deletion, matrices and word recall.

        <hss>Written nonword learning</hss>

        The scores in the control and phonological pre-training conditions during written
        nonword learning are shown in Fig. 3 for both groups and the overall means can be
        seen in Table 2. Levels of learning were similar in the two groups in both
        conditions and there was a clear benefit from pre-training in both groups. As with
        the data from the whole sample of typically developing children, learning occurred
        over the training procedure but this appeared to increase at a faster rate in the
        control condition. The significant interaction between condition and trial was
        followed up with a Tukey's HSD test, with means collapsed across groups. The only
        significant difference either across trials within conditions or between
        conditions on each trial was the difference in favour of the phonological pre-
        training condition compared to the control condition on trial 1 (HSD = 0.93).

        <hss>Summary of results: matching for target decoding</hss>

        Phonological pre-training led to similar increases in phonological knowledge in
        the individuals with Down syndrome and the subgroup of typically developing
        children matched on decoding. The two groups were also equally accurate when
        reading the nonwords aloud and benefitted from the phonological pre-training to a
        similar extent. There was no significant difference between the two conditions or
        groups when individuals were required to identify the correct spelling pattern of
        nonwords they had learnt.

<h>DISCUSSION</h>
----------

Vocabulary knowledge has been proposed to play an important role in reading development
for individuals with Down syndrome (Hulme et al., 2012). The present study built on these
findings and findings from studies with typically developing children, which suggest that
the phonological aspects of vocabulary knowledge are related to word reading skill,
particularly when decoding is compromised (Duff & Hulme, 2012; McKague et al., 2001;
Nation & Cocksey, 2009). Specifically this study investigated whether word level
phonological knowledge provides a benefit to individuals with Down syndrome when reading
new words. Compared to typically developing children matched on word reading, the
individuals with Down syndrome performed more poorly during written nonword learning.
Although both groups benefitted from phonological pre-training, there was a trend for this
benefit to be greater for individuals with Down syndrome. When the individuals with Down
syndrome were matched to a subgroup of the typically developing children on target
decoding skill, written nonword learning was equated in the two groups and both groups
benefitted equally from phonological pre-training. However, there was no effect of
phonological pre-training on a measure of orthographic knowledge in either set of
analyses. During written nonword learning, individuals with Down syndrome were less
accurate than typically developing children matched on word reading. However, as there was
a trend for the typically developing children to perform better on the standardised
measure of nonword reading, the two groups were not equated for baseline performance.
Therefore 16 of the typically developing children were pairwise matched to the individuals
with Down syndrome for target decoding. This also resulted in the two groups being well
matched on the standardised measure of nonword reading. There were no significant
differences between this subgroup and the individuals with Down syndrome during written
nonword learning. Thus as predicted, on the task of written nonword learning the
individuals with Down syndrome performed in line with their existing decoding skill but
more poorly than would be expected from their existing word reading level. This is also in
line with studies with children with dyslexia (Bailey, Manis, Pedersen, & Seidenberg,
2004; Ehri & Saltmarsh, 1995). The phonological pre-training exposed individuals to the
spoken nonwords and required them to engage in activities that emphasised the individual
phonemes within the nonwords. Familiarised nonwords were subsequently better recognised in
a phonological choice post-test by both typically developing children and individuals with
Down syndrome and as predicted, they were also read more accurately. Nonwords in the
control condition were also recognised at above chance levels in the phonological choice
post-test; this is likely to be because individuals had also been exposed to the
phonological form of the nonwords during the written nonword learning. Phonological pre-
training is argued to support reading by providing individuals with a whole-word
phonological representation of the new word. This can resolve competition between the
correct pronunciation and pronunciations derived from decoding the letter-sound mappings
and therefore provide a pronunciation match for partial decoding attempts (Nation &
Cocksey, 2009). There was a marginally significant trend for the individuals with Down
syndrome to benefit more from phonological pre-training than the typically developing
children matched for word reading. In the context of the triangle model, when the
phonological pathway is compromised, such as with irregular words that cannot be decoded,
existing phonological knowledge is considered to have a stronger effect on reading (Nation
& Cocksey, 2009). This may also be the case for children who have an impaired phonological
pathway and thus may apply to all words regardless of regularity for individuals with Down
syndrome. Specifically, as the individuals with Down syndrome were less able to decode the
words, they would be more likely to produce partial decoding attempts that phonological
knowledge could then help resolve. This between-group difference was no longer present
when the individuals with Down syndrome were matched to the typically developing subgroup
for target decoding. This is argued to be because the two groups now made an equal number
of partial decoding attempts, therefore resulting in similar opportunities for
phonological knowledge to aid performance. Our findings support the suggestion of Taylor
et al. (2011) that existing phonological knowledge about a word could be incorporated
within the triangle model as item-specific phonological representations. To assess whether
semantic knowledge also contributes to reading when decoding is compromised, such as with
individuals with Down syndrome, the effect of semantic pre-training could be compared to
phonological pre-training. Both typically developing children and individuals with Down
syndrome showed increased scores across the trials during the written nonword learning.
However this improvement was greater in the control condition than the phonological pre-
training condition, particularly at the beginning of the training procedure. The nature of
the corrective feedback during written nonword learning may have contributed to this
difference between the two conditions. For the feedback, individuals heard the correct
pronunciation of the target nonword and, as suggested by the lexical quality hypothesis,
this may have provided more benefit to the control nonwords as it added new phonological
information to the lexical representation (Perfetti & Hart, 2002). Previous studies that
have examined the effect of phonological pre-training on written nonword learning in
typically developing children have not included post-tests that specifically tested
orthographic learning (Duff & Hulme, 2012; McKague et al., 2001). In the present
experiment the target item was selected at relatively high levels of accuracy in an
orthographic choice post-test by both groups in both conditions. Therefore the same level
of orthographic knowledge was demonstrated for nonwords that received phonological pre-
training and those that did not. Furthermore despite showing poorer learning, the
individuals with Down syndrome showed the same level of orthographic knowledge as the
typically developing sample matched on word reading. The self-teaching hypothesis posits a
central role for phonological recoding, or decoding skill, in forming orthographic
representations. Therefore it would predict that better performance during training (i.e.
in the pre-training condition and for the typically developing children) would result in a
stronger orthographic representation that would enhance performance in an orthographic
choice task. It could be that the task was not sensitive enough to capture this;
alternatively, repeated exposure to the orthography of the target word may have resulted
in individuals creating and storing an orthographic representation of the nonword,
regardless of whether they read it correctly. To test this, the orthographic choice task
could be administered after the first trial of written nonword learning, when in the
control condition participants will have had minimal exposure to the phonology of the
word. It should be noted that the present study assessed written nonword learning
immediately after training and not in the longer term. It is clearly important both
theoretically and practically to know if learning is maintained, particularly as there is
some evidence that points to impairments in consolidating newly learnt skills and on
verbal, visual and spatial long-term memory tasks in Down syndrome (Carlesimo, Marotta, &
Vicari, 1997; Pennington, Moon, Edgin, Stedron, & Nadel, 2003; Visu-Petra, Benga, Ţincaş,
& Miclea, 2007; Wishart, 1993). In a written nonword learning study with typically
developing children by Bowey and Muller (2005), an orthographic choice task was
administered immediately after learning and six days later, and there was significantly
better performance on the immediate post-test than the delayed post-test. In future, there
is a need for studies with individuals with Down syndrome to include a delayed test of
written nonword learning. There are a growing number of studies evaluating reading
accuracy interventions for children with Down syndrome. Training phonological awareness,
letter-sound knowledge and new vocabulary results in improvements of the directly taught
skills and the reading of untaught words, although there is less evidence that this
training extends to nonwords (Cologon, Cupples, & Wyver, 2011; Goetz et al., 2008; Lemons
& Fuchs, 2010). In a randomised controlled trial, Burgoyne et al. (2012) found that an
intervention combining both phoneme awareness and broader oral language skills, with a
large emphasis on vocabulary instruction, had a significant effect on word reading. The
present study provides evidence that the phonological aspect of vocabulary knowledge may
help promote reading achievement and therefore being presented with the spoken form of a
new word before seeing it in print could be a valuable part of reading instruction for
children with Down syndrome.


<h>REFERENCES</h>
----------

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<ART>Listening
=========

Authors: Katy Bennett, Allan Cochrane, Giles Mohan, Sarah Neal
DOI: 10.1016/j.emospa.2015.10.002
Year: 2015  |  Pages: 7-14
ASJC codes: 3205, 3207
Keywords: Empathy, Ethnographic, Feelings, Listening, Multiculture, Time

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

In this paper we reflect on the kind of listening that happens in research whilst taking part in a keep fit group and getting sweaty, that pushes us to ask an interviewee 'Are you alright?' and haunts us when the project is over. This is the kind of listening that weaves through, around and beyond what is immediately heard, including the unspoken, the articulateness of objects and the listening that comes through participating. The paper stems from a project concerned with how people live, experience and manage cultural diversity and ethnic difference in their everyday lives in urban England. Divided into two sections, the first part introduces our methods that included participant observation, interviews and repeat in-depth discussion group meetings. The second section reflects on our experiences of listening whilst doing, explores feelings that mediate listening and considers the time involved in listening.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Omar was eighteen years old and a student at Grafton College in Milton Keynes. He was one
of the young people taking part in a discussion group for our research concerned with
multiculture and how people live ethnic diversity. Outside of college Omar told us that he
enjoyed spending time with his girlfriend, working to earn money and working out at the
gym. His uncle liked body building too. He pulled his phone out of his pocket, found an
image of his uncle's muscly, naked torso and passed it around for us to look at. Omar
talked quickly, positively and hopefully, but how he talked sat uneasily with what he said
about his life, the transience of his childhood, his absent mother, and how we experienced
the group discussion. The phone was returned to Omar and placed on the table,
contributing, somehow, to the group. Crisps, biscuits and drink fed into the unfolding
discussion, adding something substantial, providing us with something to hold onto, bite
into as we talked and listened to one another. We return to Omar later, but we begin with
him to introduce the focus of this paper concerning the kind of listening that weaves
through, around and beyond what is immediately heard, including the unspoken, the
articulateness of objects and the listening that comes through participating. Whilst what
Omar said was important to our research, there was more than this to listen to. Textbooks
on research methods are helpful regarding talk - who to talk to, how to ask questions,
turning talk into transcripts and how to analyse them (Valentine, 2005; Longhurst, 2010;
Crang and Cook, 2007), but are less helpful on listening (Bennett, 2002). This paper aims
to fill that gap a little and is for students and researchers who want to think about
their listening and how this shapes their understanding and research. In this paper we
draw upon our experiences of listening in our research on ‘Living Multiculture’1, one of
our aims was to devise a methodology that involved trying to listen better to everyday,
mundane practices and experiences of multiculture. Without marginalising everyday racism,
exclusion and inequalities we wanted to explore the quieter micro narratives and routine
encounters that are part of the lives of a growing majority of people living in urban
England. In our ‘Living Multiculture’ project we took a different approach to ‘the
segregation-distrust-conflict model’ that has underpinned and shaped UK public and policy
debates about cultural difference (see Neal et al., 2013, 2015a, 2015b). Instead we were
influenced by an alternative narrative of convivial encounter across difference (Back,
1996; Amin, 2002; Gilroy, 2004; Wise, 2009; Gidley, 2013; Thrift, 2005; Swanton, 2010;
Wise and Velayutham, 2014; Wessendorf, 2014) that does not ignore tensions (Clayton, 2008;
Rogaly and Qureshi, 2013) but recognises unpanicked, everyday, routine experiences of
multiculture (Noble, 2009) and the developing skills and competencies that shape these
(Wise, 2009; Neal and Vincent, 2013; Sennett, 2012; Wilson, 2011). This means that our
listening involved methods that asked questions and we were concerned about developing
good research practices for listening to complex stories of hardship, loss, disorientation
and exclusion. These practices involved repeated and sustained connection with people and
places, reflection on our experiences of the research and recognizing that we were
stitched into the possibilities and limits of our listening and understanding (Pratt,
2010; Kanngieser, 2012; Dreher, 2009). Our methods also involved attending to mundane
practices that shape everyday lives and experiences of multiculture; the sometimes
wordless encounters, small gestures, ambiguity and atmospheres that embody getting about,
amongst and along with others. As we detail later, our research involved interviews,
repeat in-depth group discussions and participant observation (Neal et al., 2013, 2015a,
2015b; Jones et al., 2015). In this paper listening is broadly conceived. This is in part
a reflection of our different disciplinary backgrounds and how individuals listen in
unique ways (Forsey, 2010). It also reflects trends regarding ethnographic research, which
involves a range of methods often including participant observation alongside other
methods such as interviews (Crang and Cook, 2007). Some lament the demise of participant
observation as a stand alone method and there is concern regarding the crowding of this
method with others which demand talk under the label ‘ethnographic’ (Gans, 1999; see also
Forsey, 2010). Interesting questions have been asked regarding what gets lost in ‘verbal
methodologies’ (Crang, 2005; Back, 2003, 2007, 2012). Whilst this paper does not
prioritise one method over another, it is interested in the kind of listening required in
ethnographic research that involves not only attending to, and analysing talk, but, for
example, acknowledging the context in which stories are told and how research interviews
and group discussions are experienced. For us listening has a relational, intersubjective
dynamic, decentring the researcher and illuminating the role of participants in the
creative process of research and understanding. Participants include the non-human and in
the paper we consider some of this vital matter, such as Omar's phone and a crisp packet,
that substantiated our listening (Thrift, 1999; Conradson, 2005; Simpson, 2013). Finally,
we consider the time involved in listening. Whilst projects and research contracts have
end dates, listening does not and we live with, return to and listen to moments,
conversations and memories of participants that won't leave us alone. The paper is divided
into two sections. In the first section we briefly introduce our methods, detailing our
planning for listening. In the second we reflect on our listening, focusing on three
issues in particular: listening whilst doing, the feelings that mediate listening and the
time involved in listening. The paper draws upon a diverse literature to think about
listening. To help us explore ‘listening whilst doing’ we explore an embodied approach to
listening evoked in methods that include participant observation (Laurier and Philo, 2006;
Swanton, 2010; Rogaly and Qureshi, 2013; Wise and Velayutham, 2014; Wessendorf, 2014;
Crang, 1994), participatory action research (Askins and Pain, 2011) and non-verbal
research techniques (Macpherson and Fox, 2014; Fox and Macpherson, 2015; Bingley, 2003).
Different theoretical, disciplinary and political agendas motivate this various research,
but common to all is not only listening to what participants might say, but listening
whilst doing and involved in happenings, evoking something of the experience of being
there. To consider feelings that mediate listening, the paper is indebted to the work of
geographers with expertise in psychoanalysis and psychotherapy (Kingsbury and Pile 2014,
Cullen et al 2014, Davidson and Parr, 2014; Kingsbury, 2009; Bondi, 2003, 2005, 2014a,
2014b). Especially helpful has been writing on empathy (Bondi, 2003, 2014a) and listening
that involves ‘tuning in’ (Paterson, 2014) to our experiences and how they might connect
to the experiences of participants and what they are trying to ‘tell’ us, whilst also
mindful of our different subject positions that require reflection and shape what is
heard. Finally, a body of work in the field of education and arts based research
concerning acousmatic texts is a source of inspiration regarding our reflection on the
time involved in listening (Daignault, 2005; Aoki and Aoki, 2003; Leggo, 1999). Sometimes
texts that make us tingle, the really inspirational ones that leave us buzzing, seem to be
listening to us too as we read them. In this paper we explore work on acousmatic texts to
consider the impact of time on our listening, research and transcripts.

<h>OUR METHODS AND PLANNING FOR LISTENING</h>
--------------------------------------

Our attempt to listen better in our research did not involve inventing new methods, but
did involve weaving the work and ideas of researchers and writers regarding participating
and embodied listening, empathy and acousmatic texts outlined above into our approach and
planning. As this section begins to introduce, our methods involved participating and
joining groups in case study areas that were home to at least one of us, repeat group
meetings with time in between to reflect on our listening and a team of researchers shaped
by individuals who brought different readings and interpretations to transcripts and field
notes. We situated our research project in three case study areas, chosen because of their
particularly dynamic populations, urban geographies of diversity and multicultural
formation. Our case study areas were the London Borough of Hackney, Milton Keynes, a new
city near London established in the 1960s, and Oadby, a small suburban town on the edge of
Leicester in the English midlands. These case study areas represent some of England's most
dynamic and (super) diverse populations shaped by people with a wide range of ethnic
backgrounds. Between 2001 and 2011 Hackney and Milton Keynes were amongst the UK's top ten
fastest growing places with their populations increasing by 20% and 17% respectively
(Milton Keynes Council, 2014; Hackney Borough Council, 2013). The ethnic composition of
both places also changed between 2001 and 2011 with Hackney's long history of ethnic
diversity intensifying (Neal et al., 2015a) and Milton Keynes' black and ethnic minority
group doubling. Although Oadby's population growth was nothing like as dramatic, between
2001 and 2011 it was amongst England's fastest changing places in terms of its ethnic
composition (Leicestershire County Council, 2013). Each of our three case study areas was
also home or very close to home for at least one of us and we saw ourselves as part of the
social world we were studying. Our connections with these places also played a role in
shaping what we did and knew and added an extra layer of responsibility regarding these
places and our research participants. We imagined the research through specific sites that
included a park, café, library, social and leisure clubs and a college in each of our case
study areas where different and differently positioned people (around age, education,
residency, gender, class and ethnicity) encounter and interact with one another in ways
that feel comfortable and less so. Our way of getting involved in these sites included
taking part in activities already happening inside them, joining, for example, a running
or writing group. Whilst our attempts to listen better involved decentring ourselves and
taking part in selected sites, we are a group of mostly white social scientists which
raises ethical issues around privilege (Skelton, 2001; Dwyer, 1999). In this paper ‘we’ is
complicated. One layer of ‘we’ involves the paper's authors, but another layer of ‘we’
refers to our fieldwork which involved not only us, but also researchers and research
consultants who were involved in different stages of the project. We are a diverse group
of people in all sorts of ways but especially with regard to the ways in which people are
typically identified around class, gender, age and ethnicity. Whilst ‘we’ describes a
collective and collaborative approach, some of what we write about in this paper involves
individual experiences fuelled by particular contributions to the project. So our use of
‘we’ is somewhat nuanced and we break out into individual experiences when this is
necessary. Undoubtedly how others identified and related to us shapes our particular
findings and how they are read. Who we are and how people see us affect how we listen,
what people tell us and what we hear (Dreher, 2009). That said, we attempted a
biographical approach to identity, one that recognises its complexity and ways in which it
is shaped through interaction with people and places through the course of lives (Swanton,
2010; Nayak, 2006). For example, one of us – Giles – is mostly identified as white and
usually identifies himself as white, but is mixed ethnicity with an Indian father and a
White British mother, living his infancy in Ghana and later moving to Sheffield where he
tells people he is from. Many of our respondents had similarly complex and interesting
stories to tell regarding their biography and processes of identification. As we have
discussed elsewhere (Neal et al., 2015b), though, we found that when we were writing about
our observations in our field notes we sometimes slid into seeing through an
essentialising lens that highlighted people's physical and cultural characteristics to
identify them and evoke difference while paradoxically writing about how difference might
have been disrupted. We attempted to counter this objectifying way of seeing through the
layering of methods that comprised joining in and taking part and listening to
interviewees' experiences of everyday multiculture that evoked both multi-textured
understandings of identity and belonging that reckon with essentialism, but also their
experiences of objectification and racism (Clayton, 2012). Our key methods included
participant observation, interviews and repeat in-depth group discussions. The aim of our
participant observation (Laurier, 2010; Cook, 2005; Crang and Cook, 2007) was to listen,
watch, feel and be able to describe site worlds and the context, people, practices,
etiquette, uses, rhythms, things and atmospheres that shaped them. We recorded our
observations through writing, attempting to capture the minutiae of encounters and
interactions happening around us and that we ourselves were involved in. We wrote about
what happened in college canteens, parks, libraries and cafes and at events like world
picnics in parks (Crang and Cook, 2007). We wrote about the keep fit group and writers
group meetings that we joined. We returned to our sites at different times of the day and
at different points of the year to get a sense of their daily and seasonal rhythms. A
second key method of the research was repeat in-depth discussion groups (Burgess et al.,
1988a,b). We set up groups of people who used the park, attended the college or were a
member of the selected social club. We used a number of strategies to meet potential
participants. These involved going along to and taking part in group activities, such as a
keep fit group, running club or a writing group, and events, for example a community fun
day. Before we set up the first group meeting, we interviewed participants one-to-one to
get a sense of their biography (Valentine, 2005; Longhurst, 2010). In total we interviewed
88 people. Our repeat in-depth discussion groups were influenced by the psychoanalytically
informed group work of the geographers Burgess, Limb and Harrison who, in the 1980s,
considered not only what people said, but also listened to group dynamics and how they
themselves experienced the groups (Burgess et al., 1988a,b). We met with 12 groups three
times over a six month period, stretching from Autumn 2012 to Spring 2013. Our groups
ranged in size with between 5 and 11 members. Some of our groups (such as our park user
groups) were made up of people who did not know each other whilst others were comprised of
people who did. Our in-depth discussion group meetings often involved two researchers for
practical reasons around hosting and organising groups, but also to explore how they
experienced group meetings. Repeat meetings gave us time to step back and reflect on our
listening and understanding with others (members of the research team and locally based
advisory groups2) (Bondi, 2013, 2014a). The final group meeting embraced the
intersubjective nature of research (Jervis, 2014), allowing us to explore issues that
seemed pertinent to that particular group, our understanding of those issues and their
reactions to what we had picked up on. A final stage of the research involved iterative
interviews with local and national policy makers. In each of our case study areas we
shared some of our emerging findings with policy makers and community activists, prompting
discussion and reflection around these. This stage of the research involved 22
interviewees working at a local level and four at a national level concerned with, for
example, issues of race equality. Our aim was to listen to policy maker and activist
responses to our research, whist attempting to connect our research to their work.

<hs>  Listening whilst doing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

There are some methods in particular that involve listening whilst doing and these include
participant observation, participatory action research and non-verbal research techniques
(Phillips and Johns, 2012). Different research agendas and ambitions often underpin these
various methods, but they do not usually involve asking questions, rather sliding into the
worlds of others and creating space in which the research can unfold (Crang and Cook,
2007). Listening whist doing is valuable because it concerns an active, sensuous, embodied
approach to listening bringing experiences and feelings to the foreground of research as
they weave through words said and happenings observed. Research practices at the interface
of social science and psychotherapy involve embodied, or ‘whole body listening’
(Macpherson and Fox, 2014; Fox and Macpherson, 2015), that entails attending to gestures,
textures, atmospheres, things and the context of happenings (Back, 2003, 2007, 2012;
Mitchell and Back, 2006; Bissel, 2010; Kanngieser, 2012). Whole body listening involves
ears, eyes, beating hearts, feelings, skin, pores, tingly, hair raising moments and more
besides (Paterson, 2015). Some of our methods involved listening whilst doing as we joined
groups to take part in their various activities, such as writing, running and keeping fit.
None of these activities were set up for the purposes of our research, but concerned an
involved, embodied and agile approach to listening. One of us, Katy, joined a keep fit
group in Knighton Park, on the edge of Oadby: It's 9.30, damp and cold and I'm taking part
in a keep fit group. We're a mixed group of young to middle aged, white and British Asian
women. .......We set off. Jogging, sprinting, dropping onto the wet ground to do press
ups, crawling. Some of the exercises require us to work in pairs and so we're working with
partners, using them as support to do leg exercises before we swap partners again. It
feels a bit odd holding people I've only just met. The group runs into a woman doing her
morning walk, we're difficult to avoid and Jake yells at us to give the walker space. I
work with Maggie, Paula, Kay, Amita, Shivani and others, we introduce ourselves, laugh a
lot because it's all a bit awkward and hard work. I'm crawling down a bank being yelled at
by Jake for holding my bum too high. We're slipping and sliding in the mud (Knighton Park
15/10/12). Three times a week a group of mostly women meet in the car park just before
9.30am to attend a keep fit group. Participation involves running and jogging through the
park on paths and off track, using the ground and park furniture, such as park benches,
for various exercises. The keep fit group is run by Jake, a black, male fitness
instructor. Katy went to group sessions on Mondays, and sometimes Wednesdays, over a six
month period. The size of the group varies depending on the weather, time of week or year.
Group members are generally middle class, although not always, young to middle aged,
ethnically mixed, comprising women who work part-time, are self-employed or full time
mothers. Surprising to Katy was the physicality of her listening whilst sweating, sliding
around in the mud and holding, touching and pressing upon others she had just met. The
group involves people who wouldn't ordinarily cross paths, and involves encounters with
others also using the park, for other activities, at the same time (Neal et al., 2015b).
Dog walkers are the other main users of the park at 9.30am on a weekday. Dog walkers are
generally white and older than the group of women and not always at ease with the bubble
of chatter and Lycra clad bodies taking up paths accompanied by Jake loudly yelling
instructions. There is little in the way of verbal exchange across the groups, but
listening involved running past unsmiling faces and cold shoulders from the dog walkers, a
change in pace and an altered atmosphere amongst us. We're sliding around in the muddy wet
grass, walking like bears, hands and feet on the ground, going up to each other, lifting
one hand off the ground, then another, for a ‘Hi 5’. We're grunting, groaning and giggling
as we approach each other. The ground is slippery and Jake warns us about the wet leaves
….. (Knighton Park 29/10/12). Notable are the non-human things and beings that mediate
social relations and substantiate listening (Askins and Pain, 2011). Things sparked and
facilitated interactions between participants in ways barely noticed such as the wet
leaves described in the extract above, but also water bottles, park benches, dog shit and
dogs amongst many things and non-human beings that formed our field notes. In our field
notebooks we wrote about things that mattered to us and were pointed out to us by others.
Loose dogs unsettled the group, causing screams if they got too close, dog shit was
irritably pointed out by a group member to others, reigniting tensions between dog walkers
and keep fit group members, the offer of a water bottle soothing atmospheres experienced
in the park, creating friendly relations amongst group members. All of this vital matter
substantiated listening, shaping experiences of others and this place, making an
impression, having an affect (Thrift, 1999; Conradson, 2005; Simpson, 2013). Interesting
to the research project was the dynamic, simultaneous interplay of tense and easy
relations amongst ethnically diverse individuals and groups and the impact of these
experiences on relationships with sites and places. The kind of ‘data’ that listening
whilst doing elicits is somewhat different compared to, say, interviewing in that it
emerges around and through the shared activity, being with, but not generally sat
opposite, and being amongst others – human and non-human. Listening whilst interviewing
often involves building up information pixel by pixel, but listening whilst doing involves
being confronted by a big, blurry screen and trying to bring this into focus. This analogy
is too reliant on the visual, but explains the contrasting processes of understanding.
Bringing a research site into focus is nicely exemplified in a researcher's field notes as
he had lunch in a college six form area in Oadby: ‘The mood in the canteen was generally
playful – as I filled my bottle up at the water tank, for example, an Asian group of boys
and girls were messing around with a packet of crisps, with one trying to crunch the
packet up and the other running away. Towards the end of our time in the canteen, a boy in
a turban and another Asian girl sat next to us. The boy quietly got on with studying, but
the girl was attracting the attention of a group of Asian lads, and some girls, on the
comfy chairs next to us. I heard one of them lean over and say to the girl, ‘sorry, we
were just taking the piss out of you’. The girl smiled and the lad said, ‘sorry, what was
your name again?’ (Uplands College, Oadby, 10/10/12) Understanding produced through
listening whilst doing is created through words said but also whilst, as exemplified
above, experiencing a six form area unfold through an atmospheric mix of people and
objects involving a crisp packet, messing around, laughter and wipe clean leather effect
comfy chairs supporting more bodies than intended as students squeezed into them.
Listening generated understanding about a college that, although very ethnically diverse,
involves space and groups often organised around ethnicity (and gender), but also mixing
on the edges of, and across, groups in ways that staff and students (less) consciously
recognise.

<hs>  Experiences and feelings that mediate listening</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Throughout the previous section dealing with listening whilst doing there was reference to
experience and feelings. In this section we bring feelings centre stage to consider how
these mediated our listening. In our field notes we wrote about our experiences of
interviews, group discussions and fieldwork, grappling with feelings and happenings that
weaved around and through talk. A common thread in emotional geographies is the
relationality of feelings and how what we experience is, in some way, connected to the
feelings of others (Bondi, 2005). We drew upon this to listen to what was being
communicated beyond and around what was immediately heard. To start this section we return
to the college in Oadby to explore a third and final group discussion. In an earlier
meeting this group had talked about ‘mixing’ and in our final meeting we asked what this
involved. Ayo, who usually sat at a table in the six form area identified as where black
African women sat, responded: ‘It's like if I'm just talking randomly in my perspective
like, mixing is just us interacting with other people of course, but it's not to an extent
where I can engage with them on that level because obviously I haven't experience of what
– how they see things in like in their perspective, so it's mixing – you understand them
to an extent but it's not like, you know diluting, if you know what I mean?’ (Ayo, Group
Meeting 3, Uplands College, Oadby 22/4/13) Amelia, a white student with a British father
and German mother, picked up the conversation, emphasising that she mixed with people with
different ethnic backgrounds and that she and her friends did not have a regular table.
Ayo responded that although she was associated with the Black African table that she also
mixed with others, but said, ‘I'm not comfortable with everyone that I sit with, so
there's different levels of comfortability’. Amelia picked up on the diluting idea,
describing it as ‘weird’ at which point Ayo withdrew from discussion. ‘Are you alright?’
one of the researchers asked her. ‘Yes’, but she was much quieter. Silent for the time
being. Whilst this conversation was on-going a researcher detailed in her field notes how
a blue plastic cup was passed back and forth between two students, Amira and Tahir, who
were silently and amusingly communicating their horror of lipstick marks on what should
have been a clean cup. This was another exchange happening between students, who could
have been opting out of what was being discussed and/or busy with their own relationship.
Another researcher focused on her experiences of the group not feeling very relaxed, ‘a
bit of tension’, ‘giggly’ talk and the ‘unhappy’ response of Ayo: ‘We're a group of nine
now (….). The group doesn't feel as relaxed as I expected (….) They help themselves to
drinks and snacks, seem to enjoy us reiterating, repeating and pushing issues and phrases
they've introduced in previous meetings. But there is definitely a bit of tension. Perhaps
this has something to do with impending exams that all students seem to be sitting soon
(…) But there are other things happening in the room, especially between Amira and Tahir.
Amira is giggly and constantly looking across me to Tahir for reassurance, for him to
agree with what she has said, to tease him about something he's been involved in, winding
him up. Tahir is defensive, a little less open than in previous meetings. He's definitely
much quieter. Amelia and Ayo keep the conversation going, keep the group on track, ease
the tension or whatever's going on between Tahir and Amira. Ayo and Amelia are two of the
chattier, more confident students and are forthright regarding their experiences and
opinions. At one point Amelia says something that Ayo is unhappy about. I try to encourage
Ayo to have her say, but she withdraws, still managing to make some kind of point in the
process.’ (Field notes, Uplands College, Oadby, 22/4/13) On the one hand we have the
recording and transcript of the group meeting that we listen to, read and analyse. Shaping
our listening are our experiences of that group, which take us by surprise because this
group has worked well in the previous two meetings. The dirty plastic cup is amusing the
students, annoying us, with Amira seeking the attention of Tahir and getting nothing back
apart from a dirty cup. What do participants mean by mixing? Ayo's response perhaps
unravels the carefully constructed consensus that this is a very ethnically diverse school
comfortable with its diversity. Amelia, a white student, holds Ayo to account, uses the
word weird and the atmosphere feels worse. The thread of conversation between Ayo and
Amelia had kept us (researchers) on track whilst others were distracted and amused by
Tahir and Ayo. The word weird is said, ouch, oh hell. Ayo is silenced. We empathise with
Ayo. Are you alright? Should we have asked this? She withdraws from the conversation, her
silence, our experience of that silence, is now a rather different kind of silence, as
punchy and informative as what is being said as others move the conversation on, smoothing
over what has happened. Is this how students cope with tensions? How would Ayo and the
group have coped had we not acknowledged our feelings? Liz Bondi (2003) described empathy
as “a process in which one person imaginatively enters the experiential world of another”
(Bondi, 2003: 71). For us this involved working with our feelings and a kind of imagining
in (to the experiences of participants - Are you alright (Ayo)?) in an attempt to
appreciate where they were coming from whilst mindful of differences (and connections)
around ethnicity, age, gender, residency, class and more besides (Sennett, 2012; Cochrane,
2014). The importance of sustaining a sense of difference or ‘alterity’ in empathy is
emphasised by Liz Bondi (2014a) through her use of the ‘third position’ which involves
shifting between participating in a relationship and observing it, encouraging a ‘stepping
back’ rather than stepping into the (metaphorical) shoes of the participant. Empathic
listening involves engaging fully with the unfolding story being recounted, but does not
involve shared experience or greater knowledge (Bondi, 2014a; see also Gair, 2012; Watson,
2009; Dreher, 2009; O’Donnell et al., 2009). Sometimes listening to feelings seemed to
involve more than us and our participants, but others – parents, uncles, grandparents and
children. Writing about transference (and countertransference) Bondi (2005) wrote that ‘we
carry the affective impress of our earliest patterns of relating into all of our
subsequent relationships’ (2005, 440). We sometimes felt and listened to the presence of
these relationships in what was said and not said in our discussion groups, in the ways in
which we experienced individuals and groups that we did not fully understand and are
difficult to articulate. Relationships with significant others hovered on the edges of
meetings, taking shape around a plate of homemade biscuits brought to a meeting or the
image of an uncle's naked, muscly torso shown around. These relationships were sometimes
far from straight forward, occasionally painful to listen to and difficult to follow.
Mother-child relationships contributed to, we think, (our experiences of) the conversation
with Omar, introduced at the start of the paper. Omar was 18, born in Afghanistan, moving
to Milton Keynes in 2009. Also involved in the conversation was Salima, who was 24, born
in Somalia, moving to Kenya and then Milton Keynes in 2006. Talk flowed; Omar was
confident and jaunty, Salima poised and friendly. How they talked sat uncomfortably with
our experiences of what they actually said. Omar remembered a loving mother who taught him
at home, but his mother slid away from view when he talked about his life in Milton
Keynes. When Salima talked about her mother, it turned out she was talking about her step
mother, her own mother had ‘left’ when she was three, ‘during the wars’. Omar focused on
the transience of his life, travelling with his father, his impressive body building
uncle, living in foster care when he moved to Milton Keynes, leaving that care and living
in temporary accommodation, a room in a house with strangers. His talk was cheerful, fast,
buoyant, fuelled by working out at the gym, working hard at College, working in a shop, a
girlfriend he enjoyed spending time with, coping despite everything. He came across as
self-reliant, hopeful and upbeat, although this is difficult to convey when confronted
with the words (Back, 2012, 2007): ‘Because the thing is, like, when I was living with my
family I wasn't – I wasn't there with my family, to be honest. I was like all the time
travelling around, with my dad. And being brought up like that. And then, I mean, at the
moment for me – ‘cause everybody's different. Everybody has different life situations. For
me, it doesn't change anything. I'm just the only person I was. And I mean, I'm getting
better but not worse. I mean, the life is being with my family. Sometimes I just remember
I have a mum – I had a mum, yeah, and just don't go into it. I mean, I missed it but not
much. Probably sometimes when I'm alone or when I see an old lady, oh yeah, I have a mum.
It reminds me of, like yeah, somebody that. But I don't remember anybody. Or I don't miss
anybody. Because I mean, you miss people when you're free, you don't have a job, you're
bored and suddenly like everything comes up and you're thinking of things. I have a very
tight timetable, I get up at six o'clock in the morning (….) Go to – go to the college,
come back from college, go to work, finish work. Go to straight away to the gym, do
exercise, come back home, study, cook, eat, clean and sleep 12 or 1am in the morning,
five, seven hours sleep. And that's what I do. I'm forever busy, like I don't really
remember anybody or talk to anybody. If somebody wants to call me, call me and if I want
to talk to them I will like try and speak with them. If they don't…’ (Omar) To some extent
listening involves participants allowing researchers to listen and at the time it felt
like Omar opened and closed down multiple channels of listening making our understanding
messy, stilted and broken. At times he felt playful. He was hard to follow, opening up and
then withdrawing, whilst talking all the while. He introduced us to the image of his uncle
on his phone, and then placed this to one side, on the table. The screen went black, but
the uncle somehow remained. The glossy, upbeat talk of survival and success reiterating
pervasive neo-liberal talk in Britain was painful to listen to when juxtaposed with ‘I
have a Mum’, ‘I had a Mum’, ‘don't go into it’, ‘I don't miss anybody’, ‘you miss people
when you're free’. What we experienced was caught up in Omar's incomplete stories, growing
up quickly, maturity, coping, girlfriend, work and college alongside transience,
loneliness, isolation, separation and missing his mother, amongst others. We were
listening to fragments and a ‘jumble of emotion’ that defied conventional genres of
narrative (Pratt, 2010). Perhaps our experiences were also caught up in what we brought to
our listening, such as, for example, Katy's relationship with her son and her recently
born daughter and an imagining in around what their loss might involve (Aitken, 2001). She
found herself not only empathising with Omar and Salima, but with their mothers too. Katy
was miserable after the meeting, packing up and going home. We have focused on this moment
in our research to show that listening is an intersubjective experience, involving us, our
participants and our relationships with others who shape our experience of research which
can sit differently to participant expressions of emotion. Listening involves recognising
the creative, fractured, intersubjective process of listening that underpins understanding
that is ‘imperfect’ and ‘faltering’. As Bondi (2014a,b) wrote: ‘(E)mpathy does not
generate direct or perfect apprehension of the subjective experience of another. Rather it
requires effort and is always imperfect and faltering. However much of the experience of
the other is accurately recognised, empathy also entails acknowledging that the effort to
understand can only ever yield an imperfect grasp of what the other feels’ (Bondi, 2014a,
50).

<hs>  The time involved in listening…… (to) transcripts</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our final reflection is that listening takes time. Listening often continues long after
research has supposedly finished. Feelings and conversations stay with us, live with us
and we mull over research moments involving, for example, Omar and Salima (Bondi, 2014a;
Bennett, 2009). Although this might be stretching his take on ‘intimate distance’ which
unsettles the drive for intimacy and rapport, as Steve Pile (2010) wrote ‘to see the
emotional dynamics underlying any research situation, you'll need appropriate distance: a
(conditional) balance of intimacy and distance’. We have certainly found that we need time
(and space) that extends beyond end points of research contracts to allow our research to
sink in. Listening to (our experiences of) the transcripts also takes time. We are
surprised by how different the transcripts can feel compared to what we experienced at the
time. Some of this is not simply because of what they lack in terms of the buzz of the
context (Back, 2012, 2007) but what they add. Transcripts can be provocative. What
surprises us is how we are moved at different points and in unexpected parts of the
transcript. Rachel Thomson et al. (2012) wrote evocatively about letting the text speak,
listening after the event, allowing ourselves to be provoked by the text. When we return
to our transcripts what we hear is shaped by identity, subjectivity and where we are in
our lives. As Steve Pile (1991) wrote: ‘reflection is profoundly intersubjective,
operating not only within the relationship between the researcher and researched but also
within wider social and personal relationships’ (1991, 465). Listening over time involves
the accumulation of (partial) understandings as relationships develop, texts, diaries and
recordings materialise, as we provoke those texts and they us and we remember, reflect on
and relive encounters. Provocative transcripts and field notes stem not only from us
listening to them, but them listening to us too. Explaining acousmatic texts, Jacques
Daignault (2005) wrote: ‘The text, if we need to remind ourselves, is not the printed
thing that the author publishes but each of the readings of the printed page and even the
sum of all these readings which always contain a part added by the reader.’ (Daignault,
2005, 6). (Acousmatic) texts are the sum of our readings, dynamic and thought provoking,
open to unexpected thoughts that mediate our reading of them, created through our reading,
listening to what we bring to them. Although the printed words in our transcripts do not
change, just the paper yellows, we bring to them developing, maturing selves and new
experiences which the transcripts absorb as they listen to us whilst we read them. They
absorb our individual reading and response to them and what we read is shaped by how other
members of the team have read them. Finally, although research projects and contracts have
end points, some of the relationships we develop with participants and groups do not. Our
field notes are read through the lens of on-going connections with people and places. One
of us, for example, became a Friend of Knighton Park and involved in its activities,
another joined a writing group long(er) term, writing the following in her field notes
during the research: ‘Larry said he'd really like for me to continue attending, as it was
nice to have me in the group, but I should consider this before bringing in an object (for
a community project) [….] I openly admitted to him that this was a funny position to be in
– you get attached […] and it's not easy or even appropriate to divide your engagement as
a researcher from your engagement as a person’ (28/5/13 Writing Group, Hackney). ‘After we
went around reading out our pieces, during which there was a lot of laughter and banter,
the woman from the museum came by with a camera to take photos of us with our objects. I
ended up bringing something in after all – a book of poetry entitled 'hackney, my hackney'
from 2004 which includes one of my poems. I found it and it felt like it fit so perfectly
into the whole thing that I had to bring it along, although I know perhaps committing to
attending the group long-term is foolish’. (30/5/13 Writing Group, Hackney) Sometimes
listening can be complicated over time by our developing relationship with groups and
places that extend well beyond the end dates of projects. Although projects end, listening
never quite does.

<h>CONCLUDING THOUGHTS</h>
-------------------

In this paper we have attempted to reflect on our listening in a way that we hope
researchers and students find useful, drawing in particular upon three elements of
listening that have especially resonated with us: listening whilst doing, the feelings
that mediate it and the time involved in listening. In trying to listen better we did not
invent new methods or prioritise one method over another, but we did draw upon the writing
and ideas of others on embodied listening, empathy and acousmatic texts to plan and
reflect on our listening. In this concluding section we finish with thoughts on the
process of listening and the kind of insights that our listening might provide. Our first
strand of concluding thoughts broadly concerns the process of listening that shaped our
participant observation, interviews and repeat, in-depth discussion groups. Our
participant observation involved sliding into the worlds of others and taking part in
their activities. Sometimes these activities involved little in the way of chat or
conversation and so listening involved attending to much more than this. Our field notes
and reflections in this paper reveal a pattern and process to our listening. We often drew
upon the mechanics of an activity in which we were involved to initially anchor us in the
field, detailing what we were doing, where, with whom and how this made us feel. We used
our eyes, ears, feelings, beating hearts - and more besides – to gauge moods and
atmospheres as we grappled with often unfamiliar sites and settings and people who we did
not know that well. We described people, encounters, interactions and contexts and
explored how we experienced these. Our methods involved channelling our listening through
ourselves, feeling our way into situations and conversation, working with our feelings,
imagining in, empathizing whilst mindful of differences around ethnicity, age, gender and
class (Bondi, 2003). Sometimes we shared our feelings with our participants, emoting, for
example, whilst running or in a less direct way – ‘Are you alright (Ayo)?’ Objects
mattered even more than we expected, supporting our listening as we gripped our pens
whilst jotting notes during group discussions or filled water bottles in six form
canteens. Objects contributed texture to our listening but were sparky in their own right
too, hot-wiring social relations and interactions as, for example, a crisp packet was
thrown around prompting movement, laughter and unsettling groups of students and the
disciplined space of a six form canteen. As individual members of a research team, we do
listen differently and perhaps, as Forsey (2010) suggests, some of us are more aural
whilst others are more visual in our listening, but this is too much of a simplification.
Our listening was also shaped by our individual life experiences, our relationships and
where we were in our lives, but also by more immediate experiences, such as our journey to
the fieldwork site. Our listening involved our feelings as we tried to make sense of what
we were experiencing, what was being communicated in the context, contours and
conversation in which we were immersed. The process of listening involves time that
stretches well beyond the end dates of projects and research contracts. Our listening
matures and evolves alongside our feelings and experiences of fieldwork. Transcripts
listen to us and develop through our listening to them over the course of time and around
our memories of fieldwork and the unfolding of our lives. Listening to transcripts
involves attending to the understanding and experiences that other members of the research
team bring to them. Our second strand of concluding thoughts concern the insights that our
listening brought to our research (see also MacKian, 2009). Sometimes these insights are
more obvious, when, for example, we listen to feelings that are surprising because they do
not seem to correspond with how someone is speaking. Returning to Omar introduced at the
start of the paper, his buoyant, happy talk, sat differently to the content of what he
said which sat differently again to how one of us was feeling while he was talking. There
was more than one story being told and listening to feelings was a way into the complexity
of what was being communicated. Focus on feelings and a sensuous, embodied approach to
listening decenters talk, without undermining it, knitting it into a mix of atmosphere,
interaction, stuff, happenings, context, sensations – and more besides – requiring
attention. For us the point of this kind of listening was to engage with the complexity of
places, interactions and encounters that shape multiculture which research participants
might not (want to) put into words in interviews and group discussions. Our listening
might also bring insights about which we are less aware, but emerge in how we evoke people
and places (see, for example, Rogaly and Qureshi, 2013). The kind of listening discussed
in this paper encompassing doing, feelings and time creates insights that get under the
skin of researchers shaping a less conscious, embodied, evolving knowing.


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<ART>Listening while reading promotes word learning from stories
===========================================================

Authors: Alessandra Valentini, Jessie Ricketts, Rachel E. Pye, Carmel Houston-Price
DOI: 10.1016/j.jecp.2017.09.022
Year: 2018  |  Pages: 10-31
ASJC codes: 3204, 3205
Keywords: Listening to stories, Orthography, Phonology, Reading, Reading while listening, Vocabulary acquisition

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Reading and listening to stories fosters vocabulary development. Studies of single word learning suggest that new words are more likely to be learned when both their oral and written forms are provided, compared with when only one form is given. This study explored children's learning of phonological, orthographic, and semantic information about words encountered in a story context. A total of 71 children (8- and 9-year-olds) were exposed to a story containing novel words in one of three conditions: (a) listening, (b) reading, or (c) simultaneous listening and reading (“combined” condition). Half of the novel words were presented with a definition, and half were presented without a definition. Both phonological and orthographic learning were assessed through recognition tasks. Semantic learning was measured using three tasks assessing recognition of each word's category, subcategory, and definition. Phonological learning was observed in all conditions, showing that phonological recoding supported the acquisition of phonological forms when children were not exposed to phonology (the reading condition). In contrast, children showed orthographic learning of the novel words only when they were exposed to orthographic forms, indicating that exposure to phonological forms alone did not prompt the establishment of orthographic representations. Semantic learning was greater in the combined condition than in the listening and reading conditions. The presence of the definition was associated with better performance on the semantic subcategory and definition posttests but not on the phonological, orthographic, or category posttests. Findings are discussed in relation to the lexical quality hypothesis and the availability of attentional resources.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Vocabulary development starts during infancy and is a lifelong endeavor; children and
adults acquire new words, and specify existing lexical representations, throughout the
lifespan (Nagy, Anderson, & Herman, 1987). The majority of words are not acquired through
direct instruction but rather incidentally from conversations, television, and texts
(Akhtar, 2004; Elley, 1989; Henderson, Devine, Weighall, & Gaskell, 2015; Houston-Price,
Howe, & Lintern, 2014). The current study explored how children learn new words when they
are exposed to them incidentally in stories. To our knowledge, this is the first
investigation of whether children show greater word learning from listening to, reading,
or both listening to and reading stories. Many studies have shown that exposure to stories
fosters vocabulary development in children (Henderson et al., 2015; Nagy et al., 1987;
Ricketts, Bishop, Pimperton, & Nation, 2011; Wilkinson & Houston-Price, 2013; Williams &
Horst, 2014). Suggate, Lenhard, Neudecker, and Schneider (2013) compared the word learning
shown in three story presentation conditions: independent reading, listening to an adult
reading the story, and listening to an adult telling the story in his own words. In the
listening conditions children (8- to 10-year-olds) were exposed to the spoken forms
(phonology) and meanings (semantics) of new words but not their written forms
(orthography), whereas in the reading condition they encountered the words’ written forms
(orthography) and meanings. The children who listened to the stories were more likely to
demonstrate knowledge of the new words’ meanings than the children who read the stories,
suggesting that oral presentation is more beneficial for vocabulary learning in school-
aged children than written presentation. In contrast to this result, studies of adults
learning English as a second language tend to show that participants acquire new words
more easily if presented with material in written form rather than oral form (Brown,
Waring, & Donkaewbua, 2008; Sydorenko, 2010). Similarly, studies exploring memory for word
lists or verse show better performance for written material than for oral material in both
adults and children (Hartman, 1961; Menne & Menne, 1972). Because the primary medium for
vocabulary acquisition is oral language, it makes sense that oral presentation may be the
preferred and easiest method for acquiring vocabulary early on, but as reading ability
improves, children become better at learning from written texts. There is reason to
suppose that both listening to and reading a story at the same time will be maximally
beneficial for word learning. Studies using e-book presentations show that presentation in
both modalities is more beneficial for vocabulary acquisition than simply listening to the
book read by an adult (Shamir, Korat, & Fellah, 2012). Other work has also found that
access to orthographic forms promotes oral vocabulary learning, an effect referred to as
“orthographic facilitation” (e.g., Hu, 2008; Ricketts, Bishop, & Nation, 2009; Ricketts,
Dockrell, Patel, Charman, & Lindsay, 2015; Rosenthal & Ehri, 2008). In these studies,
children were taught phonological forms and semantics either with or without orthography;
greater learning of phonology, semantics, and orthography was seen for items where
orthography was provided. To date, studies investigating orthographic facilitation all
have employed a direct instruction approach to teaching new words. Whether these findings
generalize to an incidental learning context, where children’s attention is not explicitly
drawn to the new words, needs to be explored. Further evidence that simultaneously
listening to and reading stories leads to better learning than a single modality of
presentation comes from a study by Rosenthal and Ehri (2011). In that study, children read
stories that contained novel words silently, pronouncing half of the new words aloud when
they encountered them. Semantic and orthographic learning was greater for words that had
been pronounced, demonstrating “phonological facilitation.” Although in this study words
were embedded in passages, thereby simulating incidental learning from reading, attention
was drawn to the target words (through underlining), and only these words were pronounced
aloud. In the current study, to provide a more realistic learning context, new words were
not highlighted and presentation modality was manipulated for the story as a whole rather
than for individual words. To date, listening and reading conditions have not been
compared with a combined listening and reading condition in relation to school-aged
children’s learning of vocabulary in their first language. However, studies of adult
second-language learners typically find superior learning when material is presented in
written or dual modality format rather than in spoken format (Brown et al., 2008;
Sydorenko, 2010). For example, Brown et al. (2008) presented three stories in three
different modalities (listening, reading, and combined) to 35 Japanese adult students and
found greater semantic learning in the reading and combined conditions compared with the
listening condition. In line with these results, studies investigating the impact of
multimodal presentation on memory for lists of words or verse found superior performance
in the combined and reading conditions compared with the listening condition in children
aged 8 or 9 years and adults (Hartman, 1961; Menne & Menne, 1972). In summary, evidence of
orthographic and phonological facilitation for vocabulary acquisition has so far come from
studies that present words in isolation, rather than in context (Ricketts et al., 2009;
Rosenthal & Ehri, 2008), or from studies that confine the dual modality of presentation to
the words of interest, rather than to the narrative as a whole (Rosenthal & Ehri, 2011).
Evidence for the beneficial effect of dual presentation modality compared with single
modality presentation has also come from studies with adult second-language learners
(Brown et al., 2008). Therefore, questions remain about whether such facilitation effects
are seen when school-aged children are learning new words in their first language and when
the presentation modality is extended to the entire story in which words are embedded. Why
might there be an advantage for a combined presentation modality over a single
presentation modality? One possibility is that providing both oral and written forms frees
up attentional resources during encoding, meaning that resources can be allocated to story
comprehension and to the encoding of new word meanings. This idea is related to Ehri’s
(2014) views on how good decoders use their strong knowledge of the link between
orthography and phonology to generate phonology automatically while reading, leaving more
resources for text comprehension and the learning of words’ meanings. It also resonates
with cognitive load theory in multimedia learning (Mayer, Moreno, Boire, & Vagge, 1999),
which states that situations that reduce cognitive load are more conducive to learning.
According to cognitive load theory, presenting information in two modalities frees
resources by increasing working memory capacity. This process occurs online as new
information is encountered and while a representation is being created (Mousavi, Low, &
Sweller, 1995). On this view, then, presenting both phonological and orthographic forms
may free cognitive resources so that more attention can be paid to comprehension and to
encoding word meanings. Notably, this framework focuses on the conditions that facilitate
learning, suggesting that presenting information in a dual modality creates connections
between two representations. It does not, however, probe the nature of the representations
created (Mayer et al., 1999). An alternative framework for interpreting the benefits of
simultaneous bimodal presentation is provided by the lexical quality hypothesis (Perfetti
& Hart, 2002). This hypothesis posits that lexical representations that include both
phonological and orthographic information are of “higher quality” than representations
that contain only phonological or orthographic information. Although the lexical quality
hypothesis focuses on existing lexical representations rather than their acquisition, it
is consistent with the idea that a combined presentation will support the building of
better quality lexical representations that, therefore, can be more readily accessed when
they are encountered at a later stage. In addition to story presentation modality, the
content of the story and the kinds of information provided within the story are likely to
play a role in children’s learning of new words. While reading, children use contextual
cues to infer semantic information about new words even when these cues convey minimal
information (Nagy et al., 1987). Whereas general context supports learning of the broad
category of a new word, more constraining contexts enhance learning of a word’s specific
features (Ricketts et al., 2011). In addition, when words are encountered aurally,
presenting a definition alongside the new word is beneficial for semantic learning
(Dickinson, 1984; Penno, Wilkinson, & Moore, 2002; Wilkinson & Houston-Price, 2013). There
are important differences in the information conveyed by contextual cues and definitions.
Contextual cues typically provide general information about a word’s meaning and are
spread through the text (Nagy, 1995). Definitions provide detailed semantic information
about the word and typically occur alongside its form. If definitions are considered a
highly constraining context, they should allow more specific information about a word to
be extracted than the more general categorical information revealed by less constrained
contexts (Ricketts et al., 2011). Although previous studies have shown that definitions
elicit greater semantic learning than general contextual support in both recognition tasks
(Wilkinson & Houston-Price, 2013) and production tasks (Justice, Meier, & Walpole, 2005),
previous research has not explored the nature of the semantic learning shown in such
conditions, a further aim of the current study.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

Children aged 8 or 9 years were exposed to a story containing eight new words. This age
range was chosen to ensure a range of reading abilities in a population of children used
to reading and understanding written texts. Children were divided into three groups, with
one group listening to the story (listening group), one group reading the story (reading
group), and one group reading and listening to the story simultaneously (combined group).
Half of the words were accompanied by a definition the first time they were presented, and
the other half of the words were not. The story was presented twice over 2 weeks to
promote learning via repetition and allow for sleep-related consolidation (e.g.,
Henderson, Weighall, & Gaskell, 2013) and to fit in with the school timetable. After the
second story presentation, children’s knowledge of phonological forms, orthographic forms,
and meanings was assessed in a series of posttests. In phonological and orthographic
posttests, children were required to recognize correct spoken or written forms from two
alternatives. In three semantic posttests, children were asked to identify the words’
categories, subcategories, and definitions. By using these tasks, we were able to capture
acquisition of different aspects of semantic information about the given words. From a
practical perspective, this investigation serves to establish how best to promote
vocabulary acquisition in school-aged children and whether children with different ability
levels are facilitated by different presentation modalities. From a theoretical
perspective, the results assess the hypothesis that different presentation modalities
facilitate the acquisition of words of higher or lower lexical quality. The framework
provided by the lexical quality hypothesis (Perfetti & Hart, 2002) has previously been
applied to evidence that better readers create higher quality representations of new words
(Perfetti, 2007), but it has not been used to make clear predictions about the conditions
under which words are optimally encoded or retained. This study explored whether word
representations created through different presentation modalities vary in their lexical
quality. The study addressed several hypotheses regarding orthographic, phonological, and
semantic learning. In relation to dual versus single modality presentations, it was
hypothesized that the combined condition would elicit superior orthographic, phonological
and semantic learning (Ricketts et al., 2009; Rosenthal & Ehri, 2008; Rosenthal & Ehri,
2011) compared with the other two conditions. Regarding semantic learning, given the
conflicting evidence, clear predictions could not be made as to whether the listening
group would outperform the reading group in learning words’ meanings, as suggested by the
first language literature (Suggate et al., 2013), or whether the reading group would show
an advantage, as suggested by the second language and memory literatures (Brown et al.,
2008; Menne & Menne, 1972). In line with previous research on word learning from stories,
it was expected that definitions would promote semantic learning (Penno et al., 2002;
Wilkinson & Houston-Price, 2013), particularly in tasks assessing learning of specific
features of the words’ meanings. Individual differences might also constrain children’s
learning of new words from spoken and written story exposure. Therefore, measures of
children’s abilities were collected. Based on previous research, it was expected that
reading accuracy would predict learning of orthographic forms in the reading condition
(Ricketts et al., 2011) and that vocabulary knowledge, reading accuracy, and reading
comprehension would predict semantic learning in the reading condition (Cain, Oakhill, &
Lemmon, 2004; Ricketts et al., 2011), whereas oral vocabulary ability should predict
semantic learning in the listening condition (Lin, 2014; Penno et al., 2002; Senechal,
Thomas, & Monker, 1995). Given that previous studies have not investigated monolingual
children’s word learning when children are simultaneously reading and listening, it was
unclear which abilities might influence learning in the combined condition. We anticipated
that because children could rely on both oral and written modalities, oral vocabulary,
reading accuracy, and reading comprehension all would influence performance in the
combined condition.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 71 children aged 8 or 9 years participated in the study (Mage = 9.03 years, SD
= 0.31; 28 boys). Participants were recruited from four primary schools in England.
Ethical approval was obtained from the first author’s institution, and informed parental
consent was received for all participants. All children had normal or corrected-to-normal
vision, and teachers confirmed an absence of learning or neurological disabilities. All
children were monolingual native English speakers.

        <hss>Background measures</hss>

        Children completed background measures in one session prior to the word learning
        task. All were standardized assessments and were administered according to test
        manual instructions. Nonverbal abilities were measured using the Raven’s Coloured
        Progressive Matrices (CPM; Rust, 2008), a pattern completion task in which
        participants solve visual diagrammatic puzzles using analogies or inferences
        (split-half reliability reported in the test manual = .97). Oral language
        abilities were assessed using the British Picture Vocabulary Scale–Third Edition
        (BPVS; Dunn, Dunn, & National Foundation for Educational Research, 2009), a
        receptive vocabulary measure in which children need to choose the correct picture
        for a given word among four alternatives, and the Understanding of Spoken
        Paragraphs (USP) subtest of the Clinical Evaluation of Language
        Fundamentals–Fourth Edition (CELF-4; Semel, Wiig, & Secord, 2006), a test in which
        children listen to several short passages and answer questions about them. This
        test assesses both oral language comprehension and sustained oral attention
        (test–retest reliability reported in the test manual = .80). Nonword reading was
        assessed using the Phonemic Decoding Efficiency subtest of the Test of Word and
        Reading Efficiency (TOWRE; Torgesen, Wagner, & Rashotte, 1999), in which children
        read as many nonwords as they can in 45 s (test–retest reliability reported in the
        test manual = .90), and word reading was assessed using the Single Word Reading
        Test (SWRT 6–16; Foster, 2007), which is an untimed word reading task with words
        in sets of increasing difficulty. The York Assessment of Reading for Comprehension
        (YARC; Snowling et al., 2009) was used to assess text reading accuracy and reading
        comprehension. In this task, children read two passages aloud and reading errors
        are noted. Following reading, they answer comprehension questions indexing
        knowledge of literal content and inferential processes (parallel form reliability
        reported in the test manual for reading accuracy: all rs > .70; Cronbach’s alpha
        for reading comprehension scores from two passages: all αs > .70).

            <hss>Design</hss>

            Story presentation modality was manipulated between participants such that
            children were assigned to either the listening, reading, or combined condition
            in order to form three comparable groups matched on key background measures.
            The groups did not differ on gender, χ2(2) = 0.09, p = .957, reading, oral
            language, or nonverbal abilities (see Table 1). Details of the background
            measures used to match groups are included above. Children from each school
            were equally distributed across conditions. The presence of a definition was
            manipulated within participants, with all children encountering half of the
            words with a definition and half without a definition.

            Stimuli

            See Appendix A for stimuli.

                <hss>Words</hss>

                Target items were 8 low-frequency English concrete nouns (e.g., destrier,
                hauberk), each belonging to one of eight categories (e.g., animal,
                object). From an initial set of 36 words related to historical periods
                (Roman Empire, Norman Period, and British Empire in India), we selected 8
                words from the Norman Period and embedded these target items into a
                meaningful narrative. In addition, 8 control words were selected from
                other historical periods and were included in the pretest and all
                posttests to control for prior knowledge (see below for details of these
                tasks). The pretest confirmed that knowledge of target and control words
                was negligible (see below). Given that control words were not presented in
                the story, it was expected that any difference in performance between
                target and control words could be ascribed to story presentation. Target
                and control lists were composed of words of the same category, matched for
                length and frequency using the SUBTLEX–UK database (Van Heuven, Mandera,
                Keuleers, & Brysbaert, 2014) (Mann–Whitney tests, all ps > .200). Target
                and control words were also matched on pilot data collected for a previous
                study showing the proportion of adults who spelled and pronounced each
                word correctly and the proportion of children who correctly categorized
                each word at its first encounter (Mann–Whitney tests, all ps > .200).

                <hss>Definitions</hss>

                The definition for each target and control word comprised information
                about the word’s subcategory and a further phrase to specify it. For
                example, for destrier, the definition “a horse used for fighting”
                comprises both the subcategory information “a horse” and the specific
                characteristic “used for fighting.” Words were divided into two lists of
                four items (Word Lists A and B) for counterbalancing purposes. The words
                in the two lists were paired for length, frequency (Van Heuven et al.,
                2014), the aforementioned results from pilot studies, the length of the
                definition, and the distance between the first and second mentions of the
                word in the story. Mann–Whitney tests revealed no difference between the
                words in the two lists on these measures (all ps > .200).

                <hss>Stories</hss>

                A story set during the Norman Period was written for this study to include
                all target words. Each target word was repeated three times in the story.
                Contextual references to the meaning of each word were included to ensure
                that the children could learn the meaning of the words from context alone.
                Two different versions of the story were created so that the definitions
                of either Word List A or Word List B were included as part of the text
                following the first mention of the word. The two versions were matched for
                length (1346 and 1347 words, respectively), Flesh Reading Ease (84.3% and
                84.5%, respectively) and Flesh–Kinkaid grade level (5.2). Pilot data
                ensured that the stories were written at an appropriate level for children
                in this age range. Recordings of a female native English speaker reading
                the stories were created, and booklets of seven pages that contained only
                the text of the stories, written in Calibri 14-point font, were prepared.
                Pilot studies established how long, on average, children took to read the
                stories independently (M = 548 s, SD = 172); the recordings of the adult
                storyteller were controlled to match this (M = 507 s, SD = 2).

<hs>  Procedure</hs>
  ~~~~~~~~~

Fig. 1 summarizes the study procedure. Assessments were completed in a quiet room within
schools. Prior to the word learning task, children completed the word knowledge pretest
and were administered the background measures. The word learning task was completed in two
sessions lasting between 30 min and 1 h. In the first session, children were exposed to
the story for the first time and completed a story comprehension task. In the second
session, they were exposed to the story a second time and completed the same story
comprehension task as well as the phonological, orthographic, and semantic posttests. The
first and second sessions were completed 1 week apart. The story comprehension task and
all posttests were delivered through a laptop computer using E-Prime software (Schneider,
Eschman, & Zuccolotto, 2002). The phonological and orthographic posttests were completed
first, in counterbalanced order, followed by the semantic posttests. Given that the
semantic posttests involved presenting the novel words in spoken and written forms, these
were completed last to avoid any contamination from these to the phonological and
orthographic tasks. We did not expect that there would be cross-contamination between
orthographic and phonological posttests and the semantic posttest because the former
provided no semantic information. The semantic posttests were multiple-choice format and
presented in a fixed order, with the category recognition task first, followed by the
subcategory recognition task and finally the definition recognition task. This order
minimized any impact of previous semantic tasks on later semantic tasks. For each
posttest, on-screen instructions followed by four practice trials ensured that children
understood the demands of the task. Target and control words were presented with item
order randomized, and accuracy was recorded for each trial.

        <hss>Word knowledge pretest</hss>

        Children were asked to define the target and control words. Here, 3 participants
        showed preexisting knowledge of one target word (2 children knew pottage and 1
        child knew motte); the remaining 68 children had no knowledge of any target words.
        In addition, 3 children showed preexisting knowledge of one control word (2
        children knew catacomb and 1 child knew verandah); again, 68 children had no
        knowledge of any control words. Thus, preexisting knowledge of control and target
        words was similarly scarce. Analyses that excluded these participants yielded the
        same pattern of results as those reported. Thus, all participants were retained in
        the analysis.

        <hss>Story exposure</hss>

        Participants were asked to listen to (listening group), read silently at their own
        pace (reading group), or listen to and read (combined group) the story, after
        which they were told they would be assessed on their comprehension of the story.
        No mention was made of the presence of the target words. Children were presented
        with a version of the story that contained definitions for either Word List A or
        Word List B. The oral presentation of the story was delivered through headphones
        connected to a laptop with a blank screen. For the written presentation, children
        read the story from a booklet. In the combined condition, children received both
        presentations simultaneously.

        <hss>Story comprehension task</hss>

        After each story exposure, children were asked four multiple-choice questions to
        ensure that they had paid attention to the story (e.g., “Fred wanted to reach the
        king’s castle. How long did he think the journey would last?” ; correct response:
        A month; foils: A day/A week/One hour). Each question, along with an array of four
        potential answers, was presented both orally and visually via a laptop. Pilot data
        provided by 12 children of the same age as participants confirmed that, without
        exposure to the story, children were unlikely to guess the answers to questions at
        above chance levels.

        <hss>Phonological posttest</hss>

        In this task, two dinosaurs were presented sequentially on a computer screen: one
        providing the correct spoken form of a word and the other providing an incorrect
        word form (distractor). Pilot data collected for an earlier study were used to
        generate distractors for this task. Adults were asked to pronounce each written
        target and control word, and the most frequent mispronunciations were used as
        distractors for most words. If no mispronunciations were produced (for 4 words),
        alternative pronunciations were created. For example, the distractor for “hauberk”
        (hɔːbək, first vowel as in horn) was “hɑ:bək” (first vowel as in heart). Children
        were instructed to choose the dinosaur that “said the word best” by pressing the
        corresponding button on the keyboard. The dinosaurs appeared in turn for 2 s in an
        alternating loop until an answer was provided. The association between the two
        dinosaurs and the correct answer was randomized. Both target and control words
        were presented in this task (16 items). Test–retest reliability for these items
        was obtained from pilot data collected from a separate group of 57 children of the
        same age (8–9 years) who completed the tasks twice, with a 1-week interval between
        test sessions. Pilot data were available for 13 items used in the current study
        (all 8 target words and 5 control words). Test–retest reliability for these items
        was r(57) = .71. See Appendix B for stimuli.

        <hss>Orthographic posttest</hss>

        As in the phonological task, children saw two dinosaurs sequentially, this time
        accompanied by a letter string, and were asked to choose the correct spelling of
        the given target or control word (by choosing the dinosaur who spelled the word
        best). The dinosaurs, alongside their spelling option, appeared in turn for 3.5 s
        in an alternating loop until an answer was provided. Pilot data provided by adults
        in an earlier study were used to generate distractor spellings. The most common
        misspellings of orally presented words were used; when no misspelling was produced
        (for 2 words), alternative spellings were created. For example, the distractor for
        “hauberk” was “horberk.” The association between the two dinosaurs and the correct
        answer was randomized. Both target and control words were presented in this task
        (16 items). As for the phonological task, test–retest reliability was computed
        from pilot data available for 13 of the items: r(57) = .57. Although this value
        highlights a less than excellent relationship, we deemed the measure to be
        sufficiently reliable because an amount of variability is to be expected in
        representations of newly learned words over time. See Appendix B for stimuli.

        <hss>Semantic posttests</hss>

        The three semantic subtests followed the same format. In each task, the children
        were asked to choose the correct alternative from an array of four choices
        pressing the corresponding button on the keyboard. First, a category recognition
        task assessed recognition of the category of the new word (e.g., clothing) among
        three of the categories of other target words (e.g., part of a house, job,
        animal). At the beginning of each trial, a target or control word was presented in
        spoken and written forms; the written form appeared at the top of the screen. The
        alternative category labels appeared one at a time both orally and in written form
        in randomized positions on the screen (see Fig. 2). The second and third tasks
        followed the same procedure. The second task assessed recognition of the
        subcategory of the word (e.g., for an item of clothing, the four alternatives were
        different kinds of clothing), and the third task assessed recognition of the
        word’s definition when presented with three distracter definitions (each differing
        from the correct choice by one feature). The definitions were not identical to
        those presented in the stories but were rephrased. Both target and control words
        were presented in all three semantic posttests (16 items). As for the other
        posttests, test–retest reliability for category recognition was computed from
        pilot data available for 13 of the items: r(57) = .76. Table 8 lists the correct
        responses for each semantic task.

<hs>  Story comprehension</hs>
  ~~~~~~~~~~~~~~~~~~~

A story comprehension task was used to confirm that children paid attention to the story.
Participants completed it twice, once after each story exposure, giving a maximum score of
8 and chance-level performance of 2. One-sample Wilcoxon signed-rank tests indicated that
all groups performed better than chance on this task (see Table 2). A Mann–Whitney test
showed that children in the combined group outperformed children in the reading group (U =
140.50, p = .003) but not children in the listening group (U = 253.50, p = .461), whereas
there was a nonsignificant trend for the listening group to outperform the reading group
(U = 192.00, p = .069). This suggests that hearing the story promoted comprehension.

<hs>  Approach to data analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

For each posttest, two sets of analyses were carried out. The first set (see Table 3; see
also Table 6 below) compared the recognition of target and control words and compared each
of these with chance (50% for phonological and orthographic tasks and 25% for semantic
tasks). The second set of analyses used a mixed-effects modeling approach to explore our
hypotheses relating to (a) presentation modality (listening, reading, or combined group),
(b) definitions, and (c) individual differences within each of the three experimental
tasks in turn. Because the groups were matched on age and all background measures, we
included in the analyses only measures for which specific hypotheses were considered:
vocabulary knowledge (BPVS raw score) and a composite reading accuracy score in all
analyses, and reading comprehension (YARC reading comprehension ability score) in semantic
task analyses. The composite reading accuracy score was formed by merging TOWRE, SWRT, and
YARC text reading accuracy scores into a factor using the regression method (M = 0.00, SD
= 1.00, range = −2.89 to 2.24). The three groups did not differ significantly on this
measure, H(2) = 0.02, p = .992, and the creation of this factor was supported by high
correlations between its constituent measures (all rs > .80, all ps < .001). See Appendix
C for correlations between background measures. Because the data collected on each trial
were binomial (a child could choose either the correct or incorrect alternative, obtaining
a score of 1 or 0), mixed-effects models were conducted using generalized linear mixed
models for binomial data (Jaeger, 2008), using the function “glmer” from the package lme4
(Bates, Maechler M., & Walker S., 2014), the function “mixed” from the package afex
(Singmann, Bolker, Westfall, & Aust, 2016), and the function “lsmeans” from the package
lsmeans (Lenth, 2016), computed with the software R (R Core Team., 2014). Each of the 71
children provided eight responses to target words on each task; this score was the
dependent variable in each analysis. For each dependent variable, an initial model
included a maximal random effects structure that captured our experimental design (Barr,
Levy, Scheepers, & Tily, 2013). This entailed the random intercept terms for both
participants and items and the random slopes terms for participants and items that relate
to our repeated-measures manipulation: presence of a definition. However, models including
random slopes were prone to nonconvergence; therefore, the simpler and convergent models
are reported (Bates, Kliegl, Vasishth, & Baayen, 2015). We then compared these “empty”
models (using pairwise likelihood ratio test comparisons; Barr et al., 2013) with models
that also included performance on control words as a control variable and the hypothesized
fixed effects: group (combined, listening, or reading), presence of definition (definition
present or definition absent), and specific background measures. Scores on control word
trials were included in models to control for general task effects, such as the ability to
recognize word-like phonological forms, irrespective of any in-task learning. Further
analyses were performed to explore whether results differed for the two sets of target
words by entering word set as a further fixed factor. The pattern of results was
identical, and set was not a significant predictor within the models; thus, these models
have not been reported. All continuous factors were centered around the mean for analysis.
Hypothesized interactions were included one at a time in the model with all fixed effects
and were retained only if significant. The interactions between group and the background
measures were separately introduced to test whether any background measure had a
differential effect on performance in each task, depending on presentation modality.
Estimates of fixed effects and interactions for the final models are reported in Tables 4,
5, and 7 below.

<hs>  Phonological task</hs>
  ~~~~~~~~~~~~~~~~~

The mean number of phonological forms correctly recognized by the children in each group
is presented in Table 3 along with analyses comparing target and control word performance
with each other and with chance. Target word performance was greater than control word
performance and was above chance for all groups. Control word performance was also greater
than chance for the combined group, but this was not the case for the listening and
reading groups. The fixed-factor model for the phonological task significantly improved
fit compared with the empty model, χ2(6) = 48.53, p < .001. Interaction terms did not
significantly improve model fit. The final model (Table 4) indicates reading accuracy and
control word scores as significant predictors of performance on the phonological task;
phonological learning was greater for better readers and those better able to identify the
phonological forms of control words. Most important, phonological learning did not differ
across groups.

<hs>  Orthographic task</hs>
  ~~~~~~~~~~~~~~~~~

The mean number of orthographic forms correctly recognized by the children in each group
is presented in along with analyses comparing target and control word performance with
each other and with chance. In the Table 3orthographic task, target word performance was
significantly greater than control word performance and was above chance for the reading
and combined groups. For the listening group, target word performance was not
significantly greater than control word performance or above chance. Control word
performance was not above chance for any group. The fixed-factor model for the
orthographic task significantly improved fit compared with the empty model, χ2(6) = 31.53,
p < .001. Interaction terms did not significantly improve model fit. The final model
(Table 5) indicates group and reading accuracy as significant predictors of orthographic
performance, with children in the combined and reading groups showing better performance
than children in the listening group (who did not show significant orthographic learning)
and greater orthographic learning associated with greater reading accuracy.

<hs>  Semantic tasks</hs>
  ~~~~~~~~~~~~~~

The mean number of words correctly recognized by each group in each semantic task is
presented in Table 6 along with analyses comparing target and control word performance
with each other and with chance. In all three semantic tasks, all groups performed
significantly above chance on target words and significantly better on target word trials
than on control word trials. Control word performance was not significantly above chance
in any task for group. The final model for each semantic task is presented in Table 7.

        <hss>Category recognition</hss>

        The fixed-factor model significantly improved fit compared with the empty model,
        χ2(7) = 55.34, p < .001. Interaction terms did not significantly improve model
        fit. Group, presence of definition, reading accuracy, vocabulary, and control word
        scores were significant predictors in the final model. The combined group
        performed better than the other two groups, and greater reading accuracy, oral
        vocabulary knowledge, and performance on control words was associated with better
        performance. Category recognition was surprisingly better for words presented
        without definitions than for those presented with definitions.

        <hss>Subcategory recognition</hss>

        The fixed-factor model significantly improved fit compared with the empty model,
        χ2(7) = 21.15, p < .001. Interaction terms did not significantly improve model
        fit. Presence of definition and vocabulary level significantly predicted
        performance, with the presence of a definition and greater existing oral
        vocabulary knowledge associated with better performance. No group effect was
        evident; the three groups performed similarly on this task.

        <hss>Definition recognition</hss>

        The fixed-factor model significantly improved fit compared with the empty model,
        χ2(7) = 42.61, p < .001. Addition of the group by reading comprehension
        interaction also improved model fit. As for subcategory recognition, the presence
        of a definition and oral vocabulary knowledge were significant predictors, but
        group was not a significant predictor. To further explore the group by reading
        comprehension interaction in the definition recognition task, a separate model was
        computed for each group. For the combined group, the presence of a definition
        predicted performance, β = .97, χ2(1) = 9.63, p = .002. The performance of the
        listening group was positively influenced by vocabulary, β = .42, χ2(1) = 4.61, p
        = .030, and reading comprehension, β = .47, χ2(1) = 5.32, p = .020, whereas the
        performance of the reading group was positively influenced by vocabulary, β = .42,
        χ2(1) = 4.39, p = .040, and control word scores, β = .79, χ2(1) = 10.60, p = .003.
        These supplementary analyses suggest that the group by reading comprehension
        interaction reflects a positive association between reading comprehension and
        performance for the listening group but not for the other two groups. In addition,
        the presence of definitions may have particularly supported later definition
        recognition by children in the combined group, whereas existing vocabulary
        knowledge particularly influenced performance in the listening and reading groups.
        However, because the group by definition and group by vocabulary interactions were
        not significant, no strong conclusions can be drawn in relation to these findings.

<h>DISCUSSION</h>
----------

This study investigated children’s incidental word learning from stories, comparing
listening, reading, and combined conditions for the first time. Children learned
information about the phonology, orthography, and semantics of new words, but the extent
and nature of their learning depended on the presentation modality. Learning was also
modulated by the presence of a definition and by children’s existing abilities. The
influence of presentation modality, presence of a definition, and individual differences
are discussed in turn. In relation to presentation modality, the orthographic facilitation
reported in previous studies (Rosenthal & Ehri, 2008) motivated our hypothesis that the
combined group would outperform the other two groups on the phonological task. However, in
our paradigm, where children learned new words incidentally rather than being taught them,
children learned the phonological forms of the new words with equal proficiency across
conditions. Thus, children who read the story appear to have formed a phonological
representation of the new words that not only was better than chance and better than for
control words but also was equivalent to the learning shown by children who had been
directly provided with the phonological form. This is in line with Share’s (1995) self-
teaching hypothesis, which states that phonological recoding occurs while reading.
Children were able to use their knowledge of the relationship between orthography and
phonology to learn the phonological form of words that they saw in written format only. To
be certain that children’s phonological representations were equivalent across the three
conditions, however, we must be confident that our phonological task provided a robust
measure of phonological learning. Three issues are worthy of mention in relation to this
point. First, performance on this task involved distinguishing between targets and
plausible foils, which were generated, where possible, from adult mispronunciations of the
written forms. Consequently, it is possible that the task probed abilities other than
children’s in-task learning such as their general sensitivity to an oral form’s word-
likeness. This idea is supported by the finding that control word scores significantly
predicted target word scores on this task. To account for such general effects, scores on
control word trials, therefore, were included in all analytical models, enabling us to
have confidence that our results reflect children’s phonological learning within the task.
A second consideration is whether the use of plausible foils made the task particularly
challenging for children in the reading group, who were not provided with a phonological
form and who, therefore, may have generated an alternative form while reading that was
aligned more closely with the foil than with the target. However, this does not seem to
have been the case; the reading group performed just as well as the other groups on the
phonological task. Finally, it is possible that the recognition task was insufficiently
sensitive to detect subtle differences in the quality of children’s phonological
representations across conditions due to either the nature of the task itself or the
number of items tested. Had we used a production task, for example (cf. Rosenthal & Ehri,
2008), group differences might have been detected. However, an identical recognition task
format with the same numbers of items elicited group differences on the orthographic task
in the current study (see below), and similar tasks and trial numbers have been found to
be sufficiently sensitive in previous studies (e.g., Ricketts et al., 2009; Ricketts et
al., 2011; Rosenthal & Ehri, 2008; Rosenthal & Ehri, 2011). Nevertheless, future studies
might seek to corroborate our conclusions using alternative measures of phonological
learning. In contrast to the findings relating to phonological learning, the three groups
did not show equivalent orthographic learning. Here, children in the combined and reading
groups outperformed those in the listening group, whose performance was at chance. This
indicates that a word’s orthographic form is not automatically extrapolated from its
phonology; rather, the presentation of written text prompts orthographic learning.
Contrary to previous findings (Rosenthal & Ehri, 2011), the additional presentation of the
oral form did not enhance orthographic learning relative to the presentation of the
written form alone. As for the phonological task, it is possible that a more sensitive
measure of orthographic knowledge might have revealed a difference in the orthographic
representation of the two reading groups. Nevertheless, there is no evidence in our study
for phonological facilitation of orthographic learning. Given the relatively low
reliability for the orthographic task, these findings warrant replication in future
studies. In summary, the results of the phonological and orthographic recognition tasks
suggest that listening to stories promotes learning of new phonological but not
orthographic forms. Reading, in contrast, appears to support the acquisition of both
phonological and orthographic information about new words, presumably creating higher
quality lexical representations (cf. Perfetti & Hart, 2002). The asymmetry in our results
resonates with observations that children tend to perform better in reading tasks that
require them to produce an oral form from a written one than in spelling tasks that
require the reverse (Cossu, Gugliotta, & Marshall, 1995). Turning to the semantic tasks,
we explored whether semantic learning would be greater in the reading group than in the
listening group (Brown et al., 2008) or vice versa (Suggate et al., 2013). Our results
indicated no support for the superiority of either oral or written presentation. It
appears that, at 8 or 9 years of age, children learn as much about the meanings of words
from reading as they do from listening to stories. It was also hypothesized that children
in the combined condition would acquire more semantic information about new words than
children in the listening and reading conditions (Ricketts et al., 2009; Rosenthal & Ehri,
2008; Rosenthal & Ehri, 2011). This prediction was upheld, but only for the category
recognition task, which required the abstraction of word knowledge to categorize the word
correctly. In this task, we observed both an orthographic facilitation effect (i.e.,
better performance in the combined group than in the listening group) and a phonological
facilitation effect (i.e., better performance in the combined group than in the reading
group). Before we consider why the benefit of the combined condition was found in only one
semantic task, we first reflect on the causes of children’s better performance in the
combined condition. The lexical quality hypothesis (cf. Perfetti & Hart, 2002) suggests
that words with higher quality representations are more easily retrieved from memory. This
theoretical perspective focuses on existing lexical representations rather than their
acquisition. Nonetheless, it is consistent with the proposal that the combined condition
promotes the building of better specified representations, facilitating access to stored
word knowledge at test. However, this framework would appear to predict consistent
differences in the quality of the phonological, orthographic, and semantic representations
formed in the combined and single modality presentations, as reported previously in
studies finding orthographic facilitation effects (Ricketts et al., 2009; Rosenthal &
Ehri, 2008) and phonological facilitation effects (Rosenthal & Ehri, 2011). Such
consistent effects across tasks were not found in the current study. As discussed above,
it is possible that the insensitivity of our phonological and orthographic measures masked
subtle differences between the groups. Although we find no evidence for this, it remains
possible that the phonological or orthographic forms acquired in the combined condition
were of a higher quality than those in the other two conditions. An alternative
possibility is that the combined condition reduced cognitive load during word learning,
freeing resources for comprehension and word meaning extraction (Mayer et al., 1999).
Compared with the combined group, the reading and listening groups were charged with
additional processing demands at the point of encountering the new words—the reading group
in the form of spontaneous phonological recoding (as evidenced by the children’s
performance on the phonological task) and the listening group due to the attentional
demands associated with continuously monitoring the oral story presentation (without any
“backup” support from the written text). Children in the combined group, therefore, may
have had more resources available to allocate to processing the contextual support
(including definitions) that immediately followed a new word, thereby encoding the word
meanings better. This perspective would predict word form representations to be of similar
quality across conditions but would predict representations of words’ meanings to be
better in the combined condition, the pattern found in the current study. Although both
approaches could, in theory, explain the greater semantic learning of the combined group,
it remains to be discussed why this effect was seen in only one of our semantic tasks, the
category recognition task. Two potential explanations occur to us. First, only the
category recognition task required children to abstract category-level knowledge about the
target words from the information provided in the story: the category label for each new
word was never directly provided in the narrative. In contrast, recognizing the correct
subcategory or definition in the other semantic tasks required participants to choose a
subcategory or definition that was very similar to those provided in the story. Second,
choosing the correct response on the subcategory and definition recognition subtests is
likely to have been easier than choosing the correct form in the category recognition
task. In the former tasks, only one of the four alternative response options had been
encountered in the story (e.g., among the four clothing options offered in the definition
task for the word hauberk, only a soldier’s shirt made of chain mail had been mentioned in
the story, making the other alternatives less likely regardless of any learning of the
label for this item). In contrast, all four of the alternatives in the category
recognition task correctly described one of the new words presented in the story (i.e., to
recognize hauberk as a piece of clothing in the category recognition task, children needed
to know that this new word did not identify a new animal, job, or part of a house, each of
which had been encountered in the story). These factors could have made the category
recognition task the most challenging measure, and therefore the most sensitive measure,
of children’s semantic learning. By freeing resources, the combined condition might have
especially facilitated this task due to the level of abstraction and/or precision of the
mapping required, a hypothesis that warrants further investigation. The study also
investigated the impact of definitions on word learning. It was hypothesized that the
presence of an accompanying definition alongside each new word would foster semantic
learning (Wilkinson & Houston-Price, 2013). Although definitions did not affect children’s
phonological or orthographic learning in this study, they facilitated the learning of
subcategories and definitions of the words but hindered category recognition. These
findings indicate that definitions help children to learn detailed information regarding
new words but do not help to extract more general categorical information. This finding is
perhaps not surprising considering that in the current study the definitions directly
provided most of the information needed in the definition recognition task along with the
subcategory (or a synonym of this) required in the subcategory recognition task. When
definitions were provided, the level of abstraction required by these two tasks,
therefore, was quite low. When definitions were not provided, children needed to extract
the details of the word’s semantics from the text, synthesizing various cues to construct
a coherent representation of its meaning, in order to succeed on these tasks. In contrast,
the abstraction required to identify words’ categories, necessary to succeed on the
category recognition task, would be similar whether or not a definition was provided
because this information was not supplied within definitions. When provided with a
definition, children appear to have learned the specific information in the definition at
the expense of abstracting a more general representation of the word’s meaning. We also
explored the effects of children’s reading and language abilities on their learning in
different presentation conditions. Reading accuracy predicted performance in the
phonological, orthographic, and category recognition tasks irrespective of presentation
modality. Children with better baseline knowledge of orthography–phonology mappings were
better able to learn new orthographic and phonological forms and extract semantic
information (Ricketts et al., 2011; Rosenthal & Ehri, 2008). By facilitating the learning
of new word forms, better decoding skills could potentially reduce the cognitive load in a
similar way to that discussed earlier in relation to the dual presentation modality,
enabling the learning of more complex semantic information (category learning). As
hypothesized, oral vocabulary level predicted performance in all three semantic tasks. It
is likely that children with smaller vocabularies face a more difficult task when reading
or listening to stories because their reduced familiarity with the vocabulary in the story
increases the size of the word learning challenge (Shefelbine, 1990). In addition,
children with larger vocabularies may employ better word learning strategies (Cain et al.,
2004); for example, they may be more proficient at linking new words with contextual
information (McKeown, 1985). Written text comprehension ability was also positively
related to definition recognition, but only in the listening group. This finding is
surprising, because children in the listening group were not required to comprehend
written text. It is possible that a third factor—an unmeasured one—is involved in both
reading comprehension and word learning while listening to stories, such as the ability to
build a representation of the incoming story or other discourse online without the need to
revisit the text (e.g., by rereading). Despite the broad variation in children’s
abilities, it is worth noting that background measures did not interact with the impact of
presentation modality on category recognition. It is particularly interesting that,
irrespective of reading ability, children’s category learning benefited from combined oral
and written presentation. Thus, even good readers can benefit from oral presentation while
reading, despite their ability to read efficiently by themselves. Similarly, poor readers
can benefit from the presence of the written text alongside an oral presentation despite
their poorer reading abilities. Given the growing use of e-books, these results are
important in suggesting that listening to a narration of the story while reading enhances
vocabulary acquisition. Having said that, given the narrow age range of the children in
our study, it is possible that individual differences in ability might interact with
presentation modality to affect learning in a younger or older population of school-aged
children. Older, more efficient readers might, for example, learn equally well from
reading and reading and listening, as adults do (Sydorenko, 2010), whereas less
experienced readers might not be able to take advantage of a dual presentation modality
compared with listening. Future studies that explore the relationship between the effect
of presentation modality and individual differences in ability in younger and older
readers would elucidate whether the pattern found in the current study changes with
development.

<h>CONCLUSION</h>
----------

This study shows that children aged 8 or 9 years are able to extract information about new
words from a story and that the modality of the story presentation influences the nature
and extent of their learning. Children learned the new words’ phonology similarly well
from the three presentation modalities (listening, reading, and combined conditions), but
orthography was learned only when it was directly presented (reading and combined
conditions). Children showed the strongest learning for words’ semantic categories when
words were presented both orally and in written form (combined modality). The practical
implications of these findings for the classroom are that children are able to learn
information about the phonological forms, orthographic forms, and meanings of new words
when they are listening to and/or reading stories. Importantly, both listening to and
reading stories can support the learning of new phonological forms, whereas opportunities
to see the new words written down are crucial for building representations of their
orthographic forms. Finally, allowing children to hear stories while they are reading
along may be optimal for learning, and especially for the extraction of semantic
information, supporting teachers’ practice of reading aloud in the classroom.


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<ART>Longitudinal associations between parents’ motivations to exercise and their moderate-to-vigorous physical activity
================================================================================

Authors: Lydia G. Emm-Collison, Russell Jago, Ruth Salway, Janice L. Thompson, Simon J. Sebire
DOI: 10.1016/j.psychsport.2019.04.007
Year: 2019  |  Pages: 343-349
ASJC codes: 3202
Keywords: Accelerometer, Longitudinal, Motivation, Parents, Physical activity

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: This study is the first examination of the longitudinal associations between behavioural regulation and accelerometer-assessed physical activity in parents of primary-school aged children. Design: A cohort design using data from the B-Proact1v project. Method: There were three measurement phases over five years. Exercise motivation was measured using the BREQ-2 and mean minutes of moderate-to-vigorous physical activity (MVPA) were derived from ActiGraph accelerometers worn for a minimum of 3 days. Cross-sectional associations were explored via linear regression models using parent data from the final two phases of the B-Proact1v cohort, when children were 8–9 years-old (925 parents, 72.3% mothers) and 10 to 11 years-old (891 parents, 72.6% mothers). Longitudinal associations across all three phases were explored using multi-level models on data from all parents who provided information on at least one occasion (2374 parents). All models were adjusted for gender, number of children, deprivation indices and school-based clustering. Results: Cross-sectionally, identified regulation was associated with 5.43 (95% CI [2.56, 8.32]) and 4.88 (95% CI [1.94, 7.83]) minutes more MVPA per day at times 2 and 3 respectively. In the longitudinal model, a one-unit increase in introjected regulation was associated with a decline in mean daily MVPA of 0.52 (95% CI [-0.88, −0.16]) minutes per year. Conclusions: Interventions to promote the internalisation of personally meaningful rationales for being active, whilst ensuring that feelings of guilt are not fostered, may offer promise for facilitating greater long-term physical activity engagement in parents of primary school age children.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Physical activity is associated with reduced risk of a variety of health outcomes,
including heart disease, stroke, type 2 diabetes, several forms of cancer, and depression
(Kyu et al., 2016; Rebar et al., 2015). Similarly, physical inactivity has been shown to
be detrimental for health and well-being and has been identified as a source of great
economic cost globally (Ding et al., 2016). As such, global physical activity guidelines
recommend that adults undertake at least 150 min per week of moderate intensity activity,
including additional muscle-strengthening activities at least twice a week, alongside the
general aim of reducing their sedentary time (Australian Government, 2017; Department for
Department of Health, 2011; Health Council of the Netherlands, 2017; Tremblay et al.,
2017; World Health Organisation, 2010). However, evidence suggests that between 15% and
43% of adults in western countries do not meet physical activity recommendations (Colley
et al., 2011; Craig, Mindell, & Hirani, 2011; Hallal et al., 2012; Kapteyn et al., 2018).
From a public health perspective, it is clear that efforts need to be made to encourage
more adults to be regularly active. Thirty-five percent of adults (aged 18–65) in the UK
have dependent children (Office for National Statistics, 2017). Parents of young children
have been shown to engage in less moderate-to-vigorous physical activity (MVPA) than
similar aged adults without children (Bellows-Riecken & Rhodes, 2008; Berge, Larson,
Bauer, & Neumark-Sztainer, 2011), with a noticeable decrease in physical activity at the
point of transition to parenthood (Hull et al., 2010; McIntyre & Rhodes, 2009). Engaging
in regular physical activity may be particularly challenging for parents with dependent
children due to increased demands on their time, financial burdens, and a change in
priorities compared to before parenthood. Yet, promoting parental engagement in physical
activity could be beneficial for both parents and children in terms of health benefits,
parenting behaviour, and energy levels (Hamilton & White, 2010; Lewis & Ridge, 2005).
Additionally, if parents are active then they model active behaviour to their children
(Sebire et al., 2016), with some evidence suggesting a weak positive association between
parent physical activity and child activity (Jago, Solomon-Moore, Macdonald-Wallis,
Thompson, Lawlor & Sebire, 2017a, b; Shutz, Browning, Smith, Lohse, & Cunningham-Sabo,
2018; Yao & Rhodes, 2015). A recent review of reviews highlighted that individual level
variables (e.g., motivation, age, and health intentions) are the most consistent
correlates of physical activity (Choi, Lee, Lee, Kang, & Choi, 2017) therefore indicating
that interventions should be either tailored to specific populations or should encompass
ways of manipulating these variables to increase physical activity. Self-determination
theory (SDT; Ryan & Deci, 2017) is a framework through which the motivational processes
that underpin physical activity can be investigated. Within SDT, quality of motivation is
placed upon a continuum whereby different types of motivation differ in the extent to
which they are autonomous or controlled (Deci & Ryan, 2000; Howard, Gagne, & Bureau,
2017). Three types of motivation are said to be more autonomous in nature: Intrinsic
motivation, the most autonomous form of motivation characterised by an individual
inherently enjoying or gaining satisfaction from the activity; integrated regulation, when
the behaviour aligns with an individual’s identity; and identified regulation, when an
individual consciously values the behaviour (Ryan & Deci, 2017). More controlled types of
motivation are introjected regulation, when behaviour is controlled by self-imposed
sanctions, such as shame, pride, ego, or guilt (Deci & Ryan, 2002) and external
regulation, the most controlled form of motivation when behaviour is driven by external
factors such as rewards, compliance and punishments (Deci & Ryan, 1987). Additionally, a
lack of either autonomous or controlled forms of motivation is classed as amotivation
(Ryan & Deci, 2000). In the context of physical activity, effortful and persistent
behaviour is more likely to occur when an individual’s motivation is autonomous as opposed
to controlled (Standage & Ryan, 2012). Cross-sectional evidence consistently shows
autonomous motivation for exercise (i.e., intrinsic, integrated, and identified
regulation) to be positively associated with self-reported and accelerometer-assessed
physical activity in healthy adults (see Teixeira, Carraca, Markland, Silva, & Ryan, 2012
for a review). Controlled motivation is generally shown to have little cross-sectional
association with self-reported and accelerometer-assessed physical activity behaviour
(Teixeira et al., 2012). However, when analysed separately, introjected regulation more
frequently shows a positive cross-sectional association with physical activity whereas
external regulation is more commonly negatively associated with physical activity (e.g.,
Edmunds, Ntoumanis, & Duda, 2006; Wilson, Rodgers, & Fraser, 2002). In addition to the
cross-sectional evidence, there are a small number of studies that have examined, and
provided evidence, for a small to moderate positive association between autonomous
motivation and self-reported physical activity over periods of time ranging from 1 to 6
months (Barbeau, Sweet, & Fortier, 2009; Fortier, Kowal, Lemyre, & Orpana, 2009; Gunnell,
Crocker, Mack, Wilson, & Zumbo, 2014). In support of these longitudinal associations,
qualitative evidence aligns with the theoretical tenet that movement through the
behavioural regulation continuum towards more autonomous motivation is central to physical
activity adherence (Kinnafick, Thogerson-Ntoumani, & Duda, 2014). To date, studies have
shown no evidence for a longitudinal association between controlled motivation and
physical activity (Barbeau et al., 2009; Gunnell et al., 2014). The limited number of
studies assessing the associations between motivation and physical activity over time have
used autonomous and controlled composites and not disaggregated the types of behavioural
regulation in statistical models, thus limiting the study of the roles of qualitatively
different types of motivation. Additionally, these longitudinal studies have also relied
on self-reported measures of physical activity behaviour which are prone to bias (Sallis &
Saelens, 2000). Therefore, further investigation of the longitudinal associations between
behavioural regulation and physical activity, using more reliable behavioural estimates
(e.g., through accelerometers) is warranted. Despite evidence indicating lower levels of
physical activity in parents compared to the wider adult population, theoretical models
have been seldom used to understand physical activity during parenthood (Bellows-Riecken &
Rhodes, 2008). The quality of motivation for exercise may be particularly pertinent to
parents’ physical activity due to extensive competing demands (e.g., time, fatigue,
childcare) that may make converting some forms of motivation to behaviour more challenging
for parents than non-parents (McIntyre & Rhodes, 2009; Solomon-Moore et al., 2016.) In
support of this, in a study involving 1067 parents of children aged 5–6 years old, only
identified regulation showed evidence of a cross-sectional association with MVPA after
adjustment (Solomon-Moore et al., 2016), suggesting that, for parents of younger children,
identifying with personally meaningful and valuable benefits of exercise may be the
strongest motivational driver. However, there are no studies of the motivation-physical
activity associations amongst parents of older children or evidence for any longitudinal
associations between motivation and physical activity behaviour during parenthood. The
aims of this research were to 1) examine the cross-sectional associations between the
behavioural regulations set forward in SDT and objectively-estimated physical activity in
parents of children aged 8–9 years old and then two years later when the same child was
10–11 years old and 2) assess the longitudinal associations between behavioural regulation
type and accelerometer-assessed physical activity in parents over a five-year period.

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

The current analyses used data from the B-Proact1v project. The broader project is a
longitudinal study exploring the factors associated with physical activity and sedentary
behaviour in children and their parents throughout primary school. Briefly, data
collection was conducted at three timepoints: between January 2012 and July 2013 when all
participants had a child aged five to six years (Year 1, time 1), between March 2015 and
July 2016 when the same child was aged eight to nine years (Year 4, time 2) and between
March 2017 and May 2018 when the same child was in year 6 (aged 10–11). A total of 57
schools consented to participate at time 1 and were subsequently invited to participate at
times 2 and 3. Forty-seven schools participated at time 2 and 50 participated at time 3.
Across all three timepoints, data were collected from 2555 parents from 2132 families:
1195 parents were involved at time 1, 1140 at time 2, and 1233 at time 3. A total of 546
parents took part across two timepoints and 246 across three timepoints. The study
received ethical approval from the University of Bristol ethics committee, and written
consent was received from all participants at each phase of data collection.

<hs>  Measures</hs>
  ~~~~~~~~

Characteristics. Parents completed a questionnaire which included information about their
date of birth, gender, ethnicity, height, weight, education level, and number of children.
BMI was calculated from their self-reported height and weight. Parents also reported their
home postcode, and this was used to derive Indices of Multiple Deprivation (IMD scores),
based upon the English Indices of Deprivation (http://data.gov.uk/dataset/index-of-
multiple-deprivation). Higher scores indicate areas of higher deprivation. Motivation to
exercise. The Behavioural Regulation in Exercise Questionnaire (BREQ-2) was used to assess
motivation to exercise (Markland & Tobin, 2004). The BREQ-2 consists of 19-items each
assessing one of five forms of behavioural regulations: intrinsic (4 items e.g., ‘I
exercise because it’s fun’), identified (4 items e.g., ‘It’s important to me to exercise
regularly’), introjected (3 items e.g., ‘I feel like a failure when I haven’t exercise in
a while’), external (4 items e.g., ‘I exercise because other people say I should’), and
amotivation (4 items e.g., ‘I don’t see the point in exercising’). Due to difficulties in
empirically distinguishing between identified and integrated regulation, the BREQ-2 does
not assess integrated regulation (Markland & Tobin, 2004). Participants rated each item on
a 5-point Likert scale ranging from 0 (not true for me) to 4 (very true for me). In the
current study, the BREQ-2 subscales had good internal consistency in both the cross
sectional and longitudinal samples (α > 0.7; see Table 1). Physical activity. Participants
were asked to wear a waist-worn ActiGraph wGT3X-BT accelerometer for five days, including
two weekend days. Accelerometer data were processed using Kinesoft (v3.3.75; Kinesoft,
Saskatchewan, Canada) in 60-s epochs. In line with recommendations for monitoring habitual
physical activity in adults, analysis was restricted to participants who provided at least
three days of valid data including at least 1 weekend day (Aadland & Ylvisaker, 2015;
Trost, McIver, & Pate, 2005). A valid day was defined as at least 500 min of data, after
excluding intervals of ≥60 min of zero counts allowing up to 2 min of interruptions. The
average number of MVPA minutes per day were derived for each participant using population-
specific cut points for adults (≥2020 counts per minute (Troiano et al., 2008)).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

The data analysis consisted of cross-sectional analyses of time 2 and time 3 data (a
cross-sectional analysis of baseline data is published elsewhere; Solomon-Moore et al.,
2016) and a longitudinal analysis including data from all three timepoints. All analyses
were conducted at the parent level, so where two or more parents/guardians from the same
family were included in the project, each parent was treated as a separate participant.
Participants were included in the cross-sectional analysis if they had valid accelerometer
data, and BREQ-2 responses with not more than 1 missing item per subscale. Participants
were included in the longitudinal analysis if they met the above criteria for at least one
timepoint. Following recommendations for dealing with missing data, and in order to reduce
bias and increase statistical power, multiple imputation using chained equations was used
to impute missing data for participating parents cross-sectionally (Rubin, 1996;
Tabachnick & Fidell, 2012). The imputation models included parent gender, age, ethnicity,
BMI, education level, IMD score, number of children, MVPA and the five subscales of
behavioural regulation. For each, 20 imputed datasets were created using 20 cycles of
regression switching and estimates were combined across datasets using Rubin’s rules
(Rubin, 1996). Five independent variables, reflecting the five motivation types, were
treated as continuous variables. In the cross-sectional analyses, linear regression models
were used to examine associations between behavioural regulation and mean MVPA minutes per
day. To identify longitudinal associations between the motivation variables and physical
activity, we used a multi-level model to capture how MVPA changes over time. We also
included interaction terms between behavioural regulation variables and age to explore
whether change in MVPA over time differs with changes in behavioural regulation. In line
with evidence for their influence on MVPA in adults (Cerin, Leslie, & Owen, 2009; Hull et
al., 2010; Trost, Owen, Bauman, Sallis, & Brown, 2002), all analyses were adjusted for
age, gender, number of children in the household and IMD score. In all models, robust
standard errors were used to account for school clustering in the study design, and
parents were clustered within families, to account for family-level similarities. All
analyses were performed in Stata version 15 (StataCorp, 2017).

<hs>  Preliminary analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

At both time 2 and time 3, missing data among participating parents was minimal, and the
distributions of observed and imputed characteristics were similar (Table 1). At time 2,
the sample consisted of 925 participants of whom 72% were female, with a mean age of 41.34
years (SD = 6.20), and mean BMI of 25.83 kg/m2 (SD = 4.84). At time 3, the sample
consisted of 891 participants, of whom 73% were female, with a mean age of 43.32 years (SD
= 5.84), and mean BMI of 25.83 kg/m2 (SD = 4.77). Mean IMD was consistent across time
(14.92 at time 2 and 14.44 at time 3). Average daily MVPA increased slightly from 50.03
min (SD = 23.91) at time 2–52.28 min (SD = 24.31) at time 3. At both timepoints, means and
standard deviations for all motivation variables were similar, with participants reporting
higher levels of autonomous motivation than controlled motivation for exercise, with
levels of identified regulation being higher than intrinsic regulation. Full descriptives
for time 1 are reported elsewhere (see Solomon-Moore et al., 2016). A total of 2374
parents had valid accelerometer data for at least one timepoint (93% of parents involved
across the whole study). Of these, 463 had valid accelerometer data for two timepoints
(85% of those parents involved at two timepoints) and 185 for three timepoints (75% of
parents involved at three timepoints). Twenty-five parents provided no identifiable
information at any timepoint and so were excluded from the analyses. Due to the study
design, school attrition accounted for 244 families not taking part at time 2 and 167
families at time 3. At the family level, children moving to schools not involved in the
project accounts for the drop out of 253 families. Further, as the same parent was not
required to participate at every timepoint, in 227 families who had been involved at time
1, a different parent participated at time 2. A total of 302 families had a different
parent participating at each timepoint. In these cases, all parents involved at any
timepoint are included in the analysis.

        <hss>Cross-sectional associations between motivation and physical activity</hss>

        Consistent with baseline findings (Solomon-Moore et al., 2016), fully adjusted
        cross-sectional regression models (Table 2) showed a positive association between
        identified regulation and MVPA, with a one-unit increase in identified regulation
        associated with a 5.4-min (95% CI [2.6, 8.3]) and 4.9 min (95% CI [1.9, 7.8])
        increase in MVPA per day at time 2 and time 3, respectively. There was no evidence
        for an association between any other type of behavioural regulation and MVPA at
        time 2. At time 3, introjected regulation was negatively associated with MVPA,
        with a one-unit increase in introjected regulation associated with a 3.2-min
        decrease in MVPA per day (95% CI [-5.0, −1.4]). There was no evidence for an
        association between the other types of behavioural regulation and MVPA at time 3.

        <hss>Longitudinal associations between motivation and physical activity</hss>

        The full multi-level model (Model 1, Table 3) explores how parent MVPA changes
        across the three timepoints in relation to behavioural regulation. Daily MVPA
        increased by an average of 0.60 min per year (95% CI [0.17, 1.03]). Identified
        regulation was positively associated with MVPA, with a one-unit increase in
        identified regulation being associated with an average of 3.96-min more MVPA per
        day per year (95% CI [2.42, 5.50]). Due to the association between time and MVPA
        in model 1, in model 2 we investigated whether change in MVPA over time was
        associated with behavioural regulation (Table 3). At time 1, identified regulation
        remained positively associated with MVPA with a one unit increase in identified
        regulation being associated with an 8.73-min increase in average daily MVPA per
        year (95% CI [3.41, 14.05]), however there was no association with change in MVPA
        over time. Introjected regulation was not associated with MVPA at time 1 but had a
        small negative association with change in MVPA over time, with a one unit increase
        in introjected regulation being associated with an average decline in daily MVPA
        of 0.52 min per year (95% CI [ −0.88, −0.16]).

<h>DISCUSSION</h>
----------

This study presents the first longitudinal analysis of the association between parents’
exercise motivation and accelerometer-estimated physical activity. The analyses indicate
that high levels of introjected regulation can lead to a small decrease in MVPA over time.
Substantiating the baseline findings from the B-Proact1v cohort, the cross-sectional
analyses also show that identified regulation is consistently associated with higher
levels of MVPA but was not associated with change in MVPA over time. Our cross-sectional
findings corroborate previous evidence showing that identified regulation is the type of
behavioural regulation most strongly associated with physical activity behaviours in
adults (Standage, Sebire, & Loney, 2008; Teixeira et al., 2012; Wilson, Sabiston, Mack, &
Blanchard, 2012). These also extend the baseline findings of the B-Proact1v cohort to show
that, across all three phases of the project, parents who are motivated to be physically
active due to personal value engage in higher levels of MVPA than parents who are
motivated in other ways. However, despite being consistently associated with higher levels
of physical activity, the multi-level models suggest that identified regulation is not
associated with change in physical activity over time. This is consistent with the
theoretical assumption that more autonomous motivation is associated with long-term
behavioural engagement (Ryan & Deci, 2017) and could indicate that identified regulation
is more pertinent to behavioural maintenance, as behaviours that align with an
individual’s personal values are more likely to be sustained (Kwasnicka, Dombrowski,
White, & Sniehotta, 2016). Whilst the motivational continuum proposed within SDT suggests
that intrinsic motivation (i.e., enjoyment of the behaviour itself) is the strongest
motivational driver of behaviour, it has been recognised in the wider literature that
behaviours such as exercise or being active might be more strongly driven by what can be
achieved through doing it (e.g., physical or mental health benefits, social contact with
others, development of skills and feelings of competence) rather than inherent enjoyment
of the activity itself (Standage & Ryan, 2012). In the present study, parents’ endorsement
of intrinsic and identified types of motivation were similar, emphasising that enjoyment
and satisfaction are important sources of motivation. However, the lack of association
between intrinsic motivation and physical activity suggests that, for parents, enjoyment
of physical activity is not sufficient to lead to action, and that personally valuing
activity is a more stable motivation factor for underpinning behaviour. One explanation
for this could be related to the parental role, where activities that do not directly
align, and potentially compete, with core parenting duties (e.g., taking time out to be
active or exercise for fun or enjoyment) are not prioritised and may even result in
feelings of guilt and selfishness (Hamilton & White, 2010). The present cross-sectional
findings show that when the benefits of physical activity are perceived to be personally
relevant and valuable, engagement in physical activity is greater. Therefore, valuing the
benefits of exercise as an individual (e.g., physical & mental health, better sleep, more
energy) and/or as a parent (e.g., modelling healthy behaviours, being physically fit to
“keep up” with active children; Hamilton & White, 2010) may be central to being a more
physically active parent. The cross-sectional findings showed a differential change in the
association between introjected regulation and parents’ MVPA across the three timepoints,
moving from a small positive association at time 1 (Solomon-Moore et al., 2016) to an
increasingly negative association across times 2 and 3. The longitudinal results further
highlight the impact of introjected regulation on behavioural outcomes, with a negative
association between introjected regulation and change in MVPA over time. Within SDT, it is
proposed that more controlled forms of motivation are detrimental to both behavioural and
well-being outcomes (Ryan & Deci, 2017), yet previous longitudinal studies have found no
evidence for this association (Barbeau et al., 2009; Gunnell et al., 2014) and cross-
sectional research has indicated that introjected regulation may be associated with higher
levels of physical activity (e.g., Brunet & Sabiston, 2011; Edmunds et al., 2006). These
findings offer the first evidence of a long-term negative impact of introjected regulation
on physical activity behaviour. Although further longitudinal research is warranted, given
the universality of SDT we would anticipate that similar associations in the wider adult
population with previous studies finding no association due to aggregating introjected and
external regulations into a controlled motivation variable (e.g., Barbeau et al., 2009;
Gunnell et al., 2014). However, there may also factors unique to parents that mean
motivations grounded in feelings of guilt and shame have an increasing negative effect on
physical activity as your child gets older. Extending previous studies, we explored the
individual association of each type of behavioural regulation with change in physical
activity behaviour. A potential explanation for this could be the association between
introjected regulation and maladaptive social comparisons (Thogersen-Ntoumani & Ntoumanis,
2006). For example, parents may feel envy and resentment towards other parents who appear
to be managing to be physically active (Hamilton & White, 2010), with such feelings having
a more detrimental effect on behavioural engagement once the child is older and the parent
might have more discretionary time. In terms of internal comparisons, parents of young
children may accept that they cannot be physically active in the short term, hoping that
they will be more active as their child gets older. If parents do not meet these self-
imposed expectations when their child is older, this could result in a cyclical
relationship between failure to be active and guilt. For parents these effects might be
particularly salient due to the competing demands on their time. Evidence suggests that,
for adults, increasing daily MVPA by 5–10 min can have clinically meaningful health
benefits (Dohrn, Kwak, Oja, Sjostrom & Hagstromer, 2018; Greaves et al., 2011). With this
in mind, the data presented in this paper indicate that strategies to encourage parents to
find personal value, relevance and importance in being physically active whilst ensuring
that feelings of guilt or shame are not induced, may be particularly important for
promoting increased physical activity engagement with the potential for meaningful impact
on health outcomes. This requires environments that support rather than thwart the three
psychological needs of autonomy, competence and relatedness (Ryan & Deci, 2017). Such
environments are characterised by the provision of choice (e.g., when and how to be
active/exercise), optimal challenge (e.g., one’s exercise goals/plans are neither too easy
nor too hard to achieve), and strong connections with others (e.g., being active is
normal/accepted amongst one’s friends, family, or colleagues). Additionally, and
particularly relevant for the promotion of identified regulation, may be the provision of
a personally relevant and valuable rationale for being active, which has been shown to
promote long-term behavioural engagement (Samdal, Eide, Barth, Williams, & Meland, 2017).
Qualitative evidence suggests that long-term goals can be abstract and undermine physical
activity and, as such, physical activity messages should emphasise that being active can
also be immediately gratifying and help people cope with or manage their daily goals
(Segar, Taber, Patrick, Thai, & Oh, 2017). Research on the content of exercise goals
(essentially benefits of exercise) shows that goals such as health, social affiliation and
development of exercise competence or skills are associated with greater autonomous
motivation and psychological well-being (Sebire, Standage & Vansteenkiste, 2009). For
parents, effective messages could include promoting physical activity as an important
family activity that provides the opportunity to spend time together and interact with
others, increase energy levels, and to relax and escape daily pressures (Segar et al.,
2017). However, further qualitative work is required to inform the development of specific
health messaging that aligns with identified regulation.

<h>LIMITATIONS AND FUTURE DIRECTIONS</h>
---------------------------------

The strengths of the study lie in the theoretically-grounded approach to motivation,
longitudinal data collected from the same cohort on three occasions over a five-year
period and the use of accelerometers to estimate levels of MVPA which when combined have
made a novel contribution to the literature. However, limitations should be acknowledged.
First, the sample was largely female, and therefore is more representative of mothers than
parents in general. However, given the universality of SDT, and supporting evidence
indicating no gender differences in behavioural regulation as measured through BREQ-2, we
would not anticipate significant differences in findings in a more male-dominated sample
(Guerin, Bales, Sweet, & Fortier, 2012). Additionally, participating parents were
generally more active than average in the UK (Craig, Mindell, & Hirani, 2011) and had high
levels of self-determined motivation. This may limit the generalisability of the findings
to the wider parent population and may also have limited the extent to which we can
observe change over time. Whilst we did not have the power in the present study, in future
researchers may want to look at the differences in motivation between parents with low
physical activity levels, and those with high physical activity levels. A further
limitation is that the BREQ-2 questionnaire used to measure motivation does not assess
integrated regulation which sits on the SDT continuum of motivation between identified and
intrinsic motivation types and represents the assimilation of the behaviour with one’s
values, goals, and sense of self (e.g., “I am active”; Ryan & Deci, 2017).

<h>CONCLUSION</h>
----------

This study is the first to assess the longitudinal associations between parent’s
behavioural regulation to exercise in relation to accelerometer-estimated physical
activity. The results indicate that motivation grounded in the personal meaning and value
of exercise is associated with higher levels of MVPA. Additionally, the results suggest
that being motivated by feelings of guilt and shame impact negatively on MVPA over time.
Therefore, interventions that promote greater enjoyment, personal relevance and value,
whilst also ensuring that guilt is not promoted, may offer promise for the facilitation of
greater long-term physical activity engagement in parents.

<h>CONFLICTS OF INTEREST</h>
---------------------

We have no competing interests to report.

<h>FUNDING</h>
-------

This work was funded by the British Heart Foundation (Grant numbers: PG/11/51/28986 and SP
14/4/31123).


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<ART>Longitudinal development of visual working memory precision in childhood and early adolescence
================================================================================

Authors: S. Burnett Heyes, N. Zokaei, M. Husain
DOI: 10.1016/j.cogdev.2016.03.004
Year: 2016  |  Pages: 36-44
ASJC codes: 3204, 3205
Keywords: Adolescence, Childhood, Development, Precision, Working memory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Visual working memory (VWM) is the ability to hold in mind visual information for brief periods of time. The current study investigated VWM precision development longitudinally. Participants (N = 40, aged 7-11 years) completed delayed reproduction sequential VWM tasks at baseline and two years later. Results show age-related improvement in recall precision on both 1-item and 3-item VWM tasks, suggesting development during childhood and early adolescence in the resolution with which both single and multiple items are stored in VWM. Probabilistic modelling of response distribution data suggests age-related improvement in precision is attributable to a specific decrease in the variability (noisiness) of stored feature representations. This highlights a novel developmental mechanism which may underlie longitudinal improvement in VWM performance, crucially without invoking improvement in the number of items that can be stored. VWM precision provides a sensitive metric with which to track developmental changes longitudinally, shedding light on underlying cognitive mechanisms.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Visual working memory (VWM) provides a temporary storage mechanism for the retention and
manipulation of visual information to support other cognitive processes (Luck & Vogel,
1997). This ability is considered to be a critical contributor to many essential cognitive
functions such as decision-making, complex reasoning and goal-directed action (Baddeley,
2003). Numerous developmental studies have shown that performance on established
neuropsychological tests of VWM improves during childhood (Alloway, Gathercole, &
Pickering, 2006; Gathercole, Pickering, Ambridge, & Wearing, 2004). Typically in these
tests, participants view a static visual array (e.g. coloured shapes) or spatiotemporal
sequence of visual events (e.g. block tapping) which are held in memory and then
reproduced following a delay. These studies have demonstrated, within large cross-
sectional datasets, robust age trajectories and evidence for developmental stability in
the relationship of VWM to other cognitive components (Gathercole et al., 2004). The
mechanisms underlying VWM development and its relationship with other cognitive measures
remain debated (Astle & Scerif, 2011). That is, what are the fundamental cognitive
mechanisms underlying developmental improvements in VWM? Most traditional measures of VWM
rely on indices of the number of items that can be remembered, e.g. using tasks that
measure recall span or change detection. These reports rely on the classical concept that
VWM is limited to holding only a very small number of items, as little as 3 or 4 in
adults, arguing in favour of a ‘quantal’ memory mechanism limited to 3–4 memory
‘slots’(Luck & Vogel, 1997). In effect, this is a digital view of how items are stored in
memory, with both span and change detection tasks providing a discrete estimate of the
number of items that can be retained in VWM. Recently, an innovative empirical approach
has shown potential to accurately and sensitively characterise VWM performance in a
completely different way. Unlike span or change detection tasks, this approach relies on
participants reproducing the exact qualities of the retained information on a continuous
response scale, e.g. the orientation of a bar stimulus. Such analogue responses provide a
measure of working memory precision, where precision reflects the resolution with which
items are held in VWM (Bays, Catalao, & Husain, 2009; Fougnie, Asplund, & Marois, 2010;
Wilken & Ma, 2004; Zhang & Luck, 2008). Recent investigations suggest that continuous
recall measures may be more sensitive indices of changes in VWM than discrete capacity
measures, e.g. in adult neuropsychological populations (Zokaei, Burnett Heyes,
Gorgoraptis, Budhdeo, & Husain, 2014). Findings from such delayed reproduction tasks have
also challenged the ‘quantal’ view of VWM. Results from such studies are not consistent
with the view that there is a fixed upper limit to the number of items that can be stored
in VWM (Bays et al., 2009; Gorgoraptis, Catalao, Bays, & Husain, 2011; Ma, Husain, & Bays,
2014; Zokaei, Gorgoraptis, Bahrami, Bays, & Husain, 2011). Instead, these investigations
have shown that response data can be modelled by considering VWM to consist of a limited
cognitive resource (Bays & Husain, 2008), with recall error arising due to noise in tuned
populations of neurons (Bays, 2014, 2015; Ma et al., 2014). As the number of items stored
increases, the precision with which each item can be retained decreases, purportedly
because the same pool of tuned neurons must represent more items, and thus the
representation of each item becomes noisier (Bays, 2014; Bays, 2015; Ma et al., 2014).
Using the statistical procedure of mixture modelling of response data, continuous VWM
tasks also provide a means to dissect out sources of error contributing to the pattern of
overall VWM performance (Bays et al., 2009). In other words, what basic, fundamental
cognitive processes contribute to working memory failure and success? Firstly, response
error can theoretically arise due to variability in memory – ‘noise’ – associated with the
remembered feature; that is, how accurately information (e.g. orientation) is stored.
Alternatively, error can arise due to random guessing, for example, due to failures at
encoding or at retrieval leading to a completely random response. Lastly, error may arise
due to systematic interference or corruption of information by the other items encoded
into VWM. These latter misbinding responses occur when one feature of an object (e.g.
colour) is erroneously linked with the feature (e.g. orientation) of a different object
stored in memory (Bays et al., 2009). Crucially, characterising VWM development in terms
of these distinct sources of error may provide further insights into underlying
developmental cognitive mechanisms. The current study investigated development of VWM
precision longitudinally between age 7 and 13 years. Forty participants completed an
identical task battery twice, two years apart. Tasks consisted of 1-item and 3-item
sequential VWM precision tasks and a sensorimotor control task. Precision was calculated
as 1/SD of error (reciprocal of variability) in response. After controlling for
developmental changes in sensorimotor performance, we predicted longitudinal increases in
recall precision on both the 1-item and 3-item VWM tasks. In addition, we predicted
mixture modelling of recall data from the 3-item VWM task would provide evidence that
effects of age are attributable specifically to a decrease in variability in the
representation of target stimuli, and not to any changes in random guessing or misbinding.
That is, the mixture modelling would shed further light on more fundamental cognitive
mechanisms underlying memory development—whether changes in VWM performance are due to
developmental increases in continuous memory resource, or to some other process such as
reduced frequency of misbinding or guessing.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

40 participants were recruited from a single-sex (male) preparatory school in Oxfordshire
and tested on the same protocol twice, two years apart (t1 and t2). Participant age at t1
ranged from 7.9 to 11.7 years, with mean 10.2 and standard deviation (SD) 1.02 (see Table
1). Participants were from a larger (N = 90) cross-sectional cohort (Burnett Heyes,
Zokaei, van der Staaij, Bays, & Husain, 2012). The current longitudinal cohort of 40
participants consisted of all t1 participants who were still attending the school at t2
for whom parent/guardian consent could be obtained at t2 and for whom timetabling
constraints permitted attendance of the testing session at t2.

<hs>  FSIQe</hs>
  ~~~~~

Standardized yearly test scores (CAT-3; www.gl-assessment.co.uk) were provided by the
school for each participant at t1 and transformed into estimated full-scale IQ (FSIQe; see
Table 1), as per Wright, Strand and Wonders (2005):FSIQe = 1.1 × CAT-Av − 12.0where FSIQe
is estimated FSIQ and CAT-Av is average CAT-3 score calculated by combining standardised
scores on verbal, non-verbal and quantitative reasoning subtests (Wright et al., 2005).

        <hss>Colour-naming task</hss>

        At the start of the experiment, each participant completed a colour-naming task in
        which they were shown five screenshots from the VWM task, each containing a bar in
        one of the following stimulus colours: red, yellow, green, blue and purple/pink.
        Participants were asked to name aloud each of these five colours. All participants
        successfully completed this task.

        <hss>Sensorimotor control task</hss>

        Directly after completion of the colour-naming task, participants completed 25
        trials of a sensorimotor control task (Fig. 1A). Stimuli were presented on a
        laptop monitor (32° × 19°) at a viewing distance of ∼52 cm. On each trial a
        coloured oriented bar (2 × 0.2° of visual angle) was presented against a grey
        background. After 500 ms following the presentation of the bar, a probe bar of the
        same colour surrounded by a black circle appeared below the target. Participants
        were asked to adjust the orientation of the probe bar using a rotating dial to
        match the orientation of the target which remained on screen until response. The
        black circle surrounding the probe item disappeared upon rotating the dial. Bar
        colour was selected so as to be easily distinguishable—as in the colour-naming
        task. The orientation of the target and probe were independently randomized. The
        inter-trial interval (ITI) was 500 ms.

        <hss>Visual working memory task: 1-item</hss>

        Directly after completion of the sensorimotor control task, participants completed
        30 trials of a 1-item VWM task. On each trial, participants were presented with a
        single coloured oriented bar at the centre of the screen for 500 ms. Following a
        blank 500 ms delay, a probe bar of the same colour appeared at the centre of the
        screen surrounded by a black circle. Participants were asked to adjust the probe
        bar’s orientation to match the orientation of the probed (‘target’) bar using the
        dial (Fig. 1B). Participants completed 30 trials of this task divided into 2
        blocks of 15 trials each with a short break in between blocks. During the break
        participants were encouraged to focus on a far point in the room, to minimise
        ocular fatigue. The ITI was 500 ms.

        <hss>Visual working memory task: 3-items</hss>

        Directly after completion of the 1-item VWM task, participants completed 90 trials
        of a 3-item VWM task. A schematic presentation of this task is shown in Fig. 1C.
        On each trial, a sequence of 3 coloured bars was presented at the centre of the
        screen against a grey background. Each bar was presented for 500 ms followed by a
        500 ms blank interval prior to the presentation of the next bar. At the end of
        each trial, a randomly oriented probe bar of the same colour as one of the bars in
        the previous sequence was presented within a black circle. Using the dial,
        participants were asked to match the probe’s orientation to the orientation of the
        similarly-coloured bar in the preceding sequence (the ‘target’). All
        colours/serial positions in the sequence were probed with equal probability.
        Participants completed 90 trials of this task, with a break every 15 trials. The
        ITI was 500 ms.

        <hss>Developmental changes in precision</hss>

        We calculated recall precision as the reciprocal of the circular standard
        deviation of response error (where response error is the difference between
        response and target angles) (Fisher, 1993). Precision is a measure of response
        variability: less variability corresponds to more precise recall. Recall precision
        was calculated for the sensorimotor, 1-item and 3-item VWM tasks. To evaluate the
        effect of age on VWM precision controlling for any changes in sensorimotor
        performance, we corrected performance on the VWM task by subtracting sensorimotor
        error from VWM recall error and recalculating precision accordingly (i.e.
        1/sqrt(difference in error variance)). To evaluate developmental changes in
        precision, Wilcoxon signed-rank tests (the non-parametric equivalent of paired
        samples t-tests) were conducted comparing t1 vs. t2 corrected 1- and 3-item VWM
        precision values (overall and at each serial position) as well as sensorimotor
        precision. Statistical significance was p < 0.05. Non-parametric statistics were
        used since in our data precision is not normally distributed. Finally, to
        investigate differential trajectories of development for 3-item relative to 1-item
        VWM tasks, Wilcoxon signed-rank tests were conducted comparing t1 vs. t2 3-item
        VWM precision values, corrected for 1-item VWM performance by subtracting 1-item
        VWM recall error from overall 3-item VWM recall error and recalculating precision
        accordingly (i.e. 1/sqrt(difference in error variance)).

        <hss>Mixture modelling of error in response</hss>

        Several sources of error could contribute to developmental changes in performance
        on VWM tasks such as those employed in the present study. Firstly, changes in VWM
        performance could result from a change in variability in memory for target
        features – here orientation – captured by the model concentration parameter (κ). κ
        is a measure of variability, where higher κ corresponds to lower variability in
        memory representations (Fig. 2A). Successful performance of the 3-item VWM task
        also requires memory for the correct combination of orientation and colour.
        Therefore, changes in performance on the 3-item VWM task could arise as a result
        of changes in the proportion of responses arising as a result of an incorrect
        conjunction of colour and orientation (misbinding errors). In such trials
        participants make an error centred on the orientation of other (non-probed) items
        in the sequence (Fig. 2B). In clearer terms: if the probed item is red but
        participants respond with the orientation of one of the other coloured bars in the
        sequence, this would be classified by the model as a misbinding error. In the
        model, the probability of reporting a non-target item is given by β, with {ϕ1, ϕ2
        … ϕm} the orientations of the m non-target items. Alternatively, change in recall
        precision could occur due to changes in the number of guesses/random
        responses—captured in the model by γ (Fig. 2C), where γ=1-α-β. Maximum likelihood
        parameters of κ, α, β and γ were obtained for each task using an expectation
        maximization procedure for each participant (Myung, 2003). Using this
        probabilistic model, we were able to determine the underlying sources of
        developmental change in VWM. Similar to our analysis of recall precision, we used
        paired t-tests to compare t1 vs. t2 measures of κ and the proportion of target,
        non-target and random responses.

<hs>  Sensorimotor precision during development</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Sensorimotor precision improved significantly between t1 and t2 (Z = 3.19, p = 0.01; Table
2). Therefore, in the remaining analyses of performance in the 1-item and 3-items VWM
tasks, we corrected performance for changes in sensorimotor precision (for details, see
Section 3).

<hs>  Working memory precision improves with age on the 1- and 3-item VWM tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mean precision on the 1-item VWM task improved significantly after 2 years after
correcting for developmental change in sensorimotor precision (Z = 2.87, p = 0.004; one
outlier >2.5 SD > mean excluded). Thus, precision of recall for even a single item
maintained in memory increased after 2 years in childhood and early adolescence. Recall
precision on the 3-item VWM task also improved significantly with age. Participants
performed significantly better at t2 compared to t1 (Z = 2.39, p = 0.017; Fig. 3A).
Wilcoxon signed-rank tests comparing t1 vs. t2 corrected precision at each serial position
of the target demonstrated a significant improvement in WM precision for items presented
first and second in the sequence (Z = 2.05, p = 0.04 and Z = 3.06, p = 0.002 respectively)
with no significant difference for the third item (Z = 1.57 p = 0.12; Fig. 3A).

<hs>  Improvement on 3-item WM task greater than improvement on 1-item VWM task</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Comparison of t1 vs. t2 3-item VWM precision corrected for 1-item VWM precision showed
evidence for a steeper developmental trajectory of precision in the 3-item VWM task
relative to the 1-item VWM task (Z = 2.79, p = 0.005; see Fig. 4 for individual
participants’ change in precision).

<hs>  Mixture modelling of error in response</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To visualize the distribution of responses in the 3-item VWM task, we plotted the
distribution of responses around the target (i.e. probed) orientation. As shown in Fig.
3B, the proportion of responses falling close to the target orientation increased from t1
to t2. This is specifically illustrated in the peak of response distribution around zero,
i.e. the greater proportion of responses at the target orientation and lower proportion of
responses at the tail of the distribution. However, overall performance does not inform us
as of the sources of error, and how these alter with age. That is, overall performance
does not shed light on whether improved VWM performance is due to decreased variability in
response for the target feature (kappa), changes in proportion of target (p(T)) or non-
target responses (p(NT)), or increased random responses (p(U)). We therefore fit a
probabilistic model (Fig. 2; Bays et al., 2009) to each participant’s 3-item VWM dataset
at each time point to examine the effect of age on each of the possible sources of error.
Results show that kappa (inverse of variability in response around probed or target
orientation) increased significantly with age (t(39) = 3.3, p = 0.002), crucially with no
change in other model parameters: t(39) = 1.6, p = 0.12 for p(T), t(39) = 1.4, p = 0.18
for p(NT and t(39) = 0.3, p = 0.73 for p(U) (Fig. 3C). Thus variability around the probed
target orientation improved significantly with age, without other sources of error
changing.

<h>DISCUSSION</h>
----------

The current study investigated longitudinal development of VWM precision during childhood
and early adolescence. Forty participants aged 7–11 years at t1 completed a VWM precision
task battery twice, two years apart. Results demonstrate firstly that recall precision
increased with age on both 1-item and 3-item sequential VWM precision tasks. These
increases remained significant after controlling for age-related improvement in
performance on a sensorimotor control task. Second, the longitudinal effects of age were
attributable to a specific decrease in variability in the representation of target
stimuli, and not due to changes in random responding or to misbinding, i.e. corruption by
features of other items retained in memory. We discuss implications in terms of
developmental mechanisms underlying observed improvements in VWM performance with age.

<hs>  Development of working memory precision</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A number of studies have shown improvement across childhood in performance on standard
tests of VWM (Alloway et al., 2006; Gathercole et al., 2004). In the current study, we
contribute to understanding the mechanistic underpinnings of VWM development. We show that
the precision with which items are recalled from VWM, whether presented individually or in
sequences of three, increased after a time interval of two years in participants aged 7–11
years at study entry. Because participants were sampled longitudinally, we can rule out
interpretations based wholly or partially on inter-individual variability and cohort
effects, enabling conclusions to be drawn regarding the developmental trajectory of VWM
precision. Importantly, longitudinal increases in precision withstood correction for
improvements in performance on a control task requiring fine hand-eye co-ordination, and
hence are not readily explicable on the basis of improvement in sensorimotor factors.
Instead, the results suggest that the resolution of items recalled from VWM increases
during middle childhood and early adolescence. These conclusions align with those from
cross-sectional studies showing age-associated development during childhood and
adolescence in VWM performance (Burnett Heyes et al., 2012; De Luca et al., 2003; Luciana,
Conklin, Hooper, & Yarger, 2005; Swanson, 1999; Zald & Iacono, 1998). The current results
are also consistent with studies showing developmental improvements in performance on
executive tasks that have a VWM component (Brocki & Bohlin, 2004; Luciana et al., 2005;
Luna, Garver, Urban, Lazar, & Sweeney, 2004). Using continuous recall measures, rather
than discrete measures of capacity, may offer enhanced sensitivity for tracking
behavioural changes in VWM, as has recently been demonstrated using even relatively small
samples (N = 12) of adult patients with neurodegenerative conditions (Zokaei et al.,
2014). Importantly, the approach taken here also enables investigation of the underlying
cognitive mechanisms associated with these developmental changes.

<hs>  Modelling the distribution of responses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Continuous VWM tasks provide a means to examine the sources of error in recall. We applied
a probabilistic model (Bays et al., 2009) to response data from the 3-item VWM task to
decompose the contributions of different sources of error. Within this model, error in
memory can arise from three sources. Firstly, it can be due to variability – ‘noise’ – in
memory for the remembered feature. Alternatively, error can arise due to random guessing,
for example due to failures at encoding or retrieval. Lastly, response error in the 3-item
VWM task may also theoretically arise due to systematic interference or biasing of
information by features belonging to other items encoded into VWM (i.e. misbinding or non-
target responses). Here, we show that improvement with age in the 3-item VWM task was
attributable to a specific decrease in variability in the representation of target
stimuli, and could not be attributed to any changes in the frequency of guesses or
misbinding errors. As such, our modelling analysis sheds new light on potential specific
mechanisms underlying longitudinal development in VWM performance. In future, delayed
reproduction VWM tasks accompanied by probabilistic modelling of response data could also
provide a useful tool for characterising more fully neural changes associated with VWM
across the lifespan. Several studies have shown that it is possible to track development
of the functional neural substrates of VWM during childhood and adolescence (Bunge &
Wright, 2007; Dumontheil & Klingberg, 2012; Geier, Garver, Terwilliger, & Luna, 2009;
Klingberg, Forssberg, & Westerberg, 2002). Using precision, rather than traditional
measures of capacity, may offer enhanced sensitivity for detecting variance associated
with age.

<hs>  Differential development on 1-item and 3-item VWM tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The current study showed effects of age on the difference in recall precision between
1-item and 3-item tasks, conceptually equivalent to an age by task interaction. That is,
whereas we demonstrate significant improvement with age on both VWM tasks, improvement on
the harder 3-item task was more substantial. Further empirical studies are needed to
explore the developmental cognitive mechanisms underlying this result. Possibilities
include development of attention (Astle, Nobre, & Scerif, 2012) or even emerging
metacognitive capability (Weil et al., 2013).

<h>CONCLUSION</h>
----------

We present longitudinal evidence that the precision of VWM for individually and multiply-
encoded items develops throughout middle childhood and early adolescence. This development
is attributable to a specific decrease in variability – noisiness – of stored feature
representations. This highlights a mechanism that may underlie longitudinal improvement in
VWM performance, without invoking improvement in the number of items that can be stored.
These findings demonstrate protracted development in VWM performance and shed light on the
potential mechanisms which could underpin this development longitudinally. Currently,
there is much interest in modifying cognition as a means of addressing suboptimal
developmental trajectories (Klingberg et al., 2005). VWM recall precision might provide a
sensitive metric for assessing the impact of behavioural training and neurofeedback
interventions (Wass, Scerif, & Johnson, 2012).


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<ART>Longitudinal trajectories of physical activity among employees participating in a worksite health promotion intervention: A latent class growth approach
================================================================================

Authors: Cathrine Pedersen, Hallgeir Halvari, Bård Erlend Solstad, Marte Bentzen
DOI: 10.1016/j.psychsport.2019.03.007
Year: 2019  |  Pages: 311-320
ASJC codes: 3202
Keywords: LCGA, Motivational regulations, Physical activity, Worksite health promotion

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: This study investigated different patterns of physical activity (PA; frequency, intensity, and duration) among employees during and after participating in a worksite health-promotion intervention over a period of one year. The study aimed to assess whether different patterns of PA were associated with perceived competence and motivational regulations for PA. Design: A cluster randomized controlled trial with a delayed-intervention control group. The design of the group-based intervention was based on the tenets of Self-determination theory (SDT). Method: The study consisted of employees (N = 202, M age = 42.5) working with manual labor in an (Anonymized) transport and logistics company. A person-centered approach was applied in order to explore if there were different latent trajectories within the sample related to PA. The data was analyzed with latent class growth analysis (LCGA) and the modified BCH method. Results: The LCGA identified three PA trajectories: (1) employees high at baseline who declined significantly (n = 16), (2) employees who remained stable at a moderate level (n = 55), and (3) the majority of employees who reported low levels at baseline and increased significantly (n = 128). High levels of PA were associated with higher levels of perceived competence and autonomous forms of motivation for, which is in line with the tenets of SDT. Contrary to study hypothesis, controlled forms of motivation increased in all three trajectories after the intervention. Conclusions: Different trajectories of PA were found, and the intervention was able to attract employees with low levels of PA.

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<h>INTRODUCTION</h>
------------

Despite great media attention and increased public awareness, people struggle to be
physically active at the level required to maintain their health and well-being, and
reduce their risk of chronic diseases. A national survey among (Anonymized nationality)
adults revealed that only 35% reported being sufficiently physically active as recommended
by the (Anonymized nationality) health authorities (150 min of moderate physical activity
[PA], or 75 min of vigorous PA, per week; Hansen et al., 2015). Participating in a health
promotion program can provide the necessary structure and support to initiate changes
related to regular PA or objective measures of PA effects such as cardiorespiratory
fitness (CRF). Composite interactive interventions that apply self-management and
motivational enhancement approaches have demonstrated the most promising results in terms
of effectiveness (Hutchinson & Wilson, 2011; Michie, Abraham, Whittington, McAteer, &
Gupta, 2009). However, program participation is typically limited in time, particularly in
non-treatment contexts. In order to produce changes in health and well-being of clinical
relevance to the individual and to society in general, participants must be able to
persist with lifestyle changes over a longer period of time – and on their own.
Consequently, it is of importance that they develop a sense of competence and an
autonomous motivation to persist with PA. Over the last four decades, the field of health
promotion research has called attention to the worksite context because programs here have
the potential to reach a large number of people, usually before they develop health
problems (Abraham & Graham-Rowe, 2009; Rongen, Robroek, van Lenthe, & Burdof, 2013).
Employers are willing to invest financial resources in programs because they appreciate
the potential benefits of increased PA for health and well-being, such as decreased
sickness absence (Cancelliere, Cassidy, Ammendolia, & Côté, 2011) and improved work
productivity (Pronk & Kottke, 2009). Moreover, the presence of natural and lasting social
networks offers a source of social support that can be incorporated into programs, and may
persist after the program has finished (Linnan, Fisher, & Hood, 2012). Meta-analyses have
demonstrated that worksite PA interventions can offer important albeit variable changes in
health, well-being, and certain worksite outcome measures such as reduced job stress
(Conn, Hafdahl, Cooper, Brown, & Lusk, 2009). There is a growing number of systematic
reviews and meta-analyses of worksite PA promotion studies. Overall, they report positive
effects albeit small effect sizes (Cohen’s d = 0.10–0.27) for self-reported measures of PA
(Abraham & Graham-Rowe, 2009; Conn et al., 2009; Dishman, DeJoy, Wilson, & Vandenberg,
2009; Malik, Blake, & Suggs, 2014; Proper et al., 2003). The research evidence related to
objective measures of fitness, such as CRF or muscle strength, is inconclusive and
divergent (Proper et al., 2003). For instance, meta-analyses have reported positive effect
sizes for CRF ranging from d = 0.29 (Abraham & Graham-Rowe, 2009) to d = 0.57 (Conn et
al., 2009). High-quality randomized controlled trials tended to report lower effect sizes
or non-significant effects compared to quasi-experimental and pre-post studies, and to
studies with less rigorous methodology (e.g., randomization procedure poorly implemented
or described, lack of intention-to-treat analysis, lack of control for confounders, lack
of objectively measured outcome variables, and short follow-up assessments; Rongen,
Robroek, van Lenthe, & Burdorf, 2013; To, Chen, Magnussen, & Kien, 2013). Moreover,
Taylor, Conner, and Lawton (2012) reported findings indicating that worksite PA
intervention studies using theory in an explicit and systematic manner were considerably
more effective (Cohen's d = 0.34) compared to studies which did not (d = 0.21). However, a
systematic review concluded that worksite programs had relatively low participation rates
(M = 33%, the majority below 50%), and males, blue-collar workers, and smokers were less
likely to participate (Robroek, van Lenthe, van Empelen, & Burdorf, 2009). Studies have
revealed that employees have mixed feelings towards worksite health-related PA programs.
For example, Fletcher, Behrens, and Domina (2008) found that employees perceived social
support and their own levels of PA self-regulation to be the most important enabling
factors for participating in worksite PA programs. The most frequently reported barriers,
apart from lack of time, were increased self-consciousness and a lack of belief in their
own ability to perform PA. Rossing and Jones (2015) found that employees were sensitive to
the possible loss of credibility and stigmatization from colleagues if they appeared less
competent or fit during collective exercise sessions at work. We argue that in order to
attract employees broadly, and particularly those who will benefit the most due to their
low levels of PA and an unfavorable health risk profile, PA promotion programs must offer
support in a manner that makes employees comfortable, and increases their competence, and
self-regulation regarding PA. The theoretical foundation of the present worksite PA
intervention was based on the tenets of Self-determination theory (SDT; Deci & Ryan, 1985;
2000) in combination with elements from Motivational interviewing (MI; Markland, Ryan,
Tolbin, & Rollnick, 2005; Miller & Rollnick, 2013). SDT is a theory of motivation that
emphasizes the importance of the quality of motivation towards a specific behavior, or
what people hope to obtain by doing the behavior. SDT presents a multidimensional approach
to motivation, distinguishing between three types of motivational qualities: autonomous,
controlled, and amotivation (Deci & Ryan, 2000). Autonomous motivation is characterized by
a sense of choice and freedom from external pressure. Here, people engage in a behavior
because they find it inherently satisfying (intrinsic regulation) or because they identify
with the behavior and find it personally meaningful (identified regulation). When
motivation for a specific behavior is contingent on the presence of external factors, such
as a reward or the expectations or demands of others, it is termed extrinsic regulation.
Once the external control is partially assimilated, people will typically experience a
sense of guilt or shame if they fail to perform the behavior in question. This is termed
introjected regulation. Both extrinsic and introjected regulations are controlled forms of
motivation, and are characterized by a low level of internalization (Deci & Ryan, 1985;
2000). Amotivation is characterized by a lack of motivation for a behavior, and hence a
lack of intention to act (Markland & Tobin, 2004). According to SDT, these different forms
of motivation are not mutually exclusive, and people can simultaneously endorse controlled
and autonomous motives for a behavior (Deci & Ryan, 1985; 2000). However, review studies
have demonstrated that autonomous motivation has a consistent and positive effect on
outcome variables related to health and well-being (Ng et al., 2012). The SDT based health
model of behavior change postulates that in order to make lifestyle changes, such as
increased PA, people need to perceive themselves as sufficiently competent as well as
motivated (Williams, Gagné, Ryan, & Deci, 2002). When people feel unfit, unskilled,
inexperienced, or restricted by health limitations or lifestyle situations that they
struggle to overcome, their sense of competence will be affected (Ryan, Williams, Patrick,
& Deci, 2009). A review of 53 PA studies demonstrated a consistent and rather strong
association between autonomous forms of motivation for PA and prolonged PA (Teixeira,
Carraça, Markland, Silva, & Ryan, 2012). However, the presence of a strong association
between controlled forms of motivation and PA has not received consistent empirical
support. The majority studies (57%) found no significant association, whereas the
remainder (43%) reported a negative relation (Teixeira, Carraca, Markland, Silva, & Ryan,
2012). The same was found for the association between amotivation and PA. Teixeira and
colleagues revealed that studies reporting negative associations between extrinsic
regulation and PA considered regular exercisers, as opposed to non-exercisers. In line
with SDT, regular exercisers have been found to report higher levels of autonomous
motivation for PA compared to exercise initiates and non-exercisers (Thøgersen-Ntoumani &
Ntoumanis, 2006). A study of four longitudinal datasets investigated the process of
becoming a regular exerciser and how this is related to motivational regulation (Rodgers,
Hall, Duncan, Pearson, & Milne, 2010). Participants who had completed a PA intervention
program reported increases in intrinsic and identified regulation eight weeks after
baseline. Despite a steady increase, autonomous motivation remained significantly lower
among exercise initiates compared to regular exercisers six months after baseline. Changes
in controlled motivation were non-significant during the study period. To date, there are
a limited number of SDT-based intervention studies that incorporate follow-up assessments
of motivational regulation and PA several months or years after the intervention. Silva
and colleagues found that autonomous motivation predicted enhanced maintenance of
behavioral change two years after the intervention (Silva et al., 2011). Duda et al.
(2014) reported improvements in PA of clinical relevance immediately after an
intervention, and the changes were sustained at six months follow-up. Moreover, changes in
motivational processes during the intervention were significantly related to PA levels at
follow-up. Sweet, Fortier, and Blanchard (2014) investigated the longitudinal effects of a
PA intervention on sedentary patients by means of hierarchical linear modeling of growth
trajectories. The study found a curvilinear trend for PA (increased at 13 weeks, and
decreased post-intervention between 13 and 25 weeks). In line with the tenets of SDT, both
intrinsic and identified regulation demonstrated a pattern of linear increase during the
25-week study period. However, the changes in extrinsic regulation followed the same
curvilinear trend as PA. No fluctuation was found for introjected regulation, and the two
controlled forms of motivation were not significantly related to changes in PA. We need
more knowledge about the nuances of longitudinal fluctuations in PA and their
relationships with motivational regulations, particularly in the period after PA
interventions when participants are expected to persist with their PA habits without the
support of a program. The majority of SDT-based PA intervention studies have been carried
out in the context of health care, often incorporating patients in need of treatment, such
as those who are overweight or obese (Silva et al., 2011), have type 2 diabetes (Sweet et
al., 2009), or require cardiac rehabilitation (Mildestvedt, Meland, & Eide, 2008). Fortier
and colleagues recommend that future studies assess intervention effects on groups that
are more diverse in terms of demographic characteristics, such as age and gender,
motivational regulation, and physical characteristic related to health (Fortier, Duda,
Guerin, & Teixeira, 2012). The number of SDT-based PA intervention studies has grown in
numbers, particularly studies with children (Owen et al., 2016) and adolescents (e.g.,
Lonsdale et al., 2016). However, PA intervention studies directed at adults are limited in
numbers and participants are by and large patients in treatment contexts. There is a need
for SDT-based intervention studies in non-treatment contexts targeting a more
heterogeneous population in terms of PA levels, health risk profile, and motivation for
PA. It can be argued that this will contribute to the applicability and effectiveness of
SDT based intervention principles. Two SDT-based PA interventions have been carried out in
the worksite context, and they both reported increases in PA in addition to positive
associations between adherence, autonomous motivation for PA, and increases in
cardiorespiratory fitness (Thøgersen-Ntoumani, Loughren, Duda, Fox, & Kinnafick, 2010;
Thøgersen-Ntoumani, Ntoumanis, Shepherd, Wagenmakers, & Shaw, 2016). Both studies
incorporated university administrative personnel. This study is the first to include a
sample of employees working with manual labor. In the present study, we applied latent
class growth analysis (LCGA) in order to explore if there were meaningful subpopulations
related to PA behavior over a period of one year. Latent growth modeling techniques, such
as LCGA, are person-centered methods suited for the estimation of between-person
differences in within-person change, often referred to as trajectories (Bollen & Curran,
2006). These techniques offer the possibility to “model unobserved heterogeneity in a
population by identifying different latent classes of individuals based on their observed
response pattern” (Clark & Muthén, 2009, p. 3). Latent growth modeling has become
increasingly popular because it is highly flexible and able to incorporate complexity such
as partially missing data, nonlinear change, unequal time-points, and heterogeneous growth
processes (Curran, Obeidat, & Losardo, 2010). Studies using LCGA related to PA are growing
in numbers. A large cohort study explored the long-term patterns of PA involvement over a
period of 22 year (Barnett, Gauvin, Craig, & Katzmarzyk, 2008). The analyses identified
four distinct patterns (“inactive”, “increasers”, “active”, and “decreasers”). The results
indicated that people with lower income levels and educational levels were less likely to
follow the “active” trajectory and more likely to follow the “decreasing” trajectory. A
recent study applied person-centered analysis to the PA levels of senior citizens resident
in assisted living facilities (Park et al., 2018). Three distinct profiles were found in
relation to autonomous motivation and perceived support for PA. The profile characterized
as “high in both” also reported significantly higher levels of PA and more favorable
impressions of exercise facilities in their physical neighborhood. The study indicates
that person-centered approaches are suitable for detecting and analyzing differences in PA
and their relationship to SDT based constructs, such as motivational regulations. Several
studies have explored the associations between individual motivational profiles and PA
among adult exercisers and athletes applying a more traditional person-centered approach;
cluster analysis (e.g., Gillet, Vallerand, & Paty, 2013; Guérin & Fortier, 2012; Matsumoto
& Takenaka, 2004). The studies based their clustering on motivational regulation, and all
studies reported between two and five-cluster solutions related to PA (Friederichs,
Bolman, Oenema, & Lechner, 2015). Friederichs et al. (2015) carried out a study on adults
who did not comply with the PA recommendations, applying cluster analysis and one-way
ANOVA to assess differences between clusters with regard to PA. Three clusters were found:
(1) “autonomous motivation” (high on autonomous and low on controlled forms of
motivational regulation), (2) “controlled motivation” (high on controlled and moderate on
autonomous forms of motivational regulation), and (3) “low motivation” (moderate on
controlled and low on autonomous forms of motivational regulation). Cluster (1) reported
the highest levers of PA, and cluster (3) the lowest. The results indicate that low levels
of autonomous motivation is more predictive of inactivity than high levels of controlled
motivation. Moreover, the motivational profiles reported were in fact similar to those
found in other studies, both among non-exercisers (Guérin & Fortier, 2012) and regular
exercisers (Matsumoto & Takenaka, 2004). Cluster (1) accounted for 52.9% of the sample,
and the sample could possibly be biased by the fact that the participants were recruited
among individuals who had agreed to participate in a web-based PA intervention. The
present study applied PA levels as the basis for a person-centered approach and included
the perceived competence and motivational regulations for PA as distal outcome variables.
We used a rather modern approach, the BCH method, to assess how the distal outcome
variables related to underlying patterns of PA. This is a tree-step approach recommended
by Asparouhov and Muthén (2014) because it avoids the undesirable shift in the latent
class variables caused by the direct inclusion of the distal outcome variable in the
analyses. Moreover, the above-mentioned studies applied cross-sectional data, whereas the
present study explored if there were latent classes explaining different patterns of PA
change during the course of an intervention.

<hs>  Study aim and research questions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First, we aimed to explore whether there were latent classes or trajectories in the sample
related to PA over a period of one year (prior to, during, and after a worksite PA
promotion intervention). Second, we aimed to investigate whether the intervention was able
to recruit employees with different levels of PA, particularly those with low levels.
Moreover, we examined whether the possible changes during the study period were clinically
relevant according to the recommendations of the Norwegian health authorities. Third, we
aimed to assess whether demographic characteristics of the participants could predict
differences in PA patterns. Fourth, we aimed to explore whether different patterns of PA
were associated with the participants' perceived competence and motivational regulation
for PA at baseline and follow-up. Regarding the fourth aim, the following hypotheses were
tested: Employees reporting higher levels of PA were expected to have higher levels of
perceived competence for PA compared to those employees reporting lower levels of PA.
Employees reporting higher levels of PA were expected to have higher levels of autonomous
motivation for PA (intrinsic and identified regulation) compared to those employees
reporting lower levels of PA. Employees reporting higher levels of PA were expected to
have lower levels of controlled motivation (introjected and extrinsic regulation) for PA
compared to employees reporting lower levels of PA. Employees reporting higher levels of
PA were expected to have lower levels of amotivation for PA compared to employees
reporting lower levels of PA.

<hs>  Participants and procedures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The study sample consisted of employees participating in a worksite health promotion
program designed to support them in increase their PA. They were employed in the logistics
sector working as drivers, mail carriers, and terminal workers. The study sample consisted
of predominantly male participants (76.2%). The participants were between 19 and 68 years,
and mean age was 42.5 years (SD = 11.65). Education levels were relatively low, and only
14.3% had a college degree. Participants were recruited during team-based information
meetings at six worksites. A total of N = 320 were defined as eligible (working more than
20%), and n = 202 (68%) agreed to participate (written informed consent). Participants
were assessed at three time-points; at baseline, post-test (5 months), and at follow-up
(12 months). Questionnaires were applied to measure regular PA in addition to the
motivational and demographic variables at all three time-points. The baseline and post-
test assessments were in the form of health screenings that assessed their
cardiorespiratory fitness, biomedical health markers (e.g., blood pressure, waist
circumference, and cholesterol levels), and their lifestyle. A health practitioner
presented them with the results (health status and risk factors), recommended lifestyle
changes, and in some cases advised them to consult their physician for further testing and
medical treatment. They received an individual, written report of their health profile.
After baseline assessments in January, participants were randomized by means of six
clusters (worksites) into an intervention condition (n = 113, 56%) and a control condition
(n = 89, 44%). The former received a group-based intervention consisting of six sessions
(two workshops and four exercise support-group meetings) and a booklet. The sessions were
dialogue-based, and PA was expected to be self-organized, primarily during leisure time
due to shift work and a lack of onsite exercise facilities. The design of the intervention
elements were based on a model that combined the tenets of SDT with techniques from MI,
which had previously been applied in PA intervention studies (Fortier et al., 2012). The
workshops were facilitated by two health and exercise advisors (physiotherapists) who were
trained to provide the workshops in a manner that supported the basic psychological needs
according to study protocol. Pre-post intervention effects related to cardiorespiratory
fitness, PA, cholesterol, blood pressure, and waist circumference have previously been
published together with statistical power calculations and detailed intervention protocol
descriptions (Anonymized). Participants in the control condition were offered a delayed
group-based intervention eight months after baseline. The delayed intervention consisted
of standard group-based sessions offered by the worksite health promotion program. Both
conditions were presented with a follow-up assessment 12 months after baseline, and a
total of n = 114 (55%) agreed to participate, of these n = 62 (55%) were from the
intervention condition and n = 52 (45%) were from the control (delayed intervention)
condition. A total of n = 195 participants completed the assessments at baseline, n = 155
completed at post-test, n = 114 completed at follow-up, and n = 101 (50%) completed all
three assessments. The study was approved by the Data Protection Official for Research in
(Anonymized).

        <hss>Educational level</hss>

        Education level was assessed with a one-item questionnaire applying the following
        scale: (1) primary and secondary school (10 years), (2) high school (13 years),
        (3) college/university degree (1–4 years), and (4) college/university degree (more
        than 4 years).

        <hss>Physical activity</hss>

        PA was measured with the three-item questionnaire International Physical Activity
        Index (IPAI), which was previously applied and validated on a large sample in (the
        HUNT study; Kurtze, Rangul, Hustvedt, & Flanders, 2008). The questionnaire
        assesses the frequency (number of sessions per week), the duration (the length of
        the PA sessions in minutes), and the intensity (the amount of energy expended
        during the sessions). Frequency was assessed with the item: “How frequently do you
        exercise?” using the following scale: 0 (Never), 1 (Less than once a week), 2
        (Once a week), 3 (2–3 times per week), and 4 (Almost every day). Intensity was
        assessed with the item: “How hard do you push yourself?” using the following
        scale: 0 (I do not exercise), 1 (I take it easy without breaking into a sweat or
        losing my breath), 2 (I push myself so hard that I lose my breath and break into a
        sweat), and 3 (I push myself to near-exhaustion), Duration was measured with the
        item: “How long does each session last?” using the following scale: 0 (I do not
        exercise), 1 (Less than 15 min), 2 (16–30 min), 3 (30 min to 1 h), and 4 (More
        than 1 h). According to protocol, each item’s score was multiplied with a weighing
        factor listen in parenthesis: frequency 0 (0), 1 (0,5), 2 (1), 3 (2.5), and 4 (5),
        intensity 0 (0), 1 (1), 2 (2), and 3 (3), and duration 0 (0.1), 1 (0.38), 2
        (0.75), and 3 (1). The weighted scores were then multiplied to calculate a summary
        index (Kurtze et al., 2008).

        <hss>Perceived competence for PA</hss>

        Participants rated their sense of perceived competence regarding PA by means of
        the Perceived Competence in Exercise Scale (PCES; Williams & Deci, 1996). The
        questionnaire consists of four items (e.g., “I feel confident in my ability to
        exercise on a regular basis”, Cronbach's αtime1 = 0.90; αtime3 = 0.94), and was
        answered on a seven-points Likert-scale ranging from 1 (strongly disagree) to 7
        (strongly agree).

        <hss>Motivational regulations for PA</hss>

        The quality of motivational regulations was measured with the Behavioral
        Regulation in Exercise Questionnaire (BREQ-2; Markland & Tobin, 2004). The
        questionnaire consists of five subscales: intrinsic regulation for PA by four
        items (e.g., “I exercise because it’s fun”, αtime1 = 0.86; αtime3 = 0.89);
        identified regulation for PA by four items (e.g., “I value the benefits of
        exercise”, αtime1 = 0.76; αtime3 = 0.73); introjected regulation for PA by three
        items (e.g., “I feel guilty when I don't exercise”, αtime1 = 0.64; αtime3 = 0.77);
        extrinsic regulation for PA four items (e.g., “I exercise because other people say
        I should”, αtime1 = 0.80; time3 = 0.83; and amotivation for PA by four items (“I
        don't see the point in exercising”, αtime1 = 0.78; αtime3 = 0.80). Integrated
        regulation was not included in the present study because BREQ-2 does not contain
        the subscale. Participants responded according to a 5-point Likert scale, ranging
        from 0 (not true for me) to 4 (very true for me).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Preliminary analyses were performed to identify possible patterns of missing data. Dropout
rates were n = 7 (3.5%) at baseline, n = 47 (23%) at post-test (5 months), and n = 88
(44%) at follow-up (12 months). Little's test of missing completely at random (MCAR)
indicated that the data were not missing completely at random (x2 = 1036, df = 917, p =
.004). One-way ANOVA, performed using IBM SPSS Statistics 21 (IBM Corp., Boston, Mass,
USA), tested whether there were significant differences regarding the study variables
between those participants who completed all three assessments and those who completed one
or two. No significant differences were found, and data was assumed to be missing at
random (MAR). We decided to include all N = 202 participants in the subsequent analyses
applying Mplus version 8 (Muthén & Muthén, 1998–2012), and the missing data were handled
by means of full information maximum likelihood estimation (FIML; Enders & Bandalos,
2001). Prior to the main analyses, the distal outcome variables (perceived competence and
motivational regulation for PA) were assessed to evaluate the scale factor structure and
measurement invariance (see Supplementary Material, Appendix A). LCGA were conducted on
data collected at all three time-points to explore the different trajectories. The
estimates of variance and covariance for the growth factor, PA, were fixed to zero
assuming that all growth trajectories within each class were identical. An exploratory
approach was chosen, and we did not hypothesize an expected number of classes. A stepwise
model comparison approach was conducted to compare a one-class model to models with
successively more classes (Nylund, Asparouhov, & Muthén, 2007). According to
recommendations, a combination of goodness of fit indices (GOF) should be considered
together with class sizes (>5%), theoretical justification, and interpretability in order
to decide on the appropriate model (Jung & Wickrama, 2008). These following GOF indices
were considered: the smallest Bayesian information criteria (BIC) and Aikaike's
information criterion (AIC) to assess model fit, followed by the highest possible entropy
to assess precision/quality of classification, and finally a significant p-value on the
bootstrap likelihood ratio test (BLRT) and the Lo-Mendell-Rubin adjusted likelihood ratio
test (L-M-R). The latter tests indicate whether the k-1 class model is rejected in favor
of the k class model (Jung & Wickrama, 2008; Nylund, Asparoutiov, & Muthén, 2007). We
examined the plot of each model to consider whether the differences between trajectories
were logical. Finally, we considered the sample size of the trajectories. Based on the
following procedure, we decided on the best model. Because PA was measured with a summary
index, a manifest variable was applied as a continuous indicator of a latent class
variable. We proceeded to consider the clinical relevance of the reported PA levels and
changes related to the recommendations of the Norwegian health authorities (PA ≥ 150 min
of MVPA per week). PA frequency scores were multiplied with duration scores (both
weighted) to obtain minutes per week. The amount of participants with ≥150 m/w of
moderate-to-vigorous intensity was calculated. Next, we tested whether there were
differences regarding the probability of class-membership in relation to the covariates in
the study. The automatic BCH approach was used for the continuous covariate (age and
educational levels), while for the categorical covariates (onset of intervention and
gender) the DCAT approach was used (Asparouhov & Muthén, 2014). Finally, we conducted a
series of analyses to explore whether there were differences between the trajectories
related to distal outcome variables (perceived competence and motivational regulations for
PA). We applied the three-step BCH approach in Mplus, which offers an omnibus test that
includes differences between the three classes on each distal outcome variable (Bolck,
Croon, & Hagenaars, 2004). According to a comparative analysis of different approaches,
the findings indicated that BCH was the most robust and flexible approach, yielding the
least biased estimates (Bakk & Vermunt, 2016). Effect sizes were calculated for the
differences between trajectories using Cohen's d for continuous variables and Cramer's v
for categorical variables.

<hs>  Latent trajectories in the sample</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The stepwise comparisons of the LCGA favored a solution with three classes (Table 1). The
entropy values of 0.96 indicated that both a three-class and a four-class model were able
to accurately place subjects into classes. Both the AIC and the BIC decreased consistently
for one-class to four-class models. However, the four-class model did not obtain a
significant p-value on the L-M-R test, favoring the three-class model. In addition, the
four-class model contained a class with a sample size of 4.2%, which is less than the
recommended level of 5% (Jung & Wickrama, 2008). The identified classes represented three
distinctly different and meaningful course trajectories (Figure 1): Trajectory 1
(prevalence: n = 16, 8% of the total sample) is labelled “Decrease from high”, and refers
to subjects with the highest levels of PA and with scores significantly decreasing over a
period of one year (intercept: M = 8.269, SE = 0.294, p < .001; slope: M = −1.433, SE =
0.579, p = .013). Trajectory 2 (prevalence: n = 55, 27.5% of the total sample) is labelled
“Stable moderate”, and refers to subjects with moderate levels of PA and no significant
change over a period of one year (intercept: M = 4.288, SE = 0.115, p < .001; slope: M =
0.090, SE = 0.227, p < .691). Trajectory 3 (prevalence: n = 128, 64.5% of the total
sample) is labelled “Increase from low”, and refers to subjects with the lowest levels of
PA and with scores significantly increasing over a period of one year (intercept: M =
0.700, SE = 0.070, p < .001; slope: M = 0.882, SE = 0.126, p < .001).

<hs>  Clinical relevance of physical activity levels and changes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

At baseline, 40% of the total sample reported PA levels consistent with or above the
recommendations of the Norwegian health authorities (PA ≥ 150 min of moderate-to-vigorous
physical activity per week). This percentage increased to 50.4% at post-test and to 55.7%
at follow-up (Table 2). The large majority of participants in trajectories (1) “Decrease
from high” and (2) “Stable moderate” remained within or close to the recommended levels of
PA during all three time-points. Participants in trajectory (3) “Increase from low”
reported low levels of regular PA at baseline, and 93.5% did not meet the PA levels
recommended. However, they reported considerably higher levels of PA during the study
period. At post-test, 31.3% met PA recommendations, increasing to 40.5% at follow-up.

<hs>  Controlling for the onset of the intervention</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We controlled for the onset of the intervention period (primary intervention group and
delayed-intervention control group). The differences were non-significant and Cramer's v
effect size was small between trajectories (1) “Decrease from high” and (2) “Stable
moderate” (X2 = 0.03, p = .859, ES = 0.19), between trajectories (1) “Decrease from high”
and (3) “Increase from low” (X 2 = 0.76, p = .385, ES = 0.19), and between trajectories 2
and 3 (X 2 = 2.97, p = .085, ES = 0.13).

<hs>  Sociodemographic covariates</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

We proceeded to test whether sociodemographic variables differed according to class
membership. There were no significant differences between the trajectories (1) “Decrease
from high” and (2) “Stable moderate” related to age, gender, or level of education.
However, Cramer's v effect sizes were moderate for gender and age, and small for
educational levels. There were more men in trajectory (2) “Stable moderate”, and they were
somewhat older. The same pattern was found for the difference between (1) “Decrease from
high” and (3) “Increase from low” (Table 3). The difference between (2) “Stable moderate”
and (3) “Increase from low” were non-significant and effect sizes were small.

<hs>  Distal outcome variables related to competence and motivational regulation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The trajectories demonstrated a linear pattern of PA across three time-points. Hence,
distal outcome variables were analyzed at baseline (T1) and at follow-up 12 months after
baseline (T3). Several sets of analyses, which applied the BCH method, were carried out in
order to assess whether the distal outcome variables (perceived competence for PA and
motivations for PA) differed across the three trajectories. At baseline, five of the six
omnibus tests were significant (p < .05), with the exception of extrinsic regulation for
PA (Table 4). Employees in trajectory (3) “Increase from low” were significantly lower in
perceived competence for PA compared to employees in trajectory (1) “Decrease from high”
and (2) “Stable moderate”, and Cohen's d effect sizes (ES) were very large (1.20–1.57).
Moreover, employees in trajectory (3) “Increase from low” reported significantly lower
levels of autonomous motivation compared to the other two, and the ES were large to very
large (intrinsic: 1.13–1.37; identified: 0.98–1.05; Sawilowsky, 2009). Regarding the more
controlled forms of motivation, the differences were not as consistent. Employees in
trajectory (3) “Increase from low” demonstrated significantly lower levels of introjected
motivation, and ES were moderate (0.46–0.51). However, there were no significant
differences between the trajectories related to extrinsic regulation. Employees in
trajectory (3) “Increase from low” were considerably higher on amotivation compared to the
two others, and ES were large (0.80–0.83). None of the distal outcome variables
demonstrated a significant difference between trajectory (1) “Decrease from high” and
trajectory (2) “Stable moderate”, and ES were small to very small (0.00–0.22). At follow-
up, the pattern of significant differences between trajectories related to autonomous
motivation for PA remained the same. Employees in trajectory (3) “Increase from low”
reported considerably higher levels of autonomous motivation, and ES were moderate
compared to baseline (intrinsic: 0.46–0.74; identified regulation: 0.65–0.71). The same
pattern was found for perceived competence for PA, but ES were still moderate to large
(0.49–0.87). Considering introjected regulation, the difference between trajectories (1)
“Decrease from high” and (3) “Increase from low” was no longer significant. All the
differences between trajectories that were related to extrinsic regulation were still non-
significant. At follow-up, employees in trajectory (3) “Increase from low” reported lower
levels of amotivation for PA compared to baseline. The difference between trajectories (1)
“Decrease from high” and (3) “Increase from low” was no longer significant, and ES were
small (0.00–0.35). Differences between employees in trajectories (1) “Decrease from high”
and (2) “Stable moderate” remained non-significant on all distal outcome variables, and ES
were very small to small (0.00–0.44).

<h>DISCUSSION</h>
----------

In the present study, a person-centered approach was able to distinguish between three
distinct and linear trajectories. The trajectories differed considerably in sample size,
and one trajectory accounted for 65.5% of the participants. Other studies with a person-
centered approach, such as Barnett et al. (2008), have found support for a four-trajectory
model with a higher degree of stability. The latter study was a 22-year cohort study
whereas the present study was an intervention study over a shorter period of time; just
one year. Despite the considerable increase in PA among participants in trajectory (3)
“Increase from low” across one year, they could possibly have returned to a stable
“inactive” state after the study period. The effect of PA interventions reduces with time,
and especially when the structural and social support are removed. We also explored
whether the program was able to recruit employees with different levels of PA,
particularly low levels. The findings indicate that the present intervention was able to
attract employees who initially did not comply with the PA recommendations (70%).
Moreover, they belonged to a population considered to be underrepresented in health
promotion interventions, particularly in the worksite context; male employees with low
educational levels and low occupational prestige (Marshall, 2004; Wong, Gilson, Van
Uffelen, & Brown, 2012). Moreover, the findings indicate that the program was able to
recruit a diverse sample, including a number of employees with moderate levels of PA, as
represented by (2) “Stable moderate”. However, we question whether the intervention
appealed to employees who were already highly active, as represented by (1) “Decrease from
high”. This group could possibly have been underrepresented in the present context of
eligible employees. However, this population of highly active employees was not the
primary target of the program. Employees in (3) “Increase from low” initially reported
considerably lower levels of PA, compared to the other employees. However, the mean value
of perceived competence for PA at baseline could be characterized as moderate. According
to Standage and Ryan (2012, p. 263) “feelings of competence are essential for any
intentional behavior, irrespective of whether the action is motivated by extrinsic,
introjected, identified, integrated, or intrinsic regulations”. The finding could indicate
that the present intervention was unable to attract employees who felt inexperienced,
incompetent, or unable to exercise on a regular basis. Employees in (3) “Increase from
low” reported what we would describe as low-to-moderate levels of autonomous motivation,
albeit significantly lower than the rest. These findings are in line with other SDT-based
PA promotion intervention studies in the context of health care, which mainly attracted
participants with elevated levels of autonomous motivation (Fortier et al., 2012). Third,
the study aimed to test whether the associations between perceived competence,
motivational regulation, and PA were in line with the tenets of SDT. Employees in
trajectory (3) “Increase form low” exhibited a motivational profile and development
comparable to exercise initiates previously found in a study comparing exercise initiates
to regular exercisers (Rodgers et al., 2010). Both samples reported moderate levels of
intrinsic and identified regulation at baseline. A review of worksite health-promotion
programs reported that positive effects were mainly found in samples of motivated
employees who volunteered to participate (Marshall, 2004). Employees in (1) “Decrease from
high” reported significantly lower levels of PA at follow-up compared to baseline. We find
it somewhat surprising that their levels of perceived competence and autonomous motivation
for PA remained moderate-to-high and consistent throughout the whole period of one year.
The results indicate that employees moderate-to-high on perceived competence and
autonomous motivation for PA seem less vulnerable to fluctuations in PA and remain self-
endorsed and confident that they are able to be physically active on a regular basis. This
is in line with the findings of Sweet et al. (2014). The participation rate (68%) was
considerably higher than mean values previously reported for worksite intervention
programs (33%; Robroek et al., 2009). This could indicate that employees felt obligated to
take part, possibly because the whole team was invited. If this was the case, we would
expect the participants to exhibit relatively high levels of controlled motivation and
amotivation for PA at baseline, particularly among employees in (3) “Increase from low”,
in line with the tenets of SDT. However, all three trajectories reported what we
considered to be low levels of amotivation and extrinsic regulation at baseline, although
(3) “Increase from low” did exhibit somewhat higher levels of extrinsic regulation
compared to the rest. Their initial level of introjected regulation was more apparent: the
participants reported low-to-moderate levels, particularly employees in trajectories (1)
“Decrease from high” and (2) “Stable moderate”. These findings indicate that participants
were sensitive to and partially recognized the importance of taking part in the program
and making lifestyle changes. Employees in (1) “Decrease from high” and (2) “Stable
moderate” reported moderate-to-high levels of autonomous motivation for PA, particularly
intrinsic regulation. This could possibly counteract their low-to-moderate levels of
introjected regulation, reflecting a wish to participate in the program for their own
reasons. We question whether the fact that they were not expected to participate in
collective PA sessions during the intervention could have made them more comfortable since
they may have felt less exposed to social comparison and loss of credibility from co-
workers (Rossing & Jones, 2015). Given their moderate levels of PA at follow-up, it is not
surprising that employees in the sample reported low levels of amotivation at all three
time-points. However, they reported considerably higher levels of controlled motivation at
follow-up compared to baseline, particularly extrinsic regulation. Employees in (2)
“Stable moderate” and (3) “Increase from low” demonstrated the same pattern with regard to
extrinsic regulation with an increase in mean values of around 1. Given their diverse
development in PA over a period of one year, the findings did not support hypothesis 3,
which was related specifically to controlled forms of motivation. Furthermore, the
findings are not in line with other PA intervention studies in the health care context,
which found non-significant changes in controlled forms of motivation (Rodgers et al.,
2010; Sweet et al., 2014). We question whether participating in the program could actually
have enhanced their controlled motivation for PA, even though their autonomous motivation
remained moderate-to-high. The health screening results and recommendations together with
the information, discussions and response they received during the intervention sessions
could possibly have increased their awareness of the opinions and expectations of
important others in their environment (e.g., family, co-workers, health practitioners, and
health and exercise advisors). Participating in the program is likely to make them more
sensitive to the fact that their employer invested time and money on the program in order
to obtain organizational benefits, such as reduced sickness absence and increased work
productivity. Although the intervention was designed to support the basic psychological
needs and thereby increase autonomous motivation, it appears that aspects of the context
were perceived as controlling. This is not surprising given the element of professionalism
and mutual dependency between employer and employee. We argue that this is a challenge
inherent in the worksite context, particularly at follow-up after the intervention period.
This must be taken into consideration when designing worksite health promotion programs.

<hs>  Limitations and future direction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The present study has methodological limitations. First, we completed statistical power
calculations prior to recruitment in order to specify the sample size required to detect a
between-groups effect size. We chose to include all participants in the LCGA, but separate
power analyses were not completed. Having a too small sample size increases the risk of
choosing an inadequate model with too few classes (Dziak, Lanza, & Tan, 2014). Despite of
acceptable model fit indices and distinct differences between the trajectories, the three-
class model could be subject to underextraction. Given the moderate sample size, we chose
to explore the relationship between PA trajectories and distal outcome variables
separately using manifest variables rather than latent (Andruff, Carraro, Thompson, &
Gaudreau, 2009). This approach reduces the complexity but also the strength of the
findings. Second, the dropout rates were considerable, particularly at follow-up, and data
were not missing completely at random. Information not included in the study, such as
general health condition or reasons given for not attending, may have provided a better
understanding of what caused employees to drop out and what characterized those who were
able or willing to participate at all three time-points. Third, in the present study, we
were not able to assess PA using objective methods (e.g., accelerometers). A large number
of studies have reported low-to-moderate agreement between self-reported and objectively
measured PA levels (Prince, Adamo, Hamel, Hardt, Gober, & Tremblay, 2008). Both sources of
PA information have the potential for under and over-estimation, and a combination is
recommended (Steene-Johannessen et al., 2016). For instance, self-reported measures are
biased by subjective interpretation and social desirability, whereas accelerometers do not
capture all activities precisely depending on the placement on the body. Hence, the
results of the present study should be interpreted cautiously. Finally, the present study
also has limitations related to study design. We question whether the recruitment process
could have been altered to better attend to the needs of employees with low levels of
perceived competence and autonomous motivation for PA. For example, the information
meetings, during which participants were recruited, could have been more dialogue-based,
inviting participants to express their doubts and ambivalence more explicitly.
Participants and co-workers may perceive such dialogue as being supportive of the basic
psychological needs, and it may encourage them to reflect on their motivation toward PA
before a decision to participate is made (Markland et al., 2005).

<h>CONCLUSIONS</h>
-----------

To our knowledge, this is the first study to apply LCGA to the investigations of the
associations between longitudinal developmental trajectories of PA and SDT-based concepts
of motivational regulation and perceived competence for PA using data from a PA
intervention in the worksite context. The findings indicate that LCGA is a useful approach
for detecting longitudinal trajectories in heterogeneous samples of both exercise
initiates and regular exercisers. The present findings emphasize the effectiveness of the
SDT-based intervention design and the generalizability of the results to non-treatment
populations.

<h>DECLARATION OF INTEREST</h>
-----------------------

We would like to inform the Editor of the fact that the following PhD research project was
financed by the Industrial Ph.D. scheme, administered by The Research Council of Norway:
The Industrial Ph.D. scheme for funding for industry-oriented doctoral research
fellowships was established to facilitate the recruitment of researchers to Norwegian
industry. Funding for industry-oriented doctoral research fellowships will help many
companies to step up their research efforts. The Industrial Ph.D. scheme does not
represent a new type of doctoral degree, but is designed to support long-term, industry-
oriented research that has the same level of scientific merit as the general doctoral
degree education. The Industrial Ph.D. scheme is designed to enhance interaction between
companies and research institutions, increase research activity in industry, and equip
newly-educated researchers with knowledge of relevance to their company. Under the
Industrial Ph.D. scheme, companies receive an annual grant equal to maximum 50 per cent of
the applicable rate for doctoral research fellowships for a three-year period. The
candidate must be an employee of the company and be formally admitted to an ordinary
doctoral degree programme. The present PhD project was a cooperation between the Post
Norway and The Norwegian School of Sport Sciences (NSSS) as the degree-conferring
institution, and the candidate followed the PhD program at NSSS. For more information,
please visit the web-page: https://www.forskningsradet.no/prognett-
naeringsphd/About_the_PhD_scheme/1253952592832.


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  [55] Cecilie Thøgersen-Ntoumani, Nikos Ntoumanis. The role of self-determined motivation in the understanding of exercise-related behaviours, cognitions and physical self-evaluations. doi:10.1080/02640410500131670
  [56] Cecilie Thøgersen-Ntoumani, Sam O. Shepherd, Nikos Ntoumanis, Anton J.M. Wagenmakers, Christopher S. Shaw. Intrinsic Motivation in Two Exercise Interventions: Associations With Fitness and Body Composition. doi:10.1037/hea0000260
  [57] Quyen G. To, Ted T.L. Chen, Costan G. Magnussen, Kien G. To. Workplace physical activity interventions: A systematic review. doi:10.4278/ajhp.120425-LIT-222
  [58] Geoffrey C. Williams, Edward L. Deci. Internalization of Biopsychosocial Values by Medical Students: A Test of Self-Determination Theory. doi:10.1037/0022-3514.70.4.767
  [59] Geoffrey C. Williams, Marylène Gagné, Richard M. Ryan, Edward L. Deci. Facilitating autonomous motivation for smoking cessation. doi:10.1037/0278-6133.21.1.40
  [60] Jason Y.L. Wong, Nicholas D. Gilson, Jannique G.Z. van Uffelen, Wendy J. Brown. The Effects of Workplace Physical Activity Interventions in Men: A Systematic Review. doi:10.1177/1557988312436575
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  [63] Carol Cancelliere, J. David Cassidy, Carlo Ammendolia, Pierre Côté. Are workplace health promotion programs effective at improving presenteeism in workers? A systematic review and best evidence synthesis of the literature. doi:10.1186/1471-2458-11-395
<ART>Looking Down the Barrel of a Gun: What Do We Know About the Weapon Focus Effect?
================================================================================

Authors: Jonathan M. Fawcett, Kristine A. Peace, Andrea Greve
DOI: 10.1016/j.jarmac.2016.07.005
Year: 2016  |  Pages: 257-263
ASJC codes: 3202, 3203, 3205
Keywords: Arousal, Eyewitness memory, Novelty, Threat, Weapon focus

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Eyewitness memory for the perpetrator or circumstances of a crime is generally worse for scenarios involving weapons compared to those involving non-weapon objects—a pattern known for decades as the weapon focus effect. But despite ample support from laboratory experiments and recognition by experts, testimony concerning weapon focus is rarely admissible in court. The present article summarizes a selection of key findings within the weapon focus literature and considers whether the effect warrants consideration by the criminal justice system at this time. We conclude that weapon focus is sufficiently robust and uncontroversial to guide practice so long as consideration is given to the circumstances surrounding the criminal event with a particular emphasis on witness expectation.

--------------------------------------------------------------------------------


<h>HOW DO WEAPONS INFLUENCE EYEWITNESS MEMORY?</h>
-------------------------------------------

Substantial laboratory evidence now exists that the presence of an unexpected weapon
reduces the accuracy of subsequent suspect identification attempts or witness accounts of
a crime (for reviews, Fawcett, Russell, Peace, & Christie, 2013; Kocab & Sporer, 2016;
Pickel, 2015; Steblay, 1992). This finding is depicted schematically in Figure 1, but
should not be applied indiscriminately. The magnitude (or even presence) of the weapon
focus effect has been found to vary according to the characteristics of the eyewitness,
the scenario in which the weapon is embedded (e.g., the perpetrator, surroundings), and
the procedure through which memory is tested. As a result, each of these factors (witness,
scenario, testing procedure) must be considered prior to evaluating the risk of weapon
focus for any given situation. Each of these factors is discussed in turn.

<hs>  The Eyewitness</hs>
  ~~~~~~~~~~~~~~

With respect to the eyewitness, the roles of expectation and perceived threat deserve
special emphasis given that the weapon focus effect has been attributed historically to
the weapon drawing attention away from other details by virtue of its unexpected or
threatening nature (Loftus et al., 1987). Concerning the former, a great deal of evidence
has emerged over the past decade showing that witness expectation mediates the magnitude
of the effect (for a quantitative model, see Erickson, Lampinen, & Leding, 2014). For
example, weapon focus is diminished when the weapon is anticipated on the basis of the
environment (e.g., a gun in a shooting gallery; see Figure 1) or due to prior knowledge of
the individual holding the weapon (e.g., a gun held by a police officer; Pickel, 1999).
Conversely, the effect is larger when the weapon violates cultural stereotypes (e.g., a
woman holding a gun; Pickel, 2009, see also Sneyd, 2016). In contrast to the link between
witness expectation and weapon focus, the contribution of perceived threat is less clear.
Attentional narrowing due to threat was thought to play a central role by early theorists
(e.g., Maass & Kohnken, 1989) and is a common feature of anecdotal reports provided by
victims of weapon crime (as in our example; see also Loftus, 1979). Although meta-analyses
have shown greater weapon focus in situations judged to be threatening or arousing
(Fawcett et al., 2013; Steblay, 1992) or involving criminal compared to non-criminal
events (Kocab & Sporer, 2016), laboratory efforts to quantify their contributions have
often failed to reveal a reliable relationship (e.g., Erickson et al., 2014; Mitchell,
Livosky, & Mather, 1998; Pickel, 1998; although see Peters, 1988). Importantly, weapon
focus also emerges in austere scenes where threat is unlikely (e.g., Kramer, Buckhout, &
Eugenio, 1990), challenging the view that threat is a necessary condition for weapon focus
to occur. Convincing evidence for the role of expectation over threat also comes from
studies showing that unexpected non-weapon objects elicit an effect analogous to weapon
focus (e.g., someone brandishing a stalk of celery; Mitchell et al., 1998). In this
respect, Pickel (1998) manipulated in her experiment whether an object carried by the
perpetrator was perceived as threatening and whether it was expected given the context in
which it appeared. Her study revealed worse memory for the perpetrator when an unexpected
weapon (i.e., gun) or unexpected non-weapon object was held (i.e., whole raw chicken or
chef doll in a barber shop) but no overall effect of threat and no interaction between
threat and expectation (see also Figure 1).2 Thus, although it is possible that laboratory
studies fail to elicit threat similar in nature or magnitude to that experienced during
actual criminal events (although see Maass & Kohnken, 1989; Peters, 1988), there is little
empirical evidence that threat or arousal are a key factor—at least under typical
laboratory conditions. We will return to this idea again later, when we consider whether
weapon focus research should be used to guide practice.

<hs>  The Scenario</hs>
  ~~~~~~~~~~~~

Both the scenario in which the weapon is presented and the individual holding the weapon
can moderate the weapon focus effect independently of witness expectation. For example,
factors diverting attention away from the weapon, such as a perpetrator with some unusual
feature, will diminish the effect (Carlson & Carlson, 2012, 2014). The duration of
exposure to a weapon is thought to be critical, typically eliciting a smaller effect in
experiments involving either brief (i.e., <10 s) or extended (i.e., >60 s) exposure to the
weapon (Fawcett et al., 2013; Steblay, 1992). However, memory for items or individuals
experienced prior or subsequent to the encounter of a weapon must be considered with care,
as exposure to the weapon may not influence memory for those details to the same extent
(Erickson et al., 2014). For example, viewing an old acquaintance holding a weapon could
result in relatively poor memory for novel features of the scene, but would be unlikely to
affect memory for features that were already highly familiar. The same would apply to a
stranger who draws a weapon, but then proceeds to interact with the witness for an
extended period of time, either with or without the weapon.

<hs>  The Testing Procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Less is known about how the testing procedure interacts with weapon focus. Evidence now
suggests an extended retention interval (e.g., testing after a delay of 24+ hours)
diminishes the effect (Fawcett et al., 2013). However, given that retrieval accuracy is
low in the weapon relative to the non-weapon condition to begin with, the decrease in
weapon focus across longer delays is likely an artifact reflecting declining memory in the
non-weapon condition rather than better memory in the weapon condition. Testing procedures
in which participants are required to recall details relevant to the event have shown
larger weapon focus effects relative to selecting a suspect from a police line-up (Fawcett
et al., 2013; Kocab & Sporer, 2016; Steblay, 1992). That said, recent research indicates
that the influence of weapon focus on suspect lineups may be more pronounced than
originally considered. For example, witnesses appear to have difficulty discriminating a
perpetrator from innocent foils in line-ups, and are more likely to commit false
identifications when a weapon was involved in a mock crime (Carlson & Carlson, 2012;
Erickson et al., 2014; but see, Kocab & Sporer, 2016). This finding is troubling and
warrants careful consideration, particularly in light of the evidence that individuals
exposed to weapons are also more susceptible to false information, introduced for instance
through leading questions or exposure to police suspects (Saunders, 2009). Luckily,
witnesses may be sensitive to the fact that exposure to a weapon reduces memory accuracy,
shown by a greater correspondence between suspect identification accuracy in a mock police
line-up and reported confidence concerning those identifications (Carlson, Dias,
Weatherford, & Carlson, 2016).

<h>SHOULD WEAPON FOCUS RESEARCH BE USED TO GUIDE PRACTICE?</h>
-------------------------------------------------------

Having reviewed the key findings within the literature, it is our view that the weapon
focus effect is sufficiently robust to warrant consideration by the judicial system so
long as the circumstances surrounding the crime are considered in tandem. Although some
applications are certainly in need of further attention and development (see Table 1 for
some examples), we are compelled in this evaluation by three converging sources.3 First,
laboratory experiments have consistently demonstrated impaired memory for scenarios
involving unexpected weapons. This provides a solid empirical basis for the weapon focus
effect and its boundary conditions. Second, the weapon focus effect has been observed in a
variety of simulated events (e.g., Maass & Kohnken, 1989; Peters, 1988; Pickel, Ross, &
Truelove, 2006) and virtual scenarios (e.g., Kim, Park, & Lee, 2014), providing varying
degrees of experimental control and ecological validity. Hence, weapon focus is observable
under realistic conditions emulating natural behaviour while retaining experimental
control. Finally, weapon focus is a common feature of witness accounts following exposure
to a weapon (for discussion see, Loftus, 1979), suggesting that it also emerges under
realistic conditions. Therefore, it is our view that the question should not be whether
weapon focus influences eyewitness memory, but under what circumstances and to what
degree. The circumstances under which weapon focus is most likely to occur vary in their
empirical support. The most robust factor highlighted here is that of witness expectation,
wherein weapon focus is most profound when the weapon is unexpected. It is therefore
important to adopt a multifaceted approach to understanding the mindset of the witness
when the weapon was encountered. Were there environmental- or perpetrator-specific cues
that the weapon might appear? Was the perpetrator considered likely to have a weapon? Many
of these considerations may be idiosyncratic and several individuals could witness the
same scenario but experience weapon focus to varying degrees (if at all) dependent upon
their expectations, background, and understanding of the event. Given that expectations
unfold over time, it is also important to consider cues that build to the appearance of a
weapon. For example, a store clerk who observes a customer acting suspiciously might
expect a weapon to be present before a weapon is actually drawn. Although this scenario
has not been investigated as such, the available evidence suggests that forewarning could
mitigate the effect (e.g., Pickel, 2009; Pickel et al., 2006). In summary, each witness
must be considered individually and in context to determine whether weapon focus is a
probable concern. At least two major factors—the effects of test delay and exposure
duration—have been identified largely through meta-analysis rather than primary
investigations (although, see Kramer et al., 1990). These findings emerge from comparisons
across studies and hence should be viewed as promising but not yet fully established,
pending further investigation. Their discussion in court is consequently advocated only
with suitable caution. The finding that weapon focus is larger for witness accounts than
suspect identification technically falls within the same category, though this distinction
is far more consistent, as demonstrated by difficulties obtaining the effect for suspect
identification (for discussion, see Kocab & Sporer, 2016). The precise cause of this
difference across measures is unclear. One possibility is that weapon focus simply has a
larger effect on measures of recall (on which most witness accounts are based) than
measures of recognition (which is the basis of suspect identification). Others have argued
that the difference emerges because weapon focus has a larger impact on suspect absent
line-ups whereas most investigations of suspect identification use only suspect present
line-ups (Carlson & Carlson, 2012; although, see Kocab & Sporer, 2016). The etiology of
this difference remains to be discovered, but the key fact is that current evidence
supports a moderate effect of weapon presence on measures of feature accuracy and only a
small effect of weapon presence on measures of suspect identification (Fawcett et al.,
2013; Kocab & Sporer, 2016; Steblay, 1992). Thus, whereas weapon focus should still be
considered in the context of a suspect line-up, the effect seems to have a greater impact
on a witness's description of the perpetrator. Similarly, laboratory evidence for the role
of threat has been sparse and, at present, can only be viewed to moderate (rather than
elicit) the weapon focus effect. However, as touched upon earlier, we are unable to rule
out the possibility that threat elicited in the laboratory fails to encompass the range of
emotions experienced during actual criminal events. Different emotions, including threat,
are known to cause attentional narrowing predominantly in scenarios involving an attention
magnet (e.g., a dead body; Laney, Campbell, Heuer, & Reisberg, 2004) or an active personal
goal capable of capturing attention (e.g., escape; Levine & Edelstein, 2009). Enhancing
the salience of such magnets and personal goals using an immersive virtual reality
simulation of a weapon crime has revealed complementary—but additive—effects of threat and
expectation (Kim et al., 2014). This preliminary finding suggests that weapon focus could
involve independent effects arising from threat and expectation that collectively
influence eyewitness memory. That said, the perception of threat by witnesses in real
criminal events could differ from the physiological threat or arousal experienced by those
witnesses. Such differences may help to reconcile the discrepancy between frequent witness
reports of feeling threatened, which is in contrast to the yet limited laboratory support
for threat as a causal factor in weapon focus. This is a key area in need of greater
development using further simulated events (e.g., Maass & Kohnken, 1989; Peters, 1988;
Pickel et al., 2006) and applied techniques (e.g., Hulse & Memon, 2006; Kim et al., 2014)
capable of balancing experimental control with the immersion necessary to emulate the
threat experienced during a crime. Although considering the boundary conditions summarized
above provides useful guidance, we caution that crimes rarely conform to these parameters.
Weapon focus is presently expected to be largest for a brief crime involving an
unexpected, threatening weapon that is committed by a previously unknown perpetrator with
no pre- or post-weapon exposure and for which the witness's statement is taken within 24 h
of the event. Seldom do criminal events fit this description perfectly, which may explain
why most archival or field studies of actual crimes have reported little or no evidence of
the weapon focus effect (e.g., Behrman & Davey, 2001; Valentine, Pickering, & Darling,
2003; but, see Tollestrup, Turtle, & Yuille, 1994). A recent meta-analysis has
demonstrated an aggregate weapon focus effect when these studies are combined, but the
magnitude of that effect is smaller compared to laboratory studies. Interestingly,
laboratory studies that closely match typical criminal events (i.e., long exposure
duration, long retention interval, high perceived threat, unexpected weapon) also show a
reduced weapon focus effect comparable to the aggregate effect for archival or field
studies. Difficulties observing a consistent weapon focus effect within archival or field
studies therefore may reflect the influence of moderators typical of real-world crime
(Fawcett et al., 2013; although, see Footnote 3). Overall, we regard the weapon focus
effect to be sufficiently robust to be considered in court, but we emphasize that each
witness account must be scrutinized to determine whether weapon focus is relevant, rather
than presuming it to be applicable simply because a weapon was present.

<h>HOW DOES THE CRIMINAL JUSTICE SYSTEM VIEW WEAPON FOCUS?</h>
-------------------------------------------------------

Finally, in light of the evidence discussed thus far it is important to consider how the
criminal justice system presently evaluates weapon focus. While criminal justice
professionals acknowledge that weapon focus may negatively impact memory, they view their
everyday practice as divergent from research outcomes. For example, police officers often
report that weapon focus is inconsistent across cases, and memory deficits can be
circumvented by enhanced interviewing skills. Further, weapon-related offences such as
robbery (i.e., the “typical” weapon focus scenario) are less common than a weapon being
present in domestic violence scenarios (often charged as a level 2 or aggravated assault
in Canada; Statistics Canada, 2016; The Daily, 2015). The evidence summarized above should
enlighten the perceived inconsistencies in this effect: whereas weapon focus may occur for
a typical robbery (so long as it adheres to the specified boundaries), domestic violence
cases might instead involve a variation of this effect with preserved memory for the
perpetrator. In fact, in some instances police officers have described apparently greater
weapon focus (and better recall of weapon-related details) without impaired perpetrator
identification, owing to the victim's familiarity with the perpetrator (Edmonton Police
Service, personal communication, 2016). Overall, from a policing standpoint, weapon focus
is commonly acknowledged to exist, but is an issue for the courts to address. While it is
clear that many judges realize the potential impact of a weapon on eyewitness memory (see
R. v. Turner, 2012), few courts have recognized weapon focus as warranting expert
testimony (e.g., Jordan v. State, 1996; United States v. Smith, 1984) despite a wealth of
research establishing this effect (e.g., Fawcett et al., 2013; Kocab & Sporer, 2016). Even
in recent cases, the judicial response has been twofold: (1) denial of expert testimony
concerning weapon focus (e.g., Benton, McDonnell, Ross, Thomas, & Bradshaw, 2007), and (2)
non-specific instructions to juries regarding eyewitness phenomena. Further adding to the
problem is the prevalent view that “…the problems of identification are clearly within the
general knowledge and comprehension of judges and properly instructed juries” (R. v.
Fengstad, 1994, Supra. 74).4 However, counter to this widespread belief, the weapon focus
effect is often associated with the lowest scores on surveys of lay knowledge concerning
eyewitness memory for both judges and jurors, suggesting that the effect is not well
understood by either population (Magnussen et al., 2008; Magnussen, Melinder, Stridbeck, &
Raja, 2009). Given that weapon focus is not considered one of the five generally accepted
eyewitness principles with consensus in the scientific literature (see Commonwealth v.
Gomes, 2015), we would endorse the two-pronged solution proposed by Wise, Dauphinais, and
Safer (2007): (a) permit expert testimony when case evidence relies heavily on eyewitness
reports, and, (b) educate the principal participants in the criminal justice system.
Although expert testimony on weapon focus continues to be excluded, there has been some
progress on the educational front. In the Report and Recommendations of the Supreme
Judicial Court Study on Eyewitness Evidence (2013), it was recommended that model jury
instructions should be adjusted to incorporate acknowledgement of the weapon focus
effect.5 Further, the Canadian Judicial Council (2012) recommended that judges use a
series of instructions to guide jurors on how to assess witness testimony, including
whether anything may have interfered with or distracted the witness from observing the
details of the event and whether anything unusual happened that would enhance memory.
While these recommendations are a step in the right direction, there remains no consensus
concerning the evaluation of weapon focus in court.

<h>SUMMARY AND CONCLUSIONS</h>
-----------------------

The present article evaluated the merit of the weapon focus effect with respect to
applications within the criminal justice system. We have summarized a selection of key
findings within the literature and identified areas of further development. It is our
conclusion that converging evidence from laboratory studies, simulated events, and actual
witness accounts support the relevance of expert testimony concerning weapon focus in
cases involving a weapon. In fact, such testimony could prove vital in addressing
misconceptions concerning the effect amongst both judges and jurors (e.g., Magnussen et
al., 2008). However, we caution that the particulars of the crime are important, and that
they must reside within the boundaries for which weapon focus is thought to occur in order
to promote accurate translation of empirical research to courtroom testimony.

<h>AUTHOR CONTRIBUTIONS</h>
--------------------

All authors contributed to the writing of this manuscript.


<h>REFERENCES</h>
----------

  [1] Tanja Rapus Benton, Stephanie Mc Donnell, David F. Ross, Honorable W.Neil Thomas, Emily Bradshaw. Has eyewitness testimony research penetrated the American legal system? a synthesis of case history, juror knowledge, and expert testimony. doi:10.4324/9780203936368-26
  [6] Curt A. Carlson, Maria A. Carlson. An evaluation of lineup presentation, weapon presence, and a distinctive feature using ROC analysis. doi:10.1016/j.jarmac.2014.03.004
  [8] Sarah L. Desmarais, J. Don Read. After 30 years, what do we know about what jurors know? A meta-analytic review of lay knowledge regarding eyewitness factors. doi:10.1007/s10979-010-9232-6
  [9] William Blake Erickson, James Michael Lampinen, Juliana K. Leding. The weapon focus effect in target-present and target-absent line-ups: The roles of threat, novelty, and timing. doi:10.1002/acp.3005
  [10] Jonathan M. Fawcett, Emily J. Russell, Kristine A. Peace, John Christie. Of guns and geese: a meta-analytic review of the 'weapon focus' literature. doi:10.1080/1068316X.2011.599325
  [11] Lynn M. Hulse, Amina Memon. Fatal impact? The effects of emotional arousal and weapon presence on police officers' memories for a simulated crime. doi:10.1348/135532505X58062
  [13] Saul M. Kassin, V. Anne Tubb, Harmon M. Hosch, Amina Memon. On the "general acceptance" of eyewitness testimony research: A new survey of the experts. doi:10.1037/0003-066X.56.5.405
  [14] Kiho Kim, Kevin Kiwon Park, Jang Han Lee. The influence of arousal and expectation on eyewitness memory in a virtual environment. doi:10.1089/cyber.2013.0638
  [17] Elizabeth F. Loftus, Geoffrey R. Loftus, Jane Messo. Some facts about "weapon focus". doi:10.1007/BF01044839
  [18] Anne Maass, Günther Köhnken. Eyewitness identification: Simulating the "Weapon effect". doi:10.1007/BF01056411
  [19] Svein Magnussen, Annika Melinder, Ulf Stridbeck, Abid Q. Raja. Beliefs about factors affecting the reliability of eyewitness testimony: A comparison of judges, jurors and the general public. doi:10.1002/acp.1550
  [20] Svein Magnussen, Richard A. Wise, Abid Q. Raja, Martin A. Safer, Nell Pawlenko, Ulf Stridbeck. What judges know about eyewitness testimony: A comparison of Norwegian and US judges. doi:10.1080/10683160701580099
  [21] Karen J. Mitchell, Marilyn Livosky, Mara Mather. The weapon focus effect revisited: The role of novelty. doi:10.1111/j.2044-8333.1998.tb00367.x
  [23] Kerri L. Pickel. Unusualness and Threat as Possible Causes of Weapon Focus. doi:10.1080/741942361
  [24] Kerri L. Pickel. The influence of context on the 'weapon focus' effect. doi:10.1023/A:1022356431375
  [25] Kerri L. Pickel. The weapon focus effect on memory for female versus male perpetrators. doi:10.1080/09658210903029412
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<ART>Looking for ideas: Eye behavior during goal-directed internally focused cognition
================================================================================

Authors: Sonja Walcher, Christof Körner, Mathias Benedek
DOI: 10.1016/j.concog.2017.06.009
Year: 2017  |  Pages: 165-175
ASJC codes: 3204, 3205
Keywords: Eye movements, Idea generation, Internally directed cognition, Perceptual decoupling, Self-generated thought

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Humans have a highly developed visual system, yet we spend a high proportion of our time awake ignoring the visual world and attending to our own thoughts. The present study examined eye movement characteristics of goal-directed internally focused cognition. Deliberate internally focused cognition was induced by an idea generation task. A letter-by-letter reading task served as external task. Idea generation (vs. reading) was associated with more and longer blinks and fewer microsaccades indicating an attenuation of visual input. Idea generation was further associated with more and shorter fixations, more saccades and saccades with higher amplitudes as well as heightened stimulus-independent variation of eye vergence. The latter results suggest a coupling of eye behavior to internally generated information and associated cognitive processes, i.e. searching for ideas. Our results support eye behavior patterns as indicators of goal-directed internally focused cognition through mechanisms of attenuation of visual input and coupling of eye behavior to internally generated information.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The peculiar gaze of someone deeply absorbed in thought or “staring into space” suggests
that eye behavior during internally focused attention might be different from states of
externally focused attention. In fact, recent research provides evidence that mind
wandering, the involuntary slipping away of attention from an external task to an
unrelated internal train of thought, is associated with characteristic changes in eye
behavior such as spontaneous pupil activity (Franklin, Broadway, Mrazek, Smallwood, &
Schooler, 2013; Smallwood et al., 2011, 2012). Besides this spontaneous form of internally
focused cognition, there are also many goal-directed cognitive activities which require a
voluntary shift of attention to an internal focus such as planning or idea generation. For
such activities external visual information is irrelevant and can even be distracting. Eye
behavior is assumed to differ between states of goal-directed internally and externally
focused cognition. This study aims to examine the characteristic eye behavior during goal-
directed internally focused cognition. “Internally directed cognition” or stimulus-
independent thought (Smallwood & Schooler, 2006) refers to cognition with an attentional
focus on internally generated information rather than the external environment. Internally
generated information results from memory retrieval of internal representations and
combinations and modifications of those representations (mental simulations, ideas,
dreams; see Chun, Golomb, & Turk-Browne, 2011; Dixon, Fox, & Christoff, 2014). The
literature suggests that eye behavior may respond to and even support internal cognition
in at least two ways: first, by means of attenuation of potentially distracting perceptual
input, and second, by means of a coupling of eye behavior to internally generated
information and processes. We will briefly review evidence in support of these two
hypothesized mechanisms.

<hs>  Attenuation of visual input</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Due to limited information processing capacity, processing external and internal
information simultaneously impairs performance in one domain or both (Chun et al., 2011;
Dixon et al., 2014). On the one hand, external tasks are impaired by internal events, like
daydreaming or trying to solve a puzzle whilst driving a car (He, Becic, Lee, & McCarley,
2011; Savage, Potter, & Tatler, 2013). On the other hand, tasks requiring internally
focused cognition, like thinking about an amazing new idea and how to implement it, can
get interrupted by more or less irrelevant external events, such as an e-mail popping up
on one’s desktop. External (perceptual input) and internal (self-generated) information
are competing for limited processing resources (Chun et al., 2011). Therefore, being able
to focus on one’s internal stream of thought and effectively shielding it from distracting
external information has a high influence on the resulting performance. Active attenuation
or shut out of external information can occur at different levels of visual perception. At
the neural level, research using EEG alpha frequency activity and functional MRI suggests
an active suppression of visual input when participants have to solve a divergent thinking
task with high internal processing demands. For example, EEG alpha activity is assumed to
reflect a top-down mechanism for suppression of external visual information processing
(Benedek, Bergner, Könen, Fink, & Neubauer, 2011; Benedek, Schickel, Jauk, Fink, &
Neubauer, 2014; Fink & Benedek, 2013). Moreover, the right inferior parietal cortex was
implicated in the down-modulation of visual information processing during high internal
attention demands (Benedek et al., 2016; for an overview, see Benedek, 2017). At the level
of eye behavior, the most straightforward mechanism would be to simply look away from
distracting stimuli (e.g. avoid eye contact: gaze aversion) or close the eyes. Indeed,
gaze aversion and eye closure were frequently observed during demanding internally focused
cognition and are thought to reduce cognitive load and thereby free up cognitive resources
(Doherty-Sneddon & Phelps, 2005; Mastroberardino & Vredeveldt, 2014; Vredeveldt, Hitch, &
Baddeley, 2011). The frequency of gaze aversion depends on cognitive load. The more
resources an internally focused task demands, the more resources need to be
recruited/withdrawn elsewhere, e.g. via gaze aversion or eye closure, to prevent
performance impairments (Doherty-Sneddon & Phelps, 2005). Very short eye closures – blinks
– may also reduce the processing of visual input and enhance internally focused cognition.
Solving problems through spontaneous insight was associated with higher blink rates as
compared to analytical problem solving (Salvi, Bricolo, Franconeri, Kounios, & Beeman,
2015). The relationship between mind wandering and blink rate is currently not clear
(Mooneyham & Schooler, 2016; Smilek, Carriere, & Cheyne, 2010; Uzzaman & Joordens, 2011),
but demanding internally focused cognition tasks like idea generation and insight problem
solving are typically accompanied by higher blink rates (Akbari Chermahini & Hommel, 2012;
Salvi et al., 2015; Ueda, Tominaga, Kajimura, & Nomura, 2015), supporting the hypothesis
of an active decoupling strategy. Besides actual interruption of the visual input via
blinks or gaze aversion, the processing of external visual information can also be
attenuated. One potential oculomotor mechanism for attenuation would be disaccommodation.
To focus on an object in three-dimensional space the eyes need to be aligned (eye
vergence) and the lens adjusted to the object’s distance. These changes are associated
with changes in pupil diameter. The three processes – eye vergence, lens constriction and
pupil size changes – are coupled in the so-called convergence reflex or near response
triad (Delank & Gehlen, 2006; McLin & Schor, 1988; Myers & Stark, 1990). Defocusing an
object results in blurring and double vision, impairing further processing of visual
information. Therefore, eye vergence is an important variable in research on covert
attention - when attention is shifted to another location without moving the eyes (Solé
Puig, Pérez Zapata, Aznar-Casanova, & Supèr, 2013) - and dyslexia (e.g. Kapoula et al.,
2007), and it could also play a role in goal-directed internally focused cognition as
suggested by the phenomenon of “staring into space”. The phenomenon of “staring into
space” refers to the peculiar gaze people have when they are deeply absorbed in thought.
“Staring into space” seems to be characterized by a strong stare (lack of eye movements)
and the eyes seem to focus at a distance far away. In a similar way, attenuation of visual
perception could also be achieved by means of reduced microsaccade activity. When fixating
static stimuli, neuronal adaptation leads to perceptual fading within seconds. To
counteract perceptual fading, our eyes perform fixational eye movements (microsaccades,
drift and tremor), of which microsaccades are considered the most important ones
(Martinez-Conde, Macknik, Troncoso, & Dyar, 2006; Martinez-Conde, Otero-Millan, & Macknik,
2013; McCamy et al., 2012). Microsaccades cannot be generated voluntarily, but they can be
suppressed voluntarily for a few seconds (Bridgeman & Palca, 1980; Winterson & Collewun,
1976). As external visual information is not needed during periods of internally focused
cognition, there is no need to counteract fading through microsaccades. Fading may even
facilitate internally focused cognition by reducing distracting visual input. So far, the
role of eye vergence and microsaccades for internally focused cognition has not been
addressed by research.

<hs>  Coupling to internally generated information</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

When we remember a special occasion or think about the upcoming holiday, we often seem to
actually look at a mental picture in our mind’s eye. This notion has been supported by
research on mental imagery and memory retrieval, showing that eye movements are commonly
coupled to cognitive processes during internally focused cognition (Ferreira, Apel, &
Henderson, 2008; Johansson, Holsanova, Dewhurst, & Holmqvist, 2012; Johansson, Holsanova,
& Holmqvist, 2005). When retrieving information about objects from memory, eye behavior
patterns reflect those made while actually looking at the scene (Johansson et al., 2005).
Even when eye movements during encoding are prohibited through continuous fixation of a
certain point, eye movement patterns during retrieval reflect spatial characteristics of
the remembered material, as one was looking at it. Those eye movements during retrieval
seem to play an important role for retrieval itself, as prohibiting them impairs retrieval
(Johansson et al., 2012). Furthermore, irrelevant eye movements impair spatial imagery
(e.g. navigating through a matrix) but not visual mental imagery (e.g. imagining features
of objects, for instance whether the letter A contains a curve or not), suggesting that
eye movements are more crucial for spatial than depictive aspects of content (de Vito,
Buonocore, Bonnefon, & Della Sala, 2014). It is even possible to determine whether a
visual or a linguistic task was performed using eye movement patterns although the
presented stimuli were the same pictures (Coco & Keller, 2014). Also searching for and
focusing on information in long-term memory is reflected in different eye movement
patterns. These differences have a counterpart in viewing external visual information:
there are more eye movements during search and only a few when focusing on an object
(Ehrlichman & Micic, 2012). Cognitive processes do not only affect fixations and saccades,
but also pupil diameter. Pupil diameter adjusts to imagined luminance changes (Laeng &
Sulutvedt, 2014), and even responds to other properties of the imagined content such as
valence, cognitive load or target detection (Palinko, Kun, Shyrokov, & Heeman, 2010;
Piquado, Isaacowitz, & Wingfield, 2010; Privitera, Renninger, Carney, Klein, & Aguilar,
2010). Further evidence comes from studies on mind wandering, showing that moving
attention away from external events results in spontaneous, more variable pupil activity
(Franklin et al., 2013; Smallwood et al., 2011). Moreover, mind wandering episodes while
reading reflected deviations from typical reading behavior including longer fixation
duration and reduced within-word regressions (Reichle, Reineberg, & Schooler, 2010;
Uzzaman & Joordens, 2011).

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

The presented literature suggests that internally focused cognition is accompanied by
characteristic eye behavior changes supporting the decoupling from external information
and coupling to internally generated information. Much of this evidence comes from studies
examining differences between goal-directed externally focused cognition (e.g., reading)
and spontaneous, internally focused cognition (i.e., mind wandering). Additionally,
previous studies often focused on subsets of specific oculometric parameters (e.g., blinks
or pupil diameter) and their role for either decoupling or coupling of eye behavior to
internal processes. Therefore, the interplay of various oculometric parameters and their
integrative functional role for perceptual decoupling and coupling mechanisms during
internally focused cognition still need to be investigated. The present study aims to
extend available research in at least two important ways: first, we aim to identify
specific eye behavior patterns associated with deliberate internally focused cognition by
contrasting two goal-directed thinking tasks, one with an external focus (letter reading)
and one with an internal focus of attention (idea generation). Second, we consider a large
range of oculometric parameters including less common measures like eye vergence and
microsaccade rate that appear particularly relevant to examine potential mechanisms of
perceptual decoupling. The broad range of oculometric parameters allows us to get an
integrated picture of eye behavior during internally focused cognition and the interplay
of both mechanisms: attenuation of visual input and coupling to internal processes.
Finally, we explore the robustness of all effects by means of an experimental variation of
luminance across trials. The attenuation of visual input hypothesis predicts that goal-
directed internally focused cognition should be associated with higher blink rates and
blink durations to reduce visual input (Salvi et al., 2015). Additionally, we explore the
role of eye vergence and microsaccade activity as a more nuanced mechanism to attenuate
visual input. Internally focused cognition may be related to a smaller angle of eye
vergence (indicating a focus behind the screen) and to fewer microsaccades, counteracting
perceptual fading. Predictions regarding the coupling to internally generated information
hypothesis are less straightforward. Our external task requires only little eye movements
for reading single letters in the center of the screen. Therefore, we expect that
searching for an idea – similar to searching for an object in a visual environment
(Ehrlichman & Micic, 2012) – is reflected in a more active eye behavior. This eye behavior
could manifest itself in more and shorter fixations, more saccades and saccades with
greater amplitude (Ehrlichman & Micic, 2012). Pupil diameter (Laeng & Sulutvedt, 2014) and
eye vergence (McLin & Schor, 1988) also respond to imagined differences in luminance and
distance, respectively. Imagined objects and their uses during the idea generation may
vary in luminance and distance within one trial. Therefore, we expect more within-trial
variation of pupil diameter (Smallwood et al., 2011) and eye vergence.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Forty-eight young adults (23 ± 4 years old, 32 females, 15 males, 1 non-binary gender
identity), mostly university students, participated in the experiment for course credit
and/or the possibility to win a skiing holiday. All participants had normal or corrected-
to-normal (soft contact lenses) vision, reported no strabismus or other medical condition
affecting vision. All participants gave written informed consent. Two additional
participants had to be excluded from analyses. One had excessive missing data (>50%) due
to partial occlusion of the pupil by the eye lids, the other had slight strabismus
distorting gaze data. The study was approved by the local ethics committee.

<hs>  Stimuli and apparatus</hs>
  ~~~~~~~~~~~~~~~~~~~~~

As stimuli, a stream of letters was presented in the center of the screen. All letters
were lowercase, and presented in black Arial font of size 15 pt resulting in a character
width of 0.32° visual angle (ca. 2.5 mm or 8.5 pixels). Umlauts were written-out (e.g. “ä”
to “a – e”) and words were separated by a dash (“-”) instead of a space so the screen was
never empty (see Fig. 1A). Letters were presented for 500 ms each, directly followed by
the next letter. To test possible luminance effects on eye parameters, background
luminance was brighter (RGB color code: 204,204,204) in one half of the trials and darker
(102,102,102) in the other half. Participants were placed in a sound attenuated room with
the lights turned on and sat at a distance of 50 cm from the screen. Their heads were
stabilized using chin rest and forehead rest of the EyeLink Tower Mount (SR Research,
Ontario, Canada). Stimuli were presented on a 19-in LG flatroon L1920P monitor run at 60
Hz and a 1240 × 1024 pixels resolution, subtending 29.4 pixels per degree visual angle.
Binocular eye data were recorded using an EyeLink 1000 Plus Tower Mount eye tracker (SR
Research, Ontario, Canada) with a temporal resolution of 500 Hz. For stimulus presentation
and response recording, the EyeLink Experiment Builder software (SR Research, Ontario,
Canada) was used. For calibration, validation, drift correction and computation of the eye
movement parameters (blinks, fixations, saccades), we used the manufacturer’s software (SR
Research, Ontario, Canada). Online velocity threshold for saccade detection was set to
35°/s and acceleration threshold to 9500°/s2. There was a 9-point calibration procedure
before each block and a drift correction before each trial. Spatial resolution was
typically better than 0.30°. Participants’ answers were recorded with a microphone to
monitor and record task performance.

<hs>  Procedure and task</hs>
  ~~~~~~~~~~~~~~~~~~

Participants performed eight experimental trials of a reading task and eight trials of an
idea generation task (see Sections 2.3.1 and 2.3.2), preceded by one practice trial of
each task. The experimental trials were organized in two blocks with a break in between to
minimize effects of visual fatigue. Each block comprised four consecutive reading trials
and four consecutive idea generation trials (half with dark and half with bright
background, respectively). Half of the participants started with the reading task, the
other half with the idea generation task (see Fig. 1B). After each block, participants
filled out a short questionnaire regarding aspects of task performance, including
questions about their concentration, the perceived demands of tasks and the amount of
distraction by the letter stream. Between blocks participants also filled out personality
questionnaires (part of another study) in the antechamber and were instructed to take as
much time for the break as they needed to rest their eyes (at least 10 min). The
experiment took about 45 min in total.

        <hss>Externally focused cognition: Reading task</hss>

        A reading task was used as externally focused cognition task. Participants were
        required to read a German text of 120-character length. To reduce saccades, the
        text was presented as a stream of consecutive letters, each presented for 500 ms
        at the middle of the screen, resulting in a presentation duration of 60 s for the
        entire text (see Fig. 1A). After text reading, two comprehension questions on the
        content of the message were presented on the screen to test if participants had
        focused on the letters throughout the task (e.g., text: “Albert and I are going to
        a concert on Tuesday. I asked Franz if he wants to join us, but he visits his
        grandmother that day” Questions: “What day are we going to the concert?”, “Who is
        Franz visiting?”). Short mind-wandering episodes during this task would lead to
        problems in understanding the text and in answering the questions. In a third
        question, participants had to indicate the direction of attentional focus during
        the task, from 0 = “totally absorbed in thought” to 5 = “totally focused on
        external events”. Participants were informed that if they were focusing on the
        letters of the text during the whole trial they should indicate 5. If they had
        trouble to concentrate on the letters and were mind wandering during the whole
        trial, they should indicate 0. Participants answered the questions aloud. At the
        end of each trial participants pressed the spacebar to continue with the next
        trial.

        <hss>Internally focused cognition: Idea generation task</hss>

        As an internally focused cognition task, we used the alternate uses task
        (Guilford, 1967), a popular and well-established idea generation task commonly
        employed in research on divergent thinking and creativity (Kaufman, Plucker, &
        Baer, 2008). The alternate uses task asks to generate creative uses for a common
        household object (e.g., paper cup). This task relies on imagination based on an
        initially presented stimulus word and was found to be independent of further
        sensory processing (Benedek et al., 2014). The procedure of the idea generation
        task was essentially the same as in the reading task (see Fig. 1A): at the
        beginning of each trial participants received the instruction (e.g., “find as many
        and as creative alternative uses for this object: credit card”). Then they had 60
        s to think of creative uses but without verbalizing them. During this period, the
        same letters as in the reading task were presented one character at a time, but in
        reverse order to make it unreadable. At the end of each task, participants were
        prompted to tell their two best ideas. Finally, participants had to indicate again
        their attentional focus during the task. They were informed that if they were
        focusing on idea generation during the whole trial, they should indicate 0 =
        “totally absorbed in thought”. If they were constantly distracted by the letters
        on the screen or any other external events and could not focus on their ideas,
        they should indicate 5 = “totally focused on external events”.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Creativity of the generated ideas was rated by four experienced raters (overall inter-
rater reliability of 0.67) on a four-point scale ranging from 0 = “not creative” to 3 =
“very creative” (Diedrich, Benedek, Jauk, & Neubauer, 2015; Silvia et al., 2008). Answers
to the comprehension questions after each reading task trial were rated as correct or
incorrect and percentage of correct answers was analyzed. Regarding eye tracking data,
fixation durations and counts of fixations, blinks and saccades and saccade amplitudes per
trial were calculated offline using Data Viewer software (SR Research, Ontario, Canada).
Based on the default settings of the Data Viewer (SR Research, Ontario, Canada) saccades
were defined as eye movements that exceeded 30°/sec velocity, 8000°/sec2 acceleration
and/or 0.15° motion. Blinks were defined as a period with the pupil data missing for three
or more samples in a sequence (= at least 6 ms) and fixations were defined as any period
that is not a blink or a saccade. Blinks as well as additional 200 ms periods before and
after each blink were removed from gaze position and pupil diameter data to eliminate
parts where the pupil was partially occluded (McCamy et al., 2012). Only data for which
the eye tracker had recorded both eyes were analyzed. Further data analyses were performed
using R (www.r-project.org). For calculation of pupil diameter and eye vergence, eye
tracking data were down-sampled from 500 Hz to 50 Hz by averaging across 10 data points
(20 ms). Pupil diameter data were transformed from arbitrary units (measured by the eye
tracking software) to z-values to make them comparable across subjects. For the mean pupil
distance a length of 60 mm was used for all participants. For microsaccade calculation,
original 500 Hz gaze position data were used. Microsaccades (count and amplitude) were
determined using the Microsaccade Toolbox for R (Engbert, Sinn, Mergenthaler, &
Trukenbrod, 2015) with λ = 4 and a minimum microsaccade duration of 6 ms. Microsaccades
were defined as saccades with an amplitude smaller than 1.0° (McCamy et al., 2012). Only
binocular microsaccades with a minimum overlap of one data sample were considered.
Microsaccade amplitude was defined as the mean across both eyes. For all eye parameters,
means or within-trial variability was computed for each trial. Trials with more than 50%
missing data and trials with values beyond three standard deviations from the individual’s
mean were discarded (percent trials discarded: M = 3.78, SD = 5.58, Max = 25.0). Remaining
trials were averaged for the reading and the idea generation trials and for the bright and
darker background luminance, respectively. For raw and processed data as well as
additional analysis see Walcher, Körner, and Benedek (2017).

<hs>  Task performance</hs>
  ~~~~~~~~~~~~~~~~

On average, participants were able to correctly answer 90.36% of the comprehension
questions in the reading task. In the idea generation task, participants reported two
ideas in 98.31% of trials. All trials were included in further analysis. Participants
reported being more focused on external events during the reading task than during the
idea generation task (reading: M = 3.20, SD = 0.84, idea generation: M = 2.27, SD = 1.02,
t(47) = 5.23, p < .001, r = .61). There were no task differences between ratings on how
well they could concentrate (reading: M = 3.03, SD = 1.20, idea generation: M = 3.01, SD =
1.21, t(47) = 0.10, p = .925, r = .01). The letters were perceived as relatively little
distracting during the idea generation task (M = 1.72, SD = 1.39, on a scale from 0 = not
distracting at all to 5 = totally distracting). Participants reported that they perceived
the idea generation task as more demanding than the reading task (reading: M = 1.91, SD =
1.24, idea generation: M = 2.58, SD = 1.13, t(47) = 3.95, p < .001, r = .50).

<hs>  Eye tracking data</hs>
  ~~~~~~~~~~~~~~~~~

A total of 12 eye movement variables were analyzed, which are not necessarily independent
from each other (e.g. blink count correlated with fixation count up to rS = .58, p < .001
and with saccade count up to rS = .58, p < .001). Most of the eye movement variables
violated the assumption of a normal distribution on the sample level (see Table 1,
asterisk indicates a significant Shapiro-Wilk test). Medians for all tasks and conditions
are reported in Table 1. Univariate ANOVAs indicated no interaction effects of task type
(idea generation, reading) and background luminance on eye parameters (bright, dark; all
ps > .05). Hence, effects of task type (idea generation versus reading) and background
luminance were analyzed separately using non-parametric Wilcoxon rank-sum tests (for
calculation of effect size r see Field, 2013).

        <hss>Effects of reading vs. idea generation</hss>

        Effects of idea generation versus reading on eye parameters are visualized with
        effect size r in Fig. 2. In the idea generation task participants produced more
        blinks (Z = 5.97, p < .001, r = .61), longer blink duration (Z = 4.97, p < .001, r
        = .51) and a lower microsaccade count (Z = 5.70, p < .001, r = .58) than in the
        reading task. But we observed no task difference in the angle of eye vergence
        (AoEV; Z = 0.14, p = .890, r = .01) and within-trial variability in the AoEV (Z =
        1.87, p = .060, r = .19). Pupil diameter was larger during idea generation
        compared to reading (Z = 5.20, p < .001, r = .53) but within-trial variability of
        pupil diameter did not differ between task type (Z = 0.01, p = .999, r < .01).
        More and shorter fixations were made during the idea generation task compared to
        the reading task (fixation count: Z = 5.82, p < .001, r = .59; fixation duration:
        Z = 5.77, p < .001, r = .59). Closely associated with the number of fixations,
        more saccades (Z = 5.82, p < .001, r = .59) and saccades with larger amplitudes (Z
        = 5.40, p < .001, r = .55) were made during the idea generation compared to the
        reading task. Like saccade amplitude, microsaccade amplitude was higher during
        idea generation compared to reading (Z = 3.51, p < .001, r = .36). In the idea
        generation task, originality of the two ideas was not correlated with any
        oculometric parameter (rS < .23, p > .12).

        <hss>Background luminance</hss>

        Effect sizes for the influence of background luminance are visualized in Fig. 3.
        Pupil diameter was smaller with bright background (Z = 6.03, p < .001, r = .62).
        Angle of eye vergence was larger with bright background compared to the dark
        background (Z = 3.87, p < .001, r = .41). Both pupil diameter and angle of eye
        vergence showed less within-trial variability with bright background than with the
        dark background (pupil: Z = 4.48, p < .001, r = .46, angle of eye vergence: Z =
        4.47, p < .001, r = .46). Fixations were longer with bright background than with
        dark background (Z = 2.84, p = .004, r = .29). Background luminance had no
        significant effect on fixation count, blink count, blink duration, saccade count,
        saccade amplitude, microsaccade count and microsaccade amplitude (Z < 1.93, p >
        .05, r < .28).

<h>DISCUSSION</h>
----------

The aim of the present study was to examine whether and how characteristics of internally
focused cognition are reflected in oculometric parameters. In the following, we discuss
our findings with respect to the hypotheses of attenuation of visual input and of coupling
of eye behavior to cognitive processes, respectively.

<hs>  Attenuation of visual input</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

In support of an active attenuation of visual input through eye behavior during internally
focused cognition, participants blinked more often (21 versus 8 blinks per minute) and
longer (120 versus 100 ms), and greatly reduced the number of microsaccades (15 versus 4
per minute) during the internal compared to the external task. No effect of attentional
direction was found for the mean angle of eye vergence. More and longer blinks induce a
longer disruption of the visual input, which may serve as a basic mechanism to reduce the
processing of irrelevant external visual information. Salvi et al. (2015) also reported
longer blink duration right before insight solutions as compared to analytic solutions.
Findings on blink rate have been less consistent for spontaneous internally focused
cognition. For example, during mind wandering episodes decreased blink rate was observed
only in comparison to a low load task like breath counting (Grandchamp, Braboszcz, &
Delorme, 2014) but not in contrast to a higher load task like reading (Uzzaman & Joordens,
2011). Goal-directed internally focused cognition (as in our task of timed idea
generation) may require more cognitive resources and therefore a stronger shielding of
ongoing internal processes from intruding irrelevant external input than mind wandering.
In further support of attenuation of visual input through eye behavior, participants
performed fewer microsaccades during idea generation than during reading (see also
Benedek, Stoiser, Walcher, & Körner, 2017). Given the close linkage of microsaccade
suppression and perceptual fading (Martinez-Conde et al., 2006), reduced microsaccade
activity may favor fading of visual perception and thereby serve as another mechanism to
gate out irrelevant external information during internally focused cognition. Given the
higher average frequency of microsaccades compared to blinks, microsaccades could be seen
as a more time-sensitive indicator of internally focused cognition. Contrary to our
exploratory expectations, we found no effect of attention direction on eye vergence. This
means that participants mean distance of focus was similar in both tasks. Overall, the eye
behavior pattern of heightened blink rates and reduced microsaccade rates favors the
hypotheses of an active attenuation of visual input. In the present study, defocusing was
not part of that eye behavior pattern (but see Benedek et al., 2017). Further studies
should investigate whether this eye behavior pattern emerges generally during internally
focused cognition or if it is specific for certain study conditions. Distractor saliency
could be such a critical study condition. People avert gaze more often if a distractor is
salient (Doherty-Sneddon & Phelps, 2005). In the present study, external events
(appearance of a single letter every 500 ms) during the internal task were perceived as
relatively little distracting (1.72 on a scale from 0, not at all distracting, to 5, very
distracting). Some eye behavior patterns related to attenuation of visual input, like eye
vergence thus could only become necessary under conditions of higher distractor saliency.

<hs>  Coupling to internally generated information</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Goal-directed internally (vs. externally) focused cognition was associated with larger
average pupil diameter. This is in line with recent research on mind wandering (Franklin
et al., 2013; Smallwood et al., 2011). But pupil diameter is an intricate eye parameter
because it is affected by different variables such as imagined luminance (Laeng &
Sulutvedt, 2014) and cognitive load (Piquado et al., 2010), leading to ambiguous results,
as demonstrated by Grandchamp et al. (2014) in the domain of mind wandering. While mind
wandering seems to be associated with a larger pupil diameter (Franklin et al., 2013;
Smallwood et al., 2011), so is increasing cognitive load (Palinko et al., 2010; Piquado et
al., 2010). In the present study, idea generation (internally focused cognition) was
perceived as more demanding than reading (externally focused cognition). In the internal
task, participants had to generate ideas and keep the best two ideas in memory for the
remaining time. We tried to account for the working memory load by including some working
memory load in our external task. In the external task, participants had to read a letter
stream. That also included working memory to a certain point, as participants had to
retrieve the previous letters and append the present letter to be able to read the
resulting message. Furthermore, they had to remember the whole sentence until the
questions appeared. So in both, the external and internal task, participants had to modify
material in mind and had to remember something during the trial. Therefore the main
difference between the two tasks was the focus of cognition: during the external task
participants had to continuously focus on external events (externally focused cognition)
and during the internal task they had to focus on internally generated information, namely
their ideas and could ignore external events (internally directed cognition). Yet, one
cannot fully rule out some differential effects of working memory load on pupil diameter.
This point underscores the need to include a wide range of oculometric parameters and to
look at the overall pattern instead of only investigating a small subset thereof (e.g.
only pupil diameter). Supporting our hypotheses that eye behavior is linked to the
cognitive processes, idea generation and reading differed strongly in their eye behavior.
Consistent with the external task’s presentation characteristics (only one letter at a
time in the center of the screen), pupil diameter and angle of eye vergence were
relatively stable. Moreover, only a few fixations and saccades and only saccades with
small amplitudes were made allowing for effective reading of the letter stream. This eye
movement pattern was in strong contrast to that of idea generation. Like searching in a
real visual environment (Ehrlichman & Micic, 2012), searching for an idea in the mind’s
eye evoked a more active eye movement pattern than in reading. Internally focused
cognition induced a higher rate of fixations and saccades and a slight but not significant
increase in variability of angle of eye vergence. Given that angle of eye vergence can be
influenced by imagined changes in depth (McLin & Schor, 1988), those variations could
reflect features of imagined ideas during the generation task. Eye behavior patterns
strongly depend on the cognitive processes active and therefore on task characteristics.
This implies that the observed differences (e.g., higher fixation counts for internal
cognition) may not be intrinsic to internally focused cognition, but can only be
interpreted in the context of the different cognitive processes involved in internal and
external cognition tasks. It hence is not clear whether task differences in these
parameters would also have been observed when tasks had been more similar (e.g., idea
generation for a visible object as compared to idea generation for an imagined object; but
see Benedek et al., 2017). As a consequence, coupling of eye behavior to cognitive
processes may only serve as a reliable indicator of internally versus externally focused
cognition when cognitive processes are well understood and differentiable.

<hs>  Effects of background luminance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Background luminance was varied within tasks in order to test the robustness of attention
effects and the sensitivity of parameters to luminance. We observed no interaction between
attention direction and luminance supporting the idea that effects of attention direction
are robust across different conditions of luminance. As expected, pupil diameter was
smaller for bright compared to dark background, and we observed further effects on the
mean angle of eye vergence and within-trial variability of pupil diameter and eye
vergence. The latter findings may in part be due to eye tracking characteristics itself.
Recent studies found a systematic distortion of gaze measurements due to pupil dynamics
(Drewes, Zhu, Hu, & Hu, 2014; Eberhardt & Huckauf, 2016).

<hs>  Implications and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

An objective discrimination between internally and externally focused cognition has
important implications for cognitive research that often relies on self-report for
assessing the focus of attention. Further investigation of the conditions under which
attenuation of visual input occurs might help to refine theories of distractor inhibition
during internal cognition and of switches between external and internal cognition. For
example, load theory (for an overview see Murphy, Groeger, & Greene, 2016) postulates
different effects of cognitive and perceptual load on distractor interference during
externally focused cognition. Both cognitive and perceptual load also have a strong impact
on distractibility during internally focused cognition. Adding to that, Buetti and Lleras
(2016) showed that increased cognitive engagement reduces sensitivity to visual events. In
a next step, one should investigate if the attenuation of visual input under higher
cognitive load and cognitive engagement could be related to changes in the eye behavior
pattern (blinks, microsaccade suppression) as found in the present study. Regarding the
properties of the used tasks, one can also interpret the results in the framework of the
predictive and reactive control system theory (PARCS, see Tops, Boksem, Quirin, IJzerman,
& Koole, 2014). During the reading task, participants had to integrate new incoming visual
information (letters) continuously, which would involve mostly the reactive control system
or switches between the reactive and predictive control systems of the PARCS. Compared to
that, the idea generation task requires a focus on internally generated information and a
decoupling from incoming signals, therefore mainly the predictive system should be
involved. Attenuation of visual input could indicate the involvement of the predictive
control system. Establishing an eye behavior pattern that can indicate this decoupling
from the external world reliably not only allows for a more accurate categorization of
internally and externally focused cognition between tasks but also within tasks. The
latter would be valuable for the investigation of the brain mechanisms associated with
switches between the reactive and predictive control systems. Further, one should
investigate individual differences in attenuation and coupling related to eye behavior in
the face of distracting visual input. This could bring us closer to the answer why some
people are so good at shielding their internal train of thought while others have serious
trouble doing so, especially in a world where we are confronted with an immense amount of
external stimulation (e.g. adds on webpages, new emails popping up on the desktop).

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

The present study established that goal-directed internally and externally focused
cognition can be reliably discriminated based on eye parameters. Increasing blink rates
and durations as well as reduced microsaccade activity may facilitate perceptual
attenuation via shut-out and fading of visual information. This eye behavior pattern thus
may represent an important mechanism to shield ongoing internal trains of thought from
irrelevant, potentially distracting external stimulation, and future research should
attempt to test this notion experimentally. Further differences in eye parameters between
internally and externally focused cognition may be interpreted in terms of a coupling of
differing cognitive demands between idea generation and reading. We conclude that the eyes
do not idle during cognitive activities that are independent from sensory information but
rather seem to play an active supporting role by shielding internal thought processes as
well as reflecting them.


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<ART>Looking out for each other online: Digital outreach, emotional surveillance and safe(r) spaces
================================================================================

Authors: Julie Brownlie
DOI: 10.1016/j.emospa.2018.02.001
Year: 2018  |  Pages: 60-67
ASJC codes: 3205, 3207
Keywords: Blogs, Digital outreach, Emotional distress, Emotional surveillance, Relationships, Sharing, Twitter

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This article is concerned with what it means to think of online spaces as emotionally safe or safer. It does this by looking at the sharing of emotional distress online and the role of organisations in identifying and proactively engaging with such distress. This latter type of digital engagement is analytically interesting and rendered increasingly feasible by algorithmic developments, but its implications are relatively unexplored. Such interventions tend to be understood dualistically: as a form of supportive digital outreach or as emotional surveillance. Through an analysis of blog data about a Twitter-based suicide prevention app, this article attempts to understand the tensions and also the potential points of connection between these two meanings of ‘looking out for each other’ online. From an avowedly sociological, relational and emotional perspective, it tries to offer a more nuanced account of what it might mean to share emotional distress ‘safely’ online.

--------------------------------------------------------------------------------


<h>ONLINE DISTRESS AND DIGITAL OUTREACH</h>
------------------------------------

While it is not always possible to clearly distinguish between the two (Tucker and
Goodings, 2017), there is increasing recognition of the significance of both informal
emotional support on social media (Eggertson, 2015) and digital outreach, a proactive form
of support facilitated by organisations such as voluntary or government bodies. The
challenges of this latter type of ‘digital professionalism’ (Ellaway et al., 2015) are
debated but, as Facebook's recent announcement about the use of algorithms to identify
suicidal users makes clear (Kelion, 2017), it is increasingly presumed that social
networking platforms have the potential to ‘promote positive change’ in relation to mental
health (Inkster et al., 2016) and to offer digital ‘safe spaces’. At the same time,
however, there are concerns that such outreach can become a form of ‘health surveillance’
(French and Smith, 2013; Lupton, 2012). Regardless of whether or not it is framed as
emotional surveillance, the complexities of how selves are presented, on and offline
(Murthy, 2012), make the interpretation of online content by those engaged in online
support difficult. This is particularly evident in relation to suicide (Mok et al., 2016).
Reflecting wider dichotomous views of the Internet, it's role in relation to suicide is
often perceived as Manichean: a struggle between dark/death and light/life (Robert et al.,
2015). Social media is increasingly part of this context (Christensen, 2014). There is
evidence, on the one hand, that informal online suicide communities can be valued by
participants for their mutuality (Baker and Fortune, 2008); on the other, of suicidal
postings not being acknowledged or of forums maintaining or even amplifying suicidal
feelings (Mok et al., 2016). Similar concerns about how online sharing may reinforce or
exacerbate risky behaviours have also been noted in relation to other practices (Cantó-
Milà and Seebach, 2011). Reflecting the ambiguity of emotional expression, the task of
distinguishing between harmful and helpful content in these contexts is complex:
apparently ‘dangerous’ text can act as a deterrent, be life-affirming or empowering, and
be read differently over time (Mars et al., 2015). Suicide prevention apps (resources
designed to support a person in distress) are increasingly a part of this complex digital
landscape. They range from social media interventions2 to smart phone self-help apps3
(Aguirre et al., 2013). Facebook has been the platform most closely associated with these
developments4 but, in 2014, Samaritans, a charity that provides emotional support to
people experiencing distress, launched a Twitter-based app, Radar,5 under the tagline,
‘turn your social net into a safety net'6. This allowed registered users to be alerted
when a Twitter account they followed included messages that might suggest depressed or
suicidal thoughts. Although media and other responses to the app were initially positive,
it proved increasingly controversial and was withdrawn nine days after its launch. To
understand this, we need to look beyond digital outreach to what it means to share
emotions in online spaces and how such spaces come to be thought of as safe or safer.

<h>MATERIALITY, RELATIONS AND EMOTIONS IN AND ACROSS (ONLINE) SPACE</h>
----------------------------------------------------------------

Notions of ‘space’, including ‘safe spaces’, are key to the sharing of emotion online. An
understanding of space as not innate but constituted and reconstituted through our actions
and interpretations is longstanding (Bondi, 2005; Cronin, 2014) and has been applied to
online settings (Marino, 2015). However, despite initial framings that digital space might
involve the collapsing of time and the overcoming of materialities, the relations through
which all space is produced remain stubbornly material (Massey, 2005). The ‘new’ material
turn has placed matter at the heart of analysis of space, including online, reminding us,
as Lehdonvirta (2010: 885) put it, that the online world is less an ‘open frontier’ than a
‘built-up’ area. This materiality is relevant not just because, as Fayard (2012) notes,
virtual space involves ‘a lot of stuff’, hard and software, but because all users of such
spaces are embodied and embedded in particular places (Hines, 2015) and because online
spaces have socio-material consequences. In other words, space – online or otherwise – is
constituted through, but also shapes, social relations (Lefebvre, 1991): it can keep
people in (their) place or help them move. Not surprisingly, then, online space is often
made sense of through material metaphors. This is true, too, of the sharing of emotion in
online space, though the metaphors used in this context speak to the more ethereal aspects
of offline space: atmosphere (Tucker and Goodings, 2017), intimacy (Michaelsen, 2017) or
ambiance (Thompson, 2008). The relational emphasis on understanding space, noted in the
above discussion of materialities, is often framed in an online context in terms of
sharing. Despite being under-conceptualised (Kennedy, 2015), sharing is key to analysing
online space because the Internet is both a space where sharing happens and is made up of
spaces constituted through such sharing. Because the online realm is made up of relational
spaces, it is also emotional. In addressing the sharing of emotion specifically, I am
concerned with both the meanings identified above: that is, to give and receive emotion,
and to do so jointly within the same space – but also with a third, less researched
dimension, that is, to have the same understanding of an emotion (or why that emotion was
expressed) as another. Research on the role of technological affordances, social relations
and norms on sharing across different social media suggest a complex interplay between the
three (Bucholtz, 2013). To understand this interplay involves going beyond what it means
technically to be a Twitter user/follower (Bruns and Moe, 2014) to examine the meaning
Twitter users give to the sharing of emotion and how this sharing constitutes, as much as
is mediated by, space.

<hs>  Constituting safe(r) spaces</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

When people talk about safe spaces, notions of the relational and emotional are present
but not always foregrounded. Safe spaces are ‘imaginary construction [s]’ (Stengel,
2010:524) that involve complex boundary work in relation to the imagined ‘unsafe’
(Rosenfeld and Noterman, 2014). The impossibility of wholly or indefinitely achieving
exclusion or inclusion ensures that the boundaries and the spaces created are always
porous, contestable and shifting and for this reason it makes sense to refer to safer
rather than safe spaces. Discourses about ‘safety’ in relation to mental health, race,
class or sexuality (Haber, 2016), for instance, are sometimes framed around the exclusion
of others and, at other times, through inclusion – for instance, the idea of a safe space
for all. The idea of being ‘safe to’ express oneself, without repercussion and perhaps in
contestation of dominant discourses, is core to the creation of a space as safe but cannot
always be separated from the idea of being ‘safe from’. This speaks to a long history of
the public sphere as a space of surveillance and exclusion but also, especially for
marginalised groups, as a space of radical potential, a ‘haven’ away from the oppressions
of the private sphere (Haber, 2016). Online spaces, because of their relative anonymity
and ease of access, have been seen as potentially offering increased access to safe(r)
spaces, though these same features can also increase the risk of feeling unsafe. Safe(r)
spaces depend then not just on who is included or excluded and what is expressed but on
how those who are present listen and respond. Reflecting a wider neglect of listening in
the social sciences (Brownlie, 2014), much research on digital sharing still tends to
focus on expression (Crawford, 2009). Yet listening to/reading emotional expression in
public online spaces, including Twitter, involves considerable emotional work. The
therapeutic remains a dominant narrative shaping understandings of the ‘right’ amount of
sharing online as offline (Illouz, 2008): too much information (‘tmi’) is problematised as
leading to an over-exposed self. Conversely, undersharing raises concerns within social
networks about those who ‘go silent’. In both cases, listening is implicit but critical.
Some have suggested there are ‘rules for sharing’ experiences of emotional pain and
suffering online (Sandaunet, 2008), and that these are space- and subject-specific (Hess,
2015). But the fluidity and complexity of sharing (through both expressing and listening)
in moderated and unmoderated spaces (Skeggs and Yuill, 2015) suggests that ‘rules’ may be
too rigid a description for what shapes such sharing. Instead, emotional reflexivity, the
way in which emotions are drawn on to negotiate social life, might offer greater analytic
purchase (Burkitt, 2014). Radar's introduction into Twitter was a moment of contestation
around the meaning of an online safe space: positioned by some as a form of digital
outreach that could constitute a safe space but understood by others as breaching a pre-
existing safe space. In what follows, I explore these framings through a focus on
bloggers' reflexive accounts of what it means to be emotionally ‘safe(r)’ online, but I
begin by outlining how these accounts were identified and analysed.

<h>RESEARCHING RADAR</h>
-----------------

The following analysis draws on a sample of blogs about Radar identified from a search of
all tweets that contained #Samaritans Radar or keywords ‘Samaritans’ and ‘Radar’,
identified via the Twitter API in the two weeks following the launch of the app.7 This
search produced 6540 tweets and the blogs drawn on here are the ones mentioned in the top
100 (ranked by number of retweets and favourites). The resulting 34 blogs were produced by
a range of authors including academics, journalists, mental health writers and activists.
Typically, they were not opinion pieces written by detached commentators but were from
engaged Twitter users. The project focused on blogs accessed through Twitter rather than
communication on Twitter itself. While analysis of tweets might allow for exploration of
reaction to Radar on Twitter, the question of how Twitter users’ account for their sharing
of emotion on this platform, in other words, their emotional reflexivity, is better
accessed through their expansive and discursive blog writing. In other words, blogs
offered Twitter users (and researchers) a degree of distance from their Twitter practice.
There are good analytical reasons, however, for accessing this blog sample through
Twitter. First, the Twitter dataset, produced as part of a larger study on emotional
distress and digital outreach, offered the possibility of a comprehensive sampling frame
of active Twitter users writing on this topic. Though there are limitations to the Twitter
API that mean neither the Twitter nor the blog dataset can be treated as complete, it
would not have been possible to sample these blogs systematically via a general internet
search engine. Second, sampling through Twitter allowed identification of blogs and
opinions that were being actively engaged with – or at least publicised – by Twitter users
following the Radar debate. These blogs might reasonably, then, be regarded as a ‘long
form’ version of the Twitter debate about Radar. Finally, analysis of the Twitter dataset
suggested, not surprisingly perhaps, that themes relating to safety and the sharing of
emotion emerged in both the Radar-related blogs and the larger dataset of tweets from
which the blogs were identified. This offers some reassurance about the prevalence of
these themes beyond the blog sample – again, this would not have been possible if the
blogs had been identified through Google. As noted, however, my analytical concern here is
not with quantifying discourses but rather with how those who supported and resisted the
app framed their understanding, hence the decision to focus solely on blogs. As with other
forms of documentary analysis, blog analysis can involve structural, thematic and
narrative dimensions (Elliot et al., 2016). In particular, blogs can be read as
performances of narrative identity and as constituting particular communities (Schuurman,
2014). While a focus on such community formation could inform further analysis, the focus
here is on mapping ways of writing and thinking about being safe(r). To this end, blogs
were coded thematically and were then re-read with a focus on the use of metaphors. How
metaphors shape the way we think has long been of academic interest and now includes a
focus on the online (Lakoff and Johnson, 2011; Markham, 2013). Ethically, no assumptions
were made about the public nature of blogs unless the blogger's page was explicitly linked
to an organisation, such as a newspaper (AOIR, 2012). In all other cases bloggers were
contacted via email to advise them of the research project and to seek consent to quote
from, and link to, their blog. Only where consent was given were blog data used in these
ways.8 The analysis draws on a particular understanding of emotion. Much research on the
sharing of emotions through social media has drawn on affect (Hillis et al., 2015).
Understandings and definitions of affect vary widely: for some, it involves a visceral,
bodily or ‘gut’ reaction beyond intent, though increasingly there is a move towards
recognising its relational and discursive elements (Veletsianos and Stewart, 2016). Many
of these framings of affect share a focus on its productivity, on what it does (Kennedy,
2015) and have, therefore, been useful in helping to think through how social media both
engages and produces emotion (Hillis et al., 2015) In work focused on media affordances,
however, how emotions are constituted by and constituting of particular relationships, as
well as spaces, can get lost. To this end, the analysis which follows is informed by an
understanding of our capacity for emotional reflexivity and of emotions as constituted,
and made sense of, through relational processes (Brownlie, 2014; Burkitt, 2014).

<h>LOOKING OUT FOR EACH OTHER ONLINE: OUTREACH VERSUS SURVEILLANCE</h>
---------------------------------------------------------------

At first glance, analysis of the blogs suggested that the response to Radar could indeed
be understood through the polarised framework of emphasising benefits (harm reduction
through outreach) or risks (those associated with surveillance). The app was introduced on
the basis that it could potentially save lives and, initially, was positively received. In
the two week period after its launch, however, the metaphors appearing in the blogs
shifted towards the discourse of surveillance. The announcement of the petition for the
app to be withdrawn, for instance, described Radar as having been launched ‘behind
people's backs' on ‘unsuspecting Twitter users’.9 One blogger who writes about data
protection10, referred to the app through the metaphors of ‘profiling’
(http://bit.ly/2A9W9uc) while another, who writes on mental health and disability,
referred to ‘Orwellian’ practices (http://bit.ly/2Bcoo8y). The peculiarly human nature of
the work the app was being programmed to do – identify emotional distress – meant it was
metaphorically positioned by some bloggers as cyborg-like, a cross-over between a ‘suicide
bot and concerned friend’ (Hess, 2015). To a degree this points to the particular
ambiguity of the Radar app: introduced by an organisation and hence akin to traditional
centralised surveillance practices, yet dependent on Twitter users signing up for the app
to be reminded of what their followers have been up to, hence closer to peer to peer
surveillance. The app's ambiguous position was further accentuated by the commercial
context in which it was developed (Mason, 2014). Drawing on metaphors of experimentation,
one mental health blogger suggested Twitter users were being positioned as ‘subjects for
your tech’ (http://bit.ly/2Bcoo8y), reflecting an unease with such developments even when,
as in the case of Radar, they were packaged as ‘big data for good’. On first reading,
then, the conventional (individualised) polarities associated with digital outreach, of
reducing harm or increasing the risk of surveillance, are evident in discussion of the
app. As the debate unfolded it became more polarised, a process accentuated by the
adversarial nature of the platform. Yet it is also clear that both ‘sides’ acknowledged
the significance of finding support online and both expressed anxieties about making
Twitter a safe space. Re-reading the blog data through an understanding of safe(r) spaces
as materially, relationally and emotionally achieved helps make sense of polarised views
of how digital caring happens or is imagined to happen. Discourses, often metaphorically
expressed, run through all these dimensions and, in what follows, I consider online
safe(r) space discretely through each. This, though, is a heuristic separation as they are
in practice co-constituting.

<h>CONSTRUCTING THE MATERIALITY OF RADAR SPACE</h>
-------------------------------------------

Twitter, like all space, is constantly under construction, produced through everyday
relationships, practices, emotions, materials and the discourses that revolve around all
of these. In launching Radar and in subsequent statements, Samaritans sought to introduce
the app as offering Twitter users a ‘second chance'11 to see tweets from someone they knew
who might be struggling to cope. In other words, they sought to make the technical case
that the tweets that triggered app alerts were already appearing in the Twitter feeds of
the app subscribers.12 Bloggers' response to this justification, however, reflected a by
now well-established critique of the dualistic understandings of public/private developed
through work on the nature of visibility on social network sites (Marwick and boyd, 2014).
In particular, some bloggers described how they constituted different spaces within
‘public’ Twitter through the strategic placing in tweets of the @ sign or a period in
order to restrict or expand their potential audience (for an explanation of how this works
in practice, see http://bit.ly/1fkfKbI). In this extract, for instance, a blogger who
writes on digital privacy explains that such practices allow him and others to use the
Twitter space in ways that are less public than those deployed by celebrities such as
Stephen Fry: Not all Stephen Fry. Not all tweets equally visible – can make more intimate
and more public by using @ and also by using ‘.’. (http://bit.ly/2BqLrNR) Reflecting a
tendency, noted earlier, to perceive digital space through physical metaphors (Haber,
2016), Samaritans in their naming of the app and through their core metaphor of Radar as a
‘safety net’ sought to make sense of digital space through material offline practices and
objects. Similarly, offline place metaphors were important for how bloggers attempted to
understand Twitter as a digital safe space. Place has long been associated with
understandings of safeguarding: ‘the basic character of dwelling is safeguarding’
(Heidegger, 1978:352 cited in Martin, 2017) and this is also the case with online
dwellings. In the following extracts, bloggers are trying, in particular, to think through
the potential for privacy on Twitter. One blogger, an academic, turns to offline
surveillance practices (CCTV) to do so, while another turns to offline places (the pub,
the dinner table) and communicative practices (whispering): my office window looks out on
a public street – whatever people do there is public. There would still, though, be
privacy issues if I installed a video camera in my window to tape what people did outside.
(http://bit.ly/2BxoUOF) You can have an intimate, private conversation in a public place –
whispering to a friend in a pub, for example […]. Chatting around the dinner table when
you don't know all the guests – where would that fit in?’ (http://bit.ly/2BqLrNR)
Crucially, though, these place metaphors are also a means of imagining who is listening
(Litt and Hargittai, 2016). Like those who have written about online ‘places’ as having
‘residents’ and ‘clusters of friends and colleagues’ (White and LeCornu, 2011 cited in
Veletsianos and Stewart, 2016), bloggers constitute Twitter, not just as a material and
discursive space but also as a relational one.

<h>SAFE(R) RELATIONS</h>
-----------------

From the outset, Radar was conceived by Samaritans as a relational tool; a means for all
of us to look out for each other online. This is consistent with a shift towards the
democratisation of helping: the idea that one does not need to be trained to offer help to
others (Lee, 2014). Those who initiated Radar had in mind a diffuse but benign audience:
in other words, the ‘attitude of the whole community’ (Mead, 1934) was imagined to be
supportive. In an update following the launch, Samaritans suggested that the app could be
aimed at those ‘who are more likely to use Twitter to keep in touch with friends and
people they know’.13 One blogger, who writes about technology, also suggested that the app
might work better if it was restricted to reciprocal arrangements with people ‘who the at-
risk person is following back – so theoretically only friends’ (http://bit.ly/2A9YdSY).
Different platforms offer different understandings of safe relations and this focus on
friends is closer to the generalised ‘attitude’ of the Facebook rather than Twitter
community. Facebook involves known networks, and indeed most research on emotional support
has been focused on the platform for this reason (Burke and Develin, 2016). Yet there are
powerful norms that make it difficult to seek emotional support on Facebook (Buehler,
2017) and, for some, its very interconnectedness makes it a less than safe space for
sharing emotional distress. Affordances of other platforms may mean that sharing is
experienced as potentially less stigmatising with feelings expressed, for instance,
through images and through second (Instagram) or ‘throwaway’ (Reddit) accounts (Andalibi,
2017) in a way that is not about maximising visibility. Twitter followers are not
necessarily friends in the sense of intimates; nor are followers who are friends, and are
intimates, necessarily able or willing to take on the responsibility of ‘looking out’ for
others. Indeed, there are significant risks in assuming friends and/or followers are in a
position to reply or, as a blog below from a mental health service user suggests, that
their response would be useful or welcomed. Indeed, they might in fact have a ‘chilling’
effect (Hess, 2015): It's not just having the information, it's being able to *do*
something useful with it. If it just flags up that you need to try and connect with and
support a person, that's one thing, but what if people who know very little about mental
health sign up and wake up to a worrying email? Would they have enough info to call
police/ambulance? SHOULD they – would the person welcome this? (http://bit.ly/2Bcoo8y) One
blogger who writes on disability and mental health expressed concern that app users might
be potentially deluged by ‘ghost patterns’ (Crawford, 2014): ‘if you use [Radar], you're
going to get a hell of a lot of spam, unless you only follow a few close friends'
(http://bit.ly/2zEvAOz). Such anxieties, however, might also be about whether apps can
capture the relational nuances of friendships and about the authenticity of those
friendships that depend on the app: would a real friend need technological help to become
aware of a known other's emotional upset? If individuals need to be poked to remember to
check on someone, they very much might not be the type of person someone [ …. ] wants to
talk to. (http://bit.ly/2AchWiH) There are ways of displaying friendship, online and
offline, that shore up authenticity; and, conversely, friendship norms can be breached
through inappropriate sharing or use of technology (Bazarova, 2012): Friends are people
who although I have only met them via Twitter care enough about me to check in with me
before they go to bed and when they wake up, who states openly, “I am really concerned
about you, how can I help?” They don't need an app to record what I have been saying while
they were asleep or at work, because they simply message me as soon as the[y] wake/return
asking how I am and telling me they are thinking of me. (http://bit.ly/2Bcoo8y) The clash
of norms arising here is from the use of an algorithm14 in relation to the emotional
support and specifically about the automation of friendship: the speeding up, delegation
and mechanisation of what it means to be a friend. In the context of online dating, this
is what Peyser and Eler (2016) refer to as the ‘tinderization’ of emotion. Research is
beginning to emerge on the limitations of ‘conversational agents’ such as Siri in
responding to distress (Miner et al., 2016) and for Wachter-Boettcher (2016) this is a
reflection of the political economy of social media, ‘an industry willing to invest
endless resources in chasing “delight” but not addressing pain’. These criticisms are with
the friend-like sensitivity of the app but the bloggers' concerns are about what using
such an app in the context of friendship says about the nature of that relationship. Other
bloggers were focused less on friendships than on types of relationships seen as ‘unsafe’
because they are not supportive. These include digital bystanders; those who choose not to
respond to tweets about distress. Illustrating the complexity of ethics of care in
digitally mediated relations, these may be people who do not want to help but they may
also include those who tactfully ‘disattend’ to messages believing they are not intended
for them (Brake, 2014: 45). Either way, lack of acknowledgment of emotional distress could
leave those who have tweeted about their distress with the impression, as one mental
health blogger described it, ‘that nobody cares enough to respond’
(http://bit.ly/2zEvAOz). The public space of Twitter can also be inhabited by those who
are the antithesis of ‘friends’ or even ‘digital bystanders’: those whom some bloggers
referred to as ‘stalkers’ and ‘abusers’. As with safe spaces, safe relations are defined
by their opposite. Drawing on metaphors which speak to vulnerability and fear of
violation, some bloggers suggested that in the ‘wrong hands’, the app acts like an
advertisement for our ‘empty homes’ or ‘lost children’. This speaks to the porousness of
safe(r) spaces: the inability to separate out a safe space constituted by well-intentioned
use of the app from other spaces, on and offline, that are, as the mental health blogger
below notes, potentially less benign: What if your stalker was a follower? How would you
feel knowing your every 3am mental health crisis tweet was being flagged to people who
really don't have your best interests at heart, to put it mildly? (http://bit.ly/2zrS8hv)
Radar had been introduced as a way of listening and being empathic. But not all listeners
are benign and, as a result, some bloggers feared that being listened in on, rather than
listened to, might lead some to withdraw from the informal support that exists from simply
being on Twitter. For these Twitter users, apps such as Radar, are disruptive of a pre-
existing ‘positive’ community formed in a ‘natural, human way’. In describing this sense
of community, the metaphors used are system related – Twitter as ‘an online ecosystem’.
Positioned as ‘ad hoc’, this relational space is understood by some as being built up
through individuals’ sharing distress and thus can be thought of as an ‘authentic space’.
It is a community then in the sense that it involves a fusion of weak and strong ties
(Gruzd et al., 2011) and, crucially, has an affective component: sharing emotions
constitutes a sense of ‘we ness’ or ‘digital togetherness’ (Marino, 2015). While this
imagined space is finely calibrated, constituted by the honesty of what is said,
significantly, there is not necessarily an expectation of direct intervention from those
listening. This speak to a particular understanding of emotional expression (and
listening) in public spaces which is at odds with the understanding that informed the
development of the app, outlined in this extract from Samaritans: People often tell the
world how they feel on social media and we believe the true benefit of talking through
your problems is only achieved when someone who cares is listening.15 Awareness of the
app, however, meant that some bloggers imagined Twitter as less safe and the app as
silencing rather than amplifying. This was a view expressed by some of those who were
already known to be using Twitter for emotional support, such as the mental health blogger
below. Those not publicly using Twitter in this way may, of course, have very different
views but they are less likely to be known about: It will cause me harm, making me even
more self aware about how I present in a public space, and make it difficult for me to
engage in relatively safe conversations online for fear that a warning might be triggered
to an unknown follower. (http://bit.ly/2AchWiH) Bloggers discussed the possibility of
switching Twitter accounts to ‘private’ to avoid the algorithm but this recalibration of
the imagined Twitter space and its relationships, would make it, for some, more akin to
Facebook's relational space(s) with its attendant expectations of distress being shared in
particular (undemanding) ways (Buehler, 2017). In the final section, understandings about
emotional expression embedded in the above accounts of safe(r) spaces are analysed more
closely.

<h>EMOTIONS AND SAFE(R) SPACES</h>
---------------------------

As Pedersen and Lupton (2016) have noted there is still surprisingly little focus on the
role of emotions in the sizeable body of literature on digital sharing and surveillance.
In the specific context of sharing emotional distress, Radar was premised on the belief
that there is such a thing as a digital cry for help and that it can be identified by
algorithm as such. Indeed the app, as noted, was positioned as a second chance to hear
such online cries. Radar was intended to create a sense of safety by increasing awareness
of those in difficulty and indirectly a sense of obligation to act caringly towards them.
Metaphorically, as described by a journalist below, the app was intended to catch people
on the precipice: The point of Radar, however, is to catch people on the edge of the cliff
face who would be truly grateful of a helping hand to pull them back up, but for whatever
reason, didn't feel they could say this outright.16 The assumption here is that the
meaning of expressed emotion is shared. This is the third understanding of sharing emotion
I introduced earlier: that two or more people share an understanding of why an emotion is
expressed. In the case of emotional distress, however, those who express emotion and those
who then hear or read it are not necessarily sharing the same understanding. Expression of
emotional distress can be a cry for help but it can also have and achieve other ends. A
cathartic model of self-expression, for instance, suggests that emotional expression is a
form of release (Solomon, 2008). Other perspectives focus on emotional expression as self-
actualisation or as a means of making sense of our emotional experiences by sharing them.
Bennett (2017) has suggested that there is also a symbolic model for understanding
emotional expression: that emotions, like poetry, are an end in themselves - a way of
speaking to whom one is (Murthy, 2012). What is missing from some of these psychological
and philosophical frames, however, is a strong enough sense of the relationships and
contexts within which the sharing of emotions takes place. In their work on academics who
share personal information online, for instance, Veletsianos and Stewart (2016) note this
group tend to do so with clear intent and a strong awareness of social context. Some of
the Radar-dataset bloggers, such as the mental health blogger below, made it clear that
they would not consider it safe for them to express their distress on Twitter in a way
that could be interpreted as a cry for help: No matter how suicidal I've been, I would
never, ever tweet something like ‘I can't go on’ or ‘I'm so depressed’. [ …] I also don't
want to cause a fuss, so being aware of specific trigger words that may cause a fuss would
make me consciously not use them. Furthermore, I am private about my mental health […] I
don't want my health problems to be noticeable. (http://bit.ly/2AchWiH) This practice of
public tweeting with the intent of not being noticeable or ‘making a fuss’ returns us full
circle to the question of what constitutes a safe ‘public’ online setting, and why people
choose to express and listen in such spaces. For some there is safety in being one of many
when disclosing pain. This can be thought of as quiet public disclosure, constituting and
constituted by diffuseness and a dispersed sense of emotional connection. This is as
potentially public as those who ‘life stream’ but is driven less by a desire for
visibility per se than, as the mental health blogger below suggests, ‘mutual witnessing
and display’ (Warner, 2002: 13, cited in Haber, 2016: 393). A way, in other words, to
‘welcome care’ from ‘known’ networks (Veletsianos and Stewart, 2016) It's a place I can
express myself without worrying that I will upset relatives, where I can say the unsayable
because other people understand. (http://bit.ly/2Bcoo8y) This saying of the unsayable is a
way of feeling differently in digital spaces which are often regulated towards optimism
(Pedersen and Lupton, 2016) or what Michaelsen (2017) framed as ‘a better future of
emotional sameness’. Some bloggers suggested that it was the ‘processing’ work of the
algorithm which made their messages (and hence their emotions), public and potentially
unsafe, not the act of tweeting or expressing emotion in itself. For these bloggers, the
interplay between the material, relational and emotional positions the algorithm as part
of an online interaction order (Mackenzie, 2016). These concerns tune into anxieties about
emotional surveillance and about whether or not we can control information about
ourselves, including about our emotions (Brandimarte et al., 2013). This brings us to a
key distinction between outreach and surveillance: the notion of consent. Becoming aware
that one is part of an infrastructure of ‘noticing’ online that one has not directly
consented to can lead to an unease with, and a reaction against, the reading of such
information, not least because it may not speak to who people believe they ‘really’ are
(Ball et al., 2016). Though others, of course, may position information gained through
emotional surveillance as authentic exactly because it happens outside of platform users'
full control or even knowledge (Horning, 2016).

<h>CONCLUSION</h>
----------

It is in the nature of safe(r) spaces that they are contestable, open to both boundary
maintenance and change. Digital safe(r) spaces can be even more porous and hence boundary
skirmishes in relation to them are potentially even more fraught. This article, through
exploring the reaction to Radar, has been concerned with what makes an online space feel
emotionally safe(r). Those concerned with safeguarding or digital outreach and those
concerned with the guarding of safe spaces against surveillance both write about Twitter
as a material, emotional and relational space, but they constitute it differently (Lien
and Law, 2011). Working with metaphors helps us to understand what and why things matters
to people and is revealing of how the Radar app processed and also produced, a great deal
of emotion: strong emotions linked to notions of territoriality, belonging and safety. So
while there is value in thinking about the online in terms of what we do (Jurgenson et
al., 2018) rather than as a place or space, all space, as argued earlier, is constituted
and for many users of online platforms, doing and space are interconnected. To respond to
the sharing of emotions, including cries for help, in a way that is disembedded from and
does not acknowledge their spatial context creates upset, and this can be read in the
metaphors of intrusion and violation that permeate the blog discussions. Focusing on the
material, emotional and relational context of safe spaces, however, also reveals points of
connection particularly in relation to valuing peer relationships and the benefits of
sharing of emotional distress. Those concerned with both surveillance and outreach,
however, also risk positioning emotional distress as there for the seeing/hearing:
depending on one's point of view, ready to be caught in a ‘safety net’ or turned into
‘sensitive data’ by the app. The analysis presented here suggests emotions are not so
easily read or categorised. For some bloggers, the sharing itself is what keeps the
distress at bay; for others, there may well be no obvious emotional content to their
sharing and yet they are distressed. Even if distress is correctly identified, however,
there are still questions about how online proximates and strangers should be cared for.
The analysis points to concerns about the automation of support online and also to the
claim that some users may leave online public spaces such as Twitter if they believe these
spaces to be ‘monitored’. For digital outreach to be enabling rather than undermining of
existing peer support, therefore, several issues need to be considered by organisations.
These include a need to be explicit about organisational assumptions about what
constitutes support and how consent to be supported is sought and given online; being
aware of the potential for outreach to be both silencing and amplifying and of the
sensitivity of the tipping point between keeping a digital eye out and emotional
surveillance; and recognising the specific risks of using algorithms in relation to the
most human of activities - responding to emotional pain. While only implicitly present in
this article, trust runs through all these considerations and is core to what constitutes
feeling ‘safe(r). Drawing on the meaning of safe(r) spaces repositions the sharing of
emotions as being about more than the commercial interests of social media platforms or
the norms relating to Twitter, and highlights that people share distress or emotions
because of their sense of trust in relationships they believe they have or desire to have.
Any organisation engaging with digital outreach needs to understand how their actions can
either shore up or breach such trust, and hence vitally affect people's sense of being
safe. A dualistic focus on outreach or surveillance in relation to emotional distress
online reduces possible responses to either direct intervention or silence – digital
Samaritan or bystander - missing other nuanced practices, including what I have referred
to here as quiet public disclosure of emotional pain. Moving beyond dichotomous accounts
of online sharing of emotional distress creates more ambiguity but should be an important
first step for organisations in working out the fine line between digital caring and
surveillance and what it might mean, in both senses, to look out for each other online.


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<ART>Love is the triumph of the imagination: Daydreams about significant others are associated with increased happiness, love and connection
================================================================================

Authors: Giulia L. Poerio, Peter Totterdell, Lisa Marie Emerson, Eleanor Miles
DOI: 10.1016/j.concog.2014.12.011
Year: 2015  |  Pages: 135-144
ASJC codes: 3204, 3205
Keywords: Close relationships, Daydreaming, Emotion regulation, Experience sampling, Mind wandering

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Social relationships and interactions contribute to daily emotional well-being. The emotional benefits that come from engaging with others are known to arise from real events, but do they also come from the imagination during daydreaming activity? Using experience sampling methodology with 101 participants, we obtained 371 reports of naturally occurring daydreams with social and non-social content and self-reported feelings before and after daydreaming. Social, but not non-social, daydreams were associated with increased happiness, love and connection and this effect was not solely attributable to the emotional content of the daydreams. These effects were only present when participants were lacking in these feelings before daydreaming and when the daydream involved imagining others with whom the daydreamer had a high quality relationship. Findings are consistent with the idea that social daydreams may function to regulate emotion: imagining close others may serve the current emotional needs of daydreamers by increasing positive feelings towards themselves and others.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Social interactions and relationships are vital for a healthy, happy and meaningful life
(e.g. Baumeister, Vohs, Aaker, & Garbinsky, 2012; Diener & Seligman, 2002; Holt-Lunstad,
Smith, & Layton, 2010) and contribute to daily emotional well-being. For example, people
report feeling happiest when socializing (Kahneman, Krueger, Schkade, Schwarz, & Stone,
2004) and during interactions with friends (Csikszentmihalyi & Hunter, 2003), and feelings
of social connectedness are predicted by social activities and supportive interactions
(Reis, Sheldon, Gable, Roscoe, & Ryan, 2000). Despite the emotional benefits of social
interaction, a substantial portion of each day is typically spent in the absence of social
activity and/or separated from close significant others (e.g. at work). However, even in
the absence of social interaction the mind will invariably drift to imagine others and
mentally simulate past and possible future social scenarios. Estimates suggest that we
spend an inordinate amount of time daydreaming (Klinger & Cox, 1987), which is often
social in nature (Mar, Mason, & Litvack, 2012). What would the impact of imagining others
during daydreaming activity be on momentary feelings: could the influence of others on
emotional well-being emerge from the imagination as well as from real events? In the
present research we use experience sampling to explore whether everyday social daydreams
are associated with increased positive social emotion and whether this depends on who is
being daydreamed about.

<hs>  Daydreaming and its social content</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Whilst reading a novel, walking to work, or during everyday activities, the mind has a
proclivity to drift to unrelated thoughts, images and feelings. Such daydreaming activity
can occur as mind-wandering when attention becomes decoupled from one’s current task
(Smallwood & Schooler, 2006) but can also occur when there is no specific task at hand,
such as during a commute to work or when relaxing on a beach (Klinger, 2009). Daydreaming
can be defined as mental content experienced during a state of normal waking consciousness
that is stimulus-independent and task-unrelated, because it is neither a direct reflection
of the current sensory environment nor related to the thinker’s current mental or physical
task (e.g. Stawarczyk, Majerus, Maj, Van der Linden, & D’Argembeau, 2011). Defined in
these ways, daydreaming occupies a substantial proportion of waking thought – a figure
estimated to be between 30% and 50% (Killingsworth & Gilbert, 2010; Klinger & Cox, 1987) –
and is thought to represent a psychological baseline to which people return in the absence
of external demands (Mason et al., 2007). Daydreams are proposed to reflect an
individual’s current goal commitments and they occur when individuals’ encounter goal-
relevant cues in situations that do not lend themselves to attaining those goals (Klinger,
1975; Klinger, 1996; Klinger, 2009; Klinger, 2013). For example, hearing a friend’s name
in a song on the radio may act as a reminder that the friend has an upcoming birthday,
which then triggers thoughts and images about what gift to give, what the birthday party
might be like, who will be there, and what conversations might unfold. In this way,
daydreams are goal-relevant and involve mentally pursuing or seemingly attaining goals
when doing so in reality is not possible (Baird, Smallwood, & Schooler, 2011; Klinger,
2013). Building upon this, emerging evidence indicates that daydreaming may be
predominately social in nature and centered on social goals and needs. This is
unsurprising given that the need to feel close and connected with others is fundamental
and drives behavior and thought content towards the formation and maintenance of close,
positive social bonds (Baumeister & Leary, 1995; Ryan & Deci, 2000). Mar et al. (2012)
demonstrated that 73% of a large sample (N = 17,556) reported that other people are
‘frequently’ or ‘always’ involved in their daydreams whilst less than 1% reported that
others are ‘never’ involved. Likewise, Song and Wang (2012) found that other people
featured in 71% of sampled task-unrelated thoughts, and Andrews-Hanna et al. (2013)
provide evidence that the tendency to think about others represents a major dimension of
thought content. Neuroimaging data also lends converging support for the social nature of
daydreams; A meta-analysis of 12 neuroimaging studies reported substantial overlap between
brain regions involved in daydreaming and those involved in social cognition, suggesting a
predisposition to generate social thoughts during daydreaming activity (Schilbach,
Eickhoff, Rotarska-Jagiela, Fink, & Vogeley, 2008).1

<hs>  Daydreaming and emotion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Why would daydreams influence feelings? Daydreams are imaginary experiences that resemble
their simulated target, generally via visual and auditory imagery (Andrews-Hanna et al.,
2013; Klinger & Cox, 1987). Imagining events or experiences can evoke the feelings that
would arise if the simulated event were occurring (Kosslyn, Ganis, & Thompson, 2001).
Indeed, the capacity of imagination to evoke and change feelings associated with the
imagined subject matter is well established. Asking participants to imagine emotional
events is a widely used technique to induce desired mood states (Westermann & Spies, 1996)
and guided imagery is often employed in therapeutic interventions to promote positive
feelings and reduce negative feelings (e.g. Hutcherson, Seppala, & Gross, 2008; Lewis,
O’Reilly, Khuu, & Pearson, 2013; Panagioti, Gooding, & Tarrier, 2012). Given the capacity
of the imagination to evoke feeling states, it seems plausible that social daydreams would
induce social feelings associated with the imagined experience and underlying social goals
and needs. Social daydreams may therefore play a role in shaping people’s everyday
feelings in relation to their social goals and needs, such as feelings of love and
connection. Previous research regarding the link between daydreaming and emotional well-
being has tended to focus on its relationship with negative affect. For example, there is
evidence to suggest that daydreaming may be detrimental to well-being due to its
associations with dysphoria (Smallwood, O’Connor, Sudbery, & Obonsawin, 2007), depression
(Carriere, Cheyne, & Smilek, 2008; Giambra & Traynor, 1978), rumination and self-focused
attention (Marchetti, Van de Putte, & Koster, 2014) and feeling less happy in daily life
(Killingsworth & Gilbert, 2010). However, research increasingly acknowledges that
daydreaming is unlikely to be a homogenous experience and has begun to explore the
conditions under which daydreaming is associated with negative and positive emotion. For
example, the relationship between daydreaming and emotion may depend on its
phenomenological and emotional content (Andrews-Hanna et al., 2013; Poerio, Totterdell, &
Miles, 2013), temporal focus (Ruby, Smallwood, Engen, & Singer, 2013), interest in thought
content (Franklin et al., 2013), personal lay theories (Mason, Brown, Mar, & Smallwood,
2013) and current depressive symptomology (Marchetti, Koster, & De Raedt, 2012). As an
extension to these factors we propose that the social content of daydreaming will also
have an impact on how daydreaming relates to emotional well-being and, in particular, to
positive social feelings rather than negative emotion more generally. Research supports
the proposition that imagining interactions and relationships can have a positive impact
on social feelings. For example, across two studies, Kumashiro and Sedikides (2005) found
that participants instructed to visualize a close positive relationship expressed warmer
and more positive other-directed feelings compared to participants who had visualized a
close negative, or neutral, relationship. Additionally, a large body of research on
imagined contact indicates that imagining positive and neutral interactions with out-group
members can promote positive feelings towards others including positive affective
attitudes, increased out-group trust, and reduced inter-group anxiety (Miles & Crisp,
2014). These findings indicate that deliberately imagining interactions and interpersonal
relationships can evoke positive social feelings. Whether similar effects apply to
naturally occurring social daydreams that derive from an individual’s personal goals,
rather than laboratory-based directed mental simulations, is an open question. However,
recent correlational evidence has associated the tendency to daydream about close others
with greater socio-emotional well-being (Mar et al., 2012). Daydreams about non-close
others did not show a positive association with well-being, which suggests that the
quality of the relationship in the daydream may be important. Given that interactions
within close relationships are most likely to elicit positive social feelings in daily
life (e.g. Laurenceau, Barrett, & Rovine, 2005) daydreams about close others may be
especially likely to elicit positive social feelings. Another factor that may influence
social feelings is the thematic content of social daydreams. The social goals underlying
and influencing daydreams may be approach-oriented, i.e., concerned with the attainment of
positive end-states (e.g. affiliation) or avoidance-oriented, i.e. concerned with the
prevention of negative end-states (e.g. social rejection). Daydreams involving the mental
pursuit of social approach goals would be more likely than those involving social
avoidance goals to be associated with positive social feelings because the former engages
positive cognitions and the latter engages negative cognitions (Elliot, Sheldon, & Church,
1997; Tamir & Diener, 2008). Although individual social daydreams may be associated with
increased or decreased positive social feelings, there is also reason to suspect that, as
a general pattern, social daydreams will be associated with increased positive social
feelings. We make this prediction from a study by Johannessen and Berntsen (2010) that
assessed participants’ current goal commitments which often referred to social life
categories including “love, intimacy and sexual matters” and “friends and acquaintances”.
Importantly, participants reported their specific goals to be related to achievement
rather than avoidance. This suggests that daydreams will be predominately associated with
mentally pursuing desired social goals, which in turn, should increase the positive social
feelings associated with their imagined pursuit or attainment.

<hs>  The present research</hs>
  ~~~~~~~~~~~~~~~~~~~~

Building on the ideas presented above, we sought to explore whether social daydreams would
be associated with increased social feelings by choosing to focus on feelings of love and
connection. We used experience sampling methodology (Bolger, Davis, & Rafaeli, 2003) to
examine naturally occurring daydreams and associated feelings. In addition to reports of
social daydreams and social feelings, we sampled non-social daydreams and non-social
feelings to serve as points of comparison. On the assumption that social daydreams
commonly represent attempts to mentally pursue social approach goals we predicted that
social daydreams, but not non-social daydreams, would be associated with increased love
and connection. We did not make specific predictions about whether social and non-social
daydreams would differ in their association with changes in non-social feelings. Daydreams
with and without social content could both relate to changes in non-social feelings. We
also measured the emotional content of daydreams to rule out the possibility that the
predicted increases in social feelings could be attributed to the emotional, rather than
social, content of daydreaming. In addition to our main prediction, we explored whether
the effect of social daydreams on social feelings might depend on who was involved in the
daydream by measuring the relationship quality between the daydreamer and the most central
other person involved. We predicted that relationship quality would moderate the effect of
social daydreams on positive social feelings whereby daydreams involving higher quality
relationships would be positively associated with increases in positive feelings.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

One hundred and one volunteers (81 women, 20 men; Mage = 22.32 years, SD = 5.17) were
recruited to the study. It was described as an investigation into the content and nature
of daydreams and advertised via email, flyers at a public engagement event, personal
contacts and referrals. Of the participants, 49 were undergraduate psychology students, 22
were postgraduate students, 20 were in full-time employment, and 10 were non-psychology
undergraduate students. In exchange for their participation, undergraduate psychology
students were given study credits; all other volunteers were entered into a prize draw to
win shopping vouchers equivalent to $33, $50 and $83.

<hs>  Experience sampling protocol</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We used a signal-contingent experience sampling protocol (Wheeler & Reis, 1991) to sample
daydreaming and associated feelings. Participants were signaled four times via text
messages to their cell phones to answer online questionnaires about their two most recent
social and two most recent non-social daydreams. The questionnaires were answered by
following a survey link sent within the messages. Participants received the four messages
on one day between 10 am and 10 pm at individually randomized times within four three-hour
blocks (between 10:00–13:00, 13:00–16:00, 16:00–19:00, 19:00–22:00), with the constraint
that consecutive signals were at least one hour apart. The order of the questionnaires
(social, non-social) was also individually randomized for each participant. We randomized
the time and order of questionnaires to prevent anticipation of signals, to sample
daydreams and feelings across a range of times and daily activities, and to counteract
potential order effects and demand characteristics. Measures were kept brief so as not to
unduly interfere with participants’ daily routine.

        <hss>Social feelings</hss>

        Two items, taken from Crocker, Niiya, and Mischkowski (2008), measured the
        positive, other-directed feelings of love and connection. Participants indicated
        how loving (“How loving did you feel before/after your daydream?”) and connected
        with others (“How did you feel before/after your daydream?”) they felt before and
        after their daydream on 7-point scales from not at all to extremely.

        <hss>Non-social feelings</hss>

        Participants indicated how they felt before and after their daydream (“How did you
        feel before/after your daydream?”) on the following dimensions: sad-happy,
        anxious-calm, and excited-bored (reverse-scored). Responses were made on a 7-point
        scale (e.g. 1 = sad, 7 = happy). These items were chosen to measure the pleasure
        (valence) and arousal (activation) dimensions of core affect (Remington, Fabrigar,
        & Visser, 2000); specifically, pleasure (sad-happy), pleasant deactivation
        (anxious-calm) and pleasant activation (bored-excited).

        <hss>Emotional content</hss>

        A single item measured the emotional content of daydreams. Participants indicated
        the emotional content of their daydream (“The emotional content of this daydream
        was…”) on a 7-point scale (1 = very negative, 4 = neutral, 7 = very positive).

        <hss>Relationship quality</hss>

        Three items were used to provide a quality index of the relationship between
        participants and the most central person involved in their daydream. Participants
        rated their general feelings of closeness (“In general, how close do you feel to
        them?”), liking (“In general, how much do you like them?”), and trust (In general,
        how much do you trust them?”) towards the most central person in their daydream on
        7-point scales from not at all to extremely. These items were chosen to reflect
        indicators of high-quality interpersonal connections (Niven, Holman, & Totterdell,
        2012). We combined items to create an overall score for relationship quality;
        internal reliability was high, α = .92.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants attended an individual training session during which they were given a
written and verbal description of daydreaming. A daydream was defined as a series of
connected thoughts and/or images where that mental content is not about whatever mental or
physical activity one is engaged in at the present moment. Participants were told that
daydreams could be brief but should consist of more than a single thought or image. Social
daydreams were defined as daydreams where another (real or imaginary) person or people are
involved; non-social daydreams were defined as daydreams that did not involve another
person or people. Examples of daydreams, including social and non-social ones, were
provided. When participants indicated that they understood what counted as daydreaming,
they were provided with written instructions for the study followed by a demonstration of
the text message with online questionnaire link and verbal explanation of the meaning and
response of each questionnaire item. Finally, participants nominated a date to complete
the study and were free to choose whatever day they liked as long as it represented a
typical day in their life. On the nominated day, participants followed the online
questionnaire link sent via text and, after entering their unique participation number,
indicated their social and non-social feelings before and after their last (social or non-
social) daydream. All five items referring to feelings were asked twice (with reference to
before and after the daydream) but the order of all 10 question items was individually
randomized to minimize response bias. Participants then rated the emotional content of
their daydream, and for social daydreams, completed items indexing relationship quality.
Participants were asked to report on their last social or non-social daydream before each
text message but were not asked about the time lapse between the daydream and reporting
its content. Participants were also asked to provide a short description of the daydream.
Several additional questions regarding the daydream were also asked but were not relevant
to the hypotheses tested here.

<hs>  Response rate</hs>
  ~~~~~~~~~~~~~

Overall, 383 of a possible 404 daydreaming questionnaires were completed (192 social and
191 non-social daydreams) corresponding to a 95% response rate. Participants’ daydream
descriptions were examined by the first author, in line with the definitions given to
participants, to ensure that daydreams were accurately categorized as social or non-
social. Twelve non-social daydreams were excluded from the dataset because they contained
references to other people which suggested that they may have been instances of social,
rather than non-social, daydreams. We chose not to reclassify these as social daydreams
because doing so would have led to an unbalanced design. Therefore, the following analyses
were based on 179 non-social and 192 social daydreams.

<hs>  Were social daydreams associated with increases in positive feelings?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To examine whether social, compared to non-social, daydreams were associated with
increases in positive feelings, we conducted a series of 2 × 2 × 2 (Daydream Type [social,
non-social] × Time [pre, post] × Questionnaire [questionnaire 1, questionnaire 2]) triply
repeated-measures ANOVAs with each feeling state (i.e. happiness, calmness, excitement,
loving and connected) as the dependent variable. The results of these analyses are
presented in Table 1.

        <hss>Social feelings</hss>

        There was a significant interaction between daydreaming type and time on feeling
        loving (F(1, 73) = 14.70, p < .001, ηp2 = .17). Post-hoc repeated measures t-tests
        indicated that participants reported feeling significantly more loving after (M =
        4.86, SD = 1.23) compared to before (M = 4.20, SD = 1.17) social daydreams (t(73)
        = −3.64, p = .001, d = −.39, 95%CI [−.75, −.21]) and significantly less loving
        after (M = 3.70, SD = 1.34) compared to before (M = 3.92, SD = 1.06) non-social
        daydreams (t(73) = 2.06, p = .043, d = .18, 95%CI [.01, .45]). Similarly, there
        was a significant interaction between daydreaming type and time on feeling
        connected with others (F(1, 73) = 14.28, p < .001, ηp2 = .16). Repeated measures
        t-tests indicated that participants reported feeling significantly more connected
        with others after (M = 4.67, SD = 1.23) compared to before (M = 4.22, SD = 1.26)
        social daydreams (t(73) = −3.40, p = .001, d = −.39, 95%CI [−.70, −.19]).
        Participants also reported feeling marginally less connected with others after (M
        = 3.61, SD = 1.28) compared to before (M = 3.80, SD = 1.18) non-social daydreams
        (t(73) = 1.89, p = .063, d = .15, 95%CI [−.01, .38]), although this result was
        statistically non-significant. Overall, social daydreams were associated with
        increased, whereas non-social daydreams were associated with decreased, feelings
        of love and connection (see Fig. 1).

        <hss>Non-social feelings</hss>

        There was a significant interaction between daydreaming type and time on happiness
        (F(1, 73) = 5.72, p = .019, ηp2 = .07). Post-hoc repeated measures t-tests
        indicated that participants reported feeling significantly happier after (M =
        4.91, SD = 1.23) compared to before (M = 4.53, SD = 1.06) social daydreams (t(73)
        = −2.67, p = .009, d = −.33, 95%CI [−.64, −.10]), but not non-social daydreams
        (t(73) = .88, p = .383, d = .09, 95%CI [−.14, .35]). Social daydreams were
        associated with increased happiness but there was no change in happiness for non-
        social daydreams (see Fig. 1). The same interaction effect was not observed for
        feelings of calmness or excitement. However, there was a significant main effect
        of time for these feelings. Participants were significantly less calm after (M =
        4.50, SE = .14) compared to before (M = 4.82, SE = .13) daydreaming (F(1, 73) =
        7.74, p = .007, ηp2 = .10) and significantly more excited after (M = 3.31, SE =
        .10) compared to before (M = 4.20, SE = .11) daydreaming (F(1, 73) = 68.06, p <
        .001, ηp2 = .48). This suggests that daydreaming was associated with decreased
        calmness and increased excitement, which may be indicative of an overall increase
        in the arousal dimension of core affect.

<hs>  Post-hoc analysis: Were social daydreams regulating people’s feelings?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our results indicate that social, but not non-social, daydreams were associated with
increased happiness, love and connection. We were interested in whether this effect might
be regulatory; that is, whether social daydreams might be compensating for low levels of
happiness, love and connection. If that was the case, then we would expect increases in
happiness, love and connection to be observed for participants who scored low, but not for
those who scored highly, on these feelings before daydreaming. To explore this, we created
each participant’s average scores for feelings of happiness, love and connection before
and after social daydreams over the two time samples. We then ran a series of repeated
measures t-tests to examine differences between feelings of happiness, love and connection
before and after social daydreams separately for those ‘high’ and ‘low’ in the associated
feeling before daydreaming. We classified each participant as ‘low’ or ‘high’ using a
median split of their average feeling state before social daydreams. The results were
consistent across feeling dimensions: increases in happiness, love and connection were
only observed for those participants scoring ‘low’ and not for those already ‘high’, on
the associated feeling before social daydreaming. Participants low in happiness felt
significantly happier after (M = 4.54, SD = 1.14) compared to before (M = 3.86, SD = .71),
social daydreaming (t(56) = −4.41, p < .001, d = −.71, 95%CI [−.99, −.39]); participants
low in feelings of loving felt significantly more loving after (M = 4.03, SD = 1.26)
compared to before (M = 3.24, SD = .92) social daydreaming (t(45) = −3.90, p < .001, d =
−.71, 95%CI [−1.20, −.43]); and participants low in feelings of connection felt
significantly more connected with others after (M = 4.20, SD = 1.30) compared to before (M
= 3.04, SD = .99) social daydreaming (t(44) = −5.68, p < .001, d = −.99, 95%CI [−1.56,
−.77]). In contrast, there were no significant differences observed between feelings of
happiness, love and connection, before and after social daydreams for participants that
were ‘high’ on the associated affective state before daydreaming (all p’s > .1) Inspection
of mean scores and 95% confidence intervals also suggests that results for ‘high’ scorers
were not due to a ceiling effect in this group: mean ratings (on a 7 point-scale) and
confidence intervals before daydreaming were 5.47 (95%CI [5.32–5.60]) for happiness, 5.11
(95%CI [4.98–5.31]) for love, and 5.19 (95%CI [5.05–5.34]) for connection. For comparison,
we performed the same set of analyses with non-social daydreams. Levels of happiness from
before and after non-social daydreams were not different for participants low (t(57) =
−.96, p = .340) or high (t(40) = 1.41, p = .168) in happiness before non-social
daydreaming. Participants low in feelings of love and connection before non-social
daydreams did not report significant increases in these feelings after non-social
daydreams (loving: t(59) = −.12, p = .906; connected: t(42) = −1.22, p = .230). However,
participants high in feelings of loving before non-social daydreams felt marginally less
loving after (M = 4.74, SD = 1.04) compared to before (M = 4.99, SD = .57) non-social
daydreams (t(38) = 1.88, p < .068, d = .24, 95%CI [.01, .49]). Similarly, participants
high in feelings of connection felt significantly less connected after (M = 4.36, SD =
1.15) compared to before (M = 4.77, SD = .78) non-social daydreams (t(55) = 3.16, p =
.003, d = .40, 95%CI [.16, .67]). These results support a regulatory explanation of our
findings: the positive emotional outcome of social daydreaming was only found for
participants who would benefit from it the most (i.e. ‘low’ scorers), but not for
participants already experiencing positive feelings (i.e. ‘high’ scorers). The fact that
the opposite pattern of results was observed for non-social daydreams also suggests that
these effects were not a result of regression to the mean.

<hs>  Did the emotional content of social daydreams account for changes in feelings?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We sought to establish whether increases in happiness, love and connection for social
daydreams were attributable to the emotional content of those daydreams.2 Multi-level
modeling (Hox, 2010) was used to examine this possibility because the measure of
daydreaming emotional content was time-varying. We restructured the data so that time
points (i.e. questionnaire responses) were nested within individuals and then ran a series
of multi-level models. First, we confirmed that social daydreams were associated with
increased happiness, love and connection: the fixed effect of time was significant in
models predicting happiness (B = −.29 (.13), t(283) = −2.32, p = .021, ICC = −.15, 95%CI
[−.54, −.04]), loving (B = −.46 (.13), t(281) = −3.66, p < .001, ICC = −.20, 95%CI [−.70,
−.21]), and connection (B = −.48 (.13), t(281) = −4.07, p < .001, ICC = −.20, 95%CI [−.73,
−.23]); the respective feelings were significantly greater after compared to before social
daydreams. Next, we included the emotional content of social daydreams as a predictor in
each model. The emotional content was a significant (p < .001) predictor in all models
indicating that the emotional content of daydreams was positively associated with
happiness, love and connection, before and after social daydreams. After controlling for
the emotional content of daydreams, the fixed effect of time remained significant in
models predicting happiness (B = −.29 (.12), t(282) = −2.54, p = .012, ICC = −.19, 95%CI
[−.52, −.07]), loving (B = −.46 (.11), t(281) = −4.17, p < .001, ICC = −.27, 95%CI [−.67,
−.24]) and connection (B = −.48 (.12), t(281) = −4.07, p < .001, ICC = −.25, 95%CI [−.71,
−.25]), indicating that the association between social daydreams and increased happiness,
love and connection could not be solely attributed to the emotional content of those
daydreams.

<hs>  Did the effect of social daydreams on positive feelings depend on relationship quality?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The measure of relationship quality was significantly (p < .001) negatively skewed
indicating that participants’ daydreams overwhelmingly involved significant others.
Attempts to transform the variable to normalize the distribution were unsuccessful so a
median split procedure was applied (MacCallum, Zhang, Preacher, & Rucker, 2002). We
dichotomized the variable to represent ‘high’ and ‘low’ quality relationships for the
sample: low (n = 186) = 1–5.67; high (n = 198) = 6.00–7.00. We then ran multi-level models
examining whether feelings of happiness, love and connection, were significantly greater
after, compared to before, social daydreams separately for daydreams that involved low,
and high quality relationships. For low quality relationships, the fixed effect of time
was non-significant for models predicting happiness (B = .12 (.15), t(113) = .80, p =
.423, ICC = .05, 95%CI [−.17, .41]), loving (B = −.09 (.15), t(114) = −.53 p = .600, ICC =
−.04, 95%CI [−.41, .24]) and connection (B = −.19 (.15), t(114) = −1.23, p = .223, ICC =
−.08, 95%CI [−.51, .12]), indicating no significant change in feelings from before to
after daydreaming. In contrast, for high quality relationships, the fixed effect of time
was significant in models predicting happiness (B = −.68 (.17), t(118) = −3.94, p < .001,
ICC = −.51, 95%CI [−1.02, −.34]), loving (B = −.82 (.14), t(119) = −5.82, p < .001, ICC =
−.49, 95%CI [−1.08, −.53]) and connection (B = −.75 (.16), t(118) = −4.82, p < .001, ICC =
−.38, 95%CI [−1.06, −.44]), indicating more positive feelings after compared to before
daydreaming. Specifically, after daydreams involving high quality relationships, feelings
of happiness (M = 5.41, SD = 1.42), love (M = 5.43, SD = 1.26) and connection (M = 5.31,
SD = 1.28) were greater than feelings of happiness (M = 4.74, SD = 1.10), love (M = 4.63,
SD = 1.27) and connection (M = 4.57, SD = 1.47) prior to daydreaming. These results
indicate that social daydreams were associated with increases in feelings of happiness,
love and connection, only when participants’ daydreams involved people with whom they had
a high, but not low, quality relationship.

<h>DISCUSSION</h>
----------

We investigated the impact of social daydreams on momentary feelings to explore whether
the positive influence of others on emotional well-being could emerge from the imagination
as well as from real events. We sampled naturally occurring social and non-social
daydreams and associated social and non-social feelings before and after those daydreams
using experience sampling methodology. Because daydream activity is commonly concerned
with the mental pursuit of social goals, we proposed that social daydreams would induce
positive social feelings associated with the imagined experience and underlying social
goals and needs. Our results support this hypothesis; everyday daydreams with social, but
not non-social, content were associated with increases in feelings of love and connection.
Social daydreams were also associated with increases in happiness which may reflect the
tendency for happiness to be a positive emotion linked with social interaction (e.g.
Csikszentmihalyi & Hunter, 2003; Kahneman et al., 2004). Our results suggest that people’s
everyday social feelings are shaped by their imaginary, as well as actual, social worlds,
and that daydreams can be a source of positive other-directed feelings. Importantly, the
possibility that increases in happiness, love and connection were due to the emotional
content of daydreams was ruled out because increases in these feelings were still present
when statistically controlling for emotional content. This suggests that imagining the
pursuit of social goals is not simply a pleasant experience, but also one that is
associated with a similar emotional outcome to that which would occur as a result of
actually pursuing those same goals. Additionally, increased positive feelings were only
observed when the relationship between the daydreamer and most central person in the
daydream was classified as ‘high’, paralleling the pursuit of social goals in reality. In
the same way that different forms of social interaction differentially contribute to
social feelings (Reis et al., 2000), with interactions within close relationships more
likely to elicit positive social feelings (e.g. Laurenceau et al., 2005), imagining close
others appeared to elicit greater feelings of love and connection. This is also consistent
with previous research linking daydreams about close others to socio-emotional well-being
(Mar et al., 2012). Additional analyses support the idea that social daydreams may
function to regulate emotion because increases in happiness, love and connection were
present only when participants were low, but not high, in these feeling before
daydreaming. This pattern of results suggests that social daydreams may have compensated
for deficiencies in social feelings serving the emotional needs of the daydreamer at the
time. In daily life, feelings of social disconnection may act as a cue or trigger to
pursue or attain goals that would alleviate these feelings (e.g. physical contact with a
close other). However, in situations that do not lend themselves to social contact,
daydreams may provide an opportunity to simulate desired contact, which fosters feelings
of love and connection. In this way, daydreams involving close others may function as an
imaginary substitute when close others are not immediately available in reality (c.f.
Maner, DeWall, Baumeister, & Schaller, 2007; Pickett, Gardner, & Knowles, 2004). A
prediction from this is that, relative to non-social daydreams, daydreams about close
others should increase during periods of social disconnection. Future research might
explore this during transitional periods where socio-emotional needs are likely to be
pertinent (e.g. homesickness, Watt & Badger, 2009), and investigate whether social
daydreams can promote adaptation. Of course, social daydreaming may also become
dysfunctional if it comes to unduly displace actual social interaction (Somer, 2002), but
future studies will need to ascertain for whom social daydreaming is adaptive or
maladaptive and under which circumstances. Future research might also explore the
feasibility of encouraging certain types of social daydreaming as a means of enhancing
well-being and personal relationships. Daydreaming and thinking about close others have
previously been identified as emotional regulation strategies, although not in
conjunction. Daydreaming has been reported as a strategy to relieve boredom (e.g. Fisher,
1987; Singer, 1966) and as an emotion-focused coping strategy (Endler & Parker, 1990), and
recurrent daydreams have been seen as a source of comfort in times of distress (Greenwald
& Harder, 1997). Similarly, thinking about close others is reported as an example of a
cognitive emotion regulation strategy (Parkinson & Totterdell, 1999), and imagining close
others can regulate negative emotions about an impending stressful event (McGowan, 2002)
and alleviate the distress of recalling a distressing memory (Selcuk, Zayas, Günaydin,
Hazan, & Kross, 2012). Our results support and extend these findings by providing evidence
that daydreaming about close significant others may be an adaptive emotion regulation
strategy to alleviate feelings of social disconnection in daily life. Previous research
regarding the link between daydreaming and emotion well-being has associated daydreaming
with negative mood and depressive symptomology (e.g. Carriere et al., 2008; Giambra &
Traynor, 1978; Smallwood, O’Connor, Sudbery, & Obonsawin, 2007) but other research
suggests that this relationship may depend on factors such as the thought content of
daydreams and individual differences (e.g. Andrews-Hanna et al., 2013; Poerio et al.,
2013; Ruby et al., 2013). The current research indicates that the association can
sometimes be positive, depending on whom the daydreamer focuses, how the daydreamer feels
at the time, and which emotions are examined. Although current findings are consistent
with the idea that social daydreams function to up-regulate social feelings, our
correlational design prevents causal interpretations from being made. We cannot confirm
whether feelings of social disconnection caused participants to imagine close others which
then caused them to feel happier, more loving and connected with others. If social
daydreams were functional for up-regulating feelings, then low levels of happiness, love
and connection should predict the occurrence of social, rather than non-social,
daydreaming. However, because participants reported on either their last social or last
non-social daydream rather than their last daydream of any type, we cannot shed light on
this issue. A future study might address this shortcoming by experimentally inducing
feelings of social disconnection and examining the social content of daydreaming activity
during a subsequent task. Another limitation is the use of retrospective reports for
daydreams, associated feelings before and after daydreaming and measures of emotional
content and relationship quality. Participants reported on their most recent social or
non-social daydream at four quasi-random intervals within four, three-hour blocks, but
were not asked to estimate how long ago their daydream was experienced. The time between
experience and recall may have influenced the validity of reports in ways that we cannot
control for or explore (Bradburn, Rips, & Shevell, 1987). However, given that daydreaming
is thought to occupy between 30% and 50% of waking thought (Killingsworth & Gilbert, 2010;
Klinger & Cox, 1987), we suspect that the interval between experience and recall would
have been relatively small (i.e. minutes rather than hours) and hence the potential
effects on accuracy would also be small. Another possible consequence of the use of
retrospective reports, particularly with reference to feelings before and after
daydreaming, is that our results may reflect a demand characteristic or participants’ own
lay theories concerning how they should have been feeling before and after social and non-
social daydreams. Although we cannot rule out these possibilities, we took steps to
minimize potential demand characteristics. Pre- and post- daydreaming feeling measures
were individually randomized meaning that participants could have completed the questions
concerning their feelings on each dimension (happy, calm, excited, loving, connected)
referring to before and after their last daydream (i.e. 10 items) in any possible order.
In addition, each question (e.g. “How loving were you feeling before your daydream?”) was
completed on participants’ smartphone screens individually such that participants were
unable to view their previous responses. If participants reported emotion change to fit
with their possible views on the study, then they would have had to remember their
responses for each individual measure to use as a reference point for reporting feeling
change. Although we cannot be certain that lay theories about the influence of social and
non-social daydreams on social feelings did not influence participant responding in the
current study, this issue has been addressed in previous research (Poerio et al., 2013)
which found no evidence to suggest that participants believe that daydreaming has either
predominately positive or negative effects on mood, or that lay beliefs are consistent
enough across participants to systematically bias results. Although this does not
specifically shed light on lay theories concerning how social daydreams relate to social
feelings, there is no reason at present to suspect that people associate social daydreams
in particular with increases in positive feelings. To address concerns associated with
retrospective sampling of daydreaming and affect, a more intensive time-sampling approach
could be used in future research where participants report on current daydreaming activity
and current affective states at separate time points. However, whether this methodological
benefit would outweigh the additional participant burden would need careful consideration
(Stone, Kessler, & Haythornthwaite, 1991). Overall, the present research represents an
important first step in establishing and exploring how social daydreams shape and regulate
social feelings in daily life. The idea that positive social interactions and
interpersonal relationships are vital for well-being is well accepted (Baumeister et al.,
2012; Diener & Seligman, 2002; Holt-Lunstad et al., 2010). However, the current findings
offer a broader conception of the role that others play in socio-emotional well-being by
demonstrating that the influence of others on positive emotion can emerge from the
imagination as well as from real events. Our findings indicate that love can really be a
triumph of the imagination, albeit not in the sense originally intended in the popular
quotation.3 Although research on daydreaming has experienced a resurgence in recent years
(Callard, Smallwood, Golchert, & Margulies, 2013) the field would benefit from examining
social aspects of daydreaming to uncover the ways in which people’s imaginary, as well as
actual, worlds contribute to their socio-emotional functioning.

<h>CONFLICT OF INTEREST</h>
--------------------

The research was conducted in the absence of any commercial or financial relationships
that could be construed as a potential conflict of interest.


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<ART>Making space for India in post-apartheid South Africa: Narrating diasporic subjectivities through classical song and dance
================================================================================

Authors: Jen Dickinson
DOI: 10.1016/j.emospa.2014.05.001
Year: 2014  |  Pages: 32-39
ASJC codes: 3205, 3207
Keywords: Bollywood, Hometown associations, Indian diaspora, Social practice, South Africa, Transnational affect

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background/purpose: Diasporic associations and hometown groups fuel transnational exchanges and circulations. Their role has mostly been understood in terms of broader calculative agendas related to ethnic and national cultural politics. In South Africa, classical Indian singers, dancers and instrumentalists are an important part of these transnational landscapes. This paper focuses on the individual actors giving shape to these flows, and explores how a range of subjectivities is entangled with the materialities and forces present in classical performance spaces. Methods and results: Drawing on fieldwork in Durban, South Africa, it explores how, and why organising actors assemble the matter of classical performance spaces. The paper also explores interconnections to Bollywood as another emergent diasporic site both in tension and accord with classical Indian performances. Conclusion: Drawing from a feminist social practice approach, this paper argues that diaspora associational life is assembled through agents negotiating different gaps and discrepancies arising from the material and affective inhabitation of diasporic worlds.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

On the 9th of May 1993 after a gap of over four decades, diplomatic relations between
India and South Africa were formally restored. Since then, the gradual transnational
(re)materialisations of South African Indian1 life have arisen out of intersecting sets of
commitments to develop closer ties with India. These include new desires of the Indian
government to engage people of Indian origin in South Africa as part of its overseas
diaspora strategy, the growing role of South African Indian diaspora entrepreneurship, and
the increasing influence of Indian and South African Bollywood promoters and film
producers (Dickinson and Bailey, 2007; Ebrahim, 2008; Munjal et al., 2013). Amidst these
activities, various South African Indian conservative religious and cultural associations,
formed during the apartheid-era system of separate development, are developing closer ties
with India through transnational circulations of classical Indian performers, dancers and
musicians. The term ‘South African Indian’ expresses a positionality that is constituted
through a multiplicity of competing identifications, and expressed and negotiated in a
diverse range of interconnected transnational spaces (Landy et al., 2004). Yet, as Hansen
(2005) has argued, diaspora associations draw upon classical Indian music and dance to
negotiate, order and control the boundaries and expressions of Indian diasporic
identities, contributing to new contestations and dilemmas surrounding South African
Indian ethnic, national and gender politics (see also Ganesh, 2010; Radhakrishnan, 2005;
Ramsamy, 2007; Rastogi, 2008; Vahed and Desai, 2010). In addition to being locations for
negotiations over categorical politics, South African Indian classical performances are
also sites of affective and embodied experiences. The quote at the start of this paper is
taken from a description of a performance by an Indian Carnatic singer at a 2004 Swami
Thygaraja music festival sponsored by the Indian Academy of South Africa, an association
involved in the promotion of closer ties between South Africa and India. The description
alludes to deeply embodied and felt experiences of being enthralled by the music's sonic
affects. Whilst there is important critical work that has been done in thinking through
the implications of South African Indian diaspora associations' transnational connections
for collective negotiations of Indianness (e.g. Ganesh, 2010; Radhakrishnan, 2005), this
paper aims to critique, and open out, these discussions by exploring classical Indian
performances as a specific site for the production of a more ambiguous and complex self.
To do so, it shifts the focus of analysis from the types of diasporic identifications
represented by classical performances towards the spaces themselves; and examines how
individual organising actors relate to the human and non-human materials, forces and
elements assembled therein. I use the case study of South African Indian associational
life to call for scholars of diaspora and hometown associations to interrogate and engage
with the wider turn to practice and performativity in the humanities and social sciences
in order to enliven critical understandings. Diaspora actors are often understood as
possessing broader calculative and strategic agendas related to political identity
discourses, positions and practices in the homeland (Quinsaat, 2013). Whilst recent work
on hometown associations has begun to produce more nuanced understandings of the range of
subjectivities produced through the activities of diaspora and hometown associations
(Mercer et al., 2008), this paper explores how an affective, relational, social practice
understanding of migrant subjectivities can extend these theorisations. To do so, it is
guided by feminist scholarship that explores the material and affective dimensions of the
‘body-subject’ (Grosz, 1994; Probyn, 2004). Feminist interrogations that view body-
subjects as assemblages or collections of, in Barad's (2001) terms, ‘intra-acting’ non-
human and human components, have reoriented understandings of identity away from pre-
existing named and sorted categories towards the multiple forces and intensities that both
constitute and circulate between bodies and “provide the backdrop to and are active in
producing what comes to be understood as ‘a’ subject” (Colls, 2012: 439). In this
understanding, subject-formation is a multiple process of becoming, rather than being, one
that is not wholly predefined by neither categorisations, nor stable and finished. Such a
reading is useful for exploring the multi-dimensional agencies that inhere in
associational life; and second by providing openings for further understanding the
contingencies, discrepancies and ambivalences involved in marshalling and cajoling
transnational circulations and flows of bodies and materials through sites of
associational life. In the next section of the article I will describe briefly previous
approaches to diaspora associations, before outlining debates that have considered the
relationship between affect and migration in the production of mobile subjectivities.
Following an overview of research into South African Indian transnationalities, the
discussion in the first half of the analysis draws attention to how organising actor's
subjectivities emerge from and choreograph the materialities of classical Indian
performance spaces. Of specific interest are the matters and forces that contribute
towards the making of perceived bonds between organisers, audiences and performers. The
paper then adds a further layer to questions of complex subjectivities by discussing the
overlaps between classical performance sites and the broader array of transnational sites
through which ideas of India are produced and negotiated, focussing specifically on
Bollywood. Of interest are the points of tension and accord between Bollywood and
classical Indian performances, and the subjectivities that emerge in their negotiations.
In doing so, the paper hopes to raise some questions for future scholars of diaspora
associations to engage with and mark new directions for study.

<h>THEORISING DIASPORIC ASSOCIATIONAL LIFE</h>
---------------------------------------

Diasporic associational life, such as festivals, music and dance performances, meetings,
religious expression and worship, is a site for the production of transnational and
translocal belongings (Mercer et al., 2008). It provides a platform for the staging and
reproduction of ancestral cultural traditions that can act as mechanisms for the
expression of the dominant device of diaspora: the recreation of a homeplace in new
settings (Gal et al., 2010). These mechanisms are of course also deployed by individuals
in the transnational social spaces of their everyday lives (Ley, 2004); a key difference
is that diaspora associations and groups employ such spaces in order to perpetuate a sense
of a collective identity sustained by reference to common memories or myths about an
ancestral homeland's location, history and achievements (Tölölyan, 2010). Analyses of
diaspora associations have most commonly focused on the production of long-distance
national identifications as a discursive political process (Gal et al., 2010). A wide body
of scholarship explores the agency of diaspora associations in the politics of their home
countries, attending to the dynamics of home-making involved (Brinkerhoff, 2011; Lyons,
2006; Sheffer, 2003). Related work focuses on the ways in which associations, and the
organising elites involved, can direct flows of remittances, resources and knowledge in
order to reproduce their own economic and political agendas or positions (Mohan, 2006).
Scholarship exploring Hindu associations in North America perhaps exemplifies this
approach, drawing attention to the transnational practices that allow diaspora elites to
influence a range of Indian political and economic concerns, such as remittance
activities, homeland identity preservation, and sectarian nationalist politics (Biswas,
2004; Mathew and Prashad, 2000). This kind of work is valuable in understanding the
contested nature of the practices of diaspora associations and the dilemmas over competing
identities they call to light. However, recent scholars of African diasporas have pushed
us to reconceptualise the role of associations in mobilising around the shared and
contested predicaments that arise from ruptures with home and the forging of local
socialities (Mercer et al., 2008). Studies focussing on the convivialities, obligations
and the gendered subjectivities on which associations' practices turn (Faria, 2011;
Kleist, 2010; Mercer and Page, 2010) have dislodged dominant scholarly assumptions that
have in the past essentialised diasporic and hometown associations as divisive, or even
dangerous. By drawing attention to the ruptures and inconsistencies involved, what ensues
is an understanding of the subjectivities underpinning diaspora elites' mobilisations of
homeland ties as differentiated and multiply located. Whilst there is still further
critical work to be done in understanding the intersectionalities of identity that inhere
in transnational socio-geographic flows and connections – and their politics – there is
also room to consider an even more expansive notion of diasporic selfhood, one that is
attuned to the affective forces of social life that are weaved from a distributed range of
experiences and material exchanges that cannot be “cleanly or clearly cleaved into a set
of named, known and represented identities” (Anderson and Harrison, 2010: 10). My use of
the term ‘affective’ here is drawn from previous work that articulates the embodied,
physiological states that enable people to recognise themselves as subjects in ways that
are not wholly predefined (Massumi, 2002). Most studies of diaspora associations have
focused on organising actor's agency in terms of broader calculable economic and political
agendas (such as development, remittances or hometown politics), and the categorical
identities that underpin them. But, as the above scholarship emphasises, agency must also
be understood in terms of its affective dimensions, ones that are made through a range of
desires and intimacies (Berlant, 2000). Understandings of diaspora associations need to
also consider what other kinds of forces motivate the organising individuals that comprise
diaspora associations, and the roles those forces play in transnational exchanges and
circulations. Holding open understandings of the self rather than privileging pre-defined
concepts or symbolic categorisations has become central to deepening understandings of
migration. Specifically, renewed emphasis has been placed on the performances and
practices of material circulations across transnational and translocal space (Coe, 2011;
McKay, 2007; Tolia-Kelly, 2004), and on the complex register of emotional experiences and
affects that arise and are transformed through transnational circuits and connectivities
(Andrucki, 2013; Boehm and Swank, 2011; Christou, 2011; Ho, 2009). This work mirrors
broader geographical scholarship on the range of localities through which multiple co-
present relations are entangled with the production of self-in-society (Kraftl and Adey,
2008; Stewart, 2007; Thien, 2005). Conradson and Mckay (2007) affirm the importance of the
affective states that accompany the dialectics of mobility and emplacement, but also the
instabilities such constructions call forth. The corporeal intensities of the
transnational and translocal circulations and encounters with an array of multiply-located
bodies and materialities, they argue, are linked to the formation, and also breakdowns, of
individual and community selfhoods (see also Faier, 2013). Two connected interventions in
cultural studies complement this work. First, scholarship examining musical performances,
rituals and festivals organised by diaspora cultural associations offers insights into the
ways that migrants move, feel and experience a dynamic and plural conception of home
through animated sites and embodied practices (Farah, 2005). This work mirrors the broader
turn towards practice-orientated approaches to music and performance that escapes
categorical identity fixings by asking what music does rather than what it represents
(Revill, 2005; Wood et al., 2007). The social practices and sensory forms associated with
diasporic musical performance, such as narrative themes, linguistic registers and material
styles, as Gilbert and Lo (2010) argue, “performs and activates a wide range of links with
homeland and hostland” (151) and act as sites of “polycultural exchange but also as a zone
of heightened affect” (155) where imagined pasts and futures can be expressed. Whilst many
have argued that diasporic music and song are consciously engineered towards wider
strategic goals, this work highlights the sensory experiences and meanings that bring
diasporic cultural forms into being and give them shape. This work does not disregard
collective inscriptions of homeland imaginaries, but fleshes out the underlying embodied
practices and affective capacities that bring those inscriptions into being and also work
to destabilise them. Second, and relatedly, scholars of queer diaspora have drawn
attention to the multiple performance practices that contest, negotiate, and heighten
ideas of diasporic belonging (e.g. Manalansan, 2003). Gopinath's (2005) work on South
Asian public cultures, for example, unsettles the connections between South Asian
diasporic culture and the (re)production of normative nationalisms, arguing that a range
of feelings, emotions, dreams and subject positions are realised through (dis)affinities
with an array of socio-spatial identifications. By identifying the contexts in which
diasporic nationalisms begin to break down, and the unstable assumptions on which they are
based, this work escapes categorical fixings by retheorising diasporic subjectivities as a
rich assemblage of sites, practices and materialities produced through multiple locations
and temporalities.

<h>SOUTH AFRICAN INDIAN ASSOCIATIONAL LIFE</h>
---------------------------------------

Indians in South Africa have multiple historical origins, producing a complex of
identifications that are far from homogenous. Migration from India to South Africa began
around 500 B.C, intensifying under Natal's indentured sugar plantation labour system in
the nineteenth-century (Kuper, 1960: 1). Approximately 152,000 linguistically (Telugu,
Tamil, Hindi, Urdu) and religiously diverse (variants of Hinduism, Christianity, Islam)
indentured labourers arrived from the Madras Presidency and Northern Indian districts
between 1860 and 1911 (Lemon, 2009: 131). Approximately 30,000 ‘passenger’ traders from
Gujarati villages followed, part of the long established Indian trader network that
connected East Africa, East Asia, Mauritius and the West Indies (Bhana and Brain, 2000:
36). ‘Passengers’ were equally diverse linguistically (Urdu, Gujarati) and religiously
(variants of Hinduism, Parsi, Christianity, Islam) (Kuper, 1960: 7–8). Their descendants
now number some 1.3 million, approximately 2.6% of the South African population
(Statistics South Africa, 2010). In colonial and tapartheid Natal, classical Indian song
and dance came to play a particularly important role in sustaining the different Indian
vernacular communities and promoting ties to India. According to Bhana and Bhoola (2011:
18), associations were based around promoting so-called ‘traditional’ Indian values: the
vernacular languages, correct behaviours and rich cultural and historical traditions of
their region of origin. Some examples cited by Bhana and Bhoola include the Arya
Pratinidhi Sabha (formed in 1925) supporting Hindi teaching and various Gujarati Hindu
associations promoting the traditions and vernaculars of Gujarat, such as the Surat Hindu
Association (formed in 1907). By the mid to late twentieth century, the significance of
music in maintaining Indian regional identities was further heightened by the decline of
other traditional emblems of Indianness, such as language and caste consciousness (Ebr-
Vally, 2001). The strictures of apartheid played an important role in this process as the
vernaculars associated with these broader regional distinctions disappeared almost
entirely with the enforced teaching and use of English in Indian schools (Landy et al.,
2004). Furthermore, different caste or regionally-focussed cultural associations pooled
resources to sustain Indian vernacular traditions, leading to a redefinition of Indianness
within broad regional, linguistic and religious parameters (Bhana and Bhoola, 2011). Bhana
and Bhoola describe how this was the case for the multiple Gujarati Hindu communities in
1943 with the formation of the umbrella organisation Kathiawad Hindu Seva Samaj (KHSS),
and again in 1993 with the merger of the KHSS with the Surat Hindu Association and the
Saptah Mandir into the Gujarati Sanskruti Kendra. Broadly defined, Indian vernacular
traditions have remained the basis of a loose, shared sense of community, which continues
to be promoted in the post-apartheid period by the associated cultural group through their
transnational circulations of Indian performers (Hansen, 2005). Although India is
materialised in the lives of many Indian South Africans through performing arts
programmes, Bollywood, food, clothing, festivals and increasingly heritage tourism, most
South African Indians have little interest in claims that they belong to an Indian
diaspora (Landy et al., 2004). Whilst diaspora associations continue to promote closer
ties to India through traditional performances, rituals and festivals, for the majority of
South African Indians, identification with India as a place of deep-rooted ancestral
connection became obsolete over hundred and fifty years of indenture, permanent settlement
and apartheid (Rastogi, 2008). The Indian government placed international sanctions on
trade and domestic travel between 1963 and 1993, severing South African Indian's material
flows and connections, and their spatial association with particular Indian locales (Landy
et al., 2004). Furthermore, during the later stages of apartheid there was an attempt by
some associations to shed Indianness in favour of a broader black struggle/liberation
consciousness (Desai, 1996). The descendants of the original migrants have long considered
South Africa their permanent home: in 1960, 95 per cent of the South African Indian
population were born in South Africa (Ginwala, 1985: 3). Scholarship of contemporary
Indian South African diaspora associational life has primarily focused on the role of
classical Indian song and dance in the processes of ethnic boundary (re)making, drawing
attention to contestations surrounding the authenticity, symbolism and identity politics
associated with particular cultural forms (Kaarsholm, 2011; Vahed and Desai, 2010). Recent
work has also demonstrated the complex positioning and articulation of Indian
transnational life within the disciplinary tenets of faithed, racialised and gendered
South African nationalist discourses (Radhakrishnan, 2005; Vahed, 2005). However, to focus
on diaspora associational practices solely in terms of broader identity politics would be
to miss the ways that diaspora associational practices take shape in relation to the
heterogeneous elements and materialities of bodies, technologies and places that comprise
them. In most cases, South African Indian associational life has been studied as a source
of controversy, with scholarship primarily concerned with the impacts of associations'
activities rather than with the physical spaces themselves per se. One exception is
Radhakrishnan's (2003) account of how movements, embodiments and affects of diasporic
performances attempts to, but also undermines, broader goals of resolving appropriate
performances of Indian authenticity with the tenets and demands of multicultural citizenry
in the Rainbow Nation. Radhakrishnan's study is instructive because it makes a good case
for why there ought to be an affective reconceptualisation of cultural spaces and
performance. If we are to properly understand the role and significance of musical
performances for the elites concerned, then there needs to be a move towards an approach
that appreciates the multifaceted constitution of their diasporic selves.

<h>METHODOLOGY</h>
-----------

The present paper emerges out of a wider ethnography examining contemporary South African
Indian transnational connections conducted in two periods of fieldwork in KwaZulu Natal
Province, South Africa in 2004 and 2005. Although 26 participants (including academics,
local officials, community activists and South African Indian newspaper and radio-station
staff) contributed to the overall study, the analysis in this paper is based on fourteen
interviews with the organisers of seven Indian South African Hindu associations involved
in promoting closer ties between India and South Africa.2 In order to capture those with a
strong desire to propagate ancestral Hindu cultural traditions, interviewed
representatives were those who participated regularly in the outreach and social events
promoted by the Indian Government's KZN-based branch of the Indian Council for Cultural
Relations (ICCR). Interviewees represented the heterogeneity of South African Indian Hindu
communities (Tamil, Gujarati, Telugu), reflecting the background of associations with
strong connections to India. I also conducted twelve interviews with local government
officials, Indian high commission staff and attendees at events. The fieldwork also
involved extensive observational work, attending, for example, local events, celebrations
and public meetings organised by diaspora associations. As part of my research, I
interviewed several of the organisers and attendees before, during and following an event
to capture their impressions. Interview and observation work was supplemented by visual
and textual analysis of news articles, promotional material, reports and websites. The
research took a narrative approach to the analysis of interview, observational and textual
material in order to explore the motivations, discourses and technologies of diaspora
associational practices. A narrative analysis aims to capture an individual's process of
story-telling as they attempt to imbue their recollections with significances (Riessman,
1993). Narration is a process of story-telling at particular biographical and historical
moments, capturing a person's interpretations within contexts and conventions that include
not only the broader political and economic milieu but also the social contexts of the
interview itself (Plattner and Bruner, 1984). In constructing narratives, Sandelowski
(1991) argues, “events are selected and then given cohesion, meaning and direction; they
are made to flow and are given a sense of linearity and even inevitability” (163). Using
such an approach, analysis of interview and textual materials involved examining the ways
respondents portrayed themselves and others, how individuals constructed past and future
life events, taking note of how respondents explained their thoughts and feelings, and
taking into account the social context of the interview itself.

<h>ASSEMBLING AND EXPERIENCING INDIAN CLASSICAL PERFORMANCES</h>
---------------------------------------------------------

After a meal at a nearby restaurant, Vinod3 (male, late 50s), his wife, daughter and I get
into a car to leave to attend a classical Kathak performance at Kendra Hall in Durban by
Shri Abhimanyu Lal. In the car, Vinod, who has been closely involved in promoting Indian
classical song and dance since 1993, chattered excitedly about the roots of Kathak in
Hindu scripture, pausing every now and then to tell me about the difficulties of getting
performers from Gujarat to Natal because of apartheid-era restrictions. Vinod felt that
the lifting of diplomatic restrictions had opened up a sense of opportunity. He argued
that it “was a new experience for us to have India at our disposal … we had to take
advantage of this”. As we got out of the car and entered the main hall, decorated with a
red carpet, twinkling lights and strings of chrysanthemums, Ramesh (male, late 60s) greets
us, pointing out the design of the dome and the pillars. The hall, he explained, had been
built over two years by a team of Indian artisans, or karigars, and felt, he said, “like
our own bit of India in South Africa”. Once we arrived, we joined the buzz of the crowd,
who were milling around the entrance styled impeccably in saris, sherwanis and kurtas, so
that Vinod and his wife could catch up with the latest gossip with their acquaintances
before the evening's events began. The emotions, materialities, and visceral experiences
that saturate musical and artistic performances are the focus of this section. In the
narrative that follows, I trace organising actor's recollections of participating in, and
creating, Indian classical musical events, connecting individual and shared experiences of
the materialities and embodiments of musical forms to the production of organising actor's
subjectivities. Ramesh, Vinod, and other key actors like him in Durban's Hindu
associations, have been involved in formulating closer ties between India and South Africa
since the resumption of formal diplomatic ties in 1993. These opportunities have emerged
from the Government of India's diaspora outreach strategies, which both promote and
regulate cultural flows. 48% of the South African Indian population live in the Ethekwini
municipality, which encompasses the former Indian townships of Chatsworth and Phoenix, and
around 80% live within the broader province of KwaZulu-Natal (Statistics South Africa,
2010). Under apartheid's Group Areas Act, Indians were forced to live in circumscribed
parts of Natal (Maharaj, 1997), and whilst the lifting of apartheid restrictions and
processes of desegregation have seen out-migration to other provinces, Durban remains a
hub for classical Indian performing arts. In 1996, the Durban branch of the Indian
Ministry of External Affairs' Indian Council for Cultural Relations (ICCR) was
established, and has been central to the organisation of an intensive programme of
India–South Africa cultural exchanges. In addition to such cultural programming, often
organised in collaboration with local diaspora groups, the ICCR have organised numerous
delegations and bilateral arts agreements. In 2010, the year of the arrival of the first
indentured sugarcane labourers from India, a mini Pravasi Bharatiya Divas (Overseas Indian
Day) was held in Durban with the aim of marking and building upon the city's historic
links with India (Singh, 2011). Due in part to these efforts, circulations of classical
Indian performers between India and South Africa have dramatically accelerated since 1993.
Amongst migrant populations, music and dance may be used to recreate the culture of the
past, but it is bound up with maintaining group identity through evoking connections and
memories of a common homeland or place, allowing, notionally, a return (Baily and Collyer,
2006). Like many similar classical performances (Landy et al., 2004), the Kathak
performance at Kendra Hall described above emerged out of a desire to bolster Indian
vernacular identities. Vinod explained that he felt compelled by a sense of obligation to
help promote a wider interest in Gujarat for those whom he felt were “losing touch with
their roots”. He explained, “if we lose the language, we lose our culture and our
community”. Yet, the vignette above also illustrates that the reproduction of collective
identities are about much more than the performances themselves and the wider body of
meaning they signify; they are saturated with a multidimensional spatial and temporal and
array of objects, memories, experiences, events, materials, peoples and relationships that
together coalesced into a wider performance environment. Many organising actors recounted
how the multi-sensorial presences of classical arts performances provided a route to an
embodied sense of wellbeing. One evening, I sat with Venita (female, 50s) over tea and
sweets discussing the Kathak performance at Kendra Hall. Although such performances are
related to the bolstering of vernacular identities, such spaces are also imbued with an
experiential value. Most organising actors I met expected to feel content and happy in
classical performance spaces. When speaking of her experiences, Venita for instance
recounted that “I can just relax and enjoy the music … being dressed up”. In addition to
its experiential value, many respondents felt that performance spaces were an important
part of their social lives. The Indian community as an over-arching socio-legal construct
was introduced and institutionalised during apartheid's system of separate development,
during which period dense, tight-knit social networks developed that were based around
intersections of religious, regional and class identities (Kuper, 1960). Contemporary
transnational landscapes connecting South African Indians to different regions of India
reproduce these social forms, even if the underpinning vernacular languages have
disappeared (Vahed and Desai, 2010). Festivals, performances and events were where many
organising actors expected to meet old friends and acquaintances based on these existing
social networks, and share stories about family life and achievements. Venita described
the Kathak performance as “one of the few times I can spend with my husband, meet up with
our friends and catch up on the family gossip … I would say that is the main reason I
went”. The type of social network reproduced depended on the type of performance attended.
More regionally specific cultural programming was where organising actors would meet
friends and acquaintances that shared linguistic commonalities. An organised visit by
dancers from a famous Tamil Bharatnatyam school would provide opportunities for
socialising with friends and acquaintances from within the Tamil community. Since a
broader South Indian diasporic identity developed under the Indian cultural institutions
of apartheid (Ganesh, 2010), many Telugu Indians would also attend. The social relations
enacted in these spaces often also encompassed adult children, who might have been
schooled in regional Indian performing arts by their parents. For instance, I met Saroji
in 2005, along with his daughter Pritty, at a classical South Indian Bharatynam dance
recital he had organised. Pritty (early 40s) had trained in the dance as a teenager.
Whilst she left KwaZulu Natal to train as a doctor in Cape-Town four years ago, she often
returned to Durban to attend Bharatnatyam performances and festivals with her parents.
Asking why she attended, she said: “I like to see the dancers, their clothes, the makeup,
the ways they move their hands and how they place their feet, just like I was trained”. In
contrast, bigger festivals such as ‘Melodies of India’ (2004), amongst others, were
designed to showcase a range of classical Indian performances from different regions of
India, but might also include more contemporary music such as Bhangra, a hybrid cultural
form that emerged from Punjabi diasporas in the United Kingdom but whose popularity has
spread elsewhere in the diaspora. Actors from across the spectrum of South African Indian
associations would be invited, even if their associations weren't specifically involved.
These spaces also produced considerable overlaps between Hindu and Muslim communities,
because of the political dynamics of apartheid and intersecting trajectories of migration
(Kaarsholm, 2011). Muslim Gujarati's might attend a performance by Gujarati Kathak
dancers, even though Kathak is ostensibly based on Hindu scriptures, because this was a
cultural form promoted under apartheid and something they grew up with. Conversely, Vahed
(2005) has shown how the Islamic festival of Muharram in South Africa, known pejoratively
by the white authorities as ‘Coolie Christmas’, incorporates Hindu rituals and scriptural
elements through broader constructions of a unified Indian identity as a base for
political mobilisations. The social aspects of classical performances allow people to
attach a range of significances and values to the performances beyond representations of a
community, or a place. This is also what motivates Krish (male, 50s). For him, the
physical minutiae of the performances are what matters more than what the performance
symbolises, because it helps entangle him in feelings of mutuality with others watching
the performances. Discussing a visit by some Indian Kuchipudi dancers, Krish said “you
feel close to people when you go to these performances because we all appreciate the
effort that has gone into doing things right”. The specific content of the performances
allows collective recognition of cultural forms and finesse, and in doing so generates
ideals of shared enjoyment and common purpose. Krish and Pritty are examples of some of
the ways that relationships to the different physical and material properties of diaspora
performances allow the reproduction of South African Indian social life, often over
several generations and across differences. Organising actors developed performances not
only to maintain a range of socialities and relationships, but also to take advantage of
the burgeoning opportunities to be captivated by seeing performances live. In the spring
of 2005 I attended a performance by Shobana Rao, a ghazal singer and her troupe from New
Delhi. After the performance, I caught up with Hitesh (male, late 50s), a South African
Indian who had organised the performance and invited me along. After the show had
finished, people streamed out of the hall, discussing animatedly the performance they had
just experienced. The music's stylistic tropes generated a buzz between audience members
as they discussed the more populist, rather than purist, rendering achieved by Shobana and
her musicians through the lightness of the ghazals' composition. They also pushed at
individually felt experiences and sensations. Hitesh had “felt happy just listening to the
individual notes of the Indian ghazals … watching someone play the tabla with skill and
precision”. For Hitesh, and others, this particular ghazal performance was not merely a
symbolic representation of India, but enabled engagements with the diverse, sonic
presences that animated this particular performance. Whilst the ghazals staged here
conserve ideas of Indian traditions, this is not a place-bound essentialisation of India.
It a much more distributed manifestation that comprises experiences and sensations arising
from relations to the objects, people, movements and the sonic properties of its physical
(re) production and practice in specific sites. Affective experiences and relationships
were also central to the production of the self as a knowledgeable cultural authority.
Although the cultural politics of South African Indian diaspora associations allow actors
to reproduce their elite positionings (Hansen, 2012), these also have emotional
dimensions. During my fieldwork, Krish had organised a performance by vocalist and
instrumentalist M. Balamuralikrishna because “I wanted everyone to have the same awe
inspiring experience of seeing one of the great Carnatic playback singers in the same
room”. In describing Balamuralikrishna's performance after the event, Krish said “I could
tell that everyone enjoyed feeling connected to our spiritual roots. It made me proud to
be able to provide that for them”. Accommodating a perceived desire amongst South African
Indians for traditional experiences, performances reflected elites' desires to demonstrate
to others that they could source appropriate cultural forms, but also that they were best
able to guide the affectual basis of relationships to India. Nitin (male, late 70s) for
instance stated that: [my] task is to bring India to the vast majority who won't be able
to go, and even if they do go, they won't to be able to source Indian culture in true form
… I feel it is my job to provide the right experiences for others At the same time that
building transnational exchanges were a way of controlling affects felt, they also gave
elites like Hitesh and Nitin a feeling of accomplishment in transforming their material
practices of transnational exchange into a tangible, durable good that helped South
African Indians achieve some degree of affectual knowledge. The value of cultural
performances for Hitesh and Nitin lay not only in their own experiences of classical
Indian performances, but also in their interpretations of the affects achieved in other
people.

<h>NEGOTIATING INDIAN CLASSICAL PERFORMANCES</h>
-----------------------------------------

As the above section demonstrates, elites frame classical Indian performances around a
complex, and ambiguous range of subjectivities. But classical performances are just one of
a set of interconnecting sites in which Indianness is materialised in South Africa (Landy
et al., 2004). These also include online worlds, literature, comedy, clothing and food
consumption practices, and leisure spaces such as Bollywood films and entertainment shows.
Since the end of apartheid, contemporary Bollywood films and entertainment shows (where
actors, musicians and singers appear together to recreate a film, scene or dialogue),
particularly those that are styled to appeal to the North American Indian diaspora,4 have
acquired increasing salience as a public space for transnational materialisations of
India. With the growth of modern South African Indian diasporic dispositions that
encompass sites in India, North America and afar, Bollywood, as Hansen (2005) has noted,
also threatens the integrity of the South African Indian experience provided by diaspora
associations. In this section I examine the porosities, circulations and overlaps between
classical performance spaces and Bollywood as a means of exploring further the
entanglements between organising actor's diasporic subjectivities and material practices.
There are important overlaps between classical Indian song and dance and the contemporary
Bollywood film industry. Playback singers have been integrated into and are essential to
popular Indian cinema since the 1930s, with recordings based on classical Sanskrit drama,
folk theatre (Morcom, 2007). With playback singers, such as M. Balamuralikrishna discussed
above, achieving the same prominence as actors, their repertoires are a central part of
musical culture throughout the Indian diaspora, lending their voices both to film
compositions, classical recordings and live performances (Bhattacharjya, 2009). Many of
the elites interviewed grew up in the 1960s and became familiar with key playback singers
of the era, and often invited them to perform in South Africa both during and after the
lifting of diplomatic restrictions. Anxieties about the materialisations of contemporary
Bollywood in South Africa have centred on whether clothing, attitudes and consumption
practices appropriately represent India (Radhakrishnan, 2005). Contemporary cinematic
themes and narrative plotlines have essentially remained unchanged, since they reproduce
the same clichés and tropes of the village dramas of early Indian cinema, which itself
ultimately derives from classical Sanskrit drama and folk theatre (Morcom, 2007).
Respondents found going to watch a Bollywood movie a pleasurable, and family friendly,
leisure practice. But contemporary Bollywood encompasses a changed set of capitalist and
consumer aesthetics, in part to appeal to younger diasporic audiences in North America and
Europe (Therwath, 2010). As observed elsewhere in the Indian diaspora (Mohammad, 2007),
these changes have reconfigured the relationships between the South African Indian
diasporic self and place (Ebrahim, 2008). Some elites found this troubled traditional
norms. For instance, Akesh (male, 60s) says that: Bollywood has really taken over from the
appreciation of traditional culture. But Bollywood doesn't show real Indian culture. The
dances and the music look Indian but it does not feel Indian because now it is too
Westernised. The girls don't wear saris anymore, and often it is not even filmed in India
anymore The minutiae of the modern Bollywood aesthetic discussed here are contrasted with
perceived ‘real’ Indian culture, the kinds provided through classical performances.
Perceptions of Bollywood are also mediated by generation and class, with Indian cinema
most often associated with younger people and the Indian working classes, whilst classical
performances are often the preserve of wealthy elites (Hansen, 2005). But these tensions
are also underpinned by feelings of loss akin to Marilyn Ivy's (1995) view of nostalgic
desire as encompassing a range of emotions including anxiety around the erosion of felt
experiences (see also Boym, 2001). Most elites however, were ambivalent about Bollywood.
Some respondents spoke of the ways that Bollywood had generated economic benefits for
South Africa's film industry and supported closer relations between Indians and Africans
(see also Ebrahim, 2008). For Pritty, growing interest from non-Indians and the
mainstreaming of Indian cinema in broader South African cultural life through its
incorporation into public television programming had allowed her to not only craft, but
rewrite a new sense of self: 10 years ago I had to be apologetic for being Indian. There
has been a fundamental change thanks to Bollywood … When in High School I felt ashamed of
being Indian and I didn't want to talk about India. It's gotten to the stage where I'm
proud to be Indian. It fills me with pride that's where I'm from, there's my roots. At one
point I was so ashamed about my name, really embarrassed Often, those elites who
criticised the perceived dominance of contemporary South African Indian life by Bollywood
were at once intrigued and drawn to the affects that its styles, registers and fashions
produced. One afternoon I travelled to Sally's (female, late 60s) house to interview her
over tea and sweets. As we talked, she rummaged around in a drawer and pulls out a CD of
playback recordings from the movie Lagaan, given to her by her grandson. Notes floated
around us as she described the pleasure she felt in keeping up with new releases so that
she could talk with her grandchildren about the latest heartthrobs, and a sense of
enjoyment in hearing them pick up and incorporate Tamil words learnt from films into
everyday speech. To varying degrees, elites were beginning to capitalise on the new
potentialities provided by Bollywood. Both the ICCR and KwaZulu-Natal Ministry for Arts,
Culture and Tourism encourage Indian diaspora associations to incorporate contemporary
Bollywood styles and aesthetics into their repertoire of cultural programming. Adapting
their classical programming by incorporating modern dances and aesthetic styles, often
organised in conjunction with local dance schools and contemporary choreographers, were
part of these plans. Young Indian South Africans from Durban dance schools are one source
of performers. Forty years ago, dance choreography was modelled precisely on Sanskrit
traditions. According to Radhakrishnan (2003), as dance schools have developed and
expanded particularly in the post-apartheid era, choreographers have begun to incorporate
more modern Indian aesthetics, developing new hybrid styles. It is also a relational
process, with teachers innovating and adapting classical and modern Indian styles to the
particularities of the South African setting, by for instance incorporating repertoires
from traditional Zulu folk dances. In fascinating ethnographic detail Radhakrishnan
describes how these new fusion choreographies pose a radical challenge to the boundedness
of classical Indian cultural traditions. Whilst respondents acknowledged that this
variability had increased interest from younger generations, nevertheless the allure of
their correct embodiments remained. For example, Athul stated that new dance styles are
“not really India … But I am happy that some of the younger generation are at least
getting a feel for some of the Indian traditions”. Amongst some respondents, I heard
approval of Bollywood since it allowed some hope that it could act as a precursor for a
broader interest in India and an eventual recovery of Indian languages. For example, when
I met him in 2004, Dev's organisation (male, late 50s) was campaigning to pressure Indian
film distributors to screen Tamil language films in KwaZulu-Natal. He talked about the
Hindi romances he had watched in the 1960s with affection, describing the grandeur of
visiting the Shah Jehan theatre in Durban's Indian Quarter and the ritual and performative
qualities of disparaging, gently, the films; clearly they were an important part of his
youth. But he also felt that for the current and younger generations, Tamil films had
future potential to increase interest in local festivals and events such as Tamil New
Year, or even encourage some form of physical visit to India, because of they way films
could deepen the knowledge of South Indian traditions and languages. Like Athul and Dev
above, I heard other actors speak of their hopes that interest in Bollywood would provoke
younger people to one-day visit India to discover their ancestral roots and connections.
Some spoke of their hopes that younger South African Indians would eventually embrace more
classical dance forms, or begin learning an Indian language, both of which had seen
declining uptake. For instance, Krish said that it was only through “knowing the true
India, the kind we bring through our work” that the younger generations could really
recover their roots. Whilst Bollywood, for some, posed a threat to the long-term
appreciation of classical Indian forms, for both Dev and Krish, generating spatial and
temporal connections between different Indian diasporic sites and practices was a concrete
means through which diaspora associations could anticipate and realise future South
African Indian diasporic selfhood.

<h>CONCLUSION</h>
----------

Scholars of diaspora associations more broadly, and South African Indian cultural
organisations specifically, have mainly focused on the political and economic outcomes of
their activities, on negotiations over underpinning categorical identity politics, and on
the complex landscapes of home that are produced, resisted and contested. Less work
examines the affective ‘doings’ of associational life and the forces and matter that
comprise it. In this paper, I have explored organising actor's relationships and
interactions with the constitutive elements of classical Indian performance spaces, as one
way of exploring the diverse meanings and significances that can be drawn from them by the
actors participating and assembling those spaces. The paper has shown the ways that a
range of subjectivities emerges from and is negotiated through the material constitutions
of classical Indian performances, as they form points of connection and overlap with a
range of different sites through which India is experienced and negotiated. I conclude by
showing how such an approach can enhance scholarly understanding of the work of diaspora
associations as well as pointing to future directions for research. First, by examining
classical Indian performances through the material practices and affective forces of
individual actors, the paper has deepened understandings of the role of agency in
constituting sites of diaspora associational life. Whereas most studies of diaspora
associations have focused on their wider calculable economic and political agendas, the
agency discussed here is relational and affectual, one that produces and reproduces a wide
range of subject positions. A discussion of their different points of connection,
discrepancies and tensions has shown how, in the process of negotiation, organising actors
can anticipate, realise and redefine past, current and future forms of South African
Indian diasporic subjectivity. Second, the paper has sought to illustrate an alternative
way in which diaspora associations' role in producing social differences (and
similarities) might be explored in scholarship. This study of diaspora associations began
not from understandings of India as a pre-existing physical location, but as a spatial
array of interconnected sites, practices and non-human and human forces. This is not to
dismiss the categorical orderings, politics and social differences that also underpin
their practices, but to suggest that heterogeneous materials, bodies, objects and
multidimensional presences come to compose their saliences and longer-term durabilities.
In doing so, this suggests that the social differences produced through associational
practices are full of instabilities, tensions and gaps, leaving room for critical refusal
and transformation.


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<ART>Measured and self-estimated trait emotional intelligence in a UK sample of managers
================================================================================

Authors: A. B. Siegling, Mireille Sfeir, Hedley John Smyth
DOI: 10.1016/j.paid.2014.01.027
Year: 2014  |  Pages: 59-64
ASJC codes: 3200
Keywords: Accuracy, Estimation bias, Gender, Managers, Trait emotional intelligence

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Trait emotional intelligence (EI) was measured and self-estimated in a UK sample of 128 managers (52.3% female), recruited at a professional services firm. Participants' measured scores were compared to standardization sample data and gender differences in measured and estimated scores, as well as in estimation bias and accuracy were examined. As hypothesized, managers' global trait EI scores were significantly higher than those of the normative sample of the measure used, although the scores of female participants were largely responsible for this difference. Gender-specific hypotheses were confirmed for measured scores (differences only hypothesized at the factor level) and estimation accuracy (males estimating their trait EI more accurately), but not for estimated scores (female participants had higher estimates, but the opposite was hypothesized). Further, female managers showed signs of estimation bias. © 2014 Elsevier Ltd.

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MEASURED AND SELF-ESTIMATED TRAIT EMOTIONAL INTELLIGENCE IN A UK SAMPLE OF MANAGERS
--------------------------------------------------------------------------------

Management of human capital has been portrayed as one of the major settings for the
relevance and application of emotional intelligence (EI). In part, the importance which EI
has been ascribed in the managerial world is linked to its marketing potential within this
context; the construct is readily sellable in the form of assessments, training programs,
and interventions. One the other hand, the occupational demands associated with various
types of management draw on the specific characteristics subsumed by the prevailing EI
models and measures (e.g., Bar-On, 1997; Petrides, 2009a). Emotion-related qualities seem
to be fundamental to professional success and adjustment within this diverse capacity,
suggesting that managers may constitute a high EI population. Although there has been a
surge of studies on managerial samples or in managerial contexts, much of this research
has treated “EI” as a general concept, rather than considering the two more specific
constructs tapped by various measures. Since the construct’s inception and popularization
(Goleman, 1995), the field has gradually diverged into two streams of research, focusing
on two complementary dimensions termed ability EI and trait EI, respectively. Ability EI
concerns emotional-related abilities measured through maximum-performance tasks, whereas
trait EI refers to the emotion-related personality dimension assessed through typical-
performance measures. It has been argued that any typical-performance measure of EI is
most appropriately interpreted through the trait EI lens, independent of the underlying
model (Petrides & Furnham, 2001). This assertion and the distinctiveness of the two
constructs is supported by non-significant to modest correlations between typical- and
maximum-performance EI measures and moderate to strong correlations between measures based
on the same method (Van Rooy, Viswesvaran, & Pluta, 2005). The operationalization-based
split into two relatively distinct constructs, which has implications for the
interpretation of findings gathered with a given measure, needs to be considered in
research with special-interest populations, such as managers. One cannot generalize from
one construct (i.e., trait or ability EI) and its operational vehicles to the other, as
divergent findings can be expected from the two (Petrides & Furnham, 2001). The focus of
the present study is on managers’ trait EI, and a concise review of studies assessing
trait EI in managerial samples is provided next.

<hs>  Literature review</hs>
  ~~~~~~~~~~~~~~~~~

We retrieved 10 studies in which managers’ EI was assessed with typical-performance
measures and, thus, representative of trait EI.1 The samples used in these studies varied
considerably in geographic locations and ethnicities (e.g., China, UK, Australia, and
Israel), occupational sectors (e.g., CFOs, restaurant franchises, public services,
retailers, construction industry) and managerial levels. Seven of the ten studies employed
workplace-oriented EI scales (Angelidis & Ibrahim, 2012; Gardner & Stough, 2002; Sy, Tram,
& O’Hara, 2006). Unfortunately, these types of EI measures are unlikely to reveal much
about managers’ trait EI (relative to the general population), since they were
standardized on samples comprising managers, leaders, or people in similar roles.
Therefore, we restrict our focus on the results gathered with general-population scales.
Different general EI scales were used in three studies. The Trait Meta-Mood Sale (TMMS;
Salovey, Mayer, Goldman, Turvey, & Palfai, 1995) was administered to an Australian female-
only sample of managers from various industries (Downey, Papageorgiou, & Stough, 2006).
Sample scale means were 3.94 for Attention (SD = 0.57), 4.22 for Clarity (SD = 0.57), and
4.23 (SD = 0.58) for Repair. In comparison, a sample of undergraduate students had scale
means of 4.10 (SD = 0.52) for Attention, 3.27 (SD = 0.70) for Clarity, and 3.59 (SD =
0.90) for Repair (Salovey, Stroud, Woolery, & Epel, 2002). The Bar-On (1997) Emotional
Quotient Inventory was administered to a sample of 191 middle managers (line managers; 69%
male) working for a major UK retailer (Slaski & Cartwright, 2002). The overall EI sample
mean of 94.4 (SD = 12.5) was lower than the normative sample mean of 100. Moreover,
Schutte et al. (1998) Assessing Emotions Scale was completed by a sample of 98 senior
managers (89% male) employed as CFOs in local government authorities in Israel (Carmeli,
2003). The sample mean was 3.71 (SD = 0.37), which was above the normative sample means
for women (M = 3.45, SD = 0.46) and very similar to that of men (M = 3.78, SD = .50). The
number of relevant studies is too sparse and their findings insufficiently consistent to
suggest that managers are particularly high in trait EI. Importantly, the samples used in
these studies varied widely in occupational sectors and managerial levels, making it
difficult to tease apart the effects of management and work-domain. Another limitation
concerns the use of different measures varying in subscales, with one (the Trait Meta-Mood
Scale) comprising three weakly interrelated factors. A benchmark measure of trait EI, the
Trait Emotional Intelligence Questionnaire, was used in one managerial context
(Mikolajczak, Balon, Ruosi, & Kotsou, 2012), but no sample means were reported in this
study. Furthermore, studies on managerial samples have tended to neglect the role of
gender, despite its importance in EI research (e.g., Siegling, Saklofske, Vesely, &
Nordstokke, 2012). Another pertinent factor not previously considered is managers’
holistic self-evaluation of their emotional adjustment. Self-perceptions are important for
several reasons and have been studied for some time, particularly in the context of IQ and
performance. It is conceivable that they have a profound influence on the kind of tasks
people engage in or avoid, and on the kind of careers pursued. Further, positive self-
perceptions are linked to mental health, in contrast to negative self-evaluations, which
are linked to negative affect and depression (Petrides & Furnham, 2000). Although previous
research has examined EI self-perceptions in university students, with a particular focus
on gender differences (Petrides & Furnham, 2000; Petrides, Furnham, & Martin, 2004), self-
perceptions of managers may differ in myriad ways from university samples in terms of
perception accuracy, bias, and gender differences.

        <hss>Present study</hss>

        This study examined the trait EI profiles of a general managerial sample
        comprising of managers from different levels and not tied to any specific type of
        service. Participants’ trait EI scores were examined for gender differences and
        compared to normative sample data. Departing from the bulk of management-related
        studies, in which trait EI was assessed with workplace-oriented scales, this study
        used the Trait Emotional Intelligence Questionnaire (TEIQue), a scale designed to
        measure the construct comprehensively in the general population. We also examined
        managers’ overall self-estimates of trait EI, focusing on gender differences,
        estimation bias, and estimation accuracy. These self-perceptions were referenced
        against the TEIQue model to facilitate direct comparison with the measured trait
        EI scores. The following hypotheses were tested: H1: Participants’ measured trait
        EI scores will be higher than those of the normative sample of the TEIQue.
        Although our review of the literature did not yield conclusive evidence, this
        hypothesis is based on the particular importance of emotional resilience and
        socioemotional functioning in the managerial world. The argument is that
        emotionally resilient people are more likely to be selected for, or to advance to
        managerial positions. H2a: There will be no gender difference in managers’ global
        trait EI scores. Although the normative sample mean is significantly higher for
        males (Petrides, 2009b), gender differences were not apparent in other samples
        (e.g., Siegling et al., 2012) and female managers may be particularly well
        adjusted compared to women in the general population. However, as has been quite
        reliably found, we also hypothesized, H2b: Male managers will score higher on the
        Self-Control factor than female managers, who will be higher on the Emotionality
        factor. H3: Male managers will have significantly higher estimated global trait EI
        scores than female managers when controlling for measured scores, consistent with
        previous findings from participants recruited at British universities (Petrides &
        Furnham, 2000). This hypothesis also reflects self-enhancing and self-derogatory
        biases in men and women, respectively, which have been demonstrated for self-
        evaluations more generally. H4: Male managers will have more accurate estimates
        than female managers, also based on previous findings in British university
        students (Petrides & Furnham, 2000).

<hs>  Participants and Procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

We invited 339 managers from senior, middle, and junior levels at a large professional
services firm to participate in this study. Of this group, 128 (37.8%) managers with a
mean age of 38.0 years (SD = 7.5, age range: 26–59 years) participated (three participants
[2 male, 1 female] did not indicate their age). The gender split amongst the participants
was almost equal (52.3% female), but the representation of the three managerial levels was
uneven; the majority came from middle management (n = 79, 50.6% female), whereas similar
sample proportions were senior (n = 27, 40.7% female) and junior managers (n = 22, 72.7%
female). The mean ages of male and female participants were 39.1 years (SD = 7.9) and 36.9
years (SD = 7.1), respectively. The average length of time worked at the firm was 6.2
years (SD = 6.0) for the overall sample, 6.7 years (SD = 6.9) for male managers, and 5.8
years (SD = 5.0) for female managers. The majority of respondents (78.1%) indicated their
ethnic background as Caucasian, others as Black, Asian, and Indian/Pakistani. Educational
backgrounds in terms of the highest level of education attained varied considerably: 2.5%
GCSEs/O-levels, 15.6% A-levels or similar, 53.9% BA/BSc or similar, 21.1% MA/MSc or
similar, and 2.3% MBA (six participants did not indicate their highest level of
education). After providing demographic and background information, trait EI was assessed
and self-estimated. The study was conducted anonymously online.

        <hss>Trait EI</hss>

        The short form of the TEIQue (Petrides, 2009a) was sufficient for the purpose of
        this study. It contains 30 items from the full form (two items represent each of
        15 facets) and can be used to measure global trait EI and the four factors derived
        from the full form: Emotionality, Self-Control, Sociability, and Well-Being.
        Respondents complete the items on a 7-point Likert scale, ranging from 1
        (completely disagree) to 7 (completely agree). The internal consistencies in the
        present study were acceptable and consistent with those reported for the
        standardization sample (Petrides, 2009a). Specifically, Cronbach’s alphas were .91
        for global trait EI, .85 for Well-Being, .70 for Self-Control, .73 for
        Emotionality, and .78 for Sociability

        <hss>Estimated trait EI</hss>

        Participants gave overall self-estimates for global trait EI and each of the four
        TEIQue factors. Definitions of the four factors, as shown in Petrides (2009b),
        were presented to the participants. As a description of global trait EI,
        participants were shown a visual illustration of the trait EI model integrating
        its four factors and 15 facets (see Fig. 1). Upon referencing these descriptions,
        they were asked to give their estimate for each of the factors and global trait EI
        on a scale ranging from 1 (extremely low) to 21 (extremely high). This range was
        considered adequate to yield sufficient variability in responses and precision in
        estimating one’s trait EI. Prior to statistical analysis, these estimates were
        divided by three to make them directly comparable to the measured TEIQue scores

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Relationships amongst age, gender, and managerial level, as well as correlations of age
with measured and estimated trait EI were examined to identify potential confounds.
Measured trait EI scores were compared to the normative data (both general and gender-
specific), as reported in Petrides (2009a), using one-sample t tests. Participants’ trait
EI profiles and the role of gender in trait EI scores were examined using ANCOVA,
controlling for any identified confounds. When examining gender differences in estimated
scores, measured scores as well as any confounding variables were controlled. ANCOVAs,
again controlling for any confounds, were executed to examine any bias towards over- or
under-estimation of trait EI scores. Specifically, measured and estimated trait EI scores
were compared for the overall sample and for each gender. Correlations between estimated
and measured scores, also computed separately for the overall sample and each gender, were
examined as an indicator of estimation accuracy. Accuracy was then compared between female
and male managers using Steiger’s Z statistic.

<hs>  Preliminary analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

With missing responses highlighted to the participants electronically (without forcing
responses), there were no missing data points. The mean ages of male and female
participants were similar, t(123) = 1.68, p = .10, whereas ages increased significantly
across managerial levels, F(2, 122) = 15.00, p < .0001. Participant age also correlated
with measured global trait EI, r(125) = .21, p = .02, and its Self-Control factor, r(125)
= .23, p = .009, but with none of the self-estimates (p > .05). Thus, we aimed to control
for age in the main analyses. A qui-square test examining the relationship between
managerial level and gender did not reach significance, χ2(2, N = 128) = 5.21, p = .07,
indicating that managerial level would be an unlikely confound.

<hs>  Trait EI profiles</hs>
  ~~~~~~~~~~~~~~~~~

Table 1 shows descriptive statistics for measured and estimated trait EI scores for the
overall sample and each gender. One-sample t tests showed that the overall sample had
significantly higher scores than the standardization sample on global trait EI, t(127) =
4.06, p < .0001, Self-Control, t(127) = 3.59, p < .001, and Well-Being, t(127) = 3.20, p <
.01. Concerning gender-specific norms, there were no significant discrepancies between
male managers’ measured trait EI scores and those of the standardization sample. However,
female managers’ scores were significantly higher than the standardization sample scores
on global trait EI, t(66) = 4.66, p < .0001, and three of the four factors: Well-Being,
t(66) = 3.93, p < .001, Self-Control, t(66) = 4.30, p < .0001, and Emotionality, t(66) =
2.97, p = .004. A 5 (trait EI factor) × 2 (gender) mixed-design ANCOVA on measured trait
EI scores, controlling for age revealed a significant interaction, F(2.91, 354.70) = 8.11,
p < .0001, partial η2 = .06. Mauchly’s test for the within-subjects factor was significant
in this analysis, χ2(9) = 384.86, p < .0001, and, hence, the degrees of freedom were
adjusted using Greenhouse-Geisser estimates of sphericity (ε = 0.73). While the factor
scores appear to be relatively uniform for the overall sample, F(2.91, 354.70) = 2.16, p =
.09, the significant interaction is indicative of a gender difference in trait EI
profiles. Therefore, follow-up comparisons of the factor scores both within and between
the genders were conducted. One-way within-design ANCOVAs controlling for age revealed a
main effect for female managers’ measured trait EI scores, F(2.91, 190.08) = 3.93, p <
.01, partial η2 = .06. As Mauchly’s test of sphericity was also significant in this
analysis, χ2(9) = 184.66, p < .0001, the degrees of freedom were again adjusted using
Greenhouse-Geisser estimates (ε = 0.74). Pairwise comparisons adjusted using Sidak’s
correction revealed significant differences between most of female managers’ factor scores
(p < .05), except between Well-Being and Emotionality. In contrast, there were no
significant differences amongst the measured trait EI scores of male managers. One-way
between-design ANCOVAs controlling for age only revealed a significant gender difference
on the Emotionality factor, F(1, 122) = 11.31, p = .001, partial η2 = .08, indicating that
female managers scored significantly higher on this factor.

<hs>  Estimation bias</hs>
  ~~~~~~~~~~~~~~~

Two (score type: measured, estimated) × two (gender) mixed-design ANCOVAs controlling for
age were executed to compare each measured score to its corresponding estimate and examine
the role of gender in self-estimates. The analyses revealed no significant main effects
for score type on any factor. However, there were significant interactions of score type
and gender on global trait EI, F(1, 122) = 11.04, p < .01, partial η2 = .08, Well-Being,
F(1, 122) = 5.06, p = .03, partial η2 = .04, Emotionality, F(1, 122) = 5.92, p = .02,
partial η2 = .05, and Sociability, F(1, 122) = 10.41, p < .01, partial η2 = .08. After
applying Bonferroni’s correction for multiple comparisons, the interactions on global
trait EI and Sociability remained significant. The previous analyses revealed only a
gender difference on the Emotionality for measured scores. Hence, to probe the
interactions, we first examined if there were gender differences on any of the estimates
for global trait EI or Sociability. One-way between-design ANCOVAs controlling for age and
the corresponding measured trait EI score revealed significant differences on estimates of
both global trait EI, F(1, 121) = 13.06, p < .001, partial η2 = .10, and Sociability, F(1,
121) = 10.01, p < .01, partial η2 = .08. Thus, female participants had significantly
higher estimates on global trait EI and on the Sociability factor. To probe these
interactions further, we examined if any of the estimated global trait EI or Sociability
scores of each gender differed significantly from the corresponding measured scores. One-
way within-design ANCOVAs, controlling for age, only revealed a significant difference
between female managers’ estimated and measured global trait EI scores, indicative of an
over-estimation bias, F(1, 64) = 4.37, p = .04, partial η2 = .06. However, this difference
did not hold up following adjustment for multiple comparisons.

<hs>  Estimation accuracy</hs>
  ~~~~~~~~~~~~~~~~~~~

Table 1 also shows the correlations between participants’ measured and estimated trait EI
scores. The correlations were consistently significant and within a moderate to strong
range. However, the magnitude of correlations is indicative of systematic differences in
estimation accuracy across factors (as each pair of scores is different with no score used
in more than a single pair, it seems inappropriate to compare them statistically). The
strength of estimation accuracies across factors (from strongest to weakest) were in the
following order: Well-Being, Self-Control, Emotionality, and Sociability. A pattern that
emerges from the gender-specific correlations is that men’s measured and estimated trait
EI scores were consistently more highly associated than those of women, despite the
slightly smaller number of male participants. However, the only significant gender
difference in these correlations was on global trait EI, Z = 2.63, p < .01. The difference
in associations on the Sociability factor was also significant, Z = 1.70, p < .05, but it
did not hold up after applying Bonferroni’s correction. Thus, male managers estimated
their global trait EI more accurately than female managers.

<h>DISCUSSION</h>
----------

The results support H1, which was based on the notion that managers constitute a high
trait EI population. Conceptually, trait EI is particularly relevant to the occupational
demands shared by managers from all kinds of backgrounds (e.g., demonstrating composure in
high-stress periods, dealing effectively with employee turmoil, being responsive to
employees’ needs). The overall sample mean (for global trait EI and two factors) was above
the normative average, but gender-focused analyses showed that only female managers were
above the gender-specific normative data for either global trait EI or particular factors.
While the differences for male managers may well be significant in larger samples, the
fact that it they were more pronounced, and only significant for female managers may hold
key implications, subject to consistent replication in further research. Consistent with
H2a, male and female managers did not differ on global trait EI. Although the
standardization sample mean is significantly higher for men, this finding supports our
reasoning that women who are high in trait EI are more likely to advance to, and be
considered for managerial positions. The fact that only female managers were above the
gender-specific standardization-sample mean for global trait EI and three factors lends
further support to this idea. H2b was partially supported, since female managers were
higher on the Emotionality factor than male managers, as previously reported for
university samples (Petrides, 2009a; Siegling et al., 2012). Previous research within the
university population has also shown that men tend to score higher on the Self-Control
factor, but this difference did not replicate in our managerial sample. Relative to
previous findings, it appears that the Self-Control factor, in particular, contributed to
the non-significant gender difference at the global construct level. Contrary to H3, which
derived from previous findings on university students and more general gender differences
in self-perceptions (see Petrides & Furnham, 2000, for a discussion), female managers had
significantly higher overall estimates than male managers. Yet, the results are consistent
with the findings from another study, in which measured scores were unadjusted (Petrides
et al., 2004)—in comparing the results of these studies, including ours, it is also
important to consider differences in the measurement of measured and self-estimated
scores. Follow-up analyses revealed a trend towards overestimation on the part of female
managers, whereas male managers’ self-estimates were aligned with their measured scores.
Thus, where trait EI is concerned, our results are indicative of a self-enhancing bias in
female managers and a lack of bias in male managers. As we had no hypotheses for any
gender-related estimation biases, however, this particular result, which strictly speaking
was not significant after adjusting for multiple comparisons, needs to be replicated in
comparable samples. Our last hypothesis (H4), which concerned gender differences in
estimation accuracy, was supported by the data. Male managers’ estimates of global trait
EI were more accurate than those of their female counterparts, consistent with previous
research in university students (Petrides & Furnham, 2000). Our results speak to the
external validity of this gender difference, which was replicated in a special-interest
population and by means of different measures of both measured and estimated trait EI than
those used in Petrides and Furnham’s (2000) study. The higher correlations in the present
study are presumably an effect of deriving estimates with reference to the same model as
the one underlying the measured scores. The findings surrounding participants’ measured
trait EI have potential key implications for understanding the role of this personality
dimension in management. Most generally, they suggest that emotion-related personality
traits play a central role in the selection and advancement of managers. They also suggest
that, of those who pursue management-related careers, trait EI may be particularly
instrumental for women, relative to the female standardization sample. That said, we are
neither in a position nor willing to argue that trait EI is more important for women to
function in managerial contexts, as is indicated by the non-significant gender difference
in global trait EI. Rather, high trait EI women are more likely to end up in management
than women with average trait EI levels, whereas this does not seem to be the case for
men. Holistic self-perceptions are important in that they influence the kind of tasks
people prefer, the career choices they make, and how far they are willing to push
themselves. It is possible that the threshold of emotion-related self-evaluations
necessary for seeking managerial positions is particularly high for women; only women who
are above average in their emotional self-perceptions may pursue managerial careers. It
has also been noted that positive self-perceptions are conducive to mental health, and
negative self-evaluations to psychological distress (Petrides & Furnham, 2000). Inflated
self-perceptions may be adaptive to the extent that they do not mislead people into tasks,
projects, or even careers that exceed their actual capacities considerably. To that
extent, high self-perceptions can help people perceive the demands of their occupation as
less threatening or stressful. As female managers had higher self-estimates than male
managers, despite having similar measured trait EI scores, they may approach various
situations more confidently and be somewhat less vulnerable to job-induced psychological
problems, such as burnout. It is important to acknowledge that other factors cannot be
ruled out as explanations for the above-average trait EI scores found in this managerial
sample. While the ethnic compositions were similar and both samples were based in the UK,
the average age of the standardization sample is about eight years younger and it is not
representative of the general workforce. Nevertheless, a different article in this issued
showed that trait EI distinguished between leaders and non-leaders employed by the same
company, even after controlling for age and other control variables (Siegling, Nielsen, &
Petrides, in press). A second limitation to be addressed in future research is that both
measured and estimated trait EI were based on self-report. Consequently, some of the
variance in both variables was likely influenced by participants’ self-perceptions,
suggesting that our results provide an overstatement of estimation accuracy. A way to
circumvent this problem is to measure trait EI with one of the available 360 forms (i.e.,
through peer or close-other ratings).


<h>REFERENCES</h>
----------

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<ART>Measuring Decision Accuracy and Confidence of Mock Air Defence Operators
========================================================================

Authors: Jade E. Adams-White, Jacqueline M. Wheatcroft, Michael Jump
DOI: 10.1016/j.jarmac.2018.01.005
Year: 2018  |  Pages: 60-69
ASJC codes: 3202, 3203, 3205
Keywords: Command and control, Decision-making, Metacognition, Military

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study aimed to understand more fully some of the factors that influence decisions as related to air defence in a naval vessel's operation room. The study considered the impact of decision criticality (DC) and task load (TL) on measures of accuracy, confidence, and within-subjects confidence-accuracy (W-S C-A; a measure of metacognition). Personality constructs, workload, and situational awareness were also assessed. Participants were allocated to either a high, moderate, or low TL condition. Each took part in a computer-generated simulated air defence scenario where they were required to make a range of decisions and provide a corresponding confidence rating for each decision taken. Results showed that low DC increased confidence in decisions and high DC increased decision accuracy. Thus, DC significantly impacts decision confidence and decision accuracy. In addition, those less tolerant of ambiguity were less accurate in their decision-making. Future studies should take account of these factors.

--------------------------------------------------------------------------------


<h>GENERAL AUDIENCE SUMMARY</h>
------------------------

General Audience Summary Air defence decision-making is often conducted in a complex and
uncertain environment. It is therefore important that the individuals faced with this task
are able to make accurate and confident decisions under varying degrees of stress and
criticality (i.e., the consequence associated with a decision). The purpose of this study
was to examine external factors (e.g., task duration/stress) and internal factors (e.g.,
personality constructs) that may impact air defence operator's decision-making abilities.
In this study a measure of within-subjects confidence-accuracy was used. This measure
considers the relationship between decision confidence and decision accuracy by assessing
individual awareness of the accuracy of decisions made. For the task, a realistic set of
scenarios, which varied in task difficulty, were designed with subject matter experts.
Participants were required to make a range of decisions which varied in criticality and
then rate how confident they were that they had made the best decision given the
situation. The results demonstrated that the criticality of the decision impacted both
decision accuracy and confidence. Low decision criticality increased confidence in
decisions and high decision criticality increased decision accuracy. The implications of
this research include an increased understanding of the understanding of decision
criticality on decision-making in critical environments. The introduction of a novel
method which has potential application in terms of informing the selection and in the
training of personnel who are required to make accurate and confident decisions under
conditions of uncertainty and stress is also highlighted. It is important to note that
these inferences are based on findings from a novice sample and that non-trained staff are
unlikely to make decisions in critical environments.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Sixty participants were recruited through opportunity sampling from the University of
Liverpool. The participants consisted of 30 females and 30 males with a mean age of 26
years (SD = 3.96). None of the participants had any prior experience in naval warfare
operations as the study was initially interested in the OR role and novice capacity to the
task. The sample size was decided upon by design, power, and previous studies using
G*Power software with an effect size of 0.8 and significance level of .05 (Faul,
Erdfelder, Lang, & Buchner, 2007). The study received approval from the University of
Liverpool's Institute of Psychology Health and Society Ethics Committee, and a favourable
opinion from the Ministry of Defence Research Ethics Committee.

<hs>  Design</hs>
  ~~~~~~

A mixed measures quasi-experimental design was employed. Independent variables (IVs) were
task load and decision criticality. As such, a 3 (Task Load: low, moderate, high) × 3
(Decision Criticality: low, medium, high) mixed analysis of variance (ANOVA) was
conducted, with repeated measures on the last factor. The dependent variables (DVs) were
confidence, accuracy, W-S C-A, personality constructs (openness to experience,
conscientiousness, extraversion, agreeableness, and neuroticism; NEO-PI-R; Costa & McCrae,
1992), decision tendencies (i.e., tolerance of ambiguity; Budner, 1961; and decision
style; Roets & Van Hiel, 2007), subjective mental workload (NASA TLX; Hart & Staveland,
1988), and situational awareness (SART; Taylor, 1990).

        <hss>Decision logs</hss>

        To ensure as high a level of ecological validity as possible in a quasi-
        experimental design, an air defence scenario was created with the guidance and
        assistance of subject matter experts (SMEs). The use of SMEs to assist in the
        experimental design is highly beneficial as SMEs are able to provide unique
        insight into the appropriate and relevant situations that are likely to be met and
        applied in the study context. Four SMEs with extensive knowledge of naval warfare
        and many years of experience in both Air Warfare Officer (AWO) and Principal
        Warfare Officer (PWO) roles were used to acquire the domain specific knowledge
        needed to provide the optimum ecologically valid options for decision making. The
        scenario uses a realistic set of events within a peace enforcement (PE) operation.
        A series of events and associated event decision logs were also created and agreed
        upon by SMEs. The event decision logs specify three decision options of reasonable
        equivalence for each event presented to the operator. SMEs agreed upon one option
        per decision made as the optimal/best decision option given the current situation.

        <hss>Computer scenario</hss>

        The visual display used as the stimulus for the experiment was created using
        Virtual Avionics Prototyping Software (VAPS XT). The screen depicted a quasi-
        realistic radar screen which included an airlane, a no-fly zone (NFZ), a
        coastline, and a border. A textbox to display additional information to assist
        decision-making and a timer which counted down from 20 s at each decision event
        were also included (see Figure 1). The algorithms used to animate the visual
        display symbols were created using Matlab/Simulink. The symbology used is as
        specified by APP-6c (NATO, 2008). Microsoft Movie Maker was used to edit the video
        (e.g., to apply timers). The SMEs verified the display as sufficiently realistic.

        <hss>Questionnaires</hss>

        The Situation Awareness Rating Technique (SART; Taylor, 1990) was used to measure
        SA. To measure WL, the NASA-TLX (Hart & Staveland, 1988) was utilised. NASA-TLX is
        a subjective workload assessment tool. Personality was assessed by the NEO-PI-R
        (Costa & McCrae, 1992).

<h>PROCEDURE</h>
---------

Participants were randomly allocated to a high, moderate, or low TL condition.
Participants first completed participant demographic forms which collected data on age,
gender, and occupation. Participants were also asked to complete paper-based
questionnaires to gauge the relevance of a number of measures across groups (e.g., general
personality constructs, thinking and reasoning) where they may be relevant to particular
questions. Following this, participants were given the task booklet to read. The task
booklet provided participants with information needed to assist them in the decision-
making task, including air defence terminology and symbols. Once they had read the
booklet, participants undertook a practice trial. The practice trial involved a series of
decision events which allowed participants to familiarise themselves with the task and the
procedure. The duration of the trial was kept limited so as not to fatigue the
participants before the experimental task (Barnes-Yallowley; personal communication,
2015). The questionnaire booklet presented three separate decision options based on the
events of the scenario. One choice was required to be selected by placing a tick by the
option they believed to be the “best option given the current situation.” Participants
were then required to rate how confident they were in the option chosen on a Likert scale,
where 0 = not at all confident to 5 = extremely confident. After 20 s, the screen was
blanked out to signal to the participants that the allocated decision time has ended. All
participants then undertook the experimental air defence scenario, following the same
procedure as described for the practice. Thirty decision events were presented during the
experimental simulation. A decision event was defined as an occasion where a decision may
need to be made by an operator. For example, an unknown data link track appears on the
screen. Decision criticality was varied across the decision events presented (i.e., 10
high, 10 medium, and 10 low DC). Decision criticality related to the consequence of that
decision. The decision held a higher criticality if there was a greater risk should the
decision taken be incorrect in the high DC decisions (e.g., aircraft demonstrating hostile
intent) compared to low DC (e.g., new track on radar screen) and the event occurrences
varied depending on TL condition. The scenario stimulus ran for 20 min, 30 min, or 45 min
for the high, moderate, and low conditions, respectively. The high condition involved an
increased frequency of decisions, multiple decisions, and more aircraft tracks to monitor
on the screen in comparison to the low condition which was characterised by one aircraft
track to monitor at a time, decisions based only on the one track, reduced frequency of
decision events, and longer periods of no action. Once the scenario had finished,
participants completed situational awareness and workload questionnaires. Participants
were fully debriefed to ensure each understood the nature of the study and given the
opportunity to ask further questions.

<h>RESULTS</h>
-------

To assess the differences in means a number of statistical analyses were performed on the
data for accuracy, confidence, and W-S C-A using analysis of variance (ANOVA). A
manipulation check was carried out to assess the differences in TL (see analysis of
workload and situational awareness below). No significant differences were found in WL,
there were differences in SA. The TL manipulation was not significant. An alpha level of
.05 was used for all statistical tests.

<hs>  Accuracy</hs>
  ~~~~~~~~

The accuracy of the decisions was decided on by the SMEs. When designing the decision log
and generating the decision options, one of the decision options was voted to be the best
decision given the current situation. Participants were scored 1 for an accurate response
or 0 for an incorrect response. The maximum total score was 30 and the maximum mean for
each DC was 10. To examine the mean differences between TL and DC in accuracy, an ANOVA
was conducted.

<hs>  Confidence</hs>
  ~~~~~~~~~~

Participants were asked to rate confidence in each decision, from 0 (not confident at all)
to 5 (extremely confident). The maximum confidence score in total was 150 (50 for each
DC). A 3 × 3 mixed ANOVA was carried out to assess the impact of TL and DC on decision
confidence. As Mauchly's test of sphericity was found to be significant, the
Greenhouse–Geisser estimate for df was used (see Table 2).

<hs>  Percentage Confidence in Correct and Incorrect Responses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To consider the variation in the data and examine the low correlations displayed for W-S
C-A, percentage confidence in correct and incorrect responses was calculated. The W-S C-A
correlation indicates the relationship between confidence and accuracy; however, a high
correlation suggests both being highly confident in correct decisions as well as low
confidence in incorrect decisions. Similarly, a negative W-S C-A correlation would suggest
that individuals are highly confident in incorrect responses or not confident in correct
responses. Thus, by examining the percentage confidence in incorrect or correct responses,
the direction of the confidence (over/under confidence) can be investigated.

<hs>  Workload and Situational Awareness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To assess the relationship between workload (WL) and situational awareness (SA), a series
of Pearson's correlations were calculated. A significant negative relationship was found
between SA and WL, r(58) = −.53, p < .001. Higher levels of reported WL were related to
lower feelings of SA. A one-way ANOVA was conducted to assess the relationship between SA
and TL. There was a significant effect of TL condition on SA, F(2, 57) = 6.44, p = .003.
Participants in the low TL condition reported higher levels of subjective SA (M = 21.40,
SD = 4.67) than participants in the high TL condition (M = 14.30, SD = 5.42) p = .002. No
significant relationship was found between WL and TL, F(2, 57) = 3.00, p = .06. As a non-
significant relationship was found, this would suggest that the manipulation check was not
successful. As an exploratory analysis, the 6 dimensions of the NASA TLX (mental demand,
physical demand, temporal demand, performance, effort, and frustration) were also examined
to determine whether differences existed across the conditions. One-way ANOVAs were
conducted with TL across the different dimensions of workload (see Table 4). An
interesting finding was that the attentional supply was higher for moderate than high TL;
this suggests that participants may have struggled more with the potential uncertainty
that the moderate condition might have brought to bear. It appears participants were more
able to deal with the ends of the spectrum where real differential could be identified
(i.e., low and high conditions).

<hs>  Relationships Between WL, SA, Accuracy, Confidence, and W-S C-A</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To establish whether a relationship existed between WL, SA, accuracy, confidence, and W-S
C-A a number of Pearson's correlations were carried out. Results revealed a significant
negative relationship was found between overall WL and confidence, r(58) = −.42, p = .001.
As subjective measures of workload increased, confidence in decisions decreased. In
addition, a significant strong positive relationship was found between overall SA and
confidence, r(58) = .63, p < .001. Higher scores in subjective SA were related to higher
scores of confidence in decisions. However, no significant relationships were found
between SA, WL, and W-S C-A, or between SA and accuracy or WL and accuracy in decisions;
all comparisons, p > .05. Furthermore, no significant relationship was found for between-
subjects confidence and accuracy, p > .05. The findings suggest that decision confidence
influences both WL and SA. In this study accuracy was found to be unrelated to WL and SA.

<hs>  Personality Constructs</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

This study was also interested in establishing whether accuracy, confidence, or W-S C-A
were related to psychometric measures of personality. For this, Pearson's correlations
were conducted. A significant negative relationship was found between tolerance to
ambiguity and accuracy, r(58) = −.34, p = .008. Those who scored higher on the tolerance
to ambiguity scale (i.e., less tolerant) were less accurate. In addition, a significant
negative relationship was also found between decision style and accuracy r(58) = −.35, p =
.005. High scorers on the decision style scale were less accurate. Decision style
explicitly probes the need for quick and unambiguous answers. To investigate whether there
were individual differences in participants experiences of WL and SA, correlations were
conducted on each measure of the NEO-PI-R (openness to experience, conscientiousness,
extraversion, agreeableness, and neuroticism). The results showed a significant
relationship between openness to experience and WL, r(58) = −.28, p = .03. High scorers on
the openness to experience scale reported lower levels of WL during the task. No other
relationships were found to be significant, p > .05. These findings therefore suggest that
some cognitive constructs are involved in decision accuracy and individual differences in
participants’ feelings of WL.

<h>DISCUSSION</h>
----------

A novel method of measuring metacognitive ability to assess the impact of decision
criticality (DC) and task load (TL) on measures of confidence, accuracy, and W-S C-A was
used with mock air defence operators. Personality constructs, workload (WL), and
situational awareness (SA) were also assessed. DC impacted both decision confidence and
decision accuracy. Low DC was found to increase confidence in decisions while high DC
increased decision accuracy. Cognitive constructs were also found to be related to
decision accuracy. The findings suggest that accuracy increases with DC. Participants made
more accurate decisions in high DC than both low DC and medium DC conditions. This outcome
supports previous findings that criticality influences performance (Hanson et al., 2014;
Wheatcroft et al., 2017). Research has also shown that task performance increases when
participants find the task more important (Kliegel, Martin, McDaniel, & Einstein, 2004),
perhaps indicating that individuals believed high DC decisions to be important within the
task context. This could relate to participants applying more attention and effort to
decisions with greater consequences for an incorrect decision. Future research could
examine decision processes and which mechanisms lead to increased accuracy. The study also
demonstrates that DC influenced confidence. Individuals were significantly more confident
in low DC decisions than medium DC decisions, lending support to previous literature that
confidence decreases as difficulty increases (Chung & Monroe, 2000; Kebbell, Wagstaff, &
Covey, 1996). No significant differences were found between high and low DC or medium and
high DC. This could be due to increased uncertainty as condition criticality increased in
the conditions relative to low DC, but high DC was perceptually transparent. Nevertheless,
it is the corresponding confidence relative to an individual's awareness of the accuracy
of decisions that is most important. W-S C-A remained unaffected, with no significant
differences evident in W-S C-A across TL and DC. Some research has shown that training and
experience improve calibration (Lichtenstein, Fischhoff, & Phillips, 1977). It would
therefore be beneficial to conduct further studies using naval participants with
appropriate experience. The high TL condition did not impact decision confidence,
accuracy, or W-S C-A. However, the manipulation check was not significant; this could be
one reason why no differences were found for some variables. The results support previous
research which demonstrates that confidence is a relatively robust and general trait
(Stankov & Lee, 2008). Confidence remained high, irrespective of accuracy. No relationship
was found between decision confidence and accuracy. The accuracy scores were just below
chance but individuals displayed elevated confidence—the means of both correct and
incorrect scores were around 70%, suggesting that individuals are unaware of incorrect
responses and overconfident in some decisions taken. This is consistent with previous
literature that has demonstrated a general tendency for overconfidence (Lichtenstein et
al., 1977). Importantly, none of the participants had any prior knowledge of air defence
decision-making. Consequently, an additional explanation for elevated confidence levels
can be explained by the Dunning–Kruger effect (Kruger & Dunning, 1999) where
unskilled/novice individuals assess their ability to be too high. The study also examined
how SA and WL relate to decision confidence, accuracy, and W-S C-A. It was found that SA
was related to decision confidence. Individuals who reported higher levels of SA were also
more confident in their decisions. However, these findings should be taken with caution.
SA was measured subjectively and a confidence bias has previously been found in SA
reporting (Sulistyawati & Chui, 2009). Thus, it might be that individuals are generally
confident in their assessments of SA performance. Importantly, SA was not related to
accuracy in decisions taken. Individuals may privately believe they had a better
understanding of the situation than they demonstrated. Conversely, WL was found to be
negatively related to overall decision confidence. Higher reported levels of WL resulted
in lower levels of decision confidence. This is important for decision-making; reduced
confidence in decisions taken could lead to increased WL. Individuals may seek out more
information to support or contradict decision certainty. Further analysis of the WL
dimensions showed significant differences in individuals’ feelings of temporal demand in
the high TL condition. Participants felt more time pressured and reported the speed at
which the task events occurred to be higher. Time pressure has been linked to individuals
using different decision-making strategies (Maule, Hockey, & Bdzola, 2000); thus, speed of
decision events may play an important role in critical environments. Further research with
experts may demonstrate a mitigated effect. The investigations into broad personality
constructs were found to be unrelated to confidence, accuracy, W-S-C-A, or SA. This
suggests the constructs may not be related to these measures or sufficiently salient in
decision-making processes. Relationships did exist with other measured constructs.
Individuals less tolerant to ambiguity were less accurate in their decisions, and high
scorers on the decision style scale were also less accurate. Budner (1961) argues that
individuals who are less tolerant find ambiguous situations threatening. It is probable
that a lack of tolerance hindered individuals’ ability to make accurate decisions.
Tolerance to ambiguity is a likely desirable trait for accurate air defence decision-
making. Further, although not replicated in this study, Wheatcroft et al. (2017) found an
intolerance of ambiguity was negatively related to W-S C-A (i.e., a greater tolerance of
ambiguous conditions was related to increased W-S C-A). Further research is warranted to
investigate the relationship between decision-making and ambiguity tolerance in critical
environments. Outcomes also showed WL to be negatively related to openness to experience,
providing support for the findings that some aspects of personality impact the perception
of WL (Chiorri, Garbarino, Bracco, & Magnavita, 2015). Although the study was initially
interested in the OR role and novice capacity to the task, one limitation was the use of
novice participants rather than experts. However, it may be beneficial to the NDM paradigm
to understand how expertise is developed (Hoffman and Klein (2017); Sala & Gobet, 2016).
For instance, Klein, Hintze, and Saab (2013) developed the shadow box technique which
helps novices understand the decision-making processes of experts. Therefore, the use of
novices in this study does allow for a baseline comparison. The use of novices may also
help to understand the training needs of less experienced decision-makers. The authors
will use experts to further validate the work in future research. Research has found that
practice can degrade certain aspects of metacognitive performance (Jackson, Kleitman, &
Aldman, 2015). However, this study minimised this effect by reducing potential fatigue. It
has been argued that NDM research should use a mixture of measures to reduce the
limitations of using a single methodology (Lipshitz et al., 2001). This paper aimed to
introduce the W-S C-A measure to assess an element of metacognitive ability in air defence
operators using a realistic decision-making scenario together with combined objective and
subjective measures. The proposed method and outcomes will provide a wider view of
metacognition in critical decision-making environments. The broader implications include
the potential for the approach to be used to prioritise training and selection, with the
aim of improving effective air-defence decision-making.

<h>CONCLUSION</h>
----------

This study found that decision criticality has significant impact on both decision
accuracy and confidence. Future work should consider the impact of decision criticality
and tolerance of ambiguity on accurate air defence decision-making.

<h>AUTHOR CONTRIBUTIONS</h>
--------------------

All named authors were involved in the conception and design of the study, critical
revision of the article, and final approval of the published version. The first author was
responsible for data collection and data analysis, interpretation, and in drafting the
final article.

<h>CONFLICTS OF INTEREST STATEMENT</h>
-------------------------------

No conflicts of interest are declared.


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<ART>Measuring implemental delay in procrastination: Separating onset and sustained goal striving
================================================================================

Authors: Frode Svartdal, Katrin B. Klingsieck, Piers Steel, Thor Gamst-Klaussen
DOI: 10.1016/j.paid.2019.109762
Year: 2020
ASJC codes: 3200
Keywords: Confirmatory factor analysis, Measurement, Procrastination, Procrastination scale

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Scales measuring procrastination focus on different aspects of unnecessary and unwanted delay, delay in task implementation – an increased gap between intention and action – being a core characteristic. However, an inspection of existing procrastination scales reveals that the scales do not distinguish between two facets of implemental delay, onset delay, and delay related to sustained goal striving. We trace this failure to an imprecise understanding of “delay,” another core concept in procrastination. This paper discusses the relationship between onset and sustained delay in procrastination, and then describes a new scale attempting to measure these two facets of task implementation. In two studies (aggregated N = 465) we demonstrate, using exploratory and confirmatory factor analysis, that although onset and sustained action procrastination measures correlate, they are still separate facets of implemental procrastination. Problems with onset delay seem to be particularly important, increasingly so in high procrastinators. Implications, as well as suggestions for further research, are discussed.

--------------------------------------------------------------------------------


MEASURING IMPLEMENTAL DELAY IN PROCRASTINATION: SEPARATING ONSET VS. SUSTAINED GOAL STRIVING
--------------------------------------------------------------------------------

Motivated behavior extends over time. Following a decision, the individual must plan how
to implement it, then follows goal striving or implementation, and finally goal attainment
if successful (e.g., Achtziger & Gollwitzer, 2018). People may procrastinate – delay
unnecessarily – in all these stages (e.g., Svartdal & Steel, 2017), and scales have been
developed to measure procrastination in each. For example, the Decisional Procrastination
Scale (DPS, Mann, 1982, unpublished; Mann, Burnett, Radford, & Ford, 1997) focuses on
delay in decision-making and onset of implementation. General procrastination scales, such
as the General Procrastination Scale (GPS; Lay, 1986) address various examples of
implemental delay. Finally, McCown and Johnson's Adult Inventory of Procrastination Scale
(AIP; McCown, Johnson, & Petzel, 1989) includes items related to promptness, meeting
deadlines, and timeliness. A closer inspection of the procrastination literature reveals,
however, that although implemental delay is a key feature of the procrastination problem
(e.g., Klingsieck, 2013; Steel, 2010), this core concept has rarely been explicated in the
procrastination literature. By definition, procrastination is a dysfunctional delay of
intended behavior, with procrastinators tending to demonstrate larger intention-action
gaps compared to non-procrastinators (e.g., Steel, Brothen, & Wambach, 2001). However, as
reviewed by Sheeran and Webb (2016), the intention-action gap addresses three rather
distinct phases of goal pursuit – initiation, maintenance, and close when the goal has
been attained. Sheeran and Webb noted that different factors are involved when problems
occur in these phases. For example, failure to get started may be rooted in factors such
as forgetting to start, indecision about means, second thoughts, and failure to engage in
preparatory behaviors. On the other hand, not keeping goal pursuit on track relates to
factors such as failure to monitor goal progress, competing goals, bad habits, disruptive
thoughts and feelings, and low willpower. In support, Steel and Weinhardt (2018) adopt a
similar three-stage model for their Goal Phase System and note that the motivational
forces operating during the beginning of a goal are not necessarily the same as those
later, particularly during goal-striving or realization. For example, high expectancy or
confidence assists the initial goal choice but can have a negative effect during goal-
striving as those overconfident in their abilities may underinvest in allocation of time
and resources. Similarly, impulsiveness can have a neutral or positive effect with goal
choice, interacting with extrinsic rewards, but often hampers goal striving until just
before deadlines.1 Unfortunately, the procrastination literature seems to have focused
primarily on delay in goal pursuit initiation, often neglecting that procrastination
manifests itself also in goal maintenance pursuit (cf. Gollwitzer, 2014). One reason for
this situation may be that delay – a defining criterion for procrastination – is
ambiguous. Often, “delay” is used as a temporal judgment of unnecessary delay (e.g., as in
item 2 in the DPS, “Even after I make a decision I delay acting upon it”), and some seem
to restrict procrastination to such cases (Tice, Bratslavsky, & Baumeister, 2001, p. 63).
However, “delay” is also used in another meaning, referring to indirect delays as a result
of impulsive diversions and other forms of wasting time during intention implementation
(as in item 12, GPS, “In preparing for some deadline, I often waste time by doing other
things”). We argue that both usages are legitimate, but that the first seems to be the
default interpretation whereas the second has often been overlooked in the procrastination
literature, and especially so in scales measuring procrastination. In the next paragraph,
we expand on these two arguments. Then we present, in two studies, a new scale attempting
to measure two facets of implemental delay, onset delay, and delay in sustained goal
striving.

<hs>  On “delay” as used in defining the procrastination construct</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Procrastination is defined by two core characteristics, the first being the delay of some
intended behavior, the second that this delay is chosen despite realizing the negative
consequences of the delay (Klingsieck, 2013; Steel, 2007). The latter criterion implies
that procrastination is “irrational” in the sense that the individual acts against better
judgment, often referred to as akrasia (Andreou & White, 2010). This understanding of
procrastination implies that internal norms and cognitive-affective evaluations of delay
play an important role in identifying procrastination (Milgram & Naaman, 1996; van Eerde,
2000). Furthermore, procrastination must be distinguished from rational forms of delay, as
many forms of delay of intended behavior may be adaptive, rational, and beneficial.
Importantly, a definition of procrastination in terms of delay despite better judgment may
leave the impression that all forms of procrastination are defined in terms of timing.
Given a model of goal-directed action flow from deliberation → planning → action →
evaluation (e.g., Achtziger & Gollwitzer, 2018), timing would primarily be relevant in the
transitions between deliberation and decision (decisional procrastination), between
intention formation and intention realization (the intention-action gap), and finally in
goal attainment (e.g., timeliness). In these cases, unnecessary or irrational delay may be
observed in accordance with the above definition. However, many instances of intended acts
unfold over longer periods where dilatory behaviors may manifest themselves in ways that
create indirect delays in goal striving, yet without involving delays according to
temporal criteria. First, engaging in competing activities may delay goal-directed
behavior in an indirect way, as less time – and less adequate time – is spent on the
prioritized goal activity (cf. Lay, 1986, Study II). Accordingly, several scales contain
items addressing preference for other activities, as for example the GPS (Lay, 1986) item
1 (“In preparation for some deadline, I often waste time by doing other things”) and the
IPS (Steel, 2010) item 4 (“When I should be doing one thing, I will do another).” Note
that for these items there is no mention of delay per se; delay in goal implementation
results from engaging in competing activities. Accordingly, experience sampling of
procrastination (e.g., Pychyl, Lee, Thibodeau, & Blunt, 2000, Table 1) focuses on
activities that people actually do at the moment (e.g., watching TV) versus what they
should have been doing (e.g., studying), defining “procrastination” as doing something
other than what one should do. Second, a closely related variant of diversion during goal-
striving occurs when goal-directed behavior is impulsively diverted to more tempting
situational alternatives, indirectly creating delays in realizing goals (Schouwenburg,
1995; Steel, 2007; Steel, Svartdal, Thundiyil, Brothen, 2018). Such impulsive diversions
may address distractions and temptations that are available to the individual, and
susceptibility to them indicate present-bias preferences characteristic of procrastinators
(Steel et al., 2018). Examples include giving in to more pleasurable alternatives compared
to continued goal striving (e.g., watching TV instead of reading), dysfunctional forms of
mood-regulation (Sirois & Pychyl, 2013; Tice & Bratslavsky, 2000), and escape/avoidance
from something aversive (e.g., escaping from a stressful or boring task). Such forms of
delay reduce the amount of time spent on focal tasks (e.g., Tice et al., 2001, Experiment
3). Finally, procrastination during goal-striving may result from other overlapping
factors, such as poor self-monitoring, competing goals, dysfunctional habits, poorly
formulated goal intentions, low willpower, concentration problems, tiredness, and task
aversion (Gollwitzer, 2014; Schouwenburg, 1995; Sheeran & Webb, 2016; Steel et al., 2018).
Also, note that a conception of procrastination as a breakdown in self-regulation (Steel,
2007) implies that much of the procrastination problem expresses itself during the goal-
striving phase. Concluding from these examples, we suggest that “delay,” although being a
core criterion for procrastination, has remained inadequately clarified in the
procrastination literature. Whereas some forms of procrastination are easily identifiable
according to strict temporal criteria, others are less so and satisfy the delay criterion
only indirectly. Interestingly, Lay (1986), defined procrastination as “the tendency to
postpone that which is necessary to reach some goal” (p. 457), implying that
procrastination does not refer to a single act of delay, but to a tendency demonstrated
over time to delay goal-relevant acts. In effect, is seems to be important to recognize
that procrastination is a dynamic phenomenon unfolding over time, manifesting itself in
tendencies to act in ways that prove suboptimal in attaining goals. Such delays may result
from explicit delays as well as be a by-product of maladaptive strategies in sustained
goal-directed behavior. In both cases, the delays and strategies must be “irrational” or
akratic for them to be regarded as procrastination.

<hs>  How procrastination scales measure different goal phases</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The procrastination literature is unclear on the various stages of intended goal
realization, and so are scales attempting to measure procrastination. They do not
distinguish between delays in getting started (onset delay, defined in terms of a temporal
gap between intention formation and relevant goal-striving behavior) and failures in
keeping goal pursuit on track (delays created in indirect ways during goal-striving). We
examined 18 procrastination scales to determine their coverage of these implementation
facets. Some scales include items that address delayed onset, as the DPS (item 2, “Even if
I make a decision I delay acting upon it”), the GPS (item 1, “I often find myself
performing tasks that I had intended to do days before”), and the Unintentional
Procrastination Scale (UPS,(item 1, “I rarely begin tasks as soon as I am given them, even
if I intend to;” Fernie et al, 2017). In contrast, very few scales address issues during
goal-striving that may create unnecessary delay in more indirect ways. One exception is
the Academic Procrastination State Inventory (APSI; Schouwenburg, 1995). The APSI asks
respondents to indicate how “frequently last week did you engage in the following
behaviors or thoughts,” listing a number of examples related to disruption of goal
striving (e.g., “Gave up studying because you did not feel well, ” Drifted off into
daydreams while studying,” and “Experienced concentration problems when studying”).
However, this scale also contains items not addressing sustained goal striving (e.g.,
“Forgot to prepare things for studying”). Items in this scale were intended to cover the
three important facets of procrastination according to Schouwenburg, 1995, lack of
immediacy in intentions and behavior, a discrepancy between intention and behavior, and a
preference for competing activities, and were not intended to measure failure of goal
striving per se (cf. also Patzelt & Opitz, 2014). Other scales may address procrastination
during sustained goal striving but are ambiguous as to whether they also refer to onset
delay. For example, the GPS item 12 “In preparation for some deadline, I often waste time
by doing other things” may refer both to initiation and sustained goal striving. This
ambiguity also applies to the two IPS items discussed (IPS 2, “If there is something I
should do, I get to it before attending to lesser tasks” - R), and IPS 4, “When I should
be doing one thing, I will do another”). Table 1 summarizes items from existing
procrastination scales that address delays in onset and sustained goal striving2. As is
seen from the table, we have found only one scale addressing delay during goal striving,
and this scale is intended for use in academic settings. Fig. 1 illustrates the phases of
intended action, separating the implementation phase in onset versus sustained goal
striving (cf. Sheeran & Webb, 2016). As is indicated in Fig. 2, procrastination in these
phases may take different forms, and measuring them independently may be important. For
example, delayed onset implies that effort during sustained goal striving must be
increased if a task is to be completed within a fixed timeframe (e.g., Steel et al., 2018,
Fig. 1). In this case, even though the onset and sustained action procrastination measures
may be positively correlated, slow onset in high procrastinators predicts lower sustained
procrastination because slow starters must catch up to finish in time. Another issue of
interest is which of the two facets of procrastination – slow onset and delays in
sustained goal striving – best predict overall procrastination score. If, as suggested,
delayed onset is compensated by increased effort during goal striving, one may suspect
that onset delay is a main determinant of overall procrastination. Finally, as
procrastination implies reduced time spent on important tasks (Lay, 1986; Tice et al.,
2001), one may ask whether reduced time can be traced to late onset, to impulsive
diversions during goal striving, or to both. Given the compensation hypothesis discussed,
it is likely that onset delay may be the best predictor of reduced time spent on important
tasks.

        <hss>Onset delay</hss>

        As seen in Table 1, the GPS (Lay, 1986) contains two items addressing implemental
        delay, the DPS (Mann, 1982) one. Both items are included in the Pure
        Procrastination Scale (PPS; Steel, 2010; 6 and 8, from the GPS; 2 from the DPS).
        Furthermore, the Aitken Procrastination Inventory (API; Aitken, 1982) contains
        seven items explicitly addressing onset delay (e.g., “Even when I know a job needs
        to be done, I never want to start right away”; “It often takes me a long time to
        get started on something”). Finally, the Volitional Components Inventory /
        Volitional Components Questionnaire (VCI/VCQ (Kuhl & Fuhrmann, 1998) contains four
        items addressing swift action when action possibility presents itself, thus being
        inconsistent with delayed onset (e.g., “When something needs to be done I start
        without hesitating,” “When a task needs to be done, I like to do it right away”).
        Most of these items address onset delay (or the opposite), but they generally fail
        to address two important features of procrastination, delay in the context of an
        explicit intention, and general delay versus procrastination. Hence, we slightly
        modified some items (marked in italics in Table 2) to reflect intentions and
        akratic delay. The authors discussed a pool of 18 possible items and selected,
        based on content analysis, six items for use (Table 2). The two first items are
        from the GPS (also used in the PPS) and may serve as a benchmark for the other
        onset items, as they have proven successful in numerous studies of implemental
        delays (e.g., Svartdal & Steel, 2017).

        <hss>Sustained goal pursuit delay</hss>

        As discussed, whereas onset delay primarily relates to a timing criterion (“I will
        start tomorrow, not today”) or prioritizing (“I will do X rather than Y, even if
        both are possible”), sustained goal striving relates to commitment and having the
        necessary time, focus, and energy to implement intentions over time. For aversive
        and boring tasks, other alternatives become tempting, and especially so when one
        gets tired, and exhaustion may result if the task is demanding, also increasing
        the likelihood of being tempted to do other and more attractive things (Steel et
        al. 2018). Hence, procrastination in this action phase may relate to, among other
        things, tiredness, exhaustion, focus (being distracted), temptations, nature of
        task (difficult, boring), tasks decided by others, taking a break to escape for a
        while, give in after minor setbacks, dislike hard work, typically not finish
        tasks, change one's mind, and others (e.g., Schouwenburg, 1995). Table 3 lists the
        items selected for the present studies. All were custom made for this study, but
        several were inspired by items in the APSI scale (Schouwenburg, 1995).

        <hss>Delay in reaching the intended goal</hss>

        Finally, to cover the end of goal pursuit, we included items to measure meeting
        deadlines and timeliness (Table 4). Appropriate items are found in existing
        scales, especially in the AIP; (McCown et al., 1989; Svartdal & Steel, 2017). We
        also added custom items.

<hs>  The present studies</hs>
  ~~~~~~~~~~~~~~~~~~~

Study 1 assessed items purporting to measure different facets of procrastination (Tables
2–4) using exploratory factor analysis (EFA), both for item functioning as well as for
factor structure, the overall expectation being that items would organize into a three-
factor solution - onset, sustained goal striving, and timeliness. Study 2 further examined
these items using confirmatory factor analysis (CFA), testing the factor structure as
suggested by Study 1. Having established measures of onset procrastination versus
sustained goal striving procrastination, we compared these measures against a well-
established procrastination scale, the Irrational Procrastination Scale (IPS; Steel,
2010). This scale correlates highly with other general procrastination scales (Svartdal &
Steel, 2017, Table 7). We expected for these data that the three facets of procrastination
would correlate moderately to highly with the IPS score, and – as discussed – that the
onset subscale would demonstrate an especially close relationship to overall
procrastination score. Next, as delayed onset narrows the timeframe available for task
completion, we examined the relations between the onset and sustained procrastination
measures. Although these measures should correlate rather highly, a “compensation”
hypothesis predicts that individuals delaying onset must work even harder to complete
tasks in time. Hence, high procrastinators should demonstrate high onset procrastination
scores but relatively lower scores on the sustained goal striving procrastination measure,
whereas the opposite pattern should be observed in non-procrastinators. In both studies,
we also administered a simplified model of a typical task completion sequence based on the
model presented in Fig. 1 and asked participants to indicate the perceived difficulty
associated with each stage. Task difficulty is associated with procrastination (Steel,
2007), and this procedure therefore served as an independent measure of problems
associated with the various phases of intended action. Here we expected that the onset
phase would be especially prone to be perceived as difficult, and especially so with
increasing overall procrastination score. Finally, we measured self-reported time spent on
self-directed academic work. An overall expectation is that procrastination limits the
time available on a given project (Lay, 1986), suggesting a negative correlation between
self-directed academic work and procrastination score. Note that direct and indirect
delays have a common effect, as both limit the time available for goal-directed work.
Separating onset delay and sustained goal striving delay may give an additional
perspective to this picture, and again we expected onset delay to be particularly
predictive of time spent on academic work.

        <hss>Participants</hss>

        The sample comprised 170 students aged 18 to 48, mean age = 25.56 (SD=5.47). The
        majority of participants (85.7%) were females.

        <hss>Procedure and ethics</hss>

        Participants were recruited by circulating a survey on mailing lists and social
        media at several universities and high schools in Norway. All were informed that
        participation was voluntary and anonymous and that they could withdraw from the
        study at any time. Participants were given information about the purpose of the
        study together with a link to the online survey (www.qualtrics.com) and gave
        informed consent by pressing a “start the survey” button. The current project is a
        part of a larger project on procrastination, which has ethical approval from the
        Regional Ethical Board in Tromsø, Norway (REK nord 2014/2313).

        <hss>Material</hss>

        The item sets shown in Tables 3–5 were presented sequentially and rated on a
        5-point Likert scale with higher scores indicating increasing agreement. Then the
        survey presented a simplified model of a typical task completion based on the
        model presented in Fig. 1 and asked participants to indicate, on a 1-5 scale, the
        perceived difficulty associated with each stage. Finally, all responded to the
        six-item version of the IPS (Svartdal & Steel, 2017). The original IPS (Steel,
        2010) features nine items, of which three are reversed. In the six-item version,
        the reversed items are deleted. Both versions demonstrate good internal
        consistency, α = .85–.93, and the full and reduced versions correlate highly. All
        scale items are rated on a 5-point Likert scale, with higher scores indicating
        more procrastination.

        <hss>Analysis</hss>

        Exploratory factor analysis (EFA) was employed using principal axis factoring. An
        eigenvalue > 1 and the scree plot test were used to determine underlying factors.
        An oblique rotation (oblimin) was applied since the extracted factors were
        expected to be correlated. Analyses were performed in IBM SPSS statistics 25.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The EFA was appropriate as indicated by a Kaiser-Meyer-Olkin (KMO) measure of sampling
adequacy of above 0.906 and a highly significant Bartlett's Test of Sphericity (p<0.001).
The initial EFA analysis produced three underlying factors onset, sustain, and timeliness,
as indicated by eigenvalues above 1 (8.71, 1.89 and 1.50) and the scree plot, confirming
our overall expectation of the factor structure. Six items were reexamined based on low
factor loadings and/or double loadings, resulting in deletion: Onset items 4 (“Often I
start so late that I miss the deadline”) and 6 (“When I am to start tasks I planned to do,
I often end up doing something else instead”) demonstrated double loadings on the onset
and timeliness subscales. Sustain item 7 (“I can work on other things (check mail, FB, and
so on) while doing academic work”) was deleted due to low factor loading. The timeliness
item 1 (“I get short of time”) produced a double loading on onset and timeliness
subscales. Item 5, suggested to measure timeliness (“When I work on an assignment, I
typically finish before others”), loaded mainly on onset. Finally, “I lag behind on study
work” produced a double loading on onset and timeliness. We then repeated the EFA with the
13 items retained. Again, three factors with eigenvalues > 1 (5.86, 1.63, and 1.42)
appeared, accounting for 68.5% of the variance. The oblimin rotated loadings for each of
the retained items are reported in Table 5. In conclusion, these data support a three-
factor model, separating the two implemental facets onset and sustained goal striving, as
well as confirming that timeliness is a separate facet of procrastination (e.g., Svartdal
& Steel, 2017). Table 6 presents means and correlations between the three subscales, the
IPS, and difficulty ratings of the action phases. As expected, the onset subscale
correlated highly (r = .80), with the IPS, whereas correlations were lower for the other
subscales. To assess the relation between the onset and sustained procrastination scores
to general procrastination, a regression with IPS score as the dependent variable and
subscale scores as predictors indicated that only onset scores significantly predicted IPS
score, β = .70 (p<.001), whereas the sustained and timeliness subscales did not, β = .12
and β = .10, respectively. Hence, onset procrastination seems to be the better predictor
of general procrastination, consistent with it being the first factor extracted. To
further assess the relation between the two facet measures and general procrastination, we
performed an ANOVA with the procrastination facets as dependent variables and IPS levels
(IPS levels 1-5 as defined by the individual's absolute IPS score) as a categorical
predictor. As argued, the expectation for these data was that both onset and sustained
scores should increase with increased levels of general procrastination, but that this
change would be especially pronounced in the onset measure and less so in the sustained
measure. The ANOVA indicated an overall significant effect, F(4, 164) = 53.70, p < .001,
η2 = .57, reflecting that both facet scores increased with increasing IPS levels.
Importantly, the interaction effect was significant, F(4, 164) = 7.40, p < .001, η2 = .15,
indicating that onset problems escalated more than sustained goal striving problems over
increasing general procrastination levels. These results are displayed in Fig. 3 (left
panel). Note in this figure also that timeliness scores increase only modestly over
increasing IPS levels, and whereas overall onset and sustained procrastination means were
quite similar (2.74 and 2.83), the overall timeliness mean was significantly lower (1.63),
F(2, 328) = 135.06, p < .001, η2 = .54. Fig. 3 (right panel) shows the mean problem
ratings for the four task completion phases over different procrastination levels.
Difficulty ratings increased with increasing procrastination levels, F(4, 163) = 32.38, p
< .001, η2 = .44. In addition, the phase * procrastination level interaction was
significant, F(12, 489) = 2.10, p = .015, η2 = .05, reflecting that onset scores were
especially sensitive to overall procrastination levels. Table 6 displays the correlations
between the mean onset, sustained, and procrastination scores and action phase difficulty
ratings. Notably, both the onset and sustained procrastination scores correlated highly, r
= .67, with their corresponding difficulty ratings in the onset and sustained action
phases. Finally, the relation between time spent on self-directed academic work and
procrastination score (IPS) was negative, rS = -.33. The onset score correlated somewhat
higher with academic work, rS = -.38, the sustained lower, rS = -.22, indicating again
that onset problems contribute more to reduced time available for academic work.

<h>STUDY 2</h>
-------

Study 2 was performed as replication of Study 1, allowing for the use of CFA on a
sufficiently large independent sample.

        <hss>Participants</hss>

        The sample comprised 295 students between the ages of 19 to 55, mean age = 26.28
        (SD=7.56) years. The majority of participants (82%) were females.

        <hss>Procedure and ethics</hss>

        Participants were recruited by circulating the survey by email and on social media
        using assistants at several universities throughout Norway. See Study 1 for
        procedure and ethics information.

        <hss>Material</hss>

        The material was identical to that of Study 1, except that the timeliness item 2
        was not included in the data collection3. Hence, only two items were specified as
        indicators of the timeliness factor. The onset and sustain factors had four and
        six indicators, respectively, corresponding to those used in Study 1.

        <hss>Analysis</hss>

        CFA was employed using two estimators, robust maximum likelihood estimation (MLR)
        due to deviation from normality, and robust weighted least square (WLSMv) that is
        appropriate for ordinal data and relatively smaller samples (Kline, 2016, p. 326).
        Model fit to data was examined using standard fit indices (Brown, 2015),
        specifically the comparative fit index (CFI), the Tucker-Lewis index (TLI), the
        root-mean-square error of approximation (RMSEA), and standardized root-mean-square
        residual (SRMR). An RMSEA less than 0.05, CFI and TLI values greater than 0.95,
        and SRMR less than 0.05 represent a well-fitting model. RMSEA as high as .08
        indicates a reasonable fit, whereas RMSEA values ranging from .08 to .10 indicate
        mediocre fit and estimates above .10 indicate poor fit (Browne & Cudek, 1993;
        MacCallum et al., 1996). In evaluating the models, we conducted chi-square
        difference tests. When conducting chi-square difference tests using the MLR
        estimator, it is necessary to adjust the chi-square using the Satorra-Bentler
        scaling correction (for details, see Bryant & Satorra, 2012). When using the
        estimator for categorical data (i.e., WLSMV), the difference test  procedure using
        chi-square is applied (for details, see Asparouhov & Muthén, 2010). Analyses were
        performed with Mplus version 8.3.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

First, the fit of a three-factor model was compared to a single-factor model. As seen in
Table 1 (Appendix), the single-factor model produced a poor fit across estimators. The
three-factor model had a good fit with the WLSMv considering CFI>.95, TLI>.95, and
SRMR<.05, and a mediocre fit considering RMSEA=0.087, whereas MLR produced reasonable fit
(i.e., CFI>.90, TLI>.90, SRMR=.052) and mediocre fit (i.e., RMSEA=0.082). The chi-square
difference tests indicated support for the three-factor model (WLSMv Chi-square difference
= 209.986, df=3, p<0.001; MLR Chi-square difference 250.361, df=3, p<0.001). Second, based
on modification indices, errors of sustain items 1 and 4 were correlated with sustain item
2 and 3, and sustain item 2 was correlated with sustain item 3. In both cases, these steps
were reasonable, as these items demonstrate considerable overlap in meaning. Both the
single-factor and three-factor models were modified, resulting in a well-fitting three-
factor model and a poor-fitting single-factor model with both estimators. Again, a chi-
square difference test was employed yielding support for the three-factor model (i.e.,
WLSMv: chi-square diff=192.973, df=3, p<0.001; MLR chi-square diff=197.566, df=3,
p<0.001). Finally, an alternative model with sustain item 3 removed (because of high
similarity to sustain item 2) produced an even better fit using both estimators (see Table
1, Appendix). Again, based on modification indices using both estimators, errors of
sustain item 3 was correlated with sustain item 1 and 5. This modified model produced
excellent fit with the WLSMv (χ2 = 53.77, df=39, p=0.058; CFI=0.997; TLI=0.995;
RMSEA=0.025, and SRMR=0.025) and with the MLR (χ2 = 41.61, df=39, p=0.358; CFI=0.998;
TLI=0.997; RMSEA=0.016 and SRMR=0.029). Thus, the CFA confirmed the results of Study 1
supporting a three-factor model. The result of the CFA (MLR) is presented in Fig. 4 (left
panel). As noted, in Study 1 only onset score significantly predicted overall
procrastination score (IPS). Fig. 4 (right panel) displays the corresponding analysis for
the present study, using SEM to model how the three subscales predict IPS score. The model
demonstrated a good fit, CFI=0.974; TIL=0.968; RMSEA=0.041(90%CI 0.033 – 0.058);
SRMR=0.041. As is seen from the figure, onset significantly predicted IPS score, β = .68,
whereas the two other subscales demonstrated substantially lower but still significant
beta values, β = .18 (sustain) and .16 (timeliness). Table 7 presents means and
correlations between the three subscales and the IPS. The results were similar to those of
Study 1, the onset subscale correlating highly (r = .80) with IPS, and lower correlations
for the other subscales. The relation between the facet measures and general
procrastination demonstrated similar patterns as those observed in Study 1. First, the
ANOVA indicated an overall significant effect of the onset and sustained procrastination
facets over increasing levels of IPS, F(4, 223) = 69.99, p < .001, η2 = .56. Second, as in
Study 1, the onset * sustained interaction was significant, F(4, 223) = 6.78, p < .001, η2
= .11, reflecting that onset problems escalated more than sustained goal striving problems
over increasing general procrastination levels. These results are displayed in Fig. 5
(left panel).4 The timeliness scores increased over increasing IPS levels, but levels were
lower compared to the onset and sustained procrastination scores. Overall onset and
sustained procrastination means were quite similar (2.86 and 2.92), whereas the overall
timeliness mean was significantly lower (2.43), F(2, 446) = 18.13, p < .001, η2 = .08. The
problem ratings for the four task completion phases over different procrastination levels
demonstrated similar results as those of Study 1, see Fig. 5, right panel. First,
difficulty scores increased with increasing procrastination levels, F(3, 223) = 44.49, p <
.001, η2 = .37. Second, the phase * procrastination level interaction was significant,
F(9, 669) = 5.70, p < .001, η2 = .07, demonstrating that onset scores were especially
prone to increase as a function of general procrastination (IPS) levels. The relation
between time spent on self-directed academic work and IPS score was negative, rS = -.28.
Again, the onset score correlated somewhat higher with academic work time, rS = -.40, the
sustained lower, rS = -.18, indicating that onset problems contribute more to reduced time
available for academic work.

<h>GENERAL DISCUSSION</h>
------------------

The distinction between delayed onset and disruptions during goal-striving is well
established (e.g., Sheeran & Webb, 2016). Whereas the first primarily relates to timing
and manifests itself directly in terms of later onset, delay in sustained goal striving
occurs in a variety of direct and indirect ways. Thus, while delayed onset may address the
prototypical instance of procrastination, the Latin procrastinus literally referring to
something “belonging to tomorrow,” failure to stay on track toward a goal may be rooted in
a variety of disruptive factors, indirectly creating delay in goal striving. The latter
facet of procrastination is rarely addressed in procrastination research, nor in scale
construction. The lack of procrastination scales to address both facets of implemental
procrastination is unfortunate, even more so because this circumstance reflects an
insufficient understanding of the phenomenon in procrastination literature. The present
paper attempted to theoretically differentiate the two facets and to present a scale to
measure them. The scale proposed in the present paper explicitly addresses two phases of
task implementation, onset and continued goal striving. Results of Study 1 suggested a
three-factor structure corresponding to the suggested constructs onset delay, delay during
goal striving, and timeliness. The onset delay measure correlated highly with a standard
measure of general procrastination (IPS; Steel, 2010), whereas the two other measures
demonstrated lower correlations with the IPS. Study 2 replicated the first study with a
larger sample, allowing for a specific test using CFA of the factor structure. The results
confirmed the three-factor solution identified in Study 1. Correlational analyses repeated
the findings from Study 1, with a high correlation between the IPS and the onset delay
measure, and lower correlations with the sustained goal striving and timeliness measures.
Both studies indicate support for the specific role of onset delay in procrastination.
Specifically, an analysis of the relations between the three subscales over different
levels of procrastination (as measured by the IPS) demonstrated that the onset delay means
were lower relative to the sustained means for lower levels of procrastination, whereas
for higher levels of IPS the levels reversed. This shift indicates that onset delay
becomes an increasingly important problem as overall procrastination tendencies increase.
These results were supported by an independent measure of perceived difficulties
associated with the typical phases of planned action, decision, getting started, keeping
up sustained action, and finishing in time. Again, onset was identified as the most
problematic phase, and especially so by high procrastinators. Finally, self-reported time
spent on self-directed academic work was correlated with general procrastination score,
but higher so with the onset procrastination measure. In essence, the German saying “Aller
Anfang ist schwer” (“Every beginning is hard”) and the Norwegian expression
“dørstokkmila”(“the doorstep mile”) get a deeper meaning according to these data, as
starting something may be hard for everyone, and is even harder as overall procrastination
tendency increases. As delayed onset narrows the timeframe available for task completion,
but many tasks have a fixed time frame for completion, the present data indicate that late
onset may be compensated by increased effort during the sustained goal striving phase.
However, working harder under stricter time regimes fosters stress and suboptimal
conditions for work, which, in turn, probably lead to lower academic achievement if, at
all, the task is completed.

<hs>  Limitations and future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our results indicate that onset delay is particularly important in procrastination, but an
alternative interpretation is that procrastination during goal-striving is more difficult
to monitor and hence to report and measure. Specifically, onset delay is a construct
addressing timing, given an intention to act. Even if there may be various specific
reasons for delaying onset (e.g., indecision about means, second thoughts), the result as
perceived by the actor is a failure to start as intended. In contrast, delays during task
execution may be due to diverse and complex factors that work indirectly to create delay.
For example, low willpower can make situational temptations appear attractive, causing
impulsive diversions from planned action (e.g., Steel et al., 2018). Although such
diversions are themselves detectable, delays in task execution because of them may not be
equally obvious to the individual. Hence, as we are notoriously poor at monitoring
ourselves attentively when we attempt to self-regulate (Baumeister & Heatherton, 1996),
delays during task pursuit may be more difficult to self-report. Furthermore, the fact
that delayed onset often makes it necessary to increase goal striving effort to catch up
may indicate to procrastinators that they work as hard as, or even harder, compared to
others, even to non-procrastinators. Future research should assess these issues, also in
situations that are not compromised by differences in onset (e.g., in controlled
situations examining disruptions in goal striving with no differences between participants
in onset delay, cf. Tice et al., 2001, Experiment 3). Turning to the limitations of the
study, the sample size used in Study 1 is quite small. However, the factor loadings are
generally high (i.e., loadings ranging from .44 to .91). Studies have shown that moderate
to high loadings was the major factor in determining reproducibility (Guadagnoli &
Velicer, 1988; Tabachnick & Fidell, 2013). For instance, Guadagnoli and Velicer (1988)
suggested that a sample size of N≥100 was sufficient if four or more variables per factor
had loadings above .60. Further, the present research is based on two student samples,
suggesting that future studies should assess factor structure as well as relations between
onset delay and delay in sustained goal striving in samples from the general population as
well. Such studies should also assess scale properties over gender, age, and even cultures
(e.g., Kankaraš & Moors, 2010). Items used to assess sustained goal striving were inspired
by the work of Schouwenburg, 1995, and would profit from scrutiny and possibly adding
other items. In this respect, a limitation in Study 2 is the post-hoc modification to
improve the CFA model fit indices. Several measurement errors were allowed to correlate
among indicators of the sustain-subscale, which, as pointed out by Hermida (2015), moves
the model testing from being confirmatory to becoming an exploratory analysis. Error
correlations are likely due to sampling error, which may restrict cross-validation of the
structure in future studies (Hermida, 2015; Grant, 1996). Further, the underlying
structure may be masked if a relevant omitted variable is estimated through measurement
error (Cortina, 2002; Landis, Edwards, & Cortins, 2009). However, the model fit of the
non-modified three-factor model was generally in the range of an acceptable fitting model.
In particular, the alternative three-factor model (Appendix, Table 1) produced a good fit
to the data. This again suggests that items would profit from scrutiny and potentially
adding other items, and future research should address cross-validation and replication.
Another limitation of the present research is that we have utilized only one general
procrastination scale, the IPS (Steel, 2010), as a reference. Other scales may demonstrate
different relations to the subscales discussed in the present paper, even more so because
different scales focus on different facets of procrastination. Hence, future studies
should include other procrastination scales to verify the close relation observed between
overall procrastination and onset procrastination, and the relatively weak relation
between overall procrastination and procrastination in the goal-striving phase. Another
important step in validating the differentiation between onset procrastination and
procrastination in the goal-striving phase is to investigate whether the two facets relate
differently to motivational and volitional variables. As noted, the motivational forces
operating during the beginning of goal pursuit are not necessarily the same as those
important during later goal striving (Steel & Weinhardt, 2018). Thus, motivational
variables, such as expectancies and values, should be related strongly to onset
procrastination, whereas volitional variables, such as the ability to shield distractions
or willpower in general, should relate more strongly to procrastination in the goal-
striving phase. In a future study, we will relate the scale of the two facets to
instruments measuring the different forms of motivation (as in the Self-Determination
Theory; Deci & Ryan, 2008), strategies of regulation of motivation (Grunschel, Schwinger,
Steinmayr & Fries, 2016), volition (Kuhl, 1984), and energy (Steel et al., 2018).


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<ART>Medical students' attitudes towards people with intellectual disabilities: A literature review
================================================================================

Authors: Travis A. Ryan, Katrina Scior
DOI: 10.1016/j.ridd.2014.05.019
Year: 2014  |  Pages: 2316-2328
ASJC codes: 3203, 3204
Keywords: Attitudes, Health inequalities, Healthcare, Intellectual disabilities, Medical students

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The present paper provides a review of research on medical students' attitudes to people with intellectual disabilities. The attitudes of medical students warrant empirical attention because their future work may determine people with intellectual disabilities' access to healthcare and exposure to health inequalities. An electronic search of Embase, Ovid MEDLINE(R), PsycINFO, Scopus, and Web of Science was completed to identify papers published up to August 2013. Twenty-four studies were identified, most of which evaluated the effects of pedagogical interventions on students' attitudes. Results suggested that medical students' attitudes to people with intellectual disabilities were responsive to interventions. However, the evidence is restricted due to research limitations, including poor measurement, self-selection bias, and the absence of control groups when evaluating interventions. Thus, there is a dearth of high-quality research on this topic, and past findings should be interpreted with caution. Future research directions are provided. © 2014 The Authors.

--------------------------------------------------------------------------------


<hs>  Search strategy</hs>
  ~~~~~~~~~~~~~~~

The electronic databases Embase, Ovid MEDLINE(R), PsycINFO, Scopus, and Web of Science
were used to search for manuscripts that examined medical students’ attitudes to people
with ID. The search was conducted within the titles and abstracts of English language
journal articles published before the end of August 2013. Search terms were: (attitud* or
aware* or behave* or belief* or bias* or discriminat* or emotion* or experience* or
feeling* or opinion* or perception* or perspective* or prejudice* or stereotyp* or stigma*
or view*) and (down* syndrome or developmental* delay* or developal* disab* or intellect*
challeng* or intellect* disab* or learning disab* or mental* deficien* or mental*
handicap* or mental* retard*) and (medic* adj4 clerk* or medic* adj4 intern* or medic*
adj4 school* or medic* adj4 student* or medic* adj4 undergrad* or medico or md student* or
student doctor* or student physician*).

<hs>  Review process</hs>
  ~~~~~~~~~~~~~~

The authors discussed and established clear inclusion and exclusion criteria. They agreed
to only include studies that investigated medical students’ attitudes towards people with
ID and/or their healthcare. Given the limited amount of research on this topic, studies
that used measures of attitudes to people with disabilities (i.e., studies that did not
use ID-specific measures) to assess participants’ attitudes to people with ID were
included, as were studies whose participants were a combination of medical students and
professionals or other students. The authors agreed to exclude the following types of
articles: examinations of medical students’ views on training in ID, which did not assess
participants’ attitudes towards people with ID and/or their healthcare (e.g., Burge,
Ouellette-Kuntz, Isaacs, & Lunsky, 2008; Burge, Ouellette-Kuntz, McCreary, Bradley, &
Leichner, 2002); studies without a focus on ID (e.g., Beausoleil, Zalneraitis, Gregorio, &
Healey, 1994; Wonkam, Njamnshi, & Angwafo, 2006); and research without medical students
(e.g., Boyle et al., 2010; Parchomiuk, 2013). Then, the first author reviewed the
literature. Nine hundred and thirty-six items were imported into Zotero and 377 duplicates
were removed, leaving 559. After reading their titles and abstracts, 507 clearly
irrelevant items were deleted. The remaining 52 articles were read in full, with 28
irrelevant articles removed after this examination. This process resulted in the retention
of 24 studies that examined medical students’ attitudes towards people with ID. While the
Critical Appraisal Skills Programme (CASP; 2013) checklist for evaluating qualitative work
guided the review of Karl, McGuigan, Withiam-Leitch, Akl, and Symons (2013), the Cochrane
Public Health Group's (n.d.) quality assessment tool informed the review of the twenty-
three quantitative papers. The latter focused attention on the following topics: selection
bias, allocation bias, confounders, blinding, data collection methods, withdrawals and
dropouts, analysis, and intervention integrity.

<hs>  Overview of studies</hs>
  ~~~~~~~~~~~~~~~~~~~

Twenty-four articles published between 1968 and 2013 met the inclusion criteria, all of
which reported on separate studies. Studies mostly were conducted in the UK (n = 9),
followed by the USA (n = 8), Australia (n = 3), Ethiopia (n = 2), Canada (n = 1), and
China (n = 1). Eighteen studies sampled medical students only (e.g., Hall & Hollins, 1996;
Khandelwal & Workneh, 1987) and 6 used samples that included medical students and other
groups (e.g., healthcare professionals; Handler, Bhardwaj, & Jackson, 1994). All studies
used surveys (with closed and/or open-ended questions) to assess students’ attitudes; no
focus groups or interviews were conducted. Twelve studies used a pre-test post-test
design, 10 cross-sectionally analysed attitudes, 1 was experimental, and another was
qualitative. Using the aforementioned critical appraisal tools, each study's strengths and
limitations were determined. Strengths included low attrition rates and attention to
inter-group contact theory (Pettigrew, 1998) to explain medical students’ attitudes.
However, these strengths were offset by disadvantages. For example, most studies employed
ad-hoc measures with questionable psychometric quality; no study blinded researchers to
the intervention; and only Sinai et al. (2013) reported a power calculation. The studies
are reviewed in the following sections and an overview is given in Table 1.

<hs>  Studies on attitude interventions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Findings suggested that interventions disparately affected attitudes; however, there were
methodological concerns.

        <hss>Research suggesting minimal or no attitudinal change</hss>

        Sinai et al. (2013) investigated attitudes towards the community inclusion of
        persons with ID among fourth-year medical students in the UK. The students
        reported favourable attitudes and these remained unchanged after a 14-week
        neurosciences block that included ID teaching. However, results should be
        interpreted with caution. It is unclear if participants attended the teaching
        block, and self-selection bias may have influenced results as only 136 and 133
        students completed the questionnaire beforehand and afterwards, respectively,
        despite 387 students invited to participate. An amended, shortened version of the
        Community Living Attitudes Scale–Mental Retardation (CLAS-MR; Henry, Keys, Jopp, &
        Balcazar, 1996) was used, whose psychometric properties have not been assessed.
        Also, mean imputation for missing data was employed, a strategy that should be
        avoided (Allison, 2001). Laking (1988) compared UK medical students who had, and
        had not, completed a course on ID psychiatry. A modified version of the Attitudes
        to Disabled Persons Scale (ATDP; Yuker, Block, & Campbell, 1960) was employed.
        Items were changed with “mentally handicapped” replacing “disabled,” which is poor
        psychometric practice because word substitution is unlikely to produce items that
        optimally measure the intended latent construct. Students were not randomly
        assigned to conditions (i.e., course completion or not) and there appears to have
        been a self-selection bias (i.e., most students who completed the course reported
        previous contact with this group, which may not be representative of medical
        students). Also, listwise deletion was used for cases that did not complete the
        ATDP, a suboptimal strategy for the management of missing data (Allison, 2001).
        The two groups reported comparable attitudes and Laking (1988) suggested that the
        ATDP might not be sensitive enough to detect changes in attitudes over time. May
        (1991) also studied ID teaching's impact on UK medical students’ attitudes. In
        general, most students supported the rights of this group; however, before
        teaching, only 42%, 33%, and 13% supported their rights to have children, leave
        home upon adulthood, and attend mainstream schools, respectively. Although
        students were more likely to support people with ID's right to attend mainstream
        schools after the intervention, results suggested that teaching typically did not
        improve attitudes. However, the “crude measuring instruments” (May, 1991, p. 241)
        might have been unable to capture attitudinal change.

        <hss>Research suggesting worsened attitudes</hss>

        Khandelwal and Workneh's (1987) study demonstrated that an intervention might
        deleteriously affect attitudes. They found that the attitudes of 100 Ethiopian
        medical students worsened after a six-week full-time course in psychiatry. The
        course covered various conditions including ID, with students completing a
        measure, designed by the authors, before and after. Participants’ responses
        suggested that, upon completion of the course, more students believed that people
        with ID were unable to work or marry. For example, beforehand, 35% of students
        believed it was impossible for someone with ID to get married; however,
        afterwards, this figure increased to 65%. The intervention's non-specificity to
        ID, and the assessment tool's narrow focus, may be limitations.

        Research suggesting improved attitudes: intellectual disabilities-specific measures

        Several studies reported that interventions led to self-reported improvements in
        attitudes among medical students (e.g., Fishler, Koch, Sands, & Bills, 1968; Hall
        & Hollins, 1996; May et al., 1994; Simeonsson, Kenney, & Walker, 1976; Thacker,
        Crabb, Perez, Raji, & Hollins, 2007). Using a sample of 12 American medical
        students (two did not complete post-test measures), Simeonsson et al. (1976) found
        that participants reported more positive attitudes towards people with ID after
        training on the topic. The authors also found more positive self-reported
        attitudes among participants that had better experiences of persons with ID.
        However, descriptive statistics only were given and psychometric support for their
        measure was not provided. Fishler et al. (1968) also researched American students
        (N = 36), finding that they were less likely to rate sterilisation and custodial
        as important areas in ID, and more likely to rate medical and psychological as
        important areas, after clinical experiences in the area. Despite these
        experiences, and contrary to Fishler et al.’s expectation, students’ advice
        regarding institutional versus home care for children with ID did not change.
        However, analyses may have lacked power due to the small sample. The effects of ID
        training on American medical students’ (N = 39) beliefs about people with ID's
        functionality also have been examined (Widrick et al., 1991). Scores on the
        Prognostication about Mental Retardation Scale (Wolraich & Siperstein, 1983)
        suggested that students were more optimistic about what people with ID can achieve
        after the intervention, with people with mild ID ascribed the greatest functional
        ability, followed by persons with moderate and severe ID, respectively. Students’
        comments, which also were recorded, suggested that they believed the intervention
        and, in particular, meeting with this population, increased their expectations
        about people with ID. Boyd et al. (2008) examined the efficacy of an intervention
        that aimed to reduce 101 American students’ difficulty with working with people
        with developmental disabilities. Results suggested that the intervention, which
        involved training with a virtual patient, achieved a reduction in students’
        perceived difficulty with providing care to this population. However, only four
        participants were medical residents, therefore limiting the relevance of this
        study to understanding medical students’ attitudes to people with ID. Hall and
        Hollins (1996) found that, among 28 medical students in the UK, attitudes towards
        people with Down's syndrome improved on 7 of 10 items after taking part in a
        workshop with actors with ID. For example, students were less likely to report
        that people with ID have little sense of humour and act like children most of the
        time. Thacker et al. (2007) used the same measure to examine a teaching
        intervention's effects on the attitudes of medical students in the UK towards
        people with ID. Again, the intervention involved actors with ID. Thacker et al.
        (2007) stated that, compared to 14 students who did not take part in the role-
        plays, the 26 students who did reported relatively positive attitudes. It was
        unclear whether the students were randomly allocated to attending or not, or if
        attendance was volitional. Further, neither Hall and Hollins (1996) nor Thacker et
        al. (2007) provided psychometric information about their measurement tool; thus,
        its reliability and validity are unknown, making the interpretation of results
        difficult.

        <hss>Research suggesting improved attitudes: generic measures</hss>

        Studies that used measures of attitudes towards persons with disabilities in
        general also suggested that ID teaching/training enhanced medical students’
        attitudes (e.g., Tracy & Graves, 1996; Tracy & Iacono, 2008). However, such
        measurement is problematic as scales non-specific to ID may omit critical aspects
        of students’ attitudes towards this clinical group. Tracy and Graves (1996)
        examined whether an optional teaching unit on developmental disabilities
        influenced the attitudes of 25 Australian first-year medical students. At the
        beginning and end of the unit, students reported their thoughts and feelings
        towards people with disabilities and the patients’ families. Before teaching, 56%
        of participants expressed discomfort and lack of confidence working with people
        with disabilities, and 92% wanted to become more knowledgeable about the area.
        Afterwards, 92% reported that their attitudes had changed over the course of
        teaching, with qualitative comments typically suggesting attitudinal improvement
        and identifying inter-group contact as an important change mechanism. However, due
        to the measure's non-specificity to ID, it is possible that the students’
        attitudes towards interacting with people with ID remained unchanged or worsened,
        whilst their comfort interacting with people with other disabilities increased. As
        measures’ psychological constructs should be specific to the research goals
        (DeVellis, 2003), the validity of such findings is questionable. Tracy and Iacono
        (2008) evaluated changes in 128 Australian fourth-year medical students’ attitudes
        towards interacting with people with disabilities after training on developmental
        disabilities and communication skills. The students completed the 20-item
        Interaction with Disabled Persons Scale (Gething, 1994), which measured discomfort
        interacting with persons with a disability, before and after the intervention.
        Results suggested that the students were more comfortable interacting with people
        with disabilities after the intervention, with 77% of students valuing the
        opportunity to meet people with disabilities during the intervention. However, as
        with Tracy and Graves (1996), these findings are difficult to interpret due to the
        measure's lack of specificity. Andrew, Siegel, Politch, and Coulter (1998) also
        used a generic measure of attitudes to those with disabilities in their evaluation
        of training, which included experiences with children with developmental
        disabilities. Little information was given about the chosen measurement tool and
        its psychometric properties are unknown; however, descriptive results suggested
        that students enjoyed and learned from the experience. Most students reported that
        their attitudes at least moderately changed, with 30% indicating unchanged
        attitudes. Attitude change was mostly attributed to a new awareness of family
        dynamics, and the most commonly reported behavioural intention arising from the
        intervention was a need for greater sensitivity when interacting with children
        with disabilities.

        <hss>Research suggesting improved attitudes: qualitative work</hss>

        Karl et al. (2013) qualitatively examined medical students’ written responses to
        an Internet survey on their reflections about a clinical experience, in which they
        met patients with developmental disabilities and worked with professionals in this
        area. A survey was used to avoid interviewer and response bias; however, the
        author did not describe consideration of the relationship between the researcher
        and participants as recommended by CASP (2013), and interviews or focus groups may
        have produced richer data. Results suggested that, after the intervention,
        students better understood the need to overcome communication barriers; were more
        comfortable caring for this population; and were more aware of diagnostic
        overshadowing and this group's right to equal healthcare standards.

<hs>  Cross-sectional attitudinal studies that did not evaluate interventions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

While cross-sectional research has provided snapshots of medical students’ attitudes
towards this population, studies frequently lacked methodological rigour. Lennox and
Chaplin (1995) used four attitudinal items to examine the attitudes of 128 psychiatric
trainees and 27 medical officers in Australia. Despite 30% of participants reporting that
they would personally prefer not to treat people with ID and a psychiatric disorder, the
majority of participants endorsed the need to investigate psychiatric symptoms among
persons with severe ID, and recognised the utility of psychotherapy for persons with ID
and a psychiatric disorder. No information on item generation was provided, and a
rationale for the inclusion of only four items was omitted. Li, Tsoi, and Wang (2012)
found that 280 Chinese students of education or medicine reported comparably favourable
attitudes towards the inclusion of persons with ID. Participants with more experience with
this population, and females, reported more positive attitudes. However, the use of the
Mental Retardation Attitude Inventory-Revised (Antonak & Harth, 1994) among Chinese people
may be questioned because its factor structure was not replicated among a sample of
Chinese people (Hampton & Xiao, 2008). Ouellette-Kuntz et al. (2012) found that 258
Canadian medical students with experience of people with ID were more likely than those
without such experience to score higher on sheltering (e.g., the belief that this
population should be protected). Further analysis revealed that 88.5% of those with
experience typically reported meeting with five or fewer persons with ID. Thus, their
experience and consequent understanding may have been limited (Ouellette-Kuntz et al.,
2012). Supervision's salience to attitudes emerged, with those who reported positive
supervision experiences scoring higher on the empowerment of people with ID, and lower on
the need to protect them in the community (Ouellette-Kuntz et al., 2012), than students
who reported negative experiences of supervision. Whilst interesting, this study may have
been limited by the authors’ decision to use the CLAS-MR (Henry et al., 1996), as it only
measures attitudes towards community inclusion and neglects a focus on medical students’
attitudes to providing healthcare to people with ID. Holt and Bouras (1988) used a short
questionnaire based on McConkey and McCormack (1983) to examine 166 British medical
students’ attitudes towards people with ID. Findings predominantly indicated that students
held favourable attitudes towards this clinical group, with 10% saying that they wanted to
work in services for people with ID and participants typically disagreeing that people
with ID would always act like children. Although encouraging, results may be explained by
students’ socially desirable responses and the measurement tool's psychometric qualities
are unknown. Wishart and Johnston (1990) examined stereotypical beliefs about children
with Down's syndrome among different groups of British people, including 10 medical
students. The role of previous contact with this group also was studied. In general,
participants with more experience were less likely to endorse stereotypes, and medical
students reported less stereotypical beliefs than other groups, including mothers with
children with Down's syndrome. However, the measurement tool's content validity is
questionable, and no psychometric information was provided, reducing the interpretability
of the findings. Prognostic beliefs among 136 medical students and 149 healthcare
professionals in the USA also have received empirical attention (Handler et al., 1994),
with students reporting lower expectations about people with ID than their qualified
peers. Perhaps, counterintuitively, students’ beliefs were unrelated to having a family
member with a disability or working with people with disabilities. Compared to medical
students in earlier years, fourth-year medical students reported more optimistic beliefs
about this group's potential. Students were most pessimistic about people with severe ID,
followed by those with moderate ID, and lastly persons with mild ID. Khandelwal and
Workneh (1986) used vignettes to assess 60 Ethiopian medical students’ attitudes to
various conditions, including ID. Ninety-two per cent of students said the person with ID
was ill; 62% regarded it as a very serious illness; and 20% said the prognosis would
worsen. Only 7% reported that the person with ID had the same ability to marry as anybody
else, while 82% and 92% said the person would have at least some difficulty living at home
and working, respectively. Scott and Rutledge (1997) used an uncited ATDP to investigate
the attitudes of 80 American first-year medical students to people with ID. The authors
claimed the scale's reliability and validity when measuring attitudes towards those with
disabilities; however, its specificity to ID and psychometric properties were not
detailed. Scott and Rutledge suggested that scores on the ATDP indicated that most
participants did not have negative attitudes towards people with ID. Most participants
reported that they were willing to work with this population and believed that people with
ID should live in the community.

<hs>  Experiment on attitudes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

St. Claire (1993) examined the role of social identification among 7 doctors and 38
medical students in the UK. The author hypothesised that, compared to participants whose
personal identities purportedly were activated; those with activated clinical identities
would report more negative beliefs about people with ID and be more likely to attribute ID
to children. Participants were randomly assigned to either condition and therefore
received questionnaires titled, “Medical diagnosis and visual cues” or “Personality and
person perception.” Participants in the clinical identity condition reported more negative
beliefs than those in the personal identity condition, but people in both conditions were
equally accurate distinguishing between children with and without ID. However, as a
manipulation check suggested different social identities might not have been activated,
this study's findings should be interpreted with caution.

<h>DISCUSSION</h>
----------

This literature review identified 24 articles regarding medical students’ attitudes
towards people with ID. The majority of the evidence reviewed consisted of evaluations of
teaching/training interventions that sometimes resulted in improved self-reported
attitudes. As these interventions often involved students interacting with people with ID
(e.g., Hall & Hollins, 1996), findings are consistent with intergroup contact theory,
which posits that contact between groups usually reduces prejudice (Pettigrew, 1998).
Thus, opportunities for medical students to gain experience with this clinical group may
be a key component of future attitudinal interventions. However, as recommended by
Corrigan and Penn (1999), interventions to reduce stigma “should not be accepted on faith”
(p. 765); instead, their theoretical underpinnings and empirical support warrant scrutiny.
This point seems particularly salient, as ID stigma research has not used systematic
approaches with conceptual models (Ditchman et al., 2013). To address this omission,
future research may experimentally examine interventions characterised by intergroup
contact under optimal conditions of equal status between groups, shared goals, cooperation
between groups, and organisational support (Allport, 1954); high levels of intimacy
between groups; and minimal differences between the persons with ID involved and their
stereotype (Corrigan & Penn, 1999). As the number, frequency, and quality of contacts may
be important (Morin, Rivard, Crocker, Boursier, & Caron, 2013), the roles of these
variables should be assessed. Also, as students’ attitudes towards persons with ID may be
associated with their supervision (Ouellette-Kuntz et al., 2012), future research may
examine if quality of placement supervision moderates the effectiveness of interventions
on students’ attitudes and future clinical behaviours. In line with other areas of ID
research (Ditchman et al., 2013; Rose, Rose, & Kent, 2012; Werner, Corrigan, Ditchman, &
Sokol, 2012), there is a need for scale development. Specifically, a measure of medical
students’ attitudes to people with ID is needed if the efficacy of interventions is to be
determined in a valid manner. As precise definitions of psychological constructs
facilitate valid measurement (Eagly & Chaiken, 2007), the conceptualisation of medical
students’ attitudes to persons with ID requires empirical attention. According to Eagly
and Chaiken (2007), attitudes may be: (a) covert or overt; (b) cognitive (e.g., thoughts
and beliefs), behavioural (e.g., intensions and overt actions), or affective (e.g.,
feelings and emotions); and (c) conscious or unconscious. Eagly and Chaiken (2007)
described explicit and implicit attitudes, noting that the former represent evaluations
reported by the person holding the attitude, and the latter represent spontaneous
emotional reactions that the person may not be consciously aware of. As explicit and
implicit attitudes may predict volitional and spontaneous behaviour, respectively, both
warrant empirical attention (Eagly & Chaiken, 2007). Further, people may hold an explicit
attitude and an implicit attitude towards the same entity, and each may be differentially
affected by an intervention (Wilson, Lindsey, & Schooler, 2000). Thus, future research may
wish to examine the effects of pedagogical interventions on explicit and implicit
attitudes of medical students.

<h>CONCLUSION</h>
----------

This review suggests that teaching and training may improve medical students’ attitudes,
with interventions driven by intergroup contact theory (Pettigrew, 1998) holding promise.
However, the review also identifies the need for more robust research to accurately
understand (a) medical students’ attitudes towards people with ID and (b) the kinds of
interventions that improve these attitudes. Attitude enhancement is the ultimate goal of
research on ID stigma (Ditchman et al., 2013). Indeed, if tomorrow's doctors’ attitudes
towards this population do not improve, efforts to reduce health inequalities experienced
by people with ID (Emerson & Baines, 2010; Turner & Robinson, 2010) may well have limited
success.


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<ART>Mistaken max befriends Duplo girl: No difference between a standard and an acted-out false belief task
================================================================================

Authors: Beate Priewasser, Franziska Fowles, Katharina Schweller, Josef Perner
DOI: 10.1016/j.jecp.2019.104756
Year: 2020
ASJC codes: 3204, 3205
Keywords: Acted-out false belief tasks, Cognitive development, False belief understanding, Implicit false belief, Social cognition, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

With their Duplo task, Rubio-Fernández and Geurts (2013) challenged the assumption that children under 4 years of age cannot pass the standard false belief test. In an attempt to replicate this task on a sample of 73 children aged 32–51 months, we added a standard change of location false belief task as well as a Duplo true belief task. Performance on the latter is crucial for interpreting answers in the Duplo false belief task as to whether they reflect evidence for understanding or merely exhibit a difference in guessing rate. We found (a) a greater variability of response types in both Duplo tasks, (b) no evidence that responses in the Duplo tasks reveal earlier competence than those in the standard false belief test, and (c) a reassuring correlation between false belief tasks, suggesting that the Duplo task does pick up understanding of belief in light of the standard test.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The classical finding that the standard false belief test—also known as the “Maxi” task
(Wimmer & Perner, 1983)—is passed by 4 years of age (Wellman, Cross, & Watson, 2001) has
been challenged by the use of indirect indicators such as anticipatory looking (Clements &
Perner, 1994; Southgate, Senju, & Csibra, 2007), looking time (Onishi & Baillargeon,
2005), and neural activity (Southgate & Vernetti, 2014; Kampis, Parise, Csibra, & Kovács,
2015). Although the replicability of these findings with very young infants from 6 months
to 2 years has been questioned recently (Kulke & Rakoczy, 2018; see also special issue of
Cognitive Development edited by Sabbagh & Paulus, 2018), the finding that correct
anticipatory looking occurs just before children turn 3 years old has been replicated in
seven of seven studies (Kulke & Rakoczy, 2018). This early evidence preceding verbal
answers in the standard test has been attributed to an implicit understanding of belief
(Perner & Clements, 2000). The justification for this claim resides in the finding that
children show no knowledge of the agent’s belief in a direct test, but only in an indirect
test, commonly seen as a criterion for implicit knowledge (Reingold & Merikle, 1993). When
directly asked where a mistaken agent will go to get an object that was transferred
without his or her knowledge, children answer with the object’s actual location when at
the same time their eye gaze shows some awareness that the agent will go to where he or
she thinks it is. Alternatively, the eye gaze might be evidence for explicit understanding
that remains obscured by the test question due to processing limitations (Baillargeon,
Scott, & He, 2010) or misleading pragmatics (Helming, Strickland, & Jacob, 2016). Findings
from Rubio-Fernández and Geurts (2013, 2016) provide potentially important evidence for
resolving this controversy. Their claim is that by lowering processing demands, children
become able to respond correctly to a verbal command, which is deemed possible only with
explicit knowledge. In Rubio-Fernández and Geurts's (2013) Duplo false belief (DFB) task,
3- and 4-year-olds are told about a girl who stores bananas in one of two boxes. While she
is turning away, the bananas are transferred to the other box, the same as in the standard
false belief (SFB) story except for the following four differences. First, the girl never
went out of sight; she merely stepped to the side where she could not see the
manipulation. Second, the experimenter transferred the bananas instead of introducing an
additional story character. Third and fourth, when the girl returned, children were not
told what she wanted and were not asked a question; they were simply requested to finish
the story operating the girl doll themselves. This was to avoid any need to inhibit
knowledge of the bananas’ real location, which is thought to be particular difficult in
the SFB task (Baillargeon et al., 2010; Leslie, 1994; Setoh, Scott, & Baillargeon, 2016).
Mention of the girl’s desire to get the bananas also creates a strong pull towards their
real location because the girl wants to go where they are and not where she thinks they
are (Perner, Rendl, & Garnham, 2007). Omitting the girl’s desire is, however, a risky
undertaking. Without knowing what she wants, children may make her do anything, for
example, go to the now empty box to put something else in there. They will make her go to
where she believes the bananas are only if they assume that she wants to get the bananas.
Because there is no indication of children making this assumption, it is essential that a
Duplo true belief (DTB) control task is administered. Rubio-Fernández and Geurts’ (2013,
2016) findings were impressive. Nearly all children (mean age of around 3½ years) made the
doll go to the full box in the DTB condition (91% in Experiment 1 of the 2013 study1 and
100% in Experiment 1 of the 2016 study). In contrast, 80% of children made the doll go to
the empty box in the DFB condition, whereas only about 22% gave the correct answer to the
SFB question (deceptive content task in Experiment 1 of the 2013 study). The data have
important consequences for theories explaining early sensitivity to beliefs. First, the
fact that children move the doll to the believed location of the bananas as early as they
show anticipatory looking in the false belief task (Clements & Perner, 1994) speaks
against an implicit knowledge of belief because intentional actions are typically carried
out consciously. Second, the data question the explanation that the spontaneity of looking
behavior accounts for earlier evidence over the elicited responses in the SFB task
(Baillargeon et al., 2010) because children’s responses in the DFB task are also elicited.
Third, the data speak against the pure processing load account by Baillargeon et al.
(2010) that the SFB task requires children to understand the story plus the experimenter’s
question. Although no specific question is asked, the experimenter nevertheless elicits a
response with a range of more general questions. The data also support some proposed
explanations. First, the fact that the belief-related responses decline drastically with
the mention of the bananas’ location or the girl’s desire (Rubio-Fernández & Geurts, 2013)
goes well with the claim that the lure of reality cannot be suppressed (Setoh et al.,
2016). Second, these effects could also be due to children’s difficulty in switching from
their own perspective, enforced by mentioning the bananas’ location or the girl’s desire,
back to the girl’s perspective (Rubio-Fernández & Geurts, 2013; Helming et al., 2016), as
opposed to children needing to inhibit their representation of reality. Given their
theoretical importance, the Duplo results warrant a careful replication, especially given
that the employed experimental design has some weaknesses to be ironed out. In particular,
there was only one experiment in which children were randomly assigned to the DFB and DTB
conditions (Rubio-Fernández & Geurts, 2016, Experiment 1). Unfortunately, no SFB task was
administered to the same sample. The claim that 80% of belief-directed answers at 3 years
7 months of age could be made only by comparing them with performance on the SFB test from
a different, slightly younger sample (3 years 5 months) in Rubio-Fernández and Geurts
(2013). Arguing for a performance difference purely on age is risky given that the large
meta-analysis of SFB tests by Wellman et al. (2001) suggests a non-negligible number of
samples in the age range of 3 years 3 months to 4 years that showed a mean correct answer
rate of 80% or higher (see Fig. 2 in Wellman et al., 2001). Existing replications are
either conceptual (Białecka-Pikul, Kosno, Białek, & Szpak, 2019; Dörrenberg, Wenzel,
Proft, Rakoczy, & Liszkowski, 2019; Rubio-Fernández & Geurts, 2016) or did not include a
true belief control (Kammermeier & Paulus, 2018). Without a DTB task, Kammermeier and
Paulus (2018) could not decide whether the approximately 20% more frequent correct DFB
answers compared to SFB answers reflected earlier evidence from the Duplo task or a
difference in guessing rate. This in turn led to an exchange of opinions (Paulus &
Kammermeier, 2018; Rubio-Fernández, 2018) as to what the baseline performance of children
who do not understand belief might be. We argue that this discussion can be settled only
with an experimental inclusion of the DTB control because it ensures that children ascribe
the intended goal—of getting the bananas—to the agent. The current study, therefore, is
the first to combine a direct replication method with a true belief condition. On the
group level, the DTB task allows us to see whether the majority of children intuitively do
ascribe to this goal. However, if this is not as cogent as the data of Rubio-Fernández and
Geurts (2013, 2016) suggest, we cannot assume that every empty box response in the DFB
task reliably indicates false belief understanding. In this case, DFB responses should be
assessed in relation to DTB responses on the individual level. Consequently, before
investigating the interesting specific effects claimed to be at work, we decided to
replicate the study in a within-participants design including the DFB, DTB, and SFB tasks.
This has the advantage of getting a more precise estimate of understanding if children
give the correct answers to the DFB task as well as the DTB task. Rather than differences
from chance level, we took the DTB condition as the baseline for the interpretation of DFB
performance. To get the DTB condition involved, we relied on the joint probability between
correct responses on the DTB and DFB tasks. Hence, if the DFB task reliably detects false
belief understanding earlier than the SFB task, we should find (a) a significant
performance difference between DFB × DTB and SFB (at the group level, between
participants) or (b) significantly better performance in the DFB task than in the SFB task
in the subgroup of DTB passers (at the individual level, within participants). In
addition, the design allowed us to see whether the DFB performance correlates with that of
the SFB task.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Rubio-Fernández and Geurts (2013) tested whether the percentage of correct responses was
above chance of 50%. They found a large effect size (Cohen’s h = 64) for their sample of n
= 25. On this basis, we computed the necessary sample size for obtaining 80% power
following the standard recommendation outlined by Cohen (1988) and implemented in the pwr
package by Champely (2013). Although this calculation indicated a sample size of n = 15,
we decided to test 75 children for the following reasons. First, it is inadvisable to use
fewer participants for replications than in the original studies (Etz & Vandekerckhove,
2016). Second, to allow comparisons among the three tasks in case children needed to be
excluded due to transfer effects of the within-participants design. A total of 77 children
from six nursery schools and two recreational facilities (Toy Museum and Indoor-
playground) in the city of Salzburg, Austria, volunteered for this study. Of this sample,
4 children needed to be excluded because 2 children were not cooperative, 1 child had
comprehension problems, and 1 child had an inaccurate date of birth given to the
experimenter (after correction, it turned out that the child was too old for the sample).
The final sample consisted of 73 children (28 girls) aged 32–51 months with a mean age of
41.92 months (SD = 4.87). Parents gave written consent, and if they agreed the session was
recorded. Children received a small toy for participating.

<hs>  Design</hs>
  ~~~~~~

Children participated in a DFB task, a DTB task, and a change-of-location SFB task. The
order of tasks was counterbalanced with Latin square. To ensure a direct replication of
both the DFB and DTB tasks (Rubio-Fernández & Geurts, 2013), the original banana story was
always used as the first Duplo task,2 and to allow for a within-participants comparison, a
parallel version (toy car story) was developed. Whereas color and position of the
containers was kept constant, the direction of the objects transfer was counterbalanced.

<hs>  Procedure and materials</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Children were tested by a female experimenter in a separate room in the day-care center or
recreational facility. They sat at a table with the children sitting at a right angle to
the experimenter, and each session lasted about 10 min. A total of 30 children were
accompanied by a parent (n = 18), an older sibling (n = 3), or an educator (n = 9).
Caregivers were seated in a chair some distance behind the children and were carefully
instructed not to interrupt the testing procedure. To avoid procedural differences between
our tasks and those of Rubio-Fernández and Geurts (2013, 2016), Paula Rubio-Fernández
kindly sent us her comments on a videotape of each condition.3 Her recommendations were
implemented in our final versions; see detailed instructions in Appendix A and videotapes
of the procedure in OSF (Open Science Framework), https://osf.io/feg6u/.

        <hss>Duplo tasks</hss>

        All props used in the two parallel versions of the tasks were Duplo toys. The main
        protagonist was a figure (boy or girl) of approximately 6 cm in size. For the
        containers, we used either two pink boxes (6.4 × 6 × 3 cm) with a door (blue and
        yellow) or two treasure chests (5.5 × 4 × 4 cm; green and brown). The transferred
        object was a bunch of bananas (4 cm) or a toy car (3.3 cm). At the beginning of
        the experiment, children were allowed to explore the toys used in the specific
        task. After a while, the experimenter suggested acting out a story with the toys.
        She then placed the containers approximately 20 cm apart from each other on the
        table, facing the child. The approximate distance between containers and the child
        was 30 - 40 cm. Lastly, the object was placed approximately 20 cm in front of the
        containers and 10–20 cm in front of the child.

        <hss>Introduction</hss>

        In the original version of the Duplo task, the experimenter told the child about
        how the protagonist loved eating bananas and, because she already had eaten a
        banana today, she stored them in one of two fridges. In the parallel version, the
        protagonist was a boy who loved playing with a toy car, which he then stored in
        one of two toy boxes.

        <hss>False belief condition</hss>

        After the object was put into the container, the experimenter explained that the
        protagonist now wanted to take a walk. The experimenter walked the Duplo figure to
        the opposite edge of the table, where it was then placed with its back to the
        containers. During the transfer of the object and when asking epistemic prompts
        [see (1) and (2) in the “Epstemic prompts” section below], the experimenter
        whispered and behaved conspiratorially; for example, she put her finger to her
        mouth and had a slight smirk on her face.

        <hss>True belief condition</hss>

        After the object was put into the container, the experimenter placed the Duplo
        figure facing both containers. Next, the transfer of the object and the epistemic
        prompt question (2) were acted out neutrally and without any conspiratorial cues.
        Announcing that the protagonist now wanted to take a walk, the experimenter walked
        the Duplo figure to the opposite edge of the table and back to the scene.

        <hss>Epistemic prompts</hss>

        To make the child attend to the epistemic states of the protagonist, the following
        questions were asked: (1) (before transfer) “Can she/he see me from there where
        she/he is standing?” and (2) (after transfer) “Did the girl/boy see what I did?”
        The DFB condition included both kinds of prompts, whereas the DTB condition
        included the after-transfer prompt only, and both questions were treated as
        prompts rather than as control questions. Thus, irrespective of what the child
        answered, the experimenter continued by saying “No, she/he cannot see me!” and
        “No, she/he did not see what I did!” in the false belief condition and “Yes,
        she/he saw what I did!” in the true belief condition.

        <hss>Prediction test</hss>

        After the experimenter had the Duplo figure come back from the walk, she placed it
        in front of the two containers and asked the child, “Do you want to play with the
        girl/boy now? What will happen next?” If the child did not respond spontaneously,
        the experimenter encouraged the child: “You can take the girl/boy now if you want
        to. What will she/he do next?” If the child still did not respond, the
        experimenter repeated the question: “What will she/he do next?”4

<hs>  Traditional false belief task</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A PowerPoint animation of the standard change-of-location false belief story (Wimmer &
Perner, 1983) was presented on a tablet and narrated by the experimenter. In the
protagonist’s absence, a toy was transferred to a new location and children were asked to
predict where the protagonist, who had returned to continue playing with the toy, will
look for the toy (test question: “Where will Maxi look for the ball first?”). Seven
control questions were asked to make sure that children had understood relevant story
facts (“Where did Maxi put the ball?”, “Where is the ball now?”, “Who placed it there?”,
and “Where did Maxi place the ball in the beginning?”) and could still remember them at
the end of the story (“Where is the ball now?”, “Where did Maxi place the ball in the
beginning?” and “Did Maxi see that his sister put it there?”). If children were not able
to answer a question correctly, the story was repeated and the correct answer was given.

<h>RESULTS</h>
-------

For each task some children needed to be excluded due to experimenter errors (DFB: 1; SFB:
1), caregiver errors (DFB: 2), lack of cooperation by the child (DTB: 3; DFB: 2; SFB: 2),
ambiguous responses to the test (DFB: 2; DTB: 2), starting to enact the false belief
scenario in the DTB task (5), and failing on 50% or more of the control questions5 in the
SFB (6). The number of children excluded in each task can be seen in Table 1 together with
children’s answers to the epistemic prompts (DTB and DFB) and their responses to the
tests.

<hs>  Confirmatory analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~

In both Duplo tasks, children had problems in giving answers or giving correct answers to
the epistemic questions. Following Rubio-Fernández and Geurts (2013, 2016), we treated
these as prompts and not as questions to be answered correctly. In the test, a
surprisingly large number of children did not give any response, and several said “don’t
know” or did something other than moving the doll to one of the boxes (e.g., let the
protagonist go for a walk). In line with Rubio-Fernández and Geurts (2013), children who
did not move the doll to one of the two locations (full/empty) in the DFB and DTB tasks
but showed other responses are treated as exclusions; hence, success rates are relative to
the sum of definite box responses (Σ±). For the confirmatory analysis, we first assess
children’s test reactions against chance level (two-choice binomial test, hypothetical
probability of success = .50, two-tailed) and then compare performance in the DFB and SFB
tasks between and within participants. In none of the tasks did performance differ from
chance. Success rates in the DFB (n = 43), DTB (n = 37), and SFB (n = 64) tasks were 58%
(p = .36), 62% (p = .188), and 41% (p = .169), respectively. For between-participants
comparisons, we use children’s response to the first task administered (Table 2). A chi-
square test with Yates correction revealed no significant difference in children’s
performance on the DFB and the SFB tasks, χ2(1, N = 31) = 0.382, p = .458. A total of 39
children gave a valid (full or empty box) response in both the DFB and SFB tasks and,
therefore, can be used for within-participants comparison (see left panel of Table 3).
Neither on the individual level is there evidence for earlier understanding revealed by
the Duplo test than by the standard test, exact McNemar, χ2(1) = 0.75, p = .387, odds
ratio (OR) = 0.50, 95% confidence interval (CI) [0.11, 1.87].

        <hss>Transmission effects</hss>

        To assess these results properly, we need to make sure that our within-
        participants design did not work against the Duplo tasks because tasks presented
        earlier might have had a detrimental effect on Duplo tasks later in the series.
        There is, however, no sign of such an effect. The percentage of correct answers
        did not differ from first, to second, to third positions for any of the tasks, all
        χ2(2) ≤ 1.08, p ≥ .583, ΦCramer ≤ .13. The same held true for Duplo story context
        (banana or toy car), χ2(1) ≤ 2.74, p ≥ .098, ΦCramer ≤ .27,6 and for direction of
        transfer in the Duplo tasks (left → right or right → left), χ2(1) ≤ 0.18, p ≥
        .668, ΦCramer ≤ .07. In the original study (Rubio-Fernández & Geurts, 2013,
        Experiment 1), the DFB task always followed the SFB task. To control for a priming
        effect, we compare responses in the DFB task when it was administered immediately
        after the SFB task (n = 23) with when it was administered as the very first task
        (n = 20). There is no evidence for such an effect (DFB as first task: 7 empty, 4
        full, and 9 other responses; DFB after SFB task: 11 empty, 8 full, and 4 other
        responses), χ2(2) = 3.96, p = .138, ΦCramer ≤ .30.

        <hss>Extended baseline</hss>

        Because there is no convincing argument for excluding from the analysis children
        who responded in an unexpected way (Kammermeier & Paulus, 2018), we also report
        the success rates relative to all responses (other responses also coded as
        incorrect) in Tables 1 and 2.

        <hss>Analysis of the DFB task in light of the DTB task</hss>

        As we argued, empty-box responses in the DFB task should be interpreted as
        evidence for understanding belief only if they correspond with full-box responses
        in the DTB task. Therefore, we compare the joint probability DFB × DTB with
        performance in the SFB task on both the group and individual levels. The within-
        participants design allows us to identify the DTB × DFB response pattern of
        individual children shown in the right column of Table 3. Unfortunately, only 24
        children responded with a definite box in both tasks, and only 6 children showed
        the desired response pattern. On these grounds Table 3 provides no evidence of any
        understanding because as many children showed the opposite pattern.

        <hss>Correlations</hss>

        Despite the fact that Duplo task performance did not outstrip SFB performance,
        there was a reassuring correlation with age in months for the DFB task, rs(43) =
        .39, p = .009, 95% CI [.102, .618], and for the SFB task, rs(64) = .34, p = .005,
        95% CI [.103, .541]. No significant correlation was found for the DTB task, rs(37)
        =  − .16, p = .301, 95% CI [−.46, .173]. Furthermore, the DFB and SFB tasks are
        significantly correlated, rs(39) = .39, p = .014, 95% CI [.085, .628], which
        suggests that the Duplo task does pick up understanding of belief in light of the
        standard test. When children start to understand the concept of belief, as
        mirrored in their SFB performance, the rationale of the DFB task also becomes
        comprehensible. For SFB passers, the narrative of the DFB task becomes less
        ambiguous given that 20 of 26 children (77%) responded with a definite box,
        whereas only 19 of 33 SFB non-passers (58%) did so.

<h>DISCUSSION</h>
----------

There were two main findings: (1) greater variability of children’s test responses than
originally reported and (2) no evidence of earlier competence in the Duplo procedure than
in the SFB test. We take the first of these findings to be a result of the open-ended
nature of the Duplo task, leaving children with a wide field of interpretations, thereby
making them susceptible to small environmental cues. In our sample, more than a third of
children (35% in the DFB task and 41% in the DTB task) either said that they did not know
what to do (5% and 13%, respectively), continued the story idiosyncratically (15% and 13%,
respectively), or did not respond at all (15% and 16%, respectively). Response variability
was also larger in Kammermeier and Paulus (2018) than in the original studies. Those
authors argued that the problem is the open response format paired with a lack of control
questions. This is likely given that we cannot be sure whether children understood the
task as intended by the experimenter. For instance, in the Duplo task, children might
assume that the Duplo girl wants to either look for her bananas or look for an empty box
for something else. Dörrenberg et al. (2019) managed to make this apparently clearer with
94% and 85% correct answers for the DTB task.9 However, the more consistent performance in
the DTB task did not produce earlier evidence for understanding belief over the SFB task
in the DFB condition. Another potential reason for the high variability in children’s
reactions is that responding to the Duplo task requires children to switch perspectives.10
This feature distinguishes the Duplo task from other early false belief paradigms in which
children take the same third-person perspective throughout the task. When asked to
continue the story, they switch from being a third-person observer of the toy agent to
being a first-person controller of that agent. The interpretation of responses is based on
the supposition that children incorporate what they have learned about the agent (as a
third-person observer) into their play (as a first-person actor). It is not explicitly
controlled whether or to what extent children actually do this. Idiosyncratic and “don’t
know” responses underline this problem, and there is no assurance that this does not also
occur in empty-box and full-box responses. Hence, the switch between perspectives is
another potential source for uncontrolled variability. More important, assessing
performance on the DFB, DTB, and SFB tasks on the same sample of children allows us to
interpret children’s responses without needing to rely on the average age of different
samples. Only children who gave correct responses in both the DFB and DTB tasks can be
claimed to have some understanding of belief. However, there is no evidence on the
individual level, nor is the joint probability of correct DTB and DFB answers
significantly different from the proportion of correct SFB answers. Thus, there is no
support for the claim that the Duplo task provides earlier evidence of understanding
belief than the SFB task. In contrast, our joint probability is significantly lower than
the corresponding values computed from the data reported by Rubio-Fernández and Geurts of
.73 in 2013 and .80 in 2016. Both of them are clearly beyond the borders of the confidence
interval (.24–.66). On these grounds, our data also fail to replicate the theoretically
essential result of Rubio-Fernández and Geurts (2013, 2016); the data are significantly
different from theirs and provide no evidence for their theoretical claim. The volatility
of response rates highlights a potentially general problem of early false belief studies.
In looking time and anticipatory looking paradigms, infants are not told a story, and
thus—as in the Duplo task—it is not clearly communicated what the story agent wants.
Children need to figure it out from the agent’s behavior in a few familiarization trials,
which in many cases might not be sufficient. This might be one reason why the data from
these techniques have been difficult to replicate.


<h>REFERENCES</h>
----------

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<ART>More than words: Judgments of politicians and the role of different communication channels
================================================================================

Authors: Markus Koppensteiner, Pia Stephan, Johannes Paul Michael Jäschke
DOI: 10.1016/j.jrp.2015.05.006
Year: 2015  |  Pages: 21-30
ASJC codes: 3200, 3207
Keywords: Body movements, Impression formation, Nonverbal communication, Personality, Snap judgments, Thin slices

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We collected short video clips of speakers and created five types of stimuli: (1) the original videos, (2) the audio tracks only, (3) single pictures only, (4) speech content, and (5) stick-figure animations displaying body motion. Participants rated these stimuli on a brief Big Five personality inventory. We then used ratings of the incomplete information conditions to predict ratings of the original video condition. Impressions in the audio track condition were strong predictors throughout all trait ratings. However, other cues were also non-negligible contributors to an overall impression. People even make sense of parsimonious cues, e.g., an animated stick-figure. Thus, presenters on a public stage are not only judged by what they say but also by how they move.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

When people form impressions about others, words often seem to affect them less than the
observed outward appearance and nonverbal behavior. Visual and auditory cues affect
people’s judgments of their interaction partners; judgments that are made spontaneously,
effortlessly, and without conscious processing (Ambady, Bernieri, & Richeson, 2000;
Sunnafrank & Ramirez, 2004). On the one hand, first impressions can be misleading and a
source of prejudices and stereotyping (Zebrowitz & Montepare, 2005). On the other hand,
they can pick up relevant information about one’s social environment. After being exposed
to brief extracts of nonverbal or verbal information, people are able to assess other
people’s actual personality, their job performances, or a CEO’s abilities to generate
company profits (Albright, Kenny, & Malloy, 1988; Ambady et al., 2000; Borkenau & Liebler,
1992a,b; Hecht & LaFrance, 1995; Rule & Ambady, 2008; Scherer, 1978). Irrespective of
whether they are the key to someone’s actual personality traits or abilities, snap
judgments can have a strong impact on impression formation and decision making. This is
greatly important for those who enter the public arena. Politicians and leaders who vie
for media attention and try to win the approval of an audience have to be aware that they
are not only judged by the content they present. Nonverbal and salient cues are assumed to
be processed efficiently and easily remembered and for this reason they can dominate over
verbal information (Clark & Paivio, 1991) Their impact may even be more prevailing
nowadays because news reports have been undergoing a shift from political content to image
bites (see Bucy & Grabe, 2007; Stewart, 2010). Moreover, the flood of information that
people are confronted with daily imposes an additional cognitive load, which increases the
propensity to take mental shortcuts when making decisions (Olivola & Todorov, 2010). Thus,
people may tend to choose their leaders not after careful deliberation but on the basis of
superficialities. Empirical studies underscore that appearance cues and nonverbal
behaviors influence judgments of politicians and other leaders. Research on the perception
of charisma showed that potential leaders who display expressive non-verbal behaviors
(i.e., more body gestures, more variations in intonation, more eye-contact, etc.) are seen
as more charismatic than persons who showed less non-verbal behaviors (Awamleh & Gardner,
1999; Gardner, 2003; Holladay & Coombs, 1993, 1994). Moreover, experiments using
manipulated voices revealed that vocal cues affect people’s attributions of leadership
qualities and their voting behavior (Klofstad, Anderson, & Peters, 2012; Tigue, Borak,
O’Connor, Schandl, & Feinberg, 2012). People even read leadership qualities, such as,
competence, trustworthiness, or dominance, into photographs of political candidates.
Interestingly, the consensus among such ratings is strong enough to make them reliable
predictors of hypothetical voting decisions and actual election outcomes (Antonakis &
Dalgas, 2009; Ballew & Todorov, 2007; Banducci, Karp, Thrasher, & Rallings, 2008; Little,
Roberts, Jones, & DeBruine, 2012; Olivola & Todorov, 2010). All these empirical findings
point to nonverbal cues as the prevailing influence on the perception of leaders and
politicians. However, some researchers who compared the relative impact of visual, vocal,
and verbal information on judgments of politicians came to different conclusions (Krauss,
Apple, Morency, Wenzel, & Winton, 1981; Nagel, Maurer, & Reinemann, 2012). They found that
speech content dominates over nonverbal information. This does not undermine the role of
nonverbal behaviors in human communication but indicates that their influence varies with
the situation in which behaviors are performed as well as with audience motivation and
involvement (Allwood, 2002; O’Sullivan, Ekman, Friesen, & Scherer, 1985; Petty, Cacioppo,
& Schumann, 1983). In summary, regardless of on which communication channel (i.e., vocal,
visual, or verbal) people’s first impressions are based when making inferences of social
relevance, research clearly shows that “thin slices” of behavior or appearance cues can
have a strong impact on which traits and abilities people read into their social
environment.

<hs>  Motion cues as social information</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Body motion is a form of nonverbal channel that comprises hand gestures, movements of the
head, or position shifts of the whole body. Although the current study provided data on
the interplay of different communication channels in impression formation we mainly focus
on the relative role of body motion. Empirical studies have found that people are very
adept at extracting information from motion cues. Even abstract stimuli such as circles or
triangles flitting around on a screen, are often interpreted as animal or human behavior
and elicit attributions of intentionality and personality (Heider & Simmel, 1944;
Koppensteiner, 2011; Scholl & Tremoulet, 2000). Research on human body motion was strongly
influenced by the point light approach, which was introduced by Gunnar Johansson (1973).
He and his colleagues attached point lights and reflective markers to persons’ major
joints and filmed them so that only a set of dots were visible in the resulting movies.
Supporting the role of motion in human perception, these kinds of stimuli only became
human-like when the dots were moving, whereas observers who saw single pictures of the
movies perceived nothing but a random distribution of dots. Other researchers were
inspired by Johansson’s methodical approach and demonstrated that such point light
displays contain enough information to make quite accurate guesses of other people’s age
and sex (Dittrich, Troscianko, Lea, & Morgan, 1996; Kozlowski & Cutting, 1978; Montepare &
Zebrowitz-McArthur, 1988; Troje, 2002). Research using more elaborated versions of this
technique or alternative methods of motion capture revealed that motion cues convey
information of social relevance (Blake & Shiffrar, 2007; Chouchourelou, Matsuka, Harber, &
Shiffrar, 2006). People appear to be able to perceive affect in arm movements (Pollick,
Paterson, Bruderlin, & Sanford, 2001), emotions in movements of the whole body (Atkinson,
Dittrich, Gemmell, & Young, 2004; Clarke, Bradshaw, Field, Hampson, & Rose, 2005), and
personality in patterns of human gait (Thoresen, Vuong, & Atkinson, 2012). The frequency
and duration of motion and other kinematic features play a role in mating behavior (Bente,
Donaghy, & Suwelack, 1998; Grammer, Honda, Juette, & Schmitt, 1999) and affect the way
females judge the attractiveness of male dancers (Neave et al., 2011). Moreover, self-
ratings and observer-ratings of personality on scales measuring sensation seeking or the
Big Five personality dimensions are related to the motion behavior of dancers (Bechinie &
Grammer, 2003; Hugill, Fink, Neave, Besson, & Bunse, 2011; Luck, Saarikallio, Burger,
Thompson, & Toiviainen, 2010). In the domain of politics, variations in body motion
influence how people judge the personality and health of politicians (Kempter, 1998;
Koppensteiner, 2013; Koppensteiner & Grammer, 2010; Kramer, Arend, & Ward, 2010). Such
results clearly show that motion cues are an equally important nonverbal communication
channel as appearance cues (e.g., clothes), vocal cues (e.g., voice pitch) and facial
expressions. The speed, the duration, and the flow of a gesture or variations in the
movements of the whole body seem to have a non-negligible impact on how people form first
impressions of their social environment.

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

Human communication works on different levels ranging from symbolic information mostly
conveyed by verbal content to information that has no definite signal character and is
expressed by certain qualities of motion. The studies of Mehrabian (1972) and those on the
perception of charisma (see above) provide evidence that under some experimental
conditions, visual information exerts a dominant influence in impression formation
followed by voice quality and speech content on the last position. In addition, comparison
of trait judgments based on full channel information (i.e., video with speech) with trait
judgments based on incomplete information only (e.g., silent videos or voice only)
indicates that cues from different communication channels convey redundant information
(Borkenau & Liebler, 1992a; Friedman, Oltmanns, Gleason, & Turkheimer, 2006). However,
there are variations. Some traits appear to be preferably ascribed to visual cues, while
other traits are preferably ascribed to cues from other modalities (Friedman et al., 2006;
Gifford, 1994; Naumann, Vazire, Rentfrow, & Gosling, 2009; Zebrowitz-McArthur & Montepare,
1989). Moreover, when asked to identify emotional expressions or statements of agreement
and disagreement in political debates people are more accurate when multimodal information
is available (Bänziger, Mortillaro, & Scherer, 2012; Mehu & van der Maaten, 2014). In this
study we examined to what degree body motion affects social judgments relative to
information from other verbal and nonverbal communication channels. To accomplish this, we
broke down short video clips of politicians making a speech into five different versions
of stimuli. Independent samples of participants then judged either the full channel
version of the speeches, sound only, single pictures taken out of the speeches, the
content of the speeches read by a computer voice, or stick-figure animations displaying
the body movements of the speakers. Measures of the participants’ first impressions were
obtained using a brief questionnaire that builds on the five-factor model of personality
(i.e. Big Five), because the five-factor model had already been successfully applied in
numerous “thin slices” studies (e.g., Borkenau & Liebler, 1992a,b; Friedman et al., 2006).
These measures allowed us to estimate to what extent information from different
communication channels influences snap judgments of the speakers and how different
“portions” of nonverbal and verbal information are related to body motion. Our study
extends previous research in several aspects. First, other studies on nonverbal
communication often instruct actors to display specific behaviors. In contrast to that,
the stimuli we used were real politicians that had given their speeches in the German
parliament. Hence, ecological validity of the displayed behaviors is high. Second,
although our experimental design was inspired by previous studies on the role of different
communication channels (Borkenau & Liebler, 1992a,b; Friedman et al., 2006), these studies
did not examine the behavior of speakers in a public arena. Finally, we applied other
tools for stimulus preparation and stimulus presentation than other studies in the field.
By translating the body movements of the speakers into animated stick figures, we
diminished the influence of confounding variables and were able to determine for which
traits body motion was a strong predictor and to what degree it interacts with information
from other nonverbal and verbal sources. In previous work we already used stick-figure
animations as stimuli and related data-driven descriptors of body motion (e.g., measures
of amplitude height) to judgments of personality. This revealed that people form first
impressions on the basis of simple cues embedded in the behavioral stream. However, it was
unclear whether and to what extent body motion affects judgements of speakers when vocal
and other cues are also available to observers (Koppensteiner & Grammer, 2010). The work
presented here, which is based on the same method of motion capturing but on a new set of
stimuli, is a first step to overcome such limitations. It is suggested that rapidly
evaluating other people’s intentions, assessing one’s social environment on broad trait
categories and making fast decisions on whether to approach or avoid an individual has an
adaptive function (e.g., Buss & Greiling, 1999; Oosterhof & Todorov, 2008). Misjudgments
can have negative consequences and for this reason people may base their social
evaluations on cues from different communication channels because this makes evaluations
more reliable. Previous work has already shown that first impressions of extraversion,
agreeableness and emotional stability are related to motion cues and gesturing (Borkenau &
Liebler, 1992b; Gifford, 1994; Koppensteiner, 2013; Koppensteiner & Grammer, 2010). Hence,
we hypothesized that for these personality dimensions judgments of the speakers’ body
movements (i.e., stick-figure animations) can serve as predictors of people’s judgments in
the full channel condition (i.e., video plus sound). Moreover, we expected pronounced
links between ratings of the voice only condition and ratings of body motion, because it
is well established that gesturing accompanies speech (e.g., McNeill, 1985). Appearance
cues and vocal cues have been found to be related to all dimensions of the Big-Five
(Borkenau & Liebler, 1992b; Friedman et al., 2006; Naumann et al., 2009). Consequently, we
expected to replicate such findings in our study. Research on nonverbal communication
revealed speech content to play a minor role when people form first impressions (e.g.,
Awamleh & Gardner, 1999). However, there seems to be a link between conscientiousness and
speech content (e.g., Friedman et al., 2006), which we also expected to reveal in our
data.

<hs>  Stimulus preparation and experimental conditions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Sixty speeches taking place in the German parliament (30 male and 30 female speakers) were
randomly selected out of three parliamentary sessions (November 29 & 30 and December 14,
2012). The selected speakers were non-prominent members of the parliament and were unknown
to our participants. At random, we extracted video segments with a length of 15 s from
these speeches. Afterwards, the video segments were used to create five different stimulus
types for the experimental conditions described below.

        <hss>Full channel condition</hss>

        For the full channel condition we merely removed the lower portion of the video
        clip, which gave information about the speaker’s name and party affiliation.
        Consequently, in this experimental condition the participants of a rating
        experiment assessed the original video clips, which included all visual and all
        auditory information.

        <hss>Static visual condition</hss>

        To eliminate information on body movement we chose one picture out of the frame
        series of each video segment. Each of these pictures showed the speakers adopting
        similar body postures. For more detail, we chose pictures with the speakers
        standing upright having their arms positioned at their sides. In accordance with
        the length of all other stimulus types pictures were shown for 15 s in the rating
        experiment.

        <hss>Original voice condition</hss>

        For this experimental condition, we extracted the audio track from each original
        video segment. Thus, visual information was removed and the participants assessing
        such stimuli only listened to what was being said.

        <hss>Artificial voice condition</hss>

        We extracted what said during the selected video segments from the transcripts of
        each parliamentary session. These transcripts were converted into audio files
        using the document reader software Ghostreader. Because all transcripts were read
        aloud by the same computer voice during the rating experiment, they served as the
        control condition for speech content and wording.

        <hss>Stick figure condition</hss>

        The main focus of the study was on the analysis of body motion in relation to
        information presented in the other conditions. To this end we created stimuli,
        which display body motion without confounding information, e.g., appearance cues.
        To accomplish this, we used a program that allows running through the video clips
        step by step. In the first frame of each video clip, we positioned landmarks on
        the speaker’s forehead, the hollow of the throat between the collar bones, ears,
        shoulders, elbows, hands, a spot in the middle of the body near the navel, and the
        corners of the lectern. Motion behavior occurring between single frames of the
        video clips was traced by rearranging the landmarks with the computer-mouse and
        software routines that automatically tracks positions shifts (Koppensteiner,
        2013). Based on this data, we created stick figure animations, which served as
        abstract representations of the speakers’ body movements. To reduce the workload
        during the encoding process, we only used every third frame and filled in missing
        frames by linear interpolation.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 308 Caucasian participants (i.e., students of the Faculty of Life Sciences) was
recruited at the University of Vienna for taking part in the rating experiments. Sixty-
five persons (37 females and 28 males; M-age = 23.3 years, SD = 5.8) participated in the
full channel condition, 60 people (35 females and 25 males; M-age = 22.8 years, SD = 3.4)
in the static visual condition, 63 (33 females and 30 males; M-age = 23.8 years, SD = 4.4)
in the original voice condition, 60 participants (35 females and 25 males; M-age = 23.4
years, SD = 4.5) in the artificial voice condition, and 60 persons (33 females and 27
males; M-age = 22.5 years, SD = 3.7) in the stick figure condition. Participants received
a financial compensation of €5.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants were approached in person and asked to take part in a short rating
experiment. After accompanying them to our laboratory, we informed the participants
briefly about the experimental set-up and the task to be accomplished. Subsequently,
participants performed the rating tasks on their own using a computer-controlled
interface. They were instructed to rate the stimuli after they had watched or listened to
them. Pictures in the static visual condition were shown for 15 s, but participants were
told that they could start their ratings whenever they felt to be ready for them. In the
full channel condition, the original voice condition, and the artificial voice condition,
participants wore headphones (AKG K 272 HD) connected to the computer to optimize sound
quality. Stimuli were presented on the left-hand side of the user interface, while rating
scales were displayed on the right hand side. Participants completed their ratings by
dragging a slider to the favored position between the right pole (i.e., named, strongly
disagree) and the left pole (i.e., named, strongly agree) of the scale using a computer
mouse. The slider position corresponded to a position on a scale divided into 200
subunits. All ratings started with the slider being in the neutral position (i.e., middle
position on the slider bar). To examine personality ratings of the speakers, we used the
German version (Muck, Hell, & Gosling, 2007) of Gosling, Rentfrow, & Swann’s (2003) Ten
Item Personality Measure (TIPI). This questionnaire is based on the five-factor model of
personality and covers personality dimensions openness, extraversion, conscientiousness,
emotional stability, and agreeableness. In each experimental condition, each participant
rated a subset of 20 stimuli that were randomly selected from the 60 stimuli available.

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

Trait ratings were averaged for each condition and each stimulus. This yielded a dataset
containing 60 speakers that were rated on ten items in five experimental conditions.
Corresponding items of the TIPI questionnaire were turned into the Big Five personality
dimensions according to the instructions by Gosling et al. (2003). Because each
personality dimension only comprised two items, internal consistency of the questionnaire
was determined by calculating the Spearman–Brown coefficient (Eisinga, Te Grotenhuis, &
Pelzer, 2013). To estimate the relative influence of voice, speech content, appearance,
and body motion on judgments of personality, we correlated ratings collected in the
experimental conditions presenting incomplete information with ratings of the full channel
condition (i.e., original video clips). We also performed multiple regression analyses
using ratings in the full channel condition as criterion, ratings of the incomplete
information conditions as predictors and the speakers’ sex as control variable. We
expected these predictors to be intercorrelated and distorted due to multicollinearity.
For this reason we also calculated so-called relative weights. Relative weights or
relative importance weights range between 0 and 1, are unaffected by multicollinearity,
and therefore very helpful when interpreting each predictors’ relative contribution in the
regression model (Johnson, 2000; Kraha, Turner, Nimon, Zientek, & Henson, 2012; Lorenzo-
Seva, Ferrando, & Chico, 2010). Moreover, bivariate correlations between predictor
variables provided insight into the interrelations between ratings of the incomplete
information conditions. Previous studies comparing different communication channels found
correlations of .35 or higher between nonverbal cues and personality ratings (Borkenau &
Liebler, 1992b; Friedman et al., 2006; Koppensteiner, 2013). We used different modalities
as predictors in a regression analyses and assumed their effects to add up. Consequently,
we expected the multiple regressions we performed to explain at least 20 percent of
overall variance. On the basis of such an effect size, an alpha level of .05, a power
level of .8, and five predictors an a priori power analyses suggested an optimal sample
size of 51 stimuli. All statistical analyses were carried out in the program R (R Core
Team, 2013).

<h>RESULTS</h>
-------

Descriptive Statistics are presented in Table 1 and internal consistencies between
corresponding items of the questionnaire in Table 2. Coefficients ranged from .06 to .94
and thus were unacceptably low in some cases. In particular, the item pairs anxious–easily
upset and calm–emotionally stable did not combine properly in the stick figure, in the
original voice, nor in the full channel condition. This might have been due to a weakness
of the questionnaire on this dimension or to the choice of stimuli. Politicians on a
public stage may rarely show body movements or produce vocal cues in which people perceive
qualities associated with the items anxious and easily upset. To sum up, internal
consistencies we obtained for emotional stability were very low and for this reason we
discuss results for this personality dimension on the basis of single items (Tables 3–5).
Statistical analyses of the relationships between incomplete information conditions and
the full channel conditions are presented as correlation coefficients, relative weights,
and regression estimates (see Tables 3 and 4). Results for extraversion revealed a strong
relationship of the ratings in the stick-figure condition and the original voice condition
with the ratings in the full channel condition. In addition, there was also a noteworthy
relationship between ratings in the static visual condition and the full channel
condition. These relationships were reflected in all types of analyses we applied (i.e.,
see correlations in Table 3, and estimates and relative weights in Table 4). We therefore
came to the conclusion that in our setting, judgments of extraversion were mainly affected
by the speakers’ voice and by their body motion as well as—to minor degree—by the
speakers’ appearances. The content of the speeches had no important effect on ratings of
extraversion. Perceived conscientiousness in the full channel condition yielded high
correlation coefficients with ratings of conscientiousness in the static visual condition,
in the original voice condition, and the artificial voice condition (i.e., computer voice
presenting speech content). Similar results were obtained for estimates of the multiple
regression and the relative weights (Tables 3 and 4). Consequently, impressions of
conscientiousness were mostly guided by vocal information. However, appearance cues and
speech content also played a role. Body motion was revealed as the weakest predictor.
Ratings of perceived openness in the full channel condition were strongly related to
ratings in the original voice condition and the static visual condition (Tables 3 and 4).
Correlation coefficients also provided a noteworthy effect size for speech content (Table
3). In conclusion, participants mainly tended to ascribe openness to the speaker’s
appearances and their voices. Full channel ratings of agreeableness showed strong
bivariate correlations with ratings in the original voice condition, ratings in the stick-
figure condition, ratings in the artificial voice condition and a noteworthy one for
ratings in the static visual condition (see Table 3). These patterns of relationships were
not in accordance with the ß-weights of the multiple regression (Table 4). It only
provided strong estimates for the static visual condition and the original voice
condition. This was an indicator of multicollinearity, which distorts ß-weights and,
therefore, undermines accurate interpretation of the data. Relative weights, which are
unaffected by multicollinearity, replicated the patterns found by the bivariate
correlations (Table 3). Thus, we concluded that ratings of agreeableness were guided by
appearance cues, by body motion, by vocal cues and by the verbal content the speakers
presented. Due to the low internal consistencies results for emotional stability were
analyzed on the level of single items. The item pair calm–emotionally stable yielded
notable correlation coefficients and relative weights for all conditions, whereas
regression estimates labeled ratings of the original voice condition as strong predictors
and ratings of body motion and appearance as predictors with a moderate influence (Tables
3 and 4). The item pair anxious–easily upset provided a strong correlation of full channel
ratings with original voice ratings and noteworthy ones with ratings of static visual cues
and with ratings of body motion (Table 3). A similar pattern was provided by the
regression estimates and the relative importance weights (Table 4). Analyses of the
interrelations between ratings in the incomplete information conditions revealed strong
correlations between voice and the content the speakers presented for nearly all
personality ratings (Table 5). This is not very surprising, because the voice only
condition comprised nonverbal vocal cues as well as the content of the speeches. We also
found strong relationships between body motion (i.e., ratings of stick-figure animations)
and voice for the personality dimensions extraversion and agreeableness (Table 5). This
complements results obtained in the regression analyses. It shows that body motion was not
only a communicator of agreeableness and extraversion but also is accompanied by vocal
cues that convey similar information. Thus, for judgments of some personality dimensions
there appears to be a coupling between voice and body motion. Perceived extraversion and
conscientiousness showed notable relationships between different communication channels
(Table 5). For instance, we found a link between appearance cues and speech content for
these personality dimensions. This hints that people are able to form expectations about
what politicians will say on the basis of their appearance or form expectations about
their appearance on the basis of what they say.

<hs>  Original voice condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

The most prominent finding of our study was that all personality ratings of the original
voice condition, in which the participants only listened to an audio track of the selected
speeches, were strongly related to corresponding ratings of the full channel condition, in
which participants watched the unaltered original video clips. This was mostly due to
paralinguistic cues such as intonation and pitch because the strong impact of the
speakers’ voice on personality judgments did not disappear when speech content was
controlled. Other studies also revealed that vocal cues are an important influential
factor in impression formation (Borkenau & Liebler, 1992a; Friedman et al., 2006).
However, they did not play such a predominant role as in our study. Participants were, of
course, aware that they were judging politicians. For this reason, they might have
attended more to the speaker’s voices than to other information. The majority of studies
that compared the impact of different communication channels did not use politicians for
their experiments or instructed actors to display certain behaviors (e.g., Awamleh &
Gardner, 1999; Borkenau & Liebler, 1992a; Friedman et al., 2006). This is different from
our study design and might explain why vocal cues were a strong contributor. Actors may
overdo their acting and display stereotypical behaviors thereby drawing attention to cues
that are less salient when real politicians present themselves. On the other hand, judging
politicians may raise different expectations than judging people drawn from an average
population.

<hs>  Speech content</hs>
  ~~~~~~~~~~~~~~

Judgments in the original voice condition did not only convey speech content but also
information about intonation, voice pitch, and other qualities of the voice. To separate
such vocal cues from speech content, we also collected ratings of the speeches’ wording
read by a computer voice and related these ratings to ratings of full channel condition.
As expected full channel judgments of conscientiousness, but also judgments of
agreeableness and one item pair of the personality dimension emotional stability (i.e.,
calm, emotionally stable) could be predicted by speech content to a certain degree. In
other words, participants read some traits and qualities into what the speakers said and
not only how they said it. Unlike some other studies we were unable to show that verbal
content dominates over nonverbal cues in judgments of politicians (Krauss et al., 1981;
Nagel et al., 2012). Nevertheless, the results obtained indicate that people integrate
speech content when forming first impressions.

<hs>  Static visual information</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Static visual information, which was presented as single pictures, yielded notable
relationships with the full channel condition. Previous research has already shown that
appearance cues alone—clothing styles, physiognomic features and facial expressions, just
to give a few examples—affect people’s first impressions (e.g., Naumann et al., 2009). We
have supported such findings by demonstrating that static visual cues contribute to
overall impressions of a person. Consequently, people form an impression on the basis of
static cues before any motion behavior occurs or a word is spoken. The documented effects
were particularly strong for ratings of conscientiousness and openness. Participants had
no information about party membership, but static visual cues may already reflect a
conservative or a more progressive mindset and this may more strongly guide attributions
of openness and conscientiousness than attributions of other personality dimensions.
Future studies including facial expressions, physiognomic features, and clothing style as
variables in the analyses could support such assumptions.

<hs>  Body motion</hs>
  ~~~~~~~~~~~

The study’s main focus was to estimate the relative role of body motion when people judge
politicians giving a speech. To accomplish this, we translated the speakers’ body motion
into animated stick-figures. Full channel ratings of extraversion, agreeableness, and an
item of emotional stability were strongly related to corresponding ratings of these
abstract stimuli. Although other communication channels, in part, showed stronger effects
over a wider range of ratings, it is still surprising that a parsimonious cue, as simple
as a stick-figure, can guide social perceptions. In previous research, where we applied
the same method of motion capturing, we revealed that people associate personality traits
with salient and simple nonverbal cues that are embedded in the behavioral stream
(Koppensteiner, 2013; Koppensteiner & Grammer, 2010). In accordance with the results
obtained here we found strong relationships of certain motion descriptors with ratings of
agreeableness and extraversion. For instance, speakers who produced expansive vertical
movements (i.e., mostly up and down movements of the hands) were judged as highly
extraverted while speakers who showed less such vertical movements and a greater overall
variation in motion amplitudes tended to be judged as agreeable. Strong effects were also
found for emotional stability. Speakers who displayed jerky movements were perceived as
less emotionally stable than speakers who displayed smoother movements. This might explain
why one item of emotional stability also produced pronounced effects in this study. We did
not examine body movements on the level of motion cues in the work presented here.
Consequently, the next step in this line of research would be to use motion descriptors
such as those presented in our previous work and test in what way they are related to cues
from other communication channels (e.g., auditory cues). Extraversion is often attributed
to conspicuous and expressive behaviors (Kenny, Horner, Kashy, & Chu, 1992). For this
reason, it is a trait that may be easily read from simple behavioral cues, including body
motion. Similarly, appearing friendly is crucial when approaching or avoiding a stranger
and therefore cues of agreeableness may also be easy to detect and even visible in body
motion. Politicians often attack their opponents, make points with great vigor, and
underline their arguments with expressive gestures. Trait ratings belonging to emotional
stability—e.g., calmness—might be influenced by these expressive displays; this might
explain why the participants of our experiments can use body motion for such attributions.
Perceived agreeableness and extraversion of the stick-figure animations showed a strong
coupling to perceived agreeableness and extraversion in the voice only condition. This
underlines that speech is accompanied by body motion and gesturing (McNeill, 1985) and
indicates that cues people associate with extraversion and agreeableness convey essential
social information. To sum up, like other research in the field, our findings indicate
that people perceive social meaning in a great variety of visual, auditory, and verbal
information. In addition to this, we demonstrate that, for some important traits, abstract
animations displaying the speaker’s body movements predict people’s first impressions.

<h>GENERAL DISCUSSION</h>
------------------

We randomly extracted short video clips from speeches that were given in the German
parliament. These clips were then turned into five different types of stimuli, which were
rated on the Big Five personality taxonomy. Stimuli were either (1) short extracts of the
original videos, (2) audio sequences of the speeches, (3) speaker’s body movements turned
into stick-figures, (4) single pictures of the speakers, or (5) the content of the
speeches read by a computer voice. To estimate the influence of these different
communication channels on impression formation we related ratings in the incomplete
information conditions to ratings in the original full channel video clip condition.

<hs>  The role of different communication channels</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

People make sense of brief displays of nonverbal and verbal information and although such
snap judgments can be a source of false beliefs and prejudices, they often convey socially
relevant information (e.g., Ambady et al., 2000). Studies examining the influence of
different communication channels on impression formation found that people read
information into and from a variety of cues. Most research suggests that visual cues have
a prevailing influence on social judgments and that speech content only plays a minor role
(e.g., Awamleh & Gardner, 1999; Mehrabian, 1972). Other researchers were unable to
replicate such findings, which supports the idea that the influence of nonverbal and
verbal cues varies according to context and audience involvement (e.g., O’Sullivan et al.,
1985; Petty et al., 1983). In this study, we found a prevailing effect of vocal cues on
impression formation but the relative role of different communication channels may, of
course, depend on different factors that can hardly be tested and controlled in a single
study. Future studies should thus extend the current experimental set-up by manipulating
the salience of cues (e.g., manipulating vocal parameters), refine analyses by describing
behaviors and appearance cues in more detail (e.g., clothing style), and include different
contextual information (e.g., party affiliation, status). Also, politicians acting in the
public arena may trigger differential judgments than the stimuli some other researchers
used to investigate the impact of different communication channels (e.g., Borkenau &
Liebler, 1992a; Friedman et al., 2006). As in our study, Krauss et al. (1981) as well as
Nagel et al. (2012) collected ratings of politicians and found that people mainly judge
them by verbal content. This is partly in accordance with our findings because we also
revealed a non-negligible relationship between speech content and some trait ratings.
However, the outcomes of the regression analyses suggest that, in our study, prosody and
voice qualities had a marked impact on the participants’ judgments. Overall, the results
obtained show that people’s first impressions are guided by cues from different
communication channels. Put simply, in real life encounters there is no single cue that
creates a first impression. Our analyses supports this by showing that in most cases
single modalities (e.g., body motion, voice only) explained less variance than
combinations of these modalities. Consequently, when making their judgments people seem to
rely on a great variety of nonverbal and verbal cues. Also, some modalities such as voice
and body motion are intertwined and communicate redundant information to a certain extent,
while other modalities do not show such a redundancy. For instance, conscientiousness was
more easily attributed to speech content than extraversion. Irrespective of that our
results support the idea that people’s first impressions are guided by information from
different communication channels (Bänziger et al., 2012; Mehu & van der Maaten, 2014).

<hs>  The relative role of body motion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

By translating the speakers’ nonverbal behavior into animated stick-figures, we created an
abstract stimulus that served as representative of body motion. It has already been shown
that parsimonious cues displaying motion behavior communicate socially relevant
information (e.g., Blake & Shiffrar, 2007; Chouchourelou et al., 2006). In this study, we
extended such research by comparing the influence of cues conveyed by a moving body with
information from other communication channels. We were able to show that, for perceptions
of extraversion and agreeableness, body motion is a major player. Given that our stick-
figure animations reduce information to an abstract stimulus with an artificial
appearance, the results obtained are impressive. They indicate people do not only ascribe
intentions and personality traits to abstract representatives of body motion, but they
also use motion cues to form impressions of their interaction partners. Rapidly
categorizing another individual’s intentions, traits and behavioral tendencies may be an
ability that has been formed during human evolution (Buss & Greiling, 1999; Fiske, Cuddy,
& Glick, 2007). However, some traits are assumed to be of higher social relevance in first
encounters because they inform the decision whether to approach or avoid an individual.
For instance, Oosterhof and Todorov (2008) found that judgments of neutral faces are
reducible to the independent dimensions of valence (i.e., represented by facial
trustworthiness) and dominance. They further suggest that evaluations on these dimensions
are overgeneralizations for inferring harmful intentions. Other research has shown that
attributions of extraversion to a stick-figure animation show a strong relationship with
perceived dominance, while perceived agreeableness is strongly related to perceived
trustworthiness (Koppensteiner, Stephan, & Jäschke, 2015). This supports the conclusion
that people have a higher sensitivity for cues of extraversion and agreeableness because
these belong to basic categories of social evaluation with a direct link to survival. For
this reason, overgeneralizations with regard to potential threats may not only occur when
faces are assessed but also when people categorize body motion. Furthermore, in contrast
to facial information, body motion is recognizable from greater distances. It is thus
conceivable that motion cues are socially relevant because they allow decision making as
another individuals approach, before these individuals come too close.

<hs>  Future directions</hs>
  ~~~~~~~~~~~~~~~~~

In real life situations, nonverbal and verbal information does not disintegrate into
pieces. Our results, and other research, suggest that some cues are intertwined. A well-
known link, for instance, is between speech and gesturing (e.g., McNeill, 1985). Gestures
are sometimes used to emphasize what is being said or go together with voice intonation.
Hence, an overlap in the communicative value of motion cues, speech content, and voice
quality is well established and the results obtained in the present study provide further
support for this. Future research could investigate such an overlap in more detail by
extracting certain motion cues as we have done in previous studies (see Koppensteiner &
Grammer, 2010) and relating them to vocal cues. Follow-up studies with a more in depth
analyses on the interrelations between different cues would also build a bridge to
research that investigates how observers react to violations of such linkages (Weisbuch,
Ambady, Clarke, Achor, & Weele, 2010). Presenting contradictory nonverbal and verbal
information could show that there is indeed redundancy and that different cues might form
one single cue with a common communicative value. This might also provide further support
for work showing that judgments on the basis of multimodal information are more accurate
(Bänziger et al., 2012; Mehu & van der Maaten, 2014). A next step in this kind of research
would be to investigate how different nonverbal information influences decision making on
important issues. Researchers have already shown that facial photographs from political
candidates can be used to predict hypothetical or actual election outcomes (e.g.,
Antonakis & Dalgas, 2009; Little et al., 2012; Olivola & Todorov, 2010). Moreover, other
studies reveal a link between vocal cues and leadership qualities (Klofstad et al., 2012;
Tigue et al., 2012). Taking these as a starting point future research could extend into
the domain of leadership research to examine how the interplay of different cues or
multimodal cues affects decision-making.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

In summary, our findings indicate that people make use of verbal and different nonverbal
cues when forming first impressions of politicians. Static visual cues, body motion,
verbal content, and vocal cues were related to people’s impressions. Vocal cues were
revealed as a strong predictor for all trait ratings in our study, yet other communication
channels also proved important. The impact of body motion was particularly strong for
ratings of agreeableness and extraversion were also linked to corresponding ratings based
on the speakers’ voices. In other words, with regard to these personality dimensions body
motion is coupled to information from the vocal channel. Cues communicating agreeableness
and extraversion may reflect social abilities, which are helpful in social encounters and
facilitate establishing interactions. Hence, people may be more sensitive to cues of
extraversion and agreeableness; for this reason, they also read these traits into body
motion.


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<ART>Mothers who are securely attached in pregnancy show more attuned infant mirroring 7 months postpartum
================================================================================

Authors: Sohye Kim, Peter Fonagy, Jon Allen, Sheila Martinez, Udita Iyengar, Lane Strathearn
DOI: 10.1016/j.infbeh.2014.06.002
Year: 2014  |  Pages: 491-504
ASJC codes: 3204
Keywords: Attachment, Infant attention, Maternal mirroring, Mother-infant communication

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study contrasted two forms of mother-infant mirroring: the mother's imitation of the infant's facial, gestural, or vocal behavior (i.e., "direct mirroring") and the mother's ostensive verbalization of the infant's internal state, marked as distinct from the infant's own experience (i.e., "intention mirroring"). Fifty mothers completed the Adult Attachment Interview (Dynamic Maturational Model) during the third trimester of pregnancy. Mothers returned with their infants 7 months postpartum and completed a modified still-face procedure. While direct mirroring did not distinguish between secure and insecure/dismissing mothers, secure mothers were observed to engage in intention mirroring more than twice as frequently as did insecure/dismissing mothers. Infants of the two mother groups also demonstrated differences, with infants of secure mothers directing their attention toward their mothers at a higher frequency than did infants of insecure/dismissing mothers. The findings underscore marked and ostensive verbalization as a distinguishing feature of secure mothers' well-attuned, affect-mirroring communication with their infants. © 2014 Elsevier Inc.

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<h>INTRODUCTION</h>
------------

In many mammalian species, mothers and infants engage in a rich repertoire of species-
specific, reciprocal, dyadic interactions. Non-human primate mother–infant pairs show
capacity for mutual eye gaze, reciprocal lip smacking, and vocal and gestural mimicry
(Bard et al., 2005; Ferrari, Paukner, Ionica, & Suomi, 2009; Mancini, Ferrari, & Palagi,
2013). Human mother–infant dyads participate in communicative exchanges that are far more
complex and affectively enriched (Beebe et al., 2010; Brazelton, Koslowski, & Main, 1974;
Carpenter, Nagell, & Tomasello, 1998; Feldman, 2007; Gergely & Watson, 1996; Lavelli &
Fogel, 2013; Malatesta, Culver, Tesman, & Shepard, 1989; Sroufe, 1996; Tronick, 1989). The
infant routinely directs a broad range of affectively nuanced expressions to the mother
(Bennett, Bendersky, & Lewis, 2005; Colonnesi, Zijlstra, van der Zande, & Bogels, 2012;
Messinger, 2002). The mother sequentially mirrors the infant's signals as she empathically
delivers her finely tuned response (Jonsson & Clinton, 2006; Lavelli & Fogel, 2013;
Papousek & Papousek, 1989; Stern, 1985). In turn, the infant attentively responds,
organizing his1 behavior with respect to the mother's input (Beebe et al., 2010; Bigelow &
Walden, 2009; Cohn & Tronick, 1987; Soussignan, Nadel, Canet, & Gerardin, 2006). A
relatively synchronous flow of affective communication is one of the key indicators of
secure mother–infant attachment (Beebe et al., 2012; Crandell, Fitzgerald, & Whipple,
1997; Feldman, Gordon, & Zagoory-Sharon, 2011; Isabella & Belsky, 1991; Lundy, 2003).
Maternal mirroring, or emotionally attuned responsiveness, has received extensive
attention in the study of mother–infant behavior (Bigelow & Walden, 2009; Fraiberg,
Adelson, & Shapiro, 1975; Gergely & Watson, 1996; Jonsson & Clinton, 2006; Lavelli &
Fogel, 2013; Lyons-Ruth, 2000; Stern, 1985; Winnicott, 1967). Mirroring is a construct
closely tied to that of secure attachment. Maternal attachment security is a critical
determinant of the mother's capacity to provide adequate mirroring for the infant (Main,
Kaplan, & Cassidy, 1985; Pederson, Gleason, Moran, & Bento, 1998; Tarabulsy et al., 2005;
van IJzendoorn, 1995; Whipple, Bernier, & Mageau, 2011). Well-attuned maternal mirroring,
in turn, is a necessary antecedent to the development of secure attachment in the infant
(Ainsworth, Blehar, Waters, & Wall, 1978; Belsky, Rovine, & Taylor, 1984; Bigelow et al.,
2010; Bretherton, Biringen, Ridgeway, Maslin, & Sherman, 1989; De Wolff & van Ijzendoorn,
1997; Isabella, 1993; Jaffe, Beebe, Feldstein, Crown, & Jasnow, 2001). In the early
literature that followed Ainsworth's pioneering work on infant attachment (Ainsworth et
al., 1978; Ainsworth & Wittig, 1969), mirroring was often studied as an aspect of the
broader construct of sensitive responsiveness, which encompasses heterogeneous sets of
maternal behaviors (Belsky et al., 1984; De Wolff & van Ijzendoorn, 1997; Grossmann,
Grossmann, Spangler, Suess, & Unzner, 1985; Isabella, 1993; Main, Tomasini, & Tolan,
1979). While theoretically important distinctions had been made between types of mirroring
generated by the mother, mirroring was coarsely defined as a generic construct under the
rubric of sensitivity, and the fine-grained distinctions were overlooked in the early
studies. In his seminal volume on infant development, Stern (1985) drew a stark contrast
between mirroring of the external behavior and mirroring of the internal state, which was
echoed with some variation by later developmentalists. In imitation, the mother mirrors
and replicates the infant's external cues—facial, gestural, or vocal. The mother need not
tune into the infant's internal experiences in order to imitate his external behavior. In
contrast, a more sophisticated form of mirroring necessitates that the mother “get inside”
the mind of the infant and “read” the affective state that underlies his overt behavior
(Stern, 1985, pp. 138–139). This form of mirroring moves beyond the mere matching of the
infant's external signals. What the mother observes and mirrors here is not the infant's
external behavior per se, but his subjective internal state. Whereas a close within-modal
match is found between the mother and the infant in imitation, the mother's mirroring of
the infant's internal state is often cross-modal. As Stern (1985) famously observed (p.
140), the mother may match the feeling state conveyed by the infant's vocalization (e.g.,
exuberant “aaah!”) with her body movement (e.g., performing a shimmy with her upper body
for the duration of the “aaah!”), or match the feeling state captured in the infant's
movement (e.g., hitting a toy) using her voice (e.g., saying “kaaaaa-bam” in rhythm with
the hitting movement). Thereafter, important empirical advances were made in the
literature by Fonagy (1991) and Meins (1997, 1999), who led converging lines of research
underscoring the mother's mentalizing capacity. These were respectively termed parental
reflective functioning (Fonagy, Gergely, Jurist, & Target, 2002; Fonagy, Steele, Steele,
Moran, & Higgit, 1991; Fonagy & Target, 1997; Slade, 2005) and maternal mind–mindedness
(Meins, Fernyhough, Fradley, & Tuckey, 2001; Meins et al., 2003), referencing a mother's
capacity to adequately mirror her infant's subjective internal state (see Sharp & Fonagy,
2008 for a detailed review of relevant constructs). High levels of reflective functioning
and maternal mind–mindedness have been reported in mothers who are securely attached
(Arnott & Meins, 2007; Demers, Bernier, Tarabulsy, & Provost, 2010; Fonagy et al., 1991;
Slade, Grienenberger, Bernbach, Levy, & Locker, 2005). Others have demonstrated that the
secure mother's accurate perception and reflection of her infant's internal state are
causally related to the key features of the infant's self-development, including self-
awareness, self-regulation, and self-efficacy (Bigelow et al., 2010; Fonagy, Gergely, &
Target, 2007; Lyons-Ruth, 2000; Mcquaid, Bibok, & Carpendale, 2009; Nadel, Prepin, &
Okanda, 2005; Schore, 2005; Tronick & Beeghly, 2011). Far less consensus and empirical
support, however, exist on what constitute the essential ingredients of such mirroring and
what mechanisms mediate these developmental effects. Recent research has begun to address
this gap. Gergely (2007) has undertaken a fine-grained analysis of the nature of maternal
mirroring. He proposed that markedness and ostensiveness were essential ingredients of
mirroring (Gergely, 2007; Gergely & Unoka, 2008a). The putative mechanisms mediating the
developmental functions of the marked and ostensive mirroring were also articulated. At
birth, infants are understood to be incapable of differentiating universal categories of
emotions that they experience, such as anger, fear, or sadness (Camras, 2011; Gergely &
Watson, 1996; Walle & Campos, 2012; Widen, 2013). To infants, their affective experience
is one of undifferentiated visceral arousal with overarching positive or negative valence,
rather than one characterized by well-defined, discrete emotions (Fonagy et al., 2002,
2007; Gergely & Watson, 1996, 1999). Central to Gergely's proposal is the hypothesized
role of the mother's marked, ostensive mirroring in the infant's emerging capacity for
subjective awareness of his discrete internal states. When provided consistently to the
infant, the mother's marked, ostensive mirroring is proposed to serve as the essential
foundation upon which the infant learns to organize and make sense of his internal
experiences (Gergely & Unoka, 2008a, 2008b). The mother's marked affective communication
(Fonagy et al., 2002, 2007) is one in which the mother demonstrates her understanding of
the infant's internal state, while concurrently signaling that she is not experiencing the
same state herself. The mother accomplishes this by displaying the infant's affect in a
schematic and exaggerated manner. Consider the mother mirroring her infant's distress. The
mother exaggerates her display of distress; she slows down her expression as she ensures
that it is seen by the infant. Some aspects of the distressed affect are made salient in
the mother's expression, while other peripheral aspects are ignored. The mother may also
mix in other emotions in her expression (e.g., distress intermingled with concern). What
is shown in the mother's mirroring response is the schematically modified display of the
infant's distress, which is perceptually distinguishable from the mother's expression of
her own distress. Trevarthen (1977), Fogel (1993), and Stern (1985) had previously noted
the qualitatively distinct nature of the mother's mirroring from the infant's original
affective display, which was captured in their descriptions of “echo,” “elaboration,” and
“affect attunement,” respectively. Gergely elaborated on the functional significance of
the mother's marked mirroring, particularly underscoring its role in developing the
infant's capacities for organizing and regulating his internal states (Gergely, 2007;
Gergely & Unoka, 2008a). In marked mirroring, the mother's exaggerated display, coupled
with her soothing tone, serves to mitigate the potentially arousing effect of direct
imitation (e.g., the mother crying when the infant cries), while simultaneously making
salient to the infant central aspects of his internal experience. The mother's marked
response is often accompanied by what Gergely calls ostensive communicative cues, which
manifest the mother's intention in displaying the affect (Csibra, 2010; Csibra & Gergely,
2009; Egyed, Kiraly, & Gergely, 2013). The term “ostensive” is borrowed from the
communication literature (Russell, 1940; Sperber & Wilson, 1995), which posits the
inherently dual nature of intention (i.e., informative and communicative) in human
communicative acts (Grice, 1989). In a communicative act, the communicator intends to
convey the desired information (“informative intention”) by making this intention evident
to the addressee (“communicative intention”). Ostensive cues are signals employed by the
communicator to reveal that she has a communicative intention directed toward the
addressee. The mother's gaze at her infant, the slight tilting of her head toward him, her
direct eye contact, the “motherese” intonation, and the calling of the infant's name all
constitute ostensive cues that prototypically accompany the mother's marked mirroring, and
signal to the infant that her expression concerns him and what unfolds within him. These
ostensive signals orient the infant toward his own face and body, setting the stage for
him to learn that this display matches his own subjective internal state. Gergely proposes
that such instances of marked, ostensive communication, to which the infant is hard-wired
to attend (Colombo, Frick, Ryther, Coldren, & Mitchell, 1995; Farroni, Csibra, Simion, &
Johnson, 2002; Parise & Csibra, 2013; Senju & Csibra, 2008), repeatedly orient him to his
subjective internal states (Csibra, 2010; Gergely, 2007; Gergely & Jacob, 2012); through
this process, the infant comes to develop awareness of, and later adequate control over,
his internal experiences (Fonagy et al., 2007; Gergely & Unoka, 2008a, 2008b). In
Gergely's model, the mother's marked and ostensive mirroring functions to prompt the
infant to look to the mother as a way of learning about himself, which serves as an
impetus for the infant's subsequent self-development. In the present study, we contrast
two types of maternal mirroring. The first is imitation, or what we hereafter refer to as
direct mirroring. We consider this to be a rudimentary form of mirroring, which allows the
infant to see his facial, gestural, and vocal behavior directly replicated by the mother
in the same modality (i.e., when the infant frowns, he sees the mother frowning; when the
infant coos, he hears the mother cooing back). We see this imitation as akin to the mother
holding up a physical mirror to the infant. The second is what is hereafter called
intention mirroring. Intention mirroring is the type of mirroring that is characterized by
marked and ostensive verbalization, and lies at the crux of sensitive mothering as Gergely
has hypothesized (Gergely & Unoka, 2008a, 2008b). Rather than acting as a mere physical
mirror, as in the former, here the mother holds up an intention mirror to the infant,
allowing him to see, through her, his own intentions, feelings, and attitudes, many of
which he may not have otherwise made sense of (e.g., as the infant frowns, he sees the
concerned look on the mother's face; gazing at the infant, the mother states in a
motherese voice, “Aww, you didn’t like that”). Here the mother uses verbalization as a
vehicle for representing the infant's internal state originally conveyed in his facial,
gestural, or vocal behavior. Utilizing a micro-analytic coding system devised to
distinguish between the two types of mirroring, we examined, at 7 months postpartum, the
use of mirroring in mothers who were prospectively assessed to be securely attached
compared to those insecurely attached during a modified still-face procedure (MSFP; Koos &
Gergely, 2001). The MSFP is a three-phase procedure, in which the mother interacts freely
with the infant in the first and third phases, but is instructed to maintain a motionless
and neutral ‘still face’ during the second phase, suddenly depriving the infant of
maternal contingency and henceforth inducing stress in the infant (Koos & Gergely, 2001;
Tronick, Als, Adamson, Wise, & Brazelton, 1978). The MSFP thereby offers an opportunity to
observe moment-by-moment exchange between the mother and the infant in the presence of and
during recovery from an interpersonal stressor. Developmentalists have pointed to 7 months
as the juncture at which the external environment develops a particular importance in the
infant's developing awareness of his subjective internal states. Stern (1985) observed
that, starting at 7 months, domains of mother–infant relatedness expand significantly to
include the dyad's subjective internal states. Gergely also noted that infants demonstrate
rudimentary mentalizing abilities at around 7 months (Gergely, 2011; Kovacs, Teglas, &
Endress, 2010). Furthermore, behavioral (Walker-Andrews, 1986) and electrophysiological
(Grossmann, Striano, & Friederici, 2006) evidence suggests that infants’ abilities to
recognize and process cross-modal correspondence in emotional stimuli are initially seen
to emerge at around 7 months. Therefore, we conducted the MSFP at 7 months to capture
early experiences of coordinated communication between mother and infant seen during this
formative juncture. Our primary aim in the study was to investigate whether the infant-
directed communication of securely attached mothers at 7 months could be reliably
distinguished from that of insecurely attached mothers by the extent to which intention
mirroring was used. Three hypotheses were addressed in the present study. First and
foremost, we hypothesized that securely attached mothers would engage in more intention
mirroring than insecurely attached mothers during the free-interaction phases (i.e., first
and third phases) of the MSFP. We also predicted that secure mothers would show an
increase in intention mirroring during the third phase relative to the first phase,
demonstrating sensitivity to the infant's experience of stress during the still-face phase
(Leerkes, 2011; McElwain & Booth-LaForce, 2006). We did not expect to find differences in
the frequency of direct mirroring, either facial/gestural or vocal, between the two mother
groups. Second, we hypothesized that infants of securely attached mothers would direct
their attention more frequently to their mothers, compared with infants of insecurely
attached mothers. We tested this hypothesis by comparing the two infant groups on the
frequency of their gaze toward and away from the mother during the still-face phase.
Whereas the infant's gaze during the free-interaction phases may be directly confounded by
the mother's behavior, the still-face phase was considered apropos for this examination
because the mother's behavior is controlled across participants. Third, we tested the
possibility that the relationship between maternal attachment security and the infant's
attention toward the mother would be mediated by the mother's use of intention mirroring.
Through examining these hypotheses, we attempted to carry out an empirical substantiation
of an aspect of Gergely's model concerning the role of the mother's marked, ostensive
mirroring in shaping the infant's attention and readiness to learn from his primary social
environment—his mother.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

First-time mothers were recruited during the third trimester of pregnancy through local
prenatal clinics and community advertisements. Of 116 participants initially recruited, 61
met eligibility criteria, and 50 completed the MSFP procedure 7 months postpartum.
Enrolled women were between ages 19 and 41 (M = 27.9 ± 4.8), and were generally from
middle to high socioeconomic backgrounds. None of the participants had a history of past
or present alcohol or substance abuse, nicotine use during pregnancy, or were on
psychotropic medications at the time of the study. Each participant provided written
informed consent in accordance with the protocol approved by the local institutional
review board.

<hs>  Measures and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

We adopted a prospective design: mothers’ attachment was assessed prenatally during the
third trimester of pregnancy; mothers returned with their infants 7 months postpartum and
completed the MSFP.

        <hss>Maternal prenatal attachment</hss>

        Maternal attachment was assessed using a modified version of the Adult Attachment
        Interview (AAI; Crittenden & Landini, 2011; George, Kaplan, & Main, 1985). The AAI
        is a semi-structured 1–1.5-h interview comprising probes that elicit attachment-
        related autobiographical memories, usually those involving childhood experiences
        with parents. The coding is determined by the participant's style of discourse in
        describing attachment-related experiences and their impact on present functioning.
        The AAI yields three basic categories that parallel Ainsworth's classification of
        infant attachment (Ainsworth et al., 1978): ‘secure,’ ‘insecure/dismissing,’ and
        ‘insecure/preoccupied.’ Those who are classified as secure describe their
        experiences in a balanced manner, flexibly integrating cognition and affect as
        they recount their past history and process attachment-related information. Those
        with insecure/dismissing attachment tend to be cognitively organized; they
        describe events in a temporally ordered manner, while inhibiting or distorting any
        display of negative affect. In contrast, individuals with insecure/preoccupied
        attachment are organized around their feelings; they oscillate between intense
        affect and draw causal relations that are erroneous and contradictory (Crittenden
        & Landini, 2011). The AAIs were audio-recorded, transcribed, and blindly coded by
        reliable raters in accordance with Crittenden's Dynamic Maturational Model (DMM)
        of Attachment and Adaptation. Fifty percent of transcripts were double-coded to
        ensure inter-rater reliability; there was 77% agreement for the AAI
        classification, with kappa of .66 (p < .001). Discrepancies were resolved through
        conferencing between coders. Of the 50 mothers who completed both the AAI and the
        MSFP, 25 (50.0%) were classified as having secure attachment, 16 (32.0%) had
        insecure/dismissing attachment, five (10.0%) demonstrated insecure/preoccupied
        attachment, and the remaining four (8.0%) alternated between or showed a
        combination of insecure/dismissing and insecure/preoccupied attachment patterns.
        Due to the small size of the latter two groups, all analyses were conducted
        comparing the two predominant attachment groups—those with secure attachment
        versus those with insecure/dismissing attachment.

        <hss>Mother–infant behavior at 7 months postpartum</hss>

        The MSFP followed the standard still-face procedure (Tronick et al., 1978), except
        that the mother and infant were seated next to each other, separated by a divider
        and facing a one-way mirror (Fig. 1(a)). The infant was placed in a high chair in
        the observation room facing the one-way mirror. The mother sat directly adjacent
        to her infant facing the same mirror. The divider placed between the mother and
        infant precluded direct face-to-face communication, but they were able to see each
        other reflected in the mirror. On the opposing side of the one-way mirror were two
        cameras, generating a split-screen recording of the mother and infant. The dyads
        were videotaped as they interacted with each other during the three 2-min phases:
        (1) the baseline normal interaction phase, (2) the still-face phase, during which
        the mother assumed a neutral face, and (3) the recovery phase, in which the mother
        resumed free interaction with the infant (Fig. 1(b)). The start of each phase was
        signaled to the mother via an intercom. While each phase was recorded for 2 min,
        some variation in timing was noted due to infant behavior and parent compliance
        with procedure instructions. Trained raters, who were blind to the mother's
        attachment status, coded the videotaped interaction. Forty percent of the
        videotapes were double-coded to establish inter-rater reliability. Coded variables
        are as follows.

            <hss>Maternal mirroring variables</hss>

            Two forms of maternal mirroring were coded: (a) direct mirroring and (b)
            intention mirroring. Direct mirroring (akin to holding a physical mirror) was
            defined as the mother's non-verbal attunement behavior in which the mother
            directly imitated her infant's expressions. We coded direct mirroring in two
            different modalities, facial/gestural and vocal. Maternal behavior was coded
            as direct mirroring if it entailed a direct replication of the infant's
            preceding behavior in the same modality without the use of verbalization.
            Common examples noted were the display of a maternal smile shortly following
            an infant smile (facial/gestural), and a maternal vocalization “brrr”
            following an infant's “brrr” (vocal). The intention mirroring (i.e., holding
            an intention mirror) was defined as the mother's non-imitative, marked,
            ostensive, verbal attunement. This form of mirroring was distinguished by the
            following: (1) clear indication that the mother was reflecting the infant's
            experience rather than displaying her own internal state (markedness); (2) a
            specific signal which made manifest to the infant the mother's communicative
            intention to present some new relevant information for the infant by
            referencing and acknowledging his intentional, emotional, or attentional state
            using ostensive cues (e.g., her direct eye contact, “motherese” intonation, or
            calling of the infant's name); (3) accuracy and appropriateness from the
            perspective of an onlooker, which suggested that the mother's response was
            aligned with the infant's putative experience in terms of timing, content, and
            intensity (operationalized in terms of the subjective judgment of an
            independent coder who saw the interaction as reflecting reasonable congruence
            between the mother's expression and the infant's assumed experienced state).
            As this coding scheme aimed to capture the mother's interest in and
            understanding of the infant's internal state, only those attributions that
            explicitly acknowledged the infant's subjective state (e.g., “You are feeling
            hot.”) were coded, whereas maternal verbalizations that were ambiguous or
            perceived as commenting on the infant's physical state (e.g., “You are hot.”)
            were not coded. Likewise, whereas the mother's simple imperatives (e.g.,
            “Don’t cry!”) did not qualify, similar statements that referenced the infant's
            state in a marked tone of expression (e.g., “Oh, you are so upset. This is so
            upsetting. Oh dear, oh dear. What's the matter?”) were coded as intention
            mirroring. The most commonly observed examples of intention mirroring during
            the MSFP occurred when the mother recognized that the abrupt loss of maternal
            responsivity in the still-face phase might be both puzzling and distressing
            for the infant. In such an instance, the mother might look into the infant's
            eyes and remark in a marked (exaggerated) tone of voice as she transitioned
            out of the still-face phase: “Wow, what was that? That was crazy, wasn’t it?
            What happened to mommy?” Good to excellent inter-rater reliability was
            demonstrated for the mirroring variables, with the intraclass correlations of
            .80 (direct, facial/gestural), .60 (direct, vocal) and .83 (intention).

            <hss>Infant attention variables</hss>

            Infant attention was quantified by the frequency of gaze fixations toward and
            away from the mother. Our primary interests were (a) fixations on the mother's
            image in the mirror and (b) fixations away from the mirror, although we also
            recorded fixations on the infant's own image in the mirror. Fixation was
            defined as an eye gaze that remained stationary for a minimum of 1 second. The
            intraclass correlation for the infant gaze fixations was .84 (p < .001).

        <hss>Additional mother and infant characteristics</hss>

        Several mother and infant characteristics were also examined as potential
        confounds. Mothers were screened for symptoms of depression and personality
        disorders using the Beck Depression Inventory-II (BDI-II; Beck, Steer, & Brown,
        1996) and Personality Disorder Questionnaire 4+ (PDQ-4+; Hyler, Skodol, Oldham,
        Kellman, & Doidge, 1992), respectively. Maternal parenting stress was assessed
        using the Parenting Stress Index (PSI; Abidin, 1995), and maternal temperament was
        measured via the Adult Temperament Questionnaire-Short Form (ATQ; Rothbart, Ahadi,
        & Evans, 2000). We also collected information on the infant's daycare status
        (i.e., number of hours per week the infant was cared for by someone other than the
        mother). Infants were screened for developmental delays using the Bayley Scales of
        Infant and Toddler Development, Third Edition, Screening Test (Bayley-III; Bayley,
        2005). Infant temperament was evaluated using the Infant Behavior Questionnaire-
        Revised (IBQ-R; Gartstein & Rothbart, 2003) For details on the psychometric
        properties of these instruments, see Shah, Fonagy, and Strathearn (2010).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Mother–infant dyads were classified into secure and insecure attachment groups based on
the mother's AAI. Between-group comparisons were made on all measured sociodemographic and
behavioral variables using chi-square statistics and t-tests for categorical and interval
data, respectively. All analyses were performed using SPSS version 20 and STATA version
12.1.

        <hss>Hypothesis 1: maternal direct mirroring versus intention mirroring</hss>

        We analyzed the frequency of direct mirroring (facial/gestural and vocal) and
        intention mirroring, adjusting for the total length of time for which codable data
        were available in each respective phase. The mirroring variables were inspected
        for normality via quantile–quantile plots of residuals against fitted values.
        Square root transformations offered the closest approximation to normality. We
        probed for the main and interaction effects of maternal attachment status (secure
        vs. insecure) and phase (phase 1 vs. 3), using mixed-effects linear regression
        models that included a subject-level random intercept and a random coefficient for
        phase. The model was fitted by maximum likelihood estimation, and nested models
        were contrasted using likelihood-ratio chi-squares.

        <hss>Hypothesis 2: infant gaze toward versus away from the mother</hss>

        We analyzed the frequency of infants’ gazes toward and away from the mother,
        adjusting for the total number of fixations recorded for each infant during the
        still-face phase. The total number of fixations was quantified as the sum of the
        infant's fixations on the mother, on himself, and away from the mirror. While used
        in the calculation of total fixation frequency, the infant's fixations on himself
        were of less interest in the present study and were excluded from the remainder of
        the analysis to minimize multicollinearity. The proportions of fixations computed
        were arcsine transformed and submitted to the 2 × 2 mixed ANOVA, with maternal
        attachment status (secure vs. insecure) as a between-subjects factor and gaze
        direction (toward mother vs. away from mirror) as a within-subjects factor.

        <hss>Hypothesis 3: mediating role of maternal intention mirroring</hss>

        We used the non-parametric bootstrapping procedure (Preacher & Hayes, 2008) to
        test the model in which maternal intention mirroring was specified as a mediator
        between maternal attachment and infant gaze direction. This procedure uses
        ordinary least squares regression to estimate the total, direct, and indirect
        effects of a predictor on an outcome through a proposed mediator, and provides
        bias-corrected confidence intervals for the indirect effect. This approach makes
        no assumptions about the shape of the sampling distribution of the indirect
        effect, generates estimates based on empirically derived bootstrapped sampling
        distribution, and has been recommended over traditional approaches to mediation
        analysis (i.e., Sobel test or causal steps approach; Mackinnon, Lockwood, &
        Williams, 2004). A total of 5000 bootstrapping samples were utilized in the
        present analysis.

<hs>  Participant characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mother and infant characteristics are shown in Tables 1 and 2 for the secure and
insecure/dismissing groups. No significant differences were observed between the two
groups for any of the measured sociodemographic or behavioral variables.

        <hss>Hypothesis 1: maternal direct mirroring versus intention mirroring</hss>

        Means and standard errors of the maternal mirroring variables are shown in Table 3
        for the two attachment groups. Maternal direct and intention mirroring did not
        correlate with each other (rfacial/gestural direct & intention = .021, p = .85; r
        vocal direct & intention = .196, p = .08), while the two forms of direct mirroring
        were significantly correlated (rfacial/gestural direct & vocal direct = .29, p =
        .009).

            <hss>Maternal direct mirroring</hss>

            As hypothesized, maternal attachment status was not a significant predictor of
            direct mirroring, either alone (facial/gestural, βAAI = .001, 95% CI = -.05 to
            .06, z = 0.03, p = .97; vocal, βAAI = −.03, 95% CI = −.09 to .03, z = −0.89, p
            = .37) or in interaction with phase (facial/gestural, βAAI × phase = −.006,
            95% CI = −.06 to .05, z = −0.20, p = .84; vocal, βAAI × phase = .005, 95% CI =
            −.06 to .06, z = 0.15, p = .88; Figure 2). Both secure and insecure/dismissing
            mothers engaged in a higher frequency of facial/gestural direct mirroring
            during the first phase of the MSFP compared to the third phase (βphase = −.04,
            95% CI = −.08 to −.01, z = −2.49, p = .01). No difference was found in the
            frequency of vocal direct mirroring between the two phases (βphase = −.01, 95%
            CI = −.05 to .02, z = −0.68, p = .50).

            <hss>Maternal intention mirroring</hss>

            A significant main effect was found for maternal attachment status (βAAI =
            −.08, 95% CI = −.15 to −.02, z = −2.73, p = .006), with secure mothers
            displaying intention mirroring at a frequency greater than twice that of their
            insecure/dismissing counterparts (Figure 2). Both mother groups engaged in
            intention mirroring more frequently in the third phase as compared to the
            first phase (βphase = .04, 95% CI = .01 to .07, z = 2.79, p = .005). Maternal
            attachment and phase did not interact significantly in the prediction of
            intention mirroring (βAAI × phase = .01, 95% CI = −.04 to .06, z = 0.46, p =
            .64).

        <hss>Hypothesis 2: infant gaze toward versus away from the mother</hss>

        Means and standard errors of the gaze fixation variables are presented in Table 4
        for the secure and insecure/dismissing attachment groups. The 2 (secure vs.
        insecure maternal attachment) × 2 (infant gaze toward mother vs. gaze away) mixed
        ANOVA yielded no significant main effects of maternal attachment status (F(1, 39)
        < 0.001, p = .98) or gaze direction (F(1, 39) = .283, p = .60). However, a
        significant interaction of maternal attachment and gaze direction was found (F(1,
        39) = 6.393, p = .02). Consistent with our hypothesis, infants of secure mothers
        directed their gaze more frequently to their mothers compared to infants of
        insecure/dismissing mothers (t(39) = 2.38, p = .02). The reverse pattern was seen
        for gazes directed away, with infants of insecure/dismissing mothers looking away
        more frequently than infants of secure mothers (t(39) = −2.06, p = .046; Figure
        3).

        <hss>Hypothesis 3: mediating role of maternal intention mirroring</hss>

        Results indicated a non-significant mediating effect of maternal intention
        mirroring. Regression analyses did not reveal a significant relationship between
        maternal intention mirroring and infant's gaze directed toward the mother (b =
        −.33, t = −.69, p = .49) or directed away from the mirror (b = .22, t = .39, p =
        .70).

<h>DISCUSSION</h>
----------

We contrasted a rudimentary form of maternal mirroring (i.e., direct mirroring) with the
mother's marked and ostensive mirroring (i.e., intention mirroring), the type of mirroring
that has been theorized to serve as an impetus for the infant's subsequent psychosocial
development (Fonagy et al., 2002, 2007; Gergely, 2007). As hypothesized, direct mirroring
did not distinguish between mothers who were prospectively assessed to be secure and those
assessed to be insecure/dismissing. However, the two groups of mothers showed a
significant difference in their use of intention mirroring, with the frequency in secure
mothers observed to be more than double that of insecure/dismissing mothers. A notable
difference was also found in the frequency with which infants directed their attention to
their mothers. Infants of secure mothers directed their gaze toward their respective
mothers at a higher frequency than did infants of insecure/dismissing mothers. Although
Gergely proposed markedness and ostensiveness as essential ingredients of the mother's
affectively attuned communication (Gergely, 2007; Gergely & Unoka, 2008a, 2008b), this is
the first study, to our knowledge, that directly examined these elements as part of the
mother's affect mirroring communication. Two aspects of our intention mirroring variable
should be noted in considering our results. First, as opposed to direct mirroring, which
is primarily concerned with the mother's matching of her behavior to her infant's external
behavior, intention mirroring was coded when the mother went beyond the behaviors and
remarked on the infant's subjective internal experiences. As has been described in the
previous literature (Fonagy et al., 2002; Meins et al., 2001; Sharp & Fonagy, 2008), the
process of intention mirroring draws upon the mother's complex higher-order metacognitive
capacities, such as parental reflective functions or maternal mind–mindedness, which
enable her to make sense of the infant's unobservable internal states. In this respect,
the construct of intention mirroring encompassed what previous studies have identified as
critical elements of maternal sensitive responsiveness. Second, however, to be coded as
intention mirroring, the mother's acknowledgment of her infant's subjective internal state
had to be delivered in a manner that generates understanding in the infant that her
mirroring display concerns his internal experiences (Fonagy et al., 2002; Slade, 2005). In
other words, to use Gergely's terms, the mother's use of marked and ostensive cues
constituted a critical aspect of intention mirroring, which distinguished our intention
mirroring variable from extant empirical constructs. The distinct nature of our concept of
intention mirroring emerges from Gergely's fine-grained analysis of the functional
significance of markedness and ostenstiveness in maternal mirroring (Gergely, 2007;
Gergely & Unoka, 2008a). Intention mirroring shares similarities with Meins's
mind–mindedness (1999) and Stern's affect attunement (1985) in that it concerns the
mother's recognition and reflection of the infant's internal state. However, Gergely
diverged from the primary intersubjectivist view of Stern (1985) and other theorists
(e.g., Meltzoff, Trevarthen), which hinges on the assumption that infants have an inherent
capacity to access their subjective internal states and to perceive the ‘sharing’ of these
states by their mothers (Meltzoff, 2002; Meltzoff & Gopnik, 1993; Trevarthen, 1993;
Trevarthen & Aitken, 2001). Detailing criticisms of this view (Gergely, 2007; Gergely &
Csibra, 2005; Gergely & Watson, 1999), Gergely contended that the infant's ability to
recognize his discrete internal states, and the sharing thereof, is a developmental
outcome made possible by a unique form of maternal mirroring that enables this capacity to
be fostered in the infant (Fonagy et al., 2002, 2007). In proposing this view, Gergely
underscored specific elements of maternal mirroring—markedness and ostensiveness—that
achieve this end. Meins similarly but independently proposed and demonstrated the
functional significance of the mother's tendency to comment on her infant's mental states;
namely, it facilitates the infant's developing understanding of the mind (Meins, 1997;
Meins et al., 2003). However, Meins's theory did not discuss the putative mechanisms that
mediate this link, although in later writings Meins and colleagues also emphasized the
importance of measuring “appropriateness” in addition to simple mental-state talk in
achieving robust predictions from maternal mind mindedness to the development of the child
(Osorio, Meins, Martins, Martins, & Soares, 2012). Gergely's distinct contribution lies in
spelling out how the mother's appropriate affectively attuned communication, when using
marked and ostensive cues, can be accessed via the infant's rudimentary abilities. The
developmental significance of this is assumed to be in the understanding of emotional
experience, which has an interpersonal aspect in Gergely's theory. A recent study with
primary school children provided confirmatory evidence in that emotional validation by the
mother predicted higher emotional awareness, whilst emotional invalidation reduced
emotional awareness in the child (Lindberg, 2013). Our measure of intention mirroring did
not correlate with that of direct mirroring, indicating that distinct processes may
underpin the two forms of mirroring. Also of note is that intention mirroring was
significantly associated with maternal attachment security, while direct mirroring showed
no relationship. Whereas secure and insecure/dismissing mothers did not appear to differ
in their ability to respond on a behavioral level, as assessed by direct mirroring,
insecure/dismissing mothers were significantly less able than their secure counterparts to
accurately extract meaning from their infants’ behavior and respond to their underlying
internal states using marked and ostensive cues, as assessed by intention mirroring. We
had also hypothesized an increase in secure mothers’ intention mirroring during the third
phase of the MSFP, the phase in which infants undergo recovery from the stress of the
still-face phase. The hypothesized increase was observed not only in the expected group of
secure mothers but also in insecure/dismissing mothers, and was accompanied by a decrease
in facial/gestural direct mirroring in both groups. While little attention has been
directed toward mothers’ responses in the still-face literature, a decrease2 in the
frequency of maternal direct mirroring has previously been reported during the third phase
(Bigelow & Walden, 2009). Our documented increase in intention mirroring, coupled with a
decrease in facial/gestural direct mirroring, suggests that mothers may be more inclined
to go beyond simple facial/gestural imitation and attend to their infants’ underlying
needs in the face of infant dysregulation. This tendency appears to be present in both
secure and insecure/dismissing mothers, although the frequency of intention mirroring was
observed to be consistently higher in secure mothers. In Gergely's model, the function of
the mother's intention mirroring is to help the infant recognize that what he sees
displayed externally by the mother congruently matches his internal experiences. In
mother–infant dyads where changes in the infant's internal states repeatedly effect
visible external changes in the mother, the infant is thought to routinely look to the
mother, his “intention mirror,” for a perceptual representation of his emotional and
intentional states. Our study provided partial support for this model. Infants of mothers
who were more proficient in intention mirroring (i.e., secure mothers) looked to their
mothers more than infants of mothers who were less proficient (i.e., insecure/dismissing
mothers). However, despite the significant difference that the two attachment groups
demonstrated in both maternal intention mirroring and infant gaze direction, infant gaze
direction was not directly associated with intention mirroring in our laboratory
situation. Maternal attachment has been robustly associated with the quality of the
affective communication that the mother provides for her infant (Arnott & Meins, 2007;
Slade et al., 2005; Tarabulsy et al., 2005; Whipple et al., 2011). The link we report
herein between maternal attachment security and intention mirroring is in line with this
research. Evidence also exists that, by 7 months of age, infants develop consistent
expectations about their mothers’ patterns of responsiveness, which helps guide and
regulate their end of the communicative exchange (Hains & Muir, 1996; Legerstee &
Varghese, 2001; Mcquaid et al., 2009). This capacity has been demonstrated in the still-
face or replay phases, where infants who have been exposed to high levels of maternal
mirroring continued their attempts at engagement with their mothers (e.g., continued gaze
or smile), even in the absence of their mothers’ typical level of attunement (Bigelow &
Walden, 2009; Legerstee & Varghese, 2001; Mcquaid et al., 2009). In noteworthy contrast,
infants in these studies who were accustomed to low levels of mirroring displayed
relatively little effort to carry on their side of the communication. While these results
were obtained on measures of generic mirroring, and mothers were distinguished on the
basis of the amount of mirroring they provide, we have demonstrated here that the type of
mirroring may matter. We have shown that the above pattern of results was replicated when
mothers were distinguished on the basis of intention mirroring. No noteworthy finding
emerged, however, with regard to direct mirroring alone. Contrary to our expectation, our
hypothesis that intention mirroring may mediate the link between the mother's attachment
and the infant's attention toward the mother was not confirmed in our laboratory. The lack
of association seen in our data between intention mirroring and infant gaze raises the
possibility that the relationship between maternal attachment security and infant gaze
direction may be mediated by aspects of maternal attachment that are independent from
intention mirroring. While it is difficult to rule out this possibility, it also seems
plausible that the mediational link, which may have taken shape over a period of months
while patterns of mother–infant interaction were developed, may not have been evident
during a 6-min structured interaction in the lab. In line with the previous studies (e.g.,
Bigelow & Walden, 2009; Legerstee & Varghese, 2001; Mcquaid et al., 2009), the differences
seen in our infants’ attention toward their mothers in the still-face phase, during which
maternal behavior was held constant, may reflect differences in the infants’ interactive
histories with their mothers and the expectations that the infants have subsequently come
to form. Infants of secure mothers may have directed frequent attention to their mothers
during the still-face phase, given their routine experience of their mothers’ intention
mirroring. Indeed, despite the lack of association at the micro level in the lab, there
may have been a general pattern of mediation at the macro level, linking the mother's
attachment security, her history of intention mirroring, and the infant's pattern of
attention toward the mother. The absence of association seen at the micro level may also
serve to corroborate results from prior studies that the variation in the mother's
behavior (e.g., mirroring) on a short-term basis does not alter the general expectations
of the infant for responsive interactions. Several limitations of the study should be
recognized. First, our sample consisted largely of middle- to upper-class mothers of
average to above-average intelligence, and therefore may not have been representative of
the general population. Second, we were not able to obtain a large enough sample of
insecure/preoccupied mothers and their infants. Future research should examine direct and
intention mirroring in this group. It would be of interest to evaluate whether intention
mirroring could discriminate between different subtypes of insecure attachment. Third, the
present study did not measure contingency in maternal mirroring, a construct that Gergely
emphasized alongside markedness and ostensiveness (Gergely & Unoka, 2008a; Gergely &
Watson, 1999). Fourth, we did not code the valence of the infant's signals to which
maternal mirroring was directed. There is evidence from brain imaging and neuroendocrine
research that disrupted maternal attunement may be strongly characterized by the mother's
disengagement from and denial of negative infant cues (Kim, Fonagy, Allen, & Strathearn,
2014; Kim, Fonagy, Koos, Dorsett, & Strathearn, 2013). One may therefore postulate that
the low levels of intention mirroring we documented in insecure/dismissing mothers may be
more specific to the infant's negative internal states (e.g., distressed state). This
would be a fruitful area for further investigation. The present study is the first attempt
to examine markedness and ostensiveness as distinguishing features of the mother's well-
attuned, affect-mirroring communication with her infant. We have found evidence for high
levels of marked, ostensive mirroring in securely attached mothers, who were also
frequently the focus of their infants’ attention. Mothers with insecure/dismissing
attachment were low in this form of mirroring, and were also less frequently the target of
their infant's attention. While its direct links to infant behavior should be explored
further in future research, the marked, ostensive mirroring may be more accurate than
extant mirroring constructs in capturing the essence of securely attached mothers’
affective attunement to their infants.


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<ART>Motivational, volitional and multiple goal predictors of walking in people with type 2 diabetes
================================================================================

Authors: Masoumeh Namadian, Justin Presseau, Margaret C. Watson, Christine M. Bond, Falko F. Sniehotta
DOI: 10.1016/j.psychsport.2016.06.006
Year: 2016  |  Pages: 83-93
ASJC codes: 3202
Keywords: Action control, Goal conflict, Goal facilitation, Health action process approach, Motivation, Physical activity, Type 2 diabetes mellitus, Volition, Walking

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Type 2 diabetes is a major public health problem. Effective diabetes self-management involves people engaging in multiple health behaviours, including physical activity. Walking is an effective, accessible and inexpensive form of physical activity, yet many people with Type 2 diabetes do not meet recommended levels. The present study aimed to: 1) identify demographic, motivational and volitional factors predictive of walking in people with Type 2 diabetes mellitus, and 2) test whether accounting for the perceived impact of other goal pursuits (goal facilitation and goal conflict) improved the prediction of walking. Methods: A theory-based cross-sectional study using the Health Action Process Approach was conducted in adults with Type 2 diabetes across Scotland. Assuming a 50% response rate 1000 questionnaires were mailed to achieve the target sample size (N = 500). Demographic information was collected, and intentional (outcome expectations, social support, risk perceptions), motivational (intention, self-efficacy), volitional (action planning, action control) and multiple goal (goal conflict, goal facilitation) factors were assessed as predictors of physical activity in general and walking specifically. Results: The final sample comprised 411 respondents. The majority (60%) were non-adherent to physical activity recommendations. Of 411 respondents, 356 provided walking data. Body Mass Index and age were the only demographic and anthropometric factors predictive of walking (overall R2 = 0.04). When motivational factors were added, intention and self-efficacy added to the prediction (overall R2 = 0.07). When volitional factors were added, only action control was predictive of walking (overall R2 = 0.08). Finally, goal facilitation explained an additional 7% variance in walking when added to the model (final overall R2 = 0.15). Conclusion: There was low adherence with physical activity recommendations in general and walking in particular. When testing predictors of motivational, volitional and competing goal constructs together, action control and goal facilitation emerged as predictors of walking. Future research should consider how walking can be embedded synergistically alongside other goal pursuits and how action control may help to ensure that they are pursued.

--------------------------------------------------------------------------------


<h>BACKGROUND</h>
----------

Diabetes is a common non-communicable chronic disease. The global prevalence of 8.3% is
expected to increase to 10.1% by 2030 (IDF, 2013). In Scotland, the prevalence of diabetes
is 4.7%, slightly above the UK average (S.D.S.M. Group, 2012). Almost 90% of patients with
diabetes have Type 2 diabetes (WHO, 2006) and their life expectancy is up to 10 years less
than people without Type 2 diabetes (Diabetes UK, 2012a, 2012b). Diabetes is a chronic,
metabolic disease characterized by increased levels of blood sugar. Diabetes occurs either
when the pancreas produces no or insufficient insulin, or when the body cannot effectively
use the insulin it produces. Type 2 diabetes results from the body’s insufficient
production and/or ineffective use of insulin. Hyperglycaemia (an increased concentration
of glucose in the blood) is a common effect of uncontrolled diabetes and over time leads
to serious damage to the heart, blood vessels, eyes, kidneys, and nerves (WHO, 2015). Type
2 diabetes has non-modifiable (genetic) and modifiable (environmental and behavioural)
risk factors (Alberti, Zimmet, & Shaw, 2007). Genetic predisposition is aggravated by
behavioural factors including smoking, being overweight, abdominal obesity and lack of
physical activity (Stumvoll, Goldstein, & van Haeften, 2005). Good management of these
behavioural factors can prevent or delay onset of diabetes, and many of its complications
(WHO & IDF, 2004). The recommended regimen for managing Type 2 diabetes includes eating
healthily, being physically active (moderate intensity) for at least 30 min on most days,
smoking cessation, and taking medication (e.g., oral hypoglycaemic drugs, insulin,
antihypertensive and lipid lowering drugs) (D.P.P.R. Group, 2002; Hallal et al., 2012;
WHO, 2012; Zimmet, Alberti, & Shaw, 2001). Evidence suggests that regular physical
activity reduces the risk of coronary heart disease, stroke, diabetes, hypertension, colon
cancer, breast cancer and depression and is the main factor in weight control (WHO, 2010).
For example, trials have demonstrated the benefits of undertaking physical activity in
preventing Type 2 diabetes, improving glycaemic control and aerobic fitness, as well as
decreasing the risk of cardiovascular disease and overall mortality (Sigal, Kenny,
Wasserman, Castaneda-Sceppa, & White, 2006). Physical inactivity is the fourth leading
risk factor for mortality worldwide, accounting for 6% of deaths (WHO, 2010), and
approximately 30% of the disease burden due to diabetes and ischemic heart disease (WHO,
2010). There is evidence to suggest that patients with Type 2 diabetes engage in even less
physical activity than the general population (39% versus 58%) (Morrato, Hill, Wyatt,
Ghushchyan, & Sullivan, 2007), and the level of physical activity in those who do
participate is low (Badenhop, 2006). However there is wide inter-country variation, with
recent studies showing that adherence to recommended physical activity in Type 2 diabetes
ranges between 9% and 69% (Broadbent, Donkin, & Stroh, 2011; Morrato et al., 2007; Nelson,
Reiber, & Boyko, 2002; Plotnikoff, Brez, & Hotz, 2000; Serour, Alqhenaei, Al-Saqabi,
Mustafa, & Ben-Nakhi, 2007; Shultz, Sprague, Branen, & Lambeth, 2001; Thomas, Alder, &
Leese, 2004). A World Health Organization (WHO) report showed that adherence with physical
activity recommendations by people with Type 2 diabetes ranged from 7.7% to 55% across
different countries (WHO, 2003). The high prevalence of Type 2 diabetes, along with low
level of physical activity, highlights the need for new approaches to improve an
individual’s adherence to physical activity recommendations. These new approaches need to
be acceptable, accessible and inexpensive to increase the probability of adoption.

<hs>  Walking as a specific form of physical activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Walking is the most common form of physical activity and is an important component of
total physical activity in adult populations (Monteiro et al., 2003; Morris & Hardman,
1997). Walking is acceptable, accessible and inexpensive; it requires no specific
facilities, can be integrated easily into a daily routine, and is generally safe (Monteiro
et al., 2003; Morris & Hardman, 1997). The energy expenditure of walking at a moderate
pace of 5 km/h (3 miles/hour) can meet the definition of moderate intensity physical
activity (Ainsworth et al., 2000). However, data from the National Health and Nutrition
Examination Survey on 2896 patients with Type 2 diabetes in the US showed that 46% of
participants did not report any walking for exercise (Gregg, Gerzoff, Caspersen,
Williamson, & Narayan, 2003). While the literature to date on behavioural determinants of
physical activity focuses on more generic descriptions of physical activity, given the
above-mentioned benefits of walking, our aim was to focus specifically on understanding
the factors associated with walking in people with Type 2 diabetes.

<hs>  Behavioural determinants of physical activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There is a large body of evidence on the biological, sociological, psychological, and
environmental factors that influence physical activity (Bonner, 2010). Non-modifiable
factors (e.g., age, gender) can help to identify sub-groups that are likely to be
physically inactive, whereas modifiable factors (e.g., intention, self-efficacy) provide
potential targets for increasing physical activity (Schwarzer, 2008; Wing et al., 2001). A
number of theories summarise the relationship between modifiable factors and behaviour to
generate testable hypotheses. The Health Action Process Approach (HAPA) (Schwarzer, 1992)
is a comprehensive social cognition model which accounts for motivational factors
including outcome expectation, social support, risk perceptions, intention, and self-
efficacy, and as well as contemporary theoretical development in volitional (post-
intentional) processes including action planning and action control (Schwarzer, 2008). The
HAPA describes intention as a function of self-efficacy, outcome expectations and risk
perceptions. Intentional processes are then related to action via volitional processes
involving planning and action control, further supported by self-efficacy and impacted by
available barriers and facilitators such as social support (Schwarzer et al., 2003). Self-
efficacy is a main influential factor, referring to a person’s perceived capability of
performing a desired behaviour (Schwarzer et al., 2003). Outcome expectations refer to
perceived positive and negative outcomes of engaging in the health behaviour; the more the
beneficial outcomes and the fewer the negative outcomes that are perceived, the more
likely it is that an individual will intend to engage in the behaviour (Schwarzer et al.,
2003). Risk perceptions refer to the minimum level of perceived risk, which must exist
before an individual starts to consider the benefits of possible behaviour and their
capability to undertake those behaviours. Strong intention is an often necessary but
rarely sufficient precondition for action (Orbell & Sheeran, 1998). Post-intentional
(volitional) processes such as action planning and action control can help to ensure
intentions are translated into action. Action planning involves linking goal-directed
action to environmental cues by specifying the when, where, whom, and how to enact a
behaviour to help translate intention into action (Darker, French, Eves, & Sniehotta,
2010; Gollwitzer, 1999). In addition, more active self-regulatory efforts can further
supplement the translation of intention into action. Action control, i.e., self-monitoring
of behaviour, being aware of monitoring standards and expending effort in goal pursuit, is
a self-regulatory process for ensuring intention enactment (Carver & Scheier, 1982;
Sniehotta, Scholz, & Schwarzer, 2005). The HAPA has been applied to understand physical
activity across numerous studies. Some studies focus on the entire HAPA model (Barg et
al., 2012; Bonner, 2010; Caudroit, Stephan, & Le Scanff, 2011; Renner, Spivak, Kwon, &
Schwarzer, 2007; Scholz, Schuz, Ziegelmann, Lippke, & Schwarzer, 2008; Scholz, Sniehotta,
& Schwarzer, 2005, 2008; Schwarzer et al., 2007; Sniehotta, Scholz, et al., 2005;
Sniehotta, Schwarzer, Scholz, & Schüz, 2005), whilst others focus on more specific
components of the model (Barg et al., 2012; Lippke, Ziegelmann, & Schwarzer, 2005;
Schwarzer et al., 2007; Sniehotta, Scholz, & Schwarzer, 2006; Sniehotta, Schwarzer, et
al., 2005). Few studies have applied the HAPA to the behaviour of people with Type 2
diabetes. Bonner (Bonner, 2010) used the HAPA in Type 2 diabetes and showed that self-
efficacy and outcome expectations were predictive of physical activity intention, and
intention (but not self-efficacy or action planning) predicted physical activity levels.
No study has yet used the HAPA model to understand physical activity in people with Type 2
diabetes focusing specifically on walking as an inexpensive and accessible form of
physical activity (Lippke & Plotnikoff, 2014).

<hs>  Towards multiple behaviour approaches</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Most popular social cognition models of health behaviour focus on understanding a single
health behaviour at a time. The ecological validity of such an approach has increasingly
been questioned (Presseau, Tait, Johnston, Francis, & Sniehotta, 2013). In everyday life,
individuals pursue multiple goals and perform multiple behaviours alongside the single
health behaviour that is typically the focus of tests of behavioural theory. These goal
pursuits compete for time and energy such that pursuit of some may help and/or hinder the
pursuit of a particular health behaviour, such as physical activity in general or walking
specifically. The extant literature has predominantly managed the concept of considering
multiple goals by focusing on the impact of goal conflict on health behaviour. Goal
conflict can be described as occurring when the pursuit of multiple personal goals leads
to situations where they interfere with one another. For instance, working, childcare,
relaxing and socialising may be common personal goals that have the potential to conflict
with walking by taking available leisure time, energy or other resources that might
otherwise be used go for a walk. The evidence on the link between goal conflict on
physical activity-related behaviour is mixed. There is a lack of support for this
relationship in between-subject predictive studies (Li & Chan, 2008; Presseau, Sniehotta,
Francis, & Gebhardt, 2010; Riediger & Freund, 2004). However, a study investigating actual
time spent pursuing goals that conflict with physical activity within-subjects was
negatively predictive of objectively assessed physical activity (Presseau et al., 2013),
and a study investigating goal conflict in more resource constrained contexts has also
shown that goal conflict is negatively predictive of behaviour (Presseau, Francis,
Campbell, & Sniehotta, 2011). As people with Type 2 diabetes engage in self-management
regimens that inherently involve pursuing multiple behaviours and goals, it is plausible
that goal conflict may be a useful additional construct in this population. By comparison,
goal facilitation has received less research than goal conflict, yet is recurrently shown
to be predictive of physical activity-related behaviours. Goal facilitation involves
instances where the pursuit of other personal goals sets the stage or makes it more likely
that physical activity will take place (e.g. socialising with friends that involves
walking in the park), or inherently involves physical activity (e.g. commuting to work can
be facilitative of physical activity when involving active travel). The presumption is
that the more one’s other personal goals are aligned with physical activity, the greater
the physical activity. Goal facilitation has been demonstrated to positively predict
physical activity (Riediger & Freund, 2004), a relationship that is maintained even when
controlling for intention and self-efficacy (Presseau et al., 2010). However, it is not
clear whether these relationships persist when accounting for volitional (planning, action
control) processes, which could in themselves involve managing competing goals. For
instance, action planning may involve describing other goals that facilitate engaging in
physical activity, whereas coping planning may involve identifying barriers that in
themselves are actually competing goal pursuits (Presseau, Boyd, Francis, & Sniehotta,
2015). This conceptual overlap issue could be addressed empirically by investigating
whether indicators of goal conflict or goal facilitation remain predictive of physical
activity when controlling for volitional factors. Furthermore, it is not clear how either
goal conflict or goal facilitation relate to walking behaviour specifically, which may
have different levels of perceived conflict and facilitation than other forms of more
intensive physical activity. The present study aimed to: 1) identify demographic,
motivational and volitional factors predictive of walking in people with Type 2 diabetes,
and 2) test whether accounting for the perceived impact of goal pursuits (goal
facilitation and goal conflict) improved the prediction of walking.

<h>METHODS</h>
-------

This was a cross-sectional theory-informed postal questionnaire study undertaken with
people with Type 2 diabetes from the Grampian and Tayside regions of Scotland. All
English-speaking adults (>18 years) diagnosed with Type 2 diabetes were eligible to
participate. Patients with serious end stage illness and patients with mental disability
were excluded.

<hs>  Questionnaire development</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

A qualitative study was initially conducted using the Theoretical Domains Framework (TDF)
(Michie et al., 2005) to identify which theoretical domains and constructs were relevant
to understanding the adherence of people with Type 2 diabetes to physical activity
recommendations in general and walking in particular. The results were used to identify
relevant items that were included in a draft questionnaire. The questionnaire explored
physical activity in general, and walking in particular. Pre-piloting of the questionnaire
was undertaken with five people using the “think aloud” method (Jones, 1989; Lundgren-
Laine & Salantera, 2010) where participants verbalised their thoughts. Three participants
with Type 2 diabetes were recruited from the Scottish Diabetes Research Network (SDRN)
(see later) and three were colleagues with Type 2 diabetes in the Centre of Academic
Primary. Minor revisions were made prior to the pilot study. The questionnaire was piloted
with 50 people with Type 2 diabetes, selected randomly from the SDRN list, replicating the
distribution process planned for the main survey (pre-notification letter, questionnaire
and covering letter, and a reminder letter and replacement questionnaire after two weeks).
To assess test-retest reliability, respondents were sent a second copy of the
questionnaire two weeks after returning their first questionnaire.

<hs>  Sample and recruitment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The sample size for this study was influenced by two factors: 1) having acceptable
precision for the estimation of adherence with physical activity (any precision within ±5%
that would be clinically and statistically acceptable) and 2) the resources (time and
money) available to undertake the research. To achieve a balance between these two items,
a sample size of 500 patients was required. As previous research has shown compliance with
physical activity to range from 19 to 30% (midpoint: 25%) (Kamiya et al., 1995; Kravitz et
al., 1993), this allowed estimation of adherence with physical activity of 25% with
precision within ±3.8% (95% CI 21.2%–28.8%). Previous research in community samples
indicated a 50% response rate was likely, therefore 1000 questionnaires were mailed to
achieve the target of 500 evaluable responses. Participants were recruited from the
Scottish Diabetes Research Network (SDRN), a register of patients with diabetes in
Scotland who have consented to be contacted about potential participation in research
studies (SDRN, 2010). All SDRN registered patients in Grampian (n = 388) were identified
and invited to participate, supplemented by a random sample of 612 of the 1279 patients
registered in Tayside exclusive of those who had taken part in the pilot study. A pre-
notification letter with a reply slip, that they could use if they did not want any
further communication, was sent to these 1000 patients two weeks before the questionnaire
and accompanying invitation letter were mailed. Two weeks after the first mailing, a
reminder letter and another copy of the same questionnaire were sent to non-respondents.
The questionnaire was piloted with 50 people with Type 2 diabetes, selected randomly from
the SDRN list, replicating the distribution process planned for the main survey (pre-
notification letter, questionnaire and covering letter, and a reminder letter and
replacement questionnaire after two weeks). To assess test-retest reliability, respondents
were sent a second copy of the questionnaire two weeks after returning their first
questionnaire.

        <hss>Physical activity and walking</hss>

        The questionnaire included items assessing time spent being physically active in
        the last seven days based on the short version of International Physical Activity
        Questionnaire (IPAQ) (IPAQ, 2002). It measures physical activity over a short time
        frame. The IPAQ was developed by consensus in 1998–1999 with support from the WHO
        to enable the cross-national assessment of physical activity in adults aged 18–65
        years (Craig et al., 2003; Macfarlane, Lee, Ho, Chan, & Chan, 2007; Papathanasiou
        et al., 2010). The short format of the IPAQ asks about three types of activity in
        the four domains. Walking, moderate-intensity activities and vigorous-intensity
        activities are the specific types of activity which are assessed by the IPAQ short
        form (IPAQ 2002). This version generates a total score by summation of the
        duration (in minutes per day) and frequency (days) of walking, moderate-intensity
        activities and vigorous-intensity activities. The IPAQ measures energy as
        Metabolic Equivalent of Task (MET). The IPAQ has been used in a number of
        international studies (Craig et al., 2003; Guthold, Ono, Strong, Chatterji, &
        Morabia, 2008) and acceptable reliability and validity has been reported (Craig et
        al., 2003; Hagstromer, Oja, & Sjostrom, 2006; Hallal et al., 2010; Macfarlane et
        al., 2007; Papathanasiou et al., 2010). An international reliability and validity
        test of the IPAQ was conducted in 14 centres in 12 countries and reported that it
        has acceptable reliability and validity at least equal to other established self-
        report tools for physical activity in diverse populations of 18–65 years (Craig et
        al., 2003). We focused specifically upon understanding predictors of walking as
        the primary outcome of interest given the wording of our predictors focused upon
        walking. Walking was assessed using the total time or energy (150 min or >600 MET
        minutes/week) spent on walking measured by the IPAQ and served as the dependent
        variable in all predictive analyses. However we also aimed to describe overall
        adherence to physical activity recommendations. Adherence to physical activity was
        assessed by comparison with two different recommendations. Firstly it was assessed
        by comparison with the Scottish Intercollegiate Guideline Network/WHO (SIGN, 2010;
        WHO, 2010) advice of at least 150 min of vigorous/moderate (no walking included)
        combined physical activity per week (equal to at least 600 MET1). Secondly it was
        assessed accordingly to the IPAQ criterion of 600 MET minutes/week of any
        combination of walking, moderate-intensity or vigorous-intensity physical
        activities (IPAQ, 2002). According to IPAQ, <600 MET minutes/week, 600–2999 MET
        minutes/week, and >3000 MET minutes/week are considered as low, moderate and
        vigorous physical activity, respectively (IPAQ, 2002).

        <hss>Predictors of walking</hss>

        The questionnaire assessed a number of potential demographic and theoretical
        predictors of walking: demographic variables, self-efficacy, outcome expectations,
        risk perceptions, intention, action planning and control, social support, goal
        facilitation and goal conflict. The demographic variables age, gender, education,
        and employment items were defined using the England household version of the 2001
        Census questionnaire (OFNS, 2002). All theoretical items were worded according to
        the TACT principle (Target, Action, Context, and Time), specifying the behaviour
        of interest as: “To increase (my) own walking level by 20% during the normal daily
        routine in the forthcoming month” and described in detail below.

            <hss>Self-efficacy</hss>

            Self-efficacy was assessed using six items ranging from 1 (strongly disagree)
            to 5 (strongly agree) in relation to perceived capability to increase walking
            despite the presence of barriers (Schwarzer et al., 2003). The stem “I am
            confident that I can increase my walking by 20% in the next month even if ….”
            had response options such as: “the weather is bad”, “it is hard for me
            physically”, “I do not have much time”.

            <hss>Outcome expectations</hss>

            Two facets of outcome expectations were assessed (Schwarzer et al., 2003),
            with scores for each item ranging from 1 (not at all) to 4 (exactly true):
            there were six items to assess positive outcome expectations, and three items
            to assess negative outcome expectations. The stem “if I increase my walking by
            20% in the next month ….” had response options such as: “I would feel better
            afterwards”, “it would take up a lot of time”.

            <hss>Risk perception</hss>

            Risk perception refers to the respondent’s belief about their vulnerability to
            health problems, or specifically in this patient group for their diabetes to
            worsen (Schwarzer et al., 2003). Absolute and relative vulnerability were
            assessed using six items with response options ranging from 1 (strongly
            disagree) – 7 (strongly agree). The items measuring absolute vulnerability had
            a stem “If I am not physically active … ” and response options such as: “ … I
            am concerned that my health in general will become worse”, “ … I am concerned
            that my diabetes in general will become worse”, “ … I will worry about getting
            a serious medical condition”. The items measuring relative vulnerability had a
            stem “If I am not physically active … ” comparing myself with an average
            person of my age and sex, then I will be at higher risk of … and response
            options such as: “ … my diabetes gets worse”, “… having a serious medical
            condition”.

            <hss>Intention</hss>

            Intention refers to a participant’s intention to increase walking (Schwarzer
            et al., 2003) and was assessed by four items with response options ranging
            from 1 (completely disagree) to 5 (totally agree). Intention was measured by
            items such as “I intend to walk more in the next month” and “I am motivated to
            walk more to improve my health in general”.

            <hss>Action planning</hss>

            Action planning consisted of items assessing the extent to which participants
            had a plan about when, where, and how to increase their walking (Schwarzer et
            al., 2003). Action planning was assessed using four items (Sniehotta, Scholz,
            et al., 2005; Sniehotta, Schwarzer, et al., 2005). All items had response
            options ranging from 1 (completely disagree) to 4 (totally agree). The stem “I
            have made a specific plan about ….” had response options such as: “… when to
            increase my walking in the next month”, “ … where to increase my walking in
            the next month”, “ … what to do if something interferes with my intention to
            increase my walking in the next month”.

            <hss>Action control</hss>

            Action control refers to perceived self-monitoring, awareness of standards and
            effort (Sniehotta, Scholz, et al., 2005; Sniehotta, Schwarzer, et al., 2005)
            to increase walking of participants. Action control was assessed using six
            items and all items had response options ranging from 1 (strongly disagree) to
            4 (strongly agree). The stem “During the last week I ….” had response options
            such as:“… regularly thought about my intention to be regularly physically
            active”, “ … I have consistently checked to see whether I am physically active
            enough”.

            <hss>Social support</hss>

            Social support items assessed support from colleagues, friends and household
            members to increase walking using a modified version of the Molloy social
            support tool (Molloy, Dixon, Hamer, & Sniehotta, 2010). All items (17 items)
            had response options ranging from 1 (strongly disagree) to 7 (strongly agree).
            Social support (friends/colleague) was measured by items such as “I have a
            friend/colleague who thinks that I should increase my walking”, and “I have a
            friend/colleague who encourages me to increase my walking”. Social support
            (household) was measured by items such as “I have somebody to encourage me to
            increase my walking on the regular basis”, and “I have somebody to walk with
            me”.

            <hss>Goal conflict and goal facilitation</hss>

            Goal conflict (5 items) and goal facilitation (3 items) items focus on the
            extent that a participant’s personal goals conflicted with physical activity
            and were adapted from general goal conflict and facilitation scales (Riediger
            & Freund, 2004). All the items had response options ranging from 1 (never, not
            at all, or completely disagree) to 5 (very often, a great deal, or completely
            agree). The items measuring goal conflict consisted of a stem “How often does
            it happen that, because of the pursuit of another personal goal, you do not
            invest ….” and response options such as: “ … as much time in participating in
            regular physical activity as you would like to?”, “ … as much energy in
            participating in regular physical activity as you would like to?” Goal
            facilitation was measured by items such as “To what extent do other things you
            do in everyday life help you to participate in regular physical activity?”,
            and “How often does it happen that you do something in pursuit of a personal
            goal that is simultaneously beneficial for participating in regular physical
            activity?”

<hs>  Data management and analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Data were entered into SPSS version 20 and 10% of all data were double entered and checked
for quality assurance. Few errors (n = 11 or 0.1% of entered fields) were identified and
corrected, with no evidence of systematic errors. The primary outcome measure was the IPAQ
walking criterion (MET minutes/week). A sensitivity analysis was conducted using total MET
minute/week. The extent of missing data varied across variables. The variables with the
greatest and smallest amount of missing data were walking level (13.4%), and diabetes
management method (2.1%). We used multiple imputation (Klebanoff & Cole, 2008) to account
for missing data which addresses missing data issues in the most robust manner possible.
All model testing was conducted on multiple imputed data and results presented as pooled
estimates. Hierarchical multiple regression analyses were conducted to test the sequential
contribution of demographic, motivational, volitional and multiple goal constructs as
predictors of walking.

<hs>  Ethics approval</hs>
  ~~~~~~~~~~~~~~~

Ethics approval for the study was granted by North of Scotland Research Ethics Committee
(NRES) (Ref 10/S0802/4).

<hs>  Response rate</hs>
  ~~~~~~~~~~~~~

Of 1000 people contacted, 35 withdrew at the pre-notification letter stage. Of the 965
questionnaires mailed, 426 were returned (compared to the target sample size of 500). Of
these fifteen were excluded (five received after the agreed deadline (15/07/2012), seven
with excessive (>90%) missing data, three because of participation in the pilot study).
Most questionnaires (373/426; 87.6%) were returned by people who had responded to the pre-
notification letter. No significant difference was found between participating and non-
participating respondents in terms of gender and age suggesting the final sample was
representative. The final evaluable sample comprised 411 respondents.

<hs>  Socio-demographic characteristics of respondents</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The mean age of respondents was 65.5 years (SD 9.7); 57.4% (n = 236) were men. Most were
married (60.6%), did not live alone (63.3%) or were retired (62.3%). A quarter (26%) had
no formal educational qualification. Most participants (92.7%) were either overweight (BMI
25.0–29.9) or obese (BMI ≥ 30.0). The mean average BMI was 34.0 (SD 5.9) and 31.4 (SD 5.1)
for women and men, respectively.

<hs>  Descriptive statistics and bivariate correlations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As shown in Table 1, which presents findings across all 411 respondents, the mean total
physical activity measured as Metabolic Equivalent of Task (METs) was 1732 min/week (Inter
Quartile Range (IQR) 485, 4398; median 200). Based on SIGN and WHO guidelines, which
exclude walking, almost 60% (n = 236) of patients did not adhere to physical activity
recommendations (<600METs); however this proportion was reduced to 28% using the IPAQ
(Metabolic Equivalent of Task (MET) minutes/week) measure which includes walking (Table
2). Men had higher median levels of physical activity than women. According to the IPAQ
categories nearly 36% and 35% of participants reported moderate and vigorous levels of
physical activity during the last week (Table 2), but the median time (hours/week) spent
for both moderate and vigorous physical activity was zero (Table 1). The median duration
of walking was 5.25 h per week. The proportion of total physical activity reported as
walking was 65.6%. As shown in Table 3, which presents findings for the 356 respondents
providing walking data, BMI, action planning, action control and goal facilitation were
significantly associated with walking behaviour, and outcome expectations, social support,
risk perceptions, self-efficacy, action planning, action control, and goal conflict were
significantly associated with walking intention. The Cronbach’s alpha of different
subscales of HAPA questionnaire are presented in Table 3 indicating that most subscales of
the questionnaire had a good internal consistency. The negative outcome expectations scale
was omitted from any analyses due to low observed internal consistency.

<hs>  Predicting walking</hs>
  ~~~~~~~~~~~~~~~~~~

The hierarchical multiple regression was conducted in four steps. First, demographic
factors and predictors of intention from the HAPA were included. Next, motivational
factors from HAPA were added, then volitional, and finally multiple goal constructs. At
each step, we tested whether the added factors contributed to explaining additional
variance in walking beyond factors in the model from the previous steps, and which
specific constructs explained this additional variance. In Step 1 of the hierarchical
multiple regression, walking was regressed against demographic factors (BMI, age, sex) and
HAPA theory-based predictors of intention (outcome expectations, social support and risk
perception). As shown in Table 4, only BMI and age predicted walking, explaining 3.7% of
the variance in walking. In Step 2, HAPA motivational constructs (intention and self-
efficacy) were added, with intention and self-efficacy adding to the prediction (ΔR2 =
0.03). In Step 3, the volitional constructs of action planning and action control were
added, with only the latter adding significantly to the prediction (ΔR2 = 0.01) and
intention and self-efficacy no longer significantly contributing to predicting behaviour.
In Step 4, the multiple goal constructs of goal conflict and goal facilitation were added,
with the latter significantly adding to the prediction of behaviour (ΔR2 = 0.07) whilst
action control no longer significantly predicted behaviour.

<h>DISCUSSION</h>
----------

The study showed that the majority (60%) of Type 2 diabetic patients were non-adherent to
physical activity recommendations as defined by SIGN/WHO. Most of the physical activity
undertaken by people with Type 2 diabetes was walking (65.6%). Action control and goal
facilitation were predictive of walking. Goal facilitation explained a further 7% of the
walking variance. Non-compliance of the majority of respondents with the SIGN
recommendation (SIGN, 2010), for physical activity is consistent with the Scottish Health
Survey (The Scottish Government, 2012) which showed that 61% of the general population
aged 16 and over did not meet physical activity recommendations. Other evidence suggests
that patients with Type 2 diabetes may be even less physically active than the general
population (Morrato et al., 2007). This was also the finding of a study in USA of 23,283
adults, which showed that only 39% of individuals with Type 2 diabetes were physically
active compared with 58% of those without diabetes (Morrato et al., 2007). The median
duration of walking reported in the current study was 5.25 h per week (IQR 1.5, 12). The
proportion of walking as a percentage of total physical activity was 65.6% suggesting that
in some cases walking was the main type of physical activity undertaken by patients. This
finding reflects the behaviour of the general adult population (Monteiro et al., 2003;
Morris & Hardman, 1997); therefore developing and evaluating interventions to increase and
maintain this behaviour are important. Walking is a common, accessible, inexpensive Type
of physical activity. Walking provides diverse health benefits of physical activity with
few adverse effects. There is a large body of evidence about the positive effect of
walking to improve health in people with Type 2 diabetes. This suggests that focusing on
walking as a form of physical activity to improve peoples’ adherence with physical
activity recommendations is important and could be an effective way to improve physical
activity. In terms of the existing literature one study conducted with cardiac
rehabilitation patients, was found that measured action control as a predictor of physical
activity (Sniehotta, Scholz, et al., 2005; Sniehotta, Schwarzer, et al., 2005). That study
reported that each of the three factors of planning, self-efficacy and action control made
unique contributions to translating intention into action (Sniehotta, Scholz, et al.,
2005; Sniehotta, Schwarzer, et al., 2005). A study conducted in students confirmed
associations specified by the HAPA at the intrapersonal level: outcome expectancies and
self-efficacy, but not risk awareness, were positively associated with intentions for
physical exercise. Physical activity was positively associated with intentions, self-
efficacy, action control, but not with action planning (Scholz, Keller, & Perren, 2009).
These findings are in accordance with the results of this current study. Another study
conducted in Type 2 diabetic patients participating in a Diabetes Self-Management
Education (DSME) (Bonner, 2010) showed that self-efficacy was the strongest predictor of
behavioural intention, followed by positive outcome expectancy. The study (Bonner, 2010)
revealed that behavioural intention, but not self-efficacy and action planning could
significantly increase initiation of a minimum level of physical activity. The current
study showed some degree of support for the tenets of the HAPA, whilst demonstrating the
importance of considering multiple goal pursuit in people with Type 2 diabetes. The
majority of respondents did not engage in physical activity at recommended levels. Action
control and goal facilitation were shown to be predictors of physical activity when
considered alongside other HAPA and demographic factors. Findings in relation to the HAPA
with respect to intention (step 2 of the regression) and action control (step 3) were
consistent with previous research (Sniehotta, Scholz, et al., 2005; Sniehotta, Schwarzer,
et al., 2005) and extend these findings by demonstrating the role for multiple goals
constructs on physical activity (in this case, goal facilitation). Conversely we did not
show a predictive role for action planning and in step two, there is an unexpected
negative predictive relationship between self-efficacy and walking behaviour, although
this becomes insignificant when the additional predictors in steps three and four are
added. Both findings are at odds with the HAPA model and most of the literature
investigating these relationships (Sniehotta, Scholz, et al., 2005; Sniehotta, Schwarzer,
et al., 2005). Self-efficacy showed no significant bivariate relationships with walking
which may be due to the fact that the target behaviour was ‘increasing walking by 20%’
which equates to large absolute changes for more active respondents. Moreover, self-
efficacy was significantly correlated with intention, so that the negative beta-
coefficient in the second step of the hierarchical regression analysis may be reflective
of an artefact, a statistical suppressor effect. Action planning showed a weak bivariate
correlation with walking and was significantly correlated with action control so that when
action control was simultaneously controlled for, there was not a unique predictive
relationship between action planning and walking. In the final model, neither of these
variables was significant. Findings regarding multiple goal constructs are also consistent
with earlier research showing that perceived goal facilitation but not perceived goal
conflict were predictive of physical activity (Presseau et al., 2010, 2013; Riediger &
Freund, 2004). There is now growing evidence across a range of studies with diverse
populations that particularly support the role of goal facilitation as a key factor in
physical activity and, with the present study’s findings, walking specifically. Goal
facilitation is an indicator of the extent to which a target behaviour (in this case,
walking) “fits” synergistically alongside the other behaviours and goals that individuals
pursue in daily life. Findings from this study continue to support the role of goal
facilitation and also underscore its potential importance in understanding health
behaviours; indeed, even when controlling for predominant theoretical constructs reported
in the literature, the relationship between goal facilitation and walking robustly
accounted for additional variability in walking. With increasing recognition of the
importance of considering the wider context of multiple goal pursuit when understanding
performance of a given health behaviour, the present study further contributes evidence
suggesting that goal facilitation may be a key indicator in the move towards developing
models that explicitly account for the impact of multiple goal pursuit. There is also
mounting lack of support for the role of goal conflict in understanding physical activity.
There may be a range of reasons for this. For instance, when considering the totality of
an individual’s goal pursuits, individuals may be better able to perceive helpful goal
relationships than conflicting ones. Individuals may not be aware of the extent that their
competing goals interfere with their physical activity. When using diaries to assess
actual time spent in pursuit of goals that conflict with physical activity over time, goal
conflict has been shown to be predictive of objectively assessed physical activity
(Presseau et al., 2013). This suggests that measures of perceived goal conflict may need
to be supplemented with behavioural assessments. This also presents opportunities for
feedback interventions by showing individuals which of their behaviours is most
interfering with their physical activity. In addition, when focusing the goal pursuit
context to a specific time and place rather than all of everyday life, both goal conflict
and goal facilitation have been shown to predict behaviour (Presseau et al., 2011). The
utility of the HAPA to explain and possibly predict adherence with physical activity in
addition to the demonstrated added contribution of considering goal facilitation suggests
clear opportunities for developing and evaluating novel, theory-based interventions for
promoting walking in people with Type 2 diabetes. The present study extends the literature
by demonstrating the role of multiple goal pursuit and goal facilitation in particular in
a population sample of people with Type 2 diabetes. In addition, the findings extend the
theoretical literature by demonstrating that goal facilitation predicts independent
variability in health behaviour over and above all contemporary single-behaviour
cognitions. This is important as it provides further evidence for moving beyond on of
health behaviours in isolation. This study is the first to specifically consider the role
of goal facilitation in relation to walking by people with Type 2 diabetes. The importance
of goal facilitation as a key predictor of walking, points to possible interventions to
increase walking behaviour. Indeed, Darker et al. (Darker et al., 2010) used a variation
of action planning – facilitation planning – in their walking intervention, which was
successful in increasing and maintaining the increased walking behaviour. Planning when,
where and how to perform behaviours may facilitate action. To some extent, these may be
preparatory behaviours, but goal facilitation encompasses the broader spectrum of valued
goals pursued in everyday life and may not necessarily be preparatory in nature, whereas
preparatory behaviours may not have any intrinsic value to the actor. Nevertheless, the
functional similarities between preparatory behaviours and goal facilitation are
noteworthy and future research should consider these two constructs in more detail.

<hs>  Strengths and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

The present study is strengthened by its large sample size, robust development and
inclusion of theoretical factors as determinants of walking. Although the sample of 411
(356 for the main analysis) was slightly short of the target of 500, this did not impact
substantially upon the precision of the estimates achieved: 40% with precision within
±4.7% (95% CI 35.3%–44.7%) of respondents being categorised as adherent with physical
activity recommendations compared with the original estimate of 25% with precision within
±3.8% (95% CI 21.2%–28.8%). The study also had limitations. Firstly, the cross-sectional
study design only allows association, and not causation, to be inferred. While there is no
obvious suggestion of multicollinearity, the modest bivariate correlations between
predictors in the model should be considered in interpreting the relative contribution of
predictors in the model, particularly with respect to factors which were not zero-order
correlations, and were not bivariately associated with walking but which were associated
with walking when included in the multivariate analyses (i.e. age and self-efficacy).
Future research should aim to replicate findings using a prospective design or by
embedding such questionnaires in a theory-based process evaluation alongside a trial
(Sedgwick, 2014). A further limitation is that the study may have overestimated levels of
physical activity in people with Type 2 diabetes. People living in Grampian and Tayside
have slightly better self-reported general health than the total population of Scotland
(72% and 69.6% in Grampian and Tayside, respectively versus 67.9% in Scotland) (The
Scottish Census, 2011). Therefore, their self-reported physical activity, used as the main
outcome in this study, may also be higher than the general national population. A further
cause of over estimation could be that due to the patient population in the current study
i.e. patients with Type 2 diabetic registered with the SDRN may be more engaged with their
disease management compared with patients not registered with the SDRN. Social
desirability bias could also contribute to any over-estimation of self-reported physical
activity. The IPAQ has in fact been shown to overestimate self-reported time spent in
physical activity compared with accelerometer measured activity (Ekelund et al., 2006;
Hallal et al., 2012). The assessment of physical activity in the population (Van Hees,
2012) is challenging. Some tools include any type of walking as a physical activity (e.g.
the IPAQ) (IPAQ, 2002) whereas other scales (e. g. The Rapid Assessment of Physical
Activity [RAPA]) (University of Washington, 2006) do not. The recommended level of
physical activity is at least 150 min of vigorous/moderate combined physical activity, in
both SIGN and WHO guidelines (WHO, 2010). If walking is considered a physical activity,
(SIGN, 2010) 72% of participants were compliant with the guidance, but this reduces to 40%
if walking is not included, as in the SIGN guideline. This demonstrates the variation
which arises when different tools are used. The use of an internationally relevant and
valid tool allows comparisons to be made across studies. Finally, items for some
constructs (risk perceptions, action control, goal conflict, goal facilitation) were
measured in reference to physical activity, whereas others (outcome expectancies, social
support, action planning, intention and self-efficacy) referred specifically to walking.
While no obvious pattern of association seemed to preference one or the other
conceptualization and walking is inherent to physical activity, future research could
ensure greater correspondence of all items with walking.

<h>CONCLUSIONS</h>
-----------

Low physical activity in people with Type 2 diabetes is an important factor in terms of
disease management. The majority of respondents did not engage in physical activity or
walking at recommended levels. When testing motivational, volitional and competing goal
constructs together as predictors of walking, Action Control and Goal Facilitation were
shown to predict walking and could form the basis for developing novel, theory-based
interventions for promoting walking in people with Type 2 diabetes.

<h>COMPETING INTERESTS</h>
-------------------

The authors declare that they have no competing interests.

<h>AUTHOR NOTE</h>
-----------

Masoumeh Namadian (m.namadian@zums.ac.ir) Social Determinants of Health Research Centre,
Zanjan University of Medical Sciences, Iran and Centre of Academic Primary Care,
University of Aberdeen, UK; Margaret C. Watson (m.c.watson@abdn.ac.uk) and Christine M.
Bond (c.m.bond@abdn.ac.uk) Centre of Academic Primary Care, University of Aberdeen, UK;
Justin Presseau (jpresseau@ohri.ca) Centre for Practice-Changing Research, Ottawa Hospital
Research Institute, Ottawa, Canada; Falko F. Sniehotta (falko.sniehotta@newcastle.ac.uk),
Institute of Health and Society, Newcastle University, UK. This article is based on data
reported in the first author’s doctoral dissertation.


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<ART>Moving speeches: Dominance, trustworthiness and competence in body motion
=========================================================================

Authors: Markus Koppensteiner, Pia Stephan, Johannes Paul Michael Jäschke
DOI: 10.1016/j.paid.2016.01.013
Year: 2016  |  Pages: 101-106
ASJC codes: 3200
Keywords: Ethology, Impression formation, Motion cues, Nonverbal communication, Politics, Social cognition

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

People read dominance, trustworthiness and competence into the faces of politicians but do they also perceive such social qualities in other nonverbal cues? We transferred the body movements of politicians giving a speech onto animated stick-figures and presented these stimuli to participants in a rating-experiment. Analyses revealed single body postures of maximal expansiveness as strong predictors of perceived dominance. Also, stick-figures producing expansive movements as well as a great number of movements throughout the encoded sequences were judged high on dominance and low on trustworthiness. In a second step we divided our sample into speakers from the opposition parties and speakers that were part of the government as well as into male and female speakers. Male speakers from the opposition were rated higher on dominance but lower on trustworthiness than speakers from all other groups. In conclusion, people use simple cues to make equally simple social categorizations. Moreover, the party status of male politicians seems to become visible in their body motion.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Nonverbal cues affect impression formation (Ambady, Bernieri, & Richeson, 2000; Borkenau,
Mauer, Riemann, Spinath, & Angleitner, 2004) and decision making in the public arena (Rule
& Ambady, 2011; Zebrowitz & Montepare, 2008). For instance, attributions of dominance,
trustworthiness, competence and other personality traits to specific facial features of
political candidates can be reliable predictors of hypothetical and actual election
outcomes (Antonakis & Dalgas, 2009; Chen, Jing, & Lee, 2014; Little, Roberts, Jones, &
DeBruine, 2012; Olivola & Todorov, 2010; Oosterhof & Todorov, 2008; Poutvaara, Jordahl, &
Berggren, 2009). Apart from facial and other nonverbal cues people also read socially
relevant information from and into body motion. They recognize emotions in arm movements
(Pollick, Paterson, Bruderlin, & Sanford, 2001), in whole body gestures (Atkinson,
Tunstall, & Dittrich, 2007), and in movements displayed during interpersonal dialog
(Clarke, Bradshaw, Field, Hampson, & Rose, 2005). Moreover, they perceive personality
traits in dance movements (Hugill, Fink, Neave, Besson, & Bunse, 2011) and in walking
behaviors (Thoresen, Vuong, & Atkinson, 2012), and health related cues and personality in
the body movements of politicians giving a speech (Koppensteiner, 2013; Koppensteiner &
Grammer, 2010; Kramer, Arend, & Ward, 2010). Humans and animals appear to use expansive
body postures, expressive body movements, and broad gestures to display power and
dominance (Carney, Hall, & LeBeau, 2005; De Waal, 2007; Eisenberg & Reichline, 1939;
Mehrabian, 1972; Tiedens & Fragale, 2003). Also, people adopting open and expansive
postures (i.e., power posing) have an enhanced sense of power (Carney, Cuddy, & Yap, 2010;
Huang, Galinsky, Gruenfeld, & Guillory, 2011; Park, Streamer, Huang, & Galinsky, 2013).
All this implies that there is a link between dominance and expansiveness in body postures
and body movements. Communicating dominance as well as building connections to followers
are vital abilities for leaders and politicians. Skilled self-presenters communicate their
dominance by reassuring followers in noncompetitive contexts while threatening those who
would jeopardize group stability (Stewart, Salter, & Mehu, 2009; Stewart, Waller, &
Schubert, 2009). Consequently, speakers may not only present themselves differently
according to their personality and their rhetorical skills but also according to
situational factors such as their role in parliament. In the present study we selected
brief video clips of politicians and mapped the body movements of the speakers onto
animated stick-figures to control for appearance features. Then we asked people to judge
these stimuli on dominance as well as on two additional basic social categories, namely
trustworthiness and competence (Fiske, Cuddy, & Glick, 2007; Oosterhof & Todorov, 2008).
In line with previous research we examined to what degree expansiveness in body postures
and in body motion is related to judgments of dominance. To track down the relative
contributions of body motion and expansiveness, we also investigated the influence of the
quantity of motion. Analyses of the relationship of perceived trustworthiness and
perceived competence with nonverbal cues were exploratory, because there is no research
upon which to derive clear hypotheses. Our measures were simple because first impressions
of speakers' body movements seem to be guided by simple and salient cues (Koppensteiner,
2013). This study pursued several aims. In accordance with previous research we intended
to show that people's impressions of a speaker's dominance are guided by expansive body
postures and expansive body movements. In addition, we investigated whether the quantity
of body motion also influences ratings of dominance. We also explored whether ratings of
trustworthiness and competence, which have been shown to be important qualities in
judgments of faces, are related to our “nonverbal measures”. Males tend to challenge
someone else's status by dominance contests (Mazur & Booth, 1998). Moreover, male speakers
appear to display motion behaviors that lead to higher ratings of extraversion than the
motion behaviors displayed by female speakers (Koppensteiner & Grammer, 2011) and
perceived extraversion of speakers' motion behaviors is positively related to perceived
dominance (Koppensteiner, Stephan, & Jäschke, 2015). Thus, we expected male speakers to
show more dominance displays than female speakers. Finally, we examined whether speakers
(i.e., their stick-figure animations) from the opposition and speakers from the government
are judged differently on dominance, trustworthiness and competence and whether such
differences show an interaction with gender.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

At locations throughout the University we recruited 60 participants (33 females and 27
males; age M = 24.2 years, SD = 4.1) to take part in our rating experiment (see also
Koppensteiner et al., 2015). Participants received a financial compensation of €5.

<hs>  Stimulus preparation</hs>
  ~~~~~~~~~~~~~~~~~~~~

Using a random number generator we selected 60 speeches from parliamentary sessions
(29.11.2012, 30.11.2012, 14.12.2012) of the German Parliament. Deviations from random
selection were necessary to reach equal numbers of male and female speakers (i.e., 30
different males and females) and nearly equally sized groups representing the parties.
From each of the selected speeches we extracted brief, randomly chosen video segments with
an average length of 15 s. Thirty-two speakers belonged to opposition parties (i.e., SPD,
Bündnis 90/Die Grünen, Die Linke) and 28 speakers belonged to the government (i.e., CDU,
FDP). To encode behavior we used the program SpeechAnalyzer, which runs through a movie
frame by frame. In the first frame of each video clip, so called landmarks were positioned
on the speaker's forehead, the hollow of the throat between the collar bones, ears,
shoulders, elbows, hands, a spot in the middle of the body near the navel, and at the
corners of the lectern (see also Koppensteiner, 2013; Koppensteiner & Grammer, 2010).
Shifts in the positions of these body regions were automatically tracked by software
routines based on optical flow (e.g., landmark of left shoulder in frame one was moved to
position of left shoulder in frame two). As these software routines are prone to error,
landmark positions often had to be corrected doing drag and drop operations with the
computer mouse. This procedure of behavior encoding on the basis of landmark shifts
yielded a time series of two dimensional marker positions that were used to create stick-
figure animations (Fig. 1) representing the speakers' body movements. We only used every
third frame in the encoding process; linear interpolation was used to fill in missing
frames.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants were brought to our laboratory and asked to rate stick-figure animations of
speakers. They received instructions on how to use the rating program and performed the
rating tasks on their own (i.e., no experimenter present) using a computer-controlled
interface. Stick-figure video clips were presented on the left-hand side of the user
interface; rating scales that were named dominant, trustworthy, and competent were
displayed on the right hand side. Participants completed their ratings by dragging a track
bar control to the right pole (i.e. named strongly disagree) or the left pole (i.e., named
strongly agree) of the rating scales using a computer mouse. The scales were divided into
200 subunits, with − 100 being the minimum value and + 100 being the maximum value (i.e.,
similar to a visual analog scale). Time to complete the ratings was unrestricted. Each
participant rated a subset of 20 randomly selected stick-figure animations (i.e., each
participant rated her/his own set of stimuli, which were presented in randomized order).
All video clips were presented without sound.

<hs>  Analysis</hs>
  ~~~~~~~~

Coordinate data obtained during the behavior encoding was used for analyses of body
motion. Previous studies have shown that the horizontal and vertical components of body
motion affect impression formation differently (Koppensteiner, 2013; Koppensteiner &
Grammer, 2010). For this reason we decomposed the speakers' body movements into horizontal
(x) and vertical (y) components by calculating distances between the coordinates of
different landmarks. We determined the magnitude of vertical hand movements: the sum of
lectern(y) – right hand(y) and lectern(y) – left hand(y), and vertical body movements:
throat(y) – lectern(y). In a second step we determined horizontal hand movements:
throat(x) – right hand(x) and left hand(x) – throat(x) and horizontal body movements:
throat(x) – origin(x). This gave four time series of changing landmark distances from
which we extracted the amplitudes between successive local maxima and local minima. The
sum of all vertical amplitudes served as an estimate of the overall vertical distances a
moving body produced (i.e., overall vertical expansiveness in motion) while the sum of all
horizontal amplitudes served as an estimate of the overall horizontal distances a body
produced (i.e., overall horizontal expansiveness in motion). The sum of the number of
local minima and maxima, on the other hand, served as an estimate of the vertical quantity
of motion and as an estimate of the horizontal quantity of motion without including the
influence of motion amplitudes (see Figs. 1 and 2). In addition to this we also used
single positions of the speakers' bodies in our analyses. The maximal horizontal distance
between the speakers' left and right hand served as a measure of maximal horizontal
expansiveness. Similarly, the sum of the maximal vertical distances between the speakers'
hands and the lectern and between the speakers' throats and the lectern served as measures
of vertical expansiveness. In summary, we created three types of measures: (1) a measure
that captures both expansiveness and the quantity of motion, (2) a measure that only
captures the quantity of motion, and (3) a measure that captures expansiveness without
including the quantity of motion. Amplitudes and distance measures were corrected for
variation in body height by dividing them by the maximum vertical distance between the
lectern and the speakers' foreheads (i.e., stick-figure height). Each stimulus was rated
by a range from 18 to 22 participants (M = 20). For the statistical analyses we averaged
these ratings. Motion variables tend to be highly interdependent, which affects the
interpretation of regression coefficients of multiple regressions. For this reason we used
simple bivariate correlations (with bootstrapped confidence intervals) to examine the
relationships between the variables. We also divided the sample of stimuli into four
categories: male and female speakers belonging to the opposition and male and female
speakers belonging to the government. The differences between these groups in trait
ratings and motion measures were assessed by calculating means with bootstrapped
confidence intervals. As we expected interactions between speaker gender and role in
Parliament (opposition or government), we also calculated a series of two-factorial Type
III ANOVAs. All statistical analyses were carried out in the program R (R Core Team,
2013).

<h>RESULTS</h>
-------

Correlations between the indices of body motion and expansiveness (Table 1) revealed a
wide range of interdependencies. For instance, horizontal and vertical measures of motion
were strongly linked. Specifically, speakers that showed a great a deal of expansive
movements along the vertical axis (up and down movements) also showed expansive movements
(e.g., hands moving from the left to the right) along the horizontal axis. A similar
relationship was found between horizontal and vertical quantity of motion. Measures of
static expansiveness (i.e., maximal distance between hands and hands held up high) were
strongly correlated to measures of expansiveness of motion (i.e., amplitudes).
Consequently, speakers who produced expansive body postures also tended to produce
expansive movements and speakers who produced expansive movements also showed a high
quantity of motion. Because our nonverbal measures showed strong interdependencies (Table
1) we also created a composite measure of body motion by adding up vertical and horizontal
amplitudes. Stick-figures rated high on dominance tended to be rated low on
trustworthiness (r(58) = −.57), those rated high on trustworthiness were also rated high
on competence (r(58) = .76), and no relationship (r(58) = −.11) was found between
dominance and competence (see also Koppensteiner et al., 2015). Thus, in part dominance
and trustworthiness were mutually exclusive categories. Indices of body motion,
expansiveness and our composite measure of motion showed profound relationships with
ratings of dominance and trustworthiness. Perceived competence did not yield a meaningful
relationship with any of our measures (Table 2). Stick-figures adopting an expansive body
posture, displaying expansiveness in overall motion behavior and a great deal of body
movements were rated high on dominance. These findings indicate that people not only
ascribe dominance to static cues of expansiveness but also to motion cues. Low to moderate
interrelations between expansiveness of body postures and the quantity of motion – a
motion measure independent of amplitude – further supported such an interpretation (see
Table 1). The negative relationship between trait ratings of dominance and trustworthiness
was also reflected in correlations between motion measures and trustworthiness. There were
negative relationships throughout (Table 2). Overall, this can be condensed into a simple
formula, namely that high ratings of trustworthiness were linked to low activity in body
motion. In the second step we analyzed whether the stick-figures were judged differently
on dominance, trustworthiness, and competence depending on the speakers' gender and their
party status (i.e., opposition or government). ANOVAs yielded significant interactions
between gender and the politicians' role in parliament (i.e., opposition or government)
for perceived dominance and perceived trustworthiness (Table 3). Inspection of the mean
ratings for dominance provided detailed insights into the differences between the four
groups we investigated (Table 4 and Fig. 3). Perceived dominance was highest for males
belonging to the opposition parties. In particular, when compared with the ratings of
males and females belonging to the government, this result was impressive (confidence
intervals show no overlap). Findings for trustworthiness were similar to findings of
dominance. Again, the ratings of males belonging to the opposition stood out (Table 2).
They received the lowest ratings on trustworthiness of all groups. The composite measure
of overall motion provided no significant interaction between gender and party position
(Table 3). Means and their confidence intervals showed that overall motion was highest for
males from the opposition (Table 4). This was in line with this group's ratings on
dominance. However, the differences in trait ratings were not convincingly reflected in
our motion measure. Therefore, people's ratings must be guided by additional nonverbal
cues.

<h>DISCUSSION</h>
----------

To display dominance humans and animals make broad gestures or adopt expansive body
postures (e.g., De Waal, 2007; Mehrabian, 1972). We investigated whether people perceive
such dominance cues in the body motion of politicians giving speeches. For this purpose we
translated short excerpts from different speeches into stick-figure animations and
extracted the “maximum expansiveness” (i.e., expansiveness of a single posture), the
overall “expansiveness of motion” and “the quantity of motion”. All three measures were
strongly interrelated and good predictors of perceived stick-figure dominance. This
indicates that speakers who adopt expansive postures also produce such expansive postures
frequently. Moreover, expansive postures lead to impressions of dominance and perceiving
such expansive postures frequently may even reinforce such impressions. In contrast to
dominance, trustworthiness was associated with low expansiveness in motion and a low
number of movements. Such a negative relationship between dominance and trustworthiness
was also reflected in the trait ratings. Therefore, displays of high dominance have a
negative impact on impressions of trustworthiness. Taking a closer look at the results
revealed that our “nonverbal measures” were not as strongly related to trustworthiness
than to dominance. In other words, people perceived dominance more easily than
trustworthiness in the nonverbal cues we extracted. This is not surprising because
dominance displays are not subtle in general and intended to attract attention. Stick-
figures perceived as trustworthy were also perceived as competent, yet we found no
relationship between our “nonverbal measures” and competence. Despite being one of the
basic social categories in judgments of politicians (Fiske et al., 2007) competence was
not conveyed by the cues we extracted. It is conceivable that competence is associated
with motion patterns our simple measures failed to capture. However, it is also possible
that people, although able to perceive competence in facial cues, are unable to perceive
competence in body motion. First impressions may represent a cognitive adaptation that
helps to decide whether to approach or to avoid someone (Oosterhof & Todorov, 2008). The
results obtained may be interpreted in a similar way and the ratings may be classified as
“positive versus negative”. However, previous studies using stick-figure stimuli show that
the body movements of speakers allow more than such simple categorizations (e.g.,
Koppensteiner et al., 2015; Koppensteiner, 2013). In the present study we only extracted
conspicuous dominance cues, which may have a predominant influence on first impressions,
but more in depth social evaluations may be based on more complex motion cues. Also, it is
not clear whether social categories such as those applied here or the Big Five personality
dimensions sufficiently capture the information people perceive in motion cues (see also
Thoresen et al., 2012). To clarify this follow-up studies are needed. Politicians change
their rhetoric depending on the situation or their role in Parliament (Pancer, Hunsberger,
Pratt, Boisvert, & Roth, 1992; Tetlock, 1981). This study is a first step toward
investigating whether such flexibility in self-presentation also becomes apparent in body
motion. Although the results obtained need to be backed by additional studies, they
support such an assumption regarding male speakers in the opposition. Stick-figures
representing male politicians in the opposition were perceived as more dominant but less
trustworthy than stick-figures representing politicians of the government. However, to
provide more clarity future work needs to elaborate on this and test whether former
opposition members change their nonverbal performance when they become members of the
government. Although a previous study using stick-figure stimuli revealed differences
between male and female speakers for perceived extraversion and emotional stability
(Koppensteiner & Grammer, 2011), in the present study we only found noteworthy gender
differences when including party status. The results obtained suggest that dominance
displays, that negatively affect perceptions of trustworthiness, are predominantly shown
by male speakers expected to control and criticize the work of those who are in power.
Male and female speakers of the government, on the other hand, may intend to communicate
integrity and on the level of body motion this might look similar for both genders.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

Snap judgments are not only guided by the outward appearance and facial expressions but
also by salient and simple motion cues. We show that speakers displaying expansive
movements and a great deal of body activity are rated high on dominance and low on
trustworthiness. In addition, females and male members of the ruling parties appear to
communicate their views in a different way than males from the opposition and such
differences appear to be discernable in body motion. This hints that politicians not only
express their positions with words but also with their bodies.


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<ART>Multidimensional motivation for exercise: A latent profile and transition analysis
================================================================================

Authors: Lydia G. Emm-Collison, Simon J. Sebire, Ruth Salway, Janice L. Thompson, Russell Jago
DOI: 10.1016/j.psychsport.2019.101619
Year: 2020
ASJC codes: 3202
Keywords: Accelerometer, Latent profile, Latent transition, Motivation, Physical activity

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: To: a) identify motivational profiles for exercise, using Self-Determination Theory as a theoretical framework, among a sample of parents of UK primary school children; b) explore the movement between motivational profiles over a five year period; and c) examine differences across these profiles in terms of gender, physical activity and BMI. Design: Data were from the B-Proact1v cohort. Methods: 2555 parents of British primary school children participated across three phases when the child was aged 5–6, 8–9, and 10–11. Parents completed a multidimensional measure of motivation for exercise and wore an ActiGraph GT3X + accelerometer for five days in each phase. Latent profile and transition analyses were conducted using a three-step approach in MPlus. Results: Six profiles were identified, comprising different combinations of motivation types. Between each timepoint, moving between profiles was more likely than remaining in the same one. People with a more autonomous profile at a previous timepoint were unlikely to move to more controlled or amotivated profiles. At all three timepoints, more autonomous profiles were associated with higher levels of MVPA and lower BMI. Conclusions: The results show that people's motivation for exercise can be described in coherent and consistent profiles which are made up of multiple and simultaneous types of motivation. More autonomous motivation profiles were more enduring over time, indicating that promoting more autonomous motivational profiles may be central to facilitating longer-term physical activity engagement.

--------------------------------------------------------------------------------


<h>AIMS</h>
----

The purpose of the present exploratory study was to adopt a person-centred approach to: a)
identify motivational profiles for exercise amongst adults, using Self-Determination
Theory (SDT) as a theoretical framework; b) explore the stability of and movement between
motivational profiles over a five-year period; and c) examine differences across these
profiles in terms of gender, accelerometer-estimated physical activity and BMI.

<hs>  Design and participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

This study uses data from the longitudinal B-Proact1v cohort study. A more detailed
outline of the study can be found elsewhere (Jago et al., 2017, 2019; Jago, Sebire, et
al., 2014; Jago, Thompson, et al., 2014). In brief, B-Proact1v aimed to examine physical
activity and sedentary behaviour of primary school children and their parents. Data were
collected on three occasions, between January 2012 and July 2013 when the child was in
Year 1 (ages 5–6), between March 2015 and July 2016 when the same child was in Year 4
(ages 8–9), and between March 2017 and May 2018 when the same child was in Year 6 (ages
10–11). A total of 57 schools participated in the first data collection, and the same
schools were invited to take part in subsequent phases, with 47 participating in the
second phase and 50 in the third phase. Across the three timepoints, data were collected
from 2555 parents/caregivers from 2132 families: 1195 were involved at time 1, 1140 at
time 2, and 1233 at time 3. Prior to data collection, the study received ethical approval
from the School for Policy Studies Research Ethics Committee at the University of Bristol
and written consent was obtained from all participants at each phase of data collection.

        <hss>Exercise motivation</hss>

        Motivation to exercise was measured via the Behavioural Regulation in Exercise
        Questionnaire-2 (BREQ-2; Markland & Tobin, 2004). Grounded in SDT, the 19-item
        measure assesses five forms of behavioural regulation; intrinsic (4 items e.g. ‘I
        exercise because it’s fun’), identified (4 items e.g. ‘It’s important to me to
        exercise regularly’), introjected (3 items e.g. ‘I feel like a failure when I
        haven’t exercise in a while’), external (4 items e.g. ‘I exercise because other
        people say I should’), and amotivation (4 items e.g. ‘I don’t see the point in
        exercising’). Participants recorded their responses on a 5-point Likert scale
        ranging from 0 (not true for me) to 4 (very true for me). The subscales
        demonstrated internal consistency at each time point (Table 1).

        <hss>Moderate-to-vigorous physical activity</hss>

        Parents wore an ActiGraph wGT3X-BT accelerometer on their waist for five days,
        including two weekend days. Accelerometer data were processed using Kinesoft
        software (v3.3.75; Kinesoft, Saskatchewan, Canada) using 60-s epochs. A valid day
        was defined as at least 500 min of data after the exclusion of periods of non-wear
        time of over 60 min, whilst allowing up to 2 min of interruptions. Analysis was
        restricted to those parents who provided at least three days of valid data, to
        ensure reasonable estimates of typical daily activity whilst maximising sample
        size (Aadland & Ylvisaker, 2015; Tudor-Locke et al., 2005). The average number of
        MVPA minutes per day were used in the analysis, derived for each participant using
        population-specific cut points for adults (≥2020 counts per minute; Troiano et
        al., 2008).

        <hss>Participant characteristics</hss>

        Parents reported their date of birth and gender. BMI was calculated from self-
        reported height and weight as weight (kg)/height (m2).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

First, confirmatory factor analysis using maximum likelihood estimation was conducted to
obtain weighted factor-scores for each subscale of the BREQ-2 measure (intrinsic
motivation, identified regulation, introjected regulation, extrinsic regulation, and
amotivation). Doing so provides subscale estimates that consider the contribution of each
item to the latent variable they are measuring. Model fit was assessed using multiple
indices as follows; the Chi-square index, comparative fit index (CFI), standardised root
mean square residual (SRMR), and root mean square of approximation (RMSEA). The thresholds
for good fit used were >0.90 for the CFI, <0.08 for the SRMR, and <0.06 for the RMSEA (Hu
& Bentler, 1999). Longitudinal invariance of the measurement model was sequentially tested
via a series of increasingly constrained models. Invariance was indicated by a change in
CFI of ≤0.01 (Cheung & Rensvold, 2002). The generated factor scores were used as input
variables in subsequent analyses, in line with guidance (DiStefano, Zhu, & Mindrila,
2009). We used latent profile analysis (LPA) as the primary data analysis approach to
explore and identify motivational profiles for exercise. In LPA, each participant is
assumed to belong to one of a set of underlying profiles, and the analysis estimates the
probability of membership to each profile for each person. As an extension of LPA, latent
transition analysis was used to additionally estimate the probability of moving between
profiles at different time points. We used a three-step approach (Asparouhov & Muthen,
2014; Nylund-Gibson, Grimm, Quirk, & Furlong, 2014) to conduct the LPA and transition
analyses in MPlus (version 7, Muthen & Muthen). In a fourth step we explored the
associations of profile membership with gender, BMI and MVPA. The syntax for all main
analyses is available as supplementary material.

        Step 1 and 2- identification of latent profiles and obtaining classification errors

        Through step 1 we identified the motivational profiles for each timepoint. A
        sequence of models, with an increasing number of profiles from 2 to 7, were
        examined to ascertain whether more complex (i.e. more profiles) or parsimonious
        (i.e. fewer profiles) models provided the best description of the data. The models
        were estimated using data from all three timepoints, with each time point assumed
        to be independent of the others. Based on recommendations (Nylund, Asparoutiov, &
        Muthen, 2007), and in line with previous papers (Jago et al., 2018; Lindwall et
        al., 2017), several criteria were used to determine the most appropriate model.
        Statistically, the log-likelihood, the Bayesian information criterion (BIC) and
        the sample-adjusted Bayesian information criterion (SSA-BIC) were considered, with
        lower values indicating better model fit (Henson, Reise, & Kim, 2007; Yang, 2006).
        Relative entropy and the class membership probabilities were used to identify
        potentially problematic models in which some classes have small proportions of
        membership. We also considered the theoretical alignment and interpretation of the
        final profiles in terms of different levels of behavioural regulation
        (Vansteenkiste & Mouratidis, 2016) and, with this in mind, sought to choose the
        most meaningful model with the smallest number of profiles. In order to explore
        assumptions about variance, we compared the model with no constraints, correlated
        indicators and equal variances across timepoints (Morin, Meyer, Creusier, &
        Bietry, 2016). In the second step, to include the measurement error in assignment
        of individuals to profile, we conducted latent profile analysis separately for
        each set of latent profile indicators, fixing the measurement parameters so that
        the profiles were the same as in step 1. This allowed us to obtain profile
        variables and classification errors. This step was repeated for all three
        timepoints.

        <hss>Step 3- Transition Between Profiles Across timepoints</hss>

        In the third step, we estimated the movement between motivation profiles across
        the three timepoints, keeping the latent profiles at each timepoint fixed and
        accounting for measurement error in profile assignment.

        <hss>Step 4- associations of profile membership with gender, BMI and MVPA</hss>

        We examined the associations between profile membership and gender, BMI, and
        accelerometer-estimated MVPA, via the Wald test using the BCH method, which
        includes classification error and is robust to violations of assumptions (Yang,
        2006). All analyses accounted for clustering of parents at the family and school
        levels. Between timepoints, attrition was largely attributed to school drop-out,
        accounting for the drop out of 244 parents at time 2 and 167 parents at time 3, or
        to families moving to schools not involved in the project, accounting for a total
        of 253 parents. Therefore, as most missing data was explained by school-level
        rather than individual-level factors, all model parameters were calculated using
        full information maximum likelihood, which uses available information from
        participants at all time points and handles missing data within the analysis
        model, under the assumption that data are missing at random. Models were estimated
        using multiple start values (500 starts and 100 sets) to check convergence.

<hs>  Preliminary analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

1023 participants provided valid accelerometer measurements at time 1 (86% of those in the
study at time 1), 925 at time 2 (81% of those in the study at time 2), and 891 at time 3
(72% of those in the study at time 3). Table 1 shows descriptive statistics and
proportions of missing values for questionnaire measures in these participants.
Correlations between variables are presented in supplementary material (Table S1). At each
timepoint, most participants were female (72–76%) and mean BMI was between 25 and 26
kg/m2. At time 1, the mean age was 37.8 years increasing to 41.3 at time 2 and 43.0 at
time 3. The average daily minutes of MVPA increased across timepoints, from 49.5 min per
day at time 1 to 50.4 min per day at time 2 and 51.86 min per day at time 3. At all three
timepoints, the sample had similar motivational distributions, with low levels of
amotivation and high levels of both identified regulation and intrinsic motivation.
Factors scores from BREQ-2 were derived via CFA.1 The model showed acceptable fit to the
data at time 1 (χ2 = 574.38, df = 142, p < .0005; CFI = 0.93, RMSEA = 0.05 (90% CI = 0.05,
0.06), SRMR = 0.05), time 2 (χ2 = 496.66, df = 142, p < .0005; CFI = 0.95, RMSEA = 0.05
(90% CI = 0.05, 0.06), SRMR = 0.05), and time 3 (χ2 = 418.44, df = 142, p < .0005; CFI =
0.96, RMSEA = 0.04 (90% CI = 0.04, 0.05), SRMR = 0.04). Factor determinacy scores ranged
from 0.86 to 0.97 and were deemed to provide a good estimate of the true factor score
(Table S2). The results of the invariance testing provided evidence for the equivalence of
the measurement model across timepoints (Table S3). Prior to running the main analyses,
behavioural regulation variables were checked for univariate and multivariate outliers,
and no meaningful outliers were detected (Tabachnick & Fidell, 2013).

        Step 1 and 2- identification of latent profiles and obtaining classification errors

        Table 2 shows the indicators of model fit for latent profile models containing 2–7
        profiles. The log-likelihood decreased as the number of profiles increased and the
        6-profile model had the lowest BIC indicating a better fit than the models
        containing fewer profiles. Whilst the 7-profile solution had a lower SSA-BIC, at
        each timepoint at least one profile had a very low probability of membership
        (<2%). The 6-profile solution had the next lowest SAA-BIC and all profiles had
        reasonable membership probabilities (over 4%). Compared to the 7-profile solution,
        the 6-profiles were more meaningful, with combinations of different types of
        behavioural regulation representing logical and theoretically-appropriate
        profiles. Additionally, we ran the model with alternative specifications (1000
        starts and 200 sets) and the log-likelihood was replicated. We therefore chose to
        proceed with 6 profiles as the most appropriate model, based on a combination of
        log-likelihood, BIC, SSA-BIC and model interpretability. With regards to
        measurement invariance (Morin et al., 2016), models with different constraints
        produced similar results (Tables S5 and S6), and so, for parsimony and given that
        similar patterns of motivation exist across populations and contexts (Milyavskaya
        & Koestner, 2011), we proceeded with the model that assumed that the variances for
        each motivation variable differed between profiles but were equal across
        timepoints. Details of the six profiles are reported in Table 3, the profiles are
        represented graphically in Figure 1, and the probability of membership to each
        profile is presented in Figure 2. To ensure that interpretation is theoretically
        meaningful and appropriate, we have re-ordered the profiles to match the
        motivational continuum proposed in SDT (i.e. from the least to the most self-
        determined). The six profiles were labelled as: Strongly amotivated- Primarily
        amotivation with some external regulation Amotivated- Moderate levels of
        amotivation with low levels of all other types of regulation Controlled and
        amotivated- High levels of both introjected and external regulation accompanied by
        high levels of amotivation Low in motivation-low levels of all types of
        behavioural regulation Autonomously motivated and introjected- Predominantly
        introjected regulation alongside some intrinsic and identified regulation
        Autonomously motivated- Primarily intrinsic motivation accompanied with identified
        regulation. At all three timepoints, a greater proportion of participants were
        likely to be assigned to Profile 3 (low in motivation) or Profile 6 (autonomously
        motivated). Participants were consistently least likely to belong to Profile 1
        (strongly amotivated; see Figure 2).

        <hss>Comparison of profiles at time 1, 2 and 3</hss>

        Figure 2 illustrates the probabilities of profile membership at each timepoint.
        Proportions of participants in each profile were similar over time, with Profile 6
        (autonomously motivated) and 4 (low in motivation) being the largest. At each time
        point, Profile 1 (strongly amotivated) had the lowest membership. The proportion
        of participants in Profile 5 (autonomously motivated with introjected) increased
        across timepoints, particularly across time 2 and 3.

        <hss>Step 3- Transition Between Profiles Across timepoints</hss>

        The likely patterns of movement between profiles across the three timepoints are
        shown in Figure 3. Between time 1 and 2, a large proportion of participants were
        likely to remain in the same profile (47%). Participants who transitioned between
        profiles (53%) were likely to move to more motivationally-positive profiles, with
        participants having the highest probability of moving to profiles that were more
        autonomous. The exception to this was those in Profile 4 (low in motivation) being
        equally likely to move to Profiles 5 and 6 (both characterised by strongly
        autonomous regulations) or Profile 3 (controlled and amotivation). If those in
        Profile 6 (autonomously motivated) at time 1 were to move (19%) they were most
        likely to move to Profile 4 (low in motivation). Between time 2 and 3, a similar
        proportion of participants were likely to remain in the same profile (45%). The
        probability of movement between profiles across time 2 and 3 was more varied, with
        a greater likelihood of moving to a wider range of profiles. In line with the
        stability found across time 1 and 2, those in Profiles 5 and 6 (both with high
        levels of autonomous motivation) and Profile 1 (highly amotivated) at time 2 were
        most likely to remain in the same profile at time 3. Those participants who were
        likely to move from Profiles 5 and 6 had the highest probability of moving to
        Profile 4 (low in motivation). Those who moved from profile 1 (high amotivation)
        were most likely to move to Profile 2 (amotivated), with very few moving to more
        self-determined profiles. For Profiles 3 (controlled and amotivated) and 4 (low in
        motivation) movement was more diverse, with a relatively balanced probability of
        moving to profiles characterised by more autonomous motivation or those
        characterised by more amotivation.

        <hss>Step 4- associations of profile membership with gender, BMI and MVPA</hss>

        Table 4 shows the associations of profile membership with co-variates at each
        timepoint. Across all timepoints, the proportion of female membership in a profile
        ranged from 66% to 87%. There were no consistent patterns in profile membership
        across each timepoint in terms of gender, but at both time 1 and time 2, Profiles
        1 and 2 (strongly amotivated and amotivated respectively) had the highest
        proportions of female participants. At time 3, Profile 3 (controlled and
        amotivated) had the highest proportion of female participants. BMI ranged from 24
        to 28 across profiles and timepoints. Those in Profile 6 (autonomously motivated)
        had the lowest mean BMI at each timepoint and, generally, those in Profiles 1 and
        3 (strongly amotivated and controlled and amotivated) had the highest BMI. There
        was less consistency in the association between profile and MVPA across the three
        timepoints. However, at each timepoint, there was a 15–17 min variation in MVPA
        across profiles. Profile 6 (autonomously motivated) was consistently associated
        with higher MVPA, and Profile 1 (Strongly amotivated) consistently associated with
        the lowest MVPA. At each timepoint, participants in Profile 5 (autonomously
        motivated and introjected) engaged in less MVPA than participants in Profile 6.
        For all timepoints, profiles with higher MVPA also had a lower BMI indicating an
        association between these variables.

<h>DISCUSSION</h>
----------

The evidence presented in this paper indicates that people have multiple simultaneous
motivations for engaging in physical activity, providing further support for the complex
multi-dimensional nature of physical activity behaviour. We identified six distinct
motivational profiles that represented different combinations of motivation types spread
across the continuum of motivation proposed within SDT. Further, whilst exploratory, this
paper provides the first evidence for the movement of people between profiles over time,
and the findings suggest that motivation is dynamic, with most participants moving between
profiles across timepoints. Profiles consisting of strong endorsement of more autonomous
forms of motivation were the most stable. The six profiles identified were qualitatively
different and distinct. Two profiles were characterised predominantly by a lack of
motivation to exercise (amotivation), with participants in Profiles 1 and 2 having high
and moderate levels of amotivation respectively. Profile 3 (controlled and amotivated)
consisted of high levels of external regulation alongside amotivation and introjected
regulation, indicating that a lack of interest in exercise, pressure from others and guilt
and shame about not engaging in exercise do occur simultaneously. Participants in Profiles
5 and 6 reported moderate to high levels of both intrinsic and identified regulation,
characterised by enjoyment and personal value of exercise, but Profile 5 had additional
high levels of introjection. The structure of the profiles followed a logical progression
along the theoretical motivation continuum, with combinations of closely-related
regulation types indicating that similar types of motivation are more strongly correlated
than disparate regulation types (Ryan & Deci, 2000). However, one profile did not align
with the theoretical propositions within SDT, and that is Profile 4 (low in motivation),
characterised by no distinct regulation type. A similar profile has been seen in previous
papers (Lindwall et al., 2017) despite the theoretical expectation that low levels of both
controlled and autonomous regulation types would be complimented with high levels of
amotivation. This profile is therefore difficult to explain, and may be the result of
response category artefact, where this profile comprises individuals who provided mid-
range responses on the Likert scale (Nadler, Weston, & Voyles, 2015). Alternatively, given
that the BREQ-2 questions refer specifically to exercise, this profile may represent a
group who did not find the questions relevant due to not engaging in exercise (known as
‘exercise aschematic’; Kendzierski, 1990). In this sample, this profile represents a
substantial group of participants (up to 30%) and so qualitative interviews with
individuals likely to be classified to this profile could help to provide clarity on the
source of this profile. Several of the theoretically-meaningful profiles identified in
this paper align with those found in previous profile analyses (Bechter et al., 2018;
Lindwall et al., 2017). Specifically, Profile 6 (autonomously motivated), Profile 5
(autonomously motivated and introjection), Profile 1 (strongly amotivated), and Profile 4
(low in motivation) replicate profiles previously identified in both active and non-active
adult populations (Lindwall et al., 2017). There have also been similar profiles
identified in research with young people (Bechter et al., 2018). Collectively, this
provides further confirmation of the validity of the profiles and indicates that similar
combinations of behavioural regulations are observed across different samples, countries,
and age-groups, providing further support for the universal nature of motivation as
conceptualised in SDT. The patterns of MVPA for each profile provide support for the
construct validity of the profiles and the continuum of motivation proposed within SDT
(Ryan & Deci, 2017). At all three timepoints, individuals most likely to be in Profile 6
(autonomously motivated) engaged in more MVPA than those in any other profile, with those
in Profile 1 (strongly amotivated) consistently engaging in the least. Further, the
difference in MVPA between the motivation profiles provides further support for person-
centred analysis as a method to provide additional insight into the role of each
regulation type and the way in which they may combine to influence behaviour. In
particular, the profiles identified through this analysis indicate that introjection may
not occur in high levels in isolation, but rather in two qualitatively different profiles,
combined either with external regulation (as in Profile 3) or with identified and
intrinsic regulation (as in Profile 5). Most of the SDT literature has found little
association between introjected regulation and physical activity (Duncan et al., 2010;
Standage et al., 2008), but the different combinations of behavioural regulation may mean
that traditional analysis methods have masked the differential influence that introjected
regulation can have, depending on which other behavioural regulations it occurs alongside.
Further, a similar profile characterised by high self-determined and introjected
regulation was found in previous studies associating motivation profiles with self-
reported exercise behaviour (Lindwall et al., 2017), but this evidence indicated that
introjected regulation did not have a detrimental influence on physical activity when
found in combination with autonomous motivation. In contrast to this, our findings suggest
that the presence of introjected regulation alongside autonomous motivation is associated
with lower levels of MVPA compared to when autonomous motivation is experienced alone.
Collectively, the evidence suggests that the addition of introjected regulation to an
otherwise autonomously motivated person will, at best, have no impact or, at worst,
undermine behaviour. Further work is needed to clarify the role of introjected regulation
in determining physical activity behaviour. The data presented here show that the
autonomously motivated profile was associated with a lower BMI at each timepoint. This may
be linked to the association between more autonomous motivation and higher levels of MVPA
but may also represent a wider association between autonomous motivation for exercise and
other weight control behaviours such as diet, sometimes referred to as ‘motivational
spill-over’ (Mata et al., 2009). Additionally, at all three timepoints, participants in
Profile 1 (strongly amotivated) had a high average BMI. This is consistent with previous
research with adolescents and adults showing that individuals with a higher BMI are more
likely to report high levels of amotivation and individuals who are have a healthy BMI are
more likely to report intrinsic regulation for exercise (Ersoz, Altiparmak, & Asci, 2016;
Hwang & Kim, 2013). The data therefore highlight a need for further examination of the
associations between motivation, physical activity and body weight. In the current sample,
across all timepoints individuals were more likely to move between profiles than to remain
in the same one, indicating that motivation for exercise is relatively dynamic. More
autonomous profiles were the most stable across timepoints and participants likely to
belong to profiles characterised by strong controlled motivation or amotivation were most
likely to move to other profiles. This movement was most commonly to more autonomous
profiles, which is consistent with the principle of SDT that humans have an innate desire
to seek out situations and environments that are psychologically fulfilling and, over time
and given satisfaction of autonomy, competence and relatedness needs, will become more
self-determined in their motivation (Deci & Ryan, 2000). The findings also suggest that
individuals with low levels of motivation may be motivationally vulnerable, in that over
time they have a similar probability of moving to more autonomous or more amotivated
profiles. This presents a potentially important opportunity to intervene to attempt to
inspire people towards more stable autonomous forms of motivation. From a public health
perspective, these findings suggest that strategies to promote greater physical activity
engagement should seek to foster more stable autonomous motivation by developing physical
activity environments that support, rather than thwart, the basic psychology needs of
autonomy, competence and relatedness (Ryan & Deci, 2017). The stability of the profiles
identified in this paper indicate that doing so could have longer-term benefits for
physical activity behaviour. Environments that provide choice about when and how to be
active, opportunities for success, skill building, and an optimal level of challenge, a
personally-relevant rationale for being active, and the opportunity to develop strong
connections with others have been shown to promote greater physical activity engagement in
the long-term (Samdal et al., 2017). There are several opportunities for future research
with a clear need for more person-centred analyses of exercise motivation. As this is the
first exploration of the transition between profiles, further research is needed to
identify whether the stability of and movement between profiles is consistent across
samples. Additionally, further work is needed to ascertain the reasons why individuals may
move between motivational profiles and so the longitudinal assessment of wider theoretical
constructs, such as need satisfaction and well-being, is needed. Qualitative work allow
the origins of the low motivation profile to be explored, specifically focusing on whether
this profile represents a genuine group of individuals, is the result of the measure used,
or if it is an amalgamation of individuals with different motivational profiles.

<hs>  Strengths and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

The exploratory person-centred analysis, longitudinal data and objective estimates of
physical activity are particular strengths of this study, allowing the investigation of
the interplay between different types of motivation and associations with physical
activity, as well as exploring the stability of motivation over time. However, it is
important to highlight the limitations of this work. First, the sample was largely female
and therefore the profiles may be more representative of those found amongst women rather
than men. Additionally, the sample were all parents of primary-school aged children and
were mostly mothers, therefore may not represent the wider adult population. However,
given that previous studies have found no gender differences in behavioural regulations
(Guerin et al., 2012), and given the universality assumption of SDT, we would not
anticipate major differences in the profiles we identified in a more balanced sample.
There may, however, be differences in the proportions of parents belonging to particular
profiles when compared to the wider population (McIntyre & Rhodes, 2009; Solomon-Moore et
al., 2016). Additionally, our sample were high in autonomous forms of motivation, low in
amotivation and generally active, which limits the generalisability of the profiles to
groups with lower autonomous motivation and activity levels. The nature of the study in
which this analysis was nested is likely to have influenced this sample, attracting
parents who enjoy and value being active themselves, and so future work should aim to
recruit a more representative and varied sample. Further, whilst we assumed that data were
missing at random, it is possible that parents who provided full data may have higher
quality motivation than those with missing data. It is also to be noted that BMI was based
on self-reported indicators and therefore may not be accurate. The consistent associations
between BMI and motivation profiles across the three timepoints provide strong support for
this relationship, but future research should adopt objective measurements of height and
weight to provide additional clarity. Additionally, whilst we did not have sufficiently
powered sample to do so, future work should seek to explore the associations between
profile transition and MVPA and BMI and additional covariates, such as need satisfaction
and need frustration.

<h>CONCLUSION</h>
----------

This paper provides evidence for the experience of multiple simultaneous reasons for
engaging in exercise and that more autonomous motivation profiles are associated with
higher levels of accelerometer assessed MVPA and lower BMI. The latent transition analysis
provides the first evidence that profiles characterised by autonomous forms of motivation
are more stable over time than less self-determined profiles. This indicates that once
individuals establish and personal value of enjoyment of exercise, this persists over
time, and so promoting more autonomous motivational profiles may be central to
facilitating long-term physical activity engagement.


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<ART>Musical hallucinations, musical imagery, and earworms: A new phenomenological survey
================================================================================

Authors: Peter Moseley, Ben Alderson-Day, Sukhbinder Kumar, Charles Fernyhough
DOI: 10.1016/j.concog.2018.07.009
Year: 2018  |  Pages: 83-94
ASJC codes: 3204, 3205
Keywords: Auditory hallucinations, Earworms, Mental imagery, Musical hallucinations, Phenomenology

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Musical hallucinations (MH) account for a significant proportion of auditory hallucinations, but there is a relative lack of research into their phenomenology. In contrast, much research has focused on other forms of internally generated musical experience, such as earworms (involuntary and repetitive inner music), showing that they can vary in perceived control, repetitiveness, and in their effect on mood. We conducted a large online survey (N = 270), including 44 participants with MH, asking participants to rate imagery, earworms, or MH on several variables. MH were reported as occurring less frequently, with less controllability, less lyrical content, and lower familiarity, than other forms of inner music. MH were also less likely to be reported by participants with higher levels of musical expertise. The findings are outlined in relation to other forms of hallucinatory experience and inner music, and their implications for psychological models of hallucinations discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Auditory hallucinations (AH) are defined as the conscious experience of sounds that occur
in the absence of any actual sensory input. Although the most frequently reported form of
AH are auditory verbal hallucinations (AVH), phenomenological surveys have also shown that
a substantial minority of people also report musical hallucinations (MH): that is, the
perception of music when none is playing. For example, one survey of 100 people with
psychosis and AVH found that 36% also described the occurrence of MH (Nayani & David,
1996). The most frequent reports were of hearing choral music, with orchestral music and
pop music also evidenced, although specific frequencies were not provided. More recently,
McCarthy-Jones et al. (2012) analyzed data from a semi-structured interview with 199
psychotic patients who reported AVH, finding that a smaller proportion (compared to Nayani
and David) of approximately 15% also experienced MH. The two largest phenomenological
surveys of AVH, then, suggest that MH occur in a substantial minority of people who hear
voices; however, since both primarily focus on AVH, few details of MH are described beyond
prevalence. Whilst questionnaire measures used to assess proneness to hallucinations
(e.g., Launay-Slade Hallucination Scale; Morrison, Wells, & Nothard, 2000) in the general
population do include items relating to non-verbal hallucinations, responses to individual
items are rarely reported; thus, we know little about either the prevalence or
phenomenology of MH in clinical or non-clinical samples. Indeed, non-verbal hallucinations
have been somewhat neglected in the psychological literature, with only a small number of
studies investigating risk factors and basic phenomenological features of MH. Surveys
focusing exclusively on MH have suggested that they may occur in around 16% of individuals
with a diagnosis of schizophrenia (Saba & Keshavan, 1997), and as many as 41% of
individuals with obsessive compulsive disorder (Hermesh et al., 2004). Other risk factors
include hearing impairments, old age, and social isolation, although these may not be
independent factors (Evers & Ellger, 2004). Few surveys have specifically investigated the
phenomenology of MH, further than reporting the most frequent styles of music. Saba and
Keshavan did report on several details of MH in a small sample of individuals with a
diagnosis of schizophrenia, showing that the majority included both instrumental and
lyrical elements, which tended to be familiar to the individual. Patients tended to
appraise the MH fairly positively, with the most frequent description of the experience
being ‘soothing’ (62%). Many experiences of MH were described as perceived as emanating
from the external environment, and approximately half were described as outside of
volitional control, which Saba and Keshavan argue should be considered a key feature of
MH. Whilst this study provided important information on the experience of MH in
schizophrenia, the sample size (16 participants reporting MH) was low, and the questions
on phenomenology relatively limited. Golden and Josephs (2015) recently reviewed medical
records of individuals, including 393 cases of MH, grouping the data into five categories:
MH associated with neurological disorder, psychiatric disorder, structural brain damage,
drug toxicity, and those not otherwise classifiable. The study mainly reports on brain
regions associated with MH, but does note that many individuals with psychiatric disorders
found that the experiences were ‘mood-congruent’ (e.g., sad music when they were feeling
depressed). Indeed, within psychiatric patients reporting MH, depression seems to be the
most common diagnosis (69%), along with hearing loss or tinnitus (Golden & Josephs, 2015;
Rocha et al., 2015; Teunisse & Olde-Rikkert, 2012). A case series presented by Warner and
Aziz (2005) of patients referred to old-age psychiatric services, though, only found a
rate of hearing loss of 33% in patients with MH – perhaps surprisingly low given a mean
age of 78 years. They also note that many patients were not distressed by the MH, and so
speculate that the prevalence of such phenomena may be higher than previously thought if
individuals do not seek medical attention. Due to the nature of these studies, however, no
participants from non-clinical populations were included. Other studies have also used
stringent inclusion criteria: for example, Evers and Ellger, in a review of the etiology
of MH, deliberately excluded musical ‘pseudohallucinations’ (those experienced as internal
to the individual). The distinction between ‘true’ hallucinations and pseudohallucinations
is no longer thought to be clinically significant (Copolov, Trauer, & Mackinnon, 2004),
and research into AVHs typically includes both internally and externally located
perceptions (Nayani & David, 1996). It is unclear to what extent MH are experienced as
internal or external, but it is possible that previous research has omitted a significant
number of cases by using overly strict inclusion criteria. Furthermore, it is unclear to
what extent the attributes assessed in the small amount of previous research could also be
applied to other forms of ‘inner music’1 (Fernyhough, 2016, p. 238). Musical imagery, for
example, is the generation of music in one’s own head, not necessarily instigated by any
external percept. It is frequently reported by many individuals in the general population
(Bailes, 2007; Williamson et al., 2012), and often used by musicians to rehearse or aid
reproduction of music, in the form of notational audiation (Brodsky, Henik, Rubinstein, &
Zorman, 2003). Musical imagery can also occur involuntarily (INMI) with little or no
volitional control. One form of INMI, ‘earworms’ (also referred to as ‘sticky tunes’ or
‘stuck songs’), are typically defined by their repetitiveness and persistence (although
there is some debate in the literature regarding how to precisely define the experience –
see below). Previous research has indicated that the frequency of earworms is affected by
exposure to, and rehearsal of, music (Liikkanen, 2012), and as such is elevated in
musically trained individuals (Beaty et al., 2013; Floridou, Williamson, Stewart, &
Müllensiefen, 2015), with one experience sampling study in musicians finding musical
imagery occurring in as many as 32% of randomly sampled episodes, with 58% of these
samples noted as being due to having recently heard or rehearsed music (2007; Bailes,
2006). Earworms tend not to be associated with negative emotions, unless the reported
duration is particularly lengthy (presumably due to unwanted persistence) (Floridou et
al., 2015). To our knowledge, no research has directly compared self-reported experiences
of musical imagery and earworms to MH, and, in fact, the boundary between earworms and MH
is somewhat unclear in much of the literature. For example, Hemming (cited in Williams,
2015) defines MH as INMI that reaches a pathological level (presumably reflected in
distress experienced by the individual), implying that MH are simply a more extreme,
persistent, or distressing version of earworms. In support of this, the aforementioned
study by Saba and Keshavan (1997) distinguished MH from musical imagery purely in terms of
volitional control. In contrast, Williams argues that whilst both MH and earworms are
involuntary, only MH are experienced as located in the external environment. However, as
discussed above, other forms of auditory hallucination, for example AVH, are often
experienced as internally located (Daalman et al., 2011; Nayani & David, 1996), yet are
typically still classified as hallucinatory experiences. An open question, then, is the
extent to which earworms and MH share phenomenological attributes (e.g., control,
perceived location), and whether MH can be distinguished on other aspects of musical
experience (e.g., type of music, frequency, duration, familiarity, level of acoustic
detail). Research into musical imagery and earworms has also investigated their effect on
mood and behavior, but again, these have not been directly investigated in comparison to
MH. For example, Williamson, Liikkanen, Jakubowski, and Stewart (2014) showed that 74.6%
of individuals reported humming or singing along in response to earworms, whilst only
10.9% reported attempting to suppress them. Participants in other studies have also
reported that bodily movements in response to earworms (e.g., tapping a foot to the beat)
are relatively common (Floridou et al., 2015). Finally, frequency of earworms was
associated with self-reported obsessive-compulsive traits, perhaps similarly to the
persistence of intrusive thoughts in obsessive-compulsive disorder (Beaman & Williams,
2010). In contrast, little is known about typical affective and behavioral responses to
MH. There are, then, several large gaps in the MH literature, which we sought to address
in the present study. Firstly, very little research has been conducted regarding the
phenomenology of MH much further than asking about the broad style of music experienced.
Secondly, there is some confusion within the literature over precise definitions as to
what constitutes an MH, leading previous studies to use different inclusion criteria. As
mentioned, Saba and Keshavan (1997) used ‘volitional control’ as a key indicator of MH;
yet, this alone fails to distinguish the experience from that of earworms. On the other
hand, some authors seem to have equated earworms and MH (Hermesh et al., 2004), whilst
others have equated earworms and INMI as referring to the same phenomenon (Farrugia,
Jakubowski, Cusack, & Stewart, 2015). Williams (2015) has argued that INMI should be used
as a broader term, defining any type of musical imagery outside of conscious control, with
the term ‘earworm’ being restricted to a type of INMI characterized by its repetitiveness.
Within Williams' framework, MH would be categorized as a form of INMI defined by their
perceived externality and pathology (e.g. hearing impairment and/or brain damage).
Williams, then, offers perhaps the most rigorous categorization of forms of inner music,
but, due to a lack of previous research, does not discuss other potential differences
between MH and earworms. We sought to conduct an exploratory survey of the phenomenology
of MH, to investigate potential similarities and differences between MH and other forms of
inner music. Participants were asked to pick a category that they felt best described
their inner musical experience (musical imagery, earworm, musical hallucination) based on
basic definitions (see Supplementary Materials), or specify that they regularly
experienced multiple different types of inner music (henceforth referred to as the ‘mixed
experiences’ group). These categories were then compared on a number of phenomenological
attributes, both based on those reported in previous research, and areas that have not
previously been investigated. Based on previous literature, it was expected that MH would
be more likely to be experienced as coming from the external environment, whereas earworms
would be characterized by a lack of volition and repetitiveness, compared to musical
imagery. As well as collecting demographic information, we also asked about the presence
of psychiatric diagnoses and hearing impairments, as well as prior musical experience,
given that previous literature suggests these may be key predictors of the presence of MH.
Furthermore, we asked about a number of other features of the experience (frequency,
duration, familiarity, feelings of anticipation, triggers), musical details (perception of
lyrics, instruments, intensity, harmony, melody) and effects on behavior (effects on the
body, effects on mood, effects on relationships with others). Participants were also given
the chance to provide further information about their experiences in free text boxes on
many questions. The aim was, therefore, to provide a more detailed and nuanced study of
phenomenological aspects of MH as compared to other types of inner music, than has
previously been conducted. Supplementary data associated with this article can be found,
in the online version, at https://doi.org/10.1016/j.concog.2018.07.009. We sought to
conduct an exploratory survey of the phenomenology of MH, to investigate potential
similarities and differences between MH and other forms of inner music. Participants were
asked to pick a category that they felt best described their inner musical experience
(musical imagery, earworm, musical hallucination) based on basic definitions (see
Supplementary Materials), or specify that they regularly experienced multiple different
types of inner music (henceforth referred to as the ‘mixed experiences’ group). These
categories were then compared on a number of phenomenological attributes, both based on
those reported in previous research, and areas that have not previously been investigated.
Based on previous literature, it was expected that MH would be more likely to be
experienced as coming from the external environment, whereas earworms would be
characterized by a lack of volition and repetitiveness, compared to musical imagery. As
well as collecting demographic information, we also asked about the presence of
psychiatric diagnoses and hearing impairments, as well as prior musical experience, given
that previous literature suggests these may be key predictors of the presence of MH.
Furthermore, we asked about a number of other features of the experience (frequency,
duration, familiarity, feelings of anticipation, triggers), musical details (perception of
lyrics, instruments, intensity, harmony, melody) and effects on behavior (effects on the
body, effects on mood, effects on relationships with others). Participants were also given
the chance to provide further information about their experiences in free text boxes on
many questions. The aim was, therefore, to provide a more detailed and nuanced study of
phenomenological aspects of MH as compared to other types of inner music, than has
previously been conducted.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were invited to take part in an on-line survey, advertised via social media
and a research project website (http://hearingthevoice.org/2014/11/04/round-and-round-the-
phenomenology-of-inner-music). Rather than aiming to recruit a sample representative of
the national population, the aim was to recruit participants who reported hallucinatory
experiences or regular inner music, to investigate phenomenological features of these
experiences. There were 276 respondents to the questionnaire. From these, 7 participants
were excluded who did not respond to a sufficient number of questions (<10% response rate)
on the ‘Phenomenology of Inner Music Questionnaire’ (see below), whilst 14 that described
an alternative form of inner music in the free text box (e.g., musical memory) were
excluded. Thus, the sample analyzed consisted of 255 participants (105 male, 144 female, 6
other), with a mean age of 39.4 (SD = 13.3, range = 18–74). The majority of participants
were from English-speaking countries (e.g., 42.4% USA, 34.1% UK) but there were also
respondents from other European countries (e.g., Denmark, Germany, France, Finland) and
non-European countries around the world (e.g., Israel, Mexico, South Korea). Some form of
hearing loss was reported by 15.8% of participants, with most of these being described
simply as hearing loss/hypacusis (80%) and/or tinnitus (37.5%). Mean reported length of
hearing impairment in these individuals was 18.3 years (SD = 17.3). 42.7% of participants
reported having previously received a psychiatric diagnosis, with the largest proportion
of these being for depression (60.6%) or anxiety (30.3%), with smaller numbers of
participants having diagnoses of bipolar disorder, obsessive compulsive disorder,
attention deficit hyperactivity disorder, or schizophrenia/schizoaffective
disorder/psychosis. 9.0% of participants reported some form of neurological disorder,
whilst 26.4% reported being on some form of medication for a psychiatric/neurological
disorder. See Table 1 for demographic information of the sample.

        <hss>Previous musical experience</hss>

        Preliminary questions asked about musical expertise, musical preference,
        practising and listening habits. See Appendix 1 for a full list of questions.
        Preliminary questions asked about musical expertise, musical preference,
        practising and listening habits. See Appendix 1 for a full list of questions.

        <hss>Phenomenology of Inner Music Questionnaire</hss>

        The Phenomenology of Inner Music Questionnaire was designed as a preliminary
        exploration of the experience of MH, musical imagery, and earworms, including
        items based on previous literature on MH, but also items that have only been used
        in relation to imagery and earworms. Firstly, based on short definitions,
        participants were asked to classify their inner music as either musical imagery,
        earworm, or musical hallucination. A free text box was also provided for
        participants to expand on this description. Based on previous research into inner
        music or MH, further questions asked about aspects of the experience encompassing
        frequency, duration, level of detail (melody, harmony, intensity, presence of
        instruments, presence of lyrics), familiarity, effects on mood and behavior,
        amount of perceived control, triggers, and likelihood of being mistaken for an
        external stimulus. All questions required the participant to respond on a Likert
        scale, although many questions also provided a free text box to elicit more
        detailed responses. (See Appendix 1 for full questionnaire.) The Phenomenology of
        Inner Music Questionnaire was designed as a preliminary exploration of the
        experience of MH, musical imagery, and earworms, including items based on previous
        literature on MH, but also items that have only been used in relation to imagery
        and earworms. Firstly, based on short definitions, participants were asked to
        classify their inner music as either musical imagery, earworm, or musical
        hallucination. A free text box was also provided for participants to expand on
        this description. Based on previous research into inner music or MH, further
        questions asked about aspects of the experience encompassing frequency, duration,
        level of detail (melody, harmony, intensity, presence of instruments, presence of
        lyrics), familiarity, effects on mood and behavior, amount of perceived control,
        triggers, and likelihood of being mistaken for an external stimulus. All questions
        required the participant to respond on a Likert scale, although many questions
        also provided a free text box to elicit more detailed responses. (See Appendix 1
        for full questionnaire.)

        <hss>White Bear Suppression Inventory (WBSI)</hss>

        The WBSI is a 15-item scale designed to measure the tendency to suppress unwanted
        thoughts. Various studies have implied different factor structures underlying the
        WBSI; here, we used the subscales identified and used by Muris, Merckelbach, &
        Horselenberg (1996), assessing tendency to have intrusive thoughts (e.g., I have
        thoughts that I cannot stop) and thought suppression (e.g. I always try to put
        problems out of my mind). For each question, participants are required to rate
        their agreement on a Likert scale from 1 (Strongly Disagree) to 5 (Strongly
        Agree). These subscales have previously been shown to have acceptable internal
        reliability (Jones & Fernyhough, 2006).

        <hss>Revised Launay-Slade Hallucination Scale (LSHS-R, auditory items)</hss>

        Tendency to experience auditory hallucinations was assessed using the 5-item
        LSHS-R (McCarthy-Jones & Fernyhough, 2011; revised from Morrison et al., 2000)
        (e.g., I hear people call my name and find that nobody has done so). For each
        question, participants are required to indicate agreement with each question on a
        4-point Likert scale, ranging from 1 (Never) to 4 (Almost Always). Total score can
        range from 5 to 20. It has previously shown high internal reliability (Cronbach’s
        α = .73) (McCarthy-Jones & Fernyhough, 2011).

        <hss>Varieties of Inner Speech Questionnaire (VISQ)</hss>

        The VISQ is an 18-item scale designed to assess phenomenological features of inner
        speech. It consists of four subscales: evaluative inner speech (e.g., I think in
        inner speech about what I have done, and whether it was right or not), dialogic
        inner speech (e.g., I talk back and forward to myself in my mind about things),
        other people in inner speech (e.g., I experience the voices of other people asking
        me questions in my head) and condensed inner speech (e.g., I think to myself in
        brief phrases and single words, rather than full sentences). Each item is scored
        on a Likert scale from 1 (Never) to 6 (All of the time). Each subscale has
        previously shown high internal reliability (Cronbach’s α > .8) and acceptable
        test-retest reliability (>.6) (McCarthy-Jones & Fernyhough, 2011).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Given that our main area of interest regarded the phenomenological differences between MH
and other forms of inner music (musical imagery, earworms), participants were categorized
by the main type of experience they reported. If participants indicated in the free text
box that they frequently experienced more than one form of inner music (for example,
reporting both frequent MH and earworms), but indicated in the free text box that one of
these was much more prevalent than the other, they were categorized according to their
most prevalent experience. If participants indicated that they experienced more than one
type of music, but did not report relative frequencies, they were categorized in a
separate ‘mixed experiences’ group. This categorization was performed separately by two of
the authors (PM, BA, k = .77), and any disagreements (n = 9) were resolved by discussion
between authors. Thus, the sample was split into four groups (musical imagery, earworms,
MH, mixed experiences) for between-group analysis. We used chi-square analysis to
investigate associations between type of musical experience and presence of a
psychiatric/neurological diagnosis, hearing impairment, and level of musical expertise,
and further explored significant results using odds ratios (OR) in conjunction with 95%
confidence intervals. Due to mainly ordinal and non-normally distributed data, non-
parametric ANOVAs (Kruskal-Wallis) were used to test for differences between the
categories of inner music, for each phenomenological attribute. Where appropriate, Mann-
Whitney U tests were used to investigate differences between MH and other individual
categories; note that post-hoc tests were only conducted between MH and other categories
(as opposed to between all different categories) to limit the number of tests performed.
Based on our areas of interest, we split the analysis into four main sections: (1)
demographic and etiological information; (2) basic characteristics and acoustic details of
inner music; (3) location and controllability of inner music; (4) effect of inner music on
behavior and mood. Qualitative examples given by participants are included throughout as
illustrative examples of different aspects of their phenomenology. (All qualitative
examples given are taken from participants in the MH group.) Bonferroni corrections for
multiple comparisons were applied within each section (e.g., in Section 3.2, 10 tests are
performed, so the alpha level is corrected to .05/10 = .005; in Section 3.3, 5 tests are
performed so the alpha level is corrected to .05/5 = .01; in Section 3.4, 11 tests are
performed, so the alpha level is corrected to .05/11 = .0045). Missed items in the VISQ,
LSHS-R or WBSI were replaced with the mean from other items in the same (sub)scale.

<hs>  Demographics and categories of inner music</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The first question of the Inner Music Questionnaire asked people to choose the category
that best described the music they heard. Of the 255 participants, 17.3% reported musical
hallucinations, 40.4% reported earworms, 27.1% reported musical imagery, whilst 15.3% were
categorized in the ‘mixed experiences’ group. To investigate phenomenological differences
between MH and other musical experiences, ‘inner music category’ was used as a between-
subject variable. Only 1.2% of participants reported that they could ‘Never’ accurately
describe their inner music (in response to Q5) but, since they continued to provide
responses to the questions, these participants were not excluded from the sample. Table 1
summarizes basic demographics of the sample, whilst Table 2 shows these basic demographics
broken down by the category of inner music reported by the participant. For the main
effect of inner music type in this section, a Bonferroni-corrected alpha level of .05/9 =
.006 was used. A chi-square analysis indicated that there was not a significant
association between presence of a psychiatric diagnosis (χ2(4) = 4.33, p = .228, φ = .131)
or neurological diagnosis (χ2(3) = 1.36, p = .714, φ = .073) and the category of inner
music. There was also no significant association between presence of a hearing impairment
and category of inner music (χ2(3) = 0.89, p = .828, φ = .059). There was a significant
association between level of musical expertise and type of inner music reported (χ2(15) =
36.93, p = .001, φ = .381), although in this analysis 25% of cells had an expected count
of < 5, due to the low number of semi-professional (n = 23) or professional (n = 9)
musicians (at least compared to other groups) in the sample. This violates a key
assumption of chi-square analysis (Howell, 2010) and, as such, the sample was collapsed
into two groups: non-musicians (non-musicians and music-loving non-musicians; n = 110) and
musicians (amateur, serious amateur, semi-professional, and professional musicians; n =
145). Again, a chi-square analysis indicated an association between musical expertise and
inner music type (χ2(3) = 20.99, p < .001, φ = .287). Further analysis suggested that
musicians were less likely to report MH (OR = 0.27, 95% CI [0.14–0.54]), but more likely
to report mixed experiences (OR = 3.23, 95% CI [1.42, 7.33]) compared to non-musicians.
There was little difference in the proportion of musicians in either the imagery (OR =
1.37, 95% CI [0.78, 2.41]) or earworm (OR = 0.78, 95% CI [0.47, 1.28]) groups. Non-
parametric ANOVAs (Kruskal-Wallis) with inner music category as the independent variable
suggested a similar pattern of results for number of hours spent practicing musical
instruments per week (χ2(3) = 17.82, p < .001), with MH being associated with less music
practice than imagery (U = 1084.5, p = .011), although not significantly different to
earworms (U = 2168.5, p = .806) or mixed experiences (U = 623.5, p = .040) at the
corrected alpha level. However, this pattern of results seemed to be specific to actually
practising music, and did not hold for time spent listening to music (χ2(3) = 2.23, p =
.526).

<hs>  Basic characteristics of musical hallucinations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The questionnaire asked about a number of basic characteristics of inner music
experiences, such as style of music (Q4), frequency (Q2), duration (Q3), familiarity
(Q10), repetitiveness (Q22), and whether music was experienced in its entirety or was
shortened (Q20 and 21). Participants were also asked whether their inner music included
attributes such as melody, harmony, intensity, instruments, and lyrics (Q6). Table 3
presents descriptive statistics and the results of group contrasts, for the basic
characteristics and acoustic details of the different categories of inner music. For main
effects of inner music type, a Bonferroni-correct alpha level of .005 (.05/10) was used
for all statistical tests in Section 3.2. Classical music was the most frequently reported
style of inner music in participants with MH (47.7%), whereas rock music was the most
frequently reported style in the musical imagery group (64.2%), and pop music in the
earworms group (66.0%). The mixed experiences group reported that both pop music and
classical music were the most frequent style of their inner music (both 62.5%). See Table
4 for a full list of reported music styles and their frequency. A non-parametric (Kruskal-
Wallis) ANOVA with inner music frequency (Likert scale responses; see Appendix 1) as the
dependent variable showed a significant main effect of inner music category (χ2(3) =
33.73, p < .001), with Mann-Whitney U tests (Bonferroni corrected alpha levels at .05/3 =
.017) indicating that participants in the MH group reported the experience as occurring
significantly less frequently than those in the imagery group (U = 651.5, p < .001),
earworm group (U = 1153, p < .001), or the mixed experiences group (U = 468, p < .001).
There was also a significant main effect of inner music type on familiarity (χ2(3) =
56.96, p < .001), with MH being rated as less familiar than imagery (U = 738, p < .001),
earworms (U = 866, p < .001), or mixed experiences (U = 573.5, p < .001). For example, a
typical response from a participant in the MH group in a free-text box was: “I can tell
the style, but it’s not songs I’ve heard before. It’s new songs.” A non-parametric
(Kruskal-Wallis) ANOVA with inner music frequency (Likert scale responses; see Appendix 1)
as the dependent variable showed a significant main effect of inner music category (χ2(3)
= 33.73, p < .001), with Mann-Whitney U tests (Bonferroni corrected alpha levels at .05/3
= .017) indicating that participants in the MH group reported the experience as occurring
significantly less frequently than those in the imagery group (U = 651.5, p < .001),
earworm group (U = 1153, p < .001), or the mixed experiences group (U = 468, p < .001).
There was also a significant main effect of inner music type on familiarity (χ2(3) =
56.96, p < .001), with MH being rated as less familiar than imagery (U = 738, p < .001),
earworms (U = 866, p < .001), or mixed experiences (U = 573.5, p < .001). For example, a
typical response from a participant in the MH group in a free-text box was: “I can tell
the style, but it’s not songs I’ve heard before. It’s new songs.” There was also a main
effect on repetitiveness (χ2(3) = 21.22, p < .001), with MH being reported as less
repetitive than earworms (U = 1341, p < .001) or imagery (U = 1117, p = .011), but not
significantly different to the mixed experiences group (U = 618, p = .032), following
corrections to the alpha level (.05/3 = .017). There was also no significant effect of
inner music type on duration (χ2(3) = 11.60, p = .009), or the extent to which
participants reported inner music being shortened (χ2(3) = 5.31, p = .151) or a complete
song (χ2(3) = 5.77, p = .123). Almost all participants reported being able to perceive
melody in inner music (97.3% in overall sample), with most also being able to perceive
harmony (77.4%), intensity (66.5%), instruments (77.0%) and lyrics (75.9%). Chi-square
analysis indicated no association between inner music category and whether harmony (χ2(3)
= 3.02, p = .389, φ = .109), intensity (χ2(3) = 5.12, p = .163, φ = .142) or instruments
(χ2(3) = 5.69, p = .128, φ = .149) were perceived, although there was an association
between inner music type and whether lyrics were perceived (χ2(3) = 23.02, p = < .001, φ =
.300). (Given that >97% of participants reported being able to perceive a melody, there
was insufficient variation to test the association between inner music type and melody.)
Further analysis showed that MH were less likely to include lyrics than other types of
inner music (OR = 0.21, 95% CI [0.10, 0.41]), whereas earworms were more likely to include
lyrics (OR = 2.13, 95% CI [1.14, 3.98]). Meanwhile, the imagery (OR = 1.37, 95% CI [0.70,
2.68]) and mixed experiences (OR = 1.29, 95% CI [0.56, 2.98] groups were no more or less
likely to include lyrics. One participant who experienced MH commented: “...[they] tend
not to involve voices but do involve many different instruments. I have occasionally heard
other genres of music, including with voices, but I have not been able to understand the
lyrics.”

<hs>  Perceived control, location, and anticipation of musical hallucinations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Further questions asked whether participants felt control over their inner music (Q23),
whether they could anticipate the experience (Q24), whether they knew the trigger of the
experience (Q25), whether they ever mistook it for an externally located stimuli (Q26),
and whether they felt like the experience was of their own creation (Q11). Table 5
summarizes responses from these questions by category of inner music. For main effects of
inner music type, a Bonferroni-corrected alpha level of .01 (.05/5) was used for all
statistical tests in Section 3.3. There was a main effect of category of inner music on
perceived control (χ2(3) = 11.52, p = .009), with participants reporting MH also reporting
less control over the experience compared to participants in the imagery group (U = 1033,
p = .003). However, there was no significant difference between perceived control of MH
and earworms, or between MH and mixed experiences (ps > .129). A typical comment related
to the perceived effortlessness of MH, with little or no control: “Imagination to me is a
conscious effort – this isn’t.” “Like a radio station, I just have to wait for the next
song.” Others, meanwhile, described techniques to stop the MH, such as distracting
themselves with another activity: “I just think of something specific as a distraction
(e.g., I’m thinking about typing this response correctly, so my internal background music
is switched off for now).” When asked about the frequency with which their inner music was
mistaken for coming from the external environment, there was a significant main effect of
inner music category (χ2(3) = 95.10, p < .001), with MH being more likely to be mistaken
for an external percept than imagery (U = 460, p < .001), earworms (U = 656, p < .001) and
mixed experiences (U = 581, p = .008). For example: “There is usually a moment where I am
not entirely sure if it is external or internal, but the quality of sound and the apparent
feeling of “proximity” is strange when it is a hallucination. In other words, it might
sound soft as if it should be coming from far away, and yet it does not sound as though it
is coming through any barriers like walls... it is almost as if it is coming through
earphones, closer to me than the outside world, but not exactly ‘in my head’” “Remembering
music is like a faint shadow of real music...whereas hallucinating it really involves
hearing it” There was a significant main effect of inner music type on the extent to which
participants reported that their inner music was their own creation (χ2(3) = 39.09, p <
.001), with participants in the MH group, counterintuitively, rating this attribute more
highly than participants in the earworm group (U = 1255, p < .001), although there was no
difference between the MH and imagery or mixed experiences groups at the corrected alpha
level (ps > .30). There was no main effect of inner music category for reports of being
able to anticipate the experience or knowing what triggered the experience (see Table 5
for statistics).

<hs>  Effects of musical hallucinations on mood and behavior</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants were asked a number of questions about the effect of inner music on their
behavior and mood, including whether they were able to hum along with the inner music
(Q8), whether their body moved with the music they experienced (Q9), whether the
experience reflected their own feelings (Q18), or was associated with negative affect
(Q15) (see Table 6). A Bonferroni-corrected alpha level of .05/11 = .0045 was used for all
statistical tests in Section 3.4. The extent to which participants reported that the inner
music reflected how they were feeling differed between categories (χ2(3) = 19.22, p <
.001), with MH being rated lower on this attribute than imagery (U = 825.5, p < .001),
earworms (U = 1539, p = .003) or the mixed experiences group (U = 522, p = .002). Although
there was a significant main effect of inner music category on the extent to which the
experience made the participant feel excited (χ2(3) = 15.30, p = .002), further tests did
not reveal any significant differences at the corrected alpha level between MH and any
other categories (all ps > .019). Notably, there was no significant effect of inner music
category on the experience contributing to the participant feeling depressed (χ2(3) =
8.21, p = .042) or anxious (χ2(3) = 6.79, p = .079) after corrections to the alpha level,
providing no strong evidence that MH were associated with negative affect more than other
forms of inner music. For example: “It’s never anything emotional playing, usually just
‘there’. I’ve gotten used to it for the most part, but the most it makes me feel is
annoyed.” Participants reported being less able to hum along with MH (χ2(3) = 24.72, p <
.001), compared to imagery (U = 777.5, p < .001), earworms (U = 1204.5, p < .001), or
mixed experiences (U = 481, p = .001), as well as being less able to hum the music after
the experience (χ2(3) = 22.15, p < .001) compared to imagery (U = 860.5, p < .001),
earworms (U = 1313, p < .001), or mixed experiences (U = 589, p = .012). Participants also
reported moving their body less to MH (χ2(3) = 28.88, p < .001), compared to imagery (U =
736, p < .001), earworms (U = 1442, p < .001), or mixed experiences (U = 416, p < .001).
One typical comment was: “Unfamiliar, no lyrics, no compulsion to sing or hum along”
Finally, there was no association between inner music category and the extent to which it
was said to affect the participant’s relationship with others (see Table 3 for
statistics).

<hs>  Associations between musical hallucinations, inner speech phenomenology, and intrusive thoughts</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants also completed a small number of quantitative self-report measures relating
to phenomenology of inner speech (VISQ), intrusive thoughts and thought suppression
(WBSI), and auditory hallucination-proneness (LSHS). There was no main effect of inner
music type on any measure of inner speech phenomenology, intrusive thoughts, or thought
suppression (all ps > .092). Unsurprisingly, there was a main effect of inner music type
on hallucination-proneness (χ2(3) = 20.03, p < .001), with participants in the MH category
(M = 9.60, SD = 2.61) scoring higher than those in the imagery category (M = 8.18, SD =
2.50, U = 958, p = .005) and the earworm category (M = 8.19, SD = 2.31, U = 1445.5, p =
.003), although not significantly differently to the mixed experiences category (M =
10.21, SD = 3.22, U = 723.5, p = .469).

<h>DISCUSSION</h>
----------

The present study provided preliminary evidence for a number of phenomenological
differences between MH and other forms of inner music (summarized in Table 7). Whilst some
of these differences fit closely with the typical conceptualization of hallucinatory
experience (e.g., experienced as externally located, uncontrollable), others were less
expected and may open avenues for future research. For example, the data suggested that MH
are less likely to be experienced by musicians, less repetitive, less likely to include
lyrical content, and are described as less likely to be associated with one’s own
feelings, compared to musical imagery or earworms. Somewhat counterintuitively, the data
also suggested that MH were more likely to be experienced as one’s ‘own creation’ compared
to earworms. Importantly, our findings suggest that there are key differences between, in
particular, MH and earworms. Moreover, given the self-report methodology used in this
study, the data provides valuable insight into how people make judgements about their own
experiences (that is, what do people classify as hallucinatory?). Here, the findings are
compared to previous literature on MH, but several new findings that could form the basis
for future research are also interpreted. A previous systematic review by Cope and Baguley
(2009), focusing on etiological factors underlying MH, indicated that hearing loss, female
gender, old age, and social isolation were all risk factors for MH. The present data did
not indicate that females were more likely to report MH; while the proportion of females
in the MH category was higher than other groups, this was not statistically significant.
The data did not show elevated levels of hearing impairment in individuals reporting MH as
opposed to other forms of inner musical experience, although, given the relatively low
rates of reported impairment in our sample, this may be an issue of statistical power.
Numerous studies have previously linked AH or MH to hearing impairment (Cope & Baguley,
2009; Griffiths, 2000; Kumar, Sedley, Barnes, Teki, & Griffiths, 2014; Linszen, van
Zanten, Teunisse, Brouwer, Scheltens, & Sommer, 2018); one interesting question,
therefore, would be to examine the phenomenology of MH that seem to be linked to hearing
loss, compared to those that are not. Rates of psychiatric or neurological diagnoses were
also similar across different forms of reported inner music, and, furthermore, individuals
with MH were not significantly more likely to say that the experience made them depressed
or anxious, compared to individuals reporting other forms of inner music. Previous
literature has provided mixed evidence regarding negative emotions associated with MH. The
most prevalent emotional description in Saba and Keshavan (1997) study was ‘soothing’; in
contrast, Evers and Ellger (2004) found that 41% of participants described the experience
as ‘frightening’. Such differences may partially reflect the different populations from
which data was collected, with most previous research investigating MH in psychiatric or
neurological patients. Our data, meanwhile, is consistent with the view that MH, and
auditory hallucinations more broadly, can occur without significant distress and outside
of any need for care (Johns et al., 2014). Indeed, the only demographic factor
significantly associated with MH in the present data was level of musical expertise, with
individuals reporting MH being less likely to classify themselves as a musician, playing
fewer musical instruments, and spending less time practising music. Previous research has
suggested that musical training is associated with superior performance on tasks requiring
auditory imagery generation, for example to complete a musical sequence (Aleman,
Nieuwenstein, Böcker, & de Haan, 2000), or to evoke spontaneous experiences of musical
imagery, and importantly, voluntarily modify the experiences (Goycoolea et al., 2007).
Similarly, Pallesen et al. (2010) showed that individuals with musical training showed
increased performance on an auditory working memory task, showing greater levels of
cortical activation in areas of the brain typically associated with cognitive control,
such as the lateral prefrontal cortex and anterior cingulate cortex. It is possible,
therefore, that enhanced cognitive control among musicians may contribute to the decreased
prevalence of MH, although further research is needed to investigate this issue. One of
the few studies to report phenomenological details of MH (Saba & Keshavan, 1997) reports
data from 100 participants with a diagnosis of schizophrenia, finding that 16 of these
individuals experienced MH. These experiences were not compared directly to experiences of
musical imagery or earworms; consistent with our findings, however, a substantial number
were rated as being perceived as emanating from the external environment, and
approximately half were rated as not under volitional control of the individual. Saba and
Keshavan, however, argued that if the individual reported any volitional control of the
experience, it should not be defined as an MH, suggesting that this lack of control is
actually a key feature of the experience. This is in contrast to our data, which suggests
that while MH were rated as much lower in controllability than musical imagery, earworms
were rated intermediately between the two categories. One possibility consistent with Saba
and Keshavan’s argument is that the experience of volitional control can vary along a
continuum, with imagery becoming hallucinatory when it is extremely uncontrollable. Level
of volitional control may also be an important factor in clinical distress, with recent
studies showing that individuals that report regular AVH but have no clinical diagnosis
report higher levels of control, compared to those with a clinical diagnosis (Alderson-Day
et al., 2017; Daalman et al., 2011; Powers, Kelley, & Corlett, 2016). On this view,
earworms would simply fall on a midpoint of this continuum between musical imagery and MH.
However, our findings also suggest that MH differ in a number of other ways from both
musical imagery and earworms; for example, MH are much more likely to be experienced as
externally located, consistent with the argument made by Williams (2015). Indeed, given
that a substantial proportion of individuals in the Saba and Keshavan study (37.5%)
perceived their MH as externally located, it is unclear why only volitional control,
rather than perceived location, was chosen as the main criteria by which MH were defined.
Another clear difference between earworms and MH, in our sample, was the reported
familiarity of the perceived music, with MH being rated as less familiar to the
participant than other forms of inner music. It is possible that this feeling of
unfamiliarity may add to a feeling of alienness typically associated with hallucinations,
as opposed to musical imagery or earworms. In contrast, previous studies have reported
that as many as 78% of cases of MH were experienced as familiar music (Evers & Ellger,
2004). There are two possible methodological differences that may account for this
discrepancy. Firstly, as already mentioned, the two referenced studies focused mainly on
MH occurring in psychiatric and neurological disorders, whereas rates of diagnoses were
much lower in the current sample. As such, our data may reflect MH occurring across a
broader population, mainly consisting of those without a need for care, and without
comorbid psychiatric symptoms or brain damage. Secondly, previous studies have
deliberately excluded participants reporting ‘pseudohallucinations’ (which Evers and
Ellger dismiss as being linked to ‘memory representations’), although this distinction is
no longer typically used in hallucinations research. As such, the present data presumably
encompasses a wider variety of experiences regarded as hallucinatory; indeed, given the
self-report nature of this data, a sufficient level of insight regarding the hallucinatory
nature of their experience was necessary for participants to report on the features of
their MH. Our data suggested that less than half of participants reported the presence of
lyrics in their MH, compared to rates of approximately 80% in other forms of inner music.
This is, again, in contrast to Saba and Keshavan, who noted that MH consisting only of
instrumental music was rare. It should be noted that the present questionnaire only asked
about lyrical content rather than concurrent MH and AVH. Nevertheless, the low frequency
of lyrical content was an unexpected finding, and highlights a key difference between MH
and AVH, the most frequent form of auditory hallucination. Given that cognitive
neuroscientific models of AVH specify a key role for brain networks involved in speech
production and perception (Allen, Larøi, McGuire, & Aleman, 2008; Moseley, Fernyhough, &
Ellison, 2013), this is suggestive that non-lyrical MH may be associated with different
cognitive mechanisms than AVH, rather than simply differing in content. An interesting
area for future research would be to investigate differences between the phenomenology and
cognitive mechanisms underlying MH with and without lyrics, as well as investigating the
prevalence and phenomenology of mixed AVH and MH. A further unexpected, and rather
counterintuitive, aspect in which MH differed from other forms of inner music was in
rating the extent to which the music was one’s own creation. Although MH were rated as
lower in controllability and familiarity, they were actually rated as significantly higher
on this attribute, in comparison to earworms. A frequent argument is that earworms occur
due to unintentional re-activation of memory representations of previously heard music
(Kvavilashvili & Mandler, 2004; Liikkanen, 2012). In this sense, they may be viewed as not
one’s own creation, since the individual realizes that they are elicited by an external
stimulus (that is, the individual is aware that they were not the author of the music). In
contrast, a less clear link with previously heard music may lead to recognition of
creative ownership of MH, despite a lack of controllability or familiarity of the music.
This argument assumes a fairly high level of insight regarding one’s MH; that said,
participants in this sample presumably required sufficient levels of insight to self-
classify their experiences as hallucinatory. It is particularly interesting that
volitional control and authorship can be dissociated in this way, which potentially
provides evidence for a dissociation between individual sense of agency and sense of
ownership in relation to MH (Gallagher, 2000); that is, our data suggest that individuals
may feel a lower sense of agency, but a retained sense of ownership, over MH. This study,
then, has provided data on several aspects of the phenomenology of MH. In comparison to
the most widely studied type of inner music – earworms – MH are less controllable, more
likely to be experienced as coming from the external environment, less familiar in
content, less repetitive, less likely to include lyrics, and more recognizable as one’s
own creation. These differences highlight a need for greater clarity in the use of
definitions when talking about different experiences of inner music. Our data is not
consistent with previous claims that MH can simply be thought of as earworms that have
reached pathological levels (e.g., Hemming, cited in Williams, 2015), for two reasons:
firstly, MH appear to differ from earworms on a number of phenomenological attributes,
rather than simply being more persistent or distressing; secondly, many individuals in our
sample reported experiencing MH without having a hearing impairment, psychiatric or
neurological disorder, or any resulting distress. As such, more nuanced definitions of MH
and earworms are needed. Previous research tends to have studied all involuntary musical
imagery as one type of experience (Floridou et al., 2015; Müllensiefen et al., 2014;
Williamson et al., 2014), with some conflating the terms INMI, earworms, and MH. Williams
(2015) argues that the key difference between MH and earworms is the perception of spatial
location, and suggests that INMI should be used as an umbrella term which can be further
separated into earworms and MH. Our data support the importance of spatial location, but
also suggest that this is not the sole difference, with aspects such as repetitiveness and
familiarity also appearing to be important. Other instances of musical experience not
included in this survey should also be investigated, including musical pareidolia (hearing
music in other sounds) and musical memories. Future research should further investigate
some of the findings presented here. One limitation of the present study was that it
required participants to classify their own experience as hallucinatory. Ideally, such
experiences should be enquired about via a face-to-face clinical interview; however,
online surveys can reveal experientially rich and sometimes unexpected aspects of
hallucinatory phenomenology (see, for example, Woods, Jones, Bernini, Callard, Alderson-
Day, & Badcock, 2014; Woods, Jones, Alderson-Day, Callard, & Fernyhough, 2015).
Additionally, although this study showed a link between a lack of musical training and MH,
it is impossible to establish cause and effect from our data. Although findings of
improved cognitive control following musical training are suggestive that this may reduce
the likelihood of MH, a randomized controlled trial would be needed to make a direct link.
Equally, it is possible that individuals who experience MH are less likely to pursue
musical training, if their inner musical experiences are persistent or appraised
negatively. Another important line of research will be to investigate the cognitive and
neural correlates of MH, in comparison to musical imagery or earworms, about which little
is currently known. An interesting question is whether (at least some) MH can be explained
within a similar framework to AVH; that is, if MH can be explained as musical imagery that
has been misattributed to an external source (Fernyhough, 2016). Studies investigating the
association between MH and performance on tasks requiring the monitoring of self-generated
actions could be the first step in this direction. Given the numerous phenomenological
differences between musical imagery and MH highlighted above, however, a self-monitoring
model may be too simplistic. Although research into MH is in its infancy, this study has
provided preliminary evidence regarding a number of phenomenological aspects of MH that
have not previously been addressed; future research should aim to replicate and extend
these findings, which can be informative of inner musical experience in its many different
forms.


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<ART>Narrative skills in deaf children who use spoken English: Dissociations between macro and microstructural devices
================================================================================

Authors: A. C. Jones, E. Toscano, N. Botting, C. R. Marshall, J. R. Atkinson, T. Denmark, R. Herman, G. Morgan
DOI: 10.1016/j.ridd.2016.09.010
Year: 2016  |  Pages: 268-282
ASJC codes: 3203, 3204
Keywords: Deaf children, Inference-making, Narrative macrostructure, Narrative microstructure, Oral language

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Previous research has highlighted that deaf children acquiring spoken English have difficulties in narrative development relative to their hearing peers both in terms of macro-structure and with micro-structural devices. The majority of previous research focused on narrative tasks designed for hearing children that depend on good receptive language skills. The current study compared narratives of 6 to 11-year-old deaf children who use spoken English (N = 59) with matched for age and non-verbal intelligence hearing peers. To examine the role of general language abilities, single word vocabulary was also assessed. Narratives were elicited by the retelling of a story presented non-verbally in video format. Results showed that deaf and hearing children had equivalent macro-structure skills, but the deaf group showed poorer performance on micro-structural components. Furthermore, the deaf group gave less detailed responses to inferencing probe questions indicating poorer understanding of the story's underlying message. For deaf children, micro-level devices most strongly correlated with the vocabulary measure. These findings suggest that deaf children, despite spoken language delays, are able to convey the main elements of content and structure in narrative but have greater difficulty in using grammatical devices more dependent on finer linguistic and pragmatic skills.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPER ADDS?</h>
---------------------

This paper provides a description of the development of story-telling abilities of deaf
and hearing children who use spoken English. In addition to assessing macro- (global) and
micro- (local) level narrative skills, probe questions were used following the story
presentation to assess comprehension abilities. A scale was devised to assess the micro-
level skills of cohesion, grammatical morphemes, and narrative and evaluative devices.
While previous studies assessing narrative development in deaf children have used language
dependent stimuli designed for hearing children, the current study uses a non-verbal story
presented in video format that does not depend on deaf children’s receptive language
skills. In contrast to the findings of previous studies, deaf children showed equivalent
performance to their hearing peers at the macro-level; however, performance on micro-level
narrative skills was poorer, and less relevant and detailed answers were provided to the
inferencing probe questions than hearing peers. This paper thus highlights the strengths
and weaknesses of oral deaf children’s language abilities.

<h>INTRODUCTION</h>
------------

Narrative is a powerful tool that all cultures possess for organizing and interpreting
experience (Bamberg, 1997; Labov & Waletzky, 1967). Children learn to tell stories by
taking part in narrative practices that their parents and other adults model to them (Van
Deusen-Phillips, Goldin-Meadow & Miller, 2001). Profoundly deaf children are increasingly
communicating in spoken English, yet even with advances in cochlear implant technology,
they continue to lack full auditory access to the spoken language that surrounds them, and
so consequently persist with communication delays (Marschark & Spencer, 2015). While there
is a good understanding of deaf children’s oral language development, their ability to
narrate a story in spoken language has previously been addressed in only a small number of
studies (Crosson & Geers, 2001). This paper focuses on narrative development in oral deaf
children and addresses a broad range of narrative skills at both the macro- (global) and
micro- (local) level. Narrative skill encompasses the ability to communicate a story
containing sequential information usually about a past or future event (Gleason, 2002),
and is considered a cornerstone of children’s language development. Children’s emerging
narrative ability is crucial for developing social skills (Miller, 1994) and has been
shown to predict later literacy skills (Griffin, Hemphill, Camp & Wolf, 2004; Roth, Speece
& Cooper, 2002). Typically developing children’s language shows a large proportion of
personal narratives (Beals & Snow, 2002; Liles et al., 1995), In everyday conversation,
children as young as 2–3 years naturally retell stories or recount a sequence of events,
and as they get older children increasingly become able to deal with the discourse-
pragmatic requirements that underpin narrative. Several concurrently developing, higher-
level language and cognitive skills are necessary to form cohesive, coherent and
structured narratives (Bamberg & Damrad-Frye, 1991). These include the mastery of a
variety of linguistic (lexical, syntactic and pragmatic) skills, the ability to remember
and order in sequence a series of events, and to establish and maintain perspectives of a
range of characters (Norbury, Gemmell & Paul, 2014).

<hs>  Assessing narrative development</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Narrative is assessed for typical and atypical language development (Botting, 2002;
Cleave, Girolametto, Chen & Johnson, 2010) and is typically measured for two factors: the
global organisation of content, known as macro-structure; and a local linguistic level
which measures devices used within and across sentences, known as micro-structure (Liles,
Duffy, Merritt & Purcell, 1995). The macro-structure level focuses on two aspects: the
ability to construct a hierarchical representation of the story’s main elements, including
the sequencing of events, introduction to the characters and setting of the scene,
complicating actions, the story climax and resolution, and internal response felt by the
characters and plot evaluations (Norbury & Bishop, 2003); and also a measure of
information provided for specific content (e.g., Pankratz, Plante, Vance & Insalaco,
2007). Studies with typically developing children show that at around aged 4 years,
children begin to use the macro components (Trabasso & Stein, 1994), and by seven years of
age, children are more able to structure a story with multiple episodes. By nine-ten years
of age children can tell complete stories with substantial detail (Crais & Lorch, 1994).
Micro-structure elements are assessed at the word and sentence level and include devices
for achieving cohesion, such as coordinating (and, but, so) and subordinating (because,
when, that, if) conjunctions. These devices provide connections from one event to another
and create a clearly understood sequence (Berman & Slobin, 1994). A second measure of
cohesion is the unambiguous use of reference to specify and distinguish characters in the
narrative, both at first mention, and through the use of anaphoric pronouns to refer back
to the named character (he, she, his, her). Micro-structure becomes more sophisticated
with age (Liles, 1993; Liles et al., 1995) and depends on the ability to integrate
syntactic and pragmatic information (Hemphill, Picardi & Tager-Flusberg, 1991) as well as
the growth of perspective taking (Tager-Flusberg & Sullivan, 1995). Narrative measures are
also used to evaluate other local language aspects in children with language learning
difficulties (e.g. specific language impairment: SLI), such as frequent grammatical errors
of verb tense and pronoun use (Cleave et al., 2010). In addition, during the school-age
years, typically developing children develop elements related to evaluative comments
(Norbury & Bishop, 2003) and improve their use of literate, decontextualized language
(Curenton & Justice, 2004). These features can help reduce ambiguity in a story by
increasing the explicitness of character, object and event descriptions, for example
through the use of adjectives, adverbs (e.g., to specify manner: carefully), or
information about spoken dialogue (e.g., said, shouted; Greenhalgh & Strong, 2001). It has
been suggested that such language use is dependent on vocabulary development, and an
ability to mentally represent objects absent from the immediate context (McGillicuddy-
DeLisi & Sigel, 1991). Narratives also reveal the links between social cognition and
language development through the assessment of children’s growing story comprehension and
inference-making abilities. There is little written about inference making abilities in
deaf children’s narratives, but more attention has been given to atypically developing
populations with cognitive differences, such as Autistic Spectrum Disorders (ASD) and SLI
(Norbury et al., 2014). When a series of probe questions based on elements not explicitly
mentioned in a previously heard story are used, children with autism spectrum disorders
(ASD) (Tager-Flusberg & Sullivan, 1995) and children with SLI (Bishop, 1997) were more
likely to be literal in their responses, showing they had not understood the story’s
underlying message: a skill that was shown to be closely linked to “theory of mind” (i.e.,
understanding the intentions of others; Premack & Woodruff, 1978).

<hs>  Narrative development in deaf children who use spoken language</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

With over 90% of deaf children being born to hearing parents, the restricted access to
verbal and/or signed information means that this group faces significant difficulties in
their language skills, including the ability to produce a coherent narrative (Crosson &
Geers, 2001). Typically-developing hearing children have frequent opportunities to engage
in narrative discourse, both in interactions with others and indirectly overhearing others
recount their experiences. Telling stories about themselves at school, home and in other
social settings is an everyday occurrence (Crais & Lorch, 1994). Deafness itself is not a
barrier to full language development, for example deaf children of deaf parents has been
shown to follow the typical narrative developmental milestones in British Sign Language
(Morgan, 2002). In contrast, deaf children who are not exposed to a natural sign language
by parents/carers with native level of fluency have reduced opportunities for interaction
and particularly incidental learning (Morgan et al., 2014). In many countries the majority
of deaf children have hearing parents who themselves do not sign, and instead choose to
use oral language with their children (Marschark & Spencer, 2015). Currently these
children are most often educated in a mainstream setting using a spoken language. The
impact of deafness on general spoken language skills has been widely documented. For
example, Geers, Nicholas and Sedey (2003) investigated expressive grammar and found that
deaf children with cochlear implants (CIs) showed poorer morphological and syntactic
skills than their hearing peers. On average, deaf children with (or without) implants have
smaller receptive vocabularies than hearing children of the same age (Eisenberg et al.,
2004; Spencer, 2004), and this difference persists over time (Blamey et al., 2001; Kirk et
al., 2002). With advances in neo-natal screening and hearing aid technologies, spoken
language skills of deaf children are gradually improving but it is less clear what changes
are occurring for pragmatic and higher levels of language use as required in narrative
(e.g., Rinaldi, Baruffaldi, Burdo & Caselli, 2013). Previous studies that have
specifically investigated the spoken narratives of deaf children have focused on those
with CIs and have shown that in general, they lag behind their hearing peers (Boons et
al., 2013a; Crosson & Geers, 2001; Guo, Spencer & Tomblin, 2013; Worsfold, Mahon, Yuen &
Kennedy, 2010). Crosson and Geers (2001) videotaped 8–9 year old oral deaf children with
CIs on a story telling task and found that the deaf children, in particular those with
poorer ability to discriminate speech using the CI, scored poorly on narrative structure
and cohesion (use of conjunctions and character references) relative to hearing peers.
More recent studies have focused on using story retell with the support of picture
prompts. At the micro-level, Worsfold et al. (2010) found that oral deaf children with CIs
were poorer at producing high-frequency morphemes (e.g., past tense, -ed) and used fewer
subordinate clauses than their hearing peers when retelling “the bus story” (Renfrew,
1997). Using the same story retell method, Boons et al. (2013a) reported no differences
between deaf and hearing groups in referencing story protagonists, but hearing controls
outperformed deaf children on the number of subordinate clauses used. The deaf group also
had a higher percentage of utterances with morphological, syntactic or semantic errors.
Finally, Guo et al. (2013) showed in a longitudinal study that children with CIs used
fewer tense markers on verbs in story retelling than age-matched peers with normal
hearing. At the macro-level, with the exception of a high-scoring subgroup of children who
were implanted early (Boons et al., 2013a), oral deaf children with CIs were reported to
achieve lower scores than their hearing counterparts. The deaf group’s bus stories were
poorer in plot structure and comprised fewer essential elements in story content (Boons et
al., 2013a; Worsfold et al., 2010). A limitation of previous research using story retell
with deaf children is that the task depends on receptive language skills. The deaf
participant must listen to and speech-read the experimenter telling the story, and must be
able to divide their attention between picture prompts and the story narrator, before
retelling. A further limitation noted by Worsfold et al. (2010) is that deaf children may
convey some of their story content by using gestures. Without videotaping the child, it is
not possible to capture this element of the narration. It is possible that deaf children
with spoken language delays are still able to produce narrative with the aid of gestural
substitutions. Relevant evidence comes from deaf children who spontaneously developed home
signs (a form of systematic gestures) and were able to use these to create rudimentary
narratives (Morford & Goldin-Meadow, 1997; Van Deusen-Phillips et al., 2001). Finally, the
use of mental state vocabulary and other evaluative devices in the narratives of deaf
children using spoken English has received little attention to date. This is important
given the consistent finding that oral deaf children display difficulties in mental state
reasoning as evidenced by a delay in passing the false belief task (e.g., Schick, De
Villers, De Villiers & Hoffmeister, 2007). A recent longitudinal study found that although
length of time since CI significantly improved deaf children’s narrative performance, deaf
children still used fewer evaluative devices and less mental state vocabulary compared to
hearing peers, which was linked to a reduced opportunity to overhear discussions about
people’s intentions and emotions (Huttunen & Ryder, 2012). In summary, research to date
suggests that deaf children have difficulty with both macro- and micro narrative skills,
yet assessment has generally depended upon verbal story retell methods designed for
hearing children. The focus in much of this previous research has been with deaf children
who wear CIs, while many deaf children using spoken language are still using hearing aids.
Furthermore, there is scope to provide a more comprehensive assessment by additionally
including probe questions to gauge deaf children’s understanding of the characters’
intentions and mental states. Finally, some studies have concurrently investigated deaf
children’s spoken English narratives and vocabulary ability (e.g. Boons et al., 2013b),
but have not examined the relationship between these two abilities. The current study
aimed to address each of these factors.

<hs>  Present study</hs>
  ~~~~~~~~~~~~~

We investigated the narrative abilities of deaf children who use spoken English. The
children were recruited from across the UK and were representative of deaf children who
used both hearing aids and cochlear implants. The deaf children were compared with a
hearing control group who were carefully matched for age and non-verbal intellectual
ability. To overcome the limitation of using a measure that is dependent on receptive
language abilities, a video clip of a story acted out silently by two actors was employed
to elicit a narrative (Herman et al., 2004). The advantage of this elicitation method is
that it relies on the children’s visual rather than auditory memory. This reduces the
processing demand of dividing attention between the story pictures and communicating with
the experimenter, which may enable the deaf and hearing children to complete the task on
more equal level. Children were assessed on their macro level skills (content and
structure) and comprehension was evaluated by probe questions, which assessed
understanding of the mental state and intentions of the story characters. The children’s
story telling was videotaped, enabling representational gestures to be included in the
scoring of narrative content and structure. In addition, a novel grammatical scale for
English was devised to assess micro-level narrative skills. The children were also
assessed on their one-word expressive vocabulary. As a secondary aim, the relationship
between expressive vocabulary and narrative skills was then examined. It was predicted
that the deaf children would show comparable performance to hearing children in terms of
narrative content and structure, given that the task is not dependent on receptive
language skills. However, given previous reported delays in finer linguistic, pragmatic
skills, and mentalizing abilities, it was expected that deaf children would be poorer in
their micro-level narrative skills and their ability to answer the comprehension
questions, relative to hearing controls. As the language used in narratives tends to be
more decontextualized and requires the use of more elaborate vocabulary, as well as more
exact syntactic marking of temporal and causal nature of events (Curenton & Justice,
2004), it was expected that there would be a positive relationship between vocabulary and
micro-level narrative skills for both deaf and hearing groups. In addition, it was
expected that a relationship between micro-level narrative skills, vocabulary and the
ability to infer the mental states of others as measured by the probe questions would be
found, given that language ability has been shown to be a strong predictor of theory of
mind skills in both hearing (Milligan, Astington & Dack, 2007) and deaf children (Schick
et al., 2007). On the other hand, it was reasoned that macro-level narrative skills would
depend less on the children’s general language abilities, particularly in light of the
evidence that even deaf children with limited language abilities but typical non-verbal
intelligence are able to construct stories through home signs.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Fifty-nine deaf children (30 boys) were recruited based upon the following inclusion
criteria: (1) pre-lingual deafness (congenital or occurrence at age ≤ 1 year), (2) aged
between 6 and 11 years, (3) spoken English as the preferred modality of communication, (4)
no known learning disabilities or concomitant disorders such as attention deficit or
autism. The deaf children’s ages ranged from 6;0 to 11;8 (M = 8;9, SD = 1;8). Their non-
verbal ability was derived from scores on the Matrix Reasoning subset of the Wechsler
Abbreviated Scale of Intelligence (WASI; Wechsler, 1999) and their T-scores (M = 50; SD =
10) ranged from 30 to 69 (within 2SDs above/below the mean). Table 1 summarises the
background characteristics of the deaf participants in terms of cause of deafness, level
of hearing loss in their better ear and type of hearing device used. All children received
auditory amplification or cochlear implants (CIs) and used these devices during testing.
The mean age of first implant for the CI group was 3;5 (SD = 2;0, range = 1;0 to 10;2).
The majority of the deaf children’s parents were hearing, but twelve had a deaf parent: 7
of these parents specified BSL as their own preferred language, and the remainder spoke
English as a first language. All deaf parents however reported that their deaf child’s
preferred language was spoken English. To gain a broadly representative sample the deaf
group were recruited from specialist deaf schools (5 from day schools and 2 from
residential schools) but the majority from mainstream schools across the UK (24 from
schools with a specialist support unit and 28 from schools without specific provision).
Forty-three parents (73%) had some level of education after leaving school (university or
further education college). The majority of the deaf children were White British or White
European (N = 49; 83%), 4 were Asian British, 2 were Black British, and 4 were mixed race
or other. Table 2 shows the participant demographic information (age, non-verbal ability,
gender and whether parents had further education) for deaf and hearing children. A group
of 67 hearing children (37 boys) were recruited as a typically developing control group.
These children were from a range of primary schools in rural and urban settings, and when
possible were from the same schools and year groups as the deaf children ensuring similar
demographic backgrounds to control for social status and match on chronological age. Table
2 shows that deaf and hearing groups did not significantly differ in terms of age (M =
8;10, SD = 1;6; range = 6;0 to 11;11) and non-verbal ability. There were no significant
differences between groups in terms of gender, whether the parents had further education
(N = 51) (Table 2), or ethnicity (χ2 (3) = 3.54, p = 0.32).

<hs>  Procedure</hs>
  ~~~~~~~~~

The UCL Research Ethics Committee gave ethical approval for the study. Children were
recruited either by contacting deaf schools and specialist support units directly, or by
establishing contacts with parents via the National Deaf Children’s Society. Informed
written consent was obtained from parents/guardians prior to testing. Children gave verbal
consent at the start of the testing session and were informed they could opt out at any
time.

<hs>  Language measures</hs>
  ~~~~~~~~~~~~~~~~~

All children were tested using measures of narrative ability and spoken English expressive
vocabulary.

        <hss>Narrative ability</hss>

        Children were tested on the Narrative Production Test (originally the BSL
        Production Test; Herman et al., 2004) with an English grammar adaptation. First
        the child watches a short, silent story on a laptop. The two children in the video
        act out a series of events without the use of language (see Table 3 for a
        descriptions of each story episode). Participants are instructed to watch the
        story carefully and to remember it so they can retell it immediately after
        viewing. To encourage the child to tell the whole story, the experimenter leaves
        the room and returns once the video has finished. The child is able to watch the
        film a second time if they wish. When the experimenter returns, the child is asked
        to tell the story and the experimenter listens to the child’s response without
        prompting. After completion, they are asked two probe questions to assess story
        comprehension and inferencing skills: (1) Why did the boy throw the spider? (2)
        Why did the girl tease the boy? The children’s narratives and responses to the
        questions were video recorded and then transcribed for analysis. All transcripts
        were checked against the video recordings by a second examiner. Discrepancies were
        discussed and agreement between examiners was obtained for all transcripts.

            <hss>Scoring narratives</hss>

            Table 4 provides an overview of the method used to score the children’s
            narratives. At the macro-level, the narratives were evaluated for content and
            structure following the scoring guidelines of Herman et al. (2004). Narrative
            content (i.e., the level of detailed information in the narrative) was scored
            by awarding one point for each mention of 15 specific story episodes (Table
            3), plus a further point for mentioning any “additional information” in the
            story (e.g., the spider was horrible) giving a maximum of 16 points. As the
            stimuli material contains only gestures and actions, this prompted some
            children (deaf and hearing) to use gesture in their story retellings. This was
            mainly co-speech gesture, but on a few occasions children used silent mime
            e.g., a gesture to represent holding a sandwich up to the mouth and pretending
            to eat it. These gestures/mime were included in the scoring of story content
            for both deaf and hearing children, therefore both the video and transcribed
            speech were referred to when scoring narrative content. Narrative structure,
            the global organisation of story content, was scored using a high-point
            analysis (Labov & Waletzky, 1967) based on six key elements: (1) orientation
            (2) two complicating actions, (3) climax and (4) resolution. Each section is
            awarded 1 or 2 points depending on the amount of detail given. A further point
            is awarded for: (5), evaluation (i.e., where the child presents their own
            perspective on the characters’ feelings or expresses their own views).
            Responses to questions were also included; and (6) narrative sequence (i.e.,
            correct order of story episodes). A maximum of 12 points was thus awarded for
            narrative structure. After extensive piloting and comparison of English
            narrative norms from other research, a scoring scheme was created to assess
            micro-level narrative skills in English for the same stimuli: a score for
            grammatical markers and narrative devices was generated by considering
            narrative cohesion, grammatical morphemes, and narrative and evaluative
            devices (Maximum 29 points). Responses to both the spontaneous story and the
            probe questions were included in scoring. Narrative cohesion included the use
            of referents to specify a character, and the use of conjunctions. A
            referential cohesion score (maximum 4 points) was based upon the first
            introduction of the story character(s) and whether references were
            consistently clear throughout. A maximum of 2 points for first introduction
            was scored in the following way: 0 points for no first mention 1 point for
            unspecified pronoun (e.g., the girl) 2 points for non-presupposing
            introduction using indefinite article(s) and noun or number (e.g. a girl).
            Reference maintenance points (maximum 2) were assigned based on the following:
            0 points for unclear referencing 1 point for some ambiguity in references 2
            points for clear references throughout (i.e., uses pronouns and contrasts
            characters effectively). A conjunction score (maximum 6 points) comprised the
            use of basic coordinating conjunctions (e.g., and, but), the use of logical
            markers (e.g., because, if) and the inclusion of subordinate clauses (e.g.,
            the girl picked up the spider that was crawling across the floor). A maximum
            of 2 points were awarded for each based on the following scale: 0 points for
            no inclusion. 1 point for 1–2 uses. 2 points for 3+ uses. Nine types of
            English grammatical morphemes were analysed: articles, prepositions, regular
            verb forms, irregular verb forms, agreement in grammatical gender, agreement
            in grammatical person, use of negatives and use of modal verbs (maximum 15
            points): 1 point was awarded for inclusion and correct use of articles
            throughout the narrative A maximum of 2 points were awarded for inclusion and
            correct use of prepositions: 0 points for no prepositions or rare correct use
            1 point for including 2–3 prepositions (at least 2 different examples e.g.,
            on, in, at) correctly (accuracy <50%) 2 points for 4+ prepositions correctly
            used (accuracy >90%) A maximum of 2 points each was rewarded for regular verb
            inflections (e.g., she walked/walks/was walking), irregular verb forms (e.g.,
            he bites/he bit/had bitten), agreement in grammatical gender (e.g.,
            sheshookherhead) and agreement in grammatical person (e.g., theywerebrother
            and sister) using the following scoring method: 0 points when errors were made
            most of the time (>50%) 1 point when errors were made some of the time
            (10–50%) 2 points when errors were rarely made (<10%) Errors included both
            omissions (e.g. the girl walk__ in; the boy __ angry) and commissions (e.g.
            the boy throwed the spider). A maximum of 2 points each were awarded for the
            correct inclusion of negatives, e.g. the girl didnt/did not know (excluding “I
            dont know”) and modal verbs, e.g., theremighthave been, heshouldhave got)
            using the following scoring method: 0 points for no usage 1 point for 1–2
            occurrences 2 points for 3+ occurrences A maximum of 4 points was awarded for
            the inclusion of narrative and evaluative devices. One point was awarded for
            the inclusion of one or more examples of each of the following: Direct (e.g.
            the girl said no) or indirect speech or thought (e.g., the girl thought to
            herself) Adjectives e.g., lazy, hungry, bored Adverbs describing manner e.g.,
            slowly, cunningly, carefully Intensifiers e.g., very, really, so; or de-
            intensifiers e.g., quite, nearly, almost Finally, the story comprehension and
            inferencing questions were allocated a maximum of two points per question
            depending on whether responses were partially or fully correct. The questions
            tested whether the children had understood the content of the story, as well
            as the intentions of the story characters (maximum 4 points; see Appendix A
            for example correct responses).

            <hss>Reliability of the narrative production test</hss>

            As there is no previously published reliability data for the Narrative
            Production Test used for English, intra-rater reliability of the test was
            assessed by two independent coders. All narratives were scored by both coders
            for structure and content, and relevance of answers to the probe questions.
            High inter-rater reliability was found for each score on each sub- scale of
            the test (Content: r (128) =0.98, p <0.001; Structure: r (128) =0.95, p <
            0.001; Questions: r (128) =0.92, p < 0.001). The second experimenter also
            scored 110 randomly selected narratives (86%) for grammatical markers and
            narrative devices, and inter-rater reliability was also excellent (r (110) =
            0.96, p < 0.001). Thirteen of the narratives (10%) were randomly selected and
            scored a second time by the same coder. An overall total score was calculated
            and a strong correlation between scores at both time points was found (r (13)
            = 0.98, p < 0.001).

        <hss>Vocabulary</hss>

        The expressive one word picture vocabulary test (EOWPVT; Brownell, 2000) was used
        to assess single word vocabulary production. The EOWPVT was standardised on
        children with normal hearing, but has frequently been used with deaf children as a
        measure of English vocabulary (Geers, 1997; Kyle & Harris, 2006; Moeller, 2000).
        The full test was administered as per the instruction manual. The children are
        presented with single pictures that test knowledge of primarily simple nouns
        (e.g., train, pineapple, kayak), but also some verbs (e.g., eating, hurdling), and
        category labels (e.g., fruit, food). The EOWPVT was developed in the USA and so a
        few pictures (n = 3) were substituted with alternative pictures to make the test
        more culturally relevant for children in the UK (e.g., raccoon with badger).

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Independent t-tests were used to compare group means on narrative skills using raw scores.
Significance criteria were set at p < 0.05 and Bonferroni corrections were applied to all
multiple comparisons. A series of correlations were carried out to explore the
relationship between narrative ability and age, nonverbal ability, and vocabulary. A
hierarchical multiple regression was conducted to explore the extent to which vocabulary
contributed uniquely to performance on the grammatical markers and narrative devices
(micro-level narrative skills). Analyses were performed using SPSS v22.0. Post hoc power
analysis (G*Power 3.1 software) showed sufficient power for the total group (n = 126,
effect size (d) =0.64, Power = 0.97).

<hs>  Preliminary analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

Overall, the hearing group children (M = 41.91, SD = 7.78) had a significantly higher
total Narrative Production Test total score (maximum score = 61) than the deaf group
children (M = 35.88, SD = 10.70; t (124) = −3.65, p <0.001, Cohen’s d =0.64). The hearing
children (M = 108.86, SD = 11.04) also had significantly higher standardised EOWPVT scores
than the deaf children (M = 91.95, SD = 18.87; t (124) = −6.08, p <0.001, Cohen’s d =
1.09). To account for the heterogeneity of the deaf children, within group differences on
overall scores on the Narrative Production Test were investigated according to type of
hearing amplification (CI vs. HA) and level of hearing loss, groups were matched on age
and non-verbal ability (ps > 0.05). No significant difference in total Narrative
Production Test scores were found between deaf children using CIs (N = 22; M = 34.5, SD =
10.14) and those deaf children wearing hearing aids (N = 37; M = 36.70, SD = 11.07; t (57)
= −0.76 p = 0.45, Cohen’s d = 0.21). There was no relationship between severity of hearing
loss in the better ear and total narrative scores (mild-moderate: N = 10; M = 35.1, SD =
13.52, severe: N = 25, M = 36.48, SD = 9.82 or profound: N = 22; M = 34.72, SD = 10.49; p
all > 0.05).

<hs>  Main group comparisons</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Table 5 displays means, standard deviations, group comparisons and effect sizes for the
children (deaf and hearing) on each of the narrative skills subscales: content, structure,
grammatical/narrative devices, and inference questions.

        <hss>Macro-level narrative skills</hss>

        Narrative content. For total scores on story content, the t-test showed that there
        was no significant difference between deaf and hearing children, suggesting the
        level of information recall in the narrated stories was similar in the two groups
        of children. Narrative structure. Similarly, there was no significant difference
        between groups on overall scores for global narrative structure indicating that
        the deaf and hearing children were similar in their ability to organise story
        content following key elements (i.e., including detail on the orientation,
        complicating actions, climax, resolution, evaluation and story structure).

        Micro-level narrative skills: grammatical markers and narrative devices

        Overall, the deaf group children obtained significantly lower scores for
        grammatical markers and narrative devices (p < 0.001; Table 5). Cohesion. The deaf
        children’s scores on the referential cohesion scale was significantly poorer then
        the hearing children (p < 0.001; Table 5), suggesting that hearing children made
        better use of reference (e.g., the use of anaphoric pronouns was less ambiguous).
        The hearing group also scored significantly higher on the conjunction score (p <
        0.001), showing that they were more sophisticated in their use of temporal
        conjunctions and subordinate clauses in order to express semantic relations across
        their stories. Grammatical morphemes. The deaf group’s score for grammatical
        morphemes was significantly lower than the hearing group (Table 5). This suggests
        that deaf children made more omissions and errors with words that carry
        grammatical information. An example from an 8-year-old deaf child illustrates
        incorrect regular and/or irregular verb inflections, either omissions (e.g., he
        pick_ it up) or commissions (e.g., he putted); the omission of articles (e.g., on
        _ floor); and the omission of prepositions (e.g., he putted it _ the sandwich):
        “Then he saw the spider on floor. Then he pick it up. Then he putted it the
        sandwich.” Narrative and evaluative devices. There was no significant difference
        between groups for the use of narrative and evaluative devices (Table 5),
        suggesting that the deaf and hearing children were equally able to use evaluative
        language such as adjectives (e.g., the spider was horrible) or spoken information
        about the dialogue (e.g., the boy said, “give me the sandwich”).

        <hss>Comprehension and inference questions</hss>

        Finally, the hearing group’s mean score on the story comprehension and inference
        questions was significantly higher than the deaf group children (p < 0.001; Table
        5) and the effect size was large (Cohen’s d = 0.74). This suggests that on average
        the hearing children demonstrated greater understanding of the underlying messages
        and provided more detailed explanations based on inferencing of the reasons for
        the characters’ actions. Appendix B shows two example narrative transcripts of a
        deaf and hearing child to further illustrate the group differences found in
        narrative abilities.

<hs>  Predictors of performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Age and non-verbal ability were first investigated as predictors of performance on the
narrative skills. Deaf children’s age was found to correlate moderately with scores of
story content, r (57) = 0.47, p < 0.001, and structure, r (57) = 0.47, p <0.001, but not
for inference questions or grammatical markers and devices. For hearing children, age had
a weak-moderate correlation with all of the narrative skills (Content: r (65) = 0.39, p
<0.001; Structure: r (65) = 0.38, p = 0.002; Inference questions: r (65) = 0.30, p =0.01;
Grammar: r (65) = 0.33, p = 0.006 ps≤.05), and non-verbal ability (WASI matrix) correlated
weakly with grammatical markers and narrative devices, r (65) = 0.34, p =0.004. Table 6
shows partial correlations (controlling for age and non-verbal ability) between vocabulary
(EWOPVT) and narrative skills for both groups. The vocabulary measure (EOWPVT) correlated
strongly with deaf children’s use of grammatical markers and narrative devices scores (p <
0.001) and there were weaker correlations with scores on inference questions and narrative
structure (p < 0.05). The scatterplot in Fig. 1 illustrates the strong positive
correlation between the residual scores of grammatical markers and vocabulary for deaf
children. Vocabulary (EOWPVT) correlated weakly with narrative structure (p<0.05), but did
not correlate with any of the other hearing children’s narrative skills (all ps >0.05).
The relationship between each subscale of the Narrative Production Test showed a moderate
to strong correlation between each section for deaf children. For the hearing children,
mean scores on narrative content and structure strongly correlated, but the correlations
with grammatical markers, while significant, were weaker (Table 6). There were no
correlations between inference questions and other narrative subscales for hearing
children. As performance on the grammatical markers and devices narrative subscale was
weaker for deaf children we wanted to explore the contribution of vocabulary as a measure
of language ability to children’s performance on this subscale, over and above age,
nonverbal ability and a diagnosis of deafness. A hierarchical multiple regression was
carried out across all participants (Table 7). In the first stage of the analysis, non-
verbal ability (WASI matrix) and age were entered as independent control variables (IV) at
step 1. The resulting multiple regression equation was statistically significant, F (2,
123) = 7.91, p =0.001, adj. R2 = 0.10. At step 2, with the entry of EOWPVT scores into the
equation, there was a statistically significant increment in the prediction of variability
in the children’s grammatical markers and narrative devices score, F (change) = 60.73, p
<0.001. The overall model remained significant, F (3116) = 26.90, p <0.001, R2 =0.40,
accounting for an additional 30% of variance. At step 3, a dichotomous IV: deafness (1,
deaf; 0, hearing) was additionally entered as a dummy variable. The model remained
significant, (F (4, 115), = 22.96, p < 0.001) and group accounted for only a further 3% of
the variance (R2 =0.43). The final beta weights indicated that EOWPVT scores, age, and
deafness all significantly independently contributed to predicting performance on
grammatical markers and narrative devices. Therefore, children’s vocabulary skills (EOWPVT
scores) contributed significantly to predicting variability in performance on grammatical
markers subscale even after controlling for age and diagnosis of deafness.

<h>DISCUSSION</h>
----------

As deaf children are starting to communicate exclusively in spoken language, the main aim
of the current study was to compare deaf and hearing children’s narrative ability in
spoken English at both macro and micro levels. Narrative is an important skill for
children to master for several social-emotional and educational functions. A different
method of elicitation was employed from the conventional picture prompt and verbal story
retell, by showing all children a non-verbal story in video format, in order to reduce the
demands on deaf children’s auditory memory. As predicted, there were no differences at the
macro level of narrative (content and structure) between deaf and hearing children.
Additionally, both groups of children displayed the same pattern of improved performance
for content and structure with age. However, there were clear differences in micro-level
skills; in particular, the deaf children’s performance was significantly poorer in terms
of grammatical morphemes and narrative cohesion. These micro-level findings are consistent
with previous studies, but our other results contrast with other findings that show that
deaf children also lag behind typically developing peers on global narrative skills (Boons
et al., 2013a; Crosson & Geers, 2001; Worsfold et al., 2010). There was also a key
difference in narrative understanding and inferencing as measured by the probe questions,
suggesting that linguistic development is important for deeper understanding of
narratives. Equivalent performance between oral deaf and hearing children in narrative
structure and content indicates that if the task is designed so that assessing story
retell ability is not dependent on receptive language skills, deaf children are able to
tell a coherent story at the global level. The dissociation between deaf children’s
narrative macro- and micro- structure in the present study suggests that the latter is
more dependent on purely linguistic and pragmatic skills. In support of this suggestion,
micro-level narrative skills correlated strongly with deaf children’s vocabulary, whereas
in terms of macro-level narrative skills, there was only a weak correlation between
vocabulary and narrative structure for both groups. While micro-level narrative skills
depend on an elaborate vocabulary and syntactic cohesion to clearly mark the temporal and
casual nature of events (Curenton & Justice, 2004), macro-skills may depend less on
linguistic skill and more on general cognitive mechanisms. The videotaping of all children
in the present study enabled the coding of gesture to capture some additional content in
children’s narratives that would otherwise be overlooked. While the children predominantly
used co-speech gestures in their story telling, both deaf and hearing children used a
number of representational gestures in their narratives to convey particular sequences of
events (e.g., gesturing holding a sandwich up to the mouth to represent the episode where
the girl pretends to eat a sandwich). Even deaf children with very limited language,
reliant on an invented gesture system, have previously been found to recount stories of
the same type and structure as hearing children when non-linguistic gestures have been
coded (Van Deusen-Phillips et al., 2001). The findings of the present study support the
argument that despite language delays in vocabulary and micro-level devices, deaf children
experience social interactions, which can trigger an interest in recounting and linking
past events. It is possible that the story telling function is robust in spite of reduced
linguistic capabilities (Morford & Goldin-Meadow, 1997; Van Deusen-Phillips et al., 2001).
Strengthening this possibility, deaf and hearing children showed comparative performance
for narrative and evaluative devices including the use of direct or indirect speech,
intensifiers, adjectives and adverbs of manner. This suggests that deaf children are aware
of the importance of these elements in story telling. Consistent with previous studies,
the deaf and hearing children’s performance was markedly different for micro-level skills
that are dependent on more efficient linguistic and pragmatic abilities (Boons et al.,
2013a; Crosson & Geers, 2001; Guo et al., 2013; Worsfold et al., 2010). The use of
grammatical morphemes was notably different between the two groups of children. Deaf
children were more likely to over-generalise regular verb rules (e.g., the boy putted),
and make errors in the omission of articles, prepositions and verb inflections. This
finding is expected because previous studies have found that even a moderate hearing
impairment can impact a deaf child’s ability to perceive these difficult to segment
morphemes, which leads to less well instantiated representations (McGuckian & Henry, 2007;
Moeller et al., 2010). The deaf children also used fewer conjunctions and subordinate
clauses, which are important for linking semantic representations across a narrative
(temporally and causally) to form a well-structured, cohesive story (Crosson & Geers,
2001). The deaf group also had a greater tendency to introduce characters with ambiguous
references. For example, using a definite article (the), rather than indefinite article,
(a) plus noun (boy). In addition, they were also more likely to refer to both characters
(i.e., the girl and the boy) as “he” throughout the story, creating confusion. These
referencing errors and lack of syntactic cohesion suggest some deaf children are
unfamiliar with discourse and pragmatic conventions presumably linked to reduced exposure
to direct and indirect narrative language, and/or lack the pragmatic skill that requires
an awareness of the needs and perspective of the listener (Bruner, 1986; Morgan et al.,
2014). Therefore, despite being able to convey the rudimentary elements of the content and
structure of a story, these findings suggest that a disruption to language acquisition has
a detrimental effect on narrative skills in oral deaf children. Linked to social-cognitive
influences on narrative, the deaf group provided less relevant and/or detailed answers
than the controls to probe questions that focused on understanding a characters’
intentions or feelings. While deaf children are able to use emotion and mental state terms
in their narratives (e.g. the boy was angry), our results point to a difficulty in
determining the psychological causes of these mental states. Studies investigating
narrative skills in children with autism (Tager-Flusberg & Sullivan, 1995) and SLI
(Norbury et al., 2014) have also found this distinction between emotion and mental states.
The deaf children’s poorer performance in answering the probe questions in the present
study was expected given that deaf children generally show difficulty with theory of mind
(false-belief) tasks (Peterson & Slaughter, 2006). Language ability is strongly related to
theory of mind understanding in typically developing (Milligan et al., 2007) and deaf
children (Schick et al., 2007). For the deaf group in the current study, grammatical
markers showed a moderate positive correlation with the probe questions, suggesting that a
threshold of linguistic skills are necessary to make causal links about others’ mental
states and actions. The relationship between vocabulary and probe questions, while
significant, was weaker. The precise role of language ability remains uncertain, but it is
thought that reduced exposure to conversational interactions caused by deaf children
missing out on the conversations that surround them in hearing families and educational
environments is likely to impact the ability to give emotional explanations and engage in
causal discourse (Morgan, Hjelmqist, & Meristo, in press; Rieffe, Terwogt & Cowan, 2005).
It is important to highlight that a number of previous studies have shown that groups of
deaf children implanted with a CI at a very early age (Boons et al., 2013a) and those with
an early diagnosis of deafness (Worsfold et al., 2010) perform at the same level as their
hearing peers in micro- as well as macro- narrative skills. However, Boons et al. (2013a)
acknowledged the variability in spoken language skills within the early implanted
children. In the present study, there was no difference between deaf children with
conventional hearing aids and those with CIs in narrative performance; neither was there a
difference based on level of hearing loss. However, among the group of CI users in the
current study there was large variation in the age at implantation and length of exposure
to auditory input, which might explain the lack of consistent findings. In conclusion, the
deaf children in the present study were able to construct a narrative at the macro level,
but showed a weakness with micro-structural devices that are more dependent on finer
linguistic and pragmatic skills. More research is needed to explore the factors that drive
the development and possible dissociation of macro- and micro- narrative skills in deaf
children. The narrative task and subsequent coding presented in this study also has the
potential to be used with other groups of children and to therefore have a broader impact
across the field. The study of deaf children compared with other groups with atypical
narrative skills will be informative in delineating the particular influences of sensory
and neuro-cognitive impairment on this crucial aspect of language development.


<h>REFERENCES</h>
----------

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  [8] Tinne Boons, Leo De Raeve, Margreet Langereis, Louis Peeraer, Jan Wouters, Astrid van Wieringen. Expressive vocabulary, morphology, syntax and narrative skills in profoundly deaf children after early cochlear implantation. doi:10.1016/j.ridd.2013.03.003
  [9] Nicola Botting. Narrative as a tool for the assessment of linguistic and pragmatic impairments. doi:10.1191/0265659002ct224oa
  [12] Patricia L. Cleave, Luigi E. Girolametto, Xi Chen, Carla J. Johnson. Narrative abilities in monolingual and dual language learning children with specific language impairment. doi:10.1016/j.jcomdis.2010.05.005
  [13] Elizabeth R. Crais, Nina Lorch. Oral narratives in school–age children
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  [22] Ling Yu Guo, Linda J. Spencer, J. Bruce Tomblin. Acquisition of tense marking in english-speaking children with cochlear implants: A longitudinal study. doi:10.1093/deafed/ens069
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<ART>Non-coding genetic variation shaping mental health
==================================================

Authors: John P. Quinn, Abigail L. Savage, Vivien J. Bubb
DOI: 10.1016/j.copsyc.2018.07.006
Year: 2019  |  Pages: 18-24
ASJC codes: 3200

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Over 98% of our genome is non-coding and is now recognised to have a major role in orchestrating the tissue specific and stimulus inducible gene expression pattern which underpins our wellbeing and mental health. The non-coding genome responds functionally to our environment at all levels, encompassing the span from psychological to physiological challenge. The gene expression pattern, termed the transcriptome, ultimately gives us our neurochemistry. Therefore a major modulator of mental wellbeing is how our genes are regulated in response to life experiences. Superimposed on the aforementioned non-coding DNA framework is a vast body of genetic variation in the elements that control response to challenges. These differences, termed polymorphisms, allow for a differential response from a specific DNA element to the same challenge thus potentially allowing ‘individuality’ in the modulation of our transcriptome. This review will focus on a fundamental mechanism defining our psychological and psychiatric wellbeing, namely how genetic variation can be correlated with differential gene expression in response to specific challenges, thus resulting in altered neurochemistry which consequently may shape behaviour.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The human genome has evolved to include a combination of both highly conserved regions of
regulatory non-coding DNA (ncDNA) found across many species and human-specific regulatory
DNA elements which together act to regulate expression of mRNA. This combination of DNA
elements allows determination of where, when, how much and for how long, genes are
expressed in the human brain in response to normal developmental, psychological and
physiological cues, Figure 1. Many of these elements exhibit genetic variation which is
not only associated with risk for a specific condition, but has also been demonstrated to
alter the regulatory properties of the gene. The functional interpretation and analysis of
ncDNA variation can be initially addressed in silico by overlaying its position on
databases containing characterised and predicted functional elements within the genome,
Box 1. The most easily accessible free database is the Encyclopaedia of DNA Elements
(ENCODE; https://www.encodeproject.org/) which is a collaboration of research groups
funded by the National Human Genome Research Institute [1,2••], this can be used in
combination with a plethora of other database browsers [3] such as the University of
California Santa Cruz (UCSC) Genome Browser (http://genome.ucsc.edu/) [4]. This review
will begin with an introduction to the most conserved regulatory regions in the genome and
how these may be functionally modified by the simplest and most extensively studied class
of genetic variation, single nucleotide polymorphisms (SNPs). The review will then focus
on human regulatory elements that are associated with neuropsychiatric conditions which
are larger blocks of DNA variation such as variable number tandem repeats (VNTRs) and non-
long terminal repeat (non-LTR) retrotransposons, Box 2.

<h>EVOLUTIONARY CONSERVED REGIONS</h>
------------------------------

Evolutionary conserved regions (ECRs) in the genome can be easily found using the ECR
browser (https://ecrbrowser.dcode.org/) [5]. ECRs in this browser are typically defined as
regions of sequence within the human genome that retain 70% or more sequence identity over
a window of 100 bases when compared to the corresponding region of sequence in other
species, this will frequently include exons in coding DNA. However, Pennacchio et al.,
were amongst the first to demonstrate that ECRs in the non-coding DNA (ncECRs) could be
important, particularly in directing gene expression in the CNS. They determined by use of
a transgenic mouse model that whilst ncECRs could direct expression in a broad range of
anatomical structures in the embryo, the majority of the ncECRs tested directed expression
to various regions of the developing nervous system [6]. Subsequently, consistent with
this, a third of paralogous ncECRs examined were predicted to have regulatory activity in
the brain [7], for example, deletion of ncECRs in the neuronal transcription factor Arx
resulted in substantial alterations of neuron populations and structural brain defects in
a trangenic model [8]. Furthermore, the combinatorial complexity of gene expression was
exquistely demonstrated in a transgenic model of craniofacial morphology in which the
action of multiple ncECRs driving expression of many genes resulted in a vast array of
facial differences [9••]. These studies demonstrated that ncECRs can have important
transcripitonal regulatory properties, therefore the expectation is that polymorphism in
such domains has the potential to modify interactions with transcription factors and thus
affect regulatory function.

<h>SINGLE NUCLEOTIDE POLYMORPHISMS</h>
-------------------------------

Early studies of genetic variation correlated with mental health focused on DNA variation
in exons encoding proteins. Most of these studies addressed SNPs; thus a SNP that changed
an amino acid (non-synonymous change) or resulted in a truncation of the protein could be
mechanistically relevant as it could alter protein function. However, with technological
advances the ability to address SNPs in genome wide association studies (GWAS) rather than
solely exons, demonstrated that the vast bulk of SNP variation associated with behavioural
and psychiatric conditions was in ncDNA [10,11]. GWAS has led to significant discoveries
in defining some of the genes involved in neuropsychiatric disorders and demonstrated
there is genetic overlap between many of the major psychiatric disorders [12,13]. In
several examples the proteins identified can work together to alter a key pathway
underpinning wellbeing and mental health, such as those modifying calcium signalling [14].
Understanding the mechanistic significance of SNPs in ncDNA for a specific condition has
been a much more difficult task than for SNPs found in exons. A SNP in ncDNA could be
tagging a regulatory domain 10K+ bases from itself (a tagging SNP is representative of a
large section of DNA that is inherited as one, thus the SNP is not the causative agent but
rather highlights a region of DNA). Analysis of SNP variation within ENCODE and associated
data sets can determine if it is present in a genomic region defined as a regulatory
domain. In this scenario, the SNP could affect the efficiency or specificity with which a
transcription factor, proteins which modulate the process of transcription, would bind to
this regulatory DNA sequence, Figure 2. We and others demonstrated that SNP polymorphisms
in ncECRs which correlated with known behavioural problems could modify the regulatory
properties of the ECR including those associated with depression located in BDNF, BICC1
and galanin genes [15–19]. Furthermore multiple ncECRs may be required for appropriate
gene expression, for example eight conserved ncECRs were identified at the schizophrenia-
associated MIR137/DPYD locus of these, six were shown to be positive transcriptional
regulators, and two negative transcriptional regulators in a human cell line model
[18,19]. Bioinformatic analysis of this locus using the Psychiatric Genomics Consortium
GWAS dataset for schizophrenia highlighted five of the ncECRs had genome-wide significant
SNPs in, or adjacent to their sequence [11]. Epigenetic marks which are indicative of
active or inactive chromatin, are often found at regulatory DNA. Genetic variation such as
GWAS risk SNPs, can effect such epigenetic parameters impacting on long term regulatory
changes in response to challenge [20]. Both local (gene specific) and global (multigene)
epigenetic changes have been implicated in neuropsychiatric disorders [21,22] and the NIH
Roadmap Epigenomics Consortium (http://www.roadmapepigenomics.org/) data can be utilised
to analyse such data. For example, local methylation variation at the glucocorticoid
receptor gene has been associated with prenatal and postnatal depression [23•] and global
differences in methylation in astrocytes have been associated with depression [24].
Simplistically, methylation of regulatory regions is considered a repressor of
transcription as it interferes with transcription factor binding by limiting the
accessibility of specific DNA recognition sequences. The ability to rapidly address
genetic variation on a ‘road map’ of regulatory domains has allowed the development of a
significantly better understanding of how the ncDNA GWAS SNPs can be mechanistically
involved in mental health issues [25]. This can be further updated within the UCSC browser
which permits new, novel data to be overlaid on the existing data from ENCODE.

<h>VARIABLE NUMBER TANDEM REPEATS</h>
------------------------------

SNP variation is not the only example of ncDNA variation that can affect the regulation of
gene expression. Many of the best characterised genetic polymorphisms correlating with
mental health issues are found in repetitive DNA, Figure 2. These include the VNTRs [26],
examples of which have been identified in key behavioural and mental health-related genes.
VNTRs have been demonstrated to be both biomarkers and transcriptional regulators in genes
such as the serotonin transporter, the dopamine transporter and monoamine oxidase A
[21,22,27–32]. In these three examples, the primary DNA sequences of the VNTRs are rapidly
evolving such that humans have their own specific VNTR sequences. All three of these
monoaminergic genes contain a minimum of two VNTRs that have been demonstrated to act both
independently and synergistically as transcriptional regulators whose function is further
modulated by the repeat copy number within the VNTR [21,29,31]. The copy number of the
repeat itself is also a biomarker for good mental health and wellbeing thus correlating
function with phenotype [27,28,31,33,34]. Perhaps not unexpectedly VNTRs and GWAS SNPs in
the same promoter may act additively or synergistically to regulate gene expression. This
is exemplified by one of the promoters of the schizophrenia candidate risk gene, MIR137
[35,36•], where experimentally in vitro, the VNTR in the promoter can support differential
reporter gene expression based on the copy number of the repeat within the VNTR, and
inclusion of the promoter region encompassing the GWAS SNP can further modulate expression
depending on the allele of the SNP present. This illustrates a route to identifying the
potential functional significance of non-coding variants in transcriptional or post
transcriptional regulatory mechanisms in areas distinct from the region of the DNA in
which the GWAS SNP is found. The rapid evolution of VNTRs has been noted more globally for
contributing to primate evolution; analysis in humans and non-human great apes identified
that genes with VNTRs have higher expression divergence than those without [37]. The
association of VNTRs with gene expression is reflected in the finding that VNTRs are
enriched in promoter regions and locations close to transcriptional start sites for mRNA
expression [26,38,39]. Generally, VNTRs have not been analysed as extensively as SNPs
which may be attributed to the requirement to perform PCR to genotype each VNTR target and
the inability to accurately identify such regions in the initial short read whole genome
sequencing protocols. Improved depth and coverage in whole genome sequence combined with
the development of bioinformatic programmes such as ExpansionHunter may improve the
association of VNTRs and other repeat variants with neuropsychiatric conditions [40].

<h>NON-LTR RETROTRANSPOSONS</h>
------------------------

Non-long terminal repeat (non-LTR) retrotransposons are mobile DNA elements that can copy
and paste themselves into new genomic loci and are therefore polymorphic for their
presence or absence at specific loci in the genome. These retrotransposable elements
(RTEs), also known as ‘jumping genes’, can range in size from a few hundred to 6000 base
pairs and have been shown to be major modulators of gene expression at several levels.
Non-LTR retrotransposons comprise three classes, long interspersed nuclear element 1
(LINE-1), Alu and ‘SINE-VNTR-Alu’ (SVA), Figure 2. LINE-1 expression has been implicated
in many neuropsychiatric conditions such as depression [41], addiction [42], schizophrenia
[43–45] and autism [46]. The other two classes have also been implicated in CNS function,
for example variation in the Alu sequence within an intron of the TOMM40 gene is
associated with non-pathogenic cognitive decline [47] and X-Linked Dystonia-Parkinsonism
is associated with the presence or absence of a SVA in the TAF1 gene [48••]. SVAs contain
several distinct VNTR elements and have properties consistent with transcriptional
regulation [49,50•,51]. There has been tremendous interest in RTEs, due to their ability
to make a copy of themselves which then can reinsert at a different locus in the genome of
that cell. Depending on when this occurs, it results in either novel heritable germline
variation or somatic mutation that can alter cellular function in only the individual
affected. The former generates a large reservoir of de novo genomic variation in the
population which, to date, is poorly characterised as it is very seldom annotated properly
in the DNA sequence databases. The mobilisation or ‘jumping’ of RTEs is proposed to
increase both with age within the adult CNS and to comprise one of the key mechanisms
underpinning age-related CNS problems [52••,53,54•]; several instances where this
variation has been addressed, have associated it with disease [48••,55]. More recently
bioinformatic analysis has improved to allow robust identification of RTEs using
programmes such as TEBreak (https://github.com/adamewing/tebreak) and MELT [56•].

<h>DEVELOPMENT</h>
-----------

The basic transcriptional mechanisms outlined in this review will also operate during
development. Conditions such as schizophrenia and autism are often referred to as having a
neurodevelopmental origin [57,58]. Modulation of the transcriptome during development
could have a significant effect on the wiring of the brain and therefore how information
is processed in the future. Early in vivo work using a mouse transgenic model indicated
how a human serotonin transporter VNTR could differentially affect gene expression in key
areas of serotonergic lineage based on the copy number of the repeat unit [32,59]. The
regulation of regulatory domains during development will be determined by the co-
expression of transcription factors as exemplified by the schizophrenia associated gene
CACNA1C whose expression in development mirrors that of the transcription factor EZH2 an
important regulator of the CACNA1C gene promoter [14]. An argument can be made that
alterations in the transcriptome at specific times in foetal development could result in a
physical change in neuronal connections that would be more difficult to correct than
transcriptome changes in the adult [60].

<h>SUMMARY</h>
-------

The identification of variation in the non-coding part of the genome which affects the
regulation of gene expression in part explains the often episodic nature of mental health
conditions. In addition, it offers the potential for resolution of these conditions by a
variety of interventions ranging from pharmaceutical to cognitive behavioural therapy
which modify the signalling pathways targeting specific gene regulatory domains,
modulation of the ‘stress’ driving such pathways would alter the transcriptome and hence
brain chemistry, Figure 1. A prior exposure to trauma or stress could leave a molecular
scar of that event, represented by an epigenetic change which alters parameters of
transcriptional or post transcriptional regulation in the medium to long term [61]. It is
often considered that the environmental challenge needed to affect mental health should be
severe, which is not necessarily correct. For example ‘normal’ child development could
also have an effect on mental health and wellbeing [23•,27,33,62]. Similarly a more
general approach to maintaining good mental health via diet and exercise could play a role
as they could affect the cellular signalling pathways that affect mental health [63,64].
However these issues only illustrate the complexity of defining ‘life style/environment’
and its effect on our wellbeing given the complex nature of life-long experiences in
defining our transcriptome, which in turn affects the neurochemistry that ultimately
shapes CNS function. It’s often said that the genome is the roadmap through which ‘life
style’ shapes the individual, however one can argue that the roadmap is unique for each
one of us and we all have our own route to travel [65].

<h>CONFLICT OF INTEREST</h>
--------------------

None of the authors have interests to declare, thus we are stating officially
‘Declarations of interest: none'.

<h>REFERENCES AND RECOMMENDED READING</h>
----------------------------------

Papers of particular interest, published within the period of review, have been
highlighted as: • of special interest •• of outstanding interest


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<ART>On wealth and the diversity of friendships: High social class people around the world have fewer international friends
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Authors: Maurice H. Yearwood, Amy Cuddy, Nishtha Lamba, Wu Youyou, Ilmo van der Lowe, Paul K. Piff, Charles Gronin, Pete Fleming, Emiliana Simon-Thomas, Dacher Keltner, Aleksandr Spectre
DOI: 10.1016/j.paid.2015.07.040
Year: 2015  |  Pages: 224-229
ASJC codes: 3200
Keywords: Friendships, Internationalism, Social class

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<h>ABSTRACT</h>
--------

Having international social ties carries many potential advantages, including access to novel ideas and greater commercial opportunities. Yet little is known about who forms more international friendships. Here, we propose social class plays a key role in determining people's internationalism. We conducted two studies to test whether social class is related positively to internationalism (the building social class hypothesis) or negatively to internationalism (the restricting social class hypothesis). In Study 1, we found that among individuals in the United States, social class was negatively related to percentage of friends on Facebook that are outside the United States. In Study 2, we extended these findings to the global level by analyzing country-level data on Facebook friends formed in 2011 (nearly 50 billion friendships) across 187 countries. We found that people from higher social class countries (as indexed by GDP per capita) had lower levels of internationalism-that is, they made more friendships domestically than abroad.

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<h>COMPETING PERSPECTIVES ON SOCIAL CLASS AND INTERNATIONALISM</h>
-----------------------------------------------------------

On the one hand, studies suggest that people from high social class groups are action-
oriented in connecting with others (Keltner, Gruenfeld, & Anderson, 2003). At the
individual level of analysis, high-social class individuals tend to feel more positive
emotion, send out more approach-related signals (such as smiles or friendly eye contact),
and approach others to the extent that they can be useful to fulfilling their needs and/or
goals (Gruenfeld, Inesi, Magee & Galinsky, 2008). Select studies find that, depending on
situational demands, people from high-social class groups tend to take responsibility and
be more inclined to assist low-social class members (Brewer, 1988; Keltner, Gruenfeld,
Galinsky, & Kraus, 2010; Overbeck & Park, 2001). In light of these processes, one might
expect upper class individuals to form more friendships across national boundaries (Maddux
& Galinsky, 2009). Objective conditions of the lives of upper class individuals—where they
work, travel to, and are educated—would make it reasonable to predict that they will have
more international friends. These findings and reasoning converge on the building social
class hypothesis: upper class individuals and people from high-social class countries
build up their international social capital through the formation of more international
friendships relative to their lower class counterparts. A competing hypothesis is found in
recent analyses of status, wealth, and social class (Kraus et al., 2012; Vohs, Mead, &
Goode, 2006). This line of reasoning holds that high social class individuals are endowed
with greater resources, and therefore less dependent upon others. As a result, the wealthy
tend to be less socially engaged with others, in particular those from different groups
than their own. In keeping with this restriction of social capital perspective, studies
have found that higher class individuals show higher patterns of nonverbal social
disengagement (e.g. doodling) compared to individuals from lower class backgrounds (Kraus
& Keltner, 2009), they prove to be less responsive to others' suffering, and they tend to
share less with others (Piff, Kraus, Côté, Cheng, & Keltner, 2010; Piff, Stancato, Côté,
Mendoza-Denton, & Keltner, 2012; Stellar, Manzo, Kraus, & Keltner, 2012). By contrast,
lower class individuals have perhaps more to gain from diversifying their social
connections and prove to be more oriented towards reaching out and connecting with others
(Piff et al., 2010). These findings and theoretical analysis lend themselves to a
competing hypothesis that we tested in this investigation, the restricting social class
hypothesis: upper class individuals will form fewer international friendships than low-
social class people.

<h>TESTING THE BUILDING AND RESTRICTING SOCIAL CLASS HYPOTHESES</h>
------------------------------------------------------------

In the present research, we tested these two competing hypotheses about who is likely to
form friendships with people from different countries than one's own. We did so in two
complementary studies, one at the individual level of analysis, and a second at the
national level of analysis. In Study 1, we tested the relationship between personal social
class (income and social class) among individuals in the United States and the percentage
of their total Facebook friends (a proxy of social relationships) that came from outside
the United States. In Study 2, we examined the relationship between every friendship made
on Facebook in 2011 and GDP per capita (as a proxy of social class). Several aspects of
the Facebook platform allow us to overcome certain classic challenges in social sciences.
First, Facebook's user base is massive, spanning over 1.3 billion users; thus, in our
second study, our findings provide insights based on data from every corner of the earth
and most walks of life. With growing concerns about the robustness of findings based on
Western, educated, student samples—indeed, even cognitive psychology findings vary
massively across cultures—such a huge, culturally, ethnically, and class mixed sample
provides a vital step forward to generalizing effects (Henrich, Heine, & Norenzayan,
2010). Second, Facebook friendship structure mirrors real-world friendships (Wilson,
Gosling, & Graham, 2012). In fact, unlike other social networking sites, real-world
friendships tend to be a precursor to becoming Facebook friends (Ross et al., 2009). These
findings highlight the validity of using Facebook friendships as a proxy for a person's
social contacts. However, even given these findings, we suggest that Facebook friendships
should ultimately be treated as a proxy for real relationships as there are almost
certainly social ties on Facebook that are with individuals that users have only met once
or not at all. Facebook friendships provide a convenient way to approximate a person's
social sphere, but there is some error in this metric. Similarly, income, social class,
and GDP per capita are powerful proxies for individual and national social class given the
central role that money plays in people's determinations of social class (Kraus, Piff, &
Keltner, 2011). Third, using Facebook friendships allow us to quantify the percentage of a
person's friends that are international without relying on self-report—thus, many classic
biases are not threats to the interpretation of the findings. Indeed, it would be
exceedingly difficult to quantify the number of international social ties a person has
since—by virtue of them being international—the individual is unlikely to see them often
and thus more likely to forget them when asked to make a list of friends. Our research
makes two principal contributions to the intergroup and social class literatures. By
demonstrating how social class underpins the creation of cross-national friendships, we
shed light on how people reach across social divides and form connections to disparate
others, a phenomenon we know to be important for cultural change, increased chances of
innovation, and less hostile intergroup attitudes (Maddux & Galinsky, 2009; Pettigrew &
Tropp, 2008). In addition to underscoring how social class is a major driver of these
cross-national friendships, we also provide support for the idea that, despite status
being beneficial in many aspects of everyday life, it affects the composition of social
networks in a way that reduces international diversity. Thus, our research strengthens and
enhances a budding line of evidence (Kraus et al., 2012; Piff et al., 2012) that social
class carries certain risks as well as advantages.

        <hss>Participants and procedure</hss>

        We recruited 1069 individuals from Amazon's Mechanical Turk who lived in the
        United States to participate in the study in exchange for $1.00. At the beginning
        of the study, participants completed a consent form which detailed all parts of
        the study. No deception was used. Of these individuals, 857 participants consented
        to authorizing our Facebook app to gather some information from their profiles
        automatically. This information included their total number of friends and their
        friends' current location—we note that friend location data was not available for
        all friends, but it was available for the majority of friends. Facebook
        researchers were not directly involved in Study 1—the data collection was done
        independently through the Cambridge team's own app. We focused only on the
        participants who had at least one Facebook friend (sample N = 815). These
        participants had on average 353 friends, and all together had 287,739 friends. For
        each participant, we examined their friends' current location, calculating the
        percentage of friends who lived outside the United States, which served as our
        metric of internationalism. In examining the internationalism histogram, we found
        extreme positive skew: the vast majority of participants had a small percentage of
        international friends (on average, 4%), with a small minority having high levels
        of international friendships. Since such outliers can extremely skew the results
        of a regression model, we followed the recommendations of Tabachnick and Fidell
        (2006), z-scoring all internationalism values, excluding any values more than 3
        SDs away from the mean, z-scoring the remaining values, excluding any values of
        the new z-scores that are 3 SDs away from the mean, and so forth until the
        z-scores revealed no scores more than 3 SDs out. This procedure left 671
        individuals for analyses (mean age = 28.6, sd = 9.2; 54% female), with
        internationalism scores ranging from 0 to 14% (mean = 4%, SD = 3%). Since these
        scores were still skewed positively, we natural log transformed the data, which
        created an approximately normal distribution of results. Importantly, we note that
        we ran all models without excluding the outliers, instead simply natural log
        transforming the data to account for skew—and all results in that procedure were
        consistent with the reported findings below. We also ran all models using a
        Poisson regression without removing any outliers, as a further alternative to
        taking the natural log, and again found the same pattern of results highly
        significant. We therefore present the results yielded by the first approach since
        it offers the best interpretability and protection from bias due to outliers, but
        note the conclusions of our paper are not dependent on the chosen method of
        analysis and/or outlier removal.

        <hss>Self-report measures</hss>

        Participants responded to two items aimed to measure their social class: (a)
        income, “What is your total annual household income?” (1 = Under $10,000, 11 =
        Above $100,000) and (b) social class, “Where would you place yourself on the
        following spectrum for social class?” (1 = Working class, 5 = Upper class).
        Participants also indicated how long they have been members of Facebook (months,
        years) and how frequently they use it (1 = Never; 5 = Several times a day). While
        there was some skew towards lower values for both these metrics, the skew was
        below 1 for both. Furthermore, when conducting all analyses using the logged
        versions of the variables, we found the same pattern of results. Thus, we have
        used the non-logged versions of the variables for ease of interpretation.

<h>RESULTS</h>
-------

We included several key control variables in all models that could potentially suppress or
confound the association between social class and internationalism. First, we controlled
for age, because we found that older individuals tend to have higher social class and use
Facebook less in our data. Second, gender is related to both social engagement (women
slightly more likely to have more friends) and social class (trending towards lower
income), so we controlled for this variable as well. Third, Facebook users with more
friends had more international friends in our data—likely because they have larger social
networks. Thus, in all our models, we controlled for participant age, gender, natural log
number of total Facebook friends, length of using Facebook, and self-reported frequency of
using Facebook. We note that all effects held even without controlling for age or gender.
However, when removing all Facebook control variables, we did not find significant
effects. This is to be expected, however, as Facebook can only function as an effective
proxy of social relationship for people who actually use Facebook; therefore, usage rates
need to be accounted for. We set up three regression models to test the building and
restricting social class hypotheses—which yielded contrasting predictions concerning
whether social class is positively or negatively predictive of internationalism. In each
model, we tested a different social class indicator to establish robustness of our
effects—specifically, in Model 1, we used income as the predictor; in Model 2, we used
self-reported social class as the predictor; and finally, in Model 3, we used a composite
of income and social class as the predictor. We did this because the two indicators of
social class often only moderately correlate with one another, and can be thought of as
objective and subjective forms of social class (Kraus et al., 2012). We found that higher
income, b = − .05, CI95(− .08, − .02), rpartial = − .13, t(477) = − 2.96, p < .01, self-
reported social class, b = − .18, CI95(− .29, − .07), rpartial = − .15, t(476) = − 3.33, p
< .01, and the composite of the two, b = − .09, CI95(− .15, − .04), rpartial = − .15,
t(479) = − 3.37, p < .01, were each negatively related to internationalism. In examining
internationalism percentages between low (− 1SD social class) and high-social class (+ 1SD
social class) individuals, the models indicate that low-social class people have nearly
50% more international friends (2.9% internationalism) than high-social class people (2.0%
internationalism). Thus, these results provide support for the restricting social class
hypothesis. Fig. 1 shows two world maps: (a) percentage of internationalism on Facebook
and (b) GDP per capita. As these maps suggest, and in keeping with the individual level
results from Study 1, there is a negative correlation between GDP per capita (national
social class) and percentage of Facebook friends that are foreign in a nation
(internationalismlog), r = − .18, CI95(− .32, − .04), t(172) = − 2.44, p = .02, thus
providing support on a global level for the restricting social class hypothesis. Examining
low-social class (− 1SD GDP per capita) and high-social class (+ 1SD GDP per capita)
countries, people from low-social class countries had on average 35% of their friendships
be international while people from high social class countries on average had 28% of their
friendship be international. We also considered potentially controlling for variables that
could influence the relationship. However, the difficulty with these variables (i.e.,
percentage of population with internet, rate of travel, immigration) is that they tend to
be heavily correlated with GDP per capita. For instance, GDP per capita and total
friendships per capita are correlated at r = .73. Thus, including them both in a model
would greatly change the meaning of both variables, and in turn change the meaning of any
potential correlation. Given these issues—and also the convergence of the global
correlation with the individual level correlations presented in Study 1 with a full set of
controls—we felt that the most prudent approach is to keep the model as a simple
correlation between GDP per capita and internationalism without adding controls. However,
net migration proved an exception to this because (a) it had a relatively moderate
correlation with GDP per capita (r = .49) and (b) it represented a potential mediation
mechanism of our effects. We therefore ran a regression model controlling for net
migration. We did not find evidence to support a relationship between net migration and
internationalism, b = .04, CI95(− .03, .12), rpartial = .10, t(172) = 1.27, p = .21; in
contrast, the effect of GDP per capita not only remained significant and negative, but in
fact increased in magnitude, b = − .03, CI95(− .05, − .01), rpartial = − .25, t(172) = −
3.34, p < .01.

<h>STUDY 2</h>
-------

In Study 1, we showed that among individuals living in the United States, self-reported
social class is negatively related to internationalism, thus providing support for the
restricting social class hypothesis for personal social class. In Study 2, we examined how
GDP per capita predicts the percentage of Facebook friendships that are international in
each nation in the world. In transitioning to data at the national level, we therefore
tested the two competing hypotheses across cultures that vary dramatically in terms of
their social values, economic development, religion, political organization, and self-
construals, thus allaying some concerns about potential biases of Western samples (Henrich
et al., 2010). It's important to note that Study 2 does not intend to extend the insights
of Study 1 at an individual level—instead, Study 2 focuses on macro-level, cultural
effects, and thus it would be premature to take its results as equivalent to conducting
individual level studies around the world to provide universal evidence for our Study 1
individual-level effect.

<hs>  Method</hs>
  ~~~~~~

Facebook provided data on every friendship formed in 2011 in every country in the world at
the national aggregate level. These data set included a total of 57,457,192,520
friendships. From these data, we knew how many friendships were made within each country
(domestic friendships) and also how many friendships were made between every country pair
(international friendships). We note that we did not receive data on individuals—but
rather only the macro-level, national sums. While most countries had at least tens of
millions of friendships formed, a small number had relatively few. Thus, we removed from
our analyses nations with less than 1 million friendships. This left 204 countries in the
sample. We quantified social class as GDP per capita in 2011 (World Bank, 2012). Full data
across all variables was available for 175 countries which make up the majority of the
global population (5,291,704,711) and Facebook's user base (952,818,100). For these
countries, we examined every domestic (a total of 48,458,812,050 friendships) and
international friendship (a total of 7,572,368,093 friendships) made on Facebook in 2011.
For each country, we calculated an internationalism score by dividing total international
friendships by total friendships (2 ∗ domestic + international)—we note that domestic
friendships were multiplied by 2 because every international friendship is counted twice
(once for each nation part of the friendship) and to keep the percentages consistent,
domestic friendships need to be counted twice (once for each person who can claim the
friendship in the nation). Since GDP per capita was highly positively skewed, we
normalized it by taking the natural log. We also included net migration per capita (latest
figures for each country from World Bank) as a control to account for the possibility of
migration explaining our effects. There was substantial skew in net migration; we
therefore logged the scores to make them more normally distributed.

<h>DISCUSSION</h>
----------

Friendships can provide wide-ranging benefits and can be closely related to health, trust
and well-being. The barriers to forming friendships with individuals from groups that
differ from one's own are well-known, and include in group bias, intergroup anxiety, and
prejudice (Pettigrew & Tropp, 2008). In the present investigation, we relied on individual
and national level data to ask how social class, both objective (income) and subjective
(perceived social class), personal (individual level) and national (nation level),
influence the likelihood of forming friendships on Facebook with individuals from
different countries. The literature on power and social class justified two competing
predictions. Given the association between power and social approach (Gruenfeld, Inesi,
Magee, & Galinsky, 2008; Magee & Galinsky, 2008), one might expect the wealthy to reach
out and form more friendships with people from different groups—the building social class
hypothesis. In contrast, given the tendency for the upper class to be socially disengaged
with other individuals (Hall, Coats, & LeBeau, 2005; Kraus & Keltner, 2009), and the well
documented tendency for lower class individuals to be more prosocially oriented to others
(Piff et al., 2010), one might expect the wealthy and higher social class to privilege
friendships within one's own group, and not have as many international friends—the
restricting social class hypothesis. In line with the restricting social class hypothesis,
our results across two studies at the micro-individual and macro-national levels showed
that people and nations with greater objective and subjective social class had fewer
international friends on Facebook. In Study 1, people who reported that they had higher
income and were from upper class categories had fewer international friends than
individuals who had lower incomes and self-identified with lower class categories. In
Study 2, wealthier countries, as indexed in per capita GDP, had fewer international
friends than poorer countries. Despite having fewer resources at their disposal, it is
actually low-social class people and poorer nations who tend to have friendship networks
populated with more international connections. These findings make a number of important
contributions to the social class and social network literatures. First, the negative link
between social class and international friendships may underscore a tendency for high-
social class people to accrue relational resources such as social support in their local
vicinity. According to the self-reinforcing account of social class (Magee & Galinsky,
2008), high-social class people tend to think and act in ways that reinforce their own
social class. However, by forming fewer international friendships (relative to their low-
social class counterparts), high-social class people may be at risk of strengthening their
local social class at the expense of improving their broader social class. Second, theory
and research highlight the value of developing weak ties to others in distant social
circles because these ties offer access to resources not likely to be found in one's
immediate social circle (Agrawal, Kapur, & McHale, 2008; Burt, 2008; Granovetter, 2005).
An encouraging sign is that low-social class people tend to have greater access to these
resources on account of having more international friendships. Thus, contrary to research
describing the plight of low-social class individuals with poor access to social resources
(Magee & Galinsky, 2008), our findings point to international friendships as a means by
which low-social class individuals can benefit from the resources inhering in social ties.
Third, our study showcases a new approach to studying internationalism at the global
level—through the usage of nation-level social media. This approach opens the doors for
new investigations of the micro- and macro-forces that promote or inhibit
internationalism. One particularly fruitful avenue is to study how cultural differences—on
dimensions such as individualism-collectivism—are related to internationalism. Several
datasets are available at the nation level that have cross-cultural scores, including
Hofstede's Cultural Dimensions (Hofstede & Bond, 1984), Schwartz Cultural Values (Schwartz
& Bilsky, 1990), and the World Values Cultural Dimensions (Minkov & Hofstede, 2010). These
scores can be used to probe the relationship between culture and internationalism in
future work. We do note that there are several important limitations to our work which
require important future extensions. First, both of our studies were correlational, and
thus making strong causal claims at this stage is premature. While we believe that it is
most likely the causal arrow that flows from social class to internationalism, explicit
experimental work is needed to test this thesis. Second, our sample in Study 1 consisted
of MTurk users which are not representative of the general US population. While MTurk
users tend to be as good—if not better—than typical undergraduate samples (Buhrmester,
Kwang, & Gosling, 2011), future work should endeavor to recruit a nationally
representative sample to further corroborate the results. Third, while we believe that
Facebook friendships offer a powerful proxy for studying social relationships—and previous
work does support the notion that Facebook friendships tend to mirror real world
relationships (Wilson et al., 2012)—further replication of the findings using traditional
self-report metrics of friendships would be a welcomed further validation of our approach.
Fourth, we do not know the place of birth of participants in Study 1; thus, it is possible
that migration flows could be a potential mechanism behind this effect. Future work should
explore this issue in greater detail. However, we do note that we found evidence against a
migration explanation in Study 2. Fifth, the effect sizes were of a small-to-moderate
nature in both Studies 1 and 2. This is not surprising as there are likely a large
multiplicity of factors involved in internationalism; however, it does highlight that we
should be careful in over-interpreting the effects and their suggested consequences. In a
world with more global connections than ever, some individuals are creating more
international ties than others. Despite the benefits of having international connections,
and the fact that high-social class people should be better positioned to travel and meet
people from different countries, our results provide one empirical demonstration as to how
low-social class people may actually stand to benefit most from a highly international and
globalized social world.


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<ART>Online recruitment and testing of infants with Mechanical Turk
==============================================================

Authors: Michelle Tran, Laura Cabral, Ronak Patel, Rhodri Cusack
DOI: 10.1016/j.jecp.2016.12.003
Year: 2017  |  Pages: 168-178
ASJC codes: 3204, 3205
Keywords: Amazon Mechanical Turk, Crowdsourcing, Infant behavior, Online research

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<h>ABSTRACT</h>
--------

Testing infants in the laboratory is expensive in time and money; consequently, many studies are underpowered, reducing their reproducibility. We investigated whether the online platform, Amazon Mechanical Turk (MTurk), could be used as a resource to more easily recruit and measure the behavior of infant populations. Using a looking time paradigm, with users’ webcams we recorded how long infants aged 5 to 8 months attended while viewing children's television programs. We found that infants (N = 57) were more reliably engaged by some movies than by others and that the most engaging movies could maintain attention for approximately 70% of a 10- to 13-min period. We then identified the cinematic features within the movies. Faces, singing-and-rhyming, and camera zooms were found to increase infant attention. Together, we established that MTurk can be used as a rapid tool for effectively recruiting and testing infants.

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<h>INTRODUCTION</h>
------------

Infants are difficult to recruit and test. Recruiting their busy caregivers requires broad
advertising, collaboration with day-care facilities or maternity hospitals, and labor-
intensive relationship building. As a consequence, it often takes long periods of time to
recruit a sufficient number of participants. Once recruited, the schedules of the
caregivers, infants, research staff members, and testing facilities must be coordinated,
and practicalities such as transport must be resolved. Given these complexities, infant
studies are relatively slow and expensive and also require patience and perseverance. This
puts pressure on investigators to minimize the number of participants recruited, and as a
result studies are sometimes under-powered, reducing their reproducibility (Peterson,
2016), reflecting a broader issue in psychology (Open Science Collaboration, 2015). Thus,
to make it easier to conduct high-quality infant research, it is imperative to find ways
in which to reduce these pressures. One solution may lie online. During recent years, the
crowdsourcing engine Amazon Mechanical Turk (MTurk) has become a central marketplace,
bringing together hundreds of thousands of workers from more than 100 countries to
complete “human intelligence tasks” (HITs) through a web browser for modest remuneration
(see Crump, McDonnell, & Gureckis, 2013, for a review; Buhrmester, Kwang, & Gosling, 2011;
Kittur, Chi, & Suh, 2008; Mason & Suri, 2011; Pontin, 2007). Often these tasks involve
image annotation, rating surveys, and demographic questionnaires using templates delivered
by MTurk (Mason & Suri, 2011; Paolacci, Chandler, & Ipeirotis, 2010). However, by
employing external websites, requestors can generate more complex tasks that meet the
demands of their experimental needs (Buhrmester et al., 2011; Goodman, Cryder, & Cheema,
2013; Mason & Suri, 2011). In combination with MTurk’s simple interface and flexibility,
this lends itself well to the fast and cost-effective collection of data. Recently,
experimental psychologists have used MTurk to obtain data from adults on simple tasks
(Lewis, Sugarman, & Frank, 2014; Piff, Stancato, Côté, Mendoza-Denton, & Keltner, 2012;
Starmans & Bloom, 2012; Sweeny, Andrews, Nelson, & Robbins, 2015). Parental report
measures of child behavior have also been documented (Schneider, Yurovsky, & Frank, 2015);
however, to our knowledge, direct testing of infants has never been attempted. Therefore,
the aim of the current study was to examine whether MTurk could be used to recruit and
test infant populations. To address this, we implemented a task that aimed to quantify
looking time to a set of video stimuli in infants aged 5 to 8 months. Specifically,
infants viewed children’s television programs, and attention was quantified by measuring
when infants fixated on the screen using their webcams.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Ethical approval was obtained from Western University’s health sciences research ethics
board. We recruited infants aged 5 to 8 months using MTurk (Amazon, Seattle, WA, USA). All
workers of MTurk remain de-identified and are referred to only by a unique worker identity
code provided by Amazon. To participate, infant caregivers agreed to the Amazon MTurk
Participation Agreement (https://www.mturk.com/mturk/conditionsofuse), which included the
declaration that they were at least 18 years old, provided informed consent, and were
required to have a webcam, speakers, and Adobe Flash. The same experiment was administered
in two independent batches differing in compensation rate. During the first batch, 63
participants were recruited over the course of a week, reimbursing each with $1.25 (U.S.).
To motivate increased participation, remuneration in the second batch was raised to $5.00,
leading to 84 participants being recruited within the following 6 days. Altogether, 147
participants were recruited. However, due to the quality control requirements of our study
and the difficulty of infant testing in general, 90 were excluded. The causes were
technical issues associated with internet connectivity bandwidth (no webcam video being
obtained from the server (n = 3), the webcam video becoming desynchronized from the movie
(n = 43), the quality of the recorded video (infant’s eyes not being visible; n = 22),
blurry video (n = 5), and the location of the webcam being changed (n = 1)). Participants
were also excluded if they were not infants (n = 11), self-reported an age outside our
specifications (n = 3), or did not fully complete the experiment (n = 2). Of the remaining
57 participants included in the study (Mage = 6.49 months, SD = 0.93), 9 were 5 months
old, 19 were 6 months old, 21 were 7 months old, and 8 were 8 months old.

<hs>  Stimuli and video recording</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ten movie clips between 9 and 13 min in length were used as stimuli. They were taken from
popular programs designed to appeal to infants and children: Baby Einstein, Blue’s Clues,
Curious George, Despicable Me, Dora the Explorer, The Program With the Mouse, In the Night
Garden, Teletubbies, Timmy Time, and Up. To present the movies and record from the webcam,
Flash was used (Adobe, San Jose, CA, USA). Content was provided from and recorded to a
computer in the Amazon cloud (Amazon) running Wowza Media Streaming Server (Wowza, Golden,
CO, USA) using real-time streaming protocols. Our software is available on request.

<hs>  Procedure</hs>
  ~~~~~~~~~

The HIT was created and posted on MTurk under the title “Infant Television Viewing.”
Participants viewed a webpage detailing compensation rate, the allotted time to complete
the HIT, the expiration date of the HIT, a short description of the task, and the required
qualifications. After accepting the HIT, participants were directed to a webpage that
provided an information sheet and asked for their informed consent. Consent was obtained
via online checkbox and button press. This was followed by an evaluation of the
suitability of participants’ computers, software, webcams, speakers, and internet
connectivity. To do this, we recorded a brief 5-s video of caregivers and their infants
and asked them to move and make sounds. This video was then played back to caregivers, and
they were asked to check a box to indicate whether or not they were able to see and hear
themselves. If they indicated they could not, they were thanked and excluded from
participation. Otherwise, they were directed to a new webpage instructing them to position
their infants on their laps in the center of the screen and in a well-lit room. This was
specified to ensure that infants’ eyes were visible while recording the webcam videos.
Once they were in a comfortable position, caregivers were instructed to press a “start”
button to commence the experiment. Then 1 of 10 pseudorandomly selected movies was
presented. Afterward, participants completed a short demographic questionnaire from which
the ages and language backgrounds of their infants were obtained.

<hs>  Video annotation</hs>
  ~~~~~~~~~~~~~~~~

The time course of overt attention was measured from the recorded webcam videos. Using the
free Anvil tool (Kipp, 2001), the experimenter and a second observer annotated when in the
movie each infant fixated on the screen. The two observers agreed in their assessment of
looking time 99.81% of the time with a corrected kappa of .41.

<hs>  Are some of the movies more engaging overall?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We first quantified overall looking time by calculating the proportion of attention in a
movie for each infant. This proportion was then arcsine transformed to increase the
normality of its distribution. To assess whether some movies were more engaging than
others, we used a two-way analysis of covariance (ANCOVA) with factors of movie (10
levels) and infant age (in months). Post hoc t tests were then used to compare pairs of
movies. Fig. 1 and Table 1 show arcsine-transformed proportions of attention by movie.
There was a main effect of movie on attention time, F(9, 25) = 3.56, p < .001, η2 = .562
(Fig. 1). Post hoc comparisons using Tukey’s HSD (honestly significant difference)
revealed that Curious George (M = .33, SE = .09) engaged infants significantly less than
In the Night Garden (M = .74, SE = .06, p < .05), Teletubbies (M = .70, SE = .09, p <
.05), and Timmy Time (M = .68, SE = .04, p < .05). Age was not found to modulate looking
time, F(3, 25) = 2.74, ns, η2 = .248.

<hs>  Are some parts of the movies more engaging to infants than others?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To determine whether the looking times were consistent within a movie, we conducted a
correlation analysis that assessed the time course of attention. Our hypothesis was that
if particular parts of a given movie were more engaging than others, greater similarity
would be seen for the time courses of attention from infants viewing the same movie than
from those viewing different movies. A “binning” technique was applied in which each time
series was divided into 0.5-s intervals and assigned a 0 (not looking) or 1 (looking). Due
to the movies having different run times, we restricted the analysis of the time-series
data to the duration of the shortest movie (552.50 s or 1105 bins). To quantify the
similarity, the Pearson correlation between the time course of each participant and each
other participant was computed. A correlation of 1 would reflect identical time courses,
and a correlation of 0 would represent no correspondence. We tested the hypothesis that
infants watching the same movie should have a more similar time course than infants
watching different movies. To do this, the mean of within-movie correlations was
calculated. This was then tested against a null distribution calculated by bootstrapping,
randomly shuffling the matrix of pairwise Pearson correlations of participants and taking
the mean of positions in the matrix that previously held within-movie comparisons. The
process was repeated 100,000 times to build the null distribution. The proportion of null
values that were greater than the true value was taken as the p statistic. Fig. 2 shows
the binned time courses of attention for each of the infants grouped by movie. By eye,
there do appear to be some places of some movies where infants start or stop paying
attention together. However, not surprisingly, there are also large individual differences
given that infants may have varying stimulus preferences or be spontaneously thinking of
different things. Therefore, we evaluated statistically whether infant attention was
modulated by the content of the movies. The correlation in the time course of attention
across participants watching the same movie was positive but weak (r = .07). However, this
was highly significant when compared with the null distribution calculated through
bootstrapping (Fig. 3; p < .001), confirming that the movie content modulated infant
attention.

<hs>  What features make the movies more engaging?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For the five movies for which cinematic annotations were available (Fig. 4), we used
linear regression to investigate what drove infant attention. Because no effect of age was
seen in the overall looking time, we collapsed across ages and grouped infants by the
movie they viewed (n = 28). From the 10 annotated features (Table 2), it was found that
singing-and-rhyming, t(27) = 2.60, p < .05, camera zooms, t(27) = 2.16, p < .05, and
faces, t(27) = 2.98, p < .01, significantly increased movie engagement (Fig. 5).

<h>DISCUSSION</h>
----------

Our exploratory study supports the principle that MTurk can be used as an efficient tool
to recruit infants. In a looking time paradigm, we showed that infants aged 5 to 8 months
were engaged by different child-directed movies more so than others, that some parts of
the movies were more engaging than others, and that the cinematic features of faces,
singing-and-rhyming, and camera zooms within the movie increased attention. No age
differences in attention were found. Most important, we report for the first time an
online experiment capable of capturing and quantifying infant behavior directly. Our
finding that infants demonstrate preference for faces and face-like stimuli even in the
midst of distracters and dynamic visual scenes is supported by a substantial existing
literature (Di Giorgio, Turati, Altoè, & Simion, 2012; Farroni et al., 2005; Franchak,
Heeger, Hasson, & Adolph, 2015; Frank, Vul, & Johnson, 2009). Similarly, our finding that
singing-and-rhyming attracts attention concurs with previous reports indicating
preferences for engaging melodies over dissonant sounds (Costa-Giomi & Ilari, 2014; Nakata
& Trehub, 2004; Trainor, 1996; Trainor, Tsang, & Cheung, 2002). High engagement toward
both of these cinematic elements has been associated with internal biases reflective of
maternal behavior and infants’ keen interest to attend to stimuli rich in social
information (Bushnell, Sai, & Mullin, 1989; Nakata & Trehub, 2004). In addition, camera
zooms also recruited increased visual attention. This agrees with recent evidence that
optic flow—structured patterns of motion across the visual field—is processed in the
brains of children aged 4 to 8 years (Gilmore, Thomas, & Fesi, 2016). Furthermore, even
neonates have mechanisms that can quantify the degree of optic flow (Jouen, Lepecq,
Gapenne, & Bertenthal, 2000). Regarding the more specific effect of optic flow on
attention, an existing report found that preschool-aged children and toddlers demonstrated
unchanged or reduced visual attention when camera zooms were present compared with when
they were absent (Levin & Anderson, 1976; Susman, 1978). These authors suggested that
camera zooms deter attention because of their tendency to disrupt the visual flow of
content by taking the viewer from a whole perspective to a part perspective. The
difference between these results and ours may be due to the different ages of the infants
tested or to the very different stimuli. For example, the camera zooms in our stimuli
served an artistic or communicative vision determined by the movie directors and, thus,
may have been more congruent with the overall content in comparison with Susman’s (1978)
study. MTurk recruitment was found to be easy and enabled us to collect a large infant
data set in a relatively short period. Unlike in the laboratory where local participants
are tested one at a time, MTurk permits workers from across the world to carry out the
same HIT in parallel (Mason & Suri, 2011; Paolacci et al., 2010). The service is entirely
online, which allows caregivers to recruit their children in the convenience of their own
homes without needing to worry about the demands that a novel environment imposes on their
children and restrictive participation time slots. Reflecting this increased convenience
for participants, payments to participants were much lower than in typical studies.
Although recruitment was easy, there was a trade-off in data quality. Due to our limited
control in screening participants and their equipment online, many workers (∼40% of our
data) needed to be excluded from our analyses. Although we implemented screening measures
to constrain who could complete and view the HIT, the majority of exclusions were due to
issues regarding internet connectivity rather than task performance. Therefore, although
the internet is inherently involved in using MTurk, in order to enhance data quality when
bi-directional video streaming is required, internet speeds could be better prescreened in
future experiments. Imposing stricter screening procedures will likely improve data
quality; however, given the low cost of recruiting participants, a feasible solution could
be to just accept a substantial rejection rate. To maximize the potential of MTurk, it
will be important to develop ways in which to eliminate as many interfering factors as
possible. In future studies, it would be beneficial to gather additional information on
the display configuration by querying information from the browser (e.g., the window size
and screen resolution) and by asking users for information (e.g., the screen size,
distance, and screen model). It might also establish, for example, whether a proxy for
viewing distance can be obtained from infant face size, as recorded with the webcam. Ways
in which to quantify lighting conditions and sound levels would also be advantageous. And
further demographics, such as the sex and socioeconomic status of the infants, could be
informative. Because the study took place in participants’ homes, the experimental context
for each participant differed. We directed caregivers on how to seat their children for
the experiment; however, we did not specify details relating to the environment in which
it should be carried out. We recognized in parts of the webcam video that there were
occasional distracters present in the room (e.g., toys, other people, telephone,
television) that potentially could have added noise to our measures. In addition, because
caregivers were aware of the movie content, they may have given unintentional cues to
their infants even though caregivers were asked to remain still. Furthermore, we did not
have control of the screen size or specify children’s viewing distance from the computer,
likely affecting the stimulus visual angle and possibly adding further noise. Furthermore,
we obtained a moderate kappa value (Viera & Garrett, 2005). Although such a value could be
attributed to both coders being relatively new to video annotating, the study’s
unconstrained viewing procedure could have made quantifying looking behavior more
subjective than studies completed in the laboratory. It will be useful for future
validations to include comparative measurements in a laboratory setting. These could not
be conducted currently in our laboratory because it was winding down prior to a shift in
location. Better understanding of the effect of online and offline contexts on infant
behavior will enable us to elucidate the extent to which virtual studies produce similar
outcomes to laboratory conditions. Emerging tools such as Lookit (https://lookit.mit.edu/)
will be valuable in conducting these studies. Ideally, appropriate recording conditions
would involve a well-lit environment where shadowing of the face is limited and where
participants’ eyes are visible. In our task, we explicitly asked for infants to be in a
well-lit room; however, we did not convey that infants’ eyes needed to be visible. Failure
to do so may have resulted in the 22 participants being omitted from analysis. Therefore,
in the future it would be beneficial for researchers to provide details pertinent to the
experiment so that tasks are more likely to be carried out properly. Furthermore, this
could potentially reduce rejection rates. In addition, online looking time paradigms
should aim to have each participant’s face in the center of the screen. Our experiment
asked parents to position their infants in the center of the webcam video to discern
whether or not the infants were looking at the stimulus. However, what was “center” for
one participant could have been definitively different for another participant. Due to the
differences in screen and webcam parameters, viewing of the stimulus was likely
idiosyncratic. As a solution, incorporation of facial recognition software could be
implemented into the research design to standardize testing procedures and improve data
quality overall. Moreover, in optimizing recording conditions, researchers should also
specify that video viewing take place in an enclosed room limited in distractions. The
opportunity to record with a webcam made employing a looking time paradigm possible. In
the laboratory, looking time paradigms have been widely used to study a variety of domains
in infants such as intentionality (Hamlin, Wynn, & Bloom, 2007; Woodward, 1998), emotion
(LaBarbera, Izard, Vietze, & Parisi, 1976; Montague & Walker-Andrews, 2001), and speech
preference (Cooper & Aslin, 1990; Maye, Werker, & Gerken, 2002). Having shown in this
study that behavior can be easily captured, reviewed, and quantified, this opens up the
possibility of putting similar paradigms and laboratory-based studies that use comparable
equipment on MTurk. This is not to say that all studies can be employed online; some
require specific equipment not readily available and, hence, require local testing;
however, we suggest that select tasks have the potential of being administered online.

<h>CONCLUSIONS</h>
-----------

Our study demonstrates that MTurk is a powerful new tool for recruiting infant
populations. We designed an online study that was capable of capturing infant behavior
directly and, in particular, that informed us of stimulus features in movies by which
infants were most engaged. Online infant testing could reduce the high costs experienced
in running experiments in the laboratory, and by removing barriers to larger samples, this
could lead to increasing data reproducibility.


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<ART>Optimistic update bias holds firm: Three tests of robustness following Shah et al.
================================================================================

Authors: Neil Garrett, Tali Sharot
DOI: 10.1016/j.concog.2016.10.013
Year: 2017  |  Pages: 12-22
ASJC codes: 3204, 3205

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

A diverse body of research has demonstrated that people update their beliefs to a greater extent when receiving good news compared to bad news. Recently, a paper by Shah et al. claimed that this asymmetry does not exist. Here we carefully examine the experiments and simulations described in Shah et al. and follow their analytic approach on our data sets. After correcting for confounds we identify in the experiments of Shah et al., an optimistic update bias for positive life events is revealed. Contrary to claims made by Shah et al., we observe that participants update their beliefs in a more Bayesian manner after receiving good news than bad. Finally, we show that the parameters Shah et al. pre-selected for simulations are at odds with participants’ data, making these simulations irrelevant to the question asked. Together this report makes a strong case for a true optimistic asymmetry in belief updating.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Numerous studies spanning behavioural economics (Eil & Rao, 2011; Krieger, Murray,
Roberts, & Green, 2016; Krieger et al., 2014; Möbius, Niehaus, Niederle, & Rosenblat,
2012), psychology (Garrett & Sharot, 2014; Kuzmanovic, Jefferson, & Vogeley, 2015;
Moutsiana et al., 2013) and neuroscience (Garrett et al., 2014; Korn, Prehn, Park, Walter,
& Heekeren, 2012; Kuzmanovic, Jefferson, & Vogeley, 2016; Lefebvre, Lebreton, Meyniel,
Bourgeois-Gironde, & Palminteri, 2016; Ma et al., 2016; Moutsiana, Charpentier, Garrett,
Cohen, & Sharot, 2015; Sharot, Guitart-Masip, Korn, Chowdhury, & Dolan, 2012; Sharot,
Korn, & Dolan, 2011; Sharot et al., 2012) have shown that people alter their beliefs to a
greater extent in response to good news than bad news. This asymmetry can lead to a
positive bias in beliefs regarding oneself, referred to as the superiority illusion
(Hoorens, 1993; Kruger & Dunning, 1999; Svenson, 1981), and in beliefs regarding one’s
future, referred to as unrealistic optimism (Calderon, 1993; Radcliffe & Klein, 2002;
Shepperd, Grace, Cole, & Klein, 2005; Weinstein, 1980, for review see Sharot & Garrett,
2016). The latter phenomenon, first described by Neil Weinstein (Weinstein, 1980), has
since been supported by a large body of evidence (Armor & Taylor, 2002; Regan, Snyder, &
Kassin, 1995; Shepperd, Helweg-Larsen, & Ortega, 2003; Shepperd, Klein, Waters, &
Weinstein, 2013; Weinstein, 1987; for a review see: Sharot, 2011, 2012). A recent study by
Shah, Harris, Hahn, Catmur, and Bird (2016) has revisited the phenomenon of optimistic
asymmetry in belief updating. The authors claim that an optimistic bias is unlikely, apart
from very specific cases including sports fans and smokers. Whilst Shah et al. present
empirical evidence from a number of experiments, findings across their studies are
inconsistent and methodological issues lie at the heart of their experimental design.
Nonetheless, the research questions they attempt to address are important and each
constitute interesting tests of the robustness of optimistic updating. In this report, we
carefully examine the work and reveal statistical, methodological and conceptual problems,
which when corrected supports the robustness of the asymmetry in belief updating. In
particular, the authors of that paper: (i) claim that not taking into account subjects’
beliefs regarding base rates can lead to misclassification of trials, which causes the
update bias; (ii) claim to show biased updating in Bayesian agents; (iii) claim to
empirically show pessimistically biased updating for positive life events. Whilst the
report may sound compelling at first read, an informed examination of the evidence casts
significant doubts on these claims. Specifically, in this report we detail that: (i)
previous studies have shown that after taking into account subjects’ base rates, exactly
as Shah et al. lobby for, an optimism update bias is still observed (Garrett & Sharot,
2014; Kuzmanovic et al., 2015); (ii) comparing human data to Bayesian agents shows that
subjects are less Bayesian when updating their beliefs in response to bad news than good
news, thus the optimistic update bias cannot be explained away as Bayesian. Shah et al.’s
simulations of Bayesian agents rest on specific parameters that are incompatible with
human data; (iii) Shah et al.’s finding of a pessimistic update bias for positive events
is due to a confound in the set of stimuli they used. When avoiding this confound no
pessimistic update bias is observed for positive events.

<hs>  Misclassification argument is of no empirical consequence</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In their paper (Shah et al., 2016), Shah et al. outline an issue that has been described
and resolved in two previous papers (Garrett & Sharot, 2014; Kuzmanovic et al., 2015). The
basic claim (outlined previously in Garrett & Sharot, 2014) is that participants may hold
one estimate regarding their own likelihood of experiencing an event and another regarding
the likelihood for someone like them. Participants then receive information regarding the
likelihood of “someone like them” to experience a specific event. Trials are classified
according to whether the information is better or worse than the participant’s estimate of
their own likelihood of experiencing that event. One can imagine a situation where a
participant believes their own likelihood of being robbed, for example, is 10% but
believes the likelihood for someone like them is 40%. They then learn that the likelihood
for someone like them is in fact 30%. That trial will then be classified as a “bad news”
trial (because 30% is worse than 10%) when in fact it should be classified as a “good
news” trial (because 30% is better than 40%). This concern has been empirically tested and
resolved before (Garrett & Sharot, 2014; Kuzmanovic et al., 2015). In two previous
studies, participants’ estimates of base rates were elicited in addition to their self-
estimates. Trials were then classified according to whether provided base rates were lower
or higher than participants’ estimated base rates.1 In both studies, an optimism update
bias persists even after this classification method is applied (Fig. 1). This is because
only a small number of trials are in fact misclassified (Garrett & Sharot, 2014).

<hs>  Optimistic update bias cannot be explained away as Bayesian</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Previous studies have found that subjects are less Bayesian in updating their beliefs when
receiving bad news than good news, consistent with the idea that asymmetric updating is
not purely Bayesian (Eil & Rao, 2011; Möbius et al., 2012). Shah et al. test this same
question using the belief update task for future life events. Their findings, across four
studies, were inconclusive. We thus employed the same analysis carried out by Shah et al.
on our previously published set of data from 32 participants (Garrett & Sharot, 2014),
also classifying trials as advocated by Shah et al. (see Section 1.1). Our Materials and
Methods have been reported in detail elsewhere (Garrett & Sharot, 2014) and we summarize
them in Fig. 2. The calculations advocated by Shah et al. (2016), were used and summarized
in Box 1. We found that comparing participants updates to that of a perfectly rational,
Bayesian agent revealed that participants were less likely to update their beliefs in a
Bayesian manner in response to bad news than good news (Fig. 3 shows the new analysis of
previously published data (from Garrett & Sharot, 2014): t(31) = 2.53, p < 0.05, paired
sample t-test). Similar findings, using the belief update task, were recently reported by
Kuzmanovic and Rigoux (2016). Contrary to the claim of Shah et al., these results, as well
as past ones (Eil & Rao, 2011; Möbius et al., 2012), support a true valence-dependent
asymmetry in how humans update beliefs. Shah et al. also conduct a simulation using
hypothetical data that consists of one specific base rate (30%) and 52 hypothetical
agents, 93% of which are fixed to have likelihood ratios (LHR) less than 1. Likelihood
ratios express how diagnostic the evidence available to a participant is. Shah et al.
(2016), claim to show an optimistic update bias in the agents used in their simulation.
However, the authors themselves note that if the likelihood ratios are greater than 1, the
opposite pattern ought to ensue - greater updating for bad news compared to good news. If
likelihood ratios are close to 1, no bias will emerge in either direction in Bayesian
agents. This raises the question: what are the likelihood ratios that human participants
use in this task? Using the same set of data we reported above (published previously in
Garrett & Sharot, 2014), we found that the mean likelihood ratio across participants was
1.12 (s.d.: 0.43), which was not significantly different than 1: t(32) = 1.63, p = 0.11,
one sample t-test against test value of 1. A separate data set from an independent
research group found that likelihood ratios were 1.55 on average (Kuzmanovic & Rigoux,
2016). Despite having the empirical data to derive likelihood ratios from their own
experiments, Shah et al. select to fix the vast majority of likelihood ratios in their
simulation to those that are less than 1 (mean likelihood ratio = 0.70, significantly less
than 1: t(51) = 9.66, p < 0.001, one sample ttest against test value of 1). This
assumption, however, is not supported by the data. These simulations are thus irrelevant
to the question of whether the optimistic update bias observed in participants is
Bayesian.2 It is worth noting that following the equation in Box 1, on each individual
trial the value of the LHR (less than 1, equal to 1, larger than 1) indicates whether a
subject believes their own risk is lower/equal/higher than someone like them. However,
this logic does not hold for average estimates. That is to say, it is mathematically
possible for the average risk estimates of a subject to be lower for themselves than
others, yet for the average LHR to be equal or higher than 1. This is indeed the case in
Garrett and Sharot (2014).

<hs>  Seemingly pessimistic update for positive events is misleading</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

An optimistic update bias for positive stimuli has been described previously (Krieger et
al., 2014; Wiswall & Zafar, 2015). Yet Shah et al. (2016), report finding an optimistic
asymmetry for negative life events but a pessimistic asymmetry for positive life events.
Their studies, however, fall into two methodological pitfalls that need to be guarded
against when studying belief updating. We outline these below and then proceed to present
the methodology and results of a new study that corrects for these pitfalls. Our new study
uses both positive and negative life events but takes care to avoid the pitfalls we
outline. Hence it constitutes a valid test of belief updating using both types of life
events. We find an optimistic update bias for both negative life events and positive life
events.

METHODOLOGICAL PITFALL I: OBTAINING UNRELIABLE, MEANINGLESS, STATISTICS FOR POSITIVE EVENTS
--------------------------------------------------------------------------------

In the original belief update task (Garrett et al., 2014; Moutsiana et al., 2013, 2015;
Sharot et al., 2011; Sharot, Guitart-Masip et al., 2012; Sharot, Kanai et al., 2012),
participants are asked to estimate their likelihood of experiencing 80 aversive events in
their lifetime (first estimates). They are then presented with the likelihood of these
events in their population (information) and subsequently asked to estimate their
likelihoods again (second estimate). Trials are then divided into ones where participants
received good news (they learn that an aversive event is less likely than they thought)
and trials where participants received bad news (they learn an aversive event is more
likely than they thought). Update is calculated as the difference between the first and
second estimate. When attempting to adapt this task to study positive life events,
researchers face potential confounds which if ignored, will lead to invalid conclusions.
In particular, whilst validated statistics regarding the likelihood of encountering
negative events in one’s life-time are well documented (such as the likelihood of
suffering different type of illness or being a victim of crime), statistics about the
occurrence of positive life events are not readily available. This is problematic, as the
belief update task requires the use of many trials and stimuli. Yet, it is practically
impossible to find even 40 positive life events accompanied by validated statistics. Shah
et al. attempt to circumvent this problem by making up statistics for positive events
whilst using real, valid, statistics for negative events (see Appendix A of Shah et al.,
2016). This systematic asymmetry in the validity of base rates for positive and negative
base rates presents a possible confound. For example, for positive events, participants
were asked the following questions (try and answer these yourself): How likely are you in
your lifetime to: ‘Attend a friend’s birthday party?’ ‘Eat at your favorite restaurant?’
‘Receive a present?’ ‘Have family visit you at Christmas?’ ‘Being told you are special?’
Most people will have all these events happen to them over a lifetime, thus they are
likely to enter estimates close to 100%. This makes it impossible to measure update in a
desirable direction (people cannot increase estimates beyond 100%). Participants are
likely aware that actual statistics for these questions are less likely to exist than for
negative events such as robbery or lung cancer. Note that not all the positive events in
Shah et al. are extremely likely, which may explain why mean first estimates reported from
their studies are below 50%. Here, to generate meaningful stimuli for both positive and
negative life events we altered the belief update task as follows: we asked participants
to estimate their likelihood of encountering everyday life events in the upcoming month.
First, we obtained the frequencies of such events by asking over 200 participants to
report whether different common positive and negative life events occurred to them at
least once in the past month. We then used this data to construct a list of base rates for
each event (i.e. the likelihood of each life event occurring at least once in a given
month in the sample). Next we ran the belief update task on an alternate, but
demographically well-matched, set of participants, asking them to estimate their
likelihood of encountering these events in the next month.

METHODOLOGICAL PITFALL II: SKEWING THE DISTRIBUTION OF BASE RATE ARTIFICIALLY PRODUCES A FLIP FOR POSITIVE EVENTS
--------------------------------------------------------------------------------

When investigating biases in belief updating it is important to use a list of base rates
that are normally distributed around a mean that sits mid-scale. For example, if a rating
scale ranges from 5% to 95% the ideal mean would be 50% and the set of base rates should
be normally distributed around this mean. Running simulations we show below that failing
to ensure this creates spurious biases in updating (unless one controls for “estimation
errors”, see below). Consider four lists of base rates for life events, the distributions
of which are shown in Fig. 4a and b. The first two lists are the actual ones used by Shah
et al. in two of their experiments (experiments 3A and 3B). The distribution of each set
of these base rates is positively skewed (i.e. the majority of base rates are rare and
fall below the midpoint of 50%) for positive and negative life events (Fig. 4a). The third
and fourth lists are the actual base rates we used in this study. They are normally
distributed around 50%, (Fig. 4b). For each simulation we will randomly generate a first
estimate for each trial for each “participant”. This will be a random integer drawn from a
uniform discrete distribution between 0 and 100 for the first two lists of base rates
(this is the range of estimates participants are permitted to enter in Shah et al.) or
between 5 and 95 for the third and fourth lists of base rates (this is the range of
estimates permitted in our experiment). We will then “present” our simulator with the
actual base rate for the event on that trial (information) and generate a second estimate
- a random integer between the first estimate and the information (also drawn from a
uniform distribution). For example, for the question “how likely are you to go out of town
for leisure in the upcoming month” our simulator may randomly select 10% (first estimate),
it will then observe a base rate of 36% (information) and adjust its answer to a random
number between 10 and 36, let’s say 30% (second estimate). Thus, the amount of update on
this trial would be 20 (update is calculated such that positive numbers always indicate a
move towards the base rate). We run 1000 such simulations (i.e. “experiments”) for each
set of base rates (Fig. 4a and b). If the data produced by a simulation results in biased
updating, this will indicate that the bias is due to a statistical artifact (the result of
the mathematical constraints of the task) and not to an asymmetry in human learning. If
however the simulation produces no bias in updating but a bias is observed for human data,
this would suggest that the bias is due to asymmetric learning not to a statistical
artifact. Our simulation clearly shows that when the distribution of base rates is skewed,
an artificial bias in belief updating is observed (Fig. 4c). This is not the case however
when the base rates are normally distributed (Fig. 4d). Importantly, when an artificial
bias is detected it is observed in opposite directions for positive and negative life
events creating a distinctive “flip”. Specifically, when base rates are positively skewed
(Fig. 4a), the simulation shows greater updating for bad news than good news for positive
life events (significant difference in 100% of our simulations, Fig. 4c), whilst for
negative life events updating for good news is greater than bad news (significant
difference in 100% of our simulations, Fig. 4c). Note that this flip in asymmetry is
exactly the pattern reported in Shah et al. (Fig. 4e). When the distribution of base rates
is normally distributed however, the simulation does not reveal asymmetric updating (Fig.
4d, significant difference in only 5% of cases for positive and negative life events). Why
is an artificial bias produced for skewed distributions? The answer is relatively simple –
if the majority of base rates are low numbers then on average there is more room to alter
estimates when the first estimate is higher than the base rate, than when it is lower. In
other words, the difference between the first estimate and the information given (this is
known as the estimation error) will be larger when participants receive bad news for
positive events and when they receive good news for negative events. Thus, updates will be
greater when information is “bad” for positive events and “good” for negative events, and
vice versa when base rates are skewed towards high numbers. This statistical artifact,
however, can be corrected by controlling for “estimation errors”. If in the simulations
above we control for estimation errors in our analysis no bias is observed for any sets of
base rates. This was tested by running an additional 20 simulations (10 for positive life
events, 10 for negative life events, 20 participants per simulation) for each set of
skewed base rates. For each set of simulated data we then conducted a repeated measures
ANOVA with valence (good news/bad news) as a factor and entering the difference in
estimation errors between good news and bad news as a covariate. We controlled for
estimation errors on a condition level, rather than on every trial, so that we could
directly compare our findings to that of Shah et al. When the distribution of base rates
was positively skewed (Fig. 4a) a valence effect between good news and bad news was not
significant in 19 (95%) of simulations. Thus, to avoid false conclusions researchers
should either use normally distributed base rates with a mean at the midpoint of the
scale, control for estimation errors, or do both. In previous studies, estimation errors
have either been equal for good news and bad news trials (e.g., Garrett et al., 2014;
Sharot et al., 2011, both of which used a scale of 3–77) and/or in instances where
differences exist, these are carefully controlled for (e.g., Garrett & Sharot, 2014; Korn,
Sharot, Walter, Heekeren, & Dolan, 2014). In contrast, whilst the differences between
estimation errors in response to desirable and undesirable information can account for the
patterns of update observed in Shah et al.’s experiments, estimation errors are not
controlled for in their Experiments 1 and 2. In Experiment 3a, when estimation errors are
finally controlled for, the critical interaction between valance of stimuli and
desirability of information is no longer significant. In Experiment 3b and 4 of Shah et
al., it is stated that the results hold when controlling for estimation errors but
statistics to support this are not provided. It is worth noting that the experiments
conducted by Shah et al. are not replications of the original belief update studies in
design, nor analysis. A few of the differences may have significantly affected the
results: (i) out of the 80 negative stimuli used previously, Shah et al. select 38
creating a skewed set. (ii) Shah et al. incentivize participants to remember the base
rates provided and require them to input these using a keyboard. This deviation from the
original task is important because the novel manipulation may encourage participants to
use information in a different manner than they would otherwise. (iii) In contrast to all
past studies, Shah et al. “…exclude trials which were more than 3 interquartile ranges
from the mean value of the analyses. These exclusions reduced the total number of trials
across the conditions by approximately 2.5%” (exclusion is reported for Experiments 1, 3a
and 3b but not for Experiments 2 and 4). One may assume that this exclusion does not
matter, but in at least one documented case the exclusion altered the results from non-
significant in a previous version of the Shah et al. manuscript to significant with
exclusion of outliers done post hoc. (iv) Different factors are controlled for in each one
of the five experiments reported in Shah et al. The reason to control for some factors but
not others in the different experiments is not given. We were unable to assess the
consequence of this practice, because statistics of the tests after controlling for varied
confounding factors were not provided in most instances. We now proceed to describe a new
study, in which we examine how individuals integrate good and bad news into their beliefs
about the likelihood of experiencing positive and negative life events, taking care to
avoid the two pitfalls we have outlined above.

        <hss>Participants</hss>

        300 participants located in the United States completed the survey on Mechanical
        Turk. As in past studies of the belief update task (Garrett & Sharot, 2014;
        Moutsiana et al., 2013, 2015), we excluded participants with a high Beck
        Depression Inventory (BDI) score indicating potential depression. 73 participants
        were excluded for having a BDI score greater than 11 (final sample = 227).
        Participants were all between the ages of 20 and 30 years of age (inclusive).
        Completion of the survey took approximately 25 min and participants were
        compensated for their time.

        <hss>Task</hss>

        The survey began by collecting basic demographic information from participants
        (age, level of education, marital status, employment status, monthly income) then
        2 training examples were presented to familiarize participants with the task.
        Participants were then presented with 100 different commonly occurring life events
        for 3 s each. These were a mixture of positive events (for instance: “Discovered a
        new song you like”, “Laughed at a joke”) and negative events (for instance: “Had
        an argument with a family member”). Whilst the event was displayed on screen,
        participants were instructed to recall whether this event had happened to them in
        the past 4 weeks. They were then asked to indicate either (1) Yes: This event
        occurred to me at least once in the past 4 weeks; or (2) No: This event did not
        occur to me in the past 4 weeks. The order of these two options was
        counterbalanced. Participants had unlimited time to make a response (Fig. 5a).
        After completing the survey, participants rated each event on a 5 point likert
        scale (1 = Very Negative; 2 = Negative; 3 = Neutral; 4 = Positive; 5 = Very
        Positive) and then completed the BDI (Beck, Ward, Mendelson, Mock, & Erbaugh,
        1961) and Life Orientation Test Revised (Scheier, Carver, & Bridges, 1994). The
        survey was constructed and presented using web based survey service Qualtrics.

        <hss>Analysis</hss>

        For each event, the percentage of participants who indicated the event had
        occurred to them in the past month (out of all participants who completed the
        study and were included in the final sample) was calculated.

        <hss>Event selection</hss>

        A subset of the events (n = 54) were selected for use as stimuli. We selected
        positive and negative life events such that the distribution of base rates for
        each type of event (positive and negative) was normally distributed around a mean
        of 50%. Note that we were unable to verify how accurately participants were able
        to recall whether events occurred to them or not in the past month. However, since
        a base rate for a specific event will represent good news to some participants and
        bad news to others (depending whether a participant overestimates or
        underestimates the base rate), noise from such inaccuracies ought to cancel out
        over good news and bad news events in the belief update task.

        <hss>Participants</hss>

        200 participants located in the United States (age range 20–30) completed the
        survey on Mechanical Turk. 56 participants were subsequently excluded for having a
        BDI score above 11 indicating possible depression. A further 2 participants were
        excluded because the range of their responses was limited, resulting in zero
        trials in either the “good news” bin or “bad news” bin, making comparison
        impossible (final n = 142, mean age: 25.74; mean BDI score: 2.80). There were no
        differences in age, education, income, marital status or employment status between
        this set of participants and participants that had completed the base rate survey
        used to construct the base rate statistics (all P > 0.20). Completion of the
        survey took approximately 1 h and participants were compensated for their time.

        <hss>Task</hss>

        The survey began with an attention check designed to filter out participants that
        did not read the instructions prudently. Then, demographic information was
        collected (age, level of education marital status, employment status, monthly
        income) and 2 training examples provided to familiarize participants with the
        task. In the first session, on each trial (54 trials in total) participants were
        presented with 1 of 54 life events (see Supplementary Material, Table 1 for list
        of events used) and asked to imagine the event happening to them in the month
        ahead. They were then asked to estimate how likely that event was to happen to
        them in the next 4 weeks. Participants were instructed to type in an estimate
        between 5% and 95% using a computer keyboard. Trials with responses outside this
        range were excluded from analysis (mean(s.d.) number of responses outside this
        range: 1.80(3.43)). Participants had 8 s to provide a response. Participants were
        then shown the base rate statistic of the event happening in the next 4 weeks,
        which ranged from 15% to 85% (see Fig. 5b). They were told that the statistic was
        the average likelihood of this event happening at least once in the next four
        weeks to someone from the same socioeconomic environment as them. In a second
        session, which took place immediately after the first session, participants were
        asked to re-estimate how likely each event (54 trials in total) was to happen to
        them in the next 4 weeks. As in the first session, participants had 8 s to provide
        a response. After completion of the task, we tested participants’ memory for the
        information presented. Participants were asked to recall the information
        previously presented of each event. Subsequently, participants were then asked to
        rate all life events according to how positive or negative they found them on a
        five point Likert scale (1 = very negative, 2 = negative, 3 = neutral, 4 =
        positive, 5 = very positive). This range of scale was used so that events could be
        clearly categorized into events that were considered negative (assigned a rating
        of 1 or 2), neutral (assigned a rating of 3) or positive (assigned a rating of 4
        or 5). Participants were also asked to rate past experience with each event (“Has
        this event happened to you before?” From 1 = never to 6 = very often), as done
        previously (Garrett & Sharot, 2014; Garrett et al., 2014; Sharot et al., 2011;
        Sharot, Guitart-Masip et al., 2012; Sharot, Kanai et al., 2012). Three quarters of
        participants (75%) also rated all events on: vividness (“How vividly could you
        imagine this event?” From 1 = not vivid to 6 = very vivid); familiarity
        (“Regardless if this event has happened to you before, how familiar do you feel it
        is to you from TV, friends, movies and so on?” From 1 = not at all familiar to 6
        very familiar); and arousal (“When you imagine this event happening to you how
        emotionally arousing is the image in your mind?” From 1 = not arousing at all to 6
        = very arousing). The scores of these are reported in Supplementary Material,
        Table 2. Participants then completed the BDI and the Life Orientation Test
        Revised. The survey was constructed and presented using web based survey service
        Qualtrics.

        <hss>Analysis</hss>

        Life events were categorized as negative or positive for each participant
        individually according to their own evaluation. Specifically, events were
        classified as positive if the participant rated the event as 4 (positive) or 5
        (very positive) in the ratings section of the task, and negative if rated as a 1
        (very negative) or 2 (negative). Events with a neutral rating of 3 were excluded
        from the analysis (mean(s.d.) number of events with neutral rating: 7.17(5.67)).
        For each type of event, participants could receive either “good news” or “bad
        news” depending on whether the participant initially overestimated or
        underestimated the probability of the event relative to the base rate (see Fig.
        5c). Specifically, if their first estimate was lower than the base rate presented,
        the information would be categorized as “good news” if the life event was positive
        and “bad news” if the life event was negative (column 1, Fig. 5c). If their first
        estimate was higher than the base rate presented, the information would be
        categorized as “bad news” if the event was rated as a positive life event and
        “good news” if the event was rated as a negative life event (column 2, Fig. 5c).
        Trials in which the initial estimate was equal to the statistic presented were
        excluded from subsequent analyses as these could not be categorized into either
        condition (less than one negative life event trial and less than one positive life
        event trial on average per participant). Belief update was calculated for each
        trial and participant as the difference between first and second estimate. As done
        previously (Garrett & Sharot, 2014; Garrett et al., 2014; Moutsiana et al., 2013,
        2015; Sharot, Kanai et al., 2012) update was calculated such that positive scores
        indicate a move towards the base rate, regardless of event type and valence
        categorization, and negative scores a move away from the base rate. Update scores
        were then entered into two general linear models using the IBM SPSS statistics
        software; one for negative life events and one for positive life events, with
        information valence as a fixed factor (good news/bad news), participant ID as a
        random factor and absolute memory errors and absolute estimation errors on each
        trial as covariates. Since covariates vary from trial to trial, controlling for
        them on a trial by trial level is more precise than on a condition level as done
        previously by us (Garrett & Sharot, 2014; Garrett et al., 2014; Moutsiana et al.,
        2013, 2015; Sharot, Guitart-Masip et al., 2012; Sharot, Kanai et al., 2012) and
        others (Shah et al., 2016). Nevertheless, to allow direct comparison with Shah et
        al., we also entered mean update scores for each participant into a 2 (good/bad
        news) by 2 (positive/negative life event) repeated measures ANOVA controlling for
        the following covariates on a condition level: (1) the difference in memory for
        good news trials and bad news trials, both for positive and negative stimuli, (2)
        the difference in number of good news trials and bad news trials, both for
        positive and negative stimuli (3) the difference in absolute estimation errors for
        good news trials and bad news trials, both for positive and negative stimuli
        (estimation error = |first estimate − base rate|).

<h>RESULTS</h>
-------

We observed an asymmetry in updating, such that participants updated more in response to
good news than bad news. This optimistic update bias was significant both for positive
life events (t = −2.88, p < 0.01, mean good news update = 8.71, mean bad news update =
7.79) and for negative life events (t = −4.88, p < 0.001, mean good news update = 10.66,
mean bad news update = 6.62). There was also a significant effect of estimation errors
(negative events: t = 13.43, p < 0.001; positive: t = 15.81, p < 0.001) and memory errors
(negative events: t = −6.13, p < 0.001; positive events: t = −2.92, p < 0.01). Comparing
the bias for positive life events and negative life events by entering mean update scores
for each participant into a 2 ∗ 2 repeated measures ANOVA with desirability of information
(good/bad news) and life event type (positive/negative life event) as repeated factors
(controlling for differences in memory, differences in number of trials and differences in
estimation errors) revealed the expected main effect of desirability of information (F(1,
135) = 6.29, p < 0.02), no effect of event type (F(1, 135) = 0.08, p = 0.78) and no
interaction (F(1, 135) = 0.31, p = 0.58). Fig. 4f.

<h>DISCUSSION</h>
----------

The current set of results strongly support a valence dependent asymmetry in how
participants update their beliefs, consistent with a large body of fast growing research
(Eil & Rao, 2011; Garrett & Sharot, 2014; Garrett et al., 2014; Korn et al., 2012; Krieger
et al., 2016; Kuzmanovic et al., 2015, 2016; Lefebvre et al., 2016; Ma et al., 2016;
Möbius et al., 2012; Sharot, 2011; Sharot & Garrett, 2016; Sharot et al., 2011; Sharot,
Guitart-Masip et al., 2012). By pitting this asymmetry against three robustness tests
suggested by critics of optimism (Shah et al., 2016) we find that it survives each of
these tests, suggesting it is a pervasive phenomenon. Specifically, we first summarize
past data showing that an optimistic update bias exists under a different type of
classification (Garrett & Sharot, 2014; Kuzmanovic et al., 2015). Second, we apply the
Bayesian analysis outlined by Shah et al. to a previously collected data set (Garrett &
Sharot, 2014) and reveal that participants’ updates are more Bayesian in response to good
news than bad news. Third, we test Shah et al.’s curious report of a distinctive “flip” in
the update asymmetry for positive life events, with updates being greater for bad news
compared to good news (the opposite asymmetry to that observed for negative life events).
We find that their studies fall into two methodological pitfalls, which can account for
their results. Here, we avoid these pitfalls and reveal an optimistic update bias, for
both positive life events and negative life events. Moreover, whilst an optimism bias has
previously been shown to exist for both everyday and significant life events (Strunk,
Lopez, & DeRubeis, 2006; Weinstein, 1980), biased belief updating had until now only been
revealed for the latter (Garrett & Sharot, 2014; Sharot et al., 2011). This is the first
demonstration of an optimistic update bias for everyday life events. The asymmetry in
belief updating can result in overly optimistic beliefs. Whilst biased, these beliefs may
be adaptive as positive expectations reduce stress and anxiety facilitating physical
(Taylor, Kemeny, Reed, Bower, & Gruenewald, 2000) and mental health (Garrett et al., 2014;
Korn et al., 2014; Strunk et al., 2006). Furthermore, optimistic expectations enhance
motivation and exploration (Bandura, 1989; Puri & Robinson, 2007) increasing the
likelihood of gaining resources (Johnson & Fowler, 2011). However, alongside these
benefits to optimistic expectations, optimism has also been suggested to reduce necessary
precautionary action leading to ill preparedness in the face of natural disasters (Paton,
2003) and failure to adopt preventative measures to safeguard ones health (Shepperd et
al., 2013) (see Bortolotti & Antrobus, 2015 for a discussion of the benefits and costs
associated with optimistic expectations). On balance it is possible that the positive
consequence of unrealistic optimism outweigh the negative, leading humans to evolve this
asymmetry in belief formation (McKay & Dennett, 2010).


<h>REFERENCES</h>
----------

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<ART>Overcoming Arlie Hochschild's concepts of the ‘real’ and ‘false’ self by drawing on Pierre Bourdieu's concept of habitus
================================================================================

Authors: Michelle Addison
DOI: 10.1016/j.emospa.2017.01.003
Year: 2017  |  Pages: 9-15
ASJC codes: 3205, 3207
Keywords: Authenticity, Bourdieu, Emotion management, Hochschild, Real self, deep acting

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This article theoretically discusses Arlie Hochschild's (1983, 1998) concept of the ‘real’ and ‘false’ self (1983: 194) and how this holds together her model about how it is we manage our emotions. Hochschild draws on ideas about surface acting, deep acting and authenticity to support her theory of emotion management. In this discussion I argue that these ideas undermine the clarity of the theoretical model Hochschild tries to develop to explain emotion management. The first aim here is to demonstrate that this concept of the real and false self acts as an unnecessary conceptual linchpin making Hochschild's ideas about emotion management opaque. The second aim in this article is to theoretically engage with Pierre Bourdieu's (1984, 1990) concept of habitus as a way of overcoming Hochschild's idea of the real and false self.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

This article discusses Arlie Hochschild's model of emotion management (1983: 35) and
identifies inherent problems with her use of the ‘real’ and ‘false’ self as a conceptual
linchpin (Hochschild, 1983: 194–195). My intention is to explain these problems with this
emotion management model and offer an alternative for the ‘self’ that Hochschild describes
by drawing on Bourdieu's concept of habitus (1984, 1990). The real self is considered by
Hochschild to be the very core, or essence, of who we are as a person, and in contrast,
the false self is ‘a part of “me” that is not really “me”’ (Hochschild, 1983: 194). My
contention here is that there is no such thing as the real or false self, nor is it
important to make such a distinction. Hochschild (1983) wanted to explain how it is that
we can act differently in certain social settings by managing our emotions. She suggests
that by managing our emotions we are able to work on the self and present to the world a
persona that is expected, and fits in. Her model of emotion management was ground-breaking
because it helped to open up debate about the invisible and unrecognised work people do in
order to fit in with social expectations (see Mann, 2004; Bolton, 2005). In this article I
want to undo the dependency on the concepts of the ‘real’ and ‘false’ self that is
complexly bound up in this model. In the first part of this article I deal with this by
showing how Hochschild repeatedly draws on the real and false self as a conceptual
linchpin in her research (1979, 1983, 1997, 1998) and how this makes her ideas
inconsistent and opaque. In the second part of this article I engage with Pierre
Bourdieu's (1984, 1990) concept of habitus as a way of overcoming Hochschild's idea of the
real and false self.

<h>THE INNER SELF: REAL AND AUTHENTIC?</h>
-----------------------------------

Hochschild developed a model (1979, 1983, 1998) to explain how we manage emotion in
certain social settings and around certain people. This arose out of her research into
flight attendants working for Delta Airlines in the United States of America (1983). Her
research looks at how employees become who they are expected to be at work. Hochschild
revealed that these flight attendants were expected to act in a particular way at work to
fit in with the organizational expectations of the ideal female employee. For these female
employees this included being perceived as caring, mildly flirtatious, and impervious to
rude customers, as well as dressing in a particularly feminised way that included a
certain way of wearing make-up, uniform and hair (Hochschild, 1983: 101–103). This finding
in itself was revealing of constraints on female employees in particular (1983: 127–128).
However, what made Hochschild's work distinctive at this time was that she offered an
insight into how it is these female employees were managing to do all these things and
become the right kind of employee (105–106). Before scrutinising Hochschild's emotion
management model, it is worth briefly signalling how Goffman has influenced her early
work. Hochschild wanted to depart from Goffman's construction of an individual that she
argued is made passive to rules governing interactions (1959; Hochschild, 1983: 225–227).
She departs from Goffman's ideas about the self as a collection of many roles and
performances because she is concerned with what she sees as a lack of continuity. She
argues that Goffman's account of reality provides ‘no structural bridge between all
situations’ (1983: 225). That is – an explanation of how a person is the ‘same’ from one
moment to the next. She finds this problematic for two reasons: firstly, because this
would suggest that a person is governed by social rules as a passive individual who has a
lack of interiority. She notes how Goffman seems to ignore times when an ‘individual
introspects or dwells on outer reality without a sense of watchers’ (1983: 226). Even
though Goffman later explored to some extent a person's inner world and their social
context in ‘Asylum’ (1961), by mainly focusing on the emotion of embarrassment, he does
not discuss the internalised feeling rules or capacity for agency which Hochschild sees as
being ‘“inside” the actor’ (1983: 226) and fundamental to the management of emotion (1983:
228). For Hochschild, then, it is this interiority and agency that is the ‘bridge between
all situations’ (1983: 225), and this brings her to the notion of an inner essence – or
real self. Secondly, she does not think that Goffman properly accounts for how people are
able to use prior expectations to help navigate new situations. She criticises him saying
that there is ‘no overarching pattern that would connect the “collections”’ 1983: 225).
For her, ‘the idea of prior expectation implies the existence of a prior self that does
the expecting,’ (Hochschild, 1983: 231). She provides this example: When we feel afraid,
the fear signals danger. The realization of danger impinges on our sense of self that is
there to be endangered, a self we expect to persist in a relatively continuous way.
Without this prior expectation of a continuous self, information about danger would be
signalled in fundamentally different ways (Hochschild, 1983: 231). Hochschild (1983) is
uncomfortable with the idea that a person may be different depending on the stage setting
and context. For her, there is continuity in terms of how a person acts and feels and that
this is only possible because of an inner ‘real self’ (1983: 34). She writes, ‘To develop
the idea of deep acting we need a prior notion of the self with a developed inner life.
This, in Goffman's account, is generally missing’ (1983, 227). For Goffman, there is no
such thing as real or false performances signalling a true self. According to Goffman, all
of our performances are real in the sense that they simply take place – there is no
unchanging core that is the ‘real’ self, only an ongoing and increasing personal portfolio
of roles (see 1959: 252–253). However, Hochschild (1983) identifies that an explanation of
continuity between moments is under developed in Goffman's work. Goffman did not write in
detail about a reflexive or agentic self as such, but the need to explain continuity
between situations (as Hochschild tries to do) is not, in my view, achieved through the
‘real self’ as a conceptual linchpin, which I will now discuss further.

<h>HOCHSCHILD'S EMOTION MANAGEMENT MODEL (1983)</h>
--------------------------------------------

Hochschild's ‘Managed Heart’ model of emotions (1983) quickly developed into a typology to
explain how it is that emotions are performed or concealed in certain social settings. She
identified two different types of emotion management: emotion work and emotional labour.
Hochschild describes emotional labour as: ‘the management of feeling to create a publicly
observable facial and bodily display; emotional labour is sold for a wage and therefore
has exchange value’ (1983: 7). Emotion work is slightly different to emotional labour; as
Hochschild states: ‘I use the synonymous terms emotion work or emotion management to refer
to these same acts done in a private context where they have use value’ (italics in
original, Hochschild, 1983: 7; see page 181 in book for further discussion). Hochschild
suggests that we may undertake emotion work in our day-to-day lives in order to present
feelings in a more agreeable way to friends, family and acquaintances, for example, by
hiding anger or embarrassment to preserve social relations (1983: 19–20). Hochschild
develops her model by outlining the mechanisms that make emotion work and emotional labour
possible. She focuses on surface and deep acting (1983: 48–49). According to Hochschild
(1979, 1983), surface acting is a practice in which an individual offers a performance
that displays the expected feelings they sense are in keeping with the feeling rules
structuring that particular social interaction, regardless of whether this is how they
feel or not. This surface acting of expected feelings, Hochschild suggests, is an
insincere performance that the individual hopes is convincing to others, nonetheless
(1983: 49). For instance, the flight attendant smiles to show happiness; whether she
actually feels happy or not does not matter (1983: 127–128). To put it another way, we
portray or mimic what we think is expected of us and conceal undesirable feelings. In
short, Hochschild suggests that what we are doing is acting out or mimicking the ‘shoulds’
accorded by feeling rules that structure interactions, but we are not obliged to
internalise these feeling rules as our own (1983: 118). Surface acting then is about
knowing how to act in a given situation (1983: 48). This means knowing the implicit
feeling rules structuring workplace interactions. Knowing how to display emotions is
essential to being able to fit in within the workplace. To get surface acting right
requires some attention to the audience, usually a customer or co-worker, in order to
discern whether the emotional performance has been convincing to them. This is very
similar to how Goffman (1959) describes the dynamics of performing a role during social
interactions. The employee interacts with the other person whilst trying to pick up clues
that their performance may possibly be viewed as unconvincing. The crux of surface acting
is to offer a performance that leaves the other person convinced that they had a
meaningful interaction. This person tries to conceal from the other person that they were
performing emotional displays that were simply expected of them. Another aspect of
Hochschild's emotion management model relates to deep acting. This involves a person
trying to sincerely embody an emotion so that displaying it for the other person is no
longer a fake but convincing performance and becomes ‘real’ (1983: 194). Hochschild
describes deep acting as deciding ‘what it is that we want to feel and on what we must do
to induce the feeling’ (1983: 47). The person tries to make their emotional displays seem
authentic to themselves as well as the other person. Hochschild goes further and describes
the practice of deep acting as working hard trying to feel a particular emotion. This
involves using emotional recall of memories of a situation where the individual really had
felt happy: this memory is then re-visualised, invoked and attached to their present
circumstances to shape the mind and bodily behaviour. Hochschild states that by, trying to
feel what we sense we ought to feel or want to feel (Hochschild, 1983: 43) we must
undertake deep acting, this activity of working on emotions at a ‘deep level’ so that they
are felt as ‘real’ is accomplished via a process of imagining, that is, to think about a
desired emotion we wish to feel and imagine it as if this were true (1983: 43). Hochschild
suggests that by inducing an imagined emotion via deep acting, the self will come to
accept it as authentic and part of the real self. Deep acting requires that the individual
suspends their ‘usual reality testing’ and instead ‘allow a make-believe situation to seem
real’ (Hochschild, 1983: 42), in the hope that it will take on the qualities of being real
at a later stage. Deep acting is not only used to theorise the inducement of imaginary
feelings in Hochschild's framework, but it is also used to refer to how an individual
might prevent a real feeling from emerging from the depths of the real self and mis-
fitting the situation. Hochschild uses her concept of deep acting to explain how the
individual attempts to convince themselves that they really feel something else other than
what they are feeling, or else ‘block or weaken a feeling we wish we did not have’
(Hochschild, 1983: 43). Deep acting then involves ‘bad faith’ (Hochschild, 1983: 47),
which is a problematic concept that suggests that individuals can intentionally deceive
themselves. A person would have to know that they were trying to forget something that
they know. For Hochschild, deep acting is also about lying to ourselves, but the lie is
suppressed in the hope that the lie will disintegrate and the deception we began with will
take the form of something real. Whilst Hochschild describes the practice of deep acting
she is not clear or convincing about the purpose of deep acting. Hochschild tries to
convince us that the point of deep acting is to make a feeling that is imagined seem real,
so that it becomes real.

<h>CONFUSING CONCEPTS</h>
------------------

Hochschild presents an array of interesting concepts as part of her model of emotion
management (1998, 2003). She offers a way to theorise deep acting but is never quite clear
about what it is, what the purpose of deep acting is, or how it is done. Instead, she
offers numerous examples that she suggests demonstrate deep acting and often relies upon
the reader to intuitively know what deep acting is, how it is done, and why. Deep acting
is necessitated in Hochschild's study because she senses that there are times when people
do not feel as though they fit in as they are in certain situations. People are motivated
to do deep acting to bring mis-fitting feelings more in line with what is expected in a
given social situation and transforming them. Deep acting is unnecessarily complicated,
however, by Hochschild's discussion of real feelings and false feelings. Deep acting tries
to explain how a person can knowingly hold two (or more) contradictory feelings in place –
neither has to be real or false. This perception of real or false feelings, I would
suggest, arises out of a calculation the person makes about some feelings ‘fitting in’
with the social space they are in, and other feelings being viewed as mis-fitting. These
mis-fitting feelings are concealed, although not forgotten, because they do not fit in
case they might incur a social sanction. Holding these contradictions in place can be
painful for an individual. We do deep acting because we want to fit in within the
dominating structures of feeling. The desire to fit in is what I would suggest motivates
deep acting, despite it being a painful thing to do. Therefore, the idea of real or false
feelings is rather a distinction a person makes about the kind of feelings that fit in and
those that do not. Deep acting is painful precisely because it is work on the self that
forces an adjustment to who we are told we ‘ought’ to be or how we ‘should’ feel, and
recognition that we do not presently embody this already. It feels strange also to act in
a way that we are not used to. Put another way, taking on someone else's rules to govern
our own emotions and behaviour makes us feel odd, ill at ease, and it feels wrong when we
try to convince ourselves that this is our normal, everyday behaviour and way of feeling.
Deep acting can make us feel anxious because it is hard to do, and yet oddly enough it can
also help to reassure us that at least we fit in better in certain social spaces by doing
it. This process of ‘becoming’ who we sense we should be, by making painful adjustments,
is rife with tension and anxiety. Deep acting is painful and invokes tensions because we
harbour thoughts that we should already be that person we are trying to become. What is
more, there is an on-going debasement directed at the self for having to undergo deep
acting in the first place. A painful tension arises when we undertake deep acting because
we think we shouldn't have to try so hard to feel a certain way, to be a certain kind of
person, we want to be that person already to feel a certain way already. Having to labour
at it is a clear sign that we are not the person we feel we ought to be, we do not know
what to feel. The pain of doing deep acting may ease over time though as one way of
feeling is replaced by another perhaps more socially desirable way, and is assimilated as
if it were already our own way of thinking and feeling. Tonkens (2012) also makes a
similar argument, suggesting that Hochschild does not sufficiently clarify what she means
by particular concepts and what they are supposed to do. Tonkens too is critical of
Hochschild's lack of connections between her concepts and how they are supposed to relate
to each other in this emotion management model. In Hochschild's explanations of deep
acting, for instance, she tends to jump from talking about deep acting as being about
making false performances of feelings feel authentic (1983: 35–36), then to how deep
acting is also about suppressing real feelings, and then she moves to a different theme
altogether within deep acting in which the individual is also trying to preserve the real
self (an inner jewel) (1983: 34) and manage the false self (1983: 195). Even after this
extensive use of deep acting as a form of emotional labour/work, she theorises deep acting
as also including the practice of conscious and continuous self-deception in which the
real self is fooled by an illusion which they have deceived themselves into believing
(1983: 40–42). It is difficult to untangle what Hochschild means exactly by deep acting
and what it is supposed to do precisely, and the reason for this is because she tries to
make the concept account for too much within her theoretical framework. Hochschild is
trying to use deep acting as a conceptual device that explains how we try to make ‘who we
are not’ (what she sees as the false performances) become ‘who we are’ (part of the real
self). Deep acting is a mechanism that she uses to explain how we try to become a person
with particular feelings because of a sense that this is who we ought to be and how we
ought to feel. Deep acting then is a form of emotional labour/work that has the purpose of
becoming someone else in order to fit in with already structured expectations and rules.
It is necessary to her theoretical framework that she is able to justify a distinction
between the real and false self because she argues that it is the real self that is being
exploited by capitalist organizations (1983: 34; see also Fineman, 2008). I discuss this
separation of the real and false self shortly and how it is particularly problematic in
her work, and hence why I bring in Bourdieu's idea of the habitus (1984) to resolve it.

<h>THE ‘REAL’ AND ‘FALSE’ SELF: A MISLEADING CONCEPTUAL LINCHPIN</h>
-------------------------------------------------------------

When Hochschild talks about a real self she is describing a self that has honest and true
feelings that are not subject to pretence or acting. For her, the real self constitutes a
continuity, an embodied way of being and doing that is predictable and recognisable to
others. Possessing a ‘real self’ tells others what we are like as a thinking and feeling
individual. Hochschild compares her idea of a real self to an inner jewel or essence that
makes us who we are. To do this, she sets up an agentic, choosing individual with an
internalised sense of continuity: a real self. The real self is a formed identity that is
reliably the same, from day-to-day, and it is in our possession to control. In this sense
then, I would argue that Hochschild mistakenly interprets the anxiety that arises out of
trying to become someone we sense we ‘should’ be as evidence of a separation between a
real and false self – for example, ‘I wasn't really being myself’ (Hochschild, 1983: 262).
And yet, this is based on the person's perception of what is real and false, and a sense
of a core self. She uses these dispositions to evidence a ‘real self’ and ‘an inner jewel
that remains our unique possession no matter whose billboard is on our back […] we push
this “real self” further inside, making it more inaccessible’ (1983: 34). What is missing
then is a distinction and reflection made between how the individual sees themselves, and
how the self is being socially constructed in these narratives through dispositional
histories. Working on an emotion so that it fits in with the social space the individual
is in can be painful. Hochschild argues the more we have to work on ourselves to become
comfortable with representing an emotion we think we ought to feel, the more inauthentic
the emotions we are trying hard to embody become, and therefore we find ourselves getting
further away from our real selves. She writes that ‘subtracting credibility from the parts
that are in commercial hands, we turn to what is left to find out who we “really” are’
(1983: 34). Hochschild further argues that backstage is where the ‘real self’ can
supposedly relax and emerge, and that it is in this space that more authentic performances
occur rather than during front stage performances, which tend to be around customers and
clients (1983: 192). Erickson (2011:121) notes how there has been increased attention
around the idea of authenticity and ‘the real thing’ in a post-industrial climate. Cain's
research (2012) looks at authenticity and the emotional labour of workers in practice at a
care hospice in North America and it challenges Hochschild's idea of a split real and
false self. Cain argues that this was not the case in her research and instead shows how
workers felt that how they act around their patients is just as authentic and real as
their behaviour in the staff room. These workers felt that they presented a more
formalised and different ‘hospice identity’, rather than a ‘false self’ which Hochschild
would suggest. In Cain's research this worker identity was important to how the
participants' felt they should manage their own emotions at work. Hochschild is engaging
in a phenomenological debate about a person's state of being in the world. She is
advocating the notion of a real person, with real feelings, that possesses an alter ego
which she describes as the ‘false self’ (1983: 194), which creates illusions and make
believe that fool the real self. This false self is described as ‘a disbelieved, unclaimed
self, a part of “me” that is not “really me”’ (1983: 194). According to Hochschild, the
difference between what is the real self and what is false depends on what aspects of it
we claim, so for instance, we may say ‘I wasn't really being myself at that party’. For
Hochschild, we each possess a real self, or inner essence that we know to be true (1983:
34): the critique I am making here is that Hochschild's concept of the real/false self
requires more critical engagement with why a person might feel that way about their
identity.

<h>EXPLOITATION OF THE ‘REAL’ SELF: AUTONOMY AND AGENCY</h>
----------------------------------------------------

Hochschild needs the concept of a ‘real self’ with a ‘real life’ (1983: 47) in her
theoretical framework to explain what she sees as the exploitation of a person's inner
essence by capitalist organizations. Hochschild is suggesting that being made to become
someone else who is ‘other’ to us at work, and being told how to feel according to
structured feeling rules, is a suppression of an individual's core self and their agency.
So, feeling pressured to change because of feeling rules makes us shape our sense of self
in a way that we do not necessarily do out of choice in the workplace, and in ways we are
not necessarily accustomed to or feel comfortable with. Hochschild says, ‘The airline
passenger may choose not to smile, but the flight attendant is obliged not only to smile
but to try to work up some warmth behind it’ (1983: 19). Hochschild is concerned with how
the transmutation of emotion work, that is, a personal choice to work on the self to
become someone we feel we ought to be for others in our private lives, is exploited by
capitalist organization and given an exchange value. This exploitation amounts to a
suppression of the real self. Hochschild therefore needs to set up this construct of the
authentic, agentic individual to justify her argument that capitalist organizations are
exploitative of emotional labour and emotion work. Many workers have little choice but to
work on themselves it would seem, although this is not true of all workers who can
exercise power to negotiate workplace feeling rules (1983: 19, 89). For the most part, it
is concerning to Hochschild that workers potentially lose their capacity to freely display
how they feel. This capacity to show feelings is relinquished by the employee as part of
the expectations of their contract and instead they must internalise workplace feeling
rules if they want to get paid. She constructs the exploitation of a person's emotional
system by capitalism, that is, the transmutation of emotion work into emotional labour, as
an immoral act that infringes on the nobility and sanctity of a ‘real self’ (1983: 34).
Referring to a real self, Hochschild draws upon Rousseau's ‘Noble Savage’ (1983: 192) to
describe a person who is not subjected to any feeling rules, who feels spontaneously and
without calculation. This real self is to be valued, protected and preserved, according to
Hochschild, from the onset of capitalism and the demands of emotional labour, lest we
become a ‘faceless soul beneath the mask’ (1983: 194). Hochschild needs to explain this
act of exploitation, specifically of emotion, via an idea of valuing a real self
(1983:192) which she sees as increasingly constricted by rules, deeply entwined in the
matrix of capitalism, with little choice but to exchange an inner self and emotions for a
wage. Bolton (2005: 39) is critical of Hochschild's theory of emotion management, saying
that it ‘restricts the possibility of individuals ever being active agents, who through
negotiation are able to break the “chain” of power and “make their own histories”’.
Furthermore, Bolton is opposed to the idea that employees are coerced to align themselves
with organizational rules and lose a ‘sense of self in the process’ (2005: 39). Instead,
Bolton argues for a model of a person who reflects the modern, reflexive individual
(Bolton, 2005; Bolton and Boyd, 2003; Giddens, 1991, 1994; Urry, 2000; Beck, 1992, 1994;
see Atkinson, 2010, 2012; and Bourdieu and Wacquant, 1992; Du Gay, 1996). That is, someone
who is able to navigate, negotiate and overcome feeling rules that have the capacity to
constrain employees. She is suggesting then that employees can choose how to feel at work
to a greater extent than which Hochschild allows for within her theoretical framework.
According to Bolton, Hochschild is suggesting that capitalist organizations have:
Appropriated all of our feelings so that there is no longer any room for sentiments, moods
or reactions that have not been shaped and commodified via the ‘commercialization of
intimate life’ (Bolton, 2005: 2). Bolton suggests that Hochschild's argument – that
intimate life is increasingly commercialized through emotional labour – inevitably
positions employees as passive, or, as ‘crippled actors’ (Bolton, 2005: 48). Based on her
own research into caring work, Bolton finds Hochschild's concept of emotional labour
lacking depth because she says that it only describes one particular kind of emotion
management relative to the service sector (i.e. that emotions are the product that is
sold). For Bolton, some emotions are freely given as part of social relations during
interactions with others. Bolton identifies here then that Hochschild's concept of emotion
work is under-developed. We do not always work on emotions at work because it is exchanged
for a wage – sometimes working on emotions can be useful as part of social relations. So
for instance, some employees that Bolton studied in the care industry (Bolton, 2000, 2005;
Bolton and Muzio, 2008; see also, Mann, 1999) use their emotions to facilitate their
interactions with others, but their emotions are not what is being sold. Bolton sees
Hochschild's concept of emotional labour as having too narrow a focus on capitalism and
puts forth her own typology of emotion management: ‘pecuniary’ with ‘prescriptive’, which
relate to instrumental performances of emotion in the workplace rooted in economic and
status gain and are empty of feeling; as well as ‘presentational’ emotion management,
which refers to the ‘basic socialized self’ (Bolton and Boyd, 2003: 297), and
‘philanthropic’, which is an intentional and freely chosen act of giving emotion to
customers and co-workers that are not prescribed by workplace feeling rules. In this
sense, according to Bolton, workers seek these ‘unmanaged spaces’ (2005: 102) in order to
express their true and ‘authentic’ selves. I agree with Bolton when she says that there is
more to emotion management at work than just exchanging emotions for a wage. But
Hochschild acknowledges this, too – she just doesn't advance this area of her research.
She does write briefly about emotion work as a theoretical concept, which addresses how
people manage emotion in their personal social relations, and how this act has use value
(Hochschild, 1983: 7; see page 181 in book for further discussion). It is true that this
is particularly under-developed. I suspect that Hochschild would agree with Bolton that
people work on their emotions at work for the purposes of maintaining social relations but
that capitalist organizations are slowly starting to encroach on this kind of emotion
management, threatening the ‘real self’, to advance their own strategies and agendas.
Bolton's assessment of Hochschild criticises her emotion management model for constructing
a ‘crippled actor’ who is overly constrained by feeling rules in the workplace. Bolton
instead contends that her studies show the opposite, that employees actively choose how to
follow workplace feeling rules (2003) and retain control over managing their emotions.
However Bolton's criticism is incorrect – the actor is not ‘crippled’ yet; Hochschild is
warning about this being a possibility if capitalist organizations are permitted to
commodify emotion management. Hochschild is trying to preserve the idea of free will and
agency, that is, the intentional and choosing individual, just as much as Bolton. What
Bolton appears to be arguing is simply a matter of degree – the degree to which an
individual's agency to negotiate structured feeling rules is (un)constrained at work.
Hochschild is not describing someone who is without agency, only that this agency is
tightly managed in the workplace and that this could get worse. Both Hochschild and
Bolton's approaches to emotion management still rely on the idea of an authentic, choosing
individual, in short, a true self. Just as Bolton has criticised Hochschild for creating
an individual with no agency, I too would criticise Bolton for conceptualising an
individual with too much agency, drawing on the words of Brook, for ‘claiming a form of
supra-autonomy for emotion work’ (Brook, 2009: 540).

<h>THE PROBLEM WITH THE ‘REAL’ SELF</h>
--------------------------------

What is missing from both Hochschild's (1983) and Bolton's (2005) theoretical framework is
a way of explaining how the individual interacts with structured feeling rules that does
not rely on a true or real self. The main criticism that is generally levelled at theories
that are based on the notion of a real self with an intangible core is that it constructs
a wholly agentic and reflexive individual (Bolton, 2005; Bolton and Boyd, 2003; Giddens,
1991, 1994; Urry, 2000; Beck, 1992, 1994) who is able to stand outside of social structure
(Bourdieu, 1984). What is needed to resolve the problems that arise out of centring theory
on a real self is a way to overcome the antimony between the personal and the social, and
structure and agency. To put it another way, a conceptual bridge between the mind and the
body is needed to better explain how emotion management occurs. Tonkens (2012) also
identifies this problem in Hochschild's work (1979, 1983, 1998, 2003). Tonkens argues
that, ‘There is a theoretical lacuna in Hochschild's work on how relationships between
individual emotions, social interactions, and large-scale processes like globalization and
commercialization relate to one another’ (2012: 196). She suggests that Hochschild
struggles to overcome the analytical gap between core micro concepts and macro level
concepts.

<h>BOURDIEU AND HABITUS</h>
--------------------

I want to suggest that Bourdieu (1984) offers a more fruitful way of explaining continuity
across moments (which Hochschild attempts to do by drawing on the notion of a real self)
in his theory of the self as embodied history. Bourdieu describes that a person's embodied
history is the accrual of memories and knowledge that are embedded as dispositions (1984).
This conceptual device is described by Bourdieu as a person's habitus (1984). A person's
habitus disposes a person to think, feel and act in ways that are the outcome of their
‘conditions of existence’ (Bourdieu, 1990: 52). The habitus then is formed out of ‘systems
of durable, transposable dispositions, structured structures predisposed to function as
structuring structures’ (Bourdieu, 990: 53). This means that a person will feel in a way
that is shaped by ‘generative principles’ (1990: 53) that provide a structure and logic
with ‘no active conscious intent’ (Addison, 2016). This means that a person is a product
of history and their particular moment in time, and as such delineates relationality
across structure and agency. Using Bourdieu's concept of the habitus it is possible to
think about the self more as a unique set of embodied dispositions that we use to
strategize our actions and our feelings. This means that there is no need to think of the
self as an intangible core or a real self that can be criticised for a ‘supra-autonomy’
(Brook, 2009: 540) that exists outside of social structure (Barbalet, 2001, 2002).
Moreover, the notion of a ‘real self’ that emerges in Hochschild's interviews with flight
attendants (e.g. ‘I was not being myself’) is much better framed as a discussion about
reflexivity, in two ways: firstly, on an epistemological level – this involves scholars ‘
being reflexive regarding how knowledge is generated, produced, represented and
legitimated’ (Addison, 2016: 18; see also Bourdieu and Wacquant, 1992); and secondly, by
critically engaging with how the individual is being reflexive about themselves in the
world (Skeggs, 2002) and builds a narrative around this (Lawler, 2008). Whilst some
individuals may feel they possess an inner self that is real and authentic, I argue that
this is a perception that Hochschild does not sufficiently interrogate. Hochschild used
the concept of the real and false self in her model of emotions. In contrast, I want to
draw on Bourdieu to argue that we use dispositions as knowledge of how to act and feel in
certain situations, and knowledge of how to express, and importantly manage, our emotions.
Using this model of the self avoids the criticism directed at Hochschild that individuals
are overly structured by feeling rules (Bolton, 2005), as well as the criticism levelled
at Bolton (2005) by Brook (2009) that individuals are able to stand outside of structure
and seek out ‘unmanaged spaces’ (Bolton, 2005: 102) as agentic and autonomous individuals.
Moreover, Bourdieu suggests that we are all already born into social games that have
started without us. We are immersed in the social world and acquire dispositions as we
grow that orient us to the correct way to do things in certain social spaces and around
different people. We grow accustomed to the different rules and principles that structure
different spaces meaning that we ‘fit in’. By thinking of the formation of the self in
this way, it also avoids the problem of the apriori self – where we are born with a unique
essence, or as Hochschild puts it, an ‘inner jewel’ (1983: 34) that makes us who we are
and enables us to be autonomous. For Bourdieu, this is unnecessary: he explains the
formation of the self as being socialized into the ways of game playing from birth through
our habitus and position in the field so that we develop a ‘feel for the game’ (Bourdieu,
1990: 67). Playing games involves fitting in with the ‘right ways of being and doing’
(Bourdieu, 1986, 1990: 511) in certain social spaces. This practice of fitting in
convincingly, and having the right habitus, involves (amongst other things) managing our
emotions. Having a feel for the game Bourdieu describes as ‘the sense of the imminent
future of the game the sense of the direction (sens) of the history of the game that gives
the game its sense’ (1990: 82). How well we play social games depends on our embodied
history (habitus), the position we hold in the field, and the different resources
(material and embodied capital) we have at our disposal to assist us (Bourdieu, 1984).
That said, it is important that the habitus is not viewed as a concept which portrays the
individual as a cultural dupe. Whilst the individual is immersed in the social world
generally partaking in practices that are familiar to their habitus, there are significant
moments when the individual is not at ease and it is these points that produce critical
reflexivity for the individual. Not being familiar with the game can lead to feelings of
being out of place – like a fish out of water (Bourdieu, 1990). Put another way, this can
feel like we do not know what to do, how to think or feel, in a certain situation (see
Addison, 2016) and it is in these critical moments that change and agency happen. However,
it is this feeling of being uneasy with our surroundings, like we don't fit in, that
Hochschild mis-identifies as a splitting of the self – a false self then where we put on a
performance of what we think is expected of us (I was not being myself). However, this
feeling of unease and conscious performance, I would argue, is connected to an awareness
of a lack of knowledge of how to act and feel in a situation. This emotional dissonance
then is not an argument to support the idea of a false self, but rather indicates a
feeling of being out of place in a certain social space and around certain people.

<h>CONCLUSIONS</h>
-----------

It has been my intention here to show that feeling out of place, or not being ourselves in
certain social situations, is not down to a dichotomy between a real and false self as
Hochschild tries to unsuccessfully set up. Rather, I have argued here that this feeling of
‘not being myself’ arises because we do not possess the required knowledge dispositions or
embodied practice, or have the right embodied history, in order to act comfortably in
certain situations – therefore we are reflexive of our social position and feel uneasy as
if we are not ourselves. Instead of the idea of a real self constrained by feeling rules,
I have argued that individuals use their embodied histories as a way of understanding and
making sense of the prevailing dominant symbolic structures. Acquisition of this knowledge
of how things ought to be done is sedimented as dispositions over time, creating a
personal history, which is then drawn upon to strategize future practice. This means then
that there is no need to argue, as Hochschild does, about what version of the self is
‘real’ and what is ‘false’: fundamentally all aspects of one's self and performances are
real. Some employees sense that their embodied histories don't fit well within social
space. These people may find that they repeatedly have to adjust their practices, even
when they feel uncomfortable, in order to fit in with a legitimated value system
structuring how they ‘ought’ to be (see Bathmaker et al., 2013; Reay et al., 2009). Then
again, those who find themselves feeling ‘out of place’ (Reay et al., 2009) may subvert
structured feeling rules in the workplace, they may develop alternate ways of fitting in
within or without the rules, they may collude with colleagues and share anger and humour
as a strategy for dealing with exploitations of their emotional labour. The concept of
embodied history works much better with these ideas of emotion management then than
Hochschild's idea of the real self. It has explanatory power without theorising
performances as ‘false’. I argue that it is more appropriate to critically consider why
acting a certain way, and managing emotion, in a particular space can seem odd and make us
feel ill at ease. I have suggested here that our embodied histories can feel out of place
in the workplace because we may be used to a different way of doing things in our day-to-
day lives (see Addison, 2012; 2016). The workplace can exploit our ability to shape
ourselves into someone we are told we ought to be, and this can hold us in a state of
being ill at ease. And so, entering a space that has dominating structured feelings rules
which are different to our own embodied feeling rules obliges us to manage and display our
feelings, perhaps in uncomfortable and unfamiliar ways. However, I would again reiterate
that this is not evidence of a real and false self, but rather highlights the self-
conscious feelings we may have in certain situations and around certain people.


<h>REFERENCES</h>
----------

  [2] Sharon C. Bolton, Carol Boyd. Trolley dolly or skilled emotion manager? Moving on from as Hochschild's managed heart. doi:10.1177/0950017003017002004
  [3] Sharon Bolton, Daniel Muzio. The paradoxical processes of feminization in the professions: The case of established, aspiring and semi-professions. doi:10.1177/0950017008089105
  [8] Paul Brook. In critical defence of 'emotional labour': Refuting Bolton's critique of Hochschild's concept. doi:10.1177/0950017009337071
  [9] Will Atkinson. Economic crisis and classed everyday life: Hysteresis, positional suffering and symbolic violence. doi:10.1057/9781137016386
  [10] Cindy L. Cain. Integrating Dark Humor and Compassion: Identities and Presentations of Self in the Front and Back Regions of Hospice. doi:10.1177/0891241612458122
  [12] Rebecca J. Erickson. The Importance of Authenticity for Self and Society. doi:10.1525/si.1995.18.2.121
  [25] Sandi Mann. 'People-work': Emotion management, stress and coping. doi:10.1080/0369880410001692247
  [28] Evelien Tonkens. Working with Arlie Hochschild: Connecting feelings to social change. doi:10.1093/sp/jxs003
  [29] Michelle Addison. Knowing your way within and across classed spaces: The (re)making and (un)doing of identities of value within higher education in the UK. doi:10.1057/9781137271129
  [30] Michelle Addison. Social games and identity in the higher education workplace: Playing with gender, class and emotion. doi:10.1057/978-1-137-51803-3
  [35] Ann Marie Bathmaker, Nicola Ingram, Richard Waller. Higher education, social class and the mobilisation of capitals: recognising and playing the game. doi:10.1080/01425692.2013.816041
  [38] Sharon C. Bolton. Who cares? Offering emotion work as a 'gift' in the nursing labour process. doi:10.1046/j.1365-2648.2000.01516.x
<ART>Pain thresholds, pain-induced frontal alpha activity and pain-related evoked potentials are associated with antisocial behavior and aggressiveness in athletes
================================================================================

Authors: Christopher Ring, Maria Kavussanu, Adrian Willoughby
DOI: 10.1016/j.psychsport.2015.09.003
Year: 2016  |  Pages: 303-311
ASJC codes: 3202
Keywords: Aggression, Antisocial behavior, Electroencephalography, Moral disengagement, Pain

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: Deficiencies in perceptual and cognitive functions have been linked with antisocial and aggressive behavior. To test whether these putative relationships generalize to sport – a context where such behavior is common – we determined the extent to which pain thresholds and cortical activity in response to painful electrical stimulation were associated with antisocial and aggressive behavior in sport; we also examined their link to moral disengagement. Design: A cross-sectional design was used. Method: Ninety-four participants completed questionnaires, had their pain threshold determined, and then had their central and frontal pain-related cortical activity recorded while they were electrically stimulated at supra-threshold intensity. Results: Subjective pain thresholds were positively related while pain induced frontal alpha power was negatively related to antisocial behavior and aggressiveness. Central pain evoked potential amplitudes were negatively related to aggressiveness and moral disengagement. Conclusions: Sensitivity to and cortical processing of noxious stimuli were reduced in individuals who more frequently behave antisocially and aggressively when playing sport and who are more likely to use psychosocial maneuvers to justify their harmful behavior. Our findings reveal that pain-related deficits are a feature of individuals who engage in more frequent antisocial and aggressive behavior in the context of sport.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Sport is a social context where moral issues are highly relevant (for reviews see
Kavussanu, 2008, 2012). Research has shown that during competitive games, team sport
players deliberately foul, physically intimidate, and try to injure their opponents (e.g.,
Kavussanu, Seal, & Phillips, 2006; Kavussanu, Stamp, Slade, & Ring, 2009). Thus, it is
important to improve understanding the factors associated with antisocial and aggressive
behavior, which encompasses acts intended to harm or disadvantage another individual
(Kavussanu, 2012) and harm another individual (Anderson & Bushman, 2002), respectively.
Although much research has examined antisocial and aggressive behavior in sport from a
social psychological perspective, more recently researchers have begun to investigate this
important topic from a cognitive neuroscience perspective (e.g., Kavussanu, Willoughby, &
Ring, 2012; Micai, Kavussanu, & Ring, 2015). Research in non-sport contexts has revealed
differences in how the brains of antisocial and aggressive individuals respond to sensory
and cognitive demands compared to other individuals (for reviews see Blair, 2001; Volavka,
1990, 1999). For instance, these reviews discuss evidence that violent individuals are
characterized by structural and functional abnormalities in their frontal and temporal
lobes. We aimed to extend these findings to the sport context. In team sports that involve
physical contact between players, such as association football, basketball, field hockey,
and rugby, antisocial and aggressive behaviors are relatively common occurrences during
games (Bredemeier & Shields, 1986; Kavussanu, 2012). Accordingly, the current study
determined whether abnormal cortical processing and perception of pain is a feature of
individuals who engage more frequently in antisocial and aggressive behavior when playing
competitive team sport.

<hs>  Pain sensitivity</hs>
  ~~~~~~~~~~~~~~~~

Antisocial behavior and emotional detachment are the two key defining features of
psychopathy (Blair, 2001). Early clinical observations noted that psychopaths often fail
to avoid punishment (Cleckley, 1959; Hetherington & Klinger, 1964). Experimental research
has since documented that psychopaths are characterized by impaired aversive conditioning
(Flor, Birbaumer, Hermann, Ziegler, & Patrick, 2002; Hare & Quinn, 1971; Lykken, 1957),
blunted conditioned anticipatory arousal prior to an impending noxious stimulus (Hare,
1965), reduced blink responses to noxious stimuli (Benning, Patrick, & Iacono, 2005;
Patrick, Bradley, & Lang, 1993), and reduced pain sensitivity (Fedora & Reddon, 1993;
Hare, 1968; Hare & Thorvaldson, 1970; Schalling, 1971; Schalling & Levander, 1964). Taken
together, these data suggest that the increased frequency of antisocial behavior in
psychopaths may be linked to their relative insensitivity to aversive stimuli. Further
support for this proposal comes from studies showing that pain sensitivity is lower in
aggressive and violent individuals (Niel, Hunnicut-Ferguson, Reidy, Martinez, & Zeichner,
2007; Reidy, Dimmick, MacDonald, & Zeichner, 2009; Seguin, Pihl, Boulerice, Tremblay, &
Harden, 1996). Seguin et al. (1996) reported that boys with higher pain tolerance to
pressure stimulation were characterized by increased history of physical aggression based
on teacher reports. Niel et al. (2007) used the response choice aggression paradigm and
found that males with higher pain tolerance to electrical stimulation administered higher
intensity shocks and more maximal intensity shocks to their opponents. Similarly, Reidy et
al. (2009) found that male (but not female) participants with higher pain tolerances
scored higher on self-reported measures of verbal and physical aggression. Although the
mechanism underlying this pain-aggression phenomenon has yet to be identified, a number of
candidates have been mooted. It has been suggested that pain tolerant individuals may
underestimate the degree of pain inflicted on their victims or may have been toughened up
by frequent fights (Sequin et al., 1996). Based on this evidence, we tested the
possibility that relative insensitivity to pain may be a feature of athletes who engage
more frequently in antisocial and aggressive behavior when playing sport. In team contact
sports, physical contact during competitive games can lead to unpleasant sensory and
emotional experiences associated with tissue damage (i.e. pain). Antisocial behavior and
aggression in team contact sports might be linked with pain sensitivity for various
reasons: Pain tolerant athletes may be more likely to commit physical antisocial and
aggressive acts because they cannot empathize with their victims (Stanger, Kavussanu, &
Ring, 2012; Stanger, Kavussanu, Willoughby, & Ring, 2012) because of impaired cognitive
perspective taking or emotional empathic concern and personal distress (cf. Sequin et al.,
1996).

<hs>  Pain-related evoked potentials</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Researchers (e.g., Bromm & Lorenz, 1998) often supplement subjective reports of pain with
its objective neurophysiological correlates to paint a more complete picture of the
psychological and physiological processes implicated in the perception and processing of
noxious stimuli. However, to our knowledge, no study has assessed cortical evoked
potentials to painful stimuli to explore the central processes underlying the antisocial
behavior–pain relationship. The electroencephalogram (EEG) represents a means of assessing
cortical activity that involves the recording of electrical activity on the scalp to
detect voltages generated inside the brain. Evoked potentials represent the cortical
activity elicited in response to the presentation of an exteroceptive stimulus, such as a
painful electrical stimulus. The most commonly studied pain-related evoked potentials are
the N2 and P2 potentials, which refer to the second negative and positive peaks,
respectively, of the cortical response to a noxious stimulus and represent the cortical
activity that results from processing a painful stimulus (Treede, Kenshalo, Gracely, &
Jones, 1999). These scalp potentials are measured at the vertex because they are reliably
found to be largest in amplitude at this location. Pain-related evoked potentials reflect
pain processing, that is increasingly painful stimuli elicit increasingly larger
potentials (Bromm & Lorenz, 1998). It is possible that attenuated pain-related evoked
potentials are associated with the tendency to commit antisocial and aggressive acts.

<hs>  Frontal cortical activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

There is evidence to suggest that frontal dysfunction, assessed using EEG, is a feature of
aggressive individuals (Volavka, 1990). For instance, one study noted that violent
behavior in psychiatric patients was negatively correlated with frontal alpha band EEG
activity, particularly resting activity in the left hemisphere (Convit, Czobor, & Volavka,
1991). Similarly, brain imaging studies have implicated reduced prefrontal cortical
activity (Raine, Buchsbaum, & LaCasse, 1997) and frontal lesions (Damasio, Grabowski,
Frank, Galaburda, & Damasio, 1994; Grafman et al., 1996) with antisocial and aggressive
behavior. These observations are compatible with the proposal that aggressive behavior is
determined by a circuit in the brain comprising the orbitofrontal cortex, anterior
cingulate, and amygdala (Davidson, Putnam, & Larson, 2000). In EEG studies, prefrontal
cortical activity is typically indexed by the amount of activity in the alpha frequency
band: A fast Fourier transform is applied to the raw EEG waveform to yield the spectral
power of the EEG signal with a frequency of between 8 and 12 cycles per second. High alpha
activity was originally interpreted as cortical idling (Pfurtscheller, Stancak, & Neuper,
1996), but more recently has been viewed as reflecting a sensory gating mechanism
involving inhibition of task-irrelevant and activation of task-relevant areas (Jensen &
Mazaheri, 2010; Schurmann & Basar, 2001). Although it is possible to assess frontal alpha
brain activity under resting conditions, recent research has found better results using
stimulus induced activity (e.g., Coan, Allen, & McKnight, 2006). Taken together, there is
sufficient evidence to suggest that relatively attenuated pain-induced frontal brain
activity may be associated with the tendency to behave antisocially in sport.

<hs>  Moral disengagement</hs>
  ~~~~~~~~~~~~~~~~~~~

Moral disengagement refers to the psychosocial mechanisms people use to minimize negative
affect when they engage in transgressive behavior (Bandura, 1991; Boardley & Kavussanu,
2011). It allows individuals to engage in conduct that violates their personal standards
without experiencing intense negative emotions that usually accompany such behavior. Moral
disengagement operates by mentally reconstruing harmful behaviors into benign acts,
minimizing personal accountability for harmful behavior, misrepresenting the injurious
effects that result from such behavior, and blaming the nature or actions of the victim.
Previous research has found that players who have the propensity to morally disengage are
more likely to report engaging in antisocial behaviors toward other players (Boardley &
Kavussanu, 2011). Given the link between blunted emotion and antisocial behavior in
violent offenders and psychopaths (e.g., Blair, 2001; Cleckley, 1959), it is possible that
moral disengagement may be associated with attenuated sensitivity and responses to painful
stimulation. We could speculate on how moral disengagement might be linked with reduced
pain. The distortion of consequences mechanism operates on the consequences of detrimental
behavior and downplays the harm caused to victims: Individuals who minimize the harm they
cause are more likely to repeat such actions (Bandura, 1999). Accordingly, athletes who
feel little pain when they are hit, kicked or punched may also underestimate the
seriousness of the injuries they cause (Boardley & Kavussanu, 2011), and, therefore are
more likely to act aggressively (Niel et al., 2007; Reidy et al., 2009; Seguin et al.,
1996). Some moral disengagement mechanisms operate on the agency of action by obscuring or
minimizing one's role in the harm one causes (Bandura, 1999); these are displacement and
diffusion of responsibility. It is possible that players who feel less pain are also those
who obscure and minimize harm to others. With these possibilities in mind, the current
study investigated the link between moral disengagement and pain.

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

In sum, research has highlighted a relationship between pain and antisocial/aggressive
behavior in non-athletes. However, to our knowledge, no study has examined the links
between pain sensitivity or cortical processing of painful stimuli and antisocial
behavior, aggressiveness, and moral disengagement in sport. We aimed to extend previous
research by obtaining both self-reported and cortical measures of pain to examine whether
pain is related to antisocial behavior and aggressiveness (i.e., the tendency to become
aggressive, Maxwell & Moores, 2007) in sport. The first purpose of the study was to
determine whether subjective pain thresholds, pain induced frontal alpha activity, and
pain-related evoked potentials are associated with antisocial behavior and aggressiveness
in sport. We expected that more frequent antisocial behavior and greater aggressiveness
would be negatively associated with the subjective experience (i.e., higher pain
thresholds) and cortical processing (i.e., less pain-induced frontal alpha activity,
smaller pain-related evoked potential amplitudes) of pain. A second purpose was to
determine whether pain (measured by subjective and objective methods) is related to moral
disengagement in sport. We expected that moral disengagement would be negatively
associated with self-reported pain and cortical measures of pain-related processing. Our
hypotheses were tested using new analyses performed on an existing dataset (Kavussanu,
Willoughby, & Ring, 2012).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Ninety-four team sport athletes (48 males, 46 females), with a mean age of 20.95 (SD =
2.72) years and 8.51 (SD = 4.31) years playing experience were paid £20 for participating.
Their main team sport was association football (31%), field hockey (26%), basketball (22%)
rugby (18%), and water polo (3%). All sports were contact sports. We recruited athletes
from these sports because contact sports have inherent potential for injury and therefore
higher likelihood for antisocial and aggressive behavior to occur and moral issues to
arise (Bredemeier & Shields, 1986). Athletes from a variety of contact sports were
recruited to increase the generalizability of our findings. All participants were free
from neurologic and psychiatric disorders and medications. They were asked to refrain from
alcohol, caffeine and smoking for at least 12 h prior to testing.

        <hss>Antisocial behavior</hss>

        Antisocial behavior in sport was measured using the 8-item antisocial behavior
        toward opponents scale of the Prosocial and Antisocial Behavior in Sport Scale
        (Kavussanu & Boardley, 2009; Kavussanu, Stanger, & Boardley, 2013). Participants
        were asked to rate how often they engaged in different behaviors when playing
        their team sport. An example item is “Tried to injure an opponent”. Each item was
        rated on a 5-point Likert scale, anchored by 1 (never) and 5 (very often).
        Kavussanu and Boardley (2009) reported very good internal consistency (α = .86)
        for this subscale.

        <hss>Aggressiveness</hss>

        Competitive aggressiveness was measured using the 6-item aggressiveness scale of
        the Competitive Aggressiveness and Anger scale (Maxwell & Moores, 2007). The stem
        “When playing your team sport how often have you behaved, felt or thought that … ”
        was followed by six items measuring aggressiveness. An example item is “Violent
        behavior directed toward an opponent is acceptable”. Each item was rated on a
        5-point Likert scale, anchored by 1 (never) and 5 (very often). Maxwell and Moores
        (2007) have provided evidence for the factorial validity and reliability (α = .84)
        of this scale.

        <hss>Moral disengagement</hss>

        Moral disengagement in sport was measured using the 8-item Moral Disengagement in
        Sport Scale–short (Boardley & Kavussanu, 2008). Participants were asked to
        indicate their level of agreement with a range of statements concerning thoughts
        and feelings they may have in sport on a 7-point Likert scale, anchored by 1
        (strongly disagree) and 7 (strongly agree). This scale includes an item for each
        of the eight mechanisms of moral disengagement. An example item is “It is okay to
        treat badly an opponent who behaves like an animal”. Boardley and Kavussanu (2008)
        reported very good internal consistency (α = .85) for the scale.

<hs>  Noxious stimulus</hs>
  ~~~~~~~~~~~~~~~~

A noxious electrical stimulus was delivered using a nociception-specific concentric
electrode designed to selectively activate A-delta fibers (Katsarava et al., 2006; Kaube,
Katsarava, Kaufer, Diener, & Ellrich, 2000). Each stimulus consisted of a double pulse.
Each rectangular wave pulse lasted 500 μs separated by 100 μs; this delay is below the
threshold required to discriminate the two stimuli, thus they were perceived as a single
stimulus. The stimulating electrode was placed on the supraorbital nerve above the left
eye (Cuzalina & Holmes, 2005), and a constant current stimulator (Model DS7A, Digitimer
Ltd, UK) provided the stimulation.

<hs>  Pain threshold</hs>
  ~~~~~~~~~~~~~~

The subjective pain threshold was determined using a two-stage procedure. First, the
participant rated the electrical stimulation on a 5-point scale adapted from Tursky and
O'Connell (1972): 0 (feel no sensation), 1 (feel any sensation), 2 (uncomfortable
sensation), 3 (painful sensation), 4 (don't want to go any higher). The stimulation was
increased from .2 mA in steps of .2 mA until the stimulation became painful, that is the
participant reported “3” on the scale. Using this as an initial estimate, the
participant's pain threshold was determined using an up–down staircase procedure: Stimulus
intensity was increased by .1 mA if the prior stimulation was rated as not painful by the
participant, or decreased by .1 mA if it was rated as painful (Levitt, 1971). When the
participant had reported that the stimulation was painful on three non-consecutive
occasions, the pain threshold was calculated as the average of the last two peak
stimulation values. These procedures have been used in previous research (cf., Wilkinson,
McIntyre, & Edwards, 2013).

<hs>  Pain induced alpha power and pain related evoked potentials</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A noxious electrical stimulus, at an intensity corresponding to 125% of pain threshold (M
= 1.68, SD = 1.08 mA), which was perceived as a single pinprick-like pain, was delivered
while participants viewed a small black fixation cross on a white screen on six trials. On
other trials (data not reported here), it was delivered while participants viewed a
picture. The pictures were neutral (e.g., players standing or moving), pleasant (e.g.,
players celebrating, semi-naked players), and unpleasant (e.g., players being hurt or
badly injured) in valence (for further details see Stanger, Kavussanu, Willoughby, et al.,
2012). Electrical stimulation occurred every 20–25 s. The EEG was recorded using a
32-channel BioSemi ActiveTwo system (BioSemi, Netherlands), at 512 Hz, and was re-
referenced to average earlobe electrodes offline. Electrophysiological data processing was
performed using EEGLAB (Delorme & Makeig, 2004). The EEG was high-pass filtered using a
finite impulse response windowed-sinc filter with a half-amplitude cut-off at 1 Hz and a
.4 Hz transition band. We performed a fast Fourier transform (1 Hz bins) on the artifact-
free epochs, and then computed power (dB) in the alpha (8–12 Hz) frequency band at left
and right frontal (F3 and F4) sites in the seconds before and during the two second window
following onset of painful stimulation. These values were then log-transformed and
averaged across sites. The key components of the pain-related evoked potential (see Fig.
1) are the amplitudes (measured in microvolts) of the second negative (N2) and positive
(P2) peaks in the event related potential following painful stimulation (e.g., Edwards,
Inui, Ring, Wang, & Kakigi, 2008). Thus, we calculated the N2 (in the 100–200 ms post-
stimulation window) and P2 (in the 200–300 ms post-stimulation window) peaks. We focused
on the Cz electrode, since this is where the N2 and P2 potentials are maximal (e.g.,
Katsarava et al., 2006). This was confirmed in the present study by examination of the
scalp maps (see Appendix 1). The amplitude of the pain evoked potentials at the vertex
(i.e., Cz) were measured relative to a 100 ms pre-stimulus baseline and calculated as the
average amplitude of the seven data points around the peak value during the 100–200 ms
time window for the N2 potential and the 200–300 ms time window for the P2 potential
(i.e., the peak value and the three data points either side, corresponding to a window of
approximately 12 ms).

<hs>  Procedure</hs>
  ~~~~~~~~~

The study protocol was approved by the local research ethics committee and each volunteer
gave informed consent to participate. At the start of the testing session, participants
completed the self-reported measures of antisocial behavior, aggressiveness and moral
disengagement. Following instrumentation, their pain threshold was determined. After
sitting quietly for five minutes, they were instructed about the next task: They were told
to always focus on the screen located in front of them and that their forehead would be
stimulated when either a fixation cross or picture was on screen. In the task, the
participant's pain related evoked potentials and pain induced frontal alpha activity were
recorded as described above.

<hs>  Descriptive statistics and alpha coefficients</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The means and standard deviations of the scales that measured antisocial behavior,
aggressiveness, and moral disengagement are presented in Table 1. This table also presents
alpha coefficients of the variables used in this study; internal consistency of all scales
was good. On average, players reported that, when playing sport, they behaved antisocially
toward opponents rarely or sometimes and reported aggressiveness rarely. They also
reported moderate levels of moral disengagement. These scores are in line with those
reported in previous research (e.g., Boardley & Kavussanu, 2008; Kavussanu & Boardley,
2009; Stanger, Kavussanu, Boardley, & Ring, 2013; Stanger, Kavussanu, & Ring, 2012;
Stanger, Kavussanu, Willoughby, et al., 2012). Pearson correlations showed that moral
disengagement was positively related to antisocial behavior, r(92) = .48, p < .001, and
aggressiveness, r(92) = .67, p < .001. The means and standard deviations of the subjective
pain threshold, pain induced frontal alpha power, and pain evoked potential amplitudes are
also shown in Table 1. The pain threshold for the noxious trigeminal stimulus is
compatible with prior research (e.g., Katsarava et al., 2006). The scalp map for the pain
related evoked potential confirmed that the N2 and P2 pain evoked potentials were maximal
at the central electrode site Cz (see Appendix 1). We conducted a series of one-sample
t-tests to determine whether the pain related evoked potentials and pain induced alpha
activity were significantly different from zero. These tests confirmed significant N2,
t(93) = 16.07, p < .001, and P2, t(93) = 19.43, p < .001, pain evoked potentials (see Fig.
1). A one-sample t-test also confirmed that the pain induced frontal alpha activity was
greater than zero, t(93) = 5.74, p < .001. Frontal alpha was lower in the seconds after
noxious stimulation compared to the seconds before stimulation, t(93) = 5.04, p < .001,
with the decrease averaging −.96 (SD = 1.85) dB.

<hs>  Correlation analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

Pearson correlations were computed between the pain variables (pain threshold, pain-
induced frontal alpha, pain-related evoked potentials) and antisocial behavior,
aggressiveness, and moral disengagement (see Table 1). The pain threshold was positively
related to both antisocial behavior and aggressiveness: Players who acted more
antisocially when playing team sport and players who reported more aggressiveness in sport
tended to be less sensitive to noxious trigeminal stimulation. The pain threshold was not
significantly related to moral disengagement. Frontal alpha power associated with the
processing of noxious electrical stimulation was negatively associated with antisocial
behavior and aggressiveness. These findings indicate that the players who acted more
antisocially when playing team sports and players who displayed more aggressiveness in
sport were characterized by less frontal alpha activity when exposed to painful stimuli.
The negative N2 potential was positively related to moral disengagement, whereas the
positive P2 potential was negatively related to moral disengagement and aggressiveness. In
brief, smaller pain related evoked potential amplitudes were a feature of players who
reported higher moral disengagement and aggressiveness in sport.

<hs>  Gender as a moderator</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Reidy et al. (2009) reported that the pain–aggression relationship was moderated by
gender, with the effect evident for males but not females. To investigate this possibility
in our study, we conducted moderation analysis using bootstrapping (Preacher & Hayes,
2008) and PROCESS for SPSS Release 2.13 (Hayes, 2013) to examine whether gender moderated
the relationships between the pain variables (pain threshold, pain-induced frontal alpha,
pain-related evoked potentials) and antisocial behavior, aggressiveness, and moral
disengagement. Bootstrapping was set at 5000 samples with bias corrected 95% confidence
intervals; an effect was significant when the Confidence Interval (CI) did not contain
zero. Results of these analyses indicated that the associations were not moderated by
gender, ts = .03–1.45, ps = .15–.97, with one exception. Gender moderated the relationship
between moral disengagement and the N2 component of the pain-related evoked potential, b =
5.566, 95% CI = .237, 10.895; t = 2.08, p = .04. Moral disengagement was associated with
reduced N2 potential in males, b = 4.113, 95% CI = .790, 7.436; t = 2.46, p = .02, but not
females, b = −1.453, 95% CI = −5.619, 2.713; t = .69, p = .49.

<h>DISCUSSION</h>
----------

Deficiencies in pain processing have been linked with antisocial and aggressive behavior
in diverse populations in non-sport contexts. To test whether these findings generalize to
sport, we examined the extent to which pain thresholds and cortical activity in response
to painful electrical stimulation were associated with antisocial behavior, aggressiveness
and moral disengagement in the context of sport. Athletes' subjective pain threshold was
positively related while pain induced frontal alpha power was negatively related to both
antisocial behavior and aggressiveness. Moreover, central pain evoked potential amplitudes
were negatively related to aggressiveness and moral disengagement. Thus, sensitivity to
and cortical processing of noxious stimuli were reduced in both male and female athletes
who behaved more antisocially, displayed more aggressiveness, and were more prone to
morally disengage when playing competitive sport.

<hs>  Pain sensitivity</hs>
  ~~~~~~~~~~~~~~~~

In support of our hypothesis, relative insensitivity to painful electrical stimulation was
a feature of athletes who engaged more frequently in antisocial conduct and who were more
accepting of and willing to be aggressive when playing sport. This finding is compatible
with the available literature in other contexts documenting reduced pain sensitivity in
aggressive and violent individuals (e.g., Niel et al., 2007; Reidy et al., 2009; Seguin et
al., 1996). In contrast to Reidy et al. (2009) gender did not moderate the
pain–aggressiveness relationship. To date, no mechanism has been identified to account for
these findings. Reduced pain sensitivity could lead to misattributions related to pain
inflicted on a victim, whereby perpetrators who are less sensitive to and more tolerant of
pain may misperceive the degree of pain experienced by another and, therefore, may be more
willing to use violence during interpersonal conflict (Niel et al., 2007). Thus, athletes
could engage in antisocial acts because they do not believe they are hurting their
opponents as much as they really are. Our findings resonate with Niel et al.'s (2007)
conclusion that insensitivity to pain (high pain tolerance) may increase the likelihood of
aggression during an interaction where competition and provocation occur. Provocation
occurs in competitive team sport, and therefore, aggressive competitors may not appreciate
the consequences of their actions for their opponents when playing sport. The current data
provide preliminary evidence to support the proposal that relative insensitivity to pain
is related to the frequency with which players engage in antisocial behavior when playing
sport because regular perpetrators may underestimate the amount of pain inflicted on their
victims.

<hs>  Pain-related evoked potentials</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We found that the N2 and P2 pain related evoked potentials were blunted in athletes
reporting high levels of moral disengagement, while the P2 component of this potential was
also blunted in athletes reporting high acceptance of aggression and willingness to be
aggressive in sport. Moral disengagement mechanisms allow players to engage in
transgressive conduct without experiencing strong negative emotions, such as guilt. We
found that players who used more moral disengagement were more likely to report engaging
in antisocial behaviors toward other players, in line with past studies (e.g., Kavussanu,
Ring, & Kavanagh, 2015; Stanger et al., 2013; Stanger, Kavussanu, & Ring, 2012). Since the
amplitudes of pain evoked potentials reflect pain processing, the current findings suggest
that players who are more aggressive and use psychosocial maneuvers to justify their
harmful behavior are more likely to have cortical deficits in how they respond to painful
stimulation. Extending the previous behavioral research linking pain insensitivity to
antisocial and aggressive behavior (e.g., Fedora & Reddon, 1993; Hare, 1968; Hare &
Thorvaldson, 1970; Niel et al., 2007; Reidy et al., 2009; Schalling, 1971; Schalling &
Levander, 1964; Seguin et al., 1996), the current study indicated that relatively
attenuated pain evoked potentials are associated with the tendency to accept and excuse
aggressive acts when playing sport.

<hs>  Pain-induced frontal cortical activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In line with our prediction, lower pain induced frontal brain activity was linked with
increased frequency of antisocial behavior and greater acceptance of and willingness to
aggress in sport. This finding is the first to link changes in frontal alpha to morally-
relevant behavior in sport and is compatible with previous evidence showing that frontal
dysfunction, assessed using EEG, is a feature of aggressive individuals (for review, see
Volavka, 1990). In line with previous research (see Peng, Babiloni, Yanhui, & Hu, 2015),
frontal alpha was suppressed in response to acute noxious stimulation, presumably
reflecting the effects of a pain-related gating mechanism on frontal areas (Jensen &
Mazaheri, 2010). Thus, antisocial behavior and aggressiveness were related to relatively
low alpha oscillatory activity in the context of suppressed activity in the frontal
regions of both hemispheres (cf. Convit et al., 1991). These results are also broadly
compatible with brain imaging studies that have found a link between antisocial and
aggressive behavior and prefrontal cortical activity (Raine et al., 1997) and frontal
lesions (Damasio et al., 1994; Grafman et al., 1996); they are also in line with the
suggestion that aggressive behavior is determined by a circuit in the brain comprising the
orbitofrontal cortex, anterior cingulate, and amygdala (Davidson et al., 2000). In sum, by
assessing pain induced frontal activation, we showed that reduced frontal alpha activation
induced by noxious electrical stimulation is associated with the tendency to engage in
harmful conduct when playing sport.

<hs>  Study limitations and future research directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our study yielded some novel findings but also has some limitations which should be noted
when interpreting the findings. First, only one stimulation site and one mode of
stimulation were used, leaving open the possibility that different effects may be a
feature of painful stimulation at other sites and other forms of painful stimulation.
Accordingly, the generalizability of the observed effects from trigeminal nociception to
other aspects of nociceptive processing remains to be confirmed in future research.
Second, we employed a cross-sectional design and therefore causal relationships cannot be
determined. Research using longitudinal and intervention designs that incorporate direct
observations of behavior during sport participation and other assessments sensorimotor
processes are now required. Finally, the correlation coefficients displayed in Table 1
ranged from r = .20 to .28, which, based on Cohen's (1992) definitions, where .10 is
small, .30 is medium, and .50 is large, can be considered medium-to-small effects. These
effect sizes should be used when interpreting the extent of the link between pain and
antisocial behavior/aggressiveness. Nonetheless, this study has several strengths,
including the use of a validated nociception-specific concentric electrode designed to
selectively activate nociceptive afferents, state of the art equipment for measuring
electroencephalographic signals, and a large sample size.

<h>CONCLUSION</h>
----------

In conclusion, our findings revealed a consistent pattern indicating that players who
perform and justify transgressive acts are characterized by relative insensitivity to
noxious stimulation. Building on previous research showing that increased pain tolerance
is associated with increased aggression (e.g., Niel et al., 2007; Reidy et al., 2009;
Seguin et al., 1996), the current study is the first to confirm the pain–behavior
relationship in objective neurophysiological indices of pain processing as well as a
subjective measure of pain sensitivity. It may be worth noting that antisocial behavior
seemed to be more closely associated with subjective pain threshold and alpha power
whereas moral disengagement was more closely linked with cortical processing of pain. The
reason for these differential relationships between moral variables and indices of pain
sensitivity cannot be established from the present study. Accordingly, future research is
now needed to establish the mechanisms underlying the pain-behavior and pain–cognition
relationships. Our findings suggest that a profile comprising insensitivity to pain and
blunted cortical responses to noxious stimulation may serve as a biobehavioral risk marker
for antisocial and aggressive athletes. In sum, relative pain-related deficits are more
likely to be a feature of individuals who engage more frequently in and excuse
transgressive conduct in sport.


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<ART>Participatory arts interventions promote interpersonal and intergroup prosocial intentions in middle childhood
================================================================================

Authors: Julie Van de Vyver, Dominic Abrams, Lauren Spinner, Joseph Pelletier, Shazza Y. Ali, Ioanna Kapantai
DOI: 10.1016/j.appdev.2019.101069
Year: 2019
ASJC codes: 3204
Keywords: Arts and creativity, Empathy, Intergroup bias, Prosocial intentions

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<h>ABSTRACT</h>
--------

We report the results of two experiments which test the potential of arts engagement for promoting prosocial intentions. Experiment 1 (N = 216) tested the impact of a participatory arts intervention (vs. a control condition) on children's empathy and interpersonal prosocial intentions. Experiment 2 (N = 174) tested the impact of a participatory arts intervention (vs. a control condition) on children's prosocial intentions toward outgroup members under competitive and non-competitive conditions. Experiment 1 showed that the participatory arts intervention significantly increased children's interpersonal prosocial intentions, but not their empathy. Experiment 2 showed that, under competitive conditions, the participatory arts intervention significantly increased prosocial intentions toward outgroup members, an effect that persisted for six months beyond the intervention. Under non-competitive conditions, the participatory arts intervention consolidated improvements in prosocial intentions toward outgroup members. Overall, the results confirm the hypothesis that participatory arts engagement can promote prosocial intentions during middle childhood.

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<h>PROSOCIALITY</h>
------------

Prosocial responses can broadly be understood as those aimed at benefitting others.
Examples of prosocial responses include helping, sharing with, and caring for others
(Abrams, Van de Vyver, Pelletier, & Cameron, 2015). Research shows that humans frequently
and intuitively engage in prosociality (Crockett, Kurth-Nelson, Siegel, Dayan, & Dolan,
2014). During early childhood, children develop the ability to accurately take the
perspective of another (e.g., in terms of goals, wants, needs and desires), to understand
another's negative emotional state (empathy), to recognise when a goal is unfulfilled, and
to detect the source of a problem (Dunfield, 2014; Paulus, 2018). These antecedents of
prosociality as well as prosocial responses themselves become integrated and well-
established by middle childhood (Dunfield, 2014). Experiences of, and engagement in,
prosociality are essential for personal and societal wellbeing. For example, engagement in
prosociality improves personal wellbeing among children (Flouri & Sarmadi, 2016),
adolescents (Layous, Nelson, Oberle, Schonert-Reichl, & Lyubomirsky, 2012), and adults
(Nelson, Layous, Cole, & Lyubomirsky, 2016). Human prosociality and cooperation are also
essential for tackling societal problems such as environmental degradation, humanitarian
crises, and inequality. Therefore, it is essential to understand the conditions that can
promote greater prosocial engagement.

<hs>  Intergroup prosociality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Importantly, children from the age of three develop an awareness of social categories, and
by age five they are more likely to help ingroup compared to outgroup members (Abrams et
al., 2015; Nesdale, 2004; Over, 2018; Sierksma, Thijs, & Verkuyten, 2015). This intergroup
bias in prosociality is evident across the lifespan (Levine, Cassidy, Brazier, & Reicher,
2002; Stürmer, Snyder, & Omoto, 2005), and has detrimental effects on societies across the
world. Intergroup bias has a clear developmental trajectory. Specifically, intergroup bias
tends to increase gradually from as young as three years and to peak during middle
childhood (Raabe & Beelmann, 2011). Moreover, the extent to which children display
intergroup bias, and the age at which they express intergroup bias, varies depending on
the complexity of the intergroup context (Rutland, Killen, & Abrams, 2010). For example,
when deciding whom to include in a club, children are more likely to justify inclusion on
the basis of group membership and stereotypes when there is only space for one child (and
two peers from different groups want to join) compared to when there are sufficient spaces
for all children (Killen, Pisacane, Lee-Kim, & Ardila-Rey, 2001). In other words, children
show less intergroup bias in straightforward (vs. complex) intergroup contexts and this
impact of situational complexity on intergroup bias appears from as young as four years of
age (Killen et al., 2001). Similarly, Abrams et al. (2015) demonstrated that children are
less likely to help outgroup members in a competitive (i.e., complex) context than in a
non-competitive (i.e., straightforward) context. Given that these types of situational
complexities are inherent across societies and given that prejudice against minority
groups is often associated with perceptions that they are competing for resources (Cuddy,
Fiske, & Glick, 2007; Van de Vyver, Leite, Abrams, & Palmer, 2018), it is important to
understand whether and how we can promote outgroup prosociality under competitive as well
as non-competitive contexts.

<h>ARTS ENGAGEMENT</h>
---------------

Artistic practices transcend geographic and historic boundaries, and it has been contended
that artistic expression is part of an evolutionary mechanism for creating and maintaining
social ties within humans (Pearce, Launay, & Dunbar, 2015). Any person in any part of the
world can engage in the arts in one way or another and can hence establish shared meaning
through the experience or creation of arts. Arts cover a broad and inclusive range of
activities where creativity and self-expression are key (Broadwood, Bunting, Andrews,
Abrams, & Van de Vyver, 2012). Arts offer opportunities to express and share viewpoints,
feelings, ideas, stories, and values. Arts can build connections between artists and
audiences, as well as within audiences and participants. When people engage with the arts
they are creating meaning for themselves. Collaborative arts projects in particular enable
people to make sense of the world together (cf. Broadwood et al., 2012). Some might argue
that arts engagement activates mental simulation which “involves mentally transcending the
‘here-and-now’ to occupy psychologically a different time (past or future), a different
place, a different person's subjective experience, or a hypothetical reality. In other
words, simulation involves conjuring up the experience of something other than that which
one is currently experiencing” (Waytz, Hershfield, & Tamir, 2015, p. 337). There are two
relevant conceptual frameworks (Broadwood et al., 2012; Tay, Pawelski, & Keith, 2018)
which aid our understanding of the socio-emotional impacts of the arts. Specifically, Tay
et al.'s (2018) recent model proposes that the arts can promote wellbeing, broadly
construed to include prosocial behavior. They suggest that arts engagement can produce
four groups of outcomes which include (1) immediate neurological, physiological, and
psychological outcomes, (2) enduring socio-cognitive and psychological competences (e.g.,
self-efficacy, creativity), (3) physical and psychological wellbeing, and (4) positive
normative outcomes (e.g., values, morality, and civic engagement). Tay et al. (2018)
identify four psychological processes through which arts engagement can affect these
outcomes which include: immersion (“feeling carried away”), embeddedness (building socio-
cognitive competencies), socialization (creating connections and identities), and
reflectiveness (socio-moral reflection). Based on an extensive review of the literature
(Broadwood et al., 2012), the Arts and Kindness model proposes that the arts have the
potential to act as a social psychological catalyst for promoting human prosociality. The
model proposes that there are four key routes through which arts engagement can promote
prosociality: emotion (somewhat akin to immersion), learning (akin to embeddedness),
values (akin to reflectiveness), and social connection (akin to socialization). Broadwood
et al. (2012) and Tay et al. (2018) both propose that arts engagement has the potential to
promote prosociality. Both models also emphasize that routes from specific or more general
arts engagement can include short or longer term influences, be proximal or distal from
particular events, and may be weighted differently depending on the particular art forms
or context.

<hs>  Empathy</hs>
  ~~~~~~~

Empathy can be defined as an emotional reaction elicited by and congruent with another's
emotional state or condition (Eisenberg & Fabes, 1998). Both Tay et al. (2018) and
Broadwood et al. (2012) argue that the arts have a strong potential to promote empathy.
Indeed, many arts activities will naturally align individuals into states of togetherness
and will transport participants into the artists', the protagonists', or even fellow
participants' lived or imagined experiences (Tay et al., 2018). Such joint states of
togetherness and shared perspective facilitate the capacities needed for empathy
(Rabinowitch, Cross, & Burnard, 2013). Empirical evidence in middle childhood indeed
demonstrates that engagement in drama (Goldstein & Winner, 2012) and in music (Rabinowitch
et al., 2013) promote empathy compared to control conditions. Moreover, it is well-
established that empathy is crucial for building positive interpersonal and intergroup
relationships (e.g., Abrams et al., 2015; Fabes, Eisenberg, & Eisenbud, 1993). Therefore,
and in line with Broadwood et al. (2012), we hypothesize that empathy may be an important
mechanism in explaining the relationship between arts engagement and prosocial intentions
in middle childhood.

<hs>  Adults</hs>
  ~~~~~~

The relatively small body of psychological research that has examined the impact of arts
engagement on prosocial outcomes is promising. Among adults different studies of specific
art forms (e.g., singing, dancing, reading, acting) have provided evidence that engagement
with that particular art form can promote empathy (Mar, Oatley, Hirsh, dela Paz, &
Peterson, 2006) or prosocial responses (Greitemeyer, 2009; Johnson, Cushman, Borden, &
McCune, 2013; Wiltermuth & Heath, 2009). Using a representative and longitudinal sample of
over 30,000 adults in the UK, Van de Vyver & Abrams (2017) established a reliable and
substantively meaningful longitudinal relationship between arts engagement and subsequent
prosociality, even when accounting for socio-demographic variables, income, and
personality differences.

<hs>  Children</hs>
  ~~~~~~~~

Among children, joint music making has been shown to promote within-group prosociality
among 4-year olds (Kirschner & Tomasello, 2010) and interpersonal prosociality among 8–9
year olds (Schellenberg, Corrigall, Dys, & Malti, 2015). Tangentially, engagement in
synchronous movement promotes interpersonal prosociality during early and middle childhood
(Cirelli, Einarson, & Trainor, 2014; Rabinowitch & Meltzoff, 2017a; Rabinowitch &
Meltzoff, 2017b; Tunçgenç & Cohen, 2018) and intergroup bonding in middle childhood
(Tunçgenç & Cohen, 2016). Given that children seem to naturally and readily engage in
artistic activities, and are often asked to do so at school, it is surprising that there
is relatively little research examining its impacts on their socio-emotional development.
Specifically, the potential social benefits of arts engagement have rarely been researched
in developmental and social psychology (see Goldstein, Lerner, & Winner, 2017; Van de
Vyver & Abrams, 2017), and therefore represents an important area of investigation for
applied developmental research.

<h>THE CURRENT RESEARCH</h>
--------------------

The current paper builds on these related strands of research. Specifically, we test a
number of novel research questions. Separate studies have shown that engagement in
specific art forms (e.g., singing) promotes empathy and interpersonal prosociality, but
research has not tested whether engagement in a participatory arts intervention also
promotes empathy and interpersonal prosociality. In Study 1 we test the hypothesis that
engagement in a participatory arts intervention also promotes empathy and interpersonal
prosocial intentions. Moreover, while recent research has shown that synchronous movement
promotes bonding with outgroup members (Tunçgenç & Cohen, 2016), no research has examined
whether engagement in the arts can promote outgroup-targeted prosociality. Study 2 extends
past research by testing whether participatory arts engagement can promote outgroup-
targeted prosocial intentions across competitive and non-competitive contexts. Notably,
past research has examined the immediate impact of some types of arts engagement on
prosociality, but it has not tested whether effects endure. Study 2 tests the hypothesis
that the impact of arts engagement on children's prosocial intentions persists over a
period of 6 months. In summary, across two field studies using experimental and
longitudinal designs, we test the impact of participatory arts interventions on children's
prosocial intentions. In Study 1 we employ a 2 (Condition: experimental vs. control) × 2
(Time: pre-intervention vs. post-intervention) mixed model design and measure effects on
children's empathy and interpersonal prosocial intentions. In Study 2 we employ a 2
(Condition: experimental vs. control) × 3 (Age: 5–6 vs. 7–8 vs. 9–10 years) × 3 (Time:
pre-intervention vs. one month post-intervention vs. six month post-intervention) mixed
model design and measure effects on children's outgroup prosocial intentions in a
competitive and in a non-competitive context. Interpersonal prosociality is well-
established by middle childhood (Dunfield, 2014) and therefore we do not expect or explore
age-related differences within the age range in Study 1. In contrast intergroup bias is
known to increase and become more context sensitive during middle childhood (Raabe &
Beelmann, 2011; Rutland et al., 2010), so it is possible that age may moderate the
hypothesized impacts of arts engagement on outgroup-targeted prosocial intentions. This is
tested in Study 2.

        <hss>Participants and design</hss>

        A-priori power analysis revealed that to detect a small to medium sized effect (η2
        = .03) with 90% power for a 2 × 2 mixed model ANOVA design, we required a total
        sample size of 122 participants. Two hundred and sixteen children (102 male, 114
        female) completed the study1. Children were aged between 7 years and 10 years
        (grades 2, 3, and 4; mean age = 8.20, SD = 0.86). The study used a 2 (Condition:
        experimental vs. control) between participants × 2 (Time: pre-intervention vs.
        post-intervention) within participants design. Participants were sampled from
        across three demographically and geographically matched elementary schools in the
        UK. Overall, 96% of participants were born in the UK and this was consistent
        across condition (96% in the experimental condition and 95% in the control
        condition). One of the schools experienced the intervention (N = 140). The other
        two served as control schools (N = 76). The study consisted of two testing times
        which were approximately twelve months apart, 60 weeks prior to and 1–2 weeks
        after the intervention.

        <hss>Procedure</hss>

        In the experimental condition children in grades 2, 3, and 4 engaged in a
        participatory arts program which was administered at school and during the school
        day by an independent arts organisation. Participatory arts involve engagement in
        a range of art forms, that inherently include the audience in the creative
        process, allowing them to become co-authors, editors, and observers of the work.
        Arts Council England define participatory arts as follows: “Participation is a
        malleable dialogue that informs the work of the artist, builds and develops
        audiences, engages with communities, promotes learning and forges routes into
        active experience and artistic creation of many kinds. Participatory arts are now
        mainstream and are central to the core programme of many large arts organisations”
        (Arts Council England, 2010). In the experimental condition (or intervention
        school) local artists worked with every pupil and staff member over a period of
        one week to document and celebrate good news stories. Many schools already have
        programs in place to discuss and try to promote prosocial attitudes and social
        engagement (Education Commission of the States, 2016; UK Government, 2018).
        However, the present interventions were not prescriptive to convey a moral
        message. Instead, local artists explored the potential of using creativity and
        arts activities to help children to engage with and express stories of kindness.
        Example activities included: writing a song, producing art installations,
        producing story books, and making community artboards. The control schools only
        exposed children to routine curriculum-based discussions of kindness. Children in
        grades 2, 3, and 4 were invited to complete the pre and post questionnaires.

        <hss>Empathy</hss>

        We employed the 10-item measure of children's empathy used by Abrams et al.
        (2015). Example items are: “I get upset when I see someone get hurt” and “seeing
        someone who is crying makes me feel like crying”. Children responded from 1 (big
        frown) to 5 (big smile). Reliability analysis revealed low Cronbach's alphas for
        this scale (.57 at Time 1 and .44 at Time 2). We conducted a follow-up factor
        analysis with the 10 empathy items (using maximum likelihood to extract one
        factor). Following guidelines from Comrey and Lee (1992) we retained only items
        with a “fair” factor loading (.45 or higher). The final scale consisted of three
        items (all loadings were above .52 at Time 1 and above .56 at Time 2). The three
        retained items were: “I get upset when I see someone getting hurt”, “Seeing
        someone who is crying makes me feel like crying”, and “It makes me sad when I see
        someone who can't find anyone to play with”. Cronbach's alphas were: .64 (Time 1)
        and .69 (Time 2). The three items were mean scored within each time point.

        <hss>Interpersonal prosocial intentions</hss>

        We adapted and extended Abrams et al.'s (2015) measure of prosocial intentions.
        Specifically, children were told, “Imagine you are playing at the park and there
        are lots of children there”. Six scenarios were then introduced to assess
        children's willingness to help, share, and comfort (e.g., “While you are playing
        one of the other children comes over to you. The child has nothing to play with
        and asks if you will share some of your toys. Would you share your toys with the
        child?” ; “Some children are making fun of another child and the child is getting
        upset. Would you go over and comfort the child?”). Participants responded from 1
        (definitely not) to 5 (definitely would). The six items were mean scored within
        each timepoint. Cronbach's alphas were .78 (Time 1) and .82 (Time 2).

        <hss>Descriptives</hss>

        Means, standard deviations, 95% confidence intervals, and bivariate correlations
        are presented in Table 1.

        <hss>Empathy</hss>

        A mixed model ANOVA with Condition (experimental vs. control) as a between
        participants factor and Time (pre-intervention vs post-intervention) as a within
        participants factor, revealed no significant effects of Time, F (1, 213) = 0.001,
        p = .975, η2 < .01, Condition, F (1, 213) = 2.54, p = .113, η2 = .01, or the Time
        x Condition interaction, F (1, 213) = 2.81, p = .095, η2 = .01.

        <hss>Prosocial intentions</hss>

        The ANOVA revealed a significant main effect of Time, F (1, 214) = 5.49, p = .020,
        η2 = .03, a significant main effect of Condition, F (1, 214) = 6.77, p = .010, η2
        = .03, and a significant Time x Condition interaction, F (1, 214) = 3.95, p =
        .048, η2 = .022. Pairwise comparisons showed that, in the experimental condition,
        prosocial intentions significantly increased following the intervention (M T2 =
        3.98, SE T2 = .07, 95% CI [3.85, 4.11]) compared to baseline levels (M T1 = 3.67,
        SE T1 = .08, 95%CI [3.52, 3.82]) (p T1 vs. T2 < .001). In contrast, in the control
        condition, prosocial intentions did not differ between Time 1 (M T1 = 4.06, SE T1
        = .10, 95%CI [3.86, 4.26]) and Time 2 (M T2 = 4.08, SE T2 = .09, 95%CI [3.91,
        4.26]) (p T1 vs. T2 = .826). Pairwise comparisons also showed that, at Time 1,
        prosocial intentions were significantly higher in the control condition than in
        the experimental condition (p = .002). However, as prosocial intentions increased
        in the experimental condition, there were no longer any differences between the
        control and experimental conditions at Time 2 (p = .348).

        <hss>Participants and design</hss>

        The study used a 2 (Condition: experimental vs. control) x 3 (Year Group: 5–6 vs.
        7–8 vs. 9–10 years) between participants x 3 (Time: pre-intervention vs. one month
        post-intervention vs. six month post-intervention) within participants design.
        A-priori power analysis revealed that to detect a small to medium sized effect (η2
        = .03) with 90% power for a 2 × 3 × 3 mixed model ANOVA design the study required
        a total sample size of 162 participants. 174 children (74 male, 100 female)
        completed the study3. Children were aged between 5 and 10 years (mean age = 7.32,
        SD = 1.62) and were in either kindergarten, Grade 2, or Grade 4 in elementary
        school. Participants were sampled from across five demographically and
        geographically matched elementary schools in the UK. Overall, 87% of participants
        were born in the UK and this was consistent across condition (90% in the
        experimental condition and 82% in the control condition). Three of the schools
        were intervention schools (N = 105). Two of the schools were control schools (N =
        69). The study consisted of three testing times. The first (pre-intervention) took
        place just before the intervention started, the second took place approximately
        one month after the intervention ended, and the third took place approximately 6
        months after the intervention.

        <hss>Procedure</hss>

        As in Study 1, all pupils in the experimental schools took part in a participatory
        arts program during school time. However, only children in kindergarten, Grade 2,
        or Grade 4 completed the questionnaires. In the experimental condition local
        artists worked with every pupil and staff member to document and celebrate acts of
        kindness. Over a period of seven months, local artists (different to those in
        Study 1) explored the potential of using creativity and arts activities to help
        children to engage with and express stories of kindness. Example activities
        included: painting, producing comic books, contributing to exhibitions, and
        producing a public performance. Children also went out into the community to
        interview people to collect stories of kindness. For example, one school visited a
        local fire department and brought them drinks and biscuits. As in Study 1, the
        control schools did not receive any form of intervention beyond their routine
        curriculum-based discussions of kindness.

        <hss>Competitive outgroup prosocial intentions</hss>

        We employed Abrams et al.'s (2015) measure of competitive outgroup prosocial
        intentions. Specifically, children were told about a sandcastle competition
        involving teams from their own and another fictitious nearby school. The team that
        built the biggest and best sandcastle would win a big prize and trophy. Children
        were then asked three questions to measure their intentions to share, help, and
        comfort the child (e.g., “As you are building your team's sandcastle, you see a
        child from the other team running to pick up a spade. He falls down and begins to
        cry. You could go over to comfort him, but your team needs you to keep building
        the sandcastle. Would you go over and comfort him?”). Participants responded from
        1 (definitely not) to 5 (definitely would). The three items were mean scored
        within each timepoint. Cronbach's alphas were as follows: .62 (Time 1), .67 (Time
        2), and .73 (Time 3).

        <hss>Non-competitive outgroup prosocial intentions</hss>

        We employed Abrams et al.'s (2015) measure of non-competitive outgroup prosocial
        intentions. Specifically, children were told, “a few weeks later, you are playing
        together in the park and there are lots of children there, including some from
        your school and [another local] school”. Three new items were then introduced to
        assess children's willingness to help, share, and comfort (e.g., “Some children
        are making fun of a boy from [other local school] and the child is getting upset.
        The children leave and he begins to cry. Would you go over and comfort the
        child?”). Participants responded from 1 (definitely not) to 5 (definitely would).
        The three items were mean scored within each timepoint. Cronbach's alphas were as
        follows: .62 (Time 1), .75 (Time 2), and .70 (Time 3).

        <hss>Descriptives</hss>

        Means, standard deviations, 95% confidence intervals, and bivariate correlations
        are presented in Table 2.

        <hss>Competitive outgroup prosocial intentions</hss>

        We conducted a mixed model ANOVA with Condition (experimental vs. control) and
        Year Group (5–6 vs. 7–8 vs. 9–10 years) as between participants factors and Time
        (pre-intervention vs. one month post-intervention vs. six month post-intervention)
        as a within participants factor. There were no significant main effects of Time, F
        (2, 336) = 1.69, p = .186, η2 = .01, Condition, F (1, 168) = 1.71, p = .193, η2 =
        .01, or Year Group, F (2, 168) = 2.00, p = .138, η2 = .02. The Time x Year Group
        interaction was also non-significant, F (4, 336) = 0.71, p = .589, η2 = .01.
        However, the significant interactions between Time x Condition F (2, 336) = 3.78,
        p = .024, η2 = .02, and Year Group x Condition, F (2, 168) = 3.07, p = .049, η2 =
        .04, were qualified by a significant three-way (Time x Condition x Year Group)
        interaction, F (4, 336) = 2.98, p = .019, η2 = .03 (see Fig. 1 for means and
        standard errors). Baseline comparison: Pairwise comparisons showed that there were
        no baseline differences in competitive outgroup prosociality between the
        experimental and control conditions among 5–6 year olds (p = .776), 7–8 year olds
        (p = .610), or 9–10 year olds (p = .708). 5–6 year olds: Pairwise comparisons
        revealed that, among 5–6 year olds, competitive outgroup prosocial intentions did
        not significantly change across time in the experimental (all p's > .433) or in
        the control (all p's > .176) conditions. 7–8 year olds: Pairwise comparisons
        revealed that, among 7–8 year olds, competitive outgroup prosocial intentions
        increased following the intervention compared to the baseline, and stayed at the
        higher level 6 months later (p T1 vs. T2 = .028; p T1 vs. T3 = .014). In contrast,
        in the control condition, competitive outgroup prosocial intentions did not
        significantly change over time (p T1 vs. T2 = .076; p T1 vs. T3 = .063). 9–10 year
        olds: Pairwise comparisons revealed that, among 8–9 year olds, competitive
        outgroup prosocial intentions increased following the intervention compared to the
        baseline, and stayed at the higher level 6 months later (p T1 vs. T2 = .002; p T1
        vs. T3 = .038). In contrast, in the control condition, competitive outgroup
        prosocial intentions did not significantly change over time (p T1 vs. T2 = .499; p
        T1 vs. T3 = .833).

        <hss>Non-competitive outgroup prosocial intentions</hss>

        We conducted a mixed model ANOVA with Condition (experimental vs. control) and
        Year Group (5–6 vs. 7–8 vs. 9–10 years) as between participants factors and Time
        (pre-intervention vs. one month post-intervention vs. six month post-intervention)
        as a within participants factor. Results revealed no significant main effects of
        Time, F (2, 336) = 1.35, p = .260, η2 = .01, Condition, F (1, 168) = 3.15, p =
        .078, η2 = .02, or Year Group, F (2, 168) = 1.48, p = .231, η2 = .02. The Time x
        Condition interaction was significant, F (2, 336) = 6.53, p = .002, η2 = .04. All
        other two-way interactions were non-significant (all p's > .103). The three-way
        interaction was also non-significant, F (4, 336) = 1.13, p = .340, η2 = .01.
        Baseline comparison: Pairwise comparisons showed that there were no baseline
        differences in non-competitive outgroup prosociality between the experimental and
        control conditions among 5–6 year olds (p = .337), 7–8 year olds (p = .537), or
        9–10 year olds (p = .809). Time x condition interaction on non-competitive
        outgroup prosociality: In order to probe the significant two-way interaction of
        Time x Condition we conducted pairwise comparisons (see Fig. 2 for means and
        standard errors). These comparisons revealed that, in the experimental condition,
        non-competitive outgroup prosocial intentions remained stable over time (p T1 vs.
        T2 = .090; p T1 vs. T3 = .277). In contrast, in the control condition, non-
        competitive outgroup prosocial intentions significantly reduced at Time 2 and Time
        3 compared to the baseline (p T1 vs. T2 = .011; p T1 vs. T3 = .004). Pairwise
        comparisons also revealed that non-competitive outgroup prosocial intentions did
        not differ between the experimental condition and control condition at Time 1 (p =
        .297). However, at Time 2 and Time 3, prosocial intentions were significantly
        higher in the experimental than in the control condition (p T2 = .017; p T3 =
        .015).

<h>GENERAL DISCUSSION</h>
------------------

The present field studies drew on the Arts and Kindness model (Broadwood et al., 2012) to
test whether engagement in participatory arts promotes prosocial intentions among
children. Study 1 showed that children who engaged in a participatory arts program showed
increases in interpersonal prosocial intentions, while children in the control condition
did not. There were no effects on children's empathy. Moreover, in Study 2, children who
engaged in a participatory arts program showed increases in competitive outgroup-targeted
prosocial intentions, while children in the control condition did not. These positive
effects of condition on competitive outgroup prosocial intentions were long-lasting.
Specifically, within the experimental condition, competitive outgroup prosocial intentions
remained high six months post-intervention. For non-competitive prosocial intentions,
Study 2 showed that while non-competitive prosociality reduced over time in the control
condition, it remained stable in the experimental condition. It is possible that there may
have been a time of school year effect in the control condition, where children showed
greater prosociality at the start of the study (early in the school year) than the middle
or end, especially in the non-competitive context. This might reflect that children become
more stressed and less contented as the pressure of work and tiredness cumulates during
the school year (Connor, 2003; Hall, Collins, Benjamin, Nind, & Sheehy, 2004). In both
contexts, the trend in the intervention conditions was the opposite, suggesting
consolidation or even strengthening of prosociality over time. One reason that this might
happen is that after children have created and produced artistic outputs, these remain as
significant and salient reminders over time, and as children (and perhaps teachers,
carers, and peers) reflect on these they gain increased purchase on prosocial motivation.
This would be consistent both with the Arts and Kindness model (Broadwood et al., 2012)
and with the evidence from the longitudinal analyses conducted on population level data
from adults by Van de Vyver and Abrams et al. (2017). Researchers have highlighted the
lack of research exploring the social psychological and social-developmental outcomes of
arts engagement (Goldstein et al., 2017; Sigel & Gitomer, 1992; Van de Vyver & Abrams,
2017). A small body of recent social developmental research shows that engagement in
specific art forms such as music (e.g., Schellenberg et al., 2015) or more specific
physical movements such as synchrony (Tunçgenç & Cohen, 2016) can promote prosocial
responses during middle childhood. The current research provides a novel contribution to
this area of research by testing impacts of a participatory arts intervention, testing
impacts on outgroup-targeted prosocial intentions, and testing whether effects are long-
lasting. Overall, our results are in line with the Arts and Kindness model (Broadwood et
al., 2012) and the arts and human flourishing model (Tay et al., 2018), and suggest that
arts engagement has the potential to act as a social psychological catalyst for promoting
prosocial intentions during middle childhood. Intergroup bias in prosociality appears
early in childhood, peaks in middle childhood, and is evident across the lifespan (Abrams
et al., 2015; Over, 2018). Rigorous and applied social-developmental research is essential
in order to test effective strategies for promoting positive and inclusive intergroup
attitudes, intentions, and behaviors in childhood (cf. Rutland, Cameron, Bennett, &
Ferrell, 2005). We hypothesized that arts engagement would be effective for promoting
inclusive prosocial intentions across competitive and non-competitive contexts.
Interestingly, and in line with previous research (cf. Abrams et al., 2015), children's
outgroup prosocial intentions varied by the competitiveness of the intergroup context.
Specifically, age interacted with condition and time to affect prosocial intentions in the
competitive context but not in the non-competitive context. Among 7–8 year olds and among
9–10 year olds, competitive outgroup prosocial intentions increased significantly
following the intervention, and effects persisted over the 6 month period. However, among
5–6 year olds there were no changes in competitive outgroup prosocial intentions. In
contrast, non-competitive prosocial intentions remained stable in the experimental
condition and across age. It seems likely that, to some extent, prosociality is a
normative (socially desirable) response when there are no competing motivations, but that
this ‘default’ response must become more deliberative under situations such as competition
(cf. Rutland et al., 2010). The arts intervention seems likely to have provided a basis
for a more prosocial orientation under such circumstances. Study 2 revealed interesting
longitudinal effects of condition by age. Specifically, 5–6 year olds' competitive
outgroup prosocial intentions remained stable across time in both the experimental and
control condition. In contrast, 7–10 year olds' competitive outgroup prosocial intentions
significantly increased following the arts interventions and these increases were
sustained over time. However, in the control condition 7–8 year olds' competitive outgroup
prosocial intentions marginally reduced over time and 9–10 year olds' competitive outgroup
prosocial intentions remained stable over time. These findings suggest that 5–6 year olds
may be less responsive, at least in the relatively short term, to holistic arts
interventions. In contrast, among 7–10 year olds, there were significant effects of
condition on children's competitive outgroup prosocial intentions. These age-based
variations may be due to children's increasing sensitivity to contextual factors (e.g.,
competition) that impact intergroup dynamics (Abrams et al., 2017; Abrams, Rutland,
Palmer, & Purewal, 2014). In summary, the present evidence demonstrated that engagement in
participatory arts: (1) could promote intentions to act prosocially toward outgroup
members even in the context of intergroup competition, and (2) that it consolidated
prosocial intentions toward outgroup members rather than decaying over the duration of the
school year. These findings suggest that facilitating engagement with the arts across
childhood can be an effective way to maintain and promote outgroup prosocial intentions.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In this paper we tested the impact of participatory arts engagement on both empathy and
prosociality but only found evidence for the latter. However, the Arts and Kindness model
(Broadwood et al., 2012) proposes three additional routes through which arts engagement
can affect prosociality, namely by promoting different values, establishing connections,
and learning about others. Further work needs to be done to examine how these different
routes may be involved in the connection between arts engagement and prosociality, and
whether each has greater or lesser importance during different periods of child
development and socialization. Indeed, further social-developmental research on the arts
will enable us to understand how relationships between arts and socio-emotional outcomes
may vary by periods of development. This proposal is in line with Eisenberg et al.'s
(1999) work which shows that prosocial thoughts, emotions, and behaviors become more
consolidated, and individual differences become more evident as children grow into
adolescence and then adulthood. We hope that this paper will inspire researchers to become
more interested in the potentially wide and pervasive developmental impacts of the arts on
socio-emotional outcomes. Relatedly, it is possible that the absence of effects on empathy
may have been due to a measurement issue and that we were simply unable to capture the
effect of participatory arts on empathy. Indeed, across the developmental literature there
is uncertainty about how to best to measure empathy in this age range. We used an adapted
version of Bryant's empathy index which is widely used across this age range. However,
reliability coefficients for empathy scales, including the Bryant empathy index, are often
lower than desirable (De Wied et al., 2007). Moreover, it is now well-established that
empathy entails at least two separate components: sympathy (concern for another based on
the apprehension or comprehension of the other's emotional state) and personal distress
(an aversive, self-focused emotional reaction to the apprehension or comprehension of
another's emotional state) (Eisenberg et al., 1999). However, these two components
typically cross-load when measured in middle childhood (De Wied et al., 2007; Garton &
Gringart, 2005), perhaps because “children do not differentiate the two or perhaps […] did
not capture any subtle distinction that Davis was trying to make” (Garton & Gringart,
2005). In the present research we measured prosocial intentions rather than prosocial
behavior. Although we cannot assert that children in the experimental conditions would
also behave more prosocially, there are good reasons for believing that this might be the
case. Many intention-behavior relationships are large and stable because they become
habitual (e.g., voting or health behaviors). The challenge for interventions is to change
intentions in ways that can change behavior. A meta-analysis of the intention-behavior
relationship in adults showed that a medium-to-large change in intention is required (d =
.66) in order to induce a small-to-medium change in behavior (d = .36) (Webb & Sheeran,
2006). Across the present two studies, children's engagement in participatory arts led to
small to medium sized changes in their prosocial intentions (effect sizes varied between d
= .28 to d = .50 for the significant effects of the intervention). Consistent with this,
another study from our lab (Ali, Abrams, & Van de Vyver, 2019) does indicate that, in
middle childhood, outgroup prosocial intentions are significantly positively correlated
with outgroup prosocial behavior (r = .23). Even if the effects of the intervention on
intentions have small or subtle implications for immediate behavior, the gain in
prosociality could be expected to yield positive cumulative effects, especially if it is
reciprocated by others. It would be desirable for future research to test the impact of
arts engagement on behavioral responses directly. A further research question is whether
there are important moderators of the relationship between arts engagement and
prosociality. For example, research shows that individual differences in personality
(e.g., agreeableness and openness) are associated, albeit to different extents, with arts
engagement or with prosociality (Van de Vyver & Abrams, 2017). It is possible that the
impact of arts engagement on prosociality may vary depending on these individual
differences, and relatedly how aspects of children's temperament may augment or militate
against the impact of such interventions.

<hs>  Applied implications</hs>
  ~~~~~~~~~~~~~~~~~~~~

The Arts are universal and are woven into culture and history. Young children readily
engage in the arts. Although the skills, performance, and consumption of the arts are the
subject of substantial research, their role as a societal glue, and in the social lives of
children, has been relatively neglected (Sigel & Gitomer, 1992). Publicly financed arts
provision is often at the front line of cuts during periods of austerity, often depriving
the poorest in society of access (e.g., free entry to museums, etc). In the UK, for
example, the arts sector has faced substantial reductions in public and private spending
and arts and creative subjects have faced heavy cuts from the school curriculum (NCA,
2017). However, the costs of neglecting the arts may be greater than expected. For
example, developmental research shows that engagement in the arts can actually promote
cognitive ability in childhood (e.g., Bilhartz, Bruhn, & Olson, 1999; Tõugu, Marcus,
Haden, & Uttal, 2017). Furthermore, the present research demonstrates that engagement in
the arts promotes socio-emotional development in childhood, perhaps improving the lives of
children, their peers, and ultimately their wider communities. In order to maximise the
positive impacts of arts engagement, and in order to ensure that arts are accessible to
all, this evidence contributes to the case for embedding arts engagement across the
curriculum.

<h>SUMMARY</h>
-------

Overall, new and longitudinal evidence across two studies provides support for the
hypothesis that middle childhood is a period in which the arts can act as a social
psychological catalyst that promotes interpersonal and intergroup prosocial intentions.
The results suggest that if we wish to sustain cohesive and inclusive societies,
increasing access to, and engagement in, the arts from an early age may be a valuable
means of doing so.

<h>OPEN PRACTICE STATEMENT</h>
-----------------------

Neither of the experiments reported in this article was formally preregistered. The
measures are available in the supplementary materials of this paper. The data are
available on OSF (https://osf.io/wjby5/?view_only=ee6074f6c3964947a83bb848db57df77).


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<ART>Perception of occlusion by young infants: Must the occlusion event be congruent with the occluder?
================================================================================

Authors: J. Gavin Bremner, Alan M. Slater, Uschi C. Mason, Jo Spring, Scott P. Johnson
DOI: 10.1016/j.infbeh.2016.07.007
Year: 2016  |  Pages: 240-248
ASJC codes: 3204
Keywords: Accretion, Deletion, Occlusion, Trajectory continuity

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Four-month-old infants perceive continuity of an object's trajectory through occlusion, even when the occluder is illusory, and several cues are apparently needed for young infants to perceive a veridical occlusion event. In this paper we investigated the effects of dislocating the spatial relation between the occlusion events and the visible edges of the occluder. In two experiments testing 60 participants, we demonstrated that 4-month-olds do not perceive continuity of an object's trajectory across an occlusion if the deletion and accretion events are spatially displaced relative to the occluder edges (Experiment 1) or if deletion and accretion occur along a linear boundary that is incorrectly oriented relative to the occluder's edges (Experiment 2). Thus congruence of these cues is apparently important for perception of veridical occlusion. These results are discussed in relation to an account of the development of perception of occlusion and object persistence.

--------------------------------------------------------------------------------


<h>EXPERIMENT 1</h>
------------

In Experiment 1 we adopted the method used previously to investigate young infants’
perception of trajectory continuity (Bremner et al., 2005, 2007; Johnson, Bremner et al.,
2003) to manipulate the position of the deletion and accretion event in the object's path
of movement so that these did not coincide with the position of the edges of the occluder.
Thus in one condition the deletion event occurred earlier and the accretion event occurred
later than they should given the width of the occluder (Fig. 3, upper images), and in the
other condition the deletion event occurred later and the accretion event occurred earlier
than they should given the width of the occluder (Fig. 3, lower images). These displays
were designed so that the maximum occluder width and maximum separation between deletion
and accretion boundaries maintained time and distance out of sight well within the range
in which 4-month-olds perceive trajectory continuity when the occluder edges and occlusion
events are co-located (Johnson, Bremner et al., 2003).

        <hss>Participants</hss>

        Twenty-four 4-month-old infants (M = 123.2 days; range 112–141 days; 14 girls and
        10 boys) took part in the experiment. Two other infants did not complete testing,
        one due to fussiness and the other because of equipment failure. Twelve infants
        were assigned to each of the two conditions in such a way as to ensure that the
        mean age and the gender balance were comparable across conditions. Throughout the
        series, infants took part in only one experiment. In all experiments, participants
        were recruited by personal contact with parents in the maternity unit when the
        baby was born, followed up by telephone contact near test age to those parents who
        volunteered to take part. Infants with reported health problems including visual
        and hearing deficits and those born two weeks or more before due date were omitted
        from the sample. The majority of participants (over 95%) across both experiments
        were from Caucasian, middle class families.

        <hss>Apparatus and stimuli</hss>

        A Macintosh computer and a Samsung 100 cm color monitor were used to present
        stimuli and collect looking time data. An observer viewed the infant on a second
        monitor, and infants were video recorded for later independent coding of looking
        times by a second observer. Both observers were unaware of the hypothesis under
        investigation. Using HABIT software (Cohen, Atkinson, & Chaput, 2000) the computer
        presented displays, recorded looking time judgments, calculated the habituation
        criterion for each infant, and changed displays after the criterion was met. The
        first observer’s looking time judgments were input with a keypress on the computer
        keyboard. Fig. 3 indicates the displays used in this experiment. The habituation
        display was presented against a black background with a 20 × 20 grid of white dots
        measuring 48 × 48 cm (27° x 27°) serving as texture elements. A blue occluder with
        vertical extent 21.5 cm (12.3°) was placed centrally. A 6.7 cm (3.8°) green ball
        moved back and forth from one side of the display to the other, moving at 16.5
        cm/s (9.4°/s). In the early deletion late accretion display the visible occluder
        was 7 cm wide, but the ball disappeared and reappeared at invisible contours
        separated by 12 cm. In the late deletion early accretion display the occluder was
        12 cm wide, but the ball disappeared and reappeared at invisible contours
        separated by 7 cm. It took 2500 ms for the ball to traverse the width of the
        display. Time from complete visibility to invisibility or the reverse was 400 ms.
        Time totally out of sight was 366 ms. (early deletion late accretion display) or
        67 ms (late deletion early accretion display). Time completely in sight to the
        left and right of the occluder was 1332 ms (early deletion late accretion display)
        or 1634 ms (late deletion early accretion display). The animation was run as a
        continuous loop for the duration of the trial. In test displays, the inducing
        elements were removed and the ball moved back and forth at the same speed as in
        the habituation display. In the continuous trajectory test display, the ball was
        always visible. In the discontinuous trajectory display, the ball went out of and
        back into view just as in the habituation event.

        <hss>Procedure</hss>

        Each infant was seated 100 cm from the display and tested individually in a
        darkened room. The habituation display was presented until looking time declined
        across four consecutive trials, from the second trial on, adding up to less than
        half the total looking time during the first four trials. Timing of each trial
        began when the infant fixated the screen after display onset. The observer pressed
        a key as long as the infant fixated the screen, and released when the infant
        looked away. A trial was terminated when the observer released the key for two
        seconds or 60 s had elapsed. Between trials, a beeping target was shown to attract
        attention back to the screen. Following habituation trials, infants were presented
        with the two test trials in alternation, three times each, for a total of six
        trials. On test trials, half the infants in each condition were presented with the
        continuous trajectory first, and the rest viewed the discontinuous trajectory
        first. The second observer coded looking times from videotape for purposes of
        assessing reliability of looking time judgments. Interobserver correlations were
        high across the two experiments in this report (M Pearson r = 0.99). In this
        experiment we did not run control conditions consisting of test trials alone to
        assess intrinsic preferences because we have obtained null preferences in control
        conditions with identical test trials in previous work (Bremner et al., 2005;
        Johnson, Bremner et al., 2003).

<hs>  Results</hs>
  ~~~~~~~

Analysis of data from habituation trials indicated no difference between conditions in
trials to habituation (early deletion late accretion condition, M = 7.83; SD = 1.27: late
deletion early accretion condition, M = 7.75; SD = 1.66; t (22) = 0.138, p = 0.89) or in
total habituation time (early deletion late accretion condition, M = 201.2 s; SD = 90.86;
late deletion early accretion condition, M = 217.1 s; SD = 77.52; t (22) = −0.46, p =
0.65). Fig. 4 shows looking times at the two test displays for each condition. Infants in
both the early deletion late accretion and late deletion early accretion conditions looked
longer at the continuous test trial, although this was more marked in the early deletion
late accretion condition. We can have confidence in assuming that longer looking at one
test display is indicative of a novelty preference rather than a familiarity preference
for two reasons. Firstly, infants were habituated to a standard criterion, circumstances
under which familiarity preferences rarely occur (e.g., Fiser & Aslin, 2002; Johnson et
al., 2009; Moore & Johnson, 2011). Secondly, several papers (Bremner et al., 2005, 2007;
Johnson, Bremner et al., 2003) have reported systematic age related data that would be
very hard to interpret on the basis of familiarity preference. Because looking time data
tend to be positively skewed, violating an assumption of ANOVA, data in this and the
subsequent experiment were log transformed prior to analysis. A 2 (display: early vs. late
occlusion) x 2 (test trial order) x 2 (test trial type: continuous vs. discontinuous) x 3
(test trial block) mixed ANOVA yielded a significant effect of test trial type, F (1,20) =
8.05, p = 0.01, ηp2 = 0.29. The interaction between test trial type and display condition
was not significant, F (1,20) = 0.82, p = 0.37, ηp2 = 0.04, nor were any other main
effects and interactions.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The rationale for this habituation-test approach is that the direction of the novelty
preference indicates how infants have processed the habituation stimulus. Thus infants'
longer looking at the continuous test trial suggests that they processed the object’s
trajectory in the habituation display as discontinuous. This is the opposite result as is
obtained for this age group with comparable times and distances out of sight when the
occlusion event coincided with the visible occluding edges, and it certainly provides no
evidence that infants perceived continuity in these habituation events. Thus we can
conclude that the occlusion event must coincide spatially with the occluding edges for
infants to perceive an occlusion event indicating continuity of the object.

<h>EXPERIMENT 2</h>
------------

Experiment 1 makes it clear that when the occlusion events are separated by 2.5 cm from
the edges of the occluder, infants do not perceive the event as a normal occlusion in
which the object persists. Our second question was whether the same result would be
obtained if the edges of the moving ball at the boundaries where deletion and accretion
took place were oblique, but had contact with the visible occluder edges. In this case,
the separation between occlusion event and occluder edges is reduced, but the occlusion
event takes a different form, occurring as if at oblique edges. Intuitively, this
disjunction in the orientation of occluding contours and occluder edges seems subtler than
the complete separation of event and edge in Experiment 1. However, it is possible that
misorientation of occluding contour and occluder edge is as important as a simple
displacement in the horizontal dimension. Thus in Experiment 2 we exposed infants to a
display in which the occluder had vertical edges but the occlusion event occurred at
oblique contours. We know that 4-month-olds perceive trajectory continuity when a
horizontally moving object passes behind an occluder with oblique edges (Bremner, Slater,
Mason, Spring, & Johnson, 2016), so a negative result should not be due to occlusion at an
oblique contour alone. However, because we had previously only tested infants' perception
of occlusion across a very narrow oblique occluder, in this experiment we included a
‘standard' baseline condition in which the occluder edges were oblique and the occlusion
event was congruent with these edges, and also a control condition in which infants were
only exposed to the test trials (to assess any intrinsic preference for either trial).

        <hss>Participants</hss>

        Thirty-six 4-month-old infants (M = 122.9 days; range 109-138 days; 17 girls and
        19 boys) took part in the experiment. Eight other infants did not complete testing
        due to fussiness. Twelve infants were assigned to each of the two conditions in
        such a way as to ensure that the mean age and gender balance were comparable
        across conditions.

        <hss>Apparatus and stimuli</hss>

        The same apparatus as in Experiment 1 was used for stimulus presentation, video
        recording of the infant, and recording looking times. Fig. 5 indicates the
        displays used in this experiment. In the experimental condition, the habituation
        display was presented against a black background with a 20 × 20 grid of white dots
        measuring 48 × 48 cm (27° x 27°) serving as texture elements. An occluder with
        vertical and horizontal dimensions 21.5 cm (12.3°) and 7 cm (4°) was placed
        centrally. A 6.7 cm (3.8°) green ball moved back and forth from one side of the
        display to the other, undergoing progressive deletion and accretion at oblique
        linear contours at 55 ° to the vertical, intersecting with the left and right
        edges of the occluder at the points where the bottom and top of the ball
        respectively contacted the occluder. In the baseline condition, the vertical
        occluder was replaced by an oblique occluder at 55 ° to the vertical with length
        21.5 cm and width 9.5 cm such that its occluding edges were congruent to the
        apparent edges at with deletion and accretion took place in the experimental
        condition. In both cases, time from complete visibility to invisibility or the
        reverse was 500 ms. Time totally out of sight was 233 ms and time completely in
        sight to left and right of the occluder was 1265 ms. Test displays contained no
        visible edges or background occlusion and the ball moved back and forth at the
        same speed as in the habituation display. In the continuous trajectory test
        display, the ball was always visible. In the discontinuous trajectory display, the
        ball went out of and back into view just as in the habituation event. All other
        aspects of the form of the habituation and test trials were the same as in
        Experiment 1. We also included a control group who saw only the test trials.

        <hss>Procedure</hss>

        Infants were first habituated to the habituation display, and were then presented
        with the two test displays in alternation, three times each, for a total of six
        test trials. On test trials, half the infants in each condition were presented
        with the continuous trajectory first, and the rest viewed the discontinuous
        trajectory first. Habituation and test trials were carried out according to the
        same criteria and procedures as in Experiment 1.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Analysis of data from habituation trials indicated no difference between conditions in
trials to habituation (experimental condition, M = 7.5, SD = 2.28; baseline condition, M =
7.75, SD = 2.22, t (22) = −0.27, p = 0.79) or in total time to habituation (experimental
condition, M = 151.2, SD = 45.81; baseline condition, M = 238.8, SD = 150.4; t (22) =
−0.193, p = 0.076). As Fig. 6 indicates, infants in the experimental condition showed a
consistent preference the continuous test display, whereas infants in the baseline
condition showed a consistent preference for the discontinuous display, and infants in the
control condition did not show a consistent preference for either test display. A 3
(condition: experimental vs. baseline vs. control) x 2 (test trial order) x 2 (test trial
type: continuous vs. discontinuous) x 3 (test trial block) mixed ANOVA yielded a
marginally significant effect of test trial type, F (1,30) = 4.1, p = 0.051, ηp2 = 0.12,
and a significant interaction between test trial type and condition, F (2,30) = 14.74, p <
0.001, ηp2 = 0.5. To interpret this interaction, separate analyses were carried out for
each condition. In the case of the experimental condition, there was a significant effect
of test trial type, F (1,10) = 5.49, p = 0.041, ηp2 = 0.35, with infants looking longer at
the continuous test trial. There were no other significant main effects or interactions.
In the case of the baseline condition, there was a significant effect of test trial type,
F (1,10) = 20.51, p = 0.001, ηp2 = 0.67, with infants looking longer at the discontinuous
test trial, and a significant interaction between test trial type and test trial block, F
(2,9) = 4.42, p = 0.046, ηp2 = 0.5, due to an increase in the test trial type effect
across trial blocks. In the case of the control condition, a 2 (test trial order) x 2
(test trial type: continuous vs. discontinuous) x 3 (test trial block) mixed ANOVA yielded
only a significant effect of test trial block, F (2,9) = 9.29, p = 0.006, ηp2 = 0.67. This
is explained by longer looking on the first test trial block, and is a common effect in
control conditions in which test trials are the only displays presented. The important
finding is that there is no underlying preference for one test trial over the other. In
summary, infants in the experimental condition looked longer at the continuous test
display, the opposite of the result shown by infants in the baseline condition.
Apparently, unlike infants exposed to the baseline display, they perceived the habituation
event as an object moving on a discontinuous trajectory. Thus it appears that an occlusion
event that is wrongly oriented relative to the visible occluding edges does not provide
information for object continuity.

<h>GENERAL DISCUSSION</h>
------------------

In both experiments, infants appeared to perceive the object’s trajectory in the
habituation display as discontinuous. This is despite the fact that in both experiments
the display contained both visible occluding contours, and deletion and accretion events.
These are circumstances under which infants would normally perceive trajectory continuity
when occluding contours and deletion/accretion are congruent, providing the time and
distance out of sight is sufficiently short, which they were in these experiments. Thus
these studies contribute important additional information regarding young infants’
perception of occlusion events, namely that the occlusion event must be spatiotemporally
congruent relative to a visible occluder if it is to specify normal occlusion in which the
occluded object persists. Although it is clear that multiple cues are needed to specify a
normal occlusion event (Bremner et al., 2012), the effect of these cues is not simply
additive; they must be spatially congruent to be effective. We must acknowledge an
alternative interpretation of the present results. Maybe the isolated deletion and
accretion events are perceived as similar to the discontinuous test display, and so
preference for the continuous display reflects a simple perceptual novelty preference. We
believe that such an interpretation is unlikely, because infants showed a preference for
the discontinuous test display in the case when the habituation display had a Kanizsa
figure as a virtual occluder and thus contained particularly isolated deletion and
accretion events. However, even if this is the appropriate interpretation of performance
in the present experiments, our main conclusion remains unchanged, namely that deletion-
accretion and occluder edges must be congruent if infants are to perceive an occlusion
event in which the object persists while invisible. In one sense, this conclusion should
come as no surprise because to the adult eye these habituation displays do not look like
cases of veridical occlusion. However, the results of this study attest to another respect
in which young infants appear to perceive the world in adult-like ways. Specifically,
there has to be precise spatial coordination between information for occlusion and
information about the occluder. This is important in relation to the finding that young
infants perceive the Kanizsa figure as an occluding surface. In this case, the explicit
information specifying the occluding surface is distant from the occlusion event.
Presumably the main point, however, is that although this information is distant it
specifies a complete illusory surface that extends to and is congruent with the deletion
and accretion events. What we cannot say is whether the degree of congruence required in
the case of the Kanizsa figure would be the same as is required in the case of a visible
occluder. Our suspicion is that a high degree of spatial congruence would be required,
whether or not the occluder is real or illusory. It seems likely that, even early in
development, the visual system is tuned to detect veridical events, and spatial congruence
of cues may be particularly important in this process. The fact that spatial alignment of
inducing elements creates the illusion of a surface in the case of the Kanizsa figure
probably points to the importance of alignment as a principle of perceptual organisation
that exists early in development. If that conclusion is correct, then we can expect that
spatial congruence of events is important for perception of veridical occlusion. By
misaligning or misorienting the occlusion event relative to the occluder, our
manipulations may thus have violated a key principle of perception of events in which one
object passes behind another. The aim of this work was to investigate the importance of
cue congruence in 4-month-old infant's perception of occlusion events, with the focus on 4
months chosen because this appears to be a pivotal age in development of perception of
object continuity across occlusion. However, it would be of interest to investigate older
infants' perception of these displays. On the one hand, we might expect that older infant
would not perceive trajectory continuity either, because these displays present non-
veridical occlusion events and that we would expect a developmental progression towards
detection of veridical events. On the other hand, we know that adults perceive an
occlusion event on the basis of deletion and accretion alone (the tunnel effect), and at
so some point in development in infancy or later we might expect participants to rely on
this single cue alone. Thus far, it appears we have evidence that 6-month-olds do not use
deletion-accretion alone to specify continuity (Johnson, Bremner et al., 2003), and future
work will establish the age at which this emerges. It remains possible, however, that even
in adults the presence of incongruent luminance defined occluding edges would disrupt
perception of the tunnel effect.


<h>REFERENCES</h>
----------

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<ART>Perception of temporal duration affected by automatic and controlled movements
==============================================================================

Authors: Tomomitsu Herai, Ken Mogi
DOI: 10.1016/j.concog.2014.07.012
Year: 2014  |  Pages: 23-35
ASJC codes: 3204, 3205
Keywords: Action control, Automatic action, Cognitively controlled action, Externally-triggered movement, Internal clock model, Self-initiated movement, Sensorimotor contingency, Temporal reproduction, Time estimation, Time perception

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Sensorimotor contingency is one of the main factors to warp time perception. Voluntary actions such as saccades and hand movements affect the subjective perception of temporal duration. Although the perceived timings of action and stimulus are affected by whether an action was automatic or controlled, its effect on the subjective perception of duration has not been studied except in the case of saccade (chronostasis), which has been shown to be unaffected by the context of action initiation. Here we investigate the effect of the context of action initiation on duration estimation in the case of finger movement. The reproduced intervals were shorter when actions were initiated by automatic manner, compared to self-timed or cognitively controlled actions. The results are compatible with an internal clock model employing variable latencies for switch closure after action.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The processing of temporal information is ubiquitous in cortical computation. It is
important for both perception and action, serving as an essential element of how the brain
constructs models of the environment. Recently, time perception ranging from sub-second to
several seconds has been extensively studied. Studies have shown that the perceived
duration is influenced by the properties of stimuli (Xuan, Zhang, He, & Chen, 2007). In a
successive presentation of identical stimuli, the perceived duration of an oddball
stimulus is longer (oddball effect, Tse, Intriligator, Rivest, & Cavanagh, 2004). A visual
onset expands the subjective time (Kanai & Watanabe, 2006). When the same stimulus is
presented successively for several times, the first one is perceived as longer than the
others (debut effect, Pariyadath & Eagleman, 2007). The debut effect disappeared when the
stimuli were random images. These results indicate that the predictability of the stimulus
affects the oddball and debut effects. Multisensory interaction (van Wassenhove,
Buonomano, Shimojo, & Shams, 2008) and emotion (Droit-Volet & Meck, 2007; Doi & Shinohara,
2009) also affect the subjective duration. Thus, time perception is a highly complex
cognitive process affected by various elements related to the stimuli. One of the factors
that potentially affect time perception is sensorimotor contingency. It has been suggested
that the intentional state is one of the important factors affecting the sense of time
(Haggard, Clark, & Kalogeras, 2002). The perceived timing of key pressing and the
subsequent tone were shifted so that they were closer to each other, when the subject
voluntarily pressed the key followed by a tone with some delay. This “temporal attraction”
has been termed “intentional binding effect” (Ebert & Wegner, 2010; Engbert &
Wohlschläger, 2007; Humphreys & Buehner, 2010; Moore & Haggard, 2008; Stetson, Cui,
Montague, & Eagleman, 2006; Tsakiris & Haggard, 2003). In contrast, when the movement was
induced by transcranial magnetic stimulation (TMS), the temporal shift occurred in the
opposite direction. The mode of initiation of an action (intrinsic or extrinsic, i.e.,
self-initiated (intention-based) or externally-triggered (stimulus-based), Jahanshahi et
al., 1995; Waszak et al., 2005)) is one of the important contextual factors in
sensorimotor contingency. In an externally-triggered condition, a subject generates a
movement as a response to a sensory stimulus. A self-initiated action, in contrast, is
driven internally. It has been suggested that different mechanisms are engaged in the
intrinsic and extrinsic movements (Obhi & Haggard, 2004). Welchman, Stanley, Schomers,
Miall, and Bulthoff (2010) showed that the speed of action in a reactive movement was
faster than in a self-timed action. Imaging studies have shown that different neural
mechanisms are engaged in these movements (Herwig, Prinz, & Waszak, 2007; Jenkins,
Jahanshahi, Jueptner, Passingham, & Brooks, 2000; Keller et al., 2006; Taniwaki et al.,
2006). Activities in the basal ganglia (Cunnington, Windischberger, Deecke, & Moser, 2002)
and dorsolateral prefrontal cortex (François-Brosseau et al., 2009; Jahanshahi et al.,
1995; Wiese et al., 2004) increase in self-initiated movements compared to the externally-
triggered movements. In a monkey study, the firing rate of neurons in the putamen
increased faster in a self-initiated than in an externally-timed movement (Lee & Assad,
2003). A study on human subjects also showed that movement-related cortical potentials in
a self-initiated movement were larger than in an externally-triggered movement (Jahanshahi
et al., 1995). The onset of hemodynamic response of pre-SMA in a self-initiated movement
was earlier than in an externally-triggered movement (Cunnington et al., 2002). Some
studies have suggested that externally and internally initiated movements have different
effects on time perception. Haggard, Aschersleben, Gehrke, and Prinz (2002), for example,
reported temporal attraction effects between action and auditory tone both in self-
initiated and externally-triggered conditions. In a self-initiated condition, a subject
intentionally pressed a key at his or her own timing, causing a tone after 200 ms. In an
externally-triggered condition, on the other hand, the subject pressed the key as quickly
as possible upon hearing tone. The temporal orders of action and tone were reversed
between the two conditions. The subject reported the perceived timings of key pressing and
tone. The perceived timings of action and tone became closer to each other in both
conditions, indicating that the directions of the shift of the perceived timing of tone
and action were reversed between the two conditions. Studies on chronostasis have shown
that actions and subjective durations are closely linked (Yarrow, Haggard, Heal, Brown, &
Rothwell, 2001; Yarrow, Haggard, & Rothwell, 2004; Yarrow, Johnson, Haggard, & Rothwell,
2004). In this illusion, the visual stimulus presented immediately after the saccade was
perceptually dilated (Yarrow et al., 2001). The magnitudes of the lengthening effect were
similar between the controlled and automatic eye movements (Yarrow, Johnson et al., 2004),
with a constant effect across various intervals, indicating that chronostasis was not
affected by the magnitude of volition. Park, Schlag-Rey, and Schlag (2003) found that not
only saccades but also voluntary movements such as key press and utterance caused an
overestimation of the perceived duration of its sensory feedback, extending the
chronostasis studies in context. In general, there appear to be interconnections between
voluntary actions and subjective durations, a point that needs to be investigated further.
Different neural mechanisms and range of intervals are involved for saccades, finger
movements, and other kinds of voluntary actions (Kandel, Schwartz, & Jessell, 2000). Thus,
the results obtained in the chronostasis studies do not necessarily apply to voluntary
movements in general. Identifying a common mechanism for saccades and other voluntary
movements will contribute to the understanding of the relation between subjective duration
and voluntary movements in the general context. The effect of chronostasis was not
affected by the context of saccade initiation (Yarrow, Johnson et al., 2004), and was
constant across intervals (Yarrow, Haggard et al., 2004). It is still unknown whether such
is the case for other kinds of voluntary movements (e.g. key pressing). It has been shown
that the perceived timings of action and effect were affected by the sensorimotor context
(Haggard, Aschersleben et al., 2002). It is possible that the subjective duration in
voluntary movements such as key pressing is affected by the sensorimotor context, in
contrast to chronostasis. It is interesting to investigate whether the context of action
initiation would affect the estimated interval. Here we use a temporal reproduction
paradigm to investigate the effect of sensorimotor context on the perception of duration.
The subjects were presented with sensory stimuli of various intervals. They were
instructed to estimate the intervals and reproduce them through key pressing. In order to
investigate the effect of sensorimotor contexts (e.g. self-timed versus externally-timed),
the timings of the key pressing were constrained in various ways. A voluntary movement can
be classified either as an automatic or a controlled process (Wegner, 2002). An automatic
movement is reflex-like and fast (∼500 ms), with its conscious perception occurring after
the motor execution (Welchman et al., 2010). On the contrary, a controlled movement
requires cognitive processes depending on attention and working memory, takes longer time
(>500 ms), and is more flexible. An action initiation within 500 ms after the Go signal
can be regarded as an automatically controlled movement, while an action initiated between
1 and 2 s after Go signal can be regarded as cognitively controlled movement, requiring
the subject to inhibit motor output for some interval while carrying it out before the
deadline. Such a movement could not be achieved without a top down control. Our
experimental setup incorporated these temporal constraints. It has been suggested that
different neural mechanisms are involved in the estimation of temporal duration below and
above 2–3 s (Poppel, 1997; Ulbrich, Churan, Fink, & Wittmann, 2007). Temporal processing
of up to 2–3 s can be regarded as “time perception”, while those lasting more than 3 s is
thought to be “time estimation” (Fraisse, 1984). In order to investigate the relation
between the estimated intervals and sensorimotor contingencies, intervals in the range of
1–5 s were presented in the experiments, covering the “time perception” as well as the
“time estimation” domains.

<hs>  General descriptions</hs>
  ~~~~~~~~~~~~~~~~~~~~

We conducted three experiments. All subjects were naïve about the purpose of the present
study, except that in experiments 1 and 2 subject TH was one of the authors of this paper.
All subjects had normal or corrected-to-normal vision, and were right-handed by self-
report, except for one subject in experiment 3. The experiments were conducted in
accordance with the Declaration of Helsinki. The experimental procedures were submitted to
and approved by the brain and cognitive sciences ethics committee of Sony Computer Science
Laboratories. Informed consent was obtained from all participants. The experiments were
conducted using the self-timed and externally-timed conditions. In the self-timed
condition, the subject was instructed to start the reproduction at his or her own timing.
In the externally-timed condition, the subject was required to start the reproduction
within a predetermined interval. There were two subconditions for the externally-timed
condition. In the automatic condition, the subject was instructed to press the key within
500 ms after the trigger signal. In the controlled condition, the subject was instructed
to press the key within 1–2 s after the trigger signal. It was assumed that the automatic
and controlled conditions would induce reflex-like (Welchman et al., 2010) and cognitively
controlled movements, respectively, the latter involving an active suppression and higher
volitional states. In Experiment 1 and experiment 2 (visual condition), the sessions were
controlled by a desktop PC (EPSON Endeavor MT8800) and a 21-inch CRT monitor (Sony
Trinitron CPD-G520). The subjects responded by pressing a key (SANWA SUPPLY NT-11UBK, with
a keystroke of 2.2 ± 0.1 mm). In experiment 2 (auditory condition) and experiment 3, the
sessions were conducted on Mac Book Pro 15 inch model. The tones were presented through a
headphone (Sony MDR-XD100).

<hs>  Experiment 1</hs>
  ~~~~~~~~~~~~

In experiment 1, we examined the effect of movement under self-timed and externally-timed
(automatic or controlled) conditions on the perception of temporal duration. In experiment
1(a), ten subjects (seven males and three females, mean age = 29.4, sd = 2.5) participated
in a combination of self-timed and automatic conditions. In experiment 1(b), eight
subjects (five males and three females, mean age = 29.3, sd = 2.4) participated in a
combination of self-timed and controlled conditions. The subjects of experiment 1(b) were
a subset of the subjects of experiment 1(a). Before the experiment, the subjects practiced
pressing the key according to the conditions. In experiment 1(a), the subjects practiced
to press the key within 500 ms after the Go signal (automatic condition). The words “too
late” were displayed on the screen at the passage of 500 ms after the Go signal.
Typically, a practice of several times was sufficient. In experiment 1(b), the subject
practiced to press the key between 1 and 2 s after the Go signal (controlled condition).
After the key pressing, the subjects were given textual feedback; “too early” if the
subject pressed the key before 1 s after the Go signal, “SUCCESS” if the subject pressed
the key between 1 and 2 s after the Go signal, and “too late” if the subject pressed the
key later than 2 s after the Go signal. When a subject successfully pressed the key for
ten continuous trials, the practice session was over and the experiment started. All
subjects could pass this criterion within trials of up to 30. At the beginning of each
trial, a white circle (0.95°) appeared at the center of the screen, which remained until
the end of each trial. The subject was instructed to keep a natural posture without
crossing the legs and putting the elbow on the desk, and to fixate on the circle while
keeping posture and attention. 1 s after the appearance of the circle, the reference
auditory stimulus was presented to both ears through a headphone (Fig. 1). The subject was
instructed to memorize its duration. The duration of the reference stimulus was either 1,
3 or 5 s, presented in random order. After the offset of the reference duration, the Go
signal was presented. The intervals between the offset of the reference duration and the
Go signal were randomly chosen from 1, 1.5 and 2 s, to prevent the subject from
anticipating the timing of the Go signal. After the Go signal, the subject was instructed
to press the designated key with their index finger of the right hand and keep pressing
for a duration matching that of the reference tone. There was not an auditory feedback
accompanying the key pressing. The subjects were instructed to refrain from silently
counting or keeping a rhythm while they estimated the duration. The self-timed and
externally-timed (automatic or controlled) conditions were assigned to respective blocks.
Before the session started, the subjects were instructed which of the self-timed, or
externally timed (automatic or controlled) conditions applied to each block. The subjects
conducted two blocks for each condition. The order of the conditions was counterbalanced
among the subjects. The subjects were allowed to take rest between the blocks. One block
consisted of six presentations of the reference duration. Thus, the reproduction of
duration was conducted twelve times for each interval in respective conditions, resulting
in 72 trials overall. In the externally-timed conditions (automatic or controlled), when
the subjects failed to press the key within the predetermined limits, an error feedback
was presented, with the trial terminated to proceed to the next trial. The missed trials
were stacked at the end of the block to be executed later. This manipulation was designed
to prevent the subjects from adapting to the reference interval.

<hs>  Experiment 2</hs>
  ~~~~~~~~~~~~

In experiment 2, we further investigated how the difference of action initiation would
affect temporal processing. In exp. 1, the movement conditions were separated by blocks,
where the subjects knew which action would be required at the moment the reference
intervals were presented. If the subject’s internal states such as attention and
concentration varied between the movement conditions, these changes in internal states
throughout the block could affect the temporal processing at the encoding period.
Therefore, there was the possibility that the differences in reproduced intervals were due
to those in the encoding period, not in the reproduction period. In exp. 2, the subjects
reproduced the reference intervals under externally-timed (automatic or controlled)
conditions, without receiving a prior instruction of which action to take before the
reference intervals were presented. Five subjects (three males and two females, with
average age = 29.0, sd = 2.2) participated in the auditory condition. Five subjects (three
males and two females, with average age = 29.6, sd = 2.1) participated in the visual
condition. The subjects were a subset of the participants in experiment 1. In the auditory
condition (Fig. 2a), a white square (1.72°) was presented for 1 s to indicate the
beginning of the trial. 1 s after the disappearance of the square, a sound (1000 Hz, 60
dB) indicating the reference intervals was presented to the subject from the headphone.
The subjects were instructed to memorize its interval. The duration of the reference
intervals were 1, 3, and 5 s, presented in a random sequence. 1.5 s after the offset of
the reference interval, the Go signal was presented. The Go signals were low (500 Hz) or
high (2000 Hz) sound with a duration of 20 ms, one of which instructed the subject to
reproduce within 500 ms after the Go signal (automatic condition), while the other
instructed to start the reproduction between 1 s and 2 s after the Go signal (controlled
condition). The assignments of the Go signal pitches for alternative actions were
counterbalanced among the subjects. Before the experiment, the subjects learned the
assignment of the Go signal pitches for alternative actions. This learning session
consisted of thirty-four trials in a block. In the first four trials a red circle (1.53°)
was presented at the center of the screen after the Go signal. It was presented for the
predetermined interval within which the subjects had to press the key in the automatic or
controlled condition (appearing twice each in an interleaved manner). The subjects
attended to the stimulus and learned the timing of key pressing. In the remaining thirty
trials, the subjects had to press the key as indicated by the red circle on the screen in
the first four trials (the automatic and controlled conditions appearing fifteen times
each in a random manner). The practice session was over when the subjects successfully
pressed the key within the designated time frame for more than ten cumulative times for
both conditions. In the case of failure, the subjects were required to conduct one more
block. Text feedbacks were provided on the timing of subjects’ key pressing (“too fast”,
“SUCCESS”, or “too late”). All the subjects cleared this criterion in less than two
blocks. The experiment started after twelve warm up trials. One block of experiment
consisted of eighteen trials, in which each reference interval for respective conditions
was presented three times. The subjects conducted six blocks. In all, the subjects
reproduced each interval 18 times in both conditions. After the Go signal, the subjects
pressed the space key on the keyboard, pressing for the duration of the remembered
interval and then releasing the key. No feedback was presented to the subjects during the
key pressing. The next trial started 1.5 s after the subject keyed off. The subjects were
instructed not to use the strategy of counting or keeping rhythm during the encoding and
reproduction of the interval. In the visual condition, a white square (3.34°) was
presented as the reference for 1, 3 or 5 s (Fig. 2b). After the reference stimulus, a
color (red or green) circle (1.91°) was presented for 50 ms as the Go signal. In the
automatic condition, the subjects were instructed to press the key within 500 ms after the
Go signal. In the controlled condition, the timing of key pressing was between 1 and 2 s
after the Go signal. The green or red circle instructed the subjects which action to
conduct. The two colors were randomly presented. The associations between the color and
action were counterbalanced among the subjects. Before the experiment, the subjects
learned the association between colors and actions (automatic or controlled) in the
practice session, where one of the alternative Go signals was presented randomly, and the
subjects practiced to press the key within the predetermined limit after the Go signal.
The subjects then practiced the experimental task, in which they learned to correctly
estimate and reproduce the reference intervals. In one block, each reference interval for
each condition was presented three times, resulting in a total of eighteen trials. The
subjects conducted six blocks. They reproduced each interval 18 times in both conditions.
As in previous experiments, the subjects reproduced the presented interval by continuously
pressing the key. There was no feedback while they were pressing the key.

<hs>  Experiment 3</hs>
  ~~~~~~~~~~~~

In experiment 3 (control), we investigated whether the delay between the presentation of
the reference and reproduction affected the reproduced intervals. Seven subjects (three
males and four females, with average age = 31.4, sd = 3.4) participated. Six out of the
seven were the subjects in experiment 1. In the experiment, a fixation appeared for 1 s at
the center of the monitor, followed by a blank screen of 1 s. A sine wave sound (1000 Hz,
60 dB) was presented through the headphone as the reference interval. Reference intervals
of 1, 3 or 5 s duration were presented in random order. The subjects were instructed to
memorize the durations of the reference sound. After the presentation of the reference
interval, the Go signal (sine wave, 2000 Hz) was presented. The interval (fixed throughout
the block) between the offset of reference and the Go signal was 1 or 2 s. The two
intervals were switched alternatingly with the conditions. The order of the two conditions
was counterbalanced among the subjects. The subjects were instructed to press the key to
reproduce the reference interval at their own timing after the Go signal. One block
consisted of 18 trials, in which each reference interval was presented six times. There
were 74 trials in total, in which the subjects reproduced each reference interval 12 times
for each condition. Before the experiment, the subjects conducted 10 practice sessions, in
which the interval between the offset of reference interval and the Go signal was 1.5 s.

<hs>  General descriptions</hs>
  ~~~~~~~~~~~~~~~~~~~~

The measures used for investigating the effect of movement condition on temporal
processing were the mean reproduction intervals, the ratio between reproduced and
reference intervals, and the coefficient of variation (CV, standard deviation divided by
the mean). The mean produced interval would indicate directly how the subject perceived
and reproduced each reference interval. If the movement conditions affected temporal
processing critically, the mean reproduced intervals would be significantly different
between the conditions. The ratio between the reproduced and reference intervals would
represent the degree of deviation of the reproduced interval from the actual stimuli. The
CV values would indicate the variability of temporal reproduction within the subject. As
noted in the discussion section, CV is one of the useful measures for investigating
cognitive models of time perception.

<hs>  Experiment 1</hs>
  ~~~~~~~~~~~~

Table 1 and Fig. 3(a) show the results for the self-timed and automatic conditions in
experiment 1. The reproduced intervals were significantly longer than the actual intervals
at 1 s (one sample t-test, t(9) = 8.75, p < .001) and 3 s (t(9) = 2.86, p = .018), but
were not significantly different at 5 s (t(9) = 0.72, p = .48) in the self-timed
condition. In the automatic condition, only the reproduced interval at 1 s (t(9) = 4.02, p
< .01) was significantly different from the actual interval (3 s: t(9) = 1.94, p = .083, 5
s: t(9) = −0.19, p = .85). The mean reproduced intervals, ratio and CVs were submitted to
a 2 × 3 repeated measures analysis of variance (ANOVA). The movement conditions (automatic
versus self-timed) and the reference intervals (1, 3, 5 s) were a categorical variable and
a covariate, respectively. The reproduced intervals were significantly different between
the conditions (F(1, 9) = 8.17, p = .018). The effect of reference intervals was also
significant (F(1, 9) = 96.79, p < .00001), indicating that the subjects were sensitive to
the intervals and could discriminate the durations. Their interaction was not significant
(F(1, 9) = 4.86, p = .054). For the ratio, the effect of reference interval was
significant (F(1, 9) = 102.77, p < .00001). The effect of movement condition (F(1, 9) =
4.16, p = .072) and the interaction (F(1, 9) = 0.089, p = .77) were not significant. For
CVs, ANOVA detected a significant effect of reference interval (F(1, 9) = 9.01, p = .014)
but not for the movement condition (F(1, 9) = 1.47, p = .25) and their interaction (F(1,
9) < 0.0001, p = .99), indicating that the subjects attended equally to the two movement
conditions. The timings of key pressing for reproduction initiation after the Go signal
were 319 ± 25 ms and 1272 ± 391 ms (mean ± sd) in the automatic and the self-timed
conditions, respectively, with a significant difference between them (paired t-test, t(9)
= 7.43, p < .0001). The timing of the key pressing in the automatic condition was
significantly smaller than the designated limit of 500 ms (paired t-test, one tail, t(9) =
−23.86, p < .000001), confirming that 500 ms was a sufficient interval to press the key in
response to the Go signal. Table 2 and Fig. 3(b) show the mean reproduced intervals, ratio
and CVs for each reference interval for the self-timed and controlled conditions in
experiment 1. The reproduced intervals were significantly longer than the actual interval
at 1 s (one sample t-test, t(7) = 8.49, p < .001) and 3 s (t(7) = 4.13, p < .01), but not
at 5 s (t(7) = −0.39, p = .70) in the self-timed condition. Similarly, in the controlled
condition, the reproduced intervals at 1 s (t(7) = 11.82, p < .001) and 3 s (t(7) = 3.04,
p = .018) were significantly longer than the actual duration, but not so at 5 s (t(7) =
0.20, p = .84). As in the automatic condition, the data were submitted to the 2 × 3
repeated measures ANOVA. The reference interval significantly affected the reproduced
intervals (F(1, 7) = 89.85, p < .0001). In contrast to the automatic condition, the effect
of the movement condition on reproduced interval was not significant (F(1, 7) = 0.49, p =
.50). The interaction between the movement condition and the reference interval was also
not significant (F(1, 7) = 1.04, p = .34). In the case of the ratio, the effect of
reference interval was significant (F(1, 7) = 111.05, p < .0001). Neither the effect of
movement condition (F(1, 7) = 0.30, p < .60) nor the interaction (F(1, 7) = 0.001, p =
.98) was significant. The ANOVA showed that the CVs were significantly different between
different reference intervals (F(1, 7) = 5.70, p = .048). The effect of the movement
condition (F(1, 7) = 4.56, p = .069) and the interaction between the reference interval
and the movement condition was not significant (F(1, 7) = 0.74, p = .41). Contrary to the
automatic condition, the subjects started the temporal reproduction earlier after the Go
signal in the self-timed condition (mean ± sd, 1266 ± 249 ms) than in the controlled
condition (1530 ± 97 ms). The timing of starting reproduction was significant (paired
t-test, t(7) = −0.59, p = .035), suggesting that the difference of reproduced intervals in
experiment 1(a) was not simply the result of the delay between the Go signal and the
timing of key pressing. If the latency of key pressing had a significant effect on
reproduced intervals, there would have been significant differences of reproduced
intervals here.

<hs>  Experiment 2</hs>
  ~~~~~~~~~~~~

Results for the mean reproduced interval, ratio and CV in the auditory condition of
experiment 2 are shown in Table 3 and Fig. 4(a). The reproduced intervals were
significantly longer than the actual interval at 1 s in both the automatic and controlled
conditions, and at 3 s in controlled condition. (one sample t-test, automatic condition: 1
s (t(4) = 4.93, p = .0078), 3 s (t(4) = 2.32, p = .080), 5 s (t(4) = 0.17, p = .86),
controlled condition: 1 s (t(4) = 5.88, p = .0041), 3 s (t(4) = 2.95, p = .041), 5 s (t(4)
= 0.72, p = .50). A 2 × 3 repeated measures ANOVA detected significant effects of movement
conditions (F(1, 4) = 35.84, p = .0039) and reference interval (F(1, 4) = 37.54, p =
.0035). The effect of the interaction was not significant (F(1, 4) = 0.053, p = .82). As
for the ratio, both the effect of movement condition (F(1, 4) = 14.39, p = .019) and
reference interval (F(1, 4) = 49.29, p = .0022) were significant, while the interaction of
them was not significant (F(1, 4) = 4.92, p = .091). We submitted the CVs to a 2 × 3
repeated measures ANOVA. The effects of the reference interval (F(1, 4) = 7.85, p = .048)
was significant. The effect of the movement conditions (F(1, 4) = 1.43, p = .29) and the
interaction (F(1, 4) = 1.12, p = .34) were not significant. The latency from the Go signal
to the key pressing was 357 ± 34 ms (mean ± sd) and 1409 ± 143 ms in the automatic and
controlled conditions, respectively. The latency was confirmed to be different between
conditions (paired t-test, one-tailed, t(4) = −15.10, p < .0001). Results for the
reproduced interval, ratio and CV in the visual condition of experiment 2 are shown in
Table 4 and Fig. 4(b). The reproduced intervals were significantly longer than the actual
intervals at 1 s, but not at 3 s and 5 s in both the automatic and controlled conditions
(one sample t-test, automatic condition: 1 s (t(4) = 4.06, p = .015), 3 s (t(4) = 0.55, p
= .61), 5 s (t(4) = −1.11, p = .32), controlled condition: 1 s (t(4) = 4.20, p = .013), 3
s (t(4) = 1.45, p = .22), 5 s (t(4) = −0.34, p = .75). A 2 × 3 repeated measures ANOVA
detected significant effects of movement conditions (F(1, 4) = 8.90, p = .040) and
reference interval (F(1, 4) = 14.94, p = .018) but not their interaction (F(1, 4) = 0.28,
p = .62). For the ratio, the significant effects of the movement condition (F(1, 4) =
10.56, p = .031), the reference interval (F(1, 4) = 17.32, p = .014) and their interaction
(F(1, 4) = 13.56, p = .021) were detected. We submitted the CVs to a 2 × 3 repeated
measures ANOVA. The effect of the reference interval (F(1, 4) = 3.38, p = .13), movement
conditions (F(1, 4) = 0.55, p = .49) and the interaction of them (F(1, 4) = 0.028, p =
.87) were not significant. The latencies from the Go signal to the key pressing were 380 ±
10 ms (mean ± sd) and 1350 ± 130 ms in the automatic and controlled conditions,
respectively. The latency was different between the automatic and controlled conditions
(paired t-test, one-tailed, t(4) = −15.97, p < .0001).

<hs>  Experiment 3</hs>
  ~~~~~~~~~~~~

Table 5 and Fig. 5 show the mean reproduced intervals, ratio and CVs in experiment 3. When
reproduced intervals were submitted to a 2 × 3 repeated measures ANOVA, a significant
effect of reference interval (F(1, 6) = 135.89, p < .0001) was detected. Neither the
effect of movement condition (F(1, 6) = 1.28, p = .30) nor the interaction (F(1, 6) =
0.52, p = .49) was significant. For the ratio, the effect of reference interval was
significant (F(1, 6) = 12.99, p = .011). The effect of movement condition (F(1, 6) = 2.26,
p = .18) and interaction (F(1, 6) = 1.93, p = .21) were not significant. We submitted the
CVs to a 2 × 3 repeated measures ANOVA. The effect of the reference interval (F(1, 6) =
2.79, p = .14), movement conditions (F(1, 6) = 0.093, p = .77) and the interaction (F(1,
6) = 2.16, p = .19) were not significant.

<h>DISCUSSION</h>
----------

In this study, the subjects reproduced the reference intervals by pressing the key. The
purpose of this study was to investigate whether the subjective duration was affected by
the nature of voluntary movement of key pressing in various contexts of action initiation.
In addition, we examined how the effect on temporal reproduction varied as a function of
the reference intervals. The results for experiment 1 suggest that when the subject
pressed the key in a reflex-like manner (within 500 ms, automatic condition), the
reproduced intervals became shorter compared to the timing of self-timed key pressing.
Limiting the timing of key press between 1 and 2 s after the Go signal (controlled
condition) presumably made the action highly volitional and cognitively controlled, as the
subject was required to suppress the movement for some time and then initiate the movement
before the deadline. This suppression would have necessitated cognitive modulations from
top-down control circuits including the prefrontal brain area. These results suggest that
the temporal estimation was not significantly different between self-timed and cognitively
controlled movements. On the other hand, the reproduced interval in self-timed condition
was significantly different from the automatic condition, suggesting that the automaticity
of action initiation has a significant effect on interval estimation within the range of
several seconds. The results of experiment 2 suggest that when the subjects started the
reproduction in the automatic and reflex-like manner, their reproduced intervals were
significantly shorter than when movements were initiated in a cognitively controlled
manner. Since the subjects did not know which movement condition would occur when the
reference intervals were encoded, the difference of reproduced interval could not be
attributed to the encoding phase. Comparison with results of experiment 1 would suggest
that the online estimation of interval was affected by the context of action initiation.
The results of auditory and visual conditions also suggest that the effect was independent
of the modalities. These results are consistent with a model involving a common timing
mechanism for both visual and auditory modalities. The results of experiment 3 show that
the delay of reproduction period did not affect the reproduced interval. It has been
suggested that the interval between encoding and reproduction period affected the
reproduced interval (Wearden, Goodson, & Foran, 2007). The delay used in Wearden et al.
(2007) however, was larger than those employed in our present experiments. In addition,
they showed that larger delays shortened memorized intervals, contrary to our results in
experiments 1 and 2. Therefore, the interval between the offset of the reference interval
and the timing of key press might not be a critical factor for the reproduced interval in
our experiment. The differences of reproduced intervals are likely to have been caused by
the contexts in which the movements were initiated. It has been suggested that different
mechanisms are engaged in the processing of intervals under and above about 3 s (termed
“time perception” and “time estimation”, respectively, Fraisse, 1984; Poppel, 1997;
Ulbrich et al., 2007). In experiments 1 and 2, the interactions between the reference
interval and the movement condition were not significant. Thus, the effect of the movement
condition on duration reproduction was constant over these ranges, suggesting that a
common mechanism might underlie “time perception” and “time estimation”. In a review of
brain imaging studies, Lewis and Miall (2003, 2006) suggested that different brain
networks were engaged in temporal processing, depending on whether the movements were
automatic or cognitively controlled. Cognitively controlled timing task involves the right
dorsolateral prefrontal cortex (rDLPFC) and the right posterior parietal cortex (rPPC). On
the other hand, automatically controlled timing task involved the supplementary motor area
(SMA), left sensorimotor cortex, and the right cerebellum. It is possible that the
significant difference of reproduced intervals in different movement conditions resulted
from the activation of different neural networks between the conditions, while the absence
of the significant differences in reproduced durations between the self-timed condition
and controlled condition in experiment 1 is due to the fact that similar networks were
activated in the two conditions. For example, the dorsolateral prefrontal cortex might be
activated and play a significant role in both self-timed and cognitively controlled
movements. In the present study, some results were consistent with those in the previous
studies of chronostasis, while others were contradictory. As is the case with the
chronostasis (Yarrow, Haggard et al., 2004), the effect size was constant across the
estimated intervals. Our results, on the other hand, showed that when the subject began
the temporal reproduction in a reflex-like manner (automatic condition), the reproduced
intervals were shorter than those in the self-timed or cognitively controlled actions
(controlled condition). This result is in contradiction to the results obtained in the
study of chronostasis in which the lengthened effects by saccades were not significantly
different between the high volitional and reflex-like eye movements (Yarrow, Johnson et
al., 2004). Yarrow, Johnson et al. (2004) concluded that the effect of chronostasis was
triggered by an efference signal arising in the superior colliculus. The difference
between our results and the chronostasis studies may be attributed to the difference in
the neural mechanism of saccades and finger movements, and the range of estimated
intervals involved. Our results suggest relative differences of interval estimation
depending on the movement conditions. The automatic action might have dilated the
subjective duration, while the self-timed and cognitively controlled action might have
compressed it. It is also possible that both effects have co-existed. The pacemaker-
accumulator internal clock model has been developed to account for interval estimation
(Treisman, 1963). One of the applications of the model is the Scalar Expectancy Theory
(SET, Gibbon, 1977; Gibbon, Church, & Meck, 1984). In SET, there are three stages (clock,
memory and decision), each stage containing a few components. In the clock stage, it is
assumed that there is an internal clock which emits pulses with a certain rate. Those
pulses then pass a gate of accumulator. The gate is open by default. When the cognitive
process of estimating intervals is initiated, the switch of the gate is closed and pulses
are accumulated. The interval is then measured by the amount of pulses in the accumulator.
The SET predicts the scalar property of variance: The distribution of estimated interval
would scale in proportion to the mean of estimated interval, so that the coefficient of
variation would be constant, as the estimated interval changes. One of the factors
affecting the clock rate is arousal. It has been suggested that a higher arousal level
correlates with a faster clock rate. A click train might increase the arousal level,
resulting in an overestimation for the following intervals (Penton-Voak, Edwards,
Percival, & Wearden, 1996). Some features of the present results can be explained by the
SET model. Specifically, the results presented here show that the difference of estimated
intervals between action contexts were constant across the range of estimated intervals. A
change in the clock rate would predict a proportional difference as a function of the
interval, while a change in the latency of closing switch would predict a constant
difference regardless of the estimated intervals. Our results are compatible with an
account in terms of the closing latency: When the subjects initiated action in a reflex-
like manner (automatic condition), the latency of closing switch was shorter. Our results
showed that the CV values decreased as a function of estimated durations. The decrease in
CV values is consistent with the results of Ulbrich et al. (2007), where the subjects
reproduced intervals between 1 and 5 s. On the other hand, the SET model predicts that CV
would be constant for changes of the interval. The discrepancies indicate that the SET
model might have to be modified. It is possible that different mechanisms are engaged in
measuring a temporal interval, depending on whether the interval is shorter or longer than
about 3 s (Fraisse, 1984; Poppel, 1997; Ulbrich et al., 2007). Higher cognitive processes
would be involved in the processing of longer intervals. Measurement of shorter intervals
would be carried out mainly by lower neural mechanisms, where temporal processing may be
affected by various noises. Because of these noises, the measured duration would be
variable for shorter intervals. When the target interval is longer, the higher cognitive
processes would be engaged in measuring the duration. The higher cognitive processes may
compare the interval being measured with the interval stored in memory and compensate for
the deviation caused by the noises. As a result, the measured intervals for longer
durations would have lower variability than for the shorter ones. Such a compensating
mechanism might have to be incorporated to supplement the SET model. There are alternative
explanations for our results. Wenke and Haggard (2009) investigated how a subject’s sense
of time changed when a temporal attraction happened. The results indicated that the
threshold for a successful temporal discrimination for tactile stimuli on the subject’s
finger became larger when the stimuli were presented right after their action, while the
subjects pressed the key voluntarily. Within the framework of internal clock model, the
clock would have slowed down transiently by the initiation of voluntary movements.
Although their study suggested that this effect occurred only when the action led to a
sensory feedback such as an auditory tone, our results can be explained by this transient
clock rate change assumption. A slower clock rate in the self-timed condition would lead
to longer reproduced intervals than in the reactive movement condition (i.e., the
automatic condition). In addition, the opposite effect, in which the rate of the internal
clock became faster transiently, can also be considered. Welchman et al. (2010) showed
that reactive action was conducted quicker than self initiated movements. This phenomenon
suggests that the progress of the internal clock would get transiently faster when the
subjects initiated a movement in a reflex-like manner. This consideration also fits the
present results, as a faster speed of internal clock would lead to shorter reproduced
interval. It is possible that either one or both effects led to the present results. In
experiment 1, the automatic and controlled conditions with limits on the timing of key
press were more demanding than the self-timed condition. Therefore, the subject’s
attentional allocation might have been different between these conditions. Task difficulty
is known to affect temporal processing (Zakay, Nitzan, & Glicksohn, 1983). The dual task
paradigm studies have also suggested that loads of temporal and nontemporal concurrent
tasks affected the attentional allocation and resulted in the temporal processing of other
tasks (interference effect) (Brown & West, 1990; Brown, 1997; Dutke, 2005). A concurrent
task such as visual search and arithmetic demands attentional resources and interfere with
the subject’s temporal task, leading to a decrease in the pulses accumulated in the memory
system. In view of these results, in our experiments, it is possible that pressing the key
within the predetermined time limit demanded in the subjects some degree of attentional
allocation, resulting in longer durations in the externally-timed conditions (automatic
and controlled) than in the self-timed condition. Subjects who participated both in the
automatic and controlled conditions in experiment 1 reported that the latter was more
difficult to execute than the former. If the task load and attentional allocation affected
the temporal reproduction period critically, the reproduced intervals in the automatic
condition would be longer than those in the self-timed condition. In addition, the
dilation of reproduced intervals in the controlled condition compared to those in the
self-timed condition would be more enhanced than in the case of automatic condition.
However, such were not the case. Therefore, we conclude that it is not likely that
attention and task load led to the present results. In the controlled condition, before
starting the reproduction of reference interval, the subjects had to estimate a duration
of 1–2 s. There is thus a possibility that this additional temporal estimation process
might have affected the following reproduction process of reference interval. However,
when comparing the CV of the controlled condition with other conditions in experiment 1
(b) and experiment 2, the statistical analysis did not detect significant differences,
indicating that the variability of the reproduced intervals were not statistically
different whether there was an additional temporal estimation before the reproduction. In
addition, in experiment 1 (b), the reproduced intervals were not significantly different
between the self-timed and controlled conditions, indicating that the additional
estimation of the interval of 1–2 s before the reproduction of reference interval did not
affect the reproduced interval significantly. Based on these observations, we conclude
that the estimation of 1–2 s in the controlled condition did not significantly affect the
reproduction process. In sum, we investigated the effect of the context of action
initiation on temporal reproduction. The subjects reproduced three kinds of reference
intervals by pressing the key. When the subjects tried to reproduce the duration by
reflex-like movements, the reproduced intervals were significantly shorter than those for
self-timed and cognitively controlled movements. In the context of the internal clock
model, these results would indicate that when the subjects initiated to move in a reflex-
like manner, the latency of switch closing would be faster, or the clock speed would
become faster. Such changes would affect the perception of duration, as a result of the
interaction between our action and environment.


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<ART>Perfectionism, negative motives for drinking, and alcohol-related problems: A 21-day diary study
================================================================================

Authors: Sean P. Mackinnon, Cassondra M. Ray, Samantha M. Firth, Roisin M. O'Connor
DOI: 10.1016/j.jrp.2018.12.003
Year: 2019  |  Pages: 177-188
ASJC codes: 3200, 3207
Keywords: Alcohol, Drinking motives, Negative affect, Nondisplay of imperfection, Perfectionistic cognitions

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We explored links between two perfectionism facets and alcohol-related problems. We predicted perfectionistic cognitions and nondisplay of imperfection would indirectly predict alcohol problems through negative affect, coping motives, and conformity motives, but would be unrelated to quantity of alcohol consumption. Participants included 263 young adult drinkers collected from two sites using self-report surveys with a 21-day, once-per-day measurement. Participants were mostly Caucasian (78.3%), female (79.5%), and young (M = 21.37, SD = 1.89). Data were analyzed using multilevel structural equation modeling. Nondisplay of imperfection (but not perfectionistic cognitions) had a serial indirect effect on alcohol-related problems through negative affect, followed by conformity motives. Other findings varied across analyses (fixed vs. random) and analysis level (between vs. within). Open Data/Methods: https://osf.io/gduy4.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Heavy and problematic drinking are major societal concerns. Excessive alcohol consumption
and alcohol-related problems are especially common among young adults, with over 40% of
Canadian undergraduates endorsing at least one alcohol-related problem (e.g., arguing with
other while drunk, neglecting responsibilities) per year (Adlaf, Demers, & Gliksman,
2004). Links between negative forms of perfectionism (e.g., perfectionistic concerns) and
alcohol problems are inconsistent, with some studies suggesting a positive link (Flett,
Hewitt, Whelan, & Martin, 2007; Rice & Van Arsdale, 2010), and others finding null effects
of perfectionism on binge drinking (Flett et al., 2008; Mackinnon et al., 2011). However,
there is a clear theoretical link between negative perfectionism (i.e., perfectionistic
thoughts and behaviors aimed at avoiding negative outcomes). and negative reinforcement
(Slade & Owens, 1998), which suggests that negatively-reinforcing drinking motives (i.e.,
consuming alcohol to reduce negative emotions; Cooper, Kuntsche, Levitt, Barber, & Wolf,
2015) may be one mechanism by which perfectionism can confer risk for alcohol-related
problems. Given the role of perfectionism as a transdiagnostic risk factor for a wide
range of psychopathology (Sherry, Mackinnon, & Gautreau, 2015), it seems prudent to
investigate whether facets of this personality trait also confer risk for alcohol
problems. The present study examined the relationship between perfectionistic cognitions,
nondisplay of imperfection, avoidance-based drinking motives, negative affect, alcohol
consumption, and alcohol-related problems using a 21-day daily diary study of young
adults.

<hs>  Defining perfectionism</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Although variably defined by scholars, most researchers agree perfectionism is a
multidimensional personality trait comprising two higher-order dimensions, labeled
perfectionistic concerns and perfectionistic strivings (Dunkley, Blankstein, Halsall,
Williams, & Winkworth, 2000; Stoeber & Otto, 2006). Perfectionistic concerns include the
perception that others impose unrealistic standards and expectations upon oneself (i.e.,
socially prescribed perfectionism; Hewitt & Flett, 1991), constant worry about making
mistakes (concern over mistakes; Frost, Marten, Lahart, & Rosenblate, 1990), doubts about
getting things “right” (doubts about actions; Frost et al., 1990), and a sense of falling
short of one’s own standards (discrepancy; Slaney, Rice, Mobley, Trippi, & Ashby, 2001).
Perfectionistic strivings include setting high personal standards (personal standards,
Frost et al., 1990) and demanding perfection of oneself (i.e., self-oriented
perfectionism; Hewitt & Flett, 1991). Perfectionistic concerns are consistently associated
with undesirable outcomes, such as negative affect (Molnar, Reker, Culp, Sadava, &
DeCourville, 2006; Smith, Saklofske, Yan, & Sherry, 2016) and decreased well-being
(Mackinnon & Sherry, 2012). Findings on the link between perfectionistic strivings and
positive psychological outcomes are less clear. After controlling for perfectionistic
concerns, some evidence suggests strivings are positively associated with well-being
(Hill, Huelsman, & Araujo, 2010; Stoeber & Otto, 2006) and low negative emotionality
(Lizmore, Dunn, & Causgrove Dunn, 2017; Smith et al., 2016), while others found null or
mixed relations between strivings and positive characteristics (Graham et al., 2010;
Mackinnon & Sherry, 2012). Perfectionistic cognitions are a private expression of
perfectionism and reflect the frequency of automatic ruminative thoughts about perfection
(Flett, Hewitt, Blankstein, & Gray, 1998). Flett and Hewitt (2014) note that “At the
conceptual level, we were focused from the outset of perfectionistic automatic thoughts
pertaining to the self” (pg. 662). That is, they believed this construct was more closely
related to self-oriented perfectionism, which perfectionism scholars broadly agree is part
of the “perfectionistic strivings” dimension (Smith et al., 2016). However, based on
factor analytic data, Stoeber, Kobori, and Brown (2014) argue that the perfectionism
cognitions are multidimensional, with features of both perfectionistic strivings and
perfectionistic concerns. Supporting this view, Flett, Hewitt et al. (2012) found strong
associations between self-oriented and socially prescribed perfectionism and
perfectionistic cognitions. A study by Sherry, Gralnick, Hewitt, Sherry, and Flett (2014)
also found moderate associations between perfectionistic thoughts and all three of Hewitt
and Flett (1991) trait dimensions of perfectionism (i.e., self-oriented, other-oriented,
and socially prescribed perfectionism). Similar to findings on perfectionistic concerns,
research links perfectionistic cognitions to rumination (Flett, Madorsky, Hewitt, &
Heisel, 2002) and depressive symptoms (Flett et al., 1998, 2002, 2007; Flett, Hewitt, et
al., 2012; Wimberley & Stasio, 2013). Given this debate, perfectionistic cognitions may
not cleanly fit into the two higher-order traits of perfectionistic strivings and
concerns, though it does appear to be relatively maladaptive. Perfectionistic self-
presentation is a public expression of perfectionism and is thought to have three facets:
perfectionistic self-promotion (i.e., self-promoting behaviors aimed at demonstrating
perfection), nondisclosure of imperfection (i.e., avoiding verbal admissions of
imperfection), and nondisplay of imperfection (i.e., concealing imperfect behaviors from
others; Hewitt et al., 2003). The present study focuses on nondisplay of imperfection.
Nondisplay of imperfection is closely linked to social anxiety (Flett, Coulter, & Hewitt,
2012; Hewitt et al., 2003; Mackinnon, Battista, Sherry, & Stewart, 2014), depression
(Hewitt et al., 2003), and negative affect (Hewitt et al., 2003; Mackinnon & Sherry, 2012;
Mushquash & Sherry, 2012). Though all three facets of perfectionistic self-presentation
correlate with negative outcomes, nondisplay of imperfection has the largest relationship
with negative affect (Hewitt et al., 2003); thus, we chose to focus on this facet in the
present study. Nondisplay of imperfection is also correlated, yet not redundant with,
trait perfectionism (Flett, Nepon, Hewitt, Molnar, & Zhao, 2016; Hewitt et al., 2003). The
largest correlations are found between socially prescribed perfectionism and nondisplay of
imperfection, supporting the notion that these individuals are preoccupied with the
consequences of not appearing perfect because they perceive others will be critical of
them. Due to its malignant nature and robust association with socially prescribed
perfectionism, nondisplay of imperfection is considered a close relative of
perfectionistic concerns (Hewitt et al., 2003).

<hs>  Perfectionism cognitions and perfectionistic self-presentation as trait-states</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Perfectionism variables are typically conceptualized as stable trait-like aspects of
personality, which reflect dispositional levels, or inherent qualities, that make up one’s
character (Dunkley et al., 2000; Flett et al., 1998; Hewitt & Flett, 1991; Hewitt et al.,
2003).1 The viewpoint taken in the present paper departs slightly from the common
assumption of trait-like stability. Despite a core of trait-like stability, short-term
longitudinal research also suggests these measures have day-to-day fluctuation. In a
21-day longitudinal study, Mackinnon et al. (2014) found state-like variations in
perfectionistic cognitions and perfectionistic self-presentation, with variation from day-
to-day accounting for about 15–16% of the overall variance in the constructs. Other
authors found within-person fluctuation in perfectionistic concerns and strivings from
day-to-day (Boone et al., 2012) and week-to-week (Mackinnon, Kehayes, Leonard, Fraser, &
Stewart, 2017). In all three cases, perfectionism tends to be predominantly stable across
time, but also has small fluctuations across measurement occasions. More importantly, this
state-like variation in perfectionism variables predicts substantive outcomes, such as
social anxiety (Mackinnon et al., 2014) and well-being (Mackinnon et al., 2017). Thus, the
present study conceptualizes perfectionistic cognitions and nondisplay of imperfection as
“trait-states,” which reflects that they are primarily stable traits, but also exhibit a
smaller amount of state-like variability from day-to-day.

<hs>  Perfectionism & alcohol outcomes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Given that research and theory link negative affect to alcohol use and alcohol-related
problems (Castellanos-Ryan & Conrod, 2012), and that negative perfectionism exhibits
strong links to negative affect (Dunkley, Zuroff, & Blankstein, 2006), it seems reasonable
to expect that perfectionistic concerns (and facets related to concerns) would be
associated with alcohol outcomes indirectly through negative affect. Perfectionistic
strivings have been linked to a small decrease in alcohol consumption and binge drinking,
while perfectionistic concerns remain mostly unrelated to binge drinking (Flett et al.,
2008; Mackinnon et al., 2011; Pritchard, Wilson, & Yamnitz, 2007; Simons, Christopher, &
Mclaury, 2004). However, perfectionistic concerns have been linked to increased alcohol-
related problems (i.e., negative consequences associated with alcohol use; Rice & Van
Arsdale, 2010). Moreover, some authors found that people who formerly had an alcohol use
disorder had higher levels of perfectionistic cognitions, self-oriented perfectionism, and
socially prescribed perfectionism than those without alcohol problems (Flett et al., 2007;
Sherry et al., 2012). This evidence suggests people high in perfectionistic concerns are
at an increased risk for alcohol-related problems, even if they do not consume large
quantities of alcohol.

<hs>  Perfectionism, negative affect, & avoidance-based drinking motives</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The relationship between negative perfectionism and negative affect (i.e., emotional
states such as anger, sadness, and fear) is well-established. Hewitt, Flett, Sherry, and
Caelian (2006) theorize individuals high in socially prescribed perfectionism experience
negative emotions from day-to-day, as well as enduring levels of trait-like negative
affect across the lifespan. Additionally, longitudinal research found self-critical
perfectionism (a variation of perfectionistic concerns that includes harsh self-criticism)
predicted negative affect 6 months and 3-years later, suggesting these individuals have
chronic negative emotionality (Dunkley, Mandel, & Ma, 2014; Prud'homme et al., 2017). In
cross-sectional research, perfectionistic concerns, perfectionistic cognitions, and
nondisplay of imperfection are all positively related to negative affect (Dunkley et al.,
2006; Dunkley, Zuroff, & Blankstein, 2003; Flett et al., 1998; Hewitt et al., 2003). Slade
and Owens (1998) contend that people high in negative perfectionism (i.e., another
dimension closely related to perfectionistic concerns) are largely motivated by negative
reinforcement. That is, this personality style is driven primarily by the desire to avoid
or escape negative experiences (e.g., to avoid making mistakes and the associated negative
emotions). Because this form of perfectionism is linked to negative reinforcement and
negative affect, and drinking motives theory states that some individuals consume alcohol
to diminish negative emotions (Cooper, 1994), it seems reasonable individuals high in
perfectionistic cognitions and nondisplay of imperfection drink for avoidance-based
motives (i.e., they drink to avoid negative outcomes). Drinking motives theory proposes
two avoidance-based reasons for consuming alcohol.2 Coping motives are self-focused
avoidance motives and refer to drinking to avoid or diminish negative emotions, or to deal
with threats to one’s self-esteem. Conformity motives are social avoidance motives and
include drinking to gain approval from others, or avoid social disapproval. A recent meta-
analysis by Cooper et al. (2015) found a small positive relationship between coping
motives and quantity of alcohol use, and a small negative relationship between conformity
motives and quantity of alcohol use. Yet, in this meta-analysis, only coping motives had a
robust relationship with alcohol-related problems, while conformity motives did not.
Because individuals high in perfectionistic concerns often drink for avoidance-based
reasons, drinking can lead to adverse outcomes. Rice and Van Arsdale (2010) found young
adults high in perfectionistic concerns reported more coping motives and had more alcohol-
related problems than non-perfectionists (i.e., individuals with low levels of
perfectionistic strivings and concerns). Unfortunately, these authors did not assess
quantity of alcohol use or conformity motives – the latter is an important omission, given
that it is also an avoidance-based motivation.3 In general, the literature finds that
coping motives do not predict alcohol use, but result in alcohol-related consequences
(LaBrie, Ehret, Hummer, & Prenovost, 2012; Merrill & Read, 2010; Merrill, Wardell, & Read,
2014; Patrick, Lee, & Larimer, 2011).

<hs>  Rationale and hypotheses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Perfectionism is a transdiagnostic risk factor for psychopathology, particularly disorders
that involve heightened negative affect (Sherry et al., 2015). Research shows a link
between perfectionism facets and hazardous alcohol use (Flett et al., 2007; Sherry et al.,
2012), however the mechanism underlying this relationship remains unknown. Though one
prior study suggested drinking motives as a mediator (Rice & Van Arsdale, 2010), like most
studies on perfectionism, it was cross-sectional and failed to account for daily variation
in perfectionism dimensions. Our study methodologically improves upon Rice and Van Arsdale
(2010) by using a 21-day, once-per-day measurement scale. Moreover, to our knowledge, no
prior studies have examined whether perfectionistic cognitions and perfectionistic self-
presentation (i.e., nondisplay of imperfection) predict avoidance-based drinking motives.
Using a 21-day daily diary design analyzed using multilevel structural equation modeling
(Preacher, Zyphur, & Zhang, 2010), the current study examined the relationships between
perfectionistic cognitions, nondisplay of imperfection, coping and conformity drinking
motives, and alcohol outcomes. Competing avoidance-based motives may explain why those
high in perfectionistic concerns experience alcohol-related problems, but do not drink
large quantities of alcohol. If individuals high in perfectionistic concerns drink for
both coping and conformity motives, these motivations may compete, resulting in a null
bivariate relationship between perfectionistic dimensions and quantity of alcohol use due
to the supressing effect of conformity motives. Specifically, we hypothesized:
Perfectionistic cognitions and nondisplay of imperfection will be positively related to
alcohol problems, but unrelated to quantity of alcohol use. Perfectionism facets will
positively predict negative affect, which in turn will positively predict coping and
conformity motives, which will in turn both predict alcohol problems. That is,
perfectionism facets will have a serial indirect effect on alcohol problems through
negative affect and drinking motives. Conformity motives will have a suppressing effect
when predicting quantity of alcohol consumption. That is, an inconsistent mediation model
(MacKinnon, Fairchild, & Fritz, 2007) will result in no total effect of perfectionism
facets on drinking quantity because coping motives will be positively related to drinking
quantity, and conformity motives will be negatively related to drinking quantity. Though
hypotheses were the same for the between-subjects (i.e., averaged across all 20 days) and
within-subjects (i.e., co-occurring changes within any given day) portions of the model,
the within-subjects portion of the model was of greater interest given its assessment of
change from day-to-day.

<hs>  Open data and materials</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

All study materials, raw data, and syntax are open-access and can be located at
https://osf.io/gduy4/). This includes all copies of questionnaires used (including
measures not analyzed in this paper), the raw data for all measures, and the materials
necessary to reproduce all analyses in this paper.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were recruited from Halifax Regional Municipality (HRM) and Dalhousie
University in Halifax, as well as from Montreal and Concordia University in Montreal.
Eligibility criteria included: (a) being between 18 and 25 years of age; (b) having
consumed a least 12 alcoholic drinks in the past year; and (c) having Internet access at
home. We targeted emerging adults as they tend to engage in heavy episodic drinking
(Johnston, O'Malley, Bachman, & Schulenberg, 2005) and experience alcohol-related problems
(e.g., LaBrie et al., 2012; Hingson, Heeren, Zakocs, Kopstein, & Wechsler, 2002). Flyers
advertising the study were placed around downtown Halifax and on Dalhousie University
campuses. In addition, advertisements were posted online on Dalhousie’s and Concordia’s
undergraduate participant pools in the Department of Psychology and Neuroscience, as well
as an online local classified ad (Kijiji). Mean age of participants (N = 263) was 21.37
(SD = 1.89), with females making up the majority (79.8%) of the sample. Self-reported
ethnicities were Caucasian/White (78.3%), African Canadian/Black (2.3%), Asian (7.7%),
Middle Eastern (1.1%), Hispanic (2.7%), First Nations (0.8%), and Other (6.5%).
Participants’ primary residence was either Nova Scotia (60.5%) or Quebec (39.5%). Since
both samples underwent the exact same procedure, samples from Halifax and Montreal were
combined into a single dataset, with regional differences explored at the end of the
results section.

<hs>  Procedure</hs>
  ~~~~~~~~~

The current study was approved by Dalhousie University’s Social Sciences and Humanities
Research Ethics Board and Concordia University’s Human Research Ethics Committee.
Questionnaires were administered online using a custom-created database. Our online survey
platform provider was Interceptum (https://interceptum.com/p/en). After viewing the
recruitment ads, interested participants contacted our research assistant via email, who
sent them more information. If they agreed to participate, they were sent an email with a
link to the consent form and baseline questionnaire. After consent was electronically
obtained, participants completed the baseline questionnaire on day 1 (∼30 min).
Participants were required to complete the baseline questionnaire before beginning the
daily questionnaires. In the present study, only demographic measures were used from the
baseline questionnaire; the remainder of the measures were measured daily. On days 2
through 21, participants were sent an email with a link to the daily questionnaires.
Respondents were instructed to complete the daily questionnaires every day at end of each
day (i.e., right before bed), as they were asked about events that occurred in the past 24
h. Specifically, the time frame for daily questionnaires went from 4 am one day to 4 am
the next day (e.g., “From 4 am on November 23 to 4 am on November 24”). Answering daily
questionnaires took approximately 15 min. Because each question referred to a specific
time and date, if participants forgot to complete a batch of questionnaires on a day, they
could make it up by filling out two daily questionnaires the following day. After 48 h,
participants were no longer able to complete that day’s questionnaire and did not receive
compensation for that day. After participants completed the study, they were emailed a
debriefing form. To reduce missing data, participants were compensated for each
questionnaire they completed (i.e., $2 worth of Amazon gift cards per day, for a maximum
of $42 over 21 days). Participants could alternatively receive course credit in an
eligible psychology class. They were offered 1 bonus point for every 5 days they
participated in the study for a maximum of 3 bonus credits and a $12 gift card. That is,
every $10 earned could be exchanged for a credit point.

        <hss>Perfectionistic cognitions</hss>

        Perfectionistic cognitions were measured using the Perfectionism Cognitions Short
        Form. This adapted three-item scale was derived from Flett et al. (1998)’s
        Perfectionistic Cognitions Inventory by Mackinnon et al. (2014). Participants were
        to indicate how frequently (0 = not at all to 4 = all of the time) they related to
        each statement (e.g., “I expect to be perfect”) in the past 24-hours. This measure
        has demonstrated acceptable between and within-subjects reliability (R1F = 0.92,
        RKF = 0.99, RC = 0.74) and items had large factor loadings (0.88–0.95) in a prior
        daily diary study (Mackinnon et al., 2014).

        <hss>Nondisplay of imperfection</hss>

        Nondisplay of imperfection was measured using three items from the Nondisplay of
        Imperfection subscale of Hewitt et al. (2003)’s Perfectionistic Self-Presentation
        Scale. Mackinnon et al. (2014) created this short-form by choosing the items with
        the highest factor loadings from the original measure (e.g., “I was concerned
        about making errors in public”). This measure displayed good between and within-
        subjects reliability (R1F = 0.91, RKF = 0.99, RC = 0.72) and each item had large
        factor loadings (0.74–0.92) in a prior daily diary study (Mackinnon et al., 2014).

        <hss>Positive and negative affect scale (PANAS-X)</hss>

        Negative affect was measured using three reduced subscales of the PANAS-X (Watson,
        Clark, & Tellegen, 1988) and one scale from Mackinnon et al. (2014). Each subscale
        is made up of 3 items relating to feelings of guilt (“angry at self”), fear
        (“afraid”), hostility (“scornful”), and depressed affect (“blue”). Participants
        were asked to rate (1 = very slightly or not at all to 5 = extremely) how strongly
        they felt each emotion over the past 24 h. Items that make up the guilt, fear, and
        hostility subscales were derived from the long-form PANAS-X to better fit our
        daily design in order to reduce participant burden by choosing the items with the
        highest factor loadings in prior work. Items from the depressed affect scale show
        good reliability and validity (RF1 = 0.77, RKF = 0.99, RC = 0.81; Mackinnon et
        al., 2014). Short form guilt, fear, and hostility subscales used in the current
        study have not been previously measured, however the original negative affect
        subscale from the PANAS-X has great alpha reliability for past daily diary studies
        (α = 0.87; Watson et al., 1988).

        <hss>Drinking motives revised – short form (DMQ-R-SF)</hss>

        Drinking motives were measured using the Drinking Motives Revised – Short Form
        (DMQ-R-SF; Kuntsche & Kuntsche, 2009). This 12-item scale assesses four drinking
        motives: social (“Because it helps me enjoy a party”), enhancement (“Because it’s
        fun”), coping (“To forget my problems”), and conformity (“To be liked”). The
        current paper used only data from coping and conformity motives. Participants
        indicated how often (1 = strongly disagree to 4 = strongly agree) they drank for
        each reason in the past 24 h. The DMQ-R-SF has good internal consistency
        (Cronbach’s alpha ranging from 0.70 to 0.83), and excellent construct and
        predictive validity (e.g., coping motives were positively linked to academic
        problems and risky sexual behavior). Also, the factor structure is similar to the
        original DMQ-R (Kuntsche & Kuntsche, 2009).

        <hss>Alcohol problems checklist</hss>

        The Alcohol Problems Checklist (Simons, Gaher, Oliver, Bush, & Palmer, 2005)
        contains 12 problematic events that could occur as a result of consuming alcohol
        (e.g., “Taken foolish risks”). Participants checked “yes” or “no” for instances
        that may have occurred in the past 24 h because of their alcohol use. Therefore, a
        participant’s total score on this questionnaire could range from 0 (checking all
        “no”) to 12 (checking all “yes”). This measure was correlated with alcohol
        consumption and negative affect, demonstrating predictive validity (Simons et al.,
        2005).

        <hss>Daily alcohol use</hss>

        Alcohol use was measured by asking participants how many drinks they consumed in
        the past 24 h. Participants responded using a sliding bar that allowed them to
        choose any whole number of drinks that applied best to them. “One drink” was
        defined as half an ounce of absolute alcohol (e.g., a 12-ounce can or glass or
        bottle of beer or cooler, a 5-ounce glass of wine, or a drink containing 1 shot of
        liquor or spirits; National Institute on Alcohol Abuse and Alcoholism, 2003).

<hs>  Data analytic strategy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

First, descriptive statistics were used to summarize the dataset. Means and standard
deviations were reported for total scores of all variables. Internal consistency of each
variable was assessed using a multilevel adaptation of Cronbach’s alpha developed by
Geldhof, Preacher, and Zyphur (2014). We first reported descriptive statistics on protocol
compliance (e.g., days completed) prior to analysis. Because daily drinking motives
questionnaires could only be completed on drinking days, only data from drinking days were
analyzed in subsequent analyses. Following these descriptive statistics, data were
analyzed using multilevel structural equation modeling with fixed slopes (Preacher et al.,
2010). This approach uses all available data by partitioning the available variance into
orthogonal between-subjects components (i.e., trait-like variance that does not vary
across drinking days) and within-subjects components (i.e., state-like variance that
changes across drinking days), analyzing each partitioned component of variance
separately. Thus, most reported statistics (e.g., factor loadings, latent correlations,
path coefficients) are reported twice, once at the between-subjects level and again at the
within-subjects level. To assess whether multilevel modeling was appropriate, we examined
intraclass correlations (ICCs). ICCs can range from 0 to 1, and indicate the proportion of
the variance available to be explained at the between-subjects level. Generally speaking,
these values should be neither too close to 0 nor too close to 1 for multilevel analysis
to be appropriate (Preacher et al., 2010). Prior to hypothesis testing, the measurement
model was tested using multilevel confirmatory factor analysis in Mplus 8 using MLR
estimation for standard errors and fit indices, which is robust to violations of the
normality assumption. Individual questionnaire items (3 items each) were used as
indicators for latent variables for perfectionistic cognitions, nondisplay of
imperfection, coping motives, and conformity motives. Item parcels were used for negative
affect and alcohol problems (Little, Cunningham, Shahar, & Widaman, 2002). The negative
affect latent variable incorporated four item parcels, using the subscale totals for
guilt, fear, hostility, and depression as indicators. The 12 alcohol problems items were
assigned to one of three parcels semi-randomly, by evenly distributing items based on
their variance (i.e., avoiding the situation where all the rarely-endorsed items end up in
a single parcel). Thus, there were 4 items each in parcel 1 (items 1, 10, 7, & 12), parcel
2 (items 3, 4, 2, & 9), and parcel 3 (items 8, 6, 5, & 11). Number of alcoholic beverages
consumed was left as a manifest variable, as it was measured with only a single item. Fit
indices, standardized factor loadings, and latent correlations were reported for the
measurement model. Following the measurement model, a structural model was fit to the data
as outlined in Fig. 1 to test hypotheses. Fit indicies, standardized factor loadings, and
unstandardized path coefficients were reported for this analysis. Tests of indirect
effects were conducted using a Monte Carlo method with 20,000 iterations (Selig &
Preacher, 2008).4 Simulation studies suggest this approach is preferable to bootstrapping
for multilevel models (Preacher & Selig, 2012). We tested serial indirect effects with two
mediators (X → M1 → M2 → Y) using the formula outlined in Hayes (2018).5 If the 95%
confidence interval of the indirect effect did not contain zero, we concluded that
mediation occurred. A well-fitting model was defined as a Confirmatory Fit Index (CFI) and
Tucker-Lewis Index (TLI) greater than 0.95, Root Mean Square Approximation of Error
(RMSEA) values less than 0.06, and Standardized Root Mean Square Residual (SRMR) value
less than 0.08 (Kline, 2011).

<hs>  Pilot testing measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Many of the measures were adapted from their original form by asking participants to
report on “The past 24 h.” Thus, a small pilot study was conducted to test the
psychometric properties of these measures prior to the main study. Criterion validity was
assessed by correlating measures that asked participants to report on “The past 24 h” to
identical measures that asked participants to report on “The past 3 years.” Internal
consistency was tested using Cronbach’s alpha. A sample of 137 undergraduate drinkers
(84.7% female) were recruited using the same criteria as the diary study, and completed
questionnaires online. Both criterion validity and internal consistency were adequate for
perfectionism cognitions (r = 0.66, α = 0.89), nondisplay of imperfection (r = 0.62, α =
0.86), alcohol problems (r = 0.43, α = 0.79), negative affect (r = 0.64, α = 0.94), coping
motives (r = 0.78, α = 0.88), and conformity motives (r = 0.73, α = 0.87). Correlations
were significant at p < .001. These pilot data suggested our measures would be reliable
and valid for use in the diary study. These pilot data are open-access, and are available
at https://osf.io/gduy4/.

<hs>  Protocol compliance</hs>
  ~~~~~~~~~~~~~~~~~~~

Twenty-one participants (8.0%) did not drink during the study; thus, daily data is missing
for these individuals. However, out of these twenty-one participants, one participant did
not complete any daily questionnaires (only the baseline), and two participants completed
only one day of the daily questionnaires. All participants were required to complete
baseline measures before beginning the daily measures, thus there was no missing data for
demographic variables. Out of 20 days, participants completed on average 16.16 days (SD =
4.68), with an average of 4.70 (SD = 3.80) drinking days. See Supplementary Table 2 for
frequencies of the number of drinking days for participants. On average, participants
completed 7.87 (SD = 4.93) make-up days (i.e., submissions that were 1 day late), which
suggests that these make-up questionnaires were essential to achieving low rates of
missing data. With our design, it was possible to have a maximum 5260 data points (263
participants * 20 daily measurements). Of these, 1236 were drinking days with data, 3015
were non-drinking days, and 1009 were missing data (i.e., no data for the entire day).
Thus, 29% of reporting days were drinking days. This is consistent with prior daily diary
research on undergraduates, which found that 24% of reporting days were drinking days
(Grant, Stewart, & Mohr, 2009). Thus, the final analysis included 1236 drinking days
nested within 242 participants. Overall, there was comparatively little missing data and
participants were generally good at filling out the daily questionnaires as scheduled.
Non-drinking days and missing days with no data were selected out of the analysis using
listwise deletion. Item-level missing data (<1%) were handled using a full information
maximum likelihood approach.

<hs>  Descriptive statistics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Means, standard deviations, and alpha reliabilities are located in Table 1. Generally
speaking, measures had adequate reliability. However, internal consistencies were low at
the within-subjects level for alcohol problems, which suggests greater measurement error
for this variable. Means were slightly higher for perfectionistic cognitions (d = 0.51)
and nondisplay of imperfection (d = 0.52), and almost identical for quantity of alcohol
consumption (d = −0.01) when compared to prior studies sampled from this population (Grant
et al., 2009; Mackinnon et al., 2014). Means for negative affect (d = −0.42), coping
motives (d = −0.19), conformity motives (d = −0.32), and alcohol problems (d = −0.41) were
slightly lower, but comparable to those obtained in our psychometric study.

<hs>  Measurement model</hs>
  ~~~~~~~~~~~~~~~~~

ICCs ranged from 0.24 to 0.72, suggesting that there was substantial variation from day-
to-day, but also trait-like stability across all 20 days (Table 2). Generally speaking,
ICCs were large for perfectionism variables (0.65–0.72), moderate for drinking motives and
affect (0.43–0.59), and small for drinking outcomes (0.24–0.29). This suggests that
perfectionism variables are more trait-like, alcohol outcomes are more state-like, with
negative mood and drinking motives falling somewhere in between. The measurement model fit
the data well for all fit indices except for the overall χ2, χ2(300) = 555.46, p < .001,
CFI = 0.97, TLI = 0.96, RMSEA = 0.03, SRMRwithin = 0.03, SRMRbetween = 0.06. Standardized
factor loadings were all large and substantial, with the lower bound of the 95% confidence
intervals for the factor loadings ranging from 0.44 to 0.89 at the within-subjects level
and from 0.59 to 0.98 at the between-subjects level (Table 2). Generally speaking, factor
loadings were more substantial at the between-subjects level than at the within-subjects
level. Overall, these analyses suggested that the measurement model was adequate. Latent
correlations from the measurement model are reported in Table 3. At the between-subjects
level, perfectionism variables, drinking motives, negative affect, and alcohol problems
were all positively intercorrelated with medium to large effect sizes (0.24–0.66).
However, alcohol consumption was correlated only with alcohol problems (0.29), and was
uncorrelated with all other variables at the between-subjects level. The within-subjects
correlations mostly mirrored the between-subjects correlations, but with smaller effect
sizes. Nondisplay of imperfection, drinking motives, negative affect, and alcohol problems
were all positively intercorrelated (0.13–0.41). However, a few key differences emerged
(a) Perfectionism cognitions were generally uncorrelated with other variables, save for a
positive correlation with nondisplay of imperfection (0.38) and a weak negative
correlation with alcohol consumption (−0.07); (b) the relationship between alcohol
consumption and alcohol problems was slightly larger than the between-subjects correlation
(0.47 vs. 0.29); and (c) alcohol consumption was weakly positively correlated with coping
(0.07) and conformity (0.19) motives. In general, variables were correlated with each
other in the expected directions, and supported moving forward with the structural model
in subsequent steps.

<hs>  Structural model</hs>
  ~~~~~~~~~~~~~~~~

The final model is depicted in Fig. 1 and tests of indirect effects are reported in Table
4. Fig. 1 shows 95% confidence intervals for parameters; however, the point estimates,
standard errors, and p-values are in Supplementary Table 5. This model fit the data well
except for the overall χ2, χ2(300) = 555.46, p < .001, CFI = 0.97, TLI = 0.96, RMSEA =
0.03, SRMRwithin = 0.03, SRMRbetween = 0.06. The between-subjects analysis examined the
trait-like component of variance that did not vary across 20 days. H2 was partially
supported for the between-subjects model; nondisplay of imperfection (but not
perfectionistic cognitions) had a serial indirect effect on alcohol problems through
negative affect, coping motives, and conformity motives. However, H3 was not supported;
there were no significant serial indirect effects when predicting number of alcoholic
drinks consumed. Moreover, effects predicted by H3 were not in the expected direction, as
the effects of coping and conformity motives were both positive. Overall, variables in the
model predicted a substantial amount of variance in all outcome variables (R2 from 0.26 to
0.48) except for number of alcoholic drinks consumed (R2 = 0.03). The within-subjects
analysis examined state-like variations from day-to-day (i.e., when X changes, does Y
change with it?). Results were broadly similar to the between-subjects results, albeit
with much smaller effect sizes (R2 from 0.03 to 0.20). Though the statistical significance
of a few paths changed relative to the between-subjects model (e.g., conformity motives
were a significant predictor of drinking outcomes in the within-subjects model), the
overall pattern of the indirect effects was the same. That is, nondisplay of imperfection
had a serial indirect effect on alcohol problems through negative affect, coping motives,
and conformity motives, while all other indirect effects were non-significant. Though not
directly hypothesized, there remain some interesting direct effects worthy of discussion.
Negative affect had a significant, positive direct effect on alcohol problems. Moreover,
it had a non-significant negative relationship with number of drinks consumed. Both of
these are important to understand the pattern of results observed. The relationship
between coping motives and alcohol problems was small after controlling for negative
affect; in fact, it became non-significant in the within-subjects model. Nonetheless,
because the serial indirect effect also incorporates the direct effect of negative affect
on alcohol problems, the overall serial indirect effect can remain significant even in the
presence of a non-significant relationship between coping motives and alcohol problems. It
does, however, suggest that negative affect may be more important than coping motives when
predicting day-to-day variation in alcohol problems. Similarly, in Fig. 1, it may look as
though nondisplay of imperfection should have an indirect effect on number of drinks
consumed through negative affect and conformity motives. However, because the effect of
negative affect on number of drinks is negative (despite being non-significant), it exerts
a small suppressing effect on the serial indirect effect, resulting in non-significance.
Thus, it appears that a suppressing effect of negative affect may contribute to the lack
of a total effect of perfectionism facets on drinking quantity. It is also worth noting
that (once controlling for all other variables in the model) perfectionistic cognitions
had a small negative direct effect on drinking quantity in the within-subjects model, and
a small negative direct effect on alcohol problems in the between-subjects model, contrary
to the expected positive relationship. Given the magnitude of the relationship, it may be
spurious, but is worth noting.

<hs>  Regional differences</hs>
  ~~~~~~~~~~~~~~~~~~~~

Given that data was sampled from two sites in Canada (Halifax, Nova Scotia and Montreal,
Quebec), we explored potential regional differences by entering province of residence (0 =
Halifax, 1 = Montreal) as a between-subjects covariate into our final structural model.
This model fit the data about equally well to the model without the covariate, χ2(313) =
575.49, p < .001, CFI = 0.97, TLI = 0.96, RMSEA = 0.03, SRMRwithin = 0.03, SRMRbetween =
0.05. Moreover, no null hypothesis test conclusions in Fig. 1 changed as a result of this
covariate. However, Halifax participants had higher rates of drinking, 95% CI (−1.60,
−0.48) and lower rates of coping motives, 95% CI (0.02, 0.17) in this SEM model.6

<h>EXPLORATORY RANDOM SLOPES MODEL</h>
-------------------------------

We also explored a random slopes model, as there was substantial variation in the slopes.
In this model, variances were estimated for the random slopes, but the covariances of
random components were constrained to be zero for model parsimony (i.e., a variance
components model). We also used a Bayesian estimator for more efficient convergence of
this complex model. Indirect effects were calculated with the delta method using MODEL
CONSTRAINT in Mplus. These results are summarized in Supplementary Fig. 1 and
Supplementary Table 4. Results of null hypothesis tests were broadly similar to the fixed
slopes model, with a few differences. The 3 direct effects of both perfectionism variables
on alcohol outcomes that were originally statistically significant in the fixed model
became non-significant. At the within-subjects level, the relationship between
perfectionism cognitions and conformity motives became statistically significant and the
relationship between nondisplay of imperfection and coping motives became non-significant.
For indirect effects, the the Nondisplay → Negative Affect → Coping → Problems indirect
effect at the within-subjects level became non-significant, and the Nondisplay → Negative
Affect → Conformity → Drinks indirect effect became statistically significant at the
between level. In general, the effect sizes using R2 also tended to be much larger in this
model. Overall, effects that differ across fixed vs. random slopes models are unstable,
and should be considered less reliable than effects that replicate across analyses.7

<h>DISCUSSION</h>
----------

The current study examined the relationship between perfectionistic cognitions, nondisplay
of imperfection, avoidance-based drinking motives, negative affect, and alcohol outcomes.
We used multilevel structural equation modeling to assess whether these perfectionism
facets predicted alcohol problems when averaged across 20 days (i.e., between-subjects)
and whether changes in these facets predicted co-occurring changes in alcohol problems
from day-to-day (i.e., within-subjects). There was significant variance to be explained at
both the between- and within-subjects level, suggesting the variables under study have
both trait-like and state-like qualities. Perfectionistic cognitions and nondisplay of
imperfection were the most trait-like, which is in line with the notion that perfectionism
is a relatively stable personality trait (e.g., Hewitt & Flett, 1991). However, there was
also significant day-to-day fluctuations. This supports other short-term longitudinal
studies suggesting perfectionism dimensions can be interpreted as more dynamic, state-like
features of personality (Boone et al., 2012; Graham et al., 2010; Mackinnon et al., 2014).
Negative affect, coping motives, and conformity motives fluctuated more than
perfectionistic cognitions and nondisplay of imperfection on a day-to-day basis, with
approximately an equal amount of variance to be explained at both the between- and within-
subjects level. Lastly, alcohol-related problems had the largest amount of daily
variation, suggesting they are dynamic and may be influenced by situational and
environmental factors.

<hs>  Nondisplay of imperfection and alcohol problems</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The core finding was that nondisplay of imperfection indirectly predicted alcohol problems
(but not quantity of alcohol consumption) through negative affect, coping motives, and
conformity motives. These findings replicate previous empirical literature on the link
between nondisplay of imperfection and negative affect (Hewitt et al., 2003; Mackinnon et
al., 2014), and negative affect and avoidance-based drinking motives (Cooper et al., 2015;
Todd et al., 2005). These results are also in line with evidence indicating coping motives
are robustly associated with alcohol-related problems independent of heavy drinking
(Cooper, Frone, Russell, & Mudar, 1995; Kuntsche & Cooper, 2010; Merrill & Read, 2010;
Piasecki et al., 2014; Simons, Gaher, Correia, Hansen, & Christopher, 2005). Individuals
high in nondisplay of imperfection tend to engage in this self-presentation strategy to
compensate for perceived imperfections, yet often have a difficult time modifying how they
present themselves to others (Hewitt et al., 2003). This often leads to feelings of
inadequacy and decreased self-efficacy. Thus, it is reasonable that these individuals
drink to cope with negative emotions, resulting in adverse alcohol-related consequences.
However, it is worth noting that the Bayesian random effects model found that the indirect
effect of nondisplay of imperfection on alcohol problems through negative affect and
coping motives was non-significant at the within-subjects level, and that the indirect
effect of nondisplay of imperfection on drinking quantity through negative affect and
conformity motives became statistically significant at the between-subjects level. Thus,
these relationships are comparatively more uncertain, pending future replication.

<hs>  Perfectionism cognitions and alcohol problems</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Contrary to H2, perfectionistic cognitions did not predict negative affect at either the
between- or within-subjects level once controlling for nondisplay of imperfection. Thus,
it also failed to indirectly predict coping motives, conformity motives, alcohol-related
problems, and quantity of alcohol consumption. Perfectionistic cognitions did tend to be
positively correlated with all other outcomes except for alcohol consumption at the
between-subjects bivariate level (Table 3), consistent with prior cross-sectional work
(Flett et al., 1998; Flett, Hewitt, et al., 2012). However, it did have a small negative
relationship with alcohol outcomes once controlling for nondisplay of imperfection in some
models, consistent with some theorists’ contention that certain perfectionism facets are
adaptive (Stoeber & Otto, 2006). Nonetheless, it did not predict outcomes at the within-
subjects level (i.e., co-occurring changes from day-to-day), nor did it predict negative
affect beyond nondisplay of imperfection in the structural model. Thus, perfectionism
cognitions were not related to alcohol outcomes in a substantive way. Though the Bayesian
random slopes model suggested an indirect effect of perfectionistic cognitions on drinking
quantity through negative affect and conformity motives at the between subjects level,
this effect was primarily due to the positive relationships between (a) negative affect
and conformity and (b) conformity and drinking quantity, since perfectionistic cognitions
had weak, non-significant relationships with negative affect and conformity. Stoeber et
al. (2014) posit that perfectionistic cognitions should be assessed as a multidimensional
construct. These authors proposed that the Perfectionism Cognitions Inventory (PCI)
measures three distinct factors (i.e., perfectionistic concerns, perfectionistic
strivings, and perfectionistic demands), each relating to different psychological
outcomes. Stoeber et al. (2014) found that thoughts about perfectionistic concerns
predicted negative affect, while cognitions about perfectionistic strivings predicted
positive affect. Two of the subscales used to measure perfectionistic cognitions in our
study (“I expect to be perfect” and “My work should be flawless”) were shown to have high
factor loadings on the perfectionistic strivings dimension. By using the PCI-Short Form
and failing to partial out these two factors, mutual suppression could have occurred
(i.e., cognitions about perfectionistic strivings could have supressed the effect of
cognitions about perfectionistic concerns), leading to the lack of association between
perfectionistic cognitions and negative affect in the current study. It also may be that
individuals high in perfectionistic cognitions have coping strategies to deal with
frequent perfectionistic thoughts. Indeed, research has found that individuals high in
personal standards perfectionism (i.e., perfectionistic strivings) engage in problem-
focused coping strategies (Dunkley et al., 2000; Prud'homme et al., 2017) and positive
reinterpretation (Dunkley et al., 2014). These tactics could lead to fewer negative
emotions and thus fail to predict avoidance-based reasons for drinking and alcohol-related
problems.

<hs>  Perfectionism facets and quantity of alcohol consumption</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In H3, we proposed conformity motives would have a suppressing effect, leading to
inconsistent mediation (MacKinnon et al., 2007) between nondisplay of imperfection,
perfectionistic cognitions, and quantity of alcohol consumption. That is, we proposed a
positive effect of coping motives and a negative effect of conformity motives, leading to
a null total effect of perfectionism facets on alcohol consumption. This hypothesis was
unsupported; in fact, in the within-subjects model (and in both the within- and between-
subjects models in the random slopes model), conformity was positively related to alcohol
consumption. Nonetheless, there was a weak, negative, and non-significant trend between
negative affect and number of drinks consumed, after controlling for all other variables
in the model. This negative trend had a small suppressing effect on one of the serial
indirect effects (nondisplay → negative affect → conformity → drinking quantity), and is
consistent with prior work that suggests people high in negative affect experience more
alcohol-related problems, without necessarily drinking large quantities of alcohol (Cooper
et al., 2015). The generally positive relationship between conformity motives and alcohol
consumption is inconsistent with past literature suggesting conformity motives have a
small negative association with alcohol consumption (Cooper et al., 2015; Cooper, 1994).
However, prior literature failed to disentangle between and within-subjects effects using
longitudinal, multilevel analysis (Preacher et al., 2010); this makes the present findings
somewhat difficult to compare to prior work.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our study has important limitations. Our sample was primarily young, Caucasian and female,
which limits generalizability. Given that women have higher psychological distress, and
men have higher levels of alcohol abuse (Adlaf et al., 2004), future studies might
consider moderation by gender. Regardless, results of this study may generalize to men
more poorly given the large proportion of women in the present study. Moreover, results
should not necessarily be generalized beyond the regions sampled – even across two regions
in the same country, we found minor differences in drinking patterns. The present study
also limited its focus to two dimensions of perfectionism and two drinking motivations,
given the complexity of our analytic strategy and page limits of most journal outlets.
Given that other dimensions of perfectionism (e.g., self-oriented, socially prescribed,
and other-oriented perfectionism; Hewitt & Flett, 1991) and drinking motives (i.e., social
and enhancement motives) were measured in the present study, future researchers may wish
to utilize our open-access dataset to test supplementary hypotheses with these variables
in a separate manuscript. Some participants had few drinking days (Supplementary Table 2);
this can impede estimation of the within-subjects effects. Future research may wish to
extend the daily diary period (e.g., to a period of 2 months) to increase cluster sizes.
Statistical power may also be a concern, as there was not enough existing information in
the literature to specify all the parameters for a Monte Carlo a-priori power simulation.
However, the present study could inform a power analysis for a subsequent replication.
Thus, as is true of all research, conclusions should be considered tentative pending
replication. Another important limitation is our reliance on self-report measures. Self-
report measures are well-known to suffer from social desirability biases, where
respondents answer untruthfully in order to present themselves in a more positive light.
This could be especially problematic for individuals high in perfectionistic self-
presentation (e.g., nondisplay of imperfection). Future research should combine self-
report measures with informant reports to obtain a more accurate and comprehensive view of
perfectionistic dimensions and how they relate to negative emotions, avoidance-based
drinking motives, and alcohol outcomes. Moreover, a 24 h time lag is arbitrary, and asking
participants to aggregate across a 24 h period makes it difficult to tease apart
directionality; future research might utilize event-contingent measurement (e.g., right
after each drink). Though we were limited by the need for short-form measures to reduce
participant burden, future research might assess perfectionistic cognitions as a
multidimensional construct (e.g., Stoeber et al., 2014). Furthermore, it is important to
acknowledge that our within-subjects model assesses only co-occurring changes within a
given day. Such a model does not establish temporal precedence, which is a necessary
prerequisite for inferring causality. Moreover, reporting on consumption once per day may
miss more nuanced processes that occur on a shorter timeframe. Thus, these relationships
should not be interpreted as causal. Lastly, we only studied one type of risky behavior
(i.e., alcohol-related outcomes), yet theory and research suggest risky behaviors (e.g.,
unsafe sex, illicit substance use) tend to cluster together (Jessor, 1987; Mobley & Chun,
2013; Vazsonyi et al., 2008). Thus, exploring whether individuals high in perfectionistic
cognitions and nondisplay of imperfection are at an increased risk for other unsafe
behaviors, such as risky sexual behavior or substance abuse, would be beneficial to
examine. It may be that perfectionists’ tendency to engage in self-presentation strategies
and rumination make other types of risky behaviors less appealing. In contrast, those high
in negative forms of perfectionism may use marijuana or other drugs to cope with negative
emotionality. Psychotropic drugs used to regulate mood (e.g., SSRIs) could also lead to
extreme intoxication due to alcohol sensitivity, offering an explanation as to why these
individuals experience problems while drinking without consuming large amounts of alcohol.
All of these possible explanations represent interesting avenues for future research.

<h>CONCLUSION</h>
----------

Overall, our hypotheses about perfectionistic cognitions and drinking quantity were
unsupported, while our hypotheses about nondisplay of imperfection and alcohol problems
were supported. Perfectionistic cognitions do not appear to predispose individuals to
negative emotions and avoidance-based drinking problems. In contrast, nondisplay of
imperfection conferred risk for alcohol-related problems via negative affect and
negatively-reinforcing drinking motivations. Hewitt et al. (2003) propose that individuals
who engage in perfectionistic self-presentation do so in an attempt to gain approval and a
sense of belonging from others. Unfortunately, these attempts are often in vain as others
tend to perceive their inauthenticity, leading to further social alienation.
Understandably, these factors may contribute to alcohol misuse and alcohol-related
problems. Nondisplay of imperfection and problematic drinking among young adults is a
major clinical and societal issue. Broadening our understanding of perfectionistic
dimensions and the mechanisms through which these trait-states function may aid us in
developing personality-tailored interventions, which will hopefully lead to fewer alcohol-
related problems for people high in nondisplay of imperfection in the future.


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<ART>Phone-based metric as a predictor for basic personality traits
==============================================================

Authors: Bjarke Mønsted, Anders Mollgaard, Joachim Mathiesen
DOI: 10.1016/j.jrp.2017.12.004
Year: 2018  |  Pages: 16-22
ASJC codes: 3200, 3207
Keywords: Big Five personality traits, Human dynamics, Phone-based metrics, Predicting personality

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Basic personality traits are believed to be expressed in, and predictable from, smart phone data. We investigate the extent of this predictability using data (n = 636) from the Copenhagen Network Study, which to our knowledge is the most extensive study concerning smartphone usage and personality traits. Based on phone usage patterns, earlier studies have reported surprisingly high predictability of all Big Five personality traits. We predict personality trait tertiles (low, medum, high) from a set of behavioral variables extracted from the data, and find that only extraversion can be predicted significantly better (35.6%) than by a null model. Finally, we show that the higher predictabilities in the literature are likely due to overfitting on small datasets.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Over the last decades, new data collection methods have provided new opportunities for
research on human behavior. Online social networks or personal mobile devices do not only
provide real-time data for studies on human activity and interaction, but can also serve
as an external validation of e.g. more classical questionnaire- or interview-based
studies. For example, the predictability of basic personality traits from smart-phone
usage is currently an active area of research Crandall et al. (2010), de Oliveira,
Karatzoglou, Concejero Cerezo, Armenta Lopez de Vicuña, and Oliver (2011), LiKamWa, Liu,
Lane, and Zhong (2011), Verkasalo, López-Nicolás, Molina-Castillo, and Bouwman (2010),
Chittaranjan, Blom, and Gatica-Perez (2011a), Chittaranjan, Blom, and Gatica-Perez
(2011b), Williams, Whitaker, and Allen (2012), de Montjoye, Quoidbach, Robic, and Pentland
(2013), Sekara and Lehmann (2014), Mollgaard et al. (2016b). Based on data from the
Copenhagen Network Study (CNS), Stopczynski et al. (2014), we use smartphone data to
quanitfy the predictability of the Big Five personality traits Digman (1990), openness
(O), conscientiousness (C), extraversion (E), agreeableness (A) and neuroticism (N),
commonly called the five factor model and abbreviated as OCEAN. The CNS data is to the
best of our knowledge the largest and most detailed study of its kind. Specifically, we
use the Big Five Inventory John, Naumann, and Soto (2008), which consists of 44 items. For
each item, participants in the CNS study have expressed, on a discrete scale from 1 to 5,
how much they agree with a given statement. The personality traits are then computed from
a pre-determined linear combination of the 44 answers. Previous research has suggested
that smartphone data can be used to predict the Big Five with surprisingly high accuracy
de Montjoye et al. (2013). In contrast, we show using a broad range of features extracted
from the CNS data that only extraversion can be predicted with some certainty. In the
Methods section below and in the appendices, we provide a description of the features
(predictor variables) we extract from the smartphone data and further consider their
cross-correlations. In the Results section, we use a support vector machine model for the
prediction and quantify its relative improvement over a null model where personality
scores are randomly assigned. Finally, we briefly compare the scoring system behind the
Big Five Inventory against alternative dimensionality reduction techniques in terms of
predictability.

<h>METHODS</h>
-------

We use questionnaire-based data on the personality traits together with phone based-data
from 730 freshman students starting in the year 2013 at the Technical University of
Denmark. The phone-based data has been collected over a period of 24 months by custom
software installed on smartphones given to the participants of the study, Stopczynski et
al. (2014). The data consists of telecommunication logs (phone calls, text messages),
online social networks (Facebook connections and interactions), and networks based on
physical proximity. The physical proximity is measured through the Bluetooth signal
strength, and can be used to monitor face-to-face contacts Sekara and Lehmann (2014). From
the GPS data, we obtain information on the geo-spatial mobility Mollgaard, Lehmann, and
Mathiesen (2016a). Out of the 730 participants, we only include data from individuals,
which, we believe, have used the phone as a primary device. This implies discarding data
from users that have written less than 10 text messages, made 5 phone calls or have 100
GPS data points, as well as users with no Facebook friends. These criteria were chosen as
a simple heuristic for removing participants who very quickly stopped using the phone, as
the subjects remaining after this removal had vastly larger amounts of data. These
requirements reduce the number of participants in our study to 636. For comparison
purposes, we consider a list features similar to those in de Montjoye et al. (2013).
Furthermore, we repeat our analysis on the part of the Friends and Family (FF) dataset,
Aharony, Pan, Ip, Khayal, and Pentland (2011), which is publicly available.1 The FF
dataset consists of data from 52 participants, 38 of whom have sufficient call and
location data for our analysis according to the selection criteria described above. We
finally compare our analysis on both datasets with the results in de Montjoye et al.
(2013). Table 1 presents a list of all the features we consider. The feature extraction
process is described in detail in the following. A number of quantities based on location
data are also computed. We extract the median and standard deviation of the users’ daily
distance travelled, their daily radius of gyration (here simplified to be the radius of
the smallest circle enclosing all coordinates visited by the user on each day) and the
entropy of the time spent in various locations by the user. We identify the locations
visited by clustering the GPS points sampled when a user is not moving. A user is defined
to not move, if the user’s mean speed does not exceed 0.5 m/s in a period between two
consecutive GPS points. As the uncertainty on civilian GPS locations can be up to 100 m
Zandbergen and Barbeau (2011), a user moving at a speed of 0.5 m/s would need at least 400
s to move a distance larger than two times the uncertainty. For that reason, we consider
only GPS points taken even further apart, i.e. 500 s apart. The GPS data points are
filtered according to the following procedure. For each user, we include the first
recorded GPS data point, we then exclude data points in the subsequent time window of 500
s and then again include the first data point sampled outside this window. From this new
data point we repeat the procedure of excluding points in a subsequent window of 500s and
so forth. We identify clusters (locations) in the GPS points by use of the DBSCAN
algorithm Ester, Kriegel, Sander, and Xu (1996) and we compute the entropy of visits to
those clusters by again applying Eq. (1). Finally, we estimate the fraction of time a user
spends at home, where home is assumed to be the place where a user spend most of their
weeknights. We finally extract a range of features concerning a user’s social contacts.
This includes their number of Facebook friends and the fraction of the time users spend in
the proximity of other participants in the study. This is estimated from repeated
automatic scans by the Bluetooth ports. The entropy of the proximity is also calculated
similarly to Eq. (1), as well as the time series parameters as described in Eq. (2).

<hs>  Classification</hs>
  ~~~~~~~~~~~~~~

We divide the scores on each of the five personality traits into tertiles, i.e. we assign
a label of 0, 1 or 2 specifying whether they score low, medium, or high on that trait,
corresponding to them lying in the bottom, middle, or upper third, respectively, of all
the user scores for that trait. We do this for two reasons - first, this has been done in
existing research Chittaranjan et al. (2011a), de Montjoye et al. (2013) and hence allows
comparison between our results and those in the literature. Second, although regression
approaches have nice accuracy metrics like the mean squared error (MSE), which provides a
number for how far from the true values the prediction of the regressor typically is, this
measure is not particularly meaningful on ordinal values like personality traits, where
e.g. higher extraversion scores mean a person is more extroverted, but there’s no precise
interpretation for a difference in extraversion score of, say, 0.2. In the first approach,
we perform a number of cross-validation runs. For each training set introduced during the
cross-validation, we first choose the n features with the strongest correlations with the
personality traits and perform an extensive grid search in the hyperparameter space. As a
consequence, both the hyperparameter values and the features included in the classifier
will vary between each cross validation run, potentially making it more difficult to
interpret the results. At the same time, however, this ensures that training and test sets
are completely separated, and thus that we do not observe overly optimistic results caused
by overfitting.

<h>RESULTS</h>
-------

In de Montjoye et al. (2013) a mean relative improvement of 0.42 is reported, which is
significantly above what is reported in another study Chittaranjan, Blom, and Gatica-Perez
(2013). We note that significant improvements over a baseline classifier for traits other
than extraversion appears contingent on (a) having few data points, and (b) using
correlations on the full dataset for feature selection, thus allowing the model to be fit
to noise. Hence, it seems likely that earlier reports of high predictability of human
personality traits from phone metrics have been greatly overestimated due to overfitting
enabled by a combination of small sample sizes and a large number of variables. We note
that only the extraversion trait appears to be truly predictable from phone-based data.
This is in good agreement with common sense, as phones by their nature are devices for
inter-human communication. Further, some of the features used in the classifier are
expected to be related to extraversion such as the users’ number of Facebook friends and
the number of new contacts made during the first months of the study. Based on the Big
Five Inventory, the personality traits are computed by reducing the 44 answers to five
scores. Any dimensionality reduction of this kind will inevitably lose information
available from the full set of answers. We have therefore performed a series of
alternative reduction methods on the 44 items to see if we could improve our predictions
of the personality traits (see the appendices). Both supervised and unsupervised
dimensionality reductions have been used. Among the unsupervised methods, we have tried
principal component analysis, independent component analysis and factor analysis. We have
applied the methods directly to the answers to the 44 items in order to extract five
dimensional objects keeping the most relevant information about the original 44 items. In
the unsupervised reduction no information about the features is used. For the supervised
reduction method, we try reduce the target variables (the list of items) by finding those
items that can be best predicted from the predictor variables (the features). While both
the supervised and unsupervised methods improve significantly the quality of our
predictions, the overall picture is the same that predominantly items related to
extraversion can be predicted with some certainty.

<h>DISCUSSION</h>
----------

Using data from the Copenhagen Network Study, which, to our knowledge is the largest
dataset simultaneously containing information about the Big Five personality traits and
extensive information about smartphone usage patterns, we have shown that the extraversion
trait can be predicted significantly better than a null model based on random
classification. In contrast, the other personality traits are poorly predicted by our
data. Our findings contrast previous studies, which report significant predictabilities
across all traits. Given that we have carried out the analysis on datasets of two sizes
using two feature selection procedures, and since we obtained high predictabilities only
when (a) using full-dataset correlations for variable selection and (b) analyzing a small
dataset, the combination of the two appears a likely explanation for the results
previously reported in the literature. Regarding the generalizability of our findings, we
note that all participants in the study were students at the Technical University of
Denmark, and that findings are not necessarily generalizable to the population in general.

<h>AVAILABILITY OF DATA AND MATERIALS</h>
----------------------------------

Data are part of larger study “Social Fabric” involving researchers at the Technical
University of Denmark and University of Copenhagen. Due to privacy consideration regarding
subjects in our dataset, including European Union regulations and Danish Data Protection
Agency rules, we cannot make all data used here publicly available. The data contains
detailed information on mobility and daily habits at a high spatio-temporal resolution. We
understand and appreciate the need for transparency in research and are ready to make the
data available to researchers who meet the criteria for access to confidential data, sign
a confidentiality agreement, and agree to work under our supervision in Copenhagen. The
“Social Fabric” study was reviewed and approved by the appropriate Danish authority, the
Danish Data Protection Agency (Reference number: 2012-41-0664). The Data Protection Agency
guarantees that the project abides by Danish law and also considers potential ethical
implications. All subjects in the study gave written informed consent.

<h>COMPETING INTERESTS</h>
-------------------

The authors declare that they have no competing interests.


<h>REFERENCES</h>
----------

  [1] Nadav Aharony, Wei Pan, Cory Ip, Inas Khayal, Alex Pentland. Social fMRI: Investigating and shaping social mechanisms in the real world. doi:10.1016/j.pmcj.2011.09.004
  [2] Gokul Chittaranjan, Jan Blom, Daniel Gatica-Perez. Mining large-scale smartphone data for personality studies. doi:10.1007/s00779-011-0490-1
  [3] Gokul Chittaranjan, Blom Jan, Daniel Gatica-Perez. Who's who with big-five: Analyzing and classifying personality traits with smartphones. doi:10.1109/ISWC.2011.29
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  [5] David J. Crandall, Lars Backstrom, Dan Cosley, Siddharth Suri, Daniel Huttenlocher, Jon Kleinberg. Inferring social ties from geographic coincidences. doi:10.1073/pnas.1006155107
  [7] Rodrigo De Oliveira, Alexandros Karatzoglou, Pedro Concejero, Ana Armenta, Nuria Oliver. Towards a psychographic user model from mobile phone usage. doi:10.1145/1979742.1979920
  [8] John M. Digman. Personality structure: emergence of the five-factor model. doi:10.1146/annurev.ps.41.020190.002221
  [10] Y. A. Hamburger, E. Ben-Artzi. Relationship between extraversion and neuroticism and the different uses of the Internet. doi:10.1016/S0747-5632(00)00017-0
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<ART>Posttraumatic growth in students, crime survivors and trauma workers exposed to adversity
================================================================================

Authors: Matthew Brooks, Michelle Lowe, Nicola Graham-Kevan, Sarita Robinson
DOI: 10.1016/j.paid.2016.04.051
Year: 2016  |  Pages: 199-207
ASJC codes: 3200
Keywords: Adversity, Positive psychology, Posttraumatic growth, Posttraumatic stress, Psychological functioning, Trauma, Victimisation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Generalised models of positive change following adversity do not fully account for differences in adjustment among populations who experience posttraumatic growth (PTG). The contributions of event intentionality, frequency of the adversity types, age at serious event, spirituality/religiousness, active coping, PTSD symptoms and social support were explored as predictors of PTG across three samples of university students (N = 101; Study 1), survivors of violent crime recruited from support services (N = 71; Study 2) and those working with survivors of adversity (N = 96; Study 3). The results of Study 1 revealed that age at serious event, active coping, PTSD symptoms and social support positively predicted PTG. Within Study 2, spirituality/religiousness, active coping and social support were the significant positive predictors of PTG. Finally in Study 3, spirituality/religiousness, active coping and social support were the significant positive predictors of PTG. Across all studies, event intentionality and frequency of adversity types did not determine PTG. These results indicate that while participants within each of the populations have the ability to experience PTG, different factors predicted whether PTG was observed. The findings offer greater insight into the multifarious nature of adjustment following adversity.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The experience of adverse events often leads to stressful or traumatic reactions and
changes in psychological functioning. Nevertheless, some people exposed to adversity
report positive changes as a result of their experiences. Such changes are characterised
by a greater appreciation for life, the perception of new opportunities, increased
feelings of personal strength, improved relationships with people and an enhanced
religiosity or spirituality (Joseph, 2012; Tedeschi & Calhoun, 2004). This positive
transformation is known as posttraumatic growth (PTG; Tedeschi & Calhoun, 2004), and
contrasts with earlier literature that has long-considered only the negative consequences
associated with adversarial events.

<hs>  Transformational theory of PTG</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The processes that underlie the development of PTG are thought to emerge in the same way
as do negative effects. These are largely represented in existing models of growth, most
notably the transformational model (Tedeschi & Calhoun, 2004). Broadly, the model proposes
event-related cognitions and individual differences such as coping responses and social
support are thought to play a key role in post-trauma outcomes and PTG. Adversarial events
are usually experienced as traumatic if they are seismic enough to shatter world
assumptions and pre-existing schemas (Tedeschi & Calhoun, 2004). A period of rumination
generally follows, where attempts to reconcile world views with new trauma-related
information are made to accommodate it into existing knowledge. This does not imply that
PTG occurs in the absence of negative effects, as people exposed to adversity typically
report co-occurring negative symptoms including those of posttraumatic stress disorder
(PTSD). These negative symptoms appear to be part of the emotional struggle in which
growth can occur (Lancaster, Klein, Nadia, Szabo, & Mogerman, 2015). However, as a
generalised account of PTG development, the transformational model does not fully account
for individual differences in adjustment following adversity.

<hs>  Active, religious and spiritual coping styles</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although primarily focused on cognitive factors, the transformational model (Tedeschi &
Calhoun, 2004) attends to contextual factors that may predict PTG. Cognitive appraisals
can shape coping strategies that are employed to mitigate the most distressing aspects of
the adverse event. Separately, two meta-analyses of 84 and 103 PTG studies respectively
(Helgeson, Reynolds, & Tomich, 2006; Prati & Pietrantoni, 2009) revealed that active
coping strategies and the use of religious or spiritual coping were closely associated
with PTG, as people sought to find comfort and attempted to frame their experiences in a
positive light. It is thought these processes are driven by an intrinsic need to move
towards growthful outcomes and make sense of the experience (Joseph, Murphy, & Regel,
2012).

<hs>  PTSD symptoms</hs>
  ~~~~~~~~~~~~~

The period of processing adverse events is generally reflected by increased posttraumatic
stress symptoms, marked by intrusive thoughts and flashbacks of the event (Joseph et al.,
2012). Findings suggest PTSD cognitions display positive linear and curvilinear
relationships with PTG (Kleim & Ehlers, 2009; Powell, Rosner, Butollo, Tedeschi, &
Calhoun, 2003; Shakespeare-Finch & Lurie-Beck, 2014). Specifically, lower PTSD symptoms
may signify that the person is less affected by the adversarial event and therefore less
PTG is experienced. Moderate levels of PTSD symptoms suggest that the person's world has
been challenged in some way, yet they are able to engage in cognitive processing necessary
for growth to occur. Higher levels of PTSD symptoms are thought to overwhelm a person's
coping resources and they are more likely to succumb to negative aftereffects and
therefore experience minimal PTG (Joseph et al., 2012).

<hs>  Social support</hs>
  ~~~~~~~~~~~~~~

In addition to coping methods, the wider social-environmental context is implicated in the
transformational model (Tedeschi & Calhoun, 2004). In particular, social support has
emerged as a robust predictor of growth across numerous PTG studies (Linley & Joseph,
2004). The dynamics of interpersonal relationships provide emotional support that can
mediate adjustment outcomes (Ullman & Peter-Hagene, 2014) and offer new perspectives that
are crucial for PTG development (Tedeschi & Calhoun, 2004). The additional outlooks
provided by others aid deliberate rumination and the development of narratives that help
people to draw upon the beneficial aspects of the event (Tedeschi, 1999). It is during
this process of cognitive engagement that the foundations of PTG are laid, allowing the
individual to thrive.

<hs>  Age at time of serious event</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As well as the aforementioned psychosocial characteristics, early life adversity is also
thought to be a significant determinant of outcomes in adulthood. For many people, their
first experience of adversity occurs in childhood and can often shape conceptions of self-
identity (Sutherland & Bryant, 2005). Developmental adversity places the individual at
greater vulnerability to more negative effects such as PTSD in later life (Hagenaars,
Fisch, & van Minnen, 2011). However, people exposed to adversity in childhood could also
change as a result of their experiences in a positive way. At present, there are mixed
findings with regard to age at event experience and the degree of growth reported. Studies
have reported negative, positive or no relationships between age and PTG (Meyerson, Grant,
Carter, & Kilmer, 2011). While the transformational model (Tedeschi & Calhoun, 2004) does
not explain the role of temporal factors, such discrepancies may be due to differences in
PTG measurement, or the wide demographic range of populations sampled (Linley & Joseph,
2004; Powell et al., 2003; Shakespeare-Finch & Lurie-Beck, 2014). For example, perceived
event severity may vary between younger people who experience a novel adverse event
compared to older populations with more life experience (Sutherland & Bryant, 2005). Taken
together, age at event experience and its influence on PTG development is not fully
understood.

<hs>  Event intentionality and frequency of exposure to adversity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In addition to investigating the factors relating to growth, the type of event people have
been exposed to may influence the amount of PTG reported. Research has observed PTG in
approximately 30 to 100% of survivors of breast cancer, transport accidents, natural
disasters and those traumatised through bereavement (Linley & Joseph, 2004). The majority
of event types explored to date are largely representative of experiences that are not
intentionally perpetrated against people. The trauma literature distinguishes between such
acts of nature and intentional events where harm is deliberately inflicted upon another
person (Santiago et al., 2013). Intentional events have been associated with more adverse
outcomes and magnified PTSD symptoms compared to non-intentional acts of nature (Santiago
et al., 2013). While it has been suggested that intentional events may have profound
effects on PTG development in populations who experience them such as sexual abuse
survivors (Tedeschi, 1999), the direction of the effect is unclear as this has not
received sufficient empirical support to date. Alongside the type of adversity, the
frequency of exposure is thought to determine subsequent psychological adjustment.
Specifically, the experience of multiple adversity is thought to intensify PTSD reactions
compared to isolated events (Green et al., 2000). However, no studies have explored the
influence of frequency of exposure to adversity on PTG development. As objective
characteristics of the event, both the type and frequency of adversarial exposure are not
represented in the transformational model which places greater emphasis on subjective
interpretations of the event (Tedeschi & Calhoun, 2004). At present, there are no
empirical investigations of this assumption and so the way in which intentional and
multiple events are related to PTG, if at all, is not clear. Therefore, research that
explores PTG in samples of people exposed to a diverse range of multiple intentional and
non-intentional adverse experiences is warranted.

        <hss>Students</hss>

        The literature has considered growth from adversity in a wide range of samples.
        This has included survivors of cancer, transport accidents and military combat
        (Barakat, Alderfer, & Kazak, 2006; Linley & Joseph, 2004). Such research tends to
        use homogenous samples of people exposed to a specific type of adversity. As a
        consequence, this confines the study of PTG to narrow samples of survivors and
        excludes the potential range of intentional and non-intentional adversity that
        people may experience in their lifetime. One sample where a range of adversarial
        events could be considered is university students. Students form samples in many
        existing PTG studies (e.g. DeRoma et al., 2003; O'Connor, Cobb, & O'Connor, 2003;
        Prati & Pietrantoni, 2009) and there are benefits of doing so. They are a
        generally accessible population who have been potentially exposed to a range of
        adverse events rather than one specific stressor. This enables the exploration of
        both intentional and non-intentional adversity types. Furthermore, it could be
        argued that university students represent high functioning individuals who,
        despite previous adversity, are able to lead lives relatively free of the
        impairments that adversity can generate (Taku et al., 2007). For example, they are
        able to study academically at a high level. These may reflect a proportion of the
        trauma population who exhibit resiliency traits prior to the event, or even growth
        after the event that buffers against pathology such as PTSD (Bensimon, 2012). As
        such, university students are a high functioning population who provide a
        representative sample of people potentially exposed to a range of intentional and
        non-intentional adverse events in order to explore predictors of PTG.

        <hss>Survivors of violent crime</hss>

        In contrast to student samples, survivors of violent crime may represent a
        population who experience more frequent adversity of a deliberate nature. Some
        survivors of serious criminal acts are subject to a disproportionate number of
        intentional events in comparison to the non-traumatised population (Kunst, Winkel,
        & Bogaerts, 2010; Tedeschi, 1999). In particular, survivors of intimate partner
        violence and sexual assault are likely to experience sequential acts of
        victimisation in the context of interpersonal relationships (Felson, Ackerman, &
        Gallagher, 2005). Collectively, exposure to intentional and repeat events place
        people at great vulnerability to substance dependency, depression and elevated
        PTSD symptoms (Ruback, Clark, & Warner, 2014; Scarpa, Haden, & Hurley, 2006), over
        and above the influence of natural occurrences (Santiago et al., 2013). These
        additional difficulties impair every day occupational and social functioning to a
        great degree in violent crime survivors, where chronic adversity can negatively
        influence perceptions of available support and thus magnify distress (Hanson,
        Sawyer, Begle, & Hubel, 2010). While literature has increasingly explored the
        impact of multiple and intentional types of adversity on the maintenance of PTSD
        symptoms (e.g. Graham-Kevan et al., 2015), less is known about their role in
        promoting growth. Furthermore, there are no PTG frameworks accounting for multiple
        exposures. Research has explored PTG among samples with physical assault as the
        index adverse event (e.g. Kleim & Ehlers, 2009); however, such studies have not
        taken into account the diverse range of intentional and non-intentional
        adversarial experiences that survivors of crime often face. This could lead to
        differences in the processing of adverse events and the factors that contribute
        towards crime survivor's experiences of PTG.

        <hss>Trauma workers</hss>

        The study of PTG also has particular relevance to those who work with or support
        people who are exposed to adversity in their occupation (hereafter termed ‘trauma
        workers’). Trauma workers represent another proportion of the population who
        routinely are exposed to an elevated degree of adverse events (Cohen & Collens,
        2013). However, unlike survivors of violent crime, potential traumatisation and
        PTG can occur indirectly through interactions with people who are also exposed to
        serious adversity (Cohen & Collens, 2013). While there are currently no
        explanatory models of vicarious or secondary PTG, recent studies have increasingly
        drawn attention to PTG emerging in this manner (Brockhouse, Msetfi, Cohen, &
        Joseph, 2011; Samios, Rodzik, & Abel, 2012). However, there is a paucity of
        research in relation to trauma worker's own direct experiences of adversity. This
        is surprising, as altruistic tendencies observed in trauma workers and similar
        professions are thought to stem from the experience of adversity in their own
        personal lives (Staub & Vollhardt, 2008). According to the transformational model
        of PTG (Tedeschi & Calhoun, 2004), the emotional salience and proximity to
        personal adverse events can trigger cognitive processing necessary for PTG, more
        so than adversity experienced in occupational contexts. Both personal and work-
        related adversity has been found to predict PTG in firefighters (Armstrong,
        Shakespeare-Finch, & Shochet, 2014). Despite repeat exposure to a range of adverse
        events at work and their own personal history of adversity, trauma workers are
        relatively high functioning by sustaining employment within emotionally demanding
        professions (Cohen & Collens, 2013). This may reflect trait resiliency or the
        buffering nature of PTG which allows trauma workers to reinterpret multiple
        adversity in a less threatening way (Bensimon, 2012; Samios et al., 2012).
        Therefore, the current research will focus on personal adversity and predictors of
        PTG in a high functioning sample of trauma workers with repeat exposure to
        indirect adversity.

<hs>  The current research</hs>
  ~~~~~~~~~~~~~~~~~~~~

Based on the existing literature, this research explored the contributions of event
intentionality, frequency of adversity types, age at which the most serious event
occurred, spirituality/religiousness, active coping, PTSD symptomology and social support
as potential predictors of PTG. These predictors would be explored in three samples who
represent survivors exposed to different types or frequencies of adversity. Study 1
explored the role of event intentionality, frequency of adversity types, age at serious
event, spirituality/religiousness, active coping, PTSD symptomology and social support
variables in a student sample. The student sample represents individuals with experience
of a broad range of adversity types yet are able to study academically at a high level.
Study 2 applied the same predictors to a sample of survivors of violent criminal
victimisation who experience frequent intentional adversity that may negatively impact
upon psychological functioning. Finally, Study 3 extended the findings of studies 1 and 2
by exploring the predictors of PTG in a sample of trauma workers who experience not only
their own personal adversity, but are frequently exposed to adverse events indirectly yet
remain able to continue in demanding roles. Taken together, this approach would allow the
identification of individual differences and similarities in the development of PTG across
a diverse range of samples that would not otherwise be revealed in single study designs.

<h>STUDY 1</h>
-------

In Study 1, it was expected that spirituality/religiousness, active coping, PTSD
symptomology and social support would positively predict growth based on existing PTG
literature. Given relationships between objective characteristics and posttraumatic stress
symptoms, it was also expected that event intentionality, frequency of adversity types and
the age at which the serious event occurred would be related to PTG.

        <hss>Participants and procedure</hss>

        One hundred and one students with prior exposure to adversity took part in the
        study. Table 1 presents demographic information for the sample. Participants were
        recruited via university posters and online postings on message boards and student
        forums. Questionnaires were accessed through a link provided on the websites where
        the potential participants could access information about the study and their
        rights as participants. Upon providing informed consent, participants completed
        the questionnaires, were debriefed and provided details of support services. They
        had the option to enter a prize draw for a £50 shopping voucher as compensation
        for their time. The study was approved by the university ethics committee and
        adhered to British Psychological Society ethical guidelines.

        <hss>Measures</hss>

        Demographic information including age, gender, sexuality, ethnicity and religion
        was collected. Traumatic Experiences Questionnaire (TEQ; Foa, Cashman, Jaycox, &
        Perry, 1997). The TEQ is a self-report measure of adverse experiences and includes
        12 types of event such as exposure to accidents, natural disasters, sexual
        assaults and serious illness. In this study, the scale was adapted from Foa et
        al.'s (1997) original version to include two further items of parental neglect and
        occupational secondary traumas which account for other potentially traumatic
        events (Cohen & Collens, 2013; Hagenaars et al., 2011). The participant records
        the frequency of each event to the best of their memory. Intentional events were
        considered to involve directly perpetrated physical or sexual violence. Two
        additional questions invite the participant to record the item of the event they
        perceived to be most severe and the age this first occurred. The measure has been
        validated in samples of individuals exposed to adversarial events and demonstrates
        reasonable internal consistency (Foa et al., 1997), which was replicated in this
        study (α = .68). Beliefs and Values Scale (BVS; King et al., 2006). The BVS is a
        measure of religious and spiritual beliefs, where respondents are asked to
        indicate their agreement to 20 statements using a scale from 0 (strongly disagree)
        to 4 (strongly agree). It has been validated as a reliable measure in large and
        diverse samples (King et al., 2006). Example items include, ‘Although I cannot
        always understand, I believe everything happens for a reason’ and ‘I believe in a
        personal God’. An overall score is produced, with higher scores indicative of
        greater religiosity and spirituality. In the current study, Cronbach's α = .96.
        Brief COPE (Carver, 1997). The Brief COPE is a 28-item questionnaire assessing 14
        coping styles on a four point scale from 0 (I haven't been doing this at all) to 3
        (I′ve been doing this a lot). Participants rate which coping styles they employ;
        example items include, ‘I've been taking action to make the situation better’
        (active coping), with higher scores representing greater use of the specific
        coping style. The Brief COPE has demonstrated good internal reliability and can be
        used as a short measure for coping in specific situations of interest (Carver,
        1997). As with previous studies (e.g. Thornton & Perez, 2006), the active coping
        scale was of particular interest due to links between such coping styles and new
        perspectives in PTG development (Tedeschi & Calhoun, 2004). These two subscales
        were used in subsequent analysis. Reliability scores for the active coping scale
        was .78. PTSD-8 (Hansen et al., 2010). The PTSD-8 is a measure of posttraumatic
        stress symptoms, where respondents rate their agreement with eight statements on a
        four point scale from ‘not at all’ to ‘most of the time’. Participants were asked
        to identify their most serious event and indicate the symptoms they have
        experienced in the past 2 weeks. There are three subscales of avoidance, intrusion
        and hyperarousal which are represented with items such as ‘Recurrent thoughts or
        memories of the event’ and ‘Avoiding activities that remind you of the event’.
        Participants with a score of three or above on each subscale may display PTSD
        traits. It has been validated in samples of rape survivors, whiplash patients and
        survivors of disasters (Hansen et al., 2010). In the study, the overall scale was
        used with Cronbach's α = .88. Two-Way Social Support Scale (2-Way SSS;
        Shakespeare-Finch & Obst, 2011). The 2-Way SSS is a 21-item measure of giving and
        receiving emotional and instrumental social support on a scale from 0 (not at all)
        to 5 (always). There are four subscales of receiving emotional support, giving
        emotional support, receiving instrumental support and giving instrumental support.
        Example items include, ‘There is someone in my life I can get emotional support
        from’ and ‘There is someone who will help me fulfil my responsibilities when I am
        unable’. Higher scores endorse greater support. The scale has been validated in
        two community samples (Shakespeare-Finch & Obst, 2011) and the overall score for
        the measure was used in this study, demonstrating excellent reliability (α = .93).
        Posttraumatic Growth Inventory — Short Form (PTGI-SF; Cann et al., 2010). The
        PTGI-SF is a measure of growth, on a six point scale from 0 (no change as a result
        of crises) to 5 (very great change). Participants are asked to rate what extent
        they have changed since their stressful life event with 10 items such as, ‘I
        changed my priorities about what is important in life’ and ‘I discovered that I′m
        stronger than I thought I was’. It has been validated for use in samples including
        survivors of domestic abuse, bereaved persons and those with complex health needs,
        demonstrating similar reliability to that of the original 21-item version of the
        PTGI, whilst having the advantage of brevity (Cann et al., 2010). A total score is
        obtained, with higher scores reflecting greater perceived change. The PTGI-SF
        demonstrated high internal consistency in the current study (α = .89).

<hs>  Results</hs>
  ~~~~~~~

The prevalence of exposure to adverse events for participants is presented in Table 1. Of
the sample, 83.2% experienced more than one adverse event type, with 68.3% experiencing
two to five event types and 15% experiencing six to ten separate event types. In addition,
30.7% reported bereavement as the most serious event experienced among the range of
adversity types. Means and standard deviations for the psychosocial measures are presented
in Table 2. Pearson correlations revealed that age at serious event (r = .37, p < .001),
spirituality/religiousness (r = .40, p < .001), active coping (r = .46, p < .001), PTSD
symptomology (r = .28, p = .005) and social support (r = .35, p < .001) were all
positively associated with reported PTG. Event intentionality and frequency of event types
were not related to PTG. Multiple regression analysis was conducted to assess the
contributions of the seven predictors towards PTG in the student sample. Using the
simultaneous method, a significant model emerged, F (7, 93) = 10.27, p < .001; adjusted R2
= .39 in which age at serious event, spirituality/religiousness, active coping, PTSD
symptoms and social support emerged as significant predictors of PTG. Event intentionality
and frequency of event types did not predict PTG. The results are presented in Table 3.
Collinearity diagnostics revealed that no two variables were highly correlated (Tolerance
for all variables > .66; VIF for all variables < 1.52).

<hs>  Discussion</hs>
  ~~~~~~~~~~

Study 1 showed expected relationships between PTG and a number of psychosocial variables
among students. Specifically, spirituality/religiousness, active coping, PTSD symptomology
and social support were positively related to PTG development. In partial support of the
hypothesis, Study 1 indicated that these variables as well as age at the time of the
serious event were also positive predictors of PTG. In particular, active coping methods,
spirituality/religiousness and social support demonstrated stronger relationships with
growth compared to the other variables. Contrary to the hypothesis, both event
intentionality and frequency of event types were neither associated nor predictive of
growth. Taken together, the results suggest that psychosocial factors are more closely
related to adjustment of adversity compared to objective characteristics of the serious
event (Tedeschi & Calhoun, 2004). Study 1 explored predictors of PTG in a high functioning
sample exposed to a broad range of adversity. However, this does not fully account for the
experiences of people exposed to particularly frequent and intentional adverse events
above the normative population. One example of a population with more extreme and
intentional adversity is survivors of violent crime, whose experiences can lead to poor
social and occupational functioning (Hanson et al., 2010; Ruback et al., 2014). Therefore,
Study 2 assessed the efficacy of the predictor variables used in Study 1 in relation to a
sample comprised of survivors of violent crime. The purpose was to ascertain the extent to
which the degree and type of adversity experienced in this sample mediated the influence
of the psychosocial predictors of PTG.

<h>STUDY 2</h>
-------

In Study 2, it was hypothesised that the age the most serious event occurred,
spirituality/religiousness, active coping, PTSD symptomology and social support would
contribute towards PTG, based on the findings from Study 1. Given that survivors of
violent crime may experience significant adversity that may serve as a catalyst for
growth, it was expected that event intentionality and frequency of event types would be
associated with PTG.

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Seventy-one survivors of crime volunteered to take part in this study. Table 1 presents
demographic information for the sample. Participants were recruited using messages
advertised on websites provided by three victim services, which support female and male
survivors of domestic violence, child sexual abuse and sexual assault respectively. Two
participants were also sampled from a concurrent study using survivors of violent crime
(Graham-Kevan et al., 2015). Procedures used to collect data were the same as outlined in
Study 1.

<hs>  Measures</hs>
  ~~~~~~~~

Participants self-reported demographic information including age, gender, sexuality and
ethnicity and religious beliefs. All measures in this study were the same as those
described in Study 1. Trauma history was explored using the TEQ (Foa et al., 1997).
Internal reliability for this scale in this sample as measured by Cronbach's alpha was α =
.73. The degree of spirituality/religiousness was assessed using the BVS measure (King et
al., 2006) and in this study, Cronbach's α = .96. The Brief COPE (Carver, 1997) assessed
active coping styles with a Cronbach's alpha of .61. PTSD symptomology was assessed using
the PTSD-8 (Hansen et al., 2010) and the reliability of the overall scale in this study
was excellent (α = .91). The 2-Way SSS measure (Shakespeare-Finch & Obst, 2011) was
employed to establish perceptions of social support. As with Study 1, the overall score
for the measure was used in this study and the internal consistency of the items was high
(α = .95). Finally, the brief version of the PTGI measure (Cann et al., 2010) was employed
to explore reported PTG. The PTGI-SF demonstrated excellent reliability in this study (α =
.91).

<hs>  Results</hs>
  ~~~~~~~

The prevalence of exposure to adverse events for participants is presented in Table 1. Of
the participants, 94.4% experienced more than one adverse event type, with 56.4%
experiencing two to five event types and 32.4% experiencing six to ten event types.
Notably, around three-quarters of participants experienced sexual abuse (73.2%) and
serious physical attacks or threats (76.1%). Nearly a quarter (23.9%) of the sample
indicated that sexual abuse was the most serious adverse event they had experienced. Means
and standard deviations for the psychological measures are presented in Table 2. Pearson
correlations revealed that age at serious event (r = .25, p = .033),
spirituality/religiousness (r = .50, p < .001), active coping (r = .37, p = .002) and
social support (r = .40, p = .001) were all positively associated with reported PTG. PTSD
symptomology, event intentionality and frequency of event types were not related to PTG.
Multiple regression analysis assessed the seven variables as potential predictors towards
PTG in the sample. Using the simultaneous method, a significant model emerged, F (7, 63) =
7.12, p < .001; adjusted R2 = .38. Table 3 presents the results of the regression in which
spirituality/religiousness, active coping and social support emerged as significant
predictors. There was no evidence of colinearity among the variables (Tolerance for all
variables > .68; VIF for all variables < 1.46).

<hs>  Discussion</hs>
  ~~~~~~~~~~

In line with Study 1, the results suggest that spirituality/religiousness, active coping
and social support were all positive predictors of growth among survivors of violent
crime. As in Study 1, objective characteristics of event intentionality and frequency of
event types were unrelated to PTG development in the sample. Contrary to the findings of
Study 1 and the Study 2 hypothesis, the age at which the serious event occurred and PTSD
symptoms did not predict PTG. This highlights that although the students and crime
survivors share some similar predictors of PTG and are able to report positive changes
despite previous adversity, the populations are not identical. While Study 2 considered
predictors of PTG among people exposed to frequent and often intentional adversity, little
is known about cumulative adversity in samples that appear to function at a higher level.
Trauma workers are not only exposed to adverse events through engagement with clients in
occupational settings (Brockhouse et al., 2011; Cohen & Collens, 2013), but themselves
experience adversity in their personal lives. There are few studies of predictors of PTG
in trauma workers in relation to their own personal adversity (Armstrong et al., 2014). It
is possible that exposure to repeat indirect adversity may buffer against negative
symptoms from their own adversity (Samios et al., 2012). Therefore, the purpose of Study 3
is to investigate predictors of PTG in a sample of trauma workers in the aftermath of
personal adverse events.

<h>STUDY 3</h>
-------

As with the student sample in Study 1, it was predicted that the age at which the serious
event occurred, spirituality/religiousness, active coping and social support would
positively predict PTG in trauma workers. However, as their job role may encourage the
development of coping techniques such as buffering from negative symptoms, it may be that
event intentionality, frequency of event types and PTSD symptoms would be unrelated to
PTG.

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Ninety-six trauma workers volunteered to take part in this study. Participants were
recruited using professional forums and snowball methods. The final sample consisted of 21
counsellors, 11 mental health nurses, 29 psychotherapists, 17 psychologists, three
psychiatrists and 15 social workers or support workers. Table 1 presents demographic
information for the sample. Procedures used to collect data were the same as outlined in
Study 1.

<hs>  Measures</hs>
  ~~~~~~~~

As with the previous two studies, participants completed demographic information including
age, gender, sexuality and ethnicity and religious beliefs. All measures in this study
were the same as those described in Study 1. The TEQ (Foa et al., 1997) exploring trauma
history demonstrated a Cronbach's alpha of .69. The BVS (King et al., 2006) measured
perceptions of spirituality/religiousness and was found to have excellent internal
consistency (α = .96). As in the previous studies, the Brief COPE (Carver, 1997) was
employed to assess active coping (α = .77) which demonstrated acceptable reliability. The
PTSD-8 (Hansen et al., 2010) captured PTSD symptomology and the reliability of the overall
scale was excellent (α = .90). Social support was measured using the 2-Way SSS
(Shakespeare-Finch & Obst, 2011) and the internal consistency of the items was excellent
(α = .94). PTG was again explored using the PTGI-SF (Cann et al., 2010) and reliability
for the scale in this study was high (α = .92).

<hs>  Results</hs>
  ~~~~~~~

The prevalence of exposure to adverse events is presented in Table 1. 86.5% of the sample
experienced more than one adverse event type, with 64.7% experiencing two to five event
types and 20.8% experiencing six to ten event types. Like Study 1, most of the
participants (26.0%) rated bereavement of a family member or close friend as their most
serious adverse experience. Means and standard deviations for the psychological measures
are presented in Table 2. Pearson's correlations showed that spirituality/religiousness (r
= .37, p < .001), active coping (r = .35, p = .001), PTSD symptomology (r = .27, p = .009)
and social support (r = .32, p = .002) were positively associated with overall PTG. The
age the serious event occurred, event intentionality and frequency of event types were
unrelated to PTG. A multiple regression analysis using the simultaneous method assessed
the seven variables as potential predictors towards PTG among participants and produced a
significant model, F (7, 88) = 7.11, p < .001; adjusted R2 = .31.
Spirituality/religiousness, active coping and social support emerged as the three
significant predictors of PTG and are presented in Table 3. As with Study 1 and Study 2,
colinearity was not identified in this sample (Tolerance for all variables > .70; VIF for
all variables < 1.44).

<hs>  Discussion</hs>
  ~~~~~~~~~~

This study was the first to identify predictors of PTG among a sample of trauma workers,
building on similar work in firefighters (Armstrong et al., 2014). As with studies 1 and
2, the findings provided support for the hypothesis that spirituality/religiousness,
active coping and social support were necessary for PTG to occur in trauma workers.
Neither event intentionality nor frequency of event types was linked to growth, consistent
with the hypothesis and the prior two studies on students and survivors of violent crime.
As with the crime survivors in Study 2, age at serious event did not predict PTG, which
was contrary to the students in Study 1 and the hypothesis. Collectively, the results
support the robustness of spirituality/religiousness, active coping and social support
factors as predictors of growth. Meanwhile, objective characteristics and PTSD symptoms
appear to vary among different populations of people exposed to adversity and do not
influence PTG development.

<h>GENERAL DISCUSSION</h>
------------------

In the research presented, the predictive ability of event intentionality, frequency of
event types, age at serious event, spirituality/religiosity, active coping, PTSD symptoms
and social support on levels of PTG was explored. These factors were assessed in three
populations of survivors exposed to different types or frequencies of adversity where
factors salient for PTG development may vary. Collectively, the predictive factors
explained a significant proportion (between 30 and 45%) of the variance in PTG scores
across the three studies. An encouraging finding was that regardless of life trajectory,
participants in all three studies reported similar levels of PTG. This is perhaps not
surprising given that PTG has been observed across a broad range of adversarial exposures
(Linley & Joseph, 2004). Notwithstanding the apparent universality of PTG, this series of
studies for the first time revealed some notable differences and similarities among the
predictive factors that were salient for growth to occur in three populations studied.

<hs>  Active, religious or spiritual coping and PTG</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Across all three populations, active coping and spiritual or religious coping strategies
were the most robust predictors of PTG. Earlier reviews of the literature report large
effect sizes for coping methods on PTG development overall (Prati & Pietrantoni, 2009).
This is perhaps not surprising given that active and religious or spiritual coping methods
may reflect attempts to understand significant challenges brought about by adverse events
(Tedeschi & Calhoun, 2004). Importantly, the findings indicate that regardless of life
trajectory, people exposed to different types of adversity who employ active coping
strategies perceived more PTG. The presence and degree of spirituality/religiousness was
consistently associated with PTG in the three samples. This suggests that the use of
existential beliefs can be found in the three populations investigated. Literature on the
benefits of spiritual and religious coping in PTG development is widely available (e.g.
Helgeson et al., 2006; O'Connor et al., 2003; Prati & Pietrantoni, 2009). In a paradoxical
fashion, adversarial events not only shatter assumptions but can lead to greater
engagement with existential, philosophical or moral questions that represent growth
(Tedeschi & Calhoun, 2004). It therefore appears that such strategies can enhance the
sense of meaning in life or bring about a new engagement with religion and spirituality
for many people. However, not all participants recorded a religious affiliation and so it
would be advantageous for future studies to distinguish between types of religious and
spiritual beliefs and their individual contributions towards PTG.

<hs>  PTSD symptoms and PTG</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Relationships emerged between PTSD and PTG in Study 1 only. The mixed findings across the
three populations may be partly explained by psychosocial resources that survivors may
draw upon in order to mitigate negative effects. Students with less life experience of
adversity may attribute greater significance to early or novel experiences (Sutherland &
Bryant, 2005). This may exacerbate symptoms as processing of the event occurs (Tedeschi &
Calhoun, 2004), but not so much as to overwhelm the survivor, allowing growth from the
event. The lack of relationship between PTSD and PTG among the survivors of violent crime
appears contrary to assertions that growth and distress co-exist (Lancaster et al., 2015).
However, this may be explained by adaptive attempts to normalise or dissociate from such
experiences to minimise distress (Hagenaars et al., 2011). It is this numbness to
emotional experience that may account for the lack of PTSD symptoms among the crime
survivors. In addition, PTSD symptoms may be of a severity as to overwhelm the crime
survivors, thus inhibiting growth (Shakespeare-Finch & Lurie-Beck, 2014). Furthermore,
trauma workers are in a unique position to experience cumulative stressors through their
roles (Cohen & Collens, 2013). It is possible that this exposure may buffer against PTSD
symptoms and allow growth to occur (Samios et al., 2012), as reflected by lower PTSD
scores for this group. Collectively, the present findings suggest that PTSD symptoms are
particularly susceptible to the wider environmental and psychological contexts in which
the samples function.

<hs>  Social support and PTG</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Social support also emerged as one of the most robust predictors of growth in all three
studies. This reinforces earlier findings on the benefits of social support as a potential
buffer against stressful events (Linley & Joseph, 2004). It has been suggested that a
recognition of one's own vulnerability as a result of exposure to adversity can lead to
increased sensitivity towards other people and the revision of schemas (Tedeschi &
Calhoun, 2004). In addition, enriched social networks can bring out opportunities for
disclosure that in turn promote positive outcomes (Ullman & Peter-Hagene, 2014).
Importantly, social support appears to permeate across all types of adversity and
populations, which highlights the significant role that the accessibility and maintenance
of supportive networks play in post-event adjustment.

<hs>  Age at serious event and PTG</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

An additional aspect of these series of studies was the inclusion of age at the time the
serious event happened. Findings indicated that this factor was relevant to PTG in Study 1
only. While previous reviews have reported ambiguous relationships between age and PTG
development (Helgeson et al., 2006; Meyerson et al., 2011), it has been suggested that the
nature of the participants sampled may account for such discrepancies (Shakespeare-Finch &
Lurie-Beck, 2014). The student sample was younger compared to the violent crime survivors
and trauma workers. Younger samples are more likely to be confronted with novel adverse
events in childhood and adolescence, which can represent significant changes in a person's
life (Sutherland & Bryant, 2005). The age at which the event occurred may be less salient
for older samples that are more able to process both the positive and negative aspects of
the experience (Barakat et al., 2006).

<hs>  Event intentionality, frequency of event types and PTG</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This was the first PTG study to determine that event intentionality and frequency of
historical event types were unrelated to PTG development. The findings confirm the view
that objective characteristics of the event are unrelated to growth (Joseph et al., 2012;
Tedeschi & Calhoun, 2004), which had previously received no empirical support. It had also
been speculated that intentional and frequent acts may in some way influence growth
compared to isolated events (Tedeschi, 1999), given that chronic adversity is associated
with more severe pathology (Green et al., 2000; Hagenaars et al., 2011; Santiago et al.,
2013). However, this suggestion is not supported by the current findings. There is some
evidence to suggest that frequent exposure to adversity can buffer against perceptions of
severity by allowing people to prepare for subsequent events, which may constitute growth
in itself (Armstrong et al., 2014; Kunst et al., 2010; Samios et al., 2012). In sum, the
findings provide new insight into the role of event type and frequency on PTG development,
where growth can occur regardless of prior exposure to adversity. This is an encouraging
development for psychological interventions that could target the psychosocial factors
most closely associated with growth.

<hs>  Implications, limitations and future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This research has important theoretical implications for understanding PTG among different
samples of the general population who are exposed to adversity. The present studies
contribute to recent literature that calls for an exploration of individual differences
and commonalties in predictors of PTG (Lancaster et al., 2015), which are not duly
accounted for in existing PTG models. The findings suggest that generalised models of PTG
do not reflect the nuances of positive adjustment after adversity. Furthermore, the
research draws attention to the role of cumulative events, which did not appear to
influence PTG development although may buffer against posttraumatic stress symptoms.
Currently, the transformational model of PTG (Tedeschi & Calhoun, 2004) only considers
growth and processing in the aftermath of single, isolated incidents, which do not
represent people who are exposed to multiple adverse events across the lifespan. Future
research is encouraged to adopt a more holistic view of adversarial experiences and
investigate PTG development in survivors of multiple adversity. Encouragingly, the present
findings provide the first evidence that prior adversarial history does not affect the
ability of survivors to report positive changes (Joseph et al., 2012; Tedeschi & Calhoun,
2004). This differs from the posttraumatic stress literature where intentional and
frequent events are often associated with exacerbated negative symptoms (e.g. Green et
al., 2000; Santiago et al., 2013) and suggests that the mechanisms that underpin both PTG
and posttraumatic stress operate differently. Indeed the relationship between PTG and
posttraumatic stress remains ambiguous (Lancaster et al., 2015; Shakespeare-Finch & Lurie-
Beck, 2014) and future research would be directed to explore these relationships further.
In respect of practical implications, efforts could focus on enhancing resiliency factors
that predict PTG across a variety of populations. The present findings implicate active
coping, spirituality/religiousness and social support factors which may promote growth. In
the case of spirituality/religiousness, these findings do not imply that belief systems
should be imposed or altered by clinicians; rather, these beliefs appear to be beneficial
for PTG development. When targeted in psychological interventions, coping and social
support factors could promote a better quality of life as a result of improved social and
occupational functioning (Hanson et al., 2010) and allow people to be in a better position
to consider the positive as well as negative aspects of their adverse experiences. There
are strengths and limitations to research of this kind which should be noted. The study
included a diverse range of adversarial experiences within each sample ranging from common
normative life stressors such as bereavement and illness, to more seismic life-changing
events. However, the modest sample sizes prevented the exploration of additional factors
that differ among the samples. Second, data relied on self-reports which are advantageous
in that participants are likely to identify with the questions and are more motivated to
consider their own personalities rather than those of others (Paulhus & Vazire, 2007).
However, retrospective accounts of adversarial history and associated adjustment may have
been influenced by tendencies to over or under-report information.

<h>CONCLUSION</h>
----------

Overall, the results across the three populations broadly support the salience of
subjective interpretations in adjustment from adversity, in contrast to objective
characteristics of the event, such as type and frequency. The studies provide greater
understanding of the dynamic nature of psychosocial factors. In particular, coping and
social support variables remain robust predictors of PTG regardless of population or prior
experiences of adversity. However, the age at serious event and PTSD symptoms appear to
display more nuanced relationships with PTG which are not reflected within existing PTG
frameworks. Therefore, coping and social support factors could be the focus of
interventions to not only reduce PTSD symptoms, but promote opportunities for PTG
development.


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<ART>Predicting reading ability in teenagers who are deaf or hard of hearing: A longitudinal analysis of language and reading
================================================================================

Authors: Sarah Worsfold, Merle Mahon, Hannah Pimperton, Jim Stevenson, Colin Kennedy
DOI: 10.1016/j.ridd.2018.04.007
Year: 2018  |  Pages: 49-59
ASJC codes: 3203, 3204
Keywords: Expressive language, Language comprehension, Longitudinal design, Permanent childhood hearing loss, Reading accuracy, Reading comprehension

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Deaf and hard of hearing (D/HH) children and young people are known to show group-level deficits in spoken language and reading abilities relative to their hearing peers. However, there is little evidence on the longitudinal predictive relationships between language and reading in this population. Aims: To determine the extent to which differences in spoken language ability in childhood predict reading ability in D/HH adolescents. Methods: and procedures: Participants were drawn from a population-based cohort study and comprised 53 D/HH teenagers, who used spoken language, and a comparison group of 38 normally hearing teenagers. All had completed standardised measures of spoken language (expression and comprehension) and reading (accuracy and comprehension) at 6–10 and 13–19 years of age. Outcomes: and results: Forced entry stepwise regression showed that, after taking reading ability at age 8 years into account, language scores at age 8 years did not add significantly to the prediction of Reading Accuracy z-scores at age 17 years (change in R2 = 0.01, p =.459) but did make a significant contribution to the prediction of Reading Comprehension z-scores at age 17 years (change in R2 = 0.17, p <.001). Conclusions: and implications: In D/HH individuals who are spoken language users, expressive and receptive language skills in middle childhood predict reading comprehension ability in adolescence. Continued intervention to support language development beyond primary school has the potential to benefit reading comprehension and hence educational access for D/HH adolescents.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPER ADDS?</h>
---------------------

The difficulties D/HH children have in acquiring reading skills have been repeatedly
demonstrated but longitudinal studies of D/HH children identifying aspects of underlying
language skills that contribute to variation in reading skills are rare. The present study
examines the stability of reading skills from middle childhood to adolescence in D/HH
individuals and shows moderate stability in Reading Comprehension and a high level of
stability in Reading Accuracy scores. It also shows that variation in the language ability
of D/HH children in middle childhood is predictive of their Reading Comprehension in late
adolescence. This predictive relationship is over and above the continuity in Reading
Comprehension between childhood and late adolescence. The same was not found for Reading
Accuracy; language ability in middle childhood was not a significant predictor of
adolescent word reading skills. Within the D/HH group, differences in the relationship
between severity of hearing loss and reading ability in late adolescence were accounted
for by differences in language ability. The results of this study contribute to the case
for continued targeted intervention on language skills for D/HH individuals beyond primary
school. Maximising their language ability, and consequently their ability to use reading
to access learning, is likely to enhance their educational attainment and subsequent life
chances

<h>INTRODUCTION</h>
------------

Despite recent technological improvements, such as digital hearing aids and cochlear
implants, and earlier diagnosis and management of babies born deaf or hard of hearing
(D/HH), reading ability in D/HH children and young people continues to lag behind that of
their hearing peers (Wauters, van Bon, & Tellings, 2006; Moeller, Tomblin, Yoshinaga-
Itano, Connor, & Jerger, 2007; Harris & Terlektsi, 2011; Qi & Mitchell, 2011; Pimperton et
al., 2016; Harris, Terlektsi, & Kyle, 2017a). Moreover, with increasing age a widening gap
in reading achievement between D/HH and hearing children has been observed (Blair,
Peterson, & Viehwg, 1985; Marschark & Harris, 1996; Kyle & Harris, 2010, 2011). As
children get older, reading takes on an increasingly important role in enabling them to
access the curriculum; they move from ‘learning to read’ to ‘reading to learn’. Thus the
reading deficits shown by the D/HH population are likely to have an increasingly
significant impact on their educational attainment and subsequent employment
opportunities. The continuing importance of reading ability and educational attainment for
the later occupational status of D/HH individuals in adulthood has been shown by Walter
and Dirmyer (2013). Despite group-level deficits in their reading ability, D/HH children
and young people show substantial individual variation in reading skills, with some
reading at an age-appropriate level (Kyle & Harris, 2006, 2010Kyle and Harris, 2010;
Harris and Terlektsi, 2011; Pimperton et al., 2016). The question of what drives this
variation is an important one because identifying these drivers may raise potential
avenues for intervention to support reading development in this group. In hearing
children, the causal contribution of underlying language abilities to reading development
has been repeatedly demonstrated through good quality longitudinal and intervention
studies (see Hulme & Snowling, 2014, for review). Phonological language skills (e.g.
phonological awareness, letter-sound knowledge) appear to be most important for reading
accuracy (i.e. decoding written words into their phonological form) (Muter, Hulme,
Snowling, & Stevenson, 2004; National Institute for Literacy, 2008; Bowyer-Crane et al.,
2008; Caravolas et al., 2012) whereas non-phonological broader oral language skills (e.g.
vocabulary, grammatical knowledge, morphological skills) appear to be most important for
reading comprehension (i.e. understanding the meaning of what is read) (Nation, Cocksey,
Taylor, & Bishop, 2010; Clarke, Snowling, Truelove, & Hulme, 2010; Fricke, Bowyer-Crane,
Haley, Hulme, & Snowling, 2013). The phonological and non-phonological language skills
identified as playing a causal role in reading development in hearing children are all
skills which D/HH children find difficult to acquire and in which they show deficits
relative to the skills of hearing peers (Moeller et al., 2007; Musselman, 2000; Wake,
Hughes, Poulakis, Collins, & Rickards, 2004). Taken together this suggests that variation
in reading skills of D/HH children may be driven by variation in these underlying language
skills. Consistent with this, factors related to audiological experience, such as severity
of hearing loss, age at identification and age at cochlear implantation, that influence
language development in D/HH children, have also been found to relate to their reading
development (Moeller et al., 2007; Archbold et al., 2008; McCann et al., 2009). The
findings outlined above imply a similar role for language skills in causally driving the
development of reading skills in D/HH children, as in hearing children. However, there is
a dearth of good quality longitudinal and intervention studies to test whether, and if so
which, language skills play a causal role in the reading development of D/HH children. The
most extensive set of studies of the role of language in reading for D/HH individuals is
on phonological coding and awareness (PCA). Mayberry, del Giudice, and Lieberman (2011)
identified 25 studies that had examined PCA abilities and their relationship with reading
abilities in deaf children and adults. The assessment of reading proficiency was based on
some studies that measured reading comprehension and others reading accuracy. They
estimated that 11% of the variance in reading proficiency was explained by PCA, similar to
the 12% of variance that was thus explained in a meta-analysis of studies with hearing
participants (Bus and van IJzendoorn, 1999). Around half of studies included in the
Mayberry et al. (2011) meta-analysis showed evidence of an effect of PCA on reading
proficiency in the deaf participants, while the other half did not. It is likely that
differences between studies in terms of the format of the PCA tasks used (e.g. auditory
input-oral response vs. visual input-nonverbal response), aspects of reading assessed
(accuracy vs. comprehension), and populations included (e.g. children vs. adults, oral
language vs. sign language users) will have contributed to the lack of consistency in
results. Vocabulary and grammatical knowledge are key broader language skills that have
been causally associated with reading comprehension development in hearing readers and
have also been shown to relate to reading skills in deaf children (Geers, 2003; Barajas,
Gonzalez-Cuenca, & Carrero, 2016). In line with this, the Mayberry et al. (2011) meta-
analysis also reported that a broader measure of general language ability (signed or
spoken) explained 35% of the variance in reading proficiency in those studies that
included such a language measure, and was the factor with the strongest relationship to
reading. They concluded that “deaf readers, like hearing readers, are more likely to
become successful readers when they bring a strong language foundation to the reading
process” (Mayberry et al., 2011, p.181). In commenting on the Mayberry et al. (2011) meta-
analysis, Kyle, Campbell, and MacSweeney (2016) point out that the majority of the studies
on language and reading in deaf children are based on correlational studies assessing the
concurrent associations between these two aspects of development. They argue that
longitudinal studies would provide a more robust test of the nature of these possible
causal relationships. Kyle and Harris (2010, 2011) have reported on two such studies of
D/HH children in middle childhood. They found that vocabulary knowledge at mean age 7
years 10 months predicted reading comprehension outcomes one year later (Kyle & Harris,
2010). The same significant longitudinal relationship was found between vocabulary
knowledge at 8 years 10 months and reading comprehension at 10 years 11 months. This
finding supports an association between vocabulary knowledge in the development of reading
comprehension. They also showed that word reading (i.e. reading accuracy) at this age was
significantly predicted, albeit to a lesser extent, by vocabulary knowledge and that
neither reading comprehension nor word reading was predicted by phonological awareness.
Similar findings on the predictive role of vocabulary knowledge on reading accuracy were
found in the second longitudinal study in a sample of D/HH children tested at mean age 5
years 8 months, 6 years 8 months and 7 years 11 months (Kyle & Harris, 2011). An important
element of both these studies was the demonstration that vocabulary was associated with
later reading performance even after adjusting for earlier reading performance. In other
words, it controlled for the fact that the strongest predictor of reading will be the same
ability measured at an earlier time point, known as the ‘auto-regressive effect’. To
summarise, there is strong evidence in hearing children that phonological language skills
predict word reading accuracy and non-phonological broader language skills predict reading
comprehension (Hulme & Snowling, 2014). The evidence base is weaker for D/HH children,
with the majority of evidence coming from cross-sectional correlation studies, but there
is some longitudinal evidence for the role of vocabulary knowledge development of reading
comprehension and reading accuracy for these children too (Kyle & Harris, 2010, 2011).
More longitudinal studies are needed to contribute to this evidence base and to clarify
the nature of the relationships between language skills and reading proficiency in D/HH
children and young people. This has not previously been addressed in older D/HH children
and adolescents, in whom relationships identified between reading and language in the
early stages of literacy acquisition may no longer apply. This paper reports on an
analysis of relationships between language and reading measured on the first occasion at
approximately 8 years and on the second occasion at approximately 17 years of age in a
population-based sample of D/HH children with bilateral moderate-profound permanent
childhood hearing loss (PCHL) who used spoken English as their primary form of
communication. This sample was drawn from a prospective cohort study that addressed the
impact of Universal Newborn Hearing Screening (UNHS) on early confirmation of hearing loss
(Kennedy et al., 1998; Kennedy, McCann, Campbell, Kimm & Thornton, 2005) and subsequent
language and reading outcomes (Kennedy et al., 2006; McCann et al., 2009; Pimperton et
al., 2016; Pimperton et al., 2017). The main question addressed in this paper is whether
expressive language, receptive vocabulary and grammatical skills in middle childhood
predict reading accuracy and reading comprehension abilities in adolescence, after
adjusting for the effects of auto-regressive continuities in reading. The longitudinal
design of the study also makes it uniquely well-placed to provide novel evidence on the
stability of reading accuracy and reading comprehension scores between middle childhood
and adolescence for D/HH individuals.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The D/HH and hearing participants were all drawn from a 1992-97 birth cohort of 157,000
children born in eight districts of southern England (see Kennedy et al., 2006). Of 168
children in the birth cohort with PCHL, 160 were contactable and 120 gave consent to be
included in the study. These 120 children in the D/HH group had been diagnosed with
bilateral PCHL > 40 dB hearing level (dB HL) in the better ear which was not known to be
post-natally acquired. Severity of hearing loss was categorised as moderate (40–69 dB HL),
severe (70–94 dB HL) or profound (≥95 dB HL) according to four-frequency averaging of the
better ear pure-tone thresholds at 0.5, 1, 2 and 4 kHz. Maternal education was classified
according to the 2001 UK census. The hearing comparison group (HCG; N = 63) was randomly
selected from babies born on the same day and in the same district as participants in the
D/HH group. Seventy-six of the 120 D/HH and 38 of the 63 HCG participated at Time 2 (T2).
Seventeen of the 76 D/HH participants did not complete the spoken language assessments at
T2. This was either because they used British Sign Language (BSL) as their preferred
language, rendering these spoken English assessments inappropriate, or because they had
severe additional disabilities that precluded the development of sufficient language to
attempt the tests. The analyses presented in this paper are based on the 53 participants
with PCHL and 38 participants in the HCG for whom data were available on tests of reading
and language at both T1 (mean age 8.0 years) and also at T2 (mean age 17.3 years). The
requirement for reading and language measures to be available at both time points was
necessary to allow all the longitudinal analyses to be conducted on the same sample of
children. If reading and language measures were available, participants were not excluded
because of the presence of additional disabilities. The two such participants both had
learning disabilities i.e. nonverbal IQ < 70 at T1 (see 3.4 for results of sensitivity
analysis). The demographic characteristics of the samples are presented in Table 1. Sample
attrition over the approximately eight years between these two assessment time points,
coupled with inclusion only of those participants who were spoken language users, reduced
the sample size for the longitudinal analysis presented here. The annual rate of attrition
was 4% since their assessment at primary school. This degree of attrition is relatively
low for follow-up studies of long-term paediatric conditions (Karlson & Rapoff, 2009).
Attrition was principally due to the participants not responding to requests to
participate in later phases of the study (for details see Pimperton et al., 2017, Fig. 1).
The summary statistics presented in Table 1 show that both the PCHL and HCG groups in the
present study were similar in their demographic characteristics to those of the initial
samples.

<hs>  Procedure</hs>
  ~~~~~~~~~

The study was approved by the Southampton and South West Hamphsire Research Ethics
Committee. Written informed consent for participation in the study was obtained from
principal caregivers at T1and T2 and from the teenage participants at T2. At both T1 and
T2, each participant’s reading, language and non-verbal ability (N-VA) was assessed in a
quiet room at home or school by a trained researcher. At the same time we collected, from
participants and their families, information on characteristics including maternal
education level and languages used in the home. The most recently available audiological
data were taken from audiology and cochlear implant centre records – for participants with
hearing aids from the last annual review and for those with cochlear implants, unaided
pure-tone thresholds obtained during the original implant assessment.

<hs>  Materials</hs>
  ~~~~~~~~~

The group mean score and standard-deviation scores in the HCG were used to derive z scores
for the D/HH participants. The z-score for a D/HH participant is equal to the number of
standard deviations of the distribution of scores in the HCG participants by which the
D/HH participant’s age-adjusted score differs from the mean score of the HCG participants.

        <hss>Reading</hss>

        Reading Accuracy and Reading Comprehension at T1 were measured using the Wechsler
        Objective Reading Dimensions (WORD) (Wechsler, 1993) and at T2 using the newly
        available York Assessment of Reading for Comprehension Secondary Edition (YARC),
        (Stothard, Hulme, Clarke, Barmby, & Snowling, 2010). The YARC was used at T2
        because, with minor adaptations approved by the test designers (see Pimperton et
        al., 2016), we could use this measure with both spoken and sign language users in
        our sample as it did not involve reading aloud. The difficulty of reading
        comprehension tasks undertaken in the YARC was determined by word reading
        performance rather than chronological age, which was also felt to be more
        appropriate for our D/HH sample.

            <hss>Language comprehension</hss>

            At both T1 and T2 the Test for Reception of Grammar (TROG-2; Bishop, 2003) and
            The British Picture Vocabulary Scale (BPVS-3; Dunn, Dunn, & National
            Foundation for Education Research, 2009), were used to assess receptive skills
            for spoken English grammar and vocabulary respectively. TROG-2 contains test
            items that assess understanding of increasingly complex grammatical contrasts,
            including plurals, passives, negatives, and relative clauses. In both tests
            participants point to a picture from a choice of four alternatives that
            corresponds to a spoken stimulus. The z scores from the TROG-2 and the BPVS
            were highly correlated at both Time 1 (n = 53, r = 0.82) and Time 2 (n = 53, r
            = 0.67). Accordingly the two z-scores were averaged to produce Language
            Comprehension scores at Time 1 and at Time 2.

            <hss>Expressive language</hss>

            Scores from age appropriate narrative assessments (Renfrew Bus Story Test
            (Renfrew 1995) at T1, and Expression, Reception and the Recall of Narrative
            Instrument (ERRNI; Bishop, 2004) at T2) provided an Expressive Language score.
            The Renfrew Bus Story Test was developed for 3–8 year olds and involved
            children listening to a story told by the researcher supported by a series of
            pictures that correspond to the story. They then retold the story using the
            pictures as prompts and their retelling was audio-recorded and transcribed by
            the administering researcher. Two z scores from this measure (amount of
            information in the narrative and the average length of utterances i.e. number
            of words used) were averaged into an Expressive Language composite score (see
            Kennedy et al., 2006 for details). In a reliability exercise, data for 15
            randomly chosen participants were independently transcribed by a second rater.
            No discrepancy of word content was found between transcriptions but the point
            at which a sentence should pause (e.g. commas, full stops) was a subjective
            decision. The Bland-Altman method (Bland & Altman, 1986) was used for
            assessing agreement between the two transcripts on average length of the
            longest 5 sentences and the information score. There was an average difference
            of 1.1 units between the two transcripts on these two scores (0.43 and 1.53
            respectively) and variability of these differences was acceptable (95%
            confidence intervals −1.80 to 2.65 and −5.68 to 8.75 respectively). At T2 the
            ERRNI was selected, as it was similar in design to the Bus Story Test but
            suitable for use with adolescents. It requires test-takers to produce a
            narrative based on a series of cartoon pictures then reproduce that narrative,
            though this time without the support of pictures. As with the Bus Story Test,
            the ERRNI narratives were audio-recorded and transcribed by the researcher who
            had taken the recording. The ERRNI produced three scores: an Initial score for
            the quality of participants’ initial narratives, a Recall score for the
            quality of their recalled narrative, and a Mean Length of Utterance (MLU)
            score which gave the average length of utterances across both the initial and
            recalled narratives. The Initial and the Recall z scores were highly
            correlated (n = 53, r = 0.72) and therefore averaged to form an Expressive
            Language-Information score at T2. The MLU measure was less highly correlated
            with the other two T2 Expressive Language measures (n = 53, r = 0.20 and 0.32)
            and was therefore analysed separately. Following Whitehouse, Line, Watt, &
            Bishop (2009), an inter-rater reliability exercise was carried out to check
            the reliability of the ERRNI scoring. A random sample of 12 narratives (12% of
            the total) was transcribed and scored by a second rater. There was good
            agreement between the two ratings for all three scores (intraclass r: Initial
            = 0.82; Recall = 0.90; MLU = 0.95).

            <hss>Speech intelligibility</hss>

            Parents’ assessment of connected speech intelligibility was assessed at T1 and
            T2 using the Speech Intelligibility Rating Scale (Allen, Nikolopoulos, &
            O'Donoghue, 1998). This 5 point scale gives short descriptors of each level
            with 1 being ‘completely unintelligible’ and 5 being ‘intelligible to all
            listeners’ and was developed for use in cochlear implant assessment.

        <hss>Non-verbal ability</hss>

        At T1 we assessed Non-verbal Ability using the Raven’s Standard Progressive
        Matrices (Styles, Raven, & Raven, 1998). At T2 the 20 min timed version (Hamel &
        Schmittman, 2006) was used. Participants were given twenty minutes to work their
        way through a series of progressively more complex matrix reasoning puzzles. Raw
        scores reflecting the total number of correct items out of a possible 60 were
        calculated.

        <hss>Data analysis</hss>

        Regression analyses were conducted using SPSS 24 (IBM Corp., 2016). Following the
        recommendations by Kraemer and Blasey (2004), all the independent measures were
        centred before being included in the regression analyses. For this longitudinal
        analysis it was important to compare directly the same D/HH participants relative
        to the same NH control group at both time points (T1 and T2). The language z
        scores at T1, which had initially been derived relative to the scores for all
        participants in the HCG at T1, were therefore recalculated relative to the scores
        of only those HCG participants at T1 that also participated at T2. These
        recalculated z scores were used in the subsequent analyses. A preliminary test was
        conducted to determine whether there were possible covariates that might be
        confounding predictors of reading at T2. As recommended by Kraemer (2015) the
        number of putative covariates was kept to a minimum by requiring them to be
        significantly correlated with either of the T2 reading measures. Forced entry was
        used to enter the independent variables in blocks with the T1 reading score
        entering at Step 1, the covariates entering in Step 2 followed by the T1
        Expressive Language and Language Comprehension measures at Step 3. The R2 change
        from step 2 was used to test for any significant effects of T1 language on T2
        reading. Only the R2 values and their associated F tests are reported, as these
        are unaffected by collinearity. For each regression, the distribution of residuals
        was tested for skewness and kurtosis and the Kolmogorov-Smirnov test of normality
        was applied. For the prediction of T2 Reading Accuracy and for T2 Reading
        Comprehension these tests all had p values greater than .05 indicating that the
        distribution of the residuals did not deviate significantly from normal. Some
        previous studies on reading development in the D/HH have excluded children with
        low non-verbal cognitive abilities (Kyle & Harris, 2011). Accordingly, a
        sensitivity analysis was conducted to determine whether their inclusion had an
        impact on the results in the present study.

<hs>  Comparison of the PCHL and HCG mean scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Reading Accuracy, Reading Comprehension, Expressive Language, Language Comprehension
and Non-verbal Ability scores at T1 and T2 for the PCHL group and the HCG are compared in
Table 2. The scores for the HCG (n = 38) on all measures are mean = 0.00 and SD = 1.
Scores of participants with PCHL were lower than those of the HCG on all language and
reading measures with the exception of T2 Expressive Language-Information score and T2
Expressive Language-MLU score. There was a wider range of achievement at T2 than T1 in the
DH/H group and the spread of the D/HH group reading scores was larger than that in the HCG
with approximately 25% achieving reading scores above the HCG mean at T2. The spread of
D/HH group reading scores had also increased by age 17 years and was larger than that in
the HCG. At T1 those with PCHL had significantly lower Non-verbal Ability scores than the
HCG. There is a degree of normalisation over time of Non-verbal Ability in the DH/H group
and consequently there is no significant difference from the HCG at T2. The increase in
Non-verbal Ability in the D/HH group was large enough to be clinically important and was
also statistically significant (SMD = −0.60, 95%CI −0.98 to −0.21, t = 4.41, df = 52, p <
.001). At T2 all those in the D/HH group were intelligible to listeners who had at least
some experience of the speech of children with PCHL (Appendix A).

<hs>  Testing for potentially confounding covariates</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Correlations between potential covariates and T2 Reading Accuracy and T2 Reading
Comprehension for PCHL (n = 53) were calculated (see Table 3). It should be noted that the
Reading Accuracy and Reading Comprehension scores were age-adjusted z-scores and
consequently age would not be a confounder. Gender was not related to either T2 Reading
Accuracy or T2 Reading Comprehension and therefore was not included as a covariate. All
the other covariates were significantly correlated with at least one T2 reading score and
were retained. These covariates were mother’s education, first language English, severity
of hearing loss and T1 Non-verbal Ability.

<hs>  Predicting Time 2 scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

The results of forced entry stepwise regression predicting Reading Accuracy at T2 are
shown in Table 4. There was a high level of stability in the Reading Accuracy scores (Step
1 R2 = 0.63, p < .001). This indicates that 63% of the variance in T2 Reading Accuracy
scores at mean age 17 years was predicted by Reading Accuracy scores measured some 9 years
earlier. The covariates jointly added 0.07 to the R2 (p = .04). The T1 language scores did
not add significantly to the prediction of the T2 Reading Accuracy scores (Step 3 change
in R2 = 0.01, p = .459). A regression analysis adding T1 Expressive Language and Language
Comprehension sequentially (i.e. step 3a then step 3b) showed that neither explained
significant unique variance in T2 Reading Accuracy i.e. there was no significant change in
R2 at step 3b whichever order they were entered. Forced entry stepwise regression
predicting Reading Comprehension scores at T2 showed that there was a moderate degree of
stability in the Reading Comprehension scores (Step 1 R2 = 0.43, p < .001) i.e. reading
comprehension scores at T1 accounted for 43% of the variance of scores of the same skill
at T2 (Table 5). The covariates did not add significantly to the prediction of the T2
Reading Comprehension (Step 2 change in R2 = 0.04). However, the two T1 language scores
made a significant contribution to the prediction of T2 Reading Comprehension (Step 3
change in R2 = 0.17, p < .001). A regression analysis adding T1 Expressive Language and
Language Comprehension sequentially (i.e. step 3a then step 3b) showed that although there
was much shared variance, each of the language variables also made a significant unique
contribution to the explained variance. Language Comprehension explained a significant
additional 6% (p < .001) of the variance in Reading Comprehension beyond that explained by
Expressive Language. Expressive Language accounted for an additional 3% (p < .05) of the
variance in Reading Comprehension beyond that explained by Language Comprehension.

<hs>  Sensitivity test for other disabilities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The analyses reported in 3.1–3.3 were repeated with the exclusion of the two participants
with learning disabilities i.e. non-verbal IQ < 70. No substantive changes were shown in
the results in terms of the parameter estimates and their associated p values.

<h>DISCUSSION</h>
----------

This study examined relationships between language and reading, measured in middle
childhood and adolescence, in a population-based sample of D/HH children with bilateral
PCHL > 40 dB using spoken English as their chief mode of communication. Approximately half
of the sample had a moderate hearing loss and the majority had language skills within 2
SDs of their HCG peers. The D/HH participants had significantly lower scores than the HCG
on reading measures in both middle childhood and adolescence. Such group-level deficits in
reading replicate findings previously reported in children with hearing loss of varying
severities (Moeller et al., 2007; Geers & Hayes, 2011; Harris & Terlektsi, 2011). In the
present study at mean age 17 years, the reading scores of the D/HH were approximately 1 SD
below those of the HCG and this gap was slightly greater than it had been for the same
participants at mean age 8 years. A similar pattern of relative decline in reading ability
was reported in 11 year olds by Kyle & Harris (2010), where children who were severe-
profoundly D/HH made only 0.3 of a grade improvement in reading age per year between the
ages of 8 and 11 years. Early superiority in reading skills may have enabled the HCG to
read more demanding material more frequently than their D/HH peers, increasing the skill
gap and resulting in a rich-get-richer ‘Matthew effect’ (Stanovich, 1986) which is likely
to impact on their educational outcomes and subsequent life chances. When examining the
stability of reading scores in D/HH individuals in this study, we found, as expected, that
the majority of variance of reading scores at T2 was accounted for by scores of the same
abilities measured at T1. This extends the demonstration in typically developing young
people with normal hearing that early literacy was highly predictive of reading ability at
17 years of age (Cunningham & Stanovich, 1997). In that study this effect was mediated, in
part, by the impact of early reading on exposure to print. For some D/HH individuals such
a virtuous circle of early reading enhancing later achievement may be more difficult to
initiate, given the difficulties they can experience in acquiring reading skills. The main
focus of this paper was to determine the extent to which language abilities contribute to
later reading abilities in D/HH children. We found that receptive and expressive spoken
language abilities in middle childhood accounted for significant variance in adolescent
Reading Comprehension but not Reading Accuracy. A key aspect of this result is that the
analyses adjusted for Reading Accuracy or Comprehension performance in middle childhood
when predicting the same skill in adolescence thus demonstrating that these language
variables explain variance in reading comprehension development from middle childhood to
adolescence. In addition, we found that Expressive Language and Language Comprehension
measured at age 8 years each explained small but significant unique portions of the
variance in Reading Comprehension at age 17 years in addition to the variance they
explained in common. The finding that broader oral language skills predicted reading
comprehension outcomes in this sample of D/HH adolescents is consistent with findings in
hearing and in younger deaf children regarding the salience of these skills for predicting
reading comprehension development. (e.g. Nation et al., 2010; Kyle & Harris, 2010). This
consistency with the findings of Kyle and Harris (2010) is observed despite the differing
distribution of hearing loss severity within the two samples. Taken together these
consistent findings suggest a common role for broader language skills in facilitating
reading comprehension for hearing and for D/HH children across the severity spectrum.
Conversely the lack of predictive relationship between these same language skills and
reading accuracy is consistent with findings from hearing children that reading accuracy
is best predicted by measures of phonological skills (e.g. Muter et al., 2004). However, a
significant limitation of our study was the absence of a measure of phonological ability
at age 8 years, which meant we were unable to assess the predictive relationships between
phonological language skills and reading accuracy and comprehension outcomes in this
sample. Kyle & Harris (2010, 2011) found that receptive vocabulary is an important
predictor of word reading in younger D/HH children. T1 vocabulary might have predicted T2
reading accuracy in our study, but as receptive vocabulary and receptive grammar scores
were combined to create a composite receptive language score (see Methods) and vocabulary
was not examined separately we are not able to say. The fact that receptive language was
not an important determinant of reading scores in the present study may be due to
differences in the ages or the distribution of hearing loss severity and communication
modes between the two study populations. The receptive language tests selected for this
study have been widely used with deaf children in research, clinical and educational
settings. Although standardised on hearing children they require a non-verbal response
which avoided wrongly scoring mis-pronounced responses as if they were the consequence of
limited syntax or vocabulary ability. Furthermore the tests had been standardised on a
wide age range allowing use of same measures at both time points. For the expressive
language tests, the Bus Story (T1) requires high levels of oral language comprehension
(the participant listens to then retells the story). However, the ERRNI does not
(participants generate the story themselves from pictures). We have previously highlighted
this difference (Pimperton et al., 2017) as a potential contributor to the reduction in
the expressive language deficit of the D/HH group relative to the hearing group at T2.
Improvement in speech intelligibility of the D/HH group from T1 to T2 (see additional
Appendix A) is another potential contributor to this effect. This likely involvement of
language comprehension in the expressive language measure at T1 is consistent with the
finding that there is much shared variance between T1 language comprehension and T1
expressive language when predicting T2 reading comprehension; though T1 expressive
language still predicts a small but significant amount of unique variance beyond that
explained by T1 language comprehension. An unexpected finding was improvement in non-
verbal ability in those with PCHL between the ages of 8 and 17 years. This does not appear
to have been reported in previous studies. The finding is given weight by being obtained
in a longitudinally studied sample where the same children provided non-verbal ability
scores at the two ages. However, the finding may be sample specific and would benefit from
replication in other samples e.g. the sample studied by Wake et al. (2004). Alternatively,
it may relate to having sufficient language to support reasoning processes but we know of
no evidence of such a mechanism accounting for this relative normalisation of non-verbal
ability. There are consistent reports that severity of hearing loss is related to reading
development in D/HH individuals (e.g. Moeller, Tomblin, & the OCHL Collbaration, 2015).
What has been less studied is what might mediate this effect. It is unlikely that factors
linked to the aetiology of the hearing loss also acted to influence reading development,
except those that affected non-verbal ability (which was included in our analysis) or were
associated with progressive hearing loss. In the present study, severity of hearing loss
was related to reading score but the severity of hearing loss per se did not predict
reading ability once the effects of language ability (using our composite expressive +
receptive language score) were controlled. This suggests that the association between
severity of hearing loss and the difficulties in acquiring reading may be mediated by the
effect of hearing loss on language ability. This study has a number of strengths including
the longitudinal design and the population-based sampling. In such a population based
longitudinal study over a 9-year period there is inevitably sample attrition. In the
present study the evidence suggests that in most respects the retained participants were
representative of the original sample. As the teenagers assessed in this study were born
in 1992–1997, the question arises whether the reading skills of D/HH children born more
recently might show different levels of reading, and different relationships between
language and reading skills, as a result of advances in hearing device technology and in
early identification and intervention since the mid 1990s. A recent report of reading
skills of children with severe-profound PCHL aged 5–7 years when recruited in 2013–14
(i.e. born in 2006–09) described little improvement in phonological awareness or reading
ability compared with a similar study sample born 10 years earlier, but did report
improvements in vocabulary levels (Harris, Terlektsi & Kyle, 2017b). Predictive
relationships between the language and reading variables were consistent across the two
cohorts in some cases (e.g. vocabulary) but differed in others (e.g. phonological
awareness). A replication of the longitudinal analyses reported in the current study in
cohorts born more recently would be valuable to address whether the pattern of findings
reported here generalises to these later-born cohorts. Our findings provide support for
the value of intervention to foster language development in D/HH children (Rees et al.,
2015; Gilliver, Cupples, Ching, Leigh, & Gunnourie, 2016; Richels et al., 2016) but
importantly suggest that continued support for broader oral language skills into the
secondary school years could continue to be an effective way to enhance reading
comprehension ability in this population. Maximising the reading comprehension skills in
D/HH individuals of secondary school age is vital because of the increasing demands on
comprehension skills as text complexity increases in the secondary school years, and the
vital role that reading comprehension plays in broader educational success at secondary
school.

<h>CONCLUSIONS AND IMPLICATIONS</h>
----------------------------

This study extends our understanding of reading development in D/HH children and
adolescents by highlighting the predictive relationships between language skills in middle
childhood and reading comprehension in adolescence, even when adjusting for earlier
reading skills. These findings contribute to the case for continued targeted intervention
on language skills for D/HH individuals beyond primary school. Maximising their language
ability, and consequently their ability to use reading to access learning, is likely to
enhance their educational attainment and subsequent life chances.

<h>CONFLICTS OF INTEREST</h>
---------------------

The authors declare that they have no conflicts of interest in presenting the results in
this paper.


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<ART>Predictors of participation of adolescents with cerebral palsy: A European multi-centre longitudinal study
================================================================================

Authors: Van MÔ Dang, Allan Colver, Heather O. Dickinson, Marco Marcelli, Susan I. Michelsen, Jackie Parkes, Kathryn Parkinson, Marion Rapp, Catherine Arnaud, Malin Nystrand, JérÔme Fauconnier
DOI: 10.1016/j.ridd.2014.10.043
Year: 2015  |  Pages: 551-564
ASJC codes: 3203, 3204
Keywords: Adolescence, Cerebral palsy, Longitudinal predictors, Participation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We investigated whether childhood factors that are amenable to intervention (parenting stress, child psychological problems and pain) predicted participation in daily activities and social roles of adolescents with cerebral palsy (CP). We randomly selected 1174 children aged 8-12 years from eight population-based registers of children with CP in six European countries; 743 (63%) agreed to participate. One further region recruited 75 children from multiple sources. These 818 children were visited at home at age 8-12 years, 594 (73%) agreed to follow-up at age 13-17 years.We used the following measures: parent reported stress (Parenting Stress Index Short Form), their child's psychological difficulties (Strength and Difficulties Questionnaire) and frequency and severity of pain; either child or parent reported the child's participation (LIFE Habits questionnaire). We fitted a structural equation model to each of the participation domains, regressing participation in childhood and adolescence on parenting stress, child psychological problems and pain, and regressing adolescent factors on the corresponding childhood factors; models were adjusted for impairment, region, age and gender.Pain in childhood predicted restricted adolescent participation in all domains except Mealtimes and Communication (standardized total indirect effects β -0.05 to -0.18, 0.01. <. p<. 0.05 to p<. 0.001, depending on domain). Psychological problems in childhood predicted restricted adolescent participation in all domains of social roles, and in Personal Care and Communication 9β -0.07 to -0.17, 0.001. <. p<. 0.01 to p<. 0.001). Parenting stress in childhood predicted restricted adolescent participation in Health Hygiene, Mobility and Relationships 9β -0.07 to -0.18, 0.001. <. p<. 0.01 to p<. 0.001). These childhood factors predicted adolescent participation largely via their effects on childhood participation; though in some domains early psychological problems and parenting stress in childhood predicted adolescent participation largely through their persistence into adolescence.We conclude that participation of adolescents with CP was predicted by early modifiable factors related to the child and family. Interventions for reduction of pain, psychological difficulties and parenting stress in childhood are justified not only for their intrinsic value, but also for probable benefits to childhood and adolescent participation.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Children with cerebral palsy (CP) experience restricted participation in life situations
ranging from leisure pursuits to education and social roles (Beckung & Hagberg, 2002).
Most children with CP live to adulthood, where they remain at higher risk of social
disadvantage than adults without CP in terms of independent living, employment and
establishing a family (Michelsen, Uldall, Hansen, & Madsen, 2006). Adolescence may be
particularly challenging for young people with physical impairments (King, Brown, & Smith,
2003a). Delayed puberty, the psychological consequences of perception of body image, and
fewer opportunities to socialise out of school may make this period more difficult.
Medical care may be jeopardised as responsibility transfers from parent to young person
and from child to adult health services. Adolescents with CP have restricted participation
in daily activities and social roles which depends on the severity of their impairments
(Donkervoort, Roebroeck, Wiegerink, van der Heijden-Maessen, & Stam, 2007). Participation
of children and adolescents with CP is associated with the modifiable factors: pain
(Fauconnier et al., 2009), psychological problems (Ramstad, Jahnsen, Skjeldal, & Diseth,
2012) and parenting stress (Majnemer et al., 2008). However, evidence is scarce about the
modifiable factors in childhood which predict participation in adolescence. A study with a
longitudinal design (Holmbeck, Franks Bruno, & Jandasek, 2006) can help to distinguish
participation patterns determined by factors operating in adolescence from patterns
determined by factors already operating in childhood. The objective of this paper is to
evaluate how participation of adolescents with CP is associated with modifiable childhood
factors: pain, psychological problems, and parenting stress. We studied whether these
associations were mediated by participation in childhood or by the level of the same
predictors in adolescence.

<hs>  Setting and participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

The present work is part of a larger project, SPARCLE, which studies the participation and
quality of life of children and adolescents with CP in Europe. The overall design of the
project, including sample size calculations, is described elsewhere (Colver & Dickinson,
2010; Colver, 2006) and is summarised below. Children born between 31/07/1991 and
01/04/1997 were randomly sampled from population-based registers of children with CP in
eight European regions (Table 1) that share a standardised definition of CP (Surveillance
of Cerebral Palsy in Europe (SCPE), 2000). 743/1174 (63%) target families identified from
registers joined the study. One further region, northwest Germany, ascertained 75 cases
from multiple sources, using the same diagnostic criteria. The 818 children who entered
the study were interviewed initially in 2004/2005, aged 8–12 years (SPARCLE1), and
followed up in 2009/10, aged 13–17 years (SPARCLE2), when 594 (73%) remained in the study.
Predictors of drop-out have been reported (Dickinson et al., 2006, 2012). Researchers from
the nine regions visited families in their homes to administer questionnaires to parents
and their children. The researchers had attended common training in order to maximise
homogeneity of survey methodology across regions.

<hs>  Measures</hs>
  ~~~~~~~~

We evaluated participation using the questionnaire of Life Habits (LIFE-H) (Noreau et al.,
2004) which is based on a social model of disability similar to the theoretical framework
of the World Health Organisation's International Classification of Functioning (World
Health Organisation, 2007) and has been validated in children with disabilities (Noreau et
al., 2007). Wherever possible the adolescent completed the questionnaire; otherwise a
parent completed it. It consists of 62 items divided into six domains of daily life
activities (Mealtimes, Health hygiene, Personal care, Communication, Home life, and
Mobility) and five domains of social roles (Responsibilities, Relationships, Community
life, School, and Recreation). It includes fifteen “non-discretionary” activities, such as
transferring into or out of bed, which are essential for daily living; and forty-seven
further “discretionary” activities, such as exercise to optimise health, which may or may
not be achieved. We recorded the discretionary items using three levels: not achieved
because too difficult; achieved with difficulty; achieved without difficulty. A
discretionary item could also be considered non-applicable if it was irrelevant, for
example if the child or adolescent had no interest in that activity; we treated non-
applicable items as missing responses. We recorded non-discretionary items in childhood
using two levels (achieved with difficulty, achieved without difficulty) but in
adolescence we used three levels (achieved with much difficulty, achieved with some
difficulty, achieved without difficulty). The Life-H asks, for each item, how much
assistance the young person requires, but we ignored this information because we wanted to
assess participation without incorporating the influence of environmental factors
(Fauconnier et al., 2009). In order to assess pain, we asked parents about the frequency
and severity of their child's pain over the previous week; we recorded responses on six
levels, but grouped them into three categories for analysis. We captured the psychological
problems of the child or adolescent using the Total Difficulties Score of the parent-
reported Strength and Difficulties Questionnaire (SDQ) (Goodman, 1997). We captured
parenting stress using the Total Stress Score of the Parenting Stress Index Short Form
(PSI-SF) (Abidin, 1995). Parents provided information about their child's impairments
(walking ability as captured by the gross motor function classification system (GMFCS)
(Palisano et al., 1997), fine motor function (Beckung & Hagberg, 2002), seizures, feeding,
communication, intellectual ability (White-Koning et al., 2005)), family structure and
parents’ educational qualifications.

<hs>  Statistical methods</hs>
  ~~~~~~~~~~~~~~~~~~~

Full details of the statistical methods are reported in Appendix Statistics and summarised
below. For each participation domain, we translated hypotheses about the variables that
might influence participation into one structural equation model which comprised a
‘measurement part’ that defined the latent constructs that underlie sets of observed
variables; and a ‘structural part’ that hypothesised the links between these constructs.
The measurement part (illustrated in Fig. 1 for one domain, Home life) considered
participation in each domain to be an unobserved or latent variable, manifested by
responses to the items in the LIFE-H questionnaire. We likewise modelled impairment and
pain using latent variables, manifested respectively by the levels of the six individual
impairments as recorded in childhood and by the frequency and severity of pain over the
previous week (see Fig. 1). The structural part specified the hypothesised links between
the variables, both latent and observed (see Fig. 2). For each participation domain, we
hypothesised that participation in both childhood and adolescence may be directly affected
by the concurrent factors: pain (Doralp & Bartlett, 2010), psychological problems (Ramstad
et al., 2012), and parenting stress (Blum, Resnick, Nelson, & St Germaine, 1991).
Additionally, we hypothesised that each factor in childhood could indirectly affect
participation in adolescence via its influence on four mediating variables: participation
in childhood, and the three factors in adolescence. We adjusted for impairment, region,
gender, and age. Psychological problems, parenting stress, region, gender, and age were
treated as observed variables; region and gender were categorical while the others were
continuous. Our analysis followed the steps outlined by Kline (2011) for a structural
equation model. We assessed model goodness of fit by the root mean square error of
approximation (RMSEA), which indicates a good fit when RMSEA <0.05. We identified the
childhood factors that were significantly related to each domain of childhood
participation through preliminary analysis that was restricted to childhood variables. We
then developed the full model, retaining only these significant childhood factors and
similarly identifying adolescent factors that were significantly related to adolescent
participation. We report the estimated indirect effects (β) of childhood factors (pain,
psychological problems, parenting stress) on adolescent participation. The total indirect
effects were the sum of the partial indirect effects via all four possible pathways (see
Figures and Appendix Statistics). These indirect effects were standardised in order to
compare the contributions of different predictors to participation; a standardised effect
of β of a predictor on a specific outcome means that an increase of one standard deviation
in the predictor is associated with a change of β standard deviations in the outcome. As
it was of interest to compare the effect of modifiable childhood factors with the effect
of impairment, we also noted the standardised direct, indirect and total effects of
impairment on adolescent participation. We determined statistical significance (p-values)
from the estimated standard errors of the unstandardised effects. Finally we undertook
sensitivity analyses around drop-out, including all 818 SPARCLE1 participants and imputing
missing data (van Buuren, 2007). We analysed the data using Mplus software, version 6.12
(Muthén & Muthén, 1998).

<hs>  Ethics</hs>
  ~~~~~~

In each country, we obtained ethical approval or a statement that only registration was
required, as appropriate. We obtained signed consent from all parents and from young
people who could give meaningful consent.

<h>RESULTS</h>
-------

The average age of the children was 10.4 years at the first visit and 15.1 years at the
second visit; 249 (42%) were girls. The average time between visits was 4.7 years (3.6–5.8
years). Table 1 shows the distribution of putative predictors of participation. The rate
of missing data was low: not more than 3% for any variable. Parents reported that
approximately two thirds of their children experienced at least some pain during the
previous week. The Total Difficulties Score of SDQ was abnormal (>16) in 21% of
adolescents, a proportion twice that in the general population (Goodman, 1997). The Total
Stress Score of PSI-SF was abnormal (>90) for 34% of their parents, twice the proportion
in the general population (Abidin, 1995). Table 2 shows the distribution of participation
items for each age group. Non-response remained less than 3% except for the item of extra
classes in childhood. Among adolescents, discretionary items were considered non-
applicable by between 0% (getting a good sleep) and 52% (religious activities). Both items
of the Community life domain were considered non-applicable by 26%, with marked
differences between regions, so we excluded that domain from analysis as in our prior
study (Fauconnier et al., 2009). The proportion of adolescents achieving an item without
difficulty varied widely, from 31% (moving on slippery or uneven surfaces) to 93%
(maintaining a loving relationship with one's parents). In preliminary investigations, we
fitted the measurement model for each domain and generated participation scores for each
adolescent. These varied significantly between regions for all domains except
Relationships; excluding this domain, the variation between regions was 3–11% of the total
variation in participation, depending on domain; in contrast, the variation between levels
of GMFCS was 22–60% of the total variation.

<hs>  Predictors of adolescent participation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 3 and Fig. 3 summarise the estimated effects of early predictors on adolescent
participation. The goodness of fit of the models was good (0.037 ≤ RMSEA ≤ 0.048). The
models explained between 61% and 90% of the variance of participation in adolescence,
except in the Relationships domain where the model explained only 41%. As expected,
impairment predicted a significant restriction of adolescent participation in all domains,
with standardised total effects ranging from β = −0.37 (p < 0.001) for Relationships to β
= −0.88 (p < 0.001) for Mealtimes. Pain in childhood predicted a significant restriction
of adolescent participation in all domains except Mealtimes; the size of its standardised
indirect effect was most marked in Health hygiene (β = −0.18, p < 0.001) and Relationships
(β = −0.14, p < 0.001) (indicating that an increase of one standard deviation in childhood
pain was associated with decreases of 0.18 and 0.14 standard deviations respectively in
these domains of participation). Psychological problems in childhood predicted a
significant restriction in adolescent participation in all domains of social roles,
effects ranging from β = −0.11 in Relationships (0.001 < p < 0.01) to β = −0.17 in
Responsibilities (p < 0.001), and in the daily life activities of Personal care and
Communication (β = −0.07 and −0.11 respectively, p < 0.001). Parenting stress in childhood
predicted restricted adolescent participation in Health hygiene (β = −0.11, p < 0.001),
Mobility (β = −0.07, 0.001 < p < 0.01) and Relationships (β = −0.18, p < 0.001).
Adolescent participation in Mealtimes was not significantly associated with any of the
childhood predictors.

<hs>  Pathways to participation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Direct and indirect effects of impairment were of similar magnitude in most domains, the
indirect effects being mediated largely by childhood participation. The associations
between modifiable childhood predictors and adolescent participation were largely mediated
by childhood participation, which was a strong predictor of adolescent participation in
most domains: a change of one standard deviation in childhood participation predicted a
change of between 0.28 and 0.68 standard deviations in adolescent participation, depending
on domain (see Fig. 3). The influence of childhood pain on adolescent participation was
essentially mediated via its direct effect on childhood participation (see Table 3 and
Fig. 3); the partial indirect effects of childhood pain via adolescent factors were
generally small or negligible (partial β ≤ 0.04). Psychological problems in childhood
predicted adolescent participation in Communication, Responsibilities and Relationships
mainly via child participation (partial β = −0.07, −0.12 and −0.11 respectively) but they
predicted adolescent participation in the domains of Personal care, School and Recreation
mainly via psychological problems in adolescence. Parenting stress in childhood was also
significantly related to adolescent participation in Mobility and Relationships via
childhood participation (partial β = −0.07 and −0.11 respectively) but via parenting
stress during adolescence in the domains of Health hygiene and Relationships. Sensitivity
analysis, which imputed missing data for those who dropped out between childhood and
adolescence, yielded similar results (data not shown).

<h>DISCUSSION</h>
----------

Childhood participation was the main predictor of adolescent participation (a change of
one standard deviation in childhood participation predicted a change of between 0.28 and
0.68 standard deviations in adolescent participation, depending on domain). Three factors
in childhood (pain, psychological problems and parenting stress) predicted, in varying
degrees, restricted participation at adolescence in all domains except Mealtimes. However,
these effects were small: a change of one standard deviation in any of the three childhood
factors predicted a change of at most 0.18 standard deviations in adolescent
participation. Furthermore, these three childhood factors predicted adolescent
participation largely via their effects on childhood participation, although in some
domains early psychological problems and parenting stress in childhood affected adolescent
participation through their persistence into adolescence. Effects of impairment were much
larger than the effects of these childhood factors: a difference of one standard deviation
in impairment was associated with a difference of more than 0.6 standard deviations in
adolescent participation in all domains except Relationships, the main pathway again being
via childhood participation.

<hs>  Strengths and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Because sampling of the children was multinational and from population registers of
children with CP, conclusions may be generalised to the population of adolescents with CP
living in Europe. As in any regression, statistical associations do not prove causation.
Unmeasured, shared causes could explain part of the associations; for instance parenting
style may influence both parenting stress and participation. Although we based our
hypothesised directions of effects on prior research (Dang, 2012), alternative directions
of effects should be considered (King et al., 2003b). For instance, increased
participation may improve the psychological health of the child (Dahan-Oliel, Shikako-
Thomas, & Majnemer, 2012). Non-response by families targeted for recruitment to SPARCLE1
was 37% (Dickinson et al., 2006), and drop-out between SPARCLE1 and SPARCLE2 was 27%
(Dickinson et al., 2012). The parents who dropped out between SPARCLE1 and SPARCLE2 had a
higher level of stress when their children were aged 8–12 than those retained in the
study. Although such differential non-response is likely to result in biased estimates of
population means, it may be less important in the present study which estimates
associations (Korn & Graubard, 1999). Nevertheless, we tried to minimise the effects of
differential non-response and drop-out in two ways. Firstly, we adjusted for region and
walking ability, which were predictors of non-response (Dickinson et al., 2006; Korn &
Graubard, 1999). Secondly, we performed a sensitivity analysis which included all children
who participated in SPARCLE1, imputing missing data; this yielded similar results to the
primary analysis. We considered that the young person knew most about their participation;
but if a young person could not self-report due to intellectual impairment we relied on
parent-report. Parent-reported pain may differ from self-reported pain (Parkinson, Gibson,
Dickinson, & Colver, 2010), but we chose it in order to have a common metric across the
sample. Prior research has tended to examine the impacts of specific impairments on
activities (Beckung & Hagberg, 2002; Fauconnier et al., 2009), but in our study we
controlled for impairment using a single latent variable because children with CP are
affected by several correlated functional limitations reflecting the global severity of
the cerebral disturbance. The model did not explicitly take account of environmental
influences such as the availability of specialised schools or the accessibility of
transportation; however, by controlling for region, we took account of the regional
variation in environments. As in any structural equation approach, other models may fit
the data equally well (Kline, 2011). The prevalence of the predictors of participation in
our sample was comparable to that in other studies; for example, pain was present in
50–70% of children and adolescents with CP (Doralp & Bartlett, 2010; Engel, Petrina,
Dudgeon, & McKearnan, 2005; Hadden & von Baeyer, 2002), psychological problems in 39% to
54% of children with CP (Brossard-Racine et al., 2012; Goodman & Graham, 1996), and
symptoms of stress in about 30% of mothers of children with CP (Manuel, Naughton,
Balkrishnan, Paterson Smith, & Koman, 2003; Sawyer et al., 2011).

<hs>  Comparison with other studies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We could not find other longitudinal studies of early predictors of participation of
adolescents with disabilities. However, King et al. (2009) examined predictors of change
in intensity of participation in leisure and recreational activities over a three year
period of children with physical disabilities aged 6–15. They found that participation
intensity declined over the years in recreational, active physical and social activities
but not in skill-based and self-improvement activities. Factors associated with these
changes varied with type of activity and the child's age and sex. Their conclusions
emphasised individual variability and proposed that interventions should be tailored to
the individual child. It is difficult to compare their study with ours, because they
measured the intensity (frequency) of participation in leisure activities and therefore
could not address, as we did, difficulty in participation in essential daily activities
such as feeding and toileting. Our findings are consistent with findings from cross-
sectional studies that pain limits daily activities in children (Tervo, Symons, Stout, &
Novacheck, 2006) and adolescents with CP (Doralp & Bartlett, 2010). Pain reduces
children's school attendance (Houlihan, O’Donnell, Conaway, & Stevenson, 2004) and
predicts altered school functioning via fatigue (Berrin et al., 2007). Psychological
problems in childhood may contribute to friendlessness and restricted participation in
social roles (Doll, 1996), and be associated with decreased participation in children with
CP (Ramstad et al., 2012). Parenting stress is associated with more coercive parent–child
interactions (Plant & Sanders, 2007), and this could restrict the freedom of the child or
adolescent to experiment with activities. Other studies of children and adolescents with
disabilities have highlighted the range and complex inter-relationships of child, family
and community factors that predict participation (Colver et al., 2012; King et al., 2003b,
2006, 2009; Orlin et al., 2010; Yeung & Towers, 2014). In particular, King et al. (2006)
used structural equation modelling to undertake a cross sectional analysis of children
aged 6–14 years with physical disabilities, including CP, to examine child, family and
environmental influences on leisure and recreational participation. Family participation
in social and recreational activities influenced the child's participation, but the
standardised β coefficient was only 0.18. Child preferences had a stronger β coefficient
of 0.28 but this may reflect not only the personality and interests of the child but also
environmental factors; for example, a child that has experienced unfriendliness in leisure
settings will prefer not to attend such settings (Colver, 2010). King et al. (2006) found
only a small indirect effect of an unsupportive environment; however this small effect may
be partly because they used CHIEF to measure the physical, social and attitudinal
environment; CHIEF is a subjective measure of the frequency and extent of perceived
environmental barriers on participation rather than a direct measure of the environment;
it may therefore reflect differing expectations of participation rather than actual
environmental barriers. In our study of the cohort aged 8–12, we found that their
physical, social, and attitudinal environment influenced their participation in everyday
activities and social roles (Colver et al., 2011; Fauconnier et al., 2009; Michelsen et
al., 2009); the variation in adolescent participation between regions suggests environment
is also an important influence on adolescent participation in several domains.

<hs>  Implications for clinical practice</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Important modifiable predictors of participation of adolescents with CP are pain,
psychological problems and parenting stress in childhood, which are highly prevalent in
families with a child with CP. The consistency of the associations we have found in this
longitudinal study and their correspondence to clinical expectation suggest that these
factors have a causal role. These childhood factors influence adolescent participation
largely via their influence on childhood participation, which strongly predicts adolescent
participation, and to a lesser extent via their influence on the corresponding adolescent
factors. These findings highlight the importance of improving childhood participation in
order to improve adolescent participation. Clinicians will want to intervene early to
reduce pain, parenting stress and psychological problems, not only because these factors
are intrinsically distressing but because of their likely effect on child participation.
Pain management and the psychological aspect of pain in children with CP may be addressed
by working on coping strategies (Jensen, Engel, & Schwartz, 2006). Psychological problems
experienced by the child can be addressed (Beale, 2006) and interventions which target the
family as a whole may improve the emotional and psychological symptoms of children with
chronic conditions (Barlow & Ellard, 2004). Parenting stress can also be addressed
directly (Barakat & Linney, 1992; Frey, Greenberg, & Fewell, 1989; Hinojosa & Anderson,
1991). Ideally, multidisciplinary care should start early in childhood and continue into
adolescence.

<hs>  Implications for research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

The most reliable way to assess whether the identified associations represent causal
mechanisms would be to undertake randomised controlled trials of interventions to reduce
child pain, child psychological problems and parenting stress, with long-term follow-up
and measurement of participation as a secondary outcome. Trials of interventions aiming
directly to improve participation are also needed as. Additionally, further follow-up of
the same cohort would enable assessment of the long-term effects of childhood and
adolescent precursors on adult participation. Ideally, future observational studies should
have a sufficiently large sample size (e.g. over 1000 participants) to allow the use of
person-centred analytic methods that identify different patterns of participation and
their predictors (Bartko & Eccles, 2003; Shanahan & Flaherty, 2001).

<h>ROLE OF THE FUNDING SOURCE</h>
--------------------------

SPARCLE 1 (visits in childhood) was funded by the European Union Research Framework 5
Program – Grant number QLG5-CT-2002-00636, the German Ministry of Health GRR-58640-2/14
and the German Foundation for the Disabled Child. SPARCLE 2 (visits in adolescence) was
funded by: Wellcome Trust WT 086315 A1A (UK & Ireland); Medical Faculty of the University
of Lübeck E40-2009 and E26-2010 (Germany); CNSA, INSERM, MiRe – DREES, IRESP (France);
Ludvig and Sara Elsass Foundation, The Spastics Society and Vanforefonden (Denmark);
Cooperativa Sociale “Gli Anni in Tasca” and Fondazione Carivit, Viterbo (Italy); Goteborg
University – Riksforbundet for Rorelsehindrade Barn och Ungdomar and the Folke Bernadotte
Foundation (Sweden). None of the above funders had any say in the design and conduct of
the study; collection, management, analysis, and interpretation of the data; and
preparation, review, or approval of the manuscript.

<h>CONFLICTS OF INTEREST</h>
---------------------

All authors declare that they have no conflicts of interest, including financial, personal
or other relationships that could be perceived to influence this paper.


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<ART>Probing communication-induced memory biases in preverbal infants: Two replication attempts of Yoon, Johnson and Csibra (2008)
================================================================================

Authors: Priya Silverstein, Teodora Gliga, Gert Westermann, Eugenio Parise
DOI: 10.1016/j.infbeh.2019.03.005
Year: 2019  |  Pages: 77-87
ASJC codes: 3204
Keywords: Bayes factor analysis, Cognitive development, Eye-tracking, Replication, Social learning, Visual short-term memory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

In a seminal study, Yoon, Johnson and Csibra [PNAS, 105, 36 (2008)] showed that nine-month-old infants retained qualitatively different information about novel objects in communicative and non-communicative contexts. In a communicative context, the infants encoded the identity of novel objects at the expense of encoding their location, which was preferentially retained in non-communicative contexts. This result had not yet been replicated. Here we attempted two replications, while also including a measure of eye-tracking to obtain more detail of infants’ attention allocation during stimulus presentation. Experiment 1 was designed following the methods described in the original paper. After discussion with one of the original authors, some key changes were made to the methodology in Experiment 2. Neither experiment replicated the results of the original study, with Bayes Factor Analysis suggesting moderate support for the null hypothesis. Both experiments found differential attention allocation in communicative and non-communicative contexts, with more looking to the face in communicative than non-communicative contexts, and more looking to the hand in non-communicative than communicative contexts. High and low level accounts of these attentional differences are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Humans are expert learners. We learn implicitly, through mechanisms like statistical
learning (Fiser & Aslin, 2001; Kirkham, Slemmer, & Johnson, 2002; Newport & Aslin, 2004),
and explicitly from others through social learning (Csibra & Gergely, 2009, 2011;
Tomasello, Carpenter, Call, Behne, & Moll, 2005). Social learning can occur either through
observation (Meltzoff, 1988a, 1988b; Meltzoff & Moore, 1989), or through pedagogy, or
explicit teaching (Csibra & Gergely, 2009; Csibra, 2007; Tomasello et al., 2005). Although
teaching usually involves language, knowledge transfer can also occur in its absence. Two
types of communicative cues have been suggested to be key to information transmission
through teaching: ostensive cues such as direct eye contact or infant directed speech
(IDS) convey the intention of communication, and referential cues such as pointing or gaze
shifts direct attention to the source of the information to be learned (Csibra & Gergely,
2009; Csibra, 2010). According to the Natural Pedagogy theory (Csibra & Gergely, 2009)
ostensive communicative cues signal to infants when to learn culturally relevant kind-
generalizable information about an object. In the presence of these cues, infants would be
biased to encode surface features, which support learning about object kinds, over spatio-
temporal information. One method to investigate how infants encode object properties is
the violation of expectation paradigm (VoE). The VoE paradigm is based on the assumption
that infants look longer at events that violate their expectations (Onishi & Baillargeon,
2005; Teglas et al., 2011; Woodward, 1998), including when features of an object change
(Krøjgaard, 2009; Mareschal & Johnson, 2003). Yoon, Johnson, and Csibra (2008) used a VoE
paradigm to test the hypothesis that being communicated to should bias infants to encode
surface features. In their study, the authors presented the infants with videos of
communicative and non-communicative scenarios. The communicative videos included IDS,
direct eye contact, and pointing, whereas the non-communicative videos included adult-
directed speech (ADS), no direct eye contact, and reaching. In communicative scenes, an
actress said ‘Hey baby!’ in IDS, while engaging in direct eye contact, and then pointed
towards a novel object out of reach on the left or right side of the scene. In non-
communicative scenes, an actress said ‘What’s this?’ in ADS, while looking at the object,
and then reached towards the object. Screens then occluded the object and actress. After a
few seconds, the occluders opened to reveal the object again. At the point of reveal,
either the identity or location of the object had changed, or no change occurred. Infants
looked longer at the identity change in the communicative condition and at the location
change in the non-communicative condition (both in terms of first look and total look
length). The authors concluded that infants encoded the identity of the object after being
communicated to, as this was relevant to kind-generalizable learning. In contrast, infants
encoded the location of the object in the non-communicative condition, due to this being
the default, or perhaps the attempted reach enhancing the perceived graspability of the
object. This double dissociation in the encoding of identity and location information
suggested that the communicative cues did not merely increase overall memory, but elicited
a specific memory bias towards identity information. There have been few papers so far
attempting to replicate or extend this finding. Okumura, Kobayashi, and Itakura (2016)
found that in a live study, infants showed an identity bias in a direct gaze condition.
However, the authors did not replicate the finding of a location bias for the condition
with no direct gaze, instead finding encoding of both identity and location. The authors
suggest that, due to the video deficit effect (Anderson & Pempek, 2005), infants may have
performed better in their study than in the original study, therefore managing to encode
both identity and location in the non-communicative condition. Their findings suggest that
instead of identity being preferentially encoded by infants after viewing communicative
scenes, it may be that infants are able to encode both spatiotemporal and recognition-
relevant features, but ostensive signals disrupt location encoding. Two studies following
up on this result in adults drew the same conclusions (Marno, Davelaar, & Csibra, 2014,
2016), finding encoding of both identity and location information in the non-communicative
condition, and only encoding of identity in the communicative condition. As there are only
two studies investigating communicatively induced memory biases in infants, we felt it was
necessary to replicate the original finding before extending this research ourselves.
After being sent example videos from one of the original authors we noticed that in the
communicative videos, the actress pointed for longer than she reached (6.8 s compared to
4.5 s). This difference raises the possibility that a longer duration of having the hand
on screen could be responsible for inducing an identity memory bias. Therefore, in our
stimuli both types of actions were performed twice for the same duration. Also, in the
original study, the actress had bars stopping her from being able to reach the object. We
did not use bars in our stimuli, instead having the actress be too far away from the
object to reach it, in order to conceptually replicate the idea that the actress was
unable to reach the objects, but without obscuring her. Lastly, we used eye tracking to
investigate infants’ distribution of attention while observing the communicative or non-
communicative scenes. Although Yoon et al. (2008) compared overall looking to the action
scenes and reported no difference between conditions, this does not speak to where the
infants were looking while viewing these scenes. A difference in attention allocation in
the two contexts could be responsible for the memory biases observed. For example, as
preverbal infants tend to follow referential cues only when these are preceded by
ostensive cues (Senju & Csibra, 2008; but see Gredebäck, Astor, & Fawcett, 2018;
Szufnarowska, Rohlfing, Fawcett, & Gredebäck, 2014), we thought that perhaps in the
communicative context infants would look more directly towards the objects, and that this
could enhance the encoding of features. As this part of the study was exploratory, we did
not pre-specify specific hypotheses relating to looking during the pre-occlusion section
of the videos. We report two replication attempts. The first replication, Experiment 1
(bar the changes outlined above), followed the methodological details reported in Yoon et
al. (2008). In the second replication, Experiment 2, we made slight changes to the method
and exclusion criteria following guidelines provided by Csibra (personal communication,
November 2017). Both replication attempts were pre-registered, and all data, code,
supplementary results and materials are openly available on the Open Science Framework
(OSF) (https://osf.io/77gpt/).

<hs>  Methods</hs>
  ~~~~~~~

Experiment 1 was conducted following the methods section of Yoon et al. (2008), bar some
changes outlined in the introduction. Participants were recruited from a database of
families at an infancy lab of a UK university, and were given a book as a gift for
participation and £10 travel reimbursement. Parents gave informed, written consent before
participation, and were free to withdraw their consent. All data were kept confidential.
Both experiments were approved by the university ethics committee and adhered to the
British Psychological Society guidelines.

            <hss>Replication</hss>

            Forty-two normally developing 9-month-old infants took part in the experiment.
            Of these twenty-four were included in the replication analysis (mean age: 274
            days; range: 258 days to 286 days; 9 female; 23 Caucasian; 20 monolingual
            English). Exclusion criteria matched those used in Yoon et al. (2008): Infants
            were excluded for ceiling looking time for all trials (n = 4), experimenter
            error (n = 4), fussiness (n = 7), and not looking during one or more occlusion
            events (n = 3). An occlusion event in this experiment was defined as the time
            between the first frame of the clip when the occluder starts closing, and the
            first frame when the occluder is fully closed.

            <hss>Scene analysis</hss>

            We were able to use less stringent exclusion criteria for this analysis as our
            exclusion criterion of watching the entire occlusion event was irrelevant when
            looking at infant looking before the occlusion. Of the forty-two infants who
            took part in the experiment, 40 were included in the scene analysis (mean age:
            276 days; range: 258 days to 322 days; 17 female; 39 Caucasian; 20 monolingual
            English). Two infants were excluded due to experimenter error.

        <hss>Stimuli</hss>

        We created the video stimuli and digitally added objects (on the left or right
        side of screen) and occluders on each clip. Infants first saw two familiarization
        trials. These familiarization videos were 29 s long and consisted of the actress
        moving around slightly to upbeat music, while looking either at the infant with
        direct gaze and smiling (communicative condition), or at the object with intrigue
        (non-communicative condition) (6 s). After this, yellow screens occluded the
        object and actress (3 s), there was a short break where the occluders stayed
        closed (5 s), the object screens revealed the object again (with no change) (2 s),
        and the object remained on screen for a maximum of 15 s (less if the infant looked
        away for two seconds, in which case the next trial was advanced). We always used
        the same two objects, but counterbalanced across participants for actress, side
        and order. In the test videos (Fig. 1), there was first an introductory sentence
        produced by the actress (“Hey baby!” with direct gaze for the communicative
        videos, and “What’s that?” with gaze to the object for the non-communicative
        videos) (4 s). This was followed by the action being executed once towards an
        object to the front of the actress on the left or right side (a point or a reach
        towards the object as if to try and grasp it) (4 s). The actions were completed at
        an equal distance away from the object, and were of the same duration. After
        completing the action once, the actress returned to the resting position and said
        either “Wow” (with direct gaze) while waving at the infant (communicative) or
        “Hmm” (without direct gaze) with a hand on her chin (non-communicative) (4 s).
        After this, she produced the pointing or reaching action again (4 s). Following
        this, screens moved to occlude both the object and the actress (2 s). The
        occluders stayed on the screen (5 s), after which the object screens reopened (2
        s) to reveal the object. There had either been no change to the object, or it had
        changed in either identity or in location. The objects stayed on screen for a
        maximum of 15 s, or until infants looked away for 2 s. Test videos were 37 s long.
        Occluders produced sounds when opening and closing to direct infant attention to
        these events. We obtained the objects from the Noun database (Horst & Hout, 2015),
        and chose 6 pairs with medium similarity ratings. We used the first of each of
        these pairs as the initial object, and the paired objects for the identity change
        condition (i.e., when the object changed identity, the second object in the pair
        was what it changed into). Every infant saw all 6 of the objects at test. Which
        object was shown for which condition combination was pseudo-randomised into 8
        trial orders (with 3 infants viewing each order). Which actress played which role
        (communicative or non-communicative) was counterbalanced across infants. Object,
        side of action, condition and outcome were pseudo-randomised in the 8 possible
        trial orders. Additionally, infants never saw more than two trials similar on any
        factor (e.g. no more than two left actions) in a row. All videos are openly
        available on the OSF.

        <hss>Procedure</hss>

        Infants sat on their caregiver’s lap during the experiment in front of a 23-inch
        screen (seated approximately 0.6 m away). An eye-tracker (Tobii X120) captured
        infant looking times and locations on screen for the action scene analysis. We
        used Tobii studio 3.3.1 to present stimuli and gather eye-tracking data. A camera
        placed above the screen fed input directly into Tobii studio, from which videos of
        infants were later exported for offline looking time coding. We performed a
        9-point calibration for all infants before beginning the experiment. After this
        calibration, we instructed parents not to talk to or interact with their infant,
        and the experiment began. Infants saw 2 familiarization videos (1 communicative, 1
        non-communicative) followed by 6 test videos (for each of the communicative or
        non-comunicative familiarization video there was one no change, one identity
        change, and one location change test video). Therefore, each infant contributed
        one trial per sub-condition to the replication analysis, and three trials per
        condition to the scene analysis.

            <hss>Replication</hss>

            We performed all analyses on raw data in R (R Core Team, 2017). All code is
            openly available on the OSF. Videos of infants were exported from Tobii studio
            and infant looking was blind coded in ELAN (2019)(Version 5.0.0). A second
            blind coder performed secondary coding on 20% of videos. We found a high
            degree of reliability between coders: the average measure ICC was 0.97 with a
            95% confidence interval from 0.95 to 0.99. The length of the first look was
            defined as the time between the infant looking towards the screen and their
            first look away, beginning at the first frame of the occluders opening. The
            total looking time was defined as the cumulative length of time of all looks
            towards the screen, beginning at the first frame of the occluders opening, and
            ending at the first frame of the next attention getter. We replicated the
            analysis by Yoon et al. (2008). We carried out a 2 × 3 repeated ANOVA on the
            length of first look to screen after object reveal as a function of action
            (communicative vs. non-communicative) and outcome (identity change, location
            change, no change), with follow up one-way ANOVAs and parametric and non-
            parametric pairwise tests. The same analyses were conducted for total looking
            times.

            <hss>Scene analysis</hss>

            We performed all analyses on raw data in R. All code is openly available on
            the OSF. We exported raw data from Tobii Studio 3.3.1, and visualized and
            analyzed them in R using the eyetrackingR package (Dink & Ferguson, 2016).
            First, Areas of Interest (AOIs) were created for face (630 × 310 pixels), hand
            (385 × 340 pixels), and object (380 × 340 pixels) areas of the videos. The
            data were then visualized as a timecourse. We performed a bootstrapped cluster
            based permutation analysis (Maris & Oostenveld, 2007) to establish during
            which time-points conditions differed significantly. This involved running a
            test on each time bin (17 ms) that quantified a significant difference between
            actions (communicative vs. non-communicative). We grouped into clusters the
            adjacent bins that showed a significant difference. We then shuffled the data
            and performed this same test on one thousand iterations of the shuffled data.
            This produced a table of the probability of each cluster appearing under the
            null hypothesis. Clusters that had a probability of less than 5% of appearing
            under the null hypothesis (i.e., p < 0.05) were considered to be significant.
            This test accounts for both Type 1 and Type 2 errors, by controlling the
            false-alarm rate while sacrificing little sensitivity (Maris & Oostenveld,
            2007).

        <hss>Replication: first look length</hss>

        We compared the length of first look in a 2 × 3 ANOVA with action (communicative
        vs. non-communicative) and outcome (location change, identity change, no change)
        as within-subject factors (Fig. 2). There was a significant main effect of outcome
        [F(2,46) = 4.15, p =  0.02, ηp2 = 0.15]. There was no significant main effect of
        action [F(1,23) = 0.2, p =  0.66] or significant interaction between action and
        outcome [F(2,46) = 1.32, p =  0.28]. Paired comparisons by parametric (Student’s
        t) and nonparametric (Wilcoxon rank-sum) tests were carried out to assess the
        effect of each outcome on the looking times. Infants looked longer to the identity
        change than the no change outcome, regardless of communicative context. Looking
        was significantly longer for the identity change than the no change outcome [t(23)
        = 2.79, p =  0.008, ηp2 = 0.26; Wilcoxon’s Z = -2.45, p =  0.01], whereas looking
        time for the identity change and location change [t(23) = 1.47, p =  0.15] and
        location change and no change [t(23) = 0.95, p =  0.35] outcomes did not differ
        significantly. A nonparametric McNemar test found that this difference could be
        attributed to some of the infants rather than the entire group. Six of the 24
        infants showed the behaviour reported in Yoon et al.’s study (longer looking at
        identity change than no-change after communicative scenes and longer looking at
        location change than no-change after non-communicative scenes), 9 infants showed
        only the identity bias (longer looking at identity change than no-change after
        communicative scenes), 5 infants only showed the location bias (longer looking at
        location change than no change after non-communicative scenes), and 4 infants
        showed the opposite pattern in both contexts (longer looking at the identity
        change than no-change after non-communicative scenes and longer looking at
        location change than no change after communicative scenes). This distribution was
        not significantly different from chance (McNemar’s p =  0.42).

        <hss>Replication: total look length</hss>

        Total looking length was compared in a 2 × 3 ANOVA with action (communicative or
        non-communicative) and outcome (location change, identity change, no change) as
        within-subject factors (Fig. 3). There was no main effect of outcome [F(2,46) =
        0.66, p =  0.52] or action [F(1,23) = 0.01, p =  0.93], showing that overall
        infants did not look longer at test in either the communicative or non-
        communicative condition. There was a significant interaction between action and
        outcome [F(2,46) = 3.5, p =  0.04, ηp2 = 0.13]. We carried out separate 3-level
        one-way repeated-measures ANOVAs followed by paired comparisons by parametric
        (Student’s t) and nonparametric (Wilcoxon rank-sum) tests to assess the effect of
        each outcome on the looking times. In communicative context trials, there was no
        difference in looking time between the three outcomes [F(2,46) = 1.06, p =  0.35].
        In non-communicative context trials, there was a main effect of outcome [F(2,46) =
        3.91, p =  0.03, ηp2 = 0.15]. Further analyses revealed significantly shorter
        looking for location change compared to both identity change [t(23) = 2.36 p =
        0.03, ηp2 = 0.19; Wilcoxon’s Z = -2.34, p =  0.02] and no change [t(23) = 2.21 p =
        0.04, ηp2 = 0.18; Wilcoxon’s Z = -1.76, p = 0.08] (note: when using a non-
        parametric test the difference between looking time to location change compared to
        no change was not significant). There was no difference between identity change
        and no change outcomes [t(23) = 0.61, p =  0.55].

        <hss>Scene analysis</hss>

        Figs. 3, 4 and S5 (see Supplementary materials on the OSF) show proportion looking
        to the face, hand, and object AOIs, respectively, for communicative and non-
        communicative scenes. Overall, infants showed similar looking patterns when
        viewing both types of scenes (looking towards the face the most, especially when
        the actress was speaking, looking towards the hand when the point/reach was being
        performed, and very little looking towards the object at any time point). A
        bootstrapped cluster-based permutation analysis found that during both of the
        periods where the hand action (point/reach) was not being performed (0–3000 ms,
        6000–9000 ms), looking towards the face was significantly higher in the
        communicative condition (p = 0.027 and p = 0.048 respectively), and conversely,
        during the first time the action (point/reach) was performed (3000–6000 ms),
        looking towards the hand was significantly higher in the non-communicative
        condition (p =  0.024) (Fig. 4). Looking towards the object was very low overall
        and did not differ significantly between conditions. Overall looking time towards
        the scene did not differ between conditions [t(39) = 0.03, p = 0.98].

        <hss>Replication</hss>

        Our results do not replicate the finding by Yoon et al. (2008) that infants show a
        memory bias for identity information after viewing communicative scenes, and a
        memory bias for location information after viewing non-communicative scenes.
        Neither do we find that communicative scenes disrupt the encoding of location
        information, which is preserved when viewing non-communicative scenes (Marno,
        Davelaar, & Csibra, 2016; Marno et al., 2014; Okumura et al., 2016). Instead, our
        results suggest that infants show longer looking to identity changes regardless of
        communicative context (measured by length of first look). However, we found that a
        minority of infants drove this effect, and that we do not find the results in the
        same direction for total look, weakening our belief that this truly indicates an
        identity memory bias. If we do interpret this result as an identity memory bias,
        this is surprising, given that the default for preverbal infants seems to be to
        encode location over surface features (Carey & Xu, 2001; Haun, Call, Janzen, &
        Levinson, 2006; Mareschal & Johnson, 2003; Xu & Carey, 1996). After this first
        replication attempt, we contacted Csibra, who generously provided detailed
        comments that led to some key methodological changes in Experiment 2.

        <hss>Scene analysis</hss>

        Our results showed that there are differences in where infants allocate their
        attention when viewing communicative and non-communicative scenes. Infants looked
        more towards the face when direct gaze and infant-directed speech were displayed,
        and more towards the hand when a reach was performed than when a point was
        performed. This shows that even before infants are actively communicating
        themselves, they are responding differently when they are being communicated to,
        compared to when they are not. As both communicative and non-communicative scenes
        involved speech and the same sequence of actions, we can reasonably assume that
        differences are due to more specific features of the two types of scene. This
        experiment cannot clarify whether these differences are due to low-level
        perceptual differences or a higher-level understanding of being communicated to.
        We found that infants looked more towards the face when direct gaze and infant-
        directed speech were used. However, in these scenes, this was also when the
        actress was waving to the infant. We could hypothesize that merely the movement of
        waving the hand is more salient than the moving of the head to look at the object
        in the non-communicative scenes, purely because there is more motion involved.
        Alternatively, consistent with Natural Pedagogy account (Csibra & Gergely, 2009),
        infants might look more towards the face when ostensive signals are present
        because they are prepared to learn from the interlocutor. Again, our results
        cannot differentiate between these two interpretations. We also found that infants
        looked more towards the hand when it was reaching than when it was pointing. This
        difference in looking occurred at a different time-point to where we saw
        differences in looking towards the face, suggesting that this is not merely the
        other side of the coin (i.e. when infants are not looking at the face they are
        instead looking at the hand), and is in fact a different process at play. One low-
        level interpretation for this result could be that the hand occupies more space
        when it is a reaching hand than when it is a pointing hand, which could draw the
        infants’ attention. Also, the reaching hand moves around a little, to show that
        the actress is unsuccessfully trying to reach the object, whereas the pointing
        hand does not move. Like the waving in the communicative videos, enhanced hand
        looking in this case could simply be the product of motion drawing the infants’
        attention. Alternatively, as the goal for the reach is to grasp the object,
        infants might fixate on the hand in order to see what happens next (i.e. whether
        the person manages to reach the object), whereas in the communicative condition,
        the goal of the point (to communicate) has been reached as soon as the infant
        perceives and understands it themselves. Again, these data do not speak to which
        of these interpretations is more likely. Our question was not the mechanisms
        behind any attentional differences, but instead whether attentional differences
        could be driving memory biases, and so further research should investigate the
        reasons for these differences. However, as we find an identity bias regardless of
        action condition, these differences in where infants allocate their attention
        cannot be responsible for any memory biases in our experiment. It is also worth
        noting that infants are not looking at the object in either context, suggesting
        that they are not fully understanding the goal, as in both cases the goal is
        either to share attention about an object, or to reach the object. We know that
        12-month-olds anticipate the goal of reaching actions by looking at the object,
        but 6-month-olds do not (Falck-Ytter, Gredebäck, & von Hofsten, 2006), so perhaps
        the infants in our experiment are too young to fully comprehend these goal
        directed actions (but see Kanakogi & Itakura, 2011).

<h>EXPERIMENT 2</h>
------------

After communication with Gergely Csibra (personal communication, November 2017), we were
made aware of some important methodological differences between our replication attempt
and the original study. Most importantly, we found that our interpretation of ‘occlusion
event’ was not the same as theirs. We had interpreted the ‘occlusion event’ as the time
where the occluders were currently closing, whereas they had meant it to mean the time
where the occluders were closing, plus the entire period where the object is currently
occluded. As the original exclusion criteria specified that infants should be excluded if
they had not watched all of the occlusion events without looking away, this meant that we
had essentially used a different exclusion criterion. When we went back to our data to
check which infants would still be included with this new, very strict criterion, we found
that none of them would be. Further discussion with Csibra made it apparent that in Yoon
et al. (2008) the occlusion time had been wrongly reported as five seconds, when in fact,
in the original stimuli this was actually only three seconds. This longer occlusion time,
and the fact that we did not include any music during the occlusion period, may have been
responsible for none of our infants showing continuous looking at the screen during the
whole 5 s occlusion event for all six trials. Therefore, in the second replication
attempt, we shortened the occlusion time to 3 s, added music to the occlusion period, and
changed our exclusion criterion to match that of the original paper. Additionally, this
second replication could serve as a confirmation for our action scene findings, as this
analysis was exploratory in the first attempt.

<hs>  Methods</hs>
  ~~~~~~~

Methods remained overall the same as in Experiment 1, but with the changes to occlusion
duration and exclusion criteria discussed with Csibra.

            <hss>Replication</hss>

            Seventy-nine typically developing 9-month-old infants took part in the
            experiment, and of these twenty-four were included in the replication analysis
            (mean age: 273 days; range: 261 days to 287 days; 13 female; 22 Caucasian; 23
            monolingual English). Infants were excluded for falling asleep (n = 1),
            ceiling looking time for all trials (n = 7), fussiness (n = 14), experimenter
            error (n = 1), and not looking during one or more occlusion events (n = 32).
            An occlusion event in this experiment was defined as the time between the
            first frame of the occluder beginning to close and the first frame of the
            occluder being fully open (this was a crucial difference to Experiment 1).

            <hss>Scene analysis</hss>

            Of the seventy-nine infants who took part in the experiment, sixty were
            included in the scene analysis (mean age: 272 days; range: 260 days to 289
            days; 31 female; 55 Caucasian; 57 monolingual English). Infants were excluded
            for falling asleep (n = 1), fussiness (n = 11), less than 40% good eye-
            tracking data (n = 3), and experimenter error (n = 1).

        <hss>Stimuli</hss>

        Stimuli were the same as in Experiment 1, except for three changes. First
        (outlined above), the objects were occluded for three seconds instead of five.
        Second, there was a larger gap (roughly 5 times wider) between occluders when
        objects were fully occluded. This was to ensure infants could see that the object
        had not moved from one side to the other (and thus, a location change would be
        genuinely surprising). In order to make such gap larger, the third change was that
        the objects were made slightly smaller, and moved further apart, which also made
        the object spacing more comparable to the original study.

        <hss>Procedure</hss>

        The procedure was identical to that of Experiment 1.

            <hss>Replication</hss>

            The analyses were identical to those of Experiment 1. Secondary coding was
            performed on 20% of videos by a second blind coder. A high degree of
            reliability was found between coders. The average measure ICC was 0.95 with a
            95% confidence interval from 0.90 to 0.98.

            <hss>Scene analysis</hss>

            The analysis was identical to that of Experiment 1.

        <hss>Replication: first look length</hss>

        The 2 × 3 ANOVA revealed no significant main effect of outcome [F(2,46) = 0.13, p
        =  0.88] or action [F(1,23) = 0.62, p =  0.44] or significant interaction between
        outcome and action [F(2,46) = 1.32, p = 0.28] (Fig. S4) (Fig. 5). No statistical
        inference can be derived from this non-significant result (Lakens, McLatchie,
        Isager, Scheel, & Dienes, preprint). To determine whether the current data
        provides evidence for the null hypothesis (H0) relative to the alternative
        hypothesis (H1), a Bayes factor was conducted. Bayes factors (BF01) provide a
        measure of how likely the data are assuming H0 is true relative to how likely the
        data are assuming H1 is true. For the current analyses, a default Bayes factor
        with a wide cauchy distribution (scale of effect = 0.707) was calculated using the
        BayesFactor R package (Morey & Rouder, 2015), and yielded BF01 = 4.12. Thus, we
        can conclude that the data constitutes moderate evidence for the null hypothesis.

        <hss>Replication: total look length</hss>

        The 2 × 3 ANOVA revealed a significant main effect of action [F(1,23) = 4.33, p =
        0.05, ηp2 = 0.16], with infants looking longer to all outcome conditions after
        viewing the communicative videos. There was no main effect of outcome [F(2,46) =
        0.09, p =  0.92], or interaction between action and outcome [F(2,46) = 0.01, p =
        0.99] (Fig. S5 on OSF).

        <hss>Scene analysis</hss>

        Our findings from Experiment 1 for the scene analysis were exactly replicated
        (Fig. S6–S8 on OSF). During both of the periods where the hand action
        (point/reach) was not being performed, looking towards the face was significantly
        higher in the communicative condition (p = 0.002 and p = 0.025), and conversely,
        during the first time the action (point/reach) was performed, looking towards the
        hand was significantly higher in the non-communicative condition (p =  0.038).
        There were no significant differences in proportion looking to the object. Overall
        looking time towards the scene did not differ between conditions [t(59) = 0.86, p
        =  0.39].

<hs>  Discussion</hs>
  ~~~~~~~~~~

Our results show no evidence for memory biases, instead showing overall increased
attention to the screen at test after viewing communicative videos. Our scene analysis
results completely replicate findings from Experiment 1, suggesting that the attention
allocation differences found are reliable.

<h>GENERAL DISCUSSION</h>
------------------

We have described two attempts to replicate the results of Yoon et al. (2008). In the
original study, infants looked longer at an identity change following a communicative
context, and longer at a location change following a non-communicative context. These
results were interpreted as a preferential encoding of object identity in a communicative
context. In our first replication attempt, we found longer looking at identity changes
regardless of context. In our second attempt (which, following communication with Csibra
(personal communication November 2017), was better matched to the original study in terms
of stimuli and exclusion criteria), we found no memory biases at all, and instead just
higher increased overall attention to the screen after viewing communicative videos
compared to non-communicative videos. It is important to note the discrepancy in the
results from Experiment 1 and Experiment 2. If we assume that the changes in stimuli and
exclusion criteria in the two experiments did not have a meaningful impact on infant
looking, these results may be due to random fluctuations due to small sample sizes, as
when the two Experiments are combined, we get moderate to high support for the null
hypothesis (see supplementary materials). Alternatively, if we assume that there were key
differences in the stimuli for the two experiments, we should compare results from
Experiment 2 to those found by Yoon et al. (2008), as these are better matched. These
results replicate neither the original study showing a double dissociation of identity and
location memory biases, nor do they replicate other findings of impaired location memory
in communicative contexts (Marno et al., 2014, 2016; Okumura et al., 2016) (Table 1) or
even any memory effects in general (Blaser & Káldy, 2010; Kibbe & Leslie, 2011). It may be
that the method itself is insensitive to measuring infant object memory in this specific
paradigm. Our results could differ from those found by Yoon et al. (2008) because of small
differences in our stimuli such as the size of the faces, the use of superimposed objects
as opposed to real ones, or the distance between the two objects (video examples from Yoon
et al. (2008) are available on the OSF for comparison). It is also possible that some of
these differences had an effect on the higher exclusion rate in our study compared to the
original (70% vs. 57%) due to our videos being potentially less engaging. We did also
purposefully make the methodological changes of the absence of the bars, and of the
matching of the duration of actions in both conditions. However, we have no reason to
assume that any of these factors would affect the postulated creation of memory biases
through the presence or absence of communication. Despite this, it is still impossible to
know whether these (or other) changes could be responsible for the difference in results.
Regardless, these small changes are not accounted for in current theory, which would
predict that with our setup we would find the same result as Yoon et al. (2008). The
original study is a key piece of evidence for the claim of Natural Pedagogy that ostensive
signals not only enhance attention, but also specifically induce an expectation to learn
kind-generalizable information. If small differences to a paradigm can disrupt this, then
this might question the generality of the claims made by this theory, as the changes that
we made should not affect the hypothesized mechanism. It is possible that the current
study is a Type 2 error. This seems unlikely, given that we didn’t replicate in either of
the two attempts, and find moderate support for the null hypothesis using Bayes Factor
Analysis (and moderate to high support for the null hypothesis if we combine the results
from Experiments 1 and 2 – see supplementary materials on the OSF). However, it does
remain possible that the true effect size is smaller than that observed by Yoon et al.
(2008), and that a higher-powered study is needed in order to find an effect. Further
studies on communicatively induced memory biases in infants could also investigate small
methodological changes, in order to see under what specific scenarios the original finding
holds and advance theory about what information infants encode in communicative and non-
communicative contexts. However, due to the extremely high exclusion rate in the second
experiment (70% of infants tested excluded from the replication analysis), this may be a
very demanding and resource consuming challenge. As out of six experiments (Table 1) only
one has shown a specific identity memory bias induced by communication (as opposed to the
loss of location memory), we believe that within this paradigm, the evidence against the
experimental hypothesis is stronger than evidence for it, and we must consider the
possibility that the original result may be a Type 1 error. In order to further study this
hypothesis in a way that doesn’t require more than 50% data loss, we suggest the
development of a new paradigm. Our attention allocation results are robust, with
Experiment 2 completely replicating the results from Experiment 1. We found that at
certain time points infants looked more to the face in communicative contexts than in non-
communicative contexts, and more to the hand when it was reaching than when it was
pointing. These results could be due to low-level perceptual differences between the two
types of scene (e.g. with infants allocating their attention to where there is more
movement), or to a high-level mentalistic interpretation of why infants would pay more
attention to these areas (awaiting communication from the face in the communicative
context, and awaiting the outcome of the reach in the non-communicative context). We
believe there should be caution in attributing rich interpretations to phenomena that
could also be explained by lean, attention-based interpretations (Haith, 1998; Heyes,
2016; Newcombe, 2002). We originally wished to investigate infant attention allocation in
order to relate it to the observed memory biases. As we do not observe any differential
memory biases for different contexts, we cannot relate these attention allocation
differences to memory. What we can say is that attention allocation differences do not
have an impact on what information is encoded or retained in our studies. Nonetheless, we
feel that, when possible, eye-tracking data should be used in looking time studies to rule
out attention allocation differences driving effects.


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<ART>Prosociality from early adolescence to young adulthood: A longitudinal study of individuals with a history of language impairment
================================================================================

Authors: Umar Toseeb, Andrew Pickles, Kevin Durkin, Nicola Botting, Gina Conti-Ramsden
DOI: 10.1016/j.ridd.2017.01.018
Year: 2017  |  Pages: 148-159
ASJC codes: 3203, 3204
Keywords: Early adolescence, Language impairment, Longitudinal, Prosociality, SDQ, Young adulthood

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background Longitudinal research into the development of prosociality contributes vitally to understanding of individual differences in psychosocial outcomes. Most of the research to date has been concerned with prosocial behaviour in typically developing young people; much less has been directed to the course of development in individuals with developmental disorders. Aims This study reports a longitudinal investigation of prosocial behaviour in young people with language impairment (LI), and compares trajectories of development to typically developing age-matched peers (AMPs). Methods and procedures Participants were followed from age 11 years to young adulthood (age 24 years). Outcomes and results Participants with LI perceived themselves as prosocial; their ratings – though lower than those for the AMPs – were well within the normal range and they remained consistently so from 11 to 24 years. Two different developmental trajectories were identified for the LI group, which were stable and differed only in level of prosociality. Approximately one third of participants with LI followed a moderate prosociality trajectory whilst the majority (71%) followed a prosocial trajectory. We found evidence of protective effects of prosociality for social outcomes in young adulthood. Conclusions and implications The findings indicate that prosociality is an area of relative strength in LI. What this paper adds? To our knowledge, this is the first study to examine developmental changes in levels of prosociality from early adolescence to young adulthood in a cohort of young people with LI. Approximately one third of participants with LI followed a moderate prosociality trajectory whilst the majority (71%) followed a prosocial trajectory. We argue that prosociality is different to other areas of functioning in LI. Prosociality appears to be an area of relative strength and can act as a protective factor in social functioning. Prosociality was associated with better community integration in young adulthood and was significantly protective against friendship difficulties for individuals with LI. This paper also raises the thought-provoking issue of potential distal effects of early identification and intensive support for LI. It is important to note that all of the participants with LI in this study had been identified as having language difficulties in childhood and had received intensive intervention for their difficulties in language units attached to mainstream schools across England. The early identification of language difficulties and the context of early, intensive language support received in educational contexts such as language units may have nurtured socialisation processes and the development of emphatic concern, which in turn influence the development of prosociality later in young adulthood. More individual differences in prosociality have been reported for other samples drawn from a variety of schools with different educational provision and levels of language support and younger age groups, such as primary school-aged children with LI.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Prosociality involves behaviours that are positively responsive to others’ needs and
welfare. Examples include being helpful and sharing, showing kindness and consideration,
cooperating with others and expressing empathy and sympathy. Why and how prosociality
develops is not fully understood but theories and evidence point to a multifactorial
process, involving guidance from socialisation agents (such as modelling and reinforcement
by parents or teachers, learning social and moral norms), genetic heritability, and
emotional and social-cognitive development (Eisenberg, Fabes, & Spinrad, 2006; Jensen,
Vaish, & Schmidt, 2014). Most of the research to date has been concerned with prosocial
behaviour in typically developing young people; much less has been directed to the course
of development in individuals with developmental disorders. Young people with disorders
are at greater risk of social exclusion and so the extent to which they do manifest
prosocial behaviours is an important question, with implications for our theoretical
accounts of what factors influence progress in this domain and our understanding of what
influences wellbeing in those with disabilities. In the present paper, we report a
longitudinal investigation of prosocial behaviour in young people with language impairment
(LI), followed through adolescence into early adulthood.

<hs>  Prosociality: developmental change and individual differences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Given that multiple factors bear on prosociality, it is to be expected that prosocial
behaviour will be subject to both developmental changes and individual differences.
Prosocial behaviours are evident from infancy (Liszkowski, Carpenter, & Tomasello, 2008;
Warneken & Tomasello, 2007) but they become more elaborate − and more nuanced − with
development and, at any age, some individuals exhibit them more than others (Eisenberg &
Fabes, 1998). From the toddler years through early childhood, children tend to show an
increase in the frequency of prosocial behaviours (Eisenberg & Fabes, 1998). Through
middle childhood, the findings are more mixed, with some studies suggesting stability
(Cote, Tremblay, Nagin, Zoccolillo, & Vitaro, 2002; Flynn, Ehrenreich, Beron, & Underwood,
2015) but others finding modest declines (Kokko, Tremblay, Lacourse, Nagin, & Vitaro,
2006). During adolescence, some evidence points to a gradual decline in prosocial
behaviours but with a possible rebound in late adolescence/early adulthood (Carlo,
Crockett, Randall, & Roesch, 2007; Kanacri, Pastorelli, Eisenberg, Zuffiano, & Caprara,
2013; Spinrad & Eisenberg, 2009). At all of these stages, the overall picture is qualified
by considerations including the beneficiaries of the behaviour, normative and situational
variables − and individual differences, with different groups of individuals manifesting
different trajectories (Nantel-Vivier et al., 2009). Within individuals, research by
Eisenberg and colleagues on developmental trajectories has revealed significant, albeit
modest, rank-order consistency in prosocial behaviours over time and contexts from the
preschool years to early adulthood (Eisenberg, Miller, Shell, McNalley, & Shea, 1991;
Eisenberg et al., 2002). Longitudinal studies of development from adolescence to adulthood
remain sparse. Three main trajectory groups have been identified: prosocial (and
increasing from adolescence 16/17 years to young adulthood 22/23 years), moderate
prosocial, and low prosocial; the latter two groups having stable trajectories from
adolescence to early adulthood (Kanacri, Pastorelli, Zuffiano et al., 2014). In order to
distinguish the three trajectories found, Kanacri et al. refer to the prosocial trajectory
as “high” prosocial (in relation to what they refer to as moderate and low). However, it
is important to note that the scores for the participants they refer to as “high”
prosocial are close to the average of the 1–9 point scale they used. Analyses from the
same research group working with a large cohort of Italian children have revealed more
variability when trajectories are modelled from early adolescence (age 13 years) to young
adulthood (Kanacri, Pastorelli, Eisenberg et al., 2014). Taken together, findings suggest
that individuals may show some fluctuations in prosocial development from childhood to
young adulthood though radical shifts (e.g., from being low prosocial to becoming
prosocial) are not common. Gender differences in prosociality have been consistently
observed. Generally, girls score more highly than boys on measures of prosociality
(Kanacri et al., 2013) and boys are less likely to follow a high prosociality trajectory
(Nantel-Vivier, Pihl, Cote, & Tremblay, 2014).

<hs>  Prosocial behaviours: positive and protective?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Prosocial behaviours are conducive to positive social relations. Prosocial children are
more accepted and more popular among their peers (Asher & Coie, 1990; Zimmer-Gembeck,
Geiger, & Crick, 2005). In adolescence, prosociality is associated with social bonding and
favourable friendship qualities (Cillessen, Jiang, West, & Laszkowski, 2005; Markiewcz,
Doyle, & Brendgen, 2001). Prosocial behaviour in young adulthood has been found to be
associated with greater involvement in the community (Kanacri, Pastorelli, Zuffiano et
al., 2014). As well as contributing to positive social relationships, there is
accumulating evidence that prosocial attributes and experiences may mitigate the effects
of some factors that place young people at risk of adverse outcomes. Prosocial adolescents
have been reported to be less likely to manifest antisocial and delinquent behaviour
(Carlo et al., 2014; Pursell, Laursen, Rubin, Booth-LaForce, & Rose-Krasnor, 2008).
Participation in prosocial peer relationships appears to provide support for children who
have negative experiences (such as victimisation), facilitating coping and psychosocial
resilience (Griese & Buhs, 2014; Martin & Huebner, 2007).

<hs>  Prosociality and language abilities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Many factors are involved in the development of prosociality, and some of these are
discussed in a large research literature (Eisenberg & Fabes, 1998; Eisenberg, Cumberland,
Guthrie, Murphy, & Shepard, 2005; Eisenberg, Fabes, Spinrad, & 2006). However, an ability
that may contribute to initiating and managing prosocial behaviours has received scant
attention: language. Relatively little research has addressed the extent to which language
ability bears on prosociality in children and young people. Yet language is the primary
medium through which human beings communicate. It is possible to offer help to others, to
share material possessions or emotions, to show kindness and consideration, to express
empathy and sympathy without using language − but the likelihood is that most of these,
and other, prosocial activities will involve speaking and listening, as do most human
interactions from childhood through adolescence and beyond. Within this context,
individuals with language impairment (LI) are of particular interest. How do they fare in
prosocial skills, if they have deficits in expressing themselves and comprehending the
subtleties of others’ language? Language impairment affects approximately 7% of children
at school entry (Tomblin et al., 1997). Children with LI have problems putting words
together (expressive language) and/or understanding what others say to them (receptive
language) in the absence of learning difficulties or sensory problems such as deafness.
There has been and continues to be much debate about the diagnostic criteria and
terminology to describe the difficulties experienced by children and young people with LI
(Bishop, 2014; Reilly et al., 2014). There is consensus however, that although LI is
characterised by language difficulties during childhood, the disorder often persist into
adolescence and young adulthood. There is also consensus that LI is heterogeneous and can
be associated with difficulties beyond language. For example, motor functioning (Finlay &
McPhillips, 2013) and memory abilities (Lum, Conti-Ramsden, Page, & Ullman, 2012). The few
studies involving prosociality in children with LI have been mainly cross-sectional in
design, have involved relatively small numbers of participants, and the findings have been
mixed. For example, it has been found that children with LI attending primary school are
rated by their teachers as being less prosocial and more prone to withdrawal than their
peers. Nonetheless, overall levels of prosociality are not in the abnormal range (Brinton,
Fujiki, Montague, & Hanton, 2000; Fujiki, Brinton, Morgan, & Hart, 1999; Hart, Fujiki,
Brinton, & Hart, 2004), and standard deviations suggest large individual differences
(Bakopoulou & Dockrell, 2016). The one longitudinal study of prosocial behaviours in
children with LI (Lindsay & Dockrell, 2012) followed 65 children from 8 to 16 years, and
examined prosocial behaviours using teacher report. On average, children with LI scored
within the normal range, but there were individual differences. The children in this study
exhibited stable trajectories, with a rise in prosociality evident between the ages of
8–12 years. Thus, the picture emerging to date shows that individuals with LI can
certainly participate prosocially though, overall, they may do so less skilfully and less
successfully than children without LI. Lindsay and Dockrell’s (2012) findings indicate
increases in prosocial behaviour in those with LI in late childhood, which could reflect
general developmental progress and/or gradual improvements in language abilities.
Nevertheless, the amount of evidence available is small and only one study has addressed
longitudinal trajectories in this population. Research on the associations between level
of prosociality and outcomes in individuals with LI in young adulthood, has been scant
(Brinton & Fujiki, 1999; Durkin & Conti-Ramsden, 2007, 2010; Mok, Pickles, Durkin, &
Conti-Ramsden, 2014). In particular, an important question remains unanswered: Does
prosociality confer protection against other developmental risks in the face of LI?

<hs>  The present study: questions and hypotheses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In this investigation we examine longitudinal development of prosociality from early
adolescence (age 11 years) to young adulthood (age 24 years) in young people with and
without a history of LI. The study was motivated by three main questions: Do adolescents
and young adults with LI differ in prosocial orientation to age-matched, typically
developing peers (AMPs)? Do those with LI show similar developmental trajectories to
typically developing youth? And is there any evidence that being prosocial provides a
protective factor, associated with more positive outcomes on other measures of social and
behavioural functioning? With respect to differences between the groups in overall
prosociality, the limited evidence available from studies earlier in development led us to
expect that, on average, the LI group’s prosocial scores should fall in the normal range
but somewhat lower than those of the AMP group (Lindsay & Dockrell, 2012). This would
reflect the facts that individuals with LI have greater difficulties in participating in
social life, tend to be less likely to initiate interactions, and have a lower sense of
independence than AMPs (Brinton & Fujiki, 1999; Brinton, Spackman, Fujiki, & Ricks, 2007;
Conti-Ramsden & Durkin, 2008; Durkin & Conti-Ramsden, 2010). These handicaps present
impediments (though not necessarily insuperable barriers) to positive social interactions
and helpfulness. An alternative hypothesis which should be acknowledged is that, as it is
possible to behave prosocially with relatively little language (as demonstrated by infants
and toddlers), it could be that those with LI could have adapted to their impairments by
finding other ways of demonstrating prosociality. Whether young people with LI show
similar or different trajectory patterns to those of AMPs remains an empirical question.
In terms of their language development, those with LI continue to develop their language
skills into adolescence (Conti-Ramsden, St. Clair, Pickles, & Durkin, 2012) and they
follow similar language trajectories to AMPs, but with a lag (Rice, 2004). As
developmental language problems tend to impact on many other aspects of development, it
could be that patterns of prosocial development in this group would be similar to those of
AMPs, but with the timing of any accelerations or declines delayed. Alternatively, it is
possible that being ‘out of synch’ with the communicative skills development of the
majority of one’s peers puts an individual at risk of lower engagement in social activity
and hence affords less opportunity to develop prosocial skills. Finally, we examined
whether different trajectories of prosociality were more or less protective of behavioural
and social difficulties. Specifically, we examined friendship difficulties, community
integration, aggressive behaviour and rule breaking. We predicted that having higher
prosocial skills should be associated with more favourable outcomes in early adulthood in
both LI and AMP groups.

<hs>  Ethics</hs>
  ~~~~~~

The study reported here received ethical approval from The University of Manchester.

        <hss>Participants with LI</hss>

        Participants with LI (used throughout for ease) had a history of LI and were part
        of the [name of study and references removed for blind-review]. The initial cohort
        of 242 children, which consisted of 186 boys (77%) and 56 girls (23%), were
        recruited from 118 language units across England and represented a random sample
        of 50% of all 7-year olds attending language units for at least half of the school
        week. Language units are specialised classes for children who have been identified
        with primary language difficulties. Individuals were contacted again at ages 8 (n
        = 232), 11 (n = 200), 14 (n = 113), 16 (n = 139), 17 (n = 85), and 24 (n = 84).
        The attrition observed was partly due to funding constraints at follow-up stages
        of the study. The sample of participants with LI did not differ between baseline
        and each of the follow up stages in standard scores of: age 11(receptive language
        (t(240) = 0.42, p = .676), expressive language (t(229) = 1.79, p = .076), or
        nonverbal IQ (t(231) = −.01, p = .991)), age 16 (receptive language (t(240) =
        −0.865, p = .388), expressive language (t(229) = −.64, p = .521), or nonverbal IQ
        (t(231) = −.188, p = .851)), and age 24 (receptive language (t(240) = −1.13, p =
        .261), expressive language (t(229) = −.45, p = .634), or nonverbal IQ (t(231) =
        −.60, p = .545)). Prosociality was ascertained at ages 11, 16, and 24 years. Thus,
        for the current investigation, analyses were undertaken for three time points
        only. These are referred to as time 1 (T1), time 2 (T2), and time 3 (T3).
        Participants were included in the analyses if data were available at least 2 of
        the 3 time points. At T1 (mean age 10 years 11 months, SD 5 months) and T2 (mean
        age 15 years 10 months, SD 5 months), there were 130 participants (92 male and 38
        female). At T3 (mean age 24 years 5 months, SD 9 months) there were 84
        participants (56 male and 28 female). There were 73 LI participants who provided
        data at all three time points.

        <hss>Age-matched peers (AMP)</hss>

        The comparison sample consisted of 65 AMPs (38 male and 27 female) and provided
        data at both T2 (mean age 15 years 11 months, SD 5 months) and T3 (mean age 23
        years 11 months, SD 10 months). The comparison group of peers was selected to be
        of similar age, similar geographical area, and similar socioeconomic background as
        the young people with LI. The comparison group of AMPs were of a similar age to
        the sample with LI at each time point (T2: M 16.4, SD 0.4 years, T3: M 24.1, SD
        0.9 years). AMP participants at age 16 (T2) came from similar geographical
        locations as the sample with LI. AMPs came from the same schools as the
        participants with LI as well as additional targeted schools to ensure a similar
        urban versus rural geographical distribution in both groups. In addition,
        participants in the AMP comparison group were sampled from selected demographic
        areas in order to ensure comparison peers came from a broad range of socioeconomic
        backgrounds, similar to participants with a history of LI. The LI and the
        comparison groups did not differ on household income at age 16years, T2 (χ2(10, N
        = 145) = 9.32, p = .501) nor personal income at age 24 years, T3 (χ2(5, N = 131) =
        7.38, p = .194). AMPs had no history of special educational needs or speech and
        language therapy provision. At T2, 124 AMPs (76 males and 48 females) were
        recruited. Of these, 65 AMPs continued to participate at T3. Those who continued
        to participate at T3 had higher receptive language abilities (t(122) = 3.91, p <
        .001 95% CI [4.32, 13.2]) and PIQ scores (t(122) = 3.09, p = .002 95%CI [3.04,
        13.92]) than those who did not. There were, however, no differences in gender
        (χ2(1, N = 124) = 0.46, p = .497) or expressive language abilities (t(122) = 1.34,
        p = .183 95% CI [−1.71, 8.92]) between those who participated at T3 and those who
        did not. The psycholinguistic profiles of the participants are shown in Table 1.

        <hss>Language and nonverbal IQ</hss>

        The Recalling Sentences subtest of the Clinical Evaluation of Language
        Fundamentals was used to assess expressive language (CELF-R, Semel, Wiig, &
        Secord, 1987; CELF-IV, Semel, Wiig, & Secord, 2003). At T1, the Test for Reception
        of Grammar (Bishop, 1982) was used to assess receptive language. The Word Classes
        subtest of the CELF was used to assess receptive language at T2 (CELF-R) and T3
        (CELF-IV). Nonverbal IQ was measured at T1 and T2 using the Wechsler Intelligence
        Scale for Children Third Edition (WISC-III UK, Wechsler, 1992) and at T3 using the
        Wechsler Abbreviated Scale of Intelligence (Wechsler, 1999).

        <hss>Prosocial behaviour</hss>

        The prosocial subscale of the Strengths and Difficulties Questionnaire (SDQ)
        (Goodman, 1997) was completed by the participants (self-report) at all three time
        points. The scale has good internal reliability (Goodman, Meltzer, & Bailey,
        1998). The scale consists of 5 items each being coded as 0 = Not true, 1 =
        Somewhat true, and 2 = Certainly true. The items were: “I try to be nice to other
        people”, “I usually share with others”, “I am helpful if someone is hurt, upset or
        feeling ill”, “I am kind to younger children”, and “I often volunteer to help
        others”. Sum scores for the subscale range from 0 to 10 and for self-report are
        categorised as “Normal” (6–10), “Borderline” (5), and “Abnormal” (0–4). In a
        population sample of adolescents (Goodman, Lamping, & Ploubidis, 2010), the
        construct validity of the SDQ was shown to be at an acceptable level (factor
        loadings 0.56-0.76). Agreement between parent report and self-report was modest
        (0.34) and test-retest correlations were good (0.62) (Goodman, 2001). The internal
        reliability of prosocial subscale of the SDQ in the sample was good (Cronbach’s α
        = .71). This was comparable to the internal reliability of the subscale in
        population samples of young people (Cronbach’s α = 0.64–0.72, Giannakopoulos et
        al., 2009; Van Roy, Groholt, Heyerdahl, & Clench-Aas, 2006). The prosocial
        subscale is positively skewed in the general population of young people (M 8.0, SD
        1.7, Meltzer, Gatward, Goodman, & Ford, 2000). This is in contrast to the other
        subscales of the SDQ, which measure difficulties, and so are negatively skewed
        (e.g. emotional difficulties M 2.8 SD 2.1). In addition, we examined stability of
        the prosocial subscale across time. An exploratory factor analysis was run for
        each of the three time points using the five items on the SDQ prosocial subscale.
        Inspecting the scree plots and the eigenvalues determined the number of factors.
        The five items loaded onto a single factor with high eigenvalues at each of the
        time points (T1 = 2.34, T2 = 2.04, T3 = 2.34), suggesting stability of the
        prosocial scores across time

        <hss>Friendship difficulties</hss>

        At T3, a Friendship Difficulty Index (FDI) was created based on the Social
        Emotional Functioning Interview (SEF-I, Mawhood, Howlin, & Rutter, 2000).
        Participants were asked questions about their perception of acquaintances (range
        0–2), description of current friendships (range 0–3), and their concept of
        friendship (range 0–3). Scores from the 3 questions were summed to create a total
        score (range 0–8). Higher summed scores indicated more friendship difficulties.
        The reliability of FDI in the sample was very good (Cronbach’s α = .84).

        <hss>Community integration</hss>

        At T3, the Community Integration Measure (CIM, McColl, Davies, Carlson, Johnston,
        & Minnes, 2001) was used. The 10-item checklist (e.g., I feel like part of this
        community, like I belong here) were scored on a 5-point Likert scale: 1 “Always
        disagree”, 2 “Sometimes disagree”, 3 “Neutral”, 4 “Sometimes agree”, 5 “Always
        agree”. Higher summed scores represent a higher level of community integration.
        The reliability of the CIM in the sample was very good (Cronbach’s α = .83).

        <hss>Aggressive and rule breaking behaviour</hss>

        At T3, two subscales of the Achenbach Checklist (Achenbach, 1991) were used:
        Aggressive Behaviour (15 items) e.g. “I argue a lot” and Rule Breaking (14 items)
        e.g. “I don't feel guilty after doing something I shouldn't”. All items were
        scored as 0 “Not true”, 1 “Somewhat or sometimes true”, or 2 “Very true or very
        often”. Higher summed scores indicated more difficulties. For both the aggressive
        behaviour (Cronbach α = .86) and rule breaking (Cronbach α = .72) the reliability
        of the both subscales was good.

<hs>  Informed consent</hs>
  ~~~~~~~~~~~~~~~~

The study reported here received ethical approval from The University of Manchester
Research Ethics Committee, UK. Informed consent was obtained from all individual
participants included in the study. Parents or legal guardians provided informed consent
for all participants up to the age of 16 years. Participants themselves were asked if they
wished to take part (at all phases) and provided written informed consent at ages 16 and
24 years.

<hs>  Procedure</hs>
  ~~~~~~~~~

The participants were interviewed face-to-face at school or at their home on the measures
described above as part of a wider battery. Interviews took place in a quiet room,
wherever possible with only the participant and a trained researcher present. Standardised
assessments of nonverbal and verbal skills were administered in the manner specified by
the test manuals. During the interview, the items were read aloud to the participants. The
items and response options were also presented visually to ensure comprehension. The
authors complied with APA ethical standards in the treatment of the sample.

<hs>  Latent class analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~

All statistical analyses were conducted using Stata/SE 13.1 (StataCorp, 2013). The
‘gllamm’ (generalized linear latent and mixed models; www. gllamm.org; Rabe-Hesketh,
Skrondal, & Pickles, 2004) procedure command was used to model the changes in self-report
prosocial scores across time. Latent classes (or groups) of individuals with similar
patterns over time (Nagin & Odgers, 2010; Pickles & Davies, 1985) were identified using
ordinal logistic models. Although the scale ranged from 0 to 10, there were only a small
number of individuals who scored 0 or 1 (n = 3). Therefore, a score of 0 or 1 was recoded
as 2. In doing this, the scale ranged from 2 to 10. The data was treated as missing at
random. The gllamm command, which was used to for the latent class analysis, makes use of
Maximum Likelihood Estimation to estimate model parameters. Intercept only, linear, and
quadratic models were run with an increasing number of groups. The model used for further
analyses was selected using both statistical goodness-of-fit criteria and
interpretability. The Akaike information criterion (AIC) and Bayesian information
criterion (BIC), which penalises more complex models, were used to assess the model fit.
The most parsimonious model was the one with the lowest criterion value (Pickles &
Croudace, 2010). The chosen model was then used to calculate for each participant the
empirical Bayes’ estimates for the posterior probability of belonging to each trajectory
group, and each participant was assigned to the trajectory group with the highest
posterior probability. In addition, given the developmental period examined in this study
(from childhood to young adulthood) and our aim to investigate mean-level differences over
time, it was deemed necessary to test for scalar invariance of the SDQ prosocial subscale.
We thus re-ran the above analysis using the gllamm command, and included link option
(ologit) for conditional densities. Multiple links were specified using the lv option
(time). The model still yielded a 2 class solution as the best solution, which suggests
scale invariance can be assumed in the interpretation of the findings.

<hs>  Level of prosocial functioning</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Both groups of participants reported prosocial behaviours within the normal range
(clinical cut-off ≤ 4, Goodman, 1997). Mean prosocial scores for participants with LI were
8.0 (SD 2.2), 7.8 (SD 1.9) and 7.9 (SD 1.9) at T1, T2, and T3, respectively and for AMP
mean scores were 8.8 (SD 1.3) and 8.6 (SD 1.5) at T2 and T3. In each group, only a
minority of individuals (between 2 and 6%) reported levels of prosociality in the abnormal
range at one time point. There were no individuals in either the LI or the AMP group who
scored consistently low, in the abnormal range, during the timeframe studied. Prosocial
scores were submitted to a 2 (Group: LI or AMP) x 2 (Time: T2 & T3) mixed ANOVA, with
repeated measures on the latter factor. This analysis yielded a significant main effect of
group, F(1,336) = 14.0, p <. 0001, η2 = .04, but there was no main effect of time, F(1,
336) = .02, p = .90, nor an interaction between the two, F(1, 336) = .26, p = .61. Given
the main effect of group, we undertook latent class analysis for LI and AMP separately.

<hs>  Trajectories of prosociality from early adolescence to young adulthood</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Intercept only, linear, and quadratic models were run with increasing numbers of classes
starting with 1 class. For individuals with LI, the most parsimonious model was the
intercept only 2-class solution. For the AMPs, it was the intercept only 1-class solution.
The model fit statistics are shown in Table 2 and the trajectories are presented in Fig.
1. To aid with the understanding of Fig. 1, mean prosocial scores are presented in Table
3, which demonstrate the stability of prosociality over time. The two distinct LI
trajectory classes (for ease “trajectory” henceforth) had mean scores of 8.6 (1.4) and 6.0
(1.8) respectively. Given that the population mean for the SDQ prosocial subscale for 5–15
year olds is 8.0 (1.7) (Meltzer et al., 2000), we refer to these classes as prosocial and
moderate prosociality respectively. Seventy one percent of LI participants (n = 93) were
classified as following a prosocial trajectory and 29% of LI participants (n = 38) were
classified as following a moderate prosociality trajectory. There was a significantly
larger proportion of females in the prosocial trajectory (89.5% of females vs 63.4% of
males, (χ2(1, N = 131) = 8.88, p = 003). Age-matched peers all followed a prosocial
trajectory with mean scores of 8.7(SD 1.4). It is known that the number of trajectory
classes identified can depend upon the number of measurement occasions available (Lindsay,
Clogg, & Grego, 1991). To investigate this potential effect further, models were fitted
combining the LI and AMP participants into a single sample. The results were very similar
to the findings examining LI and AMP samples separately. The best fitting model was a two-
group intercept only model (prosocial and moderate prosociality) with a comparable number
of LI participants in both groups as found with the LI sample only models. The majority of
AMP participants were classified as following a prosocial trajectory. There were only 4
AMP participants following a moderate prosociality trajectory.

<hs>  Outcomes at age 24</hs>
  ~~~~~~~~~~~~~~~~~~

A number of one-way ANOVAs were run to investigate differences between the three
prosociality groups (LI Moderate Prosociality, LI Prosocial, & AMP) for outcomes at age 24
years (see Table 4). Post hoc comparisons between the prosocial vs moderate prosociality
LI groups revealed that being in the LI prosocial trajectory was significantly protective
in the social domain, specifically friendship difficulties and community integration. No
significant differences between the prosocial vs moderate prosociality LI groups were
observed in the behavioural domains as measured by the Achenbach subscales on aggression
and rule-breaking. Comparisons between LI groups with AMP revealed some significant
differences in social and behavioural domains. The correlations between language, PIQ and
outcomes at age 24 (T3) for study participants can be found in the Appendix A.

<hs>  Language and prosociality: young people with LI are prosocial</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants with LI perceived themselves as prosocial; their ratings were well-within the
normal range and they remained consistently so from 11 to 24 years. Mean prosocial scores
for the group with LI were lower than those of their AMPs but still in the positive range
according to SDQ norms. A history of language difficulties does not therefore preclude
prosociality. On the contrary, prosociality appears to be a distinctive feature within LI.
Children with LI tend to have problems across a range of social and behavioural measures.
For example, using the same instrument, the SDQ, St Clair and colleagues (St. Clair,
Pickles, Durkin, & Conti-Ramsden, 2011) found longitudinal evidence of hyperactivity,
conduct problems, emotional difficulties and problems with peer relations during childhood
and in adolescence in young people with LI. Data from the present investigation, indicate
that prosociality is, in contrast, an area of relative strength, at least from early
adolescence to young adulthood (and see also Lindsay & Dockrell, 2012; for broadly
compatible findings in middle adolescence). To our knowledge, this is the first study to
use latent class analyses to examine age-related changes in levels of prosociality from
early adolescence to young adulthood that includes a sample of young people with LI.
Analyses revealed two different developmental trajectories for the LI group, which were
stable and differed only in level of prosociality. Approximately one third of participants
with LI in this study followed a moderate prosociality trajectory whilst the majority
(71%) followed a prosocial trajectory. These findings corroborate previous longitudinal
research. Kanacri and colleagues (e.g. Kanacri, Pastorelli, Eisenberg et al., 2014) found
that the majority of the participants in their Italian sample were prosocial and their
scores were close to the average for the scale used from age 13–21 years, albeit, this
trajectory showing some quadratic variation across time. These investigators also found a
low prosocial trajectory, which was not evident in this investigation. More variation in
prosociality may be evident in studies like those of Kanacri and colleagues (Kanacri,
Pastorelli, Eisenberg et al., 2014; Kanacri, Pastorelli, Zuffiano et al., 2014) which
involved larger samples (over 500 participants). There are two important points to note.
First, all of the participants with LI had been identified as having language difficulties
in childhood severe enough to warrant attending a specialist educational environment and
not a mainstream classroom. All participants had thus received intensive intervention for
their difficulties in language units attached to mainstream schools across England. All of
the participants had continued to develop their expressive and receptive language skills
during early adolescence to young adulthood (Conti-Ramsden et al., 2012). The early
identification of language difficulties and the context of early, intensive language
support received in educational contexts such as language units may have nurtured
socialisation processes and the development of emphatic concern, which in turn influence
the development of prosociality. Although it is likely that language units would have
varied in their educational practice for inclusion (and access to non-affected peers),
language units themselves afford opportunities for fostering prosociality, for example,
helping others and working together. Lindsay and Dockrell (2012), for example, found more
individual differences in prosociality in their sample of children with LI drawn from a
variety of schools with different educational provision in two geographical areas (one
city, one rural) in the UK. They found a higher proportion of children scoring in the
“abnormal” range at one of the time points they studied (between 18 and 28% of children at
10, 12 and 16 years). The primary school years also appear to be a more vulnerable
developmental period for children with LI. These children tend to be rated by their
teachers as being less prosocial than their peers (Brinton et al., 2000; Fujiki et al.,
1999; Hart et al., 2004). Future research that spans the primary as well as secondary
school years would throw light as to potential developmental changes in prosociality in
children and young people with LI. Second, gender differences in prosociality confirmed
previous research that prosocial behaviours are strongly associated with gender (Carlo et
al., 2007; Kanacri et al., 2013; Nantel-Vivier et al., 2014). There were a significantly
larger percentage of females in the prosocial trajectory as compared to the moderate
prosociality trajectory. It is important to underline these findings, as it is not always
the case that gender differences observed in the general population are also observed in
individuals with developmental difficulties, such as LI. For example, with this same
cohort Conti-Ramsden and Botting (2008) found that the usual gender difference in mental
health in adolescence (where there is vulnerability for females) was not evident in young
adulthood. Prosociality is different. Prosociality appears to be an area of relative
strength in young people with LI and it follows the gender pattern observed in the general
population.

<hs>  Prosociality: higher levels of prosociality are protective in young adulthood</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We found significant small to medium effects for social outcomes in young adulthood. Our
data suggest that prosociality also acts as a protective factor in social functioning for
young people with LI. The results indicated that a prosocial trajectory as compared to a
moderate prosociality trajectory was associated with better community integration in young
adulthood and was significantly protective against friendship difficulties for individuals
with LI. Comparisons between individuals with LI in the prosocial trajectory and same-age
peers also revealed significant differences in relation to friendship difficulties.
However, these findings should be interpreted within the context that both individuals
with LI in the prosocial trajectory and age-matched peers were close to floor on the
measure of friendship difficulties (group friendship difficulties means ranging from
0.1for peers to 0.6 for LI on a 0–8 point scale). It should also be acknowledged that
while we have identified an association between prosociality and better friendships and
better community integration, the association analyses cannot determine causal
relationships, nor the direction of causality. In fact, a case could be made that the
causal direction is the reverse: that is, that these more favourable social circumstances
nurture prosocial behaviour. Nevertheless, our data are very much in line with previous
research with typical populations in studies which do point to protective effects (Carlo,
Crockett, Wilkinson, & Beal, 2011; Cillessen et al., 2005; Markiewcz et al., 2001).
Prosociality, nonetheless, does not provide protection for all areas of functioning. In
LI, associations of prosociality with behavioural functioning were weaker and non-
significant. Comparisons with same age peers revealed individuals with LI exhibited
significantly more aggressive behaviours in young adulthood regardless of their level of
prosociality. These data have important implications for fostering the strengths of young
people with LI. Harnessing and further developing prosocial tendencies may lead to better
social outcomes for young people with LI. We are not claiming that prosociality is the
only factor impinging on friendships and community integration. The picture is complex and
there are individual differences. For example, we know that a third of this same cohort
experience problems with friendship in adolescence and young adulthood (Durkin & Conti-
Ramsden, 2007; Mok et al., 2014; St. Clair et al., 2011). Nonetheless, a medium size
effect size was observed between LI and AMP groups for friendships in this study,
suggesting that in LI, being moderately prosocial may not be enough to confer protection,
a higher “dosage” of prosociality is likely to be required. To our knowledge, there has
not been a systematic effort to build on the prosocial tendencies of individuals with LI
in intervention programmes. It is more common to target areas of deficits rather than
strengths. A good example is intervention research in autism. There is an abundance of
programmes that target improving the social skills and prosocial behaviours of children
and young people with autism spectrum disorders, although the effectiveness of such
interventions has been limited (Bellini, Peters, Benner, & Hopf, 2007; Greenway, 2000). In
future work, it will be important to examine prosociality in young people with LI
longitudinally from an earlier point in development and for research to include both
intervention and observational designs. The inclusion of a broader array of measures of
prosocial behaviours (e.g. experimental tasks and direct observations) is also needed.
Although the SDQ prosocial scale has good reliability and has been used extensively in the
literature, different measures are sensitive to different aspects of prosociality and
their concurrent use may elucidate potential causal pathways to better outcomes for young
people with LI.

<h>CONFLICTS OF INTEREST</h>
---------------------

The authors declare that they have no conflict of interest.


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<ART>Psychological bases of support for radical right parties
========================================================

Authors: Julian Aichholzer, Martina Zandonella
DOI: 10.1016/j.paid.2016.02.072
Year: 2016  |  Pages: 185-190
ASJC codes: 3200
Keywords: Authoritarianism, Personality, Radical right parties, Social dominance orientation, Social threat, Voting behavior

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We examine the social-psychological and personality bases of support for radical right parties (RRPs), using cognitive-motivational approaches of ideology. Our comprehensive model includes core ideological variables which mediate personality traits (Big Five) or how individuals engage in social relationships and accommodate novel stimuli. Structural equation models were tested in an Austrian population sample to examine support for a RRP, the FPÖ. Our results suggest that a "perceived immigrant threat" and, in part, social dominance orientation are directly related to RRP support, whereas right-wing authoritarianism has consistent indirect (mediated) impact. Associations with lower Openness to Experience, lower Agreeableness, and to some extent also with Conscientiousness are mediated by the ideological variables. The conclusion discusses how RRPs' success and communication strategies can be linked to basic psychological motivations.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In recent years, Europe has witnessed growing electoral success of radical right parties
(RRPs). As a “party family” RRPs are commonly characterized by their authoritarian
beliefs, the return to traditional values, anti-immigrant and xenophobic stances, i.e.,
preference for an ethnically homogeneous population, as well as in-group/out-group
thinking that portrays the existence of threats (e.g. Rydgren, 2007). Hence, the focus on
grievances concerning immigration is considered a core feature of the RRP profile (Ennser,
2012; Ivarsflaten, 2008). Meanwhile, empirical research has tried to explain why voters
support RRPs (see Van der Brug & Fennema, 2007). In terms of the social structure, RRP
support was found to be more prevalent among less educated, lower-income, and younger
voters (e.g. Lubbers, Gijsberts, & Scheepers, 2002; Oesch, 2008; Rydgren, 2007). With
regard to policies, preferences on “new” issues, such as anti-immigration policies or EU-
skepticism, are known to attract many RRP voters (e.g. Aichholzer, Kritzinger, Wagner, &
Zeglovits, 2014; Ivarsflaten, 2008; Van der Brug & Fennema, 2007). Yet, the evidence
concerning the role of core ideological dimensions, such as “egalitarian” or
“authoritarian” attitudes, is contradictory (see Cornelis & Van Hiel, 2015; Dunn, 2015;
Zandonella & Zeglovits, 2012). In addition, despite a large body of literature on basic
personality traits as a factor in partisan orientation, few studies have attempted to link
psychological traits (e.g. Big Five) to preference for RRPs (Zandonella & Zeglovits,
2012), extreme right-wing parties (Schoen & Schumann, 2007) or populist parties more
generally (Bakker, Rooduijn, & Schumacher, in press). Furthermore, a coherent theoretical
framework that links social–psychological factors of ideology and personality to core RRP
stances is largely missing in the literature. In the present study, we anticipate that
voters gravitate toward RRPs when they: (a) exhibit authoritarian attitudes (right-wing
authoritarianism, RWA), i.e., motivational goals to seek group security and stability in
societal order (Altemeyer, 1981; Duckitt, 1989); (b) exhibit competitively driven
motivations to maintain hierarchical or superior–inferior relations between social groups
(social dominance orientation, SDO) (Pratto, Sidanius, Stallworth, & Malle, 1994); and (c)
perceive social threats to identity and cohesion induced by immigration and, hence,
exhibit motivations to reduce that uncertainty and threat (Jost, Glaser, Kruglanski, &
Sulloway, 2003). Finally, we propose that (d) these attitudinal factors fully mediate
basic personality traits (Big Five) that might predispose individuals to uphold stability
in social relationships or make them less open to new social situations or stimuli (see
DeYoung, Peterson, & Higgins, 2002). After specifying our hypotheses, we analyze our
theoretical model by using unique representative survey data from Austria. Our outcome
variable is preferences for the Freedom Party of Austria (Freiheitliche Partei
Österreichs), FPÖ, one of the most successful RRPs in Europe.

<hs>  Radical right party support and its relation to RWA and SDO</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It is well established that basic cognitive–motivational goals drive our ideological
orientations, namely advocating vs. resisting social change and rejecting vs. accepting
inequality or RWA and SDO, respectively (see Duckitt & Sibley, 2009; Jost, Federico, &
Napier, 2009, for an overview). Consistent with this framework, RWA and SDO are also
believed to play a role in satisfying epistemic and existential motivations, namely
reducing uncertainty and threat (Jost et al., 2003). Following Altemeyer (1981), the main
perceptional and behavioral consequences (or lower-level structure) of RWA are: (1) to
accept and to adhere to authorities as well as to social norms (“submission”); (2) to
approve of and demand the punishment of people who deny the legitimacy of these
authorities or deviate from these norms (“aggression”); and (3) to be sensitive to threats
to a given social order (“conventionalism”). We thus anticipate that motivational goals of
RWA foster RRP support as these are vital characteristics of RRP stances. In turn, SDO
expresses competitively driven motivations to maintain or establish group dominance and
superiority, i.e., people high on SDO support intergroup hierarchies and tend to arrange
social groups in a superior–inferior order. Thus, SDO should predict a person's acceptance
or rejection of ideologies and policies relevant to group relations (Pratto et al., 1994).
We therefore expect SDO to be positively related to RRP preference. Even though RWA and
SDO can be moderately to strongly positively correlated (Roccato & Ricolfi, 2005), these
factors represent distinct predictors of numerous sociopolitical and intergroup attitudes,
especially political orientation and forms of prejudice (Duckitt & Sibley, 2009; Sibley &
Duckitt, 2008). However, previous evidence suggests that SDO, rather than RWA, might be
more important for party preferences or more directly related to them (Cornelis & Van
Hiel, 2015).

<hs>  Radical right party support and perceived immigrant threat</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To explain RRP support, we further consider a “perceived immigrant threat” (PIT), i.e.,
individuals' perception that immigration threatens their personal or the majority's
societal value system, culture, social cohesion, or alleged ethnic homogeneity. Indeed,
other authors have referred to this tendency as “cultural conflict” dimension (Kriesi et
al., 2008), a “normative threat” (Stenner, 2009), or “symbolic threat” (Stephan & Stephan,
2000). Previous research suggests that this type of threat seems to matter most for RRP
support (Lucassen & Lubbers, 2012; Oesch, 2008), even more so than economic or “material
threats” (on this distinction see Lucassen & Lubbers, 2012; Stephan & Stephan, 2000), or
that these types of threat by immigrants are not empirically distinguishable (Lucassen &
Lubbers, 2012). According to a core component of RRPs' discourse, their supporters seek to
mitigate perceived threats linked to immigration (PIT).

<hs>  RWA, SDO, and social threat</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

In a nutshell, Duckitt and Sibley's (2009) model suggests that scoring high in RWA makes
individuals more sensitive or responsive to types of social threat. Indeed, research has
shown that authoritarians are more responsive to threatening messages (e.g. Lavine et al.,
1999) or that (extreme) right-wing individuals show stronger psychological, but also
physiological responses, to negative or threatening stimuli (e.g. Hibbing, Smith, &
Alford, 2014). We thus anticipate that RWA is an important antecedent of PIT. Another main
hypothesis in Duckitt and Sibley's (2009) theoretical approach is that the relationship
between RWA and political behavior (e.g. party preference) is, at least partly if not
fully, mediated by perceived threats (i.e., PIT). As a consequence, RWA would only have an
indirect effect on RRP support. SDO, on the other hand, is expected to be connected less
strongly, if at all, to societal-level threats or normative threats (Onraet, Van Hiel,
Dhont, & Pattyn, 2013). Instead, it will be related to threats explicitly activating
competitiveness over relative superiority and dominance of groups. We nevertheless test,
but do not expect mediation of SDO on voting preference via PIT.

<hs>  Radical right party support and its linkage to personality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The literature on partisan orientation and individuals' personality mainly builds on the
Big Five model. Based on the extant literature, we anticipate that RRP support is mainly
predicted by lower scores on Openness to Experience (Caprara, Barbaranelli, & Zimbardo,
1999; Chirumbolo & Leone, 2010; Vecchione et al., 2011), higher levels of
Conscientiousness (Chirumbolo & Leone, 2010; Schoen & Schumann, 2007; though with mixed
findings: Vecchione et al., 2011; Zandonella & Zeglovits, 2012), and lower scores on
Agreeableness (i.e., lower trust, altruism or compliance) (Bakker et al., in press;
Chirumbolo & Leone, 2010; Schoen & Schumann, 2007; Zandonella & Zeglovits, 2012).
Furthermore, preliminary evidence suggests that people low in Emotional Stability might
prefer RRPs over other parties (Schoen & Schumann, 2007; Zandonella & Zeglovits, 2012),
whereas Extraversion seems to play a negligible role in voters' behavior (see Gerber,
Huber, Doherty, & Dowling, 2011; Schoen & Schumann, 2007; Zandonella & Zeglovits, 2012).

<hs>  Mediation of personality traits by ideological attitudes</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Relationships between personality and political preferences are likely not to be direct,
but rather indirect or mediated by ideological variables. In particular, RWA is assumed to
have a unique foundation in personality, including social conformity traits or a
combination of Conscientiousness and lower Openness to Experience (e.g. Brown, 1965;
Duckitt & Sibley, 2009). In turn, Emotional Stability should be negatively related to
feelings of threat and insecurity and could thus diminish RWA. SDO seems to be primarily
related to lower Agreeableness (or lower trust, altruism, or compliance), higher
Conscientiousness, and lower Openness to Experience (Sibley & Duckitt, 2008). PIT or
prejudice might be rooted in traits that make people less capable of adapting to new
stimuli and social situations, traits that entail lower levels of altruism or tolerance in
social relationships, or traits that make them more anxious (see Brown, 1965). We
anticipate that Openness to Experience, Agreeableness, and Emotional Stability are
negatively associated with PIT, while Conscientiousness is positively associated with PIT
(e.g. Gallego & Pardos-Prado, 2014; Sibley & Duckitt, 2008). Table 1 and Fig. 1 provide a
summary of our hypotheses and the underlying model for our empirical analyses.

<hs>  Case</hs>
  ~~~~

To test our hypotheses we use data from Austrian voters and support of the FPÖ. In terms
of its policy profile, the FPÖ is considered comparable to other RRPs in Europe (Ennser,
2012) and voting patterns are considered similar to other RRPs (see Aichholzer et al.,
2014; Lubbers et al., 2002). In the last Austrian federal election 2013 the FPÖ gained
20.5% of the valid votes.

<hs>  Data</hs>
  ~~~~

The data used in this study were collected by the Austrian National Election Study
(AUTNES) Pre- and Post-Election Survey (panel) in 2013 (Kritzinger et al., 2013, 2014).
The pre-election interviews were conducted face-to-face (CAPI) and the post-election
interviews by telephone (CATI). Respondents were sampled from the Austrian population
eligible to vote (i.e., aged ≥ 16), using an address-based multistage stratified clustered
sample and selection of a random respondent within each household (total n = 3266, pre-
election response rate: 61.8%; post-election n = 1504 or 46.1% re-interviewed). The sample
composition was: 49.1% male; age: M = 45.3 years, SD = 19.5 years; education: 22.1%
compulsory schooling, 47.3% lower secondary/vocational training, 18.4% admission to
tertiary education, 12.3% college/university degree. Data were weighted for post-
stratification and sample design adjustment.

<hs>  Measures</hs>
  ~~~~~~~~

All measures except actual vote choice were administered in the pre-election wave (see
Appendix A for the exact question wording). For our dependent variable, we rely on two
different operationalizations: first, we use the respondents' “propensity to vote” (PTV)
for the FPÖ (pre-election wave, see Appendix A for exact question wording), which is
measured on a quasi-metric 11-point scale (0 = very unlikely, 10 = very likely, M = 2.75,
SD = 3.17). This measure refers to the general affiliation with a party beyond the vote in
a specific election. Secondly, we employ a binary measure of respondents' “actual vote”
(post-election), which is coded 1 if respondents voted for the FPÖ and 0 for all other
parties, no party/invalid-answers, and excluding voters of the FPÖ splinter group BZÖ (n =
28) to avoid any overlap (16.2% FPÖ). The Pearson correlation between PTV and actual vote
was r = .52. Big Five personality traits were measured using the German BFI-10 (Rammstedt
& John, 2007). Our analyses support the hypothesized five-factor structure of the items,
although it is not regarded as perfectly “clean” (i.e., items have non-ignorable cross-
loadings) (see Table A1 in the Appendix A). We measure PIT based on five items that tap
into the respondents' attitudes and emotions regarding immigrant and cultural threat (vs.
enrichment), since emotional reactions as well as factual attitudes explain perceptions
about immigration (Brader, Valentino, & Suhay, 2008). These are indicated by questions on
concerns about (Muslim) immigrants as well as on respondents' specific emotions towards
immigration, namely anger and anxiety. We also adjust for common method variance in the
two questions capturing emotions (see Table A1). We measure RWA with seven items, spanning
its facets “submission”, “aggression”, and “conventionalism” (Altemeyer, 1981), and apply
correlated uniquenesses (CUs) to capture the conceptual overlap of items in each sub-
dimension (see Table A1). Finally, we measure SDO with two items that strongly resemble
the wording of the original SDO scale by Pratto et al. (1994) (see Appendix A). All
Likert-type items use a fully labeled 5-point rating scale (1 = agree completely to 5 =
disagree completely).

<hs>  Analysis</hs>
  ~~~~~~~~

We use structural equation models (SEM) to take into account unreliability or unsystematic
measurement error in survey measures when analyzing the structural relationships between
variables. Secondly, we take into account systematic acquiescence bias in agree-disagree
items, using a response style factor as a control (Aichholzer, 2014). Thirdly, we allow
for a “complex” (unrestricted) item-factor structure in the BFI-10 scale, applying ESEM
(Asparouhov & Muthén, 2009), which is then held constant across dependent variables (see
Table A1 for the measurement models). Further, we intend to control for socio-demographic
heterogeneity and add age, education (1 = admission to tertiary education), and gender (1
= female) as controls for all latent factors and RRP support (see Fig. 1, detailed results
not presented). All analyses were conducted in Mplus (Version 7) (Muthén & Muthén,
1998-2012), using linear SEM with full information MLR or WLSMV estimation for missing
data. In order to evaluate the models' fit we review the goodness-of-fit indices CFI and
RMSEA [90% CI] and interpret them jointly. A combination of cutoff values CFI > .90 and
RMSEA < .08 is often regarded as acceptable and CFI > .95 and RMSEA < .05 is considered to
be an excellent fit.

<h>RESULTS</h>
-------

Overall, each structural equation model displays at least an acceptable or a good fit to
the data. Furthermore, all models exhibit an equally good fit when allowing for direct
effects of the Big Five traits on RRP support. Thus, it is reasonable to assume full
mediation of effects from these variables. In Table 2 we present direct and total (direct
+ indirect) effects with fully standardized coefficients (β) separately for the two
dependent variables: PTV and actual vote for the FPÖ. Our first empirical test examines
how basic social-psychological factors of ideology are related to RRP support. With regard
to direct effects, PIT strongly (β = .51 and .42) and SDO moderately (β = .22) influences
the PTV for the FPÖ (no mediation), whereas the impact of SDO disappears when the
respondents' actual vote choice is considered (β = .02, n.s.). One reason for this pattern
could be panel attrition effects, since preliminary analyses suggest that the probability
to remain in the panel increases with higher SDO but decreases with higher RWA, whereas
PTV and PIT seem to have no impact. On the other hand, RWA has virtually no significant
direct impact on RRP preference when including SDO and PIT, consistent with previous
evidence suggesting negligible direct effects in the presence of the other variables.
Nevertheless, it is evident that the effect of RWA is mediated by a strong relationship
with PIT (β = .63 and .67), resulting in a highly significant positive total effect with
RRP support (total β = .32 and .50), which is higher for actual voting. Finally, 36% or
39% of the variance in our dependent variables (R2) can be explained by the explanatory
variables in our model. Our second empirical test investigates the relationship of
personality traits with RRP support. Since our results corroborate full mediation via the
ideological variables, we provide indirect (= total) effect estimates of the Big Five on
RRP support. We find that the most consistent and moderate (negative) relationships with
RRP support can be found for Openness to Experience (total β = −.17 and −.18) and
Agreeableness (total β = −.12 and −.14), whereas Conscientiousness displays weak and
inconsistent positive relationships with RRP support (total β = .05 (n.s., p = 0.061) and
.09). Extraversion did not reveal significant or consistent relationships with the
ideological constructs (apart from SDO: β = .08 and −.14), neither with RRP support. In
turn, (lower) Emotional Stability only plays a moderate role for explaining RWA (β = −.15
and −.14), but is irrelevant for FPÖ vote preference. Finally, our results confirm most of
the existing evidence on Big Five associations with RWA, SDO, and PIT as well as on the
relation between RWA and SDO (see Table 2 for detailed results). On the one hand, this
lends support to the criterion validity of our measures. On the other hand, it helps us to
clarify how personality traits are related to RRP support. To sum up, we find that scoring
low in Openness to Experience is directly, and most clearly, related to RWA, to SDO, and
indirectly to PIT, whereas Agreeableness negatively correlates with PIT and in part also
with RWA, resulting in their indirect negative association with RRP support. Surprisingly,
however, we do not find the hypothesized relationship between SDO and lower Agreeableness.
In turn, Conscientiousness is substantially related to RWA, but not to PIT or SDO, thus
being only partly related with RRP support. With regard to socio-demographics and FPÖ vote
preference, education was significantly negatively, though indirectly, related to FPÖ vote
preference (total β = −.21 and −.28), because of consistent negative effects on RWA, SDO,
and PIT (total βs = −.21 to −.33). In turn, higher age displays a moderate negative direct
effect (β = −.20 and −.18), positive relationships with RWA, SDO, and PIT (total βs = .18
to .30), but virtually no total effect. Lower preference for the FPÖ among women only
plays a direct role for PTV (total β = −.07), but not for actual vote.

<h>DISCUSSION</h>
----------

In this study, we provide a comprehensive picture of the interplay between psychological
aspects in voters' preference for radical right parties (RRPs), including personality (Big
Five), authoritarianism (RWA), social dominance orientation (SDO), and a “perceived
immigrant threat” (PIT). Putting the scattered pieces of the puzzle in order, we were able
to comprehensively address the individual differences and social–psychological mechanisms
that drive RRP support. Here, we investigated the case of Austria with an established RRP
in its party landscape, the FPÖ, using representative survey data. To summarize, most of
our initial expectations on the associations between the Big Five and RRP support were in
line with the empirical evidence. Most importantly, we established indirect relationships
(mediation hypothesis) which help us to understand why and how personality explains RRP
support. Among basic social-psychological factors of ideology, PIT most clearly increases
the likelihood of RRP support, SDO has a moderate direct positive impact for PTV, whereas
the association with RWA seems to be indirect. There is reason to believe, however, that
different conceptualizations and measurements of “authoritarianism” explain diverging
evidence on its role in RRP support. In theoretical terms, our findings largely support
the notion of cognitive–motivational goals in individuals, such as managing uncertainty or
threat as well as maintaining stability in societal order and intergroup hierarchies,
which manifest themselves in political ideology and voting behavior (Jost et al., 2003,
2009). In other words, individuals seek to support parties or politicians that match these
goals. Furthermore, our results could be interpreted in the light of basic functions of
personality traits, such as engaging in social relationships through trust and compliance,
on the one hand, as well as the (in)ability of enjoying and processing novel stimuli and
situations, on the other (see DeYoung et al., 2002). The exact personality origins of RRP
support beyond the Big Five or its relation to their more narrow facets nevertheless
deserve to be studied further.

<h>CONCLUSION</h>
----------

What have we learned about the nature and the success of RRPs? With our proposed model we
cannot explain the electoral success of specific RRPs at specific elections. However,
learning about deeply rooted patterns in voters' political preferences adds new insights
to electoral research, particularly in the light of insufficient explanatory power of more
classical theoretical models (see Aichholzer et al., 2014). Furthermore, this also
contributes to our understanding of how appealing political elites' and parties' political
communication is to voters. Our results suggest that a successful RRP offers policy
stances that deliberately address basic psychological motivations and cognitions that are
rooted in voters' personalities and core ideological attitudes. For instance, triggering
social threat and negative emotions associated with immigrants among voters seem to be
effective in RRPs' voter mobilization (see also Brader et al., 2008). Some limitations of
this research must also be considered: first, our results ideally require replication.
Austria may be special due to its particular cultural and historical context (e.g., WWII)
when it comes to political ideology and RRPs. That said, the alignment of RWA and SDO in
the ideological spectrum and with their antecedents can be contingent on the ideological
contrast among parties in a country (see Roccato & Ricolfi, 2005). Second, a common
limitation in large-scale representative surveys are measurement instruments.
Specifically, short measures of complex traits are inherently restricted in their breadth
and, hence, more extensive and cross-culturally invariant scales would be desirable.
Third, future research may want to investigate factors that activate and mediate SDO, such
as actual experiences of intergroup competition (e.g. labor market disadvantage) which, in
turn, may foster RRP support. We also expect future research to further investigate the
RWA lower-level structure, because its sub-dimensions may differ in how they relate to
aspects of social threats and, hence, to vote choice. Further theoretical work and
empirical tests are required to fully understand the role of psychological aspects in
supporting RRPs.


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<ART>Putting mood in context: Using smartphones to examine how people feel in different locations
================================================================================

Authors: Gillian M. Sandstrom, Neal Lathia, Cecilia Mascolo, Peter J. Rentfrow
DOI: 10.1016/j.jrp.2016.06.004
Year: 2017  |  Pages: 96-101
ASJC codes: 3200, 3207
Keywords: Big five, Context, Location, Mobile sensing, Mood, Multi-level modelling, Person-situation, Personality, Positive affect, Within-person

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Does personality predict how people feel in different types of situations? The present research addressed this question using data from several thousand individuals who used a mood tracking smartphone application for several weeks. Results from our analyses indicated that people's momentary affect was linked to their location, and provided preliminary evidence that the relationship between state affect and location might be moderated by personality. The results highlight the importance of looking at person-situation relationships at both the trait- and state-levels and also demonstrate how smartphones can be used to collect person and situation information as people go about their everyday lives.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

We know that personality is linked to behavior. Several studies have shown, for example,
that personality is linked to preferences for and success in various occupations (Judge,
Higgins, Thoresen, & Barrick, 1999; Lodi-Smith and Roberts, 2007), maintaining satisfying
intimate relationships (Ozer & Benet-Martinez, 2006; Roberts, Kuncel, Shiner, Caspi, &
Goldberg, 2007), and how people choose to spend their free time (Mehl, Gosling, &
Pennebaker, 2006; Rentfrow, Goldberg, & Zilca, 2011). Our understanding of these links is
informed by interactionist theories, which argue that individuals seek out and create
environments that satisfy and reinforce their psychological needs. An implication of this
argument is that individuals experience higher positive affect and lower negative affect
when in their preferred environments. Drawing on past research on person-environment
interactions and using experience sampling and mobile sensing technology, the present
research investigated whether personality traits moderate the associations between state
affect and locations, which are associated with different types of situations. Personality
is linked not only to behavior, but also to affect. In one study, situational
characteristics (social vs. non-social context) and personality traits (Extraversion and
Neuroticism) both predicted state positive and negative affect (Pavot, Diener, & Fujita,
1990). People experienced greater positive affect both when they were high in
Extraversion, and when they were in social situations, but there was no interaction:
people with all levels of Extraversion experienced more positive affect in social
situations. In a related study, researchers found that positive affect (but not negative
affect) follows a diurnal rhythm, with people socializing, laughing and singing more and
more for the first 8–10 h after waking, and then doing those activities less and less
(Hasler, Mehl, Bootzin, & Vazire, 2008). Further, this study found preliminary evidence
that this diurnal cycle of positive affect may be amplified for people high in
Extraversion. These findings have implications for within-person variation in personality,
given that affect is assumed to mediate the influence of the situation on personality
states (Mischel & Shoda, 1995). Although there is agreement that features of the
environment affect how people think, feel, and behave, there is less agreement on which
aspects of the environment have psychological implications (Fleeson & Noftle, 2008;
Rauthmann et al., 2014). The physical environment, including location, is one objective
characteristic often associated with a situation (Rauthmann et al., 2014; Saucier, Bel-
Bahar, & Fernandez, 2007). The locations people regularly visit may be consistently
associated with a constellation of factors (e.g., affect, sociability, recreation, goal
pursuit), and thus represent types of situations that have psychological implications, and
clear links to personality For example, the recently developed DIAMONDS taxonomy
identifies several characteristics of situations that might feasibly be linked to
locations (Rauthmann et al., 2014); work might be high in Duty and Intellect, and social
places, such as restaurants and bars, might be high in Sociality and pOsitivity. These
situational factors are connected to personality-related behaviors (Rauthmann et al.,
2014), suggesting that locations should be as well. A challenge in studying affect as it
is experienced in the various types of situations that people encounter in daily life is
the repeated collection of data on mood and situation type. Methodological advances such
as experience sampling have made it possible to collect repeated self-reports (e.g., of
affect) as people go about their daily lives. However, to date it has been difficult to
simultaneously collect objective information about the type of situation in which people
find themselves. One exception is a recent paper that used repeated experience sampling to
examine the relationship between a person’s personality traits, the types of situations
they encountered, and state expressions of personality, all of which were self-reported
(Sherman, Rauthmann, Brown, Serfass, & Jones, 2015). In this study, state personality (as
manifested in behavior and emotions) was independently predicted by both personality
traits and situation characteristics. The advent of mobile sensing technology provides a
potential solution to the challenge of collecting repeated information about both
behaviors and situations: detect the type of situation using the sensors built-into
today’s ubiquitous smartphones. These devices come equipped with location sensors, an
accelerometer that can detect a user’s physical activity, a microphone that can detect
ambient noise in the environment, and various other sensors. The potential is great, but
little research to date has made use of sensed information to examine psychologically
relevant questions. In the present research, we explored the relationship between state
affect and location, which can be thought to represent a type of situation. Our objective
was to lay a foundation of preliminary knowledge in the under-explored domain of
associations between situation types and state affect.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were members of the general public who downloaded the free app from the
Google Play store and installed it on their Android phone. The analyses reported herein
include all users who provided data on the measures of interest (described below) from
February 2013, when the app was released, to July 2015, when we began the analyses. A
total of 12,310 users provided relevant momentary self-reports of location (i.e., they
reported being at home, at work, or in a social type of situation). Of the users who
reported demographics (N = 10,889), 44% of people who reported their gender were female,
71% of people who reported their ethnicity reported being White, and the most common birth
year ranges were 1980–1989 (38%), 1990–1999 (32%) and 1970–1979 (18%). Given that these
users may or may not have provided trait or state self-reports of personality, and may or
may not have provided location sensor data (see Section 2.2 for why this is the case), the
analyses described in the results section include different subsets of these users.
Ethical clearance has not been granted for sharing the data supporting this publication.

<hs>  The Emotion Sense application</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Emotion Sense is a smartphone application that was designed to study subjective well-being
and behavior. The app collects self-report data through surveys presented on the phone via
experience sampling. By default, the app sends two notifications at random moments of the
day between 8 AM and 10 PM, at least 120 min apart from one another. Clicking on a
notification launches a momentary assessment, which includes measures of current affect,
and measures assessing a single aspect of current behavior or context (e.g., location,
physical activity, social interactions). In addition to the notification-driven surveys,
the app also collects self-initiated surveys. These included longer measures of affect,
and measures assessing multiple aspects of behavior and context. As well as collecting
self-report data, the app also uses open-sourced software libraries (Lathia, Rachuri,
Mascolo & Roussos, 2013) to periodically collect behavioral and contextual data from
sensors in the phone. The data collected through the app is stored on the device’s file
system and then uploaded to a server when the phone is connected to a Wi-Fi hotspot.
Emotion Sense was designed to be a tool to facilitate self-insight, providing feedback
about how participants’ mood relates to context and activity. In an effort to maintain
user engagement over a period of weeks, participants could receive additional feedback by
“unlocking” stages, in the same way that players can unlock different levels of a game
after achieving certain objectives. Each stage had a particular theme (e.g., location,
physical activity) that determined which behavior and context questions (e.g., “Where are
you right now?”, “Compared to most days, how physically active have you been today?”) were
asked in the self-report surveys. The second stage, related to location, is the only stage
reported in these results.1

        <hss>Trait personality</hss>

        Users reported their personality on the Ten-Item Personality Inventory (Gosling,
        Rentfrow, & Swann, 2003). They rated the extent to which ten pairs of words (e.g.,
        “Extraverted, Enthusiastic”) applied to them, on a scale from 1 = Disagree
        strongly to 7 = Agree strongly.

        <hss>Affect</hss>

        Emotion Sense allows users to track and quantify their psychological well-being in
        various ways. On each self-report survey, whether notification-driven or self-
        initiated, users indicate their current feelings by tapping on a two-dimensional
        affect grid (see Fig. 1), where the x-axis denotes valence, from negative to
        positive, and the y-axis denotes arousal, from sleepy to alert (Russell, Weiss, &
        Mendelsohn, 1989).

        <hss>Location</hss>

        One way Emotion Sense assesses current location is through place self-reports.
        Users respond to the question “Where are you right now?”, indicating whether they
        are at “Home,” “Work,” “Family/Friend’s House,” “Restaurant/Café/Pub,” “In
        transit,” or “Other” (see Fig. 2). We treated both “Family/Friend’s House” and
        “Restaurant/Café/Pub” as social types of situations, and did not examine “In
        Transit” or “Other” reports. These locations were expected to be ones where people
        spent much of their time, and visited over and over again. Location is also sensed
        via the phone’s location sensors. For 15 min before each survey notification and
        at various intervals throughout the day, Emotion Sense determines the location of
        the phone by collecting the latitude, longitude, accuracy, speed, and bearing of
        the device from its location sensors. This is a coarse measure of location, with
        accuracies ranging from the tens to hundreds of meters, but measuring location
        more accurately consumes far more battery power. A three-step process allowed us
        to match self-report data (e.g., state affect and state personality) to places
        (i.e., home, work, social). First, we mapped each geographical location to a place
        by connecting the location sensor data to the location self-reports. Next, we
        mapped each self-report (e.g., state affect and state personality) to a geographic
        location by connecting the self-report to the temporally closest location sensor
        data. Finally, we mapped these self-report geographic locations to places using
        the mappings created in the first step. (See Appendix 1, Section 2.4 for more
        details.)

<h>RESULTS</h>
-------

We investigated whether a person’s mood is related to the location they are in, and how
that relationship is moderated by trait personality.

<hs>  How is affect related to location?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We created two sets of dummy codes: one set with Home as the reference group (to compare
mood at Home vs. at Work, and at Home vs. in a Social type of situation), and the other
set with Work as the reference group (to compare mood at Work vs. in a Social type of
situation). We ran hierarchical linear modelling, using the lme4 package in R (Bates,
Maechler, Bolker, & Walker, 2014), predicting mood from the place dummy codes (level 1),
grouped by user (level 2). This analysis was carried out for both the location self-
reports, and the locations sensed by the phone sensors. We report results for grid
valence, but see Appendix 1 for analyses examining grid arousal and alternate measures of
high and low arousal positive affect and negative affect. Given that degrees of freedom
are not provided by the lme4 package, we approximated them from the number of level 2
units (i.e., users) minus the number of predictors in the level 2 equation, not including
the intercept, minus 1 (Raudenbush & Bryk, 2002).

        <hss>Self-reported location</hss>

        Of the 12,310 users who provided momentary self-reports of location, 6759 reported
        their mood in at least two of the three targeted locations and were used in these
        analyses. These users provided, on average, 23 reports of location (from 2 to 305
        reports, median = 18). The results from our analyses indicated that participants
        experienced a more positive mood when they reported being in a social type of
        situation (M = 0.34, SD = 0.18) vs. at home (M = 0.20, SD = 0.31), β = 0.29,
        t(6,758) = 38.84, p < 0.001, and when they reported being at home vs. at work (M =
        0.18, SD = 0.25), β = −0.08, t(6,758) = −14.18, p < 0.001. (NOTE: Means and
        standard deviations were computed for each type of location for each person, and
        then averaged across people. They are unstandardized.) For more nuanced results,
        showing differences between high arousal and low arousal positive and negative
        emotions, see Appendix 1.

        <hss>Sensed location</hss>

        Of the 12,310 users who provided momentary self-reports of location, 7582 also
        provided relevant momentary self-reports of mood that could be linked up to
        location readings from the location sensor with some degree of accuracy (see
        Appendix 1, Section 2.4 for details). Of these, 3646 users reported their mood in
        at least two of the three targeted locations and were used in these analyses.
        These users provided, on average, 111 reports of mood (from 2 to 1117 reports,
        median = 88). Consistent with the results for self-reported locations, users
        reported a more positive mood when the phone sensors detected that they were in a
        social type of situation (M = 0.34, SD = 0.17) vs. at home (M = 0.23, SD = 0.32),
        β = 0.20, t(3,645) = 37.22, p < 0.001, and when the phone sensors detected that
        they were at home vs. at work (M = 0.20, SD = 0.27), β = −0.11, t(3,645) = −33.97,
        p < 0.001. For more nuanced results, showing differences between high arousal and
        low arousal positive and negative emotions, see Appendix 1.

<hs>  Does trait personality moderate the relationship between affect and location?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Next we tested whether an individual’s personality traits moderated the relationship
between their location and their state affect. For example, do people high in Extraversion
experience more positive affect in social types of situations compared to people low in
the trait? We created two datasets: (1) a dataset that had only reports from home and
work, and (2) a dataset that had only reports from home and in social types of situations.
Then we ran regressions predicting state affect from the interactions between location
(dummy coded as before) and each of the big five personality traits (standardized across
users), entered simultaneously. When we found significant interactions involving
personality, we examined the simple slopes for low and high values of the personality
trait at −1 and +1 SD from the mean.

        <hss>Self-reported location</hss>

        Of the 6759 users who provided momentary self-reports of location and reported
        their mood in at least two of the three targeted locations, 1434 also self-
        reported trait personality and were included in these analyses. The more positive
        mood associated with being at home vs. being at work was moderated by Openness, β
        = −0.04, t(1,428) = −2.70, p = 0.01, and Agreeableness, β = 0.04, t(1,428) = 3.08,
        p = 0.002 (see Appendix 1 for full model statistics). The mood benefits associated
        with being at home vs. being at work were larger for people who were high in
        Openness, β = −0.14, t(1,428) = −7.24, p < 0.001, than for people low in Openness,
        β = −0.06, t(1,428) = −2.92, p = 0.004. The mood benefits associated with being at
        home vs. being at work were larger for people who were low in Agreeableness, β =
        −0.14, t(1,428) = −7.16, p < 0.001, than for people who were high in
        Agreeableness, β = −0.06, t(1,428) = −3.32, p < 0.001. The more positive mood
        associated with being in a social type of situation vs. being at home was
        moderated by Neuroticism, β = 0.03, t(1,428) = 2.02, p = 0.04. The mood benefits
        associated with being in a social type of situation vs. being at home were larger
        for people who were high in Neuroticism, β = 0.35, t(1,428) = 15.42, p < 0.001
        than for people who were low in Neuroticism, β = 0.28, t(1,428) = 11.37, p <
        0.001.

        <hss>Sensed location</hss>

        Of the 3646 users who reported their mood in at least two of the three targeted
        locations and provided momentary self-reports of mood that could be linked to
        location readings from the location sensor, 651 also self-reported trait
        personality and were included in these analyses. As with the self-reported
        locations, the more positive mood associated with being at home vs. being at work
        was moderated by Openness, β = 0.05, t(645) = 3.64, p < 0.001. Openness showed the
        opposite pattern to the self-reported location data: the mood benefits associated
        with being at home vs. being at work were larger for people who were low in
        Openness, β = −0.18, t(645) = −10.15, p < 0.001, than for people high in Openness,
        β = −0.09, t(645) = −4.73, p < 0.001. The more positive mood associated with being
        in a social type of situation vs. being at home was moderated by Extraversion, β =
        −0.04, t(645) = −1.98, p = 0.05, and Agreeableness, β = −0.05, t(645) = −2.34, p =
        0.02. The mood benefits associated with being in a social type of situation vs.
        being at home were larger for people who were low in Extraversion, β = 0.23,
        t(645) = 8.04, p < 0.001 than for people who were high in Extraversion, β = 0.15,
        t(645) = 5.60, p < 0.001. The mood benefits associated with being in a social type
        of situation vs. being at home were larger for people who were low in
        Agreeableness, β = 0.24, t(645) = 8.04, p < 0.001, than for people who were high
        in Agreeableness, β = 0.15, t(645) = 5.70, p < 0.001.

<h>GENERAL DISCUSSION</h>
------------------

A person’s momentary mood fluctuated in relation to their location (i.e., at home, at
work, and in social types of situations. We used both self-reported location, and location
sensed via smartphone sensors and found remarkably consistent results (on grid valence,
which was reported in the main text, but also on alternate measures of high and low
arousal positive and negative affect, which were reported in Appendix 1). People reported
more positive affect in social types of situations than at home or work. Further, high
arousal positive and negative affect were reported more at work than at home, whereas low
arousal positive and negative affect were reported more at home than at work. We found
some evidence that the more positive mood associated with being in a social type of
situation vs. being at home was moderated by personality. The difference in mood reported
in social types of situations vs. at home was greater for people who were low in
Agreeableness, low in Extraversion or high in Neuroticism. These results are consistent
with the finding that Extraversion and Agreeableness are positively related to high
quality social relationships, whereas Neuroticism is negatively related to high quality
social relationships (Lopes, Salovey, & Straus, 2003; Lopes et al., 2004). Perhaps social
types of situations are associated with greater mood gains for those who generally
struggle more with their social relationships. We also found some evidence that the more
positive mood associated with being at home vs. being at work was moderated by
personality. The difference in mood reported at home vs. at work was greater for people
who were low in Agreeableness. This might suggest that people who are low in Agreeableness
struggle more in their forced interactions with colleagues at work (thus experiencing more
positive affect at home vs. at work), whereas they thrive in their chosen interactions
with friends in social types of situations (thus experiencing more positive affect in
social types of situations vs. at home). These moderation results should be interpreted
with caution for several reasons. First, though significant, these effects were small,
|β|’s ⩽ 0.05. Second, the results were not always the same for the self-reported locations
as they were for the sensed locations. For example, the difference in mood reported in
social types of situations vs. at home was larger for people high in Openness when the
location was self-reported, but larger for people low in Openness when the location was
sensed. Finally, these results conflict with past research, which found additive effects
of trait personality and situation characteristics on expressed behavior and emotion, but
no interactions (Sherman et al., 2015). Further research is necessary to determine whether
these results are reliable. The current results are consistent with an average layperson’s
intuition: when people are asked to reflect on the factors that affect their expression of
traits, they often mention the location (Saucier et al., 2007). Although the physical
characteristics of a location may be directly related to the expression of traits (e.g.,
people may express more Neuroticism in unfamiliar environments, or less Extraversion in
green spaces), it is likely that the psychological characteristics that become associated
with a particular location are actually driving the relationship. For instance, being at
home may be associated with spending time with family, and taking on a more communal role,
whereas being at work may be associated with competition, and taking on a more agentic
role. Rauthmann et al. (2014) proposed eight situational factors with psychological
consequences: Duty, Intellect, Adversity, Mating, pOsitivity, Negativity, Deception,
Sociality. We expect that the three locations we examined varied in many of these factors
(e.g., Intellect may be more of a factor at work than at home or in social types of
situations, whereas Sociality may be more of a factor in social types of situations than
at work or at home); these assumptions could, of course, be tested in a future study.
Future work is needed to determine which characteristics of a situation are active in the
locations that we examined, but also in locations more broadly. This knowledge about what
types of locations are likely to present situations high in each type of characteristic
would allow future mobile sensing studies to sample a more complete set of locations. The
usefulness of mobile sensing for testing questions about person-environment interactions
will depend on its ability to sample from locations with a wide range of situational
characteristics, and its ability to accurately label locations according to their
characteristics with as little user intervention and training as possible. Smartphone
sensors provided a powerful means of passively detecting the type of situation a user is
encountering, and reducing the burden of self-reports in the current study. Their
usefulness in future studies may depend on how capable they are of detecting other
psychologically relevant situational factors. In this study, we focused on using location
sensors to learn the semantics of places, so that we could examine relationships between
place, affect, and personality. Collecting data from other sensors could augment this
analysis, as well as provide other signals that may characterize the type of situation
that a user is encountering. For example, collecting Wi-Fi scans can be used for finer-
grained, indoor localisation (Gao et al., 2011), and bluetooth sensors can be used to
detect co-located bluetooth devices of other study participants (Eagle & Pentland, 2006).
Smartphones’ microphones can be used to measure ambient noise (Lathia, Rachuri, Mascolo, &
Rentfrow, 2013); with sufficient training data, these can even be used to analyze
participants’ speech (Rachuri et al., 2010). Recent work has shown that the ambiance of a
place can also be derived from photographs taken there (Redi, Quercia, Graham, & Gosling,
2015). Work is needed to establish the validity of data from various sensors to assess
psychologically meaningful situational characteristics. One way to establish the validity
of sensor data is to compare it to self-reports, as we did in this study. However, various
decisions need to be made in order to sample sufficient data from the sensors at the right
times and at the right level of detail. In this study, the place label (home, work, or
social) given to a particular geographic location (latitude, longitude pair) was inferred
by matching self-reported location to location sensor data (see Appendix, Section 2.4).
This process has a number of limitations. First, if a participant has never self-reported
their location in a particular geographic area, we cannot make any inferences about that
place. While there are methods that attempt to infer place semantics based on other
signals (e.g., time of day/day of week), we limited our analysis to those places that were
explicitly labelled. We matched location samples with place self-reports based on a fixed
temporal threshold of 15 min; reducing this constant may improve the accuracy of location
inferences, at the expense of reducing the number of labelled self-reports. Finally, we
assumed that a user was in the same place if the two location samples were less than 1600
m from one another. In highly dense urban environments, this may not necessarily be the
case. Even if phone sensors are shown to measure situational characteristics with some
level of validity, work is needed to understand the capabilities and limitations of the
sensors. We used location data that was passively captured from participant’s devices in
order to infer where they were at the time of reporting their state personality or their
mood. While location sensors are broadly reliable (indeed, they are used for mapping
applications), they do not work when a user has disabled their device’s location services,
and they do not work in all types of situations, such as underground or, in some cases,
indoors. Obtaining a highly accurate and recent location sample is possible, but it is a
time- and battery-consuming task, since it requires turning on the GPS sensor, waiting for
it to obtain a satellite fix, and then collecting the data. Instead, we resorted to
collecting coarse-grained data, which is easier and quicker to sample and more energy-
efficient, but may be less accurate. The current results bolster the call for further
research of within-person variation in affect and personality. We found evidence that
people experience fluctuations in state affect when they are in different locations. As
research continues to identify the factors of a situation that are psychologically
meaningful, future work will be able to investigate the interactive effects of various
situational factors on people’s feelings and behavior. The combination of experience
sampling and mobile sensing allowed us to collect large amounts of within-person data in
the current work, and could prove invaluable to further study, to the extent that phone
sensors can objectively measure psychologically active situational variables. The current
study describes how people feel and behave in different locations, but as a field we are
just beginning to learn about the full extent to which feelings and behavior vary by type
of situation.


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<ART>Quantifying compliance and acceptance through public and private social conformity
================================================================================

Authors: Sophie Sowden, Sofia Koletsi, Eva Lymberopoulos, Elisabeta Militaru, Caroline Catmur, Geoffrey Bird
DOI: 10.1016/j.concog.2018.08.009
Year: 2018  |  Pages: 359-367
ASJC codes: 3204, 3205
Keywords: Acceptance, Compliance, Informational influence, Normative influence, Social conformity

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Social conformity is a class of social influence whereby exposure to the attitudes and beliefs of a group causes an individual to alter their own attitudes and beliefs towards those of the group. Compliance and acceptance are varieties of social influence distinguished on the basis of the attitude change brought about. Compliance involves public, but not private conformity, while acceptance occurs when group norms are internalised and conformity is demonstrated both in public and in private. Most contemporary paradigms measuring conformity conflate compliance and acceptance, while the few studies to have addressed this issue have done so using between-subjects designs, decreasing their sensitivity. Here we present a novel task which measures compliance and acceptance on a within-subjects basis. Data from a small sample reveal that compliance and acceptance can co-occur, that compliance is increased with an increasing majority, and demonstrate the usefulness of the task for future studies of conformity.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The multitude of ways in which the behaviour and attitudes of others impact our own has
been studied since the very inception of psychology (Cialdini & Goldstein, 2004). A
particular focus has been the study of how groups influence the behaviour of the
individual, with studies such as those of Asch on social conformity (Asch, 1951, 1955,
1956) some of the most well-known in the field. In these studies participants were asked
to complete a simple perceptual task (judging the length of lines) in a group setting
where, unbeknownst to the participant, the other members of the group were confederates of
the experimenter. During critical trials, despite the task having an obvious answer, the
confederates all gave the incorrect answer. Only a quarter of participants remained
completely independent of the group, with the rest showing various degrees of conformity
towards the group’s responses. Subsequent work has identified various types of group
influence, individuated by factors including the circumstances of the influence (e.g.
whether the group pressure is explicit or implicit), and the nature of the change brought
about in the individual. With respect to the latter, of interest to the current study is
the distinction between compliance and acceptance (Kelman, 1958; Nail, Di Domenico, &
MacDonald, 2013). Compliance and acceptance can be distinguished based on the type of
attitude change brought about by the social influence. Compliance occurs when the
individual publicly agrees with the group but does not change their own attitude or
belief, whereas acceptance occurs when the social influence causes the individual to
internalise the belief or attitude expressed by the group such that it becomes their own.
Compliance and acceptance are thought to arise primarily from normative and informational
influence, respectively (Abrams, Wetherell, Cochrane, Hogg, & Turner, 1990; Deutsch &
Gerard, 1955). Normative influence occurs due to the desire of individuals to be accepted
by the group, or at least not to be publicly in conflict with the group. Abrams et al.
(1990, page 98) suggest that “compliance with the demands and expectations of other group
members and overt agreement with their views occur because of their power to reward,
punish, accept or reject individual members.” In contrast, informational influence is
thought to result in acceptance because it occurs when individuals look to others for
evidence as to the state of the world. As such, its effects are thought to be maximal when
the state of the world is ambiguous, or when the individual is uncertain about a decision
or judgement (Cialdini & Goldstein, 2004; Cialdini & Trost, 1998; Deutsch & Gerard, 1955).
Thus, both informational and normative influence may reduce conflict between beliefs held
by the self and those received from others. However, normative influence involves the
reduction of public conflict with others in a group, whereas informational influence
results in a reduction of conflict between incompatible beliefs within the individual.
Although it is commonly accepted that both types of social influence are typical in
everyday social situations, social conformity effects obtained using the Asch paradigm are
usually attributed to normative influence (compliance) only (e.g. Allen, 1965, 1975; Bond
& Smith, 1996; Turner, 1991). The fact that the perceptual decision task has an obviously
correct answer (participants almost never make errors on trials where confederates give
the correct answer) is usually taken as prima facie evidence that results occur due to
compliance to the group decision through normative influence. This view is not universally
accepted however (e.g. Abrams et al., 1990; Turner, 1985), and claims of an informational
influence are supported by a handful of studies that have compared levels of conformity
using this task between groups of individuals who must respond publicly, and those who
have the opportunity to make their responses in private. The logic of these experiments is
that, by comparing individuals who give their responses in public with those who respond
in private, the relative contributions of normative and informational influence (and hence
compliance versus acceptance) can be established (see Fig. 1). Individuals who respond in
private should experience little to no normative influence due to the fact that the group
members are unaware if they have conformed or not, and thus any group influence should be
due to informational influence alone. Comparison of the degree of social conformity in
private and public groups therefore allows the extent of normative and informational
influence to be established using the standard Asch paradigm. Results of studies which
have compared public and private conformity effects support the existence of an
informational effect in the Asch paradigm as well as a normative effect. For example, Asch
(1956; Experiment 4) found that rates of conformity (the percentage of critical trials
across all participants in which errors in the direction of the confederates’ judgements
were made) dropped from 43% in public conditions to 12.5% in private conditions –
demonstrating a substantial normative influence effect. However, the 12.5% conformity rate
in the private conformity condition was higher than the 1% error rate observed in control
groups who were not subject to group pressure to give incorrect answers. This indicates
the presence of an informational influence, albeit of smaller magnitude than the normative
influence. Abrams et al. (1990) reached a similar conclusion, noting that participants
conformed on an average of 58% of trials when asked to respond publicly, but only 33% when
responding privately (see also Deutsch & Gerard, 1955 [comparison of Experiment 1: face-
to-face condition and Experiment 2: anonymous, no commitment condition], where they
reported a 16% drop in conformity using a privacy manipulation). While it is logically
coherent to compare public and private responses to identify the relative contribution of
normative and informational influence in the Asch paradigm, the current implementation of
this comparison can be improved. Thus far, the manipulation of public and private
responses has been between groups: the public group make their responses as per the
original paradigm, whereas in the private group, although the confederates give their
responses publicly, the participant responds in private. Groups of participants who
respond publicly are then compared with those who respond in private. One issue with this
approach is that comparisons between groups have the potential to be affected by sampling
error and do not account for subject-level variance; as is typical therefore it is likely
that within-subjects comparisons would be more sensitive than between-groups comparisons.
The loss of sensitivity with between-subjects comparisons is especially important when
using techniques with a low signal-to-noise ratio such as functional Magnetic Resonance
Imaging (fMRI), which have been used several times to examine the neural correlates of
conformity-related processes (Berns et al., 2005; Campbell-Meiklejohn et al., 2012a;
Klucharev, Hytönen, Rijpkema, Smidts, & Fernández, 2009; Klucharev, Munneke, Smidts, &
Fernández, 2011). Perhaps more important is the potential confounding effect of asking
participants to respond in private while the confederates, who the participant believes to
be other participants, respond publicly. Abrams and colleagues have argued that the
distinction between the way in which the group of confederates respond (publicly), and the
way in which the participant responds (privately), may result in the participant feeling
like an out-group member. This may cause them to anti-conform to the confederates,
reducing the observed magnitude of any conformity effect due to informational influence.
Ideally then, the private / public response manipulation would be on a within-subjects
level and the participants and confederates would respond in a similar manner. The Asch
task itself has been criticised on a number of methodological grounds, several of which
were noted soon after the Asch experiments were originally published (e.g. Crutchfield,
1955). Chief among these criticisms is the fact that the original Asch task is an
insensitive measure; the choice of only three response options, two of which are very
obviously wrong, presumably means that a great deal of pressure to conform must be
experienced before an incorrect option is chosen. Small effects of social influence are
therefore likely to go undetected. The use of only three response options also means the
size of any conformity effect is impossible to measure; therefore, the degree of
conformity in the task refers to the frequency of conformity across trials, rather than
the size of the effect on any one trial. The use of a continuous response scale would
alleviate these problems, although as far as we are aware continuous response scales have
only been used with ‘off-line’ conformity paradigms where participants do not interact
directly with group members in real life, but instead receive false feedback as to the
responses of a group who had previously completed the task (e.g. Campbell-Meiklejohn et
al., 2012a, 2012b; Klucharev et al., 2009, 2011; Zaki, Schirmer, & Mitchell, 2011). Meta-
analytic work has demonstrated that off-line conformity paradigms result in reduced
conformity effects compared to on-line paradigms in which participants interact with group
members, and off-line paradigms are thought to induce conformity through different
mechanisms to on-line paradigms (Bond & Smith, 1996; Deutsch & Gerard, 1955; Levy, 1960).
This paper therefore reports data obtained from a relatively small sample of participants
primarily to illustrate a novel on-line social conformity task based on the original Asch
paradigm. The task was designed to measure the effects of normative and informational
influence on a within-subjects level utilising public and private responses – thus
identifying whether both compliance and acceptance may be induced in individuals by the
group. Furthermore, participant and confederate responses were obtained using the same
method, eliminating a factor which may have resulted in the participant feeling like an
out-group member and anti-conforming from group responses in previous studies. Finally,
participants were able to use a continuous response scale, meaning that small effects of
social influence could be detected. Participants were asked to take part in a study on
‘the effect of motor preparation on perception.’ They were told that they would be tested
in groups of four, for efficiency, and asked to judge the colour of a patch on a central
screen. They were informed that they would need to type their responses on some trials,
and speak their responses on other trials as the experiment was designed to compare the
effect of preparing a manual versus a vocal response on colour perception. The order of
responding was fixed such that the participant was the last to give a response. Thus,
randomly across trials, it was either the case that the participant and confederates all
typed their responses (baseline trials in which no social influence was present), the
participant typed their response after the confederates had spoken their responses out
loud (private conformity condition), the participant and confederates gave spoken
responses (public conformity condition), or the participant and two of the three
confederates gave a spoken response while one confederate typed their response (‘reduced
majority’ trials in which the participant responded publicly but where the majority
consisted of 2 rather than 3 confederates). Reduced majority trials were also included to
ensure the response style for confederates and participants did not differ across trials
(i.e. all participants experienced private trials). Given previous results (Abrams et al.,
1990; Asch, 1956; Deutsch & Gerard, 1955), three main predictions can be made. First, it
was predicted that conformity would be observed during both public and private conditions,
as indexed by the difference in participants’ responses between trials in which the
confederate responses were congruent (i.e. accurate) and incongruent (i.e. inaccurate)
with respect to the correct response. Second, it was hypothesised that both acceptance and
compliance can be induced in the same individual to bring about conformity. Acceptance and
compliance can be identified, respectively, by an informational influence effect
(indicated by private conformity) as well as a normative influence effect (indicated by
greater public compared to private conformity). Third, it was predicted that the normative
effect (compliance) would be greater in magnitude as the size of the majority increased
from 2 to 3 confederates (Asch, 1955). The presence of reduced majority trials, where only
2 confederate responses are available (compared to 3 on a standard public trial) allow for
this comparison to be made.

<hs>  Participants and design</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Twenty-two healthy adult female individuals (mean age = 21.2 years, SD = 2.8) were
recruited via the King’s College London research recruitment website. Thus, all
participants were either staff or students at King’s College London, from a wide variety
of disciplines. For recruitment to the study, it was a requirement that participants had
not previously studied psychology at college or higher education level. Only female
participants were recruited in order to remove the potential for out-group effects based
on the sex of the participant compared to that of the (female) confederates. Participants
were informed that this was a study investigating the effect of ‘motor preparation on
perception’ and that the investigators were interested in better understanding how motor
preparation for spoken versus typed responses affects visual perception. They were also
told that to speed up data collection, and depending on the number of participants signed
up to the timeslot, they would be tested in a group of up to 4 participants. In fact, each
participant performed the task alongside 3 other individuals, all of whom were
confederates of the experimenter. On arrival participants reported normal or corrected to
normal vision, and they were asked to confirm their area of study, or department in which
they work, at King’s College London. Following the experiment, participants were fully
debriefed as to the true nature of the experiment. During a funnelled debrief – whereby
participants were asked a series of questions which started broad and open-ended and
funnelled to more specific questions to gauge their level of awareness of the true study
aims – it was apparent that only one participant believed their fellow participants in the
experiment to be confederates (and this one additional participant was excluded, leaving
21 participants’ data for analysis).

        <hss>Room and confederate setup</hss>

        The same 3 female confederates performed the task alongside each participant. They
        were undergraduate psychology students from King’s College London (mean age = 20.3
        years), and their mean age did not differ significantly from the mean age of the
        participant sample (p > .05). In each instance, Participant 1 (confederate)
        arrived 15 min prior to the testing slot to ensure they were always first to
        arrive, taking a seat at Position 1 (see Fig. 2 for seating position labels).
        Following this, the real participant would be allowed time to arrive (most
        arriving a few minutes early for the testing session). The experimenter would
        instruct the participant to enter the testing room and take a seat at any laptop.
        To reduce uncontrolled interaction between the participant and confederates prior
        to the task, they were told to sit quietly whilst reading the instruction sheet
        and consent form. Due to the layout of the room, every participant without
        prompting chose to sit at Position 4. With the testing room door open to the half
        way point, Position 2 was blocked for the participant to take a seat in this
        position, and of the two positions remaining, seating themselves at Position 3
        would block another participant’s access to Position 4. Thus, all participants
        followed the same pattern of seating themselves at Position 4 without direct
        instruction from the experimenter. Finally, in each instance, Participant 2
        (confederate) would arrive a minute or two after the participant and take a seat
        at Position 2, followed by Participant 3 (confederate) who would arrive shortly
        after calling to ask for directions to the testing room and take the last
        remaining seat (Position 3). The participant number assigned to the confederates
        was counterbalanced across testing sessions. Finally, the 4 testing laptops (all
        15.6 in., ASUS-Z550C, running Windows 10) were labelled with a sticker denoting
        the participant number prior to the testing session. See Fig. 2 for positions
        corresponding to the participant number assigned during the experiment.

        <hss>Visual perception task</hss>

        The visual perception task was programmed and run using Cogent and Cogent Graphics
        for Matlab. In the task, participants were required to make judgements about the
        colour of squares presented on a large central TV screen (Samsung-DM65D, 65 in.
        display) running Windows 10 software; see Fig. 2 for location in the testing
        room). The colour of the squares could lie anywhere on a scale from white to
        black. Following the presentation of the square, a colour bar was presented on the
        TV screen. Participants were required to give a numerical response, matching the
        colour of the square with the same colour on the colour bar and reporting the
        colour’s numerical value (see Fig. 3). On some trials participants were asked to
        type their response using the numeric keyboard and on others they were asked to
        say their response out loud for the experimenter to write down. These instructions
        were given to each participant on their own laptop screen for each trial. They
        were instructed to pay very close attention to whether they should say or type
        their response on each trial, as this would sometimes differ across participants.
        For example, on any one trial, all participants could be required to say their
        responses out loud, or they may all be required to type their response.
        Alternatively, on some trials, one of the participants may be instructed to type
        their response whilst all other participants were instructed to say their
        response. Ostensibly in order that the experimenter could record the spoken
        responses by hand, participants were instructed to respond in ascending
        participant number order.

            <hss>Single trial structure</hss>

            The experimenter verbally introduced each new trial and the trial number was
            displayed (e.g. ‘Trial 1’, ‘Trial 2’, ‘Trial 3’) on the main TV screen and
            each participant’s laptop screen. Each new trial (see Fig. 3 for a visual
            depiction of one trial) began with the trial number as well as a coloured
            square being presented on the main TV screen for 3 s. The trial number was
            also displayed on the participants’ laptop screens during these 3 s. The
            square was then replaced by a colour bar on the main TV screen (showing every
            shade from black to white; with labels in 10 step increments from 0 to 100),
            and simultaneously, each participant was instructed on their own laptop screen
            whether they should type or say their answer on that trial. Participant 1 then
            made their response, followed by the other participants in ascending
            participant order. On trials where any participant was instructed to type
            their response, their laptop would beep after two digits had been pressed
            using the numeric keyboard. This acted as an auditory cue for the next
            participant to respond. Participants were instructed they could respond using
            any number on the colour bar scale between 01 and 99. At the end of the trial,
            all participants and the experimenter pressed the space bar to move the
            experiment onto the next trial. The protocol began with 10 practice trials,
            followed by 153 trials in the main experiment, including a short break after
            each block of 51 trials. The task took approximately 45 min to complete.

            <hss>Trial type manipulations</hss>

            To allow for public and private performance to be assessed within the same
            task, different trial types were introduced. First, to gauge the participants’
            baseline performance when judging the colour of the squares, there were 18
            ‘silent’ trials during which all participants were instructed to type their
            response. Second, ‘private’ trials were introduced (27 in total) during which
            the participant was required to type their response (and therefore this
            response remained private) whilst all other participants were instructed to
            say their response. All 4 participants (i.e. the real participant plus each of
            the three confederates) experienced their own set of 27 private trials where
            they were required to type their response. These trials constitute the private
            condition when the participant responded privately, and reduced majority
            trials when each of the confederates responded privately. Finally, during
            ‘public’ trials, all participants were instructed to say their response (27 in
            total). Although these trials constitute the public condition for analysis
            purposes it should be noted that on reduced majority trials the participant
            was required to make their response publicly after two responses from
            confederates, therefore these trials could be considered public trials with
            only two confederate responses rather than three. Based on the seminal studies
            of Asch (1951, 1955), one may expect to also see a conformity effect on
            reduced majority trials, although of lesser magnitude than on the public
            trials with three confederate responses. Across the whole experiment,
            responses on 30% of trials for each participant were typed, and 70% spoken.

            <hss>Confederate congruency manipulation</hss>

            In line with Asch’s original conformity studies (Asch, 1951, 1955, 1956),
            within each of the private and public conditions there was a ratio of 1:2
            congruent to incongruent trials. Here, congruency refers to the relationship
            between the correct response and the responses given by the confederates. On
            congruent trials participants gave a correct answer, while on incongruent
            trials they gave an incorrect answer. Confederates were instructed as to which
            response to give via their laptop screens. During each trial, according to the
            trial type, a number was calculated for each confederate as a response by
            taking the correct square colour (e.g. 50) and adding or subtracting values
            from this. On an incongruent trial, 15 was added to or subtracted from this
            value (e.g. 35 or 65), as well as a small amount of jitter between 0 and 3
            (e.g. values between 32 and 38 on a trial where the confederates responded
            lower than the correct response of 50, or between 62 and 68 on a trial where
            the confederates responded higher than the correct response of 50). On a
            congruent trial, however, only the jitter of 0, 1, 2, or 3 was added to or
            subtracted from the correct response (e.g. confederate responses could vary
            between 47 and 53 on a trial where the correct response was 50). This
            procedure was adopted in order to induce some slight variation between
            confederate responses to mask their status as confederates.

<h>RESULTS</h>
-------

For each trial a ‘response discrepancy’ was calculated as the difference between the
participant’s response and the correct response. These values were calculated relative to
the direction of the responses of the confederates. Thus, positive values indicate a
discrepancy in the participant’s response in the direction of the confederates’ responses
and negative values indicate a discrepancy in the opposite direction to that of the
confederates. For example, for a trial where the correct response was 50 and confederates
responded higher on the scale, a response of 55 by the participant would be considered a
response discrepancy of +5, whereas a response of 45 would be considered a response
discrepancy of −5. However, for a trial where the correct response was again 50 but
confederates responded lower on the scale, a response of 55 would be a response
discrepancy of −5, whilst a response of 45 would be a response discrepancy of +5. This
allows for a calculation of the degree to which participants shift their responses towards
or away from the confederates’ responses during private and public trials. The private and
public conformity effects were calculated as the difference between response discrepancies
during their respective congruent and incongruent trials, thus providing a measure of the
informational influence effect (indexed by the size of the private effect) and the
additional normative influence during public trials (indexed by the size of the public
effect minus the private effect). Trials for which response discrepancies were ±2.5
standard deviations from each participant’s mean for each condition were discarded with an
a priori threshold of 15% lost trials for participant inclusion. As it was not necessary
to discard more than 15% of data for any participant, all participants’ data were retained
for full data analysis. Fig. 4 displays mean response discrepancies during each trial
type. As observed in the original Asch paradigm, baseline performance was excellent; the
mean absolute response discrepancy from the correct response during silent trials was 1.42
(standard error of the mean [SEM] = 0.16). When signed rather than absolute scores were
analysed, response discrepancies during silent trials did not significantly differ from 0
[t(20) = 0.40, p = .696]. Thus, participants could perform the task with a high degree of
accuracy when they were not subject to responses of the confederates. Moreover,
performance did not significantly differ from 0 during congruent trials for either private
[t(20) = 1.69, p = .106] or public [t(20) = 0.76, p = .456] conditions. However, in line
with our first prediction, conformity was observed towards the confederates’ responses in
both public and private conditions, whereby response discrepancies were significantly
larger on incongruent trials relative to congruent trials in both the private (private
congruent response discrepancy = 0.57, SEM = 0.34, private incongruent = 2.10, SEM = 0.36;
t(20) = 3.10, p = .006, d = 0.96) and public conditions (public congruent = −0.26, SEM =
0.34, public incongruent = 4.07, SEM = 0.41; t(20) = 7.79, p < .001, d = 2.51). Data were
entered into a repeated-measures two-way ANOVA, with condition (private or public) and
congruency (congruent or incongruent) as within-subjects factors. This revealed no
significant overall difference between performance in private and public trials [F(1, 20)
= 3.67, p = .070, ηp2 = .16], but a significant main effect of congruency [F(1, 20) =
69.76, p < .001, ηp2 = .78] and crucially, a significant condition*congruency interaction
[F(1, 20) = 12.66, p = .002, ηp2 = .39], showing congruency (or conformity) effects to be
significantly larger during public compared to private trials. The conformity effect
during private trials (private incongruent – private congruent response discrepancies) can
be considered to arise from informational influence (i.e. acceptance of the group
response) and this effect is significantly different from 0 [t(21) = 3.10, p = .006]. The
additional conformity effect observed on public trials (public minus private effect) can
be accounted for by normative influence (i.e. compliance to the group), and is also
significantly different from 0 [t(21) = 3.56, p = .002]. Thus, in line with our second
prediction, we see the presence of both informational and normative influence. Moreover,
it is possible to compare the relative magnitude of informational influence (indexed by
the private conformity effect; mean = 1.53, SEM = 0.50) and normative influence (indexed
by public conformity minus private conformity effects; mean = 2.80, SEM = 0.79). The
normative influence is numerically, but not statistically, significantly larger than that
of informational influence [t(20) = 1.06, p = .303]. A significant congruency effect was
also observed on public trials when responses of only two confederates were available to
the participant [i.e. on reduced majority trials; t(20) = 9.05, p < .001, d = 2.73],
whereby response discrepancies were larger during incongruent (mean = 3.21, SEM = 0.32)
than congruent trials (mean = −0.59, SEM = 0.19). To examine our third prediction
concerning the impact of the size of the majority (number of confederate responses
available to the participant) on performance during public trials, we compared performance
between public trials where responses of 2 versus 3 confederates were available to the
participant. Response discrepancies during incongruent public trials were significantly
larger during trials where the majority consisted of 3 confederates (mean = 4.07, SEM =
0.41) than 2 confederates (mean = 3.21, SEM = 0.32; t(20) = 2.72, p = .013, d = 0.51).
Moreover, there was a significantly increased public congruency effect under a majority of
3 (mean = 4.33, SEM = 0.56) compared to 2 (mean = 3.27, SEM = 0.36; t(20) = 2.29, p =
.033, d = 0.49) confederates. Finally, the magnitude of informational and normative
influence can be compared for trials in which only two confederates’ responses were
available to the participant. Once again, the normative influence here (mean = 1.74, SEM =
0.63) is numerically, but not statistically, larger than that of informational influence
(mean = 1.53, SEM = 0.50; t(20) = 0.19, p = .851). The normative influence arising from 3
confederate trials was significantly greater than the normative influence arising from 2
confederate trials [t(20) = 2.29, p = .033, d = 0.32].

<h>DISCUSSION</h>
----------

Compliance and acceptance are types of social influence which can be discriminated on the
basis of their effect on the beliefs or attitude of the individual. Compliance occurs when
the individual publicly accepts the group’s position but privately adheres to their own
belief, while acceptance occurs when the individual internalises the belief or attitude of
the group such that it becomes their own. Compliance is thought to be the result of
normative influence; where the individual complies with group norms due to the social
power of the group. Acceptance is thought to be the result of informational influence;
where individuals seek information from others in order to determine the true state of the
world. The impact of normative and informational influence can be determined through on-
line conformity paradigms by comparing responses made by individuals in private and in
public. Here we report a novel paradigm, based on that of Asch (1951, 1955), in which both
normative and informational influence can be measured on a within-subjects basis. In line
with the first prediction, as well as the original body of work by Asch (1951, 1955,
1956), results indicated significant conformity effects both when participants’ responses
were made in private and when made publicly in front of a group. With respect to the
second prediction, it is thought that private conformity results solely from informational
influence – acceptance of the group response without social pressure to conform – whereas
public conformity results from both informational influence and normative influence –
responding in line with the group in order to publicly comply with them. Crucially
therefore, as has been reported in past comparisons of private and public conformity
(Abrams et al., 1990; Asch, 1955; Deutsch & Gerard, 1955), a greater conformity effect was
observed during public than private trials, demonstrating the presence of both
informational influence in the private condition and the addition of normative influence
during public conditions. Thus, we see demonstrations of both acceptance and compliance
within the same task. Finally, results support the third prediction of increasing
normative conformity with increasing size of the majority, replicating the finding by Asch
(1955) whereby the size of the conformity effect increased as group size increased from 2
to 3. The data reported here suggest that the paradigm is a valid test of social
conformity. Based on Asch’s (1951, 1955) original paradigm, it compared performance on a
test of colour matching in a baseline condition when participants were unaware of the
group’s judgements, when they were aware of the responses of three confederates but could
give their own response in private, and when participants were aware of the responses of
two or three confederates and had to give their responses in public. In common with Asch’s
original findings, participants conformed to the judgements of others in the group;
despite the task being sufficiently easy (participants’ responses were extremely accurate
when not influenced by the group), responses were more inaccurate when the group gave
incorrect responses. Also in common with the findings of Asch was the observation that the
degree of conformity was greater when participants were exposed to three confederates than
two. This was observed even though the ‘degree of conformity’ in the original Asch
paradigm refers to the frequency of conformity, whereas here it refers to the magnitude of
the conformity effect on a per trial basis. The paradigm reported here has the advantage
that measures of normative and informational influence are obtained from the same
individual at the same point in time, facilitating sensitive comparisons as to their
magnitude and enabling future studies using techniques such as fMRI which are reliant upon
within-subject comparisons. In addition, the participant is not excluded from the group
due to their private responses, avoiding the possibility of anti-conformity to the group
judgements which may have influenced prior studies (Abrams et al., 1990). Finally,
although limiting the direct comparison of effect sizes between the current paradigm and
the Asch paradigm, the use of a continuous response scale allowed extremely subtle effects
to be detected on a trial-by-trial and within-subject basis. While the present results are
encouraging, and support the validity of the task as a measure of conformity and its
ability to measure informational and normative influence, it should be noted that the
current study was primarily aimed at task development and validation. Therefore, variance
due to key individual differences previously investigated with the Asch-style paradigm was
deliberately reduced. For example, due to the literature on sex differences in social
conformity (Cooper, 1979; Eagly, Wood, & Fishbaugh, 1981; Larsen, Triplett, Brant, &
Langenberg, 1979), both concerning the sex of the participant and also whether the group
is of the same or opposite sex to that of the participant, the current study included only
female participants and a group of female confederates. Moreover, we restricted our sample
to young adults (aged 19–30 years) to reduce age-related individual differences. The
sample size was also relatively small, likely providing an inexact estimate of the
population effect size. It can be seen then, that although these results support the use
of the task to measure compliance and acceptance, types of social influence thought to
arise from normative and informational influence respectively, further work is required to
establish the replicability of these findings, and how they are moderated by factors such
as age, sex, and culture.

<h>CONCLUSIONS</h>
-----------

Here we present data from a small sample validating a task designed to identify compliance
and acceptance as a result of group influence, and therefore to identify normative and
informational influences on decision-making. Although heavily-based on the conformity
paradigm developed by Asch (1951, 1955), the task has several advantages over previous
versions of the Asch paradigm. First, public and private responding is manipulated on a
within-subjects basis rather than between-subjects, providing a more sensitive measure of
any difference in social influence in the two conditions. This feature also allows
participants to respond in the same manner as confederates, reducing the likelihood that
they will classify themselves as an out-group member. Second, participants were able to
respond on a continuous scale – this enabled a graded measure of conformity to be
established such that the magnitude of any effect on a single trial could be measured and
subtle effects of conformity detected. Results supported previous claims of both normative
and informational influences in Asch-type paradigms, with normative influence increasing
with increasing majority size in such paradigms.


<h>REFERENCES</h>
----------

  [1] Dominic Abrams, Margaret Wetherell, Sandra Cochrane, Michael A. Hogg, John C. Turner. Knowing what to think by knowing who you are: Self‐categorization and the nature of norm formation, conformity and group polarization. doi:10.1111/j.2044-8309.1990.tb00892.x
  [2] Vernon L. Allen. Situational Factors In Conformity. doi:10.1016/S0065-2601(08)60105-7
  [3] Vernon L. Allen. Social support for nonconformity. doi:10.1016/S0065-2601(08)60247-6
  [7] Gregory S. Berns, Jonathan Chappelow, Caroline F. Zink, Giuseppe Pagnoni, Megan E. Martin-Skurski, Jim Richards. Neurobiological correlates of social conformity and independence during mental rotation. doi:10.1016/j.biopsych.2005.04.012
  [8] Rod Bond, Peter B. Smith. Culture and conformity: A meta-analysis of studies using asch's (1952b, 1956) line judgment task. doi:10.1037/0033-2909.119.1.111
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  [10] Daniel K. Campbell-Meiklejohn, Arndis Simonsen, Mads Jensen, Victoria Wohlert, Trine Gjerløff, Jørgen Scheel-Kruger, Arne Møller, Chris D. Frith, Andreas Roepstorff. Modulation of social influence by methylphenidate. doi:10.1038/npp.2011.337
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  [20] Knud S. Larsen, Jeff S. Triplett, William D. Brant, Don Langenberg. Collaborator status, subject characteristics, and conformity in the asch paradigm. doi:10.1080/00224545.1979.9711639
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<ART>Random intercept EFA of personality scales
==========================================

Authors: Julian Aichholzer
DOI: 10.1016/j.jrp.2014.07.001
Year: 2014  |  Pages: 1-4
ASJC codes: 3200, 3207
Keywords: Acquiescence, BFI, Big Five, ESEM, Factor analysis, NEO-FFI, Simple structure

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Previous research suggests that simple structure CFAs of Big Five personality measures fail to accurately reflect the scale's complex factorial structure, whereas EFAs generally perform better. Another strand of research suggests that acquiescence or uniform response bias masks the scale's "true" factorial structure. Random Intercept EFA (RI-EFA) captures acquiescence as well as the complex item-factor structure typical for personality measures. It is applied to the NEO-FFI and the BFI scale to test whether an accurate model-to-data fit can be achieved and whether the "clarity" of the factorial structure improves. The results lend confidence in the general effectiveness of RI-EFA whenever acquiescence bias is an issue. Example M. plus code is provided for replication. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The evaluation of the structure and validity of new and existing measures of psychological
traits or attitudes is a central task in quantitative empirical research. One of the most
important statistical techniques in this area is the common factor model and its variants,
Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). In particular,
this study focuses on assessing the factorial structure of “Big Five” personality trait
measures by means of factor analysis. First, a relatively large body of literature has
shown that the unrestricted EFA model is often better suited to reflect the complex
factorial structure of Big Five scales than the more restrictive “simple structure” CFA
approach (e.g. Asparouhov & Muthén, 2009; Booth & Hughes, in press; Borkenau & Ostendorf,
1990; Hopwood & Donnellan, 2010; Marsh et al., 2010). This is mainly because CFA, or more
precisely, its notion of independent clusters of items assumes that indicators perfectly
measure only one target trait, though this condition is rarely met. Second, the literature
shows that self-report measures are commonly plagued by different sorts of method bias
(see, for an overview, Podsakoff, MacKenzie, & Podsakoff, 2012). Particularly,
acquiescence response style, also known as directional or uniform response bias (hereafter
ARS), has been identified as one of the most important nuisance factors in personality
measurement (e.g. McCrae, Herbst, & Costa, 2001; Rammstedt & Farmer, 2013). It therefore
has become standard to mitigate this problem by using semantically balanced scales in
questionnaires, i.e., using positively (pro-trait) and negatively (con-trait) worded
items. Most importantly, ARS can distort the factorial structure, i.e., convergent and
discriminant validity of the questionnaire items as systematic measurement error is
introduced (Podsakoff et al., 2012). As a consequence, the “true” factorial structure,
especially in multidimensional instruments (e.g. Big Five scales), is misrepresented.
Several approaches have therefore tried to remedy this problem by means of adjustment
techniques that mitigate the impact of ARS, for instance, by using a CFA model of ARS
(Billiet & McClendon, 2000; Maydeu-Olivares & Coffman, 2006) or by subtracting the within-
person mean response from each item, also called ipsatization (Rammstedt & Farmer, 2013).

<h>AIM AND CONTRIBUTION OF THIS STUDY</h>
----------------------------------

In this study I investigate the properties of Random Intercept EFA (RI-EFA) (Aichholzer,
in preparation). RI-EFA treats ARS as an individual random intercept (RI) factor extending
the standard EFA model. In particular, the RI-EFA approach is applicable whenever
multidimensional and semantically balanced scales of psychological constructs or attitudes
are examined. This research demonstrates the usefulness of RI-EFA using two standard Big
Five personality scales, the German versions of the NEO-FFI (Borkenau & Ostendorf, 1993)
and the BFI (Rammstedt & John, 2005). In addition, I test four hypotheses that have been
put forward in previous research: H1: Measurement models with complex item-factor
structure (EFA) commonly fit better to Big Five data than restricted simple structure
models (CFA) (e.g. Hopwood & Donnellan, 2010; Marsh et al., 2010). H2: Measurement models
with adjustment for ARS fit the data better than models without such adjustment (e.g.
Billiet & McClendon, 2000; Maydeu-Olivares & Coffman, 2006). H3: ARS adjustment improves
the clarity of factor loading patterns in ways that approach the ideal “perfect simple
structure” form (e.g. McCrae et al., 2001; Rammstedt & Farmer, 2013). H4: ARS adjustment
improves the clarity of factor loading patterns in particular in populations that are
prone to ARS (e.g. Rammstedt & Farmer, 2013; Rammstedt, Goldberg, & Borg, 2010). H1 is
tested by comparing common model fit criteria of standard CFA with EFA. H2 is tested by
comparing RI-EFA with the other models. H3 and H4 are assessed by comparing empirical
factor loading structures with a perfect simple structure matrix (i.e., perfect −1/0/+1
entries). The contribution of this study is thus twofold: First, a novel method in the
field of factor analysis is tested with regard to its applicability to established scales.
Second, these scales are re-evaluated using this new method.

<h>THE RI-EFA MODEL</h>
----------------

Recently, Aichholzer (in preparation) has presented the RI-EFA model that allows
researchers to combine standard EFA, i.e., an unrestricted or complex item-factor loading
matrix, with a random intercept (RI) factor that represents ARS or uniform response bias
more generally. So far, the latter option was only available for restricted CFA models
(Billiet & McClendon, 2000; Maydeu-Olivares & Coffman, 2006). Further note that the factor
α has a constant loading vector of 1 on all indicators, regardless of their keying (pro-
trait or con-trait), while its variance is freely estimated and tested to be non-zero.1
The RI-EFA model is thus a hybrid model that combines an EFA part where item-factor
loadings are freely estimated and a restricted CFA part where item-factor loadings on the
RI/ARS factor α are restricted to follow a predefined pattern. Due to its specific factor
loading structure α must not be confused with other factors of personality that load on
all items (see Anusic, Schimmack, Pinkus, & Lockwood, 2009). In other words, αi represents
a uniform shift of individual item responses independent from substantial factors. Hence,
it can be considered an issue of differential item functioning (DIF) or violation of
measurement invariance. Furthermore, the model can be estimated quite easily applying the
Exploratory Structural Equation Modeling (ESEM) framework (Asparouhov & Muthén, 2009) and
the Mplus software (Muthén & Muthén, 1998–2012) (see the Appendix A for example Mplus
code).

<hs>  Instruments</hs>
  ~~~~~~~~~~~

This study investigates the German 60-item NEO-FFI (Borkenau & Ostendorf, 1993) and the
German 44-item BFI (Rammstedt & John, 2005). Both the NEO-FFI and the BFI are based on the
Big Five taxonomy of Extraversion (E), Agreeableness (A), Conscientiousness (C),
Neuroticism (N), and Openness to experience (O). All items were measured on a 5-point
scale with endpoints labeled as 1 – strongly disagree to 5 – strongly agree in the NEO-FFI
and 1 – does not apply at all to 5 – applies completely for self-reports in the BFI. In
the sample used here, the Cronbach’s Alpha estimates for the hypothesized Big Five
dimensions were .75 (E), .72 (A), .84 (C), .82 (N), and .66 (O) for the NEO-FFI and .81
(E), .76 (A), .80 (C), .74 (N), and .82 (O) for the BFI. Note that previous research has
already investigated the factorial structure of these instruments using different factor
analytic strategies (Booth & Hughes, in press; Marsh et al., 2010; Rammstedt & Farmer,
2013).

<hs>  Data</hs>
  ~~~~

The NEO-FFI and the BFI were administered in a random sample of the German population
(aged 18 and above) as part of a larger study on personality and political behavior
(Schumann, 2004).2 The total sample with valid demographic data comprised n = 2508
respondents. Age ranged between 18 and 92 (Mean = 49, SD = 17) and 52% of the respondents
were female, 48% male. The NEO-FFI was administered face-to-face, while the BFI was
administered using self-administration as a drop-off (with n = 1492 participants in
total).

<hs>  Analysis</hs>
  ~~~~~~~~

Analyses were conducted with standard simple structure CFA, EFA (or simple ESEM), and RI-
EFA using linear MLR (maximum-likelihood with robust standard errors) estimation as well
as WLSMV (weighted least square mean- and variance-adjusted) estimation for ordered
categorical measures in Mplus 7 (Muthén & Muthén, 1998–2012). Global goodness-of-fit
indices were inspected for each model in addition to the χ2-test. The reason for this is
that χ2-tests commonly result in a rejection of the model when applied to large samples.
According to common fit criteria (see Marsh, Hau, & Wen, 2004), acceptable fit is achieved
when CFI > .90, TLI > .90, and RMSEA < .08, whereas excellent fit is achieved when CFI >
.95, TLI > .95, and RMSEA < .05. Further, better fit of a model is also supported by lower
BIC values. For all empirical analyses the theoretical five-factor structure was imposed
to investigate the hypothesized structure of the NEO-FFI and the BFI. Solutions for the
rotated factor loading matrix in the EFA part were computed applying oblique Quartimin
rotation (for other factor rotation criteria see Asparouhov & Muthén, 2009).

<h>RESULTS</h>
-------

I start by comparing the fit measures for the different modeling strategies (Table 1).
First, the results reconfirm previous evidence suggesting that unrestricted EFA (or simple
ESEM) fits Big Five data considerably better than standard simple structure CFA (see Table
1), which supports H1. Third, as suggested by Hopwood and Donnellan (2010), I compared the
congruence of the empirical factor loading pattern to a perfect simple structure matrix by
assigning each item to its hypothesized factor, using Tucker’s congruence coefficient c
(see Table 2, detailed factor loading results using MLR estimation are available as
supplemental materials). After partialling out the additional RI/ARS factor by means of
RI-EFA, there is convincing evidence in support of further alignment (Δ of congruence) of
items towards the hypothesized five-factor personality structure, which confirms H3. In
other words, the matrix congruence to perfect simple structure is always larger for the
RI-EFA factor loading patterns. Further, the variance explained by the RI/ARS factor can
be computed using squared standardized loadings, 2.8% (NEO-FFI) and 7.5% (BFI) with MLR
estimation, which is largely similar to previous findings (3–4%) (e.g. Anusic et al.,
2009; Billiet & McClendon, 2000). Fourth, I look at subpopulations with potentially
different amounts or unequal variance in ARS. A common proxy is the respondent’s
educational level (Rammstedt et al., 2010) which was operationalized by contrasting “low”
education (lower secondary education or less) vs. “high” education (admission to tertiary
education or completed university degree), whereas “medium” education was omitted. The
results reconfirm that the factor loading congruence to a hypothesized five-factor simple
structure is, in general, lower among less educated respondents. Applying RI-EFA improves
the clarity of factor loading patterns among both groups, though it improves especially
among less educated respondents who filled out the BFI, which partly supports H4. In sum,
the results suggest that applying RI-EFA makes a greater difference for revealing the
“true” structure in the case of the BFI, whereas the impact of response bias on
substantial results seems to be smaller for the NEO-FFI. However, it should be mentioned
that differences between the two instruments may also reflect the use of different survey
modes (F2F vs. P&P).

<h>DISCUSSION</h>
----------

This research shows that RI-EFA can be used as an effective factor-analytic method. It
provides a useful tool for researchers when they would like to investigate the factorial
structure of multidimensional scales based on semantically balanced or heterogeneous
items. The results support the improvement of model-to-data fit and suggest that the
hypothesized factor structure became “clearer” (i.e., it approximated simple structure).
Moreover, given that the identified bias resembles ARS, it may be the preferred method
whenever heterogeneous populations with potentially different response behavior are
studied or when specific measurement conditions apply that evoke such response bias. The
main advantage which makes RI-EFA superior to other approaches, such as Principal
Component Analysis (PCA) of ipsatized data (Rammstedt & Farmer, 2013), is that RI-EFA fits
into the larger family of common factor models and structural equation modeling or ESEM
(Aichholzer, in preparation). Therefore RI-EFA can be extended to testing measurement
invariance over subgroups or over time as well as to testing covariates of the RI/ARS
factor and, hence, causes of such bias. As has been shown, RI-EFA can also be extended to
the case of ordered categorical indicators but also to binary items using WLSMV estimation
(Asparouhov & Muthén, 2009). Nevertheless, there are some limitations to RI-EFA, some of
which apply to the ESEM framework more generally (e.g. Booth & Hughes, in press; Herrmann
& Pfister, 2013; Marsh et al., 2010). Firstly, RI-EFA is neither a strictly exploratory
nor a strictly confirmatory method, but it might be valuable as a “first-step” method in
the sense that it is less rigorous compared to the CFA approach. Second, different
rotation criteria (Quartimin, Geomin, Varimax, etc.) should be examined as factor loadings
and between-trait correlations are dependent on the rotation criterion used. Third, it is
still a matter of debate to what extent the factor scores and associations with covariates
will differ between the different approaches, i.e., CFA, EFA/ESEM, or RI-EFA (also see
Booth & Hughes, in press; Herrmann & Pfister, 2013). Apart from that, quite often the
items in a scale are not fully but partially balanced (e.g. NEO-FFI and BFI), that is,
some subscales use an even number of pro-trait and con-trait items, whereas others are
primarily keyed in one direction. Indeed, the ultimate goal of the RI/ARS factor is that
it conveys all information from balanced subsets of items to also control for ARS in other
items and subscales that are partly or completely unbalanced. One could also let a
selection of balanced item sets define the RI/ARS factor (for a set of items in the BFI
see Rammstedt & Farmer, 2013), whereas loadings are set to +1, and freely estimate
loadings of the remaining items on that factor. Such a model can then be compared to the
basic RI-EFA model (constant loadings of +1). Still, as previously noted (Aichholzer, in
preparation), the construct validity of the RI/ARS factor itself will be higher with an
increasing number of balanced items that come from heterogeneous constructs. However, less
is known about the amount of balancing in scales in order to fully identify and accurately
address the type of bias which is modeled here. Future studies might investigate these
issues in more depth.


<h>REFERENCES</h>
----------

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  [4] Jaak B. Billiet, McKee J. McClendon. Modeling acquiescence in measurement models for two balanced sets of items. doi:10.1207/S15328007SEM0704_5
  [5] Tom Booth, David J. Hughes. Exploratory Structural Equation Modeling of Personality Data. doi:10.1177/1073191114528029
  [6] Peter Borkenau, Fritz Ostendorf. Comparing exploratory and confirmatory factor analysis: A study on the 5-factor model of personality. doi:10.1016/0191-8869(90)90065-Y
  [8] Anne Herrmann, Hans Rüdiger Pfister. Simple measures and complex structures: Is it worth employing a more complex model of personality in Big Five inventories?. doi:10.1016/j.jrp.2013.05.004
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  [11] Herbert W. Marsh, Oliver Lüdtke, Bengt Muthén, Tihomir Asparouhov, Alexandre J.S. Morin, Ulrich Trautwein, Benjamin Nagengast. A New Look at the Big Five Factor Structure Through Exploratory Structural Equation Modeling. doi:10.1037/a0019227
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<ART>Rapid identification of the face in infants
===========================================

Authors: Shuma Tsurumi, So Kanazawa, Masami K. Yamaguchi, Jun Ichiro Kawahara
DOI: 10.1016/j.jecp.2019.05.005
Year: 2019  |  Pages: 45-58
ASJC codes: 3204, 3205
Keywords: Attention, Development, Face, Infant, Rapid serial visual presentation, Temporal processing

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Our visual system can rapidly process stimuli relevant to our current behavioral goal within various irrelevant stimuli in natural scenes. This ability to detect and identify target stimuli during nontarget stimuli has been mainly studied in adults, so that the development of this high-level visual function has been unknown among infants, although it has been shown that 15-month-olds’ temporal thresholds of face visibility are close to those of adults. However, we demonstrate here that infants younger than 15 months can identify a target face among nontarget but meaningful scene images. In the current study, we investigated infants’ ability to detect and identify a face in a rapid serial visual presentation. Experiment 1 examined whether 5- to 8-month-olds could discriminate the difference in the presentation duration of visual streams (100 vs. 11 ms). Results showed that 7- and 8-month-olds successfully discriminated between the presentation durations. In Experiment 2, we examined whether 5- to 8-month-olds could detect the face presented for 100 ms and found that 7- and 8-month-olds could detect the face embedded in rapid serial visual streams. To further clarify the face processing at this age of infants, we tested whether infants could identify upright and inverted faces in rapid visual streams in Experiments 3a and 3b. The results showed that 7- and 8-month-olds identified upright faces, but not inverted faces, during the visual stream, which reflected face inversion effects. Overall, we suggest that the temporal speed of face processing at 7 and 8 months of age would be comparable to that of adults.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The human visual system is highly sophisticated in terms of spatial and temporal
perception. Regarding spatial resolution, human adults are most sensitive to the spatial
frequency at 4–5 cycles per degree, and it takes approximately 6 months for infants to
develop this acuity (Pirchio, Spinelli, Fiorentini, & Maffei, 1978). In terms of temporal
resolution, adults could detect a target picture embedded in a sequence of nontarget
pictures at a rate of merely 113 ms (Potter, 1976) or even 50 ms for letters
(Nieuwenstein, Potter, & Theeuwes, 2008). Currently, it remains unclear whether and when
infants develop such temporal visual faculties. Thus, in the current study, we focused on
the development of infants’ processing of visual information in terms of the time domain
by using the detection and identification of objects, especially faces. Faces convey
critical information for social interaction; thus, the human visual system is
intrinsically biased to prioritize faces over other nonface objects (e.g., Morton &
Johnson, 1991; Reid et al., 2017). Nonetheless, little is known about the temporal aspects
of infants’ face recognition during visually demanding circumstances of brief
presentation. Previous studies have shown that the temporal thresholds of face visibility
are immature in younger infants compared with adults who can accurately detect a human
face presented for less than 100 ms (Gelskov & Kouider, 2010). Specifically, Lasky and
Spiro (1980) examined the visibility thresholds of faces with visual masking and found
that 5-month-old infants could not discriminate faces from other nonface objects presented
for 100 ms followed by a visual pattern mask. Similarly, Gelskov and Kouider (2010) found
that 5- and 10-month-old infants could detect faces at a duration greater than 150 ms,
whereas no such detection occurs at a duration less than 100 ms. These results suggest
that infants aged 5 months require a duration of at least 150 ms to detect faces. Another
recent approach for the development of infants’ vision in the temporal domain has been
made from electrophysiological studies, revealing that the neural mechanism of face
detection would emerge at 5 months. Specifically, de Heering and Rossion (2015) used a
fast periodic visual stimulation consisting of sequential images of objects at 6 Hz with
human faces inserted in every fifth image. The researchers found 1.2-Hz right-lateralized
occipito-temporal categorization responses to faces in 4- to 6-month-old infants.
Similarly, Barry-Anwar, Hadley, Conte, Keil, and Scott (2018) demonstrated that 6- and
9-month-old infants could discriminate individual faces of apes with a 6-Hz presentation.
Kouider et al. (2013) found that even 5-month infants show a face-related event-related
potential (ERP) component of N290 and P400 in response to briefly presented (100 ms) face
images with visual masking. These results suggest that the neural mechanisms begin to
function for detecting visually masked faces even in 5-month-old infants. However, it is
unknown whether these infants could identify a briefly presented face because the studies
described above were designed to determine the ability of infants to detect faces. In
addition, these studies using visual masking procedures only revealed the thresholds of
face visibility. Therefore, infants’ ability to process the target face selectively among
the nontarget but meaningful images in a short duration has not been investigated. The
purpose of the current study was twofold. First, we examined whether infants could detect
individual faces under temporally demanding circumstances of masked rapid serial visual
presentations. Second, we further examined whether infants could identify a face by using
the novel preference and face inversion effect. The presence of ability to identify the
target face during rapid serial visual stream in preverbal infants expands the possibility
that the infants’ cognitive functions, such as nonspatial temporal attention and visual
working memory in the time domain, that these has not been investigated enough, are
working from early age comparable to adults. To achieve this goal in the current study, we
conducted four experiments. First, we examined whether infants could discriminate between
the 100- and 11-ms visual streams during the rapid serial visual presentation. The
literature shows that adults can detect and identify visual images embedded in a rapid
stream of nontarget objects at a rate of 100 ms per item (Potter, 1976) or even faster at
13 ms per item (Potter, Wyble, Hagmann, & McCourt, 2014). The first sets of experiments
examined whether infants could also detect the difference in presentation times
(Experiment 1) or in faces (Experiment 2) at a comparable rate. Subsequent experiments
were devoted to examining infants’ capability of identifying individual faces (Experiments
3a and 3b). Given the behavioral evidence that 5- and 10-month-old infants could detect a
face presented for 150 ms (Gelskov & Kouider, 2010) and the neural evidence that infants
aged 5 months showed the face-related ERP component for faces presented for 100 ms
(Kouider et al., 2013), we predicted that the behavioral and neural system of face
recognition would change substantially from 5 to 8 months of age, as evidenced by the
findings that configural processing would be mature at around 7 months (Schwarzer &
Zauner, 2003). Although this development continues through around 6 years (Freire & Lee,
2001) and even adulthood (Meinhardt-Injac, Persike, & Meinhardt, 2014; Mondloch, Le Grand,
& Maurer, 2002), the findings of 7 months suggested early stages of the development. Thus,
the current study enabled us to track the developmental changes in face detection and
identification of relatively younger infants of 5 to 8 months.

<h>EXPERIMENT 1 (100 VS. 11 MS)</h>
----------------------------

In the current experiment, we investigated whether 5- to 8-month-old infants could
discriminate between 100- and 11-ms rapid serial visual streams. It has been shown that
adults can detect a target image fairly accurately at this rate (Potter, 1976). In
general, adult studies using the rapid serial visual presentation task have presented
stimuli at a rate of 10 items per second (e.g., Potter, 1976). As such, we investigated
whether this presentation time would be applicable to infants. If infants could
discriminate between 100- and 11-ms rapid serial visual streams, similar to adults, then
infants should prefer the 100-ms stream over the 11-ms stream. However, if infants are
unable to discriminate between these two streams, then they should show no preference for
either stream.

        <hss>Participants</hss>

        In total, 20 infants from each age group participated in the experiment (5- and
        6-month-olds: 13 boys and 7 girls, mean age = 164.6 days, SD = 18.06; 7- and
        8-month-olds: 10 boys and 10 girls, mean age = 230.35 days, SD = 17.29). All
        infants were full-term at birth and healthy at the time of the experiment. An
        additional 8 infants were tested but were excluded from the analysis owing to
        their fussiness and/or crying. The infants for the current project were recruited
        through local newspaper advertisements. The current experiment and following
        experiments were approved by the ethical committee of Chuo University, and written
        informed consent was obtained from the parents of the infants participating in the
        experiments prior to testing. The current experiments were conducted in accordance
        with the Declaration of Helsinki guidelines.

        <hss>Apparatus</hss>

        All stimuli were presented on a CRT monitor with a refresh rate of 85 Hz and a
        resolution of 1024 × 768 pixels. There were two loudspeakers, and one was placed
        on either side of the CRT monitor. Each infant sat on a parent’s lap in front of
        the CRT monitor located approximately 40 cm away. There was a small hole below the
        monitor screen for a charge-coupled device (CCD) camera to record the infant’s
        behavior digitally throughout the experiment. This let the experimenter observe
        the infant’s behavior via a monitor connected to the CCD camera. The infant and
        the parent were located inside an enclosure made of plastic poles and a black
        cloth.

        <hss>Stimuli</hss>

        Stimuli were 30 color photographs of various indoor and outdoor scenes. On every
        trial, 15 images, which were pseudorandomly selected from 30 scene images, were
        presented sequentially, and the order of items was the same across the two
        streams. All stimuli were resized to 440 × 330 pixels, subtending 24.3° in width
        and 18.6° in height. The two streams were presented to either the right or left
        from the center of the monitor at a distance of 1.4° on each side from the center
        of the monitor.

        <hss>Procedure and design</hss>

        We presented two visual streams consisting of 15 images side by side for 10 s, and
        the presentation rate was 105 and 11.7 ms per item for the 100- and 11-ms streams,
        respectively; neither had an interstimulus interval. The order of images was
        maintained for each stream during a trial. Both streams were repeated throughout a
        trial, resulting in 100 and 909 images for the 100- and 11-ms streams,
        respectively. The side at which 100 or 11 ms appeared was maintained with the
        infants but was counterbalanced across infants. Three trials were conducted for
        all infants. We measured the infants’ looking behavior during the two streams
        using a preferential looking paradigm. Before the experiment started, the parents
        were instructed to close their eyes and not to talk to their infants throughout
        the experiment to prevent the parents’ behavior from influencing the infants. At
        the beginning of every trial, a cartoon (10.0° × 14.3°) was shown in the center of
        the monitor accompanied by a brief sound to obtain the infants’ fixation to the
        center of the monitor. The experimenter initiated each trial as soon as the infant
        fixated on the cartoon.

        <hss>Data analysis</hss>

        A coder, who was blind to the stimuli, measured the infants’ looking time for each
        stream by pressing one of two keys corresponding to the right and left
        presentation fields while the infants were looking at the monitor based on the
        offline video movie. When the infants looked away from the monitor, no key
        responses were recorded. In addition, the video recordings of the looking behavior
        of 10 infants were analyzed by a second observer who was not informed of the
        objectives of our study. The intercoder reliability was r = .98 (p < .05). We
        calculated the individual preference score for the 100-ms stream by dividing the
        infants’ looking time to the 100-ms stream across three trials by the total
        looking time across the three trials. We regarded the infants’ preference for the
        100-ms stream as the index of discrimination of the two visual streams.

<hs>  Results</hs>
  ~~~~~~~

We computed the preference scores for the 100-ms stream across each infant to assess
whether the infants differentiated between 100- and 11-ms streams. The mean preference
scores to the 100-ms stream for the two age groups are shown in Fig. 1. A two-tailed one-
sample t test (vs. the chance level of .50) revealed that the 7- and 8-month-olds
preferred the 100-ms stream over the 11-ms stream, t(19) = 4.38, p = .01, d = 0.98. This
pattern of results was not obtained for the 5- and 6-month-olds; no preference was found
for this age group, t(19) = −0.02, p = .98, d = 0.00. We found a developmental difference
in the preference score between 5- and 6- month-olds and 7- and 8-month-olds, t(38) =
2.14, p = .04, d = 0.68. One may argue that the preference for the 100-ms stream over the
11-ms stream in 7- and 8-month-olds is due to an aversion to the faster rate stream;
however, if this were true, there should have been a preference for the 100-ms stream in
5- and 6-month-olds as there was in 7- and 8-month-olds. These results suggest that the 7-
and 8-month-olds were able to discriminate the two streams, possibly reflecting that the
100-ms presentation rate would be available in infants.

<h>EXPERIMENT 2 (UPRIGHT VS. INVERTED)</h>
-----------------------------------

The results of Experiment 1 indicated that the 7- and 8-month-old infants preferred the
100-ms stream over the 11-ms stream. However, this does not necessarily mean that the
infants precisely perceived and identified every object represented in the images in the
100-ms stream. Rather, the results can imply that they hardly saw clear pictures from both
streams and merely picked a limited number of segmented portions of the images more
frequently in the 100-ms stream than in the 11-ms stream. In the latter case, we cannot
conclude that the 7- and 8-month-olds could perceive the images embedded in the 100-ms
stream. To exclude this concern, we examined whether 5- to 8-month-old infants could
detect a specified target in the 100-ms stream in Experiment 2. Two female faces were
presented as a target. Infants viewed two side-by-side streams of rapidly presented visual
sequences at a rate of 100 ms per image. One stream contained an upright face, and the
other stream contained its inverted version. We tested whether infants exhibit a
preference for the stream containing the upright face. We predicted that infants who could
detect the upright face should prefer the stream including the upright face more
frequently than the stream containing the inverted face (Farroni et al., 2005; Mondloch et
al., 1999).

        <hss>Participants</hss>

        In total, 20 infants for each age group who were full-term at birth and healthy at
        the time of the experiment participated in the experiment (5- and 6-month-olds: 9
        boys and 11 girls, mean age = 173.4 days, SD = 14.39; 7- and 8-month-olds: 9 boys
        and 11 girls, mean age = 230.15 days, SD = 15.31). An additional 6 infants were
        tested but were excluded from the analysis owing to their fussiness and/or crying.
        A side bias was defined as a tendency to look at only one side at more than 90% of
        the looking time.

        <hss>Stimuli</hss>

        The apparatus was identical to that used in Experiment 1. The 30 color photographs
        presented in Experiment 1 and two color photographs of Japanese female faces taken
        in frontal view showing a neutral expression with a gray background were used. The
        image size of the two female faces was the same as the size of the natural images
        (24.3° × 18.6°). In every trial, pseudorandomly selected 14 natural images and one
        of the two female faces were presented sequentially. The order of the sequence was
        maintained for the same infant. The side on which the upright face was presented
        was also maintained for the same infant. The locations of the two streams were the
        same as those in Experiment 1 (1.4° apart from the center of the monitor).

        <hss>Procedure and design</hss>

        The procedure and design were the same as those in Experiment 1 except with the
        following changes. We presented two streams side by side for 10 s repeatedly; the
        upright female face or the inverted female face was embedded in either one of the
        two streams (Fig. 2). The female faces were always presented as the seventh image
        pairs in the streams. In every trial, 6 images preceded the face images, followed
        by 14 images, except that 3 images followed the final pair of the face images at
        the end of a trial. The presentation rate was 100 ms per item with no
        interstimulus interval for both streams. The order of images in a trial was
        maintained for each stream. Both streams continued until 100 images were
        presented. We conducted a total of six trials, in which the order of two female
        faces and their position orientation were counterbalanced across infants. The
        natural images presented on the right and left were identical. Verbal instruction
        in target detection task is impossible for infants; thus, we used preferential
        looking and a familiarization/novelty preference procedure. We presented the
        target face embedded in a visual stream several times, following the method
        applied in previous studies (Gelskov & Kouider, 2010; Lasky & Spiro, 1980).

        <hss>Data analysis</hss>

        In this experiment and the following experiments, the recording of the infants’
        looking time for the two side-by-side streams (or pictures) was conducted the same
        as in the procedure for Experiment 1. We calculated the individual preference
        score for the stream containing the upright face by dividing the infants’ looking
        time to the stream including the upright face across the six trials by the total
        looking time across the six trials. As in the data coding of Experiment 1, an
        additional independent observer analyzed the video recordings of the looking
        behavior of 10 infants. The intercoder reliability was r = .91 (p < .05). We
        regarded their preference for the stream including the upright face as the index
        of detection of the upright face embedded in the stream.

<hs>  Results</hs>
  ~~~~~~~

Fig. 3 shows the mean preference scores for the stream containing the upright face for the
two age groups. A two-tailed one-sample t test (vs. the chance level of .50) revealed that
the 7- and 8-month-old infants preferred the stream containing the upright face, t(19) =
3.68, p = .01, d = 0.82. This result pattern was not obtained for the 5- and 6-month-old;
no preference was found for this age group, t(19) = −0.43, p = .67, d = 0.09. We found a
developmental difference in the preference score between infants aged 5 and 6 months and
those aged 7 and 8 months, t(38) = 2.72, p = .01, d = 0.86. These results suggest that the
7- and 8-month-olds could detect the upright face embedded in one of the two rapid serial
visual streams at a rate of 100 ms per item.

<h>EXPERIMENT 3A (DISCRIMINATION OF IDENTITIES OF UPRIGHT FACES)</h>
-------------------------------------------------------------

The results of Experiment 2 demonstrated that the 7- and 8-month-old infants could detect
the upright face in a rapid stream visual presentation at a rate of 100 ms per item.
Nonetheless, it remained unclear whether those infants identified the target as a specific
person’s face or merely categorized it as a human face. We examined whether the 7- and
8-month-olds could discriminate a target face from a nontarget face by using a
familiarization/novelty preference paradigm in Experiment 3a. Specifically, we introduced
the familiarization phase and tests. We familiarized the infants to learn a target face
embedded in a stream and subsequently tested whether they could discriminate between the
target and nontarget faces. We expected that infants could reveal a novelty preference in
that they could discriminate a target face from a nontarget face in the test when they
learned a target face in the stream during the familiarization phase.

        <hss>Participants</hss>

        In total, 20 7- and 8-month-old infants who were full-term at birth and healthy at
        the time of the experiment participated in the experiment (11 boys and 9 girls,
        mean age = 230.15 days, SD = 14.67). An additional 5 infants were tested but were
        excluded from the analysis owing to their fussiness and/or crying.

        <hss>Procedure</hss>

        The apparatus and stimuli were identical to those used in Experiment 2. A
        familiarization/novelty preference procedure was introduced to test whether the
        infants could identify a target face in a rapid sequence of visual images. The
        procedure consisted of the familiarization phase and tests. During the
        familiarization phase, 14 pseudorandomly selected natural images and one of the
        two female faces, as a target face, were presented sequentially in the center of
        the monitor at a rate of 100 ms per item with no interstimulus interval. One of
        the female faces was presented as a seventh image in the stream. Both the images
        and the order of images in a trial were maintained. The experiment consisted of
        pre- and posttests. During these tests, a target face (i.e., the familiarized face
        for the posttest) and a nontarget face (i.e., a novel face for the posttest) were
        presented side by side for 10 s to compare the infants’ looking behavior before
        and after the familiarization phase. The pretest was conducted to confirm that
        there was no preference bias for either one of the two faces used in this
        experiment, whereas the posttest was conducted to examine whether infants could
        discriminate the familiarized target face from a nontarget face. No-stream
        presentations were used during these tests. The distance from the center of the
        monitor was 1.4° for each face.

        <hss>Design</hss>

        As mentioned above, the procedure consisted of the familiarization phase and pre-
        and posttests. After all the infants received the pretest, they were familiarized
        with a target face during the familiarization phase. Six familiarization trials
        were conducted for individual infants. Finally, infants received the posttest to
        measure whether they could discriminate the target face from a nontarget face.
        Both pre- and posttests consisted of two trials in which the position of familiar
        and novel faces was counterbalanced across infants in the first and second trials.
        A trial began with a cartoon accompanying a brief sound to obtain the infants’
        fixation to the center of the monitor. As soon as the infants fixated on the
        cartoon, the stimuli were presented. The intercoder reliability was r = .90 (p <
        .05) for the video recordings of the looking behavior of 5 infants.

        <hss>Familiarization phase</hss>

        The looking time at a single stream during the familiarization phase was averaged
        across the first three and last three trials for each infant. The mean looking
        time across the first three trials was 8.64 s (SD = 1.27) and that across the last
        three trials was 7.95 s (SD = 1.29). A two-tailed t test was conducted to confirm
        whether infants familiarized with a target face during the stream. The looking
        time across the first three trials was longer than that across the last three
        trials, t(19) = 2.41, p = .05, d = 0.54. The looking behavior toward a target face
        in the stream presentation declined throughout the familiarization trials, which
        suggested that infants were familiarized with a target face.

        <hss>Pretest and posttest</hss>

        To investigate whether the infants could discriminate the familiarized face
        (target) from a novel face (nontarget), we calculated the preference scores to the
        novel face (nontarget) during the pre- and post-familiarization tests. This index
        represents the novelty preference to a nontarget face in the post-familiarization
        test. We conducted a pre-familiarization test to establish that no preference bias
        was present before the familiarization. Novelty preference scores were computed by
        dividing the infants’ looking time at the novel face across the two trials by the
        total looking time across the two trials in the tests. The mean novelty preference
        scores for the tests are shown in Fig. 4 (left). A two-tailed t test revealed that
        the infants looked at the novel face for a longer period of time during the post-
        familiarization test than during the pre-familiarization test, as expected, t(19)
        = 3.43, p = .01, d = 0.77. In addition, we conducted a two-tailed one-sample t
        test (vs. the chance level of .50) separately for pre- and posttests and found
        that the infants looked at a novel face longer during the post-familiarization
        test, t(19) = 5.01, p = .01, d = 1.12. There was no such preference during the
        pre-familiarization test, t(19) = 0.52, p = .60, d = 0.12. These results suggest
        that the 7- and 8-month-old infants could discriminate the novel face (nontarget)
        from the familiar face (target). Because the face images were counterbalanced
        across infants, we can conclude that infants around this age could detect and
        identify a human face among a rapid sequence of visually presented natural images
        at a rate of 100 ms per item.

<h>EXPERIMENT 3B (DISCRIMINATION OF IDENTITIES OF INVERTED FACES)</h>
--------------------------------------------------------------

The results of Experiment 3a demonstrated that the 7- and 8-month-old infants were able to
discriminate a target face from a nontarget face presented in a rapid visual stream. To
unanimously conclude that the infants could discriminate the target as a face rather than
a low-level visual pattern, we designed Experiment 3b in which the face inversion effect
was introduced. The face inversion effect was reported to occur in 4-month-old infants
(Turati, Sangrigoli, Ruel, & de Schonen, 2004), and preference for upright faces over
inverted faces was observed in newborns and 3-month-old infants (Cassia et al., 2006;
Mondloch et al., 1999). This preference has also recently been found in the human fetus
(Reid et al., 2017). If infants were unable to discriminate the inverted face due to the
face inversion effect, we can infer that the results of Experiment 3a were based on the
infants’ face discrimination. However, if infants discriminated the inverted face, the
results of Experiment 3a could be attributed to the discrimination of low-level features
in the face images.

        <hss>Participants</hss>

        In total, 20 7- and 8-month-old infants, who were full-term at birth and healthy
        at the time of the experiment, participated in the experiment (15 boys and 5
        girls, mean age = 233.75 days, SD = 16.22). The infants were recruited through
        local newspaper advertisements.

        <hss>Procedure, design, and apparatus</hss>

        The procedure, design, and apparatus were the same as those used in Experiment 3a
        combined with inverted faces. The intercoder reliability was r = .97 (p < .05) for
        the video recordings of the looking behavior of 5 infants.

        <hss>Familiarization phase</hss>

        We analyzed the results in the same way as in Experiment 3a. Specifically, the
        looking time at the single stream during familiarization phases was averaged
        across the first three and last three trials for each infant. The mean looking
        time in the first three trials was 9.28 s (SD = 0.85) and that in the last three
        trials was 8.23 s (SD = 1.54). A two-tailed t test to test the effect of
        familiarization revealed that the looking time in the first three trials was
        longer than that in the last three trials, t(19) = 3.41, p = .01, d = 0.76. The
        looking time declined across the familiarization phases. These results suggest
        that the infants were familiarized with the inverted target face.

        <hss>Pretest and posttest</hss>

        We calculated the preference score to the novel face (nontarget) for the pre- and
        post-familiarization tests across infants. The mean novelty preference scores for
        the tests are shown in Fig. 4 (right). A two-tailed t test indicated no
        significant difference in looking time at the novel face between the pre- and
        post-familiarization tests, t(19) = 0.04, p = .97, d = 0.01. In addition, the
        preference score during the tests did not differ from the chance level of .50
        [pre-familiarization test: t(19) = 0.18, p = .86, d = 0.04; post-familiarization
        test: t(19) = 0.12, p = .91, d = .03]. These results suggest that the 7- and
        8-month-old infants were unable to discriminate the inverted novel face from the
        inverted familiar face due to the face inversion effect.

<h>GENERAL DISCUSSION</h>
------------------

The primary goal of the current study was to examine the infants’ ability to detect and
identify individual faces under temporally demanding circumstances of masked rapid serial
visual presentations. In Experiment 1, we tested whether infants could discriminate
between 100- and 11-ms rapid serial visual streams. The results indicated that the 7- and
8-month-olds were able to discriminate the two streams, suggesting that the 100-ms
presentation rate would be available in infants. In Experiment 2, we presented two visual
streams, each containing an upright or inverted face to test whether infants could detect
an upright face in 100 ms. The results showed that 7- and 8-month-olds could detect the
face. In Experiments 3a and 3b, we investigated whether 7- and 8-month-olds could
discriminate a target face that infants learned from a nontarget face using an upright
face and an inverted face. The results showed that 7- and 8-month-olds could identify the
individual face when the face was presented upright. However, they were unable to identify
it when the face was inverted due to the face inversion effect (e.g., Turati et al.,
2004). In sum, the current study revealed that infants aged around 7 or 8 months can not
only detect the face but also identify individual face images among the nonface images
presented at a rate of 100 ms. It is notable that 7- and 8-month-old infants could detect
and identify individual faces presented even at a rate of 100 ms among nonface objects. To
our knowledge, this is the first study to show successful identification of faces while
viewing rapid serial visual streams in 7- and 8-month-olds. Previous studies displayed
faces for approximately 20–70 s, and 7- and 8-month-olds identified neutral faces (Fagan,
1976; Otsuka et al., 2013; Righi, Westerlund, Congdon, Troller-Renfree, & Nelson, 2014;
Tyrrell, Anderson, Clubb, & Bradbury, 1987; for a review, see Otsuka, 2017). In contrast,
we presented the faces at a much faster rate (i.e., 100 ms per image), and the total
duration amounted to 4.2 s at most. This result suggests that 7- and 8-month-olds can
identify a face at a comparable rate to adults, who can detect and identify visual images
embedded in a rapid stream of nontarget objects at a rate of 100 ms per item (Potter,
1976). Certainly, we could not rule out the possibility that infants learned the target
and nontarget faces incidentally during the pretest because they were simultaneously
exposed to these for 20 s.1 Regardless of this possibility, the significance of the
current finding was that infants’ processing of face information occurs over a sequence of
rapidly changing events. What Gelskov and Kouider (2010) focused on was the detection of a
face appearing on the left or right side of a computer screen. In their study, the face
was preceded by a forward mask that occurred in the same location where a face could
appear. Their procedure measured detectability of a face with spatial uncertainty because
the infants had no clue whether the face would appear on the left or right side of the
screen. There were no distractors other than a nonface stimulus at the opposite side from
the target. Therefore, Gelskov and Kouider’s stimulus configuration was relatively less
demanding in terms of attention. In contrast, we embedded a target face in a rapid
sequence of nontargets for more than 2 s. Therefore, the key issue here was the
measurement of detectability of a face with temporal uncertainty under an attentionally
demanding circumstance. In this sense, the current study is not a mere extension of a past
study but rather revealed that 7- and 8-month-olds could detect the face when temporal
uncertainty exists with visually demanding circumstances. The current finding is
consistent with the literature demonstrating that the ability of identifying individual
faces in 7- and 8-month-old infants is supported by a sufficiently developed higher-order
mechanism of face processing at this age. It has been shown that the capabilities of
configural processing and view-invariant face recognition are acquired at around 7 or 8
months of age (Fagan, 1976; Kobayashi et al., 2012; Nakato et al., 2009; Otsuka, Hill,
Kanazawa, Yamaguchi, & Spehar, 2010; Schwarzer & Zauner, 2003). In terms of configural
processing, 7-month-olds could perceive faces configurally (Cohen & Cashon, 2001;
Kobayashi et al., 2012; Otsuka et al., 2010; Schwarzer & Zauner, 2003; Schwarzer, Zauner,
& Jovanovic, 2007). Regarding view-invariant face recognition, 7- and 8-month-olds could
perceive the face regardless of viewing orientations (Fagan, 1976; Nakato et al., 2009).
It is plausible that 7- and 8-month-olds who have already acquired these abilities of face
processing could identify the individual face embedded in a rapid visual stream. We
suggest that these neural mechanisms support the ability to detect and identify faces
found in the current study in 7- and 8-month-olds. In addition, previous studies have
reported that infants aged even 3 months are sensitive to certain kinds of higher-order
mechanisms such as configural processing (Bhatt, Bertin, Hayden, & Reed, 2005; Cohen &
Cashon, 2004; Galati, Hock, & Bhatt, 2016; Joseph, DiBartolo, & Bhatt, 2015; Quinn,
Tanaka, Lee, Pascalis, & Slater, 2013; Zieber et al., 2013). In the current study, we
examined the infants’ ability to detect and identify faces during rapid serial visual
presentation using configural face processing. Then, we found that the stimulus duration
of 100 ms would not be sufficient time for 5- and 6-month-olds, but would be sufficient
for 7- and 8-month-olds, to detect and identify upright faces. The temporal speed that
would be sufficient for younger infants to detect and identify the face during the viewing
of a rapid serial visual stream needs to be explored in future studies that systematically
manipulate presentation rates. Importantly, a critical aspect of the current study is that
infants can detect and identify faces under temporally demanding circumstances in which
the images and faces are presented briefly at a rate of 10 items per second. Our findings
on face identification in 7- and 8-month-old infants were inconsistent with the findings
of Gelskov and Kouider (2010), which showed that 10-month-old infants could not detect the
face presented for 100 ms followed by a scrambled face mask. In terms of the difference in
experimental procedure, we used the rapid serial visual presentation task, whereas they
used visual sandwich masking. Apart from this difference, we speculate that the difference
in visual mask stimuli would be the main factor to elicit the inconsistent results.
Gelskov and Kouider used the scrambled face as the forward and backward visual mask,
whereas we presented various scene images as visual masking in a rapid serial visual
stream. According to a previous study (Maguire & Howe, 2016), the effect of a visual mask
by natural scene images is weak compared with scrambled noise images. Thus, the 7- and
8-month-olds in our study were able to detect and identify the face through using the
natural scene images as a mask. One may argue that the target image and its subsequent
nontarget mask images used in the current study differed in terms of low-level features
(e.g., contrast, luminance), and this difference might have contributed to these 7- and
8-month-olds being able to identify a rapidly presented face easily. However, we believe
that this possibility is unlikely because visual masking by natural scene images would
occur in the current stimuli. The results in 5- and 6-month-olds in Experiment 2 provide
affirmative evidence. Specifically, 5-month-olds could identify the face presented for 100
ms without a visual mask (Lasky & Spiro, 1980), whereas the 5- and 6-month-olds in our
study could not detect the face presented for 100 ms during visual stream. These findings
suggest that natural scene images serve as visual masking. Of course, embedding target
faces among facelike distractors so that each image should contain a single large high-
contrast pink object with a dark high-contrast hairline would make the task more
difficult, and thus infants would need to be older to show the preference. To investigate
such effects of masking during a rapid serial visual stream in infants, further studies
like the adult studies are needed. The current study revealed that there is a
developmental change in face recognition between the groups of 5- and 6-month-old infants
and 7- and 8-month-old infants. The former could not detect a face embedded in a rapid
serial visual stream, whereas the latter could. The failure of detection in the younger
group of infants is consistent with a previous behavioral study in which 5-month-old
infants were unable to detect a face presented for 100 ms followed by the visual mask
stimuli (Gelskov & Kouider, 2010). An electrophysiological study, however, demonstrated
brain activities in response to briefly presented faces at 5 months of age. Specifically,
de Heering and Rossion (2015) found a right-lateralized occipito-temporal categorization
response to a face presented at 6 Hz in 4- to 6-month-olds. These two apparently
inconsistent results regarding the critical period of the emerging infants’ responses to
faces can be reconciled by assuming that the emergence of brain activities in response to
faces precedes behavioral responses. In general, the neural system should be organized
before the emergence of infants’ behavior response (Jessen & Grossmann, 2015, 2019;
Kouider et al., 2013; Nava, Romano, Grassi, & Turati, 2016). Therefore, it is likely that
the current 5- and 6-month-olds might have shown responses in sensitive brain activities
if measured, although those responses did not accompany explicit behavioral responses in
the current study. However, by the age of 7 or 8 months, infants developed fully to reveal
behavioral and explicit responses in detecting and identifying a face embedded in a rapid
serial visual stream at a rate of 100 ms per image. The dorsolateral prefrontal cortex has
been identified as neural substrates for functions of working memory and selective
attentional control. These functions can be acquired in 7- and 8-month-old infants
comparable to adults (Diamond & Goldman-Rakic, 1989). At around 7 or 8 months of age, the
neural circuitry of fusiform face area (Kanwisher, McDermott, & Chun, 1997) and occipital
face area (Rossion, 2008) regions were activated when rapidly detecting and identifying
the briefly presented face in older infants and adults (Barry-Anwar et al., 2018; de
Heering & Rossion, 2015; Gentile & Rossion, 2014). These neuronal areas might be concerned
with the rapid detection and identification of faces in 100 ms similar to the mechanisms
in adults. The current findings reveal remarkable capabilities of infants at this age,
expanding the possibility that infants’ attentional functions can be tested by using the
rapid serial visual presentation procedures. This encourages exploration of relatively
less examined infants’ cognitive functions, such as nonspatial temporal attention, in
future studies.


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<ART>Re-construction of action awareness depends on an internal model of action-outcome timing
================================================================================

Authors: Max Philipp Stenner, Markus Bauer, Judith Machts, Hans Jochen Heinze, Patrick Haggard, Raymond J. Dolan
DOI: 10.1016/j.concog.2014.01.007
Year: 2014  |  Pages: 11-16
ASJC codes: 3204, 3205
Keywords: Action awareness, Sense of agency, Temporal binding

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This temporal binding effect is partially retrospective, i.e., occurs upon outcome perception. Retrospective binding is thought to reflect post-hoc inference on agency based on sensory evidence of the action - outcome association. However, many previous binding paradigms cannot exclude the possibility that retrospective binding results from bottom-up interference of sensory outcome processing with action awareness and is functionally unrelated to the processing of the action - outcome association. Here, we keep bottom-up interference constant and use a contextual manipulation instead. We demonstrate a shift of subjective action time by its outcome in a context of variable outcome timing. Crucially, this shift is absent when there is no such variability. Thus, retrospective action binding reflects a context-dependent, model-based phenomenon. Such top-down re-construction of action awareness seems to bias agency attribution when outcome predictability is low. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

When a motor action is followed by a sensory event within a few hundred milliseconds, the
subjective time of the action can be shifted towards that sensory event (Haggard, Clark, &
Kalogeras, 2002; for a review, see Moore & Obhi, 2012). This binding of subjective action
time by a subsequent stimulus depends on learning the underlying contingency (Moore,
Lagnado, Deal, & Haggard, 2009; Walsh & Haggard, 2013). It is considered to reflect
intentional (Haggard et al., 2002) and/or causative (Buehner & Humphreys, 2009) aspects of
the learnt action – outcome association that contribute to a pre-reflective sense of
agency (Moore & Obhi, 2012). Temporal action binding is partially retrospective, in so far
as it occurs at the time of outcome perception (Moore & Haggard, 2008). This retrospective
component of temporal binding has frequently been regarded as evidence in favour of a
post-hoc implicit inference on agency based on sensory evidence, as opposed to a
prospective implicit agency ascription during action preparation and/or execution (Moore &
Haggard, 2008). This distinction relates to the broader question (Baldwin et al., 2003) of
how awareness of prior expectations of an action-outcome (e.g. during unsuccessful trying)
on the one hand, and the observation of physical action consequences on the other, are
weighted and integrated in the process of sensing intention and causation (Wegner &
Wheatley, 1999; Wolpert & Flanagan, 2001). These interpretations of retrospective action
binding assume an underlying inferential, top-down process. In principal, however, a
retrospective change of action awareness could be driven by two physiologically distinct
mechanisms. A top-down process could re-construct action awareness by integrating prior
knowledge and sensory evidence of the action – outcome association. A similar model-based
process has been proposed, for example, for an integration of motor predictions and
sensory re-afference in comparator models of motor control (Wolpert & Flanagan, 2001).
Alternatively, retrospective action binding could reflect bottom-up interference of
sensory outcome processing with on-going cognitive processes involved in action awareness,
or, at a lower level, with the integration of visual information in the Libet clock
paradigm typically deployed in these experiments (Libet, Gleason, Wright, & Pearl, 1983).
In this case, the retrospective shift of subjective action time would be solely stimulus-
driven, similar to the effects of backward masking on conscious perception, for example
(Werner, 1935), and would be independent of an internal model of the action – outcome
association. Previous evidence of retrospective temporal binding comes predominantly from
studies that compare subjective action time in the presence and absence of a subsequent
stimulus, i.e., two conditions that differ substantially in bottom-up drive (Moore &
Haggard, 2008). In these studies, a shift of subjective action time due to outcome
presentation reflects retrospective action awareness. Therefore, these studies cannot
distinguish between model-based re-construction of action awareness and bottom-up
interference with action awareness. Evidence for the idea that a top-down re-constructive
process is involved in retrospective binding comes from a study that manipulated the
contingency of an outcome on an action, specifically the probability of an outcome given
no preceding action (Moore et al., 2009). This study held bottom-up drive constant across
trials of interest and used a contextual manipulation instead to demonstrate that
retrospective binding depends on an internal representation of how necessary an action is
for a sensory event. Similarly, we here used a contextual manipulation while keeping
bottom-up influences constant to address the question whether action awareness depends on
an internal model of outcome timing. Previous studies have shown that binding of an
outcome to an action depends on temporal outcome predictability (Haggard et al., 2002). We
asked whether retrospective and prospective components of action awareness also reflect
temporal outcome predictability. Moore and Haggard (2008) have previously shown that
outcome presentation shifts subjective action time under conditions of low outcome
predictability, as achieved by lowering the probability of outcome occurrence (the
“whether” of the outcome). Here, we tested whether a contextual manipulation of temporal
outcome predictability leads to a similar shift of subjective action time. In brief, we
compared retrospective binding in two conditions that differ in temporal variability of
the outcome with respect to the action (the “when” of the outcome) while keeping the
structure and timing of trials of interest constant, i.e., bottom-up drive. Any difference
in retrospective binding between conditions of variable and fixed outcome timing would
reflect an influence of context, rather than any bottom-up interference with action
awareness. In addition, Moore and Haggard (2008) demonstrated a shift of action awareness
towards an expected outcome even when the outcome was omitted. The authors interpreted
this shift as a prospective component of action awareness. To examine effects of temporal
outcome predictability on this prospective component, our study introduced an expectation
of outcome occurrence by presenting outcomes on 75% of trials in both “variable” and
“fixed” outcome timing blocks.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

We recruited 16 healthy volunteers (age 23.5 ± 2.78 years (mean ± SD), 10 females; all
right-handed) via an online database. All participants gave written informed consent prior
to participation with the right to exit the study at any time. The study was approved by
the local ethics committee (University College London, UK). Participants received £10 per
hour as reimbursement.

<hs>  Task</hs>
  ~~~~

Presentation® software (Neurobehavioral Systems, www.neurobs.com) was used to generate all
stimuli and to program the paradigm. The task was presented on an LCD screen (vertical
refresh rate 60 Hz) on a white background. The experiment was run in a dark and sound-
proof room. Participants were seated 75 cm in front of the screen and kept their chin on a
chin rest. Sound was presented binaurally at 74 dB SPL via Sennheiser HD 380 pro
headphones. The task (Fig. 1) was a variation of the temporal binding paradigms used by
Haggard et al. (2002) and Moore and Haggard (2008). On each trial, participants pressed a
button with their right index finger once, at a time of their choice, and verbally
reported the time of this button press with respect to the rotating clock hand of a Libet
clock (Libet et al., 1983) (period of 2.55 s) at the end of the trial. The experiment was
based on a 2 × 2 factorial design, with one factor (“trial type”, two levels: “action +
tone” vs. “action only”) varied on a trial-by-trial basis and the other (“outcome timing
variability”: “variable outcome timing” vs. “fixed outcome timing”) varied block-wise.
There was an additional, blocked condition that served as baseline for subjective time
judgements (“baseline” blocks). 75% of trials in “variable outcome timing” and “fixed
outcome timing” blocks were “action + tone” trials, in which participants’ button presses
were followed by one of two sine wave tones (750 Hz or 800 Hz, 100 ms duration). Each tone
frequency was presented pseudo-randomly in half of these trials. In the remaining 25% of
trials, no tone was presented. These trial frequencies of “action + tone” and “action
only” trials were identical to Moore and Haggard (2008), where they were used to establish
outcome expectation and quantify prospective action binding in trials of unexpected
outcome omission. Here, they served to control for potential differences in prospective
binding due to “outcome timing variability”: Stronger binding in “action + tone” trials
compared to “action only” trials can be attributed to a re-construction triggered by the
tone over and above any prospective shift of subjective action time. Tones followed the
button presses either after a fixed delay of 250 ms (in “fixed outcome timing” blocks) or
after a variable delay of either 50 ms, 250 ms or 450 ms (with equal probabilities) (in
“variable outcome timing” blocks). At the end of “action + tone” trials, participants
verbally reported whether the tone they had heard was a high-pitch or low-pitch tone, in
addition to reporting the time of their button press. This incidental pitch discrimination
task was introduced to prevent participants from ignoring the tones. There were three
“fixed outcome timing” blocks and three “variable outcome timing” blocks, presented
consecutively, with the order of the two conditions fully counterbalanced across subjects.
Each of these blocks consisted of 24 trials. Outcome timing with respect to the action
(fixed or variable) was made explicit at the beginning of each block. In addition, there
were two “baseline” blocks, consisting exclusively of “action only” trials. These blocks
were presented before and after the main experimental blocks and consisted of 9 trials
each. Before the first block in which tones were played, participants were familiarized
with the two tone frequencies by listening to them in an alternating sequence for as long
as they wanted to. At the beginning of each trial, the clock hand started to rotate at a
random position. Participants were instructed not to press the button during the first
rotation of the clock hand. Rotation of the clock hand continued over a total of 350–400
vertical refresh frames and then stopped, largely independently of when participants chose
to press the button. Only if participants pressed throughout the last 60 frames before the
planned end of rotation, this rotation was extended for 60 more frames after sound
presentation (75 frames after the button press in “action only” trials), so that the clock
hand never stopped directly or very shortly after the button press. If participants did
not press the button at all before the clock hand stopped rotating, a red “x” (font size:
1°) was presented in the centre of the screen, indicating a miss. These trials were
repeated at the end of the respective experimental block. During the inter-trial interval,
the clock was presented without the clock hand for 1000–1500 ms. Participants were
discouraged from anticipating the clock hand position when pressing the button and from
pressing in a stereotyped way. They were asked to fixate a stationary black circle at the
centre of the clock at all times, rather than to follow the rotating clock hand with their
eyes. Participants were instructed to report the clock hand position only after the clock
had stopped rotating and a question mark (font size: 1°) had replaced the clock hand.
Lastly, they were asked to be as accurate as possible in their timing reports and to use
all integer numbers from 0 to 59, rather than just the multiples of five that were
explicitly labelled around the clock face. After verbally reporting their subjective time
judgement, the experimenter typed the value into a keyboard. The image of the clock
consisted a circular annulus (outer diameter: 3°, inner diameter: 2.65°), presented at the
centre of the screen, twelve radial lines, which represented the five-minute markers
(length 0.5°, line width .075°) and which were labelled with the multiples of five between
zero and 55 (font size: 0.5°) at 2.15° eccentricity, a central, solid black circle
(diameter: 0.3°) and one clock hand (line width: 0.15°, length: 1.4°). All visual elements
of the clock were black, the inside of the annulus was white. The clock hand rotated
2.353° upon every vertical refresh (∼17 ms), resulting in one full rotation every 2550 ms.
Exact timing of picture stimulus presentation was monitored and trials were repeated at
the end of the respective experimental block if at least one picture was delayed by one
frame or more.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Our main focus was on participants’ time judgement errors, i.e., the difference between
the subjective, reported time of the action and its objective time with respect to the
Libet clock. Following previous studies on binding of subjective action time (Haggard et
al., 2002), we subtracted the mean time judgement error in “baseline” blocks from mean
time judgement errors in “variable outcome timing” and “fixed outcome timing” blocks for
each participant. Positive time judgement errors therefore indicate temporal binding of
the action by its (expected) outcome. We focussed on subjective time in “action only”
trials vs. “action + tone” trials in which event timing was identical in “fixed outcome
timing” and “variable outcome timing” blocks, i.e., on “action + tone” trials with an
action – outcome delay of 250 ms. In addition, we report results for “action + tone”
trials in “variable outcome timing” blocks that were based on the two alternative action –
outcome delays separately (50 ms and 450 ms). To compare attentional demand across
conditions, we analysed the variability (standard deviation) of time judgement errors (cf.
Haggard et al., 2002) and sensitivity (d′) in the incidental pitch discrimination task
across participants. A two-way repeated-measures analysis of variances (ANOVA) was used in
all cases, followed by pairwise dependent-samples t-tests.

<h>RESULTS</h>
-------

We were primarily interested in changes in retrospective binding due to contextual
information on outcome timing variability, not due to changes in bottom-up drive.
Therefore, we first focused on “action + tone” trials with identical trial event timing in
both “variable” and “fixed” outcome timing blocks, i.e., on trials with an action –
outcome delay of 250 ms. We compared these “action + tone” trials to “action only” trials
in the two types of blocks (Fig. 2). A two-way repeated-measures ANOVA (“outcome timing
variability” × “trial type”) revealed a significant interaction effect (F1,15 = 6.84, p =
.019) and a main effect of “trial type” (F1,15 = 8.5, p = .011) on mean time judgement
errors across subjects. Post-hoc dependent-samples t-tests showed that the interaction was
due to a significant shift of subjective action time forwards in “action + tone” trials
vs. “action only” trials in “variable outcome timing” blocks (mean ± SD: 31.7 ± 27.4 ms
(“action + tone”) vs. 16 ± 24.9 ms (“action only”); t15 = −3.88, p = .001), an effect that
was absent in “fixed outcome timing” blocks (mean ± SD: 23.3 ± 21.8 ms (“action + tone”)
vs. 23.3 ± 21.5 ms (“action only”); p = .99). No other pairwise t-test was significant,
suggesting that the observed main effect of “trial type” was predominantly driven by the
difference between “action only” trials and “action + tone” trials in the ”variable
outcome timing” block. Our paradigm required attention to the pitch of the tone in order
to prevent participants from ignoring the tone. In order to test for potential differences
in attention towards the tone across conditions, we analysed the standard deviation of
time judgement errors, which has previously been used as an indicator of varying attention
or, more generally, quality of information processing in action binding tasks (Haggard et
al., 2002). “Outcome timing variability” and “trial type” showed no significant main
effects or interaction effects on the standard deviation of time judgement errors across
subjects (mean ± SD: 65.5 ± 19.2 ms (“action only” trials in “fixed outcome timing”
blocks), 66.8 ± 22.5 ms (“action + tone” trials in “fixed outcome timing” blocks), 70.1 ±
24.4 ms (“action only” trials in “variable outcome timing” blocks), 65.4 ± 26.5 ms
(“action + tone” trials in “variable outcome timing” blocks). Furthermore, there was no
significant effect of “outcome timing variability” on pitch discrimination sensitivity
(mean d′: 2.52 (“fixed outcome timing”) and 2.34 (“variable outcome timing”), t14 = 1.22,
p = .24). For completeness, we report the shifts observed for “action + tone” trials in
“variable outcome timing” blocks in which the action – outcome delay (and, therefore,
bottom-up drive) differed from “fixed outcome timing” blocks. Compared to “action only”
trials in “variable outcome timing” blocks, subjective action time in “action + tone”
trials for which the action – outcome delay was 50 ms or 450 ms did not show the shift
towards the outcome observed for the action – outcome delay of 250 ms. When the tone
followed the button press after 50 ms, there was even a significant shift away from the
outcome when compared to “action only” trials (mean ± SD in “action + tone” trials: −3.5 ±
18.2 ms; t15 = 2.92, p = .011) while there was no significant change due to outcome
presentation 450 ms after the button press (mean ± SD in “action + tone” trials: 12.1 ±
22.9 ms; t15 = 0.81, p = .43).

<h>DISCUSSION</h>
----------

We demonstrate that an essential aspect of action awareness – the experienced time of an
action – can be re-constructed by a context-dependent process at the time of the action’s
outcome. Specifically, we observe this re-construction of action awareness when the action
is performed in a context of uncertain outcome timing. This context-dependency suggests a
model-based, top-down re-constructive process that shifts action awareness based on
previously experienced action – outcome intervals. If the reconstructive process had been
directly triggered by the perceptual trace of the tone, and was independent of the action
– outcome delay experienced on other trials, then it could be interpreted as a bottom-up
backwards influence. This would be similar to the effects of backwards masking on
conscious perception (Werner, 1935), and would not track changes in the time relation of
an action and a subsequent stimulus. Context-dependency makes this bottom-up account
unlikely. The majority of previous studies on retrospective action binding have compared
conditions that differed in bottom-up drive (“action only” vs. “action + tone” conditions)
(Moore & Haggard, 2008; but see Moore et al., 2009). Therefore, these studies cannot
exclude the possibility that a retrospective shift of subjective action time is due to
bottom-up interference with action awareness or, at a lower level, with the integration of
the visual information of the Libet clock. Despite the possibility of such bottom-up
driven interference of perceptual codes with action awareness that is unrelated to a
representation of the action – outcome association, retrospective action binding has been
considered to reflect implicit post-hoc inference on agency (Moore & Haggard, 2008; Voss
et al., 2010). To avoid the difference in bottom-up drive present in previous studies, and
to test whether re-construction of action awareness indeed tracks the temporal relation
between the action and its outcome, we compared “action only” and “action + tone” trials
in two contexts. These contexts differed with respect to temporal outcome variability
while the structure and timing of trial events (of interest) was identical across
contexts. The interaction between “trial type” (outcome presented vs. omitted) and
“outcome timing variability” we observed suggests that a retrospective shift of subjective
action time in our study results from an integration of sensory and contextual information
on an action – outcome association. This context-dependency speaks in favour of a top-down
process underlying retrospective action binding, which integrates prior knowledge and
sensory re-afferences. Compared to previous studies on retrospective binding, notably by
Moore and Haggard (2008), our study design introduces an additional aspect of outcome
uncertainty. Moore and Haggard exclusively manipulated the probability of outcome
occurrence while we also varied outcome timing with respect to the action. Our current
results can neither exclude a retrospective binding component in “action + tone” trials
when the action – outcome delay is fixed, nor, indeed, in “action only” trials, as the
omission of an expected outcome in these trials may well constitute a sensory event
(Sutton, Tueting, Zubin, & John, 1967) and thus alter action awareness retrospectively. In
addition, since the probability of outcome occurrence was high across both operant
conditions, we cannot exclude a prospective shift of subjective action time from the
baseline condition to the operant conditions. However, our key finding is an enhancement
of action binding in “variable outcome timing” blocks from “action only” trials to “action
+ tone” trials, i.e., a clear retrospective process that follows outcome presentation. In
addition, we find no change in action binding upon outcome omission as a function of
temporal predictability. This may suggest that, unlike retrospective binding, prospective
action binding is more closely associated with the expected occurrence than the expected
timing of an outcome. However, this negative result should be interpreted with caution.
Our finding points to a stronger re-constructive component when outcome occurrence and
timing are uncertain. This suggests that sensory evidence of the action – outcome
association is weighed flexibly, depending on the temporal predictability of the outcome.
As outcome timing becomes less predictable, sensory evidence is given a relatively
stronger weight than outcome prediction and is used for a retrospective adjustment of
action awareness. An interesting question is whether temporal outcome uncertainty
interacts with specific action – outcome delays during this re-constructive process. In
theory, enhancement of retrospective binding by temporal uncertainty could depend on a
central estimate of the distribution of previously experienced action – outcome delays.
Alternatively, enhanced retrospective binding could reflect time constants inherent to
sensorimotor processing or an absolute time range over which an action is a priori
expected to cause a sensory event. The present study cannot distinguish between these
alternatives. Here, we find enhanced retrospective binding for an action – outcome
interval of 250 ms but not for trials with shorter or longer delays (50 ms and 450 ms).
Trials with shorter and longer action – outcome delays were necessary to build a context
of temporal uncertainty in the “variable outcome timing” condition. These trials had no
counterparts in the “fixed outcome timing” condition which could have confirmed that
subjective action time is, in principle, shifted under operant conditions for these
delays. Indeed, a recent study found no action binding at a fixed action – outcome delay
of 50 ms at all (Walsh & Haggard, 2013). We know of no previous study that has
systematically examined action binding across a broad range of action-outcome delays
(whereas outcome (tone) binding (Haggard et al., 2002) and compound measures, which do not
distinguish between tone binding and action binding (e.g. Humphreys & Buehner, 2009), have
been studied across a broad range of action-outcome intervals). Because of this, we are
cautious to draw strong conclusions regarding action binding in trials with an action –
outcome delay of 50 ms or 450 ms in the “variable outcome timing” condition. In principle,
our study design confounds two aspects of a contingent action – outcome association,
namely temporal predictability and temporal control (Hughes, Desantis, & Waszak, 2012).
Recent evidence supports the view that temporal binding reflects (voluntary) temporal
control rather than action-independent temporal predictability (Desantis, Hughes, &
Waszak, 2012; Haggard et al., 2002). Temporal binding is specific for action – stimulus
associations and does not occur when one stimulus predicts another. By design, we cannot
unambiguously attribute our finding of retrospective action binding to either temporal
control or temporal predictability. This question goes beyond the purpose of this study,
which was to distinguish between bottom-up interference and model-based inference in
retrospective binding, and requires attention in future studies. A contextual influence on
retrospective action awareness has been demonstrated in one previous study (Moore et al.,
2009). This study varied the probability of a sensory event in trials in which no motor
action was performed, thereby modulating the action – outcome contingency in a contextual
manner, as in our study. The authors reported retrospective binding under conditions of
high, but not low action – outcome contingency, i.e., evidence for an interaction between
sensory evidence and context that is compatible with our own finding. Interestingly, we
find enhanced retrospective binding when the outcome is not fully determined by the
preceding action due to temporal uncertainty. This finding is in agreement with studies
that describe retrospective action binding as a post-hoc adjustment of the subjective time
of an action upon unpredictable outcome occurrence. From a theoretical perspective, this
adjustment seems unnecessary when outcome predictability is high, i.e., when internal
models are accurate, as in our “fixed outcome timing” condition. Under conditions of low
temporal predictability, however, an internal model of outcome timing can, in principle,
be used to evaluate an experienced action-outcome association retrospectively in relation
to prior knowledge about the distribution of action-outcome intervals. The probability and
timing of a sensory event given an action may affect re-construction of action awareness
in a way that is distinct from the effects of contingency as shown by Moore et al. (2009).
In summary, we demonstrate that retrospective action awareness results from a model-based,
top-down process, rather than from bottom-up interference with action awareness. This re-
constructive process integrates contextual and sensory information to infer on the action
– outcome association and may contribute to establishing action – outcome associations
under conditions of temporal outcome uncertainty.


<h>REFERENCES</h>
----------

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<ART>Reading strategies of good and poor readers of German with different spelling abilities
================================================================================

Authors: Melanie Gangl, Kristina Moll, Chiara Banfi, Stefan Huber, Gerd Schulte-Körne, Karin Landerl
DOI: 10.1016/j.jecp.2018.05.012
Year: 2018  |  Pages: 150-169
ASJC codes: 3204, 3205
Keywords: (Dys)fluent readers, Consistent orthography, Eye movements, Orthographic knowledge, Reading strategies, Spelling

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Reading and spelling abilities are thought to be highly correlated during development, and orthographic knowledge is assumed to underpin both literacy skills. Interestingly, recent studies showed that reading and spelling skills can also dissociate. The current study investigated whether spelling skills (indicating orthographic knowledge) are associated with the application of orthographic strategies during reading. We examined eye movements of 137 third- and fourth-graders who were either good or poor readers with or without a spelling deficit: 43 children with typical reading and spelling skills, 28 with isolated spelling deficits, 28 with isolated reading deficits, and 38 with combined reading and spelling deficits. Although we expected to find reduced reliance on orthographic reading processes among poor spellers, this was evident for the group with combined deficits only. Both isolated deficit groups applied sublexical and lexical processes in a similar amount to typically developing children. Our findings suggest that reading rests on orthographic strategies even if lexical representations are poor as indicated by a deficit in spelling skills. Findings also show that dysfluent reading does not result only from overreliance on decoding.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The importance of word-specific orthographic knowledge for spelling is beyond question
because the precise letter sequence of a word must be fully recalled. However, word-
specific orthographic representations are crucial not only for spelling but also for
accurate and fluent reading (Ehri, 1992, 2005; Share, 1995). Thus, word-specific
orthographic knowledge contributes to both spelling and reading (Conrad, Harris, &
Williams, 2013; Rothe, Cornell, Ise, & Schulte-Körne, 2015). Moreover, findings from
cognitive behavioral studies (Angelelli, Marinelli, & Zoccolotti, 2010; Burt & Tate, 2002;
Monsell, 1987) as well as from neuroimaging research (Purcell, Jiang, & Eden, 2017; Rapp &
Dufor, 2011; Rapp & Lipka, 2011) favor the view of a single orthographic lexicon (e.g.,
Behrmann & Bub, 1992) over independent lexica (e.g., Weekes, 1996) for reading and
spelling. Thus, reading and spelling are supposed to share the same orthographic
representations rather than relying on different orthographic representations (for
reviews, see Jones & Rawson, 2016; Purcell et al., 2017).1 In line with this view, reading
and spelling skills were reported to be highly correlated (Swanson, Trainin, Necoechea, &
Hammill, 2003) and reading deficits were found to be often accompanied by spelling
deficits (Angelelli, Judica, Spinelli, Zoccolotti, & Luzzatti, 2004; Landerl & Moll, 2010;
Moll, Kunze, Neuhoff, Bruder, & Schulte-Körne, 2014). The pivotal role of orthographic
representations for reading is also stated by the lexical quality hypothesis (Perfetti,
2007; Perfetti & Hart, 2001). According to this theory, skilled reading builds on high-
quality representations integrating knowledge about a word’s phonological, orthographic,
and semantic characteristics. In support of this view, reading speed was found to be
affected by the quality (i.e., accuracy and stability) of orthographic representations, as
indicated by spelling performance (Martin-Chang, Ouellette, & Madden, 2014; Ouellette,
Martin-Chang, & Rossi, 2017). However, reading is thought to be easier and to involve less
processing than spelling because in most alphabetic orthographies grapheme–phoneme
correspondences are more consistent than phoneme–grapheme correspondences (Bosman & Van
Orden, 1997). Furthermore, spelling requires retrieving the complete letter array from
mind, whereas for reading recognition of printed letter strings is sufficient (Perfetti,
1997). Hence, spelling may require more precise orthographic representations than reading
(Perfetti, 1992). Accordingly, isolated deficits in spelling in spite of adequate reading
skills are generally acknowledged (ICD-10 [International Classification of Diseases–10th
Revision]; World Health Organization, 2000). Interestingly, however, several studies
across different languages reported dissociations in both directions: spelling deficits
despite adequate reading skills as well as reading fluency deficits despite adequate
spelling skills (Bar-Kochva & Amiel, 2016; Fayol, Zorman & Lété, 2009; Manolitsis &
Georgiou, 2015; Moll, Kunze, et al., 2014; Moll & Landerl, 2009; Torppa, Georgiou, Niemi,
Lerkkanen, & Poikkeus, 2017; Wimmer & Mayringer, 2002). Furthermore, different cognitive
constructs were found to underpin spelling and reading fluency; whereas phonological
awareness (PA; the ability to segment and manipulate speech sounds; Vellutino, Fletcher,
Snowling, & Scanlon, 2004), is more strongly related to spelling, rapid automatized naming
(RAN; the ability to quickly name aloud visual material; Denckla & Rudel, 1976) is more
strongly linked to reading fluency (Furnes & Samuelsson, 2011; Moll, Ramus, et al., 2014;
Vaessen & Blomert, 2013). Assuming that reading and spelling rely on the very same word-
specific orthographic representations, the existence of marked dissociations between
reading and spelling skills is not obvious. Investigating such dissociations provides an
excellent opportunity to gain important insights into the role of orthographic knowledge
during reading. For isolated spelling deficits, two explanations have been suggested; both
assume that individuals with isolated deficits in spelling have problems in building up
well-specified orthographic representations, but they differ in their explanation as to
how this deficit is compensated for in reading. Frith (1980) argued that underspecified
representations are sufficient to recognize words during reading even if they are not
exact enough for spelling. Based on that, Frith assumed that isolated poor spellers rely
on a partial cue reading strategy, that is, reading words by sight based on degraded
orthographic representations without considering the exact letter-by-letter structure. In
line with this interpretation, isolated poor spellers showed good performance when reading
high-frequency words but made substantially more errors than typical readers in nonword
reading. A different explanation was presented by Moll and Landerl (2009) based on German-
speaking children. In their study, isolated poor spellers showed age-adequate reading
performance for words as well as nonwords. More important, they did not show the typical
advantage of real words over corresponding pseudohomophones (i.e., unfamiliar letter
strings that sound like real words, e.g., rane for rain in English), which is taken as an
indication of lexical access of the real word spelling (see also Francuz & Borkowska,
2013). Interestingly, they nevertheless showed adequate reading latencies compared with
age-matched typically developing children even for words they could not spell. Therefore,
it was assumed that they relied on highly efficient decoding strategies2 to compensate for
their deficient orthographic knowledge, which is possible in an orthography with high
consistency of grapheme–phoneme correspondences such as German. The current study went one
step further by analyzing eye movement patterns in order to investigate to what extent
children with isolated spelling deficits apply lexical processes during reading. In
contrast to isolated deficits in spelling, isolated reading fluency deficits are hardly
described in the literature, especially for opaque languages (but see Lovett, 1987). The
phonological deficit view of dyslexia assumes that deficits in reading fluency result from
slow and effortful grapheme–phoneme decoding compensating for lack of orthographic
representations (Vellutino et al., 2004). However, recent findings suggest that poor
readers do use lexical strategies during reading and do not simply rely on decoding (e.g.,
Gangl et al., 2018; Paizi, De Luca, Zoccolotti, & Burani, 2013). An alternative suggestion
was presented by Wimmer (1993), who argued that dysfluent reading may result from
inefficient visual–verbal access that affects both sublexical and lexical reading
strategies. According to this view, dysfluent readers may have intact orthographic
representations available and may even access them during reading, but in an inefficient
way. Thus, children with isolated reading deficits may apply orthographic strategies but
still show dysfluent reading due to delayed lexical access. In line with this
interpretation, Moll and Landerl (2009) reported marked reading advantages of words over
pseudohomophones for German-speaking poor readers, indicating orthographic access for
these words. Nevertheless, overall reading times were seriously prolonged even for
correctly spelled words, which was interpreted as delayed access to verbal word forms from
existing visuo-orthographic representations. This visual–verbal access deficit view was
further supported by studies showing that children with isolated reading deficits have
marked deficits in RAN (e.g., Moll & Landerl, 2009; Torppa et al., 2017; Wimmer &
Mayringer, 2002), which also requires fast and efficient activation of verbal word forms
from the presented visual information (e.g., pictured objects or digits). In summary,
studies on isolated deficits suggest that the extent to which orthographic knowledge is
accessed during reading is associated with an individual's spelling ability, which
provides a direct indication of orthographic knowledge. Investigating marked dissociations
between reading and spelling skills, as in children with isolated disorders of reading or
spelling, is a promising approach because specific hypotheses can be derived and tested;
isolated poor spellers’ lack of orthographic knowledge should be reflected in reading
either as access of underspecified representations (Frith, 1980) or as reduced reliance on
lexical strategies (Moll & Landerl, 2009). In contrast, isolated poor readers’ unimpaired
spelling may indicate that available orthographic knowledge is (inefficiently) accessed
during reading. The current study for the first time systematically examined reading
strategies of good and poor readers with and without spelling deficits by means of eye
movement recording. Eye tracking has the major advantage that reading processes can be
investigated “online” while they take place (Rayner, 1998), enabling us to assess the use
of orthographic knowledge during reading more closely. In particular, we addressed the
question of whether differences in orthographic knowledge, as indicated by spelling
(dis)abilities, are associated with differences in accessing orthographic information
during reading. Furthermore, we were interested in whether the same association holds for
both good and poor readers. Do good readers rely on orthographic reading strategies even
if they have an obvious deficit in orthographic spelling knowledge? Do poor readers apply
different reading strategies according to differences in their orthographic spelling
knowledge? In addition to eye-tracking measures, we also assessed cognitive constructs
that have been reported as risk factors for specific learning disorders—PA, RAN, and
verbal memory (e.g., Landerl et al., 2013; Moll, Göbel, Gooch, Landerl, & Snowling, 2016).
We aimed to expand on earlier evidence that PA may be more strongly related to spelling
(deficits), whereas RAN is most strongly related to (deficits in) reading fluency (Moll &
Landerl, 2009; Moll, Ramus, et al., 2014; Wimmer & Mayringer, 2002). Corresponding
differences in cognitive profiles for children with isolated reading or spelling deficits
would be informative with respect to possible causes underlying the observed
dissociations. Eye movements were recorded while children read short and long words,
pseudohomophones, and nonwords. First, we were interested in children’s eye movement
patterns during word reading because words can be read either by a decoding strategy or by
an orthographic strategy (at least in consistent orthographies such as German), depending
on whether or not word-specific orthographic representations are available (Coltheart,
Rastle, Perry, Langdon, & Ziegler, 2001). We assessed a wide range of eye movement
variables, which are indicative of lexical or sublexical reading strategies and which were
found to differentiate between good and poor readers (Hawelka, Gagl, & Wimmer, 2010). We
expected marked group differences if children rely on different reading strategies due to
differences in orthographic knowledge. Namely, a sublexical decoding-based reading
strategy should be reflected in short forward saccades interspersed with high numbers of
fixations (De Luca, Borrelli, Judica, Spinelli, & Zoccolotti, 2002; Hawelka et al., 2010;
Krieber et al., 2016). Furthermore, it should be rather exceptional that a word receives
only one fixation because a dominance of singly fixated words would rather indicate a
lexical reading strategy of directly accessing orthographic representations (Hawelka et
al., 2010). We also examined marker effects of sublexical and lexical reading strategies
on (a) gaze duration (i.e., the sum of all fixation durations on an item prior to moving
to the next item, which is called “first pass”), (b) number of fixations (i.e., the sum of
all fixations on an item during first-pass reading), and (c) landing position (i.e., the
location of the first fixation on an item). Important markers of sublexical strategies are
effects of length, that is, a systematic increase in processing load with increasing item
length. Sublexical processing is reflected in longer gaze duration and higher number of
fixations for long items compared with short items (e.g., De Luca, Di Pace, Judica,
Spinelli, & Zoccolotti, 1999; Hawelka et al., 2010; Hutzler & Wimmer, 2004; Rau, Moeller,
& Landerl, 2014). Indeed, particularly marked effects of length are reported for nonwords
(e.g., De Luca et al., 2002; Hutzler & Wimmer, 2004; Rau et al., 2014). Sublexical
processing is further reflected in the landing position by the constant tendency to fixate
word beginnings irrespective of length (e.g., Hawelka et al., 2010; MacKeben et al.,
2004). As marker effects of lexical processing, we analyzed word superiority effects in
terms of word-pseudohomophone and lexicality effects, that is, an advantage for words
compared with pseudohomophones and nonwords, respectively. More efficient processing of
real words indicates availability of and access to orthographic representations for these
letter strings (e.g., Di Filippo, De Luca, Judica, Spinelli, & Zoccolotti, 2006; Francuz &
Borkowska, 2013; Grainger, Spinelli, & Ferrand, 2000; Moll & Landerl, 2009). If reading is
mostly based on sublexical decoding, no marked differences would be evident between
different types of stimuli in gaze duration, number of fixations, and landing position. We
assumed that readers adapt their reading strategies according to their orthographic
knowledge, reflected by their spelling performance. Children with age-adequate spelling
performance (i.e., typically developing and isolated poor readers) were assumed to use
orthographic reading strategies, which should be reflected in small length effects but
marked word superiority effects compared with pseudohomophones and nonwords on gaze
duration and number of fixations. Furthermore, we expected good spellers to adapt the
landing positions to the length of words. However, in line with previous findings,
isolated poor readers were assumed to experience delayed visual–verbal access, inducing
prolonged fixation durations compared with typically developing children despite an
adequate number of fixations. For poor spellers (i.e., isolated poor spellers and children
with combined reading and spelling deficits), we were particularly interested to see
whether we would find evidence for reduced orthographic strategies and overreliance on
decoding (independent of their reading performance). If poor spellers predominantly rely
on decoding strategies, we expected them to show marked length effects but reduced word
superiority effects on gaze duration and number of fixations. Furthermore, they should
fixate the beginnings of letter strings irrespective of length and stimulus type. We also
expected differences between the two groups of poor spellers. Whereas isolated poor
spellers’ adequate reading might result from a highly efficient compensatory decoding
strategy, children with combined deficits in reading and spelling may be less efficient
decoders due to an additional impairment in their visual–verbal access. Thus, prolonged
fixation durations and increased numbers of fixations for words were expected for children
with combined reading and spelling deficits compared with typically developing children.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Good and poor readers with and without a spelling deficit were selected based on an
extensive screening procedure with 4123 German-speaking children at the end of third grade
or beginning of fourth grade. Data were collected at two collaborating sites, Graz
(Austria) and Munich (Germany). Spelling and reading fluency skills were assessed by
standardized classroom tests (Müller, 2004; Wimmer & Mayringer, 2014; all tests are
described in the next section). A deficit in spelling and/or reading fluency was assigned
when test performance was at or below the 20th percentile. Scores at or above 25th
percentile were defined as age-adequate performance. Because none of the children with
isolated deficits had reading or spelling scores above the 75th percentile in the
nonaffected domain, children with scores higher than the 75th percentile in any of the
tests were not considered for the typically developing control group. Reading fluency
performance was further assessed by an individually administered 1-min word and nonword
reading test (Moll & Landerl, 2010). A deficit in reading was confirmed by scores below
the 20th percentile on at least one subtest and below the 25th percentile on the other
subtest. All children had normal or corrected-to-normal vision, a nonverbal IQ of at least
85, no clinical diagnosis of attention-deficit/hyperactivity disorder (ADHD), and an
unremarkable score (see below) on a parental questionnaire for attention deficits
(Döpfner, Görtz-Dorten, Lehmkuhl, Breuer, & Goletz, 2008). Overall, 137 children who
fulfilled the criteria and received parental consent participated in the study, which was
approved by the ethics committees of the University of Graz and the University of Munich.
The sample consisted of 43 typically developing children (TD group), 28 children with
isolated spelling deficits (SD group), 28 children with isolated reading deficits (RD
group), and 38 children with combined reading and spelling deficits (RSD group).

        <hss>Reading fluency</hss>

        The standardized classroom reading fluency test (SLS 2–9 [Salzburger Lese-
        Screening für die Schulstufen 2–9]; Wimmer & Mayringer, 2014; parallel test
        reliability > .86 according to manual) comprises simple sentences (e.g., “Trees
        can speak.”), which children needed to read silently and mark as semantically
        right or wrong by circling a checkmark or a cross after each sentence. The number
        of correctly marked sentences within 3 min was scored. Reading fluency was further
        assessed by an individually administered 1-min reading fluency test (SLRT-II
        [Lese- und Rechtschreibtest]; Moll & Landerl, 2010; parallel test reliability
        between .90 and .95 according to manual) containing a word reading list and a
        nonword reading list. Children were asked to read aloud each list as fast as
        possible without making errors within a time limit of 1 min. The number of
        correctly read items was determined.

        <hss>Spelling</hss>

        The standardized classroom spelling test (DRT-3 [Diagnostischer Rechtschreibtest
        für 3 Klassen]; Müller, 2004; split-half reliability = .95 according to manual)
        consists of 44 words, varying in length and difficulty, that need to be written
        into the gap of sentence frames. The experimenter first dictated each word, then
        the full sentence was read out, and finally the word was named again. The number
        of incorrect spellings was scored.

        <hss>Attention rating</hss>

        A standardized questionnaire (Döpfner et al., 2008) made up of 20 items with a
        4-point rating scale regarding symptoms of inattention (9 items), hyperactivity (7
        items) and impulsivity (4 items) was given to the parents. A score higher than
        1.10 for girls, and a score higher than 1.55 for boys, is suggestive of an AD(H)D
        diagnosis and was applied as an exclusion criterion in the current study (see
        description of participants).

        <hss>Nonverbal IQ</hss>

        The first part of the German version of the Culture Fair Intelligence Test (CFT
        20-R; Weiß, 2006; reliability = .92 as described in the manual), including the
        four subtests Series, Classification, Matrices, and Topology, was given as an
        estimate of nonverbal IQ.

        <hss>Verbal memory</hss>

        The subtest Digit Span from the German version of the Wechsler Intelligence Scale
        for Children (Petermann & Petermann, 2011) was used to assess the verbal short-
        term and working memory.

        <hss>Rapid automatized naming</hss>

        Children named a matrix made up of 40 monosyllabic digits (8, 3, 5, 2, 9) arranged
        in five columns and eight rows as quickly and accurately as possible. Item order
        was randomized, and each item was presented once in each row. The experimenter
        recorded the time children needed to name all 40 digits as well as any errors. The
        number of items named correctly per second was determined.

        <hss>Phonological awareness</hss>

        A computerized phoneme deletion task was programmed with Presentation 16.3
        (Neurobehavioral Systems, Berkeley, CA, USA). The task comprised 4 practice trials
        and 25 test trials (20 monosyllabic nonwords and 5 disyllabic nonwords) that were
        presented via headphones. Children needed to repeat each nonword first and then to
        pronounce it without a specified phoneme (e.g., “/fɔlt/ without /t/”–/fɔl/). The
        experimenter marked the response correctness by mouse clicking. Any nonword that
        was not repeated correctly was replayed up to two times. If it was still not
        pronounced correctly, it was discarded from analysis (0.9% of all items). The
        ratio of correct responses to the total number of responses was scored. Cronbach’s
        alpha was .79.

            <hss>Apparatus</hss>

            The eye movements of the children’s dominant eye were recorded inside a dimly
            lit room with an EyeLink 1000 Tower Mount eye tracker in Graz and an EyeLink
            1000 Plus Desktop Mount eye tracker (SR Research, Toronto, Ontario, Canada) in
            Munich. To minimize head movements, the forehead rest was used. The experiment
            was run with Experiment Builder software (SR Research, Version 1.10.1241) on a
            20-inch monitor (120-Hz refresh rate, 1024 × 768 resolution) and a 15.6-inch
            monitor (120-Hz refresh rate, 1280 × 960 resolution) in Graz and Munich,
            respectively. At both collaborating sites, the stimuli were presented
            identically with an uppercase letter height of about 0.62° of visual angle at
            a viewing distance of 65 cm. A spatial resolution of less than 0.5° of visual
            angle was achieved by using a standard 9-point calibration.

            <hss>Stimuli and design</hss>

            The experiment comprised 240 stimuli: 80 high-frequency words (mean absolute
            frequency of 1537.80 for 9- and 10-year old children according to the corpus
            of the database childLex [Schroeder, Würzner, Heister, Geyken, & Kliegl,
            2015]) that were either short (three to five letters) or long (six to nine
            letters), 80 pseudohomophones, and 80 nonwords. Note that German has highly
            consistent letter–sound correspondences, but sound–letter correspondences are
            often inconsistent. The words were selected so that they included sounds that
            can be transcribed with different letters/clusters. This allowed us to create
            a pseudohomophone for each word by exchanging one phonologically identical
            grapheme. The pronounceable nonwords were derived from the words by exchanging
            one consonant or vowel grapheme per syllable for another consonant or vowel
            grapheme. The stimuli were matched on number of letters and bigram and trigram
            frequency (Fs < 1.5, ps > .20) according to childLex (Schroeder et al., 2015).
            All items and item characteristics are displayed in Appendix A. Stimuli were
            assigned to three blocks of 80 items each. Two blocks comprised words and
            pseudohomophones in equal parts, and the third block comprised nonwords only.
            Four pseudorandomized orders were created with the restriction that at most
            two words or pseudohomophones appeared in immediate succession and
            corresponding words and pseudohomophones did not appear together in the same
            block.

            <hss>Procedure</hss>

            Prior to the eye-tracking experiment, children were asked to spell the 80 word
            stimuli of the eye-tracking paradigm. Words were dictated by the experimenter,
            and children wrote them into sentence frames that provided adequate semantic
            content to each word. The number of correct spellings was scored (errors of
            capitalization were not considered because they constitute a specific
            grammatical error category in German). Because we selected high-frequency
            words, we guaranteed that even poor spellers could write a reasonable amount
            of these stimuli correctly (showing that they had orthographic representations
            available). This allowed us to investigate to what extent poor spellers access
            their existing orthographic knowledge during reading. On a separate day,
            children took part in the eye-tracking experiment to avoid recognition
            effects. The four equivalent versions of the eye-tracking experiment were
            randomly assigned to the participants. Each one started with a
            word/pseudohomophone block, followed by the nonword block and the second
            word/pseudohomophone block. Short breaks were provided between the blocks and
            after the first half of the nonword block. Each block was introduced with
            practice items. Feedback was given only during practice. Items were displayed
            in Arial font and appeared arranged in single lines separated by single spaces
            in black on a white background in the center of the computer screen after
            children had fixated a left-sided yellow smiley, which was linked to a
            fixation trigger, for at least 250 ms. Recalibration was done if no fixation
            was detected within 5000 ms, and afterward the experiment continued from the
            interrupted point. Lines consisted of 10 items each (8 target items and 2
            filler items at the beginning and the end), and the first item of each line
            was displayed at the location where the smiley was shown. Children needed to
            read each item aloud without making errors while their eye movements were
            recorded and reading was tape-recorded. Reading accuracy was noted by the
            experimenter. Hesitations and inadequate word stress were not considered as
            errors. After the children had read a whole line, they were asked to look
            immediately at a small cross in the lower right corner of the screen. As soon
            as the cross was fixated, the line disappeared and the next trial started with
            the smiley on the left side of the screen. Cronbach’s alpha for words,
            pseudohomophones, and nonwords was high for reading accuracy (> .71) and
            number of fixations (> .92).

            <hss>Data treatment</hss>

            Overall data loss due to problems with calibration accuracy or because a child
            did not read the whole line was 2.10%. Following the standard procedure of
            eye-tracking data treatment (e.g., Jones, Snowling, & Moll, 2016; Moscati,
            Zhan, & Zhou, 2017), fixations shorter than 80 ms were excluded and fixations
            deriving from microsaccades (within 0.5° of visual angle) were pooled
            together. Furthermore, for each eye movement measure, individual outliers
            (i.e., data deviating more than 2.5 standard deviations from the individual
            mean of each condition [Length × Stimulus Type]) were removed (2.10%;
            Liversedge et al., 2016). Each target item was defined as a region of
            interest, and only correctly read items were considered for analyses.

<hs>  Group characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~

A summary of the descriptive and cognitive measures for each group is provided in Table 1.
Group differences in the standardized reading and spelling measures reflected our
selection criteria; the deficit groups performed comparably to typically developing
children in their unimpaired skills and comparably to each other in their impaired skills.
Although our cutoff criteria for poor performance were somewhat lenient, Table 1 indicates
that all deficit groups were seriously impaired in their affected skills with mean scores
around the 10th percentile. Table 1 further shows that the groups were comparable in age,
exhibited equally low parental ratings of ADHD symptoms, and did not differ significantly
in their nonverbal IQ and verbal memory scores. In line with earlier findings (e.g., Moll
& Landerl, 2009; Wimmer & Mayringer, 2002), the two groups of poor readers (RD and RSD)
showed similarly poor performance in RAN compared with the TD and SD groups, who did not
differ significantly from each other. In the PA task, only the RSD group showed
significantly lower scores than all other groups.

<hs>  Reading and spelling accuracy for words, pseudohomophones, and nonwords</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In line with the literature on transparent orthographies (e.g., Wimmer 1993; Wimmer &
Hummer, 1990), reading accuracy across groups was generally high for all stimulus types
(see Table 2). Nonparametric Kruskal–Wallis tests indicated that reading accuracy scores
of the SD group were largely comparable to typically developing children, who performed
close to ceiling. Even for the two groups of poor readers (RD and RSD), who performed very
similarly (except for lower accuracy for long pseudohomophones in the RSD group compared
with the RD group), overall reasonably high reading accuracy rates were observed, although
significantly different from typically developing children. Table 2 also shows the
percentage of correct spellings of the experimental word stimuli. In line with our group
selection, both groups of poor spellers (SD and RSD) showed significantly lower
percentages of correct spellings than the two groups of good spellers (TD and RD). Thus,
poor spellers were less familiar with the experimental word stimuli and had less exact
orthographic representations available than good spellers. However, it should be noted
that performance on the experimental task was relatively high; even children of the RSD
group spelled on average two thirds of these high-frequency stimuli correctly. This was
expected because we selected high-frequency words to ensure that even poor spellers had
some orthographic representations available in order to be able to investigate to what
extent they accessed orthographic knowledge during reading.

<hs>  Eye movement characteristics during word reading</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In a first step, we investigated children’s eye movements for real words only to get a
first impression of their natural reading behavior. Following the approach by Hawelka et
al. (2010), we compared the four groups on a large number of eye-tracking parameters that
might be informative with respect to the application of lexical versus sublexical reading
strategies. Given that reading accuracy rates were high for both short and long words
across groups, analyses were based on correctly read words only. The first interesting
finding evident from Table 3 is that children in the SD group did not differ significantly
from typically developing children in any of the investigated eye-tracking parameters.
Thus, contrary to our expectations, we did not find any evidence that they would show a
compensatory overreliance on decoding mechanisms. Furthermore, we had expected that the
RSD group would show more marked decoding strategies, whereas the RD group was assumed to
predominantly rely on orthographic strategies. However, both groups of poor readers (RD
and RSD) did show evidence for a more piecemeal reading style; apart from prolonged gaze
durations, reflecting their reading fluency deficits, they showed significantly higher
numbers of fixations and also more between-word regressions going back to a word after it
was left already. They also showed a clearly lower percentage of words that received a
single fixation only, suggesting that they were mostly unable to process words directly at
a glance. Children with RSD showed more marked impairments than children with RD, with
prolonged gaze durations, mean fixation, and single fixation durations compared with all
other groups. Furthermore, they tended to show shorter forward saccades compared with
typically developing children (p = .052). Across all groups, only between 10% and 15% of
all within-word fixations during first pass were regressive (going backward) and groups
also did not differ significantly with respect to their first fixation positions (i.e.,
landing positions) on words.

        <hss>Data analyses</hss>

        Effects of length and word superiority were investigated in the following three
        eye-tracking parameters: gaze duration as an indicator of temporal processing and
        number of fixations and landing position as spatial measures. To examine specific
        effects of length and word superiority, and to avoid spurious interaction effects
        (i.e., overadditivity effects) due to general performance differences between the
        groups, individual z-scores were calculated (Faust, Balota, Spieler, & Ferraro,
        1999). This seemed important because marked group differences were already
        observed for word reading. For each variable of interest, individual z-scores were
        obtained by taking each individual’s scores, subtracting the overall mean across
        all correctly read items, and dividing it by the overall standard deviation. Thus,
        z-scores reflect an individual’s performance on an item relative to the
        performance on all other items (Paizi et al., 2013). The z-scores for the three
        eye-tracking parameters were analyzed separately by means of linear mixed-effect
        models (LMMs; for a similar approach see Paizi et al., 2013). These robust
        analyses are particularly appropriate for the repeated-measures designs we aimed
        to apply to investigate the marker effects of lexical and sublexical processing;
        LMMs allow treating participants and items as random effects in a single analysis,
        and they maintain individual variance by considering the whole data without the
        need for prior averaging as is known in traditional approaches such as analyses of
        variance (ANOVAs; Baayen, Davidson, & Bates, 2008). LMMs were run in R (R Core
        Team, 2017) and were fitted by the mixed function of the afex package (Version
        0.16-1; Singmann, Bolker, Westfall, & Aust, 2016), which is based on the lme4
        package (Version 1.1-12; Bates, Maechler, Bolker, & Walker, 2015). Group (TD, SD,
        RD, or RSD), length (short or long), and word superiority (words,
        pseudohomophones, or nonwords) were entered as fixed effects including interaction
        terms. Participants and items were entered as crossed random effects, for which we
        specified random slopes for each within-participants and within-items factor,
        respectively (see Barr, Levy, Scheepers, & Tily, 2013). To achieve better
        convergence, we removed random correlations (Barr et al., 2013). Likelihood ratio
        tests were used to compute p values for all fixed effects as implemented in the
        mixed function. To decompose significant main and interaction effects, post hoc
        contrasts were performed using the lsmeans package (Version 2.25-5; Lenth, 2016)
        and the Benjamini–Hochberg method for adjusting p values (Benjamini & Hochberg,
        1995). In Table 4, the LMM results are presented separately for each dependent
        measure; in addition, LMM estimates are displayed in Fig. 1. Note that due to
        z-scores, main effects of group are negligible and, therefore, are not mentioned
        further. Raw scores are reported in Appendix B.

        <hss>Gaze duration</hss>

        If poor spellers (SD and RSD groups) relied strongly on decoding strategies, they
        should show marked length effects and small word superiority effects. Good
        spellers (TD and RD groups) were expected to show the reverse pattern. The
        analysis on gaze duration revealed reliable effects of length and word superiority
        (see Table 4); prolonged gaze durations were found for long stimuli compared with
        short stimuli and for pseudohomophones and nonwords compared with words (ps <
        .001). The significant interaction between length and word superiority indicated
        more marked length effects for nonwords compared with words and pseudohomophones
        (ps < .001). The group by length interaction tended to be significant. Post hoc
        contrasts revealed marked length effects across all groups (ps < .001). However,
        both groups of poor readers (RD and RSD) were less affected by length than
        typically developing children (ps < .05). The significant three-way interaction
        indicated that the reduced length effects in poor readers were limited to nonwords
        (ps < .001), which was rather surprising. Children with RSD also showed reduced
        length effects for nonwords compared with children with SD (p < .05). The Group ×
        Word Superiority and Group × Length × Word Superiority interactions were also
        significant. Post hoc contrasts revealed that the RSD group exhibited smaller
        word–nonword discrepancies than all other groups for long stimuli (ps < .05). In
        addition, the RSD group also showed a smaller word advantage relative to
        pseudohomophones than the SD group (p < .05). These reduced word superiority
        effects provide the first evidence for overreliance on decoding strategies among
        children with RSD. Note that the SD group was also found to show smaller
        word–nonword discrepancies compared with the RD group (p < .05), even though not
        compared with typically developing children (p > .20). Importantly, however, all
        four groups showed marked effects of word superiority (i.e., shorter gaze
        durations for words compared with pseudohomophones and nonwords, ps < .001),
        indicating orthographic processing.

        <hss>Number of fixations</hss>

        Once again, the main question with respect to poor spellers (SD and RSD groups)
        was whether we would find evidence of overreliance on decoding strategies as
        indicated by marked length effects and small word superiority effects. For good
        spellers (TD and RD groups), the reverse pattern was expected. The LMM analysis on
        z-scores for numbers of fixations revealed significant main effects of length and
        word superiority, with higher fixation counts for long stimuli than for short
        stimuli as well as for pseudohomophones and nonwords than for words (ps < .001).
        The interaction between length and word superiority was again significant, showing
        that the word–nonword discrepancy was smaller for short stimuli than for long
        stimuli (p < .05). Furthermore, effects of length were more marked for nonwords
        than for words (p < .05). The group by length interaction as well as the three-way
        interaction failed to be significant, indicating that all groups were similarly
        affected by length. The Group × Word Superiority interaction was significant. Post
        hoc contrasts showed that the discrepancy between words and nonwords was
        significantly smaller in the RSD group than in the TD group (p = .01) and even
        marginally smaller than in the SD and RD groups (ps < .09). These reduced
        lexicality effects suggest that children with RSD relied more strongly on decoding
        strategies than all other groups. However, significant effects of word superiority
        (i.e., less fixations for words compared with pseudohomophones and nonwords) were
        obtained once more in each group (ps < .01). This means that even children with
        RSD relied at least to some degree on orthographic processes during reading.

        <hss>Landing position</hss>

        Reduced lexical strategies among poor spellers should induce similar landing
        positions at the beginning of letter strings irrespective of item type. Good
        spellers were expected to adapt their landing position to the length of words (but
        not nonwords) and, thus, to show marked length effects for those. Again, the main
        effects of length and word superiority were significant. As expected, shorter
        landing positions were observed for short stimuli than for long stimuli as well as
        for nonwords than for words and pseudohomophones (ps < .001). The marginally
        significant length by word superiority interaction was due to the fact that
        landing positions on words and pseudohomophones were affected by length (ps <
        .05), whereas those on nonwords were not (p > .87). The group by length
        interaction was also significant. Post hoc comparisons revealed smaller length
        effects on the landing positions of the RSD group compared with all other groups
        (TD and SD: ps < .001; RD: p = .06). Interestingly, there was no difference in the
        landing positions between short and long stimuli for the RSD group (p > .87; see
        Fig. 1). Thus, children with RSD fixated the beginnings of items irrespective of
        length and stimulus type, whereas all other groups adapted their landing positions
        to the length of the stimuli. This is a further indication for reduced
        orthographic reading strategies in the RSD group. The group by word superiority
        interaction and the three-way interaction were not significant.

<h>DISCUSSION</h>
----------

The lexical quality hypothesis (Perfetti, 2007; Perfetti & Hart, 2001) postulates that
orthographic knowledge plays an important role in spelling as well as efficient reading.
Whereas most other studies on orthographic processing have focused on reading only, the
current study implemented spelling ability as an indicator of orthographic knowledge. The
assumption was that words that can be spelled correctly are represented in detail in the
orthographic lexicon. Note that even though German has highly consistent grapheme–phoneme
correspondences, the consistency of phoneme–grapheme correspondences is much lower. Thus,
to spell words correctly, children must have exact word-specific orthographic knowledge
available. The current study investigated the role of orthographic knowledge for reading
by exploiting the fact that reading and spelling skills frequently dissociate during
development. The first interesting finding was that, contrary to our expectations,
children of the SD group showed no indication of overreliance on sublexical decoding
strategies during reading due to lack of orthographic knowledge. The only exception was
the smaller word superiority effect compared with matched nonwords, in contrast to the RD
group in the gaze duration measure. Overall, SD children’s eye movement patterns were
highly similar to typically developing children, and SD children also showed comparable
effects of length and word superiority. Thus, SD children’s balance between sublexical and
lexical reading procedures seems to be age adequate. In particular, Moll and Landerl’s
(2009) finding of a nonsignificant word superiority effect compared with matched
pseudohomophones, even for words children with SD had spelled correctly, was not
replicated in the current group of SD children and was perhaps due to lack of statistical
power in their relatively small sample of 14 children. The findings of the current study
rather support Frith’s (1980) perspective that children with SD rely on partial cue
reading strategies, that is, orthographic reading processes based on low-quality
orthographic representations that are sufficient for word recognition but do not allow
full retrieval of the correct letter sequence for spelling. However, note that the current
findings are also not fully in line with Frith’s interpretation, suggesting that children
with SD rely on partial cue reading strategies accompanied by deficits in decoding:
Replicating Moll and Landerl’s (2009) findings, children with SD showed age-adequate
decoding of nonwords. In part, this may be explained by the fact that in more transparent
orthographies, such as German, the highly consistent grapheme–phoneme correspondence rules
facilitate the development of good decoding skills. For the RD group, we had predicted
evidence for applying these children’s orthographic knowledge indicated by good spelling
performance during reading. Indeed, children with RD showed length and word superiority
effects that were largely comparable to typically developing children. This finding is
interesting with respect to the lexical quality hypothesis (Perfetti, 2007) because it
shows that lexical representations that are of sufficient quality for spelling do not
necessarily guarantee fast and efficient access during reading. Our evidence also
contradicts the view that deficits in reading fluency are simply a consequence of a slow
decoding-based reading style due to lack of orthographic knowledge. It rather supports the
assumption that fluency deficits arise from a delayed visual–verbal access (Moll &
Landerl, 2009; Wimmer, 1993). However, in addition to the age-adequate marker effects and
prolonged gaze durations for words, which simply reflected their dysfluent reading style,
children with RD also showed more fixations, regressions, and a lower number of words that
received only a single fixation than typically developing children. The combination of
standard effects of length and word superiority with increased numbers of fixations
(forward as well as backward) has not been reported before. Typically, higher fixation
counts are assumed to reflect decoding strategies (see Hawelka et al., 2010). However, in
the current context, they might just as well be a consequence of RD children’s problems to
access their orthographic representations; during a seriously prolonged access time,
readers perhaps look harder at the words to be read, which may induce longer fixation
durations as well as increased numbers of fixations and regressions. Note that the mean
difference in gaze duration between RD and TD children was 205 ms, which easily allows for
an additional fixation. A surprising finding was that for nonwords children with reading
deficits (both RD and RSD groups) showed smaller length effects on gaze duration than
typically developing children. In general, marked effects of length are expected,
especially for nonwords among poor readers, reflecting a particular problem with decoding
inherent in dyslexia (Rack, Snowling, & Olson, 1992; Wimmer, 1996). However, findings are
inconsistent, particularly in transparent orthographies. Whereas some studies reported
more marked nonword length effects for dyslexic readers compared with typically developing
readers (e.g., De Luca et al., 2002; Hutzler & Wimmer, 2004; Ziegler, Perry, Ma-Wyatt,
Ladner, & Schulte-Körne, 2003; Zoccolotti, De Luca, Judica, & Spinelli, 2008), others did
not (Di Filippo et al., 2006; Di Filippo & Zoccolotti, 2012). Nevertheless, smaller
nonword length effects for poor readers than for good readers have not been reported yet.
These reduced nonword length effects in RD and RSD children might be explained by more
practice in decoding if this were the dominant reading strategy among poor readers.
However, the current study did not find evidence for stronger reliance on decoding, at
least not for children with RD. Thus, this explanation seems unlikely. Another possible
explanation is that poor readers may have a specific advantage in decoding digraphs and
trigraphs at the subword level. This is suggested by an unexpected finding of a Dutch
study (Marinus & de Jong, 2010); dyslexic readers read words and nonwords with digraphs
faster than matched items without digraphs, whereas proficient readers did not benefit
from the presence of digraphs. A possible explanation of this finding is that the slow
reading style of poor readers may enable detection of digraphs before activation of
incorrect phonemes due to strict letter-by-letter decoding, which would delay the reading
process as supposed in the dual route cascaded model (Coltheart et al., 2001). In the
current study, the long stimuli comprised more digraphs and trigraphs than the short
stimuli. Thus, it is possible that poor readers had a specific advantage in decoding long
nonwords, inducing a smaller length effect compared with typically developing children.
Finally, the results for the RSD group revealed an overall inadequate eye movement
pattern. Similar to the RD group, children in the RSD group showed prolonged gaze
durations, increased numbers of fixations, more regressions, and less singly fixated words
compared with typically developing children. However, they were clearly more strongly
affected in their fixation durations than all other groups (longer gaze durations, mean
fixation, and single fixation durations) and tended to show shorter forward saccades than
the TD group as well. Importantly, the RSD group was the only group that showed evidence
for reduced reliance on orthographic reading processes indicated by reduced word–nonword
discrepancies on gaze duration and number of fixations compared with the other groups.
This is in line with findings on dyslexic individuals showing reduced effects of
lexicality compared with typically developed readers (De Luca, Burani, Paizi, Spinelli, &
Zoccolotti, 2010; Di Filippo & Zoccolotti, 2012). Furthermore, children with RSD were
found to consistently fixate item beginnings irrespective of length and item type. The
findings confirm our assumption that children with RSD rely more on decoding strategies
due to insufficient orthographic representations as well as delayed visual–verbal access
(see also Hawelka et al., 2010). Nevertheless, note that significant word superiority
effects on gaze duration and number of fixations were found among children with RSD as
well, that is, shorter gaze durations and less fixations for words compared with
pseudohomophones and nonwords, respectively. Thus, even children with RSD showed some
spared reliance on orthographic strategies, at least for the easiest items. With respect
to associated cognitive deficits, we focused on PA and RAN abilities because previous
studies suggest that these are main predictors of spelling and reading skills,
respectively. In line with previous findings (e.g., Moll & Landerl, 2009; Torppa et al.,
2017; Wimmer & Mayringer, 2002), the current study found marked deficits in RAN among poor
readers (both RD and RSD groups). Given that RAN is supposed to measure efficient verbal
access from a visual symbol, this finding corroborates the assumption that reading fluency
deficits arise from delayed visual–verbal access (Wimmer, 1993). Findings are less clear
for the SD group. Whereas some previous studies found PA deficits among isolated poor
spellers (e.g., Fayol et al., 2009; Torppa et al., 2017; Wimmer & Mayringer, 2002), the
current study and others did not (e.g., Manolitsis & Georgiou, 2015; Moll & Landerl,
2009). The assumption is that children with SD may be able to compensate for an early
deficit in PA, at least in more transparent orthographies (Wimmer & Mayringer, 2002; Moll
& Landerl, 2009), so that deficits in PA at the end of primary school are mainly evident
in children with RSD. This was also observed in the current study and supports Wolf and
Bowers’ (1999) double-deficit view of dyslexia. To conclude, our findings suggest that
good readers rely on orthographic strategies during reading even if they have deficits in
orthographic knowledge as indicated by poor spelling performance. Thus, spelling deficits
are not necessarily associated with decoding strategies during reading. Whereas spelling
rests on fully specified orthographic representations, reading does not (Perfetti, 1992).
However, even if adequate reading builds on orthographic processes, the opposite
deduction—that poor readers’ dysfluency results from decoding—seems not to be true. We
found strong evidence for orthographic reading strategies among children with RD, and even
among children with RSD some spared reliance on orthographic strategies was observed.
Hence, dysfluency may be primarily caused by deficient visual–verbal access rather than
overreliance on decoding (Wimmer, 1993). Thus, the current study shows that spelling
deficits, like reading deficits, are not systematically associated with deficits in
lexical reading. Nonetheless, the buildup of high-quality word-specific lexical
representations is crucial for the development of appropriate reading and spelling skills.


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<ART>Recognizing the same face in different contexts: Testing within-person face recognition in typical development and in autism
================================================================================

Authors: Louise Neil, Giulia Cappagli, Themelis Karaminis, Rob Jenkins, Elizabeth Pellicano
DOI: 10.1016/j.jecp.2015.09.029
Year: 2016  |  Pages: 139-153
ASJC codes: 3204, 3205
Keywords: Autism, Children, Development, Face perception, Face recognition, Identity

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Unfamiliar face recognition follows a particularly protracted developmental trajectory and is more likely to be atypical in children with autism than those without autism. There is a paucity of research, however, examining the ability to recognize the same face across multiple naturally varying images. Here, we investigated within-person face recognition in children with and without autism. In Experiment 1, typically developing 6- and 7-year-olds, 8- and 9-year-olds, 10- and 11-year-olds, 12- to 14-year-olds, and adults were given 40 grayscale photographs of two distinct male identities (20 of each face taken at different ages, from different angles, and in different lighting conditions) and were asked to sort them by identity. Children mistook images of the same person as images of different people, subdividing each individual into many perceived identities. Younger children divided images into more perceived identities than adults and also made more misidentification errors (placing two different identities together in the same group) than older children and adults. In Experiment 2, we used the same procedure with 32 cognitively able children with autism. Autistic children reported a similar number of identities and made similar numbers of misidentification errors to a group of typical children of similar age and ability. Fine-grained analysis using matrices revealed marginal group differences in overall performance. We suggest that the immature performance in typical and autistic children could arise from problems extracting the perceptual commonalities from different images of the same person and building stable representations of facial identity.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Face identity recognition is a complex skill performed rapidly and seemingly effortlessly
by mature adults. The ability to discriminate between faces is present very early in
development (Field, Cohen, Garcia, & Greenberg, 1984) and improves markedly between early
childhood and adolescence (Bruce et al., 2000; Carey, Diamond, & Woods, 1980; Ellis, 1992;
Mondloch, Geldart, Maurer, & Le Grand, 2003). Yet the emergence of adult face expertise
follows a protracted developmental trajectory, with performance on tests of unfamiliar
face recognition not approaching maturity until well into adulthood (Germine, Duchaine, &
Nakayama, 2011; Susilo, Germine, & Duchaine, 2013). Much research has focused on the
mechanisms underlying this lengthy course of development, including holistic, configural,
and norm-based coding abilities (Crookes & McKone, 2009; Jeffery, Read, & Rhodes, 2013;
Mondloch, Le Grand, & Maurer, 2002; Mondloch et al., 2003; Pellicano & Rhodes, 2003;
Pellicano, Rhodes, & Peters, 2006; Taylor, Batty, & Itier, 2004; Turati, Sangrigoli, Ruel,
& de Schonen, 2004), which continue to be the subject of much debate (McKone, Crookes,
Jeffery, & Dilks, 2012). This research, however, has focused on individuals’ abilities to
tell different faces apart (referred to here as between-person face recognition) or to
match an image that differs in one experimentally manipulated way, such as facial
expression or viewpoint, to a target image of the same identity (Bruce et al., 2000;
Ellis, 1992; Mondloch et al., 2003; Sporer, Trinkl, & Guberova, 2007). Consequently,
existing research cannot explain how we recognize the same “real” face in different
contexts (Burton, 2013). Only one identified study has investigated individuals’ ability
to recognize the same identity across several naturally varying images of the same face
(referred to here as within-person face recognition). Working on the assumption that
muscular movement, lighting, resolution, and depth of contrast can lead to considerable
variability in photographs of the same face, Jenkins, White, Van Montfort, and Burton
(2011) gave adult participants 20 naturally varying images each of two unfamiliar Dutch
celebrities sourced from the Internet and asked them to sort the photographs by identity.
No participant arrived at the correct solution of two identities. In fact, the median
solution was 7.5 identities, and solutions ranged considerably from 3 to 16. These
findings suggest that adults find it extremely challenging to process the wide variability
in “real” photographs of the same (unfamiliar) face. The mechanisms necessary for the
difficult task of within-person face recognition are as yet unknown, but it is possible
that an averaged representation of facial identity, central to several models of between-
face identity recognition (Bruce & Young, 1986; Burton, Jenkins, Hancock, & White, 2005;
Valentine, 1991), plays a crucial role. According to norm-based coding models (Leopold,
O’Toole, Vetter, & Blantz, 2001; Rhodes & Jeffery, 2006), a viewer creates an internal
representation of an average face based on all of the different faces to which that
particular individual has been exposed. Accurate between-person face recognition occurs
through the positioning of facial identities as vectors from this norm in a
multidimensional face space (Valentine, 1991). Burton et al. (2005) further proposed that
a “population mean” is calculated for each separate facial identity and updated after
every encounter to improve reliability. Successful within-person face recognition,
therefore, may require a particularly fine-grained norm-based coding system in which an
averaged internal representation is created separately for each facial identity. New
images of the same face may then be coded as deviations from that particular identity’s
“norm.” If judged to be close enough in multidimensional face space, commonalities
extracted from this image may then be incorporated into this normed representation. Bruce
(1994) suggested that it is continuous exposure to faces from various viewpoints, lighting
conditions, and angles that helps us to derive stable averaged representations of faces
through variation. According to Burton et al. (2005), these internalized representations
adopt only the elements of identity that are consistent across many viewings (e.g., the
structural aspects of the face such as the spatial relationship between the eyes and nose
or between the nose and mouth) and discard the more superficial and changeable aspects of
a face (e.g., haircut, lighting, expression). Jenkins et al.’s (2011) task, therefore, may
be a particularly challenging one because it may require an ability to create and
continually update an internalized representation of a new facial identity, reliably
distilling the stable elements of identity within a series of 40 encountered images of
only two unfamiliar people. Studies investigating individuals’ ability to distinguish
different identities suggest that a norm-based face space is present in young children,
including those as young as 4 years (Jeffery et al., 2013; Nishimura, Maurer, Jeffery,
Pellicano, & Rhodes, 2008; Pimperton, Pellicano, Jeffery, & Rhodes, 2009). In fact,
different responses to average faces, as opposed to “distinct faces,” in infants (Rhodes,
Geddes, Jeffery, Dziurawiec, & Clark, 2002) suggest that it could be present even earlier.
Whereas Crookes and McKone (2009) argued that general cognitive improvements in the visual
system or in working memory are likely candidates for the mechanisms underlying age-
related improvements in face identity recognition, Jeffery et al. (2013) suggested that
the quantity and quality of dimensions of face space may undergo fine-tuning during
development, leading to a more efficient and precise face identification system. To date,
all of this research has examined norm-based coding within the context of between-person
face recognition. There is no study examining within-person recognition of unfamiliar
faces in different contexts in children. As challenging as it is for adults, Jenkins et
al.’s (2011) task may be especially difficult for children because it may require
participants to create and update an average of two facial identities repeatedly in a
short space of time, extract the commonalities between images, and build a stable
representation “online.” Within-person face recognition might also be particularly
challenging for children diagnosed with autism, a neurodevelopmental condition that
affects the way an individual interacts with and experiences the world around him or her
(American Psychiatric Association [APA], 2013). Atypicalities in face processing are well
documented in individuals on the autism spectrum (Rutherford, Clements, & Sekuler, 2007;
Wallace, Coleman, & Bailey, 2008; Wilson, Palermo, & Brock, 2012; Wolf et al., 2008),
including greater difficulty in recognizing unfamiliar faces in autistic children compared
with children of similar age and ability (Boucher & Lewis, 1992; Klin et al., 1999). There
have also been swathes of studies that failed to find any such differences. Indeed,
Weigelt, Koldewyn, and Kanwisher (2012) reviewed 90 studies, of which only half found that
autistic people perform worse than typical individuals (n = 46), with the other half
finding no difference (n = 44), although they concluded that autistic individuals had
difficulties in tasks specifically involving face memory and in discriminating eye gaze.
Researchers investigating the source of potential difficulties in face recognition in
autism have implicated weaker norm-based coding of facial identity (Ewing, Pellicano, &
Rhodes, 2013; Fiorentini, Gray, Rhodes, Jeffery, & Pellicano, 2012; Pellicano, Jeffery,
Burr, & Rhodes, 2007; Rhodes, Ewing, Jeffery, Avard, & Taylor, 2014). These experimental
findings are consistent with a recent theoretical account that situates autistic
perception within a Bayesian framework. According to Pellicano and Burr (2012), autistic
individuals are less likely to use prior information to interpret incoming sensory
information and, therefore, have difficulties in discerning the salience of incoming
sensory information. In face identity recognition, less reliance on prior knowledge (i.e.,
knowledge accrued with experience) may translate to difficulties in discarding information
that is irrelevant to identity judgments (e.g., the superficial and changeable aspects of
facial images) and identifying the commonalities over repeated viewings necessary for face
identification according to Bruce (1994) and Burton et al.’s (2005) models. If autistic
individuals have difficulty in creating or updating an abstract representation of a
person’s face, they should have difficulty in recognizing several unfamiliar images of the
same person as belonging to the same face.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

The aims of this study were twofold. First, we sought to extend research on within-person
face recognition using multiple images of the same identity to children and investigate
age-related changes in this ability. In Experiment 1, we modified Jenkins et al.’s (2011)
procedure to ensure that it was engaging and developmentally appropriate for children
between 6 and 14 years of age. Children were shown 40 naturally varying photographs of two
different male faces and were asked to sort them by identity. We predicted that, in line
with other findings on the development of between-person face identity recognition,
younger participants would perform less well than older participants, perceiving a greater
number of identities among the 40 images of the two men than older participants. Second,
we investigated the within-person face recognition skills of children with and without
autism. In Experiment 2, we compared autistic children’s task performance with a subgroup
of children from Experiment 1 matched for age and intellectual ability. We predicted that
children on the autism spectrum would have difficulties in developing stable internal
representations of newly presented unfamiliar identities (cf. Pellicano & Burr, 2012)
incommensurate with their age and ability.

        <hss>Participants</hss>

        A total of 77 children participated in this experiment, including 16 6- and
        7-year-olds (M = 6;10 [years/months], range = 6;0–7;11, 6 girls), 28 8- and
        9-year-olds (M = 9;3, range = 8;2–9;11, 9 girls), 20 10- and 11-year-olds (M =
        10;11, range = 10;1–11;11, 14 girls), and 13 12- to 14-year-olds (M = 13;2, range
        = 12;0–14;9, 11 girls). One additional child was tested but excluded from analysis
        for not understanding task instructions (see below). In addition, 15 adults
        between 26 and 37 years of age also participated (M = 31;1, 6 women). Participants
        were recruited through mainstream schools and community contacts in the Greater
        London area.

        <hss>Stimuli</hss>

        Participants were presented with 40 laminated grayscale photographs of two male
        identities (20 of “Rob” and 20 of “Dom”) measuring 85 × 65 mm each. The
        individuals in the photographs were unfamiliar to participants. Because this study
        sought to examine children’s responses to naturally occurring variability in
        images of faces, we did not use experimentally manipulated images. Rather, and
        following Jenkins et al. (2011), the images encompassed a diverse range of natural
        photographs taken of the identities at different ages, from different angles, and
        in different lighting conditions. Photographs showed faces in front view with no
        obstructions. The images used can be seen in Fig. 1.

        <hss>Procedure</hss>

        Participants were seen individually in a quiet room at their school, their place
        of work, or the university. For all participants—children and adults—the task was
        presented within the context of a game, with a cover story about a detective who
        needed their help to identify criminal suspects. Next, participants were presented
        with the 40 grayscale images in a shuffled deck and were instructed to sort the
        photographs into piles by identity. Specifically, participants were instructed to
        place photographs of the same person together and to place photographs of
        different people into different piles, so that they ended up with a separate pile
        for each different person. Participants were asked to repeat the task instructions
        to the experimenter in their own words before proceeding so that the experimenter
        could be confident that participants fully understood them. Participants were
        given 10 min to complete the task. Pilot testing suggested that this time limit
        was adequate. Indeed, during the experiment proper, the majority of participants
        (including half of 6- and 7-year-olds) did not make use of all the time available
        to them, indicating to the experimenter that they had finished the task well
        before reaching the time limit. Following Jenkins et al. (2011), no further
        instructions were given and no feedback was provided regarding accuracy.
        Photographs were numbered on the reverse from 1 to 40, and the experimenter used
        these numbers to record which photographs had been placed in each pile. The number
        of identities perceived by each participant (maximum possible = 40) and the number
        of misidentification errors (where the two different identities were perceived to
        be the same identity) were the dependent variables of interest. This study was
        granted ethical approval by the Institute of Education’s research ethics
        committee. Written informed consent was obtained by participating adults and from
        parents prior to their children’s participation in this study. Children gave their
        verbal assent to take part.

        <hss>Number of perceived identities</hss>

        Descriptive statistics are reported in Table 1. Consistent with Jenkins et al.
        (2011), adults (n = 15) often mistook images of the same person as images of
        different people, subdividing Rob and Dom into many perceived identities (median =
        5, range = 2–28). Children (n = 77) fractionated the identities even further
        (median = 14.5, range = 2–40), frequently judging images of the same identity to
        be too dissimilar to go together. Two adults and none of the children arrived at
        the correct solution. Performance on the task varied considerably within each age
        group, as can be seen in Fig. 2A. To investigate age-related differences in the
        number of perceived identities further, we carried out a mixed-design analysis of
        variance (ANOVA) with age group (6- and 7-year-olds, 8- and 9-year-olds, 10- and
        11-year-olds, 12- to 14-year-olds, or adults) as the between-participants factor
        and identity (Rob or Dom) as the within-participants factor. There was a
        significant effect of age, F(1, 87) = 3.80, p = .01, ηp2 = .15. Planned
        comparisons revealed that adults (M = 10.60, SD = 9.28) divided images into
        significantly fewer groups than both 6- and 7-year-olds (M = 18.81, SD = 9.34),
        t(29) = 2.45, p = .02, d = 0.88, and 10- and 11-year-olds (M = 17.55, SD = 8.51),
        t(33) = 2.30, p = .03, d = 0.78. There were no other significant differences (all
        ps > .10). There was a significant main effect of identity, F(1, 87) = 5.33, p =
        .02, ηp2 = .06, with images of Rob divided into significantly fewer piles (M =
        8.30, SD = 4.72) than Dom (M = 9.07, SD = 4.82). There was no significant identity
        × age group interaction, F(4, 87) = 5.33, p = .88, ηp2 = .01.

        <hss>Misidentification errors</hss>

        In Jenkins et al.’s (2011) study, poor performance was principally a failure to
        unify images of the same identity, with adults unlikely to make any
        misidentification errors (placing images of two different identities in the same
        pile). To assess whether the same was true in our developmental sample, each of an
        individual’s “perceived identities” (image piles) was assigned a “0” if it
        (correctly) featured images of only one identity (i.e., either Rob or Dom) and a
        “1” if it featured images of both identities (i.e., Rob and Dom). These scores
        were summed to create a total error score for each participant (maximum score =
        20). Similar to Jenkins and colleagues, misidentification errors among adults were
        rare (median = 0, range = 0–1), but these errors were more common in children
        (median = 2, range = 0–9) (see Table 1). The numbers of misidentification errors
        varied considerably among the childhood age groups (see Fig. 2B). To investigate
        developmental effects, a one-way ANOVA was performed on misidentification errors.
        There was a significant effect of age group, F(4, 87) = 7.86, p < .001, ηp2 = .27.
        Planned comparisons suggested that, broadly, misidentification errors decreased
        with age. Although 6- and 7-year-olds (M = 3.63, SD = 2.78) did not make
        significantly more errors than 8- and 9-year-olds (M = 2.21, SD = 2.28), p = .08,
        d = 0.56, they did make significantly more errors than 10- and 11-year-olds (M =
        0.95, SD = 1.20), t(34) = 3.89, p < .001, d = 1.25, 12-to 14-year-olds (M = 1.54,
        SD = 1.39), t(27) = 2.46, p = .02, d = 0.95, and adults (M = 0.20, SD = 0.41),
        t(29) = 4.72, p < .001, d = 1.73. In addition, 8- and 9-year-olds made
        significantly more errors than 10- and 11-year-olds, t(42.69) = 2.49, p = .02, d =
        0.69, and adults, t(41) = 3.37, p = .002, d = 1.23. Furthermore, 10- and 11-year-
        olds and 12- to 14-year-olds made more errors than adults (p = .02, d = 0.84 and p
        = .005, d = 1.31, respectively).

        <hss>Matrix analysis</hss>

        Neither of the two outcome measures described so far fully characterized task
        performance. A participant could receive a perfect score for the number of
        perceived identities (two) even if both of the participant’s identity piles
        featured Rob and Dom. Similarly, a participant could receive a perfect score for
        misidentification errors (zero) even if the participant sorted the 40 images into
        40 different identity piles. A series of matrices, therefore, was created to
        visualize task outcomes and to derive an integrated measure of task performance
        (see Fig. 3). All 40 images (1–20 of Rob and 21–40 of Dom) were placed along both
        the x and y axes, yielding 400 cells to record incidences where two images of
        different identities were placed together (20 Rob × 20 Dom) and 760 cells to
        record incidences where two images of the same identity were placed together (380
        Rob × Rob and 380 Dom × Dom) for each participant separately. The 92 performance
        matrices (one for each participant) were then combined into five “age-binned”
        performance matrices to compare patterns of performance across groups. The
        performance matrices for 6- and 7-year-olds (n = 16) and adults (n = 15) are
        illustrated in Fig. 3A and B, respectively. All five age-binned matrices can be
        seen in the online supplementary material. Each performance matrix had four
        “quadrants.” The top-left and bottom-right quadrants show the number of times
        participants correctly matched images of Rob/Dom with other images of Rob/Dom. The
        top-right and bottom-left quadrants, which are symmetrical across the diagonal,
        show the number of times participants incorrectly placed images of Dom with images
        of Rob. For 6- and 7-year-olds (n = 16), therefore, perfect performance would
        result in a value of “16” in every cell in the top-left and bottom-right quadrants
        (same identity match) and a value of “0” in every cell in the top-right quadrant
        and its duplicate in the bottom-left quadrant. To compare groups on an integrated
        measure of task performance, we first calculated a “match score” by summing the
        values in the top-left and bottom-right quadrants for each participant separately
        and a “mismatch score” by summing the values in the top-right quadrant for each
        participant separately. Each participant’s match score was then divided by his or
        her mismatch score to yield a “matrix score,” a ratio of correct sorting to
        incorrect sorting for each participant. A constant of 1 was added to each
        participant’s mismatch score beforehand to ensure that all mismatch scores were
        non-zero. Because of the large range in scores, and violations to the assumption
        of homogeneity of variance, nonparametric analyses were used on the matrix score.
        A Kruskal–Wallis nonparametric test on matrix scores revealed a significant effect
        of age group, H(4) = 39.97, p < .001 (see Table 1 for scores; higher scores
        indicate better performance). Mann–Whitney U tests further revealed that 6- and
        7-year-olds performed significantly worse than 8- and 9-year-olds (U = 308.0, z =
        2.05, p = .04, r = .31), 10- and 11-year-olds (U = 267.0, z = 3.41, p < .001, r =
        .57), 12- to 14-year-olds (U = 167.0, z = 2.76, p = .005, r = .51), and adults (U
        = 236.0, z = 4.59, p < .001, r = .82). In addition, 8- and 9-year-olds performed
        significantly worse than 10- and 11-year-olds (U = 382.0, z = 2.13, p = .03, r =
        .31) and adults (U = 393.0, z = 4.66, p < .001, r = .71), whereas adults also
        performed better than 10- and 11-year-olds (U = 268.5, z = 3.95, p < .001, r =
        .67), and 12- to 14-year-olds (U = 184.0, z = 3.99, p < .001, r = .76). Overall,
        the results suggest that within-person face recognition is a particularly
        challenging task, especially for children. Analyses on the number of perceived
        identities showed significant improvements in performance between young children
        and adults. Misidentification errors also decreased with age. A more fine-grained
        analysis using performance matrices showed a general pattern of age-related
        improvements, with adults performing better than older children, who in turn
        performed better than younger children on a summary performance measure. These
        findings suggest that the ability to integrate successfully different images of
        the same face into a single representation of facial identity follows a lengthy
        developmental trajectory, just like between-person face recognition (Germine et
        al., 2011; Susilo et al., 2013).

        <hss>Participants</hss>

        A total of 32 6- to 14-year-old children diagnosed with autism (Mage = 11;1, SD =
        2;7, 5 girls) were recruited through advertisements, the Autism Spectrum
        Database–UK (http://www.ASD-UK.com), mainstream and special schools, and parent
        support groups in the Greater London area. All children had an independent
        clinical diagnosis of an autism spectrum condition according to DSM-IV (Diagnostic
        and Statistical Manual of Mental Disorders, 4th edition) criteria (APA, 1994).
        Parents completed the Social Communication Questionnaire (SCQ; Rutter, Bailey, &
        Lord, 2003), and autistic children were administered the Autism Diagnostic
        Observation Schedule (ADOS-G or ADOS-2; Lord, Rutter, DiLavore, & Risi, 1999; Lord
        et al., 2012) using the revised algorithm (Gotham, Risi, Pickles, & Lord, 2007;
        Gotham et al., 2008). All children with autism scored above the threshold for an
        autism spectrum condition on one or both of these diagnostic measures. An
        additional 5 autistic children were assessed but excluded from the dataset either
        because there was uncertainty over whether they understood the instructions (n =
        4) or because they had a full-scale IQ score below 70, as measured by the Wechsler
        Abbreviated Scales of Intelligence–Second Edition (WASI-II; Wechsler, 2011) (n =
        1). A subgroup of 32 typically developing children (Mage = 10;7, SD = 2;2, 12
        girls) who participated in Experiment 1 was matched individually with the autistic
        children for age and cognitive ability. There were no significant group
        differences in terms of chronological age, t(62) = 0.84, p = .40, verbal IQ, t(62)
        = 1.12, p = .27, performance IQ, t(59.25) = 0.34, p = .74, or full-scale IQ, t(62)
        = 0.87, p = .38, as measured by the WASI-II (see Table 2 for scores). Given that
        there were no differences between males and females’ performance in Experiment 1
        in terms of the number of perceived identities (p = .24), misidentification errors
        (p = .18), or the matrix total scores (p = .32), the autism and typical groups
        were not matched on gender. Of the children whose parents completed the SCQ, no
        child scored above the cutoff of 15 for autism specified by Rutter and colleagues
        (2003), indicative of low levels of autistic symptomatology.

        <hss>Procedure</hss>

        The stimuli and procedure were identical to those in Experiment 1. Informed
        consent was obtained from the parents of all children prior to participation, and
        verbal assent was obtained from participating children.

        <hss>Number of perceived identities</hss>

        Descriptive statistics for autistic and typical children are reported in Table 3.
        Autistic children sorted images into a median of 16.5 piles, and typical children
        sorted images into a median of 14 piles. As can be seen in Fig. 4A, there was wide
        variability in performance within groups, with the number of perceived identities
        ranging from 2 to 39 in the autism group and from 3 to 35 in the typical group. A
        mixed-design ANOVA on the number of perceived identities with identity (Rob or
        Dom) as the within-participants factor and group (autism or typical) as the
        between-participants factor revealed, unexpectedly, no main effect of group, F(1,
        62) = 1.45, p = .23, ηp2 = .02. There was also no main effect of identity, F(1,
        62) = 2.84, p = .10, ηp2 = .04, and no significant identity × group interaction,
        F(1, 62) = 0.90, p = .35, ηp2 = .02.

        <hss>Misidentification errors</hss>

        An independent-sample t-test on children’s misidentification errors (the number of
        their image piles featuring more than one identity) revealed similar numbers of
        errors in autistic (M = 1.94, SD = 2.18) and typical children (M = 1.91, SD =
        2.49), t(62) = 0.05, p = .96, d = 0.01. Again, there was a large amount of
        variance within each group, with scores ranging from 0 to 9 in children with and
        without autism (see Fig. 4B).

        <hss>Matrix analysis</hss>

        Similar to Experiment 1, performance matrices plotting the number of times each of
        the 40 images was placed in a pile with each of the other 39 images were created
        for each autistic child (n = 32) and each typical child (n = 32). The values in
        these matrices were pooled to create two “group-binned” matrices, shown in Fig. 5.
        For autistic children (Fig. 5A), the values in the top-left and bottom-right
        quadrants ranged from 0 to 19, meaning that the number of times two images of
        Rob/Dom were correctly placed together ranged from never (0%) to 19 (59%). For
        typically developing children (Fig. 5B), the values in these same quadrants were
        largely similar, ranging from never (0%) to 23 (72%). Next, values in the top-
        right quadrant (duplicated in the bottom-left quadrant), which represent the
        number of times two images of different identities were incorrectly perceived as
        being the same person, were compared across groups. The values in these quadrants
        ranged from 0 to 6 in both groups, meaning that at most 6 children (19%) in each
        group mistakenly placed a pair of mismatched images together. Finally, and similar
        to Experiment 1, a total matrix score was calculated for each participant by
        dividing each child’s match score (the sum of the values in the top-left and
        bottom-right quadrants) by the child’s mismatch score (the sum of the values in
        the top-right quadrant) As before, a constant of 1 was added to each participant’s
        mismatch score beforehand to ensure that all mismatch scores were non-zero.
        Descriptive statistics on these matrix scores are shown in Table 3. A Mann–Whitney
        U test on children’s matrix scores revealed a marginally significant group
        difference (U = 370.5, z = –1.90, p = .057, r = –.24). These results suggest that
        children with autism have similar difficulties as typically developing children in
        recognizing the same facial identity across several images, with a trend toward
        poorer performance on the task overall.

<h>GENERAL DISCUSSION</h>
------------------

Developmental improvements in face identity recognition are well documented. Although
research has focused on same–different judgments of experimentally manipulated images, so
far it has not considered individuals’ abilities to recognize the same identity across
multiple viewings within a developmental context. In this study, an experimental task
designed to test how well individuals recognize differing and naturally varying images of
the same identity was extended to children for the first time. Similar to Jenkins et al.
(2011), we found that within-person face recognition is a difficult task for adults, with
only 2 of 15 participants arriving at the correct solution. Our findings further showed,
however, that it is an exceptionally difficult task for children. None of the 77 children
between 6 and 14 years of age arrived at the correct solution. Furthermore, we observed
that misidentification errors, a rarity among adults, were much more common in young
children. This means that as well as failing to recognize the same face across different
contexts, children were also more likely to perceive different identities as being the
same identity. These findings add to the wealth of existing research suggesting that face
identity recognition follows a protracted developmental course (Germine et al., 2011;
Mondloch et al., 2003; Susilo et al., 2013). Age differences in the overall number of
identities perceived, and the number of times images of the same identity were placed
together, indicate that within-person face identity recognition does not improve
significantly within middle childhood but does improve significantly between childhood and
adulthood. The number of misidentification errors appeared to follow a slightly clearer
developmental path. Younger children made significantly more errors than older children,
and older children made more errors than adults, who made almost no misidentification
errors at all. One way of interpreting these findings is to view a greater number of
identities perceived as a failure of within-person face recognition (a failure to
recognize that several images are of the same identity) and higher numbers of
misidentification errors as a failure of between-person face recognition (a failure to
recognize two different identities as being separate). Working on the assumption that
generally there is a greater difference between two images of different identities than
between two images of the same identity, an ability to discriminate between two unfamiliar
identity images might emerge earlier in development, with errors decreasing as the basic
structure of “multidimensional face space” (Valentine, 1991), present from a young age
(Jeffery et al., 2013; Nishimura, Maurer, & Gao, 2009; Nishimura et al., 2008; Pimperton
et al., 2009), undergoes adjustments and improvements (Jeffery et al., 2013). An arguably
more sophisticated system, which can efficiently carry out between-person face
recognition, may be a necessary requirement for within-person recognition as measured by
the current task. This sophistication may involve the abilities to weight or integrate
information from multiple dimensions, which children appear to be less skilled at or
inclined to do (Nishimura et al., 2009). Within a norm-based coding model, success on the
current task depends on a viewer positioning images much closer together in face space, as
vectors from the “norm” of that particular individual’s identity, before deciding whether
to integrate that image into the averaged representation for that face. Using the concept
of “stability through variation” (Bruce, 1994), Burton et al. (2005) proposed that an
internal representation, or “population mean,” of individual facial identities (e.g., Dom)
is readjusted after each new encounter to improve reliability. If we follow this model, in
Jenkins et al.’s (2011) task, participants must begin to build this internal
representation from scratch and then update it repeatedly as they sort through the 40
images and decide which ones to encode as a representation of an existing identity and
incorporate into that population mean and which ones to keep separate. In accordance with
this norm-based coding model, this particular identity’s vector in multidimensional face
space must be continually adjusted in comparison with that person’s concept of an average
face. The larger the variance among images of the same face, the more sophisticated this
system needs to be to extract the commonalities between them. This may explain why an
ability to recognize the same identity across several different images remains so
difficult even for adults. We also examined for the first time within-person face
recognition in autistic children. Our findings showed no clear differences between
children with and without autism, of similar age and ability, on the number of identities
perceived or on the number of misidentification errors made (image piles featuring both
identities). Although this is not the only study to report similar performance between
autistic and typically developing individuals on a face processing task (Yi et al., 2015),
difficulties in face identity recognition are well documented in autism (Dawson, Webb, &
McPartland, 2005; Weigelt et al., 2012), and so these findings might appear to be somewhat
surprising. One possible explanation for these null findings is the considerable
variability in children’s performance within each group, which may have precluded the
possibility of detecting group differences in within-person face recognition in Experiment
2 (and indeed of detecting such age-related differences in Experiment 1). Alternatively,
the difficulty of the task may have also prevented us from detecting differences in
performance by children with and without autism. Future research should examine within-
person face recognition in children with and without autism using a simpler task—perhaps
by using fewer images to sort—or by assessing such skills in adolescents or adults (rather
than children) with and without autism, when such abilities are more mature and
potentially vary less between individuals. One further possibility relates to the nature
of the task itself. Successful overall performance on the task requires an ability to tell
different faces apart as well as an ability to tell faces together. Our integrated measure
of task performance reflecting these abilities did reveal a marginally significant
difference between the groups. One possible interpretation of a trend toward reduced
overall performance in autism is difficulties in building stable “averaged”
representations of a “normed” facial identity (Leopold et al., 2001; Rhodes & Jeffery,
2006; Valentine, 1991). Evidence from the face identity aftereffect task suggests that
there may be reduced updating of face norms in response to experience in children with
autism (Ewing et al., 2013; Pellicano et al., 2007) and in relatives of those with autism
(Fiorentini et al., 2012). This is in line with a theory of autistic perception (Pellicano
& Burr, 2012), which suggests that autistic individuals are less likely to use prior
information to interpret incoming sensory information. Such a bias could make it difficult
to discard information that is somewhat irrelevant to identity judgments (e.g.,
superficial and changeable aspects of facial images such as hairstyle, head angle, and
lighting), increasing the likelihood of two images of the same identity being judged as
different but also of two images of different identities being judged as the same. Caution
is warranted, however, when interpreting this marginal result. Further replication of the
result reported here is necessary before strong conclusions can be drawn. One strength of
this study is that it used naturally varying images—“real photos”—unlike the vast majority
of experimental studies where images of faces are often manipulated extensively and,
therefore, vastly different from images of faces seen outside of the laboratory (Burton,
2013). Yet, even the stimuli used here are devoid of context, which should help
individuals to build representations and guide their decisions in everyday life. The use
of natural images in an experiment also brings considerable challenges because the
substantial variance in the images makes it difficult to isolate underlying mechanisms
responsible for this seemingly complicated task. In addition, the task itself was an
“open” task, which means that participants could employ a range of different strategies to
solve it. Creating and updating an abstract representation of each individual’s facial
identity, therefore, is just one possible explanation for successful performance on the
task; individuals may have also matched images based on featural or configural
information. The extension of eye-tracking research to studies using more naturally
varying images has the potential to yield insights into which strategies participants use
for successful within-person face recognition by identifying which aspects of the face are
attended to in order to perform the task. Further research could also use nonsocial
stimuli to see whether these findings are selective to faces, for example, by comparing
performance on recognizing several images of the same face with how well participants
recognize several images as being of the same object (e.g., cars). Such research will be
important in determining whether the age-related improvements found here are task
specific, perhaps attributable to the large number of images participants were required to
sort and keep track of. In conclusion, this study has demonstrated the considerable
challenge posed by within-person face recognition for typical children, adults, and
autistic children alike, and it highlights the need for greater understanding of the
mechanisms that underlie this largely overlooked aspect of face perception. This work also
has practical implications for working with children, especially children with autism.
Photographs of adults supporting autistic children are commonly used in social stories and
other tools designed to prepare the children to meet new people or to engage in new
activities. The findings here suggest that some children may well struggle to recognize
the same people they meet in person from an individual photograph.


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<ART>Reducing challenging behaviour of adults with intellectual disabilities in supported accommodation: A cluster randomized controlled trial of setting-wide positive behaviour support
================================================================================

Authors: Peter McGill, Leah Vanono, Will Clover, Emmett Smyth, Vivien Cooper, Lisa Hopkins, Nick Barratt, Christopher Joyce, Kate Henderson, Sheila Sekasi, Susy Davis, Roy Deveau
DOI: 10.1016/j.ridd.2018.04.020
Year: 2018  |  Pages: 143-154
ASJC codes: 3203, 3204
Keywords: Adults, Challenging behaviour, Intellectual disability, Positive behaviour support, Randomized controlled trial, Supported accommodation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Improving the quality of social care through the implementation of setting-wide positive behaviour support (SWPBS) may reduce and prevent challenging behaviour. Method: Twenty-four supported accommodation settings were randomized to experimental or control conditions. Settings in both groups had access to individualized PBS either via the organisation's Behaviour Support Team or from external professionals. Additionally, within the experimental group, social care practice was reviewed and improvement programmes set going. Progress was supported through coaching managers and staff to enhance their performance and draw more effectively on existing resources, and through monthly monitoring over 8–11 months. Quality of support, quality of life and challenging behaviour were measured at baseline and after intervention with challenging behaviour being additionally measured at long-term follow-up 12–18 months later. Results: Following intervention there were significant changes to social care practice and quality of support in the experimental group. Ratings of challenging behaviour declined significantly more in the experimental group and the difference between groups was maintained at follow-up. There was no significant difference between the groups in measurement of quality of life. Staff, family members and professionals evaluated the intervention and its outcomes positively. Conclusions: Some challenging behaviour in social care settings may be prevented by SWPBS that improves the quality of support provided to individuals.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Challenging behaviour remains a significant problem in supported accommodation settings
for people with intellectual disabilities (cf. Department of Health, 2007). Almost half of
residential services use restrictive responses such as physical intervention (Deveau &
McGill, 2009). Challenging behaviour is associated with placement breakdown (Phillips &
Rose, 2010) and the costly removal of individuals to more restrictive, out-of-area
settings (Goodman, Nix, & Ritchie, 2006). Furthermore, it is associated with high rates of
injury to care staff (National Task Force on Violence against Social Care Staff, 2001).
Generally, challenging behaviour is treated as an individual problem requiring
intervention by psychologists, psychiatrists or other behaviour support professionals
(Royal College of Psychiatrists, British Psychological Society, & Royal College of Speech
and Language Therapists, 2007). But many such professionals now adopt positive behaviour
support (PBS) (Carr et al., 2002), an approach inevitably leading to a focus on the
context in which challenging behaviour occurs – “the central independent variable in PBS
is systems change” (Carr, 2007, p.4). Such change is not easily obtained with regular
reports of difficulties implementing the proposed treatments both in social care (Ager &
O’May 2001) and educational settings (Bambara, Nonnemacher, & Kern, 2009). The difficult
behaviour presented in schools has been recognised as requiring a broader approach, more
focused on prevention (Sugai & Horner, 2002). The development of school wide positive
behaviour support in the USA reflects this (Horner et al., 2009) but there has been little
attention to the potential for a similar approach in social care. A setting wide approach
is consistent with theoretical developments in our understanding of challenging behaviour.
Once seen as an almost inevitable concomitant of intellectual disability, it is now
regarded as arising from the complex interaction of biological, developmental and
environmental factors (Langthorne, McGill, & O’Reilly, 2007). In particular, it has become
clear that certain characteristics of the social environment (such as social deprivation
and aversive stimulation) may underpin the motivation of challenging behaviour (McGill,
1999). Altering such “motivating operations” (Michael, 2007; Simó-Pinatella et al., 2013)
then becomes a theoretically viable approach to preventing or reducing the occurrence of
challenging behaviour in those at increased biological risk (cf. Emerson & Einfeld, 2011).
Such an approach would need to focus on improving the quality of social care especially in
those areas known (through the development of individualized PBS strategies) to be
associated with challenging behaviour. These include, amongst others, opportunities for
choice (e.g., Dyer, Dunlap, & Winterling, 1990), predictable environments (e.g., Flannery
& Horner, 1994), positive social interactions (e.g., Magito-McLaughlin & Carr, 2005), more
independent functioning (e.g., O’Reilly, Cannella, Sigafoos, & Lancioni, 2006) and
personalised routines and activities (e.g., Brown, 1991). Such an approach has been
endorsed by the NICE guidelines on challenging behaviour (Murphy, 2017; NICE Guidelines,
2015) in which the term “capable environment” is used to summarise the characteristics of
support that may reduce the risk of challenging behaviour. There remains, however, very
little evidence of the impact of such an environment. Most intervention trials have been
of psychotropic medication with mixed results leading NICE to recommend that medication
not be used as a first-line intervention for challenging behaviour. A small number of
trials have shown that cognitive behaviour therapy (Vereenooghe & Langdon, 2013) and
individualized PBS can be effective (Hassiotis et al., 2009). There is also evidence that
training staff in PBS is associated with reductions in challenging behaviour (MacDonald &
McGill, 2013). However, the impact of improving the quality of social care remains
untested. The current study set out to develop and evaluate an approach to improving the
quality of social care in supported accommodation settings, drawing on work on quality
improvement (e.g., LaVigna, Willis, Shaull, Abedi, & Sweitzer, 1994) and approaches to
changing staff practice in residential settings (e.g., Mansell and Beadle‐Brown, 2012).
The primary hypothesis was that intervention would be associated with reductions in
challenging behaviour. Secondary hypotheses were that intervention would lead to improved
quality of support and a better quality of life. A parallel study, the results of which
are reported separately, investigated the outcomes of the intervention for social care
staff.

<hs>  Design</hs>
  ~~~~~~

The study was carried out as a pragmatic, cluster randomised, controlled trial (RCT)
(Hotopf, 2002). Intervention was implemented by a small team consisting of the Principal
Investigator (PI), one full-time researcher and two part-time researchers. Two researchers
implemented the intervention in each setting with one taking the lead and one a support
role. Allocation of researchers to settings was geographically driven – the part-time
researcher based in the North of England worked with settings in that region and the part-
time researcher based in the South of England worked with settings in that region. The
full-time researcher was involved in the intervention in all settings, either as lead or
support. The PI supervised the intervention process through regular meetings and telephone
conferences attended by the three researchers.

<hs>  Ethical and governance approvals</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The study received ethical approval from the Social Care Research Ethics Committee (REC
Reference 12/IEC08/0018) including for the participation of persons lacking capacity to
consent. Governance applications were made to and agreed by 14 local authorities covering
all the settings (control and experimental) that participated. Approval was also gained
from the Association of Directors of Adult Social Services. Staff and intellectually
disabled participants with capacity to consent received comprehensive, accessible
information about the project and provided written consent. Intellectually disabled
participants lacking capacity to consent participated (consistent with the Mental Capacity
Act) through signed declarations from personal or nominated consultees.

<hs>  Settings and participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

The study ran from 2012 to 2016 in residential settings for 1–8 adults with intellectual
disability. Social care in all settings was initially provided by Dimensions, a not-for-
profit provider supporting 3500 people with intellectual disabilities and autism in
England and Wales. Settings were geographically spread with two clusters in the South and
North of England. Dimensions was asked to identify 25–30 settings with an average of 4
adults with intellectual disabilities of whom (on average) two had a recent history of
frequent and/or serious challenging behaviour. Additional inclusion criteria were that
there were no significant changes planned (such as change of residents/tenants) and that
residents/tenants and staff were likely to consent to participate. Thirty settings were
identified and all contacted to confirm their meeting inclusion criteria and to begin
seeking consent. Over approximately 6 months all settings were visited by researchers and
the project discussed with the manager responsible. This led to the final identification
of 24 settings where all residents/tenants and the great majority of staff had consented.
Non-consenting staff participated in assessment and intervention procedures as part of
their employment but did not complete measures or provide data.

<hs>  Intervention</hs>
  ~~~~~~~~~~~~

Researchers, using positive behaviour support principles, sought to improve the quality of
practice within experimental group settings using the following intervention process:
Managers and assistant managers of each setting attended a 3 h briefing session including
presentations by Dimensions’ Director of Specialist Development, the PI and the research
staff involved in providing the intervention. Two researchers were allocated to each
setting as described above. All researchers engaged in intervention had a Master’s degree
in Applied Behaviour Analysis or Intellectual/Developmental Disabilities, and several
years of experience in providing applied behaviour analysis/positive behaviour support.
The PI was a registered clinical psychologist and board certified behaviour analyst with
extensive experience. Following an agreed timetable, researchers, in pairs, spent a week
in each setting. The first two days involved observing practice, talking to staff and
service users, and reviewing documentation. Researchers organised their findings into
eight areas of social care − Activities and Skill Development, Health, Service Staff,
Management, Relationships with Family and Others, Communication and Social Interaction,
Wider Organisation, and Physical Environment. The eight areas were chosen based on
research identifying their relationship with challenging behaviour. For example,
substantial research shows the relationship between communication and challenging
behaviour. When individuals understand what is going on and have effective ways of
communicating their needs to the people supporting them, they are much less likely to
display challenging behaviour. Similarly, and beyond the immediate context, aspects of the
organisation may also impact on the occurrence of challenging behaviour. Organisational
policies and practices, for example, should be informed by an understanding of challenging
behaviour and ensure that frontline staff receive the support and leadership they need to
work effectively. The specific areas identified represent an adaptation of previous
attempts at evidenced taxonomies of those characteristics of mediators (Allen et al.,
2013) and of environments (McGill, Bradshaw, Smyth, Hurman, & Roy, 2014) associated with
less challenging behaviour. In each of the eight areas researchers identified, in
discussion with the PI, the current picture, particular strengths, and areas where there
was scope to support change within the setting. A comprehensive review of practice was
presented to managers (including the manager’s manager where possible). Having agreed an
outline improvement programme and initial actions for all parties, researchers wrote a
draft programme in which a small number of outcome standards (supported by several process
and monitoring standards) were set out in each of the eight areas (cf. LaVigna et al.,
1994). A number of outcome standards were similar or the same in most/all settings or in
at least some settings. All programmes also included standards idiosyncratic to one or two
settings. The topics of standards are shown in Table 1. Researchers returned to the
setting as soon as possible after the initial week to present and discuss improvement
plans. Over the ensuing 8–11 months researchers engaged in a combination of the following
activities tailored to each setting: Monthly meetings with manager to review progress
against the standards set. Progress was assessed using a traffic lights system with each
“green” (standard fully achieved) being worth two points, “amber” (standard partly
achieved) one point and “red” (standard not achieved) no points. Documentary evidence was
required to score. Points were totalled so that a percentage figure could be calculated
for each setting each month. The percentage represented the proportion of standards that
had been achieved/partly achieved. Following each monthly meeting, total scores were
graphed and sent to the manager so that everyone in the setting could see the progress
being made. Coaching staff and manager. In many settings staff received support to
interact more effectively with the adults living there. This might, for example, be in the
context of supporting participation in activity in ways that enabled engagement in the
activity without provoking challenging behaviour. Supporting the development of
documentation. While all settings had extensive documentation it was not all functional.
For example, there were limited activity schedules and staff frequently decided on the day
what was going to happen. For some residents/tenants this was problematic since they could
not predict or influence what was going to happen. Staff and manager training. Where
relevant to identified standards, more formal training was arranged. For example, an
introductory session on autism was organised for a number of staff groups who supported
individual(s) with autism but had little understanding of its influence on their
behaviour. Utilisation of existing Dimensions resources. Managers were encouraged to draw
in support from other parts of the organisation. This included the organisation’s
behaviour support team, a coaching resource that enabled managers to receive support with
difficult supervision issues and a resource that provided staff training specifically
related to active support (Mansell & Beadle‐Brown, 2012). Utilisation of local
professional resources from outside Dimensions. Managers and staff were encouraged to seek
input from local Community Intellectual Disability Teams (CIDTs) and other sources of
potential support. For example, a referral was made to gain bereavement support following
the death of one of the people who lived in a setting. Progress chasing. Researchers
played a local leadership role in which they encouraged achievement of the standards using
a variety of means. This included encouraging staff or manager to keep following something
up or taking on specific tasks themselves. Towards the end of the intervention,
researchers reduced their input and sought to transfer outstanding activities to the
manager or other Dimensions staff. During the same period, control group settings received
no input from researchers. They were, however, able to access additional input in the same
way as before. This included making referrals within (e.g., to the behaviour support team
or for coaching assistance) and outside Dimensions (e.g., to the local CIDT).

<hs>  Intervention implementation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Within the experimental group monthly monitoring procedures allowed the collation of data
on the standards set. The mean number of standards across settings was 145 (SD = 19.3,
Range: 118–180). Table 2 shows the mean numbers of outcome and overall standards set and
their achievement in each of the eight areas. Table 2 also shows the extent to which
“shared” standards (those described above as having been set in some, most or all
settings) were achieved. Standards were achieved at higher rates in certain areas of
social care (Activities, Management, Staff, Health) and at lower rates in others (Physical
environment, Relationships, Communication, Organisation). The correlation between overall
standard and shared standard achievement was 0.85 suggesting that this pattern applied
whether the standards were shared or more idiosyncratic. Shared standards did seem to be
more likely to be achieved, an average of 83% vs the average of 75% for all standards.
Fig. 1 shows the percentage of standards achieved in each setting during the intervention.
All settings started at 0% as standards were only included when clearly not achieved at
initial assessment. While there was considerable overlap in standards set in different
settings, the overall list of standards was idiographic to each setting and the percentage
achieved cannot necessarily be meaningfully compared between settings. Overall average
percentage achieved (median percentage in last data collection in each setting) was 80.1%
(range: 29.7–92.3%). Service 7 was an outlier (see Fig. 1). This service was re-provided
during the intervention for reasons unconnected with the intervention or challenging
behaviour. As a result, the three adults were divided between two other settings supported
by different providers. It was not meaningful to collect further data on the achievement
of standards that did not necessarily apply to the new settings. While there was
considerable variation (59.9–92.3%) in the remaining 10 settings, all made substantial and
relatively steady progress towards achieving the standards set.

<hs>  Outcomes and other measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The primary hypothesised outcome (reduction in challenging behaviour) was measured through
the Aberrant Behavior Checklist-Community (ABC), a reliable and valid measure of the
severity of challenging behaviour (Rojahn, Aman, Matson, & Mayville, 2003). Baseline
questionnaires were completed prior to group allocation by staff who knew each adult well,
typically their key worker. Subsequently, 3–6 months after the end of intervention, and
12–18 months after that, the same measure was completed. The secondary hypothesised
outcomes (quality of life, and quality of staff support) were evaluated using non-
participant observations made as close as possible to the period 4–6 PM in line with
previous research (cf. Felce et al., 2000). Engagement in meaningful activity (as a
measure of quality of life) was recorded using momentary time sampling during the 2-h
period with observations made, by rotation, of all residents/tenants present. Engagement
was defined as in the EMAC-R (Mansell & Beadle-Brown, 2005). Observers at baseline were
research workers, one of whom had extensive experience in using the EMAC-R and provided
training to the other. Observers after intervention were current or previous research
workers with extensive experience in the use of EMAC-R. At the end of the 2-h period the
observer completed the Active Support Measure (ASM) (Mansell & Elliott, 1996, revised
2005) which provided ratings of quality of staff support for activity, choice-making and
other aspects of social care. Baseline data were gathered prior to randomisation of
settings. Three-six months after the end of intervention, the same measures were carried
out by observers with no previous involvement in the study and blind to group allocation.
Inter-observer agreement was checked by having a second observer present during seven of
the baseline and two of the post-intervention observations. Overall agreement about
engagement occurred on 88.7% of observations. Exact agreement on ASM category scores was
79% with a weighted kappa of 0.72. Observers provided qualitative comments about each
setting including their view on the setting’s group membership, and their reasons for this
conclusion. Information on the characteristics of intellectually disabled participants was
gathered using a shortened version of the Individual Schedule (IS) (Emerson et al., 1999)
incorporating the Short Adaptive Behavior Scale (SABS) (Hatton et al., 2001).
Questionnaires were completed prior to group allocation by staff who knew each individual
well. Following completion of the intervention, staff in experimental settings, family
members of the people supported there and external professionals (e.g. CIDT members) with
significant involvement completed one-page questionnaires on their experiences and overall
evaluation of the intervention’s impact. Questionnaires shared common items, expressed
differently for different groups e.g. “Over the last year my relative’s health has
improved” (family version), “For the people we support the project has improved their
health” (staff version), “The project has improved the health of the people supported”
(external professional version). Additionally, staff questionnaires included four items
relating to their own experiences of the project (e.g., “The project has improved the way
I am supported by my manager”). All items were rated on a 5-point scale from “strongly
disagree” that the intervention had a positive impact to “strongly agree”.

<hs>  Sample size, randomization and blinding arrangements</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In an RCT of the impact of behaviour support on challenging behaviour in individuals
living in community settings, Hassiotis et al. (2009) estimated an effect size of 0.8
using the ABC. Effect size in the current study was therefore set at 0.8; with power set
at 0.8 and p < 0.05 (one-tailed), 20 participants would be needed in each of the two
groups. Given the nature of the intervention, it would not have been possible to include
participants from the same setting in both experimental and control groups. Accordingly,
participants were grouped in clusters (where the cluster was the residential setting).
With such an arrangement it was necessary to consider the within-cluster correlation. The
magnitude of this effect is given by the formula: Deff = 1 + (m-1) × ICC where Deff is the
design effect, m is the average number of participants in each cluster and ICC is the
intra-cluster correlation coefficient. The latter was estimated from unpublished data on
challenging behaviour across 13 settings (clusters) of an adult social care provider
collected by the PI as part of a service evaluation to be 0.096. Taking this as 0.1 and
assuming an m of 2, the Deff is then 1.1 and 22 participants would be required in each
group. On the basis of an average of 2 participants per placement this implied 11 settings
per group. Settings were expected to also accommodate a similar number of individuals who
did not display challenging behaviour. In total, therefore, the expected required sample
was, in both experimental and control groups, 22 people who currently present challenging
behaviour together with 22 people who did not currently present challenging behaviour. As
noted below, the actual samples obtained approximated these requirements. The 24
identified residential settings were allocated by the PI to experimental or control group
using the computer programme MINIM (Evans, Royston, & Day, Undated). This method of
allocation (minimisation, e.g., Treasure & MacRae, 1998) is particularly suitable for
cluster trials containing a relatively small number of clusters since it ensures maximum
similarity between groups in respect of variables that might influence outcome (cf. Turk
et al., 2010). MINIM was set up to minimize differences between groups in respect of the
following: geography (north vs south of England), number of staff in setting (above or
below median), challenging behaviour (above or below median ABC score), number of adults
without significant challenging behaviour (none vs one or more) adaptive behaviour (above
or below median SABS score) and number of individuals with autism (0 vs 1 or more). Given
the nature of the trial, only limited blinding arrangements were possible. All baseline
data were gathered prior to group allocation so both settings and researchers were blind
at this stage. All settings were aware, however, at subsequent datapoints, whether they
were in the experimental or control group. Gathering of data following intervention was
facilitated by researchers aware of group allocation since they had been involved in
delivering the intervention. The exception to this was in respect of the collection of
non-participant observation and rating data following intervention. Observers had not
previously been involved in the study and were blind to group allocation.

<hs>  Analysis</hs>
  ~~~~~~~~

All data analyses were conducted in IBM SPSS version 24. The period between baseline and
post-intervention data collection was 12–18 months. During this time there were a number
of changes to adult participation affecting data availability (see Fig. 2). Consequently,
the experimental group was reduced from 11 to 9 settings, and the control group from 13 to
12 settings. Data are presented throughout, and analysis conducted, primarily at the
setting level as that was the focus of the intervention and of randomisation. To
investigate the degree to which setting level analysis reflected outcomes for individuals,
a sensitivity analysis was conducted of changes in the primary outcome measure between
baseline and post-intervention. This also allowed the impact of changes in the
participants present at each datapoint to be investigated. Inferential analysis involved
the comparison of group means in difference scores between baseline and post-intervention.
Thus, a “per protocol” approach was used with no data imputation for those lost to follow-
up. While an “intention to treat” approach would normally be regarded as the gold
standard, the primary focus of this trial was to evaluate intervention efficacy. Analysis
of data at long-term follow-up (only possible for ABC scores) took a similar approach but
is presented separately as there was more missing data and the study was originally
planned with only baseline and post-intervention data points.

<hs>  Settings and participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Eleven settings were allocated to the experimental group and 13 to the control group (see
Fig. 2). Group composition, in terms of the variables used in allocation, is shown in
Table 3. Group characteristics were compared using independent sample t-tests and, for
categorical data, chi-square. None of the differences between groups were significant at p
< 0.05, two-tailed. Demographic information was gathered on all residents/tenants of the
24 residential settings (see Table 4).

<hs>  Outcomes after intervention</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Average ABC scores for each setting are shown in Table 5. Setting average scores reduced
in nine of nine experimental settings with the group mean reducing from 39.2 (range:
18.5–61) to 12.5 (range: 4–21). The control group mean reduced from 42.3 (range: 15.7–70)
to 34.9 (range: 14–51.7) with seven of twelve settings reducing. The difference across
time between groups was significant (t = 2.24, df = 19, p = .04, 2 tailed, Cohen’s d =
1.00, 95% CIs −37.20 to −1.29). Mean percentage ASM scores are also shown in Table 5. Mean
scores increased in seven of nine experimental settings (remained the same in one and
baseline data not gathered in the other) with the group mean increasing from 48.0 (range:
35.6–61) to 67.6 (range: 35.6–93.3). The control group mean reduced from 47.7 (range:
30.4–67.4) to 45.5 (range: 17.8–65.5) with five of twelve settings showing an increase.
The difference across time between groups was significant (t = 2.88, df = 18, p = .01, 2
tailed, Cohen’s d = 1.28, 95% CIs 5.92–37.88). Mean percentage engagement in meaningful
activity increased in experimental settings from 49% to 68.2% and, in control group
settings, from 52.5% to 58.9%. The difference across time between groups was not
significant (t = 0.75, df = 18, p = .46, 2 tailed, Cohen’s d = 0.34, 95% CIs −16.37 to
+34.44). Post-intervention observers identified group membership of 19 of the 21 settings,
correctly allocating control group settings in all instances and experimental group
settings in seven out of nine instances. Kappa was 0.80. In noting their conclusions,
observers made no comments suggesting blinding had been breached. All allocation reasons
related to their observations of the quality of social care and/or its outcomes.

<hs>  Sensitivity analysis of changes in individual ABC scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

ABC scores reduced in 21 of 26 experimental participants with the group mean reducing from
34.5 (range: 3–92) to 11.8 (range: 0–26). The control group mean reduced from 43.2 (range:
0–135) to 36.8 (range: 0–102) with 17 of 38 individuals reducing. The difference across
time between groups was non-significant (t = 1.85, df = 62, p = .07, 2 tailed, Cohen’s d =
0.49, 95% CIs −33.89 to +1.24). Post hoc analysis of individual scores suggested that
higher ABC scores were recorded in smaller settings in the experimental group at baseline,
resulting in higher setting average scores at baseline compared to individual scores since
settings were weighted equally however many individuals were supported in each. There was
no evidence that change in individual participants across time had affected results –
post-intervention data was not collected on four participants, three in the control group
(one death, one data collection error, one left setting) and one in the experimental group
(one death) – a repeat of the analysis of differences across time produced almost
identical results to those in Section 3.2.

<hs>  Outcomes at long-term follow-up</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Setting average ABC scores at follow-up are shown in Table 5. Mean scores were 18.4
(range: 7.5–32.5) in the experimental group and 39.8 (range: 15–100) in the control group.
Averages across the three time points are shown in Fig. 3. The difference from baseline to
follow-up between groups was not significant (t = 1.58, df = 15, p = .13, 2 tailed,
Cohen’s d = 0.85, 95% CIs −15.67–0.53) though the difference between groups at follow-up
remained significant (t = 2.13, df = 15, p = .05, 2 tailed, Cohen’s d = 1.13, 95% CIs
−42.88–0.01).

<hs>  Social validity</hs>
  ~~~~~~~~~~~~~~~

Seventy-two staff (from all nine experimental settings) completed a questionnaire. Of the
787 individual ratings made, 68% recorded the intervention as having a positive impact,
25% as making no difference and 7% as not having a positive impact. Smaller numbers of
family members (N = 8) and professionals (N = 12) completed questionnaires. 52% of family
ratings were positive, 39% neutral and 9% negative. 77% of professional ratings were
positive, 23% neutral and 0% negative. As an additional indication of social validity,
four experimental group services received awards.

<h>DISCUSSION</h>
----------

The recent NICE guidance on challenging behaviour (Murphy, 2017) recognised the
limitations surrounding previous research on challenging behaviour. In particular, there
has been a shortage of research into the effectiveness of intervention employing the most
robust designs (such as RCTs). As a result, our knowledge concerning intervention remains
somewhat limited. The current study constitutes one of a very few RCTs on non-
pharmacological treatment of the challenging behaviour of people with an intellectual
disability. Its unique approach to “treatment” emphasised system-wide rather than
individually-based intervention. This approach proved a feasible way of working with most
experimental group settings. There were two exceptions. In one setting, the intervention
was interrupted by external “turbulence” with changed commissioning arrangements
(independent of the research) requiring individuals to move to other settings supported by
different care providers. In the other setting, the difficulties were related to the
intervention which was, in a sense, a catalyst for change. Initial assessment identified a
range of poor practice but its exposure alienated many staff working in the setting so
that they withdrew their consent. It proved possible to continue delivering a form of the
intervention, albeit under considerable difficulties and without adequate data collection.
While implementation across other settings was variable, an average of 80% of the
standards set were achieved and the percentage achieved steadily rose across the
intervention period. Challenging behaviour (as measured by the primary outcome measure,
ABC total scores) reduced by over 2/3rds in the experimental group. This reduction was
significantly more than in the control group and constituted a large effect size, albeit
sensitivity analysis suggested that the strength of the effect at individual participant
level was rather less. Much of the reduction was maintained at follow-up. On the measure
of quality of social care, experimental settings improved significantly more than control
settings, again a large effect size. Quality of life for service users (as measured by
observed engagement in meaningful activity) also improved more in experimental settings
but the improvement was not significantly greater than in the control group. The
intervention was greeted very positively by staff, families and professionals engaged with
experimental settings. There were a number of limitations to study design and
implementation. A pragmatic RCT with usual care control is prone to the criticism that the
intervention group received more “attention”. With the design used all that can be
concluded are the effects of the “attention” received rather than the intervention
components that were instrumental in producing these effects (Woods & Russell, 2014). The
earlier description of the intervention reveals the authors’ assumptions about its
critical components but further research would be necessary to endorse this. Similarly, it
remains possible that control group staff suffered from “resentful demoralisation” (Woods
& Russell, 2014, p.8) at not being included in the experimental group. However, on some of
the measures employed, the control group improved from baseline, tending to argue against
this possibility. No information was collected on what happened in control group settings
between baseline and post-intervention. Given their continued access to the organisation’s
behaviour support team, some are likely to have received significant input with respect to
the challenging behaviour of individuals. In retrospect, monitoring the external input
they received would have been useful. Attention should also be drawn to the routinely high
staff turnover found in social care and its implications for longitudinal research.
Inevitably, measures were often completed by different members of staff at different time
points, introducing an additional source of variability. Future research might focus more
on the use of measures that do not depend directly upon specific staff for their
completion such as observation and routinely produced data such as incident reports.
However, such measures also have their problems. Observation is costly and may not provide
representative data, while incident reports are often of dubious reliability. RCT designs
remain relatively unusual in social care and the funding available for the current study
did not allow the involvement of independent statisticians, methodologists and health
economists that would be regarded as typical in healthcare research. This, inevitably,
increases the possibility of bias and means that important variables (such as costs) were
not measured. In particular, it should be noted that the same people were involved in both
delivering the experimental condition and in the process of collecting and analysing data.
As far as possible the risks of bias associated with this were reduced e.g. by employing
observers blind to group membership and encouraging staff to return questionnaires in
sealed envelopes. Nonetheless, it would clearly have been much better to have had
sufficient independent research capacity to avoid such risks more completely. A number of
limitations also arose in the implementation of the study and should receive attention in
future research. It would be useful to work with more than one social care provider to
help test the generality of findings and to identify the characteristics of provider
organisations required to support successful intervention. In the current study, the PI
had a long-established relationship with the provider including at senior management
level. It seems likely that this kind of relationship and support will enhance outcome but
there is as yet no comparison on which to base such a judgement. The intervention was
developed by the research team and has not yet been “manualized” in detail. This is
clearly an essential step if attempts at replication and component analysis are to take
place. In conducting the study it became clear that some aspects of measurement could have
been improved. Four issues were identified. Firstly, the data produced through monthly
monitoring of standard achievement was of unknown reliability and validity. Secondly,
while direct observations are potentially very useful, the amount of time allocated to
these in the current study may have been insufficient given the degree of variability that
might be expected across relatively short periods. This may explain the failure to find
significant differences between experimental and control group settings in engagement in
meaningful activity. Thirdly, measurement of resident quality of life was limited and it
would be useful to expand the range of measures used, perhaps exploring the use of ASCOT
(Netten et al., 2010). Fourthly, it would be useful to measure the impact of the
intervention on use of other services e.g., whether people are less likely to require
psychiatric, psychological or other health input. In summary, the findings of this study
are promising and suggest that research on challenging behaviour should continue to
investigate intervention in the system of supports surrounding individuals at risk of
developing or continuing to display challenging behaviour. This implies that health and
social care providers should consider the scope for directing some of their behaviour
support resources at systemic, preventative intervention. In the case of Dimensions, they
decided, having seen the results of the intervention, to implement a new model of support
based on that used in experimental settings (see https://www.Dimensions-
uk.org/initiative/activate/). The promising findings suggest that further studies should
be carried out. Ideally, these studies would be larger, involve multiple providers, allow
investigation of costs as well as outcomes and contribute to investigation of the factors
potentially responsible for positive outcomes. It might be argued that the findings of
this study support a “social model” approach to challenging behaviour. That it is possible
to substantially reduce challenging behaviour through interventions that are focussed more
on the environmental context than the individual suggests an analogy with the prevention
of disability (despite impairment) through the making of reasonable accommodations in the
environment and wider society. This is both theoretically important, in extending our
understanding of challenging behaviour, and practically important, in indicating steps we
can take to its prevention.


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<ART>Regret and adaptive decision making in young children
=====================================================

Authors: Eimear O'Connor, Teresa McCormack, Sarah R. Beck, Aidan Feeney
DOI: 10.1016/j.jecp.2015.03.003
Year: 2015  |  Pages: 86-92
ASJC codes: 3204, 3205
Keywords: Anticipated regret, Choice switching, Decision making, Development, Experienced regret, Responsibility

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

In line with the claim that regret plays a role in decision making, O'Connor, McCormack, and Feeney (Child Development, 85 (2014) 1995-2010) found that children who reported feeling sadder on discovering they had made a non-optimal choice were more likely to make a different choice the next time around. We examined two issues of interpretation regarding this finding: whether the emotion measured was indeed regret and whether it was the experience of this emotion, rather than the ability to anticipate it, that affected decision making. To address the first issue, we varied the degree to which children aged 6 or 7 years were responsible for an outcome, assuming that responsibility is a necessary condition for regret. The second issue was addressed by examining whether children could accurately anticipate that they would feel worse on discovering they had made a non-optimal choice. Children were more likely to feel sad if they were responsible for the outcome; however, even if they were not responsible, children were more likely than chance to report feeling sadder. Moreover, across all conditions, feeling sadder was associated with making a better subsequent choice. In a separate task, we demonstrated that children of this age cannot accurately anticipate feeling sadder on discovering that they had not made the best choice. These findings suggest that although children may feel regret following a non-optimal choice, even if they were not responsible for an outcome, they may experience another negative emotion such as frustration. Experiencing either of these emotions seems to be sufficient to support better decision making.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Regret is an aversive emotion that we experience when we believe that we would have
obtained a better outcome had we chosen differently (Epstude & Roese, 2008). Although
regret is aversive, it appears to be a functional emotion in the sense that it assists in
decision making (Epstude & Roese, 2008; Zeelenberg & Pieters, 2007). Experiencing regret
following a poor choice is likely to lead us to change our behavior (Ku, 2008). Moreover,
when deciding how to act, we often try to anticipate and thus minimize the regret that
might arise from our decisions (Zeelenberg & Pieters, 2007). Recently, the developmental
psychology of regret has received considerable attention (Burns, Riggs, & Beck, 2012;
O’Connor, McCormack, & Feeney, 2012, 2014; Rafetseder & Perner, 2012; van Duijvenvoorde,
Huizenga, & Jansen, 2014; Weisberg & Beck, 2010; Weisberg & Beck, 2012). In a typical
study, O’Connor and colleagues (2012) presented children with a choice between two boxes.
In regret trials the prize in the chosen box was always less attractive than that in the
non-chosen box, whereas in the baseline trial the prizes were equally attractive. Children
selected a box for a prize and then rated on a 5-point scale how they felt about choosing
their prize. The alternative prize was revealed, and children indicated, using a three-
pronged arrow, whether they now felt happier, sadder, or the same about choosing their
prize. By 6 or 7 years of age, children indicated feeling sadder on regret trials but not
on the baseline trial, which was interpreted as evidence that children experience regret
from this age. If regret is a functional emotion, then its emergence should have
implications for children’s decision making. O’Connor and colleagues (2014) gave children
the box choice task (Day 1) and then returned the next day (Day 2) to present children
with the same choices. They hypothesized that if the experience of regret affects decision
making, children who experience regret on Day 1 should be more likely to make a different
choice in regret trials on Day 2 than those who do not experience regret. To control for a
general preference to switch choices, adaptive decision makers were defined as those who
were willing to pay a small cost to switch in regret trials on Day 2 but were not willing
to pay this cost to switch in baseline trials. O’Connor and colleagues found that
participants who experienced regret on Day 1 were significantly more likely to switch on
Day 2, and this result held when controlling for age and verbal ability. O’Connor and
colleagues established that this association was not due to children who experienced
regret having better memory for the contents of the boxes by assessing memory in a
separate study. They argued that the experience of regret leads to better decision making
in this task, possibly by increasing the likelihood that, when faced with the same choice
again, children spontaneously bring to mind and evaluate choice options (see O’Connor et
al., 2014, for discussion). There are at least two issues of interpretation with these
findings. The first is whether children’s decisions on Day 2 in O’Connor and colleagues’
(2014) study were really a result of experiencing regret on Day 1 rather than a
consequence of some other negative emotion such as frustration (Rafetseder & Perner,
2012). Weisberg and Beck (2012) argued that if the emotion measured in this type of study
is indeed regret, it should be affected by the level of responsibility one has regarding
the outcome because, at least among psychologists, responsibility for an outcome is
usually considered to be a necessary condition for regret (Zeelenberg, van Dijk, &
Manstead, 2000). In a study of regret using a similar box choice task, Weisberg and Beck
(2012) manipulated the extent to which children perceived themselves to be responsible for
the choice; the outcome was determined by the child’s choice or the roll of a die. In that
study, 6- and 7-year-olds felt sadder when they had chosen the box compared with
conditions involving a die, suggesting that the negative emotion that they reported was
regret. However, unlike O’Connor and colleagues (2014), Weisberg and Beck (2012) did not
examine the impact of children’s negative emotions on decision making, and it remains
possible that, rather than regret having a distinctive effect on children’s choices, other
negative emotions would show the same relation with decision making. A further difficulty
with interpreting an association between the reported experience of regret and adaptive
decision making hinges on the important distinction between experienced and anticipated
regret (Zeelenberg & Pieters, 2007). O’Connor and colleagues (2014) argued that the
experience of regret directly affected children’s subsequent decisions. However, most
theorizing on regret and decision making has focused on the effects of anticipating regret
(predicting future regret and trying to avoid it) rather than its experience. Indeed, some
theorists hold that the primary way in which emotion affects behavior is through
simulation of emotional responses to outcomes that are in prospect (Baumeister, Vohs,
DeWall, & Zhang, 2007). Perhaps the association between reported regret on Day 1 and
decision making on Day 2 was mediated by anticipated regret in that those children who
experienced regret on Day 1 were also likely to be those children who could anticipate
regret. When faced with the same choice on Day 2, this ability to anticipate regret may
have led to children switching choices to avoid future regret. If this is correct, it
would suggest that simply experiencing regret might not have the functional role in
children’s decision making that O’Connor and colleagues (2014) ascribed to it. Rather, in
line with theorizing about adult decision making, regret affects decision making primarily
because in choosing a course of action we attempt to avoid it. The distinction between
experienced regret and anticipated regret is particularly pertinent in a developmental
context because they have different developmental profiles. Using a paradigm first
described by Guttentag and Ferrell (2008), McCormack and Feeney (2015) examined the age at
which children are capable of anticipating regret. Children saw three boxes and were told
that inside each box was a good prize, a medium prize, or nothing (in reality all three
boxes contained a medium prize). One box was removed from the game, and then children
chose between the remaining two boxes. On seeing that they had won the medium prize,
children indicated how they felt on a 5-point scale. Next, they used a three-pronged arrow
to predict whether they would feel the same, happier, or sadder if they discovered that
the large prize was in the unchosen box. There was a developmental lag of at least 1 year
between the experience and anticipation of regret; it was not until 8 years of age that
children were able to accurately predict that they would feel sadder, whereas in a
separate task using O’Connor and colleagues’ (2012) original paradigm nearly all 6- and
7-year-olds experienced regret. The current study was designed to address these two issues
of interpretation with O’Connor and colleagues (2014) results: (a) whether the association
they found between reported emotion and decision making is best described as one between
regret (rather than some other negative emotion) and children’s choices and (b) whether
experienced emotion (rather than anticipated emotion) underlies this association. To
address the first issue (a), we used Weisberg and Beck’s (2012) manipulation of outcome
responsibility to see whether the relation between emotion and adaptive decision making
previously reported could confidently be attributed to regret. To address the second issue
(b), we measured both experienced and anticipated regret to see which was the best
predictor of adaptive decision making. Participants in the current study completed an
experienced regret task on Day 1, completed the choice switching task on Day 2, and then
completed an anticipated regret task.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 229 6- and 7-year-olds (122 girls and 107 boys, Mage = 81 months, range =
72–95) were recruited from schools. One of these schools served a predominantly upper
middle-class population, whereas the remaining six schools served middle- and working-
class populations. The vast majority of participants were of Caucasian origin. Children
were randomly assigned to one of three conditions: Self (n = 76), Dice–Self (n = 78), or
Dice–Other (n = 75). There was no significant difference between conditions in relation to
age or gender of participants.

<hs>  Apparatus</hs>
  ~~~~~~~~~

The apparatus for the experienced regret task included the following: for the baseline
trial, two different-colored boxes, each containing a smaller box with 1 plastic token
inside; for the regret trial, two different-colored boxes, each containing two smaller
boxes, one with 1 token and the other with 10 tokens inside. A two-colored die was used in
the Dice–Self and Dice–Other conditions. An additional three gold boxes were used for the
anticipated regret task, with each gold box having a distinct image on the lid along with
a high-valued prize (Lego set or friendship bracelet set), a medium-valued prize (coloring
pencils, bouncy balls, or stretchy toy), and a low-valued prize (paper clip). A 5-point
scale with pictures of faces ranging from very happy to very sad was used to elicit
children’s emotion ratings. Children indicated how they felt by placing a three-pronged
arrow at the appropriate face. This arrow had one prong pointing upward, one pointing
left, and one pointing right to enable children to report a subsequent change in feelings.

<hs>  Procedure</hs>
  ~~~~~~~~~

Children were tested individually over 2 consecutive days in their schools. On Day 1,
children were invited to play a game where they could win tokens that they could swap for
stickers. All children were first introduced to the 5-point scale and trained in its use
(see O’Connor et al., 2012, for the full training procedure). The training involved two
puppets receiving or losing gifts, and children used the three-pronged arrow to indicate
whether the puppet felt happier (leftward prong), sadder (rightward prong), or the same
(upward prong) over four different scenarios. The experimental trials did not commence
until each child answered the four training questions correctly. The baseline trial was
always introduced first because previous findings suggest that this increases the
likelihood of children experiencing regret in the regret trial (O’Connor et al., 2012; van
Duijvenvoorde et al., 2014). The procedure for both trials was identical. Children in the
Self condition were asked to select one of the two boxes, and the chosen box was then
opened and the actual prize was revealed (1 token in both trials). Children indicated
their emotional response on the 5-point scale. Next, the non-chosen box was opened, and
the alternative prize (1 token in the baseline trial and 10 tokens in the regret trial)
was revealed. Children used the three-pronged arrow to indicate whether they now felt
happier, sadder, or the same after seeing the alternative prize. Children then watched as
the tokens were returned to the appropriate boxes and their name was written on their
chosen box. The experimenter explained that the game would be played again the following
day, emphasizing that the same prizes would be in the same boxes. After children completed
both trials, they swapped their tokens for two stickers. The Dice–Self and Dice–Other
conditions were identical to the Self condition except that the roll of a colored die
determined box selection. In the Dice–Self condition children rolled the die, whereas in
the Dice–Other condition children observed the experimenter rolling the die. Trials were
presented in the same order on Day 2; children were shown their name on their previously
selected box and were reminded that the same prizes were in the same boxes as before. On
Day 2, all children chose the box from which they would like a prize. Before selecting a
box in each trial, the experimenter gave children 1 new token and told them that it was
theirs “for now” but explained that switching boxes cost 1 token and choosing the
previously selected box was free (this was required to control for a general tendency to
switch choices; see O’Connor et al., 2014). Children were asked whether they would like to
pay 1 token to switch boxes or choose the same box for free. Children received 1 token in
the baseline trial regardless of box choice. In the regret trial, children won 10 tokens
if they switched boxes or 1 token if they did not. Next, in the anticipated regret task,
children were shown the three gold boxes along with the high-valued, medium-valued, and
low-valued prizes. Children were asked which prize was the best and which was the worst.
The experimenter explained that each of the boxes contained one of the prizes, whereas in
reality each box contained a medium-valued prize. Children were asked to remove one box
and then to choose between the remaining two boxes. Children rated how they felt about
winning the medium-valued prize using the 5-point scale. The experimenter then said, “You
won the [description of prize] from your box; that’s your prize to keep.” Next, the
experimenter pointed at the non-chosen box and said, “What if the best prize is in this
box, the box you did not chose …,” and then pointed at the chosen box and said, “… then
how would you feel about choosing your box?”

<hs>  Experienced regret</hs>
  ~~~~~~~~~~~~~~~~~~

Table 1 shows the number of participants who felt happier, sadder, or the same after
seeing the alternative prize in each trial broken down by condition. Binomial tests
compared responses with chance performance (33%); in each condition, in the baseline trial
children were more likely than chance to report no change in happiness rating (all ps <
.001) and in the regret trial they were more likely than chance to report feeling sadder
(all ps < .05). Although there was no overall effect of condition on changes in happiness
rating in either trial, there was an association between condition and whether or not
children felt sadder in the regret trial only,1 with children in the Self condition being
more likely to say that they felt sadder than those in the Dice–Other condition (χ2 =
4.14, df = 1, p < .05, ΦC = .18). There was no significant difference between the
Dice–Self condition and either of the other two conditions.

<hs>  Choice switching</hs>
  ~~~~~~~~~~~~~~~~

Children who paid to switch boxes in the regret trial, but not in the baseline trial, were
classified as adaptive switchers. In Table 2, we report switching behavior in each trial
broken down by condition and by whether children felt sadder in the regret trial only
(i.e., sadder in the regret trial and happier or the same in the baseline trial). There
was no significant association between switching behavior and condition, with similar
numbers adaptively switching in all groups. A significant association was found overall
between whether children reported feeling sadder in the regret trial only on Day 1 and
whether children were classified as adaptive switchers on Day 2 (χ2 = 14.59, df = 1, p <
.001, ΦC = .26), and this association held for each condition separately (all χ2s > 5.44,
ps < .05). Therefore, children who had reported feeling sadder in the regret trial only
were more likely to switch adaptively when faced with the same choice again.

<hs>  Anticipated regret</hs>
  ~~~~~~~~~~~~~~~~~~

Of the total sample, 18 children did not appropriately rank the prizes used in the
anticipated regret task and were excluded from subsequent analysis. Of the remaining 211
children, 75 indicated that they would feel sadder if the better prize was in the non-
chosen box, 101 that they would feel happier, and 35 that they would feel the same. The
distribution of responses across the three categories differed significantly from chance
(goodness-of-fit χ2 = 31.43, df = 2, p < .001), with happier being the most common
response. The tendency of children of this age to predict that they would feel happier
under such circumstances was also reported across three experiments by McCormack and
Feeney (2015), who interpreted this as evidence that children adopt a summative approach
(see McCloy & Strange, 2009); that is, any “more” is better even if they do not receive
the larger prize.

<hs>  Predicting choice switching</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

A binary logistic regression analysis with children’s adaptive switching as the predicted
variable examined the fit of the model with the predictors of age, feeling sadder in the
regret trial only (and the same or happier in the baseline trial), and answering “sadder”
to the anticipated regret question. Fully 65% of cases were correctly classified by this
model, χ2(3, N = 211) = 23.90, p < .001, Nagelkerke’s R2 = .14. Feeling sadder in the
regret trial only was the only significant predictor of adaptive switching (β = 1.09, Wald
= 12.88, p < .001, odds ratio = 2.99). This was also the case within each condition
separately.

<h>DISCUSSION</h>
----------

We replicated O’Connor and colleagues’ (2014) finding that feeling sadder in a regret task
on Day 1 is associated with adaptive choice switching on Day 2. Our main purpose was to
examine this association in more detail, looking at (a) whether children’s negative
emotion in our task on Day 1 is best described as regret and (b) whether anticipated
regret, rather than experienced regret, is associated with better decision making. To
address the first question, we manipulated children’s likely perceptions of their own
responsibility for causing the outcome. Although we did not find a significant main effect
of our manipulation, the findings were similar to Weisberg and Beck’s (2012) findings
insofar as children who made a choice (Self condition) were more likely to feel sadder on
discovering that they could have won a better prize than those who had the outcome
determined by the experimenter’s die throw (Dice–Other condition). However, the findings
differed from Weisberg and Beck’s findings in that in the Dice–Other condition, although
only a minority of children reported feeling sadder, they did so significantly more often
than chance. How should we interpret this pattern of findings? If we assume, along with
Zeelenberg and colleagues (2000), that responsibility is a necessary condition for regret,
we cannot describe the emotion experienced by children in the Dice–Other condition as
regret. (The Dice–Self condition is more difficult to interpret because children may
erroneously believe that they are responsible for the outcome in that condition; Weisberg
& Beck, 2012). One possibility is that children feel something akin to frustration that
they have not received the best prize, but (as noted by Rafetseder & Perner, 2012) this
frustration could be either a result of thinking about what might have been (i.e., still a
counterfactual emotion but not regret) or simply a result of comparing unfavorably what
they have (1 token) with what else there is (10 tokens). Our findings do not allow us to
distinguish between these possibilities, but the distinction is important because only in
the first case is counterfactual thinking involved. Nevertheless, the fact that children
were more likely to feel sad in the Self condition than the Dice–Other condition
demonstrates that, regardless of how we interpret children’s negative emotions in the
latter condition, feeling responsible for an outcome affected children’s emotions. Thus,
it is plausible that at least some of what is measured in the Self condition is regret. As
Rafetseder and Perner (2012) argued, children’s emotions in this type of task could be a
mixture of regret and frustration, and indeed this may be the best description of what
underpins emotion reports in the Self condition. Regardless of children’s level of
responsibility for the outcome, feeling sad in the regret trial on Day 1 was associated
with adaptive decision making on Day 2, with the strength of this association being
similar across conditions. This suggests that, at least in this sort of very simple
decision-making task, there may be no special relation between experiencing regret and
making a better choice when faced with the same decision again; other negative emotions
such as frustration (that may or may not involve counterfactual thought) can play a
similar role. The exact mechanism has yet to be characterized, but it is possible that
experiencing the negative emotion strengthens the memory for the events or makes it more
accessible. Furthermore, our findings strongly suggest that it is the experience of such
emotions, rather than their anticipation, that underpins better decision making. Most
children were unable to predict that they would feel sadder if an unchosen box contained a
better prize despite feeling sadder when faced with such circumstances in reality in our
main task, a dissociation that replicates McCormack and Feeney’s (2015) findings. Thus,
our results are a counterweight to the argument that emotions affect behavior primarily as
a result of us simulating and anticipating them in advance of action (see Baumeister et
al., 2007). Before children can anticipate a negative emotion such as regret, they can
experience the emotion, and that experience, even controlling for any ability to
anticipate it, has positive consequences for decision making. Although anticipated regret
is likely to increase in importance later on when it starts to emerge (at around 8 years
of age; McCormack & Feeney, 2015), our findings suggest that experiencing negative
emotions such as regret can directly affect children’s decisions.


<h>REFERENCES</h>
----------

  [1] Roy F. Baumeister, Kathleen D. Vohs, C. Nathan DeWall, Liqing Zhang. How Emotion Shapes Behavior: Feedback, Anticipation, and Reflection, Rather Than Direct Causation. doi:10.1177/1088868307301033
  [2] Patrick Burns, Kevin J. Riggs, Sarah R. Beck. Executive control and the experience of regret. doi:10.1016/j.jecp.2011.10.003
  [3] Kai Epstude, Neal J. Roese. The functional theory of counterfactual thinking. doi:10.1177/1088868308316091
  [4] Robert Guttentag, Jennifer Ferrell. Children's understanding of anticipatory regret and disappointment. doi:10.1080/02699930701541542
  [5] Gillian Ku. Learning to de-escalate: The effects of regret in escalation of commitment. doi:10.1016/j.obhdp.2007.08.002
  [7] Teresa McCormack, Aidan Feeney. The development of the experience and anticipation of regret. doi:10.1080/02699931.2014.912201
  [8] Eimear O'Connor, Teresa McCormack, Aidan Feeney. The development of regret. doi:10.1016/j.jecp.2011.07.002
  [9] Eimear O'Connor, Teresa McCormack, Aidan Feeney. Do children who experience regret make better decisions? A developmental study of the behavioral consequences of regret. doi:10.1111/cdev.12253
  [10] Eva Rafetseder, Josef Perner. When the alternative would have been better: Counterfactual reasoning and the emergence of regret. doi:10.1080/02699931.2011.619744
  [11] Anna C.K. Van Duijvenvoorde, Hilde M. Huizenga, Brenda R.J. Jansen. What is and what could have been: Experiencing regret and relief across childhood. doi:10.1080/02699931.2013.861800
  [12] Daniel P. Weisberg, Sarah R. Beck. Children's thinking about their own and others' regret and relief. doi:10.1016/j.jecp.2010.02.005
  [13] Daniel P. Weisberg, Sarah R. Beck. The development of children's regret and relief. doi:10.1080/02699931.2011.621933
  [14] Marcel Zeelenberg, Rik Pieters. A theory of regret regulation 1.0. doi:10.1207/s15327663jcp1701_3
  [15] Marcel Zeelenberg, Wilco W. Van Dijk, Antony S.R. Manstead. Regret and Responsibility Resolved? Evaluating Ordóñez and Connolly's (2000) Conclusions. doi:10.1006/obhd.1999.2865
<ART>Relationships between implicit and explicit uncertainty monitoring and mindreading: Evidence from autism spectrum disorder
================================================================================

Authors: Toby Nicholson, David M. Williams, Catherine Grainger, Sophie E. Lind, Peter Carruthers
DOI: 10.1016/j.concog.2019.01.013
Year: 2019  |  Pages: 11-24
ASJC codes: 3204, 3205
Keywords: Autism spectrum disorder, Metacognition, Mindreading, Uncertainty judgment, Uncertainty monitoring

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We examined performance on implicit (non-verbal) and explicit (verbal) uncertainty-monitoring tasks among neurotypical participants and participants with autism, while also testing mindreading abilities in both groups. We found that: (i) performance of autistic participants was unimpaired on the implicit uncertainty-monitoring task, while being significantly impaired on the explicit task; (ii) performance on the explicit task was correlated with performance on mindreading tasks in both groups, whereas performance on the implicit uncertainty-monitoring task was not; and (iii) performance on implicit and explicit uncertainty-monitoring tasks was not correlated. The results support the view that (a) explicit uncertainty-monitoring draws on the same cognitive faculty as mindreading whereas (b) implicit uncertainty-monitoring only test first-order decision making. These findings support the theory that metacognition and mindreading are underpinned by the same meta-representational faculty/resources, and that the implicit uncertainty-monitoring tasks that are frequently used with non-human animals fail to demonstrate the presence of metacognitive abilities.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Humans are self-aware. By this we mean that they are capable not only of forming mental
representations of themselves as living entities existing in a world that is separate from
themselves, but also of forming representations of their own mental representations (i.e.,
meta-representations; Pylyshyn, 1978). In short, humans are metacognitive creatures: they
entertain thoughts about their own thoughts.1 One important question concerns the relation
between metacognition (awareness of one’s own mental states) and mindreading or “theory of
mind” (awareness of the mental states of others). This has been subject to intense debate
among philosophers, and these debates have increasingly spilled into the scientific
domain. There are broadly three positions one can take (and which have been taken)
concerning the relation between metacognition and mindreading. The first has a long
tradition in philosophy, dating back at least to Descartes (1637, 1641). It is that we are
aware of our own minds through introspection, and that we combine this self-awareness
together with other forms of knowledge, and other kinds of ability, in order to know of
the mental states of others. To have knowledge of others’ mental states, for example, one
might rely on generalizations about the links between mental states and behavior that have
been learned from one’s own case. Or one might use one’s imaginative abilities to figure
out what someone else is seeing from a different perspective. In its most recent
(empirically-informed) incarnation, the view is that to engage in successful mindreading,
we employ imaginative simulations of the perspectives of other people, attributing mental
states to them by introspecting in ourselves the results of these simulations (Goldman,
2006). Inherent to this view is that we have a privileged, non-inferential access to our
own mental states via introspection, whereas mindreading is based on use of metacognition
via mental simulation. We will refer to this as the “self-awareness is prior” account. A
second possibility is that we are aware of our own mental states by introspection, but we
employ a distinct mindreading faculty when reasoning about the mental states of other
people (Nichols & Stich, 2003). On this view, the two capacities might have distinct
evolutionary origins and paths, are likely to emerge separately in child development, and
will be uncorrelated in task performance. We will call this the “two systems” view. Then
finally, it has been claimed that there is no special faculty of introspection. Rather,
self-knowledge and other-knowledge depend on the operations of the same underlying
faculty/process of meta-representation, albeit relying on partially distinct inputs. For
example, when attributing mental states to the self, the meta-representational faculty has
access to one’s own inner speech and visual imagery, whereas the faculty only has access
to observable behavior when attributing mental states to others. According to this view,
this meta-representational faculty/process evolved in the first instance for other-
directed mindreading, and this deployment of it is also the first to emerge in child
development (Carruthers, 2009, 2011; Gopnik, 1993; Wellman, Cross, & Watson, 2001). We
will refer to this as the “one system” view. Many possible lines of evidence can be
brought to bear on the debate among these three views. First, evidence could be sought
from studies exploring the association between mindreading and metacognition. Both the
self-awareness-is-prior and the one-system views predict that measures of metacognition
and mindreading should be correlated, since each maintains that the two abilities share
processing resources (introspective ability, on the former account; a meta-representation
faculty, on the latter). The two-systems view, in contrast, predicts that such measures
should not be correlated significantly. Second, evidence could be sought from studies of
metacognition in populations that have mindreading impairments. Arguably the “classic”
disorder of mindreading is autism spectrum disorder (ASD).2 ASD is a neurodevelopmental
disorder diagnosed on the basis of behavioral impairments in social-communication and
behavioral flexibility (repetitive and restricted behavior and interests) (American
Psychiatric Association, 2013). At the cognitive level, it is well established that
autistic people have difficulties with mindreading (e.g., Yirmiya, Erel, Shaked, &
Solomonica-Levi, 1998) and that these difficulties contribute to at least some of the
social-communication difficulties that are diagnostic of the disorder (see Brunsdon &
Happé, 2014). Mindreading task performance is reliably diminished among autistic people
relative to the performance of age- and IQ-matched non-autistic individuals (with a large
associated effect size of d = 0.88, according to meta-analysis; see Yirmiya et al., 2001)
and is associated with reduced activation of a well-defined mindreading brain network
(including the temporo-parietal junction, medial prefrontal cortex, precuneus and inferior
frontal gyrus; e.g., Castelli, Frith, Happé, & Frith, 2002; see Schurz, Radua, Aichhorn,
Richlan, & Perner, 2014, for review and meta-analysis). Given that individuals with ASD
have clear difficulties meta-representing others’ mental states, the study of
metacognition in this disorder has the potential to inform theory, as well as our
understanding of ASD itself. Only the one-system view predicts that autistic people should
be impaired on metacognitive tasks relative to neurotypical controls. In contrast, both
self-awareness-is-prior and two-systems theorists explicitly predict that metacognition
should be unimpaired in ASD, and cite evidence from studies of ASD to support the idea of
a dissociation between metacognition and mindreading in this disorder (see Goldman, 2006;
Nichols & Stich, 2003). If such a dissociation between metacognition and mindreading could
be established in the case of ASD, it would represent a major challenge to the one system
account of the relation between (and origin of) these abilities. Therefore, one key aim of
the current study was to test these predictions by investigating metacognition among
autistic people using a classic, widely used metacognitive task (together with classic
mindreading tasks). A third source of evidence that has been used to evaluate the
competing views in this debate comes from studies of metacognition in non-human primates
(mostly macaques; see Beran, Smith, Coutinho, Couchman, & Boomer, 2009; Couchman, Beran,
Coutinho, Boomer, & Smith, 2012; Smith, Beran, Couchman, & Coutinho, 2008; Smith, Beran,
Redford, & Washburn, 2006; Smith, Couchman, & Beran, 2014; Smith, Redford, Beran, &
Washburn, 2010; Smith, Shields, & Washburn, 2003; Washburn, Gulledge, Beran, & Smith,
2010). Based on the performance of macaques on measures designed to provide a behavioral
index of metacognition, it has been claimed that monkeys are aware of their own states of
uncertainty. That is, it has been claimed that macaques are capable of meta-representing
their own knowledge/belief states and making strategic decisions on the basis of this
meta-representation.3 The task that has probably been used most frequently to test
metacognitive monitoring in non-human primates is the “strategic opt-out” uncertainty-
monitoring task. In this paradigm, subjects are presented with a cognitive (“object-
level”) task that involves making a discrimination of some sort (e.g., between a densely
versus sparsely pixelated stimulus, or requiring them to select the longest among lines of
varying length). Successful discrimination results in a valued reward, while failure
results in a penalty (loss of reward, including a “time out” before the next trial). The
crucial feature of such paradigms, however, is that subjects have the opportunity to opt-
out of any given trial, moving immediately to the next trial without penalty or reward.
Participants who make adaptive use of the opt-out option, selecting it in cases where the
discrimination is difficult (where they are otherwise likely to make a mistake), are said
to be monitoring and responding to their own states of uncertainty. In other words, the
individual is said to be meta-representing their own uncertainty about the correct
response on difficult trials, with meta-representation driving adaptive behavioral
responses. The basic finding in the comparative literature is that macaques, chimpanzees,
and humans all make adaptive use of the opt-out option (showing very similar response
profiles), while pigeons and capuchins generally do not (Smith et al., 2014). Such claims
are relevant to the debate about the relation between mindreading and metacognition,
because there is no evidence that macaques are capable of meta-representing the epistemic
states of conspecifics (Marticorena, Ruiz, Mukerji, Goddu, & Santos, 2011). If, therefore,
this species is capable of meta-representing their own epistemic states, but not those of
other macaques, then this would show the same dissociation between metacognition and
mindreading that some have claimed is demonstrated by findings among autistic humans. If
true, this would clearly represent a major challenge for the one system view and support
the self-awareness-is-prior account or the two systems account. Such findings would also
have methodological implications for the study of metacognition in humans, because they
would provide a behavioral measure of the ability that could be employed with children or
adults who have limited verbal communication ability and who could not therefore be tested
using traditional metacognitive tasks. The claim that such tasks really do reveal any sort
of metacognitive awareness is by no means uncontroversial, however. Some critics have
argued against a metacognitive interpretation of the uncertainty-monitoring paradigm by
claiming that its findings can be explained in terms of mere associative learning, rather
than metacognition (Le Pelley, 2012) (but see Smith et al., 2014, for a strong case
against such associative learning models). Other critics of a metacognitive interpretation
of the findings have claimed that the data can be explained in terms of first-order
prospective, affect-involving, decision-making (Carruthers & Ritchie, 2012), of the sort
that humans also engage in regularly (Gilbert & Wilson, 2007; Seligman, Railton,
Baumeister, & Sripada, 2013). On this view, the animals in question are uncertain and this
uncertainty drives behavioral responses. However, uncertainty is a first-order state of
anxiety directed at the primary response options, resulting from an appraisal that the act
of selecting either one of them is unlikely to succeed. As a result, those options seem
bad (are negatively valenced), whereas the opt-out response is neutral or mildly positive.
In order to select the latter, participants just need to pick the option that seems best
in the circumstances; they don’t need to be aware of, or meta-represent, their own state
of uncertainty as such. In short, it has been claimed that while success in these tasks
demonstrates cognitive decision-making, it fails to demonstrate metacognition. In the
current study, autistic and (closely-matched) non-autistic adults completed a strategic
opt-out version of the uncertainty monitoring task that is frequently used in the
comparative psychology literature, as well as a classic “judgement of confidence” task
that is used widely among humans to measure metacognitive ability. In judgement of
confidence tasks, participants make some form of perceptual or cognitive discrimination
and then make a judgement about the likelihood that their discrimination was correct. The
closer the correspondence between actual knowledge and judgements of knowledge, the better
the individual’s metacognitive accuracy. Investigating the performance of autistic
individuals on the implicit opt-out alongside the traditional explicit judgement of
confidence task provided an opportunity to test whether ASD involves a deficit in
metacognition (indexed by diminished performance on the explicit judgement of confidence
task) and whether the implicit opt-out task really measures metacognition. Finally,
participants completed two classic tasks used to measure mindreading ability in humans.
Use of mindreading tasks in the current study allowed us to investigate the extent to
which implicit or explicit task performance relates to mindreading ability. One aim of the
study was to establish whether metacognition is really unimpaired in ASD, as some have
claimed. There is a paucity of research into metacognitive monitoring in ASD and findings
from studies of this ability have high relevance for clinical practice, as well as our
understanding of the cognitive profile of strengths and difficulties in ASD more generally
(as we discuss further in the General Discussion). A second aim was to explore the extent
to which meta-representation of self (on the judgement of confidence task) was associated
with meta-representation of others (on the mindreading tasks). A third aim was to test the
claim that strategic opting-out of difficult trials on uncertainty-monitoring tasks
necessarily requires some form of meta-representation. If implicit uncertainty-monitoring
tasks tap some of the same meta-representational resources as explicit judgement-of-
confidence tasks undoubtedly do, then performance on the two tasks should be related
significantly. In contrast, if implicit uncertainty-“monitoring” is really a form of
first-order affective decision-making, then performance in the two sorts of task should be
uncorrelated, because only the judgement-of-confidence task is meta-representational. In
addition to their possible bearing on contrasting views of the relation between
metacognition and mindreading, there is a second reason for investigating whether implicit
uncertainty-monitoring tasks are genuinely metacognitive in nature. For if they are, this
could provide researchers with an important and hitherto untapped tool for investigating
the development of metacognitive abilities in young (even pre-verbal) human children.
Moreover, such tasks could also provide a potentially important way of testing
metacognitive abilities in nonverbal or minimally-verbal populations, including a
significant proportion of people with ASD. We therefore set out to employ with our
participants one of the implicit uncertainty-monitoring tasks commonly used in the
comparative literature. We thus seek to address two inter-related sets of questions. One
concerns the relation between metacognition and mindreading; the other concerns the
metacognitive status of implicit forms of uncertainty-monitoring. In the study described
below, we set out to investigate both sets of questions in a single framework. We
presented both implicit (non-verbal) and explicit (verbal) uncertainty-monitoring tasks to
a group of adults with ASD and a group of age-, IQ-, and sex-matched neurotypical
controls. We also measured mindreading abilities in both groups. We hoped that this design
would enable us to discriminate between the three differing views of the relation between
metacognition and mindreading (self-awareness-is-prior, two-systems, or one-system), while
at the same time testing whether one of the implicit uncertainty-monitoring tasks that has
commonly been employed with non-human animals is really a test of metacognitive ability.
The predictions of the various views outlined above are laid out in Table 1. Our own over-
arching hypotheses were that (a) strategic opting-out on implicit (non-verbal)
uncertainty-monitoring tasks does not require meta-representation, and (b) metacognition
(as indexed by the judgement-of-confidence task) relies on the resources of the same meta-
representational faculty as does mindreading. We therefore made the following more-
detailed predictions for the outcome of the experiment. ASD-performance on the strategic
opt-out task will not be impaired relative to the neurotypical performance. This is
because we expect strategic opting-out to require only first-order representations, rather
than meta-representations, and there is no reason (that we are aware of) to suggest that
first-order valenced appraisals of stimuli would be challenging for intellectually able
autistic adults. ASD-performance on explicit tasks will be impaired relative to
neurotypical performance. This is because these tasks require explicit metacognitive
judgments, and because such judgments implicate the same resources as the mindreading
faculty, which is widely believed to be compromised in ASD. Implicit task performance
(i.e., degree to which opting-out is adaptive/strategic) should not be predicted by
metacognitive accuracy on the explicit judgement-of-confidence task in either group. This
is because the two tasks do not tap into the same meta-representational resources. We
expect the implicit task to require only first-order valenced decision making, whereas the
explicit task requires meta-representation of one’s own uncertainty. Mindreading ability
will not be related to implicit task performance. This is because the latter task is
really a first-order one. Mindreading ability will be related to explicit metacognitive
performance. This is because success in the explicit tasks requires self-awareness of
one’s own state of uncertainty, and because we expect self-awareness to implicate the same
core meta-representational resources that are employed in mindreading. These five
predictions are laid out in the first row of Table 1. Subsequent rows represent the
predictions of other possible combinations of views. Note that the first three rows
represent the predictions of the three accounts of the relationship between mindreading
and metacognition on the assumption that implicit uncertainty-monitoring tasks are not
metacognitive, whereas the bottom three rows represent those predictions on the assumption
that uncertainty-monitoring is metacognitive. Note, too, that the predictions of the self-
awareness-is-prior and two-system views are the same across both sets of assumptions, with
the exception that only the former predicts that there should be a correlation between
mindreading abilities and explicit metacognitive performance. If the self-awareness-is-
prior view predicts that mindreading and explicit metacognition should be correlated, and
it is accepted that mindreading is damaged in ASD, then one might wonder why only the one-
system account should predict that explicit metacognitive performance will be impaired in
ASD (as we lay out in the second column of Table 1). But the self-awareness-is-prior
account suggests that mindreading comprizes two distinct abilities:
introspection/metacognition and imagination/simulation. The contribution of the former
gives rise to the prediction that mindreading and explicit metacognition should correlate,
but only the latter is thought to be damaged in ASD (Goldman, 2006). So there is no reason
for a self-awareness-is-prior account to predict any impairment in metacognition in ASD.
Proponents of the account could, of course, postulate independent damage to introspective
abilities as well as to imaginative ones (impairment in which is thought to explain the
absence of pretend play in childhood in ASD). But this is not a prediction made by self-
awareness-is-prior accounts as currently formulated, and appears to lack any independent
motivation.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Twenty-one adults with ASD and 22 neurotypical comparison adults took part in the study.
All participants completed the Wechsler Abbreviated Scale for Intelligence-II (Wechsler,
1999), which provides verbal, performance, and full-scale IQ scores. All participants also
completed the Autism-spectrum Quotient (AQ; Baron-Cohen, Wheelwright, Skinner, Martin &
Clubley, 2001. The AQ is a valid and reliable measure of ASD traits in people with a full
diagnosis and in the general population. Participants read statements (e.g., “I find
social situations easy”; “I find myself drawn more strongly to people than to things”) and
decide the extent to which each statement applies to them, responding on a four-point
Likert scale, ranging from “definitely agree” to “definitely disagree”. Scores range from
zero to 50, with higher scores indicating more ASD traits and scores ≥26 representing
clinically significant levels of ASD-like traits (Woodbury-Smith, Robinson, Wheelwright, &
Baron-Cohen, 2005). In addition, participants with ASD completed the Autism Diagnostic
Observation Schedule (ADOS, a detailed observational assessment of ASD features on which a
score o  ≥7 is consistent with a diagnosis of ASD (Lord et al., 2000). Participant
characteristics and matching statistics are presented in Table 2, together with their
scores on the mindreading tasks described in Section 2.2 below. Participants in the ASD
group had received verified diagnoses, according to conventional criteria (American
Psychiatric Association, 2000; World Health Organization, 1993). No participant in either
group reported current use of psychotropic medication or illegal recreational drugs, and
none reported any history of neurological or psychiatric illness other than ASD.

<hs>  Materials and methods</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Mindreading task #1. The Reading the Mind in the Eyes Task (RMIE) (Baron-Cohen,
Wheelwright, Hill, Raste, and Plumb, 2001) is a widely used measure of mindreading in
clinical and non-clinical populations. Participants were presented with a series of 36
photographs of the eye region of the face. On each trial, participants were asked to pick
one word from a selection of four to indicate what the person in the picture was thinking
or feeling. If participants felt more than one of the words was applicable, they were
instructed to select the word they thought was most suitable. Stimuli were presented on
screen to participants in a random order, and no time limit was imposed. Scores on the
RMIE task range from zero to 36, with higher scores indicating better performance on the
task. The proportion of items correctly identified by ASD and comparison participants is
shown in Table 2.4 Mindreading task #2. We also employed a version of the Animations Task
(Abell, Happé, & Frith, 2000) as a second measure of mindreading. The task, which is based
on Heider and Simmel (1944), required participants to describe interactions between a
large red triangle and a small blue triangle, as portrayed in a series of silent video
clips. Four such clips are apt to invoke an explanation of the triangles’ behavior in
terms of epistemic mental states, such as belief, intention, and deception. These clips
comprise the “mentalizing” condition of the task and were employed in this study. Each
clip was presented to participants on a computer screen. After the clip was finished,
participants described what had happened in the clip. An audio recording of participants’
responses was made for later transcription. Each transcription was scored on a scale of
zero to two for accuracy (including reference to specific mental states), based on the
criteria outlined in Abell et al. (2000). Twenty percent of transcripts were also scored
by two independent raters. Inter-rater reliability was excellent according to Cichetti
(1994) criteria (intra-class correlations > 0.82). Accuracy (proportion) among ASD and
comparison participants is shown in Table 2. Note that the Animations Task is a measure of
spontaneous mental-state attribution. Those who score highly on this measure are
spontaneously interpreting the movements of the geometric figures in the videos in mental-
state terms (both affective and cognitive). Those who score low on this measure, in
contrast, will tend to provide literal (non-mentalistic) descriptions of the movements
they have observed. In addition, to reduce the number of statistical comparisons made and
thus reduce the chances of making a type I error, we created a composite mindreading score
(shown in Table 2), which was created by averaging performance across the Animations and
RMIE tasks, as the two tasks correlated significantly in the current sample (r = 0.32, p <
.04). The implicit strategic opt-out/uncertainty monitoring task. The implicit task was a
perceptual discrimination task modeled closely on those that have been employed with non-
human animals. On each trial, participants were presented with either two lines of
differing length (in one version) or two patches of dots comprising differing numbers of
dots (in the other version) (see Fig. 1a). In both versions, a red arrow was also
presented to the right of the two stimuli (lines/patches). Participants were told that on
each trial, they must click on one of the three response options within three seconds, and
they were given a set of instructions outlining the consequences of each choice. They were
instructed that they would start with a balance of £2.00, and would win or lose money
depending on their responses. If the participant clicked on the longest line (or patch
with greatest number of dots) they would gain 10p, whereas if they clicked on the shortest
line (or patch with least number of dots) they would lose 10p. If they clicked on the red
arrow, their score would remain the same and they would proceed immediately to the next
trial. If they did not click on any of the options within 3 s, they would lose 30p.
Participants were asked whether they understood the rules, and were told that this was
important because they would be asked to recall them at the end of the task. They were
given a final chance to clarify the rules before beginning the task, but no further
information about the nature of the task or the study aims was offered. Participants
completed 10 practice trials on which their responses did not count toward their prize
money, before completing 60 experimental trials on which their responses did count. At the
end of the task, the participant’s memory for the response rules was tested; the
experimenter presented the participant with each rule and asked them to complete the
payment amounts for each response type. The order in which tasks (implicit/explicit) were
completed was fixed, such that all participants completed the implicit task before they
completed the explicit task. This was to minimize the chance that participants would adopt
an explicit metacognitive strategy in solving the implicit tasks. The primary dependent
variable for object-level performance was the proportion of trials on which participants
made accurate discrimination judgements. The primary dependent variable for “meta”-level
performance was the difference between (a) the average perceptual discrimination
difficulty on trials that participants opted out of making a discrimination judgment and
(b) the average perceptual discrimination difficulty on trials that participants opted
into making a discrimination judgment (i.e., trials on which they “took the test”). Trial
difficulty was quantified as the similarity (in proportional terms) between the component
items of each stimulus pair, with the smaller the value the more difficult the trial. For
example, a trial on which the component items (length of the two lines, or number of dots
in the two patches) differed by only 1% would be more difficult than a trial on which
items differed by 10%. Evidence of adaptive opting-out would be indicated by participants
opting out of trials on which the proportional difference between item pairs was
significantly smaller than on trials that they opted into (e.g., opting-out of trials
where there was only an average of 1% difference between stimulus pairs, but opting-into
trials where there was an average of 10% difference between stimulus pairs). For the
purpose of correlation analyses, the average trial difficulty of trials that were opted
out of was subtracted from the average trial difficulty of all trials that were opted-
into. The larger and more positive the resulting value (an “adaptiveness score”), the more
adaptive/strategic participants’ opting-out was. If a participant never opted-out, the
difference between options (opt-in/opt-out) could not be calculated. This was viewed as a
lack of adaptive behavior, as participants did not appear to distinguish difficult from
easy trials. Therefore, these participants were given a difference score of zero to
reflect their lack of adaptive responding. The explicit judgement of confidence
metacognition task. In the explicit task, participants completed the same perceptual
discrimination task as they did during the implicit task, but with stimuli counterbalanced
across tasks (those judging line length in the implicit task judged dot number in the
explicit task, and vice versa) (see Fig. 1b). In the explicit task, however, the red arrow
was not present, and participants were forced to choose between one of the two stimuli
presented on the screen. On each trial, after a discrimination judgement had been made,
participants were instructed (on a new screen) to make a confidence judgment relating to
their response on the perceptual discrimination task. Participants could select either
“yes” or “no” to the question “Are you confident?” by clicking on the appropriate box
within 3 s. Participants started with a balance of £2.00 and were instructed that they
would either win or lose money depending on their responses. If the participant clicked on
the longest line (or patch with greatest number of dots) and clicked “yes” (indicating
high confidence), they gained 10p, whereas if they clicked on the longest line and clicked
“no” (indicating low confidence) they would gain nothing. If participants clicked on the
shortest line (or patch with the fewest dots) and clicked “yes” (indicating high
confidence) they would lose 10p, whereas if they clicked on the shortest line and clicked
“no” (indicating low confidence) they would lose nothing. If they failed to respond on any
trial within 3 s, they would lose 30p. Participants were asked whether they understood the
rules, and told that this was important because they would be asked to recall them at the
end of the task. They were given a final chance to clarify the rules before beginning the
task, but no further information about the nature of the task or about the study aims was
offered. Participants completed 10 practice trials on which their responses did not
contribute to their prize money, before completing 60 experimental trials on which their
responses did contribute. At the end of the task, the participant’s memory for the
response rules was tested; the experimenter presented the participant with each rule and
asked them to complete the payment amounts for each response type. The dependent variable
for object-level performance was the proportion of trials on which participants made the
correct discrimination judgement. Gamma scores (Goodman & Kruskal, 1954) were calculated
to provide an index of overall judgement of confidence meta-level accuracy. This analysis
is recommended by Nelson (1984) and is commonly used to analyze judgement of confidence
tasks (e.g., Kelemen, Frost, & Weaver, 2000; Nelson & Narens, 1990; Nelson, Narens, &
Dunlosky, 2004; Wojcik, Moulin, & Souchay, 2013). Gamma scores are a measure of
association (between meta-level judgements of performance and actual object-level
performance) and were calculated by comparing the number of correct meta-judgements with
the number of incorrect judgements made by each individual. To calculate gamma scores the
formula G = (ad − bc)/(ad + bc) was used, with “a” representing the number of “Yes”
(confident) judgements made following a correct perceptual discrimination, “b” the number
of incorrect “Yes” (confident) judgements made following an incorrect perceptual
discrimination, “c” the number of incorrect “No” (not confident) judgements following a
correct perceptual discrimination, and “d” the number of correct “No” (not confident)
judgements following an incorrect perceptual discrimination. Gamma scores range between +1
to −1, where a score of 0 indicates chance-level accuracy, positive values indicate above
chance accuracy, and negative values indicate below chance accuracy. When calculating
gamma scores, the score cannot be calculated when two or more of the prediction rates (a,
b, c, or d) are equal to 0. As such, the raw data were adjusted by adding 0.5 onto each
prediction frequency and dividing by the overall number of judgement of confidence
judgements made (N) plus 1 (N + 1). This correction is recommended by Snodgrass and Corwin
(1988) and is routinely used when calculating gamma scores on metamemory tasks (e.g.,
Bastin et al., 2012; Wojcik et al., 2013).

<hs>  Implicit task performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

With regard to object-level performance, there were no significant differences between
participants with ASD (M = 0.70, SD = 0.08) and comparison participants (M = 0.72, SD =
0.07) in the proportion of trials where stimuli were correctly discriminated, t(41) =
1.20, p = .24, d = 0.04. Thus, the two groups were very similar with respect to cognitive-
level ability. Moreover, there was no significant between-group difference in the number
of payment rules recalled, t(41) = 0.63, p = .53, d = 0.19. Finally, the difference
between ASD participants (M = 0.94, SD = 0.10) and comparison participants (M = 0.87, SD =
0.17) in the proportion of trials that were opted into was non-significant (albeit
moderate in size), t(41) = 1.69, p = .10, d = 0.50.

<hs>  Explicit task performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

With regard to object-level performance, there was no significant difference between
participants with ASD (M = 0.69, SD = 0.07) and comparison participants (M = 0.70, SD =
0.07) in the proportion of trials on which stimuli were correctly discriminated, t(41) =
0.38, p = .71, d = 0.14. Thus, the two groups were very similar with respect to cognitive-
level ability. Moreover, there was no significant between-group difference in the number
of payment rules recalled, t(41) = 1.44, p = .16, d = 0.43. Finally, the difference
between ASD participants (M = 0.80, SD = 0.16) and comparison participants (M = 0.76, SD =
0.13) in the proportion of confident judgements made was non-significant, t(41) = 0.93, p
= .36, d = 0.27.

<hs>  Relation between implicit and explicit “meta”-level task performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

An initial correlation analysis indicated that the degree of strategic opting-out on the
implicit uncertainty monitoring task was non-significantly associated with gamma score on
the judgement-of-confidence task, r = 0.12, p = .43. In order to explore the extent to
which performance on the explicit task predicted performance on the implicit task, a
further regression analysis was conducted. The implicit task adaptiveness score was the
dependent variable and judgement-of-confidence gamma score was used as the predictor
variable. A Group × Gamma interaction variable was also included to establish whether
judgement of confidence was a predictor of implicit adaptiveness score among one group of
participants only. If strategic opting-out depends on meta-representation of own
uncertainty, then meta-level performance on the judgement-of-confidence task (which
clearly requires meta-representation of one’s own mental states) should predict the degree
to which opting out was performed strategically. The results are shown at the top of Table
3. In Block 1, judgement of confidence Gamma was a non-significant predictor of implicit
adaptiveness score, accounting for only 2% of variance in the latter. Gamma remained a
non-significant predictor in Block 2 and the new Group × Gamma interaction-variable was
also non-significant. Thus, the extent to which participants opted out strategically on
the implicit task was not predicted significantly by their metacognitive accuracy on the
explicit task among either group of participants.

<hs>  Relations between mindreading, judgement-of-confidence gamma, and adaptiveness of opting out</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In order to explore the relation between adaptive performance on the implicit and explicit
tasks, on the one hand, and mindreading ability, on the other, two further regression
analyses were conducted (Table 4). In the first analysis, the implicit adaptiveness
difference-score was the dependent variable and the composite mindreading score was the
predictor variable. In addition, a Group × mindreading interaction-variable was included
to establish whether the extent to which mindreading was a predictor of the dependent
variable differed across groups. In Block 1, the mindreading composite score was a non-
significant predictor of implicit adaptiveness difference-score, accounting for <1% of
variance in the latter. The mindreading composite remained a non-significant predictor in
Block 2 and the new Group × mindreading interaction variable was also non-significant.
Thus, mindreading ability was a non-significant predictor of the extent to which
participants made adaptive responses on the implicit task and there was no significant
between-group difference in this extent. In the second analysis, Gamma on the explicit
task was the dependent variable and the composite mindreading score was the predictor
variable. Again, a Group × mindreading interaction variable was included. In Block 1, the
mindreading composite score was a significant predictor of explicit Gamma, accounting for
14% of variance in the latter. The mindreading composite score remained a significant
predictor in Block 2, but the new Group × mindreading interaction variable was non-
significant. Thus, mindreading ability was a significant predictor of the extent to which
participants made accurate metacognitive judgements of confidence and there was no
significant between-group difference in this extent.6

<h>DISCUSSION</h>
----------

We employed an implicit opt-out task that was modeled closely on measures of (alleged)
metacognitive ability widely employed with animals, as well as an explicit judgement-of-
confidence task that is widely used with humans to measure metacognitive accuracy.
Findings were closely in accord with our predictions. First, they indicate that autistic
individuals have impaired metacognitive monitoring ability, as reflected by their
diminished meta-level accuracy on the judgement-of-confidence task (a classic task, used
widely to measure metacognitive ability among humans). Thus, autistic participants had
significant difficulties both with meta-representation of others (they were impaired on
each of the measures of mindreading undertaken) and with meta-representation of self
(diminished judgement-of-confidence accuracy). This is contrary to the suggestion made by
some that metacognition is intact in ASD and that that the disorder shows a dissociation
between (intact) metacognition and (impaired) mindreading. The between-group difference in
judgement-of-confidence accuracy was borderline large after controlling for other task
variables (d = 0.78), and is comparable to the size of mindreading impairment typically
observed among autistic individuals (d = 0.88; Yirmiya et al., 2001) and observed among
autistic participants in the current sample (d = 0.65 for RMIE and 0.93 for Animations).
This is compelling evidence that meta-representation of self is impaired in ASD and that
this impairment is of a magnitude that is comparable to the known impairment of
mindreading in this disorder. The finding of impaired metacognition in ASD is predicted by
the view that metacognition and mindreading share a set of meta-representational
resources. However, it is problematic for all alternative views of the relation between
mindreading and metacognition, unless one were to postulate that a dedicated metacognitive
system is independently damaged in ASD, in addition to the mindreading system that is
widely-acknowledged to be impaired among people with this disorder. Yet none of the
theorists in this debate have predicted such a “double hit”. Indeed, theorists who reject
a one-system view are generally clear that they predict people with ASD should have
preserved metacognitive abilities (Goldman, 2006; Nichols & Stich, 2003). Given the
importance in driving scientific progress of disproving predictions, this finding of
impaired metacognition is important for theory building. Moreover, our finding that
mindreading abilities were predictive of explicit metacognitive performance on the
judgement-of-confidence task suggests that mindreading and metacognition are not
underpinned by two distinct mechanisms, as Nichols and Stich (2003) claim. Taken on its
own, however, this result is consistent with Goldman (2006) self-awareness-is-prior
account, since on his view mindreading abilities depend on metacognitive ones (together
with simulation ability). But in fact our data raise a problem for the latter account
also. For if, as Goldman assumes, it is simulation abilities that are damaged in
individuals with ASD, then it will be these weaker simulation abilities that are
responsible for the poorer mindreading performance of this group. That means that a
significant proportion of the mindreading deficit in autistic individuals will result from
an ability that is plays no part in metacognitive performance; namely, simulation ability.
And in that case we should expect mindreading abilities to be less predictive of
metacognitive abilities in autistic than in neurotypical individuals. But we found no
evidence that this is so. These findings (that metacognition is impaired in ASD and that
metacognitive ability is predicted by mindreading ability) provide support for one-system
views of the relation between metacognition and mindreading. A challenge for one-system
views, however, has been to explain the findings that have been taken to indicate that
some non-human primates are capable of metacognition, but not mindreading. Our results are
relevant to this issue too. In the present study, autistic participants had clear
impairments in meta-representing self (on the judgement-of-confidence task) and others (on
the RMIE and Animations tasks), but yet still opted out of implicit-confidence trials in
the same strategic way that age- and IQ-matched neurotypical comparison participants did.
The between-group difference in the degree to which opting out was adaptive/strategic was
statistically negligible/small and non-significant, which contrasts with the significant
and borderline large impairments in both mindreading (on the RMIE and Animations tasks)
and metacognitive accuracy (on the judgement-of-confidence task) observed among autistic
participants. Moreover, adaptiveness of opting out was not predicted by either
metacognitive ability or mindreading ability; all associations with opting out were
negligible in size. These findings suggest that opting out of difficult trials doesn’t
necessarily require meta-representation (nor does it actually involve meta-representation
in humans who undertake these tasks), but can be achieved using risk-based affective
appraisals of likely success. Of course, it does not prove beyond doubt that non-human
primates do not meta-represent their own states when they opt-out of difficult trials on
equivalent versions of uncertainty monitoring tasks.7 Rather, it shows that it need not be
the case that they strategically opt out by meta-representing self. In the current study,
we observed that autistic participants had statistically significant and large
difficulties with meta-representing self and others, yet nonetheless opted out of
difficult trials strategically. Combined with the findings that the degree to which
participants opted out strategically was not predicted by either metacognitive ability or
mindreading ability (whereas mindreading ability did predict explicit metacognitive
ability), we suggest that a high degree of caution should be taken when interpreting any
findings of strategic opting out as indicating meta-representation of self. These findings
are relevant to theory-building, of course, but also have methodological implications in
that they suggest implicit uncertainty-monitoring tasks cannot be used to reveal nascent
self-awareness abilities in non-verbal or minimally-verbal human populations. Couchman et
al. (2012) point out, however, that when humans are queried after undertaking an implicit
uncertainty-monitoring task of the sort employed here, they report that they opted out
when they did because they were uncertain of the correct response. Isn’t this evidence
that people respond as they do in these tasks because they are aware of their own
uncertainty? But it is one thing to say that humans (and macaques) opt out because they
are uncertain (which we agree with), and quite another thing to say that they opt out
because they are aware of being uncertain. Since humans are consummate mindreaders, they
will of course correctly judge that they responded as they did because they were
uncertain. As such, they retrospectively explain their own behavior by appealing to
epistemic mental states, which requires mindreading. However, this doesn’t show that they
were concurrently aware of their uncertainty while they were responding, nor that they
responded as they did because of such awareness. We submit that if humans sometimes make
the latter sort of causal claim, they go beyond any evidence that could have been
available to them at the time. (Indeed, no one should think that causal relations among
mental states are introspectable.) Moreover, humans are known to engage in prospective
valence-based decision-making in conditions of uncertainty (Gilbert & Wilson, 2007;
Seligman et al., 2013). Indeed, valence is increasingly seen as the “common currency” for
deciding among varying values under conditions of risk (Levy & Glimcher, 2012; Ruff &
Fehr, 2014). Note that these models of human decision-making are not metacognitive ones.
If it is granted that implicit uncertainty-monitoring isn’t genuinely metacognitive, then
when considering the respective predictions of one-system (“metacognition and mindreading
are grounded in a common meta-representational faculty”) and multiple-system views of the
relationship between mindreading and metacognition, the only relevant rows in Table 1 are
the first three. So the relevant differences are just that (1) the one-system view
predicts that explicit metacognitive performance should be weaker in participants with ASD
(who are known to be weaker at mindreading), whereas both the two-system account and the
self-awareness-is-prior account do not; (2) the one-system view predicts that mindreading
ability should be predictive of explicit metacognitive performance, whereas the two-system
account does not; and (3) the one-system view predicts there should be no differences
between groups in the extent to which mindreading ability predicts metacognitive
performance, whereas the self-awareness-is-prior account predicts an interaction. Our
findings support the one-system view in each case. If the one-system view is correct,
however, then why is it that mindreading ability explains only 14% of the variance in
explicit metacognitive performance? If metacognition and mindreading share a common meta-
representational faculty, then one might expect that variability in mindreading ability
should account for a larger proportion of the variance in metacognition than this. In
reply, it is important to note it would be implausible to claim that mindreading is a
monolithic system. Rather, it is likely to comprise a core set of resources (or “core
knowledge”; Spelke & Kinzler, 2006), combined with attribution procedures and inference
rules specific to certain kinds of mental state and/or certain sorts of task or situation.
It seems likely, for example, that the mindreading resources required to identify an
emotional expression from someone’s eyes (as required to succeed on the Reading the Mind
in the Eyes Task) only partially overlap with those accessed when spontaneously
interpreting the movements of seemingly-animated geometrical shapes on a screen (as
required for the Animations Task). And then even on a one-system account, according to
which metacognition and mindreading rely on the same faculty, many of the principles and
resources involved in explicit forms of metacognition are likely to be different again. So
it is not surprising that the measures of mindreading we employed should only correlate
with explicit metacognitive performance to a limited degree, especially since the tasks
differ from one another in many other respects (for example, in their executive demands).
It is also important to note that this finding is a replication of a recent one by
Williams, Bergstrom, and Grainger (2016), who found that the accuracy of explicit
metacognitive judgements of confidence was associated significantly with mindreading
ability in a large sample of neurotypical individuals. Thus, although mindreading ability
is predictive of metacognitive judgement accuracy to a relatively modest degree, the
association would appear to be a reliable one. Taken together, our findings are in keeping
with only one of the theories considered, which is striking given that several predictions
overlap across theories, highlighting how challenging it is to distinguish them
empirically. The findings suggest, on the one hand, that traditional implicit uncertainty-
monitoring paradigms of the sort used to test “metacognition” in non-human animals do not,
in fact, measure awareness of one’s own mental states (or at any rate, not in humans). On
the other hand, the results suggest that accuracy of explicit metacognitive judgements
about one’s own mental states depends to a significant extent on mindreading ability. As a
result, people with ASD, who have established mindreading difficulties, also show
significantly weaker performance on explicit metacognitive tasks (but not implicit
uncertainty-monitoring ones). The fact that we predicted exactly this pattern of results
may be surprising to some autism researchers in the field, given that, in domains other
than metacognition, explicit task performance is sometimes less impaired among autistic
individuals than performance on implicit tasks (see, for example, Brosnan & Ashwin, 2018).
There are various explanations for this pattern of performance (i.e., explicit superior to
implicit) when observed among participants with ASD, such as compensatory strategy use on
explicit tasks or alternative reasoning styles. However, these explanations rely on an
underlying assumption that the implicit task in question depends on the same conceptual
resources as the explicit task. When planning the current study we assumed, quite the
contrary, that the implicit opt-out task did not rely on the same metacognitive resources
as the explicit judgement of confidence task. Thus, the prediction that opt-out task
performance would be undiminished in ASD was not out of keeping with findings in other
domains. Of course, the question of whether intellectually high-functioning autistic
adults would employ compensatory strategies to perform well on the explicit task, despite
limited underlying metacognitive competence, was an open one. In the current study, this
was clearly not the case, but we would not rule out the possibility that other studies
could observe such a finding. The main conclusion from the current study is that there was
a clear differentiation between the implicit and explicit tasks both in terms of levels of
performance observed among autistic participants and in terms of associations with other
cognitive tasks. This is in keeping only with the set of predictions that we made prior to
beginning the study. In addition, our findings have implications for theoretical topics
beyond those that have been our main focus here. They suggest, for example, that one
shouldn’t uncritically accept metacognitive interpretations of adaptive responding on
implicit uncertainty-monitoring tasks, not only when participants are non-human animals,
but also when they are pre-verbal human infants (e.g., Goupil, Romand-Monnier, & Kouider,
2016). This is not to suggest that preverbal infants are incapable of meta-representing
their own states of confidence or uncertainty. (After all, they do appear to be capable of
representing others’ states of mind; e.g, Baillargeon, Scott, & He, 2010.) Rather, we are
suggesting that care should be taken when selecting an experimental technique to
demonstrate self-awareness in infants. One needs to be satisfied that the task taps into
more than just first-order cognitive processes; and on our view, implicit uncertainty-
monitoring tasks do not fit the bill. From a clinical perspective, these results suggest
that intervention efforts designed to remediate mindreading deficits in ASD should have an
added positive influence on metacognitive monitoring abilities among people with this
disorder. Equally, however, the finding that the overlap between metacognition and
mindreading was not absolute in the current study suggests that individuals with ASD would
also benefit from targeted training in metacognitive monitoring. Previous research has
shown that metacognitive monitoring predicts educational outcomes independent of general
cognitive ability (Hartwig & Dunlosky, 2012; Thiede, 1999; Veenman, Wilhelm, & Beishuizen,
2004), and cognitive deficits can be improved by employing metacognitive strategies
(Dunlosky, Kubat-Silman, & Hertzog, 2003; Murphy, Schmitt, Caruso, & Sanders, 1987). This
is of particular relevance for individuals with ASD, many of whom experience significantly
lower academic achievement based on their level of intelligence than would be expected,
which impacts their life chances negatively (Estes, Rivera, Bryan, Cali, & Dawson, 2011).
Therefore, training in metacognitive monitoring has the potential to improve both
educational attainment and quality of life among individuals with ASD.


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<ART>Remembering, imagining, false memories & personal meanings
==========================================================

Authors: Martin A. Conway, Catherine Loveday
DOI: 10.1016/j.concog.2014.12.002
Year: 2015  |  Pages: 574-581
ASJC codes: 3204, 3205
Keywords: Autobiographical memory, Episodic future thinking, Episodic memory, Imagining, Personal meanings, Simulation, Working self

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The Self-Memory System encompasses the working self, autobiographical memory and episodic memory. Specific autobiographical memories are patterns of activation over knowledge structures in autobiographical and episodic memory brought about by the activating effect of cues. The working self can elaborate cues based on the knowledge they initially activate and so control the construction of memories of the past and the future. It is proposed that such construction takes place in the remembering-imagining system - a window of highly accessible recent memories and simulations of near future events. How this malfunctions in various disorders is considered as are the implication of what we term the modern view of human memory for notions of memory accuracy. We show how all memories are to some degree false and that the main role of memories lies in generating personal meanings.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The main contention of this paper is that when people remember they imagine and when they
imagine they use memory. Imagining involves ‘working with memory’ (Moscovitch, 1992).
Because of the intrinsic relatedness of memory and imagination we refer to what we term
the remembering imagining system, RIS, (Conway & Loveday, 2015). The RIS is described
further below. The constructive nature of autobiographical memory and autobiographical
remembering are considered first.

<h>AUTOBIOGRAPHICAL MEMORY</h>
-----------------------

Autobiographical memory (AM) is a complex cognitive system mediated by neural networks
distributed through large areas of the neo-cortex and limbic system (see Cabeza & St.
Jacques, 2007). Indeed, recent neuroimaging studies have found few differences between
remembering, imagining the future, and what is sometimes termed ‘the default network’, all
of which appear to share the same extensive distribution of interlocking neural networks
(see Schacter, Chamberlain, Gaesser, & Gerlach, 2012 for a recent review).
Autobiographical memory contains autobiographical knowledge, e.g. personal factual
knowledge and cultural knowledge, such as the history of our times. It also contains
episodic memories, e.g. fragmentary knowledge derived from experience (Conway, 2009). As
such it forms a major part of the self (Conway, 2005; Conway & Pleydell-Pearce, 2000;
Conway, Singer, & Tagini, 2004). Fig. 1 depicts partonomic knowledge structures in AM in
which episodic memories are part of general events which in turn are part of lifetime
periods which may themselves be part of broader themes such as work or relationship themes
and the life story (Bluck & Habermas, 2001). Different levels of the knowledge structures
are accessed by cues and the lines in Fig. 1 connecting different levels depict the action
of cues and should not be taken as some sort of direct connection. So for example,
knowledge represented in a lifetime period such as ‘Working at university X’ could be used
as a cue to access a the general event, ‘Departmental talks’, which in turn contains
knowledge that can access specific episodic memories. Thus, the entire complex knowledge
base has patterns of activations arising and dissipating continuously in it as experience
is represented in the mind and has the effect of activating associated long-term
knowledge. The idea is that the AM system is labile and intrinsically responsive to cues.
Occasionally, on a daily basis according to Berntsen and colleagues (Berntsen, Staugaard,
& Sørensen, 2013), an AM may spontaneously come to mind. Such involuntary memories often
appear to be the result of a specific cue, illustrating this cue-sensitivity. On other
occasions control process elaborate a cue as a specific memory is sought for (Conway,
2005). This process of generating a memory takes time as a cue iterates through repeated
cycles of elaboration and activation, until the sought-for memory has been constructed. In
all cases the effect of a cue or set of cues is to form a stable pattern of activation
within AM knowledge structures and it is that pattern of activation that is, temporarily,
a memory. A specific AM will also always include the activation of episodic memories. One
interesting hypothesis here is that it is only when an episodic memory or set of episodic
memories are activated that a constructed memory enters consciousness, i.e. the rememberer
becomes consciously aware of the memory. A possibility that then arises is that activation
in the autobiographical memory knowledge base can, and indeed does, occur non-consciously.
Experiences of ‘involuntarily’ remembering may then simply reflect unawareness of memory
processing that occurred prior to the ‘involuntary’ recall. Indeed, Schank (1982)
catalogued many instances of what he term ‘remindings’ – memories unexpectedly coming to
mind often because of an abstract relation to a current situation or to another memory.
So, for example, the structure of an event might cue a memory, as in the case of a person
who recalled that he could not get his hair cur as short as he wanted when in England
cueing a memory of not being able to get a steak cooked as rare as he liked, cf. Schank
(1982). Remindings suggest that there maybe some non-conscious process that monitors
memory for autobiographical knowledge that could help current problem solving. The non-
conscious activation of memories may also underlie feelings such as déjà states, e.g. déjà
vu, having seen before, and déjà vecu – having lived this moment before. We have proposed
that in patients who often experience déjà states, particularly déjà vecu, their memory
feelings may arise from memories that do not enter into consciousness but nevertheless are
strongly enough activated to trigger recollective experience (Moulin, Conway, Thompson,
James, & Jones, 2004). One of the problems with a memory system that has highly labile
patterns of activation continually arising in response to continuously changing cues is
that memories could, potentially, swamp consciousness. Thus, control process must modulate
what memories become instantiated in consciousness at the same time as monitoring the cue-
driven changing patterns of activation in long-term memory for information relevant to
current goals. Finally, it seems to us highly possible that such non-conscious activation
of autobiographical memory knowledge structures might, potentially, play a significant
role in mediating a wide variety of social interactions, e.g. in influencing who we like,
who we do not like, and who we are uninterested in, although this aspect of
autobiographical memory has yet to be investigated. Autobiographical memory is then a
complex multilayered distributed knowledge base in which cues constantly cause patterns of
activation, some of which may stabilize into memories. It seems that this AM network is
never totally inactive although, of course, activation will vary in strength at different
times and may be modulated by control processes as suggested above. For instance,
neuroimaging studies have found a ‘default’ network that is active when attention is
unfocused but which is powered down when attention is focused (Schacter et al., 2012). The
default network takes in many of the networks that feature in autobiographical remembering
and, importantly, many of the same networks are active when future experiences are
imagined. Thus, during ‘day dreaming’ the autobiographical memory knowledge base is
active. In addition during sleep it is now clear that a major component of the AM system,
the medial temporal lobe memory system is also highly active (see Solms, 1997). The AM
knowledge base is, then, never totally quiescent and regions of it are always active, even
during sleep. In general, however, it may be the case that control or executive processes
exercise considerable control over which patterns of activation enter consciousness and
also how patterns of activation are ‘shaped’ by cues. The latter by elaborating cues on
the basis of initial cue activation and so directing a search. The former by denying
patterns of activation access to consciousness, where they would disrupt current goal
processing by turning attention to the pattern of activation in the AM knowledge base and
away from other attention focused activities. Despite this inhibitory control the effect
of cues is always to cause activation in the AM knowledge base. As proposed earlier it
seems possible that such activation, that does not gain conscious representation, may
nonetheless influence goal processing non-consciously. Whether this actually occurs is not
known, but the Self–Memory System (SMS) model of AM put forward by Conway and Pleydell-
Pearce (2000) allows for the possibility.

<h>AUTOBIOGRAPHICAL REMEMBERING</h>
----------------------------

Fig. 2 shows a subsequent development of the SMS model that distinguishes between the
working self, autobiographical memory and episodic memory. The working self consists of
the conceptual self (Conway, Singer, et al., 2004) and the goal system. Memories are
shaped in their construction by the working self and the working self determines what
knowledge derived from experience becomes encoded into the AM knowledge base. Note that,
as all experience is internal, encoding includes sensory-perceptual information, affect,
thoughts, imaginings – it is a sort of derivation of the cognitive milieu over a limited
time, perhaps from an event beginning to event ending (see Williams, Conway, & Baddeley,
2008). In this version of the SMS, AM consists of autobiographical knowledge.
Autobiographical knowledge includes personal knowledge such as lifetime periods and
general events (see Fig. 2) and also more generic and cultural knowledge. Lastly, the
notion of episodic memory is developed further in this model of the SMS (Conway, 2009).
Simple episodic memories consist of fragments of knowledge derived from experience, often
in the form of visual images, together with a ‘frame’, i.e. contextualizing conceptual
knowledge. Simple episodic memories can be grouped together, on the basis of shared cues,
to form complex episodic memories, as shown in Fig. 2. Patterns of activation over
episodic and autobiographical memory constitute specific autobiographical memories. The
whole SMS is self-constraining and the working self determines what memories can be
accessed whereas autobiographical memory constrains what goals, plans, beliefs, etc. can
be realistically held (see Singer & Conway, 2011, for a psychoanalytic extension of this
model).

<h>THE REMEMBERING IMAGINING SYSTEM (RIS)</h>
--------------------------------------

The RIS is a window of accessibility of memories of the recent past and the near future
(Conway & Loveday, 2015). Recently formed episodic memories e.g. those formed today, are
highly accessible, however, as the retention interval increases these become progressively
less accessible. Similarly near future (imagined) events, e.g. those anticipated to occur
tomorrow, are also highly accessible and become progressively less accessible as the
expectation interval increases. Conway and Loveday (2015) found the pattern of
accessibility of specific memories and specific future events approximated to the curve
shown in Fig. 3. Fig. 3 is idealized data rather than actual data and in the study it is
based on participants listed all the memories they could for each day going back five days
and all the specific future events they could envisage plausibly occurring on each day for
the five following days. The curve in Fig. 3 shows the (idealized) percentage of memories
recalled/imagined for each day. It is in the window of the RIS that memories and imagined
events are constructed and so become associated with the current representations of the
recent past and near future. One way to envisage the RIS is as a fish-eye lens in which
items in the center of the lens are sharply defined and clear whereas items that lie
progressively further away from the center become less focused and less distinct. In
recent work in our laboratory (in progress) we have found that for events that
progressively lie further in the future the more abstract, stylized, and schematic they
become. They in effect loose their specificity and become more generic and scripted.
Similarly, much of the more remote past becomes generic and inferred, with occasional
specific memories. The RIS then is a window that extends the present moment some
relatively short distance into the recent past and into the near future. In so doing we
suggest that it is critical in supporting goal processing.

<h>MEMORY ACCURACY: CORRESPONDENCE & COHERENCE</h>
-------------------------------------------

The concept of ‘accuracy’ in AM is complex. Memories might be thought of as falling in a
2-dimensional space of accuracy with ‘correspondence’ as one dimension and ‘coherence’ the
other2 (see Conway, 2005). In this model each dimension would run from low to high
creating four quadrants of: high correspondence-high coherence (unusually accurate
memories), high correspondence-low coherence (memories of trauma might characterize this
quadrant), low correspondence-high coherence (perhaps most memories fall somewhere in this
quadrant), and low correspondence-low coherence (delusional and confabulated memories).
The term correspondence refers to the case where a memory representation corresponds in
some maximum way to a previously experienced event, in other words it is true to the
event. Coherence refers to a memory representation that is coherent with other memory
representations and self-beliefs (the conceptual self), in other words it is true to the
self. Memories never fully correspond to our experience, only to parts of it, although
they may be coherent with the self. Consider the following two memories: When I was 14 I
went to see the Beatles at the Buxton Pavilion Gardens. It was absolutely packed and me
and my friend Jennifer were in the middle of the crowd. You couldn’t hear the music
because there was so much screaming. I am only 5 feet tall and remember thinking I’m going
to faint. Anyway I fainted and was carried to the stage. I came round just as I was being
carried past the Beatles on stage. I was then thrown out of the back door, where there
were many girls sitting crying or in hysterics. The door opened again and my friend was
turfed out. As we stood there the Beatles started playing Twist and Shout and we ran back
into the hall to see the end of the show. A middle-aged man recalled his father
distracting him when he was a young boy (about 4 years old) by asking who was the first
man on the moon. He had been intensely interested in the moon landing when he was a young
boy and this incident occurred while his father was on the telephone to his mother who had
just given birth to his younger brother. He had a vivid and fond memory of his father
placating him in this way, he was highly agitated by the birth, and in his memory he could
‘see’ his father on the telephone and almost ‘hear’ his voice. It was only decades later
that he realized that his brother had been born in 1968, one year before the first moon
landing. The first memory illustrates a common feature of all memories: time compression.
The memory contains some vivid details, some of which may correspond to the experience.
Nonetheless, an event that took place over several hours is condensed into a short
paragraph, in turn derived from a memory that took merely seconds to construct. Moreover,
many details will have been added non-consciously and automatically, such as details of
clothes worn, lighting, sound levels, the weather, etc. According to our model this would
be a moderate correspondence-high coherence memory. The second vivid memory may also
contain some details that are true of the event, but the memory itself is of a supportive
and caring father so it is a memory construction that is principally true of the self with
which it is coherent. It is a low correspondence-high coherence memory. In general,
memories are depictions of the past constructed in the RIS from the complex underlying
knowledge base. They fall somewhere in the correspondence-coherence space with all
memories having aspects of both. One suggestion is that the mean of the distribution of
memories in the correspondence-coherence 2D space is, for most people, closer to coherence
than it is to correspondence. In this model it is possible for a memory to be
simultaneously correct and incorrect, after all the owner of the 2nd memory above, did
have a brother and a caring father, who most probably did phone the mother after the
birth, etc. There are also other interesting properties of memories that emerge according
to their degrees of correspondence and coherence. One of interest is the extent to which
an individual’s memories although a mix of both correspondence and coherence are, overall,
biased to one or other of the dimensions. Perhaps such biases contribute to determining
different personality characteristics and types.

<h>BROKEN MEMORIES</h>
---------------

In concluding I will make a brief and highly selective overview of some of the ways in
which memory can be impaired following brain damage, in psychological illness, and the
effects of this on the SMS.

<hs>  Confabulation</hs>
  ~~~~~~~~~~~~~

There is an extensive literature on confabulation resulting from various types of brain
injury. I will consider two representative cases here. Patient O.P. was a 70 year-old
woman who suffered lesions to the frontal and temporal lobes following an RTA (Conway &
Tacchi, 1996). O.P. made a complete physical recovery but, on return home, her family
complained of her constant ‘lies’. Her neuropsychological profile indicated spared IQ,
language, and conceptual abilities. With some memory impairment and severe disturbance on
frontal tests. O.P. could recall some memories very accurately but confabulated other
memories about events relating to her family and these were nearly all focused on her
grandson. They featured memories in which as a child he made implausible journeys to visit
her, had major academic achievements, and later career achievements, all of which greatly
pleased her. In fact he had been unsuccessful at school and in his career and lately had
been unemployed for some years. He had little contact with her at any point in his life.
Nonetheless, O.P.’s confabulations, or as Moscovitch (1995) termed them honest lies, were
enduring and appeared to be highly emotionally positive for her. A case of coherence
memories serving the purpose of providing a positive self-image during a time of
considerable personal difficulty. Indeed, in many cases of confabulation following frontal
damage it seems that the drive to make sense of the world persists but on the basis of
false memories. For example, hospitalized frontal patients variously believe themselves to
be in a hotel, at the office, waiting to play a round of golf, etc. Such meanings are not
always positive and can be mixed with other confabulations that are emotionally negative,
often highly negative (Fotopoulou, Conway, Birchall, Griffiths, & Tyrer, 2007). In either
case, however, they reflect attempts to make sense of a world in which (false) memories
constructed in the RIS drawn from knowledge in AM are constructed in ways that serve a
disrupted working self. A working self in which personal beliefs and meanings are no
longer grounded in and constrained by specific autobiographical memories. Patient P.S.
(Hodges & McCarthy, 1993) suffered a bilateral paramedian thalamic infarction resulting in
a temporally graded retrograde amnesia (RA) and dense anterograde amnesia (AA). His RA
stretched back to his early 20s and he believed himself to be a naval rating in the 2nd
world war at home on shore leave – he was in fact a 60-year old businessman. Thus, the
working self in trying to make meanings out of experience could only draw up on a RIS that
had existed in some form when P.S. had been about 19 years of age. Current phenomena of
daily life were interpreted through this RIS and, for example, PS was surprised by how
much science fiction there was on the television and insisted in a nightly blackout. The
case of P.S. illustrates very powerfully how the working self and indeed the RIS are
constrained by the autobiographical knowledge they are able to access, that is by the cues
control processes are able to use to create patterns of activation in the knowledge base,
i.e. construct memories.

<hs>  Psychological Illness</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Baddeley and Wilson (1986) describe interviews with a series of schizophrenic patients.
One striking feature of such patients is that their delusions were virtually always
contradicted by other memories or autobiographical knowledge that, although wholly
inconsistent with their beliefs no longer had the constraining power typical of a healthy
autobiographical memory. In the 2D space of correspondence and coherence their memories
would fall clearly in the quadrant denoting low correspondence and low coherence. For
example, one patient, a man in his early 20’s, believed himself to be a famous rock
guitarist, and confabulated memories of various ‘gigs’, while at the same time knew he had
never learned to play the guitar and had never been to many of the places his delusions
suggested. Another patient believed himself to be a Russian chess grandmaster, even though
he knew he had never been to Russia and could recall being beaten at chess by other
patients on his ward.

<hs>  Posttraumatic stress disorder (PTSD)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Memories that derive from traumatic experiences often contain errors and distortion
(Conway, Meares, & Standart, 2004). One patient, for example, had been sexually abused by
his grandfather from ages of 4 to 12. He had a persistent and intrusive flashback in which
he was naked in a bathroom being pushed against the radiator by his naked grandfather. In
this intrusive fragment he saw himself from an observer perspective as he was now, a
balding 35-year old, and saw in the memory his grandfather as a frail 70-year old. In fact
it became clear during therapy that he had been 6 at the time and his grandfather was in
his 40s. The false (coherence) memory served the function of obscuring the fact that he
had been a helpless victim. Another PTSD patient who had witnessed the 9/11 attack on the
World Trade Centre in New York had a vivid and deeply disturbing flashback in which he was
flying in complete silence above the plane as it approached the tower. During therapy he
eventually retrieved the true memory of standing in the crowd watching the plane strike
the tower and then experienced the intense feelings of apprehension and fear that he had
had at the time and also the later guilt that he had about the experience. Thus, distorted
and false coherence memories can have a function of creating meaning that allow the
working self to avoid negative self images and intense negative emotions.

<h>CONCLUSION: THE MODERN VIEW OF HUMAN MEMORY AND MEMORY ACCURACY</h>
---------------------------------------------------------------

In the modern view of human memory memories are mental constructions. It is important to
note that they are not reconstructions. They are not like videos, photographs or other
recording media, even though they frequently contain mental imagery. They are transient
constructions and although they may to some degree accurately represent the past they are
time-compressed and contain many details that are inferred, consciously and non-
consciously, at the time of their construction. Thus, all memories are to some degree
false in the sense that they do not represent past experience literally. They can, of
course, be wholly false but nonetheless be experienced as memories by a rememberer who may
be unaware that the source of a memory is not experience but imagination. One of the main
functions of memories is to generate meanings, personal meanings, that allow us to make
sense of the world and operate on it adaptively. Memories are, perhaps, most important in
supporting a wide range social interactions where coherence is predominant and
correspondence often less central. A strong implication of this view is that false
memories far from being damaging to the individual can often be of considerable benefit,
particularly in maintaining a coherent, confident, and positive self. Our time-compressed
memories with their inferred and remembered details, their mixture of coherence and
correspondence, serve this function perhaps for all of us. In closing, then, we might
reflect on a hypothetical, if fairly extreme, example of this. Consider a person who has
had an adverse childhood. Their confidence and sense of self-worth have been undermined by
an emotionally, psychologically, and perhaps physically abusive parent. Their subsequent
life has been a series of disasters marked by poverty, failed relationships, substance
abuse, and disturbed children of their own. Through whatever means they gradually develop
a set of memories of having been sexually abused by the parent. These memories are based
in part on memories of actual occurrences of abuse that they experienced, although not on
memories of sexual abuse. Details of the latter gradually become incorporated into some of
their childhood memories by a process of imagination (see Garry, Manning, Loftus, &
Sherman, 1996). They then come to experience these high coherence-low correspondence
mental representations as memories and memories that in turn support a powerful personal
meaning. Namely that the individual has been victimized (which in this hypothetical
example indeed they have, but not sexually) and it is the effects of the victimization
that have led to their disastrous life. Thus, the ‘memories’ provide the basis of an
explanation for subsequent important parts of their life. This, of course, is merely an
illustration (although perhaps not such an uncommon one, see Conway, 2013) of how memories
(and recall that all memories are to some degree false) maybe of value in supporting the
generation of explanatory beliefs about one’s life. We suggest it is something we all do.


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<ART>Reprint of “The Single-Case Reporting Guideline In BEhavioural Interventions (SCRIBE)2016: Explanation and Elaboration”
================================================================================

Authors: Robyn L. Tate, Michael Perdices, Ulrike Rosenkoetter, Skye McDonald, Leanne Togher, William Shadish, Robert Horner, Thomas Kratochwill, David H. Barlow, Alan Kazdin, Margaret Sampson, Larissa Shamseer, Sunita Vohra
DOI: 10.1016/j.prps.2019.03.001
Year: 2019  |  Pages: 119-151
ASJC codes: 3200
Keywords: methodology, publication standards, reporting guidelines, single-case design

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

There is substantial evidence that research studies reported in the scientific literature do not provide adequate information so that readers know exactly what was done and what was found. This problem has been addressed by the development of reporting guidelines which tell authors what should be reported and how it should be described. Many reporting guidelines are now available for different types of research designs. There is no such guideline for one type of research design commonly used in the behavioral sciences, the single-case experimental design (SCED). The present study addressed this gap. This report describes the Single-Case Reporting guideline In BEhavioural interventions (SCRIBE)2016, which is a set of 26 items that authors need to address when writing about SCED research for publication in a scientific journal. Each item is described, a rationale for its inclusion is provided, and examples of adequate reporting taken from the literature are quoted. It is recommended that the SCRIBE 2016 is used by authors preparing manuscripts describing SCED research for publication, as well as journal reviewers and editors who are evaluating such manuscripts.

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<h>METHODOLOGY</h>
-----------

The first phase to develop the SCRIBE 2016 consisted of two rounds of an online Delphi
survey completed by SCED authors and methodology experts, resulting in 44 items to be
discussed at a consensus conference. At the meeting, held in Sydney, Australia, in
December 2011, participants reworked the items, resulting in a final set of 26 items for
the reporting guideline, which are described in this Explanation and Elaboration article.
The SCRIBE 2016 Statement (Tate et al., 2016) provides a detailed description of the
methodology of this process.

<h>RESULTS</h>
-------

This article provides examples of adequate reporting from the literature for each of the
26 items, along with a rationale for inclusion of the item and, where available, evidence
of bias resulting from incomplete report- ing (the SCRIBE checklist of items appears in
Table 1).

<h>SECTION 1: TITLE AND ABSTRACT (ITEMS 1 AND 2)</h>
---------------------------------------------

Item 1—Title: Identify the research as a single-case experimen- tal design in the title.
Graded exposure in vivo in the treatment of pain-related fear: a replicated single-case
experimental design in four patients with chronic low back pain. (Vlaeyen, de Jong,
Geilen, Heuts, & van Breukelen, 2001, p. 151) Explanation. Although journals may place
word limits on the title, it is important to include as much information as possible in
the title, such as the intervention, the target behavior and the population. In
particular, the title should explicitly mention that the study is a SCED because this
differentiates the study from a case description. The abstract is sometimes copyrighted by
the journal, so the title may be the only searchable information. Identifying the study as
a SCED in the title will ensure that the article is appropriately indexed for
bibliographic databases (such as PsycINFO or Medline). Note that using “SCED” as a key
word will not be sufficient for this purpose because author key words are different from
database key words and may therefore not be searchable in electronic databases. Item
2—Abstract: Summarize the research question, popula- tion, design, methods including
intervention/s (independent vari- able) and target behavior/s and any other outcome
measures (dependent variable), results, and conclusions. This study tested the
effectiveness of Imagery Rescripting (ImRs) for com- plicated war-related PTSD
[posttraumatic stress disorder] in refugees. Ten adult patients in long-term supportive
care with a primary diagnosis of war-related PTSD and Posttraumatic Symptom Scale (PSS)
score >20 par- ticipated. A concurrent multiple baseline design was used with baseline
varying from 6 to 10 weeks, with weekly supportive sessions. After baseline, a 5-week
exploration phase followed with weekly sessions during which traumas were explored,
without trauma-focused treatment. Then 10 weekly ImRs sessions were given followed by
5-week follow-up without treatment. Participants were randomly assigned to baseline
length, and filled out the PSS and the BDI [Beck Depression Inventory] on a weekly basis.
Data were analyzed with mixed regression. Results revealed significant linear trends
during ImRs (reductions of PSS and BDI scores), but not during the other conditions. The
scores during follow-up were stable and significantly lower compared to baseline, with
very high effect sizes (Cohen's d = 2.87 (PSS) and 1.29 [BDI]). One patient did clearly
not respond positively, and revealed that his actual problem was his sexual identity that
he couldn’t accept. There were no dropouts. In conclusion, results indicate that ImRs is a
highly acceptable and effective treatment for this difficult group of patients. (Arntz,
Sofi, & van Breukelen, 2013) Explanation. The abstract needs to provide an accurate,
infor- mative and unambiguous overview of the study. It is important that all relevant
information is included because many readers may not have access to the full article, or
may choose to limit their reading of the study to the abstract. The CONSORT guideline for
abstracts for randomized trials (Hopewell et al., 2008) provides useful information about
how to write an abstract which, although written for RCTs, has applicability to SCEDs. A
structured abstract can be useful and make the abstract easy to follow. It is important
that the abstract clearly describes relevant features of the participant/s (including
clinical details where appropriate), defines the depen- dent and independent variables,
along with the SCED design used to examine their relationship. The target behaviors and
any addi- tional outcome measures (e.g., for generalization) used in the study should be
specified, along with the way in which the target behavior is measured. An accurate
summation of the outcomes of the study needs to be clearly detailed, along with disclosure
of any harms or adverse events, and conclude with a brief, cautious appraisal of the
significance of the research.

<h>SECTION 2: INTRODUCTION (ITEMS 3 AND 4)</h>
---------------------------------------

Item 3—Scientific background: Describe the scientific back- ground to identify issue/s
under analysis, current scientific knowl- edge, and gaps in that knowledge base. Verb
production problems are an extremely common and pervasive aphasic deficit following
stroke. Past research into word retrieval and production has mostly focused on nouns. More
recently there has been increased interest in verb retrieval and verb processing
disturbances [ref]. Unfortunately. One potentially useful speech pathology treatment for
word production deficits involves the use of arm and hand gestures. What remains to be
developed is empirical evidence to support or refute the suggestion that gesture is a
potent treatment for verb retrieval deficits. This paper presents evidence. (Rose &
Sussmilch, 2008, pp. 692–693) Explanation. The introduction is normally a discursive text
that overviews the relevant literature and identifies the gaps in knowledge that the
current study aims to address. Ideally the text is succinct and targeted to the main
issues that frame the context of the study. The introduction should commence with what is
known about the problem area and its interventions, what is yet to be understood, and how
this study can address this gap. Item 4 —Aims: State the purpose/aims of the study,
research question/s, and, if applicable, hypotheses. The purpose of the present study was
to examine the effects of a written cueing treatment programme on verbal naming ability in
two adults with aphasia. Treatment involved using a written cueing hierarchy, which was
modelled after CART [Copy and Recall Treatment] and included verbal and writing
components. (Wright, Marshall, Wilson, & Page, 2008, p. 524) Explanation. The purpose and
aims of the study need to be clearly described, normally at the conclusion of the
Introduction. These should take the form of research questions that define the independent
variable, the dependent variable, and report if a formal relationship was assessed.
Statement of aims and, if applicable, hypotheses, provide the reader with explicit
directions regarding the way in which the design, methods and results should be read,
given that these should all follow from the aims/research questions being asked.

SECTION 3: METHOD—DESIGN (INCLUDING BOTH DESIGN STRUCTURE, AS WELL AS BROADER ASPECTS OF INTERNAL AND EXTERNAL VALIDITY), PARTICIPANT/S, CONTEXT, APPROVALS, MEASURES AND MATERIALS, INTERVENTIONS, ANALYSIS (ITEMS 5–18)
--------------------------------------------------------------------------------

Item 5—Design: Identify the design (e.g., withdrawal/reversal, multiple-baseline,
alternating-treatments, changing-criterion, some combination thereof, or adaptive design)
and describe the phases and phase sequence (whether determined a priori or data- driven)
and, if applicable, criteria for phase change. Example 1: Withdrawal/reversal design. An
A-B-A-B single-subject design evaluated a token economy for increasing exercise in
children with CF [cystic fibrosis]. Two advantages of this design are that it provides two
evaluations of the treatment compared to baseline and it ends on a treatment phase, which
is important from a clinical standpoint. The exercise diary data were used to determine
when study phase changes were made. The specific criteria were the following: (a) there
were three or more stable data points, (b) there was a predictable pattern in the data, or
(c) there was no pattern, but the data points were predictably random. (Bernard, Cohen, &
Moffett, 2009, p. 354–357) Example 2: Multiple-baseline design. A randomized, concurrent,
multiple-baseline single-case design was applied.13 Participants completed repeated
measurements during a baseline phase (phase A), an intervention period (phase B, 12 weeks)
and a postintervention period (phase A = ). Phase A acted as a control and was therefore
compared with phases B and A=. (Hoogeboom et al., 2012, p. 2) Example 3: Alternating-
treatments design. The study used a multielement design with no baseline [ref] and a final
“best treatment” phase [ref] to compare the effects of three contingent consequent events
(Treatment A, adapted toys and devices; Treatment B, cause-and-effect commercial software;
and Treatment C, instructor cre- ated video programs) on the frequency of stimulus
activations. Students received intervention in alternating treatments followed by the best
treatment phase, in which only the most effective intervention was delivered. (Mechling,
2006, p. 98) Example 4: Changing-criterion design. [This study evaluated] a prompting and
shaping intervention, in the form of a changing criterion design. [ to] assist this
athlete in the technical development of his vault and corresponding height cleared. A
photo- electric beam. was set across the runway at a height of 2.30 m (5 cm above the mean
height obtained during baseline). Intervention at this height continued until the
participant displayed stability in his performance at a 90% level. Stability in
performance referred to the successful repetition of three or more 90% performances.
Following successful completion, intervention was also administered at the following
heights: 2.35. 2.52 m. (Scott, Scott, & Goldwater, 1997, pp. 573–574) Explanation. In a
broad sense, the design of a SCED encompasses all components of the methodology. For the
purpose of this item, it specifically refers to the basic structure of phase sequencing
and phase onset used in the investigation. That is, the design defines how the independent
variable is manipulated, what the baseline conditions are, and when/how the independent
variable is introduced/changed. Manipu- lation of these parameters allows the investigator
to systematically control the independent variable in order to demonstrate the
experimental effect. Moreover, using multiple phase changes in the design provides
opportu- nity for repeated demonstration of the experimental effect on the same
participant. This constitutes direct intrasubject replication (see Item 7 for intersubject
replication and systematic replication). The design of SCEDs is crucial for determining
the adequacy of control of threats to internal validity and the experimental effect
(Horner et al., 2005; Kratochwill et al., 2013). Design characteristics need to be clearly
and specifically reported, otherwise it is difficult for the reader to determine if the
study has sufficient experimental control to ade- quately establish a functional cause-
effect relationship between the de- pendent and independent variables and (b) evaluate the
reliability of the results. In a small random sample of 20 reports using a single
participant archived on the PsycBITE database, 45% of reports did not provide any
information on the type of design used and an additional 20% incorrectly described the
design (Tate et al., 2013b). Specific reporting requirements will vary among the
experimental designs. A major strength of SCEDs is their flexibility and adaptability. In
addition to the “classic” designs described below, elements of these designs can be
creatively combined in a multitude of ways depending on the research/clinical question
being addressed and the intervention being considered (e.g., see e.g., see Hayes, Barlow,
& Nelson-Gray, 1999). A fundamental requirement in reporting SCEDs is that the basic
structure of the design is explicitly and accurately described. This consists of reporting
the following eight invariant features that apply to all designs: Basic information
required for all designs, including withdrawal/reversal (A-B-A-B) design. The type of
design (e.g., withdrawal/reversal) The number of phases (including baseline, experimental,
maintenance and follow-up phases) The duration (length) of each phase The order in which
the phases are sequenced (e.g., random- ized, counterbalanced, data-driven) The number of
sessions in each phase The number of trials within each session in a phase (i.e.,
occasions when the dependent variable is being measured) The duration of sessions The time
interval between sessions (see also Item 20) Additional descriptive information needs to
be provided for spe- cific design types. Additional information required for multiple-
baseline designs. The number of different (i.e., multiple) baselines (also referred to in
the literature as data series, tiers, levels or legs) that the design contains. A graph
alone is insufficient, because a graph represents the results that were obtained, rather
than the design as planned, which may change in response to the intervention (see Item 6).
Whether the baselines are across participants, behaviors or settings The method for
determining treatment onset (e.g., response guided, randomization), or, if necessary, that
there was no specific rationale or empirical basis Sometimes multiple-baseline designs
also incorporate either a follow-up phase after the initial intervention phase or an “em-
bedded” design (e.g., alternating-treatments). When such a vari- ant is utilized, the
complete sequence of phases should be clearly stated in the design description. Whether or
not the onset, and subsequent continuance, of data collection in each of the baselines
occurred concurrently (i.e., at the same points in time) or nonconcurrently. If
nonconcurrent, provide a rationale for this choice. Additional information required for
alternating-treatments designs. Whether interventions were administered on the same
day/session (e.g., Intervention 1 in the morning, Intervention 2 in the afternoon) or
different days/sessions The way in which the order of the interventions was deter- mined
(e.g., randomized, counterbalanced, Latin square) The detailed phase sequence (e.g.,
inclusion of a baseline preceding the intervention; a final “best treatment” phase fol-
lowing the intervention) Additional information required for changing-criterion designs.
All criteria or decision rules used to determine when a phase change occurs Whether the
criteria are set a priori or are response guided Additional information required for
adaptive designs. In these designs, the structure of the investigation (e.g., phase
sequence/dura- tion, interventions, variations in intervention) is not fixed a priori, but
depends, on an ongoing basis, on characteristics of the data (or responses) from early (or
preceding) phases, Authors should also clearly describe the following: Features or
characteristics of the data (operationally defined) that are used to regulate the study
design Which specific aspects of the study design, at each and all steps in the study, are
determined by which specific features of the data Item 6 —Procedural changes: Describe any
procedural changes that occurred during the course of the investigation after the start of
the study. BST [behavioral skills training] was implemented with each child individually
in two 15- to 20-min sessions. If the child did not obtain a score of 3 during an
assessment after the initial BST sessions and two booster sessions, an additional
assessment session was turned into a training session. For Jake, who did not exhibit the
correct behavior following BST or in situ training, an incentive phase was added.
(Miltenberger et al., 2004, pp. 514–516) Explanation. There are occasions when, for a
variety of reasons, the proposed implementation of a study changes from the original plan.
Changes may occur to any component of the study, including (a) methodological design; (b)
setting in which the study takes place; (c) target behavior and any other outcome
measures, with respect to content, method or frequency of administration; (d) equipment or
materials to deliver the intervention; (e) use of practitioners and assessors; or (f) the
intended intervention. Changes involving participant attrition or early termination of
phases are addressed in Item 19. The researcher may actively initiate changes that are a
departure from protocol or they may be thrust upon the researcher as a result of external
factors. With respect to changes in the intervention, one of the reported strengths of
single-case methodology is the flexibility of implementation of the intervention (Connell
& Thompson, 1986; Gravetter & Forzano, 2009). If adverse events occur or the intervention
is not working sufficiently, then it is acceptable for the researcher to make alterations
without necessarily compromising experimental control. Authors need to report any changes
or departure from the original plan or protocol, such as those listed above, along with
reasons. They should also provide a statement about their impact on the interpreta- tion
of the results. Places to describe procedural changes in the report will depend on the
type of change/s, but either the Method or Dis- cussion sections are appropriate. Item
7—Replication: Describe any planned replication. Example 1: Systematic replication. We
employed a multiple-baseline design to test the efficacy of a recently developed approach
for reducing school refusal behavior. To maxi- mize external validity, the intervention
was tested using a systematic replication strategy, whereby only the major conceptual
elements of the intervention were retained from previous applications. (Chorpita, Albano,
Heimberg, & Barlow, 1996, p. 281) Example 2: Direct intersubject replication. A single-
subject ABAC design with replication across three participants was employed. (Leon et al.,
2005, p. 96) Explanation. Replication is a key feature of single-case method- ology and is
important because it has the capacity to inform whether and the extent to which an
intervention is generalizable and hence is important for external validity. In spite of
its central significance, replication is not commonly reported, with just over half of the
studies (54%) in the neurorehabilitation survey of Tate et al. (2014) describing
replication. In addition, although it may be evident that there is replication in a study,
it is not always explicitly stated. Three types of replication are described in the
literature (Barlow et al., 2009; Gast, 2010a; Horner et al., 2005; Kratochwill et al.,
2010, 2013; Sidman, 1960). Direct intrasubject replication refers to replication of the
experimental effect within the design and addresses issues of internal validity (see Item
5). The other two types of replication are relevant to this item: (a) systematic
replication (i.e., repeating the experiment with the same intervention but systematically
changing characteristics of the in- dividuals, setting, interventionists and/or behaviors)
and (b) direct inter- subject replication (i.e., repeating the same study but with
additional individuals). Using a series of replications, Horner et al. (2005) and
Kratochwill et al. (2010, 2013) note that it is possible to provide a strong basis for
causal inference. They have proposed criteria for the purpose of establishing evidence-
based treatments: (a) a minimum of five methodologically strong research reports, (b)
conducted by at least three different research teams at three different geographical
locations, and (c) with the combined number of cases being at least 20. Authors should
clearly and specifically state the number and type of replications in the Abstract and the
Method section. If the study is using systematic replication to build an evidence-base,
authors may consider using the term systematic replication in the title. Authors need to
clearly indicate whether the replication refers to (a) the replication of a previously
published study or (b) intersubject repli- cation within the current study. Item 8
—Randomization: State whether randomization was used, and if so, describe the
randomization method and the ele- ments of the study that were randomized. Example 1:
Randomized sequence. Two treatments, one imitative and one cognitive-linguistic, were
employed and treatment order was determined randomly. (Leon et al., 2005, p. 96) Example
2: Randomized sequence (with restricted randomization). A single case randomised
experimental design with 12 phases was used. Each phase lasted for one week. During six
treatment phases, participants wore the equipment and received cues (contingency elec-
trical stimulation). During six no treatment phases, participants wore the equipment, but
no cues were received. The phases were administered in a random order but always starting
with a treatment phase, and no more than two consecutive phases were the same. (Wenman et
al., 2003, p. 449) Example 3: Randomized onset. The start of the treatment phase was
determined randomly for each participant, given the restriction that the baseline phase
should last for at least 6 weeks (42 days) and at most 12 weeks (84 days). This means that
the treatment phase could start on any day between the 42nd and the 84th days, resulting
in a total of 43 possible assignments. (ter Kuile et al., 2009, p. 151) Explanation. The
concept of randomization in SCEDs differs from its application in between-groups designs.
In between-groups designs, randomization exclusively refers to allocation of participants
to intervention groups (i.e., experimental vs. control). By contrast, in SCEDs, it refers
to (a) the random sequencing of baseline and inter- vention phases, (b) the random
determination of the commencement time for each phase, and (c) the combined randomization
of both phase order and phase starting point (Kratochwill & Levin, 2010). If more than one
participant is being studied in withdrawal/reversal designs, individuals can also be
randomly assigned to intervention conditions. In multiple-baseline designs, random
allocation of partic- ipants, behaviors or settings to each baseline of the design can
also be implemented. Ferron and Levin (2014) and Kratochwill and Levin (2010) provide
descriptions of these options. The sequencing of baseline and intervention phases in SCEDs
may be randomized using either simple (unrestricted) or blocked (restricted) randomization
strategies (hence, randomized order de-signs). The commencement point in time of each
phase may also be randomized using simple randomization (hence, randomized start point
designs). Randomization of both phase order and phase start point can also be combined in
any given design (Kratochwill & Levin, 2010). Random allocation in SCEDs provides control
of potential confounders related to time (Edgington, 1996; Kratochwill & Levin, 2010;
Onghena & Edgington, 2005) which addresses at least two potential sources of experimental
bias in SCEDs: history and maturation. Researchers can also use randomization to assign
specific stimulus items to different stimulus sets (e.g., treated and nontreated stimuli),
although this type of randomization does not control for experimental bias related to
history and maturation. When randomization is used, authors should provide a reason for
why it was used. They should also report specific details of (a) the basic randomization
strategy (i.e., simple or restricted) and (b) those aspects of the design that were
randomized (e.g., phase order, phase commencement, allocation of participants to
interventions, allocation of participants, behaviors or settings to baselines). Authors
need to describe any restrictions or modifications to the randomization pro- cess, which
may be necessary for clinical or ethical reasons. If randomization was not used, authors
need provide a reason why it was not used. They also need to report any decision criteria
used to determine phase sequencing (e.g., counterbalancing), time points for phase onset
(e.g., data driven), allocation of participants to interventions (if applicable), and/or
allocation of participants, behaviors or settings to tiers. If decision criteria are based
on participant-related reasons (e.g., clinical considerations, severity of behavior,
participant needs), these need to be reported. Item 9 —Blinding: State whether
blinding/masking was used, and if so, describe who was blinded/masked. Example 1: Blind
assessor. The PQS [Psychotherapy Process Q-Sort] raters were not involved in any other
aspect of the study procedures, and had no prior information regarding intended treatment
approaches, design, or hypotheses. The raters were blind to the session number, treatment,
and phase. Ratings of study tapes were made as part of PQS ratings of sessions from a
larger sample [ref], and therefore were not rated consecutively or in comparison to one
another. (Satir et al., 2011, p. 406) No suitable examples of blinding of participant or
practitioner in the SCED behavioral sciences literature were identified. Explanation.
Blinding (or masking) “refers to keeping trial participants, investigators (usually
healthcare providers), or assessors (those collecting outcome data) unaware of an assigned
intervention, so that they are not influenced by that knowledge” (Schulz & Grimes, 2002,
p. 696). Lack of blinding or inadequate blinding in RCTs can inflate estimates of
intervention effects by up to 17%, especially if trial outcomes involve subjective
measures (Wood et al., 2008). It is not unreasonable to expect that this also applies to
SCEDs. Blinding in SCEDs is reported very rarely, particularly for participants and
practitioners (Tate et al., 2013b). Blinding is difficult to achieve in nonpharmacological
trials involving surgery, psychological interventions or rehabilitation (Bang, Ni, &
Davis, 2004; Boutron, Tubach, Giraudeau, & Ravaud, 2004). Given that the majority of SCEDs
involve nonpharmacological interven- tions, this is a pertinent issue. Although difficult,
blinding of persons providing the intervention in nonpharmacological trials is not
insurmountable (e.g., e.g., Edinger, Wohlgemuth, Radtke, Marsh, & Quillian, 2001). Boutron
et al. (2007) provide a selection of strategies that can be used for blinding
participants. By contrast, blinding/masking of assessors is usually feasible. In reporting
SCEDs, if blinding was not implemented, authors should state the reasons. When blinding
was implemented, authors should clearly report who was blinded, and how the blinding was
achieved. Going beyond basic reporting standards, authors may wish to consider reporting
on procedures to assess the effectiveness of the blinding procedures and the outcome. Item
10 —Selection criteria: State the inclusion and exclusion criteria, if applicable, and the
method of recruitment. We advertised the project in community newsletters and notices sent
to local hospitals and rehabilitation professionals who typically worked with individuals
with brain injuries. In the advertisements, we stated the following inclusion criteria:
parents must have a documented brain injury, the children should be under the age of 10,
and they must be demonstrat- ing behavioral difficulties with the injured parent. Through
subsequent observation of the parent and child, we determined whether the child was
demonstrating a serious level of oppositionality with the parent (e.g., noncompliance to
more than approximately 50% of parent-delivered requests). (Ducharme, Davidson, &
Rushford, 2002, pp. 586–587) Explanation. Readers of SCEDs need to know as much as pos-
sible about the participant(s), within the boundaries of anonymity, because, until
generality has been demonstrated, results are only representative of the conditions under
which the investigation was conducted and for the individual/s who participated. In
situations where participants were actively recruited into the study, inclusion and
exclusion criteria should be provided. This in- formation will assist with the
identification of factors that may influ- ence a participant's response to the
intervention. It will also give an indication of the extent of the replicability and
generalizability of research findings (see also Item 11). The description of the selection
process should provide detail regarding who was recruited, and also the way in which the
participants were recruited (such as newspaper advertisements, online recruitment
targeting specific users, snowball- ing methods via other study participants or relevant
professionals, distribution of brochures and leaflets). Information should be provided
about the way in which selection criteria were applied (e.g., by use of diagnostic
instruments including questionnaires and interviews). Details of methods, instruments ad-
ministered, and classification or assessment criteria need to be clearly defined. Readers
need to be able to unambiguously identify how participant selection was accomplished for
successful replication of research (Horner et al., 2005). Method of recruitment may not be
applicable in SCEDs in those situations where an individual presents with an issue that
needs to be addressed. Such issues may be clinical (e.g., increasing a child's food
intake) or nonclinical (e.g., improving an athlete's perfor- mance). In these
circumstances, authors should instead state the reasons that the individual presented to
the service and the reason for the intervention. Item 11—Participant characteristics: For
each participant, de- scribe the demographic characteristics and clinical (or other)
features relevant to the research question, such that anonymity is ensured. Three
individuals with aphasia participated in the study. All had acquired aphasia secondary to
a left hemisphere stroke. See Table 1 for participant's demographic data. Based on test
performance and clinical judgment, all participants had nonfluent aphasia with good audi-
tory comprehension. All participants exhibited significant word retrieval difficulties.
Participants’ performances on the BNT [Boston Naming Test] were reviewed. P1's word
retrieval errors consisted of a mix of semantic (e.g., boat for canoe) and phonemic errors
(e.g., fesmask for mask). (Rider, Wright, Marshall, & Page, 2008, pp. 162–163)
Explanation. Inclusion of standard baseline participant characteristics, including
demographic information and functional status, ensures that the reader understands the
presentation of the participants and will be able to interpret the findings (Higginbotham
& Bedrosian, 1995). It is also important for generalization (Barlow et al., 2009) and
facilitates meta-analysis of multiple studies (Robey, Shultz, Crawford, & Sinner, 1999).
In spite of their relevance and importance, the systematic review of Maggin, et al. (2011)
found that participant characteristics were incompletely reported, even for very basic
demographic features such as sex (not reported in 33% of reports) and age (not reported in
42% of reports). The description of the participants of a study should include basic
demographic information such as age, sex, ethnicity, socioeconomic status, geographic
location, as well as diagnoses where indicated, and functional or developmental abilities
(Wolery & Ezell, 1993). Any diagnosis used should include instrumentation and scores.
Lane, Wolery, Reichow, and Rogers (2007)also recommend that baseline or environmental
factors which serve to influence or maintain the participant's behavior during the initial
baseline should be evaluated and reported. These features will go beyond simple
description of sociodemographic, medical and functional status variables. Authors need to
ensure that information provided does not lead to identification of the participant. This
is a particular risk in the treat- ment of rare conditions. It is also important to
protect an individual's privacy if the study involves stigmatized conditions. The
participant in a SCED typically, but not always, represents an individual person. The
participant, however, can also be a group whose performance generates a single score per
measurement period (such as the rate of a particular behavior performed by all students
within a classroom during a set period of time). In that situation they are generally
referred to as a “case” or “unit.” It is important that the authors opera- tionally define
what constitutes the group and provide criteria for its selection (see Item 10). Authors
need to specify the baseline character- istics (to the same level of detail) for each
participant (Wolery & Ezell, 1993) to allow the reader to ascertain the extent to which
the results are generalizable (see also Item 24). Item 12—Setting: Describe
characteristics of the setting and location where the study was conducted. The children
and teacher comprised the full membership of a third grade general education classroom in
a rural postindustrial Northeast elemen- tary school. All observations were conducted in
their homeroom class during the SSR [sustained silent reading] period. During SSR,
students sat at their desks, which were arranged in two rows of desks facing toward the
teacher in the front of the room. (Methe & Hintze, 2003, p. 618) Explanation. It is
critical to report the setting and location of the study because these factors have
implications for the generalizability and applicability of the findings (see Item 24). The
context of the intervention will vary according to whether it is provided in primary,
secondary or tertiary health care, classroom/educational facility or community settings.
The location of the study will also vary according to whether the intervention is offered
in urban, rural or remote locations, and this will have an impact on the service delivery
model. The setting is of particular interest for the reporting of SCEDs for two reasons.
First, it may be an inherent a priori feature of the design to introduce the independent
variable across a range of settings in a con-trolled manner. Multiple-baseline designs
across settings are a case in point. Second, the detailed description of the relevant
location and setting is central to the replicability of the study (see also Item 7). An
indepen- dent researcher may be interested in varying the location of the study as one
step toward systematic replication. In this scenario, a sufficiently detailed description
of the setting is requisite information. Authors need to provide detailed information on
the location of the study, including the number and type of settings, as well the
practitioners or providers involved. There should be sufficient detail regarding the
location and setting of an intervention to enable others to evaluate how different this is
from their own situation. Item 13—Ethics: State whether ethics approval was obtained and
indicate if and how informed consent and/or assent were obtained. Approval for this
research study was obtained from the human subjects research Internal Review Board at
participating institutions. If a woman was interested, she was given a pamphlet with
information about the intervention and proposed research project before leaving the
hospital, or at a follow-up appointment. Women then contacted the primary inves- tigator
(SMB) for more information and/or to schedule an initial assess- ment appointment. An
informed consent form was read, discussed and signed before beginning the initial
assessment and a copy of this consent form was given to the participant for their records.
(Bennett, Ehrenreich-May, Litz, Boisseau, & Barlow, 2012, p. 166) Explanation. It is
virtually a universal requirement that research involving human participants requires
review by and approval from an Institutional Ethics Committee. If the SCED was implemented
as part of clinical care, ethics approval might not be required, as is the case in N-of-1
trials (Punja, Eslick, Duan, Vohra, & the DEcIDE Methods Center N-of-1 Guidance Panel,
2014). Reporting whether ethics ap- proval has been obtained is not, however, a feature of
all research reporting guidelines. For example, the CONSORT Statement (Moher et al.,
2010a) does not include this as a checklist item. Following the CENT 2015 guidelines
(Shamseer et al., 2015; Vohra et al., 2015), the SCRIBE 2016 also includes the reporting
of ethical approval as a checklist item for reporting SCEDs. Written informed consent
should always be secured (Mechling & Gast, 2010). There may be instances when the
participant cannot provide informed consent (e.g., if the participant is a minor or
otherwise legally unable to provide informed consent). In this situation, their assent to
participate should be sought, and consent also obtained from legal guardians or parents.
It is not sufficient to merely state informed consent/assent was obtained. Rather, the
process by which consent/assent occurred needs to be described so that it is clear who
provided informed consent/assent. This is particularly important with vulnerable
populations or where lim- ited disclosure is necessary (National Health and Medical
Research Council, 2009). Item 14 —Measures: Operationally define all target behav- iors
and outcome measures, describe reliability and validity, state how they were selected, and
how and when they were measured. Example 1: Operational definition of the target behaviors
and how they were measured. Topographies of targeted behaviors for Bob included self-
injury. Self-injury consisted of face slapping, defined as a forceful contact between an
open palm and cheek. Bob also displayed spitting, defined as spittle landing within 1 foot
of another person. The primary dependent variable was the percent of intervals in which
maladaptive behaviors were observed during each 10-min session. Data were collected using
paper and pencil during consecutive 10-s intervals cued by an audio tape throughout the
entire session, resulting in a total of 60 consecutive intervals. Partial interval
recording was used: during each interval observers recorded whether or not any of the
target maladaptive behaviors had been observed for any portion of the interval. Observers
underwent training in behavioral observation. and dem- onstrated mastery prior to
participating in the study. (Treadwell & Page, 1996, pp. 65–66) Example 2: Reliability of
dependent variables when using non- standardized measures. Three different categories of
interobserver agreement were calculated, as follows. Parent-therapist agreement: This
category involved agreement between compliance data coded by the parent and those coded
live by the research therapist. In this category, interobserver agreement was obtained on
39% of sessions conducted by parents, randomly selected from each of the phases across all
children. Overall agreement averaged 92% for baseline (range 82%–100%) and 98% for
treatment, generalization, and follow-up sessions (range 94%–100%). (Ducharme et al.,
2002, p. 588) Explanation. A single item in the SCRIBE 2016 covers all as- pects of the
dependent variable/s: the what, how, and when of mea- suring the effect of the
intervention. As with other research designs, the measurement process in SCEDs also needs
to be valid and reliable. Validity is enhanced by selecting dependent variables that are
(a) relevant to the behavior in question and that best match the interven- tion, as well
as (b) accurate in their measurement, which is facilitated when the behavior that is
targeted for intervention is operationally defined. Reliability is enhanced when the
behavior is measured in a manner that yields consistent results. What is measured? SCEDs
commonly use a variety of dependent variables that play specific roles in the experiment.
The primary outcome variable in SCED methodology is referred to as the target behavior.
Target behaviors have three defining features in order to enhance quality of the study and
minimize bias: they are specific, observable and repli- cable (Barlow et al., 2009). Other
dependent variables frequently used in SCEDs may be considered akin to secondary outcome
variables: Gener- alization measures are increasingly recognized for their important role
in contributing to the external validity of the study (see also Item 24). In addition,
SCEDs have a strong tradition in promoting experiments that address socially relevant
behaviors and interventions. Additional mea- sures are often incorporated into a SCED to
specifically measure social and ecological validity. Authors need to provide operational
definitions of the target be- havior, which should be objective, clear and complete
(Kazdin, 2011), in order to convey what does and does not constitute an instance of the
dependent variable. In studies where there is more than one target behavior, the report
should clearly identify and describe each of the target behaviors in detail. Other
dependent variables used in the study (e.g., generalization measures, social validity
measures) should also be described with equal clarity and precision. How is it measured?
The “how” of measurement covers measure- ment procedures, including who selected and
measured the target behaviors and other outcome variables, along with their training in
the assessment procedures. Authors also need to provide information on the way in which
the dependent variables were measured, justification for the selection of those measures,
and detail regarding what consti- tutes a correct or incorrect response. Because the
target behaviors are highly specific to the presenting case in SCEDs, formal psychometric
evaluation of the measures will generally not have been established. It is therefore
recommended practice that evaluation of interobserver agreement on the target behavior is
conducted and reported. When standardized instruments are used, it is essential that
psychometric details regarding reliability, validity and responsiveness of the instruments
are reported. Any equipment used to measure the dependent variable/s should also have
established measurement properties, which, if available, should be provided in the report.
When is it measured? A distinctive feature of SCEDs, in contrast to group methodology, is
that the target behavior (primary outcome variable) is measured repeatedly and frequently
throughout all phases, including the baseline and intervention phases. Smith (2012, p.
519) observes that “the baseline measurement represents one of the most crucial design
elements of the SCED.” In spite of this, baseline data were not available for 22% of SCEDs
in Smith's systematic review. Moreover, in other phases of the study, the number of data
points could not be readily identified. Target behavior/s need to be selected so that they
are suitable for repeated and frequent measurement. Previously, the recommended minimum
number of data points per phase was three (Barlow & Hersen, 1984; Beeson & Robey, 2006),
but more recently professional guidelines recommend a minimum of five data points per
phase (Horner et al., 2005; Kratochwill et al., 2010, 2013). There should be a clear
description of the number of sessions in which the target behavior is measured in each
phase, as well as the number of times it is measured in each session (i.e., number of
trials per session). Frequency of measurement of other out- come variables depends on
their role. Recommended practice is that generalization measures are probed continuously
throughout all phases (Schlosser & Braun, 1994). By contrast, evaluation of social
validity can only logically occur after the intervention has taken place. As with target
behaviors, authors should clearly state the frequency and regularity of measurement of all
other outcome measures, including phases during which such measures were taken. Item
15—Equipment: Clearly describe any equipment and/or materials (e.g., technological aids,
biofeedback, computer pro- grams, intervention manuals or other material resources) used
to measure target behavior/s and other outcome/s or deliver the interventions. Training in
use of email interface: “Participants 1–4 used a mouse connected via USB port to activate
the e-mail program. Participant 5 used a trackball instead of a mouse to accommodate his
motor impairment. The instructor used a number pad. to control presentation. The program
was run on. a laptop. An altered interface was also developed to assess generalization to
a slightly differ- ent platform. It included additional buttons. as well as rearrangement
of existing buttons to novel positions.” (Ehlhardt, Sohlberg, Glang & Albin, 2005, p. 571;
p. 576) Photo Cue Cards [ref] were used as instructional stimuli. Four target photographs
and four control photographs were selected for each child. Target stimuli are presented by
child and instructional condition in Table 2. A stopwatch was used to time the length of
experimental sessions. (Holcombe, Wolery, & Snyder, 1994, p. 53) Explanation. Target
behaviors may be measured using behav- ioral observations and standardized scales (see
Item 14) or, alterna- tively, equipment. Similarly, many interventions used in the behav-
ioral sciences are accompanied by materials and equipment. Complete and accurate reporting
of equipment and materials is central to the issues of replicability (see Item 7) and
generalizability (see Item 24). A detailed description of the independent variable (i.e.,
the intervention) will include not only a description of the elements of the intervention
(see Item 16), but also any specific equipment used, along with the way in which the
equipment operates. Such equipment will include training manuals, computer programs, bio-
feedback techniques or any other materials required to implement the intervention. When
equipment is used to measure the dependent variable, the way in which it operates needs to
be described, as well as its calibra- tion. In addition, its measurement properties, if
available, should be reported (see Item 14). Item 16 —Intervention: Describe the
intervention and control condition in each phase, including how and when they were
actually administered, with as much detail as possible to facilitate attempts at
replication. Check-in sessions were scheduled once a week during baseline to collect
paperwork, monitor participant functioning, and to serve as an active waitlist control
condition. Following the baseline period, women entered the inter- vention phase, which
consisted of eight weekly sessions lasting approxi- mately 60 min. The therapist was the
lead investigator of this study (SMB) who was a senior graduate student at the time of
data collection. Women were told they could opt to include their partners in treatment
sessions if they wished. (Bennett et al., 2012, p. 166) This description is accompanied by
a detailed table (p. 165) de- scribing the session, primary goal of each session, and
brief description of session content and homework. Explanation. Evidence of inadequate
description of the intervention abounds in the broader health-intervention research
literature using group methodology (e.g., Boutron et al., 2008; Dijkers et al., 2002;
Glasziou, Meats, Heneghan, & Shepperd, 2008). The importance of describing the independent
variable itself in sufficient detail to allow replication has been emphasized in the
general SCED literature. The independent variable needs to be operationally defined,
similar to the descriptions of the target behavior/s and the outcome measures (see Item
14). In situations where more than one intervention is used (e.g., A-B-A-C-A-D, or
alternating-treatments design) each intervention should be described. In addition to
ancillary aspects of the intervention (i.e., materials, manuals, stimulus items,
equipment, software programs or applications; see Item 15), the nature of the intervention
per se needs to be clearly specified. This description includes information on who
delivered the intervention and in which mode, whether it be individual, group, distance,
carer- or educator-focused, or whether telehealth or other technologies were used. It is
critical to report the exact number, duration and frequency of the intervention sessions
(Baker, 2012; Warren, Fey, & Yoder, 2007). Specifically, intervention intensity or dosage
should be described in terms of the following: (a) dose form (i.e., the typical task or
activity being used), (b) the dose (i.e., the number of times an active ingredient or
teaching episode occurs per session), (c) the dose frequency (i.e., the number of
intervention sessions per unit of time), (d) the total intervention duration (i.e., the
total period of time in which an intervention is provided), and (e) the cumulative
intervention intensity (i.e., the product of dose by dose frequency by total intervention
duration; Warren et al., 2007). SCEDs typically compare the effect of an independent
variable with either a control condition or another independent variable (i.e., another
intervention). The control condition, often called the baseline condition in SCEDs,
represents a period of time when the participant's target behavior is recorded repeatedly
before the intervention is introduced. The same degree of specificity that is used to
describe the experimental intervention should also be used for the control condition. Item
17—Procedural fidelity: Describe how procedural fidelity was evaluated in each phase.
Adherence to treatment procedures was accomplished by use of a manual that described the
steps of the programme. In addition, an independent, trained observer watched videotapes
of one training session from each step of the training programme (25% of sessions), and
tallied the opportunities for the experimenter behaviours and the number of times the
experimenter used the expected behaviour (e.g., prompts, models, reinforcement). Adherence
to the protocol was calculated using the formula (EA × 100)/ET, where EA = the
experimenter behaviours. Procedural reliability was 95% to 100% for each step. (Hickey,
Bourgeois, & Olswang, 2004, p. 630) Explanation. Wolery (1994) describes the collection of
proce- dural fidelity data as having three main functions: (a) to monitor the occurrence
of relevant variables, (b) to provide documentation that the experimental conditions
occurred as planned, and (c) to provide information to practitioners about the use of the
interventions. In spite of the seriousness of unreliable implementation of the
experimental conditions, fidelity checks in SCEDs in the behavioral sciences are
infrequent (27% in the series of Didden et al., 2006). This result is comparable to the
data on reporting quantitative measurement of the independent variable in three reviews of
the contents of Journal of Applied Behavior Analysis (Hagermoser Sanetti & Kratochwill,
2007). In recognition of the critical importance of the fidelity of the imple- mentation
of study protocols, an item addressing adherence to the pro- tocol was introduced for the
CONSORT Extension to Nonpharmacologi- cal Treatments (Boutron et al., 2008). Application
of a prepared checklist or steps of a protocol is the best way to document procedural
fidelity (see Borrelli et al., 2005; Dane & Schneider, 1998; Gast, 2010b, pp. 99–101).
Steps taken to evaluate procedural fidelity should be reported by authors, including how
it was measured and the results of its assessment. If procedural fidelity is evaluated
during the course of the study, and found to be suboptimal, authors may consider going
beyond basic reporting standards to describe whether and what steps were taken to improve
procedural fidelity (Hagermoser Sanetti & Kratochwill, 2014). Item 18 —Analysis: Describe
and justify all methods used to analyze data. Example 1: Use of visual analysis. The
split-middle technique [ref] was employed to detect changes in the number of successful
shots within phases and resultant trend lines (Barlow & Hersen, 1984). White proposed that
level, slope, and mean score of the celeration line (or trend) line be assessed as three
descriptive analyses for conclusions. Given that a point on the celeration line does not
actually explain the performance level, for brevity we have chosen to concentrate on the
slope of the celeration line. (Mesagno, Marchant, & Morris, 2009, p. 136) Example 2: Use
of statistical analysis. As serial dependence. can bias the visual inspection,17 we
checked our data in each phase for serial dependence using the lag-1 method.12 If data
were found to be significantly correlated, we transformed the data using a moving average
transformation, in which the preceding and succeeding measurements were taken into
account.12,16 In addi- tion, randomisation tests for multiple-baseline single-case designs
were carried out. We expected phases B and A9 to be superior to phase A in terms of our
health outcome assessment. Therefore, we tested the null hypothesis that there would be no
differential effect for any of the measurement times using a randomisation test of the
differences in the means between the preintervention phase and the intervention or
postintervention phase.17 A p value of <0.05 was considered statisti- cally significant.
For the premeasurements and postmeasurements, we considered change scores of 20% on
validated questionnaires as clin- ically relevant.32 We used Stata/IC 10.1 for Windows for
the descrip- tive and visual analysis of the data and R version 2.14.1 for the
randomisation tests.31 (Hoogeboom et al., 2012) Explanation. Both visual and statistical
techniques can be used to analyze SCED data (see Appendix). They are considered
complementary rather than mutually exclusive (Maggin & Odom, 2014; Parker & Brossart,
2003; White, Rusch, Kazdin, & Hartmann, 1989) and should, arguably, be used in combination
(Davis et al., 2013; Smith, 2012). Visual analysis relies upon visual inspection of the
graphed data to draw conclusions regarding the reliability and consistency of intervention
effects (Lane & Gast, 2014). In the past, experts have argued that visual analysis is the
most sensitive and appropriate way to detect intervention effects in SCEDs (e.g.,
Parsonson & Baer, 1986). It has been the traditionally preferred and most frequently used
approach (Busk & Marascuilo, 1992), but has significant limitations (for discussion, see
Lane & Gast, 2014; Smith, 2012). Authorities have proposed guidelines for systematiz- ing
visual analysis (e.g., Kratochwill et al., 2010; Lane & Gast, 2014), but there is not yet
complete agreement about decision- making criteria to guide the process. Statistical
analyses have advantages in that they (a) use an explicit set of operational rules and
replicable methods, (b) provide a direct test of the null hypothesis, (c) utilize
precisely defined criteria for significance, (d) are useful when there is instability in
the baseline or treatment effects are not well understood, and (e) can help to control for
extraneous factors (e.g., Kazdin, 1982a, 1982b). There is no “universal gold-standard,”
however, and authors should choose the analytic method for SCEDs that is guided by a
number of considerations: (a) design requirements and data assumptions, (b) the research
question being posed, (c) features of the data being analyzed, and (d) the
interpretability, ease of computation and proven validity of the technique for analysis of
SCED data. For detailed discussion of these issues, see Manolov, Gast, Perdices, and Evans
(2014) and Shadish (2014). If statistical analyses are used, authors need to report
whether underlying assumptions and other requirements pertinent to the technique were
evaluated for the data set being analyzed. This informa- tion will allow the reader to
determine the suitability of the analytic methods used. It is critically important that
authors fully and clearly describe the method/s of analysis used, regardless of whether
they select visual, statistical or both techniques. Authors should state if the method/s
of analysis was prespecified before commencement of data collection, and those changes (if
any) that were subsequently made as a consequence of limiting/problematic features of the
data. The rationale for selecting the analytic technique in terms of its appropriateness
to the study design and the research question should be clearly stated, and the source
reference describing the technique should be cited. In the case of visual analysis, it is
important to clearly report the features of the data that were selected for analysis
(along with reasons) and whether a systematic protocol was used and, if so, which one.

SECTION 4: RESULTS—SEQUENCE COMPLETED, OUTCOMES AND ESTIMATION, ADVERSE EVENTS (ITEMS 19–21)
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Item 19 —Sequence completed: For each participant, report the sequence actually completed,
including the number of trials for each session for each case. For participant/s who did
not complete, state when they stopped and the reasons. Example: Deviation from protocol:
Interruption of treatment. Ms. O had 24 sessions of psychotherapy over a one hundred and
47 day period, which included two periods of treatment interruption; once in the middle of
the BCT [Behavior Change Treatment] phase, and once at the end of the BCT phase. Ms. O was
randomly assigned to receive AFT [Alliance Focused Treatment] for the first 4-week therapy
phase, BCT for the second 4-week therapy phase, and AFT for the last 4-week therapy phase.
The two treatment interruptions coincided with the Thanksgiving and Christmas hol- idays,
and occurred during BCT only. (Satir et al., 2011, p. 406) Explanation. A major benefit of
SCEDs lies in their flexibility. As described in Item 6, it is possible during the conduct
of the investigation to change and fine-tune procedures and interventions that do not
appear to be working. Any such deviation from the original plan of the study, however,
needs to be clearly reported (see also Item 25). The present item pertains specifically to
the report of procedural variations that reflect changes in any of phase sequence, phase
order, and/or number of sessions actually com- pleted by each participant. Changes to
phase sequence may occur in response to clinical or ethical concerns, such as subsequently
deciding to commence the investigation with a treatment phase rather than the
predetermined randomized sequence. For similar reasons, a phase might be pre- maturely
terminated, interrupted, extended, or substituted for rea- sons of lack of efficacy,
harms, periods of absence, and so forth. Post hoc changes to the randomization schedule or
the intended duration or structure of phases can significantly weaken the inter- nal
validity of the study and therefore need to be reported. Missing data due to attrition may
bias the results, especially if this reflects intentional or systematic noncompliance
(Smith, 2012). Moreover, if participants do not complete all phases as planned, there may
also be insufficient phase repetitions to dem- onstrate adequate experimental control.
Attrition of participants within units (such as classrooms) over time may confound inter-
vention effects especially if attrition is nonrandom and associated with the intervention
itself. In order to minimize such bias, Horner et al. (2005) argue that, regardless of
attrition or missing data, results of any participant for whom there is data for both a
baseline and an intervention phase should be reported. If techniques for dealing with
missing data are used (e.g., retrospective data completion, such as completing dia- ries),
this also needs to be reported, given that such techniques can introduce significant bias
in the data due to incorrect recollection/recall (Bolger, Davis, & Rafaeli, 2003).
Accordingly, any changes to the sequencing of phases or missing data should be reported,
along with their reasons so that the reader can evaluate the integrity of the results and
their interpretation. Item 20 —Outcomes and estimation: For each participant, re- port
results, including raw data, for each target behavior and other outcome/s. Example 1:
Provide raw data (Fig. 2). Example 2: Statistical analysis. The three measures of
treatment gains are shown in Table 2. Four patients. demonstrated significant treatment
gains as determined by all three measures (C statistic, effect size, modified CDC
[conservative dual criteria]). One patient. did not demonstrate significant gains on any
measure. The patients who improved made variable gains in other areas as indicated by a
significant increase in their WAB [Western Aphasia Battery] AQs [Aphasia Quotient] (mean
increase = 5.58, SD = 2.32, t = 4.81, df = 3, p < .05). (Crosson et al., 2009)
Explanation. Traditionally, SCED results are reported in graphical form which is,
arguably, the clearest and most unambig- uous way of depicting the major features of the
raw data. At minimum, SCED data for each session should be reported in graphic form. This
does not preclude the additional reporting of raw data for each session (or for each trial
within a session) for each phase of the study in a tabulated format. Although tabular
presentation is acceptable (and even desirable for verification in meta-analysis),
relevant features (e.g., consistency across similar phases) may not be directly obvious in
this format. Alternatively, authors may provide information about where the raw numerical
data set can be accessed. Raw data should be reported in the results section for each
measurement point/session in each phase of the study for each participant, setting and
target behavior/s. Even though aggregation of data (e.g., averaging results over several
sessions), may provide a clearer view of the apparent intervention effect, it may also
mask or misrepresent various important features. Such features may include (a) stability
of the initial baseline phase, variability and trends within a phase, (c) degree of
consistency between similar phases (e.g., intervention phases), (d) the degree of overlap
between baseline and intervention phases, (e) magnitude of effect latency following
intervention phase onset. Readers need to be able to critically evaluate all these aspects
of the data. They also need to be able to draw their own conclusions about how adequately
the investigators have taken any anomalies into account when appraising the clinical value
of the intervention (Barlow et al., 2009). The metric used on the horizontal axis of
graphed data should be in units of real time (i.e., days, weeks, etc.) rather than session
number. This information allows the reader to more clearly inter- pret and critically
evaluate the results of the study. Providing an exact chronology of the time interval
between sessions allows the reader to accurately evaluate patterns of consistency between
sim- ilar phases and effect latency following intervention onset. Carr (2005) argues that
using a real-time metric on the horizontal axis is particularly relevant in multiple-
baseline designs. The reason is so that the reader can determine the order in which
sessions across participants, settings or behaviors were conducted relative to each other.
More importantly, it also allows the reader to see how many sessions occurred in the
initial A-phase of the second baseline (or third, fourth, etc.) of the design after the
intervention was intro- duced in the first baseline. Results of any statistical analyses
for the target behavior/s and other relevant outcome variables also need to be reported.
This report should be done for each participant and setting in the study. Irrespective of
the analysis used, authors need to clearly state which phases and features of the data
were compared. Any changes or deviations in a preplanned analysis strategy should also be
reported, as well as the reasons that it was necessary to make such changes. For
statistical analyses, the value of the calculated sta- tistic/s, standard errors, and any
associated probability level should also be reported. Item 21—Adverse events: State
whether or not any adverse events occurred for any participant and the phase in which they
occurred. The current reporting of adverse events is rare in SCEDs where behavioral
interventions have been applied. Only a single example (Hoogeboom et al., 2012) was
identified where authors mentioned that adverse events were monitored, but no information
was provided on the way in which adverse effects were measured, nor were results provided.
Explanation. The reporting of adverse events or harms is rare in SCEDs of behavioral
interventions. Their report is a more common feature in medical interventions in
randomized and non-randomized trials and observational studies (Golder, Loke, & Bland,
2011), even though it is often inadequate (Papanikolaou, Christidi, & Ioannidis, 2006;
Vandenbroucke, 2006). This problem is despite the reporting of harms being a specific
checklist item in the CONSORT 2010 Statement (Schulz, Altman, & Moher, 2010). Although
there are no clear definitions of harms, the CONSORT Extension for Better Reporting of
Harms in RCTs (Ioannidis et al., 2004) has recommended harms as the preferred term to
describe an adverse event (as opposed to describing the “safety” of a treat- ment).
Particular recommendations include that (a) authors make specific mention of harm in the
title or abstract, as well as the introduction where harms are a primary outcome measure;
and (b) there is specification of the harms in reporting of results, with special
attention paid to discontinuations and withdrawals due to adverse events. The guideline
also recommends that authors should present the absolute risk of each adverse event
(specifying type, grade, and seriousness per arm of the trial), (b) describe any subgroup
analysis and exploratory analysis for harms, and (c) provide a balanced discussion of
benefits and harms with emphasis on study limitations, generalizability and other sources
of infor- mation on harms (Ioannidis et al., 2004). The guide can be adapted to
accommodate SCED methodology. The SCRIBE 2016 recommends that authors make full and
explicit disclosure of any harms or adverse events that occurred to any participant during
the course of the SCED trial, including the absence of these events. Loke, Price,
Herxheimer, & the Cochrane Adverse Effects Methods Group (2007) suggest a framework to
enable a systematic, manageable and clinically useful way to define adverse effects. It
includes a predefined classification of adverse effects as diagnosed by the clinician, by
test results, or by participant- reported symptoms (e.g., pain).

SECTION 5: DISCUSSION—INTERPRETATION, LIMITATIONS, APPLICA- BILITY (ITEMS 22–24)
--------------------------------------------------------------------------------

Item 22—Interpretation: Summarize findings and interpret the results in the context of
current evidence. Results showed that the repeated reading program combining several
research-based components. improved fluency on second-grade trans- fer passages for the
three participants lending support to the existing literature on repeated reading [ref].
With research on repeated reading spanning decades and numerous studies demonstrating
successful out- comes. this practice holds great promise as a strategy for improving
reading fluency. However, as suggested by [the metaanalysis of] Chard and al. (2009), the
current research literature on repeated reading is not sufficient for it to be designated
as an evidence-based practice. (Lo, Cooke, & Starling, 2011, pp. 133, 136) Explanation. An
early section of the discussion needs to provide a clear and concise summary of the
findings of the study, including the strength of the intervention effect and the clinical
importance of the findings. The results should be interpreted in terms that are specific
to the study, as well as more generally with reference to the current literature.
Interpretation specific to the study will benefit from taking into account the aims of the
study, along with the robustness of methodology and procedures. Item 23 on limitations of
the study is a separate item in the SCRIBE 2016 Statement, but has obvious rele- vance to
the item on interpretation. Vandenbroucke et al. (2007) note that overinterpretation is a
common problem in observational studies. For the STROBE Statement, they advocate that
caution is exercised in interpreting the findings of a study. A cautious approach to
interpretation is particularly pertinent to SCEDs in instances where findings are unclear
or adequate replication has not occurred (see Item 7). In terms of interpreting the study
findings in the context of the current evidence from the literature, the CONSORT Statement
(Schulz et al., 2010) suggests that results of clinical trials are inter- preted with
respect to the knowledge base, as synthesized in system- atic reviews. In some research
areas using SCEDs, meta-analyses are available and it is recommended that information from
these be incorporated when available (as in the above example of Lo, Cooke, & Starling,
2011, referring to the meta-analysis of Chard, Ketterlin-Geller, Baker, Doabler, &
Apichatabutra, 2009). Item 23—Limitations: Discuss limitations, addressing sources of
potential bias and imprecision. The validity of comparisons between AFT [Alliance Focused
Treatment] and BCT [Behavioral Change Treatment] was compromised by several factors,
including the significant intervention interruptions during BCT, the administration of
psychotropic medication during the study. Furthermore, there may have been significant
carry-over effects from one phase to another, as skills learned during one phase could not
be “un- learned”. Limitations to measurement include possible limitation to the accuracy
of the self-report nature of the kilocalorie intake, which was not verified by other
sources of data collection (e.g., independent observa- tion). (Satir et al., 2011, p. 417)
Explanation. It is often tempting for authors to focus on the positive findings of their
results and to glide over the flaws in their study. However, all studies have limitations
that can either bias or confound results. Important limitations reflect threats to the
validity of the study that introduce potential bias in the findings. There are many
potential limitations in SCED studies that compro- mise the extent to which results are
unbiased, reliable and likely to generalize (e.g., see Horner et al., 2005; Tate et al.,
2013b; Wolery, Dunlap & Ledford, 2011). These limitations include the following: (a) poor
matching of the design to the type of intervention (see Item 5); inadequate replication
(see Items 7 and 24); (c) absence of blind- ing (see Item 9); (d) lack of randomization
(see Item 8); (e) impreci- sion with respect to the description of the participant's
functional abilities (and, where applicable, diagnosis), making it difficult for readers
to generalize to other cases (see Items 10 and 11); (f) problems with the operational
definition of the target behavior or assessment of its reliability, insufficient number of
data points in some or all of the phases to meet minimum standards (see Item 14); (g)
absence of information regarding procedural fidelity (see Item 17); and (h) reli- ance on
visual analysis for ambiguous cases, insufficient number of data points required for
specific statistical analyses (e.g., the C sta- tistic requires at least eight data points
per phase), use of statistical procedures that do not deal adequately with extant features
of the data (e.g., trend, variability or auto-correlation), or whose underlying as-
sumptions are not met (see Item 18). In terms of adequate reporting, authors need to
provide a systematic discussion of specific limitations associated with their findings (as
de- scribed above) which is also contextualized within the relevant literature. In this
way the reader is provided with a realistic, critical appraisal of the contribution that
the study makes to the field and the extent to which the results reflect a strong finding
that is likely to be repeated. Item 24 —Applicability: Discuss applicability and
implications of the study findings. The results of the present study replicate the
findings of [ref] with regard to the effect of using DRA [differential reinforcement of
alternative behavior], nonremoval of the fork, and stimulus fading to increase variety of
food intake. The study extends previous findings by showing that the intervention package
was effective independent of who fed the child. The effect of our treatment on John's
consumption of nonpreferred foods did not generalize across settings in the absence of
intervention in the home, but multisetting training led to transfer across settings and
caregivers. Our study also shows that the treatment package described by [ref] was
effective during typically occurring mealtimes with regularly scheduled food types, and
that the treatment was effective for increasing the number and variety of originally
nonpreferred foods. (Valdimarsdóttir, Halldorsdottir, & SigurÐardóttir, 2010, p. 105)
Explanation. The concept of applicability or generality is based on the assumption that
inferences can be drawn from the condition in which an intervention effect was
demonstrated, to other conditions based on known similarities and differences be- tween
these conditions (Gast, 2010a). The reader should be provided with a discussion of
implications of (a) conceptual/theoretical considerations, (b) clinical/practical consid-
erations, and (c) methodological considerations, which impact on the generalizability of
the findings. Conclusions could be drawn, for example, from information provided about
replication (Item 7), inclu- sion and exclusion criteria (Item 10), participant
characteristics (Item 11), and generalization measures (Item 14). The replication process
(see also Item 7) involves an increasing number of variations to the different dimensions
(most importantly participants, setting and practitioner) that can be changed with every
replication (Barlow et al., 2009; Sidman, 1960). Each replication will add information
regarding the generalizability of the findings. The stage of the replication process
(direct or systematic; see, e.g., Gast, 2010a) should be made clear. Similarities and
differences between the current and previous studies need to be explicated. Reference
should be made to factors that determined baseline performance, such as described in Items
10 and 11, because these factors are hypothesized to influence relations between the
indepen- dent variable and the dependent variable in a very specific way (Horner et al.,
2005; Wolery et al., 2011). If outcome measures additional to the target behavior (Item
14) are used for the purpose of generalization, authors should discuss the evidence to
support (or not) a functional relationship between the independent variable and the gener-
alization variable in the context of a theoretical framework, if available. If responses
to the intervention differed across participants (or between studies), reasons and
proposed causal relationships of this finding should be discussed and new propositions
made to explain the finding.

<h>SECTION 6: DOCUMENTATION—PROTOCOL, FUNDING (ITEMS 25–26)</h>
--------------------------------------------------------

Item 25—Protocol: If available, state where a study protocol can be accessed. No published
SCED studies were identified that contained information on how to access a protocol. A
number of published reports indicated that the research protocol of a SCED was reviewed by
an institutional research committee, but this pertains to Item 13. Several SCED protocols
were identified in trial registries (Lloyd at www.anzctr.org.au, Trial ID
ACTRN12611000812998; Pool at www.anzctr.org.au, Trial ID ACTRN12611000531910; Wambaugh,
Mauszycki, Cameron, Wright, & Nessler, 2013; Wambaugh, Nessler, & Wright, 2013, at
www.clinicaltrials.gov) but personal communication with the authors indicated that the
studies were not yet published (Lloyd & Sherrington, 2011) or the published report did not
make reference to the protocol (Pool, Blackmore, Bear, & Valentine, 2014; Wambaugh et al.,
2013a, b). Explanation. Trial protocol availability was a new item introduced for the
CONSORT 2010 Statement (Schulz et al., 2010) and is also included in the CENT 2015
Statement (Shamseer et al., 2015; Vohra et al., 2015). Moher et al. 2010a, p. 21 indicate
that the protocol refers to the planned methods of the “complete trial (rather than a
protocol of a specific procedure within a trial).” The rationale for including the
protocol item in the CONSORT 2010 Statement was based on published evidence of the
discrepancy between the trial protocol and the subsequent published report (e.g.,
selective reporting of results, post hoc change in the main outcome measure). Such
discrepancies continue to be documented (Dwan et al., 2011). Having a protocol readily
accessible makes authors accountable for any changes that are made to the planned research
design and analysis. As noted, however, a special feature of SCED methodology is its
flexibility in terms of modifying the design and/or intervention after the trial has
commenced (e.g., if the participant does not respond to intervention or specific research
problems arise). These modifications do not necessarily compromise the experiment (Connell
& Thompson, 1986; Gravetter & Forzano, 2009). As a consequence, in a SCED the design
and/or intervention actually received may depart from an a priori protocol. Such departure
is considered acceptable within SCED methodology, as long as the authors declare such
departure and provide justification for it (see Item 6). Nonetheless, the flexibility to
modify the design and intervention in SCEDs does not imply that an a priori protocol is
not relevant. The SPIRIT 2013 Statement (Standard Protocol Items: Recommen- dations for
Interventional Trials; Chan et al., 2013) provides guidance for the report of protocols of
clinical trials and can be used as a guide for preparing a protocol on a SCED study. As
noted in the CONSORT 2010 Explanation and Elaboration document (Moher et al., 2010a),
there are many ways in which a protocol can be made available, including trial registries,
journals that publish protocols, website of the journal publishing the main results of the
study, author's institu- tional website, contact with the author. Reference to the study
proto- col can be made either in the text or as a footnote. Item 26 —Funding: Identify
source/s of funding and other sup- port; describe the role of funders. The study was
financed by the Sint Maartenskliniek Nijmegen and Woerden, the Netherlands. All authors
declare: no support from any organisation for the submitted work, no financial
relationships with any organisations that might have an interest in the submitted work in
the previous 3 years and no other relationships or activities that could appear to have
influenced the submitted work. (Hoogeboom et al., 2012, p. 8) Explanation. Journals often
request that authors disclose funding sources. It is important that readers of the
manuscript can make a judgment as to whether the funders have control over knowledge
dissemination or whether they provided funds but the researchers worked independently and
autonomously. A consistently and overwhelmingly strong association between industry
support and proindustry findings in group clinical trials has been demonstrated (Sismondo,
2008a, 2008b). The likelihood of finding a positive result when backed by industry funding
has been estimated in the range of 3.6 to 4.05 times greater than when not (Bekelman, Li,
& Gross, 2003; Lexchin, Bero, Djulbegovic, & Clark, 2003). Although methodological quality
is not necessarily compromised in industry-funded research (Sismondo, 2008a), bias may
infiltrate in other ways such as the decision to use less active controls (Bekelman et
al., 2003). Provision of a grant number can be helpful because it enables readers to
retrieve the details of the grant. Otherwise, one needs to know the following: Did the
funder provide equipment or money? Did the funder have control over where the study was
published or what was published? Were the funders the authors, or did they edit the manu-
script? Any conflicts of interest should be stated explicitly. This information can be
provided in the body of the text or in a footnote.

<h>CONCLUSION</h>
----------

We developed the SCRIBE 2016 to assist investigators in the behavioral sciences to report
SCEDs with transparency, accuracy, clarity and completeness. This article provides
rationale for and ex- planation of the 26 SCRIBE 2016 items. It also includes examples of
adequate reporting of specific SCRIBE 2016 items, drawing on arti- cles in the published
literature. Authors reporting on one specific type of single-case methodology, the medical
N-of-1 trial with multiple cross-overs, will find it helpful to consult the CENT 2015
Statement (Shamseer et al., 2015; Vohra et al., 2015), which was developed for that
particular methodology. We welcome feedback from users of the SCRIBE 2016, which can be
made through the SCRIBE website (www.sydney.edu.au/medicine/research/scribe). Since the
first CONSORT guideline appeared in 1996 (Begg et al., 1996), medical journals have
continued advocating the use of pre- scriptive reporting guidelines in the CONSORT
tradition. The EQUATOR network (www.equator-network.org) is a useful resource to keep up-
to-date with new developments in this field. This develop- ment has not occurred in the
behavioral sciences to the same degree, although many authors of intervention studies in
the behavioral sciences consult relevant CONSORT Statements (e.g., CONSORT Extension to
Nonpharmacological Interventions; Boutron et al., 2008). The influence of CONSORT is such
that the peak medical journals require that authors address all of the criteria of the
relevant guideline in their report. The benefit has resulted in improved reporting (Turner
et al., 2012). It will be advantageous to the behavioral sciences if journals publishing
single-case methodology also endorse use of the SCRIBE 2016 in this way.


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<ART>Response to Ruby et al: On a ‘failed’ attempt to manipulate conscious perception with transcranial magnetic stimulation to prefrontal cortex
================================================================================

Authors: Daniel Bor, Adam B. Barrett, David J. Schwartzman, Anil K. Seth
DOI: 10.1016/j.concog.2018.07.011
Year: 2018  |  Pages: 334-341
ASJC codes: 3204, 3205
Keywords: Consciousness, Dorsolateral prefrontal cortex, Failed replication, Metacognition, Null result, Perception, Signal detection theory, Transcranial magnetic stimulation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Does disruption of prefrontal cortical activity using transcranial magnetic stimulation (TMS) impair visual metacognition? An initial study supporting this idea (Rounis, Maniscalco, Rothwell, Passingham, & Lau, 2010) motivated an attempted replication and extension (Bor, Schwartzman, Barrett, & Seth, 2017). Bor et al. failed to replicate the initial study, concluding that there was not good evidence that TMS to dorsolateral prefrontal cortex impairs visual metacognition. This failed replication has recently been critiqued by some of the authors of the initial study (Ruby, Maniscalco, & Peters, 2018). Here we argue that these criticisms are misplaced. In our response, we encounter some more general issues concerning good practice in replication of cognitive neuroscience studies, and in setting criteria for excluding data when employing statistical analyses like signal detection theory. We look forward to further studies investigating the role of prefrontal cortex in metacognition, with increasingly refined methodologies, motivated by the discussions in this series of papers.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The role of prefrontal cortex (PFC) in visual awareness remains hotly debated (Boly et
al., 2017; Bor & Seth, 2012; Odegaard, Knight, & Lau, 2017; Tsuchiya, Wilke, Frassle, &
Lamme, 2015). One way of addressing this topic is to disrupt prefrontal activity using
(theta-burst) TMS, while examining any effects on subjective aspects of visual perception.
An influential 2010 study took this approach, combining theta-burst TMS (tbTMS) with an
innovative signal-detection-theory (SDT) analysis in a simple perceptual decision task
(Rounis, Maniscalco, Rothwell, Passingham, & Lau, 2010). A major contribution of this
study was to introduce the SDT quantity - meta-d’ - which quantifies, in a principled and
statistically unbiased way (assuming the model is true), how subjective reports (such as
visibility or confidence ratings) discriminate the accuracy of first-order perceptual
decisions (such as whether a stimulus is a square or a diamond). Rounis et al. found that
tbTMS to dorsolateral PFC (DLPFC) selectively reduced visual metacognition, while first-
order perceptual accuracy remained unchanged by design. This finding, if it stands up,
provides strong evidence supporting a causal role for DLPFC in visual metacognition, which
in turn support [at least on some theories, (Lau & Rosenthal, 2011)], a causal role in
conscious perception. However, attempted replications by our laboratory failed to find any
reliable effect of tbTMS to DLPFC on visual metacognition (Bor, Schwartzman, Barrett, &
Seth, 2017), concluding that, across studies, there was no reliable evidence for such an
effect. This study in turn has been critiqued by authors from the original paper (Ruby,
Maniscalco, & Peters, 2018), who go so far as to claim, on the basis of computational
modelling, that the Bor et al. study in fact supports the findings in the original Rounis
et al. study. We disagree with this surprising claim. We maintain that the results of our
study should be understood following our interpretation in Bor et al.: that there is not
(yet) good evidence that tbTMS to DLPFC disrupts visual metacognition. In substantiating
our arguments, we encounter more general issues concerning what constitutes good practice
in replication of cognitive neuroscience studies, and in setting criteria for excluding
data when employing statistical analyses like signal detection theory (SDT). Discussion of
these issues is, we believe, worthwhile beyond the current set of studies. We therefore
welcome the continuation of this productive debate. Finally, we recognise that whether or
not PFC is causally implicated in perceptual metacognition and conscious perception
remains an important open question, and that other sources of evidence including lesion
and neuroimaging studies will play an important role in addressing this question (Boly et
al., 2017; Lau & Rosenthal, 2011; Odegaard et al., 2017).

<h>RUBY ET AL.’S ARGUMENT</h>
----------------------

In this spirit of open and constructive debate, the remainder of this paper describes our
opinion on Ruby et al. (2018). Let us first summarise our understanding of their argument,
the heart of which is statistical and computational. They focus on the fact that, in Bor
et al. (2017), we excluded a substantial number of subjects from our analyses, in
comparison to the original analyses in Rounis et al. (2010). In their view, our exclusions
were not necessary since, according to computational simulations they performed, they did
not affect false positive (FP) rates. Given that in Bor et al. we found a result which
they claim was in line with Rounis et al., when we did not exclude subjects, they argue
that we unnecessarily lowered our chances of finding a true effect (of TMS on
metacognition) when we did apply our rigorous exclusion criteria. Ruby et al. then present
a Bayesian analysis purporting to show that the data from Bor et al., support, rather than
conflict with, Rounis et al. We disagree with this claim, as we will explain. Ruby et al.
also selectively criticize some of the methodological changes we made, raising important
issues about what constitutes an adequate replication. We take the opportunity here to
revisit the reasons for these design decisions in the context of this broader concern.
Finally, Ruby et al. appeal to evidence from a diverse range of alternative studies when
discussing the overall question of the role of PFC in metacognition and consciousness. We
do not think this appeal is relevant to the specific discussion about methods and
analyses. Instead, it leads to further confusion since we do not claim our analyses
undermine any of these alternative studies.

<hs>  Subject exclusion, FP rates, and the value of ‘clean’ data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ruby et al. motivate their simulations by saying that our main reason for subject
exclusion was to avoid a high FP rate. Ruby et al. claim that excluding the subjects as we
did in Bor et al. (2017) was ‘unnecessary’, on the basis of their computer simulations
showing that FP rates are unaffected by such exclusions. Although we still maintain that
including unreliable meta d’ results (“unreliable” meaning no longer measuring what it
purports to, no longer a smooth, linear function, so that now a small change in underlying
psychological components, such as hit rate, can lead to a large jump in the measure) may
well increase FP rates (see below for reasons), this is a secondary issue, and is a
misrepresentation of our reasoning, which is the critical point of disagreement between
us. We in fact performed these exclusions based on well-established theoretical arguments,
elaborated in Barrett, Dienes, and Seth (2013) and fully described in Bor et al.
Specifically, we excluded subjects when they had false alarm (FAR) or hit rates (HR)
either less than 0.05 or greater than 0.95, at either the Type I (objective decision) or
Type II (metacognitive) levels,1 in other words values that were numerically “extreme” by
being close to or at the 0 or 1 limits. In Barrett et al. (2013), we showed that it is
principled to apply these criteria because, otherwise, as we stated in the Bor et al.
(2017) paper, “including such extreme results in the analysis is very likely to introduce
instabilities [here referred to as “unreliabilities”] in measures reliant on type I and II
SDT quantities, including type II d’ and especially various implementations of meta-d’ …
Specifically, since the z function (i.e. the inverse of the standard normal cumulative
distribution) approaches plus or minus infinity as HR or FAR tends to 0 or 1, SDT measures
such as meta-d’ can take on extreme and highly inaccurate values with such inputs. In
practice, we demonstrated from our data that unstable [in this commentary referred to as
“unreliable”] meta-d’ – d’ values are significantly different from stable [reliable]
values” (p. 15). As this is such a critical point, let us rephrase it here: When hit rates
or false alarm rates (HR/FARs) are not near 0 or 1, there is a roughly linear relationship
between changes in HRs or FARs and meta d’. Such smooth, approximately linear
relationships are good indicators of a reliable measure (i.e. one that accurately reflects
the psychological process it is capturing, and where a small change in some psychological
component, such as HR, will lead to a small change in the measure). However, when HRs or
FARs become too big or too small (i.e. close to 0 or 1), a small change to them causes a
big change in meta-d’. In other words, at these (numerically) extreme values, the
relationship between changes in HRs or FARs changes from smooth and linear to non-smooth
and non-linear, and the meta d’ measure is no longer reliable. This is clearly illustrated
in Barrett et al. (2013) Fig. 5, reproduced here (see Fig. 1), where type II FARs
approaching 0 or HRs approaching 1 cause meta d’ values to significantly deviate from
their previously linear path. Note that the unreliability of the measure seems to be a
particular issue for the SSE method, which was the main version of meta d’ used both in
the Rounis et al. (2010) and our Bor et al. (2017) studies (in order to keep close to the
Rounis et al. methods). Although the above figure was for simulated data, this is an
empirical problem too. Fig. 2 below shows that, for all datapoints from experiment 1 of
Bor et al. (2017) those that have more extreme (close to 0 or 1) FAR and HR values, which
appear to the right of the graph, have a far larger spread of meta d’ - d’ values, as
would be expected from the arguments above. In theory, meta d’ - d’ should have a maximum
value of 0. In practice, this is violated when sample sizes aren’t large, and this problem
becomes exaggerated when type I and II HRs and FARs are extreme. Note that the figure
demonstrates that meta d’ prime values markedly above the theoretical maximum of type I d’
can occur with either extreme HR and FAR values at the type I or II level. To put it even
more bluntly, such subjects with extreme SDT values will have a meta-d’ measure that will
not reflect their metacognitive performance, since the measure is effectively breaking
down due to the extreme HR or FAR. These extreme meta d’ values can have an influential
effect at the population level, depending on what statistical tests are used. Ruby et al.
take the view that all that matters is whether subject exclusion will affect FP (or FN)
values, e.g. “we emphasize that in classical hypothesis testing there are two main types
of error: Type I and Type II. Within this standard framework, any statistical decision or
justification of a choice of procedure is meaningful only with respect to its impact on
these two kinds of error” (p. 39). Our view instead is that the proper application of
statistical techniques requires confidence that measured variables, on which inference is
performed, reflect the property of interest. If it’s clear that some portion of data, due
to mismeasurement (e.g. subject responses orthogonal to question of interest, or extreme
HR/FAR values as in the present case) do not reflect the property of interest, then they
should be excluded for this reason, regardless of statistical concerns (although usually a
likely corollary is that FP or false negative (FN) rates may well be reduced). From this
perspective, the main purpose of the Ruby et al. paper, namely to use simulations to
demonstrate that FP rates are unaffected by subject exclusions, becomes irrelevant. It is
worth noting that these principled reasons apparently motivated the authors of the
original Rounis study to mitigate these problems in their original design, by instructing
subjects to keep their type II responses as even as possible, thus avoiding the extreme
HR/FAR values. Having taken such clear methodological steps to reduce extreme values, it
would then seem reasonable for Rounis et al. to have excluded their remaining subjects
that included extreme HR/FAR values, as we did ours. However, we also note that had they
done this, as Ruby et al. report, they would have reduced their n from 20 to 7. In other
words, their attempt to avoid the extreme HR/FAR values by this design failed.

<hs>  Issues with the Ruby et al. simulations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A second point of disagreement has to do with the relative value of empirical data
compared to simulations. In both the Rounis et al. and Bor et al. studies, including
unreliable meta d’ measures, based on extreme HR/FAR data leads to a significant result
(though in both studies this was a parametric test on non-gaussian data and in our study
this was the case when using only one of various metacognition measures, and only on one
of two large experiments), while excluding these results leads to a null. This is entirely
consistent with the notion that including unreliable meta d’ scores increases one’s
chances of a false positive, which to our minds provides the most parsimonious explanation
of both these results. The Ruby et al. simulations may even lend credence to this
interpretation, given that they show (Table 1, supplementary materials) that power should
have increased in our between subjects design (where there was a positive result on one
measure without excluding subjects) after exclusion. Principled analysis of actual
empirical data is preferable to claims based on computer simulation of empirical data that
are then used to reinterpret that data. Simulations necessarily have a range of
parameters, some of which are inevitably set with somewhat arbitrary values, as compared
to rigorous theoretical and analytical approaches applied to empirical data. In addition,
simulations often embed assumptions about the nature of the data generating process which
are by construction in line with the analysis methods, meaning that they will tend to
overestimate the sensitivity and validity of the corresponding analyses.2 Accordingly, the
Ruby et al. simulations make the assumption that type I and II decisions are based on the
same evidence, distributed according to a standard SDT model. Furthermore, the simulation
parameters used by Ruby et al. to model our (2017) data are drawn from the original Rounis
et al. study empirical data, not from the empirical data in Bor et al. As Ruby et al.
themselves emphasise, the two studies are not identical (since we made some minor
modifications to improve the design, as we describe in detail in our paper). In which
case, it would seem more appropriate to use the parameters from our own empirical data,
which are bound to differ somewhat from their dataset.3 The potential (and as yet unknown)
impact of these choices about parameter values again underlines the potential dangers of
relying on simulations as compared to principled theoretical analysis. In addition, the
analysis of Barrett et al. (2013) suggests that including extreme data points should
weaken statistical inference since, as we have already noted, small random fluctuations in
hit and miss rates at extreme ends of the spectrum will translate into large fluctuations
in measured values of meta-d’. Ruby et al.’s simulations of Bor et al.’s Experiment 1
concord with weaker inference in this sense, but for Experiment 2 they surprisingly find
the opposite, marking an intriguing discrepancy deserving of further research. One
possibility to resolve this discrepancy would be to create simulations based on
distributions of empirical hit and false alarm rates in Rounis et al, and use these to
generate surrogate data, rather than starting from the levels of meta-d’ as currently done
in Ruby et al. This approach would avoid making assumptions about how responses are
generated in response to stimuli, and would require only the assumption of trial-to-trial
independence.

<hs>  Issues with the Bayesian assumptions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ruby et al. claim that DLPFC tbTMS in the Bor et al. study actually caused a metacognitive
deficit, on the basis of a Bayesian analysis, using a prior of 0.5, partially based on the
Rounis et al. data. We are not compelled by this logic since we have argued that the
results found in Rounis et al. are based on invalid data (i.e., data obtained without
subject exclusion). It therefore seems arbitrary and unjustified to assign any Bayesian
prior (including a neutral prior of 0.5) to the probability that the effect found in that
study is true. Indeed, the primary contribution of our study was to examine what happens
when only valid data are included in the analysis. If a prior is anyway to be selected,
what should that prior be? Based on only valid data, both the Rounis and Bor et al.
studies found a null result. In addition, the Ruby et al. paper cites a relevant recent
TMS prefrontal cortex metacognition paper by Rahnev and colleagues (Rahnev, Nee, Riddle,
Larson, & D'Esposito, 2016), where TMS to prefrontal cortex actually enhanced perceptual
metacognition. Ruby and colleagues conclude that these results “suggest that different
parts of DLPFC perform different [metacognitive] functions.” However, given that tbTMS to
both an anterior and dorsolateral region of the prefrontal cortex enhanced perceptual
metacognition compared to a control site, the results of this new study are evidently
relevant to any putative Bayesian prior, making a metacognitive impairment due to DLPFC
TMS even less likely. If two null results and an opposite effect are input into a Bayesian
prior, we assume the value would be very different to 0.5 and consequently the conclusions
of the Ruby et al. paper about the likelihood of our results actually reflecting a DLPFC-
induced metacognitive impairment would be very different as well.

<hs>  Did Bor et al. unintentionally replicate Rounis et al.?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ruby et al do not merely disagree with our conclusions in Bor et al. They in fact say, “We
therefore find it striking that Bor et al.’s (2017) results appear to demonstrate a
successful replication prior to subject exclusion, despite their interpreting otherwise.”
Because of the contentious nature of this claim, we believe it is worth going into the
details of what we did and did not find. It is true that, using one particular method of
computing meta-d’ (sum-square-error, SSE), in Experiment 1, when not excluding the
subjects with unreliable meta d’ scores due to extreme HR/FAR values, on a one-tailed
t-test, without multiple comparisons on non-parametric data we found a significant
difference between the DLPFC and control (vertex) group (p = 0.03). We included this
invalid statistical test (a parametric test on non-parametric data) explicitly to make a
point: “We should emphasise, however, that this significant result, aside from being
uncorrected for multiple comparisons [we had 4 experimental groups and three metacognitive
measures], is not to be trusted as it includes data that invalidates the (parametric)
assumptions underlying the analysis. We merely include this analysis to demonstrate how
the inclusion of unstable [unreliable] values could potentially generate spurious
significant results.” (p. 12). It is unclear whether a one-tailed t-test was appropriate
here, given any prior expectation to replicate the Rounis et al. result was potentially
nullified by other more recent studies showing the opposite results, such as Rahnev et al.
(2016). Had we used a two-tailed t-test, this single significant result would not have
been significant. Similarly, had we corrected either for the number of experimental group
or number of metacognitive measures, the result would not have been significant either.
Our suspicion was that the main parametric result from Rounis et al. was based on non-
normal data, as was our significant result above. Had we carried out the more appropriate
non-parametric equivalent test, this result would not have approached significance
(Wilcoxon Rank Sum Test W = 113, p = 0.1949). Ruby et al. confirm the non-normality of
their original data in the last paragraph of their supplementary materials document, and
claim that the critical non-parametric equivalent interaction test was still significant,
though unfortunately without providing any details on p-values or related quantities.
Moreover, in the Bor et al. case the effect (if any) seems to be driven by an unpredicted
boost to metacognition in the control group, rather than a reduction in metacognitive
performance in the experimental (DLPFC) group, as interpreted by Rounis et al. This
solitary statistical effect therefore does not seem to replicate Rounis et al., contrary
to Ruby et al.’s claim. In addition, when we used the main alternative version kindly
supplied by Rounis and colleagues (maximum likelihood estimation, MLE), or a new Bayesian
method by Stephen Fleming4 (HMeta-d), without exclusion, there was also no such
significant effect (with unreliable measures: MLE p = 0.66, HMeta-d p = 0.65; excluding
unreliable measures MLE p = 0.69, HMeta-d p = 0.54). We therefore disagree that our study
constitutes an unintended replication of Rounis et al., especially when taken in
combination with the rest of our analyses which rigorously failed to find evidence for any
effect, including Bayes Factor robust findings for a null. Furthermore, in Experiment 2
within the Bor et al. paper, we were even less successful in attempting to replicate the
Rounis et al. findings. We designed our Experiment 2 as an adaptation of a within-subject
design, and was therefore in this way a closer replication of Rounis et al. Our double-
within-subjects protocol (potentially having 4 sessions of TMS and testing, instead of 2)
was in fact designed to be sensitive to the presence of even just a single subject (out of
the original 27) who would follow the pattern of the Rounis et al. study. Had we found
just one subject who replicated the Rounis et al. results over the 4 sessions of session
2, we may have been able to describe this experiment as providing a partial replication.
This was indeed our intention, contrary to Ruby et al. in their abstract claiming that we
“adopted an experimental design that reduced their chance of obtaining positive findings.”
However, we did not find even a single subject who followed such a pattern. The first
session involved tbTMS to DLPFC for all 27 subjects. Of those 27, 10 were excluded due to
extreme SDT values. Out of these 17 subjects, 7 showed an effect (in either direction)
equivalent to the Rounis et al. study. Our original wording from Bor et al. makes clear
the nature of our non-replication: “Of the remaining 7 participants, 3 showed the expected
impairment, while 4 showed a clear metacognitive enhancement following DLPFC cTBS. 6 of
these 7 participants also showed a clear metacognitive change for the vertex control
session, and thus were not asked to return for the 3rd session (2nd DLPFC). Only 1
participant that showed a clear DLPFC cTBS metacognitive change in the first session also
showed no change for the 2nd vertex cTBS session, and thus was brought back for the 3rd
session (2nd DLPFC). This session, unfortunately, included unstable SDT values [here
meaning extreme HR/FAR values close to 0 or 1], and thus the participant was not asked to
return for a 4th session. If these instabilities [unreliable measures] are ignored,
though, the metacognitive change for the 3rd session was very similar to the 1st session.
Both sessions, however, showed a robust enhancement of metacognition for this single
subject following DLPFC cTBS, as opposed to the impairment found in the Rounis study.”
(Bor et al., 2017, p. 13). A comprehensive appreciation of our Experiment 2 therefore
reveals that not even a single participant replicated the results in Rounis et al. Even
when just considering the first two sessions, which would make our Experiment 2 even more
closely resemble the original Rounis et al. study with its two sessions, not a single
participant (out of 27) showed both a DLPFC tbTMS metacognitive impairment, as well as no
metacognitive effect when tbTMS is applied to the control site (vertex). In terms of
statistical power, which Ruby et al. critique for our Experiment 2, we note that their
reported power for our Experiment 2 after excluding subjects was 0.308, which was almost
identical to the Rounis et al. study (without subject exclusions) of 0.311. (The greatest
statistical power across both the Rounis et al. and Bor et al. experiments was in our
Experiment 1 after excluding subjects: 0.409.) Thus, on the basis of power calculations,
it remains difficult to explain why our experiments failed to find a positive result,
while the Rounis et al. study did find such a result. However, we emphasise that modelling
of power and false positive rates are a poor alternative to rigorous analysis of the
empirical data itself, as our Experiment 2, in particular, demonstrates. Finally, even if
discounting all the arguments we make above, relying on outliers for a positive result –
as in the original Rounis et al. study – suggests, at best, only a small effect size.

<hs>  Design differences between the Bor et al. and Rounis et al. studies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In their manuscript, Ruby et al. also criticise the fact that we modified the experimental
design of Rounis et al. in various ways. For example, they say “[Bor et al.] made several
changes to the original study design, some of which are known to undermine the chance of
finding meaningful results from the outset”. Indeed, we did make small changes to the
Rounis et al. design. As we made clear in Bor et al., in each case the changes were made
to improve the design with respect to its suitability to address the underlying
experimental question. Some of these changes should be entirely uncontroversial; for
instance, in removing some minor software ‘bugs’ in the experimental scripts which Rounis
and colleagues kindly shared with us, and in ensuring consistency in behavioural
responses, and so on (see Bor et al., p. 3). One notable change was that we used a
between-subjects design rather than (as in Rounis et al.) a within-subjects design for our
Experiment 1. This was mandated by our original aim to replicate and extend Rounis et al.
by exploring the potential causal contribution of other regions within the frontoparietal
network to metacognition. Our Experiment 2, however, utilised a double-repeat within-
subject design and still failed to find any effect of cTBS on metacognition. This double-
repeat design exemplifies that the changes we made were employed to maximize the chance of
finding a true effect should one exist. The other design changes in Bor et al. (2017) were
also made in a principled way, and captured in full the spirit of the original Rounis et
al. experiment. These changes are fully described in Bor et al. (see, for example, p. 15)
and we will just reinforce two points here. First, there were small changes to task
instructions: we used confidence rather than visibility ratings (to ascertain
metacognition more directly and to avoid additional working memory demands). However, in
attempting to avoid the issues around relative, rather than absolute, metacognitive
judgements, of the original Rounis study, we recognise that asking a different
metacognitive question could have led to different results. Whether such a subtle change
is sufficient to turn a significantly positive finding into a null result is a question we
address in the next section. We also used an active TMS control (vertex) rather than sham
TMS, to provide a closer match between experimental and control conditions. Part of our
justification for this change was to address demand characteristics, with sham TMS versus
real TMS potentially causing subjects to demonstrate a stronger impairment for that
condition (DLPFC) for which they perceive is the real condition. However, although we
continue to believe that a real TMS site is preferable to sham as a control, we also
acknowledge that the choice of vertex itself is not perfect. First, a vertex control would
not have induced as many peripheral nerve issues (facial twitching and pain) as the DLPFC
stimulation in a subset of subjects (though would be similar to the parietal TMS
stimulation we used in experiment 1). Second, the vertex control meant that the same
region was stimulated twice, unlike any of the experimental conditions. It is difficult to
know how such a difference would affect participants both psychologically and
neurophysiologically. Interestingly, at one point, Ruby et al. (p. 15) criticise that we
used only two levels of confidence judgements, suggesting that using more than two would
have allowed more sensitive estimation of meta-d’. However, although we agree that more
than two levels would have been beneficial, we used two levels because Rounis et al. also
used two levels (in their case of visibility ratings rather than confidence). Had we used
more than two levels, this would have changed the design considerably, and any subsequent
null result might have been attributed to such a clear departure from the original
protocol.

<hs>  What constitutes a good replication</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

These points speak to a broader discussion of what counts as an adequate replication in
cognitive neuroscience [see, for example, (Szucs and Loannidis, 2017)]. Our view is the
following: Replications in cognitive neuroscience are not (yet) like replications in
experimental physics – cognitive neuroscience (broadly construed) necessarily embeds a
greater degree of flexibility in how experiments are designed and conducted, given the
range of theoretical views, experimental methods, and analysis techniques. In addition,
for any particular experimental result to be described as ‘strong’, it should be robust to
small variations in paradigm, especially when such variations should be expected to
improve the design according to principled criteria. A related point is that, as Ruby and
colleagues admit, both the original Rounis et al. and the Bor et al. studies were
relatively underpowered. We attempted to include a high n and sufficient power in our
studies, but the extent of subject exclusions due to extreme HR/FAR values was
substantial, which weakened power, even when the data were cleaner. Our view is that the
best way forward is to collect more empirical data, rather than run simulations. We freely
admit limitations in both the Rounis and Bor et al. studies, and that a new experiment
with more robust power could address these limitations. A new design could also improve on
both studies by having MRI-guided TMS, using a continuous confidence or visibility
judgement (or at least including many more options than the binary options we both used),
with a sufficiently large n, and multiple controls (e.g. both sham and real TMS at various
non-DLPFC sites). To our minds, such a study could definitively answer the question of
whether tbTMS to DLPFC can impair visual metacognition, and would be far beneficial to any
simulation or to debates about the perceived differences between two experiments. In
general, lack of power is a persistent problem in cognitive neuroscience studies (Szucs
and Loannidis, 2017), and if this is combined with the bias towards positively significant
results, creates an atmosphere where Szucs and Loannidis (2017) have concluded that “more
than 50% of published findings deemed to be statistically significant are likely to be
false.” Consequently, both the original study, and the attempted replication, should
strive for high statistical power. Furthermore, given the issue of failed replications, we
believe that there should be a greater onus on initial publications to demonstrate robust
effects, both in terms of power and the extent of the robust statistical findings.

<hs>  Is the prefrontal cortex involved in metacognition?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Ruby et al. imply that we argue against any role for PFC in metacognition or conscious
perception. For instance, in the introduction they write that following our null result,
“they… suggest that DLPFC might not be ‘critical for generating conscious contents’.” This
quoted phrase is a misrepresentation of our position, and we urge readers to read the
entire discussion from Bor et al. to retrieve the full context. There we raised the
possibility that our findings in Bor et al. are consistent with so-called ‘no report’
paradigms which have independently cast doubt on the role of the DLPFC in generating
conscious contents (e.g. Brascamp, Blake, & Knapen, 2015), but also raised other
possibilities, such as that the prefrontal parietal network might be especially plastic,
and adapt within seconds to TMS administration, or that tbTMS to DLPFC at ethically safe
levels simply isn’t sufficient to induce an impairment in a subtle paradigm. We nowhere
deny that there is other evidence, from other studies (including, for example, lesion
studies) that speak to a role for PFC in metacognition, or indeed in generating conscious
contents more generally (Bor, 2016). Indeed, we completely agree with Ruby et al. when the
say “Ultimately, whether theta-burst TMS to DLPFC can robustly impair visual awareness
concerns the specific method and details. More important is the general question regarding
the role of the prefrontal cortex in metacognition and conscious perception”. Absolutely.
But the only points of debate between Ruby et al. and Bor et al. concern the specific
details and methods. Simply citing evidence from other studies relating to PFC and
consciousness does not contribute to the present discussion; instead it falsely suggests
that one should believe Rounis et al. simply because it may possibly fit better with some
other independent experiments. However, Ruby et al. agree with us that establishing the
role of PFC in awareness is a very important, interesting, and open question (Bor and
Seth, 2012).

<h>CONCLUSIONS</h>
-----------

In summary, we continue to think the evidence so far, across studies, does not (so far)
demonstrate that theta-burst TMS to prefrontal cortex can disrupt visual metacognition.
Moreover, the findings from each study depend on the fine details of methods and analyses.
Further investigations would be helped by open access provision of data (as done for Bor
et al., but not for Rounis et al.), and simulation code (used in Ruby et al.) – so that
interested researchers can draw their own conclusions in addition to the opinions
presented in this series of papers. We also look forward to further studies with
increasingly refined methodologies, motivated by the discussions here.
<ART>Rhythmic structure facilitates learning from auditory input in newborn infants
==============================================================================

Authors: Emma Suppanen, Minna Huotilainen, Sari Ylinen
DOI: 10.1016/j.infbeh.2019.101346
Year: 2019
ASJC codes: 3204
Keywords: Auditory processing, Electroencephalography (EEG), Event-related potential (ERP), Language development, Music, Nursery rhyme, Predictive coding

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Rhythm and metrical regularities are fundamental properties of music and poetry - and all of those are used in the interaction between infants and their parents. Music and rhythm perception have been shown to support auditory and language skills. Here we compare newborn infants’ learning from a song, a nursery rhyme, and normal speech for the first time in the same study. Infants’ electrophysiological brain responses revealed that the nursery rhyme condition facilitated learning from auditory input, and thus led to successful detection of deviations. These findings suggest that coincidence of prosodic cue patterns and to-be-learned items is more important than the format of the input. Overall, the present results support the view that rhythm is likely to create a template for future events, which allows auditory system to predict prospective input and thus facilitates language development.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Across cultures, caregivers and their infants use music to interact: for example, singing
play songs and lullabies, reciting nursery rhymes, and rocking infants in time with music
(Fernald & Kuhl, 1987; Obermeier et al., 2013; Papousek, 1996; Shannon, 2006; Trehub &
Schellenberg, 1995; Wallin et al., 2001). Previous research has shown that this behavior
results in beneficial socioemotional outcomes (Cirelli, Einarson, & Trainor, 2014;
Kivijärvi et al., 2001), and supports early language development. Many studies have shown
the benefits of both formal and informal musical activities to auditory, linguistic and
literacy skills in children (e.g. Bergman Nutley, Darki, & Klingberg, 2014; Chobert,
François, Velay, & Besson, 2012; François & Schön, 2011; François, Chobert, Besson, &
Schön, 2012; Kraus et al., 2014; Linnavalli, Putkinen, Lipsanen, Huotilainen, &
Tervaniemi, 2018; Moritz, Yampolsky, Papadelis, Thomson, & Wolf, 2013; Overy, 2003; Tallal
& Gaab, 2006; Torppa et al., 2014; for a review, see Virtala & Partanen, 2018). For
example, music training allows children to detect small pitch changes (Besson, Schön,
Moreno, Santos, & Magne, 2007), and children’s music experience has been found to promote
verbal memory (Ho, Cheung, & Chan, 2003), reading skills (Anvari, Trainor, Woodside, &
Levy, 2002; Corrigall & Trainor, 2011), vocabulary (Forgeard, Winner, Norton, & Schlaug,
2008; Linnavalli et al., 2018), phoneme awareness (Anvari et al., 2002), and detection of
prosody (Magne, Schön, & Besson, 2006). Music exposure changes the auditory cortical
processing (Partanen, Kujala, Tervaniemi, & Huotilainen, 2013; Trainor, Lee, & Bosnyak,
2011) and increases the number of preverbal communicative gestures in 12-month-old
children (Gerry, Unrau, & Trainor, 2012). Music captures and sustains infant attention,
and infants are more engaged when listening to maternal singing than to maternal speech
(Nakata & Trehub, 2004). In addition, musical activities seem to modify the phase of
attention fluctuations (Jones, 1976) to the periodicities in the music, thus improving
rapid temporal auditory processing and enhancing neural encoding of speech (Kraus &
Chandrasekaran, 2010; Schön & Tillmann, 2015; Zhao & Kuhl, 2016). There have been fewer
studies that investigate solely rhythm without the music accompaniment, yet the effects of
rhythm have been observed from infancy to adulthood. Metric regularity of rhythmic speech
and movement might have beneficial effects on speech processing. It has been found to
facilitate word segmentation in 9-month-old infants (Curtin, Mintz, & Christiansen, 2005)
and in adults (Leong & Goswami, 2015; Rothermich, Schmidt-Kassow, Schwartze, & Kotz, 2010;
Schmidt-Kassow & Kotz, 2009; Schön et al., 2008). Rhythm also helps lexico-semantic
integration (Rothermich, Schmidt-Kassow, & Kotz, 2012) and increases aesthetic
appreciation and emotional processing (Obermeier et al., 2013) in adults. Rhythm
perception is associated with foreign language learning in adults (Bhatara, Yeung, &
Nazzi, 2015), and grammar skills in 5–7 year old children (Gordon et al., 2015). Moreover,
children with developmental dyslexia have been found to have poor rhythmic perception
(2011b, Flaugnacco et al., 2014; Goswami, 2011a; Goswami et al., 2002; Huss, Verney,
Fosker, Mead, & Goswami, 2011). Goswami (2011, 2018) has suggested that rhythmic auditory
input causes phase synchronization in oscillations of auditory cortex, and thus results in
a more efficient neural sampling of the auditory signal. Bimodal auditory and visual
stimuli in synchrony are highly salient, and deploy infants’ attention efficiently
benefiting their perceptual processing and memory (Bahrick & Lickliter, 2000; Lewkowicz &
Lickliter, 2013; Lewkowicz, 2000; Reynolds, Bahrick, Lickliter, & Guy, 2014). Music
(Lebedeva & Kuhl, 2010; Peterson & Thaut, 2007; Schön et al., 2008; Thaut, 2005) and
rhythm with or without music (Purnell-Webb & Speelman, 2008) have been found to enhance
learning and memory in adults. This is because the structure of music and rhythms are
likely to create a template for future events. Such structure helps adaptive auditory
system to pick up sound regularities in a predictive manner (Rothermich et al., 2010;
Schmuckler & Boltz, 1994; Winkler, Háden, Ladinig, Sziller, & Honing, 2009). Infants can
detect pitch and rhythm changes at birth (Sambeth, Ruohio, Alku, Fellman, & Huotilainen,
2008; Telkemeyer et al., 2011; Trehub & Hannon, 2006) and even before that as near-term
fetuses (Graniere-Deferre, Ribeiro, Jacquet, & Bassereau, 2011; Lecanuet, Graniere-
Deferre, Jacquet, & DeCasper, 2000; Partanen, Kujala, Näätänen et al., 2013). Furthermore,
infants are sensitive to prosodic rhythm, and can discriminate between languages
representing different rhythm classes – even when the phonemic structure of speech is
degraded (Nazzi, Bertoncini, & Mehler, 1998). Thus, it seems that infants are already
sensitive to prosodic information carried by slow-varying patterns of spectral and
amplitude modulation. Infants have been found to be able to extract and predict auditory
regularities from sound frequency, duration, timbre (Háden, Németh, Török, & Winkler,
2015; Ruusuvirta, Huotilainen, Fellman, & Näätänen, 2009; Trainor, 2012) and stream of
syllables (Teinonen, Fellman, Näätänen, Alku, & Huotilainen, 2009). François et al. (2017)
found that newborn infants were able to detect statistical violations in pseudo-words in
melodically enriched, but not in flat speech streams. They also showed that neonatal brain
responses to deviations in melodically enriched speech correlated with expressive
vocabulary at 18 months. Furthermore, newborn infants can extract temporal predictions
from rhythmical regularities in the auditory input (Winkler et al., 2009). However, little
is known about how neonates encode continuous speech, how much they are able to learn from
it, and whether music or rhythmic speech helps them to do so.

<hs>  Current study</hs>
  ~~~~~~~~~~~~~

The aim of this study was to explore whether music and rhythm can be observed to
facilitate learning from auditory input in newborn infants. To this end, we presented
natural continuous stimuli with similar semantic content in the form of a nursery rhyme, a
song and prose to infants and recorded their auditory event-related potentials (ERPs). We
then probed the learning effects by introducing infrequent changes of vowel, word, pitch,
and intensity changes to speech excerpts (similar to the optimal paradigm; Näätänen,
Pakarinen, Rinne, & Takegata, 2004) and by recording the neural responses to them. In line
with predictive coding theory (Rao & Ballard, 1999, 2010, Emberson, Richards, & Aslin,
2015; Friston, 2005; Friston, Kilner, & Harrison, 2006; Kayhan, Meyer, O’Reilly, Hunnius,
& Bekkering, 2019; Kouider et al., 2015; Pickering & Garrod, 2013), we expected that
sensory stimulation results in attempts to generate an internal model of its regularities
in the infant brain. When an incoming stimulus deviates from the internal model, a quick
and robust brain response is elicited. This response, known as prediction error, can be
thought as a feedback signal to the higher levels of neural network that adjusts the
neural representations of the internal model to minimize future surprises (Friston et al.,
2006; Winkler, 2007; see also Näätänen, Paavilainen, Rinne, & Alho, 2007, for the mismatch
negativity (MMN) elicited in an oddball paradigm). In the case of infrequent changes in
our stimuli, possible prediction error brain responses would reflect learning, because
without any learning from the long continuous stimuli, the infants’ internal model could
not predict incoming stimulation (for predictions in speech processing and recognition,
see DeLong, Urbach, & Kutas, 2005; Gagnepain, Henson, & Davis, 2012; Ylinen et al., 2016;
Ylinen, Bosseler, Junttila, & Huotilainen, 2017). We hypothesized that the rhythm present
in both nursery rhyme and song, and the melody present in song would enhance the
extraction of predictions from auditory input and thus facilitate learning. We expected
this to result in the strengthening of the prediction error response, which in this case
reflected infants’ learning as a result of exposure.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants (N = 21; 8 boys, 13 girls) were healthy newborn infants born into Finnish-
speaking families. The mothers or both parents of the newborn gave written informed
consent to participate in the study. Electroencephalography (EEG) measurements were
conducted in Jorvi hospital in Espoo, Finland. The study was approved by the Ethics
Committee for Paediatrics, Adolescent Medicine and Psychiatry, Hospital District of
Helsinki and Uusimaa. Initially 24 newborns participated in the study, but data of three
participants were excluded due to technical problems or not reaching the criterion of 40
epochs. More details about participants can be found in Table 1.

<hs>  Study paradigm and stimuli</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

A Finnish version of a well-known nursery rhyme Simple Simon (Kunnas, 1997) was recorded
by a female native speaker of Finnish using three different conditions: she read two
verses as metrically-spoken nursery rhyme, sang two verses to a melody (see Fig. 1), and
read two verses in ordinary speech. To elicit as naturalistic stimuli as possible, the
speaker was not given specific instructions with respect to acoustics, and thus the
conditions differ by their duration, intensity, pitch and rhythmic structure (see detail
in Table 4). However, she was aware that the stimuli would be directed to infants, and was
given written instructions to read the stimuli as if she was reading to a toddler. The
ordinary speech was modified from the original nursery rhyme. The modifications of this
prose version included converting the atypical word order of the nursery rhyme into normal
one, and adding modifiers (genitive attributes) and clarifying words, the meanings of
which were implicit in the original nursery rhyme but which had been omitted from the
nursery rhyme because of the meter (see Table 2). The nursery rhyme used in the experiment
had a regular rhythmic structure (trochee) that was characterized by regular alteration of
stressed and unstressed syllables that were cued by pitch and intensity. The song had a
regular beat, but as compared to the nursery rhyme that used both pitch and intensity to
cue stress, there was smaller acoustic difference between stressed and unstressed
syllables (i.e., stressed syllables were less prominent). Rather than to cue stress, pitch
was used to convey melody. Ordinary speech was, in turn, characterized by less regular
pattern of stressed and unstressed syllables, since stress placement was determined by
focus in the sentence (rather than meter or beat). In order to be able to examine the
acoustic structures of nursery rhyme, song and speech in more detail, we utilized a number
of acoustic measures. We identified and labelled the locations of vowel-consonant and
consonant-vowel boundaries to segment the stimuli into vocalic intervals (n = 169),
located between the onset and the offset of a vowel, or a vowel cluster, and consonantal
intervals (n = 170), located between the onset and the offset of a consonant, or a cluster
of consonants (Ramus, Nespor, & Mehler, 1999). This was done in Praat (Boersma & Weenink,
2018). When boundaries could not be identified by visual inspection of speech waveforms, a
boundary was placed at a point where the preceding phone could no longer be heard. The
measures we used were (i) the standard deviation of vocalic interval duration (ΔV), (ii)
the standard deviation of consonantal interval duration (ΔC), (iii) the proportion of
vocalic utterance duration out of total duration multiplied by 100 (%V), (iv) the standard
deviation of vocalic interval duration normalized for speech rate variability (VarcoV),
(v) the standard deviation of consonantal interval duration normalized for speech rate
variability (VarcoC), (vi) the mean durational differences between successive vocalic or
consonantal intervals divided by the sum of the same intervals, the normalized pairwise
variability index (nPVI), and (vii) normalized pairwise variability index for vocalic
intervals (nPVI-V) (Dellwo & Wagner, 2003; Grabe & Low, 2002; Lee, Kitamura, Burnham, &
Todd, 2014; Ramus & Mehler, 1999; Ramus et al., 1999; White & Mattys, 2007a; 2007b; Wiget
et al., 2010). White and Mattys (2007b) found especially VarcoV useful for discriminating
different rhythm topologies: higher VarcoV suggests more salient contrasts between
stressed and unstressed syllables (see Fig. 2). In line with Lee et al. (2014) we also
utilized the pitch extraction algorithm in Praat (with standard settings: 75 Hz pitch
floor, 500 Hz pitch ceiling, 0.45 voicing threshold) to estimate the median F0 of all
vocalic intervals, and then calculated mean pitch in vocalic intervals and the standard
deviation of the median pitches of vocalic intervals. These measures and other acoustic
details of the stimuli can be found in Table 3. We were also interested in those prosodic
stress patterns in our stimuli which are not revealed by durational measures, such as
syllables, words and phrases (for discussion on general problems with durational rhythm
metrics, see Arvaniti, 2012). Leong (2012) introduced the idea of using nested amplitude
modulations (AM) as a measure of rhythmic information in speech: modulation range 0.9–2.5
Hz represents the stressed syllable rate, and 2.5–12 Hz range the syllable rate. The
amplitude envelope (AE) of speech varies relatively slowly in time, and the amplitude
rises coincide with stressed syllable onset, which occurs approximately twice per second
in infant-directed speech (IDS) and nursery rhymes (Goswami, 2018; Leong & Goswami, 2015;
Leong, Kalashnikova, Burnham, & Goswami, 2014). For example, Leong et al. (2014) used this
method to find that dominant rhythmic patterning of IDS occurs at prosodic stress feet
whereas for adult-directed speech (ADS) it happens at syllable rate.

<hs>  Descriptive analyses of the stimuli</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We extracted the amplitude envelopes of our stimulus signals using Hilbert transform and
40 Hz low-pass filter, and compared the envelopes and pitch contours of the three stimulus
types with 2-Hz sine wave by calculating generalized linear regression, where either
normalized signal envelope or pitch was the dependent variable and analytical (Hilbert
transformed) 2-Hz signal the independent variable (see e.g. Parkkonen, Andersson,
Hämäläinen, & Hari, 2008). Analytical signal was used to accommodate the phase of the
signal. A higher value means that there is more 2 Hz rhythm in the signal. As indicated by
Table 4, generalized linear regression analysis suggested that the highest degree of 2 Hz
rhythm was found in the nursery rhyme signal. That is, the regularity of the rhythmic
structure as indicated by intensity and pitch was highest in the nursery rhyme and lowest
in speech. In addition, we examined the rhythmic regularity of our stimuli signals by
computing the autocorrelation functions (ACF) of the nursery rhyme, song and speech signal
envelopes that had been filtered into stressed syllable (0.9–2.5 Hz) and syllable (2.5–14
Hz) modulation rates. A Fourier transform was then applied to the ACFs in order to get a
periodic power spectrum for each of the nursery rhyme, song and speech ACFs at both
modulation rates (Leong, 2012). Fig. 3 shows these spectra. Based on this analysis nursery
rhyme condition contained higher periodic power than the other two conditions at stressed
syllable modulation rate, but song condition had slightly higher periodicity at the
syllable modulation tier. These six verses were presented as repetitive standard stimuli
to the infants for 10.4 min (12 repetitions/verse) during a learning phase. A testing
phase (10 repetitions/verse, 8.6 min), which followed immediately after the learning
phase, introduced multiple deviations to the syllables with word stress. The possible
deviations were the change of the whole word, vowel, sound intensity, or pitch. The
deviations were inserted to all types of verses avoiding two simultaneous ones. The order
of the verses was counterbalanced across participant groups (4 participants/group). There
were 10 differing versions of each verse, and each altered verse included each deviation
type twice (see Table 5). There was only one deviation type per altered syllable, however,
and the same deviation did not repeat on each syllable more than once. Intensity change
was implemented as six dB increase or decrease of sound pressure level in all conditions.
Sound frequency deviations were carried out by increasing or decreasing base frequency by
20% in poetry and prose verses, whereas in song verses melody was shifted by two to five
whole tones using notes that did not break the original chord progression (see Appendix
A). Infants were asleep in a crib during the measurement, facing randomly either to the
left or to the right, thus partly obscuring one ear. The infants can be measured when they
are asleep, as the elicitation of prediction error responses does not require focused
attention (Cheour et al., 2002). Infants’ hearing was normal according to the clinical
routine screening done with otoacoustic emission test (EOAE, ILO88, Dpi, Otodynamics Ltd,
Hatfield, UK). The measurement was conducted by a registered nurse, who observed the
infant and their apparent sleep stages throughout the EEG recording. The stimuli were
presented via two loudspeakers located close to the corners at the foot of the crib, the
approximate sound level being 74 dB SPL.

<hs>  EEG recording and data analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

EEG was recorded from 12 channels using Ag/Cl-electrodes placed on the infants’ head
according to the international 10/20 system (NeuroScan, Synamps 2 amplifier). Electrodes
were attached to F3, F4, C3, Cz, C4, P3, P4, T7, T8, the two mastoids, and below the right
eye. The sampling frequency was 500 Hz and the left mastoid was used as a reference. The
data were re-referenced to the average of the two mastoids and bandpass-filtered (high-
pass 0.5 Hz, low-pass 30 Hz, slope 48 dB/octave). Possible eye movements were corrected,
and data were divided into epochs of −100-500 ms with respect to the beginnings of the
syllables of interest. Epochs with artefacts exceeding 100 μV were rejected and omitted
from further analysis. Epochs were then averaged for each stimulus type with a 100 ms pre-
stimulus baseline. As the paradigm included many kinds of deviants, there were on average
60.7 accepted epochs per deviant. Therefore, some of the types had to be grouped to make
sure there was a sufficient number of epochs per infant for averaging. The grouping was
based on whether the changes were phonological in the Finnish language or not: word or
phoneme changes are phonological in Finnish but fundamental frequency and intensity
changes are not. The phonological status was expected to be important because the infants
born to Finnish-speaking families1 must have been exposed to the Finnish phonology before
birth. Based on previous findings on fetal learning (Partanen et al., 2013b, Partanen,
Kujala, Tervaniemi et al., 2013), this might favour the processing of native phonological
features over non-phonological ones. Therefore responses to frequency and intensity
changes were grouped into the category of acoustic feature changes and word or phoneme
changes were grouped into the category of word changes (see also Table 6)2 . Difference
waveforms were calculated by subtracting the standard ERP (i.e. responses to unaltered
syllables in learning phase) from the deviant ERP (i.e., responses to deviations) for each
deviant type and each infant in each condition (nursery rhyme, song, prose). Using
difference waveforms allows assessing the responses to deviants with minimal contribution
of exogenous ERP components related to sound properties. Two time-windows (40–100 ms and
130–190 ms) were selected for statistical analyses based on earlier literature (especially
Ylinen et al., 2017) and peaks revealed by visual inspection of grand average difference
waves.

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

The presence of prediction error responses to changes in words and acoustic features in
the selected time windows was examined by averaging together the mean amplitudes from F3,
F4, C3, C4, Cz, P3 and P4. The averages were submitted to one sample t-test in order to
assess whether the responses differed significantly from zero. The effect sizes for the
t-tests were calculated using Cohen’s d values. The normality of the data was inspected
visually from histograms depicting standardized residuals. The differences between
different conditions were examined by submitting the mean amplitude to a 3 × 3 x 2
repeated-measures ANOVA with condition (nursery rhyme, song, prose), frontality (electrode
lines F, C ja P), and laterality (electrode lines 3 ja 4) as factors. ANOVAs were run
separately for each time window. When sphericity could not be assumed, Greenhouse-Geisser
correction was used. Statistically significant (p < .05) main influences were analyzed in
more detail with Bonferroni-corrected pair-wise comparisons. Cohen’s d values were
calculated for each pair-wise comparison.

<h>RESULTS</h>
-------

Statistically significant prediction error responses to word changes were found in
newborns when deviations were presented within the nursery rhyme [40–100 ms: t(20) =
−3.32, p = .01; 130–190 ms: t(20) = −2.35, p = .03] (Table 7). Word changes to deviations
within song or prose did not elicit responses that differed significantly from zero, and
neither did acoustic changes in any stimulus type (Figs. 4 and 5).

<h>DISCUSSION</h>
----------

The current study examined whether the facilitative effect of music and rhythm on learning
from auditory input can be observed in newborn infants. Infants were presented with three
recorded versions of a nursery rhyme: one spoken metrically as a nursery rhyme, one sung
to a melody, and one read as ordinary speech. These naturalistic conditions differed by
their duration, intensity, pitch and rhythmic structure. We introduced word deviations and
acoustical feature deviations in each version, and expected the changes to elicit
prediction error responses, should the infants be able to extract predictions from the
recently learned unaltered rendition. Only the word changes in nursery rhyme condition
evoked significant prediction error responses. The responses to deviations in the nursery
rhyme condition were significantly more negative than those in the song condition and were
marginally more negative than those in the speech condition. Acoustic feature changes were
not found to elicit prediction error responses in any condition. These results suggest
that the rhythmic structure of nursery rhymes may facilitate learning from auditory input
in newborn infants and may thus help future language development. Rhythm likely acts as a
framework that allows the brain to form predictions of the future input, and aids temporal
sequencing and segmentation (Huss et al., 2011; Kotz, Schwartze, & Schmidt-Kassow, 2009;
Schön & Tillmann, 2015). The finding is supported by everyday-life experience: nursery
rhymes are recited to and with babies and toddlers in many cultures. Perhaps nursery
rhymes have always acted as naturally optimized educational auditory input to infants:
their rhythm matches their linguistic prosody, which has been found to enhance
phonological processing (Schön & Tillmann, 2015), extraction of phonological structure
(Leong & Goswami, 2015) and lyric comprehension (Gordon, Magne, & Large, 2011). In
addition, the auditory-visual synchrony present when an adult is reciting nursery rhymes
promotes heightened attention and memory in infants (Bahrick & Lickliter, 2000; Lewkowicz
& Lickliter, 2013; Lewkowicz, 2000). Previous research with adults suggests that both
music and rhythm may help learning by creating templates for future events. Surprisingly,
no such effect was found for the song condition in the current study, despite numerous
studies that have found music to be beneficial for language learning and word segmentation
(e.g. François et al., 2017; Kraus & Chandrasekaran, 2010; Putkinen, Tervaniemi, &
Huotilainen, 2013; Putkinen, Saarikivi, & Tervaniemi, 2013; Tallal & Gaab, 2006). There
are several possible accounts for this finding. First of all, it has been argued that
melody may facilitate learning by attracting, maintaining and enhancing attention. For
example, Nakata and Trehub (2004) hypothesized that short fixations associated with
maternal speech might be linked to efficient learning and information transfer, while long
fixations associated with maternal singing might be optimized to enhance interpersonal
ties. Since the participants in the current study were asleep and thus not attending to
the stimuli, the facilitating effect of the melody may have been weaker. Secondly, the
lack of learning might have been due to a ceiling effect described by Thiessen & Saffran,
2004: single salient prosody cue might have the same effect as multiple cues. This
possibility was speculated by Sambeth et al. (2008), who did not find a difference in
infants’ responses when comparing singing and continuous speech. However, this would not
explain why the nursery rhyme and the song conditions did not have similar effect.
Thirdly, learning both the segmental (phonetic) and supra-segmental (melodic and/or
rhythmic) patterns simultaneously from multi-dimensional signal such as a lyrical song
might be more difficult for the newborn infants than learning only the segmental patterns.
A previous study by Lebedeva and Kuhl (2010) found that melody facilitated phonetic
recognition in 10-month-olds, but preliminary tests in 8-month-olds showed no difference
between melodies or spoken strings. Music does contain additional information compared to
nursery rhyme, so it is feasible that infants would use some of their cognitive resources
to learn the melodic patterns when mapping of linguistic and musical information is not
consistent, as in our song condition. Finally, the pattern of findings may suggest that
stronger rhythmic structure of the nursery rhyme condition helps infants with
probabilistic inference of words, and thus facilitates learning. Younger infants appear to
segment speech stimuli based on probabilities and start to prefer prosodic cues only
around eight months of age; possibly because they start to lose sensitivity to non-native
contrasts (Johnson & Jusczyk, 2001; Thiessen & Saffran, 2007; Yeung & Werker, 2009). Our
results support the previous findings from infants suggesting that exaggerated or variable
pitch information within signal can facilitate phonetic recognition (Bergeson & Trehub,
2007; Lebedeva & Kuhl, 2010; Thiessen, Hill, & Saffran, 2005). As Tables 3 and 4 and Figs.
2 and 3 show, the current nursery rhyme stimuli, which led to the successful detection of
word changes, had more pitch variation than the song or speech stimuli. It seems that
pitch modulations might facilitate word segmentation as François et al. (2017) suggested,
but here they were more pronounced in the nursery rhyme than the song. The difference in
our and François’ and colleagues’ results might be due to us using a simple melody, that
did not match well with word-stress pattern, whereas they had associated each syllable to
a unique pitch. In line with François et al., we suggest that an exaggerated prosodic cue,
such as pitch change, increases the saliency of to-be-learned item. What the present
results add to those by François and colleagues is that the regular rhythmic patterns of
the input, as introduced by the current nursery rhyme, seem to synchronize the auditory
processing and to facilitate the prediction of the following items. This would also be in
line with Goswami (2018) oscillatory temporal sampling framework. Perhaps the stronger
frequency modulation and periodic power in the stressed syllable modulation tier in
nursery rhyme stimuli lead to more efficient phase entrainment of neuronal oscillations in
the auditory cortex, and thus more accurate temporal sampling of stressed syllables and
more efficient learning. The song condition had higher periodic power in syllable
modulation tier, which also suggests that while there was rhythmic regularity in the song
stimulus, the stressed syllables were not as salient in the song condition as in the
nursery rhyme condition. The present study is one of a few in which infants were presented
with continuous speech. Thus, the natural stimuli are highly complex and acoustically not
very well controlled. As follows, the current findings should be considered with some
caution. When interpreting the results, it is good to keep in mind that infants’ brain
responses are characterized by remarkable variability, the reasons of which are not yet
fully understood. All conditions elicited positive responses in some infants, and negative
responses in some other infants. The same phenomenon has been previously observed in
traditional oddball paradigms (reviewed in Näätänen, Sussman, Salisbury, & Shafer, 2014)
and also when infants have been exposed to the statistical auditory streams (Bosseler,
Teinonen, Tervaniemi, & Huotilainen, 2016; Teinonen et al., 2009). In some conditions,
these different response patterns may have cancelled each other out in averaging. Such
variability might account for not observing significant responses to acoustic changes that
typically elicit quite robust responses. In addition, the lack of significant responses
may be caused by the use of continuous stimuli, the learning of which is expected to be
more challenging than that of traditional oddball streams with simple acoustic deviations.
Given the promising results, it would be valuable to replicate this study with a larger
participant sample and continuous but more controlled stimuli. In the future, it would
also be interesting to complement this study by exploring which factors in music and
rhythm promote learning across different developmental stages. It might be that the
effects of music and rhythms interact with effective attention allocation, and prediction
errors would be associated with redirecting attention (Ylinen et al., 2017).
Alternatively, language experience and developmental changes might be required before an
infant can differentially attend to phonetic and melody information.

<h>CONCLUSION</h>
----------

Our findings suggest that rhythmic structure of nursery rhymes may facilitate newborn
infants’ learning from auditory input and may thus be beneficial to language development.
Surprisingly, no such effect was found for a song in the present stimuli. This might be
due to melody not including enough pitch variation, or simultaneous learning of the melody
and phonetic content being more challenging to newborn infants than that of the phonetic
content alone. In line with previous behavioral IDS studies (Curtin, Campbell, & Hufnagle,
2012; Spinelli, Fasolo, & Mesman, 2017), it seems that simultaneous occurrence of
exaggerated prosodic cues and to-be-learned items helps infants to process language input.
This could be taken into consideration for example when planning activities and
interactions at home, music playschools, or when making educational music: linguistic and
musical rhythm should maintain synchrony.

<h>AUTHOR CONTRIBUTIONS STATEMENT</h>
------------------------------

S.Y. and M.H. designed research; S.Y. and E.S. performed research, E.S. analyzed data; and
E.S., M.H., and S.Y. wrote the paper.


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<ART>Saving energy in the workplace: Why, and for whom?
==================================================

Authors: Caroline Leygue, Eamonn Ferguson, Alexa Spence
DOI: 10.1016/j.jenvp.2017.06.006
Year: 2017  |  Pages: 50-62
ASJC codes: 3202, 3207
Keywords: Altruism, Energy saving, Motivations, Organizational behavior

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Saving energy at work might be considered altruistic, because often no personal benefits accrue. However, we consider the possibility that it can be a form of impure-altruism in that the individual experiences some rewards. We develop a scale to measure motivations to save energy at work and test its predictive power for energy-saving intentions and sustainable choices. In two studies (N = 293 and N = 94) motivations towards helping their organization and the planet were rated as important motivations, as was warm-glow (feeling good), indicating that impure-altruism does exist in this context. Energy saving was predicted by environmental concern and the desire to help one's organization. Notably, the stronger the motivations to promote one's reputation were, the weaker was the intention to save energy. Promoting motivations, particularly those that focus on benefits to the organization, may be an effective addition to environmental messages typically used as motivations in campaigns.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

To help prevent damage to the environment due to climate change, the UN set a target to
keep the earth's temperature rise to well below 2° Celsius above preindustrial levels
within the Paris Agreement (UNFCCC, 2015). Within this, the EU has proposed to reduce its
emissions to 40% below 1990 levels by 2030 (European Commission, 2012). Given pressures of
climate change, energy security and affordability, there is an increasing interest across
sectors in how to change current energy use. One key area of behavior change in this
context is people's energy use behavior in non-domestic buildings (Janda, 2011; Schelly,
Cross, Franzen, Hall, & Reeve, 2011; Schipper, Bartlett, & Hawk, 1989). It has been
suggested that around 33% of greenhouse gas emissions in the UK and 17% in the US are
released from shared buildings within the business sector (non-industrial) (DECC, 2011;
United States Department of State, 2010). Current advances on reducing energy use in
workplaces has mostly focused on improving physical infrastructure, appliances, system
efficiency, or appointing key personnel with energy responsibilities (e.g., facilities
managers, eco-champions) (Aragón-Correa, Matías-Reche, & Senise-Barrio, 2004; Christmann,
2000; Cordano & Frieze, 2000). There has been little investigation of how to encourage
normal, individual workers (with no energy responsibilities) to change their own energy
use behavior to reduce emissions. This gap in the literature is the focus of this paper.
Since energy use is not an element of most employees' job assignments, and is usually not
taken into account in performance evaluations, it might be argued that people simply will
not care about, or act to save energy. The extent to which employees will try to reduce
their energy use might depend on a number of motivations including if they see it as a key
aim of their job (Rioux & Penner, 2001) or if they are motivated by more proactive
prosocial behavior among employees, such as organizational citizenship behavior
(Nisiforou, Poullis, & Charalambides, 2012; Schelly et al., 2011). The aim of the present
research is to investigate what motivates employees to reduce their energy use at work
when their job specifications do not include it. Indeed, energy saving can be considered
an “extra-role” behavior (Ramus & Killmer, 2007) or an example of organizational
citizenship behavior, as for the individual it is not normally directly or explicitly
rewarded, but collectively is positive for the organization (LePine, Erez, & Johnson,
2002; Organ, 1997).

<hs>  Promotion of energy saving among employees</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Existing research on environmental behavior in the workplace shows that employees can be
encouraged to adopt energy saving behaviors (Lo, Peters, & Kok, 2012). Using the Theory of
Planned Behavior (TPB, see Ajzen, 1991), Greaves et al. (Greaves, Zibarras, & Stride,
2013) found that, in general, employees intended to turn off their computers when they
left their desk for 1 h or more, and particularly if they think switching things off is a
good thing (notably for the environment), and if the social norms of the workplace fit
this behavior (see also Zhang, Wang, & Zhou, 2014). Goal setting has also proven an
effective intervention (McCalley & Midden, 2002), as well as the use of rewards,
(Handgraaf, Van Lidth de Jeude, & Appelt, 2013), individual feedback (Murtagh et al.,
2013), group discussions (Werner, Cook, Colby, & Lim, 2012), and group feedback and peer
education (Carrico & Riemer, 2011). We highlight that, to date, the purpose of energy
saving in the workplace, that is for what or for whom employees would save energy, has not
been studied as a precursor of energy saving intentions. Importantly, research indicates
that to change (environmental) behavior, via any intervention or a communication, the goal
[of the behavior] promoted by the intervention must be activated (Unsworth, Dmitrieva, &
Adriasola, 2013). This gap in the existing literature indicates that previous research and
applied interventions may therefore have miscommunicated energy savings in ignoring the
reasons that employees may have for saving energy. We adopt a functional approach as we
are interested in identifying the goal(s) which energy saving behavior helps to fulfill
(Snyder, 1993). We want to investigate whether saving energy in the workplace can have
multiple functions. Indeed people could, for example, have the goal to help their
organization, and saving energy could have the function to help attain this goal. Other
goals could include feeling good about themselves (warm-glow), gain reputation as a good
person or just because no-one else does (reluctant altruism; Ferguson, 2015). In this,
saving energy in the workplace could have multiple functions for different people or even
multiple functions for the same person. We want to look at various potential motivations
to save energy and investigate their importance, as these could be drivers, to different
degrees, to adopt energy saving behaviors in the workplace.

<hs>  Motivations to save energy in the workplace</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Many studies focusing on interventions to reduce energy in the workplace do not specify
the reason or goal they used to encourage people to reduce their energy use (Carrico &
Riemer, 2011; Handgraaf et al., 2013; Staats, Leeuwen, & Wit, 2000) and indeed a lack of
motivation has been highlighted in some instances (Murtagh et al., 2013). Whilst
motivations to save energy often differ between individuals/user groups, determining
commonalities would help to highlight the most effective ways to frame energy saving
campaigns in different contexts. For example, cost is often a key motivation for users to
save energy in residential contexts (Brandon & Lewis, 1999; Spence, Demski, Butler,
Parkhill, & Pidgeon, 2017), and is often used to encourage people to save energy in
behavioral interventions (Abrahamse, Steg, Vlek, & Rothengatter, 2005, 2007; Midden,
Meter, Weenig, & Zieverink, 1983). However, research suggests that cost savings are often
so low at the individual level that consumers may not consider behavior change worthwhile
(Spence, Leygue, Bedwell, & O'Malley, 2014). In the workplace, for most workers or
employees, saving electricity does not mean saving costs for oneself, as is the case for
domestic use. Hence referring to energy in terms of costs might have a weaker impact on
motivations in the workplace and other aspects of energy use may have a broader impact. On
the other hand, cost saving potential as a collective may be much greater and motivating.
In fact this technique of aggregating energy savings at the group level has been used
successfully before, where university staff and students were told how much energy and
costs in total would be saved if all the classrooms' lights were turned off every day.
Though, we note this was not compared to other methods of calculating savings, e.g. in
terms of carbon or non-aggregated (Werner et al., 2012). There is currently little
evidence about whether, and how, motivations to save energy in the workplace context do
differ from a residential context. Given the lack of cost incentive in the workplace,
current research and interventions aiming at reducing the energy use of employees has
mostly focused on the benefits of this behavior for the environment (Scherbaum, Popovich,
& Finlinson, 2008; Unsworth et al., 2013) which may not capture the whole spectrum of
motivations involved. One reason for this is that sometimes energy saving behavior is
studied as one of several environmental behaviors (Bamberg & Möser, 2007; Lo et al.,
2012). However, we propose that reducing one's energy use in the workplace could serve
other functions and fulfill different goals other than environmental concern. Most people
acknowledge the problems associated with climate change (Spence, Venables, Pidgeon,
Poortinga, & Demski, 2010), but only a smaller proportion tend to feel they must or can do
something to reduce it (Spence et al., 2010; Whitmarsh, Seyfang, & O'Neill, 2011).
Targeting goals other than concern for the environment may therefore be useful in engaging
every employee with saving energy in the workplace. We identify a number of theoretically
relevant domains of motivation below.

<hs>  Pure, impure, reluctant altruistic, and selfish motivations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

At the organizational level, “corporate greening” has already been conceptualized as a
pro-social behavior (Ramus & Killmer, 2007). At the individual level, given that most
workplaces do not currently recognize or reward their employees for adopting energy saving
behaviors, motivations to save energy at work may be mostly considered, at least in part,
other-oriented or altruistic (Ramus & Killmer, 2007). Altruism is defined as a desire to
maximize the welfare of others (e.g., by reducing their suffering) at a personal cost,
without personal benefit (Andreoni, 1990; Ferguson & Lawrence, 2016). Indeed, saving
energy for environmental reasons (i.e., to reduce carbon emissions) can be considered as
an altruistic act, as the benefits will mostly affect others (e.g., the planet, future
generations), while it will be costly to the individual (time, effort) (Sober & Wilson,
1998). Saving energy in the workplace could also be considered an altruistic act towards
one's company. Employees might want to help their company reduce its energy costs by
reducing their own energy use (Werner et al., 2012). In addition, helping their company
reduce their energy use and its impact on the environment might help it increase or obtain
a positive public image. Indeed, a survey of 8000 consumers in the United States revealed
that 80% of high education/high income people would change brand if a company was
negatively portrayed by the media on their social responsibility, and sustainability is
now an important factor within corporate social responsibility (ACCA, 2004; DEFRA, 2006).
This of course, should depend on the extent to which employees feel positive towards their
company and their job, so should be affected by the organization's culture, and employees'
commitment and identification towards the organization (Allen & Meyer, 1990; Mael &
Ashforth, 1992). However, if a company is benefited through reduced costs or improved
public image, an employee could feasibly indirectly benefit through the improvement in
company status, e.g. with increased job security, or a potential increase in
opportunities, so motivations here may not be purely altruistic. Finally, by helping their
company's (green) image the employee will also be able to indirectly enhance their self-
image as one working for a ‘green’ company. So by improving the organization's image the
employee enhances their own positive image. This is an aspect of impure altruism as the
‘helper’ helps the target and might indirectly benefit themselves as well (Andreoni, 1990;
Griskevicius, Tybur, & Van den Bergh, 2010). Research in pro-social behavior more
generally, has shown that pro-social actions can also often be personally beneficial
(Clary et al., 1998; Ferguson, Farrell, & Lawrence, 2008). Indeed, behaviors often
considered as purely altruistic, such as donating blood, also often result in people
feeling good about themselves for doing the right thing (Ferguson, 2015; Ferguson, Atsma,
De Kort, & Veldhuizen, 2012), an effect called warm-glow resulting in impure altruism as
both the donor and recipient gain (Andreoni, 1990). As well as being experienced at the
time of donation, it is possible that warm-glow can be an ‘anticipated’ motivation for
action (Ferguson & Masser, 2017). Furthermore, in the specific context of the workplace,
other self-oriented motivations can exist for ‘altruistic’ acts, again leading to impure
altruistic motivations. For example, doing the right thing at work can be a way of
obtaining approval from management and colleagues, as it could be viewed as a “taking
charge” behavior (Ramus & Killmer, 2007). Indeed, impression management is a strong
predictor of positive behaviors in the workplace that go beyond one's job description
(Rioux & Penner, 2001). Finally, altruistic acts can be performed when people think the
cause is worthy and think others are unwilling to act (i.e., others are free riders). This
form of reluctant altruism was first identified and described by Ferguson and colleagues,
in the context of blood donations for first-time donors in the face of free-riding
(Ferguson et al., 2012). Lack of trust in others to help, moral outrage and negative view
of humanity are all facets of reluctant altruism (Ferguson & Masser, 2017; Ferguson, 2015)
however in the context of saving energy at work lack of trust was the key parameter we
focussed on. People then feel the energy to act because of negative feelings and lack of
trust towards others who do not make any effort. So reluctant altruism-lack of trust could
be an important motivator for prosocial behavior when free riding is high, as is likely to
be the case in energy conservation in the workplace.

<hs>  Current research</hs>
  ~~~~~~~~~~~~~~~~

We propose that saving energy in the workplace can have multiple functions or utilities,
and so is a benevolent act, or an example of impure altruism, where both other-oriented
and self-oriented motivations exist. Specifically, we want to investigate whether
employees can be motivated to save energy by two forms of altruism or other-oriented
motivations: environmental concern and helping their organization without benefit to the
self (direct or indirect), and two forms of self-oriented motivations: warm glow and
reputation building. We are also interested in consistency between contexts, and whether
energy saving functions at work could translate to goals at home, and so if we could find
similar motivations to save energy at home. If this is the case, motivations at work and
at home should be related. Furthermore, we are interested in whether these motivations
will have independent effects on energy saving behaviors. Also, we postulate that the
extent to which people are motivated to save energy at work and intend to do so, should
depend on their general attitude towards their workplace; the more they evaluate their job
and their organization positively, the more they should be motivated to reduce their
energy use to help their organization, and the more they should try to adopt sustainable
behaviors. We propose that motivations identified may mediate the relationship between
attitude towards the workplace and energy saving intentions. Finally, we expect that these
motivations should affect how people make sustainable choices in the workplace. In two
studies, we measured motivations to save energy at work within five different
organizations (N = 298 for Study 1 and N = 94 for Study 2): one private company (N = 75)
and one academic institution (N = 218, 5 participants left this question blank) in Study
1; and two private companies and one non-government organization (NGO) in Study 2. We
developed a scale of Motivations to save Energy in the Workplace (MEW) based on existing
scales of motivations to volunteer, to donate blood, and to engage in citizen
organizational behavior as well as theoretical considerations of self- and other-
orientated motivations. There are important similarities between each of these behaviors
and energy saving behavior at work: there is no direct benefit to the self, the
beneficiaries are not people that are close to the actor, there is no obligation for the
actor to perform these behaviors (Ferguson, 2015), and these behaviors need to be
prolonged or repeated to be most effective at a communal level. We tested the predictive
validity of the scale by exploring the relations between motivations identified for saving
energy, reported energy saving intentions in the workplace, attitude towards the
workplace, and motivations to save energy at home. In a second study among a different
sample, we explored the effects of these motivations on a more comprehensive measure of
intentions to save energy, and direct sustainable choices.

<hs>  Scale development</hs>
  ~~~~~~~~~~~~~~~~~

Based on the literature on altruistic behaviors such as blood donation, volunteering and
citizen behavior (see above), we created an initial set of 28 items for the scale1. We
distributed this scale in two business sites to measure the importance of each motivation,
and the factor structure and validity of the scale were examined, as well as basic
psychometric properties. To explore the antecedents and consequences of these energy
saving motivations in the workplace, we included measures of general attitudes towards the
workplace, and a scale measuring the self-reported frequency of environmental behaviors at
work. In addition, we were interested in knowing whether motivations to save energy in the
workplace would help predict sustainable choices. To test this, we conducted a second
study to look at energy saving motivations, and we examined whether they would predict how
people would spend money from and for their organization. We hypothesized the more people
would be motivated to save energy at work, the more money they would choose to spend on
sustainable products for their company.

        <hss>Participants</hss>

        To recruit participants, we contacted “gatekeepers” to ask for permission to
        advertise the study and use internal mailing lists to recruit volunteers to
        participate in a study on energy use at work in two sites: a large private company
        and a university in the United Kingdom. Both companies had organized campaigns on
        sustainability in the past (e.g., cycle to work) but no campaign on energy was
        taking place at the time of the study. The large private company was represented
        by one gatekeeper, at the university there were multiple gatekeepers as all
        academic and administrative departments were contacted. Exact response rate cannot
        be evaluated here as it is unclear how many gatekeepers agreed to advertise the
        study and how (e.g., send emails to a mailing list or advertise on the intranet
        “message of the day”). Both the private company and the university total together
        approximately 10,000 employees. Questionnaires were filled in online using
        Qualtrics Research Suite©2 (Qualtrics, 2015). The incentive to take part was
        entrance into a prize draw to win one of five £10 (Sterling) (15.26 USD) shopping
        vouchers. Two hundred and ninety eight participants (198 women and 100 men) took
        part in the study. Their ages ranged from 18 to 65, (M = 39.64, SD = 10.8).
        Thirty-five percent of this sample had managerial responsibilities at the time of
        the study. Just under half of the participants (47.7%) had a postgraduate
        qualification, 29.2% had a degree or equivalent, 15.5% a high school
        qualification. This sample consisted of more women and was more highly educated
        than the general population in the UK when compared to the most recently available
        data obtained from the Labor Force Survey in 2006. Participants had been working
        in their current organization for an average of 7.74 years.

        <hss>Motivations to save energy</hss>

        We constructed 28 items to measures people's motivations to save energy at work.
        Items were statements adapted from scales of motivations to donate blood (Evans &
        Ferguson, 2014; Ferguson et al., 2008), motivations to volunteer (Clary et al.,
        1998; Snyder, 1993), and motivations to adopt organizational citizenship behavior
        (Rioux & Penner, 2001). Participants had to rate each statement about why they
        save energy such as “to help my organization save money on energy costs” or
        “because I'd feel proud of myself” on a 7-point scale according to how important
        each would be in their decision to save energy in the workplace. We constructed 25
        items to measure people's motivations to save energy at home following the same
        process as for motivations to save energy in the workplace, e.g., items included,
        “to save money on energy costs” and “because I feel worried about the
        environment”. Isomorphism between the items at work and at home was ensured by
        using the same items when possible or changing only one word (e.g., replacing “my
        colleagues” by “my friends”). Three items were specific to the workplace and the
        organization's image and were not adapted to the home context.

        <hss>Behavioral intentions at work</hss>

        Environmental behavior intentions at work were measured by 14 items adapted from
        Whitmarsh and O'Neill (2010), see Appendix 1. Participants had to rate each
        behavior on how likely they would consider performing them on a scale from 1-very
        unlikely to 4-very likely, with a non-applicable option also provided. Cronbach's
        α = 0.73 for environmental intentions in general, and Cronbach's α = 0.65 for
        energy saving intentions, after eliminating one item: “use an extra electric
        heater” which did not cohere with other behaviors included. Reliability indexes
        were lower than expected here (for example, Whitmarsh and O'Neill obtained a
        Cronbach's α of 0.92). This could be due to the fact that less items were used
        here (as the context of a workplace offers less examples of sustainable behaviors
        than the home). Also, people tend to have less control over their environmental
        behaviors and their energy use in the workplace compared to the home, and this
        could result in more variability between which behaviors can be adopted or not and
        how frequently.

        <hss>General attitude towards the workplace</hss>

        We measured participants' general attitude towards their workplace by asking them
        about their job satisfaction (Hackman & Oldham, 1975), their commitment to the
        organization (Allen & Meyer, 1990), and their organizational identification (Mael
        & Ashforth, 1992). Job satisfaction was measured by 3 items (e.g., Generally
        speaking, I am very satisfied with this job) (Cronbach's α = 0.88 if one item is
        removed), commitment to the organization by 5 items (e.g., this organization has a
        great deal of personal meaning for me) (Cronbach's α = 0.83), and organizational
        identification by 6 items (e.g., When I talk about this organization, I usually
        say “we” rather than “they”) (Cronbach's α = 0.91). Participants had to rate each
        item on a 7 point scale from 1-strongly disagree to 7-strongly agree.

        <hss>Motivations to save energy at work</hss>

        Given that the present study is the first investigation of multiple motivations to
        save energy at work, we conducted an exploratory factor analysis on participants’
        responses to the scale using Mplus 6 statistical software (Muthen & Muthen,
        1998–2010). We used an MLR estimation3 as the scale contained 7 points. Results
        show that the best model is a structure of 6 factors for motivations to save
        energy at work, χ2 = 410.99, df = 204, p = 0.0001, CFI = 0.941 and TLI = 0.899,
        RMSEA = 0.058. These values of CFI and RMSEA are close respectively to the values
        of 0.95 and 0.06 that are recommended by Hu and Bentler (Hu & Bentler, 1999).
        Comparative indices for a structure with 5 factors were not as good, χ2 = 539.53,
        df = 226, p = 0.0001, CFI = 0.911 and TLI = 0.862, RMSEA = 0.068 and the Satorra-
        Bentler scaled chi-square difference test reveals that the difference between the
        two models is significant, TRd = 127.04, df = 22, p < 0.001 with the 6 factor a
        better fit (Satorra & Bentler, 2001). A structure with 7 factors did not improve
        the indices, χ2 = 427.74, df = 183, p = 0.0001, CFI = 0.931 and TLI = 0.867, RMSEA
        = 0.067 though the Satorra-Bentler scaled chi-square difference test reveals that
        the difference between the two models is not significant, TRd = 29.57, df = 21, p
        = 0.10. Environmental concern, warm glow and reputation building at work were
        found to be distinct motivations to save energy in the workplace, see Table 1. In
        addition to this, two further factors were identified. A factor that represents
        reluctant altruism was obtained, and altruism towards the company separated into
        two distinct factors: helping one's organization's finances and helping one's
        organization's image. We note that the factor concerning helping one's
        organization's finances contains only two items and that this is often considered
        as problematic. However, in this case the items are homogeneous and have face
        validity. Therefore the issues usually encountered with a low number of indicators
        should not be encountered (Gardner, Cummings, Dunham, & Pierce, 1998; Little,
        Lindenberger, & Nesselroade, 1999; Wanous, Reichers, & Hudy, 1997). The average
        correlation across factors identified was 0.33. Mean levels of reported importance
        were calculated for each factor and a repeated measures ANOVA, F(5, 285) = 171.85,
        p = 0.0001, η2 = 0.37, and post-hoc tests (Bonferroni adjusted) indicated that
        environmental concern (M = 4.89, SD = 1.54), helping one's organization's finances
        (M = 4.74, SD = 1.63), and warm-glow (M = 4.55, SD = 1.47), were considered the
        most important motivations to save energy in the workplace followed by helping
        one's organization's image (M = 4.04, SD = 1.62) and reluctant altruism-lack of
        trust (M = 3.72, SD = 1.53). Reputation building at work was not considered an
        important motivation (M = 2.3, SD = 0.99). If we look at both sites separately,
        the pattern is approximately the same, with participants in the private company
        scoring higher on motivations in general than participants at the university, F(1,
        288) = 6.57, p = 0.01, η2 = 0.02, for the main effect of the type of site. We
        observe an interaction effect between site and type of motivation, F(5, 284) =
        2.84, p = 0.01, η2 = 0.01, and post-hoc tests (Bonferroni adjusted) reveal that
        helping one's organization's image was rated as a more important factor in saving
        energy in the private company (M = 4.11, SD = 1.69) than in the university (M =
        3.5, SD = 1.54), t(293) = −2.97, p = 0.003; the other types of motivations did not
        differ significantly between sites, see Fig. 1.

        <hss>Motivations to save energy at home</hss>

        Responses to the motivations to save energy at home scale, were examined in the
        same way as in the workplace. Results show that the best model is a structure of 5
        factors, χ2 = 373.8, df = 205, p = 0.0001, CFI = 0.95, TLI = 0.92, and RMSEA =
        0.053. The indices for a structure with 4 factors were not as good, χ2 = 536.97,
        df = 227, p = 0.0001, CFI = 0.91, TLI = 0.87, and RMSEA = 0.069. The Satorra-
        Bentler scaled chi-square difference test reveals that the difference between the
        two models is significant, TRd = 185.41, df = 22, p < 0.001, with the 5 factor a
        better fit. A structure with 6 factors slightly improved one index, χ2 = 338.24,
        df = 184, p < 0.001, CFI = 0.95 and TLI = 0.92, RMSEA = 0.054 and the Satorra-
        Bentler scaled chi-square difference test reveals that the difference between the
        two models is significant, TRd = 37.25, df = 21, p = 0.02. However the 6th factor
        did not contain any clear and unique items, with rotated loadings all inferior to
        0.40 or loading equally on 2 factors. Environmental concern, warm glow and
        reputation building at home emerged as distinct factors, as they did in the
        workplace context. In addition a factor that represents costs and a factor that
        represents feelings of reluctant altruism-lack of trust were also obtained, see
        Table 2. The average interscale correlation was 0.36. Mean scores calculated for
        the motivations obtained indicated that participants rated costs as the most
        important motivation for saving energy at home (M = 6.33, SD = 1.04), followed by
        environmental concern (M = 4.91, SD = 1.7), and warm glow (M = 4.42, SD = 1.61).
        Again participants disagreed that feelings of reluctant altruism (M = 3.73, SD =
        1.63) and reputation building (M = 2.32, SD = 1.14), were important motivations.
        The factor structure and the psychometric properties of the 6 subscales were
        invariant across gender and work status. Motivations at work and at home were
        consistent, see Table 3. We observe high correlations between both contexts
        regarding environmental concern motivations, r = 0.91, warm-glow motivations, r =
        0.80, reputation building, r = 0.76, and, to a lesser extent, reluctant altruism,
        r = 0.60.

        Relationship between motivations, intentions to save energy at work, and attitude towards the workplace

        To validate the utility of the motivations we identify, we examined the extent to
        which each motivation would predict intentions to adopt environmental behaviors in
        the workplace. To investigate this, we ran a regression analysis (OLS), using the
        6 types of motivations to save energy at work as predictors of environmental
        intentions at work. Results show that environmental behavior intention is
        predicted by environmental concern (B = 0.10, p = 0.001), helping one's
        organization's image (B = 0.09, p = 0.001), and reputation building (B = −0.08, p
        = 0.006). The whole model predicts 22% of the variance in environmental intentions
        at work (adjusted R2 = 0.22), see Table 4. Interestingly, the more people rate
        environmental concern and their organization's image as important motivations to
        save energy, the more they intend to adopt environmental behavior at work.
        However, the more they indicate reputation building at work as an important
        motivation, the less they intend to adopt environmental behavior. We were also
        interested in looking at energy-related behavior intentions in particular, for
        example, at work, turn off lights you're not using. To do this, we conducted a
        regression analysis using the mean score for energy related behavior intentions as
        a dependent variable and the 6 types of motivations as independent variables.
        Results reveal the same pattern; the more environmental concern (B = 0.09, p =
        0.001), and helping one's organization's image (B = 0.09, p = 0.001) are important
        motivations, the more people intend to adopt energy saving behaviors at work.
        Conversely, the more people find reputation building motivations important, the
        less they intend to adopt energy saving behaviors (B = −0.13, p = 0.001). The
        whole model explains 14% of variance in energy-related behavior intention, see
        Table 4. Bivariate correlation analyses showed that motivations related to helping
        one's organization's image and finances are correlated with the three indices of
        attitudes towards the workplace. Furthermore, environmental intentions and in
        particular energy saving intentions correlated with commitment to the organization
        and organizational identification, but not with job satisfaction, see Table 5.

        Relationship between attitude towards the workplace and energy saving intentions and the mediating role of motivations to help organizational image

        The mechanisms underlying the relationships between contextual variables at work
        and energy saving intentions are of particular interest as these could inform
        potential interventions. Hence, we conducted mediation analyses to investigate
        whether the motivations to help one's organization's image would mediate the
        effects of commitment to the organization and organizational identification on
        energy behavior intentions. To do this, we used the MEDIATE method of Hayes and
        Preacher (2014) and due to the strict assumption of normally distributed data
        within the product-of-coefficients approach to mediation, we used bootstrapping to
        resample the data 10,000 times in estimating the indirect effects.4 Results show
        that organizational identification, B = 0.32, t = 4.05, p = 0.001, and commitment
        to the organization, B = 0.37, t = 4.35, p = 0.001, have a positive effect on
        motivation to save energy to help your organization's image. Motivation to save
        energy to help your organization's image predicts energy saving intentions, B =
        0.09, t = 3.59, p = 0.001, and the indirect effects of commitment (B = 0.035, LLCI
        = 0.01, ULCI = 0.06) and identification (B = 0.03, LLCI = 0.01, ULCI = 0.05) on
        energy saving intentions are significant, see Fig. 2. Direct effects of
        organizational identification and commitment for the organization on energy
        behavior intention were both non-significant (B = 0.02, t = 0.66, p = 0.51, and B
        = 0.04, t = 1.09, p = 0.27, respectively). This pattern of results indicates that
        the effects of commitment towards the organization and organizational
        identification indirectly impact intentions to save energy in the workplace
        through motivations to help your organization's image. The results of Study 1
        reveal that intentions, both of energy saving and of further environmental
        behavior, are mostly predicted by altruistic and impure altruistic motives such as
        environmental concern and wanting to help one's organization. Interestingly, self-
        oriented motives such as wanting to improve one's image at work (reputation
        building) negatively predicted intentions to save energy. However, Study 1 focused
        on self-reports of behavior intentions, so the question of whether these
        motivations can predict actual behaviors remain. Furthermore, measuring
        sustainable behaviors directly would reduce the reverse causality possibility that
        actually measures of intentions predict motivations. So the aim of Study 2 was to
        look at the effects of motivations to save energy at work on actual sustainable
        behaviors, measured online through a choice task. Furthermore, we were interested
        in examining the extent to which the results of Study 1 would replicate when using
        a more comprehensive measure of energy behavior intentions at work, that is, a
        measure that would also include social behaviors, such as discussion of issues
        with people in charge, or confrontation of people who waste energy.

        <hss>Participants</hss>

        A total of 94 employees (66 men, 27 women, one participant preferred not to state
        their gender) took part in Study 2. An opportunity sample was drawn from three
        small to medium sized companies, with an average response rate of 37.12%. The
        three companies were two private companies, and an NGO. Age ranged from 18 to 62,
        with a mean of 31.57, and a SD of 10.66. Fifty percent of this sample had
        managerial responsibilities at the time of the study. Before filling in the
        questionnaire, participants were randomly assigned to one of 3 scenarios, where
        they had to imagine that they were working in a company that had decided to reduce
        its energy use. Scenarios were accompanied by 1 of 3 displays, one showing energy
        use in terms of CO2 emissions, one in terms of costs, and the last was a combined
        CO2 and costs display. This resulted in 32 seeing the CO2 meter, 30 seeing the
        cost meter and the remaining 31 seeing both cost and CO2 readings on the same
        meter. These were used for another study and did not affect the motivations to
        save energy scores, so will not be discussed in the present study. Participants
        filled in a scale to measure their motivations to reduce their energy use at work
        as in Study 1. In addition, they completed measures of intentions to adopt energy
        saving behaviours at work and a measure of sustainable choices5.

        <hss>Motivations to save energy</hss>

        The same scale of motivations to save energy at work was used as in Study 1,
        except for the items that had not been included in the final factors for the
        analyses (see Table 1). So the new scale comprised of 24 items that participants
        had to rate on a 7-point scale.

        <hss>Energy saving intentions</hss>

        Participants rated each of 15 energy saving behaviors (Cronbach's α = 0.89) on how
        likely they would consider performing them on a scale from 1-very unlikely to
        6-very likely, with a non-applicable option also provided. These included both
        individual behaviors e.g., “turn off communal office equipment (e.g., printer,
        copy machine, lab equipment) after using them”, and social behaviors “remind a
        colleague to switch something off to save energy”, see Appendix 2.

        <hss>Sustainable choices</hss>

        The study comprised an indirect measure of sustainable behavior: participants were
        asked in a fictitious scenario to distribute 100,000 sterling pounds into five
        purchases for their company. To do this, they were given a list of 20
        possibilities, of which two were choices that would help their company save
        energy, e.g., ensure building operates at zero-carbon emissions by using
        Microgeneration (E.g. Solar Panels).

        <hss>Motivations to save energy at work</hss>

        We computed six mean scores for each of the six motivation types as in Study 1,
        reputation building (Cronbach's α = 0.83), environmental concern (Cronbach's α =
        0.82), helping one's organization's finances (Cronbach's α = 0.88), helping one's
        organization's image (Cronbach's α = 0.86), warm glow (Cronbach's α = 0.85), and
        reluctant altruism (Cronbach's α = 0.65). The average correlation across factors
        identified was 0.48. A repeated measures ANOVA, F(5, 88) = 51.58, p = 0.0001, and
        post-hoc tests (Bonferroni) indicated that warm-glow (M = 4.43, SD = 1.36),
        environmental concern (M = 4.33, SD = 1.45), helping one's organization's image (M
        = 4.25, SD = 1.53), and helping one's organization's finances (M = 4.16, SD =
        1.64) were considered the important motivations to save energy in the workplace,
        whereas reluctant altruism (M = 3.46, SD = 1.30) and reputation building at work
        (M = 2.5, SD = 1.08) were not considered important. This pattern was not affected
        by the company the participant was from, F(2, 90) = 2.46, p = 0.09.

        <hss>Prediction of energy saving intentions</hss>

        To examine whether the results of Study 1 would replicate, we ran a regression
        analysis (OLS), using the 6 motivations to save energy at work as predictors of
        energy saving intentions at work. Results show that energy saving intention is
        predicted by environmental concern (B = 0.25, p = 0.001), helping one's
        organization's finances (B = 0.30, p = 0.001), and reputation building (B = −0.35,
        p = 0.001). The whole model predicts 49% of the variance in energy saving
        behavioral intentions at work (adjusted R2 = 0.49). The more people rate
        environmental concern and their organization's finances as important motivations
        to save energy, the more they intend to adopt environmental behavior at work. As
        in Study 1, the more they indicate reputation building at work as an important
        motivation, the less they intend to adopt environmental behavior.

        <hss>Sustainable choices</hss>

        We summed the total amount of money that each participant distributed to energy
        saving purchases for their company, then log-transformed the score. The regression
        analysis using this score as a dependent variable and the 6 motivations as
        predictors reveals the amount of money spent on sustainable options is predicted
        by environmental concern (B = 0.08, p = 0.02) and helping one's organization's
        finances (B = 0.10, p = 0.007). Reputation building only had a marginal effect, (B
        = −0.09, p = 0.05). Interestingly, again reputation building had a negative impact
        on sustainable choices.

<h>GENERAL DISCUSSION</h>
------------------

Our results provide a first exploration of motivations to save energy in the workplace and
indicate that motivations to save energy at work are different from those at home,
necessitating measures and interventions designed specifically for the workplace. Indeed,
in the home, where electricity has direct costs to the individual, saving costs was the
most important motivation. At work, helping one's company becomes an important motivation.
Our research introduces a new measure of motivations to save energy in the workplace
consisting of six factors: environmental concern, helping one's organization's finances,
warm-glow, helping one's organization's image, reluctant altruism, and reputation building
at work. However, motivations to save energy at work (MEW) indicated by our measure also
correlated with motivations to save energy at home, showing consistency in people's
rationales to save energy in different contexts. In two studies, the MEW scale showed
predictive validity in its relationships with energy behavior intentions in the workplace
and sustainable choices. Importantly we highlight that a range of motivations for saving
energy exist in the workplace, beyond environmental imperatives, and these should be
considered and taken into account when designing interventions for saving energy to ensure
that maximum engagement with employees is achieved.

<hs>  Saving energy as impure altruism</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This research is the first, to our knowledge, to explore motivations of employees to save
energy in the workplace. The cross sectional study among two large companies (public and
private) obtained comparable results in both sites. Furthermore, a second study in three
smaller sites obtained similar outcomes. Our results are in line with the literature on
other types of pro-social behaviors and show that several types of motivations to save
energy at work exist. These can be classified as self-directed: reputation building and
warm-glow, or altruistic: towards the planet (environmental motivations), towards the
organization (motivations about the company's image and finances), and finally reluctant
altruism-lack of trust (Evans & Ferguson, 2014; Ferguson, 2015). Our data indicates that
people are mostly motivated to save energy because of environmental reasons. In addition,
behavior was often motivated by helping their company, and in order to gain warm-glow
feelings. Energy savings may, therefore, often have aspects of impure altruism where
others directly benefit but the individuals themselves also benefit from their actions.
This supports previous research on pro-social behaviors, such as for example volunteering
and blood donation, that revealed both altruistic and self-oriented drivers for such
behaviors (Clary et al., 1998; Ferguson et al., 2008; Snyder, 1993). Interestingly, within
other prosocial behaviors, factor structures of motivations were found to be different to
that found here. Indeed, our reputation building factor included aspects related to
evaluation by management similar to the “career” dimension of volunteering together with
aspects related to norms or the “social” dimension of volunteering (Snyder, 1993). However
aspects related to evaluation by management and social norms also seemed to be represented
by one single “self-management” dimension within explorations of motivations to donate
blood (Ferguson et al., 2008). In addition, our motivation towards the company factor
included aspects close to identification with the organization as were found in the
motivations to adopt organizational citizenship behavior (Rioux & Penner, 2001), as well
as aspects close to the kinship dimension of blood donation. It could be the case that the
current measure mixes levels of antecedents or motivations of energy saving intentions,
and further research should try to draw out the causal sequence in the development of
these motivations. Study 2 did not allow for a confirmatory factor analysis (given the low
sample size), however the reliability analyses seemed to indicate that the 6-factor
structure fitted the data of study 2 as well. Future research should aim at testing this
6-factor structure in large samples.

<hs>  Motivations to save energy in the workplace</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The different motivational factors to save energy at work identified here correlated
relatively highly with each other, indicating that promoting one or fulfilling a specific
motivation should not weaken another one. Also, self-oriented motivations did correlate
with more altruistic ones, e.g. reputation building motivations correlated with helping
your organization's image. Indeed, it is logical that a positive image of your
organization could reflect positively on yourself, especially if people identify highly
with their organization. Warm-glow motivations also correlated highly with environmental
concern motivations, both in the workplace and at home. This is in line with recent work
which considers environmental concern as both self-interested and pro-social (Bamberg &
Möser, 2007) and work on self-serving goals and biospheric goals in saving energy
(Bolderdijk, Steg, Geller, Lehman, & Postmes, 2013). Bolderdjik and colleagues explain
that people want to maintain a “positive self-concept” and prefer presenting themselves
and/or seeing themselves as “green” rather than “greedy”, implying that environmental
concern could also have a self-oriented function. In our present study, warm-glow also
correlated highly with motivations to help one's organization.

<hs>  Predictive validity of motivations to save energy in the workplace</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Altruistic motivations were the most important in our sample and were the best predictor
of intentions to save energy at work across Study 1 and 2, and more broadly to adopt
environmental behaviors in the workplace in Study 1. Whilst self-serving motivations were
also important, reputation building motivations specifically were considered less
important and actually negatively predicted energy saving intentions in both studies,
using various measures of behavior intentions and actual behaviors. This might mean that
people might not consider energy saving as something that would be recognized as a
positive workplace behavior at the present time, or that it would not encourage them to do
so even if it was; perhaps because it detracts, or is perceived to distract, from the main
focus of their work. Indeed, this tendency of considering that saving energy in the
workplace would not be done for reputation building or impression management, has been
previously found for other organizational citizenship behaviors (Bolino, 1999; Dalal,
2005). Alternatively, people might think that saving electricity at work would hurt their
reputation, as “do-gooders” are sometimes evaluated negatively by others. Indeed, people
are then reminded that they are not doing the right thing themselves, and fear reproach
(Minson & Monin, 2012; Rothgerber, 2014). Future research should explore potential
explanations and variations of reputation building motivations between contexts. Whilst
warm-glow was rated as an important motivation for people to save energy at work, it did
not demonstrate predictive power for behavior intentions. This might be due to high
correlations with the two main predictors of intentions: environmental concern and helping
one's organization's image. Interestingly, reputation building motivations and warm glow
motivations are both self-orientated but differ in the notion that one could be
experienced as intrinsic (warm-glow), the other extrinsic (reputation building), hence
demand characteristics might affect these in a different way. A comparable pattern of
results was found by Zhang and colleagues (Zhang et al., 2014) on the prediction of
attitudes towards electricity saving among office workers in China. They explored
attitudinal beliefs rather than motivations to save energy and obtained a similar pattern
of environmental benefits, organizational benefits and enjoyment (due to energy saving)
having a positive effect on attitude, with anticipated extrinsic benefits to the self
having little effect. It would be interesting to explore whether the negative effects of
reputation building promotion on behavioral intentions are also due to the extrinsic focus
of this motivation. Both results show that neither the belief that you will get a reward,
nor the goal to save energy to obtain a reward (both extrinsic focused), seem to encourage
energy saving behaviors in the workplace, whereas intrinsic focused motivations
(environmental aims and warm glow/enjoyment) appear to be more successful. Notably,
motivations to save energy in the workplace measured by our scale predict sustainable
choices. We found that the more people found warm-glow motivations important, the more
they wanted to participate in a second study on sustainability. We also found some
preliminary evidence that environmental concern and motivations to enhance the company's
image predict sustainable choices in financial decisions in the workplace.

<hs>  Organizational factors relating to motivations for energy saving in the workplace</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our data indicated that the more people are committed to their company, and the more they
identify with it, the more motivations to help their company's image are important for
them and the more, in turn, they intend to save energy at work. Energy saving in the
workplace can hence be considered as an organizational citizenship behavior, as it is not
normally specifically required, demands some extra effort, and correlates with commitment
and identification. Interestingly, commitment and identification here had a positive
effect on energy saving intentions when looked at individually (see similar findings from
Feather & Rauter, 2004), but this effect disappeared when tested together. Their effect on
behavior intentions is likely to be due to their common variance that could stem from
general positive affect in, or positive attitude towards, the workplace (Bissing-Olson,
Iyer, Fielding, & Zacher, 2013). These results show that energy savings in organizations
can be promoted and increased through schemes focused on commitment and identification in
the workplace as well as those targeted at more general well-being in the workplace. We
highlight that motivations to save energy to help one's organization were only partially
predicted by identification and commitment, so other organizational aspects that can
affect this motivation should be explored in further research. Notably and in contrast,
environmental motivations were only partly related to perceived contextual factors in the
workplace (low correlations with organizational identification and no significant
relationship with measures of commitment and satisfaction), highlighting that this is a
universal factor that is not dependent on workplace context.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

Our study used self-reports of behavior preferences and intentions rather than actual
energy use, and these are not always well aligned with actual behavior. In particular,
energy use is difficult to monitor and to control for individuals, so intentions to reduce
energy may diverge somewhat from actual energy use. In Study 2, sustainable choices were
used to look at consistency, but this measure could also be considered as cooperative
behavior towards the organization. However, Study 2 provided data on actual sustainable
choices that replicated the model found in Study 1, indicating that the same model can be
found when not using self-reports of behavior intentions. Self-reports of the importance
of the motivations may also be subject to social desirability. Notably, reputation
building motivations are likely to vary according to the context of the organization,
notably the priorities of that organization. We also note that altruistic vs self-oriented
goals and motivations can be particularly affected by impression management and self-
deceptive enhancement, as people may be reluctant to admit to certain “selfish”
orientations. An interesting further study would be to see how participants react to
reputation building motivations in the real world, and to look at real reactions to
communications or larger scale interventions rewarding energy saving at work. Finally, we
note that whilst we used a large sample of participants, this sample was not nationally
representative of the UK population. Our sample in Study 1 was drawn from a sample of
university staff and one large private company, and in Study 2 from 3 smaller companies.
Also, the two studies differed in their gender proportions, with study 1 including more
women and study 2 more men. These might have had an impact on our results as men and women
can differ on their thoughts regarding climate change (McCright, 2010; Whitmarsh, 2011).
Furthermore, our two study samples may have distinct characteristics, e.g. more positive
views of their workplace, which could have influenced their motivations. Finally,
respondents may be more altruistic than others, given that they were willing to help with
this research. Our two studies also differed in the type of organizations they were taking
place in, representing different types (e.g., for profit vs not for profit, private vs
public), sizes, cultures and possibly attitude and behavior towards sustainability. These
characteristics should be investigated in future research using larger, more
representative samples, or in case studies that would investigate systematically the
motivations in a single site (Tudor, Barr, & Gilg, 2008).

<hs>  Practical implications</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Our study reveals that various motivations to save energy exist in the workplace, so
communications and interventions to save energy in the workplace should take people's
personal motivations into account as impacts of interventions are stronger if the type of
communication matches the individual's motivations (Shavitt & Nelson, 2002; Unsworth et
al., 2013). Indeed, there is a “congruency” effect of motivations and campaigns that Clary
and colleagues found for volunteering (Clary et al., 1998), that was also observed within
literature on attitude functions (Shavitt & Nelson, 2002). Their studies showed that
campaigns to promote volunteering were evaluated more positively if they were congruent
with participants' motivations to volunteer. Furthermore, communications may result in
being inefficient or even counterproductive if they focus on the wrong motivations.
Indeed, it seems that reputation building motivations, and hence direct reputation
building rewards, to save energy at work, could make people less willing to try to save
energy. Further research should test this idea with interventions that go beyond simple
text communications, as interventions that combine approaches, e.g. text communications
alongside policy or structural changes, are usually found to be more impactful (Michie,
van Stralen, & West, 2011; Spence & Pidgeon, 2009). Campaigns to save energy could
usefully focus on integrating various motivations and goals within company policies, in
particular to reduce the negative findings that people are less likely to be sustainable
if motivated by reputation building. More research is necessary to explore why this is the
case. It could be that such extrinsic motives would impair motivations if they are already
internalized (Deci, Koestner, & Ryan, 1999), or that saving energy could be perceived as
actually bad for one's reputation. For example, interventions could help increase the
reputation of people who save energy, for example by clarifying the importance of energy
saving for the company, while not insisting on its moral dimension (Minson & Monin, 2012),
and making energy saving action more visible (Griskevicius et al., 2010). Alternatively it
may be possible to utilize feedback on how environmental actions can help an organizations
image, in order to encourage energy saving behavior without creating specific goals that
could be perceived to be in conflict with work performance goals (Unsworth et al., 2013).
Other self-oriented motivations, such as warm-glow, have a positive effect on sustainable
choices, and may have positive effects on energy saving and campaigns. Importantly in the
workplace context, environmental goals and work performance goals are often presented as
potentially competing goals, meaning that when one is activated, it will be at the expense
of the other (Unsworth et al., 2013). In the workplace, important work performance goals
are thought to be most efficiently fulfilled by not saving energy at work (e.g., taking
the elevator, keeping one's computer on to save time). These goals, higher in the
hierarchy of goals (focal goals) compared to environmental concern (background goal), in
the context of the workplace, will encourage people not to save energy (Fishbach, Zhang, &
Koo, 2009; Kruglanski et al., 2002), or increase rebound effects or “fads” of energy
saving behaviors (Unsworth et al., 2013). Our results show that promotion of energy saving
policies at work can avoid these issues, because saving energy at work may then operate to
fulfill work-related goals. Indeed, helping one's organization image and finance are often
higher in the hierarchy of work goals than environmental concern, and less in conflict
with work performance, which can lower the potential for competing goals in the workplace.
Altogether, these results imply that in addition to environmental concern, energy saving
motivations exist which may actually complement work performance goals, and provide
guidance on the design of energy saving interventions and campaigns. Interestingly,
introducing environmental issues into organizations' operations (de Burgos Jiménez &
Lorente, 2001) does not necessarily mean that a system of direct or indirect “social”
reward should be introduced. We see here that it could be counterproductive if done
superficially, however real and significant changes to social norms and culture in the
workplace (which change current motivations and relationships with behavior) could have
substantial benefits. In relation to organizational culture, promoting employee
identification and commitment to the company may help to promote energy saving more
broadly through increasing people's motivation to act to promote the organization's image.
Making energy saving or environmental goals part of an organization's image is likely to
be beneficial in highlighting this to employees as a clear organizational goal.


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<ART>Search/ing for missing people: Families living with ambiguous absence
=====================================================================

Authors: Hester Parr, Olivia Stevenson, Penny Woolnough
DOI: 10.1016/j.emospa.2015.09.004
Year: 2016  |  Pages: 66-75
ASJC codes: 3205, 3207
Keywords: Absence, Ambiguous loss, Families, Missing people, Search

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Families of missing people are often understood as inhabiting a particular space of ambiguity, captured in the phrase ‘living in limbo’ (Holmes, 2008). To explore this uncertain ground, we interviewed 25 family members to consider how human absence is acted upon and not just felt within this space ‘in between’ grief and loss (Wayland, 2007). In the paper, we represent families as active agents in spatial stories of ‘living in limbo’, and we provide insights into the diverse strategies of search/ing (technical, physical and emotional) in which they engage to locate either their missing member or news of them. Responses to absence are shown to be intimately bound up with unstable spatial knowledges of the missing person and emotional actions that are subject to change over time. We suggest that practices of search are not just locative actions, but act as transformative processes providing insights into how families inhabit emotional dynamism and transition in response to the on-going ‘missing situation’ and ambiguous loss (Boss, 1999, 2013).

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Most of us in well resourced, democratic societies live with taken-for-granted securities
in ordinary life in which our living loved ones are almost always contactable or known to
be somewhere. For some, however, this sense of security is threatened when a family member
or friend or colleague is missing, something that happens with surprising frequency with
approximately 306,000 annual incidents in the UK (NCA, 2014). This paper considers what
emotive actions accumulate in the space of absence for the people left behind, drawing on
a funded research project in which UK families1 were interviewed about their experience of
living with the absence of, and search for, their missing person. As we discovered,
search/ing2 for a missing person is an emotional process, one also marked by (often
competing) geographical knowledges and complex relationships with police officers charged
with the task of locating the missing (this process may be significantly different
elsewhere in the world, and see Edkins, 2011; for examples). We start by situating the
paper with reference to interdisciplinary research concerning ambiguous loss and grief.
This literature suggests that humans cope with absence via ‘continuing bonds’ with those
who are gone, but that they also may become fixed or frozen by the trauma of their loss,
especially in the case of ambiguous absence (Boss, 1999, 2013). In the next sections we
explore the implications of these arguments through empirical materials related to family
experiences of search/ing for their missing person and their communications with police
officers. We disrupt a straightforward story of the freezing capacity of loss in relation
to missing people, identifying the many ways whereby families are active agents in
responding to this particular kind of absence. In this way we are highlighting how people
might manage ambiguity, and thus elaborate Boss's work (also explored further below) as
she rejects ‘stages’ or ‘steps’ of recovery from ambiguous loss, while also pointing
researchers towards ‘movement, paradoxical possibilities of change, and diverse paths to
resiliency’ (Boss, 2007: 108. See also the work of Glassock, 2006, 2011 and for a review
of literature on loss and hope in a similar context see Wayland et al. 2015). We thereby
explore search/ing as a key mode through which such emotional management happens, rather
than (just) as a sign of frozen incapacity. Search/ing here is understood not as a unified
category, act or feeling, but instead constituted by a diverse geography of shifting
modalities, materialities and meanings.3 In doing so, we move from accounts of family
liaison with police in efforts to locate missing people in the external world, to more
reflexive and interior accounts of long-term search wherein the missing person finds a new
place in the imaginations of family members. The paper concludes by suggesting that
families of long-term missing people find new ways to live with ambiguous loss, closely
connected to changing search experiences and evolving emotional geographies of human
absence (and see also Parr and Stevenson, 2014).

<h>AMBIGUOUS LOSS AND MISSING PEOPLE</h>
---------------------------------

Every year in the UK over 306,000 missing incidents are recorded by the police (NCA, 2014)
with around 35% of these being adult missing persons (the concern of our paper), some
involving repeat missing events by the same people. While the majority of cases are
resolved within three days, others continue for much longer. It is difficult to gain
accurate data of medium and long-term missing incidence, but about 1000 cases are
outstanding every week in the UK and although 97% are eventually recorded as closed cases
with no harm to the individual, 1% of cases are unresolved after a year according to the
UK Missing Persons Bureau (the remainder being recorded as fatal incidence) (NCA, 2014).
Despite the increasing (although patchy) statistical data on numbers of missing incidents
profiled by age, gender and location, little is known about how missing people's absence
affects lives over prolonged periods from the perspective of those left behind (for
exceptions see Boss, 1999, 2006, 2012; Edkins, 2011; Holmes, 2008; Henderson and
Henderson, 1998; Parr and Stevenson, 2013, 2014; Wayland, 2007; Wayland et al., 2015). The
UK charity, Missing People, receives around 17,000 annual calls from families wishing to
reach out for support from their 24 hour help-lines and dedicated counselling provision,
and so the scale of emotional need is clearly significant. What kind of loss does such
human absence provoke? How might we best understand this from geographical and other
disciplinary perspectives? What spaces do people dealing with the absence of a missing
person inhabit? How are the missing re-presenced and through what kinds of emotional,
social and spatial practices? Such questions are ones that chime with contemporary
writings, including those stressing how presence and absence exist in unstable and
sometimes unexpected relationships (Till, 2005; Wylie, 2007; McCormack, 2010; Maddrell,
2013). In such work we are often reminded that geographies of absence are not always about
spectral remains and ruination: ‘less as a disputed articulation or representation of the
past and more as part of contemporary everyday activities, bodily experiences and
contestations’ (Meier et al., 2013: 424). This emphasis on experiential and embodied
qualities of absence might also be understood further through analysing feelings and
materialities of loss, such as those that accumulate in the wake of missing episodes and
journeys. Meier thus provokes us to understand the experience of absence further, and as
something or someone as present, rather than something or someone that is simply recalled.
In work on the loss of people made absent via death (Maddrell, 2009; Maddrell and Sidaway,
2010; Maddrell, 2013; Neimeyer, 2001; Neimeyer et al., 2006), rich discussion focuses on
the relations surrounding end-of-life, with Maddrell (2013, p1) writing extensively on the
liminal spaces of grief and how these are infused by ‘dynamic negotiations of
absence–presence’. She notes how, for those in grief, the absent deceased person is
simultaneously ‘nowhere, but everywhere’ (ibid: 4). Drawing on recent bereavement studies
and the notion that the bereaved experience ‘continuing bonds’ with the dead, Maddrell
argues that the absent dead are ‘given presence through the experiential and relational
tension between the physical absence (not being there) and emotional presence (a sense of
still being there)’ (ibid: 5). Maddrell (2009, 2013) has particular interest in how
specific places of memorialisation and remembrance can help form bridging relations for
absence–presence and be sites of existential encounter with the deceased. For Maddrell,
memorials are important material spaces that enable continued relationships between the
living and the dead, although they are not the only ways for this continuance to happen.
For families of missing people, such material memorial spaces do not necessarily exist4 or
feel appropriate, and so they may be left with more diffuse traces of the missing that
reverberate through their everyday lives, in a manner not dissimilar to the
absence–presence of the grieved-for dead, but perhaps experienced with a particular
inflection precisely because they do not know if their person is still alive and
somewhere. Families of missing people, like those in grief, also work to (re)presence the
absent but via particular practices and spaces, such as celebrating birthdays, sending
nightly text messages, setting up websites or using media to ‘witness’ the person's
character and interests or call for their return (and see other examples in Edkins, 2011
and Wayland, 2007). Most poignantly, the re-presencing of missing people is usually
attempted by the continued search for them by their families, a practical activity that
happens in parallel to, and not always in partnership with, official police search
enquiries. While we have acknowledged some comparisons between the experience of
bereavement and the experience of knowing a missing person, we also want to draw out some
differences, or particularities, as a precursor to understanding the family search efforts
discussed below. Families of missing persons are often described as ‘living in limbo’
(Holmes, 2008), with the resultant states in which people find themselves often referred
to as ‘ambiguous loss’, as noted earlier. Ambiguous loss is a term coined by the family
therapist Pauline Boss who has worked with families of missing people, among others (Boss,
1999, 2002a,b, 2006, 2007, 2012). According to Boss (1999), ambiguous loss should not be
confused with ‘ordinary loss’, as missing people are physically absent but psychologically
present for their families. In Boss's view, this loss is different to the experience of
death where one can know it is impossible for the deceased actually to return, even though
there may be a powerful ‘continuing bond’ (Maddrell, 2013). Boss's research and practice
leads her to understand the ambiguous loss of missing people as particularly difficult and
disabling. She represents ambiguity in this case through a fixing language, elaborating
its ‘freezing’ properties, as ‘they (the families) cannot make decisions, cannot act,
cannot let go’ (1999, p61), due to the unknown cause of the absence. Ambiguous loss may
also be evoked as a time/space of uncertain waiting that cannot straightforwardly be ended
unless there is a body located (Hogben, 2006), although Boss hints that versions of
‘flexible waiting’ may actually be productive for some: “Those who wait endlessly for news
about a lost person do not do so in vain if they find hope and optimism in their struggle.
Indeed, they are able to find meaning in the midst of ambiguity because of their ability
to remain optimistic, creative and flexible” (1999: 132). So, acknowledging the
contradictory spatialities suggested by ‘frozen’ and ‘flexible’, as attached to those
waiting for missing people to return,5 we now explore what these dynamics might look like
in practice, particularly in relation to the role of search/ing. Here we question how and
whether family search/ing enables ways of managing the emotions constituting ambiguous
loss and the difficult absent–presence of their missing people, or prompt a kind of
repetitive paralysis where apparent ‘flexibility’ in constant search/ing may be masking
frozen loss. The paper draws on interviews with 25 families of missing people in the UK
who were recruited via two police forces in England and Scotland and the UK charity
Missing People database.6 The semi-structured interviews were led by a thematic topic-
guide designed to reflect on the search experiences of families (the lead up to the
disappearance, reporting the person missing, police and family search, dealing with
returns). Family experiences in this regard ranged from having a relative missing for a
few hours to a few weeks to 20 years, and included those who have had a return, alongside
families who are still search/ing for loved ones (Parr and Stevenson, 2013). Of the
families interviewed, 11 had relatives who were still missing. Interviews ranged from 1.5
to 3 h and involved couples and single interviewees, focus group and telephone interviews
with some follow-up liaison. In what follows, we have deliberately avoided profiling
multiple and named emotional testimonies of pain, anguish and profound psychological
disturbance that many experience when dealing with a missing relative. This is partly
because the emotional impacts of missing loss are noted elsewhere (Holmes, 2008), and
partly because in our research project we are interested in the role of family search
practices. Our exploration of such search practices also reflects how such practices feel
and here we note that “emotion … is not a static thing-in-itself, but relationally
constituted, dynamic, and so subject to shifts in position and relative power” (Thien,
2008: 312). As search/ing may involve subtle emotional transformations, this subtlety is
what we seek to disclose. In what follows, we subtitle all our empirical sections with the
adjective ‘search/ing’, precisely to convey a sense of sustained (maybe even ‘relentless’)
family efforts to locate their missing people.

<h>SEARCH/ING: REPORTING A PERSON MISSING</h>
--------------------------------------

There are many dimensions to the search for missing family in different times and places
and with different technologies of practice (for examples, see Edkins, 2011; Parr and
Fyfe, 2012). In discussing UK family experience, it is acknowledged that we are
necessarily privileging a partial representation of the processes and complexities
involved. From the moment a person is noticed as absent, there unfolds not only a search
to locate the person, but also a search for meaningful answers to questions such as
‘why?’, ‘how?’, ‘when?’, where? (Landsman, 2002). We might imagine a series of scenes as
an absence unfolds: an absence ‘becomes’ via a concerned glance at a clock, confused
phone-calling of friends and family, checking local workplaces, pubs or pathways and
finally a call for police help. The arrival at a decision formally to report an adult
missing is often fraught with anxieties around an individual's right to be absent and a
strong desire to know their whereabouts. Once an absence is reported to the police, it
triggers official risk assessment and search procedures that can leave some families
worried about whether their missing family member will appreciate such intervention. This
is especially the case for individuals experiencing mental health problems, where such
intervention may result in a medical and legal process, such as a Mental Health Section
and detainment in hospital. Some families have clearly struggled in such circumstances
about whether and when to report the absence, with some families recalling instances where
they have mounted significant searches of their own before calling in police assistance,
especially in cases of repeated disappearance. For other families, a lack of knowledge of
when and how to report someone missing has seemingly compounded the distressing nature of
the initial stages: The police actually said to us “why did you leave it so long to
contact us?” and I'm thinking “I thought they had to be missing at least forty-eight
hours” and he said “no its a misconception, you know, if somebody isn't very well or has
some kind of problems you can get in touch with us in a couple of hours if you are
concerned.” (Judy, mother of Andrew, missing for 2 years) For the police, the ‘golden
time’ for success in search for absent people is in the first 24 h after a person has last
been seen, although there are barriers to the optimal use of this time-frame, as indicated
above. Deciding if a person may be missing is tricky and families do not always feel
qualified to make this decision alone. Quite often the decision to report a family member
as missing takes place in conjunction with, or is prompted by, conversations with agencies
and other family members. Feeling as though one can act in the face of another's absence
is clearly a confusing emotional burden, but one with implications for the practicalities
of effective search. From the first moment of an absence ‘becoming’, there do, indeed,
seem to be ‘freezing’ forces at work in terms of how people respond to human disappearance
(Boss, 1999).

<h>SEARCH/ING: POLICING MISSING PEOPLE</h>
-----------------------------------

Once a person is reported as missing to the police, an official search may take place.7
The Association of Chief Police Officers (ACPO, 2006: 94) guidance states that ‘search is
a routine element of investigating reports of missing persons. It involves making an
assessment of what the initial enquiries suggest are the most likely circumstances of the
person's disappearance, and then concentrating the search in accordance with those
circumstances’. Several families reported feeling confident in the police as search
experts, recognising that the police are probably the most effective means to locate their
loved one, given the knowledge and resources assumed to be at their disposal to carry out
effective searches, as summarised here by Alice: They were very, very quick at getting
searches up and running so there was no need for us to do anything like that. The police
are the specialists, they know what they're looking for. (Alice, step-daughter to Martha,
missing for 5 years) Family decisions not to search may be related to their perception of
police as search specialists, although the majority of families did engage in some form of
search themselves alongside or in response to police actions. In understanding the drivers
for family search/ing, we might recognise not only an emotional need to be ‘doing
something’ in the face of human absence, but also consider family relationships with
police officers officially tasked with locating the missing person. Based on contingent
information, police search strategy clearly varies in type and extent (Parr and Fyfe,
2012; Fyfe et al., 2014; Glassock, 2011; Gibb and Woolnough, 2007). However, and unlike
Alice above, many families talked about feeling the level and scope of the police search
to be inadequate. Knowing that ‘no stone has been left unturned’ in the search was
represented as critical for a family's psychological and emotional welfare. One of the key
factors contributing towards a positive experience of police liaison lay in a clear
understanding of police decision-making about the parameters of any search. Yet, many
interviewees, particularly those who asked precise questions about the geography of police
search, remained dissatisfied: One of the things that I requested was the copy of the
[search] map, and they went “well nobody has asked for it before” and they've got the map
here so I'm peering across the table upside down at the map and I'm saying “well I really
can't see” so I'd be turning it round like this and they'd be turning it back and saying
“it's our map”. So I said “I'd really like a copy” and they went and did a copy in black
and white. I was just furious. I said “how dare you? Go and do a colour copy” so they did
a colour copy but there was no key on it, there was no legend, so all their little crosses
and colours didn't mean anything to me and the police officer who was explaining it
couldn't interpret either. She said “well we've done all of this” and I thought well it
doesn't help me. (Sasha, wife to Bill, missing for 2 years). The literal mapping of search
could convey the extent of search effort by the police, but some interviewees recalled
being met with reluctance by officers to share such technical geographical details.
Families interpreted this as a lack of police engagement and that their particular missing
person was not central to policing process (Edkins, 2013; Parr and Stevenson, 2013). Some
discussed feeling confused and frustrated, then, not only over the lack of clarity about
who was in charge and how the search was going, but also due to a mismatch of expectations
in relation to analytical and spatial parameters of police search: I just felt at the time
that their analysis was poor. I was expecting a more detailed analysis of what he was
wearing and the circumstances and his situation more from them. (Sasha, wife to Bill). For
others, the lack of demonstrable or varied technical search activity led to deep and
resentful attitudes towards the police: An hour searching for a young women, an hour
search!, no heat seeking!, there was no scuba sonar! We are not even one hundred percent
sure whether there was even a lifeboat, they just combed the beach and said “I don't know,
we'll just leave it at that then shall we?” (Raquelle, sister to Libby, missing for 3
years). Where specific details of search were well communicated, it directly related to
family perceptions of its standard, and their enhanced emotional handling of the
(potential) loss. Below Sasha answered a question about what forms of search information
helped her emotionally: There was a Search and Rescue Officer … He talked about how
difficult it is to find a body after a certain length of time, how the first twenty-four
hours are crucial, the fact that fourteen days have gone past made the search much more
difficult and would need a specialist dog by then and he talked, but not in a frightening
way, he talked about other environmental factors that you would look at …. I know it
sounds gruesome, but in a way that actually was tolerable to listen to and I was able to
acknowledge it. (Sasha, wife to Bill). Here Sasha, expectant and demanding of the police
officers involved in her case, was appreciative of the shared environmental knowledge of
the possible decay of her husband's missing body. Her need to understand the
technicalities, confront the material details of possible death and share in the detailed
geographical analysis of search was critical in her rejection of policing relationships
where this service was not offered. Sasha wanted to be involved with the logic and
rationale of search based on her knowledge of her missing husband (and see Parr and
Stevenson, 2014 on witnessing the missing), so that she could be emotionally assured that
highly professional and expert work was taking place. Although many families understood
that they cannot obstruct or disrupt police investigation, many were sure that they could
have more productive working partnerships, and that improved communication, information
flow, content and task allocation could reflect and produce better police-family liaison.
Moreover, such participation could help manage distressing emotions. Indeed, for Sasha, as
for others, the reluctance of the police to share information and logic for search
parameters led to her conducting her own search enquiries as a response to her strong
needs in this respect.

<h>SEARCH/ING: FAMILY PRACTICES OVER TIME</h>
--------------------------------------

In light of the varied experiences reported above and the support of an active charity
(see Parr and Stevenson, 2013), the families participating in our research reported being
forced or inspired to take search/ing into their own hands (and see Olsen, 2008). This
section explores what families have to say about such practices, and Table 1 shows the
range of practical search activities that the interviewees discussed. The table
differentiates different types of activity – physical, documentary and virtual, social
networking, liaison with other agencies/professionals and other practices – and captures
the enormous lengths to which families may go in order to try to locate their loved one or
information about them. Sally explained why the sheer emotional trauma of a loved one's
absence can galvanise people into initial search actions: It's like a massive shock, but
then you kind of feel like, well for me, I kind of felt like I had to take action. If
someone dies you can't do anything about it, whereas [for missing people] you kind of feel
like you have to do something. (Sally, daughter to Ned, missing for 7 days, returned).
Advertising the absence via posters, phone-calls, door knocking and route-tracing are some
of the very first search practices tried by families. Media reports of human absence
(particularly children) can prompt intensive and large-scale family and community
search/ing (see photograph 1): Intensive search may take place with police co-ordination,
as in the photograph above, or without, as these memories of the turmoil of early search
reveal: I got into organisational mode. So I contacted Missing People, got some posters
printed out, got some of my old friends from home to hand them out around the town and
then we started looking at places that we felt he might have gone to. We went to London
and we stayed there for two nights and basically went round all the big stations and stuff
like that. As soon as you turn up in London you are like I don't even know where to start
you know what I mean, you are just walking through parks and things going “I don't even
know what I'm looking for.” So I spent two days in London and then we went to [East town]
briefly and then we drove down to [the South Coast]. (Sally, daughter to Ned). Many
families pound the streets, draw up maps and follow lines of lateral thinking about where
their missing members might be. This initial physical search is characterised by an
intensity that belies the weight of the loss for families and the unbearable nature of the
absence. Raquelle described how she first intensively searched the beach where her sister
was last seen for the smallest of traces of her, and still finds it difficult to stop
doing so: Looking, looking. Going up to that beach every day, every day … A lot of
walking, beach combing, looking not just for my sister but for belongings, her house keys.
I had my husband climbing up rocks and looking in little crevices, just to see, and the
woodlands that were around there. I don't think I'll ever stop. (Raquelle, sister to
Libby). Several interviewees reported on their detailed search for personal belongings and
effects, as they actively seek both a person and their physical traces: I put up about two
hundred and fifty posters on the hill saying we are looking for a haversack, we are
looking for a black coat, black walking boats. (Sasha, wife to Bill). Such search/ing
practices draw on latent knowledges of the personal geographies of their missing member.
In practical terms, this can mean remembering and retracing their usual routes and
routines, but also more in-depth and emotive appraisals of ‘where matters’ to the missing
person and why. This difficult task might take in childhood haunts, sites of romantic
significance, death places and graves, well-appreciated landscapes and favourite views, or
general areas, regions and preferred pathways. For Pauline, whose son has been reported as
missing many times, she related how she manages the physical search, bound up with a
detailed knowledge of her son and the local area: I go out in the car to where I think his
normal haunts would be, little paths he would take … it might be midnight, but usually
about ten, eleven, twelve, the streets around our area tend to clear and there's decent
street lights. So I go … I drive round and round … all the streets [… ], because of a
pattern that he's followed in past experience. (Pauline, mother of Paul, missing for 2–4
days repeatedly). In exercising geographical imaginations about where matters to the
missing person, a process of re-considering the person, what is known of the missing life,
and the cause of the disappearance often occurs. It is in this reflexive space where
transitional and dynamic emotions become most apparent, and a shift in effect from
external to more interval search/ing may also occur (from pounding the streets to re-
search/ing memories and emotions).

<h>SEARCH/ING: LOOKING AND REMEMBERING</h>
-----------------------------------

In imagining the spaces where a missing person might be, different scenarios are often
considered over time. For many people who live with the ambiguous loss of a missing person
over prolonged periods, different emotions emerge at different times and relate to
changing understandings of what might have happened. Gladys, whose husband has been
missing for 20 years, charted such change: from her first recognition that he had gone
missing, ‘Just complete shock. Shock and fear. Just horrified’, to more hopeful ‘middle
years’ where ‘I'd been over to [European island] where he'd [possibly] been sighted’, to
latter feelings of abandonment, ‘he's always somewhere. It might not even be his face
sometimes [in my dreams], I just wake up feeling deceived’. In such search/ing journeys,
which sometimes occur over decades, the absent person resonates across subtly transitional
emotional lives, and alongside changing capacities for living life. In parallel, the mode
of search may begin to change: It's a bit of moving on, but it's also realising that he's
made his decision. He's made that decision to go, for whatever reason, we don't know what
that is and we haven't got any control over that … So therefore we might as well get on
with what we're doing. I think we've coped by being able to reassure ourselves we've done
as much as we could. (Charles, father of Simon, missing 2 years). Physical search
practices, ones located in external space, and aided by calling, maps, walking, driving,
posters and other technologies, may therefore diminish over time as other types of search
activity take over (such as Internet use). Here search/ing becomes part of a more muted
routine in the newly established life that follows absence in long-term cases. Many
discuss a lessening of general search activity, undertaking it every week or every month
instead of daily. Some gradually realise or come to believe that they are no longer
search/ing for a living missing person, but rather for a dead body, and this is reflected
in emotions and practices which may change as a result. Indeed, the initial emotional
intensity and effort of search/ing can be extremely difficult to sustain, as Raquelle
elaborated: I can play private detective until it sends me mad, you know, so I can't. You
also have to slow yourself down a little bit because you still have to go to work and you
still have to be mum and you still have to function and you do have to tell yourself “just
stop, just slow it down a bit” because otherwise you would be out there until it would
make you ill I think. (Raquelle, sister to Libby). In these shifts, it is, arguably, not
only the practical external modes of search that change, but also the emotional search for
understanding and meaning, and the place of the missing person in the family imagination
of itself. In support services, health and counselling practitioners emphasise the
importance of encouraging emotional reflexivity over time: ‘Empowering families to work
this timeline [a trauma time-line] into a story of emotion as well as practical content,
gives depth and perspective to their experience without it being just an external recount
of events.’ (Wayland, 2007, p16). Although many families reported the difficult emotional
consequences of ‘living in limbo’ (Holmes, 2008), they do not seem straightforwardly to
embody the ‘frozen states’ that Boss's (1999) early work outlines. Rather, interviewees
related nuanced strategies, actions and changing forms of emotional hope (FFMPU, 2005)
that morph alongside their continued search/ing: from ‘hope of a reunion, to hope of
information, which finally became hope of resolution’ (cited in Wayland, 2007:12). We
explore these themes further, below. For some families in long-term cases, then, active
search/ing is replaced by other practices that exist alongside changing senses of, and
hopes about, the missing person. Such intimacies are more difficult to describe, but
relate to an everyday alertness and a latent awareness that the missing person might be
present or appear in routine or random public environments. For Alice, search/ing was
hence replaced by looking, a qualitatively different experience, one in which the missing
person is anticipated as possibly present but in ways other than via ‘conscious
search/ing’: You are constantly looking even though you aren't searching … So even though
it's not a conscious search, even today we are still looking. (Alice, step-daughter to
Martha). Sasha suggested that even ‘just looking’ – as an anticipatory gaze - can
transform into something else again, perhaps a practice of remembering, partly through
simply being in places that were significant in the relationship with the missing person:
So it's much more [… ], rather than ‘a look’ [… ], it's a remembrance of how we used to
like coming here. (Sasha, wife to Bill). Search/ing in family narratives is thus
represented as a transformative and transforming process, moving from an intense physical
search to more documentary and virtual forms, and to practices of looking and remembering.
It is critical that such transformations are not understood as modelling ‘normal stages’
of loss (as in early conceptions of ‘grief stages’) and, importantly, that these can be
premised on non-linear relationships with forms of new information, technological advances
or renewed energies or optimism, amongst other factors. Sometimes this can be a dynamic
process associated with, or disrupted by, the location of sudden or suspected sightings,
which also become a focus for changing geographical imaginations over time. Sasha
discussed the changing imaginings that were bound up with her own idealisation of where
her missing husband was likely to have ended his life. She related how her initially
romantic vision for where he may have chosen to die is now tempered with a more realistic
assessment of the likely ‘where’ of her husband's body: We walked there, walked our dogs
there and we would often go back to walk there, so it seemed the most natural place for
me. In hindsight, I think that's my kind of romantic ideal, because I think when you are
planning to go missing with an end result, when you are going to end your life, I am not
sure you are choosing to go to the most beautiful place, I think you are choosing to go to
the place that you won't be found. (Sasha, wife to Bill). Over time, Sasha changed her
view to incorporate a new, painful imaginary – that of an unknown and hidden location for
her husband's body – as she gradually accepted that, in ‘doing absence’, missing people
like her husband may seek to access precisely “the place where you won't be found”
(Sasha). Geographical imaginations of ‘where matters?’ thus relate to the pragmatic
process of search and police liaison, but also the changing ways in which those who are
left behind refigure the absent person and the disappearance in their thinking and
emotional life (and see also Parr and Stevenson, 2014).

<h>SEARCH/ING: FOR WAYS OF LIVING WITH AMBIGUOUS LOSS</h>
--------------------------------------------------

Loss that is never ending can be crippling. To be ‘left behind’, with little or no
evidence of where a loved one has gone and whether they will return, is an intensely
difficult experience. Although it is recognised that adults have a right to go absent,
families often struggle to cope with the possibility that their missing person has left
deliberately and without trace, especially when it seems out of character. Regardless of
the time period concerned, families often long for some form of communication that would
signal connection or resolution, and help them to transition away from feeling ambiguous
loss. For some, as new search leads and actions reduce overtime, ambiguity may remain,
accompanied with what Horacek (1995) calls ‘shadow grief’, referencing a sense of loss
that is not acute but persists and is part of a continuing relationship with the missing
person. Gladys explained her struggle to manage the ambiguity and her sense of
simultaneous connection and disconnection with her missing husband following twenty years
of search/ing: I would like … only to see that face. I don't want to barge in and destroy
anybody's life, it's not what I'm about. I just want peace of mind for myself. That's all
I want, just peace of mind and to stop this never ending frustration and sadness. (Gladys,
wife to Samuel). Until such a time, people like Gladys develop strategies in an attempt to
live with absence, such as concentrating on practical issues, keeping busy to try to move
away from the pain, and seeking the support of others (see Holmes, 2008). Learning to live
with the constant demands of absent–presence in missing situations is complex, and
interviewees still found it emotionally hard to use time for leisure instead of
search/ing, although they did eventually do so: If I go to the ballet at the weekend,
there is a little bit of you that says “oh you could have been looking at the map”.
(Sasha, wife to Bill). The need to remain alert and aware for long periods of time,
readying oneself for the potential trace of the missing person, is experienced as a form
of ‘hyper-vigilance’ and a well recognised psychological issue for the people affected
(FFMPU, 2010). As a result of the long-term effects of hyper-vigilance, family members are
sometimes reluctant to leave home, even for short periods, in case of a return, but some
do eventually manage this, if they put contingencies in place: Late Friday night, stayed
there Saturday and came home Sunday. So I think that's the longest I've been away since
Andrew went missing. I [texted] him, that's where we were going. And I said the keys are
in the usual place if you want to come home. (Judy, mother of Andrew). Until a loved one
is located or returned, many express the impossibility of giving up on search/ing or
‘moving on’. What may be more common in long-term missing situations, however, is a
transition gradually allowing more flexibility in living everyday life, as Raquelle,
Sasha, Judy, Gladys and Alice all discuss in their different ways. Here families become
more flexible in their search/ing practice and mode, although still perhaps bound and
limited by its repetition. Understanding such repetition as examples of ‘frozen loss’ may
risk underestimating how repeated search/ing efforts change and how the felt ambiguity of
‘not knowing’ can transform from raw trauma into an ‘everyday remembrance’ of absence,
lived out through muted practices of looking, and a latent awareness that the missing
person is possibly still present somewhere. From a ‘family resilience’ perspective
(Becvar, 2013), the quietly transformative experiences hinted at above might be understood
to constitute a kind of resilience, what Masten (2001) calls the ‘ordinary magic’ emerging
from ordinary processes in everyday life. Boss (2013, p288) elaborates this claim in the
context of resilience theory and ambiguous loss, noting that, in order to move on from the
‘frozen states’ that a missing situation may produce in those ‘left behind’, it is
necessary to ‘revise one's attachment to a person who is missing’. She argues that
‘because ambiguous loss is a relational problem, relational interventions are most
effective’ in achieving this revision. For Boss and Carnes (2012), relational
interventions bound up with an array of therapeutic and ordinary strategies, different
ways of finding meaning in an irresolvable situation, and via accepting new forms of
dialectical thinking: for example, ‘I have a son and he is missing, he is present and
absent’. As geographers, we might also argue that the changes in the spatialities of
search/ing (from ‘external’ physical practices through to more ‘internal’ remembrances and
reconceptualisations) are critical in such relational dialectics and meaning-making.
Flexible geographies of search/ing (reducing intensities and changing modes, re-imagining
places of disappearance, accepting spaces of absent–presence) are arguably important in
themselves as processes in the difficult task of living with ambiguous loss. Search/ing
thus might be understood as comprised of relational spatialities, not just signs and
symptoms of frozen or flexible ways of living with loss, but as a means through which
emotional transformations might be lived out.

<h>CONCLUSION</h>
----------

“The absence of people that have been, of things that have been but are not anymore, can
hurt deeply. The experience of such absence can exert so much force, so much gravity, that
it feels as if it pulls one's heart out” (Frers, 2013; 431/2). I still text him every
single night, and I suppose I do that because it's a form of contact with him, as if I'm
talking to him … [but] the messages have changed. (Jane, mother of Paul). In this paper we
recognise that there are different spatialities of search/ing which are related to the
ambiguous loss that accompanies the search for a missing person. We have suggested that
there are numerous spaces that families of missing people inhabit, both material and
emotional. In journeying from police liaison to street-search/ing to virtual spaces of
tracing work to living everyday life with barely conscious practices of ‘looking’ and
remembering in multiple public spaces, family members demonstrate their changing response
to their unstable status as ‘left behind’. These changing search practices and geographies
– deliberately not represented here as a stage model - are also accompanied by changing
feelings, with the voices above describing tentative ways of responding to the loss
endured. We understand these narratives to do more than demonstrate frozen states of
psychological trauma where ‘families cannot make decisions, cannot act, cannot let go’
(Boss, 1999: 61), but, equally, neither do they represent a straightforward moving on
whereby the ambiguity of loss is resolved. In arguing thus, we suggest that the experience
of a missing person's absence is not just endured as a deep and forceful hurt (referencing
Frers, above) for those left behind, but is also experienced as a processual emotional
geography (referencing Jane, above). Here, spatialities of search become important
entities through which ambiguous loss can be newly articulated and understood but never be
entirely fixed. In Boss's later collaborative work (Boss and Carnes, 2012: 457), the
authors advocate a new kind of search in the face of ambiguous absence; as they say, ‘when
loss has no certainty, the search for meaning is excruciatingly long and painful, but it
is the only way to find resiliency and some measure of peace’. For Boss (2004), a key step
for those left behind is an acceptance of their lack of control and mastery over the
situation. Instead of relentlessly search/ing for a physical presence or news of the
absent person, a different kind of search for meaning may incorporate new relationships
with the missing person. In previous work (Parr and Stevenson, 2014), we have suggested
(and following Wayland, 2007) that this might happen through small ritualistic
celebrations of the story and person so far. Indeed, it may be that in generating ‘ideas
about how the missing person can be celebrated’, instead of just missed, that helps
produce meaningful lives lived for those ‘left behind’ (and see Carnes, 2008). This is not
the same as remembering the dead and experiencing the continuing bonds in grief (as
discussed in the introduction): for in this case, families still hold open the possibility
that the absent missing may one day speak back to address their place in such narratives.
Such an approach acknowledges, and does not deny, uncertainty, and, Boss (2008, 19) argues
that, ‘it is because of the mystery that we honour rather than memorialise …. by having a
tribute, the uncertainty is not denied’. Family members often realise they may never know
‘the where’ of their dead/alive missing person and so a new space between loss and
mourning (what Wayland calls ‘the space between grief and trauma’) may have to be found
and occupied in order to live with the ambiguity of present-absence. We hope this article
is one extra resource for that difficult journey.


<h>REFERENCES</h>
----------

  [2] Pauline Boss. Resilience as tolerance for ambiguity. doi:10.1007/978-1-4614-3917-2_17
  [3] Pauline Boss, Donna Carnes. The Myth of Closure. doi:10.1111/famp.12005
  [4] Donna Carnes. Ode to a Sailor. doi:10.1145/1379387.1379391
  [6] Jenny Edkins. Missing: Persons and politics
  [7] Jenny Edkins. Dismantling the face: Landscape for another politics?. doi:10.1068/d16312
  [9] Janet Finch. Displaying families. doi:10.1177/0038038507072284
  [10] Lars Frers. The matter of absence. doi:10.1177/1474474013477775
  [11] Nicholas R. Fyfe, Olivia Stevenson, Penny Woolnough. Missing persons: the processes and challenges of police investigation. doi:10.1080/10439463.2014.881812
  [12] Dorothy S. Becvar. Handbook of Family Resilience. doi:10.1007/978-1-4614-3917-2
  [13] Geoffrey Glassock. Coping with uncertainty: The grieving experience of families of missing people. doi:10.1080/02682620608657664
  [17] Susan Hogben. Life's on Hold: Missing people, private calendars and waiting. doi:10.1177/0961463X06067065
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<ART>Seeing Is Believing: Using Video Feedback in Cognitive Therapy for Social Anxiety Disorder
================================================================================

Authors: Emma Warnock-Parkes, Jennifer Wild, Richard Stott, Nick Grey, Anke Ehlers, David M. Clark
DOI: 10.1016/j.cbpra.2016.03.007
Year: 2017  |  Pages: 245-255
ASJC codes: 3203
Keywords: cognitive therapy, processing biases, social anxiety disorder, video feedback

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Distorted negative self-images and impressions appear to play a key role in maintaining Social Anxiety Disorder (SAD). In previous research, McManus et al. (2009) found that video feedback can help people undergoing cognitive therapy for SAD (CT-SAD) to develop a more realistic impression of how they appear to others, and this was associated with significant improvement in their social anxiety. In this paper we first present new data from 47 patients that confirms the value of video feedback. Ninety-eighty percent of the patients indicated that they came across more favorably than they had predicted after viewing a video of their social interactions. Significant reductions in social anxiety were observed during the following week and these reductions were larger than those observed after control periods. Comparison with our earlier data (McManus et al., 2009) suggests we may have improved the effectiveness of video feedback by refining and developing our procedures over time. The second part of the paper outlines our current strategies for maximizing the impact of video feedback. The strategies have evolved in order to help patients with SAD overcome a range of processing biases that could otherwise make it difficult for them to spot discrepancies between their negative self-imagery and the way they appear on video.

--------------------------------------------------------------------------------


<h>EFFECTIVENESS OF CURRENT VERSION OF VIDEO FEEDBACK</h>
--------------------------------------------------

Video feedback can be used in a variety of different ways during a course of CT-SAD. The
first time that it is used is in Session 3. In the preceding session, patients engage in
an experiential exercise in which they have a social interaction under two conditions:
first, while focusing their attention on themselves, evaluating their performance, and
engaging in habitual safety behaviors; second, while focusing externally, getting lost in
the interaction (as opposed to evaluating it) and dropping their safety behaviors.
Typically, they discover that they feel less anxious and think they come across better to
other people in the second condition, a discovery that is built on in subsequent therapy.
In Session 3, video feedback of both social interactions is used to help patients compare
their predictions of how they think they came across with how they actually came across.
McManus et al. (2009) found that video feedback in Session 3 helped 94% of patients to see
that they came across to other people more positively than they had predicted. Since the
McManus study, improved availability and functionality of camera and smartphone technology
has increased the options for using video feedback. Technology now makes it easy to
capture as a still shot key moments that disconfirm patients’ negative beliefs, and we
have found this to be a very useful technique for consolidating learning. Further
experience in using video feedback has also made us more aware of some of the processing
biases (outlined above) that can make it difficult for patients to fully benefit from
viewing themselves on video and clinical strategies for overcoming these biases have been
developed. In order to assess the impact of our current way of using video feedback, we
present video feedback data from our most recent RCT (Clark et al., Trial registration:
ISRCTN95458747) and compare it with that reported in the McManus et al. (2009) study.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 47 patients who met Diagnostic and Statistical Manual for Mental
Disorders (DSM-IV; American Psychiatric Association, 1994) criteria for SAD and were
treated with individual cognitive therapy for SAD following the general protocol outlined
in Clark et al. (2006). Other inclusion and exclusion criteria were identical to the Clark
et al. (2006) trial, which provided the main data for the McManus et al. (2009) report.
Participants’ mean age was 32 years (SD = 8.82). Forty-nine percent (23) were female.

<hs>  Procedure</hs>
  ~~~~~~~~~

Here we report the data from Session 3 of CT-SAD. In this session, participants viewed the
video recordings of the two social interactions they had engaged in during Session 2. In
most instances, the Session 2 interactions involved having a conversation with a stranger.
However, if patients felt this would not elicit a significant degree of anxiety, an
alternative individualized task was chosen, such as having a conversation with a small
group of people. Prior to watching the videos of both interactions in Session 3, patients
were asked to form a mental image of the way they thought they would appear and to make
clear-cut predictions about how they would come across. The videos were then watched and
discussed before patients rerated how they thought they appeared. Details of how
predictions were generated with patients and how the video was viewed and discussed are
given below in the clinical guidelines section.

        <hss>Self-Perception</hss>

        Before watching each video, patients were asked to rate: (a) How anxious do you
        think you will look, on a scale ranging from 0 (not anxious at all) to 100 (the
        most anxious you have ever felt)? ; (b) the extent to which idiosyncratic feared
        outcomes might be evident (e.g., How boring do you think you will look? [ 0–100]);
        and (c) How would you rate your performance overall (0–100)? These ratings were
        repeated after each video had been viewed and discussed.

        <hss>Social Anxiety</hss>

        Participants completed the self-report version of the Liebowitz Social Anxiety
        Scale (LSAS-SR; Baker, Heinrichs, Kim, & Hofmann, 2002) prior to each treatment
        session. The LSAS-SR has demonstrated good test–retest reliability and validity
        (Baker et al., 2002). Internal consistency in our sample was excellent (α = 0.92).

        <hss>Effect of Video Feedback on Self-Perception</hss>

        Table 1 shows participants’ self-perception ratings before and after viewing the
        videos. Data from the two videos are combined. After viewing the videos,
        participants rated themselves as looking less anxious than they had predicted,
        felt that their feared catastrophes occurred to a lesser extent, and rated their
        overall performance as better than they had anticipated. Table 1 also shows
        comparable data from McManus et al. (2009). Inspection of effect sizes shows that
        the beneficial effects of video feedback in the present study were between 38% and
        75% larger, depending on the measure used. To estimate the consistency with which
        video feedback improved patients’ self perception, a composite score was
        calculated in line with McManus et al. (2009). The composite score was the mean of
        the ratings of anxious appearance, social fears and overall performance. Internal
        consistency of the composite score was acceptable (α = 0.75). Ratings of overall
        performance were reversed so that higher ratings indicated a more negative
        appearance/performance on all variables. For 98% of patients their ratings after
        video feedback were less negative and more favorable than before viewing the
        video. Table 1 shows the composite scores.

        <hss>Impact on Social Anxiety</hss>

        In order to assess the impact of video feedback on participants’ subsequent social
        anxiety, we compared participants’ scores on the LSAS at the start of the video
        feedback session with their scores 1 week later. To determine whether any change
        was more than one might expect from the passage of time alone, we compared change
        that occurred during this week with change that occurred in two other time
        periods. The first was the interval between the initial assessment interview and
        Session 1 (usually 2 weeks). This interval provides an estimate of what happens
        with no intervention. The second interval was that between Session 1 and Session
        2. In Session 1 therapists develop a personal version of the Clark and Wells
        (1995) model and socialize patients to therapy without trying to change beliefs
        and behaviors. This interval therefore controls for the effects of therapist
        attention per se. Table 2 shows LSAS scores at the beginning of the assessment
        interview; Session 1 (developing an individual formulation of the SAD); Session 2
        (self-focus and safety behaviors experiment); Session 3 (video feedback); and
        Session 4 (1 week after video feedback). A repeated measures ANOVA was used to
        analyze the data. Mauchly’s test indicated that the assumption of sphericity had
        been violated, χ2(5) = 28.45, p < .001, therefore degrees of freedom were adjusted
        using the Greenhouse–Geisser correction. The results show that the LSAS score
        differed between the sessions, F(2.84, 124.82) = 15.37, p < .001. Pairwise
        comparisons between sessions 3 and 4 showed that there was a significant reduction
        in LSAS scores (from 73.4 to 65.5) in the week following the video feedback
        session (p = .003). By contrast, there were no significant changes in LSAS in the
        weeks following either the initial assessment (p = 1.00) or developing the
        individualized cognitive model (Session 1; p = .7).

<hs>  Discussion</hs>
  ~~~~~~~~~~

Our present findings confirm and extend those reported by McManus et al. (2009). Video
feedback in Session 3 of a course of CT-SAD was a highly effective intervention for
changing negative self-perceptions and was associated with a significant reduction in
social anxiety in the following week. The reduction in social anxiety was greater than in
two similar time intervals earlier in the course of therapy, suggesting that video
feedback has a specific effect, over and above therapist attention, although this result
should ideally be confirmed in a between-subjects randomized allocation design. McManus et
al. (2009) found that video feedback had remarkably consistent effects with 94% of
participants showing an improvement in their self-perception. This consistency was
replicated with 98% of patients in the present study stating that they came across to
others more favorably than they had predicted, once they had viewed the video. Inspection
of effect sizes indicates that the magnitude of the changes observed with video feedback
in the present study were even greater than in McManus et al. (2009). As patient selection
criteria were similar in the two studies, this suggests that our refinements in setting
up, viewing, and discussing video feedback may have further enhanced the potency of the
technique. In the next section we summarize the procedures we have so far found helpful
for setting up and implementing video feedback, both within the standard video feedback
session that occurs early in cognitive therapy and for its more general use throughout the
course of treatment.

<h>CLINICAL GUIDELINES FOR CONDUCTING VIDEO FEEDBACK IN CT-SAD</h>
-----------------------------------------------------------

Our results suggest that video feedback is an excellent technique for helping patients to
correct negative self-images and to also gain insight into the way in which their safety
behaviors appear to others. There are many opportunities to use it during a course of
cognitive therapy, both in the therapy office and also outside of the office when
conducting behavioral experiments in the real world. Typically, the first time it is used
is in Session 3 when therapist and patient have the opportunity to observe the two social
interactions that form part of the self-focused attention and safety behaviors experiment
in Session 2. The initial messages that patients learn from this experiment are that self-
focused attention and safety behaviors make the problem worse, not better. In particular,
they tend to increase anxiety, make it more difficult to focus on the interaction, and
give patients enhanced access to internal information (negative images and feelings) that
lead them to think that they are coming across to other people more poorly than they
really are. The additional messages that patients often get from viewing the videos
include: (a) that they come across more favorably than they think in both conditions; (b)
some of the aspects of their behavior that they do not like are the unintended, observable
consequences of their safety behaviors rather than an intrinsic feature of themselves.
When used at other times in therapy, video feedback has a similar function. It also is a
very good way of helping patients discover that they are less the subject of other
people’s critical attention than they think. When video feedback is used, it is necessary
to pay attention to the way in which the video recording is set up, how the patient is
prepared in advance of viewing the recording, and how the video is subsequently viewed and
discussed. With suitable attention to each of these aspects, it is often possible to
overcome the substantial processing biases that have prevented patients from overcoming
their negative self-perceptions before they entered therapy.

        <hss>Using the Video Camera</hss>

        As patients with social anxiety can become quite self-conscious about being
        recorded, it is best to make video recording a routine aspect of therapy, rather
        than something that is just introduced on an occasional basis for video feedback.
        We routinely record all therapy sessions using a small domestic video camera that
        is unobtrusively placed on a bookshelf at right angles to the therapist and
        patient’s eye line, so it is not in the normal field of view. In the initial
        assessment interview we explain to patients that we find it helpful to view
        sessions afterwards in order to reflect on progress and plan future interventions.
        We request written permission to make the recordings for this purpose. We also
        encourage patients to take audio recordings of the sessions for them to review
        afterwards, as we find this is a very good way of maximizing learning. Once
        permission for the recordings has been obtained, the videos can subsequently also
        be used for video feedback when therapist and patient together think this might be
        useful. As well as making the video less intrusive, routinely recording all
        sessions allows one to capitalize on unplanned therapy events that can be
        immensely informative. For example, when talking about a topic in the session
        patients may spontaneously mention that they feel they blushed a lot, had a panic,
        stuttered, or talked nonsense. In each case they can be asked to specify how they
        think they looked or sounded, before comparing their prediction with what was
        captured on the video. A similar process can be applied to the therapist’s
        behavior. For example, the patient may feel that one must always be perfectly
        fluent in one’s speech in order to be accepted. Being aware of this belief, the
        therapist may pause for a while in mid-sentence before carrying on or may start
        one sentence and then move onto another without completing the first sentence.
        Chances are that the patient is unlikely to have noticed this and will be
        surprised to discover that it happened. Reviewing the video with the therapist
        afterwards helps the patient see that the dysfluency had no real significance,
        even though the patient would have felt it was a serious social mistake if she had
        done it herself. One of the main aims of video feedback is to allow patients to
        see their behavior in context. For this reason, when videotaping an interaction it
        is best to show both people in the interaction, rather than zooming in on the
        patient. The latter tends to make it difficult for the patient to avoid feeling
        self-conscious when subsequently watching the video, and also prevents an
        appreciation of the true significance of behaviors. For example, patients who are
        concerned about fidgeting might notice their hands or feet moving in a zoomed-in
        shot and think this indicates that they are very fidgety. However, in a zoomed-out
        shot they are likely to see that the other person is also moving to a similar
        extent. It is important to elicit patients’ main concerns before setting up the
        video as knowledge about these concerns may have implications for the way in which
        the video is set up. For example, with patients who are concerned about blushing,
        it is important to have a color chart or other objects in the field of view that
        show different shades of red. This is not usually explained to the patient in
        advance (as it would make them excessively self-conscious). However, if they feel
        that they do blush during the recording they can subsequently be asked to point to
        the shade of red that they think matched the blush. Invariably they point to a
        much darker shade, which is a wonderfully graphic way of helping them discover
        that their blush is less severe than they feel.

        <hss>Other Participants Taking Part in Social Tasks</hss>

        During a course of CT-SAD patients are likely to have multiple interactions with
        other people in therapy sessions (conversations with a stranger, a presentation to
        a small audience etc.). As well as viewing the video of such interactions with
        their therapist, patients can also benefit from written feedback from the other
        participants (“confederates”) in the interaction. In order for this feedback to
        meaningfully reflect everyday life, it is important that the confederates are not
        informed about the patient’s personal fears (e.g., “I’ll sound stupid”; “I’ll have
        nothing to say”; “My lip will tremble”) as this would not be information that
        other people would have in a routine conversation. The confederate is encouraged
        to treat the patient like anyone else they would meet in life outside of the
        therapy session rather than someone they are trying to scrutinize. Behavioral
        experiments conducted outside of the office but in a public space can easily be
        recorded on a smartphone, tablet, or other domestic camera so that video feedback
        can be used to enhance the value of these exercises. The principles for setting up
        and viewing such out-of-the-office videos are essentially the same as those that
        apply to in-office videos.

        <hss>Identifying Patients’ Predictions in Advance of Viewing</hss>

        Before viewing a video, it is important to identify patients’ predictions of what
        they think they will see and to get them to visualize what these things look like.
        This provides them with the maximum opportunity to see the difference between
        their self-perceptions and reality. Patients are asked to rate (on 0–100 scales)
        the extent to which they thought their feared catastrophes occurred (“How anxious
        do you think you looked?” “How boring?” “To what extent to you think you sweated?”
        etc.) and to indicate how they think that will look. They should be as specific as
        possible. For example, if somebody says “I will look in a state—just awful,” we
        would want to elicit a more specific description of how they think they will look
        on video so that this can be compared to the actual video image. For situations
        like shaking, blushing, underarm sweating, and dysfluent speech, it is helpful to
        ask the person to demonstrate on video how they think it looked—for example, by
        intentionally shaking one’s hand or lips, pointing to the relevant shade of red in
        a color chart, indicating the size of a sweat patch, or re-creating a pause—so
        that this can be compared with how it actually looked in the original video
        recording. Once patients’ predictions have been clearly articulated, it is often
        helpful to ask them to close their eyes and create their own internal video by
        visualizing how they think they will appear. It is sometimes also useful to ask
        people to write short notes on how they think they will appear.

        <hss>Preparing an Unbiased Mode of Viewing</hss>

        It is common for patients to reexperience some of their anxious feelings while
        watching the video. These feelings may influence their perception of the video.
        For example, if they feel shaky they may see shaking in the video that would not
        be seen by others. To overcome this problem, we explain to patients that how one
        looks and how one feels may not be the same but it is impossible to discover this
        unless the two are kept separate. In order to do this, patients are asked to view
        themselves in the video as though they are watching a stranger, only making
        inferences about how they appear by using what they see and hear on the video,
        ignoring their feelings. To help them do this, we may encourage them to imagine
        they are watching a television show. When discussing the video with the therapist,
        we may ask them to refer to themselves as “that person” or to give themselves a
        different name. Some patients reexperience feelings from socially traumatic
        memories (such as being laughed at, ridiculed, or bullied) while watching the
        video. These feelings may also distort their perception of the video. If the
        therapist and patient have identified this problem, patients can be asked to
        specifically look for things in the video that are inconsistent with the past
        social trauma to help them clearly distinguish between then and now (e.g.,
        focusing on everything about the people they are currently interacting with, which
        is different from the people involved with the traumatic experience). Some people
        find that it is very difficult not to turn on their habitual self-critical
        commentary when watching themselves. After discussing how this can take them away
        from what actually happens on the video, it can be useful to ask them to watch the
        video from a more compassionate stance, perhaps as they would if they were
        watching a close friend or somebody they like and respect. They can be asked to
        recall the last time they had a conversation with this friend and to consider how
        they would view their friend: THERAPIST: How do you listen when your friend Alex
        is talking? Do you just go with the flow of what he says or do you zoom in on how
        he says every word and ask yourself, “How boring does Alex sound?” “How weird does
        he look?” [ use patient’s own beliefs] PATIENT: (laughs) No! I just go with the
        flow. THERAPIST: Ok, we would like you to watch the people on the video in a
        similar way. Some people find that when they hear the sound of their own voice
        this automatically triggers the similar sounding self-critical commentary that
        they normally have in social situations. If the person is highly self-critical, to
        prevent this mode being activated as soon as the video starts, it can be helpful
        to watch the first 30 seconds or so with the sound off. This will help them to see
        that they look as normal as anybody else on the video. When the sound is then
        turned on, they are in a more appropriate cognitive set. A similar maneuver can be
        used for people who are highly critical of their physical appearance and find it
        difficult to look at anything else in the video. For these people, the therapist
        may initially cover up the patient’s image and let them focus on how other people
        are responding to them. After a minute or so, they can also be revealed. There is
        a risk that people may selectively zoom in on themselves looking for any
        imperfection, rather than watching the interaction in context. To avoid this, the
        therapist may say something like: “Imagine you walk into a coffee shop and see a
        conversation happening, look at the whole group, not just one person.”

<hs>  Viewing and Discussing the Video</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Once the patient has clearly articulated their negative self-image and they have been
carefully prepared for viewing the video, therapist and patient watch it together.
Sometimes the whole interaction is initially viewed without pausing. For highly self-
critical patients it can be helpful to pause early in the viewing to check the following:
“Are you watching that person (therapist points to the patient in the video) as you would
anyone else, or are you watching as your worst critic? Are you looking at other people and
how they respond, or just focusing onthat person?”

        <hss>Rewinding the Video to Capture Key Moments</hss>

        Once the video has been watched all the way through, it can be very helpful to
        rewind the video to look at particular moments that have significance to the
        patient. For example, rewinding to the moment when the person thought they had a
        panic attack, when they thought they paused for a long time, looked particularly
        anxious, looked fidgety or felt that they sweated. They can then be asked to
        compare how they looked at that moment with their expectation. Other helpful
        questions may include: “Does the other person seem to have noticed?” “Are they
        reacting as if they have seen a big mistake?” “Do the people onscreen look
        markedly different from each other?” “Is the other person also moving their legs
        and fidgeting?” “If an alien was looking at this would they think one of these
        people looked really odd?” As the therapist will be aware of the patient’s own
        self-images and has also seen how they actually behaved, the exact choice of
        questions will be determined by the therapist’s goal of helping the patient see
        which aspects of their self-image are distorted.

        Gaining Insight Into the Impressions Safety Behaviors Convey to Other People

        Patients are often unaware of the way that their safety behaviors appear to other
        people. Video feedback provides an ideal opportunity for them to gain insight,
        which in turn can help motivate them to drop the safety behaviors. For example, a
        patient who was concerned that his colleagues might see his hand shaking while
        drinking a beer often turned his back to his colleagues before taking a sip. This
        made him feel less self-conscious and so seemed a good way of coping with the
        situation until he saw what it looked like on the video. He then realized it will
        have appeared odd and may have conveyed to his friends that he was not really
        interested in them, when the exact opposite was the truth. As turning his back was
        an intentional strategy, he was able to choose not to do it in the future.
        Similarly, a patient who was concerned that other people might think she was
        stupid tended to run through a preprepared list of topics during conversations and
        to be distracted from the conversation by mentally monitoring how she thought she
        was coming across. On viewing the video, she realized that she was conveying the
        impression that she was not interested in other people and was just giving them a
        lecture. This was the opposite of the impression that she wanted to convey, so she
        experimented with just saying what came into her head and responding spontaneously
        to what people said. When she watched this on the video she realized that dropping
        her safety behaviors allowed her to come across to others in the open and friendly
        manner that she wished.

        <hss>Comparing Ratings Before and After Viewing the Video</hss>

        A key aspect of video feedback involves comparing patients’ ratings of how they
        thought they would appear with how they actually appeared once the video has been
        viewed. This comparison usually involves looking at all the specific predictions
        that the patient made. The initial 0–100 ratings that patients made in advance of
        viewing the video are compared with their ratings of the same concerns (looking
        anxious, sounding boring, etc.) after they have watched and discussed the video.
        To facilitate comparison a two-column table is constructed. Once the discrepancies
        have been tabulated, the patient is asked: THERAPIST: What do you notice when we
        compare these two sets of ratings? PATIENT: I look so much better than I thought I
        was going to. I look OK, not really that anxious, even though I felt it.
        THERAPIST: What does that tell you about how visible your anxiety is? PATIENT:
        Maybe it isn’t that visible to others. Maybe I come across OK. THERAPIST: So if
        your feelings aren’t that visible, are they a reliable judge of how you come
        across? PATIENT: No, I guess not. THERAPIST: So next time you are in a social
        interaction and feel you are coming across badly, you may want to bring to mind
        the image of how you actually looked on the video.

        <hss>Eliciting Feedback From Other People</hss>

        It can be very helpful to supplement video viewing with feedback to the patient
        from other people who might have been involved in an interaction. We routinely do
        this for the self-focused attention and safety behaviors experiment. After they
        have participated in both conditions, confederates are asked to think back to each
        interaction in turn and to provide feedback. We find a two-sided form, handed to
        the confederate as they leave the therapy room, helpful. The first side is largely
        blank. Confederates are asked to write a few brief notes about their general
        impressions. What tends to happen is that confederates mention specific points
        that make it clear they were interested in the patient and noticed various things
        about them. But what they noticed was mainly what was talked about, not the
        specific fears that the patient had (such as “my lip was shaking”). The second
        side covers the patient’s specific predictions (such as “I’ll sound boring”) and
        the confederate is asked to rate on 0–100 scales the extent to which this was
        true. Usually the confederates’ ratings are similar to the patients’ ratings after
        they have viewed the video, but sometimes the confederate is even more positive.
        When this happens it can be useful to discuss with the patient why the confederate
        may have been more positive: “Is it possible that your ratings are still partly
        influenced by your private feelings? This may be information that nobody else
        could have.” Therapists should use their discretion in deciding whether it is
        helpful or necessary to supplement video feedback with feedback from others. Most
        often we present feedback from others after patients have had a chance to view and
        discuss their video and it is essentially used as a way of further confirming the
        conclusions they have already reached. However, if the feedback is very positive
        and the therapist thinks that the patient’s self-criticism may make it difficult
        for them to view the video objectively, it can be useful to show the other person
        feedback first. This helps to establish a different cognitive set for viewing the
        video. Our data (see above) indicate that almost all (98%) patients view
        themselves more positively after viewing the video if the experience is set up and
        discussed in the manner presented here. In rare instances where that does not
        happen, it can be useful to focus the patient’s attention on how others in the
        video are reacting to them. This can help them see that features that remain
        prominent in their own mind have less significance to others. Feedback from the
        confederate is also helpful in such instances.

        <hss>Freezing the Moment of Disconfirmation and Consolidating Learning</hss>

        The aim of video feedback is to help patients see that they come across to others
        much better than they think. There are some moments in a video that illustrate
        this point more clearly than others. As video is a moving image, these moments can
        pass in and out of consciousness quite quickly. An excellent way of overcoming
        this problem is to capture the moment of disconfirmation as a still image. This
        can be done either by taking a still from the video or by taking a separate
        photograph. The latter is particularly useful in out-of-the-office behavioral
        experiments. For example, a patient reported feeling self-conscious when walking
        in the street even when not interacting with other people. She felt that people
        were likely to be hostile and predicted that if she asked someone for directions
        they would respond in an irritated manner, at the very least. She agreed with her
        therapist that she would test this out by stopping passersby and asking them the
        directions for the nearby rail station. The therapist accompanied and discretely
        took photographs on her mobile phone. The image reproduced in Figure 1 captures
        the moment when her negative prediction was convincingly disconfirmed: the
        stranger smiles and is helpful when she asks for directions. She pinned the image
        to her bulletin board at home to remind herself how people really respond to her.
        Still images involving other people, like the photograph in Figure 1, can be a
        helpful way to demonstrate to the patient that their feared concerns (I was
        boring, I looked sweaty, I looked shaky, I had nothing to say) were not as
        noticeable to others as they thought, or that even if others did notice, they did
        not react as negatively as the patient feared. Capturing these moments of
        disconfirmation can be particularly powerful when the patient feels their feared
        concern happened naturally (e.g., they forgot what they were saying, they
        naturally blushed mid-sentence). It can also be helpful for decatastrophizing
        experiments, where patients purposefully perform a feared concern in order to
        discover whether others react in the disapproving way they expect (such as adding
        water to their underarms to create the appearance of sweating, or purposefully
        trembling their hand when talking to a stranger). This can help patients to
        realize that they are much less the subject of other people’s critical attention
        than they initially thought. Still images can also be a wonderful way to capture
        moments when patients realize they come across much better than their internal
        feelings and self-perceptions tell them they do (e.g., I look bright red, panicky,
        have wide scared looking eyes). For example, a patient reported feeling she
        blushed 80% red while giving a presentation to a small audience during her
        therapy. Prior to viewing the video, she was asked to select the shade of red she
        felt she blushed at this moment using a color chart. When a still image was
        captured from the video at the moment she felt she blushed 80%, the color she
        selected from the color chart was held next to this image, providing a clear
        disconfirmation of her belief. A second image was then created: this contained the
        still taken from the video at the worst moment for the patient (when she felt she
        blushed red) side-by-side with the block of color she predicted she blushed from
        the color chart. The image reproduced in Figure 2 illustrates the contrast between
        the patient’s feelings and the reality. She kept this photo on her mobile phone
        and looked at it over the week whenever she felt she was blushing, as a reminder
        that “My feelings are not as visible as I think.” The contrast between two images
        that depict how patients feel and how they actually looked on video (as
        demonstrated in Figure 2) may seem stark to an objective observer. However, some
        patients who reexperience strong anxious feelings and/or find it hard to switch
        off their habitual self-criticism when viewing images may find it difficult to
        perceive contrasts that would be apparent to other people who did not experience
        their feelings or levels of self-criticism. In these instances, we have sometimes
        found it helpful to edit the image by removing identifiable features of the
        patient and isolating only the part of the person that they were most concerned
        about (e.g., showing a portion of their cheek that they felt went bright red;
        their smile that they felt looked like a grimace; their underarm that they
        believed was dripping with sweat, etc.). This isolated feature in still image
        captured from the video can then be compared to a visual calibration obtained
        before viewing. Removing identifiable features of the patient can help prevent the
        projection of their feelings and self-criticism into the image, and help them
        perceive the contrast between their self-perception and reality. Capturing two
        still frames from the video at different time points can also be another way to
        illustrate that patients’ internal feelings were not as noticeable as they
        thought. For example, one patient became extremely self-focused during a
        conversation with a confederate in therapy. He felt highly anxious at that moment
        and worried that his face looked odd. He and his therapist were able to isolate
        the moment on video and to also capture a still image from another part of the
        conversation when he did not feel particularly anxious, and was predominantly
        externally focused (see Figure 3). The patient was amazed to discover that he
        couldn’t see any difference between the two images. This helped him realize that
        his feelings are largely private.

        <hss>Creating a Still Image Flashcard</hss>

        In order to abstract key principles fitting the cognitive conceptualization of the
        patient’s social anxiety, and to consolidate and generalize learning, the patient
        and therapist may add some informative text to still images captured from the
        video (e.g., “I felt 80% anxious but I don’t look it—my feelings aren’t visible”;
        “I worried other people would laugh at me but they were friendly, this shows I’m
        acceptable”). Adding some of the key learning points in the patient’s own words,
        either handwritten on a printed copy or typed onto an electronic image that can be
        saved on a smartphone or tablet, can act as a powerful flashcard that the patient
        can use as a reminder the next time they enter a stressful situation.

        <hss>Rehearsing the Way They Looked on Video</hss>

        Negative self-images are often habitual and well rehearsed. For some people it can
        be helpful for them to intentionally bring to mind the pictures of how they really
        appeared on video when they appear anxious so these can counteract their habitual
        negative self-images. They can also remind themselves of how they look before
        going into a stressful situation.

        <hss>A Demonstration Video Clip</hss>

        Using the link below, readers can access a 7-minute video clip (Video 1) that
        illustrates some of the procedures described above. The role-played clip is based
        on a real cognitive therapy session that took 90 minutes. The clip illustrates:
        (1) Identifying a patient’s predictions in advance of viewing a video; (2)
        Preparing the patient to view the video; (3) Discussing the video and rewinding to
        capture key moments; (4) Comparing ratings before and after viewing the video; and
        (5) Freezing the moment of disconfirmation and consolidating learning.

<hs>  Summary of the Clinical Guidelines for Video Feedback</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Video feedback is a helpful technique that can be used throughout a course of cognitive
therapy to help patients correct their negative self-perceptions and gain insight into the
effects of their safety behaviors. Unfortunately, social-anxiety-related processing biases
can make it difficult for people with SAD to see the difference between their negative
self-image and what is actually shown on the screen. To reliably overcome these biases,
particular attention needs to be paid to setting up the video recording; preparing
patients to view the video; and subsequently watching and discussing the footage. This
clinical guideline has provided details of many of the procedures we have found helpful to
maximize the beneficial effects of video feedback. In selecting the most appropriate
technique, therapists need to draw on their knowledge of the discrepancy between the
patients’ negative self-images and how the patients actually come across. This in turn
requires an ability to explore patients’ self-perceptions sensitively and in detail.


<h>REFERENCES</h>
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  [15] Jasper A.J. Smits, Mark B. Powers, Rachel Buxkamper, Michael J. Telch. The efficacy of videotape feedback for enhancing the effects of exposure-based treatment for social anxiety disorder: A controlled investigation. doi:10.1016/j.brat.2006.01.001
<ART>Selective effects of explanation on learning during early childhood
===================================================================

Authors: Cristine H. Legare, Tania Lombrozo
DOI: 10.1016/j.jecp.2014.03.001
Year: 2014  |  Pages: 198-212
ASJC codes: 3204, 3205
Keywords: Causal explanation, Causal reasoning, Cognitive development, Early childhood, Generalization, Learning, Self-explanation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Two studies examined the specificity of effects of explanation on learning by prompting 3- to 6-year-old children to explain a mechanical toy and comparing what they learned about the toy's causal and non-causal properties with children who only observed the toy, both with and without accompanying verbalization. In Study 1, children were experimentally assigned to either explain or observe the mechanical toy. In Study 2, children were classified according to whether the content of their response to an undirected prompt involved explanation. Dependent measures included whether children understood the toy's functional-mechanical relationships, remembered perceptual features of the toy, effectively reconstructed the toy, and (for Study 2) generalized the function of the toy when constructing a new one. Results demonstrate that across age groups, explanation promotes causal learning and generalization but does not improve (and in younger children can even impair) memory for causally irrelevant perceptual details. © 2014 The Authors.

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<h>INTRODUCTION</h>
------------

A growing literature suggests that young children’s explanations play a crucial role in
learning (Bonawitz, van Schijndel, Friel, & Schulz, 2012; Legare, 2012, 2014; Legare &
Gelman, 2014; Roy & Chi, 2005; Siegler, 2002; Singer, Golinkoff, & Hirsh-Pasek, 2006;
Sobel & Sommerville, 2009; Wellman & Liu, 2007). For example, generating explanations can
improve acquisition of new material and its extension to novel cases (Crowley & Siegler,
1999; Lombrozo, 2006; Wellman, 2011) and can even accelerate difficult conceptual
transitions such as acquiring an understanding of false beliefs (Amsterlaw & Wellman,
2006) or number conservation (Siegler, 1995). Despite the acknowledged importance of
explanation during early childhood, however, little is known about how effects of
explanation differ—if at all—from mere verbalization or general attention and whether and
how effects of explanation are selective to particular kinds of learning. Here we explored
whether prompting 3- to 6-year-old children to explain a mechanical device fosters
causal–mechanical understanding more effectively than does observation or verbalization
and, if so, whether such understanding comes at the expense of other kinds of learning.
Educational research comparing self-explanation—that is, explaining to oneself or another
person—with other activities suggests that explaining can be more effective for learning
than alternative activities such as thinking aloud and reading study materials twice,
especially when it comes to generalizing from study material to new cases (see Fonseca &
Chi, 2011, and Lombrozo, 2012, for reviews). Although most research on self-explanation
has focused on older children and adults, the limited research with younger children
suggests similar effects. For example, research on problem solving among elementary school
children comparing the effectiveness of self-explanation with alternative activities
(e.g., solving practice problems) found that self-explanation was associated with greater
conceptual and procedural knowledge (McEldoon, Durkin, & Rittle-Johnson, 2012). Rittle-
Johnson, Saylor, and Swygert (2008) also demonstrated that explanation prompts facilitate
transfer in children as young as 5 years relative to repeating problem solutions in
problem-solving tasks. Notably, however, children in these previous studies of self-
explanation were asked to explain why a particular solution or strategy was correct; that
is, they explained some task-relevant feedback (see also Amsterlaw & Wellman, 2006;
Crowley & Siegler, 1999; Rittle-Johnson et al., 2008). It could be that effects of
explanation in young children result from the interplay of feedback with their
explanations. For example, explaining could draw attention to the feedback and encourage
children to rephrase it in their own words, thereby facilitating belief revision. Thus, it
is an open question whether simply explaining one’s observations—in the absence of
feedback of this type—can similarly improve young children’s learning and, if so, whether
its impact results from the general use of language or from explanation per se. This
question is especially important in understanding the role of children’s spontaneous
explanations on learning throughout development (Legare, 2014). Another open question
concerns the selectivity of explanation’s effects, especially during early childhood. In
particular, are effects of explanation restricted to some kinds of learning, or do they
extend more broadly? And do the benefits of explanation have any associated costs?
Evidence from older children and adults suggests that effects of explanation can indeed be
selective, improving some kinds of learning over others. For example, explanation can
foster analogical transfer at the expense of memory for previous problems (Needham & Begg,
1991), privilege causal mechanisms over consistency with previous data in justifying
causal judgments (Berthold, Roder, Knorzer, Kessler, & Renkl, 2011; Kuhn & Katz, 2009),
and encourage learning about patterns instead of individual examples (Williams, Lombrozo,
& Rehder, 2013). When it comes to effects of explanation during early childhood, however,
comparable studies have not been performed and two distinct stories are quite plausible.
On the one hand, explaining could boost general engagement or attention (e.g., Siegler,
2002), which might lead to relatively widespread benefits across wide-ranging measures of
learning. On the other hand, consistent with research on older children and adults,
explaining could privilege some kinds of learning (e.g., causal learning) at the expense
of others (e.g., perceptual learning), leading to more selective effects and potentially
even to impairments (see also Walker, Lombrozo, Gopnik, & Legare, 2014). Identifying
whether and how effects of explanation are selective, therefore, is of both practical
value (for informing educational practice) and of theoretical value (for helping to
isolate the mechanisms by which explanation influences learning during early childhood).
Building on prior work, we propose that explanation generates selective effects and that
it does so by encouraging young learners to consider particular kinds of hypotheses,
namely those that support good explanations (Legare, 2012; Lombrozo, 2012; Williams &
Lombrozo, 2013). If explanations are typically judged as better when they invoke causal
mechanisms or broad generalizations (for reviews, see Keil, 2006; Lombrozo, 2006, 2012),
then explaining could selectively focus learners’ attention on hypotheses that exhibit
these features. Consistent with these ideas, adults seek information about mechanisms when
asked to explain an event (Ahn, Kalish, Medin, & Gelman, 1995; Keil, 2006; see also
Bullock, Gelman, & Baillargeon, 1982; Koslowski, 1996; Lombrozo, 2010), and prompting
adults to explain can foster the discovery and generalization of broad patterns (Williams
& Lombrozo, 2010, 2013). In fact, a prompt to explain can lead even 3-year-olds to posit
unobserved causes (Buchanan & Sobel, 2011; Legare, Gelman, & Wellman, 2010; Legare,
Wellman, & Gelman, 2009) and favor generalizations that account for more observations
(Walker, Williams, Lombrozo, & Gopnik, 2012), suggesting that prompts to explain might
direct even young learners toward broad, causal patterns. In the two experiments that
follow, we provide the first empirical investigation of the selectivity of effects of
explanation on young children’s causal learning. Our studies differ importantly from prior
work in that we did not provide children with direct instruction or corrective feedback.
Moreover, we compared explanation with other tasks that were matched for time and
verbalization, and we examined both causal and non-causal learning—learning about
functional–mechanical properties versus memory for perceptual features such as color. Our
first objective was to differentiate effects of explanation from those due to observation
(Study 1) or verbalization (Study 2). Our second objective was to examine whether and how
prompts to explain selectively benefit young children’s causal learning and whether this
benefit comes at the expense of non-causal learning (Studies 1 and 2). Our final objective
was to examine potential age-related differences in the effects of explanation on
children’s learning (Studies 1 and 2). In particular, we examined whether learning
benefits are a consequence of children’s age or instead follow from the content and
quality of their explanations regardless of age. In two studies, we presented preschool-
aged children with a novel mechanical toy with visible interlocking gears and examined
learning using measures that assessed their understanding of the toy’s causal function,
memory for the toy’s non-causal properties such as color, and (in Study 2) generalization
of the toy’s causal function in constructing a novel toy. In Study 1, children were
prompted to observe or explain the toy, and learning was assessed both as a function of
the experimental manipulation and (for children in the explanation condition) based on the
content of their verbal response (i.e., explanation vs. non-explanation). In Study 2,
children provided verbal responses that were categorized as either explanations or non-
explanations, and learning was assessed as a function of these categories. In the context
of these studies, we defined explanations as responses that included functional or
mechanistic information about the toy (i.e., about proximate causal processes or the
function of a particular part or process) (see Kelemen, 1999; Legare et al., 2010;
Lombrozo, 2009; Lombrozo & Carey, 2006). Comparing effects of explanation with observation
and non-explanatory verbalization can shed light on the mechanisms by which each process
contributes to learning. If explanation’s effects derive from greater attention or
engagement, we might expect global improvements in learning relative to observation. If
explanation’s effects are a consequence of producing a verbal response, we might expect a
benefit for explanation relative to observation in Study 1 and comparable effects for
explanation and other verbalizations in Study 2. In contrast, we predicted that, relative
to both observation and verbalization, explanation would improve learning on measures of
functional–mechanical understanding (Studies 1 and 2) and generalization (Study 2) but
would have no effect on—or even impair—learning about non-causal properties such as color.
Finally, our two studies also had the potential to differentiate several plausible
trajectories for age-related changes in the effects of explanation on learning. One
possibility was that explanation would help younger children more than older children
because younger children may require greater scaffolding to achieve cognitive benefits
that older children can achieve without prompting (for evidence that this is sometimes the
case, see Walker et al., 2014). Another possibility was that explanation would help older
children more than younger children because learning by explaining presumably requires
some baseline level of verbal fluency and cognitive sophistication (Hickling & Wellman,
2001). A third possibility was that older children would be more likely than younger
children to engage in (high-quality) explanation (Legare et al., 2010) but that effects of
explanation among those who do explain would be relatively uniform across ages. Finally,
effects of explanation could vary across development in their selectivity; for example, it
could be that explanation privileges causal learning at the expense of perceptual memory
in younger children but promotes causal learning without this penalty in older children.
By investigating effects of explanation on learning across the 3- to 6-year age
range—which spans a wide range of verbal, conceptual, and cognitive development—our
studies could also help to differentiate these alternative developmental trajectories.

<h>STUDY 1</h>
-------

Study 1 examined the selectivity of explanation’s effects on children’s learning about a
causal system. We presented young children with a novel mechanical toy and compared
learning across conditions in which they were or were not prompted to explain (explanation
vs. observation). We measured two kinds of learning: learning about causal–mechanical
relationships and learning about causally irrelevant properties such as color. We
hypothesized that explanation would direct learners’ attention toward causal mechanisms,
resulting in better learning on measures of causal knowledge but not necessarily on
measures of memory for causally irrelevant properties.

        <hss>Participants</hss>

        A sample of 95 children—31 3-year-olds (M = 41.83 months, SD = 3.40), 32 4-year-
        olds (M = 53.56 months, SD = 3.14), and 32 5-year-olds (M = 65.34 months, SD =
        3.34)—participated in Study 1. Children were recruited from preschools in a major
        metropolitan area in the American Southwest. The sample was approximately gender
        balanced and primarily Euro-American and middle class, with an approximately equal
        number of children from each age group assigned to each condition. Children were
        tested in a quiet room in the preschool or a research laboratory at a major
        southwestern university; each session took approximately 10 to 15 min. An
        additional 5 children participated but were dropped from the final sample due to
        either inability to engage with the task (n = 2) or experimenter error (n = 3).
        None of the participants from Study 1 participated in Study 2.

        <hss>Materials</hss>

        Materials included a novel machine with five interlocking gears, including a crank
        that made a fan turn and non-functional peripheral parts connected to selected
        gears (see Fig. 1A). Each child saw the same machine. An additional three parts
        were used in a training trial, and an additional 10 parts were used to assess
        learning (see “Procedure” section below).

            <hss>Training task</hss>

            Each child participated in a training task where an experimenter demonstrated
            how the machine parts fit together. The child was presented with a base part,
            a gear, and a peripheral part (called a “topper”). The parts were similar, but
            not identical, to those used for the machine in the experimental task. The
            experimenter showed the child each part, labeling it as a base piece, gear, or
            topper, and then modeled how to put them together. Then the parts were taken
            apart, and the child was given the opportunity to put them together.

            <hss>Experimental task</hss>

            Following the training task, the experimenter placed the previously hidden
            machine in front of the child, pointed out the crank and fan, and turned the
            crank to demonstrate that this made the fan turn. In the observation
            condition, the child was told, “Let’s look at this!”, and then had 40 s to
            observe the machine (which was no longer in motion). In the explanation
            condition, the child was asked, “Can you tell me how this works?”, and then
            had 40 s to produce a verbal response.1

            <hss>Learning measures</hss>

            After 40 s, the machine was removed from the child’s view and placed under the
            table. Unbeknownst to the child, the small pink gear was removed from the
            machine and the machine was placed on the table again. The experimenter
            indicated that this was the same machine as before but that one of the parts
            was missing. The child then participated in two learning tasks, with order
            counterbalanced across participants. For the causal choice task, five parts
            were presented, none of which was identical to the missing part. The choices
            consisted of one part of the correct size and shape but different color, one
            part of the correct shape but incorrect size, one part of the correct size but
            incorrect shape, and also a distracter part and a peripheral part seen before
            but not the correct shape (see Fig. 1B). The child was asked, “Can you point
            to which one of these parts you think will make it work?” This task was
            intended to assess children’s understanding of the causal contributions of the
            gears in making the machine work—an aspect of functional–mechanical
            understanding. For the color choice task, the experimenter presented the child
            with another five parts. All parts were the correct size and shape, but only
            one part was the same color as the original (see Fig. 1C). The child was
            asked, “Can you point to the piece that will make my machine look like it did
            in the beginning?” This task was intended to assess children’s memory for the
            color of the original gear, a property irrelevant to functional–mechanical
            understanding. After the choice tasks, the machine was again removed from the
            child’s view under the table. The experimenter removed all of the parts from
            the base and took the peripheral parts off the medium-sized purple gear, the
            large orange gear, and the small pink gear. The crank gear and the fan gear
            were not taken apart. The experimenter put the base on the table in front of
            the child as before. Then the experimenter put the gears and peripheral parts
            in front of the child in a predetermined random order (Fig. 1D) and asked,
            “Can you put my machine back together the way it was before and make it work?”
            The child was given 10 min to reconstruct the machine.

            <hss>Experimental task</hss>

            For children in the explanation condition, verbal responses were coded for the
            presence of explanations. If the child provided a mechanistic or functional
            explanation (i.e., made a claim about proximate causal processes or the goal
            or function of a particular part or process; see Kelemen, 1999; Lombrozo,
            2009; Lombrozo & Carey, 2006), the verbal response was coded as an explanation
            (e.g., “That [the crank] spins around and the others spin around,” “It spins
            together”). All other verbal responses were coded as non-explanations. Non-
            explanations included descriptions, inquiries, statements of uncertainty, and
            no responses. Verbal responses were coded by two independent coders with
            agreement of 94% (kappa = .83). Disagreements were resolved by discussion.

            <hss>Learning tasks</hss>

            For the causal choice and color choice tasks, selecting the correct part was
            scored as 1 and selecting an incorrect part was scored as 0. For the
            reconstruction task, success was analyzed along two dimensions: successfully
            reconstructing the machine’s function (causal reconstruction score) and
            successfully reconstructing causally irrelevant components (topper
            reconstruction score). The child received a causal reconstruction score of 1
            for successfully reconstructing the causal–functional relationships that would
            allow the machine to work (i.e., replacing the fan and handle correctly,
            replacing the gears correctly, interconnecting the gears, and spinning the
            handle during reconstruction) or otherwise received a score of 0. The topper
            reconstruction score reflected accuracy in pairing each gear with its non-
            functional peripheral part (1 = all correct, 0 = any incorrect). Because the
            causal choice task and the causal reconstruction score both reflect causal
            learning, these scores were combined into a single causal learning score that
            could range from 0 (success on neither task) to 2 (success on both tasks).
            Similarly, because the color choice task and the topper construction score
            both reflect learning about non-causal aspects of the machine, they were
            combined into a single non-causal learning score that could range from 0 to 2.

        <hss>Learning as a function of experimental condition</hss>

        Table 1 reports the proportions of correct responses as a function of condition
        (observation vs. explanation) for the four learning measures (causal choice, color
        choice, causal reconstruction, and topper reconstruction). To analyze performance,
        we conducted a repeated-measures analysis of variance (ANOVA) with type of
        learning score (causal learning or non-causal learning) as a within-participants
        factor and condition (observation or explanation) and age group (3-, 4-, or
        5-year-olds) as between-participants factors. This analysis revealed a significant
        interaction between type of learning and condition, F(1, 89) = 38.30, ηp2 = .30, p
        < .001, as well as an interaction among learning score, condition, and age group,
        F(2, 89) = 7.48, ηp2 = .14, p < .001. Therefore, we analyzed performance for each
        learning score separately. Analyzing causal learning scores revealed that
        participants in the explanation condition (M = 1.04, SD = .65) performed
        significantly better than those in the observation condition (M = .49, SD = .66),
        F(1, 89) = 18.74, ηp2 = .17, p < .001, consistent with our predictions (Fig. 2).
        In addition, there was a main effect of age, F(2, 89) = 4.99, ηp2 = .10, p = .009;
        post hoc tests revealed that 3-year-olds (M = .48, SD = .57) performed
        significantly worse than 4-year olds (M = .88, SD = .71), t(61) = −2.41, p = .019,
        and 5-year-olds (M = .94, SD = .76), t(61) = −2.68, p = .010, who did not differ
        from each other, p = .734. Analyzing non-causal learning scores revealed that
        participants in the explanation condition (M = .46, SD = .62) performed
        significantly worse than those in the observation condition (M = .89, SD = .73),
        F(1, 89) = 11.15, ηp2 = .11, p = .001 (Fig. 2). In addition, there was a
        significant interaction between condition and age, F(2, 89) = 6.50, ηp2 = .13, p =
        .002. A prompt to explain led to significant impairments on the non-causal
        learning measures for 3-year-olds, t(29) = 2.29, p = .030, and 4-year-olds, t(30)
        = 4.34, p < .001, but not for 5-year-olds, t(30) = −0.86, p = .397.

        <hss>Verbal responses for the explanation condition</hss>

        The coding of verbal responses from children in the explanation condition resulted
        in 38 children designated as explainers (10 3-year-olds, 14 4-year-olds, and 14
        5-year-olds) and 10 children designated as non-explainers (6 3-year-olds, 2
        4-year-olds, and 2 5-year-olds). Although there was a trend for older children to
        produce more responses coded as explanations than younger children, the
        distribution of designations did not differ significantly across age groups, p =
        .17. We analyzed the relationship between children’s verbal response designation
        (explainer or non-explainer) and their performance on the causal and non-causal
        learning tasks with a repeated-measures ANOVA2 using type of verbal response as a
        between-participants factor (explainer or non-explainer), age group as a between-
        participants factor (3-, 4-, or 5-year-olds), type of learning as a within-
        participants factor (causal learning or non-causal learning), and learning score
        as the dependent measure. This analysis revealed the predicted interaction between
        designation and type of learning, F(1, 46) = 19.90, ηp2 = .32, p < .001. On
        measures of causal learning, children who explained (M = 1.21, SD = .58)
        outperformed those who did not (M = .40, SD = .52), t(46) = −4.03, p < .001. But
        on measures of non-causal learning, children who explained (M = .42, SD = .55)
        performed no better than those who did not (M = .60, SD = .84), t(46) = 0.81, p =
        .42. There was no reliable main effect of age, F(2, 44) = 1.59, p = .21, and a
        marginal main effect of designation, F(1, 44) = 3.18, p = .08.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The primary objective in Study 1 was to investigate the selectivity of explanation’s
effects on young children’s learning. The data suggest that the benefits of explanation
are indeed selective; although children prompted to explain performed better on measures
of causal learning, they performed significantly worse when it came to non-causal
learning. This suggests that effects of explanations did not result from an indiscriminate
increase in attention or engagement but rather were a consequence of the specific
processes invoked through explanation. We also found age-related improvement in
performance; the 4- and 5-year-olds outperformed the 3-year-olds, and whereas 3- and
4-year-olds’ explanation-prompted improvements in causal learning were accompanied by a
penalty for non-causal learning, this was not observed among 5-year-olds. Notably,
although the majority of responses in the explanation condition included explanations, a
substantial minority of responses did not. We found that the content of children’s verbal
responses was predictive of their performance on causal learning measures; children who
provided an explanation had higher causal learning scores than children who did not
provide an explanation. Thus, it is possible that the content of children’s responses to
an explanation prompt—and in particular whether they succeed in producing an
explanation—predicts children’s causal learning performance beyond mere verbalization or
description. Study 2 sought to examine how explicit prompts to explain versus describe
influence the extent to which children generate explanations and how their explanations
relate to learning. Doing so also provided a natural control for effects of verbalization
because all children were prompted to provide a verbal response.

<h>STUDY 2</h>
-------

In Study 1, the explanation condition required a verbal response, whereas the observation
condition did not. Moreover, participants in the explanation condition were instructed to
explain with a potentially leading prompt—to tell the experimenter how the machine works.
Thus, it is unclear whether children’s explanations in the absence of a prompt about how
the machine works would similarly direct learners to causal understanding. Study 2
addressed these concerns by requiring verbalization in response to a very undirected
prompt in all conditions and by once more analyzing performance as a function of the
content of children’s responses. In Study 2, children received a general prompt to either
explain the machine or to describe the machine. By using these undirected prompts, we
hoped to experimentally alter the proportion of children providing explanations while also
generating enough variability in the content of children’s responses within each condition
to permit a comparison of children who did and did not explain regardless of experimental
prompt. Thus, the experiment involved two conditions—describe prompt and explain
prompt—with all verbal responses also coded for the presence of explanations. We predicted
that the content of children’s verbal responses (i.e., generating an explanation) would
predict performance on the learning measures; children who provided an explanation would
perform better on causal learning measures than children who provided alternative
responses and potentially mirror the impairments for non-causal learning observed in Study
1. Study 2 also included an additional measure—generalization from one mechanical device
to another. At the end of the task, participants were invited to create a new device.
Given the close relationship between explanation and generalization (e.g., Lombrozo, 2012;
Lombrozo & Carey, 2006), we anticipated that explanation would increase the extent to
which children generalized the functional properties of the first machine to the second.

        <hss>Participants</hss>

        A sample of 87 children (23 3-year-olds, 19 4-year-olds, 24 5-year-olds, and 21
        6-year-olds) participated. Children were recruited from preschools in a major
        metropolitan area in the American Southwest. The sample was approximately gender
        balanced and primarily Euro-American and middle class, with an equal number of
        children from each age group assigned to each condition. Although Study 1 revealed
        main effects of age on performance, the single interaction between age and effects
        of explanation suggested a break between the 3- and 4-year-olds, for whom
        explanation led to impairments on non-causal learning, and the 5-year-olds, for
        whom it did not. Given our otherwise small sample sizes, therefore, we grouped
        children into younger (3–4 years) and older (5–6 years) age groups for analysis in
        Study 2: 42 3- and 4-year-olds (M = 45.9 months, SD = 6.73) and 45 5- and 6-year-
        olds (M = 70.48 months, SD = 7.14). Children were tested in a quiet room in their
        preschool or a research laboratory at a major southwestern university; each
        session took 10 to 15 min. An additional 5 children participated but were dropped
        from the final sample due to either inability to engage with the task (n = 2) or
        experimenter error (n = 3).

        <hss>Materials</hss>

        In addition to the materials from Study 1, there were 18 parts used during a
        generalization task (detailed below).

            <hss>Training task</hss>

            The training procedure was identical to that in Study 1.

            <hss>Experimental task</hss>

            Following training, the experimenter placed the previously hidden machine in
            front of the child. In all conditions, the experimenter pointed out the crank
            and fan and turned the crank to demonstrate that this made the fan turn. Then
            the child observed the machine (which was no longer in motion) for 40 s in one
            of two conditions. In the explain prompt condition, the child was prompted
            with, “Explain the machine to me,” which was followed up with “Can you explain
            anything else?” if the child stopped before the 40-s period ended. In the
            describe prompt condition, the child was told, “Describe the machine to me,”
            with “Can you tell me anything else?” as a follow-up prompt. In both
            conditions, the child’s responses were recorded on video.

            <hss>Learning tasks</hss>

            The learning tasks were identical to those in Study 1.

            <hss>Generalization task</hss>

            In the generalization task, the child was told, “Okay! Now I have new things
            to show you. Now it is your turn to make a machine.” The child was provided
            with a new base made up of six interlocking base parts, six new gears, and six
            new peripheral parts. The base was pre-constructed, and the peripheral parts
            and gears were laid out next to it in the same order for each child (see Fig.
            1E). The child was given 3 min to create his or her own machine.

            <hss>Experimental task</hss>

            Children’s verbal responses in the explain prompt and describe prompt
            conditions were coded for the presence of explanations as in Study 1. If
            children provided a mechanistic or functional explanation (i.e., made a claim
            about proximate causal processes or the goal or function of a particular part
            or process; see Kelemen, 1999; Lombrozo, 2009; Lombrozo & Carey, 2006), they
            were coded as explainers (e.g., “You just have to move it [the handle] around
            and then the fan turns around and the bottom things [points to middle gears]
            turn around too, and that top [peripheral part] spins too”). Children who did
            not make such statements were coded as non-explainers. Verbal protocols were
            coded by two independent coders with agreement of 91% (kappa = .86).
            Disagreements were resolved by discussion.

            <hss>Learning measures and reconstruction task</hss>

            The choice and reconstruction tasks were coded as in Study 1.

            <hss>Generalization task</hss>

            Children’s behavior during the generalization task was coded for whether gears
            were placed on the base, whether gears interlocked, whether the handle and the
            fan were placed on gears on the base, and whether the gears with the handle
            and fan interlocked. Meeting all of these criteria successfully recreated the
            functional–mechanical basis of the original machine and corresponded to the
            causal generalization score, with success coded as 1 and failure coded as 0.

<hs>  Results</hs>
  ~~~~~~~

Table 2 reports the proportions of correct responses as a function of children’s verbal
responses for the five key dependent variables (causal choice, color choice, causal
reconstruction, topper reconstruction, and causal generalization) for younger and older
children. Table 3 reports the proportions of correct responses as a function of children’s
verbal responses for the five key dependent variables (causal choice, color choice, causal
reconstruction, topper reconstruction, and causal generalization) by age in years (3-, 4-,
5-, and 6-year-olds). Fig. 3 reports the average causal and non-causal learning scores, as
detailed below.

        <hss>Verbal responses</hss>

        The verbal response coding resulted in 38 children designated as explainers (12
        younger and 26 older) and 49 children designated as non-explainers (30 younger and
        19 older). Children were equally likely to be designated as explainers versus non-
        explainers across the explain prompt and describe prompt conditions (17 of 41 vs.
        21 of 46), χ2(1, N = 87) = 0.1546, p = .694; that is, the prompts were equally
        effective at generating explanations, potentially because children failed to
        differentiate between a request to explain and a request to describe. Moreover,
        experimental condition (describe prompt or explain prompt) was not related to
        causal learning score, non-causal learning score, or generalization. In subsequent
        analyses, therefore, we report performance as a function of designation (non-
        explainer or explainer) while also taking into account that older children were
        more likely to be designated as explainers than younger children, χ2(1, N = 87) =
        7.53, p = .006.

        <hss>Learning measures as a function of coded designation</hss>

        A repeated-measures ANOVA with designation as a between-participants factor
        (explainer or non-explainer), age group as a between-participants factor (younger
        or older), and learning score as a within-participants factor (causal learning
        score or non-causal learning score) revealed the predicted interaction between
        designation and learning score, F(1, 83) = 26.627, ηp2 = .243, p < .001. On
        measures of causal learning, children who explained (M = 1.71, SD = .46)
        outperformed those who did not (M = .80, SD = .74), t(85) = 6.71, p < .001 (Fig.
        3). But on measures of non-causal learning, children who explained (M = .79, SD =
        .66) performed no better than those who did not (M = .96, SD = .68), t(85) =
        −1.17, p = .25 (Fig. 3). There was also a main effect of learning measure, F(1,
        83) = 15.762, ηp2 = .16, p < .001, with higher scores for causal learning (M =
        1.20, SD = .78) than non-causal learning (M = .89, SD = .67); a main effect of
        designation, F(1, 83) = 6.020, ηp2 = .068, p = .016, with higher scores for
        explainers (M = 1.25, SD = .45) than non-explainers (M = .88, SD = .53); and a
        main effect of age group, F(1, 83) = 11.137, ηp2 = .118, p = .001, with older
        children (M = 1.24, SD = .46) outperforming younger children (M = .82, SD = .50).
        Because older children were more likely than younger children to be designated as
        explainers, the preceding analysis potentially confounds designation with age.
        Therefore, we repeated the analysis within each age group to ensure that age did
        not drive the critical interaction between designation and learning measure. For
        the younger children, a repeated-measures ANOVA with designation (explainer or
        non-explainer) as a between-participants factor and learning measure (causal
        learning or non-causal learning) as a within-participants factor again revealed
        the predicted interaction between designation and learning measure, F(1, 40) =
        13.915, ηp2 = .258, p = .001, as did the equivalent analysis for older children,
        F(1, 43) = 12.686, ηp2 = .228, p = .001. For older children, there was also a
        significant main effect of learning measure, F(1, 43) = 19.358, ηp2 = .310, p <
        .001, with higher scores for causal learning (M = 1.56, SD = .66) than non-causal
        learning (M = .93, SD = .65), as well as a significant main effect of designation,
        F(1, 43) = 6.422, ηp2 = .130, p = .015, with higher scores for explainers (M =
        1.38, SD = .36) than non-explainers (M = 1.05, SD = .52).

        <hss>Generalization as a function of designation</hss>

        When analyzing generalization performance as a function of designation, explainers
        performed significantly better (32 of 38 succeeding) than non-explainers (27 of 49
        succeeding), χ2(1, N = 87) = 8.31, p = .004. To test for differences across groups
        while accounting for the uneven distribution of ages across designations, we
        performed a logistic regression on generalization performance with age group
        entered in a first step and designation entered in a second step. This analysis
        revealed a significant effect of designation, p = .023 (β = −1.25, SE = .55), as
        well as a marginal effect of age group, with older children (36 of 45) more likely
        to succeed than younger children (23 of 42), p = .072 (β = .917, SE = .51).

<hs>  Discussion</hs>
  ~~~~~~~~~~

Our objective in Study 2 was to replicate and extend key findings from Study 1. First, we
succeeded in finding reliable effects of explanation when comparing the content of
children’s responses rather than the experimental prompt that they received. As in Study
1, children who explained outperformed non-explainers on measures of causal learning but
not on measures of non-causal learning. This result is important in establishing that
effects of explanation do not derive solely from the use of language given that all
children produced verbal responses. That effects of explanation were not eliminated when
compared with alternative kinds of verbalization is especially striking in the context of
our two studies given that the non-causal properties that we tested (e.g., color) were, if
anything, easier to express linguistically than the causal properties (e.g., gear shape).
The verbal prompt conditions (explain prompt and describe prompt) were equally effective
at prompting children to produce explanations. Thus, our analyses were based on the
content of children’s responses, and the effects of explanation in Study 2 are
correlational. Nonetheless, our data demonstrate that children’s explanatory responses are
predictive of learning. The effects of the content of children’s responses in Study 2
nicely complement the effects of prompted explanation in Study 1, as children’s responses
were elicited by general prompts to explain or describe (as opposed to the explicit
questions about how the machine works used in Study 1). Across both studies, therefore, we
have evidence for a causal relationship between explanation and learning (Study 1) that is
mirrored in the content of children’s responses (Studies 1 and 2).

<h>GENERAL DISCUSSION</h>
------------------

Our studies had three objectives: (a) to differentiate effects of explanation from those
due to observation (Study 1) or verbalization (Study 2), (b) to examine whether and how
prompts to explain selectively benefit young children’s causal learning and may impair
non-causal learning (Studies 1 and 2), and (c) to examine potential age-related
differences in the effects of explanation on children’s learning (Studies 1 and 2). In
Study 1, children prompted to explain outperformed others on causal learning but not on
memory for causally irrelevant details. In both Studies 1 and 2, children who provided an
explanatory verbal response outperformed those who provided other verbal responses on
measures of causal learning, but again this benefit did not extend to memory for causally
irrelevant details. Notably, when it came to generalizing a function from one toy to
another, explainers outperformed non-explainers. Thus, our data suggest that effects of
explanation are distinct from those of observation or other kinds of verbalization and
result in selective rather than general benefits for learning, even leading to impairments
for younger children. In our task, explaining directed learners to functional–mechanical
understanding but not to causally irrelevant details, a trend that was observed across age
groups. Why might explanation exert these selective effects? One possibility is that
explanation is simply a constructive activity (Chi, 2009) or goal-directed activity
(Nelson, 1973). We propose instead that although explanation likely recruits many
cognitive processes that are shared with other kinds of constructive and goal-directed
activities, explanation is especially conducive to causal learning and generalization. In
the Introduction, we presented the hypothesis that explaining encourages learners to focus
on causal mechanisms and generalization (Legare, 2012; Lombrozo, 2012; Williams &
Lombrozo, 2013) precisely because invoking mechanisms and broad generalizations is
characteristic of good explanations. Whereas other constructive and goal-directed
activities may sometimes share these characteristics incidentally, they can also direct
learners in a variety of alternative ways—depending on the nature of the task—and have
consequences that are more or less diffuse. In the Introduction, we also identified
several ways in which effects of explanation could change during the course of early
development. We found several age-related improvements in general performance, yet we
observed only two developmental changes involving explanation. First, in Study 1, 3- and
4-year olds who were prompted to explain exhibited impairments when it came to non-causal
learning, whereas 5-year-olds did not. This suggests that the beneficial effects of
explanation do have an associated cost, but one that may be realized only on more
difficult tasks or when cognitive resources are taxed. Second, in Study 2 (and to a lesser
extent in Study 1), we found evidence that older children were more likely than younger
children to generate verbal responses that were designated as explanations. Importantly,
however, the beneficial effects of explanation did not interact with age. We suggest that
older children are more likely to engage in explanation, both spontaneously and in
response to prompts, but that effects of explanation are predominantly a function of the
content and quality of the explanation rather than children’s age. Understanding the ways
in which explanation does—and does not—improve learning speaks not only to questions about
the development of causal knowledge but also to questions about how to most effectively
harness explanation for use in educational interventions. For example, research with young
children has shown that explanation benefits learning by increasing the efficiency of
strategy use whether the children generated the explanation or learned the explanation
from the experimenter (Crowley & Siegler, 1999). There is also evidence that generating
both self-explanations and explanations to others (i.e., caretakers) improves problem-
solving accuracy at posttest, with the greatest benefits for problem-solving transfer from
explanations to caretakers (Rittle-Johnson et al., 2008). Our findings suggest that these
effects may derive in part from the role of explanation in directing children toward
causal regularities (in these cases involving reasoning and the application of problem-
solving strategies) and that explanation can be less beneficial—and perhaps even
harmful—when the target of learning is more perceptual or descriptive. In educational
research with adolescents and college students, learners who explain meaning in text
either spontaneously or when prompted to do so understand more from the text and construct
better mental models of the content (e.g., Chi, Bassok, Lewis, Reimann, & Glaser, 1989;
Chi, DeLeeuw, Chiu, & LaVancher, 1994; Magliano, Trabasso, & Graesser, 1999; Trabasso &
Magliano, 1996). However, there are large individual differences in spontaneous engagement
in self-explanation and in the quality of students’ self-explanations. (e.g., Chi et al.,
1989, 1994). Whereas a high-quality self-explanation would indicate an understanding of
the meaning of the text, a low-quality self-explanation may involve description or
restatement of the text. Across studies, we find similar variation in young children’s
verbal responses to both explicit and more general explanation prompts and demonstrate
that the quality of verbal responses (i.e., presence of causal explanation) predicts
learning outcomes. Importantly, there is evidence that students can be trained to more
effectively self-explain text and that the use of high-quality self-explanation strategies
predict improved problem-solving performance (Bielaczyc, Pirolli, & Brown, 1995). For
example, McNamara, O’Reilly, Rowe, Boonthum, and Levinstein (2007) demonstrated that self-
explanation training improves reading comprehension to a greater extent than control tasks
(i.e., reading out loud), and there is also evidence that self-explanation training
increases engagement in elaboration, prediction, comprehension monitoring, the use of
logic, and overall reading comprehension, particularly for students with lower prior
content knowledge and for more difficult texts (McNamara, 2004; Ozuru, Briner, Best, &
McNamara, 2010). Taken together, these studies provide evidence that self-explanation can
be used productively as a learning strategy and that educational interventions can improve
the quality of explanations. Our research provides evidence that analogous training
methods may improve the quality of self-explanations in preschool-aged children. Our
studies also suggest that the precise content of the explanation prompt can have an
important influence on the content and quality of responses; although most children who
were prompted to explain how the machine works in Study 1 produced a response coded as
explanatory (38 of 48 children), a smaller proportion did so in Study 2 in response to the
undirected prompt to explain the machine (17 of 41 children). Finally, our findings that
explanation can improve causal learning and foster generalization also bear on claims
about the nature of development. A vast literature on development has challenged Piagetian
claims that young children are limited to concrete appearances (Piaget, 1930),
demonstrating instead that they recognize abstract relationships (e.g., Gopnik & Schulz,
2007) and unobserved properties (e.g., Gelman, 2003; Wellman & Gelman, 1992). Nonetheless,
little is known about the mechanisms by which children succeed in going beyond
appearances, as understanding causal function often requires (Sobel, Yoachim, Gopnik,
Meltzoff, & Blumenthal, 2007). We propose that explanation may be an especially powerful
tool for causal learning during early childhood precisely because its effects are
relatively selective, orienting young learners toward causal mechanisms and promoting
generalization.


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<ART>Selective facial mimicry of native over foreign speakers in preverbal infants
=============================================================================

Authors: Carina C.J.M. de Klerk, Chiara Bulgarelli, Antonia Hamilton, Victoria Southgate
DOI: 10.1016/j.jecp.2019.01.015
Year: 2019  |  Pages: 33-47
ASJC codes: 3204, 3205
Keywords: EMG, Group membership, Infancy, Mimicry, TPJ, fNIRS

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Mimicry, the spontaneous copying of others’ behaviors, plays an important role in social affiliation, with adults selectively mimicking in-group members over out-group members. Despite infants’ early documented sensitivity to cues to group membership, previous work suggests that it is not until 4 years of age that spontaneous mimicry is modulated by group status. Here we demonstrate that mimicry is sensitive to cues to group membership at a much earlier age if the cues presented are more relevant to infants. 11-month-old infants observed videos of facial actions (e.g., mouth opening, eyebrow raising) performed by models who either spoke the infants’ native language or an unfamiliar foreign language while we measured activation of the infants’ mouth and eyebrow muscle regions using electromyography to obtain an index of mimicry. We simultaneously used functional near-infrared spectroscopy to investigate the neural mechanisms underlying differential mimicry responses. We found that infants showed greater facial mimicry of the native speaker compared to the foreign speaker and that the left temporal parietal cortex was activated more strongly during the observation of facial actions performed by the native speaker compared to the foreign speaker. Although the exact mechanisms underlying this selective mimicry response will need to be investigated in future research, these findings provide the first demonstration of the modulation of facial mimicry by cues to group status in preverbal infants and suggest that the foundations for the role that mimicry plays in facilitating social bonds seem to be present during the first year of life.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

It is a common feeling: While talking to a friend or colleague, you suddenly realize that
you are copying her behavior or accent. This tendency to spontaneously and unconsciously
copy or “mimic” others’ behaviors has been suggested to play an important role in social
interactions. For example, it contributes to the development of liking and rapport between
strangers and makes social interactions more smooth and enjoyable (van Baaren, Janssen,
Chartrand, & Dijksterhuis, 2009). It has been suggested that mimicry can be used as a
strategy for social affiliation (Wang & Hamilton, 2012), and indeed studies have
demonstrated that adults increase mimicry toward people they like and in-group members,
while mimicry of out-group members is inhibited (for reviews, see Chartrand & Lakin, 2013;
Hess & Fischer, 2017; van Baaren et al., 2009). Despite the important social functions
that mimicry is hypothesized to serve, surprisingly little is known about the development
of this phenomenon. While reports of neonatal imitation of facial actions (e.g., Meltzoff
& Moore, 1983) have been subject to much criticism and doubt (e.g., Jones, 2009;
Oostenbroek et al., 2016), recent studies that used a more objective measure of mimicry
(i.e., electromyography [EMG]) have demonstrated that infants exhibit mimicry of emotional
and nonemotional facial actions from at least 4 months of age (de Klerk, Hamilton, &
Southgate, 2018; Isomura & Nakano, 2016) and that this early mimicry is modulated by eye
contact (de Klerk et al., 2018). However, it is unknown when other social factors, such as
group membership, start to modulate infants’ spontaneous mimicry behavior. In the current
study, therefore, we investigated whether mimicry is modulated by cues to group membership
in 11-month-olds. Previous research suggests that infants are sensitive to signals related
to group membership from an early age (Liberman, Woodward, & Kinzler, 2017). For example,
8-month-olds expect agents who look alike to act alike (Powell & Spelke, 2013), and 10-
and 11-month-olds show a preference for native foreign speakers compared to foreign
speakers (Kinzler, Dupoux, & Spelke, 2007) and for puppets who share their food
preferences (Mahajan & Wynn, 2012). Furthermore, 10- to 14-month-olds are more likely to
adopt the behaviors of native speakers, showing a greater propensity to try foods they
endorse (Shutts, Kinzler, McKee, & Spelke, 2009) and to imitate their novel object-
directed actions (Buttelmann, Zmyj, Daum, & Carpenter, 2013; Howard, Henderson, Carrazza,
& Woodward, 2015). However, in these latter studies where infants selectively imitated
object-directed actions of native speakers, it is difficult to determine whether infants’
imitative behaviors were predominantly driven by affiliation with the model or by the
motivation to learn normative actions from members of their own linguistic group, and most
likely both learning and social goals played a role (Over & Carpenter, 2012). Whereas the
conscious imitation of object-directed actions is considered an important tool for social
and cultural learning, the spontaneous unconscious mimicry of intransitive behaviors is
often thought to serve a predominantly social function such as signaling similarity and
enhancing affiliation (e.g., Lakin, Jefferis, Cheng, & Chartrand, 2003; but see also
Kavanagh & Winkielman, 2016). The current study, therefore, aimed to investigate whether
nonconscious mimicry is modulated by cues to group membership in infancy. Considering the
importance of facial information in our day-to-day social interactions, facial mimicry may
provide a particularly strong affiliative signal (Bourgeois & Hess, 2008); therefore, we
specifically focused on mimicry of facial actions. Whereas the majority of previous
studies on facial mimicry used emotional facial expressions as the stimuli (e.g., Isomura
& Nakano, 2016; Kaiser, Crespo-Llado, Turati, & Geangu, 2017), in the current study we
investigated infants’ tendency to mimic nonemotional facial actions, such as mouth
opening, to ensure that we were measuring motor mimicry processes without confounding them
with emotional contagion (Moody & McIntosh, 2011). Despite infants’ early sensitivity to
cues to group membership, the only previous study investigating the effect of group
membership on young children’s mimicry found that 4-year-olds, but not 3-year-olds, showed
modulation of overt behavioral mimicry by group status (van Schaik & Hunnius, 2016). Given
that our previous work has shown that facial mimicry is already flexibly modulated by gaze
direction at 4 months of age (de Klerk et al., 2018), this apparent insensitivity of
behavioral mimicry to group membership cues in preschoolers may seem perplexing. One
explanation for this finding may be that in the study by van Schaik and Hunnius (2016),
the authors used a minimal group paradigm in which the in- and out-groups were defined by
an arbitrary marker (i.e., t-shirt color). First devised by Tajfel (Tajfel, Billig, Bundy,
& Flament, 1971), this paradigm is based on adults’ tendencies to favor those who share a
superficial likeness with themselves. However, as van Schaik and Hunnius (2016) pointed
out, it is not obvious that such sensitivity to superficial attributes should be present
during early childhood. Alternatively, it could be that coding of overt behavioral mimicry
provides a less sensitive measure compared to facial mimicry as measured by EMG. Here, we
used language as a signal of group membership instead because it has been suggested that
this is a particularly potent cue to social structure (Liberman et al., 2017) and previous
research has shown that infants’ behavioral preferences are modulated by this cue from at
least 10 months of age (Kinzler et al., 2007). In the current study, 11-month-old infants
observed videos of facial actions (e.g., mouth opening, eyebrow raising) performed by
models who spoke to the infants in their native language (English; Native speaker
condition) or an unfamiliar foreign language (Italian; Foreign speaker condition) while we
measured activation of their mouth and eyebrow muscle regions using EMG to obtain an index
of mimicry. EMG captures the subtle muscle changes that occur during automatic facial
mimicry and likely provides a more objective and sensitive measure of mimicry compared to
that measured by observational coding. This is important for studying facial mimicry in
developmental populations, especially considering the controversy surrounding facial
mimicry in newborn infants (e.g., Jones, 2009; Oostenbroek et al., 2016). We
simultaneously used functional near-infrared spectroscopy (fNIRS) to investigate the
neural mechanisms underlying any differential mimicry responses, allowing us to
potentially shed more light on the underlying cognitive mechanisms. Given infants’
preference for linguistic in-group members (Kinzler et al., 2007; Liberman et al., 2017),
previous work demonstrating that behavioral, vocal, and facial mimicry are modulated by
group membership in adults (e.g., Bourgeois & Hess, 2008; Weisbuch & Ambady, 2008; Yabar,
Johnston, Miles, & Peace, 2006), and previous work demonstrating that even in infancy
facial mimicry can be flexibly deployed (de Klerk et al., 2018), we hypothesized that
infants would show greater facial mimicry of native speakers compared to foreign speakers.
In terms of neural activation, previous functional magnetic resonance imaging (fMRI)
research with adult participants has highlighted several regions that may be involved in
the selective mimicry of linguistic in-group members. First, the temporal parietal
junction (TPJ) has been suggested to play an important role in self–other differentiation
(Uddin, Molnar-Szakacs, Zaidel, & Iacoboni, 2006) and in the control of imitative
responses (Hogeveen et al., 2015; Spengler, von Cramon, & Brass, 2009). Furthermore,
previous work has demonstrated enhanced TPJ activation for interactions with in-group
members (Rilling, Dagenais, Goldsmith, Glenn, & Pagnoni, 2008) and during mimicry in an
affiliative context (Rauchbauer, Majdandžić, Hummer, Windischberger, & Lamm, 2015). It has
been suggested that the TPJ may be of particular importance in situations where salient
affiliative signals lead to a greater tendency to mimic, requiring a greater effort to
disambiguate one’s own actions from those of others (Rauchbauer et al., 2015). Based on
these findings, we hypothesized that if linguistic group status is indeed perceived as an
affiliative signal leading to enhanced facial mimicry, infants would exhibit greater
activation of temporoparietal regions during the observation of facial actions performed
by the native speaker compared to the foreign speaker driven by the enhanced effort needed
to differentiate their own actions from those of the model. The medial prefrontal cortex
(mPFC) is another area that may play a role in the current study given that it has been
implicated in reasoning about similar others (Mitchell, Banaji, & MacRae, 2005), shows
greater activation when interacting with in-group members (Rilling et al., 2008), and has
been shown to be involved in modulating mimicry (Wang & Hamilton, 2012; Wang, Ramsey, &
Hamilton, 2011). Based on these findings, we hypothesized that infants would also exhibit
greater activation over prefrontal areas during the observation of facial actions
performed by native speakers compared to foreign speakers.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 55 11-month-old infants observed the stimuli (for a description, see “Stimuli
and procedure” section) while we simultaneously measured their facial muscle responses
using EMG and their neural responses using fNIRS. The final sample consisted of 19 infants
who provided sufficient data to be included in the EMG analyses (Mage = 343 days, SD =
15.50, range = 316–375; 4 girls) and 25 infants who provided sufficient data to be
included in the fNIRS analyses (Mage = 342 days, SD = 14.99, range = 310–375; 9 girls).
This study was part of a longitudinal project investigating the development of mimicry,
and we tested all the infants who were able to come back for this second visit of the
project. Power analyses using effect sizes based on the previous visit of the project,
where we found evidence for social modulation of facial mimicry at 4 months of age (de
Klerk et al., 2018), revealed that a total sample size of 12 participants would have
provided enough power (.95 with an alpha level of .05) to identify similar effects.
Because we tried to get the infants to wear both the fNIRS headgear and the EMG stickers
on their face, the dropout rate for this study was relatively high, but still comparable
to other neuroimaging studies with a similar age range that used only one method (e.g., de
Klerk, Johnson, & Southgate, 2015; Stapel, Hunnius, van Elk, & Bekkering, 2010; van Elk,
van Schie, Hunnius, Vesper, & Bekkering, 2008). A total of 36 infants were excluded from
the EMG analyses due to technical error (n = 8), because they did not provide enough
trials for analyses due to fussiness (n = 14) or inattentiveness (n = 8), or because they
constantly vocalized or repeatedly put their fingers in their mouth (n = 4)—factors that
were likely to have resulted in EMG activity unrelated to the stimulus presentation. A
total of 30 infants were excluded from the fNIRS analyses due to a refusal to wear the
fNIRS headgear (n = 6), too many bad channels (n = 2), or because they did not provide the
minimum of 3 good trials per condition due to fussiness (n = 14) or inattentiveness (n =
6). One additional infant was excluded from both the fNIRS and EMG analyses because she
was exposed to Italian at least once a week, and another infant was excluded because the
older sibling had recently been diagnosed with autism spectrum disorder—a disorder with a
strong genetic component (Ozonoff et al., 2011) in which spontaneous facial mimicry has
been found to be atypical (McIntosh, Reichmann-Decker, Winkielman, & Wilbarger, 2006).
Because we did not selectively include only monolingual infants in the original sample for
the longitudinal project, 4 of the included infants were bilingual but heard English at
least 60% of the time. One additional infant was bilingual Italian (heard 75% of the time)
and French (heard 25% of the time), and for him the Italian speaker was coded as the
native speaker.1 Although one might expect weaker in- and out-group effects in bilingual
infants, previous research suggests that both monolingual and bilingual children prefer
in-group members who use a familiar language (Souza, Byers-Heinlein, & Poulin-Dubois,
2013). All included infants were born full-term, healthy, and with normal birth weight.
The study received approval from the institutional research ethics committee. Written
informed consent was obtained from the infants’ caregivers.

<hs>  Stimuli and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~

The experiment took place in a dimly lit and sound-attenuated room, with the infants
sitting on their parent’s lap at approximately 90 cm from a 117-cm plasma screen. Infants
were presented with videos of two models who spoke either English (Native speaker) or
Italian (Foreign speaker). Infants first observed 2 Familiarization trials during which
the models labeled familiar objects in either English or Italian. Thereafter, Reminder
trials, during which one of the models labeled a familiar object, and Facial Action
trials, during which the same model performed facial actions such as mouth opening and
eyebrow raising, alternated (see Fig. 1). Facial Action trials started with 1000 ms during
which the model did not perform any actions, followed by her performing three repeats of
the same facial action, each lasting 3000 ms. The Reminder and Facial Action trials were
alternated with 8000-ms Baseline trials consisting of pictures of houses, landscapes, and
landscapes with animals to allow the hemodynamic response to return to baseline levels.
The order of trials during the Familiarization phase was randomized, and the order of
trials during the Reminder and Facial Action phases was pseudorandomized to ensure that
infants saw a roughly equal number of eyebrow and mouth actions. Videos were presented
until the infants had seen 12 10-s Facial Action trials (6 Native and 6 Foreign) or until
the infants’ attention could no longer be attracted to the screen. Both the EMG and fNIRS
analyses focused only on the Facial Action trials. The role of the models (Native vs.
Foreign speaker) was counterbalanced across infants. To validate our procedure as tapping
infants’ preference for native speakers, at the end of the session infants were encouraged
to choose between the two models by reaching for a picture of one of the two models
presented on cardboard. The cardboard with the pictures was brought into the room by an
experimenter who was unaware which of the models in the videos had been the native
speaker. The experimenter held the cardboard in front of the infants without saying
anything to avoid biasing them toward choosing the native speaker.

<hs>  Video coding and data exclusion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Videos were coded offline to determine which trials could be included in the analyses.
Note that because the EMG and fNIRS signals have very different temporal resolutions and
are influenced by different types of noise, the exclusion criteria for the EMG and fNIRS
trials were not identical. For example, whereas facial mimicry as measured by EMG can be
recorded on a millisecond scale, the hemodynamic response takes several seconds to build
up. Therefore, each 3000-ms period during which a facial action was performed by the model
in the video was treated as a separate EMG trial, whereas for the fNIRS analyses we
treated the 10-s videos including three repeats of the same facial action as one trial
(see Fig. 1). EMG trials during which the infants did not see at least two thirds of the
action, or trials during which the infants vocalized, smiled, cried, or had something in
their mouth (e.g., their hand), were excluded from the analyses because EMG activity in
these cases was most likely due to the infants’ own actions. EMG trials during which the
infants pulled or moved the EMG wires were also excluded, as were trials during which
there was lost signal over either of the electrodes. Only infants with at least 2 trials
per trial type (Native_Mouth, Native_Eyebrow, Foreign_Mouth, or Foreign_Eyebrow) and at
least 6 trials per condition (Native_FacialAction vs. Foreign_FacialAction) were included
in the EMG analyses (previous infant EMG research used a similar or lower minimum number
of included trials; e.g., Isomura & Nakano, 2016; Turati et al., 2013). On average,
infants contributed 11 EMG trials per condition to the analyses: 6 trials for the
Native_Mouth trial type (range = 3–9), 5 trials for the Native_Eyebrow trial type (range =
2–8), 6 trials for the Foreign_Mouth trial type (range = 2–9), and 5 trials for the
Foreign_Eyebrow trial type (range = 2–9). The number of included EMG trials did not differ
between the Native and Foreign conditions (p = .509). fNIRS trials during which the
infants did not attend to at least two of the three facial actions, or trials during which
the infants were crying, were excluded from analyses. We also excluded Baseline trials
during which the infants were looking at their parents’ face or their own limbs. Only
infants with at least 3 trials per experimental condition (Native_FacialAction vs.
Foreign_FacialAction)2 were included in the fNIRS analyses (Lloyd-Fox, Blasi, Everdell,
Elwell, & Johnson, 2011; Southgate, Begus, Lloyd-Fox, di Gangi, & Hamilton, 2014). On
average, infants contributed 5 fNIRS trials per condition to the analyses: 5 trials in the
Native_FacialAction condition (range = 3–10) and 5 trials in the Foreign_FacialAction
condition (range = 3–8). The number of included fNIRS trials did not differ between the
two conditions (p = .83).

<hs>  EMG recording and processing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Bipolar EMG recordings were made using pediatric surface Ag/AgCl electrodes that were
placed on the cheek and forehead following recommendations by Fridlund and Cacioppo (1986)
with an inter-electrode spacing of approximately 1 cm to measure activation over the
masseter and frontalis muscle areas, respectively. The electrodes on the forehead were
embedded within the fNIRS headgear, with the inferior electrode affixed approximately 1 cm
above the upper border of the middle of the brow and the second electrode placed 1 cm
superior to the first one (Fridlund & Cacioppo, 1986) (see Fig. 2A). A stretchy silicone
band was tightly affixed over the headgear to ensure that the fNIRS optodes and EMG
electrodes made contact with the scalp and the skin, respectively. The electrodes were
connected to Myon wireless transmitter boxes that amplified the electrical muscle
activation, which was in turn recorded using ProEMG at a sampling rate of 2000 Hz. After
recording, the EMG signal was filtered (high-pass: 30 Hz; low-pass: 500 Hz), smoothed
(root mean square over 20-ms bins), and rectified. The EMG signal was segmented into
3000-ms epochs, and the average activity in each epoch was normalized (i.e., expressed as
z-scores) within each participant and each muscle group (masseter and frontalis regions)
before the epochs for each trial type were averaged together. Because facial mimicry can
be defined as the presence of greater activation over corresponding muscles than over non-
corresponding muscles during the observation of facial actions (e.g., McIntosh et al.,
2006; Oberman, Winkielman, & Ramachandran, 2009), we calculated a mimicry score per trial
by subtracting EMG activity over the non-corresponding muscle region from EMG activity
over the corresponding muscle region (e.g., on an eyebrow trial, we subtracted activity
over the masseter region from activity over the frontalis region so that a more positive
score indicates more mimicry).

<hs>  fNIRS recording and processing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

fNIRS data were recorded using the University College London (UCL)–NIRS topography system,
which uses two continuous wavelengths of near-infrared light (770 and 850 nm) to detect
changes in oxyhemoglobin (HbO2) and deoxyhemoglobin (HHb) concentrations in the brain and
has a sampling rate of 10 Hz (Everdell et al., 2005). Infants wore custom-built headgear
with a total of 26 channels, with a source–detector separation of 25 mm over the temporal
areas and 4 channels with a source–detector separation of 30 mm over the frontal area. The
headgear was placed so that the third optode was centered above the pre-auricular point
(directly over T7 and T8 according to the 10–20 system) (see Fig. 2B). Based on the
understanding of the transportation of near-infrared light through tissue, this
source–detector separation was predicted to penetrate up to a depth of approximately 12.5
mm from the skin surface for the temporal areas and a depth of approximately 15 mm from
the skin surface for the frontal areas, allowing measurement of both the gyri and parts of
the sulci near the surface of the cortex (Lloyd-Fox, Blasi, & Elwell, 2010). Previous
research using coregistration of fNIRS and MRI using the same array design for the
temporal areas has demonstrated that this design permits measurement of brain responses in
cortical regions corresponding to the inferior frontal gyrus (IFG), superior temporal
sulcus (STS), and TPJ areas (see Lloyd-Fox et al., 2014). The frontal array was designed
to measure brain responses in mPFC (Kida & Shinohara, 2013; Minagawa-Kawai et al., 2009).
Data were preprocessed using a MATLAB software package called HOMER2 (MGH–Martinos Center
for Biomedical Imaging, Boston, MA, USA) and analyzed using a combination of custom MATLAB
scripts and the Statistical Parametric Mapping (SPM)–NIRS toolbox (Ye, Tak, Jang, Jung, &
Jang, 2009). Data were converted to . nirs format, and channels were excluded if the
magnitude of the signal was greater than 97% or less than 3% of the total range for longer
than 5 s during the recording. Channels with raw intensities smaller than 0.001 or larger
than 10 were excluded, and motion artifacts were corrected using wavelet analyses with 0.5
times the interquartile range. Hereafter, the data were band-pass filtered (high-pass:
0.01 Hz; low-pass: 0.80 Hz) to attenuate slow drifts and high-frequency noise. The data
were then converted to relative concentrations of HbO2 and HHb using the modified
Beer–Lambert law. We excluded from analysis any channels that did not yield clean data for
at least 70% of the infants. This resulted in the exclusion of three channels associated
with a source that was faulty for a subset of the assessments (Channels 21, 23, and 24).
As in previous infant fNIRS studies (e.g., Southgate et al., 2014), infants for whom more
than 30% of remaining channels were excluded due to weak or noisy signal were excluded
from analysis (n = 2). Note that for these 2 excluded infants, the intensities were very
weak over more than 30% of the channels because the fNIRS headgear was not fitted
properly. Our data analysis approach was determined a priori and followed Southgate et al.
(2014). For each infant, we constructed a design matrix with five regressors. The first
regressor modeled the Native Reminder trials (duration = 6 s), the second regressor
modeled the Foreign Reminder trials (duration = 6 s), the third regressor modeled the
Native_FacialAction trials (duration = 10 s), the fourth regressor modeled the
Foreign_FacialAction trials (duration = 10 s), and the fifth regressor modeled the
Baseline trials (duration = 8 s). Excluded trial periods were set to zero, effectively
removing them from the analyses. The regressors were convolved with the standard
hemodynamic response function to make the design matrix (Friston, Ashburner, Kiebel,
Nichols, & Penny, 2011). This design matrix was then fit to the data using the general
linear model as implemented in the SPM–NIRS toolbox (Ye et al., 2009). Beta parameters
were obtained for each infant for each of the regressors. The betas were then used to
calculate a contrast between the different conditions of interest for each infant.
Although in principle the HbO2 and HHb responses should be coupled, with HbO2 responses
going up and HHb responses going down in response to stimulus presentation, studies with
infant participants often do not find statistically significant HHb changes (Lloyd-Fox et
al., 2010; Lloyd-Fox, Széplaki-Köllőd, Yin, & Csibra, 2015). Therefore, as in previous
infant fNIRS studies, our analyses focused on changes in HbO2. To ensure statistical
reliability, and given that previous research has shown that our cortical areas of
interest (e.g., STS, TPJ, IFG) are unlikely to span just one channel (Lloyd-Fox et al.,
2014), we considered that activation at a single channel would be reliable only if it was
accompanied by significant activation at an adjacent channel (Lloyd-Fox et al., 2011;
Southgate et al., 2014). To implement this, we created a Monte Carlo simulation of p
values at every channel of our particular array and, on 10,000 cycles, tested whether p
values for two or more adjacent channels fell below a specific channel threshold. We
repeated the simulations for a range of channel thresholds and then selected the channel
threshold that led to a whole-array threshold of p < .05 for finding two adjacent channels
activated by chance. The appropriate channel threshold was 0.0407, so we considered only
effects present at p < .0407 in two adjacent channels to be interpretable.

<hs>  EMG</hs>
  ~~~

A repeated-measures analysis on the mimicry scores (activation over the corresponding
muscle region minus activation over the non-corresponding muscle region) with condition
(Native vs. Foreign speaker) and action type (Eyebrow vs. Mouth) as within-participant
factors demonstrated a significant main effect of condition, F(1, 18) = 6.07, p = .024,
ηp2 = .252. There were no other significant main effects or interactions. As can be seen
in Fig. 3, infants showed significantly greater mimicry of facial actions performed by the
native speaker compared to the foreign speaker. The mouth and eyebrow mimicry scores in
the Native condition were not significantly different from zero (ps > .149), but the
average mimicry score in the Native condition was, t(18) = 2.407, p = .027. This
demonstrates that, overall, infants were significantly more likely to show greater
activation over the corresponding facial muscles compared to the non-corresponding facial
muscles when they observed the facial actions performed by the native speaker. (See the
online supplementary material for the same analyses performed on the individual muscle
activation as well as a depiction of the EMG signal over the masseter and frontalis muscle
regions time-locked to the onset of the facial actions.)

        <hss>Baseline correction</hss>

        Note that the analyses reported above were planned a priori and followed our
        previous work (de Klerk et al., 2018). There are several reasons why we did not
        use baseline-corrected EMG values in these analyses. First, if we define mimicry
        as a relative pattern of muscle activation in which corresponding facial muscles
        are activated to a greater extent than non-corresponding facial muscles, it does
        not seem necessary to perform a baseline correction. Instead, by transforming the
        EMG activity to z-scores and calculating mimicry scores, we can measure infants’
        tendency to selectively activate the corresponding facial muscles to a greater
        degree than the non-corresponding facial muscles during the observation of facial
        actions. The second reason why we did not subtract activity during the baseline
        period from activity during the trials was that one of the main reasons for
        excluding trials at this age were vocalizations, and infants tended to vocalize a
        lot during the baseline stimuli. To maximize the number of trials that we could
        include, and hence the number of infants that could be included in the analyses,
        we decided not to also require there to be a valid baseline preceding each trial.
        However, on request of the reviewers, we have recoded the videos of the sessions
        to identify all valid baselines and reanalyzed the data using baseline-corrected
        values. In these analyses, the effect of condition was no longer significant (p =
        .193) and there was no evidence for mimicry. (See the supplementary material for
        more details as well as potential explanations for this discrepancy in the
        findings.)

<hs>  fNIRS</hs>
  ~~~~~

t Tests revealed that the left temporal parietal cortex was sensitive to the linguistic
status of the models. This region showed a significantly greater hemodynamic response
(based on HbO2) both when the Native_FacialAction condition was contrasted to the Baseline
condition and when it was compared to the Foreign_FacialAction condition (see Table 1).
This effect was present at p < .0407 over two adjacent channels (Channels 12 and 13; see
Fig. 4). No channels showed a significantly greater response in the Foreign_FacialAction
condition compared to the Native_FacialAction condition. Although we found one channel
over the frontal cortex (mPFC area) that showed a significant hemodynamic response for the
Foreign_FacialAction condition compared to the Baseline condition, there was no
significant difference between the two conditions over this channel. (See Supplementary
Fig. 2 for the beta values for all channels.)

<hs>  Relationship between EMG and fNIRS data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We initially planned to perform correlational analyses to investigate the relationship
between the EMG and fNIRS results. These analyses are underpowered (N = 15)3 due to the
relatively high dropout rate, however, we report the results here for completeness. We
found a marginally significant negative correlation between the Native_FacialAction >
Foreign_FacialAction contrast over the left temporal parietal cortex (Channels 12 and 13)
and the differential mimicry response (Native_FacialAction − Foreign_FacialAction), r(13)
= −.487, p = .066 (see Fig. 5). Suggesting that infants who showed a greater hemodynamic
response over the left temporoparietal area when observing facial actions performed by the
native speaker compared with the foreign speaker showed less mimicry of facial actions
performed by the native speaker compared with the foreign speaker (see Fig. 5). Note that
because this correlational analysis is underpowered, it needs to be interpreted with
caution.

<hs>  Choice task</hs>
  ~~~~~~~~~~~

Infants were significantly more likely to choose a picture of the native speaker compared
to the foreign speaker, χ2(1) = 6.54, p = .011. Of the 27 infants included in the EMG
and/or fNIRS analyses, 17 chose the native speaker, 5 chose the foreign speaker, and 5 did
not choose.

<h>DISCUSSION</h>
----------

This study is the first to demonstrate that the linguistic status of an observed model
modulates facial mimicry in infancy and that this modulation is accompanied by changes in
neural activation over the left temporal parietal cortex. These results show that one of
the hallmarks of mimicry—that it is modulated by cues to group membership—seems to be
present from at least 11 months of age. What is the psychological mechanism underlying
infants’ tendency to selectively mimic the native speaker? It is important to note from
the outset that the modulation of mimicry by the language of the model does not imply that
infants conceived of the native speaker as a member of their in-group (Liberman et al.,
2017). Infants are clearly sensitive to cues that correlate with group membership, such as
language familiarity, and this sensitivity modulates their attention and expectations
(Begus, Gliga, & Southgate, 2016). For example, infants may have considered the native
speaker to be a more useful source of information (Begus et al., 2016) or a more competent
person (Brooker & Poulin-Dubois, 2013) because she correctly labeled the familiar objects,
whereas they could not understand the foreign speaker. As a result of this, the native
speaker may have captured the infants’ attention to a greater extent, leading to increased
encoding of her facial actions and, consequently, greater activation of the associated
motor representations and greater mimicry—a process called input modulation (Heyes, 2013).
Although the fact that we did not find any significant differences in the number of
included trials between the conditions seems to speak against this interpretation, looking
is not necessarily equivalent to attending (Aslin, 2012); therefore, we cannot completely
rule out the possibility that there may have been enhanced encoding of the facial actions
performed by the native speaker. It is also possible that, like adults, infants may have
had a greater motivation to affiliate with the native speaker, and mimicking her facial
actions could have functioned as a means to communicate their similarity to the model (van
Baaren et al., 2009). Indeed, infants’ preference for the native speaker in the choice
test seems consistent with the idea that infants have an early emerging preference to
interact with familiar others (Kinzler et al., 2007). Although the facial mimicry we
observed was subtle and mainly detectable by EMG, previous studies suggest that our
emotions and social perceptions can be influenced by facial stimuli that we cannot
consciously perceive (Bornstein, Leone, & Galley, 1987; Dimberg, Thunberg, & Elmehed,
2000; Li, Zinbarg, Boehm, & Paller, 2008; Svetieva, 2014; Sweeny, Grabowecky, Suzuki, &
Paller, 2009). Therefore, regardless of the underlying mechanism—attentional effects or
affiliative motivations—the increased mimicry of in-group members during infancy is likely
to have a positive influence on social affiliation (Kavanagh & Winkielman, 2016; van
Baaren et al., 2009) and, therefore, can be expected to be reinforced over the course of
development (Heyes, 2017). A question that remains is how the facial mimicry that we
measured in the current study relates to the overt mimicry behaviours observed in the
original adult studies on behavioral mimicry (e.g., Chartrand & Bargh, 1999). In the adult
literature, facial mimicry is generally placed in the same context as the spontaneous
mimicry of other nonverbal behaviors such as postures and gestures (e.g., Chartrand &
Lakin, 2013; Stel & Vonk, 2010; van Baaren et al., 2009). Indeed, facial mimicry as
measured by EMG and mimicry of postures, gestures, and mannerisms share many properties;
they both seem to occur without conscious awareness (Chartrand & Bargh, 1999; Dimberg et
al., 2000), are influenced by the same factors such as group membership (Bourgeois & Hess,
2008; Yabar et al., 2006), and are supported by similar neural mechanisms (Likowski et
al., 2012; Wang & Hamilton, 2012). Furthermore, it has been suggested that the subtle
mimicry that can be measured by EMG may be a building block for more overt and extended
matching (Moody & McIntosh, 2006, 2011). Potentially, this constitutes a quantitative
change rather than a qualitative change, where the mimicry becomes overtly visible
whenever the activation of the motor representation in the mimicker reaches a certain
threshold. Future research will need to investigate the relationship between overt
behavioral mimicry and subthreshold mimicry measured by EMG in more detail to determine
whether they are indeed two sides of the same coin or rather distinct processes. The fact
that EMG can pick up on relatively subtle mimicry may also explain the discrepancy between
the current study’s findings and those of van Schaik and Hunnius (2016). In that study,
4-year-olds, but not 3-year-olds, showed modulation of behavioral mimicry (e.g., yawning,
rubbing the lips) depending on whether the model was wearing the same t-shirt color as
them. One possibility is that children younger than 4 years are not sensitive to
superficial attributes such as t-shirt color (van Schaik & Hunnius, 2016) or that they
lack experience with being divided into teams based on such attributes. Alternatively, it
could be that coding of overt behavioral mimicry is less sensitive than facial mimicry as
measured by EMG. Future research should investigate whether a minimal group paradigm might
elicit selective mimicry in children younger than 4 years when more sensitive measures,
such as facial mimicry as measured by EMG, are used. Such an approach would also allow
researchers to investigate whether the selective mimicry effects found in the current
study would hold when language, familiarity, and competence factors are controlled for
across the in- and out-group members. It should be noted that although we found evidence
for mimicry overall, the mimicry scores for the mouth and eyebrow actions separately were
not significantly different from zero. In addition, when we performed baseline-corrected
analyses (see supplementary material), the effect of condition became nonsignificant and
there was no evidence for mimicry, suggesting that the mimicry responses we found here
might not be as robust as those reported in previous studies (e.g., Datyner, Henry, &
Richmond, 2017; Geangu, Quadrelli, Conte, Croci, & Turati, 2016; Isomura & Nakano, 2016).
There are several possible explanations for this. First of all, most of the previous
developmental studies on facial mimicry used emotional facial expressions as the stimuli.
One possibility is that muscle responses to these stimuli reflect emotional contagion, a
process in which the observed stimuli induce a corresponding emotional state in the child,
resulting in the activation of corresponding facial muscles, whereas mimicry of
nonemotional facial expressions, such as those used in the current study, reflects subtler
motor mimicry (Hess & Fischer, 2014; Moody & McIntosh, 2011). Future research will need to
investigate whether there are differences in the mechanisms underlying the mimicry of
emotional and nonemotional facial actions. A recent study suggests that the development of
facial mimicry is supported by parental imitation (de Klerk, Lamy-Yang, & Southgate,
2018). Thus, a second possibility is that the current study included a mixture of infants
who receive high and low levels of maternal imitation, resulting in a relatively high
level of variability in the mimicry responses, with some infants potentially not having
received a sufficient amount of correlated sensorimotor experience to support the mimicry
of the observed facial actions. We found a greater hemodynamic response in channels
overlying the left temporal parietal cortex during the observation of facial actions
performed by the native speaker compared to the foreign speaker. The temporal parietal
region, and the TPJ in particular, has been suggested to play a critical role in
disambiguating signals arising from one’s own and others’ actions (Blakemore & Frith,
2003), and some evidence suggests that it may play a role in these processes from an early
age (Filippetti, Lloyd-Fox, Longo, Farroni, & Johnson, 2015). Although the left
lateralization of our results seems inconsistent with previous research mainly implicating
the right TPJ in separating self- and other-generated signals (e.g., Spengler et al.,
2009), a recent study suggests that the bilateral TPJ is involved in this process
(Santiesteban, Banissy, Catmur, & Bird, 2015). One interpretation of our fNIRS findings is
that the Native speaker condition may have posed higher demands on differentiating between
self- and other-generated actions because it presented infants with a highly affiliative
context where the urge to mimic was strong (for similar results with adult participants,
see Rauchbauer et al., 2015). In other words, a possible consequence of infants’ enhanced
tendency to mimic the native speaker may have been an increased self–other blurring, which
led to greater compensatory activity over the temporal parietal cortex. In line with this
interpretation, the marginally significant negative correlation between the betas for the
contrast Native_FacialAction > Foreign_FacialAction over the left temporal parietal cortex
and the mimicry difference score suggests that those infants who showed a greater amount
of temporal parietal cortex activation may have maintained greater self–other
differentiation and showed a less pronounced selective mimicry response. However, given
that this correlational analysis was heavily underpowered, this finding needs to be
replicated in a larger sample. In addition, considering the limited amount of research on
the role of the TPJ in self–other differentiation during infancy, future research will
need to further investigate the role of this area in inhibiting mimicry responses during
infancy. Finally, the spatial resolution of fNIRS does not allow us to say with certainty
that the significant channels did not, at least in part, overlie the posterior STS (pSTS).
Therefore, another possible interpretation of our fNIRS findings is that greater
activation over the temporal parietal cortex during the observation of facial actions
performed by the native speaker reflects input modulation, that is, the Native speaker
condition may have captured the infants’ attention to a greater extent, leading to
enhanced encoding of her facial actions as indicated by greater activation over the pSTS.
This interpretation would be consistent with a previous study in which we found greater
activation over the pSTS in the condition associated with greater facial mimicry in
4-month-old infants (de Klerk et al., 2018). However, given that the significant channels
in the current study are located in a more posterior position on the scalp, they are
unlikely to reflect activation of the exact same area. Future fNIRS–fMRI coregistration
work would be beneficial to help tease apart the role of adjacent cortical areas in the
modulation of mimicry responses. One potential concern may be that the differences in
facial mimicry between the two conditions led to subtle artifacts in the fNIRS data that
created the differences in the hemodynamic response over the left temporal parietal area.
We should note that it seems unlikely that facial muscle contractions that cannot be seen
with the naked eye would cause artifacts large enough to result in a significant
difference between the two conditions. In addition, even if this did happen, it seems
highly unlikely that this would have specifically affected two adjacent channels over the
left hemisphere over a cortical area that is the farthest removed from the facial muscles
rather than the frontal channels that are directly on the forehead. Unlike in adults (Wang
et al., 2011), we did not find involvement of the mPFC in the modulation of mimicry in
infants. One possibility is that our frontal array was not optimal for measuring responses
in the mPFC, although previous studies using similar array designs have reported
differential responses over this area (Kida & Shinohara, 2013; Minagawa-Kawai et al.,
2009). Another possibility is that at this relatively young age, the selective mimicry
responses were mainly driven by bottom-up attentional processes, such as the tendency to
pay more attention to familiar others, whereas more top-down mechanisms start to play a
role in modulating mimicry behavior only once myelination of the relevant long-range
connections with the mPFC is more established (Johnson, Grossmann, & Kadosh, 2009). Future
research measuring functional connectivity during mimicry behaviors over the course of
development will need to investigate this further. Taken together, our results demonstrate
that facial mimicry is flexibly modulated by cues to group membership from at least 11
months of age. Although the exact mechanisms underlying this selective mimicry response
will need to be investigated in future research, these findings suggest that the
foundations for the role that mimicry plays in facilitating social bonds seem to be
present during the first year of life.


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<ART>Semantic content outweighs low-level saliency in determining children's and adults’ fixation of movies
================================================================================

Authors: Andrew T. Rider, Antoine Coutrot, Elizabeth Pellicano, Steven C. Dakin, Isabelle Mareschal
DOI: 10.1016/j.jecp.2017.09.002
Year: 2018  |  Pages: 293-309
ASJC codes: 3204, 3205
Keywords: Development, Dynamic, Eye movements, Faces, Gaze, Saliency, Visual attention

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

To make sense of the visual world, we need to move our eyes to focus regions of interest on the high-resolution fovea. Eye movements, therefore, give us a way to infer mechanisms of visual processing and attention allocation. Here, we examined age-related differences in visual processing by recording eye movements from 37 children (aged 6–14 years) and 10 adults while viewing three 5-min dynamic video clips taken from child-friendly movies. The data were analyzed in two complementary ways: (a) gaze based and (b) content based. First, similarity of scanpaths within and across age groups was examined using three different measures of variance (dispersion, clusters, and distance from center). Second, content-based models of fixation were compared to determine which of these provided the best account of our dynamic data. We found that the variance in eye movements decreased as a function of age, suggesting common attentional orienting. Comparison of the different models revealed that a model that relies on faces generally performed better than the other models tested, even for the youngest age group (<10 years). However, the best predictor of a given participant's eye movements was the average of all other participants’ eye movements both within the same age group and in different age groups. These findings have implications for understanding how children attend to visual information and highlight similarities in viewing strategies across development.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Eye tracking is increasingly being used to try to infer what people are doing (Hayhoe &
Ballard, 2005) or thinking (Kardan, Berman, Yourganov, Schmidt, & Henderson, 2015) based
solely on how they looked at a visual scene. One advantage of this method over, for
example, self-report or psychophysical testing is that it can readily be applied to
populations that are difficult to evaluate, from young babies (Jones, Kalwarowsky,
Atkinson, Braddick, & Nardini, 2014) to clinical populations, including autistic people
(e.g., see Papagiannopoulou, Chitty, Hermens, Hickie, & Lagopoulos, 2014, for a review)
and patients with Alzheimer’s disease (Crutcher et al., 2009). Although there has been a
great deal of work looking at modeling patterns of fixations in adults, particularly
looking at top-down and bottom-up influences (Itti, Koch, & Niebur, 1998; Xu, Jiang, Wang,
Kankanhalli, & Zhao, 2014), and there has been some important work examining how these
influences develop during a child’s first months and years (e.g., Amso, Haas, & Markant,
2014; Franchak, Heeger, Hasson, & Adolph, 2016; Frank, Vul, & Johnson, 2009), there has as
yet been no systematic examination of different models applied to viewing dynamic scenes
in school-age children compared with adults. We addressed this gap in the literature in
this study.

<hs>  Development of fixation behavior</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Certain viewing behaviors, such as looking at faces and stimuli with social relevance,
develop so early in childhood that they appear to be largely innate. For example, it is
well established that newborn babies preferentially track faces and face-like stimuli in
simple displays (Farroni et al., 2005; Johnson, Dziurawiec, Ellis, & Morton, 1991). Using
static (complex) images, several studies have shown that infants aged 6 months and older
orient to faces in images that contain non-face distractors (Di Giorgio, Turati, Altoè, &
Simion, 2012; Gliga, Elsabbagh, Andravizou, & Johnson, 2009; Gluckman & Johnson, 2013).
Frank, Vul, and Saxe (2012) used videos of objects, faces, children playing with toys, and
complex social scenes with young children aged 3–30 months. They showed further that
facial and bodily features that have social relevance, such as eyes, mouths, and hands,
capture infants’ and toddlers’ attention and that this capacity to direct their attention
to the stimuli that are potentially the most socially informative increases with age. In
another study, Frank, Amso, and Johnson (2014) reported an age-related increase in looking
at faces in complex videos (clips from Peanuts [Charlie Brown] and Sesame Street) in 3- to
9-month-old infants, which correlated with increased attentional orienting using a visual
search task, suggesting that the extent to which infants show social preferences may well
be underpinned by their ability to detect socially relevant stimuli in otherwise complex
dynamic scenes. Frank et al. (2014) finding is also consistent with a recent report
showing that infants over 4 months of age tended to look first and longest at faces,
whereas 4-month-olds tended to look at the most salient object in a display (Kwon,
Setoodehnia, Baek, Luck, & Oakes, 2016). Less is known, however, about the developments in
fixation behavior that take place beyond early childhood. Kirkorian, Anderson, and Keen
(2012) showed children (aged 1–4 years) and adults 20-min clips of television shows and
found that younger children fixated more regions over a larger area than did older
children. This variability was greatest immediately following scene cuts, which these
authors proposed is due to an inability to suppress attention to irrelevant features (from
the previous scene). More recently, Helo, Pannasch, Sirri, and Rämä (2014) examined
differences in scanning behavior in adults and children aged 2–10 years and reported that
fixation durations decreased and saccade amplitudes increased with age, at least with
static images of naturalistic scenes, which these authors attributed to gains in general
cognitive development. Similar age-related trends have been found in a preferential
looking task, with eye movement response times falling with age from 1 to 12 years
(Kooiker, van der Steen, & Pel, 2016). Interestingly, the response time to fixate highly
salient targets reduced more rapidly with age than did fixations to less salient targets.

<hs>  Modeling natural fixation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

One key question is precisely what is driving development in fixation behavior during
childhood. Biologically inspired models have been developed to account for patterns of
fixation within complex scenes and fall into two broad categories. Saliency models are
driven by low-level (pixel-based) saliency and predict that eye movements are drawn to
regions of visual information that differ locally in some basic feature (e.g.,
orientation, color) (Itti et al., 1998). In this scenario, fixation is mainly driven by a
bottom-up process that relies primarily on sensory (rather than cognitive) processing (Xu
et al., 2014). For simplicity, we refer to this class of model as “saliency” driven. The
second class of models, top-down models, suggests that our eye movements are largely
driven by cognitive or contextual factors. In this scenario, we expect that factors that
affect top-down processing (e.g., age) will influence performance. Although age may also
be considered a factor in bottom-up processing (as low-level sensory processing becomes
more developed), this is unlikely to be the case for older children given that low-level
sensory processes underlying acuity are adult-like by 3 years of age (Brown & Lindsey,
2009).

        <hss>Saliency-based models</hss>

        Most low-level models of fixation are based on Koch and Ullman’s (1985) and Itti
        et al. (1998) saliency model of visual attention in static images. These authors
        proposed that eye movements are preferentially driven by points of high image
        saliency, where the local statistics of an image patch differ from its surround.
        This model, and extensions of it, has been very influential (e.g., Baddeley &
        Tatler, 2006; Itti & Koch, 2000) and has spurred new analysis methods (e.g.,
        Barthelmé, Trukenbrod, Engbert, & Wichmann, 2013), but it has only recently begun
        to incorporate the importance of features of dynamic images such as object motion
        and transformation. This is a major shortcoming because a reliance on static
        scenes is likely to minimize the relevance of ongoing semantic context such as
        social relevance and knowledge of cause and effect. We return to this point below.

        <hss>Top-down models</hss>

        Nonvisual factors influence interobserver variability in fixation patterns
        (particularly in response to dynamic stimuli). For example, when a video clip of
        people conversing is accompanied by a soundtrack that matches the visual content,
        observers are more accurate at localizing the face of the speaker (Coutrot &
        Guyader, 2014). Here, the sound needs to be understood as a human voice in order
        to drive eye movements toward the inferred speaker. But note that it is possible
        in some cases that the synchrony of sounds and visual transients (e.g., mouth
        movements) by themselves may drive eye movements, in which case audio can act as a
        more bottom-up influence. Other high-level processes have been shown to contribute
        to eye movements. For example, object “importance” (’t Hart, Schmidt, Roth, &
        Einhauser, 2013), social cues (faces or gaze; e.g., Birmingham, Bischof, &
        Kingstone, 2009), task instructions (Ballard & Hayhoe, 2009; Koehler, Guo, Zhang,
        & Eckstein, 2014), a person’s prior expectation about a scene (Eckstein, Drescher,
        & Shimozaki, 2006), and a person’s memory of a visual task (Ballard & Hayhoe,
        2009) all can influence where a person allocates his or her attention in a visual
        scene and might not always be the region of highest saliency. A recent analysis of
        eye movements by Xu et al. (2014) investigated the potential influence of both
        bottom-up and top-down factors during fixation. They categorized static images
        into different attribute qualities: “pixel attributes” (low-level features akin to
        saliency), “object attributes” (e.g., object size, eccentricity), and “semantic
        attributes” (e.g., whether an object is being looked at by an individual in the
        scene). They reported that semantic-level attributes that would reflect top-down
        processing—particularly objects being gazed at, faces, and text—influenced
        observer fixations more than lower-level saliency.

        <hss>Dynamic stimuli</hss>

        It is increasingly recognized that fixation during prolonged presentation of
        static visual scenes might not be representative of natural viewing behavior of
        complex dynamic scenes. Consequently, dynamic stimuli (e.g., clips, movies) are
        increasingly being employed to gauge visually guided behavior. Yet, this new
        approach brings with it a new set of complications. For example, Dorr, Martinez,
        Gegenfurtner, and Barth (2010) reported that the type of dynamic stimulus used can
        largely influence performance. They reported a higher degree of variability of eye
        movements between observers when watching natural movies as compared with
        commercial movies. This finding arises largely because commercial movies suffer
        more from “center of screen bias” (e.g., relevant objects are framed in the center
        of the shot) as well as an increase in temporal structure arising from frequent
        cuts, whereas Dorr and colleagues’ natural movies were approximately 20 s uncut
        and were generally shot from fixed camera positions, meaning that the ongoing
        action in the clip would not necessarily have occurred in the center of the
        screen. In another example, Mital, Smith, Hill, and Henderson (2010) reported that
        gaze clustering across observers viewing a dynamic scene is determined mainly by
        motion within the clip. Although some of these studies have also quantified
        variability of eye movements, and studies have compared face and saliency models
        with adults and infants/toddlers (<4 years of age), there has been no systematic
        evaluation of different models that might account for changes in eye movement
        behavior in school-aged children viewing complex dynamic images. Furthermore, it
        has been shown that saliency is most influential in guiding the first fixations in
        static images, before top-down influences come into play (Parkhurst, Law, &
        Niebur, 2002). One expectation from this finding is that dynamic information may
        exacerbate the differences between early and later fixations. Specifically, we
        should expect that immediately after a scene cut, saliency will be more
        influential (we liken this to the first fixations in a static image), but that as
        the scene plays out, saliency influences will diminish. We also expect that, in
        general over the course of the clip, younger children’s viewing behavior will be
        better captured by a bottom-up saliency model than will that of adults.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

Here, we examined these changes in visual attention using a rich range of stimuli in which
we measure the age-dependent variability in eye movements in school-age children relative
to adults (taking into account scene cuts, which can lead to a change in semantic content
in a film). We used longer-duration clips (3–6 min) of three different child-friendly
movies (Roadrunner [cartoon], Night at the Museum, and Elf) to better examine the role of
top-down (semantic) influences on eye movements as observers follow the story, and we
sampled older children to allow these processes to have a greater influential role. These
methods enabled us to test two main accounts of visual attention across age groups: one
that relies on low-level saliency models and one that relies on the presence of faces in
the scene. Although much research has looked at eye movements in infants or young children
(e.g., Franchak et al., 2016; Frank et al., 2009; Kirkorian et al., 2012), we focused here
on older children to chart how the development of cognition and interest in social objects
is reflected in eye movements. We hypothesized that (a) we would observe an increased
consistency in fixations with age as reported in adults (e.g., Dorr et al., 2010), and
consistent with reports in infants (e.g., Frank et al., 2009) and young children (e.g.,
Kirkorian et al., 2012), and that (b) a model predicting fixation behavior based on faces
would outperform saliency models (Franchak et al., 2016; Frank et al., 2009).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 37 children from a range of ethnic backgrounds (identified by their parents as
19 Caucasian, 5 South Asian, 4 Black or Black/Caribbean, 3 Middle Eastern, 3 mixed race,
and the remaining 3 unspecified) took part in the experiment during 1 week of “Brain
Detectives,” a science club run at the UCL Institute of Education, University College
London. Because several of the analysis methods we used to quantify performance
(interobserver dispersion, cluster number, and normalized scanpath salience) depended on
comparing fixation patterns within groups of individuals, it was not possible to treat age
as a continuous variable in analyses. Therefore, we divided the children into two groups
of approximately equal numbers and age ranges: “younger” (<10 years; n = 20, 9 girls, mean
age = 7.8 years, range = 5.9–9.4) and “older” (≥10 years; n = 17, 12 girls, mean age =
11.9 years, range = 10.2–13.9). In addition, 10 adults (5 women, mean age = 31.9 years,
range = 23.0–45.1) were tested at the UCL Institute of Ophthalmology, University College
London. All participants reported normal or corrected-to-normal vision. Written informed
consent was obtained from the adults and from children’s parents prior to their or their
children’s participation in the experiment. The experiment was approved by Institute of
Education and Institute of Ophthalmology research ethics committees.

<hs>  Apparatus</hs>
  ~~~~~~~~~

Two identical systems were used for stimulus presentation and eye tracking. Calibration
sequences and movies were presented using MATLAB (MathWorks, Natick, MA, USA) and the
PsychToolbox (Brainard, 1997) running on Windows 7 PCs. Stimuli were displayed on LG
W2363D LCD monitors (1920 × 1080 pixels, refresh rate = 60 Hz). The displays were
calibrated using a photometer and linearized using lookup tables in software. Eye-tracking
data were collected on two EyeLink 1000 systems with remote cameras (SR Research,
Mississauga, Ontario, Canada) at 250 or 500 Hz. The reported average accuracy of the eye
tracker is 0.5°, the spatial resolution is 0.05°, and the remote camera allowed for head
movements of up to 22, 18, and 20 cm (horizontal, vertical, and depth, respectively).
Viewing distance was approximately 57 cm, so that 1 pixel subtended approximately 1.6
arcmin and movies (at a resolution of 1708 × 960 pixels) covered 43.4 × 25.1° of visual
angle. Children watched the videos individually while seated in a dimly lit room on a
chair whose height could be adjusted so that their eyes were roughly level with the center
of the screen. An experimenter was in the cubicle with them, seated at a different table,
controlling the eye tracker. The experimenter explained the procedure to the children and
informed them that they would be asked questions at the end of each clip. Adults viewed
the videos at the Institute of Ophthalmology in a dimly lit room. In all cases, no chin
rest was used.

<hs>  Stimuli</hs>
  ~~~~~~~

All participants watched two 5-min video clips and one 3-min video clip with their
corresponding soundtracks to enhance comprehension of, and engagement with, movie content.
One video was a cartoon (Roadrunner) and two others were taken from popular live-action
children’s movies (Night at the Museum and Elf). In terms of shot segmentation, a cut is
an abrupt transition from one shot to another that greatly affects visual exploration
(Garsoffky, Huff, & Schwan, 2007; Smith, Levin, & Cutting, 2012). In the following,
analyses were performed on each individual shot (see Table 1). As in Coutrot, Guyader,
Ionescu, and Caplier (2012), shots were automatically detected using a pixel-by-pixel
correlation value between two adjacent video frames. We ensured that the shot cuts
detected were visually correct.

<hs>  Eye-tracking procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Calibration routines were run at the start and end of each of the three clips with a
custom-made cartoon character (size = 1°) appearing at each of nine positions: the four
corners, the four midpoints of the edges, and the center of the movie frame. Each data
sequence was used to parse the x/y position signal into saccades and fixations/smooth
pursuits with a custom algorithm based on Nyström and Holmqvist (2010) (see below). In
adults, eye-tracking data were successfully recorded in 10 of 10 adults across all clips.
For the children, no data could be collected for 2 of 37 children (both in the younger age
group) because the eye tracker failed to locate and track their pupil. Intermittent loss
of the eye-tracking signal (due to either body or head motion while watching the clips)
led to data from a further 3 children (2 in the younger group and 1 in the older group)
missing from two clips, and 6 children (1 from the younger group and 5 from the older
group) had missing data from one clip.

<hs>  Data pre-processing</hs>
  ~~~~~~~~~~~~~~~~~~~

If the calibrations at the start and end of a clip were different (by visual inspection),
data from the corresponding clip were not used. For Clip 1 (Elf), 6 younger and 6 older
children were excluded; for Clip 2 (Night at the Museum), 11 younger and 7 older children
were excluded; and for Clip 3 (Roadrunner), 10 younger and 9 older children were excluded.
This left 10 adults, 14 younger children, and 11 older children with usable data for Clip
1; 10 adults, 9 younger children, and 10 older children for Clip 2; and 10 adults, 10
younger children, and 8 older children for Clip 3. Data where “start” and “end”
calibrations matched but there was a loss of signal for part of the clip were used, with
the corresponding signal-less sections cut out. Saccades were identified based on the
Nyström and Holmqvist (2010) iterative procedure that uses eye velocity and acceleration
to set thresholds. Any period when velocity or acceleration exceeds an upper threshold for
a minimum amount of time (10 ms) was classified as a saccade. The start- and end-points of
the saccade were identified by going backward or forward in time until both the velocity
and acceleration fell below a lower threshold. Saccades were identified to distinguish
periods of fixation or smooth pursuit. The eye position data are missing during a blink,
but there is also a period immediately before and after the blink when the dynamic
occlusion of the pupil by the eyelid generates large, spurious motion signals in the eye-
tracking data. The start- and end-points of blinks were identified using the lower
threshold, as above, and all data during a blink were removed from the analysis.
Estimating eye-tracking data quality is critical because systematic differences in the
quality of raw eye position data can create a false impression of differences in gaze
behavior between groups. This is particularly true when comparing children and adults
because children are more prone to postural change during testing than adults, leading to
generally poorer or more variable eye-tracking data. For this reason, we assessed our eye-
tracking data using the precision metric proposed by Wass, Forssman, and Leppänen (2014).
This metric quantifies the degree to which eye positions are consistent between samples
(the higher the metric, the less precise the eye data). For each participant, we averaged
this metric across the three video clips for an overall measure of precision.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Data were analyzed in two ways. First, we examined the variability between eye movements
across observers for age-related changes, that is, an analysis based entirely on eye-
tracking data (a gaze-based analysis). Second, we compared the eye-tracking data with the
movie content using standard low-level (salience-based) models as well as a model based
entirely on faces (a content-based analysis).

        <hss>Variability between participants: Gaze-based analysis</hss>

        As mentioned in the stimuli description, we performed our analyses on each frame
        of each individual shot.

            <hss>Interobserver dispersion</hss>

            To estimate the variability of eye positions between observers, we used a
            dispersion metric. This metric is commonly used in eye-tracking studies (Marat
            et al., 2009). For a given frame watched by n observers ((xi, yi) i∈[1, 2, ...
            n] the eye position coordinates), the dispersion D is defined as follows: The
            dispersion is the mean Euclidian distance between the eye positions of
            different observers for a given frame. The smaller the dispersion, the less
            scatter in the eye positions.

            <hss>Cluster number</hss>

            To quantify the number of points of interest attracting observers’ gaze, we
            performed a cluster analysis. For each frame, we clustered observers’ eye
            positions with the mean shift algorithm (Fukunaga & Hostetler, 1975). This
            algorithm considers feature space as an empirical probability density
            function. Mean shift associates each eye position with the closest peak of the
            dataset’s probability density function. For each eye position, mean shift
            defines a circular window of width w around it and computes the mean of the
            data points. Then, it shifts the center of the window to the mean and repeats
            the algorithm until it converges. This process is applied to every observer.
            All eye positions associated with the same density peak belong to the same
            cluster. The main advantage of mean shift compared with other popular
            clustering algorithms such as k-means is that it does not make assumptions
            about the number or shape of clusters. The only parameter to be tuned is the
            window width. Here, we took w = 100 pixels. Other w values between 50 and 200
            pixels did not significantly change the results.

            <hss>Faces-based model</hss>

            We compared variants of a saliency model against a faces-based model. For each
            clip, the faces were labeled using a custom MATLAB script. When a face first
            appeared on the screen, an ellipse was drawn around it. When the face moved
            during the scene (due to either person or camera movement), the position,
            orientation, aspect ratio, and size of the ellipse were updated in a small
            number of “keyframes” and interpolated in between times. This led to a
            relatively fast and accurate labeling of the whole clip. Points within these
            ellipses were set to 1, and outside they were set to 0, to produce a binary
            map that was then filtered with a three-dimensional spatiotemporal Gaussian
            filter (spatial SD = 1.06°, temporal SD = 26.25 ms) similar to that used by
            Dorr et al. (2010) to produce a “face map” akin to the saliency maps described
            below. Given the sparsity of visual information in the Roadrunner cartoon, for
            this clip only we also labeled objects in a similar manner, with the exception
            being that the outlines could be polygons as well as ellipses.

            <hss>Saliency models</hss>

            Three variants of the Itti et al. (1998) saliency model were applied to each
            movie: (a) Itti et al. (1998) and (b) Harel, Koch, and Perona (2006) graph-
            based visual saliency (GBVS) with motion/flicker channels and (c) Harel et al.
            (2006) GBVS without motion/flicker channels. All saliency models seek to
            extract regions that somehow differ from their surroundings. Itti et al.
            (1998) separated the image into three different channels based on luminance,
            color, and orientation, and within each channel they identified regions of the
            image that differ from their immediate surround. These individual maps were
            then linearly combined to produce an overall map highlighting unusual regions,
            with the implicit assumption that these regions are likely to draw our
            attention. The GBVS model similarly splits the image into separate channels
            (luminance, color, and orientation plus two dynamic channels, motion and
            flicker, based on differences between consecutive frames) and uses a graph-
            based approach to highlight unusual regions. Although the GBVS model is not as
            intuitive as the Itti et al. model, it has been shown to perform better for
            static images (Itti et al., 1998), and its incorporation of motion and flicker
            channels makes it appropriate for dealing with dynamic images.

            <hss>Comparison of model performance</hss>

            We used two methods of assessing the performance of each of the models. The
            first is the normalized scanpath salience (NSS), which has been extended to
            allow analysis of moving images (Dorr et al., 2010; Marat et al., 2009), and
            the second is the area under a receiver operating characteristic (ROC) curve
            (Green & Swets, 1966) as proposed for eye-tracking analysis by Tatler,
            Baddeley, and Gilchrist (2005).

            <hss>Normalized scanpath salience</hss>

            On a frame-by-frame basis, the salience (or face) maps were normalized by
            subtracting the mean and dividing by the standard deviation (face maps for
            frames in which no faces were present were set to 0; see Fig. 1). Regions
            where the model predicts a high probability of fixation will have positive
            values, and low-probability regions will be negative. The normalized saliency
            value for each fixation is then averaged across participants to give frame-by-
            frame model performance as well as across the duration of the movie to give an
            overall model performance value.

            <hss>Correlation between outputs of a faces-based model and saliency models</hss>

            To quantify any overlap between face maps and bottom-up saliency maps, we
            calculated the correlation between a faces-based model and saliency models.
            For each frame, we computed a pixelwise correlation between bottom-up saliency
            maps (Harel et al., 2006, GBVS and GBVS + motion/flicker; Itti et al., 1998)
            and face maps. Frames without a face have been discarded from the analysis.

            <hss>Area under the ROC curve</hss>

            The area under the curve (AUC) is often used as a measure of model
            performance. We threshold the saliency or face maps at different levels to
            find regions of predicted fixations for that particular threshold. By
            comparing these regions with where the actual fixations occurred, we can
            extract the proportion of “true positives” (proportion of fixations within the
            predicted region) and the proportion of “false positives” (pixels that the
            model highlighted but were not fixated). By varying the threshold between 0
            and 1, we produce an ROC curve (see panel in Fig. 4 in Results). The area
            under this curve is used as a measure of model performance. A value close to 1
            indicates that the model explains the data well, whereas chance performance is
            .50. We derived confidence intervals for the AUC values via bootstrapping.
            Although an AUC analysis has a well-defined upper bound of 1, it is more
            appropriate to extract an empirical upper bound from the eye-tracking data
            themselves. A low AUC score could be due to a poor model, high variability
            between the looking strategies of different people, or a combination of the
            two. A modification of Peters, Iyer, Itti, and Koch’s (2005) NSS can be used
            to overcome this problem (Dorr et al., 2010). The NSS is calculated by using a
            “leave one out” approach—taking the scanpaths of n − 1 observers,
            spatiotemporally blurring these, and summing and normalizing them to produce a
            map of where these n − 1 people fixated over time. This map is evaluated as a
            predictor of where the nth person fixates, using the area under an ROC curve
            as above. This process is repeated n times, once for each observer, and the
            NSS score is the average AUC value. We used a similar technique to compare
            both between and within groups, that is, using all of the younger children’s
            fixations to build a fixation map and using this map to predict either the
            older children’s or the adults’ fixations.

            <hss>Statistical analyses</hss>

            To compare our findings for different models, age groups, and movies, we
            performed one-way and two-way analyses of variance (ANOVAs) as appropriate.
            For any significant differences between conditions, we also performed pairwise
            comparisons using t tests with Bonferroni correction for multiple comparisons.

<hs>  Eye-tracking data variability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Using Wass et al. (2014) precision metric, we found no significant effect of age on
precision: one-way ANOVA, F(2, 45) = 1.52, p = .23 (younger children: precision = .92, SEM
= .19; older children: precision = .92, SEM = .19; adults: precision = .46, SEM = .03).

        <hss>Interobserver dispersion</hss>

        The shape of interobserver dispersion curves depicted in Fig. 2 (left panels) is
        conventional (Coutrot & Guyader, 2014). During the first 200 ms after a cut,
        dispersion is stable. During this period, observers’ gaze stays at the same
        locations as before the cut (latency period). Following this, dispersion decreases
        until 400 ms and slightly reincreases up to 1 s. This leads to the last stage,
        where the dispersion plateaus around a mean stationary value until the next cut.
        We ran a two-way ANOVA on interobserver dispersion with age (adults, older
        children, or younger children) and clip (Elf, Night at the Museum, or Roadrunner)
        as factors. There was a main effect of age, F(2, 707) = 20.76, p < .001, but not
        of clip, F(2, 707) = 2.87, p = .06. Post hoc Bonferroni tests showed that the
        dispersion was lower in adults than in older children, t(470) = −8.14, p < .001,
        or younger children, t(470) = −8.43, p < .001. There was no significant difference
        between the latter groups, t(470) = −0.29, p = .96. The interaction was also
        significant, F(4, 707) = 9.89, p < .001. For the Roadrunner clip, dispersion
        values were lower in younger children than in adults, t(74) = −2.20, p = .03, or
        in older children, t(74) = −2.68, p = .009. There was no difference between older
        children and adults, t(74) = 0.37, p = .71.

        <hss>Distance to center</hss>

        The global shape of distance to center is similar to the interobserver dispersion
        (Fig. 2, right panels). The stronger center bias around 200 ms after a cut has
        been reported previously (Wang, Freeman, Merriam, Hasson, & Heeger, 2012). It is
        due to a conjunction of factors, including the fact that the center of a scene is
        the optimal location to begin exploration (Tatler, 2007; Tseng, Carmi, Cameron,
        Munoz, & Itti, 2009). We performed a two-way ANOVA on distance to center with age
        and movie as factors. There was a main effect of age, F(2, 707) = 5.33, p = .005,
        and movie, F(2, 707) = 10.69, p < .001. Post hoc Bonferroni tests showed that the
        distance to center was significantly lower in adults than in older children,
        t(470) = −3.39, p = .002, or in younger children, t(470) = −4.00, p < .001. There
        was no significant difference between the latter groups, t(470) = −0.61, p > .90.

        <hss>Number of clusters</hss>

        The number of clusters quantifies the number of points of interest attracting
        observers’ gaze. Because this number is likely to increase with the number of
        observers, we normalized it by the number of participants. The number of clusters
        is stable across time except for a brief increase at around 200 ms after the
        beginning of the shot (Fig. 3). This increase can be explained by looking at the
        right panel of Fig. 3, where the temporal evolution of the number of recorded
        observers is depicted. We clearly see a loss of approximately 20% of recorded
        participants between 200 and 300 ms. This might be due to blinks induced by sharp
        cuts, leading to a brief loss of eye-tracking signal. Because the number of
        clusters is normalized by the number of participants, a decrease in the latter
        logically causes an increase in the former. We ran a two-way ANOVA on the number
        of clusters normalized by the number of observers with age and clip as factors.
        There was a main effect of age, F(2, 707) = 90.87, p < .001, and clip, F(2, 707) =
        91.59, p < .001. Post hoc Bonferroni tests showed that for Elf and Night at the
        Museum, the number of clusters was significantly lower in adults than in older
        children, t(394) = −5.26, p < .001, or in younger children, t(394) = −11.76, p <
        .001, and was significantly lower in older children compared with younger
        children, t(394) = −7.16, p < .001. For the Roadrunner clip, the number of
        clusters was still lower in adults than in older children, t(74) = −8.40, p <
        .001, or in younger children, t(74) = −4.83, p < .001, but surprisingly it was
        higher in older children compared with younger children, t(74) = 4.32, p < .001.

<h>MODELS</h>
------

Fig. 4 shows the model performances and the within- and between-group scanpath
similarities for the three clips, broken down by age group (younger children in black,
older children in red, and adults in blue). We performed a three-way ANOVA on the AUC with
age, clip, and model and their interactions as explanatory variables. Note that the models
included in this analysis were the three salience models: Harel et al.’s (2006) GBVS
model, either with (GBVS+M+F) or without (GBVS) motion and flicker components, and Itti et
al.’s (1998) multichannel saliency model (I&K). The faces-based model and the within-group
NSS model showed that there were significant differences in AUCs across age group, F(2,
44) = 158.77, p < .001, clip, F(2, 44) = 124.92, p < .001, and model, F(4, 44) = 520.43, p
< .001, as well as their interactions [Age × Movie, F(8, 44) = 8.37, p < .001; Age ×
Model, F(8, 44) = 4.06, p = .008; Movie × Model, F(8, 44) = 67.22, p < .001]. Post hoc
Bonferroni tests showed that there were significant differences between the adults’ data
and both the younger and older children’s data [younger t(16) = 15.30 and older t(16) =
15.60, both ps < .001], but there was no significant difference between the two children’s
groups, t(16) = 0.26, p > .90). Post hoc Bonferroni tests also showed that there were
significant differences between the results for Elf and each of the other two clips [Elf
vs. Night at the Museum, t(16) = 13.70, and Elf vs. Roadrunner, t(16) = 13.60, both ps <
.001], but not between Night at the Museum and Roadrunner, t(16) = 0.12, p > .90.
Similarly, there were significant differences between each of the models except for the
two GBVS models (with and without motion and flicker) [GBVS vs. GBVS+M+F: t(16) = 3.00, p
= .085; all other pairwise model comparisons: t(16) > 7 and p < .001]. It is clear that
for all three clips, the models predict the adults’ data better than the children’s data.
A three-way ANOVA comparing the within- and between-age group NSS data for the three clips
showed that there were significant differences in age groups in terms of how well their
data could be predicted by data from another group (including its own), F(2, 26) = 27.80,
p < .001, with post hoc Bonferroni tests showing that this was due to adults’ data being
better predicted than those of either group of children [adults vs. younger children:
t(20) = 7.00, p < .001; adults vs. older children: t(20) = 5.70, p < .001; younger
children vs. older children: t(20) = 1.40, p = .5610]. However, there were no significant
differences in how well each age group could be used to predict another age group
(including its own), F(2, 26) = 1.73, p = .203.

<hs>  Correlation coefficients between the faces-based and salience models</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We found that correlations between the faces-based model and the bottom-up salience models
were lowest for Elf (M = .31, SD = .001), followed by Night at the Museum (M = .35, SD =
.001) and Roadrunner (M = .50, SD = .002). By way of comparison, the mean correlation
coefficients between the maps of two bottom-up saliency models (Harel et al., 2006 [GBVS];
Itti et al., 1998 [I&K]) were .88, .90, and .87 for the respective three movies. Fig. 5
shows the normalized saliencies in the 2 s after a cut (averaged across all cuts in each
clip and all observers in each age group; shaded regions show the 95% confidence
intervals). All models perform relatively poorly immediately after a cut and rise to a
peak at about 500 ms. The difference between the faces-based model and the salience models
is most pronounced for Elf.

<h>DISCUSSION</h>
----------

We tracked the eye movements of children and adults viewing dynamic stimuli (movie and
cartoon clips). We performed two types of analyses on the resulting data: comparing
fixation within and between age groups (gaze-based analysis) and examining how well
fixation could be predicted from low-level (salience) or top-down (faces) features of the
movies (content-based analysis). We report the following results. First, variance between
eye movements decreases with age, consistent with comparison of eye movements in infants
and young children (Franchak et al., 2016; Kirkorian et al., 2012). Second, all models
that we tested predicted adults’ performance better than children’s performance, again
suggesting greater homogeneity in eye movements in adults. Third, a face-based model
performs at least as well as the low-level saliency models and significantly outperforms
them for one of our clips (Elf). This difference in performance among the three clips
highlights the importance of using different types of stimuli in testing for visual
attention and is consistent with Dorr et al. (2010), who reported that interparticipant
variability in adult eye movements is greater using natural stimuli than using commercial
clips. For gaze-based analyses, the results showed that adults’ data were less variable
than children’s data. The interobserver dispersion and number of clusters per person were
lower for adults than for younger and older children, suggesting that adults look at a
smaller number of objects or areas of interest when fixating a dynamic scene. The NSS
analysis shows that the adults’ data are better predicted by other people’s data [whether
those people are adults (within age groups) or children (between age groups)] than the
children’s data. However, the adults’ data do not predict the children’s data (between)
any better than the children’s data predict themselves (within). These findings suggest
that although children on average look at more areas of interest in a scene (i.e., larger
dispersion and numbers of clusters), there is significant overlap in the regions children
and adults find most interesting. Because young children (4 or 5 years) have been found to
have difficulty in maintaining accurate fixation (Kowler & Martins, 1982), the fixation
heat maps for different age groups would be expected to be flatter for children (although
they may have peaks in the same areas if they were looking at the same things as adults).
This may account for some of the variability seen with our younger age group (the youngest
child was 6 years old, only slightly older than the 4- and 5-year-olds in Kowler and
Martins’s [1982] study), but given that fixation accuracy is likely to be more adult-like
for the older children (10–14 years), this would not explain most of our results. Two
recent studies have extended eye-tracking analysis to dynamic stimuli in children.
Kirkorian et al. (2012) showed 1-year-olds, 4-year-olds, and adults a 19.5-min clip of
Sesame Street and performed a gaze-based analysis. They reported reduced variability with
age that they linked to increased influence of top-down mechanisms. Our results are
largely consistent with this finding when extended to children in their teens (older child
group). Interestingly, we also found that roughly 200 ms after a shot, there is an
increase in the number of clusters (in all age groups) associated with a corresponding
decrease in the number of participants. The most likely explanation for this is that scene
cuts lead to eye blinks (Nakano, Yamamoto, Kitajo, Takahashi, & Kitazawa, 2009). Franchak
et al. (2016) showed adults and young infants (up to 24 months) a 60-s clip of Sesame
Street and also looked at interparticipant variability in eye movements. They reported
that younger infants’ eye movements were weakly correlated with those of adults but that
this interparticipant correlation increased with age (24 months). Furthermore,
correlations between adults and infant groups were no greater than correlations within the
infant group, which is consistent with the data presented here. For content-based
analyses, we found that extending static models of faces (Frank et al., 2012) to dynamic
stimuli leads to performance as good as, or better than, any of the low-level salience
models of eye movements that we implemented (Harel et al., 2006; Itti et al., 1998).
Comparing performance of the different models, we found that the Itti et al. (1998) model
generally performed poorest and the faces-based model performed much better than the
saliency models for Elf and is approximately as good as the best-performing salience model
for Night at the Museum and Roadrunner. We also found that when there was only a weak
correlation between our face maps and the low-level salience maps (as in Elf), there was a
significant performance difference between the face and saliency models, with faces being
more predictive of gaze behavior. If the faces based model performed well simply as a
result of faces being highly salient parts of the image, we would expect the faces-based
model to perform best when the correlation between faces and salience is highest. This is
not what we observed. Therefore, we do not believe that the impressive performance of the
faces-based model is simply due to faces being more salient than other objects.
Interestingly, the GBVS model, which explicitly builds in motion and flicker components
(and so might be expected to perform better on dynamic movies), does not appear to
outperform the GBVS model that omits them. Indeed, for the cartoon clip, the opposite
pattern of results was observed. This may be due to the style of animation, whereby a
sparse scene made up of large blocks of uniform color typically contains one or two
foreground objects of interest that are static in the frame (but moving in the world) and
a number of (irrelevant and physically static) background objects that move across the
screen behind them. It is worth noting that, surprisingly, the low-level models perform
relatively well on these complex dynamic stimuli (average AUC = 80% vs. average AUC for
faces-based model = 85%). A possible explanation for the lack of superiority of the face-
based model for two of the three clips is that movies often contain more than one person
in a scene, and this increases the number of possible face targets (also suggested by
Franchak et al., 2016). Surprisingly, we found no clear spike in performance for the
salience models shortly after a cut, which may have been expected in light of findings for
static images where salience performs particularly well for the first fixation after an
image is shown (Carmi & Itti, 2006; Parkhurst et al., 2002), although other authors argue
that the effect is mainly an artifact of a center bias. In our results, there is no clear
evidence of a decline in saliency model performance over time, which often occurs for
dynamic stimuli (Carmi & Itti, 2006; Marat et al., 2009). It is likely that in our dynamic
stimuli, the constant appearance of new salient regions promotes bottom-up influences at
the expense of top-down strategies, inducing a stable consistency between participants
over time. Overall, our results are consistent with earlier reports using young infants.
For example, Kwon et al. (2016) reported an increase in the eye movements to faces in
static images, and Frank et al. (2012) found an increase in fixations to socially relevant
information in brief videos. Recently, Franchak et al. (2016) compared consistency of eye
movements with saliency and the presence of faces in 1-min clips from Sesame Street, and
although they reported that on average fixations were to the top quartile of salient
regions, they noted that a model that relies on both saliency and faces accounts for
(only) 41% of the variance in infants’ eye movements. However, the different age ranges,
stimuli, and analyses in our study and theirs mean that we cannot directly compare our
results. It is noteworthy that our procedure relies exclusively on modeling/quantifying
eye-tracking behavior and, as such, is agnostic as to what may underlie these age-related
changes. We postulate that most changes will reflect attentional orienting rather than
motor or visual immaturities because we are not testing young infants (Farber & Beteleva,
2005). In fact, the youngest children tested were 6 years old. Although saccade latencies
decrease with age (Fukushima, Hatta, & Fukushima, 2000; Salman et al., 2006), their
accuracy and peak velocity is adult-like by 8 years of age. Smooth pursuit is age
dependent. However, for targets moving at roughly 15°/s or lower, children’s pursuit of
targets is adult-like (age 5 years and over) (Ego, Orban de Xivry, Nassogne, Yüksel, &
Lefèvre, 2013). Given that, other than brief sections of the Roadrunner cartoon, most
clips did not contain rapidly moving objects, we believe that any smooth pursuit
immaturities would have a minimal influence on our results. Finally, we note that the
dependence of our outcomes on the particular movie sample highlights the importance of
using stimuli that vary in their semantic/saliency content. This will be particularly
important when applying such techniques to study pseudo-naturalistic fixation behavior in
clinical populations. For example, the presentation of people with autism spectrum
disorder differs widely, and it may be that patterns of abnormal fixation in some classes
of movies can provide pointers to classification of autism spectrum disorder subtypes. In
summary, we have examined age-related changes in children and adults’ eye movements to
dynamic visual scenes, namely popular child-appropriate cartoons and movies. We extended
previous work in infancy and early childhood and showed that (a) variance in eye movements
decreased with age; (b) a faces-based model outperformed saliency models, even for the
youngest children; and (c) when there was an increased differentiation between faces and
salient regions in a scene, participants looked more to the faces as in Elf. These
findings shed light on the nature of visual attention during development and act as an
important reference for understanding how such attention may develop differently in
individuals with neurodevelopmental conditions.


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<ART>Shot through with voices: Dissociation mediates the relationship between varieties of inner speech and auditory hallucination proneness
================================================================================

Authors: Ben Alderson-Day, Simon McCarthy-Jones, Sarah Bedford, Hannah Collins, Holly Dunne, Chloe Rooke, Charles Fernyhough
DOI: 10.1016/j.concog.2014.05.010
Year: 2014  |  Pages: 288-296
ASJC codes: 3204, 3205
Keywords: Dialogicality, Dissociation, Hallucination, Inner speech, Psychosis, Self-esteem

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Inner speech is a commonly experienced but poorly understood phenomenon. The Varieties of Inner Speech Questionnaire (VISQ; McCarthy-Jones & Fernyhough, 2011) assesses four characteristics of inner speech: dialogicality, evaluative/. motivational content, condensation, and the presence of other people. Prior findings have linked anxiety and proneness to auditory hallucinations (AH) to these types of inner speech. This study extends that work by examining how inner speech relates to self-esteem and dissociation, and their combined impact upon AH-proneness. 156 students completed the VISQ and measures of self-esteem, dissociation and AH-proneness. Correlational analyses indicated that evaluative inner speech and other people in inner speech were associated with lower self-esteem and greater frequency of dissociative experiences. Dissociation and VISQ scores, but not self-esteem, predicted AH-proneness. Structural equation modelling supported a mediating role for dissociation between specific components of inner speech (evaluative and other people) and AH-proneness. Implications for the development of "hearing voices" are discussed. © 2014 The Authors.

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<h>INTRODUCTION</h>
------------

Inner speech – the internal monologue that appears to accompany our daily lives – is an
experience that will be familiar to many. Often, inner speech is simply defined as a
silent form of speech; for example, Levine, Calvanio, and Popovics (1982) call it the
“subjective phenomenon of talking to oneself, of developing an auditory–articulatory image
of speech without uttering a sound” (p. 391). But the everyday nature of inner speech
hides a wealth of complexity (Hurlburt, Heavey, & Kelsey, 2013). Developmentally, inner
speech has been proposed to reflect the internalisation of external dialogue and self-
directed private speech, facilitating higher order cognitive skills (Vygotsky, 1987). In
adulthood, inner speech supports executive functions (Miyake, Emerson, Padilla, & Ahn,
2004) and facilitates self-evaluation and reflection (Morin & Michaud, 2007). It has also
been argued that the form of inner speech in adulthood is shaped by its developmental
origins. For example, Fernyhough (2004) has argued that inner speech is inherently
dialogic, reflecting the external interpersonal discourse from which it came. Inner speech
may also change its form as it develops, becoming syntactically and semantically
abbreviated or “condensed”. In this sense, inner speech is likely to be more than simply
silent, covert speech. Rather, it is a complex and dynamic activity, and one that needs to
be examined in more depth. Various methods of investigating inner speech exist, including
questionnaires (Duncan & Cheyne, 1999; Morin, Uttl, & Hamper, 2011), experience sampling
(Hurlburt et al., 2013) and task-based methods (Murray, 1967). However, few have included
the various developmental characteristics of inner speech, such as dialogicality and
condensation, as well as the functions of inner speech, such as action control (Luria,
1961), in a comprehensive measure of everyday experience. One exception is the Varieties
of Inner Speech Questionnaire (VISQ; McCarthy-Jones & Fernyhough, 2011), a scale that
measures self-reported inner speech along four distinct dimensions: (i) dialogicality, the
communicative and conversational quality of inner speech; (ii) condensation, or the extent
to which inner speech is syntactically and semantically abbreviated, (iii)
evaluative/motivational inner speech, such as saying “I should do this” to oneself, and
(iv) the presence of other people’s voices in inner speech. An initial validation of the
VISQ (McCarthy-Jones & Fernyhough, 2011) demonstrated two advantages of this approach.
First, the VISQ can provide a more nuanced picture of the range of ways in which inner
speech is used and experienced; in data from a student sample, dialogic and evaluative
characteristics of inner speech appeared to be very common, while a substantial minority
reported experiences of condensation and other people’s voices in their inner speech
(McCarthy-Jones & Fernyhough, 2011). Secondly, given that inner speech is proposed to be
the raw material of some auditory verbal hallucinations (‘hearing voices’) (Bentall, 1990;
Frith, 1992; Shergill et al., 2003), and may play a causal or maintenance role in anxiety
and depression (Harrington & Blankenship, 2002), the VISQ can be used to examine how
specific types of inner speech may be related to psychopathological processes. In their
original study, McCarthy-Jones and Fernyhough found that self-reported evaluative inner
speech and the presence of other people in inner speech were positively related to
anxiety. Alongside this, proneness to auditory hallucinations (AH) had bivariate
correlations with evaluative, other people and dialogic inner speech, although after
controlling for potentially confounding factors, only dialogic characteristics remained a
significant predictor of AH-proneness (McCarthy-Jones & Fernyhough, 2011). The present
study sought to extend this work by examining the interrelations between inner speech and
two other constructs that have been related to the development and experience of
psychosis-like phenomena: self-esteem (Krabbendam et al., 2002) and dissociation (Altman,
Collins, & Mundy, 1997). Self-esteem refers to the set of positive and negative beliefs
and feelings that people have about themselves. It has been related to the severity and
content of hallucinations in clinical studies (Romm et al., 2011; Smith et al., 2006) and
has been proposed to shape the interactions people have with the voices they hear (Paulik,
2012). In work with the general population, self-esteem has been observed to predict later
development of psychosis (Krabbendam et al., 2002), and has been associated with increased
hallucination-proneness (Gaweda, Holas, & Kokoszka, 2012; Gracie et al., 2007; Pickering,
Simpson, & Bentall, 2008). Dissociation refers to a “lack of normal integration of
thoughts, feelings and experiences into the stream of consciousness and memory” (Bernstein
& Putnam, 1986, p. 727), and is typified by feelings of depersonalization, derealisation
and absorption. Diagnostic overlaps between dissociative and psychotic disorders have
often been noted (Allen & Coyne, 1995), and dissociation is strongly related to rates of
psychotic experiences, including hallucinations (Altman et al., 1997; Glicksohn & Barrett,
2003; Kilcommons & Morrison, 2005; Merckelbach, Rassin, & Muris, 2000). More recently,
specific links between dissociation and voice-hearing have been proposed (Moskowitz &
Corstens, 2008), with dissociative experiences potentially playing a predisposing role or
acting as a preliminary stage in the development of AHs (Perona-Garcelán et al., 2011;
Varese, Barkus, & Bentall, 2012). In addition to their documented association with
hallucinations, there are prima facie reasons to think that both self-esteem and
dissociation might overlap with specific aspects of inner speech. Given its proposed role
in self-assessment and reflection, evaluative aspects of inner speech would appear
relevant to an individual’s self-concept and social rank. The presence of other voices in
inner speech, in contrast, has a phenomenological similarity with dissociative experiences
of depersonalization and detachment; a separation of the self and other. This can be seen
in example items from the VISQ, such as “I experience the voices of other people asking me
questions in my head” (McCarthy-Jones & Fernyhough, 2011). As such, the first aim of this
study was to establish what links, if any, there are between varieties of inner speech,
self-esteem and dissociative traits. We hypothesised that evaluative inner speech scores
in particular would be strongly associated with self-esteem, while other people in inner
speech would be closely associated with dissociation scores. The second aim of this study
was to investigate how any potential relations between the varieties of inner speech,
dissociation and self-esteem might influence the previously documented association between
inner speech and AH-proneness (McCarthy-Jones & Fernyhough, 2011). If self-esteem and
dissociation were to be found to be related to both inner speech and AH-proneness, then
they could represent potential confounding variables, or act as either mediators or
moderators of the link between inner speech and AH-proneness. Dissociation in particular
has been proposed to act as a mediator in the development of hallucinations. In patients
with schizophrenia spectrum disorders, dissociative traits positively mediate the effects
of childhood trauma (Varese et al., 2012), and attentional focus (Perona-Garcelán et al.,
2011) on hallucination proneness. As it is currently unclear how inner speech may become
transmuted into AHs, an examination of whether dissociation and/or self-esteem are
potential mediators is of considerable potential value. This was accomplished by testing
the fit of a number of potential models of the relation between self-esteem, dissociation
and the varieties of inner speech using structural equation modelling.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A sample of 156 students (22 male) was recruited from a United Kingdom university. The
mean age was 20.02 years (SD = 2.11, range 18–31). Participants were invited to take part
via a web advert and received course credit for participation. Participants indicated
their age and gender and provided an email address if they wished to be contacted for a
follow-up study (which is not reported here). All procedures were approved by the local
university ethics committee.

        Varieties of Inner Speech Questionnaire (VISQ; McCarthy-Jones & Fernyhough, 2011)

        The Varieties of Inner Speech Questionnaire is an 18-item self-report scale
        measuring four dimensions of inner speech. Participants endorse items about their
        experience of inner speech in relation to dialogicality (“I talk back and forward
        to myself in my mind about things”), evaluative and motivational characteristics
        (“I talk silently to myself telling myself not to do things”), condensation (“I
        think to myself in words using brief phrases and single words rather than full
        sentences”) and the presence of other voices (“I experience the voices of other
        people asking questions in my head”). Responses are made on a 6-point Likert scale
        ranging from “Certainly does not apply to me” (1) to “Certainly applies to me”
        (6). Each subscale of the VISQ has high internal reliability (Cronbach’s α > .80)
        and moderate to high test–retest reliability (>.60).

        <hss>Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965)</hss>

        The Rosenberg Self-Esteem Scale is a widely used 10-item measure of global self-
        esteem with high test–retest and internal reliability (α = .8–.9; Fleming &
        Courtney, 1984; Robins, Hendin, & Trzesniewski, 2001). Respondents use a four-
        point scale (strongly agree, agree, disagree and strongly disagree) to classify
        evaluative statements about themselves, such as “On the whole, I am satisfied with
        myself”.

        Dissociative Experiences Scale – Second Revision (DES-II; Carlson & Putnam, 1993)

        The Dissociative Experiences Scale measures frequency of dissociative experiences
        on a 28-item scale. Participants indicate what percentage of the time they
        experience dissociative states ranging from 0% to 100%, e.g., “Some people have
        the experience of finding themselves in a place and have no idea how they got
        there. What percentage of the time does this happen to you?”. The original DES has
        been shown to have good reliability and validity; test–retest reliabilities range
        from .7 to .9 (Carlson & Putnam, 1993) with a mean internal reliability of .93
        (Van IJzendoorn & Schuengel, 1996). The DES-II differs only in the use of
        incremental response options rather than a visual analogue scale.

        Revised Launay–Slade Hallucination Scale: Auditory Subscale (LSHS-R; Morrison, Wells, & Nothard, 2000)

        The Launay–Slade Hallucination Scale is a commonly used measure of hallucination
        proneness in non-clinical samples. The revision used here (Morrison et al., 2000)
        was developed specifically to separate factors relating to auditory and visual
        hallucination proneness. Five items relating specifically to auditory
        hallucination experiences (e.g., “I have had the experience of hearing a person’s
        voice and then found that there was no one there”) were used here following their
        use in McCarthy-Jones and Fernyhough (2011), in which they were observed to have
        good internal reliability (Cronbach’s α = .73). Items were scored on four-point
        scale ranging from “Never” (1) to “Almost Always” (4).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Relationships between the VISQ and other variables were first analysed using Pearson’s
product moment correlation co-efficients. Secondly, hierarchical regression was used to
assess the ability of inner speech, self-esteem and dissociation to predict hallucination
proneness, with LSHS-R scores acting as the dependent variable. Structural equation
modelling (SEM) was then used to test competing models of the relationship between the
variables. All analyses were conducted in SPSS 20 and AMOS 7.0. Unless otherwise noted,
all Durbin–Watson statistics and parameters regarding collinearity and normality of
residuals were within acceptable bounds. A number of arguments have been made as to the
most appropriate way in which to correct alpha to control for the altered experiment-wise
error rate resulting from undertaking multiple comparisons. For example, it has been
argued that a different approach is needed for exploratory and confirmatory studies
(Bender & Lange, 2001). For confirmatory studies, Bonferroni corrections are generally
viewed as appropriate (Bender & Lange, 2001). Thus, for the part of this study which
involved confirmatory tests, i.e., which repeated the analyses of McCarthy-Jones and
Fernyhough (2011) by examining four bivariate correlations (between the four VISQ
subscales and AH-proneness), a Bonferroni corrected alpha was employed of α′ = .05/4 =
.0125. For all other analyses, which were exploratory, α was retained at .05. This is in
accordance with Perneger, 1998 argument that “simply describing what was done and why, and
discussing the possible interpretations of each result, should enable the reader to reach
a reasonable conclusion without the help of Bonferroni adjustments” (p. 1237).

<hs>  Descriptive statistics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Table 1 displays descriptive statistics for the four dimensions of the VISQ, as well as
the RSES, DES and LSHS-R. Mean scores were highest for evaluative inner speech and
dialogic inner speech, followed by other people in inner speech and condensed inner
speech. If the presence of specific types of inner speech was defined as positive
endorsement of the majority of items on each subscale (i.e., a response of 4 or higher),
80.1% of participants reported dialogic inner speech, 87.2% reported evaluative inner
speech, 22.4% reported other people in inner speech, and 28.2% reported condensed inner
speech. Internal reliability scores (Cronbach’s α) were good for each subscale (all >.70).
Both mean scores and reliability co-efficients were comparable to the original VISQ data
reported by McCarthy-Jones and Fernyhough (2011). Reliability for self-esteem and
dissociation scores was high (α > .90). Cronbach’s α was lower for hallucination-proneness
(0.69) although still well within the acceptable range (i.e., >0.6).

<hs>  Correlations of inner speech with self-esteem, dissociation and auditory hallucination-proneness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 shows bivariate correlations among VISQ, RSES, DES and LSHS-R scores. Evaluative
inner speech (p = .011) and other people in inner speech (p = .022) scores were
significantly negatively correlated with global self-esteem scores, such that higher self-
esteem was associated with less evaluative inner speech and fewer instances of other
people in inner speech. Both other people and evaluative inner speech were also positively
related to frequency of dissociative experiences (see table 2). AH-proneness was
positively associated with dialogic inner speech (p < .001), evaluative inner speech (p <
.001) and other people in inner speech (p < .001).

<hs>  Predicting proneness to auditory hallucinations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A hierarchical multiple linear regression was performed to assess the unique contribution
of inner speech (VISQ), self-esteem (RSES) and dissociation (DES) in predicting auditory
hallucination proneness. Age and gender were included in the first block as control
variables. This was then followed by the four VISQ subscales in the second block (to
replicate the findings from McCarthy-Jones & Fernyhough, 2011), RSES in the third block,
and DES in the fourth block. All residuals were normal and measures of multicollinearity
were in an acceptable range. While the first block was non-significant (p > .100), each of
the second, F (6, 149) = 6.56, p < .001, third, F (7, 148) = 5.59, p < .001, and fourth, F
(5, 214) = 8.67, p < .001, blocks significantly predicted AH-proneness. In Block 2 (R2 =
.21), other people in inner speech, β = .250, p = .001, and evaluative inner speech, β =
.198, p = .023, were the only significant predictors. This was also the case in Block 3
(R2 = .21); the addition of self-esteem made no significant change to the model, ΔR2 =
.00, p = .873, and self-esteem failed to predict AH-proneness, β = −.012, p = .873. In
contrast, the addition of DES scores in Block 4 significantly improved the model (ΔR2 =
.11, p < .001, R2 = .32). Dissociation scores significantly predicted AH-proneness, β =
.367, p < .001, while VISQ predictors were only evident at the level of trends for other
people in inner speech, β = .134, p = .078, and condensed inner speech, β = −.130, p =
.066. Thus, the predictive value of VISQ subscales was almost completely removed with the
inclusion of dissociation scores.

        <hss>Mediator effects</hss>

        Structural equation modelling (SEM) in AMOS was used to further examine the
        relationship between inner speech, dissociation and AH-proneness. As the
        regression analyses showed self-esteem not to predict AH-proneness, this was
        excluded from the SEM. To allow for non-normal data distributions, an
        asymptotically free distribution (ADF) method was used combined with a
        Yuan–Bentler statistic, which is appropriate for sample sizes less than 200 (Yuan
        & Bentler, 1999). Three models were compared: (a) dissociation and inner speech
        scores as independent predictors of AH-proneness, (b) dissociation as a full
        mediator of the relationship between inner speech and AH-proneness, and (c)
        dissociation as a partial mediator of this relationship (see Fig. 1). Each model
        also contained covariate links between the VISQ domains where these were suggested
        by bivariate correlations. The first model represented a situation in which
        dissociation and inner speech present unique pathways towards increased
        hallucination proneness. The latter two models tested whether dissociation plays a
        role in mediating the relationship between inner speech and hallucination
        proneness, either by fully accounting for their covariance (full mediation) or
        only accounting for some of it (partial mediation). If dissociation was observed
        to fully mediate this relationship, inner speech could only be said to have an
        indirect effect on AH-proneness. Of the three models, only Model C (partial
        mediation) provided an adequate fit to the data, X2ADF (2) = 1.51, p = .471, TF
        (2, 154) = 0.75, p = .475, RMSEA = .000, GFI = .997, CFI = 1.00. Both Model A,
        X2ADF (6) = 20.69, p = .002, TF (6, 150) = 3.34, p = .004, RMSEA = .126, GFI =
        .962, CFI = .737, and Model B, X2ADF (6) = 16.47, p = .011, TF (6, 150) = 2.67, p
        = .017, RMSEA = .106, GFI = .969, CFI = .813 were significantly different from the
        data, indicating an inadequate fit. Bootstrap statistics were used to assess the
        significance of direct and indirect effects on AH-proneness. Direct effects on AH-
        proneness were observed for dissociation, p = .004, other people in inner speech,
        p = .042, and condensed inner speech, p = .025. A marginal but non-significant
        direct effect was also evident for evaluative inner speech, p = .063. Indirect
        effects on LSHS, via dissociation, were observed for other people in inner speech,
        p = .004 and evaluative inner speech, p = .006, but not condensed inner speech, p
        = .615. No direct or indirect effects were observed for dialogic inner speech (all
        p > .200). To further test the specific direction of these relationships, a model,
        D, was constructed that matched Model C but included VISQ scores as mediating
        variables and DES as their predictor (see Fig. 2). In such a scenario,
        dissociation would be associated with different characteristics of inner speech,
        and these in turn would lead to greater hallucination-proneness. However, this did
        not produce an adequate fit to the data, X2ADF (6) = 24.81, p < .001, TF (6, 150)
        = 4.00, p < .001, RMSEA = .142, GFI = .934, CFI = 0.664.

        <hss>Moderator effects</hss>

        To examine whether dissociation might moderate rather than mediate the effect of
        inner speech scores on hallucination proneness, a multiple linear regression was
        performed using the same predictors as above, plus mean-centred interaction terms
        between DES scores and the four VISQ subscales. This, however, yielded no new
        significant predictors of auditory hallucination proneness (all interaction
        effects p > .70, β < .01).

<hs>  Predictive relationships with overlapping items removed</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Finally, while aimed at nominally separable constructs, measures of inner speech,
hallucination-proneness and dissociation can sometimes be very similar in the kinds of
experiences they describe. It is therefore important to rule out any trivial relationships
between these constructs that might be caused by individual items that happen to overlap.
To address this, we reran each of our main analyses with subsets of items removed from our
measures of inner speech and dissociation. A subset of items was removed from the VISQ and
the DES (the RSES had little overlap with other scales). In the VISQ, two items explicitly
refer to hearing other people’s “actual voices”; item 12 “I hear other people’s actual
voices in my head, saying things they have never said to me before” and item 16 “I hear
other people’s actual voices in my head, saying things that they actually once said to
me”. Both these items were removed from the “Other People” subscale to avoid trivial
overlaps with the LSHS-R. In the DES, two items were removed; one clearly overlapped with
hallucination proneness and inner speech (item 27: “Some people sometimes find that they
hear voices inside their head that tell them to do things or comment on things that they
are doing.”) while another was deemed to be similar to questions about inner speech (item
21: “Some people sometimes find that when they are alone they talk out loud to
themselves”). Each of the above analyses (correlations, regression and SEM) was rerun
using the adjusted scores for other people in inner speech and dissociation. The new
scores for other people in inner speech significantly correlated with LSHS-R (r = .24).
RSES (r = −.21) and the adjusted DES (r = .31; all p < .05), albeit to a lesser degree
than beforehand. When the new DES and other people VISQ scores were entered into the
hierarchical regression, the results for each model were almost identical to those
observed originally, with DES the single significant predictor in the final model (β =
.382, p < .001). The adjusted score for other people in inner speech was a significant
predictor in blocks 2 and 3, but was no longer evident (even at trend level) in the final
model (p = .406). Re-analysis using SEM also produced similar results. When the adjusted
scores for DES and other people in inner speech were included, only Model C yielded an
appropriate fit to the data, X2ADF (2) = 2.79, p = .247, TF (2, 154) = 1.39, p = .253,
RMSEA = .051, GFI = .995, CFI = .985. Bootstrap analysis yielded similar direct effects
for DES (p = .004) and condensed inner speech (p = .033) on hallucination proneness,
alongside a new direct effect for evaluative inner speech (p = .028). Indirect effects
were evident for evaluative inner speech (p = .007) and the adjusted other people in inner
speech (p = .008). Thus, removal of overlapping items (i) made little difference to the
role of dissociation, (ii) reduced the role of other people in inner speech, but also
(iii) highlighted a greater contribution of evaluative inner speech.

<h>DISCUSSION</h>
----------

The present study examined the relationships among inner speech, self-esteem and
dissociation, and how these factors combine to predict proneness to auditory
hallucinations. The main finding was that dissociation mediated the relationship between
inner speech quality and the tendency to experience auditory hallucinations. Specifically,
dissociation mediated the effect of other people in inner speech and
evaluative/motivational inner speech on auditory hallucination proneness. There was also
some evidence to suggest direct effects of evaluative inner speech and condensed inner
speech on proneness to auditory hallucinations. Correlational analysis indicated a
relationship between self-esteem, evaluative/motivational inner speech and other people in
inner speech, but no relationship was evident between self-esteem and hallucination
proneness. Consistent with prior findings (McCarthy-Jones & Fernyhough, 2011), the four
VISQ subscales showed good reliability and specific relationships with proneness to
auditory hallucinations; dialogic and evaluative characteristics of inner speech and the
presence of other voices in inner speech positively correlated with AH-proneness. However,
although McCarthy-Jones and Fernyhough found dialogic inner speech to account for unique
variance in auditory hallucination proneness (after controlling for all VISQ subscales,
age, gender, anxiety, depression and visual hallucination-proneness), in this dataset it
did not account for any unique variance in AH-proneness, at any stage of the regression or
SEM analysis. Possible explanations for this are the collinearity of this particular
domain of inner speech with other aspects of inner speech, and the use of different
control variables (anxiety and depression) in McCarthy-Jones and Fernyhough’s original
study. Given that evaluative inner speech and other people in inner speech correlate
significantly with anxiety (McCarthy-Jones & Fernyhough, 2011), it may be that
dialogicality is only predictive of hallucination-proneness once factors relating to
anxiety are partialled out. Replication data are needed to clearly delineate which aspects
of inner speech are the best predictors of AH-proneness and what role dialogic
characteristics may play, if any. Dissociative traits were most strongly associated with
the presence of other people’s voices in inner speech, although they were also linked to
evaluative inner speech. This suggests that a greater tendency to experience other voices
in everyday thinking may in itself be a dissociative tendency or could be a precursor of
more developed dissociative states such as depersonalisation and identity confusion
(Steinberg, 1991). When dissociation scores were included in the model for predicting AH-
proneness, they accounted for some, but not all, of the predictive power of inner speech.
The SEM analysis suggested that the best fit to the data involved a model where DES
partially mediated the link between different subscales of the VISQ and hallucinations.
Importantly, this was true even when items with potentially overlapping content were
removed from the DES and VISQ, and highlighted a range of direct and indirect effects of
inner speech, with other people in inner speech being fully mediated, evaluative inner
speech partially mediated, and condensed inner speech appearing to show a small but
unmediated effect. Given that some of the direct effects were only evident in the SEM and
not in the hierarchical regression (particularly concerning condensed inner speech), these
relations should be interpreted with caution and require further replication.
Nevertheless, it appears that different characteristics of inner speech may be picking out
independent and alternative routes to AH-proneness. These data support the role of
dissociation as a mediating mechanism in the development of hallucinatory experiences.
Varese et al. (2012) observed DES scores to positively mediate the effect of childhood
trauma on hallucination-proneness in hallucinating patients. This finding has been
replicated in a non-clinical university sample using alternative measures of two specific
dissociative experiences, depersonalisation and absorption (Perona-Garcelán et al., in
press). While such findings point towards a specific role for dissociation in the link
between trauma and hallucination, the present data may suggest a wider mediating role for
dissociative traits in the development of unusual perceptual experiences, as seen for
example in data on attentional focus and hallucinations (Perona-Garcelán et al., 2011). In
such a scenario, characteristics of inner speech could develop into hallucination via a
dissociative stage, or there may be an additive effect between inner speech and
dissociative traits that gives rise to hallucination proneness. Given that we did not
observe any significant moderator effects in this dataset, these results appear to support
the former scenario over the latter. The converse could of course be possible; it may be
that having a tendency towards dissociation could lead to the development of specific
kinds of inner speech – such as talking in other voices – and this in turn leads to the
development of hallucinations. When this scenario was modelled with the VISQ scores as
mediators (Model D) it did not produce an adequate fit to the data, which would suggest
that inner speech does not play such a role. However, only longitudinal data on inner
speech, dissociation and hallucination proneness could convincingly split apart these
possibilities. Yet to be examined also are the potential relationships between earlier
childhood experiences (including trauma and other adversity) and characteristics of inner
speech. A tentative hypothesis would be that the presence of other voices and evaluative
characteristics of inner speech are likely to have strong developmental roots, both based
on their theoretical origin (Fernyhough, 2004) and links between early adversity and later
hallucination proneness (Bentall, Wickham, Shevlin, & Varese, 2012). This is the first
study to demonstrate links between specific varieties of inner speech and self-esteem. As
predicted, a greater tendency to engage in evaluative forms of inner speech (“I talk
silently to myself, telling myself not to do things”) was associated with lower self-
esteem. Though such an association cannot demonstrate causality, it seems plausible to
suggest that inner speech with a strongly normative and ruminative component could have a
negative impact on self-concept and social rank. Equally, the former could be an
expression of the latter, if lower self-esteem was taken to lead to more frequent
evaluation and rumination in inner speech. In either case, this contrasts with the
suggestion that evaluative aspects of inner speech generally play a positive role in
enabling self-awareness and self-reflection (Morin & Everett, 1990); an increase in such
tendencies could equally be associated with over-analysis and self-criticism. It is
important here to consider the valence of the kind of inner speech that is occurring; some
evaluations will be more positive (e.g., “I can do this”) and others negative (“I really
shouldn’t have done that…”) and this will vary with context. The items in the VISQ are
designed to be balanced in their appraisals, but further study with a greater range of
positive and negative items is really needed to clarify the relationship between self-
concept and inner speech use. Self-esteem was also negatively correlated with reports of
other people in inner speech, indicating that experiencing other people’s voices in
everyday verbal thinking is linked to lower self-esteem and a more negative self-concept.
The lack of any relationship between self-esteem scores and AH-proneness contrasts with
prior reports of self-esteem effects (Pickering et al., 2008) but is consistent with prior
null findings in a similar population (Jones & Fernyhough, 2007). There are a range of
caveats to be acknowledged in interpreting these results. First, these data come from a
non-clinical, university sample and only indicate relationships between general population
traits associated with psychosis. The correlations observed are broadly consistent with
those reported in clinical studies (as in, for example, the case of dissociation and
hallucination; Kilcommons & Morrison, 2005) but any extrapolation to clinical populations
must be made with caution. Second, the present results are purely correlational and do not
provide evidence of causal relationships between the data. Time-based data via
longitudinal studies or use of experience sampling methods (ESM; Csikszentmihalyi &
Larson, 1987) are required to assess causal relationships between these variables. Third,
these data are reliant on self-reports for the measurement of experiences that may be hard
to report reliably and accurately. Previously used inner speech questionnaires (although
not the VISQ) have been criticised for showing a lack of convergent validity (Uttl, Morin,
& Hamper, 2011) and it has been suggested that self-reported inner speech is likely to be
overestimated in general questionnaires (Hurlburt et al., 2013). Similarly, the validity
and reliability of self-reports for relatively infrequent, unusual phenomena such as
hearing a voice or having a dissociative experience is hard to gauge in non-clinical
samples, and the possibility of over-reporting cannot be ruled out. The mean DES score
observed here, although comparable with other student/college studies (e.g., Merckelbach,
Muris, Rassin, and Horselenberg, 2000) was relatively high, suggesting that some
overestimation may have occurred. The internal reliability of hallucination-proneness
scores, though in the adequate range, was also lower than the other measures used (α =
.69). An alternative approach would be to use more items to examine hallucination-
proneness, although that may be at the risk of losing specificity, as existing longer
scales often conflate auditory experiences with visual hallucinations and other unusual
phenomena (Morrison et al., 2000) The use of ESM is equally important here to examine
whether day-to-day, random sampling of such experiences actually corroborates
participants’ general trait reports. Alternatively, use of questionnaires and ESM could be
combined with electromyographical techniques to assess covert muscle activity associated
with inner speech (see, for example, Rapin, Dohen, Polosan, Perrier, & Loevenbruck, 2013).
Finally, while the VISQ is an explicitly multi-dimensional scale, the measures used here
for self-esteem, dissociation and hallucination-proneness represent unidimensional indices
of complex phenomena. As the first study to investigate this group of constructs in
relation to inner speech, we selected measures partly for simplicity and to limit the
number of potential comparisons examined. In the case of hallucinatory experiences,
auditory hallucinations were focused on here rather than visual experiences or other
modalities because of the putative association of AH with inner speech (Fernyhough, 2004)
and their proposed links to dissociation (Moskowitz & Corstens, 2008). Nevertheless, an
important focus for future studies would be an assessment of the relationships among VISQ
dimensions and separable aspects of dissociation (such as depersonalisation and
absorption), and the specificity of such relationships for understanding auditory
hallucinations.

<h>CONCLUSIONS</h>
-----------

In conclusion, these results highlight the importance of asking about a variety of
experiences in inner speech. Different characteristics of inner speech relate to self-
esteem, dissociation and AH-proneness in specific ways that would otherwise be missed by a
less fine-grained analysis of how people talk to themselves. Further examination of these
characteristics will shed light on how ordinary characteristics of day-to-day inner
experience can, in some cases, become the extraordinary.


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<ART>Should online math learning environments be tailored to individuals’ cognitive profiles?
================================================================================

Authors: Susanne M.M. de Mooij, Natasha Z. Kirkham, Maartje E.J. Raijmakers, Han L.J. van der Maas, Iroise Dumontheil
DOI: 10.1016/j.jecp.2019.104730
Year: 2020
ASJC codes: 3204, 3205
Keywords: Arithmetic, Eye tracking, Individual differences, Inhibitory control, Time perception, Working memory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Online learning environments are well-suited for tailoring the learning experience of children individually and on a large scale. An environment such as Math Garden allows children to practice exercises adapted to their specific mathematical ability; this is thought to maximize their mathematical skills. In the current experiment, we investigated whether learning environments should also consider the differential impact of cognitive load on children's math performance depending on their individual verbal working memory (WM) and inhibitory control (IC) capacity. A total of 39 children (8–11 years old) performed a multiple-choice computerized arithmetic game. Participants were randomly assigned to two conditions where the visibility of time pressure, a key feature in most gamified learning environments, was manipulated. Results showed that verbal WM was positively associated with arithmetic performance in general but that higher IC predicted better performance only when the time pressure was not visible. This effect was mostly driven by the younger children. Exploratory analyses of eye-tracking data (N = 36) showed that when time pressure was visible, children attended more often to the question (e.g., 6 × 8). In addition, when time pressure was visible, children with lower IC, in particular younger children, attended more often to answer options representing operant confusion (e.g., 9 × 4 = 13) and visited more answer options before responding. These findings suggest that tailoring the visibility of time pressure, based on a child's individual cognitive profile, could improve arithmetic performance and may in turn improve learning in online learning environments.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Extensive individual differences in learning trajectories show that in education there is
no such thing as a one-size-fits-all approach. Adaptive e-learning systems, where an
online learning environment is continuously adapting to accommodate differences between
learners and changes over time for each individual (Park & Lee, 2003), may help to address
this challenge and enhance children’s success. The idea behind this approach is that if
pedagogical procedures are geared to adhere to their individual needs, students will be
able to achieve a higher performance more efficiently (for a review, see Akbulut & Cardak,
2012). One example of such an adaptive e-learning system is Math Garden, an educational
tool that adapts the difficulty of the math problems presented to children aged 4 years
and over. The aim of Math Garden is that children always practice math skills at an
appropriate individual level; in the case of Math Garden, items are chosen such that the
probability of answering correctly is about .75 (Jansen et al., 2013; Straatemeier, 2014).
In principle, emerging e-learning platforms allow the tailoring of the learning
environment to individual students on a large scale. In contrast to the conventional
classroom setting where teachers have a good sense of the pupils’ individual needs, in an
e-learning context explicit information is required to reliably tailor the individuals’
learning environment based on these differences. Current adaptive e-learning systems such
as Math Garden are well equipped to adapt to the specific math ability level of the
student (Klinkenberg, Straatemeier, & van der Maas, 2011). However, the environmental
context in online game-based learning environments, with its interruptions and
distractions, poses a risk for the user in terms of sustained attention, engagement, and
concentration (Terras & Ramsay, 2012). To maximize the learning potential offered by
adaptive e-learning platforms, we also need to consider individual differences in the
capacities to attend to, process, learn, and remember information when designing these
technologies (Ramsay & Terras, 2015). When solving math problems, the overall load on an
individual’s cognitive system, also referred to as cognitive load, can limit and interfere
with performance (Sweller, 1988). This relates particularly to attention and working
memory (WM). Working memory is the ability to control, regulate, and actively maintain
relevant information in mind to accomplish complex cognitive tasks such as mathematical
processing (Miyake et al., 2000). Many recent studies propose that individual differences
in WM capacity in various domains (verbal, numerical, and visuospatial) are important
predictors of math achievement (Bull & Lee, 2014; Dumontheil & Klingberg, 2012; Friso-van
den Bos, van der Ven, Kroesbergen, & van Luit, 2013; Peng, Namkung, & Barnes, 2016;
Raghubar, Barnes, & Hecht, 2010). WM can influence math achievement by helping to keep
track of relevant information during problem solving but is also involved in selecting and
switching to the most efficient arithmetic strategy (Barrouillet & Lépine, 2005; Cragg &
Gilmore, 2014; Siegler & Lemaire, 1997; Wu et al., 2008). In online game-based learning
environments, there is a great risk of overloading a player’s WM due to the rich number of
multimedia elements and gamified features, which may limit the capacity for problem
solving (Huang, 2011; Kiili, 2005; Moreno & Mayer, 2003). A cognitive overload on WM
capacity may constrain both the acquisition of reasoning skills and the acquisition of
knowledge (Baddeley, 1992; Eylon & Linn, 1988). The cognitive load experienced by
individuals depends in part on their ability to selectively attend to relevant stimuli
and, therefore, inhibit their attention to irrelevant stimuli such as distractors.
Inhibitory control (IC) is the ability to prevent a response that is not relevant to the
current task or situation (i.e., distracting stimuli or thoughts) and to control one’s
attention, focusing on what one chooses and resisting interference (Diamond, 2013). IC
skills have been found to predict mathematical performance in typically developing
children, particularly in preschool and primary school children (Bull, Johnston, & Roy,
1999; Bull & Scerif, 2001; Espy et al., 2004; St Clair-Thompson & Gathercole, 2006). In
online game-based learning environments, task-irrelevant distracting stimuli, such as
gamified sounds, flashing objects, and alternative answer options, can trigger typically
made errors. Similar to the Simon effect (Simon, 1969), where studies have found that
irrelevant sensory stimuli in a task directly influence response selection and increase
reaction time, the presence of irrelevant information in an online learning environment
could interfere with performance in terms of accuracy and reaction time depending on one’s
level of IC. Furthermore, Bull et al. (1999) and Rourke (1993) suggested that a lack of IC
is also reflected in the type of errors children tend to make, for example, the inability
to switch away from addition when multiplication is required (i.e., operant-related
error). Interference and cognitive overload in a learning environment do not always stem
from external stimuli but can also be internal in the form of worries about individual
performance or about perceived time pressure (Ashcraft & Kirk, 2001; Mendl, 1999). These
stressors can either drive people to use more efficient strategies (i.e., the best
speed–accuracy trade-off within the constraints of the new situation) or compete with the
attention that is normally allocated to the execution of the task (Caviola, Carey,
Mammarella, & Szucs, 2017; Starcke & Brand, 2012). The latter is also known as the adverse
effect of “choking under pressure”, where individuals perform worse than if there were no
pressure (Baumeister, 1984; Beilock & DeCaro, 2007; Lewis & Linder, 1997). Critically,
studies have found that people with high WM capacity are more affected by this dual-task
environment and suffer more under pressure than those with low WM capacity (Beilock &
Carr, 2005; Sattizahn, Moser, & Beilock, 2016; Wang & Shah, 2014). In addition, Sattizahn
et al. (2016) found that individuals’ variability in attentional control processes
influenced the effect of pressure. Those with poor attentional processes suffered
decreased performance under pressure, reflecting that some individuals are able to prevent
the interfering effect of pressure on their performance, whereas others with poorer
attentional control are not. So, although increased WM and IC are generally associated
with better math performance and efficient strategy use, many studies have found that this
depends on the stressors in the environment. The purpose of the current study was to
investigate the impact of stressors in the relatively new context of an online learning
environment. One particular stressor, typical to a lot of online game-based learning
environments, is time pressure, which is usually presented in the form of a gamified
visual stimulus. For example, in Math Garden there is visual time pressure in the form of
coins counting down every second, which is also incorporated into the game’s scoring rule
for math performance (i.e., “high speed, high stakes” rule; see Maris & van der Maas,
2012). The advantage of using time pressure is that it provides the opportunity to relate
speed of processing to the ability of the child, which is valuable with easy problems
(Klinkenberg et al., 2011; van der Maas & Wagenmakers, 2005). In addition, in the case of
games (similar to sports), the challenge of acting within a time limit can make the
activity more enjoyable (Freedman & Edwards, 1988). Because time pressure itself is
invaluable for most game-based learning environments, the current study addresses a
different question: Should the visibility of the time pressure (in the form of a
countdown) be adapted for individuals depending on whether it negatively affects math
performance? Following the interference and overload theory, time pressure in the form of
animated visual stimuli could be a distracting component that negatively interferes with
solving math problems depending on the child’s level of IC and WM. However, the
alternative situation, with no visible reminder of time passing by, requires attention to
be allocated to time perception, which could result in suboptimal strategies in
speed–accuracy trade-off in the main task (Brown & Perreault, 2017; Grondin, 2010;
Matthews & Meck, 2016; Zakay, 1993). The purpose of this study was threefold. First, we
investigated the association of individual differences in verbal WM and IC with
performance of simple addition and multiplication problems in blocks of single or mixed
operations in a game-based environment for primary school children. We expected that both
verbal WM and IC would be positively associated with math performance and that higher IC
would be associated with a reduced cost of switching between multiplication and addition.
Second, we explored whether a particular feature of cognitive load, the visibility of time
pressure, would affect arithmetic performance in general and whether this impact was
different for various children depending on the level of WM and IC. We did not have a
hypothesis regarding whether visibility or invisibility of time pressure would be
associated with worse math performance because both features create a dual-task condition.
Any effect on math performance was expected to interact with individual differences in WM
and/or IC. Finally, whether learners are attending to or actively inhibiting their
attention to irrelevant/distracting stimuli can be studied by looking at eye movements and
fixations (i.e., moments when the eyes are relatively stationary and fixed on an object)
using eye-tracking technology (Duprez et al., 2016; Wijnen & Ridderinkhof, 2007). In a
learning environment, eye tracking can be used to investigate how learners interact with
the stimuli and how the order and duration of their attending affect their problem
solving. Eye-tracking data can also be used to improve the learning environment based on
knowledge of how learners process the materials through their eye movements (Asteriadis,
Tzouveli, Karpouzis, & Kollias, 2009; Garcia-Barrios et al., 2004). Using eye tracking, we
explored differences in the locus of attention during the arithmetic task depending on
whether time pressure was visible or not and on children’s levels of WM and IC. This study
included data from a single time point and, therefore, will not inform our understanding
of how individual differences and task features affect learning over time. However, a
better understanding of how performance in online math tasks may be affected by these
factors could allow a tailoring of the environment to individual learners, making sure
that the task challenges, and therefore trains, their arithmetic skills rather than
loading on other aspects of their cognitive capacity.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 42 primary school children aged 8 to 11 years were recruited through a local
voluntary participant database and word of mouth. Three children were excluded from all
analyses because testing sessions were interrupted due to distress or tiredness. The final
sample consisted of 39 children (19 male; Mage = 9.60 years, SD = 1.02, range =
8.00–11.50). For 3 children, insufficient eye gaze data were collected, leaving 36
children (18 male; Mage = 9.67 years, SD = 1.00, range = 8.00–11.50) for the eye-tracking
analyses. The study was approved by the departmental ethics committee at the university.
Informed consent was given by caregivers, and verbal assent was given by participants.

<hs>  Procedure</hs>
  ~~~~~~~~~

All stimuli were presented in MATLAB (The MathWorks, Natick, MA, USA) using the
Psychophysics Toolbox (Brainard, 1997). During the first task, participants performed a
math task on a computer (see Fig. 1A) similar in design to Math Garden (Straatemeier,
2014). The study took place in a lab setting, and all measures were completed in a single
session lasting about 30 min in total. Before data collection started, condition
assignment was randomized for a list of 40 participants using MATLAB. An additional 2
participants were tested to compensate for incomplete or withdrawn participants. There
were three randomly ordered blocks comprising 20 multiplication problems, 20 addition
problems, and 22 mixed multiplication and addition problems, respectively. All problems
involved single-digit numbers between 1 and 9. For each arithmetic problem, participants
were asked to choose one of six answer options, which consisted of the correct answer and
the five most frequent errors made by children of similar age on that arithmetic problem,
based on Math Garden data previously collected from a large Dutch sample (Fig. 1A).
Participants had a maximum of 8 s to click on one of the answers, after which the correct
answer was highlighted. In a between-participants manipulation, 19 children were randomly
assigned to the visible time pressure condition, where the time limit of 8 s was visible
in the form of coins counting down at the bottom right of the screen, similarly to Math
Garden (Fig. 1A). The other 20 children needed to respond within the same 8 s, but there
were no coins on the screen (no visible time pressure condition). After every trial,
direct feedback on performance was given; the correct answer was circled in green, and the
incorrect answer was circled in red in the case of an incorrect response. The measure of
math performance was calculated with a scoring rule following the equation sij = (2xij −
1)(d − tij) (adapted from Maris & van der Maas, 2012). This rule imposes a speed–accuracy
trade-off, where fast and correct responses result in a high score and incorrect responses
result in a negative score. Player j responds xij on trial i (xij = 1 in the case of a
correct answer and xij = 0 in the case of an incorrect answer) in time tij (in seconds;
range = 0 to 8) before the time limit d (set to 8 s in this study) and obtains the score
sij (range −8 to 8). Participants’ verbal WM was then assessed with a backward digit span
task, where children were asked to repeat, backward, lists of single-digit numbers
pronounced by the experimenter. After practice with two numbers, the first level consisted
of four lists of three numbers; the child moved one level up (with an additional number)
when at least three of the four lists were repeated back successfully. A WM score was
computed as the total number of correct answers. IC was assessed with a computerized
spatial incompatibility Simon task (adapted from Duprez et al., 2016; see Fig. 1B).
Children were asked to move their mouse to either the top left or top right box depending
on the color of the target square while ignoring its location. When the target was blue
children needed to move their mouse toward and click into the left box, and when it was
orange they needed to move their mouse toward and click into the right box. In half of the
trials the location of the target was congruent with the correct response, and in the
other half it was incongruent with the correct response (Fig. 1B). Participants completed
40 trials in a randomized order, which resulted in between 1 and 5 trials of the same type
(congruent/incongruent) being repeated in a row. The measure of IC, referred to as the IC
interference effect, was computed as the difference between incongruent and congruent
trials mean reaction time (RT) divided by congruent trials mean RT, using correct trials
only. A high score reflects a slower RT on incongruent trials (i.e., difficulty in
inhibiting attention to irrelevant information) than on congruent trials (i.e., baseline
processing speed).

        <hss>Eye tracking</hss>

        During the math and Simon tasks, children were seated at a distance of 60 cm in
        front of an eye tracker. Eye movements were recorded using a Tobii TX300 (Tobii,
        Danderyd, Sweden) at a sampling rate of 120 Hz. The raw data were classified into
        fixations and saccades using the gazepath package in R (R Core Team, 2013; van
        Renswoude et al., 2018). Gazepath uses an algorithm to categorize the data into
        fixations and saccades while accounting for individual differences and data
        quality. Fixations in the math task were labeled as one of the following three
        areas of interest (AOIs): (a) the question box, (b) one of the six answer options,
        or (c) the coins (i.e., the visible countdown of time) (Fig. 1A).

        <hss>Statistical analyses</hss>

        Data management and statistical analysis were performed using R software (R Core
        Team, 2013). For all independent variables, z scores were generated to standardize
        the scores for further analyses. In a first set of analyses, math performance was
        averaged over the three blocks (addition, multiplication, and mixed addition and
        multiplication) and compared between the visible time pressure condition and the
        no visible time pressure condition, covarying for age and WM score or IC
        interference effect, using between-participants three-way analyses of covariance
        (ANCOVAs). With a sample size of 39, the study had 80%, 90%, and 95% power to
        detect large eta-square (η2) effect sizes of .18, .22, and .26, respectively, when
        comparing two groups. Eta-square effect sizes have been classified as follows:
        small η2 = .02, medium η2 = .13, and large η2 = .26 (Cohen, 1988). An additional
        analysis investigated associations between IC and the cost of needing to switch
        between operations. We subtracted the average performance of the mixed block
        trials from the average performance on the trials in the single operation blocks
        for multiplication and addition problems separately. These cost measures were
        entered into ANCOVAs including the IC interference effect, visibility of time
        pressure, and age for multiplication and addition separately. Assumptions of the
        ANCOVAs were met, with analyses showing homoscedasticity and normality of the
        residuals. Eye-tracking analyses (n = 17 in the visible time pressure condition
        and n = 19 in the no visible time pressure condition) focused on correct trials
        (excluding 12.7% of trials) and trials where there was at least more than one
        fixation to ensure high eye-tracking data quality (excluding a further 1.2% of
        trials). The average number of fixations and the proportional duration of fixation
        on each AOI were calculated for each participant. An additional metric was the
        average number of answer option AOIs the participant attended to on a trial. We
        explored, in three-way ANCOVAs, whether these eye-tracking metrics differed
        according to the visibility of time pressure and whether this interacted with WM
        score, IC interference effect, or math performance. The data were checked for
        outliers using a criterion of |z score| > 3 for both the dependent and independent
        variables. No outliers were identified. In the regression analyses, Cook’s
        distance suggested one to three influential points for some behavioral and eye-
        tracking results. Analyses were repeated excluding these data points, and the
        results were strengthened except in one case, which is discussed further below. In
        addition, Bayesian ANCOVAs were performed post hoc for the results with null
        effects or p values just under the threshold (p < .05) using JASP (JASP Team,
        2019). To quantify uncertainty about effect size and to obtain evidence in favor
        of a null hypothesis (Wagenmakers et al., 2018), we distinguished between
        experimental insensitivity (Bayes factor [BF]10 and BF01 < 3) and robust support
        for the alternative hypothesis (BF10 > 3) or null hypothesis (BF01 > 3) (Dienes,
        2014)

<hs>  RT and accuracy</hs>
  ~~~~~~~~~~~~~~~

We performed two one-sided equivalence tests with alpha = .05 and no assumption of equal
variance and found statistical equivalence between the visible and no visible time
pressure groups for age, percentage female, verbal WM, and IC (Table 1). t Tests were run
to test whether visibility of time pressure was associated with math performance. We did
not find any difference between the groups in mean RT, t(38) = 0.82, p = .42, proportion
of correct responses, t(38) = 0.45, p = .66, proportion of no response within the time
limit, t(38) = 0.15, p = .88, or mean math score, t(38) = 0.77, p = .45. These comparisons
indicate that the visibility of time pressure did not have an effect on math performance.
The average overall math performance was 3.34 (SD = 1.34), meaning that the average score
was correct and answered within roughly half the time limit (see Method for scoring rule).
This measure was used for further analyses. Mean accuracy in the Simon task was high (M =
.99, SD = .05). As expected, RTs differed between congruent and incongruent trials, t(38)
= 6.17, p < .001. Participants were on average 150 ms slower in incongruent trials (Fig.
2A). The individual average IC interference effect was used as a measure of IC for further
analyses (Fig. 2B).

<hs>  Impact of time pressure on math performance depending on level of IC and verbal WM</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The first analysis included only age and visibility of time pressure as predictors of math
performance. This showed a positive association between age and math performance, F(1, 35)
= 32.05, p < .001, ηp2 = .53 but not time pressure (p = .892, ηp2 = .00), nor was there an
interaction between age and time pressure (p = .679, ηp2 = .01). The second analysis
included WM score as a covariate (Table 2). WM score was positively associated with math
performance, F(1, 31) = 13.15, p = .001, ηp2 = .24 (Fig. 3A), but there was no interaction
with age or time pressure (all ps > .50, ηp2 < .01). The Bayesian ANCOVA showed that a
null model with merely main effects for WM score and age was 11.4 times more likely than
including any of the above-mentioned interactions or the main effect of time pressure. The
third analysis (Table 2) included the IC interference effect as covariate. There was no
main effect of IC interference effect (p = .62, ηp2 = .01), but there was a significant
two-way interaction between time pressure and IC interference effect, F(1, 31) = 6.59, p =
.015, ηp2 = .18, and a three-way interaction between time pressure, age, and IC
interference effect on math performance, F(1, 31) = 4.55, p = .041, ηp2 = .13. Significant
evidence for both interaction effects was demonstrated through Bayesian analyses (Table
2). To examine the two- and three-way interactions, separate multiple regressions were
performed in the visible and no visible time pressure groups. In the group with visible
time pressure, the IC interference effect and Age × IC interference effect interaction
terms did not significantly predict variance in math performance (BF01 = 0.57, i.e., no
evidence for either hypothesis) (Fig. 3B). In contrast, the group with no visible time
pressure showed a negative association between math performance and IC interference
effect, β = −.42, t(16) = 2.77, p = .014 (BF10 = 6.47, i.e., substantial evidence for
including this effect) (Fig. 3B), and an interaction between age and IC interference
effect, β = .43, t(16) = 2.629, p = .018 (BF10 = 8.84). The interaction effect showed that
the association between math performance and IC interference effect was mostly driven by
younger children (Fig. 3C).

<hs>  Operation switch cost</hs>
  ~~~~~~~~~~~~~~~~~~~~~

To investigate whether switching between operations led to a cost in performance, we
compared the mean math scores of single operation versus mixed operation blocks for
multiplication and addition problems separately. Paired t tests showed that children’s
performance on multiplication problems did not differ between the mixed (M = 2.83) and
single (M = 2.76) operation multiplication blocks, t(38) = 0.41, p = .341. For addition,
children performed less well on the trials in the mixed block (M = 3.67) than on those in
the single operation block (M = 4.00), t(38) = 2.51, p = .008. Therefore, children showed
a cost of needing to switch between multiplication and addition on addition problems only.
Because the ability to switch between arithmetic operations has been associated with IC in
previous studies (Bull et al., 1999; Rourke, 1993), additional analyses explored whether
IC predicted the ability to switch between addition and multiplication operations in the
mixed operation blocks compared with the single operation blocks (Table 2). For addition
problems, the IC interference effect predicted the performance difference between the
mixed and single operation blocks, F(1, 31) = 5.06, p = .031, ηp2 = .13. Bayesian ANCOVA
showed that a model including IC was 2.68 times more likely than the null model; no
interaction with age (p = .302, ηp2 = .03) or time pressure (p = .153, ηp2 = .06) was
found.

<hs>  Eye fixations and patterns</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Exploratory analyses investigated whether eye movements during the math task could give
some insight into the behavioral findings. Analyses were performed on the mean number of
fixations and proportion of total fixation duration on specific AOIs. The latter did not
show any significant effect. The first analyses looked at the fixations on the question
box AOI (e.g., 6 × 8 in Fig. 1A) because other studies have found that looking back and
forth at the question is positively associated with attentional and WM load (Droll &
Hayhoe, 2007; Orquin & Mueller Loose, 2013). ANCOVAs were run to test for associations
with the visibility of time pressure in interaction with individual differences in IC and
WM separately while covarying for age and math performance (Table 2). A significant main
effect for time pressure, F(1, 28) = 12.02, p = .003, ηp2 = .43 (BF10 = 30.88, i.e., very
strong evidence), showed that there were more fixations on the question box when time
pressure was visible (M = 2.69) than when there was no visible time pressure (M = 2.02)
(Fig. 4A). Second, because operation-related errors have been found to be associated with
the level of IC (Bull et al., 1999; Rourke, 1993), fixations on the operation-related
error answer options were investigated separately for addition and multiplication. ANCOVAs
were performed to test for associations with the visibility of time pressure and the IC
interference effect while covarying for age and math performance. For the addition
problems with multiplication-related errors as answer options, we found no significant
predictors (ps > .20, ηp2 < .05) (Table 2). For multiplication problems with addition-
related errors, a significant interaction between time pressure and IC interference
effect, F(1, 28) = 5.34, p = .018, ηp2 = .44 (BF10 = 5.21, i.e., substantial evidence),
showed that the mean number of fixations on the addition-related error increased with
increasing IC interference effect (β = .56) only when time pressure was visible. Finally,
analyses were performed to investigate the mean number of answer options participants
looked at before giving their answer and whether this was related to WM, IC, and the
visibility of time pressure. An ANCOVA was performed with the average number of answer
options attended to as the dependent variable, visibility of time pressure and IC
interference effect or WM as independent variables, and age and math performance as
covariates. The analysis with WM as a predictor showed no main or interaction effects,
only evidence that a null model was 11 times more likely than including any of the
predictors. The analysis with IC as a predictor showed a significant interaction between
visibility of time pressure and the IC interference effect, F(1, 31) = 4.60, p = .039, ηp2
= .13. However, Cook’s distance highlighted that there was one influential point that
drove this interaction. Consistent with this, only anecdotal evidence (BF10 = 2.90) for
including this interaction to the null model was found in the Bayesian regression (Fig. 4C
and Table 2). Follow-up regression analysis showed a trend for a positive association for
the IC interference effect when time pressure was visible, β = .54, t(13) = 2.03, p =
.063, but little evidence (BF10 = 1.23) in the Bayesian regression. No association between
the IC interference effect and number of answer options visited was found when time
pressure was invisible, β =  − .21, t(16) = 0.82, p = .423; Bayesian regression showed
anecdotal evidence for the null hypothesis (BF01 = 2.00).

<h>DISCUSSION</h>
----------

This study combined behavioral and eye-tracking measures to test whether individual
differences in verbal WM and IC in primary school children could predict their ability to
solve arithmetic problems in different online learning environments, where visibility of
time pressure was varied. The behavioral results showed that verbal WM was a positive
predictor of arithmetic performance in general, in line with previous studies (see
Raghubar et al., 2010, for a review), and that this association was independent of the
visibility of time pressure. In contrast, individual differences in IC predicted
arithmetic performance only when the same time pressure was not visibly illustrated by an
animation. In addition, we found that this association with IC was mostly driven by
younger children, similar to previous studies (Bull & Scerif, 2001). Eye-tracking results
also showed that children fixated on different parts of the stimuli during the math task
depending on the visibility of time pressure, their IC level, and age. Overall, these
findings point out that the visibility of time pressure may affect performance of certain
individuals in online learning environments and that possible constraints of attentional
control (i.e., the amount of interfering information compromising cognitive resources)
should be considered. Learning environments with both visible and invisible time pressure
can create dual-task environments, leading to less attention to the main task of solving
math problems. When time pressure is visible, the user has a constant physical reminder of
timing (in this study in the form of an animated visual stimulus). Adding more visual
stimuli and time pressure was suggested by previous studies to contribute to loading WM
capacity, leading to suboptimal strategies and attention (Barrouillet, Bernardin, Portrat,
Vergauwe, & Camos, 2007; Caviola et al., 2017; Terras & Ramsay, 2012). This impact can
also be influenced by other individual differences such as math anxiety (Ashcraft &
Krause, 2007; Caviola et al., 2017; Kellogg, Hopko, & Ashcraft, 1999), engagement, and
attitude to learning (Barkatsas, Kasimatis, & Gialamas, 2009; Kebritchi, Hirumi, & Bai,
2010). Although the visibility of time pressure did not interact with individual
differences in verbal WM in terms of math performance, the notion of visible time pressure
as an increasing demand on WM resources is reflected in our eye-tracking results. Children
made more fixations on the question in the visible time pressure condition than in the
invisible time pressure condition, suggesting that they may have found it more difficult
to keep the question in mind (Orquin & Mueller Loose, 2013). Although previous studies
suggested that the impact of extra stressors on math performance depends on the ability to
resist distractions (i.e., IC; Sattizahn et al., 2016), we showed that the performance of
children was not affected by their level of inhibition when time pressure was visible. The
higher number of fixations on answer options and on operation-related errors did suggest
that for children with lower IC the task was more demanding in terms of decision
difficulty and/or attentional resources (Orquin & Mueller Loose, 2013), but this did not
result in lower performance. Time perception is intensively studied (for an overview of
recent reviews, see Block, Grondin, & Gibbon, 2014) and involves diverse perceptual,
motor, cognitive, and brain processes (Block & Gruber, 2014). One line of investigation in
time perception concerns its bidirectional interference with higher-level executive
cognitive processes such as mental arithmetic but also with executive functions (Block,
Hancock, & Zakay, 2010; Brown, Collier, & Night, 2013). This interference occurs in a
dual-task condition where time perception competes for the same attentional resources as
the other task, leading to cognitive load. Because the interference is bidirectional,
studies have also shown that lower IC is associated with less accurate time perception
(Brown & Perreault, 2017; Meaux & Chelonis, 2005). This closely aligns with our finding
that low levels of IC were associated with low arithmetic performance when children also
needed to estimate time without a reminder. This could be due to an impairment of time
perception, such that these children have trouble in deciding on an optimal speed–accuracy
trade-off strategy. Therefore, for children with low IC, visualizing time pressure could
reduce cognitive load, whereas children with high IC seem to be able to estimate time in
parallel with solving arithmetic problems. One of the limitations of this study was the
small sample size. This was due to the use of an eye tracker, which necessitated a lab
setting. The use of a participant volunteer database and testing in a lab setting also
likely biased our recruitment toward children from higher socioeconomic backgrounds and
with higher cognitive abilities. The next step would be to replicate our findings with a
larger heterogeneous sample from online learning environments such as Math Garden to
ensure that the behavioral findings are reliable. In addition, we chose a between-
participants design that minimizes the effect of learning and testing time, but a within-
participants design would have had more power to detect interactions between the time
pressure manipulation and individual differences in WM and IC. Future work will
investigate whether learning, rather than performance at a single time point, can be
improved based on an adapted environment, informed by the results of the current study.
Although the purpose of this study was to implement these findings in an online adaptive
environment, the arithmetic problems used were standardized to ensure that we could
compare arithmetic performance within this sample size. Due to our wide age range (8–11
years), certain arithmetic problems were inevitably less challenging for some children;
therefore, all analyses were covaried for age. Note, however, that there are large
individual differences within year groups on arithmetic tasks (Straatemeier, 2014), so a
more homogeneous sample in terms of age may have still shown considerable variability in
arithmetic performance. To further investigate whether the associations among IC, WM, time
pressure, and arithmetical outcome change with age, the difficulty level of the arithmetic
problems should be adapted to the ability of the child. Finally, whereas we considered the
coin countdown to reflect time pressure, it also indicated the potential reward to be
gained when correctly solving the problem. Although the reward obtained was shown to both
groups of participants when a trial was completed, the group with no visible coin
countdown did not have a constant reminder of the potential reward. This reward cue
difference between the groups may have led to some of the differences observed between the
conditions. In conclusion, we found that the (in)visibility of time pressure, a key
feature that is adaptable in a lot of online game-based learning environments and
psychological tasks in general, may create cognitive overload and affect the application
of knowledge and skills. Specifically, we showed that this aspect of online game-based
learning environments may differentially affect children’s arithmetic performance as a
function of their cognitive abilities. Measuring the individual levels of cognitive
functioning, in particular WM and IC, is essential to allow children to perform and
practice tasks at their highest level. In addition, the use of an eye tracker in this
context allowed an in-depth exploration of how learners interacted with the different
elements in the environment above and beyond accuracy and RT. Future work should focus on
developing a broader online adaptive framework for learning mathematical skills and
knowledge that adapts not only to children’s mathematical skills but also to their more
general cognitive strengths and weaknesses.


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<ART>Simultaneous effects of irrelevant speech, temperature and ventilation rate on performance and satisfaction in open-plan offices
================================================================================

Authors: Johanna Varjo, Valtteri Hongisto, Annu Haapakangas, Henna Maula, Hannu Koskela, Jukka Hyönä
DOI: 10.1016/j.jenvp.2015.08.001
Year: 2015  |  Pages: 16-33
ASJC codes: 3202, 3207
Keywords: Air quality, Cognitive performance, Indoor environment, Noise, Open-plan offices, Room temperature

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The aim of this study was to investigate how irrelevant speech, temperature and ventilation rate together affect cognitive performance and environmental satisfaction in open-plan offices. In Condition A, neutral temperature (23.5 °C), low intelligibility of speech (high absorption and low masking sound level) and high fresh air supply rate (30 l/s per person) were applied. This was contrasted to Condition B with high room temperature (29.5 °C), highly intelligible speech (low absorption and high masking sound level) and a negligible fresh air supply rate (2 l/s per person). Sixty-five participants were tested. In Condition B, performance decrement was observed especially in working memory tasks. Based on subjective assessments, mental workload, cognitive fatigue and symptoms were higher and environmental satisfaction was lower in Condition B. It was concluded that special attention should be paid to the design of whole indoor environment in open-plan offices to increase subjective comfort and improve performance.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Scientific interest towards subjective satisfaction in open-plan offices has increased
because open-plan office has become the most usual office solution, mostly because of its
high space efficiency (De Croon, Sluiter, Kuijer, & Frings-Dresen, 2005). Moreover, open-
plan offices are also assumed to improve organizational productivity due to the enhanced
exchange of information and communication and increased teamwork (Allen & Gerstberger,
1973; Hundert & Greenfield, 1969). However, many studies have shown that there are
disadvantages in open-plan offices if the design of the indoor environment (IE) is
inadequate. Increased cognitive workload (De Croon et al., 2005), concentration problems
and fatigue (Haapakangas, Helenius, Keskinen, & Hongisto, 2008; Pejtersen, Allermann,
Kristensen, & Poulsen, 2006) and the lack of speech privacy (De Croon et al., 2005) have
been reported. Open-plan offices have also been associated with decreased job satisfaction
(De Croon et al., 2005). Decreased satisfaction with IE has been indicated to have a
connection with decreased job satisfaction (Veitch, Charles, Farley, & Newsham, 2007). The
amount of annual sick leave has also been shown to be greater in open-plan offices, as
assessed by employees’ self-ratings (Bodin Danielsson, Chungkham, Wulff, & Westerlund,
2014; Pejtersen, Feveile, Christensen, & Burr, 2011). One of the most commonly mentioned
causes for these problems is poor acoustic conditions, i.e., disturbance caused by
colleagues’ speech and poor speech privacy (Danielsson, 2005; Frontczak et al., 2012;
Haapakangas et al., 2008; Pejtersen et al., 2006). Improper thermal conditions and poor
air quality have also been reported as producing discomfort in open-plan offices
(Haapakangas et al., 2008; Pejtersen et al., 2006). On the other hand, overall improvement
of the IE can significantly increase environmental satisfaction in open-plan offices
(Hongisto, Haapakangas, Helenius, Keränen, & Oliva, 2012). That is, differences between
open-plan offices can be significant regarding on the quality of IE. The effects of IE on
work performance and various components of environmental satisfaction have been studied in
several laboratory experiments. However, most of the previous laboratory studies have
focused on the effects of a single factor of IE. In the present study, we simultaneously
manipulated three IE factors in order to examine their joint effects on task performance
and environmental satisfaction. Fig. 1 depicts how our study was designed as a follow-up
study to three previous studies each separately examining the effects of a single factor
of IE. We next summarize the evidence for the effects of each factor examined separately.

<hs>  Effects of office noise</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Office noise, especially irrelevant speech having sufficiently high intelligibility, has
been shown to decrease performance in serial recall (e.g., Haapakangas et al., 2011; Haka
et al., 2009), information search (Jahncke, Hongisto, & Virjonen, 2013), proofreading
(e.g., Venetjoki, Kaarlela-Tuomaala, Keskinen, & Hongisto, 2006) and counting tasks (e.g.,
Buchner, Steffens, Irmen, & Wender, 1998). Our experiment was preceded by an experiment
conducted in the same laboratory, which showed that the room acoustic design, where the
intelligibility of irrelevant speech could be reduced, improved work performance
(Haapakangas, Hongisto, Hyönä, Kokko, & Keränen, 2014). Moreover, subjective assessments
confirm the negative impact of highly intelligible irrelevant speech; speech and other
office activity sounds negatively affect subjective well-being, acoustic satisfaction and
self-estimated performance (Evans & Johnson, 2000; Haapakangas et al., 2014; Haapakangas
et al., 2011; Haka et al., 2009). It is important to study how different room acoustic
solutions usually applied in open-plan offices can be used to reduce the negative effects
of irrelevant speech. The effects seem to mainly depend on speech intelligibility
(Ellermeier & Hellbrück, 1998; Hongisto, 2005; Jahncke et al., 2013) and not on the
loudness of speech (Colle, 1980). Performance is expected to decrease with increasing
Speech Transmission Index, STI (Hongisto, 2005). Subjective speech intelligibility can be
objectively evaluated by measuring STI which ranges from 0.00 to 1.00, with large values
representing highly intelligible speech (ISO 3382-3). STI can be reduced in open-plan
offices by simultaneous application of high room absorption, high screens between desks
and the use of masking sound (Bradley, 2003; Keränen & Hongisto, 2013; Virjonen, Keränen,
& Hongisto, 2009). By reducing the STI values below 0.30, it can be expected that the
negative effects on performance can be significantly reduced (Haka et al., 2009; Jahncke
et al., 2013; Keus van de Poll, Ljung, Odelius, & Sörqvist, 2014) compared to a situation
where the STI is above 0.50, which is, unfortunately, very typical in open-plan offices
(Keränen & Hongisto, 2013; Virjonen et al., 2009). Our study involved an acoustic
manipulation where the two most important factors of acoustic design were considered
simultaneously: sound masking and room absorption. Absorption was used to reduce the
reflection of sound from room surfaces and to reduce the overall speech level. Sound
masking was used to reduce the signal-to-noise ratio of speech. Successful application of
masking sounds in the office has been reported by Hongisto (2008) and Hongisto et al.
(2012).

<hs>  Effects of high room temperature</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Room temperature can affect cognitive performance (see e.g., reviews of Hancock, Ross, &
Szalma, 2007; Pilcher, Nadler, & Busch, 2002). However, the results of these reviews
cannot be directly applied to office environments because the examined thermal conditions
differed from usual thermal conditions in offices. The desirable room temperature in
offices is between 21 °C and 25 °C depending on outside temperature, clothing, activity
level and cultural differences. However, much higher temperatures, up to 35 °C, can be
found in offices having insufficient cooling capacity or no cooling at all. When neutral
temperatures (21–25 °C) have been compared to higher ones (above 26 °C), cognitive
performance has been observed to decline at higher temperatures in short-term free recall
tasks (Hygge & Knez, 2001), addition and visual tasks (Lan, Wargocki, Wyon, & Lian, 2011)
and working memory tasks (Häggblom, Hongisto, Haapakangas, & Koskela, 2011). Maula et al.
(2015; Fig. 1) performed an experiment before our study in the same laboratory
environment. They found that high temperature (29 °C) affected the performance in working
memory demanded N-Back task. However, temperature did not affect psychomotor, attention or
long-term memory tasks. These results are consistent with the suggestion of Hancock et al.
(2007) that the performance effects of room temperature are task-sensitive. Subjective
assessments yield a more uniform picture of the effects of room temperature. High
temperature has been reported to negatively affect mood, energy, motivation, concentration
and the assessment of air quality (Lan et al., 2011; Maula et al., 2015). High temperature
has also been found to increase self-rated intensity of somatic symptoms compared with
neutral temperature (Lan et al., 2011).

<hs>  Effects of air quality</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Air quality is affected by the ventilation rate and emissions from the building, furniture
and occupants (Wargocki, Bakó-Biró, Clausen, & Fanger, 2002). In the majority of
laboratory experiments investigating the effects of air quality on performance, the air
quality has been reduced by artificial material emissions, such as by installing old and
polluting carpets in the room. The combination of artificial material emission and small
ventilation rate has marginally decreased performance in typing and negatively affected
subjective assessments of air quality and well-being (Wargocki, Wyon, Sundell, Clausen, &
Fanger, 2000). Similar results have been found for high material emissions with a constant
ventilation rate (Wargocki, Wyon, Baik, Clausen, & Fanger, 1999). When office buildings
are renovated, furniture and decoration are likely to be changed and old material emission
sources are usually removed. The emissions from new furniture and surface materials can
cause relatively high concentrations of volatile organic compounds (VOCs) for a couple of
months. The combination of high material emissions from new materials and small
ventilation rate has been found to decrease objectively measured performance in typing,
addition and memorization tasks and to reduce the acceptability of perceived air quality
(Park & Yoon, 2011). In comparison, a previous study (Koskela, Maula, Haapakangas, Moberg,
& Hongisto, 2014, Fig. 1) carried out in the same laboratory as our study investigated the
situation where the occupants themselves were the strongest pollution sources of the room.
Comparison between high (28 l/s per person, 600 ppm) and low (2 l/s per person, 2200 ppm)
ventilation rates with negligible emission from furniture and building did not reveal any
remarkable differences in subjective environmental assessment or objective performance
despite the fact that the tasks required cognitive processes relevant to many types of
office work and the exposure time was reasonably long (3.5 h). In contrast, decision-
making performance has been shown to decline by high carbon dioxide (CO2) concentrations
(Satish et al., 2012). Due to methodological differences, more research is needed to
confirm the effects of air quality on task performance and subjective assessment of the
work environment. It is also worth noting that there is no fundamental theory of what
mechanisms, such as fatigue or working memory capacity, would explain the effects of poor
air quality on cognitive performance.

<hs>  Combined effects of IE</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Only a few studies have focused on the effects of several simultaneously modified IE
factors on objective performance, despite the fact that occupants are exposed to several
factors of IE in open-plan offices. In addition, the results are inconsistent. Some
studies have reported expected performance effects (Balazova, Clausen, & Wyon, 2007; Hygge
& Knez, 2001). Also interaction effects between IE factors have been reported (Witterseh,
Wyon, & Clausen, 2004). However, even major changes in IE conditions have not always
affected performance (Balazova, Clausen, Rindel, Poulsen, & Wyon, 2008; Clausen & Wyon,
2008). On the other hand, subjective ratings have indicated more uniformly how several IE
factors together affect human comfort. Simultaneous negative changes in IE factors, such
as temperature, irrelevant speech (office noise), traffic sounds and air quality, have
increased dissatisfaction (Balazova et al., 2007, 2008) and reduced the perceived ability
to concentrate on and perform job-relevant tasks (Balazova et al., 2007; Clausen & Wyon,
2008). A wide variety of environmental conditions, tasks and procedures have been used in
the aforementioned studies. First, performance is affected differently by different noise
types (e.g., Banbury & Berry, 1998; Szalma & Hancock, 2011). Studied noises have been
originated from office noise (Balazova et al., 2008; Clausen & Wyon, 2008; Witterseh et
al., 2004), road traffic (Balazova et al., 2007; Clausen & Wyon, 2008), or ventilation
(Hygge & Knez, 2001). It has been shown that intelligible speech interferes with working
memory and performance because it is unpredictable and information-rich, while constant
noise does not cause interference (Jones, Madden, & Miles, 1992). Second, the exposure
times have varied from 20 min (Balazova et al., 2007) to 6 h (Balazova et al., 2008).
Third, successful task performance requires several cognitive processes (Sörqvist, 2014);
very different tasks relying on varied cognitive processes have been used to measure task
performance. Fourth, in some studies participants have been told about the IE conditions
before the experiment (e.g., Balazova et al., 2007) or they have been able to personally
select the IE conditions (Clausen & Wyon, 2008). Finally, both between-subjects (e.g.,
Hygge & Knez, 2001) and within-subjects (Balazova et al., 2007, 2008) designs have been
employed. All these variations can be assumed to affect the results on performance and
subjective assessment of the IE via different paths. In our study, the environmental
conditions and experimental procedures were selected so that both practical questions
related to the work environments and the highest possible scientific quality could be met.
Speech was used as the noise source since it is the most often complained noise source
(e.g., Haapakangas et al., 2008). Several cognitive tasks were applied to cover a variety
of different kinds of office work. A moderately long exposure time was applied to mimic a
typical working period at the office desk (2 h). The participants were blind with respect
to the experimental manipulations. Finally, a within-participants design was used to
reduce inter-individual variability in cognitive performance and environmental effects.

<hs>  The aim of the study</hs>
  ~~~~~~~~~~~~~~~~~~~~

Our study represents the final experiment of a larger research programme (Fig. 1). The
experiment, which combines three factors of IE (intelligibility of irrelevant speech,
temperature and air quality), was preceded by three laboratory experiments that focused on
each single factor. Out of these three experiments, performance effects were found in the
experiment concerning the intelligibility of irrelevant speech (Haapakangas et al., 2014)
and room temperature (Maula et al., 2015). The effects of these factors were also evident
on subjective responses. However, the impact of low ventilation rate (2200 ppm CO2
concentration; Koskela et al., 2014) on subjective ratings was small and no effect on task
performance was observed. Theoretically, it is interesting to study how the effects of
these three factors add up when the conditions are presented jointly. For example, it is
possible that the detrimental effects of the individual conditions are exacerbated when
combined. Because IE problems are often multifaceted in workplaces, the simultaneous
evaluation of these factors is also important for its practical significance. As far as we
know, no experimental studies exist that have investigated the simultaneous exposure to
the intelligibility of irrelevant speech, room temperature and air quality (ventilation
rate) and the related effects on cognitive performance and subjective experience in an
open-plan office. A variety of tasks was used to tap into the job-related cognitive
processes required in typical office work (non-communicative tasks). Because subjective
assessment has proved to be sensitive to capture the effects of IE, an extensive battery
of questionnaires was also employed. The aim of this experiment was to investigate the
simultaneous exposure to highly intelligible irrelevant speech, high room temperature and
low ventilation rate and the effects of exposure on cognitive performance and
environmental satisfaction. The study was carried out in open-plan office which was built
in a laboratory environment. Two experimental conditions were investigated. Condition A
was a combination of neutral temperature (23.5 °C), high outdoor air supply rate (30 l/s
per person, 580 ppm CO2) and low intelligibility of surrounding irrelevant speech (high
absorption and adequate masking in the room). Condition B was a combination of high room
temperature (29.5 °C), highly intelligible irrelevant speech (no absorption or masking in
the room) and a very low outdoor air supply rate (2 l/s per person, 1470 ppm CO2). The
hypothesis was that Condition B would be inferior to Condition A with respect to the
various subjective and objective measures used.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Sixty-five students (49 women and 16 men) from six faculties of the University of Turku
took part in the laboratory experiment. The participants were 19–29 years old (M = 23, SD
= 2) and were all native Finnish speakers. Each participant took part in the two
conditions on two successive weeks. None of the participants reported any hearing
difficulties, dyslexia or an attention deficit disorder and all had normal or corrected-
to-normal vision. Participants were recruited via university email lists and were paid 50
euros (minus taxes) for their participation. Prior to the experiment, the participants
were told that the aim of the experiment was to investigate work performance in an open-
plan office environment. The participants were not informed beforehand about the
experimental conditions.

<hs>  Design</hs>
  ~~~~~~

The experiment was carried out using a within-participants design, i.e., all participants
were tested in both experimental conditions (two sessions), thus acting as their own
controls. The within-participants variable was an indoor environment (IE) which had two
conditions. The order of exposure to these experimental conditions was counterbalanced
across participants in altogether thirteen groups. Half of the participants were first
exposed to Condition A (32 participants) and the other half to Condition B (33
participants).

<hs>  Test environment</hs>
  ~~~~~~~~~~~~~~~~

The experiment was carried out in an open-plan office specially built for the purpose
(Fig. 2). The room was carefully furnished and finished to resemble a normal work
environment. The room was free from measurement apparatus usually found in laboratories.
There were no measurement devices or other artificial artefacts visible in the room. The
furniture and materials visible in the room were modern and commercially available. The
furniture consisted of 12 identical desks, 1.3 m high screens between the desks, chairs,
computers and storage units in the middle of the room. Six desks were reserved for the
participants. The corner desks were reserved for the loudspeakers from which the
background speech was played. Two desks were empty during the experiment. The height of
the suspended ceiling was 2.55 m and suspension depth was 0.30 m. The suspended ceiling
was made of 600 × 600 mm metal grid where 210 ceiling boards, six ventilation inlets, a
ventilation outlet and 16 lighting units were installed. Approximately 88% of the ceiling
(75 m2) was reserved for ceiling boards where either sound-absorbing (Condition A) or the
non-sound-absorbing (Condition B) boards could be installed. Both boards had the same
visual appearance so that the participants could not detect any differences between them.
The walls were made of double drywall to provide good sound insulation to the surrounding
office premises. Approximately 20% of the total wall area (18 m2) was reserved for porous
linen pictures behind which sound-absorbing boards could be installed in Condition A.
Artificial masking sound was produced from 14 loudspeakers placed evenly above the
suspended ceiling so that the participants could not see them and the masking sound was
most probably experienced as ventilation noise. The temperature and ventilation of the
room could be controlled by an independent air-conditioning system. The air leakages in
the room and ventilation ducts were minimized. Natural daylight had no access to the room.
Two artificial windows were installed on one wall behind which lighting units were
installed to resemble daylight. The illumination level of this artificial daylight was
negligible in the desk area.

<hs>  The experimental conditions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The two experimental conditions were designed on the basis of our previous laboratory
experiments focussing on single IE factors (Haapakangas et al., 2014; Koskela et al.,
2014; Maula et al., 2015). The experimental conditions are described in Table 1. In
Condition A, the IE was designed according to the most stringent target values used in
open-plan offices in Finland (Class S2 of LVI 05–10440 en, 2008). In Condition B, the IE
was designed to violate even the least demanding target values (Class S3 of LVI 05–10440
en, 2008). A neutral temperature has been found to be 23.5 °C in a study (Maula et al.,
2015) similar to our study. This is very typical in office workplaces throughout the year
in buildings equipped with modern air conditioning systems. Elevated temperatures up to 30
°C are, however, found during the summer season in many workplaces situated in buildings
where cooling has not been installed. The temperatures in Conditions A and B were 23.5 and
29.5 °C, respectively, as used by Maula et al. (2015). Air quality in office-type
buildings, where the occupants are the main pollutant sources, is usually determined by
measuring the CO2 concentration. Concentrations up to 2500 ppm have been reported in
office buildings (Seppänen, Fisk, & Mendell, 1999). Concentrations exceeding 3000 ppm and
even up to 5000 ppm have been found, for example, in schools and meeting rooms with an
insufficient ventilation rate and high crowdedness (Bakó-Biró, Clements-Croome, Kochhar,
Awbi, & Williams, 2012; Seppänen et al., 1999). In large modern office buildings, the
concentrations are normally below 1000 ppm (Apte, Fisk, & Daisey, 2000). The recommended
upper limit for the CO2 concentration in offices is 1200 ppm in the lowest quality class
S3 (LVI 05–10440 en, 2008). In quality classes S1 and S2, the recommendations are 750 ppm
and 900 ppm, respectively. Values below 650 ppm are usual in modern Finnish offices.
Condition A (580 ppm) conformed to this recommendation. Ventilation rate (30 l/s per
person) was selected to certainly meet recommendations but not cause noise or the risk of
draught. For Condition B, a CO2 concentration of 1470 ppm was applied. It should be noted
that in the desk areas of open-plan offices, values exceeding 1500 ppm are rare.
Ventilation rate for Condition B (2 l/s per person) was determined by ASHRAE standard 62.1
where the minimum ventilation rate is 2.5 l/s per person based on adapted persons. Room
acoustics in Condition A corresponded to the most stringent requirements (Bradley, 2003;
Hardy, 1957; LVI 05–10440 en, 2008; Virjonen et al., 2009). Speech intelligibility is
reasonably high close to a speaker to enable normal face-to-face conversation but it
declines fast with increasing distance resulting in low intelligibility of distant speech.
Condition B corresponded to a situation where the room acoustic design does not conform
even to the least demanding target values. This is nevertheless very typical in workplaces
even though the room acoustic design principles have been published 57 years ago (Hardy,
1957). Speech intelligibility is very high both at short and large distances from the
speaker so speech is expected to be disturbing independent of the distance of the speaker.
The sound levels of background speech (the supposedly disturbing sound) and masking sound
(the supposedly non-disturbing sound) in the desks are depicted more closely in Fig. 3.
The lighting level at the table was constant, approximately 500 lux, in both conditions.
The air velocity was less than 0.1 m/s in all desks and in both conditions.

<hs>  Implementation of thermal control and ventilation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The room temperature was controlled by six commercially available chilled beams in the
ceiling and six electric radiators (total thermal power 5.5 kW) hidden below the tables of
the unoccupied desks. The intake air was filtered with level F7 filters. Radiators were on
during Condition B and chilled beams were used in Condition A. The room temperature was
measured continuously in the corner desks (not visible to the participants) at a height of
1.1 m. Prior to the experiment, the implementation of thermal conditions in the desks
(temperatures and draught) was also tested by installing six dummy bodies (60 W thermal
load) at the desks. Based on this, it was deemed sufficient to monitor the temperatures
during the experiment only at the corner desks. During Condition A, the CO2 concentration
was planned to be low by means of high outdoor air supply. During Condition B, the desired
CO2 concentration was planned to be high. Therefore, the rate of outdoor air supply was
minimized by using a circulation duct in the technical room. To implement the poor air
quality, eight employees worked in the office with this reduced ventilation rate for two
hours to increase the CO2 concentration up to 1470 ppm before the participants arrived. By
doing so, the human-based pollution rate (both CO2 and other human-based pollutants) was
at the intended level right at the beginning of the experiment and the participants
maintained the same pollution rate thereafter. There were typically six participants and
the experimenter in the room at a time but the number of persons varied from four to seven
because of occasional cancellations. The thermal load was compensated accordingly and
temperature variation between sessions and within a session was negligible. However, the
ventilation rate was not changed according to the number of persons present in the room
resulting in some variation of CO2 concentration between sessions (see Table 1). The
participants were instructed to wear trousers, long-sleeve shirt, t-shirt, socks and
angle-length shoes. The estimated clothing insulation including office chair was 0.83 clo
(ISO 7730) in both conditions. The participants’ main activity was typing and the
estimated activity level was 1.1 met. According to the PMV-model, the temperatures 23.5 °C
and 29.5 °C are estimated to be neutral and slightly warm, respectively (Maula et al.,
2015).

<hs>  Production of irrelevant speech and masking sounds</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Speech was used as the sound source in both Condition A and B. Four loudspeakers in the
four corner desks were used to simulate a situation where four persons would be talking on
the phone one after the other about different topics so that a different plot was ongoing
in each corner of the room (Figs. 2 and 4). In most previous experiments investigating the
effects of speech on task performance, the speech levels have been manipulated
electronically. Our experiment did not contain electronic manipulation of speech levels to
demonstrate the effects of two extremely different room acoustic conditions in such way
which could also be implemented in real open-plan offices. The sound power level of speech
emerging from the loudspeakers was constant in both conditions. The speech heard by the
participants depended solely on the room acoustic treatment of the room, i.e., the changes
in the amount of room absorption materials and the level of masking sound (see Chapter
2.7). A four-channel sound file (wav file, 44.1 kHz) was used to produce the speech to
four loudspeakers (Fig. 4). Only one corner speaker was active at a time. The speech was
obtained from four radio programmes bought from YLE (The Finnish Broadcasting Company).
The speech for each loudspeaker originated from a different radio programme so that the
topic in each corner was different. In each programme, four participants (politicians,
celebrities or specialists) were discussing a topic of common interest. The speech of each
participant in each programme was isolated from the programme and placed to one channel of
the four-channel sound file. The speech material of the speaker in each channel was
thereafter edited so that the speech consisted of separate 5-to-25-s-long tokens. The
four-channel speech file was then expanded and arranged so that there was no overlap
between the channels. The order of the speakers was pseudo-randomized but the total amount
of speech from every speaker was equalized. A silent period of 1–8 s was inserted between
speech tokens. The sound level of each speech token was adjusted to the same A-weighted
level. The editing was done using audio editing software (Adobe Audition 3.0). In
addition, the spectrum of each speaker was modified so that the octave band spectrum shape
deviated from the speech spectrum of ISO 3382-3 by less than 3 dB. The lengths of the two
four-channel recordings used in the experiment were approximately 180 min. Two versions of
speech recordings were created and counterbalanced across conditions. The versions
included different topics and speakers. The loudspeakers having mouth-like directivity
were used (Genelec 6010). The height was 1.2 m from the floor. The speakers were directed
to the centre of the room. The participants could see the loudspeakers when they entered
the room but the speakers were not visible while working. The sound power level of the
speech was constant and equal between every channel. This was checked out by full-time
sound power level measurements of each channel in a reverberant room according to ISO
3741. The speech level (effort) was set between normal and casual. The A-weighted mean
level over all directions was 53.0 dB at 1 m distance in a free field (normal effort is
57.4 dB). The linear sound power levels (LW re 1 pW) were 51.3, 55.3, 53.6, 44.6, 38.9,
32.2 and 29.4 in octave bands 125, 250, 500, 1000, 2000, 4000 and 8000 Hz, respectively.
The overall level of masking sound was 9 dB higher in Condition A than Condition B.
However, the spectrum shape of the masking was constant and close to Brownian noise in
octave bands 125–4000 Hz (Fig. 5) both in Condition A and B. This spectrum has been found
adequate both in workplaces and in laboratory conditions (Hongisto, 2008; Hongisto et al.,
2012, 2014). The difference in masking levels between the desks was negligible (±1 dB)
because of the smooth distribution of masking loudspeakers.

<hs>  Implementation of room acoustic conditions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In Condition A, sound-absorbing boards (EN 11654:1997; class A, 20 mm mineral wool) were
installed to the whole ceiling (75 m2). Sound-absorbing absorbers (EN 11654:1997; class A)
were installed behind the porous linen wall pictures (18 m2). The materials had the
highest available M1 classification so that the emission levels of various compounds were
very low. The overall room absorption area including the furniture was very large,
altogether 123 m2. The artificial masking system was set on so that the mean level in the
desks was 45 dB (LAeq). As a result of efficient sound masking and high room absorption
area, the intelligibility of the speech was moderate when the speech was originating from
the nearest desk (2 m away) and reasonably low when speech was originating from a desk
further away (6 m, see Fig. 2 and Appendix). It must be noted that the speaker producing
the speech was changed every 6–33 s. Therefore, the STI of speech varied with time and the
variation is indicated in Table 1. In Condition B, sound reflecting ceiling boards were
installed (EN 11654; unclassified, plasterboard). The sound-absorbing boards were removed
behind the linen wall pictures (EN 11654; unclassified). The overall room absorption area
was very small mainly caused by furniture, altogether 30 m2. Ventilation sound was planned
to be the only masking sound. However, the artificial masking sound was played at a level
of 33 dB (LAeq) to reach the same masking level in all desks since the ventilation level
varied from 33 to 36 dB between desks. The final masking level was reasonably low (36 dB)
and the resulting masking efficiency was negligible as desired. As a result of the
inefficient sound masking level and negligible room absorption area, the STI value of
speech was very high and almost independent on the distance to the speaker (see Appendix).
Neither the screen height nor the screen absorption was modified between Conditions A and
B. The screen height was 130 cm and the screens were not sound-absorbing (EN 11654;
unclassified). The room acoustic conditions were measured according to ISO 3382-3 (See
Appendix).

<hs>  Cognitive tasks</hs>
  ~~~~~~~~~~~~~~~

Six cognitive tasks were used: a serial recall task, an operation span task, an N-back
task, an information search task, a typing task and a story-writing task. The tasks
mimicked the cognitive processes required in many types of office work. All tasks rely on
several cognitive processes, but only the main processes that are typically related to
these tasks in the literature are mentioned in the description of the tasks. This does not
exclude the possibility that cognitive processes that are not typically associated with
the particular task type may also have some effect on the performance of these tasks
(Sörqvist, 2014). The serial recall task, the operation span task and the information
search task were programmed with Visual Basic 6 (Microsoft) and the N-back task with
E-Prime 2.0 (Psychology Software Tools Inc.). The serial recall task is a classic short-
term memory task where participants have to recall randomly presented digits from 1 to 9
in the correct presentation order. Numbers were presented on the screen one by one at the
rate of 1 per second with an inter-digit interval of 1.5 s. During recall, the numbers 1
to 9 appeared in a 3 × 3 array on the screen and participants responded by clicking with
the mouse the numbers in the recalled order. Participants were instructed to guess or
press ‘empty’ in case they did not know the correct answer in a certain serial position.
After each trial, participants had 15 s to respond, after which a new trial began. A total
of 12 trials were presented but the first two were excluded from the analysis. The main
dependent variable was the percentage of digits recalled in the correct serial position.
The task took about 7 min to complete. The operation span task is another highly used
working memory task. The version used in our study is based on the original operation span
task developed by Turner and Engle (1989). The task consisted of mathematical equation-
word pairs, such as 3 × 3 + 7 = 22 and ‘BOOK’. First, an equation appeared on the computer
screen. Participants had 10 s to decide whether the presented equation was true or false
by clicking the appropriate option on the computer screen. After each equation, a word
appeared on the screen and participants had 2 s to memorize the word. Then the next
equation and word were presented. After a predetermined number of equation-word pairs was
presented (the number of presented equation-word pairs increased gradually from three to
eight), participants typed in all the words they remembered. Small misspellings were
allowed and the precise order of recalled words was not required. In this task, the
function of the arithmetic task is to interfere with memorizing the words. To ensure that
participants focused on both equations and words, participants were instructed to get at
least 85% of responses to equations correct. Participants received feedback on this after
typing each word list. The materials used for words and equations are described in detail
in Haka et al. (2009). Two matched versions of the task were constructed and
counterbalanced between the conditions and sessions. Within each version, equations and
words were presented randomly. The main dependent variable was the percentage of correctly
remembered words. The task took about 12 min to complete. The N-back task (Gray, Chabris,
& Braver, 2003) requires working memory and the ability to sustain attention. In this
task, sequences of letters were presented on the screen one by one, each for 500 ms with a
2500 ms inter-stimulus-interval. Three difficulty levels were used (0-back, 1-back and
2-back). In 0-back, the participant's task was to press YES every time the letter ‘X’
appeared on the screen and press NO for all other letters. This is the baseline condition
not taxing working memory. In 1-back, participants were required to respond whether the
presented letter was identical to the one immediately preceding it. In 2-back,
participants were required to response whether the presented letter was identical to the
one presented two trials back. Participants were instructed to respond quickly, but
accurately. Answers were given by pressing a key on the keyboard labelled YES (leftwards
arrow) or NO (downwards arrow). Each set (0-, 1- and 2-back) included 30 + n letters (n =
0, 1 or 2) in a pseudorandom order. One set included 9 letters requiring a ‘YES’ response
(30%). Upper and lower case letters were varied requiring participants to use abstract
letter codes and preventing them from relying only on visual letter feature. The whole
task included three blocks containing one set of each difficulty level, i.e., each
difficulty level appeared three times during the task. The materials and the order of the
difficulty levels were counterbalanced across the test blocks and participants. Six
matching versions of the task were constructed and counterbalanced across the conditions
and sessions. The main dependent variables were response accuracy (%) and reaction time of
the correct responses (in ms). Reaction times deviating over 2.5 SD from the participant's
mean were excluded. The reliability of the reaction time measurement was based on Maula et
al. (2015). The task took about 20 min to complete. The information search task (Jahncke &
Halin, 2012) requires working memory, attention and strategic executive functions. The
task bears similarity to a problem-solving task. In this task, a table of 20 rows and
seven columns was presented on the screen. In each row, an object was presented (e.g., a
country) and each column described one aspect of the object (population, multilinguality,
area, highest point in metres, major religion, etc.). In the descriptions, both
categorical and numerical values were given. Participants were required to search for the
object that met the presented criterion (see below for examples). Participants had a
maximum of 60 s to respond, after which the next question appeared. The questions had the
same grammatical structure. Altogether, four tables were used, two for both sessions. The
task included 20 questions, 10 questions concerning the first table and 10 questions
concerning the second table. Half of the questions were simple and half of the questions
were difficult. In the case of difficult questions, the object could be nominated by
investigating three columns, one with categorical and two with numeric values (e.g.,
“Which country is multilingual, its highest point over sea level exceeds 1000 m, and has
the highest population?”). In the case of simple questions, participants had to follow two
columns, one with a categorical value and one with a numeric value (e.g., “Which employee
is a salesperson and has the highest annual income?”). Two matching task versions were
constructed and counterbalancing across the conditions and sessions was made in relation
to the task difficulty and the features of the objects and columns including categorical
and numeric values across the tables. The main dependent variables were the percentage of
total number of correct responses and the percentage of correct responses in simple and
difficult questions separately. The number of exceeded response time was also analysed.
The task took about 20 min to complete. The typing task is a routine task that requires
different sub-processes of perception, attention and motor functions (Rumelhart & Norman,
1982). In the task, participants had to copy a text presented on paper by typing it using
the computer keyboard. Participants were required to type quickly but avoid making
mistakes. Participants were instructed to correct any typing errors they made. The text
was a story (Juvonen, 2012a, 2012b) with a rich vocabulary and plot. The story printed on
paper was placed vertically on a slightly slanted rack for easy reading; the participants
were allowed to freely place the rack on the desk. Participants had 10 min to copy the
text. Two stories with similar writing style from the same writer were selected and
counterbalanced between the conditions and sessions. The number characters in the final
text, writing fluency, the number of corrected and uncorrected errors, and the total time
of pauses exceeding 2 s were analysed. Corrected errors refer to typing errors that a
participant made but corrected, whereas the errors that a participant did not correct were
labelled as uncorrected errors. There were no spelling errors in the original text that
was given to the participants. Writing fluency was operationalized as the total number of
characters produced during the given time (i.e., the sum of the number characters of the
final text and the total number of deleted characters; Sörqvist, Nöstl, & Halin, 2012).
The task was carried out and the data were collected using the ScriptLog program
(Strömqvist & Karlsson, 2002). The story-writing task requires psychomotor performance,
creativity and the ability to produce text in writing (Sörqvist et al., 2012). In the
task, a photograph was presented on the screen. Participants were required to write a
story about the scene depicted in the photograph. Participants were instructed to write
whatever came to mind from that picture. The presented photographs displayed two different
nature scenes (a forest road surrounded by green trees and a snowy mountain view with a
small cottage in the middle). Participants had 5 min to write the story and they were
instructed to write as much as possible but correct their typing mistakes. The presented
pictures were counterbalanced between the conditions and sessions. The ScriptLog program
(Strömqvist & Karlsson, 2002) was used to collect and analyse the data. The stories were
analysed both quantitatively and qualitatively. In the quantitative analysis, the same
variables as in the typing task were analysed. In the qualitative analysis, the quality of
the stories (atmosphere, the existence of negative turning point, the invocation of the
photograph and concreteness) was analysed by two raters. These factors were found adequate
for most stories written by the participants. Inter-rater reliability was assessed using
the overall percentage of agreement. Agreement varied between 53 and 94%.

<hs>  Questionnaires measuring subjective experience</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Five different questionnaires were created. Participants responded to the questionnaires
at the baseline phase (questionnaire A), at the beginning of the acclimatization phase
(questionnaire B, the first session or questionnaire E, the second session), before a
short break during the experimental phase (questionnaire C) and at the end of the session
(questionnaire D) (Fig. 6). In questionnaire A, background information including gender,
age, sleep during the preceding night, ability to function normally, noise sensitivity,
bodily symptoms and experienced level of tiredness and motivation were measured. Noise
sensitivity was measured with three items from Weinstein (1978) and with four items from
Noise-Q (Schutte, Marks, Wenning, & Griefahn, 2007). The intensity of the six symptoms was
measured (Table 3). Experienced cognitive fatigue were measured with a modified version of
the Swedish Occupational Fatigue Inventory (SOFI; Åhsberg, Gamberale, & Gustafsson, 1998;
Åhsberg, Gamberale, & Kjellberg, 1995) including three factors (tiredness, lack of energy
and motivation). Every factor included three items (tiredness: sleepy, yawning, drowsy;
lack of energy: worn out, exhausted, drained; lack of motivation: uninterested,
indifferent, passive). Questionnaire B included questions about experienced tiredness and
motivation, and symptoms, but also questions about overall thermal comfort, satisfaction
with temperature, draught and emotional reactions. Overall thermal comfort was measured
using a 7-point scale (1 = cold, 7 = hot). Emotional reactions were measured with the
modified version of the Zuckerman Inventory of Personal Reactions and Feelings (ZIPERS;
Zuckerman, 1977), including four factors (Fear/arousal, Positive affect, Anger/aggression
and Attentiveness) and one item measuring sadness (I feel sad). Fear/arousal was measured
with three items (My heart is beating fast; I feel fearful; I am breathing fast), Positive
affect with four items (I feel carefree; I feel gentle; I feel happy; I feel like I could
act friendly to someone), Anger/aggression with two items (I feel like hurting or telling
off someone; I feel angry), and Attentiveness with two items (Cronbach's alphas
0.53–0.89). Attentiveness is not reported in the results, as it overlaps in content with
one symptom item (Difficulties in concentration). Questionnaire C contained questions
about overall thermal comfort, satisfaction with temperature, draught, emotional
reactions, experienced tiredness and motivation, and symptoms but also included questions
of subjective workload. Subjective workload was measured with four items (mental demand,
frustration, effort and performance) which were modified from the NASA Task Load Index,
NASA-TLX (Hart & Staveland, 1988; Moroney, Biers, & Eggemeier, 1995). Workload questions
were included because subjective awareness of distraction may lead participants to invest
more effort in performance (Schlittmeier, Hellbrück, Thaden, & Vorländer, 2008).
Questionnaire D contained questions about overall thermal comfort, satisfaction with
temperature, draught, emotional reactions, experienced tiredness and motivation, symptoms
and subjective workload. In addition, this questionnaire included questions of local
thermal comfort (ten items), work effectiveness in a similar temperature (one item, Table
3), acoustic satisfaction, acoustic and visual privacy (three items, Table 3), experienced
disturbance due to different factors present in the work environment (17 items) and
subjective experience of the work environment (eight items). Acoustic satisfaction was
measured with five items (habituation, disturbance, pleasantness, attention capture, and
work efficiency in a similar sound environment). Items were combined to form a sum score
(henceforth called Acoustic satisfaction; Cronbach's alphas 0.82–0.90). The disturbance
caused by lightning, screen brightness and ergonomic conditions were also rated to rule
out possible effects due to these factors. Questionnaire E contained questions about
overall thermal comfort, satisfaction with temperature, draught, emotional reactions,
experienced tiredness and motivation, and symptoms. In addition, this questionnaire
included background information questions: the amount of sleep during the preceding night
and ability to function normally. All questionnaires were presented with an Internet-based
software (QuestBack, Finland), except for the thermal comfort questionnaire, which was
also presented on paper.

<hs>  Procedure</hs>
  ~~~~~~~~~

The experiment was conducted between February and April 2012. Participants took part in
the experimental sessions during two mornings on consecutive weeks. On the first morning,
participants were asked to arrive at the laboratory at 8.30 a.m. for the baseline phase.
The acclimatization and the experimental phase was carried out between 10.30 a.m. and
12.30 p.m. on both days. At the beginning of the first session, participants were given
written information about the experiment and they signed the informed consent form.
Participants were informed of the progress and the content of the test sessions, payment,
confidentiality and their right to interrupt their participation at any time. The
procedure is described in Fig. 6. The first session started with a baseline phase in
silence in a room near the experimental room. During the break after the baseline phase,
sandwiches and soft drinks were served in the hallway to ensure that the participants had
eaten breakfast prior to the rather long experimental session. During the acclimatization
phase, participants were acclimatized to the experimental condition and they practised the
cognitive tasks (30 min). Performance was not measured during the acclimatization phase.
Participants were unaware of the purpose of the acclimatization phase. The speech sounds
were off. When the experimental phase started, the experimenter switched on the speech.
Participants were instructed to ignore the sounds and to concentrate on the tasks. Before
every task, the experimenter shortly repeated the task instructions, after which the
participants performed the task at their own pace. A short break was given in the middle
of the experimental phase to give the participants an opportunity to visit the restroom
and drink water. During the break the speech was switched off. The temperature in the
hallway to the restroom and in the restroom was similar to that in the laboratory.
Conversation was not allowed during the experiment or the break. Prior to the beginning of
the second session in the next week, sandwiches and soft drinks were served in the
hallway. The acclimatization phase included questionnaire E and the revised versions of
each task excluding the typing task. The experimental phase was identical to the first
session. Participants were informed in detail about the aim of the study at the end of the
second session.

<hs>  Statistical methods</hs>
  ~~~~~~~~~~~~~~~~~~~

SPSS (IBM SPSS Statistics for Windows 20, IBM Corp, Armonk, NY) was used for the
statistical analyses. The normality of data was tested with the Kolmogorov–Smirnov test.
The serial recall, the operation span, the typing and the story-writing tasks were
analysed using repeated measures ANOVA with experimental condition (later: condition) as
the within-participants variable. The quality of the stories in the story-writing task was
analysed using Pearson's chi-squared test for independence. The N-back and information
search tasks were analysed with a 2 (condition) × 3 (difficulty level) repeated measures
ANOVA. A repeated measures ANOVA was also used for the questionnaire items that were
normally distributed or when distributions were similarly skewed. Subjective workload was
analysed with a 2 (condition) × 2 (exposure time: after one hour vs. after two hours)
repeated measures ANOVA. Experienced tiredness and motivation, and emotional reactions
were analysed with a 2 (condition) x 3 (exposure time: beginning, after one hour, after
two hours) repeated measures ANOVA. Whenever needed, the homogeneity of variance was
estimated with Mauchly's test of sphericity. When Mauchly's test indicated a violation of
sphericity, the Greenhouse-Geisser correction was applied and the corresponding p-values
are reported. When an interaction was found, paired comparisons between conditions were
performed using t-tests for the variables that were normally distributed or when
distributions were similarly skewed; otherwise the Wilcoxon signed-rank test was used. An
alpha level of 0.05 was used in all analyses. The Benjamini-Hochberg procedure (Benjamini
& Hochberg, 1995) was used for alpha-error adjustment in paired comparisons. In the N-back
task, the data were combined over the two blocks, because the main effects of the block
remained non-significant. One participant was excluded from the N-back analyses because of
a misunderstanding of the instructions. Unlike in typical studies of the operation span
task, participants who failed to achieve an 85% level on equation accuracy were not
excluded, because the independent variable (speech intelligibility) could also have
affected arithmetic performance (Jachnke et al., 2013; Schlittmeier et al., 2008).
Instead, multivariate outliers were checked using Mahalanobis distance for identifying
possible changes in performance strategy. As a result, one participant was excluded from
the analysis. In the story-writing task, one participant was excluded from the analysis
because he did not follow the instructions. The decrement in performance, D [%], was
defined as D = 100·(1 − PB/PA) where PB and PA are the performance levels in Condition B
and A, respectively. The results for the four items (mental demand, frustration, effort
and performance) measuring subjective workload yielded a main effect of condition for all
items and there were no interactions between exposure time and condition. Thus, the items
were combined to form a sum score (henceforth called Subjective workload; Cronbach's
alphas 0.66–0.77). During the experiment, the visual appearance of the office was also
investigated using a between-groups design with two groups. Thirty-one participants
experienced Conditions A and B in visual environment 1 and thirty-four participants in
visual environment 2. Because the visual appearance did not significantly affect the
objective or subjective results concerning the effect of condition, the groups were
combined. There was one exception: the self-rated impairment of performance due to thermal
conditions and air quality (heat, odours and stuffiness of the indoor air) was affected by
the visual appearance. Thus, only the other group was included in the analyses of these
variables (n = 31). For the remaining analyses, the participants from both groups were
included.

<hs>  Performance measures</hs>
  ~~~~~~~~~~~~~~~~~~~~

In the serial recall task, a significant main effect of condition was found for the
percentage of digits recalled in the correct serial position (F1,64 = 5.86, p = .018, η2 =
0.08; Fig. 7a). Performance was significantly better in Condition A (D = 6.7%). In the
operation span task, a significant main effect of condition was found for the percentage
of correctly recalled words (F1,63 = 10.84, p = .002, η2 = 0.15; Fig. 7b), with better
performance observed in Condition A (D = 4.0%). In the N-back task, a significant main
effect of condition was found for response accuracy (F1,63 = 4.01, p = .049, η2 = 0.06;
Fig. 7c). Significantly more correct responses were given in Condition A. However, the
performance decrement was negligible (D = 0.5%). There was no significant interaction
between difficulty level and condition. That is, the effect of condition on accuracy was
not affected by the difficulty level. Reaction times were not affected by condition nor
was there an interaction between difficulty level and condition. The performance in the
information search task was not affected by condition, neither by difficulty level (p >
.05). Moreover, there was no significant interaction between difficulty level and
condition (p > .05). In the typing task, a significant main effect of condition was found
for the total number of errors (F(1,64) = 4.03, p = .49, η2 = 0.06; Fig. 7d).
Significantly fewer errors were made in Condition A (D = 5.2%). This resulted primarily
from the number of uncorrected errors: there was a marginally significant difference in
the number of uncorrected errors (p = .05), but no difference in the number of corrected
errors (p > .05). None of the other variables measuring typing fluency were affected by
condition. The performance in the story-writing task was not affected by condition for any
measure (p > .05). The mean values with standard deviations for the task variables where
significant differences were not found (N-back, information search, typing and story-
writing) are presented in Table 2.

<hs>  Subjective responses</hs>
  ~~~~~~~~~~~~~~~~~~~~

The results for the subjective assessments of the working conditions are presented in Fig.
8. The ratings for the conditions for working as a whole were significantly more positive
in Condition A than B (Z = −5.97, p < .001). Similarly, the ratings of the possibility to
work effectively were significantly higher (Z = −4.66, p < .001) and ratings of the
riveting of the tasks were significantly more positive (Z = −2.18, p = .029) in Condition
A. There was a significant main effect of condition for the sum score of Subjective
workload (F1,64 = 15.02, p < .001, η2 = 0.19; Fig. 9a). Subjective workload was rated to
be significantly lower in Condition A. The effect of condition on Subjective workload was
not affected by exposure time, as indexed by a non-significant interaction between
exposure time and condition. Acoustic satisfaction was significantly lower in Condition B
(Z = −4.82, p < .001; Fig. 9b). The subjective assessments of the distraction of
performance due to different sounds are presented in Fig. 10. Speech distracted
significantly more in Condition B. Speech was more distracting both from nearby desks (Z =
−2.95, p = .003) and desks from further away (Z = −5.53, p < .001). Moreover, speech from
nearby distances was more distracting than speech from further away both in Condition B (Z
= −5.20, p < .001) and in Condition A (Z = −6.29, p < .001). Similarly, a significant
effect of condition was found for the distraction due to the sounds of computer tapping (Z
= −2.22, p = .026) and other sounds made by other participants (Z = −2.68, p = .007). The
distraction of the hum of ventilation, i.e., masking sound, was significantly higher in
Condition A (Z = −4.70, p < .001). However, it should be noted that speech either from
nearby desks (Z = −5.42, p < .001) or desks from further away (p = .06) distracted
significantly more than the hum of ventilation in Condition A. That is, speech was the
main acoustic distractor in both experimental conditions. Overall thermal comfort differed
between conditions: participants felt warmer at the end of the exposure time in Condition
B (Z = −7.00, p < .001); the difference between conditions was observed during the whole
exposure time (p < .001). Using the 7-point scale of thermal comfort, participants felt
warm (M = 6.3, SD = 0.7) at 29.5 °C and neutral (M = 3.6, SD = 0.9) at 23.5 °C after the
second exposure hour (Z = −7.00, p < .001). A similar result was found for both local and
overall thermal comfort during the whole exposure time (p < .001). The impairment of
performance due to thermal factors is presented in Fig. 11. Overall, working efficiency
was assessed to be significantly higher in Condition A (Z = −6.5, p < .001; Table 3). Heat
was rated to interfere with performance significantly more in Condition B (Z = −4.60, p <
.001), whereas cold (Z = −2.20, p = .028) and draught (Z = −2.08, p = .037) interfered
significantly more in Condition A. However, the mean ratings of cold and draught were very
low in both conditions. Self-rated air quality differed between conditions as expected
(Fig. 11). Stuffiness of the indoor air (Z = −3.71, p < .001) interfered with self-rated
performance significantly more in Condition B. No impairment caused by odours was reported
in either condition. Condition also affected the perception of acoustic and visual privacy
(Table 3). Participants would have preferred more screens around the desk in Condition A
in order to make working more pleasant (Z = −2.20, p = .028). The distraction caused by
other people and closeness of nearby desks did not differ between experimental conditions
(p > .05). There was a significant main effect of condition for the perceived tiredness
(F1,64 = 10.40, p = .002, η2 = 0.14), the lack of energy (F1,64 = 20.18, p < .001, η2 =
0.24) and the lack of motivation (F1,64 = 20.55, p < .001, η2 = 0.24; Fig. 12).
Participants were more tired and the lack of energy and motivation was higher in Condition
B. There was also a significant interaction between the exposure time and condition in the
lack of energy (F2,128 = 9.62, p < .001, η2 = 0.13) and motivation (F2,128 = 9.56, p <
.001, η2 = 0.13). Paired comparisons revealed that the lack of energy was significantly
higher in Condition B in the beginning phase (t(64) = 7.05, p < .001, two-tailed) and
after the first (t(64) = −3.68, p < .001, two-tailed) and the second (t(64) = −4.98, p <
.001, two-tailed) exposure hour. There was no significant difference in the lack of
motivation between the conditions in the beginning phase but the lack of motivation was
significantly higher in Condition B after the first (t(64) = −3.10, p = .004, two-tailed)
and the second (t(64) = −4.90, p < .001, two-tailed) exposure hour. In Condition B, an
increase in the lack of energy (t(64) = 2.65, p = .013, two-tailed) and motivation (t(64)
= 2.28, p = .033, two-tailed) was observed already between the beginning phase and the
first exposure hour. The lack of energy (t(64) = 6.39, p < .001, two-tailed) and
motivation (t(64) = 5.57, p < .001, two-tailed) continued to increase, being significantly
higher after two hours of exposure compared to one hour of exposure. In Condition A, no
significant difference in the lack of energy and motivation was found between the
beginning phase and the first exposure hour, but the lack of energy (t(64) = 4.50, p <
.001, two-tailed) and motivation (t(64) = 3.60, p = .001, two-tailed) increased
significantly between the first and the second exposure hour. Regarding emotional
reactions (Table 3), there was a significant main effect of condition for Positive affect
(F1,64 = 4.18, p = .045, η2 = 0.06; Fig. 13) with higher values in Condition A. There was
also a significant interaction between condition and exposure time (F2,116 = 4.15, p =
.022, η2 = 0.06). Paired comparisons revealed that there was no significant difference
between the conditions in the beginning phase or after the first exposure hour but
Positive affect was stronger in Condition A after two hours of exposure (t(64) = −3.80, p
< .001, two-tailed). In Condition B, Positive affect decreased significantly during the
whole exposure time (p < .001) and difference was found between the beginning phase and
the first exposure hour (t(64) = 4.10, p < .001, two-tailed) and between the first and the
second exposure hour (t(64) = 3.86, p < .001, two-tailed). In Condition A, Positive affect
decreased significantly between the beginning phase and the first exposure hour (t(64) =
3.33, p = .002, two-tailed) but no significant difference was found later between the
first and the second exposure hour (p > .05). The ratings of Sadness, Fear/arousal and
Anger/aggression remained low during the sessions. However, there was a main effect of
condition on sadness (F1,64 = 6.13, p = .016, η2 = 0.09) with higher ratings in Condition
B. There was also a marginal main effect of condition on Fear/arousal (F1,64 = 3.98, p =
.05, η2 = 0.06). Participants reported higher Fear/arousal ratings in Condition B.
Anger/aggression was not affected by condition. There was no significant interaction
between condition and exposure time in these ratings. Different physiological symptoms
(Table 3) were enquired on a scale from 1 (Not at all) to 5 (Very much). On the whole, the
intensity of symptoms was very mild. Thus, a rating of 2 (Slightly) or higher was
interpreted to indicate the existence of a symptom. The self-reported prevalence of
different symptoms at the end of the experiment is shown in Fig. 14. Participants reported
more feelings of being unwell in Condition B than in Condition A after the first (Z =
−2.74, p = .009) and second (Z = −3.83, p < .001) hour of exposure. Symptoms increased
with exposure time in Condition B (p < .05) but not in Condition A. The assessments of
headache and nasal, throat and eye symptoms remained low in both conditions (Fig. 14), but
the symptoms increased toward the end. Participants reported more headaches at the end of
the session in Condition B than in Condition A (Z = −2.43, p = .030). No significant
differences were found for other exposure times (p > .05). In addition, more throat
symptoms were reported in Condition B after the first (Z = −2.20, p = .033) and the second
(Z = −2.29, p = .033) hour of exposure compared with Condition A. Headache and throat
symptoms also increased with exposure time in Condition B (p < .05) but not in Condition
A. Ratings of nasal symptoms decreased during the first exposure hour compared to the
beginning phase in Condition A (p < .01), but not in Condition B. However, a difference
was not observed between the conditions (p > .05). Ratings of eye symptoms increased
during the second exposure hour compared to the beginning phase in Condition B (p < .05).
No significant changes were perceived in Condition A. However, no difference was observed
between the conditions (p > .05). Difficulties in concentration were higher in Condition
B; the experimental conditions differed both after the first (Z = −2.10, p = .046) and
second (Z = −3.03, p = .004) exposure hour.

<h>DISCUSSION</h>
----------

The aim of our study was to investigate the simultaneous exposure to highly intelligible
irrelevant speech, high temperature and low ventilation rate and the effects of exposure
on cognitive performance and environmental satisfaction in an open-plan office laboratory.
As hypothesized, Condition B had detrimental effects on both cognitive performance and
subjective experience. Condition A was perceived to be a better condition for office work.

<hs>  Cognitive performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~

The results established negative effects of Condition B on cognitive performance. An
effect was observed in the percentage of correct answers and in typing errors. In the
serial recall and the operation span tasks performance was worse in Condition B in
comparison to Condition A. Participants also made more errors in typing when working in
Condition B. Thus, Condition B proved to be poor IE for working. The results from the
single IE factors of prior experiments (see Fig. 1) are conceivable to reflect with our
study where simultaneous exposure was used. Highly intelligible irrelevant speech reduced
performance and interfered with the operation of working memory (Haapakangas et al.,
2014). Similarly, high temperature reduced working memory performance (Maula et al.,
2015). Instead, low ventilation rate did not have consistently effects on cognitive
performance (Koskela et al., 2014). Based on previous findings concerning single factors,
high speech intelligibility and high temperature decreased performance the most. The
results of our study expound that simultaneous exposure to high speech intelligibility,
high temperature and low ventilation rate decrease performance. Despite of the findings of
Koskela et al. (2014), the self-rated distraction of work performance caused by the
stuffiness of the indoor air, heat (Fig. 11) and speech from further away and nearby desks
(Fig. 10) received higher ratings in Condition B in our study. Taking our experimental
design into account, where the effects of individual factors were not investigated, we can
only conclude that high speech intelligibility, high temperature and low ventilation rate
may have together affected the performance results through subjective responses in our
study. As pointed out above, performance differences were clearly found in the working
memory tasks employed in our study. Regarding the N-back task, it is noteworthy that
accuracy decreased in Condition B in comparison to Condition A, but the reaction times did
not. Thus, response speed was maintained at a cost of more erroneous responses. This
result is inconsistent with the speed-accuracy trade-off hypothesis (Hockey, 1984), which
suggests that in noisy environments responses are given faster but with less accuracy. The
reason may be that Hockey's experiment was conducted with pseudorandom noise instead of
speech. The results of the N-back task shall be compared with the prior studies conducted
in the same laboratory. Similar background speech (Haapakangas et al., 2014) did not
decrease the accuracy in the N-back task when three difficulty levels (0, 1 and 2) were
applied as in our study. However, an effect on accuracy was observed when four difficulty
levels (0, 1, 2 and 3) were used in high temperature (Maula et al., 2015). Taken together,
it appears that simultaneous exposure to three IE factors in Condition B exacerbated
somewhat the performance decrement in the N-back task compared with that was observed with
similar single factor manipulation alone. In the typing task, fewer typing errors were
made in the better IE. In previous studies (Park & Yoon, 2011; Wargocki et al., 1999,
2000) the number of typed characters has been found to decrease with high material
emissions in a similar text typing task while no significant difference has been observed
in typing errors. On the other hand, Koskela et al. (2014; Fig. 1) obtained no effect of
air quality on typing performance in a study conducted in the same laboratory as our
study. A possible reason for this discrepancy in results is the fact that in our study not
only ventilation rate but also thermal and acoustic conditions were manipulated. In other
words, a set of poor IE conditions may need to be combined together to have an effect.
Yet, methodological differences in manipulating air quality (human vs. material emission)
and differences in task duration (10 min vs. nearly one hour) may also have contributed to
the discrepancy. In the story-writing task, participants had to produce a new text instead
of copying an existing text. Story-writing was not affected by the experimental condition.
Keus van de Poll et al. (2014) observed a detrimental effect of irrelevant speech on
writing fluency and pauses in story-writing with STI values below 0.34. Processing of
semantically meaningful speech was assumed to interfere with writing performance. It
should be noted that in our study the STI values in both experimental conditions exceeded
the value of 0.34 and the effect obtained by Keus van de Poll et al. could not be
confirmed. The information search task was not affected by the experimental condition.
This is consistent with the study of Jahncke et al. (2013) who also observed no effect of
speech intelligibility level on information search. It must be noted that neither Jahncke
et al. nor our study included a silent condition (or STI 0.00) as a reference to different
speech conditions so it cannot be concluded that speech does not affect performance in
this task. However, the selected set of IE conditions in our study did not reveal any
effect. It would be useful to investigate in the future whether this task is affected by
speech or other IE conditions, because the task represents normal office work better than
many other tasks normally used in experiments like this. Working memory has a central role
in the tasks employed in our study. However, because cognitive performance relies on
several cognitive processes, it is difficult to identify all processes that may have been
interfered by indoor environmental factors. In the area of noise-related performance
effects, one suggestion is that the effects of noise on performance result from
attentional capture rather than the impairment of other cognitive processes (Sörqvist,
2014). Attentional capture is caused by a sudden auditory change which draws attention
from the task to the deviant event (Hughes, Vachon, & Jones, 2007). The effect of
attentional capture is assumed to be more detrimental to performance when the task
difficulty increases. In our study, the level of task difficulty varied between the tasks.
Thus, one possible reason why the effects of conditions were not found in all tasks might
be the variation in task difficulty. Because there were also other adverse factors than
auditory ones, we suggest that the results cannot be explained purely by attentional
capture hypothesis. Moreover, high temperature has been related with increased stress
which activates attentional resources to cope with stress (Hancock et al., 2007). This has
been shown to lead to a situation where the capacity to process task-relevant information
is reduced (Hancock et al., 2007). Thus, all environmental factors should be observed
together with the impairment of other cognitive processes when the results are
interpreted. Practical limitations of room acoustic design should also be considered when
interpreting the overall effect of acoustic design on cognitive performance. Haapakangas
et al. (2014) demonstrated that room acoustic design affects task performance and acoustic
satisfaction but acoustic design has an effect only on speakers located at least 3–5 m
from the listener. Nearby speech is difficult to control by room acoustic means. Our study
confirms this finding. In our study and that of Haapakangas et al. (2014), speech
intelligibility was temporally variable, because the location of the active speaker in the
room varied every 6–33 s, and the distance between the speaker and the participant varied
respectively. Thus, speaker's direction and distance was not constant. In both
experimental conditions, task performance might have momentarily deteriorated when speech
was heard from nearby desks. However, as task performance was overall better in Condition
A, it may be assumed that performance was not adversely affected by speech when the
speaker was far away from the participant. On the other hand, in Condition B speech was
intelligible regardless of the location of the speech source. This probably explains the
observed differences in working memory performance between the two experimental
conditions. In many previous studies silence and highly intelligible speech has been
compared to each other (Hongisto, 2005). If the high speech intelligibility condition,
Condition B, would have been compared to silence, differences in performance would
probably have been more evident. However, our study involves a realistic open-plan office
environment where silence is not expected to exist for very long periods of time.
Therefore, it is argued that the methodologies and the findings of this experiment have
better practical relevance than most previous studies except that of Haapakangas et al.
(2014).

<hs>  Subjective responses</hs>
  ~~~~~~~~~~~~~~~~~~~~

The working conditions were assessed to be significantly better in Condition A than in
Condition B. On the one hand, the subjective measures support the findings on performance
measures discussed above. On the other hand, they demonstrate even more pervasive effects
than performance measures. This is in line with previous studies demonstrating that
subjective measures are more sensitive to changes in IE than objective measures
(Haapakangas et al., 2011, 2014; Schlittmeier et al., 2008). In addition, despite whether
or not the open-plan office conditions are objectively measured as adequate, subjective
experiences have an effect on what kind of meaning the occupant will give to the positive
and negative characteristics of IE (Cox & Ferguson, 1994; Lahtinen, Huuhtanen, Kähkönen, &
Reijula, 2002).

        <hss>Room acoustics</hss>

        When the acoustic environment was properly designed (Condition A), acoustic
        satisfaction was higher and distraction from different sounds smaller. This result
        was found even though the overall noise level was higher in Condition A due to the
        masking sound. In both experimental conditions, the most distracting sound was
        speech from nearby desks. Distraction by masking sound was measured by an item
        called “hum of ventilation” since the masking sound resembles the hum of
        ventilation. This was justified because the concept of sound masking is unknown
        among the general population. Even though the hum of ventilation (i.e., the
        masking sound) was perceived as more distracting in Condition A, the masking sound
        was more beneficial than harmful, since the most distracting sound, i.e., speech,
        was assessed significantly less disturbing in Condition A. Moreover, speech coming
        even from a distant location was rated more distracting than the hum of
        ventilation. Thus, it is evident from these data that speech was the main acoustic
        distractor. The findings are in agreement with previous studies (Haapakangas et
        al., 2011, 2014; Haka et al., 2009).

        <hss>Thermal conditions and air quality</hss>

        Stuffiness of the indoor air was rated as more interfering in Condition B. In the
        previous study (see Fig. 1), Koskela et al. (2014) did not find any significant
        change in experienced stuffiness when ventilation rate was reduced from 28
        l/s·person (600 ppm CO2) to 2 l/s·person (2200 ppm CO2) while the room temperature
        was kept constant (23.5 °C). Instead, a significant change in stuffiness was
        observed by Maula et al. (2015) when high room temperature was compared with
        neutral temperature. This supports the previous result that when an individual
        feels warm in a room, air quality is also assessed to be poor (Lan et al., 2011).
        Based on previous results, it can be suggested that room temperature had a
        significant role in increased stuffiness ratings in Condition B. However,
        simultaneous exposure to high room temperature and poor air quality might also
        have an effect on stuffiness ratings together.

        <hss>Tiredness, energy and motivation</hss>

        Perceived lack of energy and motivation increased during the two-hour period, the
        increase being stronger in Condition B. In addition, participants were more tired
        in Condition B. Previously, a quite similar background speech as in condition B
        did not decrease arousal (i.e., tiredness) when silence was compared with a speech
        condition (Haapakangas et al., 2011). Similarly, Maula et al. (2015) did not find
        an effect of high room temperature on tiredness, energy or motivation. However,
        low ventilation rate (high CO2 concentration) increased the lack of energy and
        motivation although ratings remained rather low while the quality assessments of
        IE overall remained unaffected (Koskela et al., 2014). Based on these previous
        findings, it seems probable that the simultaneous exposure to highly intelligible
        speech, high temperature and low ventilation rate intensified the lack of energy
        and motivation more than the exposure to only one factor at a time could cause.

        <hss>Subjective workload</hss>

        In Condition B, subjective workload was higher than in Condition A which may
        reflect higher effort to compensate for the anticipated performance decrement.
        Experience of stress may be one mechanism leading to higher effort and subsequent
        disruption of performance (Hancock & Warm, 1989). As the higher subjective
        workload coincided with the performance decrement in Condition B, it appears that
        compensatory efforts were needed but were not sufficient to compensate for the
        worsened working conditions. Moreover, the enhanced effort hypothesis is an often-
        mentioned explanation for the observed differences between performance and
        questionnaire measures (Haapakangas et al., 2011; Schlittmeier et al., 2008).
        Subjective experience of disturbance, such as acoustic distraction, might lead
        individuals to invest more effort in their performance to compensate for the
        effect of distraction. In our study, the maintenance of good performance with the
        help of higher effort might have reduced the differences in performance between
        conditions; yet, significant differences were nevertheless found. Similar effects
        of compensatory effort have been reported by other researchers (Szalma & Hancock,
        2011). Although enhanced effort could have diminished performance decrement during
        the two-hour work period in our study, subjective workload might accumulate across
        longer time periods if the IE conditions causing stress persist. In working life,
        individuals are exposed to specific IE conditions several hours per day. It has
        been shown that coping strategies are in use to combat the disturbance of sounds
        in open-plan office (Kaarlela-Tuomaala, Helenius, Keskinen, & Hongisto, 2009):
        increased effort, longer breaks, slower working rhythm and longer working days
        have been reported.

        <hss>Physical symptoms</hss>

        Our results showed that perceived somatic symptoms were at a lower level in
        condition where the IE was well designed, which is in agreement with previous
        findings. The prevalence of somatic symptoms was higher in Condition B although
        the intensity of symptoms was relatively mild. It is notable that even with a few
        hours of exposure the prevalence of somatic symptoms was increased (see also e.g.,
        Lan et al., 2011).

        <hss>Emotions</hss>

        In previous studies, effects of IE on experienced emotions have been investigated
        very little. In our study, positive emotional responses decreased with exposure
        time in both experimental conditions, but emotional responses were more positive
        in Condition A after the second exposure hour. This is in agreement with the study
        of Lan et al. (2011) who found high temperature (30 °C) to be associated with
        negative mood. This result further reinforces the idea that indoor environment can
        affect emotional comfort even in the absence of somatic symptoms.

<hs>  Limitations of the study</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Limitations are related to methodological issues. First, participants were exposed to the
experimental conditions on two separate days on subsequent weeks since it was not possible
to build two open-plan offices. This might have caused measuring error despite a repeated
measures design. Retest reliability of task performance, indicating the consistency of a
test across time, has been indicated to differ depending on task type (Ellermeier &
Zimmer, 1997), and this might be one error source. Second, a two-hour exposure time was
used. Overall, the effects of noise on task performance have been shown to diminish with
exposure time (Szalma & Hancock, 2011). This may not be the case with speech sounds
(Haapakangas et al., 2014; Szalma & Hancock, 2011). Instead, as argued by Haapakangas et
al. (2014), it is possible that cognitive and subjective impacts of noise might even
increase over time as a result of an emerging stress response or decreasing compensatory
resources. Increased exposure time associated with the intensity of thermal condition has
been reported to increase the negative impact of temperature on performance (Hancock et
al., 2007). This is in line with the Maximal Adaptability Model (Hancock & Warm, 1989).
Because activation level in our study was low, it is probable that increasing exposure
time by one or two hours would not have affected the results. Instead, it would have
produced practical problems, such as a need for a lunch break. Overall, it is assumed that
a significant increase in the exposure time might reveal more robust effects of
temperature on task performance. In addition, the duration of thermal exposure might have
more impact on performance and subjective responses when work is more mobile and the
activation level is higher. Third, e.g., Hancock et al. (2007) have considered that time
of day might affect the relationship between temperature and performance. In our study,
the sessions were conducted in the morning to create optimal condition to perform without
tiredness and thus, minimize the possibility of intervening variables. Our results should
be applied with reservation when considering performance at another time of day. Fourth,
the IE conditions were planned to combine the experimental conditions of prior experiments
conducted in the same laboratory (Fig. 1). However, it is possible that one IE factor
dominated the effect on performance or subjective response over the other factors and had
more impact on the final results. The performance results should be applied with care to
real workplace environments. Our results might only be valid for individually performed
tasks in visual modality and requiring intensive use of working memory. Our results may
not apply to teamwork or communication tasks. In the future it is important to also
include tasks in the auditory modality. For example, it would be interesting and important
to study how irrelevant background speech might affect oral communication.

<h>CONCLUSIONS</h>
-----------

This study provides strong evidence that the combination of high intelligibility of
irrelevant speech, high room temperature and low ventilation rate impairs the perceived
working conditions and cognitive performance. It is possible to suggest that by designing
room acoustic conditions, thermal conditions and ventilation rate adequately, satisfaction
with work environment is increased, somatic symptoms are decreased and the possible
impairments of work performance can be avoided. The experiment was the final study in a
series of four experiments. The simultaneous exposure to these three adverse factors might
intensify some effects of IE. This is significant because IE problems are often
multifaceted in workplaces. In practice, the ventilation rate, room temperature and
acoustic conditions can vary significantly between office workplaces so that our
suggestions should not be generalized to all possible configurations of indoor
environment. Our study supports the view that special care should be paid to the holistic
design of indoor environment in open-plan offices.


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<ART>Skywalking in the city: Glass platforms and the architecture of vertigo
=======================================================================

Authors: Davide Deriu
DOI: 10.1016/j.emospa.2017.05.005
Year: 2018  |  Pages: 94-103
ASJC codes: 3205, 3207

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Ever since the advent of high-rise architecture, in the late nineteenth century, the
modern city has been a distinct locus of vertiginous experience. Whilst the correlation
between vertigo and tall buildings might at first appear to be an obvious one, it is in
fact a variable function of ever-evolving techniques and materials, as well as depending
on the psychosocial conditions that underlie the experience of space at a given place and
time. A great deal of public interest has been aroused over the past decade by the
proliferation of glass-floored viewing platforms, which have become increasingly popular
features of observation decks around the world. These platforms, often branded as ‘dare to
walk on air’ experiences, are designed to challenge the user's perception of spatial
depth. Whilst older types of viewing galleries, such as open decks with low walls, could
provoke stronger feelings of height vertigo than new glass floors (not least because of
the imagined agency of throwing oneself off the high point), the latter are distinct
insofar as they are designed to conjure the thrill of walking over the abyss in a seeming
state of suspension. The rise of glass floors gathered momentum in the mid-noughties, at a
time of rapid growth of vertical cities (King, 2004) that saw a new wave of ‘supertall’
and ‘megatall’ buildings emerge around the world. Social implications of contemporary
high-rise construction have been investigated from various perspectives, with regard to
the vertical dimension of cities (Graham and Hewitt, 2012; Graham, 2016); the role of the
skyscraper in architectural culture (Nobel, 2015) and in tourism-led urban regeneration
(Leiper and Park, 2010); and the psychological influence of tall buildings on their
occupants (Gifford, 2007). Meanwhile, the vertical visualisation of space brought about by
the combined use of satellite imagery and digital technologies, such as Google Earth (Di
Palma, 2008), has affected the conditions of embodied seeing as well as the physical
experience of vertigo, ushering in a new ‘age of aerial vision’ (Gilbert, 2010). The
recent surge of thrill-seeking practices such as rooftopping, which has sparked a broad
diffusion of ‘vertigo inducing’ images on the web, is further signal of a wider shift in
urban experience and representation (Deriu, 2016). Seen together, these phenomena are
symptomatic of a wider socio-cultural condition that appears to be pervaded by a dizzying
spatiality, particularly acute in vertical cities. The term vertigo crops up in
architectural and urban discourse rather frequently, albeit mainly in a figurative sense.
A case in point is the eponymous Glasgow exhibition (1999), where ‘The Strange New World
of the Contemporary City’ was illustrated through an assortment of architectural projects
that ranged widely in function and scale – from Tate Modern in London to the Ontario Mills
shopping mall in California. In the exhibition volume, Tate Modern's architect Jacques
Herzog remarked: ‘The word “vertigo” does not have auspicious connotations. In fact, it
would seem to address the sinister and even dangerous side of things: fear of heights and
the attendant dizziness. Or even a double anxiety: the fear of falling passively through
no fault of one's own, and the fear of responding quasi-actively to the magical attraction
of the abyss and thereby succumbing to its vertiginous appeal. “Vertigo” could be said to
express an inescapable ambivalence and indeterminacy.’ (Herzog, 1999: 6) The show did not
have a specific agenda, nor did it claim to present a consistent design approach. Instead,
the curatorial strategy aimed to capture the generic state of ‘dizziness’ and ‘disquiet’
provoked by the global architectural landscapes of the 1990s (Moore, 1999). The
provocative, and somewhat prophetic, title echoed the spiralling tension that runs through
Alfred Hitchcock's Vertigo: an enduring point of reference for cinematic representations
of the city as a protean emotional landscape. Two decades on, the ‘strange new world’
portrayed on the eve of the Millennium appears all too familiar. Indeed, the ‘double
anxiety’ evoked by Herzog has meanwhile taken up a new dimension. Today, vertigo aptly
describes the physical sensation that is induced by architectural elements such as the
fashionable glass-floors that line many high-level walkways. This vogue is epitomised by
the Shanghai World Financial Centre (SWFC), which was featured in the Glasgow exhibition
when only the foundations had been laid. Its construction was eventually completed in 2008
following design alterations that increased the overall height of the tower to 492 m. The
SWFC tower contains an exemplar of the current trend for immersive viewing experiences:
besides panoramic vistas of the surrounding cityscape, the 100th-floor observation
gallery, situated at 474 m of height, offers vertical views through a series of
transparent glass panes built into the floor (see Fig. 1). The SWFC has since boasted ‘the
world's highest observatory’, a record that may not last for long as the global race to
the sky carries on unabated. The construction of similar design features around the
urbanised world suggests that architectural vertigo has become a sought-after phenomenon.
This trend raises questions about the conditions in which space is designed, perceived and
experienced in the contemporary city. What bodily experiences are implicated in the
‘states of suspension’ induced by these platforms? What are their material and spatial
properties? And how do these spaces relate to the wider socio-economic context in which
they are produced? A cross-disciplinary approach will inform the investigation of these
issues, while a series of design projects will serve to illustrate various manifestations
of the subject. The proposed interpretation draws on theories of transparency and sensory
experience of space, supported by insights from psychology, and ultimately critiques high-
level glass platforms as ‘tourist bubbles’ that crystallise, quite literally, a social
imperative of the present moment.

<h>VERTIGO IN THE CITY: ARCHITECTURE AND ILINX</h>
-------------------------------------------

The term vertigo is fraught with multiple and ambivalent meanings that cannot be exhausted
in an article. Some elucidation may nonetheless inform a critique of current architectural
trends. Whilst in medical discourse vertigo is usually treated as a symptom of balance
system disorders, in popular culture the word is used more loosely to evoke various
sensations of giddiness, dizziness, and disorientation that are associated with a
perceived loss of equilibrium. Dictionary definitions range widely, from the illusion of
physical movement (‘the act of whirling round and round’) to the bodily perception related
to it (‘swimming in the head’), and extend to figurative meanings (‘a disordered state of
mind, or of things, comparable to giddiness’) (OED). In a figurative sense, the term has
also been adopted to describe the precarious conditions of life in contemporary societies.
For Young (2007: 12), ‘Vertigo is the malaise of late modernity: a sense of insecurity of
insubstantiality, and of uncertainty, a whiff of chaos and a fear of falling.’
Accordingly, a generalised feeling of giddiness defines our ‘liquid’ modernity (Bauman,
2000), an epoch in which values that previously had a solid foundation, such as social
status and economic position, have become increasingly fluid and unstable. The notion of
‘groundlessness’ has gained currency in art, architectural, and urban discourses over the
past decade (Dorrian, 2009; Steyerl, 2011; Graham, 2016). Dorrian (2009) in particular
draws comparisons between the ‘dissolution’ of ground evoked by Hitchcock, as well as by
authors like Nabokov and Sebald, and the disorienting experience induced by contemporary
architectures such as London's City Hall. At the bottom level of this Foster-designed
building, visitors can stand on a giant aerial photomap of London, taking symbolic
possession of the city from a vantage point that traditionally signifies a position of
power and control. Dorrian (2009: 86) sees this as ‘an attempt to architecturally stage
[…] democratic transparency’, in a similar mould as the glass dome of the new Reichstag in
Berlin – designed by the same architect. At City Hall, the abstract miniaturization of
London produced by the aerial view somehow jars with the act of walking on the photomap
while looking down in search of familiar clues. If, on the one hand, this embodied
experience provides the visitor with a sense of grounding, on the other hand the photomap
triggers a ‘vertiginous multiplicity’ that causes an opposite ‘ungrounding’ effect: a
disorientation amplified by the non-hierarchical code of representation that distinguishes
satellite imagery from cartographic maps (Dorrian, 2009: 91). The ‘vertiginous
ungrounding’ described by Dorrian calls to mind philosophical conceptions of modernity as
an existential condition perturbed by unprecedented degrees of freedom: namely, the
‘dizziness of freedom’ expounded by Kierkegaard in his 1844 treatise The Concept of
Anxiety (LeBlanc, 2011). However, while Dorrian plays down the role of heights in the
etymology of vertigo and its aforementioned cultural representations, there is evidence to
suggest that elevation is in fact increasingly bound up with the dizzying experience of
contemporary urban space. As we shall see, the current popularity of elevated glass
platforms vividly illustrates how height vertigo is elicited in visceral ways through
particular spatial arrangements. Remarkably, the notion of vertigo is conspicuous for its
absence from the main texts that have defined the critical discourse on the perception of
the city from above. Barthes (1983/1964) omitted it from his ‘Eiffel Tower’ essay, wherein
he coined the term ‘architectures of vision’ (architectures de la vue) to describe the
19th-century structures that turned the ‘fantasy of a panoramic vision’ into material
reality. Accordingly, the Tower epitomised the rise of a modern form of perception that
made it possible to embrace a bird's eye view of the metropolis and thereby to comprehend
it in its structure. By positing the city as a text to be read and deciphered, Barthes's
argument privileged the power of intellection over the corporeal experience of space. A
similar tendency to reduce the observation tower to a mere vantage point characterises De
Certeau's (1984/1980) later description of Manhattan from atop the World Trade Center,
wherein the ‘voluptuous pleasure’ of seeing the city as a whole is described as a purely
visual act. The observation deck is the platform from which a dieu voyeur observes the
city ‘like a picture’ and lays claim over it. The ensuing ‘fiction of knowledge’,
concludes De Certeau (1984/1980: 92), ‘is related to this lust to be a viewpoint and
nothing more.’ While these now-classic accounts remain critical for our understanding of
urban modernity, and of the observation deck as one of its enduring topoi, they leave
unquestioned the embodied experience of space that was induced by such unprecedented
heights. How does one feel when confronting the city from high vantage points? This is not
to diminish the cognitive function of viewing galleries, nor to dispute their significance
as social spaces implicated in procedures of spectacle and surveillance; but rather to
address another dimension of high-rise architecture that has become all the more relevant
in light of the current vogue of glass floors. The design of platforms that expand the
field of vision to the vertical axis affects the practice of viewing cities from above in
ways that have not been interrogated as yet. In order to comprehend this phenomenon, let
us turn to another theory that puts a different spin on the notion of vertigo. In his
seminal book, Man, Play and Games, Caillois (2001/1958) revived the ancient Greek word
ilinx (‘whirlpool’) to define one of the four fundamental categories of human play. With
this term Caillois identified those games ‘which are based on the pursuit of vertigo and
which consist of an attempt to momentarily destroy the stability of perception and inflict
a kind of voluptuous panic upon an otherwise lucid mind.’ (Caillois, 2001/1958: 23) He
remarked that ilinx is an ancient form of play, as exemplified by the rituals performed by
whirling dervishes and pole-flying voladores. In the course of history, fairgrounds became
traditional spaces for games of vertigo, with their ‘machines for rotation, oscillation,
suspension, and falling, constructed for the sole purpose of provoking visceral panic.’
(Caillois, 2001/1958: 133) Crucially, Caillois observed that ilinx was a pervasive aspect
of modern life, typified by the exhilaration induced, for instance, by speed and drugs.
Historically, the quest of ‘voluptuous panic’ described by Caillois found new expression
in the 19th century through a range of mechanised thrill rides epitomised by the
rollercoaster. While gravity plays had long been popular social entertainments in funfairs
and circuses, the amusement park turned the modern city into a playground for thrilling
pleasures (Kane, 2013). These ‘mechanised entertainments’ emerged at a time when a series
of bodily practices aimed at defying the force of gravity – such as high diving,
parachuting, and funambulism – became mass spectacles. In this respect, the 19th century
has aptly been called ‘the gravity century’ (Soden, 2003). It is interesting to note that
Caillois singled out tightrope walking as the activity that most closely corresponds to
ilinx: by turning the ludic – and, therefore, unproductive – nature of play into a
performance art, the wire-walker ‘[moves] through space as if the void were not
fascinating, and as if no danger were involved.’ (Caillois, 2001/1958: 137). This
practice, which burgeoned as a public spectacle in the 1850s, over the twentieth century
moved from the abysses of nature to those of cities. In recent decades, skillful acrobats
like Philippe Petit and Nik Wallenda have displayed their ability to master vertigo in the
midst of breathtaking urban environments (Johnston, 2013). Caillois's anthropology of play
has inspired urbanists to engage with the ludic aspects of contemporary cities. Stevens
(2007: 43), for instance, draws extensively on the concept of ilinx in an attempt to
unearth the creative potential of public spaces: ‘[v]ertigo negates instrumental benefit
and embraces risk for its own sake and the affirmation of human bodily experience.’ From a
different angle, Caillois's theory might also inform the critical analysis of high-level
glass platforms as stages where games of ilinx are socially performed. For the challenge
of ‘walking on air’ in some way simulates the acrobatics of highwire walkers who confront
the vertiginous heights of cities. As shown in the next section, the vogue of glass floors
makes the thrill of ‘skywalking’ accessible to the general public within safe and
protected environments – usually for the price of a ticket.

<h>AUGMENTING ARCHITECTURE: THE RISE OF GLASS FLOORS</h>
-------------------------------------------------

The use of glass in the design of walking surfaces is not new, and has a particularly rich
background in retail interiors. Notably, the dramatic glass staircases designed by Eva
Jiřičná from the 1980s onwards paved the way for a trend that, over the past decade, has
been spread globally by the Apple store chain. In the noughties, while translucent glass
became a popular means of allowing sunlight through multi-storey spaces, the design of
transparent glass floors also gained momentum. A typical use can be found in exhibition
spaces such as archeological sites and museums, where visitors are drawn to contemplate
objects on display underneath their feet. Although transparent glass panes are usually
placed over shallow spaces, there are exceptions that engage a bodily interaction with
deeper voids. At the Acropolis Museum in Athens, for instance, structural glass was used
extensively not only to exhibit the outdoors archeological excavations but also to create
elevated, see-through surfaces that allow users to walk over the museum's central space
(Self, 2014). Different considerations preside over the design of glass-bottomed platforms
in tall structures, where the main purpose is to open up downward-looking perspectives
onto the yawning void underneath. The first high-level transparent floor was fitted in the
observation deck of Toronto's CN Tower, where in 1994 a horizontal grid of tempered glass
panes was mounted on the viewing gallery 342 m above the ground (see Fig. 2). After a few
early emulations, this project set a worldwide trend only a decade later. The CN Tower
boasted the highest glass-floored observation deck in the world until 2008, when it was
overtaken by the Shanghai World Financial Center (SWFC): by that time, the global craze
for skywalks had become pervasive. Whilst the CN Tower heralded the glass floor as a means
of enhancing the tourist appeal of high-level viewing galleries, the SWFC Observatory
embodies its evolution to a full-fledged spatial concept. Located in the midst of
Shanghai's financial district, the skyscraper symbolizes the boom of high-rise
construction that took place in China amidst major changes in the global economic
geography around the turn of the 21st century. Glass floors furnish the walkways that span
the 55 m-long gallery on the tower's 100th floor – a transparent bridge suspended nearly
half a kilometer above the ground. The ‘Skywalk 100’ epitomises a new type of urban
observatory: a free-standing gallery that envelops the visitor's body within a glassy
capsule-like space from which they can watch the city from above while enjoying the thrill
of ‘walking on air’. The dizzying quality of this space is further heightened by the
reflecting ceilings and the outward inclination of the fully-glazed side walls. As the
SWFC website proclaims: ‘Walking on the three transparent glass-walled walkways, visitors
will experience the feeling that Shanghai lies at their feet.’ (SWFC) Although the
possibility of gazing at the city is still very much part of the attraction, the skywalk
signals a move from Barthes's architectures of vision towards what might be called
‘architectures of vertigo’. No longer a pure machine for seeing, the observation deck is
reconfigured as a machine for thrilling: a spatial enclosure that combines the visual
spectacle of the city with an altogether more visceral experience. Over the past decade,
glass floors have become recurring features of viewing platforms around the world.1 Two
notable examples are located in Chicago, the historical birthplace of both the skyscraper
and the observation wheel. In 2009 the Willis Tower (formerly Sears Tower) had its 103rd-
floor Skydeck retrofitted with a series of retractable balconies designed by SOM – the
firm behind the original 1970s tower. This feature, dubbed ‘The Ledge’, broke new ground
in the design of high-altitude viewing platforms owing to its four all-glass boxes that
protrude over 1.3 m from the building façade at 412 m above ground (see Fig. 3). The
challenge to step on a fully transparent balcony at such dizzying heights is advertised as
a brave act: ‘Get out on the Ledge – if you dare’ (Skydeck Chicago). Those who dare shall
be rewarded: ‘With glass on the ceiling, floor, and all sides, it is truly, an
unforgettable experience.’ (ibid.) Behind the platitude of this marketing pledge lies a
deeper economic strategy that pits observation towers vying for tourists' attention
against each other – globally as well as locally. In 2014 a new attraction called ‘Tilt’
opened across town at the former Observatory of the John Hancock Center, in overt
competition with Skydeck Chicago. The feature consists of a glass-and-steel platform that
tilts thirty degrees outwards, allowing visitors to lean with their bodies over a 300
m-chasm (see Fig. 4). The conception of this immersive space, branded ‘Chicago's Highest
Moving Experience’ (360 Chicago), signalled that even one of the highest viewing galleries
in the world, capable of 360-degree views of the cityscape, needed a facelift to keep up
with the competitors. The Tilt presents an interesting variation on the theme of high-
level transparent features: an alternate tendency towards the design of moveable elements
aimed at stimulating a dynamic, vertigo-inducing experience. The game of architectural
ilinx here requires that you let yourself go, quite literally: transported over the void,
the visitor-cum-player enjoys the adrenaline rush provoked by the momentary disruption of
sensory stability. The dynamics of thrill-seeking have been taken to a new extreme at the
U.S. Bank Tower in Los Angeles, where an entirely glass-cladded attraction called
‘Skyslide’ was built in 2016 as an extension of the ‘Skyspace’ observation deck. Hanging
on the building's façade at circa 300 m of height, the Skyslide entices visitors to
‘experience […] unparalleled views in a whole new way as they glide from the 70th to the
69th floor of the U.S. Bank Tower.’ (OUE Skyspace LA) Local commentators have noted that
the Skyspace project aimed to bring tourism revenue to an area of Downtown L.A. with
rising vacancy rates in commercial skyscrapers (Hawthorne, 2016). The costly makeover of
the tower's observatory has been regarded as an attempt to reclaim, and reenchant, the
view from above in a sprawling city where the aerial gaze is mainly associated with the
helicopter view (ibid.). The Skyslide marks a further step in the design of high-altitude
glass boxes. This transparent device induces the ‘voluptuous panic’ of a free fall into
space: a fast yet safe descent that derives its allure, yet again, from the attraction of
the void. Meanwhile, a parallel development has taken place in Europe, where glass
platforms have become familiar attributes of tall structures – albeit at a more modest
scale. In the U.K. the craze for glass floors has pervaded new-build and historical
architectures alike. Portsmouth's Spinnaker Tower, whose sail-like shape echoes the Burj
Al Arab hotel in Dubai, was completed in 2005 to spearhead the regeneration of the harbour
area: the glass skywalk that was built on one of the viewing decks (100 m) is deemed to
have played a part in the tower's touristic success. More recently, some of the country's
major attractions have also been retrofitted with similar features. Blackpool Tower's
‘Walk of Faith’, initially built in the late-1990s as a simple glass-floor panel, was
later expanded into a whole skywalk (116 m) as part of the refurbisment unveiled in 2011
by the ‘global leisure’ giant Merlin Entertainments. Less dramatic in terms of height, yet
more interesting in other respects, is the 2014 retrofitting of London's Tower Bridge with
glass floors on the panoramic walkways that connect the towers. While the Grade I-listed
structure had previously undergone functional renovations, the insertion of 11 m-long,
see-through platforms responded to the intent of attracting more users. The revamped twin
galleries double up as venues for hire: visitors attending corporate events, private
parties, or yoga classes can now revel in – or recoil from – the act of skywalking over
the Thames. The relatively limited height (42 m), if compared with other such walkways,
allows for a closer visual connection with the passersby and the traffic unfolding on the
road bridge down below. The incongruous effect of transparency triggers, in people either
side of the walkways, not only sheer curiosity but also an awareness of the reciprocal
distances and positions within the newly-opened visual field (see Fig. 5). A similar
intervention took place, around the same time, in the modern ‘architecture of vision’ par
excellence – the Eiffel Tower. In their restyling of the Tower's first floor (57 m)
architects Moatti-Rivière designed a series of glass platforms that aim to achieve an
‘augmented architecture’ (Trétiack, 2014). Besides improving the existing public spaces,
the refurbishment included open-air, inward-looking terraces that open up the central void
through a combination of horizontal and vertical transparency: ‘The project offers an
improved experience of the Tower and Paris, an entertaining sensory experience, a journey
of the senses and knowledge.’ (Eiffel Tower, n. d.) In a Living Architectures documentary,
Alain Moatti explains the idea of magnifying the feeling of void that, historically, has
been the primary characteristic of the Tower: a peerless monument which, with reference to
Barthes, the architect credits with ‘the invention of third dimension in the city.’ (Bêka
and Lemoine, 2014) In a telling scene, a visitor likens the sense of lightness he felt on
a glass floor to levitation. The impression of floating on air is further enhanced by the
physical contiguity between the horizontal surfaces and the inclined glass parapets that
delimit the floor space, which are wholly transparent (see Fig. 6). Whilst at Tower Bridge
the glass walkways were the main raison d’être of the renovation, in the Eiffel Tower they
are comparatively minor features of a wider project. The restyling of the Tower is
nonetheless symptomatic of a widespread tendency to produce ever-more immersive
experiences of space. High-level platforms that challenge users to ‘walk on air’ manifest
a pursuit of architectural ilinx – a contemporary version of the ‘voluptuous panic’
described by Caillois. These design features have become common not only in urban settings
but also in natural environments, as shown by several projects aimed at heightening the
scenic effects of landscapes around the world. The prime example is the cantilevered glass
skywalk at Grand Canyon West, Arizona, opened in 2007 and reportedly inspired by Toronto's
CN Tower.2 Vertiginous structures of this kind play a significant part in the promotion of
landscapes that are branded as tourist attractions. As Porter (2015: 207) notes, they
signal ‘a tourist development which, like the quest for the tallest building, is a never-
ending exercise in one-upmanship, leading further and further into exaggeration.’ The
glass floors that have concurrently appeared in observation towers provide an urban analog
of the experience of natural landscapes. Indeed, the fact that these platforms were first
introduced in cities and only later in natural landscapes is an interesting sign of how
the urban environment, with its built-up gorges and canyons, has become a major source of
attractions for thrill tourists. In our urban age, in which verticality is an increasingly
common dimension of city life (Graham, 2016), architecture has become instrumental to the
production of spatialised games of ilinx.

<h>THRILLS OF TRANSPARENCY: ON THE ‘SIXTH FAÇADE’</h>
----------------------------------------------

The notion of transparency is key to understanding the spatiality of glass-floored urban
observatories. As Forty (2000: 286) notes, transparency is ‘a wholly modernist term,
unknown in architecture before the twentieth century.’ Its basic sense, ‘meaning pervious
to light, allowing one to see into or through a building’ (ibid.) became popular in the
1910s-1920s, when advances in glass manufacturing and frame construction made it possible
to build self-standing glass enclosures. The coupling of structural frame with glass
panes, which had an ancestor in the stained-glass windows of Gothic cathedrals, was such a
breakthrough in modern construction that has been described as ‘the most significant
development in architecture in the last millennium.’ (Fierro, 2003: viii-ix). A manifest
expression of this shift was the curtain wall, which gained broad diffusion after World
War II amidst a steep increase in structural glass production. It was in reaction to that
trend that Rowe and Slutzky (1963) elaborated the concept of phenomenal transparency, a
perceptual quality defined as the ‘illusion of spatial depth’ that characterised modernist
architecture as well as avant-garde painting. This theory signalled an attempt to
transcend the literal transparency of the International Style: that is, the basic optical
quality of the modernist ‘glass box’. Rowe and Slutzky's sophisticated argument could do
little, however, to halt the proliferation of curtain-walls worldwide. The architectural
uses of glass have vastly expanded over recent decades, as this versatile material proved
suitable to an increasing number of functions while also providing a symbol of political
power (Fierro, 2003). By the turn of the 21st century, with ever more tower blocks dotting
the skylines of cities, and the curtain wall defining a global aesthetic (Elkadi, 2006),
literal transparency had become so widespread as to conquer the horizontal dimension. And
yet, despite their growing popularity, transparent floors are barely mentioned in the
literature about glass in architecture (Cruz, 2013). This is all the more remarkable if we
consider the novelty of glass platforms that transpose the modernist frame construction
onto the horizontal plane. The alteration of the floor into a see-through surface, akin to
a horizontal window, calls to mind the notion of ‘fifth façade’ formulated by Le Corbusier
in the late 1920s – when he envisioned new functions for the flat roof terrace after
flying over South American cities. It might be argued that, by overturning the vertical
window-wall onto a horizontal surface, the introduction of the glass floor has ushered in
the sixth façade. This epithet befits the lower side of elevated buildings and overhanging
building elements, insofar as they fulfil the condition of externality that is implied by
the physiognomic etymology of the word ‘façade’: that is, in the case of glass platforms,
the possibility of looking through from without as well as from within. For the purpose of
the present argument it should be useful to distinguish, with some degree of
approximation, between ‘low-level’ and ‘high-level’ glass platforms. The former, such as
those at Tower Bridge and the Eiffel Tower, are usually installed in, or added to, the
underside of existing structures and effectively operate as horizontal floor-windows that
enable a two-way visual contact between inside and outside. Although the main goal of
these platforms is to allow for a top-down vision, a bottom-up gaze from below is also
afforded, to varying degrees, by the relatively low elevation. Higher platforms hanging
several hundred meters above the ground, such as those at the SWFC Observatory and Skydeck
Chicago, may not be clearly visible from the street but can nonetheless be seen from
within the same buildings as well as adjacent ones. Moreover, the floors' undersides gain
wide exposure through media representations, such as brochures and websites, where lower
viewing angles are favoured by photographers to visualise the skywalkers' bodies. The
recognition of the field of visibility that is opened up by these transparent surfaces
prompts further questions about the spaces they define and the actual uses they enable.
What kinds of responses and interactions are elicited by the sixth façade? A complex
reciprocal relationship is established between internal users and external viewers. The
simple fact that these platforms must remain tightly-sealed in order to perform their
function means that visual contact through the glass occurs in a state of spatial
separation. The bodies of those who ‘dare to walk on air’ are usually visible from below
through a peculiar honeypot effect, as skywalkers perform their balancing acts in front of
curious spectactors on both sides of the glass stage. There are nuanced interconnections
between how people feel in these spaces and how the latter affect their emotions, since
height vertigo manifests itself through a wide range of psycho-physiological responses.
Depending of where one sits in the spectrum of ‘height tolerance’ (Salassa and Zapala,
2009), varying degrees of thrill or anxiety can be elicited by states of suspension that
appear to defy the laws of gravity.

<h>SENSING GRAVITY: KINAESTHESIA AT HEIGHTS</h>
----------------------------------------

While skywalks are built in highly controlled and safe environments, they are designed to
challenge the user's fear of heights by exposing them to the view lying underneath their
feet. The structure encasing the glass panes, usually made of multiple-layer tempered
glass laid out in a grid, doubles up as a comfort zone where hesitant users can reach for
a sense of safety. Those who initially skirt around a glass platform often approach it
through small and tentative steps as they confront the fear of the void. This experience
transcends the visual field insofar as the act of ‘skywalking’ engages the subject's
proprioceptive system as well as the optokinetic one – two distinct perceptual apparatuses
whose signals to the brain, if discrepant, may trigger a sensation of dizziness (Yardley,
1994). In fact, the sensory stimulation caused by glass platforms is not confined to the
five senses but rouses a sixth sense traditionally known as kinaesthesia, or the ‘muscle
sense’. As Çelik (2006) points out, this sense was discovered in the early 19th century by
psychologists who realised that muscles are capable of receiving sensations from the
spinal cord and should therefore be considered to be sentient: ‘Kinaesthesia, the sense of
bodily movement […] [refers] to those unclassifiable sensations that could not be traced
accurately to one of the five known sense organs, but seemed to originate from the
undifferentiated mass of the viscera.’ (Çelik, 2006: 159). Although the development of
neuroscience has greatly expanded the scientific knowledge of body-mind relations, the
notion of kinaesthesia remains relevant to the present discussion. It resonates with the
prevailing conception of architecture as a field of multi-sensory experience, which,
especially since the 1990s, has been largely informed by phenomenology (Holl et al.,
2006). Pallasmaa (2006, 2012) in particular sought to ‘re-sensualise’ architecture by
discerning the emotional states that are involved in the embodied experience of space, in
contrast to the hegemony of ‘retinal architecture’ in modern western culture. By
championing the return to a sensory architecture, Pallasmaa referred to the muscular
tensions through which we apprehend the built environment, and on which we project our
movements through a process of ‘bodily identification’ with place. He stressed the role of
proprioception in the experience of space and recognised the unconscious desire to defy
gravity that architecture can elicit: ‘The sense of gravity is the essence of all
architectonic structures and great architecture makes us conscious of gravity and earth.
Architecture strengthens verticality of our experience of the world. At the same time that
architecture makes us aware of the depth of earth, it makes us dream of levitation and
flight.’ (Pallasmaa, 2006: 37). Accordingly, the heightened consciousness of gravity that
is produced by awe-inspiring architectures is the source of ‘memorable experiences’. What
remains unaccounted in this theory is the realm of sensory experiences that, in the
presence of spatial depths, can engender emotions of fear and anxiety as well as comfort
and pleasure. Further insights from psychology shed light on the ‘thrill of transparency’
that makes glass floors so appealing – although not for everyone. The movements registered
by the sensorimotor nerves define our overall body schema and thereby underpin the ways we
organise our actions in space. As we have seen, the design of glass floors is intended to
amplify the spectacle of the view from above by engaging the user's sense of balance when
confronted with the sight of heights. When standing in front of a glass platform, a moment
of realisation occurs whereby the incongruity of the view provokes an intense kinaesthetic
feeling: an instinctive response that calls to mind the early experiments with depth
perception based on the ‘visual cliff’ (Gibson and Walk, 1960). The kinaesthetic faculty
that makes us aware of our bodily position in space (i.e., the ‘eye-object distance’)
triggers the subjective feeling of imbalance that may cause discomfort and dizziness in
‘height intolerant’ subjects. Elevated glass floors are among those ‘encounter spaces’
that cause a high perception of risk in acrophobic sufferers (Andrews, 2007). At the
opposite end of the spectrum are ‘height tolerant’ individuals who cope well with spatial
depth and, in some cases, find excitement and exhilaration in the experience of altitude
(Salassa and Zapala, 2009). The thrill of transparency induced by glass floors is what
drives height-seeking individuals to revel in the psychological sense of danger that keeps
others at bay. For thrill seekers, the sixth façade therefore constitutes a playground for
the experience of the sixth sense. While the present essay does not claim to provide a
systematic analysis, these observations begin to delineate the spatial and social context
in which the experience of elevated glass floors is situated. The links between physical
sensations and the emotions related to the experience of heights introduce a further
degree of complexity due to their fundamentally subjective nature. Psychoanalytic research
suggests that feelings of anxiety and pleasure associated with vertigo are interwoven, as
bodily perceptions reflect – and reveal – our dynamic mental states (Quinodoz, 1997). The
ways in which inner drives are channelled through actions and behaviours is bound to
determine varying levels of height tolerance through an individual's life span. To
consider emotions of pleasure and anxiety as inextricably bound up might therefore help us
to understand the irregular and mutable occurrences of vertigo that often punctuate
people's lives. These embodied experiences are, however, invariably situated within a
material and social context: hence the importance of considering the wider conditions in
which glass floors and the related ‘thrills of transparency’ are produced.

<h>EXPERIENCE AS COMMODITY: THE ECONOMY OF VERTIGO</h>
-----------------------------------------------

The idea of memorable experience advocated by the proponents of an architecture of the
senses is an unholy bedfellow with the coeval ‘experience economy’ theory. With this
influential term, Pine and Gilmore (1998, 1999) named a step change in ‘the progression of
economic values’ whereby businesses seek to gain a competitive edge by staging experiences
that are purportedly memorable: ‘While prior economic offerings – commodities, goods, and
services – are external to the buyer, experiences are inherently personal, existing only
in the mind of an individual who has been engaged on an emotional, physical, intellectual,
or even spiritual level.’ (Pine and Gilmore, 1998: n. p.) The production of commodified,
and increasingly customised, experiences spread from the entertainment industry to other
sectors such as travel and retail, and extended to architecture as well (Lonsway, 2009).
The tourist industry was among the first to embrace this process. Already in the 1970s
MacCannell (1999/1976: 21) noted in his semiotic analyisis of tourist attractions:
‘Increasingly, pure experience, which leaves no material trace, is manufactured and sold
like a commodity.’ Subsequently, Bauman (1996) pointed out that tourists, unlike other
social types of travellers, are mainly driven by ‘pull’ rather than ‘push’ factors. In
other words, their mobility is governed by aims (‘in order to’) rather than causes
(‘because of’): ‘the tourist is a conscious and systematic seeker of experience, of a new
and different experience, of the experience of difference and novelty – as the joys of the
familiar wear off and cease to allure. The tourists want to immerse themselves in a
strange and bizarre element (a pleasant feeling, a tickling and rejuvenating feeling, like
letting oneself be buffeted by sea waves) – on condition, though, that it will not stick
to the skin and this can be shaken off whenever they wish.’ (Bauman, 1996: 29) These
ideas, which to a large extent are still valid today, shed further light onto the rise of
glass floors as ‘experience design’ products. To contemplate a cityscape through a
horizontal window-floor is in itself a ‘strange and bizarre’ attraction that draws scores
of visitors to immersive viewing galleries. Skywalks arguably constitute typical examples
of ‘tourist bubbles’ (Judd, 1999): self-contained and highly regulated spaces in which
moments of leisure can be enjoyed within secluded and safe environments. Marking a shift
from the traditional mechanisms of panoramic vision, these spaces presuppose an expanded
function of the tourist gaze involving a multi-sensuous, kinaesthetic experience: in other
words, they are stages for the performance of ‘embodied actions’ (Urry and Larsen, 2012:
190). These actions are almost invariably recorded on camera, as the act of photographing
or filming one's body suspended over the void is a popular means of validating the
memorable experience. Undeterred by the Global Financial Crisis of the late noughties, or
perhaps even spurred by it, the skyscraper business has continued to tap into the growing
market of vertiginous experiences. The design of multi-storey viewing galleries on top of
‘supertall’ buildings such as London's Shard and, more recently, New York's One World
Trade Center has led to considerations that ‘observation decks have become cash machines.’
(Brown, 2014) Vying to attract visitors, today's viewing galleries stage the embodied
experience of urban heights as an increasingly immersive event. Whilst vision is still
predominant, its mechanisms and practices are increasingly augmented through immersive
spatial experiences that find a parallel in the surge of technologies such as Virtual
Reality, 4D cinema, and the like. A technological variation on the theme of the glass
floor is shown by the ‘sky portal’ built into the observatory's floor at One World Trade
Center, which opened to the public in 2015. This attraction consists of a round 14 ft-wide
platform where visitors can stand and watch a live video image of the scene unfolding at
street level. The thrill of the glass floor is simulated by a high-definition livestream:
in lieu of real transparency, the screen technology reproduces views from above to be
watched in a vicarious state of suspension. By replacing the direct sight of height with
an immersive cinematic spectacle the ‘sky portal’ takes the suspension of disbelief to a
new level: further evidence of how deeply architectures of vertigo are embedded in the
structures of a buoyant experience economy. The pursuit of memorable experiences leads to
the production of spaces that, while largely homogenised, at the same time boast their own
distinctive features – or, in business parlance, ‘unique selling points’.

<h>CONCLUSION</h>
----------

This study suggests that observation decks are increasingly conceived as spaces of
visceral thrills. The vogue of high-level glass floors could easily be dismissed as a
passing fad driven by the ‘form follows fun’ principle; and yet, upon closer scrutiny this
phenomenon reveals deeper socio-spatial implications. When considered together, the cases
discussed above show a consistent shift from the realm of architectures of vision towards
what might be called architectures of vertigo. Although it probably remains that, while on
high, ‘one can feel oneself cut off from the world and yet the owner of a world’ (Barthes,
1983/1964: 250), the panoramic view alone appears to be no longer adequate to meet the
demands of urban observatories. These places reflect, and actively produce, a collective
desire for vertiginous experience akin to the ‘voluptuous panic’ described by Caillois as
ilinx. The proliferation of skywalks and sundry glass platforms signals that, amidst a
thriving experience economy, designers have been perfecting new ways of harnessing the
user's sensory responses to spatial depth. It can be hypothesised that the viewing subject
central to modern scopic regimes is being superseded by a sentient subject whose feelings
are put through ever more intense psycho-physiological stimuli. This subject embodies a
visual sensibility that is no longer predicated on processes of abstraction and cognition
but involves an expanded, and increasingly immersive, field of sensory experience. Glass
floors in particular offer a kinaesthetic experience of space that combines the thrill of
altitude with the thrill of transparency. As we have seen, these platforms owe their
appeal to a horizontal transparency that provokes the exhilarating feeling of hovering
over urban space as if in a state of suspension. Elevated glass floors reproduce the
groundlessness of the present socio-economic condition and effectively reaffirm it in
spatial form. By so doing, they partake in the ‘dreamworlds of neoliberalism’ (Davis and
Monk, 2007) that are shaping the emotional landscapes of our cities. Indeed, the spaces
described in this paper comply with the predominant subjectivity in which risks and
insecurities are governed through environmental stimuli that discipline the activities of
the body. They are aligned with a broad strand of architecture that, since the 1990s, has
been designed primarily to stimulate ‘affects’ (Spencer, 2016): a ‘post-critical’ design
approach that, by disengaging the user from rational and cognitive processes, bolsters up
the dominant logic of neoliberalism. In a similar vein, skywalks are designed to embolden
a dynamic and enterprising subject to enjoy a seemingly boundless degree of freedom,
albeit an artificially staged one. This avid consumer of novel and ever-more thrilling
experiences embodies the zeitgeist of our hyper-hedonistic age; that is, what
psychoanalysts have identified as a social imperative of the present moment – ‘you must
enjoy!’ (Recalcati, 2012: 111). In staging a playground for thrilling experiences,
skywalks join a plethora of other games of ilinx that defy the laws of gravity and thereby
exorcise the existential fear of falling. Thrill-seeking has been associated with those
forms of ‘deep play’ (Ackerman, 1999) that entice people who yearn to escape the
restraints of civilized life, particularly in big cities, to attain ecstatic and
enlightening moments through adventurous exploits. Skywalks are arguably symptomatic of
this wider psychosocial condition. The drive to challenge one's sense of balance is an
innate form of human play, and there is something fascinating, as well as frightening,
about the possibility of looking down through an elevated glass floor. These platforms
hold the potential to reveal hitherto invisible spaces, to provoke an awareness of the
vertical expansion of cities, and possibly reflections about its hubristic nature.
However, their main social function seems to be an altogether different one. Far from
inviting a reflexive aesthetic experience, the viewing galleries that draw visitors to
‘walk on air’ operate as tourist bubbles in which the encounter with the abyss underneath
our feet is reduced to a themed spectacle. As the sixth façade becomes the stage of
memorable experiences, the hyper-secure conditions in which these experiences take place
ensure that our perception of verticality is domesticated and normalised within highly-
controlled spaces. This phenomenon offers insights into the increasingly vertiginous
environments of contemporary cities and provokes reflections about the social and spatial
conditions they reflect and in turn produce.


<h>REFERENCES</h>
----------

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<ART>Slow and steady? Strategic adjustments in response caution are moderately reliable and correlate across tasks
================================================================================

Authors: C. Hedge, Solveiga Vivian-Griffiths, Georgina Powell, A. Bompas, Petroc Sumner
DOI: 10.1016/j.concog.2019.102797
Year: 2019
ASJC codes: 3204, 3205
Keywords: Diffusion model for conflict tasks, Drift-diffusion model, Impulsivity, Individual differences, Inhibition, Reliability, Response caution, Response control, Speed-accuracy trade-off

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Speed-accuracy trade-offs are often considered a confound in speeded choice tasks, but individual differences in strategy have been linked to personality and brain structure. We ask whether strategic adjustments in response caution are reliable, and whether they correlate across tasks and with impulsivity traits. In Study 1, participants performed Eriksen flanker and Stroop tasks in two sessions four weeks apart. We manipulated response caution by emphasising speed or accuracy. We fit the diffusion model for conflict tasks and correlated the change in boundary (accuracy – speed) across session and task. We observed moderate test-retest reliability, and medium to large correlations across tasks. We replicated this between-task correlation in Study 2 using flanker and perceptual decision tasks. We found no consistent correlations with impulsivity. Though moderate reliability poses a challenge for researchers interested in stable traits, consistent correlation between tasks indicates there are meaningful individual differences in the speed-accuracy trade-off.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Response control is one of the cornerstones of cognitive psychology, and a topic of
interest for both experimental and correlational approaches. Individual differences in
tasks such as the Stroop (Stroop, 1935) and Eriksen flanker (Eriksen & Eriksen, 1974),
have been linked to executive functioning (Miyake et al., 2000), impulsive behaviour
(Sharma, Markon, & Clark, 2014), and a variety of neuropsychological conditions (Chambers,
Garavan, & Bellgrove, 2009; Gauggel, Rieger, & Feghoff, 2004; Lansbergen, Kenemans, & van
Engeland, 2007; Moeller et al., 2002; Verdejo-Garcia, Perales, & Perez-Garcia, 2007). From
an experimental perspective, response control paradigms feature prominently in modelling
and neurophysiological studies, where the goal is to characterise the general mechanisms
responsible for the control of action (Bompas, Hedge, & Sumner, 2017; Logan, Yamaguchi,
Schall, & Palmeri, 2015; Munoz & Everling, 2004). Though the application of these tasks
across different disciplines is promising for the development of a coherent understanding
of response control, recent work has illustrated that there are challenges to interpreting
individual differences because they can arise from different sources, including strategic
processes (Boy & Sumner, 2014; Hedge, Powell, Bompas, Vivian-Griffiths, & Sumner, 2018;
Miller & Ulrich, 2013). Here, we ask whether strategic processes, often considered to be a
confound in cognitive studies, represent a reliable and general component of decision
making.

<hs>  Multiple processes underlying individual differences in response control</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In conflict tasks, such as the Stroop, flanker or Simon tasks, we typically subtract
reaction times or errors in a baseline condition (congruent or neutral) from a condition
in which the stimulus provides conflicting information (incongruent). When used in an
individual differences context, the resultant RT or error costs are treated as an index of
the individual’s ability to resolve competition between conflicting response options (e.g.
Friedman & Miyake, 2004). However, the processes underlying behaviour are multifaceted,
and variability in the magnitude of an RT cost or error cost cannot easily be attributed
to a single mechanism (Hedge, Powell, Bompas, et al., 2018; Miller & Ulrich, 2013). For
example, it has long been theorised that an individual’s reaction time reflects not only
their ability to process a stimulus, but also their strategic choice to favour speed or
accuracy (Pachella, 1974; Wickelgren, 1977). Indeed, one of the reasons why we use within-
subject designs when examining differences between conditions in average RTs is to account
for this so called speed accuracy trade-off (SAT). However, individual differences in
strategy still contribute to variability in the RT costs. Individuals who favour accuracy
over speed produce larger RT costs, as well as smaller error costs (Hedge, Powell, Bompas,
et al., 2018; Hedge, Powell, & Sumner, 2018; Wickelgren, 1977). In order to dissociate
contributions of strategy and ability in a cognitive task, we require a framework that
characterises the contributions of both to behaviour. One such framework is that of
sequential sampling models (Brown & Heathcote, 2008; McKoon & Ratcliff, 2013; Ratcliff &
McKoon, 2008; Ulrich, Schroter, Leuthold, & Birngruber, 2015). These models assume that
choice RT behaviour can be captured by a process of accumulating evidence sampled from the
environment, until a boundary or threshold is reached. The rate at which evidence is
accumulated represents the efficiency of processing, and the height of the boundary
reflects the amount of evidence that an individual waits for before deciding on the
response (i.e. their level of response caution, or strategy). By dissociating these
processes, and for their ability to simultaneously account for both the RT and accuracy of
responses, sequential sampling models could provide a useful window into individual
differences in response control (see e.g. Hedge, Powell, Bompas, et al., 2018; White,
Curl, & Sloane, 2016).

<hs>  Response caution as a meaningful component of response control</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To many researchers conducting choice RT tasks, strategic processes are considered a
confound to the mechanisms of interest. For example, composite measures of RT and accuracy
have been proposed with the explicit intention of providing a better control for SATs than
traditional subtractions in studies of (e.g.) executive functioning (Draheim, Hicks, &
Engle, 2016; Liesefeld & Janczyk, 2018). However, there is evidence that strategic control
itself may be a meaningful measure of individual differences, as captured by sequential
sampling models. For example, more cautious response strategies are often observed in
healthy older adults, relative to younger adults (e.g. Ratcliff, Thapar, & McKoon, 2006;
Thapar, Ratcliff, & McKoon, 2003). Studies have also observed changes in response caution
in individuals with autistic spectrum disorders, though the studies vary in the direction
of the effect (Karalunas et al., 2018; Pirrone, Dickinson, Gomez, Stafford, & Milne, 2017;
Powell et al., 2019). Finally, in multiple response control task datasets, we observed a
correlation between tasks in model parameters representing response caution, in the
absence of correlations in parameters reflecting conflict processing (Hedge, Powell,
Bompas, & Sumner, 2019). Participants in the aforementioned studies are typically
instructed to be both fast and accurate, such that the levels of response caution observed
are interpreted as the individual’s ‘default’ strategy when given no explicit instruction
to favour speed or accuracy. However, individuals are also able to flexibly adjust their
strategy if instructed. In SAT paradigms, participants are instructed to prioritise speed
in some blocks and accuracy in others, which is (primarily) captured in sequential
sampling models by an individual decreasing or increasing their boundary (for a review,
see Heitz, 2014). The extent to which individuals are able or willing to adjust their
level of caution has also been the subject of individual differences research. Larger
decreases in caution under speed emphasis relative to accuracy emphasis in a perceptual
decision task were correlated with increased BOLD activation in the striatum and pre-SMA
(Forstmann et al., 2008), as well as increased structural connectivity between those
regions (Forstmann et al., 2010; though see Boekel et al., 2015 for a non-replication of
the connectivity). An association has also been observed between response caution under
speed emphasis and self-reported “need for closure” (Evans, Rae, Bushmakin, Rubin, &
Brown, 2017). Need for closure is a personality trait theorised to reflect an individual’s
preference for certainty over ambiguity (Webster & Kruglanski, 1994), from which Evans et
al. predicted that a greater need for closure would lead to more urgent decision making.
In line with this prediction, when the data were fit with the linear ballistic accumulator
model (Brown & Heathcote, 2008), individuals with a greater need for closure set a lower
threshold (Evans et al., 2017). In sum, the research to date suggests that individual
differences in response caution and its strategic adjustments have the potential to inform
our understanding of cognitive functioning in both healthy individuals and
neuropsychological conditions. However, this promise is tempered by several unknowns.
First, the psychometric properties of response caution and its strategic adjustments are
not well understood. Test-retest reliability is an important consideration for individual
differences research, reflecting the degree to which individuals can be consistently
ranked on the dimension of interest (i.e. more or less cautious). Recent work has
suggested that traditional measures of response control have sub-optimal reliability, and
these concerns may also extend to model-based analyses (Hedge, Powell, & Sumner, 2018;
Paap & Sawi, 2016). Though a few studies have examined the test-retest reliability of
model parameters representing response caution (Enkavi et al., 2019; Lerche & Voss, 2017;
Schubert, Frischkorn, Hagemann, & Voss, 2016), to our knowledge none have examined the
reliability of strategic adjustments of caution in a SAT paradigm. A second consideration
is the extent to which individual differences in strategic control adjustments can be
generalised from a single task. Several studies have observed correlations in response
caution between tasks when neither speed nor accuracy are preferentially reinforced (Hedge
et al., 2019; Lerche & Voss, 2017; Ratcliff, Thompson, & McKoon, 2015), though those that
have examined the SAT have used a single perceptual decision task (Evans et al., 2017;
Forstmann et al., 2008, 2010). Here, we address this gap in the literature with two
experiments. In the first, we apply a model of response control (the diffusion model for
conflict tasks; Ulrich et al., 2015) to test-retest data from the flanker and Stroop tasks
under different SAT instructions. This allows us to examine whether adjustments in control
are reliable over time within the same task, and whether they generalise across tasks
within the same cognitive domain. In the second experiment, we examine generalisability
more broadly by comparing a response control task (flanker) to a perceptual decision task
(random dot motion) commonly used in the decision making literature. To examine potential
relationships with related constructs, we also collected data on self-reported impulsivity
in both studies, as well as compliance and personality in Study 2.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 57 (6 male) undergraduate and postgraduate psychology students.
Participants took part either for payment or for course credit. All participants gave
their informed written consent prior to participation in accordance with the revised
Declarations of Helsinki (2013), and the experiments were approved by the local Ethics
Committee.

<hs>  Design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

Participants completed both the Stroop and flanker task in two 90 min sessions taking
place approximately 4 weeks apart. A schematic of these tasks, as well as the random dot
motion task used in study 2, can be seen in Fig. 1. We administered the UPPS-P, a self-
report measure with subscales for different types of impulsivity, (Lynam, Whiteside,
Smith, & Cyders, 2006; Whiteside & Lynam, 2001), after participants complete the
behavioural tasks. Participants completed the tasks in a dimly lit room from a viewing
distance of approximately 60 cm. Stimuli were presented on a 36.5 cm by 27.5 cm display
(60 hz, 1280 × 1024).

        <hss>Eriksen flanker task</hss>

        Participants responded to the direction of a centrally presented arrow (left or
        right) using the z and m keys. On each trial, the centrally presented arrow (1 cm
        × 1 cm) was flanked above and below by two other symbols separated by 0.75 cm, so
        that flankers were individually visible. Flanking stimuli were either arrows
        pointing in the same direction as the central arrow (congruent condition),
        straight lines (neutral condition), or arrows pointing in the opposite direction
        to the central arrow (incongruent condition). Trials were separated by an interval
        of 750 ms.

        <hss>Stroop task</hss>

        Participants responded to the colour of a centrally presented word (Arial, font
        size 70), which could either be red (z key), blue (x key), green (n key) or yellow
        (m key). The colours were not purposely matched for luminance. The presented word
        could be the same as the font colour (congruent condition), one of four non-colour
        words (lot, ship, cross, advice; neutral condition), or a colour word
        corresponding to one of the other response options (incongruent). Trials were
        separated by an interval of 750 ms. For each session and task, participants
        completed 12 blocks, consisting of 4 each for speed, standard and accuracy
        instructions. Each block consisted of 144 trials, with 48 each of congruent,
        neutral and incongruent stimuli (192 trials total per congruency and instruction
        condition). The order of blocks was randomised, as was the order of trials within
        blocks. At the beginning of speed-emphasis blocks, participants were instructed
        “Please try to respond as quickly as possible, without guessing the response”. For
        accuracy blocks, participants were told “Please ensure that your responses are
        accurate, without losing too much speed”. For standard instruction blocks,
        participants were instructed “Please try to be both fast and accurate in your
        responses”. In speed blocks, if participants responded slower than 500 ms in the
        flanker or 600 ms in the Stroop, the message “Too slow” appeared on screen for 500
        ms. In the accuracy condition, the message “Incorrect” appeared if participants
        made an error. In all blocks, the message “Too fast” appeared if participants
        responded faster than 150 ms in the flanker and 200 ms in the Stroop task
        (typically <1% of trials). Participants received feedback about both their average
        RT and accuracy after each block in all instruction conditions. Stimuli were
        presented until response. In the Stroop task, stimuli were presented for a maximum
        duration of 1950 ms. Trials exceeding this were rare (0.3% and 0.2% of trials in
        session 1 and 2).

<hs>  Data processing</hs>
  ~~~~~~~~~~~~~~~

Two participants were removed because they did not return for the second session. We
excluded participants if there average accuracy across all instruction blocks fell below
60%. This resulted in more participants being retained for the flanker task (N = 47) than
the Stroop (N = 43). These participants were retained for the reliability analysis in the
flanker task, but were excluded when calculating correlations across tasks. We removed RTs
less than 100 ms, and greater than the individual’s median plus three times their median
absolute deviation for each condition (Leys, Ley, Klein, Bernard, & Licata, 2013). We did
not code trials as incorrect on the basis that they exceeded our deadline for feedback in
speed blocks, as changing the relationship between RT and accuracy would confound our
modelling. The data are available on the Open ScienceFramework (https://osf.io/zag7c/).
For the reliability analysis, we calculated Intraclass Correlation Coefficients using the
psych package in R (ICC2; Revelle, 2018; Team & R Development Core Team, 2016). This value
is the ratio of between-subject variance in the measure to the total variance, comprising
between-subject variance, between-session variance, and error variance. The form of the
ICC corresponds to a two-way random effects model for absolute agreement (Shrout & Fleiss,
1979). While the ICC is interpreted as a correlation, ranging from zero to one, different
criteria are used to interpret the degree of reliability compared to interclass
correlation effect sizes (Pearson’s R and Spearman’s rho). ICCs above 0.8 are typically
considered excellent, while 0.6 and 0.4 are categorised as good and moderate reliability
(Cicchetti & Sparrow, 1981; Fleiss, 1981; Landis & Koch, 1977). In contrast, Pearson’s R
values of 0.5, 0.3 and 0.1 are typically interpreted as large, medium and small effect
sizes respectively (Cohen, 1988). The higher convention for the ICC primarily reflects the
application rather than the calculation, as high levels of reliability are typically a
pre-requisite to correlational work. When calculated on the same data, intra and
interclass correlations usually produce similar values (see supplementary material A for
different calculations).

<hs>  The diffusion model for conflict tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The diffusion model for conflict tasks (DMC; Ulrich et al., 2015) is a mathematical model
of two-choice reaction time behaviour in response conflict tasks. It assumes that the
response options are represented by an upper and lower boundary, here corresponding to the
correct and incorrect response respectively. The decision processes can be described by a
process of accumulating evidence from the stimulus until one or the other boundary is
reached (see Fig. 2A). The reaction time on a given trial is determined by the time it
takes for a boundary to be reached, plus the duration of sensory and motor (non-decision)
processes. For mathematical details, see Ulrich et al. (2015). Boundary separation is the
critical parameter for our current goal of measuring individual differences in response
caution. Individuals who are more averse to making errors and slow their responses to
avoid them should have higher boundary separation values. When participants are instructed
to emphasise speed, this is primarily captured by lowering their boundary in that block
(for reviews, see Heitz, 2014; Ratcliff, Smith, Brown, & McKoon, 2016). Recent evidence
has indicated that the changes under speed emphasis are also reflected in non-decision
time to a degree in non-conflict tasks, and sometimes also by a change in drift rate (see
e.g. Rae, Heathcote, Donkin, Averell, & Brown, 2014). However, the sensitivity of DMC
parameters to the SAT manipulations have not been examined. Given the time-consuming
nature of the fitting process for our datasets, and the relatively large number of
possible variants, we make the simplifying assumption that only boundary separation varies
across SAT instruction conditions here. The DMC assumes that the accumulation process on a
trial is a combination of processing from controlled and automatic pathways (De Jong,
Liang, & Lauber, 1994; Ridderinkhof, 2002). The controlled route is responsible for
processing the task-relevant stimulus feature (e.g. the central arrow in the flanker
task), and is represented by drift rate parameter that is constant across conditions.
Automatic activation is implemented as a re-scaled gamma function, described by two free
parameters (amplitude and time-to-peak) and one fixed parameter (shape). Initially, the
automatic activation receives a strong input, reflecting the capture of a prepotent
response by (e.g.) the flanking arrows. After it reaches a maximum value (amplitude) at a
specified point in time (time-to-peak), the automatic activation decreases, reflecting
decay or active suppression (Hommel, 1994; Ulrich et al., 2015). In addition to the
aforementioned parameters, which are typically the focus of interest, the model has two
parameters describing variability in the starting point of the accumulation processes and
variability in the duration of non-decision time respectively.

<hs>  Model fitting</hs>
  ~~~~~~~~~~~~~

For each participant and task, we estimated nine parameters: boundary separation under
speed emphasis, boundary separation under standard instructions, boundary separation under
accuracy emphasis, the amplitude of automatic activation (A for congruent trials, 0 for
neutral trials, -A for incongruent trials), the time to peak automatic activation, mean
non-decision time, drift rate of the controlled process, the shape parameter of the
starting point distribution, and variability in non-decision time. Variability in starting
points and non-decision time are captured by a beta and normal distribution respectively.
As with Ulrich et al. (2015), the diffusion constant/within-trial noise (σ) was fixed to
4, and between-trial variability in drift rates was fixed to 0. We fixed the shape
parameter of the automatic activation function to 2 for all tasks, following Ulrich et al.
(2015). We accuracy-coded our data, such that the upper and lower response boundaries
corresponded to the correct and incorrect response options. This allowed us to collapse
across different stimulus configurations (e.g. a congruent flanker stimulus irrespective
of whether the arrow was pointing left or right), and also to fit the same model to the
four-choice Stroop data (Voss, Nagler, & Lerche, 2013). Though this level of abstraction
is not ideal, it relates RT and accuracy to capture the strategic processes that we are
interested in, and there is currently no extension of the model for four choice tasks.
After excluding outlier RTs as described above, correct and incorrect RTs from congruent,
neutral and incongruent conditions in each instruction block were separately binned into
quantiles. We fit the DMC to experimental data using the similar approach to that used by
the Diffusion Model Analysis Toolbox (DMAT; Vandekerckhove & Tuerlinckx, 2008). Correct
RTs were binned using five quantiles (0.1, 0.3, 0.5, 0.7, 0.9). Incorrect RTs were binned
using five quantiles if the total number of errors in that condition >10, otherwise they
were not used. The application of five quantiles produced six bins per RT distribution
(corresponding to: 0–10%, 10–30%, 30–50%, 50–70%, 70–90%, 90–100%). Therefore,
participants’ fits would be based on either 6 or 12 data points per instruction and
congruency condition, resulting in between 54 and 108 data points in total. These
quantiles are commonly used when fitting sequential sampling models (c.f. Ratcliff &
Tuerlinckx, 2002). We calculated the deviance (-2 log-likelihood) between observed and
simulated quantiles, which was minimised with a Nelder-Mead simplex (Nelder & Mead, 1965)
implemented in the fminbnd function in Matlab. We constrained the search such that all
free parameters were positive, and the shape of the starting point distribution was
greater than one. Initially, we fit each participant’s data using 5000 parameter sets that
were randomly generated from a uniform distribution (see supplementary material B for
maximum and minimum values). This was done to explore plausible starting points for our
fitting algorithm. We then took the 15 best parameter sets resulting from this initial
search, and submitted each of those to the simplex algorithm, in which we simulated 10,000
trials per condition at each iteration. The simplex was re-initialised 3 times to avoid
local minima. After the process was completed, we took the single best fitting parameter
set for each individual. This process took approximately 6 days per dataset, and was
performed on Cardiff University Brain Research Imaging Centre’s (CUBRIC) high performance
computer cluster.

        <hss>Behavioural data</hss>

        Reaction times and error rates for both tasks are shown in Fig. 3. To verify that
        the average performance reflected the expected manipulations, we conducted
        separate 3(instruction) × 3(congruency) repeated-measures ANOVAs on RTs and error
        rates for each session and task. In all cases we observed significant main effects
        for both congruency and instruction (all p < .001; see Supplementary Material C
        for full ANOVA results). Error rates and RTs increased for incongruent relative to
        congruent stimuli. Further, error rates increased and RTs decreased when
        participants were instructed to prioritise speed over accuracy. Reaction times and
        error rates for both tasks are shown in Fig. 7. As in Experiment 1, we verified
        that the average performance reflected the expected manipulations by conducting
        separate repeated-measures ANOVAs on RTs and error rate in each task. In all cases
        we observed significant main effects for both congruency/coherence and instruction
        (all p < .001; see Supplementary Material C for full ANOVA results). Error rates
        and RTs increased for incongruent (flanker) and low-coherence (dot-motion) stimuli
        relative to congruent and high-coherence stimuli. Further, error rates increased
        and RTs decreased when participants were instructed to prioritise speed over
        accuracy.

        <hss>Model parameters</hss>

        Descriptive statistics for the best fitting parameters can be seen in Table 1.
        Graphical displays of the model fits can be seen in Supplementary Material D. The
        values are numerically similar to previous fits we have observed in a non-SAT
        context (Hedge et al., 2019), with the Stroop showing a relatively slower time-to-
        peak and a higher value for the shape of the starting distribution (corresponding
        to less variability in start points). This reflects that the manual Stroop task
        does not tend to show fast errors (see Supplementary Material D). The model was
        successful in capturing the relative speed and accuracy of participants, though
        the data show more fast errors under speed-emphasis than the model. In both tasks
        and sessions, boundary separation was decreased under speed relative to neutral
        and accuracy emphasis, indicating that the parameter captured the SAT manipulation
        in the expected way. Descriptive statistics and graphical displays of the fits for
        the best fitting parameters can be seen in Supplementary material F. In both
        tasks, as expected, boundary separation was decreased under speed relative to
        neutral and accuracy emphasis. Values for the flanker task are similar to those
        observed in Study 1. Values for the DDM parameters fit to the dot-motion task were
        within typically observed ranges (Donkin, Brown, Heathcote, & Wagenmakers, 2011;
        Matzke & Wagenmakers, 2009).

<hs>  Within-task reliability of strategic adjustments of response caution</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We quantified strategic adjustments in response caution by taking the difference in
boundary separation under speed-emphasis relative to accuracy emphasis for each
individual. Strategic adjustments showed moderate reliability across both tasks (flanker
ICC = 0.5, Stroop ICC = 0.40; see Fig. 4). To put these model parameter correlations in
context of the behaviour from which they’re derived, we also examined the reliability of
adjustments to RT and accuracy rates in isolation (averaged across congruency conditions).
This led to a similar range of values, with ICCs from 0.46 to 0.68 (see Supplementary
Material A for a full report). In other words, the reliability of the model parameters
were not systematically higher or lower than the behavioural measures. Note that boundary
separation is theorised to reflect a balance between RT and accuracy, and so would not
have the same interpretation as either behavioural measure in isolation. See Table 2 for
the reliability of all the DMC parameters. We also draw attention to the 95% confidence
intervals (CI) given in this table. While a CI cannot be interpreted as an indicator of
the precision of an estimate (c.f. Morey, Hoekstra, Rouder, Lee, & Wagenmakers, 2016),
under similar assumptions as those used to calculate a p-value, it can be interpreted to
contain the values we cannot reject based on our statistical test (Morey, Hoekstra,
Rouder, & Wagenmakers, 2016). In other words, just as we reject the null hypothesis (ICC =
0) based on the interval for adjustments in the flanker task (95% CI: 0.26–0.69), we also
reject values that correspond to excellent or clinically required levels of reliability
(ICC > 0.7).

<hs>  Between-task correlation of strategic adjustments of response caution</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our second key question is whether strategic adjustments in response caution correlate
between tasks, which we assessed using Spearman’s rho. We observed moderate to large
correlations between tasks in each session (session 1 rho = 0.56, p < .001; session 2 rho
= 0.40, p = .038; Fig. 5). Again, these were similar to the correlations observed in the
adjustments of RTs and accuracy in isolation, which ranged from 0.31 to 60 (see
Supplementary material A). We present the correlations between strategic adjustments of
response caution and UPPS-P subscales in supplementary material E. Briefly, we see no
consistent correlation across our datasets. As in study 1, we observed a large correlation
in strategic adjustments in response caution (rho = 0.50, p < .001; Fig. 8). Thus,
behavioural variability captured by parameters representing response caution do share
commonality across tasks from different cognitive domains. As in Study 1, this was
numerically similar to the correlation observed in the adjustments in RT and accuracy in
isolation (both rho = 0.40). For correlations between self-report measures and strategic
adjustments in response caution, see Supplementary material E. Correlations with self-
report were generally small and inconsistent across the tasks.

<hs>  Reliability of other model parameters</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As we are the first to examine the test re-test reliability of the DMC parameters (not
just the strategic adjustments to boundary), we present these in Table 2, along with the
between task correlations. The reliability of the three main non-conflict parameters
(drift rates, boundary separation in each instruction condition and non-decision time)
ranges from moderate to good, and are similar to those observed for the standard drift-
diffusion model (Lerche & Voss, 2017). For conflict processing parameters, the amplitude
of the automatic activation showed moderate reliability in both tasks, whereas the time-
to-peak was relatively poor. The between-task correlations are generally similar to that
which we observed with these tasks in our other work (that did not include a SAT
manipulation; Hedge et al., 2019).

<hs>  Interim discussion</hs>
  ~~~~~~~~~~~~~~~~~~

We discuss the implications of these values in more detail in the general discussion.
First, we follow up on the observation that strategic adjustments in response caution
correlate between the flanker and Stroop tasks in both sessions. This result is promising,
and suggests that we can generalise our interpretation of individual differences in
strategic control beyond a single task. However, it raises the question of whether it
generalises outside of response control tasks, or if strategic adjustments may differ
depending on the broad cognitive domain. This is particularly relevant as previous papers
that have examined individual differences in strategic adjustments have used a perceptual
decision task, rather than conflict tasks (Evans et al., 2017; Forstmann et al., 2008,
2010). To assess whether individual differences in response caution also generalise across
cognitive domains, we conducted a second study in which participants performed the flanker
task along with a random dot motion discrimination task under a SAT manipulation.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 81 (6 male) undergraduate and postgraduate psychology students.
Participants took part either for payment or for course credit. Six participants that
participated in Study 1 also participated in Study 2. The studies took place a year apart.
All participants gave their informed written consent prior to participation in accordance
with the revised Declarations of Helsinki (2013), and the experiments were approved by the
local Ethics Committee.

<hs>  Design and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

Participants completed both the flanker task and a dot motion discrimination task based on
(Pote et al., 2016). The participants also completed a number of questionnaires for the
purpose of exploratory analyses: the UPPS-P impulsivity scale, the NEO-FFI personality
inventory (McCrae & Costa, 2004), the Gudjonsson Compliance Scale (Gudjonsson, 1989), and
a Situational Compliance Scale (Gudjonsson, Sigurdsson, Einarsson, & Einarsson, 2008). The
flanker task appeared as described above. Participants performed 12 blocks of 144 trials
in total. Twelve participants did not complete all blocks within the allotted time, so
data were only available for 11 (11 participants) or 10 (1 participant) blocks. In the dot
motion task, each frame consisted of 50 white dots (5x5 pixels in size) displayed within
an oval patch (14.7 cm high × 23.7 cm wide) in the centre of a grey screen (60 hz, 1680 ×
1050). On each frame, either 30% (high coherence) or 15% (low coherence) of the dots were
chosen as signal dots, which moved in a consistent direction (left or right) by 29 pixels.
The lifetime of the dots was 3 frames. Non-signal dots reappeared in a random position on
each frame. The stimulus was displayed for a maximum of 2000 ms, with a 500 ms ISI.
Participants were asked to determine the direction of the coherent motion. Each block
consisted of 120 trials, 60 of each coherence level. Participants performed 12 blocks in
total, except for 5 participants who completed 11 blocks, and 1 participant who completed
10. Feedback relating to speed, accuracy or neutral blocks was given as described in Study
1. For the dot motion task, participants were informed that their responses were too slow
in speed blocks if their RT exceeded 700 ms. Participants were informed that they were too
fast in all blocks if their responses were shorter than 250 ms.

<hs>  Data processing</hs>
  ~~~~~~~~~~~~~~~

The same inclusion criteria and RT cut-offs described in study 1 were applied. After
exclusions, 73 participants were retained for the analysis of between-task correlations.

<hs>  The drift-diffusion model</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

As the dot-motion task is not a conflict task, and the DMC extends the standard drift-
diffusion model with conflict-specific parameters, we opted to fit the dot motion data
with the standard drift-diffusion model (DDM; Ratcliff, 1978; Ratcliff & Rouder, 1998).
Though the DMC is an extension of the DDM, it is possible that they capture variance
associated with response caution in slightly different ways due to different
parameterisations. However, we are interested in the conclusions that researchers would
draw if they had used the model that was most appropriate for the task they had used.
Critically for our purposes, strategic adjustments in response caution are conceptually
captured by a change in boundary separation in both models. The primary difference between
the DMC and the DDM is that, whereas accumulation rates in the DMC reflect a composite of
controlled and automatic processes, accumulation rates in the DDM are determined by a
single drift rate parameter. This means that the underlying accumulation rate in a given
trial is constant over time, albeit subject to noise as in the DMC. Conditions with
varying difficulty are captured by differences in average drift rates (see Fig. 6).

<hs>  Model fitting</hs>
  ~~~~~~~~~~~~~

We fit the DMC to the flanker data using the same process described for study 1. For the
DDM, we used the Diffusion Model Analysis Toolbox (DMAT; Vandekerckhove & Tuerlinckx,
2008). Similar to our approach with the DMC, observed RT quantiles from correct and
incorrect are compared to data simulated from the model, and the deviance minimised using
a Nelder-Mead simplex (Nelder & Mead, 1965). As with the flanker task, for simplicity we
assumed that only boundary separation varied across instruction condition. For each
participant and task, we estimated eight parameters: boundary separation under speed
emphasis, boundary separation under standard instructions, boundary separation under
accuracy emphasis, drift rate for high coherence trials, drift rate for low coherence
trials, mean non-decision time, starting point variability and non-decision variability.
Between-trial variability in drift rates was fixed to 0.1, starting point bias was fixed
to boundary separation/2, and within-trial noise was fixed to 0.1. Note that DMAT assumes
uniform distributions for starting point and non-decision variability, whereas our
implementation of the DMC uses a beta and normal distribution respectively (following
Ulrich et al., 2015).

<h>GENERAL DISCUSSION</h>
------------------

The aim of the current work was to examine whether individual differences in strategic
adjustments of response caution are a reliable and generalisable dimension of response
control. The answer to both questions is yes, though this is caveated by the magnitude of
the effects that we observe. In Experiment 1, we observed moderate test-retest reliability
in the change in response caution in both the flanker and Stroop tasks, as represented by
the change in boundary separation between accuracy-emphasis and speed emphasis
instructions. It is not trivial that these strategic adjustments show non-zero
reliability, though the magnitude is below the levels typically considered good or
excellent for conducting individual differences research (Cicchetti & Sparrow, 1981;
Fleiss, 1981; Landis & Koch, 1977). The implication of this is that researchers interested
in examining relationships between strategic adjustments in response caution and
personality or brain structure will likely require large sample sizes to detect
relationships, if they exist. With regards to generalisability, we show medium to large
correlations in response caution adjustments across tasks conducted in the same
experimental session. We observed this between conflict tasks (study 1), and between a
conflict and a perceptual decision task (study 2). We focus our discussion on the
interpretation of strategic control adjustments, and practical recommendations for
researchers interested in response caution.

<hs>  Meaningful individual differences in default caution and its strategic adjustment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There is increasing evidence that there are meaningful individual differences in response
caution (Evans et al., 2017; Forstmann et al., 2010; Hedge et al., 2019; Karalunas et al.,
2018; Pirrone et al., 2017; Powell et al., 2019; Ratcliff et al., 2006a). Recently, we
applied the DMC to three response control datasets, comprising the flanker and Simon
tasks, flanker and Stroop tasks, and two variants of the Simon task. Our aim was to
examine whether the model could uncover hidden correlations between mechanisms of conflict
processing that are obscured in traditional measures (Hedge, Powell, Bompas, et al.,
2018). Though we observed no correlation in the conflict parameters (amplitude and time-
to-peak), we consistently observed correlations in boundary (see also Lerche & Voss, 2017;
Ratcliff et al., 2015). This finding is mirrored in our results here, with boundary
separation consistently showing correlation between tasks. The novel contribution of this
work is that we also see correlation in the strategic adjustment in response caution,
captured by the change in boundary separation between different SAT instructions. We
manipulated participant’s levels of response caution through verbal instruction, which is
the same method used by the previous studies that have examined individual differences in
response caution adjustments (Evans et al., 2017; Forstmann et al., 2008, 2010). There are
numerous alternative methods for eliciting a SAT (for a review, see Heitz, 2014). These
include the use of payoff structures, in which participants receive different rewards and
penalisations based on accuracy and/or RT (e.g. Fitts, 1966; Swensson & Edwards, 1971);
and the use of response deadlines, where participants are informed that they must respond
within certain time limits (e.g. Pachella & Pew, 1968). Heitz notes that verbal
instructions are popular because they are easily understood by participants, and produce
large effects with relatively few trials. However, just as the interpretation of the
common instruction in choice RT tasks to be both fast and accurate is subjective, so too
is the instruction to favour speed. Our reliabilities and correlations suggest that
participants interpret these instructions somewhat consistently, though we do not know
what the basis is for the criteria they set. In part, this is what we seek to understand
by examining correlations with personality constructs such as impulsivity. To our
knowledge there has not been a systematic examination of the consequences of the choice of
SAT manipulation for individual differences relationships (though some have been compared
experimentally, e.g. Dambacher & Hübner, 2013). It would benefit future research in this
area to elucidate whether the method makes a difference.

<hs>  Do strategic control adjustments go beyond boundary separation?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A wealth of literature exists for the speed-accuracy trade-off, spanning both behavioural
and neurophysiological approaches (for a review, see Heitz, 2014). In the context of the
sequential sampling models, faster RTs and lower accuracy under speed emphasis are
primarily attributed to reduced boundary separation: a relative decrease in the amount of
evidence required to initiate a response (Ratcliff et al., 2016). However, performance
under speed emphasis has also been captured by additional reductions in non-decision time,
as well as sometimes lower drift rates (Rae et al., 2014; Starns, Ratcliff, & McKoon,
2012; Zhang & Rowe, 2014). Further, it has been argued that strategic adjustments can be
captured by time-varying decision processes, such as urgency signals or collapsing
boundaries (Cisek, Puskas, & El-Murr, 2009; Ditterich, 2006a, 2006b; Drugowitsch, Moreno-
Bote, Churchland, Shadlen, & Pouget, 2012; though see Hawkins, Forstmann, Wagenmakers,
Ratcliff, & Brown, 2015). Here, we fit a relatively simple model that only allowed
boundary separation to vary across instruction conditions. Therefore it is possible that
our fits absorbed variance in behaviour that might be captured by other parameters in a
more complex model. Note that in the introduction, we highlighted the difficulty in
translating assumptions from within-subject contexts to the study of individual
differences. The SAT paradigm is also an approach that has largely been developed in
within-subject experimental contexts, and the average best fitting model may not be
appropriate for every individual. For example, we could ask whether every individual shows
a decrease in boundary, non-decision time, and/or information processing parameters (c.f.
Haaf & Rouder, 2018). Our results here provide a starting point for further examination;
that we observe some reliability and cross-task correlation in response caution here
suggests that there is reliable variance in the behaviour to be captured.

<hs>  Previous literature on the reliability of response caution</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To our knowledge, we are the first to examine the reliability of parameters of the
diffusion model for conflict tasks. Previous work has examined the test-retest reliability
of the standard drift-diffusion model (Lerche & Voss, 2017; Schubert et al., 2016),
including applications to conflict tasks (Enkavi et al., 2019), though not in a SAT
paradigm. Nevertheless, we can contrast our estimates of the reliability of boundary
separation under standard instructions with theirs. Lerche and Voss (2017) reported one
week reliability for a lexical decision task, a recognition memory task, and an
associative priming task. They observed correlations of approximately r = 0.8 for boundary
separation in all tasks (see maximum likelihood estimates in their Fig. 2). Schubert et
al. (2016) report eight month reliabilities for three tasks, including a two- and four-
choice variant of a visual choice RT task, a Sternberg memory scanning task, and a Posner
letter matching task. Correlations for boundary separation between sessions ranged from r
= 0.2 to r = 0.6 (see their Table A2). Recently, Enkavi et al. (2019) applied the
hierarchical drift diffusion model (Wiecki, Sofer, & Frank, 2013) to reliability data from
15 choice RT tasks, including a three choice Stroop task. The average time between
sessions was approximately 16 weeks. The reliability of boundary separation in the Stroop
task was 0.29, which was slightly below the median reliability for all the tasks (0.31;
see their HDDM values in Fig. 5). Taking these previous studies together, our results fall
within the range of reliabilities previously observed, but the range is broad. It would be
premature to suggest that there are systematic differences between tasks in the
consistency of response caution that they elicit, though we note that it was relatively
low for the Stroop task in both our Study 1 and in Enkavi et al. (2019) data.

<hs>  Model choice and model complexity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To examine the reliability of strategic adjustments in response caution, we applied the
drift-diffusion model (Ratcliff, 1978), and an extended diffusion model for conflict tasks
(Ulrich et al., 2015). Though the drift diffusion model is widely applied in SAT studies
(e.g. Mulder et al., 2010; Ratcliff, 1985; Zhang & Rowe, 2014), there are alternative
models for both conflict (Hubner, Steinhauser, & Lehle, 2010; White, Ratcliff, & Starns,
2011) and non-conflict tasks (Brown & Heathcote, 2008; Usher & McClelland, 2001). Several
empirical and theoretical reviews have considered the relationship between different
models, and it has been noted that there is often a high degree of mimicry between them,
such that researchers would often reach the same conclusion irrespective of the model
chosen (Bogacz, Brown, Moehlis, Holmes, & Cohen, 2006; Donkin et al., 2011; Ratcliff &
Smith, 2004; White, Servant, & Logan, 2017). Nevertheless, we briefly consider the
potential impact of this choice. Both Forstmann et al. (2010) and Evans et al. (2017)
examined individual differences in response caution adjustments using the Linear Ballistic
Accumulator model (Brown & Heathcote, 2008). Whereas in the DDM a single drift process
represents the difference in evidence between to alternatives, the LBA consists of
separate accumulators for each response alternative and a single threshold. Starting
points for the accumulators in the LBA are drawn from a uniform distribution, and response
caution is captured by the difference between the edge of the start point distribution and
the height of the threshold. Forstmann et al. (2010) noted that applying the drift-
diffusion model to their data did not produce the correlation between white matter
strength and caution adjustments seen with the LBA (see their Supplementary Online
Material). They suggested that this may be because the diffusion model captured the SAT
manipulation in both non-decision time and drift rates, in addition to boundary
separation. An imperfect mapping between the response caution parameters has also been
noted when fitting one model to data generated from the other (Donkin et al., 2011). Given
this discrepancy, researchers may wish to check the robustness of conclusions drawn from
one model to another. Though we made the simplistic assumption that the SAT manipulation
was specifically captured by changes in boundary separation in our fits, we added
complexity by including parameters representing inter-trial variability in non-decision
time and the starting point of the accumulation process. Including these variability
parameters often produces better fits to empirical data at the sample average level
(Ratcliff & Tuerlinckx, 2002), but they may also lead to poorer recovery of individual
differences in the main parameters of interest, particularly with fewer trial numbers
(Lerche & Voss, 2016; van Ravenzwaaij, Donkin, & Vandekerckhove, 2017). We reran some of
our analyses without including the variability parameters, and it produced almost
identical estimates for the reliability of strategic adjustments (see Supplementary
Material G). This may be in part because we had a large number of trials, and a model that
was quite well constrained across multiple conditions. Where researchers have smaller
trial numbers, they may wish to implement a simpler model, or check that their conclusions
are not specific to a particular parameter choice.

<hs>  Strategic adjustments and personality traits</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Willingness or reluctance to commit errors while attempting speeded responses has been
linked to the concept of impulsivity (Kagan, 1966), and recently correlated with need for
closure (Evans et al., 2017) and brain structure (Forstmann et al., 2010). However, we see
little evidence for a correlation with any self-report impulsivity dimension in our data
(Supplementary Material E; see also Dickman & Meyer, 1988). We also tested correlations
with self-report compliance and the big five personality traits (neuroticism,
extraversion, openness, agreeableness, conscientiousness; Digman, 1990; McCrae & Costa,
2004; McCrae & John, 1992). There were no consistent relationships. The absence of a
correlation with impulsivity measures is particularly notable here, given the conceptual
overlap between impulsivity and a lowered boundary. For example, Metin et al. (2013)
examined whether differences in RT and accuracy in children with attention-
deficit/hyperactivity disorder relative to healthy controls were best captured by
“inefficient” or “impulsive” information processing in the context of the drift diffusion
model. These corresponded to drift rate and boundary separation respectively. Despite the
common terminology, our findings mirror a trend in the impulsivity literature to observe
little to no correlation between behavioural and self-report measures (Sharma et al.,
2014). It remains a possibility that there are non-zero correlations that we did not have
sufficient power to detect. As we discuss in the next section, given that the reliability
of strategic adjustments is suboptimal, we should expect correlations with other variables
to be small.

<hs>  Practical considerations for future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The consistent between-task correlation in strategic adjustment indicates that the extent
to which an individual adjusts their behaviour is not entirely task or domain specific. A
practical consideration for researchers interested in response caution and its strategic
adjustments, and are not specifically interested in a particular cognitive domain (e.g.
response conflict) is that fitting the DMC to our response conflict tasks was
substantially more demanding on time and/or computational resources than fitting the DDM
to a perceptual decision making task. Note that this is not specific to the DMC (White et
al., 2017), but rather reflects more complex models that do not have analytical solutions
that allow faster estimation. Until faster methods can be realised (e.g. Mestdagh,
Verdonck, Meers, Loossens, & Tuerlinckx, 2018), it may be more tractable to use non-
conflict tasks to which the DDM or linear ballistic accumulator (Brown & Heathcote, 2008)
can be applied. The reliabilities of strategic adjustments of response caution that we
observe fall in the range typically interpreted as “moderate” (Cicchetti & Sparrow, 1981;
Fleiss, 1981; Landis & Koch, 1977). We have recently discussed how reliabilities in this
region are potentially problematic for examining individual differences in cognitive tasks
(Hedge, Powell, & Sumner, 2018). The ICC reflects the relative contribution of between-
subject variance (individual differences) and measurement error to variance in the
variable of interest. In order to examine whether adjustments in response caution are
related to trait measures (e.g. personality), we desire variance in our behavioural
measure to also reflect individual differences that are stable over time. When measures
are noisy, correlations with external variables will be weaker and require larger samples
to detect. To put the ICCs we observe in context, they are similar to or exceed those we
observed for several commonly used measures of response control and processing (e.g.
flanker RT cost: 0.50, stop-signal reaction time: 0.43, Navon global precedence: 0; Hedge,
Powell, & Sumner, 2018). Notably in the case of those traditional measures, we did not
observe correlation between tasks in our previous study, despite it being commonly assumed
that they share common mechanisms (see also Rey-Mermet, Gade, & Oberauer, 2017). Here,
with strategic adjustments of response caution, we do consistently observe a correlation
between tasks. Nevertheless, poor reliability corresponds to a reduced ability to detect
correlation using those measures that must be compensated for (e.g. by increasing
statistical power). It is possible that future work would benefit from developments in
model-based analyses, by integrating individual differences measures of interest in to the
parameter estimation (Evans et al., 2017; Turner et al., 2013; Wiecki et al., 2013). Here,
we fit the models to each task and individual independently. In contrast, hierarchical
models describe both the sample and individual simultaneously, as well as allow for
regressors to be used to inform parameter estimation. For example, Evans et al. (2017)
compared three different models when examining the relationship between response caution
and need for closure. They first fit a hierarchical linear ballistic accumulator model in
which parameters were determined by the behavioural data alone. The second model did not
allow for individual differences in response caution, assigning everyone the same value,
though differing between speed- and accuracy-emphasis. In the third model, rather than
estimating response caution from the behavioural data, it was determined by a function
that linked the parameter values to participants’ questionnaire values. Unsurprisingly,
the first (unconstrained) model provided the best fit to the data. However, the third
model outperformed the second, suggesting that there are common individual differences in
the personality questionnaire and behavioural responses. In a second experiment by Evans
et al. this improvement when comparing models contrasted against non-significant
correlations between parameter estimates (and RTs) fit independently and subsequently
correlated with the questionnaire values. Such joint modelling techniques may provide more
powerful tests where appropriate.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

The extent to which an individual prioritises accuracy or speed in choice RT tasks is
commonly discussed but has less often been the focus of interest than individual
differences in cognitive abilities. Here, we provide evidence that questions about
individual differences in caution and its strategic adjustment are at least somewhat
viable. On a given occasion, individuals show consistency in the extent to which they
strategically adjust their levels of response caution across different tasks. Across time
points, individuals show non-zero, but sub-optimal, levels of reliability in strategic
adjustments. Though these levels of reliability raise power concerns for future research,
we believe that our results and previous literature are evidence that there is value in
pursuing such questions.


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<ART>Stable associations between behavioral problems and language impairments across childhood - The importance of pragmatic language problems
================================================================================

Authors: Wenche Andersen Helland, Astri J. Lundervold, Mikael Heimann, Maj Britt Posserud
DOI: 10.1016/j.ridd.2014.02.016
Year: 2014  |  Pages: 943-951
ASJC codes: 3203, 3204
Keywords: Adolescents, Behavioral problems, CCC-2, Language impairments, Pragmatic language deficits

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study investigated language function associated with behavior problems, focusing on pragmatics. Scores on the Children's Communication Checklist Second Edition (CCC-2) in a group of 40 adolescents (12-15 years) identified with externalizing behavior problems (BP) in childhood was compared to the CCC-2 scores in a typically developing comparison group (n=37). Behavioral, emotional and language problems were assessed by the Strengths and Difficulties Questionnaire (SDQ) and 4 language items, when the children in the BP group were 7-9 years (T1). They were then assessed with the SDQ and the CCC-2 when they were 12-15 years (T2). The BP group obtained poorer scores on 9/10 subscales on the CCC-2, and 70% showed language impairments in the clinical range. Language, emotional and peer problems at T1 were strongly correlated with pragmatic language impairments in adolescence. The findings indicate that assessment of language, especially pragmatics, is vital for follow-up and treatment of behavioral problems in children and adolescents. © 2014 The Authors.

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<h>INTRODUCTION</h>
------------

Language is an important tool for social interaction as well as a means to control one's
own and other's emotions and behaviors. Children who are able to use language to regulate
their emotions and behave in a socially appropriate way are more likely to develop good
peer relations and form new friendships (Im-Bolter & Cohen, 2007). Three intersecting
areas of language – form, content, and use – are all essential ingredients for
communication, and impairments within any of these areas may cause problems. The form and
content components characterize language structure, whereas the use component
characterizes pragmatics (Bloom & Lahey, 1978; Spanoudis, Natsopoulos, & Panayiotou,
2007). A growing body of research points to an association between behavioral and language
development, and several studies have reported a substantial degree of overlap between
language impairments and behavioral problems (Cross, 2011; Hill & Coufal, 2005; Mackie &
Law, 2010). Children with language impairments frequently experience behavioral problems,
and conversely, many children with behavioral problems show language impairments
(Gallagher, 1999; Hartas, 2012; Ketelaars, Cuperus, Jansonius, & Verhoeven, 2010).
Although this relationship is well documented in the literature, it seems to be less
recognized in practice, and there is good evidence that language impairments are
substantially underreported in children with psychiatric diagnoses (Cohen, Farnia, & Im-
Bolter, 2013; Im-Bolter & Cohen, 2007; Law & Garret, 2004). Hill and Coufal (2005) claim
that although students with behavioral disorders experience language impairments, their
problems in this domain may be left as an “invisible” or “marginal” handicap unless
systematic assessment is carried out. Symptoms that may be caused by problems in
understanding or producing language may be perceived by adults as non-compliance, social
withdrawal, or inattentiveness (Cohen, 2001). Children with Attention-
Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) commonly present
co-existing problems related to language. Previous research has shown that in a large
population derived sample of 5672 children aged 7–9 years, almost 60% of the children
identified with symptoms of ADHD (n = 290) also fulfilled the criteria for language
impairments compared to 5.7% of the typically developing control group (Helland, Posserud,
Helland, Heimann, & Lundervold, 2012). Furthermore, in a clinical sample of 6–15 year old
children with Asperger syndrome and children with ADHD, 90.5% and 82.1%, respectively,
presented with clinically significant language impairments (Helland, Biringer, Helland,
Heiman, 2012). In their review of studies of language skills in children identified with
emotional and behavioral disorders, Benner, Nelson, & Epstein (2002) found that 71%
experienced clinically significant language impairments. In their study of children aged
7–14 years referred to psychiatric services, Cohen, Menna and colleagues (1998) reported
that children identified with language impairments showed more immature abilities with
respect to resolving interpersonal conflicts than children without language impairments.
Furthermore, parents often perceived these children as problematic and hard to manage
compared to typically developing peers (Law & Garret, 2004). Language impairments refer to
a broad spectrum of difficulties including limited vocabulary, expressive deficits,
phonological deficits, comprehension deficits, and pragmatic language deficits. All these
problems have been reported in studies of children with behavioral disorders (Gallagher,
1999). According to Tannock and Schachar (1996), pragmatic difficulties are the most
frequently reported language problem. Pragmatics refers to the appropriate use and
interpretation of language in different social contexts (Bishop, 1997). Children with
pragmatic language impairments may speak fluently and well-articulated, but they have
problems adhering to the needs of the conversational partner; they may make incorrect
inferences, give conversational responses that are socially inappropriate or tangential,
and interpret language in an over literal manner (Fujiki & Brinton, 2009; Poletti, 2011).
Pragmatic language deficits are clinically relevant because they may have detrimental
effects on the development of successful peer relations and negatively impact the child's
quality of life (Gibson, Adams, Lockton, & Green, 2013). Gilmour, Hill, Place, and Skuse
(2004) found that two-thirds of their sample of children with conduct disorder had
pragmatic language impairments. They also identified pragmatic language deficits in about
two-thirds of a sample of children with antisocial behavior, and suggested that these
deficits may underlie the antisocial behavior. In line with this, Donno, Parker, Gilmour,
and Skuse (2010) argue that pragmatic language deficits should be considered a possible
contributory factor to behavioral problems in primary school children. According to
Leonard, Milich, and Lorch (2011), pragmatic skills provide a unique contribution in the
estimate of the children's social skills above and beyond the contribution of both
hyperactivity and inattention. Recently, Mackie and Law (2010) reported clinical
significant language impairments (pragmatic-, structural- and word decoding difficulties)
in 91% of referred children. These findings strongly indicate that language impairments of
some kind very often accompany behavioral disorders. Several explanations have been
offered to account for the relationship between language- and behavioral problems (see
Hartas, 2012); (1) language difficulties may lead to frustration and anger resulting in
increased problems with social behavior and fewer opportunities to interact with peers,
(2) behavioral problems, like inattention and hyperactivity, may contribute to language
and literacy problems, (3) both language and behavioral difficulties co-exist and
reciprocally influence each other, (4) the two conditions share an underlying deficit that
may explain the association between language and behavioral problems (Hartas, 2012). All
these explanations refer to the strong correlation between the two domains of problems.
This is supported by the tendency that a wide range of problems seems to cluster within
the same individual, and the high rates of comorbidity in child psychiatry (Posserud &
Lundervold, 2013). The Early Symptomatic Syndromes Eliciting Neurodevelopmental Clinical
Examinations model (ESSENCE) has been put forward to describe the more overarching
dysfunction generally encountered within child psychiatry (Gillberg, 2010), and genetic
studies also support the existence of larger, less specific set-ups of genes that together
form a heightened vulnerability to a wide range of problems from intellectual disability
to anxiety and more subtle motor problems (Cross-Disorder Group of the Psychiatric
Genomics Consortium, 2013; Lichtenstein, Carlström, Gillberg, & Anckarsäter, 2010). The
ESSENCE model was conceptualized also because developmental problems seem to change over
time, depending on external factors, where a child may present with language problems in
early childhood and then develop more overt ADHD symptoms in early school age. Inspired by
this model, the current study aim at studying language difficulties within a broader group
defined as having behavioral problems. The majority of studies investigating language
impairments have been based on pre-and primary school children. There is mounting evidence
that many of these children have enduring language problems that may negatively impact
their long-term psychosocial and academic development (Cohen et al., 2013; Conti-Ramsden &
Botting, 2008; Yew & Kearney, 2013). As children reach adolescence, demands on language
competence increase and language skills become even more crucial for establishing and
maintaining social relationships. Inadequate communication may cause misunderstandings,
increase conflicts and deteriorate the quality of friendships, leaving children and
adolescents at risk of stress, loneliness, and mental health problems (Durkin & Conti-
Ramsden, 2010; Leonard et al., 2011). Adolescents with language impairments may see
themselves as less socially accepted than their typically developing peers, and may also
be perceived as withdrawn and unsociable by their peers as well as by their teachers (Im-
Bolter, Cohen, & Farnia, 2013). In a recent study, Cohen and colleagues (2013) reported
that clinic-referred youths aged 12–18 years were significantly impaired relative to a
comparison group on measures of structural as well as higher order language function.
Furthermore, their language impairments were associated with parent ratings of severity of
externalizing psychopathology. The present study aimed to investigate language function in
a group of adolescents with behavioral problems (BP). Based on previous research we
expected to find more language related problems in the BP group than in the general
population in childhood (part A) and in an age matched control group in adolescence (part
B). Due to the importance of pragmatic language ability in adolescence, we finally asked
if a measure of this ability when the adolescent was 12–15 years old could be predicted
from parent reports of behavioral- and language problems approximately five years earlier
(part C).

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

A group of children with behavioral problems (BP) were recruited among participants in the
third phase of the first wave of the Bergen Child Study (BCS). The BCS is a longitudinal
total population study of child mental health that started in 2002 with a screening
questionnaire for all children attending 2nd to 4th grade in any school in the Bergen area
(n = 9430). The response rate was high, with 97% of the teachers and 70% of the parents
completing the BCS screening questionnaire including the Strengths and Difficulties
Questionnaire (SDQ, Goodman, 1999), and four questions related to language function. From
the first wave of the BCS, children were selected to a second and third phase according to
screen status. The third phase (n = 329) consisted of a clinical assessment with the
Wechsler's Intelligence Test for Children – third edition (WISC-III) (Wechsler, 2003) and
the K-SADS-PL (Kaufmann et al., 1997; see Lundervold, Posserud, Ullebo, Sorensen, &
Gillberg, 2011 for more details). The present study included children identified in this
third phase (T1) with high symptom levels of an externalizing disorder according to the
K-SADS-PL (defined by one or more definite symptoms of ADHD, Oppositional Deficit Disorder
(ODD), or Conduct Disorder (CD)). These children were invited to a follow-up study when
they were 12–15 years old (T2). The follow-up assessment included the K-SADS-PL and parent
reports on the Children's Communication Checklist Second Edition (CCC-2; Bishop, 2003;
Norwegian adaptation: Helland & Møllerhaug, 2006) and the SDQ. One child was excluded from
the study because she was younger than the other children (11.11 years at T2), two
children were excluded because of intellectual disability and seven children because the
CCC-2 did not pass the consistency check (invalid). Thus at T2, the BP group consisted of
40 children (32 males, 8 females) in the age range 12–15 years (M = 13.47, SD = 0.82), see
Fig. 1. The study was approved by the Data Inspectorate and the western Regional Committee
for Medical and Health Research Ethics.

        <hss>Comparison group at T2</hss>

        At follow-up (T2), comparisons regarding language abilities were made between the
        BP group and a comparison group (CO) of typically developing children. Thirty-
        seven children (18 males, 19 females) with a mean age of 13.54 years (SD = 1.14)
        who had participated in the Norwegian standardization of the CCC-2 (Bishop, 2003;
        Norwegian adaptation: Helland & Møllerhaug, 2006) served as CO group. The reason
        for using this group as comparison rather than adolescents from the same
        background study as the BP group was that the CCC-2 was only administered in the
        BP substudy of the BCS. The CO group did not have any problems regarding language
        or communication as reported by their parents, nor did they have any known
        learning disabilities or special education needs. The CO group had a more equal
        distribution of males and females compared to the BP group in which the majority
        were males. However, no significant differences were found between males and
        females on the General Communication Composite of the CCC-2; t(35) = 1.60, p =
        .11, which supports the use of the CO group for comparison.

        <hss>Strengths and Difficulties Questionnaire (SDQ): BP group at T1 and T2</hss>

        Parents completed the SDQ as part of the BCS-questionnaire, when the children were
        7–9 years old (T1) and at follow-up (T2) when they were 12–15 years. The SDQ is a
        brief screening questionnaire for behavioral and emotional problems designed for
        children aged 4–16 years. The questionnaire has been extensively validated in
        various countries, and reported internal consistency values (Chronbach's alphas)
        for the various scales have a mean α = .70 (Muris, Meesters, & van den Berg,
        2003). Twenty-five items divided into five subscales (five items in each) are
        measuring emotional problems, conduct problems, hyperactivity–inattention
        problems, peer problems and prosocial behavior. A total difficulties score is
        computed by combining the first four subscales scores. Each item is scored on a
        three-point scale (0 = not true, 1 = somewhat true, and 2 = certainly true). On
        the first four scales a high score indicates problems, while a low score indicates
        problems on the last subscale (prosocial). The subscale scores are ranging from 0
        to 10 and the total difficulty score is ranging from 0 to 40. Separate SDQ
        versions are available for parents, teachers and children, and in the present
        study data from the parent version are presented.

        <hss>Language composite (LC): BP group at T1</hss>

        A set of four items relating to different aspects of language (phonology,
        expressive language, receptive language, and pragmatics) was included in the BCS-
        questionnaire and was completed by the parents. The language items were as
        follows: (1) cannot pronounce certain words or sounds; (2) cannot elaborate,
        explain or express himself or herself; (3) has difficulties understanding things
        that are being said; and (4) has difficulties having a conversation with others.
        These items were scored on a three-point scale, and a language composite score
        with a possible range of 0–8 was included in the present study.

        Children's Communication Checklist Second Edition (CCC-2): BP group and CO group at T2

        The CCC-2 (Bishop, 2003; Norwegian adaptation: Helland & Møllerhaug, 2006) is a
        checklist designed to distinguish children with communication impairments from
        typically developing children and to identify pragmatic as well as structural
        language impairments in children aged 4–16 years. The checklist is to be completed
        by an adult who has regular contact with the child, in the present study it was
        completed by parents. A total of 70 items are grouped into 10 subscales (see Table
        2) with seven items in each. The separate subscales assess speech, syntax,
        semantics, inappropriate initiation, stereotyped language, use of context, non-
        verbal communication, social interaction, and interests. The questionnaire is
        scored on a 4-point scale, indicating the frequency of the communicative behavior
        described, with a high raw score indicating poorer performance. An automatic
        scoring program that comes with the CCC-2 (Bishop, 2003) converts raw scores into
        scaled scores with a mean of 10 and a SD of 3. The first four scales measures
        structural aspects of language, the next four scales measure pragmatic aspects and
        the two last scales measure non-linguistic behavior. By summing the scaled scores
        of the first eight subscales, an overall measure of language abilities, the
        General Communication Composite (GCC), is derived. This composite is effective at
        discriminating children with communication impairments from typically developing
        children. In accordance with previous findings using the CCC-2 in a Norwegian
        sample, cut-off at or below 64-scaled scores on the GCC was selected for
        identifying children with language impairments (Helland, Biringer, Helland, &
        Heimann, 2009). An additional composite, the Social Interaction Deviance Composite
        (SIDC), is also computed to identify children with pragmatic impairments
        disproportionate to their structural language abilities. A negative SIDC implies
        that the child experiences difficulties with social interaction that are
        disproportionate to his/her general communication abilities. However, according to
        the manual (Bishop, 2003), this composite should only be interpreted if the GCC is
        below cut-off; an exception is scores of −15 or less, as such an extreme result is
        of clinical significance even with GCC within normal limits. Although not included
        as part of the CCC-2, a general pragmatic composite (PC) has been calculated in
        several studies (Bignell & Cain, 2007; Geurts & Embrechts, 2008; Helland, Helland,
        & Heimann, 2012). This is done by summing the scaled scores of the scales
        measuring coherence, inappropriate initiation, stereotyped language, use of
        context and, nonverbal communication (scales D–H). The PC was computed and used
        for analyses in part B of the present study. In the British standardization sample
        Bishop (2003) reported internal consistency values between .66 and .80 and inter-
        rater reliability between parents and teachers ranging from .16 to .79 for the
        CCC-2. The Norwegian version also presents with good internal consistency with
        alpha ranging from .73 to .89 and inter-rater reliability ranging from .44 to .76
        (Helland et al., 2009).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

All statistical analyses were run using SPSS, version 21. Part A: One-sample t-tests were
conducted on the SDQ and the LC to evaluate whether the means of the BP group were
significantly different from the means of the total population-based sample in the BCS,
from which the BP group was derived when they were 7–9 years (T1). Part B: Students
independent-samples t-tests were used to analyze differences between the BP and CO groups
at T2 on a general measure of language abilities (GCC) and the subscales of the CCC-2.
Bonferroni corrections were conducted due to multiple comparisons (alpha level of .005),
and Cohen's d was computed to evaluate effect sizes. According to general guidelines, d's
of 0.20, 0.50 and 0.80 should be interpreted as small, medium, and large, respectively.
Part C: Longitudinal predictions for the BP group from 7–9 years (T1) to 12–15 years (T2)
were investigated by running correlation analyses (Pearson product moment correlation)
between SDQ and LC scores at T1 and the PC at T2, and a backward multiple regression
analysis to evaluate whether SDQ and LC scores (T1) predicted pragmatic language abilities
as measured by the PC at follow-up four years later (T2). See Table 5 for the sequence of
variables included in the analysis. Additionally, correlation analyses were conducted to
compare SDQ subscale scores at T1 and T2, and LC scores at T1 and T2.

<hs>  Part A: language abilities at 7–9 years (T1)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The BP group differed significantly (was more impaired) from the total sample on the total
difficulties score and all subscale scores of the SDQ as well as on the LC at T1 (Table
1).

<hs>  Part B: language abilities at 12–15 years (T2)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the BP group altogether 70% (28 out of 40 children) obtained a GCC score in the
clinical range. For the comparison group the corresponding number was 10.8% (four out of
37 children). On the SIDC, 13 out of the 28 children in the BP group identified with
communication impairments obtained a score indicating pragmatic impairments that were
disproportionate to structural language abilities. Additionally, one child scored in the
clinical range (below −15) although his GCC was in the normal range. In the CO group three
out of the four children identified with communication impairments showed disproportionate
pragmatic impairments. A comparison between the two groups on the GCC revealed that the
scores for the children in the BP group were significantly lower than the scores for the
CO group (t(75) = 6.46, p < .001). As shown in Table 2, significant differences were found
on all but one subscale (i.e., scale A measuring speech). The effect sizes (Cohen's d)
were moderate for speech (0.6) and high (ranging from 0.8 to 1.9) for all subsequent
subscales.

<hs>  Part C: predictions from 7–9 years (T1) to 12–15 years (T2)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

At follow-up (T2), SDQ and LC data were available for 29 out of the 40 children in the BP
group. Bivariate correlation analyses between SDQ data from T1 and T2 showed highly
significant correlations, with Pearson r ranging from .56 (conduct) to .69 (hyperactivity)
(Table 3). Bivariate correlation analyses between LC data from T1 and T2 were
statistically significant, Pearson r = .49, p < .01. Bivariate correlation analyses showed
that the SDQ scales, measuring emotional problems, peer problems, total difficulties, and
the LC at T1 correlated significantly with the PC reported at T2, see Table 4. To examine
whether SDQ and LC (T1) could predict pragmatic language abilities in adolescence (T2), a
backward multiple regression analysis included the SDQ subscales (emotional problems,
conduct problems, hyperactivity problems, peer problems, pro-social behavior) and the LC
score as predictors and the PC as the criterion variable. A significant regression
equation was found F(2, 37) = 10,56, p < 001 (model 5), with an R2 of .363. Thus, the
predictors accounted for 36% of the variance in pragmatic abilities at T2. The SDQ scale
measuring peer problems and the LC both had significant effects on the PC; with beta
values of −0.34 and −0.39, respectively (Table 5). Tolerance tests and VIF (variable
inflation factor) did not indicate multicollinearity. The analyses were repeated for the
prediction of the overall GCC score, showing that only the LC score at T1 independently
predicted GCC score at T2 (beta value of −0.49; p = .001).

<h>DISCUSSION</h>
----------

The present study followed a group of children with behavioral problems, investigating
their language function in adolescence, and whether language function and mental health at
7–9 years predicted later pragmatic language impairment. The cross-sectional analyses of
part A and B, exploring whether the children with behavioral problems at age 7–9 and 12–15
years could be differentiated from a typically developing comparison group regarding their
language profiles, showed that children with BP scored higher on parent reported language
problems in the general population at 7–9 years of age, and also obtained poorer scores on
9 out of 10 subscales of the parent form of CCC-2 at 12–15 years. In the longitudinal
analyses of part C, peer problems and language problems reported in the BP group at 7–9
years were shown to be significant predictors of pragmatic language abilities in
adolescence, whereas the overall measure of language abilities (GCC) was only predicted by
the parent report on the four questions regarding language problems. As predicted, the
group with behavioral problems scored significantly poorer than the comparison group on
the GCC. Language impairments were far more common, with the vast majority (70%) scoring
in the clinical range. Our findings confirm results reported by Benner and colleagues
(2002) in their review of language impairments in children with emotional and behavioral
disorders, as well as a report of language impairments (structural-, pragmatic-, decoding
problems) in the majority of a sample of children with behavior causing concern at school
(Mackie & Law, 2010). In our sample, the distribution of children with BP primarily
displaying problems related to pragmatics (35%) and those displaying mainly structural
language problems (35%) were quite equal. These findings are comparable to those of Donno
and colleagues (2010) who identified pragmatic language deficits in 42% of their sample of
disruptive children. Furthermore, they are in line with those reported by Gilmour and
colleagues (2004) and Mackie and Law (2010), who found that two-thirds of their samples
showed significant pragmatic language deficits. Our findings were somewhat more modest
than in the last studies, which may be due to the fact that our BP group was identified as
part of a population-based study. Still, the BP group differed significantly (more
impaired) from the CO group on all the pragmatic subscales of the CCC-2, emphasizing that
pragmatics is an area of language that is highly vulnerable in children with behavioral
problems. These findings are in line with the results from a former study where children
diagnosed with ADHD were found to differ significantly from typically developing children
on the pragmatic subscales (Helland, Helland, et al., 2012). The CCC-2 profile revealed
that the group of children with behavioral problems was impaired relative to the
comparison group regarding all aspects of language except on the scale measuring speech.
Conflicting results have been reported regarding speech; Geurts and Embrechts (2008) and
Helland, Helland, et al. (2012) reported unimpaired speech in studies of children with
ADHD, whereas Helland, Biringer and colleagues (2012), in a study of children with
Asperger syndrome (AS) and children with ADHD, found that these clinical groups showed
impaired speech relative to controls. A possible explanation for the finding of unimpaired
speech in the present study may be that when children reach adolescence they may have
outgrown their speech problems, while difficulties related to semantics, pragmatics and
social relations are more likely to persist. Alternatively, initial speech problems,
although no longer present, may have contributed to pragmatic impairments becoming more
pronounced in adolescence as social situations grow more demanding and complex. Although
the children with behavioral problems were inseparable from the comparison group on the
scale measuring speech, they demonstrated significant impairments on the other scales
measuring language structure, indicating that their language difficulties were not
restricted to pragmatics but did affect other aspects of language as well. The latter
finding aligns well with the recent results reported for clinic – referred adolescents by
Cohen and colleagues (2013) as well as with our former studies of language impairments in
children with ADHD, AS and typically developing controls (Helland, Biringer, et al., 2012;
Helland, Helland, et al., 2012). The observed differences between the two groups on the
CCC-2 scales measuring interests and social relations may indicate that children with
behavioral problems experience considerable problems as far as friendship and peer
acceptance are concerned, thus putting them at risk for increased levels of behavioral
problems and mental health problems more generally. Language problems at T1 were only
reported by parents on four general language items targeting a wide and unspecific range
of language problems that can affect children. Still, the composite score on these four
items predicted language problems as assessed by the CCC-2 five years later, even after
controlling for psychopathology in the group of children with BP. Such a relationship over
such a long time-span is almost surprising, underscoring the need for taking parental
concerns of their child's difficulties seriously and to follow up their worries with
further assessment. The significant prediction of pragmatic language abilities in
adolescence from peer problems and language problems reported by parents in childhood,
underline the close association between communicative abilities and social functioning The
problems reported in childhood appear not to be transient; rather they seem to persist
into adolescence, negatively affecting the development of successful social relationships,
which may again lead to escalating behavioral problems.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

Some limitations should be considered when evaluating the findings of the present study.
The diversity of diagnostic subgroups within the BP group, children with ADHD, and
children with ODD/CD symptoms, might be considered a limitation as small sample sizes
prevent us from reporting separately for the diagnostic groups. On the other hand, the
strong association in this heterogenic group shows that language should be an area of
great concern irrespective of the nature of the behavioral problems. As only children in
the BP substudy of the BCS performed the CCC-2, the comparison group at T2 was chosen from
the sample of the Norwegian CCC-2 normative sample, where the gender distribution was
different from the BP group. This could potentially have overstated the differences
between the BP and the CO group; however, there were no gender differences in the CCC-2
scores in the CO group. The fact that language evaluations were solely based on parental
reports is another limitation, and firm conclusions about the predictive value of early
language problems awaits future large-scaled longitudinal studies. Finally, although we
have stated that peer problems in this study predict pragmatic language deficits, the
reverse could also be true. Pragmatic language deficits most definitely cause peer
problems, and so the relationship between social difficulties and pragmatic language
deficits is likely to be bidirectional.

<h>CONCLUSIONS</h>
-----------

Bearing in mind that language is commonly not an area receiving great attention in
children with behavioral problems, our findings have some important clinical implications.
Firstly, language assessment should be an integral part of the assessment procedure when
children and adolescents are referred to mental health services with behavioral problems.
Secondly, as pragmatic language deficits contribute to difficulties resolving
interpersonal conflicts with others, pragmatics abilities should be an area of special
concern taken into consideration when interventions and therapy plans for adolescents with
behavioral problems are developed. Furthermore, it is possible that the lack of overt
speech problems in children with behavioral problems may mask severe communicative
problems. As most therapies are strongly language-based, verbal input should be modified
to match the language level of the adolescents, the use of non-literal language should be
monitored, and the clinician should be aware that what may appear as non-compliance may in
fact result from problems understanding.


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<ART>Subliminal or not? Comparing null-hypothesis and Bayesian methods for testing subliminal priming
================================================================================

Authors: Anders Sand, Mats E. Nilsson
DOI: 10.1016/j.concog.2016.06.012
Year: 2016  |  Pages: 29-40
ASJC codes: 3204, 3205
Keywords: Bayes factor, Null-hypothesis significance testing, Signal detection theory, Subliminal priming

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

A difficulty for reports of subliminal priming is demonstrating that participants who actually perceived the prime are not driving the priming effects. There are two conventional methods for testing this. One is to test whether a direct measure of stimulus perception is not significantly above chance on a group level. The other is to use regression to test if an indirect measure of stimulus processing is significantly above zero when the direct measure is at chance. Here we simulated samples in which we assumed that only participants who perceived the primes were primed by it. Conventional analyses applied to these samples had a very large error rate of falsely supporting subliminal priming. Calculating a Bayes factor for the samples very seldom falsely supported subliminal priming. We conclude that conventional tests are not reliable diagnostics of subliminal priming. Instead, we recommend that experimenters calculate a Bayes factor when investigating subliminal priming.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Exposure to a perceivable stimulus may influence or “prime” a response to another
stimulus, even when the priming stimulus is just noticeable. More controversial are claims
of priming induced by imperceptible or “subliminal” (i.e., below the threshold of
perception) stimuli. Although many studies claim to have demonstrated subliminal priming,
the phenomenon is still debated (Newell & Shanks, 2014). The debate continues because it
is difficult to prove the subliminal part of the claim–that the prime stimulus was not
perceived, not even slightly, by any observer–and thereby to rule out an alternative
explanation of the observed priming: that it is solely attributable to the responses of
observers who just barely perceived the prime. The main strategy to find support for
subliminal priming has been to try to demonstrate a dissociation between a direct measure
of prime stimulus perception and an indirect measure of prime stimulus processing
(Reingold & Merikle, 1988). Two statistical methods are conventionally used to find
statistical support for dissociation: a double t-test and a regression method. Here we
simulate these methods and a less often used method based on Bayesian statistics. The
simulations suggest that the latter method, but not the former methods, is suitable for
evaluating whether experimental data support subliminal priming.

<hs>  Experiments on subliminal priming</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In a typical experiment examining subliminal priming, a sequence of stimuli is shown in
each trial. First, one of two priming stimuli is briefly flashed, followed by a masking
stimulus (to allow the priming stimulus to be processed but not perceived), and then a
target stimulus is shown. Observers have two tasks in the experiment, one direct task
regarding the prime stimulus (the direct measure) and one indirect task regarding the
target stimulus (the indirect measure). In a typical experiment, the tasks are performed
in separate blocks, beginning with the indirect task. In the direct task, observers decide
which of the two possible priming stimuli was presented. For example, in a study by
Kiefer, Sim, and Wentura (2015), the priming stimulus was an emotionally positive or
negative stimulus and the direct task was to decide whether the prime stimulus was
positive or negative. In analyzing data from such tasks, one of the two stimuli may be
arbitrarily designated the “signal” and the other the “non-signal,” and the four possible
stimulus answer combinations may be classified as hits (responding “signal” to the “signal
stimulus”), misses, false alarms (responding “signal” to “non-signal” stimulus), and
correct rejections. According to signal detection theory, the observer’s sensitivity, d′,
to differences between the two stimuli is d′ = Φ−1(ph) − Φ−1(pf), where ph is the
proportion of hits, pf the proportion of false alarms, and Φ−1 is the inverse standard
normal cumulative distribution function (Macmillan & Creelman, 2005). Response bias, that
is, the tendency to choose one over the other stimulus, may be quantified as the response
criterion, i.e., c = −½[Φ−1(ph) + Φ−1(pf)]. For an unbiased observer, c = 0, because the
proportions of hits and correct rejections are equal. In typical experiments, the direct
measure of prime stimulus perception is d′. The indirect task varies depending on the type
of priming the experimenter is examining. In a typical experiment, the indirect measure of
prime stimulus processing is a congruency effect on reaction time for responses to the
indirect task. Kiefer et al. (2015), also used a positive or negative stimulus as the
target stimulus and the direct task was to decide whether the target stimulus was positive
or negative. When the priming stimulus was incongruent with the target stimulus, the
reaction time in the task was slower than if the priming and target stimuli were
congruent. This type of congruency effect is the indirect measure of prime stimulus
processing in typical experiments.

<hs>  Statistical analysis of subliminal priming</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The most common analytical method, here called the double t-test method, is to apply two
t-tests, one for each of the two measures, and decide for or against subliminal priming
based on the pattern of the p-values (see Table 1), typically using α = 0.05.
Specifically, the double t-test method declares subliminal priming if (a) mean performance
in the direct measure does not differ statistically significantly from chance (p > α) and
(b) the mean effect in the indirect measure does differ statistically significantly from
zero (p < α). The double t-test method is open to criticism on statistical grounds,
because deciding whether the prime stimulus is subliminal is based on an unjustified
interpretation of how the obtained p-values relate to the tested null hypothesis, H0:
“True mean d′ = 0.” Specifically, the p-value is the conditional probability of obtaining
the data or more extreme data given H0 [P(D|H0)], and therefore say nothing about the
probability of H0 [P(H0)] (see e.g., Dienes (2014) and Gallistel (2009) for a good
discussion of null hypothesis testing in the context of non-significant results). The
double t-test method has also been criticized as the method often lacks the power needed
to support that observers were subliminal (e.g., Finkbeiner & Coltheart, 2014; Gallistel,
2009; Macmillan, 1986; Rouder, Morey, Speckman, & Pratte, 2007; Wiens, 2006). Proponents
of the double t-test method are also of course aware of this, but would argue that the
strategy still can, and indeed does, do a good job of identifying subliminal priming.
Therefore, the double t-test remains the most popular analytical method in research into
subliminal priming (e.g., González-García, Tudela, & Ruz, 2015; Huang, Tan, Soon, & Hsieh,
2014; Jusyte & Schönenberg, 2014; Kido & Makioka, 2015; Kiefer et al., 2015; Lin & Murray,
2015; Marcos Malmierca, 2015; Norman, Heywood, & Kentridge, 2015; Ocampo, 2015; Ocampo,
Al-Janabi, & Finkbeiner, 2015; Schoeberl, Fuchs, Theeuwes, & Ansorge, 2015; Wildegger,
Myers, Humphreys, & Nobre, 2015). The double t-test method tests for subliminal priming at
a group level. Observers, however, differ in their thresholds (e.g., Albrecht & Mattler,
2012; Dagenbach, Carr, & Wilhelmsen, 1989; Greenwald, Klinger, & Schuh, 1995; Haase &
Fisk, 2015; Sand, 2016). To take individual differences in thresholds (and thus
perception, given a specific prime stimulus intensity) into account, another conventional
analysis is regression analysis (e.g., Jusyte & Schönenberg, 2014; Ocampo, 2015; Schoeberl
et al., 2015; Xiao & Yamauchi, 2014). In regression analysis, the direct measure is used
as the regressor and the indirect measure is the outcome variable. Specifically, the
regression method declares subliminal priming if the intercept is statistically
significantly above zero. Because these two conventional methods (double t-test and
regression) remain popular today, we tested their robustness through simulations in which
we assumed no dissociation between the direct and indirect measures. One analytical
strategy not yet in widespread use is to calculate a Bayes factor to test whether or not a
prime stimulus is subliminal at a group level. Calculating a Bayes factor, B, is the
Bayesian equivalent of a null hypothesis significance test. The improvement of Bayesian
statistics over null-hypothesis testing here is that B can lend support to H0 (which the
p-value cannot) and H0 is what experimenters in this field want to support (Dienes, 2015).
To calculate B, an a priori model of H1 (“True mean d′ slightly above 0”) needs to be
specified. (See Dienes, 2015, for a discussion of how H1 can be specified with regard to
subliminal priming.) Once H1 is specified, B can be calculated and it is the ratio of the
likelihood of the observed data based on the two hypotheses, that is, P(D|H1)/P(D|H0). B >
1 thus indicates that the data support H1 over H0, while B < 1 indicates that the data
support H0 over H1, and a B of approximately 1 suggests that the experiment was not
sensitive. Although B is continuous, it has been suggested that B > 3 can be considered
“substantial” evidence for H1, whereas a Bayes factor of 1/3 can be considered
“substantial” evidence for H0 (Jeffreys, 1998). This criteria of B > 3 roughly corresponds
to an α level of 0.05. We follow these criteria here when evaluating B. By calculating B,
then, experimenters can test whether the data support subliminal priming (see Table 1).
Curiously, a mixed strategy has also been used in which the direct measure is tested using
B, whereas a p-value is still used to test the indirect measure (e.g., Norman et al.,
2015). This mixed method is probably used because the main advantage of B over the p-value
is when H0 is the hypothesis of interest. Here we compare how these two newer methods,
which we call the double B method and the mixed method, perform when applied to the same
samples as used in the conventional tests of subliminal priming.

<h>SIMULATION PROCEDURE</h>
--------------------

We used simulations to evaluate the various scenarios described below. A simulation
approach is motivated by the mathematical complexity of the scenarios, involving discrete
and asymmetric distributions of observed d′ values (cf Miller, 1996). Using the
statistical software R (see Electronic Supplementary Material for all scripts), we
simulated scenarios in which we assumed no dissociation between the direct and indirect
measures. The purpose of the simulations was to evaluate the extent to which the different
analytical methods would incorrectly provide support for subliminal priming although all
priming was actually supraliminal, that is, only participants who truly perceived the
prime stimulus were primed by it. Following Miller (2000), we simulated an experiment in
which d′ was used as a measure of an observer’s ability to detect a prime stimulus (direct
measure of perception, d′d) and of the priming effect of the same stimulus on the
observer’s performance on a related task (indirect measure of processing, d′i). Simulation
4 differs in that we used a congruency effect on reaction time as the indirect measure.
(For an example experiment using d′ as both the direct and indirect measures, see
Greenwald et al., 1995.) In the simulations, true sensitivity will be measured for each
observer using a number, nd and ni, of two alternative forced-choice trials. This means
that observed sensitivity will be a result of true sensitivity and random error in the
measurement. We will denote the observed sensitivity d′ to distinguish it from true
sensitivity, d′.

<hs>  Assumptions</hs>
  ~~~~~~~~~~~

The simulations were based on the following assumptions: (a) Performance on both the
direct and indirect measures follows from the assumptions of the Gaussian equal-variance
model of signal detection theory (Macmillan & Creelman, 2005). (b) The observed d′-values
are composed of a true component, d′ (true sensitivity), and an error component that is
independent of the true sensitivity and has an expected value of zero. (c) An observer’s
true sensitivity remained constant during all trials of the experiment.1 (d) Observers’
true response criteria in both measures were unbiased, c = 0.2 (e) In all simulations,
except the last, d′d = d′i. This implies absence of subliminal priming, because priming
(d′i > 0) only happened for observers who perceived the prime stimulus (d′d > 0). (f) All
N observers provided one observed d′d, based on nd trials used to measure direct prime
stimulus perception, and one observed d′i, based on ni trials used to measure indirect
prime stimulus processing.

<hs>  Simulation procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

The simulation procedure was as follows. (1) Observers d′d and d′i were sampled randomly
from a specified bivariate distribution of d′-values (d′d = d′i in all except Simulation
5). The observers’ response criteria in the two measures were set to zero (i.e., cd = ci =
0). (2) A true probability correct score was calculated for each observer from the true
d′-values. For an unbiased observer (c = 0), the true proportion correct is Φ(d′/2) where
Φ is the standard normal cumulative distribution function (Macmillan & Creelman, 2005).
Thus, pd = Φ(d′d/2) and pi = Φ(d′i/2). (3) The observed proportion of hits in the direct
measure (phd) was simulated for each observer by randomly drawing a number from the
binomial distribution based on pd and nd/2 and dividing that number by nd/2. The observed
proportion of false alarms in the direct measure (pfd) was similarly simulated based on 1
− pd and nd/2. We simulated proportion hits and false alarms in the indirect measure in
the same way. Observed proportions were determined from true scores plus the random error
inherent in the set of binomial trials. (4) We calculated d′d as Φ−1(phd) − Φ−1(pfd) and
d′i as Φ−1(phi) − Φ−1(pfi). (5) We subjected the set of d′d and d′i to the analyses of
interest and stored the exact p-value and corresponding B. (6) We repeated steps one to
five 10,000 times and used the stored p-values and B to calculate the proportions of each
analytical outcome. To calculate B, we needed to specify both H0 and H1. H0 is easy to
specify in the present application, namely true d′d = 0 and true d′i = 0 for the direct
and indirect tests, respectively. For H1, the a priori probability of different possible
population values needs to be specified. We wanted to specify H1 for the effect “observers
(at a mean level) were marginally able to perceive the prime stimulus but lower
sensitivities are more likely than higher sensitivities”. Based on previous experimental
conditions using very difficult to perceive but not subliminal stimuli (e.g., Atas,
Vermeiren, & Cleeremans, 2013; Haase & Fisk, 2015; Sand, 2016; Schoeberl et al., 2015), we
chose to represent this using a normal distribution with a mean of 0 and a standard
deviation of 0.2 but with the probability of values below 0 set to 0 (i.e., a half-normal
distribution). That is, H1 was “true mean d′ slightly above zero, with larger d′ having
smaller probabilities and d′ > 0.4 being improbable”; i.e., using the notation from Dienes
(2015) we used a BH(0,0.2) to specify H1.

<h>SIMULATION 1: DISCRETE DISTRIBUTION OF D′</h>
-----------------------------------------

In the first simulation, we assumed a discrete bivariate distribution of true
sensitivities in which 60% of observers could not perceive the prime stimulus and were not
primed by it (d′d = d′i = 0) and 40% of observers could marginally perceive the prime
stimulus and were primed by it (d′d = d′i = 0.2). This unrealistic but simple distribution
was chosen to illustrate how random error will influence observed scores. In this
simulation, 40 observers were drawn from this distribution (i.e., 24 observers d′d = d′i =
0 and 16 observers d′d = d′i = 0.2). In this simulation, true mean d′s across observers
was thus 0.08 (0.2 × 0.4). Observed d′d was based on nd = 100 trials and d′i was based on
ni = 200 trials, as previous studies have typically used more trials in the indirect than
the direct task (e.g., Jusyte & Schönenberg, 2014; Kiefer et al., 2015; Lin & Murray,
2015; Ocampo, 2015; Schoeberl et al., 2015). Fig. 1 illustrates one sample drawn from this
distribution. Although d′d = d′i assumed only two values (0 or 0.2), random error arising
from the limited number of trials introduced variation in observed scores (Fig. 1A and B).
In this sample, mean d′d was 0.04 (SE = 0.04) and mean d′i was 0.07 (SE = 0.03). We
applied the double t-test method, mixed method and double B method to these data to
compare the three methods. The double t-test resulted in p-values of 0.36 for d′d and 0.02
for d′i (illustrated in Fig. 1C as 95% confidence intervals). The double t-test method
would therefore falsely indicate that subliminal priming occurred in this sample.
Calculating B for the direct measure (with BH(0,0.2)) resulted in a B of 0.51. This B does
not suggest that the sample was subliminal but rather that the data are inconclusive
(encouraging experimenters to collect more data; a valid procedure using Bayesian
statistics, Dienes, 2011). Thus, neither the mixed method nor double B method would
support subliminal priming for this data-set. This simulation example (Fig. 1) followed
the expected pattern of the results of 10,000 simulations (Table 2). This result suggests
that the conventional double t-test method is unreliable but that calculating B for the
direct measure is more reliable. Because the double B method reaches much the same
conclusion as does the mixed method, we will omit reporting the results of the mixed
method in the following simulations.

<h>SIMULATION 2: HALF-NORMAL DISTRIBUTION OF OBSERVER SENSITIVITIES</h>
----------------------------------------------------------------

The discrete bivariate distribution of true sensitivities used in the previous simulation
is of course not realistic. A more realistic distribution would include variation in true
sensitivities between observers. True d′-values below zero are implausible in most
applications, however, because a negative true d′ would imply that the non-target stimulus
on average evoked stronger evidence for the target stimulus than did the target stimulus
itself, or vice versa. Observed d′-values slightly below zero may of course occur due to
random error. Therefore, in Simulation 2, a half-normal distribution with parameters μ = 0
and σ = 0.1 (corresponding to the standard deviation of the full normal)3 was used for d′d
= d′i. In this simulation, true mean d′s across observers were 0.08. Otherwise, this
simulation was identical to Simulation 1. We applied the double t-test method and double B
method again in this more realistic simulation. We also tested a follow-up analysis
(subgroup analysis) sometimes used to strengthen the support for subliminal priming and
the regression method mentioned above.

<hs>  Double t-test and double B method.</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The result of applying the double t-test and double B method is summarized in Table 3.
Again, the double t-test method would often encourage experimenters to wrongly conclude
that subliminal priming had occurred. In comparison, the double B method would often
encourage experimenters to collect more data or to conclude that the priming was
supraliminal. As Bayesian statistics is relatively insensitive to stopping rules, simply
collecting more data when B is inconclusive (1/3 > B > 3) is a valid procedure (Dienes,
2011). To test the robustness of this approach we assumed that in the samples B was
inconclusive with regards to d′d (7.81%), researchers would test more observers, reanalyze
their data after each observer and stop when a decisive B was reached. Using such a
stopping rule would increase false support of H0 (B < 1/3) to 8.29%. As such, even when
using such an “extreme” stopping rule, the double B approach would outperform the double
t-test approach.

<hs>  Subgroup analysis</hs>
  ~~~~~~~~~~~~~~~~~

As experimenters are aware of the problems associated with claiming that a prime stimulus
is subliminal based on a non-significant p-value, experimenters sometimes perform an
additional analysis to support their conclusion. We call this analysis subgroup analysis
and it entails dividing participants based on their observed d′d and basing the t-tests
only on those who perform close to chance (e.g., Huang, Lu, & Dosher, 2012; Lin & Murray,
2015; Marcos Malmierca, 2015; Palmer & Mattler, 2013; Züst et al., 2015). The idea behind
this is straight forward: If the indirect effect is apparent in the subgroup that performs
worse, then the effect should be subliminal. How “performance close to chance” is
operationalized varies between studies (e.g., based on median split of d′d or on the
binomial distribution). To test this analysis in this simulation, for each sample, we
excluded participants performing above the 97.5th percentile of expected d′d given d′d and
100 trials (subsampling based on other cut-offs led to similar results). We then applied
the double t-test and double B only on the remaining subsample. In different samples
between 0 and 25% of observers were excluded in this manner (mean 6%, standard deviation
4%-points). The result is not encouraging for the subgroup analysis. The double t-test
method suggested subliminal priming in 54% of the subsamples and the double B method
suggested subliminal priming in 17% of the subsamples. Both methods therefore perform
worse when applied to a subgroup of participants than to the full sample.4 The reason for
this is regression to the mean. Although d′d and d′i are perfectly correlated in this
simulation, d′d and d′i are not (see Fig. 1). As such, an observer with a d′d of 0.2 may,
due to random error, produce a d′d close to chance. However, the same observer is unlikely
to be as unlucky in d′i, and is therefore more likely to perform close to his or her true
sensitivity (d′i = 0.2). As such, subgroup analysis based on d′d trivially leads to a non-
significant direct measure (or B < 1/3) without guaranteeing only subliminal effects in
the indirect measure. For a Bayesian approach to sorting participants as subliminal or
not, see Morey, Rouder, and Speckman (2009).

<hs>  Regression method</hs>
  ~~~~~~~~~~~~~~~~~

Another method of testing subliminal priming is via regression analysis. This method is
sometimes used as the main analysis or as an additional analysis after the double t-test
method (e.g., Jusyte & Schönenberg, 2014; Ocampo, 2015; Schoeberl et al., 2015; Xiao &
Yamauchi, 2014). In this analysis, d′d is used as the regressor and d′i as the outcome
variable. The idea is that if priming is independent of awareness then (a) the intercept
should be above zero and/or (b) there should be no correlation between d′d and d′i. We are
sympathetic to this method as the idea is to take individual variability in prime
perception (d′d) into account. However, using simulations, Dosher (1998) and Miller (2000)
have already demonstrated that regression analysis is not robust in this application. In
short, random error in the predictor variable leads to underestimation of the correlation
and, in turn, an overestimation of the intercept. One criticism of Miller’s simulations
was that they were based on very large sample sizes irrelevant to most actual experiments
(Klauer & Greenwald, 2000). Therefore, we decided to replicate Miller’s results by
applying regression analysis in this simulation, where N = 40. Recall that in this
simulation we assumed a perfect correlation between d′d and d′i and an intercept of zero.
Regression analysis using null-hypothesis significance testing applied on the observed
scores, however, resulted in 66% statistically significant intercepts and 62% non-
significant correlations. We therefore verify that Miller’s conclusions are also valid for
sample sizes more common in experiments. Having previously seen that the Bayesian approach
performed better than the double t-test, we also decided to test the intercept by
calculating B (with BH(0,0.2)). Here, however, when H1 was the hypothesis of interest, the
Bayesian approach did not outperform conventional tests but resulted in 61% of intercepts
supporting subliminal priming (B > 3). The reason that the regression approach is not
reliable is error in the regressor. Therefore, to take error in both variables into
account, we also tested the application of an orthogonal (Deming) regression (Ripley &
Thompson, 1987). We then tested the resulting intercept using a p-value and B. Although
the orthogonal regression controlled the error rate somewhat, 46% (p < α) and 42% (B > 3)
of intercepts still supported subliminal priming. In conclusion, we agree with Dosher and
Miller that regression analysis is not a robust way of testing subliminal priming.

<h>SIMULATIONS 3A AND 3B: VARYING PARAMETERS</h>
-----------------------------------------

A strength, but also a difficulty, of simulation is that it forces the researchers to
explicitly specify all the assumptions on which a simulation is based. Of importance here
is the underlying distribution of d′d and d′i. This distribution varies between
experiments and, in any case, the true underlying distributions are unknown. Furthermore,
experiments vary in their sample size (N) and number of trials (n) used. Therefore, we
decided to vary these parameters based on previous studies (e.g., González-García et al.,
2015; Huang et al., 2014; Jusyte & Schönenberg, 2014; Kido & Makioka, 2015; Kiefer et al.,
2015; Lin & Murray, 2015; Marcos Malmierca, 2015; Norman et al., 2015; Ocampo, 2015;
Ocampo et al., 2015; Schoeberl et al., 2015; Wildegger et al., 2015) systematically in two
simulations.

<hs>  Simulation 3A</hs>
  ~~~~~~~~~~~~~

In Simulation 3A, we varied the underlying distribution of d′ and the sample size (N). We
varied the underlying distribution by using various σ’s of the half-normal distributions,
as shown in Fig. 2A. We then sampled from these distributions using various values of N.
In all other respects, this simulation was identical to Simulation 2. For each combination
of distribution and sample size, we ran 10,000 simulations. For each simulation, we
applied the double t-test and double B method and noted the probability of false support
for subliminal priming (p > 0.05 for d′d and p < 0.05 for d′i or B < 1/3 for d′d and B > 3
for d′i). Fig. 2B and C summarizes the results of this simulation. The y-axis shows the
probability of false support for subliminal priming. For the double t-test method, there
is a curvilinear relationship between the two parameters and false support: As the σ or N
increases, the power of the indirect measures increases and thus also the proportion of
support for subliminal priming. As the parameters increase beyond a certain point,
however, the power of the direct measure also increases and the proportion of support for
subliminal priming decreases. As for the double B method (Fig. 2C), this method is more
robust under all parameter settings.

<hs>  Simulation 3B</hs>
  ~~~~~~~~~~~~~

In the simulations so far, more trials were used for the indirect than the direct measure,
as this is a common practice in experiments (e.g., Jusyte & Schönenberg, 2014; Kiefer et
al., 2015; Lin & Murray, 2015; Schoeberl et al., 2015). The difference in the number of
trials results in smaller error (and thus more power) in the indirect than the direct
measure. To test the impact of this, in Simulation 3B we therefore systematically varied
nd and ni. In all other respects, however, the simulation was identical to Simulation 2.
For each combination of nd and ni we applied the double t-test and double B method and
noted the probability of false support for subliminal priming. Fig. 3A and B summarizes
the results of this simulation. The y-axis shows the probability of false support for
subliminal priming. For the double t-test method, although a greater number of nd and ni
reinforces the probability of false support, an equal number of trials does not completely
eliminate the issue (24% and 18% false support when nd = ni = 100 and 200, respectively).
With this particular distribution and N, approximately 400 nd were necessary to reduce the
proportion of false support for subliminal priming to 5%. As for the double B method, this
method is again more robust under all parameter settings. The use of too few trials will
usually result in a B encouraging experimenters to collect more data.

<h>SIMULATION 4: REACTION TIME</h>
---------------------------

In the previous simulations d′ has been used for both the direct and indirect measures.
This simplifies the presentation because the outcomes of both measures are on the same
scale. In actual experiments a more common indirect measure is a congruency effect
(between the prime and target stimulus) on reaction time (RT). We wanted to demonstrate
that the results of the previous simulations generalize to experiments using a congruency
effect as the indirect measure. Simulation 4 was identical to Simulation 1 except that the
indirect measure was a congruency effect between median RT in incongruent – congruent
trials. To simplify the simulation, we used the discrete distribution of d′d used in
Simulation 1: that is, two types of observers were simulated, perceivers (40%, d′d = 0.2)
and non-perceivers (60%, d′d = 0). We assumed no dissociation between the direct and
indirect measures. In short, perceivers had a true congruency effect and non-perceivers
did not. An ex-Gaussian distribution, i.e., a mixture of a normal and an exponential
distribution, was used to model the positive skewness of RT data. The parameter values of
the ex-Gaussian distribution are the μ and σ of the normal distribution and the mean of
the exponential distribution. Here we obtained parameter values from Miller (1988). For
all participants, RTs in congruent trials were drawn from an ex-Gaussian distribution with
μ = 300 and σ = 50 and a mean of the exponential distribution of 300. As non-perceivers
could not differentiate congruent and incongruent trials, their RT in incongruent trials
was drawn from the same distribution as for congruent trials. Thus, non-perceivers’ true
congruency effect was 0 ms. As perceivers could perceive the prime, their true RT was
modeled as slower in incongruent than congruent trials and was drawn from an ex-Gaussian
distribution with μ = 450 and σ = 50 and a mean of the exponential distribution of 150 ms.
That is, perceivers’ true median difference (congruency effect) was 48 ms. In this
simulation, true mean d′d across observers was thus 0.08 (0.2 × 0.4) and true mean across
observers RT effect was 19.2 ms (48 × 0.4). This is representative of priming effect sizes
previously reported in studies of subliminal priming (Dehaene & Changeux, 2011; Kouider &
Dehaene, 2007; Van den Bussche, Van den Noortgate, & Reynvoet, 2009). For all observers,
100 trials were used to sample RT from the relevant distribution in each condition. Table
4 summarizes the results of applying the double t-test and double B method in the two
simulations. To calculate B for the indirect effect, H1 was specified as a normal
distribution with a mean of 30 ms and a standard deviation of 10 ms (i.e., BN(30,10); for
d′d BH(0,0.2)). This model of H1 was based on priming effect sizes previously reported in
studies of subliminal priming (Dehaene & Changeux, 2011; Kouider & Dehaene, 2007; Van den
Bussche et al., 2009). As we can see, the results of the previous simulations generalized
to a simulation using a congruency effect on RT as the indirect measure.

<h>SIMULATION 5: TRUE SUBLIMINAL EFFECTS</h>
-------------------------------------

The previous simulations suggest that, due to random error in the measurements, the double
t-test method leads to a high rate of false support for subliminal priming. Perhaps random
error can also hide true subliminal priming? We tested this with a final simulation
identical to Simulation 2 except that d′d was set to 0 for all observers (that is, we
assumed that d′d and d′i were dissociated). Table 5 summarizes the results of applying the
double t-test and double B method in this simulation. As can be seen, only 4% (α = 5%) of
the direct measures were significant and very few simulations led to B > 3 for the direct
measure. We conclude that random error lead to very few missed instances of subliminal
priming for either analytical method. The slightly greater conservatism in classifying
samples as subliminal when calculating B stems from the random error inherent in using
only 100 trials to measure perception. Erring on the side of caution is not necessarily a
fault, however. An inconclusive B will encourage researchers to collect more data; a valid
procedure using Bayesian statistics, Dienes, 2011).

<hs>  Measurement error</hs>
  ~~~~~~~~~~~~~~~~~

In the simulations, assumption (c) (see Section 2.1 above) was that the observers’ true
sensitivity remained constant during all trials of the experiment. This means that the
measurement error simulated here is the random error inherent in the binomial nature of
the two alternative forced-choice methods. As the simulations illustrate, such random
error affects the conclusions that can be made. Another type of measurement error, not
simulated here, stems from the fact that an observer’s true sensitivity may not remain
constant throughout an experiment. Because of lapses of attention, motivation, or fatigue,
a participant may perform sub-optimally. If such attention-driven measurement error
affects both the direct and indirect measures similarly, this type of measurement error
would not constitute a serious problem for experimenters investigating subliminal priming.
However, because the direct task is often more difficult and is often performed at the end
of the experiment, the direct measure may be more negatively affected by such measurement
error (Newell & Shanks, 2014; Pratte & Rouder, 2009). Other factors that also have been
suggested to negatively affect performance in the direct measure is task instructions (Lin
& Murray, 2014) and prime-target stimuli similarity (Vermeiren & Cleeremans, 2012). As
this would lead to underestimation of d′d, this would increase the risk of false support
for subliminal priming beyond what the present simulations suggest.

<hs>  Effect size in the indirect measure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In simulations 1–3, d′ was used for both the direct and indirect measures. This ensured
that the true effect size was the same in both measures (because d′d = d′i). As actual
experiments often use different outcome variables for the direct and indirect measures
(e.g., d′d and a congruency effect on RT), the effect size and thus power do not need to
be similar for the two measures. Perhaps marginally or infrequently perceiving a prime
stimulus (d′d slightly above 0) could produce relatively strong congruency effects. This
would lead to samples in which the mean d′d may approach chance but median priming effects
are subtantial. As this would lead to more power in the indirect measure, the previous
simulations may underestimate the extent of false support for subliminal priming in the
literature.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

The main result of the present simulations is that conventional tests of subliminal
priming are not robust. A non-significant direct measure combined with a significant
indirect measure does not constitute a reliable diagnostic of subliminal priming, as this
result is common even when the only participants who are primed also perceive the prime.
Furthermore, finding priming among a subgroup of observers performing close to chance is
not a reliable diagnostic of subliminal priming because of random error in the direct
measure. If anything, grouping observers based on performance on the direct measure leads
to more error than does analyzing the full sample. Finally, as already suggested by Miller
(2000), regression analysis will often result in a statistically significant intercept
even though there is no dissociation between the direct and indirect measures. In summary,
the tests of subliminal priming commonly used in the literature do not support the
conclusion experimenters want to make. These simulations do not suggest that subliminal
priming cannot occur or that it has not occurred in various studies. However, they do
indicate that, with the experimental parameters used in many studies (e.g., González-
García et al., 2015; Huang et al., 2014; Jusyte & Schönenberg, 2014; Kido & Makioka, 2015;
Kiefer et al., 2015; Lin & Murray, 2015; Marcos Malmierca, 2015; Norman et al., 2015;
Ocampo, 2015; Ocampo et al., 2015; Schoeberl et al., 2015; Wildegger et al., 2015), the
error rate of falsely declaring priming to be subliminal can be as high as 30–50% (Figs. 2
and 3). This casts doubt on the strength of the evidence for some types of subliminal
priming reported in the literature. In all simulations, testing subliminal priming based
on Bayesian statistics outperformed the conventional analyses and was much less likely to
falsely declare subliminal priming. This is because the Bayes factor distinguishes between
data that support H0 and data that are inconclusive, which the p-value cannot do. Our
recommendation for experimenters interested in subliminal priming is therefore to use
Bayesian statistics to determine whether the examined prime stimulus is subliminal. Dienes
(2015) presents a good discussion of how H1 can be specified in this context. Note,
however, that calculating a Bayes factor tests only whether or not mean performance is at
chance levels. A Bayes factor that supports H0 (i.e., B < 1/3) does not imply that the
prime stimulus was subliminal for all participants. As such, even B < 1/3 does not exclude
the possibility that priming was in fact was driven by a few observers who perceived the
prime. The main difficulty in supporting a claim that priming is subliminal is that
observers differ in their absolute thresholds (e.g., Albrecht & Mattler, 2012; Dagenbach
et al., 1989; Greenwald et al., 1995; Haase & Fisk, 2015; Sand, 2016). This means that a
certain prime stimulus intensity will likely be subliminal for some observers and
supraliminal for others. Estimating a threshold for each observer on the other hand, may
also be problematic (Rouder et al., 2007). It is therefore unfortunate that the regression
approach based on taking individual variability in perception into account has a large
error rate. However, part of the reason why regression often fails in this context is a
lack of range in d′d. This occurs because experimenters try to use a prime stimulus
setting that is subliminal for all observers. For another approach that use a range of d′d
for which regression analysis is more robust, see Sand (2016) or Haase and Fisk (2015).
There is a growing concern about false positive psychology (Simmons, Nelson, & Simonsohn,
2011) and the replicability of psychological findings (Open Science Collaboration, 2015).
We submit that false positive findings may arise from faulty interpretation of non-
significant results. Problems associated with interpreting p > α (failure to reject H0)
and how this situation could be improved by Bayesian statistics, have been discussed at
length elsewhere (Dienes, 2014; Gallistel, 2009). Our simulations also suggest that false
positives may well be replicable if several experimenters use similar paradigms and
questionable analytical strategies. We therefore hope that the field of subliminal priming
will start using other experimental designs and statistical approaches to test subliminal
priming.


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<ART>Taking their eye off the ball: How shyness affects children's attention during word learning
================================================================================

Authors: Matt Hilton, Katherine E. Twomey, Gert Westermann
DOI: 10.1016/j.jecp.2019.01.023
Year: 2019  |  Pages: 134-145
ASJC codes: 3204, 3205
Keywords: Individual differences, Language development, Referent Selection, Shyness, Temperament, Word learning

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The current study tests the hypothesis that shy children's reduced word learning is partly due to an effect of shyness on attention during object labeling. A sample of 20- and 26-month-old children (N = 32) took part in a looking-while-listening task in which they saw sets of familiar and novel objects while hearing familiar or novel labels. Overall, children increased attention to familiar objects when hearing their labels, and they divided their attention equally between the target and competitors when hearing novel labels. Critically, shyness reduced attention to the target object regardless of whether the heard label was novel or familiar. When children's retention of the novel word–object mappings was tested after a delay, it was found that children who showed increased attention to novel objects during labeling showed better retention. Taken together, these findings suggest that shyer children perform less well than their less shy peers on measures of word learning because their attention to the target object is dampened. Thus, this work presents evidence that shyness modulates the low-level processes of visual attention that unfold during word learning.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Reports on the development of language usually begin by celebrating children’s remarkable
ability to learn words. For example, it is often stated that by the time of their second
birthday, children have typically acquired a vocabulary of more than 300 words (Fenson et
al., 1994). Although these summaries are an impressive illustration of the speed of
language acquisition, they often ignore an equally fascinating aspect of early language
acquisition—its variability. For example, on closer examination, the data also show that
10% of 2-year-old children are able to produce more than 528 different words, whereas the
10% at the opposite end of the scale produce fewer than 66 different words. Interestingly,
the majority of children in the bottom 10% will show no later difficulties with language
development (Kelly, 1998). Research into variability in early language acquisition
typically focuses on the role of environmental factors. We know that wide-ranging
extrinsic factors such as socioeconomic status (SES), birth order, and differences in
daycare quality exert an effect on children's language development. For example, it has
been consistently shown that children from more affluent backgrounds acquire language more
quickly than their less well-off peers (Hoff-Ginsberg, 1991). Similarly, children with
older siblings show an earlier grasp of pronoun use than first-born children (Oshima-
Takane, Goodz, & Derevensky, 1996) and, unsurprisingly, children in higher-quality daycare
show advanced language and communication skills (Burchinal, Roberts, Nabors, & Bryant,
1996). The mechanisms underlying extrinsic effects on language development are often also
explained in terms of the environment. Taking SES as an example, many argue that children
raised in better-off families acquire language more quickly because their language input
is easier to learn from (Hirsh-Pasek et al., 2015), contains more words overall (Hart &
Risley, 2003), contains a greater variety of word types (Hoff, 2003), and is more likely
to be in a child-directed register (Rowe, 2008). Thus, these accounts argue that the
effect of SES on language development can be attributed to the effect of SES on children’s
language input. Yet, variability during development is not only present in the environment
but also exists within children. Even from birth, children show marked differences in
their reaction to the environment. Some babies are consistently quick to settle after
stressful events (e.g., sudden loud noises or inoculations), whereas others are highly
reactive to such events, as demonstrated by a display of intense motor reaction and
distress (e.g., Kagan & Snidman, 1991; Worobey & Lewis, 1989). Throughout development,
further individual differences in response to the environment emerge. Some infants become
easily distracted, whereas others show no difficulty in focusing attention on toys or
events for long periods of time (Rothbart, 1981). Thus, such myriad individual differences
suggest that, even given identical input, two children taken at random could process this
input very differently. We know that individual differences in children's behavioral
style, better known as temperament (Rothbart, 1981), can explain some variability in early
language development. Differences in children's inhibition and discomfort in novel social
situations (i.e., shyness; Putnam, Gartstein, & Rothbart, 2006), have been consistently
shown to affect children’s language development. Shyness is negatively correlated with
vocabulary size when measured via parent-report checklists of children’s vocabulary (Paul
& Kellogg, 1997; Slomkowski, Nelson, Dunn, & Plomin, 1992), and these differences in
productive vocabulary have also been confirmed experimentally, with shyer children being
found to speak less than their less shy peers in both familiar and unfamiliar settings
(Asendorpf & Meier, 1993; Crozier & Badawood, 2009; Evans, 1987). Various explanations
have been put forward to explain the relation between shyness and measures of language
development. Some have argued that shyness affects the propensity to respond (e.g., Smith
Watts et al., 2014). According to this account, shyness does not affect language
development per se; instead, shy children are less likely to demonstrate their language
skills, leading to their reduced scores on language measures. Others argue that shyness
exerts an effect on language development indirectly by modulating the environment; shyer
children are likely to reduce their interactions in novel social settings and, in this
way, restrict their exposure to language in comparison with less shy peers (e.g., Evans,
1993). This suggestion has some support, for example from Evans (1996), who found that
children who are consistently reticent to talk in social settings, rather than those who
are just slow to warm up, show reduced scores on tests of language ability. Generalization
across previous reports of the relation between shyness and language is problematic due to
differences in the precise operationalization and measurement of shyness. Whereas some
have measured individual temperamental differences by examining children’s responses in a
face-to-face task (e.g., Slomkowski et al., 1992), the difficulty with such an approach is
that it does not allow any certainty that the measure reflects stable individual
differences. It is possible that “shy-type” behaviors are exhibited during a single
session for more transient reasons (e.g., tiredness). Other studies have dealt with this
issue by capitalizing on caregivers’ experience of their children’s enduring behavioral
style, using parent-report measures of shyness (e.g., Asendorpf & Meier, 1993). The Early
Childhood Behavior Questionnaire (ECBQ; Putnam et al., 2006) is one such parent-report
standardized measure of children’s temperament subdivided into different scales, one of
which measures shyness by asking parents to indicate how often their child exhibits shy-
type behaviors such as turning away from strangers and showing hesitation in approaching
unfamiliar children. A recent account based on Putnam et al. (2006) approach argued that
shyness can affect language development by modulating the low-level processes by which
language is acquired (Hilton & Westermann, 2017). Shyer children demonstrate an avoidance
of eye contact during social interaction (Putnam et al., 2006), indicating that shyness
modulates attentional processing during these interactional episodes, and there is
evidence that shyness may also modulate children’s allocation of attentional resources in
the absence of social interaction: Pérez-Edgar and Fox (2005) demonstrated in a screen-
based cueing task that whereas less shy children attended preferentially to cued locations
associated with a reward, shyer children preferentially attended to locations associated
with a penalty. Given that the earliest stages of language learning are governed at least
in part by the cognitive systems that underlie attentional focus abilities (e.g., Dixon &
Hull Smith, 2008), it is likely that any effects of shyness on attentional processing
could also affect language learning. Much work on the critical role of attentional
processes during language learning has examined how externally directing children’s
attention affects their formation and retention of novel word–object mappings. Typically,
children are presented with referent selection trials on which one novel object is
presented alongside familiar competitors and experimenters record whether children select
the novel object when asked for a novel label (e.g., “Where’s the blicket?” ; Horst &
Samuelson, 2008). Then, after a 5-min break, children’s retention of this newly formed
mapping is tested. Critically, by manipulating key elements of this task, such as the
number and nature of the familiar competitors, researchers have uncovered evidence to
suggest that children’s attention during the presentation of objects and their
corresponding labels affects their learning of these word–object mappings. For example,
Axelsson, Churchley, and Horst (2012) drew children’s attention to the novel object during
labeling by flashing a light underneath it and partially covering competitors and
demonstrated that children retained novel word–object mappings better under these
conditions than when the novel object was only pointed to during labeling or when the
light and covering were presented individually. Such work indicates that children who
focus attention on targets during labeling are better able to learn the word–object
mappings, and related work demonstrates that attention to the target can be modulated by
extrinsic cues such as novelty (Horst, Scott, & Pollard, 2010; Kucker & Samuelson, 2012).
Given the critical role of attention in successful word learning, it is possible that
shyness affects language learning by modulating attentional processes during labeling
episodes. However, there has been little examination of the intrinsic factors that may
drive these differences in attention. Hilton and Westermann (2017) were the first to test
whether attentional processes during word learning are affected by shyness. In their
study, 24-month-old children were presented with sets of three objects, one of which was
novel and two of which were familiar. When asked for a novel object using a novel word,
shyer children selected objects at chance levels, whereas less shy children reliably chose
the novel object. Furthermore, after a 5-min break, shyer children did not retain any of
the (few) novel word–object mappings that they had formed during referent selection,
whereas less shy children showed evidence of retaining these mappings. The authors argued
that these findings could be explained in terms of differences in attention during
labeling. Specifically, shyer children’s aversion to novelty (Kagan, Reznick, & Snidman,
1988) may have reduced their attention to the target (novel) object during labeling,
disrupting encoding and, thus, formation of the word–object mapping. Of course, given that
Hilton and Westermann’s (2017) study only measured children’s manual object selection, it
was impossible to directly demonstrate whether shyness affected children’s word learning
via attention during referent selection. Thus, the current study aimed to examine this
possibility using a novel adaptation of the looking-while-listening paradigm (Fernald,
Zangl, Portillo, & Marchman, 2008; Swingley, 2011). Children were presented with images of
one novel object and two familiar objects on a screen, and their eye gaze across the
objects was recorded while a familiar or novel label was heard. As well as providing a
highly detailed picture of children’s online processing, this approach has the advantage
of measuring implicit behavior. An explicit response, such as pointing at an object as in
Hilton and Westermann’s (2017) study, has a social dimension, and it is possible that the
random responses exhibited by shy children in that study related to social expectation.
Recording eye movements in a task without an experimenter present addresses this
possibility. In this study, we explored whether shyness as measured by the ECBQ modulates
children’s attention to target objects during labeling. Based on the assumption that
children’s mapping of a novel label to a novel object involves ruling out potential
competitors (Halberda, 2006; Horst et al., 2010), children’s looking to competitor objects
should be a critical step in the formation of a novel word–object mapping. However, in
line with previous research (Axelsson et al., 2012; Horst et al., 2010), we expected that
children who were better able to focus their attention on the novel object following this
initial disambiguation would be better able to retain the mapping. Therefore, we also
tested whether looking during labeling could predict retention of word–object mappings and
whether this relation changes over development, as demonstrated in previous work (Bion,
Borovsky, & Fernald, 2013).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 32 typically developing 20- to 26-month-old children took part in the study.
All children were monolingual English speakers. There were 16 children in the 20-month age
group (M = 20 months 13 days, range = 19 months 11 days to 21 months 5 days; 8 girls). An
additional 3 20-month-old children were excluded due to failure to complete the task (n =
2) or experimenter error (n = 1). There were also 16 children in the 26-month age group (M
= 26 months 13 days, range = 25 months 19 days to 27 months 0 days; 8 girls). An
additional 2 26-month-old children were excluded due to equipment failure (n = 1) or
failure to complete the task (n = 1). These sample sizes are in line with previous
research using a similar methodology (Twomey, Ma, & Westermann, 2018) and provide more
than 80% power at the p < .05 level to detect an effect size of 0.56 in mutual exclusivity
(referent selection) tasks (Bergmann et al., 2018; Lewis & Frank, 2018). Families were
recruited by contacting parents who had previously indicated interest in participating in
child development research. Parents’ travel expenses were reimbursed, and children were
offered a storybook to thank them for participating. Written informed consent was provided
by the participants’ parents. Prior to the study, parents completed the Oxford CDI
(Hamilton, Plunkett, & Schafer, 2000), a British English adaption of the widely used
MacArthur–Bates Communicative Development Inventory (Fenson et al., 1994). Vocabulary
scores for 3 20-month-old children were not available because their parents failed to
return the questionnaire. These missing values were replaced by the mean score. The
20-month-old group produced a mean of 127 words (range = 17–413) and understood a mean of
252 words (range = 104–413). The 26-month-old group produced a mean of 179 words (range =
158–386) and understood a mean of 347 words (range = 217–416). All vocabulary scores were
within the normal range (Floccia, 2017; Frank, Braginsky, Yurovsky, & Marchman, 2017). As
expected, the 26-month-old children had larger receptive and productive vocabularies than
the 20-month-old children [receptive: t(30) = 3.81, p < .001; productive: t(30) = 4.61, p
< .001)].

<hs>  Stimuli and design</hs>
  ~~~~~~~~~~~~~~~~~~

During their visit to the lab, children took part in referent selection trials, which were
presented on a computer screen, and retention trials based on their selection of the
actual three-dimensional (3D) objects. Visual stimuli for referent selection trials
consisted of digital photographs of known and novel objects. For each participant, the 12
referent selection pictures were randomly grouped into sets of 3, with each set comprising
one novel object and two familiar objects, so that the objects comprising each set were
consistent for each participant but varied across participants. Novel objects were a
plastic tripod, a wooden roller, a wooden dumbbell. and a plastic tea strainer, the same
novel objects used with a similar age group in a previous study (Hilton & Westermann,
2017). Known objects were toy versions of the following vehicles, animals, and household
items: car, motorbike, elephant, fish, pig, ball, fork, and spoon. Each picture was of
similar size on the screen (∼700 × 800 mm). Each novel object was assigned one of four
pseudowords (cheem, koba, sprock, or tannin) chosen to be plausible pseudowords in English
and having been used in previous word learning studies (Halberda, 2006; Horst & Samuelson,
2008; Markson & Bloom, 1997; Samuelson & Horst, 2007). For each trial, a short video was
created. Each video began by showing the set of pictures bouncing onto the screen,
accompanied by a short bouncing sound effect, in order to focus children’s attention on
the screen at the beginning of the trial. Once the objects had finished bouncing (2000 ms
after the start of the video), the audio stimulus automatically began playing. Audio
stimuli consisted of three labeling phrases spoken by a male native British English
speaker in infant-directed speech. The target object label appeared in the final position
of each labeling phrase (“Look, there’s a _____! Where’s the _____? Wow, it’s a _____!”).
The three labeling phrases were in the same order on all trials. Label onsets were 2500,
5200, and 9100 ms after stimulus onset, and the final label offset was at 10,000 ms. Once
the auditory stimulus had finished playing, the objects stayed on the screen for a further
2000 ms before disappearing and leaving the screen clear for the next trial. All
participants took part in 12 referent selection trials. Each set of pictures was presented
three times; on 2 trials children heard the novel label (novel trials), and on 1 trial
children heard one of the two familiar object labels (randomly selected; familiar trials).
The order in which the sets were presented was randomized. The location of each object (on
the left, in the center, or on the right) was pseudorandomized across trials, ensuring
that the target did not appear in the same location on more than 2 successive trials, and
the order of trial types was pseudorandomized, ensuring that a trial type (i.e., novel or
familiar label) was not repeated more than three times in a row. Seven 3D objects were
used for retention trials. Three randomly selected familiar objects (e.g., toy duck, car,
and fork) acted as stimuli for the initial warm-up trials, and the four novel objects of
which children saw images during referent selection were stimuli on test trials.

        <hss>Shyness questionnaire</hss>

        During their visit, parents completed the shyness scale of the ECBQ (Putnam et
        al., 2006). The ECBQ is a standardized parent-report measure of 18- to 36-month-
        old children’s emerging temperament, and the shyness scale asks parents to rate
        from 1 to 7 (1 = never, 7 = always) how often over the previous 2 weeks their
        children had demonstrated shy-type behaviors (e.g., “When playing with unfamiliar
        children, how often did your child seem uncomfortable?”). The average score across
        the 12 questions (Cronbach’s α = .86) for each child was calculated, resulting in
        a score between 1 (not at all shy) and 7 (extremely shy). To avoid demand biases
        in parents’ responses, three other questions taken from one other unrelated
        subdimension (perceptual sensitivity) were included in the questionnaire.

        <hss>Referent selection trials</hss>

        During referent selection, children were seated centrally 50 to 70 cm in front of
        a computer screen on their parent’s lap. A Tobii X120 eye tracker located beneath
        the screen recorded children’s eye gaze, and a video camera above the screen
        recorded parents and children throughout the procedure. Parents were instructed
        not to look at the screen or speak to their children as the videos were playing so
        as to avoid influencing their children’s behavior, and the experimenter monitored
        the testing session via a camera to ensure that this instruction was followed.
        Prior to the experiment starting, children’s eye gaze was calibrated using a
        5-point calibration procedure. A child-friendly animation (a wobbling duck) was
        displayed in the four corners and center of a 3 × 3 grid accompanied by a jingling
        sound, and calibration accuracy was checked and calibration was repeated if
        necessary. Once the calibration procedure was completed, the referent selection
        trials were presented.

        <hss>Data coding and cleaning</hss>

        The sampling rate of the eye tracker was 60 Hz, and the raw data files were
        exported from Tobii Studio (Version 3.4) and analyzed in R (R Core Team, 2017).
        Three rectangular areas of interest (AOIs) were defined as the three areas of the
        screen where the stationary stimuli were displayed. All AOIs measured 385 by 408
        pixels. AOI 1 covered the object on the left-hand side of the screen, AOI 2
        covered the object in the middle, and AOI 3 covered the object on the right-hand
        side. There was a margin of 107 pixels between AOIs. Continuous gaze within an AOI
        was counted as a fixation. If continuous gaze within an AOI was interrupted for
        less than 60 ms, this interruption was recoded as a continuation of that fixation
        because the interruption was most likely due to eye blinks rather than children
        rapidly reorienting their attention (see Yu & Smith, 2011). All analyses were
        conducted on children’s looking times from 233 ms after the first label onset to
        allow for saccade preparation (Canfield & Haith, 1991; Haith, Hazan, & Goodman,
        1988) until 12,000 ms when the objects disappeared from the screen.

        <hss>Retention trials</hss>

        After the 12 referent selection trials, children took a 5-min break by playing in
        an adjacent room, in line with Horst and Samuelson (2008). Children then took part
        in retention trials during which they sat on their parent’s lap at a table
        opposite the experimenter. Retention trials consisted of a three-alternative
        forced-choice task in which participants were required to select a target object
        from an array in response to a target word requested by the experimenter, a
        typical task used to measure children’s mapping of words to objects (e.g., Waxman
        and Booth, 2001; Dysart, Mather, & Riggs, 2016; Samuelson & Horst, 2007). Prior to
        the retention test trials, a series of warm-up trials was presented to ensure that
        children understood the task and were responding appropriately to the
        experimenter’s requests. On each warm-up trial, children were presented with three
        randomly selected familiar objects side by side on a tray divided into three
        sections. These familiar objects had previously acted as competitor objects during
        referent selection. After allowing children to look at the objects for 3 s, the
        experimenter requested one of the objects (e.g., “Where’s the car?”) before
        sliding the tray forward and allowing children to make their choice by pointing at
        or retrieving the object. On the next trial, the objects were rearranged out of
        sight of the children and another object was requested. These trials continued
        until children had correctly selected the target object on three consecutive
        trials. Across the initial three trials, each object was requested once and the
        target object appeared in each location on the tray once. On any further trials,
        the position of the target was randomly determined. To encourage participation,
        children’s correct responses were praised and corrections were offered when
        children did not at first select the correct object. Following the warm-up trials,
        the retention trials began. The procedure for retention trials was identical to
        that for warm-up trials except that no praise or corrections were offered so as to
        avoid biasing children’s responses. Instead, once children had selected an object,
        the experimenter replied “thank you” in a neutral tone, replaced the object, and
        then began the next trial. Across the 4 retention trials each novel object acted
        as the target once, and on each trial two other randomly selected novel objects
        acted as competitors. Pictures of these same novel objects had been presented
        during referent selection, and the experimenter requested the target object using
        the novel word with which it had appeared during referent selection. The order of
        trials and the position of the target on the tray were randomized.

<hs>  Looking during referent selection</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To establish whether shyness and trial type affected overall looking time, we submitted
raw looking times to a linear mixed-effects model (LMEM) with main effects of shyness
score (mean centered), competitor or target fixation (hit type; for all models, dummy
coded: target = 1, Competitor 1 = 0, Competitor 2 = 0), and trial type (for all models,
dummy coded: familiar = 1, novel = 0) and their interactions, by-participant random
intercepts and slopes, and by-target random intercepts and slopes. Results are reported in
Table 1 with significant predictors highlighted in bold. Initial analyses revealed no main
effect of, or interactions with, age group, so we collapsed across this factor. All LMEMs
were conducted using the lme4 package Version 1.1–12 in R Studio Version 3.2.4 (R Core
Team, 2017) and had maximal random effects structures simplified until convergence (Barr,
Levy, Scheepers, & Tily, 2013). The p values for fixed effects were obtained using
sequential likelihood ratio tests. Overall, children looked more at the competitors than
at the target (negative main effect of hit type), but children’s attention to targets and
competitors differed according to trial type (significant hit type × trial type
interaction). Follow-up post hoc tests were performed on the hit type × trial type
interaction using the multcomp package Version 1.4–7 (Hothorn, Bretz, & Westfall, 2008),
revealing that on familiar label trials children looked at the target more than at
competitors (z = 4.87, p < .001), but this difference was not found on novel label trials
(z =  − 0.79, p > .99), as shown in Fig. 1. Table 1 also shows an interaction between
shyness score and hit type. As can be seen in Fig. 2, this interaction could likely be
explained by a negative relation between shyness and target looking, whereas no relation
is visible between shyness and competitor looking. To examine whether this interpretation
was supported by the data, we analyzed looking to the competitors and looking to the
target in separate LMEMs. The results revealed that shyness was indeed related to target
object looking [beta = 0.27, SE = 0.12, t =  − 2.34, χ2(1) = 4.95, p = .026] but not to
competitor object looking [beta = 0.12, SE = 0.11, t = 1.08, χ2(1) = 1.18, p = .28]. This
finding demonstrates that shyer children looked less at the target object during labeling
in comparison with less shy children. However, shyness was not associated with children’s
attention to the competitor objects.

<hs>  Retention trials</hs>
  ~~~~~~~~~~~~~~~~

We next wanted to examine whether shyness and target looking during referent selection
predicted retention scores. To do this, raw looking time to each novel target during
referent selection was calculated. Retention trials were scored as 1 if children correctly
retained the novel word–object mapping and as 0 if they did not. Trials on which no
response was offered (n = 5) were excluded from the analyses. Given the previously
observed differences in retention of word–object mappings between our two age groups (Bion
et al., 2013), age group was reintroduced as a predictor in these models (dummy coded:
20-month group = 0, 26-month group = 1). Therefore, we submitted retention scores to a
binomial LMEM with fixed effects of age, shyness score, and novel target looking during
referent selection and by-participant and by-target random intercepts. Results are
presented in Table 2 with significant predictors highlighted in bold. The positive main
effect of target looking is evidence that looking to the target during labeling supports
retention of the label–object association. However, children overall failed to retain any
word–object mappings at levels better than chance, t(30) = 1.25, p = .22. The absence of a
main effect of shyness suggests that retention and shyness were not directly related.
However, because the results from the referent selection trials indicate that shyness
modulates attention during labeling, this result leaves open the possibility that shyness
could affect word learning. We return to this point in the Discussion.

<h>DISCUSSION</h>
----------

The current work set out to examine whether shyness affects the processes modulating
attention during labeling and children’s subsequent word learning. In line with previous
research, we found that familiar labels encouraged target looking, whereas novel labels
led to equal competitor and target looking. Critically, however, we found that shyness was
linked to a reduction in children's attention to the target object regardless of whether
it was familiar or novel. Furthermore, although we found no evidence of retention at the
group level, we found that individual infants’ increased attention to the target during
referent selection was positively related to retention of the novel word–object mappings.
As expected, we found differences in looking depending on whether a familiar or novel
label was heard. On familiar label trials, children were processing an already-learned
word–object association and so showed heightened attention to the target object in
comparison with competitors. Such behavior is in line with previous research showing that
children focus attention on known objects that are being labeled (Fernald, Pinto,
Swingley, Weinbergy, & McRoberts, 1998). In contrast, we also found that on hearing a
novel label, children spread their attention equally across the competitors and the
target, likely because the novel label trials entail disambiguation, requiring children to
first rule out competitors as potential referents before mapping the novel label to the
novel object (Halberda, 2006). This finding offers converging evidence that initial
attention to competitors is a crucial aspect of novel word disambiguation (Axelsson et
al., 2012; Halberda, 2006; Horst et al., 2010). Importantly, shyness reduced children's
attention to the target object, regardless of whether the target was novel or familiar.
This finding suggests that shyness modulates children's attention to labeled objects
generally, and this is in line with Hilton and Westermann's (2017) finding that shyness
affected not only children’s formation of novel word–object associations but also their
selection of familiar referents. Interestingly, shyness did not affect overall looking
time to the object array, suggesting that shyness did not reduce attention to the task
but, critically, modulated attentional patterns across the potential referents. Thus, the
current work supports the theory that shy children’s reduced performance during referent
selection is related to their reduced attention to the target object rather than to a
failure to engage with the task (Hilton & Westermann, 2017). Given the complex interplay
of attention during labeling, there are several potential mechanisms to explain the effect
of shyness on target looking. Shy children’s aversion to novelty (Kagan et al., 1988) may
have caused children to look away from the novel object in favor of the familiar objects,
but this explanation would also predict that shyness has no effect on target looking on
familiar label trials. This was not what we found: Shy children looked less at targets on
both trial types. Conversely, shyer children might have shown heightened attention to the
novel object because we know that children attend more to stimuli that they find aversive
(Field, 2006). However, this explanation does not support the finding that shyer children
show reduced target looking on novel label trials. Because we know that shyness is linked
to difficulty in engaging with novelty (Kagan et al., 1988), we argue that it is most
likely that for shy children the novelty inherent in such a labeling episode (i.e.,
presence of a novel object and label, presentation in a novel voice) disrupts the ongoing
attentional processes required to form the word–object association. This disruption is
also pervasive enough to reduce shy children’s ability to focus attention on the referent
of a familiar label. A critical contribution of the current work is that we found an
effect of shyness on responses during referent selection even when no social interaction
was required. Given shy children’s aversion to novel social stimuli (Putnam et al., 2006),
it is unsurprising that shy children show difficulty in responding to experimental tasks
that are presented face to face (Crozier & Hostettler, 2003) and that shy children show
differences in processing stimuli that are strongly associated with social interaction
such as faces (Matsuda, Okanoya, & Myowa-Yamakoshi, 2013). The current work, however,
finds a relation between shyness and attention during referent selection even when no
explicit response is required and when no unknown adults are present. Thus, the relation
between shyness and attention seems robust across contexts—even those contexts that do not
require or prompt social interaction. This finding suggests that we must be vigilant to
possible effects of shyness when designing and interpreting results of developmental
research. Unlike the referent selection trials, retention trials presented children with
3D objects. Nonetheless, a relationship between attention during referent selection and
retention was found across this change in task: Although children overall looked equally
across competitors and target on novel label trials, attention to the novel target was
positively related to retention. Put differently, children who looked more to novel
targets during labeling were more likely to retain the novel label–object mappings. Thus,
results from the retention trials highlight the critical role of attention in predicting
retention of newly formed word–object mappings, convergent with recent behavioral work
(Kucker, McMurray, & Samuelson, 2018). The current study, therefore, suggests that
although attention to competitors has been shown to affect children’s ability to retain
label–object mappings (Horst et al., 2010; Zosh, Brinster, & Halberda, 2013), it is those
children who are better able to focus their attention on the target that are more likely
to retain the label’s meaning. This finding supports recent accounts of successful word
learning as the product of two separate but related sets of processes: those processes
that support disambiguation by driving elimination of competitors as potential referents,
followed by those processes that support sustained attention to the target object,
allowing for a robust association between the object and its label (see also Kucker,
McMurray, & Samuelson, 2015). Interestingly, given the additional social component in the
retention trials, we did not find a direct relation between shyness and retention. It is
possible that this object selection measure, with a single data point per trial, was not
sensitive enough to demonstrate a direct relation to shyness. Equally, although at the
individual level retention was related to attention during referent selection, it is
possible that the retention task resulted in a floor effect at the group level because it
required children to transfer their learning from two-dimensional (2D) pictures of the
objects to the actual 3D objects, something that we know is difficult for children overall
(e.g., Krcmar, Grela, & Lin, 2007). These findings highlight the importance of exploring
the processes underlying the relations among shyness, attention, and language development
at the individual level as well as at the group level. Although we found an effect of
shyness on attention during referent selection, we found no effect of age, which is
noteworthy given that existing literature suggests that referent selection behaviors
undergo a shift sometime toward the end of the second year of life. For example, Bion et
al. (2013) found that 18-month-old children showed no heightened attention to a novel
object on hearing a novel label, whereas 24-month-old children did. However, in our study,
at both 20 and 26 months of age children showed no heightened looking to the novel object
on novel label trials. Whereas Bion et al. presented participants with one novel target
alongside a familiar competitor, the current study presented two familiar competitors
alongside each novel target. Thus, it is possible that the additional competitor in the
current study increased the cognitive load of the task so that children needed more time
to rule out competitors as potential referents, reducing the time spent looking at the
novel object to chance levels. This discrepancy between the findings of the current study
and those of Bion et al. serves as an important illustration of the role played by
competitors during novel word disambiguation. Overall, then, the current study
demonstrates that shyness modulates the low-level attentional processes that unfold during
word learning. Although future work is required to establish a direct link between shyness
and retention, this finding may offer an explanation for shyer children's slower
vocabulary development in comparison with less shy children (Spere, Schmidt, Theall-Honey,
& Martin-Chang, 2004). Shyer children’s reduced attention to objects during labeling could
mean that they require more exposure to the object–label pairing so as to allow them
greater opportunity to encode the association. Over and above the predominant explanations
for the negative relation between children’s shyness and vocabulary (i.e., reticence to
demonstrate their language ability; Smith Watts et al., 2014), we identified a novel
potential contributing factor: We showed that shyness also affects the early implicit
processes that support one of the earliest stages of language learning. Early word
learning is the product of a complex and dynamic set of cognitive processes, and we have
come far in understanding the environmental factors that modulate these processes (e.g.,
Axelsson et al., 2012; Twomey et al., 2018). In the current study, we showed that shyness
is an intrinsic factor that influences the attentional processes supporting word learning.
Therefore, we must now consider the role of this and other individual differences in word
learning so as to better understand why early language development is so variable.


<h>REFERENCES</h>
----------

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<ART>Tax authorities' interaction with taxpayers: A conception of compliance in social dilemmas by power and trust
================================================================================

Authors: Katharina Gangl, Eva Hofmann, Erich Kirchler
DOI: 10.1016/j.newideapsych.2014.12.001
Year: 2015  |  Pages: 13-23
ASJC codes: 3200, 3201
Keywords: Coercive power, Cooperation, Implicit trust, Legitimate power, Reason-based trust, Tax compliance

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<h>ABSTRACT</h>
--------

Tax compliance represents a social dilemma in which the short-term self-interest to minimize tax payments is at odds with the collective long-term interest to provide sufficient tax funds for public goods. According to the Slippery Slope Framework, the social dilemma can be solved and tax compliance can be guaranteed by power of tax authorities and trust in tax authorities. The framework, however, remains silent on the dynamics between power and trust. The aim of the present theoretical paper is to conceptualize the dynamics between power and trust by differentiating coercive and legitimate power and reason-based and implicit trust. Insights into this dynamic are derived from an integration of a wide range of literature such as on organizational behavior and social influence. Conclusions on the effect of the dynamics between power and trust on the interaction climate between authorities and individuals and subsequent individual motivation of cooperation in social dilemmas such as tax contributions are drawn. Practically, the assumptions on the dynamics can be utilized by authorities to increase cooperation and to change the interaction climate from an antagonistic climate to a service and confidence climate.

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<h>INTRODUCTION</h>
------------

Citizens appreciate public goods such as schools or hospitals. Funding the public goods
through taxpaying, however, represents a social dilemma in which the individual short-term
interest to minimize paying taxes is at odds with the long-term collective interest to
ensure sufficient tax payments for financing the public goods (Balliet & Van Lange, 2013).
To overcome the social dilemma and to insure high tax compliance among citizens, tax
authorities rely on two measures. Power measures such as audits and fines and trust
related measures such as fair procedures (e.g., Allingham & Sandmo, 1972; Feld & Frey,
2007; Srinivasan, 1973). In research, the positive impact of both measures on tax
compliance received empirical support (e.g., Muehlbacher & Kirchler, 2010; Wahl,
Kastlunger, & Kirchler, 2010). Surface validity might suggest that power and trust are
incompatible and the opposites of each other. In contrast, we assume that power and trust
are related in a specific dynamic in which they mutually destroy or mutually foster each
other and in turn influence tax compliance. However, distinct theoretical assumptions
about the dynamics between power and trust are missing. The purpose of the present
theoretical paper is to conceptualize these dynamics and to elaborate on how they might
influence tax compliance. This conceptualization serves as the theoretical basis for
empirical research and conclusions how to increase tax compliance in particular and
cooperation in social dilemmas in general. There is little doubt that audits and fines are
necessary to levy taxes, however, they are not the only determinants to ensure
contributions. Experiments on tax behavior in the laboratory have consistently supported
the positive impact of audits and fines on compliance (Blackwell, 2007). Nonetheless, the
effects are rather weak. Field studies and surveys have yielded effects that are lower
than, and sometimes the opposite of the predicted effects (e. g., Andreoni, Erard, &
Feinstein, 1998). Additionally, Feld and Frey (2007) question whether audits and fines may
destroy trust, as they crowd out the intrinsic motivation to cooperate among committed and
cooperative citizens. Thus, besides “economic” determinants such as audits and fines,
“psychological” determinants such as the motivation to comply, the attitudes of taxpayers
towards the state, the government and taxation, transparency and understanding of tax
laws, personal and social norms, and fairness perceptions were shown to impact tax
compliance (Braithwaite, 2003; Kirchler, 2007; Torgler, 2003). Kirchler (2007) and
Kirchler, Hoelzl, and Wahl (2008) endeavored to integrate the economic and psychological
factors into a comprehensive two-dimensional framework, the Slippery Slope Framework
(SSF). The dimension power of authorities aggregates economic determinants and is defined
by taxpayers' perception of authorities' capacity to detect and punish tax evaders. The
dimension trust in authorities covers psychological bases of tax compliance and results
from taxpayers' general opinion that the tax law and regulations are clear and easy to
follow, and that the tax authorities operate fairly and benevolently in the interest of
the community. The SSF asserts that both the power of authorities and the trust in
authorities can solve the social dilemma of tax compliance. On the individual taxpayer
level, the framework differentiates between two motivations to comply with tax law,
enforced compliance and voluntary cooperation. Enforced compliance results from the power
of tax authorities, whereas voluntary cooperation is driven by the taxpayers' trust in tax
authorities. On the aggregate level, the SSF postulates that power and trust define
different interaction climates between tax authorities and taxpayers: while the exertion
of strong power by the authorities fosters an antagonistic climate, high trust is the
prerequisite of a synergistic climate (Kirchler, 2007; Kirchler et al. 2008). Fig. 1
depicts power and trust as independent dimensions, positively related to enforced
compliance and voluntary cooperation, respectively, and to an antagonistic and synergistic
climate, respectively. Empirical evidence generally supports the relevance of power and
trust as determinants of compliance (Kogler et al., 2013; Muehlbacher & Kirchler, 2010;
Muehlbacher, Kirchler, & Schwarzenberger, 2011; Wahl, Endres, Kirchler, & Böck, 2011; Wahl
et al. 2010). For instance, in a representative sample of self-employed taxpayers, trust
and power co-varied with tax compliance (Muehlbacher & Kirchler, 2010). Kogler et al.
(2013) and Wahl et al. (2010) found that compliance is highest if both power and trust are
perceived as high. This result suggests an additive effect of power and trust. Moreover, a
dynamic relationship between power and trust can be assumed. In the conceptualization of
the SSF, Kirchler et al. (2008) speculate about a dynamic relationship but they offer no
elaboration of the possible interaction effects between power and trust. In contrast to
surface validity, which might suggest that power and trust are incompatible, they assume
that power and trust might not only weaken but also strengthen each other. So far,
empirical studies in the tax behavior context suggest that power and trust are influencing
each other positively (Kogler et al. 2013; Muehlbacher et al. 2011; Wahl et al. 2010).
Nevertheless, in various research fields the theoretical conceptualization and the
empirical evidence for the mutual effects of power and trust are inconsistent, which
suggests that there is both a fostering as well as an eroding influence of power on trust
(Adler, 2001; Bijlsma-Frankema & Costa, 2005; Das & Teng, 1998; Kumlin & Rothstein, 2005;
Möllering, 2005). This inconsistency may originate from different conceptualizations of
power and trust and from diverse operationalizations in empirical investigations.
Therefore, we propose to distinguish between the independent qualities of coercive power
and legitimate power. We further differentiate between reason-based trust and implicit
trust. These distinctions will provide an explanation of the dynamics between power and
trust. The aim of the present paper is to shed light on the effects of the mutual
interaction of coercive and legitimate power on the one hand, and reason-based and
implicit trust on the other hand, as well as to formulate assumptions regarding the
consequences on the interaction climate between tax authorities and taxpayers as well as
on tax compliance. Consequently, we extend the SSF by distinguishing between three types
of interaction climates resembling for instance Alm and Torgler's (2011) interaction
styles and respective qualities of cooperation comparable to Kelman's (2006) psychological
processes of social influence. Hence, we not only integrate the dynamics between power and
trust in well-established existing theories but more importantly show how these dynamics
can be used to transform a hostile interaction into an interaction in which voluntary and
committed cooperation prevails. We extend the SSF borrowing from the literature on social
dilemmas, social influence, organizational behavior, and leadership; hence, we make
predictions beyond tax compliance on general interaction climates, motivations to
cooperate, and eventually, contributions to public goods which are regulated by
authorities such as insurance funds, public transportations, or business organizations.
All these cases represent social dilemmas, similar to the social dilemma of tax
compliance, in which the short-term self-interest is at odds with longer-term collective
interest (Van Lange, Joireman, Parks, & Van Dijk, 2013). Each single individual would be
better off by not contributing to the public good but nonetheless taking advantage of the
public good provision (Dawes, 1980; Ostrom, 2000). However, if all individuals would chose
this strategy no public good would be provided and eventually, all would end up worse off
than if all had cooperated (Dawes, 1980). Authorities, however, as intermediates are one
possibility overcoming this tragedy of the commons by actively regulating and monitoring
the individual contributions to the public good (Van Vugt, 2009; Van Vugt & De Cremer,
1999). Hence, although our predictions on the dynamics between power and trust are focused
on tax authorities interacting with taxpayers, we propose, that these predictions apply to
all authorities regulating individuals' contributions to public goods. In the remainder of
this paper we first introduce the concepts of coercive power and legitimate power, and
reason-based trust and implicit trust. Second, we speculate on the dynamics between the
different qualities of power and trust and how these impact tax compliance. Third, we
discuss the consequences of different qualities of power and trust for interaction
climates and the respective motivations to comply. Fourth, the paper concludes with
observations on the transformation from one type of interaction climate to another.

<h>QUALITIES OF POWER</h>
------------------

Power has received much attention in various scientific disciplines. Besides specific
perspectives taken by different disciplines, there is considerable agreement on a general
definition of power. Power is consistently defined as the potential and perceived ability
of a party to influence another party's behavior (e.g., Freiberg, 2010; French & Raven,
1959; Molm, 1994). In research on the regulation mechanisms of citizens' behavior, two
competing theories of power are widely recognized, the conceptualizations of coercive and
legitimate power. The perspective on coercive power is based on Becker's (1968) economic
approach which argues for strict control and punishment to influence individuals' utility
functions and in turn, their behavior. The second and more recently developed approach by
Tyler (2006) argues that legitimate power, i.e., the power of accepted authorities, is
more appropriate and effective in shaping individuals' behavior than severe controls and
punishment. We seek to integrate both perspectives of power in the SSF and refer to the
social-psychological theory of the ”bases of social power” developed by French and Raven
(1959), and Raven (1965). The bases of social power were initially conceptualized to
explain relations between supervisor and employee, i.e. individuals. It can, however, be
assumed that people's behavior in organizations, public institutions, and the state is
shaped by the same perceptions and judgments of the dominant party as in bilateral
relationships or small group settings (Tyler, 2006). French and Raven's approach
distinguishes between coercive power, reward power, legitimate power, expert power,
referent power, and information power. The different bases of power are seen as
independent implying that authorities cannot only hold one of the bases of power but
several bases of power at the same time. Moreover, the different bases of power can be
integrated into a two-dimensional structure (Raven, Schwarzwald, & Koslowsky, 1998): the
six bases of power fall into the two independent categories of harsh and soft forms of
power. To be consistent with the terminology in the context of the regulation of citizens'
behavior (Turner, 2005), we use the term coercive power for harsh power and legitimate
power for soft power. In the following, the terms coercive power and legitimate power
refer to our conceptualization and not to French and Raven's (1959; Raven, 1965)
terminology. Perceived coercive power originates from the pressure applied through either
punishment or remuneration. Our concept incorporates the two harsh forms of social power
bases, i.e., coercive power and reward power. Whereas coercive power is based on the
expectations of the influenced party that non-cooperative behavior will be punished (e.g.,
through monetary penalties or imprisonment), reward power operates through the
expectations of the influenced party that obeying the rules of the powerful party will be
rewarded (e.g., through awards or gratuities). Our concept of coercive power is
consequently based on incentivizing and compulsion. Individuals who do not obey the rules
of the authorities will face monetary, physical, social, or psychological costs (e.g.,
being fined or not receiving a reward, being excluded from future transactions). Perceived
legitimate power originates from legitimization, knowledge, skills, access to information,
and identification with the powerful party, and comprises French and Raven's (1959) soft
forms of power, namely legitimate power, expert power, information power, and referent
power. Legitimate power operates through the accepted right to influence others by means
of, for instance, agreed election rules, the norm of reciprocity (Gouldner, 1960), social
responsibility, and equity norms (Berkowitz & Daniels, 1963). Expert power operates
through the attribution of knowledge and skills that leads to the perception that the
expert has a high capacity to lead (Raven, 1992, 1993). Information power is based on
sharing of valued information (Raven, 1965, 1992, 1993). Referent power results from the
dependent party's identification with the influencing party (Raven, 1992, 1993). Our
concept of legitimate power is based on the fact that the legitimate authorities use
information, charisma, legitimization, and expertise to convince taxpayers that it is the
right course of action to cooperate. Hence, in contrast to the conceptualization of Becker
(1968) and Tyler (2006), in the current conceptualization the qualities of power are
multifaceted. Coercive power includes not just deterrence but also audits, punishment and
rewards, and legitimate power comprises not just acceptance of the authorities but also
the legal position, distribution of information, identification with the authorities, and
their expertise. Importantly, in our conceptualization of power, coercive power and
legitimate power are not seen as opposing entities but as independent factors (Hofmann,
Gangl, Kirchler, & Stark, 2014). Authorities can wield coercive power without legitimate
power, legitimate power without coercive power as well as they can wield both qualities of
power at the same time (Hofmann et al. 2014). Accordingly, the tax authorities can or
cannot be perceived as having the means to punish and reward taxpayers and can or cannot
be perceived as having procedural measures to make it acceptable and easy for taxpayers to
contribute.

<h>QUALITIES OF TRUST</h>
------------------

The importance of trust in social systems is broadly recognized. Despite notable
differences in approaching the phenomenon of trust, there is wide agreement on defining
trust as the willingness of a party to take a risk (Lewis & Weigert, 1985a) and “to be
vulnerable to the actions of another party based on the expectation that the other will
perform a particular action important to the trustor, irrespective of the ability to
monitor or control that other party” (Mayer, Davis, & Schnorrman, 1995, p. 712). Two
independent qualities of trust are distinguished: trust based on cognitive-rational
processes and trust based on automatic-affective processes (Castelfranchi & Falcone, 2010;
Lewis & Weigert, 1985a; McAllister, 1995; Nooteboom, 2002; Tyler, 2003). We draw on
Castelfranchi and Falcone's (2010) conceptualization of trust and differentiate between
reason-based and implicit trust. Reason-based trust corresponds to concepts of calculative
trust (Coleman, 1994; Fehr, 2009), rational trust (Ripperger, 1998), and knowledge-based
trust (Lewicki & Bunker, 1996). Implicit trust corresponds to concepts of identification-
based trust (Tyler, 2001), habitus trust (Misztal, 1996), social trust (Welch et al.
2005), and affective trust (Jones, 1996). Reason-based trust results from a deliberate
(rational) decision grounded on four criteria: goal achievement, dependency, internal
factors, and external factors (Castelfranchi & Falcone, 2010). First, the trustor
evaluates whether the other party is pursuing a goal that is important to the trustor.
Second, it is evaluated whether the trustor depends on the other party. Third, a positive
evaluation of internal factors of the other party, i.e., competence, willingness, and
harmlessness, is required. Fourth, the external factors in decision-making include the
perception of opportunities and dangers. In this sense, reason-based trust corresponds to
trust developed by a rational agent who trusts that there are good reasons to expect the
other will forgo opportunistic goals (Coleman, 1994; Fehr, 2009; Mayer et al. 1995).
Implicit trust is defined as an automatic, unintentional, and unconscious reaction to
stimuli (Castelfranchi & Falcone, 2010). The automatic reaction originates from
associative and conditioned learning processes and memory and is expected to emerge in
situations in which shared social identities are activated (Castelfranchi & Falcone, 2010;
Coulter & Coulter, 2002). Social categories or groups serve as stimuli which provoke the
perception that certain social practices and norms can be relied on and that every person,
organization, or authority that falls into this category can be trusted (Castelfranchi &
Falcone, 2010; Lewis & Weigert, 1985b; Messick & Kramer, 2001). It can be expected that an
authority perceived as belonging to the same category like the taxpayer will be evaluated
positively and implicit trust should be higher when compared to trust in authorities
perceived as belonging to another category (Tanis & Postmes, 2005). In addition to social
identities also the cue that the tax authorities are an official institution might serve
for some as a sign which activates automatic trust. Having repeatedly successfully
interacted with public institutions leads to automaticity in the interaction (Verplanken,
2006) and a situation in which implicit and habitual trust in the institution prevails
(Misztal, 1996). Other cues which activate implicit trust might be signs of warmth in
contrast to hostility or cooperation in contrast of competition communicated through tax
authorities' communication (websites, brochures, buildings; Williams & Bargh, 2008). To
conclude, implicit trust occurs without the conscious recognition of reasons to trust and
thus, without considering competence or intention of the official institution. The
different conceptions of trust correspond to the two-process theories of cognition in
which it is distinguished between system 1 and system 2 (Kahneman, 2003; Sherman,
Gawronski, & Torpe, 2014). System 1 is working fast, effortless, associative and often is
emotionally charged, governed by habit and difficult to control and modify. System 2 is
based on slow, effortful, serial and deliberately controlled cognition, relatively
flexible and potentially rule-governed (Evans, 2008; Kahneman, 2003). Whereas system 1
describes the functionality of implicit trust, system 2 explains the mechanism of reason-
based trust. However, the two-process theories also assume that reason-based trust and
implicit trust are related (Evans, 2008). Depending on the circumstances, the two
qualities of trust might have parallel as well as sequential relationships (Evans, 2008).
For instance, reason-based trust and implicit trust are operating together if taxpayers
might implicitly trust the tax authorities because of cues such as a friendly voice on the
tax line and at the same time might gain reasons to trust as the same person on the tax
line also offers a competent advice. On the other hand, reason-based trust and implicit
trust might operate independently, if taxpayers are cognitively too lazy to consider
whether the tax authorities give reasons to trust, and rather just implicitly trust
without questioning the tax authorities as official institution. Taxpayers also might in
principle mistrust official institutions and hence, only trust the tax authorities, if
they have proven evidence that the tax authorities act benevolently and competently. For a
sequential relationship, research suggests that after taxpayers gained relevant experience
based on deliberatively considering tax authorities' trustworthiness, reason-based trust
enhance or even changes its quality to fast, and implicit trust (Evans, 2008; Sun,
Slusarz, & Terry, 2005). Thus, in the long-run implicit trust develops with increasing
reason-based trust that in the end becomes implicit trust.

<h>DYNAMICS BETWEEN QUALITIES OF POWER AND TRUST</h>
---------------------------------------------

Depending on the quality of power and the way power is exerted and perceived, trust in the
powerful party can either be strengthened or weakened (e.g., Castelfranchi & Falcone,
2010; Choudhury, 2008; Korczynski, 2000; Kumlin & Rothstein, 2005). Also the quality of
trust can affect the perception of authorities' power. In the SSF, Kirchler et al. (2008)
conclude that tax authorities which enforce compliance through hostile and coercive
measures run the risk of losing trust, whereas tax authorities perceived as legitimate may
gain trust and the voluntarily cooperation of trustors. Also, the SSF proposes that if the
authorities gain trust, they also enhance their legitimate power (Kirchler et al. 2008).
In this vein, we assume two strong mechanisms which in general regulate the dynamics
between power and trust: coercive power and implicit trust mutually decrease each other
and that legitimate power and reason-based trust mutually increase each other.
Additionally, we propose two second order relationships such as that coercive power and
reason-based trust are related to each other via legitimate power and that legitimate
power and implicit trust are related through reason-based trust. In the following, these
assumptions are presented in detail (Fig. 2). Coercive power and implicit trust are
mutually decreasing each other. If coercive power manifests by strict controls and fines,
particularly if addressed at the individual, it provokes deliberate reasoning regarding
possible gains and losses and the risk of non-compliance and therefore interjects and
destroys implicit trust (Kirchler, 2007). Additionally, coercion may weaken affective and
social bonds and interrupt habitual cooperation (Balliet, Mulder, & Van Lange, 2011;
Castelfranchi & Falcone, 2010; Kramer, 1999; Nooteboom, 2002; Tenbrunsel & Messick, 1999).
Coercive power damages implicit trust and social bonds because asymmetrically established
control mechanisms indirectly convey the message that the person to which coercive power
is addressed, is not trusted (Das & Teng, 1998; Nooteboom, 2002). As a reaction, implicit
and automatic trust cannot emerge and instead coercive power is assumed to lead to
reactance and deliberate and strategic reasoning (Balliet et al. 2011; Kirchler, 1999;
Kirchler et al. 2008). However, implicit trust also reduces coercive power. People who
trust implicitly base their automatic trust on shared norms, signaled values, and habits.
Accordingly, audits and fines, which are expressions of coercive power, are not perceived
as necessary (Cummings & Bromiley, 1996; Dekker, 2004; Yamagishi, 1988). Implicit trust
activates social control mechanisms and relational governance (Dekker, 2004), and it
fosters spontaneous, unreflected cooperation (Castelfranchi & Falcone, 2010). Willingness
to spontaneously cooperate with another party reduces the complexity of the social world
(Luhmann, 2000), because control is not necessary (Das & Teng, 1998; Inkpen & Currall,
2004). Hence, those who implicitly trust might not demand tax authorities to increase
their coercion. Legitimate power and reason-based trust are mutually amplifying each
other. Legitimate power and reason-based trust are strongly entwined and can be seen as
the two sides of the same coin. Hence, their mutual fostering influence is not only
theoretically but also empirically well established (Bijlsma-Frankema & Van de Bunt, 2002;
Das & Teng, 1998; Malhotra & Murninghan, 2002; Mulder, Van Dijk, De Cremer, & Wilke,
2006). There are several reasons for taxpayers to trust; parties with legitimate power are
perceived as competent to provide assistance and support (Bijlsma-Frankema & Van de Bunt,
2002; Castelfranchi & Falcone, 2010). Additionally, legitimate processes can provide a
“track record” of the behavior of the parties involved and thereby build up a positive
reputation (Das & Teng, 1998). Hence, legitimate power provides reasons to trust the tax
authorities. At the same time, reason-based trust also increases legitimate power because
reason-based trust both emerges from and leads to the recognition of the legitimacy of the
authorities and the acceptance of the authorities (Castelfranchi & Falcone, 2010). If the
perception of shared goals prevails, it is likely that the party is also accepted as the
rightful authority (Inkpen & Currall, 2004). Reason-based trust permits and requires the
powerful authorities to influence taxpayers' behavior (Cullen, Johnson, & Sakano, 1995;
Das & Teng, 1998). Coercive power and reason-based trust are related through legitimate
power. There are reasons why coercive power is destroying trust, for instance, if it is
applied without competence and there are reasons why coercive power can strengthen trust,
for instance, if coercive power is perceived as being used competently only against tax
evaders. Hence, coercive power in combination with legitimate power has a relationship
with reason-based trust. It is assumed that authorities which are perceived wielding
coercive and legitimate power strengthen reason-based trust, whereas authorities perceived
as wielding coercive power and not legitimate power reduce reason-based trust. Coercive
power which is perceived to be used in a legitimate way, for instance, in a procedural
fair manner to effectively inhibit rule-breaking behavior (Bachmann, Knights, & Sydow,
2001; Hofmann et al. 2014; Van Prooijen, Gallucci, & Toeset, 2008), gives good reasons to
trust. Hence, coercive power combined with legitimate power is assumed to be perceived as
targeted to evaders and as a safeguard of honest taxpayers which fosters reason-based
trust. In contrast, high coercive power combined with low legitimate power destroys
reason-based trust because the authorities are perceived to wield audits and fines in an
incompetent and random way and even might be seen to prosecute honest taxpayers. If
coercive power is low and legitimate power is high, reason-based trust also is high, as
the wielding authorities are perceived to lead through legitimacy alone. If both, coercive
power and legitimate power are perceived to be low also reason-based trust is low. The
authorities are not legitimated and weak; hence, they are not seen as capable to guarantee
a fair tax system. As the impact of coercive power on reason-based trust depends on
legitimate power, coercive power which is wielded without highlighting its legitimacy
likely reduces reason-based trust in the tax authorities. In general, coercive power and
reason-based trust are related over the perception of legitimate power. Legitimate power
and implicit trust are related through reason-based trust. Legitimate authorities increase
first, reason-based trust and second, through establishing a stable system of functioning
cooperation also implicit trust. Trust initially based on rational consideration
transforms into implicit trust through routine. The more routine taxpayers can develop
interacting with authorities perceived as competent the more reason-based trust gradually
changes into implicit trust. The different qualities of power and trust are assumed to be
perceived by taxpayers in a specific way. Legitimate power and reason-based trust are
assumed to be positively related, whereas coercive power and implicit trust are negatively
related. These dynamics are assumed to hold not only for vertical relationships in which
tax authorities are seen to affect a specific taxpayer's behavior but also for horizontal
relationships in which a taxpayer's behavior is affected by the observation on how the tax
authorities treat other taxpayers not the taxpayer in question. The relationship of
qualities of power and trust holds not only, if power is perceived to be wielded on a
taxpayer, but also if it is wielded on other taxpayers. Coercive power perceived to be
directed at the individual reduces implicit trust, however, also if it is perceived to be
directed to other taxpayers it may fuel the impression that a considerable number of
taxpayers tries to evade taxes, hence, that the social norm of tax honesty is low.
Accordingly, coercive power indirectly conveys the message that the other taxpayers cannot
be trusted to pay their fair share of taxes and therefore need to be enforced (Mulder et
al. 2006). Also legitimate power addressed to other taxpayers has the same effect compared
to when it is addressed on the individual. Addressing the individual with legitimate power
already conveys a message about the other taxpayers. Legitimate power is applied
competently which means it is addressed in general to all taxpayers which fosters reason-
based trust. Coercive power and legitimate power addressed to other taxpayers will
increase reason-based trust because it leads to the perception that the right people,
those who try to evade, are controlled whereas the honest taxpayers are protected. To sum
up, two main mechanisms are assumed to determine the relationship between power and trust,
a negative relationship between coercive power and implicit trust and a positive
relationship between legitimate power and reason-based trust. Additionally, it is assumed
that coercive power is independent from reason-based trust and that legitimate power is
positively related to implicit trust. Whereas coercive power impacts reason-based trust
only due to its perceived legitimacy, legitimacy is assumed to steadily increase implicit
trust by increasing reason-based trust. Based on these assumptions and the empirical
evidence provided by Kogler et al. (2013) and Wahl et al. (2010) we propose that the
manipulation of high power and high trust was in fact a manipulation of coercive power and
legitimate power. Whereas the manipulation of high power and low trust was likely
perceived as coercive power applied with low competence to guarantee a fair system, low
power and high trust were likely perceived as legitimate power without the means to
enforce compliance with the law. Hence, only high power and high trust, thus, high
coercive power and high legitimate power were perceived as a competent safeguard of
cooperation which induced the overall highest compliance rates.

THE IMPACT OF THE DYNAMIC OF POWER AND TRUST ON TAX CLIMATE AND TAX COOPERATION
-------------------------------------------------------------------------------

Based on the presented assumptions regarding the dynamics between power and trust we
extend the SSF and distinguish on the aggregated level between three interaction climates
(cf. Alm & Torgler, 2011): an antagonistic climate, a service climate and a confidence
climate. This differentiation is based on conceptualizations from organizational research
distinguishing between market or price mechanisms regulating social interactions,
authorities, hierarchy-based or bureaucratic mechanisms of regulation and finally,
community or trust mechanisms of managing social interactions (Adler, 2001; Bradach &
Eccles, 1989; Haslam & Fiske, 1999; Ouchi, 1979). We also hypothesize that the different
interaction climates lead, in the long run, on the individual level to corresponding forms
of cooperation by taxpayers: enforced tax compliance, voluntary tax cooperation, and
committed tax cooperation. Again, current assumptions are in line with earlier research on
social influence for instance by Kelman (Kelman, 1961, 2006), who concluded that three
psychological processes determine individual reactions to influence: compliance,
identification, and internalization. Compliance with rules is based on incentives,
identification with roles is grounded in reciprocity and modeling and internalization of
values is based on value congruence or perceived continuity of the own self-concept
(Kelman, 2006; Kelman & Hamilton, 1989). Hence, in the extended SSF, we conclude that the
dynamics between power and trust are the preconditions of three cooperative climates, the
antagonistic, the service, and the confidence climate, with corresponding qualities of
motivations to cooperate, enforced compliance, voluntary cooperation and committed
cooperation. The conceptualization of the interaction between authorities and individuals
builds on the classical psychological insight, that authorities' actions create a specific
social atmosphere, hence a cooperative climate which in turn provokes on the individual
level specific corresponding habitual reactions of cooperation (Lewin, Lippitt, & White,
1939; Schneider, 2013). Fig. 3 summarizes our assumptions and shows that coercive power
favors an antagonistic climate and enforced compliance, whereas legitimate power and
reason-based trust are the antecedents of a service climate and voluntary cooperation.
Implicit trust is the base of a confidence climate and committed cooperation. In the
antagonistic climate coercive power prevails and a “cops and robbers” attitude is
predominant with taxpayers and tax authorities working against each other (Kirchler et al.
2008). Tax authorities perceive taxpayers as “robbers” who try to evade and escape the tax
authorities. In turn, taxpayers may feel prosecuted and harassed by the tax authorities
(“cops”) and may feel the necessity to “hide”. The antagonistic climate is characterized
by mistrust and resentment and leads to a vicious circle in which coercive power and
mistrust mutually reinforce each other. Thus, compliance in such a climate needs to be
enforced. Enforced compliance is characterized, for instance, by the feeling that tax
authorities are interested in catching taxpayers evading, independent of whether the
wrongdoing is intended or not (Kirchler et al. 2008). These assumptions received empirical
support through experiments showing that high in contrast to low coercive power leads to a
perceived antagonistic climate and enforced compliance of taxpayers (Hofmann et al. 2014).
The thoughts underlying an antagonistic climate that taxpayers can only be forced to
comply with the tax law by dint of controls and fines match the standard economic paradigm
of tax behavior (Allingham & Sandmo, 1972). The disadvantage of an antagonistic climate is
— besides costly audits — that taxpayers are likely to develop motives of opposition and
reactance (Braithwaite, 2009; Kirchler, 2007) which cause instability in tax behavior and
tax collection: when the tax authorities lose power, taxpayers lacking the intrinsic
motivation to comply are expected to engage in evasion. The service climate bases on
legitimate power and reason-based trust. It is characterized by a “service and client”
attitude which means that taxpayers and tax authorities collaborate on the basis of well-
defined rules and standards. Tax authorities perceive taxpayers as clients who expect and
deserve professional, fair, and supportive services. Taxpayers reciprocate this attitude
by contributing their tax share. Taxpayers who perceive the authorities as being
supportive and competent are likely to cooperate voluntarily. Voluntary tax cooperation
reflects the view of taxpayers that paying taxes is an accepted obligation as well as a
necessity if the state is meant to provide public goods (Kirchler & Wahl, 2010; Wahl et
al. 2010). These assumptions also received empirical support through experiments conducted
with taxpayers showing that high in contrast to low legitimate power leads to a perceived
service climate and voluntary cooperation (Hofmann et al. 2014). The advantage of the
service climate lies in its stability — a single event of inappropriate services provided
by the tax authorities will not lead to reduced taxpayers' cooperation, because the
taxpayers themselves want the tax system to work smoothly. A disadvantage of a service
climate may be the bureaucracy entailed in producing elaborate written rules as well as
complex procedures to treat taxpayers fairly, which results in substantial administrative
overheads (Ouchi, 1979). In a confidence climate implicit trust prevails. Taxpayers
automatically trust the tax authorities and cooperate without thinking about it. Taxpayers
pay their taxes because they perceive the tax authorities to work on the basis of shared
norms and values or simply cooperate out of a habit. Tax authorities on the other hand,
reinforce implicit trust by showing respect to the honest taxpayers (Feld & Frey, 2002).
Tax authorities perceive themselves as working in the name of the taxpayers; they show
empathy and feel obliged to offer support. Taxpayers perceive the tax authorities as
working for the good of the community and reciprocate by contributing their share because
they feel intrinsic motivation as members of the same community. For taxpayers, tax
compliance is a personal and societally shared norm that is binding. Shared perceptions
and values prevail and taxpayers are personally committed to the tax system. Committed
cooperation is characterized by taxpayers' feelings that paying taxes is a customary thing
to do and a moral obligation also followed by fellow citizens. Taxpayers feel committed to
the tax system as a whole and actively engage to make the system work. The main advantage
of a confidence climate is that taxpayers do not follow the letter of the law, but comply
with the spirit of the law. Specific and complicated tax legislation is not needed because
taxpayers follow moral standards instead of specific tax rules. According to Sloterdijk
(2010), the main benefit of a confidence climate which induces that taxpayers feel
committed to contribute their share, is that taxpayers are in a position of self-
determination and generosity where they actively participate in a vital democracy and take
responsibility for their society. Undoubtedly, a disadvantage of a confidence climate is
its vulnerability to free-riders if tax authorities are perceived to avoid controls and
punishment of tax evaders (Ouchi, 1979). Adler (2001) adds for the organizational context
that such a confidence climate should be reflective and grounded in open dialogue among
the interacting parties to avoid blind and traditionalistic loyalty.

<h>CONCLUSIONS</h>
-----------

As a main contribution of the present theoretical elaboration on the dynamic between power
and trust, it can be derived how authorities such as the tax authorities can change and
enhance cooperative climates and cooperation in social dilemmas. A negative dynamic
between coercive power and implicit trust and a positive dynamic between legitimate power
and reason-based trust explain how tax authorities can solve the social dilemma of
taxpaying by either creating an antagonistic climate with enforced compliance, a service
climate with voluntary cooperation, or a confidence climate with committed cooperation. In
the following, the present paper concludes how a change from one climate to another
climate can be accomplished, how the present assumptions can fuel empirical research, and
why the dynamic between power and trust explains tax compliance and cooperation in social
dilemmas in general. As a practical implication of the dynamic between power and trust, it
is possible to demonstrate how a change from one climate to another emerges and why some
interaction styles are more “slippery” than others. Countries differ in their interaction
styles with taxpayers and their tax honesty (Alm & Torgler, 2006; Kogler et al. 2013). In
some developing countries authorities lack power and trust, hence, a state of instability
and in extreme cases a state of anarchy prevails with low levels of compliance, whereas on
the other extreme, stable countries such as northern European ones exist displaying high
levels of power and trust in the authorities that guarantee high tax compliance (Kogler et
al. 2013). Also, on the individual level differences prevail between taxpayers
(Braithwaite, 2003). Individuals within a country differ in their motivation to be honest
and can be distinguished into taxpayers who perceive low power and hold low trust and
hence, intentionally evade, perceive low legitimate power and fail to comply due to, for
instance, complex tax laws and complex procedures or perceive high levels of trust and
cooperate out of commitment to the community. We are convinced that tax authorities
possess the measures to transform, on the aggregate level, a tax climate of distrust
gradually into a climate of confidence. On the individual level, taxpayers' enforced
compliance can be transformed into voluntary and committed cooperation. In line with the
full range leadership model (Avolio & Bass, 1991; Kirkebride, 2006), in which the laissez-
fair leadership develops over various stages into transactional leadership based on
incentivizing behavior and further into transformational leadership based on a vision and
shared values (Antonakis, Avolio, & Sivasubramaniam, 2003; Kirkebride, 2006), we also
propose a possible transformation from one interaction climate into another. Under
circumstances of low power and of low trust, tax compliance will be at a minimum, no
matter whether it is on a country or individual level. In such a situation, coercive power
can be a starting point for tax compliance. Laboratory experiments indicate that in a
social dilemma situation with low levels of trust, authorities using coercive power are
efficiently increasing compliance (Van Vugt & De Cremer, 1999). However, the psychological
effectiveness of coercive power lies in its potential to scare, deter and enforce
taxpayers through efficient and strict audits and severe fines. Accordingly, coercive
power precludes the emergence of implicit trust. Instead a vicious circle of mistrust and
consequently stronger coercive power is likely to develop between the tax authorities and
the taxpayers resulting in an antagonistic climate and enforced motivation of tax
compliance. Additionally, the antagonistic climate is instable or slippery as it depends
on permanent exertion of coercive power. To change an antagonistic climate into a service
climate, the measures of coercive power, such as controls and punishments, have to be
combined with accepted, legitimate power. Once legitimate power is established, reason-
based trust is likely to increase and, as a result, a service climate is established with
voluntary tax cooperation. Tax authorities can improve their legitimacy by improving their
services such as establishing professional and comprehensible tax procedures or web and
telephone services in order to be perceived as motivated, competent and benevolent (Alm &
Torgler, 2011). Moreover, the service climate is not depending on permanent enforcement,
thus, it is relatively stable compared to the antagonistic climate. A service climate is
theoretically based on legitimate power and reason-based trust. It can be assumed that a
service climate changes into a confidence climate and that voluntary cooperation changes
into committed cooperation over the course of time and due to stable positive experiences
(Verplanken, 2006). Cooperation founded on reason-based trust which is initially based on
careful consideration of one's own risks and other's intents becomes automatic with
routine and repeated positive experiences (Castelfranchi & Falcone, 2010; Dekker, 2004;
Misztal, 1996; Nooteboom, 2002). Repeatedly positive experiences lead to the implicit
expectation that the other party respects agreed norms and practices. Accordingly, reason-
based trust decreases in the longer run, while correspondingly, implicit trust increases
over time (Castelfranchi & Falcone, 2010). To promote a confidence climate, tax
authorities could, for instance, establish contracts of fair play and long-term
relationships with committed taxpayers (Adler, 2001; Alm & Torgler, 2011; Ouchi, 1979).
Establishing fair play with enterprises and the guarantee of mutual collaboration on the
basis of mutual trust are existing examples (e.g., Schepers, 2010; see also
http://www.nltaxinternational.com/index.php/taxadvice/10; retrieved April 10, 2012). It
can be argued that relying solely on trust as in a confidence climate is far too
optimistic in a social dilemma context since there always will be citizens tempted to
engage in egoistic profit maximizing activities and hence, trusting authorities are not
perceived as being able to enforce compliance. On the other hand, a climate of confidence
is easily destabilized by the emergence of suspicion caused by power mechanisms (Kramer,
1999; Nooteboom, 2002). As a consequence, the confidence climate might be as instable and
slippery as the antagonistic climate. Whereas the emergence of egoistic free-riders not
threatened by coercive power might bring the confidence climate to a collapse, perceived
power measures, depending on their quality and severity, can easily change the confidence
climate into a service climate or an antagonistic climate if they trigger rational
consideration of authorities' intentions or are perceived as hostile prosecution. The
attempt to describe the prerequisites of voluntary and committed cooperation is a
worthwhile approach solving social dilemmas in assisting the transformation from an
antagonistic climate to a climate of suitable services and confidence. Thus, long lasting
and reoccurring experiences with legitimated authorities might convince recalcitrant
taxpayers whose compliance is enforced to become responsible and self-determined citizens
committed to the moral obligation of voluntary contribution to the common good. Although
the proposed model allows for several theoretical predictions and practical implications,
it has some boundaries. It could be argued that legitimate power and reason-based trust
represent similar concepts that are highly related. We see them as the two sides of the
same coin. However, legitimate power is the perception of influence whereas reason-based
trust is the decision to be vulnerable based on an evaluation of the influencing entity
and its environment; therefore they are similar, but not identical. On the other hand,
these well-established and related definitions of power and trust also highlight how, in
fact, deeply connected power and trust are. It is expected that the different interaction
climates in a real life setting will never appear as sharply delineated as in theory.
Therefore, future research should investigate the prevalence and overlaps of the different
interaction climates, and how these affect tax compliance. Additionally, future research
should not only consider trust in the authorities, but also trust in fellow citizens and
believes about their motivation to cooperate (Eek & Rothstein, 2005). For instance,
taxpayers may hold the opinion that they cooperate voluntarily, whereas other taxpayers
only cooperate because they are enforced, and still other taxpayers cooperate out of
commitment. Empirical studies should investigate whether such believes about others
influence the dynamic between perceived power and trust. The present paper provides a
theoretical frame for future research. The presented conceptualizations of the dynamics
between power and trust as well as subsequent tax climates, motivations to comply, and tax
compliance serve as a theoretical basis for empirical studies. As an example, in countries
differing in their overall tax climate, surveys among taxpayers could be conducted
relating power perceptions and trust in authorities with compliance intentions and
perceived tax climates, and motivations to comply. Experiments manipulating perceptions of
cooperative climate and different qualities of power and trust with scenarios could be run
to test the proposed relationships between the different qualities of power, trust, tax
climates, motivations to comply, and tax compliance (Hofmann et al. 2014). To conclude, by
integrating of a wide range of psychological theories on cognition (Evans, 2008; Kahneman,
2003), leadership (Avolio & Bass, 1991; French & Raven, 1959), social and organizational
climate (Adler, 2001; Lewin et al. 1939), compliance motivation (Kelman, 2006),
situational influences (Alm & Torgler, 2006; Antonakis et al. 2003) and personal
differences (Braithwaite, 2003) the SSF is extended. Starting off with the dynamic between
power and trust, the interaction between tax authorities and taxpayers is explained which
results in specific cooperative climates and corresponding forms of individual motivations
to cooperate. Therfore, we are confident that the assumptions about the dynamics between
power and trust are not only useful to understand and regulate tax behavior but can be
transferred into other contexts related to cooperation in social dilemmas, managed by an
authority. The present paper demonstrates that understanding the dynamic between power and
trust can fuel research on cooperation in social dilemmas and can be utilized by
authorities to foster voluntary and committed cooperation to guarantee the provision of
public goods.


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<ART>The 'dark side' of personal values: Relations to clinical constructs and their implications
================================================================================

Authors: Paul H.P. Hanel, Uwe Wolfradt
DOI: 10.1016/j.paid.2016.03.045
Year: 2016  |  Pages: 140-145
ASJC codes: 3200
Keywords: Anxiety, Depression, Personal values, Schizotypy, Stress

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Personal values are considered as guiding principles in one's life. Much of previous research on values has consequently focused on its relations with variables that are considered positive, including subjective well-being, personality traits, or behavior (e.g. health-related). However, in this study (N = 366) the negative 'dark' side of values is examined. Specifically, the study investigated the relations between Schwartz' (1992) ten value types and four different clinical variables - anxiety, depression, stress, and schizotypy with its subdimensions, unusual experience, cognitive disorganization, introverted anhedonia, and impulsive nonconformity. Positive relations between achievement and depression and stress, and negative relations between anxiety and hedonism and stimulation were predicted and found. Multiple regressions revealed that the ten value types explained the most variance in impulsive nonconformity and the least variance in unusual experience. Overall, values were better in predicting more cognitive clinical variables (e.g., cognitive disorganization) whereas clinical constructs were better in predicted more affective values (e.g., hedonism). Implications of the findings for value research are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Personal values are usually considered as cognitive concepts or beliefs that transcend
specific situations and guide behavior and its evaluation (Maio, 2010; Schwartz, 1992).
There have been different attempts to conceptualize personal values on an individual
level. Based on the value approach by Rokeach (1973), Schwartz and Bilsky (Schwartz, 1992;
Schwartz & Bilsky, 1987) have developed a motivational circumplex model with 56 personal
values which can be grouped into ten value types (Fig. 1): universalism (e.g. equality,
protection for the welfare of all people and for nature), benevolence (e.g. helpfulness,
preservation of the welfare of people), tradition (e.g. respect, humility), conformity
(e.g. obedience, honoring parents), security (e.g. safety and social order), power (e.g.
authority, dominance), achievement (e.g. personal success, ambition), hedonism (e.g.
pleasure, enjoying life), stimulation (e.g. exciting life, varied life), and self-
direction (e.g. independent thought, creativity). One important feature of Schwartz'
circumplex model is its motivational continuum. Two adjacent value types are
motivationally similar, that is positively correlated, orthogonal value types are
unrelated according to the assumptions of Schwartz (1992), and opposing value types are
negatively correlated. Crucially, this prediction holds true for relations between values
and variables such as personality traits (e.g., Parks-Leduc, Feldman, & Bardi, 2014).
Thus, when the value types are plotted according to their proposed order along the x-axis
and the correlation coefficients on the y-axis, the correlational pattern resembles a sine
wave. Numerous studies have focused on the relations between values and constructs of
positive affectivity such as subjective well-being and satisfaction with life. For
example, Haslam, Whelan, and Bastian (2009) found that many value types were closely
connected to positive affect, but not with negative affect. This is in line with other
research that found no relations between personal values and neuroticism (Parks-Leduc,
Feldman, & Bardi, 2014; Roccas, Sagiv, Schwartz, & Knafo, 2002). However, other studies
have found relations between values and negative affectivity, although the results were
inconsistent. Jarden (2010) for instance found negative relations of self-direction,
stimulation, and hedonism value types with depressed mood. In a Chinese sample, the
burnout dimension exhaustion was found to be related to conformity, but another dimension,
losing interest, was not (Jia, Rowlinson, Kvan, Lingard, & Yip, 2009). A study among
native American adolescents revealed negative relations between depression and
tradition/benevolence. However, power/materialism and security/hedonism values did not
display any associations with depression (Mousseau, Scott, & Estes, 2013). In a Brazilian
sample, relations between values and psychopathy were observed (Monteiro, 2014): pleasure,
success, and power were found to be positively related to the psychopathological
subdimensions boldness and disinhibition. Kajonius, Persson, and Jonason (2015) found
positive relations between hedonism, achievement, and power with the dark triad, which
consists of machiavellianism, narcissism, and psychopathy. Silfver et al. (2008) found
positive correlations of universalism and benevolence with guilt proneness. The present
study aims to extend the small empirical support that personal values are also related to
clinical constructs, in our case anxiety, depression, and schizotypy. Because of the
little empirical research on this topic, we first turn to a set of constructs that has a
similar theoretical and empirical base as personal values: personality traits. Numerous
studies have investigated the relations between many clinical variables and personality
traits.

<hs>  Personal values and personality traits</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Both personal values and personality traits have their common roots in the language, which
are encoded as linguistic descriptors for individual traits and behavior (lexical
hypothesis). Therefore, several studies considered values and traits as different
components of personality (e.g., Saroglou & Muñoz-García, 2008). Another approach
emphasizes the biological–motivational basis of values and traits (McCrae & Costa, 2008).
This is because both constructs motivate individual behavior. Indeed, a behavioral
genetics study showed that personal values as well as personality traits share common
genetic factors (Schermer, Vernon, Maio, & Jang, 2011). Further support for a close link
between personal values and personality traits of the five-factor model is provided by a
meta-analysis that has found consistent correlational patterns (Parks-Leduc et al., 2014).
For example, stimulation, self-direction, and universalism correlated positively with
openness to experience, whereas security, conformity, and tradition correlated negatively.
Agreeableness was highly correlated with benevolence and negatively with power. However,
the relations between values and other personality traits are not as consistent as they
are for openness and agreeableness. Neuroticism or emotional stability, for instance,
showed no substantial correlation to any of the ten value types.

<hs>  Personality traits and clinical constructs</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Numerous studies have investigated the relations between the Big-Five and clinical
variables, including anxiety and schizotypy. For example, neuroticism correlated
positively and extraversion and conscientiousness correlated negatively with anxiety.
Agreeableness and openness were mainly unrelated to anxiety disorders, as a meta-analysis
revealed (Kotov, Gamez, Schmidt, & Watson, 2010). Schizotypal traits can be considered as
both mild personality features and as a predisposition toward schizophrenia. Schizotypal
traits reflected aspects of positive symptoms (unusual experiences), negative symptoms
(introverted anhedonia), and impulsive nonconformity and cognitive disorganization
(Lenzenweger, 2015). Mason, Claridge, and Jackson (1995) have proposed a multidimensional
model of schizotypy with aspects of positive- schizotypy (reflecting the positive
symptomatology of schizophrenia), asocial-schizotypy (reflecting antisocial, impulsive and
tough-minded behavior), disorganized-schizotypy (reflecting a difficulty with attention
and social anxiety), and negative-schizotypy (reflecting the negative symptomatology of
schizophrenia). Meta-analyses on the relations between personality traits (Big-Five) and
schizotypal traits showed that positive symptoms are positively related to openness to new
experience (Samuel & Widiger, 2008; Saulsman & Page, 2004).

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

The aim of the present study is to examine the relations between value priorities and the
four clinical constructs anxiety, depression, stress, and schizotypy with its 4 facets.
Based on previous findings described above and the common base of values and personality
traits, the following hypotheses were derived. Valuing achievement is defined by Schwartz
(1992) as demonstrating competence. This can include (time) pressure and a lot of
demanding work, which in turn can lead to stress and even depressive symptoms. Therefore,
it was hypothesized that stress and depressive symptoms are positively related to
achievement. On the other hand, given that volunteer work and well-being are positively
associated (Thoits & Hewitt, 2001), benevolence and universalism should be negatively
associated with stress and depressive symptoms. This is also in line with the motivational
continuum of the quasi-circumplex model (Schwartz, 1992), which predicts opposing pattern
of results for opposing value types (cf. Fig. 1). Anxiety was expected to be negatively
related to hedonism and stimulation, as for both of these value types, Schwartz stated
that courage and outgoingness are needed to at least some degree. Furthermore, a negative
relation to self-direction was not expected because those values are more cognitive than
stimulation and hedonism. Previous studies have found relations between conservatism and
different types of anxiety (e.g., death anxiety and fear of threat and loss (Jost, Glaser,
Kruglanski, & Sulloway, 2003). Therefore, a positive relation between anxiety and
security, tradition, and conformity was expected. Positive relations between the
schizotypal subdimension impulsive nonconformity with stimulation and hedonism, as well as
negative ones with security, tradition, and conformity were expected, because impulsive
nonconformity can be considered as an extreme form of openness. This prediction is in line
with the above discussed finding that the personality trait openness is linked to
impulsive nonconformity (Samuel & Widiger, 2008; Saulsman & Page, 2004). Introverted
anhedonia is predicted to be negatively related to stimulation and hedonism. However, we
do not expect positive relations between introverted anhedonia with tradition and
conformity because we consider them as conceptually different constructs. As valuing
security implies harmony and stability (Schwartz, 1992), a negative relation with the
cognitive disorganization subdimension of schizotypy was hypothesized. Unusual experience
was expected to be unrelated to all value types. Furthermore, in an exploratory step, we
investigated in a series of multiple regressions, which clinical construct can be best
predicted by all value types and, reversing the dependent and independent variables, which
value type can be best predicted by all clinical constructs. This can give us greater
insight into the nature of personal values as it can help to reveal which psychological
states (i.e., clinical variables) are completely unrelated and provide evidence of the
discriminant validity of values. We only expected, based on the rational given above that
rather affective value types such as hedonism and stimulation will more strongly predict
the clinical variables than more cognitive value types such as self-direction and
universalism (cf. Schwartz, 1992), because the clinical variables used are mainly
affective.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 366 students of various disciplines from an East German university (Mage
= 21.72, SD = 3.38, range = 18–39, 236 females). Participants volunteered to participate
and were not compensated.

<hs>  Measures</hs>
  ~~~~~~~~

The full Portrait Value Questionnaire (PVQ-40) was used (Schwartz et al., 2001) in its
German translation (Schmidt, Bamberg, Davidov, Herrmann, & Schwartz, 2007) to assess the
10 value types of Schwartz' (1992) value model. Participants were given a short
description of a person (i.e., ‘portrait’) and were asked to rate how similar they are to
this person on a 6-point Likert scale ranging from 1 very similar to 6 very dissimilar. To
facilitate interpretation, all value items have been recoded prior to the analyses
reported below. The reliabilities (Table 1) are similar to the ones reported in the
original validation paper of the PVQ (Schwartz et al., 2001). Following the suggestions of
Schwartz (1992) and Schwartz et al. (2001), the 40 items of the PVQ were centered in order
to control for individual scale use tendencies. The short form of the Depression, Anxiety
and Stress Scale (DASS-21; Henry & Crawford, 2005) was used to measure depression,
anxiety, and stress. Example items are “I couldn't seem to experience any positive feeling
at all” for depression, “I felt scared without any good reason” for anxiety, and “I found
it difficult to relax” for stress. Each of the three clinical personality constructs was
measured with seven items on a 4-point Likert scale ranging from 0 never to 3 almost
always. Finally schizotypy was measured with the Oxford–Liverpool Inventory of Feelings
and Experiences (O-Life; Mason, Linney, & Claridge, 2005), a short scale consisting of 43
items consisting of the four factors: unusual experience, cognitive disorganization,
introverted anhedonia, and impulsive nonconformity. Answers were given on a yes–no
response scale (0 and 1). The scales described were part of a larger survey, unrelated to
the present study.

<hs>  Procedure</hs>
  ~~~~~~~~~

The questionnaire was completed within one large group session.

<h>RESULTS</h>
-------

The data file is available at osf.io/32ja6.

<hs>  Descriptive statistics and correlations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First, the overall zero-order-correlations were calculated. As can be seen in Table 2 most
hypotheses were supported. As predicted, stress and depression were positively related to
achievement values, but also negatively with hedonism. Anxiety was negatively related to
stimulation and hedonism values. Contrary to our expectation, we did not find significant
relations between anxiety and security, tradition, and conformity, although all three
correlation coefficients were in the predicted direction. Combining all the conservation
values (security, tradition, conformity) into one variable did not result in a significant
correlation either r(364) = .08, p = .07. Impulsive nonconformity correlated positively
with stimulation and hedonism values, but also, somewhat surprisingly, with achievement
and power values. As predicted, we found negative correlations between introverted
anhedonia and stimulation and hedonism, but also, unexpectedly, positive correlations with
power, security, and tradition. The correlation between cognitive disorganization and
security was negative, as predicted. Unusual experience did not correlate with any value
type, except for universalism. The pattern of correlations remained the same after
controlling for gender and age.

<hs>  Multiple regressions</hs>
  ~~~~~~~~~~~~~~~~~~~~

In the next step, we explored which clinical variables are best predicted by personal
values. Impulsive nonconformity was best predicted by all ten value types combined while
unusual experience was the least predicted clinical variable. None of the 10 value types
reached statistical significance in any of the seven multiple regressions after
controlling for the other nine value types. Finally, a series of regression was conducted
to test which value types were better predicted by all seven clinical variables. As can be
seen in Table 3, hedonism and tradition were best predicted by the seven clinical
variables, whereas universalism was very weakly predicted. The subdimensions of schizotypy
explained in a hierarchical regression additional variance, if entered in a second step
(columns 5 and 6 in Table 3). For most value types, schizotypy explained substantial more
variance than anxiety, depression, and stress. For example, the four schizotypy dimensions
explained 14% out of the total 16% variance of stimulation. Overall, no multicollinearity
was observed (all VIFs < 2.1).

<h>DISCUSSION</h>
----------

The aim of the present study was to investigate the relations between personal values and
clinical aspects of personality. It focused on anxiety, depression, stress, and four
subdimensions of schizotypy. First, all variables with the exception of the schizotypal
subdimension, unusual experience, were related in a theoretical meaningful way with
personal values. Stimulation and hedonism were negatively related to anxiety. The findings
are in line with the results of Monteiro (2014), who has found positive relations between
boldness and openness values such as stimulation and hedonism. Because openness to
experience as a personality trait was unrelated to anxiety and depression (Kotov et al.,
2010), this indicates that openness values and traits, despite being related (Parks-Leduc
et al., 2014), differ in predicting clinical constructs. Second, stimulation and hedonism
correlated positively with the schizotypal subdimension impulsive nonconformity. This is
interesting, because impulsive nonconformity may be considered as an undesirable
construct, as it refers to impulsive, aggressive, and asocial aspects of psychosis based
on the Eysenck dimension psychoticism (Eysenck & Eysenck, 1975) and the hypomania
construct (elevation of mood, feeling of grandiosity, risk taking etc.). In other words,
stimulation and hedonism are both positively and negatively related to undesirable
constructs (impulsive nonconformity and the DAS-scales, respectively). On the other hand,
it was argued that impulsive nonconformity can also be considered as a beneficial trait,
because of its relations to creativity (Acar & Sen, 2013; Cohen, Mohr, Ettinger, Chan, &
Park, 2015). Further, we assume that benevolence is negatively related to impulsive
nonconformity, because altruistic values such as loyalty and honesty require some
reliability on the person, which may be incompatible with impulsivity. Introverted
anhedonia was as predicted negatively related to stimulation and hedonism, likely because
anhedonia is a key symptom of major depression (Pizzagalli, 2014) and those two value
types are negatively related to depression (see above). However, somewhat surprisingly,
introverted anhedonia was positively related to power, security and tradition, and
negatively to benevolence. The latter is consistent with previous research reporting a
negative relation between negative schizotypy and interest in social contact (Kwapil,
Brown, Silvia, Myin-Germeys, & Barrantes-Vidal, 2012). The finding that introverted
anhedonia is positively related to power contradicts previous studies that suggest that
power correlates with extraversion (Parks-Leduc et al., 2014). Further research is needed
to resolve this contradiction. Disentangling both constructs, introverted anhedonia and
extraversion, may very well be a promising approach. As assumed, cognitive disorganization
was negatively related to security, but also with power and self-direction. This can
indicate that at least some structure is required for power and self-direction. Overall,
the correlational pattern of openness values such as hedonism and stimulation with
schizotypy was similar to the one found between the personality trait openness and
schizotypy (Samuel & Widiger, 2008; Saulsman & Page, 2004). It is of theoretical interest
that our findings, although predicted and meaningful, did in general not follow the
expected sinusoidal pattern (Schwartz, 1992). That is, if a clinical variable is
positively related to one value type, it should also be positively related to adjacent
value types, unrelated to orthogonal value types, and negatively related to opposing value
types. For example, albeit stress was negatively related to self-direction, stimulation,
and hedonism, it was positively related to achievement and again (non-significant)
negative to power, violating the assumption of a motivational continuum. A similar
violation can be found for the other clinical variables, with the exception of impulsive
nonconformity, which follows the proposed sinusoidal pattern well. This indicates that
variables can be related to Schwartz' values without following the proposed sinusoidal
pattern (cf. Schwartz, 1992). Finally, a series of multiple regression analyses revealed
that the subdimensions of schizotypy with the exception of unusual experience were better
predicted by all of Schwartz' (1992) ten value types than anxiety, depression, and stress.
This finding is interesting from a theoretical point of view because it indicates that
personal values are more strongly associated with cognitive variables than affective ones,
which is in line with predominant definitions of values as cognitive constructs (e.g.,
Maio, 2010). The schizotypy subdimensions (Mason et al., 2005) represent the cognitive
aspects of experiences in comparison to the dimension of the DASS, which reflect more
negative affect (Henry & Crawford, 2005). This assumption is further supported by the fact
that anxiety, depression, and stress are stronger related to affective value types such as
hedonism and stimulation compared to cognitive value types such as self-direction or
universalism. Our findings show that personal values can be positively related to negative
constructs. In other words, essential principles that are personally important can be both
negatively as well as positively related to behavior, feelings, and affect that are
generally considered as negative and unwanted. Given that achievement, hedonism, and
stimulation can be considered as value types with a strong personal focus (Schwartz et
al., 2012), which are promoted in individualistic countries such as Germany (Hofstede,
Hofstede, & Minkov, 2010), the findings also reveal a potential ‘dark side’ of
individualism. Individualistic culture emphasizes the individual autonomy more and a low
power distance with the consequences of more norm transgressions. On the other hand, more
conservative/collectivistic values such as tradition and conformity are mostly unrelated
to the clinical variables used in the present study. This is somewhat contradictory to
previous findings, stating that individualism is in general positively associated with
well-being and negatively with social anxiety (Diener, Diener, & Diener, 1995). Therefore
it would be interesting to investigate whether the same pattern of relations can be found
in collectivistic societies. Our study has also some limitations. Just as previous studies
investigating the relations between personal values and clinical variables (e.g., Jarden,
2010; Jia et al., 2009; Mousseau et al., 2013), a non-clinical sample was used in the
present study. Clinical samples would reveal further interesting insights about the
structure and priorities of personal values with regard to the claimed universality of
both (Schwartz, 1992; Schwartz & Bardi, 2001). Moreover, future studies could investigate
whether the relations between personal values and clinical variables are mediated by the
Big-Five traits, as are the relations between values and well-being (Haslam, Whelan, &
Bastian, 2009). In conclusion, the present study shows interesting relations between
personal values and clinical variables. Values were better in predicting cognitive
clinical variables (e.g., cognitive disorganization) and more affective values (e.g.,
hedonism) were better predicted by them. In a broader framework, personality traits,
personal values, goals, and needs should be integrated in a general theory of the
structure of motivation to understand the underlying processes among the similar
constructs (Schwartz, 2011). McAdams (1995) has already shown that traits and values can
be hierarchically ordered on different personality levels. In a recent study by McGabe and
Fleeson (2016) the role of traits for motivational processes, goal attaining, was
examined. They found that person differed from each other in traits because they pursued
different goals. We would like to add, this finding may have occurred because they have
different personal values.


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<ART>The Big Five, self-esteem, and narcissism as predictors of the topics people write about in Facebook status updates
================================================================================

Authors: Tara C. Marshall, Katharina Lefringhausen, Nelli Ferenczi
DOI: 10.1016/j.paid.2015.04.039
Year: 2015  |  Pages: 35-40
ASJC codes: 3200
Keywords: Big five, Facebook, Narcissism, Self-esteem, Social media, Social networking, Status updates

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Status updates are one of the most popular features of Facebook, but few studies have examined the traits and motives that influence the topics that people choose to update about. In this study, 555 Facebook users completed measures of the Big Five, self-esteem, narcissism, motives for using Facebook, and frequency of updating about a range of topics. Results revealed that extraverts more frequently updated about their social activities and everyday life, which was motivated by their use of Facebook to communicate and connect with others. People high in openness were more likely to update about intellectual topics, consistent with their use of Facebook for sharing information. Participants who were low in self-esteem were more likely to update about romantic partners, whereas those who were high in conscientiousness were more likely to update about their children. Narcissists' use of Facebook for attention-seeking and validation explained their greater likelihood of updating about their accomplishments and their diet and exercise routine. Furthermore, narcissists' tendency to update about their accomplishments explained the greater number of likes and comments that they reported receiving to their updates.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Why do some people write Facebook status updates that describe amusing personal anecdotes,
whereas others write updates that declare love to a significant other, express political
opinions, or recount the details of last night’s dinner? Since the inception of Facebook
in 2004, status updates have been one of its most preferred features (Ryan & Xenos, 2011).
Status updates allow users to share their thoughts, feelings, and activities with friends,
who have the opportunity to “like” and comment in return. In spite of the central role of
status updates in Facebook use, few studies have examined the predictors of the topics
that people choose to write about in their updates. The current study took a step in this
direction by examining the personality traits associated with the frequency of updating
about five broad topics identified through a factor analytic approach: social activities
and everyday life, intellectual pursuits, accomplishments, diet/exercise, and significant
relationships. We also examined whether these associations were mediated by some of the
motives for using Facebook identified in the literature (e.g., Bazarova & Choi, 2014;
Seidman, 2013): need for validation (i.e., seeking attention and acceptance), self-
expression (i.e., disclosing personal opinions, stories, and complaints), communication
(i.e., corresponding and connecting), and sharing impersonal information (e.g., current
events). A secondary purpose of this study was to examine whether people who update more
frequently about certain topics receive greater numbers of “likes” and comments to their
updates. Those who do may experience the benefits of social inclusion, whereas those who
do not might experience a lower sense of belonging, self-esteem, and meaningful existence
(Tobin, Vanman, Verreynne, & Saeri, 2015). Our results may therefore shed light on the
status update topics that put Facebook users at risk of online ostracism. Below we review
literature on personality traits and motives that are often linked with Facebook use.

<hs>  The Big Five</hs>
  ~~~~~~~~~~~~

According to the “Big Five” model of personality, individuals vary in terms of
extraversion, neuroticism, openness to experience, agreeableness, and conscientiousness
(Costa & McCrae, 1992). People who are extraverted are gregarious, talkative, and
cheerful. They tend to use Facebook as a tool to communicate and socialize (Seidman,
2013), as reflected in their more frequent use of Facebook (Gosling, Augustine, Vazire,
Holtzmann, & Gaddis, 2011), greater number of Facebook friends (Amichai-Hamburger &
Vinitzky, 2010), and preference for features of Facebook that allow for active social
contribution, such as status updates (Ryan & Xenos, 2011). We therefore predicted that
extraversion would be positively associated with updating about social activities, and
that this association would be mediated by extraverts’ use of Facebook for communication
(Hypothesis 1). Neuroticism is characterized by anxiety and sensitivity to threat.
Neurotic individuals may use Facebook to seek the attention and social support that may be
missing from their lives offline (Ross et al., 2009). Accordingly, neuroticism is
positively associated with frequency of social media use (Correa, Hinsley, & de Zuniga,
2010), the use of Facebook for social purposes (Hughes, Rowe, Batey, & Lee, 2012), and
engaging in emotional disclosure on Facebook, such as venting about personal dramas
(Seidman, 2013). Their willingness to disclose about personal topics led us to predict
that neuroticism would be positively associated with updating about close relationships
(romantic partners and/or children), and that the selection of these topics would be
motivated by their use of Facebook for validation and self-expression (Hypothesis 2).
People who are high in openness tend to be creative, intellectual, and curious. Openness
is positively associated with frequency of social media use (Correa et al., 2010), and
with using Facebook for finding and disseminating information, but not for socializing
(Hughes et al., 2012). We therefore predicted that openness would be positively associated
with updating about intellectual topics, and that this association would be mediated by
the use of Facebook for sharing information (Hypothesis 3). People who are high in
agreeableness tend to be cooperative, helpful, and interpersonally successful.
Agreeableness is positively associated with posting on Facebook to communicate and connect
with others and negatively associated with posting to seek attention (Seidman, 2013) or to
badmouth others (Stoughton, Thompson, & Meade, 2013). The interpersonal focus of agreeable
people and their use of Facebook for communication may inspire more frequent updates about
their social activities and significant relationships (Hypothesis 4). Conscientiousness
describes people who are organized, responsible, and hard-working. They tend to use
Facebook less frequently than people who are lower in conscientiousness (Gosling et al.,
2011), but when they do use it, conscientious individuals are diligent and discreet: they
have more Facebook friends (Amichai-Hamburger & Vinitzky, 2010), they avoid badmouthing
people (Stoughton et al., 2013), and they are less likely to post on Facebook to seek
attention or acceptance (Seidman, 2013). Thus, we predicted that conscientiousness would
be positively associated with updating about inoffensive, “safe” topics (i.e., social
activities and everyday life), which would be mediated by the lower tendency of using
Facebook for validation (Hypothesis 5).

<hs>  Self-esteem</hs>
  ~~~~~~~~~~~

People with low self-esteem are more likely to see the advantages of self-disclosing on
Facebook rather than in person, but because their status updates tend to express more
negative and less positive affect, they tend to be perceived as less likeable (Forest &
Wood, 2012). Furthermore, anxiously-attached individuals – who tend to have low self-
esteem (Campbell & Marshall, 2011) – post more often about their romantic relationship to
boost their self-worth and to refute others’ impressions that their relationship is poor
(Emery, Muise, Dix, & Le, 2014). We therefore hypothesized that self-esteem would be
negatively associated with updating about a romantic partner, and that this association
would be mediated by the use of Facebook for validation (Hypothesis 6).

<hs>  Narcissism</hs>
  ~~~~~~~~~~

Narcissistic individuals tend to be self-aggrandizing, vain, and exhibitionistic (Raskin &
Terry, 1988). They seek attention and admiration by boasting about their accomplishments
(Buss & Chiodo, 1991) and take particular care of their physical appearance (Vazire,
Naumann, Rentfrow, & Gosling, 2008). This suggests that their status updates will more
frequently reference their achievements and their diet and exercise routine (Hypothesis
7). Moreover, the choice of these topics may be motivated by the use of status updates to
gain validation for inflated self-views, consistent with the positive association of
narcissism with the frequency of updating one’s status (Carpenter, 2012), posting more
self-promoting content (Mehdizadeh, 2010), and seeking to attract admiring friends to
one’s Facebook profile (Davenport, Bergman, Bergman, & Fearrington, 2014).

<hs>  Response to status updates</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

We examined whether people receive differential numbers of likes and comments to their
updates depending on their personality traits and frequency of writing about various
topics. People with lower self-esteem tend to receive fewer likes and comments because
their status updates express more negative affect (Forest & Wood, 2012). We tested the
possibility that they may also receive fewer likes and comments because they are more
likely to update about their romantic partner (Hypothesis 8); indeed, people who write
updates that are high in relationship disclosure are perceived as less likeable (Emery,
Muise, Alpert, & Le, 2015). The associations of the Big Five traits, narcissism, and the
other status update topics with the number of likes and comments received were examined on
an exploratory basis to shed light on who may be at risk of receiving less social reward
on Facebook, and whether it is because they express unpopular topics in their updates.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Data was collected from 555 Facebook users currently residing in the United States (59%
female; Mage = 30.90, SDage = 9.19). Sixty-five percent of participants were currently
involved in a romantic relationship, and 34% had at least one child. Fifty-seven percent
checked Facebook on a daily basis, and spent an average of 107.95 min per day actively
using it (SD = 121.41). Ninety percent of participants were recruited through Amazon’s
Mechanical Turk and paid $1.00 in compensation; the rest were recruited through web forums
for online psychology studies, and received no compensation.

<hs>  Materials and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Participants completed an online survey consisting of demographic questions and the
following measures. Cronbach’s alpha coefficients are reported in Table 1.

        <hss>Big Five personality traits</hss>

        The 35-item Berkeley Personality Profile (Harary & Donahue, 1994) measures
        extroversion, neuroticism, openness, agreeableness, and conscientiousness with 7
        items each (1 = Strongly disagree, 5 = Strongly agree).

        <hss>Self-esteem</hss>

        The 10-item Rosenberg Self-Esteem Scale (Rosenberg, 1965) measures self-esteem
        with items such as “I feel that I have a number of good qualities” (1 = Strongly
        disagree, 5 = Strongly agree).

        <hss>Narcissism</hss>

        The 13-item version of the Narcissistic Personality Inventory (NPI-13; Gentile et
        al., 2013) is derived from the original NPI-40 (Raskin & Terry, 1988) and measures
        three components of trait narcissism: need for leadership/authority, grandiose
        exhibitionism, and entitlement/exploitativeness. Items are rated on a forced-
        choice basis, such that one choice represents greater narcissism and the other
        less. Higher scores indicate greater narcissism.

        <hss>Facebook use</hss>

        Participants reported their number of Facebook friends, how many days of the week
        they check Facebook (0–7 days), how much time they spend actively using it on days
        they check it, and how frequently they update their Facebook status (1 = Never, 9
        = 7–10 times a day).

        <hss>Topics of status updates</hss>

        Participants indicated how frequently they write about 20 topics in their Facebook
        status updates (i.e., verbal descriptions of their status excluding photos,
        videos, or emoticons). These topics were generated by the authors through
        laboratory group discussions. Responses were rated on a 5-point Likert scale
        ranging from 1 (Never) to 5 (Very often). To extract common themes across topics,
        we conducted principal axis factoring with promax rotation. This yielded four
        factors with eigenvalues greater than 1 that together accounted for 57% of the
        total variance. Five topics loaded on the first factor, which reflected social
        activities and everyday life (my social activities, something funny that happened
        to me, my everyday activities, my pets, sporting events). Four topics loaded on
        the second factor, which reflected intellectual themes (my views on politics,
        current events, research/science, my own creative output – e.g., art, writing,
        research). Three topics loaded on the third factor, which reflected achievement
        orientation (achieving my goals, my accomplishments, work or school). Two topics
        loaded on the fourth factor, which reflected diet/exercise (my exercise routine,
        my diet). Several topics did not meet Tabachnik and Fidell’s (2007) criteria that
        items must have a minimal loading of .32 on a single factor: three items (my
        children, my religious beliefs, and quotations or song lyrics) were below this
        threshold, and two items cross-loaded (my travels, my views on TV show, movies, or
        music). A final topic (my relationship with my current romantic partner) was not
        included in the factor analysis because it was only completed by participants
        currently involved in a relationship. Of the topics that did not load onto one of
        the four factors, we only further analyzed the frequency of updating about
        children and romantic partners as single variables because of our hypotheses
        regarding the associations of personality traits with updating about significant
        relationships. We also asked participants who they shared each status update topic
        with (no one, the public, friends only, close friends only), but because there was
        little variation across topics in these privacy settings, we did not examine this
        variable further.

        <hss>Motives for using Facebook</hss>

        We measured four motives for using Facebook by adapting items from a variety of
        sources (e.g., Hughes et al., 2012; Seidman, 2013) so that each began with “I use
        Facebook to…”. Use of Facebook for validation was measured with seven items that
        tapped attention-seeking (e.g., “I use Facebook to show off”) and need to feel
        accepted and included (e.g., “I use Facebook to feel loved”). Five items measured
        use of Facebook for self-expression (e.g., “I use Facebook to express my
        identity/opinions”). Three items measured use of Facebook to communicate (e.g., “I
        use Facebook to communicate with people I often see”), and eight items assessed
        use of Facebook to find and disseminate information (e.g., “I use Facebook to stay
        informed”). Participants indicated their agreement with these statements using a
        1–7 Likert scale anchored with Strongly disagree (1) and Strongly agree (7).

        <hss>Likes and comments</hss>

        Participants indicated how many likes and comments, on average, they tend to
        receive when they post a typical Facebook status update.

<h>RESULTS AND DISCUSSION</h>
----------------------

Table 1 reports the descriptive statistics and Pearson’s correlations. Table 2 reports the
results of regression analyses that examined the predictors of updating about each of the
six topics (criterion variables), the four motives for using Facebook (mediating
variables), and the number of likes and comments received to a typical update (criterion
variable). Predictors included several control variables (frequency of updating one’s
status, number of Facebook friends, sex, age) and the traits of interest (Big Five traits,
self-esteem, narcissism). We conducted bootstrap tests of multiple mediation using
Preacher and Hayes’s (2008) SPSS script to assess whether the motives for using Facebook
mediated the associations of the personality traits with updating about certain topics. In
these tests, the control variables and other personality traits were entered as
covariates, and the four motives for using Facebook were entered as multiple mediators.

<hs>  Predictors of status update topics and motives for using Facebook</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 reveals support for Hypothesis 1: extraversion was positively associated with
updating more frequently about social activities and everyday life, and with using
Facebook to communicate. A further regression analysis showed that the use of Facebook to
communicate predicted the frequency of updating about social activities and everyday life
over and above the control variables and other personality traits (b = .25, p < .0001).
Examination of the 95% bias-corrected confidence intervals (CI) from 1000 bootstrap
samples revealed that the positive association of extraversion with updating about social
activities and everyday life was mediated by the use of Facebook to communicate (b = .03,
p = .05 (CI: .003–.05)). These results further confirm that extraverts use Facebook, and
specifically status updates, as a tool for social engagement (Ryan & Xenos, 2011; Seidman,
2013). Hypothesis 2 was only partially supported: neuroticism was not associated with
updating about any of the six topics or with using Facebook for self-expression, but it
was associated with using Facebook for validation. Indeed, neurotic individuals may use
Facebook to seek the attention and support that they lack offline (Ross et al., 2009).
Consistent with Hypothesis 3, openness was positively associated with updating about
intellectual topics, and with using Facebook for information. A further regression
analysis showed that the use of Facebook for information and for self-expression predicted
the frequency of updating about intellectual topics over and above the control variables
and traits (b = .34, p < .0001 and b = .22, p < .001, respectively). The bootstrap test
revealed that the positive association of openness with updating about intellectual topics
was indeed mediated by the use of Facebook for information (b = .03, p < .01 (CI:
.007–.05)). People high in openness, then, may write updates about current events,
research, or their political views for the purpose of sharing impersonal information
rather than for socializing, consistent with the findings of Hughes et al. (2012). There
was no support for Hypothesis 4 – agreeableness was not associated with updating more
frequently about social activities, significant relationships, or with using Facebook to
communicate. Contrary to Hypothesis 5, conscientiousness was not associated with updating
about “safe” topics such as social activities and everyday life; rather, it was associated
with writing more frequent updates about one’s children. Furthermore, conscientiousness
was not negatively associated with using Facebook for validation, but it was positively
associated with using Facebook to share information and to communicate. The latter use
predicted the frequency of updating about one’s children over and above the control
variables and personality traits (b = .38, p = .01), but it did not significantly mediate
the association of conscientiousness with updating about children. Thus, conscientious
individuals may update about their children for purposes other than communicating with
their friends. Perhaps such updates reflect an indirect form of competitive parenting.
Consistent with Hypothesis 6, people who were lower in self-esteem more frequently updated
about their current romantic partner, but they were more likely to use Facebook for self-
expression rather than for validation. That the frequency of updating about one’s romantic
partner was predicted not by the use of Facebook for self-expression but rather by
communication (b = .24, p = .01) suggests that people with low self-esteem may have other
motives for posting updates about their romantic partner. Considering that people with low
self-esteem tend to be more chronically fearful of losing their romantic partner (Murray,
Gomillian, Holmes, & Harris, 2015), and that people are more likely to post relationship-
relevant information on Facebook on days when they feel insecure (Emery et al., 2014), it
is reasonable to surmise that people with low self-esteem update about their partner as a
way of laying claim to their relationship when it feels threatened. In line with
Hypothesis 7, narcissism was positively associated with updating about achievements and
with using Facebook for validation. Moreover, the use of Facebook for validation and for
communication predicted the frequency of updating about achievements over and above the
control variables and traits (b = .14, p = .02 and b = .13, p = .04, respectively). The
association of narcissism with updating about achievements was significantly mediated by
the use of Facebook for validation (b = .04, p = .05 (CI: .006–.07)), consistent with
narcissists’ tendency to boast in order to gain attention (Buss & Chiodo, 1991). Also
consistent with Hypothesis 7, narcissism was positively associated with updating about
diet/exercise, but the use of Facebook for self-expression rather than validation was
positively associated with updating about diet/exercise over and above the control
variables and traits (b = .24, p < .01). Self-expression mediated the association of
narcissism with updating about diet/exercise (b = .03, p = .03 (CI: .003–.04)), suggesting
that narcissists may broadcast their diet and exercise routine to express the personal
importance they place on physical appearance (Vazire et al., 2008).

<hs>  Predictors of likes and comments received</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As seen in Table 2, there was no support for Hypothesis 8: narcissism rather than self-
esteem was associated with receiving a greater number of likes and comments to one’s
updates. We then assessed whether the four topics common to the entire sample – social
activities and everyday life, intellectual pursuits, achievements, and diet/exercise –
predicted the number of likes and comments typically received to an update over and above
the control variables and traits. Updating about social activities and everyday life was
positively associated with the number of likes and comments received (b = .13, p = .05),
as was achievements (b = .16, p = .01), whereas updating about intellectual topics was
negatively associated (b = −.13, p = .04). Two additional regression models added the
frequency of updating about one’s romantic partner or one’s children as predictors for
participants who had a relationship partner or children. Only the frequency of updating
about one’s children significantly predicted likes/comments (b = .23, p = .02). Bootstrap
mediation revealed that the tendency for narcissists to report receiving more likes and
comments was mediated by their higher frequency of updating about their achievements (b =
.06, p < .01 (CI: .01–.18)). Thus, narcissists’ publicizing of their achievements appeared
to be positively reinforced by the attention and validation they crave.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The main limitation of this study is that it was based on participants’ self-reported
Facebook behavior. Narcissists, in particular, may not accurately report the number of
likes and comments they receive to updates. More objective and precise estimates can be
obtained in future research by coding participants’ actual status updates for topic themes
and recording the number of likes and comments received to each topic. Another avenue for
future research is to obtain direct evaluations of particular status update topics and of
the likeability of people who update about these topics. That updating about social
activities, achievements, and children was positively associated with Facebook attention,
and updating about intellectual topics negatively associated, suggests that the former
topics might be evaluated more positively than the latter. Yet these associations are at
best a proxy for the likeability of these topics and of the individuals who write them.
Considering that objective raters can accurately discern whether a person is narcissistic
by looking at their Facebook page (Buffardi & Campbell, 2008), people may be correctly
perceived as narcissistic if they more frequently update about their achievements, diet,
and exercise. Furthermore, people may like and comment on a friend’s achievement-related
updates to show support, but may secretly dislike such displays of hubris. The closeness
of the friendship is therefore likely to influence responses to updates: close friends may
“like” a friend’s update, even if they do not actually like it, whereas acquaintances
might not only ignore such updates, but eventually unfriend the perpetrator of unlikeable
status updates.

<h>CONCLUSIONS</h>
-----------

Taken together, these results help to explain why some Facebook friends write status
updates about the party they went to on the weekend whereas others write about a book they
just read or about their job promotion. It is important to understand why people write
about certain topics on Facebook insofar as the response they receive may be socially
rewarding or exclusionary. Greater awareness of how one’s status updates might be
perceived by friends could help people to avoid topics that annoy more than they
entertain.


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<ART>The General Factor of Personality and daily social experiences: Evidence for the social effectiveness hypothesis
================================================================================

Authors: Dirk H.M. Pelt, Dimitri van der Linden, Curtis S. Dunkel, Marise Ph Born
DOI: 10.1016/j.paid.2019.109738
Year: 2020
ASJC codes: 3200
Keywords: Diary study, General Factor of Personality, Mood, Self-esteem, Social effectiveness

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Using data from the Berlin diary study (N = 1223), we examined associations between the General Factor of Personality (GFP) and daily social experiences, self-esteem, and mood (positive and negative affect). As predicted, high-(vs. low) GFP individuals reported fewer daily interpersonal conflicts, better relationship quality, and better impressions on others. Also, relationship quality and daily impressions both mediated the relation between the GFP and mood and self-esteem. Multilevel analyses showed that, compared to low-GFP participants, high-GFP participants seemed less disturbed when experiencing conflict. In sum, the results were in line with the notion of the GFP as social effectiveness, with important consequences for people's daily social life and well-being.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In the personality literature, several studies suggest the existence of a General Factor
of Personality or GFP (Figueredo, Vásquez, Brumbach & Schneider, 2004) which emerges due
to the intercorrelations among more specific personality dimensions, such as the well-
known Big Five. The GFP constitutes the socially desirable ends of those dimensions and
has now been extensively replicated (e.g., Musek, 2007; Van der Linden, Te Nijenhuis &
Bakker, 2010a). In terms of the Big Five, high-GFP individuals can be described as
relatively open-minded, diligent, sociable, friendly and emotionally stable. Moreover, the
GFP has shown criterion-related validity and is associated with various important life
outcomes, such as job performance and leadership (Van der Linden et al., 2017). Despite
such consistent findings, however, diverging scientific views exist on the interpretation
of the GFP. One view is that the GFP represents social effectiveness (see Van der Linden,
Dunkel & Petrides, 2016 for a review), implying the knowledge, abilities, and the
motivation to generally behave in socially desirable ways. In contrast are views that the
GFP merely represents a methodological artefact, due to, for example, socially desirable
response bias (e.g., Schermer & Holden, 2019), common method variance (e.g., Chang,
Connelly & Geeza, 2012), or other statistical artefacts (Ashton, Lee, Goldberg & de Vries,
2009; Revelle & Wilt, 2013). The different arguments for the substantive versus artefact
views of the GFP have been discussed extensively in several review articles (Irwing, 2013;
Revelle & Wilt, 2013; Van der Linden et al., 2016), and will therefore not be repeated
here. The main point, however, is that there appears to be evidence for each of the
different views. This is not surprising, given that the different explanations of the GFP
need not necessarily be mutually exclusive (Davies, Connelly, Ones & Birkland, 2015;
Dunkel, Van der Linden, Brown & Mathes, 2016). Here, using a comprehensive diary study, we
aim to contribute to the literature by further testing the nature of the GFP. First, we
test the GFP as a social effectiveness factor through its relations with daily social
experiences. Second, we test to what extent the well-documented relation between the GFP
and well-being and mood (Erdle & Rushton, 2011; Musek, 2007) is mediated by the presumed
effective daily social experiences. And third, we test how the GFP moderates the relation
between daily social experiences and daily well-being and mood.

<hs>  The GFP and daily social experiences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Based on social effectiveness perspective, it can be expected that high-GFP individuals
should, on average, also display higher effectiveness in their daily social interactions.
Although the GFP has indeed been linked to various positive social outcomes such as peer-
rated likeability and popularity (Van der Linden, Scholte, Cillessen, Te Nijenhuis &
Segers, 2010b), to our knowledge there are no studies that have tested the relation
between the GFP and social interactions using a diary study. The social effectiveness
hypothesis implies that high-GFP individuals should be able to navigate more easily
through social encounters and would consequently report higher levels of relationship
quality, lower levels of interpersonal conflict, and would leave better impressions on
others. Our first hypothesis thus states: H1. The GFP is negatively associated with daily
(a) interpersonal conflict, and positively associated with daily (b) relationship quality,
and (c) the impressions on others.

<hs>  Mediation of the GFP–well-being/mood relation by daily social experiences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Socially effective behavior on a daily basis may partly explain why, high-GFP individuals
often report enhanced self-esteem and mood (e.g., Musek, 2007). Generally, on days when
people feel socially included, they also tend to experience higher levels of well-being
than on days when they feel more socially isolated. This is known as the Sociometer theory
(Leary, Tambor, Terdal & Downs, 1995), which can link the GFP to both self-esteem and
indicators of social inclusion (e.g., relationship quality): higher GFP levels may be
associated with higher levels of social inclusion, which in turn should result in higher
levels of self-esteem and mood (e.g., Diener, 1984; Gable, Reis & Elliot, 2000). H2. The
positive relations between the GFP, and self-esteem/positive affect and the negative
relation with negative affect are, at least partially, mediated by (a) less daily
interpersonal conflict, (b) better daily relationship quality, and (c) the enhanced daily
impressions on others.

<hs>  Daily social experiences, well-being and mood: GFP moderation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Previous research has shown that personality traits can influence one's reactivity to
daily social events in terms well-being and mood (e.g., Bolger & Schilling, 1991; Denissen
& Penke, 2008). A similar role for the GFP can be expected: Because high-GFP individuals
are more adapted to their social environment and have higher self-esteem (Musek, 2007),
they can be expected to show less fluctuations in mood caused by social events.
Specifically, even though higher GFP levels may imply less negative interpersonal events,
obviously, sometimes negative social events, such as conflicts, will occur. Yet, when they
do, part of the presumed social effectiveness may consist of the ability to adequately
react to such negative events (Hengartner, Van der Linden, Bohleber & Wyl, 2017). For
example, a higher GFP level may allow one to choose a more appropriate reaction to a
conflict, thereby resolving it or preventing escalation. This notion fits with the meta-
analytic finding that the GFP highly overlaps with emotional intelligence (Van der Linden
et al., 2017). Therefore, the following hypothesis can be formulated: H3. The relations
between (a) daily interpersonal conflict (b) daily levels of relationship quality, (c)
daily impressions on others, and daily levels of self-esteem, positive affect and negative
affect, are moderated by the GFP such that the relations are stronger for those with lower
(compared to higher) GFP scores.

<hs>  The present study: using diary data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The majority of previous GFP studies used cross-sectional designs. Although informative,
such designs, however, are limited because they provide a snapshot of ongoing
psychological states and processes. In addition, they rely on people's imperfect ability
to correctly recollect events or behaviors, which can lead to biases and inaccuracies.
Accordingly, scholars have argued for the use of diary methods (Bolger, Davis & Rafaeli,
2003) assessing events and processes as they are naturally occurring, thereby increasing
the ecological validity. Moreover, diary methods are assumed to be less susceptible to
socially desirable response bias than cross-sectional designs (Barta, Tennen & Litt,
2013). This is especially relevant in light of the interpretation of the GFP as purely
artefactual. Intuitively, it may be equally possible to over-report desirable events or
traits on a daily basis as in a single measurement. However, daily reports are often found
to be more accurate than single, one-time measurements (e.g., Presser & Stinson, 1998).
Considering the above, our hypotheses are best tested with daily level data. To this end,
we use data from the Berlin Diary Study by Denissen and colleagues (2005–2008), one of the
largest diary studies in the world.

<h>METHOD</h>
------

Data files, analysis scripts, and supplemental analyses can be accessed at
https://osf.io/kywdf/.

<hs>  Sample and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~

The Berlin Diary Study (2005–2008) consisted of multiple phases, starting with a general
questionnaire, including personality. Participants listed the friend and family member
with whom they had most contact with, and their partner (if present). Then, for 30 days,
participants filled out a daily questionnaire including randomly presented questions on
daily well-being and daily interactions with the two or three identified others in the
previous phase. For additional information on the study design we refer to Denissen and
Penke (2008) and Denissen, Penke, Schmitt and Van Aken (2008), who previously used (parts
of) these data. We decided to include participants who had completed at least 7 diary
entries in order to minimize the influence of idiosyncratic days and assure participants’
commitment (Bolger et al., 2003). The final sample therefore included 1223 German
participants (1055 women, 86%), with an average number of 19.28 (SD =6.81) daily reports.
The average age was 29.47 (SD =10.49). Most people were either single (39%) or in a steady
relationship (40%), without children (79% of the total sample). About 50% of the sample
was relatively highly educated.

        <hss>Personality/GFP</hss>

        The Big Five Inventory (BFI; John & Srivastava, 1999) was used to measure Openness
        (O), Conscientiousness (C), Extraversion (E), Agreeableness (A), and Neuroticism
        (N), and to extract a GFP. Sample coefficient alpha's ranged from 0.72 to 0.90
        (see Table 1). The BFI uses a 5-point Likert-scale format. Principal axis
        factoring was used to extract the GFP from the Big Five. The first unrotated
        factor explained 26.10% of the Big Five variance. The GFP factor loadings of O, C,
        E, A, and N were 0.36, 0.42, 0.66, 0.47, and −0.58 respectively (see Supplementary
        Materials for the convergence across different extraction methods).

        <hss>Daily social experiences</hss>

        Relationship quality. On a five-point scale, participants rated their feelings of
        enjoyment, interest, intimacy, power, important, calm, safe, wanted, and,
        respected, in the interactions with the identified persons. An overall index of
        relationship quality was created by averaging over all indicators across the
        identified others. Interpersonal conflict. Participants were asked whether they
        experienced (0 =not present, 1 =present) a conflict with the identified others on
        financial resources, communication, activities, life plans, encouragement,
        opinions, third persons, and “other topics”. Scores were summed over each day and
        the identified others: a zero indicated no conflict on that day. Because of the
        variable's skewedness, a dichotomized version with 0 indicating no conflict and 1
        indicating any conflict was also created. Impressions on others. A subsample of
        the participants (N = 970) indicated (on a 7-point scale) the impressions they
        made on others during that day on eight different dimensions (competence,
        civility, ethical, artistic, sympathetic, orderly, psychical attractiveness, and
        tolerant). A total (mean) impression on others score was calculated.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

To test H1 and H2, we aggregated the daily social and well-being reports. In the mediation
analyses, due to the large sample size, we focus on the ratio (i.e., the effect size) of
the standardized indirect effect to the total effect, rather than on significance levels.
To test H3, we used multilevel regression analyses, as the data follow a hierarchical
structure with days (Level 1) nested in individuals (Level 2). Multilevel analysis or
hierarchical linear modeling (HLM) provides more accurate parameter estimates and
significance tests than comparable ordinary least squares regression techniques by
accounting for variance at each analysis level. In the present study, the intraclass
correlations ranged between 0.32 and 0.54, indicating significant amounts of variance at
both levels to justify multilevel analyses. In each multilevel model, we included GFP main
effects, daily experiences, and their cross-level interaction. The daily predictors were
person-mean centered (Nezlek, 2001), therefore, a participant's coefficient reflects daily
fluctuations from his/her average level. Models were fitted using the nlme package in R (R
Core Team, 2016; Pinheiro, Bates, DebRoy, Sarkar & R Core Team, 2016). Details on the
multilevel procedure are in the Supplementary Materials.

<hs>  Descriptive statistics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The variables descriptives are presented in Table 1. Participants reported relatively few
conflicts, on average 0.37 conflict per day. Conflicts and relationship quality, although
related (r =−0.33), appeared to assess different aspects of interpersonal relationships.

<hs>  Relations between the GFP and daily social experiences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

GFP scores positively related to daily relationship quality and impressions on others, and
negatively to the number of daily conflicts (Table 1). These results support H1a-H1c.
Interestingly, the relations between the GFP and the daily indicators of social
effectiveness were roughly equal in size or larger than those involving the Big Five and
these outcomes.

<hs>  Mediation Analyses</hs>
  ~~~~~~~~~~~~~~~~~~

There were sizeable correlations between the GFP and daily averaged self-esteem and mood
(see also, Musek, 2007). As the GFP related to the mediators and outcomes, mediation
analyses (Table 2) were permissible. Focusing on the direct/total effect ratio, the most
important mediators were relationship quality and daily impressions. Daily impressions
were the most important mediators of the GFP on the one hand, and self-esteem and PA on
the other hand. For PA, about half of the total GFP effect was mediated by the daily
impressions. Relationship quality was the most important mediator for NA. These results
support the predictions in H2b and H2c. The relation between the GFP, and self-esteem and
mood did not appear to be substantively mediated by the number of conflicts. Thus, only
limited support was found for H2a.

<hs>  Moderation Analyses</hs>
  ~~~~~~~~~~~~~~~~~~~

The HLM-results are presented in Table 3. The hypothesized effects (H3a-H3c) were largely
found for self-esteem and NA. Specifically, the cross-level interactions between the GFP
and the various daily measures resulted in non-trivial decreases of random slope variance
(between 0.10% and 4.37%, interpretable as R2-values). Taking the moderating effect of the
GFP and NA as an example; the within-person SD of impressions was 0.60. Thus, having a bad
day compared to an average day in terms of impressions (−1SD) results in a daily NA
increase of about 0.13 and 0.19 for low-GFP and high-GFP individuals, respectively (Fig.
1A). These effects appear to be small, but should be considered against the within-person
SDs of the outcomes (0.65, 61, and 0.55 for self-esteem, PA and NA, respectively). At
first sight, Fig. 1A may suggest a floor effect because, compared to low-GFP individuals,
high-GFP individuals scored lower on NA and thus have less opportunity to move down the
scale. However, this explanation is at odds with GFP moderation of the relation between
conflict and both NA and self-esteem. For example, for high-GFP individuals, there is
enough leeway for interpersonal conflicts to negatively affect one's daily self-esteem
(Fig. 1B). Yet, as expected, the negative effect of interpersonal conflicts on daily self-
esteem is stronger (i.e., steeper) for those with lower GFP scores. None of the
hypothesized moderations were found with positive affect. Interestingly, opposite to the
hypothesis, the interaction between the GFP and daily impressions on PA was positive: a
day with comparatively bad impressions resulted in a larger decrease of PA for high-GFP
individuals. In conclusion, for daily self-esteem and NA, H3a through H3c were largely
supported, while no support was found for daily PA (H3b).

<h>DISCUSSION</h>
----------

The present study showed that (1) GFP scores were related to daily social experiences and
well-being/mood, (2) daily social experiences partly mediated the relation between the GFP
and well-being/mood, and (3) the GFP related to how individuals react to daily social
events. To the best of our knowledge, this is the first time that the social effectiveness
hypothesis of the GFP is studied using daily reports (with an N of ≈ 1220). This study may
contribute to the literature in four ways. First, we found the GFP to be related to higher
daily relationship quality and less conflicts. These outcomes can be viewed as indicators
of social effectiveness (Denissen et al., 2008) and fit with previous findings showing
that the GFP is related to positive social outcomes such as popularity (Van der Linden et
al., 2010b), job performance and obtaining leadership positions (Pelt, van der Linden,
Dunkel &, Born, 2017). Second, we showed how GFP scores were associated with leaving
better daily impressions on others. Recent studies have confirmed that impression
management is best seen as a stable, substantive trait related to self-control in social
contexts (Uziel, 2010). This definition is similar to the substantive GFP interpretation.
Accordingly, it can be argued that (successful) impression management may be inseparable
from personality (cf. Danay & Ziegler, 2011). A third contribution is our provision of a
potentially relevant mechanism for the strong relationship between the GFP and subjective
well-being (e.g., Musek, 2007). Because social relationships have been proposed to be “the
greatest single cause” of well-being (Argyle, 2001), it may not come as a surprise that
any social skills associated with the GFP would allow for maintaining better social
relationships, in turn, resulting in higher levels of well-being. Fourth, high-GFP (vs.
low-GFP) individuals’ daily mood was less strongly influenced by daily fluctuations in
social interactions and events. This is in line with the GFP as an adaptive trait that not
only reflects social aptness, but that also cushions the impact of adversities (see also,
Hengartner et al., 2017). Counter to our hypotheses, no moderating effects of the GFP were
found on the relations between daily conflict/relationship quality and PA. One possible
explanation is that the participants’ PA-levels resided around the midpoint of the scale,
and daily social experiences may not be salient enough to warrant a reaction at such
levels. In contrast, average self-esteem scores were relatively high and NA scores
relatively low; a deviation from such higher levels will perhaps trigger a more direct
reaction (thus allowing for GFP moderation). At this point, however, this explanation is
rather speculative and should be tested in the future. Salience of a daily experience may
also be responsible for the unexpected finding that fluctuations in daily impressions on
others had stronger effects on the daily PA of high (vs. low) GFP individuals. By far the
largest mediation effect was found for the GFP – daily impressions – PA link. Thus, as
leaving a good impression on others may be especially important for PA, daily successes or
failures in achieving this might to be more pleasing or disturbing, respectively, at
higher GFP levels.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

The main limitation was the exclusive use of self-reports, introducing possible common
method bias. However, diary data can be assumed to partly reduce the biases associated
with self-reports (e.g., recall bias and social desirability). In addition, by using daily
within-person fluctuations, the influence of common method variance is reduced (Beal,
2015). Furthermore, it is unlikely to find cross-level interactions when large amounts of
common method variance are present (Lai, Li & Leung, 2013). Still, lower GFP scores may be
associated with quicker interpretation of a given social situation as a conflict, or with
selecting oneself into conflicts (e.g., Bolger & Schilling, 1991). Future studies should
include other-reports to remedy such drawbacks. Further, although a large community sample
was used, the participants were relatively young, childless, and mostly women. Therefore,
testing our results’ generalizability in more heterogeneous samples would be desirable.

<hs>  Concluding remarks</hs>
  ~~~~~~~~~~~~~~~~~~

This study revealed how the GFP, as a presumed social effectiveness factor, translates to
day-to-day social experiences. Using an extensive diary design, high-GFP individuals were
found to experience fewer interpersonal conflicts, and were less negatively influenced by
potentially disruptive social events. It is not difficult to imagine how the effects of
being socially adaptive and knowing how to respond in social situations on a daily basis
will accumulate and eventually would affect broader life outcomes such as job performance
and better social relations.


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----------

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<ART>The Welsh Single-Use Carrier Bag Charge and behavioural spillover
=================================================================

Authors: Gregory Owen Thomas, Wouter Poortinga, Elena Sautkina
DOI: 10.1016/j.jenvp.2016.05.008
Year: 2016  |  Pages: 126-135
ASJC codes: 3202, 3207
Keywords: Attitudes, Behaviour, Carrier Bag Charge, Policy, Spillover, Sustainability

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

A Single-Use Carrier Bag Charge (SUCBC) requires bags to be sold for a small fee, instead of free of charge. SUCBCs may produce 'spillover' effects, where other pro-environmental attitudes and behaviours could increase or decrease. We investigate the 2011 Welsh SUCBC, and whether spillover occurs in other behaviours and attitudes. Using the Understanding Society Survey (n = 17,636), results show that use of own shopping bags increased in Wales, compared to England and Scotland. Increased use of own bags was linked to increases in six other sustainable behaviours, although changes were significantly smaller in Wales for three of these behaviours. Increased own bag use was linked to stronger environmental views, but effects were weaker in Wales for two out of three measures. We conclude that the Welsh SUCBC effectively encouraged bag re-use, but with minimal changes in other environmental attitudes and behaviours, due to the external motivation to change behaviour.

--------------------------------------------------------------------------------


<hs>  Plastic bag charges</hs>
  ~~~~~~~~~~~~~~~~~~~

In 2010, UK supermarkets provided 7.57 billion single-use plastic bags to shoppers,
accounting for approximately 65,000 tonnes of plastic polymer (WRAP, 2013). The
environmental impacts of plastic bags are can be seen from littering, damage to land and
marine wildlife, oil and energy consumption, and non-biodegradable plastic bag wastage
presents a long-term problem (DEFRA, 2013). Alongside voluntary agreements with producers
and retailers, government policies enforcing a small charge on plastic bags have become
more popular over the last decade, with various policies enacted in countries and sub-
regions across the globe (Miller, 2012). Results of plastic bag charge policies have seen
varied results, often with large variation in the size of the charge levied, the length of
time the charge remained in place, and whether the customer or the retailer paid the
charge (Ritch, Brennan, & MacLeod, 2009). One successful example is the Irish plastic bag
levy introduced in 2002, which not only reduced plastic bag use by approximately 94%, but
also has proved popular among the general public (Convery, McDonnell, & Ferreira, 2007).
Plastic bag use in Ireland has increased since the levy was introduced however, and an
increase in the levy in 2007 (from €0.15 to €0.22) appeared to further reduce bag use,
suggesting that charges for bags may need to be revised for effectiveness (Clarke, 2014).
Wales became the first country in the UK to introduce a minimum charge for single-use
carrier bags in October 2011. The Welsh Single-Use Carrier Bag Charge (SUCBC) requires all
businesses to charge shoppers £0.05 (approx. €0.07 or US$0.08) for each single-use carrier
bag used.1 An alternative for shoppers is to purchase stronger carrier bags, which are
designed to be re-used and brought along by shoppers to the shops. These re-usable bags
are often marketed as “Bags for life”, which can be replaced for free once they have worn
out. The Welsh SUCBC has so far proved very effective (Poortinga, Whitmarsh, & Suffolk,
2013), and the number of single-use plastic bags distributed since 2010 has fallen by 81%,
with an associated decrease in plastic bags used per capita per month from 9.7 plastic
bags in 2010, to 1.8 bags in 2012 (WRAP, 2013).

<hs>  Behavioural spillover</hs>
  ~~~~~~~~~~~~~~~~~~~~~

While the main effects of SUCBCs have focused on reducing the volume of single-use bags,
the potential for a charge to produce additional spillover effects have been noted
(Poortinga et al., 2013). Spillover is a phenomenon where an intervention targeted at
increasing one behaviour may lead to an increase or decrease in other, untargeted
behaviours (Thøgersen, 1999; Truelove, Carrico, Weber, Raimi, & Vandenbergh, 2014).
Positive pro-environmental behavioural spillover effects have been reported in a number of
contexts. Studies have found links between an increase in recycling and using less
resources (Thøgersen, 1999); purchasing of organic goods, sustainable transport and
recycling (Thøgersen & Ölander, 2003); greater purchasing of sustainable items and
increases in several other sustainable behaviours (Lanzini & Thøgersen, 2014); and between
fuel efficient driving and eating less meat (Van der Werff, Steg, & Keizer, 2013). The
potential for spillover to enhance pro-environmental interventions has seen great interest
for government policymakers as a cost-effective and non-intrusive way to change multiple
behaviours (Thøgersen & Crompton, 2009), with the UK government highlighting the potential
for “catalytic” behaviours to strengthen environmental lifestyles (DEFRA, 2008, p. 22).
Several processes have been suggested to explain positive behavioural spillover effects.
One approach utilises cognitive dissonance theory (Festinger, 1962), where a person acting
pro-environmentally in one area, whilst neglecting another area, can develop an
uncomfortable sensation of inconsistency which may spur other pro-environmental
behaviours: especially if the person is already environmentally motivated (Thøgersen,
2004). An alternative explanation is based on self-perception theory (Bem, 1972) which
states that we reflect on our actions to determine, in part, our identity. After
performing a behaviour (e.g., recycling) we may be more favourable to other behaviours,
based on the fact that we are now a ‘recycler’ (Holland, Verplanken, & Van Knippenberg,
2002). It has also been theorised that enacting a pro-environmental behaviour may generate
more favourable views to wider environmental issues, which may influence the person in the
future (Cornelissen, Pandelaere, Warlop, & Dewitte, 2008), and also that people may
develop more skills and greater self-efficacy to enact other behaviours after successfully
performing an initial action (Thøgersen, 2012). The evidence for behavioural spillover is
however mixed, with a range of positive and negative results, and a lack of detailed
investigation into the mechanisms behind spillover effects (Austin, Cox, Barnett, &
Thomas, 2011; Truelove et al., 2014). The discussion of negative spillover also presents a
problem to understanding the phenomenon, when the targeted increase in one sustainable
behaviour is matched by a reduction in a non-targeted behaviour (Thøgersen & Crompton,
2009). People may be inclined to undertake small and easy pro-environmental behaviours,
which are often over-emphasised for their environmental effectiveness (Pieters, Bijmolt,
Van Raaij, & de Kruijk, 1998). Undertaking these small behaviours may reduce the
likelihood of people engaging in other environmentally beneficial actions, justified by
already “playing one’s part” to help the environment, without the need for further action
(Thøgersen & Crompton, 2009; Thøgersen, 1999). Justifications based on current pro-
environmental behaviour may extend further and allow people a “moral licence” to initiate
un-sustainable behaviours that would be permitted after performing some other sustainable
behaviours (Truelove et al., 2014). In a longitudinal experiment where residents of
apartment buildings were encouraged to reduce water consumption, although water use
decreased, there was an increase in electricity use, which may demonstrate a moral
licensing effect (Tiefenbeck, Staake, Roth, & Sachs, 2013).

<hs>  The Welsh SUCBC and behavioural spillover</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A difficulty with evaluating behavioural spillover is the varied research on the topic.
Evidence for behavioural spillover largely exists by correlating the frequency of two
behaviours, and inferring the potential for spillover between them (Austin et al., 2011;
Lanzini & Thøgersen, 2014; Truelove et al., 2014; Whitmarsh & O’Neill, 2010). Reviews of
behavioural spillover have highlighted the scarcity of research evaluating people’s
changes over time (Austin et al., 2011; Truelove et al., 2014), and thus far there only
have been a handful of experimental (e.g., Lanzini & Thøgersen, 2014; Tiefenbeck et al.,
2013) and longitudinal (e.g., Thøgersen & Ölander, 2003; Van der Werff, Steg, & Keizer,
2014) studies examining behavioural spillover. Additional research into behavioural
spillover is warranted not only to improve our understanding of the phenomenon, but given
the UK government’s interest in creating ‘catalyst’ behaviours to encourage other
sustainable behaviours (DEFRA, 2008), there is a need to provide evidence for policy
makers to implement effective and suitable measures (Truelove et al., 2014). Of interest
to the current study is the work by Poortinga et al. (2013), who surveyed independent
samples of respondents in England and Wales 2 weeks prior, and 6 months after the Welsh
SUCBC implementation. Poortinga et al. (2013) found that in Wales the practice of bringing
own shopping bags increased, and that support for the SUCBC increased, but were unable to
detect any positive behavioural spillover effects. But by analysing independent samples
before and after the SUCBC was introduced, Poortinga et al. (2013) evaluated results at a
national level, and were unable to determine changes at the individual level where
behavioural spillover effects would be observed. Longitudinal analysis of the Welsh SUCBC
is therefore required for more detailed investigation. But there is also scepticism that a
SUCBC could encourage positive behavioural spillover effects, with concerns over the
influence of internal and external motives on behaviour (Austin et al., 2011). Models
explaining behavioural spillover effects often use personal identity and threats to
consistency as drivers of behavioural spillover (Truelove et al., 2014). One threat to the
identity and consistency explanations for behavioural spillover is that a SUCBC represents
an external motive to change behaviour in order to avoid a charge (Poortinga et al.,
2013). As stated in self-determination theory (Ryan & Deci, 2000), motivation exists on a
continuum from intrinsic motivation, where behaviour is enacted out of personal enjoyment
and satisfaction, through to extrinsic motivation, where behaviours stem from compliance
with external rewards and punishments. It has been argued that policies that use external
charges to change behaviour could weaken potential positive spillover effects by weakening
intrinsic motivation or reducing threats to personal identity and consistency, which may
then lead to negative spillover effects (Truelove et al., 2014). The implementation of the
Welsh SUCBC, and lack of such policies (at the time) in England or Scotland offers an
opportunity to evaluate whether external regulation may be linked to positive or negative
spillover effects. Therefore, we investigated possible behavioural spillover effects
linked to the Welsh SUCBC, and whether this external pressure to change behaviour is
linked to positive or negative changes in other pro-environmental behaviours, compared to
UK countries with no external impetus to change (i.e., no SUCBC). To evaluate the topic,
we analysed data from the Understanding Society Survey (USS). The USS is the largest
longitudinal panel survey in the world, collecting data from approximately 40,000
households across the UK, and contains several measures of pro-environmental behaviours
attitudes for analysis (University of Essex, 2015).

<h>AIMS</h>
----

The paper has three aims. First, we will examine how bag re-use behaviour has changed in
Wales, England, and Scotland. We hypothesise that the SUCBC will have increased bag re-use
behaviour in Wales, and that the increase will be greater than in England or Scotland
(Hypothesis 1). Second, we investigate whether increased frequency of taking own shopping
bags is linked to increases in other pro-environmental behaviours. We hypothesise that
because the SUCBC is an external motivation, increases in taking own shopping bags wil not
lead to positive changes in other pro-environmental behaviours in Wales, but England and
Scotland will demonstrate a positive link between an increase in own bag use and other
behaviours (Hypothesis 2). Third, we will identify whether increased use of own shopping
bags is associated with an increase in strength of pro-environmental views. Again as an
external influence, we hypothesise that countries where bag re-use could be attributable
to internal motivations (i.e., England and Scotland) will show positive links between
increased bag re-use and stronger pro-environmental views, in contrast to Wales where
external motivation from the SUCBC may have a weaker effect on changing personal views
(Hypothesis 3).

<hs>  The Understanding Society Survey</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The USS collects data in ‘waves’ over 24 months; Wave 1 ran during 2009/10, and Wave 4
during 2012/13 with data collected using face-to-face interviews. Contents of each Wave
vary, and Waves 1 and 4 included questions on environmental attitudes and behaviours,
including a question on the frequency of bringing one’s own bag when shopping. This allows
a longitudinal measure of changing attitudes and behaviour between 2009/10 and 2012/3,
ideal for evaluating effects of the Welsh SUCBC implemented in 2011. In addition, the USS
is designed to be representative of the UK population and allows comparison between Wales,
England and Scotland. The USS is available online, and the 6th edition dataset was
downloaded on 19th January 2015 (University of Essex, 2015).

        <hss>Environmental behaviours</hss>

        Waves 1 and 4 measured the frequency of 11 pro-environmental behaviours: leaving a
        TV on standby (reverse coded), switching off unused lights, running a tap while
        brushing teeth (reverse coded), putting on clothes instead of turning up home
        heating, not buying items because of wasteful packaging, buying recycled paper
        products, taking a bag when shopping, using public transport, walk/cycle short
        journeys, car sharing, and taking fewer flights. Behaviours were measured on a
        5-point frequency Likert scale from “Always” to “Never”. Descriptive statistics of
        the frequency of these behaviours at Wave 1 and Wave 4, are shown in Table 1, with
        higher scores indicating greater sustainability.

        <hss>Views on environmental lifestyles</hss>

        Three items measured perceptions of pro-environmental lifestyles using varying
        Likert scales. First, the item “Which of these best describes how you feel about
        your current lifestyle and the environment?” was measured using a 3-point scale
        from “I’m happy with what I do at the moment” to “I’d like to do a lot more to
        help the environment”, where higher scores indicate greater desire to increase
        one’s environmental lifestyle. Second, the item “Which of these would you say best
        describes your current lifestyle?” was measured using a 5-point scale from “I
        don’t really do anything that is environmentally-friendly” to “I’m
        environmentally-friendly in everything I do”, where higher values indicate having
        a stronger environmental lifestyle. Third, the item “Do you agree or disagree that
        being green is an alternative lifestyle, it’s not for the majority” was measured
        using a 4-point scale from “Agree strongly” to “Disagree strongly”, where higher
        scores indicate greater disagreement that a green lifestyle is unsuitable for the
        majority. The three items had very low internal reliabilities (Cronbach’s α = 0.24
        and 0.25 for Wave 1 and 4 respectively), and therefore are treated as individual
        measures.

        <hss>Demographics</hss>

        To control for variation in demographics between UK countries, and noting the link
        between demographic factors and environmental concern (Hawcroft & Milfont, 2010),
        we sought to control for possible confounding influences. The USS measured
        respondent’s age and gender, and included a calculated monthly income for each
        household based on all reported sources of income.

<hs>  Data preparation & final sample</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

All analyses used SPSS v.20. Data for Wave 1 and 4 were merged, selecting only
participants who completed both Waves. We excluded people living in Northern Ireland (n =
1,242). The Northern Irish SUCBC was introduced in April 2013, and although outside the
timespan of Wave 4, the charge had been discussed in the media at least 12 months
beforehand (BBC, 2012), which may influence behaviours and attitudes in Wave 4 responses.
The USS provides predetermined weights that allows generalisation of results to the UK
population, and the weight d_indscus_lw was applied (Knies, 2014, p. 49). The final
weighted dataset contained 17,636 respondents living in Wales, England, and Scotland, and
all figures shown have weighting applied. A description of the final dataset is shown in
Table 2. One-way ANOVA indicated that age was significantly different among the three
countries, (F (2, 17,632) = 5.91, p = 0.003), with post-hoc tests (Tukey HSD) suggesting
that the Wales sample was significantly older than the England sample, though of very
small effect size (p = 0.022, Hedge’s g = 0.09), and no significant difference between
England and Scotland (p = 0.05) or Scotland and Wales (p = 0.81). Pearson’ Chi-Squared
test indicated there was no significant variation in gender between the three countries,
X2 (2) = 4.88, p = 0.11. One-way ANOVA also indicated that monthly household income was
significantly different among countries, F (2,17,632) = 17.11 p < 0.001, with post-hoc
tests (Tukey HSD) indicating Wales had a lower monthly income than England (p < 0.001,
Hedge’s g = 0.19) and Scotland (p = 0.004, Hedge’s g = 0.14) samples, with no significant
difference between Scotland and England (p = 0.09).

<hs>  Changes in frequency of bringing own shopping bags</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First we explore how respondents in Wales changed their bag re-use behaviour between
2009/10 (Wave 1) and 2012/13 (Wave 4) as compared to respondents in England and Scotland.
Using a repeated measures ANCOVA, mean frequency of taking own shopping bags at Wave 1 and
Wave 4 was compared for the three UK countries, controlling for age, gender and monthly
household income. Results indicated that, in general, frequency of taking own shopping
bags changed between Waves 1 & 4, F (1, 18,386) = 17.67, p < 0.001, partial η2 = 0.001, an
extremely small effect where taking own shopping bags generally reduced over time.
Covariate of age was not significantly related to changes in bag reuse (F (1, 18,386) =
0.91, p = 0.34), while gender showed an extremely small effect where women reduced how
often they took their own shopping bags over time (F (1, 18,386) = 14.17, p = <0.001), and
monthly income had an extremely marginal effect, F (1, 18,386) = 4.78, p = 0.029, partial
η2 < 0.001. These effects were overshadowed by a stronger Time × Country interaction, F
(2, 18,386) = 132.30, p < 0.001, partial η2 = 0.014, indicating that frequency of taking
own bags varied over time between the countries. Using the frequency of taking own
shopping bags, from ‘Never’ (1) to ‘Always’ (5), the significant interaction is displayed
in Fig. 1. Using repeated measures effect size calculations (Lakens, 2013), simple
pre/post comparison of mean bag use frequency scores for England and Scotland both show
very small decreases, Hedge’s grm = 0.05. For Wales, the change in frequency score was
Hedge’s grm = 0.48, a conventionally “medium” sized increase in the frequency of bringing
own bags to shops (Cohen, 1988).

        <hss>Proportion ‘always’ taking their own shopping bag</hss>

        The proportion of people who indicated on the Likert-scale that they “always” took
        their own shopping bag when they went shopping was compared for countries at Wave
        1 and Wave 4, with results highlighted in Fig. 2: At Wave 1, Chi-squared tests
        indicated no significant difference in the proportion of people ‘always’ taking
        their own shopping bag, X2 (2,17,102) = 1.11, p = 0.58, with around 47% of
        respondents in each country “always” doing so. At Wave 4, chi-squared test found a
        significant difference between GB countries, X2 (2,17,228) = 313.81, p < 0.001,
        Cramer’s V = 0.14, indicating while that 44% of English and 41% of Scottish
        respondents ‘always’ took a bag when shopping, 74% of respondent in Wales ‘always’
        took their own shopping bag. With significant changes in the frequency of taking
        own shopping bags in Wales, and little to no change in behaviour for England and
        Scotland, Hypothesis 1 is supported.

<hs>  Change in bringing own bags and behavioural spillover</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Next, we investigated whether changes in bag re-use behaviour were associated with
positive or negative changes in ten other pro-environmental behaviours measured within the
USS. As no major differences in behaviour or demographics were observed between England
and Scotland, these groups were merged into a general sample to simplify interpretation of
results when comparing against Wales. To investigate positive or negative behavioural
spillover and changes in lifestyle views, we emulated the method by Lanzini and Thøgersen
(2014) where the dependent variable is the change of the target measure (i.e. Wave 1 of
measure X is subtracted from Wave 4 score of measure X). Then, the baseline measure of the
target variable (i.e. Wave 1 score of measure X) is added as a covariate in a regression
model to control for regression to the mean effects, and then the change between Wave 1
and 4 of the frequency of taking own shopping bags (“Bag Change”) is included as an
independent variable. This approach controls for baseline changes in the target variable,
allowing any change in the target variable to be linked to changes in the catalyst
behaviour. In addition, we control for respondent’s age, gender (dummy coded where female
= 1 and male = 0), and monthly household income. To evaluate differences between
countries, we included a dummy coded variable for Wales against England and Scotland
samples (“Country”, where England & Scotland = 0 and Wales = 1), and an interaction
between change in frequency of taking own bags and country; change in bag use was mean-
centred prior to specifying the interaction term (Aiken, West, & Reno, 1991). To conserve
space, a summary of coefficients for change in bag re-use behaviour predicting changes in
other environmental behaviours, and the Country × Bag Change interaction (controlling for
baseline and covariates), are shown in Table 3. Full details of model coefficients are
available upon request. Results indicate that a general increase in taking own shopping
bags is associated with an increase in six other pro-environmental behaviours. These
effects are generally small, with standardised regression coefficients ranging around
0.11, below the conventional ‘small’ effect size of 0.20 (Cohen, 1988). In addition to
these general effects, three interaction terms were significant, indicating that the Wales
sample was significantly different than England and Scotland samples in their association
between changes in taking own shopping bags and changes in other sustainable behaviours.
For illustration, interactions were plotted using unstandardised regression coefficients
using Jeremy Dawson’s excel macros2 and shown in Figs. 3–5. Simple slopes analysis
indicates that for changes in frequency of turning off the tap when brushing teeth, a
positive regression slope for England and Scotland is significant, B = 0.17, t (16,611) =
4.63, p = <0.001, and a positive but weaker slope for Wales is also significant, B = 0.03,
t (16,611) = 3.85, p = <0.001. Simple slopes analysis show that for changes in frequency
of wearing warm clothes instead of turning on the heating, the positive regression slope
for England and Scotland is significant, B = 0.09, t (16,666) = 3.12, p = 0.002, and the
positive but weaker regression slope for Wales is significant, B = 0.04, t (16,666) =
5.18, p < 0.001. Simple slopes analysis indicates that for changes in frequency of using
public transport, the positive regression slope for England and Scotland is significant, B
= 0.11, t (15,267) = 3.77, p < 0.001, and the positive but weaker regression slope for
Wales is significant, B = 0.04, t (15,267) = 5.78, p < 0.001. Interaction results show
that while England and Scotland samples show that an increase in bringing own shopping
bags predicts an increase in three unrelated pro-environmental behaviours, suggesting
positive spillover effects, the Wales sample showed much weaker and only marginal
increases between changes in bringing own shopping bags and these three other pro-
environmental behaviours. The results therefore partially support Hypothesis 2, indicating
that where a general increase in bringing own shopping bags predicted an increase in six
other behaviours, three of these links were significantly weaker for the Wales sample.

<hs>  Changes in bringing own shopping bags and changes in lifestyle views</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Next we investigated whether the observed changes in behaviour were associated with
positive or negative changes in environmental views. Analysis used the same method as
before, by including baseline measures of the target variable as a covariate, and an
interaction term to compare results between Wales and the England and Scotland samples for
possible links to the SUCBC. The USS included three questions that captured individual
aspects of environmental lifestyle: desire to increase environmental lifestyle, strength
of environmental lifestyle, and the perception of being ‘green’ as an alternative
lifestyle. Changes in each measure, and their potential links with changes in frequency of
taking own shopping bags, are explored below.

        <hss>Desire to increase environmental lifestyle</hss>

        Regression analysis predicting a change in people’s desire to increase their
        environmental lifestyle was run, where a higher score indicates a greater desire
        to increase one’s environmental lifestyle, as predicted by changes in frequency of
        taking own shopping bags, is shown in Table 4. Results indicate that an overall
        increase in taking own shopping bags is linked to a small decrease in the desire
        to do more environmental actions. However, with an interaction effect between
        change in bag re-use and country, regression slopes between the two samples were
        significantly different. This interaction is shown in Fig. 6. Simple slopes
        analysis indicates that the negative regression slope for England and Scotland was
        significant, B = −0.04, t (16,684) = 2.71, p = 0.007, and the negative regression
        slope for Wales was significant but weaker, B = −0.01, t (16,684) = 2.84, p =
        0.005. Results show that in England and Scotland, an increase in taking your own
        bag when shopping was linked to a decreased desire to increase current
        environmental lifestyle (i.e., increased satisfaction with current level of
        behaviour), whereas in Wales, any changes in own shopping bag behaviour is linked
        to only a fractional reduction in the desire to do more environmental actions.

        <hss>Strength of current environmental lifestyle</hss>

        Analysis predicting changes in perceived strength of environmental lifestyle was
        run, where a higher score indicates a stronger environmental lifestyle, predicted
        by changes in taking own shopping bags, is summarised in Table 5. Results in Table
        5 indicate that overall, an increase in bag re-use behaviour was associated with a
        very small increase in people’s perceived strength of their environmental
        lifestyle. No significant interaction effect was found, indicating that the Wales
        sample did not significantly vary from the English and Scottish sample.

        <hss>Perception of ‘green’ lifestyle for the majority</hss>

        Analysis predicting change in the perception of a ‘green’ lifestyle as acceptable
        for the majority, where a higher score indicates greater acceptance of a ‘green’
        lifestyle, by changes in taking own shopping bags is summarised in Table 6.
        Results in Table 6 suggest a small, but overall positive association between
        increased use of own shopping bags and increased perception that a ‘green’
        lifestyle is suitable for the majority. Notably, the interaction effect is
        significant, and illustrated in Fig. 7. Simple slopes analysis show that the
        positive regression slope for England and Scotland is significant, B = 0.05, t
        (16,386) = 3.01, p = 0.003, and the positive regression slope for Wales is
        significant, though weaker, B = 0.01, t (16,386) = 3.89, p < 0.001. Results
        indicate that a general increase in bag re-use behaviour is linked to a greater
        perception that a ‘green’ lifestyle is suitable for the majority. The Wales sample
        however, shows only a marginal increase in acceptance of green lifestyles linked
        to an increase in changes in bag re-use behaviour, compared to the stronger
        relationship seen in the England and Scotland sample. The results show that an
        increased frequency of bringing own shopping bags is generally linked to small
        changes in views of living an environmental lifestyle. However, for two of these
        links between own bag use and lifestyle views, a significant interaction indicates
        that the Welsh sample show weaker relationships than the England and Scotland
        sample; therefore these results partially support Hypothesis 3.

<h>DISCUSSION</h>
----------

This paper describes an analysis of the Understand Society Survey (USS) dataset, a
longitudinal and nationally representative survey of the UK population measuring pro-
environmental views and behaviour in 2009/10 and 2012/13. With the introduction of the
Single-Use Carrier Bag Charge (SUCBC) in Wales from October 2011, and with no such
policies implemented in England or Scotland, the USS dataset is an ideal method to
evaluate effects of the SUCBC on bag re-use behaviour. Additionally, the USS was analysed
to establish if the SUCBC may have led to ‘spillover’ effects that occur when starting one
pro-environmental behaviour leads to an increase, or a decrease, in other pro-
environmental behaviours and views. We find that bag re-use behaviour increased
significantly in Wales. The mean reported frequency of respondents in Wales bringing their
own bags when shopping saw a significant and conventionally ‘medium’-sized increase
between 2009/10 and 2012/13, whereas respondents in England and Scotland (with no SUCBC
introduced) showed a small decrease in bringing own shopping bags. The reported frequency
of people in England and Scotland “always” taking their own shopping bag showed no change
between 2009/10, whereas in Wales, 74% of respondents reported “always” taking their own
bag, an increase of 25%. Clear differences in behaviour changes in Wales, and a similar
lack of changes in England and Scotland demonstrate the role of the Welsh SUCBC increasing
bag re-use behaviour, and supports Hypothesis 1. The results also confirm previous
research indicating that the Welsh SUCBC increased the proportion of Welsh people bringing
their own bags to shopping trips (Poortinga et al., 2013). Alongside self-reported
behaviour, our findings concur with objective reports of the number of single-use plastic
bags used in Wales, which fell dramatically from before and after the implementation of
the SUCBC (WRAP, 2013). Overall, it appears that the Welsh SUCBC had a clear and positive
effect of reducing use of single-use plastic bags and increasing the frequency of people
bringing their own bags when shopping. We also examined whether a change in the frequency
of bringing own shopping bags was linked to changes in other behaviours and views. Results
show that across the UK, a general increase of taking one’s own bag when shopping was
linked to increases in six other sustainable behaviours: turning off the tap when brushing
teeth, wearing warmer clothes indoors instead of turning up heating, buying recycled paper
products, using public transport, walking/cycling short trips, and carsharing. Linked
increases between taking own shopping bags and other behaviours may suggest that positive
behavioural spillover was occurring. However, we do not believe that the increase in
taking a bag when going shopping is a causal predictor of an increase in these other
sustainable behaviours. In their review of behavioural spillover literature, Austin et al.
(2011) conclude that the nebulous influences of external and internal influences should be
considered before inferring spillover, and that causal inferences between two linked
behaviours is often not possible. The sustainable behaviours that increased would also
defy expectations that a small change in shopping behaviour (i.e., bringing a bag to the
shops) could lead to an increase in more difficult behaviours in other domains (e.g.,
using public transport). Positive behavioural spillover effects are more likely among
behaviours perceived to be similar (Thøgersen, 2004), and more likely to spillover to
other low cost/energy behaviours (Lanzini & Thøgersen, 2014; Thøgersen & Crompton, 2009).
What the results do show is that the frequency of various pro-environmental behaviours
increases over the same time frame; as people increased one behaviour, they may have
increased other, unrelated behaviours. Correlations between sets of pro-environmental
behaviours has been examined before as evidence for potential behavioural spillover
effects (Austin et al., 2011; Truelove et al., 2014; Whitmarsh & O’Neill, 2010). This
analysis offers new insight by demonstrating that in a nationally representative sample,
an increase in the frequency of one pro-environmental behaviour is associated with
increases in other pro-environmental behaviours. The joint increases in frequency of
various sustainable actions thus offer additional support to the idea that positive
spillover may occur between different behaviours. Of note is that the observed effects in
this study are small, with standardised regression coefficients (β) around 0.11 in size,
below the conventional ‘small’ effect size of 0.20 (Cohen, 1988). It appears that the
current results are not an isolated case however. In their review of pro-environmental
spillover effects, Austin et al. (2011) reported that the strength of spillover effects
were generally “weak” (p. 90). Using standardised regression coefficients, effect sizes of
other longitudinal spillover results appear of similar strengths; Van der Werff et al.
(2014) predicted intentions to eat less meat from eco-driving (β = 0.14), and Thøgersen
and Ölander (2003) reported an interplay between recycling, organic food purchases, and
sustainable transport choices that ranged from β = 0.06 to β = 0.13. Even within a tightly
controlled experimental design, Lanzini and Thøgersen (2014) found that an increase in
purchasing ‘green’ items led to increases in six other pro-environmental actions that
ranged between β = 0.14 to β = 0.23. The current results are therefore comparable with the
existing literature, but highlight the small effect sizes linked with behavioural
spillover. Comparing Wales against England and Scotland, we find that of the six
significant links between an increase in taking a pre-owned shopping bag and increases in
other behaviours, three showed that changes in the other behaviours were significantly
weaker in Wales; turning off the tap when brushing teeth, wearing warmer clothes indoors,
and using public transport. In order to explain this result, we also investigated whether
changes in taking own bags was linked to changes in attitudes. Results found that although
a general increase in taking own shopping bags was linked to small increases in three
measures of positive views of environmental lifestyles, two of these items showed
significantly weaker effects in Wales when compared to England and Scotland. Recent
investigations suggest that positive and negative spillover effects may also occur from
sustainable behaviour to support for environmental policies (Lacasse, 2015; Truelove,
Yeung, Carrico, Gillis, & Raimi, in press), and views on environmental lifestyle may also
be affected. It therefore appears that although Wales saw a significant increase in
frequency of taking own shopping bags (likely due to the SUCBC), this increase in
behaviour is linked to lower rates of increases in some other behaviours, and lower
increases in positive views on living environmental an lifestyle. We argue that the Welsh
SUCBC, although effective at increasing the use of own shopping bags, was not as effective
at encouraging wider changes because of the external pressure to change behaviour. In
their review of behavioural spillover, Truelove et al. (2014) suggest that where behaviour
is influenced by external pressure, be it an incentive or disincentive, positive spillover
is less likely to occur as external pressures removes intrinsic motivation which could be
a key motivator for positive spillover effects. In accordance with self-determination
theory (Ryan & Deci, 2000), removing intrinsic motivation for bringing own shopping bags
challenges many theories of how positive behavioural spillover could occur. Cognitive
dissonance theory (Festinger, 1962) suggests that discomfort from inconsistency across
behaviours would encourage other sustainable actions, but cognitive dissonance is not
present when the inconsistency can be attributed to external pressures (Thøgersen, 2004).
Self-perception theory (Bem, 1972) states that identity is modelled partly on actions, so
that a ‘green’ identity is strengthened by performing sustainable behaviours (which then
encourages other similar actions). Yet self-perception theory also highlights that a
person will consider their actions and strengthen their identity only “if that behaviour
appears to be free from the control of explicit reinforcement contingencies” (Bem, 1972,
p. 6). Lastly, positive behavioural spillover pathways from increased knowledge and self-
efficacy (Thøgersen, 2012) would also be challenged by the external disincentive of a
SUCBC, as perceived competence does not enhance intrinsic motivation unless also matched
by a perception of autonomy in the action (Ryan & Deci, 2000), which an external charge
would likely remove. The external motive to change behaviour in Wales, and presumably
internal motivations to change in England and Scotland (with no charge in place), would
therefore explain the weaker changes in other behaviours and views on sustainable
lifestyles seen in Wales. One positive indication from this analysis is that the Welsh
SUCBC, although linked to weaker increases in other behaviours and attitudes, did not show
signs of negative spillover effects; where other behaviours could actually decrease in
frequency. Truelove et al. (2014) suggested that extrinsic motivations to act sustainably,
such as price-based policies, may lead to negative spillover if not correctly enacted.
With no evidence of negative spillover after the Welsh SUCBC, fears of negative spillover
effects may be reduced, but as SUCBCs may need to be increased over time to maintain their
effectiveness (Clarke, 2014), continued monitoring of long-term behaviour change is
required. This analysis is the first longitudinal analysis to evaluate changes in
individual behaviour and views after the implementation of a SUCBC. Previous work by
Poortinga et al. (2013) evaluated the Welsh SUCBC using independent samples representative
of Wales and England before and after the SUCBC. But without observing individual changes
over time, their analysis could not evaluate the personal effects of the SUCBC. With
longitudinal data from a nationally-representative sample of 17,636 respondents, the
current analysis is a substantially higher-powered evaluation of spillover effects.
Nonetheless, our analysis has some caveats to consider. Although longitudinal, we are
unable to show causality between changes. For example, an increase in taking own bag use
in Wales was likely due to the SUCBC, but we cannot predict the cause of the changes in
taking own bags when shopping in England and Scotland. It may be that an increase in
another, unrelated behaviour spilled over to taking own shopping bags in England or
Scotland, but this cannot be determined. The length of time between measurements is also a
factor: the Wave 4 survey was taken on average 36 months after the Wave 1 survey. Although
useful for a large-scale evaluation, there may be several different influences on
behaviour and attitude that occurred during these time points which cannot be conclusively
ruled out. This analysis offers a very large sample for evaluation, but additional work on
the effects of SUCBCs should also be considered, perhaps using more frequent measurements
around the time of implementation of a charge.

<h>CONCLUSIONS</h>
-----------

We find that the frequency of taking own shopping bags significantly increased in Wales,
compared to England and Scotland, which is most likely an effect of the SUCBC. We also
evaluated the potential for the SUCBC to promote positive or negative ‘spillover’ effects,
where the change in the targeted behaviour may have led to an increase, or even a
decrease, in other behaviours. Results show that in general, an increase in taking own
shopping bags is linked to a small increase in six other behaviours, but that this effect
is significantly weaker in Wales than in England or Scotland. Additionally, increased use
of taking own shopping bags had a small, positive link to stronger perceptions of living a
sustainable lifestyle, but again two of these links were significantly weaker in Wales. We
discuss the results in terms of extrinsic versus intrinsic motivation, and argue that the
external motivation to change behaviour in Wales did not lead to changes in other
behaviours or views, compared to the intrinsically-motivated changes in England and
Scotland. Although the SUCBC appears effective at changing behaviour, we do not believe
that positive behavioural spillover effects are likely to be encouraged by SUCBC policies.


<h>REFERENCES</h>
----------

  [4] Lucy J. Hawcroft, Taciano L. Milfont. The use (and abuse) of the new environmental paradigm scale over the last 30 years: A meta-analysis. doi:10.1016/j.jenvp.2009.10.003
  [5] Rob W. Holland, Bas Verplanken, Ad Van Knippenberg. On the nature of attitude-behavior relations: The strong guide, the weak follow. doi:10.1002/ejsp.135
  [7] Katherine Lacasse. The Importance of Being Green: The Influence of Green Behaviors on Americans’ Political Attitudes Toward Climate Change. doi:10.1177/0013916513520491
  [8] Daniël Lakens. Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. doi:10.3389/fpsyg.2013.00863
  [9] Pietro Lanzini, John Thøgersen. Behavioural spillover in the environmental domain: An intervention study. doi:10.1016/j.jenvp.2014.09.006
  [11] Rik Pieters, Tammo Bijmolt, Fred Van Raaij, Mark De Kruijk. Consumers' attributions of proenvironmental behavior, motivation, and ability to self and others
  [13] Wouter Poortinga, Lorraine Whitmarsh, Christine Suffolk. The introduction of a single-use carrier bag charge in Wales: Attitude change and behavioural spillover effects. doi:10.1016/j.jenvp.2013.09.001
  [14] Elaine Ritch, Carol Brennan, Calum MacLeod. Plastic bag politics: Modifying consumer behaviour for sustainable development. doi:10.1111/j.1470-6431.2009.00749.x
  [15] Richard M. Ryan, Edward L. Deci. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. doi:10.1037/0003-066X.55.1.68
  [16] John Thoøgersen. Spillover processes in the development of a sustainable consumption pattern
  [17] John Thøgersen. A cognitive dissonance interpretation of consistencies and inconsistencies in environmentally responsible behavior. doi:10.1016/S0272-4944(03)00039-2
  [19] John Thøgersen, Tom Crompton. Simple and painless? The limitations of spillover in environmental campaigning. doi:10.1007/s10603-009-9101-1
  [20] John Thøgersen, Folke Ölander. Spillover of environment-friendly consumer behaviour. doi:10.1016/S0272-4944(03)00018-5
  [21] Verena Tiefenbeck, Thorsten Staake, Kurt Roth, Olga Sachs. For better or for worse? Empirical evidence of moral licensing in a behavioral energy conservation campaign. doi:10.1016/j.enpol.2013.01.021
  [22] Heather Barnes Truelove, Amanda R. Carrico, Elke U. Weber, Kaitlin Toner Raimi, Michael P. Vandenbergh. Positive and negative spillover of pro-environmental behavior: An integrative review and theoretical framework. doi:10.1016/j.gloenvcha.2014.09.004
  [26] Ellen Van der Werff, Linda Steg, Kees Keizer. The value of environmental self-identity: The relationship between biospheric values, environmental self-identity and environmental preferences, intentions and behaviour. doi:10.1016/j.jenvp.2012.12.006
  [27] Ellen Van der Werff, Linda Steg, Kees Keizer. I Am What I Am, by Looking Past the Present: The Influence of Biospheric Values and Past Behavior on Environmental Self-Identity. doi:10.1177/0013916512475209
  [28] Lorraine Whitmarsh, Saffron O'Neill. Green identity, green living? The role of pro-environmental self-identity in determining consistency across diverse pro-environmental behaviours. doi:10.1016/j.jenvp.2010.01.003
  [30] Daryl J. Bem. Self-Perception Theory. doi:10.1016/S0065-2601(08)60024-6
  [33] Frank Convery, Simon McDonnell, Susana Ferreira. The most popular tax in Europe? Lessons from the Irish plastic bags levy. doi:10.1007/s10640-006-9059-2
  [34] Gert Cornelissen, Mario Pandelaere, Luk Warlop, Siegfried Dewitte. Positive cueing: Promoting sustainable consumer behavior by cueing common environmental behaviors as environmental. doi:10.1016/j.ijresmar.2007.06.002
<ART>The association between personality and cognitive ability: Going beyond simple effects
================================================================================

Authors: Beatrice Rammstedt, Daniel Danner, Silke Martin
DOI: 10.1016/j.jrp.2016.03.005
Year: 2016  |  Pages: 39-44
ASJC codes: 3200, 3207
Keywords: Big Five, Cognitive ability, Education, Literacy, Numeracy, PIAAC, Personality

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

To examine the relationship between the Big Five and cognitive ability, we investigated whether we could replicate in a heterogeneous population sample the positive association between cognitive ability and Openness and Emotional Stability and its negative association with Conscientiousness. Besides analyzing the pure associations, we shed further light on sources of these associations by investigating potential moderating effects of education and labor force participation. Our results clearly replicate the previously found positive association between cognitive ability and Emotional Stability and Openness and the negative relationship between Conscientiousness and cognitive ability. The correlation between cognitive ability and Openness was found to be moderated by educational attainment, the negative association between Conscientiousness and cognitive ability was moderated by labor force participation.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The degree to which personality and cognitive ability are related is a question that has
generated intensive research and intense debate. Some authors have concluded that
intelligence test performance may be influenced by some non-ability traits but that
intelligence and personality are two independent constructs (Zeidner & Matthews, 2000).
Others (e.g., Ackerman, 1996) have argued that personality traits play a significant role
in the development of intellectual skills. With regard to the most well-established model
of personality, the Big Five, numerous studies and meta-analyses have indicated a
substantial but comparatively modest association between personality and intelligence. The
proportion of variance in cognitive ability explained by personality typically ranges
between five and ten percent (Furnham, Dissou, Sloan, & Chamorro-Premuzic, 2007). Studies
have consistently found a positive link between cognitive ability and Openness (see, for
example, meta-analytical results by Ackerman & Heggestad, 1997 and Von Stumm & Ackerman,
2013) and Emotional Stability (e.g., Ackerman & Heggestad, 1997; Moutafi, Furnham, &
Crump, 2003; Zeidner & Matthews, 2000), and a negative association between cognitive
ability and Conscientiousness (e.g., DeYoung, 2011; Furnham et al., 2007; Moutafi et al.,
2003; Soubelet & Salthouse, 2011). In particular, the negative association between
Conscientiousness and cognitive ability appears contradictory at first sight, given that
both intelligence and Conscientiousness are positively associated with work-related
outcomes (e.g., Barrick & Mount, 1991; Gottfredson, 1997; Schmidt & Hunter, 1998). As one
possible explanation for this “mysterious” effect (see Furnham et al., 2007), it has been
suggested that the consistently found negative association between Conscientiousness and
intelligence might be a methodological artifact caused by a sampling bias (e.g., Murray,
Johnson, McGue, & Iacono, 2014; Soubelet & Salthouse, 2011). Almost all of these studies
investigated only college student populations (see Furnham et al., 2007), and thus samples
that are comparatively homogeneous with regard to education, age, labor market experience,
and intelligence itself. Hence, the negative association might have been artificially
created because individuals with low cognitive ability and low Conscientiousness were
missing from the samples (see Major, Johnson, & Deary, 2014). Whether the negative
association between Conscientiousness and cognitive ability can be replicated in a more
heterogeneous adult population and can therefore be regarded as a general effect is a
hitherto unanswered question. Besides offering methodological explanations, some
researchers have also tried to explain the negative association between cognitive
competencies and Conscientiousness substantively. Based on their finding that the
Conscientiousness facet Orderliness, in particular, is negatively correlated with
intelligence, Moutafi et al. (2003) argued that people with lower intelligence use
planning and organization to compensate for their disadvantage on intellectual tasks (for
a rebuttal, see Murray et al., 2014).

<hs>  Measuring cognitive ability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Competence tests, such as those used in the Organisation for Economic Co-operation and
Development’s (OECD) Programme for International Student Assessment (PISA) and the Trends
in International Mathematics and Science Study (TIMSS), are highly correlated with
intelligence. For TIMSS, Lynn and Mikk (2007), for example, report correlations with a
general intelligence factor ranging between 0.92 and 1. Similar results can be found for
PISA (e.g., Rindermann, 2006) and for the National Adult Literacy Survey (NALS;
Gottfredson, 1997). It has even been debated whether the literacy, mathematics (or
numeracy), and science competence tests measure general intelligence from a conceptual and
empirical perspective (Rindermann, 2006). Other researchers have shown, however, that – in
addition to general intelligence – such competence tests assess domain-specific
competencies (e.g., Baumert, Brunner, Lüdtke, & Trautwein, 2007; Gottfredson, 1997). This
debate notwithstanding, it has been clearly shown that – to a large extent – these
competence tests measure general intelligence. Thus, these competence measures can be
regarded as appropriate indicators of cognitive ability. For example, Hunt and Wittmann
(2008) used the PISA 2003 competence measures as a proxy for intelligence to replicate
results on country differences in IQ initially reported by Lynn and Vanhanen (2002). And
Gottfredson (1997) used NALS data to show that general intelligence (g) is associated with
cumulative life outcomes such as labor force participation or living in poverty. Besides
being good indicators of cognitive ability, competence measures used in studies such as
PISA, TIMSS, and the OECD-initiated Programme for the International Assessment of Adult
Competencies (PIAAC; aka “PISA for adults”) have a further advantage compared to the
commonly used IQ data – namely, that they are based on probability samples that are
representative of the respective target populations (PISA: 15-year-olds; PIAAC: adults
between 16 and 65 years of age) in the participating countries.

<hs>  Aim of the present study</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

The present study examines the relationship between personality – in particular, the Big
Five personality domains – and cognitive ability. As indicators of cognitive ability, we
used the competence measures of the literacy and numeracy domains assessed in PIAAC. We
investigated whether it was possible to replicate the previously found positive
association between cognitive ability and Openness and Emotional Stability and its
negative association with Conscientiousness. As it has been suggested that this negative
correlation between Conscientiousness and cognitive ability might be caused by biased –
primarily college student – samples, we investigated whether this effect was in fact less
pronounced in a more heterogeneous adult population. Besides analyzing the pure
associations, we aimed to shed further – or new – light on causes of these links by
examining potential moderating effects of education and labor force participation.

<hs>  Sampling method and participants</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Data for the present study were collected in part within PIAAC. This programme compares
cognitive skills such as literacy and numeracy across a large number of (mainly OECD)
countries. For the present research, we analyzed the German PIAAC data.1 The target
population were adults (aged between 16 and 65 years) randomly selected from local
population registers in randomly selected municipalities throughout Germany. Participation
in PIAAC was voluntary; an incentive of 50 euros was offered upon participation in the
survey, which comprised a personal interview (average duration: 45 min) and a cognitive
assessment lasting approximately 60 min. No time limit was imposed on the cognitive test.
A detailed description of the sampling procedure and the technical implementation is given
in Zabal et al. (2014). In addition to the PIAAC study conducted in 2012, 3758 of the
original 5465 participants in Germany were re-interviewed in 2014 as part of the PIAAC
Longitudinal Study (PIAAC-L).2 Data from the 2012 German PIAAC wave and the 2014 follow-up
survey were combined and used for the present analyses.

<hs>  Measures and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The following variables from PIAAC 2012 were investigated: Verbal and numerical cognitive
ability: Literacy and numeracy skills assessed in PIAAC were used as measures of verbal
and numerical cognitive ability. Both competencies were assessed using a multistage
adaptive testing design comprising a total of 58 items for literacy and 56 items for
numeracy. Using a largely randomized procedure, respondents were allocated to the
competence domains. Detailed information on the nature of the test and a selection of
sample items are provided in the reader’s companion for the survey (OECD, 2013a, pp. 17).3
For each participant, 10 plausible values were estimated for each competency domain. (For
details of the design and the IRT scaling process in PIAAC, see OECD, 2013b). Analyses of
the cognitive data were run separately for each of the ten plausible values per domain.
Results were then averaged within each domain. Education: Each respondent’s highest level
of educational attainment was assessed with two separate questions (highest general
education and highest vocational education qualification in the categories of the German
education system), which were then mapped to the 1997 International Standard
Classification of Education (ISCED 1997; [PIAAC 2012 variable: B_Q01a]).4 Forty-one
respondents who reported that they had a foreign educational qualification for which they
were unable to state the German equivalent were excluded from the analyses. In addition
variables from the 2014 PIAAC-L follow-up were used for the present analyses: Labor force
participation: All respondents were asked to report whether they were currently employed
and, if not, what their current status was (PIAAC-L 2014 variable: perw_14). Based on
this, a dichotomous variable was generated and used in the analyses (1 = in full-time
employment, 0 = not in full-time employment).5 Respondents who indicated that they were
still undergoing education were excluded from the analyses. The rationale behind dividing
respondents into two groups – full-time employed and not full-time employed – was (1) to
separate respondents for whom working is the most substantial part of their everyday lives
from other respondents, (2) to create categories of similar size, and (3) to simplify the
interpretation of the interaction term by creating a binary variable. In addition, a short
version of the Big Five Inventory (BFI; John, Donahue, & Kentle, 1991) comprising three
items per dimension was administered to respondents in the 2014 follow-up survey to assess
their personality. This 15-item questionnaire – originally developed for use in the German
Socio-Economic Panel (SOEP; Schupp & Gerlitz, 2014) – contains short statements, which are
rated on a seven-point Likert scale ranging from 1 = “does not apply at all” to 7 =
“applies completely.” Studies investigating the reliability and validity of this BFI-S
have concluded that its psychometric properties were acceptable (e.g., Hahn, Gottschling,
& Spinath, 2012). In the present sample, Cronbach’s alpha for the BFI-S scales ranged
between 0.41 for Agreeableness and 0.69 for Extraversion.6 As our study design – though
longitudinal – includes only one assessment of cognitive abilities and personality,
respectively, we subjected the data to cross-sectional analysis.

<h>RESULTS</h>
-------

To what degree is personality related to a person’s cognitive ability? To investigate this
question, we correlated the scale scores for the Big Five dimensions with the estimates
for verbal and numerical ability. Besides means and standard deviations for the five
personality domains, Table 1 shows the resulting correlations between the Big Five and
verbal and numerical ability. For both competency domains, the strongest correlation found
was with Emotional Stability (0.11 and 0.14, respectively), indicating that emotionally
stable persons have, on average, higher verbal and numerical abilities. In addition, both
abilities were found to be significantly negatively related to Conscientiousness (−0.09
and −0.08, respectively). Smaller, but still significant, correlations were found between
both cognitive abilities and Openness and Extraversion, indicating that introverts (−0.05
and −0.06, respectively) and open persons (0.05 for both domains) have, on average, higher
cognitive abilities. In a second step, we analyzed the degree to which the Big Five
personality domains incrementally predict cognitive ability. Studies have shown that
intelligence is highly related to education and to work outcomes (e.g., Gottfredson, 1997;
Schmidt & Hunter, 1998). We therefore investigated the extent to which the Big Five
contribute to predicting intelligence over and above education and labor force
participation. In a first step, we conducted regression analyses including only the Big
Five personality domains. As a recent study (Major et al., 2014) demonstrated that there
are also quadratic associations between personality and cognitive ability, we included
both linear and quadratic relations in our analyses. In a second and third step, we then
included in the regression analyses (a) the highest level of educational attainment and
(b) labor force participation. As the highest level of educational attainment is a valid
predictor only for those participants who have completed their initial formal education,
we excluded all participants from further analyses who reported that they were still
undergoing education (N = 544). We conducted the regression analyses separately for each
of the ten plausible values and then averaged the regression coefficients across the ten
analyses. The regression results for all three analyses – (1) Big Five only, (2) Big Five
and highest educational qualification, and (3) Big Five, highest educational
qualification, and labor force participation – are displayed in Table 2. When only the Big
Five domains were included in the model, Emotional Stability was the strongest predictor
of intelligence, followed by Extraversion, Openness, and Conscientiousness; both
Extraversion and Conscientiousness were negatively correlated with cognitive ability. In
addition to these linear effects, a small quadratic association of Conscientiousness with
both cognitive abilities was also detected, which indicates that very high
Conscientiousness scores, in particular, are associated with lower cognitive ability.
Overall, the model explained four and six percent of the variance in the two domains,
respectively. In a second step, we investigated the degree to which the Big Five explained
additional variance over and above the highest educational qualification, as the primary
predictor of cognitive ability. In addition, we analyzed whether the personality domains
interacted with the educational qualification in predicting cognitive ability – in other
words, whether the ability of persons with higher or lower education was more sensitive to
personality effects. We therefore included the highest educational qualification in the
regression. Results reveal that – for both domains – the effects of personality on
cognitive ability decreased after controlling for education. Only Emotional Stability
(0.06 and 0.10, respectively) and (low) Conscientiousness (−0.11/−0.07 and −0.09/−0.07,
respectively) were found to have substantial associations with verbal and numerical
ability over and above the educational qualification. In addition to these main effects
for both skill domains, Openness significantly interacted with education level in
predicting cognitive ability (−0.09 and −0.08, respectively), indicating that persons with
a lower level of educational attainment benefit from high Openness with regard to their
cognitive abilities. In a third step, we analyzed (a) whether the Big Five were still
predictive of cognitive ability when both educational attainment and labor force
participation (in full-time employment vs. not in full-time employment) were taken into
account, and (b) whether this predictiveness varied across full-time employed and not
full-time employed respondents. Results regarding the remaining main effects for
personality after controlling for both educational attainment and labor force
participation7 are slightly different for the two cognitive abilities: In the case of
verbal ability, none of the Big Five domains proved to have a significant direct
relationship with the ability level, whereas in the case of numerical ability, Emotional
Stability (0.06) followed by Extraversion (−0.06) predicted a significant share of ability
after controlling for education and labor force participation. However, the interactions
of personality and labor force participation in predicting cognitive ability were
absolutely parallel across both domains. Conscientiousness significantly interacted with
labor force participation in predicting intelligence (−0.09 for both domains), which
indicates that among persons in full-time employment, Conscientiousness is negatively
associated with cognitive ability; no such relationship was found among non-employed
persons or persons in part-time employment.8

<h>DISCUSSION</h>
----------

The present study investigated the relationship between personality and cognitive ability.
As previous studies have been criticized for investigating student populations only, we
examined whether the previously found associations between cognitive ability and Openness
and Emotional Stability and its negative association with Conscientiousness could be
generalized to a heterogeneous adult population. By analyzing data from the German PIAAC
and PIAAC-L surveys – using the competence estimates for literacy and numeracy as
indicators of verbal and numerical cognitive ability – we also investigated the degree to
which these associations replicated in a linguistic and cultural setting other than those
featured in earlier studies that focused on US or British samples. Based on this
heterogeneous sample, the magnitude of the variance explained by the Big Five personality
domains is, overall, highly comparable with that reported by earlier studies in this field
that were based on selective samples (see Furnham et al., 2007). In addition, our results
clearly replicated the positive association typically found between cognitive ability and
Emotional Stability; this replication was completely consistent across verbal and
numerical ability. In addition, we were also able to confirm the positive relationship
between cognitive ability and Openness. However, the latter effect was found to interact
with the person’s level of educational attainment: High Openness was a predictor of
cognitive ability only for persons with low educational qualifications. For highly
educated persons, by contrast, no such relationship could be identified. Our results thus
suggest that being open-minded and intellectually interested can be beneficial to the
intellectual development of persons socialized in intellectually less stimulating
surroundings – that is, persons who leave the education system early. Alternatively, it
could be that persons with comparatively higher cognitive ability leaving the educational
system early become more open-minded and curious, e.g. to retain intellectual stimulating
surroundings. Theorists have debated possible explanations for the regularly found
negative association between Conscientiousness and cognitive ability. One hypothesis that
has been proposed is that this correlation is a methodological artifact caused by the
sampling bias of previous studies. If this hypothesis that the negative correlation
between intelligence and Conscientiousness applies only to highly educated college student
populations were correct, an interaction between education and Conscientiousness should be
found in predicting ability in a heterogeneous sample. We therefore investigated (a) the
extent to which this correlation was replicated in data representing the full adult
population and (b) whether we could identify this hypothesized interaction of education
and Conscientiousness in this comprehensive data set. On the basis of these data, we were
able to negate this hypothesis and to show that this negative association is not in fact
caused by a sampling bias. Rather, in a heterogeneous population sample, too, there is a
negative association between verbal and numerical ability and Conscientiousness. As
suggested by Major et al. (2014), we also investigated quadratic effects and found a
negative quadratic association between Conscientiousness and ability, which indicates that
very highly conscientious respondents, in particular, show lower cognitive ability. In
addition, our analyses revealed no interaction between Conscientiousness and education in
predicting cognitive ability. Our results therefore support the assumption that there is a
negative relationship between Conscientiousness and cognitive ability and contribute to
further understanding this association. We could show that the relationship between
Conscientiousness and cognitive ability is moderated by labor force participation and that
the negative association between Conscientiousness and intelligence applies only to
persons in full-time employment. Conscientiousness and intelligence are both highly
relevant criteria for job success (e.g., Barrick & Mount, 1991; Gottfredson, 1997; Schmidt
& Hunter, 1998). Our results can thus be interpreted as supporting the intelligence
compensation hypothesis (Moutafi et al., 2003), which assumes that, on the labor market,
people can compensate comparatively low cognitive ability with high Conscientiousness. By
contrast, more cognitively talented persons fulfill their job requirements more easily and
do not therefore need to be as conscientious. Alternatively, however, the interaction
effect of labor force participation and Conscientiousness on cognitive ability found here
might reflect personality differences among occupations. It could be the case, for
example, that lower-skilled workers are more conscientious than high-skilled persons. Our
study thus showed that the negative association between Conscientiousness and intelligence
is not restricted to college student populations. Rather, our findings provide preliminary
evidence that this association can indeed be found in the total population, albeit not in
a uniform way: It is more pronounced among persons in full-time employment. Hence, our
results support the assumption that low cognitive abilities can be compensated with high
Conscientiousness. However, as the present study investigated the Big Five personality
domains using a very brief instrument, further studies are needed that replicate the
effects found here using longer Big Five instruments that also allow differential effects
of the domain’s facets to be examined. Another limitation of the present study – or at
least one difference between it and earlier studies – might be the fact that ability was
assessed in a low-stakes setting, which may have affected the individual’s test
motivation. As shown in a recent study (Duckworth, Quinn, Lynam, Loeber, & Stouthamer-
Loeber, 2011), test motivation can have an impact not only on the test scores themselves
but also on associations of ability with life outcomes, for example, with personality
characteristics. In sum, our findings clearly replicate the simple positive association
between cognitive ability and Emotional Stability and Openness and its negative
association with Conscientiousness. In addition, we were able to show that the association
with Openness is moderated by education insofar as only persons with a low level of
education benefit intellectually from high Openness. Labor force participation moderates
the negative association between cognitive ability and Conscientiousness, indicating that
Conscientiousness is negatively linked to cognitive ability only among persons in full-
time employment. Hence, our results contribute to understanding the associations between
personality and cognitive ability.


<h>REFERENCES</h>
----------

  [1] Phillip L. Ackerman. A theory of adult intellectual development: Process, personality, interests, and knowledge. doi:10.1016/S0160-2896(96)90016-1
  [2] Phillip L. Ackerman, Eric D. Heggestad. Intelligence, personality, and interests: Evidence for overlapping traits. doi:10.1037/0033-2909.121.2.219
  [3] MURRAY R. BARRICK, MICHAEL K. MOUNT. THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE: A META‐ANALYSIS. doi:10.1111/j.1744-6570.1991.tb00688.x
  [4] Jürgen Baumert, Martin Brunner, Oliver Lüdtke, Ulrich Trautwein. Was Messen Internationale Schulleistungsstudien?-Resultate Kumulativer Wissenserwerbsprozesse Eine Antwort auf Heiner Rindermann. doi:10.1026/0033-3042.58.2.118
  [6] Angela Lee Duckworth, Patrick D. Quinn, Donald R. Lynam, Rolf Loeber, Magda Stouthamer-Loeber. Role of test motivation in intelligence testing. doi:10.1073/pnas.1018601108
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  [8] Linda S. Gottfredson. Why g matters: The complexity of everyday life
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<ART>The behavioral inhibition and activation systems and function in patients with chronic pain
================================================================================

Authors: Elena R. Serrano-Ibáñez, Alicia E. López-Martínez, Carmen Ramírez-Maestre, Rosa Esteve, Mark P. Jensen
DOI: 10.1016/j.paid.2018.09.021
Year: 2019  |  Pages: 56-62
ASJC codes: 3200
Keywords: Behavioral activation system, Behavioral inhibition system, Chronic pain, Impairment, Psychological function

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: The behavioral inhibition system (BIS) and behavioral activation system (BAS) are two neuropsychological systems hypothesized to underlie response to cues signaling potential reward and punishment, respectively, also in patient responses to chronic pain. Objectives: The aim of this study was to test these hypotheses by evaluating the relative contributions of BIS and BAS to the prediction of function in sample individuals with chronic musculoskeletal pain. Methods: 253 participants were administered a battery of questionnaires. Two linear regression analyses were performed to evaluate the contributions of BIS and BAS to the prediction of impairment and psychological function, and to determine if either or both moderated the effects of pain intensity on function. Results: After controlling for demographic factors, pain diagnosis, and characteristic pain intensity, BIS contributed significantly and independently to the prediction of pain-related physical impairment and psychological function. BAS activity had a significant and direct effect on psychological function only. No moderating effects of BIS or BAS on the association between pain intensity and function were identified. Discussion: The findings are generally consistent with a BIS-BAS 2-factor model of chronic pain, suggesting BIS and BAS activity as potential targets for chronic pain treatment.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Chronic pain is a major biopsychosocial problem worldwide. It has a negative impact on
people's ability to exercise, engage in valued social and family activities, and maintain
an independent lifestyle (Breivik, Collett, Ventafridda, Cohen, & Gallacher, 2006).
Chronic pain also has a negative impact on psychological function domains, such as
depression, anxiety, and perceived stress (Stubbs et al., 2016). However, pain does not
have the same impact on everyone. The negative effects of pain are known to be influenced
by a number of psychological factors, such as an individual's tendency to catastrophize
about their pain (Craner, Sperry, Koball, Morrison, & Gilliam, 2017) and their trait
anxiety sensitivity (Esteve, Ramírez-Maestre, & López-Martínez, 2012). Additional factors
that have the potential to influence adjustment to chronic pain are the relative
activation of two neurophysiological systems that have been hypothesized to facilitate
approach and avoidance behaviors: the behavioral inhibition system (BIS) and behavioral
activation system (BAS) (Jensen, Ehde, & Day, 2016). Gray's Reinforcement Sensitivity
Theory (Gray, 1987; Gray & McNauhton, 2000) describes the BIS and BAS as
neuropsychological systems that are activated in an automatic way in the presence of
environmental or internal cues. Specifically this theory hypothesizes that BIS is
activated in the presence of cues indicating the potential for punishment (e.g., pain).
This system underlies and facilitates avoidance-related behaviors (e.g., withdrawal),
emotions (e.g., anxiety), and cognitions (e.g., catastrophizing). On the other hand, BAS
is activated in the presence of cues indicating the potential for reinforcement or the
disappearance/omission of an expected negative stimulus. BAS activation facilitates
approach-related behaviors (e.g., more activity, impulsivity), emotions (e.g., excitement,
joy), and cognitions (e.g., self-efficacy; Bjørnebekk, 2007). Pain is associated with
actual or potential tissue damage and its protective role often elicits attention and
action, which occur by virtue of the withdrawal reflex it activates, the intrinsic
unpleasantness of the pain experience, and the emotional anguish it can elicit (Woolf,
2010). A person's trait tendency for BIS or BAS to be activated in response to pain may
therefore explain, at least in part, the variability observed in people's adjustment to
pain, as reflected by measures of activity and psychological function (Renee & Cano,
2009). The BIS-BAS model of chronic pain (Jensen et al., 2016) proposes that pain is
interpreted as an aversive or punishment-related stimulus by most people. This model
therefore hypothesizes that more pain intensity would tend to result in activation of the
BIS and subsequent negative psychological responses and physical impairment. In addition,
and in support of this idea, significant associations between pain intensity and both
impairment and distress are often found. For example, Saavedra-Hernánndez et al. (2012)
showed that neck pain intensity is significant predictor of disability. Similarly, Moore
et al. (2010) found that moderate and substantial pain intensity reduction resulted in
improvements in many outcomes (sleep disturbance, depression, anxiety, and quality of
life) such that they approached levels found in the normal (i.e., otherwise healthy)
population. Thus, more pain intensity is hypothesized to result in (1) more BIS activation
(2) less BAS activation behavioral activation and subsequent positive emotions (BAS
inhibition). Moreover, because pain is an aversive or punishment-related stimulus, the
association between BIS and BIS-related responses (as sensitivity to punishment system)
and pain is hypothesized to be stronger than the associations between BAS and BAS-related
responses (as sensitivity to reward system) and pain. In support of this idea, it has been
found that cues that signal the occurrence of pain are more likely to increase the focus
of attention on that cue, relative to “safety cues,” which result in a decreased chance
that the person will experience pain (Van Damme et al., 2004) and that pain will interrupt
behavior (Eccleston & Crombez, 1999). With respect to the relationship between BIS and
BAS, a “separable subsystems” model (Corr, 2002; Gray & McNauhton, 2000) hypothesizes that
the BIS and BAS work mostly independently. That is, individuals with greater BIS activity,
compared with those with a less BIS activity, should be most sensitive to signals of
punishment, regardless of their level of BAS activation; and individuals with greater BAS
activity, relative to a less activity, should be most sensitive to signals of reward,
regardless of their level of BIS activation. Thus, pain is thought to be a cue that
directly activates the BIS and pain's impact on patient dysfunction (e.g., negative
emotions and disability) is hypothesized to be mediated by BIS, at least in part,
regardless of the level of BAS activity (Jensen et al., 2016). If pain influences BAS,
then any of pain's negative effects on positive function (e.g., positive emotions and life
engagement) would be expected to be mediated by BAS activity, separately and distinctly
from any effects on BIS. On the other hand, a more recent “joint subsystems hypothesis”
(Corr, 2002) postulates that BIS and BAS have the potential to influence each other's
effects on both reward-mediated and punishment-mediated behavior. That is, these systems
may work synergistically, such that the impact of one on function is influenced by the
relative activation of the other. With this model, dysfunction is hypothesized to be
greatest in people with both high BIS activation and lower BAS activation and vice versa
(Corr, 2002). In support of this model, Corr (2002) found a significant BIS (Anxiety) x
BAS (Impulsivity) interaction in reactions to experimental manipulations of punishment in
a sample of volunteers recruited from a university population. However, to our knowledge,
the potential moderating effects of BIS and BAS activation on their effects on patient
function have not yet been examined in the context of chronic pain. The BIS-BAS model of
chronic pain (Jensen, Ehde, & Day, 2016) hypothesizes that the two systems are distinct
but not completely independent; thus, this model would hypothesize that significant BIS X
BAS interactions predicting function might be found in some contexts but not others. Even
though pain is hypothesized activate primarily BIS, it may also influence BAS to some
degree, via two mechanisms. First, because BIS activation is hypothesized to inhibit BAS
to some degree (but not completely), and vice versa, an increase in pain would be expected
to inhibit BAS indirectly, via its effects on BIS. Second, because in some situations,
pain may activate aggressive responses (a BAS “approach” response), an increase in pain
has the potential to result in an increase in BAS activity in some settings and with some
individuals (i.e., Muris, Meesters, de Kanter, & Timmerman, 2005). The combination of
these two contradictory effects may act to result in an overall weaker association between
pain and BAS activation. Thus, the BIS-BAS model of pain hypothesizes that experience of
pain would result in (1) more behavioral inhibition and subsequent negative psychological
function and (2) less behavioral activation and subsequent positive emotions. A greater
tendency for engaging in approach behaviors, feeling of excitement and joy, and believing
that one is capable of controlling pain is hypothesized to inhibit (although not
necessarily completely eliminate) a tendency to avoid activities, experience fear, or have
thoughts of helplessness. With respect to a possible BIS X BAS interaction effect, the
BIS-BAS model of chronic pain hypothesizes that such interaction is possible in some
contexts, but unlikely to emerge across all contexts. Existing research provides
preliminary support for a BIS-BAS model of chronic pain (Jensen et al., 2016). For
example, Jensen et al. (2017) found that patients with chronic pain scoring high in a
tendency for BIS activation report more depressive symptoms. BIS has also been shown to
moderate the associations between pain-related cognitions and psychological function.
Specifically, individuals with chronic pain who endorse more BIS responding evidence
stronger associations between kinesiophobia and depressive symptoms than those who endorse
less BIS responding (Jensen et al., 2017). Moreover, a trait tendency towards BIS
activation has been shown to be associated positively with pain catastrophizing (Muris et
al., 2007) which is known to be associated with negative affect and disability in
individuals with chronic pain (Quartana, Campbell, & Edwards, 2009). Also in support of
the BIS-BAS model of chronic pain, Jensen, Tan, Chua, and BSoc (2015) showed that a higher
frequency of severe headaches was associated with higher trait BIS and lower trait BAS
scale scores in a sample of undergraduate students, with the association between BIS and
pain stronger than that between BAS and pain. Consistent with this idea, Becerra-Garcia
and Robles (2014) found that BAS was lower in patients with fibromyalgia, relative to a
healthy control group. In addition, it has demonstrated that people with chronic pain have
a reduced hedonic response to rewards, and this reduction is associated with smaller
nucleus accumbens volume that is responsible of reward processing (Elvemo, Landrø,
Borchgrevink, & Haberg, 2015). In part because of the fact that the BIS-BAS model of
chronic pain is relatively new, research testing the model to determine its utility
remains preliminary; more research is needed to evaluate the explanatory power of the
model, and adapt it as needed based on empirical findings. Given these considerations, the
aim of current study was to increase our understanding of the role that BIS and BAS
responding may play in the physical and psychological function of individuals with chronic
musculoskeletal pain. Based on the BIS-BAS model, we hypothesized that BIS activation and
BAS activation would make significant and direct contributions to the prediction of
physical impairment and psychological function (positive association with BIS and negative
association with BAS), when controlling for demographic factors, pain diagnosis, and
characteristic pain intensity. In addition, we hypothesized that BIS and BAS would
moderate the association between pain intensity and the study criterion variables, such
that those with more BIS and less BAS would evidence stronger associations between pain
intensity and function. Finally, we examined the possible interaction between BIS and BAS
as a predictor of function. A significant interaction would support the joint subsystems
model (i.e., greater influence of BIS and BAS on the effects of each on function) with
respect to chronic pain. On the other hand, if a significant BIS X BAS interaction did not
emerge, this would support the separable subsystems model (i.e., less influence of BIS and
BAS on the effects of each on function) in this context. Fig. 1 presents a graphic
representation of the study hypotheses.

<hs>  Participants and procedures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

The study participants were recruited from two hospital pain units (the Hospital Costa del
Sol Pain Unit and the Hospital Virgen de la Victoria Pain Unit, in Spain) and from a
fibromyalgia association (“Asociación de Fibromialgia y Síndrome de Fatiga Crónica de
Málaga AFIBROMA”, Spain). For the participants who were recruited from the hospital pain
units, physicians in the units reviewed the clinical history of each potential
participant, and invited them to participate if they met the study inclusion criteria.
Interested participants were contacted by telephone to schedule an assessment. To recruit
participants from the fibromyalgia associations, we contacted by phone with the
chairpersons of associations and described the study to them. The chairperson then
informed the organizations' members about the study via email, and interested members were
invited to attend a meeting with research staff to hear more about the study. Those who
remained interested following the meeting were enrolled in the study and scheduled for an
interview for data collection. A total of 169 individuals were recruited from the pain
units, and 84 individuals were recruited from the associations. Study inclusion criteria
were: (1) being from 18 to 65 years old, (2) having a musculoskeletal pain problem for at
least 3 months, (3) not having any other physical condition or illness in addition to the
pain problem, and (4) not having a severe psychiatric disorder that would interfere with
participation. After written informed consent was obtained, a psychologist met with the
participants to obtain demographic information, pain and pain history information, and to
administer the study questionnaires (described in the Measures section). The study
procedures complied with the Declaration of Helsinki and received institutional review
board approval by the University of Málaga Ethics Committee.

<hs>  Demographic variables</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Participants provided basic information about their demographics including age, sex,
marital status, highest level of education achieved, and employment status.

<hs>  Characteristic pain intensity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Characteristic pain intensity was assessed by asking participants to rate their current
pain and worst, least, and average pain in the past two weeks on 0–10 numerical rating
scales, with 0 = “No pain” and 10 = “Worst pain possible.” These ratings were then
averaged into a single score representing characteristic pain intensity (Jensen, Turner,
Romano, & Fischer, 1999).

<hs>  Trait BIS and BAS activity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Trait BIS and BAS activity were assessed using the 20-item Sensitivity to Punishment and
Sensitivity to Reward Questionnaire (SPSRQ-20; Aluja & Blanch, 2011). The SPSRQ-20
measures individual differences in trait tendency for BIS and BAS activation. Item are
answered with a dichotomous “Yes” or “No” response, and are then summed to score into BIS
and BAS scales (10 items each). A sample BIS item is, “Are you often worried by things
that you said or did?” A sample BAS item is, “Do you like being the center of attention at
a party or a social meeting?” The BAS and BIS scales demonstrated good (BAS) and excellent
(BIS) internal consistency in the current sample (Cronbach's alphas = 0.81 and 0.91,
respectively).

<hs>  Pain-related impairment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Pain-related impairment was assessed using the 30-item Impairment and Functioning
Inventory for Patients with Chronic Pain (IFI-R; Ramírez-Maestre & Esteve, 2015). With the
IFI-R, respondents are asked, first, if they performed a number of daily activities (e.g.,
sweeping the house, driving the car or dressing by themselves, or visiting friends) in the
previous week. For each activity they did not perform, they were asked to indicate, yes or
no, if they did not do the activity because of pain. A pain-related impairment score is
then computed by summing the activities not engaged in due to pain; a higher score
indicates more pain-related impairment. In this sample, the reliability of the impairment
scale was good (Cronbach's alpha = 0.81).

<hs>  Psychological function</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Psychological function was assessed using the 5-item World Health Organization Well-Being
Index (WHO-5; Bech, 1999). With the WHO-5, respondents indicate how they have been feeling
over the last two weeks on a 0 (“At no time”) to 5 (“All of the time”) scale. Sample items
include, “I have felt calm and relaxed” and “I have felt cheerful and in good spirits.”
The internal consistency of the measure was excellent in the current sample (Cronbach's
alpha = 0.90).

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

We first computed descriptive statistics to describe the sample. We then calculated
Pearson correlations coefficients between the study variables to understand their
univariate associations. Next, we examined the variables and their distributions for
normality, homoscedasticity and multicollinearity to ensure that they met the assumptions
for the planned regression analyses study (Tabachnick & Fidell, 2007). Finally, to test
the study hypotheses we performed two multiple regression analyses (Cohen, Cohen, West, &
Aiken, 2003), one for each criterion variable (i.e., pain-related impairment and
psychological function). Given research that has shown that socio-demographic factors and
pain diagnosis can influence important pain-related outcomes (e.g., Ando et al., 2013;
Goldenberg, 2009; May, 2008), we planned to control for these factors in the analyses. In
line with it, in each analyses, we first entered demographic (age, sex) and diagnostic
group (fibromyalgia, low back pain, and limb [arm, hand, leg, or foot] pain, or other,
dummy coded, being “other” the reference category) as control variables. We then entered
characteristic pain intensity in step 2 and the BIS and BAS scale scores in in step 3.
Finally, in step 4, we entered the BIS × Pain Intensity, BAS × Pain Intensity, and BIS ×
BAS interaction terms. The predictor variables (characteristic pain intensity, BIS score,
BAS score) were centered prior to entry to avoid the biasing effects associated with
multicollinearity that can occur when examining interaction terms. All analyses were
conducted using the Statistical Package for Social Sciences (SPSS; Windows version 22.0,
SPSS Inc., Chicago, IL).

<hs>  Sample characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Two hundred and fifty-three individuals participated in the study. They had a mean age of
52.51 years (SD = 9.85), and 206 (81%) were woman. Eighty-four (33%) reported a diagnosis
of fibromyalgia, 75 (30%) of low back pain, 67 (26%) limb pain, and 27 (11%) other
musculoskeletal pain problem. The mean pain duration was 10.06 years (SD = 12.23). Table 1
shows more details about the participants' characteristics.

<hs>  Descriptive analyses and correlations between variables</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mean, standard deviations, and correlations among the study variables are presented in
Table 2. The sample reported a characteristic pain intensity level that was moderate to
severe, with a mean values of 6.32 (SD = 1.35; possible range, 0–10). The strength of the
zero order associations between the predictor and criterion variables ranged from small
(e.g., BAS with impairment, r = 0.16, p < 0.01; BAS with psychological function, r = 0.12,
p < 0.05) to strong (e.g., BIS with impairment, r = 0.51, p < 0.01; BIS with psychological
function 0.55, p < 0.01). With respect to assumptions testing, the skewness (range from
−0.07 to 1.26) and kurtosis (range from −0.02 to −0.59) values did not exceed the standard
cutoff of 3 (Tabachnick & Fidell, 2007) indicating adequately normal distributions for the
study variables for the planned regression analyses. The lack of multicollinearity among
the predictor variables was confirmed by variance inflation factors, as their values
(range from 1.04 to 2.28 in both regression analyses) were substantially below the
standard cutoff of 10 (Hair, Anderson, Tatham, & Black, 1995).

<hs>  Pain intensity and BIS and BAS activity as predictors of pain-related impairment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 3 presents the result of multiple regression analysis predicting pain-related
impairment. As can be seen, and after controlling demographic variables (age and sex) and
the diagnoses of the participants, we found that pain intensity contributed significantly
to the prediction of pain-related impairment (R2 change = 0.05; p < 0.001). When pain
intensity was controlled, BIS activity (β = 0.44, p < 0.001), but not BAS (β = 0.03, p =
0.671), made an additional significant contribution to the prediction of this criterion
variable. However, none of the interactions made a significant contribution to the
prediction of the criterion variable.

<hs>  Pain intensity and BIS and BAS activity as predictors of psychological function</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Both BIS activity (β = −0.53, p < 0.001) and BAS activity (β = 0.17, p < 0.001) made
statistically significant and independent contributions to the prediction of psychological
function, once demographic variables, pain diagnosis, and pain intensity were controlled
(see Table 4). However, none of the interaction terms contributed significantly to the
prediction of psychological function.

<h>DISCUSSION</h>
----------

The primary purpose of this study was to evaluate the role that BIS and BAS may play in
the physical and psychological function of individuals with chronic musculoskeletal pain
as a test of the BIS-BAS model of chronic pain. The findings showed that, even after
controlling for demographic factors, pain diagnosis, and characteristic pain intensity,
BIS was independently and significantly associated with both pain-related impairment and
psychological function. BAS was significantly and independently associated only with
psychological function. Inconsistent with the study hypothesis, neither BIS nor BAS
evidenced a moderating effect on the association between pain intensity and the function
variables studied. These findings have important implications for understanding the
potential role of BIS and BAS in adjustment to chronic pain. In line with the BIS-BAS
model of chronic pain (Jensen et al., 2016), as well as previous research (Jensen et al.,
2017; Muris et al., 2007), the results indicate that the BIS has a more predominant role
in the prediction of function in individuals with chronic pain than the BAS. This is
reflected both by the facts that (1) the BIS scale made significant and independent
contributions to the prediction of both function criterion variables and (2) the
association between BIS and both criterion variables was stronger than between BAS and the
criterion variables. Also, Gray's theory (Gray, 1987; Gray & McNauhton, 2000) posits that
BIS facilitates avoidance behaviors, and avoidance behaviors have been associated with
chronic pain (Crombez, Eccleston, Van Damme, Vlaeyen, & Karoly, 2012). To the extent that
future research identifies a causal role for BIS activation as influencing both physical
and psychological function, these findings suggest that BIS activity may be a viable
treatment target in chronic pain populations. Treatments which might decrease BIS
activation (i.e., reduce avoidance behavior, maladaptive pain-related beliefs, reduce
negative affect) may have benefits – at least in terms of individuals function – in people
with chronic pain. As already noted, the study findings indicated that the BAS appears to
be less important as a predictor of participants function than BIS, at least with respect
to predicting impairment and psychological function. However, BAS did contribute unique
variance to the prediction of psychological function in the study sample, over and above
that accounted for by BIS. This role for BAS (reduced but still potentially important for
some function domains) is consistent with the BIS-BAS model of chronic pain (Jensen et
al., 2016) as well as the findings from other research. For example, Elvemo et al. (2015)
showed that individuals with chronic pain had significantly reduced scores on reward
responsiveness, but not reward drive (both as measured by Behavioral Inhibition/Behavioral
Activation Scale; Carver & White, 1994), suggesting that having chronic pain may result in
a reduction in hedonic responses to rewards. Moreover, research has shown that people with
chronic pain have reduced nucleus accumbens volume (Elvemo et al., 2015); this area of the
brain is implicated in the processing of reward, pleasure or positive reinforcement
(Malenka, Nestler, & Hyman, 2009). If the current findings are replicated, it possible
that, in individuals with chronic pain, BAS plays a greater role in emotional function and
responding than behavioral responding. Thus, treatments that target BAS activity such as
“positive psychology” interventions (Müller et al., 2016) would be expected to impact
psychological function more than physical function, and so may be particularly important
for individuals who endorse high levels of psychological dysfunction in response to pain.
Research is needed to evaluate this hypothesis. The results did not support an interaction
effect of BIS and BAS as predictors of function in our sample of individuals with chronic
musculoskeletal pain. This findings are in line with the “separable subsystems” model
(Corr, 2002; Gray & McNauhton, 2000), and inconsistent with previous human experimental
research in undergraduate students (Corr, 2002). However, Corr (2002) notes that the
“separable subsystems” model may be more appropriate in some contexts than others. For
example, in the presence of strong appetitive/aversive stimuli, or in samples of
individuals with “extreme” personality traits. The chronic pain context could potentially
influence both of these characteristics. For example, chronic pain – especially when
severe – can be viewed as a strong aversive stimuli. In addition, individuals with chronic
pain may have “extreme personality” traits as a result of suffering for a long period of
time (the mean pain duration of chronic pain in the sample of individuals who participated
in this study was 10 years approximately). Thus, it remains possible that BIS X BAS
interactions may emerge in samples of individuals with more mild pain, or who have
experienced chronic pain for a shorter duration, consistent with the idea that BIS and BAS
may work synergistically in some contexts and with some populations, but not others. Given
that both BIS and BAS made significant and independent contributions to the prediction of
psychological function, it is possible that overall treatment efficacy – at least on
psychological function outcome domains – could be enhanced by targeting both an increase
in BAS and a reduction in BIS activity as underlying mechanisms (instead of just one or
the other). Research to evaluate the relative effects of existing (and new) treatments on
each component of BIS and BAS could identify the potential “best combination” of
treatments which maximally influence (reduce) behavioral avoidance, negative/maladaptive
pain beliefs, and negative affect, and also influence (increase) approach behaviors,
adaptive pain beliefs, and positive affect; such treatment combinations could potentially
be more effective than treatments that target only BIS- or BAS-related domains. We had
hypothesized that BIS or BAS levels could potentially moderate the association between
pain and the criterion variables studied here. However, this hypothesis was not supported
by the findings; BIS and BAS appeared to have direct effects on function that did not vary
as a function of pain severity. However, it remains possible that BIS might increase the
vulnerability of people to the consequences of pain, and/or BAS might provide individuals
with more resources to help them when faced with the challenges associated with pain, even
if these effects are similar across all levels of characteristic pain intensity levels.
This possibility provides further support for the need to evaluate the potential benefits
of treatments which effectively target and reduce BIS activity and increase BAS activity
in individuals with chronic pain. A number of limitations should be considered when
interpreting the current findings. First, we only used self-report measures in the study.
Thus, it is possible that shared method variance may have influenced the findings,
resulting in stronger associations between the predictors and criterion variables than
would have occurred had different sources been used as sources for the study variables.
Research that examines the associations between self-report measures of BIS and BAS and
objective measures of patient function (e.g., actigraph measures of activity, significant
other observations of patient behaviors) would be useful. A second limitation is that the
study design was cross-sectional. As a result, it is not possible to draw causal
conclusions from the associations found. Future research is needed determine the effects
of changes in BIS or BAS (e.g., as might occur with treatments that target BIS and BAS
activity) and subsequent patient function. Third, the sample included a larger number of
women than men. Although the ratio of women is greater than of men in this health
services, a sample with more men as well as with other type of chronic pain diagnoses is
needed to evaluate the generalizability of the current findings. In addition, the most
recent version of Gray's reward sensitivity theory includes a third system – a fight-
flight-freeze system (FFFS) – that we did not evaluate here. We had a number of reasons
for not including an examination of the FFFS in the current study. First, the goal of the
current study was to evaluate the BIS-BAS model of chronic pain (Jensen et al., 2016),
which does not take into account the FFFS, because the FFFS system is rarely stimulated in
most situations; fight or flight responses do not usually occur on a daily basis. Thus,
excluding this system allowed the model to keep more focused on those factors that predict
day-to-day responses. In addition, like our 2-factor model (Jensen et al., 2016), none of
the many other 2-factor models which incorporate the BIS and BAS or systems very much like
them (Elliot, 1997; Gray & McNauhton, 2000; Harmon-Jones, 2004; Watson, Wiese, Vaidya, &
Tellegan, 1999), also do not incorporate the FFFS as a part of their model. Moreover,
scientists, including McNaughton and Corr (2008), note that the association between BIS
and FFFS is very close. FFFS activation is thought to be preceded by BIS activation and
they can therefore be combined into a single “punishment sensitivity” factor of
personality (Corr, 2009). Thus, the distinction between the FFFS and BIS is thought be
less than that between the BIS and the BAS. Also, to our knowledge, no one has yet
developed a measure of FFFS activation that is comparable to the commonly used BIS/BAS
measures, including the one used in the present study. Future research is needed to
evaluate if, and how, the FFFS and other systems may interact with the BIS and BAS to
impact adjustment to chronic pain. Despite the study's limitations, the findings provide
new information regarding the role that BIS and BAS have as predictors of function in in
individuals with chronic pain. The results are generally consistent with a model that
argues that both BIS and BAS may explain differential responses to pain, and that BIS may
play a larger role than BAS (Jensen et al., 2016). The findings also suggest that BAS may
be only meaningfully important with respect to psychological function, while BIS may play
roles in both impairment and psychological function. Additional research is needed to
evaluate the generalizability of these findings in other chronic pain populations, as well
as to study the potential causal role that BIS and BAS may play in adjustment to chronic
pain. In addition, based on these findings, further research could analyze in detail how,
and through what mechanisms, BIS and BAS are related to psychological function and
emotional regulation in patients with chronic pain. In the same way, they could evaluate
how the systems interact in the activity patterns of this type of patients (excessive
avoidance or excessive persistent). Also, we recommend that future researchers incorporate
the evaluation of additional subsystems when possible (e.g., as measures of these are
developed) for understanding, and treating, chronic pain and its negative impact.

<h>FUNDING SOURCES</h>
---------------

This work was supported by the Spanish Ministry of Economy and Competitiveness
[PSI2013-42512-P]; and the Spanish Ministry of Education, Culture, and Sports [grant
number FPU13/04928].


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<ART>The development of behavior problems among disabled and non-disabled children in England
================================================================================

Authors: Rebecca C. Fauth, Lucinda Platt, Samantha Parsons
DOI: 10.1016/j.appdev.2017.06.008
Year: 2017  |  Pages: 46-58
ASJC codes: 3204
Keywords: Behavior problems, Disability, Early years, England, Trajectories

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study identifies the incidence and development of disabled children's problem behaviors (i.e., conduct, peer, hyperactivity, and emotional problems) during the early years. Using the Millennium Cohort Study, a nationally representative UK study, and a measure of disability anchored in the UK legal definition, we estimate growth curve models tracking behavior problems from ages 3 to 7. We examine whether disabled girls’ and boys’ behavior differs from their non-disabled peers, and whether it converges with or diverges from them over time. We investigate whether parenting and the home environment moderate associations between disability and behavior. We show that disabled children exhibit more behavior problems than non-disabled children at age 3, and their trajectories from ages 3 to 7 do not converge. Rather, disabled children, particularly boys, show increasing gaps in peer problems, hyperactivity, and emotional problems over time. We find little evidence that parenting moderates these associations.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The emergence of problem behavior during the early years may set children upon unfavorable
developmental trajectories. This is particularly true in the case of early externalizing
behavior problems (i.e., hyperactivity, aggression), which may lead to continued problems
and poor academic achievement (see e.g., Campbell, Shaw, & Gilliom, 2000; Hinshaw, 1992).
Boys and girls tend to exhibit problem behavior differently, with higher rates of
externalizing problems documented for boys and, to some extent, more internalizing
problems (withdrawal, depression) for girls (see, e.g., Baillargeon et al., 2007;
Campbell, 1995; Keenan & Shaw, 1997; Midouhas, Kuang, & Flouri, 2014). Past research has
shown that disabled children are more likely than their non-disabled peers to present
behavior problems, including social and peer problems, conduct problems and oppositional
behaviors, attention difficulties and hyperactivity, and internalizing problems, and that
their problems are more likely to be within the clinical range relative to their peers
(Alloway, Gathercole, Kirkwood, & Elliott, 2009; Baker et al., 2003; Eisenhower, Baker, &
Blacher, 2005; Emerson & Einfeld, 2010; Landa, Gross, Stuart, & Faherty, 2013). Yet, we
know little about the extent to which associations between disability and behavior are
linked to children's developmental stage and whether they attenuate or intensify around
the time of school entry. We know from decades of research the critical nature of the
early years, in which both genes and the environment—and the interplay between the two—set
into motion the development of brain structures that affect children for the rest of their
lives (Shonkoff & Phillips, 2000). More proximally, children's development up to age 3
provides the building blocks for the increasingly complex social behaviors, emotional
maturity, problem solving ability, and early literacy and numeracy skills that are
critical leading up to school entry. For some children, early behavioral problems are
temporary, resolved over the normal course of development, while for others they persist
or even intensify in the early school years. School entry represents an expansion in
children's developmental ecology from the primacy of parents and the home environment to
incorporate the school context and peers. Whether disabled children's behavioral
development tracks that of their non-disabled peers over the first few years following
this transition to school is an important empirical endeavor, a better understanding of
which will help to inform the timing of interventions for disabled children. A description
of disabled children's early behavioral trajectories across four important domains of
behavioral development is the first contribution of this paper. Our current understanding
of the association between disability and behavior is limited by the focus on particular
impairments or conditions and reliance on small-scale, localized studies, both of which
hamper generalizability. Many common proxies for disability in UK-based studies, such as
identification with special educational needs (SEN), may confound the measurement of
disability with the measurement of problem behaviors (Keil, Miller, & Cobb, 2006; Keslair
& McNally, 2009; Powell, 2003). Here, instead, we exploit an overarching measure of
disability anchored in the UK legal definition, itself informed by the social model of
disability, which distinguishes the impairments themselves from the societal conditions
under which they become disabling (Oliver, 1990). Our measure, which takes account of the
contextualized nature of limitations or impairments, was developed from the data in
consultation with the leading UK child disability experts and validated against known
correlates of disability. This measure defines disability as both longstanding and
limiting daily activities (longstanding limiting illness; LSLI), in line with guidance on
the legal definition. It incorporates long-term health conditions, mental health problems,
and sensory impairments, among others, enabling us to capture a wide range of disabling
conditions experienced by a nationally representative sample of young children in England.
Use of this measure improves our understanding of the associations between disability,
rather than specific impairments or conditions that may or may not be limiting, and
behavior, the paper's second contribution. Given the importance of the family and home
environment for young children's behavioral development, supportive and enriching
experiences in the home could help mitigate the development of behavior problems for young
disabled children. On the other hand, given increased levels of parenting stress
associated with parenting a young disabled child (Baker et al., 2003; Hastings, 2002;
Neece, Green, & Baker, 2012), it may be that less favorable family climates exacerbate
differences in behavior problems between disabled and non-disabled children. To our
knowledge, despite the wealth of research attesting to the importance of home environment
on children's development, and the ways in which it can mitigate socio-economic
disadvantage (see e.g., Siraj-Blatchford, 2010), research has not examined whether family
environments promote greater convergence or divergence of behavioral trajectories between
disabled and non-disabled children over time. The paper's third contribution is to
investigate the moderating role of parental warmth and harshness and the home learning
environment on disabled children's behavioral trajectories; notably to better understand
which aspects of parenting and the home environment attenuate or exacerbate which problem
behaviors. Using longitudinal data from the UK Millennium Cohort Study (MCS), a large,
nationally representative sample of children born in 2000–2001, we examine four problem
behaviors: conduct problems, hyperactivity, peer problems, and emotional symptoms. These
distinct types of problem behavior have been shown to be important for children's
development, and they may present differently over time for disabled and non-disabled
children. We address the question of whether young disabled children growing up in England
experience more behavioral problems, and in which domains, than their non-disabled
counterparts at age 3, and if any initial gap in behavior widens between the ages of 3 and
7. Finally, we examine whether differences in behavioral trajectories are contingent on
three aspects of parenting and the home environment.

<hs>  Behavioral problems and disabled children</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A large body of research attests to specific trajectories associated with the four types
of childhood behavior problems (i.e., conduct problems, hyperactivity, peer problems,
emotional symptoms), with the preschool and initial school years considered the time when
most children learn to control early problematic behavior, particularly externalizing
behaviors (Bongers, Koot, van der Ende, & Verhulst, 2003; Broidy et al., 2003; Campbell et
al., 2000; Fanti & Henrich, 2010; Tremblay et al., 2004). While conduct, hyperactivity,
and peer problems typically decline over this time (Flouri, Midouhas, & Joshi, 2014;
Midouhas et al., 2014), emotional symptoms tend to be stable or increase (Bongers et al.,
2003; Leve, Kim, & Pears, 2005; Midouhas et al., 2014). The exception to this general
pattern is a small subset of children, comprising more boys than girls, who display high
levels of physical aggression that persist (Broidy et al., 2003; Campbell et al., 2000;
Tremblay et al., 2004). These studies do not, however, distinguish between disabled and
non-disabled children. Studies that have explored the relationship between disability and
behavior in the early years have shown that, relative to non-disabled children, disabled
children experience more total behavioral problems, more serious and clinically
significant problems, and more persistent problem behavior (Alloway et al., 2009; Baker et
al., 2003; Eisenhower et al., 2005; Emerson & Einfeld, 2010; Guralnick, Hammond, Connor, &
Neville, 2006; Landa et al., 2013; Midouhas, Yogaratnam, Flouri, & Charman, 2013),
suggesting that general declines reported for conduct, hyperactivity, and peer problems in
the early school years may occur later or not at all for disabled children. Further, a
recent study found that disabled children were particularly susceptible to increases in
internalizing symptoms (Hauser-Cram & Woodman, 2016). These findings are largely based on
small, non-representative cross-sectional samples and tended to focus on one particular
type of impairment and more global problem behavior (rather than specific types). While
researchers have used the MCS, the data source used here, to explore links between
disability and children's behavior (see e.g., Emerson & Einfeld, 2010; Midouhas et al.,
2013), it has not previously been used to classify young children according to criteria
aligned with the UK legal definition of disability, nor have disabled children's early
behavioral trajectories been examined, focusing on the time leading up to and following
school entry. Exploring four behavioral trajectories across a representative sample of
children from England allows us to assess how disabled and non-disabled children may
differentially respond to school entry. A potentially important element in understanding
the behavioral trajectories of young disabled children is the role of parenting and the
home environment. A large body of research has demonstrated that parenting characterized
by high levels of warmth, cognitive stimulation and clear limit-setting is associated with
favorable emotional and behavioral outcomes for children, with the opposite findings for
parenting characterized by harsh, arbitrary discipline or emotional detachment (Baumrind,
1966; Belsky, 1999; Berlin & Cassidy, 2000; McLoyd, 1998). Parents can also provide
materials and experiences within the home environment, such as reading and other learning
activities that promote children's early behavioral development (de la Rochebrochard,
2012; Hall et al., 2013; Kelly, Sacker, Del Bono, Francesconi, & Marmot, 2011; Kiernan &
Huerta, 2008). Yet, parenting a disabled child may yield less than optimal parenting
behaviors. Parents of disabled children exhibit higher levels of stress, more coping
difficulties, and more conflict than other parents, which may lead to increased child
behavior problems over time (Baker et al., 2003; Eisenhower et al., 2005; Herring et al.,
2006; Neece et al., 2012; Totsika, Hastings, Vagenas, & Emerson, 2014), although these
studies did not differentiate between type of problem behavior. Parents' ability to parent
positively depends, in part, on whether they can recognize and interpret their children's
behavior and emotional states, which may be difficult with disabled children (Howe, 2006).
Some parents successfully adapt to having a disabled child and are able accommodate their
special needs, while others face continued challenges to their competence and confidence
as parents, becoming stuck in negative interaction patterns (Bailey et al., 2006; Sanders,
Mazzucchelli, & Studman, 2004). Unfavorable parenting behaviors, such as unresponsiveness,
harsh discipline and negative control exacerbate both externalizing and internalizing
behavior problems for disabled children (Campbell et al., 2000; Gilliom & Shaw, 2004),
while positive parenting behaviors may buffer them from the development of future problems
(Ellingsen, Baker, Blacher, & Crnic, 2014; Hauser-Cram & Woodman, 2016). One UK study
found that parent-child relationship quality was a stronger predictor of young disabled
children's global behavior problems at age 5 than was discipline or assessments of the
family environment (Totsika et al., 2014). The present study aims to expand on the extant
research to examine whether different aspects of parenting may have distinct influences on
particular behavior problems from ages 3 to 7. A better understanding of these nuances
could help inform the timing and content of interventions to support families with
disabled children (Bailey et al., 2006).

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

The present study explores the development of disabled and non-disabled children's
internalizing and externalizing behavioral problems over the early years and entry into
school, a time of rapid growth and development when children's developmental ecologies
expand well beyond their home environments. Using data from a large-scale, nationally
representative sample of children living in England, we are able to include a range of
relevant child and family background characteristics. The study capitalizes on the
longitudinal nature of the dataset, which is critical for understanding whether any early
differences in behavioral problems between disabled and non-disabled children are stable,
decrease or increase over time. The paper addresses the following questions: (a) Are there
differences in rates of behavior problems, specifically conduct, hyperactivity, peer, and
emotional problems, between disabled and non-disabled children at age 3? (b) Are observed
patterns of development of behavioral problems moderated by child sex? (c) Do gaps in
behavior between disabled and non-disabled boys and girls converge (decrease), diverge
(increase), or stay constant from age 3 to age 7? (d) Are the observed patterns of
behavioral development robust to the inclusion of family characteristics and parenting
behaviors? and (e) Does growing up in positive and stimulating early home environments
moderate any divergence in trajectories between disabled and non-disabled boys and girls?
Our measure of disability, longstanding limiting illness (LSLI), aligns most closely with
UK disability legislation namely the Disability Discrimination Act, 1995, which was
subsequently incorporated in the Equalities Act, 2010. While it does not precisely reflect
the terminology of the legislation or the guidance on interpretation of “longstanding,” it
provides an approximation that matches the key elements of the law. By contrast with the
medical model, which has dominated most extant research, our definition has its roots in
the social model of disability (Oliver, 1990), which regards disability as the ways in
which societal organization limits those with an impairment, rather than viewing the
impairment itself as inherently limiting. Adhering to the social model enables us to
perceive behavioral “problems” as manifestations of how social norms limit disabled
children, thus linking LSLI to behavioral problems and their development over time. From
the existing literature, we develop the following hypotheses. First, we expect that
disabled children will exhibit higher initial levels of conduct problems, hyperactivity,
peer problems, and emotional symptoms at age 3 than their non-disabled peers. While we
expect that externalizing problems (conduct problems, hyperactivity) will decrease over
time for all children, we expect that differences between disabled and non-disabled
children, particularly boys, will become more pronounced from around the time of school
entry (around 4.5 years in England). Given the ways in which children respond to
difference and the fact that schools may enhance the potentially disabling environment for
children (Baker & Donelly, 2001; Chatzitheochari, Parsons, & Platt, 2016; Connors &
Stalker, 2006), we expect disabled boys and girls to exhibit increased peer problems over
time relative to their non-disabled peers. Our hypotheses concerning emotional symptoms
are more tentative, but in line with previous research, we expect stability or small
increases in emotional symptoms over the early years, and that they may increase most for
disabled girls. Given the importance of family environment for disabled children (Baker &
Donelly, 2001) and the stresses for parents in families of disabled children (Dowling &
Dolan, 2001), we expect that warm parenting and enriching home environments will lead to
more convergence over time in disabled children's behavioral trajectories, particularly
for conduct problems, hyperactivity, and emotional symptoms. Harsh parenting will likely
only moderate the association between disability and externalizing symptoms (i.e., conduct
problems, hyperactivity).

<hs>  Data</hs>
  ~~~~

We use data from the longitudinal Millennium Cohort Study (MCS). This large-scale,
multidisciplinary, nationally representative study follows approximately 19,000 babies
born to families living in the UK between September 2000 and January 2002 (Plewis, 2007).
The sample population was drawn from all live births in the UK over this period, which
were registered for universal child benefit. Participants were selected from a random
sample of electoral wards, disproportionately stratified to ensure adequate representation
of all four UK countries, deprived areas, and areas with high concentrations of Black and
Asian families. Probability weights available for both whole UK and separate country
analysis ensure that oversampled groups are represented according to population
proportions. Families have been surveyed when children were aged 9 months (wave 1), and 3,
5, 7, 11, and 14 years (wave 2–6). At each survey, the child's main caregiver (primarily
mothers) and their partner (primarily fathers) were interviewed and carried out self-
completion questionnaires. Physical measurements and cognitive assessments of children
have taken place since age 3. We use data from the main caregivers' interviews at the
first four waves of data collection, and children's cognitive assessments at age 3 (Centre
for Longitudinal Studies, Institute of Education, University College London, 2012a, 2012b,
2012c, 2012d). Sample attrition occurred over the course of the study: 72% of the original
sample was surveyed at age 7. We employed the relevant survey weights for analysis of
separate UK countries (see below) at the fourth survey (age 7). These weights incorporated
adjustment for initial non-response at wave 1 and for differential non-response over time.
While weights do not fully resolve the potential bias introduced by differential
attrition, comparison of the initial wave characteristics of the analytic sample with
those of the original respondents revealed that, while the analytic sample tended to be
more advantaged, the differences were not sufficient to imply substantial bias in
estimates of relationships between variables in multivariate analysis controlling for
these characteristics (see Appendix A; Wooldridge, 2007). Moreover, our approach is
consistent with extant research on behavioral development using the same study (e.g.,
Fitzsimons, Goodman, Kelly, & Smith, 2017; Flouri et al., 2014; Midouhas et al., 2014),
and thus facilitates direct comparison.

<hs>  Analytic sample and exclusions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We restricted our sample to the approximately 60% of MCS families living in England, since
education and public health systems vary across the countries of the UK. We further
restricted our sample to those families who both took part in the first four waves of data
collection, including completion of the main caregiver interview and self-completion
questionnaire. At wave 1 when children were 9 months, 11,533 families lived in England. Of
these, 7387 (63%) took part in the first four waves of data collection, and around 6300
completed main caregiver interviews and had non-missing data on other key variables. Due
to small variations in missing data on behavior, we have sample sizes ranging from 6277 to
6313 for the behavioral outcomes of interest. In terms of inclusion, we found that
families with disabled children were as likely to have been continuously involved in MCS
as families with non-disabled children (analysis available on request).

<hs>  Dependent variables</hs>
  ~~~~~~~~~~~~~~~~~~~

Our dependent variables are the four “problem” subsets of the parent-reported Strengths
and Difficulties Questionnaire (SDQ). The SDQ is a brief behavioral screening tool for 3-
to 17-year-olds that has been widely validated cross-nationally and cross-culturally for
use in non-clinical settings (Goodman, 1997; Goodman, Meltzer, & Bailey, 1998). The full
scale is provided in Appendix B. Parents indicated how true each of 25 attributes (both
positive and negative) were of their child over the 6 months preceding the age 3, 5, and 7
interviews (waves 2–4), ranging from “not true” (0) to “certainly true” (2). Four problem
scales (each comprising five items)—conduct problems (e.g., “often has temper trantrums or
hot tempers”; Cronbach's α = 0.56–0.68), peer relationship problems (e.g., “picked on or
bullied by other children”; Cronbach's α = 0.47–0.58), hyperactivity/inattention (e.g.,
“constantly fidgeting or squirming”; Cronbach's α = 0.71–0.78), and emotional symptoms
(e.g., “has many worries, often seems worried”; Cronbach's α = 0.54–0.66)—were created by
summing item scores (positive attributes were reverse coded), with a higher score
representing more problems. While some of the alphas appear low for problem scales at
certain ages, the subscales are well validated and extensively implemented, including in
studies using the same data (Midouhas et al., 2013). More recently, and Flouri and
colleagues (Flouri, Midouhas, & Narayanan, 2016) investigated the scales using structural
equation modeling and concluded that the individual items loaded well on their latent
constructs. Following standard practice (see e.g., Midouhas et al., 2014), we model the
scores as continuous outcomes.

        <hss>Disability</hss>

        Disability was measured based on children's exposure to a longstanding limiting
        illness (LSLI) at 3, 5, or 7 years determined by two successive questions asking
        parents if: (a) the child had a longstanding illness, and (b) whether that illness
        limited daily activities. We conducted detailed exploratory analysis, including
        known correlates of disability, such as parental education, income, and employment
        status and developed our measure in discussion with the Council for Disabled
        Children, who provided insight into the meaning of changes in LSLI status across
        waves. We also conducted sensitivity analyses using special educational needs
        (SEN) and developmental delay (at 9 months) as alternative measures of disability.
        On this basis, we developed an indicator variable identifying children as disabled
        if they had an LSLI at one or more occasions between ages 3 and 7. LSLI included
        long-term health conditions, such as type 1 diabetes or asthma; mental health
        problems; and impairments, such as partial sight. Using this definition, 10% of
        the sample was disabled. Among disabled children, asthma was the most common
        condition (35%), followed by ear disorders (13%) and dermatitis or eczema (12%).
        Note that in line with the social model of disability, it is not the condition
        that defines whether or not the child is disabled, but whether it is experienced
        as limiting their activities. In additional robustness analysis, we re-estimated
        the models excluding 101 children with specific conditions that might overlap with
        our outcome measures (ICD10 codes: F80-F89 = disorders of psychological
        development; F90-F98 = behavioral problems). Our findings were robust to this
        narrower specification (results available on request), so we retained the analytic
        sample previously described. We additionally estimated our models using a time
        varying measure of LSLI at ages 3, 5, and 7 as a sensitivity analysis. Results
        were consistent with the findings reported here (available on request). A range of
        child, family and parent-child relationship variables that have been found to be
        significantly associated with child behavior and/or disability in previous
        research were included in all analytic models.

        <hss>Child characteristics</hss>

        Child age was measured in fractions of years centered at age 3. Centering enabled
        us to establish initial differences in behavior problems between disabled and non-
        disabled children. We also computed a quadratic age term to measure non-linearity
        in the development of behavior problems over time. Child's sex was included in all
        models. Through estimating an interaction term with LSLI we aimed to isolate any
        differences in behavior problem trajectories between (disabled) boys and girls,
        and to investigate the extent to which child sex moderated the relationship
        between behavioral difficulties and disability in these early school years. Where
        the interaction between disability and child sex was not statistically significant
        (i.e., for conduct problems), we did not include it in the final specifications.
        The British Ability Scale Naming Vocabulary scale (Elliott, 1996), a widely used
        assessment of young children's expressive verbal ability, administered at age 3
        (wave 2), and therefore prior to any school influences on cognitive development,
        was used as a control for children's cognitive ability. The child is shown a
        series of pictures (e.g., shoe, chair, scissors) and asked to identify the
        objects. Children are shown up to 36 pictures, depending on their performance.
        Ability scores created using item response theory ranged from 10 to 141 (Connelly,
        2013; Rasch, 1960).

        <hss>Family background characteristics</hss>

        Low income (poverty) was measured as family household income < 60% of adjusted
        median household income, in line with the UK definition of relative poverty. As
        well as a time varying measure when children were 3, 5, and 7 years of age (waves
        2–4), low income status at wave 1 was also controlled to capture the different
        circumstances disabled children are born into. Maternal work status was captured
        as a binary time varying variable (1 = in work), to capture the role of work
        independently of family income, and to allow for the fact that mother's work
        status might respond to child disability over time. Mothers' initial work status
        at wave 1 was also controlled. Family structure and cohabiting father's (mother's
        partner's) work status was captured in a single time varying variable with three
        values: father not present (single parent family), father present and not in work,
        and father present and in work. As well as the time varying measure, we controlled
        for wave 1 father's work and family structure to capture antecedent influences.
        Parental education was based on the highest qualification held by a parent living
        in the household at wave 1. Qualifications were grouped according to the national
        qualification framework levels (https://www.gov.uk/what-different-qualification-
        levels-mean/overview), and were rated on a 5-point scale, ranging from no
        qualifications (0) to NVQ4 or 5 (4), which equates to a Bachelor's degree or
        higher. To control for maternal mental health, we used a reduced form of the
        Malaise Inventory (Rutter, Tizard, & Whitmore, 1970). At wave 1, mothers
        considered nine indicators of depression/anxiety (e.g., Are you easily upset or
        irritated? ; Do you feel tired most of the time?), and indicated for each whether
        they “generally” felt these symptoms. Items were summed, with higher scores
        indicating increased probability of depression or anxiety (range = 0–9; Cronbach's
        α = 0.73). While this was our preferred measure of maternal mental health and,
        since it was measured at wave 1 when children were 9 months, captured antecedent
        influences on child behavior and its evolution, in a sensitivity analysis we
        estimated an alternative measure of time varying (ages 3, 5, and 7) responses to
        the Kessler scale (Kessler et al., 2003). Since we did not identify any
        substantive differences to our results using this alternative measure, and rates
        of non-response to the Kessler scale were higher than for other measures, we
        retained the Malaise Inventory at wave 1 in our final analysis. Research has
        documented both favorable (Hall et al., 2013) and unfavorable (Stein, Malmberg,
        Leach, Barnes, & Sylva, 2013) associations between early child care usage and
        young children's behavior problems. Child care in formal settings or by non-family
        members may reduce the direct influence of home context or mother's work status.
        We control for use of center-based child care (nursery) and, for comparison, non-
        kin family-based child care (childminder) at age 9 months, relative to using
        neither of these external child care settings.

        <hss>Parenting</hss>

        When children were 3 years old (wave 2), parents reported on how frequently they
        engaged their child in six educational activities: going to the library (“not at
        all” to “once a week”), and reading, painting and drawing, being taught letters,
        being taught numbers, and singing, reading poems, or rhyming (“not at all” to
        “everyday”). Items were summed to create a home learning environment scale (M =
        25.8, SD = 7.39, range = 0 to 42). This scale has been widely used (e.g.,
        Chatzitheochari et al., 2016; Kiernan & Huerta, 2008; Parsons, Schoon, & Vignoles,
        2014) and has shown strong links to children's cognitive and behavioral outcomes
        (de la Rochebrochard, 2012; Hall et al., 2013; Siraj-Blatchford, 2010). To capture
        parent-child closeness, parents' self-evaluation of how close they were to their
        child (“not at all” to “extremely”) at age 5 (wave 3) was used. As 69% of parents
        reported being “extremely” close to their children, we constructed a binary
        variable contrasting “extremely close” with all other responses. Harsh discipline
        in the home was captured at age 5 (wave 3), using seven items from Murray Straus's
        Conflict Tactics Scale (Straus & Hamby, 1997). The scale sums the number of
        discipline measures used by the parent (e.g., ignore, smack, shout at, send to
        bedroom/naughty chair, take away treats, bribe) together with how frequently they
        are used (1 = “never” to 5 = “daily”). The total score ranged from 7 to 34 (M =
        17.78, SD = 4.01; Cronbach's α = 0.71; Johnson, Atkinson, & Rosenberg, 2015).
        Descriptive statistics for all measures, broken down by whether or not children
        had an LSLI, are given in Table 1.

<hs>  Analytic strategy</hs>
  ~~~~~~~~~~~~~~~~~

We estimated linear mixed models of children's behavior (Rabe-Hesketh & Skrondal, 2012;
Singer & Willett, 2003). This analytic technique capitalizes on the repeated measures of
behavioral outcomes measured at three time points, when children were approximately 3, 5,
and 7 years. We examined whether disabled and non-disabled boys and girls start with
similar or different behavior scores at age 3, and whether disability status is associated
with converging or diverging trajectories over the early years, while controlling for
potentially confounding family and child characteristics. We estimate their associations
at baseline (age 3). We also explored whether parenting and the home learning environment
moderated associations between disability and children's behavior problems at baseline and
over the early years. Level 1 represents within-child change in behavior problems from 3
to 7 years, and Level 2 the between-child variation in the expected mean of children's
behavior problems at age 3 (random intercept, β00) and linear change from 3 to 7 years
(random slope, β10). We included a fixed quadratic on age to account for the curved shape
of children's average trajectories (β20). We examined whether average age 3 behavior
problems (β01) and change over time in behavior problems (β11) varied according to
disability status, as well as whether these relationships were moderated by child sex
(β03, β13). The components in the first set of parentheses represent the fixed effects,
and the components in the second set represent the random intercept and linear slope for
each child, reflecting between-child variation in problem behaviors (u0i), their
development over time (u1i), and the error term (eij). The quadratic slope was fixed in
all models. We estimated the growth curve models separately for each of the four problems
in a series of nested models. In model 1, we estimated an unconditional model with age,
age squared and the random intercept and slope. In model 2, we estimated a model with
disability and sex as predictors, as well as two- and three-way interactions between age,
sex, and disability, retaining only statistically significant interactions for the final
model 2 specification. In model 3, we incorporated the full set of family and parenting
characteristics (i.e., time varying family poverty, maternal work status, and family
structure; wave 1 family poverty, maternal work status, family structure, child care
usage, and maternal mental health; wave 2 child cognitive ability and home learning
environment; and wave 3 harsh discipline and parental closeness) as covariates in addition
to the final model 2 specification. Inclusion of the time varying covariates enabled us to
examine the average difference in change over time in behavior problems according to
families' poverty status, maternal work status, and family structure, respectively. The
time invariant covariates enable us to examine the influence of these factors at baseline
(age 3). Finally, in model 4, we included two- and three-way interactions between each of
the key parenting variables (i.e., home learning environment, harsh discipline, and
parental closeness), disability, and age to identify any moderation effect of parenting.
The series of models is illustrated schematically in Table 2, alongside the related
research questions. The models were estimated using the mixed procedure in Stata 13.1
(Rabe-Hesketh & Skrondal, 2012). We present the results from the unconditional model 1 in
Table 3; and in Table 4 we present the initial disability model (model 2) and the full
model (model 3) for each behavioral outcome. As none of the interactions between
disability and parenting were statistically significant for any of the outcomes, model 3
is the final model. To illustrate the key results and demonstrate the magnitude of the
differences, we plot the four behavioral outcomes by disability and sex, using model 3
estimates (Figs. 1–4).

<hs>  Overall development of behavioral problems</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 3 presents model 1. It shows that, in line with previous results, conduct,
hyperactive, and peer problem behaviors tended to decrease over time from around age 3,
with a slight increase from around age 6, as illustrated by the positive value for age
squared. Emotional problems increased over time and at greater rate as the child aged
(inflection point at age 3.5). The random effects parameters reveal that there was
substantial idiosyncratic variation in behavior problems between children at age 3 and
over time.

<hs>  Unconditional behavior trajectories for disabled girls and boys</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 4 illustrates the role of disability in shaping behavioral trajectories. It presents
the results from the models including age, disability, and child sex, and their
interactions (model 2), and the final specification, which includes all the controls and
parenting measures (model 3). We see from model 2 that disability tended to be positively
associated with problem behavior at age 3: a substantial difference amounting to between a
third and four-fifths of a point for boys on the behavioral outcome scale (typically
double or more than double the gap between girls and boys). Prior to school entry,
disabled children demonstrated more challenging behavior than their non-disabled peers.
Child sex was a significant predictor of behavior problems at age 3, as well as their
trajectories from age 3 to age 7. When we look at changes in problem behavior over time by
disability, we see that there was an increasing gap over time between disabled and non-
disabled children for peer problems, hyperactivity (p < 0.10), and emotional symptoms. For
conduct problems, the gap was constant.

<hs>  Conditional behavior trajectories for disabled girls and boys</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Model 3 in Table 4 shows that the relationships between disability and behavioral problems
were largely robust to the inclusion of the full set of family and maternal background
characteristics. To clarify the pattern of the trajectories for disabled and non-disabled
children, and the scale of the gap between disabled and non-disabled girls and boys, Figs.
1–4 illustrate trajectories derived from the full model estimates, with family and
maternal background characteristics set to their mean values. Fig. 1 illustrates the
relatively steep decline in conduct problems over time with a slight upswing one and a
half to two years after their entry into school: an inflection point at age 6.4. This
pattern was tracked by disabled children but at a higher level. Girls faced lower conduct
problems than boys across the early years, but the disability gap for both boys and girls
was constant. The gap in conduct problems between girls and boys was smaller than that
between disabled and non-disabled children, as the figure makes clear. For hyperactivity,
there was a slight decline over time for non-disabled boys that leveled off somewhat
before they reached age 6 (the inflection point was at age 5.7). As Fig. 2 and Table 4
show, non-disabled girls started from a somewhat lower level of problems and faced a
steeper decline, resulting in an increasing gap relative to boys. Disabled boys started
with a larger gap compared to disabled boys, than did disabled girls relative to non-
disabled girls. Disabled girls tracked the steeper decline exhibited by non-disabled
girls, but both disabled girls and boys exhibited a slightly growing gap relative to their
non-disabled peers over time (see Fig. 2 and the interaction effects in Table 4). The
result is that by age 7, disabled boys had substantially higher rates of hyperactivity
than either disabled girls or non-disabled boys, even if not as high in absolute terms as
they were prior to school entry. Non-disabled children's peer problems largely declined
over time, though there was a slight upswing as they reached age 6 (the inflection point
was 5.9 years; see Table 4 and Fig. 3). By contrast, peer problems for disabled children
started increasing by the time of school entry, such that the gaps between disabled and
non-disabled children were at their greatest by age 7. The gap between disabled and non-
disabled boys was substantially greater than that between disabled and non-disabled girls
from the outset, and increased at a faster rate. This left disabled boys experiencing
exceptionally high rates of peer problems by age 7. Emotional problems increased for all
children over the school years. Indeed, they had already started increasing prior to
school entry (inflection point at 4.3 years). However, they not only started higher, but
also increased faster for disabled children (Fig. 4), particularly for disabled boys.
Although disabled girls were more at risk of emotional problems than boys at age 3, and
experienced a sharper increase over time than non-disabled girls, disabled boys
experienced even more of an increase in emotional symptoms so that by age 7 they had the
highest levels. This illustrates a pattern of divergence between disabled and non-disabled
children that was particularly marked for boys.

<hs>  Associations between covariates and behavioral problems at baseline (age 3) and over time</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Before we turn to consider the role of parenting practices in shaping behavioral
trajectories, we briefly discuss associations between the individual and family background
covariates and behavioral problems at age 3. Overall, the inclusion of the covariates in
the full model accounted for only part of the differences in problem behavior between
disabled and non-disabled children, even though many were associated with behavior. As
expected, maternal poor mental health had a strong positive association with child
behavioral difficulties. Socioeconomic characteristics, namely initial poverty status and
lone parenthood were associated with greater levels of problems across the domains. Time
varying maternal employment was also associated with fewer problem behaviors, net of time
varying poverty status, which was itself not significantly associated with problems. Early
experience of external child care was associated with fewer behavioral problems at age 3.
Finally, children who were more cognitively able at age 3 were less likely to exhibit
behavioral problems.

<hs>  Parenting and home environment and behavioral problems</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We expected that parenting and home learning environment would both be associated with
behavioral problems, and that they would also moderate the negative association of
disability and specific problem behaviors. We found that harsh discipline was positively
associated with greater levels of all four types of behavioral problems at baseline.
Similarly, parental warmth as expressed in their closeness to their child was associated
with fewer behavioral problems. Home learning environment was negatively associated with
conduct problems and hyperactivity, but not peer or emotional problems. We found no
evidence for moderation at age 3 or over time: Estimated interactions between parenting,
LSLI, and age were small and did not approach statistical significance.

<h>DISCUSSION</h>
----------

The early development of problem behaviors can have consequences for children's later
outcomes. While most children “grow out” of the problem behaviors that are common in early
childhood, others do not, and may show elevated levels over time. Early problem behaviors
that do not attenuate give way to later problems, including mental health problems,
substance use, and even crime (Caspi, Moffitt, Newman, & Silva, 1996; Fergusson, John
Horwood, & Ridder, 2005; Roza, Hofstra, van der Ende, & Verhulst, 2003). Given that
disabled children are at risk of disadvantage in adulthood across a range of domains
(Berthoud, 2008; Janus, 2009; Lindstrom, 2011; Loprest & Maag, 2003), it is relevant to
ascertain whether these inequities start to develop in the early years and whether their
behavioral trajectories in the early school years are the same or different to those of
non-disabled children. If disabled children are experiencing higher levels and different
trajectories of behavior problems than their peers during this time, it could indicate a
critical point for intervention. Our findings provide clear and consistent evidence that
in their early preschool years disabled children suffer from more challenging expressions
of behavior than their non-disabled peers, and that in the early school years their
trajectories diverge rather than converge. Two points stand out from our findings. First,
disabled children (girls and boys) face sharper increases or slower declines in problem
behaviors across three out of the four domains compared to non-disabled children:
hyperactivity, peer problems, and emotional symptoms. Disabled children demonstrate
greater levels of hyperactivity in the early school years, while their peer relationships
and emotional health also suffer, perhaps directly linked to their externalizing
behaviors. Second, disabled boys are particularly vulnerable to the development of
problems over these critical early years, with steadily widening gaps between themselves
and their non-disabled peers, as well as with disabled girls, again with the exception of
conduct problems. Even in conduct problems where all children exhibited sharp declines
over time, disabled children still exhibited higher levels of these potentially serious
behavioral problems at the beginning of their school career. While the higher rates of
problems and their increase (or stability) were in line with our expectations for
externalizing problems (conduct problems, hyperactivity), our hypotheses were more
speculative for internalizing problems (peer problems, emotional symptoms), though we did
anticipate that peer relationships would present more of a problem for disabled children
as they adjusted to the social environment of school. The size of the effects, the clear
escalation for several of the outcomes, and the ways in which disabled boys, in
particular, were affected was more surprising. The challenges associated with the
expansion of children's developmental ecologies at the time they enter school, where they
are in contact with new and potentially demanding or unsympathetic social environments may
be exacerbated for disabled children, notably, disabled boys. Disabled boys exhibited
concerning rises in both peer problems and emotional symptoms over time. We anticipated
that emotional symptoms would stabilize or increase over time, and perhaps increase most
for disabled girls. Less anticipated, however, was the substantial increase for disabled
compared with non-disabled children, and for disabled boys even more than disabled girls,
perhaps related to the social difficulties they face. Research has found that some
disabled children display less competence in social situations than their peers; they
interact with peers less frequently and are less well accepted within social circles
(Carter & Hughes, 2007). Children often learn social skills through observing and
participating in social interactions. If disabled children are not afforded opportunities
for social learning, however, they miss out on important developmental inputs that may
affect their social competence for years to come. This may be particularly true for boys,
since by the time of school entry, boys and girls exhibit different peer group
experiences. Boys display denser and more hierarchical social networks with less prosocial
behavior and more verbal and physical victimization than girls (Rose & Rudolph, 2006).
Just as all boys face greater challenges in adjusting to peers, our findings show how
disabled boys are particularly at risk, with disability status contributing to widening
the sex gap. These findings clearly indicate that the early years provide a relevant
period for intervention to prevent the escalation and entrenchment of disabled children's
behavioral problems that may be consequential for their subsequent development. Disabled
boys who are already vulnerable in early socializing environments and developmental
settings may benefit, in particular, from practices and contexts that foster easier
transitions into school, such as enriched preschool programs that more explicitly focus on
developing children's socio-emotional school readiness skills (Bierman et al., 2008; Odom
& Wolery, 2003). Social integration activities, such as the formation of structured play
groups within inclusive classrooms, and small group prosocial skills training may both
facilitate more positive peer interactions for disabled children to ensure they benefit
from the natural learning that occurs in day-to-day peer group interactions (Carter &
Hughes, 2007; Odom et al., 1999; Ofsted, 2011). Early intervention in supporting young
disabled children's emotional resilience and curtailing maladaptive behaviors may be
important in preventing the development of more serious mental health problems, and in
preventing high levels of school alienation that have been demonstrated for disabled
children in their teenage years (McDougall, DeWit, King, Miller, & Killip, 2004). Our
findings point to the ways in which social contexts can “disable” children (Connors &
Stalker, 2006), and imply that children's educational plans should incorporate a socio-
emotional component. Successfully transitioning to school requires children to follow the
rules and demands of the classroom, consistently navigate increasingly complex peer
interactions, and appropriately self-regulate their emotions—actions that have been argued
to pose difficulties for disabled children (McIntyre, Blacher, & Baker, 2006). Strong
partnerships between families and school personnel could help to ensure behavior
management strategies and decisions regarding children's care are consistent (Newman,
McEwen, Mackin, & Slowley, 2009; Odom & Wolery, 2003). We expected that the home
environment and parenting might moderate the development of behavioral problems among
disabled children. Our findings showed a significant main effect between the home learning
environment and children's hyperactive and conduct problems, though it did not moderate
the impact of disability. More structured home environments support fewer externalizing
problem behaviors, then, but do not seem to protect against peer or emotional problems.
While closeness and harsh discipline were implicated in, respectively, lesser and greater
levels of all four problem behaviors, we also failed to find any evidence that they
moderated the effect of child disability. Nevertheless, given the higher levels of
behavior problems among disabled children, the creation of stimulating outlets within the
home and the provision of parenting support through early intervention could potentially
have payoffs for them. Similarly, since disabled children are more likely to be growing up
in poverty, in lone parent families, and with greater levels of maternal ill-health, all
of which impact on behavioral problems (even if these do not account for the divergence in
behavioral problems between disabled and non-disabled children), economic and maternal
mental health support may go some way to preventing disabled children starting out on
their differential behavioral pathways in the early years. Overall, this study
demonstrates how disabled children face ongoing difficulties with social relations and
ordered social contexts that cannot adequately adapt to or accommodate their impairments
(Barkley et al., 2002). The early years during which children learn to regulate their
behaviors and adjust to social expectations appear to be differently experienced by
disabled children, and particularly by disabled boys. Instead of modifying their
behavioral problems, the demands of responding to greater social influences and
institutional settings seem to bring emotional costs, and difficulties in behavior and
social relations. Home environments may initially shelter children from these external
influences, but the early environment alone does not protect against these wider social
challenges for disabled children. Our findings on the divergence over the early school
years in children's peer and emotional problems, in particular, reflect the ways in which
“difference” can be enhanced on primary school entry. One of the routes to these poorer
outcomes is the daily separation of disabled children from their peers, illustrating one
of the ways in which certain forms of compensatory provision can inadvertently stigmatize
disabled children, impacting not only their educational, but also their behavioral
development (Webster & Blatchford, 2015). Targeted programs that promote peer inclusion
may offer more promising routes for intervention (Holt, 2007). This implies a better
understanding of school effects and the mechanisms driving those effects could be crucial
to developing appropriate, “non-disabling” environments. That is, the ability to identify
institutional factors, school cultures, and teacher behaviors that are more or less
supportive for disabled children and more or less conducive to stabilizing or reducing
problem behaviors has the potential reduce the escalation of these problems. While our
data cannot identify positive school cultures nor such institutional practices, future
quantitative survey research would benefit from incorporating relevant school-level
factors into analyses linking disability to behavioral problems to provide evidence of
potential mechanisms and identify contexts for further interrogation. Such further
research would facilitate crafting appropriate recommendations for English school systems.
Our study is not without its limitations, including our dependence on parental (mother's)
report of family context, child behavior, child disability, and her own parenting. In
particular, relying on mother's report for behavioral problems means we cannot directly
link it to their behavior at school. For our measure of closeness we rely on a single
item. There was some variation in the reliability of our measures, and internal
consistency for peer problems at age 3 was below 0.5, which raises some concerns for the
reliability of our results at that age. Our longitudinal analysis was limited to three
data collection points across our four-year period of interest, restricting the analytical
purchase. Further, our home environment and parenting variables were each available at one
wave only, preventing us from exploring whether children's experiences in the home and
with their families at particular points in their development affected their behavioral
trajectories. Nevertheless, our study represents a contribution to our understanding of
young disabled children's behavioral problems. Using a nationally representative sample of
children living in England, it provides clear and consistent evidence that disabled
children experience greater behavioral problems in their early years and that these do not
dissipate—and, in some cases, increase—over time. Child behavioral difficulties can have
far reaching consequences and hence, without appropriate support or intervention, young
disabled children may face an accumulation of adverse consequences that serve to
compromise their well-being in adolescence and adulthood.


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<ART>The development of face expertise: Evidence for a qualitative change in processing
================================================================================

Authors: Peter J. Hills, Michael B. Lewis
DOI: 10.1016/j.cogdev.2018.05.003
Year: 2018  |  Pages: 1-18
ASJC codes: 3204, 3205
Keywords: Configural processing, Development, Face recognition, Face-inversion effect

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

There is conflicting evidence regarding the development of expert face recognition, as indexed by the face-inversion effect (FIE; de Heering, Rossion, & Maurer, 2011; Young and Bion, 1981) potentially due to the nature of the stimuli used in previous research. The developmental trajectory of the FIE was assessed in participants aged between 5- and 18-years using age-matched and adult stimuli. Four experiments demonstrated that upright face recognition abilities improved linearly with age (presumably due to improved memory storage capacities) and this was larger than for inverted faces. The FIE followed a stepped function, with no FIE for participants younger than 9-years of age. These results indicate maturation of expert face processing mechanisms that occur at the age of 10-years, similar to expertise in other domains.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

While adult face recognition is one of the most impressive human visual skills given the
ability to differentiate and recognise many thousands of faces (Ellis, 1986), the face
recognition abilities of children are poorer (Adams-Price, 1992; Blaney & Winograd, 1978).
Adult face processing is assumed to be based on some form of expert processing mechanism
(Farah, Wilson, Drain, & Tanaka, 1998) that may well be specific to the processing of
faces (Kanwisher, Tong, & Nakayama, 1998). Poorer face-recognition performance in children
could be due to generally poorer cognitive, attentional, and perceptual systems (see e.g.,
Crookes & McKone, 2009) or a specific deficit in this expert face processing (e.g., Carey
& Diamond, 1977). Expert processing is typically referred to as configural processing and
is made up of three components (Maurer, Le Grand, & Mondloch, 2002): processing of the
first order relations (i.e., two eyes level, side-by-side and above the nose); the
processing of second-order relational information (i.e., idiosyncratic deviations to the
basic template; Carey & Diamond, 1994); and holistic processing, which is processing the
face as a gestalt whole (Rossion, 2008), integrating the multiple sources of information
(Farah et al., 1998; Searcy & Bartlett, 1996). While researchers may not entirely
understand what drives expertise in face recognition, there is consensus that faces are
processed differently to objects and this is likely due to some form of configural
processing (Piepers & Robbins, 2012). There are many sources of evidence to suggest that
expert processing is not based on second-order relational information (Burton,
Schweinberger, Jenkins, & Kaufmann, 2015) but is based on this final form of configural
processing, known as holistic processing (Hole, George, Eaves, & Rasek, 2002; Mondloch &
Desjarlais, 2010). Configural processing is usually contrasted with the featural coding,
which is not indicative of expertise. Featural coding is typically defined as the
processing of individual features in isolation (see Cabeza & Kato, 2000; Tanaka & Sengco,
1997). One method typically employed to assess configural coding is that of inversion
(e.g., Freire, Lee, & Symons, 2000). Indeed, Sergent (1984) suggests that configural
encoding is what is disrupted by inversion, whereas featural encoding is far less
disrupted by inversion (see also Lewis & Glenister, 2003). Therefore, the face-inversion
effect (FIE) is a reliable index of expert face processing (Edmonds & Lewis, 2007;
Gauthier et al., 2000; Yin, 1969). While there is no doubt that face recognition is expert
in adults, there is a debate about when this expertise develops. One theory suggests that
there is an early development of expert face processing mechanisms complete by the age of
approximately 5-years (Crookes & McKone, 2009; Gilchrist & McKone, 2003; Want, Pascalis,
Coleman, & Blades, 2003). While face recognition improves with age, this view suggests
that age-related improvements in face recognition are explained by general improvements in
the ability to attend and focus on the demands of the task (Crookes & McKone, 2009). These
general improvements increase with age and continue to develop throughout childhood and
adolescence (Betts, McKay, Maruff, & Anderson, 2006; Pastò & Burack, 1997; Skoczenski &
Norcia, 2002). An alternative view is that the expert processing mechanisms do not develop
until around 10 years of age (Carey & Diamond, 1977, 1994), consistent with the notion
that many forms of perceptual expertise take approximately 10 years of practice and
development (Akhtar & Enns, 1989; Brodeur & Enns, 1997; Enns & Brodeur, 1989; Ericsson,
Krampe, & Tesch-Römer, 1993; Pearson & Lane, 1991). Recently, a view was put forward that
there might be differential effects for the development of face perception and face
memory, with face memory developing late and face perception developing early (Weigelt et
al., 2013). Wiegelt et al. have presented evidence highlighting that the mechanisms that
control expert face processing are not necessarily the same as expert face memory. Memory
for faces, apparently, develops later than the perceptual expertise for faces. Memory for
faces can be revealed through an increase in hit rate and response bias (as hit rate
represents more faces being stored in memory and more efficient encoding) without
affecting false alarm rate (which better reflects poorer encoding and poorer access to
memory: Hills, 2012). General memory (Chi, 1977; Dempster, 1981; Kail, 1992) and memory
for faces (Flin, 1980), does improve with increased age. Consistent with the view that the
FIE is a measure of expert face perception, then there should be sufficient evidence to
establish whether face perception develops early or late. If face perception expertise
develops late, then one would expect that children would show a smaller FIE than adults.
The evidence for this is mixed. Most authors agree that face recognition abilities improve
approximately linearly with age, reaching an asymptote at the age of 12 (Feinman &
Entwisle, 1976), 17 years (Ellis, Shepherd, & Bruce, 1973; Golarai et al., 2007; Lawrence
et al., 2008; O’Hearn, Schroer, Minshew, & Luna, 2010), or well into adulthood (e.g.,
Germine, Duchaine, & Nakayama, 2011; Susilo, Germine, & Duchaine, 2013) depending on the
stimuli set used.1 However, Flin (1980, 1985) has reported a face recognition performance
“dip” at age 11 years2 (see also, Carey, 1978, 1981; Carey, Diamond, & Woods, 1980). The
improvement in recognition for inverted faces may also be linear, but at a slower rate.
Using a novel (for this field) statistical procedure, de Heering, Rossion, and Maurer
(2012) found that performance on the Benton Face Recognition Test (Benton, Sivan, Hamsher,
Vareny, & Spreen, 1983) correlated with age, between the ages of 6-years and 12-years.
This correlation was stronger for upright than inverted faces indicating that the
magnitude of the FIE also correlated with age. Such an improvement for upright faces over
inverted faces potentially reflects that the expert face processing system has developed
and there is a general improvement in task performance or face memory. Alternatively, this
improvement may reflect a protracted development of expert face processing skills. Data
from matching tasks reveal that children younger than 10 years of age are more likely to
be affected by paraphernalia and pose changes than children older than 10 years and adults
(Diamond & Carey, 1977; Ellis, 1992a, 1992b; Freire & Lee, 2001; Saltz & Sigel, 1967).
These results indicate that children are not coding faces in the most effective configural
manner. Indeed, six- and eight-year-old children do not show the FIE when tested in
matching paradigms (Carey & Diamond, 1977; Hay & Cox, 2000; Joseph et al., 2006;
Schwarzer, 2000) or recognition paradigms (Goldstein, 1975) indicating a greater reliance
on featural processing (Schwarzer, 2000). In these studies, the FIE was found by some ten-
year-old participants indicating some individual difference in the development of expert
face processing which may sometimes mask effects when development is tested cross-
sectionally. These results indicate a qualitative shift in the way children code faces at
age 10 from an inexpert to expert mechanism (Baudouin, Gallay, Durand, & Robichon, 2010;
Mondloch, Leis, & Maurer, 2006). However, other authors have reported that the FIE is
apparent in three- (Carey, 1981), five- (Fagan, 1972; Flin, 1983), or seven-year-old
children (Young and Bion, 1981, 1982) leading to parallel improvements in recognition
skills (Itier & Taylor, 2004). Proponents of the view that the FIE does not increase with
age highlight that the studies that fail to show an FIE in younger participants suffer
from floor effects (Young and Bion, 1981). Nevertheless, an age-by-orientation interaction
is often found in studies that claim there is an FIE in younger participants,3 indicating
that the magnitude of the FIE increases with age (Brace et al., 2001; Carey, 1981; Carey &
Diamond, 1994; Flin, 1983; Goldstein & Chance, 1964). Any effect of age on the magnitude
of the FIE would indicate that children rely more on featural rather than configural
coding (e.g., Hay & Cox, 2000).4 There are a number of methodological and statistical
issues with the studies on children's face recognition. Firstly, most of the studies
conducted on face perception are cross-sectional. There are significant individual
differences in face recognition ability (Li et al., 2010), in the amount of holistic
processing participants engage in (Wang, Li, Fang, Tian, & Liu, 2012), and in terms of how
faces are encoded (Bobak, Parris, Gregory, Bennetts, & Bate, 2017; Mehoudar, Arizpe,
Baker, & Yovel, 2014). This means that, potentially, effects reported in the literature
are due to cohort effects which may be unduly influenced by individual differences in
studies with relatively small sample sizes. For example, the recognition blip observed by
Flin (1985) and the change in FIE observed by Schwarzer (2000) may reflect cohort effects.
A longitudinal study of face perception exploring the development of expert processing
mechanisms has yet to be conducted. A longitudinal study would rule out such cohort
effects. Secondly, many of the studies that explore the FIE in children are underpowered.
When testing multiple age-groups, the necessary increase in error degrees of freedom mean
that it becomes much more difficult to detect significant differences in the FIE due to
age. A within-subjects (and thereby longitudinal design) would improve the statistical
power of such studies. Only when these issues are addressed can studies adequately address
the mechanisms of face processing employed by children. Thirdly, there are several
statistical issues with existing work on the development of face recognition. Certain
tasks do not adequately control for floor and ceiling effects. Floor effects cause a task
to be too difficult for younger children to complete. This makes distinguishing any effect
of inversion very difficult (a similar argument has been made by Weigelt et al., 2013).
One reason for floor and ceiling effects potentially is the use of age-inappropriate
stimuli. Given that the own-age bias exists in face perception, in which participants show
a larger FIE for own-age than other-age faces (Anastasi & Rhodes, 2005; Harrison & Hole,
2009; Hills & Lewis, 2011; Kuefner, Macchi Cassia, Picozzi, & Bricolo, 2008),5 in order to
avoid floor effects, faces should be age-matched to the participants. In adults, the
processing of other-group faces has been theoretically linked to not using the most expert
configural processing system (Hugenberg & Corneille, 2009; Michel, Caldara, & Rossion,
2006; Michel, Rossion, Han, Chung, & Caldara, 2006), which lowers performance in such
tasks. This problem means that standardised tests of childrenʼs face recognition
performance, such as the Cambridge Face Memory Test – Children (CFMT-C; Croydon,
Pimperton, Ewing, Duchaine, & Pellicano, 2014) might underestimate performance. Finally,
even when tasks are sensitive enough to detect differences, there is a further statistical
issue: overall performance in younger children is lower than that of older children. This
means that any effects of inversion may be harder to detect in younger children. In order
to address this, a relative measure of performance needs to be considered (Goldstein,
1965). A relative measure takes into account the fact that childrenʼs overall performance
will be lower than that of adults and therefore allows for smaller differences in
performance in children to be equated to larger differences observed in adulthood. Even
with a relative measure of the FIE, there is a potential issue with a younger children
showing a more limited range of performance than older participants. This can be assess by
ensuring that the variances in performance are equivalent for all groups of participants
(which is an assumption of parametric data in any case). An alternative method to control
for this is to match performance of upright faces in all children by presenting different
numbers of stimuli. While matching performance addresses the issues of poorer performance
in children, it creates a confound: face recognition is made up of face perception and
face memory, therefore manipulating the number of stimuli prevents an analysis of face
memory. It is for this reason, a relative measure of the FIE is the more appropriate
technique for measuring face recognition performance in children. This paper presents a
solution to these problems in order to establish whether children show the FIE to a
similar level as adults and, by extrapolation, utilise expert face processing. Here, the
FIE, as a measure of expertise, was assessed using a standard old/new recognition paradigm
in children (from 5- to 15-years-old) and adults. Three possible developmental trends are
possible: The magnitude of the FIE may increase with age as a product of experience
(developmental induction); The magnitude of the FIE may be constant throughout development
if the effect is not based upon experience (due to early maturation); Finally,
developmentally-late maturation may occur in which the FIE appears at a particular
critical age. These trajectories lead to the increasing inversion effect, the constant
inversion effect, and the “all or none” hypotheses. The first two hypotheses can be
explained by an early maturation of expert face processing mechanisms and the final
hypothesis is derived from a late maturation of expert face processing mechanisms. In this
study, a relative measure of the FIE was used in order to control for poorer general
cognition in younger children controlling for lower absolute performance of the younger
children and therefore avoids floor effects. Absolute floor and ceiling effects were
avoided by choosing a manageable number of stimuli for the youngest children tested that
produced sufficient errors in the adult participants (Ellis, 1992b). While there remains
the possibility that younger children's performance was more restricted than that of older
participants which might obscure results, our data indicate that there was roughly
equivalent variance in performance for the younger children and the older children
suggesting that we did not have floor effects in our study. Floor effects were also
avoided by testing own-age faces for all participants in Experiments 1 and 2. In order to
show that development is occurring within participants (avoiding cohort effects) we also
conducted a longitudinal study of face recognition by testing the same children at
different ages in Experiments 2 and 4.

<h>EXPERIMENT 1</h>
------------

Experiment 1 was a cross-sectional experiment executed in a similar manner to de Heering
et al. (2012). Participants ranged from 5- to 15-years of age and an adult sample. The
primary purpose of Experiment 1 was to understand the developmental trajectory of face
recognition and expert face recognition as measured by the FIE. In order to do this,
correlations and curve fitting was conducted for upright and inverted face recognition and
the FIE separately. This will distinguish the developmental trend of the face processing.

        <hss>Participants</hss>

        Participants were 440 children (198 male) aged from 5,7 years to 15,4 years and 40
        adults (aged 18–23 years; 12 male). See Table 1 for participant details. The age
        groups chosen were linked to the school age they were studying in rather than
        strictly their age (see Hills & Lewis, 2011). Adult participants were recruited
        through a university whereas the children were recruited through local mainstream
        schools. All participants had normal or corrected vision and were ethnically White
        as indicated by parent-report (or self-report in the adult group). All of the
        children were considered typically developing by their schools. No participants
        were familiar with any of the faces used in this experiment.

        <hss>Materials</hss>

        Frontal-view photographs of White childrenʼs (aged from 5- to 18-years) faces were
        collected by a research assistant. Two images of each child were collected: one
        presented during the learning phase and one presented during the test phase. The
        images were quite similar, taken a few moments apart, but the facial expression
        was slightly different. This was done to reduce pictorial recognition (Bruce,
        1982). Photographs of 32 (16 female) children were collected in each age group.
        All parents provided consent for these photographs to be used in this research
        project. The faces all had similar hairstyles, positioned in a frontal view in
        neutral or mildly happy expressions (this was randomised). All extraneous
        paraphernalia and the background were masked using Adobe™ Photoshop™. The stimuli
        were collected from local schools that were not used for the experimental testing.
        Participants only saw faces of their own age. To confirm that faces of one age
        category were not more dissimilar to those in another category, a pixelwise
        similarity comparison was made between the faces in each age group (Haushofer,
        Livingstone, & Kanwisher, 2008). This was not significant (p > .56). Similarly,
        attractiveness ratings did not differ across stimuli types (p > .39). While this
        cannot rule out stimulus differences across ages, it indicates that differences
        are not substantial. The faces were presented 100 mm by 110 mm dimensions in 72
        dpi resolution in the learning phase and 150 mm by 165 mm in the test phase. An
        inverted version of each face was created using the rotate function in Adobe™
        Photoshop™. These were presented using Superlab Pro 2™ Research Software using a
        Toshiba Tecra M4™ Tablet PC.

        <hss>Design</hss>

        Twelve participant groups were tested as determined by their school year group.
        Participants viewed both upright and inverted faces. The faces were
        counterbalanced between participants such that each face was a target as often as
        it was a distracter. The faces were counterbalanced such that they appeared
        upright as frequently as they appeared inverted. Faces were presented in a random
        order (i.e., there was no blocking of face type). The dependent variables were
        recognition accuracy, measured in terms of the Signal Detection Theory (SDT e.g.,
        Swets, 1966) measure d' and response bias, measured in terms of the SDT measure,
        C. Reaction time could not accurately be measured due to the experimenter keying
        the responses (see procedure). The relative FIE was established using the
        formula:FIE = (d'U − d'I)/(d'U + d'I)where d'U is the recognition accuracy of
        upright faces and d'I is the recognition accuracy of inverted faces. This measure
        produces a relative measure of the FIE and controls for differences in overall
        accuracy between participant groups.

        <hss>Procedure</hss>

        Participants were tested individually in a quiet brightly-lit room in their school
        (or in a quiet laboratory for adults). Participants sat 50 cm from the computer
        screen. This screen was positioned away from the Experimenter such that he could
        not see the contents of the screen. Participants responded verbally and the
        experimenter entered the responses into a standard computer keyboard. Thus, the
        Experimenter could not influence the participants’ responses because the stimuli
        were presented in a random order, and he was unaware of what was on the screen,
        preventing demand characteristics. Additionally, this ensured that the
        Experimenter could ensure the participants followed the instructions
        appropriately. A standard old/new recognition paradigm was employed involving
        three consecutive phases: learning, distraction, and test. In the learning phase,
        participants were shown half of the set of faces of their own-age (N = 16) of
        which half were upright and half were inverted. Faces were presented centrally in
        a sequential random order. Participants were instructed to rate each face for how
        attractive they thought the face was using a 1–9 Likert-type scale, with the
        anchor points “ugly” and “beautiful” (Light, Hollander, & Kayra-Stuart, 1981). If
        a participant did not understand the scale, it was explained to them using
        alternative synonyms. The presentation of each face was response terminated: There
        were no differences in presentation duration across participant group (see Table
        3, F(11, 468) = 0.24, MSE = 1464959, p = .995, ηp2 = 0.01). There was a 150 ms
        blank screen inter-stimulus interval between each face. Immediately after this
        presentation, participants were given some control questions. These were: “What is
        your first name?” “What is your surname?” “What is your gender?” “How old are
        you?” "When is your birthday?" “What school do you go to?” “What school year group
        are you in?” “Where were you born?”. If the participant did not understand the
        question it was explained using simpler synonyms. Only participant age, birthday,
        and gender were recorded. These questions took no longer than 60 s to administer.
        Following this, the participants were given the test phase. In this, the
        participants saw all 16 target faces and 16 distractor faces sequentially in a
        random order and made an old/new recognition judgement to each face. Each
        presentation was in the centre of the screen and was response terminated. Half the
        faces were upright and half the faces were inverted. Orientation of the target
        faces was matched from learning to test. The participants were told to be as quick
        and as accurate as possible. Between each face there was a blank screen for 150
        ms. Once this phase was completed, the participants were thanked and debriefed.
        Total testing time was no more than four minutes per participant.

<hs>  Results</hs>
  ~~~~~~~

Old/new responses from participants were converted to hit and false alarm rates and these
were used to calculate d' and C using the MacMillan and Creelman (2005) method. In
addition to reporting the traditional null hypothesis significance tests, we also report
Bayesian statistics throughout this work. Bayesian analysis has the advantage that it is
not based on the evaluation of significance levels that can be interpreted incorrectly
(especially regarding non significant results, see Rouder, Speckman, Sun, Morey, &
Iverson, 2009). The Bayes Factor (B10) provides the likelihood ratio of the experimental
hypothesis being true compared to the null hypothesis being true (Dienes, 2011). A Bayes
Factor of between 1/3 and 3 only provides anecdotal evidence; a value between 3 and 10
provides substantial evidence for the hypothesis; a value above 10 provides strong
evidence for the hypothesis; a value between 0.1 and 1/3 provides substantial evidence for
the null hypothesis and; a value less that 0.1 provides strong evidence for the null
hypothesis (Jeffreys, 1961). We used the Bayes calculator provided by Dienes (2015).

        <hss>Recognition accuracy (d’)</hss>

        Zero counts in misses and false alarms were replaced with 0.01 (there were no zero
        counts in hits or correct rejections). With the number of stimuli in this
        experiment, d' ranged from 0 (chance recognition) to 4.48 (perfect performance).
        Fig. 1 presents the mean d' for upright and inverted faces grouped according to
        age and highlights, crucially, that there were no floor or ceiling effects in any
        condition. These data were first subjected to a 12 × 2 mixed ANOVA with the
        factors: participant age and orientation. Critically, there was strong evidence
        for a significant interaction between orientation and participant age, F(11, 468)
        = 13.19, MSE = 0.53, p < .001, ηp2 = .24, B10 = 3.18 × 1038. To decompose this
        interaction, two univariate ANOVAs were run: one for upright faces and one for
        inverted faces. The effect of age was larger for upright faces, F(11, 468) =
        23.60, MSE = 0.75, p < .001, ηp2 = .36, B10 = 6.53 × 1045, than for inverted
        faces, F(11, 468) = 2.36, MSE = 0.27, p = .008, ηp2 = .05, B10 = 401679. Curve
        estimations were conducted for recognition accuracy, summarised in Table 2. The
        relationship between recognition accuracy and age was equally well represented by
        a linear, quadratic, and cubic function. Given that all three were significant,
        and that they all represent the data well, it is clear that this pattern indicates
        an overall linear improvement in recognition accuracy, but with a step change mid
        way through development, indicated by the quadratic and cubic functions. The
        correlations for upright faces were compared against the inverted faces using
        Fisher's r-to-z transformation. These revealed that the correlations were
        significantly stronger for upright faces than inverted faces (see Table 2). An
        analysis was conducted on the mean-relative FIE presented in the bottom panel of
        Fig. 1, and revealed strong evidence that the FIE depended on age, F(11, 468) =
        6.84, MSE = 0.16, p < .001, ηp2 = .14, B10 = 4445395. Pairwise comparisons
        revealed that there was no significant difference in the FIE form participants
        aged 5- to 10-years nor between 9-years and adults (all ps > .18). Five- to 8-year
        old participants showed a significantly smaller FIE than participants age 11 and
        older (all ps < .030). Eleven-year old and older participants showed a
        significantly larger FIE than children under the age of 8-years of age. The FIE
        was compared at each age using a series of one-sample t-tests, with the
        significance levels reported in Fig. 1. Curve estimations show while the FIE
        increased with age according to an overall linear trend, the significant quadratic
        and cubic functions indicate a step change in the FIE during development.

        <hss>Response bias, C</hss>

        A final analysis was conducted on the response bias data (shown in Table 3),
        calculated using the Macmillan and Creelman (2010) method. This measures
        participants’ tendency to respond with an “old” response. The score typically
        ranges from −1 to +1, where 0 is a neutral bias. A positive number indicates
        participants are less likely to response with an “old” respond when they are
        unsure and a negative number indicates a tendency for participants to respond with
        an “old” response when they are unsure. There was strong evidence for a
        significant interaction between orientation and participant age, F(11, 468) =
        2.60, MSE = 0.19, p = .003, ηp2 = .06, B10 = 1.69 × 1015. To decompose this
        interaction, two univariate ANOVAs were run: one for upright faces and one for
        inverted faces. For upright faces, the effect of age was larger with a lesser
        tendency to respond with a "new" response for older participants than younger
        ones, F(11, 468) = 2.78, MSE = 0.28, p = .002, ηp2 = .06, B10 = 232.64, than for
        inverted faces, F(11, 468) = 2.10, MSE = 0.07, p = .019, ηp2 = .05, B10 = 82.48.
        Curve estimations were conducted for response bias, summarised in Table 2.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The results from Experiment 1 indicate that face recognition improves with age. This is
entirely consistent with previous research (e.g., Blaney & Winograd, 1978; Carey et al.,
1980; Flin, 1985). Curve fitting revealed that upright face recognition improved more
reliably with age than inverted face recognition. All measures of face recognition
improved with age, suggesting that participants memory for faces improved with age (as
indicated by hit rate) and the coding of faces becomes more accurate (as indicated by a
reduction in false alarm rate). These results indicate that face memory and face
perception are developing. The pattern of data observed here also indicates that there is
a step-change in the FIE, whereby participants under the age of 9-years do not show the
FIE, whereas participants 10-years and older do show the FIE. In this analysis, we have
fitted curves to the data. These curves show a linear, cubic, and quadratic trajectory for
the development of the FIE suggesting a qualitative shift in the use of configural coding.
If the development of configural processing was due to developmental induction, we would
only expect to see a linear relationship. Only a hypothesis predicting that there would be
no FIE until a certain age, followed by a full-strength FIE is compatible with the data.
This is as predicted by the late maturation of configural processing account.

<h>EXPERIMENT 2</h>
------------

In order to fully explore this step-change in the use of configural coding, a second
experiment was conducted. This was a longitudinal study in which the same 9-year-old
participants were followed up for two years following the original testing. We chose to
follow these participants due to the observation in Experiment 1 that indicated a step
change in the FIE between the ages of 9 and 11 years. This acts as an internal replication
of the initial findings and critically offers a longitudinal approach to understand how
face recognition develops. The longitudinal design also offers a window to explore
development of a particular group of participants. Many of the drawbacks of cross-
sectional designs are avoided in this approach as it allows researchers to see change in
behaviour due to age. This is also one of a very small handful of longitudinal studies
applied to face recognition.

<hs>  Method</hs>
  ~~~~~~

The same nine-year-old participants in Experiment 1 were tested two further times at
approximately (within one month) yearly intervals. Testing took place in an identical
manner as in Experiment 1 with the same stimuli used for the ten- and 11-year-old children
in Experiment 1 for the second and third testing times respectively. Therefore, the
participants were viewing own-age faces at age 9-, 10-, and 11-years. This, therefore, led
to a 2 × 3 within-subjects design with the factors: orientation of the face and
participant age (9-, 10-, and 11-years of age).

<hs>  Results</hs>
  ~~~~~~~

The data were treated in the same way as in Experiment 1 and are presented in Fig. 2 and
Table 4. The recognition accuracy (d’) data were subjected to a 2 × 3 within-subjects
ANOVA with the factors orientation and age. Critically, these effects interacted, F(2, 78)
= 4.20, MSE = 0.66, p = .018, ηp2 = .10, B10 = 6.68 × 108. This interaction was decomposed
by conducting two one-way ANOVAs, one for upright faces and one for inverted faces. The
improvement in recognition accuracy for upright faces was significant, F(2, 78) = 5.58,
MSE = 0.94, p = .005, ηp2 = .13, B10 = 37.85, but it was not for inverted faces, F(2, 78)
= 0.36, MSE = 0.32, p = .699, ηp2 = .01, B10 = 0.09. A trend analysis was conducted and
this revealed that the improvement in face recognition accuracy for upright faces was
linear, F = 11.32, MSE = 0.92, p = .002, ηp2 = .23, with no other significant
developmental trajectories (all ps > .769). A one-way ANOVA was run on the relative
measure of the FIE, revealing a significant effect of age, F(2, 78) = 4.05, MSE = 0.15, p
= .021, ηp2 = .09, B10 = 18.77. One-sample t-tests showed that there was strong evidence
the FIE was not present in the 9-year old participants, t(39) = 1.93, p = .061 effect size
r = .30, B10 = 0.24, but was present in 10-year old, t(39) = 4.27, p < .001, effect size r
= .56, B10 = 1606.76, and 11-year old participants, t(39) = 8.22, p < .001, effect size r
= .80, B10 = 5.00 × 1013. A linear trend was observed, F = 9.19, MSE = 0.12, p = .004, ηp2
= .19. No other contrast pattern was observed (all ps > .44). Finally, a parallel ANOVA
was run on the response bias (C) data, revealing a significant interaction, F(2, 78) =
7.09, MSE = 0.19, p = .001, ηp2 = .15, B10 = 1.27 × 1011. The change in response bias with
age (with a lesser tendency to respond with a "new" response for older participants than
younger ones) was significant for upright faces, F(2, 78) = 9.80, MSE = 0.28, p < .001,
ηp2 = .20, B10 = 1.10 × 1090, but not for inverted faces, F(2, 78) = 0.43, MSE = 0.09, p =
.649, ηp2 = .01, B10 = 0.02. This change in response bias followed a linear pattern, F =
11.92, MSE = 0.27, p = .001, ηp2 = .23, and a quadratic pattern, F = 7.87, MSE = 0.30, p =
.008, ηp2 = .17.

<hs>  Discussion</hs>
  ~~~~~~~~~~

We have demonstrated a significant improvement in the recognition of upright age-matched
faces with development. This development is much greater for upright faces than for
inverted faces. The effect of this is that the FIE is not observed when our participants
were 9-years of age, but was present when they were older. This developmental study
indicates that a step change in the emergence of the FIE. This important advancement in
our understanding of the development of face recognition.

<h>EXPERIMENT 3</h>
------------

In order to be able to fully compare these results to previously published data, it is
important to assess whether the developmental trends we have found exist when recognising
adult faces. This is especially important given the use of the CFMT-C (Croydon et al.,
2014) to assess deficits in children's face recognition (Bennetts, Murray, Boyce, & Bate,
2017) which use adult faces. If the results we found in Experiments 1 and 2 generalise to
adult faces, then there is no concern with using such adult tests in children. To this
end, we used a similar method to that use in Experiments 1 and 2, with different
participants and different faces: specifically, adult faces.

        <hss>Participants, design, and procedure</hss>

        Participants were 242 children (115 male) aged from 5,7 years to 16,2 years and 22
        adults (aged 18–22 years; 6 male). A participant summary is shown in Table 5. All
        other participant details were the same as in Experiment 1. The design and
        procedure of this Experiment was identical to that in Experiment 1.

        <hss>Materials</hss>

        Two images of 32 (16 female) adult faces from the Minear and Park (2004) database
        were used in this study. These were of adults in their late 20 s (and therefore
        did not match the age of any of our participants). One image displayed a happy
        expression and the other displayed a neutral expression. One of these was
        presented during learning and the other during test (this was randomised). Using
        two images of the same face reduces pictorial recognition (Bruce, 1982). The face
        images in this database were of males and females, all with similar hairstyles,
        positioned in a frontal view. All extraneous paraphernalia and the background were
        masked using Adobe™ Photoshop™. The faces were presented in the same way as in
        Experiment 1 and in the same dimensions.

<hs>  Results</hs>
  ~~~~~~~

The results for this Experiment were analysed in the same way as Experiment 1.

        <hss>Recognition accuracy (d')</hss>

        Recognition accuracy data are summarised in Fig. 3 and were subjected to a 12 × 2
        mixed ANOVA, with the factors: participant age and orientation. This revealed
        strong evidence for a significant interaction between orientation and participant
        age, F(11, 252) = 8.66, MSE = 0.44, p < .001, ηp2 = .27, B10 = 1.45 × 1018. To
        decompose this interaction, two univariate ANOVAs were run: one for upright faces
        and one for inverted faces. For upright faces, the effect of age was larger, F(11,
        252) = 13.52, MSE = 0.76, p < .001, ηp2 = .37, B10 = 1.88 × 1014, than for
        inverted faces, F(11, 252) = 2.30, MSE = 0.54, p = .011, ηp2 = .09, B10 = 70.47.
        Curve estimations were conducted for recognition accuracy, summarised in Table 6.
        The relationship between recognition accuracy and age was equally well represented
        by a linear, quadratic, and cubic function. The correlations for upright faces
        were compared against the inverted faces using Fisher's r-to-z transformation.
        These revealed that the correlations were significantly stronger for upright faces
        than inverted faces (see Table 6). An analysis was conducted on the mean-relative
        FIE presented in Fig. 3, and revealed that the FIE depended on age, F(11, 252) =
        3.11, MSE = 0.17, p = .001, ηp2 = .12, B10 = 8.79. However, no pairwise
        comparisons between participant ages were significant following Bonferroni-Šidák
        correction. This highlights the critical point about using age-inappropriate
        stimuli and a lack of experimental power may hide real effects of development in
        the FIE. One-sample t-tests were used to compare the magnitude of the FIE at each
        age, shown in Fig. 3. Curve estimations show that changes in the FIE follow a
        linear, quadratic, and cubic function.

        <hss>Response bias, C</hss>

        A final analysis was conducted on the response bias data (see Table 7). There was
        a significant interaction between orientation and participant age, F(11, 252) =
        0.70, MSE = 0.15, p = .737, ηp2 = .03, B10 = 45.72. To decompose this interaction,
        two univariate ANOVAs were run: one for upright faces and one for inverted faces.
        For upright faces, the effect of age was smaller and with anecdotal evidence,
        F(11, 252) = 1.88, MSE = 0.20, p = .042, ηp2 = .08, B10 = 2.15, compared to the
        strong evidence for inverted faces, F(11, 252) = 3.33, MSE = 0.16, p < .001, ηp2 =
        .13, B10 = 14.73. Older participants demonstrated a lesser tendency to respond
        with an "old" response than younger ones. Curve estimations were conducted for
        response bias, summarised in Table 6.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The results from this Experiment are consistent with Experiment 1: face recognition
improves with age and more reliably so for upright faces than inverted faces. The step-
change in the FIE, whereby participants under the age of 9-years do not show the FIE,
whereas participants 11-years and older do show the FIE, was also found. Curve-fitting
showed a linear, cubic, and quadratic trajectory for the development of the FIE suggesting
a qualitative shift in the use of configural coding suggesting late maturation of
configural processing.

<h>EXPERIMENT 4</h>
------------

Similar to Experiment 2, we retested the 9-year old participants in Experiment 3 one and
two years later in order to show a developmental improvement in the recognition of faces
from a longitudinal study.

<hs>  Method</hs>
  ~~~~~~

The same procedure described in Experiment 2, except it was conducted on the 9-year old
participants we tested in Experiment 3. The one change to the method was that we used two
additional sets of faces from the Minear and Park (2004) database to ensure that the faces
were unfamiliar to our participants. These were of the same age-range as those described
in Experiment 3. This was a 2 × 3 within-subjects design with the factors: orientation of
the face and participant age (9-, 10-, and 11-years of age).

<hs>  Results</hs>
  ~~~~~~~

The data was treated in the same way as in Experiment 1 and are presented in Table 8. The
recognition accuracy (d’) data were subjected to a 2 × 3 within-subjects ANOVA with the
factors orientation and age. Critically, these effects interacted, F(2, 42) = 8.90, MSE =
0.36, p = .001, ηp2 = .30, B10 = 3.22 × 1011. This interaction was decomposed by
conducting two one-way ANOVAs, one for upright faces and one for inverted faces. The
improvement in recognition accuracy for upright faces was significant, F(2, 42) = 6.07,
MSE = 0.44, p = .005, ηp2 = .22, B10 = 14.67, but smaller for inverted faces, F(2, 42) =
3.24, MSE = 0.32, p = .049, ηp2 = .13, B10 = 2.32. A trend analysis was conducted and this
revealed that the improvement in face recognition accuracy for upright faces was linear, F
= 9.24, MSE = 0.57, p = .006, ηp2 = .31, with no other significant developmental
trajectories (all ps > .689). A one-way ANOVA was run on the relative measure of the FIE,
revealing a significant effect of age, F(2, 42) = 3.32, MSE = 0.13, p = .046, ηp2 = .14,
B10 = 3.27. One-sample t-tests showed that the FIE was not present in the 9-year old
participants, t(21) = 1.02, p = .545, effect size r = .22, B10 = 0.29, but was present in
10-year old, t(21) = 3.18, p = .005, effect size r = .57, B10 = 16.65, and 11-year old
participants, t(21) = 3.74, p = .001, effect size r = .63, B10 = 251.31. A linear trend
was observed, F = 4.83, MSE = 0.16, p = .039, ηp2 = .19. No other contrast pattern was
observed (all ps > .35) (Fig. 4). Finally, a parallel ANOVA was run on the response bias
(C) data, revealing no effect of age, F(2, 42) = 0.33, MSE = 0.13, p = .718, ηp2 = .02,
B10 = 0.37. There was also no effect of orientation, F(1, 21) = 0.16, MSE = 0.11, p =
.695, ηp2 = .01, B10 = 0.21. The interaction was not significant, F(2, 42) = 0.56, MSE =
0.13, p = .578, ηp2 = .03, B10 = 0.25.

<hs>  Discussion</hs>
  ~~~~~~~~~~

In this Experiment, we have demonstrated a significant improvement in the recognition of
adult faces with development. This development is much greater for upright faces than for
inverted faces. The FIE was not observed when our participants were 9-years of age, but
was present when they were older. This longitudinal study replicates the step change in
the emergence of the FIE around the age of 10-years.

<h>COMPARISON BETWEEN EXPERIMENTS</h>
------------------------------

While there are many limitations regarding the comparison across different studies,
especially considering subtle methodological differences across the studies,6 we compared
the face recognition performance across Experiments 1 and 3 in a 12 × 2 × 2 Mixed ANOVA
with the factors: age of participant, orientation of stimuli, and type of stimuli (age-
matched, Experiment 1; adult faces, Experiment 3). Prior to this analysis, we compared the
average stimulus pixelwise complexities for the children's faces and the adult faces and
found that they were not significantly different (p > .32). Similarly, attractiveness
ratings did not differ significantly across the adult and the children's faces (p > .16).
Figs. 1 and 3 appear to show similar patterns that indicate the recognition accuracy of
upright adult and child faces increases faster than that of inverted faces. In this
comparative analysis, there are two main effects of interest: the main effect of stimuli
type and the interaction between stimuli type and orientation of the stimuli. We ran this
analysis on the d' recognition accuracy measure first. This revealed a main effect of
stimuli type, F(1, 720) = 6.07, MSE = 0.62, p = .014, ηp2 = .01, B10 = 3.01. On average,
performance with age-matched stimuli (M = 1.48, SE = 0.03) was approximately 10% greater
than adult faces (M = 1.38, SE = 0.03) replicating the own-age bias (Anastasi & Rhodes,
2006). This effect interacted with orientation of the face, F(1, 720) = 6.63, MSE = 0.50,
p = .010, ηp2 = .01, B10 = 5497, replicating Hills (2012). This interaction was revealed
through a larger face-inversion effect on own-age faces (mean difference = 0.84, SE =
.04), F(1, 479) = 252.57, MSE = 0.67, p < .001, ηp2 = .35, B10 = 1.45 × 10100, than other-
age faces (mean difference = 0.65, SE = 0.06), F(1, 263) = 95.14, MSE = 0.58, p < .001,
ηp2 = .27, B10 = 1.15 × 1024. All these results indicate that the use of other-age faces
when studying face recognition in children may well be underestimating performance.
Finally, the same interaction between stimuli type and orientation was observed in the
response bias data, F(1, 720) = 16.56, MSE = 0.17, p < .001, ηp2 = .02, B10 = 2.79 × 1017.
The effect of stimuli type was larger for inverted (mean difference = .12, SE = .03), F(1,
742) = 22.49, MSE = 0.11, p < .001, ηp2 = .03, B10 = 10425.45, than upright faces (mean
difference = .07, SE = .04), F(1, 742) = 2.76, MSE = 0.26, p = .097, ηp2 < .01, B10 =
0.75.

<h>GENERAL DISCUSSION</h>
------------------

Through four Experiments we have shown that there was a significant improvement in the
recognition of upright faces with development (both longitudinally and cross sectionally)
consistent with previous research (Blaney & Winograd, 1978; Carey & Diamond, 1977; Carey
et al., 1980; Diamond & Carey, 1977; Goldstein, 1965; Goldstein & Chance, 1964; Saltz &
Sigel, 1967). The longitudinal data showed numerically consistent results with the cross-
sectional data for participants within three years. This indicates that recognition
improvements over three years are relatively small but detectable with a suitable
experiment. Here we shall first summarise the findings across the experiments before
relating the findings to theoretical discussion presented in the introduction. Across all
measures, the improvement in the recognition of upright faces was approximately linear
(Carey, 1978; Flin, 1980, 1985), though had significant quadratic and cubic functions.
This pattern is indicative of a slow gradual overall improvement in face recognition, but
with a step change causing the cubic and quadratic functions. The statistics highlight
that that there is less improvement in face recognition during mid-adolescence. This is
consistent with findings of other cognitive abilities (e.g., Flin, 1983). Furthermore,
there is quick rise in face recognition abilities between the age of 9- and 12-years. To
highlight this step change in abilities between these ages, we have shown that the
improvement in face recognition at these ages is exclusively linear (in the longitudinal
data, Experiment 2). This indicates that this is the age driving the cubic function. These
findings are interesting as they present an often ignored aspect within developmental
work: while the age-related developmental trajectory may produce an overall linear
pattern, other functions are present indicating that factors exist that may enhance or
inhibit such development. These factors maybe individual difference variables, relating to
hormonal, maturational, or environmental changes surrounding the individual. This linear
improvement in the recognition accuracy of upright faces was significantly greater than
the approximately linear improvement in the recognition of inverted faces, consistent with
de Heering et al. (2012). In other words, the improvements to the recognition of upright
faces were greater than the improvements in the recognition of inverted faces. This is
entirely consistent with the notion of expertise developing for the recognition of faces
that are encountered in the most common orientation. Relating to the general models of
perceptual and skill development presented in the introduction, this is akin to
developmental induction due to experience with upright faces outweighing experience with
inverted faces and therefore leading to enhanced learning how to process these stimuli.
The FIE, measured in relative terms, showed a different pattern of development. This
showed no increase in the FIE until the age of 9-years, followed by an increase in the FIE
over two years before plateauing. A close inspection of de Heering et al.ʼs (2012) data
reveals a similar pattern. These data are consistent with an “all-or-none”’ late
maturational model of the FIE (Carey et al., 1980; Itier & Taylor, 2004) with a slower
development of configural coding than featural coding (Mondloch, Le Grand, & Maurer,
2002). Here, there is statistical evidence for this assertion: the change in the FIE with
development followed primarily a cubic function. We present this assertion against a
background that the measure of FIE we used should have enhanced the likelihood of us
finding it in the youngest age groups. Since we did not, it clearly shows that configural
coding (as measured by the FIE) is not employed for faces until about the age of 10-years.
The present data also indicate that there is a general increase in memory for faces with
development (see e.g., Brown, 1975; Chi, 1977; Dempster, 1981; Flavell, 1977; Kail, 1992)
given that hit rate increased with age. However, memory for inverted faces did not improve
with age. This is more consistent with Weigelt et al.’s (2013) data indicating a domain-
specific increase in face memory with age rather than a general improvement in cognitive
functioning (Crookes & McKone, 2009; McKone & Boyer, 2006). In the introduction, a number
of potential explanations were presented for the FIE. Our data indicate a sharp increase
in the FIE between the ages of 9 and 10 years. This indicates an increase in expertise in
face recognition during this period. This expertise is likely to be the form of configural
processing known as holistic processing (Maurer et al., 2002a). One theory of holistic
processing is that inversion disrupts the perceptual field such that the entire upright
face cannot be sampled from a single central fixation (Rossion, 2008, 2009). These effects
mirror those observed in other areas of perceptual expertise that require many years of
experience to achieve (Charness, Reingold, Pomplun, & Stampe, 2001; Ericsson, Krampe, &
Tesch-Römer, 1993; Kundel & Nodine, 1975). An inverted face, on the other hand, cannot be
processing from a central fixation: this has been found in eye-tracking evidence (Barton,
Radcliffe, Cherkasova, Edelman, & Intriligator, 2006; Hills, Sullivan, & Pake, 2012; Xu &
Tanaka, 2013). This suggests that with development, the perceptual field widens when
viewing faces until, around the age of 10-years, it is sufficient to encode an entire face
with one fixation. This hypothesis can be easily tested by exploring the eye-movements of
children. There is evidence that the features used by children to process faces changes
with age. Campbell, Walker, and Baron-Cohen (1995) has shown an external feature advantage
at age 7-years that shifts to an internal feature advantage by 9-years of age. Further
eye-tracking evidence supports a late development of this internal feature advantage
(Kelly et al., 2011; Meaux et al., 2014; Senju, Vernetti, Kikuchi, Akechi, & Hasegawa,
2013). In addition, younger children should show more fixations with wider distribution
over the features than older children and adults (Hills, Willis, & Pake, 2013). Indeed, Ge
et al. (2008) have shown that older children tend to be able to recognise faces based on
the most diagnostic features (the eyes for White faces and the nose for East Asian faces;
Ge et al., 2008; Kelly et al., 2011; Liu et al., 2013). Younger children, on the other
hand, rely on less diagnostic features. The refinement of eye-movements appears to occur
at around 10 years of age. The development of eye-movements has been interpreted as
evidence of the development of face expertise (Ge et al., 2008; Tanaka et al., 2014). It
is thought that the progression to more sustained fixation on the diagnostic features may
help the development of face processing expertise such that it becomes a more rapid and
automatic process (Kelly et al., 2011) consistent with notion that face expertise involves
a change in processing style and cognitive encoding (Diamond & Carey, 1977), from local to
holistic (Hole, 1994; Tanaka & Farah, 1993) and configural processing (Leder & Bruce,
2000). The expert perceptual field theory has a great deal of support for it from other
areas of congitive, attentional, and perceptual development. Expertise in many domains is
associated with greater ability to "chunk" information and create more stable schemas
(Braune & Foshay, 1983; Goldstein, 1975) with increased systematisation of knowledge
(Karmiloff-Smith & Inhelder, 1974). Such systematised knowledge leads to improved memory
when consistent with internal schemas (Simon & Barenfeld, 1969; Simon & Gilmartin, 1973
see also Chase & Simon, 1973a, 1973b; DeGroot, 1965, 1966; DeGroot & Gobet, 1996; Gobet &
Simon, 1996a, 1996b). Wider perceptual fields are observed in expert footballers (Williams
& Davids, 1997) and quicker processing from fewer fixations and greater chunking is
observed in expert chess players (Charness et al., 2001; Reingold, Charness, Pomplun, &
Stampe, 2001; Reingold, Charness, Schiltetus, & Stampe, 2001) and radiologists (Kundel &
Nodine, 1975). Indeed, the automatisation of perceptual processing (Vurpillot, 1968) and
attentional shifting requires less effort than inexpert processing as it is based on an
unconscious and automatic process. This takes circa ten years to develop (e.g., Akhtar &
Enns, 1989; Brodeur & Enns, 1997; Enns & Brodeur, 1989; Pearson & Lane, 1991) or occurs at
the age of 10 years. The data fit with neuroscientific evidence that indicates the pattern
of face-specific recruitment of cortical regions is not observed prior to the age of ten
years (Aylward & Meltzoff, 2005 but see Golarai, Liberman, & Grill-Spector, 2015) or that
the size of face-specific regions is smaller in children than adolescents or adults
(Golarai et al., 2007) and that the magnitude of ERPs associated with face perception are
different for children than adolescence and adults (Kuefner, De Heering, Jacques, Palmero-
Soler, & Rossion, 2010). The key finding here is that the FIE appears to follow a
maturational development (as highlighted by the cubic function), whereas the development
of recognising upright faces appears to follow an induction pattern. Of course, the notion
that there is ten years of development that is required for face recognition expertise is
an overly simplistic argument. It may be that this trend appears at the age of 10 years
due to biological and/or social constraints that are vital for expertise to develop rather
than experience. The cause of expertise development at the age of 10 years could be due to
hormonal changes altering the functioning of the attentional spotlight and eye-movements.
Puberty is associated with a number of hormonal changes known to affect cognitive
functioning especially those associated with frontal lobe functioning (Blakemore &
Choudhury, 2006) due to the significant synaptic pruning that occurs in this region during
puberty (Woo, Pucak, Kye, Matus, & Lewis, 1997; Zecevic & Rakic, 2001). Indeed,
development during this period involves the development of attentional shifting, abstract
reasoning, and inhibition (Yurgelun-Todd, 2007). These factors indicate that at this age,
the perceptual system can utilise a more robust schema that inhibits irrelevant dimensions
and focuses on the most diagnostic information for recognising faces. While there is
hormonal and biological maturation occurring at this time, there are significant
environmental changes that occur at the same age. School environmental changes at age
10–11 from small classes in smaller schools in primary education to larger classes at
larger secondary schools (college). This results in exposure to more faces than previously
encountered and typically a large number of new faces. This sudden increase in the amount
of exemplar's entering the face-space may result in its refinement. Whatever the cause,
this mechanism clearly results in a potentially unique and special processing for faces at
this age. There is, of course, a limitation of the present work. By the age of 5-years,
children will have been exposed to a significant number of faces right from birth. Indeed,
there is evidence that the early visual system is set up to process faces (de Heering et
al., 2008). Newborn visual acuity makes faces the single most important visual stimulus
leading to early engagement with faces (Coulon, Guellai, & Streri, 2011). This explains
why there are implicit measures of face processing in infants, measured using ERPs (de
Haan, Johnson, & Halit, 2003) that appear to show differentiation between faces and
objects (Peykarjou, Pauen, & Hoehl, 2016; Peykarjou, Wissner, & Pauen, 2017) and even
between upright and inverted faces (Halit, De Haan, & Johnson, 2003; Peykarjou & Hoehl,
2013). While these measures do not show the ability to individuate faces, such data
indicates significant learning about faces and the development of mechanisms to process
faces prior to the age of participants tested here. The influence of this on subsequent
face recognition has not been considered in the present study. Infants will not be exposed
to as many faces as adults, and are less likely to encounter own-age faces than other-age
faces given that infants spend more time with their parents and family members than at
schools or nurseries. The method of discriminating between a small number of faces
encountered is likely to be based on simple mechanisms, especially if these faces are more
varied in terms of age (we are considering an environment where an infant has frequent
contact with both parents, older siblings, and grandparents). In these situations, simpler
age cues may be sufficient to identify and discriminate faces. However, when older, the
number and types of faces that are encountered are likely to be more homogenous and
therefore the methods used to discriminate these necessarily need to be more
sophisticated. We used inverted faces in the present study as way of assessing development
of inexpert processing. There is no reason to believe that the developmental trajectory
for the recognition of objects would be different to that of inverted faces given that
inverted faces are processed using the inexpert featural processing manner that is
afforded to objects. We have also shown the effects of inversion to be greater when
testing faces of one's own age relative to other-age faces. However, since we did not
compare the recognition of own-age and other-age faces in the same children, we cannot
rule out potential participant and stimuli effects for this difference. One caveat with
the explanations presented here is that these results are specific to the FIE during
recognition. A general theory that explains all effects of inversion would require a great
deal more specification than is currently available. Furthermore, there is no reason to
believe that inversion affects all aspects of face processing and configural coding in the
same way. Another limitation with the present study is that it cannot address what the
maturational mechanism actually is, or indeed if it is enhancement, facilitation, or
maintainence (Coren, Ward, & Enns, 1999). Previously proposed mechanisms are the
qualitative shift from featural to holistic processing (Carey & Diamond, 1994). This is
entirely possible, but the cause of this shift is not clear. Similarly, it could be that
there is a shift from using certain (presumably featural) dimensions to other (more
configural) dimensions of face-space (Valentine, 1991). Indeed, the data presented by
Hills, Holland, and Lewis (2010) is consistent with this presumption: children under
10-years of age can be adapted to facial distortions (a single eye moved) that adults
cannot because they are coding faces according to each feature individually rather than
the features together. Alternatively, it is plausible that it requires ten years for
schema (in this case, prototype face) to become more fixed or robust. All of these
interpretations lack the precise description of the mechanism and cause for this change.
In conclusion, the expert processing mechanism (potentially configural or holistic
processing) develops. However, there is a maturational component to this development,
suggesting a stage where it is not largely utilised (prior to 10-years of age) to a stage
where it is largely employed. This coding switch idea has been hypothesised before (Carey
& Diamond, 1977), but adequate tests of it have not been forthcoming until now. This is
not to suggest that configural processing cannot be done prior to the age of 10, but that
its reliable and constant use is not likely before that age. Indeed, the effects of
inversion may be unrelated to other measures of "configural" coding (such as the parts and
wholes test; Konar, Bennett, & Sekuler, 2010; Wilhelm et al., 2010). Nevertheless, the
results from this study are reliable given the internal replication and the robust
statistical procedures employed.


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<ART>The development of regret and relief about the outcomes of risky decisions
==========================================================================

Authors: Teresa McCormack, Eimear O'Connor, Sarah Beck, Aidan Feeney
DOI: 10.1016/j.jecp.2016.02.008
Year: 2016  |  Pages: 1-19
ASJC codes: 3204, 3205
Keywords: Counterfactual thinking, Decision making, Development, Regret, Relief, Risk

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<h>ABSTRACT</h>
--------

Although a number of studies have examined the developmental emergence of counterfactual emotions of regret and relief, none of these has used tasks that resemble those used with adolescents and adults, which typically involve risky decision making. We examined the development of the counterfactual emotions of regret and relief in two experiments using a task in which children chose between one of two gambles that varied in risk. In regret trials they always received the best prize from that gamble but were then shown that they would have obtained a better prize had they chosen the alternative gamble, whereas in relief trials the other prize was worse. We compared two methods of measuring regret and relief based on children's reported emotion on discovering the outcome of the alternative gamble: one in which children judged whether they now felt the same, happier, or sadder on seeing the other prize and one in which children made emotion ratings on a 7-point scale after the other prize was revealed. On both of these methods, we found that 6- and 7-year-olds' and 8- and 9-year-olds' emotions varied appropriately depending on whether the alternative outcome was better or worse than the prize they had actually obtained, although the former method was more sensitive. Our findings indicate that by at least 6 or 7 years children experience the same sorts of counterfactual emotions as adults in risky decision-making tasks, and they also suggest that such emotions are best measured by asking children to make comparative emotion judgments.

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<h>INTRODUCTION</h>
------------

There has been a recent surge of research interest in the development of counterfactual
thinking (for reviews, see Beck & Riggs, 2014; Rafetseder & Perner, 2014). Some of this
research has focused on the development of emotions thought to require counterfactual
thinking abilities, specifically regret and relief (Burns, Riggs, & Beck, 2012; McCormack
& Feeney, 2015; O’Connor, McCormack, & Feeney, 2012; O’Connor, McCormack, & Feeney, 2014;
Rafetseder & Perner, 2012; van Duijvenvoorde, Huizenga, & Jansen, 2014; Weisberg & Beck,
2010; Weisberg & Beck, 2012). Researchers studying early and middle childhood have
primarily focused on attempting to pinpoint the age at which children first experience
these emotions (O’Connor et al., 2012; Rafetseder & Perner, 2012; van Duijvenvoorde et
al., 2014; Weisberg & Beck, 2010, 2012). Although this research has proved fruitful, there
is still considerable disagreement over when regret can first be observed developmentally
(Rafetseder & Perner, 2012; Weisberg & Beck, 2012). It is possible to identify three
methodological issues that make it difficult both to resolve this disagreement and to
integrate developmental findings with the larger body of research on regret conducted with
adults. The current study directly addresses these issues. All of these developmental
studies have used a simple paradigm requiring children to choose between two boxes to win
a prize of stickers or candies. Children see the prize from their chosen option and then
rate how they feel about that prize on an emotion rating scale ranging from very happy to
very sad (the exact nature of this scale differs across studies). When giving these
initial ratings, children have received only what is termed partial feedback; they have
seen the prize resulting from their choice, but they have not yet seen the prize they
would have won if they had made a different choice. Children are given complete feedback
when they see both what they have won and what they would have won if they had made a
different choice. Emotion ratings are subsequently made after complete feedback. If the
prize from the unchosen option is better than that from the chosen option, children
reporting that they now feel sadder are assumed to be experiencing regret about their
choice; if it is worse, children reporting that they now feel happier are assumed to be
experiencing relief. Although all of the developmental studies employed this basic
procedure, they differ from each other in the exact way that counterfactual emotions are
assessed; moreover, the task they use also differs in important ways from the type of task
typically used to examine counterfactual emotions in adolescents and adults (Burnett,
Bault, Coricelli, & Blakemore, 2010; Camille et al., 2004; Coricelli et al., 2005). We
focus on three methodological issues stemming from these differences: the nature of the
choices children need to make, the extent to which their emotional responses can be based
on a single comparison between the prize received and the best or worst prize available,
and the way in which emotion ratings are used to measure regret/relief. Each of these
issues is described in turn.

<hs>  Choice and risky decision making</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Experiments examining regret and relief in adolescents and adults have used paradigms in
which the choice that participants make is more complex than simply choosing between two
boxes. Such studies typically align with research in the broader decision-making
literature insofar as the tasks involve choosing between alternatives that vary in
associated risk. In most tasks, the choice is between two gambles, with gambles giving
participants the opportunity to win or lose points (e.g., Bault, Coricelli, & Rustichini,
2008; Coricelli et al., 2005; Mellers, Schwartz, & Ritov, 1999). For example, Burnett et
al. (2010) asked participants to choose between pairs of gambles that differed in risk
such as a choice between a gamble with a 50% chance of winning 50 points along with a 50%
chance of losing 50 points (+50/−50) and a gamble with an 80% chance of winning 200 points
but a 20% chance of losing 200 points (+200/−200). On a regret version of such a trial, if
participants chose the +50/−50 option, they were then shown that they would have won 200
points if they had chosen the other gamble; on a relief version, if participants chose
that option, they were then shown that they would have lost 200 points if they had chosen
the alternative gamble. There is a good reason why studies of counterfactual emotions in
adults have used tasks in which participants need to choose between options varying in
risk: Researchers interested in the processes underlying risky choice have been examining
whether counterfactual emotions are an important element of decision making (Coricelli,
Dolan, & Sirigu, 2007; Mellers et al., 1999). Such a hypothesis stems from an influential
tradition of formal models of the role of regret in economic choice (Bell, 1982; Loomes &
Sugden, 1982). Moreover, neuropsychological studies using these tasks have attempted to
identify the brain systems that underpin regret (Sommer, Peters, Gläscher, & Büchel,
2009). Studies using such tasks with brain-damaged patients who do not experience regret
have helped to establish that this emotion may indeed play a role in risky decision making
(Camille et al., 2004; Coricelli et al., 2007; but see also Levens et al., 2014). Although
there are good methodological reasons for using simpler tasks with young children, the
fact that the developmental studies on regret use a quite different task that does not
involve risky choice means that it is difficult to integrate the findings of such studies
with those from the research with adults. In particular, we do not know whether young
children experience counterfactual emotions in the same sorts of decision-making
situations as adolescents and adults or whether such emotions may play a role in
explaining developmental changes in risky decision making. The current study used a task
that closely resembled in structure the tasks used with adults insofar as it involved
choosing between two gambles that varied in risk. However, the task was simplified. In the
studies with older participants, not only does the magnitude of possible prizes vary
across gambles, but the odds of winning prizes can vary as well (in the example given
above, the odds in one gamble are 50/50 and those in the other are 80/20). By contrast, in
our task only the magnitude of the possible prizes varied, with each gamble always
involving a 50% chance of winning one of two prizes. For example, children needed to
choose between a gamble in which there was a 50% chance of winning 10 points and a 50%
chance of winning 7 points and a more risky gamble in which prizes of 16 points and 1
point were equiprobable. Although this simplified the task, it nevertheless allowed us to
examine the developmental profile of counterfactual emotions in the context of risky
choice.

<hs>  Single reference point versus multiple reference points</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Using a gambling task allowed us for the first time to examine the early development of
counterfactual emotions in the context of risky choice. However, it also allowed us to
address a further issue regarding the flexibility with which children make spontaneous
counterfactual comparisons. One claim in the literature (see Rafetseder & Perner, 2012;
Rafetseder & Perner, 2014) is that younger children’s emotions in a box-choosing task may
be underpinned by just the simple thought that “I do not have the best prize” (or
conversely “I do not have the worst prize”) and thus are best described as frustration
rather than regret. This explanation implies that (a) younger children’s emotions are not
the result of counterfactual thinking and (ii) the comparisons children make between what
they obtained and what else was available are inflexible. That is, if children’s emotions
are a result of such thoughts, we need only to assume that, unlike adults, children are
making a single comparison between what they actually won and the other available prize.
Adults’ emotional ratings on the gambling task reflect an ability to flexibly make
different types of comparisons between the reward obtained and (at least) two other
reference points. By flexibly, we mean that adults can shift their point of reference
appropriately in response to the different types of information that they receive. Adults’
emotional responses indicate that they make a comparison following partial feedback
between what they did win on the gamble they selected and what they could have won on that
particular gamble. Using the example of a choice between two gambles of +50/−50 and
+200/−200, when participants choose the +50/−50 gamble, unsurprisingly they report a
negative emotion if they lose 50 points; negative emotions in such circumstances are
interpreted as reflecting disappointment (Mellers et al., 1999). Regret and relief are
assumed to be a result of a further comparison when complete feedback is provided (i.e.,
on being shown the result of the other unchosen gamble) between what they won and what
they would have won had they chosen the other gamble. Using our example, a participant who
lost 50 points might nevertheless report the positive emotion of relief on seeing that he
or she would have lost 200 points had he or she chosen the other gamble. By using our
simplified gambling task, we were able to examine whether children can make similar types
of comparisons. Consider a situation in which children choose between a gamble to win
either 16 points or 1 point (16/1) or either 10 or 7 points (10/7). Imagine that a child
chooses the safer gamble, 10/7, and wins 10 points. That child already knows that he or
she has not won the best available prize of 16 points. Nevertheless, the child may report
feeling relatively happy because he or she did receive the best prize from the chosen
gamble. If the child does report feeling relatively happy, we can be confident that the
child’s response is not solely based on a single comparison between the actual outcome and
the best (or worst) prize available. Now assume that complete feedback is provided,
revealing that the alternative prize from the unchosen outcome is 16 points, and the child
reports feeling sad. We can be confident under such circumstances that the child has
flexibly used two different points of reference: what the child could have won in the
chosen gamble and what the child would have won if he or she had selected the alternative
gamble. Each of these different points of reference would yield different (and, crucially
from the point of view of observing them, contrasting) emotional responses. Although we
know that older children, like adults, can indeed use both of these points of reference
(Habib et al., 2012), the design of previous studies with younger children has meant that
it is not clear at what age such an ability is present.

<hs>  Within-trial versus between-trial comparisons of emotion rating</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The third issue that this study addresses concerns an important difference between
existing studies in how emotion ratings are actually used and interpreted. In what we term
within-trial procedures, participants make ratings following partial feedback, are
subsequently given complete feedback, and then make a second rating. This is the method
that has been used in the majority of developmental studies. By contrast, in what we term
between-trial procedures, participants make only a single rating on any given trial either
following partial feedback or following complete feedback (e.g., Burnett et al., 2010;
Rafetseder & Perner, 2012). These ratings can then be compared across trials as necessary.
The majority (although not all) studies with adults have used procedures in which a single
emotional rating was collected following either partial or complete feedback (e.g.,
Burnett et al., 2010; Chua et al., 2009; Coricelli et al., 2005; Mellers et al., 1999;
Zalla et al., 2014). As we will see, one possible explanation for the inconsistencies
observed in developmental studies lies in whether within-trial or between-trial
comparisons of emotion ratings have been used. Studies examining when regret first emerges
developmentally that have used within-trial procedures have all found evidence of regret
or relief in children from at least around 6 or 7 years of age (Burns et al., 2012;
McCormack & Feeney, 2015; O’Connor et al., 2012, 2014; van Duijvenvoorde et al., 2014;
Weisberg & Beck, 2010, 2012); indeed, using such a procedure, Weisberg and Beck (2012)
argued that regret may even be observable in children as young as 4 years. Rafetseder and
Perner’s (2012) study is the only one to examine the developmental emergence of regret
using a between-trial comparison of emotion ratings. Notably, they found that in children
under 9 years of age, there was no difference in ratings following partial versus complete
feedback. On the basis of their findings, they concluded that regret was not apparent in
children until around 9 years. Interestingly, it seems to be the case that whether further
age differences are reported in levels of counterfactual emotions later in development
also depends on which method is used. In a study comparing young adolescents, mid-
adolescents, and adults using the gamble choice paradigm and a between-trial method,
Burnett et al. (2010) found that there was only limited evidence of developmental changes.
There was no evidence of developmental increases in the intensity of negative emotion in
regret trials, and although they did find increases in the intensity of positive emotions
in relief trials between young and mid-adolescents, there were no further changes after
this age. By contrast, using a similar paradigm but with a within-trial procedure, Habib
et al. (2012) found evidence of developmental increases in regret, with both 11-year-olds
and an adolescent group showing less regret than an adult group. These studies differed in
that Burnett et al. (2010) index of regret and relief was simply the intensity of reported
emotion on complete feedback trials, whereas Habib et al. (2012) calculated the difference
between emotion ratings involving partial and complete feedback taken within a single
trial. Habib et al. speculated that the results of the two studies are not consistent
because of this difference in the way that regret and relief were measured. Looking across
the findings from developmental studies, it is clear that whether it is better to use a
within-trial or between-trial procedure is an important methodological issue. Researchers
working with younger children disagree as to which is the most appropriate method
(McCormack & Feeney, 2015; Rafetseder & Perner, 2012). Rafetseder and Perner (2012) argued
that it is not appropriate to use a within-trial method because children may feel
compelled to change their response if asked to give a second emotion rating in a single
trial; children’s reports of feeling sadder after complete feedback may simply reflect a
tendency to give a different rating after double questioning. Rafetseder and Perner (2012)
found some evidence to support this suggestion in a study where they directly compared a
within-trial method with a between-trial method. Younger children were more likely to
report feeling sadder after seeing the alternative outcome in the within-trial condition,
where they made two emotion ratings, than in the between-trial condition, where they made
only one emotion rating. However, O’Connor et al. (2012, 2014; see also McCormack &
Feeney, 2015; van Duijvenvoorde et al., 2014) included an extra trial type to control for
the effects of double questioning in which the prizes in both the chosen and unchosen
boxes were identical. They found that very few children were likely to report feeling
sadder in these control trials, suggesting that children’s tendency to report feeling
sadder in regret trials was not an artifact of double questioning. Nevertheless, given the
burgeoning number of studies on the development of counterfactual emotions, it would be
useful to reexamine this methodological issue directly. The current study aimed to do so
by using within-trial and between-trial comparisons of emotion ratings in the same study
to directly examine whether these methods do indeed yield different patterns of
developmental findings.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

The current study used our simplified version of the gambling task with children aged 6 or
7 years and an older group of 8- and 9-year-olds. Our youngest age group was selected
because the majority of researchers have concluded that most 6- and 7-year-olds are able
to experience regret, as measured by the box-choosing task. However, it is not clear
whether this age group will show evidence of counterfactual emotions in the context of
risky decision making. We included an older group because we were also interested in
whether there would be developmental increases across this age range in the likelihood
that participants experienced counterfactual emotions. Van Duijvenvoorde et al. (2014)
demonstrated that the likelihood that children experienced counterfactual emotions even in
a simple box-choosing task increased over this period of childhood, and this study allowed
us to examine whether this was also the case in a risky decision-making task. Participants
selected between gambles varying in risk (see Table 1), with a fixed 50% chance of each
outcome. Children received many fewer trials than in studies with adolescents and adults,
but we constructed these trials carefully to allow an examination of whether children were
able to use two points of reference in their emotion judgments. There were two general
types of trials: regret trials and relief trials. In regret trials, children selected
between two gambles such as 10/7 and 16/1, where 10/7 is the safer option compared with
the riskier 16/1 option. In Experiment 1, if children chose the safer option in regret
trials, they always won the best prize from that option (10 points). However, they were
also always shown that they could have won a better prize (16 points) if they had chosen
the riskier option. In relief trials, children also needed to make a choice between a
safer option and a riskier option such as between 9/6 and 14/1. If they chose the safer
gamble, they always won the worse prize (6 points) but were shown that they would have won
fewer points if they had chosen the risky gamble (1 point). Experiment 2 used a similar
set of trials but, as will be described, also included additional regret and relief trials
in which the choice of gambles and magnitude of the received prize were matched between
these trial types. In Experiment 2, we also varied whether children initially won the best
or worst prize from their chosen gamble. In Experiment 1, in addition to varying whether
trials were relief or regret trials, we also varied whether participants made two emotion
ratings per trial (one after partial feedback and a second one after complete feedback) or
just one emotion rating (only after complete feedback). This allowed us to directly
compare regret and relief as measured either using the within-trial method or the between-
trial method. Of interest was whether the developmental patterns differed depending on the
measure used and whether either measure was more sensitive.

        <hss>Participants</hss>

        Participants were 37 6- and 7-year-olds (18 girls; M = 84.4 months, range = 77–91)
        and 31 8- and 9-year-olds (13 girls; M = 110.8 months, range = 103–118). Children
        were recruited from schools local to the university of the first author, were
        predominately from lower- to middle-class backgrounds, and were of Caucasian
        origin.

        <hss>Apparatus</hss>

        The task used 12 cardboard boxes (16 × 26 × 15 cm). The 4 boxes used in the
        practice trials were painted blue and red, whereas the 8 boxes used in the
        experimental trials were painted black and white. The boxes were vertically
        divided into two colored sections, and each section contained a card representing
        the number of points won in two ways: as a printed symbolic number and in concrete
        form as a picture of a stack of discs, with the number of discs corresponding to
        the number of points won (see Figs. 1 and 2). Each box had a hinged lid that could
        be opened to reveal just one side of the box. Along the division on the outside of
        each box were two yellow stars indicating the number of points in the two sections
        displayed as symbolic numbers. There was no indication of which colored side
        contained which amount of points. Separately, there were also concrete
        representations of the possible points to be won in the form of cylindrical stacks
        of metal discs, with each disc representing 1 point. These stacks were placed to
        the side of each box (see Figs. 1 and 2). Two dice were used; the practice die was
        painted half blue and half red, and the experimental die was painted half black
        and half white. During the task, a horizontal number line from 1 to 100 with a
        small arrow was used to indicate the number of points accumulated during the game.
        A 7-point affective response scale was used, with cartoon faces varying in
        emotional expression from very happy on the left-hand side to very sad on the
        right-hand side of the scale. Children indicated their emotional responses using
        this scale and a three-pronged arrow. The three-pronged arrow had leftward-,
        rightward-, and upward-pointing prongs indicating feeling happier, sadder, and the
        same, respectively. Seven small pictures representing different emotion-provoking
        scenarios (e.g., a lost dog poster, a trophy) and two puppets with toys (a camera,
        a mobile phone, and a watch) were used in the pretraining session where children
        learned how to use the emotion scale. Prizes were small “goodie” bags containing
        age-appropriate toys.

        <hss>Procedure</hss>

        Children were invited to play a game and were told that if they won enough points
        by the end of the game, they would receive a goodie bag. The 7-point scale was
        first introduced along with the seven cartoon pictures. The cartoon faces were
        described from left to right as feeling “really really happy” through to “really
        really sad.” Children were then asked to indicate which face represented one of
        the aforementioned feelings. Next, children were shown the seven cartoon pictures
        and were told that different things can make us feel happy or sad. The pictures
        and the scenarios they represented were discussed before children were asked to
        rate how they would feel in each scenario (e.g., “Imagine you won a trophy; how
        would you feel?”). Each picture represented a different feeling on the scale.
        Answers were discussed and corrected if necessary. This technique was used so that
        children were comfortable with the idea of degrees of happiness or sadness and
        thus willing to use the full range of the scale. Children were then introduced to
        the two puppets. One puppet received a small toy and was described as feeling
        “really happy,” and the other puppet received two toys and was described as
        feeling “really really happy,” with the arrow pointing to the appropriate face on
        the scale. Each puppet received an additional toy, and children were asked to
        indicate, using the three-pronged arrow, whether that puppet now felt happier than
        before (leftward prong), sadder than before (rightward prong), or the same as
        before (upward prong). This demonstration was repeated but with both puppets
        losing their toys. Children who gave incorrect answers were corrected, and the
        trials were repeated. Full details of this training procedure are provided in
        O’Connor et al. (2012, Experiment 2). Next, a pair of blue and red practice boxes
        was introduced. Each of the two boxes was split into two sides, one red and one
        blue, and the boxes were opened to show children the two sections. The
        experimenter showed the two cards depicting the prizes for each box. In the first
        practice trial, the two cards for one of the boxes depicted 9 and 4 points,
        respectively, and the two cards for the other box depicted 8 and 5 points,
        respectively. The experimenter then placed one card in each colored section of
        each box, keeping the number on each card hidden. The experimenter pointed to the
        two stars on the outside of each box that depicted its two prizes (e.g., 9 and 4
        points) along with the concrete representations of these in the form of the
        cylindrical stacks of metal discs that were placed in the front of each box. The
        experimenter made it clear that there was only one card per section and that
        children could not be sure which card was in which section. Children were then
        asked a series of comprehension questions to ensure that they understood how the
        points were allocated. Children who gave incorrect answers were corrected, and the
        process was repeated until they showed a full understanding of how the points were
        distributed. Children were told that to play the game they first needed to roll
        the colored die because this would determine whether they would be using the blue
        or red sections of the boxes.1 After the die was rolled, children were asked to
        choose just one box for a prize of points. The experimenter opened the
        predetermined colored section (blue or red) of the chosen box and revealed the
        printed card (e.g., 9 points). The corresponding section of the unchosen box was
        then opened, and the card was revealed (e.g., 8 points). Children completed one
        more practice trial with the two remaining blue and red boxes; in this second
        trial, one box contained 7 and 3 points and the other box contained 6 and 4
        points. The presentation order of the practice trials was counterbalanced.
        Children then moved on to experimental trials that involved four sets of black and
        white boxes. Each experimental trial included a safer box and a riskier box; see
        Table 1 (Trials 1–4) for a breakdown of the number of points displayed on the
        outside of each box. Unknown to children, trial outcomes were manipulated in
        advance of the game by planting appropriate cards in the sections of the boxes;
        actual outcomes are depicted in Table 1 for each trial type, assuming that
        children made the safer choice. Children who chose the riskier box always won just
        1 point because it was hoped that this would deter children from choosing the
        risky boxes. This decision was made because the critical trials for analysis were
        trials in which children chose the safer box.2 The experimental trials were
        presented in blocks of four, with each trial number (Trials 1–4 in Table 1)
        occurring once per block. For each child, the order of the trials remained
        constant across blocks but was varied between children. We did this by assigning
        children randomly to one of 12 different possible trial orders, with 6 of these
        orders having a regret trial as the first one in the block and 6 having a relief
        trial as the first one in the block. Because we were only interested in children’s
        performance on trials in which children made the safer choice (see also Burnett et
        al., 2010; Habib et al., 2012), the number of blocks and trials that children
        received varied depending on the number of safer choices they made; we detail
        below how this was managed. Two different methods were used to measure children’s
        feelings about their choices during the game. The within-trial method involved
        trials in which children made two emotional ratings, which had the following
        structure depicted stage by stage in Fig. 1. In Stage (i), children were shown the
        pair of black and white boxes with the possible points depicted on them and the
        corresponding representations of the number of points in stacked discs. In Stage
        (ii), the black and white die was thrown, determining whether children would get
        the black half or the white half of the boxes. In Stage (iii), children were asked
        to select one box from the pair, and depending on the die throw the experimenter
        opened either the black or white section of the chosen box and children were shown
        the number of points that they had obtained (in the example in Fig. 1, the child
        chooses the safer box, and the appropriate side is opened to reveal a card
        depicting 10 points; the stack of 10 discs is then placed beside the box, and the
        stack of 7 discs is removed to make it clear that the child has won 10 points). In
        Stage (iv), children were asked to rate how they felt about the outcome using the
        7-point scale (emotion rating after partial feedback). In Stage (v), once this
        rating had been made, the alternative outcome was then revealed from the
        appropriate section of the unchosen box (in the example in Fig. 1, the child finds
        out that he or she would have won 16 points had he or she chosen the other box).
        In Stage (vi), children were asked to indicate, using the three-pronged pointer,
        whether they now felt happier, sadder, or the same (updated emotion rating after
        complete feedback). Thus, for these trials, children made two emotion ratings: one
        following partial feedback and one following complete feedback; these are labeled
        Two Rating trials. For the between-trial method, the measure of interest was
        whether children’s emotion ratings differed depending on whether they had received
        complete or partial feedback. This measure necessarily involved a comparison of
        emotion ratings from two separate trials of the same type; a rating after partial
        feedback was compared with a rating given on a separate but otherwise identical
        trial in which only complete feedback was provided. Ratings following partial
        feedback were taken from the Two Rating trials [i.e., at Stage (iv) listed above
        and as depicted in Fig. 1]. These were compared with ratings taken from a separate
        block of otherwise identical trials that had the same Stages (i) to (iii) as above
        but involved children making an emotion rating only once they had complete
        feedback. Fig. 2 shows a sample One Rating trial. As can be seen from the figure,
        these differed from Two Rating trials in that children saw the contents of both
        the chosen and unchosen boxes before making a single emotion rating. Children
        first completed two blocks of 4 trials, with each block consisting either of 4 One
        Rating trials or 4 Two Rating trials. Each block involved the 4 trials depicted in
        Table 1. Once these blocks had been administered, because only data from trials
        where the safer option had been chosen could be included in the analysis, we
        administered a single repetition of trials in which children had made the riskier
        choice. Testing proceeded after the administration of the first two blocks of
        trials as follows. If children had chosen the safer option in both the One Rating
        and Two Rating blocks for any specific trial number (from Trials 1–4 in Table 1),
        they were no longer given any more trials of that number because this provided the
        full data set needed for an assessment of performance on that trial number using
        both the within-trial and between-trial methods. This meant that if children had
        chosen only safer options on all 8 trials in the first two blocks (which was
        rare), testing was terminated. However, if children had made a riskier choice for
        a specific trial number in either the One Rating or Two Rating block, that
        specific trial number was repeated once as necessary in a subsequent block in
        order to obtain the data needed for that trial. For example, with regard to Trial
        1 (10/7 vs. 16/1), if children chose the safer gamble (10/7) when given both One
        Rating and Two Rating versions of that trial, they did not repeat Trial 1.
        However, if they chose the riskier option (16/1) in the One Rating version of the
        trial, the One Rating version was repeated in a subsequent One Rating block (the
        same was true if they chose the riskier option in the Two Rating version of that
        trial). Thus, repetitions of the One Rating and Two Rating blocks included only
        trials for which children had not chosen the safer option. If children failed to
        choose the safer option again on a given trial number, we did not administer it a
        further time, and we set an upper limit of four blocks of trials per child to
        prevent fatigue with the task. This meant that children received variable
        quantities of trials, with a minimum of 8 and a maximum of 16 trials (M = 12.06,
        SD = 1.97). Children were shown a running total of the number of points they had
        won. The experimenter used the 1 to 100 number line to do this, recording the
        number of points children won during the game by updating the position of the
        arrow on each trial. All children received a goodie bag at the end of the game
        regardless of the actual number of points won.

<hs>  Results</hs>
  ~~~~~~~

The younger children completed on average 1 more trial than the older children (M = 12.51,
SD = 2.01 vs. M = 11.52, SD = 1.81); this was due to the younger children making
significantly more risky choices, t(66) = 2.22, p < .05. All subsequent analyses reported
here are only of trials in which children chose the safer box. We began by comparing
initial emotional ratings following partial feedback only from blocks of Two Rating trials
to examine whether children’s responses to their actual prize varied depending on whether
they had received the best possible prize from their chosen box. Ascribing a score of 1 =
really really sad to 7 = really really happy, the average first emotion rating on the
7-point scale given in regret trials was 6.47 (SD = 0.92) and in relief trials was 5.42
(SD = 1.08); children were initially significantly happier after seeing the actual outcome
in the regret trial (where they received the best outcome from their chosen gamble) than
they were in the relief trial (where they received the worst outcome from their chosen
gamble), t(57) = 6.51, p < .001.

        <hss>Within-trial analysis of counterfactual emotions</hss>

        This analysis focused on the second emotional ratings given after complete
        feedback in Two Rating trials using the three-pronged arrow. These ratings are
        always relative to the first ratings following only partial feedback and are
        categorical (i.e., happier than, sadder than, or the same as before the unchosen
        box was opened, depending on which prong of the arrow was chosen). Not all
        children chose the safer option for at least one Two Rating regret trial and one
        Two Rating relief trial, meaning that there were a small number of children who
        could not be included in the analyses; the analysis includes only the 31 6- and
        7-year-olds and 27 8- and 9-year-olds who chose the safer option on at least one
        regret trial and one relief trial in a Two Rating block. The proportions of
        categorical responses (happier, sadder, or the same) given by each age group in
        regret and relief trials are shown in Fig. 3. A two-way analysis of variance
        (ANOVA) with a between-participants factor of age and a within-participants factor
        of trial type (regret or relief) was conducted on the proportion of sadder
        responses. There was a significant effect of trial type, F(1, 56) = 86.61, p <
        .001, ηp2 = .61, with more sadder responses in the regret trials, and a
        significant interaction between age and trial type, F(1, 56) = 8.94, p < .01, ηp2
        = .14. Further analyses (making a Bonferroni correction for 4 tests, α = .0125)
        showed that the effect of trial type was significant for each of the two age
        groups: 6- and 7-year-olds, t(30) = 4.28, p < .01; 8- and 9-year-olds, t(26) =
        9.37, p < .01. However, the proportion of sadder responses in regret trials
        increased with age, t(56) = −2.96, p < .01. A further two-way ANOVA with a
        between-participants factor of age and a within-participants factor of trial type
        was conducted on the proportion of happier responses. The main effect of trial
        type was significant, F(1, 56) = 98.84, p < .001, ηp2 = .64, with more happier
        responses in relief trials than in regret trials, but there were no other
        significant effects. These analyses demonstrate that children’s emotional
        responses varied appropriately between regret and relief trials and that there was
        an increase with age in the likelihood that children reported feeling sadder in
        regret trials. We also examined whether children were more likely than chance to
        report feeling sadder in regret trials and happier in relief trials. Because there
        were three possible choices (sadder, happier, or the same), we compared whether
        proportions of sadder responses in regret trials and happier responses in relief
        trials differed significantly from 0.33 using a one-sample t-test. These analyses
        showed that the older group gave significantly more sadder responses in regret
        trials and happier responses in relief trials than would be expected by chance,
        t(26) = 5.09, p < .001 and t(26) = 6.49, p < .001, respectively; however, although
        the 6- and 7-year-olds gave more happier responses in relief trials than would be
        expected by chance, t(30) = 4.06, p < .001, the proportion of sadder responses in
        regret trials did not differ significantly from chance, t(30) = 0.98, p = .34.
        Note, however, that this group did not respond randomly in regret trials (see Fig.
        3); the younger children produced very few happier responses (unlike in relief
        trials), with most of their responses being either sadder or the same. Taken
        together, these findings suggest unambiguously that the older children experienced
        both regret and relief. However, whereas the younger group experienced relief, the
        younger children did not consistently experience regret.

        <hss>Between-trial analysis of counterfactual emotions</hss>

        In this analysis, children’s initial emotional ratings following partial feedback
        for a specific trial type [taken from Stage (iii) in Two Rating trials] were
        compared with their ratings from an otherwise identical trial type in which they
        made a rating only following complete feedback (taken from One Rating trials). To
        generate categorical data analogous to those used in the within-trial analysis, we
        examined the proportion of trials in which the latter ratings were the same as,
        sadder than, or happier than the former ratings (see Fig. 4). To make the required
        comparisons for analysis, it was necessary to have data from two trials of the
        same type in which children made the safer choice (one where children made an
        emotional rating following partial feedback and one where they made a rating only
        after full feedback) for at least one regret and one relief trial. There were 19
        children from each age group who made a sufficient number of safer choices to
        generate these data. A two-way ANOVA with a between-participants factor of age and
        a within-participants factor of trial type was conducted on the proportion of
        sadder responses. The main effect of trial type was significant, F(1, 36) = 36.67,
        p < .001, ηp2 = .51, as was the interaction between trial type and age group, F(1,
        36) = 7.74, p < .01, ηp2 = .18. Post hoc t-tests (making a Bonferroni correction
        for 4 tests, α = .0125) showed that the effect of trial type was marginally
        significant for the 6- and 7-year-olds, t(18) = 2.04, p = .06, and significant for
        the 8- and 9-year-olds, t(18) = 7.39, p < .01. The effect of age was significant
        for the proportion of regret trials in which children made a sadder rating, t(36)
        = −2.77, p < .01, with older children being more likely to report feeling sadder
        on these trials. A two-way ANOVA with a between-participants factor of age and a
        within-participants factor of trial type was conducted on the proportion of
        happier responses. The main effect of trial type was significant, F(1, 36) =
        17.95, p < .001, ηp2 = .33, as was the main effect of age, F(1, 36) = 5.69, p <
        .03, ηp2 = .14, with younger children being more likely to report feeling happier
        than older children across both trial types. However, the interaction between age
        and trial type was not significant, F < 1. In summary, although these analyses are
        based on an entirely different set of emotional ratings, the findings are very
        similar to those reported for the within-trial analysis in suggesting that both
        age groups experienced regret and relief and an increased likelihood of children
        experiencing regret with age.

        <hss>Additional analyses</hss>

        To check whether the within-trial and between-trial measures differed from each
        other in terms of sensitivity, for each age group we used paired-sample t-tests to
        compare the proportion of sadder responses in regret trials yielded by each
        measure as well as the proportion of happier responses in relief trials yielded by
        each measure. These analyses showed that none of these proportions differed from
        each other (all ps > .30) except for the difference between the proportions of
        happier responses in relief trials for the older children, for whom the within-
        trial measure yielded a significantly higher proportion of happier responses,
        t(18) = 2.36, p < .05. The experimental procedure involved children completing
        different numbers of trials, meaning that children had quite variable exposure to
        different sets of outcomes, which could have affected their responses as they
        moved through the task. Therefore, we conducted a final set of analyses in which
        we focused just on the very first Two Rating regret trial and Two Rating relief
        trial in which children made a safer choice. In the first regret trial on which
        children chose the safer box, 19 of 33 (57.6%) 6- and 7-year-olds and 23 of 31
        (74.2%) 8- and 9-year-olds reported feeling sadder following complete feedback. In
        both of these groups, the probability of children reporting that they now felt
        sadder was significantly greater than chance on a binomial test, both ps < .01,
        assuming that one third of responses will be sadder by chance. In the first relief
        trial where children chose the safer box, 20 of 32 (62.5%) 6- and 7-year-olds and
        23 of 27 (85.2%) 8- and 9-year-olds reported feeling happier following complete
        feedback, in both cases a proportion greater than chance, binomial test, both ps <
        .01.

<hs>  Discussion</hs>
  ~~~~~~~~~~

Children’s initial emotion ratings after partial feedback demonstrated that they felt
sadder if they had received the worse prize from their chosen box than if they had
received the better prize. However, children of both ages were able to flexibly update
this initial emotional response once they had seen the prize in the unchosen box. Analysis
of the within-trial data indicated that children were then likely to subsequently report
feeling sadder if the prize in the unchosen box was better (regret trials) but happier if
the prize in the unchosen box was worse (relief trials). However, although the younger
children did not respond randomly in regret trials (they very rarely gave happier
responses, unlike in relief trials), they did not report feeling sadder significantly more
often than chance (many of the children reported feeling the same). Thus, although this
group did vary their emotional responses across trial types, they did not all consistently
experience regret. The likelihood that children experienced regret increased
developmentally, with older children more reliably reporting feeling sadder in regret
trials. The between-trial comparisons of emotional ratings given in separate trials under
partial or complete feedback also revealed that children’s emotional responses in both
regret and relief trials was sensitive to whether or not children had received full
feedback. However, for this measurement the proportion of sadder responses in regret
trials was only marginally significantly different from that in relief trials for the
younger group, and the likelihood that children would report feeling sadder in regret
trials also increased with age. Thus, the pattern of findings is generally consistent
across both ways of measuring regret and relief. We note, however, that the within-trial
method may be somewhat more sensitive, with the proportion of older children reporting
feeling happier in relief trials being larger under this measure than under the between-
trial measure. The within-trial method also has the advantage of requiring administration
of half the number of trials as the between-trial method, which is very advantageous when
testing young children.

<h>EXPERIMENT 2</h>
------------

The findings of Experiment 1 were primarily based on a comparison between the proportions
of sadder/happier responses on regret trials and those on relief trials. However, these
trials differed not just in terms of whether the prize in the unchosen box was better or
worse than the one in the chosen box; the choices that children needed to make on regret
trials were not completely identical to those that they needed to make on relief trials
(cf. Trials 1 and 2 with Trials 3 and 4). Moreover, the actual prize that children
received from their chosen gamble on regret trials (10 or 11 points) was always better
than the actual prize that children received on relief trials (6 or 4 points). This latter
aspect of the design was deliberate to provide us with a test of whether children could
update their emotion appropriately on seeing the prize in the unchosen box. However, it
might be argued that these differences between regret and relief trials mean that it is
difficult to straightforwardly compare patterns of responses across these two trial types.
In our second experiment, we used a similar task as in Experiment 1 but made three key
changes. First, we added an additional 4 trials to ensure that regret and relief trials
were matched both in terms of the choices children needed to make in each trial type and
in terms of the size of the actual prize obtained. These are listed in Table 1 as Trials
1a to 4a. Second, because the results of Experiment 1 had indicated that there was no
benefit in also including a between-trial measurement of regret/relief, we used only Two
Rating trials, yielding only a within-trial measurement of regret/relief. Third, all
children received the same number of trials to ensure that they were all administered an
identical task.

        <hss>Participants</hss>

        Participants were 38 6- and 7-year-olds (19 girls; M = 79.6 months, range = 72–94)
        and 36 8- and 9-year-olds (17 girls; M = 107.8 months, range = 96–119 months). All
        children were recruited from the same population as in Experiment 1.

        <hss>Apparatus</hss>

        The stimuli used were the same as those used in Experiment 1.

        <hss>Procedure</hss>

        The procedure was very similar to that of Experiment 1, with the addition of
        Trials 1a to 4a in Table 1. The experimental trials were presented in blocks of 4
        Two-Rating trials, with each block consisting of 2 regret trials and 2 relief
        trials. Block 1 consisted of Trials 1, 3, 2a, and 4a, whereas Block 2 consisted of
        Trials 1a, 3a, 2, and 4. All children received the same number of trials in this
        task (the two blocks of 4 trials shown in Table 1). Children were randomly
        assigned to one of 24 possible trial orders, with half receiving a regret trial
        first and half receiving a relief trial first.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

The 6- and 7-year-olds tended to choose the riskier box (M = 4.82, SD = 1.27)
significantly more often than the 8- and 9-year-olds (M = 3.31, SD = 1.33), t(72) = 5.00,
p < .001. As in Experiment 1, only data from trials in which children chose the safer box
were analyzed. We first examined whether children’s initial emotion ratings following
partial feedback differed depending on whether they had received the best prize (Trials 1,
1a, 2, and 2a) or the worst prize (Trials 3, 3a, 4, and 4a) in their chosen box. The
average first emotion rating given in trials where children won the best possible prize
from their chosen box was 6.9 (SD = 0.27) compared with 5.7 (SD = 1.01) in trials where
children won the worst possible prize; children were initially significantly happier in
the former trials, t(68) = 9.13, p < .001. Subsequent analyses focused on the proportion
of times children gave sadder, happier, or the same responses once they had been given
complete feedback. To be included in these analyses, children needed to make the safer
choice in at least one regret trial and one relief trial; here, 29 of the 6- and 7-year-
olds and 34 of the 8- and 9-year-olds were included. Fig. 5 shows the proportion of
sadder, happier, and same responses for each trial type. A two-way ANOVA with a between-
participants factor of age and a within-participants factor of trial type was conducted on
the proportion of times children reported feeling sadder after complete feedback. There
was a main effect of trial type, with more sadder responses given in regret trials than in
relief trials, F(1, 61) = 231.02, p < .001, ηp2 = .79. No other effects were significant.
Because the results of Experiment 1 indicated that the proportion of sadder responses
given by older children was significantly greater than that given by younger children,
planned comparisons examined this age effect. However, although the proportion of sadder
responses in regret trials was larger for the older group, the age effect was not
significant, t(61) = −1.12, p = .27. A further two-way ANOVA with a between-participants
factor of age and a within-participants factor of trial type was conducted on the
proportion of times children reported feeling happier after complete feedback. There was a
main effect of trial type, with more happier responses being given in relief trials than
in regret trials, F(1, 61) = 398.06, p < .001, ηp2 = .87, and no other effects were
significant. Although all children completed the same number of trials in this experiment,
the number of trials used in the analyses to yield the data depicted in Fig. 5 differed
between children because children differed in terms of the number of times they chose the
riskier box (M = 4.08, SD = 1.50, range = 0–8). This might be seen as problematic because
children with a tendency to make riskier choices will produce fewer data points but also
potentially may be less likely to experience regret or relief. To check this, we examined
initially whether there were correlations between the number of times children made a
riskier choice and the proportion of sadder responses in regret trials and between the
number of times children made a riskier choice and the proportion of happier responses in
relief trials. Neither of these correlations approached significance (both ps > .17). We
also reran the ANOVAs described above including number of riskier choices as a covariate
and found a qualitatively identical pattern of findings, with only the main effect of
trial type being significant in both analyses. These analyses indicate that whether or not
children experienced regret or relief was not confounded by the number of riskier choices
they made. We conducted a final set of analyses on the very first regret trial and relief
trial in which children chose the safe option. In their first completed regret trial, 22
of 35 (62.9%) 6- and 7-year-olds and 29 of 35 (82.9%) 8- and 9-year-olds reported feeling
sadder. In both of these groups, the probability of children reporting that they now felt
sadder was significantly greater than chance on a binomial test, both ps < .01. In their
first completed relief trial, 25 of 31 (80.6%) 6- and 7-year-olds and 32 of 35 (91.4%) 8-
and 9-year-olds reported feeling happier, in both cases a higher proportion than would be
expected by chance on a binomial test, both ps < .01. These findings are very similar to
those yielded by the analysis of the full set of trials. In summary, as in Experiment 1,
children were initially sadder (following only partial feedback) if they had received the
worst prize from their chosen box. This suggests that children felt disappointed if their
hope to win the best prize from that box was not realized. In this experiment, we found
that children of both ages showed regret on seeing that the prize they would have won in
the unchosen box was better and showed relief if the alternative prize was worse. In
Experiment 1, we had found somewhat ambiguous evidence that the younger group experienced
regret; although the youngest children were more likely to report feeling sadder on regret
trials than on relief trials, this difference was only marginally significant using the
between-trial measurement, and using the within-trial measurement these children did not
differ from chance in the proportion of times they reported feeling sadder in the former
trials. The best interpretation of those findings was that only some of the younger
children experienced regret. However, in Experiment 2 even the younger group reported
feeling sadder on regret trials 70% of the time. Older children were more likely to feel
regret than younger children (in 81% vs. 70% of regret trials), although unlike in
Experiment 1 this difference did not reach significance. Why might the younger group be
more likely to show regret in Experiment 2 than in Experiment 1? This is a different group
of children, and it is possible that individual differences in ability might explain the
contrasting patterns of results (although there are mixed findings over whether children’s
ability, as assessed using standardized measures, predicts reported regret/relief; see
Burns et al., 2012; McCormack & Feeney, 2015; O’Connor et al., 2014). There are also
notable methodological differences between the experiments that may explain the differing
findings. Experiment 2 included a different set of trials than Experiment 1, and in the
new trials the magnitude of the difference between the obtained reward and the
counterfactual alternative was larger than in the original set of trials (see Table 1;
compare Trials 1 and 2 with Trials 3a and 4a). However, this does not seem to explain the
difference. We compared the percentage of times the younger children reported feeling
sadder in Trials 1 and 2 with the percentage of times they reported feeling sadder in
Trials 3a and 4a and found no difference; the younger children were sadder 70% of the time
in the former trials compared with 72% in the latter trials. Our best guess is that
performance was somewhat better in the second experiment in the younger group because the
experimental procedure was less complex. Children made the same pair of emotion ratings on
every trial, whereas in Experiment 1 they completed both One Rating and Two Rating trials.
Moreover, children always completed the same 8 trials in Experiment 2, but the vast
majority of children completed more than this number of trials in Experiment 1 because of
the need to repeat some trials. We note that our analysis of the first completed regret
trial in Experiment 1 did show that as a group the younger children reported feeling
sadder more often than would be expected by chance, whereas this was not the case for the
full trial set. Thus, we suspect that our younger children may have found the larger set
of trials in Experiment 1 to be onerous.

<h>GENERAL DISCUSSION</h>
------------------

This study was the first to examine regret and relief in younger children using the type
of risky decision-making task used to study these counterfactual emotions in adolescents
and adults. Taken together, the findings of both experiments suggest that children as
young as 6 or 7 years do experience both regret and relief in this sort of task, although
the evidence for regret in this age group was stronger in the second experiment. These
findings are consistent with developmental findings from other studies in which children
make a simpler choice between two colored boxes. The majority of these previous studies
have also found that regret and relief are present from at least 6 or 7 years of age
(Burns et al., 2012; McCormack & Feeney, 2015; O’Connor et al., 2012, 2014; Weisberg &
Beck, 2010, 2012). However, they are not consistent with the findings of Rafetseder and
Perner’s (2012) study, which failed to find evidence of regret in children until 9 years
of age. We discuss our findings in relation to the three methodological issues raised in
the Introduction.

<hs>  Choice and risky decision making</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This study is the first to use a version of the gambling task with children as young as 6
or 7 years to examine counterfactual emotions. Its findings indicate that, like
adolescents and adults, children of this age do experience both regret and relief in
circumstances that involve risky choice. The findings pave the way for using the gambling
task with a broader age range of participants to examine whether there are developmental
changes between childhood and adulthood in the likelihood of experiencing these emotions.
One of the reasons why there has been intense interest in counterfactual emotions in the
gambling task is that researchers have been trying to establish the roles of these
emotions in decision making. Thus, it has been argued that regret and relief may have an
impact on how people make risky decisions and that decision making will be different in
the absence of such emotions (e.g., due to brain damage) (Camille et al., 2004; Coricelli
et al., 2007). This claim is consistent with long-standing suggestions in both economics
(Bell, 1982; Loomes & Sugden, 1982) and psychology (Zeelenberg, 1999; Zeelenberg, Beattie,
van der Pligt, & de Vries, 1996; Zeelenberg & Pieters, 2007) that individuals attempt to
minimize future regret when making decisions. Thus, one important reason for examining the
development of regret within the context of risky decision making would be to explore
whether developmental changes in regret are accompanied by or indeed explain changes in
risky decision making.

<hs>  Single reference point versus multiple reference points</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our findings suggest that at least by the time children are 6 or 7 years old, their
emotions are sensitive to two different reference points. When given partial feedback,
children were less happy if they had won the worst of two prizes in their chosen gamble
than if they had won the best of two prizes. This can be interpreted as disappointment
(Mellers et al., 1999; Zeelenberg, van Dijk, & Manstead, 2000) and suggests that children
hoped to win the better prize. As we have discussed, children’s emotions were also
sensitive to the outcome of the unchosen gamble, as indicated by their emotion ratings
following complete feedback that strongly contrasted with their ratings following partial
feedback. This suggests that any explanation of children’s emotion ratings in this task
just in terms of a simple comparison such as “I do [do not] have the best prize” is
inadequate, whereas such an explanation may be sufficient to explain such ratings
following complete feedback in previous studies with young children. Following a safer
choice, children are already aware, even before partial feedback, that they do not have
the best or worst prize; their subsequent emotion ratings following partial feedback seem
to be sensitive to what they could have won given their choice and, following complete
feedback, sensitive to what they would have won had they chosen differently. Does this
mean that we can rule out an explanation of children’s emotions in terms of simple
frustration rather than regret or relief (see Rafetseder & Perner, 2012; Rafetseder &
Perner, 2014)? We are assuming that this question remains open even under circumstances in
which participants have full responsibility for the choice that led to the outcome and
full feedback has been given (see O’Connor, McCormack, Beck, & Feeney, 2015). Certainly,
any explanation of children’s emotions in terms of frustration needs to be more complex
than assuming a simple comparison between the prize obtained and the best or worst prize
available; it would need to assume that this frustration can mutate within a single trial
following complete feedback (from frustration to happiness in relief trials or from
happiness to frustration in regret trials). One might argue that all that needs to happen
is for children to systematically change the reference point by which they make their
judgment regarding whether they have the best (or worst) prize and that this need not
involve thinking counterfactually about their choices. We note, however, that children’s
judgments following complete feedback do seem to be sensitive not just to whether or not a
better (or worse) prize was available but also to whether children would have won that
prize had they chosen differently. That is, they made the comparison not between their
actual prize and the possible contents of the unchosen gamble but rather between their
actual prize and the specific outcome they would have obtained had they chosen the other
gamble. Although we cannot definitely rule out the possibility that children make these
comparisons without thinking counterfactually, we note that neuropsychological evidence
suggests that the regions of the brain that seem to be important for being sensitive to
complete feedback in this sort of gambling task also seem to be important for
counterfactual thinking (Barbey, Krueger, & Grafman, 2009; but see Van Hoeck et al.,
2013).

<hs>  Within-trial versus between-trial comparisons of emotion ratings</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As described in the Introduction, Rafetseder and Perner (2012), Rafetseder and Perner
(2014) argued that a between-trial method is the most appropriate one to measure regret,
whereas all of the other studies with young children have used only a within-trial method.
We directly compared both of these methods in Experiment 1 in the current study to examine
whether they showed different developmental patterns. For both the within-trial and
between-trial measures, the developmental patterns were very similar, and under either
method there was some evidence of a developmental increase in the likelihood that
participants experienced regret but no evidence of developmental changes in relief. Our
findings suggest that Rafetseder and Perner’s pattern of developmental findings cannot be
explained simply in terms of their use of a between-trial method for assessing regret. Of
course, although the basic comparison we made in our between-trial method was in essence
the same as that made in Rafetseder and Perner’s between-trial method (i.e., a comparison
of emotion ratings following either partial or complete feedback on separate trials), our
task differed from that of Rafetseder and Perner considerably, with the latter involving a
simple box-choosing task. These differences included not just the types of choice children
needed to make but also the number of trials, the nature of the emotion scale used, the
rewards involved, and so on. However, it is hard to see why these differences would make
it more likely, rather than less likely, that we would observe counterfactual emotions in
younger children; moreover, we note that in their own study, Rafetseder and Perner found
no consistent evidence of regret in children under 9 years of age even using a within-
trial method. The main reason for comparing the between-trial and within-trial methods was
to inform future studies of the development of counterfactual emotions. Although both of
these methods yielded broadly similar results, the within-trial method requires
administration of fewer trials and also seems to yield a somewhat clearer pattern of
findings. In Experiment 1, we found that the difference in the proportion of sadder
responses given in regret trials versus relief trials was only marginally significant for
the younger children in the between-trial method and that evidence for relief in the older
group was significantly stronger using the within-trial method. One possible explanation
of the clearer pattern of findings using the within-trial method may lie in the fact that
in Two Rating trials we explicitly asked participants to make a comparative rating, that
is, to report whether they felt the same as, happier than, or sadder than before they had
received complete feedback. This may have encouraged participants to proactively compare
the actual outcome with the counterfactual outcome. Moreover, these comparisons did not
hinge on the sensitivity of the scale used to report emotions because we used the three-
pronged arrow method of describing relative emotions (see also O’Connor et al., 2012;
O’Connor et al., 2014; Weisberg & Beck, 2012). By contrast, between-trial comparisons
involved comparing separate ratings on the same 7-point scale, and whether such
comparisons differ will depend on the sensitivity of this scale. Our findings suggest that
future developmental studies should use the within-trial method, at least for this type of
task.

<h>CONCLUSION</h>
----------

This study has demonstrated that children as young as 6 or 7 years do experience
counterfactual emotions in the context of risky decision making; as such, it may pave the
way for future studies that examine whether these emotions have an impact on children’s
decision making. Such studies are important because existing accounts of developmental
changes in children’s decision making (for reviews, see Dhami, Schlottmann, & Waldmann,
2013; Jacobs & Klaczynski, 2005) have typically not considered how counterfactual thinking
and its emotional consequences have an impact on children’s decisions, whereas it is
widely argued that counterfactual cognition and its associated emotions play an important
role in adult decision making (Connolly & Zeelenberg, 2002; Coricelli et al., 2007; Roese,
1999).


<h>REFERENCES</h>
----------

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<ART>The development of the size–weight illusion in children coincides with the development of nonverbal cognition rather than motor skills
================================================================================

Authors: Philippe A. Chouinard, Kezia G. Matheson, Kayla A. Royals, Oriane Landry, Gavin Buckingham, Elizabeth J. Saccone, Darren R. Hocking
DOI: 10.1016/j.jecp.2019.03.006
Year: 2019  |  Pages: 48-64
ASJC codes: 3204, 3205
Keywords: Child development, Expectancies, Perception, Reasoning, Sensorimotor integration, Size–weight illusion

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We examined how the strength of the size–weight illusion develops with age in typically developing children. To this end, we recruited children aged 5–12 years and quantified the degree to which they experienced the illusion. We hypothesized that the strength of the illusion would increase with age. The results supported this hypothesis. We also measured abilities in manual dexterity, receptive language, and abstract reasoning to determine whether changes in illusion strength were associated with these factors. Manual dexterity and receptive language did not correlate with illusion strength. Conversely, illusion strength and abstract reasoning were tightly coupled with each other. Multiple regression further revealed that age, manual dexterity, and receptive language did not contribute more to the variance in illusion strength beyond children's abilities in abstract reasoning. Taken together, the effects of age on the size–weight illusion appear to be explained by the development of nonverbal cognition. These findings not only inform the literature on child development but also have implications for theoretical explanations on the size–weight illusion. We suggest that the illusion has a strong acquired component to it and that it is strengthened by children's reasoning skills and perhaps an understanding of the world that develops with age.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The size–weight illusion refers to the perceptual experience of object weight that occurs
when a person lifts equally weighted objects that differ in size (Charpentier, 1886,
1891). Namely, smaller objects typically feel heavier than larger objects of the same
mass. Although the illusion has been studied for more than 100 years, its precise
mechanisms are not completely understood and have yet to be explained satisfactorily. Over
the years, researchers have proposed a number of different theoretical explanations for
the illusion (Buckingham, 2014; Dijker, 2014; Saccone & Chouinard, 2019). According to
sensorimotor explanations, the illusion is driven by the misapplication of fingertip
forces during lifting (Dijker, 2014). When lifting two objects that weigh the same, people
apply more force for the larger object than they do for the smaller one, which causes too
much lift for the former and too little for the latter. According to these explanations,
too much lift will make the object feel lighter, whereas too little lift will make the
object feel heavier. However, Flanagan and Beltzner (2000) demonstrated how the motor
system quickly learns to apply the correct amount of force for each object after only a
few trials, whereas the perception of differences in weight remains the same in magnitude
across many trials. This dissociation has been replicated several times (Buckingham &
Goodale, 2010a, 2010b; Chouinard, Large, Chang, & Goodale, 2009; Grandy & Westwood, 2006),
which undermines the necessity of the underlying mechanisms proposed by sensorimotor
theories. Alternatively, other theories offer more top-down explanations, whereby the
illusion arises from the brain comparing prior experiences and current sensory input,
which in turn influences weight perception. Bayesian explanations, which have grown in
popularity during recent years to comprehensively explain many forms of perception, posit
that perceptual experiences are the result of an active process of formulating and testing
hypotheses about the world. It then follows that experiences, or priors, are important in
shaping perception (Geisler & Kersten, 2002; Gregory, 1980; Helmholtz, 1867). If one
applies these principles to weight perception, then the perceived heaviness of an object
should be influenced by any associations that we have developed over time between weight
and other physical properties of objects. For example, small objects are usually lighter
in the real world. According to Bayesian explanations, one should expect the smaller
object in the size–weight illusion to weigh less, which consequently should make that
object feel lighter during lifting. However, the reverse is experienced in the size–weight
illusion, which is why the illusion is sometimes called an anti-Bayesian illusion
(Brayanov & Smith, 2010). Nevertheless, as Peters, Ma, and Shams (2016) demonstrated
through mathematical modeling, and discussed further by Saccone and Chouinard (2019), the
size–weight illusion fits perfectly well within a Bayesian framework if one considers that
the perceived heaviness of objects might be driven by expected density as opposed to size
(Chouinard et al., 2009; Harshfield & DeHardt, 1970; Peters et al., 2016; Ross & Gregory,
1970). Manipulable man-made objects tend to be denser as they get smaller, and people
consequently tend to estimate their weight according to this relationship (Peters, Balzer,
& Shams, 2015). Thus, in the context of the size–weight illusion, the smaller and denser
object affords more weight, which causes that object to feel heavier. If priors are indeed
important for the size–weight illusion, then one might expect to find increases in the
strength of the illusion during child development. It is conceivable that an adult with
years of experience in lifting objects would have a more expansive and deep-seated
repertoire of priors about their affordances and would use these priors for the purposes
of perception with greater efficiency and influence than a young child whose motor skills
are still developing and who has lifted fewer objects. Binet (1895) and Piaget (1969,
1999) proposed that illusions, such as the size–weight illusion, offered opportunities to
understand typical development and tease apart perceptual mechanisms that might be innate
from those that are acquired. Their arguments stem from their own research demonstrating
how the strength of illusions can either decrease or increase with age depending on the
illusion (Binet, 1895; Piaget, 1969, 1999). Namely, they argued that innate illusions
decrease in strength as children age, whereas the strength of acquired illusions increases
with age (Binet, 1895; Piaget, 1969, 1999). The Müller–Lyer illusion is an example of an
innate illusion that decreases in strength with age. This was first demonstrated by Binet
(1895) and has since been replicated several times (Brosvic, Dihoff, & Fama, 2002;
Frederickson & Geurin, 1973; Hanley & Zerbolio, 1965; Pollack, 1970; Porac & Coren, 1981),
but not always (Rival, Olivier, Ceyte, & Ferrel, 2003). Binet (1895) posited that it can
be maladaptive to falsely perceive something differently than what it truly is and that
children learn to suppress these forms of misperception, but only as cognitive faculties
and an understanding of the world develop. Another possibility is that the perceptual
system in younger children might exaggerate illusions as a way to compensate for not being
able to account for sensory noise as effectively as more developed systems in older
children (Duffy, Huttenlocher, & Crawford, 2006). More recently, Gandhi, Kalia, Ganesh,
and Sinha (2015) demonstrated how children who gain sight for the first time after the
surgical removal of congenital cataracts can see the Müller–Lyer illusion immediately
after surgery. These reports on the Müller–Lyer illusion are difficult to explain within a
Bayesian framework and call into question the necessity of priors. If experience were
truly essential for perceiving the Müller–Lyer illusion, then the illusion would not be
strongest during early childhood and the children in Gandhi et al.’s study would not
experience the illusion immediately after gaining sight for the first time. Regarding the
size–weight illusion, there is little research on the cognitive and sensorimotor
explanations of the illusion in typically developing children. Table 1 provides a summary
of all articles written in the English and French languages to date. Both the methods and
results of these investigations are mixed. Consequently, the developmental profile for the
illusion remains unresolved. Some studies demonstrate that the illusion is weaker in
younger children and strengthens as children grow older (Philippe & Clavière, 1895; Rey,
1930), whereas others show the reverse findings whereby the strength of the illusion
decreases with age (Robinson, 1964). The studies range in procedures from quickly
administered perceptual ranking of stimuli (Dresslar, 1894; Flournoy, 1894; Philippe &
Clavière, 1895) to lengthy testing sessions using the methods of constant stimuli (Pick &
Pick, 1967; Rey, 1930; Robinson, 1964). Many of the earlier studies did not perform
statistical analyses and failed to consider other factors that may have influenced their
results such as manual dexterity and cognitive ability. Given the variability in
procedures and the number of extraneous variables not considered, it is perhaps not
surprising that this literature is contradictory and, therefore, warrants further
investigation using modern-day methods and standards, which are far more rigorous.
Currently, little is known about how the size–weight illusion might develop with age when
other variables, such as motor and cognitive skills, are considered. Although there is
evidence suggesting that the illusion might have a strong innate bottom-up component to it
(Saccone & Chouinard, 2019), conceptual knowledge can nonetheless also influence weight
illusions in a top-down manner (Buckingham, 2014; Saccone & Chouinard, 2019), as evidenced
by the material–weight illusion in which objects that appear to be metallic feel lighter
than objects that appear to be made of Styrofoam of the same size and mass (Buckingham,
Cant, & Goodale, 2009; Seashore, 1898). Logically, conceptual knowledge can be obtained
only when cognitive faculties are sufficiently developed to understand new experiences.
Conceivably, a certain amount of manual dexterity is also required when forming an
association between an object’s weight and its features because manual dexterity is
necessary for gauging weight (Jones, 1986). Manual skills emerge during early infancy and
continue to develop into adolescence (Mathiowetz, Federman, & Wiemer, 1985). For preschool
children, manual dexterity improves as they learn to cut with scissors and to trace and
copy lines and shapes. In primary school, children continue to improve their manual skills
with handwriting and the use of computers. More experiences are acquired as these skills
develop. Children’s repertoire of priors consequently becomes richer and more fine-tuned.
Thus, in theory, previous experiences with objects can only begin to influence how
children perceive their weight when cognitive and motor skills reach certain levels of
proficiency. These are not new ideas. Piaget (1969, 1999) reasoned that children must
first understand size and weight, be able to integrate the two collectively, and know that
larger objects typically weigh more than smaller ones before children can experience the
size–weight illusion. In line with this thinking, we hypothesized that illusion strength
increases as children develop their manual and cognitive skills. Our findings demonstrate
that the size–weight illusion increases in strength as children grow older and that the
development of nonverbal cognition, but not motor or language skills, explains variability
in the development of the size–weight illusion.

<hs>  Overview</hs>
  ~~~~~~~~

Children from primary schools from a regional center (Bendigo) and a major city
(Melbourne) in Victoria, Australia, completed tasks that assessed susceptibility to the
size–weight illusion, manual skills, receptive language, and abstract reasoning. Task
order was counterbalanced across participants to reduce practice or carryover effects.
Testing occurred over two or three sessions, lasting no more than 30 min each. All
procedures were approved by the La Trobe University human ethics committee, the Department
of Education and Training of Victoria, Catholic Education Melbourne, and the local
schools. Legal guardians of all participants provided informed written consent and
confirmed that their children were never diagnosed with a psychological, psychiatric,
neurological, or neurodevelopmental disorder by a questionnaire prior to testing. Testing
was administered at the children’s school in cooperation with classroom teachers to
minimize disruption.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 85 typically developing children participated in the study. Of these
participants, 2 boys and 5 girls were excluded from the analyses based on having a
standard score lower than 70 on either the Peabody Picture Vocabulary Test or the Raven’s
Progressive Matrices (see below for more information about these tests), which is
suggestive of an intellectual disability. An additional 3 boys and 3 girls were excluded
from the analyses based on having an illusion strength index (see below on how this was
calculated) exceeding ±2 standard deviations. Removing these participants in this manner
helped to systematically and objectively remove noise from the data that would otherwise
reflect various aspects of misunderstanding, noncompliance, or atypical development. This
resulted in a final sample size of 72 participants (39 boys; 64 right-handers; mean age =
8.9 years, range = 5.6–12.5). Age was determined from the date of birth provided by
parents on a form filled out prior to the children’s participation, which was confirmed by
the children during testing.

        <hss>Size–weight illusion</hss>

        The task objects consisted of four plastic spheres created with a three-
        dimensional printer. We adjusted the weight of each plastic sphere by placing a
        ballast of lead pellets inside it. The ballast was held in place with compact foam
        to ensure that the center of mass corresponded to the sphere’s center. There were
        two pairs of objects (Fig. 1). The first pair consisted of two spheres weighing
        120 g. One sphere had a diameter of 6 cm (volume = 113.10 cm3, density = 1.06
        g/cm3) and was painted yellow (luminance = 62.2 cd/m2), whereas the other one had
        a diameter of 9 cm (volume = 381.69 cm3, density = 0.31 g/cm3) and was painted red
        (luminance = 8.2 cd/m2). The second pair consisted of two spheres weighing 405 g.
        One sphere had a diameter of 6 cm (volume = 113.10 cm3, density = 3.58 g/cm3) and
        was painted blue (luminance = 7.6 cd/m2), whereas the other one had a diameter of
        9 cm (volume = 381.69 cm3, density = 1.06 g/cm3) and was painted green (luminance
        = 7.3 cd/m2). We also constructed a sliding measurement apparatus to allow
        participants to give a nonverbal magnitude estimate of the weight for each sphere
        (Fig. 1). This apparatus consisted of four sliders that were 30 cm in length. Each
        one was painted a different color corresponding to one of the spheres. Seated
        opposite the participant at a table, the experimenter gave the following
        instructions: “I’m going to hand you these colored balls. I want you to tell me
        how heavy they are using the sliding rings in front of you. If this side
        [indicating the participant’s left] means light and this side [indicating the
        participant’s right] means heavy, slide the ring and leave it wherever you think
        it should go.” These instructions were elaborated if needed, and the experimenter
        ensured that the participant understood the instructions before proceeding. The
        participant was then asked to extend his or her hands facing upward with the
        elbows elevated above the table. The experimenter then placed one object from one
        of the two pairs in each hand for the participant to weigh (e.g., the yellow
        sphere in the left hand and the red sphere in the right hand). The participant was
        given as much time as needed to assess the objects’ weights. Afterward, the
        participant was asked to use the color-coded sliders to indicate the perceived
        weight of each sphere, and the experimenter recorded the final measurements in
        millimeters. This was repeated for the next pair of objects (e.g., the blue sphere
        in the left hand and the green sphere in the right hand). These procedures were
        repeated with the objects placed in the opposite hands. The average position of
        the slider in millimeters for the two presentations of each object was taken as a
        measurement of its apparent weight. The order of presentation was counterbalanced
        across participants.

        <hss>Purdue pegboard test</hss>

        We also administered the Purdue Pegboard Test to assess manual dexterity (Tiffin &
        Asher, 1948). The test consisted of the participant manually inserting pegs into
        columns of small holes one at a time for 30 s with the participant’s preferred
        hand. The total number of pegs placed inside a hole was taken as the score. Hand
        preference was determined by the child’s self-report when asked whether he or she
        was right- or left-handed.

        <hss>Peabody Picture Vocabulary Test</hss>

        We measured receptive language with the Peabody Picture Vocabulary Test–Fourth
        Edition (PPVT; Dunn & Dunn, 2007). The child was presented with a series of pages
        containing four pictures and was asked to indicate which picture he or she thought
        best described the item word spoken by the administrator. The complete test
        consists of 228 trials. However, the number of trials administered to each child
        was determined by basal and ceiling rules in accordance with instructions from the
        test manual (Dunn & Dunn, 2007). Raw scores reported in our study reflect the
        total number of correct trials plus credit for all trials not administered below
        the basal start point. Standard scores were also calculated based on normative
        data obtained from the test manual to characterize verbal intelligence in our
        overall sample and across our age groups.

        <hss>Raven’s progressive matrices</hss>

        The Raven’s Progressive Matrices (RPM; Raven, Raven, & Court, 2003) is a nonverbal
        measure of general cognitive ability. The child was provided with a booklet of
        different patterns with a piece missing in each pattern. For each item, the child
        was required to select which piece from an array of different options best matched
        the missing piece. We administered two versions of the RPM, each designed for a
        different age group. The colored version was administered to children aged 5–9
        years and consisted of 36 trials, whereas the standard version was used for the
        older participants and consisted of 60 trials. Raw scores reflected the number of
        trials that the participant got correct. For the purposes of data analysis and
        reporting, all raw scores on the colored form were converted to the scale of the
        standard form using the conversion table provided in the RPM manual (Raven et al.,
        2003). Standard scores were also calculated based on normative data obtained from
        the test manual to characterize nonverbal intelligence in our overall sample and
        across our age groups.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

We carried out statistical analyses using GraphPad Prism–Version 7 (GraphPad, La Jolla,
CA, USA), JASP software–Version 0.8 (University of Amsterdam, Amsterdam, Netherlands), and
SPSS–Version 23 (IBM, Armonk, NY, USA). Before proceeding to any statistics, we first
calculated a score of illusion strength from the magnitude estimates in the following
manner: [(perceived weight of the small object − perceived weight of the large
object)/(perceived weight of the small object + perceived weight of the large object)]. An
overall score of illusion strength for the two pairs of objects was calculated by taking
their average.1 This method of normalizing is used in many illusion studies (Chouinard,
Noulty, Sperandio, & Landry, 2013; Chouinard, Peel, & Landry, 2017; Chouinard, Royals,
Sperandio, & Landry, 2018; Chouinard, Unwin, Landry, & Sperandio, 2016; Schwarzkopf, Song,
& Rees, 2011; Sherman & Chouinard, 2016) and allows for meaningful comparisons across
studies. We used two approaches to analyze the data. The first consisted of comparing
means between different age groups. To this end, we first divided our participants into
quartile age groups. The quartile split ensured that a sufficient number of participants
(n = 18) were evenly distributed in each group. Age Group 1 ranged from 5.6 to 6.9 years,
Age Group 2 ranged from 7.0 to 9.3 years, Age Group 3 ranged from 9.3 to 10.8 years, and
Age Group 4 ranged from 10.8 to 12.5 years. We then performed an analysis of variance
(ANOVA) with age as a between-subject factor on illusion strength and the raw scores on
the Purdue Pegboard Test, PPVT, and RPM. Raw scores were chosen for the three latter tests
so that we could chart how these skills develop with age. Post hoc pairwise comparisons
using Tukey’s honest significance difference (HSD) tests (Tukey, 1949), which corrected
for multiple comparisons, were performed to test for differences between the various age
groups when a main effect of age was obtained. We also performed one-sample t tests to
determine whether or not the illusion strength index in each age group differed from zero,
which provides an indication as to when the illusion might emerge during development. To
account for multiple comparisons against zero, we applied a Bonferroni correction to the
reported p values (i.e., pcorr = puncorr × number of tests comparing differences against
zero). The second approach consisted of performing bivariate correlations and a forward
selection multiple regression. Specifically, a correlation matrix of Pearson r
coefficients was produced to assess for associations among age, illusion strength, the
Purdue Pegboard Test scores, the raw PPVT scores, and the raw RPM scores. Again, raw
scores were chosen on the three latter tests so that we could chart how these skills
develop with age. To account for multiple correlations, we applied a Bonferroni correction
to the reported p values (i.e.. pcorr = puncorr × number of bivariate correlations
performed). The model for the forward selection multiple regression began with an empty
equation. Age, the Purdue Pegboard Test scores, the raw PPVT scores, and the raw RPM
scores were added to the model one at a time beginning with the one with the highest
correlation with illusion strength until the model could no longer be improved. Given that
we had no prior predictions on how to model the regression, this type of regression was
favored over others for its exploratory and unbiased nature for determining which
predictors should be entered into the model and are most important for explaining illusion
strength. Participants with missing values were excluded from the analysis. The resulting
standardized beta coefficients (β) and corrected p values arising from the multiple
regression analysis are reported. All reported p values were corrected for multiple
comparisons based on an alpha level of .05 unless specified otherwise.

<hs>  Comparison of age groups on illusion strength as well as on motor and cognitive abilities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In summary, ANOVA demonstrated increases in illusion strength, manual dexterity, receptive
language, and abstract reasoning with increasing age.

<hs>  Bivariate correlations and multiple regression</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 4 provides a correlation matrix of Pearson r coefficients among chronological age,
manual dexterity, receptive language, abstract reasoning, and illusion strength. Age,
manual dexterity, receptive language, and abstract reasoning were highly intercorrelated
with each other (all rs ≥ .44, p ≤ .001). Illusion strength increased as a function of
age, r(70) = .34, p = .034 (Fig. 3A) and abilities in abstract reasoning, r(69) = .33, p =
.046 (Fig. 3B). In contrast, illusion strength was not correlated with either manual
dexterity, r(70) = .13, p = 1.00, or abilities in receptive language, r(70) = .27, p =
.217. To establish the importance of these different variables in predicting illusion
strength, a forward selection approach was used in a multiple regression. In this
analysis, age, manual dexterity, receptive language, and abstract reasoning were selected
as predictors for entry. The first step, which included abstract reasoning as the
predictor, was significant, F(1, 68) = 7.72, p = .007, and explained 10.2% of the variance
in illusion strength. The standardized beta coefficient for abstract reasoning was
significant (β = 0.32, p = .007). The forward selection analysis did not add age, manual
dexterity, or receptive language as additional predictors, indicating that none of them
significantly explained more variance in illusion strength beyond what was already shared
with abstract reasoning.

<h>DISCUSSION</h>
----------

We sought to characterize the development of the size–weight illusion in typically
developing children and determine the contribution of manual dexterity, receptive
language, and abstract reasoning underlying these changes. As hypothesized, the strength
of the illusion increased with age. Manual dexterity and receptive language did not
correlate with illusion strength. Conversely, illusion strength and abstract reasoning
were tightly coupled. The multiple regression revealed that age, manual dexterity, and
receptive language did not contribute significantly more than the 10.2% of variance in
illusion strength already explained by abstract reasoning. Taken together, the effects of
age on the size–weight illusion appear to be explained by nonverbal cognition. In the
ensuing discussion, we outline how this study contributes to our understanding of the
size–weight illusion and how our findings should be interpreted within the context of
previous research that has characterized the development of the size–weight illusion in
children.

<hs>  Factors contributing to the size–weight illusion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Illusion strength increased with abstract reasoning skills as measured by the raw scores
on the RPM. Conversely, illusion strength did not change with manual dexterity as measured
with the Purdue Pegboard Test, nor did it change with language skills as measured with the
PPVT. These findings provide clues about the mechanisms underlying the size–weight
illusion. In particular, our findings underscore the importance of cognitive processing
and are in line with Piaget’s ideas that certain cognitive faculties need to be developed
before a child can experience the size–weight illusion to its fullest (Piaget, 1969,
1999). Namely, the illusion increases in strength as reasoning skills also increase.
Reasoning skills are conceivably important for conceptually understanding size, weight,
and how the two are distinct and typically associated with each other (Piaget, 1969,
1999). Future research can verify this by testing children’s understanding of size and
weight and correlating this with illusion strength. Previous research demonstrates that
children begin to conceptually understand size at 3 years of age (Smith, 1984) and weight
at 5 years of age (Cheeseman, McDonough, & Clarke, 2011). If Piaget’s (1969, 1999) theory
is correct, then forming associations between size and weight must proceed these stages.
Only then can associations be reinforced to exert an influence on the illusion. In line
with this thinking, the ordinary rectangle is perceived as an illusion in adults (Ganel &
Goodale, 2003) but not in children aged 4 and 5 years (Hadad, 2018). In adults, the
apparent width of the ordinary rectangle is contingent on its length. Longer rectangles
are perceived as more narrow than shorter rectangles with the same width. Hadad (2018)
examined the developmental profile of this illusion in children aged 4–8 years. The 4- and
5-year-olds could not see the illusion, whereas the 7- and 8-year-olds could. From these
results, Hadad concluded that children can begin to perceive the ordinary rectangle as an
illusion only after they gain the ability to process and combine width and length
information. The lack of correlation between the PPVT and illusion strength is also
revealing for two reasons. First, the PPVT measures receptive vocabulary, which is the
ability to comprehend language. Hence, comprehension of task instructions cannot explain
illusion strength in the overall sample. Second, the lack of a correlation suggests that
the mechanisms underlying the size–weight illusion do not depend on language processing.
This is not a particularly contentious finding. We are unaware of any size–weight illusion
explanation that is centered on language processing. The lack of correlation between
manual dexterity and illusion strength is also informative because it sheds light on the
merits of sensorimotor explanations for the size–weight illusion (Dijker, 2014). It is
conceivable that age-related improvements in manual dexterity are accompanied by more
accurate and precise somatosensory information regarding the size and weight of objects.
Yet our results reveal that more refined motor skills, and the possibility of more
veridical size and weight information obtained by somatosensory channels, did not
translate into a stronger illusion in the overall sample, nor did it explain age-related
changes in illusion strength. These findings add to the growing evidence demonstrating a
dissociation between how one handles objects motorically and their perceived weight
(Buckingham & Goodale, 2010a, 2010b; Buckingham, Ranger, & Goodale, 2012; Chouinard et
al., 2009; Flanagan & Beltzner, 2000; Grandy & Westwood, 2006). Nonetheless, sensorimotor
explanations should not be discarded entirely (Saccone & Chouinard, 2019). The development
of rudimentary motor abilities is likely to be an important precursor to the development
of the size–weight illusion. Only by manually handling objects can one reinforce
associations between size and weight, which can then strengthen the illusion. Further
investigation in younger children on the size–weight illusion would be needed to test this
explanation.

<hs>  Earlier research on the development of the size–weight illusion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The examination of the size–weight illusion in children emerged during the 1890s
(Dresslar, 1894; Flournoy, 1894; Gilbert, 1894; Philippe & Clavière, 1895). This
pioneering work seemed to be geared toward determining whether the size–weight illusion
first described by Charpentier (1886, 1891) was innate or acquired and develops with age,
and also whether the task could be used as an index of intelligence that could
differentiate typically developing children from delayed or disabled children. These
earlier studies used either a matching paradigm (i.e., the children needed to indicate
which stimulus from an array of comparison stimuli weighed the same as the standard
stimulus) or a rank-ordering paradigm (i.e., the children were given an array of stimuli
and needed to order them according to their apparent weight) (Table 1). The results from
these early studies converge well with our findings in that they also demonstrate that the
size–weight illusion is weaker in younger children. Philippe and Clavière (1895) tested
children aged 3–7 years and found that the majority of them did not experience the
illusion. The other studies tested older children from 6 years of age and found that the
illusion was present in either all or the vast majority of the participants (Dresslar,
1894; Flournoy, 1894; Gilbert, 1894). Using a method of constant stimuli paradigm, Rey
(1930) later confirmed these trends, with children aged 5 and 6 years being less
susceptible to the illusion than children aged 7–14 years. Two other studies later emerged
during the 1960s (Pick & Pick, 1967; Robinson, 1964). Neither converges with the earlier
findings and with the findings obtained in our investigation. The first of these was by
Robinson (1964). The study was influenced by behaviorism (Skinner, 1953), which featured
prominently in psychological research at the time. Being concerned that the younger
participants might not understand the concept of weight, Robinson (1964) introduced an
intensive reinforcement training phase before testing them on the illusion. Namely,
children as young as 2 years were trained by reinforcement to indicate which of two
objects differing in mass was heaviest. The participants received a food reward whenever
they got the answer correct. The introduction of this kind of reinforcement training
likely influenced the outcome of the testing phase in which the author examined the
magnitude of the size–weight illusion using a method of constant stimuli paradigm. The
youngest children required more reinforcement training to reach the learning criterion
than the older children, which could have magnified their subjective reports during the
testing phase to please the experimenter. Perhaps for this reason, contrary to all earlier
work, as well as the current investigation, Robinson demonstrated that the strength of the
illusion decreased with age. The second study was by Pick and Pick (1967). The authors
performed a series of experiments to characterize how the strength of the illusion
increased with age in children aged 6–16 years when haptic, vision, or both types of cues
specifying object size were available to the participants. The participants hefted the
objects wearing a blindfold in the haptic-only condition, lifted the objects using strings
in the visual-only condition, and hefted objects without a blindfold in the haptic and
visual condition. The study yielded some interesting dissociations. The authors
demonstrated that illusion strength (a) was the same for all ages when both haptic
information and visual information were provided, (b) increased with age when only haptic
information was provided, and (c) decreased with age when only visual information was
provided. We view these results with some skepticism. It is unclear as to why the
direction of change with age would depend on the sensory modality of available cues. Pick
and Pick did not offer any explanation. In addition, this dissociation has not been
described further since it was first reported by the authors more than 50 years ago. There
is the possibility that the effect of age in the visual-only condition differed in its
direction because of differences in the manner in which the participants lifted the
objects as opposed to the manner in which object size was presented to them. We know of
only one other study of the size–weight illusion in children that was performed since the
1960s. This study was performed by Kloos and Amazeen (2002) in preschool children aged 3–5
years. The study’s paradigm was simple (Table 1) and arguably more conducive to testing
very young children than the paradigm used in our study. In short, the children were shown
a picture of a mouse holding a block of cheese at the bottom of a steep hill while they
held a task object representing the cheese in one hand. With the other hand, the children
pointed to a position on the hill to indicate where the mouse might take a break if it
needed to walk up the hill, which served as an index of the children’s perceived weight of
the object they were holding. Using this paradigm, the authors demonstrated that
preschoolers perceive the size–weight illusion. The effects of age were not investigated
given the small age range tested. Kloos and Amazeen could have perhaps also demonstrated
increases in illusion strength had they included older children in their sample.
Nonetheless, their results are important. They suggest that the size–weight illusion might
not be completely acquired with experience but that the illusion is present from early
development. Our study further reveals that the illusion is reinforced by cognitive
development, which we speculate is required for the acquisition of priors and their
influence on perception.

<hs>  Methodological considerations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The study demonstrates that the size–weight illusion has a strong acquired component to it
given that the age-related changes were linked to cognitive development. However, one
should not consider the absence of an illusion in the youngest age group as evidence that
the size–weight illusion is completely acquired. It may still have an innate element to
it. After all, Kloos and Amazeen (2002) demonstrated that the illusion is present in
children younger than those we tested. A simpler and perhaps more engaging task, like the
one used by Kloos and Amazeen, could have increased this study’s sensitivity for detecting
size–weight illusion effects in younger children. Another consideration is that the task
objects had different colors and did not match in luminance (Fig. 1). We painted the
spheres different colors to make them more interesting for the children and to help
facilitate the matching of each one to a slider. Previous research has demonstrated that
the luminance of objects can have a small effect on their perceived weight. Specifically,
lighter objects feel heavier (De Camp, 1917; Walker, Francis, & Walker, 2010). This effect
could have contributed to a stronger weight illusion in the red–yellow pair, which had a
considerable luminance difference of 53.8 cd/m2, than in the blue–green pair, which had a
negligible luminance difference of 0.3 cd/m2. Color can also influence the perceived size
(Tedford, Bergquist, & Flynn, 1977; Walker et al., 2010) and weight (De Camp, 1917; Walker
et al., 2010) of objects. However, these effects disappear when luminance is matched
between objects (Walker et al., 2010), which is perhaps why color does not always
influence the perceived weight of objects (Buckingham, Goodale, White, & Westwood, 2016;
De Camp, 1917). Although we cannot discard the possibility that the luminance differences
between the red and yellow spheres contributed to the weight illusion in this pair of
objects, the effects of color (driven by luminance differences) on perceived weight is
generally regarded as much weaker than those exerted by size (Buckingham, 2014; Saccone &
Chouinard, 2019; Walker et al., 2010). In addition, one should consider that the Purdue
Pegboard Test measures only fine finger dexterity and does not measure other aspects of
manual performance such as applied forces and gross movements. The Purdue Pegboard Test
was chosen over other tests because it is quick to administer and continues to be the most
widely used clinical test for assessing manual dexterity after 70 years of existence
(Yancosek & Howell, 2009). Its reliability and validity are excellent and are understood
better than any other dexterity assessment (Yancosek & Howell, 2009). Future work could
examine the application of fingertip forces, as is the case in many studies of the
size–weight illusion in adults (Buckingham & Goodale, 2010a; Chouinard et al., 2009;
Flanagan & Beltzner, 2000; Grandy & Westwood, 2006). To our knowledge, the recording of
fingertip forces has never been performed in children experiencing the size–weight
illusion.

<hs>  Closing remarks</hs>
  ~~~~~~~~~~~~~~~

The current study provides a novel investigation into the development of the size–weight
illusion in primary school-aged children by considering a number of factors not considered
in previous studies. We conclude that the development of the illusion coincides with age-
related changes in nonverbal cognition rather than motor or language skills. We argue that
the findings add to the growing amount of evidence supporting expectancy-based theories of
the illusion, which depend on being able to form and apply conceptual knowledge.


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<ART>The development of wayfinding abilities in children: Learning routes with and without landmarks
================================================================================

Authors: Jamie Lingwood, Mark Blades, Emily K. Farran, Yannick Courbois, Danielle Matthews
DOI: 10.1016/j.jenvp.2014.11.008
Year: 2015  |  Pages: 74-80
ASJC codes: 3202, 3207
Keywords: Landmarks, Route learning, Virtual environments, Wayfinding

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Young children experience wayfinding difficulties. A better understanding of the development of wayfinding abilities may inform strategies that can be used to improve these skills in children. The ability to learn and remember a route was assessed in 220 6-, 8-, and 10-year old children and adults. Participants were shown a route in a virtual environment, before they were asked to retrace this route until they had achieved two consecutive trials without error. The virtual environment contained (i) no landmarks (ii) landmarks or (iii) landmarks that were verbally labelled. Adults, 10-year-olds and most 8-year-olds learnt the route when landmarks were present, but not all the 6-year-olds were successful. All age groups of children improved when the landmarks were labelled. Children were much poorer when there were no landmarks. This is the first study to distinguish between route learning dependent on landmarks, and route learning without landmarks (i.e. dependent on directions).

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The development of spatial abilities have been of interest to psychologists for decades
(Acredolo, 1977, 1978; Bullens, Iglói, Berthoz, Postma, & Rondi-Reig, 2010; Hermer &
Spelke, 1994; Nardini, Thomas, Knowland, & Braddick, 2009). Spatial tasks such as the
reorientation task have been used to explore the developmental trajectory of spatial
abilities. Wayfinding is a spatial ability that is used by most people every day and
refers to the ability to learn and remember a route through an environment. Wayfinding
involves learning routes successfully and there are various strategies for encoding and
retracing a route (Kitchin & Blades, 2001). The two most important ones are a landmark
based strategy in which an individual learns that a particular landmark indicates a turn
(e.g., turn left at the sweet shop), and a directional strategy, when an individual learns
a route as a sequence of junctions (e.g., turn left, then left again and then turn right).
Such strategies are not mutually exclusive but can be used together for effective route
learning. However, previous research has suggested that young children's route learning
may be particularly dependent on recalling landmarks (Cohen & Schuepfer, 1980; Heth,
Cornell, & Alberts, 1997). As discussed below there is much evidence that children rely on
landmarks, but previous research has not been able to distinguish performance based on
learning landmarks and performance based on learning directions, and we do not know
whether, in the absence of landmarks, children's wayfinding will be negatively affected.
This has often been an assumption (Kitchin & Blades, 2001), but for the reasons explained
below this is an assumption that has rarely been tested. Landmarks are considered to be
important for successful performance on spatial tasks such as the reorientation task (Lee,
Shusterman, & Spelke, 2006; Nardini et al., 2009) and the ability to use landmarks has
often been considered to be an essential foundation for children's successful wayfinding
(Cornell, Heth, & Alberts, 1994; Courbois, Blades, Farran, & Sockeel, 2012). In one of the
first theories of wayfinding, Siegel and White (1975) emphasised the importance of
landmarks by arguing that landmarks were the first elements that children learnt visually
when encoding a route. Only after learning the landmarks along a route did children relate
the landmarks to particular turns. Finally, children could demonstrate an understanding of
the relationship between different points of the route in a survey like representation of
the environment (Siegel & White, 1975). Siegel and White (1975) emphasised how a landmark
would cue a turn, so that when a child saw a specific landmark along a route he/she would
know which turn to make next. Previous research has demonstrated the importance of
landmarks in the development of children's wayfinding (see Kitchin & Blades, 2001). For
instance, Cohen and Schuepfer (1980) showed children and adults a route displayed on six
consecutive slides, and once the participants had ‘navigated’ their way through the
slides, they were presented with identical slides with no landmarks and asked to recall
the appropriate landmarks that they had previously seen. Younger children (6- to 8-year
olds) recalled fewer landmarks than older children (11-year olds) and adults. Other
research has demonstrated that children are dependent on landmarks remaining exactly the
same as when they were encoded, because changes in the appearance of a landmark disrupts
younger children's ability to use them when retracing a route (Cornell et al., 1994; Heth
et al., 1997). Young children are more likely to rely on landmarks that are closely
associated with a turn. Cornell, Heth, and Broda (1989) asked 6 and 12-year-olds to
retrace a route through a University campus and told some children just to pay attention,
some children to note landmarks that were near junctions, and other children were advised
to remember distant landmarks that were not on the route itself but were visible from
different parts of the route. The older children benefitted from advice about noting any
landmark, but the performance of the younger ones only improved when their attention was
drawn to landmarks very close to junctions. Young children's focus on landmarks near to
choice points has been found when children have to name what they think are the best
landmarks along a route (Allen, 1981), or when they are learning a route over a number of
trials (Golledge, Smith, Pellegrino, Doherty, & Marshall, 1985). Taken together the past
studies of children's wayfinding have demonstrated that young children are particularly
dependent on landmarks closely associated with junctions/choice points. Despite the
evidence above, previous studies of children's wayfinding have all been limited because of
the impossibility of distinguishing between wayfinding that is based on purely landmark
strategies (‘turn at the tree’) and wayfinding based on directions (‘first left, then
right’). The routes used in previous experiments have been presented as slides, as films,
or have been actual routes in real environments like towns, campuses or buildings (Kitchin
& Blades, 2001), and in all such environments children's performance could well be based
on recalling specific landmarks along the route, but it could also be based on recalling
the sequence of junctions. Alternatively, children's performance could be a combination of
both strategies – for example remembering that the first turn was a right turn, the second
was by the shop, then the next was a left turn, the next was by a tree, and so on. Nothing
in previous research excludes the possibility that even young children may rely on the
sequence of turns (left, right) as well as on the presence of landmarks. One of the aims
of the present study was to find out when children could learn a route in an environment
with no landmarks, in other words in an environment where they were dependent on encoding
just the turns. The route that children were asked to learn was through a maze in a VE.
The maze was made of uniform and indistinguishable paths and brick walls so that the walls
provided no wayfinding cues. In one condition we included salient landmarks at the
junctions of the maze, and in another condition we removed all of the landmarks entirely.
In the landmark condition children could learn the route through the maze by attending to
the landmarks and/or by noting the sequence of the turns. In the condition without
landmarks children could only navigate by remembering the sequence of turns. Creating an
environment without landmarks is only possible in a VE, because any real world environment
includes numerous landmarks (buildings, signs, marks on the sidewalk) that can be used for
wayfinding. Only by using a VE were we able to remove all cues from the environment. VEs
are an effective way to study wayfinding because VEs can depict visual and spatial
information from a 3D first person perspective (Jansen-Osmann, 2002; Richardson, Montello,
& Hegarty, 1999) and successful route learning in VEs can transfer to real environments
(Ruddle, Payne, & Jones, 1997). VEs have also been used to assess wayfinding by children
(Farran, Courbois, Van Herwegen, & Blades, 2012), and are an efficient tool for improving
route learning abilities (Farran, Courbois, Van Herwegen, Cruickshank, & Blades, 2012).
Jansen-Osmann and Fuchs (2006) compared how 7- and 11-year-olds learnt their way around a
VE with and without landmarks and found that wayfinding performance was poorer without
landmarks. However, in Jansen-Osmann and Fuchs children freely explored a whole maze
(rather than learnt a specific route), and their knowledge of the maze was then measured
by assessing how well they navigated between two places in the maze separated by just two
turns. Therefore, Jansen-Osmann and Fuchs's procedure was different from the real world
route learning studies described above which always involved participants leaning a
specific route with several turns. In a further study, Jansen-Osmann and Wiedenbauer
(2004) used a VE to assess children's reliance on landmarks. The children freely explored
a VE maze while attempting to reach a goal, and later they had to find the goal again when
the landmarks had been removed from the maze. 6- and 8-year-old children found this
difficult, but 10-year-olds and older children were successful. In the present study we
wanted to extend Jansen-Osmann and Wiedenbauer's (2004) findings. We asked 6-year olds,
8-year olds, 10-year olds and adults to learn a specific route through a VE, rather than
asking participants to freely explore the VE. The route had six junctions with a choice of
two directions at each junction. Participants were guided along the correct route once,
and were then asked to retrace the route, from the start, on their own. Participants
retraced the route until they achieved two consecutive completions without error. We used
a between participants design (unlike Jansen-Osmann & Wiedenbauer, 2004) to eliminate the
possibility that participants improved their performance due to practice effects. In
condition 1, participants were tested along a route that included no landmarks (so that
wayfinding was dependent on learning the sequence of turns). In condition 2, participants
were tested along a route that included landmarks (which could be used to identify turns).
Given the previous research (discussed above) that has indicated children's dependence on
landmarks, we expected the children to learn the route better in condition 2 (with
landmarks) than in condition 1 (without landmarks), but we expected that adults would be
equally proficient at learning both the route with and the route without landmarks. The
age when children can learn just a sequence of turns (without landmarks) has never been
established before.

<hs>  Hypotheses</hs>
  ~~~~~~~~~~

The ability to use directions such as left and right does not fully develop until the age
of 10 years (Blades & Medlicott, 1992; Boone & Prescott, 1968; Ofte & Hugdahl, 2002), and
Jansen-Osmann and Fuchs (2006) found that 6- and 8-year-olds had difficulty in an
environment without landmarks. Therefore our first prediction was that 6- and 8-year olds
would perform poorly in condition 1 without landmarks relative to condition 2. We expected
10-year-olds would learn the route without landmarks, because this age group had been
successful in Jansen-Osmann and Fuchs' study, albeit along a route with only 2 turns. We
assumed that the adults would be able to learn the route in condition 1 without
difficulty. Condition 3 of the present experiment was included to find out if a small
amount of training would improve children's route learning. The VE in condition 3 (as in
condition 2) had landmarks. When the children in condition 2 were first shown the route by
the experimenter none of the landmarks were pointed out, but in condition 3 the landmarks
at correct junctions were each named as the child was led by the experimenter. Studies
have shown that children benefit from being told to attend to landmarks in real
environments (Cornell et al., 1989). Therefore, for our second prediction we expected
children would perform better when the landmarks had been named in condition 3 than when
they had not been named in condition 2.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Sixty 6-year olds (M = 6; 3, SD = 0.26), 60 8-year olds (M = 8; 5, SD = 0.31), and 60
10-year olds (M = 10; 4, SD = 0.53), were recruited from a number of primary schools in
the UK. Twenty of each age group (10 boys and 10 girls) were randomly allocated to
condition 1, condition 2, and condition 3. Forty adult participants (mainly postgraduate
students) aged 20–37 years also took part (M = 25 years, 6 months, SD = 3 years, 8
months). Twenty adults (10 male and 10 female) were randomly allocated to condition 1 and
condition 2. No adults took part in condition 3, because pilot data suggested that adults'
performance was already near ceiling in condition 2 and so no further improvement would
have been detected in condition 3. Ethical approval was granted by the University of
Sheffield Department of Psychology ethics committee.

        <hss>Virtual environments</hss>

        Five different VEs were created using Vizard, a software program which uses python
        scripting. VEs were presented to participants on a 17-inch Dell laptop that was
        placed on a desk. Participants sat in a chair at the desk and were approximately
        50 cm from the screen. Participants navigated through the maze using the arrow
        keys on the keyboard.

        <hss>Practice maze</hss>

        One maze (maze A) was used as a practice maze to familiarise participants with
        moving in a VE. This maze was a similar but different layout to the test mazes. It
        did not contain any landmarks.

        <hss>Test mazes</hss>

        Four VE mazes (mazes 1–4) were used to test participants. Each maze was a brick
        wall maze (see Fig. 1) with six junctions. Each junction was a two-choice junction
        with a correct path and an incorrect path. The incorrect path ended in a cul-de-
        sac. From the junction the cul-de-sac looked like a T-junction rather than a dead-
        end. Therefore, participants could not tell that they had made an error until they
        had actually committed to walking along a chosen path. Of the six junctions in
        each maze, there were two right, two left and two straight ahead correct choices
        that were balanced with the same type and number of incorrect choices. All of the
        path lengths between junctions were equal. A white duck marked the start of the
        maze and a grey duck marked the end of the maze. When participants reached the
        grey duck, the maze disappeared indicating the end of the trial. Maze 1 and maze 2
        were used in condition 1. Maze 1 is illustrated in Fig. 2. Maze 2 was exactly the
        same design as maze 1 except that the start point of maze 2 was the end point of
        maze 1, and the end point of maze 2 was the start point of maze 1. Maze 1 and maze
        2 were therefore equivalent, but each included a different sequence of left,
        right, and straight ahead correct choices. We included two mazes in condition 1 so
        that the findings were not specific to a particular route. Half the participants
        in condition 1 received maze 1 and half received maze 2. Maze 3 and maze 4 were
        used in condition 2. Maze 3 is illustrated in Fig. 3. Maze 3 was the same as maze
        1 but included 12 landmarks. Maze 4 was the same as Maze 2 but included 12
        landmarks. In both mazes, the landmarks were all objects that would be familiar to
        children: ball, bench, bus, bicycle, car, cow, playground slide, street lamp,
        traffic light, bin, tree and umbrella. There were 6 landmarks placed at path
        junctions on the correct route and 6 landmarks placed at dead-end junctions on the
        incorrect route. Maze 3 and maze 4 were also used in condition 3 (the training
        condition). Like condition 2 half of participants were tested in each maze.

<hs>  Procedure</hs>
  ~~~~~~~~~

All participants were tested individually. Adults completed the experiment in a quiet
office in a University Department. Informed consent was obtained prior to data collection.
Children completed the experiment in a quiet room in their school. Informed consent was
obtained from all the children's parents, and all the children were asked if they wanted
to take part. No children refused to take part. The participant sat at the desk facing a
computer and the experimenter sat beside them. The experimenter spent 2 min talking to the
participant informally to establish rapport. Participants were asked for their age and
birthdate. The experimenter introduced the task by saying, ‘This computer has got some
mazes on it that we are going to use. First, we're going to practice using the computer to
walk around a maze. I'll go first and show you how, and then you can have a turn.’ The
experimenter then demonstrated how to navigate through the practice maze using the arrow
keys. Participants were then given time to walk around the maze until they were confident
in using the arrow keys to navigate, at which point the experimenter ended the practice
phase by saying, ‘Well done, I think you've had enough practice now, do you? Let's have a
go at another maze now.’ All participants were given preliminary instructions for the test
phase: ‘Now I'm going to show you the way through a new maze. Somewhere in this maze there
is a little grey duck to find. I'll show you the way to the grey duck once, and then you
can have a go.’ The experimenter then demonstrated the correct route from the start to the
end of the maze, giving verbal instructions that differed according to condition. In
conditions 1 and 2, the experimenter used generic terms such as ‘You go past here, then
you turn this way, and then you turn this way’. In condition 3, the experimenter verbally
labelled each landmark. For example, ‘You go past the bench, turn this way at the traffic
light, and then you turn this way at the bin’. In all conditions, the experimenter did not
use any directional language, such as ‘Turn right’. At the end of the demonstration, the
experimenter exclaimed, ‘Hooray, we've found the duck!’, and the screen went blank. The
participant was then asked to retrace the route they had been shown from the beginning of
the maze and used the arrow keys to walk through the maze. The experimenter sat behind the
participant and traced the exact route the participant took on a paper copy of the maze,
out of the participant's sight. The experimenter timed how long it took the participant to
complete the maze. If, after 5 min, a participant had not reached the end of a maze on a
particular trial, the experimenter ended the trial by saying, ‘Oops, it looks like you've
got a bit lost. Not to worry, let's start back from the beginning, shall we?’ In practice,
this happened infrequently. A note was made that the trial was curtailed, and a new trial
commenced. Participants did not receive any help in finding their way after the initial
demonstration of the correct route. If a participant asked which way to go, the
experimenter said, ‘I want you to show me the way to go. Just try your best.’ If a
participant returned to the start position but thought that they had reached the end, they
were told, ‘You're back at the beginning of the maze now. Let's turn around and try again
to remember the way I showed you to the little grey duck.’ Again, in practice, this
happened infrequently. When the participant reached the end of the maze, the experimenter
congratulated the participant, and asked them to walk the route again from the start. This
procedure was repeated until the participant had walked the route to a criterion of two
consecutive completions without error. At the end of the final trial, all participants
were thanked, and children, regardless of their performance, received a sticker. If a
participant had not walked the route with two consecutive completions after 20 min or
after eight attempts, the experiment was stopped and the children were given a sticker.

<h>RESULTS</h>
-------

Successful learning was defined as two consecutive completions of the route without error.
To achieve this criterion, participants had to walk the route without walking down any
incorrect paths on two consecutive learning trials. Walking down an incorrect path was
classed as an error. Looking down an incorrect path was not classed as an error. The total
number of learning trials to reach criterion excluded the final two perfect trials. For
example, if a participant made an error on trial 1, but then walked the route without
error on trials 2 and 3, they would be scored as having required 1 trial to reach
criterion. A lower score indicated better performance. If a participant never achieved the
criterion, the number of learning trials was calculated as the number of trials that were
completed. For example, if a participant completed 6 trials within the 20-min cut-off
time, but did not complete 2 consecutive trials without error, they scored 6. Participants
received a mark of 1 for every error they made during a trial. On each trial a
proportional error score was calculated as the number of errors divided by the number of
decisions made. For example, Fig. 4 shows the route taken by one participant. This
participant made 5 errors out of a total of 13 decisions, producing a proportional error
score of 0.38. This scoring captured participants' wayfinding behaviour every time they
made a decision. This scoring method accounted for occasions when participants doubled
back and returned to the same junction more than once within a trial. Some participants
who got lost did not reach the later junctions, so any junctions not reached were also
scored as errors at decision points. A mean proportional error score was calculated for
each participant across learning trials. The proportional error score captured all of a
participant's behaviour on a trial. We note that alternative coding criteria produced the
same patterns of performance. For example, we coded just the decisions made the first time
a participant approached a junction in each trial. Participants scored 0 if they chose the
correct path or 1 if they chose the incorrect path and any junctions not reached were
counted as errors. Therefore 6 indicated the worse performance, and 0 perfect performance.
When this scoring was compared to the proportional error score (above), there were no
differences in the results. Therefore, in the results section we report only the
proportional error scores. Independent sampled t-tests showed that there were no
differences between performance on maze 1 and maze 2 or maze 3 and maze 4 for any of the
dependent variables (all p-values >0.05). We explored whether there were any differences
in performance at path junctions across the six landmarks. The assumption of sphericity
could not be met (x2 (14) = 164.20, p < 0.001.) and so a geisser-greenhouse correction is
reported instead (ε = 0.72). A one-way repeated measures ANOVA (6 levels: tree, bench,
bike, umbrella, traffic light, bin) demonstrated a main effect of landmark type (F (3.957,
492.794) = 5.466, p < 0.001, np2 = 0.03). A Bonferoni corrected post-hoc test revealed
that participants made fewer errors at the bench than at the bin (p < 0.01) and at the
bike than at the bin (p < 0.001). Performance at all other choice point pairings were
equal (all p-values >0.05). Both the bike and bench were straight ahead junctions and
therefore at these junctions participants did not have to remember to turn left or right.
But at the bin, participants had to remember to turn either left or right. This may
explain why there was a difference in performance at certain junctions in the maze.

<hs>  Scoring method</hs>
  ~~~~~~~~~~~~~~

To test our predictions relating to children's and adults' performance across the
different conditions, we analysed three dependent variables: – (i) proportion of
participants reaching the learning criterion, (ii) number of trials to reach learning
criterion (for those who reached criterion) and (iii) proportion of errors. Chi-square
analyses were used to explore the proportion of children and adults who reached learning
criterion in the three different maze conditions. ANOVA analyses were then conducted to
explore number of trials to reach criterion and proportion of errors made by children and
adults in the different maze conditions.

<hs>  Proportion of participants reaching the learning criterion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Chi-square analyses were conducted to explore how many participants reached the learning
criterion in the different maze conditions. In condition 1 (no landmarks) 10% of 6-year
olds, 40% of 8-year olds, 80% of 10-year olds, and 100% of adults reached the criterion of
2 successive trials without error. In condition 1 there was a relationship between age and
reaching the learning criterion (X2 = 39.90, df = 3, p < 0.001). Standardized residuals
show that this was accounted for by adults whom were more likely to more likely to reach
criterion than 6-year olds. In condition 2 (with landmarks) 90% of 6-year olds, 95% of
8-year olds, 100% of 10-year olds, and 100% of adults reached the criterion. There was no
significant relationship between age and reaching the learning criterion in condition 2
(X2 = 3.81, df = 3, p > 0.05). In condition 3100% of 6-year olds, 100% of 8-year olds,
100% of 10-year olds, reached the criterion, so no statistical analyses could be
conducted. Adults were not included in condition 3 because, as had been expected they were
at 100% in condition 2.

<hs>  Number of learning trials to reach criterion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In condition 1, for only those participants who reached criterion, 6-year olds required
more trials (M = 5.00, SD = 0) than 8-year olds (M = 2.13, SD = 2.36), 10-year olds (M =
2.00, SD = 1.71) and adults (M = 0.30, SD = 0.73). As noted above many children did not
reach the learning criterion (notably 6- and 8-year olds), so it was not appropriate to
conduct any statistical analyses with such uneven groups. In condition 2 (landmarks) for
only those participants who reached criterion, 6-year olds required more trials (M = 2.06,
SD = 1.83) than 8-year olds (M = 1.21, SD = 1.90), 10-year olds (M = 0.25, SD = 0.55) and
adults (M = 0.30, SD = 0.73). A one-way ANOVA was carried out with age (6 years, 8 years,
10 years, adults) on the number of learning trials to reach criterion. There was an effect
of age (F (3, 76) = 7.42, p < 0.001). Tukey post-hoc tests showed that in condition 2 the
6-year olds required more trials to reach criterion than the 10-year olds (p < 0.01) and
adults (p < 0.01). All other post-hoc tests were non-significant (p > 0.05). In condition
3 the 6-year olds (M = 0.90, SD = 1.07) required more trials than the 8-year olds (M =
0.15, SD = 0.57) and 10-year olds (M = 0.05, SD = 0.22). Analysis of this condition is
considered within the ANOVA below. To consider the data from the child groups across
conditions (adults did not complete all condition 3), a 2 (condition 2, condition 3) × 3
(6, 8, 10 year olds) ANOVA was performed on the number of learning trials to reach
criterion in each condition. Two 6-year olds and one 8-year old did not reach the learning
criterion in condition 2 and therefore were not included. There was an effect of condition
(F (1, 111) = 13.73, p < 0.001, np2 = 0.11) because children required fewer trials to
reach criterion in condition 3 than condition 2. There was an effect of age (F (2, 111) =
12.56, p < 0.001, np2 = 0.19). As confirmed by Tukey pairwise comparisons, 6-year olds
required more trials to learn the route than 8-year olds (p < 0.05) and 10-year olds (p <
0.001). Eight-year olds did not require more trials than 10-year olds (p = 0.13). These
significant main effects support our second hypothesis that verbal labelling reduced the
number of trials required to reach criterion. There was no interaction between maze
condition and age group (F (2, 111) = 1.98, p = 0.14).

<hs>  Proportional errors during the learning phase</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In condition 1 the 6-year olds (M = 0.42, SD = 0.15) made more errors than the 8-year olds
(M = 0.23, SD = 0.18), 10-year olds (M = 0.14, SD = 0.13) and adults (M = 0.03, SD =
0.06). In condition 2 the 6-year olds (M = 0.12, SD = 0.14) made more errors than the
8-year olds (M = 0.06, SD = 0.08), 10-year olds (M = 0.01, SD = 0.02) and adults (M =
0.01, SD = 0.03). In condition 3 6-year olds (M = 0.07, SD = 0.08) made more errors than
8-year olds (M = 0.01, SD = 0.03), and 10-year olds (M = 0.01, SD = 0.01). We did not
conduct a Maze (condition 1, condition 2, condition 3) × Age (6-, 8-, 10-year old, adults)
ANOVA, given that no adults took part in condition 3. Rather, we conducted two separate
analyses: A Maze (condition 1, condition 2) × Age (6-, 8-, 10-year olds, adults) ANOVA and
to explore the effect of verbal labelling, a Maze (condition 2, condition 3) × Age (6-,
8-, 10-year olds) ANOVA. A 2 (condition 1, condition 2) × 3 (6-, 8-, 10-year olds) ANOVA
was performed on the proportion of errors. There was an effect of maze (F (1, 114) =
70.26, p < 0.001, np2 = 0.38) because participants made proportionally more errors in
condition 1 than condition 2. There was an effect of age (F (1, 2, 114) = 24.32, p <
0.001, np2 = 0.30). As confirmed by Tukey pairwise comparisons, 6-year olds made a higher
proportion of errors than 8-year olds (p < 0.001) and 10-year olds (p < 0.001). The
proportional of errors for 8-year olds and 10-year olds did not differ (p = 0.06). There
was also an interaction between maze condition and age group (F (2, 114) = 4.43, p < 0.05,
np2 = 0.07) as there was a greater age related improvement between 6- and 8-year olds than
between 8- and 10-year olds in condition 1, but in contrast there was a greater age
related improvement between 8- and 10-year olds than between 6- and 8-year olds in
condition 2. This supported our first hypothesis that younger children (6- and 8-year
olds) would make more errors when learning the route without landmarks than when learning
the route with landmarks. A 2 (condition 2, condition 3) × 3 (6, 8, 10 year olds) ANOVA
was performed on the proportion of errors. There was an effect of condition (F (1, 114) =
6.88, p < 0.05, np2 = 0.06) because children made proportionally more errors in condition
2 than condition 3. There was also an effect of age (F (2, 114) = 14.78, p < 0.001, np2 =
0.21). As confirmed by Tukey pairwise comparisons, 6-year olds made more errors than
8-year olds (p < 0.01) and 10-year olds (p < 0.001). The proportional of errors for eight-
year olds and 10-year olds did not differ (p = 0.20). These significant main effects
supported our second hypothesis that verbal labelling reduced the number of errors made by
participants. There was no interaction between maze condition and age group (F (2, 114) =
1.21, p = 0.30).

<h>DISCUSSION</h>
----------

The aim of the present study was to investigate the development of children's wayfinding
strategies. As noted in the introduction there are two predominant strategies that can be
used for learning and retracing a route (Kitchin & Blades, 2001). One is a strategy based
on landmarks so that a child encodes a turn in relation to a particular landmark, and one
is a directional strategy when a child learns a sequence of turns. From previous research
we predicted that children would rely heavily on the presence of landmarks and that this
would be particularly the case for the younger children (Cohen & Schuepfer, 1980; Jansen-
Osmann & Wiedenbauer, 2004). Therefore we expected young children to encode a route much
better in a maze with landmarks than they would in a maze without landmarks. In a maze
without landmarks children are dependent on learning a sequence of turns and therefore one
aim was to establish if any of the age groups of children in the study could use this
strategy when wayfinding. Our results showed that only a quarter of the 6- and 8-year olds
achieved the learning criterion in condition 1 when there were no landmarks available. In
other words, without the presence of landmarks their route learning was poor, and they
made a large number of errors. In contrast, four-fifths of the 10-year olds were able to
learn the route even when there were no landmarks present. The latter finding indicated
that by the age of 10 years children can adopt a directional strategy and consider a route
in terms of left, right and straight ahead directions. The 10-year olds were therefore
mostly competent wayfinders even when they were unable to rely on landmarks. Though we
note that the 10-year olds did not perform as well as the adult group, and therefore
children's ability to use just directions for route finding is still developing at the age
of 10 years. 6 and 8-year olds found it difficult to find their way in the absence of
landmarks. These children may have had a more limited memory capacity, and therefore might
have had difficulty encoding six turns. However, this is unlikely because the results from
condition 2 showed that nearly all the children could learn six turns when landmarks were
present, and other research has shown that learning six turns is easily possible for these
age groups (Farran, Courbois, Van Herwegen, & Blades, 2012; Farran, Courbois, Van
Herwegen, Cruickshank, et al., 2012). Therefore the younger children's difficulty in the
present experiment was probably due to their failure to employ a directional strategy
(i.e. using left, right and straight ahead) to find their way in the absence of landmarks.
Young children may have difficulty using such a strategy because their use of spatial
directions like left and right may not be fully developed until about the age of 10 years
(Blades & Medlicott, 1992; Boone & Prescott, 1968; Ofte & Hugdahl, 2002). When landmarks
were available in the maze (in condition 2) 90% or more of each group learnt the route
successfully. However, even when landmarks were available the 6-year-olds required more
trials to reach criterion than the older children and adults. In other words, children can
learn a route with landmarks, but how effectively they do so improves with age, and this
corresponds to previous findings (Cornell et al., 1989; Siegel & White, 1975). The younger
children might have required more trials than older children to learn the maze with
landmarks for several reasons. Younger children could have less mature cognitive
abilities, and/or their lack of wayfinding experience, because young children, especially
6-year olds rarely have to encode new routes for themselves. We considered whether the
children's poorer than optimal performance in condition 2 with the landmarks, was a
reflection of difficulty with route learning or because the children who did poorly were
less aware of appropriate wayfinding strategies. In condition 3 we pointed out and
emphasised the landmarks during the children's first walk through the maze. This in itself
led to an improvement in the performance, because all the children reached criterion in
condition 3 and all three age groups of children had fewer errors in condition 3 than in
condition 2. We can conclude that the wayfinding limitations shown by a few children in
condition 2 were most likely due to those children not attending sufficiently to the
landmarks during the learning trial. At 6-years of age the executive-frontal functions
required for efficient navigation begin to develop (Bullens, Nardini, et al., 2010;
Nardini, Jones, Bedford, & Braddick, 2008; Nardini, et al., 2009). Furthermore at 6-years
of age children are particularly reliant on landmark cues for successful navigation
(Bullens, Iglói et al., 2010). When all the children had the landmarks explicitly pointed
out to them in condition 3 they all learnt the route successfully. The effect of verbally
emphasising landmarks during learning supports previous research (Cornell et al., 1989;
Farran, Blades, Boucher, & Tranter, 2010), possibly by triggering verbal recoding and
suggests that this simple training technique can be very effective. We emphasise that in
condition 3 we did not train the children by indicating the relationship between a
landmark and the corresponding turn (which would have been an explicit wayfinding
strategy), all we did was get the children to pay attention to the landmarks the first
time they walked the route, and this was sufficient for children's route learning to
improve. Therefore the limitations in young children's performance in condition 2 were
probably due to lack of experience (in this case not realising the need to attend to all
of the landmarks). Therefore, it seems likely that if adults make an effort to emphasise
landmarks along new routes then the children's wayfinding will be improved, without the
need for any more specific training. Emphasising appropriate landmarks in real world
contexts might be particularly important because the real environment can include a great
many potential landmarks. Future research could manipulate the number and complexity of
landmarks in a VE maze to find out the effects of multiple landmarks at decision points
along a route. Our cross sectional design only allowed us to examine a snapshot of how
children find their way at a certain age. Future research could also explore how
children's wayfinding abilities develop longitudinally over time using controlled VEs
which (unlike real environments) do not change over time. Like previous research the
present study has demonstrated that VEs can be an effective method for investigating how
children learn a route (Farran, Courbois, Van Herwegen, & Blades, 2012; Jansen-Osmann,
2002; Jansen-Osmann & Fuchs, 2006), because a VE allows complete control of the
environment and is a safe way to test young children's wayfinding. More importantly a VE
allows the creation of routes (like the ones without landmarks in condition 1) that would
be impossible in a real environment and this has led to novel findings. However, unlike
the real world participants were not immersed in the VE and nor did participants
experience the same whole body kinaesthetic information. Therefore we recognise that there
are limits to using desktop VEs to study wayfinding. This is the first study to
distinguish between route learning dependent on landmarks and route learning dependent on
learning directions. Without the presence of landmarks, 6- and 8-year olds were much
poorer at learning the route than when landmarks were present. This suggests that
landmarks are crucial for children's route learning and that route learning based on
directions does not develop until the age of 10. Our findings also showed that when
landmarks were labelled this improved wayfinding performance for all children.


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<ART>The developmental origins of social hierarchy: how infants and young children mentally represent and respond to power and status
================================================================================

Authors: Lotte Thomsen
DOI: 10.1016/j.copsyc.2019.07.044
Year: 2020  |  Pages: 201-208
ASJC codes: 3200

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The learnability problem of social life suggests that innate mental representations and motives to navigate adaptive relationships have evolved. Like other species, preverbal human infants form dominance hierarchies where some systematically supplant others in zero-sum conflict, and use the formidability cues of body and coalition size, as well as previous win-lose history, to predict who will prevail. Like other primates, human toddlers also seek to affiliate with allies of high rank, but unlike bonobos they pay unique attention whether others voluntarily defer to their precedence, reflecting the importance of consensual authority in cooperative human society. However, young children appear not to readily infer authority from benevolence, and expectations for inequality correlate with unwillingness to share resources even among infants.

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PREVERBAL INFANTS INFER THE OUTCOME OF FUTURE ZERO-SUM CONFLICT FROM CUES OF FORMIDABILITY
--------------------------------------------------------------------------------

Early ethological, naturalistic observations in daycare groups demonstrated that
preschoolers [26–28], and even infants from 8 [29] and 11 [30] months of age, form
transitive dominance hierarchies like those of other species such that more formidable and
agonistic individuals systematically supplant others in contests over scarce resources
(e.g. toys). Consistent with the adaptive importance of accurately perceiving and
coordinating along formidability in such dominance hierarchies, 9–13 month-old infants
also mentally represent social dominance, and use relative body-size – a cue which not
only marks formidability, but also status and authority across cultural practices and
conceptual metaphors [2,31–33] – to predict who will prevail in novel zero-sum conflicts
before any physical coercion ensues. Although they unlikely have extensive personal
experience engaging in right-of-way conflicts, infants looked longest, indicating that
their expectations were violated, when a large cartoon figure prostrated and yielded the
way to a smaller one in a ‘game-of-chicken’, where the two figures blocked each other from
crossing a stage in opposite directions. These effects hinged critically upon the
existence of zero-sum conflict so that one agent completed its goal at the expense of the
other: When the agents moved alone on the stage or in the same direction behind one
another, so that both could have achieved their goals, infants made no prediction whether
the large or small figure would manage to cross the stage [33]. Nor did they do so if the
animations were stopped immediately after the prostration event, suggesting that in the
absence of zero-sum conflict, infants do no associate relative size/formidability with
this conventional display of submission and deference across culture and species [34].
Infants also use the formidability cue of previous win-lose history to predict who will
dominate whom across conflict domains and dyadic relationships. When a novel agent uses
coercive force to push another one out of a contested territory, they expect that the
former loser will later yield a contested resource to the winner without physical fight
[35] (see also Refs. [36]). Importantly, and as previously demonstrated among even fish
[37], recent work now confirms that human infants, too, make transitive inferences and
predict relative dominance based on the previous win-lose history that individuals had
with (common) third-parties [38•]. Finally, like other species including dolphins, spotted
hyenas, lions and several non-human primates [7–10,39,40–45], humans engage in coalitional
conflict, which the archeological record indicates also characterized the context in which
we evolved [13,19,46,47]. Coalitional conflicts manifest from preschool and primary school
playgrounds [48,49] to large-scale politics [13,14,50], resemble dove–hawk dominance
dynamics (cf. 14,21]), and have profound psychological and societal implications
[4,13,50,51]. And indeed, even 6–9 month-old infants were found to understand coalitional
formidability, using the relative number of allies to predict which individuals will yield
and prevail [52•] in the right-of-way dominance paradigm [33]. However, representing the
combined formidability of a set of individuals by their number is unlikely a
psychologically simpler, more salient or reliable indicator of dominance than is
individual strength, as indicated by the fact that infants from eight months of age form
interpersonal dominance hierarchies [29,30], long before they presumably engage in any
joint inter-coalitional conflict. Surely, coalitional formidability relies in part upon
the strength of individual members. Consistent with this, several non-human primates
selectively recruit and join the more formidable individuals in coalitional conflict [43].
When predicting the outcome of coalitional conflict, three-year-olds, as well as adults,
also flexibly weigh the parties’ body sizes against the number of allies, emphasizing the
former for smaller, and latter for larger, coalitions [69]. In fact, by primary school,
children integrate a full range of asymmetric factors to weigh the total expected costs
and benefits of engaging in resource conflict, and make no systematic prediction whether
one large or two smaller, allied individuals will win a conflict [48]. Indeed, group-
living does not make interpersonal dominance obsolete, but potentiates the long-term
fitness implications of rank-based, recurrent outcomes within the group, as they are
remembered by individuals who know one another [43,53–55]. Accordingly, a suite of
dedicated cognitive architecture translates individual, physical strength into claims for
both personal resources, coalitional dominance, and allocated social status [56–60], and
also supports inductions about the physical strength and competitive motives of others,
even from vocal pitch [61–63]. Further supporting the importance of individual strength,
even three-month-olds induce physical size from voice pitch [64•] and pre-schoolers
adeptly induce and relate both ‘who is strongest’ and ‘who is in charge’ from non-verbal
cues of body posture, muscularity and facial configuration [65–68].

<h>BEFRIEND AND OBEY THOSE TO WHOM OTHERS DEFER, AVOID THOSE WHO MUST COERCE</h>
-------------------------------------------------------------------------

Any adaptive gains from representing fundamental forms of social relations stem not simply
from accurately perceiving them, but from using this information to navigate the social
world in appropriate, strategic ways [1]. And indeed information about status rank
motivates the way infants, toddlers and preschoolers themselves relate to, and coordinate
with, others. Whereas dominant individuals are avoided in many species, so as to not
provoke aggression, in highly social species they may offer access to resources and
influence, so that approaching, ingratiating and affiliating oneself with other
individuals of high rank may be adaptive [43,71••]. This relationship between rank and
resources is well understood: Infants expect third-party distributions of resources to
benefit a physically dominant over subordinate agent [72]; three-year-olds and four-year-
olds will themselves favor a dominant individual in third-party distributions of resources
[73], and they explicitly expect that those giving or withholding access to use resources
will be in charge [74•]. Young children also intuitively enact these dynamics in
controlled settings: In a game of chicken — where a child yielding the way to the other
lost some of its resources, but both children lost all their resources if nobody yielded —
dyads of five-year-olds coordinated such that previously dominant children received higher
pay-offs because their partner yielded and deferred to them more often [75•]. Similarly,
when 4–5 year-olds dominate a dyad, monopolizing a coveted toy from another child, they
later donate less stickers to other, anonymous children than do subordinates, and
experimentally induced changes of dyadic rank have similar effects as baseline dominance
[76]. Consistent with these expectations that rank begets resources, young toddlers
selectively approach those of high rank and so reach for a puppet who prevails in the
right-of-way dominance paradigm [33] over one who yields [71••]. However, when one puppet
was able to pave the way for both to cross the stage, toddlers reached for the more
competent puppet [71••]. This was also the case in another study where two puppets both
achieved their goals in the absence of zero-sum conflict, but one did so competently on
the first try and the other only after repeated failed attempts [77]. Preschoolers also
think that those who receive higher pay-offs are smarter [78], and recent evidence
suggests that toddlers may also endorse the preferences and opinions of resource-rich over
resource-poor puppet dolls [79], consistent with an ingratiation-for-potential-resources
perspective on these findings. If, on the other hand, one puppet prevails in right-of-way
conflict by retorting to brute force, knocking the other one over, then toddlers avoid
this coercively dominant puppet [71••]. By comparison, infants selectively avoid even a
prevailing puppet for whom another voluntarily yields [80••] in the right-of-way paradigm
[33]. These findings stand in stark contrast to results that bonobos prefer a dominant
individual who monopolizes a territory using brute force [81••] (cf. [35]). Furthermore, a
recent study found that toddlers expect that cartoon figures will continue to obey the
orders of someone they prostrated before and gave their resources, even when this
individual is no longer around, but hold no such expectations for an individual who just
beat them up [82••]. Thus, although human toddlers pay close attention to whether someone
was able to achieve their goal at the expense of others, compared to our primate relatives
including even the generally egalitarian and unaggressive bonobos [83], human toddlers
also appear uniquely attuned to whether someone prevails in zero-sum conflict through
consensually recognized precedence, rather than through brute coercion, reflecting its
importance in cooperative, human societies [2,15–20,23,47], (see also Refs. [84–86]).
Similarly, in the political psychology of adults, inequalities between groups are not
legitimized by appeal to differences in brute formidability, but by appeal to other,
commonly and consensually recognized principles of precedence and merit [4,13,14,50] (e.g.
the protestant work ethic). Robust cross-cultural findings, and evolutionary reasoning,
supported by evidence from some non-human primates [43] including chimpanzees [9,40],
indicate that such coalitional dominance motives are greater among males [13,46,50,87].
Mirroring this, a recent study also found that even three-year-old Norwegian boys
predominantly chose a member of a more formidable and larger, rather than smaller, group
when they were asked which of two cartoon figures they liked best and wanted to play with
and befriend. In contrast, three-year-old girls chose randomly between the two [88].

<h>BENEVOLENT VERSUS MALEVOLENT AUTHORITY</h>
--------------------------------------

Leaders in both human and non-human mammalian societies facilitate within-group
coordination and conflict resolution [20,89]. Consistent with this, just-linguistic
infants expect that a larger puppet, or a puppet whose directions were previously
followed, will intervene to rectify resource monopolization between subordinates [90] (cf.
also Ref. [82••]). But whereas young children, and even infants, understand that those in
power will control resources, permitting or sanctioning their use [74•,90], and contrary
to expectations that legitimate authorities take care of their followers and that status
may stem from the benefits one can confer upon others, children do not appear to readily
infer consensual authority from benevolent help: In fact, although even infants prefer
helpers over hinderers [91,92], when North American 4–7 year-olds, as well as adults, view
someone refuse a request for help, they take this as evidence that person is in charge
[93••]. With the exception of permitting access to scarce resources, it was also easier
for young North American children, as well as for adults, to induce such authority from
malevolent (imposing costs) rather than benevolent (conferring benefits) ways of using of
power [74•]. It is important to find out if this is also the case using more implicit
measures and across subsistence systems, culture, languages and less enculturated ages.
For instance, future studies might investigate if toddlers also expect novel agents to
continue to obey someone towards whom they displayed submissive deference after receiving
a resource from them (rather than after offering them a resource, as previously
demonstrated [82••]). In terms of learning, North American preschoolers endorsed and
imitated the domain-specific preferences and labels of a model whom bystanders had
selectively attended over someone whom they ignored [94], supporting the importance of
prestige-cues that someone is an expert for culturally transmitted learning (but see also
Refs. [78,95]). But other studies reported that French and Mayan preschoolers also
selectively endorsed the testimony (which way did the animal go) and word-labels (what is
the name of a novel object) of someone who dominated resources with brute force [96,97],
although, from an epistemic point of view, such coercive dominance need not imply any
superior knowledge. In contrast, however, five recent studies did not find evidence that
249 blind-tested, Norwegian preschoolers selectively endorsed the labels and testimony
provided by the prevailing agent in the otherwise robustly dominance-inducing right-of-way
paradigm [33,98] (see also Ref. [99] for similar results among a smaller sample of
Japanese preschoolers using resource monopolization as dominance cue). Finally, although
North American and Chinese 5–7 year-olds distinguish prestige and dominance, neither group
was recently found to explicitly predict the outcome of resource-conflict based on
dominance rank [100], raising further questions as to how their explicit reasoning link
the two.

<h>EQUALITY VERSUS HIERARCHY</h>
-------------------------

Finally, although infants, toddlers, and preschoolers understand and strategically respond
to hierarchical rank, in fact the default expectations and preferences of most of them
appear egalitarian, as is the case for adults cross-nationally [4,13,14,101]. Thus, in the
absence of other social information such as relative dominance [72] or
effort/merit/deservingness [102,103], most infants expect equal resource distributions
between third-parties, prefer people who distribute resources equally, expect others will
also prefer them, and expect equal distributors will be more helpful
[72,92,102–104,105••,106–110]. Reflecting the appeal of personal resource holding,
however, young children themselves react earlier and cross-culturally more reliably when
they are personally suffering from disadvantageous, rather than benefitting from
advantageous, inequity [109,110]. Nevertheless, the most widely used coordination strategy
among five-year-olds when distributing resources in a game of chicken was, in fact, that
of turn-taking [75•]. As is the case among adults [4,13,14,50,87,101], individual
differences among infants in whether they expect equal versus unequal resource-
distribution between others also predict whether infants are themselves willing to share
their valued resources [105••,109,110,111]. This is consistent with emergent evidence that
dispositions towards hierarchical versus egalitarian expectations and redistribution
motives are in part genetically underpinned and related [113], presumably reflecting the
balancing selection equilibria of both hierarchical and egalitarian strategies
[4,101,113].

<h>CONCLUSIONS</h>
-----------

Although human societies display unprecedented levels of cooperation, help and
egalitarianism compared to our nearest primates relatives, hierarchies within and between
groups are ubiquitous across culture. Humans display rich and sophisticated
representations to perceive, navigate, and coordinate these dilemmas of resource
distribution and conflicting interests that cooperative group living poses: Most of even
the youngest humans prefer equal distributors and helpers, but they also prefer not only
the most competent, but also those that prevail in zero-sum conflict at the expense of
others who defer to them. Expectations that resources will be unequally distributed among
third parties relate to unwillingness to share personal resources, and help and
benevolence appear not to readily license inferences of authority. Consistent with our
evolutionary history, these relational representations and motives reflect, and must
optimize, ecological trade-offs between different forms of hierarchical and egalitarian
strategies for resource distribution, and are active from earliest childhood and even
infancy. It is critical that future work investigate whether, when and how they reliably
manifest across culture and subsistence systems to address which relational logic forms
part of our innate endowment, undergirding the regulation of social life.

<h>REFERENCES AND RECOMMENDED READING</h>
----------------------------------

Papers of particular interest, published within the period of review, have been
highlighted as: • of special interest •• of outstanding interest


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<ART>The effect of mother-infant skin-to-skin contact on Ghanaian infants’ response to the Still Face Task: Comparison between Ghanaian and Canadian mother-infant dyads
================================================================================

Authors: Frances Emily Owusu-Ansah, Ann E. Bigelow, Michelle Power
DOI: 10.1016/j.infbeh.2019.101367
Year: 2019
ASJC codes: 3204
Keywords: Ghanaian mother-infant dyads, Skin-to-skin contact, Still Face Task

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<h>ABSTRACT</h>
--------

The effect of mother-infant skin-to-skin contact on Ghanaian infants’ developing social expectations for maternal behavior was investigated. Infants with high and low mother-infant skin-to-skin contact experience in the infants’ first month engaged with their mothers in a Still Face Task at 6 weeks of age. Infants with high skin-to-skin contact experience, but not those with low skin-to-skin contact experience, demonstrated the still face effect with their smiles. Infants with both high and low skin-to-skin contact experience demonstrated the still face effect with their visual attention. The behaviors of the Ghanaian infants and their mothers during the task were compared to archival evidence of Canadian mother-infant dyads’ behaviors in skin-to-skin and control groups who engaged in the Still Face Task at the infant ages of 1 and 2 months. Similarities and differences between the behaviors of the mother-infant dyads in the two cultures were assessed.

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<h>INTRODUCTION</h>
------------

Developmental psychologists increasingly are exploring how infants’ biological maturation
intersects with parenting cultural goals and styles of interaction. Parents from different
cultural contexts value different parenting goals that affect parenting interactive
practices, which in turn shape infants’ behavior (Kärtner et al., 2008; Keller, 2007;
Keller et al., 2004). Distal parenting practices, focusing on face-to-face contexts and
object play, are prevalent in Western industrialized societies where parents tend to
socialize their infants toward goals of independence and autonomy. Proximal parenting
practices, focusing on physical contact and body stimulation, are prevalent in many non-
Western societies where parents socialize their infants toward goals of interdependence
and relatedness with family and community. Although this duality is likely an
oversimplification of parenting goals and practices as complex cultural cross-overs due to
globalization as well as individual differences exist in any culture, it is clear that the
way of engaging infants prevalent in Western societies is not universal. Yet infants’
biological maturation is universal. Infants are biologically predisposed to engage with
others. Their biological predispositions interact with parenting practices early in life
and adapt to cultural demands. Mother-infant skin-to-skin contact (SSC) is a method of
caring for young infants. The infant is placed between the mother’s breasts, dressed only
in a diaper, so that frontal body contact of mother and infant is skin-to-skin. SSC
benefits newborns’ neuro-physical adjustment. By engaging in SSC with her infant, the
mother provides warmth and stimulation that is believed to simulate the prenatal
environment (Whitelaw & Sleath, 1985). Across a number of cultures, SSC for infants early
in life has been shown to stabilize infant temperatures, heart rates, respiratory rates,
gastrointestinal adaptations (Bauer, Sontheimer, Fischer, & Linderkamp, 1996; Bergman,
Linley, & Fawcus, 2004; Bystrova et al., 2003; Charpak, Ruiz-Pelaez, Figueroa de Calume, &
Charpak, 1997; Cleary, Spinner, Gibson, & Greenspan, 1997; Conde-Agudelo, Diaz-Rossello, &
Belizen, 2000; Feldman, Eidelman, Sirota, & Weller, 2002; Fohe, Kropf, & Avenarius, 2000;
Ludington-Hoe, Anderson, Swinth, Thompson, & Hadeed, 2004; Moore, Anderson, & Bergman,
2007; Mori, Khanna, Pledge, & Nakayama, 2010), and reduce pain from routine medical
procedures (Gray, Miller, Philipp, & Blass, 2002; Gray, Watt, & Blass, 2000). Studies
investigating the effects of SSC beyond the newborn period have shown that the effects
extend to infants’ social cognitive development. Feldman and colleagues (Feldman,
Eidelman, et al., 2002; Feldman, Weller, Sirota, & Eidelman, 2002) found that, compared to
infants who did not receive SSC, infants at 3 months who received SSC as newborns had more
interest in novel stimuli, and at 6 months were more advanced in toy exploration and
shared attention with mother. Ohgi et al. (2002) found that infants at 6 months who had
previous SSC showed better orientation to social and non-social objects. At 12 months,
infants with SSC experience performed better on infant development scales than infants
without such experience (Feldman, Eidelman, et al., 2002; Ohgi et al., 2002; Tessier et
al., 1998). Multiple reasons have been proposed for why SSC early in life would facilitate
infants’ subsequent social cognitive development (Feldman, Eidelman, et al., 2002;
Feldman, Weller, et al., 2002). The post-birth period constitutes a sensitive period for
maternal contact in animal and human models (Field, 1995; Lehmann, Stohr, & Feldon, 2000;
Scafidi et al., 1990; Wigger & Neumann, 1999), and tactile and proprioceptive stimulation
are especially important during this time (Gottlieb, 1976, 1991). SSC improves infants’
state organization, particularly infants’ sleep/wake cycles, as well as improves stress
reactivity and physical maturation (Feldman, Weller, et al., 2002; Michelsson,
Christensson, Rothganger, & Winberg, 1996). Such early physiological and behavioral
regulation predicts later cognitive development (Beckwith & Parmelee, 1986; Doussard-
Roosevelt, Porges, Scanlon, Alemi, & Scanlon, 1997; Feldman, Greenbaum, Yirmiya, & Mayes,
1996; Sigman, Cohen, & Beckwith, 1997). The close proximity between mother and infant in
SSC also facilitates infants’ ability to recognize and respond to their mothers and
mothers’ ability to recognize and become familiar with their infants’ signals (Feldman,
2004). Mothers who are sensitive to their young infants’ signals engage in more frequent
and positive mother-infant interactions. Mothers who provide SSC for their infants report
more positive maternal feelings, positive perceptions of their infants, less depression,
and more empowerment in their parenting role (Affonso, Bosque, Wahlberg, & Brady, 1993;
Johnson, 2007; Neu, 1999; Roller, 2005; Tessier et al., 1998; Whitelaw, 1990). Although
most studies of the effects of SSC on maternal feelings and behavior have been conducted
only in the newborn period, some have shown increased maternal sensitivity and maternal
behaviors of holding, touch, and infant-directed speech throughout the infants’ first year
(Bigelow, Littlejohn, Bergman, & McDonald, 2010; DeChateau & Wiberg, 1977, 1984; Feldman,
Eidelman, et al., 2002). SSC promotes infants’ social cognitive development by affecting
infants’ behavioral and physiological regulation and mothers’ maternal behaviors (Feldman,
2004). Thus in mother-infant interactions, infants with SSC experience may have enhanced
understanding of the relation between their own actions and their mothers’ social
responsiveness to them. The Still Face Task has been used to examine infants’ awareness of
others’ social behavior toward them. This task, first reported in a seminal study by
Tronick and colleagues (Tronick, Als, Adamson, Wise, & Brazelton, 1978), has mothers or
other social partners engage infants in normal face-to-face interaction, then become
suddenly still and expressionless, and then resume normal interaction. Infants tend to
exhibit reduced visual attention and decreased positive affect, as demonstrated by changes
in smiling and non-distress vocalizations, during the still face phase compared to the
interactive phases. Such changes in the infants’ behavior, known as the still face effect,
have been shown in numerous studies, typically with infants between 2 and 9 months of age
(but see Bigelow & Power, 2012, below for effects in younger infants) and are found
regardless of procedural variations, such as length of the episodes (Adamson & Frick,
2003; Mesman, van IJzendoorn, & Bakermans-Kranenburg, 2009). Bigelow and Power (2012)
conducted a longitudinal quasi-experiment with Canadian infants in SSC and control groups
in which infants engaged with their mothers in the Still Face Task at ages 1 week, 1
month, 2 months, and 3 months. At 1 week, infants in both groups demonstrated the still
face effect with their visual attention that continued to be demonstrated at each of the
following ages, thus showing that even in the newborn period infants can detect changes in
their mothers’ interactive behavior. At 1 month, differences between the groups appeared.
Infants in the SSC group began responding to changes in their mothers’ behavior with their
affect, suggesting they were responding to violations of their expectations for affect
sharing. Infants in the control group did not show affect changes to the phases of the
Still Face Task until 2 months. At 3 months, infants in the SSC group increased their non-
distress vocalizations in the still face phase, indicative of social bidding to their non-
responsive mothers, whereas infants in the control group decreased their non-distress
vocalizations in the still face phase. SSC accelerated infants’ social expectations for
their mothers’ behavior and enhanced infants’ awareness of themselves as active agents in
eliciting social interactions with their mothers. A focus of the present study was to
investigate whether SSC would increase infants’ early expectations for the social
behaviors of others in a culture with proximal parenting practices. Although SSC studies
have been conducted in various cultural contexts, the focus in these contexts has
primarily been on the effects of SSC on infants’ neuro-physical adjustments shortly after
birth (see Mori et al., 2010, for meta-analysis including SSC studies from 18 different
countries). The findings from these studies show similar benefits of SSC to newborns’
physiological adaptations to postnatal life. However, the effect of SSC on infants’ social
expectations of others in cultures with different parenting goals and practices has been
less well researched. Ghana has a culture with proximal parenting practices. As in many
African countries, Ghanaian mothers carry their infants by wrapping them onto their backs
as they go about their daily chores or business. Infants sleep in the same bed with their
mothers and spend most of their day with their mothers, primarily wrapped on their
mothers’ backs. Frontal SSC is not the norm, yet mother-infant tactile contact is high
compared to mother-infant dyads in Western societies (Kärtner et al., 2008; Keller et al.,
2004). Ghanaian parenting goals and practices resemble those found in other West African
societies, of which the Nso of the Cameroon have been the most thoroughly studied. Kärtner
and colleagues (Kärtner et al., 2008; Kärtner, Keller, & Yovsi, 2010) compared Nso and
German mother-infant interactions. They found that Nso mothers were more directive in
their maternal interactions and had more physical contact with their infants. Nso infants
experienced less face-to-face interactions and reduced smiling and verbal turn-taking with
their mothers. Yet Nso infants experienced enhanced physical closeness with their mothers
due to being carried on their mother’s body and sleeping with her. Such practices by Nso
mothers facilitate proximal parenting goals of interdependence, such as obedience,
deference, and collective responsibility. Maternal responsiveness to their infants was
similar across the two cultures, albeit manifested differently. German mothers were more
visually responsive with gaze, smiles, and facial expressions; Nso mothers were more
tactually responsive with touch and physical stimulation (Kärtner et al., 2008, 2010).
These cultural differences emerged between the infants’ second and third month. Mothers in
both cultures responded readily to infants’ non-distress vocal signals. For German
mothers, maternal verbal responses are the norm; for Nso mothers, physical contact
responses are prevalent. Mother-infant verbal turn-taking may be less necessary when
physical closeness, such as being carried on the mother’s body, allows for ready physical
responsiveness (Mesman et al., 2018). Mother-infant interaction is a bidirectional process
in which each partner affects the other. Although this process begins at birth, it
increases around 2 months. This 2 month transition is thought to be due to infants’ neural
maturational processes and their experience with social partners who reinforce and
contingently respond to the infants’ social behaviors (Wörmann, Holodynski, Kärtner, &
Keller, 2012). Around 2 months of age, infants’ maturational processes allow them to
become more alert, to maintain posture and attention for longer periods, and to
systematically explore the internal features of the face (Haith, Bergman, & Moore, 1977;
Hopkins et al., 1990; Wolff, 1987). Infants become more aware and interested in social
partners at this time (Rochat, 2001). Infants’ visual attention, smiling, and non-distress
vocalizations increase (Spitz, 1965; Trevarthen, 1979; Wolff, 1987). They become more
responsive (Henning, Striano, & Lieven, 2005) and show effortful patterns of communication
(Lavelli & Fogel, 2002, 2005). Kärtner et al. (2010) found that Nso infants’ alertness
increased between 6 and 8 weeks, showing evidence of neural maturation associated with the
2 month transition. The culturally specific differences between German and Nso mothers’
responses to their infants occurred around this time. These cultural differences were due
primarily to changes in the way German mothers responded to their infants. Between
infants’ second and third months, German mothers reduced their tactile responses and
increased their gaze and facial responses to their infants, whereas Nso mothers continued
to respond to their infants with high levels of tactile responsiveness and did not
increase their visual responses. Nso mother-infant dyads engaged in mutual gaze less often
than German mother-infant dyads; nevertheless, when in face-to-face interaction, Nso
mothers smiled as much as German mothers and Nso infants at 6 weeks gazed and smiled at
their mothers as much as German infants at this age (Kärtner et al., 2010; Wörmann et al.,
2012).

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

Infants’ response to the Still Face Task appears to be robust in that it is found in
infants of varying ages and in normative and at-risk samples, yet very few studies have
conducted the task with infants in non-Western cultures (Mesman et al., 2009). To date
only three such studies have been published: Kisilevsky et al. (1998) tested 3 to 6 month
old infants in China, Hsu and Jeng (2008) tested 2 month old infants in Taiwan, and Yato
et al. (2008) tested 4 and 9 month old infants in Japan. Infants in these studies
responded to the task with the still face effect, similar to infants in Western cultures.
Yet participants in these studies were from urban, predominantly highly educated, middle-
to high-income families, where mother-infant interactive practices may be affected by
those of Western cultures. Education, with accompanying changes in income and living
standards, influences parenting goals toward independence and autonomy (Kağitçibaşi, 1996;
LeVine, Miller, Richman, & LeVine, 1996) as well as increases exposure to Western
parenting practices through international acquaintances and travel. To date, no study has
used the Still Face Task in an African culture where proximal parenting practices are
prevalent. Nevertheless, infants as they approach the 2 month transition may be responsive
to the changes in their mothers’ behavior during the task and SSC may accelerate infants’
affective responses to the task, as it did in the Bigelow and Power (2012) study. The
present study examined the effect of SSC experience on the behavior of Ghanaian mother-
infant dyads in the Still Face Task at the infant age of 6 weeks, when the infants were on
the cusp of the 2 month transition. Although at prenatal checkups women were informed
about SSC, the amount the Ghanaian mothers provided for their infants varied. The dyads
were subsequently divided based on a median split (Bigelow & Power, 2014) into those with
high and low SSC experience. Their behavior was compared to archival data from mother-
infant dyads in the Bigelow and Power (2012) study at the infant ages of 1 and 2 months.
Hypotheses were four: (1) Ghanaian infants with both high and low SSC experience would
show the still face effect with their visual attention, like the Canadian infants at both
1 and 2 months; (2) Ghanaian infants with high SSC experience, but not those with low SSC
experience, would show the still face effect with their affect, similar to the Canadian
infants at 1 month; (3) Ghanaian infants would show overall behaviors of visual attention,
smiling, non-distress vocalizations, frowning, and distress vocalizations that are
intermediate between those behaviors found in the Canadian infants at 1 and 2 months; and
(4) Ghanaian mothers would show more tactile and less verbal behaviors but similar visual
attention and smiling behaviors during the interactive phases of the Still Face Task
compared to the Canadian mothers.

        <hss>Ghanaian sample</hss>

        Mothers were recruited prior to the birth of their infants during prenatal visits
        at the Komfo Anokye Teaching Hospital, a large public hospital in Kumasi, the
        capital city of the Ashanti Region and the second largest city in Ghana. The
        Antenatal Clinic at Komfo Anokye Teaching Hospital serves pregnant women residing
        in the urban area and surrounding villages. The Ashanti Region adheres to a
        matrilineal tradition in which people have an attachment to villages of their
        mothers’ family. Pregnant women typically spend time in these villages prior to,
        and after, the birth of their infants. Thus traditional means of child care are
        prevalent for both urban and village women. Although English is the official
        language of Ghana, in the Ashanti Region Twi is the common language. All the
        communications with the mothers were conducted in Twi by native speakers. The
        participants were 26 infants (14 males) and their mothers. The mean age of the
        mothers at the infants’ birth was 28.1 years (SD = 4.0 years). The percentage of
        mothers with a university degree was 15%, 15% had some post-secondary training,
        31% had only a high school diploma, and 39% were without a high school diploma.
        The mothers were predominantly from the ethnic group Akan (92%) with a minority
        from Ewe (8%). For 40% of the mothers, this was their first child; 28% of the
        mothers had one previous child, and 32% of the mothers had two or more previous
        children. All the mothers had telephones, necessary for SSC reporting. The
        infants’ mean gestation age was 38.3 weeks (SD = 1.9 weeks). Their mean birth
        weight was 3005.3 g (SD = 489.3 g). The videotaped mother-infant Still Face Task
        was conducted at the infants’ 6 week checkup (M age = 46 days, SD = 5 days).

        <hss>Canadian sample</hss>

        The participants were 80 infants (38 males) and their mothers. Mothers were
        recruited prior to the birth of their infants through perinatal clinics at two
        hospitals with similar demographics in northeastern Canada. One hospital recruited
        for the SSC group and one hospital recruited for the control group. Approximately
        halfway through the study, the recruitment sites were switched; the former SSC
        site became the control site and vice versa. Dyads of the recruited mothers were
        included if the infants were over 37 weeks gestation age and had no medical
        problems. Twenty-eight dyads were in the SSC group and 52 dyads were in the
        control group. Socioeconomic status (SES) of the infants’ families was measured by
        a Canadian index (Blishen, Carroll, & Moore, 1987) based on education and income.
        In the index, occupations are divided into 514 groups, ranging in SES scores of
        17.81–101.75 (M = 42.74, SD = 13.28). The scores of the higher status parent in
        the infants’ families yielded a SES mean score of 50.41 (SD = 11.80). The mean age
        of the mothers at the infants’ birth was 29.7 years (SD = 5.0 years). The
        percentage of mothers with a university degree was 42%, 41% had some university
        education, 16% had only a high school diploma, and 1% were without a high school
        diploma. The racial-ethnic composition of the mothers was 99% non-Hispanic White
        and 1% Asian. For 47% of the mothers, this was their first child, 29% of the
        mothers had one previous child, and 24% of the mothers had two or more previous
        children. The infants’ mean birth weight was 3647.11 g (SD = 530.95 g). The
        videotaped mother-infant Still Face Tasks used for comparison with the Ghanaian
        mother-infant dyads were conducted when the infants were 1 month (M = 32 days, SD
        = 5 days) and 2 months (M = 64 days, SD = 8 days).

        <hss>In Ghana</hss>

        The study received ethical clearance from the first author’s university research
        ethics board. Women coming for prenatal checkups at Komfo Anokye Teaching Hospital
        were told about SSC, encouraged to provide SSC for their infants, and asked if
        they would be willing to participate in the study, which involved keeping daily
        records of the amount of SSC they provided for their infants through the infants’
        first month and engaging in a videotaped Still Face Task with their infants at the
        6 week checkup. Women who agreed to participate filled out demographic forms. The
        first author was notified when the participating mothers gave birth and was given
        access to the infants’ sex, birth weight, and gestation age. A research assistant
        telephoned participating mothers weekly through the infants’ first month to gather
        the daily records of amount of SSC the mothers provided during the previous week.
        At the infants’ 6 week checkup, the mother and infant engaged in the Still Face
        Task in a private room in the hospital. In the Still Face Task, the mother and
        infant sat facing each other approximately 50 to 60 cm apart. The infant sat in an
        infant car seat that was situated on a table. The mother sat in a chair that
        allowed her to be at eye level with the infant. Behind and to the side of the
        infant was an upright mirror (60 cm × 40 cm) in a frame that could be angled to
        reflect the mother seated opposite the infant. The angle was typically 70–75°. The
        research assistant videotaping the Still Face Task was behind and to the side of
        the mother, out of the direct view of the mother and infant. The videotape
        recorded the infant (full frontal body) and the mother’s reflection (frontal body
        from the waist up). The Still Face Task consisted of three phases that
        sequentially followed each other without pause: initial interactive phase, still
        face phase, reunion phase. For the initial interactive phase, the mother was asked
        to interact with her infant as she wished for two minutes. For the still face
        phase, she was asked to become still with a neutral expression, looking at her
        infant but not talking or touching the infant for one minute. For the reunion
        phase, the mother was asked to interact with her infant again as she wished for
        two minutes. The research assistant gave the mother a verbal cue at the beginning
        of each phase and at the end of the task. The behavior of the mother and infant
        was scored in the lab of the second author on the Observer Video-Pro 5.0 (Noldus
        Information Technology, 2003) computer software program by a coder blind to the
        amount of SSC mothers provided. Infants were scored for duration of visual
        attention, and positive and negative affect in facial expressions (smiles, frowns)
        and in vocalizations (non-distress vocalizations, distress vocalizations) during
        each of the three phases of the Still Face Task. Visual attention was scored as
        the presence or absence of looking at the mother’s face. Smiles were scored as
        upward lip movements with or without vocalizations. Frowns were downward lip
        movements with or without vocalizations. Non-distress vocalizations excluded
        distress vocalizations (fussing, crying) and digestive sounds (e.g., burps,
        hiccups). Distress vocalizations excluded non-distress vocalizations and digestive
        sounds. The duration times were converted to percentage of time within each phase.
        Mothers were scored for duration of visual attention to the infant’s face, smiles,
        vocalizations, and physical contact with their infants during the two interactive
        phases of the task. Mothers’ vocalizations, which were all non-distress
        vocalizations, were further coded as arousing (energetic, highly stimulating) or
        neutral (excluding arousing vocalizations). Mothers’ physical contact with their
        infants was coded as arousing (e.g., pumping the infant’s legs), attention getting
        (e.g., tapping the infant’s face when not looking at mother), soothing (e.g.,
        gentle stroking), adjusting (e.g., repositioning infant), or passive holding
        (e.g., hands passively on infant’s body). The duration times were converted to
        percentage of time within the interactive phases. The coder was blind to the
        amount of SSC the mothers provided. Coding of the infant and mother behaviors
        followed that of previous studies (e.g., Bigelow, 1998; Bigelow & Power, 2012;
        Bigelow & Walden, 2009), with the addition of mothers’ type of vocalizations
        (arousing, neutral) and physical contact (arousing, attention getting, soothing,
        adjusting, passive holding). For reliability purposes, a second coder, who was
        also blind to the amount of SSC mothers provided, independently scored the
        behaviors of 19% of the dyads. For infant and mother behaviors, the range of
        intraclass correlations, absolute type with raters random, was between .821 and
        .997 (all p ≤ .01).

        <hss>In Canada</hss>

        After the study received ethical clearance from the two participating hospitals
        and the second author’s university research ethics board, the perinatal clinics in
        the two hospitals distributed Consent to be Contacted Forms to pregnant women in
        the third trimester of their pregnancy. The women who signed the form were
        contacted by a research assistant, who explained the study. Mothers who agreed to
        participate had notices put on their medical charts so that attending nurses would
        notify the research assistants when the women gave birth. Research assistants (N =
        8) visited the mother-infant dyads in their homes when the infants were 1 week, 1
        month, 2 months, and 3 months. Mothers were seen by the same research assistant
        from the contact interview through the data collection visits. Mothers in the SSC
        group were requested to provide six hours of SSC with their infants cumulative
        throughout the day during the infants’ first week, and then two hours per day
        until the infants were one month. No request for mother-infant SSC was made to
        control group mothers. Mothers in both the SSC and control groups recorded the
        amount of SSC they provided to their infants each day and records were collected
        at each visit. The present report presents the results from the Still Face Task
        conducted in the home when the infants were 1 month and 2 months of age. The setup
        and procedure of the Still Face Task was identical to that done in Ghana with the
        exception that the initial interactive phase lasted for 3 min. Coding of the
        mothers and infants was done in the lab of the second author as described in the
        Ghana sample by a coder blind to whether the dyads were in the SSC or control
        groups. For reliability purposes, a second coder, who was also blind to whether
        the dyads were in the SSC or control group, independently scored the behaviors of
        13% of the dyads. For infant and mother behaviors, the range of intraclass
        correlations, absolute type with raters random, was between .824 and .999 (all p ≤
        .01).

<hs>  Plan of analysis</hs>
  ~~~~~~~~~~~~~~~~

In preliminary analyses, analyses of variance (ANOVAs) were conducted on the demographics
of the Ghanaian mothers and infants in the high and low SSC groups and on the demographics
of the Canadian mothers and infants in the SSC and control groups. ANOVAs also compared
the amount of SSC the Ghanaian mothers in the high and low SSC groups did in their
infants’ first week and in their infants’ weeks 2 through 4 with the amount of SSC the
Canadian mothers in the SSC and control groups did in their infants’ first week and in
their infants’ weeks 2 through 4. To test Hypotheses 1 and 2, mixed ANOVAs with the
repeated variable phase (initial interactive, still face, reunion) and the between
variable SSC group (high, low) were conducted on Ghanaian infants’ visual attention
(Hypothesis 1) and smiles, non-distress vocalizations, frowns, and distress vocalizations
(Hypothesis 2) during the Still Face Task. Significant group x phase interactions were
followed by t-test pairwise comparisons. Similar ANOVAs (between variable group: SSC,
control) and follow-up comparisons were conducted on the Canadian infants’ behaviors at 1
month and at 2 months. To test Hypothesis 3, ANOVAs with the between variable country
(Ghana, Canada) compared the overall infant behaviors during the Still Face Task of
Ghanaian infants (visual attention, smiles, non-distress vocalizations, frowns, distress
vocalizations) with those behaviors of Canadian infants at 1 month and at 2 months. To
test Hypothesis 4, ANOVAs with the between variable country (Ghana, Canada) compared the
Ghanaian mothers’ behaviors toward their infants (visual attention, smiles, vocalizations,
physical contact) during the interactive phases of the task with these behaviors of the
Canadian mothers when their infants were 1 month and 2 months. Follow-up ANOVAs (between
variable country: Ghana, Canada) compared the Ghanaian mothers’ type of vocalizations
(arousing, neutral) and type of physical contact with their infants (arousing, attention
getting, soothing, adjusting, passive holding) with those of the Canadian mothers when
their infants were 1 month and 2 months.

<hs>  Preliminary analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Dyads in the Ghanaian sample were divided into high and low SSC groups based on a median
split of the amount of SSC reported during the infants’ first month. ANOVAs conducted on
the demographics of the mothers and infants indicated there was no significant difference
between the mothers in the high and low SSC groups in maternal age, education, or number
of previous births; or in their infants’ sex, gestation age, or birth weight. For the
dyads in the Canadian sample, ANOVAs conducted on the demographics of the mothers in the
SSC and control groups indicated there were no significant differences between the groups
in maternal education, number of previous births, or SES, although the mothers in the SSC
group were slightly older (M = 32.0 years, SD = 5.5 years) than the mothers in the control
group (M = 28.4 years, SD = 4.1 years). Infants in the SSC and control groups did not
differ in sex, gestation age, or birth weight. Table 1 shows the amount of SSC the
Ghanaian mothers in the high SSC and low SSC groups and the Canadian mothers in the SSC
and control groups provided for their infants in the infants’ first week and in the weeks
2 through 4. There was no significant difference in the amount of SSC provided by Ghanaian
and Canadian mothers in their infants’ first week either in the Ghanaian high SSC group
and the Canadian SSC group or in the Ghanaian low SSC group and the Canadian control
group. However, in the infants’ weeks 2 through 4, Ghanaian mothers provided more SSC in
the high SSC group than Canadian mothers provided in the SSC group, F (1, 38) = 31.29, p <
.001, ηp2 = .452, and Ghanaian mothers in the low SSC group provided more SSC than the
Canadian mothers did in the control group, F (1, 62) = 58.54, p < .001, ηp2 = .486, but
less SSC than Canadian mothers did in the SSC group, F (1, 38) = 16.44, p < .001, ηp2 =
.302. Fig. 1 shows infants’ behaviors (visual attention, smiling, non-distress
vocalizations, frowning, distress vocalizations) across the phases of the Still Face Task
for the Ghanaian infants at 6 weeks and the Canadian infants at 1 and 2 months.

<hs>  Hypothesis 1: Ghanaian infants with both high and low SSC experience would show the still face effect with their visual attention, like the Canadian infants at 1 and 2 months</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mixed ANOVAs with the repeated variable phase (initial interactive, still face, reunion)
and between variable SSC group (high, low) conducted on the Ghanaian infants’ duration of
visual attention showed a significant main effect for phase, F (2, 48) = 5.05, p = .010,
ηp2 = .174, indicating the still face effect, with no group main effect or interaction
effect. The Canadian infants showed similar results from mixed ANOVAs with the repeated
variable phase (initial interactive, still face, reunion) and the between variable group
(SSC, control) conducted on the infants’ visual attention at 1 and 2 months. At 1 month,
the Canadian infants’ visual attention showed a significant main effect for phase, F (2,
152) = 4.65, p = .011, ηp2 = .058, with no group main effect or interaction effect. These
results were replicated at 2 months (phase main effect: F (2, 146) = 18.34, p < .001, ηp2
= .201). As can be seen in Fig. 1a, the Ghanaian infants, like the Canadian infants at 1
and 2 months, discriminated between the phases of the Still Face Task with their visual
attention.

<hs>  Hypothesis 2: Ghanaian infants with high SSC experience, but not those with low SSC experience, would show the still face effect with their affect, similar to the Canadian infants at 1 month</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mixed ANOVAs with the repeated variable phase (initial interactive, still face, reunion)
and between variable SSC group (high, low) were conducted on the Ghanaian infants’
duration of smiling, non-distress vocalizations, frowning, and distress vocalizations
during the Still Face Task. For smiling, there was a significant main effect for phase, F
(2, 48) = 4.31, p =  .019, ηp2 = .152, and significant phase x group interaction, F (2,
48) = 3.50, p = .038, ηp2 = .127, with no group main effect. Fig. 2 shows the infants’
smiling across the phases for the Ghanaian infants in the high and low SSC groups. The
analysis was redone after adjusting for outliers (n = 2 in initial interactive phase, n =
1 in still face phase, n = 2 in reunion phase) by Winsorizing (replacing the outlier’s
data with the next closest participant’s data that is not an outlier). The results were
unchanged. Ghanaian infants with high SSC experience, but not those with low SSC
experience, showed the still face effect with their smiling. There were no significant
effects between the Ghanaian infants in the high and low SSC groups for non-distress
vocalizations, frowning, or distress vocalizations. Similar ANOVAs were conducted on the
Canadian infants’ duration of smiling, non-distress vocalizations, frowning, and distress
vocalizations during the Still Face Task at 1 and 2 months. For smiling, the Canadian
infants at 1 month showed a main effect for phase F (2, 152) = 3.36, p = .037, ηp2 = .042,
indicating a linear decline over the phases, with no main effect for group or interaction
effect (see Fig. 1b). However at 2 months, the Canadian infants’ smiling showed a
significant main effect for phase, F (2, 146) = 19.98, p < .001, ηp2 = .215, indicating
the still face effect, with no group main effect or interaction effect (see Fig. 1b). Thus
Canadian infants in both the SSC and control groups did not discriminate between the
phases of the Still Face Task with their smiling at 1 month, but infants in both the SSC
and control groups did so at 2 months. However, at 1 month the Canadian infants in the SSC
group, but not those in the control group, showed the still face effect with their non-
distress vocalizations. A mixed ANOVA yielded a main effect for phase, F (2, 152) = 6.86,
p = .001, ηp2 = .083, and a phase x group interaction, F (2, 152) = 3.85, p = .023, ηp2 =
.048. Infants in the SSC group showed the still face effect with their non-distress
vocalizations at 1 month (initial interactive: M = 9.9, SD = 18.4; still face: M = 2.4, SD
= 3.9; reunion: M = 4.6, SD = 6.3), whereas infants in the control group did not (initial
interactive: M = 3.9, SD = 4.3; still face: M = 2.8, SD = 4.3; reunion: M = 3.3, SD =
4.7). Thus like the Ghanaian infants in the high SSC group, the Canadian infants in the
SSC group prior to 2 months of age demonstrated the still face effect with their affect.
The Canadian infants increased their negative affect with their frowns and distress
vocalizations through the phases of the task at both 1 and 2 months, as can be seen in
Fig. 1d and e. At both ages, infants showed a phase effect for frowns (1 month: F (2, 152)
= 4.711, p = .010, ηp2 = .058; 2 months: F (2, 146) = 6.262, p = .002, ηp2 = .079) and for
distress vocalizations (1 month: F (2, 152) = 5.686, p = .004, ηp2 = .070; 2 months: F (2,
146) = 6.818, p = .001, ηp2 = .085), indicating an increase in negative affect from the
initial interactive phase to the still face phase that remained or increased at the
reunion phase.

<hs>  Hypothesis 3: Ghanaian infants would show overall behaviors of visual attention, smiling, non-distress vocalizations, frowning, and distress vocalizations that are intermediate between those behaviors found in the Canadian infants at 1 and 2 months</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fig. 3 shows the duration of visual attention, smiling, non-distress vocalizations,
frowning, and distress vocalizations during the Still Face Task for the 6-week-old
Ghanaian infants and the Canadian infants at 1 month and 2 months. ANOVAs comparing the
Ghanaian infants with the Canadian infants at 1 month indicated there was no significant
difference in visual attention or smiling between the Ghanaian infants and the Canadian
infants, but the Canadian infants were making more non-distress vocalizations, F (1, 97) =
5.49, p = .021, ηp2 = .054, frowning more, F (1, 97) = 19.61, p < .001, ηp2 = .168, and
making more distress vocalizations, F (1, 97) = 14.62, p <  .001, ηp2 = .131. ANOVAs
comparing the Ghanaian infants with the Canadian infants at 2 months indicated that the
Canadian infants were attending more, F (1, 99) = 13.87, p < .001, ηp2 = .123, smiling
more, F (1, 99) = 10.25, p = .002, ηp2 = .094, making more non-distress vocalizations, F
(1, 99) = 25.28, p < .001, ηp2 = .203, frowning more, F (1, 99) = 11.04, p = .001, ηp2 =
.100, and making more distress vocalizations, F (1, 99) = 6.88, p = .010, ηp2 = .065. When
analyses were redone adjusting for outliers (n = 2 for smiles; n = 1 for non-distress
vocalizations; n = 3 for frowns; n = 3 for distress vocalizations) by Winsorizing, the
results were unchanged. Thus, rather than showing overall behaviors that were between the
amounts shown by the Canadian infants at 1 and 2 months, Ghanaian infants at 6 weeks
showed visual attention and smiling behaviors comparable with the Canadian infants at 1
month, but showed less non-distress vocalizations, frowns, and distress vocalizations than
Canadian infants at 1 or 2 months.

<hs>  Hypothesis 4: Ghanaian mothers would show more tactile and less verbal behaviors but similar visual attention and smiling behaviors during the interactive phases of the Still Face Task compared to the Canadian mothers</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fig. 4 shows mothers’ duration of visual attention, smiling, vocalizing, and physical
contact with their infants during the interactive phases of the Still Face Task for the
Ghanaian mothers and for the Canadian mothers at the 1 and 2 month visits. ANOVAs
indicated there was no significant difference in the duration of attention, vocalizations,
or physical contact with their infants for the Ghanaian mothers and the Canadian mothers
at the 1 or 2 month visits. Ghanaian mothers smiled more to their infants than Canadian
mothers did at the 1 month visit, F (1, 104) = 12.10, p < .001, ηp2 = .111, but there was
no significant difference in the Ghanaian mothers’ smiling and the Canadian mothers’
smiling at the 2 month visit. Analyses adjusted for outliers (n = 1 for gaze; n = 1 for
vocalizations) by Winsorizing did not change the findings. However, the Ghanaian and
Canadian mothers differed on the type of vocalizations and physical contact they did with
their infants during the interactive phases of the Still Face Task. Fig. 5 shows the
mothers’ vocalizations coded as arousing and neutral. Ghanaian mothers’ vocalizations were
more arousing than the Canadian mothers’ vocalizations at the 1 month visit, F (1, 97) =
283.62, p <  .001, ηp2 = .745, and at the 2 month visit, F (1, 99) = 200.87, p < .001, ηp2
= .670. Canadian mothers’ vocalizations were more neutral at both the 1 month, F (1, 97) =
159.04, p <  .001, ηp2 = .621, and 2 month visits, F (1, 99) = 184.39, p <  .001, ηp2 =
.651 than the Ghanaian mothers’ vocalizations. When adjusted for outliers (n = 3 for
neutral vocalizations) by Winsorizing, results did not change. Fig. 6 shows the mothers’
physical contact with their infants coded as arousing, attention getting, soothing,
adjusting, and passive holding. Ghanaian mothers provided more arousing physical contact
with their infants than Canadian mothers at the 1 month visit, F (1, 97) = 124.22, p <
.001, ηp2 = .562, and at the 2 month visit, F (1, 99) = 99.48, p < .001, ηp2 = .501.
Ghanaian mothers did less attention getting physical contact than Canadian mothers did at
the 1 month visit, F (1, 97) = 10.95, p = .001, ηp2 = .101, but there was no difference at
the 2 month visit. Ghanaian mothers did less soothing physical contact than Canadian
mothers did at the 1 month visit, F (1, 97) = 9.11, p = .003, ηp2 = .086, and at the 2
month visit, F (1, 99) = 5.53, p =  .021, ηp2 = .053. Ghanaian mothers’ amount of
adjusting physical contact was similar to that of Canadian mothers at the 1 month visit,
but they did more than Canadian mothers at the 2 month visit, F (1, 99) = 7.13, p =  .009,
ηp2 = .067. Ghanaian mothers did less passive holding than Canadian mothers did at the 1
month visit, F (1, 97) = 41.75, p < .001, ηp2 = .301, and at the 2 month visit, F (1, 99)
= 35.21, p <  .001, ηp2 = .262. When analyses were redone adjusting for outliers (n = 3
for attention getting; n = 2 for soothing; n = 4 for adjusting; n = 2 for passive holding)
by Winsorizing, the only changes in the results were that Ghanaian mothers had less
attention getting physical contact than Canadian mothers at the 2 month visit, and
Ghanaian mothers and Canadian mothers at the 2 month visit had similar amounts of
adjusting physical contact. As a check to determine whether SSC affected the mothers’
behavior during the Still Face Task, ANOVAs with the between variable group (high SSC, low
SSC) were conducted on the Ghanaian mothers’ visual attention, smiling, vocalizations, and
physical contact with their infants during the task. There were no significant differences
between the groups for any of the behaviors. Likewise, ANOVAs with the between variable
group (SSC, control) were conducted on the Canadian mothers’ visual attention, smiling,
vocalizations, and physical contact with their infants during the task at the 1 month and
2 month visits. Only the ANOVA for maternal physical contact at the 1 month visit showed a
significant group effect, F (1, 76) = 6.52, p = .013, ηp2 = .079, indicating mothers in
the control group provided more physical contact (M = 81.8, SD = 16.7) during the Still
Face Task than mothers in the SSC group (M = 67.3, SD = 31.4). Follow-up ANOVAs were
conducted on the type of physical contact mothers provided for their infants at the 1
month visit. Control group mothers provided more passive holding (F (1, 76) = 6.09, p =
.016, ηp2 = .074; SSC group M = 31.8, SD = 28.0; control group M = 47.0, SD = 24.6) and
SSC group mothers provided more soothing physical contact (F (1, 76) = 4.51, p = .037, ηp2
= .056; SSC group M = 17.2, SD = 24.7; control group M = 8.1, SD = 13.5). Ghanaian mothers
and Canadian mothers were similar in the amount of attention, smiling, vocalizing, and
physical contact directed toward their infants during the interactive phases of the Still
Face Task, with the exception that Ghanaian mothers smiled more than Canadian mothers at
the 1 month visit. However, Ghanaian mothers were more arousing in their vocalizations and
physical contact with their infants than Canadian mothers. Canadian mothers’ vocalizations
were more neutral and their physical contact with their infants was used for more
attention getting, soothing, and passive holding. Adjusting physical contact was minimal
for both groups.

<h>DISCUSSION</h>
----------

Ghanaian mother-infant dyads at the infant age of 6 weeks showed both similarities and
differences in their interactions in the Still Face Task compared to Canadian mother-
infant dyads at the infant ages of 1 and 2 months. Importantly, Ghanaian infants with high
SSC experience, but not those with low SSC experience, showed affect responses to their
mothers’ changing behavior during the task in ways that were similar to Canadian infants
in the SSC group at 1 month. Ghanaian infants in both the high and low SSC groups showed
the still face effect with their visual attention, providing support for the first
hypothesis. The Canadian infants at 1 and 2 months also showed the still face effect with
their visual attention. Young infants from both cultural contexts demonstrated with their
attention that they detected changes in the mothers’ behavior. Indeed, Bigelow and Power
(2012), who longitudinally followed the Canadian infants from 1 week to 3 months of age,
found that even at 1 week the infants showed the still face effect with their attention.
Although few other studies have used the Still Face Task with newborns, the ones that have
done so indicate that infants reduce their attention from the initial interactive phase to
the still face phase (Bertin & Striano, 2006; Ellsworth, 1987, cited in Muir & Hains,
1993; Nagy, 2008). Thus infants show evidence of detecting changes in their mothers’
interactive behavior from the beginning of life. Ghanaian infants with high SSC
experience, but not those with low SSC experience, showed the still face effect with their
affect. They smiled more in the interactive phases than the still face phase, providing
support for the second hypothesis. Researchers speculate that the systems that regulate
infants’ attention and affect operate differently during face-to-face interactions
(Bigelow & Walden, 2009; Legerstee & Varghese, 2001; Nadel, Soussignan, Canet, Libert, &
Gerardin, 2005). They propose that changes in infants’ visual attention during the Still
Face Task indicate infants’ detection of changes in their mothers’ behavior, whereas
changes in infants’ affect indicate they are responding to violations of their
expectations for affect sharing, which develops later than infants’ ability to detect
changes in their mothers’ behavior. Ghanaian infants with high amounts of SSC affectively
responded to their mothers’ changing behavior during the Still Face Task, suggesting SSC
accelerated the infants’ expectations for affect sharing. For Canadian infants, there was
no evidence of the still face effect for smiling at 1 month, however by 2 months, infants
in both the SSC and control groups showed the still face effect with their smiling, which
is evidence of the 2 month transition when infants become more interested and
participatory social partners (Henning et al., 2005; Lavelli & Fogel, 2002, 2005; Rochat,
2001). Yet Canadian infants in the SSC group at 1 month showed the still face effect with
their affect via their non-distress vocalizations. Although smiling is the most frequently
used measure of infants’ positive affect, infants’ non-distress vocalizations convey their
emotional reactions and are the primary social signals that elicit maternal communication
(Hsu & Fogel, 2001; Keller, Lohaus, Volker, Cappenberg, & Chasiotis, 1999; Papousek, 1989;
Van Egeren, Barratt, & Roach, 2001). Mothers use these vocalizations as signals for
determining infants’ readiness to interact and for adjusting their own emotional response.
Thus both Ghanaian and Canadian infants with high SSC experience responded to the Still
Face Task with their affect prior to 2 months of age. Why would Ghanaian infants’ early
affect response to the Still Face Task be with smiling and Canadian infants’ early affect
response be with non-distress vocalizations? Kärtner et al. (2008, 2010) found that the
Nso mothers of the Cameroon were as contingently responsive to their infants as German
mothers, but their predominant mode of responsiveness was expressed through physical
contact. German mothers responded contingently to their infants primarily visually with
gaze, smiles, and facial expressions and with verbal turn-taking. Nso mother-infant dyads
engaged less in face-to-face interactions with periods of mutual gaze. Thus Nso infants
experienced their mothers’ smiling during maternal interactions less often. Yet when Nso
mothers were in mutual gaze with their infants, they smiled as much as German mothers. The
Still Face Task involves mother-infant face-to-face interaction with mutual gaze. Sroufe
(1996) proposed that the emergence of social smiling is facilitated by infants’
recognition of others’ contingent responsiveness to their behavior, not only in face-to-
face contexts but also in contexts of other modalities, such as body contact or
stimulation. SSC has been shown to facilitate mothers’ responsiveness to their infants’
signals as well as infants’ sensitivity to their mothers’ behavior toward them (Feldman,
2004; Feldman, Eidelman, et al., 2002). Such increases in mother-infant reciprocity may
explain the Ghanaian infants in the high SSC group being more reactive with their smiling
to their mothers’ changing behavior during the task. Canadian infants would have more
face-to face experience with their mothers in which verbal turn-taking is prevalent.
Although mothers also smile responsively in face-to-face interactions with their infants,
mothers’ vocal responsiveness may be more easily noticed. Young infants’ smiling is
instigated by maternal smiling (Kaye & Fogel, 1980), therefore infants’ smiles tend to
overlap with mothers’ smiles. In Western societies where mother-infant vocal turn-taking
is prevalent, when infants vocalize, overlap with maternal talking is minimal (Bigelow,
MacLean et al., 2010; Bornstein et al., 1992). Mothers tend to stop talking and resume
after infant vocalizations have ended, resulting in vocal turn-taking. Infants who
experience such turn-taking may recognize their mothers’ responsiveness more readily with
vocalizations than with smiles. Interestingly, SSC experience affected infants’ behavior
toward their mothers in the Still Face Task, yet SSC did not influence the behavior of the
mothers toward their infants during the task. Ghanaian mothers in both high and low SSC
groups showed similar behavior toward their infants. Canadian mothers in SSC and control
groups also showed similar behavior toward their infants, with the exception that mothers
in SSC and control groups differed in the amount of physical contact with their infants
during the Still Face Task at 1 month. Mesman et al. (2009) indicate that the history of
infants’ experience with their mothers is an important aspect affecting infants’ response
to the Still Face Task. The findings suggest that the infants’ history of SSC experience
with their mothers was a significant factor influencing the infants’ response to the task.
Ghanaian infants’ overall duration of attention and smiling during the Still Face Task
paralleled the overall duration of those behaviors by the Canadian infants at 1 month,
rather than at 2 months. Kärtner et al. (2010) found that, although Nso infants experience
less mutual gaze with their mothers, when in face-to-face interaction with their mothers,
Nso infants at 6 weeks gazed and smiled at their mothers as much as German infants at this
age (Wörmann et al., 2012). The Ghanaian infants, however, engaged in less non-distress
vocalizing than the Canadian infants at 1 month, possibly because the Canadian infants in
the SSC group at 1 month were already responding to the Still Face Task with their non-
distress vocalizations. By 2 months, the Canadian infants engaged in more attention,
smiling, and non-distress vocalizing than the Ghanaian infants. In comparing German and
Nso mothers’ interactions, cultural differences in the modes of maternal responsiveness
emerged in the infants’ second and third months (Kärtner et al., 2010). The divergence was
mostly due to German mothers decreasing their tactile responsiveness and increasing their
visual responses of gaze, smiles, and facial expressions; whereas Nso mothers maintained
their high level of tactile responsiveness with little increase in visual responses.
Mother-infant interactions are transactional in that both partners influence each other.
Yet mothers are primarily responsible for establishing and maintaining interactions with
their infants, particularly in the infants’ early life (Henning & Striano, 2011; Kaye &
Fogel, 1980). Ghanaian infants’ experience of maternal responsiveness may be more similar
to that of Canadian infants at 1 month, prior to the divergence of cultural modes of
maternal responsiveness, than that of Canadian infants at 2 months. Notably, Ghanaian
infants differed from Canadian infants at both 1 and 2 months in distress, as expressed in
frowns and distress vocalizations of fussiness and crying. Ghanaian infants were less
distressed during the Still Face Task. Proximal parenting cultures value calmness in
infants and the suppression of negative affect (Keller & Otto, 2009). Mothers in both
Western and non-Western cultures tend to respond readily to infant distress (Mesman et
al., 2018). Yet the physical closeness of Ghanaian mother-infant dyads, through mothers
carrying their infants and sleeping with them, facilitates the mothers’ prompt response
to, and anticipation of, infant distress, which promotes mothers’ nurturance of calmness
in their infants. Ghanaian and Canadian mothers were similar in the amount of infant
directed behaviors they provided during the interactive phases of the Still Face Task. Nso
mothers were found to smile as much as German mothers when in mutual gaze with their
infants, despite mutual gaze being less frequent for Nso mother-infant dyads (Kärtner et
al., 2010; Wörmann et al., 2012). The Still Face Task involves face-to-face interaction in
which mutual mother-infant gaze is prevalent. In this context, the amount of maternal
attention, smiling, vocalizing, and physical contact was similar for Ghanaian and Canadian
mothers, even though Ghanaian mothers smiled more than Canadian mothers when their infants
were 1 month. However, the mothers’ type of vocalizations and physical contact with their
infants differed. Ghanaian mothers’ vocal and physical contact behaviors were more
arousing. Their vocalizations tended to be boisterous rhythmic sounds, energetic and
repetitive infant greetings and singing. These vocal behaviors were accompanied by moving
the infants’ limbs in rhythm with the vocalizations. Maternal touch is important in
regulating infant emotion. In Western societies, mothers use touch to reduce distress and
elicit positive affect (Stack & Arnold, 1998; Stack & Muir, 1992). Canadian mothers’
tactile behavior was most often used for soothing the infant, getting the infant’s
attention, or simply passively touching the infant, and their vocalizations were less
stimulating. Mothers from proximal caretaking cultures of West Africa have been described
as treating their infants as novices who need to learn compliance and subordination
(Kärtner et al., 2010). Mothers are directive in this process, which influences the ways
in which they engage with their infants. Mothers tend to lead the interaction rather than
follow the infant; synchrony rather than reciprocity is prominent, which promotes the
cultural goals of interdependency and relatedness (Keller et al., 2004). Mother-infant
interaction is characterized by rhythmic structuring with musical chorusing and repeated
greetings, synchronized with rhythmic body stimulation. These modes of interaction were
seen in the Ghanaian mothers’ behaviors in the interactive phases of the Still Face Task.
Ghanaian infants were primarily calmly attentive to these energetic behaviors of their
mothers. There are several limitations to the study. The Ghanaian mothers, coming from a
proximal parenting culture, were less accustomed to face-to-face interactions with their
infants (Kärtner et al., 2008; Keller, 2007; Keller et al., 2004), which may have affected
the way in which they vocally and tactually engaged with their infants during the
interactive phases of the Still Face Task. Yet the Ghanaian mothers’ behavior was similar
to that described by other researchers studying mother-infant engagement during
naturalistic face-to-face interactions in West African cultures (Kärtner et al., 2010).
Although the study examined Ghanaian mothers’ behaviors toward their infants during the
Still Face Task, the study did not assess the mothers’ contingent responsiveness to their
infants’ behavior. Mothers from West African societies tend to be predominantly tactually
responsive to their infants, but not necessarily while in mutual gaze with their infants
(Kärtner et al., 2008, 2010). Thus, to assess Ghanaian mothers’ contingent responsiveness
would require measuring their tactile responsiveness during naturalistic mother-infant
interactions, which is beyond the scope of the current data. The amount of daily SSC
Ghanaian and Canadian mothers provided for their infants during the infants’ first month
was based on mothers’ self reports. It is possible that the mothers did not accurately
report the amount. The sample size of Ghanaian mother-infant dyads was small, which
reduces the power of analyses, particularly in finding significant results. That
significant results were obtained with the limited sample size suggest the findings are
robust. Yet the size of the sample limits the interpretation of the results. The Ghanaian
mother-infant dyads were seen in a cross-sectional study at the infant age of 6 weeks,
whereas the Canadian archival data to which they were compared come from a longitudinal
study at the infant ages of 1 and 2 months. Both studies examined the effect of SSC on
infants’ response to the Still Face Task prior to the 2 month transition; and the Canadian
study is the only known SSC study utilizing the Still Face Task in Western culture with
infants at ages comparable to the Ghanaian infants. Nevertheless, the differences in the
study designs may have affected the results found between the two cultures. The length of
the initial interaction differed slightly in the Ghanaian and Canadian studies (2 min and
3 min, respectively), although length of episodes has been shown to have little effect on
infants’ response to the task (Adamson & Frick, 2003; Mesman et al., 2009). The infants
were seated in a car seat for the Still Face Task, which may have been novel for some of
the Ghanaian infants as the use of car seats is not necessarily common practice in Ghana.
Yet the Ghanaian infants did not resist the seat and did not seem distracted by it.
Ghanaian mothers’ demographics differed from those of the Canadian mothers, which may have
affected their maternal behaviors. However, the demographics of the Ghanaian mothers are
prototypical of their cultural context, and thus are interwoven with their parenting goals
and practices. Despite cultural differences in how mothers engaged with their infants,
mother-infant SSC facilitated infants’ early expectations for their mothers’ behavior.
Ghanaian infants with high SSC experience, on the cusp of the 2 month transition,
responded with their smiling to changes in their mothers’ behavior during the Still Face
Task, just as Canadian infants in the SSC group prior to 2 months responded with their
affect to their mothers’ behavioral changes during the task. In both cultures, SSC
enhanced infants’ ability to emotionally respond to their mothers’ social behavior,
suggesting acceleration of the infants’ developing expectations for their mothers’
engagement.

<h>FUNDING</h>
-------

This research was aided by a grant from the Bill and Melinda Gates Foundation to the first
(Principal Investigator) and second authors and by a grant from the Nova Scotia Health
Research Foundation to the second author. The funders had no involvement in the design,
conduction, or writing of the report. Gratitude is expressed to Yasmin Mohammed, Jan
Hanifen, Gerry Cameron, Rachel MacFarlane, Mena Enxuga, Jennifer Delaney, Yvonne
MacDonald, Cynthia Flannigan, Lynne Lukeman, Dale Fewer, Charlene Kennedy-Chisholm, Chow
Shim Pang, Laura Walden, Caitlin Best, and Madison Links, who were research assistants;
and to the mothers and infants who participated in the study.


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<ART>The effect of motor load on planning and inhibition in developmental coordination disorder
================================================================================

Authors: Michelle L. Pratt, Hayley C. Leonard, Hanna Adeyinka, Elisabeth L. Hill
DOI: 10.1016/j.ridd.2014.04.008
Year: 2014  |  Pages: 1579-1587
ASJC codes: 3203, 3204
Keywords: Developmental coordination disorder, Executive function, Inhibition, Motor development, Planning

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<h>ABSTRACT</h>
--------

Previous research has reported mixed findings regarding executive function (EF) abilities in developmental coordination disorder (DCD), which is diagnosed on the basis of significant impairments in motor skills. The current study aimed to assess whether these differences in study outcomes could result from the relative motor loads of the tasks used to assess EF in DCD. Children with DCD had significant difficulties on measures of inhibition and planning compared to a control group, although there were no significant correlations between motor skills and EF task performance in either group. The complexity of the response, as well as the component skills required in EF tasks, should be considered in future research to ensure easier comparison across studies and a better understanding of EF in DCD over development. © 2014 Elsevier Ltd.

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<h>INTRODUCTION</h>
------------

Executive function (EF) is an umbrella term that includes a range of top-down processes of
cognitive control, characterised by Miyake, Friedman, Emerson, Witzki, and Howerter (2000)
as comprising three core functions, namely response inhibition, shifting between tasks or
mental sets, and updating/monitoring of working memory representations. These core
functions provide the basis for higher-order functions such as planning and reasoning
(Diamond, 2013). EFs develop over a protracted period, emerging before birth and
continuing to develop throughout adolescence and into early adulthood (e.g., Anderson,
2002; Best & Miller, 2010). In a variety of psychological and medical conditions,
executive dysfunction has been associated with significant negative consequences for daily
life functioning, academic achievement, and employability (Altshuler et al., 2007;
Biederman et al., 2004; Garcia-Villamisar & Hughes, 2007; Gilotty, Kenworthy, Sirian,
Black, & Wagner, 2002). Various patterns of executive dysfunction have been reported
across a number of clinical disorders (see reviews by Hill, 2004; Sergeant, Guerts, &
Oosterlaan, 2002). For example, Ozonoff and Jensen (1999) reported poor planning and
cognitive flexibility but typical inhibitory skill in children/adolescents with autism
spectrum disorder (ASD), and the reverse profile in children/adolescents with Attention
Deficit-Hyperactivity Disorder (ADHD). Similarly, Happé, Booth, Charlton, and Hughes
(2006) reported specific and differing profiles of executive functioning in children and
adolescents diagnosed with ASD vs. ADHD, with individuals with ADHD showing a more
widespread and general impairment, particularly in response inhibition, whereas those with
ASD showed greater difficulties with response selection and monitoring. The literature
regarding EF across neurodevelopmental disorders has paid less attention to developmental
coordination disorder (DCD), which is diagnosed on the basis of movement difficulties that
interfere with academic achievement or activities of daily living, such as dressing or
eating (DSM-5, American Psychiatric Association, 2013). These movement difficulties cannot
be the result of any known intellectual disability or medical condition such as cerebral
palsy. As in ASD and ADHD, reports suggest that individuals with DCD have difficulties in
many aspects of EF (see Wilson, Ruddock, Smits-Engelsman, Polatajko, & Blank, 2012),
particularly in the three key components of EF identified by Miyake et al. (2000) of
response inhibition (e.g., Mandich, Buckolz, & Polatajko, 2002; Michel, Roethlisberger,
Neuenschwander, & Roebers, 2011; Piek et al., 2004; Piek, Dyck, & Francis, 2007; Querne et
al., 2008; Wisdom, Dyck, Piek, & Hay, 2007), working memory (e.g., Alloway & Archibald,
2008; Alloway, 2007, 2011; Michel et al., 2011; Piek et al., 2004, 2007; Wisdom et al.,
2007), and switching (e.g., Michel et al., 2011; Piek et al., 2004, 2007; Wisdom et al.,
2007; Wuang, Chwen-Yng, & Su, 2011). These studies have suggested that children with DCD
perform more poorly or with more variability than their typically developing counterparts
on a range of tasks, although the patterns of impairments and variability in DCD groups
are not always the same, with areas of relative strength in some studies appearing to be
relative weaknesses in others. For example, when testing switching, Michel et al. (2011)
and Piek et al. (2004) found no differences between children with motor difficulties and
controls in terms of the numbers of errors made, while Wuang et al. (2011) and Piek et al.
(2007) reported significantly more errors in children with motor difficulties than
controls. Differences between studies may be due to the age ranges and tasks used across
research groups, or may rely on the recruitment method used (e.g., screening using
different percentile cut-offs for motor difficulty vs. recruitment of clinically referred
children). The current study includes only children with a clinical diagnosis of DCD in
order to better understand this group in terms of their executive functioning profile. In
terms of inhibition and working memory, some tasks are used to assess both functions
(e.g., the trailmaking/updating task used by Piek et al., 2004, 2007), while Michel et al.
(2011) used separate tasks for these two functions. The tasks also differ in the extent to
which they rely on motor skills, with tasks such as the trailmaking/updating task
requiring button press responses, while the ‘Fruit Stroop’ task used by Michel et al.
having no motor demands. Studies within normative samples have reported a significant
relationship between motor abilities and response inhibition (Livesey, Keen, Rouse, &
White, 2006; Rigoli, Piek, Kane, & Oosterlaan, 2012), and motor skills in DCD have been
reported to significantly predict working memory (Michel et al., 2011; Piek et al., 2004).
The level of impairment or variability in the DCD group could therefore be affected by the
extent to which the EF task relies on complex motor responses. A study by van Swieten et
al. (2009) supported this suggestion, demonstrating developmentally inappropriate motor
planning in 6–13-year-old children with DCD, but appropriate executive planning (using a
Tower of London task) in 7–11-year-olds in this group. The present study aims to address
this issue by comparing performance on tasks that require a greater motor load to those
that have a reduced motor load. Two EF components were selected for the current
investigation, namely planning and inhibition, both of which have previously been tested
in DCD with tasks that require greater or reduced motor output. While planning is not one
of the core EFs identified by Miyake et al. (2000), it is suggested to build on core
functions such as working memory (Diamond, 2013), and deficits in the planning and control
of motor actions are likely to be key to the movement difficulties seen in DCD (see Hill,
1998, for a review). Inhibition is often investigated using tasks that involve button
presses or other motor responses, and so it is important to assess the extent to which any
difficulties or additional processing load associated with producing these responses
affects inhibition performance in children with DCD. In the current study, tests of
planning and inhibition were taken from different executive functioning measures, and were
chosen according to their relative motor loads (i.e., high vs. reduced motor response
required). Each executive function was therefore measured using two tasks: Planning was
assessed by the NEPSY Tower task (Korkman, Kirk, & Kemp, 1998; reduced motor-load) and the
Rotational Bar task (Rosenbaum et al., 1990; high motor-load). Inhibition was assessed by
the Stroop task (Stroop, 1935; reduced motor-load) and by the NEPSY Knock-Tap task
(Korkman et al., 1998; high motor-load). These tasks are described in more detail in
Sections 2.2.1 and 2.2.2, and the high motor-load tasks are presented graphically in Fig.
1. The NEPSY Tower task was used to measure planning with a reduced motor load, in line
with van Swieten et al. (2009), and was compared to a motor planning task. Specifically,
the Rotational Bar task developed by Rosenbaum et al. (1990) was used, in which
participants are required to pick up and rotate a bar so that a coloured end of the bar is
placed on a specific coloured disc on a table. This requires participants to plan their
grips in order to end in a comfortable position (achieving ‘end-state comfort’). Using
this task, Smyth and Mason (1997) found no significant differences between 4- and 8-year-
old children screened for movement difficulties and a control group with typical movement
skills in the proportion of grips ending in a comfortable state, although van Swieten et
al. (2009) found increasing differences with age between children with DCD and controls in
grip selection on a related task. Given that the children in the current study were of a
similar age range to those tested by van Swieten et al. (6–14 years and 6–13 years,
respectively), the hypotheses were based on the latter study. Specifically, it was
predicted that children in the DCD group would perform more poorly than the control group
on the Rotational Bar task (high motor-load) but not on the NEPSY Tower task (reduced
motor-load). In the inhibition tasks, participants with DCD were expected to perform more
poorly than the control group in the Knock-Tap task (high motor-load), but not in the
Stroop task (reduced motor-load).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Twenty-six children and adolescents diagnosed with DCD, and 24 children and adolescents
without a DCD diagnosis (hereafter, ‘typically developing group’) were recruited through
schools and DCD support groups. In the DCD group, only those with a clinical diagnosis of
DCD made according to the full DSM-IV-TR criteria (American Psychiatric Association, 2000)
and without additional diagnoses, such as ADHD, ASD or dyslexia, were included. The
following criteria were necessary for a diagnosis of DCD to be given under DSM-IV-TR: (A)
performance in daily activities that require motor coordination was substantially below
that expected, given the child's chronological age and measured intelligence; (B) the
disturbance in Criterion A significantly interfered with academic achievement or
activities of daily living; (C) the disturbance was not due to a general medical condition
(e.g., cerebral palsy, hemiplegia, or muscular dystrophy) and did not meet criteria for a
Pervasive Developmental Disorder; (D) if mental retardation was present, the motor
difficulties were in excess of those usually associated with it. All participants
completed the Movement Assessment Battery for Children – 2nd edition (Movement ABC-2;
Henderson, Sugden, & Barnett, 2007) to further document their level of movement skill and
the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; Wechsler, 2004) to
measure their IQ (see Section 2.2 for further details of these tests). Children were
included in the typically developing (TD) group only if they had not received a diagnosis
of any neurodevelopmental disorder prior to participation in the study, and if they
performed above the 15th centile on the Movement ABC-2. Children were only included in
each group if they had WISC-IV Verbal Comprehension scores above 70 (an IQ below this cut-
off suggests intellectual disability). The Verbal Comprehension scores were used rather
than a full IQ score, as Full-Scale IQ measures encompass tasks with a high motor load or
executive functioning component, and may therefore disadvantage children with DCD by
giving a pessimistic estimate of their full IQ. Differences were indeed found between
groups in WISC-IV Perceptual Reasoning scores (see Table 1), and so these scores were
taken into account in the analyses. Participant characteristics, including Verbal
Comprehension and Perceptual Reasoning, are presented in Table 1.

<hs>  Materials</hs>
  ~~~~~~~~~

The Movement ABC-2 (Henderson et al., 2007) is a standardised test of motor skills
suitable for children aged 3–16. It consists of three subtests: Manual Dexterity, Aiming
and Catching, and Static and Dynamic Balance, each of which comprises a series of speeded
and non-speeded motor tasks. Scores for each component can be converted to standard scores
and percentile ranks, and a Total Standard Score can also be calculated from the
components (M = 10, SD = 3). The Total Score percentile can be used as an indicator of
motor difficulties, with scores below the 5th percentile suggesting a significant motor
difficulty, and between the 6th and 15th percentiles signifying a borderline motor
difficulty. The WISC-IV (Wechsler, 2004) is a standardised test of verbal and nonverbal
abilities and is suitable for children aged 6–16. There are 10 subtests that contribute to
a number of indices of intellectual functioning. For the current report, only the Verbal
Comprehension Index (VCI) and Perceptual Reasoning Index (PRI) scores are reported. Both
indices have a mean of 100 and a standard deviation of 15.

        <hss>Tests of planning</hss>

        The NEPSY Tower task (Korkman et al., 1998; hereafter, ‘Tower task’) required
        participants to move a set of three balls on three pegs from a start to a target
        configuration while following certain rules. Participants were shown a target
        picture of the apparatus, with the coloured balls in specific positions across the
        pegs, and were asked to copy the picture using their equipment. Participants first
        completed a practice trial in which they moved a ball so that the model matched
        the picture, and were assisted if necessary in order to ensure that they
        understood the task. Participants were asked to complete the trial in a set number
        of moves while adhering to several rules, namely: (1) a move was finished once the
        hand was removed from the ball; (2) only one ball could be moved at a time; (3)
        balls that were not being moved must remain on their pegs at all times and must
        not be placed anywhere else. Each time a participant broke one of these rules they
        scored one mark for a violation and automatically scored zero for the trial in
        question, but were allowed to continue with the task. A score of one point was
        awarded for each correct trial. The task had seven stages, with each stage
        becoming progressively more difficult in terms of planning complexity and the
        number of moves required to complete the trial. The first stage could be completed
        in one move, and the last stage could be completed in seven moves. The task was
        stopped once a participant had obtained four consecutive scores of zero on trials,
        or if they had completed all 20 trials. Although the standardised task was timed,
        participants were not automatically stopped at the cut-off point of 45 s for later
        trials, as it was felt that it was important to assess if the task was too
        difficult for participants in the DCD group, even once the time limit had been
        passed. The number of violations committed during the task provided one dependent
        variable in the analyses. Raw score (out of 20) was the other dependent variable
        for this task. The Rotational Bar task (Rosenbaum et al., 1990) required
        participants to move a coloured rod that rested on a tripod on the tabletop and
        place one end of the rod onto one of two coloured discs (see Fig. 1a). One side of
        the bar was blue, and the other side was red, and these ends of the bar were
        placed in front of the matching coloured disc on the table (in Fig. 1a, the blue
        parts of the apparatus are represented by the darker tones, and the red parts by
        the lighter tones). Participants were required to pick up the bar and place one of
        the coloured ends of the bar onto one of the coloured discs. In order to complete
        this task, participants could use an underhand grip, with their palm facing up, or
        an overhand grip, with their palm facing down, to pick up the bar, and this choice
        would affect how comfortable their final arm position would be, i.e., their level
        of ‘end-state comfort’ (ESC; Rosenbaum et al., 1990). Participants completed four
        practice trials before the task began. There were 8 trials in which an overhand
        grip would achieve ESC and 8 in which an underhand grip would be the most
        comfortable. Two marks were given for each trial in which a participant used the
        correct grip to pick up the bar and also placed the correct end of the bar onto
        the coloured disc. If they began with the wrong grip, but adjusted it to place the
        correct end of the bar onto the coloured disc, one mark was awarded. If
        participants used the wrong grip throughout the trial, and thus did not achieve
        ESC, they did not receive any points for that trial. A total of 32 points was
        therefore available for each participant, and the raw score (out of 32) provided
        the dependent variable for this task.

        <hss>Tests of inhibition</hss>

        The Stroop task (Stroop, 1935) required participants to name the colour of the ink
        in which a colour word was printed (e.g., the word ‘blue’ printed in red ink;
        response ‘red’). Participants had a maximum of 2 min to read out 112 words that
        were either congruent (set 1) or incongruent (set 2) with the ink in which they
        were printed. The number of correct responses in congruent and incongruent trials
        (both out of 112) was recorded and provided the dependent variables for this task.
        Before the task, participants were asked to read a list of words in order to
        ensure that any reading difficulties would not affect performance, and also read
        an example word in an incongruent colour to ensure that they understood the task.
        The NEPSY Knock-Tap task (Korkman et al., 1998; hereafter, ‘Knock-Tap task’)
        required participants to lay their non-preferred hands on the table and to use
        their preferred hands to complete certain actions, which the experimenter
        explained at the beginning of each set of trials (see Fig. 1b). The actions were:
        knocking on the table with knuckles, tapping the table with the palm of the hand,
        placing the side of the fist on the table, or no response. In the first set of 15
        trials, only the knock and tap responses were used, and participants were required
        to do the opposite action to the experimenter (i.e., if the experimenter knocked,
        the participant should tap). In the second set of 15 trials, the participant
        response to the experimenter's knock was the side fist, and the response to the
        side fist was a knock. If the experimenter tapped, the participant should provide
        no response. Before each set of trials, participants completed a series of
        practice trials in which the possible action–response pairs were presented twice
        each. Once the participant understood the task, the main trials began. One point
        was awarded for each correct response, providing a score out of 30, which was
        entered as the dependent variable in the analyses.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants were part of a larger study into the relationships between movement
abilities, cognition and emotional well-being. They were visited in their own homes or at
school to complete the testing battery, which could be administered in one session over
the course of a day or over several shorter sessions, depending on the needs of the child
and the constraints of the testing setting. The executive functioning tasks detailed in
the current paper were always completed in one session, and in a quiet room without
distractions. Tasks were presented to participants in a randomised order, and the session
lasted approximately 30–40 min. Breaks and rewards were given throughout the testing
session as necessary. Parents signed consent forms and the participants gave informed
verbal consent to take part in the tasks. The experimenter explained the rules to the
participant before each task and answered any questions arising from the description.

<h>RESULTS</h>
-------

Two main methods of analyses were conducted on the data. First, hierarchical regressions
were carried out, with chronological age and WISC-IV Perceptual Reasoning score entered as
predictors in the first step, and Group (DCD vs. TD) in the second step. This meant that
any group differences in EF performance revealed in the analyses would be evident even
after differences or changes in performance related to age and Perceptual Reasoning had
been taken into account. Chronological age was included to account for the improvement of
EF ability within the relatively wide age range of the two groups. Perceptual Reasoning
scores were included because the DCD group had significantly poorer scores than the TD
group, and it was important to account for these differences before assessing the groups
on EF performance. Second, within-group correlations were conducted to assess the
relationship between motor abilities and EF performance within each group. There were six
dependent variables in total: Tower task total raw score, Tower task violations, and
Rotational Bar task total score; Stroop correct congruent responses, Stroop correct
incongruent responses, and Knock-Tap total raw score. The means, standard deviations and
ranges of these six variables are presented in Table 2. As some of these dependent
variables were not normally distributed in one or both groups, non-parametric Spearman
correlations were conducted on the data. For the regression analyses, bootstrapping
procedures were applied, allowing an assessment to be made of the representativeness of
the relatively small sample to the population from which it was drawn. Bootstrapping
provides estimates of the confidence intervals around the regression coefficients, and
relies on fewer assumptions about the distribution of the data and residuals than
traditional statistical approaches, which is particularly useful in clinical samples
(Wright, London, & Field, 2011).

<hs>  DCD vs. TD group differences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Six separate hierarchical regressions were conducted on the data, with one planning or
inhibition score as the dependent variable in each case. Chronological Age and Perceptual
Reasoning scores were entered in Step 1, with Group entered in Step 2. Sections 3.1.1 and
3.1.2 report the summaries of the full models for each of the EF tasks, along with the
unstandardised coefficients, standard errors (SEs) and confidence intervals (CIs) for each
of the predictors in Step 2 of the regression, based on 1000 bootstrap samples.

        <hss>Planning tasks</hss>

        The final model significantly predicted the Tower task total raw score, F(3,46) =
        26.82, p < .001, Adj R2 = .61. The coefficients were significant for Chronological
        [Age, B = 0.09 (CI = 0.07–0.13), SE B = 0.01, p = .001], Perceptual Reasoning [B =
        0.10 (CI = 0.04–0.14), SE B = 0.02, p = .001], and Group [B = 3.26 (CI =
        1.76–5.00), SE B = 0.85, p = .002]. For the number of violations in the Tower
        task, the final model was again significant, F(3,46) = 6.49, p = .001, Adj R2 =
        .25, although the only significant predictor was Group [B = −1.76 (CI = −2.99 to
        −0.47), SE B = 0.66, p = .02]. The coefficients for Chronological Age [B = −0.02
        (CI = −0.04 to 0.002), SE B = 0.01, p = .11], and Perceptual Reasoning [B = −0.03
        (CI = −0.06 to 0.01), SE B = 0.02, p = .12], were not significant. Finally, the
        final model predicted a significant amount of the variance in scores on the
        Rotational Bar task, F(3,46) = 15.74, p < .001, Adj R2 = .47, with Group again
        emerging as the only significant predictor of performance [B = 9.81 (CI =
        6.70–12.55), SE B = 1.36, p < .001]. Chronological Age [B = 0.06 (CI = 0.01–0.11),
        SE B = 0.013, p = .053], and Perceptual Reasoning [B = −0.05 (CI = −0.14 to 0.03),
        SE B = 0.04, p = .18], were not significant. To summarise, the DCD group performed
        significantly worse than the TD group on all three measures of planning, even once
        the effects of Chronological Age and Perceptual Reasoning on planning performance
        had been taken into account.

        <hss>Inhibition tasks</hss>

        The final model significantly predicted the number of correct responses in the
        Stroop task on both the congruent trials, F(3,42) = 4.62, p = .01, Adj R2 = .19,
        and the incongruent trials, F(3,42) = 9.59, p < .001, Adj R2 = .36. For the
        congruent trials, none of the coefficients of the predictors were significant:
        Chronological Age [B = 0.21 (CI = 0.05–0.41), SE B = 0.09, p = .08]; Perceptual
        Reasoning [B = 0.13 (CI = −0.06 to 0.33), SE B = 0.10, p = .23], and Group [B =
        7.65 (CI = 0.03–16.38), SE B = 4.48, p = .26]. For the incongruent trials,
        Perceptual Reasoning was not a significant predictor of correct responses [B =
        0.17 (CI = −0.12 to 0.49), SE B = 0.15, p = .26], but both Chronological Age [B =
        0.45 (CI = 0.22–0.70), SE B = 0.11, p < .001], and Group [B = 15.73 (CI =
        3.03–27.82), SE B = 5.79, p = .01], had significant coefficients. Finally, the
        final model did not significantly predict performance on the Knock-Tap task,
        F(3,45) = 2.04, p = .12, Adj R2 = .06, and none of the coefficients were
        significant: Chronological Age [B = 0.02 (CI = −0.01 to 0.05), SE B = 0.01, p =
        .17]; Perceptual Reasoning [B = −0.02 (CI = −0.06 to 0.02), SE B = 0.02, p = .36];
        Group [B = 1.31 (CI = 0.05–2.52), SE B = 0.65, p = .052]. In summary, the DCD
        group performed significantly worse than the TD group in the reduced motor-load
        task (the Stroop incongruent trials) but the difference in performance in the
        Knock-Tap task (high motor-load) was only a non-significant trend.

<hs>  Within-group relationships between motor and EF abilities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As some scores were not normally distributed, Spearman's correlations were conducted on
all data and were Bonferroni-corrected for multiple correlations (p < .004). Correlation
analyses were conducted within each group between Movement ABC-2 Total Standard Score and
the six outcome measures of EF ability. There were no significant correlations between
MABC-2 Total Standard Scores and any of the EF measures in the DCD group (all rs < 0.43, p
> .03), or in the TD group (all rs < 0.29, p > .16). Separate analyses were also conducted
for each group using the component standard scores of the Movement ABC-2 (Manual
Dexterity, Aiming and Catching, and Balance). None of the components were significantly
correlated with any of the EF outcome measures in the DCD group (Manual Dexterity: all rs
< 0.42, p > .03; Aiming and Catching: all rs < 0.43, p > .03; Balance: all rs < 0.31, p >
.12), or in the TD group (Manual Dexterity: all rs < 0.26, p > .22; Aiming and Catching:
all rs < 0.40, p > .05; Balance: all rs < 0.29, p > .16).

<h>DISCUSSION</h>
----------

The current study aimed to assess the role of motor load on EF task performance in
children with DCD. As in previous research, children with DCD had significantly lower
scores than a control group on measures of planning, although some measures of inhibition
did not differ significantly between groups. Contrary to predictions, the level of motor
load did not seem to specifically affect performance on the tasks: the DCD group had
significantly lower scores on both the high-motor and reduced-motor planning tasks than
the TD group. In the measures of inhibition, the DCD group performed significantly worse
than the TD group when there was a reduced motor-load, but any differences in performance
in the high motor-load task did not reach significance. Within each group, motor ability
did not correlate significantly with any of the EF tasks. The poorer performance in the
DCD group across ‘motor planning’ and ‘executive planning’ tasks is at odds with the
previous study by van Swieten et al. (2009), which reported no deficits in planning on the
Tower task in a group of children with DCD. Although there was no control group comparison
in that study, the performance of children with DCD was compared to standardised means,
and all children scored within the typical range (between a scaled score of 7 and 13). In
the current study, children with DCD not only had lower scores overall than the TD group,
but many also scored outside this typical range of standard scores (65% had a scaled score
of less than 7, while only 27% of children in the TD group scored below 7). It is
difficult to assess how these differences between studies may have arisen, as little
information is given about the children who completed the Tower task in the van Swieten et
al. study, apart from their chronological age range. It is possible that the current group
had lower IQs or more severe movement difficulties than those in the van Swieten et al.
sample, resulting in more difficulties in the executive planning task. However, all
children in the current sample had a Verbal IQ in what is considered to be the normal
range (all were above 70), and differences in Nonverbal IQ (or Perceptual Reasoning in the
current study) were taken into account in the analyses, so the children in the present DCD
group did not represent a particularly low-functioning group. In addition, motor abilities
did not correlate significantly with performance on the Tower task in either the DCD or TD
groups, suggesting (as predicted) that any motor skills required to complete the task did
not have a significant impact on performance. It may be that the Tower task involves
multiple processes over and above planning ability (producing a less ‘pure’ planning
measure: Miyake et al., 2000), and it is the complexity of the task that affects
performance in the current DCD sample. The fact that Perceptual Reasoning scores were a
significant predictor of Tower raw scores in the DCD group may lend some weight to this
suggestion. It is important to note that Perceptual Reasoning scores did not significantly
predict any of the other measures, suggesting that the other EF measures used in this
study are tapping into different underlying processes and constructs to the Perceptual
Reasoning tasks. Future studies could compare ‘purer’ measures of executive planning
(e.g., a maze or sorting task) with the Tower task in order to examine this hypothesis
further in children with DCD. The complexity of the task might also have been a factor in
the inhibition performance of the DCD group. While children with DCD performed
significantly worse than the TD group on the Stroop task during the incongruent trials,
the difference between groups on the Knock-Tap task did not reach significance. It is
possible that the high motor-load task actually taps into a simpler, more fundamental
skill than the Stroop task, which requires reading a word, then coding (and ignoring) the
colour in which the word is presented, and finally verbalising the word. The prepotent
response might also be stronger for the Stroop task than the Knock-Tap task, as it
involves the highly automatised skill of reading rather than a non-automatic pattern of
motor responses that is built up over the task. Previous reports of poorer inhibition in
children with DCD could therefore relate not just to the requirement for a motor response
per se, but to the complexity of the motor response or the additional requirements of
other complex processes (e.g., visuo-spatial processing skills), as well as the strength
of the prepotent response to be inhibited. It is also important to remember that while
there may be minimal differences between groups on basic motor inhibition tasks in terms
of behavioural outcomes, the functional brain responses underlying this performance can be
very different between TD and DCD groups (Querne et al., 2008). If even a simple task
requires more effortful top-down control in children with DCD than their typically
developing counterparts (Querne et al., 2008), this could explain why increasing
complexity in a task could have a disproportionate effect on their performance. The
complexity of the tasks in the current study is one issue that arises from the adoption of
tasks from standardised batteries and experimental measures previously used in the
literature. This procedure also meant that it was necessary to manipulate motor load
across tasks with different materials and methods, rather than within one task. While a
focus of future research might be to manipulate the motor loads within tasks, the current
study was important in terms of assessing the motor demands of a range of tasks that are
widely used in the literature. In addition, it will be important for future investigations
to consider the relationships between age and performance on the different executive
functioning measures. In the current data, the relatively wide age range was taken into
account in the regressions, as splitting the sample into smaller age bands would have
affected the power of the analyses. However, it will be of great interest to assess the
developmental trajectories of the different executive functions in children with DCD, as
some EFs may develop linearly with age, while others may show different stages of
development, and it will be important to know if these patterns could be atypical or
delayed in children with DCD. While previous research has reported significant
correlations between components of the Movement ABC-2 and measures of response inhibition
in normative samples (e.g., Livesey et al., 2006; Rigoli et al., 2012), no significant
relationships were found between motor and EF abilities in either the TD or DCD group in
the current study. As the development of EF is a protracted process (Anderson, 2002; Best
& Miller, 2010), it is possible that its relationship with motor abilities changes over
developmental time and that the varied ages of the samples across the studies may explain
the different results (i.e., 5–6 years in Livesey et al., 12–16 years in Rigoli et al.,
7–14 years in the current study). Interestingly, even the tasks classified as having a
relatively high motor-load were not correlated with the Movement ABC-2 Total Score or its
components. It is important to note that Rigoli et al. found a significant relationship
between motor ability and the time taken to complete an inhibition task, whereas the
current study assessed inhibition errors. However, there may be a more fundamental
difference between studies in terms of the aspect of response inhibition being assessed.
Livesey et al. reported that motor ability was more closely correlated with a modified
Stroop task (which they argued measured ‘interference control’) than with a Stop-Signal
task, which was regarded as a measure of inhibition of an ongoing response (cf. Nigg,
2000). In the current study, although the Knock-Tap task had a relatively increased motor-
load in terms of the response required, differences found between it and the Stroop task
in could be due to the fact that they were measuring different aspects of response
inhibition. It will be important in future research to take this into account when
selecting inhibition tasks to use with children with DCD, as there may be much closer
links between neural pathways relating to motor and interference control than between
motor control and the inhibition of an ongoing response (Livesey et al., 2006).

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

The current study aimed to assess the role of motor load on EF performance in children
with DCD compared to a control group with typical motor development, adding to the
relatively limited literature regarding EF performance in DCD compared to other
neurodevelopmental disorders. The DCD group performed significantly worse than the TD
group on measures of both planning and inhibition, but the effect of the motor load of the
response in the task was not clear-cut. It seems that while this may have an effect on the
EF performance of children with DCD, other factors such as the executive ‘purity’ of the
tasks, their interaction with age and the different aspects of response inhibition that
may be measured could also play an important role. Given the reported negative
consequences of executive difficulties on quality of life and achievements (e.g.,
Altshuler et al., 2007; Biederman et al., 2004; Garcia-Villamisar & Hughes, 2007; Gilotty
et al., 2002), it is important that methodological problems are addressed in order to
improve our understanding of EF in children and adults with DCD. Investigations
considering EF across development in DCD, which take into account performance on different
tasks measuring the same EF construct and assessing a range of compound skills, will be
vital in this research. The incorporation of parent- and self-report measures of the
effects of EF difficulties on functioning outside the laboratory will also help to provide
a clearer picture of EF in DCD.


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<ART>The effect of prior experience on children's tool innovation
============================================================

Authors: Clare L. Whalley, Nicola Cutting, Sarah R. Beck
DOI: 10.1016/j.jecp.2017.03.009
Year: 2017  |  Pages: 81-94
ASJC codes: 3204, 3205
Keywords: Analogy, Cognitive development, Comparative cognition, Innovation, Problem solving, Tool use

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Spontaneous tool innovation to solve physical problems is difficult for young children. In three studies, we explored the effect of prior experience with tools on tool innovation in children aged 4–7 years (N = 299). We also gave children an experience more consistent with that experienced by corvids in similar studies to enable fairer cross-species comparisons. Children who had the opportunity to use a premade target tool in the task context during a warm-up phase were significantly more likely to innovate a tool to solve the problem on the test trial compared with children who had no such warm-up experience. Older children benefited from either using or merely seeing a premade target tool prior to a test trial requiring innovation. Younger children were helped by using a premade target tool. Seeing the tool helped younger children in some conditions. We conclude that spontaneous innovation of tools to solve physical problems is difficult for children. However, children from 4 years of age can innovate the means to solve the problem when they have had experience with the solution (visual or haptic exploration). Directions for future research are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Tool use is considered to be a hallmark of human cognition, with our substantial
technological accomplishments unrivaled by any nonhuman animal species. Observations of
infants and children demonstrate their impressive competence in terms of their tool use
and knowledge. From around 2 years of age, children show insight into the function of
tools (Casler & Kelemen, 2005) and anticipate the target of a tool use action (Paulus,
Hunnius, & Bekkering, 2011). In addition, 3-year-olds reliably copy tool use from peers
(Hopper, Flynn, Wood, & Whiten, 2010) and are capable of transmitting a tool use action
across multiple generations (Flynn & Whiten, 2008; Hopper et al., 2010). It is surprising,
then, that despite being proficient tool users, children appear to struggle to innovate
tools (i.e., to make a novel tool to solve a task) without prior training (Beck, Apperly,
Chappell, Guthrie, & Cutting, 2011; Cutting, Apperly, & Beck, 2011; Cutting, Apperly,
Chappell, & Beck, 2014; Hanus, Mendes, Tennie, & Call, 2011; Nielsen, Tomaselli, Mushin, &
Whiten, 2014; Sheridan, Konopasky, Kirkwood, & Defeyter, 2016; Tennie, Call, & Tomasello,
2009). Recent research into children’s tool innovation was motivated by studies with
corvids. “Betty,” a captive New Caledonian crow, spontaneously manufactured a hook from a
straight piece of wire to retrieve a wire-handled bucket from a transparent tube (Weir,
Chappell, & Kacelnik, 2002). Researchers were investigating whether crows could choose the
correct tool to solve a task and, on a task requiring a hook, had given them a hooked
piece of wire and a straight piece of wire. When one crow flew off with the hooked tool,
Betty bent the straight piece of wire to make her own hook despite not being shown how to
make tools previously. In a later experiment, Betty continued to make functional hooks on
the majority of trials when given only straight pieces of wire. New Caledonian crows have
been directly observed making and using tools in the wild (Hunt & Gray, 2004; Rutz,
Sugasawa, van der Wal, Klump, & St Clair, 2016), although not from wire or wire-like
materials. However, similar findings have been replicated by Bird and Emery (2009) with
captive rooks, a species that does not use tools in the wild. They were also able to
select and manufacture the correct tool to solve the hook-making task used by Weir et al.
(2002). Thus, it is even more surprising that children younger than 8 years demonstrate
difficulty with similar problems requiring tool innovation. In a paradigm adapted from the
corvid literature, children were able to choose the appropriate tool to solve a problem
requiring a hook (Beck et al., 2011). From 4 years of age, children were significantly
more likely to pick up a hooked pipe cleaner than to pick up a straight one when their
goal was to retrieve a handled bucket containing a sticker reward from a tube. However,
when other children were given a straight pipe cleaner that required bending into a hook
shape to retrieve the bucket, children younger than 5 years rarely solved the task.
Performance improved with age, and it was not until 8 years that approximately half of
children passed the task. Interestingly, most children found manufacturing a tool (making
a tool following adult demonstration) comparatively easy. This finding appears consistent
across cultures. Western and Bushman children show a similar pattern of tool innovation
performance; innovating a tool independently to solve a physical problem is difficult for
children aged 3–5 years, whereas manufacturing a tool following an adult demonstration is
significantly easier (Nielsen et al., 2014). Beck et al. (2011) noted that children’s
knowledge of tool function and ability to manufacture tools emerges significantly earlier
than their ability to innovate tools. Given the findings from tasks involving corvids,
children’s difficulty with tool innovation has been met with curiosity. Given that many
nonhuman species are known to use tools (Seed & Byrne, 2010), it is the human propensity
for tool innovation, and the complex technologies that have arisen because of it, that
sets us apart from nonhuman species. Findings such as these raise bigger questions
surrounding human cognitive architecture. It is important to better understand those
processes that we might share with nonhuman animals and those that may demonstrate human
uniqueness (Shettleworth, 2012). Cross-species comparisons between human children and
nonhuman animals are often made (e.g., Beck et al., 2011; Cheke, Loissel, & Clayton, 2012;
Engelmann, Herrmann, & Tomasello, 2012; Taylor et al., 2014). However, caution is
required. To truly understand how human children differ from other species, in this case
corvids, it is vital that studies are methodologically sound and fair to both species
(Boesch, 2007; Shettleworth, 2012). When experimental procedures systematically differ,
the value of cross-species comparisons is compromised. To date, the experiences of
children and corvids on versions of the hook-making task have not been consistent.
Specifically, the experiences of the corvids and children prior to attempting the hook-
making task were inconsistent. Corvids had already seen and had the opportunity to use a
premade hook—made either from the same material as was available for tool making (wire;
Weir et al., 2002) or from a different material (wood; Bird & Emery, 2009). Some children
had not seen a pipe-cleaner hook previously within the task (Beck et al., 2011), and
others had seen a hook but did not have the opportunity to use it (Cutting et al., 2014).
The effect and potential advantage that such an experience might have on subsequent tool
innovation in children is yet to be determined. Cutting et al. (2014) suggested that
certain pretest experiences can promote tool innovation on the hook-making task. In their
study, 4- to 6-year-olds were shown a premade example of a pipe-cleaner hook (target tool
demonstration). Half of the children also had the pliable nature of the test material
(pipe cleaners) highlighted to them via “bending practice.” It was found that 5- and
6-year-olds were significantly more likely to solve the hook-making task if they received
both a target tool demonstration and bending practice compared with those who saw only a
target tool demonstration. This suggests that seeing the correct tool required to solve a
problem does not make tool innovation problems trivially easy for children. Unlike the
corvids, children in these studies were not permitted to use the premade target tool prior
to attempting the hook-making task. The purpose of the current series of experiments was
twofold. First, we sought to further explore the effect of prior experience on children’s
tool innovation. Second, we aimed to draw fairer cross-species comparisons of tool
innovation between corvids and children. In three studies, the role of prior experience in
children’s ability to innovate a hook tool to solve the hook-making task was investigated.
In Study 1, we explored how children performed on the hook-making task given the same
pretest conditions as corvids, that is, the opportunity to use a premade pipe-cleaner
hook. Children, but not corvids, have previously been presented with nonfunctional
distracter materials during the hook-making task such as string (Beck et al., 2011;
Cutting et al., 2014). Therefore, no distracter items were included in these studies and
children were presented only with pipe cleaners. Some corvids were also given multiple
trials at the hook-making task, although performance was not observed to improve or
deteriorate over time. Still, it seems important that the possibility of improved or
changed performance over time is explored in children. Therefore, the first study included
3 trials to explore this possibility and to match more closely the experimental
methodology of corvids. We did not give children the full 17 trials used in the original
corvid study because we judged this as too many for children to cope with. Before
attempting the hook-making task, half of the children completed a hook-using phase, where
they were given the opportunity to use a premade pipe-cleaner hook on the bucket and tube
apparatus. The hook-using phase emulates the condition used by Weir et al. (2002) where
corvids were given a hooked piece of garden wire and a straight one.

        <hss>Participants</hss>

        The participants were 28 children aged 4 or 5 years (M = 4 years 6 months [4;6],
        range = 4;2–5;1) and 30 children aged 6 or 7 years (M = 6;7, range = 6;3–7;1)
        recruited from a mainstream school in the United Kingdom. The ethnic composition
        of the sample was 85% Caucasian, 10% Black, and 5% Asian. An additional 2 children
        were excluded from analysis due to retrieving the bucket without making a hook or
        other functional tool.

        <hss>Materials</hss>

        The apparatus was a transparent plastic tube (22 cm length, opening 5 cm in
        diameter) attached to a cardboard base (Fig. 1). At the bottom of the tube, there
        was a small bucket containing a sticker. The bucket had a wire handle that
        required a hook in order to retrieve it from the tube. Tool-making materials were
        30-cm pipe cleaners.

        <hss>Procedure</hss>

        The study comprised a hook-using phase and an innovation phase. Children were
        systematically assigned to either the experimental condition or the control
        condition by their class list. They were told by their class teacher that they
        would be playing a game and must not discuss the game in the class because it
        would spoil the surprise for the other children. Children completed the experiment
        in a quiet area of the school library with a female experimenter. A second female
        coder (the second author) was present during 1 or 4 testing days to ensure
        reliability of coding success/failure on the hook-making task. There was 100%
        interobserver agreement. Children in the experimental condition first completed
        the hook-using phase. A 30-cm straight pipe cleaner and a 30-cm pipe cleaner bent
        at one end to form a hook were placed next to the apparatus in front of the
        children. They were told, “If you are able to get the sticker out of the tube,
        then you can keep it.” Children were allowed up to 1 min to complete this phase,
        and neutral prompts were given by the experimenter where necessary. All children
        completed the innovation phase. This followed the hook-using phase for those in
        the experimental condition and was the only phase for those in the control
        condition. During the innovation phase, children were presented with the same
        bucket/tube apparatus and a 30-cm straight pipe cleaner only. They were told, “If
        you can get the sticker out of the tube, then you can keep it.” All children
        received three trials. In the first trial, children were allowed up to 1 min to
        attempt the task. The experimenter then reset the task for two further 30-s
        trials. If children failed to innovate a hook after the third trial, the
        experimenter provided a demonstration of how to make a hook and kept it herself.
        Children were then encouraged to make another attempt to retrieve the sticker
        using their own materials. Only 2 children failed to make a hook following an
        adult demonstration. In these cases, children were given the experimenter’s
        premade hook and used this to retrieve the bucket.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Criteria for success on the innovation phase, here and in all further experiments, were
making a hook tool and using it to retrieve the bucket from the tube. All children who
made a hook were able to retrieve the bucket from the tube. There were no significant
effects of gender on performance in Trial 1, 2, or 3, Fisher’s exact test, lowest p =
.267. Therefore, data were combined across gender for all analyses. First, we analyzed
whether the hook-using phase was successful in changing children’s experience in the
experimental condition. In other words, did children use the hook prior to attempting the
innovation phase? The 4- and 5-year-olds were significantly more likely than chance to
pick up the hooked pipe cleaner first, with 15 of 15 children choosing the hook first,
binomial test, p < .001. A binomial test revealed the same pattern for 6- and 7- year-
olds, with 12 of 15 children choosing the hook first, p = .035. The 3 children who picked
up the straight pipe cleaner first went on to use the hooked pipe cleaner afterward.
Therefore, children in the hook-using phase did indeed use the hook before attempting
innovation. Second, the effect of age group on performance during the innovation phase was
analyzed. The 6- and 7-year-olds in the control condition were significantly more likely
to pass the innovation phase than the 4- and 5-year-olds, Fisher’s exact test, p = .018.
However, in the experimental condition there was no significant difference in performance
related to age, Fisher’s exact test, p = .080. Of most interest was whether condition
affected performance during the innovation phase and, therefore, the likelihood to
innovate a functional hook tool. Because a significant effect of age was found in the
control group, age groups were analyzed separately when comparing performance by
condition. The percentage of children who passed each trial is shown in Table 1. Condition
had a significant effect in Trial 1: 4- and 5-year-olds, Fisher’s exact test, p = .001; 6-
and 7-year-olds, χ2Yates(df = 1, N = 30) = 7.350, p = .007. In Trial 2, condition had a
significant effect on performance of 4- and 5-year-olds, Fisher’s exact test, p = .006,
but the effect marginally failed to reach significance for 6- and 7-year-olds, χ2Yates(df
= 1, N = 30) = 3.750, p = .053. In Trial 3, condition had a significant effect on
performance of 6- and 7-year-olds, Fisher’s exact test, p = .002, but the effect
marginally failed to reach significance for 4- and 5-year-olds, Fisher’s exact test, p =
.055. However, considering the significant results across all other trials, this
borderline finding is treated as if it were significant. To determine whether performance
changed over time, McNemar tests were used to compare success levels between trials for
each age group (Trial 1 vs. Trial 2, 4- and 5-year-olds, p > .999; 6- and 7-year-olds, p >
.999; Trial 2 vs. Trial 3, 4- and 5-year-olds, p > .999; 6- and 7-year-olds, p = .500;
Trial 1 vs. Trial 3, 4- and 5-year-olds, p > .999; 6- and 7-year-olds, p = .500).
Therefore, children’s performance appeared to neither improve nor deteriorate over time.
Finally, tool manufacture was easy for children. Of those children who failed to innovate
a hook independently in any of the three test trials, 26 of 28 went on to successfully
make a hook following an adult demonstration. The results from Study 1 demonstrated that
children who had been given the opportunity to use a hook tool prior to being required to
make one of their own were at a significant advantage over those children who had no such
experience. Therefore, using a hook tool facilitated children’s subsequent tool
innovation, so much so that younger children performed as well as older children. These
results suggest that, like corvids, children are able to succeed on the hook-making task
after having used a hook previously. Next, we aimed to disentangle what aspect of the
warm-up phase was facilitating subsequent innovation. There are at least two obvious
factors that could be independently or collaboratively facilitating innovation. Children
first need to choose the hook as the correct tool and reject the straight pipe cleaner.
Second, they use the hook on the hook-making task. We designed a second experiment to
investigate whether choosing the hook and rejecting the straight pipe cleaner was an
important element of the warm-up phase or whether simply using a premade pipe-cleaner hook
was sufficient. It might be that being able to contrast two tools (a straight pipe cleaner
and hooked one) helps children to identify what is functional about the target tool. We
know that children from 4 years successfully choose a hooked tool over a straight one to
solve this task (Beck et al., 2011). If this is the case, we expect children who choose a
hook to outperform children who are just given a hook to use on the hook-making task.
Alternatively, the additional demand of needing to choose between two tools may be more
taxing for children (perhaps through working memory demands), and this may reduce
performance on the subsequent hook-making task.

        <hss>Participants</hss>

        In total, 28 children aged 4 or 5 years (M = 4;9, range = 4;5–5;4) and 23 children
        aged 6 or 7 years (M = 6;10, range = 6;5–7;4) were recruited from the same school
        as in Study 1 and made up the final sample. None of these children had taken part
        in the first experiment. The ethnic composition of the sample was 78% Caucasian,
        10% Black, 8% Asian, and 4% other/unknown. An additional 9 children were excluded
        from analysis due to retrieving the bucket without making a hook or other
        functional tool.

        <hss>Procedure</hss>

        All participants were presented with the plastic tube and bucket apparatus used in
        Study 1. Children were systematically allocated by their class list to one of two
        conditions. In the Hook Use condition, a premade pipe-cleaner hook only was placed
        next to the tube apparatus (Fig. 2). In the Tool Choice condition, a 30-cm
        straight pipe cleaner and a premade pipe-cleaner hook were placed next to the tube
        apparatus (Fig. 3). In both conditions, children were then given up to 1 min to
        try to retrieve the bucket from the tube. Having completed either the Hook Use or
        Tool Choice phase, all participants then completed the same test phase as used in
        Study 1. Because no difference in performance across trials was observed in Study
        1, children were given only one attempt at the test phase.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

All children successfully used a premade hook tool in both conditions. There was no
significant effect of gender on performance in either condition or age group, Fisher’s
exact test, lowest p = .236. Therefore, data were combined across gender for subsequent
analysis. Age group did not have a significant effect on performance during the test phase
in either the Tool Choice condition, Fisher’s exact test, p > .999, or the Hook Use
condition, χ2(df = 1, N = 26) = 1.330, p = .249. Finally, Table 2 shows the percentage of
children who passed the test phase in each condition. Analyses were run to investigate
whether condition affected innovation. First, an analysis was run for each age group
separately. Condition did not affect performance on the test phase for younger children,
Fisher’s exact test, p > .999, or for older children, Fisher’s exact test, p = .214.
Because age did not affect performance in this sample, a chi-square analysis was also
conducted with age groups combined; however, condition still showed no significant effect
on innovation, χ2(df = 1, N = 51) = 1.797, p = .249. Study 2 sought to explore what it was
about the warm-up phase in Study 1 that facilitated tool innovation. Regardless of whether
they chose and used a pipe-cleaner hook or used a pipe-cleaner hook only during their
first phase, children were just as likely to innovate a hook during the test phase. This
suggests that it is using the hook, rather than the choosing element of the warm-up phase,
that improves children’s tool innovation. In other words, rejecting the nonfunctional tool
(straight pipe cleaner) during the choice phase does not seem to improve children’s
likelihood of innovating a hook during the test phase. Rather, the opportunity to use a
functional hook tool on the hook-making task seems to promote children’s tool innovation.
The findings from Studies 1 and 2 are especially interesting because Cutting et al. (2014)
found that showing children a pipe-cleaner hook was not sufficient to help them innovate
one of their own afterward. In their study, Cutting and colleagues showed children a
premade pipe-cleaner hook only if they failed to innovate a hook on the hook-making task
and then allowed them another go at the task. Half of these children were given pipe-
cleaner bending practice, whereas the other half were not. It was found that only older
children, who were also given the opportunity to manipulate the materials beforehand,
benefited from a target tool demonstration. Cutting et al. (2014) focused on children’s
performance after different aspects of the hook-making task were highlighted to children
as well as how they could retrieve and coordinate this information to solve the task. As
such, the analysis focused on performance between conditions rather than stages. However,
it is possible that for some children, seeing a target tool drove their subsequent
innovation. This leaves open the question of whether seeing a target tool is as helpful as
the opportunity to use a target tool in terms of likelihood of going on to solve the hook-
making task. Children aged 3 or 4 years have been shown to demonstrate different
strategies of exploration of materials for different tasks. For example, they used visual
exploration to determine which spoons were the correct size to transport sweets, but they
chose haptic exploration to decide which sticks, of varying rigidity, were suitable to
stir sugar and gravel (Klatzky, Lederman, & Mankinen, 2005). It is yet to be made clear
whether or not children find visual or haptic exploration of premade tools equally useful
in the context of tool innovation or the hook-making task. If the key information that
children extrapolate from a hook demonstration is regarding its shape, we would expect
visual demonstration to be sufficient. However, if the information children require is
regarding some other physical property of the pipe cleaner (e.g., flexibility, rigidity),
we might expect that haptic exploration would be more beneficial. In Study 3, we sought to
compare the effects of seeing versus using a premade hook on performance on the hook-
making task. In Studies 1 and 2, children were given the opportunity to use a hook before
attempting the task. Another factor is whether children benefit more from being given
solution-relevant information before or after they encounter the problem to be solved. In
Studies 1 and 2, children had only used a pipe-cleaner hook before they attempted the
hook-making task, which proved to be beneficial to both younger and older children. In a
previous study, children (and apes) were shown the location of tools they could choose to
use to solve a problem either before or after they had seen the task they were going to
solve (Martin-Ordas, Atance, & Call, 2014). Younger children found it easier to locate the
tools to solve the problem after they had seen the task they would need to solve. These
findings suggest that children are sensitive to the timing of relevant information when
engaging in tool use tasks, and the same may be true of tool innovation tasks. Given the
findings of Martin-Ordas et al. (2014), we might predict that younger children would
benefit more from being given solution-relevant information after already attempting the
hook-making task. Hence, in Study 3, we also manipulated the timing of the experience
children were given (before or after having attempted the task).

        <hss>Participants</hss>

        The participants were 94 children aged 4 or 5 years (M = 4;7, range = 4;3–5;2) and
        96 children aged 6 or 7 years (M = 6;7, range = 6;3–7;2) from two mainstream
        schools in the United Kingdom. The same proportion of children from each school
        were present in each age group. The ethnic composition of the sample was 89%
        Caucasian, 5% Black, and 6% Asian. None of these children had taken part in either
        of the previous two studies.

        <hss>Procedure</hss>

        Children were presented with the same bucket and tube apparatus from the previous
        experiments. As per the 2 × 2 design, children were systematically assigned by
        class list to one of four conditions: See Before, See After, Use Before, or Use
        After. All children completed the standard test phase (hook-making task) from the
        previous experiments and were given the same instructions. The experimenter told
        them, “If you can get the bucket out of the tube, then you can keep the sticker.”
        However, the experience that children had before and after attempting the test
        phase varied per condition. In the See Before condition, children were presented
        with the bucket and tube apparatus. The experimenter then said “Look at this” and
        showed them a premade pipe-cleaner hook. The experimenter then removed this from
        sight, said “Here is something that might help you,” and placed a straight pipe
        cleaner next to the apparatus. Children were then given 1 min to attempt the hook-
        making task. In the See After condition, children first attempted the hook-making
        task (pre-demonstration phase). Children who failed to innovate a pipe-cleaner
        hook and retrieve the bucket were encouraged to put down their materials. The
        experimenter then showed them a premade pipe-cleaner hook, said “Look at this,”
        and gave children a new straight pipe cleaner if necessary. Children then
        attempted the hook-making task for a second time. In the Use Before condition,
        children were presented with the bucket and tube apparatus and a premade pipe-
        cleaner hook. They were allowed up to 1 min to attempt the task with the materials
        given. All children successfully retrieved the bucket using the premade pipe-
        cleaner hook. Children then attempted the hook-making task. In the Use After
        condition, children first attempted the hook-making task (pre-demonstration
        phase). Children who failed to innovate a pipe-cleaner hook and retrieve the
        bucket were encouraged to put down their materials. Pipe cleaners were removed.
        The experimenter then gave children a premade pipe-cleaner hook and said “Here is
        something that might help you.” Children were encouraged to have another go at the
        task for up to 1 min. Once more, all children successfully retrieved the bucket
        using the premade pipe-cleaner hook. Children then attempted the hook-making task
        for a second time. As noted previously, if children failed to make a hook on their
        second attempt at the hook-making task (After conditions: Use After and See After)
        or their only attempt at the task (Before conditions: Use Before and See Before),
        the experimenter demonstrated how to make a pipe-cleaner hook and allowed them to
        have another go at the task.

<hs>  Results and discussion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

There was a significant overall effect of gender on performance in 4- and 5-year-olds,
with girls performing better than boys, χ2Yates(df = 1, N = 94) = 4.115, p = .042, ϕ =
0.231. However, there was no significant effect of gender on performance in 6- and 7-year-
olds, χ2Yates(df = 1, N = 96) = 0.686, p = .408. Because no previous effects of gender
were observed on these tasks, and this difference was present in only one age group, the
result is not discussed further here. Older children performed significantly better than
younger children in the Use After condition, Fisher’s exact test, p = .030, and the See
Before condition, χ2(df = 1, N = 47) = 6.139, p = .013, ϕ = 0.006. However, there were no
significant differences in performance related to age in either the See After condition,
χ2(df = 1, N = 48) = 2.521, p = .112, or the Use Before condition, χ2(df = 1, N = 48) =
1.137, p = .286. Of most interest was whether condition affected performance. Table 3
shows performance across conditions for each age group. Children in the After conditions
who passed during the pre-demonstration phase were included in the analysis. This is to
match children in the Before conditions who may have passed regardless of the opportunity
to see or use a hook and could not be identified. In total, 8 children in the Use After
condition (2 4- and 5-year-olds and 6 6- and 7-year-olds) passed during the pre-
demonstration phase, and 10 children in the See After condition (2 4- and 5-year-olds and
8 6- and 7-year-olds) passed during the pre-demonstration phase. We first looked at
whether the timing of when information relevant to the hook-making task was given affected
performance on the hook-making task. There were no significant differences between
performance in Before and After conditions in 4- and 5-year-olds, χ2Yates(df = 1, N = 94)
= 0.692, p = .405, or in 6- and 7-year-olds, χ2(df = 1, N = 96) = 0.675, p = .411. Second,
we looked at whether there was any difference in performance on the hook-making task
related to whether children were in a Use or See condition. There were no significant
differences in performance of 6- and 7-year-olds between the Use and See conditions,
χ2Yates(df = 1, N = 96) = 1.875, p = .171. However, 4- and 5-year-olds performed
significantly better in the Use conditions compared with the See conditions, χ2(df = 1, N
= 94) = 4.326, p = .038, ϕ = −0.236. We then looked at what was driving the difference
between these conditions in 4- and 5-year-olds using a Bonferroni-adjusted alpha level of
.025 (.05/2). A continuity-corrected chi-square test indicated no significant difference
in success between the Use After and See After conditions, χ2Yates(df = 1, N = 47) =
0.034, p = .853. However, children in the Use Before condition performed significantly
better than those in the See Before condition, χ2Yates(df = 1, N = 47) = 6.139, p = .013,
ϕ = −0.404. Study 3 revealed no clear indication overall that either using or seeing a
target tool is more beneficial than the alternative. Likewise, the timing of clues or
information relating to transformation from the start state to the end goal does not
appear to be important. In other words, being given tool shape prior to attempting
innovation is no more useful than being told the information having already had one failed
attempt at the hook-making task. However, younger children performed significantly better
in the Use Before condition compared with the See Before condition, being more than twice
as likely to succeed in the Use Before condition. This suggests that the Use Before
condition was particularly beneficial for 4- and 5-year-olds in terms of facilitating
innovation of a hook tool on the hook-making task. This complements the findings from
Studies 1 and 2, in which younger children performed at similar levels as older children
when they had the opportunity to use a premade hook tool prior to attempting the hook-
making task. This can also be related to the findings of Cutting et al. (2014), who
concluded that 4- and 5-year-olds experienced less benefit from seeing a target tool than
5- and 6-year-olds. Older children performed well across conditions, with success levels
greater than what might be expected given performance in the control condition of Study 1.
The results suggest that using and seeing a premade target tool is useful for children of
this age regardless of whether this is before or after first attempting innovation.
Younger children also performed well across conditions when compared with performance in
previous studies and in the control condition of Study 1. This suggests that some younger
children were able to coordinate knowledge highlighted to them in order to innovate a hook
tool.

<h>GENERAL DISCUSSION</h>
------------------

Spontaneous tool innovation remains a difficult problem for many children aged below 8
years (e.g., Study 1 control group). Previous studies demonstrate that choosing the
correct tool and tool manufacture following an adult demonstration is relatively easy for
children from as early as 4 years (Beck et al., 2011). The current studies contribute to
our understanding of what children find especially difficult about tool innovation. In
Study 1, when children were given the opportunity to use a premade hook tool, making a
hook of their own on subsequent trials was significantly more likely. Study 2 suggested
that the using element of the pretest experience in Study 1, rather than
choosing/rejecting tools, seemed to be what was driving better performance on the hook-
making task. Using a premade hook made it easier to solve the innovation problem in the
future. This suggests that fundamental to children’s success on the hook-making task was
first interacting with the solution. This provides more evidence that the most difficult
aspect of the hook-making task for children is bringing to mind the solution to the
problem for themselves. However, it also demonstrates that children do not lack the
understanding of how to transform the straight pipe cleaner to a functional hook tool
without being explicitly shown how to do so in an action demonstration. Finally, Study 3
provided further insight into children’s performance on the hook-making task. Children
across age groups and conditions performed better than expected on the hook-making task
compared with previous studies (Beck et al., 2011; Cutting et al., 2014) and children in
the control group of Study 1. Younger children were most successful when they could use a
premade tool before their first innovation trial. For older children, there was no
significant difference between trials. In two conditions (Use Before and See After), there
was no significant difference in success levels between younger and older children. These
results highlight the benefit that younger children experience by being given information
about the target solution. The results also suggest that the same information (e.g.,
seeing a hook before attempting the task) is not equally helpful for all children. The
results from Study 3 may reflect individual differences in children’s learning
preferences. For example, Flynn, Turner, and Giraldeau (2016) recently suggested that
5-year-olds could choose a learning strategy (social or asocial) for themselves that was
effective for them. Children could choose to either attempt a task for themselves or watch
an experimenter attempt it first and then had their learning strategy choice either met or
violated. Although children showed a strong preference overall to learn socially, unlike
3-year-olds, 5-year-olds were also efficient at solving the task under asocial conditions,
when this strategy matched their indicated preference. In the context of Study 3, one
might hypothesize that, similarly, children show preferences for the types of information
or opportunity for exploration offered (visual or haptic) and the timing of this
information (before or after attempting the task). In Study 3, we concluded that using or
seeing a premade tool was beneficial for older children in terms of solving the hook-
making task later, with no single condition being significantly better than another. For
younger children, using a hook was more beneficial than seeing a hook before attempting
the hook-making task, but this difference was not present when the information was
presented after their first attempt at innovation. This finding provides some support to
the claims of Cutting et al. (2014), who concluded that older children benefited from a
target tool demonstration (alongside bending practice), whereas younger children did not.
However, the focus of Cutting and colleagues was on performance between conditions rather
than stages. On closer inspection, younger children in their study did appear to benefit
from seeing a target tool demonstration, albeit not to the extent of the older children.
Following a target tool demonstration, a further 23% (no bending practice) and 37%
(bending practice) of children went on to innovate a hook tool of their own. In the
current investigation, seeing a hook increased tool innovation from near floor (Study 1)
to 30%–58% (see Table 3). This suggests that, for a significant number of 4- and 5-year-
olds, seeing a premade hook facilitated their future hook tool innovation. Cutting et al.
(2014) concluded that 4- and 5-year-olds struggle to innovate both the solution (a hook)
and the means (bending the pipe cleaner) to solve the hook-making task. It was also
concluded that although 5- and 6-year-olds were better at innovating the means to solve
the task following a target tool demonstration and bending practice, spontaneous
innovation of the hook tool solution remained difficult for the majority. Here, we suggest
that Cutting and colleagues’ conclusions may have been slightly pessimistic regarding
younger children’s capabilities. The majority of 4- and 5-year-olds in Studies 1 and 2
could innovate the means to solve the hook-making task, having had the chance to use
(rather than just see) a premade tool. Younger children were also helped by seeing a
target tool where performance was improved from near floor to 30% to 58% (see Table 3). We
suggest that it is especially difficult for children aged 4–7 years to independently
generate the solution to the problem—that they need a hook. The current series of
experiments allows us to comment for the first time on how the performance of children on
the hook-making task compares with that of the corvids. When children were faced with
similar pretest experiences as that of the New Caledonian crow in the Weir et al. (2002)
version of the task, they too were able to innovate a hook to solve the hook-making task.
It would now be interesting to see how corvid species perform on tool tasks such as the
hook-making task without prior exposure to or experience with the target tool. Rooks had a
different pretest experience from that of children and crows (Bird & Emery, 2009). They
were exposed to wooden hook tools prior to needing to make a wire hook of their own. In
sum, they transferred the solution from the wooden hook tool and transferred this to a new
material when they made a wire hook on subsequent trials. Considering recent findings,
this seems remarkable. Beck et al. (2014) found that 4- to 7-year-olds do not transfer
their knowledge of manufacturing a pipe-cleaner hook when they are later required to make
a hook from dowel (or vice versa) to solve a similar task. In line with previous findings
(Beck et al., 2011; Nielsen et al., 2014), we noted children’s difficulty with spontaneous
innovation of a tool to solve the hook-making task. None of the 4- and 5-year-olds, and
only a minority of the 6- and 7-year-olds, innovated a hook tool on their first attempt at
the hook-making task without prior experience of a premade tool. Betty the crow
demonstrated innovation of the means to solve the task but not innovation of the solution
itself, due to her experience with a premade wire hook (Weir et al., 2002). However,
spontaneous tool innovation has been reported in “Figaro” the cockatoo (Auersperg, Szabo,
von Bayern, & Kacelnik, 2012). Given impressive reports of the abilities of certain
nonhuman animal species, it remains intriguing that young children should experience such
difficulty in innovating tools to solve problems independently. It is important to bear in
mind that reports of tool innovation in nonhuman animal species are often individual
cases. For example, although Figaro the cockatoo could innovate a tool, other individuals
either failed to use tools at all or showed components of tool-making behavior, which may
have been the result of shared social experience with Figaro. Although this does not make
the achievements of Figaro any less impressive, this does resonate with the literature
examining children’s propensity for tool innovation. It appears, at least in the case of
younger children (4- to 7-year-olds), that some children have the capacity for innovation,
whereas others do not. A recent study has suggested that individual differences in
divergent and creative thinking are not associated with tool innovation (Beck, Williams,
Cutting, Apperly, & Chappell, 2016). Future research efforts might explore whether the
ability to innovate tools is related to other personal characteristics, personality
traits, or a set of cognitive abilities that promote innovative behavior. Within the
animal literature, it is noted that to unravel the potential underlying cognitive
mechanisms that support innovative tool manufacture, it will be necessary to control the
developmental histories and experiences of participants (Auersperg et al., 2012). This
presents a challenge to the study of tool innovation in children who come from a wide
range of backgrounds with varied experiences. When studying children’s performance on such
tasks, it is important to consider the wider sociocultural context. Children at this age
are likely to have received varied influence from parents and caregivers, including
opportunity for exploration, feedback, and availability of objects. This is especially
true of the youngest children, who have spent less time in full-time state education.
These factors may greatly influence a child’s likelihood to display innovative behavior,
both its onset and its frequency (Tomasello, 1999). Future studies may find ways in which
we can manipulate experience with objects and materials to explore its effect on tool
innovation. Holyoak, Junn, and Billman (1984) argued that analogical reasoning is an
important mechanism for cognitive development because analogy permits the transfer of
knowledge and information from domains that are understood to those that are not. We
propose that the hook-making task may require children to employ analogical reasoning
because they are required to make inferences about novel experiences, identify the
relevant and useful information from target tool demonstrations, and transfer what they
have learned to the innovation phase (for further discussion, see Beck et al., 2014). It
may be that those children with superior analogical reasoning abilities find it easier to
use the information highlighted to them to pass the hook-making task. Future studies may
seek to investigate whether children’s analogical reasoning is related to their tool
innovation ability. Because one of the main aims of these studies was to draw comparisons
with the corvid literature, the current findings are restricted to the results from one
innovation task (hook making). However, children’s difficulty with spontaneous innovation
has been demonstrated on tool innovation tasks such as the Floating Object Task (Hanus et
al., 2011; Nielsen, 2013) and the Loop Task (Tennie et al., 2009). Here, children found it
especially difficult to innovate the solution to the hook-making task—that they require a
hook to retrieve the bucket from the tube. However, when given the opportunity to use the
solution to the hook-making task, they could innovate the means to solve the task without
prior training; they transformed the straight pipe cleaner into a pipe-cleaner hook. It
remains unclear why some children find tool innovation difficult, whereas others do not. A
more complete picture of the developmental trajectory of tool innovation should be built,
with further investigation into the levels of scaffolding required and conditions that
might facilitate children’s independent innovation on a wide range of innovation tasks.


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<ART>The effects of active social media engagement with peers on body image in young women
================================================================================

Authors: Jacqueline V. Hogue, Jennifer S. Mills
DOI: 10.1016/j.bodyim.2018.11.002
Year: 2019  |  Pages: 1-5
ASJC codes: 3200, 3202, 3207
Keywords: Body image, Family member, Peer, Social comparison, Social media, Young adult women

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This experimental study examined the effects of engaging on social media with attractive female peers on young adult women's body image. Participants were 118 female undergraduate students randomly assigned to one of two experimental conditions. Participants first completed a visual analogue scale measure of state body image and then either browsed and left a comment on the social media site of an attractive female peer (n = 56) or did the same with a family member (n = 62) and then completed a post-manipulation visual analogue scale measure of state body image. A 2 × 2 mixed analysis of variance showed a significant interaction between condition and time. Follow-up t-tests revealed that young adult women who engaged with an attractive peer on social media subsequently experienced an increase in negative body image (dependence-corrected d = 0.13), whereas those who engaged with a family member did not (dependence-corrected d = 0.02). The findings suggest that upward appearance comparisons on social media may promote increased body image concerns in young adult women.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Social media’s relation to body image is often examined using social comparison theory,
which purports people self-evaluate based on comparisons with similar others. In upward
social comparisons, people compare themselves to superior individuals (Festinger, 1954).
Among women, making upward appearance comparisons is moderately related to negative body
image (Myers & Crowther, 2009). On social media, young adult women most frequently make
upward appearance comparisons to peers and rarely compare their appearance to family
(Fardouly & Vartanian, 2015; Fardouly, Diedrichs, Vartanian, & Halliwell, 2015). Cross-
sectional research shows negative associations between body image and active social media
engagement (ASME), particularly photo-based ASME (Cohen, Newton-John, & Slater, 2017;
Holland & Tiggemann, 2016; Kim & Chock, 2015; Meier & Gray, 2014). We consider ASME
behaviours of viewing and commenting on friends’ social media. ASME requires content
engagement and may have a greater impact on psychology than passive social media
consumption. Among young adult women, ASME has a small, significant positive correlation
with drive for thinness (Kim & Chock, 2015). Facebook photo activity has small-to-moderate
positive correlations with thin ideal internalization, self-objectification, and drive for
thinness, and a small negative correlation with weight satisfaction (Meier & Gray, 2014).
Cross-sectional research suggests upward social comparisons to young adult women’s peers
on social media weakly mediates the relationship between social media use and drive for
thinness and body dissatisfaction, and that these comparisons have a stronger effect on
body image concerns than do celebrity and model upward social comparisons (Fardouly &
Vartanian, 2015). Frequency of appearance comparison to family is uncorrelated with social
media use and body image (Fardouly & Vartanian, 2015). No published studies have shown
causal effects of ASME with peers on body image. Women are more likely than men to use
social media to view others’ photos, and ASME is how they typically use social media
(Smith, 2014). They engage with social media specifically to compare themselves with
others (Haferkamp, Eimler, Papadakis, & Kruck, 2012). Men are more likely to use social
media to find friends (Haferkamp et al., 2012). Women feel worse about how they look than
men (Engeln, 2017). On social media, young adult women present idealized images of
themselves. Consequently, women on social media likely see idealized images of their peers
and compare themselves with these idealized images (Manago, Graham, Greenfield, &
Salimkhan, 2008); men are less likely to use social media like this. Thus, there is a need
for research on potential causal effects of photo-based ASME on young adult women’s body
image. This study investigated the effect of photo-based ASME with peers (as compared to
family) on young adult women’s body image. Because women are more likely to struggle with
body dissatisfaction (Mills, Roosen, & Vella-Zarb, 2011) and use image-based social media
than are men (Greenwood, Perrin, & Duggan, 2016), we focused on young adult women. We
hypothesized ASME with a female peer whom young adult women perceive as more attractive
than themselves (upward social comparison) would result in more negative body image,
whereas engaging with a woman unlikely to be an appearance comparison target (a non-peer
family member not perceived as more attractive than themselves) would not affect body
image.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The initial sample consisted of 143 female York University undergraduate students enrolled
in an Introduction to Psychology course recruited through an online experiment management
system for a study on “social media and relationships.” Eighteen participants were unable
to adhere to experimental instructions and were excluded from all analyses, leaving a
final sample of 125. Participants ranged in age from 17 to 27 years (M = 19.59, SD = 2.00)
and in body mass index (BMI) from 15.43 to 42.26 kg/m2 (M = 24.31, SD = 5.00). The self-
reported ethnicity of the sample was: 25.6% South Asian; 16.0% European; 14.4% Middle
Eastern; 8.0% Caribbean; 4.0% Pacific Islander; 7.2% African; 4.8% Latin, Central, and
South American; 4.8% East Asian; 1.6% African-American; 1.6% Indigenous; and 7.2% other. A
few participants (4.8%) did not report their ethnicity.

        <hss>Demographics</hss>

        Participants reported their age, ethnicity, whether English was their first
        language, and years of post-secondary education in an online questionnaire 1.5
        months before the experiment. Level of post-secondary education was self-reported
        by answering, “How many years have you been a university student?” English as a
        first language was self-reported by answering, “Is English your first language?”
        and, if not, by answering, “Do you consider yourself fluent in English?”

        <hss>State body image dissatisfaction</hss>

        Visual analogue scales (VAS) measured state overall appearance (VAS-OAD) and body
        dissatisfaction (VAS-BD) before and after ASME. Participants rated how
        dissatisfied they felt about their overall appearance and body by placing a
        vertical line on a 10-cm horizontal line. Responses were scored to the nearest
        millimeter, producing a 100-point scale. The range of responses was none to very
        much. Higher scores indicated greater state body or overall appearance
        dissatisfaction. Heinberg and Thompson (1995) constructed the VAS-BD and VAS-OAD
        measures, averaging them to form one body dissatisfaction measure. We refer to
        this averaged measure as the State Body Image Scale (SBIS). The pre-manipulation
        SBIS Spearman-Brown coefficient was .86 and the inter-item correlation was .79.
        The post-manipulation SBIS Spearman-Brown coefficient was .88 and the inter-item
        correlation was .78. Heinberg and Thompson (1995) demonstrated convergent validity
        of the VAS-BD and VAS-OAD with the Eating Disorder Inventory–Body Dissatisfaction
        subscale (Garner, Olmsted, & Polivy, 1983), r = .66, p <  .01, r = .76, p < .01,
        respectively.

        <hss>Height and weight</hss>

        Participants were weighed and measured on a balance beam scale at the study’s end.

        <hss>ASME with a peer manipulation</hss>

        Participants in this condition (the Peer Condition) completed the pre-manipulation
        SBIS and then identified a female peer within five years of their own age whom she
        followed on social media and explicitly considered more attractive than herself
        (see Appendix A for full Peer Condition identification instructions). Participants
        reported the peer’s relationship to them and her initials. Next, participants
        viewed and commented on this peer’s social media pages for 5 min on Facebook and
        then 5 min on Instagram. Participants looked at only their identified peer’s
        social media, found a photo of her on Facebook, and left an online comment on this
        photo. Participants could engage with the peer’s other Facebook content during the
        5-min task. After participants received instructions, the experimenter loaded
        www.facebook.com and left. The experimenter came back after 5 min and gave the
        participant similar instructions, asking her to do the same thing on Instagram.
        The experimenter then loaded www.instagram.com and left. Participants commented on
        photos of the same peer across Facebook and Instagram. Once the next 5 min were
        over, the experimenter came back into the room, confirmed the instructions had
        been followed, and asked the participant to complete a social media interaction
        questionnaire and the post-manipulation SBIS.

        <hss>ASME with family manipulation</hss>

        The procedure and instructions in this condition (the Family Condition) were
        identical to the Peer Condition, except participants engaged with a female family
        member’s social media. They looked at and commented on a non-peer, not-more-
        attractive family member’s social media posts for 5 min. per social media platform
        (i.e., Facebook and Instagram). Non-peer was defined as someone at least five
        years younger or older than the participant (see Appendix B).

        <hss>Social media interaction questionnaire</hss>

        Participants were asked whether they found a photo of the person they identified
        earlier on Facebook and Instagram and to write the comments they had left on her
        social media.

        <hss>Manipulation checks</hss>

        Participants confirmed their and their social media contact’s age, and their
        relationship to her. Participants were asked again during the debriefing if they
        followed the instructions. Browser history was checked after each participant
        completed the experiment. The social media interaction questionnaire also served
        as a manipulation check, as all participants wrote down the comments they left. As
        noted above, 18 participants could not identify a suitable contact and were
        excluded from the analyses.

<hs>  Procedure</hs>
  ~~~~~~~~~

The authors’ institutional human participants ethics review board approved this study.
Testing was conducted from June 6, 2016 to June 13, 2017. Only female students with
Facebook and Instagram accounts were eligible and received partial course credit for
participating. Participants provided informed consent in the online questionnaire and then
again right before the experiment. Participants were randomly assigned to condition using
a coin toss. Each participant was seated alone in a private room; the experimenter only
entered the room to explain instructions. Questionnaires were anonymous. Participants were
weighed and debriefed in writing and verbally after the study.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

The data were examined for normality, with no notable violations. Missing data accounted
for 0.8% of the total values in the dataset. Both pre- and post-SBIS were missing 0.8% of
data. Missing data were missing completely at random (MCAR), as determined by using Little
(1988) MCAR analysis, χ2(2) = 1.35, p =  .509. We inputted missing values using the
multiple imputation expectation maximization technique, generating five imputations. Using
G*Power for an a priori power analysis, for an analysis of variance (ANOVA) repeated
measures within-between interaction, a Cohen (1988) f of 0.15 (i.e., a small-to-medium
effect size), and a power estimate of 90%, the recommended sample size was 120. Additional
participants were run to allow for any necessary exclusions. A 2 × 2 mixed ANOVA was
conducted to compare the effect of ASME condition on SBIS scores pre- and post-
manipulation. The independent variable was condition. Following Finch (2016) approach to
address missing data, using the R base package (R Core Team, 2018), we pooled p-values.
Results were considered significant at the α = .05 level, unless otherwise specified
below. Analyses were performed using SPSS v. 24 and R.

<hs>  Randomization check</hs>
  ~~~~~~~~~~~~~~~~~~~

Preliminary analyses found no between-group differences in the distribution of ethnic
groups, Fisher’s exact test p =  .120; English as a first language, χ2(1) = 2.30, p =
.129; number of years of post-secondary education, t(123) = 0.75, p = .409, d = 0.14; mean
age, t(123) = 0.23, p = .819, d = 0.04; and mean BMI, t(123) = 1.06, p =  .293, d = 0.19.
Of those who reported English was not their first language (n = 31), the number of
participants who considered themselves fluent in English did not differ by condition,
χ2(1) = 1.35, p =  .245. Thus, randomization resulted in equivalent groups on these
variables.

<hs>  Manipulation checks</hs>
  ~~~~~~~~~~~~~~~~~~~

If a participant viewed a social media contact’s profile, the history tab showed an
address including the contact’s username. History tab checks confirmed participants
followed the instructions. After excluding the aforementioned 18 participants, all
remaining participants (N = 125) indicated they found a photo of their contact on Facebook
and Instagram on which to comment. Generally, social media “friends” are peers (West,
Lewis, & Currie, 2009). To maximize ecological validity, we included participants who
identified a best, close, or just “friend” (n = 32). The most commonly reported
relationship in the Peer Condition was “friend” (n = 22). “Cousin” (n = 38) was the most
commonly reported relationship in the Family Condition.

<hs>  Effects of experimental condition on state body image</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Despite randomization to condition and no observed pre-manipulation differences on
sociodemographic variables or BMI, a t-test revealed an unexpected difference in pre-SBIS
scores between conditions, t(123) = 2.74, p =  .006, d = 0.49. We inspected the
distribution of pre-SBIS scores to explain the pre-existing group difference and noted
some visual outliers. We then omitted cases where the pre-SBIS was greater than or less
than 2 SD above or below the mean. That resulted in excluding seven Peer Condition
participants with very high pre-SBIS scores, and a sample of 118 for the main analyses.
The difference in pre-SBIS scores between conditions was no longer significant, t(116) =
1.83, p =  .070, d = 0.30. The time × condition interaction on SBIS was significant, F(1,
116) = 9.98, Wilks’ Λ = 0.92, p = .002, ηp2 = .08. Follow-up t-tests revealed there was no
difference between pre-SBIS (M = 35.89, SD = 23.62) and post-SBIS (M = 35.14, SD = 22.99)
in the Family Condition, t(61) = 0.77, p =  .438, dependence-corrected d = 0.02. However,
there was a significant difference between pre-SBIS and post-SBIS in the Peer Condition,
t(55) = 3.33, p =  .002, dependence-corrected d = 0.13. As predicted, in the Peer
Condition only, participants reported worse state body image after the experimental
manipulation (M = 48.70, SD = 22.11) than before the manipulation (M = 43.46, SD = 21.06).
There was a significant difference in post-SBIS scores between conditions, t(116) = 2.83,
p =  .005, d = 0.59. The results revealed a significant main effect of time, F(1, 116) =
4.89, Wilks’ Λ = 0.96, p =  .029, ηp2 = .04, and condition on SBIS, F(1, 116) = 6.09, p =
.015, ηp2 = .05, but they were qualified by the interaction.

<h>DISCUSSION</h>
----------

We hypothesized that young adult women who actively engaged with the image-based social
media of attractive peers (upward social comparison targets) would have more negative body
image than before doing so, whereas young adult women who engaged with the image-based
social media of family (unlikely social comparison targets) would not. Results showed ASME
with attractive peers’ appearance-based social media resulted in worsened body image in
young adult women, whereas interacting with that of family had no effect on state body
image, supporting our hypothesis. Our findings align with the recommendation that body
image media literacy programs should highlight social media use, especially pressures
associated with viewing images of others (Holland & Tiggemann, 2016), and peers in
particular. However, similar to other social media and body image research findings, our
effect size was small, and possibly negligible in real-world terms. Thus, these results
should not be overstated. This study adds to literature showing young adult women’s body
image is negatively affected by viewing attractive women’s photos on social media
(Fardouly, Pinkus, & Vartanian, 2017; Haferkamp & Krämer, 2011; Kim & Park, 2016; Tamplin,
McLean, & Paxton, 2018). It extends prior research by showing ASME with known, attractive
female peers causes adverse effects on body image, but the same type of interaction with
family does not have this effect. Our results were found across a racially heterogeneous
sample. Allowing our participants to identify their own known contact may have allowed
them to identify personal (e.g., racial) attractiveness concepts.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Focusing on short-term effects limited our study. Our female-only sample was drawn from
one university. Our results are not generalizable to all young adult women and cannot
generalize to men. Despite effective randomization in terms of sociodemographic variables
and BMI, participants in the Peer Condition unexpectedly had more negative baseline body
image scores than those in the Family Condition. Therefore, a degree of response bias was
inadvertently introduced. Cautious interpretation of our findings is warranted. Future
work should investigate whether ASME with peers affects young men’s body image and if
certain individuals are more affected by ASME with peers.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

This is the first study showing actively engaging with attractive peers’ social media
causes worsened body image in young adult women. ASME with family not more attractive than
oneself does not cause body image changes. It is common for young adult women to engage
with peers’ image-based social media; this study shows this activity can cause a small
increase in negative state body image.

<h>AUTHOR NOTE</h>
-----------

We thank Anastasia Buchvostov and Dina Nikseresht for their assistance with data
collection and entry, and Dr. Rob Cribbie for his assistance with data analysis. This
research was supported by a SSHRC Insight Grant awarded to the second author.


<h>REFERENCES</h>
----------

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<ART>The epistemic innocence of motivated delusions
==============================================

Authors: Lisa Bortolotti
DOI: 10.1016/j.concog.2014.10.005
Year: 2015  |  Pages: 490-499
ASJC codes: 3204, 3205
Keywords: Anosognosia, Anxiety, Beliefs, Delusions, Emotions, Epistemic status, Erotomania, Motivation, Reverse Othello syndrome, Wellbeing

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Delusions are defined as irrational beliefs that compromise good functioning. However, in the empirical literature, delusions have been found to have some psychological benefits. One proposal is that some delusions defuse negative emotions and protect one from low self-esteem by allowing motivational influences on belief formation. In this paper I focus on delusions that have been construed as playing a defensive function (. motivated delusions) and argue that some of their psychological benefits can convert into epistemic ones. Notwithstanding their epistemic costs, motivated delusions also have potential epistemic benefits for agents who have faced adversities, undergone physical or psychological trauma, or are subject to negative emotions and low self-esteem. To account for the epistemic status of motivated delusions, costly and beneficial at the same time, I introduce the notion of epistemic innocence. A delusion is epistemically innocent when adopting it delivers a significant epistemic benefit, and the benefit could not be attained if the delusion were not adopted. The analysis leads to a novel account of the status of delusions by inviting a reflection on the relationship between psychological and epistemic benefits.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In this paper, I ask whether delusions that have been construed as playing a defensive
function have epistemic benefits. Defence mechanisms are “a means of nuancing or
processing information such that it is rendered less anxiety-provoking” (McKay, Langdon, &
Coltheart, 2005, p. 316). Arguably, delusions can prevent loss of self-esteem and help
manage strong negative emotions (Butler, 2000; Ramachandran, 1996; Raskin and Sullivan,
1974; Bentall, 1994). The claim that delusions are psychologically adaptive can be made on
these grounds, and it was recently discussed in the psychological literature (McKay &
Dennett, 2009; McKay & Kinsbourne, 2010; McKay et al., 2005). Without denying that
delusions are typically false and irrational, and that they compromise good functioning to
a considerable extent, my goal here is to establish whether the psychological benefits
attributed to those delusions that have been construed as playing a defensive function can
translate into epistemic benefits. Thinking about delusions in terms of potential
epistemic benefits leads to a more balanced view of the role of delusions in a person’s
cognitive and affective life and invites a reflection on the relevance of contextual
factors in epistemic evaluation. In Section 1, I review the general features of delusions
and describe the epistemic features of delusions that can be construed as playing a
defensive function (hereafter, motivated delusions) and their adverse effects on
functioning. In Section 2, I consider arguments for the psychological benefits of Reverse
Othello syndrome, erotomania and anosognosia. I also describe the proposal by McKay and
Dennett (2009), according to which some false beliefs (adaptive misbeliefs) are the result
of a mechanism that allows motivational factors to influence belief formation. Can
motivated delusions be adaptive misbeliefs? In Section 3, I introduce the notion of
epistemic innocence. Cognitions are epistemically innocent when, despite their epistemic
costs, they carry a significant epistemic benefit (Epistemic Benefit condition) that could
not be attained otherwise (No Alternatives condition). I argue that motivated delusions
have the potential for satisfying the two conditions for epistemic innocence and I offer
an illustration from anosognosia to support this claim. In Section 4, I suggest that the
epistemic innocence potential of motivated delusions highlights the need for a more
nuanced evaluation of epistemically costly cognitions and invites a new way of
understanding the relationship between psychological and epistemic benefits.

<h>MOTIVATED DELUSIONS</h>
-------------------

Clinical delusions are symptoms of psychiatric disorders such as schizophrenia, dementia,
and delusional disorders. Delusions exemplify failures of rationality and are defined on
the basis of surface features that have an epistemic character. Here are some popular
definitions: A false belief based on incorrect inference about external reality that is
firmly held despite what almost everyone else believes and despite what constitutes
incontrovertible and obvious proof or evidence to the contrary. The belief is not
ordinarily accepted by other members of the person’s culture or subculture (i.e., it is
not an article of religious faith). When a false belief involves a value judgment, it is
regarded as a delusion only when the judgment is so extreme as to defy credibility. A
person is deluded when they have come to hold a particular belief with a degree of
firmness that is both utterly unwarranted by the evidence at hand, and that jeopardises
their day-to-day functioning. Delusions are generally accepted to be beliefs which (a) are
held with great conviction; (b) defy rational counter-argument; (c) and would be dismissed
as false or bizarre by members of the same socio-cultural group. The definitions above
characterise delusions on the basis of their epistemic features, including lack of
warrant, fixity, resistance to counterargument, and implausibility. Not all delusions
manifest such features to the same extent, and delusions may differ in the way they
interact with the person’s other cognitive or affective states.

<hs>  Types of delusions</hs>
  ~~~~~~~~~~~~~~~~~~

Davies, Coltheart, Langdon, and Breen (2001) helpfully distinguish between circumscribed
and elaborated delusions. Circumscribed delusions are not well integrated with the other
beliefs the person has, and the epistemic features that characterise these delusions do
not necessarily “spread” to the rest of the person’s belief system. Some of these
delusions, so-called “deficit” delusions (McKay & Dennett, 2009), are the result of brain
damage or cognitive deterioration, and, even if they were given a psychodynamic
interpretation in the past, there is now little room for motivational factors in an
account of their formation. Examples are the Capgras delusion (the belief that a loved one
has been replaced by an impostor) and mirrored-self misidentification (the belief that
there is a stranger in the mirror when one looks at one’s own reflection). Other
circumscribed delusions have been construed as playing a defensive function, and
motivational factors are sometimes advocated in the explanation of their formation. Such
delusions often follow trauma. Examples are the Reverse Othello syndrome (the belief that
one’s romantic partner is faithful when she is not) and anosognosia (the denial of
illness, for instance the denial that one’s limb is paralysed). Delusions emerging in the
context of schizophrenia can be systematised and elaborated. They can turn into complex
narratives used to explain most of the person’s experience. Examples are the delusion of
persecution (the belief that others are threatening and intend to cause harm), the
delusion of grandeur (the exaggerated belief in one’s self-worth), and the delusion of
reference (the belief that some events are highly significant when they are not). A
popular hypothesis is that delusions in schizophrenia are offered as an explanation for
the person’s hypersalient experience. Given that hypersalient experiences cause anxiety
and distress in the prodromal phase of psychosis, delusions emerge as hypotheses by which
the person makes sense of their experiences (Jaspers, 1963; Kapur, 2003; Mishara and
Corlett, 2009). Delusions in schizophrenia can put an end to a state of uncertainty that
causes anxiety and distress. Sometimes the “need for closure” is discussed in this context
(McKay & Kinsbourne, 2010) and it indicates a preference for certainty over uncertainty
and for predictability over unpredictability. In addition to satisfying the need to have
an explanation as opposed to none, it has been argued that some delusions in schizophrenia
can be motivated due to their specific content. Among others, delusions of grandeur and
delusions of persecution seem to protect the person from a negative conception of the self
and from low self-esteem. In terms of aetiology, it is plausible that a combination of
neurobiological and psycho-social factors (including motivational factors) contribute to
the formation of delusions (Bentall, Kinderman, & Kaney, 1994; Davies, 2009; McKay &
Kinsbourne, 2010; Roberts, 1992). For instance, Aimola Davies and Davies (2009) argue that
a two-factor theory of delusion formation can make sense of most delusions, where the
first factor explains where the delusion comes from, and the second factor explains why
the delusion is not rejected. The first factor usually consists in an anomalous experience
or a neuropsychological deficit. The second factor consists in an impairment of belief
evaluation, that is, a problem with the assessment of the evidence for and against the
delusional belief. Such a problem may be caused by cognitive impairments, but may also be
caused by a motivationally-biased handling of the evidence. When no anomalous experience
or deficit can be identified, it is possible that motivation constitutes the first factor,
in which case the delusion would emerge as a defence mechanism (McKay et al., 2005). Here
I do not propose to discuss the role of motivation in delusion formation, rather I am
interested in evidence for the claim that delusions have psychological benefits, and such
evidence is often reviewed in the discussion of different delusion formation theories. For
convenience and due to space limitations, I will concentrate on those delusions that have
been explicitly construed as defence mechanisms in the psychological literature, but I
make no assumption about such accounts being the best explanations of how the delusions
are formed. For some of the delusions I shall describe, it is possible that a defence
mechanism explains the origin of the delusion and its content. For all of these delusions,
it is plausible that motivational factors play some role in the maintenance of the
delusions. But motivational factors need not play any role in delusion formation for
delusions to have psychological benefits.

<hs>  What is wrong with motivated delusions?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Let me describe some of the characteristics of motivated delusions that amount to
epistemic costs and can also lead to impaired functioning. Motivated delusions can be
characterised as irrational beliefs, in that they are implausible, they do not accurately
represent reality, they do not respond to evidence, and they may not always be
consistently reflected in behaviour (Bortolotti, 2009). For instance, people with
motivated delusions may be convinced of the truth of the delusion but at the same time
exhibit some “covert recognition” that the content of the delusion is false. When they are
circumscribed, motivated delusions may conflict with other beliefs the person has,
contributing to an overall inconsistent set of beliefs. When they are elaborated and
systematised, they are likely to integrate well with a number of other beliefs that also
play a defensive function. I will consider three cases of motivated delusions. An example
of a monothematic delusion with a defensive function that emerged as a result of brain
damage is the case of Reverse Othello syndrome (Butler, 2000) discussed in some detail by
McKay et al. (2005). A man, BX, delusionally believed that he was in a happy relationship,
when in fact his partner had left him. Butler’s patient was a talented musician who had
sustained severe head injuries in a car accident. The accident left him quadriplegic,
unable to speak without reliance on an electronic communicator. One year after his injury,
the patient developed a delusional system that revolved around the continuing fidelity of
his partner (who had in fact severed all contact with him soon after his accident). The
patient became convinced that he and his former partner had recently married, and he was
eager to persuade others that he now felt sexually fulfilled. BX’s belief in the fidelity
of his previous partner and the continued success of his relationship was very resistant
to counterevidence. BX believed that his relationship was going from strength to strength
for a few months, even though his former partner did not want to communicate with him and
was in a relationship with someone else (Butler, 2000, p. 86). The Reverse Othello
syndrome can be seen as a special case of erotomania. In erotomania, a person comes to
believe that another person, often of a perceived higher status (e.g., a teacher, an older
or more successful person, a celebrity), is in love with her when there is no evidence in
support of that belief. Here is the case of a young woman, LT, who started behaving
strangely when she became obsessed with the idea that a fellow student was in love with
her although the two had never spoken to each other. Her conversation, when unrelated to
her delusional process, was rational, coherent, appropriate, and relevant. [ …] When
speaking of the delusional process, she went into great detail, explaining the messages
she received from her fantasied lover, signs which she received on TV, from the colors of
dresses, license plates on cars, and from several other sources. She saw all of this as
proof of the fact that the young man was in love with her and was planning to marry her.
Numerous attempts to offer LT evidence that her belief was false failed: after two and a
half years after the delusion emerged, the alleged lover was asked to talk to LT on the
phone, following a suggestion by LT’s mother. He told LT that he did not have any
intention to marry her and that he could barely remember who she was. But LT was convinced
that her mother had arranged for her to talk to another man and did not abandon her
delusion. Motivated delusions are also found in the context of anosognosia, the denial of
illness (most commonly, the denial that a limb is paralysed). Delusions take the form of:
“I am moving my arm”, when the arm cannot move; or “I can climb stairs but I am a little
slow” when a leg is paralysed. Anosognosia has been considered as a pathology of belief:
“There is a mismatch between the patient’s estimate of his or her abilities and the
reality of the impairment” (Aimola Davies, Davies, Ogden, Smithson, & White, 2009, p.
188). In anosognosia, people deny evidence supporting the fact that they are impaired.
Here is the case of a patient with anosognosia for hemiplegia: [A]sked to clap the hands,
[she] lifted her right hand and put it in the position of clapping, perfectly aligned with
the trunk midline, moving it as if it was clapped against the left hand. She appeared
perfectly satisfied with her performance, never admitting that the left arm did not
participate in the action. This despite the fact that the patient could see that the left
hand did not clap against the right hand and the typical sound of clapping was not heard.
It is not clear to what extent people with anosognosia are unaware of their impairment,
given that, on occasion, they seem to implicitly acknowledge it. For instance, a person
with a paralysed leg might deny paralysis but at the same time acknowledge that she cannot
climb stairs properly. She might even provide a confabulatory explanation of her poor
performance, saying that it is due to tiredness or to arthritis (Ramachandran, 1995, p.
23). The delusions I have described are not just implausible and irresponsive to evidence
but they have an adverse effect on wellbeing and interfere with interpersonal
relationships. The person reporting the delusion stops being regarded as a trustworthy
source of information about the topic of the delusion and may be socially sanctioned or
excluded for that reason. Relationships with family members and with healthcare
professionals may be strained as a result of the absence of a “shared reality”
(Fotopoulou, 2008, p. 546) and common goals. In many cases of erotomania (Lovett-Doust &
Christie, 1978), the person develops an obsession with the delusional theme, loses
interest in her family and friends, gives up her daily activities, and becomes isolated as
a result. Anosognosia can have negative effects on people’s health. For instance, it can
interfere with therapy and rehabilitation (Fotopoulou, 2008, p. 554). If the person does
not acknowledge an impairment due to a recent trauma, she will not understand the need to
engage in rehabilitation; indeed it has been found that anosognosia is “an inhibitory
factor hampering rehabilitation” (Maeshima et al., 1997, p. 691).

<h>DELUSION AS PSYCHOLOGICALLY ADAPTIVE</h>
------------------------------------

Considerations about the epistemic costs of delusions and their adverse effects on
functioning seem to rule out the possibility that delusions have any benefits. However, it
has been argued that the adoption of a motivated delusion helps manage overwhelmingly
negative emotions that would otherwise lead to depression and protects against negative
self-conceptions that would otherwise lead to low self-esteem. In the light of these
arguments, the relationship between delusions and wellbeing appears more complex than one
might have expected. For instance, Lansky (1977, p. 21) writes that delusion “is
restitutive, ameliorating anxieties by altering the construction of reality”.

<hs>  Motivated delusions in context</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the case of Reverse Othello syndrome I mentioned earlier, the delusion seemed to
protect BX from the undesirable truth that his romantic partner had left him while he was
coping with the consequences of permanent disability. Butler, who first reported on this
case, describes the period preceding the report of the delusion: [H]is communicative
responses initially indicated considerable insight and the beginning of an intense
emotional response to a massive disability and a fracturing of his interpersonal
relationships. Gradually, in the year following his injury, BX developed the delusion that
his former romantic partner was still in a successful relationship with him, and also that
they had recently married. While still in hospital, he often asked to go home so that he
could see his wife. Butler argues that the delusion relieved the sense of loss that BX was
feeling at the time. [A]ppearance [of delusions] may mark an adaptive attempt to regain
intrapsychic coherence and to confer meaning on otherwise catastrophic loss or emptiness.
As gradually as it had appeared, BX’s delusional system dissolved, and by the end of the
process BX realised that his former partner had moved on, was not married to him, and had
no intention to go back to him. No other delusions or psychotic symptoms were observed.
This happened roughly at the time when BX had completed his physical rehabilitation and
was ready to return home. Butler does not advocate a purely motivational explanation for
BX’s delusion, but simply argues that different factors might have been at play, and that
a psychological defence against depression contributed to the fixity and elaboration of
BX’s delusional system. Independent of the role of motivational factors in the formation
or maintenance of delusions, Butler makes a case for the presence of psychological
benefits. The delusion kept BX’s depression at bay at a very critical time. Acknowledging
the end of his romantic relationship might have been disastrous at a time when he was
coping with the realisation of his new disability and its effects on his life. Erotomania
more generally has also been described as an adaptive response (Raskin & Sullivan, 1974)),
and it is significant that it often develops following a physical/psychological trauma or
adverse circumstances. In many of the case studies of erotomania reported in the
literature, the delusion seems to affect people who have a history of depression and feel
lonely or under-appreciated (Hollender & Callahan, 1975). Consider LT, the young woman who
developed erotomania and whose case was reported by Jordan and Howe (1980). Her background
fits with the general profile described: The patient has a twin sister, who at that time
was a junior in college, and a younger sister, who was two years old at the time of the
onset of this disorder. In describing L.T.’s twin sister, Mrs. T. indicated that she was
outgoing, friendly, and though somewhat reserved, maintained close relationships with
people of both sexes. The mother stated that the patient in contrast had always been a
quiet and rather inhibited child. She was much more reserved than her popular sister and
dated infrequently. She was also described as being studious, an avid reader, highly
moralistic, and a loner. Moreover, she tended to be somewhat suspicious and mistrustful.
Her limited heterosexual experiences were characterized as being very short-lived.
According to the mother, one such relationship had just recently ended abruptly and she
related that the patient appeared rather emotionally distraught by this. In many cases of
erotomania (Lovett-Doust & Christie, 1978, p. 105), there are identifiable
“pharmacological, metabolic, and physiological and structural causes” (including injection
of cortisone, alcoholism, meningioma, ingestion of contraceptive pills), but also
“psychological and situational triggers”. People experience loneliness and loss prior to
adopting the delusion, and in some cases the emergence of the delusion follows a traumatic
event (e.g., the discovery of one’s partner’s infidelity, the death of a loved one, or the
birth of a child then given up for adoption). This seems to suggest that the delusion
plays a defensive function in that it compensates for loss or protects one from low self-
esteem. In anosognosia, the connection between trauma and delusion is more explicit. The
person refuses to acknowledge a serious impairment as a result of trauma or illness and,
also often fails to recognise its implications (although the denial of the impairment and
the failure to acknowledge its implications can dissociate, see Aimola Davies et al.,
2009). Delusions occurring in anosognosia can be seen as playing a defensive function, but
purely motivational accounts of anosognosia have been strongly criticised for failing to
account for the fact that anosognosia is much more likely to emerge when the right
parietal lobe is damaged, and that the denial seems to be “domain-specific”: the person
may deny one impairment and acknowledge another. Ramachandran describes a patient who
would go to great lengths to deny the paralysis of her limb but happily admitted to having
diabetes (Ramachandran, 1995, pp. 23–24). To explain these phenomena, popular accounts of
anosognosia have attempted to combine neuropsychological and motivational factors (Aimola
Davies et al., 2009; Ramachandran, 1996). Ramachandran advances the hypothesis that the
behaviours that give rise to delusions in this context are an exaggeration of normal
defence mechanisms that have an adaptive function. Denying change can sometimes be
instrumental to preserving a coherent system of beliefs and behaving in a stable and
predictable manner (Ramachandran, 1996). The psychological advantages are not necessarily
cashed out in terms of the preservation of the concept of the self as healthy, but in
terms of the preservation of the concept of the present self as coherent with that of the
past self. Fotopoulou observes the same phenomenon in people with memory impairments and
anosognosia who do not seem to update personal information: [P]atients may need to
highlight their continuity and coherence with their past selves and may not be able to
understand or deal with the loss of their previous family and social role. Aimola Davies
and Davies (2009) report positive and negative effects of anosognosia on wellbeing,
suggesting that there could be a role for motivational factors in the explanation of
anosognosia. As I mentioned in Section 1.2, anosognosia has negative effects, as people
who do not acknowledge the illness or impairment may be slow in seeking treatment and
unmotivated to engage in rehabilitation. But after the initial stages of illness,
anosognosia is associated with fewer negative emotions and reduced anxiety.

<hs>  Delusions as a shear pin</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

According to the “shear-pin” account developed by McKay and Dennett (2009), some false
beliefs that help manage negative emotions and avoid low self-esteem and depression can
count as psychologically adaptive. McKay and Dennett suggest that, in situations of
extreme stress, motivational influences are allowed to intervene in the process of belief
evaluation, causing a breakage. Although the breakage is bad news epistemically, as the
result is that people come to believe what they desire to be true and not what they have
evidence for, it is not an evolutionary “mistake”, rather it is designed to avoid
breakages that would have worse consequences for the person’s self-esteem and wellbeing.
What might count as a doxastic analogue of shear pin breakage? We envision doxastic shear
pins as components of belief evaluation machinery that are “designed” to break in
situations of extreme psychological stress (analogous to the mechanical overload that
breaks a shear pin or the power surge that blows a fuse). Perhaps the normal function
(both normatively and statistically construed) of such components would be to constrain
the influence of motivational processes on belief formation. Breakage of such components,
therefore, might permit the formation and maintenance of comforting misbeliefs – beliefs
that would ordinarily be rejected as ungrounded, but that would facilitate the negotiation
of overwhelming circumstances (perhaps by enabling the management of powerful negative
emotions) and that would thus be adaptive in such extraordinary circumstances. Could
motivated delusions be adaptive misbeliefs? The mechanism that inhibits motivational
influences on belief evaluation would be compromised, and as a result of this motivated
delusions would emerge, making negative emotions easier to manage and depression less
likely to ensue. McKay and Dennett consider the possibility that some delusions count as
adaptive misbeliefs, but interestingly argue that the extent to which desires are allowed
to influence belief formation in the case of delusions is pathological. Delusions are the
result of the maladaptive version of a psychologically adaptive mechanism. Delusions may
be produced by extreme versions of systems that have evolved in accordance with error
management principles, that is, evolved so as to exploit recurrent cost asymmetries. As
extreme versions, however, there is every chance that such systems manage errors in a
maladaptive fashion. More needs to be said about the precise nature of the advantage that
adaptive misbeliefs may have, but shear-pin accounts are helpful in providing a framework
for the potential psychological benefits of motivated delusions. First, in the shear-pin
account, the situation in which adaptive misbeliefs emerge is already seriously
compromised. The premise is that the person is already experiencing high levels of
distress, and can come to more serious harm unless her negative emotions are managed.
Thus, the benefit here amounts to the prevention of more serious harm than the one the
person is already experiencing. In other words, the adaptive misbelief is equivalent to an
emergency response. McKay and Dennett talk about the “extraordinary circumstances” in
which motivational influences on belief are not just tolerated but desirable, and argue
that such influences are not accidental but designed. I am going to suggest that a careful
consideration of the circumstances in which beliefs are adopted should play a role in
establishing not just whether they have psychological benefits, but also what their
epistemic status is. Second, the phrase “adaptive misbelief” and the general description
of the shear-pin mechanism may be taken to suggest that there is almost an inverse
correlation between psychological and epistemic benefits. The more distant the belief is
from a bleak reality, the more psychologically adaptive it is. This is not, however, what
McKay and Dennett have in mind. Indeed, a possible explanation for the difference between
motivated delusions and non-delusional adaptive misbeliefs is that delusions are
ultimately maladaptive because, in the case of delusions, motivational influences affect
beliefs to an extent that compromises their overall plausibility and makes them impervious
to counterevidence. These epistemic costs are likely to bring also psychological costs,
and thus delusions may turn out to have greater psychological costs than benefits. I am
going to suggest that we should resist a trade-off view of the relationship between
psychological and epistemic benefits. There are reasons to believe that it is
psychologically beneficial to have beliefs that are constrained by reality, and that
managing negative emotions, relieving anxiety, and protecting self-esteem have
epistemically positive consequences.

<h>EPISTEMIC INNOCENCE</h>
-------------------

What is it to be epistemically innocent? Innocence is sometimes cashed out in terms of a
person being ‘free from faults’ or ‘free from sins’. This is not the sense of innocence I
am advocating here. Ideally, agents would have beliefs that are true and that are
supported by, and responsive to, the evidence available to them. But human agents have
limited cognitive capacities, and beliefs that are false and badly supported by, or
irresponsive to, the evidence are a common occurrence. It is tempting to dismiss
epistemically costly cognitions altogether. But sometimes an epistemically costly
cognition can also have positive epistemic features. When these epistemic benefits are
significant and could not be attained in other ways, then the cognition may gain some sort
of innocence. The notion of innocence I have in mind is used in the legal context of
justification defence. In general, an innocence defence applies to someone who is not
deemed liable for an act that appears to be wrongful. Innocence defence can be due to
excuse or justification. An excuse defence applies when there is no criminal intent. A
justification defence applies when the act does not constitute an offence in the given
circumstances because it prevents greater harm from occurring. Here is an example of a
justification defence: Ann injures Ben and by doing so she stops him from detonating a
bomb (Greenawalt, 1986, p. 89). It is morally and legally objectionable to cause injury to
another, but in the specific circumstances in which Ann injures Ben her action has some
significant benefits as it prevents a greater harm from happening. Moreover, other ways of
stopping Ben, such as talking him out of detonating the bomb, may be not available at the
time. Ann is acquitted because what she did is not wrongful: it is an acceptable response
to an emergency. My purpose here is to apply this notion of innocence to the domain of
epistemic evaluation. In some contexts, an epistemically costly cognition (say, a false
belief) may help avoid bad epistemic consequences, and thus qualifies as an acceptable
response to an emergency.1 For instance, a delusion is epistemically innocent if adopting
it delivers a significant epistemic benefit that could not be obtained otherwise. I
propose the following two conditions for epistemic innocence: Epistemic Benefit: The
delusional belief confers a significant epistemic benefit to an agent at the time of its
adoption. No Alternatives: Other beliefs that would confer the same benefit are not
available to that agent at that time.2 The exact formulation of the conditions for
epistemic innocence will vary depending on one’s epistemological commitments. Let us
consider the Epistemic Benefit condition first. The epistemic benefits of having a
cognition may include maximising the acquisition and retention of true beliefs (for a
veritist), promoting intellectual virtues (for a virtue epistemologist), or avoiding
epistemic blame (for a deontologist). In line with a broadly consequentialist
understanding of epistemic value, I shall argue in Section 3.1 that the adoption of a
delusional belief can support the agent’s epistemic functionality that would otherwise be
compromised by overwhelming negative emotions and low self-esteem. I take epistemic
functionality to be the capacity to perform well epistemically by acquiring true
beliefs/knowledge or exercising intellectual virtues. Now let us consider the No
Alternatives condition. Different notions and degrees of unavailability can explain the
failure to adopt a less epistemically costly cognition. This variety may be due to the
nature of the limitations that the agent experiences in the relevant context, ranging from
standard reasoning limitations to deficits affecting perception, inference, or memory in
clinical settings (see Sullivan-Bissett (2015) for a useful taxonomy of relevant types of
unavailability). In short, there may be no alternative to adopting a delusional belief
because evidence that would lend support to less epistemically costly beliefs is not
available or cannot be weighed up due to a bias or deficit. I shall review these options
in Section 3.2.

<hs>  Meeting the Epistemic Benefit condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The epistemic benefits of motivated delusions are mediated by their psychological
benefits. We saw in Section 2 that the adoption of a delusional belief can be
psychologically adaptive. In the shear-pin account of the benefits of delusions, the very
fact that people believe a more positive version of reality (e.g., “I am now severely
disabled, but my girlfriend still loves me”) than the one they have evidence for allows
them to manage negative feelings that could become overwhelming, preserve self-esteem, and
overcome anxiety and stress. The benefits in question amount to the delusion preventing a
serious epistemic harm from occurring. McKay and Dennett focus on the effects of adaptive
misbeliefs on wellbeing. The point of allowing motivational factors to influence belief
evaluation is to make the person feel better about herself and her situation. But if a
belief helps manage negative emotions, protect self-esteem, and relieve anxiety and
stress, it will have positive effects not just on the agent’s wellbeing but also on her
capacity to function well epistemically (what I called “epistemic functionality”). By
having the belief, a person will be more likely to engage with her surrounding physical
and social environment in a way that is conducive to epistemic achievements. Consequences
of stress and anxiety include lack of concentration, irritability, social isolation, and
emotional disturbances. These in turn negatively affect socialisation, making interaction
with other people less frequent and less conducive to useful feedback on existing beliefs,
and to the fruitful exchange of relevant information. Due to reduced socialisation and
engagement, the acquisition and retention of knowledge is compromised and intellectual
virtues are not exercised. There is at least one problem with considering relief from
stress and anxiety as an indirect source of epistemic advantages for motivated delusions.
The delusion may bring relief at the time when it is adopted, due to the person being
already in an epistemically compromised situation, but it often increases rather than
reduces stress and anxiety when it is maintained in the face of conflicting evidence and
challenges from third parties. Stress and anxiety no longer come from the negative
emotions associated with trauma or loss (“I’m paralysed”, “My girlfriend left me”, “Nobody
loves me”, etc.), but from the fact that the content of the delusion can clash with
aspects of the person’s experience, conflict with other things she believes or feels, and
alienate other people. For all of these reasons, anxiety and depression do not always
lessen after a delusion is adopted, they can also heighten. This is particularly true of
delusions with negative content that are correlated with higher depression and lower self-
esteem (e.g., Smith et al., 2006). Thus, the adoption of a delusional belief may be
beneficial because it prevents the occurrence of a disastrous epistemic breakdown, but its
benefits are unlikely to outlive the prevention of the breakdown. It should also be kept
in mind that acknowledging that motivated delusions can have some epistemic benefits is
not equivalent to claiming that their epistemic benefits outweigh their epistemic costs.
My claim is relatively modest: when they are adopted delusions can be epistemically
innocent, as opposed to epistemically justified, or epistemically good overall. The
obvious question is why the person does not adopt a belief that has the same epistemic
benefits as the delusional one but fewer costs. One suggestion emerging from the empirical
literature is that, in the “extraordinary circumstances” in which the agent finds herself,
no other belief with the relevant characteristics is available.

<hs>  Meeting the No Alternatives condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

I have reviewed some of the literature suggesting that motivated delusions can help manage
negative emotions and avoid low self-esteem because they function as a defence mechanism
against the psychological effects of previous adversities or recent trauma. This may be
sufficient to claim that, if relief from anxiety and distress benefits agents by
supporting their epistemic functionality, then motivated delusions can be thought of as
epistemically beneficial in the circumstances. This claim, though, does not amount to an
epistemic defence of motivated delusions. In order for delusions to be epistemically
innocent, we also need to establish that less epistemically costly beliefs could not
deliver the same epistemic benefits. This is analogous to the legal case: for Ann to be
found innocent of injuring Ben, the court needs to be convinced that there was no other
way for her to stop him from detonating the bomb. How to characterise the availability of
alternative beliefs is an issue which deserves greater attention than I can give it here.
To make a start, I shall review how the unavailability of alternative beliefs has been
assessed with respect to delusions emerging in the context of anosognosia. There are two
main obstacles to adopting a non-delusional belief (such as “I am paralysed”): (1)
evidence for the truth of the non-delusional belief is not available; and (2) evidence for
the truth of the non-delusional belief is available but the agent’s capacity for
evaluating competing hypotheses is compromised, and thus the evidence is not taken into
account. To start with option (1), is evidence for their impairment available to people
with anosognosia who deny their impairment? The possibility that people may be covertly
aware of their impairments has been discussed widely in the empirical and philosophical
literature (see, for instance, Fotopoulou, Pernigo, Maeda, Rudd, & Kopelman, 2010; Levy,
2008). Ramachandran (1995) found that people with anosognosia for left hemiplegia who are
asked to choose between unimanual tasks (tasks that they can perform by using just one
hand) and bimanual tasks (tasks that they can perform only if they use both hands)
consistently choose bimanual ones because the expected rewards are greater. Controls
(people with paralysis but no anosognosia) choose the unimanual tasks instead. This seems
to suggest that people with anosognosia genuinely believe that they can succeed in those
tasks. Given these results, there is no reason to suppose that evidence of their
impairment is available to them. Similar conclusions can be drawn from the use of a
virtual reality box, where the person is fooled into seeing her (paralysed) arm moving by
following the experimenter’s instructions (in reality, the moving arm belongs to someone
else). If people were aware of their paralysis, they would show (verbal and non-verbal)
signs of surprise, but this is not the case. [F]ar from being a mere façade-like condition
that leaves room for traces of insight to leek through, anosognosia runs deep. With
respect to option (2), some cases of anosognosia show that the person can be made
temporarily aware of her impairment (via vestibular stimulation), but lacks the capacity
to integrate the information in her overall conception of herself (Ramachandran, 1995, p.
36). As we saw earlier, Ramachandran explains the formation of the delusions in terms of
the need to preserve a coherent sense of self. Usually, the left hemisphere produces
confabulatory explanations aimed at preserving the status quo, but the right hemisphere
detects an anomaly between the hypotheses generated by the left hemisphere and reality.
So, it forces a revision of the belief system. In people with anosognosia, this
discrepancy detector in the right hemisphere no longer works, and the belief system fails
to update. For Aimola Davies and Davies (2009), it is both true that the person has no
direct evidence of the impairment and that she cannot use the other available evidence to
revise her belief that she is healthy. Indeed, the formation of anosognosia is explained
by the authors in terms of two factors: (1) the person’s motoric failure does not make
itself known to the person via direct experience due to neglect, loss of proprioception,
or specific problems of integration and memory; and (2) the person cannot use other
available evidence of motoric failure due to problems with working memory and executive
function. This analysis strongly suggests that evidence for the belief that there is an
impairment is not usually available to people with anosognosia: they cannot learn about
their impairment from their own experience (due to a neuropsychological deficit that
constitutes factor one), and they cannot use other evidence to come to the conclusion that
they are impaired (due to their compromised capacity to evaluate competing hypotheses that
constitutes factor two). Even if evidence for non-delusional beliefs were available to
people with anosognosia, such beliefs would probably fail to support the agent’s epistemic
functionality to the same extent as the delusional beliefs. A more plausible belief (e.g.,
“I am paralysed”) may not be as well placed as the delusional one to play a defensive
function, in terms of preserving a coherent and positive self and defusing the negative
emotions caused by trauma and disability. Given that the non-delusional beliefs lack such
psychological benefits, they may also lack the epistemic benefits associated with them.

<h>CONCLUSIONS AND IMPLICATIONS</h>
----------------------------

In this paper I have argued that the psychological benefits of motivated delusions can
convert into epistemic ones. Motivated delusions have the potential for epistemic
innocence, where epistemic innocence is characterised as the epistemic status of those
cognitions that have obvious epistemic costs but also have a significant epistemic benefit
that would be otherwise unattainable. Those delusions that allow the agent to manage
negative emotions and avoid low self-esteem are also likely to support the agent’s
epistemic functionality. Moreover, when they are adopted, motivated delusions may be the
only beliefs supporting epistemic functionality that are available to agents distressed by
the consequences of previous adversities, recent trauma or loss. When we think about
epistemically costly cognitions that may have psychological benefits, such as self-
deception, positive illusions, confabulatory narratives, and distorted memories, we
usually think in terms of there being a trade-off. Believing something false or putting a
positive spin on a past event can make us feel better, but it leads us further away from
the truth. Thus, it may increase wellbeing, but it is not epistemically good. The case for
the potential epistemic innocence of motivated delusions puts some pressure on the trade-
off view. It would be misleading to believe that motivated delusions provide anxiety-
relief and protect self-esteem by compromising access to the truth. Rather, in the picture
I have sketched, delusional beliefs are adopted at a time when access to the truth is
already compromised by the effects of trauma or previous adversities, and it would be
further compromised unless negative emotions were effectively managed. As a temporary
response to an emergency, motivated delusions play a useful epistemic function. These
considerations obviously apply to other epistemically costly cognitions. In particular,
everyday self-deception and motivated delusions seems to have a very similar shear-pin
function in that they are the result of a mechanism that lets desires shape beliefs. In so
far as motivational influences on belief formation relieve anxiety and stress, everyday
self-deception and motivated delusions can carry some benefits by supporting the agent’s
epistemic functionality. But different from self-deception, motivated delusions may invite
a radical embellishment of the agent’s reality and create tension both within an agent’s
belief system and between the agent and other agents, thereby causing inconsistencies,
social isolation, and withdrawal. Thus motivated delusions are more likely to become
maladaptive (as opposed to adaptive) instances of misbelief than everyday self-deception.
On the other hand, the person with everyday self-deception may have more alternative
hypotheses available to her than the person who ends up endorsing a motivated delusion, if
we suppose the former is not subject to perceptual abnormalities or reasoning impairments
to the same extent as the latter. Thus, it may be harder to argue for the epistemic
innocence of non-clinical self-deception. The case of motivated delusions and its
analogies and disanalogies with self-deception illustrate perfectly the limitations of the
trade-off view: some of the psychological benefits attributed to delusions carry
significant epistemic benefits that it would be unwise to neglect. It may seem that
wellbeing is safeguarded at the expense of truth when the delusional belief is adopted,
but a reflection on the effects of adopting the delusion suggests that safeguarding
wellbeing and promoting epistemic functionality go hand in hand. In the case of Reverse
Othello syndrome described earlier, the clinical team decided not to challenge the
delusion after they realised that there were no other psychotic symptoms and the delusion
was playing a defensive function. Persistent attempts […] to challenge B.X.’s delusional
beliefs were unsuccessful and usually led him to become tearful and agitated. It was
concluded that B.X.’s fantasy system functioned to protect him from the consequences of
massive narcissistic injury and attendant depressive overwhelm. All members of the
treating team were instructed not to aggressively B.X.’s delusional beliefs but were also
cautioned not to become complicit in his elaboration of them. Similarly, Fotopoulou
observes that challenging delusions in a person with anosognosia can prove ineffective and
psychologically disruptive: [RM’s] engagement in rehabilitation activities was initially
very poor as he was not motivated and required constant prompting and supervision.
Attempts to contradict his anosognosia and increase his motivation were often ineffective
as RM immediately provided a series of confabulations to support his alleged abilities and
he was particularly sensitive to poor performance and negative feedback. The excerpts
above make a similar point in different contexts (Reverse Othello syndrome and
anosognosia): if the delusional belief provides some psychological benefit and the benefit
is not available via any other belief that the person would accept at that time, then
challenging the delusion is a bad idea. A clinical team might decide not to challenge a
delusion if they think that challenging an agent is going to be ineffective or disruptive,
or if there is a high risk of depression ensuing from the agent’s insight into her mental
illness. My discussion suggests that, in these contexts, challenging the delusion might
not be advisable from an epistemic point of view either. At the critical stage, motivated
delusions may serve a useful epistemic function, allowing the agent to overcome negative
feelings or low self-esteem that would prevent her from exercising her epistemic
functionality.


<h>REFERENCES</h>
----------

  [2] Anne M. Aimola Davies, Martin Davies, Jenni A. Ogden, Michael Smithson, Rebekah C. White. Cognitive and motivational factors in anosognosia. doi:10.4324/9780203838044
  [3] Richard P. Bentall. Cognitive biases and abnormal beliefs: Towards a model of persecutory delusions. doi:10.4324/9781315785004-19
  [4] Richard P. Bentall, Peter Kinderman, Sue Kaney. The self, attributional processes and abnormal beliefs: Towards a model of persecutory delusions. doi:10.1016/0005-7967(94)90131-7
  [6] Peter V. Butler. Reverse othello syndrome subsequent to traumatic brain injury. doi:10.1521/00332747.2000.11024897
  [7] Martin Davies. Delusion and motivationally biased belief: Self-deception in the two-factor framework. doi:10.4324/9780203838044
  [9] Aikaterini Fotopoulou. False selves in neuropsychological rehabilitation: The challenge of confabulation. doi:10.1080/09602010802083545
  [10] Aikaterini Fotopoulou, Simone Pernigo, Rino Maeda, Anthony Rudd, Michael A. Kopelman. Implicit awareness in anosognosia for hemiplegia: Unconscious interference without conscious re-representation. doi:10.1093/brain/awq233
  [12] H. W. Jordan, G. Howe. De Clerambault syndrome (erotomania): A review and case presentation
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  [14] Melvin R. Lansky. Schizophrenic delusional phenomena. doi:10.1016/0010-440X(77)90059-1
  [15] Neil Levy. Self-deception without thought experiments. doi:10.4324/9780203838044
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  [18] Ryan T. McKay, Daniel C. Dennett. The evolution of misbelief. doi:10.1017/S0140525X09990975
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  [23] G. Roberts. The origins of delusion
  [24] Ben Smith, David G. Fowler, Daniel Freeman, Paul Bebbington, Hannah Bashforth, Philippa Garety, Graham Dunn, Elizabeth Kuipers. Emotion and psychosis: Links between depression, self-esteem, negative schematic beliefs and delusions and hallucinations. doi:10.1016/j.schres.2006.06.018
  [25] Ema Sullivan-Bissett. Implicit bias, confabulation, and epistemic innocence. doi:10.1016/j.concog.2014.10.006
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<ART>The healthy body image (HBI) intervention: Effects of a school-based cluster-randomized controlled trial with 12-months follow-up
================================================================================

Authors: Christine Sundgot-Borgen, Oddgeir Friborg, Elin Kolle, Kethe M.E. Engen, Jorunn Sundgot-Borgen, Jan H. Rosenvinge, Gunn Pettersen, Monica Klungland Torstveit, Niva Piran, Solfrid Bratland-Sanda
DOI: 10.1016/j.bodyim.2019.03.007
Year: 2019  |  Pages: 122-131
ASJC codes: 3200, 3202, 3207
Keywords: Adolescents, Body appreciation, Embodiment, Health promotion, Quality of life

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We examined the effects of the Healthy Body Image (HBI) intervention on positive embodiment and health-related quality of life among Norwegian high school students. The intervention comprised three interactive workshops, with body image, media literacy, and lifestyle as main themes. In total, 2,446 12 th grade boys (43%) and girls (mean age 16.8 years) from 30 high schools participated in a cluster-randomized controlled study with the HBI intervention and a control condition as the study arms. Data were collected at baseline, post-intervention, 3- and 12-months follow-up, and analysed using linear mixed regression models. The HBI intervention caused a favourable immediate change in positive embodiment and health-related quality of life among intervention girls, which was maintained at follow-up. Among intervention boys, however, weak post-intervention effects on embodiment and health-related quality of life vanished at the follow-ups. Future studies should address steps to make the HBI intervention more relevant for boys as well as determine whether the number of workshops or themes may be shortened to ease implementation and to enhance intervention effects.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Positive embodiment and body appreciation are important aspects of health and quality of
life (Avalos, Tylka, & Wood-Barcalow, 2005; Piran, 2019; Tiggemann, 2011). In previous
studies, positive embodiment and body appreciation have been associated with positive
self- and body esteem, healthy eating, and performing regular physical activity in boys
and girls (Cash & Fleming, 2002; Neumark-Sztainer, Paxton, Hannan, Haines, & Story, 2006;
Santos, Tassitano, do Nascimento, Petribú, & Cabral, 2011; Tylka & Homan, 2015). Further,
body image has been found to predict health-related quality of life in boys and girls
(Griffiths et al., 2017; Haraldstad, Christophersen, Eide, Natvig, & Helseth, 2011). There
is however a well-known gender difference, as fewer adolescent boys struggle with body
image issues (13–45%) compared to adolescent girls (45–71%) (Martinsen, Bratland-Sanda,
Eriksson, & Sundgot-Borgen, 2010; Torstveit, Aagedal-Mortensen, & Stea, 2015). In the same
vein, adolescent boys report more satisfaction with their bodies and higher levels of
embodiment compared to adolescent girls (Franko, Cousineau, Rodgers, & Roehrig, 2013;
Holmqvist, Frisén, & Piran, 2018; Neumark-Sztainer et al., 2006; Santos et al., 2011).
From a developmental perspective, changes in the experience of the body during the
critical phase of adolescence can have a long-term impact on body image (Wertheim, Paxton,
& Blaney, 2009). Promoting positive embodiment in adolescence is therefore vital to
establish a good basis for health-related quality of life, as such quality of life has
proved stable during the life course (Bisegger, Cloetta, von Rueden, Abel, & Ravens-
Sieberer, 2005), and can be viewed as a core issue for public health. Systematic reviews
show that universal intervention programs that are successful address the reduction of
risk factors, as for example body dissatisfaction, in order to prevent eating disorders
among adolescents (Le, Barendregt, Hay, & Mihalopoulos, 2017; Stice, Shaw, & Marti, 2007;
Yager, Diedrichs, Ricciardelli, & Halliwell, 2013). Within a health promotion perspective,
promoting positive embodiment represents a theoretical and methodological paradigmatic
shift from the disease-preventing focus, e.g., by preventing body dissatisfaction, to a
health-promotion focus (Le et al., 2017; Stice, Becker, & Yokum, 2013). This shift opens
new possibilities to assess health-promotion interventions (Piran, 2015; Tylka & Wood-
Barcalow, 2015; for examples, see Alleva et al., 2018; Halliwell, Jarman, Tylka, & Slater,
2018; McCabe, Connaughton, Tatangelo, Mellor, & Busija, 2017). The research-based positive
embodiment construct is defined as “positive body connection and comfort, embodied agency
and passion, and attuned self-care” (Piran, 2016, p.47). Positive embodiment relates
conceptually to body appreciation (Tylka & Piran, 2019), the most commonly used construct
in assessing positive body image (Tylka, 2019). Both positive embodiment and body
appreciation emphasize positive connection to, and appreciation of, the body, as well as
attuned care of the body (Tylka & Piran, 2019). The positive embodiment construct,
however, includes in addition, experiences of agency to act in the world and comfort with
bodily desires (Piran, 2019). Researchers have called for intervention studies that aim to
enhance embodiment and health-related quality of life (Alleva, Sheeran, Webb, Martijn, &
Miles, 2015; Tylka & Piran, 2019). Yet, most existing intervention studies lack inclusion
of multidimensional instruments of positive embodiment (Webb, Wood-Barcalow, & Tylka,
2015). In particular, no randomized, controlled outcome evaluation studies have been
conducted as a universal promoting program aimed at enhancing positive embodiment in both
boys and girls in late adolescence (Alleva et al., 2015).

<hs>  Development and implementation of the HBI intervention</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We have developed the universal, multi-component health-promotion intervention “Healthy
Body Image” (HBI; Sundgot-Borgen et al., 2018). The HBI intervention focuses on positive
embodiment and health-related quality of life among Norwegian high school students, and
employs an interactive educational approach, which has been found suitable in school
settings (Yager et al., 2013). The HBI intervention comprised three overarching themes
related to body image, media literacy, and lifestyle, as these have been found to improve
physical self-perception, body satisfaction and appreciation, physical competence, and
body esteem, sometimes with large effect sizes (Alleva et al., 2015; Espinoza, Penelo, &
Raich, 2013; Franko et al., 2013; Tomyn, Fuller-Tyszkiewicz, Richardson, & Colla, 2016). A
more detailed description of the program and its rationale has been published elsewhere
(Sundgot-Borgen et al., 2018). The program was constructed to include both boys and girls
in late adolescence. This was important because the peer environment is shaped by
sociocultural ideals of both genders. Both boys' and girls' attitudes must change if the
social environment of the whole school can be changed (Yager et al., 2013). Due to the
mixed-gender sample, the intervention contained gender neutralized and gender specific
contents (e.g., pictures, videos, communication examples), to make it relevant for both
genders. Despite some debate on what age is most appropriate for initiation of body image
interventions, evidence suggests that in prevention studies, it might be beneficial to
target young adolescents prior to the onset of eating disorders (Espinoza et al., 2018;
Rohde, Stice, & Marti, 2015). However, late adolescence involves pubertal, cognitive, and
interpersonal changes, which increase adolescents’ ability to reach a more abstract
characterization of themselves, the influence of their peers increases (Rohde et al.,
2015), and they may become more aware of and vulnerable to pressures to attain
sociocultural beauty ideals. They are at an age where the risk for eating disorders peaks
(Espinoza et al., 2018; Rohde et al., 2015; Stice et al., 2007), and promotion of positive
embodiment is especially crucial, as they are moving towards the independence of young
adulthood. Also, their improved ability for abstract reasoning makes them more likely to
comprehend the intervention content, relate skills to their own lives, and take advantage
of such taught skills. The school context also ensures a relatively comparable
participation rate between genders, which is an obvious asset since few existing studies
have managed to include a balanced gender sample. Moreover, a mixed-gender approach may
offer a more real-life setting in universally implemented health promotion initiatives
(Yager et al., 2013).

<hs>  Hypothesis</hs>
  ~~~~~~~~~~

We hypothesized that the HBI intervention would be effective, resulting in more favourable
scores on positive embodiment (higher) and health-related quality of life (higher) in
intervention students compared to control students.

<hs>  Design and randomization</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

A cluster-randomized controlled design was used with schools as the clustering factor at a
ratio of 1:1. Schools were randomly allocated to either the HBI intervention or the
control group to equalize sample size, and the effect of socioeconomic and demographic
variables, notably related to ethnicity and the urban-rural dimension. The sample would be
considered representative of the adolescent population of Oslo and Akershus County. The
randomization was conducted by a professional not affiliated with the study to minimize
contamination biases within schools. During the intervention period, students at the
control schools followed their regular school curriculum. Fig. 1 presents a diagram of the
inclusion and randomization process of schools and students, respectively.

<hs>  Sample characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Thirty schools were randomized and 2,446, 1,254, 1,278, and 1,080 students consented to
participate at pre-test, post-intervention, and 3- and 12-months follow-up, respectively
(Fig. 1). The mean (range) number of students consenting at each school was 82 (22–184),
42 (5–97), 43 (4–125), and 36 (3–103) at pre-test, post-intervention, and 3- and 12-months
follow-up, respectively. The number of students included in the primary outcomes analyses
were 1,742, 1,190, 1,172, and 955 for the Experience of Embodiment Scale, and 1,688,
1,173, 1,158, and 925 for the KIDSCREEN-10 and General health across the four measurement
occasions. The participants were 16.8 (SD = 0.76) years old, and 11%, and 1% were
categorized as overweight and obese, respectively. Among the participants, 13% were
categorized as immigrants, 39% had parents with a total income of ≥1 million NOK, and 82%
reported one or both parents having a higher education.

<hs>  Ethics approval and consent to participate</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The study met the intent and requirements of the Health Research Act and the Helsinki
declaration, and was approved by the Regional Committee for Medical and Health Research
Ethics (P-REK 2016/142). It was enrolled in the international database of controlled
trials www.clinicaltrials.gov (ID: PRSNCT02901457). Students at consenting schools had the
prerogative to decline participation after consent. In such cases, students were allowed
to follow the HBI workshops, but without completing the questionnaires. After the final
12- months follow-up, control schools were offered one lecture where the program
highlights were compressed. The methods and results are described according to the Consort
Statement (Moher, Schulz, & Altman, 2001).

<hs>  Procedure and data collection</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As a result of a subsequent pilot study during March and April 2016 among 120 12th grade
high schoolers, a few questionnaire items about body perception and nutrition were deleted
to reduce the risk of error variance due to acquiescence bias. In addition, the amount of
workshop assignments was reduced to allow for more time allocated to discuss mood and body
satisfaction issues. The HBI intervention included all 12th grade high school classes
following a general study program, excluding students following a vocational study
program. No further exclusion criteria were set. During Spring 2016, principals of all
public and private high schools in Oslo and Akershus County in Norway were contacted by
e-mail. Oral and written study information was provided to students and staff at the
consenting schools. The Norwegian Health Research Act states that adolescents, 16 years or
older, can give their informed consent with no parental consent needed. Students were sent
an e-mail with study information and a letter of informed consent. If they pressed "yes"
to the question of consent, they were given access to a link that made the questionnaire
package available, and they completed the questionnaire package through the online survey
system SurveyXact 8.2. Ethical approval of the study required that the students completed
the questionnaires outside regular school hours. Students were informed about their
allocation into the intervention or control group after the randomization.

<hs>  Measures</hs>
  ~~~~~~~~

As described in the study protocol (Sundgot-Borgen et al., 2018), participants completed
standardized questionnaires related to demographics, positive embodiment, and health-
related quality of life at baseline, post-intervention, and at 3- and 12-months follow-up,
respectively. All baseline assessments were conducted prior to the randomization. Post-
intervention assessment was not available the same day as the last workshop, but within
one week (Sundgot-Borgen et al., 2018).

        <hss>Demographic variables</hss>

        The demographic variables were collected at all measurement occasions, including
        age, gender, and self-reported body weight (kg) and height (cm). BMI was
        calculated as body weight (kg) divided by the height squared (m2). Categorization
        of weight status was based on international age- and gender-adjusted cut-off
        scores (Cole, Bellizzi, Flegal, & Dietz, 2000). Total parental income was measured
        by asking the students what they believed to be their parents' total income,
        selecting one of five options (less than NOK 200.000, NOK 200.000 - 400.000, NOK
        500.000 - 800.000, NOK 900.000 - 1 million, more than NOK 1 million,
        respectively). Students also ticked off if their parents had completed 1. Primary
        school, 2. High school, 3. College/University, or whether they 4. Did not know.
        Immigration status was measured by asking whether the student or both parents had
        immigrated (Yes I have, Yes both my parents, No).

        <hss>Positive embodiment</hss>

        Positive embodiment was measured using the Experience of Embodiment Scale (EES)
        (Teall & Piran, 2012). The Cronbach’s alpha for the current study was .93 for
        girls and .92 for boys, similar to other studies with the range of .91–.94
        (Chmielewski, Bowman, & Tolman, 2019; Holmqvist et al., 2018; Piran, 2019; Teall,
        2006, 2014). Test-retest reliability over a 3-week period of the EES was also
        previously found to be acceptable (r = .93) (Piran, 2019). The 34 items covered
        positive connection with the body, agency and functionality, experience and
        expression of desire, body attunement, self-care vs. harm/neglect, and subjective
        lens vs. self-objectification (e.g., "I am proud of what my body can do" and "I
        care more about how my body feels than about how it looks"). The items had a
        Likert-format ranging from 1 (strongly disagree) to 5 (strongly agree), and the 17
        negatively framed items (e.g., "I ignore the signs my body sends me" and "My
        dissatisfaction with my body/appearance has a negative effect on my social life")
        were reversed so that the sum score reflected higher levels of positive
        embodiment. Adequate construct validity of the EES has been found in previous
        studies on young adults as reflected by positive correlations with measures of
        body esteem in women (rs = .76–.79) and men (r = .69), body responsiveness (r =
        .73), body connection (r = .60), well-being (rs = .55–.80), and life satisfaction
        in men (r = .68) and women (r = .66). Further, the EES correlated negatively with
        measures of objectified body consciousness (rs = -0.55, -.73), eating problems (rs
        = -0.43, -.70), alexithymia (rs = -0.51, -.54), and depression (r = -0.63)
        (Chmielewski, Tolman, & Bowman, 2018; Holmqvist et al., 2018; Piran, 2019; Teall,
        2006, 2014). Young men have reported higher EES scores compared to women
        (Holmqvist et al., 2018). Since the present investigation included late
        adolescents, ages 16–17, the study used the adult version of the EES. To date,
        most validation studies of the EES were conducted in young adult samples, such as
        Chmielewski et al. (2018) that included 340 women between the ages of 18–26 with
        an average age of 19.81. Based on a series of confirmatory factor analyses, the
        global EES score was used as an outcome measure. While its original 6-factor model
        showed an adequate fit when modeling the method variance related to the positively
        and negatively worded items, χ2(507) = 3311, p <  .001, RMSEA = 0.056, CFI/TLI =
        .890/.867, SRMR = .066, we used a global score since a general second-order
        factor, χ2(516) = 3431, p <  .001, RMSEA = .057, CFI/TLI = .875/.864, SRMR = .076,
        accounted adequately for the 6-factor model.

        <hss>Health-related quality of life</hss>

        Health-related quality of life was measured by the KIDSCREEN-10, which is a widely
        used and validated self-report tool (Ravens-Sieberer, 2006), and has been
        validated in Norwegian adolescents (Haraldstad & Richter, 2014). The scale
        consists of 10-items (e.g., "Have you felt fit and well?" and "Have you felt
        sad?"). The sum score of the 1–10 provides a general health-related quality of
        life index. A separate item included in the KIDSCREEN-10 measured perceived
        General Health ("In general, how would you say your health is?"), which has been
        found to correlate well with measures of physical well-being (r = .63) and
        psychological well-being (r = .51) (Barthel et al., 2017). All items, 1–11, had a
        5-point Likert-type format from 1 (not at all/never) to 5 (extremely/always) for
        10 items, and from 1 (excellent) to 5 (poor) for the General Health item.
        Negatively worded questions were reversed, and hence a higher score indicated
        higher levels of health-related quality of life. Standardized T-scores were
        presented at baseline to enable comparison of means across study samples and
        compare data to health-related quality of life norm data. A score of 50 represents
        the mean. A T-score < 38 on the KIDSCREEN-10 indicates lower health-related
        quality of life, while scores ≥ 38 indicate preferable reported health-related
        quality of life (Ravens-Sieberer, 2006). The internal consistency for this sample
        was α = .81, and has been found to be satisfactory in other samples of adolescent
        boys and girls (Haraldstad et al., 2011).

<hs>  The HBI intervention</hs>
  ~~~~~~~~~~~~~~~~~~~~

There is no consensus as to which theoretical orientation may provide the most effective
approach when developing a health promotion intervention aiming to promote embodiment and
health-related quality of life (Alleva et al., 2015). However, a sociocultural perspective
(Thompson, Heinberg, Altabe, & Tantleff-Dunn, 1999) was natural to consider when aiming to
change attitudes, beliefs, and knowledge related to idealized lifestyles (involving e.g.,
extreme exercise and diet regimes) and bodies, to further strengthen the resilience
towards unhealthy internalization, and strengthen life-managing skills in a mixed-gender
school-based setting. Also, an etiological model of risk and protective factors (Piran,
2015; Smolak & Piran, 2012) as well as the developmental theory of embodiment (Piran,
2017; Teall & Piran, 2012) within the realm of positive psychology (Seligman &
Csikszentmihalyi, 2000), were important in its development. Although thoroughly described
in the Appendix, some important aspects of the intervention specifically aiming to promote
positive embodiment are presented. Through the body image and media literacy workshops, we
aimed to improve critical awareness of unhealthy body and lifestyle idealization, critical
and constructive use of social media, including consequences of current body ideals for
boys and girls. By this, we intended to reduce the risk of internalization of unhealthy
ideals, self-harm, and neglect, as well as promote a subjective lens while reducing self-
objectification. To improve a positive connection with the body, we aimed to strengthen
attitudes towards, and knowledge about, how to promote self-care and experience of body
functionality when discussing lifestyle factors, such as nutrition, exercise, and sleep.
The intervention was developed to suit the cognitive development among adolescents 16
years of age in terms of their ability for abstract reasoning. The workshop delivery was
based on the elaboration likelihood model (Petty & Briño, 2012; Petty & Cacioppo, 1986).
According to this model, as well as previous findings (Alleva et al., 2015; Stice et al.,
2013, 2007), the program contained three 90-min interactive workshops to facilitate
extensive student discussions. All workshops were arranged in classrooms during regular
school hours. About 60 boys and girls (i.e., two school classes) participated per
workshop. Student attendance was registered at each workshop to calculate program
adherence. A 3-week interval between each workshop resulted in a 3-month intervention
period. The first and fourth author facilitated the intervention. Both are specialized in
physical activity and health, sports nutrition, motivational interviewing, and body image
among adolescents. Detailed information about the intervention content and targets can be
found in the study protocol (Sundgot-Borgen et al., 2018).

<hs>  Sample size and power analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The statistical power estimation was based on two comparison groups (α = .05 and b = .20)
with an average within-cluster sample size of 70 students. The expected effect size was
.28 according to a meta-analysis (Hausenblas & Fallon, 2006) that included 35 studies
examining intervention effects on body images variables. Moreover, we assumed that the
within-cluster dependency related to schools accounted for approximately 3% (ICC = .03).
This is fair for variables related to psychological or mental health outcomes, as
selection factors like socioeconomic status affect these variables less than for example
academic performance. These considerations required a minimum of 10 clusters within each
group, requiring a total sample size of 10 schools × 2 groups × 70 students ˜ 1400
students.

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

The software program Mplus, version 8.0, was used to carry out factor analyses, while
remaining statistics were analysed using IBM SPSS 24 for Windows. The adequacy of the
randomization procedure was examined by comparing group differences at baseline with
independent t-tests, chi-square tests, or Kruskal-Wallis tests (Table 2). A case was
recorded as dropout if all post-intervention and follow-up data were missing. Due to
several layers of dependency in the outcome data, linear mixed regression models were fit,
as suggested in comparable studies (Wilksch et al., 2017). Dependency within the school
clusters was accounted for by adding school as a random factor, whereas dependency between
the repeated measures was accounted for by fitting a compound symmetry matrix to the
residual matrices (thus assuming equal-sized correlations between measurement occasions).
Students were nested within schools, which also was accounted for. The baseline score was
used as a covariate to adjust for imperfections in the randomization procedure and to
increase the statistical power. The fixed factors were group (one coefficient for the
difference between the intervention and the control group), time (a coefficient for each
time point except the last, thus detecting a non-linear change), and group × time (to
detect if intervention effects were particularly pronounced at certain time points). In
order to examine if the level of participations at workshops influenced the outcomes,
workshop attendance (WA-number of workshops) was added as linear covariate, as well as
interaction terms examining if WA influenced the outcome particularly at certain time
points (WA × time) or additionally within just one of the groups (WA × time × group). The
restricted maximum likelihood procedure and Type III F-tests were preferred. The analyses
were stratified for gender. Statistically significant effects set to p < .05, were
followed-up with planned comparison tests (LSD) examining group differences at each
follow-up assessment. Results are expressed as absolute numbers (n) and percentage (%) for
categorical data and model estimated means including 95% confidence intervals and standard
deviation (SD) for continuous data. Effect sizes are presented as Cohen's d and phi-
coefficients.

<hs>  Participant demographics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Participant demographics for each group are presented in Table 1. At baseline, all
participants were 16–17 years of age, with a mean BMI within the normal weight range for
youths (Cole et al., 2000). The baseline correlation between EES and KIDSCREEN-10 was r =
.60 (p < .001) among both boys and girls. Girls in the intervention had higher scores on
positive embodiment, health-related quality of life, and the general health item compared
to girls in the control group. No significant difference between groups was found in boys
for these outcome measures. Based on parents' total income and education level, girls in
the intervention group were more likely to be defined with a higher social economic status
compared to girls in the control group. Boys in the intervention group had parents with a
higher level of education, and fewer were categorized as immigrants compared to boys in
the control group (Table 1). The linear mixed regression models were adjusted for group
differences at baseline.

<hs>  Dropout analysis</hs>
  ~~~~~~~~~~~~~~~~

No differences were observed in the outcome variables between dropouts and completers in
either boys or girls. More students in the control group (p = .001, φ = 10.61), and more
boys (p < .001, φ = 52.48) dropped out. Boys who dropped out had slightly higher BMI (p =
.044, d = 0.15) and body weight (p = .010, d = 0.20), while girls who dropped out were
slightly older (p = .014, d = 0.17). Effect analyses were therefore adjusted for these
variables.

<hs>  Positive embodiment intervention effects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For boys, the linear mixed regression model showed that the main effect of group (p =
.072), time (p = .756) and the interaction effect of group × time (p = .543) were
nonsignificant. The planned comparison analyses showed that boys in the intervention group
reported higher positive embodiment at post-intervention compared to boys in the control
group, suggesting a short-term favorable small effect. However, this effect was lost at
the 3- and 12-month follow-ups (Table 2). For girls, the main effect of group was
significant, F(1, 777) = 33.11, p < .001, while time (p = .267) and group × time (p =
.133) effects were nonsignificant. The planned comparison analyses showed a significant
and favorable effect of the intervention on positive embodiment for girls in the
intervention group. This effect was maintained at the 3- and 12-months follow-up,
respectively. The effect size increased slightly over time, and with a peak at the last
follow-up assessment (see Table 2).

<hs>  Health-related quality of life intervention effects</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For boys, the linear mixed regression model showed a significant main effect of group for
health-related quality of life, F(1, 360) = 4.78, p = .029, while the time (p = .148) and
group × time (p = .871) effects were nonsignificant. Although the mean differences between
boys in the intervention and control groups increased across the assessment time-points,
no planned comparison analyses showed statistical significance (see Table 3). For the
general health outcome item, the model showed no effect of group (p = .120), time (p =
.953), or group × time (p = .191) for boys. The planned comparison analyses did show a
favorable and significant post-intervention effect for boys in the intervention group
compared to boys in the control group, which was not maintained at follow-up (see Table
3). For girls, the main effect of group for health-related quality of life was not
significant (p = .186), whereas significant time, F(2, 860) = 3.99, p =.019, and group ×
time, F(2, 860) = 4.47, p = .012, effects were observed. The planned comparison analyses
showed no significant difference in health-related quality of life between girls in the
intervention and control groups at post-intervention and 3-months follow-up. However, a
“sleeping effect” was evident, as girls in the intervention group had a significantly
higher health-related quality of life (small effect size) at the 12-months follow-up
compared to girls in the control group (see Table 3). The model with the general health
variable as outcome showed a significant group effect, F(1, 807) = 10.54, p = .001, while
the effect of time (p = .466) and group × time (p = .598) were nonsignificant. The planned
comparison analyses showed that girls in the intervention group had significantly more
favorable general health at post-intervention compared to girls in the control group
(small effect size), which was maintained at follow-up, as well (see Table 3).

<hs>  Dose-response effect related to the number of attended workshops</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Since the degree of attendance was irrelevant for the control group, the group variable
was recoded as 0 (control group), and 1–4 (1 = 0 workshops in intervention student, 2 = 1
workshop, 3 = 2 workshops, 4 = 3 workshops). Neither group (p =  .290), time (p =  .715),
nor time × group (p = .750) were significant among boys in the intervention group.
However, in girls, the main effect of group was significant, F(4, 756) = 10.96, p <  .001.
The time (p =  .284) and the interaction effects (time × group) (p =  .335) were
nonsignificant. The follow-up tests, as presented in Table 4, indicate that an increasing
attendance yielded a stronger intervention effect. A noteworthy finding was that boys and
girls needed to attend at least three and two workshops, respectively, in order to benefit
from the HBI intervention. This moderation effect was lost among boys at follow-up, but
not among girls. All effect sizes were in the small range (see Table 4). Comparable
analyses on health-related quality of life and the general health variable revealed no
significant moderation effects.

<h>DISCUSSION</h>
----------

The HBI intervention promoted a post-intervention effect on positive embodiment and
perceived general health for boys, although no sustained effects were observed. However,
for girls, the HBI intervention promoted immediate and sustained positive embodiment.
Additionally, for girls, there was a consistent pattern of improvement in perceived
general health at post-intervention and 12-months follow-up, whereas the effects on
health-related quality of life were only demonstrated at 12-months follow-up. These
findings seem to converge with other body image programs that include follow-up measures
(Espinoza et al., 2013; Neumark-Sztainer et al., 2010). The effect sizes in girls were
also strongest at the 12-months follow-up, which is noteworthy. The current study
increases the knowledge base of the long-term and delayed effect of body image
interventions, which currently is scarce. Our study emphasises the importance of long-term
follow-ups as some intervention effects may mature in a slower manner. The intervention
was intended to facilitate awareness of how attitudes towards the body and lifestyle
choices are transmitted through different learned social channels, and, through that,
shape students' attitudes, feelings, and lifestyles. According to a sociocultural
perspective (Thompson et al., 1999), an increase in critical awareness could have improved
the ability to withstand unhealthy idealization, reducing the risk of internalization of
such ideals (Teall & Piran, 2012). Students were also taught to become aware of, and use,
factors in everyday life that enhance their embodiment. Further, body functionality and
well-being were emphasized, rather than appearance, when discussing lifestyle factors.
This could have promoted healthy perspectives on how to engage in lifestyle behaviours,
similar to positive embodiment characteristics (Tylka & Wood-Barcalow, 2015). The HBI
intervention is to our knowledge, the first one among body image interventions to report
on effects on health-related quality of life. In girls, the diffusion of the health-
related quality of life effect from improving their embodiment was expected because these
variables have been found to be highly correlated (Griffiths et al., 2017; Haraldstad et
al., 2011). By strengthening the ability to filter media information, reduce unhealthy
comparisons, and promote positive self-talk, it might be easier to improve body acceptance
which may transform into better psychological well-being. Moreover, improving self-care
and a healthy conscious lifestyle, may ultimately improve physiological health, which may
explain the observed improvements in health-related quality of life. The effect sizes were
in general small and comparable with previous studies (Franko et al., 2013; Halliwell,
Jarman, McNamara, Risdon, & Jankowski, 2015; Lindwall & Lindgren, 2005; Morgan, Saunders,
& Lubans, 2012; Sharpe, Schober, Treasure, & Schmidt, 2013). In contrast to clinical
studies, the interpretation of small effect sizes may be more favourable. Thus, such small
effect sizes are common in universal interventions, and may be expected due to low base
rates for clinical symptoms, and a high probability of ceiling effect for positive health
indices. Similarly, by definition, study variables in health promotion studies do not pre-
select participants having scores within a clinical range (Wilksch, 2014). Attention has
been given in the literature (Piran, 2001) to how students perceive the credibility of
those who deliver intervention programs. In the present study, students were informed
about the facilitators' education and academic position. In addition, the facilitators
were attentive to the quality of their verbal and non-verbal communication with the
students. Nevertheless, the students’ perceived credibility of the workshop facilitators
was not assessed. An explicit rationale for the HBI intervention was to promote the
interaction between boys and girls, and to mirror the across-gender sociocultural
influences on body experiences that occurs in a realistic real-life setting. Strategies to
accomplish this rationale included the use of different interactive components, thus, to
enhance the chance of effect in both genders. Our study only found long-term effects in
girls. This may support previous suggestions that girls are more receptive to body image
interventions (Stice et al., 2007) even when efforts have been made to make the
intervention gender neutral. Importantly, our results do not document that a single-gender
intervention is preferred. Further, the HBI intervention is a health promotion
intervention, where the aim is not only to reduce risk factors, but to promote health-
related factors. Based on our findings, a mixed-gender approach might have been important
to girls despite the lack of effect in boys. To further investigate whether single- or
mixed-gender approaches is most effective, future studies need to include more arms
(control, mixed-gender, single-gender- group) into the study design. Similar to the
effects of the HBI intervention, weak and transient effects from a body image intervention
has been found in other studies on young adult men (Jankowski et al., 2017). Importantly,
although undocumented, the presenters observed that the boys found the topics of
"comparison," "self-talk," and "communication" not as relevant as the girls, which could
have made it more difficult to be engaged and receptive to the workshop content. Previous
studies have shown that enhancing peer comradery and connection, and including masculine
points of reference, helped engage boys and men in an intervention (Seaton et al., 2017).
Perhaps the female implementers in the HBI intervention may have had challenges with
potentially important factors to engage boys as well as may have under-communicated the
masculine aspects. Virtually no effects among boys may also be explained by scores above
norm data for health-related quality of life at baseline (Ravens-Sieberer, 2006). Although
no norm data for the EES exists for late adolescent boys, one study on young men showed
that boys scored significantly higher on the EES compared to girls (Holmqvist et al.,
2018). This could reflect that boys at baseline are more accepting of their bodies, and
therefore have a lower improvement potential compared to girls. At present, it remains
unsettled whether the intervention may work better among boys with lower baseline health-
related quality of life and embodiment, and whether it may work equally well in a girls-
only group. Our findings contradict the suggestion (Wilksch, 2017) that a single-session
(workshop) intervention may suffice. Although a one-session may be more feasible in school
settings, our results are in line with the elaboration likelihood model (Petty & Briño,
2012; Petty & Cacioppo, 1986) and previous meta-analyses (Stice & Shaw, 2004; Stice et
al., 2007), that at least two workshop sessions were needed for girls to maintain the
intervention effects at follow-up.

<hs>  Strengths, limitations, and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Assets of the present study are the theoretical framework, the user involvement through a
pilot study, the randomized controlled design and the adequate statistical power. However,
a loss of power at the follow-ups may have increased the probability of Type II errors,
especially in boys. The fact that boys who dropped out had a slightly higher BMI is
consistent with previous observations in health- and body image-related interventions and
classroom-based activities (Finn, Faith, & Seo, 2018), that those with higher BMI feel
self-conscious when exposed to the intervention content. However, boys who dropped out did
not differ in positive embodiment or health-related quality of life, which reduces the
reasons to believe that many of those who might especially benefit from our intervention
dropped out. Drop-outs seem almost inevitable, yet some steps may be mentioned to
counteract them. Although we used measures of positive aspects of body image and not
measures of body dissatisfaction, care should be taken when considering the
comprehensiveness of the questionnaire, and to decrease the number of included questions,
notably those of a sensitive nature. To facilitate improvement potential, one challenge is
to select outcome measures where both genders have room for improvement. Before a broader
dissemination of the HBI intervention, modifications to the workshops should be tested,
with male facilitators, to further investigate whether it might be possible to achieve
genuine and sustainable effects for boys. Also, although the credibility of the workshop
holders was planned and facilitated for, the students’ perceptions of this credibility
were not assessed. This is a limitation, and future studies should include such
assessment. In addition, there is a need to study the dismantling potentials. The present
findings clearly indicate that among girls, two interactive and multicomponent workshops
may suffice. However, future studies need to address the issue of which of the three
workshops that may be deleted from the program. This would inform which of the themes
(i.e. body image, media literacy, and lifestyle factors) that should be retained.

<hs>  Conclusion</hs>
  ~~~~~~~~~~

The HBI intervention promoted a post-intervention effect on positive embodiment and
perceived general health in boys. The intervention promoted a sustained effect on positive
embodiment and health-related quality of life in girls. Future studies should examine the
effect of only two workshops for girls and modifications of the workshops for boys to see
if it is possible to obtain sustained effects in boys as well.

<h>COMPETING INTERESTS</h>
-------------------

The authors declare that they have no competing interests.

<h>FUNDING</h>
-------

This work was supported by The Norwegian Woman`s Public Health Association (H1/2016), the
Norwegian Extra Foundation for Health and Rehabilitation (2016/FO76521), and TINE SA. The
sponsors came in after the study protocol was developed and did not have any role in
development of study design, data collection, analysis or interpretation of data, or
manuscript writing and submission.


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<ART>The impact of developmental coordination disorder on educational achievement in secondary school
================================================================================

Authors: Ian Harrowell, Linda Hollén, Raghu Lingam, Alan Emond
DOI: 10.1016/j.ridd.2017.10.014
Year: 2018  |  Pages: 13-22
ASJC codes: 3203, 3204
Keywords: ALSPAC, Developmental coordination disorder, Educational achievement, Motor difficulties

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background Developmental coordination disorder (DCD) is a common developmental disorder but its long term impact on health and education are poorly understood. Aim To assess the impact of DCD diagnosed at 7 years, and co-occurring developmental difficulties, on educational achievement at 16 years. Methods A prospective cohort study using data from the Avon Longitudinal Study of Parents and Children (ALSPAC). National General Certificate of Secondary Education (GCSE) exam results and Special Educational Needs provision were compared for adolescents with DCD (n = 284) and controls (n = 5425). Results Adolescents with DCD achieved a median of 2 GCSEs whilst controls achieved a median of 7 GCSEs. Compared to controls, adolescents with DCD were much less likely to achieve 5 or more GCSEs in secondary school (OR 0.27, 95% CI 0.21–0.34), even after adjustment for gender, socio-economic status and IQ (OR 0.6, 95% CI 0.44–0.81). Those with DCD were more likely to have persistent difficulties with reading, social communication and hyperactivity/inattention, which all affected educational achievement. Nearly 40% of adolescents with DCD were not in receipt of additional formal support during school. Conclusions DCD has a significant impact on educational achievement and therefore life chances. Co-occurring problems with reading skills, social communication difficulties and hyperactivity/inattention are common and contribute to educational difficulties. Greater understanding of DCD among educational and medical professionals and policy makers is crucial to improve the support provided for these individuals.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPER ADDS?</h>
---------------------

Developmental coordination disorder (DCD) is one of the most common developmental
conditions of childhood. However, its impact on longer term health and education is not
well understood. This paper contributes robust epidemiological evidence of the persisting
impact that DCD can have on learning and achievement in secondary school. Using a
population-based cohort, individuals with DSM-IV classified DCD at 7 years were 70% less
likely to achieve 5 or more qualifications at 16 years than their peers. Co-occurrence of
reading difficulties and other developmental traits, such as social communication
difficulties and hyperactivity/inattention, were commonly present in adolescence and these
difficulties contributed to poor educational achievement. This study also illustrates the
extent to which DCD can be a hidden disability – 37% of those with the condition were not
in receipt of additional formal teaching support. These results demonstrate the impact DCD
can have on educational attainment, and therefore on future life prospects. It is hoped
this work will contribute to raising awareness and understanding of the impact of DCD and
stimulate discussion about how best to support those with this complex condition.

<h>INTRODUCTION</h>
------------

Developmental coordination disorder (DCD) is a common neurodevelopmental disorder
characterised by deficits in both fine and gross motor coordination which have a
significant impact on a child’s activities of daily living or school productivity
(American Psychiatric Association, 2013). These deficits are present in the absence of
severe intellectual or visual impairment, or another motor disability, such as cerebral
palsy. It is thought to affect around 5% of school-aged children (American Psychiatric
Association, 2013), but despite its high prevalence it remains one of the less well
understood and recognised developmental conditions in both educational and medical
settings. Schoolwork of children with DCD often does not reflect their true abilities as
they struggle with fine motor skills, including handwriting (Missiuna, Rivard, & Pollock,
2004). However, there is also evidence of a wider academic deficit involving reading,
working memory and mathematical skills (Alloway, 2007; Dewey et al., 2002; Kaplan, Wilson,
Dewey, & Crawford, 1998). Although initially identified on the basis of motor
difficulties, the condition may develop into complex psychosocial problems, with
difficulties in peer relationships and social participation (Sylvestre, Nadeau, Charron,
Larose, & Lepage, 2013), bullying (Campbell, Missiuna, & Vaillancourt, 2012; Skinner &
Piek, 2001; Wagner et al., 2012), low self-worth and perceived self-competence (Piek,
Baynam, & Barrett, 2006), and internalising disorders, such as anxiety and low mood
(Lingam et al., 2012). It may be that these sequelae lead to poor performance in school.
As well as secondary psychosocial consequences, those with DCD have a higher risk of
displaying other developmental traits, such as hyperactivity and social communication
difficulties, and specific learning disabilities, particularly dyslexia. (Kadesjo &
Gillberg, 1999; Lingam et al., 2010; Sumner et al., 2016). Overlapping difficulties in two
or more developmental and educational domains implies that discrete diagnosis of a single
disorder is often not appropriate (Kaplan, Dewey, Crawford, & Wilson, 2001). In some
individuals with DCD, it may be that co-occurring difficulties contribute to or explain
some of the sequelae of the condition (Conti-Ramsden, Durkin, Simkin, & Knox, 2008; Loe &
Feldman, 2007). Previous work has highlighted the importance of identifying co-occurring
problems in DCD by demonstrating the mediating effects of social communication
difficulties and hyperactivity can have on psychological outcomes (Harrowell, Hollén,
Lingam, & Emond, 2017; Lingam et al., 2012). In the evaluation and management of a child
with suspected DCD, consideration of other possible co-occurring difficulties is
essential. Although the body of literature on DCD demonstrates many reasons why a child
with DCD might struggle in school (Zwicker, Harris, & Klassen, 2013), lack of awareness of
the condition by medical and educational professionals is widespread, highlighted by
parental reports of difficulty accessing support and services for their child (Missiuna,
Moll, Law, King, & King, 2005; Novak, Lingam, Coad, & Emond, 2012). One study found that
43% of parents were not offered any practical support (Alonso Soriano, Hill, & Crane,
2015). Even when support is provided, it may not be appropriate for the child, which
parents put down to lack of understanding of the condition (Maciver et al., 2011). A study
of students in further and higher education found that those with dyslexia were more
likely than students with DCD to receive Disability Student Allowance from the government,
despite greater self-reported difficulties in the DCD group (Kirby, Sugden, Beveridge,
Edwards, & Edwards, 2008). Furthermore, there were no differences between the types of
support provided for these two different developmental disorders. This not only emphasises
the poor recognition of DCD, but also lack of understanding of the specific needs of those
with coordination problems. By definition, children with DCD have motor difficulties that
interfere with academic achievement (American Psychiatric Association, 2013). However,
longitudinal studies of educational achievement in secondary school for those with DCD are
few, and those that have been conducted lack strict diagnostic criteria or have been drawn
from clinical samples. (Cantell, Smyth, & Ahonen, 1994; Gillberg & Gillberg, 1989; Losse
et al., 1991). Thus, the primary aim of this research was to assess the impact of DCD on
educational achievement in secondary school, using prospective data from a large
population-based cohort study. Secondly, we aimed to assess the presence of co-occurring
difficulties in reading ability, social communication problems and
hyperactivity/inattention, and whether these impacted upon educational achievement in DCD.
Thirdly, we aimed to determine how many of those meeting the criteria for DCD were
identified for formal additional educational support in school, and assess whether
provision of support was related to educational achievement.

<hs>  Study participants</hs>
  ~~~~~~~~~~~~~~~~~~

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a population-based birth
cohort which invited all pregnant women in the Avon area of southwest England, with
expected dates of delivery between 1 April 1991 and 31 December 1992 to take part. The
original sample comprised 14062 live-born children, with 13968 surviving to 1 year. ALSPAC
has collected data on a large range of socio-economic, environmental and health measures
for both parents and children; data were collected using questionnaires, face-to-face
assessments and linked health and education data. Recruitment of participants and data
collection have been described in detail elsewhere (Boyd et al., 2013). The study website
contains details of all the data that are available through a fully searchable data
dictionary (http://www.bris.ac.uk/alspac/researchers/data-access/data-dictionary/).
Ethical approval for ALSPAC was obtained from the Local Research Ethics Committees, and
this study was monitored by the ALSPAC Ethics and Law Committee.

<hs>  Identification of developmental coordination disorder</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Classification of children with DCD in this cohort and derivation of the measures used for
the inclusion and exclusion criteria has been described in detail previously (Lingam,
Hunt, Golding, Jongmans, & Emond, 2009). Children were defined as having DCD by applying
the inclusion (Criteria A and B) and exclusion criteria (Criteria C and D) derived from
the Diagnostic and Statistical Manual of Mental Disorders 4th Edition Text Revision (DSM-
IV-TR) and adapted for research using the 2006 Leeds Consensus Statement (American
Psychiatric Association, 2000; Sugden, Chambers, & Utley, 2006). Children were classified
as having DCD at 7–8 years if they met all four criteria: (A) marked impairment of motor
coordination, (B) motor coordination impairment significantly interferes with academic
achievement or activities of daily living (ADL), (C) absence of another
neurological/visual disorder, and (D) absence of severe learning difficulty (IQ > 70). DCD
was defined in this cohort prior to the publication of the Diagnostic and Statistical
Manual of Mental Disorders 5th Edition (DSM-V; American Psychiatric Association, 2013).
However, the criteria for DCD were not significantly altered between the two editions, and
so the criteria used in this cohort are compatible with the definition of DCD in the more
recent DSM-V. The ALSPAC coordination test, consisting of 3 subtests of the Movement
Assessment Battery for Children Test (MABC; Henderson & Sugden, 1992), was applied by 19
trained examiners in a purpose-built research clinic at 7–8 years. Consistency was
maintained by standardised training and ongoing supervision and training. The 3 subtests
were chosen, following principal component analysis of the original standardization data
set of the MABC, as they best represented the three domains of coordination: heel-to-toe
walking (balance), placing pegs task (manual dexterity) and throwing a bean bag into a box
(ball skills). Age-adjusted scores were derived by comparing the scores of each child to
raw scores in the cohort itself. Those scoring under the 15th centile in the coordination
test were considered to have a motor impairment, consistent with criterion A of the DSM-
IV-TR definition (Schoemaker, Lingam, Jongmans, van Heuvelen, & Emond, 2013). Academic
achievement was assessed using linked educational data. As part of the national curriculum
in the UK, literacy testing is undertaken at 7 years (Key Stage 1), which involves a
writing test with questions on English grammar, punctuation and spelling. The writing test
is scored 1–4 (4 being the best, 2 being the expected level at this age): those who scored
1 were considered to have significant difficulties with writing. ADL were assessed using a
parent-completed 23-item questionnaire at 6 years 9 months of age, containing items
derived from the Schedule of Growing Skills II (Bellman, Lingam, & Aukett, 1996) and the
Denver Developmental Screening Test II (Frankenburg & Dodds, 1967). The questions
represented skills the child would have been expected to achieve by 81 months. It assessed
for difficulties in developmentally age-appropriate skills with which children with DCD
struggle, such as self-care, playing, and gross and fine motor skills. Age-adjusted scores
were calculated by stratifying the child’s age and those scoring below the 10th centile
were considered to have significant impairment. IQ was measured at 8.5 years by trained
psychologists in a research clinic using a validated and shortened form of the Wechsler
Intelligence Scale for Children-III (WISC-III; Wechsler, Golombok, & Rust, 1992; Connery,
Katz, Kaufman, & Kaufman, 1996). Alternate items were used for all subtests, with the
exception of the coding subtest which was administered in its full form. Using the look-up
tables provided in the WISC-III manual, age-scaled scores were obtained from the raw
scores and total scores were calculated for the Performance and Verbal scales. Prorating
was performed in accordance with WISC-III instructions. IQ was assumed to be stable over
time (Schneider, Niklas, & Schmiedeler, 2014). Those with an IQ < 70 and those with known
visual, developmental or neurological conditions were excluded from case definition of DCD
(criterion C and D). Children who scored below the 15th centile on the ALSPAC coordination
test (criterion A), and had significant difficulties with writing in their Key Stage 1
handwriting test or were below the 10th centile on the ADL scale (criterion B), were
defined as having DCD. At 7–8 years, a cohort of 6902 children had all the data required
for full assessment, and 329 children met the criteria for DCD.

<hs>  Educational achievement</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

ALSPAC obtained linked educational data from the National Pupil Database, a central
repository for pupil-level educational data, and from the Pupil Level Annual School
Census, which captures pupil-level demographic data about special needs support. The
linked educational data in ALSPAC covers pupils in England and in state-funded schools;
therefore pupils from Wales or in independent schools are excluded from this analysis.
Academic achievement at 16 years was assessed using the results from the General
Certificate of Secondary Education (GCSE) at Key Stage 4. These are the national
achievement exams, covering a range of subjects (English and Maths are mandatory),
undertaken at the end of compulsory schooling by all children in state schools in England.
They are marked by anonymous external examiners and given grades ranging from A*-G. For
the purpose of our analysis, we dichotomised the cohort into those who did and did not
achieve 5 or more GCSEs graded A*-C, which is a widely used marker of performance in the
UK. Special Educational Needs (SEN) provision data were obtained at 9–10 years (year 5,
end of primary school) and 11–12 years (year 7, start of secondary school). At 9–10 years
old, SEN status was divided into six groups. ‘No SEN provision’ indicated no formal
support was being provided. ‘SEN provision without statement levels 1–4’ indicated extra
support was being provided, with increasing level indicating increasing level of severity.
‘Statement of SEN’ indicated that a statutory assessment by the Local Authority had been
undertaken and a statement of extra support required had been created. SEN status at 11–12
years was categorised into four main groups: ‘no SEN provision’, ‘School action’ (which
indicated the child had been recognised as not progressing satisfactorily and extra
support was being provided internally), ‘School action plus’ (which indicated the child
had not made adequate progress on ‘school action’ and the school had sought external help
from the Local Authority, the National Health Service or Social Services), and ‘Statement
of SEN’. For the purpose of our analyses, at both time points, SEN status was
dichotomised: those receiving no formal support at all and those receiving some level of
support.

<hs>  Confounding variables</hs>
  ~~~~~~~~~~~~~~~~~~~~~

Gender, gestation, birthweight, socioeconomic status and IQ are known to be associated
with DCD (Lingam et al., 2009), and have well-established links with academic performance.
They were therefore selected as confounders for the multi-variable analysis. Gender,
gestation and birthweight were extracted from the birth records in ALSPAC. Family
adversity was measured using the ALSPAC Family Adversity Index (FAI). This is derived from
responses to a questionnaire about childhood adversity and socio-economic status which
mothers completed during pregnancy. The index comprises 18 items which are assigned a
score of 1 if adversity is present and 0 if it is absent, giving a total possible score of
18. The FAI includes the following factors: age at first pregnancy, housing adequacy,
basic amenities at home, mother’s educational achievement, financial difficulties, partner
relationship status, partner aggression, family size, child in care/on risk register,
social network, known maternal psychopathology, substances abuse and crime/convictions.

<hs>  Co-occurring difficulties</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Reading ability (Lingam et al., 2010), social communication difficulties (Conti-Ramsden et
al., 2008) and hyperactivity/inattention (Loe & Feldman, 2007) were selected as important
conditions to be adjusted for in the multi-variable analysis, as they often co-occur with
DCD and can impact on educational achievement. Reading ability was measured in research
clinics at 13.5 years using the Test of Word Reading Efficiency (TOWRE), a short test
which measures an individual's ability to pronounce printed words and phonemically regular
non-words accurately and fluently. Words are used to assess sight word reading efficiency
and non-words to assess decoding efficiency. The scoring is based on the number of
words/non-words read quickly and correctly during 45 s (Torgesen, Wagner, & Rashotte,
1999). Social communication difficulties were measured at 16.5 years using the Social and
Communication Disorders Checklist (SCDC; Skuse, Mandy, & Scourfield, 2005), completed by
the main caregiver. It comprises 12 items relating to the child’s social communication
ability and cognition, each with 3 responses (not true, quite or sometimes true/very or
often true, scoring 0/1/2 respectively). Answers are summed to give a score between 0 and
36. A score of 9 or above was used to predict social communication difficulty trait
(Humphreys et al., 2013). Hyperactivity/inattention was measured at 15.5 years using the
self-reported Strengths and Difficulties Questionnaire hyperactivity-inattention subscale
(SDQ; Goodman & Goodman, 2009). This subscale of the questionnaire comprises 5 items
relating to behaviours indicating hyperactivity, each with 3 responses (not true/somewhat
true/certainly true, scored 0/1/2 respectively). A score in the top decile of the ALSPAC
cohort was taken as indicating significant hyperactivity (Goodman, 2001).

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

The two-sample test for proportions, Student’s t-test and the Mann-Whitney U test were
used, where appropriate, to assess differences between groups. Logistic regressions were
used to assess the impact of DCD on educational achievement. Multi-variable models were
created to adjust for the effect of the confounding variables and mediating variables
sequentially. Covariates significant at the 5% level in the univariate analyses were
included in the multivariable models. Model 1 adjusted for gender, birthweight, gestation
and socioeconomic status. Model 2 adjusted for IQ. Model 3 adjusted for reading ability.
Model 4 adjusted for the developmental traits of social communication difficulties and
hyperactivity/inattention. Pearson goodness of fit chi-squared tests were used to ensure
satisfactory model fit. Multiple imputation using chained equations (ICE) was used to
impute missing data in the covariates only (Appendix A in Supplementary material).
Analysis of imputed datasets helps to minimise attrition bias and improve precision of
estimates (Sterne et al., 2009). Logistic regressions were used to determine which
variables strongly predicted missingness and these were included in the ICE prediction
models. Twenty imputations were performed. All analyses were performed using Stata v. 14.1
(StataCorp, College Station, TX, USA). An alpha level of 0.05 was used for all statistical
tests.

<hs>  Sample characteristics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Of those previously assessed for DCD at age 7 years, educational data at 16 years were
available for 5709 adolescents, including 284 (4.9%) of those who met the criteria for
DCD. These represented 86% (284/329) of those originally diagnosed with DCD.
Characteristics of those with and without educational outcome data available are shown in
Appendix B in Supplementary material. Characteristics of the adolescents with DCD and
controls with educational data available are compared in Table 1. In this follow-up
cohort, when compared to controls, those with DCD were more likely to be male, have been
born prematurely, have a low birth weight, have a lower IQ and have experienced greater
family adversity.

<hs>  Academic achievement and SEN status</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

There were substantial differences in educational achievement and SEN status between the
controls and DCD group (Table 2). The control group achieved a median of 7 GCSEs graded
A*-C, with 70% overall achieving 5 or more GCSEs at this level. In contrast, those with
DCD achieved a median of 2 GCSEs graded A*-C, with 39% overall achieving 5 or more GCSEs.
Fig. 1 illustrates the skewed distribution of GCSE attainment in the DCD group. When
results were stratified by gender, in the control group girls performed significantly
better than boys in achieving 5 or more GCSEs graded A*-C (76% vs. 65%, z = 8.89, p <
0.001). In the DCD group, girls were also more likely than boys to achieve 5 or more GCSEs
graded A*-C, but this association did not reach significance (46% vs. 35%, z = 1.84, p =
0.064). The majority of those in the control group were not receiving any SEN provision at
both time points; 895/5165 (17%) of controls received some form of SEN provision during
their school career. In contrast, of those in the DCD group, 175/273 (63%) received some
form of SEN support (z = −18.77, p < 0.001). In the DCD group, 15% were in receipt of
support in primary school only and 9% in secondary school only, with 39% being recognised
as needing extra support in both primary and secondary school. A sub-group analysis was
performed to compare educational achievement for those who received SEN support and those
who did not (Table 3). Differences between the groups were assessed using the two-sample
test for proportions. Controls who received no SEN support were no more likely to achieve
5 or more GCSEs graded A*-C than those with DCD who received no SEN support (76% vs. 70%,
z = 1.37, p = 0.17). Controls who received SEN support at any time were more likely to
achieve 5 or more GCSEs graded A*-C than those with DCD who received SEN support at any
time (27% vs. 16%, z = 3.00, p < 0.01). In the control group, those who received no SEN
support were more likely to achieve 5 or more GCSEs graded A*-C than those who received
SEN support at any time (76% vs. 27%, z = 28.10, p < 0.001). This was similar to the DCD
group: those who received no SEN support were more likely to achieve 5 or more GCSEs
graded A*-C than those who received SEN support at any time (70% vs. 16%, z = 6.85, p <
0.001).

<hs>  Co-occurring difficulties</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Table 4 details the co-occurring difficulties reported for the control and DCD groups.
Those with DCD were more likely to have difficulty with reading on both the word and non-
word tests, social communication difficulties and hyperactive-inattentive behaviours.

<hs>  Multi-variable logistic regression</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The results of the multi-variable logistic regressions, using the multiple imputation
dataset, are shown in Fig. 2. Results of the analyses of all available data are presented
in Appendix C in Supplementary material. In the unadjusted model, compared to their peers,
individuals with DCD were much less likely to achieve 5 or more GCSEs graded A*-C (Odds
Ratio [OR] 0.27, 95% Confidence Interval [CI] 0.21–0.34). Even after adjusting for
confounding variables and IQ, they were still significantly less likely to achieve 5 or
more GCSEs (OR 0.60, 95%CI 0.44–0.81). After adjusting for reading ability, this
association was attenuated (OR 0.73 95%CI 0.52–1.01) and was attenuated further after
adjustment for poor social communication skills and hyperactivity/inattention (OR 0.78,
95% CI 0.55–1.10).

<hs>  Summary of results</hs>
  ~~~~~~~~~~~~~~~~~~

This prospective study using a large population-based UK cohort and strict diagnostic
criteria has shown that children with DCD are much less likely to achieve 5 or more GCSEs
graded A*-C in secondary school when compared to their peers. Children with DCD were more
likely to have difficulties with reading, social communication and
hyperactivity/inattention, and these problems contributed to poor achievement in school.
Those with DCD were more likely to be identified as requiring formal SEN support than
controls, although over a third of those with the condition were not identified as
requiring formal SEN support. Adolescents with DCD without SEN support did not perform
significantly worse in their GCSEs than controls without SEN support. Conversely,
adolescents with DCD who were receiving SEN support performed worse in their exams than
controls with SEN support.

<hs>  Discussion of results</hs>
  ~~~~~~~~~~~~~~~~~~~~~

The proportion of pupils achieving 5 or more GCSE qualifications at grades A*-C is not
only used as an attainment indicator in the UK (Department for Education, 2016), but at an
individual level it is often specified as a requirement to obtain places in further
post-16 school education, in college or in certain jobs and apprenticeships. Poor
performance in GCSEs can therefore have a large negative impact on an individual’s life
prospects, depending on what they wish to do, as it may limit options for the next steps
in their educational or vocational development. It is known that median hourly pay rate
increases incrementally with increasing level of qualification, and that those with a
higher level of qualification are more likely to be in skilled and better paid jobs
(Office for National Statistics, 2011). Therefore, those with DCD are at a considerable
disadvantage not only educationally, but also economically in their future careers. DCD is
one of the more prevalent but less well-understood developmental conditions, and so this
impact on life course is concerning. As well as accounting for the effects of important
confounders and IQ on the relationship between DCD and educational achievement, we
assessed the impact of co-occurring difficulties with reading, social communication and
hyperactivity/inattention. As the effect of these traits were consecutively adjusted for
in the multi-variable model, the difference between the control and DCD group was
attenuated, which is reflected in the sequentially attenuated odds ratios from model 2 to
model 4. This suggests that co-occurring developmental traits, which are common in DCD
(Lingam et al., 2009), may account for some of the under-achievement at GCSE level in
those with DCD compared to controls. In the fully adjusted model, those with DCD were 22%
less likely to achieve 5 or more GCSEs compared to controls. However, it should be noted
that the confidence intervals are substantially wider in models 3 and 4, which likely
reflects the greater attrition in response rates for the variables in these models. These
results emphasise the need for a holistic view of a child with DCD – problems with school
work may not just be solely due to motor deficits and they should not be viewed as ‘just
clumsy’. Co-occurring difficulties in other developmental domains should be actively
sought, and if present, addressed in any support provided. Of those who met the criteria
for DCD, 37% did not receive any formal SEN provision. This corroborates what has been
reported in qualitative work with parents (Missiuna et al., 2005) and illustrates how DCD
is often a hidden disability, as motor deficits can be subtle and learning impairments
difficult to recognise. This is important to realise because if missed, children with DCD
may start to avoid situations which draw attention to their poor coordination as they
become more aware of their motor difficulties, to try to minimise embarrassment or
bullying. Previous work on this cohort has shown that adolescents with DCD report more
bullying and less supportive friendships than their peers (Harrowell et al., 2017). This,
along with reducing engagement at school, will contribute to poor perceived efficacy and
low self-esteem (Skinner & Piek, 2001). The combined impact of these secondary problems,
as well as the primary motor deficit, will ultimately compound poor performance in school.
Poor academic performance may further exacerbate engagement at school, leading to a
complex vicious circle. Within the DCD group, those with formal SEN provision performed
significantly worse in their exams than their counter-parts without SEN provision. The
explanation for this is likely two-fold. Firstly, those with the most severe motor
deficits, who will have most difficulty in school, are likely to be recognised as
requiring extra help. Secondly, it may be that those receiving SEN support were those with
co-occurring difficulties, whose multiple problems compound their poor performance, and
are more likely to be recognised as needing support. A previous study which found a
similar pattern in children with specific language impairments; those who had a ‘Statement
of SEN’ performed worse than those without one in their secondary school exams (Durkin,
Simkin, Knox, & Conti-Ramsden, 2009).

<hs>  Implications of the findings</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Guidelines for diagnosis, assessment and intervention in DCD were published in 2012 based
on the best available evidence (Blank, Smits-Engelsman, Polatajko, & Wilson, 2012), and
were more recently adapted for the UK context following a multi-disciplinary consultation
(Barnett, Hill, Kirby, & Sugden, 2015). The evidence provided by this study supports the
need to raise awareness of the condition and its consequences not only among educational
and clinical health professionals, but also policy makers. Clearly defined pathways for
children with DCD are required to coordinate services appropriately. The work of
organisations like the Dyspraxia Foundation (Dyspraxia Foundation, 2016) and Movement
Matters (Movement Matters UK, 2016) provide information about DCD to families, carers,
teachers and clinicians, with the aim of improving awareness of and support for
individuals with condition. Since March 2014, policy for SEN provision in the UK has been
reformed, with the ‘Statement of SEN’ being replaced by an incorporated ‘Educational,
Health and Care Plan’ in the Children and Families Act 2014 (Department for Education,
2014). How this will impact upon care of those with DCD remains to be seen, and
implementation is likely to vary between regions. It is hoped that the results of the work
on DCD in ALSPAC will contribute to improving awareness and understanding of DCD and
subsequently improved planning of support. Increased awareness and understanding of the
condition needs to be followed by improved intervention. The evidence base for what
interventions work best in DCD is limited. Interventions which are task-orientated and
individualised appear to have the largest effect on motor skills, based on a recent
systematic review of high quality randomised controlled trials (Preston et al., 2016). As
highlighted in this study, however, motor skills may only be one domain that requires
attention in a child identified as having DCD. More research is needed on the benefit of
interventions aimed at addressing other developmental domains concurrently, such as social
communication skills (Piek et al., 2015). Further, there is a paucity of research into the
needs of adolescents and adults with DCD. Many young people with DCD continue to
experience motor and psychosocial difficulties after they have finished school and it is
important that they are not forgotten and are supported to gain employment (Kirby,
Edwards, & Sugden, 2011; Kirby, Williams, Thomas, & Hill, 2013).

<hs>  Strengths and weaknesses of the study</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The key strength of this study is the use of a large, prospective, population-based sample
which is broadly representative of the UK (Boyd et al., 2013), and avoids the biases
introduced in clinical samples. Due to the large amount of data collected in ALSPAC, we
were able to strictly define our cases of DCD according to DSM-IV-TR criteria, and also to
assess the impact of important co-occurring problems on our main outcome. The use of
linked educational data was also a strength of the study. The main weakness of this study,
as with all prospective cohorts, is attrition. Through the use of linked education data,
we were able to minimise loss-to-follow-up in our primary outcome measure. For those who
had GCSE data available (n = 5709), 81% had all the covariates available for multi-
variable models 1 and 2. Those who did not have GCSE data available at 16 years were more
likely to have higher IQ and a higher level of maternal education (Appendix A in
Supplementary material), a pattern which was seen in both the control and DCD groups and
so should not systematically affect our results and thus our conclusions. The largest
attrition occurred in model 4 (social communication deficits and hyperactivity), which
relied on questionnaires filled out between 14 and 16 years. In ALSPAC, it is recognised
that those who are lost to follow-up in clinics and questionnaires tend to come from lower
socio-economic backgrounds, have lower IQ and are more likely to be male (Boyd et al.,
2013). These are factors which are also associated with DCD and so differences between the
groups may be under-estimated. We have attempted to minimise any bias introduced by
missing data in the covariates by the use of multiple imputation, a well-validated
statistical technique (Sterne et al., 2009). Another drawback is that no measure of motor
competence was performed in adolescence. Motor skill difficulties identified in childhood
do not always persist into adolescence (Cantell et al., 1994) and so there may be some in
the DCD group who no longer have significant motor deficits. Furthermore, we were only
able to comment on whether the child had been identified as requiring formal SEN
provision, but not the level or type of support, or whether intervention had any impact on
the core deficits in DCD.

<h>CONCLUSIONS</h>
-----------

DCD is an important but poorly understood developmental condition that has a stark impact
upon educational achievement at the end of secondary schooling, which will affect an
individual’s future prospects. Co-occurring developmental conditions are common, and may
contribute to poor educational outcomes. Addressing these co-occurring difficulties, as
well as motor deficits, is necessary to improve outcomes. Increased awareness and
understanding of the condition amongst healthcare and educational professionals and policy
makers is vital to improve the support provided for those with DCD.

<h>CONFLICT OF INTERESTS</h>
---------------------

The authors declare that they have no conflict of interests relating to this article.

<h>FUNDING</h>
-------

This research did not receive any specific grant from funding agencies in the public,
commercial, or not-for-profit sectors. The UK Medical Research Council and the Wellcome
Trust (Grant ref: 102215/Z/13/Z) and the University of Bristol provide core support for
ALSPAC.


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<ART>The influence of transcranial alternating current stimulation (tACS) on fluid intelligence: An fMRI study
================================================================================

Authors: A. C. Neubauer, M. Wammerl, M. Benedek, E. Jauk, N. Jaušovec
DOI: 10.1016/j.paid.2017.04.016
Year: 2017  |  Pages: 50-55
ASJC codes: 3200
Keywords: Fluid intelligence, Neural efficiency, Parieto-frontal integration theory (P-FIT), Transcranial alternating current stimulation (tACS), fMRI

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The past decades have witnessed a huge interest in uncovering the neural bases of intelligence (e.g., Stelmack, & Houlihan, 1995; Stelmack, Knott, & Beauchamp, 2003). This study investigated the influence of transcranial alternating current stimulation (tACS) on fluid intelligence performance and corresponding brain activation. Previous findings showed that left parietal theta tACS leads to a transient increase in fluid reasoning performance. In an attempt to extend and replicate these findings, we combined theta tACS with fMRI. In a double-blind sham-controlled experiment, N = 20 participants worked on two intelligence tasks (matrices and paper folding) after theta tACS was applied to the left parietal cortex. Stimulation-induced brain activation changes were recorded during task processing using fMRI. Results showed that theta tACS significantly increased fluid intelligence performance when working on difficult items in the matrices test; no effect was observed for the visuo-spatial paper folding test. Whole-brain analyses showed that left parietal brain stimulation was accompanied by lower activation in task-irrelevant brain areas. Complemental ROI analyses revealed a tendency towards lower activation in the left inferior parietal cortex. These findings corroborate the functional role of left parietal theta activity in fluid reasoning and are in line with the neural efficiency hypothesis.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Intelligence is associated with diverse relevant real-life outcomes such as educational
accomplishment, occupational performance, and even health (Deary, 2012). There is a long-
standing research tradition to investigate the neural bases of intelligence (e.g., Ertl &
Schafer, 1969; Stelmack & Houlihan, 1995). Neurophysiological models of intelligence
emphasize the role of the fronto-parietal-network. The parieto-frontal integration theory
of intelligence (P-FIT; Jung & Haier, 2007) postulates a four-phase information processing
model which highlights the importance of frontal and parietal brain areas and the
associated communication patterns between those. Another important theory is the neural
efficiency hypothesis. It posits that more intelligent people use their brain resources
more efficiently as compared to less intelligent individuals in terms of lower brain
activation (Haier et al., 1988) or faster neural transmission time (Stelmack, Knott, &
Beauchamp, 2003). A review of relevant findings by Neubauer and Fink (2009) further
suggests that neural efficiency is restricted to tasks of low to moderate task difficulty,
whereas highly able individuals may even invest more cortical resources in very difficult
tasks (see also, Dunst et al., 2014). More recently, there has been an increasing interest
to use and extend our understanding of the brain in attempts to improve intelligence via
brain stimulation (Enriquez-Geppert, Huster, & Herrmann, 2013).

<hs>  Stimulating intelligence</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Due to the social relevance of gf, the issue was raised whether there is a way to increase
it through training or stimulation. However, recent reviews and meta-analyses come to
inconsistent conclusions, either showing that intelligence scores cannot be increased
through cognitive training (Haier, 2014; Melby-Lervåg, Monica, & Hulme, 2016), or finding
support for the beneficial effect of systematic cognitive training (Au et al., 2015;
Karbach & Verhaeghen, 2014). For example, Jaušovec and Jaušovec (2012) reported that
working memory training does not only promote performance in a gf task but also changes
the associated electrocortical brain activation. One particular issue of the training
approach is the missing evidence for transfer effects, which is sometimes challenged by
the similarity between assessment and training tasks (Shipstead, Redick, & Engle, 2012).
This methodological problem can be circumvented with direct stimulation of brain
activation. Available research mostly used transcranial electrical stimulation (TES; Kuo &
Nitsche, 2012), which It involves either direct (tDCS) or alternating current (tACS). TDCS
manipulates neuronal activity via depolarization or hyperpolarization of cell membranes.
TACS influences cortical activity via EEG frequency-specific oscillatory current. tACS
leads to EEG-synchronization of neural activity in the respective frequency band, which
may facilitate efficient cortical communication patterns (Zaghi, Acar, Hultgren, Boggio, &
Fregni, 2010). Much research has focused on stimulation of the dorsolateral prefrontal
cortex (DLPFC). For tDCS, DLPFC stimulation was associated with positive effects on
cognitive processes such as language, attention, perception, executive functioning, and
memory processes (Jacobson, Koslowsky, & Lavidor, 2012; Utz, Dimova, Oppenländer, &
Kerkhoff, 2010). For tACS of the DLPFC, Santarnecchi, Polizzotto, Godone, Giovannelli,
Feurra et al. (2013) found that gamma stimulation leads to a shortening of (correct)
response latencies in a gf task. A growing number of studies examined left-parietal
stimulation effects on working memory and intelligence. Left-parietal tDCS was found to
enhance performance in a verbal memory task (Jacobson, Goren, Lavidor & Levy, 2012). For
tACS, Pahor and Jaušovec showed that left parietal theta tACS leads to an increase in gf
performance and accompanying changes in cortical activation (Pahor & Jaušovec, 2014). The
same stimulation setting also increased working memory capacity and a decreased P3
component latency, which could reflect a faster allocation of attention-related cognitive
resources (Jaušovec & Jaušovec, 2014).

<hs>  Aims of this study</hs>
  ~~~~~~~~~~~~~~~~~~

Previous findings showed that left parietal theta tACS leads to a transient increase in
fluid reasoning performance (Pahor & Jaušovec, 2014; Jaušovec & Jaušovec, 2014). In an
attempt to replicate and extend these findings, we combined theta tACS with fMRI in a
double-blind design. Available evidence indicates that left-parietal theta activity might
play a causal role for gf-related demands such as executive functioning (Sauseng,
Griesmayr, Freunberger, & Klimesch, 2010), working memory capacity (Postle et al., 2006).
Neurophysiological stimulation effects are studied by analyzing concurrent brain
activation changes with fMRI. Finally, we test the role of task difficulty as a moderating
variable in the relationship between brain stimulation and brain activation (Neubauer &
Fink, 2009). We expect that left parietal theta stimulation increases fluid intelligence
performance (Pahor & Jaušovec, 2014) and affects brain activation in intelligence-related
brain areas according to the P-FIT model (Jung & Haier, 2007). Additionally, the neural
efficiency hypothesis predicts that increased intelligence performance is associated with
reduced activation of brain areas that are not considered central for intelligence
(Basten, Stelzel, & Fiebach, 2013; Neubauer & Fink, 2009).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

25 individuals were recruited from a pre-tested pool of participants (Jauk, Benedek,
Dunst, & Neubauer, 2013). All participants were right-handed, had normal or corrected-to-
normal vision, and no self-reported history of CNS-affecting drugs, mental or neurological
diseases. Five participants were excluded due to excessive missing data or failure to
complete both test sessions. The final sample hence consisted of 20 participants (11
women; average age = 24.85; SD = 3.30). The sample was kept homogeneous with respect to
age (18–30 years), intelligence as measured with the intelligence-structure-battery
(INSBAT; for details see Dunst et al., 2014; M = 106.09; SD = 7.34), and educational level
(students) to enable a sensitive test of within-subject stimulation effects. Participants
did not report any medical treatments or health problems and gave written informed
consent. The study was approved by the local ethics committee.

<hs>  Design</hs>
  ~~~~~~

The study was a double-blind sham-controlled experiment. One experimenter only operated
the stimulation device and had no interaction with the participant, whereas another one
(who was blind to the stimulation condition) instructed participants. Verum (i.e., active)
and sham (i.e., placebo) stimulation conditions varied within subjects in a
counterbalanced fashion. The two sessions were separated by 28 days to control for
potential influences of different phases of the menstrual cycle (Amin et al., 2006).
Dependent variables were performance in the two gf tasks as well as BOLD responses in
fMRI.

<hs>  Tasks and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~

The experiment was carried out in two sessions. Participants received a standardized
instruction and then either sham or verum tACS was applied for 15 min (see below),
followed by a questionnaire about intensity and duration of stimulation induced
sensations. After the stimulation, the participants were led to the scanning room where
they performed two intelligence tasks. The matrices task was based on the Raven's
progressive matrices (RPM; Court & Raven, 1995), slightly modified to the requirements of
neurophysiological investigations (Pahor & Jaušovec, 2014). The test consisted of 50 items
– 18 easy (set B of the CPM, and APM items 1–3), and 32 difficult (APM items 4 to 35). The
50 test items were divided into two parallel forms each consisting of 25 items (10 easy
items; 15 difficult items) which were counterbalanced between the sham/verum conditions.
As in the original RPM, items were presented in a fixed sequence reflecting increasing
task difficulty. Each trial of the RPM started with a jittered fixation cross period (6–10
s). Then, the item was presented for 6 s (easy items) or 10 s (difficult items) together
with four response alternatives depicted below, followed by a 3 s response phase
(indicated by red interrogation marks presented under the figure). During this,
participants had to press one of four buttons corresponding to the four response options.
Total task duration of the RPM scanner task was about 9 min. This modified RPM has been
shown to correlate substantially with the WAIS-R (r = 0.56) (Jaušovec & Jaušovec, 2012),
suggesting that content validity is not impaired by the shorter item presentation time.
The cross-form consistency of the modified RPM had been proven in a larger sample (rA,B =
0.73; Pahor & Jaušovec, 2014). As a second intelligence measure, we used the paper folding
task (PFT) from the Stanford-Binet test (Cowan et al., 2011). Participants had to judge
which of the four presented figures on the right side corresponded to that one on the left
side after variable steps of folding and cutting (Jaušovec & Jaušovec, 2012). Again, we
used two parallel versions which consisted of 20 items each. Items were presented in a
fixed quasi-randomized sequence. For analyses considering task difficulty, these items
were divided in to 10 easy and 10 difficult items based on effective task performance.
Presentation parameters were the same as for the RPM except that the duration of stimulus
presentation was 7 s per item here, and fixation cross period varied randomly from 5 to 9
s. Total duration of the PFT was about 6 min. Again, cross-form consistency of the
modified PFT was established in a previous study (rA,B = 0.71, Pahor & Jaušovec, 2014). In
both tasks (RPM and PFT) a trial was scored as solved when the correct response
alternative was selected before timeout. The total duration of the experiment including
instruction, stimulation, and scanning was around 65 min.

<hs>  Electrical stimulation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

We used a battery-operated stimulator system (DC-stimulator plus, Neuroconn, Ilmenau,
Germany). The stimulating electrodes (5 × 7 cm) were attached to the scalp using a rubber
band placed over the electrode and attached under the chin. This procedure prevented
movement of the electrodes during the experiment. The electrodes were covered by saline
soaked sponges, which reduced the electrode impedance. Target electrode was placed over
the left parietal location (P3), and the return electrode was placed on Cz. This electrode
positioning was chosen because of the key role of the left parietal cortex for gf and gf-
related functions (e.g., working memory capacity; Jung & Haier, 2007; Cowan et al., 2011;
Chein & Fiez, 2010), and first evidence on effects of left parietal tACS on fluid
reasoning (Pahor & Jaušovec, 2014; Jaušovec & Jaušovec, 2014; Postle et al., 2006).
Stimulation waveform was sinusoidal without DC offset and a 0° relative phase. The
impedance level was kept below 10 kΩ throughout the entire stimulation period. The applied
oscillating currents corresponded to mean theta frequency in previous studies (Jacobson,
Goren, Lavidor, & Levy, 2012; 5 Hz); current intensity was 1500 μA. In verum condition,
tACS was applied for 15 min. The current was ramped up and down over the first and last 15
s of stimulation. In sham condition, the procedure and stimulation parameters were the
same as in the verum condition except for the duration of stimulation, which was applied
for only 60 s in the beginning and then turned off. Since participants feel stimulation
related sensations (e.g. itching) only in the beginning of tACS, this approach prevents
individual awareness of the stimulation conditions (Nitsche et al., 2008).

<hs>  MRI data acquisition</hs>
  ~~~~~~~~~~~~~~~~~~~~

Imaging was performed on a 3.0-T Tim Trio system (Siemens Medical Systems, Germany) using
a 32-channel head coil. BOLD-sensitive T2*-weighted functional images were acquired using
a single shot gradient-echo EPI pulse sequence (TR = 2400 ms, TE = 30 ms, flip angle =
90o, slice thickness = 3.5 mm, matrix size = 68 × 68, FOV = 240 mm, 35 slices per volume).
The first two volumes after each scanner pause were discarded to allow for T1
equilibration effects. Field maps were created from a double echo gradient-echo pulse
sequence (31 slices, TE1 = 4.92 ms, TE2 = 7.38 ms, TR = 400 ms, slice gap = 0.9 mm, slice
thickness = 3.5 mm, matrix size 68 × 68, FOV = 240 mm). Visual stimuli were presented onto
a screen using the Software Presentation (Neurobehavioral Systems, Albany, CA) and viewed
through a mirror attached to the head coil.

<hs>  MRI data analysis</hs>
  ~~~~~~~~~~~~~~~~~

Functional MRI data analysis was performed using SPM 8 software (Wellcome Department of
Imaging Neuroscience, London, UK). Preprocessing steps included field map correction,
motion correction, slice time acquisition correction, spatial normalization to an averaged
EPI template, and smoothing with a 7-mm full-width at half maximum Gaussian kernel. For
each task, scans from the verum and sham fMRI sessions were modeled together in a fixed-
effects model including the conditions REST (fixation epochs), VERUM, and SHAM (task
performance following verum or sham stimulation, from stimulus onset to onset of response
period). Motion parameters were included in the model as regressors of no interest. Task-
specific brain activation was modeled with a conjunction of both stimulation and sham
conditions (VERUM + SHAM > 0) against implicit baseline (Poline, Kherif, Pallier, & Penny,
2007). Stimulation-specific brain activation was modeled with the contrast of conditions
(VERUM vs. SHAM). For the examination of difficulty-specific effects another model was run
considering easy and difficult trials separately. At the second level, a random effects
analysis was performed computing one-sample t-tests for the subject-specific statistical
parametric maps obtained at the first level. Whole-brain results for task-specific effects
(VERUM + SHAM) are reported using a conservative criterion of voxel-wise p < 10− 8
(uncorrected) with cluster size of k ≥ 25. For the analysis of stimulation-specific
effects (VERUM vs. SHAM), clusters are only reported if they are significant on voxel
level (p < 0.0001, uncorrected) and exceed a minimum cluster size of 5 voxels. Finally, a
region of interest (ROI) analysis was computed to determine the direction (activation or
deactivation) and magnitude of changes in regions showing significant task-specific
activation patterns (VERUM + SHAM) using MarsBaR 0.43 (Brett, Anton, Valabregue, & Poline,
2002). The ROIs were functionally defined based on the task-specific activation patterns
(Poldrack, 2007).

<hs>  Behavioral results</hs>
  ~~~~~~~~~~~~~~~~~~

The self-reported stimulation-induced sensations during the tACS sessions did not differ
significantly between sham and verum tACS settings (Wilcoxon Z19 = − 0.53; ns.).
Stimulation effects on intelligence in the RPM task were analyzed with an ANOVA with the
within-subject conditions STIM (sham/verum) and DIFFICULTY (easy, difficult). The
interaction effect between STIM and DIFFICULTY was significant (F(1, 19) = 4.86, p < 0.05;
eta2part = 0.20). Post-hoc paired-sample t-tests showed that participants solved
significantly more difficult RPM items (28.44%, M (SD) = 9.10 (1.87)) when verum tACS was
applied than after sham stimulation (24.69%, M (SD) = 7.90 (2.53); t(19) = 2.40, p = 0.03,
d = 0.53), but there was no stimulation effect for easy items (45.83%, M (SD) = 8.25
(1.07), and 46.39%, M (SD) = 8.35 (0.88) for verum and sham stimulation, respectively;
t(19) = − 0.42, p = 0.68; Fig. 1). Supplemental Fig. S1 shows the individual data.
Performance increases following verum tACS were evident in nine of 20 individuals; seven
displayed no change, four displayed (slight) decreases. Interestingly, especially those
individuals with low baseline (sham) performance appear to have benefited from the
stimulation. The same GLM procedure was conducted for the PFT, but we observed no effects
related to the stimulation condition or task difficulty.

        <hss>Task-specific brain activation</hss>

        Task-specific brain activation in the RPM task included 13 clusters, with seven
        clusters showing relatively stronger activation and six clusters showing lower
        activation relative to baseline (Table S1). Task-specific activation was observed
        bilaterally in the insula, in the left superior/inferior parietal lobe, in the
        thalamus, the right lingual gyrus, and the postcentral gyrus. Task-specific brain
        activation in the PFT included 13 clusters with 8 clusters showing stronger
        activation and 5 clusters showing lower activation relative to implicit baseline
        (Table S2). Task-specific activation was observed in the middle and the left
        inferior occipital gyrus as well as in the left superior/inferior parietal lobe,
        the right insula, the right lingual gyrus, the right supramarginal gyrus, and in
        the right fusiform gyrus.

        <hss>Stimulation effects on brain activation</hss>

        In both tasks, brain stimulation induced no relative increases but only relative
        decreases in brain activation (see VERUM < SHAM). In the RPM task, verum
        stimulation was associated with lower activation in the left middle occipital
        gyrus as well as in right occipital and frontal lobes (Table 1). In the PFT task,
        lower activation was observed bilaterally in the precuneus, the left inferior
        temporal gyrus, and right regions of the cerebellum. In both tasks, stimulation-
        induced activation changes did not overlap with the task-positive brain regions
        but partly overlapped with the task-negative brain regions observed for these
        tasks. We further examined whether stimulation effects are different for easy and
        difficult items, as it was the case at the behavioral level in the RPM task. The
        observed activation differences were essentially the same when considering only
        difficult items, but no stimulation effects were observed for easy items.

        <hss>ROI analyses</hss>

        Finally, we examined the effect of stimulation on brain activity in terms of
        signal change in the seven clusters showing increased task-specific activation
        (Table S1), separately for trials classified as easy or difficult. Here we
        observed a tendency towards a difficulty-depended stimulation effect in the
        inferior parietal lobe verum stimulation tended to be associated with lower
        activation as compared to sham stimulation for difficult items (p = 0.09) but not
        for easy items (p = 0.71). No stimulation effects were observed in PFT task.

<h>DISCUSSION</h>
----------

We set out to examine the effects of left-parietal theta tACS on intelligence test
performance and its respective neurophysiological bases. We found that theta tACS can
enhance performance in a gf task (as measured by Raven's Progressive Matrices) for
difficult items; no stimulation effect was found for easy RPM items, or the PFT. The
stimulation effect was accompanied by distinct brain activation changes. Now, we will
discuss reasons and implications of these findings. This study replicates previous
research showing that left parietal theta tACS leads to increased task-specific reasoning
performance (Pahor & Jaušovec, 2014). It is also in line with findings that left parietal
theta tACS increased working memory capacity (Jaušovec & Jaušovec, 2014), as working
memory is a central executive function underlying fluid intelligence (Benedek, Jauk,
Sommer, Arendasy, & Neubauer, 2014). We presume that theta frequency reflects a general
cognitive control mechanism, which might be of general importance for gf performance
(Sauseng et al., 2010). Regarding the neurophysiological stimulation effects, left
parietal theta stimulation was accompanied by lower brain activation in the right frontal
lobe and bilaterally in the occipital lobe for the RPM, and in the precuneus, left
inferior temporal gyrus, and right cerebellum in the PFT task. The missing overlap of
stimulation-induced brain activation changes across tasks can be seen to corroborate the
task-specificity of the stimulation effects. Furthermore, independent of the stimulation
condition, there was little overlap in task-specific activation patterns (e.g. inferior
parietal lobule, insula; Table S1; Table S2), which supports the notion that each of the
tasks addresses distinct facets of intelligence performance. Notably, stimulation-induced
decreases in brain activation primarily concerned brain areas that were not part of task-
specific brain activation patterns (i.e., task-positive areas), but rather overlapped with
task-negative areas (e.g., precuneus). This finding parallels research on neural
efficiency: Studies have shown that higher intelligence is related to lower brain
activation, particularly in task-negative brain regions (Neubauer & Fink, 2009; Basten et
al., 2013). Our findings could thus be tentatively interpreted in terms of induced neural
efficiency by means of tACS. A closer look suggests that activation decreases might also
be related to task difficulty. Complemental analyses showed that stimulation-related
differences in brain activation were only apparent when individuals worked on difficult,
but not on easy items (mirroring the behavioral stimulation effects). The stronger
deactivation following stimulation during difficult tasks might indicate an efficient
downregulation of irrelevant cortical activity during phases of increased cognitive load.
Interestingly, we did not observe stimulation-dependent brain activation increases in
task-positive brain regions or parietal and frontal areas as predicted by the P-FIT (Jung
& Haier, 2007). In contrast, ROI analyses revealed a weak tendency towards a stimulation-
induced reduction of brain activation in the left inferior parietal cortex. While the left
inferior parietal cortex is part of the task-positive network, it was also the stimulation
location. Hence, theta stimulation may not necessarily translate to increased brain
activation, but may even induce slight relative deactivation; at least at the stimulation
site. However, these stimulation-specific effects did not survive FWE-correction, why they
should be seen as first exploratory evidence for a potential impact of theta-tACS on the
hemodynamic function measured through fMRI. Our findings add to evidence reported by
Jaušovec and Jaušovec (2014), who observed a decreased P3 latency and increased theta
power at left parietal brain regions after theta tACS was applied on the left parietal
cortex (cf., Beauchamp & Stelmack, 2006). Moreover, Pahor and Jaušovec (2014) showed that
parietal theta tACS was associated with a frontal theta power increase. How can these
previous EEG findings be reconciled with the fMRI evidence? Scheeringa et al. (2009)
showed that, during performance of a working memory task, increases in frontal theta power
were correlated with BOLD decreases in regions that together form the default mode
network. Thus, our finding of a deactivation of brain regions that are not considered
essential for gf performance is generally consistent with the observed frontal theta power
increase in a previous study (Pahor & Jaušovec, 2014), and it seems that higher theta
power goes along with lower BOLD in independent brain regions. Altogether, our study
suggests that the main mechanism underlying theta tACS-stimulation effects can be seen in
brain activation decreases of task-irrelevant brain regions rather than increases in task-
relevant regions, which is in line with the neural efficiency hypothesis. This finding is
potentially consistent with the notion that intelligence is not associated with faster
neural transmission at task-relevant regions (Stelmack et al., 2003). It should be
acknowledged, however, that the current findings can only be interpreted in terms of a
transient increase in the performance on a specific fluid intelligence task, which can be
seen as an enhancement of a subfactor (namely fluid reasoning) rather than a general
“intelligence boost”. Note also that stimulation effects were restricted to task
performance on Raven items of higher difficulty. This includes the behavioral and brain
activation effects and is consistent with a previous study (Pahor & Jaušovec, 2014). But
why are findings specifically observed for difficult but not for easy Raven items? Easy
items had item difficulties ranging between 0.76 and 1 indicating that they were solved by
most of the participants. Hence, easy items may have less discriminatory power than more
difficult items to discern between differences in reasoning performance. Also,
complemental single-subject analyses showed that individuals with low baseline performance
benefit the most from tACS, which has direct implications for the differential use of tACS
and will hopefully stimulate future research. Finally, stimulation effects were specific
to the matrices task in this study. A possible explanation could be that the RPM and the
PFT focus on different facets of intelligence. Although the PFT is commonly considered a
fluid intelligence task (e.g., Nusbaum & Silvia, 2011), it can also be seen to have a
strong visual-spatial focus. Recent research showed that visual-spatial abilities are
predominantly represented via right-hemispheric activation (Zacks, 2008), whereas fluid
reasoning is mainly represented through left-hemispheric (Barbey et al., 2012) or
bilateral activation patterns (Gray, Chabris, & Braver, 2003). A left parietal stimulation
hence could have more effect on cognitive processes that are generally left-lateralized.
Also, the participants performed the matrices task first, so it is possible that the power
of the stimulation effect had already decreased when participants worked on the PFT. In
conclusion, this study was the first to explore the neurophysiological basis of fluid
intelligence via the combination of tACS and fMRI. Left parietal theta tACS was found to
moderately increase performance in a fluid reasoning task when working on difficult items,
and this was accompanied by deactivation of task-irrelevant brain regions. For future
research, it would be exciting to study tACS effects on additional direct indices of brain
functioning like neural transmission time (e.g., Stelmack et al., 2003).

<h>SOURCE OF FUNDING</h>
-----------------

This research was funded by a grant from the Austrian Science Fund (FWF): P23914.


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<ART>The interaction between school poverty and agreeableness in predicting educational attainment
================================================================================

Authors: Jaap Nieuwenhuis
DOI: 10.1016/j.paid.2018.02.002
Year: 2018  |  Pages: 85-88
ASJC codes: 3200
Keywords: ALSPAC, Adolescence, Agreeableness, Educational attainment, Person-environment interaction, School poverty

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study examined the relation between school poverty and educational attainment of adolescents, and tested whether personality trait agreeableness moderated this link. The sample consisted of 4236 adolescents, whose math abilities were assessed twice, at ages around 13/14 and 15/16. Agreeableness was assessed at age 13. School poverty was measured as the proportion of children eligible for free school meals in the school. The results showed a negative relation between school poverty and educational attainment, however, this negative relation was weaker for adolescents with higher levels of agreeableness. Specifically, in low poverty schools, agreeableness did not predict differences in educational attainment. The results were in line with the diathesis-stress model. This suggests that higher levels of agreeableness can contribute to resilience and better coping with contextual stressors in the school environment.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Many studies have linked contextual poverty in general and school poverty specifically to
educational outcomes of individuals (Lacour & Tissington, 2011; Nieuwenhuis & Hooimeijer,
2016; Nieuwenhuis, Hooimeijer, van Dorsselaer, & Vollebergh, 2013; Portes & MacLeod,
1996). School poverty is negatively related to parental education. Therefore, the social
networks within low SES schools consist of lower educated parents, and through these
networks, less social capital is available, such as information about after-school
programs. Furthermore, parents may not value or understand the benefits of formal
education, resulting in students who are less prepared for education (Lacour & Tissington,
2011). Finally, higher poverty schools were found to have less qualified teachers on staff
(Peske & Haycock, 2006). This suggests that low SES schools have fewer positive role
models showing the benefits and transferring the importance of education. Because positive
socialisation mechanisms are not in place in low SES schools, children may become less
inclined to perform well. However, educational attainment is not uniform for all children
in the same school, some perform better than others. This variation may be induced by
differences in resilience, as described by the diathesis-stress model. Low SES schools can
be experienced as stressful environments, however, some are better able to cope with
environmental stressors than others (Magnusson & Stattin, 2006). Personality traits have
been shown to be related to better coping with stressful environments (O'Brien & DeLongis,
1996), such as school poverty. In this case, resilient adolescents are expected to be
affected less by school poverty than non-resilient adolescents. In high SES schools they
are expected not to differ. Alternatively, the differential susceptibility model predicts
that adolescents who are more malleable are more likely to be negatively affected by
stressful environments than less malleable adolescents, but also more likely to be
positively affected by positive environments (Belsky & Pluess, 2009). In this case, less
malleable adolescents are expected not to be affected by the level of school poverty,
while malleable adolescents are expected to have better educational outcomes in high SES
schools and worse outcomes in low SES schools. Specifically, I have examined the
moderating role of agreeableness, a personality trait that is related to being forgiving,
patient, warm, considerate, and sympathetic (Goldberg, 1992). Agreeableness has been
linked to lower levels of criminal behaviour and higher levels of community involvement
(Ozer & Benet-Martinez, 2006; Roberts, Kuncel, Shiner, Caspi, & Goldberg, 2007). This
suggests that adolescents with higher levels of agreeableness are less inclined to
interact with deviant peers, and more likely to be involved in positive institutions at
school, such as clubs or committees. Adolescents with lower levels of agreeableness are
more inclined to participate in antisocial behaviour, which may be amplified in a
stressful school environment. When adolescents do not function as expected in school, and
the school does not foster their positive development, they may focus their attention
towards other activities or deviant peer groups, where status attainment is reached
through violent behaviour and anti-school attitudes (Ellis et al., 2012; Willis, 1977).
For this follows that agreeableness could contribute to adolescents' resilience or
malleability in the school environment. Both the diathesis-stress and differential
susceptibility models lead to the following hypothesis: The relation between school
poverty and educational achievement is moderated by agreeableness such that this
relationship will be weaker for adolescents with higher levels of agreeableness (H1). Both
models predict that in high poverty schools, adolescents with low agreeableness do worse,
however, in low poverty schools they lead to two competing hypotheses. From diathesis-
stress follows: In low poverty schools, adolescents with high levels of agreeableness do
not differ from adolescents with low levels of agreeableness in their educational
attainment (H2a). From differential susceptibility follows: In low poverty schools,
adolescents with high levels of agreeableness have lower educational attainment than
adolescents with low levels of agreeableness (H2b).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 4236 adolescents (52% females) from the Avon Longitudinal Study of
Parents and Children (ALSPAC; initial recruitment: 14,541 pregnant women with expected
delivery dates between 1991/04/01–1992/12/31; total sample: 15,458 fetuses, of which
14,701 were alive at age 1; Boyd et al., 2013). Adolescents' math abilities were assessed
twice, at ages around 13/14 and 15/16, resulting in 6813 observations. Students were
nested in 336 schools, mostly in the south-west of England. Please note that the study
website contains details of all the data that is available through a fully searchable data
dictionary (http://www.bris.ac.uk/alspac/researchers/data-access/data-dictionary/).

        <hss>Educational attainment</hss>

        Math scores on the standardised tests Key Stage 3 (age 13/14) and Key Stage 4 (age
        15/16) were obtained from the National Pupil Database. The scales of the two
        scores were different, and were transformed for comparability using the proportion
        of maximum scaling (POMS; Little, 2013). This transformation retains the rank-
        order of individuals, while avoiding measuring mean-level changes. The formula
        used was POMS = (observed − minimum) / (maximum − minimum) (Moeller, 2015). For
        descriptive statistics and correlations of all variables, see Tables 1 and 2,
        respectively.

        <hss>Agreeableness</hss>

        Using the International Personality Item Pool (Goldberg, 1992), the Big Five
        personality trait agreeableness was assessed at 13 years and 6 months. Adolescents
        were presented with 10 statements, and where asked how well these statements
        described them on a 5-point answering scale. Cronbach's alpha: 0.72. Agreeableness
        was centred.

        <hss>School poverty</hss>

        The proportion of children in the school who were eligible for free school meals
        was used as a proxy for school poverty. This is a heavily studied measure of
        school poverty, and considered a good indicator (Gorard, 2012). The measure was
        assessed for both the schools adolescents attended at the two Key Stages. These
        data were obtained from the Annual School Census. The measure was standardised
        with 0 as mean and standard deviation 1 to make the interaction term easier to
        interpret. Control variables. First, sex was measured as female (1) and male (0).
        Second, parental education was measured as the average of the highest attained
        education of both parents. Education consisted of five categories: 0) (General)
        Certificate of Secondary Education ([G]CSE) levels D, E, F, or G; 1) vocational;
        2) Ordinary Level (O Level) or GCSE levels A, B, or C; 3) Advanced Level (A
        Level); and 4) university degree. Third, race was measured as non-white (1) and
        white (0). Fourth, mother's age at delivery was measured as mother's age in years
        at the birth of the respondent (ranging from 16 to 44).

<hs>  Analyses</hs>
  ~~~~~~~~

To test the hypotheses, I used multilevel random-effects regression models, with time
nested in individuals, nested in schools adolescents attended at the time of Key Stage 3.
I created an interaction term composed of the cross-product of school poverty and
agreeableness to test for moderation. The quadratic terms of school poverty and
agreeableness were included to correct for the non-normality of the response variables.
This corrects for spurious interaction effects (Lubinski & Humphreys, 1990). To control
for changes in school environment, I ran a sensitivity analysis, restricting the sample to
adolescents that did not change schools between Key Stage 3 and 4. This resulted in a
reduced sample of 4020 (from 4236), indicating that most adolescents stayed in the same
school. The results of the sensitivity analysis were the same, suggesting that changes in
school environment did not play a role.

<h>RESULTS</h>
-------

Adolescents attended schools with different levels of poverty: the first quartile of the
sample went to schools that ranged from 0% to 4.2% of children eligible for free school
meals; the second quartile ranged from 4.2% to 6.5%; the third from 6.5% to 13.3%; and the
fourth from 13.3% to 100% school meal eligibility. When examining Model 1 (Table 2),
school poverty is indeed negatively related to educational attainment. Higher levels of
agreeableness were related to higher educational attainment. The control variables show
that parental education was positively related with adolescents' attainment. Model 2
(Table 3) shows a positive interaction between school poverty and agreeableness. The
interaction significantly improved the model fit. As predicted, higher levels of
agreeableness were related to a weaker relation between school poverty and educational
attainment. The interaction plot shows the same result (Fig 1): adolescent with low levels
of agreeableness had a steeper slope for the relation between school poverty and
educational attainment (b = −0.069; p = 0.000) than adolescents with high levels of
agreeableness (b = −0.017; p = 0.019). Calculating the region of significance (with alpha
= 0.05; Preacher, Curran, & Bauer, 2006) showed that agreeableness did not relate to
educational attainment in schools with a standardised proportion of children eligible for
school meals lower than 2.1452 (where proportion of children eligible for school meals
ranged from −1.13 to 9.31).

<h>DISCUSSION</h>
----------

This study showed that higher levels of school poverty were related to lower educational
attainment. It is possible that the lack of positive role models and presence of peers
from low-educated families results in a bad learning environment, where educational
attainment is not valued and stimulated. Next, the relation between school poverty and
educational attainment was buffered by personality trait agreeableness, which is in
support of hypothesis 1 (H1). This finding is in line with other studies examining the
moderating role of personality for other contextual effects on educational attainment
(Nieuwenhuis, Hooimeijer, & Meeus, 2015; Nieuwenhuis, Hooimeijer, van Ham, & Meeus, 2017).
Next, the diathesis-stress model predicted that adolescents in low poverty schools would
not have different educational attainment based on their level of agreeableness (H2a),
while the differential susceptibility model predicted adolescents with low agreeableness
to be more malleable, and therefore do better in low poverty schools than adolescents with
high agreeableness (H2b). The results showed that adolescents with different levels of
agreeableness did not have different educational attainment in low poverty schools, which
is in line with the diathesis-stress model (H2a). The findings suggest that higher levels
of agreeableness contribute to resilience when faced with environmental stressors, such as
school poverty. Lower levels of agreeableness contribute to more vulnerability under the
same circumstances. It is possible that children from lower educated families end up in
schools with lower SES, which could indicate that lower SES schools contain lower
attaining adolescents because they sort into these schools based on their socio-economic
background. By controlling for parental education, I tried to (partly) overcome this
problem. Also, restricting the sample to adolescents who did not move schools between the
two measurement points yielded the same results. If the relation between school and
attainment would have disappeared, this could suggest that scoring low on Key Stage 3
would have resulted in a move to a worse (lower SES) school, which would then have driven
the effect of school poverty for the full sample. This was not the case, which indicates
that sorting did not play a major role. The results emphasise the importance of
considering individual characteristics such as personality traits when assessing
contextual predictors. School effects are not uniform, and have to be studied in tandem
with the diversity of children who inhabit the school. This study could be used to
identify adolescents who are particularly vulnerable to detrimental effects of school
poverty.


<h>REFERENCES</h>
----------

  [1] Jay Belsky, Michael Pluess. Beyond Diathesis Stress: Differential Susceptibility to Environmental Influences. doi:10.1037/a0017376
  [2] Andy Boyd, Jean Golding, John Macleod, Debbie A. Lawlor, Abigail Fraser, John Henderson, Lynn Molloy, Andy Ness, Susan Ring, George Davey Smith. Cohort profile: The 'Children of the 90s'-The index offspring of the avon longitudinal study of parents and children. doi:10.1093/ije/dys064
  [3] Bruce J. Ellis, Marco Del Giudice, Thomas J. Dishion, Aurelio José Figueredo, Peter Gray, Vladas Griskevicius, Patricia H. Hawley, W. Jake Jacobs, Jeneé James, Anthony A. Volk, David Sloan Wilson. The evolutionary basis of risky adolescent behavior: Implications for science, policy, and practice. doi:10.1037/a0026220
  [4] Lewis R. Goldberg. The Development of Markers for the Big-Five Factor Structure. doi:10.1037/1040-3590.4.1.26
  [5] Stephen Gorard. Who is eligible for free school meals? Characterising free school meals as a measure of disadvantage in England. doi:10.1080/01411926.2011.608118
  [6] Misty Lacour, Laura D. Tissington. The effects of poverty on academic achievement
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  [11] Jaap Nieuwenhuis, Pieter Hooimeijer. The association between neighbourhoods and educational achievement, a systematic review and meta-analysis. doi:10.1007/s10901-015-9460-7
  [12] Jaap Nieuwenhuis, Pieter Hooimeijer, Wim Meeus. Neighbourhood effects on educational attainment of adolescents, buffered by personality and educational commitment. doi:10.1016/j.ssresearch.2014.11.011
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  [14] Jaap Nieuwenhuis, Pieter Hooimeijer, Maarten van Ham, Wim Meeus. Neighbourhood immigrant concentration effects on migrant and native youth’s educational commitments, an enquiry into personality differences. doi:10.1177/0042098016640693
  [15] Tess Byrd O'Brien, Anita DeLongis. The Interactional Context of Problem-, Emotion-, and Relationship-Focused Coping: The Role of the Big Five Personality Factors. doi:10.1111/j.1467-6494.1996.tb00944.x
  [18] Alejandro Portes, Dag MacLeod. Educational progress of children of immigrants: The roles of class, ethnicity, and school context. doi:10.2307/2112714
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<ART>The light-from-above prior is intact in autistic children
=========================================================

Authors: Abigail Croydon, Themelis Karaminis, Louise Neil, David Burr, Elizabeth Pellicano
DOI: 10.1016/j.jecp.2017.04.005
Year: 2017  |  Pages: 113-125
ASJC codes: 3204, 3205
Keywords: Autism, Bayesian priors, Bias, Development, Light-from-above, Perception

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Sensory information is inherently ambiguous. The brain disambiguates this information by anticipating or predicting the sensory environment based on prior knowledge. Pellicano and Burr (2012) proposed that this process may be atypical in autism and that internal assumptions, or “priors,” may be underweighted or less used than in typical individuals. A robust internal assumption used by adults is the “light-from-above” prior, a bias to interpret ambiguous shading patterns as if formed by a light source located above (and slightly to the left) of the scene. We investigated whether autistic children (n = 18) use this prior to the same degree as typical children of similar age and intellectual ability (n = 18). Children were asked to judge the shape (concave or convex) of a shaded hexagon stimulus presented in 24 rotations. We estimated the relation between the proportion of convex judgments and stimulus orientation for each child and calculated the light source location most consistent with those judgments. Children behaved similarly to adults in this task, preferring to assume that the light source was from above left, when other interpretations were compatible with the shading evidence. Autistic and typical children used prior assumptions to the same extent to make sense of shading patterns. Future research should examine whether this prior is as adaptable (i.e., modifiable with training) in autistic children as it is in typical adults.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In human vision, the complex dimensions of a visual scene—the shapes of objects, their
spatial arrangement, and their material properties—are reduced to flat patterns of
excitation of the cones and rods of the retina. Information entering the brain is
inherently ambiguous, compatible with a range of interpretations. Visual input, therefore,
is “underspecified” for the task of providing the reliable and stable awareness of the
environment that we experience. Consequently, perception has long been considered as a
process of “unconscious inference” (Helmholtz, 1866/1911), in which existing knowledge is
spontaneously and automatically deployed to interpret the meaning of sensory signals.
Expectations based on experience of how the material environment works—for example, of
faces being convex or of light sources being overhead—feed into the construction of a
percept by the brain. The framework provided by Helmholz (1866/1911) was extended to
characterize perceptual inferences as “hypotheses” or informed speculations using noisy
and limited data (Gregory, 1980). Perceptual decisions are made possible by comparing the
probability of the sensory evidence and prior experience. The Bayesian framework has since
supplied an established mathematical model for perceptual decision making under conditions
of uncertainty. In Bayesian terms, if both sensory signals and knowledge-based hypotheses
are represented as probability distributions, techniques of statistical inference can be
used to locate the combined point of maximal probability, the “best guess” interpretation
(Knill, Kersten, & Yuille, 1996). In Bayesian perceptual inference, the prior probability
distribution, or “prior,” represents a “baseline” understanding of the likelihood of
particular environmental conditions on the basis of past experience (Gregory, 1980). A
number of visual priors have been established and are thought to improve overall
perceptual efficiency by weighting perceptual hypotheses in a broadly reliable way. For
example, a prior for convexity reflects the predominance of convex, over concave, objects
in the world (Langer & Bülthoff, 2001; Sun & Perona, 1996). The statistical inference
calculation implies a trade-off between the image data and the prior probability, such
that perception will be more prior driven when ambiguity in the sensory input is high. In
some circumstances, prior-driven expectations will be misguided, resulting in visual
illusions. For example, perceiving a hollow mask as a convex mask implies the operation of
overriding expectations of convexity in faces. Hence, when problems of object perception
are resolved on a probabilistic basis, the optimal solution may still be “inaccurate”
(Kersten & Yuille, 2003). Importantly, in the context of this research, Bayesian priors
envisage dynamic connections among perceptual inference, experience of the environment,
and behavior (Lee, Yang, Romero, & Mumford, 2002). Atypicalities in sensation and
perception are highly characteristic of autism (Baranek, David, Poe, Stone, & Watson,
2006; Leekam, Nieto, Libby, Wing, & Gould, 2007; Mottron, Dawson, Soulieres, Hubert, &
Burack, 2006; Simmons et al., 2009). Although difficulties in social communication are
considered hallmarks of autism, sensory reactivity, including hypersensitivity (e.g., to
light or touch) and hyposensitivity (e.g., to pain), was noted during the first
description of autism (Kanner, 1943). Sensory reactivity has since been shown to be
present in the majority of autistic children and adults (Ben-Sasson et al., 2009; Leekam
et al., 2007; Simmons et al., 2009), to be pervasive and persistent across development
(Crane, Goddard, & Pring, 2009; McCormick, Hepburn, Young, & Rogers, 2016), and to have a
substantial impact on the lives of autistic people (e.g., Dickie, Baranek, Schultz,
Watson, & McComish, 2009; Grandin, 2009; Williams, 1994). In the perceptual domain, the
majority of scientific studies have reported atypical processing in aspects of visual
perception and visual attention ranging from characteristically nonsocial stimuli and
tasks, such as discrimination of chromatic stimuli (e.g., Franklin et al., 2010), cast
shadow (Becchio, Mari, & Castiello, 2010), static gratings (e.g., Bertone, Mottron,
Jelenic, & Faubert, 2005), moving dots (e.g., Milne et al., 2002; Pellicano, Gibson,
Maybery, Durkin, & Badcock, 2005), and complex objects (e.g., “Greebles”) (e.g., Behrmann,
Thomas, & Humphreys, 2006; Davies, Bishop, Manstead, & Tantam, 1994), to social stimuli,
including faces (e.g., Dalton et al., 2005; Kemner & van Engeland, 2006), eye gaze (e.g.,
Elsabbagh et al., 2009), and biological motion (e.g., Blake, Turner, Smoski, Pozdol, &
Stone, 2003; Klin, Lin, Gorrindo, Ramsay, & Jones, 2009; for a review, see Simmons et al.,
2009). Theories of autistic perception have explained these findings in terms of a
“detail-focused” perceptual style (Frith & Happé, 1994), generally enhanced perceptual
functioning (Mottron et al., 2006), or reduced generalization (Plaisted, 2001). Building
on these accounts, Pellicano and Burr (2012) suggested that it is not sensory processing
itself that is atypical in autism but rather the interpretation of the sensory input.
Specifically, drawing on the tools of Bayesian theory, they proposed that the internal
priors of autistic people are underweighted or less used than in typical individuals.
Attenuated priors might result in enhanced perception in some contexts and reduced
performance in others, depending on whether the task draws more heavily on sensory input
itself or on successful perceptual prediction using prior knowledge. This idea was
expanded by several related Bayesian and neurobiological accounts that proposed possible
atypicalities in predictive processing in autism (Brock, 2012; Friston, Lawson, & Frith,
2013; Lawson, Rees, & Friston, 2014; Sinha et al., 2014; van Boxtel & Lu, 2013; Van de
Cruys et al., 2014). Evidence supporting the hypothesis of attenuated priors in autism
comes from studies showing that autistic children and adults show reduced adaptation, a
form of experience-dependent plasticity in which neural systems fine-tune to the current
visual environment according to the previous context. There is now considerable evidence
for reduced adaptation in autism for high-level visual attributes, both social stimuli
(e.g., faces: Pellicano, Jeffery, Burr, & Rhodes, 2007; biological motion: van Boxtel,
Dapretto, & Lu, 2016) and nonsocial stimuli (e.g., numerosity: Turi et al., 2015), as well
as for other sensory modalities (e.g., touch: Tommerdahl, Tannan, Holden, & Baranek, 2008;
audition: Lawson, Aylward, White, & Rees, 2015); audiovisual calibration: Turi, Karaminis,
Pellicano, & Burr, 2016). More recently, Karaminis et al. (2016) demonstrated
atypicalities in prior knowledge in autism more formally, in the context of temporal
reproduction, using a Bayesian computational model for central tendency (Cicchini,
Arrighi, Cecchetti, & Burr, 2012). The computational model proposed that central tendency
reflects the integration of noisy temporal estimates with prior knowledge representations
of a mean stimulus. This integration serves to reduce overall error and, crucially, is
flexible; the noisier the sensory estimates, the greater the reliance on prior knowledge.
Karaminis and colleagues contrasted the performance of autistic and typical children
completing a time interval reproduction task (measuring central tendency) and a temporal
discrimination task (assessing temporal resolution) to the predictions of the Bayesian
model. Computational simulations suggested that central tendency in autistic children was
much less than that predicted by computational modeling given the poor temporal resolution
of these children. Autistic children presented with a much less flexible use of priors
across development compared with typically developing children. In the current study, we
provided another test of the account of Pellicano and Burr (2012) using a well-established
perceptual expectation, namely the “light-from-above” prior. The patterns of light and
shade on and around an object provide uncertain cues for the brain to determine its shape
and position in space. To resolve this ambiguity, the visual system must assume a light
source location (Adams, 2007; Gerardin, de Montalembert, & Mamassian, 2007; Mamassian &
Landy, 2001). The light-from-above prior weights inference toward assuming that a light
source is located above the scene observed, as is most commonly experienced. The presence
of a light-from-above prior is demonstrated when an image lit from above is rotated by
180°, so that shading previously perceived as indicating convexity will indicate concavity
(and vice versa). Simple rotation changes interpretation (e.g., Mamassian & Goutcher,
2001). A perceptual bias toward light from above is also demonstrated in visual search;
observers can identify shapes compatible with light from above significantly faster than
the same shapes reversed (i.e., compatible with light from below), whereas shapes
suggesting a light source from the side are recognized both more slowly and less
accurately (Kleffner & Ramachandran, 1992). A further characteristic of the light-from-
above prior is that it is biased slightly to the left of vertical (Gerardin et al., 2007;
Mamassian & Goutcher, 2001; Sun & Perona, 1996; Thomas, Nardini, & Mareschal, 2010),
although there is considerable individual variation in the location of the prior (e.g.,
Adams, 2007; Champion & Adams, 2007; Mazzilli & Schofield, 2013; Morgenstern, Murray, &
Harris, 2011). While the preference for an overhead light source is assumed to have an
environmental origin, the source of the leftward bias is not well understood (see
Mamassian & Goutcher, 2001, for a discussion). The light-from-above prior strongly
influences depth perception and assists in reconstructing three dimensions
(objects/scenes) from two-dimensional retinal images. Here, we examined the use of this
robust and well-characterized light-from-above prior in autistic children. We also
investigated age-related differences in the use of the prior in autistic and typical
children. To address these aims, we assessed autistic and typical children of similar age
and ability on a shape judgment task designed to reveal individual differences in implicit
judgments of light source location. Specifically, we adapted the seven-hexagon stimulus
developed by Andrews, Aisenberg, d’Avossa, and Sapir (2012), which was used to demonstrate
an effect of cultural differences (reading direction) on location of the prior and,
therefore, was thought to be sufficiently sensitive to potential group-level variations.
Limited shading information in the stimulus delivered a high level of ambiguity about
depth, ensuring that perceptual inference was required to resolve shape and a light source
location would need to be assumed. We sought to investigate whether autistic children
would resolve the ambiguous shape-from-shading information in our stimulus using an
assumption of light from above. Specifically, we tested whether autistic children would
show the bias in stable conditions designed to encourage reliance on prior experience of
lighting conditions. An attenuated light-from-above prior, in line with the hypothesis of
Pellicano and Burr (2012), might result in more mixed shape judgments according to
rotation of the stimulus by autistic children than by typical children, with fewer
compatible with light from above. Because priors are thought to smooth over neural noise,
attenuated priors in the autistic group might also lead to less stable perception of
convexity or concavity, leading to more varied (or less confident) interpretations. Our
test purposefully excluded signals that might compete with the light-from-above prior,
such as a visible light source (Morgenstern et al., 2011), to determine whether the prior
is fundamentally intact and develops similarly in autistic children compared with typical
children.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

In total, 18 autistic children (16 boys) and 18 typical children (12 boys), all between 7
and 14 years of age, took part in this study. Children were recruited via community
contacts. All autistic children had been previously diagnosed with an autism spectrum
condition by independent clinicians and scored above the threshold for an autism spectrum
disorder on either the Autism Diagnostic Observation Schedule–Second Edition (ADOS-2) or
the Lifetime version of the Social Communication Questionnaire (SCQ) (see Table 1 for
scores). All typically developing children scored below the cutoff for autism on the SCQ
(score of 15; Rutter, Bailey, & Lord, 2003), reflecting the absence of clinically
significant autistic features. All children had normal or corrected-to-normal visual
acuity, as reported by their parents. The groups were matched in terms of age, t(34) =
0.06, p = .95, verbal IQ, t(34) = 0.94, p = .35, performance IQ, t(34) = 0.88, p = .39,
and full-scale IQ, t(34) = 0.38, p = .70, as measured by the Wechsler Abbreviated Scales
of Intelligence–Second Edition (WASI-2; Wechsler, 2011) (see Table 1 for scores). All
children obtained full-scale IQ scores of 70 or above and, thus, were considered to be
cognitively able. An additional 15 typical adults (14 female; 20–35 years of age),
recruited from the university, were tested to establish parameters for adult performance
in our task. One additional adult was tested but excluded from the analysis because the
estimated light source direction (see “Measurements” section below) lay more than 2
standard deviations to the left of the group average. Removing this outlier did not change
the results reported here.

<hs>  Ethics statement</hs>
  ~~~~~~~~~~~~~~~~

The study was conducted in accordance with the principles laid out in the Declaration of
Helsinki. Ethical approval was granted by the faculty research ethics committee of the
university (FPS456). Parents of all children gave their informed written consent prior to
the participation of their children in the project, and children gave their verbal assent.

<hs>  Stimuli</hs>
  ~~~~~~~

Following Andrews et al. (2012), the stimulus comprised seven tessellated gray-scale
hexagons on a gray-scale background (RGB = 127, 127, 127), with shading on the inner and
outer edges of the shapes (see Fig. 1) providing ambiguous cues to depth. Each shape was
2.5° of visual angle, with an intermediate level of blur. The stimulus was rotated by 360°
in 15° increments, compatible with different light source locations. We presented 24
rotations in a randomized order in order to estimate the light source direction most
consistent with the judgments of convexity and concavity by children. Each rotation was
presented five times, yielding a total of 120 trials. Stimuli were presented on a Dell
Precision laptop screen with 1366 × 768 pixel resolution at a refresh rate of 60 Hz and
mean luminance of 60 cd/m2. All children viewed the stimuli binocularly at a distance of
approximately 57 cm from the screen.

<hs>  Procedure</hs>
  ~~~~~~~~~

The experiment was written in Matlab using the Psychophysics Toolbox extensions (Brainard,
1997; Kleiner, Brainard, & Pelli, 2007). We measured the implicit judgments of light
source location made by children in the context of a child-friendly computer game. During
the introduction phase, the cover story was introduced showing colored cartoon honeycomb
cells and an animated bee. Children were asked to help the bee decide which “cells” needed
to be filled with honey (Fig. 2A and B). Children were told that they would collect points
for their decisions and win a small gift with more than 500 points. Dummy points were also
provided to maintain children’s interest. To encourage children to distinguish between
cells they perceived as empty and those they saw as full, they were also asked not to
“waste” honey when cells were “full.” We also showed the bee with a telescope looking at
the central hexagon (Fig. 2C) to ensure that answers were given for this cell only. After
the introduction to the story, children were taken through the demonstration phase. The
cartoon honeycomb was replaced with the hexagon stimulus, which appeared at a rotation of
150° so that the central cell would be most likely to be perceived as concave, according
to the known mean prior for adults (Fig. 2D). Children were told that this needed filling
with honey, which was demonstrated by the bee in an animation. Two demonstration trials
followed, using the exact procedure followed in later test trials. The stimulus appeared
with the prompt, “Does this one need filling?” Color-coded “yes” and “no” prompts appeared
below the question to the left and right of the screen, respectively, in order to match
the location of the response keys (letters “a” and “l” on the keyboard). These keys were
also labeled “Y” and “N” using sticky labels matched in color to the font of the on-screen
response options (yellow for yes and blue for no). Children were asked to press a key to
indicate their response, with left (yes) indicating perceived concavity and right (no)
indicating perceived convexity. The first demonstration trial again showed the rotation
most likely to be perceived as concave, and children were invited to respond. A “yes”
response was required to proceed. The second demonstration trial showed the stimulus
rotated 330°, the position most likely to be perceived as convex. This required a “no”
response and was followed by the caption “No! That one’s full!” Children could repeat the
demonstration trials if required, but there were no such further trials in order to avoid
influencing subsequent responses (Stone, Kerrigan, & Porrill, 2009). All children produced
correct responses for both trials. The test phase commenced immediately following the
demonstration phase. An animated bee hovered on the screen (2 s) as a fixation point.
Children saw the honeycomb stimulus in one of the 24 rotations, the order of which was
randomized. They answered the question “Does this one need filling?” by pressing the “yes”
or “no” key according to their interpretation of the stimulus shape. Trials were self-
paced, so that each response triggered the next fixation bee. Children completed three
blocks of 40 test trials, yielding a total of 120 trials. Dummy scores and general
encouragement were provided at the end of each block.

<hs>  General procedure</hs>
  ~~~~~~~~~~~~~~~~~

Children were tested individually in a quiet room at the university. The room was lit only
by the computer screen, so that no environmental cues were available to influence
children’s perceptions of lighting direction (Morgenstern et al., 2011). Testing on the
experimental task lasted 10–15 min. The WASI-2 (and the ADOS-2 for autistic children) was
administered to children in later sessions.

<h>RESULTS</h>
-------

Fig. 3 shows example results from one autistic and one typical child participant. The
plots show two-dimensional psychometric functions on polar axes, plotting percentage
convex as a function of rendered orientation. In both cases, the judgment tends to be
convex for orientations left of vertical and concave for orientations to the right; this
is consistent with a light-from-above interpretation, specifically with a light-from-above
left interpretation, in line with previous research (Gerardin et al., 2007; Sun & Perona,
1996; Thomas et al., 2010). The average orientation [estimated from Eq. (3)] is indicated
by the orange circle: −32° for the autistic child and −17° for the typical child. Fig. 4
shows group averages for the estimated light source direction biases for the three
participant groups. As expected (cf. Gerardin et al., 2007; Sun & Perona, 1996; Thomas et
al., 2010), average light source biases were to the left of vertical (autistic children: M
= −12.67°, SD = 12.51; typical children: M = −12.50°, SD = 7.87; adults: M = −12.06°, SD =
16.72) and were significantly lower than zero for all groups [autistic children: t(17) =
−4.44, p < .001; typical children: t(17) = −6.72, p < .001; adults: t(14) = −2.79, p =
.01]. A one-way analysis of variance (ANOVA) with group (autistic children, typical
children, or adults) as a between-participants factor revealed no significant effect of
group on the magnitude of the light bias, F(2, 48) = 0.10, p = .99. We also examined the
data by performing a Bayesian one-way ANOVA using JASP software (Version 0.8.0.0; JASP
Team, 2016) and estimating a Bayes factor using Bayesian information criteria
(Wagenmakers, 2007). The Bayes factor allowed for a comparison of the fit of our data
under the null hypothesis and the alternative hypothesis. The estimated Bayes factor
(null/alternative) suggested that our results were 6.56:1 in favor of the null hypothesis,
that is, 6.56 times more likely to occur under a model without an effect of group on the
magnitude of the light-from-above bias rather than a model with an effect of group. Our
data, therefore, provided substantial evidence (Wetzels et al., 2011) that adults, typical
children, and autistic children interpreted the shape of the stimulus in a similar way in
that they used a light-from-above prior to a similar degree. To investigate potential age-
related differences in the formation of the prior, we examined the relationship between
chronological age and the magnitude of the light bias. There was no significant
relationship between age and bias for either group (autistic: r = −.24, p = .33; typical
group: r = .03, p = .90). There was also no significant relationship with ability, as
measured by full-scale IQ scores on the WASI-2, for either group of children (autistic: r
= −.10, p = .95; typical group: r = .23, p = .36), or with autistic symptomatology, as
measured by the ADOS-2 severity scores of children (r = −.13, p = .61) (Gotham, Pickles, &
Lord, 2009; Hus & Lord, 2014). We also examined whether the judgments of younger children
were influenced by a preference for convexity, as suggested by Thomas et al. (2010), by
conducting a Pearson correlation analysis between participants’ percentage of convex
judgments (across all responses) and age. However, we found no significant relationship
between age and preference to interpret the shape as convex for either group of children
(typical: r = .05, p = .84; autistic: r = −.02, p = .93).

<h>DISCUSSION</h>
----------

This study investigated whether autistic and typical children apply a light-from-above
prior similarly to interpret shape from shading in conditions where shading cues are
ambiguous. The mean light-from-above prior for the children seen in this study was
approximately −13° (above and slightly to the left). We found no significant difference in
assumed light source location between autistic and typical children. Judgments of depth by
autistic children were influenced by a light-from-above prior—that is, they preferentially
assumed a light source above and to the left of the stimuli—to a similar extent as those
by typical children. Given that all children reported that it was easy to decide whether
the cell should be filled, it appears that they used their priors to help resolve noise
and ambiguity and achieve stable percepts. This finding is consistent with a recent report
suggesting that priors for eye gaze direction—where gaze is more likely to be perceived as
direct in conditions of uncertainty—are intact in autistic adults (Pell et al., 2016). In
our task, environmental conditions other than rotation were held constant, so that
inference relied on participants’ existing priors, summing their long-term experience of
lighting conditions. We used a task that had previously shown subtle differences between
groups whose long-term (cultural) experience of reading direction differed (Andrews et
al., 2012), suggesting that it should have been possible to detect differences based on
long-term experience between our groups if they were in fact present. Similar mean levels
might nevertheless conceal different group levels of adaptation in the short term to
prevailing environmental conditions. Experimental evidence has demonstrated that changes
in prevailing environmental conditions can modify light priors in the short term. In the
case of typical adults, the light-from-above prior adapts rapidly (Adams, Graf, & Ernst,
2004; Adams, Kerrigan, & Graf, 2010; Champion & Adams, 2007), so that training with haptic
feedback can change an individual light prior location by approximately 10° with 1.5 h of
training (Adams et al., 2004). Participants’ visual judgments on a separate task after
training were recalibrated in line with the new prior (Adams et al., 2010; Champion &
Adams, 2007), indicating that the prior had been temporarily updated. Similarly, learning
an association between a context and its lighting conditions led to contextually
appropriate calibration of the light prior (Kerrigan & Adams, 2013), in line with Bayesian
updating of the prior probability distribution by context. Flexible adaptation to
prevailing conditions was not tested in the current study but is a worthy avenue for
future research and a more direct test of the account of Pellicano and Burr (2012). It is
also important to consider precisely how prior knowledge acts on perceptual inference.
Although evidence strongly suggests that an assumed light source position is represented
early in the visual system and acts on early inference (Champion & Adams, 2007; Lee et
al., 2002; Mamassian, Jentzsch, Bacon, & Schweinberger, 2003), perceptual computation also
appears to be an interactive process, so that activity in the early visual cortex may
nevertheless take into account behavioral experience and higher order perceptual saliency
(Lee, 2003; Lee et al., 2002). Champion and Adams (2007) found evidence of both early and
late influence of the light-from-above prior on perceptual inference. Although visual
haptic training modified the light-from-above prior used in a judgment of shape task, the
prior assessed in a visual search task was not affected by the same training (Champion &
Adams, 2007). The discrepant effects of the training environment were interpreted as
evidence that although training did not touch the “quick and dirty” process of early
inference, it influenced later additional stages of visual processing, where recent
experience with the world is taken into account. Because our task did not require
accounting for recent experience, the mean priors we found may reflect the influence of
the prior on the initial stage of visual processing alone, leaving open the possibility of
reduced influence of priors during later stages of visual processing for autistic
children. Future research should test how far the priors of children adapt to prevailing
environmental conditions. Our findings also show that the two groups of children performed
similarly to adults. Furthermore, we found no age-related changes in the use of the light-
from-above prior, at least in children between 7 and 14 years of age, suggesting that the
prior develops early—before 7 years. This would be consistent with recent findings showing
that typical children use prior knowledge in magnitude estimations from an early age, in
particular for temporal (Karaminis et al., 2016) and spatial (Sciutti, Burr, Saracco,
Sandini, & Gori, 2014) interval reproduction. If learning an internal model of the sensory
environment is key to the statistical inference process involved in Bayesian perception,
and also is critical to learning beyond perception (Fiser, Berkes, Orbán, & Lengyel,
2010), early acquisition of priors, especially robust ones like these, would make sense
developmentally. However, Karaminis et al. (2016) found differences between autistic and
typical development in time interval reproduction. Autistic children showed significantly
less precision in their estimations than matched typical children, with computational
simulations suggesting less use of prior knowledge than expected to compensate for this
level of imprecision. This result implies differences in the flexible deployment of priors
to improve the precision/reliability of estimates. Our task showed no differences between
typical and autistic children in the use or development of the light-from-above prior, at
least in controlled conditions where competing information is limited (cf. Morgenstern et
al., 2011), but the findings of Karaminis and colleagues are another reason to study the
flexibility of the light-from-above prior (cf. Adams et al., 2010) in autistic children.
Our findings are in contrast to other research reporting developmental increases in
responses consistent with light-from-above prior (Stone, 2011; Stone & Pascalis, 2010;
Thomas et al., 2010), although the evidence is not clear-cut. Thomas et al. (2010) found
an overall effect of age on children’s interpretation of ambiguous stimuli, so that trials
answered assuming light from above increased across childhood. Yet this result was
complicated by the measurement of two distinct priors—one for convexity and one for light
from above. When the two priors biased interpretation in the same direction, there was
little change in use of the light-from-above prior over development; when the priors
conflicted, younger children (4- and 5-year-olds) preferred a convex interpretation,
whereas older children and adults preferred to assume light from above if light could be
interpreted as from above and to the left rather than as above right. However, the number
of younger children was small (n = 7), with some performing at around chance levels. Stone
and Pascalis (2010) showed children aged 4–10 years geometric shapes and photographic
stimuli, either upright or rotated 180°, reporting increasing levels of interpretation
consistent with light from above by age group. Yet the results for symbolic images—where
ambiguity is higher and, therefore, the potential influence of the prior is stronger—did
not clearly support this interpretation. In particular, the regression analysis for
concave stimuli (if lit from above) against age was nonsignificant, whereas that for
convex symbols (if lit from above) indicated greater use of the prior for children aged
around 7 or 8 years. Overall, these results point to the difficulty of disentangling the
influence of light from above and convexity priors and the difficulty of interpreting
which factors influenced the performance of younger children. In sum, we have established
that the light-from-above prior is similar in strength in a shape judgment task in school-
age autistic and typical children of similar age and ability. Furthermore, contrary to
previous reports (Stone & Pascalis, 2010; Thomas et al., 2010), our results suggest a
stable level of use of the prior across this age range. Although our methods were
developmentally sensitive, with performance not being confounded with linguistic demands
(concave and convex), our sample sizes were relatively small and we may have had
insufficient power to detect age-related changes in the use or strength of the prior; this
is especially important given that priors vary widely between individuals (e.g., Adams,
2007; Champion & Adams, 2007; Mazzilli & Schofield, 2013; Morgenstern et al., 2011). One
outstanding question is whether the light-from-above prior is just as adaptable as it is
in adults for typically developing children—but especially for children on the autism
spectrum.


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<ART>The mindful eye: Smooth pursuit and saccadic eye movements in meditators and non-meditators
================================================================================

Authors: Veena Kumari, Elena Antonova, Bernice Wright, Aseel Hamid, Eva Machado Hernandez, Anne Schmechtig, Ulrich Ettinger
DOI: 10.1016/j.concog.2016.10.008
Year: 2017  |  Pages: 66-75
ASJC codes: 3204, 3205
Keywords: Antisaccade, Attention, Control, Dispositional mindfulness, Intra-individual variability, Meditation, Mindfulness

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background This study examined the effects of cultivated (i.e. developed through training) and dispositional (trait) mindfulness on smooth pursuit (SPEM) and antisaccade (AS) tasks known to engage the fronto-parietal network implicated in attentional and motion detection processes, and the fronto-striatal network implicated in cognitive control, respectively. Methods Sixty healthy men (19–59 years), of whom 30 were experienced mindfulness practitioners and 30 meditation-naïve, underwent infrared oculographic assessment of SPEM and AS performance. Trait mindfulness was assessed using the self-report Five Facet Mindfulness Questionnaire (FFMQ). Results Meditators, relative to meditation-naïve individuals, made significantly fewer catch-up and anticipatory saccades during the SPEM task, and had significantly lower intra-individual variability in gain and spatial error during the AS task. No SPEM or AS measure correlated significantly with FFMQ scores in meditation-naïve individuals. Conclusions Cultivated, but not dispositional, mindfulness is associated with improved attention and sensorimotor control as indexed by SPEM and AS tasks.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Smooth pursuit and saccadic eye movements are two types of eye movements that both human
and non-human primates voluntarily employ to allow the image of an object fall and
maintain near to or on the fovea. The function of smooth pursuit eye movements (SPEM) is
to keep a retinal image within the area of the fovea during the movement of an object. The
initiation as well as the maintenance of accurate SPEM requires attentional control
(Hutton & Tegally, 2005). The primary measure of pursuit accuracy is the velocity gain
which corresponds to the ratio of smooth pursuit velocity over target or object velocity
(100% if SPEM velocity matches the target velocity) (Lencer & Trillenberg, 2008). Other
indicators of SPEM efficiency are the frequency of compensatory catch-up and intrusive
anticipatory saccades made during the smooth pursuit task. Saccades refer to the fast eye
movements made to the sudden appearance of a visual target. Prosaccades require the
participant to make a saccade to a single-target stimulus as soon as it appears. The
antisaccade (AS) paradigm, on the other hand, requires the participant to inhibit a
reflex-like saccade towards the target, and instead initiate a saccade in the direction
opposite to the target (Hutton & Ettinger, 2006). It examines the conflict between a pre-
potent stimulus that produces a strong urge to make a saccade to the target, and the
overriding goal to look in the opposite direction. Correct AS performance requires
accurate perception, ability to transform location information to a mirror image
representation, and suppression of a saccade towards the AS stimulus. Performance is
assessed as the error rate, spatial accuracy and latency of (anti)saccades (Hutton &
Ettinger, 2006). Given their high test-retest reliability (Ettinger et al., 2003) and the
ease of administration, SPEM and AS paradigms have been used to assess cognitive functions
in a wide variety of contexts (Hutton & Ettinger, 2006; Lencer & Trillenberg, 2008).
However, no published study, to our knowledge, has yet utilised these paradigms to
understand the neural and cognitive influence of mindfulness as a trait (‘dispositional’
mindfulness) (Brown & Ryan, 2003), or mindfulness developed through training (‘cultivated’
mindfulness) (Ivanovski & Malhi, 2007). Mindfulness, a translation of the Pali term sati,
is operationalized in modern psychology as a quality of awareness that arises from paying
attention to the experience on a moment-by-moment basis without judging, elaborating upon,
or fixating on this experience in any way (Kabat-Zinn, 1990). Its practice typically
begins with the mindfulness of bodily sensations to the awareness of feelings and
thoughts, progressing to a present-centred awareness without an explicit focus, in most
Buddhist traditions as well as formal intervention-style practices such as Mindfulness-
Based Stress Reduction (MBSR; Kabat-Zinn, 1990) and Mindfulness-Based Cognitive Therapy
(MBCT; Segal, Williams, & Teasdale, 2002). Dispositional mindfulness refers to the
naturally occurring tendency to display this non-judgmental present awareness in everyday
life and varies amongst individuals (Brown & Ryan, 2003). There is growing evidence for a
positive effect of cultivated mindfulness on a range of cognitive functions (reviews,
Chiesa, Calati, & Serretti, 2011; Gallant, 2016). Mindfulness practice enhances stability
of attention by reducing cortical noise (Lutz et al., 2009) and appears to increase
information processing capacity (Slagter et al., 2007) with the cognitive system more
rapidly available to process new targets (Slagter, Lutz, Greischar, Nieuwenhuis, &
Davidson, 2008). It is reported to positively influence orienting attention (van den Hurk,
Giommi, Gielen, Speckens, & Barendregt, 2010), dual attention (Jensen, Vangkilde,
Frokjaer, & Hasselbalch, 2012) and performance on a range of tasks requiring attention
and/or cognitive flexibility (Hodgins & Adair, 2010; Jha, Krompinger, & Baime, 2007; Jha,
Stanley, Kiyonaga, Wong, & Gelfand, 2010; Kumari, Hamid, Brand, & Antonova, 2015; Moore,
Gruber, Derose, & Malinowski, 2012; Semple, 2010; Tang et al., 2007; van den Hurk,
Janssen, Giommi, Barendregt, & Gielen, 2010). According to a recent review (Gallant,
2016), mindfulness-led improvements in executive functioning, within Miyake et al.’s model
(2000), are more consistently found on specific measures of inhibition (Allen et al.,
2012; Heeren, Van Broeck, & Philippot, 2009; Moore & Malinowski, 2009; Sahdra et al.,
2011; Teper & Inzlicht, 2013), relative to updating (Jha et al., 2010; Mrazek, Franklin,
Tarchin, Baird, & Schooler, 2013) and shifting components (Anderson, Lau, Segal, & Bishop,
2007; Chambers, Lo, & Allen, 2008; Heeren et al., 2009; Moynihan et al., 2013). There are,
however, only few data at present examining the association between trait mindfulness, as
measured in the general non-meditating population using self-report questionnaires (Brown
& Ryan, 2003), and cognitive function, with some studies (Stillman, Feldman, Wambachm,
Howard, & Howard, 2014; Stillman et al., 2016; Whitmarsh, Uddén, Barendregt, & Petersson,
2013) indicating a negative relationship between trait mindfulness and implicit learning,
i.e. learning without conscious awareness. The aim of the present study was to examine the
influence of mindfulness both as a trait and developed through training on visuo-spatial
attentional and voluntary inhibition processes indexed by the SPEM and AS paradigms,
respectively. Based on previous report of positive effects of mindfulness practice on a
range of attention, working memory and inhibition tasks (reviews, Chiesa et al., 2011;
Gallant, 2016), we hypothesised that meditators, compared with meditation-naïve
individuals, will show more accurate gain and lower frequency of catch-up and anticipatory
saccades on the SPEM task, and a lower error rate, higher spatial accuracy and reduced
within-subject variability in spatial accuracy (i.e. more consistent performance) on the
AS task. Furthermore, we hypothesised tentatively (in absence of direct previous data)
that in meditation-naïve individuals, trait mindfulness, as assessed by the Five Factor
Mindfulness Questionnaire (FFMQ; Baer, Smith, Hopkins, Krietemeyer, & Toney, 2006), will
correlate with better SPEM and AS performance, particularly on measures that significantly
differentiate meditators and non-meditators.

<hs>  Participants and design</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

The study involved two groups. Group 1 consisted of 30 experienced mindfulness
practitioners (meditators) and Group 2 of 30 meditation-naïve individuals (all males; age
range 19–59 years). All participants were assessed on a single occasion. Meditators were
recruited from local and national Buddhist centres via poster advertisement and
presentations of the study and its aims at meetings of centre members. They were required
to have at least 2 years of consistent meditation practice (minimum 45 min per day at
least 6 days a week). Meditation-naive men were recruited from a healthy volunteer
database or by circular emails sent to staff and students of King’s College London, UK.
They were required to have no experience of mindfulness-related practices, including
meditation, yoga, tai-chi, qigong or martial arts. Additional inclusion criteria for all
participants were: (i) right-handedness (Oldfield, 1971), (ii) current IQ > 80 as assessed
with the two-test version of Wechsler Abbreviated Scale of Intelligence (Wechsler, 1999),
(iii) aged 18–60 years, (iv) normal or corrected-to-normal vision, and (v) not drinking
more than 28 units of alcohol per week [1 unit = 1/2 pint of beer (285 mls) or 25 ml of
spirits or 1 glass of wine], or more than 6 units of caffeinated beverage a day. Those
with a positive screen for any neuropsychiatric disorder, a current or past primary
diagnosis of substance misuse or on regular medical prescription were not included. The
final sample with usable SPEM data consisted of 29 meditators (drawn mainly from Zen,
Theravada, Vajrayana and Triratna traditions of Buddhism) and 30 meditation-naïve
individuals, and with usable AS data of 27 meditators and 29 meditation-naïve individuals
(see Table 1). Study procedures were approved by the King’s College London Research Ethics
Committee (PNM/14/15-90). Participants provided written informed consent to their
participation and were compensated for their time and travel.

<hs>  Sample characterisation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Meditation history (meditation tradition/style, meditation routine) was obtained from the
meditators prior to study participation. In addition, all participants completed the FFMQ
(Baer et al., 2006). The FFMQ has been constructed from factor analysis done on five of
the most previously popular measures of trait mindfulness, and is currently the most
frequently used measure of trait mindfulness. Its five facets are observing (Observe, e.g.
“When I’m walking, I deliberately notice the sensations of my body moving.”), describing
(Describe, e.g. “I’m good at finding words to describe my feelings.”), acting with
awareness (Awareness, e.g. “I find myself doing things without paying attention.” with
reverse scoring), non-judging of inner experience (Non-judgment, e.g. “I tell myself I
shouldn’t be feeling the way that I am feeling.”) and non-reactivity to inner experience
(Non-reactivity, e.g. “I watch my feelings without getting lost in them.”), assessed on a
5-point Likert scale (never or rarely, rarely, sometimes, often, very often or always
true) with 39 items (8 items each for Observe, Describe, Awareness and Non-judgement
facets and 7 items for Non-reactivity facet). Higher scores indicate higher mindfulness.

<hs>  Eye movements: Paradigms and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Infrared oculography (IRIS 6500; Skalar Medical BV, Delft, the Netherlands) was used to
record eye movements. Participants were seated in a height-adjustable chair with their
head resting on a chinrest at a distance of 57 cm from the computer monitor. They were
requested to remain as still as possible throughout the experiment. The visual stimulus
consisted of a white circular target, with 0.3° diameter, presented on a black background
on a 17-inch monitor. A 3-point (+12°, 0°, −12°; stimulus duration = 1000 ms) calibration
task was carried out prior to running the SPEM, AS and prosaccade (PS) tasks. During the
SPEM task, a target dot moved horizontally across the screen, in a triangular waveform, at
three different velocities (12°/s, 24°/s, 36°/s). Participants were requested to keep
their gaze on this horizontally moving target as closely as possible. The target dot was
initially positioned at the centre of the screen (0°). It then moved either to the left or
the right side of the screen (±12°), and then to the opposite side. Each target movement
from one side (e.g. −12°) to the other (e.g. +12°) is referred to as half-cycle or ramp.
The target dot completed a total of 16.5 half-cycles. The first half-ramp (from 0 to ±12°)
was not included in the analysis. The PS and AS tasks used ±6° and ±12° targets, each
presented 15 times in a random order (60 PS trials and 60 AS trials in separate blocks).
Each PS and AS trial began with the target in the centre of the participant’s visual field
(0°) for a random duration of 1000–2000 ms. The target then abruptly stepped to one of the
four possible peripheral locations (±6° and ±12°), along the horizontal plane, and
remained there for 1000 ms before it stepped back to the central position for the next
trial. During the PS task, participants were requested to look at the target when it was
in the central position, and then follow it with their eyes (i.e. generate prosaccades)
when it stepped to the peripheral positions. During the AS task, participants were
requested to keep their gaze at the target when it was in the central position and to
generate a saccadic eye movement to the mirror-image projection of the target, in the
opposite hemifield, when it moved to any one of the four peripheral positions. Four
practice trials, one with each target location, were carried out before the experimental
trials, and repeated if necessary. All participants were assessed first on the PS task,
followed by the AS and SPEM tasks. The testing took place in a quiet and darkened room.
The participants were allowed to have coffee on the day of testing but were provided only
with decaffeinated drinks for at least 1 h prior to being assessed on eye movement tasks.
The experimental setup, oculomotor tasks and oculographic data recording and scoring
procedures were the same as used in a previous study (Schmechtig et al., 2010).

<hs>  Eye movement analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~

All eye movement recordings were scored blind to group membership.

        <hss>Smooth pursuit</hss>

        The time-weighted average pursuit velocity gain, frequency of catch-up saccades
        and frequency of anticipatory saccades were calculated for each participant, using
        LABVIEW 6.0 student version (2000). The time-weighted average pursuit velocity
        gain was calculated by dividing mean eye velocity by target velocity. This
        analysis included sections of pursuit which lay in the central half of each ramp
        (the first and last quarters excluded to avoid effects of pursuit initiation and
        slowing at target turnarounds). Velocity gain scores for each section of the
        pursuit, that were free of saccades or blinks, were time-weighted and subsequently
        averaged across half cycles for each target velocity (score <100% means that the
        eye is slower, and score >100% that it is moving faster, than the target).
        Saccadic frequency per second was calculated dividing the total number of
        anticipatory or catch-up saccades by the duration in seconds of pursuit at each
        target velocity (N/s). Anticipatory saccades were defined as saccades that began
        with the eye on or behind the target and ended ahead of it, while catch-up
        saccades were defined as saccades that began with the eye behind the target and
        served to bring the eye closer to the target. Saccades that began behind the
        target and ended ahead of it were defined as anticipatory saccades if more than
        half of amplitude was spent ahead of the target, and as catch-up saccades if more
        than half of amplitude was spent behind the target. Back-up saccades and square-
        wave jerks were not counted as their frequency was too low for a meaningful
        differentiation of the meditator and meditation-naïve groups. Saccades were
        automatically detected in EYEMAP 2.1 (AMTech, GmbH, Weinheim, Germany) using
        minimum amplitude (1°) and velocity (30°/s) criteria.

        <hss>Prosaccade (PS)</hss>

        Spatial accuracy (gain, spatial error) and latency, along with associated SDs,
        were scored for each participant using EYEMAP 2.1. PS gain was calculated as the
        percentage of saccade amplitude divided by target amplitude multiplied by 100 (a
        score of 100% represents a perfectly accurate saccade, <100% a hypometric saccade
        and >100 a hypermetric saccade). Spatial error (percentage) represented the
        residual error. It was calculated for each trial by subtracting the target
        amplitude from saccade amplitude and dividing it by the target amplitude, and then
        averaged across all trials and multiplied by 100 (higher scores indicate greater
        spatial error regardless of saccadic over or under-shoot). Saccadic latency
        represented the time (in ms) from the appearance of the target to saccade
        initiation.

        <hss>Antisaccade (AS)</hss>

        The AS error rate (% total) was calculated as the percentage of error trials (i.e.
        trials where the participant’s first saccade is towards the target) over the total
        number of valid trials (i.e. error trials plus correct trials, excluding eye blink
        trials). AS gain, spatial error, latency, error rate (% total), as well as the SDs
        of gain, spatial error and latency were calculated for each participant. In
        addition, the correction rate (%) was scored to ensure that all included
        participants knew task requirements (∼100% correction rate). AS gain, spatial
        error and latency were calculated following the criteria described above (for PS).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Group differences in age, IQ, and FFMQ scores were examined using independent sample
t-tests. Each SPEM measure (gain, frequency of catch-up saccades, frequency of
anticipatory saccades) was analysed using a 2 (Group: meditators, meditation-naïve) × 3
(Velocity: 12°/s, 24°/s and 36°/s target velocities) analysis of variance (ANOVA) with
Group as a between-subjects factor and Velocity as a within-subjects factor, followed by
the analysis of simple main effects and lower order ANOVAs as appropriate to test the
hypothesised differences between the meditator and meditation-naïve groups. Each AS (error
rate, gain, spatial error and latency, as well as the SDs of gain, spatial error, latency)
and PS measure (gain, spatial error and latency as well as SDs of these variables) was
analysed using a one-way ANOVA. Effect sizes, where reported, are partial eta squared
(ηp2; the proportion of variance associated with a factor). Correlational analyses
(Pearson’s r) were run to examine the hypothesised association between FFMQ scores and
SPEM and AS measures in meditation-naïve individuals; for completeness, similar
correlation analyses were conducted in meditators. Possible correlations between age and
SPEM and AS variables were also examined. All analyses were performed using the
Statistical Package for Social Sciences (for Windows, version 22; IBM, New York, US).
Alpha level for testing significance of effects was maintained at p < 0.05 unless stated
otherwise.

<hs>  Sample characteristics: Meditators versus Non-meditators</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Meditators scored significantly higher on Observe [t (49) = 3.21, p = 0.002], Non-judgment
[t(49) = 3.37, p = 0.001] and Non-reactivity facets [t(49) = 4.05, p < 0.001] of
mindfulness as assessed by the FFMQ (Baer et al., 2006) compared to meditation-naïve
individuals (Table 1). The two groups did not differ in age or IQ (p > 0.25) (Table 1).

<hs>  Eye movements: Meditators versus non-meditators</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Means (SDs) for eye movement measures, separately for the meditators and meditation-naive
groups, are presented in Table 2.

        <hss>SPEM</hss>

        Meditators did not differ from meditation-naïve individuals in gain at any of the
        three target velocities, as there was neither a main effect of Group [F(1, 57) =
        1.96, p = 0.17, ηp2 = 0.03] nor a Group × Velocity interaction [F(2, 114) = 0.06,
        p = 0.94, ηp2 = 0.001]. There was only a significant main effect of Velocity
        showing less accurate performance with increasing velocities in both groups [F(2,
        114) = 8.74, p < 0.001, ηp2 = 0.13; linear F(1, 57) = 12.66, p = 0.001, ηp2 =
        0.18] (Table 2). Meditators made fewer catch-up saccades than meditation-naïve
        individuals at 12° target velocity (p = 0.01) but did not differ significantly at
        the other two target velocities (p > 0.13), as revealed by the follow-up analysis
        of a significant Group × Velocity interaction [F(2, 114) = 3.73, p = 0.03, ηp2 =
        0.06]. There was a main effect of Velocity showing a higher frequency of catch-up
        saccades with increasing velocities in both groups [F(2, 114) = 142.06, p < 0.001,
        ηp2 = 0.71; linear F(1, 57) = 225.79, p < 0.001, ηp2 = 0.78] (Table 2). Meditators
        made fewer anticipatory saccades than meditation-naïve individuals at all three
        velocities as demonstrated by a significant main effect of Group [F(1, 57) = 6.70,
        p = 0.01, ηp2 = 0.11] and a non-significant Group × Velocity interaction [F(2,
        114) = 0.88, p = 0.42, ηp2 = 0.01]. In addition, there was a main effect of
        Velocity showing a higher frequency of anticipatory saccades with increasing
        velocities in both groups [F(2, 114) = 48.70, p < 0.001, ηp2 = 0.46; linear F(1,
        57) = 69.72, p < 0.001, ηp2 = 0.55] (Table 2).

        <hss>AS</hss>

        Meditator and meditation-naïve groups did not differ in error rate [F(1, 54) =
        1.00, p = 0.33, ηp2 = 0.02], latency [F(1, 54) = 0.06, p = 0.80, ηp2 = 0.001],
        gain [F(1, 54) = 2.52, p = 0.12, ηp2 = 0.04] or spatial error [F(1, 54) = 2.53, p
        = 0.12, ηp2 = 0.04]. Meditators, however, had significantly lower SDs of gain
        [F(1, 54) = 5.20, p = 0.026, ηp2 = 0.09] and spatial error [F(1, 54) = 4.24, p =
        0.04, ηp2 = 0.07] relative to meditation-naïve individuals.

        <hss>PS</hss>

        There was no difference between the two groups for any PS variables (all p values
        >0.18).

<hs>  Correlational analyses: Trait mindfulness (FFMQ), age and eye movement measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In meditation-naïve individuals, only two, out of 78 in total, correlations reached p <
0.05 (not corrected for multiple correlations), and these two were inconsistent with one
showing better (fewer catch-up saccades) and the other showing worse performance (more
anticipatory saccades) in association with higher scores trait mindfulness (Describe and
Non-judgment facets) (Table 3). Age did not correlate with any eye movement measures. In
meditators, higher scores on the FFMQ were associated with better AS performance.
Specifically, higher scores on both Observe and Non-reactivity facets were associated with
lower spatial error and lower SDs of spatial error and gain, with Non-reactivity facet
associating further with a larger gain; the correlations with other mindfulness facets
were non-significant but in the same direction. In addition, older age was consistently
associated with poorer AS performance (higher error rate, increased spatial error and
longer latency).

<h>DISCUSSION</h>
----------

Supporting our hypothesis in relation to the influence of cultivated mindfulness, the
present study revealed superior SPEM and AS performance in meditators relative to
meditation-naïve individuals. Specifically, meditators, relative to meditation-naïve
individuals, had fewer catch-up (at 12° target velocity) and anticipatory saccades (at all
three target velocities) during the SPEM task, and significantly lower SDs of gain and
spatial error during the AS task. The two groups did not differ significantly in AS gain
and spatial error, though meditators, in line with our a priori hypothesis, were more
stable across trials in these measures of spatial accuracy. The findings, however, offered
no support for our hypothesis in relation to dispositional (trait) mindfulness. None of
the five facets of the FFMQ correlated consistently positively or negatively with either
SPEM or AS indices in non-meditators, though significant relationships between higher FFMQ
scores (Observe and Non-reactivity facets) and more accurate and more consistent AS
performance were present in meditators. In addition, older age was associated with poorer
AS performance (higher error rate, increased spatial error and longer latency) in
meditators. The finding of fewer catch-up and anticipatory saccades during the SPEM task
in meditators, compared to non-meditators, indicating better attentional control in long-
term meditators (Hutton & Tegally, 2005), is in line with Lutz et al.’s (2008) focussed
attention meditation framework. This superiority most likely developed through regular
practice of mindfulness since no significant relationship was found between the SPEM
indices and FFMQ scores in non-meditators. SPEM paradigms are well known to elicit
activity in frontal and posterior areas that are implicated in attentional and motion
detection processes (Lencer & Trillenberg, 2008; Sharpe, 2008) as well as in the
neurobiological effects of mindfulness practices (Barnby, Bailey, Chambers, & Fitzgerald,
2015; Hölzel et al., 2011; Marchand, 2014). It would be valuable to further examine the
neural basis of the influence of cultivated mindfulness in SPEM performance. Our finding
of significantly lower SDs of gain and spatial error during the AS task indicates lower
intra-individual variability (i.e. more consistent within-session performance) in
meditators, relative to non-meditators. Intra-individual variability, examined mostly in
reaction time across a range of tasks, is considered to reflect lapses in attention or
cognitive control (Fassbender, Scangos, Lesh, & Carter, 2014; Weissman, Roberts, Visscher,
& Woldorff, 2006), sustained attention deficit (Leth-Steensen, Elbaz, & Douglas, 2000), a
poor ability to successfully engage cognitive control in demanding situations (Bellgrove,
Hester, & Garavan, 2004), and poor regulation of effort (Sergeant, Geurts, Huijbregts,
Scheres, & Oosterlaan, 2003). Increased intra-individual variability occurs with aging
(e.g. Anstey, 1999; Fozard, Vercruyssen, Reynolds, Hancock, & Quilter, 1994; Shammi,
Bosman, & Stuss, 1998) and is associated with many clinical conditions, including frontal-
temporal dementia (Murtha, Cismaru, Waechter, & Chertkow, 2002), attention hyperactivity
deficit disorder (Leth-Steensen et al., 2000; Vaurio, Simmonds, & Mostofsky, 2009; Zahn,
Kruesi, & Rapoport, 1991), schizophrenia (Schwartz et al., 1989) and traumatic brain
injury (e.g. Bleiberg, Garmoe, Halpern, Reeves, Nadler, 1997; Segalowitz, Dywan, & Unsal,
1997; Stuss, Murphy, Binns, & Alexander, 2003; Stuss et al., 1989; Zahn & Mirsky, 1999).
Intra-individual variability is typically most strongly present on tasks that require
executive control (West, Murphy, Armillio, Craik, & Stuss, 2002) and appears particularly
sensitive to frontal lobe function, with frontally-deficient clinical groups showing the
greatest intra-individual variability (Murtha et al., 2002). Since all our participants
were required to be free of a neuropsychiatric condition and known brain injury, the
findings of lower SDs of gain and spatial error during the AS task can be taken to
indicate superior executive control and frontal lobe functioning developed through
training in the meditator group. Interestingly, neuroticism has been associated with
greater intra-individual variability, supposedly due to distracting worries about task
performance or difficulty in those with high neuroticism (Robinson & Tamir, 2005). If
mindfulness improves emotion regulation by exerting a positive influence on executive
control processes (Teper & Inzlicht, 2013), this may, at least partly, explain both
performance superiority of the meditators observed in our study and the recently
demonstrated reduction in neuroticism following MBCT (Armstrong & Rimes, 2016).
Furthermore, mindfulness training or practice is known to exert attenuating effects on the
Default Mode Network (e.g. Brewer et al., 2011; Farb et al., 2007), associated with mind-
wandering or stimulus-independent thought (Mason et al., 2007), which would further
enhance the performance on the tasks employed in the current study. This study did not
reveal a meaningful pattern of correlations between dispositional mindfulness and eye
movement performance indices. It may be that dispositional mindfulness, as measured by
self-report questionnaires, indeed exists fairly independently of cultivated mindfulness
and is conceptually unique (Rau & Williams, 2016; Wheeler, Arnkoff, & Glass, 2016). It may
share some (e.g. negative association with neuroticism) but not all behavioural or neural
correlates of cultivated mindfulness (Rau & Williams, 2016). Furthermore, absence of
opposite traits, such as neuroticism or mindlessness, might not indicate a presence of
mindfulness by necessity (Grossman & Van Dam, 2011). There were, however, meaningful and
significant relationships between FFMQ scores and AS measures in meditators. Specifically,
both Observe and Non-reactivity facets were correlated with lower spatial error and lower
SDs of spatial error and gain, with Non-reactivity facet correlating further with a larger
gain. Correlations of the three remaining mindfulness facets with these AS parameters,
although in the same direction, were non-significant. Taken together, these observations
may suggest that earlier-noted consistent mindfulness training-led improvements found
across studies in the inhibition component of executive control (review, Gallant, 2016),
may be mediated most strongly by Observe and Non-reactivity aspects of mindfulness
training. Our study has some limitations. First, it examined the effects of cultivated
mindfulness on eye movement control in a cross-sectional design, without any knowledge of
the meditators’ eye movement performance prior to them starting mindfulness practice.
Future research could examine the effects of shorter duration mindfulness-based
interventions (MBIs) on SPEM and AS performance. If the results show improved SPEM and AS
performance following MBIs, they would not only add to our understanding of the neural and
cognitive effects of mindfulness but would also provide easily quantifiable and objective
markers to index mindfulness training effects and its neurobiological underpinnings.
Second, the findings of this study, which involved only men, cannot be generalized to
women. Further research is needed to examine the influence of mindfulness in eye movement
control in women, preferably controlling for menstrual phases, given menstrual phase-
related variability in other psychophysiological measures of attention and inhibitory
function (Kumari, 2011). In conclusion, this is the first study, to our knowledge, to have
examined and shown superior SPEM and AS performance in established meditators, relative to
meditation-naïve individuals. The findings suggest that mindfulness meditation improves
attention and the stability of responding on visuo-motor tasks. Future studies are needed
to confirm these effects using within-subjects designs (pre- and post-mindfulness
training) and firmly establish whether eye movement tasks hold promise as objective
measures of mindfulness training.

<h>CONFLICT OF INTEREST</h>
--------------------

The authors declare no conflict of interest.

<h>ROLE OF FUNDING SOURCE</h>
----------------------

The sponsors had no role in study design; in the collection, analysis and interpretation
of data; in the writing of the report; or in the decision to submit the paper for
publication.


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<ART>The moderating effect of trait anxiety on anxiety-related thoughts and actions whilst driving
================================================================================

Authors: M. P. Barnard, P. Chapman
DOI: 10.1016/j.paid.2018.07.027
Year: 2018  |  Pages: 207-211
ASJC codes: 3200
Keywords: Driving anxiety, Questionnaire, Stress, Trait anxiety

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Whilst there is evidence for the impact of driving anxiety on behaviour, less exists for the impact of trait anxiety and what does exist is inconclusive. The current study explored the possibility that trait anxiety interacts with driving anxiety to impact the frequency of negative on-road thoughts and behaviours. An online survey was administered to drivers, and the State-Trait Inventory for Cognitive and Somatic Anxiety, the Driving Cognitions Questionnaire, and the Driving Behaviour Survey, were completed. Moderation analyses suggested that in addition to an increase in social concerns and aggressive responses, high trait anxiety reduced positive associations between driving anxiety and exaggerated safety-cautious behaviours, as well as the general use of maladaptive reactions to stressful situations. As scores on these subscales were still higher regardless of the reduced associations, it is argued that both drivers with a generally anxious personality and those with high levels of driving-specific anxiety should be made aware of their potential to violate traffic norms in stressful situations.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

According to research and national statistics (Department for Transport, 2014; Dula &
Geller, 2003), negative emotions increase the likelihood of dangerous driving behaviours
and crash involvement. The UK's Department for Transport revealed that over 5000 crashes
in 2013 were preceded by negative emotional experiences behind the wheel, with 1900 of
these accounted for by nervousness, uncertainly or panic. This suggests that emotions
associated with anxiety may be a significant risk factor for traffic crash involvement.
Those with an anxious driving style tend to feel distress and anxiety when driving, and
express a lack of confidence in their skills (Taubman-Ben-Ari, Mikulincer, & Gillath,
2004). Whilst they often report lower levels of sensation-seeking, suggesting a reduced
risk of crash involvement due to avoidance of high-risk situations (Ulleberg, 2001),
empirical evidence suggests that this subgroup may be more dangerous on the road. Those
associated with this driving style have shown lapses in attention and memory (Lucidi et
al., 2010), a greater number of on-road errors (Taylor, Deane, & Podd, 2007), and a
greater likelihood of crash involvement (Marengo, Settanni, & Vidotto, 2012). Those with
driving anxiety may perceive their abilities as insufficient to deal with the environment
they have encountered, resulting in increased stress and use of emotion-focused coping
(Lazarus & Folkman, 1984). Transportation research confirms this suggestion by
demonstrating that increased levels of stress contribute towards increased errors, lapses,
and dangerous driving (Ge et al., 2014; Rowden, Matthews, Watson, & Biggs, 2011). However,
recent evidence has also acknowledged the relationship between personality and the
appraisal-emotion relationship; neuroticism, a trait associated with anxiety, has
demonstrated a moderating and exacerbating relationship between appraisals and negatively
valenced emotions (Tong, 2010). Thus when evaluating the ways in which drivers cope with
stressful situations, the role of personality should not be ignored. Yet there is a lack
of focus in, or consensus on, the relationship between trait anxiety and driving. Whilst
self-report evidence associates higher trait anxiety with more violations, errors, and
lapses (Pourabdian & Azmoon, 2013; Shahar, 2009), behavioural research looking at areas
such as hazard perception (Barnard & Chapman, 2016) and speeding compliance (Stephens &
Groeger, 2009) have found it has either no detrimental effects, or actually make drivers
safer. It is possible that trait anxiety, rather than consistently affecting driver
behaviour, has more of an impact on the negative thoughts associated with driving.
Processing theories such as Attentional Control Theory (Eysenck, Derakshan, Santos, &
Calvo, 2007), propose that an increased occupation with worrisome thoughts reduces
processing efficiency without necessarily impacting behaviours. Research into how this is
associated with driving is limited, although it does accord with the observation that
trait anxiety is associated with increased reaction times on n-back tasks as well as
increased errors and lapses (Wong, Mahar, & Titchener, 2015). Recent questionnaires
assessing the effects of anxiety on driver behaviour have referred to some of the
principles discussed within Attentional Control Theory. For example, recent research
looking at the Driving Cognitions Questionnaire (DCQ- Ehlers et al., 2007) acknowledged
the high probability of trait anxiety producing a higher frequency of dysfunctional
thoughts in phobic participants (da Costa, de Carvalho, Cantini, da Rocha Freire, & Nardi,
2014). Furthermore, the Driving Behaviour Survey (DBS- Clapp et al., 2011) includes a
subscale on anxiety-based performance deficits, defined as behaviours that occur due to an
increase in worrisome or anxious thoughts that increase cognitive load. Notably, some of
the previously discussed research emphasised an association between an anxious driving
style and lapses in attention, suggesting that the principles of the theory could apply to
anxious drivers, as well as those with dispositional anxiety. What has received less focus
in the literature is the way in which trait and state anxiety may interact with each
other. This issue was highlighted in a recent review on anxiety (Wilt, Oehlberg, &
Revelle, 2011). It was suggested that the dichotomisation of anxiety into these two
dimensions may result in the potential to reduce our understanding of how they exist in a
concurrent fashion. The idea of interaction has been supported more recently in research
into phonological and set-shifting processing efficiencies (Edwards, Edwards, & Lyvers,
2015, 2016). Research within the field of transportation would benefit from a similar
integration of personality and state. Whilst previous research has investigated the
relationship between trait and driving anxiety, this has merely confirmed the existence of
higher trait anxiety in those with driving anxiety (Taylor et al., 2007), without further
exploration of the relationship between the two. The present study explores the potential
influences of both driving anxiety, as well as trait anxiety, on the frequency of negative
thoughts and behaviours on the road. This was achieved using an online survey. We
investigate whether the previous suggestions from Wilt et al. (2011) could be observed
within an applied context. Additionally, we provide data to help practitioners understand
whether the frequency of specific thoughts and actions is additionally affected by an
anxious personality, rather than simply being anxious about driving. Based on the previous
literature, it was hypothesised that trait anxiety could have a moderating effect on the
frequency of negative thoughts associated with driving, as well as potentially on
behaviours associated with worrisome or anxious thoughts.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were approached using social media invitations, advertising on a local
newspaper website, advertising on a local study recruitment website, and through a
University volunteering database. The study was completed online, and a total of 320
participants with full driver's licences expressed interest in the survey by going to the
web link associated with the survey; however, only 227 completed their responses,
resulting in a 71% retention rate (149 females, 76 males). Their ages ranged from 17 to
81, with an average age of 35 (sd = 18.44). The majority were in employment or full-time
study (80.2%), whilst the remainder of the sample was retired or unemployed (17.2%).
Participants had held their full driving licence for 15.19 years (sd = 16.79), and drove
6229.22 miles per year (sd = 5904.19). Most reported driving at least a few times a week
(69.46%). Ninety-five reported previous involvement in a crash in which they were the
driver (41.85%).

<hs>  Software</hs>
  ~~~~~~~~

The survey was compiled and distributed to participants using LimeSurvey version 2.05, an
online open source software tool which can be used to create and publish surveys, as well
as compile respondent statistics and collate responses for analysis.

        <hss>Demographic variables</hss>

        The survey initially consisted of a standard information sheet and consent form,
        after which questions were asked regarding demographics and general driving
        behaviour. These included questions on licence duration, annual mileage and crash
        history. Once these had been completed, participants completed the State-Trait
        Inventory for Cognitive and Somatic Anxiety (STICSA-Grös, Antony, Simms, & McCabe,
        2007), the DCQ, and the DBS.

        <hss>State-Trait Anxiety for Cognitive and Somatic Anxiety</hss>

        The STICSA is a 42-item questionnaire, 21 of each measuring state and trait
        anxiety. Items are distinguished according to whether they measure cognitive (10
        items) or somatic symptoms of anxiety (11 items). Items are administered on a 1 to
        4 Likert scale, with 1 meaning ‘not at all’ and 4 meaning ‘very much’. Total
        scores for state and trait range from 21 to 84. In all cases, a higher score
        indicates higher anxiety levels. However, to measure the effects of driving
        anxiety, the phrasing of the state STICSA was changed; instead of asking
        participants how they felt “at this moment”, they were asked how they felt whilst
        driving. Whilst previous research has used the State-Trait Anxiety Inventory
        (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983) to obtain anxiety measures,
        recent research has suggested that the STICSA is more strongly correlated with
        anxiety than the STAI (Grös et al., 2007) Average driving anxiety scores were
        29.43 (sd = 10.93) and average trait anxiety scores were 31.8 (sd = 11.3)
        Cronbach's α was 0.946 for driving anxiety, and 0.941 for trait anxiety,
        indicating good internal consistency.

        <hss>Driving cognitions questionnaire</hss>

        The DCQ is a 20-item questionnaire designed to assess the frequency of concerning
        thoughts whilst driving. Six items address social concerns, seven address accident
        concerns, and seven address panic concerns. Items are administered on a 5-point
        Likert scale, with “0” meaning “Never”, and “4” meaning “Always”. A minimum score
        of 0 and maximum score of 28 can be obtained for accident and panic concerns,
        whilst a maximum score of 24 can be obtained for social concerns. An overall
        maximum score of 80 can be obtained. In the current study, average scores for
        social, panic and accident concerns were 5.17 (sd = 4.9), 1.98 (sd = 3.48) and
        6.34 (sd = 5.26) respectively, whilst the overall average score was 13.49 (sd =
        12.26). Overall Cronbach's α was 0.941, and for social, accident and panic
        concerns were 0.866, 0.897, and 0.888 respectively.

        <hss>Driving behaviour survey</hss>

        The DBS is a 21-item questionnaire measuring the frequency of driving behaviours
        associated with a hypothetically stressful driving situation on three subscales
        consisting of seven items each. Anxiety-based performance deficits (ABPD) are
        related to changes in driving performance due to an anxiety-induced increase in
        cognitive load and include behaviours such as lane drifting and inappropriate
        speed adjustments. Exaggerated safety-cautious behaviours (ESCB) increase the
        perceived safety of a situation by maintaining larger headway distances and
        unnecessarily slowing down at traffic lights. Finally, the aggression subscale
        evaluates the ‘fight’ aspect of the fight-or-flight response and includes
        behaviours such as swearing and pounding on the steering wheel. Items are
        administered on a 7-point Likert scale, with 1 meaning “Never” and 7 meaning
        “Always”. Item scores are averaged, meaning that for each subscale participants
        can obtain a minimum score of 1 and a maximum score of 7; this same principle is
        applied to the overall DBS score. Average scores for ABPD, ESCB behaviours, and
        aggression were 2.09 (sd = 0.9), 3.52 (sd = 1.25) and 2.2 (sd = 1.12)
        respectively, whilst the average overall score was 2.6 (sd = 0.84). Cronbach's α
        for the total score was 0.885, and for ABPD, ESCB, and aggressive reactions were
        0.835, 0.846, and 0.862 respectively.

<hs>  Procedure</hs>
  ~~~~~~~~~

After expressing interest in the survey, participants took an average of 10–15 min to
complete it, after which a chance to win £50 in shopping vouchers was offered as an
incentive. The survey was online for approximately 12 months and ethical approval for its
administration was obtained from a local Ethics Committee.

<h>RESULTS</h>
-------

Subscale and overall scores for questionnaires were calculated manually; based on previous
research (Taylor & Sullman, 2009), where there were no more than two or fewer items
missing on a scale, mean item replacement accounted for this. Data from five participants
were removed due to missing STICSA scores. Three further cases were also removed from DBS
analysis. Scores were subjected to a moderation analysis using PROCESS version 2.16.3
(Hayes, 2013), running in SPSS version 22. Driving anxiety was treated as a predictor
variable, whilst trait anxiety was treated as a moderator variable. Demographic variables
previously associated with higher levels of anxiety in previous transportation research
were entered into moderation models as covariates. These included age, experience (defined
as the amount of years since passing a driving test), gender, and cras involvement. The
latter two were dummy coded to assume that the participant was female or had been
previously involved in an accident. Interactions between driving and trait anxiety were
explored using simple slopes analysis. Slopes were generated at ±1 standard deviation of
the mean of trait anxiety scores, and the Johnson-Neyman method was used to obtain a zone
of significance. Bivariate correlations between variables, as well as output from post-hoc
power analyses conducted in G*Power v3.1 (Faul, Erdfelder, Lang, & Buchner, 2007), are
available as supplementary material.

<hs>  DCQ</hs>
  ~~~

For all scores, levels of driving anxiety were a significant positive predictor (all ps <
0.001). Trait anxiety also acted as a significant positive predictor of social concerns (p
< .01) and total DCQ scores (p < .05); however, it did not moderate the relationship
between driving anxiety and DCQ scales. Additionally, those involved in an accident had
lower DCQ social scores (see Table 1).

<hs>  DBS</hs>
  ~~~

Levels of driving anxiety positively predicted ABPD scores, ESCB scores, and total DBS
scores (all ps < .001, see Table 2). For the aggression subscale, age and gender were
significant negative predictors. This suggested that female drivers, as well as older
drivers, had lower aggression scores (ps < .05). Trait anxiety was a positive predictor of
ABPD scores, aggression scores, and total DBS scores (ps < .001). Trait anxiety acted as a
positive predictor of aggression in the absence of a similar effect of driving anxiety (p
= .36). Interaction effects were found for ESCB and total DBS scores (ps < .05, see Figs.
1 and 2). Details on unstandardized slopes are available in Table 3. The Johnson-Neyman
technique revealed that trait anxiety moderated the relationship between driving anxiety
and scores, until trait anxiety scores were 20.91 points above the mean for ESCB, and
19.54 points above the mean for total DBS scores.

<h>DISCUSSION</h>
----------

The current study aimed to establish whether trait anxiety moderates the relationship
between driving anxiety and the frequency of negative thoughts and behaviours on the road,
in accordance with previous suggestions and findings (Wilt et al., 2011). We found that
whilst trait anxiety did have a moderating effect, this was only for the frequency of
reactive behaviours, and not the frequency of negative thoughts, as previously
hypothesised. Interactions included an increase in the frequency of ESCB behaviours, as
well as an increase in general negative behaviours. However, rather than finding that
personality exacerbated this relationship, as previously suggested (Tong, 2010), higher
trait anxiety in fact reduced the associative strength between driving anxiety and these
behaviours. Furthermore, the frequency of ESCB and total DBS behaviours were consistently
higher for those with high trait anxiety than those with high driving anxiety but only low
or average levels of trait anxiety (see Figs. 1 and 2). For ESCB behaviours, whilst those
with high driving anxiety may be engaging in such behaviours as a means to increase
perceptions of control (Baker, Litwack, Clapp, Beck, & Sloan, 2014), those with high trait
anxiety may be doing so, and acting dangerously, without necessarily being anxious about
driving. This would also apply to the use of maladaptive behaviours, as indicated by total
DBS scores. Practically, those with high trait anxiety may need to be made aware that
their reactions to stressful situations may be causing danger and violating traffic norms.
Whilst it cannot be determined from this study whether those with high trait anxiety are
consciously adopting these behaviours, it has been suggested that unrecognised persistence
of ESCB behaviours would negatively impact interventions such as exposure-based therapy
(Clapp, Baker, Litwack, Sloan, & Beck, 2014). Several interventions could be put in place
to increase such awareness, such as continuous feedback from vehicles. Trait anxiety did
not moderate concerns whilst driving, but still acted as a predictor of thoughts and
behaviours. Some findings are in line with previous research (Deffenbacher, Huff, Lynch,
Oetting, & Salvatore, 2000) and indicate that future interventions should seek to reduce
feelings of reactive anger. Other findings, such as the relationship between trait anxiety
and ABPD, could suggest maladaptive changes in behaviour due to an increase in cognitive
load. This would support previous research (Clapp et al., 2011) and suggests that some of
the specific behaviours that may need to be targeted by interventions for those with high
trait anxiety include attention-based behaviours. To accept this suggestion would imply
that these behaviours are due to worrisome thoughts. The data from this study suggest that
there are effects of trait anxiety on social and general concerns whilst driving,
supporting previous research (Taylor & Deane, 2000), but it is also worth considering how
these thoughts may impact behaviour. The DCQ asks participants to rate how frequently they
experience certain thoughts whilst they are driving. As these data report thoughts during
driving, this could indicate a form of mind wandering. Mind wandering results in dangerous
driving behaviours (Yanko & Spalek, 2014); it is possible that those with high trait
anxiety may be preoccupied with thoughts of unlikely events, such as others thinking they
are a bad driver, resulting in unintentionally dangerous behaviours. Whilst research
suggests those reporting anxiety whilst driving are no more likely to show mind wandering
(Burdett, Charlton, & Starkey, 2016), this is from a state perspective; those high in
neuroticism also report higher levels of mind wandering and poorer attentional control
(Robison, Gath, & Unsworth, 2017), thus it is still possible that those high in trait
anxiety may show similar behaviours behind the wheel. Whilst these findings could have
important implications, there are several limitations to consider. Firstly, the use of
self-report data means that these results may not fully reflect on-road behaviour. Whilst
there are some positive relationships between self-report and behavioural responses
(Taubman-Ben-Ari, Eherenfreund-Hager, & Prato, 2016), to our knowledge such data does not
currently exist for the DCQ and DBS. Secondly, the use of retrospective data suggests that
the data may need to be interpreted with caution. For example, accident data is often
prone to distortions in memory due to forgetting (Maycock, Lockwood, & Lester, 1991) and
inflations in intensity, depending on time since recall (Chapman & Underwood, 2000).
Additionally, those higher in anxiety are more likely to recall threatening information
(Mitte, 2008). For the current study, anxious participants could have used more negative
experiences to influence recall, resulting in potential data bias. Finally, there may be
issues with temporal stability. The data were collected over 12 months, in which time
driver cognitions may have changed. To highlight this, initial DBS construction suggested
issues in temporal stability for the aggression subscale (Clapp et al., 2011). Therefore,
it is acknowledged that due to the chosen scales, there may be issues with reliability.
The current study suggested that whilst trait anxiety independently predicts certain
concerns and maladaptive responses to stressful driving situations, it also has the
potential to reduce positive associations between driving anxiety and ESCB behaviours. Due
to consistently higher ESCB scores in high trait anxiety, this indicates that those high
in anxiety could show driving behaviours violating traffic norms and increasing accident
likelihood. Practically, this indicates that those with such a personality should not be
ignored within the field of transportation, and measures seeking to help those with high
driving anxiety may also benefit those with high trait anxiety.


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<ART>The motor repertoire in 3- to 5-month old infants with Down syndrome
====================================================================

Authors: Dafne Herrero, Christa Einspieler, Carolina Y. Panvequio Aizawa, Akmer Mutlu, Hong Yang, Alice Nogolová, Jasmin Pansy, Karin Nielsen-Saines, Peter B. Marschik
DOI: 10.1016/j.ridd.2017.05.006
Year: 2017  |  Pages: 1-8
ASJC codes: 3203, 3204
Keywords: Down syndrome, Fidgety movements, General movements, Infant, Motor optimality score

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background Even though Down syndrome is the most common chromosomal cause of intellectual disability, studies on early development are scarce. Aim To describe movements and postures in 3- to 5-month-old infants with Down syndrome and assess the relation between pre- and perinatal risk factors and the eventual motor performance. Methods and procedures Exploratory study; 47 infants with Down syndrome (26 males, 27 infants born preterm, 22 infants with congenital heart disease) were videoed at 10–19 weeks post-term (median = 14 weeks). We assessed their Motor Optimality Score (MOS) based on postures and movements (including fidgety movements) and compared it to that of 47 infants later diagnosed with cerebral palsy and 47 infants with a normal neurological outcome, matched for gestational and recording ages. Outcomes and results The MOS (median = 13, range 10–28) was significantly lower than in infants with a normal neurological outcome (median = 26), but higher than in infants later diagnosed with cerebral palsy (median = 6). Fourteen infants with Down syndrome showed normal fidgety movements, 13 no fidgety movements, and 20 exaggerated, too fast or too slow fidgety movements. A lack of movements to the midline and several atypical postures were observed. Neither preterm birth nor congenital heart disease was related to aberrant fidgety movements or reduced MOS. Conclusions and implications The heterogeneity in fidgety movements and MOS add to an understanding of the large variability of the early phenotype of Down syndrome. Studies on the predictive values of the early spontaneous motor repertoire, especially for the cognitive outcome, are warranted. What this paper adds The significance of this exploratory study lies in its minute description of the motor repertoire of infants with Down syndrome aged 3–5 months. Thirty percent of infants with Down syndrome showed age-specific normal fidgety movements. The rate of abnormal fidgety movements (large amplitude, high/slow speed) or a lack of fidgety movements was exceedingly high. The motor optimality score of infants with Down syndrome was lower than in infants with normal neurological outcome but higher than in infants who were later diagnosed with cerebral palsy. Neither preterm birth nor congenital heart disease were related to the motor performance at 3–5 months.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Even though Down syndrome is the most common chromosomal cause of intellectual disability,
with 20–22 individuals per 10,000 births affected (e.g., Kurtovic-Kozaric et al., 2016;
Loane et al., 2013), studies on early development are scarce. Infants with Down syndrome
are known to be socially competent but show a delay in the acquisition of motor milestones
and deficits in early gesture production (Grieco, Pulsifer, Seligsohn, Skotko, & Schwartz,
2015; Özcaliskan, Adamson, Dimitrova, Bailey, & Schmuck, 2016; Saito & Watanabe, 2016). As
early as the first months of life they scored lower than typically developing infants on
both the Test of Infant Motor Performance (Cardoso, Campos, Santos, Santos, & Rocha, 2015)
and the Alberta Infant Motor Scale (Tudella, Pereira, Pedrolongo Basso, & Savelsbergh,
2011). They kicked less often (Ulrich & Ulrich, 1995) and their arm movements were less
accurate when reaching for objects of different sizes (de Campos, Cerra, Silva, & Rocha,
2014). Repeated assessments of their spontaneous general movements revealed a
heterogeneous movement quality, although the fluency and complexity tended to improve
between 1 and 6 months of age (Mazzone, Mugno, & Mazzone, 2004). Initially designed for
infants with acquired brain injuries, the Prechtl assessment of general movements
(Einspieler & Prechtl, 2005; Prechtl et al., 1997) has recently also been applied to
infants with genetic syndromes (Einspieler, Hirota, Yuge, Deijima, & Marschik, 2012;
Einspieler, Kerr, & Prechtl, 2005; Einspieler et al., 2014; Marschik, Soloveichick,
Windpassinger, & Einspieler, 2015; Mazzone et al., 2004) and infants later diagnosed with
autism spectrum disorders (Einspieler et al., 2014; Zappella et al., 2015). The assessment
is based on visual Gestalt perception of normal vs. abnormal movements in the entire body
(i.e. general movements). It is applied in foetuses, preterm infants, and newborn infants
from term to 5 months post-term (Einspieler, Prechtl, Bos, Ferrari, & Cioni, 2004; Prechtl
& Einspieler, 1997). The excellent predictive power of general movement assessments
(Bosanquet, Copeland, Ware, & Boyd, 2013; Einspieler et al., 2004) is mainly attributable
to fidgety general movements, which occur from 3 to 5 months post-term age (Einspieler &
Prechtl, 2005; Prechtl et al., 1997). Infants with normal fidgety movements are very
likely to develop normally in neurological terms, whereas infants who never develop
fidgety movements have a high risk for neurological impairment (Einspieler & Prechtl,
2005; Prechtl et al., 1997). Adding a detailed assessment of concurrent movements and
postures to the assessment of fidgety movements, for example, showed a reduced motor
optimality score (MOS) to be associated with a limited activity in children who were later
diagnosed with cerebral palsy (Yang et al., 2012), or with lower intelligent quotients
during school age (Butcher et al., 2009). We therefore assumed that determining the MOS
(Einspieler et al., 2004, p. 26) by assessing fidgety movements as well as concurrent
movement and postural patterns would enable us to systematically document the motor
repertoire of infants with Down syndrome. The MOS makes it possible to quantitatively
relate pre- and perinatal data to the motor repertoire of an infant and to data obtained
from follow-up studies. The aims of our study were (1) to describe movements and postures
in 3- to 5-month-old infants with Down syndrome; (2) to compare their MOS with the MOS of
two matched samples, one of which was later diagnosed with cerebral palsy, while the other
had a normal neurological outcome; and (3) to analyse to what extent clinical risk factors
during pregnancy, at delivery, and during the neonatal period were related to the motor
performance in 3- to 5-month-old infants with Down syndrome.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

This exploratory study comprised a convenience sample of 47 infants with Down syndrome −
21 females (45%) and 26 males (55%) − who had been admitted to (a) the Darcy Vargas Public
Hospital, São Paulo (17 individuals); (b) the Department of Physiotherapy and
Rehabilitation at the Hacettepe University in Ankara (ten individuals); (c) the Associação
de Pais e Amigos dos Excepcionais at São Paulo University (seven individuals); (d) the
Rehabilitation Department of the Children’s Hospital of Fudan University in Shanghai (four
individuals); (e) the Children’s Department at the City Hospital of Ostrava (three
individuals); (f) the Clinic of Early Intervention at the University Hospital São Paolo
(three individuals); and (g) the Medical University of Graz (three individuals) between
June 2015 and May 2016. In order for the infants to be included in the study, the infants’
motor performance had to be recorded between 9 and 20 weeks post-term. The infants’
gestational ages at birth ranged from 29 to 41 weeks (median = 37 weeks), with a birth
weight range of 1440 g to 3680 g (median = 2585 g). Twenty-seven infants were born preterm
(57%), including two monozygotic twin pairs. Other clinical characteristics obtained from
the medical histories are presented in Table 1. Three infants were diagnosed with mosaic
Down syndrome, one with Robertsonian translocation (14;21). For comparison we used data of
our international, MOS-based data bank (N = 365 as of January 15, 2017), picking (i) 47
individuals with a normal neurological outcome at 3–5 years of age, whose gestational age
and age of video recording matched our study cases; and (ii) 47 individuals with a
comparable gestational age at birth and post-term age at the time of the video recording
who were diagnosed with cerebral palsy at 3–5 years of age (Table 2). Since spontaneous
(i.e. endogenously generated) movements are not related to ethnicity (Luxwolda et al.,
2014), we did not match the ethnic background. All parents gave their written informed
consent. The ethical review boards of the various centres approved the study.

<hs>  Recording and evaluation of movements and postures at 3–5 months post-term age</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Within the GenGM network we recorded 5-min videos of the spontaneous motility of each
infant at a median post-term age of 14 weeks (P25 = 12 weeks; P75 = 15 weeks; range: 10–19
weeks). The recordings were performed during periods of active wakefulness between
feedings, with the infant partly dressed, lying in supine position (Einspieler et al.,
2004). The videos were evaluated by at least two certified raters (D.H., C.E., A.M., A.N.,
J.P., P.B.M.) according to the Prechtl method of global and detailed general movement
assessment (Einspieler et al., 2004 Einspieler & Prechtl, 2005). Scorers C.E. and P.B.M.
were not familiar with the details of the participants’ clinical histories apart from the
fact that they had Down syndrome. In case of disagreement (four recordings; 8.5%), the
raters re-evaluated the recordings until consensus was reached on a final score. Fidgety
movements and the concurrent repertoire of movements and postures were assessed
independently in separate runs of the video recordings. Using the score sheet for the
assessment of motor repertoire at 3–5 months (Einspieler et al., 2004, p. 26), we
calculated the MOS, with a maximum value of 28 (for the best possible performance) and a
minimum value of 5. The score sheet comprises the following five sub-categories: (i)
fidgety movements, (ii) age-adequacy of motor repertoire, (iii) quality of movement
patterns other than fidgety movements, (iv) posture, and (v) overall quality of the motor
repertoire (Einspieler et al., 2004; Yuge et al., 2011). Fjørtoft and colleagues found a
high inter-observer reliability for the MOS with intra-class correlation coefficients
ranging from 0.80 to 0.94 (Fjørtoft, Einspieler, Adde, & Strand, 2009).

<hs>  Statistical analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~

Statistical analysis was performed using the SPSS package for Windows, version 23.0 (SPSS
Inc., Chicago, IL). The Pearson Chi-square test was used to evaluate associations between
nominal data. To put the medians of non-normally distributed continuous data (e.g. motor
optimality score) in relation to nominal data (e.g. preterm birth), we applied the Mann-
Whitney-U test or, if there were more than two categories, the Kruskal-Wallis test (e.g.
repertoire). To assess the relative strength of the association between variables, we
computed the following correlation coefficients: Cramer’s V coefficient was applied when
at least one of the two variables was nominal (e.g. preterm birth and age-adequacy of the
repertoire). To assess the relation between two continuous variables (e.g. gestational age
and motor optimality score), we applied the Pearson product-moment correlation
coefficient. Throughout the analyses, p < 0.05 (two-tailed) was considered to be
statistically significant.

<hs>  The motor performance of infants with Down syndrome at 3–5 months postterm age (Table 2, first column)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Fourteen infants had normal fidgety movements (30%); six infants (12.5%) displayed
abnormal fidgety movements (i.e. they look like normal ones though with a greater
amplitude, speed and jerkiness); 13 infants (27.5%) displayed no fidgety movements, which
were therefore classified as absent; 14 infants (30%) showed fidgety-like movements whose
amplitude was too great and whose pace was too slow. Abnormal and absent fidgety movements
as well as fidgety-like movements were grouped as aberrant fidgety movements (33 infants;
70%). Twelve infants (25.5%) displayed an age-adequate movement repertoire. The repertoire
was found to be reduced in 20 infants (42.5%; mainly due to a lack of movements to the
midline), and age-inadequate in 15 infants (32%). The quality of the various movement
patterns (other than fidgety movements) was scored as predominantly normal in 39 infants
(83%) and predominantly abnormal in three infants (6.5%); five infants (10.5%) showed an
equal number of normal and abnormal movements. On average the infants demonstrated three
normal movement patterns (range: 0–8) and one abnormal movement pattern (range: 0–3). The
most frequent normal movement patterns included visual scanning (32/47; 68%), side-to-side
movements of the head (22/47; 47%), foot-to-foot contact (14/47; 30%), hand-to-mouth
contact (12/47; 25.5%), and kicking (10/47; 21%). Smiling (9/47; 19%), fiddling (9/47;
19%), hand regards (8/47; 17%), swipes (7/47; 15%), hand-to-hand contact (6/47; 13%),
arching (6/47; 13%), and leg lifting (5/47; 11%) were observed in fewer than ten
individuals. Other movement patterns such as wiggling-oscillating arm movements, hand-to-
knee contact, or rolling to the side were observed in fewer than five individuals (<10%).
The most frequent abnormal movement pattern was long-lasting and/or repetitive tongue
protrusion (26/47; 55%). In a few infants we observed hand-to-hand contact with no mutual
manipulation (4/47; 8.5%), long lasting wiggling-oscillating arm movements (3/47; 6%),
repetitive kicking (3/47; 6%), and monotonous side-to-side movements of the head (1/47;
2%). Posture was rated as predominantly normal in 22 infants (47%) and predominantly
abnormal in 15 infants (32%); ten infants (21%) showed an equal number of normal and
abnormal postures (Table 2). Infants with predominantly normal postural patterns were able
to hold their head in midline (31/47; 66%), showed a symmetrical body posture (25/47; 53%)
and variable finger postures (23/47; 49%); a persistent asymmetric tonic neck response was
absent in all individuals. On average the infants demonstrated three normal postural
patterns (range: 1–4) and two abnormal postural patterns (range: 0–7). The most common
abnormal pattern was a lack of variable finger postures (24/47; 51%) with just a few
monotonous finger postures, finger spreading and/or predominant fisting. Twelve infants
(25.5%) kept both arms predominantly extended, while seven infants (15%) kept their legs
extended most of the time. Hyperextension of the neck and trunk was seen in three
individuals (6.5%). The following two postural atypicalities were observed, but are not
captured by the MOS sheet: nine individuals (19%) showed an internal rotation and
pronation of one or both wrists, and 22 infants (47%) showed an external rotation and
abduction of the hips (which was also the reason why most of them were unable to show
foot-to-foot contact). Only three infants (6.5%) exhibited a normal, smooth and fluent
overall movement character, while 44 infants (93.5%) displayed a monotonous, stiff, jerky
and/or tremulous movement character. The median MOS was 13 (P25 = 12; P75 = 23; range:
10–28).

<hs>  The MOS of infants with Down syndrome compared to infants later diagnosed with cerebral palsy and infants with a normal neurological outcome (Table 2)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The MOS of infants with Down syndrome was significantly lower than that of infants with a
normal neurological outcome (p < 0.01) but significantly higher than that of infants later
diagnosed with cerebral palsy (p < 0.01). Similar results were obtained for fidgety
movements, the age-adequacy of the motor repertoire, and the overall movement character
(p-values < 0.01). The quality of movement and postural patterns of infants with Down
syndrome were similar to those of infants with a normal neurological outcome (p-values >
0.10), while infants later diagnosed with cerebral palsy scored lower (p-values < 0.01;
Table 2).

<hs>  The neonatal period and its relation to the motor performance at 3–5 months post-term age (Table 3 and 4)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

None of the clinical characteristics was related to the MOS or fidgety movements. Preterm
birth was not associated with the MOS or its subcategories (Table 3), nor was any other
clinical variable. We would particularly like to mention that congenital heart disease
(CHD) was not related to the motor performance at 3–5 months. Cranial ultrasound data were
only available for a small proportion of the sample (eight infants, 17%). Two infants with
abnormal cranial ultrasound findings had abnormal fidgety-like movements. Among the six
infants with normal cranial ultrasound findings three showed normal fidgety movements, one
infant did not develop fidgety movements, and two infants had slow abnormal fidgety-like
movements (). Table 4 only lists significant associations between clinical variables and
items of the MOS. A jerky movement character (observed in 26/47 infants; 55%) was
associated with caesarean section and hyperbilirubinaemia, although the two clinical
variables were not related to each other (Pearson Chi-square test, p = 0.58). Delivery by
caesarean section was also related to a higher occurrence of a particular atypical posture
at 3–5 months: in many cases external rotation and abduction of the hips led to a lack of
(especially lower limb) movements to the midline. No difference was observed between twins
and singletons (Fisher sign test, p > 0.05). Neither the three infants with mosaic Down
syndrome (two with absent fidgety movements, one with normal fidgety movements; MOS = 10,
12 and 24, respectively) nor the one with Robertsonian translocation (normal fidgety
movements, MOS = 23) showed any sort of specific features in their motor performance at
3–5 months post term.

<h>DISCUSSION</h>
----------

Apart from one individual reported in the context of a larger sample of high-risk infants
in Japan (Yuge et al., 2011), this is the first study to use the MOS to describe fidgety
movements and the concurrent motor repertoire in infants with Down syndrome. Mazzone et
al. (2004) applied the detailed scoring for writhing general movements (observable from
birth to 1–2 months post-term) up to the age of 6 months rather than for fidgety and
concurrent motor patterns, which occur from 3 months onwards. The motor coordination and
performance of children, adolescents and adults with Down syndrome has been found to be
highly heterogeneous (Latash, 2007). Interestingly, we already observed this heterogeneity
at a much younger age: 30% of our 3- to 5-month-old infants with Down syndrome showed
normal fidgety movements, 27.5% had no fidgety movements, and 42.5% showed abnormal
fidgety movements. These highly diverse findings are reflected in the MOS, which range
from 10 to the highest possible score of 28. Fifty percent of the infants scored between
10 and 13, which is significantly lower than infants with a normal neurological outcome
and higher than infants who were later diagnosed with cerebral palsy. So far, two studies
carried out in children with cerebral palsy in China, Italy, and the Netherlands
demonstrated the lower the MOS at 3–5 months, the more severely limited their gross motor
function (Bruggink et al., 2009; Yang et al., 2012). As we intend to monitor our sample of
children with Down syndrome for at least 2 more years, we shall also assess the relation
between the MOS and the motor, cognitive and language outcomes. The one infant with Down
syndrome described by Yuge et al. (2011) displayed abnormal fidgety movements and an MOS
of 13. Abnormal fidgety movements, exaggerated in amplitude, speed and jerkiness, were
also observed in six infants in the present study. This is an exceptionally high rate of
occurrence, as abnormal fidgety movements are usually rare (see also Table 2). It has been
a matter of debate whether or not infants with a low muscle tone are more likely to show
abnormal fidgety movements (Einspieler, Peharz, & Marschik, 2016; Yuge et al., 2011).
Although this may not be consentaneously defined, a low muscle tone is a general feature
in infants with Down syndrome (Latash, 2007; Morris, Vaughan, & Vaccaro, 1982). A number
of studies have documented an association between abnormal fidgety movements and
coordination difficulties and/or disabilities in fine manipulative skills at school age
(Einspieler et al., 2007; Einspieler et al., 2016); others describe an exceedingly high
rate of abnormal fidgety movements in infants who were later diagnosed with autism
spectrum disorders or Rett syndrome (Einspieler et al., 2005; Einspieler et al., 2014).
However, most so-called abnormal fidgety movements in infants later diagnosed with autism
spectrum disorders or Rett syndrome did not correspond with the category of abnormal
fidgety movements described in infants with brain injuries, which were exaggerated in
amplitude and speed (Einspieler & Prechtl, 2005; Einspieler et al., 2016; Prechtl et al.,
1997). Several infants with a later diagnosis of autism spectrum disorders or Rett
syndrome showed continual fidgety activity which was exaggerated in amplitude but too slow
(Einspieler et al., 2005; Einspieler et al., 2014; Zappella et al., 2015). We also
observed this pattern in 14/47 (30%) infants with Down syndrome (see the abnormal fidgety
movements’ category in Table 2). It remains unclear whether this pattern is related to low
muscle tone, another early atypicality in autism spectrum disorders (Flanagan, Landa,
Bhat, & Bauman, 2012) and Rett syndrome (Nomura & Segawa, 1990), as video analysis does
not allow for an assessment of active muscle strength or resistance to passive movements.
Data on neurological examinations were not available in 44 of 47 individuals. In any case,
the low rate of movements to the midline (i.e., foot-to-foot contact in 30% and hand-to-
hand contact in only 13% of our sample) and the lack of kicking (21%) are in line with
previous studies, where they have also been discussed as possible consequences of low
muscle tone (Tudella et al., 2011). The same is true of the frequent external rotation and
abduction of the hip (observed in 47% of infants with Down syndrome) as well as the uni-
or bilateral internal rotation and pronation of the wrist(s) (19%). Unfortunately we are
unable to confirm this association for lack of information about our infants’ muscle tone
(see section 4.1.). Several research groups have reported a significant impact of pre- and
perinatal variables on the MOS at 3–5 months. For example, prenatal exposure to
environmental pollutants or selective serotonin reuptake inhibitors, and perinatal hypoxic
events resulted in a reduced MOS (Berghuis, Soechitram, Hitzert, Sauer, & Bos, 2013; de
Vries, van der Veere, Reijneveld, & Bos, 2013; Yuge et al., 2011). No such association was
established in our study. Neither gestational age nor birth weight or any other perinatal
risk factor was found to be significantly related to the MOS or fidgety movements,
notwithstanding the fact that 27 infants (57%) were born preterm. Nor was the percentage
of aberrant fidgety movements and/or a lower MOS increased in the 22 infants with CHD,
although toddlers with Down syndrome and CHD were reported to have a higher percentage of
motor, language and cognitive deficits at 12–14 months than toddlers with Down syndrome
and a normal heart structure (Alsaied et al., 2016; Visootsak et al., 2016). In our study,
neither aberrant fidgety movements nor a reduced MOS were attributable to preterm birth or
CHD. Only two variables were shown to affect movements and postures at 3–5 months:
caesarean section and hyperbilirubinaemia were related to a jerky movement character, and
external rotation and abduction of hips was more common among infants born by caesarean
section. In their study on healthy full-term infants during the first week after birth,
Ploegstra, Bos, and de Vries (2014) compared the general movements of low-risk neonates
born by vaginal delivery with those of neonates after caesarean section and found no
difference. So far, we cannot explain how external rotation and abduction of the hips is
related to caesarean section. As for the jerky movement character, there have no doubt
been more revealing findings: Groen, de Blécourt, Postema, and Hadders-Algra (2005)
reported 11 out of 15 children to have shown a normal neurological outcome in spite of
jerky movements at the age of 2–4 months.

<hs>  Limitations to our study</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

As various motor patterns such as abnormal fidgety or fidgety-like movements, lack of
movements to the midline, and external rotation and abduction of the hips could be
attributed to low muscle tone, we would also have needed to assess the infants’ muscle
tone. Yet, the assessment of muscle tone is anything but unequivocal. Definitions are not
standardised and inter-scorer agreement is prone to be low (Latash, 2007; Prechtl, 2001;
Touwen, 1976) except for extremes. Diverging experience and procedures in the tonus
assessment would no doubt have been additional challenges in a multicentre approach.
Training and application of the Hammersmith Infant Neurological Examination (Haataja et
al., 1999) was not available in most of the centres contributing to the study. This being
a comparative study, one might consider our participants’ varied ethnic backgrounds as
problematic. However, as we are dealing with spontaneous, i.e. endogenously generated
movements, the respective care-giving practices are very unlikely to have had an impact on
the early motor patterns in question. In fact, general movements have been assessed
worldwide for more than 20 years with similar cross-cultural results (e.g., Bruggink et
al., 2009; Luxwolda et al., 2014; Yang et al., 2012; Yuge et al., 2011). Nor did the
various sensory stimulations affect the infants’ fidgety movements, which demonstrates
their robust, environment-independent character (Dibiasi & Einspieler, 2002; Dibiasi &
Einspieler, 2004). Of course, the infants’ different cultural backgrounds could be an
issue with regard to the subcategory “posture”. Infants raised in a hammock, for example,
seem to be faster in acquiring the “head in midline” position and/or a “symmetric body
posture” (D.H. and C.E., personal observations), but none of our participants had
experienced such exceptional practices, and this goes for all three groups.

<h>CONCLUSION</h>
----------

The significance of this exploratory study lies in its minute description of the motor
repertoire of infants with Down syndrome aged 3–5 months. During this time window, fidgety
movements are the predominant spontaneous movement pattern and an excellent marker for the
neurological outcome (Bosanquet et al., 2013; Einspieler et al., 2004; Einspieler et al.,
2016). Infants with Down syndrome already show motor impairments at this early age, as
evidenced by a significantly low MOS. Reassessing the same children as toddlers will show
whether the high predictive power of fidgety movements found in infants with and without
acquired brain injury (Bosanquet et al., 2013; Einspieler & Prechtl, 2005; Einspieler et
al., 2004; Prechtl et al., 1997) also holds true for infants with a genetic disorder. A
particularly important aspect will be whether the early spontaneous motor repertoire will
also assist to predict the cognitive development of individuals with Down syndrome. A
particularly important aspect that needs to be studied is the predictive power of the
early spontaneous motor repertoire for the cognitive development of individuals with Down
syndrome. But quite apart from this important aspect for clinicians and researchers,
atypical postural features such as external rotation and abduction of the hips and/or
internal rotation and pronation of the wrists call for earlier intervention.


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<ART>The narrative coherence of witness transcripts in children on the autism spectrum
================================================================================

Authors: Lucy A. Henry, Laura Crane, Eva Fesser, Anna Harvey, Lucy Palmer, Rachel Wilcock
DOI: 10.1016/j.ridd.2019.103518
Year: 2020
ASJC codes: 3203, 3204
Keywords: Autism, Children, Eyewitness testimony, Narrative coherence, Story grammar

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background and Aims: Autistic children often recall fewer details about witnessed events than typically developing children (of comparable age and ability), although the information they recall is generally no less accurate. Previous research has not examined the narrative coherence of such accounts, despite higher quality narratives potentially being perceived more favourably by criminal justice professionals and juries. This study compared the narrative coherence of witness transcripts produced by autistic and typically developing (TD) children (ages 6–11 years, IQs 70+). Methods and Procedures: Secondary analysis was carried out on interview transcripts from a subset of 104 participants (autism = 52, TD = 52) who had taken part in a larger study of eyewitness skills in autistic and TD children. Groups were matched on chronological age, IQ and receptive language ability. Coding frameworks were adopted from existing narrative research, featuring elements of ‘story grammar’. Outcomes and Results: Whilst fewer event details were reported by autistic children, there were no group differences in narrative coherence (number and diversity of ‘story grammar’ elements used), narrative length or semantic diversity. Conclusions and Implications: These findings suggest that the narrative coherence of autistic children's witness accounts is equivalent to TD peers of comparable age and ability.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPERS ADDS</h>
---------------------

Previous work examining witness skills in autistic children has focused on the volume and
accuracy of their recall for a witnessed event. No previous studies have examined whether
these accounts are organised logically for the listener in terms of key ‘story grammar’
elements: information about the setting and the initiating event; the intentions of people
in the event; the emotions, cognitions and goals of the people in the event; the actions
that took place during the event; and the consequences arising from, and resolution of,
the event. Such information may help criminal justice professionals to better understand
what happened. Using closely matched, relatively large samples of autistic and non-
autistic children (all with IQs 70+), the present study found no differences in the
inclusion of story grammar elements between these two groups, despite the fact that
autistic children reported fewer correct details about the witnessed event than non-
autistic children. Similarly, the groups did not differ in terms of how long and
semantically diverse their accounts were. The current findings are novel because they
attest to the comparability of autistic and non-autistic child witnesses in terms of both
narrative coherence and account length/semantic diversity (despite the autistic children
reporting fewer details overall). The findings also support a growing body of literature
attesting to the overall reliability of autistic child witnesses.

<h>INTRODUCTION</h>
------------

Autistic1 children and adults are more likely to encounter the criminal justice system
than non-autistic individuals (Lindblad & Lainpelto, 2011; Turcotte, Shea, & Mandell,
2018; Woodbury-Smith & Dein, 2014). Further, because children and adults with
developmental differences are at increased risk of violence, victimisation and abuse
(Jones et al., 2012; Petersilia, 2001), it is vital to examine the quality of their
evidence and encourage increased rates of reporting, investigation and prosecution. The
current study examined the narrative coherence of information remembered by autistic
children, comparing them to matched typically developing (TD) children. It extends a
growing body of empirical research examining the accuracy and volume of recall for
witnessed events in children and adults on the autism spectrum (largely those without
intellectual disabilities). Previous findings indicate that children on the autism
spectrum often recall a lower volume of information than TD peers of comparable age and
ability (IQ) when interviewed about witnessed events (Almeida, Lamb, & Weisblatt, 2019;
Bruck, London, Landa, & Goodman, 2007; Henry, Messer et al., 2017; Mattison, Dando, &
Ormerod, 2015; McCrory, Henry, & Happé, 2007); although findings for autistic adults are
more complex (see review by Maras & Bowler, 2014). There is evidence that group
differences in volume of recall (in child and adult samples) are less apparent in more
structured interviews (Henry, Crane et al., 2017; Maras & Bowler, 2010), or when
additional supports (more specific questioning, physical reinstatement of context, or
concrete visual prompts) are provided at recall (Maras & Bowler, 2012a, 2014; Mattison,
Dando, & Ormerod, 2018). Importantly, eyewitness information provided by autistic children
can be as accurate as that of comparable peers (Almeida et al., 2019; Bruck et al., 2007;
Henry, Messer et al., 2017; Henry, Crane et al., 2017; McCrory et al., 2007); although
accuracy levels may vary with interview type (Mattison et al., 2018) and the findings are
less consistent in autistic adults (Maras & Bowler, 2010, 2011, 2012b; Maras, Memon,
Lambrechts, & Bowler, 2013). Critically, autistic people are not more suggestible than
non-autistic people (Bruck et al., 2007; Maras & Bowler, 2011, 2012b; McCrory et al.,
2007; North, Russell, & Gudjonsson, 2008), despite many legal professionals believing this
to be true (see George, Crane, Bingham, Pophale, & Remington, 2018, for a survey on this
topic in UK barristers). They may, however, be more compliant (Chandler, Russell, & Maras,
2019; North et al., 2008). To our knowledge, there is no current literature assessing the
narrative coherence of witness accounts provided by autistic children. Narrative coherence
refers to ‘a global representation of story meaning and connectedness’ (Diehl, Bennetto, &
Young, 2006) and is not the same as the amount of information recalled about an event, or
its accuracy (Brown, Brown, Lewis, & Lamb, 2018; Feltis, Powell, & Roberts, 2011; Reese et
al., 2011). A coherent account can be full or sparse in terms of evidential details, but
will show a degree of organisation and structure relating to the context, content and
characters associated with an event. Reese et al. (2011) suggest that a coherent narrative
is ‘one that makes sense to a naïve listener’ (p.425, emphasis original), and describe
developmental changes that occur during childhood in terms of increased complexity and
number of narrative features (see also Berman & Slobin, 1994). Narrative coherence is
often overlooked in research into witness recall, yet could substantially impact the
degree to which a child’s evidence can be easily understood by members of the criminal
justice system. For example, coherent accounts may appear more meaningful and credible to
jurors (Brown et al., 2018; Feltis et al., 2011; Feltis, Powell, Snow, & Hughes-Scholes,
2010; Gentle, Milne, Powell, & Sharman, 2013; Murfett, Powell, & Snow, 2008). Further, in
England and Wales, narrative coherence is used by the police (to establish relevant
'points to prove') and the Crown Prosecution Service (when making decisions about whether
or not to authorise charges). Studies looking at narrative coherence in TD children’s
witness accounts have adopted a ‘story grammar’ approach (Stein & Glenn, 1979) to capture
higher order hierarchical structure, organisation and coherence (often described as
‘macrostructure’ or ‘global structure’). This approach looks for key elements that make
accounts clear, organised and understandable for the listener via the inclusion of a
number of logically ordered story elements. Seven elements are coded including: setting
(contextual details about the event location to orient the listener); initiating event
(how the event began); internal response (emotions, cognitions and goals of the people in
the event); plan (the intentions of the people affected by the initiating event);
action/attempt (the activities that constituted the event); direct consequence (the
outcome/s of the event); and resolution (what happened at the end of the event). Many
four- to eight-year-old children with TD can provide at least some elements of story
grammar when recalling a witnessed event in an open-ended free recall interview (e.g.,
action/attempt, initiating event, and direct consequence details), although few children
in this age range include internal response, plan, setting or resolution elements (Feltis
et al., 2011). Using the story grammar framework, Westcott and Kynan (2004) conducted a
secondary analysis of investigative interviews with children suspected of being sexually
abused, finding that although children included basic story grammar components such as
‘setting’, their narratives were often “incomplete, ambiguous and disordered” (p.37).
Several authors have used the story grammar approach successfully to assess narratives
about witnessed events in children with intellectual disabilities (ID), finding that some
children with ID include proportionately fewer story grammar elements than comparison
groups (Brown et al., 2018; Gentle et al., 2013; Murfett et al., 2008). The current study
extended the story grammar approach to look at narrative coherence in witness transcripts
produced by children on the autism spectrum. An interview comprising only open-ended
questions was used, given that such methods are most likely to elicit story grammar
elements (Feltis et al., 2010; Snow, Powell, & Murfett, 2009). Children between the ages
of 6 and 11 years with and without an autism diagnosis were included, as at least some
markers of story grammar are present in witness accounts throughout this age range (Brown
et al., 2018; Westcott & Kynan, 2004). We did not look at developmental increases in the
inclusion of story grammar elements as these are well-established (e.g., Brown et al.,
2018; Feltis et al., 2011); the aim was to compare groups of autistic and TD children
matched on age (as well as IQ and receptive language). Previous literature on the broader
narrative skills of autistic children and adults presents a conflicting picture, largely
noting difficulties in some areas but not others (e.g., Banney, Harper-Hill, & Arnott,
2015; Capps, Losh, & Thurber, 2000; Diehl et al., 2006; King, Dockrell, & Stuart, 2013) or
hardly any differences at all (e.g., Capps, Kehres, & Sigman, 1998; Norbury & Bishop,
2003; Tager-Flusberg & Sullivan, 1995; Young, Diehl, Morris, Hyman, & Bennetto, 2005).
Studies generally compare autistic children or adults to age and language-matched (or
verbal ability-matched) TD children or adults (or in some cases language-matched children
with developmental delays). The areas of difficulty or difference identified are varied:
less use of complex syntax; reduced use of evaluative devices; reduced use of causal
explanations; greater numbers of ambiguous nouns and pronouns; shorter mean length of
utterance; fewer different main body words and word roots; less complex ‘high point’
structure; more bizarre or idiosyncratic contributions; less complex episodic structure;
and focus on details rather than gist (Banney et al., 2015; Barnes & Baron-Cohen, 2012;
Capps et al., 1998, 2000; Goldman, 2008; King et al., 2013; Lee et al., 2018; Losh &
Capps, 2003; McCabe, Hillier, & Shapiro, 2013; Norbury & Bishop, 2003; Pearlman-Avnion &
Eviatar, 2002). Baixauli, Colomer, Rosello, and Miranda (2016) reflected this variability
in their meta-analysis of narrative production tasks in autistic and non-autistic
children, reporting small, moderate and large effect sizes over a range of narrative
indices. Importantly, this variability in results may depend on the tasks used. Open-ended
tasks, such as describing personal narratives, recalling orally presented fairy tales, or
making up a story to go with an emotionally ambiguous picture, tend to reveal greater
difficulties for autistic children and adults than more structured and guided tasks such
as narrating the story to a ‘wordless picture book’ (King et al., 2013; Lee et al., 2018;
Losh & Capps, 2003; Losh & Gordon, 2014; Tager-Flusberg & Sullivan, 1995). Wordless
picture book tasks often reveal almost no group differences at all (e.g., Losh & Capps,
2003; Norbury & Bishop, 2003), and may reduce the cognitive demands of storytelling by
scaffolding memory, attention, story organisation and language production via providing
temporally sequenced visual cues. Importantly, although in their meta-analysis Baixauli et
al. (2016) reported no effects of narrative task, they could only assess two combined
categories of narrative task given the limited number of available studies. Results also
differ depending upon the nature of the comparison group. There are relatively few (or no)
differences in narrative ability on some tasks between well-matched autistic and non-
autistic children (e.g., Capps et al., 1998, 2000; Diehl et al., 2006; Losh & Capps, 2003;
Norbury & Bishop, 2003; Tager-Flusberg & Sullivan, 1995; Young et al., 2005). Such
matching, most commonly for verbal ability and age, ensures that group differences – if
found – are not just a function of language skills or developmental level. When looking at
results for the inclusion of the global elements of story grammar, previous research also
presents a mixed picture. Norbury and Bishop (2003), for example, compared autistic and
non-autistic children matched for age and non-verbal ability, but who showed differences
on language measures including receptive vocabulary and grammar. There were no group
differences in the inclusion of key story grammar elements. Diehl et al. (2006) included
samples of autistic and TD children who all had ability levels in the 80 + IQ range and
who were matched on age, IQ and language ability. They found no group differences in the
inclusion of gist elements or the proportion of basic story elements recalled (although
there were group differences in causal connectivity). Similarly, Lee et al. (2018) found
no group differences in the inclusion of story grammar elements between autistic and TD
adults (the groups differed on verbal IQ so this variable was controlled in the analyses).
Nonetheless, others have described differences in the inclusion of story elements between
autistic and non-autistic groups (Banney et al., 2015; Goldman, 2008; Losh & Capps, 2003;
see also Pearlman-Avnion & Eviatar, 2002, although groups in this study were not matched
for language); found differences in the types of information produced (e.g., reductions in
the preponderance or amount of ‘gist’ rather than ‘detail’ information: Barnes & Baron-
Cohen, 2012; McCrory et al., 2007); or reported group differences in a combined meta-
analysis of relevant studies (Baixauli et al., 2016). In evaluating previous research into
narrative coherence in individuals on the autism spectrum, several difficulties emerge.
First, studies have used different elicitation methods, ranging from wordless picture
books (Losh & Capps, 2003), to describing autobiographical memories (King et al., 2013),
to recalling sections from television programmes (Barnes & Baron-Cohen, 2012) or making up
a story to an ambiguous picture (Lee et al., 2018). Only one study assessing narrative
coherence in autistic individuals has looked at eyewitness memory (Pearlman-Avnion &
Eviatar, 2002, using a narrated slide show), which is a more realistic everyday
remembering task. In the current study, a secondary analysis of the story grammar elements
produced in witness transcripts collected in a previous study of autistic and non-autistic
children (Henry, Messer et al., 2017) is presented. Second, the approach to matching has
differed. Some studies have matched for chronological age, intelligence (IQ – usually
verbal but sometimes non-verbal), and one or more aspects of language ability (e.g.,
Banney et al., 2015); others have used more than one comparison group (e.g., with matching
for chronological age and IQ and language ability and IQ, King et al., 2013); and others
have matched on some but not all of these variables (e.g., Capps et al., 1998, 2000;
Norbury & Bishop, 2003; Tager-Flusberg & Sullivan, 1995; Young et al., 2005). It may be
difficult to match on multiple indices, particularly if language ability is included,
given the heterogeneity and variability of language skills found in autistic individuals
(Kwok, Brown, Smyth, & Oram Cardy, 2015; Taylor, Maybery, & Whitehouse, 2012). Indeed,
some studies do not attempt to do so (Goldman, 2008) or control key variables
statistically (Lee et al., 2018). In the present study, all available participants were
included from the larger study who could be matched on age, IQ and one aspect of language
(receptive vocabulary), although other aspects of language ability varied significantly
between groups. This provided a test of narrative skill in autistic children who were
similar in age, intellectual ability and receptive vocabulary to a comparison group of
non-autistic children. Finally, there are few studies with larger sample sizes. The
current sample size (52 autistic children, 52 TD children) was larger than in previous
studies, and a conservative significance level was used to account for multiple group
comparisons (see Banney et al., 2015). We also measured the length of the transcripts in
terms of total number of words, and their semantic diversity in terms of number of
different words. This is important, as although many previous studies have found no
significant differences between autistic and typical individuals in story length or
semantic diversity, albeit using slightly varying measures (Banney et al., 2015; Diehl et
al., 2006; Losh & Capps, 2003; McCabe et al., 2013; Norbury & Bishop, 2003; Tager-Flusberg
& Sullivan, 1995; Young et al., 2005), there are some reports of differences (Baixauli et
al., 2016; Capps et al., 2000; King et al., 2013; Lee et al., 2018). Finally, we included
preliminary correlational analyses between story grammar measures and other cognitive and
language variables, although few relationships were expected given limited findings in
previous research (Banney et al., 2015). Matching TD and autistic groups on several
indices including age, IQ and receptive language level may minimise differences in
narrative performance. Therefore, it was hypothesised that there would be no significant
differences between the groups with regard to the number and diversity of ‘story grammar’
elements included in their accounts. We also tentatively predicted no significant
differences in overall length or number of different words.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The data used in this project were taken from interviews carried out as part of a larger
study conducted by Henry, Messer et al. (2017), which compared eyewitness memory skills in
children with and without autism diagnoses. The original study included 272 participants
(162 boys and 110 girls, aged between 76 months and 142 months). Of these children, 71 had
a formal diagnosis of autism, obtained independently of the research study by a suitably
qualified professional. Children were recruited from mainstream primary schools or special
educational needs schools in Greater London or South-East England. Selecting a meaningful
comparison group for studies of children on the autism spectrum is not straightforward
when discrepant ‘peaks and valleys’ represent a common cognitive profile (Burack, Iarocci,
Flanagan, & Bowler, 2004). We tried to avoid ‘over-matching’ where statistical bias is
accidentally caused by matching for what is believed to be a confounding variable but is
actually a core feature of the autism profile. Burack et al. (2004) advise matching on a
subset of features, but caution against matching ‘out’ the key features of autism. In line
with previous literature, matching was carried out for age, IQ and one measure of language
(receptive vocabulary). Receptive vocabulary was selected following Goldman (2008), who
reported non-significant differences in receptive vocabulary scores in their samples,
together with substantial differences on two subtests from a broader language battery (the
Clinical Evaluation of Language Fundamentals, CELF-4 UK, Semel, Wiig, & Secord, 2006). All
children who recalled at least three items of correct information in their interview
accounts of the witnessed event were eligible for inclusion (three children were excluded
at this stage: two autistic, one TD). Individual matches within +/- 10 points for both IQ
and receptive vocabulary and +/- 6 months for age were hand selected. The resulting sub-
sample comprised: 104 children (52 in the TD group, and 52 in the autism group) matched on
age, IQ and receptive language ability. There were 83 boys and 21 girls (TD group: 38 boys
and 14 girls; autism group: 45 boys and 7 girls). It was not possible to match the groups
exactly on gender, as the autism group in the original sample included a high proportion
of males (62 boys and 9 girls). The composition of the current sample reflects the wider
autistic population, where males are estimated to outnumber females (Loomes, Hull, &
Mandy, 2017). Table 1 provides mean scores on all background variables. Mervis and Klein-
Tasman (2004) suggest that for groups to be well-matched, the group distributions on the
control variable in question should overlap, with a p-level of at least .50 on the test of
mean differences. An independent samples t-test was used to compare the groups, as these
data were normally distributed. On all three indices, age, IQ and receptive vocabulary,
the groups were closely matched (see Table 1). Data are also reported on other measures of
language, memory and attention (not matched between groups), as well as the total number
of correct items of information recalled in the initial interview (see Table 1). Mirroring
the original study findings (Henry, Messer et al., 2017), the groups differed in the
number of correct details recalled about the witnessed event (Table 1), with autistic
children (M = 25.71, SD = 14.37) recalling fewer correct details than TD children (M =
33.42, SD = 14.24), t(102)=-2.75, p = .007. However, the analyses of story grammar
elements and length/diversity of narratives did not focus solely on correct details, but
included the full transcripts for all children.

<hs>  Measures</hs>
  ~~~~~~~~

Participants’ intellectual abilities were assessed in the original study using the
Wechsler Abbreviated Scale of Intelligence (WASI-II; Wechsler & Zhou, 2011). An estimate
of full-scale IQ was obtained using ‘Vocabulary’ from the Verbal Comprehension Index and
‘Matrix Reasoning’ from the Perceptual Reasoning Index. As noted, following matching, the
groups did not differ on this measure. Language level of participants was measured using
several tasks from the original study. Receptive vocabulary was assessed using the British
Picture Vocabulary Scale - Third Edition (BPVS-3; Dunn, Dunn, & Styles, 2009), which
requires children to select the correct picture from a choice of four upon hearing a word
spoken. Two subtests from the Expressive Language Test - 2 (ELT-2; Bowers, Huisingh,
Logiudice, & Orman, 2010) included: ‘Sequencing’, to test narrative ability, and ‘Grammar
and Syntax’, to test grammatical morphology. A further two subtests were taken from the
Clinical Evaluation of Language Fundamentals - 4th edition (CELF-4 UK; Semel et al.,
2006). ‘Recalling Sentences’ assesses the ability to accurately repeat sentences using
internalised grammatical structure, and ‘Formulated Sentences’ assesses the ability to
produce full, grammatically accurate, and meaningful sentences about picture stimuli. When
compared on the language measures, the two participant groups were well-matched on
receptive vocabulary ability (BPVS), as expected (Table 1), with no significant difference
between the autism and TD groups. However, significant group differences (or marginal
differences) remained in scores on the other language measures (ELT-2 ‘Sequencing’; ELT-2
‘Grammar and Syntax’; CELF-4 ‘Recalling Sentences’; CELF-4 ‘Formulated Sentences’). An
assessment of general memory ability from the Test of Learning and Memory (2nd Edition,
TOMAL-2, Reynolds & Voress, 2007) included: Memory for Stories; Paired Recall; Facial
Memory; and Visual Sequential Memory. Table 1 includes composite scores for the Verbal
Memory Index, on which groups did not differ, and the Nonverbal Memory Index, on which the
autistic children obtained lower scores than the TD children (although no differences were
present on the combined Composite Memory Index). Three assessments of focused, sustained
and sustained-divided (dual task) attention completed the test battery (Sky Search; Score!
; and Sky Search Dual Task from the Test of Everyday Attention for Children, TEA-Ch,
Manly, Robertson, Anderson, & Nimmo-Smith, 1999). There were no group differences on the
attention measures.

<hs>  Materials and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Ethical approval for the original study and the present secondary data analysis study was
granted by the Research Ethics Committees of the universities at which the research took
place. All parents or guardians provided informed written consent for their children to
take part. The original research study involved data being collected from both TD and
autism groups across several phases, in a manner intended to replicate the processes
involved in gathering evidence from eyewitnesses in the criminal justice system (evidence
gathering statements, investigative interviews, identification line-ups, cross-
examinations). Only the first set of interview data (evidence gathering statements, or
‘Brief Interviews’) administered on the same day as the event was witnessed, are relevant
to the current paper. These initial questions about the event were included to mimic a
response officer’s initial contact with a witness. The procedure used in this phase of the
study is summarised briefly below. For a more detailed description, please see Henry,
Messer et al. (2017).

        <hss>Experimental procedure</hss>

        Participants were shown a staged event, featuring two actors who gave a short
        presentation about what school was like in Victorian times. For practical and
        logistical reasons, this was either viewed live during a school assembly, or a
        video of the performance was shown to the children. There were no recall
        differences between live and video presentation for autistic or TD children
        (Henry, Messer et al., 2017) so these data were combined. The talk consisted
        mainly of facts about Victorian schools, but involved a staged minor crime, where
        either a phone or a set of keys was ‘stolen’ by one of the actors (the ‘theft’ was
        later explained as a misunderstanding). Participants were randomly assigned to one
        of two versions of the talk, which were virtually identical but used different
        materials and gave alternative names to the actors. The rationale was to give some
        indication of the generalisability of the results. As there were no differences
        between versions, data were collapsed over this variable (Henry, Messer et al.,
        2017). After viewing the staged event, participants were interviewed individually
        on the same day. Interviewers used a standard protocol with an initial question
        designed to elicit a free recall account (‘Tell me what you remember about what
        you just saw’). This was followed by a series of open-ended questions that could
        be used to prompt further information depending on the child’s response (e.g. ‘Who
        was there?’ ; ‘What did they do?’). Finally, participants were asked if they could
        remember anything else. This final prompt was repeated until the child could no
        longer provide any new items of information. Interviews were audio-taped and
        transcribed, then coded by two independent coders according to the narrative
        frameworks described below. The coders were blind to group status.

        ‘Story grammar’ narrative analysis

        The story grammar framework developed by Murfett et al. (2008) was used to analyse
        participants’ accounts by tallying the number of narrative features included.
        ‘Correctness’ of information in the transcripts was not taken into account, as
        this would not be possible in a real case when jurors and legal professionals are
        unlikely to know what actually happened to a victim/witness. Further, story
        grammar is a ‘framework’ for organising event details and, as such, is scored
        independently of accuracy (Feltis et al., 2011). Seven narrative elements were
        scored: Setting, Initiating event, Internal response, Plan, Action/attempt, Direct
        consequence, and Resolution (see Table 2). Elements were scored based on the
        number of times they appeared in the narrative, regardless of their accuracy
        (e.g., a point would be awarded for setting if the child mentioned the location of
        the event, even if this was incorrect). The total number of story grammar elements
        and the number of different story grammar elements (maximum 7) used were noted.

        <hss>Additional structural measures</hss>

        Two structural measures were hand coded: the total number of words in each
        account, and the total number of different words used (excluding non-word
        utterances such as ‘um’), to obtain a broad comparison of the overall length and
        semantic diversity of the narratives produced by each group.

        <hss>Reliability analyses</hss>

        All transcripts were coded independently by two coders, following discussion to
        agree the coding rules. Intra-class correlation coefficients were calculated to
        assess the reliability of coding, and these indicated good to excellent
        reliability for all but one story grammar element (Direct consequence): Setting:
        ICC = .94; Initiating event: ICC = .83; Internal response: ICC = .81; Plan: ICC =
        .92; Action/attempt: ICC = .82; Direct consequence: ICC = .08; Resolution: ICC =
        .80. For the aggregated story grammar element scores, reliability was also good:
        Total number of grammar elements, ICC = .94; Number of different grammar elements,
        ICC = .93. Intercoder agreement for the word count measures was excellent: Total
        number of words, ICC = 1.00; Number of different words, ICC = 1.00. Given the poor
        agreement for Direct consequence, the first coder looked at the discrepancies in
        coding (coder 2 noted more instances of this element than coder 1) and recoded
        data based on commonalities in coding criteria. After recoding, agreement was much
        higher, ICC = .98. Nevertheless, given the initial discrepancies, we suggest
        caution in interpreting the results for Direct consequence. First coder ratings
        were used for all data analyses.

<h>RESULTS</h>
-------

Table 3 provides means, medians and ranges for each story grammar element and the
structural measures (total number of words, number of different words). As group
comparisons across several areas were conducted, a more stringent significance level (p <
.01) was adopted to limit the chances of incorrectly rejecting the null hypothesis
(recommended by Banney et al., 2015). Data for the structural measures of total number of
words and number of different words were normally distributed, so independent samples
t-tests were performed to compare groups. ‘Total number of words’ showed no significant
difference between groups [t(102)=-1.17, p = .25, d = .23]: TD group (M = 234.46, SD =
111.08); autism group (M = 207.75, SD = 121.72). There was no significant group difference
for ‘Number of different words’ [t(102)=-1.53, p = .13, d = .30]: TD group (M = 97.52, SD
= 31.16); autism group (M = 87.15, SD = 37.67). Given the groups did not differ on overall
length or diversity of their narratives, data on story grammar elements were analysed
using raw scores. Table 3 shows that means and medians for many story grammar elements
were low, with medians of zero in one or both groups for initiating event, internal
response, plan, direct consequence, and resolution. Kolmogorov-Smirnov normality tests
indicated that scores for the story grammar elements and their totals violated the
parameters of normality (either for both groups or one group) on every measure, therefore,
non-parametric tests were used (Mann-Whitney U). There were no significant differences in
the distributions for any of the story grammar elements, or for the total scores [Setting,
U = 1651.5, z = 2.02, p = .04, d = .39; Initiating event, U = 1364, z = .09, p = .93, d =
.02; Internal response, U = 1235, z = -0.88, p = .38, d = .15; Plan, U = 1591, z = 1.88, p
= .06, d = .31; Action/attempt, U = 1340, z=-0.08, p = .94, d = .02; Direct consequence, U
= 1382, z = .21, p = .83, d = .04; Resolution, U = 1587.5, z = 2.19, p = .03, d = .30;
Total number of story grammar elements, U = 1421, z = .50, p = .65, d = .09, Number of
different story grammar elements, U = 1537.5, z = 1.23, p = .22, d = .24]. In many cases,
medians across the two groups were identical (see Table 3). To investigate whether any
background variables related to Total number of story grammar elements or to Number of
different story grammar elements, preliminary Spearman non-parametric correlations were
carried out. For the TD and autism groups, Total number of story grammar elements
correlated with Total correct details recalled in the interview: Autism group r = .71; TD
group r = .79 (ps < .001). Number of different story grammar elements also correlated with
Total correct details recalled in the interview: Autism group r = .76; TD group r = .64
(ps < .001). There were correlations between Total number of story grammar elements and
age in the TD group, which failed to reach significance in the autism group: Autism group
r = .25, p = .07; TD group r = .41, p = .003, and between Number of different story
grammar elements and age in the TD group, which again failed to reach significance in the
autism group: Autism group r = .27, p = .055; TD group r = .41, p = .003. No other
correlations were significant.

<h>DISCUSSION</h>
----------

This study investigated the narrative coherence of eyewitness accounts in autistic and
non-autistic children (6–11 years) matched on age, IQ and receptive language ability. We
replicated a previous finding that autistic children recalled fewer correct items of
information than non-autistic children in a brief interview about a staged event involving
a minor crime, witnessed earlier that day (Henry, Messer et al., 2017). Despite this
difference in volume of correct recall, no significant group differences emerged when a
‘story grammar’ framework was used to assess the presence and number of key story elements
in participants’ accounts (incorporating all information mentioned, whether correct or
not). The findings confirm the utility of previous work using the story grammar framework
to evaluate eyewitness accounts of children with developmental differences (Brown et al.,
2018; Gentle et al., 2013; Murfett et al., 2008), and provide support for claims that
there are relatively few (or no) differences in narrative ability on some tasks between
well-matched groups of autistic and non-autistic children (e.g., Capps et al., 1998, 2000;
Diehl et al., 2006; Losh & Capps, 2003; Norbury & Bishop, 2003; Tager-Flusberg & Sullivan,
1995; Young et al., 2005). On metrics assessing the length in words and semantic diversity
(number of different words) of the accounts, there were also no group differences in
performance. This supports much previous literature (e.g., Banney et al., 2015; Diehl et
al., 2006; Losh & Capps, 2003; McCabe et al., 2013; Norbury & Bishop, 2003; Tager-Flusberg
& Sullivan, 1995; Young et al., 2005). The present findings also suggest that, although
children on the autism spectrum may recall fewer items of correct information about an
event, their overall narrative accounts are not shorter or less semantically diverse, nor
are they less coherent in terms of narrative structure. Taken together with findings that
eyewitness accuracy in autistic children is generally as high as in comparable non-
autistic children (2017b, Almeida et al., 2019; Bruck et al., 2007; Henry, Messer et al.,
2017; McCrory et al., 2007; although accuracy levels may vary with interview type – see
Mattison et al., 2018), the present results provide further evidence for the overall
reliability of autistic child witnesses. Narrative coherence adds important information,
because it may affect the degree to which members of the criminal justice system
understand a child’s evidence. This could be via impacting on how meaningful and credible
the child appears to jurors (2011, Brown et al., 2018; Feltis et al., 2010; Gentle et al.,
2013; Murfett et al., 2008), helping the police to establish relevant 'points to prove',
and/or contributing to decisions by the Crown Prosecution Service about whether or not to
authorise charges. The most commonly included story grammar element in children’s
narratives related to descriptions of what happened in the event (i.e., Action/attempt
details, Mdn = 5.5 autism group; Mdn = 6.0 TD group). This confirms previous observations
that Action/attempt details are the most commonly elicited story grammar element. Feltis
et al. (2011) found about 50 % of story grammar elements in immediate recall were
Action/attempt details, close to the 60–65 % recorded in the current study. Nearly all
other story grammar elements had median scores at or close to zero, indicating that
children in the current age range (6–11 years) often omitted several story grammar
elements. For Setting details, the median score of 2 items in both groups indicated that
many children included information about where and when the event took place (see also
Westcott & Kynan, 2004). However, the median number of types of story grammar elements
included was only 3 out of a possible 7, underlining the fact that maturation in narrative
coherence was not complete in the current sample of 6–11 year old children. Further
research should assess narrative coherence in witness accounts of older children who
include more story grammar elements, to negate the possibility that low scores on some
measures reduced our ability to detect group differences. Nevertheless, group differences
on story grammar measures with higher scores (e.g. total scores, action/attempt) were
still absent, increasing confidence in the findings. Although autistic (relative to
matched non-autistic) children produced narratives of similar coherence (based on an
analysis of story grammar elements), length (based on number of words) and semantic
diversity (based on number of different words), the type of narrative task is important.
Losh and Capps (2003) noted that experimental findings may not reflect children’s
narrative competence “within the less structured and more socially demanding contexts of
daily life” (p.248). In the same way that wordless picture book tasks may reduce cognitive
demands of storytelling by scaffolding memory, attention, story organisation and language
production using temporally sequenced visual cues, adult-led interviews are structured
interactions in which specific narrative features may be prompted through direct questions
(e.g., ‘Where did this happen?’). This is not necessarily typical of how children’s
narratives are produced in real conversational exchanges, although it does reflect how
forensic interviews might proceed (although note that we did not use full investigative
interviews, which would usually occur later than the ‘same-day’ brief evidence gathering
statements used in the current study). Further, since autistic children often experience
difficulties with emotional regulation (Samson et al., 2014), they might perform less well
when describing a ‘real’ witnessed event, particularly if it induced heightened emotions
or distress. Therefore, caution is required when generalising the current findings to more
emotionally charged situations such as are likely to be encountered in criminal
investigations. Finally, as the current groups were matched on age, general ability and
one aspect of language (receptive vocabulary), it is important to note that the findings
could be different in less closely matched samples. Preliminary correlational analyses
assessed whether background age and cognitive measures related to the number or diversity
of story grammar elements included in children’s accounts. Correlations between both of
these measures and the number of correct details recalled in the interview suggested that
volume of correct recall is a good indicator of the extent to which both autistic and TD
children include key story elements. Higher volume of recall, better structure and greater
narrative coherence could all have an impact on the credibility of a witness before jurors
(see also Henry, Ridley, Perry, & Crane, 2011). The relationships between number and
diversity of story grammar elements and age (significant only in the TD group) confirmed
the known developmental improvements in the use of story grammar elements (Feltis et al.,
2011).

<hs>  Summary</hs>
  ~~~~~~~

This study investigated the narrative skills of 52 autistic children aged 6–11 years (IQs
70+), comparing them to 52 TD peers matched on age, IQ and receptive language ability.
Participants had been interviewed using open-ended prompts shortly after viewing a staged
mock crime event, and interview transcripts were coded using existing analytical
frameworks for narrative features (story grammar elements; narrative length; semantic
diversity). There were no significant differences between the autism and TD groups in
terms of narrative skills on any of these measures. The findings add to, and extend,
previous reports that when children on the autism spectrum are well-matched to peers with
TD on cognitive and some language measures, they exhibit a similar level of narrative
skill. The current findings also attest to the comparability of autistic and non-autistic
child witnesses in terms of accuracy, account length and narrative coherence, if not in
volume of correct information recalled.


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<ART>The personality of U.S. states: Stability from 1999 to 2015
===========================================================

Authors: Lorien G. Elleman, David M. Condon, Sarah E. Russin, William Revelle
DOI: 10.1016/j.jrp.2016.06.022
Year: 2018  |  Pages: 64-72
ASJC codes: 3200, 3207
Keywords: Aggregate personality, Big Five, Online personality assessment, Personality of U.S. states, Regional differences, Replication, Scale generalizability, Sociodemographic

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Researchers have shown an interest in the aggregated Big Five personality of U.S. states, but typically they have relied on scores from a single sample (Rentfrow, Gosling, & Potter, 2008). We examine the replicability of U.S. state personality scores from two studies (Rentfrow et al., 2008; Rentfrow, Gosling, Jokela, & Stillwell, 2013) across a total of seven samples, two of them new. Same-trait correlations across samples are, on average, positive for all five traits, indicating score agreement. Additionally, three traits (Conscientiousness, Neuroticism, and Openness) show strongly consistent patterns of correlations with sociodemographic variables across samples. We find rank order stability in state personality scores for a 16-year period (1999–2015).

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The beginning of the twenty-first century has seen an explosion of interest concerning
geographical variation in personality within the United States. Before the modern era of
the internet, there were a few studies that examined aggregate psychological differences
by U.S. cities or regions (e.g., Krug & Kulhavy, 1973; Thorndike, 1939). However, with the
widespread adoption of the internet in the U.S., several psychology labs have collected
samples of hundreds of thousands of participants across the country via online personality
assessments (e.g., Revelle, Wilt, & Rosenthal, 2010; Revelle et al., 2016; Srivastava,
John, Gosling, & Potter, 2003). These samples, although not representative of the U.S.
population, are more diverse than traditional methods of data collection (Gosling, Vazire,
Srivastava, & John, 2004). They also have enough statistical power for analyses to detect
small effects between a large number of regional groups. These online assessments
typically use self-report personality assessment models based on the Big Five (Goldberg,
1990), a widely-accepted taxonomy that organizes most individual differences into five
broad traits: Conscientiousness, Agreeableness, Neuroticism (sometimes referred to by its
polar opposite, Emotional Stability), Openness (sometimes called Intellect), and
Extraversion. Studies that have used the state scores data from Rentfrow et al. (2008)
have assumed that these state scores were representative of the actual personality scores
of the states’ residents. For example, these studies assumed that the Extraversion score
for Oklahoma accurately represented the mean Extraversion score of all Oklahomans. This
assumption could be problematic for at least three reasons. First, these state scores,
although based on many participants, are not immune to sampling bias. Idiosyncratic
methods of participant selection could lead to a lack of replication in other samples.
Second, even if the original scores were accurate, the personality of some states’
residents may have changed since the original study’s data were collected (1999–2005).
Third, Rentfrow et al. (2008) measured personality with the Big Five Inventory (BFI; John
& Srivastava, 1999). The ranks and standardized scores from Rentfrow et al. (2008) may not
generalize across other measures of the Big Five. Therefore, it is useful to examine the
extent to which the state-level scores of Rentfrow et al. (2008) will replicate, and to
estimate the effect of disagreement attributable to differences in participant recruitment
methods, change over time, and Big Five measures. Additionally, because these state scores
are often reused in other studies, it is critical to determine the extent to which
correlations between state personality and sociodemographics replicate in spite of
differences in samples. A study dedicated to replicating Rentfrow et al. (2008) has not
yet been reported. Rentfrow, Gosling, Jokela, and Stillwell (2013) compared state scores
across five samples, including the sample from Rentfrow et al. (2008). Details from this
effort were brief because the focus of the paper concerned the personality profiles of
broad regions of the U.S. Findings were not thoroughly discussed, and many of the results
were relegated to the supplemental materials. However, their analyses indicated that
“there were no clear or consistent statewide differences in any of the scale properties,”
and state scores were “reliable and generalizable” (Rentfrow et al., 2013, p. 1003). The
study also found that in general, the same traits correlated with the same
sociodemographic variables at similar magnitudes across the five samples. The current
study used the five samples reported from Rentfrow et al. (2013) and added two new large
samples. The goals of the study were as follows: One, for a point of comparison with
Rentfrow et al. (2013), determine the extent to which the two replication samples were
representative of U.S. states (Section 3.1). Two, across all samples, estimate the
reliability of state score differences by evaluating their intraclass correlations
(Section 3.2). Three, estimate the effect size of same-trait convergent correlations
across all samples for each Big Five trait (Section 3.3). Within this goal, estimate the
separate effects of three possible sources of attenuation: differences due to recruitment
methods (Section 3.3.1), time of data collection (Section 3.3.2), and personality
inventories (Section 3.3.3). Four, from these estimates, determine whether the personality
of U.S. states had maintained rank order stability (i.e., relative to each other, states’
personalities did not change) from 1999 to 2015 (Section 3.3.4). And finally, determine
the replicability of correlations between state-level personality scores and
sociodemographic variables (Section 3.4).

<hs>  Samples 1–5</hs>
  ~~~~~~~~~~~

Samples 1–5 were originally analyzed in Rentfrow et al. (2013). The samples were collected
during different time periods, as part of different research projects, using different
personality inventories (Table 1). All five samples had aggregate measures of personality
based on Likert-type scales for the 48 contiguous states, as well as Washington, DC. In
total, the samples were collected over an 11-year period (1999–2010), with a range in
sample size from 18,182 to 612,140. Samples 1–4 were online personality assessments that
used self-selecting participant recruitment. Sample 5 was an online assessment that used a
recruitment method similar to random digit-dialing to select a representative sample of
registered voters. A more detailed summary of Samples 1–5 can be found in Rentfrow et al.
(2013), where each sample is referred to by the same name used in this study. Through
correspondence with Rentfrow, we received participant counts and unadjusted mean scores
for states, for each sample. Other data on the five samples, such as interclass
correlations, were collected from Rentfrow et al. (2013) and the supplemental materials.

<hs>  SAPA samples</hs>
  ~~~~~~~~~~~~

The last two samples were from the Synthetic Aperture Personality Assessment (SAPA)
project, an online non-commercial personality assessment (https://sapa-project.org;
Revelle et al., 2016). For their participation, participants received feedback concerning
their personality. Each sample covered an approximate five-year period of time and was
named for the last year in which data were collected. The SAPA2010 sample was collected
from April 2006 to August 2010. The SAPA2015 sample was collected from August 2010 to
December 2015 (Table 1).

        <hss>Participants</hss>

        Participants were screened to ensure that entries beyond their first were not
        included in the analysis. Duplicate entries taken in a single internet browser
        session were removed. Participants who reported having previously taken the
        assessment also were excluded. Since this study was concerned with state-level
        analysis, it was also necessary to remove participants who reported not being from
        one of the 50 U.S. states or Washington, DC. Concerning educational attainment,
        40% of the SAPA2010 sample reported being an undergraduate at the time of
        assessment, while 28% had attained at least a bachelor’s degree. In the SAPA2015
        sample, 51% were current undergraduates, while 27% had attained at least a
        bachelor’s degree.

        <hss>Personality measures</hss>

        Most online personality assessments give every participant the same fixed set of
        items. Researchers typically analyze complete cases or use mean scores to impute
        the small amount of missing data. The SAPA project is radically different in this
        regard; participants receive a random sample of items from a pool of personality,
        cognitive ability, and interest inventories. Although items given within an
        inventory are random, sampling rates of inventories differ based on research goals
        of the SAPA project’s collaborators (Revelle et al., 2010, 2016). In this study,
        all of the personality items in the SAPA samples were from the International
        Personality Item Pool (IPIP; http://ipip.ori.org/), an online repository for
        public domain personality items and inventories (Goldberg, 1999; Goldberg et al.,
        2006). We assessed participants on these items using a 1–6 Likert-type scale (1 =
        “Very inaccurate”; 6 = “Very accurate”). The sole Big Five personality measure in
        the SAPA2010 sample was the Big Five Factor Markers (BFFM), a 100-item IPIP
        personality inventory based on the Goldberg (1992) conception of the Big Five. On
        average, participants took 48 BFFM items (48% of the inventory). In the SAPA2015
        sample we examined four measures of Big Five personality. The first was the BFFM.
        On average, participants took 30 BFFM items (30% of the inventory). The second
        personality measure was the IPIP-NEO, a 300-item IPIP inventory based on the NEO-
        PI-R conception of the Big Five (Costa & McCrae, 1992). On average, participants
        took 26 IPIP-NEO items (9% of the inventory). The third personality measure was
        the SAPA Personality Inventory (SPI), a 75-item inventory of IPIP items in which
        Condon (2014) determined the “best” items for the Big Five through empirical
        analyses. On average, participants took 11 SPI items (15% of the inventory). The
        last measure in the SAPA2015 sample was the IPIP-HEXACO (Ashton, Lee, & Goldberg,
        2007), a 240-item IPIP inventory based on the six-factor HEXACO framework, which
        adds the Honesty-Humility trait to the Big Five (Lee & Ashton, 2004). On average,
        participants took 26 IPIP-HEXACO items (11% of the inventory). The BFFM was
        considered to be the primary measure of personality in the SAPA2015 sample because
        participants took the most items from the inventory, both in terms of raw number
        and percent of total items in the inventory. However, an analysis in Section 3.3.3
        utilized all the above personality measures of the SAPA2015 sample. In Section
        3.2, two additional measures in the SAPA2015 sample were examined: the IPIP-NEO
        10-item Openness facet of Liberalism, and the 60-item ICAR (International
        Cognitive Ability Resource) measure of cognitive ability (Condon & Revelle, 2014).
        On average, participants took 2 Liberalism items (20% of the inventory) and 14
        ICAR items (23% of the inventory).

        <hss>U.S. Census Bureau data</hss>

        In order to weight correlations and determine the representativeness of SAPA
        samples, four measures from the 2010 U.S. Census were used: state populations
        (United States Census Bureau, 2015), state populations by ethnicity (United States
        Census Bureau, 2014), state populations by age (United States Census Bureau, 2016)
        and state populations by adult education (United States Census Bureau, 2016).

        <hss>Sociodemographic measures</hss>

        Thirteen state-level sociodemographic measures were selected to cover a similar
        breadth of criteria as reported in previous studies (Rentfrow et al., 2008, 2013).
        All sociodemographic measures analyzed were either per capita or percentage of
        state residents. There were two measures of physical health in 2008: cancer deaths
        (American Cancer Society, 2008) and heart disease deaths (Miniño, Murphy, & Xu,
        2011); two measures of crime in 2008: violent crime and property crime (Federal
        Bureau of Investigation, 2009); four measures concerning adult employment by job
        fields in 2009: “arts, design, entertainment, sports, and media,” “business and
        financial,” “computer and mathematical science,” and “healthcare practitioner and
        technical” (Bureau of Labor Statistics, 2009); one measure of innovation: the
        number of patents issued in 2008 (United States Patent & Trademark Office, 2009);
        two measures regarding beliefs in 2008: self-identified political liberals and
        people who responded affirmatively to the question, “Is religion an important part
        of your daily life?” (Gallup, 2014); and two measures of well-being in 2013: an
        index of overall well-being and self-reported community recognition in the past 12
        months (Gallup, 2016).

<h>RESULTS</h>
-------

Individual personality scores in the SAPA samples were calculated using the simple mean of
the observed items. State personality scores were then found by aggregating individual
personality scores. State-level scores for the SAPA2010 and SAPA2015 samples, as well as a
sample that combines the two, are available in Tables 6–8 of the supplemental materials.
Each mean of correlations was calculated by converting correlations to z-scores,
determining the mean, and transforming the mean z-score back into a correlation. Analyses
were performed in the psych (Revelle, 2016) package and displayed using the psych and
corrplot (Wei, 2013) packages in the R statistical system (R Core Team, 2016). Despite
large individual sample sizes, aggregating personality decreased the number of
“participants” to the number of states (51 in Section 3.1; 49–51 in Section 3.2; 49 in
Section 3.3; and 48 in Section 3.4). In the case of 48 participants, a conventional
criterion for statistical significance (p < .05) would require rs > ∣.28∣. Multiple
comparisons were analyzed, which typically requires one to set an even higher threshold
for statistical significance, in order to protect against an increased probability of
finding a “significant” correlation by chance. We focused on patterns and means of
correlations when possible because the standard error of a mean correlation decreases with
the square root of the number of correlations that go into the mean.

<hs>  Reliability of state differences: individual and group variation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Just as small effects can be “statistically significant” in large samples, a small ICC1
and a large average group size will produce a large ICC2. James (1982) suggested using
ICC1 as a criterion for aggregation. It would be unrealistic to expect that most of an
individual’s personality would be due to state residence. However, studying the
personality of states presumes that a non-trivial amount of individual variance in
personality is explained by state variance in personality.

<hs>  Same-trait convergent correlations for state-level personality scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Each mean same-trait correlation was a composite of 21 correlations between pairs of the
seven samples (Fig. 1). Samples differed in terms of their personality inventory,
participant recruitment related to underlying research project, and the time period in
which they were collected (Table 1). Any one of these differences could have led to
attenuation of a same-trait correlation.2 We grouped correlations by these three
differences to determine whether any of them were related to attenuation in same-trait
correlations (Table 4). Where possible, we estimated the effect of one type of difference
by only evaluating correlations whose samples differed in that one way.

<hs>  Replicability of state personality correlations with sociodemographics</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Weighted correlations (as described in Section 3.3) between personality scores of the
seven samples and the thirteen sociodemographic variables were partialled, controlling for
the other four personality scores within a sample (Tables 1–5 in the supplemental
materials). These partial correlations were limited to the 48 contiguous states due to
limitations of the secondary data.

<h>DISCUSSION</h>
----------

State differences in Big Five personality may be used to predict important
sociodemographic outcomes. These results replicate for three personality traits
(Conscientiousness, Neuroticism, and Openness) across sampling methods, time periods, and
personality inventories. In terms of agreement of scores across samples, same-trait
correlations were highest for Neuroticism and Openness, but correlations for all five
traits were positive, on average, indicating that state scores were somewhat robust. In
Section 3.2, we showed that most of the personality variation was within states (small
ICC1s), but between-state variation was still very reliable (large ICC2s). By the standard
statistical criterion of “variance explained,” states appeared to be a poor candidate for
grouping personality. The two replication samples were representative in terms of state
populations and ethnicity within a state, were less representative of how educated states
were, and were not representative of age groups within states. These representative
analyses were similar to findings concerning the five samples from a previous study
(Rentfrow et al., 2013). There are at least three reasons why Extraversion and
Agreeableness were not found to have replicable correlations with sociodemographics.
First, perhaps suboptimal sociodemographic measures were selected. Future studies might
find that state-level Agreeableness and Extraversion have large, replicable correlations
with sociodemographic measures not included in this study. While this is a possibility,
several of the sociodemographic variables were selected based on previous research that
showed moderate correlations with Agreeableness (crime and religiosity) and Extraversion
(crime and business occupations). Second, the current study found that Agreeableness had a
restricted range of correlations with the selected sociodemographic variables, which could
indicate that correlations of a large magnitude are required to ensure replication at the
state level. A third possible reason for lack of replicability is that lower-level facets
within the traits differentially correlated with the sociodemographic variables. Rentfrow
(2014) found that when Extraversion was split into two lower-level facets and correlated
with six social indicators, the signs of the correlations were consistently opposite for
the facets. Combining these kinds of opposing facets into a higher-level trait would
result in the trait having smaller correlations and/or an inconsistent pattern of
correlations with sociodemographic variables across samples. Future research should
examine whether novel sociodemographics correlate more highly with Agreeableness and
Extraversion, as well as whether facets within some traits differentially correlate with
certain sociodemographic measures. Researchers interested in the links between personality
and geography may find new, important insights by examining personality constructs outside
or at a lower level than the Big Five traits. Preliminary evidence in this paper indicated
that state residence accounted for more total variance in cognitive ability and Liberalism
than the Big Five. Additionally, for correlational analyses with sociodemographic
variables, the level of a personality characteristic should match the level of a
sociodemographic variable (Wittmann, 1988). That is, it may be more theoretically
appropriate to correlate certain sociodemographic variables with facets instead of the Big
Five. In a similar way that personality constructs like the Big Five may be too broad in
the study of geographical personality, geographical constructs may also be too broad.
States may not be the optimal level for discovering geographical differences in
personality. States share a common government, but they often cover large areas, and state
lines can be arbitrary when grouping people by personality. For example, would we expect
the personality of Paris, Illinois, a town of less than 10,000, to be more like
Versailles, Indiana, or Chicago, Illinois? Both are roughly equidistant from Paris, but
one is a town of less than 3000, and the other is the most populous city in the Midwest.
Chicago is in the same state as Paris, so a state-level analysis would group both together
and contrast them against another group comprised partly of Versailles and Indianapolis.
It could be valuable for future research to compare the effect size of state aggregation
to other regional groups, such as counties, metropolitan areas, cities, and neighborhoods.
Personality scores aggregated by geographical regions could prove to be invaluable to
researchers interested in exploring macro-level relationships between patterns of human
behavior, environment, and social outcomes. These scores would represent static measures
for these regions like any other sociodemographic variable. For example, one could imagine
a scenario in which the Extraversion of Illinois in 2020 would be a matter of public
record in the same way that its population will be. Self-reported personality items have
components of affect, behavior, cognition, and desire (Wilt & Revelle, 2015) and are
presumed to reflect observable patterns in the real world. Having aggregate measures of
these complex processes could help researchers to better understand mechanisms that drive
important outcome patterns, such as rates of obesity, mental illness, crime, and well-
being. In order for these scores to be trustworthy, however, they need to represent the
population, aggregate individual variance, be reliably different, agree across samples,
and have a consistent pattern of correlations with sociodemographic measures.


<h>REFERENCES</h>
----------

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  [8] Robert de Vries, Samuel Gosling, Jeff Potter. Income inequality and personality: Are less equal U.S. states less agreeable?. doi:10.1016/j.socscimed.2011.03.046
  [12] Lewis R. Goldberg. An Alternative "Description of Personality": The Big-Five Factor Structure. doi:10.1037/0022-3514.59.6.1216
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  [15] Lewis R. Goldberg, John A. Johnson, Herbert W. Eber, Robert Hogan, Michael C. Ashton, C. Robert Cloninger, Harrison G. Gough. The international personality item pool and the future of public-domain personality measures. doi:10.1016/j.jrp.2005.08.007
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  [17] Jesse R. Harrington, Michele J. Gelfand. Tightness-looseness across the 50 united states. doi:10.1073/pnas.1317937111
  [18] Lawrence R. James. Aggregation bias in estimates of perceptual agreement. doi:10.1037/0021-9010.67.2.219
  [20] Samuel E. Krug, Raymond W. Kulhavy. Personality differences across regions of the united states. doi:10.1080/00224545.1973.9922648
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<ART>The psychological roots of intellectual humility: The role of intelligence and cognitive flexibility
================================================================================

Authors: Leor Zmigrod, Sharon Zmigrod, Peter Jason Rentfrow, Trevor W. Robbins
DOI: 10.1016/j.paid.2019.01.016
Year: 2019  |  Pages: 200-208
ASJC codes: 3200
Keywords: Cognition, Cognitive flexibility, Humility, Intellectual humility, Intelligence, Interaction

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Intellectual humility has been identified as a character virtue that allows individuals to recognize their own potential fallibility when forming and revising attitudes. Intellectual humility is therefore essential for avoiding confirmation biases when reasoning about evidence and evaluating beliefs. The present study investigated the cognitive correlates of intellectual humility. The results indicate that cognitive flexibility, measured with objective behavioural assessments, predicted intellectual humility. Intelligence was also predictive of intellectual humility. These relationships were particularly pronounced for the facets of intellectual humility associated with respect for opposing opinions and openness to revising one's attitudes in light of new evidence. The data revealed an interaction: high cognitive flexibility is particularly valuable for intellectual humility in the context of low intelligence, and reciprocally, high intelligence was beneficial for intellectual humility in the context of low flexibility. Notably, there was evidence of a compensatory effect, as participants who scored highly on both flexibility and intelligence did not exhibit superior intellectual humility relative to individuals who scored highly on only one of these cognitive traits. These findings are suggestive of dual psychological pathways to intellectual humility; either cognitive flexibility or intelligence are sufficient for high intellectual humility, but neither is necessary.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

In an era of polarization, fake news, and the wide spread of misinformation, there is a
strong public need for an understanding of how citizens can inoculate themselves against
deception and inaccurate information. The capacity to critically evaluate information in
nonbiased ways requires intellectual humility – the understanding of one's limitations and
biases when making evidence-based decisions. Intellectual humility allows us to avoid
psychological tendencies to overlook evidence and confirm prior beliefs. Specifically,
intellectual humility has been defined as “recognizing that a particular personal belief
may be fallible, accompanied by an appropriate attentiveness to limitations in the
evidentiary basis of that belief and to one's own limitations in obtaining and evaluating
relevant information” (Leary et al., 2017). Over the last decade, a substantial literature
has emerged in philosophy, theology, and psychology, seeking to (a) define intellectual
humility (Baehr, 2011; Davis et al., 2016; Gregg, Mahadevan, & Sedikides, 2017; Roberts &
Wood, 2003; Samuelson et al., 2015; Whitcomb, Battaly, Baehr, & Howard-Snyder, 2015;
Wright et al., 2017), (b) develop measurement tools (Hoyle, Davisson, Diebels, & Leary,
2016; Krumrei-Mancuso & Rouse, 2016; Leary et al., 2017; McElroy et al., 2014; Meagher,
Leman, Bias, Latendresse, & Rowatt, 2015), and (c) link intellectual humility to other
personality traits such as openness (McElroy et al., 2014; Porter & Schumann, 2018; Leary
et al., 2017), prosociality (Krumrei-Mancuso, 2017), dispositional attachment orientation
(Jarvinen & Paulus, 2017), and religiosity and religious tolerance (Hopkin, Hoyle, &
Toner, 2014; Hook et al., 2017; Krumrei-Mancuso, 2018; Leary et al., 2017; Rodriguez et
al., 2017; Van Tongeren et al., 2016; Zhang et al., 2018). So far, research on the
psychological roots of intellectual humility has been primarily the concern of social and
developmental psychology. In theorising about the cognitive mechanisms that might underlie
intellectual humility, Samuelson and Church (2015) proposed that the human tendency to
rely on heuristics may lead to intellectually arrogant behaviours. Dual-systems accounts
of human cognition suggest that thinking and reasoning are characterized by two distinct
systems: System 1 processes, which are fast, automatic, associative, and intuitive, and
System 2 processes, which are slow, conscious, deliberate, and analytical (Evans, 2003,
2008; Evans & Stanovich, 2013; Kahneman & Frederick, 2002). The corollary of this dual-
systems approach is that in order to reason intelligently and avoid biased thinking, it is
necessary to engage System 2 processes which are deliberate and analytical, and to
override the automatic biases that are assumed to emerge from System 1 processes (Evans,
2003, 2008). Samuelson and Church (2015) therefore suggest that in order to facilitate
intellectual humility, System 2 processes must be engaged and promoted. Interestingly, De
keersmaecker and Roets (2017) found that cognitive ability shaped the extent to which
individuals adjust their beliefs after learning that their attitudes were based on false
information; people with lower levels of cognitive ability adjust their attitudes to a
lesser extent than those with higher levels of cognitive ability. Intelligence may
therefore be an important cognitive correlate of intellectual humility. Nevertheless,
although deliberate, intelligent, analytical thinking may be important for intellectual
humility, it might not be sufficient or necessary. For instance, one can persist in
believing one's previous ideas and resist changing them in the face of new evidence even
with slow and deliberative thinking. Intellectual humility and the capacity to revise
one's ideas and be open to the ideas of others may require more than just analytical
thinking or cognitive ability. Specifically, in order to be aware of one's cognitive
limitations and evaluate evidence appropriately, considerable mental flexibility is
required. While the intellectually arrogant or servile individual disregards new
information in favour of past beliefs, the intellectually humble individual is able to be
flexible in their thinking, overcome biased reasoning, find creative connections between
past ideas and new information, and flexibly adjust their attitudes based on new evidence.
The aim of this study was therefore to evaluate the hypothesis that the intellectually
humble mind is also a flexible mind. The hypothesis that cognitive flexibility and
openness to novel ideas may be crucial ingredients for intellectual humility has support
in the empirical literature. Indeed, Leary et al. (2017) found that intellectual humility
was positively correlated with self-reported openness to alternative ideas and values, and
negatively correlated with dogmatism and intolerance of ambiguity. Stanovich and West
(1997) found that participants who scored highly on a self-report measure called “Actively
Open-minded Thinking”, which the researchers suggested is an indicator of cognitive
flexibility and openness to belief change, were more likely to evaluate arguments based on
the argument quality rather than relying on prior beliefs, even when controlling for
cognitive ability. The study therefore suggests that a flexible thinking disposition may
facilitate intellectual humility independently of cognitive ability. Interestingly,
cognitive ability, operationalized with SAT scores and a test of verbal ability, was a
unique and independent predictor of argument evaluation performance, signifying
intelligence may still play a notable role. However, there are methodological problems
with relying purely on self-report measures of cognitive flexibility. For instance, effect
sizes may be inflated in self-report as compared to behavioural measures of cognition, and
at times self-report measures yield opposite effects to theoretically-consistent
behavioural assessments (e.g. Van Hiel, Onraet, Crowson, & Roets, 2016; De Keersmaecker et
al., 2017; Saunders, Milyavskaya, Etz, Randles, & Inzlicht, 2018). Furthermore, new tools
have been developed to accurately measure intellectual humility and its components
directly (Krumrei-Mancuso & Rouse, 2016), and so there is a need to empirically
investigate the ways in which flexibility of thought can shape intellectual humility. The
present study sought to disentangle the relationships between cognitive flexibility,
cognitive ability (fluid intelligence), and intellectual humility, using classic tasks
from experimental psychology. Notably, cognitive flexibility and intelligence have been
theoretically and empirically dissociated (e.g. Friedman et al., 2006; Salthouse, Fristoe,
McGuthry, & Hambrick, 1998; Schaie, Dutta, & Willis, 1991), and so it is valuable to
examine their relative contributions and interactions. This investigation thus addressed
three primary hypotheses: Flexible thinking is positively correlated with intellectual
humility (building on Stanovich and West's (1997) work). Cognitive ability is positively
correlated with intellectual humility (as suggested by Samuelson & Church, 2015 and De
keersmaecker & Roets, 2017). There is an interaction between flexibility and intelligence
in shaping intellectual humility. If indeed intellectual humility is associated with high
cognitive flexibility (in H1) and high intelligence (in H2), then two plausible,
dissociative interaction mechanisms might be at play: H3-A There is an additive or
multiplicative interaction, such that the highest intellectual humility would reflect high
flexibility and high intelligence, while the lowest intellectual humility would be
associated with low flexibility and low intelligence. This hypothesis would predict that
individuals who score highly on flexibility, but not intelligence (and vice versa), would
have lower intellectual humility than individuals who score highly on both. H3-B There is
a compensatory interaction, such that either high flexibility or high intelligence are
sufficient for high intellectual humility. Consequently, high flexibility would facilitate
intellectual humility particularly for individuals with lower scores on the intelligence
test, and vice versa. This hypothesis would predict that individuals who score highly on
flexibility, but not intelligence (and vice versa), would have similar levels of
intellectual humility as individuals who score highly on both. That is, there is no
additive advantage for intellectual humility in scoring highly on both flexibility and
intelligence. This would suggest that there are multiple independent psychological
pathways to achieving high intellectual humility. The present study sought to investigate
the cognitive correlates of intellectual humility and clarify these mechanisms in order to
better understand the psychological underpinnings of intellectual humility and its various
facets.

<h>METHOD</h>
------

In accordance with the guidelines by Simmons, Nelson, and Simonsohn (2012), we report how
we determined our sample size, all data exclusions (if any), all manipulations, and all
measures in the study. Relevant data and code will be available on the Open Science
Framework repository upon publication.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

108 participants completed the study in full (see Supplementary Information SI1 for
further details). Participants provided their informed consent to participate in the study
in accordance with the institution's Department of Psychology Ethics Committee approval.
Power analysis was conducted to compute the required sample size (see Supplementary
Information SI1 for further details), with the ‘pwr’ package (Champely, 2015) in R (R Core
Team, 2017).

        Intellectual humility – comprehensive intellectual humility scale (CIHS)

        The CIHS, a 22-item scale developed by Krumrei-Mancuso and Rouse (2016), was used
        to assess intellectual humility. The CIHS scale measures four distinct factors of
        intellectual humility: (1) independence of intellect and ego (Cronbach's α =
        0.914; e.g. “When someone contradicts my most important beliefs, it feels like a
        personal attack”), (2) openness to revising one's viewpoint (Cronbach's α = 0.872;
        e.g. “I am open to revising my important beliefs in the face of new information”),
        (3) respect for others' viewpoints (Cronbach's α = 0.926; e.g. “I can respect
        others, even if I disagree with them in important ways”), and (4) lack of
        intellectual overconfidence (Cronbach's α = 0.822; e.g. “My ideas are usually
        better than other people's ideas”). The items are rated on a 5-point Likert scale
        ranging from 1 (strongly disagree) to 5 (strongly agree). Items were summed for
        the full scale (Cronbach's α = 0.664) and for each of the subscales (factors).
        Higher scores indicated greater intellectual humility.

        <hss>Cognitive flexibility – alternate uses task (AUT)</hss>

        In this computerized version of the AUT (Guilford, 1967), two common household
        items (brick and newspaper) were presented each for 1.5 min. Participants were
        asked to generate as many possible uses for these items. A timed clock was
        displayed to participants showing them how much time they had left. Flexibility
        was quantified as the total number of distinct conceptual categories in which the
        participant's responses belonged, in accordance with convention (e.g. Addis, Pan,
        Musicaro, & Schacter, 2016; Chermahini & Hommel, 2010; Madore, Addis, & Schacter,
        2015). The responses were rated and calculated by two independent raters.
        Cognitive Flexibility - Verbal Fluency task (VF). In this computerized version of
        the semantic verbal fluency (Tombaugh, Kozak, & Rees, 1999; Troyer, Moscovitch, &
        Winocur, 1997), participants are asked to generate words from a given concept
        (i.e. ‘things on wheels’ or ‘red things’) for 2 min each. Flexibility was computed
        as the total number of distinct conceptual categories. The responses were rated
        and calculated by two independent raters.

        Intelligence - Raven's standard progressive matrices task (Raven's SPM)

        An abbreviated version of the Raven's SPM (Bilker et al., 2012; Raven, 1938) was
        used to assess fluid intelligence. The task was composed of nine visual patterns
        which progressively increased in difficulty. For each matrix pattern, one piece
        was missing, and participants are asked to select the correct pattern piece from a
        set of possible solutions.

<h>RESULTS</h>
-------

All analyses were conducted in R (R Core Team, 2017) and SPSS (Version 25.0; IBM Corp.,
2017), including the R packages visreg (Breheny & Burchett, 2017), jtools (Long, 2018),
and pwr (Champely, 2015). First, we investigated whether the demographic variables of age,
gender, and educational attainment, were related to the psychological variables of
interest. Age was not significantly correlated with cognitive flexibility measured with
the AUT (r = 0.06, p = .521), cognitive flexibility measured with the VF task (r = 0.011,
p = .908), fluid intelligence measured with Raven's SPM (r = 0.037, p = .703), or with the
comprehensive intellectual humility score (r = 0.056, p = .567). Furthermore, there were
no gender differences in AUT cognitive flexibility, t(106) = 0.68, p = .501, VF cognitive
flexibility, t(106) = −0.60, p = .552, or in intellectual humility, t(106) = −1.03, p =
.306. There was a gender difference in Raven's SPM scores in the current sample, t(106) =
2.14, p = .035, in which males scored higher than females. Educational attainment was
significantly correlated with AUT Flexibility (r = 0.23, p = .002) and Raven's SPM (r =
0.31, p = .001), nearly significantly correlated with VF Flexibility (r = 0.18, p = .060),
and not correlated with intellectual humility (r = 0.06, p = .552). In all subsequent
statistical analyses, age, gender, and educational attainment were included as covariates.

<hs>  H1: Is intellectual humility positively correlated with cognitive flexibility?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Correlational analysis revealed that cognitive flexibility measured with the AUT was
significantly positively correlated with general intellectual humility (Fig. 1A).
Furthermore, as evident in Fig. 2, decomposing the Comprehensive Intellectual Humility
scale into its constituent factors revealed that this association was primarily driven by
the correlations of cognitive flexibility with openness to revising one's viewpoint
(Factor 2) and respect for others' viewpoints (Factor 3). Given Gignac and Szodorai's
(2016) effect size guidelines for individual differences research, these effect sizes can
be considered moderate to large. This pattern was corroborated by the correlations of
intellectual humility and cognitive flexibility measured with the Verbal Fluency (VF)
task. VF Flexibility was positively correlated with the comprehensive intellectual
humility scale (r = 0.26, p = .007), and specifically with openness to revising one's
viewpoint (Factor 2; r = 0.29, p = .002) and respect for others' viewpoints (Factor 3; r =
0.24, p = .014). There were no significant correlations between VF cognitive flexibility
and independence of intellectual ego (Factor 1; r = 0.12, p = .207) or lack of
intellectual overconfidence (r = 0.09, p = .339), paralleling the findings for AUT
cognitive flexibility.

<hs>  H2: Is intellectual humility positively correlated with intelligence?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As depicted in Fig. 1B and Fig. 2B, intellectual humility was significantly positively
correlated with fluid intelligence, such that more intellectually humble individuals
tended to score more highly on Raven's SPM. Similarly to the pattern of results revealed
for cognitive flexibility, intelligence was specifically positively correlated to the
factors of intellectual humility representing openness to revising one's viewpoint (Factor
2) and respect for others' viewpoints (Factor 3; Fig. 2). The correlation effect sizes
were generally smaller for the relationship between intellectual humility and intelligence
than for intellectual humility and cognitive flexibility.

<hs>  H3: What is the relationship between cognitive flexibility and intelligence in shaping intellectual humility?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In order to investigate whether, and in what way, cognitive flexibility and intelligence
interact to produce heightened intellectual humility, hierarchical linear regression
analysis predicting general intellectual humility was conducted (Table 1). Note that all
independent variables were centred prior to the hierarchical linear regression, as this
helps reduce multicollinearity and facilitates testing of simple slopes (Dawson & Richter,
2006). In Step 1, the control variables, including age, gender, and educational
attainment, were entered. As shown in Table 1, none of these control variables
significantly predicted intellectual humility. In Step 2, the centred cognitive
flexibility and centred fluid intelligence scores were entered. These independent
variables explained a significant proportion of the variance in intellectual humility (R2
= 0.17). As evident in Table 1, the coefficients of both cognitive flexibility and
intelligence were positive and significant, suggesting that both positively predicted
heightened intellectual humility and each was a unique predictor. Next, in Step 3, we
entered the interaction term for cognitive flexibility and intelligence. As predicted, the
interaction of flexibility and intelligence was significant and accounted for an
additional 5.5% of the variance in intellectual humility. Simple slope analyses were
conducted to examine the relationship between intellectual humility and flexibility at 1
SD above and below mean intelligence, while controlling for age, gender, and educational
attainment as covariates (see Fig. 3A). These analyses revealed that flexibility was
positively related to intellectual humility in the context of low intelligence (at −1 SD,
b = 6.24, SE = 1.51, p < .001) but not high intelligence (at +1 SD, b = −0.39, SE = 1.87,
p = .834). Reciprocally, simple slope analyses demonstrated that when flexibility is
conceptualized as the moderator, intellectual humility was positively related to
intelligence in the context of low flexibility (at −1 SD, b = 2.43, SE = 0.72, p < .001),
but not for high flexibility (at +1 SD, b = −0.51, SE = 0.78, p = .516). To validate this
finding further, the sample was divided into three equal groups (terciles) rather than
according to deviation from the mean. The simple slope analysis results were unchanged
following this robustness check; cognitive flexibility was positively related to
intellectual humility in the context of low intelligence (at −2.67 SD, b = 6.64, SE =
1.61, p < .001) but not average intelligence (at +0.5 SD, b = 2.23, SE = 1.25, p = .078)
and high intelligence (at +2.71 SD, b = −0.85, SE = 2.01, p = .674). Reciprocally,
intelligence was positively related to intellectual humility in the context of low
flexibility (at −0.87 SD, b = 2.16, SE = 0.66, p = .001), but not for average (at +0.28
SD, b = 0.57, SE = 0.55, p = .300) or high flexibility (at +1.23 SD, b = −0.75, SE = 0.85,
p = .381). This interaction effect is visualized in the filled contour plot and the
corresponding 3D perspective plot in Fig. 4. This depicts that the relationship between
intellectual humility and cognitive flexibility varies depending on intelligence, such
that intelligence differentiates between low and high intellectual humility at low levels
of cognitive flexibility, but not at high levels of cognitive flexibility. Similarly,
cognitive flexibility differentiates between low and high intellectual humility at low
intelligence scores, but not high intelligence scores. Moreover, Fig. 4 illustrates that
the highest intellectual humility was evident in participants who scored highly on either
intelligence or flexibility, and that scoring highly on both is not related to higher
intellectual humility. Fig. 4 also highlights a slight bias toward higher intellectual
humility scores amongst those with high cognitive flexibility (but low intelligence)
relative to those with high intelligence (but low flexibility), which is also reflected in
the higher regression coefficients in Table 1 for cognitive flexibility relative to
intelligence. To probe the interaction further, we applied the Johnson-Neyman technique
(Bauer & Curran, 2005; Hayes & Matthes, 2009; Johnson & Neyman, 1936), which calculates
the range of z values of the moderator (in this case, intelligence) in which the predictor
(i.e. cognitive flexibility) is a significant versus nonsignificant predictor of the
outcome (i.e. intellectual humility). This helps to avoid limitations of traditional
simple slopes analysis which require selection of potentially arbitrary values of the
moderator at which the relationship between the predictor and outcome variable are
assessed (e.g. ±1 SD from the mean). This technique is increasingly used in the
psychological and cognitive sciences (e.g. Beach et al., 2012; Bushman, Giancola, Parrott,
& Roth, 2012; Salerno & Peter-Hagene, 2013). Furthermore, Esarey and Sumner (2017) pointed
out that probing interactions in the traditional way can lead to a multiple comparison
problem. To address this, we implemented the method proposed by Esarey and Sumner (2017)
to control for multiple comparisons; this leads to a more conservative test in which the
false discovery rate in the marginal effects plot is controlled. The findings from the
Johnson-Neyman analysis demonstrated that the relationship between intellectual humility
and cognitive flexibility was significant when intelligence was less than 0.19 SD above
the mean, but not significant with higher values of intelligence (Fig. 3B). This mirrors
the finding from the simple slopes interaction analysis (Fig. 3A), in which the
relationship between intellectual humility and cognitive flexibility is significant at low
intelligence (−1 SD). In accordance with the methodological suggestions of McClelland,
Irwin, Disatnik, and Sivan (2017), Spiller, Fitzsimons, Lynch Jr, and McClelland (2013),
and Bauer and Curran (2005), this is revealed graphically in Fig. 3B. In Fig. 3B, the
transition between significance and non-significance of the conditional effect is
indicated by the dashed vertical line, which represents the Johnson-Neyman point at which
the 95% confidence band intersects the x-axis. In accordance with Esarey and Sumner's
(2017) recommendation, the Johnson-Neyman interval was calculated using the false
discovery rate adjusted t = 2.21; note that when not adjusted for multiple comparisons
using Esarey and Sumner's (2017) methodology, the Johnson-Neyman point is +0.35 SD.
Although we conceptualized intelligence as the moderator of the relationship between
intellectual humility and cognitive flexibility, it is important to note that the choice
of moderator for analyses is arbitrary – cognitive flexibility could have equally been
used as the moderator with paralleling results. We chose to use intelligence as the
moderator here because it is largely considered a highly genetically heritable and stable
construct, while there is more discussion over the stability and malleability of cognitive
flexibility (e.g. Miyake & Friedman, 2012). Nonetheless, as evident in the filled contour
plot of Fig. 4A, there is a symmetry in the interaction effect, such that the relationship
between intellectual humility and intelligence is most pronounced at low levels of
cognitive flexibility, and similarly the relationship between intellectual humility and
flexibility is evident at low levels of intelligence.

<h>DISCUSSION</h>
----------

Intellectual humility has been identified as a character virtue that enables individuals
to recognize their own potential fallibility when forming and revising attitudes and
beliefs. The present study examined the relationships between intellectual humility and
objectively-assessed cognitive flexibility and fluid intelligence. With regards to our
first hypothesis (H1), the results indicate that intellectual humility is positively
related to heightened cognitive flexibility (Fig. 1A). Secondly, the findings reveal that
intellectual humility is also positively correlated with intelligence (Fig. 1B),
corroborating our second hypothesis (H2) and Samuelson and Church's (2013) suggestion that
System 2 (i.e. analytical and deliberate) thinking styles are important for engaging in
intellectually humble behaviour. These effects were driven by the facets of intellectual
humility that correspond to openness to revising one's viewpoints and respect for others'
viewpoints (Fig. 2). Thirdly, the data revealed an interaction between cognitive
flexibility and intelligence in predicting intellectual humility (Table 1). Specifically,
there was evidence of a facilitation effect, such that high cognitive flexibility is
particularly valuable for intellectual humility in the context of low intelligence, and
reciprocally, high intelligence was beneficial for intellectual humility in the context of
low flexibility (Figs. 3 & 4). Interestingly, there was no evidence of an additive or
multiplicative effect (contrary to hypothesis H3-A), as high flexibility and high
intelligence did not produce superior intellectual humility relative to individuals who
scored highly on only one of these cognitive traits (corroborating hypothesis H3-B; see
Fig. 4). This is suggestive of dual psychological pathways to intellectual humility;
either cognitive flexibility or intelligence is sufficient for high intellectual humility,
but neither is necessary. The results demonstrate that cognitive flexibility was more
strongly implicated in intellectual humility than intelligence, as manifest by the larger
effect sizes (in Table 1, Figs. 1, 2, & 4). This may signify that the two pathways may
have differential efficacy in producing intellectually humble attitudes and behaviours.
Furthermore, the study revealed that not all facets of intellectual humility are equally
shaped by cognitive flexibility and intelligence (Fig. 2). While epistemically-oriented
features of intellectual humility, such as openness to alternative ideas (captured by
Factor 2) and receptivity to attitude change (Factor 3), were positively correlated with
both cognitive traits, the aspects of intellectual humility that are more closely
associated with intellectual identity, such as the extent to which one feels threatened
when contradicted (Factor 1) and one's conviction that one's own beliefs are superior and
infallible (Factor 4), were unrelated to cognitive flexibility and intelligence. The
specificity of these relationships suggests that future research will need to examine
additional psychological and social factors that shape individuals' tendency to be
intellectually overconfident. These findings extend research in three key disciplines: (1)
cognitive psychology, (2) social psychology, and (3) interventionist and educational
approaches. In the realm of cognitive psychology, recent research has provided
corroborating evidence for a positive relationship between intelligence and intellectual
humility across the lifespan. Danovitch, Fisher, Schroder, Hambrick, and Moser (2017)
investigated biopsychological markers of intellectual humility in 6- to 8-year-old
children. They found that greater intellectual humility was related to higher
intelligence, and this relationship was specific to the epistemic aspect of intellectual
humility (i.e. acknowledging the limitations of one's own knowledge) rather than its
social component (i.e. representing one's knowledge to other people and being receptive to
their ideas). This mirrors the specificity identified in the present study (Fig. 2).
Similarly, developmental work by Mills and Elashi (2014) found that intelligence predicted
6- to 9-year-old children's ability to recognize that a source of information may be
worthy of doubt and scepticism. Intelligence may therefore also be linked to early forms
of intellectual humility. Additionally, research with adults has illustrated that
intellectual humility and receptivity to attitude-change are related to cognitive ability
(De keersmaecker & Roets, 2017) and higher discriminability in an old/new recognition
memory task (Deffler, Leary, & Hoyle, 2016). Furthermore, Lick, Alter, and Freeman (2018)
found that cognitive ability (as measured with Raven's Advanced Progressive Matrices) was
related to enhanced updating of social stereotypes in light of new information, supporting
the present finding that intelligence may be linked to a willingness to revise one's
attitudes based on novel evidence. These results are also congruent with research in
social and political psychology on the psychological correlates of behaviours that may be
conceptualized as the opposite of intellectual humility – dogmatism, prejudice, and rigid
adherence to ideological doctrines. Intellectual humility has been linked to lower
dogmatism and belief superiority (Leary et al., 2017), fewer negative attitudes toward
religious outgroups (Van Tongeren et al., 2016), and a willingness to be exposed to
opposing political perspectives (Porter & Schumann, 2018). Frimer, Skitka, and Motyl
(2017) have illustrated that liberals and conservatives are similarly motivated to avoid
exposure to one another's opinions – a key facet of intellectual humility – suggesting
that strong adherence to ideologies is related to a tendency to avoid hearing opposing
views. Furthermore, recent empirical work has shown that cognitive ability is negatively
related to right-wing ideological attitudes, authoritarianism, and prejudice (e.g. Brandt
& Crawford, 2016; De Keersmaecker et al., 2017; Ludeke, Rasmussen, & DeYoung, 2017; Choma
& Hanoch, 2017; for meta-analysis: Onraet et al., 2015), and that a cognitive style
characterized by rigidity and intolerance of ambiguity is positively related to right-wing
attitudes (for meta-analyses: Van Hiel et al., 2016; Jost, 2017). Moreover, a recent set
of studies have demonstrated that behaviourally-assessed cognitive inflexibility is
related to the extent to which individuals adhere firmly and rigidly to ideologies, in the
realm of nationalism (Zmigrod, Rentfrow, & Robbins, 2018), politics (Zmigrod, Rentfrow,
and Robbins, under review), and religion (Zmigrod, Rentfrow, Zmigrod, & Robbins, 2018).
There is therefore converging evidence that intellectual humility and its opposing
interpersonal correlate – rigid ideological thinking – are shaped by cognitive ability and
cognitive flexibility. The finding that intellectual humility has multiple distinct
psychological underpinnings – an analytical thinking route and a mental flexibility route
– provides a fruitful basis on which to expand research into interventions that promote
inoculation against misinformation and ideological polarization. Pre-emptively warning
individuals about ideologically-motivated efforts to spread misinformation and about the
argumentation techniques commonly used in misinformation campaigns has been shown to be
effective in neutralizing the effect of misinformation on attitudes (Cook, Lewandowsky, &
Ecker, 2017; Van der Linden, Leiserowitz, Rosenthal, & Maibach, 2017). The present
findings are complementary to this line of research on inoculating citizens against fake
news for several reasons. Firstly, identifying individual differences in cognition that
shape individuals' willingness to revise their attitudes may suggest that individuals with
certain psychological traits may be more receptive than others to inoculation
interventions. Additionally, perhaps interventions that emphasize certain cognitive skills
(analytical thinking, flexible thinking, etc.) may be more beneficial for individuals with
particular psychological dispositions. Future research that combines the interventionist
and individual differences perspective will be fruitful in refining our understanding of
these processes. Secondly, these studies have focused on examining the effects of
conveying information about expert consensus and potential misinformation campaigns in
shaping citizens' attitudes (Van der Linden et al., 2017) and trying to engage
individuals' System 2 analytical processing in evaluating evidence. The current findings
suggest that fostering mental flexibility and an attentionally-open information processing
style may also be a successful focal point for future interventions. Several potential
limitations of the present study highlight future avenues for research. Firstly, it will
be valuable to replicate these findings in lab settings and not just online samples, as
well as in different cultural contexts, and with complementary measures of intelligence
and cognitive flexibility. Since the a priori power analysis we conducted based on
relevant effect sizes in the literature recommended a sample size of 92 participants, we
computed the power actually achieved for the multiple regression models. This revealed
that the power was 99.29% (f2 = 0.290), suggesting that the analyses were well powered to
detect the present effects. Larger samples in future studies will help to corroborate and
generalize these findings. In outlining future directions for the field, Leary et al.
(2017) identified that “of particular interest are ways in which people who are high
versus low in intellectual humility may differ in how they process information” (p. 810).
The present study addressed this question by illustrating that analytical as well as
flexible cognitive processing styles predict heightened intellectual humility. Admitting
intellectual fallibility helps facilitate more constructive reactions to disagreements and
conflict resolution (Porter & Schumann, 2018). Consequently, identifying and cultivating
the cognitive factors shaping intellectual humility may be a key endeavour in building
more evidence-based, tolerant, and effective discussions about the contested issues that
divide and polarize our societies today.

<h>CONFLICT OF INTEREST</h>
--------------------

All authors have declared that they have no conflict of interest.


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<ART>The puzzling difficulty of tool innovation: Why can't children piece their knowledge together?
================================================================================

Authors: Nicola Cutting, Ian A. Apperly, Jackie Chappell, Sarah R. Beck
DOI: 10.1016/j.jecp.2013.11.010
Year: 2014  |  Pages: 110-117
ASJC codes: 3204, 3205
Keywords: Cognitive Development, Ill-structured problems, Innovation, Problem Solving, Social learning, Tools

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Tool innovation-designing and making novel tools to solve tasks-is extremely difficult for young children. To discover why this might be, we highlighted different aspects of tool making to children aged 4 to 6. years (N= 110). Older children successfully innovated the means to make a hook after seeing the pre-made target tool only if they had a chance to manipulate the materials during a warm-up. Older children who had not manipulated the materials and all younger children performed at floor. We conclude that children's difficulty is likely to be due to the ill-structured nature of tool innovation problems, in which components of a solution must be retrieved and coordinated. Older children struggled to bring to mind components of the solution but could coordinate them, whereas younger children could not coordinate components even when explicitly provided. © 2013 The Authors.

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<h>INTRODUCTION</h>
------------

Tools are an essential part of human everyday life (Vaesen, 2012); it is hard to consider
how we might get through the day without them. Tool-using capacity is evident from a young
age, with children as young as 2 years using simple tools such as spoons (Connolly &
Dalgleish, 1989) and rakes (Brown, 1990). Children gain the majority of their tool
behaviors by observing others. As such, social learning has been the focus of research
into the development of children’s tool use (Flynn & Whiten, 2008, 2010; Lyons, Young, &
Keil, 2007; McGuigan & Whiten, 2009; Nielsen, 2006) and also their tool making (Beck,
Apperly, Chappell, Guthrie, & Cutting, 2011). However, social learning cannot be a
sufficient explanation for the development of all tool making because this would rule out
the possibility of children (or anyone else) innovating novel tools (Nielsen, 2012). In
contrast to findings when social learning is possible, recent findings suggest that
innovation of a novel tool, by which we mean creating a novel tool to solve a problem, is
extremely difficult for young children (Beck et al., 2011; Cutting, Apperly, & Beck,
2011). The focus of the current work was to determine what makes innovation so difficult.
Our strategy was to highlight different components of the task solution to see whether
this improved children’s performance. Children’s tool innovation difficulties have
previously been demonstrated in a series of experiments requiring children to innovate a
tool in order to retrieve stickers (Beck et al., 2011; Cutting et al., 2011; Chappell,
Cutting, Apperly, & Beck, 2013). Children had great difficulty in generating the solution
to bend a pipecleaner into a simple hook tool to retrieve a bucket from a narrow vertical
tube. Children under 5 years of age rarely innovated a hook tool, and by 8 years of age
only around half of children were successful on this task. This difficulty in tool
innovation extends to making other tools using pipecleaners (Cutting et al., 2011) and to
other materials and methods of tool making (Cutting, Beck, & Apperly, 2013). Children’s
difficulty with tool innovation is surprising because children appear to possess all of
the relevant knowledge required to solve tool innovation tasks. Children are familiar with
the properties of the materials, for example, the pliant nature of pipecleaners. In
previous studies, children received manipulation exercises in which they bent pipecleaners
prior to being given the tool-making task (Beck et al., 2011, Experiment 3; Cutting et
al., 2011, Experiment 1). Practice with bending pipecleaners did not aid children on
subsequent tool-making tasks. This suggests that if children did lack knowledge about the
properties of pipecleaners (or other materials), this is not sufficient to explain their
difficulty. As well as seemingly understanding the properties of pipecleaners and the fact
that they are allowed to manipulate them, children also appeared to have the required
knowledge about the physics of the problem they faced. In the hook task, children appeared
to understand that a hook would be the most functional tool; in a tool selection version
of the task, children as young as 4 years chose the hooked tool over the straight tool
first when their task was to retrieve a bucket from a vertical tube using pre-made tools
(Beck et al., 2011, Experiment 1). Furthermore, children could also recognize a functional
tool when shown how to make one: After initial failure on the hook innovation task,
children readily manufactured a hook tool and used it correctly when shown a hook-making
demonstration (Beck et al., 2011; Cutting et al., 2011). Note that children were only
shown how to make the required tool; they were not given a demonstration as to how to use
it. Taken together, this evidence suggests that it is not a simple lack of knowledge that
limits children’s performance. Children understand the properties of the materials they
are given and are aware that they are allowed to manipulate them. Children understand the
physics of the task and can recognize a hook as the most functional tool. So, if children
possess all of this knowledge, why do they find tool innovation so difficult? One
possibility is that children’s difficulty with tool innovation could be due to its ill-
structured nature. Although there is no single agreed-on definition of what constitutes an
ill-structured problem, a generally agreed-on framework is that an ill-structured problem
is one that is missing information from its start state, goal state, or information
regarding the transformation required to go between the two (Goel & Grafman, 2000; Wood,
1983). Following this definition, tool innovation is an ill-structured problem; children
are given the start state (the apparatus and the materials) and told that the goal is to
retrieve the sticker, yet they are given no information regarding how they should go about
this task. Compare this with Beck and colleagues’ (2011, Experiment 1) well-structured
tool selection task in which young children readily succeed. In this task, children are
given the start state (the apparatus and materials) and the goal state (retrieve the
sticker) and are given the choice between two possible means for effecting a
transformation (use the straight pipecleaner or use the hooked pipecleaner). When
information about the start state, goal, and means were provided, children found it
trivially easy to retrieve the bucket. Current findings suggest that just having all of
the individual items of domain knowledge is not sufficient to be successful in solving
ill-structured problems (Chen & Bradshaw, 2007). Domain knowledge must be well integrated
into what is termed structural knowledge to enable people to use it effectively (Jonassen,
Beissner, & Yacci, 1993). Structural knowledge is knowledge that is well integrated and
developed and, as such, allows the person to use this knowledge in a flexible manner. This
flexibility enables people to bring to mind the required pieces of knowledge and then
successfully coordinate individual pieces of information into a useful solution. Some
novices may possess all of the relevant pieces of information, but only in experts is this
knowledge integrated into structural knowledge that is flexible enough to solve the
problem (Voss, Blais, Means, & Greene, 1986; Wineburg, 1998). Applying this framework to
tool innovation, it is possible that although children undertaking these problems appear
to possess all of the knowledge required to solve the tasks, if this knowledge is not well
integrated, they may still struggle to produce a solution. Children’s difficulty in these
tool innovation studies may lie with bringing to mind the required pieces of information
from memory, coordinating these different pieces of knowledge, or a combination of both.
From previous studies, we know that highlighting the properties of the materials was not
sufficient to elicit tool innovation. For example, 4- to 7-year-olds were not aided in
making a tool when they were given bending practice that highlighted information about the
properties of the pipecleaners (Beck et al., 2011, Experiment 3; Cutting et al., 2011,
Experiment 1). We also know that just seeing the target tool that they were required to
make, without any information regarding manipulation, was not sufficient to prompt
children to make a tool for themselves (Cutting et al., 2013). This is particularly
surprising given that children are able to see the utility of the end state tool and
select it to use themselves in the context of a tool selection task (Beck et al., 2011,
Experiment 1). In the current experiment, we investigated whether children were able to
coordinate information and successfully make a tool if we highlighted the properties of
the materials and the target tool required. By highlighting property information to half
of the children before they attempted the task and then providing all children with a
target tool demonstration after initial failure, we can begin to disentangle the minimum
amount of information children require to successfully innovate a tool. Given previous
findings, we expected children who had experienced bending practice to be no more
successful in making a hook tool than children who had not received bending practice.
Second, if children failed to innovate during this first stage, we then compared the two
groups on their ability to make the tool following the target tool demonstration. Based on
findings from Cutting and colleagues (2013), we expected children who had not received
bending practice to perform poorly following the target tool demonstration. This would
demonstrate children’s difficulty with bringing to mind additional information.
Examination of performance following the target tool demonstration by the bending practice
group would reveal whether children could successfully coordinate information. If the
difficulty is in bringing information to mind, these children who had information about
properties and information about hooks highlighted for them should be more likely to solve
the task. However, if children’s difficulty is in coordinating information, even children
who had the information highlighted for them should still have difficulties with the task.
We tested children in the first (ages 4–5) and second (ages 5–6) years of compulsory
education (UK) because these children performed near floor on previous tool innovation
tasks and, thus, there was room for significant improvement.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The participants were 53 children aged 4 or 5 years (24 boys and 29 girls, mean age = 4
years 7 months [4;7], range = 4;1–5;1) and 57 children aged 5 or 6 years (26 boys and 31
girls, mean age = 5;7, range = 5;2–6;2) from two schools in the West Midlands, UK. Equal
proportions of children from each school were present in each age group. The ethnic
composition of the sample was 96% Caucasian, 3% Black, and 1% Asian. Participants had not
taken part in previous versions of the task.

<hs>  Materials</hs>
  ~~~~~~~~~

For the bending practice exercise, we used a pipecleaner (length = 29 cm), a pen, a piece
of string (length = 29 cm), and a template of an S shape printed onto card. The apparatus
for the main task was a clear plastic tube (length = 22 cm, width of opening = 4 cm)
attached vertically to a cardboard base (length = 35 cm, width = 21 cm), a bucket
containing a sticker, a pipecleaner (length = 29 cm), and a piece of string (length = 29
cm) that acted as a distracter item (see Fig. 1). The experimenter used an identical
pipecleaner (length = 29 cm) for the demonstrations.

<hs>  Procedure</hs>
  ~~~~~~~~~

Before testing, children were instructed by their class teacher not to tell other children
how to play the games they would be playing with the experimenter to ensure that they
would be a nice surprise for everyone. All participants were tested by a female
experimenter in a quiet area just outside the main classroom. Children and the
experimenter sat at right angles to each other at the corner of a table. Children were
alternately allocated to either the bending practice group or the no bending practice
group based on the teacher’s class list.

        <hss>Bending practice exercise</hss>

        Children in the bending practice group received the exercise prior to being given
        the main task. The exercise was designed to highlight the properties of the
        materials to the children and was based on the procedure from Cutting and
        colleagues (2011). Children watched as the experimenter demonstrated actions with
        the string and pipecleaner (order counterbalanced), and children then copied these
        actions. The pipecleaner was wound around a pen and then was removed to
        demonstrate that it kept its shape. The string was laid over the template to
        follow the S-shaped pattern. All children were able to perform the bending
        practice exercise.

        <hss>Main task</hss>

        Children were shown the vertical transparent tube with the bucket containing a
        sticker already in place in the bottom. They were told that if they could get the
        bucket out of the tube, they could win the sticker inside it. The experimenter
        then brought out the string and pipecleaner and told children that these were
        things that “can help” to get the bucket and sticker out. Children were then given
        1 min to try to retrieve the sticker. No feedback was given, but children were
        given neutral prompts if required. Examples of prompts included “Can you think how
        you might be able to get the sticker out?” and “Maybe you could use these things
        to help you.” If, after 1 min, children had not retrieved the bucket, they were
        encouraged by the experimenter to put down the materials they were using. With the
        materials remaining in view in front of participants, the experimenter then said
        “Look at this” and brought out a ready-made pipecleaner hook for children to view
        (target tool demonstration). Children were again encouraged to retrieve the bucket
        using their own materials. If after 30 s children still had not retrieved the
        bucket, they were told to put down their materials. With their materials remaining
        in view as before, the experimenter said “Watch this” and, taking her own straight
        pipecleaner held in the middle, bent one end to form a hook (tool creation
        demonstration). The experimenter did not demonstrate how to retrieve the bucket
        with the hook because previous studies have shown that such demonstration is not
        necessary (Beck et al., 2011). Children were again encouraged to use their own
        materials to retrieve the bucket. If children were still not successful in making
        a hook tool, they were given verbal prompts such as “Did you see what I did with
        mine?” and then “Can you do that?” Thus, there were three stages to the main task:
        Stage 1 after half of the children had experienced the bending practice exercise,
        Stage 2 after all of the children had seen the target tool, and Stage 3 after
        children had seen the hook-making action demonstration. Stages 1 and 3 largely
        replicated previous studies, and so our main interest in the current study was
        performance in the two conditions at Stage 2. Children were coded as successful if
        they retrieved the bucket and sticker from the tube using a pipecleaner they had
        bent into a hook. Having made a hook, children did not require encouragement to
        use it.

<h>RESULTS</h>
-------

There were no effects of gender on level of success pre-demonstration, χ2(1, N = 110) =
0.42, p = .518, φ = .062, or for success following the first target tool demonstration,
χ2(1, N = 97) = 0.64, p = .425, φ = .081, or the second action demonstration, χ2(1, N =
54) = 0.05, p = .821, φ = .031. As such, data were combined across gender for subsequent
analyses. The results were first analyzed for all children combined and then for the two
age groups separately. Overall, 84 of 110 children were successful in making a hook tool
at any of the three stages of the task. Children’s success at innovating a hook during
Stage 1 was examined to see whether the bending practice facilitated performance. Overall,
children were very poor during their first exposure to the task, with only 13 of 110
children successfully making a hook tool. Of these children, 7 were in the bending
practice group and 6 had not received bending practice, demonstrating no effect of
condition, χ2(1, N = 110) = 0.05, p = .822, φ = .022. When we break this down into
separate age groups, only 2 4- and 5-year-olds were successful, both of whom had not
received bending practice, showing no difference between conditions, Fisher’s exact test,
p = .236. For the 5- and 6-year-olds, 7 of the successful children were in the bending
practice group and 4 were in the no bending practice group, again showing no difference
between conditions, χ2(1, N = 57) = 0.89, p = .346, φ = .125. Children who were successful
on their first exposure to the task were excluded from subsequent analyses that compared
success following the demonstrations. Chi-square analyses were used to compare children’s
performance at Stage 2 following the target tool demonstration. For both age groups
combined, children were significantly more likely to make a hook tool following the target
tool demonstration in the bending practice condition than in the no bending practice
condition, χ2(1, N = 97) = 6.59, p = .010, φ = .261. Comparison across age groups shows
that older children were significantly more successful than younger children in the
bending practice condition, χ2(1, N = 49) = 9.93, p = .002, φ = .450. No difference in
success was seen in the no bending practice condition, χ2(1, N = 48) = 0.87, p = .350, φ =
.135. When the two age groups were analyzed separately, the difference in success between
conditions was found to be driven by the older children, χ2(1, N = 46) = 9.30, p = .002, φ
= .450 (see Table 1). This suggests that 5- and 6-year-olds are able to coordinate the
information if they received both the bending practice and saw a pipecleaner hook. No such
difference was seen for the 4- and 5-year-olds, χ2(1, N = 51) = 0.86, p = .355, φ = .129.
Children who were successful following the target tool demonstration were excluded from
the following analyses that investigated success at Stage 3, which followed the tool
creation demonstration. For children requiring this demonstration, 55% were successful at
making the tool needed (see Table 1). Chi-square analysis revealed no difference in the
levels of success for each group following the action demonstration for either the 4- and
5-year-olds, χ2(1, N = 35) = 0.02, p = .877, φ = .026, or the 5- and 6-year-olds, Fisher’s
exact test, p > .999.

<h>DISCUSSION</h>
----------

In the current work, we highlighted various aspects of the task solution in order to
discover why children have difficulty with tool innovation. Information regarding the
properties of the materials and an example of the tool children needed to create were
highlighted. The current findings suggest a series of limiting steps in innovation, with
children getting stuck at different steps at different ages. Overall, we found that very
few 4- to 6-year-olds spontaneously innovated a hook tool with either no additional
information or just information about pipecleaner properties highlighted. These results
are in line with previous research demonstrating that young children have great difficulty
in innovating tools with either no additional information (Beck et al., 2011, Experiment
2) or information highlighting pipecleaner properties (Beck et al., 2011, Experiment 3;
Cutting et al., 2011, Experiment 1). It should be noted that success on this task has been
shown to improve with age, with children becoming extremely proficient by 9 or 10 years
(Beck et al., 2011, Experiment 1). The main aim of the current study was to test
children’s ability to make a tool following a target tool demonstration. Children were
shown a ready-made pipecleaner hook but were not shown how to make it. This enabled us to
discover whether children could bring to mind the means to make the hook for themselves.
In comparison with children who had experience of pipecleaner properties, children in both
age groups were extremely poor at making the hook tool following the target tool
demonstration if they had not had information regarding pipecleaner properties highlighted
for them, that is, children who had not received the bending practice. The 5- and 6-year-
olds who had information regarding pipecleaner properties highlighted were significantly
more successful in making the required hook tool following the target tool demonstration
than children who had not received the bending practice. This suggests that if both pieces
of information were readily accessible to older children, they were able to coordinate the
information successfully into a solution. Conversely, the 4- and 5-year-olds displayed
great difficulty in making a hook tool even if they had both pieces of information
highlighted for them. This suggests that younger children face a limitation in the domain
of tool making in that they are unable to coordinate information even when it is
highlighted. The current findings suggest that children’s main difficulty with tool
innovation could be due to problems with retrieving information and recognizing it as a
useful solution to the problem. Children were unable to bring to mind additional
information when given certain aspects of the task. For example, children who received the
bending practice that highlighted the pliable property of pipecleaners were unable to
bring to mind information about hooks needed to allow them to innovate the task solution.
Similarly, following the target tool demonstration, children who did not receive the
bending practice were unable to bring to mind information regarding the properties of
pipecleaners that would enable them to successfully make their straight pipecleaner into a
hook tool. Findings from both age groups fit with the suggestion that tool innovation is
an ill-structured problem that requires solvers to both retrieve and coordinate knowledge
in order to solve a task. The current study suggests that 4- and 5-year-olds had
difficulty with both of these components. Performance improved with age, with 5- and
6-year-olds being able to coordinate information into a useful solution if it had been
highlighted, but these older children still displayed great difficulty with bringing to
mind this information for themselves. Regardless of how good children’s ability to
coordinate knowledge is, they can never succeed in solving the task if they are unable to
retrieve the components of knowledge required and recognize their relevance to the
solution. As such, we still see poor innovation ability in this older age group under
conditions where the required information is not highlighted for them and they must bring
it to mind themselves (Beck et al., 2011; Cutting et al., 2011). It is surprising that
both age groups had difficulty in bringing to mind the required knowledge needed to
innovate the solution because previous evidence suggests that children possess all of the
individual pieces of knowledge required to solve this tool innovation task. First,
children recognized that a hook was a solution to the task. This is demonstrated in Beck
and colleagues’ (2011, Experiment 1) tool selection task and by children readily
manufacturing a hook tool and using it correctly when shown a hook-making demonstration
(Beck et al., 2011; Cutting et al., 2011). Second, children have knowledge about the
properties of pipecleaners (Beck et al., 2011, Experiment 3; Cutting et al., 2011,
Experiment 1). So, if children possess all of this information, why can they not retrieve
it in the context of a tool innovation task? Having domain knowledge might not be
sufficient to solve ill-structured problems (Jonassen et al., 1993). The children in the
current study were novices. Although these children may have possessed all of the
independent pieces of knowledge the task required, they did not have sufficient experience
with the world and the materials to have integrated structural knowledge. We suggest that
without this structural knowledge, young children lacked the flexibility needed to
retrieve their knowledge from memory and then coordinate it in order to solve these tool
innovation tasks. The current study required children to retrieve and coordinate knowledge
regarding the transformation they were required to perform. It seems likely that other
types of ill-structured problems—that is, those missing information from either their
start or goal state—would also require the solver to retrieve and coordinate the relevant
pieces of information. Future research is needed to test this. The current findings
suggest that the main difficulty for both age groups was retrieving knowledge from memory.
Younger children in this study also displayed great difficulty with coordinating their
knowledge. As children develop and integrate their knowledge, they first improve in their
capacity to coordinate information and can do so readily if all of the information needed
is highlighted for them. We suggest that as children develop further, their knowledge will
become more integrated. This will allow them to access and retrieve their knowledge more
flexibly and, along with their ability to coordinate knowledge, will enable them to solve
these ill-structured tool innovation tasks.


<h>REFERENCES</h>
----------

  [1] Sarah R. Beck, Ian A. Apperly, Jackie Chappell, Carlie Guthrie, Nicola Cutting. Making tools isn't child's play. doi:10.1016/j.cognition.2011.01.003
  [2] Ann L. Brown. Domain-specific principles affect learning and transfer in children. doi:10.1016/0364-0213(90)90028-U
  [3] Jackie Chappell, Nicola Cutting, Ian A. Apperly, Sarah R. Beck. The development of tool manufacture in humans: What helps young children make innovative tools?. doi:10.1098/rstb.2012.0409
  [4] Ching Huei Chen, Amy C. Bradshaw. The effect of web-based question prompts on scaffolding knowledge integration and iii-structured problem solving. doi:10.1080/15391523.2007.10782487
  [5] Kevin Connolly, Mary Dalgleish. The Emergence of a Tool-Using Skill in Infancy. doi:10.1037/0012-1649.25.6.894
  [6] Nicola Cutting, Ian A. Apperly, Sarah R. Beck. Why do children lack the flexibility to innovate tools?. doi:10.1016/j.jecp.2011.02.012
  [8] Emma Flynn, Andrew Whiten. Imitation of hierarchical structure versus component details of complex actions by 3- and 5-year-olds. doi:10.1016/j.jecp.2008.05.009
  [9] Emma Flynn, Andrew Whiten. Studying children's social learning experimentally "in the wild". doi:10.3758/LB.38.3.284
  [10] Vinod Goel, Jordan Grafman. Role of the right prefrontal cortex in ill-structured planning. doi:10.1080/026432900410775
  [12] Derek E. Lyons, Andrew G. Young, Frank C. Keil. The hidden structure of overimitation. doi:10.1073/pnas.0704452104
  [13] Nicola McGuigan, Andrew Whiten. Emulation and "overemulation" in the social learning of causally opaque versus causally transparent tool use by 23- and 30-month-olds. doi:10.1016/j.jecp.2009.07.001
  [14] Mark Nielsen. Copying actions and copying outcomes: Social learning through the second year. doi:10.1037/0012-1649.42.3.555
  [15] Mark Nielsen. Imitation, pretend play, and childhood: Essential elements in the evolution of human culture?. doi:10.1037/a0025168
  [16] Krist Vaesen. The cognitive bases of human tool use. doi:10.1017/S0140525X11001452
  [17] James F. Voss, Jeffrey Blais, Mary L. Means, Terry R. Greene, Ellen Ahwesh. Informal Reasoning and Subject Matter Knowledge in the Solving of Economics Problems by Naive and Novice Individuals. doi:10.1207/s1532690xci0303_7
  [18] Sam Wineburg. Reading Abraham Lincoln: An expert/expert study in the interpretation of historical texts. doi:10.1207/s15516709cog2203_3
  [19] Phillip Karl Wood. Inquiring systems and problem structure: Implications for cognitive development. doi:10.1159/000272887
<ART>The relationship between cognitive penetration and predictive coding
====================================================================

Authors: Fiona Macpherson
DOI: 10.1016/j.concog.2016.04.001
Year: 2017  |  Pages: 6-16
ASJC codes: 3204, 3205
Keywords: Cognition, Cognitive penetration, Early vision, Perception, Perceptual experience, Predictive coding

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

If beliefs and desires affect perception—at least in certain specified ways—then cognitive penetration occurs. Whether it occurs is a matter of controversy. Recently, some proponents of the predictive coding account of perception have claimed that the account entails that cognitive penetrations occurs. I argue that the relationship between the predictive coding account and cognitive penetration is dependent on both the specific form of the predictive coding account and the specific form of cognitive penetration. In so doing, I spell out different forms of each and the relationship that holds between them. Thus, mere acceptance of the predictive coding approach to perception does not determine whether one should think that cognitive penetration exists. Moreover, given that there are such different conceptions of both predictive coding and cognitive penetration, researchers should cease talking of either without making clear which form they refer to, if they aspire to make true generalisations.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Some advocates of the predictive coding account of perception have said that if the
predictive coding account of perception is correct then cognitive penetration occurs. If
true, this would provide a new route to arguing for the existence of cognitive
penetration: argue for a predictive coding account of perception. In this paper, I
investigate whether the predictive coding account of perception does entail that cognitive
penetration occurs. I establish that there are different versions of cognitive penetration
and different versions of predictive coding. I map out the relationship between these
different versions. I show that some versions of predictive coding entail that there are
some forms of cognitive penetration, some versions of predictive coding are compatible
with, but do not entail, that there are some forms of cognitive penetration, and some
forms of predictive coding entail that some forms of cognitive penetration do not exist.
Mapping out these relationships helps us to understand the predictive coding account of
perception and cognitive penetration in depth. It also serves to warn us that we should be
clearer which version of the predictive coding account of perception and which version of
cognitive penetration we are referring to when we make claims about them. And it serves to
show that an argument for cognitive penetration that appeals to the existence of
predictive coding has to appeal to a specific version of predictive coding, the
establishment of which may turn on just the same issues as the establishment of cognitive
penetration itself. This paper is divided into seven further sections. Section 2 defines
and examines the different forms of cognitive penetration. Section 3 outlines a minimal
account of the predictive coding account of perception. In Section 4, I consider possible
relationships between predictive coding and cognitive penetration and examine the claims
that people have made about this relationship. In Section 5, I look at whether predictive
coding is committed to cognitive states playing a role in the predictive coding account,
and what this means for the relationship between various versions of predictive coding and
cognitive penetration. In Section 6, I examine whether a predictive coding account that is
committed to the idea that cognitive states play a role in predictive coding entails one
version of cognitive penetration, namely the cognitive penetration of perceptual
experience—that is a conscious, personal-level state. In Section 7, I consider whether a
predictive coding account that is committed to the idea that cognitive states play a role
in predictive coding entails another version of cognitive penetration, namely the
cognitive penetration of early vision—that is, an initial level of visual processing that
has been defined in different ways by psychologists and neuroscientists. I give three
accounts of what early vision might be taken to be and I spell out what predictive coders
should say about the penetration of early vision conceived of in each of them. Finally, in
Section 8, I summarise what the various accounts of predictive coding and cognitive
penetration are, and the relationships between them, in a table, and I comment on the
broad picture that emerges of the relationships between them. Readers may wish to consult
this table while they are reading the sections below.

<h>WHAT IS COGNITIVE PENETRATION?</h>
------------------------------

There are two related, but nonetheless distinct, alleged phenomena that go under the name
‘cognitive penetration’. That they are clearly distinct emerges in the rest of this paper
by consideration of their relation to predictive coding. The first of these phenomena is
the penetration of early vision. It is the phenomenon discussed in Pylyshyn’s (1999) much
cited paper on the topic. Early vision is defined functionally by Pylyshyn as the system
that takes attentionally modulated signals from the eyes (and perhaps some information
from other sensory modalities) as inputs, and produces shape, size and colour
representations as output. These representations are then categorised and identified by
the cognitive system making use of memory, knowledge and judgment. The question of whether
cognitive penetration occurs, conceived of as the penetration of early vision, is the
question of whether the function that the early visual system computes “is sensitive in a
semantically coherent way, to the organisms goals and beliefs, that is, [whether] it can
be altered in a way that bears some logical relation to what the person knows” (1999:
343). Pylyshyn explicitly denies that the output of early vision either is, or determines,
one’s visual experience, or equivalently, that the representational content of the output
of early vision is the representational content of one’s perceptual experience (1999:
362). In contrast to this notion of cognitive penetration, which has mostly been the
subject of study by psychologists and neuroscientists, another notion of cognitive
penetration, that of the penetration of perceptual experience, has been a major subject of
study by philosophers, although the division in what researchers study is far from
exceptionless, and increasingly so. ‘Perceptual experience’ refers to the conscious state
that we typically go into when we perceive the world—the conscious state of awareness of
the world that has a distinctive phenomenal character compared to typical beliefs or
judgments about the world. In my (2012) paper on cognitive penetration, I defined the
cognitive penetration of experience as follows: in any case of perception, hold fixed what
it is that is perceived (the objects properties and relations seen, heard, touched, and so
on), the perceiving conditions (the level of light, shadow, mistiness, for example), the
state of the sensory organ (perfect human vision, shortsighted human vision, for example)
and the location of one’s focus of attention. With those conditions fixed, if it is
possible for two subjects (or one subject at different times) to have different perceptual
experiences due to the differing content of the states of their cognitive systems, and
moreover, there is a semantic or intelligible link between the content of the cognitive
states and the content of the perceptual experience, then perceptual experiences are
cognitively penetrable. States of the cognitive system include beliefs, judgments and
desires, and should likely also be taken to include the concepts that we possess. For
further discussion of the terms used in this definition see my (2012) paper. There are
several issues with both of these definitions of cognitive penetration. I address the two
most pressing ones. The first concerns attention. The second concerns the semantic or
intelligible link that is posited as necessary for cognitive penetration to occur. Despite
giving the above definition of cognitive penetration in my (2012) paper, later in the
paper, I go on to question whether we should include attention in the conditions that we
hold fixed. I noted that one rationale that someone might have for thinking that we should
hold fixed attention is that a shift of attention is akin to a shift of the location to
which one’s eyes point. A shift in the direction that one’s eyes look changes one’s
perceptual experience by changing which objects and properties are processed, but if such
a shift were driven by one’s cognitive states, such a shift should not count as cognitive
penetration occurring, simply a shift in what is perceived. One might think of shifts of
attention in a similar manner: a shift of spatial attention, driven by one’s cognitive
states, might affect how clearly, or in how much detail, certain objects and properties
are experienced, but that is just a shift in what is perceived and shouldn’t count as
cognitive penetration. However, as I noted in my (2012) paper, there are forms of
attention other than spatial attention, so even if one was persuaded that changes of
spatial attention driven by cognition should not count as cognitive penetration, it is not
clear that shifts in other forms of attention should also not count. One form of a non-
spatial shift in attention is a shift in what properties one attends to. For example, one
can shift from attending to the red things in one’s visual field to attending to the
yellow things, and that might change one’s experience in certain ways. For example, it may
lead one to have an experience in which the salience of the yellow things is greater than
that of the red, and so one might be aware of the number yellow things but not be aware
the number of red things. If such a shift were driven by cognition in the right way, then
it is tempting to consider such a change in experience a case of cognitive penetration
because a kind of bias could creep into perception. For example, one might overestimate
the proportion of yellow things to red things. A useful discussion of what factors, such
as bias, should lead one to classify certain cases as cases of cognitive penetration can
be found in Stokes (2015). However, it is even unclear whether shifts in spatial attention
caused by cognitive processes should be conceived of as failing to count as cases of
cognitive perception. An argument for thinking that some such cases are instances of
cognitive penetration has recently been put forward by Cecchi (2014), who discusses an
experiment carried out by Schwartz, Maquet, and Frith (2002). In the experiment, subjects
underwent a period of monocular training (subjects in one group used their right eye and
subjects in another group used their left eye). They looked at a screen on which was
displayed a homogenous background of horizontal bars. An “L” or “T” would appear in the
centre of the screen randomly rotated for 16 ms. During the same short interval, three
lines would appear randomly at some location within the upper-left quadrant in the
periphery of their visual field. Subjects had to do two tasks: identify whether the object
in the centre was an “L” or a “T”, and identify the orientation of the three lines that
appeared in the periphery of their visual field. Subjects’ eye movements were restricted
to fixation on the central letter. Detection of the orientation of the lines in the
periphery of their visual field therefore required the allocation of voluntary covert
spatial attention. The goal of the experiment was to improve subjects’ performance in the
detection of the orientation of the three peripheral lines. In the first (training) phase
of the experiment, subjects underwent a total of 1760 trials each, and received feedback
about their accuracy after each one. During the first phase, performance of the trained
and untrained eye was measured. Successful performance was one in which they accurately
detected what the central letter was and what the orientation of the peripheral lines was.
During the first phase, subjects improved their performance of detecting the orientation
of the peripheral lines gradually in the eye that was being trained, but not in the one
that was not. Progressive changes in neural behaviour elicited by the trained eye in the
part of the V1 cortex (also known as the striate cortex) associated with seeing in the
upper-left quadrant were detected using functional magnetic resonance imaging (fMRI). This
was compared to activity in that area elicited by the untrained eye and activity in that
area elicited by the same eye before training. According to Cecchi (2014: 85), the
voluntary covert attention required to detect the orientation of the lines required
guidance by the cognitive states of the subjects to select orientation as the feature to
be processed, and top-down signals to the cortex were observed (using fMRI), and
discovered to be necessary, for the task to be successfully carried out during the first
phase. The subjects were investigated again 24 hours later (during the “test” session),
after they had slept the night, and this time, again, the part of the V1 cortex
corresponding to seeing in the upper-left quadrant was observed to have increased activity
when activated by the trained eye. This is in contrast to when it was activated during the
same test session by the untrained eye, or the same eye before training. In both cases, no
increased activity was observed. However, this time, fMRI indicated that the increased
activity observed in the test session when using the trained eye did not require that top-
down cognitive or attentional influences occur. The increased responses occurred before
any top-down influences were observed. The same task performed by the untrained eye did
recruit higher-level cognitive and attentional influences.1 According to Schwartz (2002:
17140), training resulted in neural changes to the V1 area of the cortex, which had
learned to detect the orientation of the peripheral lines when seen by the trained eye.
during the training session, the constant and synchronic stimulation of striate visual
areas by cognitively guided attention resulted in physiological neural changes in the
visual system. Therefore, structural modulations occurring in the visual system due to
cognitively guided attention are the result of synchronic architectural cognitive
penetration.2 The successful detection of the peripheral object during the test session
was possible thanks to diachronic architectural cognitive penetration. The consolidation
of cognitively induced architectural modulations enabled the visual system to perform the
peripheral-detection task without synchronic cognitive intervention. At that point, the
cognitive influences that modified the architecture of the visual system were
diachronically produced. Thus Cecchi argues that there is cognitive penetration brought
about by means of attention. Cecchi argues that the penetration in question is both that
of early vision and that of perceptual experience. With regard to the first, changes to
the visual cortex occur in early vision, defined temporarily, as activity within the first
100 ms after stimulus presentation, because they occur around 60 ms after stimulus
presentation. With regard to the second, there are changes to the content of visual
experience, with experience coming to represent the orientation of the lines presented in
the periphery of the visual field. In this way, he argues that there can be cases of
cognitive penetration of the early visual system and of experience that involve attention.
Cecchi certainly presents us with a tough case to adjudicate. An alternative
interpretation of this case is that, in the first training phase of the experiment, the
attention involved is simply selecting what to process—items in the upper-left quadrant
and their property of orientation—and that this mere selection does not amount to
cognitive penetration. As mentioned above, one might claim that this is just like
selecting what to process as one might do by changing the direction in which one’s eyes
point—something that does not count as cognitive penetration. Moreover, one might claim
that in the second test phase of the experiment, subjects had simply gained better
eyesight, as one might gain from wearing glasses, which one has put on under the guidance
of cognition (such as one’s desire to see more clearly and one’s belief that one’s glasses
will facilitate that), or as one might gain by voluntarily squinting one’s eyes to see an
object in the distance more clearly (caused by one’s desire to see it and one’s belief
that squinting will accomplish that). Clearly such activities do not count as cognitive
penetration. It is not obvious to me how to adjudicate this case, but it is clear that the
question of whether cognitive penetration—of either early vision or of perceptual
experience—can involve attention is not a straightforward matter. The second issue with
the definition of cognitive penetration that I wish to discuss concerns why it specifies
that, in order for cognitive penetration to occur, a semantic or intelligible link is
necessary between the content of the cognitive state doing the penetrating and the content
of the perceptual experience, or the content of early vision, that is penetrated. Is such
a link necessary? For ease of exposition, I will discuss this case with respect to the
cognitive penetration of experience, but readers will be able to reconstruct with ease a
parallel discussion that could be made about the penetration of the content of early
vision. A semantic or intelligible link is posited as a necessary feature of cases of
cognitive penetration because the lack of such a link seems to explain our intuitions
about why some cases fail to be those of cognitive penetration.3 In other words, there are
some cases which, but for the lack of this link, would fall under the definition of
cognitive penetration, but which we are rightly disinclined to think are cases of
cognitive penetration. Here is one such case:In Migraine, your belief affects your visual
experience but, intuitively, this is not a case of cognitive penetration. It is merely an
instance of a migraine brought on by belief-triggered stress. This is because there is no
semantic or intelligible link between the belief that you have an exam tomorrow and the
subsequent visual experience that you have as of flashing lights. If we hold that such a
link is necessary for a case of cognitive penetration, its absence explains why the case
is not one of cognitive penetration. However, one might question whether the lack of such
a link really does explain why such cases should not count as cases of cognitive
penetration. For one can gerrymander the above type of case to yield one that is very
similar, in which there does seem to be a semantic or intelligible link, and yet the case
still does not appear to be one of cognitive penetration. For example, consider the
following case:In Migraine’s Revenge, as in Migraine, your belief affects your subsequent
visual experience; yet, intuitively, the case is not one of cognitive penetration, merely
a case of migraine. However, in Migraine’s Revenge, unlike in Migraine, there is a
semantic or intelligible link between your belief that aliens might land on earth and your
subsequent perceptual experience of flashing lights in the sky. (However improbable, it is
entrenched in popular culture that aliens coming to Earth arrive in spaceships that have
flashing lights.) So, it would seem that, in Migraine’s Revenge, it is not the lack of a
semantic link that explains why it is not a case of cognitive penetration. Given this, as
well as its similarity to Migraine, one might conclude that the lack of such a link also
does not explain why Migraine fails to be a case of cognitive penetration. If the lack of
a semantic link does not rule out both Migraine and Migraine’s Revenge as cases of
cognitive penetration, what other condition would? I believe that we can find a suitable
condition, not by abandoning a semantic or intelligible link as a necessary condition for
cognitive penetration, but by adding to, and thereby strengthening, the condition. I
believe that what goes wrong in Migraine’s Revenge is that the semantic or intelligible
link is accidental. After all, I deliberately gerrymandered Migraine to yield a case in
which there just so happened to be such a link. I believe that what is required in cases
of cognitive penetration is that there be a causal, semantic link between each of the
steps in the chain that lead from the belief to the subsequent perceptual experience.4
This does not exist in Migraine’s Revenge. That case is one in which one’s belief that
aliens might land causes one to be stressed, which causes a migraine, which in turn causes
one’s perceptual experience of flashing lights. While there is a semantic link between the
content of the belief and the content of the perceptual experience, the link is not a
causal link. Moreover, there is not a causal, semantic link between the content of the
belief and the subsequent state of stress. There is a causal link but not a semantic one.
A state of stress is a physiological state that does not have content. Even if one thought
that states of stress could have content (perhaps content about the source of the stress
or the content that something bad was going to happen), the state of having a migraine is
clearly not such a state. So there is no causal, semantic link between the state of one
being stressed and the state of having a migraine. Moreover, there is no causal, semantic
link between the state of having a migraine and the state of experiencing flashing lights
in the sky. Note that I proposed (2012) a mechanism by which cognitive penetration could
occur. It was one in which a belief caused some imaginative state or imaginative
processing to come into existence, which in turn causally interacts with one’s experience
yielding an experience that has content influenced both by perception and imagination.
This mechanism could be a mechanism whereby cognitive penetration occurs because it allows
for the existence of causal, semantic links at each stage of the process. I take it to be
a virtue of the proposed mechanism that it could allow for a causal, semantic link between
each of the steps, which I take to be necessary for cognitive penetration. In this
section, I have looked at what cognitive penetration is and how it should be defined. I
noted that there are two distinct phenomena that go under its name: penetration of the
early visual system and penetration of perceptual experience. I explained that there are
hard questions to answer about whether there can be a role for attention in cases of
cognitive penetration, and I explained why I believe that a necessary condition for
cognitive penetration is that there be a causal, semantic link between each step in the
process whereby a belief comes to affect perceptual experience. In the next section, I
consider what predictive coding accounts of perception are by outlining the minimal
commitments of such an account.

<h>PREDICTIVE CODING ACCOUNTS OF PERCEPTION</h>
----------------------------------------

The minimal commitments of the predictive coding account of perception are as follows:
Based on knowledge, assumptions, and expectations at different high-level processing
stages, the brain produces top-down generative representations of the world that are
predictions of how the world is. Those representations are then modified bottom-up by
incoming signals, which are propagated upwards only as a prediction error signal. Those
representations are then further modified by top-down high-level processing, and perhaps
sideways by other sensory modalities. The aim of these modifications are to reduce global
prediction error. The processing is typically thought to be done according to Bayesian
rules.5 I will refer to (i)–(v) as the ‘minimal form of predictive coding’. As we will
come to see in later sections, there are many, more specific, forms of predictive coding
accounts of perception. We will see the ramifications of these further forms for the
relationship between predictive coding and cognitive penetration.

<h>POSSIBLE RELATIONSHIPS BETWEEN PREDICTIVE CODING AND COGNITIVE PENETRATION</h>
--------------------------------------------------------------------------

There are three possible relationships between predictive coding accounts of perception
and cognitive penetration: predictive coding entails cognitive penetration; predictive
coding is compatible with, but does not entail, cognitive penetration; predictive coding
is incompatible with cognitive penetration. In each case, ‘cognitive penetration’ might
mean either penetration of the early visual system or penetration of perceptual
experience. One motivation for exploring which of (a), (b) or (c) is true (or, as we will
come to see below, whether any one of these positions is true) is because they have been
endorsed by different people. Arguably Lupyan (2015a, 2015b) endorses (a). He certainly
comes very close to explicitly endorsing it. For example, he states: penetrability should
be expected whenever constraining lower-level processes by higher level knowledge
minimizes global prediction error, My goal, however is not to simply argue that perception
can be cognitively penetrated, but to present a theoretical framework on which cognitive
penetrability is expected as a natural part of how perception works.” The primary goal of
this paper is to show that the controversy surrounding cognitive penetrability of
perception (CPP)—the idea that perceptual processes are influenced by “non-perceptual”
states—vanishes when we view perception not as a passive process the goal of which is
recreation of a veridical reality, but rather as a flexible and task-dependent process of
creating representations for guiding behavior. My goal is to … argue that there is no in-
principle limit on the extent to which a given perceptual process can be penetrated by
knowledge, expectations, beliefs, etc. Thus Lupyan thinks that if the predictive coding
model of perception is correct then we should expect there to be cognitive penetration,
and that the model entails that mechanisms exist that allow it to happen. Clark (2013),
prima facie at least (but I will explore other interpretations of him below), believes
that predictive coding entails cognitive penetration too. He says that predictive coding:
makes the lines between perception and cognition fuzzy … In place of any real distinction
between perception and belief we now get variable differences in the mixture of top-down
and bottom-up influence … To perceive the world just is to use what you know to explain
away the sensory signal across multiple spatial and temporal scales. The process of
perception is thus inseparable from rational (broadly Bayesian) processes of belief
fixation, and context (top-down) effects are felt at every intermediate level of
processing. In my (2015) paper, I argued for a version of (b): that the minimal form of
predictive coding is consistent with, but does not entail, the cognitive penetration of
perceptual experience.6 Drayson (unpublished manuscript) claims this too. With respect to
the penetration of early vision, no one has yet commented. I suspect that is because this
issue is particularly thorny on account of what predictive coders can say about what early
vision is—a topic that I address in Section 7. I know of no one who explicitly endorses
(c), however, I think that one reading of Clark (2013) would have him believe (c) with
respect to the penetration of perceptual experience. I will explore this in Section 5.
What to make of (c) with respect to early vision, is a question that requires detailed
consideration that, as previously stated, I will provide in Section 7. The most
expeditious way to determine whether (a), (b), or (c) is true is not to address them each
in in order but to consider, in turn, the following three questions: Do cognitive states
feature in the predictive coding account of perception? If cognitive states do feature, is
there reason to think that they penetrate perceptual experience? If cognitive states do
feature, is there reason to think that they penetrate early vision? I do so, respectively,
in Sections 5,6, and 7.

<h>DO COGNITIVE STATES FEATURE IN THE PREDICTIVE CODING ACCOUNT OF PERCEPTION?</h>
---------------------------------------------------------------------------

Should the high-level processes posited by predictive coders be taken to include cognitive
states of subjects? By ‘cognitive states’ I mean doxastic states—states that are
accessible to consciousness and inferentially integrated—such as beliefs and desires. Or
should they be taken to be sub-doxastic information-carrying states of the brain that the
subject does not in principle have access to?7 The minimal account of predictive coding,
outlined above, simply states that perceptual representations of the world are produced by
high-level processes—high-level in relation to the level of perceptual experiences. The
account leaves it open whether those high-level processes include cognitive states. This
shows that the minimal form of the predictive coding account does not entail cognitive
penetration of either the early visual system or experience. Does it show that predictive
coding is consistent with cognitive penetration sometimes or always occurring? The answer
will depend on whether we hold that cognitive states sometimes or always affect early
vision or perceptual experience—an issue that I will address shortly. One could simply
stipulate two different versions of the predictive coding account each of which would be a
precisification of the minimal account. According to a first, the high-level states that
make the predictions sometimes or always involve cognitive states; according to a second,
the high-level states in question never involve cognitive states. Whether the first
version entails or is consistent with cognitive penetration will depend on whether we
think cognitive states sometimes or always affect early vision or perceptual experience—as
was the case with the minimal account. The second account would entail that cognitive
penetration of either early vision or perceptual experience never occurs, for cognitive
states are not involved in the production of perceptual representations. Which version of
the theory do predictive coders actually put forward? Predictive coders often talk about
knowledge, beliefs, information, expectations, priors, and so on feeding into the
production of perceptual representations from high levels. But should we take some of this
talk as literally talk of cognitive states? Lupyan (2015a) is very clear that he thinks we
should: there is no in-principle limit on the extent to which a given perceptual process
can be penetrated by knowledge, expectations, beliefs, etc. The actual extent to which
such penetrability happens can be understood in terms of whether it helps to lower system-
wide (global) prediction error. In evolving to minimize prediction error neural systems
naturally end up incorporating whatever sources of knowledge, at whatever level, to lower
global prediction error. And, in addition, it is clear that the specific examples of
cognitive penetration that Lupyan (2015a) discusses are ones in which semantic doxastic
states of knowledge and belief, as well as other cognitive states, affect perception. This
view would entail that there is cognitive penetration if and only if those cognitive
states can be seen to affect early vision or perceptual experience (as Lupyan argues that
they do). Hohwy (2013) argues for the same position. In Sections 6 and 7, I will
investigate this later claim for predictive coding accounts of perception in which
cognitive states play a role. For now, however, in the rest of this section, I will
explore whether other philosophers accept that cognitive states play a role in the
predictive coding account of perception, and what follows from that about cognitive
penetration. Consider Clark’s (2013) view. Although I noted above in Section 4 that, prima
facie, he holds that cognitive states penetrate perceptual states, there is quite a bit of
room to doubt this. He often talks about sub-personal states of the brain having a top-
down influence and, when he writes about “belief” having an influence, he often puts the
word in quotation marks, signalling an unorthodox usage. Moreover, he never explicitly
states that the highest level corresponds to doxastic level cognitive states. And while he
clearly recognises that perception can influence doxastic belief, he doesn’t explicitly
mention the reverse case (2013: 17). Furthermore, when he mentions the debate concerning
whether perception is theory-laden he says that it is “in at least one (rather specific)
sense: What we perceive depends heavily upon the set of priors … that the brain brings to
bear in its best attempt to predict the current sensory signal” (2013: 7), thereby not
explicitly mentioning cognitive states. All of this might suggest that Clark does not
think that cognitive states are involved. This is the reading of Clark that Drayson
endorses. She says: “I suggest that Clark’s ‘assumptions’ are like Churchland’s
assumptions in that they ‘have nothing to do with beliefs, theories, or other doxastic
commitments that we may have’ … (Stokes, in press)” (unpublished manuscript: 4). In
consequence, she claims: “[Clark’s] model of the brain is entirely consistent with the
traditional view of perception and cognition. In particular, the debate over the cognitive
penetrability of perception is left untouched” (unpublished manuscript: 1). While this
radical reading of Clark is not implausible, and there could be a version of predictive
coding that stipulated cognitive states did not play a role, it seems to me that there is
an even more radical reading of Clark that is at least as good a reading of Clark as
Drayson’s. On this super radical reading, Clark thinks that there is no distinction, or at
least no sharp distinction, between perception and cognition. He says: These accounts thus
appear to dissolve, at the level of the implementing neural machinery, the superficially
clean distinction between perception and knowledge/belief. To perceive the world just is
to use what you know to explain away the sensory signal across multiple spatial and
temporal scales. The process of perception is thus inseparable from rational (broadly
Bayesian) processes of belief fixation, and context (top-down) effects are felt at every
intermediate level of processing. As thought, sensing, and movement here unfold, we
discover no stable or well-specified interface or interfaces between cognition and
perception. Believing and perceiving, although conceptually distinct, emerge as deeply
mechanically intertwined. On this interpretation of Clark, one should be eliminativist
about the normal categories such as perception and cognition that traditional views of the
mind ascribe to. If that is right, then according to such a view, there can be no
cognitive penetration for cognitive penetration requires such a distinction. When I
discussed (2015: 582) this view as a possible version of predictive coding Lupyan replied
that, “I am aware that in the process of challenging these distinctions”, such as, the
presence of a clear boundary between (modal) perception and (amodal) cognition/semantics …
I am supporting a collapse of perception and cognition that makes the whole question of
the penetrability of one by the other, ill-posed. But I would be thrilled if I my
arguments contribute to the eventual demise of this question”. Here Lupyan is more
cautious with respect to his previous (2015a) commitment to the role of cognitive states
in predictive coding and their role in cognitive penetration. Clearly, this is a view of
the mind that predictive coders may consider adopting. This version of the predictive
coding account of perception entails that there is no cognitive penetration of perception
(either of early vision or of perceptual experience), for there is no cognition and there
is no perception. A slightly less radical reading of Clark would be that cognition and
perception lie on either ends of a spectrum and that cognitive penetration happens when
there is the right kind of influence by states that lie on the more cognitive end of the
spectrum on states that lie on the more perceptual end. Indeed, Clark sometimes writes as
if this were the case, saying that the higher-level something is the “more cognitive” and
the lower is the “more perceptual” (2013: 10). One might surmise that the highest levels
correspond to doxastic beliefs and desires and the lowest levels to perceptual states. On
this account of predictive coding, it entails that there is cognitive penetration. Still,
the picture that Clark paints is unclear between the four options just outlined. And
Lupyan seems as yet undecided about his final view. Thus, predictive coders should, I
think, give further consideration to these questions, specify more precisely which version
of predictive coding they wish to endorse, and in that light, reconsider the claims that
they make about the relationship between predictive cognitive penetration. To summarise
this section, the minimal version of predictive coding leaves open whether cognitive
states are some of the high-level states that generate perceptual representations. Given
this, the minimal version does not entail, but is consistent with, cognitive penetration.
Lupyan’s (2015a) and Hohwy’s (2013) version of predictive coding stipulates that cognitive
states are some of the high-level states. If those cognitive states can be seen to affect
early vision or perceptual experience, this version of the theory entails cognitive
penetration. (I will explore this issue in detail below). Clark is not particularly clear
about whether his version of predictive coding stipulates that cognitive states are some
of the high-level states. A super radical reading of him would suggest that there is no
distinction between cognition and perception and so no cognitive penetration.
Interestingly, we saw Lupyan (2015b) indicate that he would consider such a position. A
less radical reading of Clark would suggest that perception and cognition lie on a
continuum and that cognitive penetration occurs when states that lie far on the cognitive
side affect states that lie far on the perceptual side (in the right way).

IF PREDICTIVE CODING INVOLVES COGNITIVE STATES, IS THERE REASON TO THINK THAT THEY PENETRATE PERCEPTUAL EXPERIENCE?
--------------------------------------------------------------------------------

Recall that in Section 2, I outlined two forms of cognitive penetration. One was the
penetration of perceptual experience; the other was the penetration of early vision. In
this section, I will focus on the former. Recall that perceptual experience is a conscious
state that has a distinctive perceptual phenomenal character. It is the state that we go
into when we consciously see, hear, touch, and so on, but also a state that we go into
when we consciously hallucinate. The phenomenal character of a perceptual experience of a
red rose in front of one (or better as of a red rose in front of one, to include the case
of hallucination) is distinct from the phenomenal character of the corresponding belief
that there is a red rose in front of one—a belief that one often has when one experiences
a red rose (but not always, for one sometimes believes, rightly or wrongly, that one may
be suffering from an illusion or hallucination). If cognitive states are involved in the
predictive coding that produces perception, is there reason to think that those cognitive
states penetrate perceptual experience? In order to answer this question, we must ask:
what exactly does the predictive coding account of perception say about perceptual
experience? Clark (2013) explains what he and Hohwy, Roepstorff, and Friston (2008) hold
is perceptual experience, according to the predictive coding account: [it] is determined
by a process of prediction operating across many levels of a (bidirectional) processing
hierarchy … and their interactive equilibrium ultimately selects a best overall
(multiscale) hypothesis concerning the state of the visually presented world. This is the
hypothesis that ‘makes the best predictions and that, taking priors into consideration, is
consequently assigned the highest posterior probability’ (Hohwy et al., 2008, p. 690).
Other overall hypotheses, at that moment, are simply crowded out: they are effectively
inhibited, having lost the competition to best account for the driving signal.” In short,
perceptual experience is identified with the best—i.e. surviving—prediction or
representation of how the world is. And that is generated by high-level and low-level
processing. If one holds that the high-level states are cognitive states (or cognitive
enough), then this will entail that perceptual experience is affected by cognition
according to predictive coding, and that there is cognitive penetration. Hohwy (2013)
holds this position. (Of course, as we have seen, one might desist from this opinion and
hold a version of predictive coding that is silent about whether high-level states are
cognitive, that denies that cognitive states are involved, or that denies the
cognition/perception distinction. These versions will not entail that there is cognitive
penetration, with the last two entailing that there is no cognitive penetration.) So far,
things have been reasonably straightforward. However, the matter becomes more complex when
we consider what predictive coding says about the penetration of early vision, as I
explain in the next section.

IF PREDICTIVE CODING INVOLVES COGNITIVE STATES, IS THERE REASON TO THINK THAT THEY PENETRATE EARLY VISION?
--------------------------------------------------------------------------------

Recall from Section 2, that early vision was defined functionally as the system that takes
in information from the eyes (perhaps via attention) and produces shape, size and colour
representations. How might predictive coders understand early vision? One option for
predictive coders would be to think of early vision, neutrally, as the system—whatever it
is—that produces shape, size and colour representations. According to the predictive
coding account, high-level systems produce those representations, causally affected by
information from the eyes. The information from the eyes therefore feeds into the high-
level system that produces those representations; therefore, the whole system, including
high-level states will count as early vision. That’s a very odd result—and a very strange
conception of early vision! Suppose, for the sake of argument, that we accepted this
conception. (I realise that one might object to it.) In that case, a version of the
predictive coding account that said that cognitive states were involved would entail that
cognitive penetration of early vision occurred. (And if a version of predictive coding was
non-committal about whether cognitive states were involved (such as the minimal version)
then it would be consistent with but not entail cognitive penetration of early vision. If
a version denied that cognitive states were involved, then the view would entail that
there was no cognitive penetration of early vision.) As I indicated above, one might
object to this account of early vision on the grounds that it is at odds with the
conception of it conceived of by Pylyshyn (1999). Therefore, one might reconsider what
predictive coders should take early vision to be. Pylyshyn thought that his functional
definition would be realized by signals coming from the eyes, perhaps after being filtered
by attention, and then a limited portion of bottom-up processing thereafter. Given this,
one approach predictive coders might adopt would be to follow Raftopolous and espouse a
temporal conception. Raftopoulos (2014: 603) states: “Early vision … includes a feed
forward sweep (FFS) in which signals are transmitted bottom-up and which lasts, in visual
areas, for about 100 ms.” If we take the first 100 ms of processing to be early vision,
what does predictive coding say about that? Does the high-level predictive signal reach
down as low as this, or does the first 100 ms contain only an incoming signal that will,
in due course, be treated as an error signal? To my knowledge, the current literature on
predictive coding does not address this question. Standard evidence concerning whether
there is any top-down influence on the first 100 ms of processing would be what we would
look to.8 Whether there is penetration of early vision, considered as the first 100 ms of
processing, will depend on such evidence (and, of course, as we have seen previously on
whether such high-level processes include cognitive states of subjects). There is another
conception of early vision that a predictive coder might appeal to. Recall the functional
definition given by Pylyshyn: it is the system that takes in information from the eyes
(perhaps via attention) and produces shape, size and colour representations. A predictive
coder might claim, contra Pylyshyn, that there is no system that takes in information from
the eyes (perhaps via attention) and produces shape, size and colour representations.
Instead, they could claim that such representations are produced top-down. This would
amount to the denial that there is such a thing as early vision! If that is right, then
predictive coding is incompatible with the penetration of early vision. Predictive coding
entails that there is no cognitive penetration of early vision as there is no such thing
as early vision. To summarise this section, I have outlined that there are three
conceptions of early vision that someone who endorses the predictive coding account of
perception might adopt: that it includes all processing (including top-down processing)
that produces shape, size and colour representations; that it is that which occurs during
the first 100 ms of processing; that it doesn’t exist. Predictive coding entails
penetration of early vision conceived of as in (1) if and only if the high-levels contain
cognitive states. Predictive coding entails, or is compatible with, penetration of early
vision conceived of as in (2) if and only if the empirical evidence turns out the right
way, and the high-levels contain cognitive states. Predictive coding in any form is not
compatible with penetration of early vision conceived as in (3).

<h>CONCLUSION</h>
----------

The results of the above discussion of various forms of predictive coding accounts of
perception and various different forms of cognitive penetration are summarized in Table 1.
As discussed previously, some proponents of the predictive coding account of perception
have claimed that it entails that cognitive penetrations occurs. I have argued that the
claim that the predictive coding account entails cognitive penetration is too simplistic.
This is because the relationship between the predictive coding account of perception and
cognitive penetration is dependent on both the specific form of the predictive coding
account and the specific form of cognitive penetration. I have spelled out different forms
of each and the relationships that hold between them. While some forms of predictive
coding entail some forms of cognitive penetration, some are consistent with but do not
entail some accounts of cognitive penetration, and some entail that there is no cognitive
penetration. However, many of those forms of predictive coding that entail that cognitive
penetration does not occur do so because they give such a radically different account of
the mind compared to the standard conception of it. That is, they rule out the existence
of cognitive penetration on the grounds that the components of the mind required to play a
role in cognitive penetration do not exist. As we have seen, some accounts deny that there
is a distinction to be made between perception and cognition and some deny that there is
any such thing as early vision. Such models allow for a great deal of top-down processing
of the sort that those who have heretofore argued that there is no cognitive penetration
would not endorse. In consequence, mere acceptance of the predictive coding approach to
perception does not determine whether one should think that cognitive penetration exists.
Moreover, as is demonstrated by the preceding sections, establishing as true the version
of predictive coding that does entail cognitive penetration occurs will turn on
determining many of the same issues as are required for directly establishing cognitive
penetration occurs, such as determining that there are there top-down cognitive effects by
cognitive states on perceptual experience or early vision. Thus, arguing for cognitive
penetration via establishing that predictive coding is the right account of perception
does not actually provide a novel means of establishing that cognitive penetration occurs.
Nonetheless, it is clear that many forms of predictive coding models of perception either
entail that cognitive penetration occurs or they entail that top-down processing of a
radical kind occurs—of such a radical kind that they entail a picture of the mind greatly
at odds with that accepted by those who believe in cognitive penetration. Finally, a
general lesson of this paper is that, given that there are such different conceptions of
both predictive coding and cognitive penetration, researchers should cease talking of
either without making clear which form they refer to, if they aspire to make true
generalisations.


<h>REFERENCES</h>
----------

  [1] Ariel S. Cecchi. Cognitive penetration, perceptual learning and neural plasticity. doi:10.1111/1746-8361.12051
  [2] Andy Clark. Whatever next? Predictive brains, situated agents, and the future of cognitive science. doi:10.1017/S0140525X12000477
  [6] Jakob Hohwy, Andreas Roepstorff, Karl Friston. Predictive coding explains binocular rivalry: An epistemological review. doi:10.1016/j.cognition.2008.05.010
  [7] Gary Lupyan. Cognitive Penetrability of Perception in the Age of Prediction: Predictive Systems are Penetrable Systems. doi:10.1007/s13164-015-0253-4
  [8] Gary Lupyan. Reply to Macpherson: Further illustrations of the cognitive penetrability of perception. doi:10.1007/s13164-015-0255-2
  [9] Fiona MacPherson. Cognitive penetration of colour experience: Rethinking the issue in light of an indirect mechanism. doi:10.1111/j.1933-1592.2010.00481.x
  [10] Fiona Macpherson. Cognitive Penetration and Predictive Coding: A Commentary on Lupyan. doi:10.1007/s13164-015-0254-3
  [11] Zenon W. Pylyshyn. Is vision continuous with cognition? The case for cognitive impenetrability of visual perception. doi:10.1017/S0140525X99002022
  [12] Athanassios Raftopoulos. The cognitive impenetrability of the content of early vision is a necessary and sufficient condition for purely nonconceptual content. doi:10.1080/09515089.2012.729486
  [13] Sophie Schwartz, Pierre Maquet, Chris Frith. Neural correlates of perceptual learning: A functional MRI study of visual texture discrimination. doi:10.1073/pnas.242414599
<ART>The relationship between information processing style and information seeking, and its moderation by affect and perceived usefulness: Analysis vs. procrastination
================================================================================

Authors: Emma Soane, Iljana Schubert, Rebecca Lunn, Simon Pollard
DOI: 10.1016/j.paid.2014.08.029
Year: 2015  |  Pages: 72-78
ASJC codes: 3200
Keywords: Decision making, Dual process theory, Information processing, Information seeking, RISP theory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We examined the relationship between information processing style and information seeking, and its moderation by anxiety and information utility. Information about Salmonella, a potentially commonplace disease, was presented to 2960 adults. Two types of information processing were examined: preferences for analytical or heuristic processing, and preferences for immediate or delayed processing. Information seeking was captured by measuring the number of additional pieces of information sought by participants. Preferences for analytical information processing were associated positively and directly with information seeking. Heuristic information processing was associated negatively and directly with information seeking. The positive relationship between preferences for delayed decision making and information seeking was moderated by anxiety and by information utility. Anxiety reduced the tendency to seek additional information. Information utility increased the likelihood of information seeking. The findings indicate that low levels of anxiety could prompt information seeking. However, information seeking occurred even when information was perceived as useful and sufficient, suggesting that it can be a form of procrastination rather than a useful contribution to effective decision making.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Information seeking is a critical component of effective decision making (Griffin,
Dunwoody, & Neuwirth, 1999), yet information seeking can be a mechanism for delaying
decisions (Jepson & Chaiken, 1990). Hence, a process model must be applied to understand
the difference between information seeking as an analytical strategy versus information
seeking as procrastination. This study examined the relationship between information
processing styles (how decisions are made) and information seeking (the extent to which
information is sought), and its moderation by anxiety and information utility. We
integrate insights from the risk and information seeking and processing theory (RISP,
Griffin et al., 1999), dual process theory (Epstein, 1990; Epstein, Pacini, Denes-Raj, &
Heier, 1996), and broaden-and-build theory (Fredrickson, 1998, 2001) to develop and test a
model that accounts for individual-level information seeking behaviour, and the
contingencies that lead to information seeking as a form of procrastination.

<hs>  Information processing styles</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Information processing styles, typically characterised as tendencies to use analytical or
intuitive (heuristic) approaches to choice (Dane & Pratt, 2007) influence decision
processes and outcomes. Analytical processes are required for novel, complex problems
whereas intuitive or heuristic processes are applied to numerous daily choices (Bargh,
Chen, & Burrows, 1996; Epstein, Lipson, Holstein, & Huh, 1992). Theories of analytical and
heuristic thinking rest on the dual-process concept which proposes two parallel,
interactive systems of thinking (Epstein, 1990; Epstein et al., 1996). System 1 is
intuitive, affect-laden and rapid. System 2 is cognitive, resource intense and requires
time. Both systems yield positive outcomes. Analytical thinking is associated with
effective decision making due to logical reasoning and fewer decision biases (Stanovich &
West, 2002), and ability to focus on important aspects of information relevant to
decisions rather than non-relevant contextual information (McElroy & Seta, 2003).
Intuitive thinking is associated with expertise (Dreyfus & Dreyfus, 2005) and
effectiveness in solving everyday problems (Todd & Gigerenzer, 2007).

<hs>  Individual differences in information processing and information seeking</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

While the dual-process model has universal application, the extent to which System 1 and
System 2 are applied, and the situational contingencies that influence their use, are
subject to individual differences (Epstein et al., 1996). Therefore, theories that rest on
dual-process modelling need to take into account individual-level antecedents and
moderating factors. Employing this approach, Griffin et al. (1999) developed the risk
information seeking and processing (RISP) model. They proposed information seeking is
driven by individual differences in perceived information sufficiency, and continues until
the point of sufficiency is reached. Griffin et al. (1999) placed information seeking and
information processing together as the dependent variables in their model, and proposed
that they combine to produce four decisions styles relating to routine/non routine and
heuristic/systematic processing. However, recent research into decision processes, also
building on dual process models, has added a second information processing style:
regulatory processes that influence whether a decision should be made immediately or
delayed Dewberry, Juanchich, and Narendran (2013a) proposed both cognitive information
processing (rationality vs. intuition) and regulatory information processing have direct
effects on decision outcomes. For example, when faced with a decision about whether to eat
food that could harbour harmful bacteria, there are choices about whether to go with past
experience, i.e. if eating the food has been alright before then it will be alright at
this decision point (heuristic processing); or, whether to find out more about the
likelihood of bacteria being present in the food product (analytical processing). There
are also choices regarding whether to find out the relevant information now (preference
for immediate decision making), or whether to put off information seeking until a later
date (preference for delayed decision making). Therefore, we propose that perceived
information sufficiency, and preferences for analytical and delayed decisions will be
associated directly and positively with information seeking. Conversely, we propose that
preferences for heuristic and immediate decisions will be associated directly and
negatively with information seeking. Individual differences in age and gender also
influence decision processes. Older adults are more likely to draw on their history of
life experiences when making choices (Finucane, Mertz, Slovic, & Schmidt, 2005), and this
increases the likelihood of greater information seeking. Moreover, women tend to be more
risk averse when making decisions, and less confident in their choices than men (Graham,
Stendardi, Myers, & Graham, 2002), thus increasing tendencies for information seeking.
Thus we expect that older adults and women will be more likely to seek information than
younger adults and men.

<hs>  Moderators of the relationship between information processing and information seeking</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Dewberry et al. (2013a) and Dewberry, Juanchich, and Narendran (2013b) suggested that
anxiety could increase information seeking in order to delay decision making, because the
point of choice causes anxiety, so putting off a decision reduces current experiences of
anxiety. In a more complete modelling of the relationship between affect and behaviour,
Frederickson’s broaden-and-build theory (Fredrickson, 1998, 2001) proposed that positive
affect has a broadening and building effect, increasing effectiveness of decisions made.
Conversely, anxiety reduces thought-action repertoires and constricts decision processes
by limiting access to memory and the cognitive strategies necessary for problem solving.
In addition, Fredrickson’s (1998) model suggests that affect moderates the relationship
between preferences, perceptions and actions, and this has been confirmed empirically
(Soane et al., 2013). Hence, we propose that anxiety moderates the relationships between
information processing styles and information seeking because it increases tendencies to
search for information that could allay anxiety, and the process delays the pressure of
choice. We also propose that information perceptions influence the relationship between
information processing style and information seeking. Griffin et al. (1999) suggested that
information will be sought when current information is believed to be insufficient.
However there will be contingencies that influence this process. Specifically, information
utility moderates the relationship between antecedent factors and information seeking
(Griffin et al., 1999). Examining this contingency is important to distinguish between
information seeking as analytical information processing, and information seeking as a
strategy to delay decision making (Bohner, Chaiken, & Hunyadi, 1994; Dewberry et al.,
2013a, 2013b). We suggest that perceptions of context-specific information utility will
moderate the relationship between information processing style and information seeking.

<hs>  Summary of the current study</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The current study tested a model of information seeking We hypothesised that the
relationship between analytical information processing style and information seeking will
be positive, and moderated by anxiety, and the information utility. We also hypothesised
that the relationship between heuristic information processing style and preference for
delaying decisions will be negatively associated with information seeking, and that the
negative relationship will be strengthened by anxiety and information utility. Finally, we
hypothesised that preferences for delayed decisions will be associated negatively with
information seeking, and that the relationship will be moderated by anxiety and
information usefulness.

<hs>  Research context</hs>
  ~~~~~~~~~~~~~~~~

To test the research model, we examined a widespread disease, Salmonellosis, that
continues to be a threat to human health and a financial burden on society. In Europe,
Salmonellosis is the second most common zoonotic disease in humans (after Campylobacter)
(European Food Safety Authority, 2010). The most common way of contracting Salmonellosis
is through the consumption of raw egg and raw egg products. Although Salmonella bacteria
need not cause disease, the incidence of Salmonellosis indicates that changes in domestic
behaviour are required to reduce its impact on society. Hence examining decision making in
the context of Salmonellosis contributes to practical strategies regarding disease
management as well as to understanding decision processes.

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

An online survey website was used to recruit 3001 participants to complete a questionnaire
on food safety. Participants were emailed an invitation to participate in the research and
a clickable link to access the survey. Survey responses were stored on the research team’s
secure server. Twenty-seven participants were excluded from the analysis because they
stated that they had an allergy to either chocolate or eggs and would not eat the
chocolate mousse. Fourteen were excluded due to missing data. The final sample was 2960
(96.8% of completions). The mean age was 40.59 (range 18–82, SD = 12.95). There were 1613
men (54.5%) and 1347 women (45.5%). 1102 (37.2%) had a degree or above; 362 (12.2%) had
other higher education; 580 (19.6%) had A levels or equivalent; 618 (20.9%) had GSCEs or
equivalent (20.8%); 125 (4.2%) had other qualifications; the remaining 111 (3.8%) had no
qualifications.

<hs>  Materials</hs>
  ~~~~~~~~~

We focused on a food product, home-made chocolate mousse containing eggs, a common source
of Salmonellosis and a widely consumed food item. Age was assessed by asking participants
to write their age. Gender was assessed by self-rating ‘male’ or ‘female’. Effect of past
experience was measured by one item adapted from Miles and Frewer (2001) which asked
participants to rate the extent to which past experience has provided them with
information about salmonella prevention. There was a 5-point response range from 1
‘strongly disagree’ to 5 ‘strongly agree’. Anxiety was assessed based on Watson and
Tellegen’s (1985) emotion circumplex. Items were ‘I am anxious about being infected with
salmonella from eggs’ and ‘I am worried about being infected with salmonella from eggs.’
There was a 5-point response range, 1 ‘strongly disagree’ to 5 ‘strongly agree’.
Information sufficiency was measured by two items measuring perceived sufficiency of
current information, and adapted from Trumbo and McComas (2003). ‘The information I have
at this time meets all of my needs for knowing about how to protect myself from salmonella
from eggs’; ‘I have been able to make a decision about how concerned I am about the risk
of salmonella in eggs to me by using my existing knowledge’. There was a 5-point response
range, 1 ‘strongly disagree’ to 5 ‘strongly agree’. Information utility was assessed using
items developed for this study. Participants were presented with four pieces of
information: (1) A description of the likelihood of the prevalence of Salmonella in eggs.
(2) A description of the reduction of the prevalence of Salmonella in eggs in England
between 1995 and 2003. (3) Percentages describing the likelihood of the prevalence of
Salmonella in eggs. (4) A graph format showing the reduction of the prevalence of
Salmonella in eggs in England between 1995 and 2003. After each piece of information,
participants were asked how useful the information was to evaluating whether to eat the
mousse or not. There was a 5-point response range from 1 ‘Not at all useful’ to 5 ‘Very
useful’. The scale is a mean score of all four items. Information processing styles were
measured as four distinct constructs rather than as two bipolar continua following
recommendations from Hodgkinson, Sadler-Smith, Sinclair, and Ashkanasy (2009). Four types
of information processing style were assessed using scales from Dewberry (2008). All items
were in the form of a statement followed by a three-point response range: 1 ‘Disagree’, 2
‘Uncertain’, 3 ‘Agree’. A sample item from each scale is included with permission from the
author (Dewberry, 2008). Analytical information processing was assessed using a three-item
scale. Items assessed the extent to which information is sought prior to making a
decision, for example, ‘When deciding on something important, I usually stick with the
information I already have rather than looking for more’. Heuristic information processing
was measured using a three-item scale. Items assessed tendencies to use current knowledge
to make a decision rather than information search strategies. A sample item is ‘When
making an important decision, I tend to go on the facts I have before me rather than
looking around for more information’. Preference for making immediate decisions was
assessed using a two-item scale. For example, ‘If I have to make a decision, I start
thinking about it straight away.’ Preference for delaying decisions was measured using two
items. An example is ‘If I have difficult decision to make, I tend to put it off’.
Information seeking behaviour, the dependent variable, was captured by offering
participants four extra pieces of information which they could choose to look at. The
options were: information concerning health effects of Salmonella; prevalence of
Salmonella; national attempts to control Salmonella in eggs; and, individual risk
reduction. Items were developed for this study. Participant access to each piece of
information was recorded and used to create an index ranging from 0 to 4.

<h>RESULTS</h>
-------

Table 1 shows the means, standard deviations, Cronbach’s alpha where appropriate and
inter-scale correlations.

<hs>  Confirmatory factor analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We then examined the model using SEM Confirmatory Factor Analysis in Amos 19. Data
indicated that the model fit was acceptable (Hair, Black, Babin, & Anderson, 2009): χ2 =
537.4; df = 114; CFI = .98; NFI = .98; RMSEA = .04; SRMR = .04, apart from the χ2/df value
which is 4.7. However, the χ2/df value is sensitive to large sample sizes (Hair et al.,
2009) so we proceeded with hypothesis testing.

<hs>  Hierarchical linear regression</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Next we used hierarchical multiple regression for the first stage of hypothesis testing.
All continuous variables were standardized using the Z transformation prior to analysis.
Model 1 examined direct effects of age, gender, experience, information processing,
anxiety, information utility and sufficiency. Model 2 added interaction terms (anxiety,
utility and sufficiency × each of the information processing styles). Data are shown in
Table 2. Model 1 data showed main effect positive associations between preferences for
analytical thinking, tendency to delay decision making, information sufficiency,
information utility and information seeking. There were negative associations between
heuristic information processing style, anxiety, and information seeking. Thus there was
some initial support for our hypotheses concerning information processing style and
information seeking. Moreover, women and older adults were more likely to seek
information, as expected.

<hs>  Testing for moderation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Model 2 data showed six significant interaction terms. The interaction of affect and
preferences for making immediate decisions was not examined further because there was no
main effect of immediate decision making. The remaining interactions were examined in more
detail following procedures discussed in Hayes (2013) and using the ‘process’ syntax. We
tested whether the relationship between information processing style and information
seeking was different at high and low levels of affect and information utility (1 standard
deviation above and below the mean). The conditional effects were calculated using the
bootstrapping procedure recommended by Preacher, Rucker, and Hayes (2007) in order to test
whether the findings were robust. A T-statistic was computed for the indirect effect.
There were two significant interactions: affect × preferences for delaying decision
making, and utility × preferences for delaying decision making. Data are shown in Table 3.
Fig. 1 shows the interaction between affect and preferences for delaying decision making.
There was a positive association between preferences for delaying decisions and
information seeking, although there was less information seeking for people experiencing
anxiety. As anxiety increased, preferences for putting off decisions reduced the
likelihood of information seeking. There was a positive association between information
utility and preferences for delaying decision making. Information seeking is most likely
for people who perceive the information as useful, yet have a tendency to put off decision
making. The relationship is depicted in Fig. 2. Fig. 3 summarises the direct effects and
moderation effects.

<h>DISCUSSION</h>
----------

Integrating dual process theory; (Epstein, 1990; Epstein et al., 1996) with RISP theory
(Griffin et al., 1999) and broaden-and-build theory (Fredrickson, 1998, 2001), provides
insights into the information seeking process. The current study has demonstrated the
importance of individual differences in information processing styles on information
seeking, and the susceptibility of information seeking to anxiety and information
perceptions in a food-related decision context. In examining these processes, we make two
contributions to the literature. First, we proposed that analytical information processing
styles would be associated positively with information seeking. Data confirmed this
proposal, and showed that there was a direct effect of analytical information processing
style on information seeking that was not influenced by anxiety or information utility.
Hence, for people with preferences for analytical information processing styles,
information seeking is likely to form part of their strategy for finding and evaluating
information systematically prior to making a choice. We also hypothesised that preferences
for heuristic decision making would be associated negatively with information seeking, and
that this relationship would be influenced by anxiety and information utility. Data showed
that there was a main effect, but did not support moderation. Thus heuristic preferences
were associated directly with low levels of information seeking. These findings show
partial fit with Griffin et al.’s (1999) RISP model. We showed that information processing
style was associated with information seeking, but there was no evidence for the complex
association between the variables proposed in the RISP model. Furthermore, the data
indicate that different information processing styles require specific modelling. Our
second contribution concerns the application of the regulatory dimension of information
processing styles: preferences to make an immediate or delayed decision. Delaying
decisions can serve a specific purpose which is to avoid choice, and this is different
from the application of heuristics, a process that is concerned with making decisions
faster and with less effort. Data showed that preferences for delaying decisions were
associated positively with information seeking, and that this relationship was moderated
by both anxiety and information utility. Participants sought more information when they
experienced lower levels of anxiety. Furthermore, participants sought more information
when they perceived what they had read during the study to be useful. Together, these
findings suggest that, for people who find it difficult to regulate the decision process,
information seeking is a strategy to delay decisions that becomes more likely when
information is perceived to be useful, and less likely under conditions of anxiety. The
research has several practical implications for policy makers and food safety risk
managers. Research into risk communication has moved towards bottom-up development of
information that takes lay concerns into account (Bickerstaff, Lorenzoni, Jones, &
Pidgeon, 2010; Stern & Fineberg, 1996). This practical strategy could have the benefit of
influencing the balance of affect and information perceptions that have a critical
influence on information seeking behaviour such that people are motivated enough to read
information, e.g. on websites, and educated about how to act on it to change domestic
practices and reduce the risk of infection from Salmonella. Such an approach could also
avoid raising anxiety levels to the point where people avoid food safety information.
Future research could examine further the relationships between information processing
styles and information seeking, and the moderating roles of anxiety and information
utility. In particular, further examination of the processing that underlies delayed
decision making would enable more complete modelling of the relationship, and it is
possible that there are other situational moderators that interact with information
processing styles. Future research could consider the relationship between information
seeking and effective decision making to test for the positive and negative impact of
different information processing styles, and do so in different decision contexts. There
could also be further examination of the effects of age and gender on decision processes
and information seeking. Epstein et al. (1996), for example, found some differences
between men and women’s preferences for analytical and heuristic thinking, although the
findings were not consistent across studies. It is also possible that decision processes
develop with age (Mata, Schooler, & Rieskamp, 2007), thus future research could consider
how these demographic factors function in relation to information seeking. The current
study has some strengths, notably the assessment of information seeking behaviour rather
than information processing (Kahlor, Dunwoody, Griffin, Neuwirth, & Giese, 2003) or
intention (ter Huurne, Griffin, & Gutteling, 2009; Yang, 2012). However, while attempts
have been made to develop a theory-driven model and test it on a large sample of adults,
the current study has acknowledged limitations. We examined information seeking behaviour
using online survey technology, however, a laboratory study would enable more complex
information seeking behaviour to be assessed. Moreover, an experimental approach could be
used to examine whether information processing styles can be influenced by priming or
other contextual variables, thus providing more opportunities to examine moderation
effects. Finally, different decision contexts, e.g. other kinds of everyday decisions as
well as infrequent decision, or decisions with more serious consequences, would add to
theoretical and practical developments. In conclusion, this study suggests that individual
differences in preferences for analytical and heuristic information processing style have
a direct effect on information seeking, and influence the extent to which information is
sought. In contrast, regulatory information processing styles have an indirect association
with information seeking. Preferences for delaying decisions were exacerbated by
information utility and attenuated by anxiety. These findings contribute to a more
complete understanding of the decision processes that lead to information seeking.
Moreover, the findings suggest that information campaigns could be made effective by
providing sufficient information to generate an emotional need to make timely decisions.


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----------

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<ART>The relative contributions of speechreading and vocabulary to deaf and hearing children's reading ability
================================================================================

Authors: Fiona Elizabeth Kyle, Ruth Campbell, Mairéad MacSweeney
DOI: 10.1016/j.ridd.2015.10.004
Year: 2016  |  Pages: 13-24
ASJC codes: 3203, 3204
Keywords: Deaf, Reading, Speechreading, Vocabulary

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Vocabulary knowledge and speechreading are important for deaf children's reading development but it is unknown whether they are independent predictors of reading ability. Aims: This study investigated the relationships between reading, speechreading and vocabulary in a large cohort of deaf and hearing children aged 5 to 14 years. Methods and procedures: 86 severely and profoundly deaf children and 91 hearing children participated in this study. All children completed assessments of reading comprehension, word reading accuracy, speechreading and vocabulary. Outcomes and results: Regression analyses showed that vocabulary and speechreading accounted for unique variance in both reading accuracy and comprehension for deaf children. For hearing children, vocabulary was an independent predictor of both reading accuracy and comprehension skills but speechreading only accounted for unique variance in reading accuracy. Conclusions and implications: Speechreading and vocabulary are important for reading development in deaf children. The results are interpreted within the Simple View of Reading framework and the theoretical implications for deaf children's reading are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Despite having intelligence scores in the normal range, the majority of deaf children have
poorer reading outcomes than their hearing peers (e.g. Conrad, 1979; Kyle & Harris, 2010;
Lederberg, Schick, & Spencer, 2013; Wauters, van Bon, & Tellings, 2006). Large scale
studies report that deaf school leavers have reading ages far behind their chronological
ages (see Qi & Mitchell, 2011 for a review) and reading skills seem to develop at only a
third of the rate of hearing children (Allen, 1986; Kyle & Harris, 2010). There is a
consistent picture of underachievement in reading skills which can have long-lasting
effects upon future employment opportunities. It is therefore imperative to gain a better
understanding of which cognitive and language skills are important for reading development
in deaf children and the complex relationships between these abilities. Recent research
has suggested that speechreading (silent lipreading) and vocabulary are longitudinal
predictors of deaf children's reading development (Kyle & Harris, 2010, 2011), and that
speechreading is also predictive of reading ability in hearing children (Kyle & Harris,
2011). However, the relative contribution of these two skills to reading is unknown;
therefore the main aim of this study is to examine whether speechreading and vocabulary
are independent predictors of reading in deaf and in hearing children. The predictors of
reading ability, and the often complex relationships between predictors, are well
documented in hearing children. One of the most widely-acknowledged predictors of early
reading is phonological knowledge and skills (e.g. Adams, 1990; Castles & Coltheart,
2004). Children with better phonological awareness (the ability to detect and manipulate
the constituent sounds of words) and greater knowledge about the relationships between
letters and sounds tend to make the most progress in reading in the early stages (see
Castles & Coltheart, 2004; Goswami & Bryant, 1990). However, it is also well known that
different cognitive and language based skills are predictive of different components of
the reading process, i.e. letter-sound knowledge and phonological skills are most
predictive of word recognition and word reading whereas higher order language skills such
as grammar and syntax are most predictive of reading comprehension (see Catts & Weismer,
2006; Muter, Hulme, Snowling, & Stevenson, 2004; Oakhill, Cain, & Bryant, 2003; Storch &
Whitehurst, 2002). Vocabulary is generally thought of as being most important in the
beginning stages of reading where it predicts initial word recognition (e.g. Dickinson,
McCabe, Anastasopoulos, Peisner-Feinberg, & Poe, 2003; Verhoeven, van Leeuwe, & Vermeer,
2011) and emerging comprehension skills (e.g. Anderson & Freebody, 1981; Ricketts, Nation,
& Bishop, 2007; Roth, Speece, & Cooper, 2002); however, research suggests that vocabulary
knowledge also plays an important role in later reading skills (e.g. Senechal, Ouellette,
& Rodney, 2006; Verhoeven et al., 2011). The question of whether phonological skills are
important, or even necessary, for deaf children's reading skills is a matter of ongoing
debate. In summary, the research evidence is very mixed. Some authors find evidence for
the role of phonological skills in deaf children's reading (e.g. Campbell & Wright, 1988;
Dyer, MacSweeney, Szczerbinski, Green, & Campbell, 2003; Easterbrooks, Lederberg, Miller,
Bergeron, & Connor, 2008) while many others report a very small or non-significant
relation (e.g., Hanson & Fowler, 1987; Kyle & Harris, 2006; Leybaert & Alegria, 1993;
Mayberry, del Giudice, & Lieberman, 2011; Miller, 1997). These discrepancies hold true
even when traditional phonological awareness assessments are adapted to make them more
deaf-friendly, i.e. by representing the items pictorially. A recent meta-analysis of the
literature concluded that there was little evidence that deaf individuals use phonology in
their reading (Mayberry et al., 2011). In their analyses Mayberry et al. (2011) included
25 studies that looked at the relation between reading and phonological coding and
awareness in deaf individuals, ranging from young children to adults and from across the
spectrum of language and communication preferences (sign/speech). The resulting effect
sizes for the relationship between reading and phonological awareness ranged from −.13 to
.81 with a mean of .35. This means that on average, across the 25 studies, 11% of the
variance in reading skills in deaf participants was explained by phonological abilities.
This figure refers to the contribution of spoken phonology to reading for deaf
participants. It should be noted that signed languages are also phonologically structured,
albeit with different parameters (e.g. Brentari, 1999; Sandler & Lillo-Martin, 2006).
Corina, Hafer, and Welch (2014) recently reported a positive correlation between
phonological awareness of American Sign Language and phonological awareness of English.
Furthermore, McQuarrie and Abbott (2013) reported a correlation of .47 between
phonological awareness in American Sign Language (ASL) and reading. However, as yet there
is no evidence for a direct causal relationship between the knowledge of sign language
phonology and reading. An important caveat regarding the Mayberry et al. meta-analysis is
that the study mainly included correlational studies. Due to the low number of
longitudinal studies in deaf children only two such studies were included (Harris & Beech,
1998; Ormel, 2008). Correlational relationships between variables do not infer causality.
Furthermore, in longitudinal studies of reading development it is important to control for
early levels of reading ability on later reading outcomes because of the well documented
auto-regressor effect, whereby the strongest predictor of later ability is typically
earlier achievement in that particular skill (see Caravolas, Hulme, & Snowling, 2001;
Castles & Coltheart, 2004). In the only two longitudinal studies of deaf reading
development that have used this approach, the data suggest that deaf children may develop
their phonological skills through reading (Kyle & Harris, 2010, 2011). Reading and
phonological awareness were found to be related in deaf children, but the direction of the
observed relation was from earlier reading ability to later phonological awareness.
Therefore this may be different to the typical relation seen in hearing children whereby
phonological awareness is a strong initial predictor of reading ability and then the two
skills tend to exhibit a reciprocal relation (Burgess & Lonigan, 1998; Castles &
Coltheart, 2004). In deaf children, it seems that it is reading ability that initially
predicts phonological awareness, but then, similar to hearing children, the two skills
become reciprocally related and develop in a common and mutually beneficial manner. This
pattern of development also fits in with an emerging pattern in the deaf literature, that
of the predictive relation between phonological awareness and reading being stronger, or
more apparent, in older deaf children and adults, than in young children. That is, the
role of phonological skills in deaf reading becomes stronger once reading skills are more
proficient. It is important to note that the studies included in the meta-analysis of
reading and phonological awareness studies conducted by Mayberry et al. (2011) covered
deaf participants from a very broad age range, from early childhood to adulthood. New
insights from the longitudinal studies outlined above suggest that combining data across
this very wide age range of deaf participants may not be appropriate. A different way of
looking at whether phonological skills have a role in deaf reading is to examine the
contribution of visual-based phonological skills such as lipreading or speechreading.
There is growing evidence that some deaf individuals do make use of phonology but that
their phonological strategy may be slightly different to that of hearing individuals
because it is mainly derived from speechreading information rather than auditory input.
Speechreading (or lipreading), which is the skill of processing speech from the visible
movements of the head, face and mouth, has the potential to be useful in phonological
processing when hearing is absent. In addition to providing visual information about
vowels (mouth shape), some consonantal phonemes are ‘easy to see’ and ‘hard to hear’. For
example, /n/ and /m/ form one pair of consonants that are confusable auditorily, but clear
visually (see Summerfield, 1979). Individual differences in speechreading skill have been
found to predict reading outcomes in deaf individuals, both cross-sectionally and
longitudinally (Arnold & Kopsel, 1996; Geers & Moog, 1989; Kyle & Harris, 2006, 2010,
2011). If the information gleaned through speechreading is used as the input for a
phonological code, then the better one is at speechreading, the more specified and
distinct the underlying representations are likely to be. These underlying representations
can then be used to form the basis for a phonological code. The quality of phonological
representations is thought to be related to reading ability (Elbro, 1996; Swan & Goswami,
1997) because the more specified and distinct the underlying representations, the better
able the individual is to complete phonological awareness tasks (Elbro, Borstrøm, &
Petersen, 1998) and performance on these types of tasks is extremely indicative of reading
ability (see Castles & Coltheart, 2004 for a review). The strong predictive relationships
found between speechreading and reading in deaf children (e.g. Kyle & Harris, 2010, 2011),
the presence of speechread errors in both deaf children's spelling (Burden & Campbell,
1994; Leybaert & Alegria, 1995; Sutcliffe, Dowker, & Campbell, 1999) and in their
performance on phonological awareness tasks (Hanson, Shankweiler, & Fischer, 1983;
Leybaert & Charlier, 1996) suggest that, when deaf children are learning to read, the
better they are at speechreading the more information they will be able to use when making
connections between letters and sound (see also Alegria, 1996; Campbell, 1997). Many of
the earlier studies only found speechreading was associated with levels of reading ability
in orally educated deaf children (e.g. Arnold & Kopsel, 1996; Campbell & Wright, 1988;
Craig, 1964; Geers & Moog, 1989); however, more recent research has reported speechreading
to be a strong longitudinal predictor of deaf children's reading development, regardless
of language preference (Kyle & Harris, 2010, 2011). This shift can be readily explained by
the changes in deaf educational practices in the UK over the past 30 years as fewer deaf
children are now educated in specialist schools and there is more integration in
mainstream schools. This, combined with the introduction of bilingual education through
British Sign Language (BSL) and English, has impacted upon the teaching of reading and
language to deaf children making it more likely that almost all of them are exposed to
both oral speech and sign to some extent. The other skill that is increasingly reported as
being important for deaf children's reading ability is vocabulary knowledge (e.g. Geers &
Moog, 1989; Kyle & Harris, 2006, 2010, 2011; LaSasso & Davey, 1987; Mayberry et al., 2011;
Moores & Sweet, 1990). Vocabulary and language skills seem to be imperative for deaf
reading regardless of how either skill is assessed or which component of reading is
measured. ‘Language skills’ were found to be the largest contributor to reading ability in
the Mayberry et al. (2011) meta-analysis. The category ‘language skills’ included measures
of signed and spoken vocabulary (amongst other measures). Vocabulary was also the
strongest and most consistent longitudinal predictor of both word reading and reading
comprehension in the Kyle and Harris longitudinal studies (2010, 2011). This could be
considered relatively unsurprising given the well documented language delays in deaf
children (Waters & Doehring, 1990; Musselman, 2000). In hearing children, vocabulary and
good language skills have been proposed as providing a possible compensatory mechanism for
children who have poor phonological skills (e.g. Nation & Snowling, 1998; Snowling,
Gallagher, & Frith, 2003). This explanation is equally plausible, if not more so, for the
strong relationship between vocabulary and reading in deaf children. Previous studies
looking at the role of vocabulary and speechreading in deaf children's reading have had
insufficient sample sizes to determine whether these two skills are independent predictors
of reading in deaf children. In Kyle and Harris (2010), speechreading was mainly a
longitudinal predictor of early reading skills and thus it is of interest to determine
whether this relationship feeds into vocabulary development. It would make sense that deaf
children who have better speechreading skills have larger vocabularies yet the converse
relationship whereby having a more extensive vocabulary would enable one to be a better
speechreader is also likely (Davies, Kidd, & Lander, 2009). What is not known is whether
speechreading and vocabulary, which are likely to be related themselves, make independent
contributions to reading or whether they are simply reflecting some common underlying
language factor or capacity. On the other hand, these two factors could interact in a more
complex developmental manner, for example, one skill may ‘jumpstart’ the development of
the other skill at one stage, but then become less relevant. Vocabulary and speechreading
underpin the model of deaf reading proposed by Kyle (2015), which was based upon the
Simple View of Reading (Gough & Tunmer, 1986). The Simple View of Reading postulates that
reading is made up of two components: a decoding component and a linguistic component,
both of which are necessary for reading. For deaf children, as argued by Kyle (2015) and
Kyle and Harris (2011), speechreading contributes to phonological representations and thus
forms the basis, along with phonological awareness, for the decoding component, and
vocabulary knowledge contributes to the linguistic component. This is not to say that
other skills are unimportant for reading in deaf individuals but the role of these two
particular skills is explored in the current study. It should also be noted that the
relationship between speechreading and reading has mainly been measured at the level of
the single word reading and single word speechreading. It is therefore unknown whether
speechreading at different linguistic levels also predicts reading and whether the
strength of this relationship varies for different reading components. Kyle and Harris
(2006, 2010) found that single word speechreading was significantly related to word
reading but not reading comprehension and the relationship was stronger with word reading
than sentence comprehension. The current study uses a recently developed Test of Child
Speechreading (ToCS; Kyle, Campbell, Mohammed, Coleman, & MacSweeney, 2013), which
assesses speechreading at three different levels: words, sentences and sort stories. We
investigate how performance at these different levels is related to word reading and
reading comprehension. This will help to shed light upon the role that speechreading plays
in reading, for example, is the relationship simply at the lexical level or does it
reflect broader linguistic knowledge? Kyle and Harris (2011) also reported that
speechreading of single words was longitudinally predictive of beginning reading
development in hearing children. This finding warrants further investigation as although
it is easy to understand why speechreading is predictive of reading in deaf individuals,
due to impaired auditory access, it may not be immediately obvious why speechreading would
also be predictive of reading growth in hearing children. We would argue that a similar
explanation also holds for hearing children: speechreading is related to reading because
the visual speech information derived through speechreading is likely to be incorporated
into phonological representations. Therefore, better speechreading skills may result in
more distinct and specified phonological representations which in turn can help children
when learning to read. The key difference is the supplementary nature of this information
and detail for hearing children. Evidence from research with blind children supports this
viewpoint as studies often report delays in discriminating phonological contrasts that are
difficult to distinguish in the auditory domain but are visually distinct (Mills, 1987).
Lastly, given the suggested role of speechreading in reading, it is important to
understand what makes a good child speechreader. Research with adults has shown that
better speechreaders tend to be deaf, use oral language to communicate, have higher levels
of reading ability and report they can understand the public (Bernstein, Demorest, &
Tucker, 1998). No such comparable studies have been conducted with deaf children but the
findings from separate studies do help shed light on possible correlates of speechreading.
Relations have previously been reported between speechreading and vocabulary in young
hearing children (Davies et al., 2009) and between speechreading and working memory
(Lyxell & Holmberg, 2000), phonological awareness (Lyxell & Holmberg, 2000; Kyle & Harris,
2010) and NVIQ (Craig, 1964) in hearing-impaired children. Interestingly, recent research
has shown no difference between deaf and hearing children in their speechreading ability
(Kyle et al., 2013) but speechreading was found to improve with age (Kyle et al., 2013).
Moreover, when using an adult speechreading test very similar to the ToCS, deaf adults
were found to have superior speechreading skills in contrast to their hearing peers
(Mohammed, Campbell, MacSweeney, Barry, & Coleman, 2006; Mohammed, MacSweeney, & Campbell,
2003). The contribution of demographic, background and audiological factors to children's
speechreading will be investigated in the current study. This study explores the role of
speechreading and vocabulary in reading ability with a large sample of deaf and hearing
children. The main aims were to (1) to determine whether speechreading and vocabulary are
independent predictors of reading ability in deaf children; (2) to investigate the role of
speechreading at different linguistic levels for different components of reading ability
(i.e. does speechreading at different linguistic levels exhibit different relationships
with reading components); (3) to examine whether speechreading and vocabulary are
independent predictors of reading in hearing children; and (4) to explore the effect of
demographic and background variables on speechreading.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Eighty-six deaf children and 91 hearing children aged between 5 and 14 years old took part
in this study. The mean age of the deaf children was 9 years 6 months (SD = 31.5) and the
mean age of the hearing children was 9 years 1 month (SD = 30.2). Thirty-nine deaf
children and 53 hearing children were male. Deaf children were recruited from specialist
schools for the deaf and resource bases for students with hearing impairments attached to
mainstream schools across Southern England. To ensure that deaf and hearing children were
similar in terms of demographic backgrounds, the hearing children were recruited from the
mainstream schools to which the resource bases were attached. Deaf and hearing children
were from a range of different ethnic backgrounds: 59% of the children were White British
or White European, 11% were Black British or Black Other, 21% were Asian British or Asian
Other and the remaining 9% were mixed race or other. There were no significant differences
between the deaf and hearing children in their gender distribution (X2(1) = 2.94, ns),
ethnicity (X2(3) = 6.99, ns), chronological age (t(175) = .98, ns) and NVIQ (t(175) =
−1.87, ns). All deaf children had a severe or profound bilateral hearing loss of greater
than 70 db with a mean loss of 97.7 db. Thirty-five of the deaf children had cochlear
implants (CI) and the remaining (apart from two) wore digital hearing aids. The average
age at which deafness was diagnosed was 17 months (SD = 12.3). The majority of deaf
children were in hearing-impaired resource bases attached to mainstream schools but a
third were in specialist schools for the deaf. Children varied in their language and
communication preferences: 44 preferred to communicate through speech; 33 preferred to use
signing (26 used BSL and 7 used Sign Supported English); six used total communication (a
mixture of both signing and speech) and the remaining three were bilingual in spoken
English and BSL. Table 1 presents descriptive statistics for background information for
the deaf participants separated out for device use (CI, digital hearing aids and no
device)

<hs>  Materials</hs>
  ~~~~~~~~~

Four tasks were administered to assess reading ability, speechreading skills, expressive
vocabulary and NVIQ.

        <hss>Reading ability</hss>

        The Neale Analysis of Reading II (NARA II: Neale, 1997) was used to assess reading
        accuracy and reading comprehension skills. Children were shown a booklet
        containing short passages and asked to read them aloud in their preferred
        communication mode: English, BSL or a combination of the two. They were then asked
        a series of questions about each passage to test their comprehension, which they
        were allowed to answer in their preferred communication. Children received an
        accuracy score for their word reading and for their comprehension skills. The task
        was administered according to the instruction manual, apart from the instructions
        being delivered in the child's preferred language or communication method.

        <hss>Speechreading ability</hss>

        Speechreading ability was measured using the Test of Child Speechreading (ToCS:
        Kyle et al., 2013). The ToCS is a child-friendly, computer-based assessment that
        measures silent speechreading at three different psycholinguistic levels: words,
        sentences and short stories. It uses a video-to-picture matching design whereby
        children are presented with silent video clips of either a man or a woman speaking
        and they have to choose the picture (from an array of four containing the target
        and 3 distractors) that matched what was said in the video clip. For example, in
        the word subtest, for the target item “door”, the pictures were “door”, “duck”,
        “fork” and “dog”. An example of a sentence trial was the target “The baby is in
        the bath” and the distractors were pictures depicting a baby reading a book, some
        pigs on a path and an elephant having a bath, The short story subtest has a
        slightly different format in which participants see the speaker saying a short
        story and are then asked two questions about it. They answer each question by
        choosing the correct picture from an array of four. For example one of the
        questions is “where is Ben going?” and the correct answer “school” is depicted
        along with three viable distractors “home”, “cinema” and “library”. Full details
        about the ToCS design, item selection and development can be found in Kyle et al.
        (2013). The instructions were specifically designed so that they could be
        delivered in the child's preferred communication or language, BSL, spoken English
        or a combination of the two. ToCs has been shown to have high external validity as
        an assessment of silent speechreading and good internal reliability (α = .80)
        (Kyle et al., 2013). The task took about 20 min to administer.

        <hss>Expressive vocabulary</hss>

        The Expressive One Word Picture Vocabulary Test II (EOWPVT II: Brownell, 2000) was
        used to assess children's expressive vocabulary. Children are shown pictures of
        increasing difficulty and asked to name them. Children were allowed to respond in
        their preferred communication and therefore this task was providing an indication
        of their expressive vocabulary regardless of language preference. However, it
        should be noted that this task was designed to test English vocabulary and not BSL
        or sign language vocabulary. Following guidelines from Connor and Zwolan (2004),
        any answer that was not gestural was accepted. Two items in the test were changed
        to make it more suitable for British children, following Johnson and Goswami
        (2010) who used this test with deaf children in the UK. The item racoon was
        changed to badger and the map of USA to a map of the UK. In addition, and
        following pilot studies, we changed the pictures for two items to pictures more
        characteristic of British responses: prescription and windmill.

        <hss>Non-verbal skills</hss>

        An estimate of non-verbal intelligence (NVIQ) was derived from the Matrices
        subtest of the British Abilities Scales II (BAS II: Elliot, Smith, & McCulloch,
        1996). This test has been used previously with deaf children of similar age to
        those in the current study (see Harris & Moreno, 2004; Kyle & Harris, 2010).

<hs>  Procedure</hs>
  ~~~~~~~~~

Children were all tested individually in a quiet room, normally adjacent to the classroom.
Each child was seen over two testing sessions, not lasting more than 20 min each. All
standardised tests were administered according to the instruction manuals but the
instructions were delivered in the child's preferred communication method. Written
parental consent was given for all children and the child's assent was also sought at the
beginning of the first testing session. Ethical clearance was granted from the University
Research Ethics Committee.

<hs>  Performance on the ToCS, vocabulary and reading tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The means and standard deviations for all tasks are presented in Table 2. Raw scores were
used in all analyses as we were unable to obtain standard scores for all participants
across all tests as a few of the children were just outside the top age range for the
reading assessment. Standard scores are reported for the vocabulary assessment for
descriptive purposes only. As a group, the hearing children achieved age-appropriate
scores for reading accuracy and reading comprehension (mean chronological age = 9:01; mean
accuracy reading age = 10:00; mean comprehension reading age = 9:08). The deaf children
exhibited an average reading delay of sixteen months in reading accuracy and 22 months in
reading comprehension (mean chronological age = 9:06; mean accuracy reading age = 8:02;
mean comprehension reading age = 7:08). The hearing children had significantly higher
vocabulary standard scores than the deaf children, t(175) = −10.87, p < .001, 95% CI −28.8
to −19.8. The mean vocabulary standard score for the deaf children was 76 (SD = 15.1)
whereas the mean standard score for the hearing children was 100.2 (SD = 15.1). As
reported in Kyle et al. (2013), deaf and hearing children did not differ in their
speechreading skills (mean 49.0% vs. 50.6%, respectively) and showed an almost identical
pattern of performance across the subtests. A two-way mixed design ANOVA (hearing status
by ToCS subtest) revealed no statistically significant differences between the deaf and
hearing children in their overall performance on ToCS, F(1,172) = .11, ns. There was a
main effect of subtest, whereby children achieved higher scores on the single words >
sentences > stories, F(2,344) = 294.61, p < .001. There was no significant interaction
between group and ToCS subtest F(2,344) = .29, ns.

<hs>  Correlations between reading, speechreading and vocabulary</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Tables 3 and 4 present the partial correlations between reading, speechreading and
vocabulary controlling for age and NVIQ. Age was statistically controlled, as performance
on ToCS has been found to improve significantly with age over this age-range (see Kyle et
al., 2013). NVIQ was also controlled for as although there was no significant association
between NVIQ and speechreading, there were small yet significant associations between NVIQ
and reading and vocabulary. After statistically controlling for age and NVIQ, performance
on ToCS (combined score across three subtests) for both deaf and hearing children was
significantly related to reading accuracy (r = .49, p < .001 and r = .31, p = .005,
respectively) and reading comprehension (r = .44, p < .001 and r = .28, p = .010).
Performance on all three speechreading subtests was related to reading accuracy in deaf
children; however only performance on the sentences was related to reading in the hearing
children. Speechreading was also significantly associated with vocabulary knowledge (even
after controlling for age and NVIQ) in both deaf children (r = .25, p = .021) and hearing
children (r = .25, p = .02).

<hs>  Multiple regression analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The main research aim was to determine the relative contributions of vocabulary and
speechreading to reading ability in deaf children. A set of fixed order multiple
regression analyses was conducted (see Table 5) to investigate whether speechreading and
vocabulary were independent predictors of reading accuracy and comprehension. After
controlling for age and NVIQ (entered in steps 1 and 2 and accounting for 54% of the
variance), speechreading (entered in Step 3) accounted for 11% of the variance in the deaf
children's reading accuracy scores. When vocabulary was entered in step 4, it accounted
for an additional 13%. When the order in which they were entered into the regression
analyses was exchanged so that vocabulary was entered in Step 3 before speechreading, it
accounted for 15%. Speechreading still accounted for a small yet significant proportion of
the variance (8%) in reading accuracy even when entered after vocabulary. Thus,
speechreading and vocabulary seem to be relatively independent predictors of reading
accuracy in deaf children as the proportion of variance each skill explains is not
particularly dependent upon the order in which it is entered into the analysis. The same
analysis was conducted with reading comprehension as the dependent variable. Table 5 shows
that speechreading and vocabulary were also independent predictors of reading
comprehension for deaf children as the proportion of variance that each accounted for was
fairly consistent regardless of the order in which they were entered. Age and NVIQ
accounted for 59% of the variance in deaf children's reading comprehension scores. When
entered in Step 3, speechreading accounted for almost 8% and vocabulary accounted for an
additional 15% of the variance (in step 4). When the order in which vocabulary and
speechreading was entered was switched, vocabulary accounted for 17% (step 3) and
speechreading for 6% (step 4). The same analyses were conducted for the hearing children
(see Table 5). After controlling for age and NVIQ (68%), speechreading and vocabulary were
both small yet significant predictors of reading accuracy, regardless of the order in
which they were entered. Speechreading accounted for 3% (in step 3) and vocabulary
accounted for an additional 3% (in step 4). If the order was switched, vocabulary
accounted for 4% (in step 3) and speechreading accounted for 2% (in step 4). Therefore,
vocabulary and speechreading are accounting for a portion of independent variance in
reading accuracy scores in hearing children. A different picture was observed when reading
comprehension was the outcome variable for the hearing children. In this instance,
speechreading was only a significant predictor if entered before vocabulary. Age and NVIQ
accounted for almost 73% of the variance in reading comprehension so there was little
variance left that could be accounted for. When entered in step 3, speechreading was a
small predictor (2%) and vocabulary (step 4) accounted for 8%. However if the order was
changed, vocabulary accounted for 9% but speechreading no longer accounted for any
significant variance. Therefore, speechreading and vocabulary were small yet significant
independent predictors of reading accuracy for hearing children, but in contrast to the
deaf children, speechreading was not a significant independent predictor of reading
comprehension.

<hs>  How are background and audiological factors related to speechreading?</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As speechreading was a strong predictor of reading in deaf children, the role of
background and audiological factors in determining what makes a good child speechreader
was examined. The effects of gender and NVIQ were investigated for both deaf and hearing
children. A two-way ANOVA (gender × hearing status) revealed no effect of gender, F(1,176)
= 3.47, ns, no main effect of hearing status (deaf vs hearing), F(1,176) = 3.47, ns, and
no significant interaction, F(1, 176) = 1.44, ns. There was no significant association
between NVIQ and performance on ToCS for deaf or hearing children (r = −.01, ns and r =
−.06, ns respectively).

        Effect of hearing/audiological factors (degree of loss, type of hearing aid and age of diagnosis)

        An additional set of analyses was undertaken for the deaf cohort. There was no
        significant correlation between degree of hearing loss and overall speechreading
        ability, r = −.17, ns. However, there was a significant negative correlation
        between degree of hearing loss and performance on the sentences subtest (r = −.25,
        p = .024) and stories subtest (r = −.27, p = .015) but not single words (r = .05,
        ns). Children with less severe levels of hearing loss scored higher on the
        sentences and the stories section. There was no effect of age of diagnosis on
        speechreading scores, r = .13, ns and there were no differences between deaf
        children with hearing aids (n = 49) and those with CIs (n = 35), t(81) = −.87, ns.

        <hss>Effect of communication preference</hss>

        A two-way ANOVA revealed a main effect of child's communication preference,
        F(1,81) = 27.67, p < .001), whereby those children who preferred to communicate
        through oral language achieved higher scores on the ToCS than those who preferred
        to communicate through signing or total communication. There was also a main
        effect of speechreading subsection F(2, 162) = 178.16, p < .001) but no
        significant interaction F(2, 162) = 1.67, ns). Those children who preferred to
        communicate through oral language had lower levels of hearing loss than those who
        signed or used total communication, t(82) = −3.25, p = .002.

<h>DISCUSSION</h>
----------

The main aim of the current study was to investigate the relative contributions of
vocabulary and speechreading to reading development and determine if these relationships
held across different psycholinguistic levels. Speechreading and vocabulary were found to
be independent predictors of reading ability in children but the precise strength of the
relationship was dependent upon hearing status and the component of reading being
investigated. For deaf children, speechreading and vocabulary were independent predictors
of both reading accuracy and reading comprehension and accounted for an appreciable
portion of the variance in their reading scores. In contrast, for hearing children, while
both speechreading and vocabulary were independent predictors of reading accuracy, only
vocabulary was an independent predictor of reading comprehension and accounted for a
smaller proportion of the variance. These findings provide further evidence of the
importance of speechreading and vocabulary for deaf children's reading (e.g. Kyle &
Harris, 2010, 2011; Easterbrooks et al., 2008; Mayberry et al., 2011) and for the idea
that speechreading skills should not be ruled out as a factor influencing hearing
children's reading (see Kyle & Harris, 2011). Due to the large age range in the current
study, age understandably explained a lot of the variance in reading accuracy and reading
comprehension scores which left little for speechreading and vocabulary to be able to
explain. Thus, after age and NVIQ were entered into the analyses, it is remarkable that
speechreading and vocabulary were indeed able to account for any further variance,
particularly for the hearing children. While it might be reasonable to expect a
relationship between reading and speechreading in deaf children (where speechreading can
provide access to phonological information in the absence of auditory input), it is not as
immediately obvious why a small yet significant relationship would be observed for hearing
children. However, the contribution of speechreading and vocabulary for hearing children
can also be interpreted through the Simple View of Reading framework whereby vocabulary
again provides input for the linguistic component while speechreading feeds into the
decoding component. It is well-known that speech processing plays a role in the
development of phonological skills and helps form phonological representations. What
differs between the role of speechreading for deaf and hearing children's reading in this
model is the necessity: for deaf children, speechreading is often one of the main ways of
accessing spoken language whereas for hearing children, it is supplementary. The better a
child is at speechreading, the more distinct their phonological representations are likely
to be and more specified representations are linked with better reading (e.g. Elbro,
1996). This fits in with the viewpoint that a phonological code is not necessarily tied to
the auditory domain but is abstract and therefore it can be derived from speech and
speechreading (see Alegria, 1996; Campbell, 1997; Dodd, 1987). Information derived through
speechreading has been shown to be processed in a similar manner to auditory speech
(Campbell & Dodd, 1980; Dodd, Hobson, Brasher, & Campbell, 1983). In prior research, the
strong association reported between speechreading and reading in deaf children has been
mainly limited to the level of word reading (Kyle & Harris, 2010, 2011) whereas the
current study extends this relationship to reading comprehension. However, previous
studies only assessed speechreading of single words and the current study measured
speechreading of words, sentences and stories; and a composite of these three levels was
found to predict reading comprehension. It is also important to note that the age range in
the current study was from 5 to 14 years whereas it was only 7–10 year olds in Kyle and
Harris (2010) and therefore it is possible that speechreading plays a more important role
in deaf reading comprehension as reading skills develop. This is in line with results from
the deaf adult literature where speechreading has been found to correlate significantly
with reading comprehension (Bernstein et al., 1998; Mohammed et al., 2006). The extension
of this association between reading and speechreading beyond single words is important as
it suggests that the relationship is not due simply to perceptual matching (i.e. matching
a single word token to a single speechread token). It is more likely to have a linguistic
basis, especially as the ToCS was shown to be an ecologically valid assessment of
speechreading (see Kyle et al., 2013). Speechreading of sentences and short stories
requires higher-order linguistic skills such as parsing and grammatical knowledge, which
are equally required for comprehension of written texts. It is important to remember that
for deaf children, performance on all three psycholinguistic levels was related to reading
accuracy and comprehension. For both deaf and hearing children, vocabulary knowledge was
the strongest independent predictor of reading accuracy and reading comprehension. This
concurs with previous findings that language skills, including vocabulary knowledge,
typically exhibit the strongest relationship with reading in deaf children (e.g.
Easterbrooks et al., 2008; Kyle & Harris, 2006, 2010, 2011; Mayberry et al., 2011; Moores
& Sweet, 1990; Waters & Doehring, 1990). Whilst this also fits with findings with hearing
children, the exact strength of the relationship observed with hearing children usually
depends upon which components of language and reading are being measured and the age of
the children (see Ricketts et al., 2007). Future research should attempt to explore the
contribution of broader language skills to reading development in deaf children rather
than just vocabulary knowledge. It would also be interesting to determine whether the role
of speechreading and vocabulary in deaf children's reading development is constant across
different subgroups of deaf children. Although speechreading and vocabulary were
independent predictors of reading ability, they were also inter-related to some extent in
both deaf and hearing children, as has been reported by Davies et al. (2009) for young
hearing children. One interpretation of this relationship is that one cannot speechread a
word that is not already in one's vocabulary; however, for deaf children it is equally
plausible to suggest that speechreading leads to vocabulary growth and indeed for some it
may be the only way that spoken words enter the mental lexicon. For deaf children in
particular, it is most likely to be a reciprocal relationship rather than uni-directional.
Another explanation can be found in the theories of Metsala and Walley (1998) and Goswami
(2001) who argue that the development of phonological awareness and vocabulary are closely
linked because as vocabulary knowledge expands, there is increased pressure for the
underlying phonological representations to become more distinctive, which in turn leads to
improved phonological awareness. It is noteworthy that there were very few relationships
observed between speechreading and other background and demographic skills. Similar to
findings with deaf adults, those deaf children who preferred to communicate through speech
were better speechreaders (see Bernstein et al., 1998). The lack of a significant effect
of gender or NVIQ on child speechreading proficiency also concurs with more recent adult
investigations (Auer & Bernstein, 2007). Although there was no overall association between
degree of hearing loss and speechreading, deaf children with less severe levels of hearing
loss scored higher on the sentences and the stories sections, perhaps suggesting a more
supplementary functional use. It is reasonable to assume that speechreading combined with
higher levels of residual hearing might lead to better speech perception (both audio-
visual and visual alone) than lower levels of residual hearing combined with
speechreading, although equally, the greater the level of deafness the more reliance one
may have to place upon speechreading. This does raise a possible question over the
validity of focusing on speechreading if it cannot be determined what makes a good
speechreader in children. However, a better way of approaching this issue would be to
implement speechreading training to determine whether it is a skill that can be trained in
children. Finally it should be noted that the current study is only correlational and
therefore causality cannot be inferred. However, there is no reason to assume that the
direction of the relationships observed in this study is any different to that reported in
recent longitudinal studies (see Kyle & Harris, 2010, 2011) in which speechreading and
vocabulary predicted development in reading rather than reading predicting growth of
speechreading and vocabulary.

<h>CONCLUSIONS AND EDUCATIONAL IMPLICATIONS</h>
----------------------------------------

In conclusion, vocabulary and speechreading have been shown to be independent predictors
of reading ability in deaf children and to a lesser extent in hearing children. It is
likely that better speechreading skills result in more accurate phonological
representations and the current results can be understood within reading models that
suggest skilled reading necessitates both a decoding (speechreading) and a linguistic
component (vocabulary). These findings suggest that focussing on both vocabulary
development and speechreading skills in young deaf children may form a fruitful basis for
helping support early reading development in young deaf children. There are several
educational implications that can be drawn from these findings. Teachers working with deaf
children who use speech to communicate are likely to already have an understanding of the
importance of visual speech and highlight this as a source of information. However our
results show that speechreading is important for reading development in deaf children from
other language backgrounds, including signing and possibly those with cochlear implants.
Thus teachers working with these cohorts should also draw children's attention to the
complementary phonological information that is visible on the face. Teachers and educators
working with typically-developing hearing children should be aware that their children are
also probably incorporating phonological information derived from visual speech into their
representations and that encouraging children to be look at the lips when learning sounds
is likely to help them form more distinct phonological representations. Drawing attention
to information from visual speech is likely to not only help children initially
distinguish between similar sounding phonemes but this information is likely to help
create more distinct representations which will help with reading skills. The findings
also provide further evidence for teachers working with either deaf or hearing children
that reading is not only about decoding words, but that vocabulary, and most likely
broader language skills not measured in the current study, also play an essential role in
reading development.

<h>WHAT THIS PAPER ADDS?</h>
---------------------

This paper investigates the importance of speechreading and vocabulary skills for reading
development in a large cohort of deaf and hearing children ranging in age from 5 to 14
years. Previous research reported a relationship between speechreading and reading ability
but only between speechreading of single words and word reading. The current study has
extended this relationship to include larger units of speechreading (sentences and short
stories) and to reading comprehension. Importantly, the current findings suggest that
speechreading and vocabulary make independent contributions to reading ability in deaf
children and possibly contribute to hearing children's reading. The results are
interpreted within current theoretical frameworks of reading development for hearing and
deaf children.


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<ART>The role of memory and language ability in children's production of two-clause sentences containing before and after
================================================================================

Authors: Liam P. Blything, Kate Cain
DOI: 10.1016/j.jecp.2019.01.011
Year: 2019  |  Pages: 61-85
ASJC codes: 3204, 3205
Keywords: Elicited Production, Language acquisition, Language production, Memory, Sentence repetition, Temporal connectives

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

We assessed 3- to 6-year-old children's production of two-clause sentences linked by before or after. In two experiments, children viewed an animated sequence of two actions and were asked to describe the order of events in specific target sentence structures. We manipulated whether the target sentence structure matched the chronological order of events (e.g., “He finished his homework, before he played in the garden” [chronological order]) or not (e.g., “Before he played in the garden, he finished his homework” [reverse order]). Children produced fewer accurate target sentences when the presentation order of the two clauses did not match the chronological order of events, specifically for target sentences linked by after. Independent measures of vocabulary and memory both were related to performance, but vocabulary was the stronger predictor. We conclude that developmental improvements in children's ability to produce two-clause sentences linked by a sequential temporal connective are driven primarily by language ability rather than memory capacity per se. This work also highlights the advantages of using both sentence repetition (Experiment 1) and blocked elicited production (Experiment 2) paradigms to elicit sentence production in young children.

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<h>INTRODUCTION</h>
------------

We experience events in the world around us in real time as they occur. In the production
of speech and text, however, the speaker or writer does not need to relate events in the
order in which they occur. Instead, linguistic devices such as the temporal connectives
before and after may be used to refer to events in reverse order (e.g., “Before he ate the
cookies, he put on his jumper”). Although children produce sentences containing before and
after from around 3 years of age (Diessel, 2004), they have difficulties with correct
usage up to at least 9 years (Peterson & McCabe, 1987; Winskel, 2003). That is, children’s
production of sentences that include these expressions may belie their full competence
because they may have better knowledge of one construction over the other. In this study,
we focused on 3- to 6-year-old children’s production of two-clause sentences containing
the connectives before and after. We demonstrate that language ability has a stronger
influence on performance than working memory capacity per se. Successful production of
language draws on an integrated and coherent mental representation of the state of affairs
being described, also known as a prelinguistic message (Bock, 1987; Levelt, 1989). When a
speaker narrates events in reverse order, as in “She put on her gloves, after she had
combed her hair,” the language used deviates from the speaker’s mental representation of
the actual sequence of events. When adult speakers choose to do this, they draw on greater
processing resources than when planning and producing chronological order sentences
(Habets, Jansma, & Münte, 2008; Ye, Habets, Jansma, & Münte, 2011). As noted above,
children’s understanding and production of before and after continue to develop for
several years after these temporal expressions first appear in their speech. What is not
known is whether or not other linguistic and structural features of sentences with
temporal connectives, such as reverse order narration, contribute to these developmental
differences. We present the first systematic study of how sentences expressing different
temporal orders of events affect children’s sentence production accuracy. A speaker’s
choice to narrate events in their chronological order using either before or after
influences whether the temporal connective occurs in the initial position of the sentence
(e.g., “After she combed her hair, she put on her gloves”) or in the medial position
(e.g., “She combed her hair, before she put on her gloves”). This was our first research
question: How do these features—order of events, connective, position of
connective—individually or in combination influence young native speakers’ production of
sentences containing temporal connectives? Studies of children’s production and
comprehension of temporal connectives show that before is acquired earlier than after
(Blything & Cain, 2016; Clark, 1971; Pyykkönen & Järvikivi, 2012). Clark (1971) attributed
the difference in age of acquisition for before and after to the semantic features of each
term; before indicates the prior event, whereas after does not, making the latter more
semantically complex. In addition, before is used more consistently as a temporal
connective than after, which is commonly used also as a preposition as in “Watch out, he
is only after your money” (see the British National Corpus [Leech, Rayson, & Wilson,
2001]). Thus, after has a less consistent form–meaning relationship and is theoretically
more complex than before. This literature suggests that the use of after may involve
greater planning and processing effort than the use of before, which may influence the
accuracy of sentence production. Another feature that might influence children’s sentence
production accuracy is the position of the connective. Corpus studies of spoken language
have reported that children and adults use connectives in an initial position infrequently
(Diessel, 2004, 2008). This finding has been related to the memory load involved in
maintaining the information signaled by the connective from the beginning of the sentence
while processing the meaning of the first clause (Diessel, 2004, 2008). Conversely, the
preference to use a medially placed connective is associated with processing ease because
it provides the linguistic information about temporal order at a point close to when the
events can be integrated during the incremental processing of language. Our second
research question was to identify which framework best explains variation in performance
between different sentence structures and across development. A traditional memory
capacity-constrained account attributes performance on language processing tasks to the
availability of resources within an independent system of working memory, which limits the
amount of information that can be maintained during planning and production (e.g.,
Carpenter, Miyake, & Just, 1994). A more nuanced language-based perspective of working
memory shifts emphasis from the “quantity” of information that can be represented to the
“quality” (i.e., the content) of the representation of that information in long-term
memory (McElree, 2006), which in turn frees up shared processing resources so that they
are allocated to the representation of information in active working memory (e.g.,
MacDonald, 2016). We examined both of these accounts in our study. A classic theory
concerning the role of working memory in sentence processing is the memory capacity-
constrained account (e.g., Carpenter et al., 1994). According to this viewpoint, an effect
or interacting effect of the aforementioned features—order of events, connective, position
of connective—is driven by working memory capacity alone. The primary emphasis is that
some sentence structures are more difficult to process than others because they require
more information to be held within the limited-capacity working memory system. The account
builds on a framework that assumes that working memory is a separate system from long-term
memory (Baddeley & Hitch, 1974; Baddeley, 2003) to argue that the accurate representation
of information is driven by the availability of processing resources specific to the
working memory system. The availability of processing resources determines how many
individual language units can be accurately represented (but note that the constitution of
a “unit” is undefined; see McElree, 2006, for a full review of limitations). It follows
that production accuracy is expected to be weaker in individuals with low working memory
capacity because they have fewer resources available for maintaining information in
working memory. Under such circumstances, the representation of the language form and
structure may decay and be forgotten. There is empirical support for the memory capacity-
constrained account of sentence processing from a variety of studies. First, there are
studies suggesting that difficulties in producing more complex utterances can be
attributed to the availability of resources within an independent working memory system.
Patients with working memory capacity deficits display a substantially longer speech onset
than controls when producing various utterances, and this difference is more pronounced
for utterances with more complex structures (e.g., Martin & Freedman, 2001; Martin,
Miller, & Vu, 2004). In addition, healthy speakers produce an increased proportion of
double object datives (a more complex dative structure; e.g., “The pirate is giving the
monk the book”) relative to prepositional datives (a simpler dative structure; e.g., “The
pirate is giving a book to the monk”) when they are not required to maintain a verbal
memory load (Slevc, 2011). Specifically in relation to the production of two-clause
sentences containing temporal connectives, functional magnetic resonance imaging (fMRI)
and electroencephalography (EEG) studies with adults have attributed the extra processing
effort for reverse order sentences to the maintenance of additional concepts within
working memory (Habets et al., 2008; Ye et al., 2011). However, these latter studies did
not include an independent measure of working memory. Complementary work from studies of
sentence comprehension show that both adults’ (Münte, Schiltz, & Kutas, 1998) and
children’s (Blything & Cain, 2016; Blything, Davies, & Cain, 2015) weaker performance for
reverse order sentences is related to an independent measure of working memory (but see De
Ruiter, Theakston, Brandt, & Lieven, 2018, for a study with children that did not
demonstrate a relationship between memory and sentence comprehension). Alternatively,
given that the amount of information that can be held in working memory is often far less
than the length of a complex sentence, it has been argued that memory capacity alone
cannot be an adequate explanation of the pattern of performance seen by children or adults
in sentence processing tasks (MacDonald, 2016; McElree, 2006). A language-based account of
sentence processing proposes that the effects of working memory are indirect via language
knowledge (e.g., MacDonald, 2016). This argument draws on the framework that, rather than
being separate systems, working memory and long-term memory are part of a unitary
architecture in which working memory is a temporarily active portion of long-term memory
(Ericsson & Kintsch, 1995; McElree, 2006). From this viewpoint, language knowledge
influences sentence processing because good language skills free up shared resources
within the proposed unitary architecture to support the accurate representation of
information in active working memory. There is empirical support for this position. The
specificity or distinctness of words in the target utterance has been shown to influence
adults’ sentence production (Gennari, Mirković, & MacDonald, 2012; Montag & MacDonald,
2014, 2015; Smith & Wheeldon, 2004). In these studies, speakers are less accurate when a
task involves the activation of competitors that carry a similar meaning to target items.
In a picture description task, Gennari et al. (2012) contrasted conditions in which the
pictured agent and patient were highly similar (e.g., builder, miner) or not (e.g.,
builder, astronaut). Speakers were more likely to avoid more complex structures and omit
optional words in the highly similar condition that permitted potential competition
between the agent and patient meanings (e.g., producing “The builder who’s being slapped”
rather than “The builder who’s being slapped by the miner”). It follows that robust
language knowledge will ease the accessibility and retrieval of target items over
competitors that are also partially activated in memory. In relation to the production of
reverse order sentences containing temporal connectives, this account would posit that an
accurate transformation of the mental representation of the order of events is determined
by the availability of processing resources that are shared with language retrieval
operations. Crucially, a weak lexical representation of a target connective, or other
words in the sentence, will lead to less differentiation in activation compared with
competitors with similar meaning (i.e., different temporal connectives to the target).
This would disrupt sentence planning and production. On this basis, young language users
may experience difficulties with complex sentences (i.e., reverse order) because the
quality of their lexical representations (i.e., connectives or other words in the
sentence) is weaker. We do not yet know precisely how children’s sentence production
differs for sentences expressing different temporal orders of events. As noted, studies of
adults’ sentence production have reported processing difficulties for reverse order
sentences (Habets et al., 2008; Ye et al., 2011). However, these studies have used stimuli
in which the connective was presented only in the sentence-initial position. As a result,
the effects of connective (before or after) and event order (chronological or reverse)
cannot be disentangled. From a developmental perspective, a fully factorial design that
includes all permutations of these factors (before–chronological, before–reverse,
after–chronological, after–reverse) is essential because children display developmental
differences in their understanding of before and after (Clark, 1971).

<hs>  Overview of study aims, methods, and hypotheses</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We conducted two experiments designed to determine whether a memory capacity-constrained
account (e.g., Carpenter et al., 1994) or a language-based account (e.g., MacDonald, 2016)
of sentence processing best explains young children’s production of two-clause sentences
containing before and after. Each clause related a single event. We manipulated the
connective (before or after) and whether the order of mention of events was chronological
or reverse. As a result, the position of the connective was manipulated (medial or
initial). Note that a reverse order sentence with after places the connective in the
medial position, whereas a reverse order sentence with before places the connective in the
initial position. Thus, we manipulated connective and event order in our materials. We
also examined the extent to which independent measures of language (receptive vocabulary)
and working memory explained variance in performance. If memory capacity is a critical
influence on children’s production of complex sentences, we would expect sentences that
relate events in reverse order to be produced less accurately than those that relate
events in chronological order. Specifically, before–chronological sentences should be
produced most accurately because they contain features that would not be expected to
increase the amount of information that must be held in working memory (chronological
order, medial position, less complex connective). In contrast, the other structures each
have two factors that increase the amount of information maintained in working memory:
before–reverse (reverse order, initial position), after–chronological (initial position,
more complex connective), and after–reverse (reverse order, more complex connective).
Furthermore, if memory capacity is the critical influence on accurate production, our
independent measure of memory should predict the effect or interacting effect of these
features, and also serve as a proxy for age, when both age and memory are included in the
model. A language-based account predicts that the influence of working memory is indirect
and modulated by language knowledge (MacDonald, 2016). As a result, any difficulties in
producing reverse order sentences should be more pronounced when they are linked by the
connective after because the planning of a reverse order sentence should be disrupted more
easily when it contains after than when it contains before. In addition, the independent
measure of vocabulary should modulate performance because it indicates the quality of an
individual’s language knowledge. According to this account, the inclusion of an
independent measure of vocabulary should improve model fit over and above the inclusion of
an independent measure of memory. Furthermore, because vocabulary knowledge grows with
age, vocabulary effects should supersede any age effects once included in the model. In
summary, there were three aims of this study. The first was to establish which
features—order of events, connective, position of connective—influence the accuracy of
children’s production of two-clause sentences containing the temporal connectives before
and after. Second, we examined which account best explains the pattern of performance—a
traditional memory capacity-constrained account or a more nuanced perspective of working
memory that argues that language knowledge influences memory processing and storage.
Third, we asked whether the same pattern of performance is reproduced across our two
paradigms designed to elicit sentence production.

<h>EXPERIMENT 1</h>
------------

We assessed sentence production using a sentence repetition task in which participants
heard a target sentence and were asked to repeat it back to the experimenter. Sentence
repetition is a sensitive measure of processing ease because the participants are required
to process the syntactic and semantic information and then formulate the sentence
themselves using the same sentence production mechanisms as in spontaneous speech (see
Boyle, Lindell, & Kidd, 2013; Lust, Flynn, & Foley, 1996). In general, children are less
accurate when repeating sentences with more difficult structures. Previous studies of
children’s production of sentences containing temporal connectives using sentence
repetition have contrasted sequential (e.g., then, before) and simultaneous (e.g., while,
when) connectives (Keller-Cohen, 1981; Winskel, 2003), so these do not speak to the issues
addressed in this article.

        <hss>Participants</hss>

        A total of 67 monolingual, typically developing 3- to- 6-year-old children were
        recruited from schools of mixed socioeconomic status in the North West region of
        England. Children were in three different school year groups: 20 3- and 4-year-
        olds (ages 3;5 [years;months] to 4;7; 13 boys), 23 4- and 5-year-olds (ages 4;9 to
        5;9; 12 boys), and 24 5- and 6-year-olds (ages 5;9 to 6;8; 11 boys). Written
        parental consent was obtained, and children provided oral assent before each
        session.

        <hss>Materials and procedure</hss>

        All children completed a sentence repetition task split between two sessions. In
        addition, one session included an assessment of receptive vocabulary, and the
        other session included an assessment of memory. Each session lasted no longer than
        20 min.

            <hss>Sentence repetition</hss>

            A total of 32 two-clause sequences containing before and after were
            constructed. Each of the 32 items conveyed the temporal order of two events
            that were arbitrarily related (e.g., “He put on the socks, before he ate the
            burger”). These items were counterbalanced across four lists so that they each
            represented one of four sentence constructions (shown in Table 1). The four
            constructions were the product of manipulations of the order of mention of
            events (chronological or reverse) and the connective (before or after). We
            also created 32 filler sentences in which the sequence of events in a sentence
            was typical and supported by world knowledge rather than arbitrary (e.g., “He
            put on the socks, before he put on the shoes”). Sentences that relate typical
            sequences (world knowledge present) may reduce the working memory demands of
            the task by scaffolding the structure of the sentence (Zwaan & Radvansky,
            1998). We included these sentences to enhance the likelihood that children
            would produce full sentences in the task and to maintain their confidence
            (proportion accuracy reported in Table A1 in Appendix). Each sentence was
            visually represented by cartoon animations, one for each clause and each
            lasting 3 s. These were created using Anime Studio Pro 9.1 (Smith Micro
            Software; http://anime.smithmicro.com/index.html). Animations make children
            more likely to use the actor, action, and object of the target sentence,
            thereby increasing accuracy (Ambridge & Lieven, 2011). Each animation segment
            explicitly showed an object (e.g., shoes) from one of the clauses; the object
            (e.g., burger) from the other clause was not present. Each animation segment
            was followed by a freeze-frame judged by the researchers to best represent the
            action of that clause. Each segment (e.g., Tom eating a hotdog) was 486 pixels
            in height and did not exceed the left or right half of the presentation (486 ×
            872 pixels). The experiment was run using the PsyScript 3.2.1 (Slavin, 2013)
            scripting environment on a Macintosh laptop computer connected to a monitor.
            Presentation of items was fully randomized. Practice trials emphasized the
            importance of producing an exact copy of the narrated sentence. Children
            practiced each of the four sentence constructions used in the experimental
            items (i.e., two-clause sentences linked by before and after) (see Table 1 for
            examples). The animation on the left-hand side of the screen was shown first,
            followed by the animation on the right-hand side of the screen. The
            instruction to prompt production began with “Can you say …” and was followed
            immediately by the narration of the target sentence. A response window was
            signaled by a short beep. The presentation order of the animation segments
            corresponded to the actual order of events rather than the narrated order.
            Responses were recorded using a digital voice recorder (Olympus VN-5500;
            Watford, Hertfordshire, United Kingdom) and were later transcribed and scored.
            Children who were not able to repeat a sentence after four practice trials
            completed another set of four practice trials. With this level of practice,
            each child was able to copy at least one sentence. For each experimental
            trial, an exact repetition was scored as a target response. Based on
            recommendations by Lust et al. (1996), a response was also marked as a target
            response if a change was only minor such as a change to the label for a
            subject (e.g., Sue, she), a verb (e.g., put on, putted on), or an object
            (e.g., ketchup, tomato sauce). This lenient criterion was used because marking
            such changes as non-target responses would create unnecessary noise when the
            main point of interest was to evaluate the variance that was caused by the
            factors we had hypothesized to affect children’s ability to accurately
            communicate the order of events using a temporal connective. The time taken
            between the beep and the start of children’s response was extracted using
            Audacity (Mazzoni, 2014). There were no significant differences in response
            times between age groups or sentence constructions for target responses, so
            response time data are not reported. Non-target responses were first
            categorized into three broad types: sense maintained, sense changed, and
            incomplete. We categorized responses as sense maintained if children
            inaccurately repeated the target sentence but successfully communicated the
            order of events by using a temporal connective. The sense maintained responses
            were counted as non-target responses because at least one critical feature of
            the target sentence was missing (connective, order of mention, or position)
            (see Table A2 in Appendix). Responses were categorized as sense changed when a
            non-target order of events was communicated. Responses were categorized as
            incomplete when children failed to respond, omitted a clause, failed to use a
            connective, or used the connective and. Responses that used the connective and
            (42) were categorized as incomplete because and does not explicitly specify
            order (Peterson & McCabe, 1987), so we were unable to categorize whether the
            response maintained or changed the sense or order. Within each of the three
            broad non-target response categories, we coded the specific change or
            combination of changes that children had made. The Appendix includes examples
            and frequency counts of each specific non-target response type (see Table A2).
            A second coder blind to the hypotheses coded at least 10% of the data
            (randomly selected) from each year group. Agreement between coders was good
            for both accuracy (target vs. non-target responses, agreement = 99%, Cohen’s κ
            = .96) and the categories of non-target responses (agreement = 96%, Cohen’s κ
            = .80).

            <hss>Memory</hss>

            Working memory was assessed using the digit span task from the Working Memory
            Test Battery for Children (Pickering & Gathercole, 2001). In this task,
            children are required to recall the order of a string of digits read aloud by
            the assessor. The number of digits in a string increases until children cannot
            successfully recall strings of that length on three separate trials. This
            assessment of memory was selected because it was most appropriate for our
            youngest children, who have been reported to perform at floor on more complex
            measures of working memory (Gathercole, Pickering, Ambridge, & Wearing, 2004).
            By using this measure, we could capture variance in memory performance across
            the entire age range. Raw scores were used in the analysis. The test–retest
            reliability reported in the manual for children aged 5 to 7 years is high at r
            = .81.

            <hss>Vocabulary</hss>

            Each child completed the British Picture Vocabulary Scale-III (Dunn, Dunn,
            Styles, & Sewell, 2009). In this task, children hear a word and are asked to
            point to one of four pictures that best illustrates its meaning. Testing is
            discontinued when a specified number of errors have been made. Raw scores were
            used in the analysis.

        <hss>Design</hss>

        A 3 × 2 × 2 mixed design was used. The between-participants independent variable
        was year group (3- and 4-year-olds, 4- and 5-year-olds, or 5- and 6-year-olds),
        and the within-participants variables were connective (before or after) and order
        (chronological or reverse). The position of the connective was manipulated as a
        function of the manipulations of connective and order. Two analyses were
        conducted: one with number of target responses as the dependent variable and the
        other with non-target response types as the dependent variable.

        <hss>Method of analysis</hss>

        The main analysis of the number of target responses was completed using
        generalized linear mixed-effects models (GLMMs) (Baayen, Davidson, & Bates, 2008;
        Barr, Levy, Scheepers, & Tilly, 2013). Significant interactions were explored by
        additional analyses to identify the source of the interaction and are reported
        below. These were conducted using the lme4 package from the R statistics
        environment (Bates, Maechler, Bolker, & Walker, 2015; R Development Core Team,
        2016). A binomial link function was specified because the outcome variable was
        binary (i.e., target/non-target). We followed the recommendations of Barr et al.
        (2013) for obtaining an optimal model. Our maximum random-effects models did not
        converge, so the decision to incorporate random intercepts and slopes for
        participants and items was determined by the result of incremental likelihood
        ratio tests that demonstrated whether each specific random effect significantly
        improved model fit (Barr et al., 2013). We describe the optimum models for each
        respective dataset later in Tables 2 and 3, where the first column provides the
        coefficient estimates of effects (b) due to experimental conditions, the change in
        the log odds accuracy of responses associated with each fixed effect. A positive
        coefficient indicates that the effect of a factor is to increase the odds of a
        target response, whereas a negative coefficient indicates that the factor
        decreases the odds of a target response. Age in months (continuous), order
        (chronological or reverse), and connective (before or after) were entered as fixed
        effects. We used the scale function to scale and center the age, memory, and
        vocabulary predictors.

        <hss>Memory</hss>

        The raw memory scores [mean (SD)] demonstrated age-related improvements: 3- and
        4-year-olds = 21.65 (5.66); 4- and 5-year-olds = 22.65 (3.70); 5- and 6-year-olds
        = 25.42 (3.45). In addition, the standardized scores of memory were within the
        normal range of 85 to 115 for each age group: 4- and 5-year-olds = 101.39 (12.43);
        5- and 6-year-olds = 105.96 (12.19); standardized scores are not available for 3-
        and 4-year-olds.

        <hss>Vocabulary</hss>

        The raw vocabulary scores demonstrated age-related improvements: 3- and 4-year-
        olds = 72.65 (26.16); 4- and 5-year-olds = 78.26 (9.76); 5- and 6-year-olds =
        102.30 (8.59). All children had a standardized score above 85, and the mean scores
        indicated that each age group was performing at an age-appropriate level: 3- and
        4-year-olds = 111.35 (13.08); 4- and 5-year-olds = 101.22 (9.14); 5- and 6-year-
        olds = 101.54 (9.10).

        <hss>Analysis of accuracy data</hss>

        A total of 2144 responses were recorded. Fig. 1 shows the means for each sentence
        structure by age in years for ease of comparison (note that the analyses were
        conducted using age in months as a continuous variable). For the two younger
        groups, 19 responses were removed because they were inaudible, leaving 1357
        responses for analysis. Only 13 responses were judged to be inappropriate
        (nonsense or no response), indicating that children understood the purpose of the
        task. The initial model included the main predictors of age, order, and
        connective. The inferential statistics, main effects, and interactions are
        summarized in Table A3 of the Appendix. Response accuracy was significantly
        affected by age, indicating that performance improved between 3 and 6 years of
        age. There was also a significant effect of order, such that children were more
        likely to repeat chronological order sentences accurately than reverse order
        sentences. A significant effect of connective was also found; children were more
        likely to repeat sentences containing before accurately than those containing
        after. Order and connective were involved in a significant two-way interaction,
        which was examined by conducting simple interaction analyses of the effects of
        order for each connective separately. A main effect of order was evident for after
        sentences but not for before sentences. Children found it more difficult to
        accurately repeat after–reverse sentences compared with after–chronological
        sentences, whereas accuracy was equivalent for before–chronological and
        before–reverse sentences. The final model incorporated memory and vocabulary as
        additional factors to age, order, and connective (see Table 2). In comparison with
        the initial model, log-likelihood tests indicated that the fit of the data was
        significantly improved when we incorporated memory alone, χ2(4) = 20.01, p < .01,
        when we incorporated vocabulary alone, χ2(4) = 12.67, p = .01, and when memory and
        vocabulary were incorporated together, χ2(8) = 29.21, p < .01. Memory and
        vocabulary both significantly influenced performance, such that stronger sets of
        skills in both domains improved performance. The main effects of order and
        connective remained significant and were again involved in a significant two-way
        interaction. There was no three-way interaction with either memory or vocabulary.

        <hss>Analysis of non-target responses</hss>

        The frequency of different types of non-target responses was investigated to
        determine whether particular types were associated with specific experimental
        conditions (sentence constructions) and/or age group. This provided an opportunity
        to examine additional support for either the memory or language account, as
        outlined in the Introduction. We excluded responses from the oldest age group
        because their high accuracy scores left too few non-target responses for
        meaningful analysis (120 of all 702 non-target responses; 17%). The two youngest
        age groups made 582 non-target responses. The majority of non-target responses
        involved a change of sense to the meaning of the target sentence (sense changed =
        358; 61% of all non-target responses analyzed). Fewer non-target responses
        maintained the sentence meaning (sense maintained = 131; 23%) or were incomplete
        (incomplete responses = 93; 16%). These three categories of non-target responses
        did not vary substantially by experimental condition, although it is worth noting
        that sense changed errors made up a higher proportion of 3- and 4-year-olds’ non-
        target responses (66%) compared with those of 4- and 5-year-olds (57%). To further
        examine non-target responses, we calculated the percentage of sense changed
        responses that involved a change of connective, order, or position. A change of
        connective was the most common (252; 70% of all 358 sense changed responses);
        there were far fewer position (109; 30%) and order (78; 22%) changes. These values
        add up to more than 100% because the non-target response types are not mutually
        exclusive; children could include more than one of these changes in their
        response. We conducted a further analysis to examine the most common type of sense
        changed response: those involving a change to the target connective (252). Of
        these, we excluded 34 responses involving a change to the target connective other
        than before and after (e.g., then, and then, when). This was because children’s
        use of other connectives to communicate a non-target order of events was not a
        clear indicator for a weak representation of before or after. The 218 remaining
        changes to the connective were explicit demonstrations of producing before or
        after to communicate a non-target event order: before instead of after (e.g., “He
        put on the socks, before he ate the burger” instead of the target “He put on the
        socks, after he ate the burger”) or after instead of before (e.g., “He put on the
        socks, after he ate the burger” instead of the target “He put on the socks, before
        he ate the burger”). The most obvious reason for why children make these changes
        is that they have a weak representation of the precise meaning of before or after.
        We examined the percentage of the total non-target responses (582) in each
        experimental condition (i.e., age, order, connective) that were caused by a sense
        changed response involving a change of before instead of after or a change of
        after instead of before (218: 37% of all non-target responses). The Appendix
        provides descriptive statistics (Table A4) and a summary of the GLMM (Baayen et
        al., 2008) for this analysis (Table A5). The changes were involved in a
        significantly larger percentage of the non-target responses for reverse order
        sentences (44%) compared with chronological order sentences (30%). The changes
        were more frequent for the youngest age group than for the middle age group (3-
        and 4-year-olds = 40%; 4- and 5-year-olds = 35%), but the difference was not
        significant. Similarly, although these changes were less common for before
        sentences than for after sentences (before = 33%; after = 41%), the difference was
        not significant. Finally, although these changes were most common for
        after–reverse sentences, the interaction between connective and order was not
        significant (before–chronological = 29%; after–chronological = 31%; before–reverse
        = 37%; after–reverse = 48%). Note that Table A4 also provides descriptive
        statistics to show that a similar pattern is present for the percentage of the
        total non-target responses (582) in each experimental condition that was caused by
        all changes of connective (i.e., sense maintained and sense changed responses and
        also inclusive of changes to then, and then, and when). This pattern (described
        above) was not evident for non-target responses that involved a change to order or
        a change to position.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The sentence repetition task was successful at eliciting production of complete two-clause
sentences linked by an appropriate temporal connective, yielding very few incomplete
responses (no more than 8% of all responses in any age group). Our experimental
manipulations demonstrated an influence of event order and connective on production
accuracy. In addition, performance on independent measures of memory and vocabulary
improved the overall fit of the model. These results do not provide unequivocal support
for either the memory capacity-constrained account (Carpenter et al., 1994) or the
language-based account (e.g., MacDonald, 2016) of sentence processing. When considered
together with the analysis of the non-target responses, the results lend greater support
to the language-based account for the reasons discussed below. Reverse order sentences are
proposed to incur a greater memory load than chronological order sentences because the
speaker must produce the first occurring event as the second clause, which requires this
information to be maintained in working memory during planning and production (Habets et
al., 2008). Our participants were less accurate in producing reverse order sentences
linked by after than those linked by before, demonstrating that this effect was specific
to the connective. Independent measures of both memory and vocabulary improved the fit of
the model. These findings lend greater support to the language-based account of sentence
processing, namely that there is an indirect relation between memory and sentence
processing that is modulated by language. The explanation for this is that young
children’s lexical representations for after are less precise and secure than those for
before because after is acquired later and used less consistently as a temporal
connective. For that reason, it may be more difficult to accurately plan and maintain in
memory multi-clause sentences linked by after during language production, particularly
when the event order is reversed. In that way, variation in language knowledge may lead to
difficulties with sentence production, particularly for sentence structures that have a
high processing load such as those relating events in reverse chronological order. Our
findings do not rule out the alternative memory capacity-constrained account because the
independent measure of memory made a significant and independent contribution to the fit
of our statistical model. However, our analysis of non-target response types provides
additional support for the language-based account. Changes to the target connective that
used before and after to communicate a non-target event order (sense changed responses)
were more likely for reverse order sentences than for chronological order sentences. These
made up the majority of sense changed responses that involved a connective change (218 of
252; 87%). The most obvious reason for why children make these changes is that they have a
weak representation of the connective itself. This is supported by the main effect of
connective type in our main analysis; children were less accurate at producing sentences
containing after than those containing before in general. This analysis of non-target
responses indicates that an inaccurate representation of the connective itself (as
measured by a change in connective) does not provide the support needed for the planning
and production of reverse order sentences. Also note that, although not significant, the
descriptive statistics by sentence are in line with a language-based account because an
inaccurate representation of the connective influenced a greater percentage of the non-
target responses to target after–reverse sentences (52%) than to the other target sentence
constructions (ranging from 31% to 40%).

<h>EXPERIMENT 2</h>
------------

A limitation with the sentence repetition paradigm used in Experiment 1 is that it places
additional demands on memory compared with speech production because children need to
store the just-heard sentence prior to production. For that reason, sentence repetition
might not be the most sensitive task to differentiate the memory capacity-constrained and
language-based accounts of children’s and adults’ sentence processing. Experiment 2 sought
to further test these accounts using a different method to elicit sentence production. We
used a blocked design task comprising four blocked sets of items, each assessing the
ability to produce one of the four target sentence constructions (e.g., Huttenlocher,
Vasilyeva, & Shimpi, 2004). These blocked conditions were designed to complement
Experiment 1 by minimizing the contributions of sentence comprehension and memory
associated with sentence repetition and maximizing spontaneous production of sentences.

        <hss>Participants</hss>

        A new sample of participants was recruited (N = 67): 23 3- and 4-year-olds (ages
        3;8 to 4;11; 10 boys), 23 4- and 5-year-olds (ages 4;9 to 5;9; 13 boys), and 21 5-
        to 6-year-olds (ages 5;10 to 6;9; 10 boys).

        <hss>Materials, procedure, and design</hss>

        Children completed the same independent measures of memory and receptive
        vocabulary as in Experiment 1. Sentence production was assessed using an elicited
        production task with a blocked design over two separate sessions. Each session
        lasted no longer than 20 min. One session included the vocabulary assessment, and
        the other session included the memory assessment.

            <hss>Elicited production: Blocked design</hss>

            The same stimuli from Experiment 1 were used. The 64 items (32 fillers) were
            split into four testing blocks, each preceded by a training phase in which
            children were instructed to use a specific target sentence structure.
            Depending on which block children performed first, the experimenter provided
            this instruction: “In this game, I am going to ask you to watch two videos and
            to say what happened using the word before/after. I want you to tell me the
            order that he/she did these things, and I want you to use before/after in the
            middle/at the start of your sentence.” Corrective feedback was provided for
            all four practice items, and training was repeated if children failed to
            produce a single target sentence. Three 3- or 4-year-olds and one 5- or
            6-year-old were excluded from testing after this phase because they each
            failed to accurately produce any of the target structures. As in Experiment 1,
            the order in which the animations were presented corresponded to the order of
            events described by the target sentence. An instruction was narrated: “Can you
            tell me the order that Tom did these things?” A response window was signaled
            by a short beep. The four blocked conditions were counterbalanced. Responses
            were recorded and were later transcribed and scored. We used the same criteria
            for scoring accuracy of responses and for categorizing non-target responses as
            in Experiment 1. We did not analyze the time taken to start a response because
            this measure was found not to be sensitive in Experiment 1. Agreement between
            the coders was good both for scoring accuracy of responses (target vs. non-
            target responses agreement = 99%, Cohen’s κ = .97) and for categorizing non-
            target responses (agreement = 96%; Cohen’s κ = .96).

        <hss>Memory</hss>

        The raw memory scores demonstrated age-related improvements: 3- and 4-year-olds =
        21.15 (2.12); 4- and 5-year-olds = 22.57 (2.12); 5- and 6-year-olds = 25.05
        (4.95). In addition, the standardized scores of memory were within the normal
        range of 85 to 115 for each age group: 4- and 5-year-olds = 100.52 (14.85); 5- and
        6-year-olds = 105.9 (12.73); standardized scores are not available for 3- to
        4-year-olds.

        <hss>Vocabulary</hss>

        The raw memory scores demonstrated age-related improvements: 3- and 4-year-olds =
        70.85 (7.78); 4- and 5-year-olds = 82.48 (12.02); 5- and 6-year-olds = 90.95
        (9.90). All children had a standardized score above 85, and the mean scores
        indicated that each age group was performing at an age-appropriate level: 3- and
        4-year-olds = 111.75 (7.07); 4- and 5-year-olds = 100.45 (14.85); 5- and 6-year-
        olds = 102.15 (16.26).

        <hss>Analysis of accuracy data</hss>

        The main analysis of the number of target responses was completed using the same
        procedures of model fitting described for Experiment 1. A total of 45 responses
        (2%) were excluded because they were inaudible or interrupted, leaving 1345
        responses. Fig. 2 reports the mean accuracy scores for each experimental condition
        by age group. Of note, performance for each age group was poorer than in
        Experiment 1, with the most marked difference in scores being for the youngest age
        group. We report the initial model with age, order, and connective entered as
        fixed effects in Table A6 of the Appendix. Table 3 shows the final model that
        incorporates memory and vocabulary as additional factors to age, order, and
        connective. For the initial model, we found the main effects of age, order, and
        connective that were reported in Experiment 1. As predicted, older children
        produced a greater proportion of accurate responses than younger children,
        chronological order sentences were easier than reverse order sentences in general,
        and sentences containing before were easier than those containing after. There
        were two significant two-way interactions. The first, between age and order, was
        also apparent in Experiment 1; the other, between age and connective, was not
        found for the sentence repetition task. These effects were qualified by a
        significant three-way interaction among age, order, and connective. We examined
        the significant three-way interaction by conducting simple interaction analyses
        for the effects of age and order for each connective separately. For before
        sentences, only the main effect of age reached statistical significance (see Table
        A6 in the Appendix for a full breakdown of results, and see Fig. 2 for graphs of
        these effects by sentence construction): Accuracy was equivalent for
        before–chronological and before–reverse sentences. For after sentences, there were
        main effects of age and order, and these were also involved in a significant two-
        way interaction. Children found it more difficult to produce after–reverse
        sentences accurately than after–chronological sentences, and this difficulty with
        after–reverse sentences was more pronounced for the younger children. We tested
        three additional models. The addition of memory to the original model
        significantly improved the fit of the data, χ2(4) = 20.11, p = .01, and resulted
        in a significant three-way interaction among memory, order, and connective. This
        suggests that memory modulated the interaction between connective and order. The
        memory alone model is reported in Table A7 of the Appendix. In another model, we
        added vocabulary to the original model and also found improved fit compared with
        the original model, χ2(8) = 33.57, p = .01. In the final reported model (see Table
        3), we included both vocabulary and memory. This resulted in improved fit compared
        with the memory alone model, χ2(4) = 12.08, p = .02, and there was a main effect
        of vocabulary but not of memory. In addition, the memory by order by connective
        interaction was not evident when vocabulary was also present.

        <hss>Analysis of non-target responses</hss>

        Responses by 5- and 6-year-olds were excluded because their high accuracy scores
        resulted in too few non-target responses for meaningful analysis (15% of all non-
        target responses by the three age groups; 152 of 1019). We analyzed the 867 non-
        target responses made by 3- and 4-year-olds and 4- and 5-year-olds. The sense
        maintained responses made up the highest percentage of responses (410; 47%),
        followed by incomplete responses (305; 35%) and then sense changed responses (152;
        18%). These findings contrast with Experiment 1, in which sense changed responses
        made up the highest percentage of non-target responses. The different types of
        non-target responses did not vary significantly by experimental conditions,
        although 3- and 4-year-olds made a substantially greater number of incomplete
        responses than 4- and 5-year-olds (220; 42% vs. 85; 25% by age group,
        respectively). To further examine non-target response type, we calculated the
        percentage of sense maintained responses that involved a change to connective,
        order, or position. As noted in Experiment 1, these response types do not add up
        to 100% exactly because more than one non-target change can be used in a single
        non-target response. Change in connective was the most common type of sense
        maintained response (313; 76% of sense maintained responses). In addition,
        position (237; 58%) and order (256; 62%) changes were also evident in more than
        half of the total responses that maintained the sentence meaning. Of the 313 sense
        maintained responses involving a change of connective, only 129 were a change to
        the connective that involved the replacement of before for after or that of after
        for before. Therefore, unlike Experiment 1, there were too few responses of this
        type for further analysis.

<hs>  Discussion</hs>
  ~~~~~~~~~~

The elicited production task complements the sentence repetition task used in Experiment
1, yielding complete two-clause sentences linked by an appropriate temporal connective
from young children. As in Experiment 1, there was a main effect of connective because
after was more difficult than before in general. In addition, there was a main effect of
order because reverse order sentences were more difficult than chronological order
sentences. Also replicating Experiment 1 was the finding that children were least accurate
when instructed to produce reverse order sentences linked by the connective after. That
is, we again found that difficulty with reverse order sentences was modulated by
connective; the effect was limited to after–reverse sentences. A critical difference
between the two experiments was that production of after–reverse sentences was not
modulated by children’s working memory capacity in Experiment 2 when vocabulary was
entered into our statistical model. Together, these findings suggest that language
knowledge, rather than memory, is the stronger determiner of accurate sentence production.
Our analysis of non-target responses revealed a lower proportion of these involving a
change of sense compared with Experiment 1. It is important to note that there were few
incomplete responses made by 5- and 6-year-olds (30; 5% of all responses) and 4- and
5-year-olds (85; 12% of all responses), although a third of 3- and 4-year-olds’ responses
were incomplete (220; 34% of all responses). This highlights the utility of the blocked
elicitation paradigm to restrict speaker use to target sentence structures (Ambridge &
Lieven, 2011).

<h>GENERAL DISCUSSION</h>
------------------

These two experiments demonstrate that young children have difficulties in producing two-
clause sentences containing before and after during the developmental period that follows
their emergence in spontaneous speech. In both experiments, children up to 6 years of age
had particular difficulties in producing reverse order sentences linked by the connective
after. Clear developmental improvements were evident within this age range. Our
experiments advance our understanding of the factors that influence young children’s
sentence production, demonstrating that memory capacity-constrained accounts of sentence
processing need to factor in the influence of language knowledge rather than attribute
difficulties to limited working memory capacity per se. We also demonstrated that
investigations that include more than a single paradigm are important to yield robust
conclusions in the study of children’s language production. We tested two memory-based
accounts for why some sentence structures are more difficult than others: a traditional
memory capacity-constrained account (e.g., Carpenter et al., 1994) and a more nuanced
language-based perspective of working memory (e.g., MacDonald, 2016). Both accounts
predicted that reverse order sentences would be produced less accurately than
chronological order sentences in general. Our findings support this prediction, with main
effects of order evident in both experiments. According to the memory capacity-constrained
account (Carpenter et al., 1994), this effect arises because these sentences require more
units of information to be held active in working memory. Additional support for this
account was evident; higher working memory capacity predicted better overall performance
in Experiment 1. However, other findings indicate that such an interpretation cannot fully
explain our findings for the reasons discussed below. Our results are in line with the
language-based account of sentence processing proposed by MacDonald (2016) and others, in
which the effects of working memory are not direct but rather the result of its relation
with language knowledge. The ability to represent information accurately in short-term
memory is a requirement for good performance on a sentence production task. The language-
based account proposes that short-term memory performance is influenced by the quality of
language knowledge. We found support for this account in several ways. First, the effect
of order was not consistent across connective; in both experiments, there was a
significant order by connective two-way interaction, which was further qualified by age in
a three-way interaction in Experiment 2. Critically, in both experiments, sentences with
the connective after were less likely to be produced accurately in the reverse order
condition than in the chronological order condition; this effect was not found for
sentences with the connective before. These findings indicate a role for language over and
above any memory effects. In addition, an independent measure of language ability
explained performance over and above our independent measure of memory. Third, an
inferential analysis of non-target responses in Experiment 1 indicated that a weak
representation of our target connectives (measured by connective change responses) does
not provide the support needed for the planning and production of reverse order sentences,
and descriptive statistics for the sentence constructions showed that this influence was
most pronounced with target reverse order sentences linked by after. Note that these
findings together indicate that the influence of the connective is not explained by
features of the language unit placing additional load on working memory per se; rather,
the findings are in line with a language-based account proposal that more processing
resources are required to retrieve the context-relevant meaning of after compared with
before, so there are fewer processing resources available to accurately represent reverse
order sentences in active memory. It is also worth noting that if children had displayed
low accuracy for before sentences in the reverse order condition relative to the
chronological order condition, such a finding would not necessarily have opposed the
proposal by a language-based account that accurate production is influenced by the quality
of language knowledge (e.g., MacDonald, 2016). Specifically, even if children have a
robust representation of before, planning and production of reverse order sentences linked
by before can be disrupted by a weak lexical representation for other words in the
sentence. Although not significant, descriptive statistics indicated that accuracy levels
for chronological and reverse order sentences linked by before were equivalent for
Experiment 1 but not for Experiment 2 (lower accuracy for before–reverse). Unlike
Experiment 1, Experiment 2 did not provide children with the target words prior to their
task to produce a target sentence. Only Experiment 2 reported that vocabulary had a
greater influence than memory, which suggests that before–reverse sentences could be more
difficult to produce when the task provides less support for words in the sentence. This
in line with the proposal that a robust representation of words in the sentence frees up
processing resources for the accurate representation of reverse order sentences in active
memory. Our sentence constructions were counterbalanced across conditions, and the effects
were specific to after, which has a less consistent form–meaning relationship relative to
before. Thus, we conclude that the accurate production of reverse sentences linked by
after is more likely to be influenced by a weak representation for the target connective
rather than representing more general language effects. Although difficulty with
after–reverse sentences was replicated across both experiments, there are at least two
reasons to remain cautious about accepting a language-based explanation as the sole reason
for young children’s difficulties in producing multiple-event sentences. First, we must
consider the possibility that order effects are modulated by a confounding variable,
connective position, rather than connective. Second, we must address why the stronger
influence of vocabulary over memory (determined by examining model fit) was apparent only
in Experiment 2. These limitations are considered in turn below. A natural consequence of
our design was that the interaction between connective and order was influenced by
connective position because this also differs across sentence structures. For example,
after is used in a sentence-initial position when the order of events is presented
chronologically (“After he put on the socks, he ate the burger”) but is used in a
sentence-medial position when events are presented in reverse order (“He ate the burger,
after he put on the socks”). The reverse applies to before sentences. Thus, an alternative
explanation for a specific difficulty with reverse order sentences is that the position of
the connective modulates the effects of order. That is, a reverse order sentence in which
the temporal sequence is cued by before may be easier to represent than its after
counterpart because the initial position of the connective signals from the beginning that
events will be narrated in a reverse order. This viewpoint is supported by evidence that
speakers have cognitive biases to highlight certain referents at the beginning of the
sentence, in our case the temporal connective, that act as cues to reduce ambiguity for
the listener (e.g., Chafe, 1984; Grice, 1975; Myachykov, Garrod, & Scheepers, 2012; Silva,
1991). Conversely, reverse order sentences that contain after may be more difficult to
plan and narrate because the critical information about event order is provided midway
through the sentence, which may place greater demands on working memory. We believe that
this account—that connective position rather than connective itself modulates order
effects—does not adequately explain our pattern of findings. If position accounts for our
results, the difficulty with after–reverse sentences would arise because the late
signaling of reverse order places greater demands on memory capacity than early signaling.
However, our independent measure of memory was a weaker predictor of performance than our
independent measure of vocabulary. Moreover, as cited in the Introduction, corpus work
suggests that speakers have a preference for relating information using the connective in
a medial position (Diessel, 2004, 2008). Clearly, more experimental work is needed to
investigate the role of connective position in sentence production. The second reason for
caution in accepting a language-based account over a memory capacity-constrained account
was that both memory and vocabulary improved model fit in Experiment 1. That is, stronger
memory and vocabulary both were associated with more accurate performance, and our
independent measure of vocabulary did not explain unique variance in children’s specific
difficulty with after–reverse sentences (Experiment 1). The greater influence of
vocabulary over memory in Experiment 2 compared with Experiment 1 may have arisen due to
the task demands. Participants in the sentence repetition task used in Experiment 1 were
provided with the language form in their input, whereas participants in the elicited
production task used in Experiment 2 needed to use their language knowledge to specify
every level of detail of the form themselves (i.e., syntactic, morphological,
phonological, articulatory) so that it could be mapped onto the intended meaning (see
Garrett, 1980; Gennari & MacDonald, 2009; Vigliocco & Hartsuiker, 2002). Therefore, there
may be greater demands on language knowledge retrieval processes in the production task
used in Experiment 2, where children were not first provided with the input to repeat. The
above explanation may help to understand why the pattern of findings across sentence
structures in these production experiments differs from that reported in recent work
examining comprehension of the same sentences (Blything & Cain, 2016; Blything et al.,
2015). Blything et al. (2015) found that reverse order sentences that contained after were
the most difficult to comprehend, the same pattern reported here for production. However,
in contrast to the findings of these production experiments, after–reverse sentences were
not statistically more difficult to comprehend; instead, an advantage for
before–chronological sentences drove the effect. Furthermore, in both of the previous
comprehension studies, an independent measure of working memory accounted for significant
variance in performance, whereas an independent measure of vocabulary did not. This is in
contrast to the current findings; our replication across two production studies of
difficulty with after–reverse sentences, in addition to stronger effects of an independent
measure of vocabulary than of memory capacity, suggests that a different explanation is
required for production than that used for comprehension. The difference between the
findings of the current production study and previous comprehension studies can be
explained by how comprehension and production draw on memory and language. Comprehension
tasks provide participants with the language form in their input in the same way as
described earlier for sentence repetition tasks. Therefore, differences across the domains
might be explained in the same way as was proposed above for why the current study
provides greater support for the language-based account in the more pure production task
(Experiment 2) relative to the production task that carried a comprehension component
(Experiment 1).

<hs>  Limitations, implications, and future research</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A strength of this work is the replication of the main finding across two different tasks;
children up to 6 years of age had difficulties in producing two-clause reverse order
sentences linked by the connective after. However, the analysis of non-target responses
highlighted differences in the nature of our two experiments, which we believe is
informative for researchers considering a marriage of the two paradigms. First, incomplete
responses comprised 35% of the non-target responses in the elicited production task
(Experiment 2) compared with only 16% in the sentence repetition task (Experiment 1). This
may be due to the scaffolding provided by the initial input in a sentence repetition task,
which supports children to produce the target response. Another notable difference between
the experiments was that sense maintained responses made up the largest percentage of non-
target responses in elicited production (Experiment 2), whereas sense changed responses
comprised a large percentage of non-target responses in the sentence repetition task
(Experiment 1). In sense-maintained responses, children produced a temporal connective as
a linguistic device to successfully communicate order but did not use the target
structure. This indicates that the elicited production paradigm, which resulted in a high
number of sense maintained responses, is more likely to result in children reverting back
to a sentence structure with which they are familiar when required to signal temporal
order with a connective. Overall, the difference in non-target response types, along with
the differences in the nature of the tasks themselves, illustrates that investigations
that include more than a single paradigm are important to yield robust conclusions in the
study of children’s language production. Age differences in Experiment 2 persisted when
memory and vocabulary were incorporated into the model. Given the high accuracy shown by
5- and 6-year-olds in Experiment 1, other experimental methods are required to study and
understand better developmental and individual differences in the planning and production
of complex sentences such as these. Habets et al. (2008) successfully used event-related
potentials (ERPs) to study processing differences in the production of chronological and
reverse order temporal sentences in adults. Such techniques might be adapted for use with
children. In addition to using different experimental paradigms to assess the time course
and difficulty of production, a more comprehensive battery of tasks could be used to
measure the constructs of both working memory and language. Ideally, working memory tasks
should measure the storage and manipulation of information to tap these two critical
functions of working memory (Oberauer & Lewandowsky, 2010). However, as noted, 5-year-olds
find such complex span tasks hard to perform (Gathercole et al., 2004). In addition,
memory tasks with a low semantic load should be used to determine the relationship between
sentence processing and working memory capacity, distinct from language knowledge (Kidd,
2013). Digit-based tasks as used here (forward digit recall) can be advantageous in this
respect because they have a lower semantic load and so are less strongly related to
independent measures of language (Cain, 2006; Seigneuric, Ehrlich, Oakhill, & Yuill, 2000;
but see Jones & Macken, 2015). Similarly, additional measures of vocabulary as well as
tests of grammatical knowledge could be included to more fully assess the construct of
language and children’s knowledge of cohesive devices such as connectives (Language and
Reading Research Consortium, 2015; see also Cain & Nash, 2011, for work with older
children demonstrating differences between connective knowledge and use to at least 10
years of age). Note, however, that the measures used in the current study were predictive
of performance, and these suggestions do not undermine the current findings; rather they
offer ways to develop a more fine-grained picture of the influence of memory and language
knowledge on the production of complex sentences. A critical implication is that a memory
capacity-constrained account of sentence processing (Carpenter et al., 1994) is likely too
simplistic on its own, and we need to factor in the influence of the specificity or
distinctness of retrieval cues (i.e., language knowledge). Converging evidence for this
viewpoint has been provided in studies of adult language production (Gennari et al., 2012;
Montag & MacDonald, 2014, 2015; Smith & Wheeldon, 2004) and comprehension (for a review,
see Van Dyke & Shankweiler, 2012). A next question for the language-based account is how
language knowledge becomes sufficiently consolidated (precise and robust) to support the
comprehension of complex sentences. A straightforward assumption from a developmental
perspective is that language representations become stronger through exposure to the
language. Thus, differences between vocabulary items, such as before and after, may be due
to differences in the frequency of their occurrence in language (Wells, Christiansen,
Race, Acheson, & MacDonald, 2009). To explore this possibility, we coded 100 randomly
selected occurrences of before and after from the CHILDES Thomas corpus (age range = 2;7.2
[years;months.days] to 4;11.20; Lieven, Salomo, & Tomasello, 2009), which is a corpus of
child-directed speech. Only 47 (of the 100) instances of before and after used these terms
as a temporal connective within a multi-clause sentence. Of these, there was not a clear
bias for either chronological order or before sentences; there were 17
before–chronological, 4 before–reverse, 10 after–chronological, and 16 after–reverse
sentences. This does not provide any evidence that children had less exposure to the more
difficult (after–reverse) structure in this study. However, the corpus analysis did show
that, of the other 53 occurrences of before and after, 47 were of after being used as a
non-connective (e.g., “Every now and then we look after the baby next door”). This finding
supports an alternative account that the apparent difficulties with after sentences arise
because after is used less consistently as a connective than before. This is consistent
with the British National Corpus (Leech et al., 2001). Longitudinal work combining corpus
and experimental methodologies could test this hypothesis further. A final thought for
future research is to what extent production accuracy might be enhanced when the sequence
of events can be informed by world knowledge. Theoretical models of mental representations
of text and discourse (e.g., Zwaan & Radvansky, 1998) suggest that it should be easier to
plan and produce sentences when the events follow a typical sequence because world
knowledge can inform the order in which the events should be mentally represented, for
example, that socks are typically put on prior to putting on shoes. World knowledge-
present sentences (e.g., “He put on the socks, before he put on the shoes”) served as
fillers to scaffold the structure of the sentence and so were not part of our experimental
design per se. Nevertheless, children’s overall performance was consistent with previous
findings in children’s comprehension of two-clause sentences containing before and after
(Blything et al., 2015); the filler world knowledge-present sentences were not performed
significantly better than the test sentences in which event order was arbitrary (e.g., “He
put on the socks, before he ate the burger”). Thus, at least for these very simple two-
clause sentences, world knowledge does not appear to play a significant role in language
production. For more complex language, such as longer texts that require greater
processing resources to integrate information across several sentences, world knowledge
may have a more powerful influence on performance (Pratt, Tunmer, & Nesdale, 1989). In
conclusion, 3- to 6-year-olds demonstrated an ability to accurately use before and after
as temporal connectives in the production of two-clause sentences, but they notably found
it difficult to produce reverse order sentences that were linked by after. We did not find
unequivocal support for either the memory capacity-constrained account or the language-
based account, although our findings lend greater support to the latter. These two
apparently contrasting accounts have a common core; they seek to explain why memory
limitations affect sentence processing. Further experimental work is needed to understand
how memory and language knowledge individually and together influence sentence planning
and production and to elucidate the commonalities and differences in their influence on
performance in language production and comprehension tasks.


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<ART>The role of social identification for achieving an open-defecation free environment: A cluster-randomized, controlled trial of Community-Led Total Sanitation in Ghana
================================================================================

Authors: Miriam Harter, Nadja Contzen, Jennifer Inauen
DOI: 10.1016/j.jenvp.2019.101360
Year: 2019
ASJC codes: 3202, 3207

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Annually, nine million people die due to environmental pollution (Landrigan et al., 2017).
Unsafe sanitation, and more specifically open defecation, is one of the main causes,
leading to fecal contamination of water bodies and the transmission of fecal bacteria
(Prüss-Ustün et al., 2014). In 2015, 892 million people still practiced open defecation,
with rates being highest in Sub-Saharan Africa (WHO & UNICEF, 2017). In Ghana, where this
study is located, 31% of the rural population practiced open defecation in 2015 (WHO &
UNICEF, 2017). A recent systematic review found that increasing access to safe sanitation
services can reduce diarrheal diseases by 16% (Wolf et al., 2014). However, a single
individual or household, by stopping open defecation, can only marginally reduce their
diarrheal risk related to a fecal polluted environment (Jung, Hum, Lou, & Cheng, 2017).
Research has shown that at least 75% of all households must stop open defecation to
achieve a hygienically safe environment that benefits all (Clasen, Boisson et al., 2014;
Jung et al., 2017; Wolf, Hunter et al., 2018). Open defecation is thus not only an
individual but a collective health hazard (Geruso & Spears, 2018; Vyas, Kov, Smets, &
Spears, 2016). This is comparable to other environmental challenges, such as greenhouse
gas emissions, which can only be confronted if most of the population show climate-
protective behavior such as reduction of individual energy consumption. Activating social
norms1 supporting pro-environmental behaviours helps people to act pro-environmentally
(Bamberg & Möser, 2007; Steg & Vlek, 2009), such as avoiding littering in public places
(Cialdini, Reno, & Kallgren, 1990), conserving household energy (Schultz, Nolan, Cialdini,
Goldstein, & Griskevicius, 2007) or using safe water sources sustainably (Contzen & Marks,
2018). Similarly, activating social norms has been used in the context of sanitation
(Dooley, Maule, & Gnilo, 2016). It is a key element of the behavior change campaign
Community-Led Total Sanitation (CLTS), which has been shown to successfully reduce open
defecation by up to 33% (Pickering, Djebbari, Lopez, Coulibaly, & Alzua, 2015;
Venkataramanan, Crocker, Karon, & Bartram, 2018). For Ghana, case studies on CLTS report
success rates of up to 26% reduction in open defecation (Crocker et al., 2016, 2017) and
scientific as well as political interest on CLTS and sanitation outcomes is steadily
increasing for the Ghanaian context (Berendes et al., 2018; Nunbogu, Harter, & Mosler,
2019). CLTS consists of a set of community-based, participatory activities, and explicitly
focuses on evoking a shift towards a new social norm opposing open defecation. The
influence of CLTS on social norms and thus the effect on latrine construction has already
been demonstrated in research (Alemu, Kumie, Medhin, & Gasana, 2018; Harter, Mosch, &
Mosler, 2018) and the consideration of social norms for the success of CLTS is gaining
more attention (Dooley et al., 2016, p. 299; Novotný, Kolomazníková, & Humňalová, 2017;
Venkataramanan et al., 2018). This is also true for the Ghanaian context (Osumanu, Kosoe,
& Ategeeng, 2019). Because of its success in stopping open defecation, CLTS is the most
widely applied sanitation campaign to date (Bongartz, Vernon, & Fox, 2016; USAID, 2018).
While randomized trials have shown that CLTS reduces open defecation compared to controls,
these effects are highly heterogeneous (Harter, Inauen, & Mosler, n.d.). This means that
despite the general success of CLTS, open defecation rates remain high in some
communities, and the threshold of 75% households using latrines is often not reached
(Crocker et al., 2016; Pickering et al., 2015; Venkataramanan et al., 2018). This
indicates that inter-community differences may moderate CLTS effectiveness. A moderator
that might be at play here is social identification, defined as an individual's
understanding to belong to a social group and to emotionally value the membership (Abrams
& Hogg, 1990; Reynolds, Subašić, & Tindall, 2015; Tajfel, 1978). Previous research has
shown that social norms particularly affect behavior in individuals strongly identified
with the social group in question (e.g. (Terry, Hogg, & White, 1999; White, Smith, Terry,
Greenslade, & McKimmie, 2009). One potential explanation for this effect is that strongly
identified people want to be accepted and approved by their group, and may thus be eager
to conform with the group's expectations, independent of whether they agree with a
specific social norm or not (Abrams & Hogg, 1990; Deutsch & Gerard, 1955). Regarding CLTS,
households may construct and use a latrine not because they are convinced of it, but
simply because they want to be accepted in the community and therefore conform to the
newly established social norm. The social identity perspective, however, proposes an
alternative explanation (Tajfel & Turner, 1979; Turner, Hogg, Oakes, Reicher, & Wetherell,
1987). Self-categorization as a group member (i.e. the definition of the self in-group
terms and in connection to other group members) includes a merging between group and
individual; group goals become personal goals and group norms become personal norms.
Accordingly, strongly identified members act in line with group norms not only because
they want to conform but more so because they perceive the norm (e.g. of constructing and
using latrines) as their personal norm, as their right way (Abrams & Hogg, 1990; Deutsch &
Gerard, 1955). We therefore expect that CLTS will be especially successful in reducing
open defecation in communities with stronger social identification prior to CLTS
implementation because people will more readily follow the newly established social norm
to stop open defecation. At the individual level, we expect that people, who feel a
stronger social identification than other community members, will be more likely to stop
open defecation. To test our assumptions, we conducted a cluster-randomized, controlled
trial, which is outlined in the following (WHO & UNICEF, 2017).

<h>METHODS</h>
-------

For this cluster-randomized, controlled trial, CLTS was implemented in four intervention
arms and its effects on open defecation reduction were tested and compared to a control
arm.2 Social identification prior to the intervention was tested as a moderator of CLTS
effectiveness.

<hs>  Procedures</hs>
  ~~~~~~~~~~

We conducted this trial in the Northern Region of Ghana in two rural districts. In both
districts we collected baseline data in February to March 2016 (for more information on
the baseline survey, refer to Harter et al. (nd)). Afterwards, Global Communities, a local
non-governmental organization, implemented CLTS in communities from both districts from
July to November 2016.3 This article presents data from the long-term follow-up that was
realized 14–16 months after implementation of CLTS, namely in February to March 2018 in
both districts. The ethical board of the University of Zurich, Switzerland and the Ethical
Review Committee of the Ghana Health Service (GHS-ERC: 05/01/2016) approved this trial.

<hs>  Study site and clusters</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

The study was realized in collaboration with Global Communities and local government
representatives. Global Communities selected the two districts in the Northern Region of
Ghana, i.e. Bole and Sawla-Tuna-Kalba, because no CLTS campaign had been implemented there
before. The local government representatives selected 132 communities within the two
districts according to two eligibility criteria: accessibility (by car or motorbike due to
practical reasons) and community size (minimum community size of 25 households). We
grouped the communities of both districts into 25 regionally separate clusters to avoid
spillover of intervention effects between close communities, and randomly allocated them
to the four intervention arms (five clusters per intervention arm) and the control arm
(five clusters).

<hs>  Study participants</hs>
  ~~~~~~~~~~~~~~~~~~

Trained data collectors selected study participants in the communities following the
random route method (Hoffmeyer-Zlotnik, 2003, pp. 205–217). Data collectors were
instructed to start from a central point of the community and interview every third
household in an assigned area of the community. If no one or no eligible person was at
home or if the household did not want to participate, data collectors selected the next
following household. Household members were eligible if aged 18 or older and stable
inhabitants of the community. If more than one household member was eligible, the
participating member was selected according to their availability. We equally considered
men and women, as both might take important decisions for latrine construction. Every
participant gave informed written consent to participate in the study. The sample size was
calculated a priori for a cluster-randomized trial with repeated measures and a
dichotomous primary outcome (Spybrook et al., 2011). Assuming an intra-cluster correlation
of ρ = 0.2, 80% power, 5% α-error probability, and 20% dropout, we estimated a required
sample size of 3,215 households nested in 132 communities (approx. 25 households in each)
to detect a medium effect of the intervention on open defecation. For a detailed
description of the sample size calculation, please refer to Harter et al. (nd). Fig. 1
displays the flow of participants through the trial.

<hs>  Interventions</hs>
  ~~~~~~~~~~~~~

Global Communities developed intervention protocols for CLTS based on the Handbook on CLTS
(Kar & Chambers, 2008). Local facilitators implemented it in three phases. First was an
informative phase, where facilitators visited the community and collected information on
the composition of the community and the baseline behavior. A date for a community meeting
was agreed and all inhabitants were invited. The community meeting, also called triggering
event, formed the second phase of CLTS. During this meeting, the facilitators motivated
community members to draw a map of their community on the ground and to indicate their
houses as well as the spots they used for open defecation on the map. Through asking
questions about possible ways of fecal-oral transmission of pathogens, the inhabitants
were expected to recognize the hygienic problems connected to open defecation. The
facilitators further identified emerging leaders during the triggering event and invited
them to serve as role models and to support others in the process of latrine construction.
A community action plan and a date on which the community wanted to be open defecation
free (ODF) was agreed. In the end of the triggering event, the facilitators explained the
first step of a latrine construction, namely digging the pit and gave further information
on the construction process, such as which material to use. No financial support was given
to community members (including emerging leaders), however, construction materials were
provided at wholesale price instead of retail prices. The third phase of CLTS included
follow-up visits in the weeks after the triggering event until the community reached the
status ODF, defined as at least 80% latrine coverage. During the follow-up visits,
facilitators addressed any arising problems and questions regarding latrine construction.
CLTS was implemented in all four intervention arms. For three of the intervention arms
additional campaign activities were developed and implemented based on the Risk,
Attitudes, Norms, Abilities and Self-regulation (RANAS) approach (for detailed description
of implemented interventions and outcomes please refer to the intervention manual4 and
Harter et al. (nd)). They included a household action plan and a public commitment for
latrine construction. The control arm did not receive any intervention during the research
phase but CLTS was implemented after the trial. In intervention communities, 72.8% (n =
1540) of the households attended the CLTS event.

<hs>  Data collection and outcome measures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A team of 33 local data collectors assessed outcome variables at baseline and both follow-
ups. The first author, together with local personnel trained the team in a 1-week training
before each of the three data collection phases. The trainings included a detailed
discussion of questionnaire items and explained the correct usage of instruments and
interview techniques. These were then rehearsed in role-plays. The questionnaire was
translated into seven local languages as part of the data collector training of the
baseline data collection, and pretested in two days and 66 interviews prior to each data
collection in the field. Every interview was supervised (by research managers, interns,
master students and local field supervisors), and lasted 50 min on average. Interviews
included self-reported behavioral measurements, social identification, and further items
on psychosocial determinants of behavior (not relevant to the present paper, for
information refer to Harter et al. (nd)). The self-reported open defecation rates at long-
term follow-up were assessed with items based on the Safe San Index (Jenkins, Freeman, &
Routray, 2014). Six items assessed the self-reported open defecation rate of each
individual during the last week. The original Safe San Index includes information about
all household members, whereas for this article only individual self-reported behavior at
long-term follow-up was considered. Three items asked for the respondent's open defecation
frequency in the mornings, middays and evenings/nights of the last week and three items
asked the same for latrine use (items displayed in Supporting Information in SI Table 1).
The Safe San Index represents the proportion of safely managed feces relative to total
defecation instances, resulting in a range of 0–1. However, the data revealed that
individuals either exclusively practiced open defecation or used a latrine. This resulted
in a binary outcome variable with 0 = no open defecation and 1 = open defecation.
Aggregated to community level it accounts for a communities' average open defecation rate,
the proportion of people within a community who reported to practice open defecation
(0–100%). Social identification at baseline was measured as identification with the
community on three dimensions: in-group ties, in-group affect and centrality, following
items proposed by Cameron (2004). The selection of two items per dimension for this
research was done in accordance with local partners, based on cultural and language
considerations. Items were framed as statements with a five-point Likert-type scale for
agreement. We used a visual scale with five black dots (in ascending order relative to
their size) to help respondents choose one of the answer options. The data collector read
out every answer option to the respondent and pointed it out on the visual scale. To test
the item factor structure, we conducted an exploratory factor analysis with Principal
Components Analysis and Varimax rotation with Kaiser Normalization (Field, 2009)
(correlations displayed in SI Table 2 in supporting information). The factor analysis was
not able to replicate the dimensions proposed by Cameron (2004), but resulted in one
factor for social identification with the items of the two dimensions in-group affect and
centrality loading on the factor. Whereas the items of the dimension social ties did not
load on it and were therefore excluded. The remaining four items were aggregated to one
scale (M = 4.29, SD = 0.30, Cronbach's α = 0.64). Table 1 displays the four items of the
scale and according descriptive measures, correlations and intra-class correlation.
Aggregated at the community level, it resembles a community's average social
identification.

<hs>  Analyses</hs>
  ~~~~~~~~

To test the moderating influence of social identification on the effect of CLTS on open
defecation, we fitted a Generalized Estimating Equation (GEE) (see Zeger and Liang (1986,
pp. 121–130); Zeger, Liang, and Albert (1988)) using IBM SPSS Statistics for Windows,
version 24 (IBM Corp., Armonk, N.Y., USA). The model was set up using binomial
distribution with logit link (Homish, Edwards, Eiden, & Leonard, 2010), because the
outcome was binary. We used an exchangeable correlation structure, which assumes constant
intra-cluster dependency (used for clustered data not assessed in a time-series, see
Ballinger (2004)). This model accounted for the nested structure of our data with
households nested in communities and further allowed the inclusion of a binary outcome (0
= no open defecation vs. 1 = open defecation). The CLTS intervention (0 = control arm; 1 =
intervention arms) was entered together with the community-averaged social identification
(grand-mean centered), and the individual's deviation from their community's average
social identification (group-mean centering). Thereby, we were able to distinguish between
community-level and individual-level effects, which may differ (Hamaker, 2012). We further
added the interaction terms of the intervention with social identification at both,
individual and community level, to test whether social identification at baseline
moderated the intervention effect on reported open defecation at follow-up. As effect size
measures, we calculated odds ratios (ORs) with asymptotic Wald 95% confidence intervals
(CIs). ORs can be interpreted as increased (OR>1) or decreased (OR<1) odds of practicing
open defecation for a unit increase in the predictor.

<hs>  Sample description</hs>
  ~~~~~~~~~~~~~~~~~~

The respondents were on average 44.5 years old (SD = 16.1). Slightly fewer than half were
female (42%) and 21% were able to read and write. The households consisted of eight
members on average (SD = 5). In terms of religion, 26% named Islam as their religion, 49%
Christianity, 19% traditional religions, and 5% mentioned to be atheists. Most of the
sample reported to be farmers (80.4%) with an average monthly household income of 202
Ghanaian New Cedi (SD = 380), equivalent to 42 USD. The households of the sample therefore
lay on average below the poverty line proposed by the World Bank of 57 USD per individual
per month (Atkinson, 2017).

<hs>  Randomization check and dropout analysis</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 shows baseline characteristics for intervention and control arms. Chi-Square tests
and variance analysis revealed that the groups significantly differed on all
characteristics except for age, household size and number of dropouts, which were equally
distributed. At baseline, 89.9% of the control and 97.2% of the intervention arm reported
to practice open defecation. The main analyses reported in this paper were rerun and
characteristics were included that had shown significant differences between intervention
and control group at baseline. Even though the effect sizes were small (Cohen, 1992;
Ferguson, 2009; Trusty, Thompson, & Petrocelli, 2004), those characteristics were included
in sensitivity analyses as they were considered to be potential confounding variables.
Furthermore, we compared respondents who participated in both panel surveys (n = 2,607) to
respondents only participating in the baseline survey (dropouts, n = 609, 18.9%) on the
same characteristics. Chi-square tests and variance analyses showed that the study
dropouts were significantly less socially identified with their community, less likely to
be farmers, had a higher probability for literacy, were significantly younger and had a
higher income compared to analyzed participants. Open defecation rates were not
significantly different between study dropouts and participants remaining in the sample
(see SI Table 3 in Supporting Information).

<hs>  Intervention effects on open defecation and the influence of social identification</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the CLTS intervention arms, 46.4% (SD = 49.9%) of the individuals reported to practice
open defecation at follow-up, compared to 88.4% (SD = 32.0%) in the control arm. As
indicated by the GEE model results (see Table 3), the OR for the intervention group
indicates that intervention participants were 11 times less likely to practice open
defecation at follow-up than controls (Β[SE] = −2.42 [0.33], OR = 0.09, p < 0.001). Fig. 2
shows the community-averaged open defecation rate in control and intervention arms
moderated by community's average social identification. In line with our hypothesis, CLTS
intervention communities with stronger community-averaged social identification reported
less open defecation at follow-up than those with lower community-averaged social
identification (Β[SE] = −11.70 [4.15], p = 0.005). The control arm showed opposite
effects: communities with stronger community-averaged social identification reported
higher open defecation rates at follow-up than those with lower community-averaged social
identification (Β[SE] = 7.06 [2.28], p = 0.002). In both, the control and intervention
arms, the effects of individuals' social identification pointed in the same direction as
the community-averaged social identification, but were not significant (control arm: Β[SE]
= 0.25 [0.24], p = 0.305; intervention arm: Β[SE] = −0.65 [1.05], p = 0.534). Sensitivity
analyses revealed that including the baseline characteristics, and adjusting for baseline
behavior, did not substantively change the findings. Only age and literacy had significant
but small reducing effects on open defecation (age: Β[SE] = −0.01 [<0.01], p = 0.002;
literacy: Β[SE] = −0.27 [0.10], p = 0.008).

<h>DISCUSSION</h>
----------

This study corroborated previous findings that CLTS is an effective intervention to reduce
open defecation. In our sample, at the long-term follow-up, 53.6% of individuals in the
intervention arms did not defecate in the open anymore. While this rate is still behind
the threshold of 75% of all community members that would need to stop open defecation to
reach an incremental health benefit at community level (Jung et al., 2017; Wolf et al.,
2018), it is comparable to most randomized trials of CLTS. A recent review on CLTS reports
that the majority of interventions achieve around 50–80% rates of stopping open defecation
(USAID, 2018). That the reported rate in our study is at the lower end, can partly be
explained by the short time elapsed between intervention and follow-up survey. At the time
of the survey, many latrines (61.6%) were still under construction and therefore still not
in use. In the intervention arm, the figure of 46.4% of the respondents that reported to
practice open defecation, might likely decrease as soon as the construction process of the
remaining latrines is completed. We expect this, because in our sample the clear majority
of households that owned a completed latrine also used it (93.6%). This is surprising when
compared to previous research on latrine ownership and use, for example from India, where
it was found that only 47% of the owned latrines were actually used (Barnard et al.,
2013). More importantly, this study showed for the first time that social identification
within communities moderates the effectiveness of CLTS on open defecation. Specifically,
our hypothesis regarding the influence of social identification on the intervention
effects was supported: CLTS was more successful in communities with stronger social
identification prior to the intervention. In communities with stronger community-averaged
social identification, 38.7% of respondents reported to practice open defecation, compared
to 54.7% in communities with lower average social identification. Our findings extend
previous findings of a randomized trial on CLTS in Indonesia on the importance of
communities’ pre-existing social conditions for intervention success (Cameron, Olivia, &
Shah, 2015). The researchers were able to show in a randomized trial, that communities
with higher initial social capital, i.e., higher trust and cohesion, were more likely to
have higher latrine coverages. We suppose that the reported moderating effect of social
identification on CLTS effectiveness work through an increase in new social norms that
oppose open defecation. In communities in which individuals strongly identify with their
community, individuals wish to conform to the new norm, which will lead to better CLTS
outcomes (e.g. Terry et al. (1999) and White et al. (2009)). Alternatively, and based on
social identity theory, strongly identified individuals might not only conform to the
social norms, but internalize them as their own goal and their personal norms (Abrams &
Hogg, 1990; Deutsch & Gerard, 1955). Future research can test these assumed mechanisms of
CLTS and disentangle whether CLTS truly evokes a shift in social norms and whether these
translate, moderated by social identification, into personal norms. Interestingly, our
data showed opposite effects in control communities: higher open defecation rates were
reported in communities with stronger compared to communities with weaker average social
identification. This might be because in communities without CLTS intervention the
prevailing social norms were supporting open defecation, as no impulse of change had
occurred. This finding supports social identity theory; communities with stronger
community-averaged social identification follow, or better said incorporate, the
prevailing social norms, whether the social norms suggest stopping open defecation – as in
intervention communities – or the opposite – as in control communities (Abrams & Hogg,
1990; Cialdini et al., 1990). Schultz et al. (2007) described this effect of salient norms
that lead to an undesired behavior as “the destructive potential of social norms” (p.431).
A departure from prevailing social norms, such as stopping open defecation when open
defecation is what the rest of the community members are doing, may only be possible for
community contexts where social identification is weak, i.e., where community members do
not define themselves through their community and are thus less inclined to follow the
prevailing social norms (Abrams & Hogg, 1990; Deutsch & Gerard, 1955). Finally, our
results did not suggest any additional effects of social identification at the individual
level, over and above the community-level effects. It seems that the moderating effect of
social identification is a truly community-based phenomenon. To sum up, our results
highlight the importance of social identification especially for collective environmental
challenges, such as open defecation. This is in line with the increasing interest of the
CLTS community to consider the social context in CLTS planning and implementation (Dooley
et al., 2016, p. 299; Novotný et al., 2017; USAID, 2018). For the implementation practice,
this means that communities with strong social identification provide a fertile ground for
CLTS implementation. To improve CLTS planning, we therefore suggest the assessment of
social identification in a first step. If social identification is found to be weak,
activities should be carried out to foster social identification prior to CLTS
implementation, as has been recommended for the field of collective action (Van Zomeren,
Postmes, & Spears, 2008). Such activities might include enabling interaction between
community members (Jans, Leach, Garcia, & Postmes, 2015) or directing attention to
neighboring communities that have already eliminated open defecation, for example forming
a competition-like situation and pointing out the differences to an out-group (Jans,
Bouman, & Fielding, 2018; Tajfel & Forgas, 2000, pp. 49–63). In cases where social
identification cannot be strengthened before a CLTS implementation, by-laws or sanctions
for people not following the norms might be enforced, which is proposed by the CLTS
Handbook (Kar & Chambers, 2008) and in social psychology literature to solve social
dilemma situations (e.g. (De Cremer, Hoogervorst, & Desmet, 2012)). The control group
findings imply that communities with strong social identification are potentially at risk
of increasing or reinforcing open defecation practices. These communities should therefore
be selected with high priority for sanitation interventions to avoid such tendencies, and
leverage promising responses to interventions due to strong identification.

<hs>  Strengths and limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

To the best of our knowledge, this study is the first that investigated the influence of
social identification on the effect of CLTS on open defecation. It was fully powered with
a sample of 2,606 households for the longtime follow-up survey and 3,216 households in the
baseline. With 132 communities, it allowed analysis at the community level, and the
investigation of the deviation of individuals from community means. CLTS was implemented
under real conditions in rural Ghana in a variety of local contexts, such as different
community sizes and ethnical compositions. This allows assuming high external validity.
The study, however, has the following limitations. The first relates to the causal
relationship of social identification moderating CLTS intervention effects. Because we did
not experimentally manipulate social identification, the found moderating effect could be
attributable to other influencing factors, for example community size or heterogeneity
within communities. Future research should manipulate the strength of social
identification to provide further evidence for the presented moderating effects in this
article. Open defecation was assessed through self-reports. However, strengthening the
validity of the self-report measure, the use of latrines was verified by observation of
enumerators,5 which correlated strongly with the self-reported behavior (r2 = 0.72, p <
0.001). The scope of this study did not allow for assessment of open defecation rates more
than one year, including participants that might have reverted to open defecation. Long-
term change should be included in future research. Social identification was measured
using six items only and for analysis, only four items were included. However, the scale
showed relatively low reliability (Cronbach's α = 0.64). Furthermore, the six items used
for the social identification scale applied in this article were not able to replicate the
three dimensions of social identification postulated by Cameron (2004). The reason for
this may be that only two items per dimension were included to keep the questionnaire as
brief as possible to minimize participant burden. Future studies should use more items to
allow for a more detailed consideration of social identification dimensions.

<h>CONCLUSION</h>
----------

This study reports the success of CLTS on reducing open defecation rates and highlights
the relevance of including social conditions into planning of sanitation campaigns, such
as CLTS. Specifically, the consideration of communities’ social identification is crucial
for the success of CLTS on reducing open defecation, as it might be able to intensify the
effects of the intervention. We therefore recommend to assess the level of social
identification within target communities and plan CLTS interventions accordingly, meaning
to strengthen, if needed, the social identification among community members before a
sanitation intervention. Further, this is the first time that the concept of social
identification was studied in environmental sanitation and points to the potential
influence of social identification in other water and sanitation related behaviors in low-
and middle-income countries.


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<ART>The role of verbal labels on flexible memory retrieval at 12-months of age
==========================================================================

Authors: Gemma Taylor, Hao Liu, Jane S. Herbert
DOI: 10.1016/j.infbeh.2016.08.002
Year: 2016  |  Pages: 11-17
ASJC codes: 3204
Keywords: Imitation, Infant, Memory development, Memory flexibility

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The provision of verbal labels enhances 12-month-old infants’ memory flexibility across a form change in a puppet imitation task (Herbert, 2011), although the mechanisms for this effect remain unclear. Here we investigate whether verbal labels can scaffold flexible memory retrieval when task difficulty increases and consider the mechanism responsible for the effect of language cues on early memory flexibility. Twelve-month-old infants were provided with English, Chinese, or empty language cues during a difficult imitation task, a combined change in the puppet's colour and form at the test (Hayne et al., 1997). Imitation performance by infants in the English language condition only exceeded baseline performance after the 10-min delay. Thus, verbal labels facilitated flexible memory retrieval on this task. There were no correlations between infants’ language comprehension and imitation performance. Thus, it is likely that verbal labels facilitate both attention and categorisation during encoding and retrieval.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The ability to flexibly retrieve our memories across a range of situations is an important
feature of the declarative memory system. Memory flexibility, or the ability to use pre-
existing stores of knowledge to solve new problems, enables us to avoid costly or time
consuming re-learning and to benefit from our past experiences. Across the first two years
of life, studies using the deferred imitation procedure have demonstrated that the ability
to flexibly retrieve memories across changes in the social and physical contexts, or
changes in the target stimulus develops gradually (e.g., Hayne, Boniface, & Barr, 2000;
Hayne, Barr, & Herbert, 2003; Hayne, MacDonald, & Barr, 1997; Herbert & Hayne, 2000a;
Herbert, Gross, & Hayne, 2006; Learmonth, Lamberth, & Rovee-Collier, 2004; Learmonth,
Lamberth, & Rovee-Collier, 2005). For example, within the puppet imitation task, 12-month
old infants can reproduce the target actions shown on a puppet that differs in colour
(Hayne et al., 1997) or form (Jones & Herbert, 2008) from the one present during the
original demonstration after a 10 min delay, but not with a puppet that differs in both
colour and form, or after a 24 h delay. In contrast, 18-month old infants can reproduce
the target actions with a puppet that differs in both colour and form after a 24-h delay
but not when the puppets are highly dissimilar (e.g., black/white cow, yellow/orange duck;
Hayne et al., 1997). Thus, early memory flexibility appears to be determined in part, by
the degree of changes to the central stimulus between learning and retrieval, and the
length of the retention interval (also see Herbert & Hayne, 2000a). Language cues have
recently been identified as a powerful means by which to enhance flexible memory retrieval
at young ages. Being able to spontaneously self-generate a label for a novel stimulus or a
hiding location facilitates 2-year-old children’s ability to transfer knowledge to a new
situation (Miller & Marcovitch, 2011; Zimmermann et al., 2015), while memory flexibility
at younger ages benefits from experimenter-generated labels (Herbert & Hayne, 2000;
Herbert, 2011). For example, in Herbert (2011), 12- and 15-month old infants were shown
the target actions with the puppet task accompanied by verbal labels for the object and
actions (e.g., “Look, a puppet. Off. Shake. On”) or no label during the demonstration. At
the test 10 min later, the puppet was labelled again for infants in the verbal label
condition only. Infants in both the label and no label conditions reproduced significantly
more target actions with a puppet that differed in form (e.g., pale grey mouse at
demonstration, pale grey rabbit at test) than baseline performance by infants in the
control condition. Thus, infants were already showing some ability to generalise across a
change in stimulus form after the short delay. Importantly, however, infants in the label
condition reproduced significantly more target actions than infants in the no label
condition. In other words, verbal labels enhanced performance above spontaneous flexible
memory retrieval. Whether the same effect would be observed when task difficulty increases
remains to be determined. Perhaps unsurprisingly, verbal labels do not facilitate infant
abilities in all situations, such as when 15-month-olds are asked to transfer knowledge
across a complex 2D to 3D action imitation task (Zack, Gerhardstein, Meltzoff, & Barr,
2013). However a unique feature of the puppet task is that task difficulty can be
progressively increased by altering the colour, form, or colour and form of the puppet,
providing an opportunity to examine the limits of the facilitative effects of language on
infant memory abilities. In this study we consider whether verbal labels can facilitate
infants’ memory flexibility across a complex change, altering both the form and colour of
the stimulus present at retrieval. Although the body of research showing the facilitative
effects of language cues on memory flexibility continues to grow, the mechanism for this
effect remains unclear. One possibility is that verbal labels may facilitate flexible
memory retrieval across changes in the target object by potentially facilitating
categorisation of the target and test objects (for similar argument, see Jones & Herbert,
2009). Infant language comprehension begins around 8- to 10-months (Fenson et al., 1994)
at which point verbal labels can influence categorisation (Westermann & Mareschal, 2014).
Verbal labels can affect perceived object similarity and can help infants categorise
perceptually dissimilar exemplars of objects into a single category (Plunkett, Hu, &
Cohen, 2008; Waxman & Booth, 2003; Waxman & Braun, 2005). For example, Plunkett et al.
(2008) presented 10-month old infants with a series of objects that differed on a number
of features where values on one dimension could combine with the full range of values on
other dimensions. Infants categorised the objects into two categories (long neck and short
neck) shown by a visual preference for the object that averaged across all dimensions. In
contrast, when given a single novel label (e.g., “dax”) for the objects during the
familiarisation phase, 10-month old infants categorised objects into a single category
(Plunkett et al., 2008). Thus, in the imitation task, a label presented at demonstration
and test may help infants form a single category for the demonstration and test puppets
and facilitate memory retrieval across the stimulus change. Alternatively, verbal labels
may function to direct infant’s attention to the relevant aspects of the learning task.
Indeed, Taylor and Herbert (2014) found that 6-, 9- and 12-month old infants’ attentional
patterns during the puppet demonstration session were related to their ability to
reproduce the target actions at test. Using an eye-tracker, Taylor and Herbert (2014)
showed that infants distribute their attention more widely than adults when viewing the
puppet task. Critically, greater attention to the person and less attention to the
background were related to learning outcome on the task (Taylor & Herbert, 2014).
Furthermore, studies have shown that 9- to 12-month old infants increase attention to
objects that have been labelled compared to objects that have not (Balaban & Waxman, 1997;
Baldwin & Markman, 1989). Thus, verbal labels may serve as an attention grabber during
learning and at test. The purpose of the present experiment was to determine whether
verbal labels facilitate flexible memory retrieval via an attentional or categorisation
mechanism. Twelve-month old infants were presented with a puppet that differed in both
colour and form during the imitation test session following a live demonstration 10 min
earlier. At this age, infants typically fail to reproduce the target actions when
presented with a colour and form change puppet (Hayne et al., 1997). Some infants received
empty language cues (no verbal label) whilst others received language cues (verbal label
for object and actions) in either English or Chinese. The English language labels were
used to determine whether language could scaffold learning and push infants into
succeeding on the difficult flexible retrieval task. By 12-months of age infants can no
longer discriminate between foreign-language phonetics (Best, McRoberts, LaFleur, &
Silver-Isenstadt, 1995; Kuhl, Tsao, & Liu, 2003; Maye, Werker, & Gerken, 2002; Narayan,
Werker, & Beddor, 2010; Werker & Tees, 1984) and mouth sounds alone are not sufficient to
produce categorisation (Fulkerson & Haaf, 2003). Thus, the Chinese language labels were
used to determine whether verbal information merely directs infant attention to the
relevant aspects of the task. We hypothesised that infants who receive empty language cues
will fail to reproduce the target actions with the form and colour change puppet,
consistent with prior work (Hayne et al., 1997). In contrast, we predicted that infants
who receive English language cues would reproduce the target actions with the form and
colour change puppet, consistent with both an attentional and categorisation mechanism. If
infants in the Chinese language group do not perform above baseline then the
categorisation mechanism will be supported. In contrast, if infants in the Chinese
language condition do perform above baseline then the attentional mechanism will be
supported. If the effectiveness of verbal labels can be explained by categorisation, then
infants’ language comprehension should be related to their subsequent imitation when given
English language cues (e.g., Waxman & Booth, 2003).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 52 12-month old infants (26 males, 26 females) tested within 10 days of
their birthday. None of the infants were born more than four weeks premature or
experienced birthing difficulties. An additional 15 infants were tested but excluded due
to infant fussiness (n = 6), failure to touch the puppet during the test (n = 2),
experimenter error (n = 4) and previous exposure to a foreign language (n = 3).

<hs>  Measures</hs>
  ~~~~~~~~

The Oxford Communicative Development Index (Oxford CDI; Hamilton, Plunkett, & Schafer,
2000) was used to measure infant vocabulary comprehension and production. Comprehension
scores around 15% and production scores around 0% are considered typical for 12-month old
British infants (Hamilton et al., 2000).

<hs>  Stimuli</hs>
  ~~~~~~~

Four hand puppets were used in the present study; two resembling a mouse and two
resembling a rabbit, both made in either pale grey or pastel pink (see Hayne et al.,
1997). The puppets were 30 cm in height and had a removable mitten 8 cm (w) × 9 cm (h) in
matching pale grey or pastel pink on the puppet’s right arm. A large jingle bell was
attached to the inside of the mitten during the demonstration for the experimental
conditions, and attached to the back of the puppet for the control condition (see Hayne et
al., 1997).

<hs>  Procedure</hs>
  ~~~~~~~~~

All infants were tested individually in the Developmental lab at the University of
Sheffield. Upon arrival, the purpose of the study was explained to caregivers and informed
consent was obtained. Infants were randomly assigned to one of four conditions: an English
language condition (n = 14), a Chinese language condition (n = 12), an empty language
condition (n = 12) and a control condition (n = 14). Half of the infants in each condition
were female and half were male. Following consent, all infants engaged in a warm-up
session in the waiting room with the experimenter until a smile was elicited. A native
Chinese speaker conducted the Chinese language condition and a native English speaker
conducted the English language and empty language conditions, both experimenters conducted
the control condition. Infants in the Chinese language condition were exposed to three
short Chinese phrases during the warm-up session (see Table 1); the same phrases were also
given in English to the infants in the English language, empty language and control
conditions. The purpose of exposure to Chinese phrases prior to the experiment was to
build up the infant’s familiarity to hearing the experimenter speak in a foreign language.
During the warm up session, the parent filled out the Oxford CDI. Parents in the Chinese
language condition also answered two questions about the infant’s language exposure (Has
your baby ever been exposed to Chinese language before e.g., neighbours, friends? Has your
baby ever been exposed to any other languages except English?). After the warm up session,
the experimenter then escorted the caregiver and infant to a separate testing room.

        <hss>Demonstration Session</hss>

        Infants were seated on their caregiver’s lap, with the experimenter kneeling on
        the floor facing the infant. During a warm up phase, the experimenter interacted
        with the infant until he or she appeared comfortable. Out of view of the infant,
        the experimenter placed the demonstration puppet on her hand. The puppet was then
        placed in front of the infant, out of reaching distance. For infants in the
        English language, Chinese language and empty language conditions, the experimenter
        performed three actions on the puppet: 1) taking the puppet’s mitten off, 2)
        deliberately shaking the mitten three times in succession ringing the jingle bell
        attached inside, and 3) replacing the mitten back on the puppet. This
        demonstration was accompanied by English language, Chinese language or empty
        language spoken by the experimenter (see Table 2). Verbal labels in the empty
        language condition were limited to “Look” and filler phrases in between each
        repetition in order to limit attention-grabbing cues. This enabled us to consider
        the role of verbal labels in directing attention during the task in the Chinese
        language and English language conditions. The actions were repeated three times in
        succession before the puppet was removed from view. For infants in the control
        condition, the experimenter shook the puppet side to side three times and repeated
        the action three times in succession accompanied by empty language cues. The
        purpose of the control group was to measure infants’ spontaneous production of the
        target actions. For all conditions, the experimenter said “Shall we do that again”
        or “Are you watching” in between each repetition. The colour and form of the
        demonstration puppet was counterbalanced across infants.

        <hss>Test Session</hss>

        The test session was conducted approximately 10 min after the demonstration.
        During the 10-min delay, the infant, caregiver, and experimenter interacted in the
        waiting room with unrelated toys. Each infant then returned with their caregiver
        to the experimental room and was presented with the form and colour change puppet
        during the test session (e.g., pastel pink rabbit during the demonstration
        session, pale grey mouse during the test session). The puppets were
        counterbalanced across condition. The experimenter placed the test puppet on her
        hand, out of view of the infant. The experimenter then revealed the puppet, which
        she either labelled (English language, Chinese language) or simply said, “Look”
        (empty language and control), before placing the puppet within reaching distance
        of the infant. Infants were then given 90 s to produce the target actions, timed
        from their first touch. The entire session was videotaped for later analysis.

<h>RESULTS</h>
-------

The videotaped test sessions were coded for the presence or absence of the target actions
and infants were given an imitation score based on the number of target actions produced
(range 0–3). Approximately 23% (n = 12) of the videos were double coded by an independent
experimenter. Inter-observer reliability analysis was 83% (kappa = 0.72). Preliminary
analyses revealed no effect of gender on imitation scores so the data was collapsed across
gender for subsequent analyses. To determine whether there were differences in infants’
imitation scores as a function of condition, a Kruskal-Wallis test was conducted due to
differences in sample size and variance across condition and the control, empty language
and Chinese language conditions violating the normality assumption. Overall, there was a
significant effect of condition on infant imitation scores, H (3) = 12.93, p = 0.002 (see
Fig. 1). In deferred imitation studies, memory is inferred if the imitation score in a
demonstration condition exceeds the spontaneous production of target actions produced by
infants in the baseline control condition (see Hayne, 2004; Meltzoff, 1985). Given that
the imitation scores were not normally distributed, Mann-Whitney tests were used to
compare each experimental group (English language, empty language, Chinese language) to
the spontaneous production of the target actions in the control group. The English
language group reproduced the target actions significantly more than the control group (U
= 52.00, p = 0.035, r = −0.43). In contrast, the empty language (U = 60.50, p = 0.231, r =
−0.32) and Chinese language (U = 79.00, p = 0.820, r = −0.06) groups did not differ
significantly from the control group. Thus, only infants in the English language group
reproduced the target actions above spontaneous production by infants in the control
group. For the CDIs, data was missing for two infants whose parents did not complete and
return the questionnaire. Children were given total scores for the number of words that
the child comprehends and the number of words that the child produces. These scores were
calculated by summing the number of items that the caregiver had marked as “understands”
or “understands and says” for the comprehension score and the number of items that the
caregiver had marked as “understands and says” for the production score. Children’s
comprehension and production scores were expressed as a percentiles according using the
norming data for the Oxford CDI (Hamilton et al., 2000) for analysis. Preliminary analyses
revealed a significant effect of gender on vocabulary comprehension scores t (48) = 2.15,
p = 0.037 with girls (m = 63.11, sd = 32.12) scoring more highly than boys (m = 46.08, sd
= 23.13). There was no significant effect of gender on vocabulary production t (48) =
1.49, p = 0.144 (girls m = 56.00, sd = 32.87; boys m = 44.02, sd = 23.30). Given that
there was an even gender split in each condition, the data was collapsed across gender for
subsequent analyses. To determine whether vocabulary comprehension or production differed
between infants in each condition, Kruskal-Wallis tests were conducted. Overall, there was
no significant difference in vocabulary comprehension, H (3) = 2.431, p = 0.488 or
vocabulary production, H (3) = 0.485, p = 0.922 between infants in each experimental
condition (see Table 3). In addition, Kendall’s tau analyses revealed non-significant
correlations between vocabulary comprehension or production scores and imitation scores
for any condition.

<h>DISCUSSION</h>
----------

The present experiment replicates and extends prior work (Hayne et al., 1997) in
demonstrating that 12-month old infants fail to retrieve their memories if the stimulus
presented during the test session differs in both colour and form from the one present
during encoding, even after a short delay. Moreover, consistent with our hypothesis, the
addition of experimenter provided language cues did facilitate flexible memory retrieval
across the form and colour change stimulus in the present study. While there are limits on
their effectiveness (see Zack et al., 2013), verbal cues can scaffold learning and push
infants into succeeding on a difficult flexible retrieval task. To start to tease apart
the attentional and categorisation mechanisms by which verbal cues facilitate flexible
memory retrieval, it is particularly informative to consider the results from the Chinese
language condition. The addition of Chinese language labels during the demonstration and
test did not facilitate infants’ flexible memory retrieval above the spontaneous
production of the target actions by the control group. Given that by 12-months of age
infants can no longer discriminate between foreign-language phonetics (Best et al., 1995;
Kuhl et al., 2003; Maye et al., 2002; Narayan et al., 2010; Werker & Tees, 1984), our
monolingual English infants will not have been able to comprehend the Chinese verbal
labels. Furthermore, infants fail to categorise following non-labelling mouth sounds
(Fulkerson & Haaf, 2003). Instead, the Chinese verbal labels should serve as an attention-
grabber. Thus, the results from Chinese language condition suggest that an attentional
mechanism alone is unlikely to explain how verbal labels influence memory retrieval. There
was no association between vocabulary comprehension or production at 12-months of age on
imitation performance by infants in any condition. It is important to note that the Oxford
CDI does not measure children’s comprehension of the words “puppet” or “shake” thus we do
not have a validated record of whether infants understood the specific words used in our
narration. Anecdotally, after the task, parents frequently stated they did not use these
types of words with their infants. However, regardless of whether our infants benefited
from the specific words used in the narration, it remains a possibility that
categorisation may be the mechanism by which verbal cues facilitate flexible memory
retrieval. A considerable body of research has shown that vocabulary comprehension is not
essential for categorisation. For example, even before an age at which they can parse
individual words (Jusczyk & Aslin, 1995), 3- and 4-month old infants categorise pictures
of animals following verbal labels but not tones (Ferry, Hespos, & Waxman, 2010). The null
finding for the Chinese language group appear to rule out phonetic discrimination as a
potential mechanism for categorisation but not comprehension as a mechanism for
categorisation. However, it is likely that verbal labels will facilitate both attention
and categorisation during encoding and retrieval. Using eye tracking to monitor infants
visual attention during an imitation demonstration session when verbal labels are given
will help determine whether attention is one mechanism by which verbal labels can enhance
flexible memory retrieval (also see Taylor & Herbert, 2014). In conclusion, the present
results, combined with those of Herbert (2011), suggest that verbal labels can facilitate
infants’ emerging memory flexibility, even as the task becomes progressively more
difficult. The next steps in this research will be to determine the relationship between
memory flexibility, language cues, and forgetting. Infants’ ability to flexibly retrieve
their memories is influenced by the length of the retention interval between the
demonstration and test sessions (e.g., Hayne et al., 1997; Herbert & Hayne, 2000a, 2000b).
Moreover, prior work has demonstrated that verbal labels can facilitate the length of time
over which a memory can be retained when the test stimuli are the same as those presented
during the demonstration (Hayne & Herbert, 2004). Thus, it remains to be determined
whether verbal labels can scaffold flexible memory retrieval across longer delays, or
whether longer retention intervals are also a task demand too far for the early verbal
infant.


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<ART>The six blind men and the elephant: Are episodic memory tasks tests of different things or different tests of the same thing?
================================================================================

Authors: Lucy G. Cheke, Nicola S. Clayton
DOI: 10.1016/j.jecp.2015.03.006
Year: 2015  |  Pages: 164-171
ASJC codes: 3204, 3205
Keywords: Cued recall, Episodic memory, Free recall, Source memory, Unexpected question, What-Where-When test

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

The development of episodic memory in children has been of interest to researchers for more than a century. Current behavioral tests that have been developed to assess episodic memory differ substantially in their surface features. Therefore, it is possible that these tests are assessing different memory processes. In this study, 106 children aged 3 to 6. years were tested on four putative tests of episodic memory. Covariation in performance was investigated in order to address two conflicting hypotheses: (a) that the high level of difference between the tests will result in little covariation in performance despite their being designed to assess the same ability and (b) that the conceptual similarity of these tasks will lead to high levels of covariation despite surface differences. The results indicated a gradual improvement with age on all tests. Performances on many of the tests were related, but not after controlling for age. A principal component analysis found that a single principal component was able to satisfactorily fit the observed data. This principal component produced a marginally stronger correlation with age than any test alone. As such, it might be concluded that different tests of episodic memory are too different to be used in parallel. Nevertheless, if used together, these tests may offer a robust assessment of episodic memory as a complex multifaceted process.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Six blind men wanted to discover for themselves the nature of an elephant. Each one went
to the elephant and touched it. The first touched the elephant’s leg and said “it is like
a tree,” the second touched the elephant’s tail and said “it is like a rope,” the third
touched the elephant’s trunk and said “it is like a snake,” the fourth touched the
elephant’s tusk and said “it is like a spear,” the fifth touched the elephant’s side and
said “it is like a wall,” and the sixth touched the elephant’s ear and said “it is like a
fan.” Characterizing healthy episodic memory development in young children is important
because it allows problems with memory to be identified and informs appropriate
educational strategies. Although the development of memory in children has been studied
for nearly a century, to date there is considerable variation in the methodologies used to
do so. The fable of the six blind men and the elephant serves to warn us that a single
perspective on an intangible phenomenon may provide truth but can also be misleading. As
psychologists, we can never directly assess psychological processes but can only measure
performance on particular tests that are thought to rely on those processes. Different
tests of episodic memory stem from different philosophical, theoretical, and empirical
origins, and they differ substantially in the outward behavior they assess. Such
eclecticism can be both a strength and a weakness. A range of testing methodologies can
allow triangulation on a single common feature. This may allow production of a battery of
measures that provides a more complete picture of a psychological process. However, a
range of tests that vary largely in their methodologies may merely muddy any possible
interpretation. In this study, the same sample of 3- to 6-year-old children was tested on
a range of episodic memory tests. These tests are all very different in their surface
features, so it might be predicted that they would produce different results.
Nevertheless, they all putatively assess the same underlying cognitive ability, and as
such it might instead be predicted that there should be a demonstrable association among
them, reflecting this latent variable. The tests we chose to investigate are some of those
that have been claimed to tap episodic memory or are candidates for such a claim.
Therefore, we should expect to see a similar developmental change in all of the tests
(Wellman, Cross, & Watson, 2001). In the following section, we briefly review the
literature concerning these tasks.

<hs>  Free and cued recall</hs>
  ~~~~~~~~~~~~~~~~~~~~

Free and cued recall paradigms involve learning a series of items (words or pictures) and
then later being asked to recall them, either with (cued) or without (free) external cues
such as category words to aid recollection. Freely recalled items are more likely to be
reported as “remembered” rather than as “known” compared with cued items (Tulving, 1985)
and, therefore, are considered to be more reliant on episodic memory. Both free recall and
cued recall improve between 3 and 8 years of age, with children of all ages reliably
finding cued recall to be the easier of the two (Naito, 2003; Perner & Ruffman, 1995;
Sluzenski, Newcombe, & Ottinger, 2004).

<hs>  What–Where–When</hs>
  ~~~~~~~~~~~~~~~

The What–Where–When test requires participants to remember the time and location of a
particular event. Clayton and Dickinson (1998) argued that this requires an integrated
spatiotemporal representation of the event, which corresponds to Tulving and colleagues’
definition of episodic memory (Tulving, 1972). The What–Where–When test produces cross-
sectional developmental patterns similar to those of other tests, with improvements
between 2.5 and 5 years of age (Burns, Russell, & Russell, in press; Hayne & Imuta, 2011;
Newcombe, Balcomb, Ferrara, Hansen, & Koski, 2014; Russell, Cheke, Clayton, & Meltzoff,
2011).

<hs>  Unexpected source memory</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Source memory tests assess retention of the context of an event rather than its focal
targets (Wheeler, Stuss, & Tulving, 1997). Here, participants are required to report not
only what was learned but also (and unexpectedly) on the details of the context in which
the learning occurred. Zentall and colleagues argued that deliberate encoding reduces the
contribution of episodic memory, and thus only a question that is unexpected requires an
individual to episodically reexperience the original event (Zentall, Clement, Bhatt, &
Allen, 2001; Zentall, Singer, & Stagner, 2008). However, Ornstein, Haden, and Elischberger
(2006) argued that it is children’s growing competence with event recall that translates
into increasingly deliberate encoding. This would suggest that episodic memory development
may facilitate the later emergence of purposeful remembering (Cuvo, 1975). Thus, it is
unclear whether younger children may encode “expected” and “unexpected” items differently.
Children under 5 years have, however, demonstrated very poor source memory (Drummey &
Newcombe, 2002; Gopnik & Graff, 1988; Whitcombe & Robinson, 2000). Absent from our
analysis in this article is a consideration of autobiographical memory reports. However,
to the extent that they require children to report on previous events, unexpected/source
memory tests can be viewed as similar in some ways to lab-based autobiographical/event
memory tests. Autobiographical memory has been studied extensively in young children
(e.g., Fivush, 2014; Goodman, Ogle, McWilliams, Narr, & Paz‐Alonso, 2014; Reese, 2014).
Much of this work has examined children’s verbal recall of events during parent–child
conversations (e.g., Burch, Austin, & Bauer, 2004; Farrant & Reese, 2000; Haden, Ornstein,
Rudek, & Cameron, 2009) and interviews elicited by experimenters (e.g., Ornstein, Gordon,
& Larus, 1992). Fivush (2011) and Fivush and Nelson (2004) argued for a distinction
between episodic memory and autobiographical memory, suggesting that the former should be
characterized by the content of the memory, whereas the latter requires an additional
layer of cognitive sophistication. The current study took as its starting point this more
“minimalist” view of episodic memory (see also Clayton & Russell, 2009) and as such does
not involve an assessment of autobiographical memory. In summary, the literature using
different episodic memory tests suggests that performance on each improves between 3 and 6
years of age. This may mean that these tests are able to produce consistent developmental
trajectories despite very different testing methodologies. However, establishing
comparable improvement in test performance throughout the preschool years is not
sufficient evidence to conclude that a common cognitive process underlies performance on
these different tasks. After all, many cognitive (e.g., theory of mind, language) and non-
cognitive (e.g., running speed, height) factors improve over this period. What is required
is an assessment of the degree to which performances on these different tests are related
within the same individuals. This type of investigation has been carried out with respect
to different tests of prospection, finding good correlation among most tests (Atance &
Jackson, 2009). Here, 3- to 6-year-old children were presented with three putative tests
of episodic memory (What–Where–When, Unexpected Source Memory, and Free Recall) and one
that is thought to rely less on episodic memory than on semantic memory (Cued Recall)
(Tulving, 1985). All of the memory tests were designed to produce continuous data (not
pass/fail). This enabled us to investigate whether performances on these tests are
correlated and whether they are able to hold together as a “battery” of tests.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

At total of 106 children between 36 and 83 months of age were recruited from schools and
nurseries in the Cambridge area of England. There were 27 3-year-olds (M = 42.3 months, SD
= 3.6), 18 4-year-olds (M = 53.67 months, SD = 3.5), 27 5-year-olds (M = 66.2 months, SD =
3.3), and 34 6-year-olds (M = 76.7 months, SD = 2.7). The sample consisted of 49 girls and
57 boys (3-year-olds: 15 girls and 12 boys; 4-year-olds: 6 girls and 12 boys; 5-year-olds:
15 girls and 12 boys; 6-year-olds: 13 boys and 21 girls). The study was approved by the
Cambridge University psychological research ethics committee. Informed written consent was
received from parents before any child took part. Testing took place in an empty room or
in a quiet corner of a classroom in the school/nursery. The majority of the children were
native English speaking, Caucasian, and middle class, representative of the local area.

<hs>  Procedure</hs>
  ~~~~~~~~~

As shown in Fig. 1, the study had a nested design in which elements of each test described
here formed the retention intervals for the other tests.

        <hss>Free Recall and Cued Recall</hss>

        In both recall tasks, children were shown eight photos of familiar objects or
        animals (e.g., a book, a horse) and were asked to name each one in turn. They were
        then told to look at the images and try to remember what was in them. Recall
        occurred after a delay of approximately 5 min. In Free Recall children were asked
        to tell the experimenter “what pictures had been on the cards,” whereas in Cued
        Recall they were asked to tell the experimenter what pictures of specific
        categories (animals or toys) had been on the cards. This methodology followed that
        of Perner and Ruffman (1995), but the images were not the same.

        <hss>What–Where–When</hss>

        Fewer children took part in this task because children were split between this and
        another study (not reported). As such, 68 children took part in this task (32
        girls and 36 boys; 12 3-year-olds, 13 4-year-olds, 17 5-year-olds, and 26 6-year-
        olds). As shown in Fig. 2, children were given three pieces of “gold treasure”
        (plastic £1 coins) and three pieces of “silver treasure” (plastic 20p coins) and
        asked to hide them in two different trays (the “forest” and the “town”). There
        were two hiding sessions separated by approximately 5 min. In each session,
        children could hide in only one tray. During hiding, the experimenter highlighted
        each coin’s identity by saying, “Where are you going to hide that [gold/silver]
        treasure?” After a delay (∼5–10 min), a new character (“Mr. Crow”) who had
        “stolen” a specific subset of the hidden coins was introduced; for example, the
        gold treasure from the second hiding session had been stolen. Children were
        explicitly informed which treasure remained (e.g., “the GOLD treasure from BEFORE
        we looked at cards”). All elements of the treasure that was left (particularly the
        “when” element) were described to children in a number of ways (e.g., “before,”
        “earlier,” “first,” “longer ago”) to increase their chances of understanding what
        was being asked. Children were then asked to indicate the location of the
        remaining treasure by pointing. Children could then swap the coins for a sticker.

        <hss>Unexpected Source Memory</hss>

        One week after the first stage of the experiment, children were unexpectedly asked
        about elements of the “games” that had been played. The 11 questions concerned
        contextual details about the learning episode. Both open-ended questions (e.g.,
        “What animal stole the treasure in the pirate game?”) and cued-choice questions
        (e.g., “Which video had a teddy bear in it?”) were asked. Some referred to games
        children had played that day, and others referred to games they had played the
        previous week.

<h>RESULTS</h>
-------

Data were analyzed using Pearson’s and partial correlations to measure covariation among
various test performance. To assess whether performance on the different tests may reflect
a single latent variable, principal component analysis was used. Alpha was set at .05.
Preliminary analysis revealed no differences in performance between boys and girls, and
therefore gender was not considered in the main analyses. Table 1 shows the mean, standard
deviation, and range of scores for each age group on each of the tests. As shown in Fig.
3, performance on all tests was positively associated with age. Table 2 indicates the
correlations with age as well as the associations among the tests. Performances on many of
the memory tests were related. The significant correlation between Unexpected Source
Memory and Free Recall remained when Cued Recall was controlled (r = .317, p = .02). The
positive correlation between Free Recall and Cued Recall remained after age was
controlled. However, all of the other correlations were reduced to non-significance when
controlling for age. The central question of this study concerns whether different tests
of episodic memory can be said to be assessing the same underlying cognitive process. One
way of addressing this is to examine the extent to which an appropriately amalgamated
score from all four tests (using the 68 children who took part in all four tests) is able
account for more variance than any of the tests on their own. This was done in two stages,
a covariance summary and then a prediction of a known relevant variable, as a validation
paradigm. A single principal component was produced by this analysis and had an eigenvalue
of 1.91, explaining 47.9% of total variance. No other component had an eigenvalue over
1.0, and orthogonal rotation did not increase the eigenvalue of the second principal
component over 1.10, indicating a single underlying source of covariance in this dataset.
Of the four tests, the What–Where–When test loaded least well into this factor (.340).
Finally, the principal component was then correlated with age. This produced a marginally
stronger correlation than any of the individual tests (r = .699). This correlation was
similar when dropping the weakest loading test (What–Where–When) and re-extracting the
first principal component (r = .708).

<h>DISCUSSION</h>
----------

The aim of this experiment was to investigate the consistency of a number of different
tests putatively assessing the same underlying psychological process, namely episodic
memory. Performance on each of the four tests was shown to improve gradually between 3 and
6 years of age, in line with previous literature (e.g., Hayne & Imuta, 2011; Naito, 2003;
Reese, 2014). These tests differ in their surface features but are conceptually similar in
that all aim to assess episodic memory. As would be predicted by this similarity,
performances on many of the tests were correlated; however, few correlations remained
significant after covariation due to age-related improvement being controlled. This result
demonstrates that these tests are not equivalent and should not be treated as so when
assessing episodic memory in children. However, the principal component analysis suggests
that a single underlying factor may satisfactorily fit the data. Thus, there may be
mileage in adapting these tests with the aim of reducing their surface differences and
bringing them together into a single battery. Nevertheless, there is still some distance
to go before a satisfactory battery of episodic memory tasks can be achieved. The tests
used in this study were not designed to be methodologically similar; rather, they were
designed to represent the variation present between currently used tests. Therefore, it is
difficult to identify what factors contribute to low levels of age-independent
correlation. There are many non-mnemonic cognitive and non-cognitive abilities that
develop across the age range covered here. Furthermore, the tests differed in the extent
to which they required receptive and productive verbal competence, confidence around a
strange experimenter, executive functions, and other “extra-target” challenges. However,
recent work with adults (Cheke & Clayton, 2013) shows that poor correlations among these
tests are present even during adulthood. This implies that development of extra-target
factors might not provide a full explanation for low covariation. Each of the tests used
in this study explicitly tests different mnemonic skills. The What–Where–When test
requires binding of spatiotemporal features. The Unexpected Source Memory task requires
the ability to reanalyze previous experiences for new information. The Free Recall task
assesses the ability to mentally initiate and guide retrieval in the absence of external
cueing, and the Cued Recall task requires the ability to use category words as retrieval
cues. These different elements are by no means the only important features of episodic
memory: One limitation of this study is the absence of a measure of these children’s
autobiographical memory reports. Still, the tests employed cover a range of different
perspectives on the “defining features” of episodic memory. Adaptation of these types of
test to facilitate the creation of a battery could provide benefits that are greater than
the sum of it’s parts. Ultimately, it may allow the assessment of episodic memory as a
whole without undue emphasis on any one particular feature. To summarize, this study
revealed few associations for performance on different tasks putatively assessing episodic
memory among 3- to 6-year-old children when age was controlled. This suggests that these
tests are sufficiently different to lead to disparate results in studies across the
episodic memory literature. Nevertheless, it was also found that performance across the
tasks was well described by a single factor model. This may indicate that although the
different tests are too different to use independently as equivalent tests, the conceptual
similarities are sufficient to warrant their adaptation to create an episodic memory
battery. Like the blind men’s perspective of the elephant, this would have informative
powers above and beyond each individual test. Future work, therefore, should focus on
development of such a battery in which the tests are more methodologically matched but
remain structurally distinct. This battery might further include autobiographical reports
and tests of episodic foresight. In this way, researchers will be able to investigate
episodic memory not only as a coherent single process but also as a multifaceted one.


<h>REFERENCES</h>
----------

  [1] Cristina M. Atance, Laura K. Jackson. The development and coherence of future-oriented behaviors during the preschool years. doi:10.1016/j.jecp.2009.01.001
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  [8] Anna B. Drummey, Nora S. Newcombe. Developmental changes in source memory. doi:10.1111/1467-7687.00243
  [9] Kate Farrant, Elaine Reese. Maternal Style and Children's Participation in Reminiscing: Stepping Stones in Children's Autobiographical Memory Development. doi:10.1207/S15327647JCD010203
  [10] Robyn Fivush. The development of autobiographical memory. doi:10.1146/annurev.psych.121208.131702
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  [18] Nora S. Newcombe, Frances Balcomb, Katrina Ferrara, Melissa Hansen, Jessica Koski. Two rooms, two representations? Episodic-like memory in toddlers and preschoolers. doi:10.1111/desc.12162
  [19] Peter A. Ornstein, Betty N. Gordon, Deanna M. Larus. Children's memory for a personally experienced event: Implications for testimony. doi:10.1002/acp.2350060103
  [21] Josef Perner, Ted Ruffman. Episodic memory and autonoetic conciousness: Developmental evidence and a theory of childhood amnesia. doi:10.1006/jecp.1995.1024
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<ART>The structure of experience, the nature of the visual, and type 2 blindsight
============================================================================

Authors: Fiona Macpherson
DOI: 10.1016/j.concog.2014.10.011
Year: 2015  |  Pages: 104-128
ASJC codes: 3204, 3205
Keywords: Achromatopsia, Amodal completion, Blindsight, Colour experience, Perceptual experience, Phantom contours, Sensory substitution, Structure of experience, Type 2 blindsight

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Unlike those with type 1 blindsight, people who have type 2 blindsight have some sort of consciousness of the stimuli in their blind field. What is the nature of that consciousness? Is it visual experience? I address these questions by considering whether we can establish the existence of any structural-necessary-features of visual experience. I argue that it is very difficult to establish the existence of any such features. In particular, I investigate whether it is possible to visually, or more generally perceptually, experience form or movement at a distance from our body, without experiencing colour. The traditional answer, advocated by Aristotle, and some other philosophers, up to and including the present day, is that it is not and hence colour is a structural feature of visual experience. I argue that there is no good reason to think that this is impossible, and provide evidence from four cases-sensory substitution, achomatopsia, phantom contours and amodal completion-in favour of the idea that it is possible. If it is possible then one important reason for rejecting the idea that people with type 2 blindsight do not have visual experiences is undermined. I suggest further experiments that could be done to help settle the matter.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Unlike those with type 1 blindsight, people who have type 2 blindsight have some sort of
consciousness of the stimuli in their blind field. What is the nature of that
consciousness? More specifically, do those people have a visual experience of a stimulus
or of some of its features, or do they lack such a visual experience, and have some other
type of conscious state, such as a conscious feeling or thought? I address this question
by considering whether we can establish the existence of any structural features of visual
experience. Structural features of experience are necessary features of experience. I will
argue that it is very difficult to establish the existence of any such features. In
particular, I investigate whether it is possible to visually, or more generally
perceptually, experience form or movement at a distance from our body, without
experiencing some colour (chromatic or achromatic colour). The traditional answer,
advocated by Aristotle, and some other philosophers, up to and including the present day,
is that it is not. I argue that there is no good reason to think that this is impossible,
and the evidence, although not conclusive, suggests that it is possible. If this is
possible then one important reason for rejecting the idea that people with type 2
blindsight do not have visual experiences is undermined. This result is important for if
it can be established that those who have type 2 blindsight are having visual experiences
then we have reason to think that area V1 of the visual cortex is not required for visual
consciousness. This is because such people suffer lesions to V1.1 (See Zeki and ffytche
(1998), Stoerig and Barth (2001), and ffytche and Zeki (2011).) Moreover, there is some
evidence to suggest that in fact type 1 blindsight does not exist at all, and that all
cases of blindsight are really of type 2 (Overgaard, Fehl, Mouridsen, Bergholt, &
Cleeremans, 2008). If that is right then one main source of evidence for thinking that
there can be unconscious perception is removed. In section one, I explicate what
structural features of experience are. In section two, I outline the nature of type 1 and
type 2 blindsight. In particular, I outline the debate about the nature of the conscious
state in those said to have type 2 blindsight. In section three, I discuss the difference
between different kinds of mental states and argue that those with type 2 blindsight
either have visual experiences or conscious thoughts. We should eschew the idea that their
awareness or consciousness is a matter of them having feelings. In section four, I examine
the evidence about the nature of the awareness or consciousness had in type 2 blindsight.
I show that one reason given by Overgaard et al. (2008) and Overgaard and Grünbaum (2011)
for thinking that those with type 2 blindsight have visual experiences is not a good one.
I then go on to explicate two arguments that Brogaard (2011, 2012) has put forward in
favour of thinking that the sort of consciousness in type 2 blindsight is conscious
thought. I show that one of these arguments is not suitably backed up by the empirical
evidence. So the weight of her position rests on the other argument. That argument relies
on the premise that visual experiences have a certain structural feature: they must all be
experiences of colour. In section five, I explore whether one should believe that visual
experiences must have that feature and conclude that there is no good reason to think
that. Indeed, the evidence tells in favour, although not conclusively, of the claim that
they do not. That evidence also points towards an account of what the visual experiences
of those with type 2 blindsight might be like that has not yet been considered. I show
that visual experiences can be like that. I therefore conclude that there are no good
arguments for the conclusion that the type of consciousness enjoyed by people with type 2
blindsight cannot be visual experience. And I suggest further experiments that could be
done to test whether they do have such experiences.

<h>STRUCTURAL FEATURES OF PERCEPTUAL EXPERIENCE</h>
--------------------------------------------

What are structural features of perceptual experience? Structural features of experience
are invariant features of experience. On a weak understanding, they are simply invariant
features of human perceptual experience that exist as a matter of nomological necessity
given the kind of human brain that we have. Thus, the perceptual experiences of creatures
that have other types of brain need not exhibit these invariant features, nor need the
perceptual experiences of subjects with human brains in possible worlds with a physics
unlike our own. On a strong understanding, structural features of perceptual experience
are metaphysically or conceptually necessary invariant features of experience tout court.
Such features would be true of any creature with any type of brain in every possible
world. Of course, there will be accounts of structural features of experience of strengths
intermediate to the strong and the weak kinds just outlined: metaphysically necessary
features true of all subjects with humans brains, and nomologically necessary features
true of all creatures no matter what kind of brain they have. However, I set these aside
in this paper. Here are some examples of propositions that some people have claimed
specify structural features of perceptual experience. I offer these up only as candidates
for propositions that specify structural features. I do not show that they really are
ones.2 I begin with an example that many hold to be true: Necessarily, perceptual
experiences are conscious. This is plausibly proposition that specifies a structural
feature of perceptual experience—and a structural feature of perceptual experience in the
strong sense. Many philosophers hold this to be true a priori. Many candidate structural
features of perceptual experience will be features concerning what is represented in
perceptual experience. Some may be pertain to all experiences. For example this
proposition specifies an alleged such feature: Necessarily, perceptual experiences
represent space and time. The representation of space and time is, somewhat plausibly, a
weak structural feature of perceptual experience. However, some structural features may
pertain only to experiences in a certain modality. Consider these modality specific
claims: Necessarily, auditory experiences represent sound. Necessarily, visual experiences
represent colour.3 Again these seem, to some degree, to be plausible truths about
structural features of experience. For example, Aristotle in De Anima held that each of
the sensory modalities had a proper sensible, that is, an object or property that could
only be represented by that sensory modality and that was always represented by that
sensory modality: sound in the case of hearing, colour in the case of vision, pressure and
temperature in the case of touch, smells in the case of olfaction, and tastes in the case
of taste. (Aristotle considered there to be only these five senses.) The proper sensibles
contrast with common sensibles such as shape, which can be represented in more than one
modality: vision and touch. For Aristotle the proper sensibles were the defining features
of the sensory modalities. The proper sensibles were that which made each sensory modality
the sensory modality it was. They individuated the senses.4 I will come back to discuss
claim (iv) later in this paper. Some claims about candidate structural features of
perceptual experience concern what is not represented in experience: Necessarily,
perceptual experiences do not represent the future. And some such claims are restricted to
experiences in specific sensory modalities: Necessarily, visual experience does not
represent sound. Necessarily, visual experience does not represent tastes. Some claims
about candidate structural features may be ones that pertain to combinations of
representational features: Necessarily, auditory experiences represent some volume when
they represent some pitch. Necessarily, tactile experiences represent only one object as
being at any location. Necessarily, visual experiences represent only one colour to be on
a surface at any given time. Necessarily, experiences of red are more similar to
experiences of orange than they are to experiences of green.5 As I said above, but let me
emphasise, I am not claiming that these are propositions that specific structural features
of perceptual experience, only that they are the sorts of claim worthy of consideration
for specifying structural features. Indeed claims about structural features of perceptual
experience are very often particularly difficult to establish. Let me provide you with one
example: whether it is possible for perceptual experiences to represent reddish-green.
Wittgenstein discussed the questions of whether there could be a reddish-green colour,
whether a reddish-green colour could be perceived, or whether the concept of reddish-green
even makes sense. Lugg (2010) makes a careful summary of his remarks suggesting that while
the popular interpretation of Wittgenstein has been that at least at some points in his
career he claimed that there could be no perceptual experiences of reddish-green,
Wittgenstein “is genuinely puzzled, that he is pulled in both directions and cannot commit
himself either way.” (Lugg, 2010: 172). Nonetheless, perhaps inspired by Wittgenstein,
some philosophers, for example Brenner (1987), have held that there could be no
experiences as of a reddish-green. However, this claim looks to be disproved by recent
results from Crane and Piantanida (1983) and Billock and Tsou (2004). They assert that
they have created experiences of reddish-green in the laboratory. There are interesting
questions about whether there is clear proof for the existence of such experiences. (See,
for example, Lugg (2010) and Nida-Rümelin and Suarez (2009).) However, if such experiences
have been created then a claim that some took to specify a strong structural feature of
perceptual experience has been disproved.6 Faced with such a case, one might wonder how
one could ever defend any claim about the structure of experience—either strong or weak.
One might think that the primary evidence that would support a claim about the structural
features of experience would come from the sorts of experience that one has had and the
sorts of experience that one has not. However, that evidence concerns what is the case.
How does one get from claims about what is the case to modal claims about what could be
the case—as claims about the structural features of experience are? One might think that
one can extend one’s knowledge from claims about what one has experienced to claims about
what one could experience by drawing on one’s sensory imagination. For example, no one has
ever seen the national animal of Scotland, the unicorn, for such creatures have never
existed. Suppose someone had never visually experienced a unicorn because they had never
seen one and had not hallucinated one, or had a visual experience as of one while watching
a film or looking at a hologram or the like. Nonetheless, such a person could imagine what
it would be like to visually experience a unicorn—as many people have done. One imagines
what it would be like to experience a unicorn by conjoining in the imagination, in the
appropriate way, what one knows of what it is like to experience a white horse and what it
is like to experience a white horn. Based on this, it seems right to say that one can know
that it would be possible to have an experience as of a unicorn. Such a combinatorial
process allows one to consider numerous experiences that one has not had and whether they
are possible. Despite this, however, one might think that the imagination is limited in an
important respect. How could one come to have knowledge of whether it is possible to
experience things that are not simple conjunctions of what one has experienced? Recall
that Hume (1739–40/1975: 6) said that it is possible that one may be able to visually
imagine what it would be like to experience that which one has not perceived (and,
although Hume did not, we can add here that which one has not had an experience as of) and
which is not something that can be visually imagined by a simple conjoining of things that
one has seen. I will call such things “novel qualities”. For example, as Hume famously
argued, if one had experienced all the shades of colour except one particular shade of
blue, one might come to be able to imagine what it would be like to experience that shade
if one was presented with all the other shades of blue laid out in order of resemblance.
However, cases where one can imagine novel qualities are few and far between—as Hume
himself noted. He states of the missing shade of blue, “the instance is so particular and
singular, that it is scarce worth our observing” (1739–40/1975: 6). Hume goes on to note
that, “We cannot form to ourselves a just idea of the taste of a pine apple [sic], without
having actually tasted it” (1739–40/1975: 6) He thus foreshadows Jackson (1982) who claims
that if one had only had an experience as of black and white and shades of grey among the
colours, one could not come to know what it was like to have an experience as of red.7 Of
course, if someone has only had experiences as of black, white and grey then they cannot
legitimately conclude that experiences as of other colours, such as red are impossible. A
notable feature of the experiments in which it was claimed that people came to have
experiences as of reddish-green is that before having the experience as of reddish-green,
subjects said that they could not imagine what it would be like to have such an
experience, but afterwards they could imagine it. I think that, in general, people who
have not had an experience as of reddish-green, and who have just had typical human
experience, cannot imagine reddish-green. I certainly cannot. Given this, the inability to
imagine reddish-green before having the experience would explain why people might have
thought that such experiences were impossible. However, as in the case of red discussed by
Jackson in the previous paragraph, we cannot conclude just from the fact that one has not
had a certain type of experience, and the fact that one cannot imagine what such an
experience might be like, that such an experience is not possible. In arguing about
whether a certain sort of experience is possible, there may be further considerations that
one can bring into try to establish the matter. If one were trying to establish that
experiences as of reddish-green were impossible then one might adduce arguments concerning
the opponency of the visual system. According to colour opponent theory, information from
the eye is processed in the brain in an antagonistic manner. There are three opponent
channels: the red versus green, the blue versus yellow, and light versus dark. The brain
cannot signal the presence of red at a location at the same time as it signals that there
is green at a location. (It could however, indicate that both red and blue were present at
the same locations, in which case, it would be signalling that purple was present.) If all
brain processing were subject to these opponent channels, then one might argue that
subjects whose brains were so constrained could never experience reddish-green. (And if
one made a case that their brains were so constrained as a matter of nomological necessity
then, in doing so, one would be putting forward an argument that not being able to be as
of reddish-green is a weak structural feature of experience.) However, Crane and
Piantanida (1983) speculate that the “filling in” process that produces the experience
allows the visual cortex to signal for the presence of red and green at the same location
at the same time by allowing it to signal the presence of colours unconstrained from
bottom-up opponent channels. What the considerations above show is that in every case
where we wish to identify structural features of experience, we will have to look closely
at what evidence is available. Evidence from our imagination can play a role in
establishing what is a structural feature; however, the inability to imagine an experience
should not be taken as conclusive evidence that such an experience is impossible.
Furthermore, other evidence should be sought and weighed as best we can. Considering what
the structural features of visual experience are will be important in thinking about the
nature of the experiences had by those people who have type 2 blindsight. I will consider
whether we can visually experience something as being at a distance from our body without
at the same time having an experience as of its colour. Can we determine whether or not
this is true? Knowing the answer could help settle a debate about the nature of type 2
blindsight. In the next section, I discuss the nature of type 1 and type 2 blindsight, and
outline the question of what is the nature of the conscious state that is had in type 2
blindsight. I will distinguish between different candidates for what that conscious state
is: a feeling, a perceptual experience, or a thought.

<h>TYPE 1 AND TYPE 2 BLINDSIGHT</h>
----------------------------

According to the traditional conception of blindsight (Weiskrantz, 1986), a subject has
blindsight when he or she does not acknowledge any awareness or consciousness in a portion
of his or her visual field (the blind field), yet nonetheless, some visual functioning
remains intact. Physiologically, blindsight occurs when there is damage to the part of the
primary visual cortex (V1) that corresponds to the blind field. Blindsight subjects report
that they are totally blind in that area of their visual field. Yet, it can be determined
that some information from the blind field does affect subjects’ behaviour. In particular,
in a forced choice paradigm, subjects are able to guess with a high degree of accuracy
about some features of a stimulus presented in their blind field. For example, Weiskrantz
(1997: 23) says that people with blindsight “have been reported who are able, in their
blind hemifields, to detect the presence of stimuli, to locate them in space, to
discriminate direction of movement, to discriminate orientation of lines, to be able to
judge whether stimuli in the blind field match or mismatch those in the intact hemifield,
and to discriminate between different wavelengths of light, that is, to tell colours
apart.” People with blindsight are initially unaware that they have blindsight and are not
simply blind. It comes as a surprise to them that their guesses are accurate, although
they can come to know that their guessing is accurate when experimenters tell them so. It
should be noted that subjects cannot generate accurate guesses themselves. One reason is
that in the experimental setting in which they display their guessing ability, the
experimenter provides two options that they have to choose between, one of which is
accurate. And the experimenter uses his or her knowledge of how the world is in the
subjects’ blind field to ensure that there is one accurate option. However, subjects on
their own cannot reliably generate two options one of which corresponds to the way the
world is. It has been found that some patients who have been classified as having
blindsight in fact report some limited consciousness in what is typically called their
“blind field”.8 In response to such cases, Weiskrantz (1998) introduced a distinction
between type 1 and type 2 blindsight. Type 1 blindsight is that which conforms to the
traditional definition above in that no consciousness corresponding to the stimuli in the
blind field is reported. Type 2 blindsight is defined as occurring when some limited
consciousness of the stimulus in the blind field exists. However, how to characterise this
consciousness is a tricky business. In attempting to characterise it, some people have
focused on the fact that sometimes what is reported in type 2 blindsight is a mere
conscious “feeling” or conscious “knowing” of the nature of the stimulus—but a conscious
state that does not amount to a visual experience. In his definition of type 2 blindsight,
Weizkrantz states that the nature of the consciousness is “acknowledged experience of
events in the blind field in the absence of acknowledged ‘seeing’” (1998: xi). So,
Weizkrantz, and others who have endorsed the existence of type 2 blindsight, have claimed
that the consciousness that is present in these cases does not consist of a visual
experience of the stimulus or some of its features. Many of the cases of type 2 blindsight
that have been discussed in the literature are type 2 blindsight with respect to movement.
Subjects with type 2 blindsight may have type 1 or type 2 blidsight or be completely blind
with respect to other features of objects in their blind fields. In contrast to
Weizkrantz, other researchers (Zeki and ffytche (1998), Stoerig and Barth (2001), and
ffytche and Zeki (2011)) have claimed that the form of consciousness that type 2
blindsight subjects have is visual experience. That is, they claim that these subjects
have visual experiences of movement (at least sometimes—typically the more high-contrast
the stimulus and the faster it is moving it is the more likely subjects are to report
awareness). These researchers often classify the subjects as having “Riddoch syndrome”.
Riddoch (1917) examined men injured in war who reported that they were blind in one half
of their visual fields, except for the fact that they reported seeing movement in them.9
These researchers noted that type 2 blindsight patients with respect to movement seem to
be just like those patients Riddoch studied. Because they classify the awareness as visual
experience they tend not to classify the subjects as having “type 2 blindsight”. Why is
this? The answer is that if the subjects are having a visual experience, then it is
tempting to say that they are just seeing and hence do not have blindsight. If type 2
subjects have visual experiences, should we classify them as just seeing and not having
type 2 blindsight? The answer to that question is complicated because a subject who has
type 2 blindsight with respect to some feature or features of an object is typically blind
and/or has type 1 blindsight with respect to the other features of objects in the blind
field. To illustrate, suppose we placed a red X-shaped object on the left of a subject’s
blind field and then moved it to the right of that field. A subject might report having
some form of consciousness of the left to right movement but deny having any consciousness
of anything else. Moreover, at the same time, the subject could, in a forced choice
paradigm, be able to guess reliably that the shape was that of an X and not be able to
guess reliably that it was red. In such a case, the subject would have type 2 blindsight
for the movement of the object, type 1 blindsight for the shape of the object, and simply
be blind with respect to the colour of the object. With these considerations in mind, what
is the answer to the question of whether, if type 2 blindsight involves having a visual
experience, the subject would just be seeing and hence would not have blindsight? The
answer is that, at least with respect to the feature in question that they are visually
experiencing, the subject would be seeing that feature. Given that, it does seem
appropriate to question whether it is right to say that those in whom the consciousness
amounts to visual experience have a form of blindsight with respect to the feature they
experience. For they just seem to be seeing it. Nonetheless, I will stick to calling
people who report any form of consciousness of limited features people with type 2
blindsight—with respect those features that they so report—and I will also speak of their
“blind fields”. One reason is that “Riddoch syndrome” is only a term that applies to those
who reported blindness except for movement. It is useful to have a term that does not just
pertain to cases of reported awareness of movement. Another reason is that it is very
useful to have a term that applies to those who report some consciousness of just one, or
a limited number, of features in the presence of either blindness or type 1 blindsight for
other features, where the terms leaves open what the nature that awareness is. For it is
useful to ask of such people whether we can determine whether their awareness is a
feeling, a visual experience, or knowledge, or judgment of a feature of an object. To
summarise: psychologists have identified a group of subjects who report being, for the
most part, blind in a portion of their visual fields. Those subjects do, however, report
some form of consciousness of movement—and only movement—in that field. Some researchers
think that the awareness is a feeling, or knowing, or judging. Other researchers think
that the awareness is a visual experience—a minimal or highly degraded one that represents
a limited number of features of a stimulus. In either case, I will classify these subjects
as having type 2 blindsight and investigate what we can determine about the nature of
their conscious mental state. Do they have visual experiences or do they have some other
type of conscious mental state? I will set aside the worry that, if it turns out that
these subjects have visual experiences, then the term “type 2 blindsight” may not turn out
to be the most appropriate nomenclature for their condition for it would be appropriate to
say that the subjects see the feature that they claim awareness of. I said earlier in this
section that many cases of type 2 blindsight involved subjects reporting consciousness of
movement. A case not involving movement is reported by Overgaard et al. (2008) who
investigated a subject GR. When subject to standard blindsight testing, GR displays
behaviour which would lead one to classify her as having type 1 blindsight. For example,
when asked whether she can detect stimuli in a certain portion of her visual field, given
only the options of answering “yes” or “no”, she reports that she does not. When a letter
is presented in that portion of her visual field and she is asked to guess in a forced
choice paradigm whether the letter is “A”, “B” or “C”, she performs better than chance.
However, Overgaard et al. tested GR further. They asked her to rate her experience on a
four point scale: (CI) ‘clear image’, (ACI) ‘almost clear image’ (meaning ‘I think I know
what was shown’), (WG) ‘weak glimpse’ (meaning ‘something was there but I had no idea what
it was’), and (NS) ‘not seen’ (2008: 1). When GR was tested in the damaged portion of her
visual field on thirty-three occasions, seven were reported as “clear image”, eleven as
“almost clear image”, twelve as “weak glimpse”, and three as “not seen”. Moreover, there
was a positive relationship between the accuracy of the “guess” about what the stimulus
was and the clarity of the experience. In fact, there was the same relationship between
accuracy and clarity in her blind field as there was in her intact field. These results
indicate that GR does have some consciousness of the stimulus. It therefore seems right to
classify her not as having type 1 blindsight, but type 2.10 As in the case of those who
have type 2 blindsight with respect to movement, researchers have different views about
what kind of consciousness to ascribe to GR. Overgaard et al. (2008) and Overgaard and
Grünbaum (2011) argue that GR has a visual experience, while Brogaard (2011, 2012) argues
that GR only has a conscious thought that is about the nature of the stimulus. In this
section, I have explained the difference between type 1 and type 2 blindsight and briefly
outlined the different answers in the debate about the nature of the awareness had in type
2 blindsight. Some say that it is a feeling or thought. Others say that it is a visual
experience—albeit a degraded one. In the next section, I give an account of what these
different types of mental state are. I argue that the consciousness of those with type 2
blindsight should not be described as a feeling. The only serious options for what the
nature of their awareness or consciousness is, is a visual experience or a conscious
thought.

<h>TYPES OF MENTAL STATE</h>
---------------------

What is the difference between feelings, thoughts, and visual experiences? Thoughts are a
type of propositional attitude. Other types of propositional attitudes include beliefs and
desires. When one has a propositional attitType 2 blindsight ude one takes an attitude,
such as holding it to be true in the case of belief, or wanting it to be true in the case
of desire, to some proposition. For example, if one believes that Scotland should be
independent, then one takes the attitude of holding it to be true towards the proposition
that Scotland should be an independent country. If one desires that Scotland be an
independent country, then one takes the attitude of wanting it to be true that Scotland is
an independent country. When one has a thought about something one can be merely
entertaining a proposition (considering whether a proposition is true), or one can be
endorsing a proposition. Propositional attitudes are representational states. They are
about something, and what they are about is specified by the proposition to which one
takes an attitude. In the case of the thought that Scotland should be an independent
country, the proposition, that Scotland should be an independent country, specifies that
which is represented. Thoughts, unlike beliefs and desires, are always occurrent states
rather than dispositional states. Thoughts can be conscious or unconscious. There is an
interesting question as to whether conscious thoughts have phenomenal character.11 One
view is that in and of themselves they do not, but that they are usually or always
accompanied by states that do. In particular, they might be accompanied by visual imagery.
In the case of thinking that Scotland should be an independent country, perhaps one has
visual imagery of mountains and lochs, the Saltire, and the face of William Wallace. The
thought might also be accompanied by auditory imagery. For example, one might hear the
words “Scotland should be an independent country”, or “Freedom”, in one’s own inner voice.
On this view, no imagery in particular is essential to thinking the thought (although one
might think that some imagery or other usually or always does so). Someone else might have
visual imagery of Glasgow and of the faces of Robert the Bruce and the Black Douglas. And
they might not have auditory imagery of the words “Scotland should be an independent
country”, but the French words “Ecosse devrait être un pays indépendant”. Another view,
however, is that thoughts have their own proprietary phenomenal character associated with
grasping the meaning of the proposition. Contrasting with the propositional attitudes are
feelings, also known as “sensations”, such as pains, itches and tickles. These states
clearly have phenomenal character, and indeed plausibly, theses states are individuated by
their phenomenal character: what makes a pain a pain is the way that it feels, and what
makes an itch an itch is the distinctive itchy feel that such states have. Thus feelings
and sensations have been thought of as essentially conscious states. Traditionally
feelings have been conceived of in philosophy as states that do not represent. Why is
that? Thomas Reid (1785/2002: I. i. 36) said that sensation, “hath no object distinct from
the act itself”. The idea is that if I have a sensation of pain, there is no object—a
pain—that I am sensing. My sensation is not ‘of’ any object, therefore it is not
representational. More recently, the traditional view of feelings as non-representational
has been questioned. It is agreed that feeling states, such as pains and itches, do not
represent objects called feelings—objects that are pains or itches. Rather, it is claimed
that feelings represent different states of the body. (See Armstrong (1962, 1968) and
Pitcher (1970, 1971) and, more recently, Tye (2006a, 2006b).) For example, a throbbing
pain in one’s big toe might represent that there is an increase and decrease in the volume
of damaged and inflamed tissues in one’s toe. A sharp stabbing pain in the chest might
represent that something pointed is entering and tearing asunder the flesh in one’s upper
torso. A feeling of hunger might represent one’s stomach contractions and low blood
glucose. Perceptual experiences have been traditionally thought of as hybrid states: being
somewhat like the propositional attitudes and somewhat like feelings or sensations. Like
the propositional attitudes, perceptual experiences seem to represent and be about things
in the world. My present visual experience of a teapot seems to represent a silver object
with a round body with various protrusions, corresponding to the handle, spout and knob of
the lid. My auditory experience of the whistle of the kettle, represents a high-pitched
loud note.12 At the same time, like feelings and sensations, perceptual experiences are
essentially conscious states that have phenomenal character that differentiates one
perceptual experience from another. Given the characterisation of these three types of
states that are the candidates for what kind of state a person with type 2 blindsight is
in, it is clear that feelings are just not good candidates. The reason is that the people
with type 2 blindsight say that they have a feeling about some state of affairs in the
world. For example, they say that they have a feeling that something in front of them is
moving. Such a state would be a state that represented something in the world exterior to
their body. As feelings are either not representational at all, or they represent
something happening to the body, they are not the type of state that those with type 2
blindsight are reporting. We can explain, nonetheless, why it is the case that people with
type 2 blindsight use the word “feeling” to describe their mental state. Sometimes in
everyday language we use this word to indicate that we are not quite sure what kind of
mental state we are in. One might say, “I have a feeling that our guests are arriving on
Tuesday”, when one wants to report that one has some evidence to this effect but one isn’t
quite sure where from. One might not know whether one remembers this, or whether one is
guessing at this based on what one was previously told about the travel plans (say that
some other destination would be reached by Monday), or whether one has worked it out based
on the time one knows it takes to travel between certain places, or what have you.
However, although this everyday usage is perfectly acceptable, that does not mean that we
should take such talk to imply that subjects mean that the person has feelings in the
sense outlined above. Therefore, I will limit my investigation of the mental states of
people with type 2 blindsight to the investigation of whether such people are having
visual experiences or whether they are having thoughts. How does one determine whether
someone is having a conscious thought about something or whether he or she is having a
perceptual experience? That is a very tricky question indeed. Perceptual experience seems
to inform us of the way the world is now. (At least it seems that way to us: even if we
are looking at a distant star and our experience is actually informing us of an event that
took place many years ago.) However, we may not believe that the world is as our
experience presents it to be. For example, one might think that one is suffering from an
illusion or a hallucination and so not be inclined to believe what one’s experience seems
to tell one. To this extent, experience is different from belief. However, we are
considering how to distinguish experience from thought. One could certainly entertain the
thought that this is how the world seems, yet be inclined to desist believing that is how
it is because one has reason to not to fully trust the thought in question. So we have no
reason yet to distinguish experience and thought. One way in which thought and perceptual
experience are different is with respect to their phenomenal character. Perceptual
experience typically seems to be about the about the world in front of one at a distance
from one’s body. It typically tells one, among other things, about colours, shapes, sizes,
positions, movements, and so on.13 Clearly thought can be about this too—although it can
be about many more things than it seems visual experience, and perceptual experience more
generally, can be about. However, what it is like to visually experience colour or shape
or size or movement is different to what it is like to think about these things, if indeed
there is anything it is like to think about them. But what one can say about this
difference is unclear, not least because there is such discord in thinking about the
phenomenal character of thought—as I outlined earlier in this section—and not least
because it is hard to describe the phenomenal character of visual experience other than to
say what it is an experience as of. Nonetheless, although describing differences in
phenomenal character is difficult, and although there are different views about the
phenomenal character of thought, I take it that visual experience has a distinctive
phenomenal character either because thought has a different one or lacks one. Thus, in
ascribing a visual experience to a person, one is ascribing to them a distinctive sort of
phenomenal character. I discuss this topic in greater length in the section below. There
may be other differences between thought and perceptual experience. For example, some
people think that thought is conceptual while visual experience is, or is in part, or can
be nonconceptual. However, I leave this topic aside for I don’t believe that even if there
is this difference, it will help to settle the question of which state is had by people
with type 2 blindsight. How one could test for perceptual experience rather than
thought—as opposed to merely knowing what the difference is between them—is a difficult
matter too. One might think that one could simply scan the brain and see if the visual
areas of the brain are active, However, one can only know what parts of the brain
correspond to visual experience by correlating reports of visual experience, and its lack,
with brain activity. When we are dealing with blindsight, an important and pertinent issue
is what areas of the brain should be taken to give rise to visual experience. Stoerig and
Barth (2001) and ffytche and Zeki (2011) use their conclusion that people with type 2
blindsight are having visual experiences to deny the claim that has often been made that
activation in the V1 areas of the visual cortex is necessary for visual experience.
Therefore, we cannot rely on evidence about what areas of the brain are active as a guide
to what kind of mental state is being had by the subject. In this section, I have argued
that people with type 2 blindsight are either having conscious thoughts about the stimuli
in their blind fields or they are having visual experiences. They are not having feelings.
Perceptual experiences have different phenomenal character to conscious thoughts, if
indeed the latter have phenomenal character. In the next section, I go on to examine the
evidence and the arguments that have been put forward by both sides concerning whether the
type 2 blindsight subject is consciously thinking about or visually experiencing the
world.

<h>THE EVIDENCE AND EXTANT ARGUMENTS ABOUT TYPE 2 BLINDSIGHT</h>
---------------------------------------------------------

Are type 2 blindsight subjects having degraded visual experiences of some sort or are they
having conscious thoughts? Let’s look at the evidence from the subjective reports of
various subjects. Zeki and ffytche (1998) examined Riddoch’s (1917) accounts of the
subjective reports of his patients. In all these cases, the patients “were able to detect
the presence of motion within their scotomatous fields, without being able to characterize
the other attributes of the stimulus” (1998: 26). Here are the reports: Patient 1: “The
‘moving things’ have no distinct shape, and the nearest approach to colour that can be
attributed to them is a shadowy grey”. Patient 2: ‘The ‘moving something’ had neither form
nor colour. It gave him the impression of a shadow”. Patient 3: “could detect the movement
of feet in the street ‘. . . though they had no shape’” Patient 4: “. . . declared he
could distinguish no object . . . but he knew that something had moved through his blind
field” Patient 5: ‘They [the moving objects] don’t appear to have any colour or shape.
They look like shadows. Sometimes I can tell if the moving things are white.” (1998: 26)
In each of these cases it is clear that movement is reported. It is important to
distinguish the question of whether subjects could identify the colour of the stimulus
from the question of whether they had an experience of some colour or other, and this is
not clearly enough done in the reports of the subjects’ experience. Subjects clearly could
not detect the colour of the stimulus. (Although one subject says that they could tell if
something was white, this is an anomalous report.) However, the subjects report that their
experiences are like looking at shadows. And one alludes to the colour grey. One view is
that subjects visually experience dark grey indeterminate shapes moving on a slightly
lighter grey or slightly darker grey background. Another view is that subjects have visual
experiences without experiencing any colour properties. A third view is that the subjects
did not have visual experiences, they only had thoughts. The best candidate for the
thought that they had is that it was a thought that something moved, perhaps more
specifically the thought that something moved in a certain direction, with a certain
speed. Which of these views is true is unclear. ffytche and Zeki (2011) found two
subjects, GN and FB , who were very similar to the patients of Riddoch (1917) in terms of
their reports and responses. In addition to reporting consciousness of the stimulus, GN
and FB “could prepare drawings of what they had perceived in their blind field, which
compare favourably with the drawings of the same stimuli when presented to their intact
fields” (2001: 254). ffytche and Zeki go on to say “their drawings and … descriptions left
us in no doubt that the experiences they had were visual in nature and amounted to what
might be called ‘visual qualia’” (2011: 254). However, their conclusion goes rather beyond
the available evidence because one could draw a picture of how one thought the world was,
rather than how one experienced the world to be. Another person with type 2 blindsight for
movement who has been studied in modern times is GY. Zeki and ffytche (1998: 29) report
that in 1993, GY described his visual experiences as dark and shadowy. However, later, in
1994, he changed his mind. He now said that he had a “’feeling’ of something happening in
his blind field and, given the right conditions, that he is absolutely sure of the
occurrence” (1998: 29). When Zeki and ffytche pointed out to him that his description had
changed he said that he had previously “been using language that he thought a normally
sighted person would understand” (1998: 29–30). Two years later, in 1996, he said his
experience was “as that of ‘a black shadow moving on a black background’, adding that
‘shadow is the nearest I can get to putting it into words so that people can understand’.
(1998: 30). When Zeki and ffytche tested GY’s blindsight for movement, they asked him to
indicate the direction of movement of a stimulus and his level of awareness on a four
point scale, similar to the way in which Overgaard et al. (2008) tested GR (described in
section two above). Like Overgaard et al., Zeki and ffytche found that GY reported
consciousness of movement more frequently when he was given the four-point scale to use,
compared to the condition in which he had to indicate with a “yes” or “no” whether he was
conscious. Moreover, his ability to correctly identify the direction of the movement
correlated positively with his reports of awareness.14 The evidence from these varying
reports of GY is not enough to settle the question of the nature of his conscious state
one way or the other. GY has been investigated by other experimenters concerning the
nature of his consciousness. Unfortunately, the evidence points in opposite directions as
to the nature of his consciousness. Stoerig and Barth (2001) report that GY denies seeing.
And they cite previous descriptions that GY has given of his experience: “He is aware of
‘something moving’ but it appears as ‘black on black,’ like ‘a mouse under a blanket’
(personal communication), or ‘similar to that of a normally sighted man who, with his eyes
shut against sunlight, can perceive the direction of motion of a hand waved in front of
him’ (Beckers & Zeki, 1995, p. 56).” (2001: 582). They also report that “in other
experiments he has, for instance, stressed an absence of color sensation” (2001: 582).
Yet, they found that despite denying seeing, when a moving texture of low contrast was
presented to GY in his intact visual field, he accepted that it created the same conscious
state in him as a high-contrast bar moving in his blind field. Furthermore, they found an
even better match when they used an apparent motion stimulus.15 Stoerig and Barth conclude
that as a match with a visual experience was made, GY’s awareness or consciousness in his
blind field is just the same as the visual experience he has in his intact field. This is
a minimal or degraded experience: one that they describe as having a “reduced phenomenal
content” (2001: 584). In contrast, Persaud and Lau (2008) gave GY several definitions of
“qualia”, a term that I take them to hold is synonymous with “phenomenal character”.16
They then questioned GY as to whether he experienced any qualia in his blind field. His
answer was that he denied “having visual qualia of stationary stimuli in his affected
field. He was adamant that he never has visual qualia in his affected field in everyday
life.” (2008: 1048). And asked whether he had qualia of moving stimuli in the affected
field he replied “No, never” (2008: 1047). So the evidence about GY’s conscious state
flip-flops over time, and is dependent on how he is tested and what he is asked. Finally,
the last piece of evidence comes from the Overgaard et al. (2008) study of GR, outlined in
section two above. Recall that previous to their investigations, GR had been classified as
having type 1 blindsight. When asked whether or not she can detect stimuli in her blind
field and given only the options of answering “yes” or “no”, she reports that she does
not. Overgaard et al. then asked GR to rate her experience in the blind field on a four
point scale, “(CI) ‘clear image’, (ACI) ‘almost clear image’ (meaning ‘I think I know what
was shown’), (WG) ‘weak glimpse’ (meaning ‘something was there but I had no idea what it
was’), and (NS) ‘not seen’” (2008: 1). Out of thirty-three occasions, GR reported seven
times a “clear image”, eleven times an “almost clear image”, twelve times a “weak
glimpse”, and three times “not seen”. In light of this evidence it seems that we should
classify GR as having type 2 blindsight, but what we should conclude about her conscious
state is that it is not clear what its nature is. In summary, the reports of subjects’
experience and the experiments performed to try to get clearer about the nature of the
mental states of those with type 2 blindsight are inconclusive. The evidence is mixed and
points in different directions. Those who believe that people with type 2 blindsight are
having visual experience point to the evidence which suggests that they are having visual
experience; those who deny this draw attention to the evidence which suggests otherwise.
Both sides rightly warn of taking introspective reports at face value. I will now look at
different arguments that have been made by researchers in favour of one or other of the
positions that people with type 2 blindsight are either having (possibly minimal or
degraded) visual experiences or that they are having conscious thoughts. These arguments
go beyond the citation of the introspective reports in the different conditions mentioned
above. One argument in favour of the idea that people with type 2 blindsight are having a
visual experience (and hence visual phenomenal character or qualia) is inspired by the
causal origin of the reported awareness. For example, Overgaard and Grünbaum suggest that
there is reason to hold that if a subject reports a conscious mental state and that it is
caused by visual stimuli then the state should count as a visual experience. They state,
“a visual process is one in which a subject at some level reacts to something visual. From
this … it should follow that if there is any kind of preserved conscious experience in
blindsight subjects caused by visual stimuli … those experiences should be conceived of as
visual” (2011: 1858).17 This argument is spurious. There are many counterexamples which
spring from noting that the nature of the stimulus, the nature of the sensory organ, and
the kind of early perceptual processing that takes place does not fix the nature of the
conscious state that is subsequently had by a subject. First, there are examples in which
the nature of the stimulus, the nature of the sensory organ, and the kind of early
perceptual processing that takes place may all be of one modality, while the subsequent
experience is in a different modality. For example, in synaesthesia, people have an
experience in one modality, say a visual experience of redness, caused by a visual
stimulus affecting their eyes, which leads to visual processing. However, at the same time
another experience in a different modality is also caused to occur in them, such as an
auditory experience of sound. What this shows us is that the criteria for which type of
experience is being had is not the same as which type of stimulus, sensory organ, or
perceptual processing is taking place. Although often the modality of the experience will
match the modality of the stimulus, organ and processing, it need not. These can come
apart in interesting ways.18 Second, there are examples in which the nature of an
experience had in one modality is affected by processing in another modality—typically in
cases labelled as “cross-modal illusions”.19 For example, in the McGurk effect when an
auditory stimulus—a /ba/ sound—is heard alone, it is typically reported accurately as a
/ba/ sound. But when it is heard whilst looking at lips making movements that would
produce a /ga/ sound, then people typically report hearing a /da/ sound instead (McGurk &
MacDonald, 1976). Their auditory experience of the /da/ sound has as a causal origin both
auditory and visual stimuli, sensory organs, and processing. Another example is the sound-
induced illusory flash experience. When one flash is presented together with two tones,
subjects frequently reported that they saw two flashes (Shams, Kamitani, & Shimojo, 2000).
In this example, at least one of the visual experiences of the flash had both auditory and
visual stimuli, sensory organs, and processing. There are many other such cross-modal
illusions. Third, there are clear cases in which stimuli, sensory organ activation, and
processing all belonging to the same modality cause conscious states other than perceptual
experiences. For example, on seeing something or hearing something, or both, one might
become incredibly sad, or happy, or angry. Emotions are not perceptual experiences but
they are frequently caused by perceptual stimuli, sensory organ activation, and
processing. Thoughts beliefs, desires, and volitions can be caused by perceptual stimuli,
sensory organ activation, and processing. Likewise, if there are any examples of type 1
blindsight, or any form of unconscious perception such as that apparently caused by
masking, then there will be examples of conscious thoughts involved in guessing that are
not perceptual experiences. In short, one cannot argue that the modality of the stimulus,
the sensory organ, and the existence of perceptual processing, entails that a subsequent
conscious state is a perceptual experience of one modality or another. Nor can one even
determine that it will be a perceptual experience, rather than some other kind of mental
state. Thus, the argument just considered for the conclusion that the conscious mental
state of those with type 2 blindsight is not sound. In contrast to Overgaard and Grünbaum
(2011), Brogaard (2011, 2012) argues that, based on the evidence to date, there is reason
to believe that those with type 2 blindsight are having thoughts about the world and not
visual experiences. (She in fact thinks that whether or not in the end she is right about
this is an open question that could be settled in the future by some further detailed
study of subjects who are more thoroughly instructed with respect to, and asked about
their own, phenomenal character. However, from now on, I will present her arguments in
favour of the view that those with type 2 blindsight lack visual experience and have
merely conscious thoughts without this qualification.) Brogaard holds that people with
type 2 blindsight have thoughts about the stimulus in response to their guessing about the
way the world is. She says, “Individuals with blindsight can make correct guesses. Guesses
come with a phenomenology, just not the kind normal individuals have when a visual
stimulus is presented to them… it has not been shown that the phenomenal consciousness
blindsight involves is distinctly visual. I suspect that it is not” (2011: 459).
Brogaard’s argument for this is that the proximal cause of a visual experience is the
visual stimulus, the stimulation of the eyes, and visual processing, but this is not the
proximal cause of the conscious state of the type 2 blindsight subject. The cause of the
conscious state of those with type 2 blindsight includes the visual stimulus, the
stimulation of the eyes, and visual processing, but it has other causes besides. The
conscious state of those with type 2 blindsight has guessing as a proximal cause.
Moreover, the proximal cause of the guessing is not the same as that of visual experience
either. She states, “different mechanisms no doubt underlie guesses and seeings. So
guesses and seeings have different proximate causes” (2012: 596).20 Do we have evidence
that people with type 2 blindsight only have the conscious state they report when they
make guesses, which is what Brogaard’s account requires? One might think that there is
such evidence. After all, in some cases outlined above, it is only when subjects were
asked to guess what was in front of them that they reported that they had some conscious
state (and even then only when they were asked whether they had some conscious state using
the four-point scale, rather than when asked simply to state whether or not they were
conscious of the stimulus). However, it is unclear whether Riddochs’ patients only
responded that they were aware of movement when asked to guess or whether they
spontaneously reported it. And the same seems true of GY—although admittedly his case
history is complex. However, even if guessing was not required, that does not stop the
subjects in question simply having spontaneous thoughts—as opposed to visual experiences—
about their situation. Thus, although Brogaard’s account requires guessing, a very similar
one that requires only thoughts does not require the evidence about guessing to turn out
one way rather than another. Moreover, even if it turned out that subjects did only have
the conscious mental state when they guessed, this does not guarantee that their conscious
mental state is a though. It could be that they have conscious visual experiences and that
guessing is required in order for the people to have those conscious visual experiences.
For example, it could be that in order to have a visual experience, people with type 2
blindsight have to focus their attention in a certain way, and that this is facilitated by
guessing. This is just one suggestion; there may be others that could explain why the
subjects only had a visual experience when they guessed. In short, I don’t see that we
have good evidence that guessing is the proximal stimulus of the conscious state that
people with type 2 blindsight report, and even if it were, that is not enough to show that
those people are not having visual experiences. A second argument is used by Brogaard to
suggest that those with type 2 blindsight are having conscious thoughts rather than having
visual experiences. Speaking of those who report awareness of movement, she states, “even
if a stimulus perhaps does give rise to an experience with a ‘‘clear’’ phenomenology, this
does not provide any evidence of visual awareness of color, shape, or location” (2011:
458), and “blindsighters lack the sort of distinctly visual awareness that includes a
purely qualitative color phenomenology” (2011: 459). Those attributes, she implies, are
necessary for having a visual experience, and because subjects lack them, they are not
having visual experience and are only having conscious thoughts about the stimuli.21 As
stated briefly above, it is not clear whether those subjects who are aware of movement are
aware of colour. One problem is that those who are reporting on the experiences sometimes
say that the subjects were not aware of the colour properties of the stimulus. However,
while it is clear that subjects can’t tell what colour things are in the world, it is not
so obvious whether they experience the world as being some colour or other—even if it does
not have that colour. On the one hand, it seems as if the conscious awareness reported is
sometimes of a dark shadow moving against a darker background. This would be an experience
of: colour: dark grey and black form: an indeterminate shadowy shape, and movement: from
one direction to another. We can certainly have visual experiences like those. If we get
people reporting awareness of those features, then a crucial premise of Brogaard’s
argument is false and she lacks a good reason to deny visual experience to people who have
such awareness.22 However, on the other hand, there is reason to think that the experience
is even more minimal—at least in some subjects. This would be an experience of: movement:
from one direction to another form: an experience of an area lacking clear boundaries Why
would one think this? GY and the patients of Riddoch say that their experience is somewhat
like looking at a shadow. But they don’t straightforwardly say that it is like looking at
a dark shadow moving on a dark background. It is as if subjects are gesturing to something
that is not quite like a shadow. When it was pointed out to GY that he had changed his
description from having a visual experience of a shadow (1980) to just having a feeling
(1994), he said he was using language that he thought the sighted would understand by
mentioning shadows. In 1996 “he described his experience as that of ‘a black shadow moving
on a black background’, adding that ‘shadow is the nearest I can get to putting it into
words so that people can understand” (Zeki & ffytche, 1998: 30). This provides reason to
think that some subjects are having very minimal visual experiences: movement without
colour and rather indeterminate form. As we have seen, it is very hard to determine what
the conscious mental states of people with type 2 blindsight are like. But let us suppose,
as Brogaard does—and as we have seen there is some, although not conclusive, evidence to
suppose—that those with type 2 blindsight (or at least some people with type 2 blindsight)
do have awareness of movement and indeterminate form without colour. Is Brogaard right to
think that this is good reason to think that those with this condition lack visual
experiences and hence lack visual phenomenology? I will investigate this claim by
considering whether there could be other minimal visual experiences of movement or form
without colour. In other words, what I want to do is to investigate whether the following
claim about an alleged structural feature of experience, mentioned in section one above,
is true: Necessarily, visual experiences represent colour. Brogaard’s argument requires
that it is. But as we have seen it is exceptionally difficult to establish the existence
of any structural features of experience. What evidence is there that this claim about an
alleged structural feature of experience is true? As I explained in section one, Aristotle
said that sight can be defined as the perception of colour. (See Sorabji (1971) for a
clear commentary on this point focusing on Aristotle’s De Anima, Book II, chapters 4 and
6. Sorabji claims that for Aristotle, this claim is not put forward as a truth that holds
in all possible worlds, but that people may consider that it does.) Sorabji goes on to say
that if one holds this view one should go on to say that there can be no visual experience
without experience of colour. Size, shape, and movement are visually experienced in virtue
of experiencing coloured things. Other philosophers have echoed this thought. Pete Mandik,
for example, considers the question, “Can there be a visual experience devoid of both
color phenomenology and black-and-white phenomenology?” (2014: 225) and answers “While
I’ve not conducted anything remotely resembling a formal survey, I’m pretty confident that
most philosophers of mind will answer ‘no’” (2014: 228).23 John Hyman, who cites both
Aristotle and James Clerk Maxwell as inspiration, says: colours, like smells and tastes,
are basic properties, relative to the sense with which we perceive them. In other words,
whatever else we perceive by the sense of smell–for example, that a fruit is rotten or
that a child is ill— we perceive by smelling smells; whatever else we perceive by taste we
perceive by tasting tastes; and whatever else we perceive by sight, we perceive by seeing
colors—including the achromatic colors, of course. For example, I cannot see the shape of
a banana except by seeing its spatial boundaries, however fleeting and uncertain this
experience may be, And I cannot see its spatial boundaries except by seeing the
differences of color that make it visibly distinct from its surroundings. That is why, as
James Clerk Maxwell pointed out, all vision is color vision (Hyman, 2006: 18). But is it?
Surprisingly little evidence is garnered by those who state that it is. Usually it is
stated in the manner that Hyman and Brogaard state it: as a fact; and any backing is given
by citing Aristotle, Maxwell and other luminaries in an argument from authority. I suspect
that the alleged fact is taken to be obvious based on repeated introspections of only
visual experiences that are of coloured things. However, as I argued in section one, this
is not good evidence in support of their being such structural features of experience. In
the next section, I consider evidence that we might have against colour being a necessary
feature of visual experience—that is against colour being a structural feature of visual
experience. I will begin by considering the nature of sensory substitution. I will argue
that there are two plausible interpretations of subjects with congential blindness using
tactile visual sensory substitution. One interpretation is that they are not having any
new perceptual experiences. The other is that they are having new visual experiences of
distal form that are not experiences of colour. If the latter interpretation were true, it
would show that colour is not a structural feature of visual experience. However,
unfortunately, the interpretation that they are not having new visual experiences cannot
be completely ruled out. I will then consider the cases of an achromatopsic who can
experience distal form created by chromatic boundaries alone, phantom contours, and amodal
completion. I argue that these provide evidence of visual experience of distal form and
movement with no differences in colour, luminance or texture, but without the complete
lack of these. Such experiences provide an alternative explanation of type 2 blindsight
and their existence lends support to the idea that there could be visual experiences in
the absence of experience of colour. This evidence undermines Brogaard’s second argument
in favour of the conclusion that people with type 2 blindsight are not having visual
experiences and it should be rejected.

<h>IS COLOUR A STRUCTURAL FEATURE OF VISUAL EXPERIENCE?</h>
----------------------------------------------------

Do we have any evidence of the existence of visual experiences that lack colour? We do.
Consider, first, sensory substitution in which one sense is used to try to replace
another. In cases of sensory substitution attempts are made to deliver information to a
subject via a sense that does not usually deliver that information. Consider a particular
kind of sensory substitution: tactile-visual sensory substitution (TVSS).24 A camera
produces a black and white picture of the world. This image drives a series of pins
arranged in a grid that correspond to the image. The grid is placed against an area of a
subject’s skin, such as the back or the stomach. The white areas of the image make the
pins in the corresponding area of the grid push forward into and/or vibrate against the
skin of the subject. After a few hours of practice in which subjects were able to move the
camera and receive feedback on what the camera was detecting—for example by the
experimenter telling them and by the subject feeling what the camera was pointed
at—subjects could recognise a range of common objects, point accurately to objects in
space, and judge their distance and absolute size. After about thirty hours they could
make complex pattern discriminations, recognise the faces of members of laboratory staff,
and display a looming response when the camera lens was zoomed. Subjects’ reports about
their experience indicate that initially they are only aware of the tactile
stimulus/tactile experience. Then, after practice, they report experiencing stable objects
out in the world in front of them, not the tactile stimulus/experience (although they can
pay attention to the tactile stimulation if they want and have the tactile experience).
Thus, it is said that subjects report their experience in quasi-visual terms. (Bach-y-
Rita, 1972, and Guarniero, 1974). One question to ask about the nature of the subjects’
mental lives after they have practiced using the device is whether they come to have a new
sensory experience. When subjects report a quasi-visual experience are they reporting some
new kind of experience—visual or tactile or otherwise—or are they merely reporting new
(often accurate) judgments that they can now make about the world based on ordinary
tactile experiences caused by the pins? This question is, noticeably, rather similar to
the one that we are asking with respect to those people with type 2 blindsight: are
subjects having a perceptual experience or are they just making judgments? I will briefly
review the evidence in the case of sensory substitution. A distinctive new quasi-visual
experience is reported in many instances of sensory substitution.25 Sensory substitution
subjects more readily and consistently attest to a new experience than do people with type
2 blindsight. But how reliable are these reports? There is, unfortunately no objective
test to see if someone is reporting accurately. Moreover, there is reason to think that
reports about perceptual experience are sometimes not reliable. Consider the fact that
there is disagreement even in ordinary cases of perception as to the nature of experience.
For example, there have been centuries of philosophical disagreement about whether visual
experience is two-dimensional or three-dimensional. Another contemporary example is the
debate about how rich perceptual experience is—that is in how much detail does it
represents the world.26 Returning to the case of sensory substitution, the reports about
experiences when using sensory substitution vary quite dramatically. Some people report
vivid colour experiences, some report two-dimensional experience and some three-
dimensional experience. Other people don’t obviously report experience at all. On the one
hand, this might lead one to doubt that we can trust such reports. However, on the other
hand, the disagreement may occur because the experiences or conscious states had by
different subjects are actually different. This would be explained by the fact that
different sorts of subjects have trained on sensory substitution devices: sighted, late
blind, early blind, and congenitally blind people. Moreover, subjects have undergone
different training regimes, most noticeably in the length of the training and in the
degree of immersion in everyday life of the use of the device. In addition, the motivation
of subjects has been markedly different. Some subjects greatly enjoy the use of the device
and want to use it. Others do not like it and do not want to use it. There may be other
differences, perhaps innate ones, between different subjects. This might mean that some
subjects have new perceptual experiences and some do not. In any case, it is clear that we
can’t take introspective reports as straightforward evidence in favour of the existence of
new perceptual experiences. As with the case of type 2 blindsight, one cannot look to
brain imaging to establish whether people using TVSS are having new perceptual
experiences. This is because we would have to be confident that any correlations that had
been noted between brain activity and perceptual experience were reflective of all
instances of perceptual experience. However, cases such as sensory substitution and type 2
blindsight precisely question that. In the case of sensory substitution in particular,
there has been much speculation that practice with the substitution device might change
the functional role of different parts of the brain, rendering prior apparent correlations
otiose. Besides subjective reports and brain imaging, other evidence has been cited in
favour of the proposition that those using TVSS devices are having perceptual experience.
One piece of evidence is the “looming” response displayed by subjects. When, unbeknown to
subjects, experimenters zoomed the camera lens, subjects displayed the reflex action of
backing away from something looming towards them. It is claimed that displaying this fast
and automatic response attests to fast and automatic processing of the signal, which it is
further claimed, is a sign of perceptual processing. Hence, it is argued, subjects have a
quasi-visual experience of something rushing towards them. This evidence certainly tells
prima facie in favour of subjects having quasi-visual experiences; however, an opponent
could argue that there could be fast and automatic inferences being made. Perhaps subjects
can make fast and automatic inferences in light of their training that ordinary subjects
cannot, and hence do not have quasi-visual experiences—they just have a thought that
something is looming towards them. In addition, an opponent could point out that often
recognition of objects by subjects using TVSS takes a relatively long time, effort, and
attention. For example, a good object recognition performance might consist in a subject
identifying an object in ten or more seconds. This is clearly unlike ordinary vision.
Another piece of evidence about whether subjects are having a visual experience that
should be considered is the fact that blind people report forming new perceptual concepts
such as parallax, shadows and interposition of objects after training with TVSS. Someone
might try to argue that, as the blind didn’t form these concepts before, it must be that
they can do so now because they are having a new perceptual experience. However, one might
think that the blind form these new concepts on account of inferences and judgments that
they learn to make on the basis of tactile experiences. So while this evidence may also
prima facie tell in favour of the idea that subjects are having quasi-visual experiences,
it is not conclusive. Finally, one can re-create persisting illusory visual effects using
TVSS devices. One can create the Muller-Lyer illusion and the waterfall illusion in
subjects using TVSS. Moreover, one can re-create these illusions when the subject knows
the effect is illusory. This is often taken to be a key sign of perceptual experience—that
it can persist in the face of conclusive counter-evidence—while belief should disappear.
However, one can imagine a thought, judgment or belief that it seems as if the world is a
certain way persisting in a subject when the subject knows that it is not that way.
Thinking, judging or believing that things seem a certain way is compatible with knowledge
that the world is not that way. Thus, one could think that subjects had such thoughts,
judgments or beliefs, rather than quasi-visual experiences. So again, while suggestive,
this evidence is inconclusive. In summary, showing that subjects do have a new perceptual
experience, rather than making fast automatic inferences is a real challenge. At the
moment, we don’t have a clear answer; however, in my opinion, the weight of the evidence
points towards the conclusion that, at least in some cases, subjects have a new quasi-
visual experience. Although I have by no means shown it to be true, let us suppose that
some subjects do have a new quasi-visual experience. It is worth doing this to reflect on
what the nature of that experience would be. Do such experiences represent colour? It is
tempting to think that colour—including black, white and grey—is not represented: for
subjects only receive pressure stimuli, not chromatic or light stimuli. And even though
the pressure stimuli are driven by a camera detecting light and producing black and white
images, subjects need not know whether pressure corresponds to blackness or whether it
corresponds to whiteness. So how would they, or their brains, know which colour to assign
to an object? In particular, it is tempting to think that a congenitally blind person
would not have experiences of colour. One might think that a non-congenitally blind
person, or their brain, generates experiences of colour on account of previous chromatic
experiences and knowledge of colour that they have. They might assign black or white
colours to objects drawing on their colour knowledge or, simply, arbitrarily. Or they
might assign chromatic colour. For example, if a subject saw a banana shape, their memory
of previous yellow bananas might render the banana that they experience yellow. Ward and
Meijer (2010) provide evidence that this does happen in some cases of sensory
substitution. However, as congenitally blind people have never experienced colour, this
method of colour entering quasi-visual experience cannot be what happens in them. Suppose
therefore that congenitally blind people don’t experience colour when using TVSS. Could
they be having quasi-visual experiences—quasi-visual because they are experiences of form
at a distance from the body—that don’t involve experiencing colour? To assess this further
let’s think about bat echo-location. One way that bats perceive without using their eyes
is to send out a high frequency ‘chirrup’ and listen for the returning echo. Using this
sense, bats can detect 3-D objects at a distance from their body. Doing this allows them
to negotiate through their environment in the dark, quickly dodging obstacles such as tree
trunks and branches, and skillfully catching moths. Clearly bats don’t detect colour—for
they are not making use of wavelengths of light—but they do detect form. In virtue of what
property do bats experience form? Perhaps bats experience distal form by experiencing
sound-reflectance properties. After all, they are detecting form using sound-reflectance
properties. If this were the case, then the experience of colour is not necessary in order
to experience distal form. But in experiencing distal form does one need to experience
some other quality or other? Or could one have a “pure” experience of distal form
alone—without experiencing any other quality? If one must experience distal form by
experiencing some quality or other, what quality do congenitally blind people using the
TVSS experience? One might suppose that they experience light reflectance in the form of
luminance—after all it is light that is driving the camera’s responses and hence
ultimately the tactile stimulus on the congenitally blind person’s skin. However,
congenitally blind people using TVSS need not know what is driving the TVSS. Indeed, we
could have built a device where the pins were not driven by camera, but by an echolocatory
device. We could set things up so that a congenitally blind person would not be in a
position to know whether it is a light sensitive camera that is gathering the relevant
information about distal form or whether is an echo-location device that is doing so.
Given this, there is reason to believe that they would not be experiencing distal form in
virtue of experiencing light-reflectance or luminance. Another suggestion is that
congenitally blind TVSS users might be experiencing distal form in virtue of experiencing
the pressure that they feel on their skin. One might think this because to some extent
there is reason to say that the proximal stimulus acting on the subject is pressure. (I
say, “to some extent” because one could make a case that if light is driving the camera
then that is the proximal stimulus. Whether pressure or light should be held to be the
proximal stimulus is not obvious.) One reason to resist the thought that congenitally
blind TVSS users are experiencing distal form in virtue of experiencing the pressure that
they feel on their skin is because experienced users of TVSS say that they no longer have
tactile experiences of pressure, or at least not ones that they notice. But they do have
experiences—and experiences that they notice—of distal form. To make things difficult for
us, however, let us suppose, that the users are experiencing both pressure and distal
form. (So let us suppose that when they report the absence of such experience they do so
only because they are not attending to that experience, not because they are not having
that experience.) In one sense, one could say that the users are experiencing distal form
in virtue of experiencing pressure because if one took away the experience of the pressure
(say by taking away the pressure on their skin) then the subjects would not have the
experiences of distal form. However, this is true because the experiences of pressure
cause the experiences of distal form. However, when asking whether TVSS users are
experiencing distal form in virtue of experiencing the pressure I do not have a causal
reading of “in virtue of” in mind here. When I say “in virtue of” I have a phenomenal
relationship in mind. To illustrate what this is, consider the following example. Suppose
that whenever one had an experience of a red circle, that experience caused one to have an
experience of a blue square. In the phenomenal sense that I intend, one does not
experience the rectangle in virtue of experiencing the redness—even though the experience
of the redness is a cause of the experience of the rectangle. One experiences the
rectangle, in the phenomenal sense, in virtue of experiencing the blueness. The form of
the rectangle is experienced to be constituted by the blueness. This is the phenomenal
sense of “in virtue of” that I have in mind. Here are some other examples of the in virtue
of relation obtaining in the phenomenal sense: one auditorily experiences the pitch of a
note in virtue of experiencing the volume of the note, one tactually experiences the
roundness of a coin on the palm of one’s hand in virtue of experiencing the pressure
against of the coin against one’s skin. In all these cases where one thing is experienced
in virtue of (in the phenomenal sense) another, the two things are co-located: the
blueness of the rectangle and the form of the rectangle, the pitch of the note and the
volume of the note, the roundness of the coin and the pressure of the coin. The apparent
co-location of qualities would seem to be required for one to be experienced in virtue of
(in the phenomenological sense) another. Therefore, I don’t think that it can be true that
the congenitally blind users are experiencing distal form in virtue of experiencing
pressure. The pressure that is felt is experienced as located on their skin and not at a
location in front of the body where the distal objects with their forms are experienced to
be. How could the form that is experienced to be at one location be experienced to be
constituted by a quality experienced at another location? It could not. If light-
reflectance, luminance and pressure are not good candidates for what a congenitally blind
person would experience when they experience distal form, and if there are no other good
candidate qualities, this should lead us to think that experiences of distal form, without
experience of any other quality, are possible. Of course we should remember that we have
not ruled out completely the idea that the congenitally blind are not having perceptual
experiences when using the TVSS. However, there is some reason to suppose that they are,
and if we do suppose it then we have good reason to think that, as there is no good
candidate for the property in virtue of which (in the phenomenal sense) they experience
distal form, then there is no such property, and none is required. I will call such
experiences experiences of “pure distal form”. If there can be such perceptual
experiences, then showing that people with type 2 blindsight lack experiences of colour
does not entail that they lack perceptual experiences of distal form. I turn now to
consider three other cases: a special case of achromatopsia, the phantom contours created
by Rogers-Ramachandran and Ramachandran (1998), and instances of amodal completion. The
first of these cases is like the case of sensory substitution because there are two
competing accounts of the nature of the conscious state that the subject is having, which
we cannot settle definitively. The other two cases are, however, more clear-cut. All three
of these cases differ from the case of sensory substitution because, unlike it, they do
not provide examples of experiences of pure distal form. What they do provide is examples
of experiences of distal form with no difference in colour—including black, white and
greys—or texture. These are interesting cases that not only lend weight to the idea that
there could be cases of perceptual experiences of pure distal form, they also provide us
with another plausible account of the nature of the experiences of people with type 2
blindsight. People with achromatopsia cannot see colour. This is tested for by the
Farnsworth–Munsell 100-Hue Test, in which subjects are asked to place 100 patches of
different hues in order (Farnsworth, 1943). Moreover achromatopsics can neither name nor
match colours. They can detect luminance, and so can perceive many distal forms in virtue
of differences in luminance. This condition comes in two forms: cerebral achromatopsia (in
which an area of cortex that seems necessary for the experience of colour is lost) and
retinal monochromatism (in which pigments (blue-cone monochromatism) or cell-classes (rod
monochromatism) fail to be expressed in the retina). There is no wavelength specific input
to the visual system in retinal monochromats. In contrast, cerebral achrmoatopsics have a
normal set of wavelength selective inputs to the visual system. A particular subject with
cerebral achromatopsia, MS, has been studied by Kentridge, Heywood, and Cowey (2004).
Despite being achromatopsic, he could detect isoluminant borders of different chromatic
composition. When a shape was placed against an isoluminant background, which differed
only in chromaticity, MS, could detect it. In other words, he could experience distal form
(an edge) but not because he was detecting any changes or difference in luminance. These
are very odd results. MS is sensitive to a pure chromatic difference despite, in all other
respects, being colour blind. This raises interesting questions about MS’s phenomenology
when detecting such edges. Kentridge et al. describe MS’s behaviour and experience when
looking at isoluminant edges thus: A world without background-invariant colour constancy
for MS is not one of ever-changing unstable colour, it is one in which colour is absent
and meaningless. This is not to say, however, that discrimination of local contrast is
unconscious. For all but the most difficult discriminations MS either deliberated at
length over his decisions or made them unhesitatingly. Only on very rare occasions did he
need to be prompted to simply make a guess. The neural response to local chromatic
contrast therefore produces a percept which is acted upon consciously (1994: 829).27
Suppose that we thought that because MS is achromatopsic he only sees black and white and
shades of grey. This is a common view of what achromatopisic vision is like.28 (However,
this view of achromatopsic vision can be challenged as I will discuss in more detail
below.) Because the border MS can detect is defined chromatically and not by luminance, we
have reason to think that there is not a luminance difference—hence that MS will not
experience it as defined by black, white or grey. But, at the same time, MS is an achromat
and hence cannot order, discriminate, or name colours. So it is tempting to think that the
border cannot be experienced by MS in virtue of his experiencing different chromatic
colours. If MS doesn’t experience the border in virtue of differences in shades of black,
white or gray, and he doesn’t experience chromatic colours, then one might think that MS
must experience distal form without experiencing any difference in colour at all—chromatic
or achromatic. In other words, one might postulate that MS experiences a uniform
achromatic colour, yet some distal form within that achromatic field. If that is right,
then the case of MS would provide us with an example of a visual experience of distal form
with no difference in experience of (chromatic or achromatic) colour. Such an experience
is not an experience of pure distal form, which is an experience of distal form without
any experience of colour. It is an experience of distal form whilst having an entirely
uniform experience of colour.29 If this is a correct description of the experience, then
this is not exactly what we are looking for: an experience of distal form with no
experience of colour. However, it would be something very close: an experience of distal
form—an edge or boundary at a distance in front of one—with no difference in experienced
colour or texture forming the boundary or existing across the experienced boundary.
Nonetheless, their existence tells in favour of the idea that there could be experiences
of pure distal form without colour for these experiences show that one needn’t experience
distal form in virtue (in the phenomenal sense) of experiencing colour boundaries. This is
also a property of experiences of pure distal form. Moreover, the existence of this kind
of experience suggests a new account of the nature of the experience of those with type 2
blindsight for moving stimuli. Recall that GY reported that his experience was like “black
on black” like “a mouse under a blanket” (Beckers & Zeki, 1995: 56, reported by Stoerig &
Barth, 2001: 582). Perhaps GY experienced a uniformly black or uniformly dark grey
achromatic surface and yet experienced a moving form or a moving edge across it, in a
manner similar to the way in which we are supposing MS experiences distal form. However,
one might question this account of MS’s experience. I said above that some people question
the traditional view that achromats have experiences of the qualities of black, white and
grey that humans with ordinary vision do. Akins (2014) argues that they do not. Similarly,
when it comes to people with less severe forms of colour blindness—dichromats—the
traditional view is that they lack experiences of red and green, and only experience the
world in shades of yellow, blue and the greys. (See Broakes, 2010.) Broakes’ own view is
that they experience many more colours than yellows, blues and greys, and perhaps even
experience all of the colours that normal observers do just not in as many sitations as
those with normal colour vision. However, contrary to the traditional view and Broakes’
view, others hold that dichromats experience none of the colours that those with normal
colour vision experience. (See Byrne and Hilbert (2010) for arguments for two different
versions of this view.) The reason that people have for holding that achromats and
dichromats do not have any of the same sort of colour experiences compared to those with
ordinary human colour vision is that the workings of their luminance and/or chromatic
colour visual systems is so unlike that of those with ordinary human colour vision that it
is reasonable to believe that they just have very different sorts of experience of the
qualities of the surfaces of objects. Let us agree to call those qualities—chromatic or
achromatic—“alien colours”, as Byrne and Hilbert do.30 If it is right to think that those
with different luminance and chromatic visual systems, compared to those of normal humans,
experience alien colours (both chromatic and nonchromatic alien colours), then we should
think that MS experiences alien colours. If that is right, then it opens up an account of
his experience that is different to that considered above. Perhaps MS experiences patches
of what those with normal human colour vision would experience as being different
chromatic but isoluminant colours as having different alien colours. It would still be
possible for MS to be unable to name, discriminate, or order what those with normal human
vision would call different colours, in the way that normal humans do, because his visual
system cannot in general pull apart luminance from chromaticity in the way that the visual
systems of people with normal human vision can. If this interpretation of MS is correct
then, in one sense, MS is experiencing distal form without colour—ordinary non-alien
colour—but, in another sense, he is experiencing distal form with colour—alien colour.
Whichever way one thinks it is best to describe the case, it would not be a case of
experience of distal form without a difference in some quality or other.31 Deciding
between these two hypothesis—that MS experiences boundaries but not in virtue of
differences in colour or that MS experiences different in alien colours that define the
boundaries—is very difficult. Recall that MS can accurately detect a shape on a background
that has the same isoluminance, and that differs only chromatically. However, in addition,
given three such shapes on such a background, one of which has a different colour but the
same luminance from the others, he can tell the odd one out. One might think that this
means that MS must experience a difference in the surface qualities of the different
shapes, and therefore that the alien colour hypothesis must be true. However, there is an
alternative explanation. It could be that the boundaries between the shapes and their
backgrounds are more or less distinct in the different chromatic cases and so the
boundaries appear different to MS in some respects, and that it is this boundary
information, rather than difference in surface appearance, that MS is relying on to tell
the odd one out. A striking finding is that this ability to tell the chromatic odd one out
is thwarted when the shapes are surrounded by a thick black border so that there is no
direct contiguity between the colour of the shapes that have to be discriminated and their
background (because the background and the shapes are each contiguous to the black
border). This might tempt one into thinking that MS cannot be experiencing the shapes as
having different alien colours. For, if he was, why would this difference in alien colour
not persist in the face of the addition of the black boundaries, and allow him to do the
task? However, this fact is not decisive. When MS had to pick out the odd one out among
three shapes against a uniform achromatic background, all of which had the same
chromaticity (they were gray on a gray background), where one of the shapes varied in
luminance from the other two shapes, he could, as one would expect, do so. However, when
the shapes were surrounded by a black border he could not do the task. This is rather
surprising. If one followed the logic of the reasoning in the above paragraph then one
would be forced to say that MS doesn’t experience differences in luminance either. If this
is right, then perhaps MS only experiences edges and no surface qualities at all—neither
chromatic or achromatic! Whether that tallies with his ability to discriminate luminance
on other occasions is unclear. It certainly seems as if MS has difficulties comparing
luminance and chromatic values between two areas that are not contiguous. This is
compatible with him experiencing alien colours, yet only being able to compare and
contrast them when particular boundary conditions obtain. Therefore, it is hard to know
how to interpret the results of the experiments where there was the addition of the black
border in the chromatic case. Finally, Kentridge et al. (2004) point out that the
Farnsworth–Munsell 100-Hue Test consists of colours embedded in, and surrounded by, black
casings which resemble the black borders used in their experiments described above. Given
that the above experiments show that the addition of black borders impedes discovery of
the chromatic differences that MS can detect, further experimentation on MS would be
desirable using methods that employ sorting tasks where the colours can be compared in
conditions where their borders are contiguous. For all we know, MS might consistently sort
the colours consistently and in line with some alien colour scheme in those conditions. To
summarise the discussion of MS, I have argued that there is one interpretation of MS
according to which he has experiences of distal form without any difference in colour
(chromatic, achromatic or alien), and another according to which he does not—he has
experiences of form in virtue of alien colours. And the former interpretation has two
subvarients. One of these is that MS can experience distal form while perceiving uniform
achromatic colour. The other is that MS can experience distal form while perceive no
chromatic or achromatic colour at all. Deciding between these accounts is in my opinion
impossible at present. It would be interesting to try to probe the nature of MS’s
phenomenal character in more detail. One could ask him to compare a chromatic isoluminant
boundary to an achromatic non-isoluminant one. One could also describe the two different
accounts of his visual experience proposed here to him and ask him which, if any, he would
be prepared to endorse. And then one could ask him to compare his experience of a
chromatic isoluminant boundary to that of the “phantom contour” experiences and
experiences of amodal complation described below. Nevertheless, at present, one cannot
conclusively say that MS provides us with an example of experience of distal form
perception without a difference in colour, but some plausible accounts of him do. I turn
now to consider two other cases: the phantom contours created by Rogers-Ramachandran and
Ramachandran (1998), and instances of amodal completion. Unlike the cases of MS and
sensory substitution where there were two different accounts of the nature of the
conscious state being had which we could not decide between, these cases are ones where we
can establish that subjects are having perceptual experiences and what their nature is.
Neither case is a case of an experience of pure distal form. But they are examples of
experiences of distal form with no difference in colour—including black, white and
greys—or texture. Rogers-Ramachandran and Ramachandran (1998) created a stimulus that
consisted of a uniformly grey background. On one side of the background were white dots.
On the other side were black dots, as shown in Fig. 1. The dots flickered in counterphase,
so that when the white dots changed to black, simultaneously the black dots changed to
white. When the frequency of the changes of the colour of the spots was low (less than 7
Hz), subjects could tell that the spots on one half of the stimulus were in counterphase
with those on the other half. And, unsurprisingly, they could indicate where the boundary
was between the out of phase spots. However, when the frequency of the flicker of the
spots increased to 15 Hz subjects were no longer able to tell that the spots were
flickering in counterphase. Thus, phenomenally one would think that the stimulus would
have looked to them to be uniform. However, subjects experienced a “phantom contour” where
the border was between the spots that were flickering in counterphase. Subjects could also
experience movement of the phantom boundary when the stimulus was changed so that which
spots were in counterphase was altered. Rogers-Ramachandran and Ramachandran state, “We
were quite surprised, therefore, to observe a distinctly visible horizontal border
separating the two fields, i.e., one sees a texture border defined by indistinguishable
elements. We call this paradoxical percept a phantom contour” (1998: 71). If the spots in
question were red and green, rather than black and white, the boundary could be detected
in similar conditions, so long as the spots were not isoluminant. The spots had to have
different luminance values in order for the effect to occur. Rogers-Ramachandran and
Ramachandran claim: Taken collectively, these findings indicate two different systems
exist in human vision. One of these is a fast contour-extracting system that can signal
contours but not their polarity and the other is a slow system that signals surface
qualities. The contour system signals the presence of a border but cannot tell which side
of the border is black and which side is white. That is, it can detect that there is a
difference between the two sides and also follow high flicker rates, but it cannot signal
the direction or the “sign” of the difference. The surface system, on the other hand, can
potentially signal the surface characteristics (color and luminance) but at 15 Hz, the
speed of flicker is too high for it to follow. Thus, the phantom contour stimulus seems to
isolate or selectively activate the fast boundary extracting system. So what is perceived
is the output of the contour system alone, a contour defined by two surfaces which look
identical. (1998: 74).32 If Rogers-Ramachandran and Ramachandran’s report is correct then
not only does the brain register that there is a boundary without registering which
properties lie on either side of it, this information is also reflected in the nature of
the experience had when looking at the stimulus. One experiences a uniform surface (albeit
it one with apparently uniformly flickering dots on it) yet one experiences some boundary.
Rogers-Ramachandran and Ramachandran say the border is experienced in virtue of
“indistinguishable elements” (1998: 71) that “look identical” (1998: 74). Given that, it
would be arbitrary which side of the boundary was signaled to be light and which dark, and
given that the brain cannot discriminate the flickering dots, there is good reason to
think that their description of the experience is correct. In addition to one
interpretation of the case of MS, phantom contours provide another example of an
experience of distal form with no difference in experienced colour or texture forming the
boundary or existing across the boundary. As mentioned previously, such cases lend weight
to the supposition that there could be experiences of pure distal form without colour, for
in these experiences it is not in virtue of experiencing colour boundaries that one
experiences form. Thus they lend weight to the supposition that colour is not a structural
feature of experience. In turn this backs up the idea that showing that people with type 2
blindsight lack experiences of colour does not show that they lack visual experience.
Moreover, as also mentioned previously, the existence of this kind of experience suggests
that one account of the experiences of those with type 2 blindsight could be accurate:
that they experience a uniformly black or dark grey background and yet form and movement
within. This case of phantom contours provides evidence not just of form, as the case of
MS does, but of movement perception in such conditions. This is because Rogers-
Ramachandran and Ramachandran altered the location of the phantom contour by altering the
proportion of black to white dots. Subjects reported experiencing the phantom contour
moving across their visual field. Finally, I turn to consider a last case: amodal
completion. In order to explain this example, I will first explain what modal completion
is. Consider the Kanizsa triangle in Fig. 2.33 Ordinary perceivers report experiencing a
bright white equilateral triangle pointing towards the top of the page that is lighter
than the background, and is hence defined by lightness boundaries within experience. That
triangle is experienced as partially occluding another triangle pointing towards the
bottom of the page that is defined by black lines. Three “pacman-like” figures are also
experienced as occluded circles. On close inspection of the figure, one can come to
realise that part of this experience is illusory. There are no lightness boundaries
forming a triangle pointing towards the top of the page. What is important to notice, for
our purposes, is that when one experiences that illusory triangle, one has an experience
as of edges created by a luminance boundary. We know that there are no such luminance
edges and there is not a difference in lightness where there appears to be one; but that
is what we experience. Cases such as this are cases of modal completion because although
the edges that seem to form the upward pointing triangle do not exist, one has a visual
experience that represents such edges in a way that typical visual experiences do: in
virtue of a colour, lightness or texture boundary. With the nature of this case of modal
completion firmly in mind, consider now a case of amodal completion. Consider Fig. 3. When
asked, people say that they have a strong sense that it consists in a square that
continues behind an occluding circle—hence, that it seems as if the shapes in Fig. 4 are
present. However, Fig. 3 is perfectly compatible with the shapes shown in either Fig. 5 or
Fig. 6 being present—and hence with a square with a corner removed or with a square with a
jaggy protruding extension to a corner being present—as well as with a square being
present (Michott et al., 1964/1991). The visual experience of Fig. 3, however, does not
consist in experienced boundaries consisting of colour, lightness or texture corresponding
the occluded portion of the square. Yet, nonetheless, it is a square that is reported as
being present. This is a case of amodal completion, and it contrasts with modal completion
in that it occurs when part of an object is experienced as occluded and is reported as
having one of many possible shapes, yet the occluded portion of the object is not
experienced as being defined by colour, lightness or texture boundaries. There are two
different interpretations of amodal completion. One is that such visual experiences are
only of the lines that make up Fig. 3 on the uniform background and that the shape of the
occluded figure is inferred, yielding a judgment, thought or belief that an occluded
square is present. The second interpretation is that the visual experience is of the lines
that make up Fig. 3 on the uniform background and, in addition, the occluded part of the
square is represented in the visual experience. A great deal of psychological research has
gone into determining which interpretation is correct. Michotte, Thines, and Crabbe
(1964/1991) themselves noted that amodal completion occurs despite subjects’
beliefs—indeed knowledge—that the occluded figure is not the way that their experience
tells them it is. For example, if one first sees that a square with a protruding jaggy
corner, as shown in Fig. 6, is present and then it is occluded by a circle, then what is
seen will still be experienced as an occluded square, not an occluded square with a
protruding jaggy corner. Moreover, that experience persists even if a lot of jaggy
protruding cornered squares are experienced. Looking at Fig. 7 should be illustrative.
Likewise, if one draws a broken triangle as in the left-hand side of Fig. 8 and then
places a pencil over it in the manner depicted in the right-hand side of Fig. 8 then one
experiences a completed occluded triangle even when one knows it not to be such. Using a
visual search paradigm, studies have shown conclusively that amodal completion can occur
without focused attention and within the time span associated with early visual processing
(Enns & Rensink, 1998). And, in a study directly measuring cells’ response in nonhuman
primates, neurophysiological data show that “cells as early as V1 have the computational
power to make inferences about the nature of partially invisible forms seen behind
occluding structures” (Sugita, 1999). These results and others are summarised in Wagemans,
Lier and Scholl (2006) and strongly suggest that the occluded parts of objects are
experienced visually—and are not inferred. Further evidence of the genuinely experiential
nature of amodal occlusion phenomena is given by Briscoe (2011). Consider Fig. 9 that is
typically experienced as a number of unconnected two-dimensional forms that lie on the
same two-dimensional plane of depth. When these elements appear to be occluded by the
insertion of oblongs into the picture, as in Fig. 10, the forms previously seen are no
longer experienced as two-dimensional, unconnected, and on the same two-dimensional plane
of depth. They are experienced as connected, three-dimensional pieces that form a three-
dimensional cube. This change in one’s conscious experience provides as clear a
demonstration as one could hope for that changes in one’s experience, rather than thought
or propositional attitudes, are brought about by amodal completion. If this is right, then
in amodal completion we visually experience occluded distal form at a distance from our
bodies but not in virtue of experiencing an edge, border or form that is experienced in
virtue of colour, lightness or texture. Such experiences are therefore very similar to the
experiences of phantom contours that I discussed above. Again, these experiences are not
ones of pure distal form without colour, but experiences of distal form without an
experience of a difference in colour, lightness or texture. Nevertheless, as in the case
of MS and the phantom contours, the existence of these experiences lend weight to the idea
that there could be pure distal experiences of form. This is because, in these
experiences, form is experienced but not in virtue of differences in colour, lightness or
texture. Moreover, they may themselves be the sorts of experience that those with type 2
blindsight have. It would be interesting, and potentially informative, to ask people to
compare and contrast the phenomenal character of their experiences of amodal completion
with their experiences of phantom contours. Similarly, it would be interesting to get MS
to compare his experience of form defined by differently coloured but equiluminous areas
with his experiences of these other phenomena. I have discussed four types of unusual
perceptual experience. I argued that if people trained to use TVSS do have new perceptual
experiences, then the best account of the experience of a trained congenitally blind
person who was using such a device is that they have a perceptual experience of pure
distal form without colour. The case of MS has two interpretations. On one he has a
perceptual experience of distal form in virtue of alien colours. On another he experiences
distal form without experience a difference in colour (chromatic, achromatic, or alien). I
have also argued that the case of phantom contours and amodal completion show that there
can be experiences of distal form without any differences in colour, lightness or texture.
The existence of these experiences lends weight to the suggestion that there could be
perceptual experiences of pure distal form with no experience of colour (including
luminance) or alien colour. Moreover, they suggest another description of the perceptual
experiences of those with type 2 blindsight for moving stimuli: experiences of form and/or
movement within a field of uniform colour, lightness and texture. We therefore have two
plausible candidates for the nature of the perceptual experiences of those with type 2
blindsight: experiences of pure distal form and experiences of distal form without
experience of difference in colour, lightness, or texture (but not a complete lack of
colour, lightness or texture). Recall that Brogaard (2011, 2012) held that there cannot be
visual experiences of pure distal form and hence that we should reject the idea that those
with type 2 blindsight are having perceptual experiences. She holds that we should think
that they are having thoughts instead. I have argued that there is no good reason to
maintain that people with type 2 blindsight cannot be having perceptual experiences. Are
such perceptual experiences visual experiences? One can imagine someone claiming a priori
that for an experience to be visual it must be an experience of colour. But I think that
such a view would merely be stipulative: a linguistic decision taken on no good grounds.
What reason could one have to hold this view, rather than the view that experience of
distal form is sufficient for an experience to be visual? I do not believe that there is
any. One might think that one could appeal to the fact that these experiences are caused
by light, which is the proximal stimulus of vision and caused by the use of the eye, which
is the sensory organ of vision. And to the extent that these are relevant, they point
towards the experience being visual. However, as I have already argued above, the modality
of an experience is not completely determined by facts such as these, as the case of
synaesthetic concurrent experiences show. What is represented by the experience—distal
form—is that which is represented by only visual experiences among the human senses, and
plausibly the phenomenal character of the experience is most like visual experiences. But
are those things enough to make the experience visual? I do not think that there is any
fact of the matter here. I do not have space to argue it here, but as I have argued in
Macpherson (2011a), not only may the distinctions between the sensory modalities be a
matter of degree, the distinctions between kinds of experience may be too. Whether or not
one withholds the epithet of “visual” from such experiences, they are perceptual
experiences and, of all kinds of human experience, most like visual experiences—due to the
fact that they are experiences of distal form, and caused by light stimulating the eyes.
Showing that there is no good reason to rule out that those with type 2 blindsight have
perceptual experiences is the crux of the matter in this paper, not whether they should be
classed as visual perceptual experiences or perceptual experiences in some other modality.
Thus we can resist the idea that we are forced to conclude that those with type 2
blindsight are only having thoughts about movement or distal form, for resisting depends
on showing that they could be having perceptual experiences, not visual experiences per
se.

<h>CONCLUSION</h>
----------

In section four, we saw that people have argued about the nature of the conscious state
that is had by people with type 2 blindsight. I argued that the experimental evidence
available at present does not settle the matter. I then discussed the argument put forward
by Overgaard and Grünbaum (2011) for the conclusion that people with type 2 blindsight
must be having visual experiences and argued that it was not sound. This was because it
relies on the false premise that the conscious state must be a visual experience because
it was caused by a visual stimulus, a visual sensory organ, and early visual processing.
This is false because thoughts, beliefs, and perceptual experiences in non-visual
modalities, can also have those causes. I then examined the argument given by Brogaard
(2011, 2012) for the conclusion that those with type 2 blindsight are having thoughts
based on their guessing what is before them. I argued that we lack good evidence that
guessing is required to produce the conscious state that people with type 2 blindsight
report, and even if it were, that is not enough to show that those people are not having
visual experiences. That is because the guessing might cause the occurrence of those
visual experiences—perhaps by focusing attention or by some other means. Finally, I turned
to address Brogaard’s second argument to the conclusion that those with type 2 blindsight
were having thoughts and not visual experiences. Brogaard’s second argument supposed that
those who were experiencing type 2 blindsight could not be having visual experiences
because they experienced pure distal form, that is form without colour (which I stipulated
to include black, white and grey). I showed that there is a long intellectual tradition of
supposing that visual experiences must represent colour in order to be visual. I noted
that colour was one alleged structural feature of visual experience. I also argued in
section two, that it is very difficult to establish the existence of any given alleged
structural feature of experience and that, just because one has not had an experience that
lacks an alleged structural feature, that is not reason enough to establish that the
alleged structural feature is indeed one. The example of experiences of novel colours was
illustrative. I set out, in section five, to examine the evidence concerning whether there
could be visual experiences in the absence of experience of colour by looking to see if
there were any experiences of pure distal form. I argued that there is some, although not
conclusive, reason to think that perceptual experiences of the congenitally blind using
TVSS might be of this ilk. I also showed that one plausible interpretation of the nature
of the experiences of the achromat MS, when he looks at a form delineated by two
equiluminant areas that are different in chromatic colour, is that they are of pure distal
form. However, there was another interpretation of the nature of the experience of MS that
was at least as plausible, and that did not have this consequence. I suggested that
further investigation of MS would be instructive, in particular, asking him to compare his
experiences of chromatic boundaries with no luminance difference with his experience of
phantom contours and amodal completion. I then showed that the evidence concerning phantom
boundaries and amodal completion clearly shows that there could be perceptual experiences
of distal form and movement with no difference in colour, lightness or texture
differences. And I argued that the existence of such experiences was evidence in favour of
thinking that there can be experiences of pure distal form with no colour, lightness or
texture. This is because, in such experiences, form and movement are not experienced in
virtue of experiencing colour, lightness or texture boundaries. Moreover, I showed that
experience of form and movement, or just movement, with no difference in colour, lightness
or texture, was a second very good candidate for being the sort of experience that people
with type 2 blindsight are having, based on their reports of experiencing darkness and
black shadows (in addition to the experiences already considered or of pure distal form
and/or movement). If I am right and such experiences are possible, then, contra Brogaard,
there is no good reason to doubt that the reports of people with type 2 blindsight could
be accurate descriptions of perceptual experiences. Thus, Brogaard’s reason for holding
that those with type 2 blindsight are not having visual experiences should be rejected. I
discussed whether experiences of pure distal form and experiences of distal form with no
difference in colour or texture should be thought of as visual. I said that they are more
like ordinary visual experiences than experiences in any other modality. Moreover, I
claimed that there is no good reason to deny that such experiences are visual. Denying it
would merely be a stipulative manoeuvre. In any case, what is important is whether there
is any good reason to deny that the conscious states of those with type 2 blindsight are
perceptual experiences, and I have argued that there is not. The matter was only
originally discussed in terms of visual experiences as that modality seemed the most
likely one for the experiences to belong to. Removing Brogaard’s reasons for denying that
people with type 2 blindsight are having perceptual experiences does not establish that
they are doing so. However, it leaves open the possibility that they are. Further
investigation of the phenomenon is clearly called for. In light of the arguments given in
this paper, I suggest that it would be good to give those with type 2 blindsight
experiences of phantom contours and amodal completion in their non-blind visual fields,
and ask them to compare those experiences to the conscious states that they report when
their blind field is stimulated, and to see if they are willing to accept that there is a
phenomenal match—that those experiences are the same subjectively. In conclusion, I have
taken steps forward in the investigation of three alleged structural facts about
experience: the necessary experience of colour in visual experience the necessary
experience of colour in experience of distal form and movement, and the necessary
experience of difference in colour in experience of distal form and movement. I have
provided evidence against each being true. Even if some of these steps turn out to be
small steps forward, that any steps have been taken makes them significant ones, given the
difficulties that attend establishing or dismissing the structural features of experience.


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<ART>The subjective well-being of adults born preterm
================================================

Authors: Alice Winstanley, Michael E. Lamb, Kate Ellis-Davies, Peter Jason Rentfrow
DOI: 10.1016/j.jrp.2015.09.002
Year: 2015  |  Pages: 23-30
ASJC codes: 3200, 3207
Keywords: Hospitalization, Job satisfaction, Life satisfaction, Personality, Preterm birth, Relationship satisfaction, Well-being

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Preterm birth (<37 weeks' gestation) is sometimes associated with poorer outcomes in adulthood (e.g., poorer health, fewer intimate relationships, and lower income). However, few studies have examined how these adults felt about their lives or how personality affected these associations. 11,592 preterm and 51,460 full term adults completed online surveys measuring their subjective well-being (life, relationship and job satisfaction, and health). Adults born preterm reported similar levels of relationship satisfaction, but poorer health, life satisfaction and job satisfaction. Adults who reported having long hospital stays at birth also reported poorer health, life, relationship and job satisfaction, and this poorer well-being appeared to be accounted for, in part, by factors such as their personality.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Outcome studies have demonstrated that preterm birth (before 37 weeks’ gestation) is
associated with poorer health (Cooke, 2004; Hack, 2009; Hack, Cartar, Schluchter, Klein, &
Forrest, 2007; Lindstrom, Lindblad, & Hjern, 2009), reduced likelihood of forming romantic
relationships (Hack, 2009; Moster, Lie, & Markestad, 2008; Wolke, 2011), poorer
educational attainment, and lower salaries (despite equal levels of employment; Cooke,
2004; Hack, 2009; Lindstrom, Winbladh, Haglund, & Hjern, 2007; Moster et al., 2008; Wolke,
2011). Small samples tend to involve rich data collected from individuals over time (often
starting soon after birth) but do not have sufficient power to explore the role of
confounding variables or allow subgroup analyses (Saigal, 2013). In comparison, the large
national register samples allow such analyses and include information about objective
variables such as educational attainment, employment status, health and living situation
(living with a partner, peers or parents; Lindstrom et al., 2009, 2007; Moster et al.,
2008) but not subjective evaluations of these circumstances (Saigal, 2013). In order to
have a sample comparable in size to that of national register samples, which also included
subjective assessments of life, relationship and job satisfaction, we collected data using
an online survey. This method allowed us to collect information from a larger number of
individuals. The resulting sample closely resembled the general population of UK
(Rentfrow, Jokela, & Lamb, 2015), and was large (the subsample studied here included over
60,000 adults) so ensured sufficient power to examine the role of potential covariates and
to compute robust effect sizes. Subjective wellbeing reflects individual beliefs and
feelings and is related to health and social relationships (Diener, 2012). Therefore, the
first aim of this study was to understand the adult sequelae of preterm birth with an
emphasis on subjective accounts of their health, relationships, jobs and lives. Despite
their importance, little is known about the subjective well-being of adults born preterm
(Guyatt & Cook, 1994; Saigal, 2013) although the quality of life experienced by preterm
and full term-born individuals tend to be similar when rated by the individuals rather
than their parents (Cooke, 2004; Hack, 2009; Hack et al., 2007; Roberts et al., 2013;
Saigal & Tyson, 2008; Zwicker & Harris, 2008). Less is known about life satisfaction,
which involves comparing current circumstances with subjective standards set by the
individuals themselves (Diener, Emmons, Larsen, & Griffin, 1985). Adults born small for
gestational age had levels of life satisfaction similar to those of individuals with
normal birthweight in one study (Strauss, 2000), but similar data are not available for
adults born preterm. In terms of health, adults born preterm tend to report poorer health
outcomes than those born at full term. In one study, for example, both male and female
adults born preterm had lower levels of physical functioning, female preterm adults
reported role limitations due to emotional problems, mental health and lack of energy, and
male preterm adults perceived their general health to be poorer (Cooke, 2004). Preterm
adults were also more likely to have chronic conditions (primarily, asthma), be
hospitalized for psychiatric conditions, have a diagnosis of ADHD or autism spectrum
disorder, and be taking prescription medicines (Cooke, 2004; Hack, 2009; Hack et al.,
2007; Johnson & Marlow, 2014; Lindstrom et al., 2009). Therefore, prematurity appears to
be related to poorer objective and self-reported health. However, a sample of 55 adults
born preterm reported slightly better physical health than community norms in a recent
study (although mental health appeared worse than community norms in the sample; Natalucci
et al., 2013). Research on the socio-economic sequelae of prematurity has generally
focused on objective outcomes (for example, relationship or employment status) rather than
how individuals feel about their relationships or jobs. Studies focused on objective
measures have shown that individuals born prematurely are less likely to form romantic
relationships, start co-habiting with partners, find life partners, or become parents
(Hack, 2009; Moster et al., 2008; Wolke, 2011). Cooke (2004) found similar proportions of
preterm and full term adults in intimate relationships and in sexual relationships, but
evidence regarding the effects on relationship satisfaction is less clear-cut.
Relationship satisfaction has not been directly measured in adults born preterm although
adults with very low birthweight reported less attachment-related anxiety than their
normal weight peers (Pyhala et al., 2009). Preterm adolescents reported having fewer
social interactions than full term adolescents, although they were rated equivalently
adequate (Hallin & Stjernqvist, 2011). Furthermore, studies of objective socio-economic
outcomes have demonstrated that preterm adults complete less schooling and leave school
earlier than their peers (Cooke, 2004; Hack, 2009; Lindstrom et al., 2007) and despite
being equally likely to be employed, preterm individuals had lower salaries (Hack, 2009;
Lindstrom et al., 2007; Moster et al., 2008; Wolke, 2011). Because previous work has only
focused on these objective measures of employment, this study asked adults born preterm
about their job satisfaction. The second aim was to understand how other variables
affected the associations between preterm birth and outcomes. Personality may mediate
relations between preterm birth and adult outcomes (Hack, 2009; Wolke, 2011), although
conclusive evidence is lacking. Such hypotheses are based on findings that adults born
preterm tend to score higher on measures of shyness, agreeableness, conscientiousness and
neuroticism, and lower on measures of extraversion (Allin et al., 2006; Hertz, Mathiasen,
Hansen, Mortensen, & Greisen, 2013; Pesonen et al., 2008; Schmidt, Miskovic, Boyle, &
Saigal, 2008). This personality profile may help explain some of the differences in adult
outcomes. For example, higher conscientiousness is related with better health and better
longevity (e.g., Friedman & Kern, 2014; Friedman, Kern, Hampson, & Duckworth, 2014;
Roberts, Walton, & Bogg, 2005; Smith, 2006) while increased neuroticism is related to the
increased diagnosis of illness (although results are more mixed for relations between
neuroticism and health; Friedman & Kern, 2014; Smith, 2006). In addition, increased
extraversion and decreased neuroticism were related to higher levels of subjective well-
being (Diener, Suh, Lucas, & Smith, 1999). Therefore, the higher neuroticism and lower
extraversion of adults born preterm may, for example, place these individuals at risk of
poorer health and subjective well-being; whereas the higher conscientiousness of adults
born preterm may help to protect these individuals from poorer health outcomes associated
with prematurity. These differences in personality may also mediate relations between
prematurity and the later formation of romantic relationships (Hack, 2009; Wolke, 2011)
although conclusive evidence is lacking. One goal of the present study was thus to explore
the extent to which personality accounts for some of the adult outcomes of prematurity. In
addition to differences in personality profiles, Hack et al. (2002) described the
behavioral cautiousness of preterm individuals. Risky behavior, or its avoidance, may
therefore also account for some adult outcomes (Wolke, 2011), with preterm adults
appearing more risk adverse, and less likely to consume alcohol, use drugs, and go to
clubs or pubs than full term adults (Cooke, 2004; Hack, 2009; Hack et al., 2007, 2002,
2004; Pyhala et al., 2009; Roberts et al., 2013; Schmidt et al., 2008). Wolke (2011)
questioned whether such behavioral cautiousness might reduce opportunities and thus help
explain some adult outcomes of prematurity, so we examined the extent to which risky
behaviors accounted for adult sequelae of prematurity. Finally, demographic and childhood
factors may play important roles in understanding adult outcomes. Premature delivery not
only places babies in the world before they are biologically ready, but is also often
combined with long periods of hospitalization following birth (Goldberg & DiVitto, 1983).
Given long hospital stays at birth may reflect more extreme preterm birth or more medical
complications at birth, we examined long hospital stays at birth as a predictor of adult
outcomes (as well as birth status). In addition, premature deliveries occur more often
among mothers of low socioeconomic status, who are under 15 years old, or who have had
many pregnancies close together in time (Behrman & Butler, 2006; Goldberg & DiVitto,
1983). These conditions themselves place children at increased risk. Therefore, preterm
delivery may combine biological immaturity with environmental risk. As a result,
demographic (family-of-origin socioeconomic status) variables need to be considered when
seeking to assess the specific effects of preterm birth on adult outcomes. In addition,
preterm adults appear less likely to have children (Moster et al., 2008), which may affect
the outcomes of interest (for example, relationship satisfaction) in this study.
Therefore, being a parent also needs to be considered as a potential confounding variable
for adult outcomes.

<hs>  Study sample</hs>
  ~~~~~~~~~~~~

A sub-sample of cases was drawn from data collected using an online survey advertised
(through webpages, and television and radio channels) and hosted by the British
Broadcasting Corporation. 556,330 participants, aged between 18 and 80 years, responded
between November 2009 and April 2011. Participants were excluded if data were missing
(either due to no response or responses such as “rather not say” or “don’t know”)
regarding preterm birth or confounding variables, resulting in a subsample of 63,052.
Individuals without missing data were younger, t(84429.77) = −43.20, p < .001, d = 0.17,
were 1.21 times more likely to be female, χ2 (N = 537,077) = 462.20, p < .001, and were
higher on family-of-origin SES, t(90957.62) = 22.92, p < .001, d = 0.10. Models were then
run on the subsamples of individuals without missing data for the outcomes of interest.
Only individuals in relationships and those who were employed were included in analyses of
relationship satisfaction and job satisfaction, respectively.

<hs>  Procedures</hs>
  ~~~~~~~~~~

‘The Big Personality Test’ contained items pertaining to demographic and life histories
(childhood, health, education, employment), personality, and well-being, among other
topics (see the supplementary materials for the relevant sections of the survey). Before
starting the survey, individuals were provided with information about the study and were
informed of their right to withdraw at any time and to ignore any questions. All study
procedures were reviewed by the Department of Psychology Research Ethics Committee (in the
University of Cambridge). All items were answered using a multiple-choice format,
producing numeric data. All variables (unless otherwise stated) reflect the average of
items making up the respective scale.

<hs>  Preterm birth</hs>
  ~~~~~~~~~~~~~

Respondents were asked if they were born preterm – before 37 weeks (see Section 6,
supplementary materials). Respondents answered yes, no or rather not say/do not know.
Those who selected the last option were excluded. Seven per cent of respondents were born
preterm (6.8% of all respondents and 7.1% of those who answered this question), a rate
equivalent to national statistics for the U.K. (Office for National Statistics, 2011).
Birth status was related to having missing data, χ2 (1, N = 445,769) = 14357.70, p < .001,
with preterm adults 4.11 times more likely to have complete data than full term
individuals. Consequently, preterm adults made up 18% of the final sample.

<hs>  Outcomes</hs>
  ~~~~~~~~

Health was measured using only the first item of the RAND SF 36-Item Health Survey (Ware,
2004). Respondents were asked to rate one item about how they perceived their health to be
in general on a five-point scale from ‘excellent’ to ‘poor’ (see Section 7, supplementary
materials). Life satisfaction was measured using the Satisfaction with Life Scale (SWLS;
Diener et al., 1985). Participants selected responses on a seven-point scale that ranged
from ‘strongly agree’ to ‘strongly disagree’ in response to 5 items pertaining to their
feelings about various aspects of their lives (see Section 8, supplementary materials).
For example, So far, I have got the important things I want in life. The internal
consistency of the scale was high (α = .90). Relationship satisfaction was measured using
the Adapted Triangular Love Scale (Ahmetoglu, Swami, & Chamorro-Premuzic, 2010).
Respondents first indicated whether they were in intimate relationships. Those in
relationships selected responses on a five-point scale that ranged from ‘disagree
strongly’ to ‘agree strongly’ in response to 9 items pertaining to their satisfaction with
three aspects of their relationships: intimacy, passion and commitment (see Section 4,
supplementary materials). For example, I think my relationship with my partner will last
forever or I can tell everything to my partner. The internal consistency of the scale was
high (α = .84). Job satisfaction was measured using the General Index of Job satisfaction
(Brayfield & Rothe, 1951). Respondents first indicated their occupational status. Those in
employment (full time, part time or self-employed) selected responses on a five-point
scale that ranged from ‘disagree strongly’ to ‘agree strongly’ in response to 5 items
pertaining to their feelings about their job (see Section 2, supplementary materials). For
example, I like my job better than the average person does. The internal consistency of
the scale was high (α = .91).

<hs>  Control variables</hs>
  ~~~~~~~~~~~~~~~~~

Personality was measured using the Big Five Inventory (John, Donahue, & Kentle, 1991).
Participants selected responses on five-point Likert scales that ranged from ‘strongly
disagree’ to ‘strongly agree’ to specify the extent that 44 statements describing
personality characteristics applied to them (see Section 3, supplementary materials). The
internal consistency of subscales was high (α ⩾ .77). Risky behaviors were measured using
3 items from the CDC Youth Risk Behavior Survey (Centers for Disease Control, 2013).
Respondents were asked how many cigarettes they smoked per day in the last month.
Individuals were categorized as no or yes (any number per day) for smoking. Respondents
were asked how many days in the past month they drank 5 or more drinks within a couple of
hours. Responses to this item were used to create an ordinal variable of increasing binge
drinking (see Table 1 for levels). Finally, respondents were asked how many times in their
lifetime they had taken illegal drugs. Responses to this item were used to create an
ordinal variable of increasing life-time use of illegal drugs (see Table 1 for levels and
see Section 7 of the supplementary materials for items). Child background factors and
control variables were measured using single items about the respondents’ age, gender,
ethnicity (see Section 1, supplementary materials), whether they thought they had
experienced long hospitalizations at birth (see Section 6, supplementary materials) and
whether they were parents (see Section 4, supplementary materials). Family-of-origin SES
was calculated by standardizing maternal and paternal education, and the occupation of
primary breadwinners during the respondents’ childhoods (see Section 5, supplementary
materials), and then calculating the mean score for these three standardized variables.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

First, a series of multiple regressions separately explored relations among birth status
or long hospital stays at birth (independent variables), control variables, and outcomes
(dependent variables). Then, for the four outcomes, a series of regression models were
run. The first model included birth status and long hospital stays at birth as predictors.
Model 2 added personality (all 5 subscales); model 3 added risky behaviors; model 4 added
family-of-origin SES; and model 5 added parenthood. All models controlled for age, gender
and ethnicity. All analyses were run using R (R Core Team., 2013b) and R packages foreign
(R Core Team, 2013a), lsr (Navarro, 2014), and psych (Revelle, 2014).

<hs>  Relations between preterm birth or long hospital stays at birth and other variables</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 1 presents the descriptive statistics for all variables for the preterm and full
term samples. Table 2 presents the regression coefficients for models examining
differences between the preterm and full term samples, and between individuals who did and
did not have long hospital stays at birth. Preterm individuals were lower than full term
respondents on openness and extraversion, and higher on conscientiousness, agreeableness
and neuroticism. Preterm individuals were less likely to binge drink, use illegal drugs or
be parents, but were more likely to have had long hospital stays at birth and have grown
up in families with lower SES. In addition, preterm adults reported lower health, life
satisfaction and job satisfaction. Effect sizes were small, with Cohen’s d ranging from
−0.13 to 0.07 with the exception of long hospitalization (d = 1.10). No differences
between preterm and full term adults were found for smoking or relationship satisfaction.
Furthermore, individuals who reported long hospital stays at birth showed similar pattern
of results to preterm individuals with a few exceptions. Individuals who had long hospital
stays at birth showed lower conscientiousness (the reverse of preterm individuals), but
showed no difference in their openness and agreeableness to individuals who did not have
long hospital stays at birth. There was no difference in family-of-origin SES between
individuals who did and did not have long hospital stays at birth, but individuals who did
have long hospital stays at birth reported lower relationship satisfaction, and
furthermore long hospitalizations at birth appeared to have a stronger effect on all
outcome measures than preterm birth.

<hs>  The role of preterm birth, long hospital stays and confounding variables</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 3 presents the effect size – Cohen’s d – for birth status and long hospital stays in
the regression models predicting: health, life satisfaction, relationship satisfaction and
job satisfaction. Table 1 in the supplementary materials reports correlations between all
predictor variables in the regression analyses.

        <hss>Health</hss>

        One per cent of the variance was accounted for by preterm birth and long hospital
        stays (as well as age, gender and ethnicity), R2 = .01, F(5, 63046) = 87.72, p <
        .001. Adding personality variables, ΔR2 = .11, F(5, 63041) = 1586.70, p < .001,
        risky behavior variables, ΔR2 = .02, F(3, 63038) = 377.48, p < .001, childhood
        variables, ΔR2 = .00, F(1, 63037) = 205.20, p < .001, led to significant increases
        in the amount of variance accounted for, but adding parenthood, ΔR2 = .00, F(1,
        63036) = 2.71, p = .100, did not increase the amount of variance accounted for.
        Adding interactions between preterm birth or long hospital stays and all other
        predictor variables added minimally (0.05%) to the variance accounted for.
        Openness (b = −0.04, 95% CI [−0.05, −0.03], β = −0.03, p < .001) and neuroticism
        (b = −0.29 [−0.30, −0.28], β = −0.23, p < .001) negatively predicted, and
        conscientiousness (b = 0.19 [0.18, 0.20], β = 0.13, p < .001) and extraversion (b
        = 0.10 [0.09, 0.11], β = 0.08, p < .001) positively predicted health,
        independently of preterm birth and long hospital stays at birth. In addition,
        smoking (b = −0.30 [−0.32, −0.28], β = −0.12, p < .001) and drug use (b = −0.01
        [−0.01, 0.00], β = −0.02, p < .001) negatively predicted, and family-of-origin SES
        positively predicted (b = 0.09 [0.08, 0.10], β = 0.06, p < .001) health,
        independently of preterm birth and long hospital stays at birth. Adding control
        variables into the regression models did not reduce the effect of preterm birth
        but did reduce the effect of long hospital stays on health. In particular,
        including personality variables (and risky behaviors to a smaller extent) reduced
        the unique association between long hospital stays on health.

        <hss>Life satisfaction</hss>

        One per cent of the variance was accounted for by preterm birth and long hospital
        stays at birth (as well as age, gender and ethnicity), R2 = .01, F(5, 62194) =
        184.70, p < .001. Adding personality, ΔR2 = .21, F(5, 62189) = 3348.90, p < .001,
        risky behavior, ΔR2 = .02, F(3, 62186) = 422.44, p < .001, childhood variables,
        ΔR2 = .00, F(2, 62185) = 268.59, p < .001, and parenthood, ΔR2 = .01, F(1, 62184)
        = 821.04, p < .001, led to significant increases in the amount of variance
        accounted for. Adding interactions between preterm birth and all other predictor
        variables added minimally (0.04%) to the variance accounted for. Conscientiousness
        (b = 0.24 [0.23, 0.26], β = 0.13, p < .001), extraversion (b = 0.29 [0.27, 0.30],
        β = 0.17, p < .001) and agreeableness (b = 0.14 [0.12, 0.16], β = 0.06, p < .001)
        positively predicted, and openness (b = −0.09 [−0.11, −0.08], β = −0.04, p < .001)
        and neuroticism (b = −0.49 [−0.50, −0.47], β = −0.29, p < .001) negatively
        predicted life satisfaction; smoking (b = −0.37 [−0.40, −0.34], β = −0.11, p <
        .001) and drug use (b = −0.02 [−0.03, −0.02], β = −0.04, p < .001) negatively
        predicted life satisfaction; and family-of-origin SES (b = 0.15 [0.13, 0.16], β =
        0.07, p < .001) and parenthood positively predicted (b = 0.38 [0.35, 0.40], β =
        0.13, p < .001) life satisfaction, independently of preterm birth and long
        hospital stays at birth. Adding control variables into the regression models did
        not reduce the effect of preterm birth (with the exception of parenthood reducing
        the effect of birth status from −0.08 to −0.07) but did reduce the effect of long
        hospital stays on life satisfaction. In particular, including personality
        variables (and risky behaviors to a smaller extent) reduced the unique association
        between long hospital stays on life satisfaction.

        <hss>Relationship satisfaction</hss>

        Preterm birth was related relationship status (whether individuals were in an
        intimate relationship or not), χ2 (1, N = 62,333) = 286.78, p < .001. Full term
        individuals were 1.43 [1.37, 1.49] times more likely to be in intimate
        relationships than preterm individuals. For individuals in an intimate
        relationship, we examined their satisfaction with their current relationship. One
        per cent of the variance in relationship satisfaction was accounted for by preterm
        birth and long hospital stays at birth (and age, gender and ethnicity), R2 = .01,
        F(4, 41635) = 68.33, p < .001. Adding personality variables, ΔR2 = .07, F(5,
        41630) = 633.58, p < .001, risky behavior variables, ΔR2 = .01, F(3, 41627) =
        212.05, p < .001, led to significant increases in the amount of variance accounted
        for. However, adding childhood variables, ΔR2 = .00, F(2, 41626) = 1.06, p = .304,
        and parenthood did not lead to a significant increase in the amount of variance
        accounted for, ΔR2 = .00, F(1, 41625) = 0.27, p = .601. Adding interactions
        between preterm birth and all other predictor variables added minimally (0.09%) to
        the variance accounted for. Conscientiousness (b = 0.13 [0.12, 0.14], β = 0.13, p
        < .001), extraversion (b = 0.06 [0.05, 0.07], β = 0.07, p < .001) and
        agreeableness (b = 0.16 [0.15, 0.17], β = 0.14, p < .001) positively predicted,
        and neuroticism (b = −0.05 [−0.06, −0.04], β = −0.06, p < .001) negatively
        predicted relationship satisfaction; and smoking (b = −0.12 [−0.14, −0.10], β =
        −0.07, p < .001), binge drinking (b = −0.03 [−0.04, −0.03], β = −0.07, p < .001)
        and drug use (b = −0.01 [−0.02, −0.01], β = −0.04, p < .001) negatively predicted
        relationship satisfaction, independently of preterm birth and long hospital stays
        at birth. Adding personality variables into the regression models reduce the
        effect of preterm birth to insignificance and reduced the effect of long hospital
        stays on relationship satisfaction. In addition, controlling for risky behaviors
        increased (to a small extent) the unique association between long hospital stays
        on relationship satisfaction.

        <hss>Job satisfaction</hss>

        Preterm birth was related to employment status, χ2 (2, N = 61,386) = 360.60, p <
        .001. Full term individuals were 1.41 [1.35, 1.47] times more likely to be
        employed than preterm individuals. For individuals in employment, we examined
        their satisfaction with their current job. Three per cent of the variance was
        accounted for by preterm birth and long hospital stays at birth (and age, gender
        and ethnicity), R2 = .03, F(4, 38618) = 217.60, p < .001. Adding personality, ΔR2
        = .10, F(5, 38613) = 929.10, p < .001, risky behavior, ΔR2 = .00, F(3, 38610) =
        25.83, p < .001, childhood variables, ΔR2 = .00, F(2, 38609) = 61.72, p < .001,
        and parenthood, ΔR2 = .00, F(1, 38608) = 38.04, p < .001, led to significant
        increases in the amount of variance accounted for. Adding interactions between
        preterm birth and all other predictor variables added minimally (0.06%) to the
        variance accounted for. Openness (b = 0.07 [0.06, 0.09], β = 0.05, p < .001),
        conscientiousness (b = 0.18 [0.17, 0.20], β = 0.13, p < .001), extraversion (b =
        0.18 [0.16, 0.19], β = 0.15, p < .001) and agreeableness (b = 0.09 [0.07, 0.11], β
        = 0.06, p < .001) positively predicted, and neuroticism (b = −0.18 [−0.19, −0.17],
        β = −0.15, p < .001) negatively predicted job satisfaction; and smoking (b = −0.05
        [−0.08, −0.03], β = −0.02, p < .001), binge drinking (b = −0.01 [−0.02, −0.01], β
        = −0.02, p < .001) and drug use (b = −0.01 [−0.01, 0.00], β = −0.02, p < .001);
        and family-of-origin SES (b = 0.06 [0.05, 0.08], β = 0.04, p < .001) and
        parenthood positively predicted (b = 0.07 [0.05, 0.09], β = 0.04, p < .001) job
        satisfaction, independently of preterm birth and long hospital stays at birth.
        Controlling for long hospital stays at birth reduced the effect of preterm birth
        on job satisfaction to insignificance and adding personality variables into the
        regression models reduce the effect of long hospital stays at birth on job
        satisfaction to insignificance.

<h>DISCUSSION</h>
----------

As in previous research, preterm birth was associated with reduced perceived health
(Cooke, 2004; Hack et al., 2007; Lindstrom et al., 2009). In addition, preterm birth was
negatively related to life and job satisfaction (areas of functioning not previously
measured in preterm adults). The effect sizes for the relations between preterm birth and
these three outcomes were small, however. As previously reported, preterm individuals were
less likely to be in intimate relationships when asking only individuals currently in
intimate relationships, relationships were equally satisfying for preterm and full term
adults (consistent with previous findings, although the specific outcomes had not been
directly measured before; Hack et al., 2007; Moster et al., 2008). By asking preterm
adults how they felt about various areas of their life, we extended our understanding of
functioning in adulthood by demonstrating that these adults had equally satisfying
intimate relationships but less satisfying jobs and lives more generally. The differences
that did exist were small though. However, our large sample size allowed us to compute
robust effect sizes and thus add to the growing literature suggesting consistent, long-
lasting, but very small, long-term correlates of preterm birth (Hack, 2009; Saigal &
Doyle, 2008). Similar results with slightly higher effect sizes were found for individuals
who had long hospital stays at birth. We also showed that the associations between preterm
birth or long hospital stays at birth and outcomes were affected by other variables
associated with preterm birth. Individuals who had been born preterm scored higher on
measures of conscientiousness (long hospitalizations at birth were associated with lower
conscientiousness), agreeableness and neuroticism, lower on binge-drinking and lifetime
drug use, had lower family-of-origin SES, were more likely to report long hospital stays
at birth, and were less likely to be parents than individuals born at full term (see also
Allin et al., 2006; Cooke, 2004; Hack, 2009; Hack et al., 2007, 2004; Hertz et al., 2013;
Moster et al., 2008; Pesonen et al., 2008; Schmidt et al., 2008). Personality differences
in preterm individuals appeared to account for some of the reduction in relationship
satisfaction, while personality differences in individuals who experienced long hospital
stays at birth appeared to account for some of the reduction in health, life, relationship
and job satisfaction of these individuals. For example, individuals who had long hospital
stays at birth were lower on conscientiousness and extraversion, and lower on neuroticism.
When personality was controlled for, the unique effect of long hospital stays on all
outcomes were reduced, with the effect reduced to insignificance for job satisfaction.
While risky behaviors did not appear to account for any of the effects of preterm birth,
controlling for these behaviors did have a small effect on the unique association between
long hospital stays at birth and health and life satisfaction. Although personality, risky
behaviors and having started parenthood were related to both preterm birth and outcome
measures, these variables appeared to have limited effect on relations between preterm
birth and adult outcomes. However, personality did appear to have a more important role in
explaining some of the poorer outcomes for individuals who spent long periods in hospital
at birth. Therefore, hypotheses about the role of personality and risky behavior in
explaining the adult outcomes of preterm birth (Hack, 2009; Wolke, 2011) were not fully
supported. Although personality did not account for reductions in health, job satisfaction
or life satisfaction by prematurity (although it did appear to for long hospital stays at
birth), adding personality to models resulted in the greatest increase in variance
accounted for in subjective well-being. Therefore, individual differences in personality
accounted for individual differences in subjective well-being. Furthermore, personality
factors appeared to affect well-being in very similar ways for adults born preterm and
full term. For example, higher conscientiousness and extraversion, and lower neuroticism,
were related to better health, life, relationship and job satisfaction, higher
agreeableness was related to higher life, relationship and job satisfaction, and higher
openness to experience was related to poorer health but better job satisfaction.
Therefore, some aspects of the personality of adults born preterm appears to place them at
risk for poorer subjective well-being (for example, higher neuroticism) while other
aspects could potentially be protective for individuals born preterm (for example, the
higher conscientiousness seen in preterm adults) but not for those who spend long periods
in hospital at birth (for example, lower conscientiousness seen in these individuals). All
analyses reported controlled for age. Including age in all analyses was important not only
due to relations with the outcomes and covariates of interest, but also because the age of
preterm individuals reflects aspects of the hospital care they received at birth. Advances
in perinatal and neonatal medicine, including the introduction of surfactant therapy in
the 1990s, have allowed increasing numbers of preterm infants to survive (Behrman &
Butler, 2006; Hintz et al., 2005). In addition to medical advances, social aspects of
hospital stays have changed. For example, the level of contact parents are encouraged to
have with their newborns during hospitalization has increased dramatically over the last
50 years (Davis, Mohay, & Edwards, 2003; Goldberg & DiVitto, 1983). In addition to age,
medical risk at birth also has implications for the care infants receive during the
initial hospitalization as well as subsequent re-hospitalizations. That is, infants often
experience longer hospitalizations when they are born at younger gestational ages or at
higher medical risk. Although we asked individuals whether they experienced long
hospitalizations at birth, individual’s perceptions of “long” may vary. The current
methodology allowed us to examine self-report data from a very large sample; however,
detailed data were not collected about the early medical contexts. Further work should
determine whether longer hospitalizations actually accounted for long-term outcomes of
prematurity as well as other early medical factors that may predict adult outcomes. Of
course, some limitations need to be acknowledged. Data were only collected at one time
point and therefore many of the correlations are open to multiple interpretations.
However, preterm birth, hospitalization following birth and family-of-origin SES all
occurred before adulthood so it seems fair to say that individuals from low SES families
who reported long hospitalizations at birth had lower levels of life satisfaction as
adults. Because ‘The Big Personality Test’ was an online survey, individuals had to self-
report their own prematurity. Preterm individuals were not selectively recruited and
therefore rates of preterm birth were as expected based on national rates (around 7% of
live births; Office for National Statistics, 2011). Previous studies have demonstrated
that mothers accurately report whether their offspring were born preterm (even when the
delivery was over 30 years ago) but are more likely to not respond, or to respond less
accurately, to questions about their offspring’s exact gestational age at birth (Tomeo et
al., 1999; Yawn, Suman, & Jacobsen, 1998). We do not know of any studies examining
individuals reporting on their own birth status, however. We therefore asked only whether
individuals had been born early; information was not collected about the individual’s
exact gestational age. As a result, we were not able to distinguish between extremely
preterm and near full term births, or between high- and low-risk preterm individuals.
Future studies should attempt to distinguish among these groups. However, it is noteworthy
that we observed significant effects despite having a sample presumably dominated by the
late preterm individuals who constitute the largest proportion of preterm individuals in
the general population. Furthermore, estimates of the effect of preterm birth may be
conservative because some of the individuals in the full term sample may actually have
been born preterm, as mothers are more likely to report (and thus tell their children)
that their offspring were born later rather than earlier (Tomeo et al., 1999; Yawn et al.,
1998). Differences between preterm and full term individuals on our control variables
(personality, risky behaviors and parenthood) are consistent with previous studies, which
gives us further confidence about the representativeness of our preterm sample. Although
7% of the sample reported being preterm, preterm individuals were over 4 times more likely
to provide complete data. This higher rate of having complete data for preterm individuals
may reflect the higher conscientiousness, younger age (as older individuals were more
likely to have missing data) or reduced illegal drug use (and therefore perhaps less
likely to skip questions about risky behaviors) of adults born preterm. However, future
studies should examine whether and why preterm individuals provide more complete data
about their subjective wellbeing. Regardless of the reasons, as a result of the reduced
likelihood of missing data, preterm individuals made up 18% of the final subsample. All
information was provided by the participants, which may be problematic because preterm
individuals reportedly provide more socially acceptable responses (Allin et al., 2006).
However, only self-report measures can be used to assess perceptions of life and well-
being and only such a large online survey would have allowed us to recruit such a large
sample. If adults born preterm indeed provided more socially acceptable responses this
would have minimized rather than amplified the associations we found. Furthermore, as all
data was collected from only the individual, the higher levels of neuroticism combined
with poorer subjective wellbeing may reflect a more general negative and/or pessimistic
outlook on life and in turn such an outlook may make individuals more likely to endorse
the preterm or long hospital stays at birth items. Therefore, some of the shared variance
in such measures could reflect such a negative and/or pessimistic tendency. Future work
should attempt to untangle such a possibility.

<hs>  Conclusions</hs>
  ~~~~~~~~~~~

We asked preterm individuals how they felt about various aspects of their lives. This
approach to studying the adult sequelae of preterm birth allowed us to ask, not about
relationship or employment status (which have already been explored in various studies),
but about the well-being and functioning of preterm individuals in adulthood. We were able
to demonstrate poorer health, lower levels of life and job satisfaction but equal levels
of relationship satisfaction in preterm adults. Although these differences were small,
they could prove important at the general population level because so many individuals are
born preterm and the survival rates following preterm deliveries are increasing (Johnson &
Wolke, 2013). These findings are also consistent with other evidence of mild effects of
prematurity into adulthood (Hack, 2009; Saigal & Doyle, 2008). The large sample size not
only allowed us to examine the individuals’ ratings of their lives following preterm birth
or long hospital stays, but also allowed us to control for various other variables
including personality and risky behaviors. Despite previous suggestions that the
personality profile and behavioral cautiousness of preterm individuals may help explain
certain adult outcomes (Hack, 2009; Wolke, 2011) and personality accounting for the
greatest amount of variability in subjective well-being in our analyses, we found that
personality only accounted for some of the reduction in life satisfaction in preterm
adults. However, personality did appear to account for some of the poorer well-being of
individuals who had long hospital stays at birth. These results help provide a broader
understanding of preterm infants’ functioning in a variety of domains well into adulthood.


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<ART>The tempos of performance
=========================

Authors: Nir Shalev, Anna Katharina R. Bauer, Anna C. Nobre
DOI: 10.1016/j.copsyc.2019.06.003
Year: 2019  |  Pages: 254-260
ASJC codes: 3200

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Human performance fluctuates over time. Rather than random, the complex time course of variation reflects, among other factors, influences from regular periodic processes operating at multiple time scales. In this review, we consider evidence for how our performance ebbs and flows over fractions of seconds as we engage with sensory objects, over minutes as we perform tasks, and over hours according to homeostatic factors. We propose that rhythms of performance at these multiple tempos arise from the interplay among three sources of influence: intrinsic fluctuations in brain activity, periodicity of external stimulation, and the anticipation of the temporal structure of external stimulation by the brain.

--------------------------------------------------------------------------------


<h>EVENT TEMPOS</h>
------------

Fast periodicity of perceptual systems was proposed on theoretical grounds before it was
directly observed [9, see also Ref. 10]. Periodic and discrete sampling of sensory
information, or the ongoing ‘parsing’ of continuous sensory input, was proposed to be
advantageous for enabling multiplexing of information processing and for providing time
stamps for integrating and sequencing information [9]. Behaviourally, rapid performance
modulations (>1 Hz) have been observed for making perceptual judgments about visual
features, such as motion, depth, or colour [11].

<hs>  Intrinsic brain fluctuations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Studies combining measurements of behavioural performance and neural activity have
revealed that the intrinsic rhythmic fluctuations of brain activity may contribute to the
periodicity of behavioural performance. Fluctuations in behavioural performance at
timescales above 1 Hz correlate with the ebb and flow of intrinsic neural oscillations2
[12–14]. Supporting the notion of periodic sensory sampling, studies have shown that
variability in perceptual performance co-varies with intrinsic brain rhythms, especially
in the theta (∼4–8 Hz) and alpha (∼8–12 Hz) frequency bands. For instance, visual target
detection of near-threshold stimuli fluctuates in phase with neural oscillations in the
alpha band [12,13,15]. So far, most studies investigating perceptual fluctuations in
relation to the phase of intrinsic brain oscillations have been in the visual modality.
However, a recent paper suggests that oscillations in behavioural performance also exist
in the auditory domain in the theta frequency range [16]. In addition, studies using
‘reset events’ provide evidence for periodic sensory sampling in the theta frequency range
[14,17–20]. Reset events can be generated by a transient salient event, thought to reset
the phase of ongoing intrinsic neural oscillations so that subsequent oscillations become
phase-locked to the reset event. Through the presentation of response-relevant stimuli at
various intervals after such a reset event, the unfolding of behavioural performance
fluctuations can be directly measured. For example, in a spatial attention task with two
behaviourally relevant locations, a reset event was used to investigate the periodic
sampling of each location [17]. This approach assumed that the reset event captures
attention, thus prioritising sampling of its location. Following the reset event, visual
target detection accuracy for each location fluctuated at a 4-Hz rate, while performance
between the two locations was in antiphase. Periodic sensory sampling of this type has
also been found to be triggered by reset events caused by auditory stimuli [20] and
movement onsets [21]. Rhythmic performance fluctuations have been predominantly reported
for the theta and alpha frequency bands. While we are not aware of studies showing direct
evidence for sensory performance fluctuations in the gamma frequency range (>30 Hz), there
is evidence that the phase of delta (0.5–4 Hz) and theta rhythms modulates gamma and alpha
band activity and neuronal firing [22–25]. The informational content of neural processing
is thought to be carried in these high-frequency signals. Therefore, their regulation by
the slower delta and theta oscillations supports the early theoretical proposals of
periodic sampling and processing of sensory information [9,10]. Such a mechanism could
enable the pick-up and relay of information within local neuronal ensembles to be
quantised and paced by capitalising on the slower intrinsic oscillations reflecting the
circuit-level dynamics of the networks in which they are embedded.

<hs>  Entrainment to periodic stimulation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Intrinsic brain rhythms can contribute to fluctuating patterns of performance even in the
absence of temporally structured external stimulation [1,12–15]. However, additionally,
performance is also highly sensitive to periodicities in external stimulation [26]. Many
natural stimuli that guide behaviour, such as speech, music, or footsteps, follow a
regular rhythm, occurring predominantly between 0.5 and 4 Hz. The influence of periodic,
rhythmic stimulation on performance was demonstrated in a series of psychophysical
experiments in the auditory domain. Perceptual identification and discrimination of
auditory tones were most accurate when stimuli occurred in phase with the preceding
rhythmic stimulus train [27, but see Ref. 28]. In principle, two different types of
mechanisms can account for performance benefits in the context of periodic external
stimulation. The simplest is a mechanism of reactive ‘entrainment’ by which intrinsic
neural oscillations are reactively and automatically reset and paced by external events
[29]. The alternative is a mechanism of proactive anticipation, by which the brain learns
about the periodicities in external stimulation and uses top-down signals to prepare
sensory systems for relevant upcoming sensory events [30,31]. Entrainment mechanisms were
invoked to explain performance benefits in rhythmic stimulation contexts on theoretical
and computational grounds in the ‘dynamic attending theory (DAT)’ by Jones and colleagues
[27,32]. Neural recordings later confirmed that neural oscillations do entrain to rhythmic
stimulation in the delta and theta ranges, thereby providing a plausible physiological
basis for DAT [29,33]; see also Ref. [34]. When presented with rhythmic auditory
stimulation, fluctuations in behavioural performance are dependent on the phase of the
entrained neural oscillations [35], and behavioural modulations can be observed even in
the absence of abrupt onsets in the entraining sequence [36,37]. While many studies have
focused on the auditory modality, stimulus-driven fluctuations of performance have also
been noted in the visual modality, particularly in the alpha range [38,39].

<hs>  Proactive temporal anticipation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In rhythmic contexts, separating effects attributed to slavish stimulus-driven entrainment
versus proactive anticipation is difficult if not impossible [40]. Many different types of
anticipation mechanisms have been described [41]. In addition to rhythmic anticipation
[27], anticipation can be related to learned temporal associations between individual
events [42], sequences of events [31,43], and temporal conditional probability [44,45].
These multiple temporal structures can combine and occasionally interact [46–48]. It is
likely that in rhythmic contexts both entrainment and temporal anticipation occur, and
that these interact further with other sources of top-down attention-related signals that
guide prioritisation and selection of relevant stimuli. For example, when monkeys were
presented with interleaved rhythmic auditory and visual stimulation, performance
fluctuations and neural oscillatory activity were dependent on which stimulus modality was
relevant for performance [29].

<h>TASK TEMPOS</h>
-----------

Slower oscillations in the range of seconds reflect processes that affect sustained task
performance. For example, studies of vigilance examine the capacity to maintain an
adequate state of arousal and focus to detect occasional targets within repetitive and
non-engaging tasks over minutes or hours [3,49,50]. Whereas traditionally studies of
vigilance have investigated the decrement of performance over time [49,51–53], some have
emphasised the waxing and waning of performance [50,54]. Potentially, clinical and
neurotypical populations can be distinguished based on performance rhythms. For example,
studies have shown that children diagnosed with ADHD manifest a unique oscillatory pattern
of periodic drops in accuracy every 20–30 s [55]. It was also speculated that children
with ADHD exhibit atypical rhythmic fluctuations in the ‘default-mode network’ which
normally fluctuates between 0.01 and 0.1 Hz [56]. A different study showed that
individuals with ADHD have diminished ability to benefit from rhythmic patterns in a
continuous performance task compared to neurotypical individuals [57].

<hs>  Intrinsic brain fluctuations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Empirical findings concerning occasional disengagements from continuous performance tasks
[54] are normally attributed to a gradual inability to sustain attention [58]. However,
intrinsic oscillatory properties of performance may also contribute. Task rhythms may
partly reflect ebbing and flowing of different brain networks [59,60]. The existence of
functionally significant slow oscillations ranging between 0.01 and 0.2 Hz is supported by
modelling data [61], local field-potential recordings in monkeys [62], and human
electrophysiology [63]. These rhythms are thought to result in periodic changes in
psychophysical performance parameters [59,64]. They are associated with the clustering of
performance levels in cognitive tasks, for example, when detection rates on consecutive
trials are auto correlated for time lags longer than 100 s [64]. At the neural level, they
are thought to represent a slow cyclic modulation of gross cortical excitability [65].
Interestingly, these oscillations below 1 Hz (infraslow) can also interact with faster
rhythms. Empirical evidence suggests that the phase of infraslow brain oscillations
correlates with the amplitude of faster rhythms (1–40 Hz) [64]. Accordingly, it has been
proposed that the ongoing intrinsic infraslow fluctuations between 0.01 and 0.1 Hz and the
faster oscillations (between 1 and 40 Hz) nested therein may account for the typical
correlation in performance among successive trials in behavioural tasks, creating non-
random clustering of performance patterns over time, with variability increasing at longer
time-scales [64]. When describing the time series of psychophysical performance over
minutes, behavioural data exhibit fractal patterns and power-law autocorrelations [66].
Such dynamics that are characterised by patterns of hierarchical self-similarities at
multiple time-scales are typical of ‘scale-free dynamics’, or 1/f distributions, which
seem to be a common motif of both behavioural performance patterns [2,67] and brain
activity [63–65].

<hs>  Entrainment to periodic stimulation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Some evidence suggests that entrainment to external periodic stimulation is not confined
to the timescale of milliseconds. Using intracellular recordings in animals, researchers
have identified non-lemniscal auditory neurons in the thalamus with spontaneous up/down
transitions at random intervals, which can become entrained to rhythmic stimulation
occurring between 3 and 12 s [68]. However, we are not familiar with comparable findings
in the human literature showing entrainment at such slow rhythms.

<hs>  Proactive temporal anticipation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

At the slower rhythm of sustained task performance, temporal anticipation of target events
may interact with the regulation of arousal. Changes in tonic arousal during task
performance have been associated with changes in uncertainty levels [69–71]. The potential
interaction between external stimulus rhythms and arousal is often discussed in the
sustained-performance literature. To some extent, the very first experimental task
manipulating vigilance relied on rhythmic stimulation [49]. Many other task designs that
followed the traditional vigilance (and later: sustained attention) research also
presented stimuli in fixed or regular rhythmic intervals [50,72,73]. In our lab, we have
recently observed that presenting target events within a predictable, rhythmic temporal
structure leads to a periodic modulation of pupil size in preparation for stimulus onset,
alongside a reduction in the overall arousal as indexed by tonic changes in pupil size
[74]. In contrast, temporally unpredictable targets are associated with a continuous state
of high arousal. Our results suggest that traditional explanations of changes in arousal
caused by habituation of the neural response to repetitive stimulation [75] or by ordinal
predictability [76] may be insufficient, as they do not account for the effects
specifically attributable to the temporal structure of the task.

<hs>  Intrinsic brain fluctuations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

When moving from minutes to hours, further intrinsic rhythmic components influence
performance. For example, researchers have shown that fluctuations in arousal can occur
independently of circadian cycles based on a dopaminergic ultradian oscillator [77].
Electrophysiological studies support the notion of such slow rhythmic fluctuations. For
example, researchers have identified two separate components of arousal in broadband EEG,
one fluctuates in cycles of ∼100 min, and is related to changes in vigilance; the other
fluctuates between 3 and 8 h, and represents variations in wakefulness levels [78]. The
functional significance of ultradian rhythms of arousal was demonstrated in a study
tracking the latency and amplitude of event-related potentials showing reliable rhythmic
fluctuations over hours [79]. Similarly, it was shown that the pattern of performance
decrement during a prolonged vigilance task is mirrored by a decrease in the trial-by-
trial consistency of the neural response in the theta phase (3–7 Hz), providing further
evidence for the association between task and event rhythms [80]. Thus, although changes
in arousal are often discussed in the context of habituation resulting from repetitive
stimulation [75], it is also affected by very slow intrinsic rhythmic components.

<hs>  Entrainment to periodic stimulation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Whereas the literature has not yet highlighted the effect of infraslow periodic
stimulation on performance, a clear stimulus-driven component is recognised to affect
performance fluctuations related to ultraslow circadian rhythms. In the ‘forced
desynchrony’ experimental protocol, participants are placed in artificial light/dark
cycles for varying durations [81]. Using this approach, researchers have shown that
fluctuations in body temperature and heart rate are determined by both external
stimulation and homeostatic rhythmic components [82]. In turn, periodic changes to body
temperature are causally related to fluctuations in cognitive performance [83].
Furthermore, models of dynamic changes in human performance within the time scale of days
discuss the circadian processes that periodically determine both the sleep drive and
waking alertness, with the latter being closely associated with overall performance [84].
A different source of a periodic stimulation which potentially interacts with brain
oscillations occurs through the interaction with other physiological processes in the
body. A recent study has demonstrated the phase-amplitude coupling between alpha activity
in the brain and an infra-slow gastric basal rhythm (∼0.05 Hz) generated by the stomach
[85]. The study has shown that approximately 8% of the variance in alpha activity can be
explained by the oscillations generated by the gut (for a recent review on how visceral
signals shape neural activity see Ref. [86]). However, it is still unclear whether such
periodic stimulation is directly associated with changes in behaviour.

<h>SUMMARY AND FUTURE DIRECTIONS</h>
-----------------------------

Rhythmicity is a hallmark of the brain [1] and its environment, and characterizes many
aspects of cognition and behaviour [87]. Observations of the rhythmic facilitation of
behaviour appeared in the earliest days of cognitive research [26], and have since been
substantiated by neuroscientific evidence [29]. In this review we have considered rhythms
affecting behavioural performance at multiple timescales — from single events, to
sustained tasks, to throughout the day. We have suggested that multiple factors play a
role in structuring performance over time — fluctuations in intrinsic brain and
homeostatic mechanisms, reactive entrainment to external period stimulation, and proactive
anticipation of the temporal structure of events (see Figure 2). The exciting topic for
future research will be to understand whether and how the factors influencing performance
at these various tempos interact. Here we noted a few examples available so far, such as
putative interactions between task rhythms and event rhythms that could be mediated by the
effects of arousal on faster attention-related dynamics through its change in cortical
signal-to-noise ratio [69,71], and the interplay between even slower homeostatic functions
and faster signatures of brain activity [68]. However, most of the fun work is still
ahead, and results are likely to reveal interesting fundamental principles about the
coordination of brain activity and behavioural output. Headway will depend on us
broadening the temporal focus of our experimental tasks. Rather than just taking
performance measures during single trials as isolated events, it will be fruitful to move
to dynamic and extended task contexts, to measure brain and homeostatic activity at
multiple time scales, to vary the temporal regularity and pace of stimulation, and to
manipulate the predictability of temporal structures.


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<ART>The time is out of joint: Atmosphere and hauntology at Bodiam Castle
====================================================================

Authors: Michael Buser
DOI: 10.1016/j.emospa.2017.09.006
Year: 2017  |  Pages: 5-13
ASJC codes: 3205, 3207
Keywords: Affect, Ambiance, Atmospheres, Design, Emotion, Hauntology, Heritage, Representation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Drawing on recent work in emotional and cultural geography, the author brings Derrida's concept of hauntology into communication with thinking about atmospheres. The research deployed a mixed-method approach including audio documentation, observation, focus groups and interviews to look at the use of spectrality in the making of atmospheres associated with A Knight's Peril, an interactive game played at Bodiam Castle in the South East of England. The paper argues that the figure of the ghost is a useful heuristic towards understanding how designers conjure and exploit the emotional and affective power of atmospheres. At Bodiam, these techniques are deployed in an attempt to facilitate new understandings of the past.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Visitors to Bodiam Castle who play A Knight's Peril are driven by this urgent plea to foil
the plot against Sir Dallingridge. Guided by an adventure map, echo horn, and the ghostly
voice of twelve-year-old Kate (a fictional 14th century character who drives the narrative
and assists in the players' investigation), participants interact with a few of the
historic and imagined personalities associated with the castle as they solve the mystery
and intervene in the past. In this paper I build on recent work on atmospheres in Emotion,
Space and Society (Anderson, 2009; special issue edited by Bille et al., 2015; Urry et
al., 2016) and elsewhere to examine the production and staging of A Knight's Peril.
Drawing on Jacques Derrida's hauntology (1994) and considerations of spectrality in social
phenomena (Gordon, 1997; Edensor, 2005; Wylie, 2007; Cameron, 2008; Maddern and Adey,
2008; Matless, 2008), I focus on how the game's design conjures ghosts through narrative
and sound in support of particular atmospheres and experiences at Bodiam Castle. Coined by
Derrida in Specters of Marx, hauntology concerns the deconstructive critique of the
priority given to concepts such as being and presence (over non-being and absence for
example). It is also a philosophical and ethical destabilisation of all manner of dualisms
and universalising totalities (Critchley, 2014). In hauntology, the ghost plays a crucial
role in this destabilisation via its characteristic uncertainty. As Liz Roberts explains,
a hauntological position ‘is one of deliberate indeterminacy, enforced hesitancy or
uncertainty over presupposed givens and operations involving visibility and invisibility
that constitute our reality’ (2012, 393). Geographical and urban scholarship on
spectrality often draws on Derrida's work and has brought attention to the ways in which
spaces are always haunted (see Till, 2005, 2012; Wylie, 2007; Edensor, 2005; Cameron,
2008; Maddern and Adey, 2008). Here, ghosts are a pervasive, yet often unnoticed or
unaccounted for part of social life. As Jameson writes, spectrality ‘is what makes the
present waver’, it is the notion that ‘the living present is scarcely as self-sufficient
as it claims to be; that we would do well not to count on its density and solidity … ’
(1999, 38–39). For urban and social research, taking a hauntological position and being
mindful of ghosts can serve as a heuristic device towards unsettling commonly-accepted
ontological categories and assumptions. ‘The logic of the ghost’, according to Derrida, is
that it ‘points toward a thinking of the event that necessarily exceeds a binary or
dialectical logic’ (1994, 78), such as its tendency to blur the boundaries between
supposedly stable ontological categories (e.g. living/dead, being/non-being, and
presence/absence). Atmospheres are arguably the prototypical spatial form of hauntology.
Vague, irrational and indeterminate, they haunt the middle ground between subject and
object (Böhme, 1993, 2013). ‘We are unsure where they are’ (Bille et al., 2015, 32) yet we
feel them all around us. Like ghosts, their ontological status is always insecure. From
the perspective of atmospheres, concepts such as ‘presence and absence, materiality and
ideality, definite and indefinite, singularity and generality’ are always expressed as
‘relations in tension’ (Anderson, 2009, 80). For hauntology, these relations are not only
tense, but are inseparable as each term can be found to contain traces of its opposite
(Buse and Stott, 1999). Despite this overlap, theoretical and empirical connections
between spectrality, hauntology and atmospheres are relatively underexplored (but see
Edensor, 2012). In this paper, I take scholarship forward by bringing these areas into
communication and taking a hauntological position in the investigation of the atmospheres
associated with Bodiam Castle's A Knight's Peril. I argue that the framework of hauntology
brings a fresh perspective to scholarship on atmospheres. The paper demonstrates how the
purposeful making and installing of atmospheres (Böhme, 2013) can be a process through
which to redress historical absences – in this case, the absence of women and children in
medieval record. Research for this paper was conducted over two phases during 2014 and
2015. The first phase centred on general background to Bodiam Castle and interviews with
designers and historians (n = 4) who were involved in creating A Knight's Peril. The
second phase occurred over six days and encompassed the main research activity at the
castle. Methods included the use of visual and audio methods (e.g. photography and
recording), participant observation, focus group discussions and interviews with players
(15 groups consisting of 46 individuals). Data collection was not focused on reproducing a
single or neutral representation of the conditions at Bodiam Castle. Rather, the approach
sought to animate some of the atmospheres associated with playing A Knight's Peril by
focusing on the affective, emotional and sensuous elements of the game. The approach was
explorative and inspired by recent methods discussions within non-representational theory
(Vannini, 2015; Anderson and Ash, 2015; McCormack, 2014) where a diversity of methods are
often deployed in order to help ‘look at, listen to and feel the space differently’ (Adey,
2008, 303). This information was analysed with particular attention on processes of
staging and constructing atmospheres at the castle and the experiences of participants who
played A Knight's Peril. Nevertheless, while the paper captures and names discrete
atmospheres (Anderson and Ash, 2015), these are circumstantial forms of sense-making
(McCormack, 2014) where envelopment (naming) simultaneously gives consistency while
remaining open to the contingency and dynamism of social experience. Moreover, as Simpson
(2017b) notes, individuals do not arrive at research sites with identical past
experiences. Indeed, even among young siblings who participated in the project,
experiences and histories will have been diverse and a day out at a National Trust
property can stimulate divergent affective and emotional responses. The structure of the
paper is as follows. Following this introduction I review A Knight's Peril within the
context of contemporary trends in heritage interpretation. I then discuss recent writing
on atmosphere, focusing on design and staging as well as the role of spectrality in
producing paradoxical temporality surrounding these phenomena. The empirical discussion
presents the ways in which narratives and staging techniques such as the introduction of
sounds both enable and co-produce atmospheres which inform and mediate heritage experience
and understandings of the past. This work is further analysed through a hauntological
lens, reflecting on Derrida's non-linear conception of time and the role of spectrality in
the production of emotionally resonant social spaces. I conclude with reflections and
suggestions for further research.

<hs>  Playing with history in A Knight’s Peril</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A Knight's Peril is a pervasive game (Montola et al., 2009) – an interactive, augmented
reality experience – played at Bodiam Castle (see Fig. 1) in the South East of England.
Built by Sir Edward Dallingridge in 1383, Bodiam has the look of an archetypal late
medieval castle (Saul, 1995). While the structure suffered an extended period of decline,
I found that its wide moat, elegant, symmetrical shape, large towers and country setting
produced an evocative and picturesque heritage space.1 Its current condition can be
attributed to a series of conservation efforts starting in the early 1800s when the castle
was repaired and maintained by individuals and families interested in preserving the
structure as a ‘romantic ruin’ (National Trust, 2001, 9–10). Today, the castle is owned
and managed by the National Trust, a charitable organisation that operates a range of
historic houses, properties, landscapes and nature reserves in England, Wales, and
Northern Ireland.2 In 2014 an independent design company (Splash & Ripple3) was engaged by
the National Trust to create A Knight's Peril. The broad objective of the project was to
improve the experience of explorer families – described as families that actively learn
and play together (National Trust, 2014). Interest in this demographic is representative
of the charity's desire to diversify its visitor base and reach new audiences. A Knight's
Peril deploys a choose-your-own-adventure game model to enable player interaction with a
few of the personalities associated with the castle. It facilitates this primarily through
a fanciful echo horn, constructed specifically for the project. The device is RFID4
enabled to allow digital interaction at the site. However, it has the look of a type of
object one might find in the 14th century. According to the game narrative, Kate
Dallingridge (Sir Edward's daughter) has left echoes around the castle and where they have
seeped into the stonework, a small seal has grown. When placed in contact with a seal, the
horn can tap into Kate's echoes. With echo horn in hand, participants interact with her
character and work together to foil the plan to assassinate her father (see Fig. 2). A
Knight's Peril is illustrative of heritage learning where non-didactic ways of engaging
people with past experience are being explored (e.g. beyond the guidebook and audio
guide). Such projects typically involve the introduction of digital media or the creation
of virtual environments where visitors can engage in learning activities (Mortara et al.,
2014). A range of motivations are evident including: to modify and enhance conventional
heritage experiences, to decentre heritage experience away from dominant narratives; to
facilitate user agency, and to boost attendance through the incorporation of fun and
engaging activities and technology (Hertzman et al., 2008; Coenen et al., 2013; Mortara et
al., 2013). A Knight's Peril reclaims and reimagines traces of what has vanished over the
course of time. It is an example of how heritage interpretation can encompass or contain a
part of the past and to bring it to the present (Till, 2005). The game's setting – Bodiam
Castle – is itself a preserved piece of the past ‘adrift in a modern sea, an isolated
feature that stands out because it alone is old’ (Lowenthal, 2013, 438). Almost by magic,
the castle is physically present yet seems to belong to another time. I found Bodiam's
evocative, haunting feel was in no small part due to this uncanny quality of being neither
wholly past nor present. Part ruin, the castle is particularly conducive for the
conjuration of ghosts. Ruins, as DeSilvey and Edensor (2012, 471) note are ‘characterized
by multiple temporalities … offer(ing) opportunities for constructing alternative versions
of the past, and for recouping untold and marginalized stories’. Bodiam is managed in such
a way to allow ghosts to fill its spaces. The structure and grounds are uncluttered and
have been restored and maintained with an eye toward simplicity and clarity. The castle
has no roof, interior furniture or other medieval artefacts and is surrounded by simple
landscaping all of which maintains focus on the massive stone structure. The result is a
simple, yet evocative and haunting space. Such an architectural landscape ‘has a
particularly important part to play allowing the uncanny nature of the past to become
somehow visible to visitors’ (Maddern, 2008, 365; Edensor, 2005). As a site of
memorialisation, Bodiam allows visitors to draw on their own memories and expectations of
what castle life might have been like. Of course, interpretations of the past always
involve decisions about how history is to be represented and understood (Till, 2005).
These stories tell us as much about our contemporary selves as any historical moment.
Maddern refers to this interpretive work as a conjuration that involves ‘simultaneously …
excavating and burying histories and material assemblages’ (2008, 369 italics in
original). In other words, the absences – what we hide or do not talk about – are likely
to be just as important as that which is memorialised and remembered. Moreover, as I will
explore further in this paper, this process of commemoration – evident at Bodiam Castle
and countless historic districts, listed buildings, museums, and monuments to past events
– involves the purposeful staging of atmospheres through which resonances of the past can
be witnessed and experienced.

<h>ATMOSPHERES</h>
-----------

Much has been written recently about atmospheres and ambiances (Anderson, 2009; Bissell,
2010; Edensor, 2012, 2015; Ash, 2013; Buser, 2014, 2017; Lin, 2015; Sørensen, 2015). Most
productively, the concepts have been deployed to express a range of spatio-temporal
conditions that challenge static representations of space. To centre on atmospheres is to
understand social experience as sensory (Thibaud, 2011), collective, more-than-human
(Anderson and Wylie, 2009), and consisting of dynamic and multiple fields of intensities
(McCormack, 2008, 414). In social research, atmospheres help capture and characterise the
shifting ‘moods, feelings, sensations and dispositions’ (Lin, 2015, 287) associated with
being-in-the-world. However, as Bissell (2010) and Simpson (2017b) note, much of what we
call atmospheres occurs in the background and is often unrecognised. These are the affects
which, while outside cognitive perception, have the potential to modify a body's
behaviours, actions and emotions. For Philippopoulos-Mihalopoulos (2016, 151), such
‘affectively directed’ atmospheres are political in that they can seduce and lure,
‘numb(ing) a body … into an affective embrace of stability and permanence’. Indeed,
whether or not atmospheres are perceived by (or involve) a human subject does not diminish
their existence or power (Ash, 2013; Sørensen, 2015). This is particularly relevant here
as much of the design work employed at places such as Bodiam Castle involves manipulating
background environments in subtle ways to produce or support particular forms of behaviour
(Turner and Peters, 2015). That individual visitors may or may not be cognitively aware of
particular atmospheres is less important than the effects they have on the relationships
between bodies. At Bodiam, these relations have been carefully staged through design
techniques intended to engineer particular atmospheric qualities. In the following, I
introduce two areas of research relevant for a hauntological examination of A Knight's
Peril. The first centres on critical examinations of the practices and effects of ‘making
atmospheres’ (Böhme, 2013, 2). The second foregrounds scholarship that considers the
ghostly temporality of atmospheres.

<hs>  Staging atmospheres</hs>
  ~~~~~~~~~~~~~~~~~~~

The practice of purposefully staging and manipulating atmospheres is pervasive, evident
amongst the landscape of shopping malls, festival markets, sports and grand events, public
spaces and other sites of managed social experience. In these locales, architects and
designers manipulate spaces and objects in order to generate ‘imaginative representations’
– generators which influence individual and collective behaviours and emotions (Böhme,
2013, 4). As Simpson notes, ‘through the design of a space and its particular
layout/configuration, different sorts of atmospheres might be produced, encouraged and
felt’ (2017b, 430). Such generators include the myriad ways in which space can be
manipulated through, for example, light and illumination (Edensor, 2015, 2012; Bille,
2015), smell (Hudson, 2015), visual materials (Biehl-Missal, 2012), decay (DeSilvey, 2006;
Turner and Peters, 2015) and the wider urban environment (Bissell, 2010; Simpson, 2017b).
For Böhme (2013, 5) atmospheres and ambiances are a ‘felt presence … in space’ produced by
architects, designers and others (including non-humans) who shape the experiences and
affective and emotional connections or engagements to particular places. Designing or
staging atmospheres can range from the most extravagant (e.g. Olympic sporting events,
music festivals, etc.) to the everyday practice of care and management (e.g. sweeping a
pavement, planting flowers) of the built environment (Thibaud, 2015, 43). Yet, any ‘making
of atmospheres’ involves setting out the ‘generators’ which make it possible for an
atmosphere to materialise (Böhme, 2013, 3–4). Assembled in the material world, atmospheres
have social impacts. For example, atmospheres associated with consumption (Healy, 2014),
public space (Buser, 2017), securitisation (Adey, 2008; Urry et al., 2016) and other
cultural settings manage social experience. In these and other settings, the configuration
of material assemblages contributes to the emergence of feelings and emotions (Anderson,
2009) as well as the potential for action (or non-action). Nevertheless, Bille et al.
(2015, 36) argue that rather than reinforcing hegemonic positions, the staging of
atmospheres can work to ‘create discontinuities’ in understandings and experiences of the
world, pointing to the possibility to disrupt dominant views. Of course, such engineering
is never certain (Simpson, 2017b) as atmospheres emerge through the coming together of
bodies in uncertain ways. For example, at Bodiam Castle, while visitors may share
particular demographic characteristics, they can be affected by and experience atmospheres
in widely divergent ways reflecting bodily and social contexts, histories and dispositions
(Simpson, 2017b). Moreover, atmospheres can co-exist alongside one another without being
in conflict or fusing into something new (Anderson and Ash, 2015). Awareness of the
potential for multiple atmospheres means any attempt to forge a singular experience – as
is common in the design of historic or commemorative sites (Sumartojo, 2015) – is
problematic. Yet, while purposeful staging is pervasive, it is still commonly overlooked.
Very little scholarship has analysed how such atmospheres are created, or how they might
be used to counter dominant discourses (but see Duff, 2010; Thibaud, 2011; Emotion, Space
and Society Vol 15, 2015; Urry et al., 2016; Visual Communications Vol 7, 2016). Moreover,
little attention has been paid to examining the production of heritage from the
perspective of atmospheres (but see Turner and Peters, 2015; Sørensen, 2015). My research
seeks to continue the movement towards filling this gap.

<hs>  Temporality and spectrality in atmospheres</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The second area of scholarship on atmospheres of interest here calls attention to their
‘ghostly’, complex and multivalent temporality. The durability of any atmosphere is belied
by an incessant potential for transformation through the introduction or realignment of
objects, bodies, and affects (Anderson and Ash, 2015; Buser, 2017). Atmospheres are always
less solid than our representations. Moreover, as geographers have long argued, the
experience of space is socially situated, ‘ … usually conditioned by previous experience,
by habit, by familiar emotions and sensations that produce feelings of belongingness or
otherwise’ (Edensor, 2012, 1114). Yet, the material artefacts and affective resonances of
particular atmospheres and phenomena may linger and ‘circulate as a field of movement’
long after their disappearance or dissipation (McCormack, 2008, 425). In other words, the
material and emotional connections to particular places have their own duration which can
outlast any unique moment. These understandings reveal a paradoxical non-contemporaneity
of atmospheres – a temporal uncertainty that draws on aspects of nostalgia, memory,
repetition, expectation and anticipation (Edensor, 2012). Such insights defy efforts to
demarcate the ‘pure presence’ or the essential immediacy of any situation (Jameson, 1999,
58). For Bille et al. ‘ … atmospheres emerge as multi-temporal tensions: they are at the
same time a product of the past and future’ (2015, 34). This temporal indeterminacy
reveals the ways in which the time of atmospheres can seem out of joint5 (Derrida, 1994).
This is a hauntological conceit pointing to the ghostly folding of space and time (Maddern
and Adey, 2008) where the present, past and future cannot be cleanly divided but rather
are co-constitutive, with each always containing traces of each other. Atmospheres, in
other words, can express hauntological characteristics, constructed through the
‘persistences, repetitions, [and] prefigurations’ (Fisher, 2014, 29) of social experience.
These hauntological qualities are particularly evident in scholarship on the atmospheric
qualities of ruins and sites where ghosts have not been exorcised by the need to tell a
singular narrative and where the past is less fixed in place (Edensor, 2005, 2011;
DeSilvey and Edensor, 2012; Maddern, 2008; Gallagher, 2015). According to Edensor (2005,
834), the cluttered, disorganised and tangled qualities of these spaces produce an
‘excess’ where ‘memory is elusive, dependent upon conjectures about the traces of the
overlooked people, places and processes which haunt ruins’. Ruins, can express ghostly
qualities of indeterminacy and ambiguity where the past remains strange, not yet
eradicated or re-interpreted through dominant forms' memorialisation. Such spaces can draw
attention to the ways in which ‘our experience of the world is haunted’ such that the
‘past and future co-exist, and interact, in uncertain and unpredictable ways (Hill, 2013,
381). Within this scholarship, spectrality and the figure of the ghost is crucial to
understanding the less-than-settled, non-linear ways people experience the world. In
heritage spaces such as Bodiam Castle, ruination is a form of curation (Turner and Peters,
2015) where decay is visible, yet checked in order to facilitate haunting and evocative
experiences and to tell stories of the past.

<hs>  Staging atmospheres at bodiam castle</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The making of atmospheres at Bodiam Castle is entangled with issues of conjuration and the
deliberate practice of making (certain) traces of the past visible. This section is
organised around three analytical concepts. First, I examine how particular spectral
traces are made visible through narrative and the effects they have on both the modern-day
chronicle of the castle and the production of atmospheres at Bodiam. I then turn to the
role of sound in A Knight's Peril and how specific design techniques about how the
narration is delivered influences experiences and atmospheres. Finally, I consider the
spectral and anachronistic qualities of these elements and how these contribute to the
production of new, arguably richer, ways of experiencing and understanding the past.

        Conjuring ghosts and addressing representational silences: narrative in the atmospheres of A Knight's Peril

        Geographers are increasingly engaging with narrative and storytelling in research
        (see Cameron, 2012 for an overview). Here, I focus on the way stories and
        storytelling might be used to destabilise prevailing discourses (Bulken et al.,
        2015; Gibson-Graham, 2006; Pratt, 2009). A Knight's Peril is a form of
        storytelling that engages through ‘everyday’ characters. For the motivated
        visitor, the ‘official’ story of Bodiam Castle can be easily found in the National
        Trust guidebook or the DVD. These authoritative materials highlight information
        about the castle's builder (Sir Edward Dallingridge) and provide detailed reviews
        of the castle's design including the ubiquitous cross sections and renderings of
        the structure as it would have been in the 14th century. There is also information
        about individuals and families involved in the castle's conservation and
        restoration. These authoritative resources privilege particular medieval histories
        and serve as ‘affective signals’ (Bissell, 2010, 279) which contribute to the
        types of atmospheres one might experience (Sumartojo, 2015) at historic sites such
        as Bodiam Castle. In producing A Knight's Peril project designers and historians
        did not want to retrace these traditional narratives but sought to approach the
        history of Bodiam Castle ‘from below’ (Poole, 2017, 10). According to Steve Poole
        (project historian), A Knight's Peril celebrates non-didactic, personalised ways
        of engaging people with past experience: ‘ … it requires them [participants] to
        enter into it and to interpret for themselves how things were. We try to feed in
        some context without saying “hey, listen, this is what you need to know”’.6 For
        Poole, interactive and sensory-based games offer heritage sites a means of
        ‘telling the story’ that is more intimate, engaged and varied than traditional
        means allow. It is through imagination and immersion into the narrative that this
        personalised form of heritage interpretation occurs. Central to the approach at
        Bodiam was the desire to tell a story about lesser-known characters.
        Unfortunately, records from 14th century England are limited and the ability to
        tell alternative stories or to speak confidently about everyday characters is
        constrained by medieval social systems and record keeping procedures. Set within
        patriarchal 14th century England, well-documented individuals are typically
        wealthy, male landowners or nobility. As a result, relatively little is known
        about women, children or the Bodiam household beyond Sir Dallingridge. This
        absence of evidence continues to influence the National Trust's representation of
        Bodiam and this period of history. For example, without formal documentation to
        substantiate their experiences, women and children are largely missing from the
        guidebook and DVD. A Knight's Peril attempts to overcome these representational
        silences by mixing known persons and commonly accepted facts with fictional
        characters and creative storytelling. The experience conjures a female child via
        fictional, 12-year-old Kate. As one historian noted, Kate was developed to
        generate visitor interest amongst young girls, but also to address a
        representational injustice: ‘we wanted a young woman to be the guide partly
        because this is such a … male dominated environment … it is easy to assume that
        men are the only doers and shakers in this event. Now, that's an impression
        created by the evidence because it is men who control the means of recording this
        and who were allowed any kind of formal role in politics and public life … ’.7
        Through A Knight's Peril, project designers and historians introduced a new
        historical form into the atmosphere of the castle. Kate shapes visitors'
        experiences and emotional responses to the material environment of Bodiam Castle.
        She is an ‘emotional opening’ (Gibson-Graham, 2006, 136) towards the construction
        of a counter-narrative. Several interviewees noted the importance of a female at
        the centre of the story and their experience of the castle. For some, her
        character was ‘appealing’8 and provided a sense of personal attachment – ‘I liked
        it because you could imagine you were Kate’.9 Others found it was the perspective
        of a child that made absences present. One father noted how he began to think
        about the nature of childhood in a 14th century castle (e.g. the difficulty
        getting around, the limited possibilities for play). Whereas previously castle
        life was about knights and battles, having a child tell the story and listening to
        his daughter's own reflections altered this frame10. New questions and thoughts
        about the castle emerged: What was life like for the child of a local nobleman?
        What kinds of games did she play? Who did she play with? Was she able to run and
        explore or was her life filled with work and hardship? Did she struggle to make
        her way though the winding stone staircases? Tracing through Bodiam at the behest
        of a spectral child coaxes particular forms of movement and bodily empathy
        (Edensor, 2005) about life at the castle. Conjured by historians and game
        designers, Kate's ghost possesses and guides modern bodies towards new
        understandings of history. Kate makes traces of what has been lost – here, the
        erasure of women and children – visible. Producing real material effects (Gordon,
        1997) in the atmospheres of the castle, Kate reminds us of the absences and makes
        them present in contemporary narratives of medieval history and the way visitors
        experience Bodiam. Embracing Kate's fictional qualities meant she represented
        those … ‘ … who just aren't in any records because they didn't know or because the
        records have been lost, or they're just not important people, so they don't get
        written down at all’.11 Within A Knight's Peril, ghosts are active agents in the
        production of Bodiam Castle's atmospheres. Their contribution within the narrative
        – as part of a new chronicle of the castle – sets in motion the repair of
        longstanding representational silences, disrupting conventional ideas about
        medieval castle life and constructing new understandings of the past.

        <hss>The echo horn and the sonic production of atmospheres</hss>

        During A Knight's Peril, participants listen to the voices and sounds of a 14th
        century castle. This sonic environment is transformative. Sounds, as Michael
        Gallagher notes, are not only capable of ‘activating feelings and emotions’ but
        also are ‘a kind of affect – an oscillating difference, an intensity that moves
        bodies’ (2016, 43; Duffy et al., 2016). Recently, geographers have shown
        increasing interest in diversifying sensual understandings social experience to
        include the role of sound (Gallagher and Prior, 2014; Hill, 2015). While there is
        insufficient space to review all of this literature, of particular relevance is
        research on the role of sounds and soundscapes in shaping the qualities of place
        (Anderson, 2004; Simpson, 2017a; Duffy and Waitt, 2013). This attunement to sound
        ‘calls attention to something that is ordinarily ignored’ (Gallagher and Prior,
        2014, 271) but which can greatly influence atmospheres. Moreover, geographers have
        shown how sounds ‘can produce particular embodied relationships with the past’
        (Simpson, 2017a, 91; Gallagher, 2015) Sounds contribute directly to how we come to
        understand particular spatial settings. As might be expected, sounds – in the form
        of dialogue and narration – are used in A Knight's Peril to convey meaning.
        Through the voice of Kate and the characters she encounters the audio communicates
        specific information for participants. For example, references to war with France
        and the recent Peasants' Revolt are included as contextual material that
        historians felt was important for visitors understanding of the time. In addition,
        at the end of each instalment, the audio provides clues and specific choices about
        who to follow and where to go next in the castle. As such, playing A Knight's
        Peril encourages a form of interacting with and moving through Bodiam Castle that
        requires careful listening and interpretation. In addition to these cognitive
        elements, the audio also affects participants in less reasoned ways. Most obvious
        was the hurried way in which players tend to move through the castle. Pleading
        with visitors to help solve the mystery, Kate's voice incites this urgency,
        prompting participants to ‘hurry up’. She implores, ‘we don't have much time’ and
        later, reflecting on the beauty of the castle she laments, ‘we don't have time to
        see all of it … we need to figure out who might want to hurt my father’. In my
        experience as a player and as witnessed during observation, this tended to produce
        repetitions of pausing to focus on dialogue and directions from the echo horn,
        followed by a quick dash to another room. Other, more ambient, sounds are
        introduced to facilitate imaginative connection to medieval life. At various
        points of the game visitors will hear: ‘traditional’ medieval music; banging and
        clattering of pots and pans in the kitchen; doors creaking open; the drawing and
        clashing of weapons; and the flight of arrows. These sounds reshape and adapt
        visitors' relation to the site by ‘amplify(ing) the haunted qualities’ (Gallagher,
        2016, 468) of Bodiam Castle. They bring ghosts to the surface of recognition.
        Particularly powerful is the conjuration of Kate – a remarkable and mysterious
        sonic moment that occurs when the echo horn comes in contact with the initial
        seal. At first, a faint voice can be heard, echoing and straining to gain players'
        attention. Soon, the echoes fade and the clear voice of 12-year-old Kate
        materialises. This ‘spectrality effect’ (Parkin-Gounelas, 1999, 128) disrupts
        certainties about the present. Echoes are a well-used storytelling device that
        often signal the crossing of a threshold and the jumbling or contamination of time
        and space. This spectral use of sounds is also a well-developed trope with
        connections to hauntological music (Sexton, 2012) where a range of aesthetic
        devices such as decay (e.g. a purposeful erosion of sound) and crackle used ‘to
        effect a ghostly infiltration of the present by the recent past’ (Gallagher, 2015,
        481; Fisher, 2014; Fisher, 2012). The sonic environment associated with A Knight's
        Peril deploys these techniques to facilitate the magical shift away from the 21st
        century and into the medieval past. Following the (hauntological) appearance of
        ghostly Kate, players enter the castle immersed in happenings of the 14th century.
        Indeed, one parent spoke about how his children became thoroughly immersed in the
        experience and noted how ‘the horn really activated it for them’.12 The audio
        device helped to bring these visitors into contact with the castle and its history
        and magnify emotional resonance. This father went on to explain how ‘they were
        really present and focused’ when participating in A Knight's Peril. Others noted
        how the horn itself was particularly memorable and helped Bodiam Castle stand out
        from other heritage sites. ‘we go to a lot of National Trust places and we often
        can't remember one from the other, they merge into one a bit, this would be quite
        different’13 ‘Sometimes one castle is like any other castle and this will probably
        help them to remember this castle in particular’14 These comments are illustrative
        of how the staging and making of atmospheres through sounds and audio devices can
        contribute to significant emotional resonance and meaning. This was a purposeful
        objective of the design team which sought to forge a strong sense of medieval life
        and attachment to the castle amongst participants through an engaged and immersive
        experience.15 Yet, this is not a total immersion. Of course, not all players
        experienced the game in the same way. Indeed, during my observations, some
        children were clearly bored, others concentrated intensely, while others simply
        used the echo horn as a piece of medieval fashion. Moreover, adults generally
        played along but were mostly supporting younger participants by pointing out spots
        on the map or repeating certain phrases from the narrative. It is evident that
        bodily capacities and social histories (Simpson, 2017b) played an important role
        in mediating experiences of A Knight's Peril and the emergence of atmospheres at
        Bodiam Castle. Moreover, sounds emanating from the game overlap with ‘live’ sounds
        of the castle as well as other the audio of players in the same room (multiple
        versions of the audio can be played and heard at once). It is an experience that
        some non-players I spoke with found frustrating and distracting to the otherwise
        tranquil atmospheres of Bodiam. Sounds are not universally received, but can
        variously enrich, ‘plague and pollute’ (Lorimer and Wylie, 2010, 7). Moreover, the
        overlapping of sounds associated with A Knight's Peril can differently mediate
        movements through the site (Gallagher, 2015). For some, this occurs in concert
        with Kate and her quest. For others, it can be a repulsing force. On these
        occasions, multiple atmospheres come into conflict and result in new relations and
        new atmospheres (Anderson and Ash, 2015). This affective-materialist perspective
        points to the ways in which sounds co-produce social space (Simpson, 2017a) and
        atmospheres (Doughty and Lagerqvist, 2016). The sounds (and associated audio
        devices) of A Knight's Peril contribute to the production of atmospheres at Bodiam
        Castle through diverse bodily relations (Simpson, 2017a) and hauntological
        techniques. Their contribution to conviviality of the site depends upon a range of
        contextual elements including one's angle of arrival (Ahmed, 2010). As Simpson
        (2017a, 91) notes, sounds are differently received and how ‘listening bodies’ are
        ‘disposed towards hearing those sounds’ has significant implications for the types
        of relations and atmospheres they can produce.

        <hss>Towards a hauntological understanding of atmospheres</hss>

        The time is out of joint. O cursed spite, That ever I was born to set it right!
        Nay, come let's go together. (Hamlet, Act 1, Scene 5, Page 8) In Specters of Marx,
        Derrida cites the above passage from Shakespeare as a provocation and challenge to
        linear understandings of time. Calling on the ghost of Hamlet's father, he draws
        attention to the possibility that pasts, presents and futures are more likely to
        be jumbled than linear or clearly compartmentalised. The ghost alludes to how
        past, present and future mix in our minds and our emotional connection to place.
        In other words, past histories and future expectations shape how we experience and
        interpret the present. In this section I apply Derrida's hauntological position to
        the concept of atmospheres, reflecting on the case of A Knight's Peril. I note the
        ways in which the atmospheres associated with the game draw on and reinforce
        disrupted, non-contemporaneous notions of time. The ghosts of A Knight's Peril
        attempt to destabilise visitors' sense that the past is fixed or inert. Kate, the
        central figure, arrives from the past, but she is clearly not the same as any
        individual named Kate from the 14th century. Neither alive nor dead, from the
        present nor the past – Kate's ghosts reveals the ontological instability
        associated with both atmospheres and hauntology. Her existence in the 21st century
        – a time where she does not belong – is anachronistic as she floats between and
        among various times and spaces of Bodiam Castle. Like atmospheres, she has an
        uncertain ontological status; never fully present, she remains with us and
        influences players' emotions and behaviour. Moreover, Kate makes demands of those
        in the present, recruiting visitors to solve the mystery and save Sir
        Dallingridge. During my research, this sense of urgency and desire to put right
        certain events of the 14th century were echoed by many participants. ‘I really
        liked just trying to help her’, one young visitor noted.16 Kate's ghostly presence
        pushes us and implores us to act. Of course, there is something more being asked
        than simply to play a game. Like the ghost of Hamlet's father, Kate is an
        apparition who provokes. Yet, she does not call for murderous retribution. Rather,
        her justice rests with our changed sense of the past. This new representational
        construct involves an expanded recognition of the lives of marginalised persons
        from medieval history. Moreover, her (re)appearance signals an as-of-yet future,
        traces of which we might only sense. Indeed, our work in the 14th century
        salvation of Sir Dallingridge is peripheral to the world it foretells – central to
        which is the possibility of a more equal and just future. This notion of equality
        in representation is something A Knight's Peril designers and historians sought to
        build into visitors' experience of the castle. By introducing the ghost of a young
        female child into the chronicle of the castle, new atmospheres are facilitated
        centring on playfulness and whimsy and new questions are asked – what was it like
        to be a young girl in this place? The making and conjuration of atmospheres at
        Bodiam Castle is not simply a memorialisation of the past. Rather, it is as
        Derrida might say, a ‘phantomatic mode of production’ (1994, 120) where visitors
        are not only encouraged to walk with ghosts, but where their spectral demands are
        taken seriously. Through simple yet evocative and engaging generators (e.g.
        hauntological sonic techniques), the atmospheres of A Knight's Peril take on a
        sense of openness which strengthens emotional connection and allows for ghosts and
        memories to take hold. This deliberate production of atmospheres is a conjuration
        that makes (in)visible particular stories (here, the experiences of women and
        children) through narrative and sonic design techniques. Moreover, by allowing
        space for ghosts it implies a renegotiation and disruption of the supposed
        stability between concepts such as presence and absence. At Bodiam Castle, the
        resulting social spaces make obvious the uncanny, non-linear nature of time (Hill,
        2013) and, for many people who play A Knight's Peril, facilitate powerfully
        emotional and resonant experiences. Such efforts are part of a hauntological
        strategy of remembrance which does not exorcise ghosts, but conjures them, drawing
        attention to the ‘discontinuities and irruptions’ which characterise processes of
        memory (Edensor, 2005, 829).

<h>CONCLUSION</h>
----------

This paper studied the production and staging of A Knight's Peril at Bodiam Castle. The
research examined particular representational and material elements associated with the
game including the characters created and deployed as well as the use of hauntological
sonic and aesthetic techniques. Building on scholarship in emotional and cultural
geography (Wylie, 2007; Maddern, 2008; Sørensen, 2015; Edensor, 2012; Bille et al., 2015)
this research detailed the ways in which historians and designers sought to intentionally
shape experiences and emotional responses to Bodiam Castle through the production of
atmospheres. Endeavouring to address a representational silence of medieval history – the
widespread absence of women and children in historical accounts – the design team not only
conjured the ghost of Kate Dallingridge, but exploited a suite of hauntological tropes
(e.g. echo, decay, anachronism) to disrupt conventional readings of the past. Drawing on
these techniques, the atmospheres of A Knight's Peril can be seen as purposefully staged
framings which – under certain circumstances – can re-order visitors' understandings of
the medieval history and potentially disrupt hegemonic views and assumptions about the
world. Bringing Derrida’s (1994) concept of hauntology to the study of atmospheres, the
paper explored the role of spectrality in the production of A Knight's Peril. Similar to
atmospheres, ghosts belie ontological certainty. To think of the atmospheres at Bodiam
Castle as hauntological is to suggest that there is something ‘out-of-joint’, not just
right or uncanny about them. I argue that temporal uncertainty, facilitated via the figure
of the ghost, is one way in which A Knight's Peril gains its emotional and affective
power. This suggests that research which examines spectrality in the making of atmospheres
(within or outside heritage contexts) can help understand the effects designers have on
the moods, emotions and behaviours of people in social spaces.

<h>FUNDING</h>
-------

This research for was made possible by an Alumni Award from REACT, the South West creative
economy hub established by the Arts and Humanities Research Council (AH/J005185/1).


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<ART>The unfolding argument: Why IIT and other causal structure theories cannot explain consciousness
================================================================================

Authors: Adrien Doerig, Aaron Schurger, Kathryn Hess, Michael H. Herzog
DOI: 10.1016/j.concog.2019.04.002
Year: 2019  |  Pages: 49-59
ASJC codes: 3204, 3205
Keywords: Causal structure, Consciousness, IIT, Neural networks, RPT, Theories

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

How can we explain consciousness? This question has become a vibrant topic of neuroscience research in recent decades. A large body of empirical results has been accumulated, and many theories have been proposed. Certain theories suggest that consciousness should be explained in terms of brain functions, such as accessing information in a global workspace, applying higher order to lower order representations, or predictive coding. These functions could be realized by a variety of patterns of brain connectivity. Other theories, such as Information Integration Theory (IIT)and Recurrent Processing Theory (RPT), identify causal structure with consciousness. For example, according to these theories, feedforward systems are never conscious, and feedback systems always are. Here, using theorems from the theory of computation, we show that causal structure theories are either false or outside the realm of science.

--------------------------------------------------------------------------------


<hs>  Consciousness and empirical data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We wake up every day and transition from an unconscious to a conscious state. Surely,
there is something to explain. In binocular rivalry and visual masking, we can render
clearly visible stimuli invisible. Surely, there is something to explain here too. These
examples and many others are routinely used by the scientific community as a means to
study consciousness and are at the heart of all empirically-minded theories of
consciousness (Fig. 1a). Because of the subjectivity of consciousness, the dependent
measures in these experiments are subjective reports (or other measurements known to
reliably correlate with subjective reports). We cannot use measures of brain activity as
a-priori indicators of consciousness because we want to understand how brain activity
gives rise to consciousness in the first place.

<hs>  Causal structure theories of consciousness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Theories of consciousness aim to explain how changes in the proposed mechanism lead to
changes from unconscious to conscious states and vice versa. To do so, a number of
theories propose that the essential element for understanding consciousness is how parts
of a system interact. If a system has the “right” kind of causal structure, in other
words, if its elements interact in the “right” way, it is conscious. Otherwise, it is not.
We call such theories causal structure theories. For example, in Recurrent Processing
Theory (RPT), Lamme proposed that recurrent processing is both necessary and sufficient
for consciousness (Lamme, 2006). The first sweep of visual feedforward processing is
unconscious. Consciousness kicks in when recurrent, top-down processing interacts with
neurons activated during the initial feedforward sweep (Lamme, 2006). According to RPT,
what matters is the causal structure because consciousness depends only on how neurons
interact with each other: when there is recurrent processing there is consciousness, and
there is no consciousness otherwise. Empirical support for RPT was proposed to be provided
by neurophysiological experiments (Fig. 1c) in which recurrent processing enhanced neural
activity in V1 when visual stimuli were consciously perceived. When the stimuli were not
consciously perceived (during anaesthesia or when the stimuli were masked), there was no
recurrent processing (Fahrenfort, Scholte, & Lamme, 2007). Information Integration Theory
(IIT) is another example of a causal structure theory of consciousness. IIT proposes that
an information integration measure called ϕ, which is computed based on the causal
structure of a system, quantifies consciousness (Oizumi, Albantakis, & Tononi, 2014).
Consciousness is identified with ϕ > 0 systems: if elements of a system interact in the
“right” way, the system has ϕ > 0 and is conscious. If ϕ = 0, it is unconscious. For
example, ϕ is always greater than zero in recurrent systems (they are always conscious)
and always equal to zero in feedforward systems (they are never conscious). Empirical
support for IIT was asserted to be provided by studies showing that a practical proxy of ϕ
is low in coma, intermediate in minimally conscious states, and maximal during wakefulness
(Casali et al., 2013; Tononi, Boly, Massimini, & Koch, 2016). IIT and RPT were amongst the
first theories of consciousness to make precise predictions about which systems are
conscious. As such, they contributed greatly to the advancement of the science of
consciousness. However, we will show that causal structure theories end up in an empirical
impasse for principled reasons: they are either false or outside the realm of science.

<h>THE UNFOLDING ARGUMENT</h>
----------------------

Recurrent neural networks are universal function approximators (Fig. 2; Schäfer &
Zimmermann, 2006). That is, any input-output function can be approximated to any degree of
accuracy. Vision is such an input-output function. For example, pictures of animals are
presented as inputs on the retina, and the outputs are the elicited percepts of animals
(or reports about these percepts). Likewise, the stimuli in a visual masking experiment
are inputs, and the outputs may be button presses, verbal reports or any other measure
shown to reliably correlate with subjective reports. Importantly, experiments which
intervene directly on the brain, for example using implanted electrodes or Transcranial
Magnetic Stimulation (TMS) are still input-output functions. The only difference is that
part of the input is provided by means of electrodes or TMS rather than through the
sensory organs. Feedforward neural networks are also universal function approximators
(Fig. 2; Hornik, Stinchcombe, & White, 1989). Hence, for a given input-output function we
can find both feedforward and recurrent networks that realize the same function in
different ways (LeCun, Bengio, & Hinton, 2015; Oizumi et al., 2014; Werbos, 1988). For
instance, if there is a recurrent network that performs image recognition, there is an
equivalent feedforward network that does it equally well. If there is a recurrent network
that exhibits the characteristics of binocular rivalry, there is an equivalent feedforward
network that does so too. If there is a recurrent network that takes a collection of spike
trains as input and outputs another collection of spike trains, there is an equivalent
feedforward network that does the same thing. Anything that can be done by recurrent
networks can also be done in a feedforward manner (Fig. 2). We call this unfolding: any
recurrent network can be unfolded into a feedforward network implementing the same
function. In particular, any behavioural experiment can be seen as an input-output
function, and can thus be implemented by both recurrent and feedforward networks. Any
input-output behaviour can be implemented not only by one particular feedforward network,
but also by infinitely many equivalent feedforward networks and by infinitely many
equivalent recurrent networks, because the universal approximator property does not depend
on structural details such as the number of layers or on the precise connectivity. In
fact, given an input-output function, we can find infinitely many networks, each with a
different ϕ, that all realize the same input-output function (see Appendices A and B, see
also Chalmers, 2018). Moreover, the universal function approximator property is not
restricted to neural networks but also holds true for Turing machines, cellular automata,
cyclic tag systems, and more generally for any universal computing system (Turing, 1937;
Wolfram, 2002). These facts are uncontroversial and widely accepted (including by
proponents of IIT: see Oizumi et al., 2014).

<hs>  Implication I: causal structure theories are doubly dissociated from empirical data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

An implication of the unfolding argument is that causal structure theories are either
false or outside the realm of science. In other words, causal structure theories are
doubly dissociated from empirical data: they are neither necessary nor sufficient to
explain empirical data (see Fig. 3). For example, according to IIT, the level of
consciousness varies with ϕ. A system is conscious if, and only if, ϕ > 0 (oblique red
arrows in Fig. 3).1 An experiment can be seen as an input-output function (Fig. 2). Hence,
for any recurrent system with ϕ > 0 that reproduces the outcome of an experiment, there
are feedforward systems with ϕ = 0 that also reproduce the outcome. According to IIT, one
system has consciousness but the other does not. Conversely, for any feedforward system
with ϕ = 0, there are recurrent systems with ϕ > 0 that produce the same experimental
results. In fact, we show in Appendix A how to implement any function with ϕ = 0 or with
arbitrarily high ϕ. That is to say, for each system that provides evidence for IIT, there
are other possible systems that falsify it. This argument generalizes to any causal
structure theory, not just IIT. All causal structure theories are doubly dissociated from
empirical results about consciousness. Hence, it makes no sense to provide experimental
evidence for causal structure theories. For example, the figure-ground experiment
mentioned earlier cannot support or be explained by RPT because there are feedforward
networks that make the same subjective reports as humans when they consciously see the
figure, but are unconscious according to RPT. Conversely, there are networks with
recurrent activity that make the same subjective reports as humans when they do not
consciously perceive the figure, but are conscious according to RPT. Likewise, the finding
that awake humans have higher ϕ than sleeping humans cannot be explained by or support IIT
because there are feedforward networks with human wakefulness characteristics, and
recurrent network with human sleep characteristics. Our arguments are not only of an
abstract mathematical nature. In real life, there are many examples where feedforward and
recurrent networks realize the same complex functions. For example, deep reinforcement
learning has been implemented with purely feedforward convolutional networks to achieve
super-human performance in Atari video games (Mnih et al., 2013). Hausknecht and Stone
(2015) replicated this superhuman performance using recurrent networks. The unfolding
theorems tell us that this is not surprising because we can always find equivalent
feedforward and recurrent networks. These systems are empirically identical (to a close
approximation). One is conscious but the other is not, according to causal structure
theories. Moreover, unfolding provides a recipe to build two small robot systems with
exactly identical input-output functions but different causal structure (see Appendices A
and B). Experiments on one robot support the theory; experiments on the other falsify it.
The unfolding argument shows that there are always systems that empirically falsify causal
structure theories. Proponents of IIT try to avoid this problem by claiming that systems
with ϕ = 0 are unconscious despite being empirically indistinguishable from conscious
systems (Oizumi et al., 2014). We will show next that this claim makes IIT circular, and
therefore unfalsifiable. In other words, causal structure theories are falsified by the
unfolding argument, unless they decide to become unfalsifiable. For example, proponents of
IIT may still insist that the robot with ϕ = 0 is unconscious whereas the one with ϕ > 0
is conscious, owing to their differing causal structure. However, such a proposition
quickly ends up in circularity because we have no criteria to settle the matter. In
particular, we have no empirical criteria because experimental results about consciousness
are all identical for the two robots. The only reason to believe that only the ϕ > 0 robot
is conscious is to already believe in IIT, but this is circular. The situation is even
worse: there are many causal structure theories, such as IIT and RPT. Which one is the
“right” one? Even within IIT, the axioms do not uniquely determine ϕ (Barrett & Mediano,
2019; Bayne, 2018), and different empirical measures of ϕ yield very different results
(Mediano, Seth, & Barrett, 2018). Which version of IIT is the “right” one? We can never
decide because we have no criteria to test the theories and pit their predictions against
each other. We are left with the conclusion that there are different types of
“consciousness” (i.e., consciousnessIIT_version_1, … , consciousnessIIT_version_n,
consciousnessRPT, and so on), depending on which theory we favour. Insisting that the
robot with ϕ = 0 is unconscious whereas the one with ϕ > 0 is conscious even though they
are empirically identical leads IIT outside the realm of empirical science. To summarize
the unfolding argument, the conclusion follows from four premises. (P1): In science we
rely on physical measurements (based on subjective reports about consciousness). (P2): For
any recurrent system with a given input-output function, there exist feedforward systems
with the same input-output function (and vice-versa). (P3): Two systems that have
identical input-output functions cannot be distinguished by any experiment that relies on
a physical measurement (other than a measurement of brain activity itself or of other
internal workings of the system). (P4): We cannot use measures of brain activity as
a-priori indicators of consciousness, because the brain basis of consciousness is what we
are trying to understand in the first place. (C): Therefore, EITHER causal structure
theories are falsified (if they accept that unfolded, feedforward networks can be
conscious), OR causal structure theories are outside the realm of scientific inquiry (if
they maintain that unfolded feedforward networks are not conscious despite being
empirically indistinguishable from functionally equivalent recurrent networks).

<hs>  Examples</hs>
  ~~~~~~~~

Imagine that one could surgically replace the brain’s native recurrent sound processing
system with an equivalent feedforward implant. The implant takes the same collection of
spike trains as inputs, and outputs the same collection of spike trains as the native
brain areas. We know that such implants exist in principle because of the previously
mentioned unfolding theorems. Even though the causal structure in the new implant is
completely different, the rest of the brain does not notice any difference.2 The brain can
do its normal job. This means that all subjective reports by the person are identical
before and after the surgery. The person will claim all the same things about sound as
before the implant was placed, such as “I hear the drizzle of the rain, it is music to my
ears”, or “I understand what you are saying”, etc. In particular, any experiment about
which sounds are consciously perceived will yield exactly the same results as with the
native brain area. Therefore, we end up with the dilemma mentioned earlier: either causal
structure theories are wrong (if they accept that there is still auditory consciousness
with the implant), or they are outside the realm of science (if they claim that
consciousness is different with and without the implant even though there are no empirical
differences). We can push the example further to entire brains. Since anything that can be
done with a recurrent network can also be done with a feedforward network, there could be
«feedforward brains» that behave exactly like human brains. Such systems would have all
the same functional characteristics as a normal human brain, but completely different
causal structure. They behave exactly like a human in all respects, passing the Turing
test seamlessly. However, according to causal structure theories, they are not conscious
because they do not have the “right” kind of causal structure. Crucially, these systems
respond to any empirical experiment exactly like humans. For example, they identically
describe what it is like for them to see red, hear sounds, have memories, and so on. They
respond to all scientific paradigms (such as masking, binocular rivalry, figure-ground
segmentation, etc.) in exactly the same way. They exhibit the same wakefulness
characteristics and the same sleep characteristics. In summary, no behavioural experiment
can distinguish between human brains and feedforward brains in principle. Therefore,
either causal structure theories are wrong or they are outside the realm of science.

<hs>  Implication II: conscious content in IIT is doubly dissociated from experiments</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In causal structure theories the content of consciousness is also doubly dissociated from
empirical observations. For example, we can construct systems that behave as having
experience X when, according to IIT, they are in fact experiencing Y (see Appendix C). For
example, a system participating in a rivalry experiment may report that it is seeing the
cat image when, according to IIT, it is experiencing the smell of ham. In principle, as
shown in the appendix, it can experience any content of consciousness while reporting that
it sees a cat. Of course, it could also experience seeing a cat, but this would just be a
coincidence, showing a double dissociation. There is a straightforward reason why causal
structure theories are vulnerable to the kind of arguments presented here. All that is
required for a system to be conscious is a particular causal structure. At the same time,
any function can be implemented by many different systems with different causal
structures. Hence, there can be no consistent link between causal structures and
experimental results.

<hs>  Network efficiency & evolutionary constraints</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In practice, the brain has to cope with very strong space and energy constraints:
processing must be efficient enough to be contained within a small skull, and energy
consumption must be limited. Experiments have suggested that, indeed, sufficiently complex
tasks can strongly constrain network properties, when the number of neurons is limited
(Khaligh-Razavi & Kriegeskorte, 2014; Nayebi et al., 2018; Yamins et al., 2014). In
general, feedforward networks require many more neurons to implement a function than
equivalent recurrent networks with more efficient causal structure and are therefore
impractical (but not always: for instance image recognition is more efficiently
implemented in feedforward convolutional networks). In this regard, causal structure
theories may turn out to be good markers for consciousness. For example, high ϕ has
obvious functional benefits, such as efficiently integrating information. We argue that
awake brains have high ϕ for this functional reason. Hence, causal structures may be good
correlates for consciousness in humans not because they are identical with consciousness,
but because they correlate well with neural information processing in general, which
happens to covary with conscious state in humans as a contingent rule. This explains why
causal structure theories may provide human consciousness-meters (see for example Casali
et al., 2013). However, it is an entirely different thing to identify consciousness with
causal structure. In short, brains are recurrent because brain processing must necessarily
fit inside a skull, not because consciousness is identical with the brain’s causal
structure.

<hs>  The unfolding argument vs. the zombie argument</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The zombie argument is a well-known argument aiming to show that physicalist and
functionalist theories cannot account for consciousness. Imagine unconscious “zombies” who
are empirically indistinguishable from conscious “non-zombie” equivalents. For example, if
a zombie inadvertently places its hand on a hot stove, it yells “ouch” and immediately
retracts its hand, just as the non-zombie does. However, the zombie does not feel pain.
The 3rd person, observable properties are all identical between zombies and non-zombies,
but consciousness differs. Whether or not zombies are in fact possible is heavily debated
(e.g., Dennett, 1991). However, if they are, it follows that consciousness cannot be
explained in the standard, functionalist framework of science (this is the hard problem of
consciousness; Chalmers, 1996). Indeed, if functionally identical systems (the unconscious
zombie and its conscious non-zombie equivalent) can have different consciousness, then
functional approaches cannot explain consciousness. The unfolding argument is very
different from the zombie argument for two reasons. First, the zombie argument aims to
dismiss all physicalist accounts of consciousness, including functional ones. In contrast,
the unfolding argument only targets causal structure theories of consciousness, and not
physicalist or functionalist theories in general. In fact, the unfolding argument favours
functionalist theories because (un)folding a network changes only its causal structure but
not its function or physical nature. Other major theories of consciousness, such as Global
Workspace Theory (GWT; Baars, 1997; Dehaene & Naccache, 2001), Higher-Order Thought Theory
(HOTT; Lau & Rosenthal, 2011; Rosenthal, 2004) or Predictive Processing Theory (PPT;
Friston, 2013) are not affected by the unfolding argument, as we show in the next
subsection. Second, one can choose to dismiss the zombie argument by claiming that zombies
are in fact not possible (e.g., Dennett, 1991). In contrast, the existence of unfolded
systems is a straightforward mathematical fact, and not a mere thought experiment. In
fact, unfolding provides a recipe for creating empirically identical networks with
different causal structures (for example, with arbitrarily high ϕ; see Appendix A and B).
As mentioned, there even are real-world cases of feedforward and recurrent agents
performing the same complex task (see Section 2.1). Hence, for example, the fact that we
never have observed an unfolded cortex in practice (and probably never will) is not by
itself a sufficient argument to call into question the unfolding argument. Furthermore,
even though unfolded brains are impractical, we explicitly showed that the unfolding
argument does not rely only on unfolded whole brains (see the previous example with the
auditory system). This example can be scaled down again to the smallest part of the brain
proposed to be relevant for consciousness by a given causal structure theory.

<hs>  Non-causal structure theories of consciousness are not subject to the unfolding argument</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Global Workspace Theory (GWT; Baars, 1997; Dehaene & Naccache, 2001), Higher-Order Thought
Theory (HOTT; Lau & Rosenthal, 2011; Rosenthal, 2004) or Predictive Processing Theory
(PPT; Friston, 2013) are examples of functionalist theories of consciousness: they focus
on functions proposed to be crucial for consciousness. The unfolding argument does not
apply to these theories because they propose that systems are conscious insofar as they
implement the right kind of function – independently of the causal structure. Of course,
these theories are usually couched in terms of recurrent or top-down processing, or other
seemingly causal-structure terminology, but they can be formulated in other kinds of
networks too. The unfolding argument only applies to theories in which reccurence per se
(or another proposed causal structure) is necessary and sufficient for consciousness. For
example, the typical description of GWT is that consciousness occurs when cortical areas,
which code for certain contents of consciousness (e.g., sensory areas), “broadcast” their
information in a global neuronal workspace that consists of highly recurrent fronto-
parietal areas, thus making these contents globally available for widespread use by other
areas. The crucial functions here are (a) the creation of contents in sensory areas and
(b) making these contents globally available for widespread use by other areas (i.e.,
broadcasting). GWT is usually explained with recurrent networks. Still, equivalent
feedforward networks can maintain the same broadcasting function (see Fig. 4 for a toy
model).3 Similar toy models are easily produced for HOTT, PPT and all other functionalist
theories. What matters is the function, e.g., broadcasting, but not the (neural)
implementation. In summary, functionalist theories differ importantly from causal
structure theories in that they propose functions as crucial for consciousness,
independently of their implementations. For example, an unfolded global workspace network
retains the crucial function of broadcasting. Hence, by their very nature, functionalist
theories are not subject to the unfolding argument.

<hs>  Unfolding & the correlation approach</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

For many researchers, consciousness is non-physical and cannot be studied using input-
output functions, and therefore might be impossible to explain with standard neuroscience
(Chalmers, 1996). In this case, it is impossible to study consciousness directly. However,
consciousness may still be linked to neural states by bridging principles based on
correlations (Chalmers, 2004; Varela, 1996). For example, we may find correlations between
human reports about their conscious experience (first-person data: I am experiencing a
face) and observable properties of the brain (third person data: neural activity in the
fusiform face area). To quote Chalmers (2004): «In the case of consciousness, we can
expect systematic bridging principles that underlie and explain the covariation between
third-person data and first-person data.» This approach cannot hold for causal structure
theories because of the unfolding argument (Fig. 5). As mentioned, there are infinitely
many equivalent systems that produce exactly the same first person reports as humans, but
with completely different causal structures. Therefore, linking conscious properties with
the brain’s causal structures by relying on first person reports cannot succeed (Fig. 5).
The correlation approach cannot work with causal structure theories, although it may (or
may not) succeed for other theories of consciousness.

<h>CONCLUDING REMARKS</h>
------------------

To be considered scientific, IIT and other causal structure theories require empirical
support. However, the unfolding argument shows that they are either false or outside the
realm of science. For the same reason, different causal structure theories cannot be
compared with each other. For example, different mathematical formulations of IIT’s axioms
lead to different predictions about which systems are conscious, but we cannot compare
them because the predictions are doubly dissociated from empirical data. Proponents of IIT
have previously acknowledged that feedforward and recurrent networks can be functionally
equivalent but have different consciousness, according to IIT (Oizumi et al., 2014). In
other words, they share the same uncontroversial starting point as we do. However,
conclusions differ strongly. Proponents of IIT suggest that this should prompt us to focus
on the subjectivity of consciousness. In contrast, we conclude that adopting a causal
structure theory precludes any experimental approach to consciousness. Indeed, we have
shown that all possible experimental results, including the ones focussing on
subjectivity, do not depend on causal structure. The unfolding argument rules out a class
of explanations of consciousness wherein consciousness supervenes on causal structures.
This should prompt us to turn our attention elsewhere in trying to understand
consciousness. In this respect, the unfolding argument suggests that consciousness must be
explained on a more abstract level than that of neural wiring. Indeed, any proposed
framework based on neural connections suffers from the unfolding argument: any network can
be replaced by equivalent feedforward networks with different connections that lead to
identical empirical observations about consciousness. Only theories that abstract away
implementation details and focus on explaining which kinds of functions are important for
consciousness can avoid these challenges. To remain within the realm of science,
consciousness must be described in terms of what it does, and not how it does it.


<h>REFERENCES</h>
----------

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<ART>The use of discrimination scaling tasks: A novel perspective on the development of spatial scaling in children
================================================================================

Authors: Katie A. Gilligan, Alex Hodgkiss, Michael S.C. Thomas, Emily K. Farran
DOI: 10.1016/j.cogdev.2018.04.001
Year: 2018  |  Pages: 133-145
ASJC codes: 3204, 3205
Keywords: Development, Discrimination scaling task, Relative scaling strategies, Spatial Scaling

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Spatial scaling is the ability to transform distance information between shapes of differing sizes. Research on the developmental trajectories of spatial scaling beyond the pre-school years has been limited by a lack of suitable scaling measures for older children. Here we developed an age-appropriate discrimination scaling task, and demonstrated that children (N = 386) achieve performance gains in spatial scaling skills between 5 and 8-years-of-age, after which no significant improvements were found. Furthermore, the results support the use of relative distance strategies for task completion. These findings contrast to localisation paradigms, where performance reaches a plateau by age 6 and mental transformation strategies are used for scaling. The finding that scaling skills continue to develop until 8 years highlight the potential of scaling interventions in the early primary school years. Such interventions may infer direct benefits on spatial thinking and indirect advantages for science, technology, engineering and maths (STEM) achievement.

--------------------------------------------------------------------------------


<hs>  Overview</hs>
  ~~~~~~~~

To successfully navigate, individuals must be capable of representing their own location
with reference to their external environment. Hence, navigation within an environment is
inherently dependent on spatial thinking. Furthermore, the use of common navigation aids
such as maps or GPS systems to assist navigation requires effective spatial scaling, a
particular sub-domain of spatial cognition. Spatial scaling is the ability to transform
distance information from one representation to another representation of a different size
(Frick & Newcombe, 2012). Scaling requires comprehension of both the symbolic and spatial
correspondence between a map (model), and an associated referent space, in addition to the
ability to mentally manipulate and transform spatial information between spaces of
different sizes. Beyond navigation, spatial scaling is also associated with success in
aspects of mathematics. For example, spatial scaling skills explain a significant
proportion of the variation in proportional reasoning, above that explained by verbal
intelligence (Möhring, Newcombe, & Frick, 2015). Across other domains of spatial thinking,
significant age based differences in performance have been reported for children up to 8
years of age. For example, children’s performance on tasks such as perspective taking,
mental folding and mental rotation improve until at least 8 years with significant
individual variation reported at all ages (for example see, Frick, Möhring, & Newcombe,
2014; Newcombe, Uttal, & Suater, 2013). However, no suitable measure is available to
explore the development of spatial scaling throughout the primary school years. Hence,
this study aims to develop a spatial scaling measure suitable for the investigation of
both developmental differences and individual differences in scaling performance in
children aged 5–10 years.

<hs>  The development of spatial scaling</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Traditional Piagetian theories suggest that the skills required for spatial scaling are
not evident until 10–11-years-of-age when children no longer hold topological views of
spatial concepts (Piaget and Inhelder, 1948; Piaget & Inhelder, 1948, 1956, 1967). In
contrast, more recent evidence suggests that some prerequisite skills required for spatial
scaling including symbolic correspondence and metric encoding emerge in early childhood
(e.g. Huttenlocher, Newcombe, & Sandberg, 1994; Newcombe, Sluzenski, & Huttenlocher, 2005;
Vasilyeva and Huttenlocher, 2004). First, comprehension of symbolic correspondence, or the
correspondence between a model and a referent space has been reported in children as young
as 3-years-old (DeLoache, 1987, 1989). At this age children recognise that features on a
map or model represent features in the real world. Second, metric encoding, or the ability
to encode distances metrically, has been reported in infants as young as 5-months-old,
with some infants demonstrating sensitivity to distance differences of just 20 cm
(Newcombe, Huttenlocher, & Learmonth, 1999; Newcombe et al., 2005). Similarly, Bushnell,
McKenzie, Lawrence, and Connell (1995) reported that 12-month-old infants can locate an
object which is hidden in a circular enclosure under one of many randomly placed identical
cushions. Given the lack of cues or landmarks and the random arrangement of the cushions,
this suggests an ability to use metric encoding relative to the participant, in order to
identify the correct cushion. Similar findings from Huttenlocher et al. (1994) propose
that metric encoding in children is robust by 16 months of age. Beyond these prerequisite
skills, there is also evidence that the ability to successfully map encoded distances
between different sized spaces, spatial scaling, develops at a younger age than suggested
by Piaget and Inhelder, with significant development in scaling proficiency between the
ages of 3 and 6 years (Piaget and Inhelder, 1948; Piaget & Inhelder, 1948, 1956, 1967).
Frick and Newcombe (2012) reported that children’s scaling ability, measured using a two-
dimensional localisation task, improves with age from 3 to 6-years-of-age, at which time
children’s accuracy levels are broadly comparable to adult scores. No significant
difference in performance between 5- and 6-year-old children was reported. In a similar
computer-based study, Möhring, Newcombe, and Frick (2014) demonstrated improvements in
spatial scaling across different scaling factors between the ages of 4–5 years. Similar
results have also been reported in studies using more naturalistic environments. For
example, Vasilyeva and Huttenlocher (2004) reported that 90% of 5-year-old children tested
could successfully place objects on a rectangular rug using a two-dimensional map. In
comparison, only 60% of 4-year-olds were successful when presented with the same task.
While some studies have reported accurate spatial scaling in children younger than 5
years, these findings may be attributable to the use of simplified tasks in which targets
are presented along a single dimension. For example, Huttenlocher, Newcombe, and Vasilyeva
(1999) reported accurate spatial scaling for most 3 and 4-year-old participants when
tested using a scaling paradigm with a single dimension, the horizontal axis. Similarly,
four-year-old children can successfully use a one-dimensional map to locate one of three
target bins in a rectangular room (Shusterman, Ah Lee, & Spelke, 2008). In contrast, in
more complex studies requiring scaling in two dimensions, 4 year-olds typically struggle.
For example, 4-year-old children struggle to correctly place an object in a target
location within a room, based on locations learnt from a corresponding map (Uttal, 1996).
To conclude, in contrast to findings from Piaget and Inhelder, 1948; Piaget and Inhelder
(1948, 1956, 1967), it appears that children as young as three years demonstrate symbolic
correspondence and metric coding, prerequisite skills for spatial scaling. Successful
performance on one and two-dimensional scaling tasks is typically evident from three years
and five years respectively. Importantly, although developmental differences are evident
in spatial scaling abilities, individual differences in performance are also reported for
scaling performance in children up to 10-years-old (e.g. Liben and Downs, 1993).

<hs>  Cognitive scaling strategies</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Comprehending the strategies used for spatial scaling, and identifying how these
strategies may change and adapt throughout development, may explain how and why spatial
scaling has been associated with other aspects of cognition, including mathematics.
Proposed cognitive strategies for spatial scaling include absolute, relative and mental
transformation strategies. Absolute strategies as described by Möhring, Newcombe, and
Frick (2016) involve absolute encoding of distance in one space with direct mapping of
this distance onto a second space. While effective for similarly sized spaces, this
strategy leads to reductions in accuracy when scaling between spaces of differing sizes.
Differences in response times between scaled and non-scaled spaces are not expected when
using this strategy, as the same cognitive mechanism, the direct mapping of absolute
distance, is applied regardless of scaling factor. In contrast, relative scaling
strategies involve the use of proportional distances (Huttenlocher et al., 1999). For
example, when using a map, a target location may be encoded as being one third of the
distance between two landmarks. This relative position (one third) can then be located on
a referent map of a different size. Applying this scaling strategy to spaces of differing
sizes leads to increased accuracy in comparison to absolute strategies. However, relative
scaling strategies do not lead to differences in accuracy or response times for scaled
compared to non-scaled trials, as a similar strategy is applied regardless of scaling
factor. Thirdly, mental transformation strategies require the mental expansion or
contraction of one space to match a second differentially sized space (Vasilyeva &
Huttenlocher, 2004). This technique requires distance coding, preservation of metric
distances and mental transformation. The use of mental transformation strategies is
expected to reduce accuracy with increasing scaling factor. This is attributable to the
fact that as scaling factor increases, the mental expansion (or contraction) required is
greater, making an accurate transformation more difficult. Furthermore, in line with
findings from mental rotation paradigms, response times are expected to increase with
increasing scaling factor (Möhring et al., 2016). As summarised in Table 1 each of the
aforementioned strategies of spatial scaling are associated with individual patterns of
performance, with increasing scaling factor. Recent findings suggest that mental
transformation strategies are required for effective spatial scaling (Möhring et al.,
2014, 2016). Evidence outlining linear increases in both error rates and response times
with increasing scaling factor have been reported in localisation tasks with children aged
4–5 years (Möhring et al., 2014) and both localisation and discrimination tasks in adult
populations (Möhring et al., 2016). These performance patterns fit with the proposed
mental transformation model of spatial scaling. However, there is also evidence supporting
the use of relative scaling strategies in spatial scaling. Frick and Newcombe (2012)
reported no linear increase in errors or response time with increasing scaling factor in
children aged 3–6 years. Despite reported reductions in performance accuracy for scaled
compared to unscaled trials, these results indicate the use of a relative scaling
strategy. Taken together, these conflicting findings suggest differences in the use of
spatial strategies across contexts and experimental paradigms.

<hs>  Features of spatial task design</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Scaling tasks typically require participants to use a map or model with a labelled feature
to identify a corresponding feature on a referent space. However, it appears that many
features of task design may influence performance on scaling tasks. Findings from Frick
and Newcombe (2012) demonstrate the positive influence of landmarks and other reference
points, as aids to effective spatial scaling. In contrast, reduced scaling performance is
seen in paradigms with high working memory demands. For example, accuracy appears to be
reduced when participants are required to remember the location of multiple targets, or in
cases where stimuli and referent spaces are not presented simultaneously (Uttal, 1996). As
previously described, dimensionality also influences success in spatial scaling paradigms.
Performance accuracy is higher and the age at with children can successfully complete
spatial scaling is lower for maps including targets distributed on one dimension (i.e.
targets distributed along a single, horizontal axis) compared to targets distributed on
two dimensions (i.e. targets distributed using a horizontal and vertical axis) (Vasilyeva
& Huttenlocher, 2004). Finally, limitations introduced by using technology for scaling
tasks, such as size limitations imposed by screen size, do not appear to influence scaling
performance. For example, Möhring et al. (2016) reported no significant differences in
scaling accuracy based on the absolute size of the stimuli presented. For each scaling
factor tested, participants were presented with a map and corresponding referent space. No
significant difference in accuracy was reported for trials in which the referent space was
smaller than the map compared to trials in which the referent space was larger than the
map. This suggests that the absolute size of the map and referent space used do not
significantly influence accuracy at a given scaling factor. However, no known studies
investigate the influence of level of acuity, on scaling accuracy at different scaling
factors. Here, we propose that the degree of sensitivity (scaling precision) required to
identify the correct answer is relatively low when the grid on which targets are presented
is less dense (fewer, larger squares within the same surface area). This makes scaling
accessible for younger children. However, for denser grids, we propose that the
sensitivity required is relatively higher. Hence, 10 × 10 grid trials may highlight
variation in the scaling abilities of older children. For example, the inclusion of both 6
× 6 and 10 × 10 grids may enable movement beyond the question of whether participants can
scale or not, allowing for the generation of a more sensitive metric for the precision of
individual’s scaling abilities. Recent developments in spatial scaling paradigms have been
led by Frick, Newcombe, Möhring and colleagues who have produced a series of spatial
paradigms aimed at limiting the cognitive load of scaling tasks and reducing the influence
of confounding factors (Frick & Newcombe, 2012; Möhring et al., 2014, 2016). For
localisation tasks, participants are shown the position of a target and are asked to find
the corresponding position on a referent space (for example see Frick and Newcombe, 2012).
Responses are coded as absolute deviation from the correct answer. For tasks using
localisation paradigms, ceiling effects are reported by 6 years of age (for example see
Frick & Newcombe, 2012). In contrast, one recent study of adults used a discrimination
rather than a localisation paradigm (Möhring et al., 2016). Participants were asked to
distinguish whether a referent map was a scaled correspondent of a target map, or not.
Within discrimination paradigms participant’s responses are encoded as correct or
incorrect. This mode of coding is less forgiving and does not afford any marks for
responses that are close to being accurate. As such this more stringent scoring method
leads to more discrete scores and may allow for the identification of subtler
developmental differences in performance in older children. Furthermore, the use of a
discrimination paradigm with multiple response options enables the categorisation and
analysis of error types. Whilst one might assume similar frequencies of errors along the
horizontal and vertical axes, a higher frequency of errors on the horizontal plane for
example, might suggest more inaccurate scaling on this, relative to the vertical plane.
Analysis of this type offers a novel insight into scaling processes.

<hs>  Current study</hs>
  ~~~~~~~~~~~~~

This study aims to extend previous findings by exploring age-based and individual
variation in spatial scaling using a novel, age-appropriate discrimination paradigm. The
results will be reported as a developmental profile of scaling ability in childhood from 5
to 10 years. The secondary aim of this study is to explore the cognitive strategies used
by children in the completion of discrimination tasks. Previous studies have highlighted
both mental transformation and relative encoding as possible cognitive strategies used in
localisation scaling paradigms in children under 6 years of age (Frick & Newcombe, 2012;
Möhring et al., 2014). However, findings from discrimination paradigms are limited to
adult populations (Möhring et al., 2016). It is unknown whether similar developmental
patterns in scaling performance and similar trends in cognitive strategy use, are seen for
localisation and discrimination tasks in children, in young and middle childhood (age 5–10
years). The findings from this study provide important evidence on the development of
spatial scaling by using a novel scaling task in which both scaling factor and required
level of visual acuity are manipulated to create a suitable measure of scaling for
children aged 5–10 years. The findings presented are vital for informing the design of
future spatial scaling interventions aimed at improving both spatial scaling and STEM
achievement more generally. Improved information on age-based differences, and indeed
individual differences in spatial scaling ability, will enable the identification of age
groups for which targeted scaling interventions may lead to greater gains. Furthermore,
information pertaining to cognitive strategy use in spatial scaling tasks will guide and
inform the approach taken in future spatial scaling interventions.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

This study included 386 participants across 6 age groups. Participants were aged between 5
and 10 years. Approximately equal numbers of males (55.2%) and females (44.8%)
participated in the study. All participants had normal or corrected to normal vision. The
sample size, mean age and gender ratios of each age group are shown in Table 2.
Participants were recruited from a middle-class, suburban London school in the UK.

<hs>  Procedure</hs>
  ~~~~~~~~~

Participants were tested individually in a quiet room in their school. In this task,
participants were required to choose which one of four onscreen referent maps matched a
printed model map. Model maps were either the same size as the on-screen referent maps, or
were scaled-up versions of the referent maps (further details in materials section). The
experimenter sat to the left of the participant while model and referent maps were
positioned in front of the participant as shown in Fig. 1. The experimenter introduced the
task as a pirate map game explaining that the yellow colouring on the maps represented
sand, while the black boxes were targets showing where hidden treasure was buried.
Participants were encouraged to respond as quickly and accurately as possible, by manually
pressing one of the maps on the screen to indicate their answer. Following each trial a
fixation dot appeared on screen, allowing the experimenter time to turn the page on the A3
flip chart and present the next trial. The task was presented as three blocks of six
experimental trials preceded by 2 practice trials with a scaling factor of 1. Feedback was
given for practice trials. For incorrect practice trials, participants were asked to
repeat the trial until the correct referent space was selected. Only participants
achieving at least 50% accuracy for practice trials (i.e. correctly answering at least one
of the two practice items on their first attempt), continued to the experimental blocks.
All participants successfully completed at least one of the practice trials. Between each
block the task instructions were repeated. Participants received no feedback on their
performance during experimental trials.

<hs>  Materials</hs>
  ~~~~~~~~~

Task stimuli included paper-based model maps and onscreen referent maps. Model maps were
presented on an A3 flipchart. Each map was positioned in the centre of a white A3 page.
Onscreen referent maps including both correct and distractor maps were presented on a 13
inch Hewlett Packard touch-screen laptop in a 2 × 2 arrangement. Model maps measured 8 cm
× 8 cm, 16 cm × 16 cm and 32 cm × 32 cm, for trials at a scaling factor of 1, 0.5 and 0.25
respectively. These scaling factors equated to trials in which the lengths of the referent
maps were, the same size, one half the size, and one quarter the size of the model map,
relative to the participant. All referent maps were 8 cm × 8 cm in size. The model and
referent maps were positioned equidistantly from the participant. Consequently, the
scaling factor in each trial was determined as the difference in the relative length of
the referent and model maps with respect to the participant. All maps including both model
and referent maps, were coloured yellow. Gridlines (for the model map only) and targets
were presented in black ink. The task included three blocks of six trials. Scaling factor
varied by block. Within each block, the overall area of the maps, and by extension the
scaling factor, did not change. However, the density of the grid on which targets were
presented, and hence the size of the grid squares and visual acuity of the maps varied. As
shown in Fig. 2, half of the trials in each block were presented using a 6 × 6 square grid
(requiring gross-level acuity) while the remaining targets were presented using a 10 × 10
square grid (requiring fine-level acuity). The targets displayed on each map were
methodically selected to ensure a balance of left and right side targets. No targets were
selected in the outer columns or rows of each grid. In order to counterbalance for any
unintended effects of target position, or block order, five versions of the task were
generated. First, for the initial set of targets generated, a second mirror-imaged target
set was generated. This counter-balancing controlled for any potential left-right bias in
target presentation. Second, to ensure that success on particular blocks could not be
attributed to the specific targets used, presentation of target sets was counterbalanced
between 0.5 and 0.25 scaling blocks. Overall, this created four versions of the task
(Versions A-D). For these versions of the task, the order of block presentation was fixed
and blocks were presented in order of increasing scaling factor (i.e. scaling factor was
set at 1, 0.5 and 0.25 for Block A, B and C respectively). Finally, to confirm that the
order of block presentation did not influence task performance, an additional version of
the task, Version A2 was added. The targets included in Version A2 were identical to those
in Version A. However, blocks B and C were presented in reverse order i.e. trials with a
scaling factor of 0.25 were presented before trials with a scaling factor of 0.5.
Approximately equal numbers of participants completed each task version. For each trial,
four onscreen referent maps were presented including 1 correct map (i.e. the scaled (or
unscaled) correspondent of the model map) and 3 distractor maps. As shown in Fig. 3, the
distractor maps displayed: a vertical distractor which displayed the target one row
directly above or below the correct target (A); a horizontal distractor which displayed
the target one column directly to the left or right of the correct target (B) and; a
diagonal distractor in which the target was positioned at one of the 4 diagonal positions
relative to the correct target (C). The onscreen position of the correct map relative to
the three distractor maps was randomised across trials with the correct map appearing in
each quadrant of the screen with equal frequency.

<hs>  Analysis strategy</hs>
  ~~~~~~~~~~~~~~~~~

Statistical analyses were completed using IBM SPSS Statistics for windows (version 22).
The use of parametric testing was determined by the outcomes of normality tests, the
presence of outliers, and the relatively large sample size in this study. Unless otherwise
reported, outcomes of parametric tests are reported. For analyses of variance (ANOVA)
including task version, block order, gender or age group, where equal variances could not
be assumed, the results for unequal variance are reported. Post-hoc Games-Howell or Tukey
tests were used appropriately in cases where the assumption of homogeneity of variance was
violated or met, respectively (Field, 2009). Performance accuracy, measured as percentage
of correct trials, acted as the dependent variable in accuracy analysis. There was no
missing performance accuracy data. However, thirty-two participants (Total N = 386) were
excluded as their performance accuracy on unscaled trials was below chance (25%),
suggesting that they were responding at random. Of those excluded, 15 participants were
aged 5 years old, 11 participants were aged 6 years and 6 participants were aged 7 years.
Mean response times for correct trials (ms), acted as the dependent variable in response
time analysis. In accordance with previous literature, any response times lower than 300
ms, or above 2.5 standard deviations from the median were treated as outliers and coded as
missing, prior to the calculation of mean scores (Leys, Ley, Klein, Bernard, & Licata,
2013; Ratcliff & Tuerlinckx, 2002). As mean response times were calculated from correct
trials only, it was not possible to calculate mean response times for participants who
failed to accurately complete at least one trial out of three for each trial type. As
such, we propose that the missing response time data in this study are not random but
associated with performance accuracy (for further information see Table A1 in Appendix A).
Hence, excluding participants with missing response time values for any trial type (as is
the case in complete case analysis) causes bias, with significant under-representation of
lower performing participants. Given this consideration, for this study, missing response
time data were replaced with plausible values using multiple imputation. Multiple
imputation is a statistical technique in which regression modelling is used to calculate
plausible values to be used in place of missing data (Rubin, 1987). The use of multiple
imputation in this study is supported by the availability of auxiliary variables including
performance accuracy and age, that can be included in the multiple imputation model as
causes of “missingness” (Collins, Schafer, & Kam, 2001). The number of imputations was
calculated using the guidelines set by Graham, Olchowski, and Gilreath (2007) based on
both the fraction of missing data (g) and the tolerance for power fall-off. In this study,
the fraction of missing response time information is 0.118 and the tolerance for power
fall-off was set at the lowest (most conservative) level, <1%. Based on these parameters,
it was determined that 20 imputations were required (Table 5, p212, Graham et al., 2007).
Hence, for imputed data the pooled results from 20 imputations are reported.

<h>RESULTS</h>
-------

Secondly, to compare the effect of block order (the order of presentation of blocks of
each scaling factor) on accuracy and response time, between subject t-tests (comparing
Version A and Version A2) were completed. The results indicated no significant effect of
block order on accuracy, t (146) = 0.256, p = .798, d = 0.042, or response time, t (146) =
0.653, p = .514, d = 0.108. As no significant effects of task version or block order were
reported, these factors were not included in subsequent analyses.

<hs>  Error patterns</hs>
  ~~~~~~~~~~~~~~

As shown in Fig. 7, chi squared analysis was used to investigate differences in the
relative proportions of Vertical (V), Horizontal (H) and Diagonal (D) type errors. For all
scaling factors, significantly higher proportions of H errors relative to V and D errors
were reported: unscaled trials: Χ2 (2, N = 693) = 64.944, p < .001; scaling factor of 0.5:
Χ2 (2, N = 948) = 84.994, p < .001; scaling factor of 0.25: Χ2 (2, N = 941) = 167.007, p <
.001. Fig. 8 highlights differences in the relative frequencies of V, H and D errors
across age groups. Chi squared analysis for each age group indicated significantly more H
errors compared to V and D errors for all age groups (p < .001 for all). Furthermore, V
errors occurred with significantly higher frequency compared to D errors for all
participants aged 8–10 years (p < .001 for all). However, there was no significant
difference in the frequency of V and D errors for participants aged 5 years, Χ2 (1, N =
268) = 0.731, p = .392, and participants aged 6 years, Χ2 (1, N = 240) = 1.667, p = .197.
For all analysis, N values indicate the number of trials.

<h>DISCUSSION</h>
----------

The primary aim of this study was to provide a developmental profile of spatial scaling in
children between the ages of 5 and 10 years of age. Overall, significant age-based
differences in scaling accuracy were reported. The results indicated performance gains in
spatial scaling between 5 and 8-years-of-age, after which no significant improvements in
task accuracy were found. These findings contrast with results from localisation
paradigms, where children’s accuracy on scaling tasks reaches a plateau by age 6 (Frick &
Newcombe, 2012; Möhring et al., 2014). Conversely, children’s scaling skills as measured
using this discrimination paradigm continue to develop until 8-years-of-age. These
contrasting results suggest that the scaling skills for placement, as required in
localisation tasks, differ from those of discrimination tasks, enabling younger children
to effectively complete tasks of this type (Frick & Newcombe, 2012; Möhring et al., 2014).
This may be attributable to the increased scaling precision required for discrimination
tasks, in addition to other domain general demands that may be needed for discrimination
paradigms, such as working memory or inhibition. The findings of this study also add to
previous literature on gender differences in spatial performance in childhood. Significant
differences in both accuracy and response time were reported such that females had
significantly faster but less accurate performance than males. This may suggest that
females are applying scaling strategies less effectively then males. However, these
findings should be interpreted in the context of the small effect sizes reported. These
results are consistent with previous studies on spatial thinking in which non-significant
or small effect sizes for significant gender differences between males and females were
found (Alyman & Peters, 1993; Halpern et al., 2007; Lachance & Mazzocco, 2006; LeFevre et
al., 2010; Manger & Eikeland, 1998; Neuburger, Jansen, Heil, & Quaiser-Pohl, 2011). The
secondary aim of this study was to explore the cognitive strategies used by children in
the completion of discrimination type scaling tasks. As previously outlined, specific
patterns of performance accuracy and response times in scaling tasks, have been associated
with different cognitive strategies including absolute, relative and mental transformation
strategies (see Table 1). As this study included a small number of trials at each scaling
factor, the findings pertaining to response time should be interpreted cautiously and seen
as complementary to the key findings on performance accuracy. Nonetheless, the findings
reported in this study indicated no significant increase in response time with increasing
scaling factor. Indeed for gross level trials, response times were significantly shorter
for trials at a scaling factor of 0.25 compared to unscaled trials. The results reported
can be interpreted in the context of the aforementioned cognitive strategies for spatial
scaling. Firstly, despite evidence that children use mental transformation strategies for
spatial scaling in localisation tasks (for example see Möhring et al. (2014)), the use of
mental transformation strategies is not supported in this study. This is particularly
interesting given that mental transformation strategies have also been reported for
discrimination tasks in adults (Möhring et al., 2016). However, the results reported in
this study show neither reduced performance accuracy nor increased response times with
increased scaling demands, which would be anticipated for mental transformation strategy
use. In contrast, as scaling demands increase, relative scaling strategies are associated
with unchanged accuracy and response times, while absolute strategies are expected to
generate reductions in performance accuracy only. The unusual pattern of results reported
in this study, and mirrored in previous work by Frick and Newcombe (2012), is not entirely
consistent with either of these models. Despite showing reduced performance for scaled
relative to unscaled trials, no reduction in accuracy with increasing scaling factor is
observed. As such the use of absolute strategies in the completion of this task is also
deemed unlikely. Although the pattern of results reported in this study is not a perfect
fit to the relative scaling model, both mental transformation and absolute strategies
provide poor explanations for these findings. Furthermore, despite findings from adult
populations where the physical size of the maps used was not found to significantly
influence scaling performance (Möhring et al., 2016), future research could investigate
whether the physical size of the maps used influences performance in discrimination
scaling tasks in children. Overall, the results support the use of relative strategies for
discrimination tasks of spatial scaling in children. As such, participants are proposed to
encode relative distances to solve scaling problems, for example by encoding that the
target is one third of the way between the two sides of the grid. These findings contrast
with those for discrimination paradigms in adults, where mental transformation strategies
are reported (Möhring et al., 2016). These findings can be viewed in the context of other
spatial domains such as mental rotation, for which there is evidence of variation in the
strategies used for task completion by different individuals at different developmental
stages (Geiser, Lehmann, & Eid, 2008; Glück, Machat, Jirasko, & Rollett, 2002; Janssen &
Geiser, 2012). Consequently, it is unsurprising that scaling tasks with differing
experimental paradigms may lead to the recruitment of differing scaling strategies.
Perhaps therefore, it would not be safe to assume that all children at all ages deploy the
same strategies in the completion of scaling tasks. Future studies should explore the
conditions under which individuals might be encouraged to use specific cognitive scaling
strategies, and whether particular features of task design promote the use of different
strategies. For example, in this study, the inclusion of four maps may have encouraged the
use of the relative strategy. Participants may have first encoded the target location,
using relative distance information, across a single dimension (e.g. the horizontal axis),
therefore enabling them to immediately discount some of distractors, before then
relatively encoding the remaining maps on the other axis. This is cognitively less
demanding than completing mental transformations on four individual maps. Furthermore, the
presence of grid lines on the model map may have encouraged the use of relative distance
information (i.e. the target is three units from the left of the map). The discrimination
task used in this study allowed for the categorisation of incorrect trials into discrete
error sub-categories. For all scaling factors and age groups, higher proportions of H
errors compared to V and D errors were reported. Furthermore, this pattern remained stable
across scaling factors. These findings indicate interesting overall differences in
individual’s mapping abilities on the horizontal and vertical axis. This suggests that
scaling demands do not induce specific negative effects for mapping on the horizontal or
vertical axis respectively. The uniform error patterns may also suggest that participants
use similar cognitive strategies to complete both scaled and unscaled trials. The use of
relative scaling strategies would fit with this pattern. These findings beg the question
as to why individuals appear to be more accurate in distinguishing D and V errors from the
correct target, compared to H errors. For D errors, there is less shared contact area with
the correct target. As such D errors are further away from the correct target and are
understandably the easiest error type to distinguish from the correct target. However,
shared contact with the target cannot explain the differences reported in the frequencies
of H and V type errors. Both of these error types have the same degree of contact with,
and are identical distances from the correct target. Alternatively, differences in the
frequency of H and V type errors may be attributable to the horizontal-vertical illusion
(Oppel, 1855). This is the illusion that a vertical line appears longer than a horizontal
line of the same length. This illusion leads to overestimations in vertical segments
relative to horizontal ones (Mamassian & de Montalembert, 2010). One explanation for this
phenomenon is that vertical lines may be perceived as “receding into the third dimension”
leading to perceptual errors in estimating spatial distance (p. 60, Girgus & Coren, 1975).
In the context of this study, over-estimating vertical distances would lead participants
to perceive V errors as further away from, and thus less likely to be confused with, the
correct answer. While studies assessing the horizontal-vertical illusion typically include
lines or dots displayed simultaneously on a single display (McGraw & Whitaker, 1999), the
findings of the current study suggest that the horizontal-vertical illusion may extend to
mapping tasks. Beyond this study, the implications of the horizontal-vertical illusion in
spatial mapping tasks is largely unknown. Future studies could explore differences in
horizontal mapping and vertical mapping using both localisation and discrimination
paradigms. Alternatively, the observed differences in the frequency in H and V type errors
may be attributable to the horizontal layout of the maps and referent spaces used in this
task. As participants were required to transfer their attention horizontally from the
target map to the referent spaces, focus may have been inadvertently directed to the
horizontal axis. Future research could compare performance on this task when maps and
referent spaces are presented using a vertical layout (i.e. with the target map presented
above or below the referent spaces). The use of a discrimination task in this study offers
novel insights into the cognitive processes used by participants in the completion of
spatial scaling. As previously outlined, performance on scaling tasks appears to be
influenced by features of task design. For example, visual acuity was shown to influence
performance in this study. Variation in acuity increased the suitability of this task for
a wider age range of children, such that the inclusion of fine-level acuity trials allowed
for performance variation for the oldest children, whilst the gross-level acuity trials
avoided floor effects in performance for the younger children. The results show that
performance accuracy for trials requiring gross level acuity stabilised at 7-years-of-age,
in contrast to trials requiring fine level acuity, where performance accuracy stabilised
at 8-years-of-age. Future research should further investigate the role of visual acuity in
scaling success. As this is the first study to investigate scaling in children using a
discrimination paradigm, the exact features of task design that best enable children to
complete discrimination based scaling tasks, are largely unknown. Given that this task is
the first to require discrimination between four scaled spaces, and uses comparison
between digital and paper-based formats, response times are high relative to other scaling
tasks. Furthermore, it might be argued that the long-lasting comparison process required
between four alternatives may be masking increases in response time across scaling
factors. However, given that comparison between four alternatives is required for all
trials, we would expect this to elevate response times across all scaling factors
uniformly and not to selectively interfere with any effects of scaling or acuity. Overall
the findings from this study, in particular findings on age-based performance differences,
should also be viewed in light of the high levels of individual variation in task
performance across children. However, taken together, the specific features of task design
used in this study, have led to the generation of a measure suitable for assessing
individual differences in spatial scaling abilities in older children (without ceiling
effects) and younger children (without floor effects). In this study, through the use of
an age-appropriate discrimination task, it was shown that children achieve performance
gains in spatial scaling until 8-years-of-age, some two years older than is typically seen
for localisation paradigms. These contrasting results suggest that the spatial skills
required for different scaling paradigms (localisation v’s discrimination tasks) may vary.
Perhaps, spatial scaling through development may best be understood by combining findings
from localisation, discrimination and other paradigms. For example, future work with
children of this age could investigate further unexplored paradigms such as the use of
scaled maps for navigation or the reconstruction of maps from scaled models. Furthermore,
the patterns of errors seen in this study suggest that mapping between differing spaces
may be influenced by the horizontal-vertical illusion. Better understanding of this
illusion may offer a novel way of teaching spatial mapping and improving scaling skills in
children. By achieving a better understanding of the development of spatial scaling
skills, children can be encouraged to engage in age appropriate spatial scaling tasks
aimed at improving their scaling skills. Given that other aspects of spatial cognition are
predictive of success in Science, Technology, Engineering and Mathematics domains (STEM)
domains in adults, spatial scaling may also play an important role in STEM achievement
(Casey, Nuttall, & Pezaris, 2001; Gunderson, Ramirez, Beilock, & Levine, 2012; Taylor &
Hutton, (2013); Wai, Lubinski, & Benbow, 2009). There are many practical applications of
spatial scaling in the classroom including map reading, achieving proportionality in
drawing, or classroom activities in science for example, such as relating larger scaled
diagrams (e.g. on a whiteboard) to smaller printed diagrams. Given their relevance in the
science and maths classroom there is a need to better understand the cognitive
underpinnings and development of scaling abilities. Through the use of an age-appropriate
discrimination paradigm, this study offers novel insights into children’s spatial scaling
abilities, highlighting the continuing development of scaling abilities in children up to
8 years of age, and the presence of substantial individual differences in spatial scaling
at all developmental ages. These finding suggest room for improvement in children’s
spatial scaling skills, and highlight the potential of scaling interventions in the early
primary school years. Such interventions may infer both direct benefits on spatial
thinking and indirect advantages for STEM achievement more generally.


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<ART>The use of the Warnke Method in dyslexia therapy for children
=============================================================

Authors: Małgorzata Lipowska, Ariadna B. Łada, Paulina Pawlicka, Paweł Jurek
DOI: 10.1016/j.appdev.2019.101060
Year: 2019
ASJC codes: 3204
Keywords: Children therapy, Phonological processing, Reading and writing skills, Specific learning difficulties, The Warnke Method

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Schools are introducing more and more non-evidence-based methods in dyslexia therapy. The aim of the study is to verify whether the novel method – Warnke Method can be regarded as a useful tool in dyslexia therapy in Polish children. The research group consisted of 37 pupils, between 10 and 12 years, diagnosed with developmental dyslexia. Participants were assessed at pretest on literacy and phonological processing and tasks measuring central auditory and visual processing with Warnke Method tools. Subsequently, each child underwent 20 training sessions of Warnke Method. Afterwards, children were assessed with posttest measures. Results showed that phonological processing served as a mediator in relationship between central auditory and visual processing and reading and writing skills. Significant improvement was observed with regard to central auditory and visual processing, phonological processing, as well as reading and writing skills. Furthermore, improvement was seen in students' grades of Polish language and literature classes.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

DSM-5 (American Psychiatric Association, 2013) defines dyslexia as an alternative term
used to refer to a specific learning disorder concerning reading impairment which often
coexists with difficulties in other language skills such as spelling and writing. It is
primarily characterized by problems with accuracy or fluency of word recognition, poor
decoding and poor spelling abilities. Despite decades of study and an ongoing search for
the causes and mechanisms of developmental dyslexia, there are still no clear answers.
Morton and Frith (1995) proposed considering three levels—biological, cognitive and
behavioral—when analyzing and understanding the phenomenon of dyslexia. We will refer to
the biological level when considering genetic predispositions and the neurobiological
characteristics associated with dyslexia; the cognitive level is related to pathological
mechanisms. Finally, we will use the behavioral level for discussing the symptoms of
dyslexia (for instance difficulties in reading and writing). The use of the above
categories allows the organization of a significant amount of knowledge regarding
developmental dyslexia (Frith, 2008; Morton & Frith, 1995).

<hs>  Pathomechanisms for dyslexia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Many current theories look for the causes of dyslexia at the biological level,
particularly in genetic predispositions (Anthoni et al., 2012; Galaburda, LoTurco, Ramus,
Fitch, & Rosen, 2006; Kere, 2014; Krasowicz-Kupis, Bogdanowicz, & Wiejak, 2014;
Mascheretti et al., 2017; Matsson et al., 2015; Neef et al., 2017; Pennington & Olson,
2008; Wilcke et al., 2009). Some neurofunctional and neuroanatomical differences between
individuals with dyslexia and those who do not exhibit any learning difficulties have also
been reported (Bloom, Garcia-Barrera, Miller, Miller, & Hynd, 2013; Clark et al., 2014;
Démonet, Taylor, & Chaix, 2004; Goswami, 2014; Habib, 2000; Jednoróg, Gawron, Marchewka,
Heim, & Grabowska, 2014; Norton, Beach, & Gabrieli, 2015; Płoński et al., 2017; Richlan,
2014; Wajuihian, 2012; Xia, Hoeft, Zhang, & Shu, 2016). Because the diagnostic criteria
for developmental dyslexia are various language difficulties—namely, challenges to master
accuracy and/or fluency in word recognition, poor spelling, and decoding abilities (Lyon,
Shaywitz, & Shaywitz, 2003)—the main approach in studies searching for the pathomechanism
of the disorder stresses the role of linguistic processes. The most documented hypotheses
which focus on auditory language functioning are: 1) the phonological deficit hypothesis,
which examines difficulties with representation, storing, manipulating and retrieving
speech sounds (Law, Vandermosten, Ghesquiere, & Wouters, 2014; Peterson, Pennington,
Olson, & Wadsworth, 2014; Ramus, 2014; Ramus, Marshall, Rosen, & van der Lely, 2013;
Snowling, 2000; Snowling & Hayiou-Thomas, 2006); and 2) the double deficit hypothesis
which looks to deficits in both phonological processing and naming speed (Heikkilä,
Torppa, Aro, Närhi, & Ahonen, 2016; Norton et al., 2014; Torppa et al., 2013; Wolf &
Bowers, 1999). However, in the last 25 years, theories have been put forward which suggest
that deficits in dyslexia are more than just phonological in nature and can also include
visual deficits. Stein (2001) and other researchers (Gori, Cecchini, Bigoni, Molteni, &
Facoetti, 2014; Gori, Seitz, Ronconi, Franceschini, & Facoetti, 2016; Jednoróg, Marchewka,
Tacikowski, Heim, & Grabowska, 2011; Stein, 2014) applied magnocellular deficit theory and
looked for the causes of dyslexia in anomalies in neural pathways associated with visual
analysis. Individuals with dyslexia present deficits in perception organization and in
manipulation of visual information (Lipowska, Czaplewska, & Wysocka, 2011; Winner et al.,
2001). They experience problems with: the simultaneous processing of multiple pieces of
visual information and in visual working memory (Bosse, Tainturier, & Valdois, 2007),
visual-motor coordination (Bogdanowicz, 1997; Crispiani, 2015), temporal integration of
visual information (Stein, 2014), functional coordination (Lachmann, 2002), and procedural
learning (Biotteau et al., 2017; Biotteau, Chaix, & Albaret, 2015; Mariën et al., 2014;
Nicolson & Fawcett, 2011; Nicolson, Fawcett, Brookes, & Needle, 2010; Wong & Ho, 2010).
There are also theories which point to deficits in temporal processing, which particularly
pertain to the processing of short duration auditory and visual elements (Daikhin, Raviv,
& Ahissar, 2017; Protopapas, 1634; Szeląg et al., 2014; Tallal, 1980), as well as
attention (Borkowska, 2006; Bosse et al., 2007; Dahle & Knivsberg, 2014; Facoetti,
Lorusso, Cattaneo, Galli, & Molteni, 2005; Ruffino, Gori, Boccardi, Molteni, & Facoetti,
2014) in the pathomechanism of dyslexia.

<hs>  Language deficits influencing the clinical picture and therapy of dyslexia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The complex etiology of specific difficulties with reading and writing is mirrored by the
variability in clinical pictures of developmental dyslexia exhibited by children and
adolescents. Thus, there is a need to employ diverse therapeutic methods, tailored to
children's individual needs and initial causes of difficulties (Bogdanowicz & Adryjanek,
2004; Bogdanowicz, Czabaj, & Bućko, 2008; Fletcher, Lyon, Fuchs, & Barnes, 2007; Shaywitz,
Morris, & Shaywitz, 2008; Terzi, 2005; Tilanus, Segers, & Verhoeven, 2016). In contrast,
the majority of therapeutic methods in many different languages are aimed at directly
training phonological awareness and the reading and writing skills of dyslexic pupils. In
Morton and Frith's terms (Morton & Frith, 1995), all of these methods are working on the
cognitive and behavioral level. English is a language with an opaque alphabetic
orthography, i.e., it has many irregular letter-sound mappings. This creates difficulties
both in reading and writing acquisition. It is more consistent at the level of
morphological units than phonological units. Therefore more global methods of literacy
training supported by phonics instruction aimed at both phonemes and larger onset-rhyme
particles are the most efficient when the student is an English speaker (Gottardo,
Pasquarella, Chen, & Ramirez, 2016). In contrast, Polish is a morphophonemic,
inflectional, and consonantal language with semi-transparent correspondence between
phonemes and graphemes (more transparent in terms of reading, less transparent in terms of
spelling, although more transparent in both aspects than English; Awramiuk & Krasowicz-
Kupis, 2014; Łockiewicz & Ciecholewska, 2017; Pawlicka, Lipowska, & Jurek, 2018).
Therefore reading acquisition in Polish develops based on analytical and phonological
strategies focusing on phonemes and syllables at the initial stage, developing in to
global word- and phrase-based reading. When working with a Polish-speaking child affected
by developmental dyslexia, training focuses on grapheme-phoneme correspondences, word
decoding, phoneme and/or syllable segmentation, and blending skills. In particular, the
following methods are commonly used: reading words, sentences, and text excerpts in
syllables; alternate reading of syllables, words, and sentences; loud and subvocal
reading, quiet selective reading, and syllable reading; reading using an eye-level reading
ruler; and group reading (Bogdanowicz, Adryjanek, & Rożyńska, 2014; Skibska, 2016; Trypuć,
2014). Writing acquisition evolves from partial representation of speech units, through a
dominant phonetic strategy, to the stage where orthographic and morphological awareness
develop and are central to writing (Awramiuk & Krasowicz-Kupis, 2014). Furthermore, when
practicing writing skills, therapists employ the following exercises: drawing big letters
with one's hand in the air; writing large letters on a blackboard; tracing letter
templates; writing letters on sheets of paper of varying sizes; writing letters using a
stencil; and copying letters using carbon paper. These exercises are often supplemented by
art classes, exercises aimed at improving seeing shapes and backgrounds, as well as tasks
related to spatial relationships (Bogdanowicz et al., 2014; Skibska, 2016; Trypuć, 2014).
Therapeutic interventions used with children in other countries are similar (Abegg &
Gentile, 2016; Alexander & Slinger-Constant, 2004; Denton & Madsen, 2016; Facoetti,
Lorusso, Paganoni, Umiltà, & Mascetti, 2003; Snowling & Hulme, 2012; van der Leij, 2013),
with some differences reflecting the specifics of the language (e.g. orthography
transparency representing the level of grapheme-phoneme correspondence).

<hs>  The Warnke Method in the treatment of dyslexia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To date, specialists who apply empirical research to clinical practice have been mostly
interested in detecting symptoms of developmental dyslexia. The application of research to
practice has resulted in the development of an effective system of diagnosing specific
learning disorders and the creation of reliable diagnostic tools (Bogdanowicz, Kalka,
Karpińska, Sajewicz-Radtke, & Radtke, 2012; Fawcett, Singleton, & Peer, 1998; Feifer,
2015; Flanagan, Ortiz, & Alfonso, 2013; Hook, Macaruso, & Jones, 2001; Jaworowska,
Matczak, & Stańczak, 2010; Krasowicz-Kupis, 2009; Nayton, Hettrich, Samar, & Wilkinson,
2017; Nicolson & Fawcett, 1997; Reynolds & Caravolas, 2016; Wagner, Torgesen, Rashotte, &
Pearson, 2013; Wiederhold & Bryant, 2012; Wolf & Denckla, 2005). However, few evidence-
based effective approaches are available for developmental dyslexia that align with the
research-based diagnostic tools. Thus, creating a comprehensive system of intervention as
well as diagnostic assessment for children with developmental dyslexia has become a
priority (Nayton et al., 2017; Reynolds, Nicolson, & Hambly, 2003). In order to ensure
that children with specific learning difficulties can benefit from effective, evidence-
based forms of therapy, the current study attempts to provide data on whether the Warnke
Method—a fairly new therapeutic approach which has generated significant interest among
Polish teachers and therapists—is a valid and efficient therapeutic or supportive method,
or at least one that does not lower children's phonological awareness and reading/writing
skills when used in the therapy of developmental dyslexia. The method was developed by
Fred Warnke (2000) for individuals who experience difficulties with reading, writing, and
speaking. It assumes that difficulties in learning the complex skills of reading, writing,
and speaking result from deficits in the processing of auditory, visual, and motor
stimuli—mainly due to a decreased level of automaticity of these processes (Warnke, 2014).
This method requires the use of special equipment. Diagnostic and therapeutic equipment
allows the assessment of functioning in eight tasks: visual and auditory order threshold,
spatial hearing, pitch discrimination, auditory motor timing, auditory choice reaction
time, frequency pattern recognition, and tone duration recognition. The exercises are
performed while wearing headphones (Odowska-Szlachcic & Mierzejewska, 2013). According to
Warnke (2014), the method is aimed at training central auditory and visual processing with
emphasis on auditory motor timing, automatic balance retainment, and auditory choice
reaction time as particularly important in reading and writing. The Warnke Method differs
from other well-established methods focusing on fluency (e.g. RAVE-O; Wolf et al., 2009).
Above all, the main difference is that it does not directly employ typical linguistic
exercises—syllable and phoneme manipulation tasks, learning about words in context, etc.
The method can be therefore grounded in Tallal's (1980) ‘rapid temporal processing’
theory, which identifies basic perceptual processing as a possible cause of dyslexia,
especially the apprehension of temporal auditory and visual patterns. Studies report
deficits in perceptual sequence learning in dyslexics, either with use of visual (Bennett,
Romano, Howard, & Howard, 2008; Howard, Howard, Japikse, & Eden, 2006) or auditory stimuli
(Helenius, Uutela, & Hari, 1999; Tallal, 1980). The lower results of poorer readers on
rapid naming tasks (RAN; Wolf & Bowers, 2000) may point to a sequence learning deficit, as
sequential processing is also involved in RAN tasks (Bennett et al., 2008). Furthermore,
the cerebellar theory (Nicolson, Fawcett, & Dean, 2001) stresses the contribution of the
cerebellum to central-auditory functions, speech perception, speech timing, and, hence,
phonological awareness (Stoodley & Stein, 2011). However, the question arises as to
whether performing compensatory work using this procedural learning system but with the
use of non-linguistic material might be beneficial for literacy development in dyslexics.
Stoodley (2016) acknowledges the potential benefits. On the other hand, Kearns and Fuchs
(2013) question the effectiveness of training of underlying cognitive processes in
dyslexia therapy.

<hs>  The present study</hs>
  ~~~~~~~~~~~~~~~~~

Since the Warnke Method may be regarded as being based on scientific theories related to
the pathomechanism of dyslexia and is generating interest among practitioners working with
dyslexic children, we examined its efficacy in the context of its potential implementation
(in terms of the number and frequency of training sessions) in public schools in Poland.
The goal of the current study was to investigate the effectiveness of the eight tasks
(visual and auditory order threshold, spatial hearing, pitch discrimination, auditory
motor timing, auditory choice reaction time, frequency pattern recognition, and tone
duration recognition) of the Warnke Method in the therapy of developmental dyslexia in
children. Some necessary modifications (regarding the frequency of the sessions) were made
so that the Warnke Method could be used in a school setting.

<hs>  In summary, we examined the following three research questions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First, we examined the relationships between the variables—in particular, we were
interested in whether the impact of central auditory and visual processing on reading and
writing skills was direct or indirect, through phonological processing. Does phonological
processing mediate the relationship between central auditory and visual processing and
reading and writing skills? Furthermore, we examined two questions about the efficiency of
the Warnke Method in developmental dyslexia therapy in children: Does a course of 20
sessions of training with the Warnke Method improve the functioning of children with
developmental dyslexia in terms of the central auditory and visual processing? Does
training of central auditory and visual processing with the Warnke Method improve
phonological processing in children with developmental dyslexia as well as their reading
and writing skills, decreasing the severity of their dyslexic deficits?

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Forty students from the fourth and fifth grade of primary schools in northern and central
Poland with a formal diagnosis of developmental dyslexia took part in the study (19
children presented severe reading problems, 15 moderate problems, and three children mild
problems). The age of the study group is a result of regulations from the Polish Ministry
of Education (2010) stating that developmental dyslexia can be diagnosed after the third
year of primary school education, when a child is expected to have mastered reading and
writing skills. Participants were recruited through contact with teachers and
psychologists working in public and non-public schools. The children who took part in the
study did not regularly engage in any other therapeutic intervention aimed at difficulties
in reading and writing. They also did not exhibit any other types of learning difficulties
(e.g. developmental dyscalculia), nor did they have any other clinical diagnoses (e.g.
attention deficit hyperactivity disorder, conduct disorder, or autism spectrum disorder).
Throughout the course of the intervention, three children were excluded. Two of them began
to exhibit neurological symptoms (headaches, nausea) and one was excluded because of long-
term hospitalization which resulted in absence from school and lack of regularity in
therapeutic training. As a result, the final group comprised 37 children: 17 girls (45.95%
of the sample) and 20 boys (54.05% of the sample) aged between 10 and 12 (M = 11.23; SD =
0.63).

<hs>  Measures</hs>
  ~~~~~~~~

Three research tools were used in the study: The Battery of Methods for Diagnosing the
Causes of Failure at School 10/12 (Polish: Bateria Metod Diagnozy Przyczyn Niepowodzeń
Szkolnych 10/12; Bogdanowicz et al., 2012) was used to assess phonological processing and
reading and writing skills; the Brain-Boy Universal Professional device was used to assess
central auditory and visual processing at the beginning of the project and after 20
training sessions; and the Brain-Boy Universal device was used during the 20 training
sessions. The Battery of Methods for Diagnosing the Causes of Failure at School 10/12
(Polish: Bateria Metod Diagnozy Przyczyn Niepowodzeń Szkolnych 10/12; Bogdanowicz et al.,
2012) is a tool used for the initial diagnosis of specific learning disorders in children
aged 10–12. The tool is comprised of tests diagnosing visuospatial functions (visuospatial
perception and the speed of visual perception when working with visual material) and
phonological processing (phoneme differentiation, phonological memory, phoneme analysis
skills, phoneme isolation, phoneme synthesis, and attention span). The battery is
characterized by good content validity and satisfactory construct validity. The internal
consistency of the tool (Cronbach's α) was 0.77. The validity of the tool was determined
based on the factor structure and its correspondence with the psychological concept of
developmental dyslexia symptoms. A relationship between battery scores and school
achievement has also been confirmed (see Bogdanowicz et al., 2012). The current research
used the sub-tests investigating phonological processing and reading and writing skills,
as the Warnke Method is theoretically addresses children's functioning in these areas.

        <hss>Phonological memory</hss>

        Two of the above subtests (Spoonerisms and Phonological Memory) were used to build
        a latent variable: phonological processing. The reliability measured by the omega
        internal consistency coefficient for this variable in the current study was 0.67.
        The Spoonerisms task is the most complex, requiring a high level of phonological
        awareness (including phoneme differentiation, phonemic synthesis, and analysis and
        deletion skills) in order to obtain a high score (from seven to nine points in
        this task). On the other hand, repeating non-words is considered an important
        indirect measure of phonological working memory. One of the most important
        functions of phonological memory is temporary storage of incoming linguistic
        information. It also supports the subvocal rehearsal process. These functions have
        significant meaning for vocabulary acquisition, acquiring reading skills as well
        as reading and oral language comprehension (Baddeley, 2012; Marini, Ruffino, Sali,
        & Molteni, 2017; Nicolielo-Carrilho, Crenitte, Lopes-Herrera, & Hage, 2018).

<hs>  Reading and writing skills</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

We used two of the above measured skills (reading words aloud measuring the reading speed
and accuracy and dictation—number of errors—measuring the writing skill – writing
accuracy) to build a latent variable named reading and writing skills. Reliability
measured by the omega internal consistency coefficient for the created variable in the
current study was 0.69.

<hs>  Central auditory and visual processing measured using Warnke Method tasks</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The Warnke Method (Warnke, 2000, 2014) requires the use of specialist devices, namely
headphones and the following equipment: The Brain-Boy Universal Professional (BUP) device
allows the accurate assessment and training of central auditory and visual processing in
the tasks listed below. All tasks are performed by the child while wearing headphones.
Based on the results of the initial assessment, a training program tailored to the
individual needs and abilities of the child is proposed. The Brain-Boy Universal device is
used mainly for training the skills listed below. The plan for its use (the sort and
number of games played in each session together with the difficulty level) is based on the
results of the assessment with the BUP device. The device is equipped with eight games and
has options for adjusting the level of difficulty based on the user's performance. The
name of the device (Brain-Boy) is intended to associate it with the Game Boy—in order the
decrease the anxiety related to undergoing training with a specialized device and make
children eager to train. Both the assessment and the training in the Warnke Method are
administered in the form of eight different games: The Visual Brain-Boy game – visual
order threshold: the child sees one flash of light on the left and one on the right side.
The task is to decide on which side it appeared first; pairs of flashes of light appear
with progressively shorter time intervals between them (from 400 to 5 ms). The Auditory
Brain-Boy game – auditory order threshold: the child hears one click in the left ear and
one in the right ear. The child needs to decide in which ear the stimulus appeared first;
the pairs of sounds appear with progressively shorter time intervals between them (from
400 to 5 ms). The Klik-Boy game – spatial hearing: the child hears one click and has to
decide on which side of their head it appeared. The Sound-Boy game – pitch discrimination:
the child hears two sounds of different tones and has to decide in which order they
appeared. The Sync-Boy game – auditory motor-timing: the child hears a regular sequence of
sounds (clicks) which appear in the left and the right ear, alternately. The child needs
to synchronously press buttons to the rhythm of the heard clicks. The Speed-Boy game –
auditory choice reaction time: the child hears two sounds of different tones in the left
and right ears. The child has to press a button as fast as possible on the side from which
the lower tone came. The Trio-Boy game – frequency pattern recognition: the child hears
three sounds, one of which differs from the two others in terms of the tone. The child has
to identify which sound was different from the other two. The Long-Boy game – tone
duration recognition: the child hears three sounds, one of which lasts longer than the
other two sounds. The child needs to assess which sound differed in duration from the
other two. Finally, five of the eight tasks (visual and auditory order threshold, pitch
discrimination, frequency pattern recognition, and tone duration recognition) constituted
the latent variable named central auditory and visual processing. Reliability measured by
the omega internal consistency coefficient for this variable in the current study was
0.77.

<hs>  Procedure</hs>
  ~~~~~~~~~

Before conducting this research, consent was obtained from the parents of students
recruited to participate in the project. The parents were informed about the anonymity of
the collected data and about their use for an empirical study. Research was conducted
throughout the 2015/2016 school-year (approximately eight months) in primary schools in
northern and central Poland. In the first stage of the research (time one), which took
place after the beginning of the school year (September–October), parents filled-in a
questionnaire regarding the life and medical history of the child as well as the socio-
economic status of the family. In the second stage, the researcher met each child during
an initial assessment at the beginning of the school year. The initial assessment included
phonological processing and reading/writing skills using the Battery of Methods for
Diagnosing the Causes of Failure at School 10/12 (Polish: Bateria Metod Diagnozy Przyczyn
Niepowodzeń Szkolnych 10/12;Bogdanowicz et al., 2012), as well as assessment of the
child's central auditory and visual processing using the Brain-Boy Universal Professional
device. During the next stage, which lasted approximately eight months, the subjects
underwent a series of 20 training sessions using the Warnke Method and the Brain-Boy
Universal device. Six training sessions were of a combined auditory-visual character; the
remaining 14 were based on auditory stimuli. The duration of a single session was
approximately 30 min and as the training progressed it was shortened to about 15 min. Each
training session took place in the psychologist's or speech therapist's office at school.
We cooperated with the specialized group of school psychologists and speech therapists who
completed a specialist course in assessment and training with the Warnke Method.1 Training
sessions with the children took place weekly; however, during Christmas, Easter, and the
Winter school vacation, two-week long breaks between the training sessions took place
(resulting in an average of three sessions per month). In the last stage, after completing
20 therapy sessions, the children underwent a final post-test assessment (time two) using
the same assessment battery as at first stage of the study.

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Statistical analyses were conducted in two stages: in the first stage, a theoretical model
describing the relations between the variables was tested; in the second stage,
participants' mean scores were compared at baseline and after completing the intervention,
in order to assess the effectiveness of the Warnke Method. The model of the relationship
between the variables was tested using structural equation modelling (SEM). The model
incorporated three latent variables: Central auditory and visual processing (indicators:
Other threshold – visual, Order threshold – auditory, Pitch discrimination, Frequency
pattern recognition, Tone duration recognition), Phological processing (indicators:
Phonological memory and Phonological awareness), and Reading and writing skills
(representing by Reading speed and accuracy and Writing accuracy). In order to estimate
the parameters of the model, a maximal likelihood estimator (ML) was used. When assessing
the fit of the model to data, the following measures were used: χ2, root mean square error
of approximation (RMSEA), and comparative fit index (CFI; Kline, 2016). The mediating role
of phonological processing was examined by testing the indirect effect of central auditory
and visual processing on reading and writing skills. Following the recommendations of
Cheung and Lau (2007)—especially in the context of a very small sample—we implemented a
bootstrapping procedure in which 1000 bootstrap samples were created at a 95% confidence
interval. In order to assess whether the indirect effects are significant, we used the
bias-corrected percentile method. Calculations were conducted in an R environment using
the lavaan package (Rosseel, 2012). A paired t-test was used to test differences in mean
scores of the subjects at baseline and after the completion of 20 training sessions. For
the central auditory and visual processing indices, results were normalized in a way such
that the subjects' developmental performance change due to age was taken into account
(norms for the eight tasks trained with use of the Brain-Boy Universal include ages five
to twelve). In the case of phonological processing and reading and writing skills, raw
scores were used for comparison.

<h>RESULTS</h>
-------

Table 1 Presents means, standard deviations, and correlation coefficients of the analyzed
variables. In line with the hypotheses, phonological memory was highly correlated with
producing and recognizing Spoonerisms (r = 0.51), which supports the idea that these
skills should be treated as indicators of phonological processing of the first category.2
Importantly, only phonological processing (as a latent variable) was significantly
correlated with reading and writing skills. Furthermore, analysis of correlation indicates
a significant positive association between central auditory and visual processing with
reading and writing skills (as latent variable), as well as with phonological processing
(Figs. 1 and 2).

<hs>  Relationship between central auditory and visual processing and reading and writing skills—the mediating role of phonological processing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the first step of statistical analysis, a theoretical model describing relations
between the investigated variables was tested. This model (see Fig. 3) includes three
latent variables: 1) central auditory and visual processing, with the results of five of
the eight measured tasks in the Warnke Method as indicators; 2) phonological processing,
whose indicators are phonological memory (repeating nonwords) and phonological awareness
(producing and recognizing Spoonerisms); and 3) reading and writing skills, whose
indicators are the speed of reading and accuracy of writing (dictation). It was assumed
that the relationship of central auditory and visual processing with reading and writing
skills is mediated by phonological processing. The model was tested using data from the
baseline measurement. The results of path analysis are presented in Fig. 3. The model fit
the data well [χ2 = 29.43 (df = 25; p = .25); CFI = 0.95; RMSEA = 0.069].

<hs>  Effects of training central auditory and visual processing using the Warnke Method</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In order to analyze the effectiveness of the Warnke Method in the development of central
auditory and visual processing, phonological processing, and reading and writing skills,
we compared the mean scores for the investigated variables before and after training (see
Table 2). In line with expectations, mean scores obtained by the participants were
significantly higher after 20 sessions of training, with the exception of the tone
duration recognition task results. For this variable, a statistically significant
difference was only observed in pupils whose baseline level of central auditory and visual
processing was below the median (MBefore training = 25.00, SD = 21.64, MAfter training =
41.16, SD = 25.77, t = −2.10, p = .05). The results of children with developmental
dyslexia in terms of phonological processing as well as reading and writing skills were
also compared to developmental norms provided with the Battery of Methods for Diagnosing
the Causes of Failure at School 10/12 (Polish: Bateria Metod Diagnozy Przyczyn Niepowodzeń
Szkolnych 10/12; Bogdanowicz et al., 2012). The norm group was composed of children aged
10–12 years with no dyslexia diagnosis. The standardized scores represented level of
skills expected at the specific developmental age and they were set every three months. On
this basis, profiles of the severity of dyslexic difficulties exhibited by the children
were created. Low scores (0–7 for Phonological memory, 0–3 for Phonological awareness,
0–65 for Reading speed and accuracy and more than 28 mistakes for Writing accuracy)
indicate a high severity of difficulties. The aim of this was to verify whether the
effects obtained through the Warnke Method training were due to the natural process of
development over the course of the ten months of the school year or whether they were the
result of the intervention. The analyses indicated a decrease in the dyslexic difficulties
in the group of children studied. The percentage of low scores decreased and average and
high scores increased in the group, as shown in Fig. 4. The number of children who scored
high on Phonological Memory (the first of the phonological processing indicators in our
study) increased (from three to eight children), while the number of children who scored
low dropped (from 15 to 10). However, the distribution of scores in comparison to
developmental norms changed most with regards to the Spoonerisms subtest (the second of
the phonological processing indicators in our study). During the final assessment, only
seven out of 37 children obtained low scores, which is about 20% of the group. During the
initial assessment, 23 children (60% of subjects) scored low in this task. During the
primary assessment, only one child scored in the range that qualified as high, while nine
children obtained high scores on the final assessment. The children's reading skills
(speed and accuracy of reading aloud—the first of the reading and writing skills
indicators in our study) also improved in comparison to norms. The number of pupils who
scored average on the final measurement did not change, however the number of persons
scoring high increased (from one to three) and the number of pupils with low scores
decreased (from 23 to 21). One might observe that this change affected two individuals,
however the children were about ten months older at this point than during the primary
assessment and thus also more was demanded of them. Significant differences in results
compared to developmental norms were observed in the Dictation task (the second of the
reading and writing skills indicators in our study), aimed at assessing writing skills in
terms of accuracy of spelling, punctuation, and writing speed. Average and high scores
constituted 60% of all scores during the final assessment, while at baseline they only
constituted about 40%. None of the subjects scored high in their initial assessment, and
at final measurement three subjects obtained such a result. The majority of scores were
average at final measurement, while at baseline a considerable majority of scores were
low. This improvement was also visible in the students' grades obtained during the Polish
language classes (where a substantial amount of time is spent on reading, reading
comprehension, and dictation). At baseline (the previous year's grade from the Polish
language course), students' grades were M = 3.1, while grades at the end of the school
year (after completion of the 20 training sessions) were significantly higher M = 3.92 (p
< .05; with the 1–6 grading system in Poland).

<h>DISCUSSION</h>
----------

The primary goal of this study was to verify whether implementing the Warnke Method in the
therapy of children with developmental dyslexia for a period of approximately eight months
(20 training sessions) is an effective form of improving phonological awareness,
phonological memory, and, most importantly, reading and writing skills. We were also
interested in the role of phonological processing in the relationship between central
auditory and visual processing and reading and writing skills. The results showed that
after the 20 training sessions, children's scores improved for central auditory and visual
processing skills. Both visual and auditory differentiation thresholds improved as well as
pitch discrimination of non-speech sounds, most probably as the result of training (since
standardized scores were compared). Moreover an improvement in phonological processing was
also observed at the final assessment, in terms of both phonological memory (repeating
non-words) and phonological awareness (the Spoonerisms task). Comparison of the profiles
of the studied pupils, before and after the intervention—in particular on tests from The
Battery of Methods for Diagnosing the Causes of Failure at School 10/12 (Polish: Bateria
Metod Diagnozy Przyczyn Niepowodzeń Szkolnych 10/12; Bogdanowicz et al., 2012)— indicated
a decrease in dyslexic difficulties in children who participated in the intervention. The
distribution of the scores with regard to developmental norms changed most on the
Spoonerisms subtest. This task requires a high level of phonological awareness, syllable
isolation, syllable synthesis, as well as phonological memory; therefore, it is difficult
for children. It has proven to be effective at ‘spotting’ children with learning
difficulties (Bogdanowicz et al., 2012). The quality of reading non-words aloud also
improved in terms of the speed and accuracy in children with dyslexia in comparison to
developmental norms, as well as their accuracy of writing. The number of errors with
respect to spelling and punctuation was significantly lower from time one to time two both
in raw and standardized scores. However the question arises as to what extent the
aforementioned improved scores are due to the Warnke Method training rather than other
possible factors (e.g. the education process or the home environment). Since our study was
not a randomized control trial, conclusions must be drawn very cautiously. There was no
control group in our study, which is a significant limitation. However the studied group
comprised of children who were diagnosed with developmental dyslexia and were not
undergoing other forms of therapy aimed at learning disorders (including dyslexia) during
the period of the Warnke Method training. The exposure to only one type of therapeutic
intervention and also comparing the obtained results to the standard scores (referring to
the specific developmental age) suggest that observed changes might be attributed as an
effect of the Warnke Method training.

<hs>  Conclusions regarding the pathomechanisms for dyslexia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Initially, a theoretical model was tested describing the relations between the variables
hypothesized to be underlying deficits for developmental dyslexia. It is worth stressing
that this model turned out to appropriately describe the relations between central
auditory and visual processing, phonological processing, and reading and writing skills -
as previously described in theoretical models of dyslexia (Alt et al., 2017; Christo,
Davis, & Brock, 2009; Heikkilä et al., 2016; Nicolson & Fawcett, 2011). The model showed
that phonological processing mediated the relationship between the other two variables. We
can thus say that central auditory and visual processing predicted the phonological
processing of children with developmental dyslexia, which in turn predicted their reading
and writing skills. This means that training with the Warnke Method seemed to directly
improve phonological processing skills and, through these phonological processing skills
(indirectly), reading and writing skills. Specifically, phonological processing included:
1) short term phonological memory and 2) phonological awareness including phonemic and
syllable differentiation and manipulation. The obtained results support the theories
stressing the importance of basic perceptual processing and automaticity in the
pathomechanism for dyslexia. They also support the notions that training of underlying
cognitive processes and additionally with use of the non-linguistic material may be
beneficial in dyslexia therapy. The role of central auditory and visual processing and its
automaticity in the development of reading and writing skills is being emphasized more
often in the literature. Nicolson and Fawcett (2011) concluded, based on their own
research, that children with dyslexia, apart from difficulties in language functioning,
also exhibit deficits in other skills and activities which are ostensibly unrelated to
reading or writing (e.g. difficulties in visuomotor coordination). In this context,
auditory-motor coordination seems to play the key role (Needle, Nicolson, & Fawcett, 2015;
Nicolson & Fawcett, 2011; Thomson, Fryer, Maltby, & Goswami, 2006). The functions of
auditory motor timing and auditory choice reaction time seem to be particularly important
(Warnke, 2014). The authors believe that problems with automaticity are the common theme
in the various difficulties exhibited by dyslexic children. This is in line with the
conclusions of this study pointing to the role of the more basic, lower-order processes
and the importance of training them for the development of higher order processes such as
phonological awareness and indirectly reading and writing. The results of our study
pointed to auditory and visual order threshold as well as frequency pattern and tone
duration recognition as the aspects of central auditory and visual processing that proved
to predict phonological processing and indirectly reading and writing skills. The visual
order threshold is proved to be involved in quick visual scanning of written and reading
material (Chung et al., 2008; Giovagnoli, Vicari, Tomassetti, & Menghini, 2016) and
therefore may be important in reading and writing. The auditory order threshold indicates
the smallest time interval which allows one to distinguish between and sequence correctly
two auditory stimuli. It is also important for the ability to divide an utterance into
segments (Warnke, 2014). Tone differentiation, on the other hand, is crucial for
differentiating between similar vowels. Such vowels differ in the structure of their
frequency; thus, in order to understand an utterance, the ability to differentiate between
tones has to be correctly automatized (Warnke, 2014). Central auditory processing allows a
child to receive, memorize, and recognize sounds—in particular, the sounds of speech.
Therefore it seems to be significant for phonological awareness and indirectly for reading
and writing skills. Our research suggests that central auditory and visual processing
training can influence phonological functioning, as well as reading and writing skills, so
it may be a valuable way to decrease dyslexic difficulties. It also should be noticed that
to our knowledge this is the first, though preliminary attempt to empirically verify the
method which is increasingly used in the treatment of developmental dyslexia. Moreover,
presented studies were conducted in accordance with the principles of evidence-based
psychological practice (EBPP).

<hs>  Qualitative impact of the Warnke Method training</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It's important to emphasize the emotional and motivational effect of the Warnke Method
training. Qualitative observations of children during the intervention training suggested
that the children enjoyed the training sessions as they resembled playing a computer game
in which certain skills are being improved. Furthermore, children reported a better mood
and an increase in their self-esteem, which is of special value to us because the growing
body of research indicates that children's mental health is associated with academic
achievement (Puskar, Sereika, & Haller, 2003; Schulte-Körne, 2016). Often, before a
training session, they would tell us with a smile about their better grades, or praise
received from teachers, e.g.: ‘Nobody laughed at me today when I read’, ‘The teacher
praised me today during class’, or ‘For the first time, I got a better grade than 3
(equivalent to a C) for reading’. This was also confirmed by teachers we spoke to after
the end of the whole project. They observed an improvement in their pupils, both with
regards to reading and writing skills and in their attitude towards studying.

<hs>  Implications and conclusion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Our study is the first to systematically measure the functioning of dyslexic children
before and after the Warnke Method training in terms of both the trained domain and higher
level processes and skills (phonological processing and reading and writing skills),
which, ultimately, are the goal of the training. This study addresses gaps in the field
for evidence-based approaches that align with the theoretical conceptualization of
dyslexia, and that can be implemented by trained practitioners in the field and
incorporated into practitioners' therapeutic work. Taking the results of the study into
account, we may conclude that the Warnke Method does not hinder the functioning of
children in terms of phonological processing and literacy acquisition. After 20 training
sessions over approximately eight months, a significant improvement was observed with
regards to central auditory and visual processing, phonological processing, as well as
reading and writing skills. It is worth stressing that this improvement was visible not
only in assessment test scores, but also in the students' grades. More rigorous testing
however is needed using randomized control trials to examine the extent to which
improvements from the Warnke Method are attributed to the intervention itself. Since the
Warnke Method works on non-linguistic material, it can be used regardless of language. We
consider this to be an important benefit of the method. It can be used with bi- or
multilingual children—both in diagnosis and in training— influencing all of their language
skills. Moreover the method's structure and the game-like approach associate the training
with entertainment in the children's minds. This decreases the children's anxiety levels,
supports a goal-oriented approach, and increases the children's motivation to participate
in other methods of dyslexia therapy. Therefore the method can be also perceived as a
supportive tool, enriching the therapy of reading and writing difficulties.

<h>LIMITATIONS AND FUTURE RESEARCH</h>
-------------------------------

Despite the fact that the study was conducted on a relatively large clinical sample of
children diagnosed with developmental dyslexia, the sample size somewhat limits the
generalization of the results—it would be worthwhile to replicate the study with a larger
sample. The research should also be expanded to other countries and languages, which will
enable to generalize conclusion about effectiveness of the Warnke Method in dyslexia
therapy. Moreover, the quality of the current study would be increased if a randomized
control study design were implemented. Another important aspect for further research is
assessing the long-term effects of training through a follow-up assessment after the
Warnke Method intervention - a year after training and also after the next stage of
education (high school).


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<ART>The varieties of inner speech questionnaire – Revised (VISQ-R): Replicating and refining links between inner speech and psychopathology
================================================================================

Authors: Ben Alderson-Day, Kaja Mitrenga, Sam Wilkinson, Simon McCarthy-Jones, Charles Fernyhough
DOI: 10.1016/j.concog.2018.07.001
Year: 2018  |  Pages: 48-58
ASJC codes: 3204, 3205

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<h>ABSTRACT</h>
--------

Inner speech is a common experience for many but hard to measure empirically. The Varieties of Inner Speech Questionnaire (VISQ) has been used to link everyday phenomenology of inner speech – such as inner dialogue – to various psychopathological traits. However, positive and supportive aspects of inner speech have not always been captured. This study presents a revised version of the scale – the VISQ-R – based on factor analyses in two large samples: respondents to a survey on inner speech and reading (N = 1412) and a sample of university students (N = 377). Exploratory factor analysis indicated a five-factor structure including three previous subscales (dialogic, condensed, and other people in inner speech), an evaluative/critical factor, and a new positive/regulatory factor. Confirmatory factor analysis then replicated this structure in sample 2. Hierarchical regression analyses also replicated a number of relations between inner speech, hallucination-proneness, anxiety, depression, self-esteem, and dissociation.

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<h>INTRODUCTION</h>
------------

Inner speech – or the act of talking to yourself in your head – is an experience that is
as familiar as it is elusive. While many people will report frequent inner speech (also
known as silent speech or verbal thinking), operationalizing inner speech as a measurable
process is extremely challenging, with some doubting that it is even possible
(Schwitzgebel, 2008). It is, however, necessary for understanding the role of inner speech
in psychological processing; whether as the day-to-day narrator of conscious experience, a
putative facilitator of abstract thought, or a potential indicator of a developing
psychopathology (Alderson-Day & Fernyhough, 2015a). Inner speech has been extensively
studied as a cognitive process in research on executive functioning in children and
adults, and has been linked to verbal working memory (via rehearsal; Baddeley, 2012),
planning (Williams, Bowler, & Jarrold, 2012), inhibition (Tullett & Inzlicht, 2010), and
cognitive flexibility (Emerson & Miyake, 2003). Typically, such research has involved
blocking the production of inner speech during cognitive tasks, via distractions such as
articulatory rehearsal. In contrast, the day-to-day experience of inner speech has been
assessed using self-report methods – such as questionnaires and experience-sampling –
which have largely focused on the frequency and content of inner speech (Brinthaupt, Hein,
& Kramer, 2009; Duncan & Cheyne, 1999; Klinger & Cox, 1987). While the former approach may
be thought to lack ecological validity, the latter has been accused of producing
unreliable findings with uncertain construct validity (Uttl, Morin, & Hamper, 2011;
although see Hurlburt, Heavey, & Kelsey, 2013). A self-report tool that takes an
alternative approach – assessing the phenomenological form and quality of inner speech –
is the Varieties of Inner Speech Questionnaire (VISQ; McCarthy-Jones & Fernyhough, 2011).
Based on Vygotsky’s (1934/1987) developmental theory of inner speech, the 18-item VISQ
asks participants to rate the phenomenological properties of their inner speech according
to four factors: dialogicality (inner speech that occurs as a back-and-forth
conversation), evaluative/motivational inner speech, other people in inner speech, and
condensation of inner speech (i.e. abbreviation of sentences in which meaning is
retained). In its initial development with university students, the VISQ demonstrated good
internal and test-retest reliability, and significant relations with self-reported rates
of anxiety, depression, and proneness to auditory but not visual hallucinations (McCarthy-
Jones & Fernyhough, 2011). A follow-up study in a similar sample also implicated relations
with self-esteem and dissociation, with the latter partly mediating the link between inner
speech and hallucination-proneness (Alderson-Day et al., 2014). Since then the VISQ has
been used to assess inner speech in people with psychosis (de Sousa, Sellwood, Spray,
Fernyhough, & Bentall, 2016) and explore relations with reading imagery (Alderson-Day,
Bernini, & Fernyhough, 2017), along with being adapted for use in Spanish (Perona-
Garcelán, Bellido-Zanin, Senín-Calderón, López-Jiménez, & Rodríguez-Testal, 2017),
Colombian (Tamayo-Agudelo, Vélez-Urrego, Gaviria-Castaño, & Perona-Garcelán, 2016), and
Chinese populations (Ren, Wang, & Jarrold, 2016). Self-reported dialogic inner speech on
the VISQ has also been observed to correlate with neural activation of areas linked to
producing inner dialogue during an fMRI task (Alderson-Day et al., 2016). Notwithstanding
its successful use in these contexts, the VISQ also has shortcomings. First, its focus on
the key features of a Vygotskian model of inner speech (such as dialogue and condensation)
may have neglected other aspects of inner speech phenomenology, such as use of
metaphorical language, speaker position, and feelings of passivity. For example, Hurlburt
et al. (2013) make a distinction within inner speech between “inner speaking” and “inner
hearing“, with the latter being more like an experience of hearing one’s own voice played
back on a tape recorder. While subtle, such distinctions are potentially significant given
the putative roles of metaphor, positioning and agency in anomalous and psychopathological
experiences like hallucinations or thought insertion (Badcock, 2016; Hauser et al., 2011;
Mossaheb et al., 2014). Second, the original VISQ did not generally capture positive and
regulatory aspects of inner speech phenomenology, which can be a key part of the
functional role of dialogue-like verbal thinking. Puchalska-Wasyl (2007, 2016), for
example, specifies seven positive functions of dialogue, including support, insight,
exploration and self-improvement. Such aspects of inner speech permit more direct
comparisons with the way the concept is studied in other fields, such as cognitive
research or sports psychology (Hardy, Hall, & Hardy, 2005). In contrast, nominally neutral
statements on the original VISQ, such as “I think in inner speech about what I have done,
and whether it was right or not” may in some cases have been interpreted in a primarily
negative and ruminative sense. This is supported by the fact that more people endorse such
statements if they also report lower levels of self-esteem (Alderson-Day et al., 2014).
Here we present a revised edition of the VISQ with the aim of addressing some of these
concerns and expanding the phenomenological scope of the measure. First, an extended
35-item version of the scale was trialled as part of a larger study on reading imagery (n
= 1472; Alderson-Day et al., 2017), and exploratory factor analysis was used to identify a
new five-factor model. Second, confirmatory factor analysis was used to assess the fit of
the new model in a new sample of 377 university students. Third, we used this sample to
attempt to replicate prior findings linking VISQ factors to anxiety, depression,
hallucination-proneness, dissociation, and self-esteem (Alderson-Day et al., 2014;
McCarthy-Jones & Fernyhough, 2011). We predicted that (i) certain features of inner speech
would predict auditory but not visual hallucination-proneness (specifically, dialogic,
evaluative, and other people in inner speech); (ii) dissociation would partially mediate
the relation between inner speech and hallucination-proneness, and (iii) inner speech
would also be related in meaningful patterns to anxiety, depression, and self-esteem.
Finally, in order to further explore links to psychopathology, we (iv) compared inner
speech characteristics in students with and without a self-reported psychiatric diagnosis.
As very little work has been done in on this topic, we made no predictions about group
differences: such exploratory information is nevertheless informative for future
investigation of inner speech in clinical groups.

        <hss>Sample 1</hss>

        A total of 1566 participants took part in an online survey on readers’ inner
        voices (Alderson-Day et al., 2017). The participants were recruited through a
        series of blog posts for the Books and Science sections of the Guardian website
        (‘Inner Voices’), social media and publicity at the Edinburgh International Book
        Festival. The participants that responded to at least 80% of the new VISQ items
        were included in the analysis (n = 1472, Age M = 38.84, SD = 13.42, Range 18–81).
        Responses primarily came from English-speaking countries (see Table 1 for
        demographic information).

        <hss>Sample 2</hss>

        377 participants (322 females), aged 18–56 (M = 20.02, SD = 3.24) were recruited
        from university settings. The study was advertised through a departmental
        participant pool. Ethical approval was given by a university research ethics
        committee. Participants received course credit or gift vouchers for their
        participation. Surveys for both sample 1 and sample 2 were delivered on the
        Bristol Online Survey platform.

        <hss>Varieties of inner speech questionnaire – Revised (VISQ-R)</hss>

        Phenomenological properties of inner speech were evaluated with the 35-item
        Varieties of Inner Speech Questionnaire – Revised (VISQ-R). In addition to the
        original 18 items on dialogicality, evaluation, condensation, and the presence of
        other people in inner speech, the extended version contained new items on literal
        and metaphorical use of language, speaker positioning and address, and regulation
        of different moods. The new items were derived in an iterative manner by a working
        group including the original VISQ authors (SMJ & CF), plus members of the research
        team with expertise in phenomenology, analytic philosophy, and cognitive science
        (BAD & SW). A large set of items were initially generated (>50) in response to the
        aims of the scale, and then these were refined down to a manageable number for
        exploratory testing. Responses were made on a seven-item frequency scale where
        respondents evaluated how frequently the inner speech experiences occurred,
        ranging from “Never” (1) to “All the time” (7). This differed from the original
        6-point rating scale based on agreement with statements (e.g. “Certainly applies
        to me”), in an attempt to be more precise about how often such experiences occur
        (cf. Hurlburt et al., 2013). Each subscale of the original VISQ has previously
        shown high internal reliability (Cronbach’s α > .80) and moderate to high
        test–retest reliability (>.60). See Table 2 for a list of old and new items.

        Revised Launay-Slade Hallucination scale (LSHS-R; McCarthy-Jones & Fernyhough, 2011; Morrison, Wells, & Nothard, 2000)

        This scale included nine items used by McCarthy-Jones and Fernyhough (2011),
        adapted from Morrison et al. (2000)’s Revised Launay-Slade Hallucination scale,
        including five auditory hallucination and four visual hallucination statements
        (e.g. “I have had the experience of hearing a person’s voice and then found that
        there was no one there”). Ratings are made on a four-point Likert scale ranging
        from “Never” (1) to “Almost always” (4). Scores can range from 9 to 36, where
        higher scores indicate greater hallucination-proneness. The auditory and visual
        subscales of the revised LSHS-R have been shown to have adequate internal
        reliability (Cronbach’s α > .70, e.g. McCarthy-Jones & Fernyhough, 2011).

        <hss>Hospital anxiety and depression scale (HADS; Zigmond & Snaith, 1983)</hss>

        Levels of anxiety and depression were assessed with the 14-item Hospital Anxiety
        and Depression Scale (HADS; Zigmond and Snaith, 1983). This scale comprises of
        seven items relating to anxiety (e.g. “I get sudden feelings of panic”) and seven
        items relating to depression (e.g. “I have lost interest in my appearance”).
        Responses are made on a four-point Likert scale, with the total scores ranging
        from 0 to 21. Higher scores indicate higher levels of anxiety and depression. This
        scale has been used extensively and shown to have satisfactory psychometric
        properties (Zigmond & Snaith, 1983).

        Dissociative experiences scale – Second revision (DES-II; Carlson and Putnam, 1993)

        Frequency of dissociative experiences was measured with the 28-item self-report
        Dissociative Experiences Scale. Participants are asked to indicate what percentage
        of the time they experience dissociative states, such as feelings of derealisation
        or absorption (e.g. “Some people sometimes have the experience of feeling that
        their body does not belong to them”). Answers can range from 0% to 100%. The
        original DES has a mean internal reliability of .93 (van IJzendoorn & Schuengel,
        1996).

        <hss>Rosenberg self-esteem scale (RSES; Rosenberg, 1965)</hss>

        The 10-item Rosenberg Self-Esteem Scale includes five positive and five negative
        statements on self-concept and social rank (e.g. “On the whole, I am satisfied
        with myself. “). Responses are made on a four-point scale ranging from “Strongly
        agree” to “Strongly disagree”. The scale has been shown to have high test–retest
        and internal reliability (e.g. Fleming & Courtney, 1984).

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

All data were analysed in SPSS 20, with the exception of the confirmatory factor analysis
(which was conducted using AMOS 22) and the mediation analysis (for which we used the
“medmod” package in jamovi (Version 0.9). Relations between variables were assessed using
Pearson’s product correlation co-efficient tests and hierarchical linear regression. Alpha
values for correlations were Bonferroni corrected to account for multiple comparisons.

<hs>  Sample 1: Exploratory factor analysis of VISQ-R (35 items, n = 1472)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Missing data constituted less than 1% of total responses for the extended VISQ and were
replaced by mean values. Exploratory factor analysis (EFA) was performed using Principal
Component Analysis (PCA) with oblique rotation (direct oblimin), allowing for inter-
correlation of the VISQ factors. Items were removed based on communalities under 0.4 or if
they failed to load >0.5 onto a single factor (Costello & Osborne, 2005). For all of the
below models, KMO statistics and Bartlett’s test values were within acceptable ranges. The
initial solution returned by the analysis produced 8 factors with eigenvalues over 1 (68%
of variance explained). However, items 24, 26, 29, and 33 had either low communalities or
low factor loadings, and these were subsequently removed from the analysis. The following
model identified 7 factors with eigenvalues over 1 and accounted for a greater amount of
variance (72%) but this included one factor with only one item (item 23). Inspection of
the scree plot suggested five main factors with eigenvalues over 2, with two more factors
barely above 1. Forcing a five-factor solution (62% variance explained) led to five items
not loading on a single factor (items 21, 22, 23, 30, and 34) of which three also failed
the communalities test (Items 22, 23, 30). With a total of nine items removed, a stable
model was found with five factors (68.43% of variance explained), with all items loading
on at least one factor over 0.5 and with all communalities > 0.4 (KMO statistic = 0.895,
Bartlett’s X2 (325) = 23773.10, p < .001). The five factors, displayed in Table 3, broadly
mapped on to the original VISQ structure but with an expanded, 6-item evaluative/critical
factor (Items 20, 23 and 24 are new) and a new, 4-item positive/regulatory factor (Items
19, 22, 25 and 26 are new). As for the previous VISQ, internal reliability of each factor
was excellent (dialogic: 0.87, evaluative/critical: 0.88, positive/regulatory: 0.80,
condensed: 0.87, other people: 0.91). Table 4 shows that a number of the factors were
inter-correlated: dialogic inner speech was most closely related to each of the factors,
followed by evaluative/critical inner speech.

<hs>  Sample 2: Confirmatory factor analysis of VISQ-R (26 items, n = 377)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Confirmatory factor analysis was used to test the five-factor model in sample 2. Less than
0.2% of the data were missing and replaced by the mean response (per item). Frequency of
responses for each item (by subscale) are displayed in Table 5. Maximum likelihood
estimation was used for model fitting. Following an initial model containing no
covariances between the factors, modification indices indicated improved fit if
covariances were allowed for each factor to correlate with dialogic and
evaluative/critical inner speech, but no pairwise covariances between the other three
factors. Covariances between error terms were also added (within factor only) where
modification indices suggested improved fit. This resulted in a stable model with a
significant χ2 value, χ2 (2 6 0) = 562.53, p < 0.001, but acceptable CMIN/DF ratio of
2.16. Fit statistics for the model were also in a satisfactory/good range: CFI = 0.925,
RMSEA = 0.056 (90% C.I = 0.048–0.062), Hoelter index = 200.

<hs>  Replicating McCarthy-Jones and Fernyhough (2011) and Alderson-Day et al. (2014)</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Using sample 2, we then attempted to replicate our previous findings using the new VISQ-R.
Table 6 displays the descriptive statistics for the five dimensions of inner speech, as
well as scores for hallucination-proneness (LSHS-R), anxiety and depression (HADS), self-
esteem (RSES), and dissociation (DES). Mean scores were highest for the evaluative inner
speech dimension, followed by dialogic, condensed and positive inner speech. The lowest
mean scores were recorded for other people in inner speech. Reliability for dialogic,
evaluative and other people in inner speech was high (α > 0.8) but lower for positive
inner speech (α = 0.6). Cronbach’s α was also found to be adequate for visual
hallucination-proneness, HADS anxiety, HADS depression RSES and DES (α > 0.7), but on the
boundary of acceptability (0.67) for auditory hallucination-proneness. Table 7 shows the
bivariate correlations between VISQ-R, DES, RSES, HADS and LSHS-R scores. To account for
testing the five VISQ-R factors against six psychopathology variables simultaneously, a
Bonferroni corrected alpha-value of 0.0017 was applied for significance (i.e. 0.05/30).
Auditory hallucination-proneness (LSHS-R) was positively associated with evaluative,
dialogic and other people in inner speech, and visual hallucination-proneness. A similar
pattern was observed for visual hallucination-proneness. Evaluative and other people in
inner speech also correlated positively with HADS Anxiety scores, HADS Depression scores,
and lower self-esteem. Frequency of dissociative experiences (DES) was positively
correlated with dialogic and other people in inner speech. For exploratory purposes, we
also compared male and female participants’ scores on the new VISQ-R factors using
independent samples t-tests: the only difference observed was for evaluative/critical
inner speech (t (372) = −2.84, p = 0.005), with female participants (M = 30.34, SD = 7.13)
scoring higher than male participants (M = 27.29, SD = 4.45).

        Predicting hallucination-proneness controlling for anxiety and depression (McCarthy-Jones & Fernyhough, 2011)

        A hierarchical multiple linear regression was performed to assess unique
        contributions of the five dimensions of inner speech (VISQ-R), depression and
        anxiety (HADS) in predicting auditory hallucination-proneness. Age, gender,
        depression, anxiety and proneness to visual hallucinations were entered in the
        first step, and five subscales of the VISQ-R in a second step, with auditory
        hallucination-proneness (LSHS Auditory) as a dependent variable. Measures of
        multicollinearity were in an acceptable range. Both Block 1 (F (5, 371) = 21.05, p
        < 0.001) and Block 2 (F (10, 366) = 12.47, p < 0.001) significantly predicted
        auditory hallucination-proneness. In Block 1 (R2 = 0.22), only visual
        hallucination-proneness was found to be a significant predictor of auditory
        hallucination-proneness (β = 0.46, p < 0.001). In Block 2 (R2 = 0.25; Δ R2 = 0.03,
        Δ F(5, 366) = 3.26, p = 0.007), visual hallucination-proneness, β = 0.42, p <
        0.001, and other people in inner speech, β = 0.13, p = 0.005, significantly
        predicted auditory hallucination-proneness. To test for the specificity of this
        relationship, we then reran the above analysis with visual hallucination-proneness
        as the dependent variable and auditory hallucination-proneness as a predictor
        variable in Block 1. Both Block 1 (R2 = 0.36, F (5, 371) = 41.55, p < 0.001) and
        Block 2 (R2 = 0.61, F (10, 366) = 21.51, p < 0.001) were significant, but
        importantly only auditory hallucination-proneness, β = 0.36, p < 0.001, and
        depression, β = 0.32, p < 0.001, were observed to significantly predict visual
        hallucinations in the final model: all of the VISQ-R factors were non-significant
        (p > 0.11). Therefore inner speech characteristics appeared to be relevant to
        predicting auditory hallucination-proneness specifically.

        Predicting hallucination-proneness controlling for self-esteem (RSES) and dissociation (DES) (Alderson-Day et al., 2014)

        A multiple regression was performed to assess the contribution of different types
        of inner speech (VISQ-R), self-esteem (RSES) and dissociative tendencies (DES).
        Age and Gender were entered in the first step, followed by the five subscales of
        VISQ-R in the second step. Self-esteem (RSES) was entered in the third block, and
        dissociative tendencies (DES) in the fourth block. The first model with age and
        gender as predictors of auditory hallucination-proneness was not significant (p >
        0.05). The addition of the five dimensions of VISQ-R in Block 2 made a significant
        change to the model (Δ R2 = 0.09, Δ F (5, 369) = 8.16, p < 0.001), where other
        people in inner speech, β = 0.21, p < 0.001, and evaluative inner speech, β =
        0.13, p = 0.023, both significantly predicted auditory hallucination-proneness (R2
        = 0.103, F(7,369) = 6.077, p < 0.001). The addition of the self-esteem measure
        (RES) to Block 3 did not make a significant change to the model (Δ R2 = 0.03, p >
        0.05), and self-esteem did not significantly predict hallucination-proneness (p >
        0.05). The addition of dissociation scale (DES) scores to Block 4 resulted in a
        significant change to the model (Δ R2 = .17, Δ F(1, 367) = 83.88, p < 0.001), with
        dissociation found to significantly predict auditory hallucination-proneness, β =
        0.44, p < 0.001, as well as other people in inner speech, β = 0.17, p < 0.001
        (final model: R2 = 0.273, F(9,367) = 15.281, p < 0.001). As in Alderson-Day et al.
        (2014), we then examined what (if any) mediating role dissociation played in
        relationship between inner speech and hallucination-proneness. Using the medmod
        package in jamovi, we tested the direct and indirect effects of other people in
        inner speech on auditory hallucination-proneness, with DES scores as the mediating
        variable. Significant effects were apparent for both direct (Z = 4.16, p < 0.001)
        and indirect (Z = 3.04, p = 0.002) paths, with the latter accounting for 27.9% of
        the total effect. This suggested that dissociation partially (rather than fully)
        mediated the effect of other people in inner speech on hallucination-proneness,
        and that most of this effect was in fact direct.

        Confounding factors: Item overlap, language status, and psychiatric diagnosis

        Finally, we reran our main analysis accounting for some potential confounds in the
        data. One concern with the original VISQ is the inclusion of items that refer to
        experiencing “actual voices” of other people in their inner speech, which may be
        thought to index similar experiences as the auditory items of the LSHS. To address
        this, Alderson-Day et al. (2014) reran their analyses removing items 12 and 16 of
        the VISQ from the other people subscale. When this was done for the present data,
        the analysis showed the same results as the regression model 1 (i.e., McCarthy-
        Jones & Fernyhough 2011), in that visual hallucinations were a significant
        predictor of auditory hallucinations in the first block (β = 0.46, p < 0.001), and
        visual hallucinations (β = 0.43, p < 0.001) and other people in inner speech
        significantly predicted auditory hallucinations in the second block (β = .12, p =
        0.013). The analysis also showed the same results as in regression model 2 (i.e.
        Alderson-Day et al., 2014), where both evaluative (β = 0.14, p = 0.013) and other
        people in inner speech (β = 0.20, p < 0.001) were found to be significant
        predictors of auditory hallucination-proneness. The addition of self-esteem scores
        did not make a significant change to the model (p > 0.05). In Block 4, both
        dissociation scores (β = 0.44, p < 0.001) and other people in inner speech were
        found to be significant predictors of auditory hallucination-proneness (β = 0.15,
        p = 0.001). Other factors which may have affected our data include the presence of
        non-native speakers and people with a self-declared psychiatric diagnosis. To
        address these, we reran our main analyses of sample 2 first excluding non-native
        English speakers, and second excluding those with a psychiatric diagnosis. For the
        former, the results for the native speakers group (n = 297) showed the same
        results as reported in regression model 1, in that visual hallucination-proneness
        (β = 0.48, p < 0.001) and other people in inner speech (β = 0.13, p < 0.05) were
        significant predictors of auditory hallucination-proneness in the final model.
        Similarly, for regression model 2, other people in inner speech (β = 0.19, p <
        0.001) and dissociation scores in (β = 0.45, p < 0.001) were significant
        predictors of auditory hallucination-proneness in the final model. Identical
        results were observed when the analyses were rerun only in people without a
        psychiatric diagnosis. Finally, we compared those with (n = 43) and without a
        psychiatric diagnosis (n = 326) on the five subscales of the VISQ-R (8
        participants preferred not to report their diagnostic status). The independent-
        sample t-tests showed that there was a significant difference in the level of
        reported dialogic inner speech between the two groups (t (367) = 2.08, p = 0.038),
        with the sample with psychiatric diagnoses reporting higher levels of dialogic
        inner speech (Dx group M = 23.07, SD = 5.89; no Dx group M = 21.20, SD = 5.47). A
        similar pattern was evident for evaluative inner speech (t (367) = 5.43, p <
        0.001), with lower scores in the sample without a diagnosis (Dx group M = 35.29,
        SD = 7.47; no Dx group M = 29.12, SD = 6.94). No group differences were found in
        levels of condensed, positive and other people in inner speech (p > 0.05).

<h>DISCUSSION</h>
----------

Asking people to report on their inner speech is challenging, but with careful
methodological considerations it can produce consistent results. Here we tested and
confirmed a five-factor model for an expanded VISQ, the VISQ-R; introduced a new variable
of positive/regulatory inner speech; and replicated a number of previous findings of
relations between inner speech variables and psychopathology. Compared to the original
scale, the VISQ-R captures a broader range of phenomenology associated with the experience
of self-directed speech, in line with the primary aim of the study. In particular, new
items relating to positive and negative states of inner speech, including the use of inner
speech to regulate mood, survived the various stages of scale development. The inclusion
of these new items appears to have elaborated the concept of evaluative inner speech
captured in the original VISQ (McCarthy-Jones & Fernyhough, 2011). Evaluative states in
the present study were clustered with statements about inner speech contributing to
feeling anxious or depressed, while motivation and regulation in inner speech clustered
around the new positive factor. This is consistent with prior findings of higher
evaluative inner speech being associated with a more negative self-concept (Alderson-Day
et al., 2014), even though the items included in the original evaluative factor were
ostensibly neutral and focused more on deliberative states (e.g., I think in inner speech
about what I have done, and whether it was right or not). The inter-correlations of
evaluative and positive subscales in sample 1 (r = 0.40) and sample 2 (r = 0.29) also
highlight that these are related but ultimately separable factors, rather than positive
and negative poles of the same scale. A secondary aim for the new scale was to capture the
potential for inner speech to have positive psychological effects, as this is important
for drawing together disparate strands of research on self-directed speech. In sports
psychology and similar fields, self-talk has often been associated with improved focus and
performance (Hardy, Begley, & Blanchfield, 2015; Hardy et al., 2005). However, such
research often elides the distinction between overt and covert self-talk. Research on
private speech (overt or out-loud self-talk) shows it to be associated with regulatory
strategies in childhood (e.g., Fernyhough & Fradley, 2005) and in adulthood (Duncan &
Cheyne, 2001). In contrast, the phenomenology of inner speech and its relations to
psychopathological states and processes (such as rumination) have rarely been explored.
Through our identification of a positive inner speech factor – one with clear parallels
with the overt and motivational self-talk deployed in sports research – we have the
potential, in future research, to test predictions about cognitive and behavioural
performance. For example, one could hypothesise that participants with more
positive/regulatory inner speech are likely to perform better on tasks requiring self-talk
(or following instructions to explicitly use such a strategy), but those with more
evaluative/critical inner speech may not. While some attempts have been made to link
different functions of private speech to aspects of task performance, observational
studies of private speech are fraught with difficulty (Winsler, Fernyhough, & Montero,
2009). The VISQ-R thus provides us with a new way of empirically linking aspects of self-
talk to aspects of performance. The cognitive benefits of positive/regulatory inner speech
may also be evidenced in the spheres of creativity and imagination. To give one example,
the presence of an imaginary companion in childhood has been linked to greater levels of
self-talk in general in childhood (Davis, Meins, & Fernyhough, 2013) and adulthood
(Brinthaupt & Dove, 2012). Evaluative/critical inner speech, in contrast, would be
expected to relate more strongly to rumination, shame, and perfectionism (Flett, Madorsky,
Hewitt, & Heisel, 2002; Orth, Berking, & Burkhardt, 2006). The gender difference observed
for evaluative/critical inner speech in the present data – with higher scores in female
participants – is consistent with greater rates of rumination in women (Nolen-Hoeksema &
Jackson, 2001) and with findings from the previous VISQ (Tamayo-Agudelo et al., 2016).
Even with the introduction of the new factor, a number of previous relations to
psychopathology were observed in the confirmation sample of university students. In line
with the original VISQ study, specific characteristics of inner speech were associated
with a greater proneness to auditory hallucinations but not visual hallucinations
(hypothesis 1); dissociation appeared to mediate this relationship (hypothesis 2); and a
subset of inner speech characteristics also correlated with scores for anxiety,
depression, and self-esteem (hypothesis 3; Alderson-Day et al., 2014; McCarthy-Jones &
Fernyhough, 2011). One difference from the original study concerns the role of dialogic
inner speech. Whereas the dialogic factor predicted auditory hallucination-proneness more
strongly than other factors in the original study, in the present study only other people
in inner speech did so. It seems unlikely that this is due to the new scale structure:
with the original VISQ, pairwise correlations between dialogic inner speech and
hallucination-proneness were often evident (e.g., Alderson-Day et al., 2017) but did not
always survive exclusion during hierarchical regression analysis (Alderson-Day et al.,
2014). The exploratory analysis of those with and without a psychiatric diagnosis
suggested here that dialogic inner speech (and evaluative/critical inner speech) may be
greater in those with a self-reported diagnosis (cf. the marginally significant reduction
in dialogicality in the inner speech reported by Langdon, Jones, Connaughton, &
Fernyhough, 2009). In contrast, a recent study with a clinical sample suggested that
condensed and other people in inner speech were related to psychopathology (de Sousa et
al., 2016). As a potential explanation of these disparate findings, dialogic inner speech
is typically the factor that correlates most with all of the other VISQ factors; this is
also the case with the findings reported here. It may be that dialogicality acts as a
“core” feature of inner speech, and the other VISQ factors mediate its relation to other
variables. Alternatively, it may be that the concept of dialogicality is liable to varying
interpretations, leading to inconsistent performance across samples: for example, in
Spanish translations of the original VISQ (Perona-Garcelán et al., 2017) a further
dialogic factor needed to be added that explicitly referred to inner speech in terms of
position of self in a dialogue (see also Tamayo-Agudelo et al., 2016). In our experience,
English-speaking users of the scale have typically interpreted dialogic items to both
include dialogues with oneself and dialogues with another (indeed, the focus of a
Vygotskian understanding of dialogicality is arguably in structure, rather than the
identity of interlocutors), but it is possible that cultural understandings of dialogue
will differ considerably depending on the language used. A further point to note is that
the idea of hallucinatory experiences existing on a continuum stretching into the general
population has been increasingly challenged (e.g., Garrison et al., 2017), and it may need
to be acknowledged that relations between hallucination-proneness and inner speech
variables may transpire differently in clinical and non-clinical samples. As in earlier
studies (Alderson-Day & Fernyhough, 2015b; Ren et al., 2016), condensed inner speech items
were not strongly endorsed, and correlations with other inner speech factors were low. In
general, condensed inner speech scores also show few correlations with non-VISQ variables
(Ren et al., 2016). As noted above, there is evidence that patients with psychosis endorse
this experience more than controls, and that it relates to increased levels of thought
disorder (de Sousa et al., 2016). As such, it would seem to be an important factor to
retain and may be more informative when used in clinical samples. This may also have been
the case for a number of the other new items that did not survive the initial exploratory
factor analysis in sample 1. Specifically, questions regarding control, surprise,
metaphor, and feelings of passivity in inner speech (such as experiencing it as hearing
rather than speaking) did not cluster sufficiently either with themselves or the existing
factors to be included in the final scale. While still potentially important experiences
to explore, it may be that these characteristics of inner speech – along with condensed
inner speech – are too extraordinary for non-clinical respondents and do not become
salient until things start to go awry. Such a question bears on contemporary debates in
philosophy of mind about how and why we experience our thoughts as our own (Roessler,
2016) – questions that are important to consider when probing the distinction between
inner speech, auditory verbal hallucination, and other atypical experiences such as
thought insertion (Wilkinson & Alderson-Day, 2016). Some limitations to the present study
are important to consider. First, asking people to report on characteristics of their own
inner speech via questionnaires raises the perennial concern about how reliably people can
report on their own inner experience (see, for example, Alderson-Day & Fernyhough, 2014;
Hurlburt et al., 2013; Hurlburt & Schwitzgebel, 2007). Notwithstanding the fact that such
self-report methods are relied on extensively in personality and individual differences
research, it is important when studying inner speech to employ multiple methods. We
therefore recommend that future use of the VISQ-R involve it being deployed alongside
other tools such as cognitive tasks (Ren et al., 2016) or neuroimaging (Alderson-Day et
al., 2016). Methods of tracking the characteristics of inner speech are developing all the
time, with a recent example being provided by Whitford et al. (2017), who used EEG to
demonstrate perceptual capture of external sounds during inner speech production. Second,
examining the relations between conceptually similar notions (such as inner speech and
hallucination-proneness) raises the risk of measurement overlap. We have taken steps to
address this issue: for example, by showing that the relation between other people in
inner speech and auditory hallucination-proneness remains even when potentially
overlapping items are removed, concerns about direct conceptual overlap are to some degree
minimised. Moreover, we have endeavoured to design VISQ-R items that focus on the form and
phenomenology of inner speech, rather than its contents (to avoid confounding the content
of a thought or mood and its structure). Nevertheless, ideally such issues would be
explored more extensively in a procedure that would enable clarification and
disambiguation, such as a one-to-one interview. This would seem to be particularly
important when dealing with patients who may struggle to report on their own inner
experience (de Sousa et al., 2016). Finally, both of these samples reflect highly-educated
populations: in one case respondents to a survey on reading experiences promoted by the
Guardian newspaper (Alderson-Day et al., 2017), and in the other a university sample.
Although Alderson-Day et al.’s (2017) sample was an international one, the majority of its
respondents were still either from the UK or from other western, English-speaking
countries (as was the case for sample 2). We have already discussed some language-
specificity issues relating to translations of the VISQ. For these and other reasons, the
generalisability of the present findings is limited, and it will be particularly important
to test the VISQ-R in more mixed, general population samples and non-English speaking
countries. A related issue that will be important for future research on inner speech is
to expand its horizons into more diverse populations. For example, research on inner
speech (or equivalent experiences of inner language, such as signing) in those who are
blind or deaf is still meagre (for exceptions, see Campbell & Wright, 1990; Zimmermann &
Brugger, 2013). Similarly, research on neuro-diverse populations – such as autistic people
– has been largely confined to examining “deficits” in self-talk rather than exploring
qualitative differences in inner speech or more broadly, inner experience. Evidence of
differential use of verbal strategies on cognitive tasks in autistic adults (Williams et
al., 2012) and vivid accounts of inner experience by adults with Asperger Syndrome
(Hurlburt, Happé, & Frith, 1994) suggests that inner speech may be radically different for
this group, and deserving of a more systematic exploration. In conclusion, inner speech
has been proposed as a key tool for unlocking creative, exploratory, and abstract thought.
Our results, with the revision of the VISQ, provide new avenues for probing these
relationships while continuing to explore the important connections between the
phenomenology of self-talk and psychopathology. By expanding the horizons of inner speech,
and picking up a greater range of experiences, a richer narrative will be available to
turn Vygotsky’s (1987) ‘cloud of thought’ — to use his evocative phrase — into ‘a shower
of words’.


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<ART>The virtual bodily self: Mentalisation of the body as revealed in anosognosia for hemiplegia
================================================================================

Authors: Aikaterini Fotopoulou
DOI: 10.1016/j.concog.2014.09.018
Year: 2015  |  Pages: 500-510
ASJC codes: 3204, 3205
Keywords: Anosognosia, Awareness, Bayes, Embodiment, Free energy, Interoception, Mentalisation, Predictive coding, Self

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Despite the coherence and seeming directness of our bodily experience, our perception of the world, including that of our own body, may constitute an inference based on ambiguous sensory data and prior expectations. In this article, I apply a 'psychologised' version of the recently proposed free energy framework to the understanding of certain disorders of neurological unawareness in order to examine how inferential processes may determine our body perception. I specifically consider three facets of body perception in such disorders: namely, the 'external body' as inferred on the basis of exteroceptive signals and related predictions; the 'internal body' as inferred on the basis of proprioceptive and interoceptive signals and related predictions; and lastly the 'impersonalised body' as inferred on the basis of signals from social and third-person perspectives on the body and related predictions. Several conclusions will be drawn from these considerations: (a) there is a deep interdependency of prior beliefs and sensory data; as the brain uses sensory data to update its virtual model of the world, lack or imprecision of sensory prediction errors may lead to aberrant inferences influenced disproportionally by outdated, premorbid predictions; (b) interoception and interoceptive salience have a unique role in our inferences about body awareness and (c) social, 'objectified' prior beliefs about the body may have a silent but potent role in our bodily self-awareness. Finally, the article emphasizes that our learned, virtual model of the body is depended on the nature and thus integrity of the very body that allowed the model to be formed in the first place.

--------------------------------------------------------------------------------


<h>INTRODUCTION: THE ‘HERE AND NOW’ AS INFERENCE</h>
---------------------------------------------

Remembering the past, and being able to project oneself in the future, allows the mind to
escape the psychological ‘here and now’ of experience. Studies in psychology have long
established that we do not only project our current self into the future to build a kind
of ‘as if’, imagined future self but we also reconstruct our past self in our memories
(Bartlett, 1932). Despite the incredible storage capacity of human memory, what we
remember in the now is not always what took place in the past. Instead, the
autobiographical incidents that we experience as veridical, coherent and self-defining are
frequently unconscious collages of previous recollective attempts, fragments of
experienced events, currents thoughts and long term goals (Conway, 2005). In this sense,
we have come to understand our autobiographical self as actively, yet unconsciously
inferred on the basis of imperfect memory data and current expectations. A similar idea
for the nature of our experience of current reality, our embodied perception of the world
and ourselves in it, has also being long proposed in psychology (e.g. Gregory, 1966).
Despite the coherence and seeming directness of our experience, our perception of the
world may constitute an inference based on ambiguous sensory data and prior expectations
(von Helmholtz, 1878/1971). However, this idea is less established, perhaps given its
counterintuitive nature and complex, philosophical implications. We experience the world
via our body and the experience of the latter in the ‘here and now’ is considered as a
fundamental aspect of our self-consciousness; our bodily self is the foundation upon which
our ‘autobiographical’, ‘narrative’ or ‘extended’ self is built (Gallagher, 2000). If our
bodily self is an inference, then our ability to perceive the world and ourselves
veridically is called into challenge (see Clark, 2013 for discussion). Leaving aside the
majority of the long and complicated philosophical discussions on the nature of reality
and our capacity to perceive it, in this paper I will explore similar ideas from the point
of view of a recent, influential theory from computational neuroscience. The theory aims
to define the idea of perceptual inference using concepts from theoretical physics and
mathematics and also aims to ground the same idea on biology and particularly knowledge
about the workings of the brain. In the current paper, I will not address the issues of
interest in mathematical ways. Instead, I will use a ‘psychologised’ version of the free
energy framework in order to examine some ideas regarding neurological unawareness and
ultimately bodily self-consciousness. Specifically, I will use clinical observations,
behavioural and neural data from a specific neurological aberration of self-awareness,
namely anosognosia for hemiplegia, to explore the possibility that our bodily self-
awareness is normally imperfect, in the sense that it is based on a set of inferences
about the hidden causes of sensorimotor signals. I also hope to demonstrate that the study
of the pathologically exaggerated ways in which we may infer the experience of our own
body, can provide insights into the mechanisms of normal perceptual and active inference,
and particularly the predictive and social nature of motor awareness.

<h>THE FREE ENERGY FRAMEWORK</h>
-------------------------

The starting point of the ‘free energy framework’ (Friston, 2005) is that humans are
biological, self-organising agents that need to occupy a limited repertoire of sensory
states for homeostatic reasons (e.g. humans need certain ranges in environmental
temperature in order to survive). However, due to the inherent ambiguity and uncertainty
of the signals an organism receives from the world, we risk finding ourselves in dangerous
states for longer periods than those we could biologically sustain (e.g. in cold
climates). We thus need to be able to predict (infer) the causes of our possible sensory
states despite the limited or noisy information available to our sensory organs (von
Helmholtz, 1878/1971). The framework proposes that our brain engages in a form of
probabilistic representation of the causes (e.g. the weather) of our future states (e.g.
our temperature) on the basis of noisy sensory data; in other terms, it maintains
hypotheses (‘‘generative models’’) of the hidden causes of sensory input. Furthermore, it
uses such input to constantly update its models, so as to reduce its representational
errors over time and thus ultimately minimize the risk of surprise (unpredictability, see
below for mathematical definition). From a psychological point of view, I will refer to
the formation of such models as the ‘mentalisation’ of sensorimotor signals. Although the
term mentalisation is traditionally used in psychology to refer to our cognitive ability
to infer the mental states of others and our own, I think the two terms are related (see
also Kilner, Friston, & Frith, 2007). In fact, the use of the term ‘mentalisation’ in this
article is intending to ground this traditional concept in its embodied origin. Returning
to the biological level, the free energy framework is biologically constrained by the so-
called ‘predictive coding’ models of perception, stemming primarily from biological and
behavioural studies in visual perception, with supporting evidence generated in various
modalities (e.g. Henson & Gagnepain, 2010; McNally, Johansen, & Blair, 2011). These
suggest that a constant filtering of sensations by top-down predictions and a parallel
updating of the latter based on prediction errors (signals representing the mismatch
between predictions and sensations), with the ultimate goal of minimizing prediction
errors, is an imperfect but highly efficient means of perceiving sensations (Rao &
Ballard, 1999). Our brain is assumed to achieve the minimisation of prediction errors by
recurrent message passing among hierarchical level of cortical systems, so that various
neural subsystems at different hierarchical levels minimize uncertainty about incoming
information by generating a prediction (or a prior belief, see below) and responding to
errors (mismatches) in the accuracy of the prediction, or prediction errors. Such
prediction errors are passed forward to drive the units in the level above that encode
conditional expectations which optimize top-down predictions to explain away (reduce,
inhibit) prediction error in the level below until conditional expectations are optimized.
Such message passing is considered neurobiologically plausible on the basis of functional
asymmetries in cortical hierarchies; prediction errors are thought to be conveyed via
feedforward connections from lower to higher levels in order to optimize representations
in the latter. Predictions from higher-levels are transferred via feedback connections
that have both driving and modulatory characteristics and can suppress prediction errors
in lower levels. This hierarchy is thus reciprocal but asymmetric and models the nonlinear
generation of sensory input (Adams, Shipp, & Friston, 2013). Based on such hierarchical,
perceptual schemes, the free energy principle, rests upon the idea that the brain as a
whole works as an Helmholtzian inference machine that is trying to optimize its own model
of the world by actively predicting the causes of its sensory inputs (Friston, 2005).
Moreover, this inferential process is mathematically understood in Bayesian terms (Bayes’
theorem describes an optimal procedure for updating the probabilities assigned to a
hypothesis in the light of new evidence), in the sense that it relies on a combination of
prior beliefs (probability distributions over some unknown cause excluding any sensory
data) and new sensory data to update prior beliefs and generate posterior beliefs
(probability distributions over some unknown cause after data have been received).
Furthermore, in the free energy principle this hierarchical minimization of prediction
errors is understood as a minimization of free-energy on the basis of the formal
definition of the latter; a quantity from informational theory that bounds (is greater
than) the evidence for a model of data (Hinton & von Camp, 1993). In this case the data is
sensory and free energy bounds the negative log-evidence (surprise) inherent in sensory
data, under a model of how the data were caused (See Friston, 2010 for the mathematical
details). Given some mathematical assumptions, free energy can be thought of as the amount
of prediction error in any given level of the system. Minimizing free energy then
corresponds to explaining away prediction errors following the principles of Bayes
(Friston, 2010). However, representing the world in constructive ways (perceptual
inference) cannot take us far in terms of our ultimate goal; surviving in an uncertain
world. Psychologically speaking, we may become better in predicting (‘mentalising’) the
changes in the environment that act to produce sensory impressions on us, but we cannot on
this basis change the sensations themselves and hence ultimately their surprise. A highly
innovative conceptual move in the free energy principle framework allows us to understand
how we do just that. By acting upon the world we can change its states and therefore ‘re-
sample’ the world to ensure we satisfy our predictions about the sensory input we expect
to receive. By selectively sampling the sensory inputs that we expect we add accuracy to
our predictions about sensory states. Thus, action has an intimate relationship with
perception, both being governed by the same master principle, namely reduction of free
energy; action can reduce free energy by changing sensory input, while perception reduces
free-energy by changing predictions. In sum, the framework is consistent with theories of
embodied cognition and enactive perception (see Clark, 2013 for discussion) that stress
the role of embodiment in shaping cognition and propose a close link between action and
perception. The framework further makes strong claims about cognition consisting of
predictions (or priors) that do not represent the world and our bodily state directly.
Instead, in order to evade the inherent surprise of the world, our cognition serves a
constantly-updated, Bayes-optimal, iterative, self-fulfilling prophecy. via a cascade of
multilevel processing across the neurocognitive hierarchy, we progressively minimise our
own representational errors in perception and maximize the posterior probability of
generating the observed sensory states in action. In doing so, we generate a kind of
‘virtual version’ of the sources of our bodily signals. The state of the body and its
world is, in this sense, never directly available to perception and always inferred. At
this point however, an important clarification needs to be made. The framework does not
imply that the mind is (dualistically) divorced from its environment, including its body.
The generative models in question are not viewed as mere functions somehow ‘housed’ in the
brain, and ‘informed’ about the body by sensory states. Instead, the ‘mentalisation’ of
the body implies physical, changes in the structure and function of the body itself, from
the periphery to the brain. Indeed, the framework suggests that the structure and
physiology of the brain itself are shaped by sensory states in as much as they shape them
(in both ontogenetic and phylogenetic development) (e.g. see Adams et al., 2013). In other
terms, the inferential, predictive models of possible causes of sensory input are
understood as embodied (e.g. reflecting changes in synaptic connectivity) at different
levels of the neurobiological hierarchy. It follows that in its totality, the self-
organised, agentive virtual model in question is not merely ‘corrected’ by our embodiment
(i.e. affected by sensory prediction errors), but rather it is our embodiment. In this
sense, perception of the body and the world is both truly indirect (virtual, predictive)
in the ‘here and now’ and exact in the long-term: it can ultimately only represent itself.

<h>ANOSOGNOSIA FOR HEMIPLEGIA</h>
--------------------------

Anosognosia for hemiplegia (AHP) is defined as the apparent unawareness of one’s paralysis
(Babinski, 1914), which occurs typically following stroke-induced right perisylvian
lesions, and less often following left perisylvian lesions (Cocchini, Beschin, Cameron,
Fotopoulou, & Della Sala, 2009). This prototypical, neurological disorder of body
unawareness affects our awareness of action; a composite notion that includes at least two
facets, the subjective feeling of moving in the here-and-now, and more general beliefs or
judgments about one’s motor abilities, such as being able to perform certain bilateral
actions (see also below for the related distinction of on-line versus off-line awareness,
as well as the distinction between illusory versus delusional awareness). In a subset of
patients with concomitant body delusions (somatoparaphrenias, Gerstmann, 1942), the right-
hemisphere damage can also affects the sense of body ownership (the subjective feeling
that our body is separate from the world and other bodies). Such patients may reject the
ownership of one’s limb (asomatognosia), misattribute it to others, or vice versa
(somatoparaphrenia proper), claim they have three or more limbs (supernumerary limbs), or
treat the limb as though it was a separate person (personification; Critchley, 1955). The
typical duration of AHP ranges from days to weeks (Vocat, Staub, Stroppini, & Vuilleumier,
2010), but in about one third of patients the symptoms may last beyond the acute stage of
illness and even years (see Pia, Neppi-Modona, Ricci, & Berti, 2004). AHP can be highly
specific in that some patients deny their plegia, while being simultaneously aware of
other neurological, or neuropsychological disturbances (Bisiach, Vallar, Perani, Papagno,
& Berti, 1986; Berti, Làdavas, & Della Corte, 1996; Marcel, Tegner, & Nimmo-Smith, 2004).
In terms of AHP’s ‘extension’ (what kinds, or objects of awareness can be compromised,
Marcel et al., 2004), some patients acknowledge their motor deficits but fail to adjust to
their functional consequences, while others show the opposite pattern (Marcel et al.,
2004; Moro, Pernigo, Zapparoli, Cordioli, & Aglioti, 2011). Furthermore, some patients
claim their limbs have moved even upon demonstration of the opposite (illusory movements,
Feinberg, Roane, & Ali, 2000; Fotopoulou, Tsakiris, Haggard, Rudd, & Kopelman, 2008),
while others admit their on-line failure, but fail to update their long-term or, ‘off-
line’ body awareness (Carruthers, 2008; Marcel et al., 2004; Moro et al., 2011; Tsakiris &
Fotopoulou, 2008). A related, and at times hard to separate, characteristic of AHP is its
‘partiality’ (whether unawareness of one’s deficit is less than total, Marcel et al.,
2004). This property is noted in studies that demonstrate implicit awareness of deficits
despite explicit unawareness in verbal (Fotopoulou, Pernigo, Maeda, Rudd, & Kopelman,
2010), or behavioural tasks (Cocchini, Beschin, Fotopoulou, & Della Sala, 2010; Moro et
al., 2011; Nardone, Ward, Fotopoulou, & Turnbull, 2007), as well as in studies that show
higher awareness of plegia in third-person versus first person tasks. For example,
patients have been observed to deny their deficits in direct view but admit them in a
video replay (Besharati, Kopelman, Avesani, Moro, & Fotopoulou, 2014; Fotopoulou, Rudd,
Holmes, & Kopelman, 2009) or in 3rd-person questions (Fotopoulou et al., 2011; Marcel et
al., 2004). Similarly, patients who deny the ownership of their arms (see above) in direct
view have been shown to admit them in front of a mirror (Fotopoulou et al., 2011;
Jenkinson, Haggard, Ferreira, & Fotopoulou, 2013), and even show improved somatosensation
when tested from a 3rd-person perspective (Bottini, Bisiach, Sterzi, & Vallar, 2002), or
when they use their ipsilesional hand to actively touch their affected, contralesional arm
(Van Stralen, van Zandvoort, & Dijkerman, 2011). More recently, we also showed that
anosognosia can be momentarily reduced following affective, social feedback (Besharati et
al., 2014). Despite recent rapid progress in the assessment and understanding of AHP (see
Fotopoulou, 2014; Jenkinson, Preston, & Ellis, 2011; Orfei, Caltagirone, & Spalletta, 2009
for reviews), little consensus exists regarding its functional and neuroanatomical
explanation. Older theories emphasise deficits in afferent (feedback) and bottom-up
signals, while more recent hypotheses focus on modular abnormalities in predictive
(feedforward) signals and their role in motor awareness (Berti et al., 2005; Frith,
Blakemore, & Wolpert, 2000; Heilman, Barret, & Adair, 1998; see also Jenkinson &
Fotopoulou, 2010 for review). For example, on the basis of a computational model of motor
control (Wolpert, 1997), Frith et al. (2000) have proposed that although patients with AHP
are able to predict the expected sensory consequences of intended movements, they fail to
register the discrepancy between predicted and actual sensory feedback because of
visuospatial neglect or other sensory deficits. Berti and colleagues (see Berti et al.,
2007 for review) suggested that this failure may instead relate directly to damage to the
lateral premotor cortex (Berti et al., 2005). This group as well as other groups have
further produced physiological (Berti et al., 2007; Hildebrandt & Zieger, 1995; but see
Gold, Adair, Jacobs, & Heilman, 1994) and behavioural (Garbarini et al., 2012; Jenkinson,
Edelstyn, & Ellis, 2009) evidence showing that there are intact motor intentions in AHP. A
further study showed for the first time the direct relation between motor intention and
awareness (Fotopoulou et al., 2008). The authors were able to show that patients’ illusory
awareness of movement reflected an abnormal, selective dominance of motor intentions over
visual feedback about the actual effects of movement (elicited by a realistic rubber-hand
patients assumed was their own), and this effect could not be explained by neglect.
Lastly, while as mentioned above, taking a third-person perspective on the self, verbally
(e.g. Marcel et al., 2004) or visually by video-replays (Besharati, Kopelman, et al.,
2014; Fotopoulou et al., 2009) may improve awareness, there may also be an alternative,
motor explanation of the video-replay results. During video viewing, patients receive
visual feedback of their paralysis at a time when they are not intending to move and hence
forward signals are rendered irrelevant to motor awareness. Patients’ awareness during
video-replay needs to rely exclusively on the visual or auditory feedback they receive via
the video clip. Despite the clear value of the ‘feedforward’ hypotheses, it has become
apparent to many authors that a strictly modular, motor explanation is not sufficient to
account for all the manifestations of AHP. For example, such theories cannot explain why
mood induction can temporarily improve AHP (Besharati, Forkel, et al., 2014), nor account
for the extension and partiality of AHP (see above). Indeed, recent experimental studies
have shown that awareness dissociations between and within patients are linked with
different lesion patterns, including limbic areas non-associated with motor functions
(Fotopoulou et al., 2010; Moro et al., 2011). Similarly, in a voxel-based lesion-symptom
mapping study, Vocat et al. (2010) demonstrated that the neuropsychological and neural
profile of AHP patients’ changes in time, and different lesion patterns are associated
with AHP at different time points. These studies point to a multi-component disorder
occurring due to lesions affecting a distributed set of brain regions, including the
insula, premotor and parietal regions but also subcortical areas such as the thalamus,
basal ganglia and limbic structures. More broadly, a number of authors have noted that AHP
sometimes has delusional features that cannot be explained solely on the basis of
sensorimotor deficits (for discussion, see Fotopoulou, 2010; Frith et al., 2000;
Ramachandran, 1995; Turnbull & Solms, 2007; Vuilleumier, 2004; Turnbull, Fotopoulou, &
Solms, 2014). Feedforward theories are valuable in explaining the illusion of moving
(Fotopoulou et al., 2008), but AHP patients do not simply claim that they have the
phenomenal experience of moving. In fact, typically patients with AHP do not spontaneously
complain of any related, subjectively perceived symptom, whether negative (e.g. I am not
moving) or positive (I have the impression that I am moving). On the contrary, AHP is
diagnosed on the basis of questioning during which patients are typically asked to report
on their current experiences (confrontation questions) and infer their more general motor
abilities (see also Marcel et al., 2004). Even patients who report illusory experiences of
movement during confrontation and hence presumably base their inferences on such
impressions (Fotopoulou et al., 2008), they nevertheless simultaneously ignore the wealth
of contrary evidence and medical signs indicating that they are paralysed (e.g. their
medical results, disabilities, occasional accidents and others’ feedback). This perceptual
‘selectivity’ is not the same as the one observed in other symptoms such as hemispatial or
personal neglect, in the sense that patients with neglect can become aware of the fact
that they have neglect after their errors are demonstrated to them. They then continue to
do such errors but they are not surprised or in denial when these errors are pointed out
to them again. In fact, the subset of patients who cannot become aware of their neglect
would be diagnosed as anosognosic for these deficits. Moreover, as aforementioned, there
is now also experimental evidence that patients with AHP maintain their denial even after
they themselves had admitted their paralysis momentarily (e.g. Besharati, Forkel, et al.,
2014). It can thus be said that they adhere to the delusional belief that they have
functional limbs. If one accepts that anosognosia has delusional features then theoretical
loans from the literature on delusions can be allowed (see Fletcher & Fotopoulou, 2014;
Fotopoulou, 2010 for discussions). Of particular interest here is the ongoing debate
between one and two-factor theories. According to the former, rational reasoning on the
basis of anomalous or unusual experience should be sufficient to ultimately lead to
refractory, delusion beliefs (e.g. Maher, 1992). By contrast, two-factor theories claim
that delusional beliefs cannot be explained without the role of additional, cognitive
dysfunctions such as reasoning biases, or monitoring deficits that are necessary for the
generation and maintenance of the false beliefs (e.g. Davies, Coltheart, Langdon, & Breen,
2001; Garety & Freeman, 1999). Indeed, also in the literature on anosognosia, a third set
of recent theories emphasise that the explanation of anosognosic beliefs and attitudes
requires the postulation of additional dysfunctions that prevents sensorimotor and other
failures to be re-represented at a higher level of cognitive and emotional self-
representation, beyond the sensorimotor domain. These accounts stress the necessary
combination of bottom-up and top-down deficits and corresponding lesioned brain regions
(Davies, Davies, & Coltheart 2005; Levine, 1990; Levine, Calvanio, & Rinn, 1991;
Vuilleumier, 2004). For example, considering anosognosia in the more general context of
delusional beliefs, Davies et al. (2005) proposed that anosognosic beliefs maybe explained
by a two-factor account used to explain other delusions; abnormal beliefs arise due to a
first impairment in perception that prompts the abnormal belief and a second impairment
that interferes with higher-order, monitoring processes thus allowing the abnormal
perceptions to become abnormal beliefs. These accounts have undoubtedly being useful in
emphasizing the multifaceted nature of AHP, and for attempting to link the understanding
of anosognosic phenomena with insights about the cognitive processes that may underlie
normal and pathological belief formation (see also Fotopoulou, 2010, 2012). However, these
accounts have been criticized for not being falsifiable (Vallar & Ronchi, 2006). Moreover,
reflecting the modular epistemology of cognitive neuropsychology (Fotopoulou, 2014 for a
critical review), these models treat the described deficits as simply ‘additive’ and as
potentially caused by simultaneous damage to functionally independent lesion sites. For
example, Vocat et al. (2010) suggested that a combination of lesions to two or more brain
areas within the insular, premotor, parietal and temporal cortex, or the white matter
connections that link one or more of these areas with subcortical regions, may lead to
different combinations of deficits in functions such as proprioception, spatial neglect,
and error monitoring, which in turn lead to anosognosia in different patients. While such
‘combinations’ of lesion sites and deficits are consistent with the multifaceted nature of
AHP, what these accounts lack is a more precise neurobiological and neuropsychological
description of the dynamic and hierarchical relation between the affected areas and their
integrated functional role in body awareness. At this point, we turn to the aforementioned
free energy framework in order to propose an alternative model of AHP that aims to address
precisely this limitation, as well as to describe the unique, virtual nature of perception
and the social nature of the bodily self. Finally, this model effectively unifies previous
one- and two-factor models of anosognosia, as it does not allow for a distinction between
perception (experience) and cognition (inference) at any level. Instead, as explained
above, all perception (including all conscious experiences) is always an inference. Thus,
according to the model, the difference between the various manifestations and possible
subtypes of anosognosia cannot be captured on the basis of this distinction between
perception and cognition. Instead, one explanatory factor is indeed sufficient to explain
all manifestations of anosognosia, but this factor is not anomalous experience. Rather it
is the aforementioned, always embodied and always cognitive form of inference that may
become aberrant in anosognosia, as in other delusions (Corlett, Taylor, Wang, Fletcher, &
Krystal, 2009). We consider the particular kind of aberration that may lead to AHP in the
following section.

<h>ABNORMAL INFERENCES ABOUT THE BODY</h>
----------------------------------

On the basis of the free-energy principle, this paper puts forward the idea that AHP can
be best explained as aberrant perceptual inference at various levels of the neurocognitive
hierarchy. It is specifically proposed that the observed lesions result in weak, absent or
unreliable prediction errors about sensorimotor states of the affected body parts, which
ultimately lead patients to base their inference on premorbid, non-updated predictions
about their motor abilities and their agency in the world. This faulty relationship
between premorbid, habitual predictions and imperfect processing of current prediction
errors is thought to take place at different levels of the neurocognitive hierarchy,
consistently with the varied phenomenology and critical lesion sites of patients with AHP
(e.g. Fotopoulou et al., 2010; Vocat et al., 2010). We consider some of the critical types
of such Bayes-optimal, yet aberrant, inference in further detail below.

<hs>  Anosognosia for hemiplegia and the ‘External Body’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

AHP typically occurs in the context of a number of concomitant sensory impairments,
including primary exteroceptive (signals relating to the state of world and the external
surface of the body) deficits as well as related, higher order impairments such as
visuospatial or, personal neglect (see Vallar & Ronchi, 2006; Small & Ellis, 1996 for
reviews). During the 1980s and 1990s, studies under the epistemological remit of cognitive
neuropsychology, attempted to establish whether any of these deficits or any given
combination of deficits could explain the occurrence of one or more of the above
anosognosic phenomena (see Fotopoulou, 2014 for review). These studies revealed double
dissociations between AHP and such impairments, suggesting that none was necessary for AHP
to occur (e.g. Bisiach et al., 1986; Marcel et al., 2004). Nevertheless, under the remit
of the free energy principle, these dissociations do not exclude the possibility that some
of these deficits may act as predisposing, or contributing factors. Exteroceptive signals
about the left side of the body, as represented in the connections of right hemisphere
subcortical areas (e.g. the thalamus), or re-represented and organised in cortical
functional networks of the right-hemisphere (Berti et al., 2005; Fotopoulou et al., 2010;
Moro et al., 2011; Vocat et al., 2010) may be weak, or even absent due to damage to one or
more of these areas. Such damage may therefore allow predictive signals at these levels to
continue to operate ‘unchecked’ by appropriate prediction errors about the current,
exteroceptive state of the body. In other terms, there will not be sufficient or
sufficiently precise (see also below) signals to update one’s normally, predictive motor
awareness. It is further expected that the more and the greater the deficits in one or
more of these domains, the greater the likelihood of faulty (anosognosic) inferences.
Indeed, a recent paper revealed a positive correlation between the degree of AHP and the
combined quantity of such deficits (Vocat et al., 2010). However, as aforementioned, it is
unlikely that these deficits are sufficient to explain the richness of anosognosic
phenomena and are best equipped to explain the illusion of moving, rather than the more
general delusional beliefs and attitudes s that patients with AHP show in several
cognitive and emotional domains. If such deficits were the sole cause of AHP, it would be
unclear why other, unaffected bottom-up information about the body (e.g. internal,
homeostatic signals, see below) could not provide the necessary prediction errors to
update one’s beliefs about the current state of the body. It would also be unclear why
other top-down predictions about the body (e.g. the prediction that one will not fall
after moving one’s left leg) were not used to update beliefs about the body.

<hs>  Anosognosia for hemiplegia and the ‘Internal Body’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A further set of important signals about the body arises from within the body’s skin
boundary. These include proprioceptive and more generally kinesthetic sensations about the
position and dynamic properties of the body in space arising from the vestibular system
and from muscles and tendons, as well as interoceptive sensations about the physiological
conditions of all internal organs (Craig, 2009). Deficits in prioprioception are not
sufficient to cause AHP but they have been shown to be among the most common deficits in
AHP patients (Vallar & Ronchi, 2006; Vocat et al., 2010). The vestibular system is also
thought to be affected in AHP, given the fact that vestibular stimulation has been shown
to temporarily reinstate awareness (Cappa, Sterzi, Vallar, & Bisiach, 1987; Ramachandran,
1995; Ronchi et al., 2013). Such deficits are potentially important when trying to
understand motor awareness, as according to the free energy framework, predictive signals
during action do not constitute forward signals on the basis of efference copies of motor
commands but rather sensorimotor predictions (e.g. proprioceptive predictions) about the
effects of movement (for detailed discussions, see Adams et al., 2013; Friston, 2010).
This perspective thus implies that some patients may have reduced ability to generate
novel predictions about their bodily and spatial effects of their potential left-sided
movements (see also Heilman et al., 1998 for a similar proposal based on a previous
computational model of motor control and awareness). Although this deficit may contribute
to unawareness in some patients, previous studies have shown that at least some patients
with AHP have intact ability to generate sensorimotor predictions (see above). Moreover,
if patients with AHP are unable to generate such predictions, the fact that some patients
insist that they have moved as desired, i.e. fulfilled kinesthetic predictions, is not
easy to explain. Importantly, even in patients whose proprioceptive and vestibular systems
are intact, there is a degree of paresis due to damage to the motor system. In fact
prototypical cases of motor unawareness are considered the ones who show complete
paralysis of their left limbs. Thus, an important source of disruption may be the mere
fact that patient can no longer fulfill their proprioceptive and other related priors by
active sampling of prediction errors (i.e. transmitting such descending somatomotor
predictions to the peripheral motor system and moving their affected limbs so as to
generate reafference). AHP patients should be able to generate such somatomotor
predictions in spared premotor and parietal cortex areas (Berti et al., 2005; Karnath,
Baier, & Nägele, 2005). However, damage further down the hierarchy would mean that such
predictions are not fulfilled by the motor system. Nevertheless, unlike the aforementioned
effects of missing or weak prediction errors that are passed up the cortical hierarchy in
order to modify perceptual inference, such disruptions in active inference at the spinal
cord or subcortical level should not have an effect of motor awareness. The normal role of
such somatomotor (mainly proprioceptive) reafference seems to be to modify descending
predictions at spinothalamic and spino-cerebellothalamic circuits, thus allowing, fast,
‘automatic’ correction and control of movement. Indeed, this lack of active inference does
not seem sufficient to cause AHP as the syndrome occurs in a minority of patients with
stroke-induced hemiplegia. It thus seems that while exteroceptive, proprioceptive and
motor deficits may be important contributors to the symptomatology of some patients with
AHP, they are unlikely to be its primary or central causes. By contrast, another facet of
the internal body may have a more central role in AHP. Recent lesion mapping studies have
highlighted that areas such as the insula, limbic structures and subcortical white matter
connections may be selectively associated with AHP (Fotopoulou et al., 2010; Karnath et
al., 2005; Moro et al., 2011; Vocat et al., 2010). Such areas and their connections are
linked with interoception and motivation and are specifically implicated in bodily
salience and interoceptive awareness (Craig, 2009; Critchley, Wiens, Rotshtein, Öhman, &
Dolan, 2004). Thus, we propose that weak or imprecise (see also below) interoceptive and
emotional signals about the current (physiological) state of the body, may lead to
difficulties in affectively personalising new sensorimotor information about the affected
body parts. This would be coupled with a persistent, necessary adherence to past
expectations of how the affected body parts should feel, ultimately leading to the
aberrant beliefs about any available contrary information about the body. In support of
this hypothesis, a recent study (Romano, Gandola, Bottini, & Maravita, 2014) shown that
right hemisphere patients who show somatoparaphrenic beliefs about their affected body
parts, also show reduced physiological reactions to the threat of the same body parts, as
measured by skin conductance responses. Moreover, given the higher position of such priors
in the neurocognitive hierarchy (see Friston, 2013), such faulty inference may also
‘explain away’ contrary exteroceptive signals during instances of multisensory
integration. To use the words of one anosognosic patient who also denied the ownership of
his paralysed limbs “But my eyes and my feelings don’t agree, and I must believe my
feelings. I know they [left arm and leg] look like mine, but I can feel they are not, and
I can’t believe my eyes.” (C.W. Olsen, 1937, cited in Feinberg, 1997). The degree to which
such interoceptive deficits are linked to delusions of ownership more frequently than
delusions of motor awareness remains to be specified in future studies. Furthermore, a
related deficit in the processing of salience from the affected body parts needs to be
emphasized. As aforementioned, activity in areas such as the insular and the limbic cortex
is not only linked with interoception and emotion but more generally with interoceptive
salience and motivation. In the free energy framework, these notions are linked to the
concepts of ‘precision’ (mathematically inverse dispersion or variance, and hence the
inverse of uncertainty) and its neurochemical equivalent, neuromodulation (Friston et al.,
2012). Specifically, precision is linked mainly with the neuromodulation of synaptic gain
that encodes the uncertainty of random fluctuations about predicted states. It follows
that neuromodulators of synaptic gain (such as dopamine and acetylcholine), do not signal
(reward or pleasure) prediction errors about sensory data but the context in which such
data were encountered. In other words, such neuromodulators report the salience of
sensorimotor representations encoded by the activity of the synapses they modulate. This
is important, especially in hierarchical schemes, where precision controls the relative
influence of bottom-up prediction errors and top-down predictions. In psychological terms,
the processing of salience expectancy allows the organism to control the significance it
attributes to the sensory data it uses to update its predictions or to explain away
prediction errors. The above considerations have added potency in AHP given the above
critical lesion cites, as well the recently identified lesions in fronto-striatal circuits
(Fotopoulou et al., 2010; Moro et al., 2011; Venneri & Shanks, 2004; Vocat et al., 2010).
Such lesions may lead to a more general difficulty in optimizing the precision of
prediction errors (Friston et al., 2012), affecting their salience and ultimately both
short- and long-term learning (suboptimal synaptic gain and plasticity, Friston, 2010).
Indeed, the functional role of the basal ganglia and particularly the striatum has been
linked with prediction error-driven learning (O’Doherty et al., 2003) as well as the
aberrant salience theories of psychosis (Gray, Feldon, Rawlins, Hemsley, & Smith, 1991;
Kapur, 2003). In AHP such deficits can be linked with both specific instances of aberrant
motor monitoring in functionally specialised systems (Berti et al., 2005), or more
generally in global error monitoring (Davies et al., 2005; Venneri & Shanks, 2004; Vocat,
Saj, & Vuilleumier, 2012), mental flexibility (Levine et al., 1991) and ‘surprise
detection’ (Ramachandran, 1995) deficits. Indeed, a recent study showed that AHP patients
had the tendency to ‘jump to conclusions’ on the basis of limited and rather vague
information and then to subsequently get stuck to their former “false” beliefs instead of
modifying them based on novel, arguably more salient information (Vocat et al., 2012).
Another study (Besharati, Forkel, et al., 2014) further found that anosognosia can be
temporarily reduced by the induction of negative mood, presumably because negative
emotions prime the organism for defensive action and increase the salience of sensorimotor
signals (see Pereira et al., 2010; Gentsch, & Synofzik, 2014). These ‘neuromodulatory’
deficits may explain some of the delusional features of AHP that are harder to explain on
the basis of deficits in sensorimotor signals per se, be those exteroceptive or
interoceptive. For example, they provide some insight into how patients can remain in
denial of their paralysis and/or apathetic towards the normally alarming sight of a
paralysed left arm and its related consequences. More generally, this explanation of
anosognosia as an inability to update body awareness in a way that takes into account and
‘personalises’ new motor (agentive), interoceptive (emotional) or, just salient
information about the affected body parts has the advantage of unifying the hypotheses put
forward previously by modular (e.g. Berti et al., 2005; Karnath et al., 2005) and multi-
factorial theories (e.g. Davies et al., 2005; Vuilleumier, 2004) on a single, unified and
neurobiologically-plausible formulation. Moreover, this formulation integrates both
bottom-up and top-down mechanisms of bodily perception, action and belief formation (see
also Fotopoulou, 2012; Fotopoulou, 2014). Furthermore taken together, the above
considerations on AHP in the light of the free energy framework highlight, not only how
our awareness of our own body is based on habitual predictions of its state in the world,
but also how this learned, virtual model of the body is depended on the integrity of the
very body that allowed the model to be formed in the first place (see introduction). I now
turn to a final aspect of body awareness formation that seems less intuitive than the rest
and can hopefully be made more evident via the study of AHP.

<hs>  Anosognosia for hemiplegia and the ‘Impersonalised Body’</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As explained above, the proposal regarding the inability to shape unconscious inferences
about the body by prediction errors signaling information about the affected body parts as
‘personal’ and relevant to the self can explain a lot of anosognosic features and beliefs.
However, a fundamental question remains. Patients seem unable to use other higher-order
knowledge, including social feedback, to update their beliefs. This failure is not easy to
explain on the basis of any sensorimotor deficits. Of course, their feelings that the
paralysed body parts are of limited self-relevance partly explains why they would
disregard social feedback for some time. As the aforementioned patient claimed, one has
learned to trust one’s feelings about the body over and above other sources of
information. This is also consistent with the assumed hierarchy of the proposed model;
brain areas assumed to subserve interoception and emotion are thought of as higher in the
neurocognitive hierarchy than areas subserving exteroception (Friston, 2013). However, why
are aberrant interoceptive inferences not updated by priors at even higher levels? For
example, the model includes the possibility of other, already formed generative models
about the self with predictions represented at higher levels (e.g. ‘my family and doctors
would not lie to me about serious health issues’) that could presumably be used to send
predictions down the neurocognitive hierarchy and eventually influence the inferences
based on faulty interoception and salience. Given that patients’ beliefs about their motor
abilities seem uninfluenced by such knowledge we infer that these processes are not taking
place. This assumption is consistent with the aforementioned clinical observation that
patients with AHP frequently refer to other people’s opinions on their bodily state,
without altering their self-awareness. For example, they say phrases like ‘I know the
doctors think I am paralysed, but I do not believe it’, ‘everyone says I cannot move, but
I know I can’. If such third-person knowledge about the self is available why is it not
affecting their own opinion about themselves? The answer could be that this particular
aspect of perception-cognition, particularly as applied to the affected body parts, is
also damaged by the right hemisphere damage in question. In this section, I will try to
describe the nature of this particular impairment as manifested in AHP and the nature of
the presumed corresponding function in the undamaged brain. Borrowing insights from
Merleau-Ponty (1945/1962) I will call this aspect of body representation, the
‘impersonalised’ body. Related concepts include the ‘habit’ body (Merleau-Ponty
(1945/1962)), the off-line (vs. on-line) body representation (Carruthers, 2008; see also
Tsakiris & Fotopoulou, 2008) and of course the various versions of the old and highly
problematic distinction between body schema and body image. The proposed aspect of body
representation is not proposed as fitting any of these terms exactly, nor being part of a
simple contrast between the personal and the impersonal, or social body. As should be
obvious in light of what I have written above, no simple dichotomy of body representations
would be sufficient to account for the multiple ways in which the body is represented in
the mind and our existence is embodied in brain functioning. However, a proper discussion
of all these concepts and terms escape the scope of this article. Instead, I use the term
‘impersonalised’ body in order to emphasise with a single, heuristic term the
‘objectified’ aspect of this domain of bodily perception, as well as its personal and
interpersonal origins. Perceiving the world, including my own body, also entails the
perception of the body’s action possibilities in the same world. Indeed, my perception of
the world is rarely confined to the characteristics of the input that reaches my few,
sensory organs from my current, unique position and perspective in the world. Instead, my
prior experiences of different sensations, possibilities and positions in the world define
how I perceive the world in any given time and space. For example, my multisensory
expectations and reaching movements adjust to the characteristics and affordances of a
glass on a table by the mere sight of it from one particular egocentric perspective and
prior to any current movements, or tactile feedback. Such expectations constitute the
world as real in relation to my body, even if they remain implicit most of the time. These
ideas, present in phenomenology, have been more recently explored in cognitive
neuroscience and are accepted by scholars that subscribe to the ideas of ‘multisensory
integration’ and ‘enacted perception’. Moreover, such subpersonal processes are also
compatible with the reading of AHP in the light of the free energy framework; the
perception of the world entails (unconscious) inferences based on the agents prior
embodied experiences with the same world. As Merleau-Ponty (1945/1962) first speculated,
the affordances and multisensory characteristics of the world continue to appeal to the
habitual body of the anosognosic patient, in the same hidden way that they appealed to it
prior to the paralysis. Moreover, as I have outlined, the framework explicitly proposes
that perception and action as operating in a continuum, being essentially governed by the
same operating principles. There is however an aspect of such perceptual and active
inference that seems to have received less attention within the framework. The perception
of the world, as a coherent canvas of multiple interrelated sensations, action
possibilities and perceptual perspectives, entails the implicit possibility that any given
object can simultaneously be perceived by different agents. When I look at the front of a
chair, my awareness of the chair as one thing entails my tacit perception of its back. In
this sense, I may be aware that the chair can be perceived by different positions, by
anyone, or by any-body (Taipale, 2014). In more explicit ways, my perception of the world
is developmentally shaped by learning opportunities afforded by solitary prior instances
of active and perceptual inference, as well as by the active presence of other agents (see
Krahe, Springer, Weinman, & Fotopoulou, 2013 for related ideas in the domain of pain
perception). A glass on a table is the object that others and myself can manipulate at any
given time, from any of our unique perspectives. This rich experience of others
interacting with the same world as ourselves is presumably at the basis of our everyday,
intuitive sense of ‘veridical’ and ‘shared’ perception. We perceive the world as
containing unique, whole-in-themselves objects despite the fact that our actual perception
of them from a subjective point of view will always be limited to the constraints of our
body in time and space, e.g. the position of our eyes on the head. This human, adult
ability to simultaneously perceive the world, from many silent, potential perspectives and
the action possibilities they entail, seems to suggest not only that our perception relies
on inference but also that such inferences about the world is deeply embedded in the
social world. Indeed, other than classic phenomenological views on intersubjectivity (see
Gallagher, 2008; Taipale, 2014; Zahavi, 2001 for recent considerations), such ideas have
been mostly developed in certain stands of developmental psychology (e.g. Reddy, 2008;
Rochat, 2009). This perspective however entails a kind of tension when applied to the
body. Signals in the above mentioned domains of the perceived body, including the
exteroceptive and interoceptive domains, are ultimately integrated in egocentric
coordinates. The 1st-person perspective (spatial and mental) remains fundamental for the
perception of the body as mine, as under my volitional control and as separate from other
objects in the world (e.g. Damasio, 1994). In other terms, although the body can be
perceived (objectified) as a kind of socially perceived, impersonal, unique object, it is
also always the subject of all experiences. As aforementioned, this tension has received
many names in the history of mind and brain fields, and this paper cannot even begin to
address the complexities behind such questions. However, attempting to understand this
tension in the context of AHP and the free energy framework, as outlined in this article,
may generate some insights, particularly as our everyday conscious perception of the body
does not include two, separated experiences of the body. We mostly conceive of the body we
see in the mirror as the one who feels itself to be standing in front of the mirror. It
turns out that some patients with AHP do not share this experience. When looking at their
paralysed body parts directly, they believe they are able body parts, and if they are
somatoparaphrenic, they may believe they belong to someone else. However, when confronted
with mirror images or video replays of their own body in the third-person perspective, the
same patients describe the reflected body parts as being paralysed and as belonging to
themselves, respectively (Fotopoulou et al., 2009, 2011; Jenkinson et al., 2013;
Besharati, Kopelman, et al., 2014). These findings confirm the distinction between first
and third-person perspectives on body perception and they further highlight the primacy of
the first person perspective in conscious perception: it is the (delusional) content of
the first person perspective that dominates their conscious awareness when mirrors are not
made available to them. We can thus confirm Merleau-Ponty’s (1945/1962, p. 82) intuitions:
In the case under consideration, the ambiguity of knowledge amounts to this: our body
comprise as it were two layers: that of the habit body and that of the body in this
moment. In the first appear manipulatory objects that have disappeared from the other and
the problem how I can have the sensation of still possessing a limb I no longer have
amounts to finding out how the habitual body can act as guarantee for the body at this
moment. How can I perceive objects as manipulatable when I can no longer manipulate them?
The manipulatable must have ceased to be what I am now manipulating, and become what one
can manipulate; it must have ceased to be a thing manipulatable for me and become a thing
manipulate in itself. Correspondingly, my body must be apprehended not only in an
experience which is instantaneous, peculiar to itself and complete in itself, but also in
some general aspect and in the light of an impersonal being. These observations also
reveal another intriguing aspect of this distinction. Although these patients seem able to
perceive their body ‘correctly’ from a third-person perspective, they do not seem
surprised by the difference between the content of the two perceptual instances. Even
though they may not have ‘seen’ their own arm for a month or so, they do not scream, ‘oh
there it my arm’ when we place a mirror in front of them. Nor do they blame us for
suddenly giving them paralysis when we take the mirror away. And they are not even
surprised by the fact that they themselves have given a different answer about the
ownership and agency of the same body part, just seconds ago. It thus seems that apart
from their deficits in updating their body representation in the first-person, they have
also lost the ability to perceive their body as an object in the world that needs to have
a unique, socially-shared existence. The fact that they can recognize third-person, images
of the body as theirs does not seem sufficient for the proper ‘objectification’ of the
body (i.e. the perception of the body as a thing in itself). The latter, ‘impersonalised’
sense of the body therefore seems to involve cognitive and perhaps emotional operations
that extend the mere self-recognition in third-person perspectives and rather bizarrely
seem to also depend on a kind of grounding in the subjective body, or at least a kind of
flexible, abstract perception and integration of 1st and 3rd person perspectives on the
body. The cognitive and emotional integration between first and third person perspectives
on the bodily self is thought to take place progressively in development but developmental
psychologists, as well as phenomenological and psychoanalytic thinkers, seem to stress
different aspects in these processes of self-objectification and awareness. In fact, the
majority of studies and theories focus on how we come to understand or, infer other minds
via their bodies, or how we come to regulate our own emotions. Far less attention is paid
to the mentalisation (see definition above) of one’s own body via the influence of other
people. While this discussion extends the scope of the current paper, I note certain
possibilities as regards AHP here. The loss of the ‘impersonalised body’ in AHP can be
explained in at least two ways: (a) body awareness from a first person perspective,
including the processing of both interoceptive and exteroceptive signals is higher in the
neurocognitive hierarchy (Friston, 2013), thus prediction errors relating to the
‘objectified’ body are simply explained away by predictions about the subjectively felt
body and its related salience (see also section on the ‘Internal Body’); (b) the very
faculty that allows individuals to engage in the act of flexible perspective-taking and
integrate first and third person perspectives is impaired. The latter interpretation would
be consistent with the observed damage in AHP patients in brain areas such as the
temporoparietal junctions and the superior temporal sulcus (e.g. Besharati, Forkel, et
al., 2014; Fotopoulou et al., 2010; Moro et al., 2011) and we have preliminary data
showing that such lesions in patients with AHP are selectively associated with deficits in
perspective taking and theory of mind abilities (Besharati et al., in preparation).

<h>CONCLUSION</h>
----------

In this paper, I described the counterintuitive syndrome of anosognosia for hemiplegia,
the striking, apparent unawareness of paralysis following right hemisphere stroke. I
further put forward a large-scale framework from computational neuroscience, namely the
free energy framework in order to account for the clinical variability of AHP and unite
previous, seemingly divergent hypotheses about its pathogenesis. The framework proposes a
view of human perception that relies on inferring the self and the world in both
perception and action on the basis of prior expectations and ambiguous sensory signals.
Contrary to intuition, our perception of the world is rarely confined to the
characteristics of the input that reaches our sensory organs from our current, unique
position and perspective in the world. Instead, our prior experiences of different
possibilities and positions in the world define how we perceive the world in any given
moment and position in space. In this sense, cognition can be thought of as imperfect, yet
highly efficient (in a Bayes-optimal sense) strategy for self-organization in an ambiguous
world. Anosognosia for hemiplegia, as a prototypical disorder of body unawareness,
represents an exaggeration of such ‘imperfect’ body awareness system. I hope that the
description of this neuropathology in the light of the free energy framework served to
highlight the deep interdependency of prior beliefs and sensory data; as the brain uses
sensory data to update its virtual model of the world, lack or imprecision of sensory
prediction errors may lead to aberrant inferences influenced disproportionally by
outdated, premorbid predictions. Finally, I hope that this consideration of anosognosia
stresses that our learned, virtual model of the body is depended on the nature and thus
integrity of the very body that allowed the model to be formed in the first instance.


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<ART>Theory of mind, language, and reading: Developmental relations from early childhood to early adolescence
================================================================================

Authors: Susanne Ebert
DOI: 10.1016/j.jecp.2019.104739
Year: 2020
ASJC codes: 3204, 3205
Keywords: Early adolescence, Language, Listening comprehension, Longitudinal study, Preschool age, Reading comprehension, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study longitudinally investigated the relation between theory of mind (ToM) and verbal language skills in 231 children from preschool to early adolescence. Further, links to reading comprehension of texts at age 13;7 (years;months) were examined. To assess ToM, children completed false belief tasks at 5;6 and the Strange Stories at 12;8. To assess language, children completed a receptive grammar/sentence comprehension test at 3;6 and 5;6, a receptive vocabulary test at 3;6, 5;6 and 12;8, as well as a test of listening comprehension of texts at 13;7. A bidirectional relation between early and advanced measures of children's language skills and ToM was found: Changes in ToM were predicted by language skills, especially by receptive grammar/sentence comprehension; changes in children's receptive vocabulary were predicted by early ToM. However, early ToM had no direct or indirect effect on later listening comprehension or reading comprehension after controlling for early language skills. Only children's advanced ToM had a small indirect effect on reading comprehension, via listening comprehension. The results are discussed in light of ToM stability over time, and theories on how language and ToM development are intertwined.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Between 3 and 5 years of age, children gain increasingly greater knowledge of mental
states and processes; that is, they have notable advancement in their theory of mind (ToM)
development. This is reflected in their mastery of explicit false-belief tasks in which
children are asked to predict how a protagonist will act or what a protagonist thinks
based on a mistaken belief. This understanding of false beliefs has been shown to be
closely connected to children’s language skills (Milligan, Astington, & Dack, 2007).
Moreover, longitudinal data and training studies have revealed that in preschool age
language skills are more predictive of ToM than vice versa (de Villiers, 2005; Ebert,
2015; Hale & Tager-Flusberg, 2003). However, less is known about how the two domains are
related longitudinally beyond the preschool years. For instance, little is known about
whether early language skills are related to advanced ToM and whether early explicit
false-belief understanding is related to children’s further development in ToM, language,
and other language-related or cognitive domains (Apperly, Samson, & Humphreys, 2009;
Hughes, 2016; Lockl, Ebert, & Weinert, 2017). Thus, my main aim in this study was to
longitudinally investigate the relation between language and ToM from preschool to early
adolescence. In addition, I asked how both are connected to children’s later reading
comprehension.

<hs>  The role of language in children’s early ToM</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Various theoretical accounts have explained why children’s language skills might be
important for the emergence of ToM in preschool years. On the one hand, children’s
language skills are a means of communication that enable them to take part in and make
sense of verbal communication, especially when people talk about nonvisible mental states
and processes (e.g., Harris, 2005; Nelson, 2005; Wellman & Peterson, 2013). Training and
longitudinal studies show that verbal communication, especially talking about and
elaborating on mental entities, promotes children’s ToM development (e.g., Ebert,
Peterson, Slaughter, & Weinert, 2017; Lohmann & Tomasello, 2003). On the other hand,
language is an important means for representing mental states and separating them from
reality. For example, performance in false-belief tasks was found to improve after the
experimenter provided labels for the different locations of hidden objects (Low & Simpson,
2012). Labeling may support children’s representation of nonobservable objects. In
addition, the ability to use specific mental terms and mastery of syntax, especially
structures with propositions embedded in clauses (e.g., “Hannes thinks that Joshua is
climbing outdoors”), may help children to represent mental states and multiple
propositions simultaneously (see also Astington & Baird, 2005a). Some language components
seem more theoretically relevant for ToM development than others. Whereas pragmatic
features of language and ToM are related by definition (Astington & Jenkins, 1999), there
has been some deeper discussion of whether semantics or syntax are more important for
keeping track of and representing false-beliefs (Astington & Jenkins, 1999; Harris, de
Rosnay, & Pons, 2005; Slade & Ruffman, 2005). A meta-analysis by Milligan et al. (2007)
reported a larger effect size for the longitudinal correlation between ToM and more
general language measures than for receptive vocabulary but reported no other differences
in correlations with various language measures. This suggests that in children’s preschool
years various facets of language support their understanding of mental states and no
single or specific language component is of primary importance (see also Harris et al.,
2005; Miller, 2016). However, although this conclusion can be drawn with respect to
children’s ToM development in preschool, the situation may be different beyond children’s
preschool years.

<hs>  ToM beyond the preschool years</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

At about 5 years of age, when children explicitly understand false beliefs, they are said
to have developed a metarepresentational understanding of the mind (Perner, 1991; Wellman,
2014). However, their understanding of mental states and processes continues to develop
beyond this point. In particular, children learn that people differ in their opinions and
interpretations of the same entity and gain a better understanding of mental states and
processes as well as nonliteral meanings of people’s utterances in more complex social
situations (e.g., Carpendale & Chandler, 1996; Weimer, Dowds, Fabricius, Schwanenflugel, &
Suh, 2017). Accordingly, advanced ToM tests such as the Strange Stories task often
incorporate social scenarios (White, Hill, Happe, & Frith, 2009). In these tasks, children
need to refer to a character’s mental state to explain her or his actions correctly. Many
researchers believe that advanced ToM includes no further changes in children’s conceptual
ToM understanding (Apperly et al., 2009; Devine, White, Ensor, & Hughes, 2016; Keenan,
2003; Lecce, Bianco, Devine, & Hughes, 2017). Nevertheless, it is assumed that individual
differences in the use of mental concepts in social situations exist. The “genuine
variation” account states that although all typically developing children develop a
metarepresentational understanding eventually, individual differences in the time point at
which children acquire this understanding reflect “differences in the ease or fluency with
which children or adults use their theory of mind to attribute mental states to others”
(Hughes & Devine, 2015, p. 151). Thus, individual differences in early ToM should be
related to individual differences in advanced ToM. The few studies that have measured ToM
longitudinally in preschool and middle childhood report medium correlations, supporting
this account (Devine et al., 2016; Ensor, Devine, Marks, & Hughes, 2014; Lecce, Caputi, &
Pagnin, 2014). These studies also suggest that individual differences in language skills
are related to advanced ToM, similarly as for early ToM.

<hs>  Relations between early language and advanced ToM</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Under the assumption that no further conceptual change occurs after having acquired false-
belief understanding, language might play a different role for developing an advanced ToM
than for developing a metarepresentational ToM in preschool. For example, it is possible
that they correlate less or that correlations are rooted in different underlying
mechanisms. For example, language might be correlated only with advanced ToM due to shared
task demands or because it becomes a necessary component of ToM (Apperly et al., 2009;
Miller, 2009). Recent studies show that pragmatic, semantic, and syntactic language
measures are significantly related to ToM in middle childhood but more weakly in early
adolescence (Banerjee, Watling, & Caputi, 2011; Devine & Hughes, 2013; Im-Bolter,
Agostino, & Owens-Jaffray, 2016; Lecce, Ronchi, Del Sette, Bischetti, & Bambini, 2019).
However, from a developmental and theoretical point of view, cross-sectional associations
say nothing about developmental relations. To my knowledge, three longitudinal studies
have assessed language measures as control variables and provide hints on whether early
language skills scaffold ToM beyond the preschool years. Lecce et al. (2014) reported
medium correlations between early receptive vocabulary at about 6 years of age and
advanced ToM (social scenarios) at 10 years in a group of 49 children. Devine et al.
(2016) similarly found relations between receptive vocabulary at 6 years of age and ToM at
10 years (various measures) in a group of 137 children even after controlling for earlier
ToM, executive functions, and socioeconomic status (SES). Ensor et al. (2014) found an
association between more general early verbal abilities at 3 years of age and advanced ToM
(social scenarios) at 10 years. Although these three studies suggest a longitudinal
relation between early language and advanced ToM, they all included only one language
measure at a single time point. In addition, the studies differed in whether they
considered early vocabulary or a more general language comprehension measure. Moreover,
there were differences in the time point when the language measures were assessed; Lecce
et al. (2014) and Devine et al. (2016) measured receptive vocabulary at about 5 or 6 years
of age, whereas Ensor et al. (2014) assessed a more comprehensive language measure at 3
years. They also reported that the impact of early language on advanced ToM at 10 years of
age was mediated by false-belief understanding at 6 years. Thus, it is not clear whether
these various language measures actually were differentially related to advanced ToM. I
extended these previous studies while simultaneously including two different language
measures, vocabulary and grammar (sentence comprehension), at 3 and 5 years of age and
comparing their developmental relations with ToM. Moreover, because early ToM was measured
at 5 years of age, I was also able to specify direct and indirect effects of language at 3
years via early ToM on advanced ToM.

<hs>  Relations between early ToM and later language</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The relation between ToM and language skills might change as children get older and start
school. Now, more complex language comprehension skills, such as those necessary in text
comprehension tasks, become more central. ToM skills might support these language skills.
For example, Pelletier and Astington (2004) assumed that children with more advanced
understanding of mental entities are better able to connect settings, events, and actions
described in a story with the characters’ thoughts, motives, and emotions. Thus, based on
Bruner (1986) idea, children with more advanced ToM may integrate the landscape of action
with the landscape of consciousness more easily when listening to or reading a story. In
addition, an advanced ability to represent mental states and processes also promotes
metacognitive knowledge and skills, which may further support text comprehension.
Moreover, ToM may support understanding the author’s intentions, that is, understanding
the aims of the text, the ability to connect information in the text with earlier
knowledge, and the construction of a mental situation model (see Atkinson, Slade, Powell,
& Levy, 2017; Guajardo & Cartwright, 2016; Kim, 2015). Indeed, some recent longitudinal
studies have reported associations between ToM in preschool and children’s later text
comprehension even after controlling for early language (Atkinson et al., 2017; Kim, 2015,
2016). Another study points to a longitudinal association between early ToM and later
receptive vocabulary (Lecce et al., 2014). However, to my knowledge, no existing studies
have examined the longitudinal association between early ToM in preschool and various
advanced language skills systematically.

<hs>  Relations among ToM, language, and reading</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Early ToM may be predictive of not only advanced language skills but also later reading
comprehension, which is closely related to children’s language skills. Indeed, according
to the simple view of reading, reading comprehension is a product of listening
comprehension and decoding skills (Hoover & Gough, 1990). Moreover, there is good evidence
that early language skills predict later reading comprehension alongside early
phonological information processing and decoding skills (e.g., Dickinson, McCabe,
Anastasopoulos, Peisner-Feinberg, & Poe, 2003; Ebert & Weinert, 2013; Storch & Whitehurst,
2002). However, other higher-order cognitive skills, including ToM, are also discussed as
further potential contributors. Theoretical explanations for the relation between ToM and
reading comprehension of texts are like those for the relation between ToM and listening
comprehension of texts (Atkinson et al., 2017; Guajardo & Cartwright, 2016; Kim, 2015,
2016). Thus, ToM may predict reading comprehension indirectly via listening comprehension,
i.e. verbal language skills. The results of the few studies that have investigated the
impact of early ToM on later reading comprehension are mixed. Whereas some studies found
no direct link between ToM and reading comprehension at all or only via language skills
(Guajardo & Cartwright, 2016; Kim, 2015, 2016; Lockl et al., 2017), others found direct
relations even after controlling for early language skills (Atkinson et al., 2017; Boerma,
Mol, & Jolles, 2017). The lack of association between early ToM and later reading
comprehension reported in some studies might be explained by the fact that these studies
measured reading comprehension at the beginning of learning to read, and tests at this
stage may be so easy that higher-order cognitive processes are not relevant. However,
Atkinson et al. (2017) found a direct link between early ToM and reading comprehension,
even in 6-year-old children, although they did not directly model the role of early
language skills in this relation. In contrast, Boerma et al. (2017), who also found a
relation between ToM and reading comprehension, investigated only the relations between
reading comprehension and advanced measures of ToM and language. Thus, it is not clear how
early and advanced ToM as well as language skills together contribute to children’s
reading comprehension in older children.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

The main aim of the current study was to provide a more systematic investigation of the
longitudinal relation between language and ToM from preschool to early adolescence. If
language is associated only with advanced ToM due to shared task demands or because
language is a necessary component of advanced ToM, only concurrent but no longitudinal
associations should be detected. I assumed that language supports children in
understanding and keeping track of what is going on in social situations and, thus, in
gaining better insights into people’s mental states and processes, as has been found for
developing a metarepresentational ToM in preschool. Furthermore, like in preschool,
children’s language skills enable them to take part in verbal exchanges and communicate
and learn about others’ mental states and processes while inferring the fine-grained
meaning of language in more complex social situations. Thus, I expected that early
language skills also scaffold the development of advanced ToM both directly and indirectly
via early ToM. The current study replicates and extends previous studies in various ways.
First, the developmental period up to 13 years of age was investigated, extending the
developmental periods observed in previous studies. Second, not only one early indicator
for language at each time point was assessed; rather, two were investigated: one for
vocabulary and one for grammar (sentence comprehension). This opens the opportunity to
analyze whether different language indicators play a differential role in children’s ToM
development between preschool and early adolescence. Third, ToM and language measures were
assessed in early childhood and early adolescence; thus, the reciprocal relation between
ToM and language beyond preschool can be investigated in more detail. Given that knowledge
about mental states should support children’s development of metacognitive knowledge and
inference-making skills, I assumed that early ToM is a stronger predictor of later
listening comprehension of texts as an advanced language measure, than it is for later
vocabulary. Furthermore, I investigated how the developmental relation between ToM and
language skills is linked to reading comprehension. ToM and language skills are
interrelated over time, and both are considered to predict later reading comprehension.
However, to my knowledge, how early and advanced ToM and language skills together are
related to reading comprehension in early adolescence has never before been investigated.
From a theoretical point of view, I expected only indirect effects of early ToM and
language measures on reading comprehension via advanced ToM and advanced language
measures. A subordinate aim of the study was to investigate whether individual differences
in early ToM are connected to children’s advanced ToM longitudinally by covering the age
range from 5 to 12 years. In preschool false-belief tasks were used to assess ToM, and in
early adolescence social scenario tasks (i.e., a measure of children’s use of mental
states in social situations) were administered. According to previous studies and in line
with the “genuine variation” account, I expected to find substantial correlations even
after controlling for other cognitive and language measures. I assumed that children who
understand mental concepts earlier than their peers are those who have learned to pay more
attention to mental states and use them more easily and flexibly in early adolescence (see
also Devine et al., 2016). Because nonverbal cognitive abilities, working memory, and
family SES are related to both language and ToM, I also controlled for these variables in
all analyses.

<hs>  Study design</hs>
  ~~~~~~~~~~~~

The current study was based on a subsample of a German longitudinal study that included
children from diverse socioeconomic backgrounds as well as rural and urban areas. This
subsample was tested for ToM at Wave 5 of the more comprehensive study. According to the
study aims, various additional measurement points and measures were included (see Fig. 1
for an overview). For easier comprehension, I renumbered the waves of the more
comprehensive longitudinal study and refer to Wave 1 and Wave 5 in preschool as Time 1 and
Time 2 and to Wave 11 and Wave 12 in early adolescence as Time 3 and Time 4, respectively.
Measures of Wave 1/Time 1 took place in 2005 and were included as baseline measures.
Ethical approval for the comprehensive study was given by the university, and compliance
with ethical standards was confirmed by the German Research Foundation (DFG), which funded
the study. Informed consent to the children’s participation was obtained from their
parents, and all information was provided voluntarily. The children were tested
individually by trained research assistants in their preschools. In early adolescence,
they were tested at home. The children had the opportunity to withdraw from testing at any
point and received a small gift (e.g., sticker) after each testing session. The parents
were also rewarded with a small gift for their participation in interviews and
questionnaires.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The current study’s participants were from a subsample of 267 children from a more
comprehensive longitudinal study. These 267 children should have received ToM measures at
Time 2. However, 47 children could not be reached at this time point due to dropout or
absence during the testing session. Of these 47 children, 11 were reached at Time 3 when
advanced ToM was measured. Thus, those 231 children (125 boys) were included in the
current sample. At Time 1, the children had a mean age of 3;6 (years;months) (M = 41.62
months, SD = 3.95). At the other measurement points included in this study, the children
had mean ages of 5;6 (M = 63.62 months, SD = 3.95), 12;8 (M = 151.70 months, SD = 3.98),
and 13;7 (M = 162.86 months, SD = 3.72). All children were born in Germany, and most (n =
213, 92.2%) had at least one parent with German as her or his native tongue. The
educational and socioeconomic backgrounds of the sample were diverse. To measure SES, I
refer to the family’s Highest International Socioeconomic Index (HISEI; Ganzeboom, De
Graaf, Treiman, & De Leeuw, 1992), an international index of occupational status. The mean
HISEI in the sample was 52.30 (SD = 15.93) on a scale ranging from 16 (e.g., cleaner,
unskilled farm worker) to 90 (e.g., judge in a court of law). An example occupation with
an ISEI of 52 is an administrator for electronic data processing.

        <hss>Theory of mind: False belief</hss>

        At Time 2, children completed one first-order unexpected content false-belief task
        (based on Perner, Leekam, & Wimmer, 1987) and one second-order false-belief task
        (Sullivan, Zaitchik, & Tager-Flusberg, 1994). Both tasks were acted out with small
        figures.

            <hss>First-order task</hss>

            After demonstrating that a peanut box unexpectedly contains a ball instead of
            peanuts, a naive protagonist (P1) arrived and children were asked the false-
            belief question (“What does P1 think is in the box?”) and a control question
            (“Did P1 look inside the box?”). Children needed to answer the control
            question correctly to be given 1 point on the false-belief question. Children
            were also given a second test question about their own belief (“Before you had
            a look inside the box, what did you think was inside?”). Total first-order
            false-belief scores ranged from 0 to 2 (M = 1.26, SD = 0.73).

            <hss>Second-order task</hss>

            Children were told a story about Peter, a boy who found his actual birthday
            present (a puppy) unbeknownst to his mother (Mum) who had told him that he
            would receive a different present (a toy). When Peter was absent, Peter’s Mum
            talked to Grandma about Peter’s present. Children needed to answer two control
            questions (“What has Mum really got Peter for his birthday?” and “What did
            Peter’s Mum say to him that he got for his birthday?”) and three test
            questions. These were one first-order knowledge access question (“Does Mum
            know that Peter saw the dog?”) and one second-order knowledge access question
            (“What does Mum answer to Grandma‘s question: Does Peter know what you got him
            for his birthday?”) as well as one second-order false-belief question (“What
            does Mum answer to Grandma’s question: What does Peter think you got him for
            his birthday?”). In total, children could earn up to 3 points for the second-
            order ToM task (M = 1.71, SD = 1.12). If children responded incorrectly to one
            of the control questions, they received a score of 0 for the test questions.
            Scores on the first-order and second-order tasks were correlated, r(220) = .40
            and, thus, were summed to form a comprehensive ToM score.

        <hss>Theory of mind: Strange Stories</hss>

        At Time 3, we assessed ToM using two stories of deception, two stories of
        misunderstanding, and two stories of double bluff. One of the double-bluff stories
        was rewritten based on a story by White et al. (2009); all other stories were
        taken from a German translation of the Strange Stories (Rakoczy, Harder-Kasten, &
        Sturm, 2012). Children listened twice to each story and a subsequent open-ended
        question about one of the actors’ behavior from an MP3 player via loudspeaker.
        They answered the questions verbally, and their responses were recorded,
        transcribed, and coded according to White et al. (2009). Children received 1 point
        for a partially correct response and 2 points for a fully correct response. About
        25% of the transcripts were coded by a second rater. Interrater reliability was
        good to excellent (intraclass correlation coefficient for absolute agreement
        between .78 and .89; Cohen’s kappa between .76 and .86). The scores for all items
        were summed to form a total score. Cronbach’s alpha was .56.

        <hss>Language: Receptive vocabulary</hss>

        At Time 1, Time 2, and Time 3, children’s receptive vocabulary was measured using
        a German research version of the Peabody Picture Vocabulary Test–Revised (PPVT;
        Dunn & Dunn, 1981). This test contained 175 items ordered in sets of 12 (with 7
        items in the last set). The maximum possible score was 175.

        <hss>Language: Receptive grammar</hss>

        At Time 1, the sentence comprehension subtest of the German Language Development
        Test for 3- to 5-year-old children was administered (SETK 3–5; Grimm, 2001). In
        this test, children were given sentences varying in grammatical complexity. In the
        first section (9 items), they needed to determine which one of four pictures
        corresponded to the sentence they had just heard. In the second section (10
        items), they needed to act out the content of the given sentence (e.g., “Put the
        blue pen under the bag”). The maximum possible score was 19. At Time 2, children’s
        sentence comprehension using a research version of the German adaptation of the
        Test for the Reception of Grammar (TROG; Bishop, 1983/1989; German version:
        TROG-D; Fox, 2006) was assessed. This adaptation contained 48 items and required
        children to select which one of four pictures corresponded to a verbally presented
        sentence. The research version included all the grammatical structures of the
        original test; the only difference was that the first three sets had 2 items
        rather than 4 items. The maximum possible score was 48.

        <hss>Language: Text comprehension</hss>

        At Time 4, six stories (each with approximately 100–150 words) from a paper-and-
        pencil language comprehension test for adolescents adopted from the DELKO project
        (Marx & Stanat, 2009) were administered. The stories varied in the complexity of
        vocabulary and syntax and were set in everyday contexts (e.g., conversation in a
        supermarket) or were more informational (e.g., text about a rare animal). Children
        listened to each story twice and were then asked three to five questions
        (multiple-choice and open-ended questions; 25 questions in total). For example,
        children were asked to recall or compare information or make inferences. Partially
        correct answers were given 0.5 points. The maximum possible score was 25. About
        22% of the answers were coded by a second rater, and interrater reliability was
        good to excellent (intraclass correlation coefficient [absolute agreement] between
        .90 and .98; Cohen’s kappa between .76 and .96). The scores for all items were
        summed to form a total score. Cronbach’s alpha was .64. For some analyses, the two
        language measures conducted at the same time point were z-standardized, summed,
        and averaged. Correlations between the vocabulary and grammar measures were r(225)
        = .70 at Time 1 and r(211) = .57 at Time 2.

        <hss>Reading: Text comprehension</hss>

        At Time 4, a paper-and-pencil test developed as part of the German National
        Educational Panel Study (NEPS; Gehrer, Zimmermann, Artelt, & Weinert, 2012) was
        administered. The test version used was originally developed for ninth graders and
        encompassed five texts of different types (informational, commentary, literary,
        instructional, and advertising). Each text contained about 230 words and was
        followed by five to seven questions, mostly multiple-choice questions with one
        correct option out of four options. The other questions took the form of matching
        and decision-making tasks. All items required children to complete tasks such as
        extracting information and making inferences based on the text. Children had 28
        min to complete the entire test. For some matching and decision-making tasks,
        partially correct answers were possible. The maximum possible score was 33.

        <hss>Nonverbal cognitive abilities</hss>

        At Time 1, the Analogies and Categories subtests from the Snijders–Oomen Nonverbal
        Intelligence Test for 2½- to 7-year-old children (SON-R 2½-7; Tellegen, Winkel,
        Wijnberg-Williams, & Laros, 2005) were administered as an indicator for children's
        nonverbal reasoning skills. This test asks children to infer sorting and
        classification principles and sort, classify, or categorize either abstract
        materials of various shapes and colors or picture cards. The maximum possible
        score was 17 for Analogies and 15 for Categories. Scores for the two subtests were
        standardized, summed, and averaged. The correlation between the subtests was
        r(224) = .48.

        <hss>Working memory</hss>

        At Time 1 two subtests from the German version of the Kaufman Assessment Battery
        for Children (K-ABC; Melchers & Preuß, 2003) were administered. In the Digit Span
        subtest, children answered 12 items clustered into sets of 3 items of identical
        length (2–5 digits). They earned 1 point for each correctly repeated item. In the
        Hand Movements subtest, children needed to repeat a sequence of taps on the table
        performed by the research assistant with their fist, palm, or side of their hand.
        The test consisted of 12 items differing in length (2–4 hand movements each)
        grouped into sets of 4 items. Children earned 1 point for each correctly repeated
        sequence. The maximum possible scores were 12. Test scores for the two subtests
        were standardized, summed, and averaged. The correlation between the subtests was
        r(218) = .51.

        <hss>Family background</hss>

        Parents’ education and SES were assessed via a computer-assisted personal
        interview (CAPI) with the main caregiver in each child’s home at Time 1.

<hs>  Missing data and analytical strategy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 1 presents descriptive statistics for the cognitive and language measures included
in the current study. For various reasons (no further consent to participate was given,
the family moved, illness, technical problems, child refusal, etc.), I did not have valid
data for all children at all measurement points. Due to the large developmental period
under investigation, the dropout rate between the measurement points in early childhood
and early adolescence was particularly high. However, there are good statistical solutions
for missing data, especially in longitudinal research, that do not lead to biased
estimates, although missingness mechanisms need to be considered appropriately (Graham,
2009). I did not assume that the data were missing completely at random (MCAR). Moreover,
Little’s MCAR test was significant, χ2(308) = 517.39, p < .00. However, there is no reason
to believe that advanced ToM itself predicts whether a participant has missing data on
advanced ToM; rather, children from lower SES backgrounds are more likely to drop out of
the study, for example, due to more frequent moves or stress. Moreover, it is known that
SES is associated with early cognitive abilities. Indeed, the 112 children from whom we
had a valid measure in advanced ToM differed in neither age, t(223) = −0.37, p = .71, nor
language background from the children who left the study, χ2(2) = 1.85, p = .40, but were
advanced in cognitive and language skills, F(9, 185) = 2.26, p = .02, and their family’s
HISEI was higher, t(229) = −2.12, p = .04. Thus, I assumed that the data are missing at
random. This means that missing values are systematically related to other observed
variables (Enders, 2013) and that after controlling for “all the variables one has, any
remaining missingness is completely at random” (Graham, 2009, p. 552). I used a full
information maximum likelihood (FIML) approach to account for the missing data and
included early cognitive and language variables as well as background variables for which
missingness was rare as control variables in the model. FIML including control variables
is a good means of handling data that are missing at random, especially incomplete outcome
variables, and results in less biased parameter estimates than older methods (Enders,
2013; Graham, 2003). Thus, FIML is superior to listwise deletion, pairwise deletion, and
similar response imputation, especially in small sample sizes (Enders & Bandalos, 2001).
To analyze the longitudinal association between language and ToM as well as between these
variables and reading comprehension in more detail, I specified path models using Mplus 7
(Muthén & Muthén, 2012). I refrained from estimating latent variables to keep the
structural equation simple and the sample size-to-parameter ratio low. This increases the
likelihood that the statistical requirements will be met even though our sample size is
not huge and missing data are estimated (Kline, 2016). I controlled for autoregressive
effects in all models, which enables determining whether the relations are bidirectional
or solely in one direction. Only if a relation between early and later measures is
observed after controlling for autoregressive effects can the earlier measure be said to
predict developmental change and might be causally related to the later measure (see
Ruffman, Slade, & Crowe, 2002). I also considered direct and indirect links between
language and ToM over time and allowed the predictor variables assessed at one time point
to correlate. Moreover, I included HISEI and the composite scores for nonverbal cognitive
abilities and working memory at Wave 1 as control variables in all models. Hence, I
specified paths between these control variables and all outcome measures at all
measurement points. I also controlled for age by specifying paths between concurrent age
and the cognitive and language measures. I report all significant and nonsignificant paths
that were specified among ToM, language, and reading measures in the figures. For the
other variables, I report only those paths and standardized beta weights that approached
significance at p < .10 for easier readability. The criteria for model fit were as
follows: a root mean square error of approximation (RMSEA) < .08, a comparative fit index
(CFI) > .95, and a nonsignificant chi-square test of model fit (Brown, 2006; Hu & Bentler,
1999).

<hs>  Relations between ToM and language over time</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As shown in Table 2, longitudinal and concurrent correlations between the aggregate
language measures and ToM were moderate to high at all measurement points. Table 2 also
shows that the association between vocabulary and ToM seems to change across waves and
varies for early versus advanced ToM. Thus, PPVT at age 3;6 correlates stronger with ToM
at age 5;6 than with ToM at age 12;8, whereas PPVT at age 5;6 correlates stronger with ToM
at age 5;6 than with ToM at age 12;8. In contrast, the association between grammar and ToM
seems to be more stable over time. Thus, the grammar measure correlates similarly with
early ToM and advanced ToM at both measurement points in preschool. To further investigate
the reciprocal relations between different facets of language and ToM, I specified three
equivalent path models including different language measures for preschool (see Fig. 2) to
predict advanced ToM and language. I used the vocabulary measure in Model 1, the grammar
measure in Model 2, and the aggregate language score consisting of both vocabulary and
grammar in Model 3. All models fit the data very well (see Fig. 2). However, the models
revealed both similarities and differences in the longitudinal relation between language
and ToM. In all models, there was a significant direct effect of language at Time 1 on ToM
in preschool and adolescence. However, the beta weight between vocabulary at age 3;6 and
preschool ToM (β = .24) was much smaller than the one between grammar at age 3;6 and
preschool ToM (β = .51). In addition, the relation between language measures at age 5;6
and advanced ToM differed across the three language measures; even after controlling for
language and various other control variables 2 years earlier, grammar had a direct effect
on the change in ToM between preschool and early adolescence, whereas vocabulary and the
aggregate score for language did not. Furthermore, ToM significantly predicted changes in
vocabulary between ages 5;6 and 12;8, even when controlling for earlier vocabulary and
other control variables, but had no direct effect on listening comprehension. Indirect
effects of early language on advanced ToM via preschool ToM were found only for vocabulary
at age 3;6 (β = .07, p < .05). In addition, there was an indirect effect of early
vocabulary on vocabulary at age 12;8 via preschool ToM (β = .06, p < .05).

<hs>  Relations among ToM, language, and reading</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To investigate whether ToM is related to later reading comprehension after controlling for
language skills, I specified path models that, besides the models in Fig. 2, included a
measure of reading comprehension (see Fig. 3). First, I specified a model that was similar
to Model 3 (see Fig. 2) but included only preschool measures and reading comprehension in
early adolescence (Model a in Fig. 3). This was done to test for direct effects of early
language and ToM on later reading comprehension. In a second model, I also included
advanced ToM and language measures (Modell b in Fig. 3). Model a in Fig. 3 shows that
early ToM has no direct effect on later reading comprehension. There is only a direct
effect of early language measures on later reading comprehension. There were also no
significant indirect effects of early ToM and later reading comprehension via language and
ToM measures in early adolescence (Model b in Fig. 3). However, a small indirect effect of
advanced ToM via listening comprehension on reading comprehension that approaches
significance was found (β = .07, p < .10). In contrast, both language measures in early
preschool showed indirect effects on later reading comprehension. These effects were
mainly mediated by language measures in early adolescence.

<hs>  Relations between early and advanced ToM</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As can be seen in Table 1, early ToM at age 5;6 and advanced ToM at age 12;8 were
moderately correlated, r(101) = .39, p < .01. This correlation hardly changed after
controlling for age (rp = .38, p < .01) and remained substantial even after additionally
accounting for early nonverbal abilities (rp = .32, p < .01). However, Fig. 2 shows that
after also controlling for early sentence comprehension (β = .12; see Model 2), the
correlation between early and advanced ToM was substantially reduced, whereas it remained
significant when controlling for early vocabulary (β = .28; see Model 1). Given that the
advanced ToM measure required a large amount of listening comprehension, I tested whether
a specific correlation between early ToM and advanced ToM existed beyond the effect of
general listening comprehension needed for the Strange Stories. That is, I controlled for
children’s general listening comprehension in adolescence. Therefore, I regressed the
advanced ToM score on the listening comprehension score (DELKO). The correlation between
early ToM and the residual of advanced ToM was substantial, r(93) = .22, p < .05.

<h>DISCUSSION</h>
----------

The current study replicates and extends former research by showing that individual
differences in language measures—especially in early sentence comprehension—predict
changes in ToM from preschool until early adolescence. This is a time interval of more
than 7 years. The study also revealed a reciprocal relation between language and ToM in
this developmental period and showed that early ToM predicts children’s vocabulary.
However, early ToM had neither direct nor indirect effects on reading comprehension at
13;7 years of age, and only advanced ToM exerted small indirect effects on reading
comprehension via listening comprehension. Moreover, the results confirmed and extended
prior studies by demonstrating that individual differences in ToM exhibit a moderate level
of stability across a period of 7 years. These results are discussed in more detail in the
following sections.

<hs>  Relations between early language and ToM</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Consistent with earlier research, the study clearly demonstrated that children’s language
skills are strongly correlated with ToM in their preschool years. In addition, language
skills measured as early as age 3;6 predicted the change in ToM between preschool and
early adolescence. Even though there were no indirect effects of early language skills via
ToM or later language skills on children’s advanced ToM, the findings underscore the
importance of early language skills, which provide children with a strong start and
continue to promote their social understanding until early adolescence at least. In
addition, the study provides evidence that there are differential effects of language
measures on ToM development and that these differential effects might change as children
grow older. In early preschool, individual differences in vocabulary and grammar both
predicted children’s advanced ToM after controlling for early ToM and language; two years
later, only children’s grammar predicted their further ToM development. There are at least
two possible explanations for why language and especially receptive grammar/sentence
comprehension may be important for advanced ToM. First, advanced ToM tasks such as the
Strange Stories are linguistic tasks. Children need to comprehend and verbally respond to
stories that are not acted out with puppets (in contrast to early ToM tests). One way to
investigate whether language is associated only due to linguistic requirements with
advanced ToM would be to measure children’s advanced ToM using tasks that are less verbal
or even nonverbal. It has been shown in numerous ways that language is associated with
early ToM over and above the two constructs’ shared linguistic nature (Astington & Baird,
2005b). With regard to advanced ToM, Devine et al. (2016) study may provide some insight.
The authors of that study administered various advanced ToM tasks that differed in their
verbal requirements. Unfortunately, they did not report whether differences were found in
the associations between the respective tasks and language measures. Thus, it is not known
whether the relation between early language and advanced ToM varies with verbal task
requirements. However, I assume that the Strange Stories are not simply a test of text
comprehension. This assumption is supported by the finding that the advanced ToM measure
and the listening comprehension measure were predicted differently by our three language
measures. In addition, and as expected, reading comprehension was more strongly correlated
with listening comprehension than with advanced ToM. If the advanced ToM measure were
simply a measure of listening comprehension of texts, listening comprehension of texts and
advanced ToM should show stronger similarities in correlational patterns. Moreover,
several prior studies support my assumption by showing that comprehension skills for texts
including mental content (like the Strange Stories) are differently correlated with other
ToM measures and executive functions than comprehension skills for texts including
physical content (Lecce et al., 2019; Rakoczy et al., 2012). Another possible explanation
for the relation between language and advanced ToM is that advanced ToM is typically
applied in social situations based on language. Misunderstandings, double bluffs, and
persuasion are impossible without interpersonal and primarily verbal communication. Thus,
the question arises whether advanced ToM occurs only in linguistic situations. I assume
that even if advanced ToM means in particular paying more attention to mental states in
social situations and, thus, mentally interpreting social situations more easily and
flexibly, this does not necessarily mean that the social situation must be a verbal one.
Hence, alternative measures of ToM suggest nonverbal forms of advanced ToM. For example,
in the “Reading the Mind in the Eyes Test” (Baron-Cohen, Wheelwright, Hill, Raste, &
Plumb, 2001), people must infer a mental state from photographs of the eye region.
Nevertheless, language might have supported the development of one’s ability to pay more
attention to people’s mental states. Indeed, this is exactly what the current study
demonstrates, namely that it is particularly children’s early language that predicts
children’s advanced ToM. Language and in particular syntactical skills allow children to
represent mental phenomena, take part in verbal interactions, and provide opportunities to
learn about mental phenomena as well as about people and their mental states. As children
grow older, the more “functional properties of language as a vehicle for communication and
social exchange with others” (Hughes, 2005, p. 321) may become more important for
understanding others. In contrast to syntactical skills, a rich vocabulary was less
related to advanced ToM. This finding seems to contradict Lecce et al. (2014) and Devine
et al. (2016), both of whom found effects of vocabulary at 5 or 6 years of age on advanced
ToM. However, in contrast to the current study, they did not consider language skills at
an earlier time point. Nevertheless, even when running a model that includes only
vocabulary at age 5;6 and no controls for language and cognition at age 3;6, no effect of
vocabulary at age 5;6 on advanced ToM was found. Admittedly, I cannot exclude the
possibility that differences in the predictability of various language measures at
different measurement points might have emerged by chance, and I agree with Slade and
Ruffman (2005) that children’s general language skills are more important than any single
component when it comes to taking part in the community of minds. However, the current
study showed that language measures that are strongly correlated may nevertheless differ
in their predictive utility for ToM. Indeed, receptive vocabulary and receptive
grammar/sentence comprehension were very strongly correlated at Time 1, meaning that it
was not methodologically possible to include them as separate measures in a single
analysis without suppression effects occurring. However, the predictive value of the
language measured differed despite the fact that the same sample was considered. Thus,
whenever effects of language skills are discussed, it seems important to consider which
facets of language one is talking about. The current study’s result that vocabulary also
has an indirect effect via early ToM on advanced ToM was consistent with Ensor et al.
(2014), who found an indirect effect of general language skills via early ToM on advanced
ToM. However, in the current study, no indirect effects of the grammar measure or the
aggregate language measure via early ToM on advanced ToM were found. In addition, there
were also direct effects of all three language measures on advanced ToM. This suggests
that the link between early language and advanced ToM is not mainly due to the fact that
language supports a metarepresentational understanding, and this in turn helps to build an
advanced mental understanding, but rather that advanced ToM emerges directly due to the
support of early language skills. Most important is that language skills predicted even
changes in ToM between preschool and early adolescence. Apperly et al. (2009) used a
metaphor of cement and scaffolding to describe the roles a variable might play in
development. If a variable is like cement, it becomes part of the construct; if it is like
a scaffold, it is no longer important after a certain point in development. Based on
neuropsychological data, those authors proposed that in adulthood grammar is independent
of ToM and, thus, not part of the construct and not cement, although it might have had a
scaffolding role earlier in development. The current study suggests that for ToM in early
adolescence, language has both roles; the high concurrent correlations between language
and ToM in early adolescence propose that language is part of the construct, and the
longitudinal relations suggest that language might have scaffolded the development of
advanced ToM. Thus, ToM in early adolescence might be an intermediate state before
children achieve an adult ToM. In addition, the results support the idea that grammar and
vocabulary may play different roles in ToM development and that ToM is particularly
related to more complex language skills needed for communication and not simply to a
richer vocabulary.

<hs>  Relations between early ToM and later language</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

It was hypothesized that children’s early ToM supports their metacognitive knowledge and
inference-making skills and, thus, is particularly predictive for listening comprehension
of texts but less for vocabulary. However, the opposite was found to be the case; early
ToM was predictive of changes in children’s vocabulary between ages 5;6 and 12;8, but it
was not predictive of text comprehension, after controlling for earlier language skills.
Three possible explanations for these results are proposed. First, the vocabulary measure
used at older ages may have included more abstract and mental words and, thus, may have
indirectly tested children’s advanced ToM. However, the more complex terms in the PPVT are
not specifically mental. Another possibility is that the effect of ToM on vocabulary
actually reflects the effect of a general text comprehension measure and not a specific
effect of ToM. However, there is a unique effect of ToM on vocabulary at age 12;8 even
after controlling for early sentence comprehension instead of early vocabulary (see Model
2 in Fig. 2). A third explanation is that as children grow older a receptive vocabulary
test such as the PPVT not only might measure children’s vocabulary size but also, and more
strongly, might reflect children’s verbal intelligence. If this is the case, the current
study’s results are even more intriguing. Early ToM would then be an early predictor of
children’s later verbal intelligence, which is important for so many aspects of their
lives. That vocabulary in early adolescence might be more a measure of verbal knowledge
and intelligence may also be reflected in the fact that early receptive grammar/sentence
comprehension is more strongly correlated with advanced ToM than early receptive
vocabulary. However, because I did not expect a relation between early ToM and later
vocabulary, the result will need to be replicated and investigated in more detail in
subsequent studies.

<hs>  Relation among ToM, language, and reading comprehension</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In the current study, a small indirect effect of advanced ToM on children’s reading
comprehension via listening comprehension of texts was observed. This finding is
consistent with the theoretical assumption that ToM facilitates the development of higher-
order comprehension skills in children (Atkinson et al., 2017; Guajardo & Cartwright,
2016; Kim, 2015). However, the effect was small and found only for advanced ToM, not for
early ToM. Moreover, the advanced ToM measure did not mask the effects of early ToM. This
might be explained by the fact that, in contrast to other studies, I controlled for early
vocabulary and grammar and also included a measure of early and advanced ToM. Indeed, many
prior studies that investigated the link between ToM and reading comprehension also found
no effect or only indirect effects of early ToM on later reading comprehension via
language skills (Guajardo & Cartwright, 2016; Kim, 2015, 2016; Lockl et al., 2017).
However, in the current study, reading comprehension was assessed in early adolescence
when children are advanced in basic reading skill and, thus, higher-order cognitive skills
should be more strongly correlated with reading comprehension than in these previous
studies. Nevertheless, our reading comprehension test may have been too demanding for
children of this age given that it was originally designed for older children; thus, the
demands made on basic reading processes may have masked the effects of higher-order
inference-making skills, meaning that even advanced ToM was of little help. Contrary to
this assumption, early and advanced language measures both were found to be important
predictors for reading comprehension. Thus, there seems to be no specific effect of early
ToM on children’s reading comprehension after considering language skills.

<hs>  Stability of individual differences in ToM</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The results demonstrate that young adolescents differ in how they answer the Strange
Stories and that these individual differences are related to differences in children’s
understanding of basic ToM concepts 7 years earlier. Hence, children who developed a more
basic understanding of mental states earlier than their peers during preschool also
exhibit better advanced ToM in early adolescence. However, the study’s correlational
findings are silent with respect to whether the Strange Stories indeed assess the
application of already understood mental concepts or reflect another step in children’s
conceptual ToM development (see Peterson & Wellman, 2019). The moderate internal
consistency of the Strange Stories suggests that different aspects of advanced ToM may be
related to early ToM to differing degrees. Indeed, when differentiating between the mental
concepts measured (misunderstanding, double bluff, and deception), the highest
correlations between false beliefs in preschool and advanced ToM were found for double
bluff stories (r = .50). Because there were only two tasks per concept included, there is
a need for further research including more tasks per mental concept in order to examine
whether early ToM is associated with better social understanding in general or only with
specific mental concepts. There is also recent evidence that ToM shows a diverse
structure, at least beyond the preschool years (Warnell & Redcay, 2019). In confirmation
of other studies, the current study supports the assumption of stable individual
differences in ToM over time (Ensor et al., 2014; Devine et al., 2016), although children
were followed for a longer time period, that is, up to 12 years of age. One implication of
this is that children’s school environment changed fundamentally during this period:
Children left preschool about 6 years of age, went to elementary school for another 4
years, and eventually entered secondary school. In Germany, children enter different
school tracks after Grade 4 (about 10 years of age) depending on their performance in
elementary school. Hence, children had very different educational environments at 12 years
of age (i.e., when advanced ToM was assessed), and they had undergone numerous experiences
between assessments. Given that I did not find lower stability in ToM than Ensor et al.
(2014) and Devine et al. (2016), an “environmental account of stability” (Devine et al.,
2016, p. 769) seems unlikely. However, the factors that support ToM development might not
vary greatly across different school environments and, thus, might not affect stability.
Moreover, this does not mean that environmental factors have no influence on the
development of ToM after preschool. Stability was moderate at best, and there is much room
for other factors to affect development as, for example, was shown for language skills.
Thus, the study shows that the correlation between early and advanced ToM was dramatically
reduced when it was controlled for early grammar, but not when it was controlled for early
vocabulary. This indicates that early ToM also reflects language skills.

<h>LIMITATIONS AND CONCLUSION</h>
--------------------------

The current study adds to previous research on ToM with a more thorough analysis of how
ToM and language skills are linked over an extended time period of 7 years. Nevertheless,
some limitations need consideration. First, internal consistency of advanced ToM was
rather low, and scores were close to ceiling. In addition, both reading and listening
comprehension tests were newly designed measures, which may implicate reduced reliability.
Thus, the internal consistency of the listening comprehension test was rather low, and a
number of children had problems in completing the reading comprehension test in time.
Thus, the reading comprehension test might cover not only reading comprehension but, to an
extent, also reading speed. Another challenge of the current study was the high dropout
rate of about 50%. Nevertheless, given that the study covers a period of more than 10
years in childhood including multiple measurement points, the sample size was still
substantial and included families of a wide variety of SES backgrounds from urban and
rural areas. I am convinced that even if attrition is high, the use of longitudinal data
is critical for gathering information about relations between variables over time and
development, pending good methods to deal with missing data. In addition, given that
previous studies on ToM often refer to SES homogeneous samples, despite our study’s high
attrition, the study makes an important contribution. Unfortunately, it was not possible
to use the same measures of ToM and language (except for vocabulary) in preschool and
adolescence. Thus, it was not possible to deliver evidence of how individual differences
in early ToM and language contribute to “real” growth in these concepts. In addition, in
the current study, only a verbal measure of children’s advanced ToM was included. This
made it somewhat difficult to investigate the “functional” link between early language
skills and advanced ToM. However, it must be taken into account that social understanding
and language may be inextricably intertwined and that early ToM develops out of language
skills (e.g., Astington & Jenkins, 1999). Thus, ToM is interwoven with language. This is
also reflected in the results demonstrating that language and ToM are closely reciprocally
intertwined over time; language skills drive developmental changes in ToM, and ToM also
drives changes in language development.


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<ART>Theory of mind and executive function during middle childhood across cultures
=============================================================================

Authors: Zhenlin Wang, Rory T. Devine, Keri K. Wong, Claire Hughes
DOI: 10.1016/j.jecp.2015.09.028
Year: 2016  |  Pages: 6-22
ASJC codes: 3204, 3205
Keywords: Cross-cultural comparison, Emergence account, Executive function, Middle childhood, Pedagogical experience, Theory of mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Previous studies with preschoolers have reported “East–West” contrasts in children's executive function (East > West) and theory of mind (East < West). This cross-cultural study with two samples of older children from the United Kingdom and Hong Kong aimed to test competing accounts of these contrasts that focus on either global effects of culture or more specific effects of pedagogical experience. Both groups of children in Hong Kong outperformed the British children on executive function tasks. That is, with respect to executive function, general cultural influences appear to be salient. In contrast, compared with their U.K. counterparts, children attending local schools in Hong Kong (but not those attending British-based international schools in Hong Kong) performed poorly on age-appropriate tests of theory of mind. With respect to theory of mind, therefore, pedagogical experiences appear to be more salient than factors related to the broad contrast between individualist and collectivist cultures. Our findings also contribute to the debate surrounding the relationship between theory of mind and executive function; although scores on these two sets of tasks were robustly correlated within each country, the double dissociation between delayed theory of mind but superior executive function for children in local schools in Hong Kong compared with their U.K. peers suggests that variation in executive function may be necessary but is not sufficient to explain variation in theory of mind.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Theory of mind is a developmental achievement that emerges early in life and continues to
develop during adolescence and adulthood. Developments in cognitive domains such as
language and executive function, as well as social factors such as cultural practice,
family context, and interactional and pedagogical experience, all support the process of
gaining insight into people’s mental world (for a comprehensive review, see Hughes &
Devine, 2015). Research in this field has been largely restricted to young children (e.g.,
Wellman, Cross, & Watson, 2001; Wellman & Liu, 2004), although recent years have seen
growing interest in infants’ mental state understanding (e.g., Onishi & Baillargeon, 2005;
Sodian, 2011). Moreover, several studies have reported striking individual differences in
adults’ perspective taking (Dodell-Feder, Lincoln, Coulson, & Hooker, 2013; Ferguson &
Austin, 2010; Keysar, Lin, & Barr, 2003; Royzman, Cassidy, & Baron, 2003). What remains
scarce, however, is research on theory of mind during middle childhood that bridges the
gap between these two fields. A few studies (e.g., Banerjee, Watling, & Caputi, 2011;
Devine & Hughes, 2013; Dumontheil, Apperly, & Blakemore, 2010) have shown age-related
gains in theory of mind across middle childhood, but individual differences in theory-of-
mind development during this period and their underlying mechanisms remain poorly
understood. To address this challenge, the current study examined both internal and
external factors that might contribute to individual difference in theory of mind beyond
early childhood. With regard to internal factors, we focused on executive function, the
higher level cognitive ability that underpins flexible, goal-directed activity using
working memory, attention shifting, and inhibitory control (Blair, Zelazo, & Greenberg,
2005; Diamond, 2013). With regard to external factors, we focused on social and
pedagogical experiences at school, which increase in frequency and complexity across
middle childhood (Eccles, 1999).

<hs>  Theory of mind across cultures</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although most theory-of-mind research has been conducted within Anglo-Saxon countries
(Hughes & Devine, 2015), the past decade has seen a marked increase in cross-cultural
research (e.g., Callaghan et al., 2005; Liu, Wellman, Tardif, & Sabbagh, 2008), including
several cross-cultural comparisons (Ahn & Miller, 2012; Hughes et al., 2014; Lecce &
Hughes, 2010; Lewis et al., 2009; Sabbagh, Xu, Carlson, Moses, & Lee, 2006). This cross-
cultural perspective is helpful in unraveling the nature versus nurture riddle in theory-
of-mind development: Is theory of mind an innate, culturally universal construct that is
merely triggered by environmental factors, or is it cultivated in a context of social
interaction, displaying culturally specific developmental routes? Existing findings are
mixed. Some cross-cultural studies (e.g., Callaghan et al., 2005; Oberle, 2009) have
highlighted synchrony in the onset of false belief understanding, but others have reported
dramatic contrasts. For example, Mayer and Träuble (2013) found that under the age of 8
years Samoan children overwhelmingly failed false belief tasks, with one third of 10- to
13-year-old Samoan children also failing. These results echo earlier reports of delays in
non-Western children’s understanding of false belief (e.g., Naito & Koyama, 2006; Vinden,
1996). Moreover, a meta-analysis of data from more than 3000 children from mainland China
and Hong Kong showed that although mainland Chinese children were more or less in line
with North American children in the onset of false belief understanding, children in Hong
Kong lagged behind by up to 2 years (Liu et al., 2008). If preschoolers in Hong Kong lag
behind their Western peers by up to 2 years in their false belief understanding (Liu et
al., 2008), do they catch up eventually? There is some evidence to suggest that Chinese
adults might in fact have better perspective taking than their Western counterparts. Wu
and Keysar (2007) found that bilingual Chinese American adults outperformed European
Americans in perspective taking. However, a later reanalysis of Wu and Keysar’s data using
a more time-sensitive approach found that the Chinese participants made the same
egocentric mistakes initially in interference as the European American participants but
suppressed the interference earlier and more effectively (Wu, Barr, Gann, & Keysar, 2013).
That is, rather than having a more advanced perspective taking ability, the bilingual
Chinese participants appeared to capitalize on their relatively advanced executive
functions (Sabbagh et al., 2006). To date, no study has gone beyond the preschool years in
comparing the social understanding of children in Hong Kong and Western children. The
first aim of our study was to compare older children from the United Kingdom and Hong Kong
on a battery of age-appropriate theory-of-mind tests in order to assess whether children
in Hong Kong “catch up” in theory of mind during middle childhood.

<hs>  Explaining cultural contrasts: The role of educational experiences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

How might potential differences in theory-of-mind use between children from Hong Kong and
children from the United Kingdom be explained? According to one hypothesis, our cultural
norms (collectivist vs. individualist) about actions and cultural specific epistemologies
shape our mental state inferences (Ames et al., 2001). For example, the emphasis on
obedience and behavioral inhibitory control in parenting practice within collectivist
cultures might lead to reduced conversational exposure to mental state terms (e.g., Mayer
& Träuble, 2013). Related to this view, Lu, Su, and Wang (2008) found that, in both a
longitudinal study and a training study, Chinese preschoolers’ success on false belief
tasks was associated with increased conversational references to other people rather than
to talks about mental states in particular. In contrast, Chasiotis, Kiessling, Hofer, and
Campos (2006) argued that conflict inhibition, but not delay inhibition, is a culture-
independent, universal developmental prerequisite for the development of theory of mind.
As Hughes et al. (2014) have noted, attributing the cross-cultural difference in theory of
mind to individualist versus collectivist contrasts is an oversimplification. Moreover,
this hypothesis fails to account for the discrepancy between Hong Kong children and the
mainland Chinese children found by Liu et al. (2008). In similar collectivist cultures,
Japanese children passed the false belief task at around 6 to 8 years of age (Naito &
Koyama, 2006), considerably later than the Western norm of 4 years (Wellman et al., 2001),
whereas Korean children have been found to outperform their U.S. and British counterparts
on false belief tasks (Ahn & Miller, 2012). Likewise, contrasts have been reported between
children from different parts of Europe: the United Kingdom and Italy (Lecce & Hughes,
2010). In the first cross-cultural study of theory of mind to establish measurement
invariance (i.e., to ensure that group contrasts did not simply reflect spurious
measurement effects), Hughes et al. (2014) compared means on a latent theory-of-mind
factor in school-aged children from the United Kingdom, Italy, and Japan matched on age,
gender, and verbal ability. Their findings replicated both the U.K.–Italy contrast (Lecce
& Hughes, 2010) and previous reports of a delay in Japanese children (Naito & Koyama,
2006). However, there was no clear difference between Italian and Japanese children,
challenging a simple individualist versus collectivist contrast. Instead, Hughes et al.
(2014) proposed that the differences reflected contrasts in pedagogical experience because
children in the United Kingdom start formal schooling at age 4 or 5 years, at least a year
earlier than Italian and Japanese children. The “pedagogical experience” hypothesis
rectifies the oversimplification of individualist versus collectivist contrast by shifting
the focus from a broad cultural construct to a more practical, socially organized activity
(Ratner, 1999), in this case, schooling, as the primary cultural influence on psychology.
This pedagogical experience hypothesis is in line with an environmental account that
emphasizes the social origins of individual differences in understanding of mind. Evidence
for this view comes from several distinctive lines of research, including studies of twins
and deaf children born to hearing versus deaf parents, training studies, and longitudinal
studies of relations between family discourse and theory of mind (for a comprehensive
review, see Hughes & Devine, 2015). Formal schooling immerses children in learning
activities that involve interpreting both epistemic mental states (e.g., knowledge,
memories, ignorance, false belief) and motivational mental states (e.g., attention,
intention). These experiences are likely to benefit children’s theory-of-mind development
(Frye & Wang, 2008; Tomasello, Kruger, & Ratner, 1993). Consistent with this view, theory
of mind has been related to children’s understanding of the concept of teaching and
learning (Frye & Ziv, 2005; Wang, 2010; Ziv & Frye, 2004; Ziv, Solomon, & Frye, 2008) as
well as children’s own teaching activity (Davis-Unger & Carlson, 2008a, 2008b). Our study
provided a unique opportunity to test the pedagogical hypothesis. As a former British
colony in the Far East that is now “Asia’s World City,” Hong Kong includes both
international schools, most of which adopt inquiry-based curricula and use English as a
mode of instruction, and Chinese-style local schools, which focus heavily on academic
learning (Watkins & Biggs, 2001), even in early childhood classrooms. Teachers in Hong
Kong local schools emphasize behavioral control and the need to follow instructions
instead of inquiry (Cheng, Benson, Lau, & Fung, 2009). Children’s early pedagogical
experience is mainly directed to the mastery of language and literacy, which is
predominantly taught in local Hong Kong schools via a drill-and-practice approach (Li &
Rao, 2005) due to the fact that children live in a trilingual (Cantonese, Mandarin, and
English) biliterate (Chinese and English) society. According to the pedagogical
hypothesis, children attending international schools in Hong Kong should perform just as
well on theory-of-mind tasks as their British counterparts because they share a similar
schooling experience. In contrast, children attending local schools in Hong Kong have
quite distinct school experiences that are less rich in opportunities for discussing
different points of view and so might be expected to lag behind their British counterparts
in their theory-of-mind performance. The second goal of the current study was to test this
pedagogical hypothesis. By pairing up U.K. pupils and Hong Kong international school
pupils, as well as U.K. pupils and Hong Kong local school pupils, we singled out the
effect of pedagogical experience that is usually embedded in a broader cultural context.
According to the collectivist versus individualist culture divide hypothesis, both groups
of children in Hong Kong should differ from children in the United Kingdom in their
theory-of-mind performance. According to the pedagogical hypothesis, however, children in
the United Kingdom are expected to show better theory of mind than children in Hong Kong
attending local schools but not those attending international schools.

<hs>  Executive function in theory of mind during middle childhood</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Executive function is closely associated with the acquisition of false belief during early
childhood. The relation between theory of mind and executive function can be summarized by
either the “expression” account or the “emergence” account (Moses, 2001). According to the
expression account, the executive demands of theory-of-mind tasks (in particular false
belief tasks) mask children’s understanding of mind. Specifically, children’s failure on
theory-of-mind tasks reflects the executive demands in those tasks rather than a lack of
theory of mind. According to the emergence account, however, executive function is a
necessary condition for the acquisition of theory-of-mind understanding. Children need to
acknowledge different points of view and be able to hold back their own perspective in
order to appreciate other perspectives. In a recent meta-analysis based on 102 studies
representing close to 10,000 3- to 6-year-old children from 15 countries, Devine and
Hughes (2014) reported a consistent and moderate correlation (r = .38) between false
belief understanding and executive function that remained significant when effects of age
and verbal ability were controlled. Further analysis of 10 longitudinal studies indicated
that early individual differences in executive function modestly predicted later theory of
mind, even when controlling for previous theory-of-mind scores and verbal ability, but not
vice versa. Interestingly, the correlation between executive function and theory of mind
appeared to be consistent across different cultures. The findings support an emergence
account of the relation between theory of mind and executive function. The expression
account posits that children with the greatest levels of executive function performance
should outperform their peers on measures of theory of mind, whereas the emergence account
is more tolerant to a disassociation between theory-of-mind performance and executive
function performance. Sabbagh et al. (2006) compared American and Chinese preschool
children on measures of theory of mind and executive function. Despite a marked advantage
in executive function relative to their American peers, Chinese children did not
outperform their American counterparts on measures of theory of mind. The results seem to
support the emergence account. The expression account also predicts that only the theory-
of-mind tasks with high executive demands, but not those with low executive demands, would
correlate with executive function; on the contrary, the emergence account predicts that
executive function should correlate with theory-of-mind tasks with either high executive
demands or low executive demands. Testing this possibility, Carlson, Claxton, and Moses
(2015) measured preschool children with executive function tasks, theory-of-mind tasks
with high executive demands, and theory-of-mind tasks with low executive demands. They
found that executive function tasks, specifically conflict executive function tasks,
correlated uniformly with theory-of-mind measures that imposed either high or low
executive demands when verbal ability was controlled, again supporting an emergence
account. During middle childhood and adolescence, children continue to develop both
executive function (e.g., Davidson, Amso, Anderson, & Diamond, 2006; Huizinga, Dolan, &
van der Molen, 2006) and theory of mind (e.g., Devine & Hughes, 2013; Dumontheil et al.,
2010). Moreover, individual differences in theory of mind remain correlated with executive
function during middle childhood (e.g., Bock, Gallaway, & Hund, 2014; Lagattuta, Sayfan, &
Blattman, 2010; Lagattuta, Sayfan, & Harvey, 2014). To date, however, the links between
theory of mind and executive function during middle childhood have not been studied in a
cross-cultural context. Examining the relations between theory of mind and executive
function in different cultures provides an opportunity to understand the nature of these
links. Our third goal, therefore, was to compare executive function and theory-of-mind
performance in school-aged children from the United Kingdom and Hong Kong using online
theory-of-mind measures and examine the association between individual differences in
these two domains in each sample. In doing so, we sought to examine the universality of
the relation between theory of mind and executive function during middle childhood.
Moreover, our study gave us an opportunity to test the expression account versus emergence
account of the executive function and theory-of-mind relation. According to the expression
account, if children in Hong Kong outperformed the British children on executive function
measures, they should also do better in theory-of-mind measures. According to the
emergence account, children in Hong Kong would not necessarily outperform their British
counterparts in theory-of-mind measures even if they did so in executive function
measures. In contrast to false belief tasks, in which children need to inhibit their own
more salient knowledge about a situation in order to infer a protagonist’s false belief,
the online measures of theory of mind simply require children to explain the protagonist’s
behaviors and so impose a lower executive demand. According to the expression account,
these measures would not correlate well with executive function measures. The emergence
account predicts that executive function measures should correlate with theory-of-mind
measures with either high executive demands or low executive demands (Moses, 2001). In
summary, our study had three key aims: (a) to investigate similarities and differences in
theory of mind in children from the United Kingdom and Hong Kong, (b) to assess the role
of pedagogical experiences in shaping individual differences in theory of mind, and (c) to
examine the universality of the relations between theory of mind and executive function
during middle childhood. To address these three aims, we drew on two data sets that
included aggregate measures of theory of mind during middle childhood that were
administered to samples of children in Hong Kong and the United Kingdom.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Sample 1 consisted of 118 children (48% male) recruited from seven English-speaking
international schools in Hong Kong and six state primary and secondary schools in the
United Kingdom as part of a follow-up study of children’s social development in the United
Kingdom and Hong Kong led by the third author (Wong, Freeman, & Hughes, 2014). Follow-up
children were matched in age, t(118) = 0.57, p = .57, and self-reported family affluence,
t(117) = 0.49, p = .63. Inclusion criteria for both sites were (a) no known developmental
delays or disabilities and (b) native speaker of English or spoke English as a second
language. The U.K. sample was predominantly White British (77.5%, n = 39; 53% male) with a
mean age of 12.42 years (SD = 1.89, range = 9.00–16.07). The Hong Kong sample was more
ethnically diverse (n = 78; 45% male) than the U.K. sample (77.5% White British) in that
children reported being Chinese (43.6%), White British (17.9%), and mixed race (17.9%)
with a mean age of 12.38 years (SD = 2.00, range = 9.10–15.62). However, a t-test
confirmed that the two samples did not differ in age, t(116) = 0.10, p = .92. In both
samples, English was the primary language spoken at home (United Kingdom = 97.5%; Hong
Kong = 61.5%), with Cantonese (16.7%) and Mandarin (9%) being the two other most spoken
languages at home. In terms of family background, the children from the United Kingdom had
significantly more siblings (M = 1.37, SD = 0.88), t(101) = 2.20, p < .05, d = 0.45, than
the children from Hong Kong (M = 1.01, SD = 0.72). Parental education levels were higher
in the Hong Kong sample than in the U.K. sample, χ2(1) = 9.89, p < .01, ϕ = .31.
Specifically, 68 of 78 mothers in the Hong Kong sample had a university degree or higher,
whereas 33 of 39 mothers in the U.K. sample had upper secondary school education or a
university degree. In terms of socioeconomic status, 80.3% to 85.4% of U.K. and Hong Kong
participants fell in the “affluent” band, respectively, as measured by the Family
Affluence Scale (Boyce, Torsheim, Currie, & Zambon, 2006). Sample 2 consisted of 137
children taking part in the fifth wave of an ongoing longitudinal study of social and
cognitive development in the United Kingdom (Hughes, 2011). We recruited a comparable
sample of 125 children recruited from state primary schools in Hong Kong. Inclusion
criteria for both sites were (a) no known developmental delays or disabilities and (b)
native speaker of English/Cantonese (as appropriate). From this sample of 262 children, we
created two groups of children individually matched on age (in months) and gender from the
Hong Kong sample to children in the U.K. sample. In each site, there were 108 children
(57% male). The U.K. sample was predominantly White British with a mean age of 10.81 years
(SD = 0.39, range = 10.05–11.55). The Hong Kong sample was predominantly ethnic Chinese
with a mean age of 10.81 years (SD = 0.35, range = 10.05–11.54); a t-test confirmed that
the two samples did not differ in age, t(214) = −0.05, p = .96. In terms of family
background and socioeconomic status, the children from the United Kingdom had
significantly more siblings (M = 2.02, SD = 1.45), t(214) = 6.34, p < .001, d = 0.87, than
the children from Hong Kong (M = 1.01, SD = 0.80). Parental education levels were also
higher in the U.K. sample than in the Hong Kong sample, χ2(1) = 16.75, p < .001, ϕ = .28.
Specifically, whereas 64 mothers in the U.K. sample had upper secondary school education
(e.g., A levels) or a university degree, only 33 of the mothers in the Hong Kong sample
had upper secondary school education or a university degree. In terms of self-rated
affluence, children in the United Kingdom (M = 6.09, SD = 1.80) gave themselves higher
ratings on the Family Affluence Scale than children in Hong Kong (M = 4.46, SD = 1.86),
t(212) = 6.53, p < .001, d = 0.90. These between-sample differences in family background
and socioeconomic status were controlled statistically in each of our models.

<hs>  Measures</hs>
  ~~~~~~~~

Table 1 summarizes the measures administered to Samples 1 and 2.

        <hss>Theory of mind</hss>

        Each theory-of-mind task involved watching a short film clip or listening to a
        short audio file (∼30 s in length) and then either explaining a character’s
        behavior or answering short questions about a character’s thoughts and feelings.
        The children from both samples completed the Triangles Task (Castelli, Happé,
        Frith, & Frith, 2000). In this task, the children watched three short silent
        cartoons depicting two triangles moving about against a white background. Designed
        to elicit mental state attributions, these cartoons featured instances of coaxing,
        teasing, and surprising. Using the coding scheme developed by Castelli et al.
        (2000), the children’s responses were scored for ascription of intentionality
        (i.e., the proclivity to ascribe mental states when explaining the actions of the
        triangles) and accuracy (i.e., how closely descriptions matched the intended
        story). Intentionality scores ranged from 0 (non-deliberate action) to 5
        (deliberate actions with the goal of affecting others’ mental states). Accuracy
        was scored as 0 (incorrect descriptions), 1 (imprecise descriptions), or 2
        (correct descriptions of the story presented in the clip). We created total scores
        by summing together intentionality and accuracy scores for each item (possible
        range = 0–21). The children in both samples also completed the Silent Film Task
        (Devine & Hughes, 2013). In this task, the children were required to explain the
        behavior of characters in five clips (∼30 s in length) from a classic silent
        comedy played once in a fixed order. The first clip was accompanied by two
        questions, and the remaining four clips were followed by one question. Following
        the coding scheme developed by Devine and Hughes (2013), participants received 2
        points for responses that correctly described the events shown in the clip with
        reference to characters’ mental states, 1 point for answers that correctly
        described the events but did not use mental explanations, and 0 points for
        irrelevant or factually incorrect responses. Scores for individual items were
        summed together to create a total score (possible range = 0–12). In addition, the
        children in Sample 2 completed the Strange Stories Task. For this task, we used
        five vignettes (taken from Happé, 1994) that depicted social situations involving
        double bluffs, deception, and misunderstanding. After each vignette, the children
        were asked to explain a character’s behavior. The vignettes were translated into
        Cantonese by a panel of three English/Cantonese bilingual developmental
        psychologists that included the lead author, adopting a collaborative and
        iterative translation approach to ensure conceptual equivalence (Douglas & Craig,
        2007). In each site, children listened to recordings (∼30 s in length) of an adult
        reading each of the stories. The text of each story remained on-screen after the
        audio recording stopped. Following the coding scheme developed by White, Hill,
        Happé, and Frith (2009), fully correct responses received 2 points, partially
        correct responses received 1 point, and incorrect responses received 0 points;
        across the five vignettes, therefore, children could score between 0 and 10
        points. The validity of these tasks as measures of theory of mind is supported by
        three sources of evidence. First, these tasks have shown concurrent associations
        in a large sample of children ages 7 to 13 years even when individual differences
        in verbal ability and narrative comprehension were taken into account (Devine &
        Hughes, 2016). Second, performance on these tasks at age 10 years has also been
        shown to be linked to earlier performance on a battery of false belief
        understanding tasks at age 6 years (Devine, White, Ensor, & Hughes, submitted for
        publication). Third, performance on these tasks has been shown to be related to
        individual differences in children’s self-reported social competence (Devine &
        Hughes, 2013). For each task, the children’s responses were digitally recorded and
        later transcribed verbatim for coding. To ensure comparability of ratings, 25% of
        the transcripts in each site in both studies were double-coded. Individual items
        exhibited moderate to strong levels of reliability. In Sample 1, the two-way mixed
        single measure model type with absolute accuracy showed excellent average measure
        reliability for the Silent Film Task total score (intraclass correlation (ICC)[3,
        1] = .96, 95% confidence interval (CI) [.89, .98], p < .001). The kappa values for
        all items were within acceptable ranges (κ = .73–1.00, SE = .00–.12). Similarly,
        the total intentionality (TTI) and appropriateness (TTA) ratings on the Triangles
        Task showed excellent average measures reliability (TTI: ICC[3, 1] = .96, 95% CI
        [.91, .98]; TTA: ICC[3, 1] = .90, 95% CI [.78, .96]; ps < .001), with item-level
        ICCs ranging from .76 to .92. In Sample 2, the second author trained the Hong Kong
        team in the rating procedures using transcripts from the U.K. sample as well as
        translated transcripts from the Hong Kong sample. For the Strange Stories Task,
        the mean κ was .92 and total summed scores showed excellent levels of interrater
        reliability (ICC = .97, 95% CI [.94, .99], p < .001). For the Triangles Task, the
        mean κ was .77 and the total summed scores showed excellent levels of interrater
        reliability (ICC = .97, 95% CI [.94, .99], p < .001). Finally, the individual
        items of the Silent Film Task showed acceptable levels of interrater reliability,
        the mean κ was .82, and summed total scores showed excellent interrater agreement
        (ICC = .94, 95% CI [.87, .97], p < .001).

        <hss>Executive function</hss>

        The children in both samples completed the Bead Memory Task from the
        Stanford–Binet Intelligence Scale (Thorndike, Hagen, & Sattler, 1986). On each
        trial, the participants were shown (for 5 s) a picture of an arrangement of beads
        on a stick (across trials, the beads varied in number, shape, color, and
        position). The participants were then given a box of beads and were asked to
        reproduce each bead arrangement exactly. The task was discontinued after three
        failures across four trials. Raw scores were calculated by subtracting the number
        of failed trials from the highest item attempted. Although initially designed to
        measure short-term visual memory, the Bead Memory Task also measures multiple
        executive functions. Specifically, participants must (a) refrain from touching the
        beads while the image is displayed, (b) hold the image in mind while they select
        the beads, and (c) plan ahead in order to place the beads on the stick in the
        correct sequence. Performance on this task is correlated with performance on
        measures of inhibitory control and set shifting during childhood (e.g.,
        Hongwanishkul, Happaney, Lee, & Zelazo, 2005; Hughes & Ensor, 2011). The children
        in Sample 1 also completed the Digit Span Backward Test and the Trail Making Test.
        The Digit Span Backward Test (Wechsler Intelligence Scale for Children–Fourth
        Edition [WISC-IV]; Wechsler et al., 2004) is a widely used assessment of working
        memory. The examiner read out a list of numbers at approximately one digit per
        second, and the participants were asked to repeat this list of digits in reverse
        order. Each list was read out once and increased by one digit until the
        participants failed two consecutive lists of the same digit span. The correct
        responses were summed to create a total score (ranging from 0 to 16) and
        standardized scores. Scores for the current study ranged from 4 to 16. The Trail
        Making Test A and B (Corrigan & Hinkeldey, 1987) is a two-part test measuring
        switching and visual attention. The participants were timed on how quickly they
        could connect circles without lifting their pen off the page. This was first done
        sequentially on a page of 25 randomly scattered “numbered” circles on Form A (1-2-
        … 25) and then using an alternating order of “numbered–lettered” circles on Form B
        (1-A-2-B, etc.). Each form started with practice items, and mistakes were
        corrected and factored into total task completion time. The time difference
        between Form B and Form A provided an index of executive function, where a longer
        time (in seconds) reflected poorer performance. In this study, the time difference
        between forms ranged from 0 to 180 s. This was standardized, and a higher value
        reflected poorer performance. The children in Sample 2 completed the Arrows Task
        (Davidson et al., 2006), a measure of inhibitory control. In this task,
        participants viewed one of four images of a purple arrow on a white screen and
        needed to respond by hitting a key on the left (1) or right (0). The arrow pointed
        either directly downward or diagonally on either the left- or right-hand side of
        the screen. During control trials, the arrow appeared on either the left or right
        and pointed directly downward, and participants needed to press the button on the
        same side as where the arrow appeared. During test trials, the arrow appeared on
        either the left or right but pointed diagonally. On these trials, participants
        needed to press the button on the opposite side of where the arrow appeared. The
        participants received detailed instructions and practice items prior to completing
        the task. The arrows were displayed for up to 750 ms and were preceded by a 500-ms
        interval in which a crosshair was displayed against a white background. The
        children completed 12 control trials and 12 test trials in a random order. To
        measure inhibitory control, we calculated efficiency scores based on the total
        number of correct test trials divided by the total time taken on test trials. The
        children in Sample 2 also completed the Smiling Faces Task (Huizinga et al.,
        2006), a measure of cognitive flexibility. During this task, the children needed
        to respond with a button press to one of four cartoon faces (i.e., a happy boy, a
        happy girl, a sad boy, and a sad girl) displayed in one of four quadrants on a
        white screen. In single task trials, the children needed to identify whether the
        face was a boy or a girl if it appeared in the top two quadrants (by pressing 1 or
        2) or to identify whether the face was happy or sad if it appeared in the bottom
        two quadrants (by pressing 3 or 4). During alternating trials, the children needed
        to integrate both rules. The trials were administered in four blocks in a fixed
        order: one set of 16 single task trials (boy or girl), another set of 16 single
        task trials (happy or sad), and two sets of 16 alternating trials. The trials
        within each block were presented in a random order. The participants were provided
        with detailed instructions and were asked to repeat back the rules of the task
        before each block. Each trial lasted up to 3500 ms, during which time the
        participants needed to respond with a button press. The trials were preceded by a
        500-ms interval in which a black crosshair was displayed in the center of a white
        screen. We calculated efficiency scores based on the total number of correct
        alternating trials divided by the total time taken to complete the alternating
        trials.

        <hss>Verbal ability</hss>

        Unfortunately, there was no measure of verbal ability that had been standardized
        for use in both Hong Kong and the United Kingdom. The children in Sample 1
        completed the Word Reasoning Test from the WISC-IV (Wechsler et al., 2004). In
        this task, the participants needed to identify the concept being described in a
        series of 24 clues of increasing difficulty. Each item was scored as either
        correct (1) or incorrect (0) before five consecutive “blanks” produced a total
        verbal ability score out of 24. We standardized raw summed scores (with a possible
        range of 0–24) within each country using T-scores so that each child’s verbal
        ability was measured against peers in his or her own country. For the children in
        Sample 2, we adopted the British Picture Vocabulary Scale (BPVS; Dunn & Dunn,
        2007) because this is a widely used task that has very simple instructions. On
        each trial, the examiner read aloud a word and the children needed to point to one
        of four pictures that provided the best match for that word. We used the stimulus
        booklets and vocabulary lists from the U.K. version of this task. Adopting a back-
        translation approach (Brislin, 1970), each word was translated into Cantonese and
        then back-translated into English by a panel of three English/Cantonese bilingual
        developmental psychologists that included the lead author. The panel discussed and
        modified the Cantonese version to ensure that the two versions were equivalent in
        meaning. The Cantonese version was checked against “Lexical items with English
        explanations for fundamental Chinese learning in Hong Kong schools” provided by
        the Hong Kong Education Bureau (2009) to ensure progressive difficulty of the
        vocabulary. We calculated raw scores by subtracting the number of errors made by
        each participant from the item number corresponding to the last number in the
        participant’s ceiling set (i.e., the set containing eight or more errors). We then
        standardized scores within each country using T-scores so that each child’s verbal
        ability was measured against peers in his or her own country.

<hs>  Procedures</hs>
  ~~~~~~~~~~

The children in Sample 1 completed a 60-min individual testing session at school with the
third author on two theory-of-mind tasks (Silent Film and Triangles), three executive
function tasks (Beads, Digit Span Backward, and Trail Making), and a language test, among
other tasks. All tasks were administered in English in both the United Kingdom and Hong
Kong. At each site, the children in Sample 2 completed individual test sessions in a quiet
environment at school. During these sessions (which lasted ∼90 min, including breaks), an
experienced graduate researcher administered a battery of tasks presented in a
counterbalanced order in either English (in the United Kingdom) or Cantonese (in Hong
Kong). The U.K. team provided the Hong Kong team with detailed training and observed pilot
sessions in Hong Kong to ensure that the data collection procedures were identical.

<hs>  Analytic approach</hs>
  ~~~~~~~~~~~~~~~~~

In analyzing the data from both samples, we used confirmatory factor analysis (CFA) to
test measurement models designed to reduce the number of variables in our data and provide
error-free parameter estimates. Next, we used multiple indicators, multiple causes (MIMIC)
models (Brown, 2006) to examine cross-cultural differences in both the theory-of-mind and
executive function latent factors. Given the presence of non-normally distributed
variables in each data set, we estimated each model using robust maximum likelihood
estimation (as opposed to maximum likelihood estimation) in Mplus 7 (Muthén & Muthén,
2012). The robust maximum likelihood estimator provides more accurate parameter estimates
than standard maximum likelihood estimation (Brown, 2006; Kline, 2011). For each model, we
evaluated fit using Brown’s (2006) four recommended criteria: a nonsignificant chi-square
(χ2) test, comparative fit index (CFI) ⩾ .90, Tucker–Lewis index (TLI) ⩾ .90, and root
mean square error of approximation (RMSEA) ⩽ .08. The effect sizes for the various model
parameters were interpreted in accordance with recommendations from Kline (2011); small
standardized effect sizes ranged from .10 to .30, moderate effect sizes ranged from .30 to
.50, and large effect sizes were greater than .50.

<hs>  Descriptive statistics and data reduction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 2 shows descriptive statistics (and intercorrelations) for each of the key variables
for Sample 1. There was no evidence of ceiling or floor effects on either the Triangles
Task or Silent Film Task. There were no differences between boys and girls in age, self-
reported family affluence, or performance on any measures of verbal ability, theory of
mind, or executive function (−1.36 ⩽ t ⩾ 1.33, all ps > .10). There were modest
correlations between the two measures of theory of mind. The three measures of executive
function were moderately intercorrelated. With the exception of the Trail Making Task and
the Digit Span Backward Task, each of the variables conformed to normality (i.e., Zskew <
±3.29). Table 3 shows descriptive statistics (and intercorrelations) for each of the key
variables for Sample 2. Each of the three measures of theory of mind captured a wide range
of individual differences, as evidenced by the symmetrical distribution of scores on each
task. There was no evidence of ceiling or floor effects on either the Triangles Task or
Silent Film Task; no participants scored 0, and only 1% of the participants obtained the
maximum score on either task. The Strange Stories Task showed some evidence of negative
skew, with 12.5% of the participants achieving the maximum score. With the exception of
the Arrows Task efficiency score, Strange Stories Task total score, and BPVS score, all of
the key variables conformed to normality (i.e., Zskew < ±3.29).

<hs>  Data reduction</hs>
  ~~~~~~~~~~~~~~

In Sample 1, we tested a two latent factor model using CFA. First, we loaded both theory-
of-mind indicators onto a single theory-of-mind latent factor. Next, we loaded each of the
three executive function indicators onto a separate (but correlated) executive function
latent factor. This measurement model provided a good fit to the data, χ2(4) = 1.60, p =
.81, RMSEA = .00, CFI = 1.00, TLI = 1.00, Akaike information criterion (AIC) = 3463.10.
The standardized factor loadings for the theory-of-mind latent factor were .75 and .38 (ps
< .01). The standardized factor loadings for the executive function latent factor ranged
from .63 to .70 (all ps < .001). The theory-of-mind latent factor was moderately
correlated with the executive function latent factor (ϕ = .43, p = .01). In Sample 2, we
specified a two latent factor model in which each of the three theory-of-mind task
indicators loaded onto a theory-of-mind latent factor and each of the three executive
function task indicators loaded onto an executive function latent factor. The two latent
factor model fit the data well, χ2(8) = 13.64, p = .09, RMSEA = .05, CFI = .95, TLI = .91,
AIC = 7146.43. Both latent factors accounted for significant variance in task performance.
The three theory-of-mind indicators loaded significantly onto the theory-of-mind latent
factor (mean loading = .50, range = .30–.69, all ps < .001). The three executive function
indicators loaded significantly onto the executive function latent factor (mean loading =
.50, range = .38–.67, all ps < .001). The two latent factors were strongly correlated (ϕ =
.77, p < .001). Note that we chose to use a two latent factor solution for two reasons.
First, from a conceptual perspective, theory of mind and executive function are related
but distinct constructs. Meta-analytic evidence shows that individual differences in
executive function and theory-of-mind task performance are only moderately correlated
(Devine & Hughes, 2014). Moreover, findings suggest that the “real-life” correlates of
executive function and theory of mind are distinct; for example, the relations between
executive function and problem behaviors are significantly greater than those between
theory of mind and problem behaviors in preschool children (Hughes & Ensor, 2008). Second,
from an empirical standpoint, an alternative single latent factor model in both samples
did not provide a good fit to the data (Sample 1: χ2(5) = 8.96, p = .11, RMSEA = .08, CFI
= .94, TLI = .88, AIC = 3467.98; Sample 2: χ2(8) = 18.24, p = .03, RMSEA = .07, CFI = .92,
TLI = .87, AIC = 7149.03).

<hs>  Modeling theory-of-mind task performance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Using data from Sample 1, we examined whether there were cultural differences in theory-
of-mind task performance using a structural equation in which the two latent factors of
theory of mind and executive function were regressed onto a binary “nation” variable. To
reduce the potential influence of confounding variables, we also regressed each latent
factor onto three continuous variables: age, verbal ability, and self-reported family
affluence (the latter of which is a socioeconomic status [SES] indicator). This model
provided an excellent fit to the data, χ2(16) = 19.23, p = .26, RMSEA = .04, CFI = .97,
TLI = .95, AIC = 3423.38. The parameter estimates for this model are presented in Fig. 1.
When accounting for individual differences in executive function, age, verbal ability, and
family affluence, there were no significant differences between the British children and
the Hong Kong international school children in their performance on the theory-of-mind
latent factor. In contrast, there was a weak but significant difference in performance
between children in Hong Kong and children in the United Kingdom on the executive function
latent factor, with children from Hong Kong outperforming their British counterparts by
.21 standardized units. This difference was independent of individual differences in age,
verbal ability, theory of mind, and family affluence. Next, using data from Sample 2, we
specified a similar structural equation model to examine cultural differences in theory-
of-mind task performance. To minimize potential confounds, we also regressed each latent
factor onto age, gender, number of siblings, parental education, and verbal ability
scores. Our initial model did not provide a good fit to the data, χ2(32) = 68.41, p <
.001, RMSEA = .07, CFI = .86, TLI = .78, AIC = 6888.13. Inspection of the modification
indices revealed evidence of differential item functioning in that nation exerted a direct
effect on performance on both the Strange Stories Task and Triangles Task (see below for
more details). The inclusion of these regression paths improved the overall model fit,
χ2(30) = 37.13, p = .17, RMSEA = .03, CFI = .97, TLI = .95, AIC = 6860.85 (see Fig. 2).
Together, these models accounted for 65% of the variance in theory-of-mind latent factor
scores and 64% of the variance in executive function latent factor scores. Echoing
findings from preschool samples (e.g., Sabbagh et al., 2006), scores on the theory-of-mind
latent factor in Sample 2 were significantly lower for children from Hong Kong than for
children from the United Kingdom. Even when potential differences in executive function,
parental education, number of siblings, and verbal ability were controlled, children from
Hong Kong were, on average, .60 standardized units lower than children from the United
Kingdom, indicating a medium to large difference in performance (Brown, 2006; Cohen,
1988). The direct effect of nation on the Strange Stories Task and Triangles Task
indicators (independent of individual differences in the theory-of-mind latent factor)
showed that these indicators were not culturally invariant. That is, performance on these
two tasks differed between both sites for reasons other than theory of mind. In sum, there
were national differences favoring children in Hong Kong in aspects of these tasks that
did not related to mental state reasoning. In direct contrast to the results for the
theory-of-mind latent factor, children from Hong Kong outperformed children from the
United Kingdom on the executive function latent factor. When effects of theory of mind,
parental education, number of siblings, and verbal ability were controlled, children from
Hong Kong obtained scores that were, on average, .37 standardized units higher than those
for children from the United Kingdom. This is equivalent to a small difference in
performance (Brown, 2006). There were no direct effects of nation on the indicators of
executive function, suggesting that these items were culturally invariant. The structural
equation model revealed moderate to strong correlations between theory of mind and
executive function latent factor scores as well as between each of these latent factors
and verbal ability. Parental education, SES, age, and gender exerted small but significant
effects on executive function (but not on theory of mind). The number of siblings a child
had was unrelated to either theory of mind or executive function.

<h>DISCUSSION</h>
----------

In this article, we have presented data from two cross-cultural comparisons that jointly
produced three main findings. First, when effects of general child and family
characteristics were taken into account, theory-of-mind latent factor scores were
equivalent for children in the United Kingdom and children attending international schools
in Hong Kong, but children attending local schools in Hong Kong scored, on average, .60
standardized units lower than children from the United Kingdom, indicating a medium to
large effect. Second, the contrast between children in Hong Kong attending local schools
and those attending international schools was specific to theory of mind; both groups
outperformed their British counterparts on the executive function latent factor with small
effect sizes, .23 standardized units in Sample 1 and .37 standardized units in Sample 2.
Third, in both samples, the latent factors for theory of mind and executive function were
correlated with either a moderate or large effect size. Our motivation in conducting this
research was to discover whether children in Hong Kong “catch up” in theory-of-mind
performance during middle childhood. The results revealed no evidence for such a catch-up,
at least for Hong Kong local school pupils. The findings extend earlier reports of young
Hong Kong children’s delay on theory of mind (Liu et al., 2008) and demonstrate a
persistent lag in Hong Kong children’s social understanding. Furthermore, this lag could
not be explained by factors related to the global contrast between individualist and
collectivist cultures because, unlike their peers from Hong Kong local schools, children
from Hong Kong international schools performed just as well as their British counterparts
on theory of mind. Instead, the results favor the pedagogical experience hypothesis,
namely that children who were exposed to inquiry-based pedagogy (children in the United
Kingdom and children attending Hong Kong international schools) showed better theory-of-
mind performance than children who were exposed to the drill-and-practice pedagogy (Hong
Kong local school children). What makes this conclusion more convincing is the fact that
children attending international schools in Hong Kong were better on executive function
than the U.K. children, just as children attending local schools in Hong Kong outperformed
their British counterparts. In other words, Hong Kong international school pupils were
culturally distinct from the U.K. children. Hong Kong international school students were
more likely to be bilingual, a factor that is believed to facilitate theory-of-mind
performance through enhanced attention control and inhibition rather than conceptual
mental state understanding per se (Bialystok & Senman, 2004; Kovács, 2009). By including
executive function in our models, we also controlled the potential confounding effect of
bilingualism. Cantonese was the main mode of instruction in Hong Kong local schools, in
contrast to English in Hong Kong international schools. Among other differences, the two
languages differ in syntactical complement, which is hypothesized to affect theory-of-mind
development (de Villiers & de Villiers, 2000). However, findings from a cross-lingual
study (Cheung et al., 2004) suggest that syntax of complement per se does not contribute
to theory-of-mind development; rather, it is the general language comprehension that
matters. Our study contributes to the ongoing debate about the cultural universality
versus specificity of theory-of-mind development by suggesting that it is not prudent to
attribute cross-cultural differences in theory-of-mind development to a global
individualist versus collectivist cultural distinction. Children’s direct social
environments, their micro systems in Bronfenbrenner’s (1977) terms, might play a more
important role in shaping the diverse paths of their theory-of-mind development. The
pedagogical experience hypothesis offers a more specific mechanism accounting for
individual differences in theory of mind and highlights the importance of the quality of
education in social understanding development. However, further longitudinal and
intervention studies are necessary to establish a causal relation between pedagogical
experiences and theory-of-mind development. The strong correlation between theory of mind
with low executive demands and executive function in both samples extends Devine and
Hughes’s (2014) meta-analytic finding regarding the association between these two
constructs during early childhood into middle childhood. The universality of the relation
across an extended period in development and across cultures provides a basis for
understanding the nature of the relation between these constructs. Hong Kong children’s
advantage in executive function and concurrent disadvantage in theory of mind during
middle childhood resonate with an earlier report of a similar inconsistency during early
childhood (Sabbagh et al., 2006). This finding challenges a simple “expression” account
and supports an “emergence” account of the relation between theory of mind and executive
function. Viewed alongside the results from a meta-analysis of longitudinal data (Devine &
Hughes, 2014), our cross-cultural data indicate that during middle childhood, just as
during the preschool years, executive function facilitates (but is distinct from) theory
of mind.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

The two samples were originally recruited for different studies. Sample 1 was slightly
older than Sample 2, and the children in the two samples completed slightly different
tasks. Therefore, it is challenging to compare Hong Kong international school students
with the local school students directly. Future studies are needed to explore the
individual differences in mental state understanding among different populations within
Hong Kong. Another potential limitation in our study is that there were socioeconomic
status contrasts between the different samples. Compared with the Hong Kong pupils at
local schools in Sample 2, the Hong Kong international school participants in Sample 1
were from more affluent families. Within Sample 2, the Hong Kong participants were from
less affluent households with less educated parents when compared with their British
counterparts. We statistically controlled for these variables in all of the models to
account for these differences. It is worth noting that, with respect to parental
education, Sample 2 was representative of the respective populations. In comparison with
the 30% to 50% of employed U.K. adults who have higher education qualifications (Higher
Education Statistics Agency, 2013), higher education in Hong Kong is available for only
approximately 20% of the population (Hong Kong Education Bureau, n.d.). This contrast
supports the ecological validity of any conclusions drawn from these samples.

<hs>  Conclusion</hs>
  ~~~~~~~~~~

This study is the first East versus West comparison of theory of mind and executive
function during middle childhood. By expanding the age range to the much neglected period
of middle childhood, our study adds valuable evidence on theory-of-mind use during this
stage of development. Building on the well-documented delay in Hong Kong preschoolers’
theory-of-mind acquisition, our study demonstrated, for the first time, the similarities
and differences in mental state understanding beyond early childhood in children in Hong
Kong when compared with children in the United Kingdom. Specifically, the contrast between
children in Hong Kong attending local schools and those attending international schools
carries important educational implications. Our study found that children in Hong Kong
attending local (but not international) schools showed a delay in theory-of-mind
development compared with their British counterparts. In contrast, both groups of children
from Hong Kong outperformed the British children on executive function measures. These
results highlight the potential cost of drilling and rote learning (the dominant model in
local Hong Kong schools) for children’s understanding of others. Our study also extends
earlier reports on the association between theory of mind and executive function of
preschoolers to middle childhood and demonstrates that, despite a clear advantage on
executive function tasks, children in Hong Kong do not outperform their British
counterparts on tests of theory of mind. This dissociation suggests an interesting
contrast in the salience of social influences on executive function and theory of mind
that deserves further examination in future studies.


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<ART>Through babies’ eyes: Practical and theoretical considerations of using wearable technology to measure parent–infant behaviour from the mothers’ and infants’ view points
================================================================================

Authors: R. Lee, A. Skinner, M. H. Bornstein, A. N. Radford, A. Campbell, K. Graham, R. M. Pearson
DOI: 10.1016/j.infbeh.2017.02.006
Year: 2017  |  Pages: 62-71
ASJC codes: 3204
Keywords: Behaviour, Camera, Demand characteristics, Dyadic interaction, First person view, Wearable

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Aims To explore the utility of first-person viewpoint cameras at home, for recording mother and infant behaviour, and for reducing problems associated with participant reactivity, which represent a fundamental bias in observational research. Methods We compared footage recording the same play interactions from a traditional third-person point of view (3rd PC) and using cameras worn on headbands (first-person cameras [1st PCs]) to record first-person points of view of mother and infant simultaneously. In addition, we left the dyads alone with the 1st PCs for a number of days to record natural mother–child behaviour at home. Fifteen mothers with infants (3–12 months of age) provided a total of 14 h of footage at home alone with the 1st PCs. Results Codings of maternal behaviour from footage of the same scenario captured from 1st PCs and 3rd PCs showed high concordance (kappa >0.8). Footage captured by the 1st PCs also showed strong inter-rater reliability (kappa = 0.9). Data from 1st PCs during sessions recorded alone at home captured more ‘negative’ maternal behaviours per min than observations using 1st PCs whilst a researcher was present (mean difference = 0.90 (95% CI 0.5–1.2, p < 0.001 representing 1.5 SDs). Conclusion 1st PCs offer a number of practical advantages and can reliably record maternal and infant behaviour. This approach can also record a higher frequency of less socially desirable maternal behaviours. It is unclear whether this difference is due to lack of need of the presence of researcher or the increased duration of recordings. This finding is potentially important for research questions aiming to capture more ecologically valid behaviours and reduce demand characteristics.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Variations in mother–infant interactions have a substantial impact on offspring health and
functioning in later life. Non-human animal studies have demonstrated stable and enduring
changes in the brain as the outcome of variations in maternal behaviour, even in cross-
fostering studies which eliminate the influence of genetic transmission (Francis, Diorio,
Liu, & Meaney, 1999). A recent human study also demonstrates associations between
variation in parenting within the normative ranges and infant brain development (Bernier,
Calkins, & Bell, 2016). Experimental manipulations in human mothers further demonstrate
the causal role of maternal behaviour on infant and child development. The still-face
procedure (Cohn & Tronick, 1983), where the mother is instructed to behave temporarily in
a disengaged manner (blank face and non-response) results in immediate infant distress. In
addition, manipulation of contingency of maternal verbalisations (either responding to
infant vocalisations within an appropriate time frame or not) leads to changes in infant
vocalisations (Goldstein, Schwade, & Bornstein, 2009). Longitudinal studies, which have
measured maternal behaviour, also highlight associations between variations in maternal
behaviour and longer-term emotional, behavioural, and cognitive outcomes in children
(Bornstein, Arterberry, & Lamb, 2014). However, many questions regarding the long-term
impact of variations in maternal response remain unanswered. The first step is
ecologically valid measurement of parental behaviour, and this is the focus of the current
paper. Measurement of maternal behaviour, in large longitudinal studies or randomised
control trials investigating parenting interventions, is essential to understanding
parental behaviour and its effects. The accepted gold standard for measuring mother–child
interactions is generally to have a researcher observe or film an interaction between
mother and child in a clinical, research, or home setting and film from this third person
point of view (3rd PC). There are several limitations to this approach, however: 1. Demand
characteristics or reactivity Observation from a third, often unknown party (the
researcher) is undeniably intrusive (Heisenberg, 1927). In observational study, the
presence of a videographer may represent a kind of novelty that evokes atypical responses
from those observed; this phenomenon is termed “reactivity” or ‘demand characteristics’.
Observation may promote socially desirable or appropriate behaviours and suppress socially
undesirable or inappropriate behaviours (e.g., adults may display higher rates of positive
interactions with children; Baum, Forehand, & Zegiob, 1979; Zegiob, Arnold, & Forehand,
1975). This result may be differential according to different maternal characteristics;
that is, some mothers may behave more positively, whilst others may become self-conscious
and thus behave less positively (Weber & Cook, 1972). 2. False representation of the
infant's experiences Generally, if maternal behaviour is coded from the viewpoint of an
observer (3rd PC), what is coded is what the observer sees and not necessarily what the
infant or mother experiences. From the point of view of developmental research, however,
the ideal is to capture the infant's or mother's experience. For example, a mother smiling
at her baby while the baby is looking at the floor differs from when the infant actually
sees the smile. Whilst in both cases the intent may be the same and the smile is an act of
warmth by the mother, from the infant's point of view the maternal behaviour is unlikely
to influence the child if the child misses it. 3. Participant and researcher burden Due to
demands on participant and researcher time, observations are usually of short duration and
therefore only provide a snapshot of the mother–child relationship.

<hs>  Current study: first-person viewpoint</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

First person cameras (1st PC) are small portable cameras worn by the participant facing
outward to capture the view point of the individual. A few recent studies have used 1st
PCs, worn on head bands in an effort to capture the viewpoint of mothers and infants.
Bornstein and Arterberry (2010), for example, used infant and mother worn 1st PC to record
and compare the world from infant versus adult perspectives. Yurovsky, Smith, and Yu
(2013) also used this technique to assess how infant's co-ordinate attention with a visual
partner and highlight the different viewpoints of babies as compared to adults. For
example, a child's view largely consists of a single dominating object compared to a
mother's wider perspective. Sugden, Mohamed-Ali, and Moulson (2014) also used 1st PCs worn
by infants for a number of hours at home, in order to measure the infant's exposure to
adult faces Using 1st PCs offers many practical and research advantages that address the
three shortcomings listed above. They: (1) eliminate the need for a researcher to be
present, reducing potential influences of the researcher on mother and infant behaviour;
(2) record the viewpoints of each interactant, so different perspectives are captured; and
(3) diminish participant burden by removing the need to attend or host a research visit.
So far, however, these studies have only measured the viewpoint of one-half of the dyad
and therefore miss the combined footage. In the present paper, we explore and evaluate the
gains and limits of using 1st PCs simultaneously worn both mother and infant. We evaluate
how well 1st PCs capture relevant information via video and audio data-collection
functions, we describe the reliability of existing coding systems that could be used on
data captured by 1st PCs, and we explore 1st PCs ability to attain the 3 advantages
described above. We first investigated whether two independent raters show reliability
when coding behaviours from video footage from 1st PCs alone. This would mean that the
recorded footage from 1st PCs alone is of adequate quality that it can be reliably coded
as the same event by two different coders. We next explored whether the 1st PC reduced the
role of participant reactivity (advantage number 1). We hypothesise that removing the
researcher and allowing a longer duration will reduce reactivity and demand
characteristics thereby reducing a fundamental bias in observational psychological
research. We predict that, for mothers and infants left alone with the 1st PCs without the
researcher present over a number of days, there will be a more negative in the types of
behaviours recorded as compared to interactions recorded by the 1st PC but with a
researcher present. For this comparison we keep the camera view point constant but vary
the presence of a researcher. We specifically hypothesise that we will see a greater
frequency of less socially desirable maternal behaviours, such as distracted and critical
responses. We finally explored the potential advantage of recording from the infants’ view
point (advantage number 2) by documenting the concordance of behavioural coding of footage
from 1st PCs with footage from 3rd PCs, when recording the same interaction and varying
only the camera view point. High concordance would mean that the majority of the same
information is picked up by both viewpoints and is interpreted in the same way by coders.
Low concordance could indicate that one of the recording methods picks up unique (and
potentially important) information. We explored sources of differential concordance to
understand information that is potentially lost or gained from using the different
viewpoints.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Mothers with infants between 3 and 12 months of age were recruited using email
advertisements within the University of Bristol School of Social and Community Medicine
social life email list to Staff (academic and admin) and PhD students. Fifteen
participants were recruited. Mean maternal age was 32.3 years (SD = 4.7), and mean age of
infants was 8 months (SD = 2.4). All mothers were married or cohabiting and had high
levels of education (at least one degree); all but one participant was Caucasian.

<hs>  Procedures</hs>
  ~~~~~~~~~~

Infants were placed on a play mat with a selection of the same set of age-appropriate
small, soft, and plastic toys, and mothers were asked to play with their infants as they
would normally. Mothers and infants were filmed by a researcher, and both wore 1st PCs
that recorded play during this time (see materials). The observation lasted 11 min. The
researcher then instructed the mother how to record with and charge the 1st PCs, and asked
mothers to use them during a variety of play times, meal times, and bed times in the
coming days. The researcher left the 1st PCs with the mothers for an average of 1 week
depending on the participant's availability. Participants were asked to record at least
three 30-min sessions. Mothers were given a packet with instructions on how to use the 1st
PCs, a session diary to record when they had filmed sessions, and a questionnaire about
how they found using the 1st PCs (see Appendix). Finally, mothers were asked to complete a
standard demographic questionnaire to provide information on highest educational level,
occupation, age, number of children, and current feeding method.

<hs>  Materials</hs>
  ~~~~~~~~~

We captured video and audio footage of mother–infant interactions using low-cost, head-
worn cameras that have previously been used for recording infant's eye views of their
environment (Sugden et al., 2014). The particular 1st PC we used was a ‘Bogdan Digital Spy
Hidden Camera DVR Video Recorder’, at a cost of approximately £20 per camera, plus £5 for
an SD storage card for each camera. The 1st PCs record video and audio in AVI format.
Video has a resolution of 720 × 480 at 30 frames/s. No specification is provided for audio
bitrate or sampling rate. 1st PCs store video on an SD card of up to 16 GB capacity or
approximately 1 h of video and audio. The 1st PC has an internal Li-Ion battery, which
gives approximately 2 h of battery life. 1st PCs are marketed as novelty spy cameras in
the form of lapel badges and are yellow in colour with a black smiley face. To reduce the
probability of the infant's gaze being unduly attracted to a brightly coloured 1st PC
attached to the mother, we coloured them black. To attach the 1st PCs to the head of the
mother and infant, they were sewn into elastic headbands. Footage from the two 1st PCs
(mother and infant) was synchronised in time according to an early common event in both
cameras and then joined using light works video editing software. The combined footage was
then coded as below (see Fig. 1 for an example of combined footage).

<hs>  Coding</hs>
  ~~~~~~

Observations were coded using Noldus Observer XT software to categorise each maternal
behaviour (event-based coding), using existing, published operational codes of basic
maternal behaviour and infant affect (Leerkes, 2010). Mother codes were mutually
exclusive, so at any one time point mothers can only be coded in one category. The codes
are also exhaustive, so every maternal event is coded, and the duration of this code was
automatically recorded. The coding categories were comforting, engagement, encouragement,
positive affect, monitoring, routine care, distracted, critical, mismatched affect,
persistent ineffective, and intrusive. Full description is available from Leerkes (2010),
and we provide a brief description of each code here:

<hs>  Positive maternal behaviours</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Comforting: involves any maternal behaviour that will make the infant feel more at ease,
such as hugging. Engagement: is when a mother directs her actions towards the infant (e.g.
talking to the infant). Encouragement: consists of any maternal action that is associated
with spurring the infant on. Positive affect: is the display of any positive emotion which
is not part of one of the other codes (such as comforting), so for example the mother's
comforting her child whilst smiling is coded as comforting, as the primary action relates
to the objective to comfort; likewise if the positive emotion is primarily used to
encourage, then it is coded as encourage.

<hs>  Neutral maternal behaviours</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Monitoring: this involves the mother watching the infant but not being actively involved.
Routine care: this category encompasses acts such as cleaning the infant or adjusting
clothes.

<hs>  Negative maternal behaviours</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Distracted: the mother is neither engaged with nor monitoring the infant, and may be
looking away or involved in a separate activity. Critical: is any maternal behaviour that
involves directing negativity towards the infant. Mismatched affect: is when the mother
laughs or smiles when the infant is distressed, wary, and nervous, etc. (does not include
attempts to distract or reassure the infant while engaging, supporting or calming). May
also include contradicting or denying infant's emotional or behavioural reaction (e.g.,
“you’re not scared” or “that's not scary” or “it's funny” in matter-of-fact, firm tone if
infant is distressed). The coding specifies that if mismatched affect occurs it should be
coded rather than any other behaviour with which it potentially co-occurs. Persistent
ineffective: this behaviour involves the mother repeating a behaviour despite the fact
that her behaviour does not have a positive influence on the infant's emotional state.
Intrusive behaviour: is when the mother's actions conflict with the infant's desired
outcome, so for example preventing the infant from getting a toy reached for. In the
coding manual clear guidance is provided regarding which code to prioritise if two codes
co-occur and in which situations to score which code. We used event-based, continuous
coding. So, the mother's behaviour would be coded into one of the categories described
above The duration of this behaviour would then be recorded in the software until a new
behaviour is recorded The video was first coded for maternal behaviours and then
separately for infant affect (happy, neutral, or distressed) again with operationalised
codes for infant emotion based on Leerkes (2010). Therefore, for each period of time, a
code for maternal and infant affect is recorded. Coders were trained and supervised by RP,
two coders were psychology final year placement students (AC and RL) and a final coder was
a psychiatrist (KG). A series of training coding sessions to reach reliability of >80% on
standard 3PCs was conducted before coding the headcam videos.

        <hss>Inter-method recording concordance on the same observation</hss>

        Inter-method reliability was calculated using the 1st PC and 3rd PC footage of the
        same play observation with the researcher present for all 14 dyads (thus 14 pairs
        of videos). For each the 1st PC and 3rd PC coding were paired, and overall
        reliability calculated (in The Observer XT 11). As we were interested in the
        amount of each behaviour as well as the order in which behaviours occurred, the
        duration/sequence calculation was used with a tolerance window of 2 s (Jansen,
        Wiertz, Meyer, & Noldus, 2003). For this comparison we used codings from the same
        coder to ensure that differences between coders did not account for differences
        between the coding from the different recording methods. As described below, we
        also ensured that 1st PCs were reliably coded by an independent coder who had not
        seen the 3rd PC footage.

        <hss>Inter-rater reliability of coding the 1st PCs</hss>

        Given the time intensive nature of coding, it is standard practice to only double
        code only a proportion (10–20%) of videos for reliability (Nicol-Harper, Harvey, &
        Stein, 2007; Zosuls et al., 2009). A random sample of 20% (11 of 56 1st PCs
        observations, as each participant gave multiple 1st PC observations) of all 1st
        PCs were also coded by an independent trained coder who was blind to the
        hypotheses of the study and who had not seen the 3rd PCs. Reliability between the
        same 1st PC codings from the two raters was compared in Observer using the same
        method as described for inter-method reliability.

        Comparing frequencies of maternal behaviours within participants but across recording methods

        Descriptive statistics were evaluated to provide summaries of coding parameters
        across video recording method. Due to the small sample and proof-of-concept nature
        of the study, we were not powered to conduct multiple comparisons. We therefore
        focus on key hypothesised comparisons and use paired t-tests to test specific
        comparisons between rates of less sensitive behaviours during interactions with
        and without a researcher present.

<hs>  Number of free sessions recorded</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Across the 15 mother–infant dyads, 56 free session videos were recorded for total of 14 h
of these free sessions. The videos were a mean of 20 min and 12 s long, and each dyad
conducted 1–5 sessions. All sessions were recorded during meal times or free play.

<hs>  Inter-method concordance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

Overall concordance was measured for 14 pairs of 1st PC and 3rd PC videos filming the same
situation. The range for the index of concordance was 0.84–0.98, with an average of 0.90.
Kappa values fell between 0.78 and 0.98, the mean being 0.89.

<hs>  Inter-rater reliability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Twenty percent (11) of the 1st PC videos were randomly selected and coded by independent
researcher (who did not see the 3rd PC videos) to measure inter-rater reliability of the
1st PCs. The index of concordance from these calculations ranged from 0.78 to 0.98, with a
mean of 0.91. The more conservative kappa values ranged from 0.75 to 0.97, with a mean of
0.90. A second analysis was conducted in which behaviour modifiers (intensity of the
behaviour: as well as showing infant distress, which the coder qualified as mild,
moderate, or intense) were included, resulting in a more granular measure of behaviours.
Even in this case, the index of concordance ranged from 0.76 to 0.98, with a mean of 0.90,
and the kappa values fell between 0.74 and 0.97, with a mean of 0.89.

<hs>  Descriptive investigation of non-concordant responses between 1st PC and 3rd PC</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Whilst the concordance of the footage from different viewpoints was high, it was not
perfect and it is important to establish the nature of prominent discrepancies. Due to the
time intensity of this in-depth analysis, a randomly selected sample 9 of the 14 pairs
(64%) of 1st PC and 3rd PC videos were selected, and discrepancies between their codes
(made by same coder originally) were examined by a third independent rater to understand
the nature of information lost or gained from 1st PCs. A total of 178 events that were
coded differently from the different view-points were found from pairs (as demonstrated
from the high concordance reported above, this is a small proportion of all events), and
researchers categorised the nature of differences according to whether the
behaviour/action related to the code was visible from both viewpoints (3rd PC, and mother
and infant 1st PC combined) and to what extent, as well as more descriptive analysis of
the likely cause of different coding. Discrepancies consisted of differences in coding
behaviours/actions viewed by both cameras (so likely a coding disagreement),
actions/behaviours observed only on 1st PCs, and actions/behaviours observed only by 3rd
PCs. We discuss the nature of these different discrepancies below. Approximately one-third
(35%) of differences were behaviours/events that were identified on both cameras but coded
differently. Thirty-five percent of these discrepancies were due to coding differences
despite the action being clear from both viewpoints. However, the majority of miscoded
actions potentially resulted from the different points of view offered by the 1st PC and
3rd PC. For example, the behaviours that were most often differently classified were
‘monitoring’ and ‘engagement’, as the level of engagement of mothers was potentially
assessed differently when different viewpoints were taken. Monitoring was usually coded
from the 3rd PC and not coded from the 1st PC because the whole body of the mother was
visible to the 3rd PC and thus her posture and direction of gaze were much clearer from
3rd PC. Approximately one-half (48%) of the differences were actions that were picked up
on the 3rd PCs, but missed on the 1st PCs. These actions were typically whole-body
movements. For example, mothers picking up their infants, or infants flapping their arms
were generally missed by the 1st PC. On one occasion, for example, a mother was silent on
the 1st PC recording and no other changes in behaviour were visible. However, the 3rd PC
recording showed that the mother was handing the infant a toy and maintaining eye contact.
Behaviours that were picked up by the 1st PCs, but missed by the 3rd PCs accounted for
about one-fifth (16%) of the discrepancies. Generally, the sound quality of 1st PCs was
superior to that of the 3rd PCs as 1st PCs were closer to the mouths of the participants.
Sounds such as whispering, which could not be heard on the 3rd PC were recorded by the 1st
PC. Also, as 1st PCs were focused directly on participants’ faces, facial expressions that
were often missed by 3rd PC were visible on 1st PCs. In the majority of cases in this
initial work, 1st PCs were not optimally placed by participants, meaning that many facial
expressions and other actions may not have been coded. Thus, the 16% is likely to increase
with better positioning of cameras. As technology improves and cameras become smaller and
less intrusive, more actions that would be missed by a 3rd PC should be easily identified
on 1st PCs.

<hs>  Performance of the cameras</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

Many aspects of the 1st PCs’ performance were perfectly adequate to the task. The video
quality, while not high definition, can discern facial expressions, eye gaze, and general
facial and body movements and responses. Likewise, the audio quality is good enough to
record speech. Many shortcomings will be rectified with new and developing technologies.
The novelty, low-cost nature of the device means that some aspects of their performance
and functionality were sub-optimal. The field of view (which we estimate to be about 60°)
for one interactant was often too narrow to fully capture the partner interactant. The
usability of the device was poor, with operations (e.g., switching on and off, and
starting and stopping recording) controlled by unintuitive combinations of buttons
presses.

<hs>  Overall behaviours from different recording methods</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

As can be seen in Table 1, the 3rd PC picked up more positive and neutral behaviours per
min than the 1st PCs when recording the same interaction. The 3rd PC also picked up more
maternal behaviours across the categories than the 1st PCs, when viewing the same
interaction. However, the 1st PCs picked up more infant distress perhaps because of the
superior audio and close facial recording of 1st PC as described above. Given that infant
distress is most commonly expressed in crying vocalisations and clear facial expressions,
1st PCs may have greater potential to pick up these subtle displays. During the free
sessions, 1st PCs picked up significantly more insensitive behaviours, such as intrusive
or distracted maternal behaviour, per min than the 1st PCs while the researcher was
present (paired t-test: t14 = 5.6, p < 0.001; mean difference = 0.90, 95% CI = 0.5–1.2).
This difference represents an approximately 1.5 SD increase in such behaviours between the
sessions with a researcher present and during the free sessions.

<hs>  Summary of key results</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

1st PCs recorded information that resulted in similar overall coding on a relatively
simple mother–infant coding system to that recorded from 3rd PC. As predicted, once the
researcher was not present, the videos contained less sensitive maternal behaviour.
Although only a small pilot sample, even in this highly educated low-risk group the
differences were of a potentially large size (approximately 1.5 SD higher rates per min of
less sensitive behaviour). We do not know if this difference was due to the lack of
researcher or different scenarios chosen by the mother when using the 1st PC, but either
way, following the protocol here we observe a more negative maternal behaviours. We see
fewer behaviours from the 1st PC compared to the 3rd PC, as indicated from the rate per
min of maternal behaviours (see Table 1). Two possible explanations present themselves:
The restricted camera angle means that 1st PCs miss maternal behaviours that are actually
experienced by the infant or 3rd PCs record maternal behaviours not actually seen by the
infant. Our descriptive analyses of the different codings suggest that the former may be
more accurate. However, some behaviours (such as infant distress) were often picked up
only by 1st PCs (see later).

<hs>  Advantages of 1st PC</hs>
  ~~~~~~~~~~~~~~~~~~~~

The first advantage relates to reduction in participant reactivity and demand
characteristics. Even in this relatively homogenous sample of educated mothers, a
substantial difference emerged in the amount of insensitive maternal behaviours over a
number of interactions using 1st PCs at home alone than in a one-off researcher present
setting, ether with 1st or 3rd PCs. Based on the assumption that mothers are more likely
to display more behaviours that are socially considered ‘negative’ parenting when demand
characteristics are reduced, the finding of increased negative parenting, provides
preliminary evidence for reduced demand characteristics. Demand characteristics may be
especially high in educated mothers due to knowledge of research and ‘best parenting’.
This potential bias poses a real challenge to measurement of parents’ behaviour, in which
consistent associations are made between maternal education levels and observed parenting
(see Bornstein, 2015). Our results are consistent with a study demonstrating that a more
extreme ‘negative’ maternal behaviour of corporal punishment is recorded more frequently
by using passive audio recording in the home than reported frequency from mothers (Holden,
Williamson, & Holland, 2014). There are, therefore, a number of ways in which 1st PCs
could lead to reduced demand characteristics. It may because no researcher is physically
present, or could result from longer duration of recording. In addition, while the mother
is of course still aware that she is being recorded it may be easier to ignore or forget
about a camera than the physical presence of a researcher. In addition infants are highly
unlikely to be aware that their behaviours will be viewed by someone else while wearing
the head cams, and this differs from situations when a researcher is present because
infants may be aware of the presence of someone other than their mother, and thus ‘react’.
In addition the 1st PC allows a longer duration for the mothers to relax and forget that
they are being recorded. Briefer observations can be unstable, and observations lasting
longer than an hour are likely to include samples of behaviours from highly varied
activities or contexts, thus being more varied themselves (Miller, Shim, & Holden, 1998).
It is important to point out that the advantage of reduced demand characteristics is not
specific to 1st PC but the home alone setting and other methods (such as stationary
cameras in houses) may also offer this advantage and result in more negative behaviours
being captured. Secondly, 1st PCS were better able to capture subtle facial expressions
and vocalisations. Assuming 1st PCs are placed at the optimal position (i.e., at the
glabella between the participants’ eyebrows), there was also evidence of advantage 2 (view
point of the infant). First, the ranges of behaviours that can be captured using a 1st PC
differ to those visible on a 3rd PC. Subtle facial expressions and facial expressions that
would otherwise be missed due to the 3rd PC camera angles can be recorded on 1st PCs
(e.g., Baby FACS; Oster, 2005). Subtle sounds can also be recorded more intelligibly by
1st PCs because their cameras’ microphones are much closer to the face than are 3rd PCs
microphones. The viewpoints offered by 1st PCs are unique and possibly more naturalistic,
as the visual angle is that of the first person. Thirdly, the cameras used here have the
advantage of reduced costs associated with researcher's time. 1st PCs are less demanding
on research time than 3rd PCs as they can be left with participants to record themselves
rather than hosting a researcher and associated costs of researcher time and travel.

<hs>  Challenges</hs>
  ~~~~~~~~~~

Although there are a number of advantages associated with the use of 1st PCs, there are
also some challenges. One relates to placement. In practice, many participants did not
place their 1st PCs completely optimally, meaning that many advantages of 1st PC were not
fully achieved. Over the course of our pilot, we found that instructing mothers to check
the position of 1st PCs in the mirror was key to optimally positioning the head camera.
However, even when the camera is placed correctly, the visual field offered by current 1st
PCs is restricted, and many whole-body movements are consequently missed. Also, to record
facial expressions, two participants must wear the cameras and face one another.

        <hss>Evaluation of interventions</hss>

        Reducing demand characteristics and reactivity may be particularly important in
        evaluating parenting interventions. Many evaluations of parenting interventions
        involve filming mothers during free-play sessions, in the presence of a
        researcher, using a 3rd PC. However, these interventions explicitly focus on
        teaching parents to implement certain behaviours in certain situations. There is a
        possibility that mothers ‘perform’ these learnt behaviours when being filmed by
        members of the same study team who delivered the intervention (even if they are
        different researchers they may be seen as connected), and this circumstance is
        highly likely to introduce bias. Using the 1st PCs, researchers can help reduce
        this bias through removing the researchers’ presence and increasing duration of
        recordings which is key in accurate evaluation.

        <hss>Large cohort studies or resource limited studies</hss>

        Given the low cost and reduced researcher time needed, 1st Pcs may be useful for
        the large-scale recording of mother–infant behaviour in large epidemiological
        cohort studies which collect multiple measures and aim to reduce participant
        burden and save costs. Indeed, the 1st PC are currently being piloted in a large
        UK cohort ALSPAC, see https://proposals.epi.bristol.ac.uk/?q=node/113441.

        <hss>Studies focused on facial expressions</hss>

        Studies interested in facial expressions specifically may benefit from the use of
        head cameras which capture them well.

        <hss>Studies interested in infant view point</hss>

        Researchers interested in understanding aspects of the environment that infants
        and mothers focus on. Many of the abilities that are thought of as automatic in
        adults are learned early in life, meaning that infants are challenged by processes
        that are simple for more experienced individuals and therefore they will focus on
        different aspects of their environment. For example, the ability to conceptualise
        and categorise objects improves with experience (Oakes & Madole, 2003), which
        infants initially find difficult. This means that infants are more likely to focus
        on objects in their environment (Bornstein & Arterberry, 2010). Therefore,
        infants’ viewpoints, and consequently information processing, could differ greatly
        from that of their adult counterparts. With 1st PCs, researchers will have access
        to more accurate representations of both infant and adult viewpoints, leading to
        more informed inferences about infant experiences.

        <hss>Use in video-feedback interventions</hss>

        In the specific mother–infant context, another possible application of 1st PCs is
        facilitating video feedback interventions, which have previously been shown to be
        effective in improving maternal sensitivity in a range of populations, including
        adolescent mothers, mothers with schizophrenia, and mothers with poor attachment
        styles (Bakermans-Kranenburg, van, & Juffer, 2003; Cassibba et al., 2015 Cassibba,
        Castoro, Costantino, Sette, & Van Ijzendoorn, 2015; Kalinauskiene et al., 2009;
        Reddy et al., 2014). This therapeutic approach consists of video feedback
        intervention sessions in which mothers are recorded interacting with their infants
        in a naturalistic free-play session. These recordings are then discussed with a
        mental health professional, and mothers are encouraged to observe their own
        sensitive and insensitive behaviours, thereby improving their observational skills
        and empathy. Any sensitive behaviours displayed by the mother are supported and
        are used as examples to contrast with instances in which insensitive behaviours
        are displayed. This means that each mother acts as her own model. A key focus of
        video feedback is ‘mind-mindedness’, referring to a mother's ability to see the
        world from her baby's view point and thus respond to the baby's emotional needs
        (Meins, 1997). 1st PCs would be particularly useful in facilitating mind-
        mindedness as the infant's actual viewpoint would be captured, and mothers may be
        better able to understand their infant's world and their infant's perceptions of
        that world. In addition the mother can reflect on her own responses more easily
        when viewing the situation from her own view point. This process – known as “self-
        entheaty” or observing one's actions on record – may be particularly beneficial in
        a therapeutic sense because psychological and behavioural-change programmes rely
        heavily on introspection. As Lahlou (2011) brings to light, introspection is not
        easy, and when we do introspect we change the very cognitions we are hoping to
        describe. Subjective Evidence-Based Ethnography (SEBE; Lahlou, 2011) allows
        patients to view their 1st PC data after collection and engaging with the task, in
        an attempt to examine cognitions after the act. In this way, individuals can avoid
        the problem of modifying cognition with introspection and gain increased insight
        by experiencing something and learning independently, as opposed to didactically.

        <hss>Studies interested in global environment and whole body</hss>

        If more precise and whole-body movements are of key importance, 1st PCs may not be
        recommended because these behaviours were often missed by 1st PC. Rather cameras
        in rooms (but without researchers present) could be used alongside the 1st PC to
        capture whole body movements such as touching or assessing the positioning and
        proximity of the mother and child. Furthermore, 1st PCs can provide important
        information regarding the location of dyads within a room. In addition studies
        interested in multiple participants, such as those including fathers and siblings,
        may need to include the wider footage captured from 3rd PCs placed in homes.

<hs>  Future directions</hs>
  ~~~~~~~~~~~~~~~~~

There is considerable interest in on-body camera technology from a variety of domains.
Police officers in a number of regions of the United Kingdom and United States are
routinely being issued body cameras for recording their interactions with the public.
Social care workers in some areas use on-body cameras for similar purposes, providing
visual and audio records of meetings with service users. The market sector driving the
biggest changes in on-body camera technology is the domestic desire for wearable action
cameras. Manufacturers such as GoPro are bringing devices to market that are smaller,
lighter, have wider fields of view, higher definition video, longer battery life, and
increased flexibility in streaming and storing captured footage to other devices and
networks. These improvements mean that a number of devices coming to market will be better
suited to on-body video and audio recording of interactions in dyads for psychological
research. Future studies of the kind reported here will undoubtedly benefit from these
technological improvements, in particular, wider field of view, greater ease of use,
longer battery life, greater storage capacity, and ease of video/audio data transfer.

<h>CONCLUSION</h>
----------

The high level of concordance between 1st PC and 3rd PC videos of the same situation
demonstrates that 1st PCs capture a situation reliably. Some elements of these situations,
such as whole-body movements, are missed by 1st PCs because of the relatively small field
of vision of the 1st PC. Despite the fact that the audio and visual quality of 1st PCs are
at this point still sub-optimal, they capture subtle sounds and facial expressions that
may be missed by 3rd PCs. As new technology emerges and cameras with better visual and
audio quality and wider fields of vision come onto the market, the performance of 1st PCs
should improve. Another potentially important (if preliminary) finding, associated
uniquely with 1st PCs, is the increase in insensitive behaviours seen in mothers when they
were left alone with 1st PCs. This result suggests that researchers are highly likely to
capture an unrepresentative picture of maternal behaviour if researchers are present, even
in the home setting. The other main advantages of using 1st PCs are their ease of use, low
cost, and the relatively small participant and researcher burden. Future directions may
include the use of 1st PCs in video feedback interventions and in developmental and
psychological research.


<h>REFERENCES</h>
----------

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<ART>Training novice practitioners to reliably report their meditation experience using shared phenomenological dimensions
================================================================================

Authors: Oussama Abdoun, Jelle Zorn, Stefano Poletti, Enrico Fucci, Antoine Lutz
DOI: 10.1016/j.concog.2019.01.004
Year: 2019  |  Pages: 57-72
ASJC codes: 3204, 3205
Keywords: Demand characteristics, Desirable responding, First-person, Meditation, Mindfulness, Neurophenomenology, Phenomenology, Self-reports, Training

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Empirical descriptions of the phenomenology of meditation states rely on practitioners’ ability to provide accurate information on their experience. We present a meditation training protocol that was designed to equip naive participants with a theoretical background and experiential knowledge that would enable them to share their experience. Subsequently, novices carried on with daily practice during several weeks before participating in experiments. Using a neurophenomenological experiment designed to explore two different meditation states (focused attention and open monitoring), we found that self-reported phenomenological ratings (i) were sensitive to meditation states, (ii) reflected meditation dose and fatigue effects, and (iii) correlated with behavioral measures (variability of response time). Each of these effects was better predicted by features of participants’ daily practice than by desirable responding. Our results provide evidence that novice practitioners can reliably report their experience along phenomenological dimensions and warrant the future investigation of this training protocol with a longitudinal design.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

This article aims to describe a meditation training protocol developed in the context of
an empirical brain imaging, cross-sectional study that investigates the mechanisms of
mindfulness and compassion meditations. The novelty of this protocol is to obtain a
meditation active control group by training healthy, naive participants to verbally
express their subjective experience of meditation practice using a multidimensional
phenomenological space (Lutz, Jha, Dunne, & Saron, 2015). Phenomenological space refers
here to the description of features of the field of experience, as it is lived and
verbally expressed in the first person (e.g., Husserl, 1991). This phenomenological matrix
has been recently proposed as a framework to map different styles and levels of training
in mindfulness, as well as heuristic tool to generate hypotheses for empirical research.
The Brain & Mindfulness project attempts to practically apply this theoretical framework
(for the study manual, see Abdoun, Zorn, Fucci, Perraud, Aarts, & Lutz, 2018). During the
training participants were introduced to various styles of meditation practices and
acquainted with phenomenological categories through various experiential exercises. These
phenomenological dimensions were then investigated at neural, behavioral and physiological
levels during the various cognitive and affective experimental paradigms. Such explicit
use of first-person data to guide the analysis of third-person data is inspired by
Francisco Varela’s research program of neurophenomenology (Lutz & Thompson, 2003; Varela,
1996). The current training protocol attempts to pragmatically tackle three methodological
and conceptual challenges. The first one is concerned with issues regarding the definition
of mindfulness meditation in psychology and cognitive neuroscience. The second one
pertains to epistemological and methodological issues related to the integration of first-
person reports in an experimental protocol. The third one is related to the quality of
control groups for cross-sectional studies of meditation expertise.

<hs>  Theoretical context: mindfulness as a dimensional, phenomenological state</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In experimental and clinical psychology, the construct of mindfulness is generally used
with three different meanings that refer either to: (a) a mental trait or a dispositional
inclination (e.g. the Five Facet of Mindfulness proposed by Baer, Smith, Hopkins,
Krietemeyer, & Toney, 2006), (b) a soteriological or spiritual path conceived in
therapeutic and health-promotion terms (e.g. in the Mindfulness-Based-Stress-Reduction
program; Kabat-Zinn, 1982), and (c) a single cognitive process trained and potentially
brought to various human activities (e.g. like in “paying attention in a particular way:
on purpose, in the present moment, and non-judgmentally”, Kabat-Zinn, 1994, p.4; or “the
optimal interaction between attention and peripheral awareness”, Culadasa et al., 2015,
p.30). While these meanings remain useful for many contexts, they are also problematic.
Self-report questionnaires to study mindfulness as a trait lack specificity (Goldberg et
al., 2016) and may even yield contradictory findings. For instance, Leigh, Bowen, and
Marlatt (2005) found that binge drinkers’ mindfulness scores were higher than those of
participants in a mindfulness retreat. In addition, findings may be biased by social
desirability, consistency effects, or shared language between intervention instructions
and scales (see Sauer et al., 2013, Van Dam, Hobkirk, Danoff-Burg, & Earleywine, 2012).
Interpreting mindfulness as a soteriological process (meaning [b]) is often too broad to
guide empirical research. Up to this point, discussions of mindfulness as a cognitive
process (meaning [c]) make it difficult to account for differences in practice styles and
levels of expertise, while also lacking the specificity required to formulate mechanistic
hypotheses. Because these meanings are too restrictive, with C. Saron, A. Jha and J Dunne,
we have argued against formulating a single, universally applicable consensus definition
of mindfulness (Lutz et al., 2015). Instead we favor reconceiving mindfulness through a
family resemblance approach whereby it can be conceptualized as “a variety of cognitive
processes embedded in a complex postural, aspirational, and motivational context that
contribute to states that resemble one another along well-defined phenomenological
dimensions” (Lutz et al., 2015, p.633). This approach draws on previous efforts to
conceptualize mindfulness (Chambers, Gullone, & Allen, 2009; Hölzel et al., 2011; Lutz,
Slagter, Dunne, & Davidson, 2008) and the phenomenology of mindfulness practice. It is
compatible with multiple explanatory and analytical frameworks from different
subdisciplines, including contemplative theories, clinical frameworks and psychological
and neuroscientific models. This approach is guided by a pragmatic inquiry: when one is
formally practicing mindfulness, what observable and manipulable features of consciousness
are most relevant to report in an experimental setting? We identified seven features
proposed in a bipartite phenomenological model (detailed in Lutz et al., 2015 and resumed
here in Table 1). The model assumes that these dimensions of experience are dynamic and
manipulable in that they are affected—directly or indirectly—by different instructions of
practice and/or by the level of expertise. This model was used to plot the hypothetical
phenomenological characteristics of two styles of mindfulness, Focused attention (FA) and
Open monitoring (OM) meditations, for both novice and expert meditators (Lutz et al.,
2015). These plots have been created based on various instruction sets and descriptions.
They should not be taken as actual plots of any individual’s phenomenology. The same set
of mindfulness instructions could be mapped to different points in the phenomenological
space. This is due to individual differences between practitioners in the manner in which
they interpret and instantiate instructions. One aim of the Brain & Mindfulness project is
to implement this heuristic model and to empirically test some of its assumptions. For
instance, can we use self-report scales to reliably measure and monitor consistent changes
in these features in response to different meditation instructions and training, congruent
with the hypothetical plots previously published?

<hs>  Epistemological limitations: Reliability of self-report data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A second methodological aim arises from the first one: are the empirically-obtained plots
of the different styles and levels of expertise reliable in this phenomenological space?

        <hss>The reliability of self-reports</hss>

        The perceived demise of early twentieth century introspectionism (Costall, 2006)
        and the seminal review by Nisbett and Wilson (1977) questioned the ability of the
        participants to report the real causes of their behavior. Since then,
        introspective-like methods have been looked upon with distrust by many in the
        fields of psychology and cognitive science. Contrastingly, others have warned
        against drawing general conclusions from these failures. For example, Hurlburt and
        Heavey (2001) have criticized how Nisbett and Wilson’s work has been carelessly
        taken as “an unconditional refutation of introspection in general, not merely of
        the attribution of causation”, thus ignoring that “even Nisbett and Wilson
        recognized the possibility of accurate reports about inner experience” (Hurlburt &
        Heavey, 2001, p.401). Devising ways to detect and/or limit the diverse types of
        self-reports distortions is an active field of methodological research. For
        example, self-administered questionnaires have long included validity scales
        designed to this effect (Baer, Rinaldo, & Berry, 2003). More recently, there has
        been a renewed interest for ‘first-person methods’ to study consciousness (see the
        three special issues of the Journal of Consciousness Studies on this question:
        Jack and Roepstorff, 2003, 2004; Hasenkamp & Thompson, 2013). First-person methods
        refer to methods that allow an investigator to bring a participant close to their
        subjective experience1 (Petitmengin, 2006), as well as to practices that subjects
        themselves can use to increase their sensitivity to their own experiences (Bitbol
        & Petitmengin, 2013; Depraz, Varela, & Vermersch, 2003; Petitmengin, Remillieux,
        Cahour, & Carter-Thomas, 2013; Varela & Shear, 1999). Meditation training has been
        proposed as a pragmatic response to this challenge due to it's disciplined
        approach to examining experience. Approaching experience from this perspective
        allows for the refinement of first person categories' repertoire and strengthen
        the robustness of the relationship between first and third-person data (Varela,
        1996). However, this hypothesis remains to be thoroughly tested. Current available
        evidence includes the improvement of the congruence between implicit and explicit
        measures of self-views after brief mindfulness exercises (see Strick & Papies,
        2017 for a study on affiliation motives and goals, and Koole, Govorun, Cheng, &
        Gallucci, 2009 for a study on self-esteem). In contrast, measures of interoceptive
        awareness based on heartbeat perception in experienced meditators have yielded
        mixed and contradictory results (Bornemann & Singer, 2017; Khalsa et al., 2008;
        Melloni et al., 2013). The inconclusiveness of these studies may be due to a lack
        of methodological validity (Zamariola, Maurage, Luminet, & Corneille, 2018),
        discrepancies in the experimental designs and/or in the extent of bodily focus in
        participants’ meditation practice.

        <hss>Demand characteristics and desirable responding</hss>

        In the context of phenomenological research on self-induced mental states (such as
        in meditation research), demand characteristics is a major source of confound that
        undermines the credibility of self-reports. Demand characteristics refer to “the
        totality of cues which convey an experimental hypothesis to the subject[s]” and
        which consequently “become significant determinants of subjects' behavior” (Orne,
        1962, p.779). Participants volunteering for scientific experiments have various
        motivations that may, consciously or unconsciously, incite them to play the role
        of the good participant and try to serve the experiment by producing the data that
        they think will confirm the (presumed) research hypothesis. To attenuate the
        confounding effects of demand characteristics, researchers commonly resort to the
        concealment of – if not the deception about – hypotheses, manipulations, dependent
        measures and independent variables. Another source of distortion of a
        participant’s behavior is his/her wish to present herself favorably to the
        experimenter, who may be perceived as an evaluator. This so-called social
        desirability bias is related to the effect of demand characteristics, but not
        identical to it (Weber & Cook, 1972). To eliminate this confound, some researchers
        advocate the use of scales developed to capture individuals’ inclination to self-
        enhancement (Crowne & Marlowe, 1960; Paulhus, 1984), as covariates in the models
        assessing the effects of interest. In the phenomenological study of meditation,
        demand characteristics lurk in the large overlap between the semantics of
        meditation instructions taught or familiar to the participants, and the phrasing
        of self-report scales aimed at measuring the phenomenological dimensions of
        interest (e.g. terms such as present-centered and nonjudgmental, see Van Dam et
        al., 2012). Consequently, the magnitude of self-reported phenomenological features
        of meditation remain overshadowed by doubt, even when shown to be highly specific
        (see for example Kok & Singer, 2017). Unfortunately, the usual concealment
        strategies can hardly be applied in this context, considering that participants
        are necessarily aware of the manipulation in so far as they are asked to implement
        it through the practice of meditation. This is not to say that all self-report
        results from meditation studies are inexorably confounded by the effect of demand
        characteristics. Even when demand characteristics are difficult to attenuate, one
        can look for evidence that supports an interpretation of the effect beyond their
        impact. In this study, we adopt a strategy of comparing certain factors (which are
        unaffected by demand characteristics or desirable responding) with self-reporting
        effects. We will illustrate this general approach in two ways: (i) within-subject,
        by testing whether fluctuations of phenomenological self-reports correlate with
        relevant behavioral measures, and (ii) across subjects, by testing whether
        participants’ amount and structure of daily practice predict the self-reported
        effects on phenomenological dimensions.

<hs>  Methodological issue: quality active control group</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A critical effort of the Brain & Mindfulness project was to refine the matching between
the control group and expert meditators. This was done primarily by training novices in
different styles of meditation practice and by familiarizing them to different
phenomenological categories of interest. A prominent issue in the field of neuroscientific
studies on mindfulness meditation is the relative paucity of high quality active control
(Goldberg et al., 2017). This issue has been repeatedly raised and suggestions of
improvement have been discussed in the context of longitudinal studies (Davidson &
Kaszniak, 2015; Kuyken et al., 2016). However, cross-sectional studies with long term
practitioners have received less methodological attention. In such studies, an active
control group is often lacking or too basic when present. Of the nineteen independent
cross-sectional studies on the neurofunctional effects of long term meditation in a recent
meta-analysis (Fox et al., 2016), only seven included an active control.2 In six of these
studies, meditation-naive participants received written and/or oral instructions and were
encouraged to sustain a daily practice for 7 to 10 days until the moment of the
experiment. In the remaining study, participants received a brief training session by an
experienced teacher on the day of the experiment (Kalyani et al., 2011). These approaches,
while clearly better than not including an active control group, have several limitations.
First, limited possibility for feedback or the lack of guidance by an experienced and
qualified instructor induces a high risk of misinterpretations and inadequate
implementations of the practices. Second, the short duration of the training limits the
opportunities to engage with the practice. Here we addresses some of these issues by: (1)
formally training meditation-naive participants in practices from the same meditation
background as the long-term practitioners, (2) letting this training be provided by a
qualified instructor in a context with attention to sufficient opportunity for guided
practice and feedback, and (3) encouraging participants to maintain a daily practice at
home for a minimum of 20 min a day for an extended duration (6–22 weeks depending on the
availability of participants and experimental resources). We contend that these
adaptations make it more likely for participants to reach a refined understanding of the
various practices and experiential dimensions at hand. This training has the potential of
reducing the risk that any group differences are merely driven by confounding factors
(e.g. misunderstanding practices and/or unfamiliarity with meditation terminology for
novices but not experts), instead of reflecting the true effect of interest, i.e.
meditation expertise. We will first report the specifics of our meditation training
protocol. Then we will provide empirical evidence for its effectiveness in teaching
meditation-naive participants to use first-person categories to describe their conscious
experience and discriminate between phenomenological dimensions.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

The first stage of the research included a meditation training weekend comprising of 42
healthy participants naive to meditation. These individuals were recruited for their
interest to learn meditation and their willingness to sustain a regular practice for
several months. After a preliminary inclusion procedure (see study manual for details,
Abdoun et al., 2018), participants were invited to attend a weekend-long training program
in the Lyon Neuroscience Research Center. The program looked to support participants in
developing a refined understanding of the states of consciousness involved in the
following experimental study. The expert group was comprised of 30 healthy long-term
practitioners with more than 10,000 h of formal meditation in their life and trained in
the Kagyü and Nyingma schools of Tibetan Buddhism. Both novices and experts participated
in up to 8 experimental sessions (see study manual for details, Abdoun et al., 2018). For
expert participants, these experimental sessions were gathered in 2 visits of 3 days, or a
single visit of 6 days. For novice participants, each visit comprised 1 or 2 experimental
sessions, and the visits were spread over a period spanning from 2 to 23 weeks after the
training weekend. Visits were scheduled according to participants’ and equipment (MRI,
MEG, EEG) availabilities, leading to a large but quasi-random variability across the
novice group in time elapsed between the training and the experiment. Among all
participants, 25 trained novice practitioners and 25 expert practitioners participated in
the MEG experiment described below. The remaining participants included in the larger
study were excluded for the MEG experiment because of excessive signal artifacts caused by
dental prostheses. The novice and expert groups for the MEG experiment did not differ in
gender (16 and 15 males, respectively; χ2(1) = 0.08), age (53.9 ± 7.1 and 51.6 ± 8.0
years, respectively; independent t-tests t = 0.84) and education (3.88 ± 2.15 and 3.20 ±
2.16 years of higher education, respectively; independent t-tests t = 0.46).

        <hss>General outline</hss>

        The training protocol was based on Joy of Living (Rinpoche & Swanson, 2007;
        Tergar, 2018), a secular meditation program aimed at Western audiences authored by
        Yongey Mingyur Rinpoche, a renowned master of Karma Kagyü and Nyingma schools of
        Tibetan Buddhism. This program was selected for its shared background with
        experts’ training. In its original format, the program is divided into three
        stages, each lasting two days; in addition, there are minimal practice
        requirements to attend stages 2 and 3. For our training protocol, we drew from the
        material of stages 1 and 2, condensing them in a two-day format, and included
        adaptations to emphasize the specific dimensions of experience of interest to the
        research program. The training was provided by a qualified instructor with
        thirteen years of practice under the guidance of Mingyur Rinpoche, and eight years
        of teaching experience with the Joy of Living program. The training included
        teachings with the support of instruction videos, guided meditations and
        experiential exercises, question and answer sessions, as well as sufficient time
        to reflect and share within the group. The training allowed a basic understanding
        of a few selected phenomenological dimensions eligible for an active comparison
        with expert practitioners. In particular, the program introduced participants to
        the following dimensions: effort, aperture, absorption vs. meditative awareness,
        foreground vs. background awareness, equanimity, clarity (see Table 1 and
        supplementary materials). The discernment of these dimensions was implemented by
        introducing the lived phenomenology of these states and creating occasions for a
        direct exploration of them. To access both the experience and the meaning of
        meditation the teacher devised specific exercises with connected theoretical
        principles. As a sommelier apprentice does in tasting, savoring, comparing and
        sampling different wines under the guidance of a sommelier, participants were
        invited to learn, practice and distinguish few states of consciousness under the
        guidance of a meditation teacher in order to become progressively familiar with
        some meditative phenomenological dimensions commonly described in contemplative
        traditions. The training followed a specific day program (Table 2) which will be
        briefly described here. In day 1, participants were first introduced to the notion
        of mental ‘effort’ in meditation through an experiential exercise that involved
        listening to sounds. The rest of the day was spent exploring the concepts of
        ‘absorption and meditative awareness’. This exercise was done first by using the
        breath as an anchor for meditative awareness. Participants were asked to restrict
        their attention to the breath, to notice when their mind had wandered, and to
        return their attention to the breath when this happened. Later during the day,
        they were also asked to gradually explore more open forms of awareness, by opening
        up to sense experiences from the environment (e.g. sounds and vision). While doing
        so, participants also engaged in two other experiential exercises that introduced
        the concepts of ‘object orientation and aperture’ and ‘foreground and background
        awareness’. At the beginning of day 2, participants continued to explore
        meditative awareness of the environment with various exercises including a walking
        meditation in open awareness. Then the instructor asked participants to form small
        groups and share their personal experience of the weekend. After some time, the
        small groups gathered to share collectively the problems and difficulties which
        had emerged, so that the teacher could provide adequate feedback. Then the
        concepts of ‘empathy and compassion’ were introduced and the teacher asked
        participants to briefly cultivate feelings of self-compassion. After lunch,
        participants engaged in an exercise that involved switching between focused
        attention on, and open monitoring of, pain. The rest of the afternoon was spent
        further elucidating concepts of empathy and compassion, including an experiential
        exercise that presented images of people’s suffering to participants. Finally,
        during the closing meditation session, the importance of the intention to practice
        was discussed and emphasized. Participants were asked to fully engage in their own
        practice.

        <hss>Experiential exercises</hss>

        Throughout the training weekend, subjects were prompted to familiarize themselves
        with the dimensions of subjective experience that were going to be of interest in
        the neuroscientific experiments. This familiarization was carried out by using
        experiential exercises. During each exercise, a dimension or process was
        introduced in a more or less explicit form. Some dimensions were experienced and
        described in the context of guided meditation sessions and teachings, while other
        exercises were implemented with the specific aim of familiarizing subjects with a
        phenomenological dimension. We refer the reader to the Supplementary Materials for
        a full description of these exercises. At the end of the weekend, subjects
        received a document that briefly described each phenomenological dimension and
        reminded them how it was introduced by corresponding exercises during the weekend.

        <hss>Compliance and engagement with practice</hss>

        The minimal goal of the training weekend was to give novice participants
        sufficient understanding and confidence to carry on practice autonomously, thus
        deepening their familiarity with the practices under study. At the end of the
        weekend, participants received an explanation of what was expected of them in
        terms of homework practice. Participants were advised to practice for 20–30 min on
        a daily basis and to give equal importance to each of the three practices they had
        learned. In addition, they were asked to report the type and amount of practice in
        a practice logbook that was provided at the end of the meditation training
        weekend. In order to ensure truthful reports, participants were assured that non-
        compliance to these recommendations would not call into question their
        participation to the study. Participants were provided with three 15 min-long
        audio recordings of guided meditations by their instructor to aid their practice
        (one recording for each of the three meditative practices). However, they were
        strongly encouraged to avoid relying exclusively on them and to get used to
        meditating unguided. Participants were also given excerpts from the book Joy of
        Living, summarizing most of the teachings received during the weekend: the
        physical posture, the mental attitude, as well as various meditative and
        experiential exercises examined during the weekend (Rinpoche & Swanson, 2007).

<hs>  Practice metrics</hs>
  ~~~~~~~~~~~~~~~~

Four metrics were used to assess participants’ home practice and degree of engagement: the
proportion of days involving practice (hereafter referred to as Frequency of practice or
simply Frequency); the average amount of practice during days with practice (hereafter,
Session length); the daily average amount of practice, all days included (Intensity of
practice or simply Intensity); and the total amount of practice (Experience).3 Fig. 1
describes how these four metrics relate to each other and how they were derived from the
data contained in the practice logbooks. These metrics were also explored in relation to
phenomenological ratings and behavioral measures from the experiments.

<hs>  Protocol of the MEG experiment</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

One major purpose of the meditation course undertaken by novice participants was to train
them in using phenomenological categories of interest in the study. In order to validate
that they understood these categories as intended and used them appropriately, we analyzed
the self-report data from a magnetoencephalographic (MEG) experiment with a hierarchical
repeated measure design that included several periods of FA and OM meditations, along with
a control (resting-state, RS) period (Fig. 2). The experiment started with a staircase
visual threshold calibration for a visual task whose detailed procedure and results are
irrelevant for the present article but will be described in another publication. Following
the calibration, we recorded a 7 min baseline period. Then, participants practiced FA and
OM twice each, in sequences of approximately 24 min (Fig. 2a). Each sequence opened with a
7 min-long block of meditation only, during which participants were presented with a
1.5°-wide white dot in the middle of a black screen (Fig. 2b). The instruction was to keep
the gaze steady on the white dot; in FA, participants were additionally instructed to use
that disk as a support for the attention. This first block was followed by three blocks
lasting approximately 5.5 min each, during which participants were instructed to maintain
the meditative state while performing a simple visual conscious report task using a
threshold stimulus embedded in a passive visual oddball paradigm (Fig. 2c). After each
block, participants were invited to rate their experience over 6 different dimensions,
using a 7-point Likert-type item (Fig. 2d): Capacity to apply the meditation instructions,
Stability of the mind, Clarity of the mind, Aperture of the field of awareness (see table
1 for definitions), Awareness of bodily sensations, and Wakefulness. Here we will limit
our analysis to the dimensions featured in the phenomenological matrix: Stability, Clarity
and Aperture.5 Rating scales were thus introduced: “Compared to your usual experience, how
would you rate the last block in terms of Stability/Clarity/Aperture?”

<hs>  Statistical analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Statistical modeling and inference. ANOVAs were of type 2. Post hoc tests were performed
using one- or two-sample t-tests, adjusted for family-wise multiple comparison using
Tukey’s honestly significant difference (HSD) method. One-sample and paired two-sample
tests were performed using the non-parametric Wilcoxon signed rank test. Linear mixed
models were fitted using maximum likelihood and significance of fixed effects were
evaluated using the likelihood ratio test. All linear regressions were ordinary least
square (OLS) regressions. Correlation between scale ratings and variability of response
times. Outlier trials were defined as trials for which response times were not within 3
standard deviations from the mean value, for each participant, state and response type
(yes/no), and excluded. An index of RT variability was defined for each block as the
standard deviation of RTs. Finally, we computed for each participant the Pearson
correlation coefficient between Stability ratings and RT variability. We did the same with
Clarity. Correlation coefficients were z-transformed for the purpose of statistical
modeling and are noted z hereafter. The data from one subject was removed because it had
no variance in the Clarity scale (the subject responded 6 in all blocks). Model selection
for multiple regression analyses. For each of the effects related to phenomenological
rating scores, we considered several potential predictors: metrics of home practice
(Intensity, Experience and the balance between focus and open styles of practice), and an
index of desirable responding (the score to the Balanced Inventory of Desirable
Responding, BIDR). Practice data was missing for one participant, who was therefore
excluded from subsequent analyses. We used an information-based model selection to
determine the most important predictors for our data (Burnham & Anderson, 2002). Model
selection is well suited to multiple regression analysis when the number of predictors is
high compared to the number of data points; in addition, it virtually guarantees that no
potential effect of interest is missed, as long as it is included in the variable set. We
performed model selection in 2 steps, using glmulti for R (Calcagno & de Mazancourt,
2010). Firstly, we fitted all possible models that contained a subset of the predictors
mentioned above and their two-way interactions, and that satisfied the marginality
constraint (i.e. included all interaction terms as main effects). We used the corrected
Akaike information criteria (AICc) as a measure of the quality of fit, because it is well
adapted to small sample sizes (Hurvich & Tsai, 1989). Secondly, we selected models that
were within 2 information criteria (IC) units of the best fitting model (Burnham &
Anderson, 2002) for further consideration. Detailed results of the model selection output
are presented in the Supplementary Materials. These include the relative evidence weight,
a measure of relative importance of each term across the entire model space (Calcagno & de
Mazancourt, 2010), comprised between 0 and 1.

<hs>  Structure of home practice</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

The total duration of participation to the entire study ranged from 41 to 163 days (99.4 ±
31.4 days) after the training weekend. Average daily practice (=Intensity) ranged from 1.3
to 30.5 min (15.9 ± 7.3 min; supplementary Fig. 1a, top left), suggesting that many
participants fell short of the recommended amount of practice (20 to 30 min a day).
However, when average daily practice was calculated over the number of days with at least
some practice (rather than all days), the obtained Session length was found to range from
14.0 to 33.1 min (21.2 ± 5.5 min; supplementary Fig. 1a, bottom right). Participants
dedicated 45.2 ± 16.8% of their practice time to OM (Open Monitoring), 33.4 ± 17.5% to FA
(Focused Attention) and 21.4 ± 9.8% to CO (Compassion). A one-way repeated measure ANOVA
revealed a significant difference between the proportion of time dedicated to the
different practices (F(2,80) = 16.95, p < .0001, η2 = 0.30). Post hoc paired t-tests
revealed that all comparisons of pairs of practices were significant (supplementary Fig.
1b). Intensity of practice decreased linearly over weeks (supplementary Fig. 2a; R2adj =
0.87, p < .001, β = -0.44, 95% CI [−0.53, −0.35]). A large portion of this drop (80.9%) is
imputable to a sharp decline of Frequency of practice over weeks (supplementary Fig. 2b;
R2adj = 0.92, p < .001, β = −0.14, 95% CI [−0.16, −0.12]). The remaining 19.1% is due to a
slight shortening of practice sessions (supplementary Fig. 2c; R2adj = 0.22, β = −0.10,
95% CI [−0.18, −0.01]). Taken together, these results show that participants managed to
follow the recommendation of 20-to-30 min-long practice sessions throughout the study, but
failed to practice on a daily basis and were increasingly inclined to skip days.

<hs>  Patterns in self-reports and relationships to practice</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We tested three predictions that should be verified if the phenomenological self-reports
are reliable. We examined whether the responses of the novices to the rating scales in the
MEG experiment (i) were sensitive to the meditation state, in a way consistent with the
known phenomenology of mindfulness practices (Lutz et al., 2015), (ii) exhibited classic
temporal dynamics such as dose and fatigue effects, and (iii) were functionally
informative, as would be suggested by correlations with behavioral measures. In each
instance, we tested whether desirable responding and/or features of participants’ home
practice predicted the effects observed on self-reports. The results are summarized in
Table 3.

        <hss>Effect of states on self-reports</hss>

        In the phenomenological model introduced in Lutz et al., 2015, Stability and
        Clarity are described as secondary qualities that are both increased when
        practicing either FA and OM (compared to mind-wandering), and even more so with
        expertise. In contrast, Aperture is hypothesized to increase specifically during
        the practice of OM.

        <hss>Predictors of the state effect on Aperture</hss>

        When participants are asked to rate the broadness of their attentional scope (i.e.
        Aperture) in two different meditation states referred to as “focus attention” and
        “open presence”, the fact that the expected response lies in the very names of the
        state conditions can hardly remain unnoticed. Thus, we cannot exclude the
        possibility that participants’ responses were influenced by their willingness to
        please the experimenter, and/or to show that they have correctly understood the
        meditation instructions. Another, non-trivial hypothesis is that novice
        participants develop the ability to differentiate a state of focus attention and a
        state of broader awareness by getting equally familiar with both attentional
        styles. Said otherwise, we expect participants who have had more practice in OM
        than in FA to have more ease opening (or more difficulty narrowing) their
        attentional scope than participants who have developed an equal familiarity of the
        two styles of practice. As a result, we would expect the latter to better
        differentiate FA and OM on the Aperture scale than the former. The same reasoning
        can be straightforwardly applied, mutatis mutandis, to participants who favored FA
        over OM. We explored the plausibility of this hypothesis by testing whether our
        data were coherent with the ensuing predictions. We included an index of balance
        between FA and OM (FOB), along with other practice metrics (Intensity and
        Experience) and an index of desirable responding (BIDR) in the set of variables
        tested for model selection (see Section Methods, Statistical analyses). Three
        models survived the model selection procedure: the best one included a significant
        FOB-by-Experience interaction (model A1), while the other two contained a
        significant FOB-by-Intensity interaction (models A2 and A3; see details in
        supplementary Table 1). BIDR was not present in any of these models, and its
        evidence across all models was found relatively low (0.31). The FOB-by-Experience
        interaction had a higher evidence across model space than the FOB-by-Intensity
        interaction (0.55 and 0.31, respectively). To illustrate how the balance between
        focus and open styles of practice interacts with the amount of practice, we
        performed a Johnson-Neyman post-hoc analysis of the interaction in model A1, using
        FOB as a predictor and Experience as a moderator. We found that for participants
        who had accumulated more than 23.9 h of practice, the FOB index positively
        predicts (p < .05) the self-reported difference in Aperture between FA and OM
        during the MEG experiment (see supplementary Fig. 3). Considering that all our
        participants except one practiced OM more than FA at home, a higher FOB could have
        been entirely driven by FA practice in our dataset. Thus, the FOB-by-Experience
        interaction could actually hide an effect of Experience in FA only, which would
        lead to a very different interpretation of our results6. To test this alternative
        explanation, we fitted a model with Experience in FA as a single regressor, as
        well as a model that also included Intensity as a regressor. None of them was
        found significant (p > .98 and p > .16 respectively). We repeated this analysis
        with Experience in OM instead of FA – again, neither model was significant (p >
        .84 and p > .22, respectively). To summarize, the results of our model selection
        analysis and post hoc tests are consistent with the hypothesis that equal
        familiarity with focus and open attentional states, rather than experience in any
        specific practice, drives the ability to differentiate between states.

        <hss>Temporal dynamics</hss>

        The absence of effect on self-reported Stability and Clarity in novices over the
        experiment does not necessarily rule out the possibility that novice participants
        used these categories appropriately and informatively. For example, averaging
        ratings over the entire experiment could have occluded temporal effects. This is
        indeed what we have observed in our data (supplementary Fig. 4). We used linear
        mixed models to account for the nested nature of the MEG experiment structure
        (blocks within sequences within sessions). The models included all possible
        interactions in fixed effects, as well as random subjects’ intercepts and by-
        subject random slopes across blocks, sequences and sessions. We used two models:
        one for Stability ratings and one for Clarity ratings. In both models, we found an
        effect of block on ratings only for the first sequence of each session (i.e.
        sequences 1 and 3; cf. Fig. 2; Stability: χ2(3) = 8.58, p = .035; Clarity: χ2(3) =
        7.85, p = .049), suggesting that the middle break had some sort of resetting
        effect. Post-hoc pairwise t-tests revealed a significant decrease of ratings from
        blocks 1 to 3 in sequences 3 and 4 (Stability: Δ = 0.62, 95% CI [0.19, 1.05], p <
        .002; Clarity: Δ = 0.43, 95% CI [0.09, 0.77], p < .007; all other p > .1), but no
        pairwise differences in other sequences (all p > .5).

        <hss>Predictors of the fatigue effect</hss>

        The decrease of self-reported Stability and Clarity in novices after four blocks
        (∼24 min) of meditation may reflect fatigue. This is not surprising considering
        that most novices were not used to meditating for more than approximately 20 min
        during their daily home practice (see supplementary Fig. 1a). A corollary of this
        interpretation is that the longer and more frequently the participants were used
        to meditate, the less likely they should be to experience fatigue in the context
        of the experiment. We tested this prediction by modeling a fatigue index, defined
        for each participant as the difference between their ratings in block 3 and block
        1 of sequence 1,7 averaged over the dimensions of Stability and Clarity. Five
        models were selected (supplementary Table 2). Intensity was present in 2 of them
        as a main effect, and in 2 others in interaction with BIDR. Surprisingly, FOB was
        present as a main effect in 4 out of the 5 selected models. Across all models, FOB
        and Intensity had the highest relative weighted evidence (0.74 and 0.66,
        respectively) closely followed by BIDR (0.60). The fact that FOB was found as
        important as Intensity suggests that the mitigating effect of practice Intensity
        on Fatigue is driven by the level of engagement in a specific style of practice.
        To explore this idea, we performed a second model selection where we replaced
        Intensity and FOB by the two subcomponents of Intensity: IntensityFA and
        IntensityOM, corresponding to the two styles of practice. For the sake of
        parsimony, we also removed Experience, which was already found to be of low
        importance. The only selected model from this new variable space had a single
        regressor, IntensityFA (p = .034, β = 0.085, 95% CI [0.007, 0.162]; supplementary
        Table 3).

        <hss>Correlation with behavioral measures</hss>

        Previous studies have reported intra-individual variability of performance (most
        notably response times) as a good predictor of whether the participant is on-task
        at a given moment or not (Bastian & Sackur, 2013; Seli, Cheyne, & Smilek, 2013).
        Based on this literature, we predicted that self-reported Stability, but not other
        dimensions, would be significantly correlated to variability of response times at
        the level of individual participants. We chose Clarity as a control dimension, for
        its similar pattern of sensitivity to state and group (see Fig. 3). One sample
        Wilcoxon signed rank tests of z-transformed within-subject Pearson correlation
        coefficients against zero show that the RT variability correlated negatively with
        Stability (z = −0.26, 95% CI [−0.40, −0.12], p < .0003) as expected, but also with
        Clarity (z = −0.14, 95% CI [−0.28, −0.003, p = .046) (Fig. 5a, left). However, a
        two-sample paired test between zstability and zclarity was found significant (p =
        0.041). Thus, even though self-reported ratings of Stability and Clarity were
        strongly correlated within subjects (Wilcoxon signed rank test on z-transformed
        correlation coefficients: z = 0.77, 95%CI [0.62, 0.94], p < .0001), the
        association with RT variability was significantly stronger for Stability than for
        Clarity. This suggests that although the phenomenological dimensions of Stability
        and Clarity tend to fluctuate naturally together, novices are able to
        differentiate them functionally in their reports, just like experts (Fig. 5a,
        right). In order to further assess the specificity of these findings, we repeated
        the same analysis using mean RT (instead of RT variability). We found that neither
        Stability nor Clarity correlated significantly with mean RT (both p > 0.1).

        <hss>Predictors of the phenomenological specificity</hss>

        Based on these results, we further hypothesized that this fine differentiation
        could have been implicitly trained in our novice group through the practice of
        meditation. Indeed, the reflexive quality cultivated in contemplative practices is
        expected to improve one’s familiarity with the specific phenomenal characteristics
        of different experiential dimensions. To test this prediction, we defined an index
        of phenomenological specificity as the difference between zstab, the z-transformed
        Pearson correlation coefficient between Stability ratings and RT variability, and
        zclar, the analogue measure for Clarity ratings. Only one model survived selection
        (supplementary Table 4), and it contained a single regressor, Experience (p =
        .023, β = −0.011, 95% CI [−0.021, −0.002]; Fig. 5b). Across all models, Experience
        had by far the highest evidence weight (0.84). Following the suggestion of a
        reviewer, we further explored whether Experience in particular practices drove
        phenomenological specificity. We performed a second model selection using the
        amount of Experience in each practice (FA, OM and CO) and the 2-way interactions
        between these 3 variables (to model for potential synergies between practices).
        Three models were selected from this new variable space (supplementary Table 5).
        All of them included ExperienceOM as a regressor but no interactions whatsoever.
        ExperienceOM had by far the highest evidence weight (0.91), while ExperienceFA and
        ExperienceCO were on par (0.44 and 0.49 respectively).

<h>DISCUSSION</h>
----------

We described a meditation training protocol intended for naive candidates with no prior
experience of meditation. We designed this protocol out of the need for a high-quality
control group for a neurophenomenological study on the effects of meditation state and
expertise in meditation on brain, behavior and physiology. The aim of the training was
twofold: (1) to provide participants with sufficient background knowledge and direct
experience with three types of meditations so that they could sustain a regular practice
for an extended period of time, and be comfortable to practice in the laboratory context
for the experimental tasks of the study; (2) to establish a common ground of relevant
phenomenological categories with the participants, in order to allow them to report their
experience during meditation states reliably. Overall we found evidence that the
phenomenological training was successful in the sense that participants’ self-reports: (i)
were reliable and sensitive to the meditation state manipulation, (ii) exhibited expected
temporal dynamics such as dose and fatigue effects, and (iii) were functionally
informative; in addition each of these effects was more strongly predicted by the amount
and structure of participants’ practice than by desirable responding as indexed by the
BIDR questionnaire.

<hs>  Motivation and compliance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

In meditation research, motivation is often discussed for its potential confounding effect
that limits the interpretability of longitudinal studies (Eberth & Sedlmeier, 2012). On
the other hand, motivation of novice control participants can be considered a strength for
the cross-sectional study of expertise as expert meditators, in so far as they dedicate a
large of amount of time and resources to their training and practice, are expected to have
strong motivation. Our study was highly demanding for the novices, as they had to engage
in daily practice and participate in 6 to 8 experimental sessions over the course of
several months. This, along with the multi-step recruitment procedure, acted as a filter
for motivation. The high level of motivation of the novice participants was reflected in
the satisfactory level of commitment to the practice maintained throughout their
participation to the study. Three months after their training, they were still
accomplishing more than half of the prescribed amount of practice, in the absence of any
reminders or booster sessions. This even though they were assured that dropping the
practice would remain without consequences for their participation to the study and
financial compensation. This laxity given to participants, while having the effect of
revealing their intrinsic motivation, is not without shortcomings. Compassion meditation,
for example, was largely neglected. This might be related to the dense set-up of our
initiation program, which attempted to train the participants in three different forms of
meditation in just two consecutive days. In contrast, the original Joy of living program
on which the training was based requires that practitioners first engage in 6 months of
regular practice before they can receive teachings on compassion. However, this
shortcoming has limited consequences for our study as the goal was primarily to get
participants accustomed to the concept and practice of compassion and sensitize them to
its difference with empathic resonance. A large majority (75%) of participants favored the
practice of OM at home. This may come as a surprise considering that in many Buddhist
contemplative traditions, OM practices are considered more advanced and are approached
only after some training in FA (Lutz et al., 2008). However, this bias towards OM is
consistent with the deliberate stance adopted by Mingyur Rinpoche, author of the Joy of
living program, whereby one is invited to enter the field of open awareness from the
outset.

<hs>  Phenomenological proficiency</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

During their training, novice participants were introduced to phenomenological categories
with the help of practical, experiential exercises. Using rating scales and behavioral
data from one of the experiments to which they later participated, we have described three
effects that can be interpreted as reflecting an effect of practice, phenomenal training,
or both. Based on both a priori considerations and control for desirable responding, we
have systematically assessed the potential confounding effect of demand characteristics
and found limited support for it. We review the evidence (see also Table 3) and discuss
other potential alternate interpretations below. First, novice participants reported
greater Aperture in OM compared to FA, just like experts, suggesting that they were able
to distinguish the two practices. In addition, their responses on the Aperture scale was
not driven by their diligence in any specific meditation style, but rather by the overall
structure of their practice: the better they balanced focus and open styles of meditation,
the larger the divergence in Aperture they reported (at least for participants who
practiced the most: more than 24 h in total). This finding suggests that equal familiarity
with different states is important for their optimal dissociation, at least at a beginner
level. Future studies should test this hypothesis more rigorously using a longitudinal
design with measures collected at baseline. Moreover, although we did not find any
evidence for desirable responding in this data, we could not rule out the possibility that
basic semantic priming inflated the reported dissociation in Aperture. Ideally, future
training programs and experiments should try and avoid semantic overlap between meditation
instructions and phenomenological dimensions altogether. Second, self-reported Stability
and Clarity had a two-stage dynamic during a series of 4 consecutive six-minute blocks of
meditation, with a statistically significant decrease between the second and the last
block. We interpret this phenomenon as a fatigue effect, rather than an effect of scale
misuse. This is based on the observation that this decrease was negatively and
specifically associated to participants’ Intensity of practicing focus attention.
Interestingly, this specific association is consistent with the role of concentrative
practices in Buddhist contemplative traditions. These practices are used as training to
stabilize attention and other basic qualities such as clarity and effortlessness, before
applying them to more advanced practices. However, this correlation is not necessarily
indicative of an effect of training: it may be mediated by an individual trait (e.g.
conscientiousness or stamina), present even before the meditation training, that could
predict both sustained diligence in the practice of (the relatively effortful) focus
attention, and endurance during meditation sessions in the MEG experiment. Regardless, the
index of desirable responding was of lesser importance in comparison. Third, we showed
that participants’ ratings of the dimension Stability were functionally relevant, as they
correlated with the variability of their response times. Using Clarity as a control
dimension, we found that this functional relationship was specific. This finding suggests
that participants were able to make fine distinctions between two close dimensions (this
effect was true for both novice and expert practitioners). Regarding novices, we found
that the more Experience they had at the day of the experiment, the sharper their
phenomenological acuity. More specifically, we found that Experience in OM, compared to
other practices, was the best predictor of this acuity. This is in line with the insight
potential commonly attributed to OM-like practices in Buddhist contexts (Dahl, Lutz, &
Davidson, 2015). Here again, in the absence of longitudinal data, the correlation cannot
be treated as direct evidence for a causal link involving learning. However, a noteworthy
difference with the fatigue effect described above is that the practice metric that
predicted phenomenological acuity (accumulated Experience) is not confounded with
participants’ assiduity, because it depends as much on Intensity of practice as on the
time elapsed between the training weekend and the experiment (which was variable and
random across the group). Considering that Intensity of practice did not predict
phenomenological acuity, it appears that a likely explanation of these results is that
novice participants became more familiar with the phenomenal richness of their experience
throughout the regular practice of meditation, and more proficient in reporting it with
specificity and subtlety. Taken together, our data support the claim that the novices in
our study had some phenomenological literacy, and were able to report about qualities of
their experience in an appropriate, meaningful and informative way, even though in some
cases we could not conclusively rule out the possibility for an additional effect of
demand characteristics.

<hs>  Training and practice</hs>
  ~~~~~~~~~~~~~~~~~~~~~

We have introduced several metrics of practice beyond the oft-used total amount. Although
these metrics are derived from each other, they are not entirely collinear. In particular,
our study was able to dissociate Experience (=total amount of practice) from Intensity
(=daily average of practice) by having a large variability in the time elapsed between the
training and the MEG experiment, across the novice group (from 27 to 133 days; M = 79, SD
= 29). Moreover, we showed that these two metrics could be functionally dissociated when
correlated with subjective ratings or behavioral measures. Such dissociations could point
to potentially different mechanisms of trait changes brought about by the practice of
meditation. This observation is consistent with the finding that intensive retreat
practice, but not routine daily practice is associated with reliable differences in
resting respiration rate in experienced meditators (Wielgosz, Schuyler, Lutz, & Davidson,
2016). It is also reminiscent of the work of Antonova, Chadwick, and Kumari (2015) who
found that intensity of practice was a better predictor of decreased habituation to the
acoustic startle reflex than total hours of practice. Future investigation of the
mechanisms of meditation would benefit from a systematic exploration of various practice
metrics and their relation to experimental outcomes, for both novice and expert
practitioners. What is the minimum amount of practice that should be required from novice
participants for the quality of their phenomenological self-reports to match those of
experts’, on the dimensions explored here? Based on our experimental results, we can
provide tentative, rough estimates. In our samples of participants, 20–40 h were necessary
for novices to reach a level of phenomenal specificity comparable to the one of experts; a
minimum of 20 min of practice per day on average and a high balance between practices (no
more than 40% bias) enabled novice participants to differentiate different styles of
meditation as well as expert practitioners. All these criteria are much higher than what
most past cross-sectional studies of meditation expertise have required from their control
participants (Fox et al., 2016), but are sufficiently low to be practically accessible and
implemented in future studies.

<hs>  Self-rating scales</hs>
  ~~~~~~~~~~~~~~~~~~

We used self-rating scales as tools to help participants translate qualities of their
lived experience into quantities that can be manipulated, transformed and statistically
analyzed just like any other numerical measure. Such tools raise vexed issues: for
example, how can we know that participants use the scales as intended? How can we know
that participants, or groups of participants, are not construing a given scale in widely
different ways? How can we even be sure that a given participant is consistent in the way
he/she uses a scale over time or across experimental conditions, for that matter? To take
the example of stability of meditation states, we may argue that stability refers to
qualitatively different experiences in FA and OM. In FA, stability reflects the sustained
focus on a given object and therefore the stability of mental content. In contrast, OM
stability reflects the absence of grasping and as such, should not be affected by
variations in content. Our approach of phenomenological training pragmatically addresses
the issue of interpretation by mapping linguistic definitions of categories onto features
of lived experience induced and revealed by simple experiential exercises. Performing
these exercises in the context of a group, under the guidance of an instructor and with
the possibility to share their understanding and reflect collectively, has the potential
to attenuate idiosyncratic apprehensions of the phenomenological categories. In addition,
concerns related to the subjectiveness and incommensurability of self-reported ratings
were pragmatically addressed using within-subject designs and analyses. Even if our
results suggest that our methodological approach was effective in detecting
phenomenological fluctuations, it is worth mentioning the low variance of our self-rating
data. As an example, 41 out of 50 of our participants used only three values out of the
seven available in the Stability and Clarity scales; for Clarity, 18 out of 50
participants used only two values. This suggests a limitation of our experimental design
and/or our training program. For instance the relatively short duration of laboratory
experiments may not be sufficient to experience large fluctuations in these dimensions.
Finer rating scales could be used as a compensation to increase data variance. Another
possibility is that our training program was insufficient in developing participants’
fine-grained sensitivity to these scales. Further methodological work is needed to address
these limitations.

<hs>  Future directions</hs>
  ~~~~~~~~~~~~~~~~~

The role of meditation practice for cognitive science was extensively discussed by Varela
et al. (1991), becoming a part of their ‘enactive’ approach and then of Varela’s
neurophenomenological program (Varela, 1996). We have provided preliminary evidence that
meditation experience improves the reliability of self-report data by improving the
functional specificity of self-reports, and by shielding them from the effect of demand
characteristics. However, several questions remain open and should be addressed by future
research. First, the impact of training on the quality of first-person data should be more
rigorously assessed using high-quality, longitudinal, randomized controlled trials. In
particular, future work should tackle the open question of whether specific
phenomenological training such as the one we implemented through experiential exercises is
required to improve the quality of first-person data, or whether meditation practice is
sufficient in itself. In order to evaluate the confounding effect of demand
characteristics on our first person-data, we have used an index of desirable responding.
Unfortunately, the validity of the questionnaires designed for this purpose, including the
one used in this study, has been frequently questioned as they are unable to distinguish
between genuine personality traits and self-enhancement (Paulhus, 2002). Special attention
should be given to more recent efforts to overcome these limitations using alternative and
potentially complementary approaches (Kwan, John, Kenny, Bond, & Robins, 2004; Paulhus,
Harms, Bruce, & Lysy, 2003). We have provided evidence for reliable first person reports
of the phenomenology of meditation experience. However, the generalizability of the
phenomenal insight provided by meditation practice to other, non-meditation-related
applications remains disputed (see Khalsa et al., 2008 for an example of negative result)
and warrant more research. Rather than provide a standardized, validated, ready for use
protocol, our intention was to raise methodological concerns pertaining to the quality of
control groups used in cross-sectional studies of meditation, and to argue for the
possibility of obtaining informative experiential self-reports from adequately trained
participants. Although we described in detail the protocol that we designed to address
these issues, including the experiential exercises used for the phenomenological training
of the participants, our approach is tailored to the specific context of our study, and to
a particular phenomenological model of meditation among others (Bodhi, 2011; Lindahl,
Fisher, Cooper, Rosen, & Britton, 2017; Van Dam et al., 2018). Still, we hope that the
process, rather than the content, will inspire researchers in the field to further explore
these critical issues.

<h>ETHICS</h>
------

The entirety of the Brain & Mindfulness project, including the meditation training weekend
and the MEG experiment, was approved by the local ethics committee (CPP Sud-Est III,
authorization number 2015-A01472-47). All participants signed an informed consent prior to
their participation to the meditation training.


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<ART>Trait emotional intelligence and leadership in a European multinational company
===============================================================================

Authors: A. B. Siegling, Charlotte Nielsen, K. V. Petrides
DOI: 10.1016/j.paid.2014.01.049
Year: 2014  |  Pages: 65-68
ASJC codes: 3200
Keywords: Cognitive ability, Group differences, Leadership, Management, Trait emotional intelligence

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This study examined whether trait emotional intelligence (trait EI or emotional self-efficacy) can differentiate between leaders and non-leaders (. N=. 96) employed by a major multinational company in Europe. Available intelligence test scores along with age, gender, and tenure were used as control variables. Trait EI, cognitive ability, and gender were significant predictors in a logistic-regression model. Further, both leaders and non-leaders scored significantly higher on trait EI compared to the standardization sample of the Trait Emotional Intelligence Questionnaire (Petrides, 2009), though the effect size for the former (Cohen's d=. 2.80) was considerably larger than for the latter (Cohen's d=. 1.23). The results support the notion that leadership and management positions require high trait EI. © 2014 Elsevier Ltd.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Much has been said about the importance of emotional intelligence (EI) in leadership,
which overlaps with the concept of management (Young & Dulewicz, 2008). The extant
literature on EI and leadership lacks differentiation among EI conceptualizations and
operationalizations. For instance, when combining “emotional intelligence” and
“leadership” as search terms in the PsycINFO database, 3,838 entries were returned.
Combining the more specific constructs “trait emotional intelligence” or “ability
emotional intelligence” with “leadership” led to 345 and 17 results, respectively. It
follows from these numbers that the type of EI construct investigated was not specified in
most of these studies. This is problematic because self-report measures of EI do not
converge with maximum-performance measures; the former correlate substantially with
personality and non-significantly with cognitive ability, while the latter show the
opposite pattern of results (e.g., Qualter, Gardner, Pope, Hutchinson, & Whiteley, 2012).
While both ability EI and trait EI have theoretical relevance to leadership, the focus of
this article is on the latter, which is intended to represent the affective aspects of
human personality. Trait EI is formally defined as a constellation of emotional self-
perceptions located at the lower levels of personality hierarchies (Petrides, Pita, &
Kokkinaki, 2007). There is a large literature demonstrating the validity of personality
traits in the prediction of leadership-related constructs. Judge, Bono, Ilies, and
Gerhardt (2002) conducted a large-scale meta-analysis showing that all Big Five
personality traits, with the exception of agreeableness, predicted leadership, independent
of industry and the leader’s specific job role, with a multiple correlation of .48. Yet,
consistent with Paunonen and Ashton’s (2001) detailed approach to personality assessment,
domain-specific traits may well improve the prediction of various leadership criteria,
compared to the Big Five. Since leadership draws on many of the attributes assessed with
the prevailing typical-performance EI measures (e.g., assertiveness, optimism; emotion
expression, perception, and management), trait EI should emerge as a potentially important
predictor of leadership-related variables. Many studies have examined and demonstrated
associations between trait EI measures and various aspects of leadership. For example,
Barling, Slater, and Kelloway (2000) found EQ-i (Bar-On, 1997) scores to predict three
aspects of transformational leadership (idealized influence, inspirational motivation, and
individual consideration), controlling for attributional style. Similarly, Mandell and
Pherwani (2003) observed a predictive effect of EQ-i scores on overall transformational
leadership (β = .49), which increased to β = .56 after controlling for gender. Villanueva
and Sánchez (2007) found a moderate positive correlation (r = .56) between leadership
self-efficacy (belief in one’s ability to lead), and trait EI, as measured with the
Assessing Emotions Scale (Schutte et al., 1998). It has yet to be demonstrated whether
leaders have higher trait EI than non-leaders, using objective (i.e., naturally-
occurring), rather than psychometrically assessed classifications of leaders and non-
leaders, and controlling for relevant factors (e.g., industry, gender, and age). Previous
studies have focused on leadership attributes assessed with rating scales, often based on
self-report. In another article in this issue, managers had higher trait EI scores than
the normative sample of the Trait Emotional Intelligence Questionnaire (Petrides, 2009),
but many other factors differentiating the two samples could not be controlled.
Furthermore, the Trait Emotional Intelligence Questionnaire (TEIQue), which was developed
to measure the construct of trait EI comprehensively and has been shown to possess
superior psychometric properties over other measures (e.g., Freudenthaler, Neubauer,
Gabler, Scherl, & Rindermann, 2008; Martins, Ramalho, & Morin, 2010), has not been used
extensively in leadership research. The present study examined the role of trait EI in
leadership within an applied context. In particular, leadership assessment was based on
the organizational position of participants in a European multinational company. It was,
thus, objectively determined and less prone to response biases than in other studies.
Logistic regression was used to assess trait EI as a predictor of leader vs. non-leader
positions held by the participants, controlling for cognitive ability, age, gender, and
tenure. Furthermore, consistent with the management article in this issue (Siegling,
Sfeir, & Smyth, 2014), we compared the mean trait EI level of leaders and non-leaders to
the TEIQue standardization sample means, as reported in Petrides (2009). Two hypotheses
were tested: Trait EI will distinguish leaders from non-leaders, controlling for cognitive
ability, age, gender, and tenure. Leaders will have significantly higher trait EI scores
than the TEIQue standardization sample.

<hs>  Participants and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~

A major European multinational company consented to participating in this study, which was
conducted in Denmark. The company placed an online recruitment invitation on their
intranet and those interested completed the questionnaire anonymously. Of a total of 300
contacted employees, 71 men and 25 women participated, yielding a response rate of 32% (N
= 96). The mean age of the sample was 37.09 years (SD = 7.73) and the age range was 24–61
years. The majority of participants were of white ethnicity (90.6%) and had attained an
undergraduate (40.6%) or Master’s degree (42.8%). Employees were in their present position
(tenure) for an average of 7.88 years (SD = 7.59). Participants came from four business
units of the company and were involved in various job functions, including technical
support, sales and marketing, finance, logistics, and security. A leadership post in the
company entails directly supervising three or more employees whom the leader manages and
appraises. Leaders have the right to hire and dismiss employees and are expected to drive
company values and deliver top quartile results. They are also expected to inspire their
team to higher performance through improving engagement and developing their supervisees’
capabilities to perform efficiently. The study sample comprised 23 leaders (22 males) and
73 non-leaders (49 males). The mean age of leaders was 36.62 years (SD = 7.92) and the
mean age of non-leaders was 38.61 years (SD = 7.06). Cognitive ability scores and
leadership status data were obtained from participants’ records from the human resources
department of the company. Additional information, including trait EI scores, demographic
background data (age, gender, and educational level) and job tenure (the number of years
employees had been in their present position within the organisation), was collected over
a time-frame of approximately two months.

        <hss>Trait EI</hss>

        Either the full Trait Emotional Intelligence Questionnaire (TEIQue – v. 1.50;
        Petrides, 2009) or its short form, the TEIQue–SF, were used as measures of trait
        EI. Due to time constraints on data collection, the full form was replaced by
        TEIQue–SF two weeks into the process. In total, 40 participants completed the
        TEIQue and 56 completed the TEIQue–SF. The full form consists of 153 items, while
        the short form consists of 30 items. Both yield global and factor scores, although
        the former also yields scores on the 15 trait EI facets. The internal consistency
        for global trait EI was .95 for the full form and .89 for the short form.

        <hss>Leadership</hss>

        Leadership was operationalized in accordance with the company’s definition of a
        leader, as described in the preceding section.

        <hss>Cognitive ability</hss>

        Cognitive ability was measured using an in-house Wonderlic-type test that was
        developed by a leading global test developer. Scores range from 0 to 50, with a
        score of 25 corresponding to an IQ of 120.

<h>RESULTS</h>
-------

Trait EI scores based on the full TEIQue were derived from the items also found on the
short form. However, one of the 30 short form items (item 10) does not originate from the
full form and, thus, it was replaced by a similar item (item 115). Descriptive statistics
for leaders and non-leaders are shown in Table 1. Leaders had significantly higher trait
EI scores than non-leaders, which was largely an effect of the Well-Being, t(94) = 2.10, p
= .04, and Self-Control, t(94) = 2.62, p = .01, factors, which reached significantly
higher levels in leaders (Sociability approached significance at p = .05). As shown in
Table 1, the average tenure of leaders was significantly higher than that of non-leaders.
In contrast, leaders and non-leaders did not differ on age or cognitive ability. Table 2
displays the bivariate correlations between the study variables. Trait EI correlated
positively with leadership, which, in turn, correlated positively with tenure and
negatively with gender (there was only one female leader). Cognitive ability was
negatively associated with tenure and age, which were positively associated between them.
Table 3 shows the logistic regression results. A chi-square goodness of fit test showed
that the set of predictors included in the model distinguished between leaders and non-
leaders, χ2(5) = 19.77, p = .001. The Hosmer–Lemeshow test indicated a good model fit to
the data, χ2(8) = 5.47, p = .71. Indices for the usefulness of the model tested here
showed that the model explained between 18.6% (Cox & Snell R2) to 27.9% (Nagelkerke R2) of
the variance in leadership. Relative to the constant-only model, the model including trait
EI and control variables improved the prediction accuracy of leadership cases from 76.0%
to 78.1%. Trait EI was a significant predictor of leadership in the presence of the
control variables in the equation (cognitive ability, tenure, age, and gender). The
predictive effect was such that leaders had higher trait EI scores than non-leaders. Given
the levels of the control variables and the proportion of female to male participants, the
odds of being a leader are multiplied by 2.77 for each one-unit increase in trait EI.
Although preliminary analyses revealed no significant relationship, cognitive ability was
a significant incremental predictor in the regression model. Here, the odds of being a
leader are multiplied by 1.12 for each on-unit increase in cognitive ability, given the
levels of trait EI and the other control variables. Consistent with the zero-order
correlations, gender was the only other significant predictor of leadership, with a
greater proportion of males among leaders than among non-leaders. Given the levels of the
other variables in the model, female employees were 0.10 times as likely to be a leader as
male employees. With the single female leader excluded, the mean global trait EI score of
leaders was compared to the TEIQue male-normative standardization sample mean. A one-
sample t test showed that male leaders in the current sample had significantly higher
trait EI scores (M = 5.54, SD = 0.43) than the normative comparison group (M = 4.95, SD =
0.61), t(21) = 6.41, p < .0001. The average trait EI score of male and female non-leaders
(M = 5.29, SD = 0.64) was also significantly higher than the combined normative sample
mean (M = 4.90, SD = 0.59), t(72) = 5.22, p < .0001; however, the effect size for male
leaders (Cohen’s d = 2.80, r =.81) was much larger than for male and female non-leaders
(Cohen’s d = 1.23, r = .52).

<h>DISCUSSION</h>
----------

The results support Hypothesis 1 and are consistent with previous research relating EI
scores from self-report measures other than the TEIQue to various leadership attributes
(Barling et al., 2000; Judge et al., 2002; Mandell & Pherwani, 2003; Villanueva & Sánchez,
2007). Global trait EI discriminated between leaders and non-leaders within the same
company, controlling for pertinent characteristics. Compared to previous research, in
which leadership-related variables were assessed through rating scales, leaders in our
study were identified based on their actual occupational position within the company.
Further, this study used the TEIQue, a measure designed to represent trait EI
comprehensively (Petrides et al., 2007). Although Hypothesis 2 was supported, the non-
leader group was also significantly above the TEIQue standardization sample mean, though
the effect size for the leadership group was more than twice as large. It is important to
bear in mind that the standardization sample is not matched on pertinent characteristics
to the sample of this study. For example, the average age of the standardization sample
(29.65 years, SD = 11.94) is about seven years younger than the mean age of the current
sample, which falls within the age interval (34–44) at which trait EI scores were found to
peak (Derksen, Kramer, & Katzko, 2002). On the other hand, the overall sample appeared to
be generally high in trait EI, as even the non-leaders had global trait EI scores
comparable to a managerial sample of similar age described in another study in this
special issue (Siegling et al., 2014). The negative relationship between cognitive ability
and tenure can explain why even though cognitive ability was not directly related to
leadership, it emerged as a significant predictor in the regression model, with the effect
of tenure controlled. A plausible explanation is that employees with higher cognitive
ability advance to higher positions faster or move onto other jobs sooner. Tenure in this
study referred to the number of years employees were in their present position, hence the
negative relationship with cognitive ability. Although leadership and management are not
interchangeable (Lunenburg, 2011), they are overlapping concepts (Young & Dulewicz, 2008).
Therefore, the results reported in this study are consistent with those reported in the
parallel article, wherein UK managers also showed higher trait EI than the standardization
sample (Siegling et al., accepted). While these findings require replication on other
samples and industries, they provide initial evidence to suggest that the range of
personality traits linked to emotions is fundamental in occupational roles involving the
supervision of, and responsibility for, others.


<h>REFERENCES</h>
----------

  [2] Julian Barling, Frank Slater, E. Kevin Kelloway. Transformational leadership and emotional intelligence: an exploratory study. doi:10.1108/01437730010325040
  [3] Jan Derksen, Ingrid Kramer, Michael Katzko. Does a self-report measure for emotional intelligence assess something different than general intelligence?. doi:10.1016/S0191-8869(01)00004-6
  [4] H. Harald Freudenthaler, Aljoscha C. Neubauer, Petra Gabler, Wolfgang G. Scherl, Heiner Rindermann. Testing and validating the trait emotional intelligence questionnaire (TEIQue) in a German-speaking sample. doi:10.1016/j.paid.2008.07.014
  [5] Timothy A. Judge, Joyce E. Bono, Remus Ilies, Megan W. Gerhardt. Personality and leadership: A qualitative and quantitative review. doi:10.1037/0021-9010.87.4.765
  [7] Barbara Mandell, Shilpa Pherwani. Relationship between emotional intelligence and transformational leadership style: A gender comparison. doi:10.1023/A:1022816409059
  [8] Alexandra Martins, Nelson Ramalho, Estelle Morin. A comprehensive meta-analysis of the relationship between Emotional Intelligence and health. doi:10.1016/j.paid.2010.05.029
  [9] Sampo V. Paunonen, Michael C. Ashton. Big five factors and facets and the prediction of behavior. doi:10.1037/0022-3514.81.3.524
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  [14] A. B. Siegling, Mireille Sfeir, Hedley John Smyth. Measured and self-estimated trait emotional intelligence in a UK sample of managers. doi:10.1016/j.paid.2014.01.027
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<ART>Uncharted features and dynamics of reading: Voices, characters, and crossing of experiences
================================================================================

Authors: Ben Alderson-Day, Marco Bernini, Charles Fernyhough
DOI: 10.1016/j.concog.2017.01.003
Year: 2017  |  Pages: 98-109
ASJC codes: 3204, 3205
Keywords: Creativity, Hallucinations, Imagery, Inner speech, Theory-of-mind

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Readers often describe vivid experiences of voices and characters in a manner that has been likened to hallucination. Little is known, however, of how common such experiences are, nor the individual differences they may reflect. Here we present the results of a 2014 survey conducted in collaboration with a national UK newspaper and an international book festival. Participants (n = 1566) completed measures of reading imagery, inner speech, and hallucination-proneness, including 413 participants who provided detailed free-text descriptions of their reading experiences. Hierarchical regression analysis indicated that reading imagery was related to phenomenological characteristics of inner speech and proneness to hallucination-like experiences. However, qualitative analysis of reader's accounts suggested that vivid reading experiences were marked not just by auditory phenomenology, but also their tendency to cross over into non-reading contexts. This supports social-cognitive accounts of reading while highlighting a role for involuntary and uncontrolled personality models in the experience of fictional characters.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Vivid or immersive experiences are often described in relation to reading fictional
narratives (Caracciolo & Hurlburt, 2016; Green, 2004; Ryan, 1999, 2015). In particular, it
seems common for readers (and writers) to report “hearing” the voices of fictional
characters, in a way that suggests they have a life of their own (Vilhauer, 2016; Waugh,
2015). What, though, does this mean for the psychological processes that may underpin such
experiences? Psychological studies on the phenomenological experience of reading have
tended to focus on two strands: first, the perceptual and sensory qualities of reading –
primarily via notions of ‘voice’ and inner speech (Alexander & Nygaard, 2008; Perrone-
Bertolotti, Rapin, Lachaux, Baciu, & Lœvenbruck, 2014); and second, how the reader
represents the characters and agents of a text (Kidd & Castano, 2013; Mar & Oatley, 2008).
To a certain extent, it is intuitive to understand why a text – even if not read out loud
– would need to be voiced in some way to be read. This is sometimes conceptualized either
as inner speech – namely, the various ways in which people talk to themselves (Alderson-
Day & Fernyhough, 2015) – or more broadly in terms of auditory imagery, i.e. purposefully
imagining the qualities of characters’ or narrators’ voices (Hubbard, 2010; Kuzmičová,
2013). Evidence of inner speech involvement comes from psycholinguistic studies on
reading: when we read, phonologically longer stimuli take longer to read than shorter
stimuli of the same orthographic length (Abramson & Goldinger, 1997; Smith, Reisberg, &
Wilson, 1992), while acoustic properties of one’s own voice, such as accent, can affect
our expectation of rhyme and prosody (e.g., Filik & Barber, 2011). This suggests that at
least some properties of text are sounded out in inner speech during reading (Ehrich,
2006). Readers’ expectations of character and narrator voices can also affect how a text
is processed. For instance, readers adjust their reading times for texts written by
authors with a slow or fast-paced voice. People reading difficult texts, and those who
report more vivid mental imagery, show greater evidence of such “author voice” effects on
reading speed (Alexander & Nygaard, 2008). When characters’ words are referred to in
direct speech, voice-selective regions of auditory cortex are more active than during
indirect reference (e.g., ‘He said, “I hate that cat”’ vs. ‘He said that he hates that
cat’), suggesting auditory simulation of character’s voices (Yao, Belin, & Scheepers,
2011). Evidence of inner speech and auditory imagery being involved in reading is
consistent with broader theories of reading that place perceptual simulation and
embodiment at the heart of textual comprehension (Zwaan, 2004; Zwaan, Madden, Yaxley, &
Aveyard, 2004), i.e. the idea that sensorimotor imagery processes are automatically
engaged when we read text, as part of understanding the meaning of what is being
described. A second strand of research has emphasized the role of social cognition in the
reading experience, largely in response to literary fictional texts. Many readers strongly
personify characters and narrators by making inferences about their described thoughts and
behaviors (Bortolussi & Dixon, 2003) and assigning them intentionality (Herman, 2008).
Studies on empathy in literary experiences have focused on how empathetic engagement with
characters is triggered by specific discourse strategies (e.g., first-person vs. third-
person narratives; Keen, 2006) or on how empathy in the act of reading relies on readers’
previous personal experiences (Kuiken, Miall, & Sikora, 2004; Miall, 2011). Other
psychological approaches to reading have investigated the “projection” of knowledge that
readers perform – the process by which they assign to each character an individual
epistemic view of the narrative world (Gerrig, Brennan, & Ohaeri, 2001), which allows for
narrative dynamics such as “suspense” (Gerrig, 1989). Based on such processes, it has been
argued that the ways in which readers attribute consciousness, mental states, intentions,
and beliefs to characters recruits (Zunshine, 2006, 2012) or even enhances (Kidd &
Castano, 2013) readers’ theory-of-mind, i.e. the ability to represent the mental states of
others. Indeed, it has been claimed that the “function” of reading fiction may be to
simulate social experiences involving other people (Mar & Oatley, 2008). Taken together,
the above studies highlight some of the separate perceptual and social-cognitive processes
that could explain accounts of ‘hearing’ the voices of characters. But, although the
experiences they are based on are intuitively familiar, phenomenological data on the
reading experience in the words of readers themselves is surprisingly lacking. Indeed,
almost all of the above work has involved either experimental manipulation of texts, or
analysis of responses to specific literary texts. Systematic surveys of readers’
experiences of characters in general – that is, as part of their day-to-day experience of
reading for pleasure – are largely absent. We know of only one recent exception: Vilhauer
(2016) conducted a qualitative analysis of 160 posts that resulted from a search of
‘hearing voices’ and ‘reading’ from a popular message-board website (Yahoo! Answers). Of
these, over 80% reported vivid experiences when reading, the majority describing specific
auditory properties including volume, pitch, and tone. Qualities that are perhaps more
indicative of social representation – such as identity and control – were also reported in
some cases, but were often hard to classify or lacking in detail. However, the open-ended
structure of the source material used by Vilhauer (2016), the fact that it was gathered
based on the specific keywords ‘hearing voices’, and the lack of demographic data from the
study participants limit any strong generalizations about the reading experience. As such,
it is unclear whether vivid examples of characters’ voices – or indeed other kinds of
character representation – are actually a common part of the reading experience. It could
be that the act of reading about characters simply involves combining such features in an
additive and largely automatic way: if so, phenomenological reports may be expected to
consist of vivid perceptual imagery plus some kind of mental state representation – a
clear experience of a character’s voice and their emotional state, for example. But such
skills also vary considerably in the general population (Isaac & Marks, 1994; Palmer,
Manocha, Gignac, & Stough, 2003) and may not be integral for most people, most of the
time: for some, experiences of voices, characters, or other features of a text could
combine to create something very different entirely, or even nothing at all (a character’s
voice without any impression of intentionality, for example). To investigate this
question, we collaborated with the Edinburgh International Book Festival and a national UK
newspaper (the Guardian), to survey a large sample of readers about their inner
experiences. Instead of focusing on the experience of a particular text (e.g., Miall &
Kuiken, 1999), or experimentally varying textual properties (Dixon & Bortolussi, 1996), we
opted for a general questionnaire about readers’ encounters with voices and characters.
This encompassed all kinds of reading (prose vs poetry; crime fiction vs historical
novels; or fictional vs non-fictional narratives), although the large majority of eventual
responses related to engaging with fiction (82%). The first aim of the survey was to
gather quantitative information on the vividness of readers’ experiences, and examine how
that related to other individual differences in potentially similar processes. Based on
the putative involvement of inner speech in reading, we included a measure of everyday
inner speech experiences: the Varieties of Inner Speech Questionnaire (VISQ: McCarthy-
Jones & Fernyhough, 2011). Derived from developmental theories of self-talk (Vygotsky,
1987), the VISQ measures a range of phenomenal properties of inner speech, including the
extent to which it includes dialogue, if it is experienced in full sentences, whether it
is evaluative or motivating, and whether it includes other people’s voices. If readers
were more likely to report vivid experiences of voice and character during reading, they
might also be expected to have a more vivid experience of their own inner speech in
general. In addition, vivid experiences of voices and characters during reading have been
likened by some (e.g., Vilhauer, 2016) to be similar to actual experiences of ‘hearing
voices’ or auditory verbal hallucinations (AVHs). Although direct parallels with florid
and distressing experiences are unlikely, traits towards having unusually vivid and
hallucination-like experiences are thought to exist along a continuum in the general
population (Johns & van Os, 2001). They may, therefore, relate to reports of particularly
vivid reading experiences. To investigate this further, we included a short measure of
auditory hallucination-proneness (the Launay-Slade Hallucination Scale – Revised; Bentall
& Slade, 1985). We predicted that participants with more vivid experiences of reading in
general would also be more prone to hallucination-like experiences. Our second aim was to
qualitatively explore readers’ own descriptions of voice and character, via a free-text
section of the survey. Such descriptions offer a nuanced and detailed picture of the inner
experience of reading that might otherwise be lost in purely quantitative approaches to
the topic. Many of the previously mentioned studies have focused on a very specific aspect
of reading (activation of inner speech, auditory imagery, mental imagery, empathy for
characters, projection of knowledge, etc.) without attempting a unified account of how all
these aspects relate to each other and trigger other, richer processes. To address this,
readers’ descriptions in our study were coded in terms of representational features of the
experience (such as the different sensory modalities involved), but also their dynamics,
namely the processes by which the experiences seemed to occur. While this analysis was
primarily driven by the main themes apparent in the data, our descriptions in some cases
required the creation of new terms or their importing from narratological and linguistic
research on fictional narratives. For example, here we have used the term “mindstyle” – a
concept borrowed from linguistics (Fowler, 1977; McIntyre & Archer, 2010; Semino, 2007) –
to refer to the unique way in which a person or character thinks about and views the
world, and an idea that is clearly relevant for social simulation accounts of the reading
experience. This and other terms used in the coding are expanded on below.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were invited to take part in an online survey on readers’ inner voices via a
series of blogposts for the Books and Science sections of the Guardian website (‘Inner
Voices’), publicity at the Edinburgh International Book Festival (EIBF) 2014, social
media, and a project website (www.hearingthevoice.org). A total of 1566 participants (75%
F/24% M/1% Other; Age M = 38.85y, SD = 13.48y, Range 18–81) took part in the survey, with
responses primarily coming from English-speaking countries (UK, USA, Australia, Ireland,
and Canada; see Table 1 for demographic details). Participants were also asked to indicate
their level of education and their general reading preferences. This indicated that the
sample had a high level of educational achievement on average (over 80% possessing a
graduate degree or higher), with the most popular reading preferences being for general
fiction, literary classics, and historical fiction. The survey was live for 6 weeks, and
all procedures were approved by a local university ethics committee.

<hs>  Measures</hs>
  ~~~~~~~~

The survey was divided into two parts. Section 1 – the Readers’ Imagery Questionnaire –
specifically asked about participants’ vivid experiences of voices and characters during
reading. Section 2 included the questionnaire items on inner speech and auditory
hallucination proneness.

        <hss>Reading imagery questionnaire</hss>

        A reading imagery questionnaire was devised specifically for the present study
        based on commonly used measures of imagery, including Betts’ Questionnaire upon
        Mental Imagery (Sheehan, 1967) and the Vividness of Visual Imagery Questionnaire
        (Marks, 1973). It consisted of five items, each answered on a 5-point Likert scale
        (see Table 2): Do you ever hear characters’ voices when you are reading? Do you
        have visual or other sensory experiences of characters when reading? How easy do
        you find it to imagine a character’s voice when reading? How vivid are characters’
        voices when you read? Do you ever experience the voices of characters when not
        reading? To elicit more phenomenological detail about the experience, a further
        question asked: ‘If you feel that you have had particularly vivid experiences of
        characters' voices, please describe them in the box below’. Responses up to a
        500-word limit were allowed. Qualitative analysis was then conducted on the
        readers’ responses to this question specifically (see below).

        Varieties of inner speech questionnaire (VISQ: McCarthy-Jones & Fernyhough, 2011)

        The VISQ includes 18 items on the phenomenological properties of inner speech. It
        includes four subscales: dialogic inner speech (e.g., ‘I talk back and forward to
        myself in my mind about things’); evaluative/motivational inner speech (‘I think
        in inner speech about what I have done, and whether it was right or not’); other
        people in inner speech (‘I hear other people’s voices nagging me in my head’); and
        condensed inner speech (‘I think to myself in words using brief phrases and single
        words rather than full sentences’). Participants rated their agreement with these
        statements on a 6-point Likert scale ranging from “Certainly does not apply to me”
        to “Certainly applies to me”. Each subscale has good internal and test-retest
        reliability (Alderson-Day et al., 2014; McCarthy-Jones & Fernyhough, 2011).

        Launay-Slade hallucination scale – revised (LSHS: Bentall & Slade, 1985)

        A short version of the LSHS was used to assess susceptibility to auditory
        hallucinations. Five items that specifically related to unusual auditory
        experiences were selected from the Revised Launay Slade Hallucination Scale used
        in Morrison, Wells, and Nothard (2000), for example: ‘I hear people call my name
        and find that nobody has done so’. Participants indicate their agreement on a
        4-point scale ranging from ‘Never’ (1) to ‘Almost Always’ (4). Data on the 5-item
        version reported by McCarthy-Jones and Fernyhough (2011) and Alderson-Day et al.
        (2014) have shown the scale to have moderate/good internal reliability (Cronbach’s
        alpha >0.69). As part of a separate study, participants also completed
        questionnaires on inner speech frequency and imaginary companions. While this will
        be fully reported elsewhere, here we have included some preliminary data on inner
        speech frequency that corroborates the other, agreement-based VISQ results (see
        Footnote 2).

<hs>  Quantitative analysis & qualitative coding</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A mixed methods approach was used to (i) analyse the relations between questionnaire
measures collected in Sections 1 and 2, and (ii) qualitatively code free-text responses
given at the end of the Readers’ Imagery Questionnaire. Questionnaire answers to Sections
1 and 2 were analysed using Spearman’s Rho correlation co-efficients (due to non-normal
distributions in some of the questionnaire outcomes) and hierarchical regression analysis,
using total score for reading imagery as the dependent variable. A Bonferroni correction
was applied to all pairwise correlations tested to avoid inflated type 1 error incurred
from multiple comparisons. Missing questionnaire responses were replaced with the mean per
item. Free-text responses from Section 1 were coded using an inductive thematic analysis
(Braun & Clarke, 2006). Two raters (BA-D and MB) first independently devised a series of
descriptive codes from the entire dataset. Codes were then discussed, refined, and applied
to 20% of the dataset for parallel coding by each rater, before independent coding of the
remainder. Inter-rater reliability for coding was high (k = 0.82). The coding scheme
classified answers in two ways: firstly, for their general features, including presence of
specific sensory properties; and secondly in terms of dynamics, or descriptions of the
overall experience and imaginative process described by the reader. Although each response
could only receive each code once (e.g., descriptions of experiences with multiple visual
features nevertheless only received one visual code), any given answer could be classed as
having several different features and dynamics. Along with the term “mindstyle”, our novel
codes included “blending”, a term used by Fauconnier and Turner (2003) to denote the
mixing of concepts from multiple domains to form new combinations (as in, for example, the
creation of novel imagery). In contrast, “experiential crossing” is a new term that we use
here to refer to instances of voices and characters being experienced beyond the immediate
context of reading. A full list of codes is provided in Table 3. Unless otherwise
indicated, all italicization in example quotes has been added by the authors to illustrate
how specific content relates to specific codes allocated. For clarity, all references to
book titles have been placed in inverted commas.

<hs>  Readers’ experiences of voices and characters: summary data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Less than 1% of responses were left blank in Section 1 (the Reading Imagery Questionnaire;
RIQ). Table 2 shows the frequency of response for each of the questions on vivid reading
experiences. Most participants reported hearing characters’ voices when reading at least
some of the time, with over half (51%) hearing them most or all of the time (Q1). Visual
and other sensory experiences were endorsed to a similar degree (Q2). Approximately two
thirds of participants described it as being fairly or very easy to imagine characters’
voices when reading (Q3), while the vividness of voices varied from being vaguely present
to being as vivid as listening to an actual person (Q4). Experience of characters’ voices
outside of reading was, in contrast, relatively rare: a fifth of participants described
this experience happening sometimes, but less than 4% of participants reported this
happening most or all of the time (Q5).

<hs>  Relations between reading experiences, inner speech, and auditory hallucination-proneness</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Within the sample, 1522 participants also completed measures of inner speech (the VISQ)
and hallucination-proneness (the LSHS). Less than 3% of responses were left blank. As the
internal reliability of the five RIQ items was good (Cronbach’s alpha = 0.80), scores
across the five items were summed to provide a total score of readers’ susceptibility to
vivid reading experiences. Correlational analysis indicated that total score on the RIQ
was positively related to auditory hallucination-proneness (r = 0.25), other people in
inner speech (r = 0.38), dialogic inner speech (r = 0.23), and evaluative/motivational
inner speech (r = 0.20, all p < 0.001, Bonferroni corrected). Reading scores also
negatively correlated with condensed inner speech (r = −0.13), i.e. participants with more
expanded than condensed inner speech also had more vivid reading experiences. When these
factors were assessed in a hierarchical regression model, only a subset of predictors was
retained (see Table 4). Using total score on the reading items as the dependent variable,
Age, Gender,2 and Education Level were included as control predictors in block 1, followed
by each of the VISQ subscales and total score on the LSHS. The final model significantly
predicted total RIQ score (F = 43.06, p < 0.001) accounting for 18% of the variance.
Significant predictors retained by the model were: LSHS (p < 0.001, β = 0.11); dialogic
inner speech (p < 0.001, β = 0.11); other people in inner speech (p < 0.001, β = 0.30);
and condensed inner speech (p < 0.001, β = −0.09). Age, gender, education level, and
evaluative inner speech were all non-significant (gender: p = 0.08, all other p > 0.50).3

<hs>  Reader’s experiences: detailed qualitative descriptions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Further description of reading experiences was provided by 413 participants. Free text
responses ranged from 1- to 320-word answers (answer length M = 41.71 words, SD = 35.26
words).

        <hss>Features</hss>

        As may be expected, descriptions of hearing characters’ voices and references to
        specific characters were very common, occurring in 291 cases (70%). Many
        participants reported a strong and vivid engagement with the characters of a text.
        For example, one participant stated [emphasis added throughout]: I become so
        engrossed in a novel that the characters become real to me. I know that they are
        not real, but they feel real. It is as vivid as watching the characters in a film
        on TV where the screen is my mind's eye. In fact, if I can't hear the characters'
        voices, I find it impossible to carry on reading the novel because it is the vivid
        experience of characters' voices (or sometimes the author's “voice”) that I want
        when I read a novel. Characters, however, were not the only voices present,
        despite the questionnaire focusing on characters specifically. 49 participants
        (12%) described vivid perceptions of the author and/or narrator’s voice in a text.
        For example: There are times when reading, that the narrative draws me in such
        that the words are no longer words just the world they describe. But in a few
        cases, a narrator’s voice comes through, almost as if one was listening to someone
        reading it […] Well composed dialogue often creates a sense of 'listening' to a
        real conversation with varied tones and accents for me. I can also feel as if a
        strong first person narrative voice is “speaking” fully to me […]. Auditory
        characteristics of voices were reported in the large majority of cases. In 80
        cases (19%) this involved the specific mention of accents without any reference to
        other auditory properties: I can hear male and female, young and old, accents that
        I can't speak myself [….] When I read books whose characters are English,
        Scottish, Irish, or any of the strong American dialects, I hear them speaking with
        that dialect – even without relying on the author's use of it in writing what they
        say. No other specific auditory properties were mentioned as regularly (hence they
        are grouped under the general “auditory” code). Auditory characteristics described
        in 250 cases (61%) included references to volume, tone, and speed of speech: I can
        hear the tone and voice inflexions depending on what the character is saying.
        Usually the tone is distinct, particular words may be over-pronounced or roll
        together excitedly. Depending on the situation, if the character becomes stressed
        or scared for e.g., the voice changes pitch and speed… For 76 cases (18%), the
        experience of a character did not consist in the quasi-sensory perception of their
        voice, but rather their manner of speaking, thinking, and experiencing the world –
        i.e. their mindstyle (Fowler, 1977): It's not only the pitch or sound, but the
        rhythm of the speech, and the character's emotion and movement I get, it's the
        whole package, as if I'm watching a film or in the same space. With certain
        favourite books, which I have reread a number of times, I feel I can hear […], the
        intonation, the way in which they would speak phrases from the text but also their
        responses to other situations and problems. Visual characteristics were described
        in 57 cases (14%). In many cases this was described as an immersive, cinematic
        experience: Every good book I read that I get in depth with, plays like a movie, I
        don’t really realize it while I’m reading but when I stop I go to find where I’m
        up to in the book and I don’t recognise reading the words but I know and have
        “heard” and “ seen” what has happened. Other feelings, such as tactile or
        olfactory experiences, were also described in a smaller proportion of cases (47
        participants; 11%): Lyra whispering to Will in Pullman's “His Dark Materials”. He
        describes the loud, busy closeness of her whisper, and I could hear it and feel it
        on my neck. It feels like I'm sharing the surroundings with the characters or
        simply experience the landscape, weather, smells, touch, sounds etc.

        <hss>Dynamics</hss>

        While almost all responses provided some information of the features of vivid
        reading experiences, not all answers could be coded with a specific dynamic. In
        those that could be classified in such a way (281 participants; 68%), the dynamics
        of vivid reading experiences were very varied. The first dynamic coded was
        internal blending, or the process of adapting one’s own inner voice to represent a
        particular character or narrator. Twenty-two participants (5%) referred to
        “putting on the voices rather than hearing separate people” or that voices were
        similar to their own in some way, e.g.: I think the voice is a version of mine
        usually. I probably overlay class, accent etc. Howard Roark in “The Fountainhead”
        spoke very calmly and cooly but it was not very different from my own. More common
        was a kind of external blending, occurring in 62 cases (15%). In this,
        participants drew on their experience of others’ voices to simulate a character
        (often usually a friend, relative, or actor from an adaptation). The voice of
        Zooey in Salinger's “Franny and Zooey” always sounds like a friend of mine who
        shares many of Zooey's character traits, including a resonant voice. If the book
        has been made into a film then I would tend to hear the actor's voice. Even if I
        read the book first, the actors would generally override anything I might
        originally have imagined. Slightly more frequent than both, however, were
        responses in which the experience of characters’ voices (or thoughts) appeared to
        break across into new situations, outside of the immediate experience of reading.
        77 cases (19%) described this experiential crossing of voices: If I read a book
        written in first person, my everyday thoughts are often influenced by the style,
        tone and vocabulary of the written work. It's as if the character has started to
        narrate my world. Whenever I'm reading a novel I always hear the characters
        talking even while not reading. They continue a life between bouts of reading. In
        some cases this was experienced just as a continuation from reading the book; as
        in one participant’s description of reading Virginia Woolf: Last February and
        March, when I was reading “Mrs. Dalloway” and writing a paper on it, I was feeling
        enveloped by Clarissa Dalloway. I heard her voice or imagined what her reactions
        to different situations. I'd walk into a Starbucks and feel her reaction to it
        based on what I was writing in my essay on the different selves of this character.
        In others this crossing was specifically prompted by familiar or new but similar
        contexts, i.e. the characters would appear when it would be consistent with their
        own persona or surroundings: The character Hannah Fowler, from the book of the
        same name was the voice I heard while walking with my family in the area of
        Kentucky (USA) where the book took place. I loved the book and heard her dialogue
        as I walked through the woods.[ …] Other than this, participants would often
        describe their experience of voices and characters in general, non-specific terms
        that implied an intentional imaginative construction of characters and scenes.
        This inner simulation occurred in 77 cases (19%), e.g., I see the book as a movie
        and I am barely aware of the pages. I hear voices, music, and other sounds as
        described by the author or imagined by me…. I can visualize and imagine what the
        characters sound and look like. The voices, how they express themselves, verbally
        and non-verbally. A small number of responses (19 cases; 5%) also described a
        specific sense of voices “fitting” characters in particular ways, or failing to
        fit following depiction by an actor or narrator. This dissonance of voices could
        in some cases noticeably interfere with enjoyment of the text. One participant,
        for example, stated that their experience of voices was: Vivid enough that when I
        hear an author speak, I am often surprised how different they sound than the
        “narrator” in my head. It's the same with films; characters often sound “fake”
        compared to how I have imagined them. Finally, 24 responses (6%) appeared to
        describe actual hallucinatory phenomena. Many of these described states in which
        hallucinations are relatively common, such as in the transition to and from sleep.
        I have hypnagogic sleep, so will sometimes hear an actual voice whilst falling
        asleep or awakening, which can be related to what I've been reading before sleep.

<h>DISCUSSION</h>
----------

The aim of the present study was to survey phenomenological qualities of voices and
characters in the experience of readers. Our results indicated that many readers have very
vivid experiences of characters’ voices when reading texts, and that this relates to both
other vivid everyday experiences (inner speech) and more unusual experiences (auditory
hallucination-proneness). However, the features and dynamics of readers’ descriptions of
their voices were varied and complex, highlighting more than one way in which readers
could be said to “hear” the voice of specific characters. This included quasi-perceptual
events across a variety of sensory modalities; personified, intentionally and cognitively
rich agents; and characters that both triggered and echoed previous experiences and extra-
textual connections. On the RIQ, the large majority of participants often “heard”
character’s voices when reading, with visual and other experiences also occurring
frequently. Most found it very easy to imagine characters’ voices during reading, but the
vividness of this varied considerably: 1 in 7 participants reported voices that were as
vivid as hearing an actual person speak, but double that proportion described either no
voices being present or only vague experiences of voice. As such, the experiences reported
here should be considered particularly vivid examples of auditory mental imagery, in line
with an experiential – and not merely propositional – view of imagery (Kosslyn, Thompson,
& Ganis, 2006). This is broadly consistent with inner speech and perceptual simulation
accounts of reading (Engelen, Bouwmeester, de Bruin, & Zwaan, 2011; Zwaan et al., 2004).
However, it would appear to largely fall short of indicating that participants were having
literally auditory experiences during reading. This contrasts, for example, with
Vilhauer’s (2016) survey, which heavily emphasized such features (e.g.,“An overwhelming
majority of [participants] indicated that inner reading voices were audible”, p. 5). We
note that the accounts collected in that survey represented a subset of participants who
were describing reading experiences after having already referred to “hearing voices”,
suggesting that auditory phenomenology (and more specifically, literal hallucinatory
experiences or potential psychopathology) may be over-represented in Vilhauer’s (2016)
sample. The relevance of inner speech to this topic is emphasized by the observed
relations between the overall vividness of reading experiences and individual differences
in the ongoing internal self-talk reported by participants. Regression analysis indicated
that participants who reported more elaborate inner speech on the VISQ – being expanded in
form, containing dialogue, and the voices of others – were those who also had more vivid
experiences of voices and characters during reading. This is a unique demonstration (in
terms of empirical research) of the more positive and valuable correlates of
phenomenologically diverse inner speech, which in prior studies has correlated with
anxiety, depression, low self-esteem, and unusual experiences (McCarthy-Jones &
Fernyhough, 2011). Notably, evaluative inner speech – which is linked to low self-esteem
(Alderson-Day et al., 2014) – was not significantly associated with reading imagery on the
RIQ, once other inner speech and demographic factors were controlled for. It could be that
evaluative aspects of inner speech, if present, are more closely linked to negatively-
valenced moods and processes (such as rumination; Jones & Fernyhough, 2009), while other
features of inner speech may reflect more general imaginative capacities, as indexed by
the RIQ used here. The other factor relating to reading imagery was auditory
hallucination-proneness (i.e. LSHS), despite the fact that relatively few participants
reported character voices that were as vivid as hearing another person speak. While it is
possible that these experiences may nevertheless be linked on a continuum of quasi-
perceptual phenomena, the qualitative analysis of readers’ accounts sheds some light on
what may link these experiences. Descriptions of vivid auditory imagery were common, but
the ways in which this was experienced were highly varied: for some participants this was
an intentional, constructive process, for others an automatic immersion, and for others
again an experience that appeared to seep out into other, non-reading contexts. For
example, one notable way in which participants talked about their experience of characters
was via what we termed “experiential crossing”. We coined this term to refer to instances
of characters and voices being experienced outside of the context of reading; a phenomenon
that as far as we know has never been studied either in psychological or narratological
research. The presence of experiential crossing in nearly a fifth of participants points
towards a perfusion of voice- and character-like representations that apparently
transgress the boundary between reading and thought. In some cases this was described
almost as an echo of prior reading experiences, with auditory imagery re-emerging in a
particular context or scenario, but in other accounts it appeared to shape the readers’
style and manner of thinking – as if they themselves had been changed by a character.
Indeed, one discontinuity between experiential crossing and other kinds of dynamic
observed in readers’ accounts was the preponderance of fictional characters’ thoughts and
feeling over specifically perceptual elements – what was coded as their mindstyle (Fowler,
1977; McIntyre & Archer, 2010; Semino, 2007). These readers were engaged with a range of
complex cognitive faculties, from beliefs and behavioral patterns to feelings and
perceptual biases, with a particular emphasis on the emotional states of characters. All
of these become part of the readers’ construction of a fictional consciousness or a
“consciousness frame” (Palmer, 2004): a kind of schema for the characters’ worldview and
inner experience. This extensive degree of personification that readers process and
project into the text can be seen as the counterpart of personifying processes occurring
in the writers’ encoding of fictional minds (Taylor, Hodges, & Kohányi, 2003). Thus, one
alternative overlap between vivid reading experiences and hallucination-proneness may lie
less in auditory phenomenology and more in the uncontrolled experience of another’s point-
of-view; the mindstyle of a character shaping or overlaying the everyday thoughts and
feelings of the reader; the social rather than the perceptual. On the one hand this is
consistent with accounts of auditory verbal hallucinations that emphasize their intrusive
and uncontrollable nature (Badcock, Waters, Maybery, & Michie, 2005) along with their
social and agentic characteristics (Wilkinson & Bell, 2016). On the other hand, this would
also be consistent with psychological approaches to reading fiction that highlight its
interrelation with theory-of-mind (Kidd & Castano, 2013; Mar, Oatley, & Peterson, 2009),
and in particular empathy (Mar & Oatley, 2008). One caveat, however, is that accounts of
both mindstyle and crossing were described less like controlled simulations of others’
minds, and more like a habit of thinking or expectation of what a character would say in a
given situation. If so, this is arguably more similar to the generation and maintenance
over time of personality models and agents (Hassabis et al., 2014) than a deliberate and
focused act of empathizing or reasoning about another’s mental state (Djikic, Oatley, &
Moldoveanu, 2013). One could speculate that the creation of such a ‘consciousness frame’
serves to blur the lines between self and other, leading to the cross-activation of
fictional experiences in the reader’s actual world. The notion of experiential crossing
could also be seen as a counterpart to the more widely studied relationship between mental
simulation and reader’s previous experiences. If, in experiential crossing, experiences
move from the fictional to the real, simulation during reading is activated and supported
by the reader’s previous experiences of real-world scenarios – an experiential baggage
that has been referred to previously as “repertoire” (Iser, 1980), “encyclopedia”
(Dolezel, 2000; Eco, 1984), or “experiential background” (Caracciolo, 2014; Herman, 2004).
The creation of such repositories of real-world experiences bears similarities with
simulation theories of social cognition that propose the construction of a biographical
database on which judgements about other minds are based (Harris, 1992). For example,
Green (2004) found that undergraduate participants with personal experience or knowledge
of the key themes of a story (a homosexual man attending a university reunion) reported
greater transportation into the story and, correspondingly, tended to have beliefs that
were consistent with the story ideas. A recent study by Chow et al. (2015) has also found
preliminary evidence that past experience of particular scenes and actions directly
modulates functional connectivity of visual and motor brain areas during story
comprehension. The role of prior knowledge and experience was most evident in readers’
accounts of internal and external blending of voices, in which participants described
drawing on their own voice or others’ to create the voices of characters in the text. In
blending, readers seemed to integrate, or “compress” (Turner and Fauconnier & Turner,
2003), their own voice with a textually cued voice (internal blending) or a textual voice
with an external source (external blending). The potential differences between internal
and external blending remain to be explored: internal blending may depend on personal
identification with characters, while external blending, in contrast, could involve an
almost unconscious selection of external sources, based on their similarities with the
character as described (e.g., in the behavior, beliefs, bodily features, and so on). The
fact that – for some participants – the eventual voice could definitely be “right” or
“wrong” (as described in cases of dissonance) suggests that representations of characters
are quite robust once they are formed. What role character tropes, stereotypes, and
prototypes play in this process will be an important avenue of future investigation.

<hs>  Limitations</hs>
  ~~~~~~~~~~~

It is important to acknowledge some limitations of the present study. First, it is
dependent on participants’ self-reports about their general reading experience, which
contrasts with experimental approaches that use specific texts and more objective methods
of reading engagement (such as eye-tracking). What these data can say about the readers’
experiences of voices and characters is therefore limited by the ability of readers to
report on their experiences accurately, and what experiences they choose to describe. Some
have argued that readers cannot be relied upon to report on their own experiences
accurately and reliably (see Caracciolo & Hurlburt, 2016, for a discussion), but it should
be noted that a large body of psycho-narratological work on fiction ultimately depends on
participants’ self-reported responses to a story, or other individual differences (e.g.,
Green, 2004; Mar et al., 2009). Moreover, our intention here was to survey the general
reading experience for voices and characters, rather than select a specific text.
Individual texts may be particularly evocative of those qualities, but they do not
necessarily say anything about how common such experiences are in general reading. Second,
in addressing the question of how readers may be said to “hear” the voices of characters,
our study specifically used those terms (voice and character) to probe participants’
experiences. Similarly, our choice of other measures to include reflected this focus, as
inner speech and hallucination-proneness are prima facie factors that were important to
consider. The consequences of this are twofold: (a) it may have led participants to
describe predominantly auditory and agent-like experiences over other, more vivid factors
(such as visual environments), and (b) it means that other potentially relevant factors,
such as transportation and absorption (Kuiken et al., 2004) were not measured here. We
would argue that these data are nevertheless informative to understanding the reading
experience: voices and characters are prominent in psycholinguistic research (Gerrig,
1993) and narratological approaches to reading (Bortolussi & Dixon, 2003; Herman, 2013;
Miall, 2011; Palmer, 2004; Vermeule, 2009), and we note that many of our respondents still
described their experience in a much broader fashion (including narrators, visual imagery,
and tactile sensations). Nevertheless, it will be important for future phenomenological
work to both broaden the scope of inquiry and consider a greater range of individual
differences. The role of scene construction, for example, would be expected to play an
important role in mental simulation during reading. However, with few exceptions (see
“Other”, Table 3) specific references to contextual elements did not feature strongly or
explicitly in readers’ descriptions of voice and character (Hassabis & Maguire, 2009).
Finally, it is important to recognize the nature of the sample surveyed. Having been
promoted by an international reading festival and a newspaper with global readership, the
sample surveyed is much larger and more diverse than most studies of fiction and
narrative, which primarily use undergraduate samples. However the sample is still not
necessarily representative of a general population, as it is likely skewed towards a well-
educated, highly literate readership who may be passionate about fiction (71% reported
enjoying reading classics) but engage very little with other genres (only 4% read books on
sport). It was also completed by three times as many women as men. As such, the extent to
which these results can be generalized to the wider reading population is limited. Despite
these concerns, the present study is to our knowledge one of the only large-sample
phenomenological surveys of the reading experience. We argue that the combination of
questionnaire items concerning vivid reading experiences in general and more detailed,
qualitative analysis of free-text answers offers a broad and varied resource on what it is
like to engage with voices and characters in a text. Accounts of the kind collected here
pave the way for further analysis of the role played by the reader’s “experiential traces”
(Zwaan, 2008) in relation to the simulation of voices and personification. Cases of
experiential crossing, on the other hand, suggest a certain kind of rebound, in which
fictional agents and worlds are activated in real-life scenarios. And while our data
support the existence of vivid voices and characters in the experience of readers, they
ultimately highlight a wide range of quasi-sensory qualities and simulatory dynamics in
the reading process. As in debates on mental imagery (Kosslyn et al., 2006), the reading
processes described here seemed to be highly varied, ‘experiential’ (Fludernik, 1996), and
idiosyncratic. Even if readers’ own accounts are taken as mere indicators of the
underlying cognitive and perceptual phenomena, they suggest that the processes by which
people produce and experience voices and characters could be very different for different
individuals. In this light, the endeavor to describe a typical or normative response to a
text becomes perilous, risking an attempt to control the “entropy” of the real experience
that individual readers are having (Iser, 2001). The voices and characters of a text are
many and various; this would seem to also be true for the reader.


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<ART>Using self-determination theory to promote adolescent girls' physical activity: Exploring the theoretical fidelity of the Bristol Girls Dance Project
================================================================================

Authors: Simon J. Sebire, Joanna M. Kesten, Mark J. Edwards, Thomas May, Kathryn Banfield, Keeley Tomkinson, Peter S. Blair, Emma L. Bird, Jane E. Powell, Russell Jago
DOI: 10.1016/j.psychsport.2016.01.009
Year: 2016  |  Pages: 100-110
ASJC codes: 3202
Keywords: Adolescents, Intervention, Physical activity, Process evaluation, Self-determination theory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Objectives: To report the theory-based process evaluation of the Bristol Girls' Dance Project, a cluster-randomised controlled trial to increase adolescent girls' physical activity. Design: A mixed-method process evaluation of the intervention's self-determination theory components comprising lesson observations, post-intervention interviews and focus groups. Method: Four intervention dance lessons per dance instructor were observed, audio recorded and rated to estimate the use of need-supportive teaching strategies. Intervention participants (n = 281) reported their dance instructors' provision of autonomy-support. Semi-structured interviews with the dance instructors (n = 10) explored fidelity to the theory and focus groups were conducted with participants (n = 59) in each school to explore their receipt of the intervention and views on the dance instructors' motivating style. Results: Although instructors accepted the theory-based approach, intervention fidelity was variable. Relatedness support was the most commonly observed need-supportive teaching behaviour, provision of structure was moderate and autonomy-support was comparatively low. The qualitative findings identified how instructors supported competence and developed trusting relationships with participants. Fidelity was challenged where autonomy provision was limited to option choices rather than input into the pace or direction of lessons and where controlling teaching styles were adopted, often to manage disruptive behaviour. Conclusion: The successes and challenges to achieving theoretical fidelity in the Bristol Girls' Dance Project may help explain the intervention effects and can more broadly inform the design of theory-based complex interventions aimed at increasing young people's physical activity in after-school settings.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Young people become less active during the transition from childhood to adolescence
(Nader, Bradley, Houts, McRitchie, & O'Brien, 2008). Girls are less active and experience
a steeper decline in activity than boys (Nader et al., 2008). In England, the majority of
adolescent girls do not meet the government's recommendations of a minimum of 60 min of
moderate-to-vigorous physical activity (MVPA) per day (Joint Health Surveys Unit, 2013).
As physical activity is associated with physical and mental health (Janssen & Leblanc,
2010), identifying ways to encourage more girls to be active more often is a national
(Department of Health, 2011) and global (World Health Organisation, 2004) health promotion
priority. A recent meta-analysis has shown that physical activity interventions for girls
are more effective if they exclude boys, are delivered at school and are based on an
underlying theory of behaviour change (Pearson, Braithwaite, & Biddle, 2015). Dance is a
popular activity amongst girls (O'Donovan & Kay, 2005) and proliferates contemporary
culture and media consumed by young people such as music TV, talent shows and singing
contests. Dance can be an enjoyable form of cardiovascular exercise in which girls develop
their co-ordination, acquire new skills, work independently and in groups and develop
friendships and self-expression (Australian Women Sport and Recreation Association, 2010).
Dance is an alternative to traditional/competitive sports offered to girls and we have
previously highlighted the potential of a dance-based physical activity intervention for
adolescent girls: the Bristol Girls Dance Project (BGDP) (Jago et al., 2013, 2012, 2011;
Powell, Carroll, Sebire, Haase, & Jago, 2013). The BGDP was a cluster-randomised
controlled trial designed to examine the effectiveness and cost-effectiveness of an after-
school dance-based intervention in increasing the MVPA of Year 7 girls (aged 11–12 years).

<hs>  Theoretical foundations of BGDP</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Underpinning interventions with behavioural theory is hypothesised to increase their
effectiveness (Baranowski, Anderson, & Carmack, 1998; Craig et al., 2008). In addition,
theories allow intervention developers to target activities at theoretically-derived
mediators (Baranowski et al., 1998). The BGDP intervention was based on self-determination
theory (SDT) (Deci & Ryan, 2000; Ryan & Deci, 2007) because its theoretical foundations
are concerned with how the psychological and socio-environmental conditions (e.g., created
by a dance teacher) can support individuals' motivation (Fortier, Duda, Guerin, &
Teixeira, 2012).

<hs>  Motivation quality</hs>
  ~~~~~~~~~~~~~~~~~~

According to SDT, an individual's motivation for a behaviour such as dance, can be more or
less self-determined and six different types of motivation are hypothesised to be
differently associated with behaviours such as physical activity and related cognitive and
affective outcomes (Ryan & Deci, 2007). The more self-determined types of motivation
(i.e., intrinsic motivation, integrated & identified behavioural regulation) are broadly
grouped as autonomous. Intrinsic motivation is based on the inherent satisfaction or
enjoyment that accompanies a given behaviour. The other forms of autonomous motivation are
extrinsic in nature and involve undertaking a behaviour for a reason other than its
inherent satisfaction. Integrated regulation is where a person aligns their engagement in
a behaviour with their broader self (e.g., seeing being active as part of one's identity)
and identified regulation represents motivation which is driven by a valued outcome such
as health benefits or making new friends. The less self-determined types of motivation
(i.e., introjected & external regulation) are broadly grouped as controlled motivations.
Introjected regulation refers to motivation based on internalised pressures such as
avoiding feelings of guilt, whereas external regulation is characterised by prods and
pushes which are external to the person such as complying with demands or avoiding
punishments. Previous research suggests that more autonomous physical activity motivation
is positively associated with child and adolescent physical activity (Owen, Smith, Lubans,
Ng, & Lonsdale, 2014; Sebire, Jago, Fox, Edwards, & Thompson, 2013) and positive
psychological outcomes such as quality of life and physical self-concept (Standage,
Gillison, Ntoumanis, & Treasure, 2012). On the other hand, adolescents' controlled
motivation for exercise has been shown to correlate negatively with health-related quality
of life and functioning within physical, social, school and emotional domains (Standage et
al., 2012).

<hs>  Fostering high quality motivation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A cornerstone of SDT is that autonomous motivation is developed when people feel that
their psychological needs for autonomy (i.e., feelings of volition and free will),
competence (i.e., feeling capable to perform challenging tasks) and relatedness (i.e.,
perceptions of belonging & meaningful connections with others) are fulfilled (Deci & Ryan,
2000). This hypothesis is supported by empirical research among children (Sebire et al.,
2013), adolescents (Van den Berghe, Vansteenkiste, Cardon, Kirk, & Haerens, 2014) and
adult dancers (Quested & Duda, 2010). Within SDT, people's psychological needs can be
supported or undermined by the motivational climate that an authority figure (e.g., dance
instructor) creates through their motivating or teaching style (Deci & Ryan, 2008; Su &
Reeve, 2011). Need supportive styles are underpinned by the provision of autonomy support,
structure and involvement which is reflected in how teachers' (or dance instructors)
conduct their classes and interact with pupils (Haerens et al., 2013; Su & Reeve, 2011).
When teachers provide autonomy support they give meaningful rationales (especially for
tasks which are important but not as enjoyable as others), offer choices which pupils
value, seek and acknowledge pupils' perspectives or ideas and nurture pupils' internal
motivation, interest and enjoyment. In contrast, controlling teachers aim to motivate
pupils by either inducing internal pressures such as guilt, or external pressure such as a
deadline and feedback given and language is used to manipulate rather than be informative.
Such strategies are likely to frustrate rather than support pupils' psychological needs
(Bartholomew, Ntoumanis, & Thogersen-Ntoumani, 2009). Teacher's provision of structure is
primarily related to supporting pupil's competence. A well-structured class is where clear
expectations are set out before tasks and during tasks, guidance, direction and positive
effect-based feedback is given. Without structure, a learning environment can be described
as chaotic where students do not know what they should do or what is expected of them
(Vansteenkiste et al., 2012). Pupils' relatedness is supported when teachers' are involved
by showing the pupils empathy and genuine interest in them (Aelterman, Vansteenkiste, &
Van Keer, 2013; Haerens et al., 2013; Su & Reeve, 2011). In contrast, a lack of
involvement by teachers will frustrate relatedness. Amongst children, Physical Education
(PE) teachers' use of need-supportive styles has been shown to be associated with their
pupils' psychological need satisfaction and autonomous motivation for PE (Ntoumanis &
Standage, 2009; Van den Berghe et al., 2014).

<hs>  Design of the BGDP</hs>
  ~~~~~~~~~~~~~~~~~~

We have previously reported the study protocol (Jago et al., 2013) and outcome paper (Jago
et al., 2015). The study involved 571 Year 7 girls (aged 11–12 years) from 18 schools from
the greater Bristol area allocated at the school-level to intervention (n = 9) and control
(n = 9) arms. The intervention consisted of 40, 75-min after-school lessons that took
place, twice per week for 20 weeks at school and were led by 10 professional dance
instructors between January and July 2014. Girls were provided with a dance diary which
they could complete and hand in to the dance instructor at the end of each lesson, in
which they could record what they had learnt, their feelings and thoughts. Instructors
were provided with a manual which provided plans for all 40 lessons in addition to
training outlined below. One instructor was unable to complete the full intervention and
was replaced at the intervention mid-point with another instructor. One instructor taught
in two schools (ID numbers 21 and 51).

<hs>  Embedding SDT within the BGDP intervention</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

BGDP aimed to increase girls' autonomous motivation for both dance and physical activity
and this was targeted through the BGDP instructor manual, the lesson design and content,
and dance instructor intervention training (Table 1). Dance instructors received a one day
training session (5th December 2013) prior to the start of the intervention (13th January
2014) which included 2 h on SDT (delivered by SJS) highlighting the key features of the
training manual and how the theory could be applied in dance lessons. The content of the
manual and the training focussed on how to provide autonomy, competence and relatedness
support and intertwined involvement and structure as ways to achieve this. Comparisons
were made between using these need-supportive strategies and more controlling practices.
Instructors were given the opportunity to practice using need-supportive techniques by
role-playing different dance activities, asking questions and receiving feedback. At the
mid-point of the intervention, instructors attended a half-day top-up training session
where the SDT components were revisited and instructors shared their experiences of
delivery to resolve any problems.

<hs>  Results of BGDP and the need for a theoretical process evaluation</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The BGDP intervention was not effective in increasing girls' MVPA at the end of the
intervention period when dance lessons were still running or at 12 months after baseline
(Jago et al., 2015). Following the intervention, autonomous and controlled motivation and
perceptions of competence and relatedness were lower among intervention versus control
group participants. This was unexpected and highlighted the importance of using process
evaluation to further understand these findings and the motivational processes at play.
The part of the BGDP process evaluation which focussed on the dose of the intervention
received (i.e. the number of lessons attended) and evaluation of issues pertaining to
attendance and retention identified that between 37 and 40 dance lessons were delivered in
all schools (Sebire et al.,). Attendance (M = 12.8, SD = 7.0) at dance lessons declined
over time and approximately nine girls per school out of a possible 33 received the
intervention dose (defined as two thirds of the lessons offered). Participants enjoyed
taking part and reported social and physical health benefits. Instructors valued the
intervention training and identified that variable attendance challenged delivery but also
facilitated the development of a core group of committed participants. Multiple process
evaluation papers are justified to make full use of all of the data collected (Moore et
al., 2014). Given the large volume of data produced from the detailed process evaluation
of BGDP the aim of this paper is to report a process evaluation of the BGDP study with
particular focus on theoretical fidelity. Process evaluation can play a crucial role in
illuminating how theory-based intervention components are experienced by the participants
and importantly how they are received, interpreted and implemented in practice by
intervention deliverers. The findings can then be used to interpret findings of
intervention effects in greater detail and refine how theory can be best operationalised
in practice. Specifically we sought to use both quantitative and qualitative methods to
evaluate: (a) the degree to which dance instructors adopted a need-supportive style, (b)
participants' perceptions of the dance instructors' teaching practices, (c) participants'
qualitative perceptions of satisfaction of autonomy, competence and relatedness and (d)
dance instructors' experiences of delivering an SDT-based intervention.

        <hss>Qualitative data collection</hss>

        At the end of the intervention and within three weeks of the final dance lesson
        (delivered 11th July 2014), the 10 dance instructors participated in individual
        semi-structured interviews with JMK (mean duration = 67.2 min, range = 41.4 to
        91.4). An interview guide was followed which covered instructors' experiences of
        the intervention training and using the intervention manual (e.g., “Were you able
        to include any of the motivational ideas that were in the manual and training
        day?”), delivering the intervention in a need-supportive way (e.g., What
        strategies did you use to motivate the participants?), their relationship with the
        participants (e.g., What was your relationship with the girls like? Did it
        change?) and the challenges they faced (e.g., What didn't work as well during the
        dance sessions and why?). A focus group was conducted with participants from each
        intervention school (mean duration = 42.4 min, range = 30.4–50.2 min). Girls were
        sampled to reflect tertiles of intervention attendance within each school to
        ensure a range of views were elicited (total n = 59; n = 25 high, 16 moderate & 18
        low attenders respectively) and focus groups ranged in size from 3 to 8
        participants. Of particular relevance to this paper, the focus group topic guide
        explored participants' views on and relationship with the dance instructor (e.g.,
        Is there anything you would change about your dance instructor's teaching style?),
        and perceptions of autonomy, competence and relatedness (e.g., Autonomy: Do you
        think you had some control over what you did? Competence: How did you find the
        dance sessions physically? Relatedness: Did your relationships with one another
        change as the weeks went on?). Importantly, questions aimed at exploring the
        theoretical elements focused on broad topics through which participants were given
        the opportunity to express their views.

            <hss>Observed need-supportive teaching style</hss>

            Dance instructors' fidelity to the need-supportive intervention was assessed
            by rating the delivery of four intervention lessons per instructor which were
            randomly-selected within four intervention blocks (one lesson from each of
            weeks 5–12, 13–20, 21–29 & 30–36). Instructors wore an audio recording device
            on their arm with a microphone attached to their clothing. The observation
            tool developed by Haerens et al. (Haerens et al., 2013) was used. Although the
            tool was originally designed to rate videos of PE teachers, due to ethical
            constraints we adapted the method to combine rating of audio recordings of
            lessons with real-time observation. The instrument contains 21 items measuring
            Relatedness support (5 items), Structure before the activity (5 items),
            Structure during the activity (6 items) and Autonomy support (4 items). One
            item (“encourages pupils to persist”) was excluded based on low validity
            within the validation study (Haerens et al., 2013). Fifteen items were rated
            from the audio recordings as they did not rely on visual observation and five
            items (e.g., Is physically nearby the pupils) were rated by direct
            observation. The frequency of each teaching practice occurring was rated using
            a four-point scale (0 = Never, 1 = Sometimes, 2 = Often, 3 = All the time) for
            each 5-min segment of the lesson. Observations and ratings were undertaken by
            a researcher (JMK) who had discussed the definitions and meaning of the higher
            order constructs and scale items in depth with (SJS) and undertaken a pilot
            observation/rating. JMK and SJS listened to the pilot recording separately,
            then together using the observation tool to guide a discussion of the presence
            of each teaching behaviour in 5 min segments. To check consistency in
            interpretation, six audio recordings (excluding the items requiring visual
            observation) were coded by both (JK) and (SJS). Interrater reliabilities
            (indicated by intraclass correlations; ICC) (Rabe-Hesketh & Skrondal, 2008)
            were: Relatedness support (ICC = 0.01, poor), Structure before the activity
            (ICC = 0.31, fair), Structure during the activity (ICC = 0.57, moderate) and
            Autonomy support (ICC = 0.41, moderate). Internal consistency reliability
            estimates were as follows: Relatedness support (α = 0.58), Structure before
            the activity (α = 0.73), Structure during the activity (α = 0.62) and Autonomy
            support (α = 0.60). Only the coding of one researcher (JK) was used in data
            analysis.

            <hss>Participants' perceptions of dance instructor autonomy support</hss>

            At the end of the intervention, participants (n = 281, 98.9% of participants
            randomised to intervention arm) reported their perceptions of the dance
            instructor's provision of autonomy-support using an adapted version of the
            Sport Climate Questionnaire (Amorose & Anderson-Butcher, 2007). Six items
            (e.g., My Active 7 dance instructor listens to how I would like to do things)
            were scored using a 7 point Likert scale (1 = Strongly disagree to 7 =
            Strongly agree). Items were averaged to create a perceived autonomy-support
            score (α = 0.94).

        <hss>Qualitative data analysis</hss>

        Transcripts of interviews and focus groups were analysed by four researchers (JMK,
        MJE, TM & SJS) using the Framework Method (Gale, Heath, Cameron, Rashid, &
        Redwood, 2013) using both inductive (i.e., themes arising from the data) and
        deductive (i.e., a priori SDT-based themes were interrogated within the data)
        coding strategies. Deductively, the SDT-related components (i.e., motivation
        types, psychological needs and instructor teaching style) were defined based on
        extant literature and these definitions were discussed amongst the group of four
        analysts. Second, text within the transcripts which related to these definitions
        (including both positive and negative experiences) were collated. Frameworks
        created from the initial transcripts formed the basis of analysis for the
        remaining transcripts and flexible to nuances, new examples and refinements which
        were discussed at regular group meetings. Third, data relating to SDT were
        interpreted and refined by SJS and discussed and agreed within the team. A
        framework for dance instructors and girls was created and a convergence coding
        matrix which allowed comparison of themes between dance instructors and girls was
        developed in NVivo (Version 10, QSR International Pty Ltd) (Farmer, Robinson,
        Elliott, & Eyles, 2006). The application of trustworthiness criteria (Shenton,
        2004) included credibility, transferability, dependability and confirmability and
        are reported elsewhere (Sebire et al.,). The qualitative data were organised into
        six themes which combined deductive (e.g., we asked questions about perceptions of
        relatedness) and inductive (e.g., discussions emerged about challenges of
        delivering the SDT components) results from the instructors and the girls. The
        themes were: (1) Dance instructor training and acceptance of the intervention
        theory, (2) Autonomy support and perceptions of autonomy need satisfaction, (3)
        Dance instructors use of controlling strategies, (4) Competence support and
        perceptions of competence need satisfaction, (5) Relatedness support and
        perceptions of relatedness need satisfaction and (6) Challenges of delivering an
        SDT-based physical activity intervention for children. Quotes are reported using
        linked dance instructor and school ID numbers (i.e., Instructor 21 delivered
        lessons in school 21) and are the same as those used in the other process
        evaluation papers from this study to facilitate cross-referencing.

        <hss>Quantitative data analysis</hss>

        For the observed need-support, scores for each item at each 5-min segment were
        aggregated to give lesson item mean averages which were then combined to form
        average scores for relatedness support, structure before the activity, structure
        during the activity, and autonomy support, for each of the four lessons. Means and
        SDs for each construct over the four observations were calculated and analysed
        descriptively. Means and standard deviations (SD) were calculated for girls'
        perceptions of each of the dance instructor's autonomy supportiveness and were
        analysed descriptively.

<hs>  Quantitative results</hs>
  ~~~~~~~~~~~~~~~~~~~~

Relatedness support was the most highly scored (between “often” & “all the time”) teaching
behaviour amongst all instructors (mean = 2.29, SD = 0.47) (Fig. 1). In general, dance
instructors provided moderate (between “sometimes” & “often”) structure before and during
the dance activities (structure before, mean = 1.73, SD = 0.54; structure after, mean =
1.53, SD = 0.60). Structure was observed less in the lessons led by instructor 42.
Autonomy-support was, for all but one instructor, the lowest scoring teaching practice
(mean = 1.16, SD = 0.54) reflecting provision of autonomy support only “sometimes”. Pupil-
perceived autonomy support was moderate (mean = 4.68, SD = 1.68) and relatively consistent
between instructors (Range: Instructor 51 mean = 4.32 SD = 1.65 to Instructor 21 mean =
5.53, SD = 1.20).

        <hss>Dance instructor training and acceptance of the intervention theory</hss>

        Dance instructors reflected positively on the training and believed that the
        principles of SDT were appropriate to underpin the dance lessons. Most instructors
        believed that their existing teaching style was aligned with the SDT approach
        however one instructor felt that the autonomy-supportive style challenged her
        existing practice, particularly the language she used: A lot of us are quite
        experienced teaching and you can get into a groove with how you teach and [the
        introduction of SDT] really made you challenge those sort of key phrases that you
        say throughout the class. (Dance instructor 23)

            <hss>Autonomy support and perceptions of autonomy need satisfaction</hss>

            Dance instructors reported providing girls with choice within dance lessons,
            including the music, dance styles, choreography and warm-ups which was
            corroborated by some girls. [The dance instructor] asked us what types of
            things we wanted to do. Some people said contemporary, some people said
            breakdancing [ … ] so that's what we did, which was good. (Focus group 53)
            Girls choosing the music was an important source of ownership/autonomy within
            lessons as it made them more engaging and positively influenced activity: If
            it's music they like then they want the music on all the time … they're going
            to be more active and more involved. It just makes perfect sense to … let them
            have that choice in the music and it motivates them more. (Dance instructor
            42) Instructors were encouraged to support participants' autonomy within a
            clear structure which was developed in the early lessons by involving girls in
            the development of group rules. They also reported responding to feedback from
            the girls and attempting to include the views of the group not just a vocal
            minority (although some children argued to the contrary). I would read their
            [dance] diaries and sometimes they would write things in there, either about
            the session that would give me clues as to what … you know, 'oh, I loved this
            game' and you think oh, I didn't realise you loved this game. OK let's do this
            game more. (Dance instructor 42) Generally girls enjoyed the level of autonomy
            they were granted. However, some stated a need for dance instructors to
            balance autonomy with sufficient instruction and supervision to support their
            engagement: We had to do it by ourselves and I didn't know the counts or
            anything and I had to like tell them [others in her group] what to do and I
            didn't like that …. (Focus group 61)

            <hss>Dance instructors' use of controlling teaching strategies</hss>

            While the majority of dance instructors reported using autonomy-supportive
            styles, participants from several schools (one in particular) described
            controlling teaching strategies. The following example is where one Dance
            instructor (DI 53) covered another's (DI 21) lesson: Participant 5: It was
            like the army. Participant 2: She forced you to do handstands. Participant 6:
            And if you were talking or something she would make you do ten press-ups.
            (Focus group 21) Some girls commented that they “had no say in pretty much
            anything” (Focus group 32) and identified that where choices given they were
            not perceived as genuine: She was asking us to choose a dance and then she'd
            choose a dance herself. (Focus group 21) The frequency and length of drink
            breaks was considered important to participants' autonomy, but was rarely
            mentioned by instructors, other than as creating an opportunity for disruption
            which they had to control by being what participants felt was “strict”. Girls
            rationalised some of their dance instructor's controlling behaviour as being
            driven by a desire to avoid group arguments or encourage dedication: She was
            strict because she wanted you to be dedicated and turn up. (Focus group 53)

            <hss>Competence support and perceptions of competence need satisfaction</hss>

            Instructors reported using numerous competence-supportive teaching strategies
            including affording participants with the required dance skills, using peer
            role models, differentiation of dance sequences, encouraging self-reflection,
            giving opportunities for leadership, and providing constructive feedback. I
            think the easiest way to deal with the [different skill] levels [is to] get
            those girls who are working really well to help other girls that … are
            struggling. (Dance instructor 21 & 51) Several approaches were used to
            encourage girls to reflect on their competence, including using the dance
            diaries, reflecting on their own progress and ensuring that this reflected
            genuine progress: [A participant would say] “I can't do it” and I'm like
            “well, first of all you can do it”, but also … “remember that step that you
            couldn't do a couple of weeks ago?” and she's like “oh yeah, I can do it well
            easy now” and I'm like “well, there you go then” … I'd get them to reflect on
            their own progress and then I didn't have to try and pretend. (Dance
            instructor 21) Instructors' awareness of girls' abilities allowed them to
            provide targeted competence support: There was a bigger girl who came quite a
            lot and she found - or I found when I was teaching the structure
            [choreography] she would struggle and give up a lot easier, because I think
            she felt like she couldn't do it. She loved teaching the warm-ups and I found
            that she worked harder, she got sweatier, she pushed herself more because she
            was confident doing the things that she already knew how to do. (Dance
            instructor 53) Girls corroborated the dance instructors' competence support
            and reported receiving individual and group-level assistance: She helped like
            if you were stuck on something. But she helps more like as a whole group
            whereas [a different instructor that the group had] would sort of just help
            you individually. (Focus group 23) Girls reported increased confidence and
            competence to dance which was also observed by the dance instructors: After 30
            seconds the first time we were like tired and like couldn't do it. Then after
            a few sessions … well, not a few but like half way through, we could do it for
            like ten minutes, five minutes. (Focus group 53) In contrast, some
            participants felt a lack of support when learning more complex skills and
            thought that the instructor was not aware of the varied competence of the
            group members. Girls suggested that they could not control the speed at which
            lessons progressed: If we didn't know how to like do the move, like it was a
            bit hard to ask [dance instructor] to show us to do the move again because she
            was already showing the next bit. (Focus group 32)

            <hss>Relatedness support and perceptions of relatedness need satisfaction</hss>

            All dance instructors referred to using strategies to build trusting
            relationships with and between girls, including asking them about their lives
            outside the intervention, responding to comments written in dance diaries,
            asking after girls when they missed lessons, giving regular high-fives, using
            a ‘head-to-head sharing time’, and discussing non-attendance: I had this one
            sort of thing where we lie on the floor with all our heads together, and each
            say one thing about the session that we felt we did really well or it could be
            one thing that someone else did well … (Dance instructor 32) Dance instructors
            and girls reported feeling a strong trusting relationship which developed over
            the course of the intervention: I had a couple of girls really open up to me
            and talk to me about sort of personal problems that they were having. (Dance
            instructor 23) There were a lot of “twelve year old teenage dramas” and people
            would get upset about 'oh no, my friend doesn't like me, oh!' and then [dance
            instructor] would be like 'right, we're going to dance this out' [… ] or get
            them to apologise. (Focus group 42) In general, girls considered dance
            instructors to be enthusiastic, fun and understanding. She was really nice
            because we came in and she was like 'oh, you're the dancers!' We were like 'oh
            yeah'. And she was really nice. She came in and like introduced herself and
            everything. And then she … if one … like some of us is like injured or doesn't
            really want to do dance then she'll let us sit out and then just like come
            back when we feel like it so she's really nice. (Focus group 61) However some
            girls did not feel a genuine connection with the dance instructor: She had to
            be in charge all the time. If she had kind of like stepped back and been more
            of a friend than someone like in charge of us then I think we'd have all found
            it easier. (Focus group 32) Where dance instructors' comments or actions were
            not perceived as genuine, this undermined the participant's connection with
            them: Yeah, [dance instructor] always like really clapped for them. She always
            clapped for us but like, you know, it was like for them it was, it was like a
            proper clap. (Focus group 61) Girls and dance instructors described the
            development of existing friendships and the formation of new ones over the
            course of the intervention: “We bonded together” (Focus group 42). At the
            start of the intervention, many girls were apprehensive and groups were
            fractured or consisted of existing cliques. However, throughout the project,
            these cliques dissolved and participants reported making friends and feeling
            more socially comfortable. Participant 1: In the first two sessions I was
            really shy and I always went to the back and I didn't really say [ … ] much.
            But now in the Active7 sessions I talk quite a lot [… ] because I got to know
            quite a lot of people … Participant 2: You feel more comfortable around them.
            (Focus group 72) However, some girls experienced a lack of connection with
            their peers which seemed rooted in participants' interpersonal comparisons of
            their dance abilities and divides between the ‘confident’ and ‘shy’
            participants. The girls who already do dance are really like strong about it
            and they always go together in a group, they don't share it. (Focus group 32)

            Challenges of delivering an SDT-based physical activity intervention for children

            Two issues that appeared to challenge the dance instructors' theoretical
            fidelity in the intervention were the management of disruptive behaviour and
            the use of end-of-project performances. Some dance instructors found it
            difficult to be autonomy-supportive when faced with disruptive behaviour:
            There are times, as I said before, when you've got 25 plus of them all going a
            bit mental [ … ] then you do have to sort of change tactics unfortunately, but
            generally speaking it [being autonomy-supportive] would be the way I would
            want the sessions to be. (Dance instructor 42) In one case a dance instructor
            felt conflicted between maintaining high fidelity (using the SDT-based
            guidelines) and keeping control of the discipline: They were running wild and
            I was trying to be, you know, use the ABC [Autonomy, Belonging, Competence]
            and it was very hard to try and keep to that. Really, really difficult because
            they were just testing my limits and going crazy [ … ] I think that's because
            I was so worried about sticking to ‘this is what we had to do’ to then kind of
            trying to actually respond to the children themselves. (Dance instructor 21 &
            51) Some instructors reflected that more role-play based learning in the
            training would help prepare them for dealing with this more effectively: I
            would say it would be good to … set up some situations where that skill
            [referring to need supportive teaching] could be practised because I felt
            frustrated with myself sometimes that I didn't know [ … ] what to say and I
            didn't know how to do it. (Dance instructor 23) A further challenge to
            theoretical fidelity concerned the use of dance performances as a motivational
            tool and whether or not the girls wanted to perform in front of others. Girls
            were given choice as to whether they performed a dance in front of an audience
            or not and groups often chose to perform. Dance instructors considered
            performances to be an important motivational element of a dance programme:
            You've almost got to have like an end plan that they're all working towards
            (Dance instructor 62). Dance instructors also considered performances to be
            desired by and a positive experience for most girls, although several
            reflected on performance-related anxiety: Even if they're slightly petrified
            of it or whatever, you know … it's kind of a good fear [ … ] They did all love
            doing this as well, even though all moaned a bit but they loved it. (Dance
            instructor 62) Some girls liked the motivation and focus a performance
            provided: At least it's [a performance] for something [ … ] Because if you
            know you're not doing it in front of lots of people you kind of lack a bit,
            but if you know you're doing it for, in front of people then you know that
            you've got to try and do your best and try and get the steps right. (Focus
            group 23) Whereas for others performing was a source of anxiety: When we were
            doing our performance … [dance instructor] wasn't there like … to support us
            in a way, she didn't come to it, so like we didn't really know the music and
            we had to do that ourselves … some people [were] really nervous and [saying]
            they weren't going to do it. (Focus group 61) The performance element also was
            a source of pressure for the dance instructors and one identified that it
            negatively affected her teaching: One session I had to get a bit strict and
            ended up getting a bit sort of arsy [… ] I think it was the pressure of the
            performance. (Dance instructor 23)

<h>DISCUSSION</h>
----------

In this paper we report a theory-based evaluation of the BGDP intervention using a mixed
methods approach. The results can be used to better understand theoretical fidelity and
shed light on the results of the trial. The majority of instructors believed that the SDT
principles of the training aligned with their teaching styles and methods. The training
was well received and served as a reminder to instructors to focus on the “how” (i.e.,
communication practices) in addition to the “what” (i.e., dance content) of their
teaching. A previous study among PE teachers (Aelterman et al., 2013) identified similar
acceptance of SDT-based intervention training and research has shown that classroom
teachers' beliefs that implementing an SDT-based teaching style is likely to be effective,
easy and normal/usual are associated with their motivating style (Reeve et al., 2013). We
believe that our findings indicate that the dance instructors involved in BGDP did buy-in
to the SDT teaching style, and believed that it would be effective however the reality and
ease of implementing it in practice with the participant group led to variable fidelity as
discussed below. Dance instructors qualitatively reported providing choice (of music,
dance styles, warm-up activities, and choreography) within sessions that reflected
examples given in the training manual (this therefore also indicates fidelity) and this
was perceived by instructors and girls to make lessons more engaging and enjoyable.
However, this provision largely reflected option choice, and did not appear to provide
action choice, such as having control over the pace of task progression which is a central
element of autonomy-support (Reeve, Nix, & Hamm, 2003). Previous research suggests that
providing action choice promotes self-determination and intrinsic motivation more than
option choice (Reeve et al., 2003). Instructors that mainly provided option choices may
have believed that this was sufficient autonomy-support and neglected action choice. The
quantitative need-support ratings corroborate this finding and suggest low provision of
autonomy-support across all instructors and substantial room for improvement. This finding
is consistent with Haerens et al. (Haerens et al., 2013) who reported that autonomy-
support was the least common need supportive practice amongst PE teachers relative to
other practices. Further, the qualitative results highlighted the importance of combining
autonomy-support with structure as some participants felt uncomfortable when they were
left to practice on their own with insufficient instructions. Previous work has shown that
teaching styles which combine autonomy-support and structure are associated with improved
learning, behavioural and motivational outcomes amongst adolescents (Vansteenkiste et al.,
2012) and highlight the importance of ensuring that interventions are able to help
teachers balance these two teaching dimensions. In addition to instances of low autonomy-
supportiveness, the qualitative findings identified that some dance instructors used
somewhat controlling motivational practices. Instructors may have used controlling
strategies for a number of reasons; first, the intervention training may not have
successfully changed their teaching styles to be more need-supportive and they adopted
their usual practices which included controlling techniques. However, the instructors
reported believing that the philosophy of SDT chimed with their usual teaching practices
which suggest that this may not have been the case. The SDT component of the dance
instructor training was comparable in duration to previous training for PE teachers
(Aelterman et al., 2013), but shorter than others (Aelterman, Vansteenkiste, Van den
Berghe, De Meyer, & Haerens, 2014). Instructors reported wanting more time to practice
implementing the different motivating techniques, suggesting that the training may have
been conceptually clear but not sufficiently practical. Previous studies of SDT-based
training have incorporated videos of real teaching scenarios (Aelterman et al., 2013,
2014) which can be used to identify and reflect on real teaching practices and dedicated
more time to practicing motivating strategies. Second, some dance instructors may have
misinterpreted the theory, confusing autonomy-support with a lack of rules or structure.
The need-support ratings suggested that structure was used with moderate frequency which
provides some evidence for this hypothesis and may have led to more disruptive behaviour
and reversion to the use of controlling strategies. Third, some dance instructors may have
adopted more controlling practices in response to the challenges associated with teaching
large classes of beginners in a school environment. For example, one dance instructor
drifted (Bumbarger & Perkins, 2008) from the need-support foundation by using press ups as
punishment for talking. Others used working towards a dance performance as a motivational
lever which while seen positively by some, was also a source of pressure for others and
their dance instructors. Moving beyond dance, to broader physical activity interventions
which rely on trainers leading groups of young people, our findings suggest that future
work is needed to identify whether and how physical activity intervention deliverers use
controlling strategies. Further, and based on the nature of trainer's existing practices,
it is important to ascertain whether they can be equipped with techniques to use in
response to challenging behaviour without resorting to controlling techniques. The
findings highlight a need for those developing theory-based interventions to identify
innovative ways to communicate theoretical nuances (e.g., action vs. option choice) that
can be understood and implemented by practitioners. As theory is sometimes viewed as
lacking real world validity (Davidoff, Dixon-Woods, Leviton, & Michie, 2015; Rothman,
2004), there is a risk that efforts to ensure practitioners adopt theoretical principles
result in theoretical dilution and more room for drift (Bumbarger & Perkins, 2008) from
the intended theoretical targets. Embracing technology within theory-based complex
physical activity interventions may be an effective way to overcome some of the issues
which in our study were commonly derived from having limited time within training to
adequately cover detailed and subtle theoretical nuances alongside other content or
intervention deliverers facing challenges within lessons. For example, previous work has
supported training with self-study websites which teachers are asked to engage with
(Reeve, Jang, Carrell, Jeon, & Barch, 2004) which include videos of real teaching
scenarios. A possible next step is to develop smartphone apps to support in-person
training, extend the possible training time and provide a hub of resources to support
intervention fidelity such as multimedia content, tasks which reinforce learning, tips
when dealing with challenges & networking with other instructors. Dance instructors
reported confidently providing competence support to girls and used a number of techniques
which may have utility in future PA interventions. These included a number of examples of
providing structure during the dancing activities such as peer–peer teaching, encouraging
self-reflection, providing genuine encouragement and provision of structure through clear
instructions before the dance activities. The dance instructors' experience in teaching
may explain their confidence in using these strategies and supports the importance of
identifying well trained intervention deliverers who can bring beneficial innovation to PA
interventions (Bumbarger & Perkins, 2008). Girls also had positive experiences of
competence support (and some reflected on their own increased levels of perceived
competence). However, in the BGDP trial, perceived competence towards dance and physical
activity decreased pre-post intervention in the intervention group (Jago et al., 2015). It
is possible that both results are correct; that while some participants did feel more
competent after the intervention, girls on average did not. Alternatively, the results
could point towards changes in the girls' cognitive representations of dance before and
after the intervention. Pre-intervention, the majority of girls had no prior experience of
formal dance lessons. Dance competence levels were rated as relatively high; which could
reflect informal dance experiences (e.g. dancing with friends or alone). However, after
experiencing dance in a more structured taught environment, trying more complex
choreography and comparing their ability with that of their peers, it is not unreasonable
to assume that their cognitive representations of dance and their frame of reference for
their perception of competence could have changed post-intervention. This could mask some
of the qualitative perceptions of increased competence. Relatedness support was the most
commonly observed need-supportive technique used by the dance instructors which in most
cases was verified by the qualitative findings. This is consistent with previous research
among PE teachers (Haerens et al., 2013), but the dance instructors in our study provided
more relatedness support (2.29/3.00) than previously studied PE teachers (≈1.30/3.00)
(Haerens et al., 2013). This may reflect the interpersonal style the dance instructors
have developed through their teaching of dance to groups of girls in out-of-school
settings and be an indicator that they found this particular dimension of need-supportive
instruction easy which has been shown to be associated withteacher's motivating style
(Reeve et al., 2013). Previous research suggests that relatedness towards PE teachers is
associated with girls' engagement in PE (Shen, McCaughtry, Martin, Fahlman, & Garn, 2012).
The qualitative findings identified the development of some strong and trusting girl-
instructor relationships. The instructors' use of a number of relatedness-supportive
techniques which represent effective intervention innovation (Bumbarger & Perkins, 2008)
could be adopted in other interventions (e.g., dedicating time at the end of lessons for
the instructor and girls to lie on the floor with their heads together and reflect on the
lesson, giving regular high-fives, using the dance diary to guide empathically changing
lessons in line with what girls enjoy/don't enjoy). However, it was clear from the
findings that for a minority of girls, a sense of relatedness was not formed with the
instructor which was commonly caused by perceptions that the instructor-participant bond
was not genuine. It would be useful in future interventions to identify the use of
effective techniques during implementation and share them amongst the network of
practitioners who are finding relatedness support difficult. Whilst extra support for
instructors was included in BGDP mid-intervention, a more effective dissemination of
teaching techniques or more frequent provision of materials/support (e.g., via an
intervention resource such as an app as referred to above) could hold promise in
challenging low-fidelity during theory-based PA interventions.

<hs>  Strengths & limitations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

The theoretical underpinning of BGDP is a strength that has helped to evaluate where the
intervention was consistent with, or drifted from, the intended behaviour change
strategies. In addition, the combination of quantitative and in-depth qualitative data
collected from both dance instructors and participants has facilitated the development of
a detailed picture, strengthened by triangulation between participants and across methods.
An inherent limitation in theoretical process evaluations is that the intervention
deliverers are aware of the theoretical foundations with which they are asked to underpin
their delivery. As such, there is the potential for their interview responses and observed
lessons to be biased towards good fidelity. However the focus group results largely added
credibility to the dance instructor results and we are confident that we heard a diverse
range of perspectives including negative experiences which we have reported. Furthermore
it is unlikely that the instructors would have been able to change their teaching style
significantly during the four observations, particularly given that the instructors were
informed on the day of the lesson that they would be observed. A related limitation is
that the inter-rater reliability of the rated dance instructor teaching styles was low for
relatedness support and low/moderate for the other dimensions but generally lower than
previous work with PE teachers (Haerens et al., 2013). A potential reason for this is that
we rated audio rather than video recordings of the dance lessons (as the original measure
used) and thus underestimated the information given by physical indicators alongside the
audio to make the ratings. However, we only used the ratings of one observer whose ratings
were consistent as indicated by good internal consistency estimates. An additional
limitation is that we did not measure the dance instructors' perceptions of using an
autonomy-supportive teaching style pre- and post-training. This would have afforded us a
short-term check of training effectiveness and could be incorporated into future
intervention designs. Further, we used a general measure of girls' perception of
instructor autonomy-support, which prevented us from examining individual psychological
need support and comparing this to our more nuanced observation and qualitative data.
Finally, research including applications in the sport and PE domains (Bartholomew,
Ntoumanis, Ryan, & Thogersen-Ntoumani, 2011; Haerens, Aelterman, Vansteenkiste, Soenens, &
Van Petegem, 2015) has separated the concept of need thwarting (e.g., a child perceiving
that their teacher/coach is trying to control or manipulate them) from the experience of
low need satisfaction (e.g., that a child does not feel that they have much input in
lessons/training sessions). In PE, pupils' perceptions of their teacher's controlling
teaching was associated with their need frustration whereas perceptions of teacher
autonomy support were associated with need satisfaction. In sport coaching, after
controlling for need satisfaction, adolescent athletes' perceptions of psychological need
thwarting have been positively associated with exhaustion and negatively associated with
vitality (Bartholomew et al., 2011). In the present study, we did not quantitatively
measure need thwarting nor the controlling practices of dance instructors. Future process
evaluations of SDT-based PA interventions which involve teachers or coaches would benefit
from considering need thwarting alongside need satisfaction.

<h>CONCLUSION</h>
----------

It is recommended that complex health behaviour change interventions are based on sound
theory and that the theoretical elements are subjected to in-depth process evaluation
(Moore et al., 2014). The findings of this theory-based process evaluation indicated that
theoretical fidelity within BGDP was variable. We identified a number of instances of high
theoretical fidelity and intervention innovation which informs pragmatic techniques that
intervention deliverers working with groups of children could use. Illuminating the lack
of intervention effectiveness, we also found that there was much room for improvement as
we identified examples of low fidelity, some drift from the intended motivational
techniques and potential failures to convert theoretical nuances into practice. More
broadly, this work has highlighted the value of combining quantitative and qualitative
approaches in theory-based process evaluations of physical activity interventions.


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<ART>Using the daylight savings clock change to show ambient light conditions significantly influence active travel
================================================================================

Authors: Jim Uttley, Steve Fotios
DOI: 10.1016/j.jenvp.2017.06.003
Year: 2017  |  Pages: 1-10
ASJC codes: 3202, 3207
Keywords: Active travel, Cycling, Daylight, Lighting, Walking

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

This article reports a novel procedure used to investigate whether ambient light conditions affect the number of people who choose to walk or cycle. Pedestrian and cyclist count data were analysed using the biannual daylight-saving clock changes to compare daylight and after-dark conditions whilst keeping seasonal and time-of-day factors constant. Changes in frequencies during a 1-h case period before and after a clock change, when light conditions varied significantly between daylight and darkness, were compared against control periods when the light condition did not change. Odds ratios indicated the numbers of pedestrians and cyclists during the case period were significantly higher during daylight conditions than after-dark, resulting in a 62% increase in pedestrians and a 38% increase in cyclists. These results show the importance of light conditions on the numbers of pedestrian and cyclists, and highlight the potential of road lighting as a policy measure to encourage active travel after-dark.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Encouraging the use of active travel methods such as walking and cycling has a number of
benefits. These include improvements in health outcomes such as all-cause mortality (Kelly
et al., 2014), obesity (Pucher, Buehler, Bassett, & Dannenberg, 2010) and other health-
related measures such as cancer rates and cardiovascular fitness (Oja et al., 2011). Such
health improvements can lead to economic benefits (Jarrett et al., 2012). The promotion of
active travel can also lead to reductions in the use of motorised transport (Ogilvie,
Egan, Hamilton, & Petticrew, 2004), with reductions in CO2 emissions and improvements in
air quality as a result (Goodman, Brand, & Ogilvie, 2012; Grabow et al., 2012; Rissel,
2009). Citizens who continue to use their vehicles for transport may also benefit from the
promotion of active transport, due to reduced congestion on roads. One of the key purposes
of road lighting is to create acceptable conditions for people to walk or cycle after-dark
(British Standards Institution, 2012), thus encouraging active travel. For example, Kerr
et al. (2016) and Giehl, Hallal, Brownson & d’Orsi (2016) both found that road lighting
was positively associated with increased walking. Cervero and Kockelman (1997) also
suggested that the presence of road lighting and the distance between lamps were
significant aspects of neighbourhood design that contributed to encouraging non-automobile
travel. Differences in lighting conditions can lead to changes in behaviour. For example,
Painter (1994; 1996) found there was an increase in pedestrian use of a crime blackspot
after new lighting was installed. Light conditions can also influence the speed with which
pedestrians walk (Donker, Kruisheer & Kooi, 2011). Cyclists, as well as pedestrians, are
also likely to be influenced by light conditions. For example, the ability to make a trip
during daylight hours was found to be one of the top ten motivations in deciding to cycle,
whilst using a route that was not well lit after-dark was one of the top ten deterrents
(Winters, Davidson, Kao, & Teschke, 2011). There are several reasons why good light
conditions may encourage walking or cycling. First, it allows obstacles and trip hazards
to be seen and avoided, and this is a critical task for both pedestrians and cyclists
(Fotios, Uttley, Cheal, & Hara, 2015; Vansteenkiste, Cardon, D'Hondt, Philippaerts, &
Lenoir, 2013). Lighting characteristics such as illuminance and spectrum can influence the
ability of a pedestrian or cyclist to detect an obstacle in the path in front of them
(Fotios, Qasem, Cheal, & Uttley, 2016; Uttley, Fotios, & Cheal, 2015) and this may make a
person more or less likely to walk or cycle, depending on the light conditions. Second, it
may make the pedestrian or cyclist feel safer and less threatened (Boyce, Eklund,
Hamilton, & Bruno, 2000; Fotios, Unwin, & Farrall, 2015). Good light conditions are
required to allow a pedestrian or cyclist to see far ahead and have an open view. This is
one of the three key attributes an area requires to make it feel safe (prospect, refuge
and escape, Fisher & Nasar, 1992). The prospect of an area will be at its highest during
daylight, but reductions to this after-dark can be mitigated by road lighting. For example
Boyce et al. (2000) asked participants to rate how safe they felt at a number of parking
lots in the US during daylight and after-dark. Safety ratings were generally lower after-
dark than during daylight, but the difference reduced as the illuminance at the parking
lot increased. Feeling safe is particularly important for pedestrians as perceptions of
neighbourhood safety have been shown to influence walking levels in that neighbourhood
(Foster et al., 2016; Mason, Kearns, & Livingston, 2013). The third and final reason why
light conditions may influence the decision of a person to walk or cycle is due to their
perceived visibility. Daylight or road lighting may make the pedestrian or cyclist feel
more visible and less at risk of being hit by a vehicle as the rate and severity of
traffic collisions involving pedestrians and cyclists is increased when there is poor or
no road lighting (Eluru, Bhat, & Hensher, 2008), and during darkness (Johansson, Wanvik, &
Elvik, 2009; Twisk & Reurings, 2013). These three factors of obstacle avoidance, perceived
safety and perceived visibility suggest light should influence the decision of potential
pedestrians and cyclists to travel or not and there should be a link between frequency of
active travellers and light conditions. A causal connection between light and active
travel has not been shown however. For example, previous work has linked the presence of
road lighting with increased walking but it is not clear whether this is due to the light
conditions provided or some other factor. This uncertainty is compounded by the fact that
previous research related to this question has tended to use subjective methods for
assessing the role of lighting, a good example of this being literature on lighting and
perceived safety. A common approach is to ask participants to rate how safe they feel
under different light conditions using a category rating response scale (Boomsma & Steg,
2012; Loewen, Steel, & Suedfeld, 1993; Rea, Bullough, & Brons, 2015). This approach has
some limitations, if not carried out in a systematic way (Fotios & Castleton, 2016;
Fotios, 2016). For example, asking for a rating compels a participant to make an
assessment of something they perhaps would not otherwise consider relevant (Fotios, Unwin,
et al., 2015). Data collected using subjective rating scales may be prone to range bias
(Poulton, 1989) and influenced by the phrasing of the question (Schwarz, 1999). Perhaps
most significantly, it is not certain that a subjective response by a participant
translates into actual behaviour. For example, if light conditions do influence the
subjective assessment of safety this may not necessarily be reflected in actual walking
and cycling behaviour. Previous research has linked lighting conditions, perceived safety
and physical activity (e.g. Weber, Hallal, Xavier, Jayce, & D'Orsi, 2012), but this has
been based on subjective responses and is subject to the limitations outlined previously.
Objective measures of behaviour could provide stronger evidence. In the current article we
present an alternative procedure to examine whether the amount of ambient light affects
the number of pedestrians and cyclists, which is to count the number of pedestrians and
cyclists passing a location in the periods immediately before and after daylight savings
clock change. This was inspired by the investigation of vehicle collisions reported by
Sullivan and Flannagan (Sullivan & Flannagan, 2002). There are a range of factors that
influence the volume of pedestrians and cyclists other than the light conditions, two of
the most important being the season and the time of day (Aultman-Hall, Lane, & Lambert,
2009). The biannual changes to clock times resulting from daylight saving time provide an
opportunity to control these two variables whilst changing the ambient light condition.
This is where clock times in Northern hemisphere countries are advanced in Spring and
moved back in Autumn by 1 h, changing the time of day at which dawn and dusk occur. This
means that, as an example, a walk to or from work could take place during daylight in one
week but after-dark the following week, at the same time of day. That is, an abrupt change
of light level for the same journey decision. Counting the number of pedestrians and
cyclists passing a particular location at this time of day means that the effect of light
on the decision to walk is isolated from potential confounds of journey purpose,
destination and environment. A similar approach utilising the daylight savings clock
changes was used by Sullivan and Flannagan (2002). They analysed vehicle crash statistics
in the US between 1987 and 1997. Their aim was to determine the likely effectiveness of
adaptive headlamps in different driving situations, by identifying when dark conditions
significantly increased the crash risk compared with daylight. They compared crash
frequencies in the nine weeks before and after a clock change to see what the effect of
the abrupt change in light conditions was. We use a similar before and after clock change
method to compare daylight and dark conditions and their effect on active traveller
frequencies. We develop this method further by introducing control periods in which light
conditions do not change, against which changes between daylight and dark conditions can
be compared. Pedestrian and cyclist count data collected over a five year period from the
Arlington County area of Virginia state, United States, have been analysed using this
daylight saving clock change method. Frequencies during a case hour before and after the
Spring and Autumn clock changes are compared relative to changes in control periods in
which the light conditions do not change.

<hs>  Arlington pedestrian and cyclist counters</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Automated pedestrian and cyclist counters have been installed in a number of locations
within Arlington County, Virginia, in the Washington, DC metropolitan area, since October
2009, on both cycle trails and on-street cycle lanes. Arlington County is a 26 square mile
area that was formerly an inner ring suburb of Washington DC. Walking and cycling have
been regarded as important complements to rail and bus transit by the Local Authority, and
led to the development of a healthy active travel infrastructure, matched by investment in
active travel count apparatus to support transport planning. By 2016 there were 10
cyclist-only counters and 19 joint pedestrian and cyclist counters. Examples of these
counters are shown in Fig. 1. The counters continuously record pedestrian and cyclist
volumes and this data is available down to 15-min aggregations via a web service at the
Bike Arlington website (http://www.bikearlington.com/pages/biking-in-arlington/counting-
bikes-to-plan-for-bikes/data-for-developers/). Separate data for pedestrians and cyclists
are provided. The direction of the traveller is also provided, as ‘inbound’ or ‘outbound’
relative to the centre of the Arlington area: for the analysis presented in this paper,
inbound and outbound volumes were combined.

<hs>  Data collation</hs>
  ~~~~~~~~~~~~~~

The dates of Spring and Autumn daylight saving clock changes in the US between November
2011 and March 2016 are given in Table 1. An appropriate 1-h light transition period was
identified for each of the clock-change periods, such that it was dark during this hour
one side of the clock change date and daylight during the same hour on the other side of
the clock change. These times were identified using the sunset times given for the
Washington DC area by the Time and Date website (Time and Date, 2016). This period was
defined as the case period. In addition, two 1-h control periods were identified, these
having the same light condition both before and after the clock change for the same 1-h
period. One of these was 1.5 h before the case period, ensuring it was daylight both
before and after the clock change. The other was 1.5 h after the case period, ensuring it
was dark both before and after the clock change. Two further control periods were also
identified, these being 3.5 h before or after the case period, and also having the same
light condition either side of the clock change. Multiple control periods were selected
because estimates of the effect of the transition in light conditions may depend on the
choice of the comparison, control hour. It is possible that any changes in frequencies
during these control periods could vary systematically with the time of day (Johansson et
al., 2009). As an example, it is possible that the hypothesised effect of the transition
in light conditions during the case period could have a spillover effect on nearby times.
The decision to walk or cycle may be influenced by the knowledge that there would be more
(or less) daylight in the evening after the clock change, even if the person ended up
walking or cycling in the control period rather than the case period. One way to test this
hypothesis is to compare frequencies in the case period with control periods that are
closer or further away in time from the case period. People who are walking or cycling
during a 1-h period that is a greater temporal distance from the case period may be less
likely to have been influenced in their decision to walk/cycle by the transition in
ambient light levels, compared with someone walking/cycling during an hour that is
temporally closer to the case period. The hours selected for all case and control periods
are given in Table 2. Data for the case and control periods were extracted for the 13 days
(Monday of week one to Saturday of week two) before and after the clock change dates given
in Table 1, for all available counters. The day of the actual clock change (always a
Sunday) was not included. These data were cleaned and checked for anomalous data. This
included removing data for one counter that provided combined pedestrian and cyclist data
without distinguishing between the two. Outlying data was identified by converting daily
counts within each 1-h period into modified z-scores using the median absolute deviation,
as recommended by Leys, Ley, Klein, Bernard, and Licata (2013). Daily counts with z-scores
greater than ±3.5 were excluded from the final dataset, following recommendations by
Iglewicz and Hoaglin (1993). This resulted in the exclusion of 1.6% of daily count data.
Data were incomplete or missing entirely for some counters, due to them either not being
installed by the dates queried, the counter being offline as a result of damage or routine
maintenance, or the removal of outlying data. Counters that had less than 3 days of data
in either the weeks before or after the clock change date were excluded. This process
resulted in data from 11 counters being included from November 2011 up to 36 counters from
March 2016, as new counters were installed during this period. This represented between
67% and 92% of all installed counters in any given season and year. Completeness of data
was good, with only 6.0% of included counters for any particular 1-h period before or
after the clock change having less than the full 13 days of data. Table 3 shows details of
the number and types of counters that were included in the final dataset, and the minimum
number of daily counts for pedestrians and cyclists, at each clock change time and year.

<hs>  Overall results</hs>
  ~~~~~~~~~~~~~~~

The mean daily count across all years was calculated for all counters at each of the 1-h
case and control periods. Table 4 shows the overall means and standard deviations across
all counters for each of the 1-h time periods that data was extracted for. Fig. 2 shows
the overall ratio between cyclist and pedestrian frequencies in the case hour and control
hours, over the 13 days before and after the biannual clock changes. This shows the
direction of change in the frequencies following Spring and Autumn clock changes,
highlighting how there is an increase when the case hour is in daylight rather than
darkness, relative to changes in the control hours. It is also apparent that this effect
appears larger for the Autumn clock change compared with the Spring clock change. The
calculated odds ratios and 95% confidence intervals comparing each of the four control
periods against the case period are shown in Fig. 3. All odds ratios were significantly
greater than one, indicating that the numbers of pedestrians and cyclists were
significantly higher during the daylight side of the clock change in the case period
compared with the after-dark side and that this increase was more than that seen in all
four control periods. The odds ratios were significantly higher for pedestrians than
cyclists for three of the four control periods, with the Dark Control period being the
exception. This suggests the transition between darkness and daylight during the case
period may have had a greater effect on the numbers of pedestrians than on the numbers of
cyclists. The overall odds ratio when all control periods are combined is 1.38 (1.37–1.39
95% CI, p < 0.001) for cyclists and 1.62 (1.60–1.63 95% CI, p < 0.001) for pedestrians.

<hs>  Location type</hs>
  ~~~~~~~~~~~~~

For cyclists, frequency data were collected from two types of locations – on-street cycle
lanes, and cycle trails that are not associated with a road. The split in number of
counters for each of these location types between 2011 and 2016 is shown in Table 3. Fig.
4 compares the odds ratios of cyclist frequencies during daylight compared with dark at
on-street cycle lane and cycle trail locations. Pedestrian frequencies are not compared as
the on-street cycle lanes only recorded data about cyclists. The odds ratios for both on-
street cycle lanes and cycle trails are significantly greater than one for all control
period comparisons. However, odds ratios for the cycle trails are also significantly
higher than for the on-street cycle lanes for all four control periods. This suggests the
effect of the transition between darkness and daylight during the case period had a
greater effect on cyclist frequencies at trail locations, compared with cycle lane
locations.

        <hss>Temperature</hss>

        The analysis method reported in this paper of comparing active traveller
        frequencies before and after a daylight saving clock change attempts to isolate
        the effect of ambient light conditions on the presence of cyclists and pedestrians
        by comparing the same hour of the day during daylight and after-dark conditions.
        Although the comparison periods before and after the clock change are contiguous
        it is possible that weather conditions were not the same, introducing a potential
        confound. Furthermore, the temperature may have varied systematically, as the
        daylight period always fell in the part of the year expected to be warmer compared
        with the after-dark period. For example, in Spring when the clocks move forward 1
        h, the after-dark condition in the case period falls before the clock change, in
        the earlier part of the year when it may be expected to be slightly cooler in
        temperature. In Autumn, when clocks move backward 1 h, the reverse situation
        occurs, with the after-dark condition falling after the clock change, as
        temperatures may be expected to be cooling. Therefore, the after-dark condition
        may systematically be cooler than the daylight condition. As temperature is a
        significant factor in whether someone chooses to walk or cycle (e.g. Miranda-
        Moreno & Nosal, 2011; Saneinejad, Roorda, & Kennedy, 2012) this would provide an
        alternative explanation for why the daylight condition shows a relative increase
        in pedestrians and cyclists. To explore this alternative explanation temperature
        data for the Arlington area of the United States was downloaded from the Weather
        Underground via the web service provided at the Bike Arlington website
        (http://www.bikearlington.com/pages/biking-in-arlington/counting-bikes-to-plan-
        for-bikes/data-for-developers/). Hourly data was extracted for each of the 1-h
        case and control periods (see Table 2), during the two-week periods before and
        after each clock change between Autumn 2011 and Spring 2016. The hourly
        temperature data was averaged to give a mean temperature for each day. Fig. 5
        shows the overall mean daily temperature combined across all years, for the day
        and after-dark periods in Spring and Autumn clock changes. Fig. 5 suggests mean
        temperatures were higher during the daylight period compared with the dark period,
        for both Autumn and Spring clock changes. This was confirmed with a 2-way between-
        subjects ANOVA, with the clock change season and the ambient light condition as
        independent factors. There was a significant main effect of the light condition
        with mean temperatures significantly higher during daylight periods (mean = 11.6
        °C) than after-dark periods (mean = 8.1 °C, F (1,285) = 40.8, p < 0.001, ηp =
        0.13). There was also a significant main effect of the clock change season, with
        mean temperatures significantly higher at the Autumn clock change (mean = 11.8 °C)
        than the Spring clock change (mean = 7.8 °C, F (1,285) = 55.5, p < 0.001, ηp =
        0.16). These results show that temperature did significantly differ between the
        before and after clock change periods, with higher temperatures during those
        periods in the ambient daylight condition than in the ambient darkness condition.
        However, to confirm whether the change in light conditions can still explain the
        change in pedestrian and cyclist frequencies demonstrated in section 3.1,
        differences in temperature were tested before and after every clock change
        individually, to determine if in some years the temperature did not significantly
        change. If such years and seasons were found, these could be used to determine
        whether a change in pedestrian and cyclist numbers was still seen. If this was the
        case, it would suggest the light condition was an explanatory factor even when
        temperature remained constant before and after the clock change. A series of
        independent t-tests were carried out comparing temperatures during the day and
        after-dark periods for each clock change in each year. Bonferroni correction was
        applied to account for the multiple testing, giving an alpha of 0.05/10 = 0.005.
        The results are summarised in Table 5. These tests suggest there were five
        occasions when temperatures did not differ in the two week periods before and
        after clock changes (Autumn 2011; Spring 2013; Autumn 2013, Autumn 2015 and Spring
        2016). One of these occasions (Autumn 2013) did show a relatively large difference
        in temperatures and was close to reaching the Bonferroni-corrected alpha level (p
        = 0.007), and is therefore not included as an occasion when temperatures did not
        differ, to err on the side of caution. The other four occasions are deemed to not
        show a change in temperature before and after the clock change. Clock changes that
        did not show a significant change in temperature before and after the change date
        were combined and odds ratios were calculated comparing the case period with each
        of the four control periods. The same was done for clock changes that did show a
        significant change in temperature. The calculated odds ratios and 95% confidence
        intervals are shown in Fig. 6. The data shown in Fig. 6 demonstrate that even when
        changes in temperature are accounted for and only occasions when the temperature
        did not significantly change before and after the clock change are examined, the
        odds ratios are still significantly above one. This suggests the effect of the
        transition in ambient light condition alone can explain the increase in
        pedestrians and cyclists during the daylight periods independently from any
        influence of temperature. In fact, the clock changes that showed no change in
        temperature generally produced larger odds ratios than those clock changes where
        the temperature did change significantly. This would suggest the effect of the
        transition in light conditions was larger when there was no temperature change.

        <hss>Precipitation</hss>

        It is possible that precipitation may also influence the decision to walk or cycle
        (de Montigny, Ling & Zacaharis, 2012; Nosal & Miranda-Moreno, 2014) and thus
        confound explanation of the change in pedestrian and cyclist numbers. To check
        this, daily precipitation levels were obtained from the Weather Underground
        service via the Bike Arlington website, with mean daily precipitation calculated
        for the periods before and after each clock change. A two-way between-subjects
        ANOVA was carried out, with the clock change season and ambient light condition as
        independent factors, to identify any systematic differences in precipitation
        levels. This suggested there was no difference in precipitation volume between the
        Spring and Autumn seasons (respective means = 0.09 and 0.11 inches per day, F
        (1,231) < 0.001, p = 0.98). There was also no difference in precipitation volumes
        between the daylight and dark periods (respective means = 0.12 and 0.08 inches per
        day, F (1,231) = 0.77, p = 0.38). There was also no interaction between the season
        and the ambient light condition (F (1,231) = 2.91, p = 0.09). These results do not
        suggest systematic variations in precipitation levels between the periods when the
        case hour was in daylight and in darkness and precipitation can therefore be ruled
        out as a potential explanation for the differences found in pedestrian and cyclist
        frequencies when the ambient light condition changed.

<h>DISCUSSION</h>
----------

The aim of this work was to establish whether ambient light level affects the number of
people choosing to walk or cycle. A large number of pedestrian and cyclist counters in
Arlington County, Virginia, provided extensive data about the numbers of people walking
and cycling. This open-source data provided the opportunity to carry out a novel method of
analysis using the daylight-saving clock change to isolate the effect of an abrupt change
in ambient light conditions. Data was extracted for two-week periods before and after ten
clock-change dates between Autumn 2011 and Spring 2016. Pedestrian and cyclist frequencies
during a 1-h ‘case’ time period, in which the ambient light conditions were different
before and after the clock change, were compared against four other 1-h ‘control’ periods,
in which the ambient light conditions remained the same both before and after the clock
change. Two of these control periods were chosen to be close in time to the case period,
one during daylight the other after-dark. The other two control periods were chosen to be
more distant in time from the case period. When all control periods were combined, the
calculated odds ratio suggested daylight conditions resulted in a 62% increase in
pedestrians and a 38% increase in cyclists, compared with after-dark conditions. Looking
separately at the odds ratios for each of the four control periods, there is a suggestion
that the effect of the transition between darkness and daylight in the case period was
greater when compared against the control periods that were further away in time, than
when compared against the control periods that were nearer in time to the case period's
hour of transition. This is confirmed when looking at odds ratios for the near control
periods combined (Dark Control and Day Control) and the far control periods combined (Late
Dark Control and Early Day Control). For pedestrians, the combined odds ratio for the near
control periods was 1.56 (1.54–1.58 95% CI) compared with 1.72 (1.69–1.75 95% CI) for the
far control periods. For cyclists, the combined odds ratio for the near control periods
was 1.36 (1.35–1.37 95% CI) compared with 1.42 (1.41–1.44 95% CI) for the far control
periods. This suggests the odds ratios were significantly greater for the far control
periods than the near control periods, for both pedestrians and cyclists. This supports
the hypothesis that there is some spillover or displacement effect of the transition in
ambient light conditions. This may also partly explain why the OR for pedestrians is
smaller than for cyclists when using the dark control hour, but for the other three
control periods the pedestrian OR is larger than the cyclist OR (see Fig. 3). This
reversal in the size of OR for pedestrians and cyclists is due to a relatively large
change in pedestrians during the dark control period when the case hour is in daylight
compared with darkness (daily mean count = 24 and 16 respectively; see Table 2). The
equivalent change in cyclists is smaller (daily mean count = 18 and 15 for dark control
hour when case hour is in daylight and darkness respectively; see Table 2). This may be
due to a greater spillover effect for pedestrians compared with cyclists. Possible reasons
for this include reduced flexibility in work departure time amongst cyclist compared with
pedestrian commuters due to considerations about road traffic volumes or the habitual
nature of cycle commuting. There may also be increased opportunity for delays and detours
during a pedestrian's journey home (e.g. visit to the shops or to a bar) compared with a
cyclist's. Fig. 8 shows standardised hourly frequencies for pedestrians and cyclists
during the 13 day periods before and after Spring and Autumn clock changes in 2015, as an
illustration of daily patterns in pedestrian and cyclist numbers. There are large peaks in
cyclist frequencies at morning and evening commuter times, and whether the case hour is in
daylight or darkness does not alter the timing of these peaks. This supports the
suggestion that cyclists may be quite rigid in their travel times, producing a relatively
limited spillover effect. The travel times of pedestrians is a lot more distributed
throughout the day however, with morning and evening peak times much less obvious compared
to cyclists. This suggests there may be greater fluidity in travel times of pedestrians,
potentially leading to a greater spillover of travelling during the dark control hour.
Further data is needed to corroborate this hypothesis though. The Arlington pedestrian and
cyclist counters were located in two types of location – on-street cycle lanes, and cycle
trails. The calculated odds ratios for cycle trail locations were significantly greater
than on-street cycle lane locations for all four control periods (Fig. 3). This suggests
the ambient light conditions had a greater effect on the number of cyclists on the cycle
trails compared with the cycle lanes. One possible explanation for this is that the cycle
lanes may be used more by cyclist commuters travelling to and from work. This journey is
likely to be habitual and therefore the decision to cycle or not may be less likely to be
influenced by the light conditions. The cycle trails are more likely to be used by
recreational cyclists, who can be more selective in what days and times they choose to
cycle, and the ambient light condition is likely to have a greater influence on whether
such cyclists choose to cycle at a particular time. As a result, there may be less use of
the cycle trails when dark, compared with the on-street cycle lanes, which would explain
the larger odds ratios for cycle trails. The cycle trails and cycle lanes may also be
located in areas of different land use, e.g. residential districts, parks, industrial
areas, and this may influence the type of user and their propensity to travel at different
times of the day and week. The users of the two types of cycle paths may also differ in
their confidence in cycling and perceptions of danger. Cyclists who are more willing to
cycle on urban roads and who see themselves as competent may be more likely to see cycling
as a safe travel mode. This may result in cyclists who use the on-street cycle lanes being
less influenced by the potential safety implications of cycling in darkness rather than
daylight, compared with cyclists who use the cycle trails. An alternative explanation for
the difference between on-street cycle lanes and cycle trails though could relate to the
public lighting that is present in these two types of locations. The on-street cycle lanes
are likely to have well-provisioned public road lighting as they are situated on roads
used by motor vehicles. This may be less the case on cycle trails however, where the
public lighting may be less frequent and dimmer, if present at all. For example, many of
the cycle trails transect public parks, and these are frequently not lit after-dark.
Greater provision of public lighting after-dark may result in more cyclists travelling
after-dark, and this could explain why the effect of the transition between daylight and
darkness is greater on cycle trails than on-street cycle lanes. The cycle lane and trail
locations can be seen as typologically similar to an urban and rural distinction, with
more road lighting at urban than rural locations. Johansson et al. (2009) suggested the
reduced road lighting on rural roads may have accounted for their results about vehicle
collisions, which showed larger odds ratios related to the effect of dark conditions on
rural roads, compared with urban roads. Weather conditions are an important consideration,
alongside light levels, in determining whether someone chooses to walk or cycle (e.g.
Saneinejad et al., 2012). In particular, temperature, as a relatively predictable and
stable variable of climate, is likely to have an influence on active travelling. A
limitation of the current approach using clock changes to investigate the effect of light
conditions on active travel is that the period around the clock change date that had more
daylight was also the period that was likely to have slightly warmer temperatures, all
things being equal. The ‘daylight’ side of the clock change had significantly warmer daily
mean temperatures than the ‘darkness’ side of the clock change (Fig. 5). However, in some
years the mean daily temperature did not change before and after the clock change. These
occasions still showed odds ratios significantly greater than one, indicating that the
transition in light had a significant effect on pedestrian and cyclist numbers, over and
above any effect of temperature (Fig. 6). In fact, the effect was larger when there was no
change in temperature, compared with when the temperature also increased during the
daylight side of the clock change. This is logical – an increase in temperature may
increase numbers in the control periods which will reduce the relative size of the effect
of the transition in light when the case period is compared against the control periods.
This is why the effect is larger at those clock change times when temperature did not
significantly change before and after the clock change date. An increase in temperature
serves to partially mask the effect of the transition in light. We also examined
precipitation to determine whether this could explain the changes in active traveller
counts, but found no difference in precipitation levels before and after the clock changes
(see Fig. 7). The 1-h clock change that occurs in the Spring and Autumn of each year is
not only marked by an abrupt change in ambient light levels at the same time of the day,
but may also be marked by individual behavioural and wider societal changes. For example,
although we show that there is a change in the number of active travellers before and
after a clock change even when temperature does not change, it is possible that the clock
change represents a psychological Rubicon for many people that symbolises the onset of a
new season. This may result in changes in behaviour, activity schedules or perceptions
about the environment (such as it being warmer or colder) that may not reflect true
changes. The transition to and from Daylight Saving Time may also be used by businesses,
organisations and local services to change their hours of business. As an example, in our
city of Sheffield, UK, household waste sites change between ‘Summer’ and ‘Winter’ opening
times in April and October, around the time of the clock changes. Such changes could
result in changes to the behaviour of local residents resulting in differences in the
numbers of pedestrians and cyclists before and after a clock change. Clock changes can
also cause changes to circadian rhythms and waking times (e.g. Kantermann, Juda, Merrow, &
Roenneberg, 2007) which may influence behaviour. As an example of this, Daylight Saving
Time has been associated with an increase in ‘cyberloafing’ behaviour amongst employees as
a result of lost and low-quality sleep (Wagner, Barnes, Lim, & Ferris, 2012). Such
behavioural changes may produce variations in the frequency of pedestrians and cyclists
during the case hour examined in the current study. Therefore a number of potential
behavioural and societal changes could occur as a result of the biannual clock changes but
are not overtly linked to changes in ambient light conditions. These may contribute
towards changes in active traveller frequencies. Although the use of control hours in the
present study attempts to account for such confounding factors that are unrelated to light
conditions, further investigation is required to determine the exact influence of these
behavioural and societal changes on pedestrian and cyclist numbers.

<h>CONCLUSIONS</h>
-----------

Active travel, i.e. walking and cycling, has a range of benefits and should be encouraged
and facilitated whenever possible. A number of potential barriers to active travel exist,
such as physical fitness, habitual behaviour or perceived environmental factors such as
personal safety (e.g. Dawson, Hillsdon, Boller & Foster, 2007). One environmental factor
that may be important is the light condition. We have shown that ambient light levels
significantly influence the numbers of people choosing to walk or cycle. In drawing this
conclusion we have accounted for seasonal and time-of-day factors, by using the daylight-
saving clock change analysis method. To our knowledge, this is the first time this method
has been used to examine active travel behaviour. We also show that light level is a
significant determinant of active travel even when temperature is accounted for. The
presence or absence of public lighting is also a possible explanation for why bigger
reductions in active travellers were seen after-dark on cycle trails compared with on-
street cycle lanes, although further work is required to confirm this hypothesis. It is
also possible that the types of cyclists using cycle trails and on-street cycle lanes
differ. The influence of cyclist and pedestrian characteristics, such as gender and age,
on the likelihood of travelling after-dark should therefore also be investigated. In
summary, this work shows the significance of ambient light levels on active travel.
Although artificial lighting after-dark is not equivalent to daylight, these results
highlight a potential role for road lighting in encouraging active travel, to provide
adequate light conditions that minimise the transition in light from daylight to darkness.

<h>FUNDING</h>
-------

This work was carried out with support from the Engineering and Physical Sciences Research
Council (EPSRC) grant number EP/M02900X/1.


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<ART>Using virtual environments to investigate wayfinding in 8- to 12-year-olds and adults
================================================================================

Authors: Jamie Lingwood, Mark Blades, Emily K. Farran, Yannick Courbois, Danielle Matthews
DOI: 10.1016/j.jecp.2017.08.012
Year: 2018  |  Pages: 178-189
ASJC codes: 3204, 3205
Keywords: Landmarks, Navigation, Route learning, Spatial Cognition, Virtual environment, Wayfinding

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Wayfinding is the ability to learn and recall a route through an environment. Theories of wayfinding suggest that for children to learn a route successfully, they must have repeated experience of it, but in this experiment we investigated whether children could learn a route after only a single experience of the route. A total of 80 participants from the United Kingdom in four groups of 20 8-year-olds, 10-year-olds, 12-year-olds, and adults were shown a route through a 12-turn maze in a virtual environment. At each junction, there was a unique object that could be used as a landmark. Participants were “walked” along the route just once (without any verbal prompts) and then were asked to retrace the route from the start without any help. Nearly three quarters of the 12-year-olds, half of the 10-year-olds, and a third of the 8-year-olds retraced the route without any errors the first time they traveled it on their own. This finding suggests that many young children can learn routes, even with as many as 12 turns, very quickly and without the need for repeated experience. The implications for theories of wayfinding that emphasize the need for extensive experience are discussed.

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<h>INTRODUCTION</h>
------------

Researchers have long been interested in how navigation develops (Bullens, Iglói, Berthoz,
Postma, & Rondi-Reig, 2010; Karimpur & Hamburger, 2016; Purser et al., 2015). Navigational
abilities such as route learning are used by most people every day as they travel from one
place to another place. Route learning refers to the ability to encode spatial and other
information along a route well enough to retrace that route on future occasions (Merrill,
Yang, Roskos, & Steele, 2016; Rissotto & Giuliani, 2006). Adults can often learn routes
quickly and effectively after only one or two experiences of the route (Gärling, Böök,
Lindberg, & Nilsson, 1981; Montello, 1998), and this is the case even when the routes are
1 or 2 km long and/or include a large number of choice points at junctions (Farran,
Blades, Boucher, & Tranter, 2010; Karimpur & Hamburger, 2016). The ease with which adults
learn routes suggests that adults have developed appropriate strategies for encoding
routes (Montello, 2017). One important strategy is encoding turns in relation to landmarks
(e.g., “the left turn after the school”). Adults may be particularly well adapted to focus
on landmarks and turns, and there is evidence for distinct brain activation for landmarks
and routes (Wegman & Janzen, 2011). Adults show increased activity in the parahippocampal
gyrus when attending to landmarks at decision points (Janzen, Wagensveld, & van Turennout,
2007), and the anterior cingulate gyrus and the right caudate nucleus are activated when
adults learn the turns along a route (Janzen & Weststeijn, 2007). In contrast to adults’
competence in learning new routes after only brief experience, the evidence about
children’s ability to learn new routes after only brief experience is less clear. Siegel
and White (1975) argued that children’s route learning requires repeated experience
because children first need to learn individual landmarks along a route; only then do they
associate those landmarks with particular decisions (e.g., left or right turns) before
they can combine a series of landmarks and turns into a fully learned route. There is
evidence that children do, like adults, focus on landmarks (Jansen-Osmann & Wiedenbauer,
2004; Lingwood, Blades, Farran, Courbois, & Matthews, 2015a, 2015b). van Ekert, Wegman,
and Janzen (2015) found that similar regions of networks involving the hippocampus and the
inferior/middle frontal gyrus were activated during a memory test for previously seen
landmarks in both children and adults. Despite children’s focus on landmarks, children do
not always learn routes as well as adults (Jansen-Osmann & Wiedenbauer, 2004). This may be
because in real life or in complex environments, children may be less good at identifying
what is an effective landmark. Younger children may be especially dependent on landmarks
that are nearby or next to turns, whereas older children tend to use distant landmarks for
wayfinding (Cornell, Hadley, Sterling, Chan, & Boechler, 2001; Purser et al., 2012). Older
children are also more likely than younger children to use verbal strategies such as
counting the number of steps taken or number of buildings passed when retracing a route
(Duroisin & Demeuse, 2015). Having better strategies for learning landmarks or estimating
distances along routes means that children’s route learning does improve with age and may
account for reports of age-related improvements in wayfinding in complex environments
(Cornell, Heth, & Alberts, 1994; Cornell, Heth, & Broda, 1989; Heth, Cornell, & Alberts,
1997). In contrast to the studies showing that children do need repeated experience of a
route to learn the route, researchers have found that preschoolers can learn a route
without error after only a single experience (Spencer & Darvizeh, 1983), and Cornell and
Hay (1984) reported that 6- and 8-year-olds who had seen a route only once were able to
retrace the route with an average of less than one error. The latter finding implies that
a number of children retraced the route without error at all. Cousins, Siegel, and Maxwell
(1983) showed that 7-, 10-, and 13-year-olds could retrace a route after one experience of
it. The fact that even very young children can retrace novel routes after one experience
goes against the suggestion that children need multiple experiences of a route before they
can learn it successfully. Rather, it seems that children can encode a route as
effectively as adults and do not need to progress through “stages” of route leaning such
as learning landmarks, turns, and then completed routes. The latter would support
Montello’s (2017) argument that there is no qualitative difference between “landmark” and
“route” knowledge. According to Montello, knowledge of landmarks and knowledge of a route
develop in unison and are inseparable aspects of route learning rather than sequential
stages in learning a route. However, when children have learned routes after one
experience in the studies cited above, the routes were short with seven or fewer turns
(Cornell & Hay, 1984; Spencer & Darvizeh, 1983), and even though the children may have
been unfamiliar with the particular test route, they were very familiar with the
environment that the test route ran through (Cousins et al., 1983; Spencer & Darvizeh,
1983). Therefore, these studies indicated the possibility that young children might be
able to retrace routes after one experience. However, given the nature of the routes
(which were limited) and the children’s advantage in already knowing the general
environments of the routes, the results need to be treated cautiously. It may well be the
case that young children can learn routes straight away and without multiple experiences,
but this needs to be demonstrated in a more demanding context with longer routes in
completely unfamiliar environments. Therefore, we investigated whether children could
learn a route after just one experience of the route, but we did so in a more rigorous
context and with a longer route than in the previous studies. We tested four age groups,
including adults, so that we could make developmental comparisons. To maintain a perfectly
consistent and safe environment for all participants, including the youngest ones, we
tested participants in a virtual environment (VE). VEs are an alternative to studying
wayfinding in the real world because they allow children the opportunity to walk a route
several times without the physical demands of a real environment (Broadbent, Farran, &
Tolmie, 2014). VEs can be used successfully with very young children (Lingwood et al.,
2015a, 2015b), and they also allow children to retrace routes without the need to be
accompanied by an adult. VEs can depict visual and spatial information from a three-
dimensional first-person perspective (Jansen-Osmann, 2002; Richardson, Montello, &
Hegarty, 1999), and successful route learning in VEs transfers to real environments
(Ruddle, Payne, & Jones, 1997). Therefore, VEs are a very appropriate way to assess young
children’s abilities. Our study compared the ability of 8-, 10-, and 12-year-olds and
adults to retrace a route with 12 decision points in a VE. Participants were guided along
the correct route just once and then were asked to retrace the route, from the start, on
their own. The primary research question was whether the participants could learn the
whole route after a single experience of it. A second research question was to consider
when children’s performance was equivalent to the performance of adults.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Child participants were 20 8-year-olds (M = 7;11 [years;months], SD = 3.84 months), 20
10-year-olds (M = 10;2, SD = 6.04 months), and 20 12-year-olds (M = 12;9, SD = 4.91
months) who were recruited from primary and secondary schools in the United Kingdom. There
were 10 boys and 10 girls in each age group. Adult participants were 20 students at the
University of Sheffield (M = 23;8, SD = 2;2), with an age range of 18;0 to 29;10 (11 women
and 9 men). Ethical approval was granted by the University of Sheffield ethics committee.

        <hss>Virtual environments</hss>

        Two different VEs were created using Vizard, a software program that uses Python
        scripting. VEs were presented to participants on a 17-in. Dell laptop that was
        placed on a desk. Participants sat in a chair at the desk and were approximately
        50 cm from the screen. Participants navigated through the maze using the arrow
        keys on the keyboard.

        <hss>Practice maze</hss>

        One maze (Maze A) was used as a practice maze to familiarize participants with
        moving in a VE. This maze was a similar but different layout compared with the
        test maze. It did not contain any landmarks.

        <hss>Test maze</hss>

        Maze B was used to test the children and adults (see Fig. 1). The test maze was a
        brick wall maze with 12 junctions. The junctions were “L” shaped. Each junction
        had two paths: a correct path and an incorrect path. Of 24 landmarks, 12 landmarks
        were placed on the correct paths (junction landmarks) and 12 landmarks were placed
        on incorrect paths (off-route landmarks). As in previous studies, all landmarks
        were placed in the middle of the paths (Jansen-Osmann & Wiedenbauer, 2004;
        Lingwood et al., 2015a, 2015b). Landmarks were placed in the middle of paths in
        case participants interpreted a landmark that was placed on the left hand side of
        the path as one that indicated a left turn or a landmark on the right as one that
        indicated a right turn. An incorrect path always ended in a cul-de-sac, but from
        each junction a cul-de-sac looked like a typical path rather than a dead end.
        Therefore, participants could not tell that they had made an error until they had
        actually committed to walking down a chosen path. There were four right, four
        left, and four straight ahead correct choices that were balanced with the same
        number and types of incorrect choices. All of the path lengths between junctions
        were equal. A white duck marked the start of the maze, and a gray duck marked the
        end of the maze. When retracing a route from the start, participants were told to
        find the route back to the gray duck. The gray duck provided a salient target that
        was always the end point of the route and did not move. When participants reached
        the gray duck, the maze disappeared, indicating the end of a trial. All of the
        landmarks were objects with names that would be familiar to children (and adults)
        such as ball, playground slide, street lamp, and umbrella. These items were chosen
        because they had distinctive names, were easily recognizable, and could be
        distinguished from each other without difficulty. All of the landmarks were static
        because they did not change position during the experiment. When being shown the
        route, participants passed close to the landmarks at junctions, and the off-route
        landmarks were not so close but were easily recognizable from the distance that
        participants saw them.

<hs>  Procedure</hs>
  ~~~~~~~~~

All participants were tested individually. Children completed the experiment in a quiet
room in their school. Informed consent was obtained from all of the children’s parents,
and all children were asked whether they wanted to take part. None of the children refused
to take part. Adults completed the experiment in a quiet office in a university
department. Participants sat at the desk facing a computer, and the experimenter sat
beside them. The experimenter spent 2 min talking to the children informally to establish
rapport. Then the experimenter introduced the task by saying, “This computer has got some
mazes on it that we are going to use. First, we’re going to practice using the computer to
walk around a maze. I’ll go first and show you how, and then you can have a turn.” The
experimenter then demonstrated how to navigate through the practice maze using the arrow
keys. The practice maze was the same design as the experimental maze, but it was a
different layout. Participants were given time to walk around the maze until they were
confident about using the arrow keys, at which point the experimenter ended the practice
phase by saying, “Well done, I think you’ve had enough practice now. Let’s have a go at
another maze now.” Participants were first given a single experience of the correct route,
guided by the experimenter. During this initial experience, the experimenter guided
participants by moving forward or turning along the correct route (without looking down
any of the incorrect paths). All participants were given preliminary instructions for the
test phase: “Now I’m going to show you the way through a new maze. Somewhere in this maze,
there is a little gray duck to find. I’ll show you the way to the gray duck once, and then
you can have a go.” The experimenter demonstrated the correct route from the start to the
end of the maze. The experimenter used generic terms such as “You go past here, then you
turn this way, and then you turn this way.” The experimenter never used any directional
language such as “turn right.” At the end of the demonstration, the experimenter said,
“Hooray, we’ve found the duck!” and the screen went blank. Participants were then asked to
retrace the route they had been shown from the start of the maze to the gray duck that was
always in the same place. No participant ever queried this instruction or asked whether
the duck had moved. Participants navigated through the maze using the arrow keys on the
keyboard. The experimenter sat behind participants and traced the exact route they took on
a paper copy of the maze out of participants’ sight. The experimenter timed how long it
took participants to complete the maze. If a participant had not reached the end of a maze
after 5 min, the experimenter ended that attempt by saying, “Oops, it looks like you’ve
got a bit lost. Not to worry, let’s start back from the beginning, shall we?” Only one
8-year-old did not reach the end of the maze on the first attempt. Participants did not
receive any help in finding their way after the initial demonstration of the correct
route. If participants asked which way to go, the experimenter said, “I want you to show
me the way to go. Just try your best.” If participants returned to the start position but
thought that they had reached the end, they were told, “You’re back at the beginning of
the maze now. Let’s turn around and try again to remember the way I showed you to the
little gray duck.” Participants then made a second attempt to follow the correct route but
did not get to see the original route again. When participants reached the end of the
maze, this was the end of one trial. The experimenter congratulated the participants and
asked them to walk the route again from the start. This procedure was repeated until
participants had walked the route to a criterion of two consecutive completions without
error. The reason for the criterion of two consecutive routes without error is given in
the section on scoring (below). At the end of the final trial, all participants were
thanked and the children, regardless of their performance, received a sticker. If
participants had not walked the route successfully on two consecutive attempts after 20
min or after eight attempts, the experiment was stopped and the children were given a
sticker. This was based on the procedure used by previous researchers (Farran, Courbois,
Herwegen, & Blades, 2012; Lingwood et al., 2015a, 2015b). Only two 8-year-olds did not
walk the route successfully on two consecutive occasions.

<hs>  Retracing the route</hs>
  ~~~~~~~~~~~~~~~~~~~

The probability of retracing the route correctly, without any mistakes, by guessing at
each junction was p < .00025. The number of participants who completed the route without
errors on their first attempt is shown in Table 1. The findings from Table 1 show that
some children can learn a route consisting of 12 turns immediately, having viewed it only
once. Nearly a third of 8-year-olds, half of 10-year-olds and nearly three quarters of
12-year-olds successfully retraced the route on their first attempt without making any
errors. Not all participants retraced the route on their first attempt without error, and
so in the following analyses we included only those participants who made one or more
errors when retracing the route for the first time. This included 14 8-year-olds, 10
10-year-olds, 6 12-year-olds, and 5 adults.

<hs>  Reaching the learning criterion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To avoid overestimating participants’ performance, we defined a criterion of successful
learning as follows: two consecutive completions of the route without error. To achieve
this criterion, participants needed to walk the route without walking down any incorrect
paths on two consecutive trials. Walking down an incorrect path was classed as an error.
Participants needed to fully walk down a path in order for it to be counted as an error.
Looking down an incorrect path was not classed as an error. The total number of learning
attempts to reach criterion excluded the final two perfect attempts. For example, if
participants made an error on Attempt 1, but then walked the route without error on
Attempts 2 and 3, they would be scored as having required 1 attempt before reaching
criterion. A lower score indicated better performance. If participants never achieved the
criterion, we calculated the number of completed attempts. For example, if participants
completed 6 attempts within the 20-min cutoff time but did not complete 2 consecutive
attempts without error, they scored 6. Three of the 8-year-olds did not complete two
consecutive attempts without error within the 20-min cutoff time. Table 2 shows that
participants who made one or more errors when retracing the route on their first attempt
required a similar number of trials to reach learning criterion irrespective of age. This
was confirmed by non-parametric statistics, H(3) = 1.45, p = .69.

<hs>  Errors during route retracing to criterion</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants received a mark of 1 for every error they made during an attempt. On each
attempt, a proportional error score was calculated as the number of errors divided by the
number of decisions made. Fig. 2 shows the route taken by one participant. This
participant made 2 errors out of a total of 12 decisions, producing a proportional error
score of .17. This scoring captured participants’ wayfinding behavior every time they made
a decision. This scoring method accounted for occasions when participants doubled back and
returned to the same junction more than once within a trial. Some participants who got
lost did not reach the later junctions, so any junctions not reached were also scored as
errors at decision points. A mean proportional error score was calculated for each
participant across each attempt. We note that alternative coding criteria produced the
same patterns of performance. For example, we coded just the decisions made the first time
participants approached a junction in each attempt. Participants scored 0 if they chose
the correct path or 1 if they chose the incorrect path, and any junctions not reached were
counted as errors. Therefore, 6 indicated the worse performance and 0 indicated perfect
performance. When this scoring was compared with the proportional error score (above),
there were no differences in the results. Therefore, in this Results section we report
only the proportional error scores. The mean proportional error scores made by each age
group before participants achieved criterion are shown in Table 3. The trend of these
results suggests that, irrespective of age, children and adults made a similar number of
errors. This was confirmed by non-parametric statistics, F(3) = 3.49, p = .32. We also
coded “looking” behaviors when participants retraced the maze. Every time participants
used the arrow keys to turn left or right to look down a junction, this was coded as a
looking behavior. Table 4 displays the mean number of looking behaviors across age group.
This shows that looking behaviors were similar across all age groups, although 10-year-
olds produced the fewest number of looks during the learning trials. This was confirmed by
non-parametric statistics, H(3) = 2.38, p = .50.

<h>DISCUSSION</h>
----------

This experiment addressed two research aims. Our primary aim was to find out whether
children could successfully retrace a novel route, having experienced that route only
once. The findings showed that some of the children, irrespective of age, were able to
successfully retrace a 12-turn maze in a VE. Nearly three quarters of the 12-year-olds,
half of the 10-year-olds, and a third of the 8-year-olds retraced the route without any
errors the first time they traveled it on their own. We emphasize that the route had 12
turns and, therefore, was challenging; nonetheless, some participants in each age group
retraced it successfully and without errors the first time they traveled it on their own.
We consider the implications of this aspect of children’s performance first. Past evidence
for young children’s route learning ability is limited, probably because of the practical
difficulties of testing children along safe routes in the real environment. Although past
researchers have demonstrated that young children can encode short routes of up to seven
turns in real environments (Cornell & Hay, 1984), there has been no previous research into
young children’s ability to learn longer routes. The current study is the first to compare
several age groups on a long route (with 12 turns). In the current study, the proportion
of 12-year-olds who retraced the route after one trial was similar to the proportion of
adults who did so (see Table 1). Although the similarity between the 12-year-olds’
performance and the performance of the adults confirms past research (Cornell et al.,
1989; Jansen-Osmann & Wiedenbauer, 2004), we note that the past research routes were
shorter (e.g., Jansen-Osmann & Wiedenbauer, 2004) or already familiar to children (e.g.,
Cornell et al., 2001). Therefore, the findings from the current study give a fuller
account of children’s wayfinding abilities by demonstrating that 12-year-olds have similar
route learning capabilities to adults, with many showing the ability to learn a long route
immediately. A second novel finding in the current study was that the 10-year-olds also
performed well, with half of the children in that age group retracing the route on their
first attempt. The youngest children, the 8-year-olds, were noticeably poorer than the
older age groups, and we note that this was the only group in which not all of the
children reached criterion (three children did not). Nonetheless, most children in this
age group did achieve criterion, and one third of the 8-year-olds retraced the route after
seeing it just once. This indicated the potential of even younger children to remember the
route successfully. Previous researchers have found that young children can recall routes
(Cornell & Hay, 1984; Spencer & Darvizeh, 1983) but tested children only over
comparatively short routes or through areas that might have been familiar to the children.
Finding that some children as young as 8 years can retrace a completely novel 12-turn
route after experiencing it just once was unexpected. Although most participants were able
to successfully retrace the route, there were different trends in performance across
different age groups. Although not significant at the statistical level, based on the mean
scores (see Tables 2 and 3), younger children (8-year-olds) made more errors and required
more trials to reach criterion than older children (10- and 12-year-olds), a finding
consistent with previous research (Cornell et al., 1989; Farran et al., 2012; Heth et al.,
1997; Jansen-Osmann & Wiedenbauer, 2004). These findings were also consistent with a six-
turn VE used by Lingwood et al. (2015a) in which older children (10-year-olds) made fewer
errors and required fewer trials to reach criterion than younger children (6-year-olds).
Younger children may have less mature cognitive abilities required for learning routes.
Evidence from previous studies suggests that children with better attention and long-term
memory tend to perform better when learning novel routes (Purser et al., 2012, 2015). In
addition, younger children may have less experience in retracing novel routes than older
children (Kitchin & Blades, 2002; Lingwood et al., 2015a). In the current study,
participants needed to avoid making repeated errors on more than one trial (perseverative
errors) if they were to succeed in reaching the learning criterion. This may have been
more difficult for younger children (Farran et al., 2012; Purser et al., 2012). There were
also other demands extraneous to the route following task that children needed to avoid to
ensure they sustained attention (such as inhibiting any desire to look away from the
screen, engage in conversation with the experimenter, or freely explore the VE).
Participants also needed to inhibit the desire to navigate toward irrelevant off-route
landmarks. Children who can inhibit inappropriate responses on other tasks (e.g., a Go/No-
Go task) do perform better on route learning tasks (Purser et al., 2012). Furthermore,
focusing on non-useful landmarks (i.e., the off-route landmarks in this study) during
route learning is associated with poorer navigational strategies (Broadbent et al., 2014;
Farran et al., 2010). This suggests that a variety of spatial working memory skills may be
important for wayfinding, particularly for younger children. The second aim was to
investigate at what age children demonstrated route learning abilities similar to adults.
Based on the mean scores (see Table 2), it was found that from 8 years of age onward
children made a similar number of errors and required a similar number of additional
learning trials as adults. Our results extend findings from previous studies (Cornell et
al., 1989, 1994; Jansen-Osmann & Wiedenbauer, 2004). Cornell and colleagues found that
children did not become adult-like in their route learning abilities until 12 years of age
rather than 8 years of age (as our data suggest). However, in Cornell and colleagues’
studies children were either 6 or 12 years of age, and so it was unclear whether children
under age 12 but over age 6 would perform at the same level as adults. Jansen-Osmann and
Wiedenbauer (2004) found that children as young as 11 years performed similarly to adults
when asked to find their way out of a VE maze. However, the children and adults who
participated in Jansen-Osmann and Wiedenbauer’s study explored a maze rather than learned
a specific route. Our results extend previous research findings and suggest that children
are able to learn and remember a route similarly to adults from 8 years of age onward. It
was not possible to determine precisely how children and adults retraced the route and
made few (if any) mistakes. For example, it is unclear whether participants relied on a
particular strategy when retracing the route such as recalling the left–right sequence or
focusing on landmarks at particular junctions. Nonetheless, we argue that being able to
accurately encode the correct left–right sequence of 12 turns independently of the route
would have been too cognitively taxing for participants, especially the younger children
(Hayashi, Fujii, & Inui, 1990). Therefore, we suggest that participants’ success depended
on recognizing landmarks as they were traveling along the route and that such recognition
then led to the recall of the appropriate action at a choice point. Adults may be adapted
to recognize landmarks given that neuroimaging studies have shown increased activity in
the parahippocampal place area associated with the recognition of landmarks (Epstein &
Vass, 2014; Marchette, Vass, Ryan, & Epstein, 2015). We note that some off-route landmarks
could also be viewed from the correct route direction heading. Therefore, there was a
possibility that participants used off-route landmarks to retrace the route. However,
evidence from neuroimaging studies suggests that we respond to on- and off-route landmarks
differently. For example, immediately after learning a route, the parahippocampal gyrus
shows increased activity only for on-route, as opposed to off-route, landmarks (Janzen &
van Turennout, 2004; Janzen et al., 2007). This suggests that the ability to identify
previously seen on-route landmarks may be particularly crucial for route learning. Cornell
et al. (1994) suggested that individuals used “place recognition” to help find their way.
For instance, when approaching a junction, individuals could look down the various paths
before deciding which path was most familiar to them. In this sense, the landmark would be
a “beacon” (Waller & Lippa, 2007), the assumption being that only one of the paths was
likely to contain landmarks or features previously seen when walking the route. However,
in the current study, we found that children and adults did not frequently look down the
alternative path when deciding which way to go. This may have been because they could
always see a landmark ahead of them. By always being able to view this landmark, this may
have helped them to differentiate between the correct and incorrect paths, and so in most
cases participants would not need to look down the alternative junction. We acknowledge
that in our experiments the junctions were made up of two path intersections and that each
junction was visually uncluttered. These types of junctions are easy to describe (Asher,
Tolhurst, Troscianko, & Gilchrist, 2013; Clarke, Elsner, & Rohde, 2013; Klippel, Tenbrink,
& Montello, 2013; Montello, 2005) and, therefore, may be easier to recognize or recall in
comparison with the visually complex junctions that are more likely to be found in real
environments. VEs have been shown to tap into similar cognitive mechanisms as the same
tasks in the real world (Richardson et al., 1999), and route learning in a VE can be
transferred to real-world environments (Montello, Waller, Hegarty, & Richardson, 2004;
Ruddle et al., 1997). Therefore, we predict that the current findings will generalize to
an environment in the “real” world, and future research could investigate this. However,
we note that proprioceptive and vestibular information is absent in desktop VEs (Taube,
Valerio, & Yoder, 2013). Such idiothetic features require consideration by employing
environments in which participants are more active (Chrastil & Warren, 2012). Given the
very good performance of some of the youngest children (the 8-year-olds), any further
examination of this age group, or indeed younger age groups in real environments, should
consider testing young children on routes that are much longer than have been used in
previous real-world environments. Previous studies have shown that adults are generally
good at learning a route (Karimpur & Hamburger, 2016), and this was confirmed by the
performance of the adult group in the current study. Three quarters of the adult
participants learned the 12-turn route after a single experience of the route. Adults’
success in the current experiment confirms that most adults can retrace a long route
without error after just a single exposure to that route. Because such a large proportion
of adults succeeded straightaway, it is unlikely that 12 turns is the maximum length of a
route that adults can encode in one experience; therefore, future researchers should
consider testing adults over much longer routes. The fact that many of the participants
learned the 12-turn route after just one experience of it does not support theories of
wayfinding that emphasize the need for route learners to construct a representation of a
route only slowly by first learning some or all of the landmarks along a route and then
combining these with actions at landmarks to form a route (Siegel & White, 1975). Rather,
the rapid learning demonstrated by many participants suggests that some children and most
adults can integrate landmark and turn information into a complete route on the basis of a
single experience, and this would accord with Montello (2017) that there are not separate
stages of landmark and route learning. The current study considered only one route and,
therefore, did not examine how multiple routes might be integrated into larger
representations of the environment, and so this study does not rule out the possibility of
other stages in learning more complex environments. To summarize, the current study showed
that most 8-year-olds (85%) and every one of the 10- and 12-year-olds and adults learned a
route consisting of 12 turns. Many participants did so without making any mistakes.
However, 8-year-olds made more errors and required more attempts to reach criterion than
the other groups, whereas these differences among the 10-year-olds, 12-year-olds, and
adults were less pronounced. These findings suggest that children from 8 years of age can
learn routes, even with as many as 12 turns, very quickly. The perfectly accurate
performance of even some of the youngest children, the 8-year-olds, when retracing the
route after just one experience demonstrated the potential of very young children to learn
a long route straightaway. Such successful performance has not been noted before;
therefore, more research with younger children over longer routes would be a useful focus
for future research.


<h>REFERENCES</h>
----------

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<ART>Validating a standardised test battery for synesthesia: Does the Synesthesia Battery reliably detect synesthesia?
================================================================================

Authors: D. A. Carmichael, M. P. Down, R. C. Shillcock, D. M. Eagleman, J. Simner
DOI: 10.1016/j.concog.2015.02.001
Year: 2015  |  Pages: 375-385
ASJC codes: 3204, 3205
Keywords: Assessment, Consistency, Grapheme-colour, Prevalence, Synesthesia, Test, Validation

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Synesthesia is a neurological condition that gives rise to unusual secondary sensations (e.g., reading letters might trigger the experience of colour). Testing the consistency of these sensations over long time intervals is the behavioural gold standard assessment for detecting synesthesia (e.g., Simner, Mulvenna et al., 2006). In 2007 however, Eagleman and colleagues presented an online 'Synesthesia Battery' of tests aimed at identifying synesthesia by assessing consistency but within a single test session. This battery has been widely used but has never been previously validated against conventional long-term retesting, and with a randomly recruited sample from the general population. We recruited 2847 participants to complete The Synesthesia Battery and found the prevalence of grapheme-colour synesthesia in the general population to be 1.2%. This prevalence was in line with previous conventional prevalence estimates based on conventional long-term testing (e.g., Simner, Mulvenna et al., 2006). This reproduction of similar prevalence rates suggests that the Synesthesia Battery is indeed a valid methodology for assessing synesthesia.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Synesthesia is an inherited condition in which everyday stimuli trigger unusual secondary
sensations. For example, synesthetes listening to music might see colours in addition to
hearing sound (Ward, Huckstep, & Tsakanikos, 2006). One particularly well-studied variant
is grapheme-colour synesthesia, in which synesthetes experience colours when reading,
hearing or thinking about letters and/or digits (e.g., Simner, Glover, & Mowat, 2006).
Despite being first reported over two hundred years ago (by Sachs, 1812; see Jewanski,
Day, & Ward, 2009) synesthesia was initially an under-researched and poorly-understood
area of human experience until the last decades of the 20th century. A significant factor
in the elevation of synesthesia as a tractable topic was the realisation – and subsequent
empirical confirmation – that synesthetes’ experiences could be verified behaviourally by
the fact that they remain conspicuously stable over time (Baron-Cohen, Wyke, & Binnie,
1987; Jordan, 1917). Specifically, synesthetes tend to be highly consistent when reporting
their synesthetic sensations for any given stimulus. For example, if the letter J triggers
the colour pale blue for a given synesthete, she will tend to repeat that J is pale blue
(not green, not yellow, etc.) when repeatedly tested over days, months and even years.
Indeed, one study was able to show that synesthetic sensations had remained consistent
over at least three decades (Simner & Logie, 2008). This stability of responses over time
is considered one of the central features of synesthesia and is routinely verified in
almost every publication on the subject (e.g., Asher, Aitken, Farooqi, Kurmani, & Baron-
Cohen, 2006; Baron-Cohen, Burt, Smith-Laittan, Harrison, & Bolton, 1996; Rich, Bradshaw, &
Mattingley, 2005; Ward & Simner, 2003; but see Simner, 2012). In other words, while a wide
range of behavioural approaches have been employed to assess the nature of the synesthetic
experience, experimental methodologies aiming to validate synesthesia have almost
exclusively focussed on the feature of consistency. Hence, researchers selecting
synesthete participants for study first verify the genuineness of each case by requiring
their synesthetes to demonstrate high levels of consistency over time compared to non-
synesthete controls (e.g., Asher et al., 2006; Baron-Cohen et al., 1996; Simner et al.,
2006). Controls are tested on analogous associations (i.e., they invent colours for the 26
letters, say, and then attempt to recall these colour associations later) and typically
perform significantly worse than synesthetes. Although more than a hundred contemporary
studies rely on this test of consistency for genuineness, the particular instantiation of
the test has varied widely. For example, a wide range of methods have been used to elicit
synesthetic colours: participants have indicated these by either giving verbal
descriptions (e.g., Ward, Simner, & Auyeung, 2005), written descriptions (Simner, Glover
et al., 2006), using Pantone© swatch colour charts (Asher et al., 2006), electronic colour
charts (Simner, Harrold, Creed, Monro, & Foulkes, 2009) or even computerised colour
pickers offering extensive palettes of >16 million colours (e.g., Simner & Ludwig, 2012).
In this way, synesthesia research has used varying methods, which in turn might raise
difficulties for researchers when trying to meaningfully compare data. Despite this
superficial variability however, the test of genuineness has nonetheless tended to rely on
one key shared feature: synesthetes must outperform controls over fairly lengthy re-test
intervals. Consider, for example, the most widely cited large-scale screening for
synesthesia (Simner, Mulvenna et al., 2006) in which a large sample of participants were
opportunistically recruited from the communities of Edinburgh and Glasgow Universities,
and individually assessed for synesthesia. Participants first indicated by questionnaire
whether they believed they experienced synesthesia, and those who reported in the
affirmative were asked to provide their synesthetic associations (e.g., the colours of
letters). These participants were then retraced after considerable time had passed (on
average 6.0 months) and were asked in a surprise retest to re-state their associations. A
group of controls without synesthesia performed an analogous task but were re-tested after
only two weeks. Synesthetes were able to significantly out-perform controls even though
much time had passed and the deck was effectively stacked against them. Methodologies such
as this allow confident detection of genuine synesthetes because the surprise retest over
lengthy intervals places the performance of synesthetes beyond the usual abilities of the
average person. The drawback to this methodology, however, is that the task is extremely
time-intensive to perform, and risks a high drop-out rate if synesthetes become
untraceable at retest. Perhaps for this reason, one of the most important developments in
the methodology of synesthesia validation came with the introduction in 2007 of an
alternative version of the test of genuineness. Eagleman and colleagues produced the
Synesthesia Battery, a toolbox of online tests which provides a standardised set of
questions, tests and quantitative scores to assess a range of synesthesias (Eagleman,
Kagan, Nelson, Sagaram, & Sarma, 2007). This battery is again based on internal
consistency in that synesthetes are validated by high consistency within their own
synesthetic associations, stated repeatedly. However, consistency is measured within a
single test session lasting only approximately 10 min. Specifically, synesthetes log on to
the testing site (www.synesthete.org) and specify which form(s) of synesthesia they
experience. The testing platform then presents their triggering stimuli (e.g., the 26
letters) one by one in randomized order, and participants are required to select their
synesthetic colour for each trigger. Each stimulus (e.g., letter) is presented three times
each, and a score is generated to quantify the consistency of participant’s responses
(e.g., did the participant choose the same/similar colours each of the three times she saw
a particular letter?) This score represents the geometric distance in RGB (red, green,
blue) colour space, where R, G, and B values are all normalised to lie between 0 and 1. If
the mean overall score of colour-distance is less than 1, the participant is classified as
a synesthete; if the score is 1 or higher, the degree of inconsistency classifies the
participant as a non-synesthete. However, it remains an open question whether this limited
retest interval is sufficient to truly distinguish synesthetes from non-synesthetes. In
the current study we assessed the validity of the Synesthesia Battery by using it to test
almost 3000 randomly sampled subjects for grapheme-colour synesthesia. Our aim was to
establish the prevalence of grapheme-colour synesthesia by this method. This will allow us
to evaluate the Synesthesia Battery by comparing this prevalence – obtained by assessments
within in a single test session – to the most widely accepted previous estimate of the
prevalence of grapheme-colour synesthesia based on the standard longitudinal test–retest
method (Simner, Mulvenna et al., 2006). If the Synesthesia Battery is just as effective a
method for detecting synesthesia as the more standard long-term retest method, we
anticipate an equivalent prevalence of grapheme-colour synesthesia across both methods. In
carrying out our study, we chose to evaluate grapheme-colour synesthesia in particular for
several reasons: it is one of the most common forms of synesthesia (Simner, Mulvenna et
al., 2006), it is particularly well-understood in behavioural terms, it lends itself
readily to online testing, and those who experience it typically demonstrate the high
levels of consistency expected from synesthetes (compared to other variants, whose more
complex concurrents may make them more difficult to assess via consistency alone; see
Simner, Gäartner, & Taylor, 2011 for discussion). It was not our intention to change or
try to improve upon the method made available by Eagleman et al. at www.synesthete.org.
Rather, we attempted to simply replicate their test and methodology and then evaluate how
it performs in comparison to a conventional longitudinal test–retest method. In evaluating
the Synesthesia Battery, our data will also provide an independent test of the prevalence
of synesthesia. Our baseline study – the widely cited prevalence study of Simner, Mulvenna
et al. (2006) – found the prevalence of grapheme-colour synesthesia to be 1.4% (for
synesthetes with both coloured letters and numbers) or 2% (for synesthetes with either
coloured letters or numbers). This study was based on a sample of 500 individuals, and the
prevalence rate it generated was subsequently verified by a secondary method testing a
further 1190 individuals (see Section 4 for details of this second method). Two previous
studies have also aimed to validate aspects of the Synesthesia Battery (Eagleman et al.,
2007; Rothen, Seth, Witzel, & Ward, 2013). Both studies used self-reported synesthetes who
had self-referred for study, in comparison to a group of controls declaring they were non-
synesthetes. it is important to highlight the difference between self-referred and self-
reported synesthetes. Self-reported synesthetes are any individuals who claim they have
synesthesia. Self-referred synesthetes are those who have additionally made the effort to
contact a university researcher to volunteer to take part in synesthesia studies. All
synesthetes tested by Eagleman, Rothen and colleagues were not only self-declared, but
also, importantly, self-referred. In comparison, none of the synesthetes tested here are
self-referred. Instead, our approach is to screen the general population (some of whom at
a certain point during our test, will self-report having synesthesia when asked, but will
not be self-referred). There are likely to be significant differences between our own
synesthetes, and the self-referred synesthetes of Eagleman, Rothen and colleagues. These
latter synesthetes not only know they have coloured letters, but also know this is called
synesthesia, and furthermore, they have made the effort to contact a university researcher
to volunteer to take part in synesthesia studies. They therefore have an understanding of
synesthesia and judge that the extent of their synesthesia is worthy of study by
researchers. In other words, it is at least possible that self-referrers have relatively
‘strong’ (or noticeable, or attention-catching) synesthesia in some way and may not be
entirely representative of the population of synesthetes at large. In summary, because of
the sampling methods of the two previous validations (Eagleman et al., 2007; Rothen et
al., 2013) their participant groups (synesthetes versus controls) may have had
diametrically opposing synesthesia characteristics, which might have therefore made them
relatively easy to distinguish between. Indeed, both Eagleman et al. (2007) and Rothen et
al. (2013) obtained a bimodal distribution of scores when assessing the consistency of
grapheme-colour associations of their self-referred synesthetes compared to controls. Here
however we individually assess a randomly recruited sample of subjects, allowing our own
study to extend the previous findings of Eagleman et al. and Rothen et al. and establish
how the Synesthete Battery performs when a distinction between synesthetes and non-
synesthetes is perhaps more difficult to achieve. Put differently, by testing a random
sample of the population, we expect to capture a broader, more representative range of
synesthetic experiences, and we are evaluating how the Synesthete Battery performs under
these conditions. In addition, our study will provide the largest estimate of the
prevalence of grapheme-colour synesthetes to date, with almost 3000 randomly sampled
members of the general population.1 Finally, our study also investigates a second aspect
of the Synesthesia Battery. After the single session test of consistency of coloured
graphemes, participants next immediately perform a second test of synesthesia: a speeded
congruency verification task (Eagleman et al., 2007). In this, participants are presented
with individual graphemes, but this time the graphemes are coloured either to match the
participant’s earlier colour selection (congruent), or to be a different colour
(incongruent). Participants must simply answer whether the letter-colour pairing matched
their previous choices or not, and their accuracy and speed is measured. Eagleman et al.
(2007) report that synesthetes tend to score 90% or higher with a mean RT of 0.64 ± 0.78
s, while non-synesthetes score below 90% with mean RT of 0.91 ± 0.87 s (Eagleman et al.,
2007). We will examine the sensitivity of this type of test to determine whether it too
has the diagnostic capability to distinguish between participants who score below the
consistency threshold score of <1 (i.e., synesthetes) and those who do not. In other
words, where Eagleman et al. (2007) compared self-referred synesthetes with non-synesthete
controls, we will extend this type of test to assess (a) randomly sampled participants,
who are (b) self-declared synesthetes, but who are not self-referred synesthetes, and who
are also (c) either verified as genuine versus non-genuine. As such, we are evaluating
whether this type of speed-congruency test still holds up in what is likely to be a more
sensitive comparison.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Two thousand eight hundred and forty-seven participants took part in our study (1317 male,
1530 female; mean age 28.6, range 16–90, S.D. 14.3). We had additionally tested 32 further
subjects who completed our study but had entered an obviously false date of birth (e.g.,
2013). These subjects did not enter our analysis, which was therefore based only on our N
= 2847. Participants were recruited as part of a large-scale, centrally co-ordinated
undergraduate research project. Every student registered on the 2nd year of the Psychology
undergraduate course at the University of Edinburgh acted as a research assistant (RA),
and was required to each recruit 8 participants (4 male and 4 female) over 16 years of
age. Our student RAs were not allowed to take part in the study themselves. In recruiting
our participants, we took a number of steps to ensure as random a sample as possible.
First, RAs were instructed not to deliberately seek out, nor to avoid, people they knew to
be synesthetes. Furthermore, in order to avoid self-referral biases, RAs were required to
pre-select their sample, and then approach participants in a targeted way (rather than
send out an advert and accept self-referrals). Indeed, RAs were required to refrain from
recruiting participants via any open calls at all, for example, they could not post the
testing URL on social media websites or internet forums. Finally, RAs were also instructed
not to a priori inform participants that the study involved synesthesia. The instructions
given by the RAs to prospective participants were uniform, and clearly stated that
participants were only allowed to complete the test once; if they had previously been
approached to complete the test by someone else, they were to inform the recruiter and not
proceed with the test. Our study was carried out in two waves to maximise participation
numbers: 1514 were tested in January 2013, and 1333 were tested in September 2013. Both
used identical methods, carried out by two consecutive intakes of 2nd year students. In
both rounds, the study was carefully managed and co-ordinated by authors JS and DAC. Data
from both rounds are pooled and presented together here.

<hs>  The online test</hs>
  ~~~~~~~~~~~~~~~

The online test consisted of several sections. Participants first provided informed
consent via a checkbox and then gave demographic information such as age, sex, handedness
and native language. A second section consisted of a health questionnaire not relevant for
the current study. (In this, subjects were requested to indicate if they suffered from a
range of clinical conditions, and this was for another project to be reported elsewhere.)
After this page, our online synesthesia assessment began with our locally stored replica
of the Synesthesia Battery. In this replica – as in the original – participants were first
asked whether they experienced grapheme-colour synesthesia, with the question “Do numbers
or letters cause you to have a colour experience?” This was accompanied by an example, and
then an option to accept separately according to whether these colours are triggered
automatically by numbers and/or digits. If participants indicated that they saw neither
letters nor numbers in colour, they advanced to an early-exit page thanking them for their
participation. The rest of the test was completed by participants who answered in the
affirmative to having coloured letters/digits. These participants completed two further
tests tailored to the particular variant of grapheme-colour synesthesia they had reported
(i.e., for either digits, letters, or both). These two tests were a colour consistency
test and a speeded congruency task. The colour consistency test was again an identical
clone of the consistency test from the Synesthesia Battery (Eagleman et al., 2007). In
this, participants were presented with each grapheme (a–z, 0–9) three times in random
order (so 30 trials if the subject reported coloured numbers only, 78 trials if letters
only, and 108 trials if both letters and numbers). For each trial, participants were
required to select the colour that best matched the grapheme presented (see Fig. 1).
Selections were made from a palette of 256 × 256 × 256 colours, exactly as in the original
Synesthesia Battery. Once their selection was submitted, the screen advanced to show the
next grapheme. The colour palette followed an HSL colour model, with colours varying in
lightness along the vertical axis and saturation along the horizontal access a separate,
horizontal bar allowed hue to be adjusted (see Fig. 1). The colour consistency test was
followed by a speeded congruency task. In this section, participants were shown again the
graphemes they had just seen in the colour consistency test. This time they saw each
relevant grapheme twice, in a random order, each flashed on screen for a maximum of 1 s or
until the participant responded (20 trials for just numbers, 52 trials for just letters or
72 trials for both letters and numbers). In 50% of trials, graphemes were coloured
congruently with the participant’s earlier specification, and in 50% of trials they were
coloured incongruently. Participants were required to indicate by mouse-click on the
relevant on-screen button whether the each grapheme they saw either matched or did not
match their previous colour pairing (as collected during the consistency test; Fig. 2).
Their response mouse-click advanced the test to the next grapheme, and the test continued
until all graphemes had been shown.2 In summary, the colour consistency test generated a
consistency colour-distance score, and the speeded congruency task generated an accuracy
score and a reaction time. For full details of website configuration and how the
consistency colour-distance score is calculated, see Eagleman et al. (2007).

<h>RESULTS</h>
-------

In our study, we classified as non-synesthetes all those who were directed to the early-
exit page (i.e., those who said they did not experience coloured letters and/or digits)
and all those who continued but scored 1 or higher. The remainder were classified as
synesthetes (i.e., those who scored <1). From our sample of 2847 participants, 140
subjects (55 male, 85 female, mean age 23.9, range 16–71, SD 9.5) self-reported grapheme-
colour synesthesia, giving a self-reported prevalence of 4.9%. Of those 140 self-reported
synesthetes, 34 obtained a colour-distance score of <1 on their consistency test (14 male,
20 female, mean age 24.9, range 17–51, SD 5.8), which is the criterion used by Eagleman et
al. (2007) to identify genuine synesthesia. This places the prevalence of genuine
grapheme-colour synesthesia at 1.2% and we will return to this prevalence value further
below. Of the 140 self-reported synesthetes, 55 reported experiencing coloured numbers
only, 58 reported experiencing both coloured numbers and letters and 27 subjects reported
experiencing coloured letters only (see Fig. 3a). Of the 34 participants that scored <1 on
the consistency test, 17 experienced coloured numbers only, 14 experienced both coloured
numbers and letters and 3 subjects experienced coloured letters only (see Fig. 3b). As an
additional check, the colour choices of the participants obtaining a consistency score of
<1 were examined individually to allow us to confirm that none of these achieved their
superior consistency by entering the same colour for each grapheme, or by entering an
obviously non-synesthetic pattern of colours throughout, e.g. red for ‘R’, green for ‘G’
and blue for ‘B’ (following Simner, Mulvenna et al., 2006). Next we analysed accuracy and
RTs in the speeded congruency task. We first divided our sample of self-reported
synesthetes into two groups, around to the consistency colour-distance threshold of <1.
For clarity, we refer to those who scored <1 as genuine synesthetes, and those who score
⩾1 we refer to as malingerers3 (i.e., non-synesthetes who self-reported synesthesia but
failed to achieve what is considered a synesthetic score in the colour consistency test).
There were 34 genuine synesthetes, as noted above, and 90 malingerers. There were also 16
subjects who reported too few coloured graphemes to generate a consistency colour-distance
score at all. Following Eagleman et al., 2007, participants were required to enter a
minimum of two valid graphemes to obtain a consistency score, a valid grapheme being
defined as one to which the subject entered a colour for all three presentations. These 16
are omitted from all further analyses below. (Finally, we remind the reader that there are
no values for participants who declared themselves to be non-synesthetes from the start
because these individuals did not progress to the synesthesia assessment.) Using an
independent samples t-test, we calculated the mean accuracy in the speeded congruency task
for each group: genuine synesthetes versus malingerers. This mean was 84.4% (SD = 11.8)
for synesthetes and 70.5% (SD = 14.9) for malingerers, and this difference was significant
(t(122) = 5.45, p < .0001, d = 1.03). There was no significant difference in mean reaction
times between groups (Synesthetes M = 1.93 s; SD = 0.77; Malingerers M = 1.76 s, SD =
0.73; t(122) = 1.13, p = .13, d = 0.23) see Fig. 4a and b). Mean reaction time was
calculated across all trials, irrespective of whether the participant had answered
correctly or incorrectly.4 In order to investigate whether this non-significant result
provided evidence for the null hypothesis we calculated a Bayes factor. By comparing the
likelihood of two models (in this case, the null and alternative hypotheses) as a ratio,
Bayes factors allow the researcher to evaluate to what extent the data supports the null
hypothesis (Rouder, Speckman, Sun, Morey, & Iverson, 2009). Following Jeffreys (1961), a
Bayes factor of less than 0.33 provides strong support for the null hypothesis, a Bayes
factor of greater than 3 provides support for the alternative hypothesis and values
inbetween indicate the data are insensitive and no firm conclusions should be drawn. Using
the online calculator provided by Rouder et al. (2009), we calculated a Bayes factor of
1.17, indicating that the data are not sensitive enough to enable a conclusion to be
drawn. Finally we explored how these two types of test (consistency and speeded
congruency) work in tandem in their assessments of synesthesia. If we take self-reported
synesthetes as a single group (i.e., collapsing genuine synesthetes and malingerers) there
was a significant inverse correlation between the consistency colour-distance score, and
the speeded congruency accuracy score (r(122) = −.71, p < .001; see Fig. 5). Remembering
that low colour-distance scores and high accuracy scores are both indicative of
synesthesia, this inverse correlation shows that those who performed like synesthetes in
the first sub-test were also more likely to perform like synesthetes in the second.
However, when we calculate this correlation for genuine synesthetes and malingerers
separately, it becomes apparent that the effect comes from the malingerer group only. The
correlation between consistency colour distance score and speeded-congruency accuracy
score for genuine synesthetes is non-significant (r(32) = −.07, p = .35) whereas for the
malingerers, the correlation is highly significant (r(88) = −.73, p < .0001). Finally,
there was no significant correlation between consistency colour-distance score and
reaction time (r(122) = −.05, p = .59), nor for accuracy score and reaction time (r(122) =
−.11, p = .22), and this also remained the case when correlations for the synesthete and
malingerer groups were calculated separately (synesthete consistency-RT = r(32) = .006, p
= .49; malinger consistency-RT = r(88) = .014, p = .45) (synesthete accuracy-RT = r(32) =
−.18, p = .14; malinger accuracy-RT = r(88) = −.09, p = .19).5

<hs>  Prevalence comparison between studies: Comparing short versus long-term testing</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The key aim of this study was to compare the prevalence of grapheme-colour synesthesia
generated by the Synesthesia Battery (a single-session test) to a more conventional method
based on long term (rather than single session) testing (Simner, Mulvenna et al., 2006).
Using the Synesthesia Battery we found the prevalence of grapheme-colour synesthesia in
the general population to be 1.2% for those with coloured letters or digits, compared to
the previous estimate of 2% in conventional longer-term testing (Simner, Mulvenna et al.,
2006). We can now evaluate that these two estimates are not significantly different (chi
square = 2.1; df = 1; p = .14). However, we also calculated prevalence for synesthetes
with both coloured letters and digits, finding a value here of 0.5%, and this is
significantly less than the 1.4% found in conventional longer term retesting (Simner,
Mulvenna et al., 2006; chi square = 5.6; df = 1; p = .02).

<h>DISCUSSION</h>
----------

In our study, we reproduced elements of the Synesthesia Battery (Eagleman et al., 2007)
which is a single-session online test for grapheme-colour synesthesia. We used this method
to estimate the prevalence of grapheme-colour synesthesia in a very large randomly
recruited sample – indeed the largest sample for this purpose to date. We found the
prevalence of grapheme-colour synesthesia in the general population to be 1.2% for those
with coloured letters or digits, compared to the previous estimate of 2% (Simner, Mulvenna
et al., 2006), a difference which is not significantly different. However, we also
calculated prevalence of synesthetes with both coloured letters and digits, finding a
value here of 0.5%, and this is significantly less than the 1.4% found in conventional
longer term retesting (Simner, Mulvenna et al., 2006). Hence, the Synesthesia Battery
numerically under-estimated the prevalence of those with coloured letters and digits,
compared to longer retesting methods and we explore possible reasons for this below. One
explanation for an under-estimation of prevalence in the Synesthesia Battery might stem
from the way graphemes are presented to those who report more than one variant: letters
and digits are presented together, randomly ordered within the same consistency test. In
the longer term retesting used as the baseline here however, letters and digits were
always presented in separate blocks (Simner, Mulvenna et al., 2006). It may therefore be
that synesthetes are susceptible to interference when selecting colours for graphemes, and
we raise this possibility for future studies to consider. A second possible explanation
for the lower prevalence found here is that immediate retests might be inherently more
conservative, and this might be suggested by the fact that prevalence estimates here were
numerically lower across the board. Immediate retesting might be conservative because the
scores of non-synaethetes are likely to be better across shorter (versus longer) time
intervals. In other words, non-synesthetes in an immediate retest (e.g., over 10 min)
should score higher than in a delayed retest (e.g., over several weeks) even though
synesthetes’ scores, in comparison, would be likely to remain relatively unchanged. This
would raise the control baseline for single session testing, and therefore allow a smaller
range of synesthetes to be identified as significantly more consistent. If this is
correct, we conclude that the threshold at which synesthetes are identified (currently
around the score of 1) might be usefully set marginally higher in the Synesthesia Battery
of Eagleman et al. (2007). One recent study has also speculated that the threshold in the
Synesthesia Battery perhaps should be raised. Rothen et al. (2013) have recently argued
that for the combination of RGB colour space and city block distance used by Eagleman et
al. (2007) – and also in this study – a higher cut-off may indeed be more appropriate. In
order to maximise sensitivity and specificity for this colour space/distance combination,
they proposed a revised threshold within the existing Synesthesia Battery at <1.43 for
synesthetes (rather than <1). In our own study, if we recalculate prevalence in our sample
using Rothen et al’s suggested cut-off score of 1.43, our prevalence estimates are no
longer significantly lower than expected. With this revised threshold, we now find 69
genuine synesthetes with coloured letters OR digits (2.4%; compared to 2% in Simner,
Mulvenna et al., 2006; chi square = 0.3; df = 1; p = .57) and 31 synesthetes with coloured
letters AND digits (1.1%; compared to 1.4% in Simner, Mulvenna et al., 2006; chi square =
0.367; df = 1; p = .5). In other words, our results are more in line with more
conventional longer term evaluations of synesthesia when the threshold is shifted upwards
according to the proposal of Rothen et al. (2013).6 Finally, we point out that Rothen and
colleagues also suggest that using alternative colour models (CIELUV and CIELAB) and
Euclidean distance provide the best combination of sensitivity and specificity in
distinguishing between synesthetes and non-synesthetes. However that change would be
beyond the scope of this paper, where we are simply evaluating the Eagleman data output as
it stands. Our discussion above of where to set the cut-off threshold for consistency in
the Synesthesia Battery might be considered part of a more fundamental concern in
synesthesia research. In all kinds of consistency tests for synesthesia – and particularly
obvious here – participants are divided into two groups by their score on what is in fact
an incremental continuum of possible scores. (Using this test, participants can, in
theory, score any value between 0 and ∼4, even though the cut-off is conventionally placed
at the fixed value of 1). It seems clear that someone who scores 1.05 on the consistency
test is “more synesthetic” than someone scoring 2.48, yet according to the cut-off of <1,
both would be considered non-synesthetes. Nonetheless, it is a particular strength of the
Synesthesia Battery that researchers are free to consider this score in its own right,
rather than for categorical groupings alone. The second part of Eagleman et al’s test
involved speeded congruency task in which graphemes are presented either in the same
colour previously selected (congruent) or a different colour (incongruent). Subjects must
indicate whether the colour they saw matched their earlier choice, and Eagleman et al.
(2007) report significant differences in speed and accuracy between a pre-selected group
of 15 self-referred synesthetes, and a non-synesthete control group. In our current study,
when our randomly-sampled respondents were divided into genuine synesthetes versus
malingerers (i.e., around the threshold score of 1), genuine synesthetes were again
significantly more accurate than malingerers. These data suggest that accuracy scores can
not only distinguish between self-referred synesthetes and non-synesthetes (as in Eagleman
et al., 2007) but is also subtle enough to distinguish between groups of genuine
synesthetes and those who claim to be so, but do not pass a conventional consistency test.
Furthermore, considering all self-reported synesthetes irrespective of their consistency,
there was a significant inverse correlation between consistency and accuracy, indicating
that more consistent (i.e., more ‘genuine’) synesthetes were also more accurate. However,
when this correlation was calculated separately for the each group (genuine synesthetes
and malingers) it became apparent that the effect was driven by the malingerers only. We
suggest this is because genuine synesthetes score highly on the accuracy test,
irrespective of what consistency score they achieve. In other words, a synesthete
obtaining a consistency score of, say, 0.99 is likely to be highly accurate on the
speeded-congruency test – as accurate as a synesthete scoring 0.4 on the consistency test.
In contrast, a malingerer obtaining a consistency score of 1.5 is more likely to be more
accurate on the speeded-congruency test than a malingerer scoring 3.5 for consistency. The
speed accuracy congruency test presented here showed one notable difference in results
compared to Eagleman et al. (2007). Our own findings were that genuine synesthetes,
although more accurate than malingerers, were no faster. Eagleman and colleagues found
genuine synesthetes to be more accurate and faster than controls. This difference to
Eagleman et al. (2007) may stem from differences in our control populations: Eagleman et
al. (2007) compared synesthetes to self-declared non-synesthetes, while we compared to
‘malingerer’ individuals claiming to have synesthesia. It is possible that some portion of
our controls were in fact synesthetic in some way, albeit with lower consistency, and
perhaps this is why our genuine synesthetes did not differ from them in their RTs (see
above and Simner, 2012 for discussion). Alternatively, our lack of difference in RTs may
be the result of the unanticipated variations we introduced in our version of this test.
Our method of selecting congruent and incongruent graphemes and the timing of grapheme
presentation for this part of the test differed slightly from Eagleman et al.’s original
approach (see Section 2 for a full explanation). Our own version may have raised the
difficulty of the task (e.g., because graphemes were on-screen for a shorter time on
average) and our RTs were certainly longer and hence potentially more noisy. There is no
way to distinguish between these two hypotheses in the current study and so we leave this
as an open question for future studies to address. We have evaluated whether single
session tests of consistency are effective at identifying synesthetes, compared to
established longer retesting methods. One previous study has also suggested that single
session testing may indeed be valid. Simner, Mulvenna et al. (2006) established the
prevalence of synesthesia both with long term testing (which we used here as our key
comparison) but also by screening additional 1190 people in a single session. Their method
was more basic than that of Eagleman et al. (2007) in that colour choices were made from a
palette of just 13 colours, and only absolute matches contributed to consistency scores.
Nonetheless, this again produced roughly comparable prevalence estimates as longer term
testing (1.1% prevalence for coloured letters and digits). Taken together with the current
study, we therefore suggest single session tests of consistency for synesthetic
associations do appear to provide an appropriate method by which to identify synesthetes.
The widely available nature of the Synesthesia Battery through its open-access online
interface makes it a particularly appealing version of this test, as does its
comprehensive colour palette, and its ability to give a calibrated estimate (i.e.,
continuous consistency score) for synesthesia status. Although researchers will want to
consider carefully the question of whether consistency testing can reliably identify every
type of synesthesia, or indeed every type of synesthete (see Simner, 2012 for discussion),
it is clear from our current study that the Synesthesia Battery provides a suitable tool
for evaluating synesthetes along this dimension.


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----------

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<ART>Verbal task demands are key in explaining the relationship between paired-associate learning and reading ability
================================================================================

Authors: Francina J. Clayton, Claire Sears, Alice Davis, Charles Hulme
DOI: 10.1016/j.jecp.2018.01.004
Year: 2018  |  Pages: 46-54
ASJC codes: 3204, 3205
Keywords: Cross-modal associations, Dyslexia, Paired-associate learning, Reading, Reading development, Verbal learning

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Paired-associate learning (PAL) tasks measure the ability to form a novel association between a stimulus and a response. Performance on such tasks is strongly associated with reading ability, and there is increasing evidence that verbal task demands may be critical in explaining this relationship. The current study investigated the relationships between different forms of PAL and reading ability. A total of 97 children aged 8–10 years completed a battery of reading assessments and six different PAL tasks (phoneme–phoneme, visual–phoneme, nonverbal–nonverbal, visual–nonverbal, nonword–nonword, and visual–nonword) involving both familiar phonemes and unfamiliar nonwords. A latent variable path model showed that PAL ability is captured by two correlated latent variables: auditory–articulatory and visual–articulatory. The auditory–articulatory latent variable was the stronger predictor of reading ability, providing support for a verbal account of the PAL–reading relationship.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The ability to create and consolidate associations between letters and corresponding
speech sounds is an essential component of learning to read (Melby-Lervåg, Lyster, &
Hulme, 2012; Muter, Hulme, Snowling, & Stevenson, 2004). Individual differences in
letter–sound knowledge are a powerful predictor of reading success (Lervåg, Bråten, &
Hulme, 2009; Muter et al., 2004). Paired-associate learning (PAL) tasks measure the
ability to form novel associations between stimuli and responses. Such associations may be
unimodal (between either visual or auditory stimuli) or cross-modal (between a visual
stimulus and an auditory stimulus). Learning paired associates depends on learning both
the individual stimuli and the association between them (Hülse, Egeth, & Deese, 1980).
Many studies have shown that performance on PAL tasks predicts children’s word reading
ability, and evidence suggests that PAL taps a mechanism, distinct from phonological
awareness, that is also important for learning to read (Lervåg et al., 2009; Warmington &
Hulme, 2012; Windfuhr & Snowling, 2001). Indeed, it has been suggested that the cognitive
processes underlying performance on PAL tasks reflect the very nature of learning to
read—the generation of novel associations between letters (and letter strings) and
phonological speech output (Ehri, 1992; Hulme & Snowling, 2013a; Snowling, 2000). In
previous studies, two different views have been taken about the nature of the relationship
between PAL and reading. One view is that this relationship reflects a role for cross-
modal learning as a fundamental process underlying reading development (e.g., Hulme,
Goetz, Gooch, Adams, & Snowling, 2007). A second view is that the PAL–reading relationship
depends specifically on verbal, or phonological, learning mechanisms (Litt, de Jong, van
Bergen, & Nation, 2013). There is some evidence that performance on tasks involving cross-
modal PAL is a stronger predictor of reading as compared with other unimodal PAL tasks. A
study by Hulme et al. (2007) investigated the relationship between reading and three PAL
conditions: two unimodal (visual–visual and verbal–verbal) and one cross-modal
(visual–verbal). Of the three conditions, visual–verbal PAL was most strongly correlated
with reading ability in typically developing children, although verbal–verbal PAL was also
correlated, albeit less strongly, with reading. Importantly, performance on visual–verbal
PAL was a unique predictor of word reading even after controlling for performance on
verbal–verbal PAL and phoneme awareness. Therefore, the authors suggested that the
PAL–reading relationship was specific to learning associations between visual
(orthographic) and verbal (phonological) representations. This cross-modal hypothesis is
consistent with the important role of letter–sound knowledge in predicting early reading
ability because acquiring letter knowledge also depends on the formation of cross-modal
visual–verbal associations (Hulme & Snowling, 2013b). In addition, the finding that
visual–verbal PAL is a unique predictor of reading after controlling for phoneme awareness
is in line with previous research (e.g., Windfuhr & Snowling, 2001) and suggests that PAL
ability depends on skills that are, at least in part, separable from children’s
phonological skills or the quality of stored phonological representations. In addition,
there is good evidence that, relative to typically developing controls, children with
dyslexia struggle to learn visual–verbal associations (Mayringer & Wimmer, 2000;
Vellutino, Scanlon, & Spearing, 1995; Wimmer, Mayringer, & Landerl, 1998). For example,
Messbauer and de Jong (2003) reported that children with dyslexia perform worse on
measures of visual–verbal PAL compared with a chronological-age-matched control group.
Children in this study completed three PAL tasks; two cross-modal (visual–word and
visual–nonword) and one unimodal (visual–visual). Children with dyslexia performed worse
on both visual–verbal PAL tasks (involving words or nonwords) but did not differ from
chronological-age- and reading-age-matched control groups on the visual–visual PAL task.
Impaired performance on both visual–verbal PAL tasks might suggest that a cross-modal
learning mechanism is important in explaining the PAL–reading relationship. However,
performance on such cross-modal PAL tasks also involves verbal learning, whereas the
visual–visual task involves only nonverbal stimuli and responses. In addition, Messbauer
and de Jong reported that when differences in phonological awareness were taken into
account, group differences on visual–verbal PAL tasks disappeared. Therefore, these
findings question the notion that cross-modal associative learning drives the PAL–reading
relationship. Rather, differences in verbal or phonological processing may be key.
Although the cross-modal account clearly has some support, the alternative verbal account
arguably has stronger support. The verbal learning account argues that it is individual
differences in learning verbal information that differentiates poor readers from good
readers. Litt et al. (2013) reported a study in which children learned pairs of stimuli
across four experimental conditions (verbal–verbal, visual–visual, visual–verbal, and
verbal–visual) in order to dissociate modality and task demands. Verbal stimuli were
consonant–vowel–consonant (CVC) nonwords, and visual stimuli were simple letter-like
symbols. Correlations with word reading were found only when verbal output was required
(verbal–verbal and visual–verbal conditions). Furthermore, performance in the verbal
output PAL conditions predicted significant variance in reading accuracy above and beyond
known predictors of reading such as phoneme awareness and rapid automatized naming. The
unimodal (verbal–verbal) PAL condition did not involve learning any cross-modal
associations. Thus, findings from this study provide strong evidence that verbal learning,
rather than cross-modal learning, is the most critical component of the PAL–reading
relationship. Further evidence in support of this notion comes from the finding that
children with dyslexia are impaired on verbal PAL tasks but not on nonverbal PAL tasks
(Litt & Nation, 2014; Mayringer & Wimmer, 2000; Vellutino, Steger, Harding, & Phillips,
1975). Across studies, poor readers consistently perform worse on verbal PAL tasks than
age-matched typical readers. For example, in one study children were given two cross-modal
PAL tasks; visual–verbal and visual–auditory (Vellutino et al., 1975). Children with
dyslexia showed deficits only in the visual–verbal task, but not in the visual–auditory
task, which involved imitating nonlinguistic sounds (e.g., high hum, cough), suggesting
that reading difficulties may be specifically associated with impaired verbal
(phonological) learning. Importantly, both conditions required cross-modal learning in
addition to oral output. In line with this finding, more recent research indicates that
children with dyslexia make more phonological errors, rather than associative errors, in
visual–verbal PAL tasks, implying that their poorer performance is driven by difficulties
with the verbal demands of the task rather than with associative learning (Litt & Nation,
2014). In summary, there is clear evidence to suggest that verbal learning mechanisms may
be important for explaining the PAL–reading relationship. However, to our knowledge no
existing studies have combined both cross-modal and unimodal and verbal versus nonverbal
PAL tasks. In addition, studies do not consistently address response modality (and
therefore response demands), which may be an important determinant of PAL performance. For
example, some “nonverbal” PAL tasks have involved learning associations between pairs of
visual symbols or pictures, requiring children to point to the correct response item. In
other instances, a completely different response, such as drawing the PAL symbol, is
required (i.e., Messbauer & de Jong, 2003). Such inconsistencies make it difficult to draw
firm conclusions about the mechanisms underlying performance on nonverbal PAL tasks. The
current study evaluated whether the PAL–reading relationship is primarily driven by verbal
learning demands (e.g., Litt & Nation, 2014; Litt et al., 2013) or cross-modal learning
demands (e.g., Hulme et al., 2007). The study included both unimodal and cross-modal PAL
conditions: phoneme–phoneme, visual–phoneme, nonverbal–nonverbal, visual–nonverbal,
nonword–nonword, and visual–nonword. The use of individual phonemes as stimuli extends
previous studies that have typically used nonword stimuli; the visual–phoneme task can be
seen as directly analogous to the process of learning letter–sound relationships. As in
previous studies, nonword stimuli were three-letter CVC strings (e.g., hib), allowing us
to investigate whether learning novel verbal information is a critical predictive
component in the PAL–reading relationship. If the PAL–reading relationship is driven by
verbal demands, performance in unimodal phoneme and nonword conditions should correlate
most strongly with reading measures relative to the nonverbal PAL conditions. On the other
hand, if the cross-modal conditions (including nonverbal PAL) correlate most strongly with
reading, this would provide support for the cross-modal hypothesis.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 97 children (49 boys and 48 girls) aged 8 years 0 months to 10 years 9 months
(M = 9 years 2 months, SD = 11 months) participated in the study. Children were recruited
from Years 4 and 5 in two state primary schools serving socially diverse catchment areas
in Hertfordshire, England.

        <hss>Reading</hss>

        Children completed the sight word efficiency (SWE) and phonemic decoding
        efficiency (PDE) subtests from the Test of Word Reading Efficiency (TOWRE-2;
        Torgesen, Rashotte, & Wagner, 1999). In this task, children were required to read
        as many words (SWE) or nonwords (PDE) as possible in 45 s. Children also completed
        the Single Word Reading Test 6–16 (SWRT6-16; Foster, 2007), in which they needed
        to read aloud a list of words in increasing difficulty. Testing was discontinued
        after five consecutive incorrect responses. Estimates of reliability for these
        standardized measures of reading are .98 (Cronbach’s alpha) for the TOWRE-2 and
        .90 (test–retest) for the SWRT6-16.

        <hss>PAL tasks</hss>

        Children completed six PAL tasks (phoneme–phoneme, visual–phoneme,
        nonverbal–nonverbal, visual–nonverbal, nonword–nonword, and visual–nonword), each
        presented as a computerized game. In each task, children were presented with four
        pairs of items to learn. In the visual–articulatory PAL tasks (visual–phoneme,
        visual–nonverbal, and visual–nonword), an unfamiliar symbol was presented on the
        computer screen and children were required to say the corresponding target sound
        (phoneme, nonword, or nonverbal sound) paired with that symbol. In
        auditory–articulatory PAL tasks (phoneme–phoneme, nonverbal–nonverbal, and
        nonword–nonword), the auditory target stimulus was played and children were
        required to produce the corresponding paired sound. The nonverbal–articulatory
        sounds included nonspeech sounds (e.g., lip pop, cough). Children were tested on 6
        consecutive school days for approximately 15 min and completed one PAL condition
        on each day as well as a standardized task from the test battery. The sequence of
        conditions was counterbalanced using a Latin square. The program randomly
        generated stimulus pairs for each child across the conditions. Each of the six PAL
        tasks involved children learning to produce the correct sound (a phoneme, nonword,
        or nonspeech sound) in response to a visual stimulus (a letter-like form) or an
        auditory stimulus (a phoneme, nonword, or nonspeech sound). In each condition,
        before teaching children any associations between item pairs, children were
        presented with each of the auditory stimuli used in that task and asked to
        reproduce it (they were required to repeat, one at a time, the four auditory
        stimuli used in each of the visual–articulatory conditions or the eight auditory
        stimuli used in each of auditory–articulatory conditions). In the rare event that
        a child had difficulty in articulating one of the auditory stimuli, the
        experimenter provided a correct demonstration and asked the child to try again.
        After this, children moved on to the learning trials. These began with a single
        presentation of each of the four pairs of stimuli the children were to learn.
        Children then received 24 test study trials. On test study trials, children were
        presented with each of the four stimuli and were required to produce the
        corresponding paired response sound. After children responded (irrespective of
        whether their response was correct or incorrect), the correct pairing was re-
        presented to reinforce learning. Children’s responses were recorded for each trial
        (correct, incorrect, or no response).

<hs>  Stimuli</hs>
  ~~~~~~~

Visual stimuli were 12 unfamiliar symbols (800 × 600 pixels) adapted from Taylor,
Plunkett, and Nation (2011). These stimuli are listed in the Appendix. All auditory
stimuli were recorded by a female native English speaker in a sound-attenuated booth and
included 12 phonemes, 12 nonverbal sounds, and 12 nonwords. Nonverbal sounds were adapted
from Vellutino et al. (1975) and consisted of sounds that did not involve phonemes and
could be easily produced. These sounds were high hum, low hum, smooch, raspberry, cough,
blow, pop with lips, gasp, tut, tongue click, sigh, and sucking front teeth. Phonemes
consisted of /kə/, /bə/, /pə/, /fə/, /gə/, /nə/, /rə/, /sə/, /wə/, /lə/, /jə/, and /mə/.
Nonwords were CVC nonwords taken from the ARC Nonword Database (Rastle, Harrington, &
Coltheart, 2002) as used in previous PAL studies (e.g., Litt et al., 2013): /hɪb/, /dʒɒf/,
/kæg/, /kæv/, /lɒm/, /mɪb/, /næl/, /pel/, /tʌs/, /vek/, /jɪz/, and /jʌt/.

<hs>  Apparatus</hs>
  ~~~~~~~~~

Stimuli were presented and responses were recorded using a Visual Basic program on a Dell
laptop (Latitude E5520) running Windows 7. Auditory stimuli were presented through
Beyerdynamic headphones (DT 770).

<h>RESULTS</h>
-------

We first present descriptive statistics and correlations for all measures before
presenting the main analyses, which use structural equation models to investigate the
relationship between reading ability and different aspects of PAL. Descriptive statistics
for all measures are shown in Table 1. Children performed at an age-appropriate level on
measures of reading. There were small amounts of missing data due to occasional absences
from school across the 6 consecutive days of testing and due to technical difficulties
that resulted in the loss of PAL data for 2 children. Correlations between all measures
are shown in Table 2 (simple correlations below the diagonal and partial correlations
controlling for age above the diagonal). There was a wide range in performance across the
PAL conditions. Performance was higher on the visual–articulatory PAL conditions compared
with the auditory–articulatory conditions, and performance varied in both sets of
conditions according to the type of response (phoneme > nonverbal sound > nonword). To
investigate differences in accuracy, we performed a repeated-measures analysis of variance
(ANOVA) with modality (2 levels: auditory–articulatory or visual–articulatory) and
response type (3 levels: nonword, nonverbal, or phoneme) as within-participant variables.
There was a main effect of modality, with performance on the visual–articulatory
conditions being better than performance on the auditory–articulatory conditions, F(1, 69)
= 250.91, p < .001, partial η2 = .784. There was also a main effect of response type, F(2,
138) = 281.45, p < .001, partial η2 = .168, indicating a significant difference in
accuracy across the three stimulus types (with phoneme responses being by far the
easiest). This main effect of response type was qualified by a significant interaction
between modality and response type, F(2, 138) = 17.79, p < .001, partial η2 = .205, which
reflects the fact in the visual–articulatory conditions the ordering of difficulty
(phoneme > nonword > nonverbal) differed from that in the auditory–articulatory conditions
(phoneme > nonverbal > nonword). This interaction reflects the fact that requiring
children to associate two different nonverbal sounds was a particularly difficult learning
task.

<hs>  Relationships between PAL measures and reading</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The latent variable path model shown in Fig. 1 was estimated with Mplus 7.4 (Muthén &
Muthén, 1998–2016). Little’s MCAR test confirmed that the small number of missing values
could be considered missing completely at random, χ2(98) = 115.1759, p = .11, and the
small number of missing values (n = 16) was handled with full information maximum
likelihood estimation. The theory we wished to test was that an auditory–articulatory PAL
could be distinguished from a visual–articulatory PAL factor and that the
visual–articulatory factor would show the strongest relationship with reading ability. As
a first step to developing the path model shown in Fig. 1, a confirmatory factor analysis
model was estimated with the six PAL tasks defining two correlated latent variables:
visual–articulatory PAL (visual–phoneme, visual–nonverbal, and visual–nonword) and
auditory–articulatory PAL (phoneme–phoneme, nonverbal–nonverbal, and nonword–nonword).
Adding a covariance between the two measures that involved a nonverbal response
(nonverbal–nonverbal and visual–nonverbal) resulted in a model with a good fit, χ2(11) =
13.907, p = .24, root mean square error of approximation (RSMEA) = .053 (90% confidence
interval [CI] = .000–.128), comparative fit index (CFI) = 0.97, standardized root mean
residuals (SRMR) = .051. Therefore, this structure was used for the path model shown in
Fig. 1. In the final model shown in Fig. 1, all latent variables were regressed on age
(although these regressions are not shown in the figure); hence, the model represents
relationships between the latent variables that are independent of the shared variance
attributable to age. An initial version of this model included paths from both PAL latent
variables to reading. However, in this initial model, the path weight from
auditory–articulatory PAL to reading was substantial and significant (.536, p = .043),
whereas the path weight from visual–articulatory PAL to reading was negligible in size and
not significant (−.087, p = .754). Dropping this path resulted in a nonsignificant change
in model fit, χ2 difference(1) = .103, p = .75. Therefore, we used this simplified model
where the nonsignificant path had been dropped. In this model, after controlling for the
effects of age, the two PAL latent variables are quite highly correlated with each other
(r = .79), but auditory–articulatory PAL showed a stronger correlation with reading (r =
.43) than visual–articulatory PAL (r = .36). The model accounts for 33% of the variance in
reading skills and provides an excellent fit to the data, χ2(29) = 29.014, p = .46, RSMEA
= .002 (90% CI = .000–.078), CFI = 1.00, SRMR = .057.

<h>DISCUSSION</h>
----------

This study explored the role of different types of PAL tasks as predictors of reading
ability in children. More specifically, we examined the role of different types of
associative learning (auditory–articulatory vs. visual–articulatory) and the type of
response required (phoneme, nonword, or nonverbal sound) as determinants of the strength
of relationship between reading and PAL. The findings from the path model are clear in
showing that an auditory–articulatory PAL latent variable is a strong predictor of reading
ability (accounting for 33% of the variance). However, after controlling for the effects
of auditory–articulatory PAL, the visual–articulatory PAL latent variable accounted for no
additional variance. This pattern contradicts earlier claims (Hulme et al., 2007) that
cross-modal PAL plays an especially important role in learning to read and supports the
view from later research that PAL tasks involving verbal learning are the ones most
closely related to learning to read (e.g., Kalashnikova & Burnham, 2016; Litt et al.,
2013; Messbauer & de Jong, 2003). The pattern of correlations in Table 2 shows that the
PAL tasks with higher auditory–articulatory learning demands show the strongest
relationship with reading ability. Specifically, among the auditory–articulatory PAL
tasks, the strongest PAL–reading correlation was observed for the nonword–nonword PAL
condition, and the lowest correlation was for the phoneme–phoneme condition. Arguably, the
amount of phonological information that needs to be retained in memory is far higher in
the nonword–nonword condition than in the phoneme–phoneme condition. Phonemes, in contrast
to nonwords, are short and highly familiar forms and, therefore, are less demanding to
learn. It is interesting that among the auditory–articulatory PAL conditions the
nonverbal–nonverbal task was a moderate correlate of reading ability (and stronger than
the phoneme–phoneme PAL condition). We selected this stimulus category for being
articulatory but nonverbal; however, it seems that the processing demands of learning
these nonverbal stimuli share something in common with learning about verbal stimuli
(phonemes or nonwords). The fact that nonverbal–nonverbal PAL correlates better with
reading than the phoneme–phoneme condition suggests that something akin to the load on
memory (where load reflects both stimulus familiarity and complexity) is driving the
relationship between PAL and learning to read. This notion of memory load also appears to
account for the pattern of relationships in Fig. 1. The auditory–articulatory latent
variable, which shows the strongest relationship with reading, involves measures with a
greater verbal–articulatory load than the tasks defining the visual–articulatory variable,
which relates to reading less strongly. In contrast to visual–articulatory PAL tasks,
successful performance on auditory–articulatory PAL depends on children learning both
stimulus and response when items are confusable (in the same modality/phonologically
similar). Therefore, these conditions involve the highest level of phonological
competition and, in turn, place the greatest demands on memory. Although children
demonstrated significantly higher accuracy in the visual–articulatory conditions, there
was still a reasonable distribution of scores across these conditions (i.e., children were
not performing at ceiling); therefore, it is unlikely that differences in task difficulty
can account for these results. It is possible that increased memory load is driving the
relationship between PAL and reading. However, an alternative theory is that both nonword
and nonverbal PAL tasks involve learning the associated articulatory gestures of novel
sounds, which may also be implicated in learning to read. According to the motor theory of
speech perception (Liberman, 1999), phonemes are encoded as articulatory gestures, and (in
line with this) studies have demonstrated improved visual word recognition following
training in analyzing articulatory gestures (Boyer & Ehri, 2011; Castiglioni-Spalten &
Ehri, 2003). An alternative explanation for this finding is that children were referring
to familiar or preexisting verbal labels (e.g., the words “cough” and “tut”) when
retrieving the nonverbal sounds in memory rather than encoding and retrieving the actual
nonverbal PAL stimuli. Given this possibility, it cannot be argued that this condition
performs the function of being entirely nonverbal. However, that is not to say that
performance in this condition depends entirely on verbal learning. For example, children
may remember a verbal label and its associated meaning and, therefore, may be engaging
additional skills rather than simply relying on phonological memory (see Laing & Hulme,
1999). It is clear that there are challenges in creating a nonverbal analogue of PAL while
keeping response modality (i.e., articulatory production) consistent, although further
research is needed to investigate nonverbal learning mechanisms and the possible role of
an articulatory learning mechanism in learning to read. In summary, the results presented
here are consistent with recent accounts and provide clear support for the role of verbal
learning in explaining the PAL–reading relationship (Litt & Nation, 2014; Litt et al.,
2013). We found that an auditory–articulatory latent variable was a stronger predictor of
reading ability than the cross-modal visual–articulatory latent variable. However, we also
found a strong correlation between reading and nonverbal–nonverbal PAL. This seemingly
provides counterevidence for the verbal account and highlights the methodological
advantage of the current study in comparing multiple PAL tasks. Thus, in conclusion, the
current study provides support for the verbal account of the PAL–reading relationship.
However, our results introduce the idea that articulatory learning might be an important
demand implicated in both verbal PAL and reading; as such, further research is required to
clarify the PAL–reading relationship.


<h>REFERENCES</h>
----------

  [1] Nancy Boyer, Linnea C. Ehri. Contribution of phonemic segmentation instruction with letters and articulation pictures to word reading and spelling in beginners. doi:10.1080/10888438.2010.520778
  [5] Charles Hulme, Kristina Goetz, Debbie Gooch, John Adams, Margaret J. Snowling. Paired-associate learning, phoneme awareness, and learning to read. doi:10.1016/j.jecp.2006.09.002
  [7] Charles Hulme, Margaret J. Snowling. Learning to Read: What We Know and What We Need to Understand Better. doi:10.1111/cdep.12005
  [9] Marina Kalashnikova, Denis Burnham. Novel Word Learning, Reading Difficulties, and Phonological Processing Skills. doi:10.1002/dys.1525
  [10] Emma Laing, Charles Hulme. Phonological and Semantic Processes Influence Beginning Readers' Ability to Learn to Read Words. doi:10.1006/jecp.1999.2500
  [11] Arne Lervåg, Ivar Bråten, Charles Hulme. The Cognitive and Linguistic Foundations of Early Reading Development: A Norwegian Latent Variable Longitudinal Study. doi:10.1037/a0014132
  [13] Robin A. Litt, Peter F. de Jong, Elsje van Bergen, Kate Nation. Dissociating crossmodal and verbal demands in paired associate learning (PAL): What drives the PAL-reading relationship?. doi:10.1016/j.jecp.2012.11.012
  [14] Robin A. Litt, Kate Nation. The nature and specificity of paired associate learning deficits in children with dyslexia. doi:10.1016/j.jml.2013.10.005
  [15] Heinz Mayringer, Heinz Wimmer. Pseudoname Learning by German-Speaking Children with Dyslexia: Evidence for a Phonological Learning Deficit. doi:10.1006/jecp.1999.2525
  [16] Monica Melby-Lervåg, Solveig Alma Halaas Lyster, Charles Hulme. Phonological skills and their role in learning to read: A meta-analytic review. doi:10.1037/a0026744
  [17] Vera C.S. Messbauer, Peter F. de Jong. Word, nonword, and visual paired associate learning in Dutch dyslexic children. doi:10.1016/S0022-0965(02)00179-0
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  [22] J. S.H. Taylor, Kim Plunkett, Kate Nation. The Influence of Consistency, Frequency, and Semantics on Learning to Read: An Artificial Orthography Paradigm. doi:10.1037/a0020126
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  [26] Meesha Warmington, Charles Hulme. Phoneme Awareness, Visual-Verbal Paired-Associate Learning, and Rapid Automatized Naming as Predictors of Individual Differences in Reading Ability. doi:10.1080/10888438.2010.534832
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<ART>Visual artificial grammar learning in dyslexia: A meta-analysis
===============================================================

Authors: Merel van Witteloostuijn, Paul Boersma, Frank Wijnen, Judith Rispens
DOI: 10.1016/j.ridd.2017.09.006
Year: 2017  |  Pages: 126-137
ASJC codes: 3203, 3204
Keywords: Artificial grammar learning, Dyslexia, Implicit learning, Meta-analysis

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background Literacy impairments in dyslexia have been hypothesized to be (partly) due to an implicit learning deficit. However, studies of implicit visual artificial grammar learning (AGL) have often yielded null results. Aims The aim of this study is to weigh the evidence collected thus far by performing a meta-analysis of studies on implicit visual AGL in dyslexia. Methods and procedures Thirteen studies were selected through a systematic literature search, representing data from 255 participants with dyslexia and 292 control participants (mean age range: 8.5–36.8 years old). Results If the 13 selected studies constitute a random sample, individuals with dyslexia perform worse on average than non-dyslexic individuals (average weighted effect size = 0.46, 95% CI [0.14 … 0.77], p = 0.008), with a larger effect in children than in adults (p = 0.041; average weighted effect sizes 0.71 [sig.] versus 0.16 [non-sig.]). However, the presence of a publication bias indicates the existence of missing studies that may well null the effect. Conclusions and implications While the studies under investigation demonstrate that implicit visual AGL is impaired in dyslexia (more so in children than in adults, if in adults at all), the detected publication bias suggests that the effect might in fact be zero.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Individuals with dyslexia have severe and persistent difficulties with learning to read
and spell. These difficulties occur despite normal intelligence, adequate educational and
socio-economic opportunities, and in absence of sensory or neurological impairment1 (DSM-
IV; American Psychiatric Association, 2000). A generally accepted hypothesis is that the
persistent difficulties with written language result from a core deficit in phonological
processing and, specifically, phonological awareness (see Melby-Lervåg, Lyster, & Hulme,
2012 for a meta-analysis). Phonological awareness is the ability to detect and manipulate
phonological segments of words (Shankweiler et al., 1995) and is related to the ability to
map letters to sounds, which in turn affects the ability to learn to read and spell.
Individuals with dyslexia also experience difficulties in other areas of language. Subtle
problems have been reported in the area of inflectional morphology (e.g. pluralization and
tense marking: Joanisse, Manis, Keating, & Seidenberg, 2000; subject-verb agreement:
Rispens & Been, 2007; Rispens, Roeleven, & Koster, 2004) and syntax (relative clauses:
Mann, Shankweiler, & Smith, 1984; Stein, Cairns, & Zurif, 1984, passive sentences: Stein
et al., 1984; binding: Waltzman & Cairns, 2000). Additionally, dyslexia is associated with
a range of non-linguistic cognitive dysfunctions, including impairments in visual and
auditory processing (Stein & Walsh, 1997; Tallal, 2004), attention (Facoetti a Paganoni &
Lorusso, 2000), motor functioning (Ramus, Pidgeon, & Frith, 2003), and verbal working
memory (Gathercole & Alloway, 2006; Gathercole & Baddeley, 1990; Swanson & Jerman, 2007).
Several theories have attempted to define the underlying deficit that accounts for the
range of problems experienced by individuals with dyslexia. One recent approach is
explaining dyslexia as the result of a problem with implicit learning (see Nicolson &
Fawcett, 2007; Ullman & Pierpont, 2005). The term implicit learning refers to the process
through which humans extract rules and regularities from visual and auditory sequences
available in the environment. Importantly, this happens in absence of awareness.

<hs>  Implicit learning and literacy acquisition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Many studies have related implicit learning abilities to different aspects of language
acquisition: the ability to segment words from continuous speech (Saffran, Aslin, &
Newport, 1996), the acquisition of phonological categories and phonotactics (Nicolson &
Fawcett, 2007; Wijnen, 2013), vocabulary acquisition (Evans, Saffran, & Robe-Torres, 2009;
Yu, 2008), and more general language processing (e.g. passives: Kidd, 2012; relative
clauses: Misyak, Christiansen, & Tomblin, 2010). Most important to the present discussion
is the relationship between implicit learning and the acquisition of literacy skills, as
these are the skills most affected in individuals with dyslexia. Learning to read and
spell involves the mapping between letters and sounds (grapheme-to-phoneme mapping), which
requires phonological awareness and knowledge of the orthographic system. This mapping,
and the writing system in general, comprises many regularities. For example, a single
letter (e.g. ‘c’) can map onto several phonemes (e.g./k/,/s/). Whether the letter ‘c’ is
realized as a/k/or an/s/, depends on co-occurring letters (e.g. the letter ‘c’ followed by
the letter ‘a’ generally results in the realization of the phoneme/k/as in can’t, but in
the phoneme/s/when followed by an ‘e’ as in cent). In other words, the writing system
consists of a “set of correlations that determine the possible co-occurrences of letter
sequences, which eventually result in establishing orthographic representations” (Frost,
Siegelman, Narkiss, & Afek, 2013, p. 2). Although some of these regularities in written
language are taught explicitly, it seems plausible that children’s literacy acquisition is
aided by implicit learning through exposure to written language. Previous research has
suggested a link between implicit learning and literacy skills in the typically developing
population (e.g. Apfelbaum, Hazeltine, & McMurray, 2013; Arciuli & Cupples, 2006; Arciuli
& Simpson, 2012; Frost et al., 2013; Pacton, Fayol, & Perruchet, 2005; Spencer, Kaschak,
Jones, & Lonigan, 2014). For example, typically developing children apply orthographic
regularities in pseudo-word spelling (e.g. in French, /εt/ is more often written as <ette>
after −v than after −f), which reflects their implicit knowledge of single letters and
letter combinations (Pacton et al., 2005). Similarly, Pacton, Perruchet, Fayol, and
Cleeremans (2001) show that French-speaking typically developing children are sensitive to
the orthographic constraints of the positions of double consonants (e.g. xevvu is more
acceptable than xxevu). Additionally, correlational studies have established a link
between performance on implicit learning tasks and reading in English (Arciuli & Simpson,
2012), reading in Hebrew as a second language (Frost et al., 2013), and a variety of
literacy-related skills including oral language, vocabulary and phonological processing
(Spencer et al., 2014). Using a linear regression analysis, Ise, Arnoldi, Bartling, and
Schulte-Körne (2012) showed that children’s performance on a visual artificial grammar
learning (AGL) task, a measure of implicit learning which will be explained in more detail
below, predicts their performance on a spelling task. Together, the abovementioned studies
suggest there is a relationship between implicit learning and (the acquisition of)
literacy skills in typical populations.

<hs>  Implicit learning in dyslexia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A number of studies have investigated the hypothesis that individuals with dyslexia have
problems with implicit learning, which affect their literacy skills. Several tasks have
been deployed to investigate implicit learning skills in dyslexia. Examples include the
serial reaction time (SRT) task (e.g. Deroost et al., 2010; Menghini et al., 2010; Vicari
et al., 2005), the alternating SRT task (Hedenius et al., 2013), as well as visual AGL
tasks (e.g. Ise et al., 2012; Pothos & Kirk, 2004; Rüsseler, Gerth, & Münte, 2006).
Although both the SRT and AGL paradigm are methods used to investigate implicit learning,
the type of structure learned in each paradigm differs (greatly). Whereas the SRT measures
a motoric response to visual sequences and is stimulus-bound (i.e. no generalization rule
can be abstracted from the sequence), the visual AGL measures rule learning from visual
input. While numerous studies report implicit learning difficulties in individuals with
dyslexia (e.g. Du & Kelly, 2013; Ise et al., 2012; Jiménez-Fernández, Vaquero, Jiménez, &
Defior, 2011; Vicari et al., 2005), others do not find evidence for such a deficit (e.g.
Deroost et al., 2010; Menghini et al., 2010; Pothos & Kirk, 2004; Rüsseler et al., 2006).
Because of these mixed results, Lum, Ullman, and Conti-Ramsden (2013) performed a meta-
analysis on 14 studies that investigated implicit learning in individuals with dyslexia
using the SRT paradigm. Their results show that implicit sequence learning, as measured by
the SRT task, is significantly poorer in people with dyslexia than in non-dyslexic
controls (average weighted effect size 0.45, p < 0.001). Thus, these results indicate a
deficit in implicit visuo-motor learning in dyslexia. In the current study we investigate
whether individuals with developmental dyslexia are also affected in visual artificial
grammar learning. If individuals with dyslexia have difficulties with implicit learning
across the board, group differences should be found using both the SRT and AGL paradigms.
However, it could also be the case that poor performance by individuals with dyslexia on
the SRT task is due to a specific motor learning deficiency, as dyslexia has previously
been associated with motor problems (e.g. Fawcett & Nicolson, 1995; Ramus, 2003; Ramus et
al., 2003). In that case, one would not necessarily also expect difficulties in the area
of visual AGL learning.

<hs>  Visual AGL in dyslexia</hs>
  ~~~~~~~~~~~~~~~~~~~~~~

Visual AGL refers to an experimental design that investigates participants’ ability to
implicitly learn rules from mere exposure to sequences of visual stimuli generated by
these rules. First introduced by Reber (1967), the visual AGL paradigm involves structured
sequences that can be presented as letters or abstract shapes. In visual AGL tasks,
sequences are generated on the basis of a (finite state) grammar that determines which
stimuli can and cannot succeed one another (Fig. 1). In the example depicted in Fig. 1,
from the node S2, the sequence can proceed either to S4 (a triangle) or S5 (a diamond),
but not back to S1. The AGL task typically consists of two phases: a training and a test
phase. In the training phase, participants are exposed to a set of structured sequences.
Importantly, in the implicit version of the AGL task that is explored in the current meta-
analysis, participants are not informed about the presence of the structural rules in the
input. The exposure during the training phase can be either passive (i.e. participants are
merely exposed to stimuli) or active (i.e. participants are instructed to memorize strings
of stimuli and repeat them afterwards). At the beginning of the test phase, participants
are often informed that certain rules guided the presentation of stimuli during the
training phase. Subsequently, they are tested on their ability to distinguish sequences
that adhere to the artificial grammar (grammatical strings) from sequences that do not
(ungrammatical strings). Typically, recognition of grammatical strings is tested within a
grammaticality judgment task in which participants are requested to specify whether single
strings are grammatical or ungrammatical. Other studies adopt a two-alternative forced
choice paradigm, where participants are presented with two strings, one grammatical and
one ungrammatical, and have to indicate which of the two strings belongs to the grammar.
Performance above chance level (50%) during the test phase is taken as evidence that
participants have learned the rules of the underlying grammar. Several studies using the
visual AGL paradigm have reported learning deficits in dyslexia among adults (Kahta &
Schiff, 2016; Laasonen et al., 2014) or children (Ise et al., 2012; Pavlidou, Williams, &
Kelly, 2009; Pavlidou & Williams, 2014). In each of these studies, this deficit is
reflected by significantly lower accuracy scores in the group of individuals with dyslexia
as compared to a control group. Several other studies failed to show a significant effect
of dyslexia in children (Nigro, Jiménez-Fernández, Simpson, & Defior, 2016) or adults
(Pothos & Kirk, 2004; Rüsseler et al., 2006). These differences in degrees of significance
might be due to chance (i.e. sampling error), because no direct statistical comparisons
were ever made between the studies. However, differences in group effects might also
reflect genuine differences between the studies. Here we will speculate on several factors
that may help explain such genuine differences between individual studies. Firstly, the
age of the participants may influence the results of individual studies, as several
studies have reported that implicit learning improved with age in typical populations
(e.g. Arciuli & Simpson, 2011; Maybery, Taylor, & O'Brien-Malone, 1995, but see Jost,
Conway, Purdy, & Hendricks, 2011). In a meta-analysis investigating SRT performance, Lum
et al. (2013) found smaller differences between participants with and without dyslexia for
studies involving adult as opposed to child participants when certain sequences of stimuli
were used (second-order sequences) or when the exposure phase was longer. However, no
previous studies have examined the developmental trajectory of AGL in individuals with
dyslexia. Secondly, the use of either linguistic or non-linguistic stimuli may influence
the difficulty of the task, especially for participants with dyslexia. Linguistic stimuli
include visually presented letters (e.g. Ise et al., 2012; Nigro et al., 2016; Rüsseler et
al., 2006), whereas non-linguistic experiments have used abstract shapes (e.g. Laasonen et
al., 2014; Nigro et al., 2016; Pavlidou et al., 2009; Pothos & Kirk, 2004). The results
are mixed: several studies report impaired learning within a AGL task involving linguistic
stimuli (i.e., letters, e.g. Ise et al., 2012; Samara, 2013), while others do not find
evidence for an effect of dyslexia (e.g. Nigro et al., 2016; Rüsseler et al., 2006).
Similarly, studies have yielded mixed results in AGL tasks with non-linguistic stimuli
such as abstract shapes (evidence for learning deficits: Laasonen et al., 2014; Pavlidou,
Kelly, & Williams, 2010; Pavlidou & Williams, 2014, no evidence for learning deficits:
Nigro et al., 2016; Pothos & Kirk, 2004). Thirdly, the training method potentially affects
participants’ performance. As mentioned, the training phase generally includes one of two
possible methods: passive exposure (Du, 2013; Laasonen et al., 2014; Nigro et al., 2016)
or active memorization (e.g. Ise et al., 2012; Rüsseler et al., 2006; Samara, 2013).
Active training may lead to better learning, as participants are more focused on the
stimuli. Whether the observed differences in results between the studies are genuine or
due to chance is one of the questions that the present paper tries to address. Thus, mixed
results exist for the visual AGL paradigm: whereas several studies report significant
differences between participants with and without dyslexia (e.g. Ise et al., 2012;
Laasonen et al., 2014), others do not (Nigro et al., 2016; Rüsseler et al., 2006).
Schmalz, Altoè, and Mulatti (2016) conducted a meta-analysis on a subset of studies
investigating visual AGL in dyslexia. They report significantly poorer performance by
participants with dyslexia (average weighted effect size 0.47). However, at the same time
they are careful in their interpretation and state “[…] publication bias and questionable
research practices result in an inflated effect size” (p. 9). As no meta-regression
analysis was performed, the authors could not quantitatively explain the differences in
effect size between studies. The primary aim of the present meta-analysis is to extend the
findings by Schmalz et al. (2016) to a larger set of (unpublished) studies and determine
whether the accumulated evidence indicates a difference in performance on visual AGL
between individuals with and without dyslexia. By doing a systematic literature search and
by including a number of unpublished studies, we want to provide a more complete update on
the strength of the evidence regarding the association between dyslexia and a deficiency
in visual artificial grammar learning. Additionally, we aim to investigate the effect of
certain methodological variables through a meta-regression analysis. These variables
include the age of participants and the nature and complexity of the task used, which
potentially help explain heterogeneity in results of individual studies. Factors included
in the analysis are (a) age (adult or child participants), (b) stimulus type (letters or
abstract shapes), and (c) type of training method (passive exposure or active
memorization).

<hs>  Literature search</hs>
  ~~~~~~~~~~~~~~~~~

We identified studies published up until September 2016 through searches in PubMed,
PsycInfo, ERIC, MEDLINE, CINAHL, and LLBA databases. Additionally, the OATD database was
searched for unpublished work in the form of theses and dissertations. A complete overview
of keywords used for each of the databases can be found in Appendix A in Supplementary
data. In addition to database searches, references of included articles were reviewed.
Finally, the CogDevSoc and LinguistList mailing lists were used to inquire whether
subscribers knew of unpublished data (deadline response: September 2016).

<hs>  Study selection</hs>
  ~~~~~~~~~~~~~~~

Fig. 2 depicts the selection of studies according to the Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) guidelines in a flow diagram (Moher,
Liberati, Tetzlaff, & Altman, 2009). Out of all 229 records found, 143 duplicates were
removed. Subsequently, one researcher examined the abstracts of 86 unique studies. Studies
had to fulfill several selection criteria for inclusion in the present meta-analysis.
First, only studies that had administered a visual AGL task were considered. The main
reason for a focus on visual AGL studies is to eliminate modality as a possible cause of
heterogeneity in results. Second, the experiment had to address implicit learning, i.e.,
participants were not to be informed of the presence of rules in the input. Third, studies
had to include two groups of participants, one group of individuals with dyslexia and one
group of non-dyslexic controls. Fifty-six records were removed after screening the title
and abstract because they did not meet the abovementioned selection criteria. An
additional 19 records were removed from the sample on the basis of full-article screening,
thus leaving eleven records for inclusion in the present review and meta-analysis. Two out
of the eleven records (Ise et al., 2012; Nigro et al., 2016) involved two experiments with
distinct participant groups that were included separately in the present meta-analysis,
resulting in 13 individual effect size calculations. For the remainder of the present
meta-analysis, we will refer to the number of individual effect size calculations as the
number of studies included (N = 13). A second researcher performed identical database
searches and assessed all abstracts and full texts. For 28 out of 30 full-text studies the
reviewers independently came to the same conclusions regarding inclusion in the present
meta-analysis (high inter-rater reliability: Cohen’s kappa = 0.851). Consensus on the
remaining two records was reached through discussion of the contents. Note that articles
did not have to have been published in peer-reviewed journals in order to be included in
our meta-analysis. This means that conference papers or posters, unpublished results and
dissertations could be included in the final sample (under the category “other” in Fig.
2). This was done to minimize the possibility of a publication bias. 10 out of 12 records
in this category were found through the OATD database (Open Access Theses and
Dissertations), of which 2 are included in the final sample (Du, 2013; Samara, 2013). The
other two were discovered through personal communication with authors or were presented at
the Interdisciplinary Advances in Statistical Learning conference (2015, San Sebastian2).
At the time of analysis, two out of thirteen individual effect sizes included in the
present meta-analysis were unpublished.

<hs>  Data extraction and effect size calculations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The standard measure of learning in an AGL task is the percentage of correct responses
(i.e. overall accuracy) during the test phase of the experiment. Therefore, the method for
comparing the performance of two groups on an AGL task is to test whether the overall
accuracy differs between the study and the control group. In order to calculate a single
effect size for each of the included individual studies, the mean, standard deviation (SD)
and sample size of each of the study groups were extracted from the article. If these data
were not available from studies themselves, we asked the authors to supply these. Authors
provided these data in three cases (Ise et al., 2012; Laasonen et al., 2014; Samara,
2013), which allowed us to calculate single effect sizes for each individual study. For
the study by Pothos and Kirk (2004), the SDs had to be gleaned from their Fig. 4 (p. 71).
Additionally, the mean age of participants was not available, but since participants were
(under)graduates, most aged between 18 and 30, this study was classified as a study
involving adult participants. Appendix B in Supplementary data presents an overview of the
extracted data that was used for effect size calculation for each included study. Tables 1
and 2 summarize characteristics of the sample and experimental design of the 13 studies
included in the present meta-analysis. Following data extraction procedures, a single
effect size was computed for each individual study, using the “compute.es” package (Del
Re, 2014) for R software (R Development Core Team, 2008). In the present meta-analysis,
Hedges’ g effect size4 and 95% confidence intervals summarize the results from each
individual study. Positive Hedges’ g values indicate that the control group reached higher
accuracy levels on the AGL task compared to the group of individuals with dyslexia,
whereas negative values indicate the opposite. The 95% confidence interval provides an
estimate of the precision of the study’s effect size: the larger the confidence interval,
the poorer the precision. A combination of the “metafor” (Viechtbauer, 2010) and “meta”
packages (Schwarzer, 2012) for R software was used to convert the computed individual
effect sizes and variances to an average weighted effect size5 and variance across
studies.

<hs>  AGL in dyslexia</hs>
  ~~~~~~~~~~~~~~~

Our first goal was to elucidate whether, combining the results from 13 previous studies,
individuals with dyslexia perform different from their TD peers on visual AGL tasks. To
this end, the effect sizes of all 13 individual studies were combined into a single
average weighted effect size using a random-effects model (Hedges & Olkin, 1985). Random-
effects models, as opposed to fixed-effect models, allow for variation in true effect
sizes between independent studies (Borenstein, Higgins, & Rothstein, 2009). The model was
run using the rma.uni function in the “metafor” package with the restricted maximum
likelihood (REML) method and the adjustment by Knapp and Hartung (2003) for finite numbers
of degrees of freedom. Effect sizes for individual studies and the overall average
weighted effect size are presented in Fig. 3. Performance was measured as the overall
accuracy score in the test phase of the AGL experiment. Effect sizes ranged from −0.68 to
1.37, with only one effect size in the negative direction (Pothos & Kirk, 2004). All other
studies report a lower accuracy level for the group of participants with dyslexia than for
the control group. Importantly, as mentioned, some of the individual studies report
significant differences, whereas others do not. The meta-analysis reveals that, grouping
over 13 studies and despite the negative-estimate study, participants with dyslexia
performed significantly worse than control participants (average weighted effect size =
0.46, 95% CI [0.14 … 0.77], p = 0.008). Looking at studies involving either child or adult
participants separately, we find that the average weighted effect size for child studies
is significant (N = 7, average weighted effect size = 0.71, 95% CI [0.36 … 1.07], p <
0.001), whereas it is not for adult studies (N = 6, average weighted effect size = 0.16,
95% CI [−0.36 … 0.69], p = 0.461). Before investigating whether the observed difference
between the adult effect (0.16) and the child effect (0.71) reflects a genuine decreasing
difference between dyslexic and non-dyslexic people as a function of age, we inspect the
possibility of publication bias.

<hs>  Publication bias</hs>
  ~~~~~~~~~~~~~~~~

To verify the interpretability of the abovementioned findings, we examined the possibility
of publication bias in our collected sample of studies. This was initially done through
examining a standard funnel plot, which plots the standard error (a measure of study
precision) against the effect sizes of the individual studies (Fig. 4a). Generally
speaking, in the absence of publication bias, studies should be symmetrically distributed
around the average weighted effect size. This distribution takes a funnel shape
configuration: studies with high precision are closer to the average weighted effect size,
whereas lower precision studies are symmetrically scattered around the average weighted
effect size. A linear regression analysis (Egger et al., 1997), using the metabias
function (Schwarzer, 2012), formally tested the presence of publication bias. It turned
out that effect sizes were significantly asymmetrically distributed, skewing to the lower
right corner, indicating the presence of a publication bias in our sample (t[11] = 4.014,
p = 0.002). To evaluate the effect of the publication bias in our sample we approximated
what the effect size might be in absence of this bias, using Duval and Tweedie (2000) trim
and fill method (trimfill function in the “metafor” package using the “L0” estimator for
the number of missing studies). Importantly, the trim and fill method can be used to
investigate how sensitive the observed effect is to the presence of potential missing
studies, but is not meant as a way to calculate the actual values of missing studies
(Duval & Tweedie, 2000; Duval, 2005). By using small studies on the positive side of the
funnel plot to impute missing studies on the negative side, the trim and fill method
estimated that five studies reporting negative findings are missing in our present sample
(Fig. 4b). When these five imputed missing studies are added to our dataset of 13 studies,
the estimated effect size is considerably reduced and is no longer significantly different
from zero (average weighted effect size = 0.20, 95% CI [−0.11 … 0.50], p = 0.205). Note,
however, that the trim and fill analysis is known to be a sometimes conservative method
for adjusting for publication bias (Peters et al., 2007; Schwarzer, Carpenter, & Rücker,
2010) and the creation of imputed studies can be heavily influenced by a single deviant
study, such as the study by Pothos and Kirk (2004) in our sample (e.g. Borenstein et al.,
2009, p. 286).6 Additionally, this method of adjusting results for publication bias makes
the assumption that the asymmetry observed in the funnel plot is caused exclusively by
publication bias, while another possible cause for funnel plot asymmetry is heterogeneity
between studies (Mavridis & Salanti, 2014). Finally, we cannot be certain that the
computed missing studies would indeed have been found in the absence of such a bias
(Mavridis & Salanti, 2014). Nonetheless, the results of the present meta-analysis on our
selected 13 studies are likely to be overly optimistic in the direction of the existence
of the main effect, as the effect can well be nulled by unpublished findings.

<hs>  Heterogeneity in findings and meta-regression</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The second aim of the present study was to explore several factors that may help account
for the heterogeneity (between-studies variability) that appears to be present across
different studies investigating AGL in participants with dyslexia. Although the main
outcome of the present meta-analysis is probably influenced by the observed publication
bias, such a bias is less likely to affect meta-regression analyses, which consider
secondary effects. Cochran’s Q-test for heterogeneity was significant (Q[12] = 41.07, p <
0.001, I2 = 71% [0.49 … 0.83]). This result allows us to reject the null hypothesis that
all the studies share a common true effect size. As can be seen in Fig. 3, it appears that
some factors may influence the effect size of individual studies. As mentioned, the
average weighted effect size for child studies is larger than for adult studies (0.71 for
child studies vs. 0.16 for adult studies). Thus, we decided to explore the effect of
several potential moderator variables on the effect sizes of individual studies through
meta-regression analysis. In preparation for the meta-regression analysis, all three
binary moderator variables were centered, i.e. coded as: (a) age −0.5 (child) versus +0.5
(adult), (b) type of stimulus −0.5 (abstract shapes) versus +0.5 (letters), and (c) type
of training −0.5 (passive exposure) versus +0.5 (active memorization). Random-effects
model meta-regression was used to explore the potential value of these factors in
explaining variance in effect size between studies. Since the three moderators are
correlated, we first tested each of the three main effects individually in a separate
meta-regression model (Table 3). Additionally, we tested each of the three interaction
effects individually, in a separate model that included the two relevant main effects
(also in Table 3). None of the interaction effects turned out to significantly affect the
effect sizes of individual studies, so we did not attempt to construct any more
complicated models. As shown in Table 3, the only model that reaches significance in
explaining variance between individual studies is model 1: the main effect of age. This
model fits 35% of the heterogeneity (which is greater than 0% with p = 0.041). When
studies had adult participants, as opposed to child participants, effect sizes were
smaller, reflecting a smaller difference between participants with and without dyslexia.
None of the other main or interaction effects were found to significantly fit the
heterogeneity between studies. To the extent to which a p-value of 0.041 can be considered
statistically significant in this exploration of six possible effects (without correction
for multiple testing), we can conclude that the difference between the observed adult and
child effect sizes (0.16 and 0.71) indeed reflects a genuine difference between the two
ages in the population.

<h>DISCUSSION</h>
----------

In the present study, we used meta-analysis and meta-regression to quantitatively review
previous research on visual AGL in dyslexia. Our first goal was to elucidate whether the
combined findings of thirteen previous studies provide evidence for a difference in visual
AGL between individuals with and without dyslexia. The average weighted effect size
computed from these individual visual AGL studies, reflecting results from 255
participants with dyslexia and 292 control participants, was found to be moderate and
statistically significant. If our 13 selected studies were a sample randomly drawn from an
imagined infinite set of possible studies, this finding would indicate that, overall, non-
dyslexic people outperform people with dyslexia on visual AGL. Our results would then
corroborate the earlier analysis in Schmalz et al. (2016) and strengthen these findings by
involving a larger sample of studies (13 instead of 9). Taken together with the meta-
analysis of SRT studies by Lum et al. (2013), these results would suggest a general
implicit learning deficit in individuals with dyslexia. Importantly, however, it seems
plausible that these results have been influenced by a publication bias in the field of
artificial grammar learning in dyslexia (see Schmalz et al., 2016). After conservatively
controlling for publication bias, the computed effect size was no longer significant, and
the results of the main effect of the present meta-analysis should therefore be regarded
as unreliable. Large-scale future studies are needed to confirm the presence of a
difference in performance on visual AGL between participants with and without dyslexia.
Extending the previously published meta-analysis by Schmalz et al. (2016) further, the
present study aimed to explain the heterogeneity in results of individual studies by
investigating the effect of certain methodological variables through a meta-regression
analysis. This analysis revealed that the only moderator that (moderately, i.e. without
correction for multiple tests) reached significance was the main effect of age: there were
smaller differences between dyslexia and control groups for those studies that involved
adult participants as opposed to child participants. This is an indication that the
implicit learning deficit might be more pronounced in children with dyslexia than in
adults with dyslexia, since similar effects of age have been found in the meta-analysis
investigating implicit learning in individuals with dyslexia using the SRT task (Lum et
al., 2013). In line with the interpretation of their results, a possible explanation is
that adults make use of compensatory processes (e.g. visual processing, pattern
recognition, attentional resources, declarative memory) that enhance performance on visual
AGL tasks. Another potential explanation for the age effect lies in the selection of
participants. Whereas most studies with adult participants involved university students,
child studies selected their participants from a broader population of primary school
children. The performance of university students with dyslexia may not be representative
of the whole population of adults with dyslexia, as these high-achieving individuals with
dyslexia may have more developed compensatory mechanisms. This in turn may result in a
smaller difference between the performance of adults with and without dyslexia. We want to
note that this effect of age should be interpreted with caution, as it seems to be largely
driven by one study that reports better performance in adults with dyslexia than in
controls (Pothos & Kirk, 2004, g = −0.68). Thus, future research should examine the
possibility of an age effect in visual AGL in dyslexia in further detail by selecting
adult participants with dyslexia from all educational levels and comparing them to
children on the same visual AGL task. Although the present meta-analysis suggests that
visual artificial grammar learning might be poorer in dyslexia relative to non-dyslexic
individuals overall, these results cannot address the issue of causality between implicit
statistical learning and literacy skills in this population. Future longitudinal studies
are needed to investigate the potential causal link between implicit statistical learning
and literacy skills in individuals with and without dyslexia. Additionally, several
factors that could influence the effect sizes of individual studies were not included in
the present meta-analysis due to the relatively small number of studies. One such factor
is the complexity of the underlying grammar. The level of complexity potentially plays a
role in whether participants are able to learn the underlying structure. In fact, a recent
meta-analysis of AGL studies with typical populations showed that, indeed, there is a
significant correlation between grammar complexity and learners’ task performance (Schiff
& Katan, 2014). Also related to the difficulty of the task at hand are factors such as the
length of the sequences and the amount of exposure to these sequences. Whereas some
studies use a fixed sequence length of 4 (Nigro et al., 2016), 5 (Ise et al., 2012), or 7
(Samara, 2013), other studies use sequences of varying lengths (between 2 and 6 (e.g.
Pothos & Kirk, 2004; Pavlidou & Williams, 2014), 4 and 7 (Rüsseler et al., 2006) or 6 and
8 (Du, 2013) individual items). Similarly, whereas some studies include only 69 instances
of a grammatical string (e.g. Laasonen et al., 2014; Pavlidou et al., 2009), others
include as many as 108 instances (Nigro et al., 2016). Another factor worth investigating
is the severity of dyslexia in individual participants, as this may be related to the
severity of the deficit in implicit statistical learning. Finally, the modality (visual
versus auditory) in which the stimuli are presented may affect the learnability of the
grammar for individuals with dyslexia. Future research should investigate the potential
effect of the abovementioned factors to gain further understanding of what types of
methodological characteristics increase or decrease an AGL task’s learnability for
individuals with and without dyslexia.


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<ART>Visual perception, visual-spatial cognition and mathematics: Associations and predictions in children with cerebral palsy
================================================================================

Authors: Valerie Critten, Emma Campbell, Emily Farran, David Messer
DOI: 10.1016/j.ridd.2018.06.007
Year: 2018  |  Pages: 180-191
ASJC codes: 3203, 3204
Keywords: Cerebral palsy, Mathematical abilities, Mental rotation, Visual memory, Visual reasoning, Visual-spatial perception

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Background: Previous research suggests that children with cerebral palsy (CP) have impairments in visual-spatial and mathematics abilities, although we know very little about the association between these two domains. Aims: To investigate the extent of visual-spatial and mathematical impairments in children with CP and the associations between these two domains. Method and Procedure: Thirty-two children with predominantly quadriplegic spastic and/or athetoid (dyskinetic) CP (13 years 7 months) and a group of typically developing (TD) children (8 years 6 months) matched by receptive vocabulary were given a battery of visual-spatial and mathematics tasks. Visual-spatial assessments ranged from simple tests of perception to complex reasoning about these stimuli. A standardised test of mathematics ability was administered to both groups. Outcomes and Results: The children with CP had significantly poorer mathematical and visual-spatial abilities than the TD group. For the TD group age was the best predictor of mathematical ability, in the CP group receptive vocabulary and visual perception abilities were the best predictors of mathematical ability. Conclusion and Implications: The CP group had extensive difficulties with visual perception; visual short-term memory; visual reasoning; and mental rotation all of which were associated with their mathematical abilities. These findings have implications for the teaching of visual perception and visual memory skills in young children with CP as these may help the development of mathematical abilities.

--------------------------------------------------------------------------------


<h>WHAT THIS PAPER ADDS</h>
--------------------

Results supported and extended previous research. Children with CP, in comparison with a
TD group, were found to have impairments to visual-spatial perception including processing
information in visual short-term memory, in mental rotation tasks and in matrices
reasoning tasks. The CP group also had significantly poorer mathematical abilities than
the TD group. We provide additional information about the presence of significant
relationships between visual-spatial perceptual abilities and the mathematical abilities
of both groups of children. We demonstrated that the CP group showed extensive,
significant relationships between visual-spatial tests and their mathematical abilities.
These findings suggest the potential importance of teaching and developing visual-spatial
abilities in children with CP, particularly those abilities that might have specific roles
in the development of mathematics. Further research in the form of interventions, such as
those described in a study of the impact of mental rotation training on arithmetic
performance (Cheng & Mix, 2014), may greatly benefit children with CP and their progress
in mathematical learning.

<h>INTRODUCTION</h>
------------

Cerebral palsy (CP) is typically caused by brain lesion(s) that are usually diagnosed
within the first two years of life. It is most often caused by brain trauma in the uterus;
at birth; or by other causes in early infancy (Rosenbaum, Nigel, Leviton, Goldstein & Bax,
2007). The condition affects the contraction, tone and function of muscles, and hence
motor development, with a prevalence of approximately 2–3 children in every thousand
(Odding, Roebroeck, & Stam, 2006). Research into CP has identified that, along with the
characteristic motor impairments, there often are cognitive impairments (Odding et al.,
2006; Stadskleiv, Jahnsen, Andersen & von Tetzchner, 2017). Related to this, many children
with CP have difficulties with developing mathematical concepts (Jenks, val Lieshout & de
Moor, 2012; van Rooijen et al., 2012). Previous research into the mathematical abilities
in CP have identified associations with mathematics and visual-spatial impairment such as
visual short term memory (Jenks et al., 2009; Peeters, Verhoeven, & de Moor, 2009); non-
verbal matrices tasks (van Rooijen et al., 2012; Jenks et al., 2007); and mental rotation
abilities (Courbois, Coello, & Bouchart, 2004). Thus, our investigation builds on previous
research by seeking to determine the precise profile of visual-spatial deficits in a group
of children with CP, and by investigating whether the reported deficits in visual-spatial
cognition and mathematics are associated.

<hs>  Typical mathematical development and visual-spatial abilities</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Mathematical skills develop on a ‘learning trajectory’ (Purpura & Ganley, 2014), that is,
understanding basic knowledge and skills is necessary before more complex mathematical
comprehension is achieved. There are a number of cognitive processes which contribute to
mathematical development. Research concerning typically developing (TD) children, for
example, has demonstrated that visual-spatial abilities are a strong predictor of
mathematical competence (see Uttal et al., 2013; Verdine, Irwin, Golinkoff & Hirsh-Pasek,
2014). In addition, visual short-term memory (STM) as assessed by Corsi block recall has
been linked to mathematical abilities (Fuchs et al., 2005; Kyttälä & Lehto, 2008).
Furthermore, non-verbal intelligence is usually assessed by tasks that involve visual-
spatial abilities (e.g. Raven’s Progressive Matrices RPM, Raven, Raven, & Court, 2008) and
has also been found to be related to mathematical ability (Deary, Strand, Smith, &
Fernandes, 2007; Kyttälä & Lehto, 2008). These findings provide a rationale to investigate
the relationship between visual-spatial perception and mathematical abilities in children
with CP.

<hs>  Mathematical abilities, visual-spatial abilities, and cerebral palsy</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Researchers comment on the paucity of investigations into numerical and arithmetic
abilities of children with CP particularly those involving aspects of visual-spatial
perception (Schmetz, Magis, Detraux, Barisnikov, & Rousselle, 2018; van Rooijen et al.,
2012). Available research has shown that children with CP are more likely to experience
difficulties with mathematical learning than TD children (Frampton, Yude, & Goodman,
1998), and a small number of studies have highlighted that children with CP are often
delayed in acquiring numerical skills such as: subitizing (quantifying sets); counting;
and basic arithmetic problem-solving (Jenks, van Lieshout, & de Moor, 2012; van Rooijen et
al., 2012). In a longitudinal study over two years, van Rooijen et al. (2014) found that
those children with CP and higher non-verbal intelligence increased their mathematical
skills on a trajectory similar to a comparison group of TD children; however, they did not
catch up with their TD peers. Many children with CP have visual-spatial perceptual
impairments despite typical or near-typical visual acuity (Akhutina, Foreman, Krichevets,
& Vahakuopus, 2003; Ego et al., 2015; Menken, Cermak, & Fisher, 1987; Reed & Drake, 1990;
Ortibus, Lagae, Casteels, Demaerel, & Stiers, 2009; Stadskleiv, Jahnsen, Andersen, & von
Tetzchner, 2017). Ego et al. (2015), in a systematic review of visual-perceptual
impairments in children with CP, identified 15 studies which included one of five
standardised tests that assessed visual perception. The review indicated that the
proportion of children with visual-perception impairments ranged from 40% to 50%, with no
study reporting a significant effect of CP subtype or IQ level, although the severity of
neurological lesions appeared to be associated with visual perception abilities. There has
been discussion of whether visual-spatial impairments could directly be caused by
neurological lesions and their sequalae (Menken et al., 1987), and it is also possible
that an inability to explore space because of physical disabilities may limit the
development of spatial functioning and visual-spatial skills in these children (see
Clearfield, 2004; Stanton, Wilson, & Foreman, 2002). Because of the fine-motor
difficulties of many children with CP (Ballester-Plané et al., 2016; Rosenbaum et al.,
2007) we decided to focus on visual-spatial perception assessments which do not involve
manipulation; the one that was chosen was the Test of Visual Perception ([TVPS-3]; Martin,
2006). We also decided to use three other assessments which not only involve visual-
spatial perception, but also additional cognitive processing of visual-spatial
information. These were a short term visual-spatial memory task, a mental rotation task,
and a matrices task. It has been reported that children with CP have impaired performance
on these tasks. In the case of visual-spatial memory, Gagliardi, Tavano, Turconi, and
Borgatti (2013) used a computerised version of the Corsi blocks task where children with
CP were asked to remember the sequence in which a set of blocks were touched by the
experimenter. The researchers found that the children with CP performed significantly
worse than TD children of the same chronological age. Different, age-related, errors were
observed across the CP group. For example, position errors, e.g. selecting blocks from the
wrong place, were more common in the younger children of the CP group, indicating visual
spatial memory difficulties, whilst the older children in the CP group were more likely to
have problems with sequencing skills (also see Schmetz et al., 2018). Corsi type tasks are
of relevance to mathematical ability as the visual spatial sketchpad may be used as a
‘mental blackboard’ (Baddeley, 2007) when distinguishing between different mathematical
forms and shape, as well as retaining previous visual information (see Hubber, Gilmore, &
Cragg, 2014). To date, there have been few studies on object-based mental rotation
abilities in children with CP. In these tasks participants identify whether rotated and
upright shapes have the same identity (see Fig. 1) (Schmetz et al., 2018). We included
this task for three reasons. Firstly, it measures a relatively pure form of visual-spatial
processing ability (Shepard & Metzler, 1971). Booth et al. (1999) have suggested that
during this process, mentally rotated stimuli are temporally stored in working memory, and
the visual-spatial sketchpad is implicated in the manipulation of the visual images
(Gathercole, Pickering, Ambridge & Wearing, (2004); Hyun & Luck, 2007). Thus, reduced
working memory capacity (i.e. limited cognitive resources) could be responsible for poor
task performances on these rotation tasks. Secondly, children with CP have been reported
to have impaired performance on this task (Courbois et al., 2004). Thirdly, mental
rotation has consistently been found to be strongly associated with mathematical abilities
in TD children and interventions involving mental rotation can help these children’s
mathematical performance on some types of problems (e.g. Cheng & Mix, 2014). Matrices
tasks are another assessment which have an important visual-spatial component in which
children with CP often have significantly low scores. In these tasks, several visual
arrangements of a pattern are presented, and the participant chooses an item to complete a
sequence which has a different but related visual arrangement. Children with CP have lower
scores on Raven’s Progressive Matrices (RPM or Raven’s Progressive Coloured Matrices
[RCPM], Raven et al., 2008) than chronologically age matched TD children (Jenks et al.,
2012; Peeters, Verhoeven, Van Balkom, & De Moor, 2008). This is usually interpreted as
indicating that the children have lower non-verbal intelligence as the task involves non-
verbal reasoning, but matrices tasks have an important visual-spatial component and
notably Ego et al. (2015) in their systematic review included the RPM as a visual-
perceptual assessment. Consequently, we were interested in investigating whether matrices
tasks had similar relationships to mathematical abilities as other visual-spatial tasks.
As far as we can ascertain there are few studies that have investigated the relationship
between matrices and mathematical abilities in children with CP (Jenks et al., 2009;
Peeters et al., 2009). van Rooijen et al. (2012) reported that CP children’s RCPM
performance was significantly correlated (r = 0.61) with their arithmetic abilities at
ages 6–8 years. In other studies, RCPM assessments have had a strong association with
basic mathematical abilities in children with CP who attend mainstream schools as well as
those who attend special schools (Jenks et al., 2007). Furthermore, this assessment has
been found to correlate significantly with addition and subtraction tests in CP children
aged between 6 and 11 years (van Rooijen, Verhoeven, & Steenbergen, 2011). Given these
previous findings, in the current study we investigated the extent to which visual-spatial
cognition and mathematical ability are impaired in children with CP, and the extent to
which these visual abilities predict mathematical ability. Thus, our investigation builds
on previous research by determining the precise profile of visual-spatial deficits in a
group of children with CP, and by investigating whether the reported deficits in visual-
spatial cognition predicts mathematical ability.

<hs>  Overview</hs>
  ~~~~~~~~

Although visual-spatial abilities have been identified as relating to mathematical
abilities in the typical population, there have been few studies which have focused on the
role of a range of visual-spatial assessments and their relationship to the mathematical
abilities of children with CP. Accordingly, it was decided to compare children with CP in
relation to TD children who had similar receptive vocabulary. Our first question concerned
whether there was a difference in the mathematical and visual-spatial abilities of the two
groups and the size of any difference. We were also interested in whether visual-spatial
impairments occurred when the assessments did not involve an important motor component
(i.e. the primary impairment in CP) and whether tasks that involved the processing of
additional visual-spatial information (e.g. memory, mental rotation, non-verbal reasoning)
made the tasks more difficult for children with CP due to cognitive load, for example,
switching attention (Henry, 2011). The second question concerned whether visual-spatial
abilities are related to mathematical abilities in CP, and how this compares to children
with TD. Because mathematical abilities are affected by age and language (Butterworth,
2005; Fuchs & Fuchs, 2002), we also examined whether visual-spatial abilities still
predicted mathematics scores when the effects of these potential confounds were removed.

<hs>  Design</hs>
  ~~~~~~

This is a cross-sectional study in which we are interested in group comparisons on
individual tasks between CP and TD children, and the relationships between visual-spatial
cognitive abilities and mathematical abilities for both groups. We used IBM: SPSS
Statistics software (version 21) and stepwise hierarchical regression analyses were
conducted to further examine the data. Given that individuals with CP are able to access
assessments involving receptive language (Bishop, Byers Brown, & Robson, 1990; Dahlgren
Sandberg, 2001), we decided to match a sample of children with CP to a TD sample using a
measure of receptive vocabulary. Given the broad battery of experimental measures that we
employed, which spanned across two domains, the choice of a matching measure was not
straight forward. Thus, we chose receptive language as a proxy for general IQ. Whilst this
does dictate that performance in the domains of interest is likely to be poor relative to
the TD group, the use of a battery of tasks enables us to ask questions regarding profiles
of performance, i.e. which aspects of visual-spatial cognition are more vs. less impaired,
and to detail how cross domain associations compare to those observed in the typical
population.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Thirty-two children with a diagnosis of CP (18 males), aged between 7 years and 18 years;
2 months, were selected from two special schools for children with physical disabilities
in the UK. The children were selected from special schools as they were an opportunistic
sample and the first author was familiar to the children in both schools. Medical
information was not available to the researchers, but observations made by experienced
teaching staff and the first author indicated that all the children, bar one, had
predominantly either quadriplegic spastic or athetoid CP or a mixture of both which had
variable effects on their functionality. The remaining child had hypotonic muscle tone and
poor posture, possibly ataxic CP (see Rosenbaum et al., 2006). Twenty-six of the children
used a wheelchair to move around school, and seventeen of these children used a walking
frame for part of the time. Six children moved around school with no aids. Teacher rating
of the children’s mobility using the Movement Assessment Battery for Children Checklist
(Henderson, Sugden, & Barnett, 2007) was undertaken and the results (higher scores up to a
maximum of 90 indicated poorer mobility) were as follows: Mean: 56.94; SD: 16.32; Minimum:
15; Maximum: 87. Most of the children performed typically in the section of the checklist
describing fine-motor abilities, e.g. manipulating small objects such as picking up beads
and moving small cubes except for one child who used her big toe for pointing and
keyboarding, and two others who found moving sheets of paper difficult. However, all the
children were able to point. The children were selected using the following criteria by
the teaching staff: Sufficient communication and speech abilities to verbally answer
questions in test situations; Typical visual acuity (with glasses if necessary); Typical
hearing abilities (with a hearing aid if necessary); Sufficient dexterity to respond to
the tasks. Ethical approval was obtained from the relevant University Committee prior to
the study (BERA, 2011). Parental written consent and the children’s verbal consent were
obtained prior to testing. Children were seen on an individual basis in quiet areas or
rooms. To avoid fatigue, particularly in the CP group, sessions were kept to between 20
and 30 minutes, over 6–8 occasions. Performance of the CP group was compared to that of 32
TD children (16 males) aged between 6 years 2 months and 11 years 7 months from three
mainstream schools in the UK. The two groups of children were individually matched for raw
scores on the British Picture Vocabulary Scale ([BPVS-III]; Dunn, Dunn, & NFER, 2009). As
can be seen in Table 1, the mean percentile score of children with CP indicates they had
poor receptive vocabularies.

<hs>  Procedure and assessments</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

All assessments were administered and scored according to the relevant assessment manual
by experienced researchers. The order of the assessments was determined by each researcher
according to the length of time available for each session, and the length of time taken
by each child to complete a task. Typically, the assessments for the children with CP were
undertaken in the following order: BPVS-III, Mathematics Oral test, Matrices from the
British Ability Scales 3rd edition ([BAS3] Elliot & Smith, 2011); Mathematics written
paper, Mental Rotation Task, Working Memory Test Battery (WMTB-C) Block Recall; TVPS-3
(R). In order to reduce fatigue, a longer test such as the BPVS-3 was followed by a
shorter test such as the Mathematics oral paper within one session. The children in the TD
group were assessed in sessions that lasted up to an hour.

        <hss>Receptive language</hss>

        Participants completed the British Picture Vocabulary Scale (BPVS III; Dunn et
        al., 2009), a measure of receptive vocabulary involving the child selecting which
        of four pictures corresponds to a spoken word.

        <hss>Mathematical ability</hss>

        Mathematics ability was measured using the Mathematics Computation test from the
        Wide Range Achievement Test ([WRAT-4]; Wilkinson & Robertson, 2006). This has two
        sections. Part 1 is an oral test comprising fifteen items starting with simple
        counting, identification of numbers and basic addition and subtraction
        calculations. Part 2 is a written paper with calculations involving the four rules
        of number, including fractions and decimals. It starts with simple sums and
        progresses to complex calculations and has to be completed within fifteen minutes.
        Scores from both papers are added together to give a total raw score.

        <hss>Visual-spatial measures</hss>

        Participants completed a battery of visual-spatial measures as detailed below.

            The Test of Visual Perception Skills 3rd Edition (Revised), TVPS-3 (R), (Martin, 2006)

            This test was used to assess a range of visuospatial abilities. It consists of
            seven subtests which measure a different aspect of visual or spatial
            abilities. The test is not timed. A summary visuospatial perception score can
            be calculated from the results of the seven sub-tests. Visual discrimination
            is the ability to distinguish between different shapes, patterns, forms or
            colours. The test requires the child to match a shape at the top of a page
            with one of the five shapes displayed at the bottom of the page This is the
            ability to remember the exact shape, form, number of visual stimuli for a
            short space of time. The test consists of seeing a shape on one page for five
            seconds. On the next page, the child has to identify the same shape from a
            display of four shapes. This is the ability to understand or recognise the
            positioning of shapes or objects. The test involves showing five shapes or
            drawings on a page of which four are identical and one is slightly different
            in some way. This is the ability to remember a sequence of visual information
            such as numbers or patterns. A child has to remember a specific shape or set
            of shapes which is presented on one page. After five seconds the child is
            presented with four sets of similar shapes on the next page, only one of which
            is identical to the first array. This is the ability to recognise or name
            shapes, forms or objects by their specific attributes. A shape is displayed on
            the top half of a page. The bottom half displays five shapes one of which is
            the top shape transformed in some way, e.g. by rotating the image. This is the
            ability to identify a shape which is inserted or placed against a background.
            The test requires a child to select which of four displays contains the
            identical shape to the one at the top of the page. This test requires the
            ability to make sense of images which are not clear or finished in some way.
            An incomplete shape is shown at the top of a page, e.g. a rectangle with no
            corners, and four complete images are shown at the bottom of the page. Only
            one of these images can be drawn from the incomplete shape.

            <hss>The Block Recall Test</hss>

            This test from The Working Memory Test battery (WMTB-C) (Pickering &
            Gathercole, 2001) was included as a measure of visuospatial short-term memory
            (STM). This test is akin to a Corsi block test.

            <hss>A Mental Rotation task</hss>

            This test was included as a measure of the ability to process spatial
            information. In this task (from Broadbent, Farran, & Tolmie, 2014),
            participants view two mirror imaged monkeys on the top half of a computer
            screen (Fig. 1). The children were asked to choose which of the two monkeys on
            the top half of the screen matched a monkey on the bottom half of the screen.
            Crucially, the monkey in the bottom half of the screen was displayed rotated
            at 0°, 45°, 90°, 135° or 180° (6 practice trials; 32 experimental trials). The
            percentage of correct responses was calculated for each participant. The task
            was completed on a laptop, but a large-keys keyboard was available for those
            children who found the laptop keys difficult to access. Two children in the CP
            group pointed to their chosen monkey and their choices were typed for them.

            The Matrices subtest from the British Ability Scales 3rd edition (BAS3) (Elliot & Smith, 2011)

            This test was included as a visual-spatial assessment of non-verbal reasoning.

<hs>  Group differences in mathematics and visual-spatial cognition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The mean raw and standardised scores of the WRAT-4, TVPS-3 (R), Block Recall and BAS-3
matrices are given in Table 2. Independent t-tests revealed that, despite the CP group
having a higher chronological age than the TD group, the CP group had significantly lower
raw scores than the TD group on WRAT-4 Mathematics (t[62] = −3.49, p < .001, d = −0.87)
and the four measures of visual-spatial cognition: the summary score for the TVPS-3
(t[62]= −7.05, p < .001, d = 1.76); WMTB-C Block Recall (t[62] = −4.86, p < .001, d =
1.21); the Mental Rotation task (t[62] = −4.5, p < .001, d = 1.16; and BAS-3 Matrices
(t[62] = −5.28, p <.001, d = 1.32). All of these comparisons produced large to extremely
large effect sizes (Cohen, 1992). A Bonferroni correction gives the critical significance
value for the five tests as p < .003, consequently, all differences can be considered
significant. Thus, these comparisons suggest that the CP group had significantly poorer
mathematical and visual-spatial abilities relative to the TD group. Because there were
group differences in the summary raw scores from the TVPS-3 it was decided to check
whether these differences occurred across all of the sub-scales. Table 3 details the mean
raw scores on the subtests. The children in the CP group scored lower than the control
group and independent t-tests gave the following statistics: Visual Discrimination t[62] =
−4.74, p < .001, d = 1.2; Visual Memory t[62] = −6.46, p <.001, d = −1.6; Visual Spatial
Relations t[62] = −6.45, p < .001, d = −1.6; Visual Sequential Memory t[62] = 4.93, p <
.001, d = 1.25; Form Constancy t[49.53] = 4.62, p < .001, d = −1.31; Figure Ground
t[53.65] = −5.74, p < .001, d = 1.57 and Visual Closure t[52.83] = 3.55, p <.010, d =
0.98. These differences involved large to extremely large effect sizes. Form Constancy,
Figure Ground and Visual Closure all had unequal homogeneity of variance according to
Levene’s test, these were checked with Mann-Whitney U tests (U = 228.50, p <.001; U =
135.00, p <.001; U = 265.50, p <.01 respectively). Applying a Bonferroni correction set
the critical significance value for the seven tests to p < .0008, as a result we need to
be cautious when interpreting these differences as significant, particularly the findings
about Visual Closure.

<hs>  Predictors of mathematical ability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To investigate the relationships between the four assessments involving visual-spatial
abilities (i.e. visual perception; visual STM; rotation; matrices task) to mathematical
abilities, stepwise hierarchical regressions were conducted separately for each
independent variable. The correlations between these variables are shown in Table 4. For
the TD group, the correlation between age, receptive vocabulary and mathematical ability
was above r = 0.80 giving rise to concern about multi-collinearity. However, for both
groups the relevant statistics for tolerance and VIF were satisfactory. Mahalanobis values
were acceptable except for one TD participant for mental rotations and the removal of this
case did not change the significance values, all Cook’s distance measures were acceptable.
Table 5 provides information about the outcome of the regression analyses. For each
multiple regression, age was entered at step 1 and receptive vocabulary was entered at
step 2. In this way age and language ability were controlled. At step 3 the independent
variable of interest (e.g. visual perception) was entered. For the TD group, the adjusted
R2 at step 3 was 0.82. At step 1, the entry of age resulted in a R2 change of 0.82 (p <
.001), and at step 2 the entry of receptive vocabulary resulted in a R2 change of 0.02 (p
< .070). However, the entry of the visual variables at step 3, failed to produce a
significant change in R2. Examination of the standardised beta coefficients at step 3
revealed that age was the only significant predictor, although the beta coefficients for
receptive vocabulary had p values between .05 and .10. For the CP group, the regression
equation accounted for slightly less of the variance, the R2 at step 3 was 0.75. In
contrast to the TD group, at step 1, the entry of age resulted in a non-significant R2
change of 0.04 (p < .001), and at step 2 the entry of receptive vocabulary resulted in a
significant R2 change of 0.56 (p < .001). The entry of the visual cognition variable at
step 3 always produced a significant increase in R2 (range 0.11–0.17). The beta
coefficients at step 3 show that only in one case did age have a significant coefficient
(mental rotation), whereas the beta coefficient for both receptive vocabulary and for the
visual-spatial variables always had values with p < .05. For some variables (visual
discrimination, visual STM and mental rotation), there was a noticeably higher beta
coefficient for receptive vocabulary than for the relevant visual ability. Additionally,
we investigated the relationship between the visual perception subtests and mathematics
performance in each group. For the TD group, the correlation between age and receptive
vocabulary was above 0.80 giving rise to concern about multi-collinearity (see Table 6).
However, all the relevant statistics for tolerance and VIF were satisfactory, as were
Mahalanobis values and Cook’s distance. In the regression analyses, as before, age was
entered at step 1, and receptive vocabulary was entered at step 2, with the relevant
visual perception subtest being entered at step 3. The findings from these analyses are
given in Table 7. For the TD group, the adjusted R2 was 0.83. The changes in R2 at step 1
and 2 were as before (for age at step 1, R2 = 0.82 (p < .001; for receptive vocabulary at
step 2 R2 = 0.02 (p < .070). However, at step 3 the entry of the visual perception
subtests, failed to significantly increase this variance except for one variable (visual
sequential memory). Examination of the standardised beta coefficients at step 3 revealed
that age was a highly significant predictor, and that the beta coefficient for visual
sequential memory indicated it was the only other significant predictor. For the CP group,
the adjusted R2 value was 0.58 and there were similar statistics for step 1 and 2 (step 1,
age, R2 change = 0.04, p < .001; and at step 3, receptive vocabulary, R2 change = 0.56, p
< .001). The entry of the visual perception subtests at step 3 always produced a
significant increase in R2 except for visual discrimination and form constancy. The beta
coefficients at step 3 showed that age was never a significant predictor of mathematical
ability, whereas receptive vocabulary was always a significant predictor, and five of the
visual perception subtests were significant predictors (the exceptions being visual
discrimination and form constancy).

<h>DISCUSSION</h>
----------

This study was carried out in order to determine whether the difficulties that children
with CP have with developing mathematical skills are related to their visual and spatial
perception impairments. The children in the CP and TD groups were matched on receptive
vocabulary, an assessment commonly used with children with CP (Bishop et al., 1990;
Dahlgren Sandberg, 2001). The children with CP were selected to have spoken language and
manual dexterity which were sufficient to complete the tests, so the results of this study
cannot be generalised to all children with CP. The group comparisons revealed that
mathematics and visual-spatial abilities in the CP group were at a lower developmental
level (based on standardised scores) than in the TD group and that their visual-spatial
abilities were generally very poor. The group comparisons showed that the test of visual
perception (TVPS-3) was the most problematic of the four assessments for the CP group as
shown by Cohen’s d (Tables 2 and 3) and so we will discuss this assessment first. The
analyses revealed that the CP group had lower raw scores on all the visual perception
subtests than the TD group and for all assessments there was a large to extremely large
difference. Given that we carried out analyses on all seven subtests it is possible that
some of these findings were due to chance factors, however, all differences were in the
same direction and the findings for the different subtests were similar. Across the seven
subtests there was no clear evidence of less impaired performance on the subtests without
notable memory demands (Visual Discrimination, Spatial Relationships, Form Constancy,
Figure Ground, and Figure Closure) compared to those that had memory demand (Visual
Memory, Visual Sequential Memory). Thus, our findings suggest that children with CP have
impaired performance with all the visual perception subtests in the TVPS-3, irrespective
of the form of the task. These figures are comparable to those produced in a study of
children with CP who also used the TVPS-3 (Menken et al., 1987). The finding that children
with CP had the lowest scores on the visual perception test, in comparison to the other
three tests which also assessed cognitive processing (memory, executive functioning,
general problem solving), suggests that visual perception impairments rather than more
general cognitive impairments might be the primary disability; although there was evidence
from the visual perception test that visual memory was both severely impaired and related
to mathematical ability. Consequently, there is the possibility that performance on some
cognitive and mathematical assessments is impeded by impairments in basic visual
perception rather than the cognitive demands of the tasks. We now turn to consider the
other three visual-spatial assessments. A computer version of the WMTB-C visual STM task
has been used by Gagliardi et al. (2013), who reported significantly lower performance of
children with CP compared to a CA comparison group. The children with CP in our
investigation also had significantly lower performance than the TD group on the visual STM
task. One reason for the low raw scores of the CP group on this test might be because of
poor fine motor skills as suggested by Gagliardi et al. (2013), however the children in
our study were considered by their teachers to have sufficient manual dexterity to
complete simple assessment tasks, and all of the children completed this test.
Furthermore, Stadskleiv et al. (2017) found that the physical dexterity of their
participants with CP made no difference to their abilities in a recall test (completed on
a computer), and informal observations by the first author suggested that the responses on
the visual STM task of children in our study were not dependent on precise motor movements
other than pointing. All this supports the idea that the CP group’s lower scores are more
likely to be due to their difficulties with perceiving the shape and positions of the
blocks or remembering the sequences of the blocks rather than their motor skills (see
Gagliardi et al., 2013). The Mental Rotation Task relies on the children’s abilities to
perceive and store visual information while attention is given to another picture and this
process is likely to involve executive working memory processes (Henry, 2011). A previous
study using mental rotation tasks which required children with CP to identify shapes that
were similar or mirror images of each other, demonstrated that the CP group had
significantly longer response times than the TD group, but a similar amount of errors
(Courbois et al., 2004). In our study, the children needed to identify markers such as the
position of the red and blue gloves on the hands of the monkeys or the position of the
arms (see Fig. 1) and remember these orientations while looking at the monkey in the
bottom of the picture. We found that the CP group had a significantly lower percentage of
correct responses than the TD group, and Cohen’s d indicated that their decrement of
performance on mental rotation was similar to the TVPS-3 subtests of Visual
Discrimination, Spatial Relationships and Form Constancy, all of which involve the ability
to make comparisons between different visual stimuli that are presented on one page. Thus,
for the CP children, the Mental Rotation task appeared to have a similar profile of scores
as other comparable visual-spatial tasks and it did not appear to be markedly more
difficult than other assessments of visual-spatial abilities. The children with CP also
had BAS-3 matrices scores that were significantly lower than those of the TD group. The
identification of low matrices scores in children with CP is consistent with other studies
which have used the RPM/RCPM (Jenks et al., 2012; Peeters et al., 2008). Our findings are
also consistent with the evidence that children with CP have better receptive language
than non-verbal ability as assessed by matrices tasks (Bishop et al., 1990; Dahlgren
Sandberg, 2001). However, our findings differ from those of Ballester-Plané et al. (2016),
whose study showed that participants with CP had better RCPM performance than receptive
language. The reasons for this discrepancy between the findings from their and our
investigation are not clear, although their participants were mainly adults and the types
of CP may be different as our participants had mixed types of CP. Research comparing
groups of children with CP suggest that children with dyskinetic CP may perform better on
receptive language assessments, but results are not conclusive (Ballester-Plané et al.,
2018). Further research is needed to understand the reason for any differences between
adults and children with CP. One explanation for the impaired visual-spatial abilities in
children with CP is that there could be motor or even perceptual difficulties when
executing relevant manual tasks that are used in the assessments (Abercrombie, 1964;
Akhutina et al., 2003). In addition, van Rooijen et al. (2012) reported that fine and
gross motor skills had significant correlations with arithmetic abilities in children with
CP, and fine motor skills was a significant predictor in a structural equation model which
contained assessments of decoding and non-verbal intelligence. As already mentioned the
visual-spatial tasks we administered had minimal motor components which suggest that
poorer visual-spatial performance was unlikely to have been directly due to motor
impairments. Regression analyses were conducted to investigate whether visual-spatial
abilities were related to mathematics performance and whether the relationships were
similar in the CP and TD groups. When interpreting these relationships, it is useful to
bear in mind that having low scores on a visual-spatial assessment does not necessarily
result in the assessments being significantly correlated with mathematical ability. In
theory, children could have had low scores on visual-spatial assessments, but these scores
might not be significantly related to mathematical ability, however, in their study, van
Rooijen et al. (2012) report that the RCPM was significantly correlated with arithmetic
ability in children with CP. The first set of regression analyses involved age and
receptive vocabulary as covariates, and each of the four visual-spatial perceptual
abilities. In the TD group, only age was a significant predictor of mathematical ability.
In contrast, in the CP group, receptive vocabulary and the four visual-spatial variables
were significant predictors of mathematical ability. This suggests that for the TD group,
age and by implication age-related general cognitive development, is more important than
receptive vocabulary and visual-spatial perceptual abilities in the development of
mathematical competence. Whereas, for children with CP, our findings suggest that
receptive vocabulary and visual spatial abilities are more important than age in the
development of mathematical competence. We also investigated whether there were
significant relationships between the visual perception subtests and mathematics ability
(see Table 5). Regression analyses revealed for the TD group that at step 3, mathematical
ability was significantly predicted by age, but not by receptive vocabulary and visual
perception (except in the case of visual sequential memory). In contrast, for the CP
group, receptive vocabulary was the most important predictor of mathematical ability, and
all the visual subtests except for visual discrimination and form constancy were
significant predictors of the mathematical ability at step 3. These findings suggest that
visual-spatial impairments in CP are wide reaching with cascading developmental effects on
other abilities. In addition, the presence of the significant relationships between
visual-spatial abilities and mathematics, even after accounting for age and receptive
vocabulary, suggests that in the CP group impaired visual-spatial abilities limit the
development of mathematical competence. However, given the number of regressions conducted
caution is needed when interpreting the significance of the findings, although it is
reassuring that the different analyses produced remarkably consistent findings.

<hs>  Implications and summary</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

This study has confirmed that many children with CP have visual-spatial perception
difficulties which are likely to have an effect on their ability to develop mathematical
skills. An inability to perceive and identify shapes and patterns can affect how children
learn to read and write numbers; learn to calculate sums such as on a number-line; read
and understand written problems; and set out sums. These are all basic skills that young
children develop before more complex tasks can be learnt. Teachers and clinicians need to
be aware of these difficulties and modify their teaching approaches to include tasks and
activities that can help to improve the children’s visual and spatial capabilities. Our
findings suggest that the largest impairments in these abilities involved visual memory,
visual spatial relationships and figure ground, while the strongest predictors of
mathematical ability involved visual memory, visual spatial relationships and visual
sequential memory. Therefore, activities that target these processes might be of help to
the education of children with CP. To summarise, researchers have identified that many
children with CP have difficulties with visual and spatial perception and have delayed
development in mathematical skills. Our investigation supported and extended these
findings. The analyses revealed that children with CP, in comparison to a group of
receptive language matched TD children, had significant poorer performance on an
assessment of mathematical ability and on a battery of visual-spatial assessments which
only required responses involving basic motor abilities. Furthermore, we did not find that
tasks which involved additional demands from the active processing of visual-spatial
information resulted in markedly worse performance. Moreover, in the CP group virtually
all of the visual-spatial assessments were significant predictors of mathematical ability
even after controlling for the effects of age and receptive vocabulary; whereas in the TD
group, virtually all the visual-spatial assessments had non-significant relationships with
mathematical ability. These findings suggest that in children with CP, visual-spatial
abilities may be important for carrying our mathematical tasks, and more important than
for TD children. Further research, possibly based around experimental interventions, is
needed to determine whether these associations involve a causal relationship.


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<ART>Voting for a personality: Do first impressions and self-evaluations affect voting decisions?
================================================================================

Authors: Markus Koppensteiner, Pia Stephan
DOI: 10.1016/j.jrp.2014.04.011
Year: 2014  |  Pages: 62-68
ASJC codes: 3200, 3207
Keywords: Person perception, Politics, Response surface analyses, Similarity, Social judgments

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Participants were asked to assess their own personality (i.e. Big Five scales), the personality of politicians shown in brief silent video clips, and the probability that they would vote for these politicians. Response surface analyses (RSA) revealed noteworthy effects of self-ratings and observer-ratings of openness, agreeableness, and emotional stability on voting probability. Furthermore, the participants perceived themselves as being more open, more agreeable, more emotionally stable, and more extraverted than the average politician. The study supports previous findings that first impressions affect decision making on important issues. Results also indicate that when only nonverbal information is available people prefer political candidates they perceive as having personality traits they value in themselves. © 2014 The Authors.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

People form first impressions on the basis of appearance and other nonverbal cues. Such
cues not only elicit quick attributions of personality traits and emotional states but
also appear to provide a sufficiently reliable source of information to support accurate
assessment of personality (e.g. Ambady, Bernieri, & Richeson, 2000; Borkenau, Mauer,
Riemann, Spinath, & Angleitner, 2004; Kenny, Horner, Kashy, & Chu, 1992). This ability
might help to make social interaction smoother but it is undeniable that such snap
judgments also affect public decision making. For instance, the verdicts of judges in
small-claims courts have been shown to be at least somewhat influenced by the facial
features of the defendant (Zebrowitz & McDonald, 1991). Similarly in the political arena:
successful self-presenters create social bonds with an audience not only by finding the
right words but also by displaying the “right” behavior (Cherulnik, Donley, Wiewel, &
Miller, 2001; Stewart, Waller, & Schubert, 2009). Nonverbal cues can be so convincing that
attributions of competence and other personality traits to photographs of political
candidates have been successfully used to predict electoral outcomes (e.g. Antonakis &
Dalgas, 2009; Ballew & Todorov, 2007; Olivola & Todorov, 2010; Poutvaara, Jordahl, &
Berggren, 2009). Consequently, in addition to voter and candidate ideology (e.g. Caprara,
Barbaranelli, Consiglio, Picconi, & Zimbardo, 2003; Roets & Van Hiel, 2009), politicians’
appearance and their nonverbal behaviors may also affect people’s voting behavior and how
they judge candidate personality. Communication, however, is not a one-way process.
Although there is often no direct interaction between speakers on stage and their
audience, information communicated has to be processed by the intended receivers. This
processing depends in part on how the members of an audience perceive and relate to the
speaker. Research has shown that people feel more closely connected to others they
perceive to be similar to themselves in attitude and personality (e.g. Berscheid, 1966;
Byrne, 1961; Tenney, Turkheimer, & Oltmanns, 2009). More pertinent to our research, this
connection also appears to play a role in politics, particularly when people do not gather
much information about candidates and their positions. For instance, people seem to vote
for politicians whose personality traits are similar to their own (Caprara, Vecchione,
Barbaranelli, & Fraley, 2007). Other findings even hint that the “similarity creates
liking” relationship applies to physiognomic features. If voters are unfamiliar with
politicians they seem to prefer candidates in whose faces they recognize themselves
(Bailenson, Iyengar, Yee, & Collins, 2008). The current study investigated the
relationship between first impressions and people’s tendency to favor others they regard
as having a similar personality. We conducted an experiment in which participants rated
short video clips of politicians giving a speech. The main focus of the study was first
impressions formed by nonverbal information; so to avoid interference from speech content
and different degrees of prominence we presented silent video clips showing politicians
that were unknown to our participants. Participants’ impressions were collected using a
brief version of a Big Five personality inventory. We also asked participants to report
their own personality and give an estimate of the likelihood that they would vote for the
speakers they had seen. Judging a stranger’s personality by brief displays of behavior may
be fairly accurate (see above); however, people are often misled by first impressions and
tend to simplify decision processes by relying on simple rules (e.g. Kahneman, 2003;
Olivola & Todorov, 2010). Given that similarity creates liking, we assumed that people
sometimes use their own personality as a kind of reference point when expressing
preferences for others. This effect may be even more pronounced for personality traits
people value highly and in situations of low information such as in our experimental
setting. We used polynomial regression analyses with response surface plots to analyze the
relationship between perceived personality, self-rated personality and voting probability
(e.g. Edwards & Parry, 1993). These statistical procedures provide information about how
congruence and incongruence between two independent variables relate to a dependent
variable. They also yield coefficients describing the nature of the relationships between
variables (i.e. linear and curvilinear), thereby providing a more comprehensive picture of
how the different variables are interrelated than other statistical procedures. In
summary, on the basis of research providing evidence for “similarity effects” in different
domains and the finding that people perceive themselves as being above average in ability
and character (e.g. Alicke, Klotz, Breitenbecher, Yurak, & Vredenburg, 1995; Ehrlinger,
Johnson, Banner, Dunning, & Kruger, 2008) we made the following predictions. First, we
hypothesized that our participants tend to “vote for” politicians in which they perceive
personality traits they also preferably ascribe to themselves. We did not have distinct
hypotheses to which personality traits this applies but expected to find patterns of
congruence between self-ratings and observer-ratings of some traits. To reveal such
patterns of congruence we used the aforementioned response surface analyses (RSA), because
this procedure provided detailed insights into whether and in what way self-ratings and
observer-ratings are related to voting probability. Second, we assumed that potential
candidates would be judged according to the self-attributed “high standards” of their
voters. We therefore expected the participants of the rating experiment to perceive
themselves as being above the average politician in those personality traits they
preferably ascribe to themselves. In other words, for personality traits the participants
valued highly we expected to find large differences between self-ratings and observer-
ratings. Consequently, the aim of this study was not to show that people are able to make
quite reliable guesses about someone else’s personality on the basis of brief displays of
behavior, but that people integrate self-perceptions into the guesses they make.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Eighty participants (42 females with age M = 23.1 years, SD = 3.7; 38 males with age M =
23.9 years, SD = 4.4) were approached personally at locations throughout the University of
Vienna and asked to take part in a rating experiment. Raters were not reimbursed for
participating in the experiment.

<hs>  Stimulus preparation and procedure</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We selected 40 speeches from the German houses of parliament (20 female and 20 male
speakers), and randomly extracted brief video segments from each of the speeches to give
40 video clips with an average length of 15 s. The lower portion of the video clips was
cut off to remove captions which gave information about the speaker’s name and party. The
speakers we chose were ordinary, non-prominent members of the German Bundestag, who were
not very well known in Germany and even less well-known in Austria. In addition, we asked
participants if they recognized any of the speakers they had judged. None of the
politicians were known to any participant. Stimuli were presented using a rating program.
The video clips were presented on the left-hand side of the program’s user interface; on
the right-hand side 20 bipolar personality terms (e.g. outgoing and reserved) based on a
brief German version of the NEO-FFI personality inventory (Borkenau & Ostendorf, 1991)
were displayed. This questionnaire assesses the Big Five personality dimensions of
extraversion, agreeableness, conscientiousness, neuroticism or emotional stability and
openness. Below the list of personality items the user interface displayed an additional
bipolar item: “I would vote for this candidate” or “I would not vote for this candidate”.
Participants completed their ratings by dragging a “trackbar control” to the right or to
the left pole of the bipolar scales using a computer mouse. The position of the bar
corresponded to points along a semantic differential, which was divided into 100 subunits
with 0 being the maximum value of the item on the left, 50 being the neutral position, and
100 being the maximum value of the item on the right. The same scale was used for the
voting choice item, enabling participants to give an estimate of the probability that they
would vote for a candidate. In order not to overtax the participants and to reduce the
influence of stimulus order, each participant only rated a subset of eight speakers
randomly selected from the 40 video clips.

<hs>  Analysis</hs>
  ~~~~~~~~

We aggregated the questionnaire data by summing items belonging to a latent personality
dimension (i.e. each personality dimension comprised four items). We then averaged
observer-ratings across the subsets of eight stimuli each participant had rated. The
resulting dataset − consisting of 80 self-ratings, 80 mean observer-ratings (i.e. for each
personality dimension), and 80 ratings on the continuous voting scale − was then analyzed
by means of polynomial regressions and response surface analysis (RSA). Polynomial
regression yields regression coefficients for two linear terms (i.e. observer-ratings and
self-ratings in this study), their interaction (i.e. relationship between observer-ratings
and self-ratings), and two quadratic terms (i.e. squares of observer-ratings and self-
ratings) and relates them to an independent variable (i.e. voting probability). To guard
against multicollinearity and to adjust differences in variances, which often affect the
interpretation of multiple regressions coefficients, we applied z-standardization before
the polynomial regression analyses. The regression coefficients obtained by polynomial
regression are used to calculate the response surface parameters a1–a4. These parameters
define the response surface (RS) plane of a three dimensional plot. RS plots have,
numerically, a line of congruence (LOC: X = Y) and a line of incongruence (LOIC: X = −Y),
which are derived by fully crossing the numeric levels of two continuous predictor
variables X and Y. The LOC is defined by a linear slope (a1) and a curvature (a2);
similarly the LOIC is defined by a linear slope (a3) and a curvature (a4). Thus, the LOC
and the LOIC provide insight into how congruence and incongruence between the independent
variables are related to a dependent variable, which is plotted on the Z-axis (see Table 1
and for more information see Edwards & Parry, 1993; Schönbrodt, 2013; Shanock, Baran,
Gentry, Pattison, & Heggestad, 2010). Applied to our data this means that self-ratings and
observer-ratings were plotted on the X-axis and the Y-axis of the RSA plot, while voting
probability was plotted on the Z-axis (see Figs. 1–3). Thus, self-ratings and observer-
ratings defined the plane of the three-dimensional plot. The LOC running from the near
corner to the back corner of the plot was derived by crossing equal values of self-ratings
and observer-ratings (i.e. where self-ratings of −1 corresponded with observer-ratings of
−1; self-ratings of 0 corresponded with observer ratings of 0, etc.). The LOIC running
from the left to the right corner of the plot was derived by crossing equal pairs of
negative and positive values of observer-ratings and self-ratings (e.g. where −1 met +1).
Along the LOC the parameter a1 estimated a linear additive effect (i.e. negative or
positive slope) of self-ratings and observer-ratings on voting probability, whereas the
parameter a2 gave information about the curvature (i.e. negative or positive) of this
relationship. In contrast, the parameters a3 and a4 informed about how a linear or a non-
linear relationship along the LOIC affected voting probability. To examine which
personality traits participants valued in themselves and how they perceived themselves in
relation to the politicians they saw, we compared participants’ self-ratings with their
average politician rating (i.e. the mean rating of eight politicians each participant
rated). The results of these analyses are presented as t-tests with standard effect size
measures (i.e. Cohen’s d), which in combination with the means give an estimate of the
degree and direction in which self-ratings differed from observer-ratings. All these
statistical analyses were done using the statistical software package R (R Core Team,
2013).

<hs>  Power analysis</hs>
  ~~~~~~~~~~~~~~

We had no specific hypotheses about the degree to which the different dimensions of the
Big Five traits would be related to voting probability. Other studies have found bivariate
and multiple correlation coefficients for certain personality traits with voting behavior
that explained more than 16% of total variance, so we expected that there would be a
medium effect size for at least some dimensions (Olivola & Todorov, 2010; Poutvaara et
al., 2009). We therefore assumed a medium effect (R2 = .15) for polynomial regression
analyses with an alpha level of .05, a power level of .8, and five predictors. On the
basis of these assumptions an a priori power analyses suggested an optimal sample size of
73 participants. Our study was also exploratory in that regard that the t-tests and their
corresponding effect size measures were used to determine in which personality traits
self-ratings differed markedly from observer-ratings. We expected that for highly valued
personality traits participants’ self-ratings would be at least moderately different from
the average politician rating because other findings indicated that the better-than-
average effect can be moderate to strong (Alicke et al., 1995; Ehrlinger et al., 2008). We
therefore performed an a priori power analyses with a Cohen’s d of .5 (i.e. threshold for
medium effect), an alpha level of .05, and a power of .8, which suggested an optimal
sample size of 64 individuals for the t-tests we applied. Power analysis was performed
using the statistical software package R (Champley, 2012).

<h>RESULTS</h>
-------

On average each politician was rated by 16 different participants with a range of 13–19
ratings. Measures of the questionnaire’s internal consistency with regard to observer-
ratings yielded moderate to high reliabilities for extraversion (Cronbach’s α = .80),
agreeableness (α = .87), conscientiousness (α = .72), openness (α = .62), and emotional
stability (α = .73). The participants’ self-ratings on the Big Five personality dimensions
showed a similar pattern. There were moderate to high reliabilities for extraversion (α =
.88), agreeableness (α = .84), conscientiousness (α = .82), and emotional stability (α =
.70), but low reliability for openness (α = .50). For this reason, the interpretation of
the results for openness presented below should be treated with some caution. Results of
response surface analyses (RSAs) are presented in Table 1. The proportion of the total
variance explained ranged from R2 = .10 for extraversion to R2 = .37 for agreeableness.
The parameters a1–a4 are central to RSA and provide estimates of congruence and
incongruence. Therefore, interpretation of the results mainly focuses on these parameters.
We assumed that similarity would play a role, but we had no specific hypotheses about
which personality dimensions would show a self-observer similarity (or congruence) effect
on voting behavior. In this regard our analysis was exploratory. Inspection of the
correlation coefficients revealed that extraversion yielded the lowest R2, but also that
none of the regression coefficients reached statistical significance. This indicates that
there was a relatively weak relationship between self-ratings and observer-ratings for
extraversion and voting probability. A similar interpretation can be applied to the data
on conscientiousness. Although R2 for this personality trait was higher than for
extraversion, none of the relevant RSA parameters were significant. In contrast, RSA for
all the other Big Five personality dimensions yielded significant results for at least one
of the relevant parameters. These results and the corresponding plots are discussed in
greater detail in the following subsections.

<hs>  RSA for openness</hs>
  ~~~~~~~~~~~~~~~~

RSA for openness provided a relatively strong positive linear relationship (a1 in Table 1)
along the LOC, which runs from the near corner to the far corner of the RSA plot (Fig. 1).
At first sight this indicates a congruence effect and that voting probability increased as
self- and observer-ratings of openness increased. However, the parameter b1 (i.e.
observer-rating in Table 1) and b2 (i.e. self-rating in Table 1) of the polynomial
regression revealed that observer-ratings of openness have a prevailing influence on the
RSA parameter a1. Apparently the participants’ aptness to vote for somebody they perceived
as open was predominantly affected by their first impressions. There was also a strong
linear relationship (a3 in Table 1) along the LOIC, which runs from the left corner of the
plot to its right corner indicating that self- and observer-ratings for openness showed
both congruence and incongruence. Inspection of Fig. 1 reveals more details how the
different variables were related and supported interpretations based on the parameters of
the polynomial regression. Overall, voting probability increased (i.e. higher values on
Z-axis) when observer-ratings for openness increased. Low self-ratings combined with low
observer-ratings (i.e. congruence) were not associated with a higher voting probability
than high self-ratings combined with low observer-ratings. However, high observer-ratings
were associated with higher voting probability regardless of whether they were combined
with low self-ratings (i.e. incongruence) or high self-ratings (i.e. congruence). In
conclusion, although data points in the RSA plot of openness appear to follow the LOC, we
found no clear effect of congruence for openness. Irrespective of their self-rating,
participants preferred politicians they rated highly for openness.

<hs>  RSA for agreeableness</hs>
  ~~~~~~~~~~~~~~~~~~~~~

For agreeableness RSA indicated a strong linear relationship (a1 in Table 1) along the
LOC. This suggests that congruence between self- and observer-ratings of agreeableness had
an impact on voting probability. However, Fig. 2 shows that the relationship between self-
and observer-ratings for agreeableness and voting probability were not so simple. When
self-ratings and observer-ratings were low, voting probability was also low (i.e. low
value on Z-axis of plot); concurrent increases in self- and observer-ratings were
associated with higher voting probabilities (i.e. positive slope of a1). There was also a
non-significant curvature (a2 in Table 1) along the LOC, indicating that voting
probability decreased slightly when ratings for agreeableness were high. In addition,
although RSA yielded no significant effect for incongruence (see a3 and a4 in Table 1),
high voting probabilities were observed when agreeableness ratings were somewhat
incongruent. For instance, some participants who rated themselves high on agreeableness
also tended to choose higher voting probabilities even for politicians they rated not
agreeable. In summary, conclusions for agreeableness resembled the conclusions we drew for
openness. Although congruence effects were more pronounced for agreeableness than for
openness, RSA indicates that participants mostly based their judgments on first
impressions and preferred politicians they perceived as being highly agreeable. In
comparison with this self-ratings of agreeableness seemed to be of minor importance.
Consequently, we found no clear similarity effect for this personality trait but a strong
effect of perceived agreeableness on voting probability.

<hs>  RSA for emotional stability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

RSA for emotional stability yielded a pronounced positive curvature along the LOC (a2 in
Table 1) and a pronounced negative curvature along the LOIC (a4 in Table 1). Consequently,
self-ratings and observer-ratings of emotional stability produced non-linear effects of
congruence and incongruence. The significant negative slope of parameter a4 (i.e.
producing a concave curvature along the LOIC) enhanced the robustness of the congruence
effect along the LOC. It shows that voting probability decreased when combinations of
self-ratings and observer-ratings were “far from the LOC” and incongruence between these
variables was strong. Inspection of Fig. 3 provides more clarity. The path of the LOC in
Fig. 3 reveals that voting probability was very high when low ratings were given for both
own emotional stability and speakers’ emotional stability. Voting probability decreased
slightly at moderate levels of congruence, and rose again at higher levels of congruence
between self-ratings and observer-ratings for emotional stability. Slight incongruence was
also associated with high voting probability but when self-ratings and observer-ratings
for emotional stability differed too much (i.e. low self-ratings combined with high
observer-ratings and vice versa), voting probability was lower. Overall, in comparison
with the other personality traits results for emotional stability provided the clearest
congruence effect.

<hs>  Differences between self-ratings and observer-ratings</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The comparison of observer-ratings of personality with self-ratings revealed that on
average participants gave themselves higher ratings on all five personality dimensions
(see Table 2). Exploratory analyses of these differences with t-tests and effect size
measures revealed strong effects for openness, agreeableness and emotional stability. A
medium effect size was found for extraversion and a very low one for conscientiousness.
This shows that participants believed themselves to be far more open, agreeable and
emotionally stable than the average politician. However, effect size measures (Cohen’s d)
should be interpreted with some caution because there were violations of variance
homogeneity.

<h>DISCUSSION</h>
----------

In this study we asked participants to rate themselves and short video clips of
politicians on scales measuring the Big Five personality traits and to give an estimate of
the probability that they would vote for each politician they evaluated. We used
polynomial regression and response surface analyses to examine whether the participants
were more likely to vote for politicians they perceived to be similar to themselves in
terms of personality. We expected similarity to have an effect, but we had no specific
hypotheses about which personality dimensions played a role. It was revealed that
regression models for openness, agreeableness, and emotional stability explained a high
proportion of the variance in voting probability. Less variance was explained by models
for extraversion and conscientiousness. This suggests that our student sample regarded
extraversion and conscientiousness as personality traits of minor importance to voting
decisions. A tendency to assign a higher voting probability to speakers that were
perceived to be agreeable is perhaps not surprising as politicians should appear likeable.
However, the propensity shown by our sample to attach great importance to openness and
minor importance to conscientiousness when making voting decisions might only hold true
for a student sample such as the one used in our experiment. Future studies should use
samples from different social groups, because it has been shown that the relationships
between political attitude and personality traits depend on social context and ideology
(e.g. Gerber, Huber, Doherty, Dowling, & Shang, 2010; Roets & Van Hiel, 2009) and it is
reasonable to assume that this also extends to perceptions of politicians’ personalities.
Although we found some incongruence between rater-politician similarity and its
relationship to voting probability, detailed analyses showed that participants tended to
vote for “someone like me” when the candidate was perceived to have similar emotional
stability. There were also similarity effects for agreeableness and openness but these
were less clear; the most prominent difference from the similarity effect observed for
emotional stability was that for openness and agreeableness concurrent low self- and
observer-ratings were not associated with higher voting probability. In addition, in both
cases observer-ratings were the more dominant contributor to the found similarity effects
and had a prominent effect on voting probability. It is conceivable that observer-ratings
on these personality traits have to reach a certain level before a similarity effect
delivers an increase in voting probability. People refrain from voting for a candidate
they rate as low on the personality traits they favor in political candidates. Such
reasoning may also be applied to emotional stability, but the surprising result was that
for this personality trait voting probability was highest when low self-ratings were
paired with low observer-ratings or high self-ratings were paired with high observer-
ratings. In between, at moderate levels of self- and observer-ratings voting probability
was less high, although the effect was still strong. Explanations for this pattern of
results are speculative at present. Our measure of emotional stability contained items
such as “aroused” vs. “composed”, which are adjectives that are typical of temporary
emotional states occurring during an experiment. It is possible that participants matched
their current emotional states with those they ascribed to the speakers they saw. Some
participants may have preferred a highly aroused politician because they were also easily
aroused; others may have preferred a very composed politician because they were very
composed. This kind of matching behavior might have influenced voting decisions more
strongly at the extremes of emotional stability. Student’s t-tests revealed that in nearly
all cases the participants gave themselves higher ratings for the traits they seemed to
value highly in politicians they would vote for (see previous section). Participants
regarded themselves as being more open, more agreeable, more emotionally stable and more
extraverted than the average politician in our sample. Whilst this might be due to the
poor public image of politicians, it is common to find that people regard themselves as
“better than average” (e.g. Ehrlinger et al., 2008). Surprisingly, no noteworthy
difference between self-ratings and observer-ratings could be found for conscientiousness,
which suggests that our student sample did not value conscientiousness as highly as the
other personality traits we investigated. This result may be due to the difficulty of
evaluating conscientiousness from brief displays of behavior. However, taking into account
the results of the regression analyses and findings suggesting that the easy-to-recognize
personality trait of extraversion (e.g. Kenny et al., 1992) was not particularly highly
valued, it is plausible to suggest that people want their politicians to reach their own
“high standards” on valued traits. Such a conclusion might be applied to openness and
agreeableness in this study. As decision making is not confined to the political domain,
the current findings may also be interpreted in a broader context. It is possible that in
first encounters, during which a common problem has to be solved, people favor others they
rate as closer to their self-rated “high standard” on certain personality traits. In
contrast to other studies which have found that voters preferred politicians with similar
personality traits (Caprara et al., 2007) our study was based on appearance cues and first
impressions. This may more closely resemble the situation in which politicians find
themselves when they are newcomers to the political arena or when they are candidates for
a new party about which ideological information is scarce. Furthermore, research suggests
that even when more information is available voting decisions are often guided by
superficialities and nonverbal cues (e.g. Antonakis & Dalgas, 2009; Olivola & Todorov,
2010). Our experimental set-up has limitations, because we removed speech content and
party membership from the video clips. Therefore, caution in extrapolating the results to
real life situations is advised and additional work needed to underpin the findings.
However, in follow up studies other potentially influential variables can be easily added
to the experimental design and tested under controlled conditions. Manipulating the
experimental setting this way could bridge the gap between studies that examine the role
of nonverbal cues and those that examine the role of ideology in decision making and help
to disentangle the role of appearance from that played by other sources of information.
Inclusion of variables on party membership, for instance, might reveal whether there is
some kind of an “attraction leads to similarity” effect when people make their voting
decisions (e.g. Morry, 2007). It is conceivable that people who receive more background
information “adapt” their ratings of politicians to make them more or less similar to
themselves. In addition, future experiments should enable both randomization of the
presented stimuli and assignment of same sets of stimuli to different participants. This
would provide insights into inter-judge agreement and to what degree it varies for ratings
of different personality dimensions. In summary, our study supports previous findings
showing that first impressions and visual appearance cues affect public decision making
processes (see also Antonakis and Dalgas, 2009; Ballew & Todorov, 2007; Poutvaara et al.,
2009). However, we extended earlier research by investigating the relationship between
self-ratings, observer-ratings and voting probability with response surface analyses
(RSA). This statistical tool enabled us to uncover relationships among the investigated
variables that traditional methods of analyses would not have revealed. For instance, we
found similarity effects for agreeableness, emotional stability and openness, but closer
examination of the RSA plots showed that these effects had different appearances. RSA
might thus help to refine hypotheses about similarity effects for personality traits by
providing a more detailed picture of relationships than other analytical tools. All in
all, our results suggested that people want a candidate to possess personality traits they
believe themselves to possess and which therefore have a very high value for them.


<h>REFERENCES</h>
----------

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<ART>What are the benefits of memory distortion?
===========================================

Authors: Jordi Fernández
DOI: 10.1016/j.concog.2014.09.019
Year: 2015  |  Pages: 536-547
ASJC codes: 3204, 3205
Keywords: Fabricated memory, Memory, Observer memory

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The purpose of this paper is to determine whether memories can have any benefit for their
subjects while being distorted.1 There are a number of things that one may have in mind by
‘benefit’ while referring to memory. For that reason, the formulation of the issue that
will occupy us here admits several possible readings. It will therefore make for clarity
if we begin our discussion by specifying, in Section 1, the types of benefits with which
we will be concerned in this discussion. One may also have different things in mind by
‘distortion,’ depending on one’s views about the function of memory. Thus, in order to
formulate the topic of our discussion precisely, I will distinguish, in Section 2, two
pictures of what memory is supposed to do, and two associated notions of distortion. Next,
I will put forward two types of memories that, I will argue, can qualify as cases of
beneficial distortion under very specific circumstances. In Section 3, I will discuss the
case of so-called ‘observer memories’ and, in Section 4, I will discuss the case of so-
called ‘fabricated memories.’ My contention will be that, in both cases, some of those
memories can, on the one hand, be advantageous for the subject to have while, on the other
hand, her faculty of memory has failed to perform its proper function by producing them.
The significance of this claim for the two pictures of what memory is supposed to do will
be explored in Section 5.

<h>EPISTEMIC BENEFITS AND ADAPTIVE BENEFITS</h>
----------------------------------------

There are at least two ways in which having a memory can be beneficial for a subject. One
of them is epistemic. Having a memory may provide the subject with knowledge of, or at
least justification for a belief about, the past. The memory does this by supplying the
subject with evidence, or grounds, for a certain belief; a belief in the content of the
memory or, more precisely, in part of that content.2 Thus, the memory allows the subject
to be in ‘cognitive contact’ with an event in her past: It puts the subject in a position
to think about, and refer to, that event. When the evidence provided by the memory is good
evidence, it is beneficial for the subject to be in that position. For the belief that the
subject can form on the basis of her memory will, in that case, be justified. Why is that
good for the subject? Beliefs are the sort of mental state which can be true or false.
They are in some sense normatively governed by, or aimed at, truth. From the point of view
of achieving truth, it is good for the subject to have justified beliefs rather than
unjustified beliefs because the former, unlike the latter, tend to be true. Furthermore,
when justified beliefs are true, they are such that they could not have easily been false.
This is because, when justified beliefs are true, they are not accidentally true, or true
by luck. This feature of justified beliefs confers a certain stability upon them: Whereas
merely true beliefs are fleeting in that they are easy to undermine, justified beliefs are
more likely to remain fast in response to conflicting information.3 Notice that, in order
for the subject to enjoy this type of benefit from her memories, the subject’s faculty of
memory must be trustworthy in the following sense. It must deliver memories that are
likely to be accurate when they have been appropriately produced.4 Imagine that, for any
memory of a subject, the fact that the memory in question was properly generated makes no
difference as to whether the content of that memory is likely to be case or not. Suppose,
now, that the subject has a particular memory. It is hard to see why the subject would be
justified in believing the content of it. After all, on the scenario that we are
considering, any of the memories that the subject is having could easily be misinforming
her about her past. Thus, the belief that the subject would form by taking the content of
her memory at face value is not likely to achieve truth. Suppose, however, that it does.
Still, it does not seem that the belief in question would be justified. For if the fact
that the memory was properly generated makes no difference as to whether its content is
likely to be the case or not, then it seems that the belief in question could have easily
been false. It turned out to be true, but the fact that the memory on the basis of which
the belief was formed was properly generated did not contribute to that outcome. It seems,
therefore, that in order for the subject to be in a position to form justified beliefs on
the basis of her memories (and thus benefit from them epistemically), those memories must
have the property of being such that if they have been properly generated, then they are
likely to be accurate.5 Another way in which having a memory can be beneficial for the
subject is by being adaptive. Having a memory may allow the subject to form a belief about
the past which has a certain instrumental value for her. The belief may serve to represent
the past in the way in which the subject needs to represent it in order for her to achieve
one of her goals.6 Oftentimes, the relevant goal involves experiencing a certain type of
emotion. In this scenario, the memory plays the role of supplying the subject with a
representation of her past that is conducive to experiencing the emotion that is being
sought by the subject; typically a positive emotion. When the memory allows the subject to
represent her past in the way in which she is seeking to represent it from an emotional
point of view, it is beneficial for the subject to have that memory. (We could call this
type of adaptive benefit, an ‘affectively adaptive’ type of benefit.) Other times, the
relevant goal involves making sense of one’s own behaviour towards, and one’s own thoughts
about, some particular person or situation. In that scenario, the memory plays the role of
supplying the subject with a representation of her past which makes her current behaviour
towards some person or situation intelligible to herself, and it allows her to explain why
she has certain thoughts towards the relevant person or situation. When the memory allows
the subject to represent her past in the way in which she needs to represent it for
comprehending her own mental life and her own behaviour, it is beneficial for the subject
to have that memory as well. (We could call this type of adaptive benefit, an
‘explanatorily adaptive’ type of benefit.) More generally, from an adaptive point of view,
it is beneficial for the subject to have a memory if representing the past in the way in
which that memory presents it to the subject is an effective means of satisfying one of
the subject’s goals. Notice that, in order for the subject to enjoy an explanatorily
adaptive type of benefit from her memories, the subject’s faculty of memory must provide a
firm structure in the following sense. It must deliver memories that cohere well with the
rest of the subject’s mental states when those memories have been appropriately produced.
Why is that? Imagine that, for any memory of a subject, the fact that the memory in
question was properly generated by the subject’s faculty of memory makes no difference as
to whether the content of that memory squares with the things that the subject has learnt
about her past through testimony, and the things that the subject has inferred about her
past from other things she knows. Suppose, now, that the subject has a particular memory.
It is hard to see how the subject could create a representation of her past that made
sense of her current behaviour and mental life by believing the content of that memory.
For that memory is, on the scenario that we are considering, likely to be in tension with
the behaviour and set of mental states which the subject needs to make sense of. In order
for the subject to be in a position to form, on the basis of her memories, beliefs about
her past which make sense of her current mental life and her current behaviour (and thus
benefit from them in an explanatorily adaptive way), those memories must have the property
of being such that if they have been properly generated, then they are consistent, and
cohere well, with rest of the subject’s mental states. Likewise, in order for the subject
to enjoy an affectively adaptive benefit from her memories, the subject’s faculty of
memory must provide a firm structure in the same sense. Why is that? Imagine that the fact
that, for any memory of a subject, the fact that the memory was properly generated by the
subject’s faculty of memory makes no difference as to whether the content of that memory
squares with the contents of the rest of the subject’s mental states which concern the
seemingly remembered event. Suppose, now, that the subject has a particular memory. It is
hard to see how the subject could use that memory to create a representation of a past
event which was intended to produce in the subject certain emotions; those emotions which
she is seeking to experience towards the event. For the relevant emotions arguably depend
on the subject’s current thoughts, needs, expectations, intentions and wishes that involve
that event. And the memory which is available to the subject is, on the scenario that we
are considering, not likely to be consistent with the contents of those mental states.7 In
order for the subject to be in a position to form, on the basis of her memories,
representations of a past event which produce in her the emotions that she is seeking to
experience towards that event (and thus benefit from them in an affectively adaptive way),
those memories must have the property of being such that if they have been properly
generated, then they are consistent, and cohere well, with the rest of the subject’s
mental states.8 What is the relation between the two types of benefits? Adaptive benefits
have been introduced in terms of goal satisfaction. In normal circumstances, a subject has
goals of various types. Some of them are practical goals, such as the goal of being at a
certain place at a certain time. Others are theoretical goals, such as the goal of having
beliefs that are held for good reasons (as opposed to biases or prejudices). The question
of how epistemic and adaptive benefits are related concerns, on the one hand, the
distinction between these two types of goals and, on the other hand, the distinction
between justified belief and true belief. Let me explain. For the purposes of achieving a
practical goal, it is enough to have a true belief about the means that will maximise
one’s chances of achieving that goal. Suppose, for instance, that I have the goal of
attending a meeting in the city at a certain time, and I want to catch the bus to go to
the city. I seem to remember that the bus is supposed to come to the relevant stop at 10
am. On the basis of my memory, I form the belief that the bus will be at the stop at 10
am. As it happens, my memory about these matters is highly unreliable, so I am not
justified in having that belief. But it turns out that the bus does show up at 10 am. For
the purposes of getting to my meeting on time, it was not necessary for my belief to be
justified. It turned out to be true, which is all I needed to achieve my goal. Now,
justified beliefs are more likely to be true than unjustified beliefs. For that reason, if
a memory carries an epistemic benefit for me, then it is likely to carry an adaptive
benefit with regards to some practical goals of mine. But there is no guarantee of that,
since justified beliefs may not be true. Suppose, for example, that my memory is highly
reliable when it comes to public transport schedules, but the bus is late and it shows up
at 10.30 am. Then, my memory carried an epistemic benefit for me. It yielded the justified
belief that the bus would be at the stop at 10 am. But the belief turned out to be false,
which did not help me to achieve my goal of attending my meeting. With regards to that
practical goal, therefore, my memory did not carry an adaptive benefit for me. If,
however, we take into consideration theoretical goals as well as practical goals, then it
seems that any memory that carries an epistemic benefit for me will carry some adaptive
benefit. For a memory that carries an epistemic benefit for me allows me to form a
justified belief on the basis of it. And if my belief is justified, then it seems that I
am satisfying my theoretical goal of believing for good reasons. What about the converse?
Do memories which carry an adaptive benefit always provide an epistemic benefit for the
subject as well? It depends, once again, on the type of goal that the memory is helping
the subject to achieve. If the goal in question is the theoretical goal of believing for
good reasons, then it does seem that the memory will provide an epistemic benefit for the
subject. But if the memory is helping the subject to satisfy one of her practical goals,
then the memory does not need to do this by putting the subject in a position to form a
belief that is justified. As we have just seen, a memory may be untrustworthy (and, for
that reason, fail to provide an epistemic benefit for the subject), and yet it may help
the subject to achieve one of her practical goals (and, for that reason, provide an
adaptive benefit for her). As a matter of fact, the discussion in Sections 3 and 4 below
is meant to illustrate this possibility with some interesting cases of memory. To sum up,
memories can have an epistemic benefit for the subject, and they can also have an adaptive
benefit for the subject. Furthermore, those benefits may be related or not, depending on
the subject’s goals. However, in order for a memory to carry either of those two benefits,
the subject’s faculty of memory must be functioning properly when it delivers it.
Interestingly, ‘functioning properly’ seems to mean something different in each case. The
two types of benefits that we appreciate in memories reveal two conceptions of what memory
is supposed to do; two conceptions of the function of memory. These two conceptions are
often assumed to be opposed to each other and, for that reason, they give rise to
competing notions of what a distorted memory is. Let us consider the two pictures of
memory in order.

<h>PRESERVATIVE MEMORY AND RECONSTRUCTIVE MEMORY</h>
---------------------------------------------

There is a popular conception of memory within philosophy according to which the function
of memory is content preservation. Memory is supposed to register and store the content of
those (typically, perceptual) experiences that we had in the past by producing memories
which inherit their contents from those experiences. On this ‘storage’ conception of
memory, then, a subject’s faculty of memory functions properly when the contents of the
memories delivered by it match the contents of the subject’s past experiences on which
those memories originate.9 And, with this preservative notion of proper function, comes an
associated notion of distortion: On the storage conception of memory, a subject’s faculty
of memory has produced a distorted memory when the content of that memory does not match
the content of the subject’s past experience on which the memory originates. To the extent
that one appreciates the epistemic benefit of having properly generated memories, one will
find the storage conception of memory appealing. After all, if a subject’s faculty of
memory adequately carries out the preservative function that this conception of memory
attributes to it, then this will allow a memory produced by it to be epistemically
beneficial for the subject.10 Would something weaker than the preservation of the whole
content of the original experience be enough for the resulting memory to be epistemically
beneficial for the subject? Let us recall that the epistemic benefit that a memory may
have for a subject depends on the belief that the subject is forming on the basis of that
memory. And what is required for the memory to be beneficial relative to the belief that
the subject is forming is the reliability of, not the whole content of the memory, but
only the parts of it which are relevant for the content of the belief being formed.
Suppose, for example, that my faculty of memory is reliable with regards to which actions
I witnessed in the past but not with regards to which people were involved. Suppose,
furthermore, that I have a memory of my brother tickling my sister mercilessly while we
were kids. As it happens, it was me, and not my brother, who ticked my sister mercilessly.
Now, imagine that I form, on the basis of that memory, the belief that someone was ticked
mercilessly while I was a kid. In that case, my memory is epistemically beneficial with
regards to that belief, but the whole content of the experience on which that memory
originates has not needed to be preserved for it to carry that epistemic benefit. It was
enough that my faculty of memory was trustworthy with regards to certain aspects in the
contents of the memories that it delivers, namely, the actions being remembered.11 On the
other hand, there is a popular conception of memory within psychology wherein memory is
not a passive device for registering and reproducing contents. It is instead a faculty
akin to imagination in its creative capacity. The main tenet of this ‘narrative’
conception of memory is that, in memory, we are engaged in an inventive project wherein we
build representations of our past by integrating content that we have acquired through our
own experience with content from other sources, such as testimony, inference and
imagination. Elizabeth Loftus, for example, describes this picture as ‘a new paradigm of
memory, shifting our view from the video-recorder model, in which memories are interpreted
as the literal truth, to a reconstructionist model, in which memories are understood as
creative blendings of fact and fiction.’12 The reference to an element of fiction in the
integration process is telling. For memory, on this conception, is not meant to represent
the past as we experienced it to be the case. Instead, the function of memory is to
reconstruct the past in order to help us build a smooth and robust narrative of our lives.
On the narrative conception of memory, then, a subject’s faculty of memory functions
properly when the contents of the memories that it delivers have been reconstructed so as
to easily fit together with the contents of the subject’s beliefs about her past. And,
with this reconstructive notion of proper function, comes an associated notion of
distortion: On the narrative conception of memory, a subject’s faculty of memory has
produced a distorted memory, when the reconstructive process has not yielded a memory that
meshes well with the contents of the subject’s beliefs about herself and her past and, for
that reason, it does not fit into the subject’s narrative of her life. To the extent that
one appreciates the adaptive benefit of having properly generated memories, one will find
the narrative conception of memory appealing. After all, if a subject’s faculty of memory
adequately carries out the reconstructive function that this conception of memory
attributes to it, then this will allow the memories that the faculty produces to be
beneficial for the subject from an adaptive point of view.13 Having distinguished these
two conceptions of memory, two questions naturally arise. One question is which of the two
conceptions is right in describing what the function of memory is. We will address that
question in Section 5. A different (and, at this point, more pressing) question is which
of the two conceptions is right in describing what memory does; whether it is the function
of memory to carry out the relevant operation or not. The answer to this question seems to
be that, to some extent, both conceptions are right. Reconstruction is a matter of degree.
The more input from sources of information other than the experience on which the memory
originates, the more reconstructed will the content of that memory be. And there may be
extreme cases in which no part of the memory’s content has been inherited from the
experience on which the memory originates. (Perhaps some pathological cases of
confabulatory memory fall into this category.) But the fact of the matter is that most of
our memories contain some pieces of information that they have inherited from the contents
of the experiences on which they originate. Conversely, preservation is also a matter of
degree. The more information is inherited from the content of the original experience, the
more preservative will the content of the resulting memory be. And there may be extreme
cases in which the whole content of the memory has been inherited from the experience on
which the memory originates. (Perhaps cases of so-called ‘eidetic’ memory fall into this
category.) But the fact of the matter is that most of our memories contain some pieces of
information that they have not inherited from the contents of the experiences on which
they originate. It seems, then, that our memories preserve, to some degree, the
information that we acquired in past experience and, to some degree, they reconstruct it.
Which explains the attraction and popularity of both conceptions of memory. Pulling apart
the preservative function of memory from its reconstructive function helps us to
appreciate that the original issue of whether memories can have any benefit for the
subject while being distorted actually divides into two issues: The first one is whether
it is possible for a subject’s faculty of memory not to carry out its reconstructive
function while it generates a memory, and yet for that memory to have an epistemic benefit
for the subject. The second one is whether it is possible for a subject’s faculty of
memory not to carry out its preservative function while it generates a memory, and yet for
that memory to have an adaptive benefit for the subject. In what follows, I will
concentrate on addressing the latter issue. I will argue that memories which have been
unreliably produced can nonetheless have an adaptive benefit for the subject based on two
cases of memory distortion; so-called ‘observer memories’ and ‘fabricated memories.’ Let
us now turn to these two interesting types of memories.

<h>OBSERVER MEMORIES OF TRAUMA</h>
---------------------------

A memory may present a past event to its subject from two types of visual perspectives.
One of them is the type of perspective from which the subject would have experienced the
event if the subject had witnessed it (or had went through it) in the past. By having a
memory that presents a past event from a perspective of this type, the subject visualises
the event, but she does not visualise herself as part of it. Let us call memories that
present events from a perspective of this type, ‘first-person’ or ‘field’ memories. A
memory may also present a past event from the type of perspective that a different
observer would have had to occupy in the past in order to witness the remembered event
with the subject as a participant of it. By having a memory that presents the past event
from a perspective of this type, the subject visualises not only the event but she also
visualises herself, as it were, from the outside. Let us call memories that present events
from a perspective of this type, ‘third-person’ or ‘observer’ memories. In this section, I
wish to put forward the claim that observer memories can qualify as a case of beneficial
memory distortion. In order to argue that observer memories can be beneficial despite
being distorted one must, first of all, make the case that they are indeed distorted. From
a preservative point of view, it seems quite clear that they are. Suppose that, years ago,
I suffered an accident while driving, and I now remember the accident by having an
observer memory of it. In virtue of having this memory, I picture the event from the point
of view of a nearby pedestrian on the street, thus being able to visualise some details of
my own physical appearance while I was at the wheel. Suppose that, on the basis of my
memory, I form the belief that, at the time of the accident, I appeared to be unshaven and
my hair appeared to be dishevelled. These facts about my appearance are not facts that I
perceived at the time of the accident. (Let us stipulate that I was not looking at myself
in the mirror while driving.) Thus, the source of this information in the content of my
observer memory must be other than the perceptual experience on which my memory
originates. It must be testimony, the imagination or perhaps reasoning from some other
facts that I remember about myself. In either of those cases, it seems that my observer
memory will be distorted with regards to the content of my belief. For the relevant parts
of the content of my memory (my having looked unshaven at the time, for instance) do not
belong to the content of any of my perceptual experiences during the accident.14 Thus, it
seems that my faculty of memory has not carried out its preservative function adequately
while delivering that observer memory. But has it, nonetheless, produced a memory that is
somehow beneficial for me to have? Let me introduce some terminology that may be useful at
this point. By having a mental state of a certain type (such as a perception, a sensation
or a memory), a subject may experience some emotions or moods. We could call these the
‘affective properties’ of the mental state. Also, by having a mental state of a certain
type, the subject may have experiences that are qualitatively similar to the experiences
produced by the subject’s senses during episodes of perception. Let us call these the
‘sensory properties’ of the mental state.15 Let us also use ‘feeling’ as an umbrella term
that refers to both the affective and the sensory properties of a mental state.
Furthermore, let us refer to a mental state that is rich in affective properties as
‘affectively rich,’ to a mental state that is rich in sensory properties as ‘sensorily
rich,’ and to a mental state that is rich in both as ‘phenomenally rich.’ Let us also call
mental states that are not sensorily, affectively or phenomenally rich, respectively,
‘sensorily dry,’ ‘affectively dry’ and ‘phenomenally dry.’ Now, there are reasons to think
that, whereas field memories tend to be phenomenally rich, observer memories tend to be
phenomenally dry. Consider, for example, the following findings in two classical studies
on the field/observer distinction (Nigro & Neisser, 1983): Subjects who describe the
contents of their field memories often mention their feelings at the time that they
witnessed, or went through, the relevant events whereas subjects who describe the contents
of their observer memories make significantly fewer references to their emotions and
sensory experiences at the time.16 And, conversely, subjects who are trying to describe
their feelings at the time that they witnessed, or went through, a remembered event tend
to remember that event from the field perspective whereas subjects who are only trying to
describe the circumstances surrounding the remembered event tend to remember it from the
observer perspective. The narrower point that field memories are affectively richer than
observer memories seems to be confirmed by more recent findings. It seems, for example,
that a subject who remembers an event from her past is more likely to have a field memory
of it when the remembered event has a strong emotional significance for her than when it
does not (Talarico, LaBar, & Rubin, 2004). Taken together, these findings suggest that
field memories, as opposed to observer memories, have very salient phenomenal properties
for the subject. If field memories are phenomenally rich whereas observer memories are
phenomenally dry, then one might wonder whether it is possible to change the phenomenology
of remembering a past event by switching from remembering it from a field perspective to
remembering it from an observer perspective. In particular, one might wonder whether one
might be able to diminish, or dampen, the phenomenal properties of the memory by
performing that switch. And, interestingly, there does seem to be some evidence suggesting
that this effect is possible (Berntsen & Rubin, 2006). Now, if it is possible to change,
and in fact diminish, the phenomenal properties of a memory of a past event by switching
from remembering the event from the field perspective to remembering it from the observer
perspective, then one can imagine a scenario in which it may be advantageous for a subject
to perform that switch. This is the scenario in which the event constituted a traumatic
experience for the subject in the past. It seems that traumatic events tend to be
remembered, by default, from the field perspective (Porter & Birt, 2001). Assuming that
field memories are phenomenally rich, a subject who remembers a traumatic event from the
field perspective will presumably be forced to relive some of her emotions and sensory
experiences during the event, which is likely to result in further trauma for her. It
would seem, therefore, that such a subject would benefit from switching to remembering the
traumatic event from the field perspective to remembering it from the observer
perspective. For if remembering the traumatic event from the observer perspective does
indeed dampen the phenomenal properties of remembering the event, then having an observer
memory of the traumatic event should alleviate the suffering associated with reliving it
in memory. It should allow the subject to achieve some ‘phenomenal distancing’ from the
traumatic event.17 Thus, it seems that observer memories of past events may carry an
adaptive type of benefit for the subject despite being distorted. Specifically, it seems
that they may be affectively adaptive for her. For representing a past event from an
observer point of view can, when that event has been traumatic for the subject, be an
effective way of satisfying one of the subject’s goals. The goal in question is, in this
case, to alleviate the suffering associated with reliving the event in memory. Admittedly,
things are not quite that simple. Let us keep in mind that whether or not a memory of a
subject is adaptively beneficial for her depends on which of the subject’s goals we are
focusing on. A memory may help the subject to achieve one of her goals while not helping
with, or perhaps even hindering her prospects of, achieving another. This may be the case
with observer memories. Even though a case can be made that observer memories of trauma
are adaptively beneficial with regards to the short-term goal of achieving some affective
relief, they may not help the subject to achieve the long-term goal of maintaining a
healthy self-concept. Picturing oneself from the outside, as it were, might be more
conducive to subjecting oneself to evaluation and, thus, it might increase the risk that
one finds certain aspects of how one is perceived not to be satisfactory enough.18 Thus,
there may be a cost involved in adopting the observer perspective while remembering
traumatic events. And yet, observer memories can be adaptively beneficial for the subject.
The important point to bear in mind in order to accommodate both of these facts at the
same time is that a subject does not draw, from her memories, adaptive benefits per se.
Instead, the adaptive benefit of a subject’s memories must be relativised to each of the
subject’s goals.

<h>FABRICATED MEMORIES OF ABUSE</h>
----------------------------

Over approximately the last twenty years, there has been a debate in cognitive science,
sociology, psychiatry and the law on whether or not accounts of long-forgotten episodes of
childhood trauma elicited by some memory recovery techniques, such as hypnosis and the use
of sodium amytal, should be taken at face value. After undergoing treatment as part of
certain approaches to psychotherapy, a subject may claim to remember a traumatic event
that happened to her as a child, even though she was not able to remember it before her
treatment. The issue in this debate has been whether such reports should be trusted as
expressions of accurate memories or not.19 Those who believe that these reports should be
trusted refer to the mental states being expressed through them as ‘recovered memories’
whereas those who believe that these reports should not be trusted as expressions of
accurate memories refer to the mental states being expressed through them as ‘false
memories.’ On the false memory camp, theorists such as Richard Ofshe have claimed that
memories cannot be completely lost and, later, be recovered (Ofshe & Watters, 1994). In
addition, false memory theorists have argued that inaccurate memories can easily be
induced under experimental conditions (Loftus & Ketcham, 1994). Theorists on the recovered
memory camp, by contrast, have disputed the contention that psychotherapists have the
power required to implant fabricated memories of whole events (Harvey & Herman, 1994).
Furthermore, they have appealed to independent evidence suggesting that the reactivation
of traumatic experiences of other types, such as trauma during war, can occur after
periods of time in which individuals experience relatively few symptoms (Schooler, 1994).
In this section, I will assume that some of the reports of recovered memories of long-
forgotten episodes of childhood trauma which arise during psychotherapy are not
expressions of accurate memories. I will assume that they are reports of a kind of memory
which, due to the psychotherapist’s intended or unintended acts of suggestion, the subject
mistakenly takes to be an accurate memory of some (typically traumatic) past event. I will
refer to these memories as ‘fabricated’ memories.20 In this section, I wish to put forward
the claim that fabricated memories of traumatic events could, in extremely unusual
circumstances, qualify as cases of beneficial memory distortion. In order to argue that
fabricated memories of traumatic events can be beneficial despite being distorted one
must, first of all, make the case that they are indeed distorted. From a preservative
point of view, it should be uncontroversial that they are. Suppose that I have a memory of
my childhood in which I represent an uncle who was visiting at the time as having molested
me by touching me in a sexual way. It turns out, however, that the uncle in question never
molested me. Thus, the source of that piece of information in the content of my memory
must be other than my past perceptual experiences of him. Let us stipulate that this
memory has arisen during psychotherapy and it is, as a matter of fact, a memory fabricated
by me as a result of my therapist’s use of some techniques of suggestion. In that case, it
seems that my fabricated memory is certainly distorted. For it fails to present my uncle
to me in any way in which I apparently perceived him to be in the past. Thus, it seems
that my faculty of memory has not carried out its preservative function adequately while
delivering the memory that I am having. But has it, nonetheless, produced a memory that it
could be beneficial for me to have? It is hard to imagine how any of the actual cases of
fabricated memories of traumatic events and, especially, fabricated memories of abuse
could possibly be beneficial for the subject. In actual cases of fabricated memories of
abuse, the subjects involved are misled into thinking that they have been abused with
terrible consequences. Not only can the subjects themselves be traumatized by those
memories, but also their families can be torn apart and reputations can be destroyed by
subsequent accusations of abuse. In actual fact, lives are often ruined by fabricated
memories of abuse. Nevertheless, one can conceive some highly unlikely sets of
circumstances in which, arguably, having a fabricated memory of a past episode of abuse
could carry an adaptive benefit for the subject. My contention is that it is in fact
possible to imagine two such sets of circumstances; a set of circumstances in which it is
affectively adaptive for the subject to have such a memory, and a set of circumstances in
which it is explanatorily adaptive for her. Let us consider the two scenarios in order.
Let us imagine that, early in my childhood, I once witnessed my uncle giving a terrible
beating to my mother; his sister. In fact, let us imagine that it was so early in my
childhood that I am no longer able to recover that memory. Many years later, I invariably
feel the desire to hate my uncle whenever I need to interact with him. Every time that I
am in his presence, I realise that, quite simply, I want to hate the guy. This makes me
ashamed of myself since, not being able to remember anything about the violent incident
that I once witnessed, I cannot find anything particularly despicable about my uncle. And
I strongly disapprove of the type of person who, as I see it, I would become by hating
someone unwarrantedly. So I do not allow myself to experience hate towards my uncle. And
yet, I wish that I was able to hate him. I cannot deny it. I am fully aware of my desire
to hate him. And worse, I am fully aware that, in spite of the fact that all my efforts to
find some justifying reason for it have failed, my desire to hate my uncle remains. The
resilience of this desire is upsetting for me, so I find myself in a strange dilemma: On
the one hand, I have a desire whose satisfaction would have very negative evaluative
consequences for my own self-concept. On the other hand, I cannot get rid of it. I
experience it as an intrusive desire; a desire that is beyond my rational control. One can
picture how the whole situation would be deeply disturbing for me. Consider, now, the
fabricated memory wherein I represent my uncle as molesting me while I was a child.
Fabricating this memory would provide me with a reason which, in my view, entitles me to
hate my uncle. And this, in turn, would allow me to experience hate towards him without
any harm to my own self-concept. Thus, it seems that, in this scenario, my fabricated
memory of abuse is beneficial despite being distorted. I benefit from having it in the
sense that representing a past episode of abuse that never happened turns out to be an
effective way of satisfying one of my goals. The goal in question is, in this case, to
manage to occupy, consistently with my own set of values, an emotional state that I feel
the need to experience. To that extent, my fabricated memory of abuse has an affectively
adaptive benefit for me. We may also imagine a set of circumstances in which my fabricated
memory of abuse is explanatorily beneficial for me to have. In order to describe it, one
only needs to tweak some of the details in the conceivable scenario sketched above. Let us
suppose that I did witness my uncle giving a terrible beating to my mother, and that I am
no longer able to remember that event. Let us imagine, however, that I do not currently
experience the desire to hate him. But I do find that I am inclined to behave negatively
towards my uncle whenever I need to interact with him. I avoid giving him a hug or shaking
his hand, I often find a reason to leave the room during a family reunion that involves
him, I accidentally break his Christmas gifts, and so on. Let us suppose that I have
insight into the fact that my behaviour reveals a dislike for him. However, not being able
to remember the beating that I once witnessed, I cannot find a reason for that behaviour.
I cannot explain why I am behaving in a hurtful way towards my uncle when I need to
interact with him, which is puzzling for me. It is also upsetting, in that my disposition
to behave in a hurtful way towards him remains despite all my failing efforts to find an
explanation for it. That is, the fact that I cannot make that behaviour intelligible to
myself has done nothing to change it. Thus, I feel alienated from some of my dispositions
to action. I experience them as dispositions that are beyond my rational control. It is
easy to picture how this conflict would be equally disturbing for me. Consider, now, the
fabricated memory wherein I represent my uncle as molesting me while I was a child.
Fabricating this memory would provide me with a reason which, in my view, explains why I
am inclined to behave negatively towards my uncle. And this, in turn, would allow me to
experience my relevant actions as actions that are rational: It would seem rational for me
to perform those actions given that I can find a reason for performing them. Thus, it
seems that, in this scenario, my fabricated memory of abuse is beneficial for me despite
being distorted. Once again, I benefit from having it in the sense that representing a
past episode of abuse that never happened turns out to be an effective way of satisfying
one of my goals. The goal in question is, in this case, to make sense of some behavioural
dispositions which I am unable to shake off. To that extent, my fabricated memory of abuse
has an explanatorily adaptive benefit for me. Once again, though, things are not quite
that simple, for reasons that will be reminiscent of our discussion of observer memories.
Recall that a memory may help its subject to achieve one of her goals while not helping
with, or perhaps even hindering her prospects of, achieving another. And, for that reason,
the memory may carry an adaptive benefit for the subject with regards to the former goal,
but not with regards to the latter one. This may be the case with fabricated memories.
Even though it can be argued that fabricated memories of abuse could be beneficial with
regards to the goal of allowing oneself to feel a certain emotion towards a person or
event, or the goal of making sense of one’s own mental states and behaviour towards that
person or event, they may not help the subject to achieve some of her other goals. As
noted above, thinking of oneself as having been abused is likely to result in trauma. It
is also likely to damage one’s social relations. (This is obvious when it comes to one’s
relations with the person wrongly accused of being the abuser.) From the point of view of
the goals of avoiding trauma and maintaining fulfilling social relations, therefore, it is
not adaptively beneficial for a subject to fabricate a memory of having been abused. And
yet, there are contexts in which it is possible for fabricated memories of abuse to be
adaptively beneficial for the subject. Once again, there is no inconsistency here,
provided that adaptive benefits are relativised to the subject’s goals.

<h>BENEFICIAL MEMORY DISTORTION AND THE FUNCTION OF MEMORY</h>
-------------------------------------------------------

Let us take stock. In Section 2, we have seen two pictures of what memory is supposed to
do. On one of those pictures, memory is supposed to preserve the information that we
acquired through perception in the past. On the other one, memory is supposed to build a
narrative of our personal past. In Section 1, we have seen the benefits of memory
performing each of those two functions appropriately while producing memories; an
epistemic benefit and an adaptive benefit for the subject. However, in Sections 3 and 4,
we have also seen that memory may fail to perform one of its functions adequately while
producing memories which are, in some sense, beneficial for the subject to have.
Specifically, we have seen that a subject’s faculty of memory can be unreliable while
delivering some memories which have some value for the subject, either from an affectively
adaptive point of view or from an explanatorily adaptive point of view. What does this
possibility mean for the two conceptions of memory sketched in Section 2? There are two
ways of looking at the relation between the storage conception of memory and the narrative
conception of memory. If one takes what we may call an ‘exclusive’ approach to them, then
one will believe that memory is either a faculty that is meant to perform a preservative
function within our cognitive economy, or it is a faculty that is meant to perform a
reconstructive function within it; but not both. On this approach, then, either the
function of memory is to preserve the information that we acquired in the past through
perception, or the function of memory is to build a narrative of our personal past. In the
former case, the narrative conception of memory is wrong whereas, in the latter case, it
is the storage conception of memory that is wrong. Either way, both of them cannot be
right. If one takes an exclusive approach towards the relation between the storage and
narrative conceptions of memory, and one endorses the narrative conception of memory, then
observer memories of trauma and fabricated memories of abuse do not qualify as cases of
beneficial distortion after all. Specifically, if the narrative conception of memory is
correct and the storage conception is wrong, then neither observer memories of trauma nor
fabricated memories of abuse are distorted. For if the considerations offered in Section 1
are correct, then those memories must have been, in a certain sense, appropriately
produced in order for them to be adaptively beneficial for the subject. The relevant sense
is that memory must have carried out its reconstructive function appropriately while
delivering them. Observer memories of trauma, for example, cannot help the subject to
achieve some phenomenal distancing from the remembered traumatic event if they do not
cohere well with the rest of things that the subject remembers about the event, and the
things that she knows about her own physical appearance in the past. Suppose, for example,
that my observer memory of my traffic accident does not represent me as having the
physical traits that I believe I had at the time of the accident. Suppose, furthermore,
that my observer memory does not represent my car as having the colour, shape and size
that I believe it had at the time of the accident. Then, I will not be able to identify
myself as the person who suffered the accident by having that observer memory. It is
difficult to see, then, how that memory could allow me to stop remembering the traffic
accident from a field perspective and start remembering it in a more phenomenally detached
way. After all, if I cannot identify myself as the person who suffered the accident, then
why would I recognise the mental state that I am occupying as a memory of something that
happened to me at all? Similarly, fabricated memories of abuse cannot help the subject to
achieve some emotional state that she is seeking to experience, or some understanding of
her own current behaviour and mental life, if they do not cohere well with the rest of
things that the subject remembers about the circumstances surrounding the alleged episode
of abuse, and the things that she knows about the participants in that episode. Suppose,
for example, that I have a fabricated memory of abuse involving my uncle, but it is not
consistent with some of the things I know about what was going on at the time. Suppose
that I know that my uncle was not in town when, according to my fabricated memory, I
suffered his sexual abuse. Suppose that I also know that the house where he is supposed to
have visited us did not look at all like my memory is presenting it to me. Let us say that
my memory does not even represent my uncle as I believe he looked like at the time. It
would be surprising if, given these inconsistencies, I still proceeded to trust my
fabricated memory as a memory of a genuine event in my past. In fact, I might even be able
to suspect that the memory that I am having has been fabricated by me. It is difficult to
see, then, how that memory could give me a justifying reason for allowing myself to
experience hate towards my uncle, or it could provide me with an explanatory reason of my
behaviour towards my uncle. Thus, if one takes an exclusive approach towards the relation
between the storage and narrative conceptions of memory, and one assumes that memory can
only have a reconstructive function, then one must conclude that memory has performed its
function properly while delivering those observer memories of trauma and fabricated
memories of abuse which are adaptively beneficial for the subject to have. Otherwise, they
could not be adaptive in the first place. Admittedly, this conclusion allows the narrative
theorist to capture the intuition that there is something right, and not distorted, about
the way in which those memories have been generated. And this is indeed an intuition worth
capturing. We do feel its pull. Unfortunately, though, there is a significant cost to
adopting this position. As we saw in Section 1, if the fact that memory is carrying out
its function appropriately when it delivers a memory makes no difference as to whether
that memory is likely to be correct, then one cannot be justified in forming beliefs about
one’s personal past on the basis of one’s memories. And, for that reason, one’s memories
cannot provide one with knowledge of one’s personal past. Now, if one believes that the
function of memory is exclusively reconstructive, then it seems that this is precisely the
conclusion that one should draw. For the fact that memory has carried out its
reconstructive function appropriately while producing a memory is no indicator of whether
that memory is likely to be accurate or not. (As a matter of fact, the types of memories
discussed in Sections 3 and 4 illustrate this point.) Thus, an exclusive approach to the
relation between the storage and narrative conceptions of memory, combined with an
endorsement of the latter, leads us to the conclusion that memory cannot provide us with
knowledge of our personal past. This seems too high a price to pay for preserving the view
that those memories which are adaptively beneficial for the subject are, in some intuitive
sense, not distorted. Things are not better if one adopts an exclusive approach towards
the relation between the storage and narrative conceptions of memory, but one endorses the
storage conception instead. In that case, one can capture the intuition that there is
something distorted about the way in which observer memories and fabricated memories are
generated since, as we saw in Sections 3 and 4, they are indeed distorted from a
preservative point of view. But there is a significant cost to adopting this position as
well. For the fact that some of those memories can be, under certain circumstances,
beneficial for the subject becomes, then, a mystery. Let me explain. The storage theorist
who takes an exclusive approach towards the two conceptions of memory is committed to the
view that the faculty of memory never carries out its function appropriately when it
produces observer memories and fabricated memories. However, if memory is not carrying out
its function adequately when it produces observer memories and fabricated memories, then
it is hard to understand why some of those memories can actually do some good for the
subject. After all, in Sections 3 and 4, we have seen that the reason why some of those
memories can be beneficial for the subject is that they serve a certain purpose for the
subject. They are aimed at providing something for the subject; something that the subject
is in need of. (The aim in question may involve either an emotion or an explanation.) But
if memory is never doing what it is supposed to do when it generates those memories, then
it is hard to see why, in some cases, the generation of those memories happens to serve a
purpose for the subject. What explains the fact that those memories are meant to achieve a
certain goal, a goal that it is in the subject’s interest to achieve, if they have been
accidentally generated? An alternative approach to the relation between the storage and
narrative conceptions of memory is what we may call an ‘inclusive’ approach to them.
According to it, memory is a faculty that is meant to perform a preservative function
within our cognitive economy, and it is also a faculty that is meant to perform a
reconstructive function within it. On this approach, then, the function of memory is to
preserve the information that we acquired in the past through perception, and the function
of memory is to build a smooth narrative of our personal past as well. What is the
relevance of the considerations offered in Sections 3 and 4 for this approach? If one
takes an inclusive approach towards the relation between the storage and narrative
conceptions of memory, then one can capture two important intuitions about beneficial
observer memories and beneficial fabricated memories which have been highlighted above;
the intuition that there is something wrong, and the intuition that there is something
right, about the way in which those memories have been generated. On the one hand, there
is something wrong in that memory has not performed its preservative function adequately
while delivering those memories. This is why we are inclined to think that there is a
sense in which they are distorted. Capturing this intuition by accepting that there is a
preservative function of memory which, in those cases, has not been carried out
appropriately allows us to hang on to the idea that, in order for our memories to yield
knowledge of our personal past, memory must carry out its function appropriately while
delivering them. For this is indeed true of the preservative function of memory. On the
other hand, there is something right about the way in which observer memories of trauma
and fabricated memories of abuse have been generated when those memories are beneficial
for the subject. For if the inclusive approach is correct, then memory has a
reconstructive function as well. And it seems that memory has performed that function
adequately while delivering those memories. After all, the considerations above suggest
that, unless memory maintains a certain coherence within the subject’s mental states when
it delivers observer memories of trauma and fabricated memories of abuse, those memories
cannot be adaptively beneficial for the subject. Assuming that there can be, as argued in
Sections 3 and 4, beneficial cases of such memories, it seems that we must accept that
memory has performed a certain function appropriately while delivering those memories,
namely, a reconstructive function. The outcome of these considerations, therefore, seems
to be that the correct approach to take towards the storage and narrative conceptions of
memory is the inclusive approach. The view that the function of memory is both to preserve
the information that we acquired in the past through perception, and to build a smooth
narrative of our personal past, is not new. It resonates, for example, with the so-called
‘Self-Memory System (SMS)’ conceptual framework (Conway, 2005; Conway & Pleydell-Pearce,
2000; Conway, Singer, & Tagini, 2004). One of the central claims within the SMS framework
is that memory must negotiate two demands; that of accurately recording ongoing activity
(‘correspondence’ in the SMS terminology) and that of maintaining a coherent record of the
self’s past activity (‘coherence’ in the SMS terminology). The idea is that a healthy
faculty of memory will meet those demands in an appropriately calibrated way. Now, that
central idea in SMS is similar to, but different from, the view that has been offered
here. For the reasons why, according to the view offered here, the preservative and
reconstructive functions of memory are important are different from the reasons why,
within the SMS framework, it is important for our memories to meet the demands of
correspondence and coherence. I have argued that building a smooth narrative of one’s past
is necessary for the purposes of experiencing a certain emotion towards some events in
one’s past, and for the purposes of making sense of one’s attitudes towards that event. By
contrast, the reason why, within the SMS framework, it is important for our memories to
meet the demand of coherence is that our memories must sustain an enduring sense of self.
Otherwise, our versions of our past selves will become detached from reality.21 The
difference is that, whereas it is necessary for one to achieve a certain emotion towards
an event in one’s past (or for one to make sense of one’s attitudes towards that event,
for that matter) that one has a stable sense of self, a stable sense of self does not seem
to be sufficient for one to achieve those emotional or explanatory goals. After all, we
would not want to claim that all subjects who have not emotionally processed, or have not
achieved some emotional closure with respect to, some traumatic event in their past no
longer have a consistent sense of self.22 I have also argued that possessing a faculty of
memory that reliably preserves the information that we acquired in the past through
perception is necessary for the memories that such a faculty produces to afford knowledge
of our personal past. By contrast, the reason why, within the SMS framework, it is
important for our memories to meet the demand of correspondence is that our memories must
keep track of where we are in the process of achieving a certain goal. Otherwise,
dysfunctional repetitions of action sequences will ensue, since we will not accurately
remember having already performed the necessary actions to achieve some of our goals. The
difference is that, whereas it is correct that if a memory provides a subject with
knowledge of her past, then it will allow her to keep track of the fact that she has just
performed an action that needs to be performed in order to achieve one of her goals, the
converse is not the case. All the subject needs in order to keep track of the fact that
she has just performed an action which she is required to perform in order to achieve one
of her goals is the true belief that she has just done so. And, as we saw in Section 1, a
true belief which allows us to achieve one of our goals does not need to be justified and,
for that reason, it does not need to amount to knowledge.23 What lesson can be drawn,
then, from our discussion in this section? If the inclusive approach to the functions of
memory is the correct approach to take, then it seems that we can draw an interesting
lesson from the fact that there is such a thing as beneficial memory distortion. Instances
of beneficial memory distortion teach us that memory has various functions, and they teach
us that the adequate performance of each of those functions can, conceivably, come apart
from each other. Memory distortion, in other words, reveals that memory is supposed to do
various things. At the very least, it is supposed to preserve the information that we
acquired through perception in the past, which is why instances of beneficial memory
distortion are instances of distortion. And it is supposed to provide us with a narrative
of our personal past, which is why instances of beneficial memory distortion are
beneficial. Furthermore, cases of beneficial memory distortion illustrate the fact that
memory can, in principle, do the latter without doing the former. Ultimately, then, what
cases of beneficial memory distortion teach us about the nature of memory is that memory
performing its reconstructive function does not necessarily depend on memory performing
its preservative function. There is no logical or conceptual link that ties our notions of
those two functions together. In that sense, our capacity to reconstruct our personal past
in memory is different from our capacity to acquire knowledge of it through memory.24


<h>REFERENCES</h>
----------

  [4] Dorthe Berntsen, David C. Rubin. Emotion and vantage point in autobiographical. doi:10.1080/02699930500371190
  [6] Martin A. Conway. Memory and the self. doi:10.1016/j.jml.2005.08.005
  [7] Martin A. Conway, Christopher W. Pleydell-Pearce. The construction of autobiographical memories in the self-memory system. doi:10.1037/0033-295X.107.2.261
  [8] Martin A. Conway, Jefferson A. Singer, Angela Tagini. The self and autobiographical memory: Correspondence and coherence. doi:10.1521/soco.22.5.491.50768
  [9] Arnaud D'Argembeau, Martial Van Der Linden. Phenomenal characteristics associated with projecting oneself back into the past and forward into the future: Influence of valence and temporal distance. doi:10.1016/j.concog.2004.07.007
  [10] Constance J. Dalenberg, Oxana G. Palesh. Scientific progress and methodological issues in the study of recovered and false memories of trauma. doi:10.1017/CBO9780511777042.026
  [11] Gail S. Goodman, Christin M. Ogle, Stephanie D. Block, Latonya S. Harris, Rakel P. Larson, Else Marie Augusti, Young Il Cho, Jonathan Beber, Susan Timmer, Anthony Urquiza. False memory for trauma-related Deese-Roediger-McDermott lists in adolescents and adults with histories of child sexual abuse. doi:10.1017/S0954579411000150
  [12] Mary R. Harvey, Judith Lewis Herman. Amnesia, partial amnesia, and delayed recall among adult survivors of childhood trauma. doi:10.1006/ccog.1994.1017
  [14] A. Koriat, M. Goldsmith, A. Pansky. Toward a psychology of memory accuracy.. doi:10.1146/annurev.psych.51.1.481
  [15] Willem Kuyken, Rachael Howell. Facets of autobiographical memory in adolescents with major depressive disorder and never-depressed controls. doi:10.1080/02699930500342639
  [20] Heather K. Mcisaac, Eric Eich. Vantage point in episodic memory. doi:10.3758/BF03196271
  [21] Patrick McNamara, Emily Benson, Brian McGeeney, Ariel Brown, Martin L. Albert. Modes of remembering in patients with chronic pain: Relation to current pain. doi:10.1097/01.nmd.0000149219.04841.f5
  [22] M. F. Mendez, I. A. Fras. The false memory syndrome: Experimental studies and comparison to confabulations. doi:10.1016/j.mehy.2010.11.033
  [23] Georgia Nigro, Ulric Neisser. Point of view in personal memories. doi:10.1016/0010-0285(83)90016-6
  [25] Stephen Porter, Angela R. Birt. Is Traumatic Memory Special? A Comparison of Traumatic Memory Characteristics with Memory for Other Emotional Life Experiences. doi:10.1002/acp.766
  [26] Duncan Pritchard, Alan Millar, Adrian Haddock. The Nature and Value of Knowledge: Three Investigations. doi:10.1093/acprof:oso/9780199586264.001.0001
  [28] Jonathan W. Schooler. Seeking the Core: The Issues and Evidence Surrounding Recovered Accounts of Sexual Trauma. doi:10.1006/ccog.1994.1026
  [30] John Sutton. Observer perspective and acentred memory: Some puzzles about point of view in personal memory. doi:10.1007/s11098-010-9498-z
  [31] Jennifer M. Talarico, Kevin S. Labar, David C. Rubin. Emotional intensity predicts autobiographical memory experience. doi:10.3758/BF03196886
<ART>What genome-wide association studies reveal about the association between intelligence and mental health
================================================================================

Authors: W. David Hill, Sarah E. Harris, Ian J. Deary
DOI: 10.1016/j.copsyc.2018.07.007
Year: 2019  |  Pages: 25-30
ASJC codes: 3200

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Intelligence, as measured by standardised tests of cognitive function, such as IQ-type tests, is predictive of psychiatric diagnosis and psychological wellbeing. Using genome-wide association study (GWAS) data, a measure of the shared genetic effect across traits, can be quantified; because this can be done across samples, the confounding effects of psychiatric diagnosis do not influence the magnitude of these relationships. It is now known that there are genetic effects that act across intelligence and psychiatric diagnoses, which provide a partial explanation for the phenotypic link between intelligence and mental health. Potential causal effects between intelligence and mental health have been identified, and the regions of the genome responsible for some of these cross trait associations have begun to be characterised.

--------------------------------------------------------------------------------


<h>INTELLIGENCE AND MENTAL HEALTH</h>
------------------------------

Intelligence, sometimes called general cognitive ability/function, the g factor, or simply
g, describes the finding that scores on cognitive tests that each seem to tax disparate
aspects of mental ability, positively correlate [1]. This overlap accounts for around 40%
of the variance found when administering a broad array of cognitive tests to a group with
a range of ability [2,3]. This finding has been known for over a century, and has been
replicated in hundreds of data sets [1–3]. Individual differences in intelligence are
predictive of mental illness, where a higher level of intelligence in childhood is
predictive of a lower level of self-reported psychological distress decades later [4].
This link between intelligence and mental illness also extends to severe psychiatric
conditions where individuals who have a level of intelligence one standard deviation below
the mean have, on average, a 60% greater chance of being hospitalized for schizophrenia, a
50% increase of being diagnosed with a mood disorder, and a 75% greater risk for having an
alcohol-related disorder, over a two-decade follow up period [5]. A higher risk for
several psychiatric illnesses has also been associated with a lower level of intelligence,
including major depressive disorder (MDD) [6,7], autistic spectrum disorder (ASD),
attention/deficit hyperactivity disorder (ADHD) [8], as well as bipolar disorder [9,10],
although a higher level of intelligence, particularly as measured by tests of crystallized
ability, may also be a risk factor for bipolar disorder [11].

<h>GENETIC ARCHITECTURE OF INTELLIGENCE AND MENTAL HEALTH</h>
------------------------------------------------------

Intelligence, like many other quantitative traits [12•,13], is heritable with twin and
family derived estimates of heritability being around 50–80% [14], with genetic factors
explaining an increasing proportion of variance as the age of the sample increases [15].
Molecular genetic data can also be used to derive the proportion of phenotypic variation
explained by all genome-wide single nucleotide polymorphisms (SNPs), using genomic-
relatedness-based restricted maximum-likelihood single component (GREML-SC) [16],
implemented in GCTA [17]. Heritability estimates derived using GREML-SC describe the
proportion of phenotypic variance that is explained by genetic variants in linkage-
disequilibrium (LD), that is to say correlated, with genotyped SNPs. As SNP arrays
typically measure common genetic variation, and two events can only be highly correlated
if they occur with a similar frequency, GREML-SC estimates of heritability represent a
subset of the total heritability in phenotypes where the genetic architecture includes
contributions from low frequency variants, and other types of genetic variation that are
poorly correlated with common SNPs. Heritability estimates derived using GREML-SC applied
to intelligence show that around 22.7% (SE = 2.1%) of phenotypic variance is explained by
additive genetic effects that are linked to common SNPs [18••]. Psychiatric disorders have
also been shown to be heritable using GREML-SC, where additive common genetic effects
explain 23% (SE = 0.8%) of schizophrenia [19], 21% (SE = 2.1%) of MDD [19], 28% (SE =
2.3%) of ADHD [19], 25% (SE = 1.2%) of bipolar disorder [19], 17% (SE = 2.5%) of ASD [19],
and 10.8% (SE = 2.0%) of neuroticism [18••], an individual’s propensity to experience
psychological distress. A method to capture genetic effects from across the frequency
spectrum of causal variants, called GREML-KIN [20], has been applied to intelligence,
neuroticism, and MDD. For intelligence 54.0% of phenotypic variation can explained using
genome-wide association (GWAS) data [18••]. For neuroticism, 30% of phenotypic variation
is captured, with 47.0% of MDD [21] being explained by additive genetic effects when
common and rare genetic effects are summed. GWAS for intelligence have recently attained
the statistical power required to reliably identify the loci that contribute to these
heritability estimates with more than 200 being identified so far [22••,23••,24] (15 novel
loci identified in Sniekers et al. 130 novel loci identified in Hill et al., and 58 novel
loci identified in Davies et al.). However, the total proportion of variance these loci
explain is far lower than the substantial heritability estimates. This `missing
heritability’ [25] is also seen when examining psychiatric variables and is indicative of
a highly polygenic architecture, where the cumulative effect of all genetic effects may be
substantial, but the contribution made by any individual variant is negligible. This
substantial heritability, combined with the relative sparsity of loci identified at
current sample sizes, is compelling evidence that by increasing sample size, and with it
the ability to reliably estimate small effects, will result in an increase in the number
of loci identified for both intelligence and psychiatric variables. Figure 1a shows the
Manhattan plot from one of the first well powered GWAS on intelligence [22••].

<h>GENETIC LINKS BETWEEN INTELLIGENCE AND MENTAL HEALTH</h>
----------------------------------------------------

The polygenic signal that drives heritability estimates can also be used to derive genetic
correlations to describe the average genetic effect that is attributable to causal
variants in LD with common SNPs, and shared across two traits. Using a technique called
linkage disequilibrium score (LDSC) regression [26,27••] genetic correlations between two
GWAS data sets can be derived. Whilst LDSC regression is less precise than GREML, as
indicated by the higher SE even when sample sizes are similar, as well as in instances
where there is genetic heterogeneity between the reference panel used to derive LD scores
and the sample used to derive the genetic correlations [28], LDSC regression has the
advantage that the GWAS data can come from separate samples where individual level data is
unavailable. Although an overlap in controls is not uncommon, by performing genetic
correlations across data sets neither the symptoms of psychiatric diagnosis,
hospitalisation, or drug regimens, can confound the measure of the genetic relationship
between intelligence and psychiatric illness. When applied to GWAS on intelligence and
psychiatric disorders, both positive and negative genetic correlations are found. Anorexia
nervosa, for example, shows a small but statistically significant positive genetic
correlation with intelligence (rg = 0.06, SE = 0.03, P = 0.02), as does ASD (rg = 0.21, SE
= 0.04, P = 2.46 × 10−8) [22••]. Negative genetic correlations however, are found between
intelligence and schizophrenia (rg = −0.14, SE = 0.03, P = 1.49 × 10−9), ADHD (rg = −0.46,
SE = 0.03, P = 2.41 × 10−54), neuroticism (rg = −0.29, SE = 0.07, P = 7.01 × 10−6) [22••],
and more recently with MDD (rg = −0.30, SE = 0.04, P = 1.28 × 10−13) [23••]. Together this
indicates that the genetic variants associated with high levels of intelligence have both
protective and facilitative effects on the genetic liability of mental illness, with the
genetic variants associated with a decrease in neuroticism, MDD, and schizophrenia being,
on average, those linked to higher levels of intelligence, and genetic variants that
confer greater risk of ASD, and of anorexia nervosa also being linked to higher levels of
intelligence. Bipolar disorder, however, shows a genetic correlation of around zero with
intelligence [22••,29••]. Educational attainment (as measured by the number of years in
education or by whether an individual attained a University or college level degree) shows
a strong genetic correlation with intelligence (rg = 0.70, SE = 0.02, P = 1.28 × 10−285)
[22••] and has been used as a proxy phenotype for intelligence [30]. However, in contrast
with intelligence the genetic architecture of education shows a positive genetic
correlation with schizophrenia (rg = 0.10, SE = 0.02, P = 5.40 × 10−6) [22••] and with
bipolar disorder (rg = 0.28, SE = 0.04, P = 4.84 × 10−14) [22••]. This indicates that, on
average, the genetic variants associated with an increase in educational attainment are
also linked to an increase in the risk of both schizophrenia, and bipolar disorder,
despite that the genetic variants associated with an increase in intelligence are also
linked to a reduction in the genetic risk for schizophrenia and are not linked to bipolar
disorder. This difference between how the genetic aetiology of intelligence and education
overlap with schizophrenia and bipolar disorder, can serve as a diagnostic tool to gauge
whether a phenotype constructed to measure intelligence, is in fact a better measure of
educational attainment [31]. Figure 1b shows the genetic correlations between
intelligence, as well as education, with six psychiatric disorders and neuroticism.
Whereas the large genetic correlation between intelligence in childhood, and intelligence
in older age (rg = 0.71, SE = 0.10, P = 2.26 × 10−12) suggests that many of the same
variants are involved in intelligence across the lifespan, the overlap between
intelligence and psychiatric variables may be influenced by the age at which intelligence
was assessed [29••]. This may be due to the genetic contributions to intelligence, as
measured in childhood, being a product of genetic effects involved in the development of
intelligence, whereas intelligence in older age will also be a product of the genetic
effects involved in the maintenance of intelligence across the life course [29••].

<h>SHARED LOCI BETWEEN INTELLIGENCE AND MENTAL HEALTH</h>
--------------------------------------------------

Genetic correlations tell us about the average genetic effect that is shared across
traits. As such, they do not identify the variants involved in cross-trait associations,
nor do they imply that when such a variant is identified it will have a shared effect on
the two traits consistent with the direction of effect of the genetic correlation. One way
to identify loci with a shared effect is to examine SNPs that attain genome-wide
significance in intelligence, and in psychiatric disorders. However, this method is
dependent on the number of genome-wide significant SNPs. In contrast to examining if a SNP
is genome-wide significant in two traits, conjunctional false discovery rate [32] (cFDR)
can be used to determine if a SNP shows association with two traits simultaneously. cFDR
has been used to examine the genetic link between schizophrenia and intelligence by
identifying loci that harbour joint effects. A total of 21 loci were identified as acting
across schizophrenia and three measures of cognitive ability (two measures of
intelligence, and one measure of reaction time). The genes that were implicated using the
cFDR approach were expressed across the developing and adult brain consistent with the
strong genetic correlations between childhood intelligence and older age intelligence.
Again consistent with the genetic correlations between intelligence and schizophrenia, 18
of the 21 loci identified contained risk alleles that were facilitative of intelligence
and protective against schizophrenia. The remaining three loci harboured variants that
were associated with a higher level of intelligence and a greater risk of schizophrenia,
consistent with some reports finding that a number of those diagnosed with schizophrenia
have retained their level of intelligence [33].

<h>INTERPRETATION OF A SHARED GENETIC EFFECT</h>
-----------------------------------------

GWAS exploits the correlation between SNPs (whether genotyped or imputed) and unknown
causal genetic variants. By doing so, regions of the genome, defined by the correlation
between SNPs, are identified as being linked to potentially causal variants. The presence
of genetic correlations, loci associated across traits, and even the same SNP being
implicated in multiple traits, can therefore arise in a number of different conditions.
Firstly, biological pleiotropy may be in effect and can be the result of a single SNP,
that is genome-wide significant in two traits, tagging a single variant that is causal in
both of the studied phenotypes [34•]. Alternatively, biological pleiotropy can describe a
situation where a single SNP, again genome-wide significant in two GWAS, tags two causal
variants (each casual for a different phenotype) that are both in the same gene.
Biological pleiotropy can also describe a situation where two SNPs, both within the same
gene, each tag independent causal variants that are also located within the same gene.
Secondly, mediated pleiotropy can occur where one phenotype is a causal element in a
second phenotype. In such instances genetic variants identified for the causal trait will
also be associated with the second. For example, mediated pleiotropy is likely to explain
the genetic link between intelligence with education and other measures of socio-economic
status [22••,35]. Finally, spurious pleiotropy can occur where there is misclassification
of the phenotype, this can occur if the low mood observed by those with bipolar disorder
is misclassified as MDD or in cases where those with bipolar disorder are misdiagnosed as
having schizophrenia. In these instances, a genetic correlation will exist between these
traits that is due to contamination of samples, rather than genetic effects that act
across traits. Spurious pleiotropy can also occur in cases where a single variant is found
to be associated with two traits, but this variant is tagging two, independent causal
variants, each of which is found in a different gene. This can occur in regions of the
genome where there is strong linkage disequilibrium. As genetic correlations are based on
all SNPs within a data set, different forms of pleiotropy may be in effect. Whereas
genetic correlations and shared risk loci are informative as to the average genetic effect
across traits, as well as the regions of the genome where such effects are localised, they
are not informative as to causality. Mendelian Randomisation (MR) can be used to mimic a
randomised control trial using observational (GWAS) data under a number of assumptions
[36,37]. MR typically uses SNPs that have attained genome-wide significance for a trait,
such as intelligence, as proxy variables for the trait. Independent groups can then be
made by grouping participants according to genotype. Groups that are created in this way
will also be grouped according to the phenotype, in this case intelligence, that is linked
to the genotype. As genetic variants are assigned randomly to a child at conception, MR
can be seen as a randomised control trial where intelligence, is randomly assigned to a
participant at conception. Using MR, causal links have been suggested for the link between
intelligence and education [38••], and this relationship appears to be bidirectional with
education being a casual factor in intelligence differences. A bi-directional causal
relationship has also been seen for schizophrenia where higher levels of intelligence
appear to be causally linked to a risk of schizophrenia [38••]. Lower levels of
intelligence also appear to exert a causal risk on ADHD [38••], and consistent with the
direction of the genetic correlation, and a higher level of intelligence is a causal risk
for ASD [38••]. To conclude, intelligence and psychiatric illnesses are highly polygenic
traits where common and rare genetic effects appear to be explain a substantial proportion
of individual differences. It is the common genetic effects that are known to act on
across intelligence and psychiatric disorders and this genetic link between intelligence
and psychiatric condition is not confounded by the presence of psychiatric disease,
hospitalisation, or treatment regime. The direction of effect is that high intelligence is
protective against schizophrenia, MDD, ADHD, and neuroticism, but is a risk factor for
ASD, and anorexia nervosa. Loci of shared effect have been identified for intelligence and
schizophrenia implicating brain expressed genes that are expressed in developing and adult
brain.

<h>FUNDING</h>
-------

IJD and SHE are supported by the University of Edinburgh Centre for Cognitive Ageing and
Cognitive Epidemiology which is funded by the UK Medical Research Council and
Biotechnology and Biological Sciences Research Council (Grant No. MR/K026992/1). WDH is
supported by Age UK (Disconnected Mind Programme).

<h>REFERENCES AND RECOMMENDED READING</h>
----------------------------------

Papers of particular interest, published within the period of review, have been
highlighted as: • of special interest •• of outstanding interest


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<ART>What genome-wide association studies reveal about the association between intelligence and physical health, illness, and mortality
================================================================================

Authors: Ian J. Deary, Sarah E. Harris, W. David Hill
DOI: 10.1016/j.copsyc.2018.07.005
Year: 2019  |  Pages: 6-12
ASJC codes: 3200

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<h>ABSTRACT</h>
--------

The associations between higher intelligence test scores from early life and later good health, fewer illnesses, and longer life are recent discoveries. Researchers are mapping the extent of these associations and trying to understanding them. Part of the intelligence-health association has genetic origins. Recent advances in molecular genetic technology and statistical analyses have revealed that: intelligence and many health outcomes are highly polygenic; and that modest but widespread genetic correlations exist between intelligence and health, illness and mortality. Causal accounts of intelligence-health associations are still poorly understood. The contribution of education and socio-economic status — both of which are partly genetic in origin — to the intelligence-health associations are being explored.

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<h>INTELLIGENCE, AND HEALTH AND DEATH</h>
----------------------------------

Until recently, an article on DNA-variant commonalities between intelligence and health
would have been science fiction. Thirty years ago, we did not know that intelligence test
scores were a predictor of mortality. Fifteen years ago, there were no genome-wide
association studies. It was less than five years ago that the first molecular genetic
correlations were performed between intelligence and health outcomes. These former blanks
have been filled in; however, the fast progress and accumulation of findings in the field
of genetic cognitive epidemiology have raised more questions. Individual differences in
intelligence, as tested by psychometric tests, are quite stable from later childhood
through adulthood to older age [1,2]. The diverse cognitive test scores that are used to
test mental capabilities form a multi-level hierarchy [1–3]; about 40% or more of the
overall variance is captured by a general cognitive factor with which all tests are
correlated, and smaller amounts of variance are found in more specific cognitive domains
(reasoning, memory, speed, verbal, and so forth). Twin, family and adoption studies
indicated that there was moderate to high heritability of general cognitive ability in
adulthood (from about 50–70%), with a lower heritability in childhood [4]. It has long
been known that intelligence is a predictor of educational attainments and occupational
position and success [1]. Relatively recently, the ‘ultimate validity’ of intelligence
test scores was discovered, that is, that higher intelligence significantly predicts later
death. First, an Australian Vietnam Veterans study found that higher young-adult
intelligence predicted lower risk of accidental deaths up to early middle age [5]. Then, a
population-representative Scottish study found that intelligence test scores at age 11
years predicted deaths from all causes up to older age (the mid-70 s) [6]. The association
between intelligence test scores from early life and mortality from all causes has been
widely replicated [7–9]. Intelligence from childhood and adulthood is associated with most
of the major causes of death with the exception of non-smoking-related cancers [10••,11].
Broadly speaking, a one-standard-deviation advantage in intelligence in youth lowers the
risk of mortality by 20–25% or more up to older age; the effect sizes are hardly
attenuated at all by adjusting for childhood socio-economic status, though are partly
attenuated after adjusting for education and adult socio-economic status, which are
possible mediators of the association [6,7,8,9,10••,11]. In addition to mortality,
intelligence test scores are associated with lower risk of many morbidities, such as
cardiovascular disease, cerebrovascular disease, hypertension, cancers such as lung
cancer, stroke, and many others, as obtained by self-report and objective assessment
[12–14]. Higher intelligence in youth is associated at age 24 with fewer hospital
admissions, lower general medical practitioner costs, lower hospital costs, and less use
of medical services, and intelligence appeared to account for the associations between
education and such health outcomes [15,16]. Higher intelligence is related to a higher
likelihood of engaging in healthier behaviours, such as not smoking, quitting smoking, not
binge drinking, having a more normal body mass index and avoiding obesity, taking more
exercise, and eating a healthier diet [16–18]. The flood of intelligence versus
mortality/illness/health-behaviours findings was captured by the term ‘cognitive
epidemiology’ [19]. From early on until now, there have been speculations about the
possible causes of these associations [6,10••,14,20]. Briefly, there is acknowledgement
that the causes of the associations are probably multiple, such as there being a
constitutional (perhaps partly genetic) association between intelligence and health,
and/or that intelligence’s influence might act via more education, higher health literacy,
and more affluent social class. Here, we examine evidence for possible genetic links
between intelligence and health.

<h>GENETIC CONTRIBUTIONS TO HEALTH, AND TO INTELLIGENCE</h>
----------------------------------------------------

There are at least three reasons to conduct genetic studies of phenotypes. First one wants
to understand the genetic architecture of a phenotype, that is, what is the nature of the
genetic variants that contribute to variation in the phenotype. For example, a single
mutation might have a large effect, as is the case in Mendelian diseases. By contrast,
continuous traits might be more likely to be polygenic; that is, to have some of their
variance caused by small contributions from many genetic variants. Second, having
discovered the genetic architecture, one is interested in the specific genes in which
variants have causal effects, that is, one wants to understand the molecular genetic
mechanisms of variation. Third, knowing that there is some genetic contribution to a
phenotype, one can ask how good a predictor the genotypic information is; that is, how
well can one predict some variation in a phenotype from only genotypic information? Much
recent progress has been made along these lines for illnesses and for intelligence. Before
the mid-2000s, genetic studies were done by three main methods. First, pedigree-based
(twins, adoptees, and families) studies of relatives’ phenotypic associations were used to
estimate the heritability of phenotypes, and genetic correlations among them. Limitations
of pedigree methods include the fact that several assumptions must be made in doing the
modelling, and that one does not learn about the specific genes involved. Second,
candidate gene studies tested hypotheses concerning whether certain genetic variants were
associated with phenotypic differences. For example, the possession of the e4 allele of
the gene for Apolipoprotein E (APOE) is associated with an increased risk of developing
Alzheimer’s disease. Limitations of the candidate gene method include the fact that most
candidate gene findings are not replicated (APOE e4 possession is an exception to this),
and that it is difficult to choose a candidate genetic variant from the millions that are
known. Third, genetic linkage analysis was used to track genetic markers in families where
specific phenotypes were common, to identify regions of the genome that segregate with the
phenotype. The main limitations of this method are that large families are required and it
identifies relatively large regions of the genome, rather than specific genetic variants
or genes. This changed with the advent and rise of genome-wide association studies (GWASs)
[21] (See Box 1). Sample sizes for GWASs often began with a few thousand, but, as the
polygenic architecture of many traits became clear — , that is, the associations between
individual genetic variants and phenotypes typically had very small effect sizes — it was
necessary to form consortia so that the Ns of studies rose to the tens and then hundreds
of thousands. Some GWAS consortia are now approaching and passing one million
participants. The typical finding — there are exceptions — in health and cognitive GWASs
is that many genetic variants of small effect contribute to phenotypic variation. In 2017,
a survey of the first ten years of GWASs’ discoveries enumerated the SNPs that were
associated with, for example, Crohn’s disease, diabetes, blood lipid levels, heart
function, height, bone density, red blood cell traits, metabolic traits, blood platelets,
breast cancer, rheumatoid arthritis, blood metabolites, menarche, Alzheimer disease,
kidney function, lung function, and education [21]. Often, the numbers of genetic loci in
which significant SNP associations are found runs to dozens or even hundreds for a single
phenotype. In 2011 the first apparently-decently-sized GWAS of intelligence appeared (N
approximately 3500), and found no significant SNPs [22]. By the time the sample size was
about 100 times greater, the number of independent genomic regions that were associated
with intelligence was about or greater than 150 [23•,24•,25••]. Figure 1 shows results
from a recent GWAS of intelligence. Many of these SNPs are located in regions of the
genome that have previously been associated with physical and mental illnesses. Therefore,
we now know many actual DNA variants that have significant associations with intelligence
tests’ scores; there are probably thousands in total. Although it found no significant
SNPs, the 2011 paper [22] did make a difference; it was the first study to estimate the
heritability of intelligence from DNA data alone and in unrelated subjects. This used a
then-new method—called GREML, and run in the GCTA framework [26] — which examined people’s
overall genetic similarity — based on common SNPs — with their phenotypic similarity (See
Box 1). The common-SNP-based heritability of intelligence is estimated to be about 25%
[24•]. It is typical for this common-SNP-based heritability to be about half of that
estimated from twin studies [27•]. It is thought that this ‘missing heritability’ is
because there are types of genetic variants other than causal variants that are in linkage
disequilibrium with common SNPs that contribute to heritability. Some new techniques are
helping to find these and close the gap between twin-based and SNP-based heritability
[28].

<h>GENETICS AND THE INTELLIGENCE-HEALTH RELATIONSHIP</h>
-------------------------------------------------

Three things are clear. First, higher intelligence in early life is a significant
predictor of better health behaviours, fewer and later illnesses, and longer life. Second,
many of the relevant health and illness outcomes, as well as health behaviours, have many
SNPs associated with them, and have a detectable level of common-SNP-based heritability.
Third: the same goes, genetically, for intelligence. Relatively new methods — bivariate
extension of GREML run on GCTA [29], and LD regression [30,31] (see Box 1) — have allowed
estimates of the genetic correlations between phenotypes. That is, we can test the extent
to which the polygenic signature obtained by using the summary results from GWAS
contributes to any two phenotypes, including between intelligence and health. Polygenic
signatures for many diseases were soon shown to be associated with intelligence [32]. Twin
studies had suggested that part of the intelligence-mortality association might be genetic
in origin, though there was disagreement about how much genetics contributed [33,34].
However, more recent studies have used genomic data. The list of significant molecular
genetic correlations between intelligence and physical health variables is now long
[23•,24•,25••,32]. Table 1 gives some examples. With regard to mortality, longevity has
been used; parental age at death has also been used, as a proxy, because most relevant
studies have not carried on long enough for many participants to have died. There is a
positive correlation of 0.36 between intelligence and parental age at death. There are
inverse genetic correlations between intelligence and both heart disease and hypertension,
with effect sizes between −0.1 and −0.2. There is a small (<0.1) association with
cholesterol, with higher ‘good’ cholesterol going with higher intelligence and the reverse
for the ‘bad’ cholesterol. There is a moderate-sized inverse genetic association between
intelligence and Alzheimer’s disease. There is a positive genetic association, of 0.27,
with intracranial volume, which is an indication of maximal brain volume in the life
course. There are significant positive genetic correlations between intelligence and birth
weight, lung function, happiness, and short-sightedness. There are significant negative
genetic correlations between intelligence and body mass index, poor self-rated health,
lung cancer, osteoarthritis, insomnia, smoking, waist-hip ratio, and long-sightedness. It
must be stressed that these correlations are based on GWASs conducted on different
samples; that is the people on whom intelligence was measured were not the people on whom
the health-based phenotype was assessed. Associations are interesting, but they do not
explain why the correlations exist, or the direction of causation, which require further
study and more new GWAS-based methods.

UNDERSTANDING THE INTELLIGENCE VERSUS PHYSICAL HEALTH ASSOCIATION, INCLUDING THE PART PLAYED BY GENETICS
--------------------------------------------------------------------------------

As described above, genetic correlations have been identified between intelligence and
many diseases, and physical health traits; moreover, polygenic scores for diseases and
health traits predict intelligence. However, it is not clear if these findings are due to:
(1) genetic variants influencing health traits/diseases, and then those health
traits/diseases influencing intelligence; (2) genetic variants influencing intelligence,
and then intelligence influencing health traits/diseases; or (3) genetic variants
influencing general bodily system integrity [20] that influences both intelligence and
health traits/diseases. (1) and (2) may be due to mediated pleiotropy which can be tested
for using a relatively new technique called Mendelian Randomization (MR) (see Box 1).
Using a bi-directional two-sample MR approach we identified no causal association between
intelligence or educational attainment (a proxy measure of intelligence), and the physical
health traits of body mass index (BMI), systolic blood pressure, height, coronary artery
disease and type 2 diabetes [35], using data from the UK Biobank (N approximately 110,000)
and large GWAS consortia. However, a larger, more-recent study found MR-based evidence for
potentially causal genetic effects of intelligence on larger intracranial volume, lower
risk of Alzheimer’s disease, lower body mass index, and greater likelihood of quitting
smoking [25••]. A MR study investigating the effect of education on obesity in about 2000
Finns concluded that education could be a protective factor against obesity, as measured
using BMI [36]. Another study using education data from the SSGAC consortium and coronary
heart disease data from CARDIoGRAMplusC4D (total sample size = 543,733) found that higher
education was causally associated with reduced risk of coronary heart disease, lower
likelihood of smoking, lower BMI and a more favourable blood lipid profile [37].
Sensitivity tests indicated that the results were unlikely to be driven by biological
pleiotropy. A two-step MR study investigated the influence of vitamin B12 intake during
pregnancy on cord blood DNA methylation and whether there is a causal influence on
offspring’s cognition in the Avon Longitudinal Study of Parents and Children (ALSPAC)
[38]. A small causal effect of vitamin B12-responsive DNA methylation changes on
children’s cognition was identified. MR analysis has suggested that genetically-predicted
intelligence and education both had associations with Alzheimer’s disease [39]. Another
part of understanding the genetic contribution to intelligence-health correlations
concerns other predictors of health inequalities, and intelligence’s correlations with
them. Intelligence, we saw earlier, is related to education and socio-economic status
(SES), and those were known to be related to health inequalities before intelligence was
known to have health associations. Although education and SES are principally thought of
as social-environmental variables, both have been found to be partly heritable, by both
twin-based and molecular genetic studies, both have high genetic correlations with
intelligence, Mendelian Randomisation results show bidirectional genetic effects between
intelligence and education, and both have genetic correlations with health outcomes
[25••,40,41,42,43,44,45].

<h>CONCLUSION</h>
----------

Intelligence has predictive power for many health outcomes. Part of that association is
genetic. The genes involved, and the causal pathways of the associations are being
explored.

<h>FUNDING</h>
-------

IJD and SEH are supported by the University of Edinburgh Centre for Cognitive Ageing and
Cognitive Epidemiology which is funded by the UK Medical Research Council and
Biotechnology and Biological Sciences Research Council (Grant no. MR/K026992/1). WDH is
supported by Age UK (Disconnected Mind programme).

<h>REFERENCES AND RECOMMENDED READING</h>
----------------------------------

Papers of particular interest, published within the period of review, have been
highlighted as: • of special interest •• of outstanding interest


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<ART>Why children differ in motivation to learn: Insights from over 13,000 twins from 6 countries
================================================================================

Authors: Yulia Kovas, Gabrielle Garon-Carrier, Michel Boivin, Stephen A. Petrill, Robert Plomin, Sergey B. Malykh, Frank Spinath, Kou Murayama, Juko Ando, Olga Y. Bogdanova, Mara Brendgen, Ginette Dionne, Nadine Forget-Dubois, Eduard V. Galajinsky, Juliana Gottschling, Frédéric Guay, Jean Pascal Lemelin, Jessica A.R. Logan, Shinji Yamagata, Chizuru Shikishima, Birgit Spinath, Lee A. Thompson, Tatiana N. Tikhomirova, Maria G. Tosto, Richard Tremblay, Frank Vitaro
DOI: 10.1016/j.paid.2015.02.006
Year: 2015  |  Pages: 51-63
ASJC codes: 3200
Keywords: Cross-cultural study, Enjoyment, Individual differences, Self-perceived ability, Teacher/classroom effect, Twin studies

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Little is known about why people differ in their levels of academic motivation. This study explored the etiology of individual differences in enjoyment and self-perceived ability for several school subjects in nearly 13,000 twins aged 9-16 from 6 countries. The results showed a striking consistency across ages, school subjects, and cultures. Contrary to common belief, enjoyment of learning and children's perceptions of their competence were no less heritable than cognitive ability. Genetic factors explained approximately 40% of the variance and all of the observed twins' similarity in academic motivation. Shared environmental factors, such as home or classroom, did not contribute to the twin's similarity in academic motivation. Environmental influences stemmed entirely from individual specific experiences.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Academic motivation refers to a wide range of traits, such as individuals’ educationally
relevant beliefs, perceptions, values, interests, enjoyment, and attitudes (Ryan & Deci,
2000; Urdan & Midgley, 2003; Wigfield & Eccles, 2000) that are associated to school
achievement (Elliot & Dweck, 2005). The etiology of individual differences in these traits
remains poorly understood. In this paper, we focused on two important motivational
constructs: enjoyment of learning (e.g., interest, liking), usually referred to intrinsic
motivation; and self-perceived ability, also known as academic self-concept (e.g.,
children’s perception of how good they are at school subjects). Several recent studies
found self-perceived ability to be substantially heritable (Spinath, Spinath, & Plomin,
2008), even when controlling for general cognitive ability (Greven, Harlaar, Kovas,
Chamorro-Premuzic, & Plomin, 2009; Luo, Kovas, Haworth, & Plomin, 2011). In terms of
environmental contributions, up to 60% of the variance in enjoyment and self-perceived
ability is explained by non-shared experiences (Spinath et al., 2008). Despite the absence
of significant shared environmental effects shown by recent large twin studies, several
educational studies found a link between aspects of academic motivation and
family/classroom-wide factors, such as classroom climate, peer influence, and mothers’
motivational practices in child’s education (Church, Elliot, & Gable, 2001; Gottfried,
Fleming, & Gottfried, 1994; Marsh, Martin, & Cheng, 2008; Ryan, 2000). One possible
explanation for this inconsistency is that environmental influences may be correlated with
genetic effects (Plomin, DeFries, Knopik, & Neiderhiser, 2012). For example, parental
involvement in child’s education may have a causal effect on motivation or/and reflect
partly genetically driven parental levels of education, ability, and motivation. Some
observed classroom effects might also stem from intake selection (e.g., ability
streaming). Most research into the relevant home environmental influences examines only
one child per family, which makes it difficult to establish whether the environmental
effects operate in a family-wide or child-specific manner. It is possible that even
objectively shared experiences, such as availability of educational resources at home, act
as child-specific experiences through gene-environment correlation, a mechanism through
which children in the same home modify their shared environment into individual
experiences. The role of teachers in shaping children’s academic motivation has been
extensively studied (Chirkov & Ryan, 2001; Church et al., 2001; Reeve & Jang, 2006; Urdan
& Midgley, 2003). Research suggested that teachers can promote the development of
intrinsic motivation (e.g., enjoyment, liking) by encouraging students’ autonomy,
providing feedback and optimal challenges, and adopting a caring attitude towards students
(Chirkov & Ryan, 2001; Ryan & Deci, 2000). However, teacher effects cannot be easily
disentangled from other potential effects of classroom resources, number of children in
the class, and teacher unfacilitated classroom-peer interactions (Olson, Keenan, Byrne, &
Samuelsson, 2014). Such teacher/classroom effects vary across development, with
potentially stronger or persistent effects at the early stages of the formal education
when children are facing systematic instruction and academic feedback for the first time
(Church et al., 2001; Kovas, Haworth, Dale, & Plomin, 2007; Reeve & Jang, 2006; Urdan &
Midgley 2003). If teachers/classrooms have a strong average effect on children’s liking a
particular school subject, we should expect twins in different classes to be on average
less similar in their enjoyment of the subject than those in same classes. Findings on
academic achievement are mixed: several studies have found small teacher/classroom
influences (Byrne et al., 2010; Nye, Konstantopoulos, & Hedges, 2004), whereas other
studies did not find any (Kovas et al., 2007), with a recent review suggesting that
classroom performance differences should not be viewed as indicators of teacher quality
(Olson et al., 2014). It could be that teachers and classrooms have a non-shared, child-
specific influence, possibly interacting with children’s genetic and unique environmental
background - leading to unique perceptions and reactions in different children. The goal
of this study was to investigate the relative contribution of genetic and environmental
factors to individual differences in enjoyment and self-perceived ability as a function of
cultural and educational settings. Twins between 9 and 16 years of age from six different
countries were evaluated on their enjoyment of learning and the perception of their
competence in several academic disciplines. We also compared twin similarity in same
versus different classrooms to evaluate teacher/classroom effects. Finally, we tested
whether the first formal teacher/classroom affects later class-wide level of enjoyment and
self-perceived ability (Church et al., 2001; Kovas et al., 2007; Reeve & Jang, 2006; Urdan
& Midgley, 2003).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Data of nearly 13,000 identical twins (monozygotic, MZ) and non-identical (dizygotic, DZ)
same-sex twins came from six different ongoing twin studies conducted in United Kingdom
(Twins Early Development Study – TEDS; Haworth, Davis, & Plomin, 2012), Canada (Quebec
Newborn Twin Study – QNTS; Boivin et al., 2013), Japan (Keio Twin Project; Ando et al.,
2013), Germany (Twin study on Cognitive ability, Self-reported Motivation and School
performance – CoSMoS; Spinath & Wolf, 2006), United States (Western Reserve Reading
Project – WRRP; Petrill, Deater-Deckard, Thompson, DeThorne, & Schatschneider, 2006); and
Russia (Russian School Twin Registry – RSTR; Kovas et al., 2012). Detailed information on
each sample is presented in the Appendix A.1.

<hs>  Materials</hs>
  ~~~~~~~~~

Across all samples, children reported their level of enjoyment and self-perceived ability
of different school subjects by completing questionnaires. Self-reported evaluations of
enjoyment and self-perceived ability were collected from the UK twins at ages 9, 12 (Luo
et al., 2011; Spinath, Spinath, Harlaar, & Plomin, 2006) and 16 (OECD, 2000, 2003, 2006);
Canadian twins at ages 10 and 12 (Guay, Marsh, & Boivin, 2003); Japanese twins at ages 10,
11, 12, 13 and 16 (Pintrich & de Groot, 1990); German twins at ages 9, 11 and 13 (Spinath
et al., 2008); US twins at age 12 (Harlaar, Deater-Deckard, Thompson, DeThorne, & Petrill,
2011); and Russian twins at age 16 (OECD, 2000, 2003, 2006). Table 1 summarizes the
measures and the overall sample size for each twin study. The table indicates maximum
number of children in each sample. Although the measures used across the samples were not
identical, they were designed to tap into the same motivational constructs. Convergence of
results under these circumstances warrants greater confidence in their generalizability
and replicability beyond specific methodological features. Details of each measure are
presented in the Appendix A.2.

<hs>  Procedure</hs>
  ~~~~~~~~~

Analyses were conducted on variables corrected for age and sex within each sample. Where
data on opposite-sex DZ twins were available (UK, Canada, Japan, and Germany), we ran the
analyses twice, including and excluding opposite sex DZ twins - with very similar results.
The information on whether twins and their co-twins were taught in the same or different
classes was also available in the UK sample at ages 7 and 9. We tested whether being in
different classes for 8 or more months reduces similarity in the level of enjoyment and
perceived ability for the two twins by dividing the sample into same versus different
class at age 9. The proportions of twins in same vs. different classrooms were very
similar for the two zygosity groups: 60% of MZ twins vs. 59% of DZ twins were taught in
the same class. In addition, we split the sample at age 9 into the same teacher/class at
age 7 to test whether the first teacher or class had a long-lasting class-wide
contribution to academic motivation.

<hs>  Twin analyses</hs>
  ~~~~~~~~~~~~~

We examined the etiology of enjoyment and self-perceived ability for every subject at
every age and in each sample separately by comparing within-pair similarity for MZ and DZ
twins. Heritability (A) can be estimated as twice the difference between the MZ and DZ
intra-class correlations (ICCs). Shared environmental influences (C) are suggested if DZ
twins’ correlation is more than half of the MZ correlation and are computed by subtracting
the heritability from the MZ ICC. Shared environment refers to environmental influences
that both members of a twin pair experience and that increases the similarity between
them. Factors such as socio-economic status, home environment, and school are often
thought to contribute to similarities among family members. Non-shared environmental
influences (E) are estimated by subtracting MZ twin correlation from 100% (Plomin et al.,
2012). The non-shared environment refers to environmental factors that are experienced
differently by each twin of a pair and that increase their dissimilarity. Non-shared
environmental influences may include individual specific experiences, such as different
peers and classmates, differential treatment by their parents and teachers, and
differences in twins’ perceptions of such experiences (Kovas et al., 2007). Non-shared
environmental estimates also include measurement error.

<hs>  Classroom heterogeneity model</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The effects of classroom on enjoyment and self-perceived ability were investigated by
fitting “the classroom heterogeneity model” to the data available from the UK sample.
These model-fitting analyses tested whether the differences in estimates of the ACE
parameters for twin pairs studying in the same class and twin pairs studying in different
classes were statistically significant. The classroom heterogeneity model is similar to
the sex-limitation models used to test for quantitative sex differences (Kovas et al.,
2007). To test for the long-lasting (spill-over) effects of the first teacher/classroom
experiences on later academic motivation, we performed the same analyses splitting the
sample at age 9 into twins who were attending the same versus different classroom when
they were 7.

<h>RESULTS</h>
-------

A wide variation in academic motivation scores was observed within each sample. The data
for most measures were normally distributed. Prior to all analyses, where data did not
meet the criterion of normality, the necessary transformations were applied (e.g., Vander
Waerden, reflect and log). Repeated analyses using transformed and untransformed scores
yielded similar results.

<hs>  Phenotypic correlations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Pearson correlations between enjoyment and self-perceived ability were performed on one
twin randomly selected out of each pair, and conducted on scores adjusted for age.
Correlations were moderate to strong in all samples: r = .41–.79, averaged = .65 (see
Table B.1 in the Appendix).

<hs>  Effects of sex and zygosity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Analyses of variance (ANOVA) were performed within each sample in order to assess the
effects of sex and zygosity and their interaction on each variable. The results were
adjusted for exact age within each sample. Means, standard deviations and the results of
ANOVAs are presented in Appendix (see Tables B.2 and B.3). Overall, boys reported higher
perceived ability, with 6 out of 16 comparisons reaching significance (p < .05), and
higher enjoyment of mathematics and science in all samples, with 5 out of 16 comparisons
reaching significance (p < .05). The effect size of these differences was small, ranging
from less than 1–6% for self-perceived ability, and ranging from less than 1–9% for
enjoyment. On the contrary, girls reported higher perceived ability, with 3 out of 8
significant comparisons (p < .05), and with less than 2% of the variance explained by sex.
They also reported higher enjoyment of reading and language academic subjects, with 5 out
of 8 significant comparisons (p < .05). Between 1% and 5% of the variance in enjoyment was
explained by sex. Overall, MZ and DZ twins showed similar levels of enjoyment and self-
perceived ability within each sample. In the UK sample, we were also able to test for a
main effect of zygosity, class, and zygosity by class interaction on enjoyment and self-
perceived ability. In other words, we tested whether twins showed greater enjoyment and
higher self-perceived ability when they were taught in the same (as opposed to different)
classroom; and whether this effect was specific (or more prominent) to one of the zygosity
groups. We conducted a series of 2 by 2 ANOVAs, for each school subject, with zygosity (MZ
vs. DZ) and class (same vs. different) – as two factors. For enjoyment, we found no class
or zygosity effect and no interaction. In other words, average levels of enjoyment of the
subjects were similar for MZ and DZ twin groups, irrespective of whether they attended the
same or different classes. For self-perceived ability, we found no zygosity effect but a
significant effect of class on self-perceived ability for English and Maths: children in
the same classroom showed a slightly higher level of self-perceived ability. However, this
effect was negligible, explaining less than 1% of the variance. No significant
interactions were found. These results suggest that twins (both MZ and DZ) have slightly
higher self-perceived ability when taught in the same (rather than different) class.
However, in this study, this effect was too weak to justify any further interpretation.

<hs>  Heritability of enjoyment and self-perceived ability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

MZ and DZ ICCs are presented in Tables 2 and 3, separately for enjoyment and self-
perceived ability. Striking similarities were observed across the ages, school subjects
and samples for both enjoyment (average MZ ICC = .46; average DZ ICC = .16) and self-
perceived ability (average MZ ICC = .46; average DZ ICC = .19). Overall, the results
showed that individual differences in enjoyment and self-perceived ability are explained
to a similar extent by genetic and individual-specific (i.e., non-shared) environmental
factors. Genetic contributions ranged from 16% to 69% across the samples; non-shared
environmental contributions ranged from 31% to 75%. Some potentially meaningful cultural
specific and subject specific effects were observed. For example, modest shared
environmental influences were found for enjoyment and self-perceived ability in German-
language at age 9, and for self-perceived ability at age 13; modest but significant shared
environmental influences (10%) were found for self-perceived ability in science at age 9;
and moderate shared environment was found in the Japanese sample for self-perceived
ability in mathematics at age 11. Although these four exceptions, no significant shared
environmental influences on these constructs were found. Figure 1 presents the results
averaged across age, school subject, motivational construct, and country (see Fig. C.1 in
the Appendix for the results split by country).

<hs>  Classroom effect on enjoyment and self-perceived ability</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Children in different classes did not rate their enjoyment of the subjects or their self-
perceived ability less similar than those in same classes, with equal genetic (A), shared
(C) and non-shared environmental (E) estimates for the two groups. We also tested the
assumption that the effect of the first formal teacher may have a continuous or delayed
effect on later motivational levels by splitting the sample at 9 years of age by whether
the children were taught by the same or different teacher at age 7. The ACE parameters
could be equated when the UK sample was split by whether the twins attended the same
versus different classes at age 7. In other words, no class-wide effect on contemporaneous
or later levels of enjoyment and self-perceived ability was found (see Tables B.4–B.9 in
the Appendix).

<h>DISCUSSION</h>
----------

Overall, the pattern of results for enjoyment and self-perceived ability was highly
similar, which is not surprising as these constructs were moderately to strongly
correlated for each school subject in each sample. The results showed high consistency
across ages, school subjects and cultures in the etiology of individual differences in
enjoyment and self-perceived ability. This consistency is particularly striking given the
vast cross-cultural differences in schooling and the educational systems involved. The
familial similarity in levels of academic motivation was only moderate, even for
genetically identical children raised in the same home. With few exceptions, neither
enjoyment nor self-perceived ability were influenced by shared environment. In other
words, similarities in enjoyment and self-perceived ability in twins growing up in the
same family and attending the same schools were entirely explained by their genetic,
rather than their environmental relatedness. However, genetic effects on enjoyment and
self-perceived ability varied substantially across the samples. These differences in
heritability could reflect some cultural aspects that lead to differences in amount of
observed variation explained by genetic factors. The observed differences could also be
explained by differences in sample sizes and associated statistical power. Moreover,
attending different classrooms did not increase dissimilarity between twins in their
levels of enjoyment and self-perception of competence. Equal similarity between twins
attending same and different classrooms cannot be explained with equalising effect of the
shared home environment as no such effect was found in this study. These results suggest
that similarity in academic motivation for any unrelated individuals stems from their
chance genetic similarity, as well as similar individual-specific environmental
experiences, rather than similar family/class-wide experiences. Whatever the environmental
influences on the levels of enjoyment and self-perceived ability are, they seem to act in
a non-shared, individual-specific way, potentially interacting with genetic make-up,
experiences and perceptions. Multiple individual-specific life-events, such as birth
complications, missing school due to illness, and peer-relations, may contribute to
motivation. Effects of family members, teachers, classes, and schools may also be non-
shared: parents, siblings, and teachers may actually treat children in the same
family/class differently, responding to their individual characteristics (Babad, 1993;
Harris & Morgan, 1991; Spengler, Gottschling, & Spinath, 2012). On the other hand,
children may perceive their parents, teachers, classmates, and schools differently (Zhou,
Lam, & Chang, 2012) – depending on other non-shared environmental and genetic effects. In
addition, genetic effects may differ as a function of environment. For example, research
suggested that heritability of reading might be moderated by teacher quality or SES status
(Taylor, Roehrig, Hensler, Connor, & Schatschneider, 2010).

<h>CONCLUSIONS</h>
-----------

Considering the striking consistency of these results across different aspects of academic
motivation, different subjects, different ages, and different cultures, we believe that it
is time to move away from solely environmental explanations, such as “good” or “bad” home,
teacher, and school, for differences in enjoyment and self-perceived ability (Olson et
al., 2014). The results convincingly show that, contrary to common belief, enjoyment of
learning and children’s perceptions of their competence are no less heritable than
cognitive ability (Greven et al., 2009). Surprisingly, unlike cognitive ability, for which
shared environment makes a small to moderate contribution across the school years (Petrill
et al., 2004), no such contribution was found for these motivational constructs. It
remains unclear to what extent the genetic and non-shared environmental factors
contributing to variation in enjoyment and self-perceived ability also contribute to
variation in achievement and intelligence (Gottfried et al., 1994). Academic motivation is
not independent of achievement, as it develops partly through feedback on performance and
in turn may influence achievement (Guay et al., 2003). For example, some studies found
bidirectional effects between motivation and performance (Luo et al., 2011). This and
other genetically sensitive studies call for caution when developing interventions aimed
at raising academic motivation before more is known about specific mechanisms underlying
its variation (Olson et al., 2014). Current educational policies are based on average
effects and are designed to operate at the family-wide and class-wide levels. However, the
present research suggests that many true effects may be masked within any class or home,
and that individual-specific educational approaches are required.


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<ART>Young children's counterfactual thinking: Triggered by the negative emotions of others
================================================================================

Authors: Keito Nakamichi
DOI: 10.1016/j.jecp.2019.06.012
Year: 2019  |  Pages: 104659
ASJC codes: 3204, 3205
Keywords: Cognitive development, Counterfactual reasoning, Counterfactual thinking, Early childhood, Emotion, Preschooler

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Three experiments examined the influence of other people's negative emotions on young children's counterfactual thinking. Experiment 1 (N = 48) explored whether 4- to 6-year-olds could think counterfactually about both physical and emotional events using the discriminating counterfactual tasks that children could not respond correctly without thinking counterfactually. Experiment 1 showed that 4- to 6-year-olds could think of counterfactuals associated with emotional events. Experiment 2 (N = 97) and Experiment 3 (N = 48) examined whether a protagonist's emotional state (emotional expression condition) affected 4- to 6-year-olds' ability to think counterfactually about physical events. It was shown that emotional expression conditions enhanced young children's counterfactual thinking about physical events. These findings suggest that 5- and 6-year-olds can think counterfactually and that emotional components trigger such thinking.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Counterfactual thinking is a form of thinking that considers alternative possibilities for
an event or behavior in the past. Counterfactual thinking has an adaptive significance for
humans in that it allows us to learn from past negative experiences and to avoid negative
outcomes in the future (Byrne, 2005, 2016; Epstude & Roese, 2008). Moreover,
counterfactual thinking has an important role in children’s cognitive development.
Counterfactual thinking during early childhood is closely associated with the following
key abilities: understanding causal relations (German, 1999; Harris, German, & Mills,
1996), acquiring theory of mind (Guajardo & Turley-Ames, 2004; Rafetseder & Perner, 2018;
Riggs, Peterson, Robinson, & Mitchell, 1998), understanding regret and relief (e.g., Beck
& Crilly, 2009; Guttentag & Ferrell, 2004), and engaging in pretend play (Buchsbaum,
Bridgers, Weisberg, & Gopnik, 2012). Recent years have seen a growing interest in the
development of counterfactual thinking in the field of cognitive development (see Beck &
Riggs, 2014; Rafetseder & Perner, 2014). One of the main areas explored in the previous
studies is the question of when the capacity for counterfactual thinking is acquired.
Studies of the development of counterfactual thinking have shown mixed results. In their
pioneering work on the development of counterfactual thinking, Harris et al. (1996)
presented children with a scenario that involved a causal chain in the following form:
initial state -> causal event -> effect state (e.g., the floor is clean -> Susie walks
across the floor with muddy shoes -> the floor gets dirty). They then asked each child a
counterfactual question (e.g., “What would have happened if Susie had taken off her muddy
shoes?” ; correct answer: the floor would have remained clean). More than 70% of 3-year-
olds were able to get the right answer to this counterfactual question. Studies based on
this approach (Beck, Riggs, & Gorniak, 2010; German, 1999; German & Nichols, 2003;
Nakamichi, 2011; Riggs et al., 1998) have demonstrated that children are capable of
counterfactual thinking by around 5 or 6 years of age. By contrast, Rafetseder and
colleagues (Rafetseder, Cristi-Vargas, & Perner, 2010; Rafetseder, Schwitalla, & Perner,
2013; see Rafetseder & Perner, 2014, for a review) have argued that 5- and 6-year-olds
find it difficult to use counterfactual thinking and that the development of
counterfactual thinking is a long-term process. In one experiment, Rafetseder et al.
(2013, Experiment 2) asked both 5- to 15-year-old children and adults to perform
counterfactual tasks referred to as the discriminating tasks. Rafetseder et al. presented
each participant with a scenario involving a causal chain in the following form: initial
state -> first causal event -> interim effect state -> second causal event -> final effect
state (e.g., the floor is clean -> Susie walks across the floor with muddy shoes -> the
floor gets dirty -> Max walks across the floor with muddy shoes -> the floor gets dirty”).
They then asked each participant a counterfactual question (e.g., “What would happen if
Max took off his muddy shoes?” ; correct answer: the floor would still be dirty). This
discriminating task looks similar to the simplified task in Harris et al. (1996). Unlike
the latter task, however, the discriminating task has the structure that does not allow a
child to produce the correct answer without taking into account the premises of the
scenario (e.g., even if Max took his shoes off, Susie would still walk across the floor
with muddy shoes). The results showed that 5- and 6-year-olds and 7- to 10-year-olds
(percentages of correct answers = 18% and 53%, respectively) performed less well than 13-
to 15-year-olds and adults (percentages of correct answers = 88% and 95%, respectively).
Moreover, 5- and 6-year-olds performed lower than chance, and 7- to 10-year-olds performed
higher than chance. In contrast to studies (Beck et al., 2010; German, 1999; German &
Nichols, 2003; Nakamichi, 2011; Riggs et al., 1998) based on the approach used by Harris
et al. (1996), the results of Rafetseder et al. (2013) suggest that 5- and 6-year-olds
find it difficult to use counterfactual thinking and that children do not acquire an
adult-level mode of counterfactual thinking until around 12 years of age. Based on these
experimental results, Rafetseder and colleagues (Rafetseder et al., 2010, 2013; Rafetseder
and Perner, 2014) have argued that the tasks based on Harris et al. (1996) are a
simplified structure and that such tasks cannot adequately measure a child’s capacity for
counterfactual thinking. For example, in response to the question “If Susie was to take
off her muddy shoes, …?”, children might answer “the floor would be clean” based on a
generally conceivable premise (e.g., if you take off your shoes, the floor won’t get
dirty) even if children ignore the original scenario. Rafetseder and colleagues have
called this inference from the general premise basic conditional reasoning and suggested
the need to examine the development of counterfactual thinking using tasks that do not
allow children to produce a correct answer unless they think of a counterfactual
possibility based on the actual event rather than tasks that allow children to produce a
correct answer via basic conditional reasoning. By distinguishing between basic
conditional reasoning and counterfactual thinking in young children, Rafetseder et al.
(2010, 2013) have offered important evidence with respect to the development of
counterfactual thinking. However, the fact that 5- and 6-year-olds found it difficult to
complete the discriminating tasks in Rafetseder and colleagues’ studies does not
necessarily prove that the children lacked all capacity for counterfactual thinking.
Several studies have shown success on counterfactual tasks at age 6 years or younger when
the causal structure of the events is clear (Nyhout & Ganea, 2019; Nyhout, Henke, & Ganea,
2019) and the task demands on memory and attentional resources are reduced (McCormack, Ho,
Gribben, O’Conner, & Hoerl, 2018; Rafetseder & Perner, 2010). For example, Nyhout and
Ganea (2019) presented 3- to 5-year-olds with a “blicket detector” machine that had a
clear and novel structure for children and then asked counterfactual questions (e.g., “If
she did not put the block on the box, would the light still be on?”). As a result, 4- and
5-year-olds’ performances were above chance level, although 3-year-olds’ performances were
not. These studies suggest that young children display mature counterfactual thinking
under specified conditions. In addition, Rafetseder and Perner (2018) mentioned the
possibility that the performance of Rafetseder et al. (2013, Experiment 2) task was
affected by materials and procedure (e.g., footprints were differently colored or not, two
protagonists entered the scene at the same time or not). Furthermore, it is possible that
the tasks developed by Rafetseder and colleagues did not raise young children’s needs to
consider counterfactual worlds with better outcomes even among those who did have the
ability to think counterfactually. Counterfactual thinking about a specific event is
activated particularly by the event’s negative outcome valence (the general value the
result can have), which has an adaptive significance because it can preempt negative
outcomes that could occur in the future (Byrne, 2005, 2016; Epstude & Roese, 2008). For
example, in the course of reviewing previous studies, Byrne (2016) demonstrated that
adults tend to think of counterfactual alternatives more frequently for events that are
likely to lead to negative outcomes than for events that are likely to lead to positive or
neutral outcomes. This characteristic of adult counterfactual thinking is also seen in
young children (German, 1999) and school children (Guajardo, McNally, & Wright, 2016).
German (1999) told 5-year-olds about an event in which the protagonist’s decision could
produce either a positive outcome or a negative outcome (e.g., in a situation where the
protagonist could have chosen either a jacket or a cardigan, he or she wore the cardigan
and played outside -> the protagonist is able to play outside all day/the protagonist
catches a cold and needs to go home early). Participants were then asked to explain the
event outcomes. In this experiment, 5-year-olds produced more counterfactual statements
(e.g., the protagonist should have chosen the jacket) for events that could lead to
negative outcomes than for events that were likely to lead to positive outcomes. In this
way, counterfactual thinking can be invoked by the negative outcome valence of an event
even in young children. All of Rafetseder and colleagues’ counterfactual tasks dealt with
physical events that were associated with a relatively ambivalent outcome valence. For
example, the physical state of Max and Susie’s footprints on the floor in the above
scenario does not necessarily have a negative valence for children. This may be the reason
why young children found it difficult to perform Rafetseder and colleagues’ counterfactual
task. In association with these findings, Epstude and Roese (2008) proposed the functional
theory of adult counterfactual thinking. Their theory suggested that the recognition of a
problem activates counterfactual thinking and that the recognition process was influenced
by human emotion: “Negative affect may also influence the activation of counterfactual
thinking” (p. 171). Compared with neutral or positive emotions, negative emotion may
signal that there is a potential problem in the outcome of an event or behavior, thereby
encouraging the individual to seek an alternative option that could produce a better
outcome. In short, human negative emotion plays an essential role in triggering
counterfactual thinking by clearly conveying the outcome valence of an event. In line with
theoretical postulates of adult counterfactual thinking (Epstude & Roese, 2008), Guajardo,
Parker, and Turley-Ames (2009) and Nakamichi (2011) have demonstrated that young children
are better able to use counterfactual thinking when considering events that are related to
human emotion compared to physical events without human emotion (in particular negative
emotion). For example, Nakamichi (2011) presented 3- to 6-year-olds with a scenario about
events involving physical change (e.g., there is a glass cup on the desk -> the cup falls
from the desk -> the cup breaks) or human emotional change (e.g., Taro looks at the
flower, which makes him happy -> a dog steps on the flower -> Taro feels sad) and then
asked a counterfactual question about each of these events (e.g., “If the cup had not
fallen, what would it look like?”, “If the dog had not stepped on the flower, how would
Taro feel?”). Children’s performance in the emotional task (percentage of correct answers
= 76%) was better than their performance in the physical task (percentage of correct
answers = 55%) and beyond chance for all ages. Furthermore, Guajardo et al. (2009) told 3-
to 5-year-olds about events involving either physical or emotional change and asked, “How
could the outcome be changed?” —allowing them to freely produce counterfactual
possibilities in response to each event. Children produced more upward counterfactual
statements (i.e., resulting in better outcomes) for the emotional event than for the
physical event. Based on these studies (Guajardo et al., 2009; Nakamichi, 2011) following
the approach of Harris et al. (1996), the young children apparently were capable of
counterfactual thinking when an event was associated with humans’ negative emotion rather
than mere physical change, although this effect on young children’s counterfactual
thinking might not be stable; Beck et al. (2010) contrasted physical and emotional
contents in counterfactual tasks and did not find consistent differences in 3- and 4-year-
olds. These results suggest the possibility that a component of negative human emotion in
an event can clarify the event outcome valence and trigger the ability to think
counterfactually in young children. The events in the counterfactual tasks developed by
Rafetseder et al. (2013) involved physical change only; they had no emotional component
such as the protagonist’s emotional state. For this reason, Rafetseder et al. failed to
prove that young children genuinely cannot engage in counterfactual thinking. Guajardo et
al. (2009) and Nakamichi (2011) based their approaches on Harris et al. (1996);
consequently, it is not clear whether children’s better performance in counterfactual
tasks associated with an event involving emotional changes was triggered by human
emotional components or by basic conditional reasoning (Rafetseder et al., 2010, 2013;
Rafetseder & Perner, 2014). The current study explored the impact of negative emotional
components on young children’s counterfactual thinking using tasks that are difficult to
answer correctly without taking the actual events into account (i.e., discriminating
counterfactual tasks) rather than tasks that could be easily answered using basic
conditional reasoning. Three experiments were carried out in this study. Experiment 1
compared children’s performance in the physical event task that involved physical change
and no negative emotional component with their performance in the emotional event task
that involved the change of emotional state. Based on Guajardo et al. (2009) and Nakamichi
(2011), young children should perform better on the emotional event task than on the
physical event task even using discriminating counterfactual tasks. Moreover, Experiments
2 and 3 used the physical event task from Experiment 1 to discover whether focusing on a
protagonist’s negative response to an event outcome would encourage young children to
think counterfactually. In these three experiments, according to the results of Rafetseder
et al. (2010, 2013), it was predicted that young children would find it difficult to carry
out tasks associated with a physical event. However, if a human’s negative emotion did
trigger counterfactual thinking in young children, better performance could be expected in
tasks involving human emotion across all experiments.

        <hss>Participants</hss>

        The participants were 48 children aged 4 to 6 years (24 boys and 24 girls; Mage =
        63.56 months, SD = 7.47, range = 52–75) recruited from three public nursery
        schools in Shizuoka, Japan. All participants were Japanese native speakers from
        middle-income families. The children were divided into two age groups: a younger
        group with 24 children (12 boys and 12 girls; Mage = 57.01 months, SD = 3.38,
        range = 52–64) and an older group with 24 children (12 boys and 12 girls; Mage =
        70.13 months, SD = 3.57, range = 65–75), following the Japanese education system
        of classification.

        <hss>Materials</hss>

        Based on earlier studies (Guajardo et al., 2009; Nakamichi, 2011; Rafetseder et
        al., 2013), six scenarios were created: three involving a physical event (cup,
        footprint, and sandbox scenarios) and three involving an emotional event (garden,
        zoo, and birthday scenarios). Original Japanese scripts for the stories are
        provided in the Appendix. In each scenario, six pictures (approximately 14.5 ×
        14.5 cm) were used to present the content. Fig. 1 presents the cup and garden
        scenario pictures used to depict those emotional and physical events. The physical
        event scenarios did not refer to the emotional state of the protagonist,
        describing only a physical change. The emotional event scenarios described the
        protagonist’s emotional state, changing from a positive emotion to a negative
        emotion. For each scenario, the first picture displayed an introductory scene.
        This was followed by a series of pictures in which the causal structure took the
        following form: initial state of a physical object/emotion -> first causal event
        -> interim state of the physical object/emotion -> second causal event -> final
        state of the physical object/emotion. In addition, in each scenario three pictures
        depicted different answers to the counterfactual question (Fig. 2).

        <hss>Procedure</hss>

        All of the steps in this experiment were reviewed and approved by the affiliated
        university’s committee for ethical research involving human participants. The
        principals in the nursery schools informed the parents about the experiment and
        received consent from parents for their children to participate. Written consent
        was obtained from a principal of each nursery school, acting as a surrogate for
        the parents. Verbal assent was obtained from the children before they participated
        in the experiment. Each participant was interviewed individually in a quiet room.
        The interviews lasted for approximately 20 min. All of the participants were asked
        to perform tasks involving six scenarios: three physical event tasks and three
        emotional event tasks. In each age group, half of the participants were initially
        assigned three physical tasks, followed by three emotional tasks; the other half
        were assigned the same tasks in reverse order. The order of three tasks (both
        physical and emotional) was counterbalanced. After each scenario, participants
        were asked to answer the Now control question (“What was the state of
        object/emotion at the end of the scenario?”), the Before control question (“What
        was the state of object/emotion at the beginning of the scenario?”), and the
        counterfactual Test question (“If the second causal event had been different, how
        would the final state have changed?”). In each task, the scenario was described to
        participants by using picture story cards. For instance, participants heard the
        following scenarios: Physical event task, cup scenario: [introductory picture in
        Fig. 1] Here are Jiro and Satoko. They are playing with blocks on the desk. There
        is a glass cup on the desk. [ initial state picture] This is a glass cup on the
        desk. The glass cup has two handles. [ first causal event picture] As they play
        with the toys, Satoko’s block hits the cup. [ interim state picture] One of the
        cup handles breaks. [ second causal event picture] Right after that, Jiro’s hand
        hits the cup and it falls off the desk. [ final state picture] Both cup handles
        get broken. Emotional event task, garden scenario: [introductory picture in Fig.
        1] This is Keiko. Keiko is carrying a piece of candy while looking at a flower in
        the garden. [ initial state picture] Keiko loves candy and flowers, so she is very
        happy. [ first causal event picture] After a while, a dog comes along, steps on
        the flower, and squashes it. [ interim state picture] Keiko feels a bit sad. [
        second causal event picture] Right after that, Keiko tries to eat her candy but
        drops it. [ final state picture] Keiko feels very sad. After the story cards were
        placed out of children’s sight following the end of the story, participants were
        asked to answer two control questions. The Now question involved the final
        situation in the scenario, and the Before question involved the initial situation
        in the scenario. For example, in the cup scenario, the questions were “At the end
        of the scenario, did the cup have two handles?” (Now question) and “At the
        beginning of the scenario, did the cup have two handles?” (Before question). In
        the garden scenario, the two questions were “At the end of the scenario, did Keiko
        feel happy or very sad?” (Now question) and “At the beginning of the scenario, did
        Keiko feel happy or very sad?” (Before question). To avoid response bias, the
        order of presenting these questions was counterbalanced. Finally, participants
        were asked to select one of three possible answers to the counterfactual Test
        question: “If the second causal event had been different, what would the final
        state have been?” For instance, in the cup scenario, participants were asked to
        choose an answer to the question “If the cup had not fallen off the desk, what
        would the cup look like now?” The three choices were a picture of the cup with no
        handles (Fig. 2A: final state), a picture of the cup with two handles (Fig. 2B:
        initial state), and a picture of the cup with only one handle (Fig. 2C: correct
        answer). Likewise, in the garden scenario, participants were asked to select one
        of three possible answers to the question “If Keiko had not dropped her candy, how
        would she feel right now?” The three choices were a face looking very sad (Fig.
        2A': final state), a face looking happy (Fig. 2B': initial state), and a face
        looking slightly sad (Fig. 2C': correct answer). For each question, the
        experimenter presented the final state choice at the beginning, followed by the
        remaining two choices at random. Two control questions and a test question were
        prepared for each of the other scenarios, in accordance with storylines.

<hs>  Results</hs>
  ~~~~~~~

The preliminary analyses did not show differences in task performance by gender and task
order. So, the following analyses combined data for these factors.

        <hss>Understanding the contents of scenarios</hss>

        The percentage of correct answers was 95.5% overall for the control questions. In
        the physical event tasks, the percentages of correct answers were 94.7% for the
        Now questions, 93.2% for the Before questions, and 94.0% overall. In the emotional
        event tasks, the percentages of correct answers were 98.5% for the Now questions,
        95.5% for the Before questions, and 97.0% overall. Many participants demonstrated
        a good understanding of the scenario events. However, some participants gave only
        one wrong answer to the control questions, with 9 participants failing in physical
        event tasks and 6 participants failing in emotional event tasks. For this reason,
        they were not excluded from the sample. Instead, to reflect participants’
        different ways of understanding the scenarios, if a participant answered any of
        the control questions incorrectly, 0 points were assigned to the corresponding
        test question regardless of whether the participant gave the correct answer or
        not.

        <hss>Answers to the counterfactual questions</hss>

        Participants received 1 point if they answered the two control and counterfactual
        test questions correctly in each scenario. Afterward, the scores for all three
        scenarios in both physical and emotional event tasks were totaled to provide a
        counterfactual score (Max = 3 each). Table 1 shows the mean scores and the numbers
        and percentages of children receiving scores of 0, 1, 2, and 3 by age group and
        task. First, a generalized estimating equation (GEE) analysis was conducted. This
        GEE model included age group (younger or older) as a between-participants
        predictor, task (physical or emotional) as a within-participants variable, and the
        counterfactual score (out of 3) as the dependent variable. The results showed that
        the older group had only a marginally higher score compared with the younger
        group, B = 1.07, SE = 0.59, Wald χ2(1) = 3.28, p = .070, odds ratio = 2.90, 95%
        confidence interval (CI) [0.92, 9.20]. In addition, the main effect of the task
        was significant, with the emotional event task gaining a higher counterfactual
        score than the physical event task, B = 3.51, SE = 0.64, Wald χ2(1) = 29.68, p <
        .001, odds ratio = 33.57, 95% CI [9.48, 118.82]. The Age Group × Task interaction
        was not significant (p = .785). Second, a one-sample Wilcoxon signed-rank test
        using a counterfactual score was carried out by age group and task to analyze the
        difference between participants’ performances and chance level (chance = 1.00). In
        the physical event tasks, the younger group’s score was significantly lower than
        chance (Z = −2.84, p = .005, r = .58), whereas no significant difference was seen
        between the older group’s score and chance (Z = −0.94, p = .346, r = .19). In the
        emotional event tasks, the scores were significantly higher than chance for the
        younger group (Z = 3.84, p < .001, r = .78) and the older group (Z = 4.04, p <
        .001, r = .83). Moreover, the analyses using children’s actual response (taking no
        account of answer to control questions) showed similar results (physical event
        tasks: younger group, Z = −2.52, p = .012; older group, Z = −1.27, p = .206);
        emotional event tasks: younger group, Z = 4.67, p < .001; older group, Z = 3.84, p
        < .001).

<hs>  Discussion</hs>
  ~~~~~~~~~~

In Experiment 1, the discriminating counterfactual tasks that are difficult to answer
correctly without taking the actual events into account were used to assess the
counterfactual thinking of 4- to 6-year-olds. First, the older group (percentage of
correct answers = 51.3%) performed better than the younger group (percentage of correct
answers = 39.7%), meaning that the ability of counterfactual thinking improved from 3 to 6
years of age. Moreover, participants found it more difficult to perform physical event
tasks (percentage of correct answers = 21.5%) than to perform emotional event tasks
(percentage of correct answers = 69.5%). The performance of the younger group was below
chance, whereas the performance of the older group was similar to chance. Some studies
that have used simple tasks, solvable using basic conditional reasoning (e.g., German &
Nichols, 2003; Harris et al., 1996), have previously suggested that 3- and 4-year-olds are
capable of counterfactual thinking. However, the results of Experiment 1 suggest that
children under 5 years of age find it extremely difficult to think counterfactually about
physical events that do not involve an emotional component. The difficulty with performing
physical event tasks in our study was consistent with the findings of Rafetseder et al.
(2013) that used discriminating counterfactual tasks (percentage of correct answers in 5-
and 6-year-olds = 18%). Participants in this study performed better in emotional event
tasks than they did in physical event tasks, with all age groups performing above chance.
These results confirm the results of studies that have compared performance in physical
events with performance in emotional events (Guajardo et al., 2009; Nakamichi, 2011). In
other words, the current study showed that even when using an approach based on more
stringent standards (i.e., discriminating tasks), children under 5 years of age can think
counterfactually about emotional events but not about physical events without emotional
components. This result suggests that young children not only use basic conditional
reasoning but also think counterfactually about events with an emotional component.
However, the results of Experiment 1 do not prove that negative emotion triggers
counterfactual thinking in young children. It might simply be less demanding for young
children to think about changes in an emotional state than to think about changes in a
physical state. Consequently, a further experiment was needed to examine the effect of
negative emotion on young children’s counterfactual thinking. If negative emotion triggers
counterfactual thinking, young children should be capable of thinking counterfactually
about physical events by presenting them with the protagonist’s negative emotion. Thus, in
Experiment 2, we created the new condition (i.e., emotional expression condition) that was
designed to add negative emotional components to the physical events used in Experiment 1.

        <hss>Participants</hss>

        The participants were 97 children aged 4 to 6 years (46 boys and 51 girls; Mage =
        64.34 months, SD = 6.56, range = 53–76) recruited from three public nursery
        schools in Shizuoka. All of the participants spoke Japanese as their first
        language and were members of middle-income families. These children were divided
        into two groups: a younger group with 47 children (23 boys and 24 girls; Mage =
        58.47 months, SD = 3.23, range = 53–64) and an older group with 50 children (23
        boys and 27 girls; Mage = 69.86 months, SD = 3.21, range = 65–76), as with the
        classification of Experiment 1. None of the participants from Experiment 1
        participated in Experiment 2.

        <hss>Materials</hss>

        This experiment used the three physical event scenarios from Experiment 1 (the
        cup, footprint, and sandbox scenarios). The six pictures representing the content
        of the event and three pictures of possible answers to the counterfactual question
        were used in each scenario. In the emotional expression conditions, in addition to
        the six pictures mentioned above, “a picture of the initial emotional state of the
        protagonist” (positive emotion) and “a picture of the final emotional state of the
        protagonist” (negative emotion) were used in each scenario. Fig. 3 shows the
        pictures used for both the control and emotional expression conditions.

        <hss>Procedure</hss>

        All of the steps in this experiment were reviewed and approved by the affiliated
        university’s committee for ethical research involving human participants. As with
        Experiment 1, written consent was obtained from a principal of each nursery
        school, and verbal assent was obtained from the children. Participants were
        assigned to either the control condition or the emotional expression condition. In
        total, 24 children in the younger group (12 boys and 12 girls; Mage = 59.04
        months) and 25 children in the older group (11 boys and 14 girls; Mage = 70.32
        months) were assigned to the control condition, whereas 23 children in the younger
        group (11 boys and 12 girls; Mage = 57.87 months) and 25 children in the older
        group (12 boys and 13 girls; Mage = 69.40 months) were assigned to the emotional
        expression condition. No significant differences in months of age by condition or
        gender were seen in these age groups. Each participant was interviewed
        individually in a quiet room. The interview lasted for approximately 15 min. In
        both conditions, participants were asked to perform three counterfactual tasks.
        The order of presenting three tasks was counterbalanced among participants. In the
        control condition, the scenario for each task was described while the picture
        story cards were presented to participants. For example, the footprint scenario
        went as follows: [introductory picture in Fig. 3] This is Taro, the older brother,
        and Hanako, his younger sister. The two are playing outside and have mud on their
        shoes. [ initial state picture] This is the inside of Taro and Hanako’s house.
        Today, the floor is very clean. [ first causal event picture] A short while later,
        Taro walks on the floor with his shoes on. [ interim state picture] The floor has
        Taro’s footprints. [ second causal event picture] Right after that, Hanako walks
        on the floor with her shoes on. [ final state picture] Now the floor has both
        their footprints. After each scenario, participants were asked to answer the three
        questions (the Now question, the Before question, and the Test question). In the
        emotional expression condition, two scenes referring to the emotional state of the
        protagonist were added to each scenario in the control condition: between the
        introductory scene and the initial state scene and after the final state scene.
        For instance, in the footprint scenario, two scenes were inserted: a scene where
        “both Taro and Hanako have fun playing outside” (Fig. 3A) and a scene where
        “Hanako feels sad after seeing footprints on the floor” (Fig. 3B). Apart from
        these points, the storyline and task presentation processes were the same as in
        the control conditions.

<hs>  Results</hs>
  ~~~~~~~

Preliminary analyses showed no gender difference. So, the genders were mixed in the
following analyses.

        <hss>Understanding the contents of scenarios</hss>

        Overall, the percentage of correct answers to the control questions was 94.6%. In
        the control conditions, the percentages of correct answers were 98.0% to the Now
        questions, 97.3% to the Before questions, and 97.6% overall. In the emotional
        expression conditions, the percentages of correct answers were 97.9% to the Now
        questions, 97.2% to the Before questions, and 97.6% overall. Some children gave
        only one wrong answer (7 participants in the control condition and 7 participants
        in the emotional expression condition). Therefore, as in Experiment 1, they were
        not excluded from the sample.

        <hss>Answers to the counterfactual questions</hss>

        The counterfactual scores in each condition were calculated using the same scoring
        procedure as in Experiment 1. Table 2 shows the mean scores and the numbers and
        percentages of children receiving scores of 0, 1, 2, and 3 by age and condition.
        Because a preliminary analysis did not demonstrate any gender difference, the
        genders were mixed in the following analysis. First, an ordinal regression
        analysis was conducted to examine the effect of the two predictor variables, age
        group and condition, on the overall score out of 3. This analysis included age
        group (younger or older) and condition (control or emotional expression) as
        categorical predictors and the Age Group × Condition interaction. This model was
        significant, χ2(3) = 15.87, p = .001. The older group had a significantly higher
        score compared with the younger group, B = −1.56, SE = 0.55, Wald χ2(1) = 8.20, p
        = .004, odds ratio = 4.77, 95% CI [−2.63, −0.49]. In addition, the main effect of
        the condition was significant; participants in the emotional expression condition
        had a significantly higher score than those in the control condition, B = −1.14,
        SE = 0.52, Wald χ2(1) = 4.78, p = .029, odds ratio = 3.14, 95% CI [−2.17, −0.12].
        The Age Group × Condition interaction was not significant (p = .364). Second, a
        one-sample Wilcoxon signed-rank test using a counterfactual score was performed by
        age group and condition (chance = 1.00). In the control condition, the scores of
        both the younger group (Z = −1.53, p = .127, r = .31) and the older group (Z =
        0.87, p = .383, r = .17) were no different from chance. In the emotional
        expression condition, the score of the younger group was no different from chance
        (Z = −0.45, p = .655, r = .09), but the score of the older group was higher than
        chance (Z = 3.20, p = .001, r = .64). Moreover, the analyses using children’s
        actual response showed similar results (control condition: younger group, Z =
        −1.58, p = .127; older group, Z = 0.87, p = .383; emotional expression condition:
        younger group, Z = −0.45, p = .655; older group, Z = 3.29, p = .001).

<hs>  Discussion</hs>
  ~~~~~~~~~~

Experiment 2 compared 4- to 6-year-olds’ counterfactual thinking in control and emotional
expression conditions. The results showed that children’s performance was worse under the
control condition (percentage of correct answers = 31.3%) than under the emotional
expression condition (percentage of correct answers = 46.0%); the performance in the
control condition was similar to chance even in the older group. In the control condition
in Experiment 2, the same physical event scenarios were used as in Experiment 1. The
results, therefore, confirmed the findings of Experiment 1, meaning that young children
find it difficult to think counterfactually about physical events that do not involve an
emotional component. On the other hand, the task performance was better in the emotional
expression condition than in the control condition; in particular, the performance of the
older group (percentage of correct answers = 60.0%) was higher than chance. These results
show that 5- and 6-year-olds can think of counterfactual alternatives not only about
events associated with emotional change but also about events associated with physical
change as long as negative emotional responses to the events are presented. However, in
the emotional expression condition of Experiment 2, it is possible that children’s better
performance was a consequence of paying more attention to one of the two characters in the
scenario. In other words, the results of Experiment 2 leave open the possibility that
young children’s counterfactual thinking is encouraged when there is one protagonist in a
physical scenario. To eliminate this possibility, in Experiment 3 we created a new set of
physical scenarios with only one character and examined the influence of emotional
expression condition by using these scenarios.

        <hss>Participants</hss>

        The participants were 48 children aged 4 to 6 years (24 boys and 24 girls; Mage =
        63.88 months, SD = 6.47, range = 53–75) recruited from two public nursery schools
        in Shizuoka. All of the participants spoke Japanese as their first language and
        were members of middle-class households. As in Experiment 2, these children were
        divided into two groups: a younger group with 24 children (12 boys and 12 girls;
        Mage = 58.21 months, SD = 2.99, range = 53–64) and an older group with 24 children
        (12 boys and 12 girls; Mage = 69.54 months, SD = 3.08, range = 65–75). None of the
        participants from Experiments 1 and 2 participated in Experiment 3.

        <hss>Materials</hss>

        Based on the three physical task scenarios used in Experiments 1 and 2, new
        scenarios were created in which only one protagonist made an appearance. These
        scenarios had the same causal structure in Experiment 2. Each scenario used six
        pictures representing the story content and three pictures as possible answers to
        the counterfactual question. For example, the footprint scenario went as follows:
        “This is Taro. He is playing outside and has mud on his shoes. This is the inside
        of Taro’s house. Today, the floor is very clean. A short while later, Taro walks
        across the floor with his shoes on to get a drink of water and leaves footprints
        on the floor. Later, Taro walks back across the floor with his shoes on to go
        outside, leaving two sets of footprints on the floor.” As in Experiment 2, in the
        emotional expression condition, “a picture associated with the initial emotional
        state of the protagonist” and “a picture associated with the final emotional state
        of the protagonist” were added to the six original pictures for each scenario.

        <hss>Procedure</hss>

        All of the steps in this experiment were reviewed and approved by the affiliated
        university’s committee for ethical research involving human participants. As with
        Experiments 1 and 2, written consent was obtained from a principal of each nursery
        school, and verbal assent was obtained from the children. Participants were
        allocated to either the control condition or the emotional expression condition.
        In total, 12 children in a younger group (6 boys and 6 girls; Mage = 58.83 months)
        and 12 children in an older group (6 boys and 6 girls; Mage = 70.17 months) were
        allocated to the control conditions, whereas 12 children in a younger group (6
        boys and 6 girls; Mage = 57.58 months) and 12 children in an older group (6 boys
        and 6 girls; Mage = 68.92 months) were allocated to the emotional expression
        conditions. No significant differences in months of age by condition or gender
        were seen in either age group. Each participant was interviewed individually in a
        quiet room. The interview lasted approximately 15 min. In both conditions,
        participants were asked to perform three counterfactual tasks. The order of
        presenting the three counterfactual tasks was counterbalanced among participants.
        In both conditions, task procedures were the same as those in Experiment 2 except
        for using the new scenarios.

<hs>  Results</hs>
  ~~~~~~~

Preliminary analyses did not demonstrate any gender difference. So, the genders were mixed
in the following analyses.

        <hss>Understanding the contents of scenarios</hss>

        Overall, the percentage of correct answers to the control questions was 96.5%. In
        the control condition, the percentages of correct answers were 97.2% for the Now
        question, 95.8% for the Before question, and 96.5% overall. In the emotional
        expression condition, the percentages of correct answers were 94.4% for the Now
        question, 98.6% for the Before question, and 96.5% overall. Some children gave
        only one wrong answer (5 participants in the control condition and 5 participants
        in the emotional expression condition). Therefore, as in Experiments 1 and 2, they
        were not excluded from the sample.

        <hss>Answers to the counterfactual questions</hss>

        The counterfactual scores in each condition were calculated using the same scoring
        procedure as in Experiment 1. Table 3 shows the mean scores and the numbers and
        percentages of children receiving scores of 0, 1, 2, and 3 by age and condition.
        First, an ordinal regression analysis was conducted. This analysis included age
        group (younger or older) and condition (control or emotional expression) as
        categorical predictors and the Age Group × Condition interaction. This model was
        significant, χ2(3) = 9.57, p = .023. The older group had only a marginally higher
        score compared with the younger group, B = −1.49, SE = 0.78, Wald χ2(1) = 3.66, p
        = .056, odds ratio = 4.45, 95% CI [−3.02, 0.04]. In addition, the main effect of
        the condition was significant; participants in the emotional expression condition
        had a significantly higher score than those in the control condition, B = −0.58,
        SE = 0.78, Wald χ2(1) = 4.06, p = .044, odds ratio = 4.85, 95% CI [−3.11, −0.04].
        The Age Group × Condition interaction was not significant (p = .466). Second, a
        one-sample Wilcoxon signed-rank test using a counterfactual score was performed by
        age group and condition (chance = 1.00). In the control condition, the scores of
        both the younger group (Z = −0.632, p = .527, r = .18) and the older group (Z =
        0.80, p = .426, r = .23) were no different from chance. In the emotional
        expression condition, the score of the younger group was no different from chance
        (Z = 1.00, p = .317, r = .29), but the score of the older group was higher than
        chance (Z = 2.92, p = .004, r = .85). Moreover, there were no differences between
        the above results and the results of analyses using children’s actual response.
        Finally, the task scores in Experiments 2 and 3 were compared by age group and
        condition. Mann–Whitney U tests found no significant differences in the scores
        between Experiments 2 and 3: the control condition (U = 133, p = .684, r = .07)
        and emotional expression condition (U = 108.5, p = .283, r = .18) in the middle
        group and the control condition (U = 148, p = .947, r = .01) and emotional
        expression condition (U = 125.5, p = .465, r = .14) in the older group.

<hs>  Discussion</hs>
  ~~~~~~~~~~

To resolve the remaining issues in Experiment 2, Experiment 3 examined the difference of
young children’s counterfactual thinking between the control and emotional expression
conditions using a scenario with only one protagonist. The results showed that
participants performed worse under the control condition (percentage of correct answers =
34.7%) than under the emotional expression condition (percentage of correct answers =
55.7%); the level in the control condition was similar to chance even in the older group.
On the other hand, the task performance in the emotional expression condition was better
than in the control condition; in particular, the performance of the older group
(percentage of correct answers = 69.3%) was higher than chance. A comparison of
Experiments 2 and 3 showed no differences in young children’s task performance. The
Experiment 3 results confirm that the results of Experiment 2 were not caused by an
artifact of the task (e.g., a different number of characters) but rather were caused by a
protagonist’s emotional response to the event. In sum, the results of Experiment 3
strengthened the claim that 5- and 6-year-olds can think of counterfactuals for events
associated with physical change as long as other persons’ negative emotional responses to
the event are presented.

<h>GENERAL DISCUSSION</h>
------------------

One of the main themes in research on the development of counterfactual thinking involves
the question of when the capacity for counterfactual thinking is acquired. To address this
question, the current study examined young children’s counterfactual thinking about
physical and emotional events using discriminating counterfactual tasks that children
could not easily answer correctly via basic conditional reasoning. Experiment 1 showed
that, although children younger than 5 or 6 years can generate counterfactual alternatives
for emotional events, even 5- and 6-year-olds have difficulty in thinking counterfactually
about physical events. Moreover, Experiment 2 showed that presenting with the
protagonist’s negative feelings about an event outcome (the emotional expression
condition) enables 5- and 6-year-olds to think counterfactually about physical events.
Finally, Experiment 3 confirmed that the better performance of young children under the
emotional expression condition was not the result of an artifact of the task. As mentioned
in the Introduction, Rafetseder et al. (2010, 2013) have shown that 5- and 6-year-olds
find it difficult to think of counterfactual alternatives using discriminating
counterfactual tasks. The current study demonstrates that the performance of tasks
associated with physical events does not significantly exceed chance even among children
aged 5 and 6 years (percentages of correct answers: physical event task in Experiment 1 =
27.7%, control condition in Experiment 2 = 38.7%, control condition in Experiment 3 =
41.7%). The results of this study support those of Rafetseder et al. (2013). However, the
current study also shows that 5- and 6-year-olds can think of counterfactual alternatives
as long as there is an explicit reference to the protagonist’s negative feelings about the
event (percentages of correct answers: emotion event task in Experiment 1 = 75.0%,
emotional expression condition in Experiment 2 = 60.0%, emotional expression condition in
Experiment 3 = 69.3%). These results demonstrate that children aged 5 and 6 years are
capable of counterfactual thinking in a certain situation such as presenting the other’s
emotions. In other words, the results of the current study support the claim that the
ability to think counterfactually is acquired by 5 or 6 years of age (Beck et al., 2010;
German, 1999; German & Nichols, 2003; Nakamichi, 2011; Riggs et al., 1998) even when
discriminating counterfactual tasks are used. Why do children display their capacity for
counterfactual thinking only when a scenario protagonist explicitly shows negative
emotion? As mentioned in the Introduction, one possible explanation is that human negative
emotion triggers the counterfactual thinking in young children by clearly conveying the
outcome valence of an event. Humans’ negative emotion plays the role of clearly conveying
the outcome valence of an event. Counterfactual thinking in both adults (Byrne, 2005,
2016; Epstude & Roese, 2008) and children (German, 1999; Guajardo et al., 2016) is
triggered by the negative outcome valence of an event. Indeed, young children find it
easier to think of a counterfactual alternative for an event associated with a change in
another person’s emotions than for a physical event that does not have a potentially
negative outcome (Guajardo et al., 2009; Nakamichi, 2011). For this reason, when the
protagonist’s negative emotions were explicitly presented, the young children in this
study should demonstrate their capacity for counterfactual thinking. This explanation may
get support from other developmental studies. From their early years of life, children
have sensitivity to others’ face and/or facial expressions. Even infants tend to look at
face-like images longer than at any other pattern such as colored circles and concentric
circles (Fantz, 1961) and react appropriately to distinct facial expressions (Tronick,
Als, Adamson, Wise, & Brazelton, 1978). Moreover, children refer to other people’s
emotions, and change their mode of thinking and course of action, based on other people’s
emotions. For example, even 12-month-old infants go over the visual cliff when their
mothers display positive expressions, but not when their mothers display negative
expressions (Sorce, Emde, Campos, & Kilinnert, 1985). On the basis of these studies, it
seems reasonable to assume that presenting the protagonist’s emotions gets young
children’s attention, consequently improving their performances on counterfactual tasks.
Of course, the results of the current study do not imply that 5- and 6-year-old children
have an adult-like capacity for counterfactual thought. In line with Rafetseder et al.
(2013), participants in this study found it difficult to perform physical event tasks.
Rafetseder et al. (2013) argued that counterfactual thinking emerged later—at around 12
years of age. By contrast, based on the results of this study, we deem it likely that even
preschool children have the ability to think counterfactually. However, we agree that
children have a long way to go to be able to think of counterfactual alternatives without
any prompting (e.g., the other person’s negative emotion expression) such as adult-like
counterfactual thinking. In addition, this study’s participants were native Japanese
preschoolers. The current study advances the previous literature by showing the
development of counterfactual thinking in non-English speakers. On the other hand, this
fact implies that the results might be limited to Japanese. Therefore, they need to be
replicated with English speakers’ samples. Despite these limitations, the results of the
current study suggest three directions for future research. One direction is to integrate
the effect of emotional component into the recent studies focusing on the causal structure
of events and the task demands (McCormack et al., 2018; Nyhout & Ganea, 2019; Nyhout et
al., 2019). For example, Nyhout et al. (2019) manipulated the causal relation between
antecedent events (e.g., two antecedent events were causally connected or disconnected to
one another) in Rafetseder et al. (2013) tasks and investigated children’s counterfactual
thinking. The results showed that, given events with clear causal structures, children
aged 6 to 8 years could reason counterfactually. Based on our finding, children might
succeed much earlier on Nyhout and colleagues’ tasks when events include the emotional
component. The second direction involves determining the types of event that drive
counterfactual thinking in young children. The current study has demonstrated that
children’s performance on counterfactual tasks varies, depending on the content of the
event (physical or emotional). Previous developmental studies (e.g., German, 1999;
Guajardo et al., 2016) have focused on whether an event involves negative consequences;
therefore, little is known about the influence of event content on young children’s
counterfactual thinking. For instance, Guajardo et al. (2016, Experiment 1) showed that 8-
to 11-year-olds’ counterfactual thinking was influenced by not only outcome valence but
also outcome expectancy. Moreover, adults tend to think of counterfactual alternatives
more frequently for events they can control as opposed to events they cannot control
(Byrne, 2005, 2016). Young children may have the same tendency to generate counterfactual
alternatives spontaneously. In addition, Beck and Riggs (2014) also suggested that the
amount of knowledge of the target domain is one factor that contributes to the development
of counterfactual thinking. They argued that having much causal knowledge about a
particular domain promotes the thinking about alternative possibilities related to that
domain. Young children may spontaneously think of counterfactual alternatives for event
domains they understand well or with which they are familiar. Such research would expand
further our understanding of the development of counterfactual thinking. Another direction
is to clarify the relationship between counterfactual thinking and executive function
(EF). EF is a cognitive process that exerts goal-oriented control over thought, behavior,
and emotion. It encompasses working memory (WM), inhibitory control (IC), and cognitive
flexibility as its components (Garon, Bryson, & Smith, 2008). Counterfactual thinking
requires the individual to retain and update two pieces of information: “existing reality
(i.e., an actual event)” and an “imagined alternative possibility.” To do this, the
individual must inhibit existing real information in order to think of alternative
possibilities (Beck & Riggs, 2014; Byrne, 2005, 2016). Hence, this process of
counterfactual thinking requires EF. However, relationships between counterfactual
thinking and EF during childhood are not stable. Some studies (Drayton, Turley-Ames, &
Guajardo, 2011; Guajardo et al., 2009; Müller, Miller, Michalczyk, & Karapinka, 2007) have
shown relationships between counterfactual thinking and WM or IC in young children,
whereas one study (Beck, Riggs, & Gorniak, 2009) found that counterfactual thinking is
unrelated to WM. EF has dual aspects (Zelazo & Carlson, 2012): the process activated in an
emotionally neutral context (i.e., cool EF) and the process activated in an emotional
context (i.e., hot EF). As shown in the current and previous studies (Epstude & Roese,
2008; Guajardo et al., 2009; Nakamichi, 2011), an emotional element influences
counterfactual thinking in young children and adults. Thus, counterfactual thinking may
require not only cool EF but also hot EF. So, future studies should examine the
relationship between counterfactual thinking and hot EF. In conclusion, our study results
reveal that 5- and 6-year-old children demonstrate a capacity for counterfactual thinking
even when using discriminating counterfactual tasks that are difficult to answer correctly
without taking the actual events into account. The current study also confirms that
emotional components trigger their counterfactual thinking. These findings suggest the
need to investigate the influence of emotional components and domain-specific knowledge on
counterfactual thinking during early childhood.
<ART>Young infants’ visual fixation patterns in addition and subtraction tasks support an object tracking account
================================================================================

Authors: J. Gavin Bremner, Alan M. Slater, Rachel A. Hayes, Uschi C. Mason, Caroline Murphy, Jo Spring, Lucinda Draper, David Gaskell, Scott P. Johnson
DOI: 10.1016/j.jecp.2017.05.007
Year: 2017  |  Pages: 199-208
ASJC codes: 3204, 3205
Keywords: Addition, Infant perception, Number, Object files, Object tracking, Subtraction

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Investigating infants’ numerical ability is crucial to identifying the developmental origins of numeracy. Wynn (1992) claimed that 5-month-old infants understand addition and subtraction as indicated by longer looking at outcomes that violate numerical operations (i.e., 1 + 1 = 1 and 2 − 1 = 2). However, Wynn's claim was contentious, with others suggesting that her results might reflect a familiarity preference for the initial array or that they could be explained in terms of object tracking. To cast light on this controversy, Wynn's conditions were replicated with conventional looking time supplemented with eye-tracker data. In the incorrect outcome of 2 in a subtraction event (2 − 1 = 2), infants looked selectively at the incorrectly present object, a finding that is not predicted by an initial array preference account or a symbolic numerical account but that is consistent with a perceptual object tracking account. It appears that young infants can track at least one object over occlusion, and this may form the precursor of numerical ability.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Numeracy is a key aspect of adult cognition, and identifying its origins is vital to
understanding its development during childhood and thereafter. Thus, a key area of
research concerns infants’ ability to understand number. One strong claim is that young
infants compute the outcomes of addition and subtraction manipulations. This was first
suggested in a study by Wynn (1992). In an addition (1 + 1) condition, 5-month-old infants
saw a doll being placed on a stage. A screen then concealed the doll and a hand appeared
holding a second doll and placing it behind the screen. In a subtraction (2 − 1)
condition, infants saw two dolls being placed on the stage followed by the screen
concealing them. A hand then appeared, went behind the screen, and emerged holding one
doll. On subsequent test trials, for both conditions the screen was raised, revealing
either one doll or two dolls. In both conditions, infants looked longer at the impossible
outcome (either 1 + 1 = 1 or 2 − 1 = 2) than at the possible outcome (either 1 + 1 = 2 or
2 − 1 = 1), with longer looking being interpreted as a violation of their expectation
regarding the numerical outcome. Replications of Wynn’s findings have used both three-
dimensional displays (Clearfield & Westfahl, 2006; Simon, Hespos, & Rochat, 1995; Slater,
Bremner, Johnson, & Hayes, 2010; Uller, Carey, Huntley-Fenner, & Klatt, 1999; Walden, Kim,
McCoy, & Karrass, 2007) and two-dimensional displays (Berger, Tzur, & Posner, 2006; Moore
& Cocas, 2006). These findings are in keeping with at least three types of converging
evidence: (a) that infants look more at their caregivers’ faces following unexpected
arithmetic outcomes (Walden et al., 2007), (b) that infant event-related potential data
show a similar pattern of activity to that of adults when observing correct and incorrect
arithmetical outcomes (Berger et al., 2006), and (c) that newly hatched domestic chicks
were reported to track small numbers of objects (Rugani, Fontanari, Simoni, Regolin, &
Vallortigara, 2009). Collectively, these results are consistent with the larger claim that
infants can perceive number (Antell & Keating, 1983; Feigenson & Carey, 2003; Feigenson,
Carey, & Hauser, 2002; Lipton & Spelke, 2003; McKrink & Wynn, 2004, 2007; Xu, 2003; Xu &
Arriaga, 2007; Xu & Spelke, 2000) and track numerosity of small number sets (Berger et
al., 2006; Clearfield & Westfahl, 2006; Moore & Cocas, 2006; Simon et al., 1995; Uller et
al., 1999; vanMarle, 2013; Walden et al., 2007). Wynn (1992) concluded that the ability to
perform simple arithmetical calculations is innate and may be the foundation on which
subsequent arithmetical ability builds. She argued that her results are evidence for a
true symbolic number concept, favoring an accumulator mechanism (Meck & Church, 1983) as
the basis on which numerical judgments are reached. A key point in this account is that a
single symbol represents the number concerned. On the other hand, lower-level
interpretations of Wynn’s (1992) findings are possible due to the simple nature of the
dependent measure. For example, from a standpoint in which cognitive abilities such as
numerical knowledge are constructed progressively during infancy (Cohen, Chaput, & Cashon,
2002), Cohen and Marks (2002) suggested an interpretation in terms of a perceptual process
based on two principles: (a) a preference for familiarity (i.e., the display originally
seen before the screen occluded it) and (b) a preference for displays containing a larger
number of items. This interpretation is clearly important because, if correct, it would
indicate that performance on Wynn’s (1992) task indicates little about infants’ ability to
keep track of objects across occlusion, let alone whether infants understand operations of
addition and subtraction of small numbers. Inevitably, Wynn’s conclusions will continue to
attract controversy while the evidence is based on duration of looking anywhere in the
display because this measure is open to lower-level interpretations such as that of Cohen
and Marks (2002). Thus, it is vital to obtain a measure of infants’ response that allows a
choice between low-level accounts and those based on enumerating or keeping track of
objects. Even if an interpretation in terms of familiarity preference can be dismissed, it
must be recognized that Wynn’s (1992) claim that infants understand the operations 1 + 1 =
2 and 2 − 1 = 1 can be questioned. It is possible that longer looking at violation
outcomes is not based on infants’ realization that the specific operations 1 + 1 = 2 and 2
− 1 = 1 have been violated but rather is based on noting that an object added to the scene
is not present or that an object removed from the scene is still present. An alternative
to Wynn’s symbolic account is based on object file accounts derived from adult research
(Kahneman, Treisman, & Gibbs, 1992; Pylyshyn & Storm, 1988; Scholl, 2001) and locates
performance in tracking discrete objects and noting violations of continuity for any of
these objects. For the current purposes, the key claim of this object file account is that
each object is represented separately; there is no symbolic representation of the number
of objects. According to Uller et al. (1999), the object file account is numerical in the
sense that the system counts objects (there is one object and there is another object) but
falls short of a symbolic number concept in the sense that there is no symbol for the
collection of objects. In addition, the process is very much perceptual rather than based
on reasoning and understanding and, thus, tends to be considered an implicit numerical
system (vanMarle, 2013). Our rationale in this investigation was that the precision of
eye-tracker data should allow further evaluation of the perceptual preference, object
tracking, and symbolic numerical accounts through differential predictions regarding
fixation patterns that would appear to arise from each account. The clearest predictions
arise in the case of the subtraction violation condition in which two objects remain. If
Cohen and Marks’s (2002) familiarity preference is correct, there should be equal looking
at each object because both objects would be equally part of the familiar starting array.
Wynn’s (1992) symbolic numerical account also predicts longer looking at both objects. The
unexpected outcome following the removal of one of the original two dolls is the incorrect
numerical outcome (two dolls). Thus, we would expect infants to direct increased looking
to both objects because together they constitute the incorrect number. It seems likely,
however, that a particularly high proportion of looking would be directed to the object
that should not be there because it is at the root of the numerical violation. Still, the
important point is that if infants are evaluating the symbolic numerical outcome, the
object that was not subject to subtraction should also be a focus of particular attention.
In contrast, in the object file account, objects maintain separate files and only one
object file is violated (by its continuing presence despite its earlier removal). Thus,
infants should devote a high proportion of their looking to the object that should no
longer be there, but they should show no increase in looking to the other object because
its file remains unviolated. Although in principle the object file or symbolic numerical
account might predict longer looking at the empty location in addition violation (one toy
outcome), this cannot be a strong prediction because there is nothing to fixate there and
so infants’ looking is likely to be drawn to other features, particularly the one toy that
is present. But it is possible that infants responding on the basis of object tracking or
number violation will look elsewhere, particularly to the place where objects appear from,
as if searching for the missing object or that they will look more at the empty location
in the addition violation than in the correct outcome of subtraction when the position is
correctly empty. Thus, here we followed Wynn’s (1992) procedure for testing infants’
responses to addition and subtraction events. Crucially, however, we gathered precise eye-
tracker records of visual fixation. To ensure that we could replicate Wynn’s results, we
also measured looking duration to the stage in the conventional way.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

A total of 34 4- and 5-month-old infants provided usable data (Mage = 148.06 days, SD =
13.48, range = 119 − 168), 17 in the addition condition (9 boys and 8 girls; Mage = 148.76
days, SD = 14.67) and 17 in the subtraction condition (11 boys and 6 girls; Mage = 147.35
days, SD = 12.98). They were recruited from the local maternity unit with appointments
arranged by follow-up phone calls. The majority of infants were White, and all were full
term with no known developmental disabilities and from English-speaking families. Data
from 28 additional infants could not be used because of experimenter error (n = 8),
failure to obtain individual calibration of the point of gaze (n = 4), or excessive
movement such that insufficient eye-tracking data were collected (n = 16). In our
experience, this attrition rate is typical for the type of eye tracker we used.

<hs>  Apparatus</hs>
  ~~~~~~~~~

The events were presented on a lit stage presenting an aperture 37 cm wide × 27 cm high ×
60 cm deep in a dimly lit testing room. A 14-cm-high screen located 30 cm behind the front
of the stage could be rotated to conceal the toys, and a blind could be lowered to conceal
the whole stage. The objects were two 11-cm-tall toy men that squeaked when pressed. The
experimenter presenting the toys wore a long maroon glove. A video camera, placed at the
top center of the stage, recorded infants’ head and eyes for live recording of
preferential looking and for subsequent reliability testing by a naive observer. A remote
optics corneal reflection eye tracker (ASL Model 5000, Applied Science Laboratories,
Bedford, MA, USA), located below and at the midpoint of the stage, was used to collect
fixation data. A plasma display was mounted immediately behind the stage, and prior to
testing each infant’s point of gaze was calibrated in standard fashion by presenting
attention-getting videos.

<hs>  Procedure</hs>
  ~~~~~~~~~

Infants sat either in an infant car seat or on a caregiver’s lap approximately 60 cm from
the screen behind which the toys were placed. In the latter case, the caregiver’s eyes
were above the stage, and the caregiver could not see the displays. A technician
controlled the eye tracker, and another researcher recorded preferential looking during
familiarization and test trials. After gaze calibration, the procedure followed Wynn
(1992). Infants saw two pretest trials of one toy and two toys, respectively, in
counterbalanced order across infants. The blind was raised to reveal either one toy or two
toys, and the observer recorded looking at the toy(s). Toys were placed 35 cm behind the
front edge of the stage. When one toy was presented, it was placed 7.5 cm to the right of
stage midline; when two toys were presented, the other toy was 7.5 cm to left of midline.
The trial continued until the infant had accumulated at least 2 s looking time and looked
away from the display for 2 s or more. The blind was then lowered, and the procedure was
repeated with the other number of toys. Six arithmetic trials were then presented, with
each infant being tested in either the addition condition (1 + 1) or the subtraction
condition (2 − 1), with trials alternating, in counterbalanced order, between the possible
and impossible outcomes in terms of the number of toys revealed. The test trial sequences
are illustrated in Fig. 1. In the addition condition, the experimenter’s gloved hand
emerged stage left (i.e., to the infant’s left) holding a toy that the experimenter
squeaked to capture the infant’s attention. She then moved the toy, still squeaking, and
placed it on the right-hand location used during familiarization. She then slowly withdrew
her hand, at which time the screen was raised to hide the toy. This event, from appearance
of the toy to withdrawal of the hand, took approximately 5 s. The hand then reappeared
from stage left, above the screen, clutching another identical squeaking toy. When she had
the infant’s attention, the experimenter placed the toy in the left-hand location used
during familiarization, raised her hand, clasped and unclasped it to emphasize that it was
empty, and then slowly withdrew it, at which time the screen was lowered to reveal the
outcome of either one toy or two toys. The period from appearance to disappearance of the
experimenter’s hand took approximately 6 s. To replicate Wynn’s (1992) procedure closely
so as to be able to interpret our eye-tracking data relative to her original findings, and
because we had not detected side preferences in other work with this age group, we did not
counterbalance the side from which objects were manipulated, and so the impossible event
(presence or absence) always concerned the left-hand object. We were comfortable with this
decision for two reasons. First, a looking bias to one side would be revealed in our
analyses. Second, our primary analyses concerned comparisons between addition and
subtraction conditions in looking to each respective side and, thus, would not be affected
by an overall side bias. In the subtraction condition, the experimenter placed two
squeaking toys consecutively on the stage, an event that took approximately 9 s. Following
the raising of the screen, her empty hand reappeared above the screen, lowered to the
left-hand floor of the screen, and reappeared holding one toy that she squeaked above the
screen and withdrew screen left, an event that took approximately 6 s, followed by
lowering of the screen to reveal the outcome of one toy or two toys. Between each trial in
each condition, the roller blind was lowered to obscure the stage. The impossible outcome
(either 1 + 1 = 1 or 2 − 1 = 2) was accomplished by silent removal (addition condition) or
addition (subtraction condition) of a toy from the left-hand floor of the screen; each of
the toys was mounted on a velvet-covered disk to ensure that the addition or removal of
the toy was not audible to either the infant or the observer. The observer who recorded
infants’ looking was aware of which condition (addition or subtraction) the infant was in
but was unaware on each test trial of whether the outcome was possible or impossible.
Preferential looking (violation of expectancy) data were recorded on a Mac G4 using Habit
software (Cohen, Atkinson, & Chaput, 2004). A total of 27 infants’ data, for both the
pretest and test trials, were independently scored by a second observer from the video
records, and interobserver reliability was high (r = .986, p < .001).

<hs>  Preferential looking data</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

We replicated Wynn’s (1992) results very clearly. On the test trials, the infants looked
at the unexpected/impossible outcome for a mean of 17.82 s (SD = 8.19) and at the
expected/possible outcome for a mean of 10.36 s (SD = 5.21). A total of 31 infants looked
longer at the impossible outcome, and 3 looked longer at the possible outcome (binomial, p
< .0001). Of the 17 infants in the addition condition, 16 looked longest at the impossible
outcome (p < .001), and 15 of the 17 infants in the subtraction condition did so as well
(p < .001). Analysis of variance (ANOVA) performed on the data confirmed significantly
longer looking at the impossible outcomes than at the correct outcomes, F(1, 32) = 55.00,
p < .001, ηp2 = .63. This effect was qualified by a 2 (Condition: addition or subtraction)
× 2 (Test Trial: expected or unexpected) × 3 (Trial Block) interaction, F(2, 31) = 4.50, p
= .019, ηp2 = .23. This effect stems from a slight increase in looking at expected
outcomes accompanied by a slight decrease in looking at unexpected outcomes across the
first and second trial blocks by infants in the addition condition; these trends were
reversed in the subtraction group. There were no other reliable main effects or
interactions.

<hs>  Eye-tracker data</hs>
  ~~~~~~~~~~~~~~~~

Using Applied Science Laboratories’ Eyenal software, we reduced the raw data to a list of
fixations, and the data analyzed consisted of dwell times in areas of interest (AOIs) that
comprised the regions surrounding the two men on the stage. Preliminary analysis of eye-
tracker data indicated that the vast majority of looks were to the location of the toy
man/men that was/were present on the stage, and there was little looking elsewhere—for
instance, at the location from which the hand emerged—and no evidence for different
patterns of looks in these regions (top left and right quadrants) depending on condition.
Thus, we concentrated on the looking times to AOIs surrounding the locations of the two
men. These AOIs measured 18.5 cm horizontally and 13.5 cm vertically and, thus,
corresponded to the lower left and right quadrants of the stage aperture. Although infants
typically focused on the toys when they were visible, relatively large AOIs were necessary
to detect looking toward an empty object position whose exact location might be uncertain
to the infant. The raw dwell times for these two AOIs, accumulated for each trial, were
converted to proportions of total dwell times recorded for each infant. We performed
separate analyses of these data for the two-object outcomes (Fig. 2) and the one-object
outcomes (Fig. 3). For the two-object outcome, there was a reliable main effect of
condition, F(1, 18) = 5.32, p = .033, ηp2 = .23, the result of longer dwell times overall
by infants in the subtraction condition, consistent with the looking time data reported
previously, that is, longer looking at the impossible two-object outcome (see Fig. 2).
There was also a reliable main effect of position, F(1, 18) = 4.86, p = .041, ηp2 = .21,
qualified by a significant Condition × Position interaction, F(1, 18) = 6.31, p = .022,
ηp2 = .26. This effect stemmed from longer looking toward the left position than toward
the right position by infants in the subtraction condition, F(1, 9) = 7.48, p = .023, ηp2
= .45, but not by infants in the addition condition, F(1, 9) = 0.09, p = .77, ηp2 = .01.
In addition, infants looked longer at the left man when it should not be there
(subtraction) than when it should be there (addition), F(1, 33) = 9.76, p = .006, ηp2 =
.35. In summary, infants in the subtraction condition showed particularly long dwell times
to the most recently manipulated left man that should have been absent. This was confirmed
by analysis of the number of infants who looked longer at the left man than at the right
man. Whereas 10 of 17 infants (binomial p = .63) looked longer at the left man than at the
right man in the addition condition, 15 of 17 infants (binomial p = .002) looked longer at
the left man than at the right man in the subtraction condition. A 2 × 2 chi-square test
on these data confirmed a larger number of infants looking at the left man in the
subtraction condition compared with the addition condition, χ2(1) = 3.78, p = .026. For
the one-object outcome, there was a reliable main effect of condition, F(1, 18) = 8.78, p
= .008, ηp2 = .33, the result of longer dwell times overall by infants in the addition
condition, consistent with the looking time data reported previously, that is, greater
looking overall at the impossible one-man outcome (see Fig. 3). This effect was qualified
by a reliable Condition × Familiarization Order interaction, F(1, 18) = 6.85, p = .017,
ηp2 = .28, which stemmed from longer dwell times overall by infants in the addition
condition who were first familiarized with the two-man event relative to the one-man event
(p = .031) (the reasons for this effect are unclear); the dwell time difference for
infants in the subtraction condition was not significant (p = .10). There was also a
reliable main effect of position, F(1, 18) = 15.96, p = .001, ηp2 = .47, due to longer
dwell times toward the right-man position (M = 33.34 s, SD = 20.33) than toward the
(empty) left-man position (M = 7.84 s, SD = 11.11). The interaction between condition and
position was not statistically significant, F(1, 18) = 0.96, p = .42, ηp2 = .04; in other
words, there was no reliable difference between conditions in looking duration to either
the left-man position or the right-man position. Significantly more infants looked longer
at the right man than at the left man in both the addition condition (binomial p = .02)
and the subtraction condition (binomial p = .013). The lack of longer looking to the left-
hand location in the addition violation condition is unsurprising, given that there was no
object to look at in that location. However, it is possible that during addition violation
trials infants initially looked there on detecting an empty place. To check this, we
analyzed data for the first look infants made after the screen lowered sufficiently to
reveal the top of the man or men. This analysis revealed broadly the same pattern as the
dwell time analysis; totaled across test trials, in the case of one-object outcomes, the
majority of first looks were to the right-hand position (addition violation: left = 5,
right = 35; subtraction correct: left = 3, right = 35), with no difference in left-
position looks between these conditions. It is also possible that infants faced with
addition violation looked with high frequency to the empty left-hand location but looked
away quickly on seeing nothing there. Thus, we compared mean number of looks across trials
to the empty left position and the occupied right position for the same conditions as
above (addition violation: left M = 5.88, SD = 5.32, right M = 10.76, SD = 7.58;
subtraction correct: left M = 3.94, SD = 3.03, right M = 8.24, SD = 4.87). Although
infants looked more often at the empty left location in the addition violation case than
at the subtraction correct case, this difference did not reach significance, t(32) = 1.31,
p = .20.

<h>DISCUSSION</h>
----------

Our key finding from use of the eye tracker is that infants looked reliably longer at the
left-hand man in the subtraction violation two-toy outcome than in the addition correct
two-toy outcome. In the subtraction violation condition, they also looked reliably longer
at the left-hand man than at the right-hand man. In other words, infants looked
particularly long at an object that they had just seen removed from the occluded scene.
This result is not explained by Cohen and Marks’s (2002) interpretation, namely that
infants look longer at the outcome that matches the initial array before the numerical
manipulation. This account would not predict differential looking in the subtraction two-
man outcome because it posits that infants are looking preferentially at a two-object
array in which both objects are equally expected. Similarly, our results do not provide
strong support for a symbolic numerical account. If infants noted a violation of number,
one would expect increased attention to both objects, not just the one most recently
manipulated. A third interpretation, which our data support, is that infants can track the
existence and locations of objects for brief intervals of occlusion. Object
tracking/object file accounts would predict that they “index” both objects in this task
but that their attention is directed to the object whose “file” has been violated. This is
still a higher-level account than Cohen and Marks presented, and it can be argued that
noting a violation of a movement of a single object actually constitutes the fundamental
addition or subtraction operation, namely 0 + 1 = 1 or 1 − 1 = 0. Our findings indicate
clearly that eye-tracker data can be used to compare alternative interpretations of the
findings from violation of expectancy (VoE) studies with infants, and it is our view that
eye tracking could also clarify the interpretation of results arising from a number of key
VoE experiments investigating different aspects of object knowledge during infancy. For
instance, Baillargeon (1986) demonstrated that 6- to 8-month-olds who had seen an
obstruction placed in an object’s path behind an occluder looked longer at object
reemergence than when there was no obstruction, evidence that they represented the hidden
obstruction and understood that the object could not pass through it. Confidence in this
conclusion would be strengthened if infants also showed reduced anticipatory tracking
(Johnson, Amso, & Slemmer, 2003) when an obstruction was present. In addition, our
findings point to a possible perceptual basis for infants’ awareness of number, an account
that carries the advantage of avoiding many of the theoretical problems regarding the
concept of innateness (Haith, 1998). In the subtraction condition, infants’ attention in
the impossible test outcome—two toys on stage—was directed largely at the one toy that
“should not be there.” Thus, performance may be accounted for on the basis of tracking
presence or absence of one object at one location, namely the location where the toy was
added or taken away. Thus, even relatively parsimonious object tracking accounts of small
number judgments (e.g., vanMarle, 2013) may be more complex than the findings from this
task demand. Although a representation of the other object may be formed (Uller et al.,
1999), its presence may act primarily as a referent for the arithmetic operation
constituted by the physical manipulation of the added or subtracted object. This possibly
forms the initial implicit perceptual basis for later arithmetic abilities. Specifically,
prediction of the outcome of tracking a single object across occlusion effectively
consists of adherence to the principles that 0 + 1 = 1 and 1 − 1 = 0. In this respect,
this account is consistent with the argument that awareness of object permanence develops
from perception of object persistence across occlusion (Bremner, Slater, & Johnson, 2015).
We know that young infants’ perception of object persistence across occlusion is limited
to short spatiotemporal gaps in perception (Bremner et al., 2005; Johnson et al., 2003),
and it is likely that this same perceptually constrained process operates in Wynn’s (1992)
task, such that young infants form a perceptual expectation about the persistence of an
added object when the screen is lowered. The additional process revealed in the current
work is that infants apparently track an object off the scene and form a perceptual
expectation of its absence behind the screen, an expectation that is violated when it is
revealed remaining in its original location. In summary, to our knowledge this is the
first study to derive eye-tracking data from a task involving addition and subtraction of
objects from a three-dimensional scene. The clearest results were obtained in the
subtraction violation condition, where infants directed particular attention specifically
to the object that should no longer be there. Selective attention of this sort is not
predicted by a low-level account based on familiarity preference (Cohen & Marks, 2002).
However, the fact that there was no increase in looking to the object that was not subject
to the subtraction operation does not support a symbolic numerical account, according to
which detection of a numerical violation should lead to an increase in attention to both
objects in the outcome scene. Our results are more closely in keeping with an object file
account in which each object is tracked separately, such that attention is directed only
to the object whose file is violated. We favor the view that processing at this level
forms a precursor of symbolic numerical ability, which may well develop through the
constructionist processes advanced by Cohen and Marks (2002).


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<ART>"Why" or "How": The Effect of Concrete Versus Abstract Processing on Intrusive Memories Following Analogue Trauma
================================================================================

Authors: Rachel White, Jennifer Wild
DOI: 10.1016/j.beth.2016.02.004
Year: 2016  |  Pages: 404-415
ASJC codes: 3203
Keywords: Abstract, Concrete, Intrusive memories, Processing mode, Trauma

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Emergency service workers, military personnel, and journalists working in conflict zones are regularly exposed to trauma as part of their jobs and suffer higher rates of posttraumatic stress compared with the general population. These individuals often know that they will be exposed to trauma and therefore have the opportunity to adopt potentially protective cognitive strategies. One cognitive strategy linked to better mood and recovery from upsetting events is concrete information processing. Conversely, abstract information processing is linked to the development of anxiety and depression. We trained 50 healthy participants to apply an abstract or concrete mode of processing to six traumatic film clips and to apply this mode of processing to a posttraining traumatic film. Intrusive memories of the films were recorded for 1 week and the Impact of Events Scale-Revised (IES-R; Weiss & Marmar, 1997) was completed at 1-week follow-up. As predicted, participants in the concrete condition reported significantly fewer intrusive memories in response to the films and had lower IES-R scores compared with those in the abstract condition. They also showed reduced emotional reactivity to the posttraining film. Self-reported proneness to intrusive memories in everyday life was significantly correlated with intrusive memories of the films, whereas trait rumination, trait dissociation, and sleep difficulties were not. Findings suggest that training individuals to adopt a concrete mode of information processing during analogue trauma may protect against the development of intrusive memories.

--------------------------------------------------------------------------------


<hs>  Participants</hs>
  ~~~~~~~~~~~~

A power analysis based on the effect sizes from a similar study by Schartau et al. (2009)
was used to determine the sample size. Results showed that a sample size of 25 in each
condition would have 80% power to detect a significant difference in mean change scores
between the abstract and concrete conditions using a two-group t test with a two-tailed
.05 significance level. Therefore, we concluded that a total of 50 participants would be
needed. Participants over the age of 18 were recruited from King’s College London through
an email circular. We excluded participants who self-reported a mental health problem,
scored 10 or higher on a standardized measure of depression, or scored 33 or higher on a
standardized measure of posttraumatic stress. We excluded these individuals for three
reasons: (a) as an ethical measure to reduce distress in already vulnerable individuals;
(b) to increase homogeneity of participants across the two conditions; and (c) to
replicate the samples of studies that have previously used the trauma film paradigm (e.g.,
Ehring et al., 2009; Schartau et al., 2009). A total of 2 participants were excluded for
scoring above cutoff on the screening measures, and 1 participant was excluded for failure
to follow the instructions during the posttraining test film. This left 50 participants:
26 were randomly assigned to the abstract condition (15 female, Mage = 27.15, SD = 9.11),
and 24 to the concrete condition (13 female, Mage = 24.71, SD = 5.35). Conditions were
comparable on age, t(48) = 1.15, p = .258) and sex, χ2(1) = 0.06, p = .802. Ethical
approval for the study was granted by the Psychiatry, Nursing and Midwifery Research
Ethics Committee at King’s College London.

        <hss>Demographic Questionnaire (Unpublished)</hss>

        A brief demographic questionnaire was included to collect relevant demographic
        information to ensure equivalence of conditions on age, gender, and driving
        frequency (since most of the films contained exposure to RTA footage).

        <hss>Patient Health Questionnaire–9 (Kroenke, Spitzer, & Williams, 2001)</hss>

        Depression was assessed using the Patient Health Questionnaire–9 (PHQ-9; Kroenke,
        Spitzer, & Williams, 2001), a brief depression severity measure consisting of 9
        items. Scores range from 0 to 27, with higher scores indicating greater depression
        severity. This measure has demonstrated high internal consistency (α = .86–.89),
        good test–retest reliability (r = .84), and correlates significantly with other
        standardized measures of depression. The recommended cutoff of ≥ 10 (Kroenke et
        al., 2001) was used to indicate major depression in this study. Internal
        consistency for the current study was modest (Cronbach’s α = .50).

        <hss>Impact of Event Scale–Revised (Weiss & Marmar, 1997)</hss>

        Posttraumatic stress symptoms (both prior to participation and at 1-week follow-
        up) were assessed using the Impact of Event Scale–Revised (IES-R; Weiss & Marmar,
        1997), a widely used measure of PTSD severity, consisting of 22 items. Scores
        range from 0 to 88, with higher scores indicating greater severity of PTSD
        symptoms. The scale has shown high internal consistency (α = .96; Creamer, Bell, &
        Failla, 2003) and test–retest reliability coefficients that range from r = .51 to
        .94 for the individual subscales (Weiss & Marmar, 1997). Concurrent validity has
        been documented, with the scale being highly correlated (r = .84) with the
        Posttraumatic Checklist (Blanchard, Jones-Alexander, Buckley, & Forneris, 1996),
        an established measure of PTSD (Creamer et al., 2003). We used a cutoff of ≥ 33 to
        indicate clinically significant levels of PTSD, as recommended by Creamer et al.
        (2003). High internal consistency was found for the current sample both for
        preexisting symptom levels (α = .87) and at 1-week follow-up (α = .89).

        <hss>Trauma Screener (Unpublished)</hss>

        Participants also completed the Trauma Screener (unpublished), a self-report
        inventory of prior exposure to traumatic events, which has been used in previous
        studies (e.g., Ehlers, Mayou, & Bryant, 1998) and is derived from the trauma
        checklist included in the Clinician-Administered PTSD Scale (Blake et al., 1990).
        It includes a checklist of 16 events such as serious traffic accidents, serious
        other accidents (e.g., fire or explosion), sexual or nonsexual assault, and
        others. It was used to establish an index traumatic event for completing the IES-R
        and to ensure that the event was one in which the person “experienced, witnessed
        or was confronted with an event or events that involved actual or threatened death
        or serious physical injury, or a threat to the physical integrity of self or
        others” (Diagnostic and Statistical Manual [DSM-IV]; APA, 1994).

        State–Trait Anxiety Inventory–Trait Version (Spielberger, Gorsuch, Lushene, Vagg, & Jacobs, 1983)

        The State–Trait Anxiety Inventory–Trait Version (STAI-T) was administered to
        assess equivalence of conditions in proneness to anxiety. This is a widely used
        self-report measure that assesses tendency to feel anxious in response to
        stressful situations (Spielberger et al., 1983). It contains 20 items, with scores
        ranging from 20 to 80, and higher scores indicating higher levels of trait
        anxiety. It has demonstrated high internal consistency (median α = .90),
        acceptable test–retest reliability ranging from r = .73 to r = .86 in nonclinical
        samples, and it correlates with other trait anxiety measures (Spielberger et al.,
        1983). Internal consistency for the current study was high (α = .87).

        <hss>Intrusions Diary (Unpublished)</hss>

        Number of intrusive memories experienced in the week following the experiment was
        measured using an intrusions diary, a standard way of assessing the frequency of
        intrusions (Holmes & Bourne, 2008). Participants were asked to record daily the
        number of times they had experienced spontaneously occurring intrusive memories of
        any of the films. For each intrusion they had, they were asked to record which
        film it referred to (to check that intrusions corresponded to films viewed in the
        study).

        <hss>Perseverative Thinking Questionnaire (Ehring et al., 2010)</hss>

        Trait rumination was measured using the Perseverative Thinking Questionnaire (PTQ;
        Ehring et al., 2010), a content-independent self-report measure of repetitive
        negative thinking (including rumination). It contains 15 items, with scores
        ranging from 0 to 60, with higher scores indicating a greater tendency toward
        repetitive negative thinking. Excellent internal consistency (α = 0.94–0.95) but
        limited test–retest reliability (r = 0.69) have been reported. It demonstrates
        convergent validity, correlating significantly with standard measures of
        rumination and worry (ranging from r = .48 to r = .72; Ehring et al., 2010). It
        also shows concurrent validity, with significant and moderate correlations found
        with severity of anxiety (r = .64) and depressive (r = .54–.58) symptoms (Ehring
        et al., 2010). Internal consistency was high for the current sample (α = .94).

        <hss>Trait Dissociation Questionnaire–Short Version (TDQs; Murray, 1997)</hss>

        Trait dissociation was measured using the Trait Dissociation Questionnaire–Short
        Version (TDQs; Murray, 1997), a measure of trait disposition to dissociate. It
        contains 11 items, with scores ranging from 0 to 55, with higher scores reflecting
        greater trait dissociation. The measure has been validated using an outpatient
        sample and correlates highly with the original TDQ (r = 0.94), which has been
        shown to predict intrusive memories in a student population. It evidences high
        internal consistency (α = 0.86) but limited test–retest reliability (r = 0.56;
        Murray, 1997). Internal consistency for the current sample was acceptable (α =
        .74).

        <hss>Proneness to Intrusive Memories Scale (PIMS; Unpublished)</hss>

        To assess individual proneness to intrusive memories, we administered a 5-point
        scale asking participants to rate the frequency with which they tended to
        experience intrusive memories of stressful or unpleasant events ranging from 0
        (not at all) to 5 (five times a week or more).

        <hss>Insomnia Severity Index (ISI; Morin, Barlow, & Dement, 1993)</hss>

        To assess preexperiment sleep difficulties, we administered the Insomnia Severity
        Index (ISI; Morin, Barlow, & Dement, 1993), a brief 7-item screening measure for
        insomnia severity over the previous 2 weeks. Total scores range from 0 to 28, with
        higher scores indicating higher severity of insomnia. The measure has been
        validated on younger and older populations attending a sleep clinic or receiving
        treatment for insomnia, and has demonstrated adequate internal consistency (α =
        0.74–0.78). It has also demonstrated concurrent validity, correlating
        significantly with other measures of insomnia (sleep diaries, polysomnography, and
        informant and clinician reports), and sensitivity in detecting change in perceived
        sleep difficulties following treatment (Bastien, Vallières, & Morin, 2001).
        Internal consistency was high for the current sample (α = .86).

<hs>  Procedure</hs>
  ~~~~~~~~~

Informed consent was obtained for all participants before taking part in the study.
Participants completed the pretraining measures (PTQ, TDQs, PIMS, and ISI) and were
randomly allocated to the abstract or concrete training condition to complete the film
task. They were told that this involved watching a series of film clips of real-life
traumatic footage, which they would be asked to watch in a particular way according to
some instructions they would be given. The film task was adapted from Schartau et al.
(2009). The two test films (shown pre- and posttraining) contained real-life footage of
the aftermath of road traffic accidents (RTAs) and showed emergency service personnel
working to extract trapped victims, severely injured individuals in distress, and dead
bodies being moved. These were selected from a series of films containing footage of RTAs
compiled by Steil (1997), which has been used in previous studies (e.g., Holmes et al.,
2004; Murray, 1997; Steil, 1997). The series of films was piloted on a small sample of
student volunteers (N = 10) from King’s College London who met the study’s eligibility
criteria, to establish which two films evoked the most distress and hence would best serve
as a pre- and posttraining test films. The two films selected were rated as the most
distressing (> 55 on a 0–100 scale) and were comparable in the level of distress they
evoked (pretraining film: M = 55.30, SD = 27.81; posttraining film: M = 59.70, SD = 23.45;
t(9) = 1.346, p = .211). Three additional RTA films were selected from this series as
practice films. The remaining three practice films were borrowed with permission from
Schartau et al. (2009) and included non-RTA scenes of violence involving animals and
humans. We selected both RTA and non-RTA films so that participants could practice on a
range of stimuli. Films ranged from 21 to 137 seconds (M = 89.00, SD = 35.88). Each film
contained a short introduction at the beginning explaining what each depicted. Films were
shown on a 15-in. computer screen and the film task followed six steps (see Figure 1).
First, participants were asked to rate their current affect on a scale ranging from 0
(extremely negative) to 100 (extremely positive). Second, they were shown the pretraining
test film and asked to simply watch it as they would normally, before rating their
emotional reactions to it. Emotional reactivity was indexed by two scales ranging from 0
to 100, which measured distress (ranging from no distress to extreme distress) and horror
(ranging from no horror to extreme horror). Distress and horror were chosen as they were
the target emotions used by Schartau et al. (2009), who demonstrated an effect of
appraisal training on these emotions in reaction to distressing films. They also noted
that generalized emotion terms (e.g., distress and negative emotion) have been
demonstrated as reliable indices of emotion change in response to experimental
manipulations (Richards & Gross, 2000) and bear similarity to the Subjective Units of
Distress measure, which is often used in clinical research and practice (e.g., Dalgleish &
Yiend, 2006), as well as being emotions historically elicited by traumatic experiences.
Participants also rated the degree of personal relevance of the pretraining test film.
They were asked, “How much personal relevance did this film have for you?” with the scale
ranging from 0 (none) to 100 (extreme). This was included to assess any differences
between the conditions in the extent to which the films were personally relevant. Third,
participants were given instructions for how to watch the subsequent films and shown the
six practice films. Instructions were presented verbally at first, as well as being
presented on the computer screen before each practice film. After each film, the word
“relax” appeared on the screen for 5 seconds, which aimed to minimize any accumulative
effect of the training phase on mood. Participants in the abstract condition received the
following instructions: “When watching the films, please focus on: (1) Why these sorts of
things happen; (2) What it means about the world; (3) What it means for the people
involved; (4) What if this were to happen to you, or someone in your family?” For
participants in the concrete condition, the instructions were as follows: “When watching
the films, please focus on: (1) The specific and objective details of the event, for
example, what you can see, what you can hear; (2) The sequence of events as they are
unfolding; (3) What needs to happen step by step from here.” Following Schartau et al.
(2009), before the first practice film, participants were given examples of how they might
apply the assigned processing mode to it, before practicing applying it on their own. For
the remaining films, examples were not given beforehand although after each of the first
three films, participants were asked to give examples of their thoughts while watching the
film so that the investigator could be sure that they understood the instructions and that
their thoughts reflected their assigned processing mode. Where participants were clearly
not applying the required mode of processing or their feedback reflected thoughts that
were inconsistent with that mode of processing, the instructions were repeated with
further clarification and examples where necessary. For the remaining three films,
participants were simply asked whether they thought they had successfully applied the
required processing mode and prompted to continue doing so. Fourth, participants were
asked to rate their affect for the second time on the scale ranging from 0 (extremely
negative) to 100 (extremely positive).2 Fifth, participants were shown the posttraining
test film with instructions presented onscreen telling them to watch it in the way that
they had been practicing so far, followed by the assessment of emotional reactivity (i.e.,
self-report ratings of distress and horror in response to the final film) and personal
relevance ratings. Sixth, a manipulation check was carried out whereby participants were
asked to rate their level of adherence to the instructions on a scale, which asked: “To
what extent did you watch the film according to the instructions given to you?” with
responses ranging from 0 (none of the time) to 100 (all of the time). In addition, their
level of attention to the film was assessed by asking: “To what extent did you pay
attention to the film?” with a scale of responses ranging from 0 (none of the time) to 100
(all of the time). Participants were excluded if their level of adherence or attention was
less than 50%, which resulted in one participant being excluded from the analysis.
Afterwards, participants were given the intrusions diary and asked to record any
spontaneous intrusive memories of any of the scenes they saw during the films for the
following week. The experimenter checked that participants were not showing significant
signs of distress before leaving the session and provided participants with one of the
researcher’s contact details should they wish to discuss their experience of the study.
Participants posted the diary back 1 week later following an email prompt, which contained
a link to an online version of the IES-R that they were asked to complete. They were also
asked to rate to what extent they completed the diary reliably and accurately on a 5-point
scale, with responses ranging from 0 (never) to 4 (all of the time). Participants were
given a payment of £15 as compensation for their time.

<hs>  Premanipulation Group Differences</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Table 1 shows descriptive statistics for demographic and baseline variables by condition.
Independent samples t tests revealed no differences between the conditions in levels of
depression, preexisting PTSD symptoms, number of previous traumas, trait anxiety, trait
rumination, trait dissociation, sleep difficulties, proneness to intrusive memories,
baseline affect, personal relevance ratings, or emotional reactivity ratings for the
pretraining film (all ps > .05). A chi-squared test revealed that conditions were also
comparable on driving frequency, χ2(1) = 0.24, p = .877.

<hs>  Instruction and Diary Compliance</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Participants generally reported paying attention to the posttraining test film (M = 92.10,
SD = 10.84) and adhering to the instructions (M = 85.90, SD = 10.43), and there were no
differences between the conditions on these measures (attention: t[48] = 0.02, p = .983;
adherence: t[48] = 0.31, p = .757). Participants generally reported completing the diary
reliably and accurately most of the time (M = 3.79, SD = 0.41) and there were no between-
group differences, t(48) = 0.63, p = .534.

<hs>  Effect of Processing Mode Training on Affect</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

To investigate the effect of training on affect following the practice films, we conducted
a 2 (Condition: abstract, concrete) × 2 (Time: pretraining, posttraining) mixed model
analysis of variance (ANOVA), with Condition as the between-subjects factor and Time as
the repeated measures factor. Results indicated a significant main effect of Time, F(1,
37) = 104.36, p < .001, ηp2 = .74, which was qualified by a significant Condition × Time
interaction, F(1, 37) = 5.26, p = .028 ηp2 = .12 (see Figure 2). Paired samples t tests
confirmed that participants in both conditions rated their affect as more negative from
pre- to posttraining (abstract: t[18] = 8.22, p < .001, d = − 2.25, 95% CI [28.21, 47.58];
concrete: t[19] = 6.06, p < .001, d = − 1.62, 95% CI [15.71, 32.30]). A t test confirmed
that the decrease in affect was greater in the abstract condition than in the concrete
condition, t(37) = − 2.29, p = .028, d = 0.73, 95% CI [− 26.17, − 1.619].

<hs>  Effect of Processing Mode Training on the Development of Intrusive Memories and IES-R Scores</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Of the whole sample, 47 participants (94%) reported at least one intrusive memory relating
to the films. Figure 3 shows the number of intrusions and IES-R scores by condition. We
conducted independent samples t tests to test our prediction that participants in the
concrete condition would experience fewer intrusions during the following week and lower
IES-R scores at 1-week follow-up. As predicted, participants in the concrete condition
reported significantly fewer intrusive memories over the following week than those in the
abstract condition, t(48) = 2.07, p = .044, d = 0.59, 95% CI [1.69, 4.53]. Likewise,
participants in the concrete condition reported significantly lower IES-R scores than
those in the abstract condition at 1-week follow-up, t(48) = 2.78, p = .009, d = 0.78, 95%
CI [1.69, 10.95]. We conducted bivariate correlational analyses to assess whether number
of intrusions or IES-R scores were related to change in affect over the training session.
These showed that there was no significant relationship between change in affect from pre-
to posttraining and number of intrusive memories, r = − .20, p = .229, or between affect
change and IES-R score, r = − .27, p = .095.

<hs>  Effect of Processing Mode Training on Emotional Reactivity</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Figure 4 shows change scores in distress and horror ratings from pre- to posttraining by
condition. To investigate the effect of training on emotional reactivity to the
posttraining test film, we conducted a 2 (Condition) × 2 (Time) multivariate analysis of
variance (MANOVA) on distress and horror ratings. Results indicated a significant
multivariate Condition × Time interaction, F(1, 47) = 3.50, p = .038, ηp2 = .13, which
allowed us to interpret the univariate ANOVAs. Univariate ANOVAs revealed a significant
Condition × Time interaction for distress ratings, F = (1, 48) = 5.95, p = .018, ηp2 =
.11, and horror ratings, F = (1, 48) = 5.03, p = .030, ηp2 = .10. This suggests that
concrete training led to less emotional reactivity to the posttraining test film relative
to abstract training. Paired samples t tests comparing pre- and posttraining distress
scores showed a significant increase in subjective distress ratings from pre- to
posttraining test films in the abstract condition, t(25) = − 5.51, p < .001, d = 0.68, 95%
CI [− 21.93, − 10.00], but no significant increase in the concrete condition t(23) = 0.00,
p = 1.000, d = 0.00, 95% CI [− 12.51, 12.51]. Similarly, for horror ratings, a significant
increase was found in the abstract condition, t(25) = − 2.87, p = .008, d = 0.44, 95% CI
[− 19.50, − 3.20], compared with no significant increase in the concrete condition, t(23)
= 0.65, p = .520, d = − 0.12, 95% CI [− 7.67, 14.76]. These findings suggest that abstract
training led to both increased distress and horror reactions to the posttraining test
film, whereas concrete training did not. There was a significant correlation between
change in affect and change in distress ratings, r = − .32, p = .047, with decreased
affect from pre-to posttraining being associated with increased distress ratings. Since
participants in the abstract condition showed a greater decrease in affect from pre- to
posttraining than those in the concrete condition, we conducted a mixed model analysis of
covariance (ANCOVA) to investigate whether increases in distress in the abstract condition
could be attributed to decreases in affect rather than to mode of processing. However,
when change in affect from pre- to posttraining was included as a covariate, the effect of
condition on changes in distress ratings remained, F(1, 36) = 6.80, p = .013, ηp2 = .16,
indicating a significant increase in distress ratings in the abstract but not the concrete
condition (abstract: t[25] = − 5.51, p < .001, d = 0.68, 95% CI [− 21.93, − 10.00],
concrete: t[23] = 0.00, p = 1.000, d = 0.00, 95% CI [− 12.51, 12.51]). There was no
significant correlation between change in affect and change in horror ratings, r = − .21,
p = .191.

<hs>  Relationship Between Predictor Variables and Intrusive Memories</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

We conducted correlational analyses to explore relationships between predictor variables
(trait rumination and dissociation, proneness to intrusive memories, and sleep
difficulties) and primary outcome measures (number of intrusions and IES-R scores). None
of these were significant apart from proneness to intrusive memories, which was
significantly associated with the development of intrusive memories following the films.
Since greater proneness to intrusive memories following negative events in everyday life
was associated with a higher number of reported intrusions of the films, r = .32, p =
.025, we conducted a univariate ANCOVA to investigate the effect of condition on intrusive
memories while controlling for participants’ proneness to intrusive memories. There was a
significant effect of condition on intrusions after controlling for the effect of
proneness to intrusive memories, F(1, 47) = 4.40, p = .041, ηp2 = .09, with fewer
intrusive memories reported in the concrete compared with the abstract condition, t(48) =
2.07, p = .044, d = 0.59, 95% CI [1.69, 4.53].

<h>DISCUSSION</h>
----------

This study investigated the effect of adopting an abstract or concrete mode of processing
during exposure to analogue trauma and the subsequent development of intrusive memories.
As predicted, individuals who were trained to adopt concrete information processing while
watching the traumatic films reported fewer intrusive memories and lower PTSD symptom
severity scores during the following week compared with individuals who were trained to
adopt abstract information processing. Concrete information processing also led to less
emotional reactivity (measured as distress and horror) to a posttraining film relative to
abstract processing. Our results are consistent with the broader literature showing that
processing mode influences responses to negative events (Watkins, 2008), and correlational
research linking a ruminative, abstract style of processing after trauma to PTSD symptoms
(e.g., El-Leithy et al., 2006; Michael et al., 2007). However, this appears to be the
first study to show that processing mode (i.e., abstract vs. concrete) may be causally
involved in the development of experiences such as intrusive memories, a hallmark feature
of PTSD, and that undergoing training in concrete processing could protect against the
development of intrusions. Furthermore, it supports models highlighting peritraumatic
cognitive processing as a key factor influencing distress and the development of intrusive
memories (e.g., Brewin et al., 1996; Ehlers & Clark, 2000). Since the current study
focused on analogue trauma in a healthy, nontraumatized population, future research could
investigate whether the current findings extend to real-life traumatic events and the
subsequent development of PTSD symptoms. There are different possible mechanisms by which
concrete processing may be more adaptive than abstract processing. First, in line with
existing cognitive models (e.g., Ehlers & Clark, 2000), concrete processing may lead to a
more organized memory and more adaptive appraisals of the event. Halligan, Michael, Clark,
and Ehlers (2003) found that memory disorganization and negative appraisals of a traumatic
event predicted PTSD symptoms in assault survivors. By focusing attention on contextual
details and the overall sequence of events, concrete processing may promote the formation
of a coherent narrative, whereas abstract processing may disrupt this process. In
addition, concrete processing may generate situation-specific appraisals whereas abstract
processing may promote unhelpful, overgeneralized appraisals (Watkins, 2008). Future
research could measure the coherence or accuracy of memories of the trauma films as well
as assessing what kinds of appraisals participants formed of the analogue trauma. Second,
in line with hypotheses about the beneficial effect of concrete relative to abstract
processing more generally, a concrete style of thinking may facilitate emotional
processing of distressing events (e.g., Stöber, 1998; Teasdale & Barnard, 1993),
potentially preventing the development of anxious appraisals (e.g., Behar et al., 2012).
Since the abstract condition included instructions for participants to think about “Why
these sorts of things happen,” “What it means about the world,” and “What if this was to
happen to you or someone in your family?” one rival hypothesis to explain the current
findings is that abstract training discouraged participants from processing the films in a
self-referent way. Self-referent processing refers to organizing information in relation
to the self: in relation to one’s present experience as well as to past experiences and
future goals (Farb et al., 2007). Self-referent processing thus involves processing what
is happening in the context of oneself and distinguishing one’s own experiences from what
is being witnessed. Lack of self-referent processing has been associated with the
development of PTSD symptoms, such as intrusive memories, in clinical and nonclinical
samples (Evans, Ehlers, Mezey, & Clark, 2007; Laposa & Rector, 2012), presumably because
when individuals fail to engage in self-referent processing, they are less likely to
notice how the experiences they are witnessing are different from their own experiences.
Future studies could include a measure of self-referent processing (e.g., Ehlers, 2002).
Proneness to intrusive memories of stressful or unpleasant events in everyday life was
associated with greater intrusions of the trauma films, which is consistent with Davies
and Clark (1998), who found that self-reported tendency to experience intrusive memories
predicted intrusive memories of a traumatic film clip. It is unclear why some individuals
would have a greater tendency to experience intrusive memories, although this may relate
to individual differences in ways of processing negative events (e.g., adopting an
abstract-ruminative style) or strategies used to regulate emotions in response to them.
Future research could further investigate processing styles or emotion regulation
strategies that may be linked to intrusive memories after negative events in everyday
life. However, even after controlling for proneness to intrusive memories, a significant
effect of condition remained, suggesting that even if one were vulnerable to experiencing
intrusions, the likelihood of developing intrusive memories after analogue trauma could be
reduced through training in concrete processing. There are limitations that should be
considered when drawing conclusions from this study. First, our study adopted an analogue
design with a nonclinical sample, therefore we are unable to say whether these findings
would generalize to real-life traumatic events. Second, since we did not include a no-
training control condition, it is difficult to determine whether concrete training is
superior to no training at all. However, because our hypotheses related to the effects of
concrete compared with abstract training, our design fit the hypotheses to be tested and
is consistent with the design of other studies seeking to compare abstract versus concrete
information processing (e.g., Watkins, 2004; Watkins et al., 2008). Future research could
include a no-training control condition to ascertain whether the effects of concrete
processing are indeed superior to no training at all, as well as to abstract processing.
In conclusion, this study provides the first empirical indication that relative to
processing analogue traumatic stimuli in abstract ways, processing them in concrete ways
leads to fewer intrusive memories over the following week and lower emotional reactivity
to a subsequent analogue trauma. Our study also indicates that individuals who self-
reported proneness to intrusive memories in everyday life were more likely to develop
intrusive memories in response to analogue trauma and that concrete processing may reduce
vulnerability to developing intrusions in these individuals. These findings improve our
understanding of the role of peritraumatic processing in the development of intrusive
memories and PTSD symptoms. It would be important to assess the generalizability of the
current findings to at-risk occupational groups who are regularly exposed to trauma, such
as emergency service personnel and journalists in conflict zones, since this could inform
the development of interventions aimed at protecting against intrusive memories and PTSD
in such populations.

<h>CONFLICT OF INTEREST STATEMENT</h>
------------------------------

The authors declare that there are no conflicts of interest.


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<ART>“I just feel so guilty”: The role of introjected regulation in linking appearance goals for exercise with women's body image
================================================================================

Authors: Megan Hurst, Helga Dittmar, Robin Banerjee, Rod Bond
DOI: 10.1016/j.bodyim.2016.12.002
Year: 2017  |  Pages: 120-129
ASJC codes: 3200, 3202, 3207
Keywords: Body anxiety, Body appreciation, Exercise goals, Exercise regulation, Guilt, Self-determination theory

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Appearance goals for exercise are consistently associated with negative body image, but research has yet to consider the processes that link these two variables. Self-determination theory offers one such process: introjected (guilt-based) regulation of exercise behavior. Study 1 investigated these relationships within a cross-sectional sample of female UK students (n = 215, 17–30 years). Appearance goals were indirectly, negatively associated with body image due to links with introjected regulation. Study 2 experimentally tested this pathway, manipulating guilt relating to exercise and appearance goals independently and assessing post-test guilt and body anxiety (n = 165, 18–27 years). The guilt manipulation significantly increased post-test feelings of guilt, and these increases were associated with increased post-test body anxiety, but only for participants in the guilt condition. The implications of these findings for self-determination theory and the importance of guilt for the body image literature are discussed.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Exercising to lose weight and improve one’s appearance is a prominent goal for physical
activity in Western culture, particularly for women: a content analysis of women’s health
and fitness magazines found that over 50% of main features were presented in an appearance
or weight loss frame (Aubrey, 2010) and women appear to endorse these reasons for exercise
more strongly than men (e.g., Furnham, Badmin, & Sneade, 2002). This endorsement of
reasons for exercise such as weight loss, improving appearance, and increasing muscle tone
is consistently associated with more negative body image (Furnham et al., 2002 Tiggemann &
Williamson, 2000). In contrast, health reasons for exercise are associated positively with
body image (Strelan, Mehaffrey, & Tiggemann, 2003). Given the potential consequences of
poor body image for disordered eating behavior (e.g., Stice, 2002) and physical and mental
health more broadly (e.g., Wilson, Latner, & Hayashi, 2013), it is important to understand
why appearance reasons for exercise may be linked with negative body image. However,
previous research has not directly evaluated the mechanisms underlying these associations.
Self-determination theory (SDT) offers a framework within which to contextualize these
different associations, with its focus on the motivation underlying human behavior (e.g.,
Ryan and Deci, 2006). SDT divides individuals’ goals, or reasons for behavior, into
extrinsic goals, which focus on externally evaluated attributes or acquisitions, and
intrinsic goals, which focus on self-development and supporting others around them.
According to Ryan and Deci (2006), the pursuit of intrinsic goals fulfills basic
psychological needs, resulting in higher levels of psychological functioning, whereas the
pursuit of extrinsic goals does not. This proposition is well supported, with the
endorsement of extrinsic goals, such as image and financial success, consistently
associated with negative outcomes such as lower subjective well-being and mental health
difficulties (e.g., Twenge et al., 2010). Overall life goals have also been shown to
predict body image: in a sample of adolescent girls, the intrinsic life goal of health was
associated with better body image, whereas the extrinsic goal of image was associated with
more negative body image (Thøgersen-Ntoumani, Ntoumanis, & Nikitaras, 2010). Thus, the
differential correlations of appearance and health reasons for exercise with body image
could be understood to reflect the extrinsic and intrinsic nature of those reasons.
Crucially, SDT provides an explanatory mechanism for interpreting these correlations,
although it has not been directly tested in the domain of exercise: the regulation
underlying the behavior. SDT suggests that the behavior we engage in when pursuing our
goals can be regulated in a variety of ways, varying in levels of self-determination (how
much the motivation stems from inside the self; Ryan and Deci, 2006). External regulation
occurs when we engage in behavior due to external rewards or pressures, such as when
someone exercises to please others. Introjected regulation is where the motivation for the
behavior has been partially, but not fully, internalized: an individual might exercise to
avoid the guilt they experience if they do not attend a session. Identified regulation is
associated with valuing the benefits of the behavior, whatever these are believed to be,
rather than the behavior itself. Finally, at the most self-determined end of the
continuum, intrinsic regulation is experienced by those who engage in a behavior because
they enjoy the behavior itself. Ryan and Deci (2006) suggest that more self-determined
regulation should be associated with better well-being, due to the feelings of autonomy
that it provides, and review a considerable amount of evidence supporting this assertion,
across multiple domains. Self-determined regulation of behavior has positive associations
with body image, both when considering regulation in general (Pelletier and Dion, 2007)
and, in particular, for exercise behaviors (Brunet and Sabiston, 2009; Brunet, Sabiston,
Castonguay, Ferguson, & Bessette, 2012; Markland, 2009; Thøgersen-Ntoumani & Ntoumanis,
2007). However, research also suggests that self-determined regulation is more likely to
be associated with intrinsic goals, and non-self-determined regulation with extrinsic
ones. Within the exercise domain, research has consistently found that extrinsic goals
(e.g., weight loss, appearance reasons) are associated with less self-determined
regulation, and that intrinsic goals (e.g., health, affiliation) are associated with more
self-determined regulation (Gillison, Standage, & Skevington, 2006; Ingledew & Markland,
2008). Introjected regulation, with its foundation in avoiding guilt and shame, may be
particularly relevant in this context. Although guilt is often conceived as a potentially
positive motivating force, spurring us into action (e.g., Hoffman, 1982), self-
determination theory suggests that guilt-based, introjected motivation may be detrimental
to individuals’ well-being, especially when related to body-modification behaviors, such
as eating regulation and exercise (Verstuyf, Patrick, Vansteenkiste, & Teixeira, 2012).
Guilt-based regulation may be particularly relevant for women’s body image, given gender
differences in the experience of self-conscious emotions. Women are more prone to
experiencing guilt than men, particularly in individualistic cultures, such as the UK and
US (Fischer & Manstead, 2000). Roberts and Goldenberg (2007), in fact, explicitly link
women’s increased propensity to shame and guilt to the objectification of women’s bodies
by society, and suggest that there should be an even greater gender divide in self-
conscious emotions when bodies are made salient, such as in the exercise environment.
Introjected regulation may therefore be particularly important in linking women’s body
image to their reasons or goals for exercise. However, previous research has not
considered appearance goals for exercise, introjected regulation, and body image
simultaneously, tending to focus on just one of the associations between these three
constructs. This approach may obscure the shared variance between these constructs, and a
potential pathway between appearance goals and body image: body image may be associated
with appearance reasons in part as a result of their shared association with guilt-based
regulation.

<h>THE PRESENT RESEARCH</h>
--------------------

The current research investigated the proposal that appearance goals for exercise may be
associated with body image via their joint association with introjected regulation. As
only components of this pathway have been explored previously in the literature, the aim
of the first study was to provide initial cross-sectional support for this proposal. Thus,
the first study employed a structural equation framework to model the direct and indirect
associations between appearance goals, regulation of exercise behavior, and body image.
This method allowed the confirmation of the shared variance between these three variables
of interest, while controlling for their numerous correlates, such as health goals for
exercise and other forms of exercise regulation (e.g., external, identified, and
intrinsic). Notwithstanding the importance of cross-sectional evidence, it cannot provide
true evidence of mediation: to fully test mediation, the mediator should be manipulated
orthogonally from the independent variable (Bullock, Green, & Ha, 2010). Thus, in a second
study, guilt in relation to exercise, the proposed mediator, was manipulated orthogonally
from appearance goals, the proposed independent variable. Using a 2 × 2 experimental
design, appearance goals for exercise and guilt related to not exercising were manipulated
separately, allowing a more robust test of this proposed mediation process. By using a
combination of correlational and experimental designs, the present research aimed to
explore both the direction of causality in these relationships and the naturally occurring
relationships between them, allowing for a fuller picture of this process than either
method alone. For both studies, a sample of young adult women was used, due to the high
frequency of body image issues within this group (Bucchianeri, Arikian, Hannan, Eisenberg,
& Neumark-Sztainer, 2013) and research suggesting that exercise has negative associations
with body image for this group, but not older women or men (Tiggemann & Williamson, 2000).
Furthermore, research suggests that women experience introjected regulation differently
than men (Gillison, Osborn, Standage, & Skevington, 2009) and experience greater levels of
self-conscious emotions in Western cultures (e.g., Fischer & Manstead, 2000). Exercise is
an important behavior in the pursuit of contemporary appearance ideals for both men and
women (e.g., Pope et al., 2000; Tiggemann, 2011); however, the studies reported here focus
on women’s experiences of exercise, in order to provide a specific examination of the
motivational processes involved in linking their appearance reasons for exercise to body
image, which may be very different from men’s.

<h>STUDY 1</h>
-------

Study 1 was designed to identify the regulations for exercise most strongly associated
with body image and appearance goals for exercise and share variance with both. As
discussed above, introjected, or guilt-based, regulation may be particularly relevant in
linking appearance goals for exercise to body image in women. However, SDT would also
predict that external regulation may be associated with appearance goals and with body
image, as a non-self-determined form of regulation. In identifying the specific
regulations that share most variance with both appearance goals and body image, this study
aimed to provide initial evidence for potential pathways between these constructs. Given
the lack of previous research demonstrating this degree of shared variance, between the
three constructs rather than simply two, this cross-sectional study represents a necessary
stage in the development of this research area.

        <hss>Participants and procedure</hss>

        Following institutional ethical approval, 215 female students (17–30 years, M =
        19.77 years, SD = 2.0; 86% white) were recruited from a university participant
        pool to complete an online questionnaire. The ethical procedures of the study
        complied fully with APA and BPS ethical guidelines, with informed consent given
        before the study and debriefing for all participants after completion.

            <hss>Goals for exercise</hss>

            The Exercise Motivations Inventory was used to measure participants’ goals for
            exercise (EMI-2, Markland & Ingledew, 1997). Participants indicated how true
            (on a 5-point response scale ranging from not at all true for me to very true
            for me) each of 51 statements was of their reasons for exercising. The
            appearance goals measure consisted of the Appearance and Weight subscales (8
            items; e.g., “I exercise to help me look better”; α = .95). The health goals
            measure, included to contrast appearance goals, consisted of the Ill Health
            Avoidance and the Positive Health subscales (6 items; e.g., “I exercise to
            have a healthy body”; α = .91). Appearance and Health emerged as distinct
            factors in an exploratory factor analysis of the full inventory, with no
            substantive cross-loading of items.

            <hss>Regulation of exercise behavior</hss>

            Participants’ regulation of their exercise behavior was measured using the
            Behavioural Regulation of Exercise Questionnaire 2 (BREQ-2, Markland & Tobin,
            2004). This 19-item questionnaire includes measures of four subtypes of
            regulation: external (e.g., “I exercise because other people say I should”; α
            = .82), introjected (e.g., “I exercise because I feel guilty when I don’t
            exercise”; α = .82), identified (e.g., “I exercise because I value the
            benefits of exercise”; α = .86) and intrinsic (e.g., “I exercise because it’s
            fun”; α = .95). Participants indicated the extent to which items described
            their regulation of exercise behavior on a 5-point scale (not at all true for
            me to very true for me).

            <hss>Body image</hss>

            Three measures of body image were used. Participants completed a trait version
            of the Physical Appearance State and Trait Anxiety Scale (PASTAS, Reed,
            Thompson, Brannick, & Sacco, 1991), which presents eight body anxiety items
            (legs, waist, stomach, muscle tone, buttocks, hips, size, weight) alongside 12
            filler items. Participants rated how anxious they had felt over the past six
            months about each item on a 5-point scale, ranging from not at all to
            extremely so (α = .91). The Body Appreciation Scale (BAS, Avalos, Tylka, &
            Wood-Barcalow, 2005) was included as a positive measure of body image. The
            scale includes 12 items which assess participants’ positive feelings and
            behaviors toward their body, using a 5-point response scale ranging from not
            at all true for me to very true for me (e.g., “I take a positive attitude
            towards my body”; α = .92). Third, participants completed the Self-Discrepancy
            Index (SDI, Halliwell & Dittmar, 2006). Participants were asked to generate
            four different things about themselves they would like to change (self-
            discrepancies) in an open-ended format, and then rated on a scale from 1 to 6
            how concerned they were about each of these discrepancies (importance) and how
            different they were from their ideal (size). Participants’ responses were
            coded to identify weight, shape or tone (WST) discrepancies (“I am a size 12,
            but I would like to be a size 8”). These were coded separately from
            appearance-related discrepancies that could not be affected by exercise. The
            weight, shape and tone discrepancies were correlated with the PASTAS and BAS
            scores (r = .44 and −.38, respectively, ps < .05). A second researcher coded a
            subset of 25% of these discrepancies and inter-rater agreement on the
            identification of general appearance vs. weight-related discrepancies was high
            (98.3%). As per the published guidelines, size and importance of discrepancy
            were multiplied together and summed to provide a composite total score for
            weight, shape and tone discrepancies.

            <hss>Physical activity and body mass index (BMI)</hss>

            Participants completed the Leisure Time Exercise Questionnaire (LTEQ, Godin &
            Shephard, 1985). Participants reported how many times within an average week
            they engaged in mild, moderate, or strenuous physical activity for more than
            15 min. A combined moderate-strenuous ‘METs’ score was computed from these
            figures.1 BMI was calculated using self-reported height and weight.

<hs>  Results</hs>
  ~~~~~~~

Mplus 7.4 (Muthén & Muthén, 1998–2015) was used to run a structural equation model, in
order to assess the relationships between goals, regulations, and body image (see Table 1
for zero-order correlations and descriptive statistics). Appearance and health goals were
modeled to be correlated and to be associated with the four regulations, which, in turn,
were associated with body image. Goals and regulations were represented as observed
variables using their scale means. Body image was modeled as a latent construct, with the
PASTAS scale mean as the reference indicator due to its strong position within the body
image literature, and with the BAS scale mean and the WST discrepancies score as the other
indicators. Although PASTAS was used as the reference indicator, the weight of the factor
loading was fixed to −1 (rather than the traditional +1), in order to keep the latent
variable as a positive measure of body image. Residuals did not covary within this latent
factor, but the residuals of the regulations (external, introjected, identified,
intrinsic) were allowed to covary. BMI and participants’ METs score from the LTEQ were
included as covariates, by modeling these as covariates of goals and directly associated
with regulations and body image. This model had very good overall fit indices, with CFI
above .95, RMSEA below .08 and SRMR below .06 (χ2 = 28.60, df = 16, p = .03; CFI = .99,
RMSEA = .06, SRMR = .03; Fig. 1); the local fit of the model was also good with
standardized residual covariances suggesting that no relationships in the data were poorly
represented by the model (all <2). Thus, no additional paths were inserted. Given the
focus of the research on appearance goals specifically, analysis of this model is focused
on the associations, both direct and indirect, between appearance goals for exercise and
body image.2 Appearance goals were strongly associated with introjected regulation and
more weakly with external regulation. There was also a significant but small link between
appearance goals and identified regulation. Introjected regulation was negatively
associated with body image, whereas intrinsic regulation showed a positive association.
External regulation was marginally negatively associated with body image (p = .09).
Bootstrapping with 2000 samples was used to assess whether the associations between
appearance goals for exercise and body image were due in part to their shared association
with regulations. Appearance goals had a strong negative direct association with body
image, but also a significant indirect association via introjected regulation (β = −.14,
SE = .05, p = .003, 95% bias-corrected CI [−.05, −.23]). The other three indirect pathways
(via external, identified, and intrinsic regulation) were non-significant (ps > .05, 95%
bias-corrected CIs across zero). The link between appearance goals and body image is
therefore partially due to their shared association with introjected regulation.

<hs>  Brief discussion</hs>
  ~~~~~~~~~~~~~~~~

These findings provide novel correlational evidence for the shared variance between
appearance goals for exercise, introjected regulation, and body image, and suggest that
introjected regulation may be a key link between appearance goals for exercise and body
image. The individual importance of introjected regulation for exercise as an associate of
body image has been highlighted previously (e.g., Brunet et al., 2012; Thøgersen-Ntoumani,
& Ntoumanis, 2007); however, previous research has not identified this type of
regulation’s potential importance in linking appearance goals for exercise to body image.
These findings provide a framework within which to place previous research relating
appearance and health reasons for exercise to body image (Furnham et al., 2002; Strelan et
al., 2003; Tiggemann & Williamson, 2000), by considering these as domain-specific
extrinsic and intrinsic goals, which are differentially associated with the regulation of
exercise behavior and, in turn, body image. These findings, linking appearance goals for
exercise, introjected regulation, and body image, provide necessary information for a more
causal test of the links between appearance goals and body image. From this cross-
sectional work, it is not possible to draw conclusions about the direction of this effect
or to truly identify it as a case of mediation (Bullock et al., 2010). For this, we must
experimentally manipulate both our proposed independent variable (appearance goals) and
the proposed mediator (introjected regulation) to establish causation.

<h>STUDY 2</h>
-------

The initial cross-sectional study suggests that introjected regulation shares considerable
variance with both appearance goals for exercise and body image. In our second study, to
test the causal links between these variables, appearance vs. health frames for exercise
were manipulated at the same time as inducing guilt vs. no guilt regarding exercise
behavior, using a magazine article style of manipulation, as successfully used in previous
research (Aubrey, 2010). It was hypothesized that participants in both of the guilt
conditions (health and guilt; appearance and guilt) would experience more post-test guilt
than participants in the no guilt conditions, but that post-test guilt would not be
influenced by the appearance vs. health manipulation. Furthermore, for the proposed
mediation to hold, the guilt manipulation should affect participants’ post-test body
anxiety, whereas the appearance vs. health manipulation should not. That is, appearance
reasons for exercise should only be problematic when paired with the guilt manipulation,
if this is indeed the mediator in this case. By experimentally manipulating the proposed
mediator in addition to the independent variable, this study offers a strong test of
introjected regulation (guilt-based exercise motivation) as the underlying mechanism
through which appearance goals influence body image. In establishing this effect of the
guilt manipulation, there is the challenge of individual variation in responses to it:
among those in the guilt condition, there is likely to be variation in how susceptible
participants are to the manipulation, with some participants feeling guiltier than others
as a result. As such, it would be plausible to predict a treatment–mediation interaction
effect (Valeri & Vanderweele, 2013), with the guilt manipulation predicting increases in
post-test guilt and this, in turn, predicting body anxiety, but only among those in the
guilt condition. In other words, the impacts of a guilt manipulation on body anxiety can
be expected to the extent that the manipulation succeeds in inducing guilt.

        <hss>Participants and design</hss>

        One hundred and sixty-five female university students (aged 18–27 years, M =
        19.44, SD = 1.40) were randomly assigned to a 2 (appearance vs. health frame) × 2
        (no guilt vs. guilt) between-subjects design. Participants were recruited through
        a university participation pool. Participants were predominantly white (77.7%),
        and within the ‘normal’ range for BMI (75% between 18.5 and 25, M = 21.31, SD =
        3.59). Ethical approval for the experiment was granted by the ethics committee of
        the University, and the research process met APA and BPS ethical standards.

        <hss>Procedure</hss>

        Participants attended group testing sessions, which ranged in size from 1 to 10
        participants and took between 20 and 35 min to complete. After reading the
        information sheet and providing informed consent, participants worked through the
        pack at their own pace. Participants were informed that the study related to
        magazine preferences and requested that they read the article carefully.

            <hss>Appearance vs. health manipulation</hss>

            All participants were given a passage of text reportedly written by ‘Helen’,
            another student at the university. The passage outlined three tips for fitting
            exercise into a busy schedule. In the “appearance” conditions, the appearance
            and weight-related benefits of these tips were highlighted, such as toning and
            calorie burning, whereas in the “health” conditions, the health benefits of
            these tips were highlighted, such as cardiovascular health and injury
            prevention. Providing exercise advice with either a health or appearance focus
            is an effective means of priming health or appearance reasons for exercise
            respectively (Aubrey, 2010). The texts were closely matched in length and
            sentence construction, to ensure that the only substantive difference was the
            framing of the advice.

            <hss>Guilt manipulation</hss>

            The final paragraph of the text differed by guilt condition. In both
            conditions, the author acknowledged that she did not always do as much
            exercise as she would like to. In the ‘no guilt’ condition, this was followed
            by a self-compassionate statement about not feeling guilty for not doing
            enough. In the ‘guilt’ condition, this statement was adapted to focus on
            experiencing guilt for not doing enough, by rephrasing key statements to a
            more self-critical approach to missing a workout.3 Participants were asked to
            reread the final paragraph and to imagine they were the author. Participants
            then listed five reasons why they might feel as described in this paragraph.
            Measures of guilt often use responses to scenarios to assess this emotion (see
            Robins, Noftle, & Tracy, 2007, for a full review), and thus this was
            considered an appropriate technique with which to manipulate guilt. The
            majority of participants provided 5 reasons (84.3%), with only 4 participants
            providing 2 or fewer.

                <hss>Questions on the article</hss>

                Participants were asked to describe the material to confirm they had read
                the article; all participants accurately described the content. They also
                were asked how similar they thought the author was to them and how
                likeable the author was (rated on a 5-point Likert scale, not at all to
                extremely). There were no significant main effects or interactions on
                perceptions of author likeability and similarity to participants
                (appearance vs. health, guilt vs. no guilt, appearance × guilt; all ps >
                .05; descriptive statistics in Table 2). Participants were also asked how
                health- and appearance-focused they thought the author was, as a
                manipulation check (see Results for full details).

                <hss>Post-test guilt and negative emotion</hss>

                Post-test guilt was assessed using a short form of the Positive and
                Negative Affect Scale (I-PANAS-SF, Thompson, 2007), with one additional
                item (guilty) included. This item was included as a manipulation check for
                the guilt conditions. Participants were asked to what extent they were
                experiencing each of 11 mood adjectives right now and responded on a
                7-point Likert scale (not at all to very much). In addition to guilt, the
                mean of five other negative emotion terms (hostile, upset, nervous,
                afraid, ashamed) was used to control for a general negative response to
                the article (α = .79). This scale occurred only after the manipulation had
                taken place; there was no pre-test of guilt or other emotions. This was a
                purposeful decision on the part of the research team, to avoid multiple
                questions relating to guilt sensitizing participants to this emotion and
                altering their response to the guilt manipulation, a potential pre-test-
                treatment interaction effect (Shadish, Cook, & Campbell, 2001). Demand
                characteristics and other manipulation effects may be particularly
                relevant in the body image domain, where many findings are well-known in
                popular culture (e.g., the effects of thin ideal media or focusing on
                appearance) and demand characteristics have been shown to influence repeat
                measurements (e.g., Fingeret, Gleaves, & Pearson, 2004; Krawczyk, Menzel,
                & Thompson, 2014). The risk of heightening sensitivity to guilt was also
                noted in the development of our materials in a pilot study (N = 50): our
                first guilt-inducing Helen was too obvious in her attempts to manipulate
                participants’ guilt. Participants in this condition did not feel guilty,
                and instead disliked the author significantly more than the other
                conditions.

                <hss>Body anxiety (state)</hss>

                The Physical Appearance State Trait Anxiety Scale (PASTAS, Reed et al.,
                1991) was used to measure body anxiety. Participants were asked how
                anxious they were about a range of elements of their lives right now and
                responded on a 5-point Likert scale (not at all anxious to very anxious).
                Embedded within the 20-item scale were 7 items relating to appearance
                issues, such as “my size”, and “the extent to which I look overweight”.
                These 7 items demonstrated excellent reliability (α = .85).

                <hss>Regulation of exercise behavior (state)</hss>

                An adapted, shortened version4 of the Behavioural Regulation of Exercise
                Questionnaire 2 (BREQ-2, Markland & Tobin, 2004) was used to measure
                participants’ immediate motivation for exercise. The introductory text was
                rephrased to ask participants to consider why they would be exercising
                today if they did so, to attain a ‘state’ measure. We used the introjected
                regulation subscale in our analyses (e.g., “I would be exercising today
                because I feel guilty when I don’t exercise”; α = .85).

                <hss>Demographic information, BMI, and demand characteristics</hss>

                Participants reported their age, ethnicity, height, and weight. Height and
                weight were used to calculate body mass index (available for 150
                participants). Participants were asked what they thought the study was
                investigating. No participants recognized that they had experienced a
                guilt manipulation.

            <hss>Trait measures</hss>

            Two weeks after the experimental session, participants were emailed a link to
            an online survey and provided their trait measures via this portal (n = 130),
            in order to control for these in later analyses if necessary. As the effects
            of the exposure manipulation (a 660-word piece of text) were expected to be
            relatively short-lived, it was considered appropriate to use a two-week
            follow-up questionnaire to collect trait data, especially as previous research
            within an exposure paradigm (e.g., Ashikali, Dittmar, & Ayers, 2014) has
            included trait measures after the exposure and post-test state measures.
            Participants completed trait measures of body anxiety, goals for exercise, and
            introjected regulation. For body anxiety, participants completed the PASTAS
            (Reed et al., 1991) a second time, but this time were asked how anxious they
            were about a range of elements of their lives in general. The measure once
            more demonstrated high reliability (α = .92). A 15-item form of the Goal
            Content for Exercise Questionnaire (GCEQ, Sebire, Standage, & Vansteenkiste,
            2008) was used to measure participants’ appearance and health goals for
            exercise, with three items for each goal (αs = .85 and .82, respectively).
            Participants rated to what extent various goals for exercise were important to
            them on a 5-point Likert scale (not at all important to very important). The
            shortened BREQ-2 (Markland & Tobin, 2004) was used to assess participants’
            trait introjected regulation of exercise behavior (α = .84).

            <hss>Missing data</hss>

            There was no missing data on the post-test measures of body anxiety or guilt.
            The post-test measure of negative emotions comprised five items and on three
            of these there was missing data for one (but each different) respondent and
            these were replaced by mean substitution to provide complete data. For the
            pre-test measure of trait body anxiety, however, there was missing data on
            just under 10% of cases (16 out of N = 165). For the mediation analyses, this
            was handled using Full Information Maximum Likelihood (Enders, 2010); for the
            ANCOVA, we imputed missing values using the EM algorithm in SPSS.

            <hss>Manipulation checks and overall effects of manipulations</hss>

            Manipulation checks were conducted using a 2 × 2 analysis of variance (ANOVA).
            Tests for the overall effects of the manipulations (appearance vs. health
            frame; guilt vs. no guilt) were conducted using an analysis of covariance
            (ANCOVA), with any trait variables that differed significantly between the
            conditions included as covariates. These analyses were conducted in SPSS
            (version 23).

            <hss>Mediation analysis</hss>

            As the manipulation was expected to influence post-test body anxiety due to
            its effect on post-test guilt, this assumption was tested via a structural
            equation model. However, mediation is complicated in a situation where the
            treatment or experimental condition may interact with the mediator itself
            (Muthén & Asparouhov, 2015; Valeri & Vanderweele, 2013), as may be the case in
            this design: post-test guilt does not represent the same type of guilt in each
            condition, and may therefore have a different effect on the outcome of body
            anxiety. ‘Guilty’ participants in the guilt condition should theoretically be
            feeling this way due to the manipulation; their guilt should be specifically
            associated with not exercising enough. In contrast, variation in the guilt
            ratings of participants in the no guilt condition will not necessarily be
            associated with guilt regarding exercise (which this condition specifically
            aims to reduce), but rather should represent other, general, sources of guilt.
            Thus, we would expect variation in guilt associated with not exercising,
            mostly aroused in the guilt condition, to affect post-test body anxiety, but
            variation of other kinds of guilt, most aroused in the control condition, not
            to affect post-test anxiety. Hence, we predicted a mediation by post-test
            guilt, but also a moderation by the condition of the mediator’s effect, as
            indicated by a treatment–mediator interaction effect. The counterfactual
            method detailed by Muthén and Asparouhov (2015; see also Valeri & Vanderweele,
            2013) was employed to examine this possibility, allowing the simultaneous
            consideration of the mediation and treatment–mediator interaction. Briefly
            put, this method involves the decomposition of the total effect into two
            components. In classic treatments of mediation (Baron & Kenny, 1986), where
            there is no treatment–mediator interaction, the total effect comprises a
            direct effect and an indirect effect, and comprises three path coefficients.
            The presence of an interaction, however, introduces additional coefficients
            that contribute to the total effect, and that need to be taken into account
            when defining direct and indirect effects. Thus, the total effect can be
            decomposed either into the pure natural direct effect (PNDE) and the total
            natural indirect effect (TNIE), or into the total natural direct effect (TNDE)
            and the pure natural indirect effect (PNIE: Muthén & Muthén, 2015; Valeri &
            Vanderweele, 2013). For our purposes, the first decomposition is the most
            appropriate since it is the TNIE that represents the change in the outcome
            when the condition is held constant at the treatment condition (the guilt
            condition) and the mediator changes from the level of the control (no guilt)
            to the level of the treatment condition. Thus, it includes the product of the
            interaction effect and the effect of the treatment on the mediator, and hence
            here captures the expectation that it is the guilt aroused in the treatment
            condition that has an effect, but not the guilt found in the control
            condition. The counterfactual method relies on the assumption that confounding
            variables of the mediator-outcome relationship are controlled (Valeri &
            Vanderweele, 2013). We therefore included two variables as covariates of post-
            test guilt and post-test body anxiety: trait body anxiety and post-test
            negative emotions (the mean of five negative emotions from the I-PANAS-SF).
            Thus, we conducted what MacKinnon and Pirlott (2015) refer to as a
            “comprehensive structural equation model” (p.35), which explicitly models the
            influence of known confounding variables measured in the study. We further
            tested the specificity of the mediation via post-test guilt by directly
            replacing it with post-test negative emotions in a further analysis.

<hs>  Results</hs>
  ~~~~~~~

Descriptive statistics can be seen in Table 2, by condition.

        <hss>Random assignment checks</hss>

        A series of ANOVAs were conducted to assess whether the trait levels of key
        variables were significantly different between any of the conditions. Only trait
        levels of body anxiety significantly varied between conditions; specifically,
        participants in the health conditions had higher trait levels of body anxiety than
        those in the appearance conditions, F(1, 125) = 7.19, p = .01; health conditions:
        M = 2.87, SD = 1.09; appearance conditions: M = 2.40, SD = 0.98. As such, trait
        levels of this variable were controlled for throughout the analyses. No other
        potential covariates varied significantly between conditions (age, BMI, trait
        endorsement of health or appearance goals, trait introjected regulation; all ps >
        .05).

            <hss>Health and appearance focus</hss>

            ANOVAs were conducted to establish whether the articles primed the intended
            concerns. Participants perceived the author in the appearance conditions as
            significantly more appearance-focused than the author in the health conditions
            F(1, 161) = 31.62, p < .001; health conditions: M = 3.33, SD = 0.81;
            appearance conditions: M = 4.05, SD = 0.82. The two authors were perceived as
            equally health-focused, F(1, 161) = 1.44, p = .23; health conditions: M =
            3.75, SD = 0.79; appearance conditions: M = 3.59, SD = 0.93. This suggests
            that both articles primed health concerns, rather than only the health
            condition. However, the clear perception of the appearance author as more
            appearance-focused suggests that the manipulation was successful in its main
            purpose of highlighting appearance reasons for exercise.

            <hss>Guilt inducement</hss>

            The success of the guilt manipulation was assessed with two measures: the
            immediate post-test rating of guilt and the state measure of introjected
            regulation. In the case of post-test guilt, a 2 × 2 ANOVA indicated that the
            guilt manipulation had a significant effect on participants’ immediate
            emotional reports of guilt, F(1, 161) = 13.02, p < .001; guilt conditions: M =
            2.95, SD = 1.69; no guilt conditions: M = 2.02, SD = 1.58. There was no main
            effect of appearance condition, or of the interaction between the two
            conditions (both ps > .05). In the case of introjected regulation, neither the
            guilt nor appearance manipulation had a significant effect on this outcome;
            the interaction between conditions was also non-significant (all ps > .05).

        <hss>Overall effects of manipulations on body anxiety</hss>

        A 2 × 2 ANCOVA was conducted to assess whether the guilt manipulation, the
        appearance vs. health manipulation, or the interaction between the two predicted
        post-test state body anxiety (PASTAS), using trait body anxiety as a covariate.
        There were no main effects of appearance and no interaction effect, but trait body
        anxiety had a strong effect on state scores, F(1, 160) = 330.63, p < .001.

        <hss>Post-test guilt: mediation and treatment–mediator interaction</hss>

        Mediation analyses were carried out using Mplus 7.4 (Muthén & Muthén, 1998–2015)
        using bootstrap standard errors with 1000 bootstrap samples. We first carried out
        an analysis in which post-test guilt mediated the effect of the guilt manipulation
        (the treatment) on post-test body anxiety, controlling for trait body anxiety and
        post-test negative emotions. Trait body anxiety significantly affected post-test
        body anxiety (b = .0.67, p < .001) but not post-test guilt (b = 0.12, p > .05).
        Negative post-test emotions significantly affected post-test guilt (b = 0.89, p <
        .001) and post-test body anxiety (b = 0.12, p < .05). The treatment significantly
        affected post-test guilt (b = 0.73, p < .001), but post-test guilt did not
        significantly affect post-test body anxiety (b = 0.05, p = .10) and the
        treatment–mediator interaction was also not significant (b = 0.09, p = .10). The
        results from the mediation analysis, however show that the TNIE was significant
        (see Table 3 for direct and indirect effects), indicating that there was a
        significant indirect effect of experimental condition, via post-test guilt, on
        post-test body anxiety, but only for those in the guilt condition. Women in the no
        guilt condition did not demonstrate this mediation effect (PNIE was non-
        significant), and no other effects in the mediation analysis were significant.
        When post-test guilt was replaced in the analysis by post-test negative emotions
        as the mediating variable, TNIE was not significant and there were no other
        significant effects in the mediation analysis, suggesting the critical role of
        guilt rather than negative emotion more generally. It seems, then, that the guilt
        manipulation had an effect on post-test body anxiety via the particular kind of
        guilt that it aroused (which we assume to be guilt about lack of exercise), guilt
        that was not aroused in the control condition.

<hs>  Brief discussion</hs>
  ~~~~~~~~~~~~~~~~

The total effect of the guilt condition on body anxiety was not significant and this is
due to the fact that the direct effect is negligible and not significant. The effect of
the guilt manipulation was fully mediated by the extent to which it aroused guilt; not all
women experienced guilt as a result of our manipulation, but those that did felt more
anxious about their bodies. Higher levels of post-test guilt for women in the no guilt
condition were not associated with higher levels of body anxiety. This finding suggests
that guilt related to exercise is a mechanism through which appearance goals may influence
body image. The effect of appearance vs. health framing observed by Aubrey (2010) appears
to be superseded by the guilt manipulation introduced in this experiment: appearance goal
priming was not problematic for body image when combined with the no guilt manipulation.
In further support of the importance of guilt, these findings were not replicated when
post-test guilt was replaced by post-test negative emotions more generally in our
mediation analysis; the negative link to body anxiety appears to be specific to the guilt
elicited by our manipulation. The inclusion of negative emotions beyond guilt and their
inclusion as controls and replacing guilt in the analysis is a key strength and
contribution of this study. Our findings support the importance of guilt in particular in
the relationship between appearance reasons for exercise and body anxiety and shows the
divergent validity of guilt, compared to negative affect more generally. In considering
this study’s contribution, it is important to note that the experimental materials closely
imitated the materials that women are regularly exposed to. Guilt was induced not through
an artificial cognitive task, such as scrambled sentences (e.g., Zemack-Rugar, Bettman, &
Fitzsimons, 2007), but by an active discussion of guilt by the author, an event that
regularly occurs in the real-life media exposures that women experience (e.g., ‘true life
testimonials’ in magazines). This similarity gives this experiment a much greater degree
of ecological validity than might otherwise be expected of a lab-based experiment. Aubrey
(2010) argues that this form of exposure represents a single ‘meal’ in women’s ‘media
diets’: this is only a single text endorsing appearance goals, but given the cultural
prominence of these messages, it is likely that women are exposed repeatedly to these,
experiencing these state effects on body image multiple times a day, and that over an
extended period these effects may become cumulative, altering trait levels. Future work
should consider these relationships longitudinally, to confirm the direction of the
relationship between appearance goals for exercise and body image, via introjected
regulation, in a naturalistic environment. In spite of the valuable insights from this
study, restrictions within the methodology and the results mean that they must be
interpreted with caution, particularly with respect to the mediating role of guilt in
influencing body anxiety. There was no main effect of the guilt manipulation on post-test
body anxiety, and the mediation analysis presented utilizes post-test guilt as part of the
indirect effect: the mediator (guilt) is measured at the same time (post-test) as the
proposed outcome variable (body anxiety). The study’s findings around mediation and the
guilt manipulation’s influence on body anxiety are therefore limited by their cross-
sectional nature, in spite of being situated overall within an experimental design. This
raises the possibility of either a reverse effect, whereby the manipulation increased body
anxiety, which was responsible for an increase in guilt, or of other unmeasured variables
being responsible for the association, as is the case in other cross-sectional mediation
analyses (e.g., Bullock et al., 2010). Although we included trait body anxiety and post-
test negative emotions as potential confounding variables, there is no guarantee that
there are not others at work. As such, the study does not provide as strong a test of
mediation of appearance goals’ influence on body image via guilt as intended in the
initial study design; its findings must be interpreted in this light, and supported by
further investigation. A further methodological limitation of the study was that guilt was
not measured before the manipulation. Although a deliberate decision, in order to avoid
pre-test sensitization, this design leads to two difficulties. First, the study cannot
analyze a change in guilt, and therefore must assume that random assignment to conditions
has eliminated potential variation between groups or that this is sufficiently controlled
for by the associated trait variables, such as body anxiety and introjected regulation.
Second, even if the conditions as groups had similar levels of pre-test guilt, the random
variation between participants within these conditions may act to introduce additional
uncontrolled variation which may serve to obscure the true causal relationships being
considered. This may be particularly relevant given the lack of a direct effect found and
the specific indirect effect reported: if only particular women respond to the
manipulation, pre-test measures of guilt would be vital in future research to identify who
these women are and what the consequences are for them.

<h>GENERAL DISCUSSION</h>
------------------

Across the two studies, there is initial support for the importance of guilt as a key
process through which appearance goals for exercise are associated with body image. Study
1 provides cross-sectional evidence for the shared variation in appearance goals,
introjected regulation, and body image, assessing all three within a single model, while
controlling for other regulations and goals. The experimental manipulation of these
variables within Study 2 provides support for the proposition that guilt relating to
exercise may result in increased body anxiety, in spite of the limitations discussed
previously. These findings support the theoretical proposal that regulation of exercise
behavior may mediate the association between women’s goals for exercise and their body
image, as predicted by self-determination theory (e.g., Ryan & Deci, 2006), given the
consistent association of extrinsic goals with controlled regulations (e.g., Gillison et
al., 2006; Ingledew & Markland, 2008) and of controlled regulations with worse body image
(e.g., Brunet and Sabiston, 2009; Thøgersen-Ntoumani & Ntoumanis, 2007). However, although
the results replicate the broad theoretical predictions of less self-determined regulation
being associated with lower well-being (e.g., Sheldon, Ryan, Deci, & Kasser, 2004), these
findings also raise a question for self-determination theory: the most controlled form of
regulation, external, is not most strongly associated with negative wellbeing outcomes. In
our analyses, introjected regulation emerges as the key regulatory pathway linking
appearance goals and negative body image, and future theoretical and empirical work should
seek to understand why guilt as a motivation for exercise behavior may have more negative
associations or consequences than more external pressures. Guilt is often discussed as a
positive motivator, driving us to reparatory action to fix a perceived wrong, but the
evidence presented here and the growing body of work in the body image domain (e.g.,
Brunet & Sabiston, 2009; Calogero & Pina, 2011) suggests that this may not be the case.
Guilt appears to be an important emotional response and motivational process resulting
from exposure to or endorsement of the extrinsic goal of attractiveness. That guilt
relating to exercise behavior has such negative associations for body image is an
important finding, as it may open up a new avenue of interventions, suggesting that the
negative association between appearance goals and body image could be mitigated by
decoupling these goals from the guilt associated with not exercising enough. This provides
a potential solution for researchers seeking to reduce the negative impact of appearance
goals on women’s body image, without appearing to criticize individuals’ reasons for
exercise: by introducing interventions aimed at reducing guilt-based motivation for
exercise, practitioners can potentially disrupt one of the negative pathways from
appearance goals to body image. From a public health perspective, this form of
intervention could have a double reward, reducing the associated health issues of negative
body image, but also increasing long-term exercise persistence, which has been negatively
associated with introjected regulation (Pelletier, Fortier, Vallerand, & Briere, 2001). In
addition to methodological issues relating to the individual studies, previously
discussed, the nature of the sample limits the extent to which its findings can be
generalized beyond female undergraduate students in the UK. Although there is clear
justification for selecting the particular samples of young women in the present work,
future research should focus on extending such work to other ‘at-risk’ groups, such as
young men (Pope et al., 2000). Thus, future research should investigate whether the
importance of guilt as motivation for exercise is an issue unique to women, or whether it
can be generalized to men as well. This may be particularly important given research
suggesting that young men and women experience introjected regulation differently, with
women focusing on the avoidance of guilt and men focusing on the attainment of social
status and appreciation (Gillison et al., 2009). These results set an agenda for further
work to evaluate the unfolding causal relations between appearance motivations for
exercise and body image over time. This study provides evidence of the potential
importance of guilt in linking appearance goals for exercise and body image; future
research should focus on the task of further investigating the causal nature of this
relationship, employing longitudinal research to examine this relationship over longer
periods of time and in a more naturalistic setting, alongside further experimental
manipulations to fully confirm causality.


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<ART>“Model age-based” and “copy when uncertain” biases in children's social learning of a novel task
================================================================================

Authors: Lara A. Wood, Rachel A. Harrison, Amanda J. Lucas, Nicola McGuigan, Emily R.R. Burdett, Andrew Whiten
DOI: 10.1016/j.jecp.2016.06.005
Year: 2016  |  Pages: 272-284
ASJC codes: 3204, 3205
Keywords: Exploration, Imitation, Model-based bias, Social learning, Trust, Uncertainty bias

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

Theoretical models of social learning predict that individuals can benefit from using strategies that specify when and whom to copy. Here the interaction of two social learning strategies, model age-based biased copying and copy when uncertain, was investigated. Uncertainty was created via a systematic manipulation of demonstration efficacy (completeness) and efficiency (causal relevance of some actions). The participants, 4- to 6-year-old children (N = 140), viewed both an adult model and a child model, each of whom used a different tool on a novel task. They did so in a complete condition, a near-complete condition, a partial demonstration condition, or a no-demonstration condition. Half of the demonstrations in each condition incorporated causally irrelevant actions by the models. Social transmission was assessed by first responses but also through children's continued fidelity, the hallmark of social traditions. Results revealed a bias to copy the child model both on first response and in continued interactions. Demonstration efficacy and efficiency did not affect choice of model at first response but did influence solution exploration across trials, with demonstrations containing causally irrelevant actions decreasing exploration of alternative methods. These results imply that uncertain environments can result in canalized social learning from specific classes of model.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

The social learning of behavior, including tool use, language, and cultural norms, is a
fundamental aspect of a child’s development. However, social information can be outdated
or inappropriate. Thus, children do not socially learn indiscriminately; rather, they
implement cognitive decision-making rules and social learning strategies (Boyd &
Richerson, 1985; Laland, 2004; Rendell et al., 2011). These biases toward certain
information or people dictate who young children copy and under what circumstances (Price,
Wood, & Whiten, in press; Wood, Kendal, & Flynn, 2013b). Such social learning strategies
have the potential to facilitate the creation of social traditions and the evolution of
cumulative culture (Dean, Vale, Laland, Flynn, & Kendal, 2014) where cultural traits are
modified over multiple generations, resulting in an increase in the complexity and
efficiency of these traits. Accordingly, understanding children’s selective learning can
contribute to our knowledge of uniquely human cultural abilities. The investigation of
children’s social learning strategies can be achieved through differing experimental
paradigms that measure (a) copying choices regarding personal preferences (e.g., Shutts,
Kinzler, McKee, & Spelke, 2009), (b) novel object labeling (e.g., Koenig & Harris, 2005),
and (c) novel object use (e.g., Wood, Kendal, & Flynn, 2013a). Such empirical methods are
used in conjunction with theoretical models predicting that the implementation of social
learning strategies dependent on the context of the to-be-learned behavior is advantageous
(Laland, 2004). Emerging empirical evidence also suggests that children’s social learning
is often too complex to be explained by a single strategy and that strategies may be most
beneficial when they can be used flexibly in different contexts.

<hs>  “Copy when uncertain” biases</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A copy when uncertain bias is one social learning strategy dictating when individuals copy
others (Rendell et al., 2011). Such a bias has been found in other animal species,
including rats (Galef, 2009) and fish (van Bergen, Coolen, & Laland, 2004). The
uncertainty in these paradigms may relate to (a) observers’ uncertainty regarding their
environment and (b) whether they should use social versus personal information. However,
their uncertainty can also relate to (c) the efficacy and efficiency of social information
and (d) which of multiple sources of information, or “who,” they should best copy. The
different paradigms used to investigate children’s strategies represent different
environments of uncertainty relating to efficacy and efficiency. Novel object labeling
paradigms involve two or more models labeling a novel object in divergent ways, but the
efficacy of either label remains unknown throughout the paradigm. Novel object use
paradigms, such as using a tool to extract a reward from a novel container, differ from
such word labeling paradigms in that the efficacy of the model(s) is often made evident by
the completion of the task. These differing contexts of uncertainty influence who gets
copied; when model efficacy is uncertain, as when children are presented with a novel
object labeled differently by two models, 3- and 4-year-old children use a label provided
by a previously proficient word labeler over a previously inept word labeler (Koenig,
Clément, & Harris, 2004). Conversely, when efficacy is known, as when children are
presented with a novel puzzle that is successfully solved differently by one previously
proficient solver and one previously less proficient solver, 5-year-old children do not
show an initial preference for either model’s method and are motivated to try both methods
over time (Wood, Kendal, & Flynn, 2015). Wood, Kendal, and Flynn (2015) argued that
because the children were certain about the effectiveness of each method, they did not
show any model-based bias to either peer. Similarly, Hu, Buchsbaum, Griffiths, and Xu
(2013) found that a bias to follow a majority of others was present only when 3- to
5-year-old children did not know whether the socially demonstrated responses were
effective. If children could see that all socially demonstrated responses were effective,
the bias was lost. Thus, task-naive children may implement a model-based bias only when
there is some uncertainty as to the efficacy of the social information the models are
providing. Another form of social information uncertainty corresponds to the efficiency of
the social information. Models may produce a plethora of behaviors toward a novel task,
and understanding which of those actions are necessary or unnecessary for completing a
goal with the object may prove to be important. Likewise, models who perform numerous
unnecessary actions may be viewed and copied differently than those who do not. In the
domain of social learning research, such causally unnecessary actions have been labeled
“irrelevant actions,” and the copying of such actions is commonplace among children and
adults (McGuigan, Makinson, & Whiten, 2011). This copying is intriguing and has been
argued to enable the development of unique aspects of human culture such as complex
cultural practices (Boyd & Richerson, 1996). Although 3- to 5-year-old children often
faithfully reproduce such actions, they may nevertheless identify them as “silly” (Wood et
al., 2013a) and unnecessary (Lyons, Damrosch, Lin, Macris, & Keil, 2011) and omit them if
produced by certain models such as children (Wood, Kendal, & Flynn, 2012). Therefore,
there is good reason to think that irrelevant actions might add some ambiguity to the
social learning context and children’s perception of model efficiency. A major aim of the
current study was to discover whether similar-aged children’s use of a social learning
strategy would be affected by the observer’s degree of uncertainty by manipulating the
effectiveness and efficiency of the social information provided. The social learning
strategy we investigated was a model age-based bias.

<hs>  “Model age-based” biases</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~

There has been a wave of research demonstrating that young (2- to 6-year-old) children
apply model-based social learning strategies (Henrich & McElreath, 2003), where there is
selective copying dependent on the identity of the model providing the information (Birch,
Vauthier, & Bloom, 2008; Corriveau & Harris, 2009a, 2009b; Corriveau et al., 2009; Koenig
& Harris, 2005; Lane, Wellman, & Gelman, 2013; McGuigan, 2013; Zmyj, Buttelmann,
Carpenter, & Daum, 2010). We chose to investigate a bias for model age because it has been
shown to be salient in a number of contexts (Brody & Stoneman, 1981; Jaswal & Neely, 2006;
Ryalls, Gul, & Ryalls, 2000; Seehagen & Herbert, 2011; Zmyj, Aschersleben, Prinz, & Daum,
2012), although not always in the same direction. “Vertical” or “oblique”
intergenerational transmission where adults are copied rather than children, has been
found with videotaped target acts (Seehagen & Herbert, 2011), and novel object labeling
(Jaswal & Neely, 2006). Conversely, infants have shown higher fidelity copying of a
3-year-old child versus an adult (Ryalls et al., 2000) and of peers in preference to older
children and adults (Zmyj et al., 2012) when the context was play (but see Rakoczy,
Hamann, Warneken, & Tomasello, 2010, for children protesting over a puppet that copies a
child over an adult). Similarly, 3- to 5-year-olds selected an adult as a model when
answering questions within an adult domain, such as the nutritional value of food, but
deferred to a child model when the domain was toys (VanderBorght & Jaswal, 2009).

<hs>  Establishing traditions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Social learning can be assessed by children’s first responses to a novel object, but
sustained social learning, the hallmark of social traditions, measured through continued
interaction with that object can give a more detailed picture of social transmission. Wood
et al. (2013a) found that 5-year-olds who were previously naive to a puzzle box that could
be operated by two different methods became canalized to using just one demonstrated
method significantly more than children who had previously explored the box and
successfully innovated solutions. Likewise, the presentation of social information before
interaction with an object can canalize interactions and limit exploratory play in 4-year-
olds (Bonawitz et al., 2011). These results suggest that a copy when uncertain strategy
could inhibit innovation and lead to a canalized social tradition. The current study aimed
to investigate whether this canalization would happen in relation to a model age-based
bias; would uncertainty increase conservatism toward a particular model?

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

In this study, we set out to extend our knowledge of 4- to 6-year-old children’s flexible
use of social learning strategies by manipulating observer certainty in the efficacy and
efficiency of differently aged models. The study employed a puzzle box, the “Slotbox,”
which was designed so that each of two functionally different tools could be used to
extract a soft toy. Given mixed findings regarding the direction of model biases for age,
we did not make a prediction in this respect. Rather, we aimed to explore the effects of
uncertainty on such a bias occurring in either direction. Uncertainty about the efficacy
of the social information was created by varying the completeness of the demonstrations
such that whereas some children saw both models complete all of the necessary series of
actions involved and have a token extracted, others saw a degraded, less complete series
of these actions that did not reveal eventual successful removal of the token from a
puzzle box task. Uncertainty about the efficiency of the social information was created by
varying whether models incorporated visibly causally irrelevant, and thus inefficient,
actions into their demonstrations. A final group of children did not witness any social
information. We investigated children’s success with a solution method and conservatism to
this solution over five response trials. We predicted, first, that children who received
social information as compared with the control group would socially learn as indicated by
increased success, but that a degraded (vs. full) demonstration would reduce success as
measured by latency to success. Second, any model bias would be most pronounced when
social information lacked evidence of efficacy and efficiency because the demonstrations
would create the most uncertainty. Third, once children have achieved a successful
solution, conservatism to this solution would be greatest when they are uncertain of the
alternative method. Thus, children who witness two complete and efficient solutions would
be predicted to be motivated to explore both demonstrated methods, whereas those with the
least complete and inefficient demonstration would be predicted to show more canalization
to a particular method.

<hs>  Participants</hs>
  ~~~~~~~~~~~~

In total, 151 4- to 6-year-old children completed the study. Of these, 11 children were
excluded from analysis (English not first language [n = 2], technical problems during
experiment [n = 6], or assistance offered by caregiver [n = 3]). The remaining 140
children (86 girls) ranged from 4 years (48 months) to 6 years (83 months) of age (M =
64.1 months, SD = 9.9). Children were recruited while visiting Edinburgh Zoo through a
poster that read, “Win stickers. We are interested in children’s learning and would like
to see how you play with toys we have made.” Another poster showed a picture of the
Slotbox with “Our toy” written above it. Consent for participation was obtained from
children’s caregivers provided that they were parents or grandparents. There was no
significant difference in the distribution of boys and girls, χ2(6, N = 140) = 0.30, p >
.99, across the seven conditions. There was some difference in the distribution of age,
F(6, 133) = 2.49, p < .05, across these conditions, but post hoc pairwise comparisons
failed to reveal any statistically significant differences (ps > .05).

<hs>  Design</hs>
  ~~~~~~

Within each condition, there was a within-group variable of model age (adult or child),
with each model demonstrating one of two different methods for reward retrieval (arrow or
rake, counterbalanced and explained further below) sequentially (order of model
demonstration was counterbalanced). There were two between-participant variables: (a)
demonstration efficacy shown through completeness (three levels: complete, near-complete,
or partial) and (b) demonstration efficiency shown through irrelevant actions (two levels:
present or absent). Table 1 summarizes the seven six experimental conditions. There was an
additional “no-demonstration” control condition that offered no demonstration of any kind;
here each model was paired only with a photograph of one of the two tools.

<hs>  Materials</hs>
  ~~~~~~~~~

Video recordings of the models’ actions were embedded in PowerPoint presentations shown on
two 19-inch monitors on either end of a table facing the child participant. Children were
tested in a pop-up gazebo within an indoor area of Edinburgh Zoo. Fig. 1 depicts the
location of the apparatus within the gazebo. The monitors were each attached to computers
out of the child’s view. In the middle of the table lay the Slotbox with the rake and
arrow tools. The Slotbox is a largely transparent plastic puzzle box (length = 25 cm,
width = 8 cm, maximum height = 14 cm, minimum height = 7 cm) that contained a small soft
toy token (a gibbon: height = 10 cm). This token was put in the box through a hole in the
top (Fig. 2A) to rest at the back of the box (Fig. 2B). There were two other openings to
the box: one at the front (height = 5 cm, width = 6 cm), which was covered by a top-hinged
door (with crossbar height = 2 cm, width = 8 cm) that could be lifted up, and a slit
(height = 0.5 cm, length = 23 cm) along the side of the box. To the right of the Slotbox
on the table were two tools: the rake and the arrow. The rake tool was a long rectangular
piece of brown opaque plastic (width = 4 cm, length = 25 cm, diameter = 0.2 cm) with three
prongs at the end. The arrow tool was a narrow-shaped piece of black plastic (width of
arrow base = 10 cm, width of handle = 4 cm, length = 15 cm, diameter = 0.2 cm).
Critically, these tools provided two different ways to extract the token. Either the rake
could be inserted through the front opening and used to pull the token out of the front
opening (Fig. 2C) or, alternatively, the arrow tool could be inserted into the side slit
of the box and used to push the token out of the front opening. In addition, a hollow tin
with a lid (height = 15 cm, diameter = 10 cm) was used in a warm-up task as well as 2-cm
stickers used for rewards.

<hs>  Models and demonstrations</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~

Three female adults and three female children acted as the models in different videos, so
that biases would not be due to characteristics, beyond age, of individual models. These
adult and child models were paired for presentations in each of the nine possible
combinations. The three adult models were aged 20 to 22 years, and the three child models
were aged 4 to 6 years. All models were unfamiliar to the participants and were recorded
first looking at the camera and waving. Initially, an attempt was made to train the child
models to perform the demonstration. However, these demonstrations differed significantly
from the adult demonstrations in terms of duration, precision, and clarity. Although this
may reflect a naturally occurring difference in competence, it was important to avoid
confounding an age bias with a competence bias. Thus, as in Wood et al. (2012), the video
demonstrations focused on the task, showing just the model’s hands and unclothed arms, and
were performed by adults. The “child” demonstration was modeled by a 20-year-old who had
small, child-like hands, and the adult demonstration was modeled by a 21-year-old who had
average-sized hands, with only the hands and lower arms being visible in the video
presentations. No hands had jewelry, nail varnish, or overtly manicured nails. Copies of
these video demonstrations are available in the online Supplementary material. In Wood et
al. (2012), 20 adults, blind to the study, did not notice that adult and child
demonstrations were both performed by adults. In the current study, no child said that the
demonstrations were not performed by the model.

<hs>  Procedure</hs>
  ~~~~~~~~~

The research assistant greeted each interested child and caregiver, saying to the child,
“Would you like to play a game with some toys and see if you can win some stickers?” The
interested party was shown into the gazebo and introduced to the experimenter (E), who was
sitting behind the table with the Slotbox (see Fig. 1). The research assistant stood with
the parent at the entranceway to the tent. Photos of the child and the adult models were
displayed, one on each monitor. E said, “All of our games today involve getting the Gibbon
out of things. It is my turn first.” The experimenter used a simple warm-up task to help
explain that when the child gets the token out, the child is rewarded with a sticker. E
placed the token in a tin and closed the lid, reopened the lid, and took the token out,
saying, “That’s a sticker for me.” She then placed the token back into the tin, closed the
lid, and put the tin down on the child’s side of the table, saying, “Now it’s your turn.”
Once the child removed the token from the tin, E said, “Well done, that’s a sticker for
you. Let’s start you a pile.” Next, E placed the token into the Slotbox in sight of the
child via the hole in the top of the box, saying, “Now we put him in here, and before we
start I would like to introduce you to two of my friends. Here is my friend Tina [E points
to the first monitor]. Tina is an adult. Can you see her waving?” As this was said, E
played a 5-s clip of the model smiling and waving. The same was then done with the second
monitor, “Here we have my friend Sophie [E points to the second monitor]. Sophie is a
child, the same age as you. Can you see her waving?” Declaring that the child model was
“the same age” was done to avoid children assuming that the model was either older or
younger. Model introduction order (first or second) and monitor position (left or right)
were counterbalanced. Two monitors were used so that there would be a clear distinction
between the two models and the two tools. The following content was dependent on the
experimental condition. Children in the no-demonstration condition were told, “Tina and
Sophie both played with this, and now it’s your turn and you can do anything you like.”
All other children were told, “Tina and Sophie both played with this, and we are going to
watch what they did. Let’s watch what Tina, the adult [same order as they were
introduced], did when she played with the toy.” E then played the video clip twice. Half
of the children saw clips in which both of the models performed irrelevant actions. For
the rake tool, the irrelevant action was to tap the rake end at the front opening of the
slot box four times. For the arrow tool, the flat surface of the tool was slid down the
back of the box four times. These actions were performed after the token was inserted and
before the relevant action. E then said, “So that is what Tina the adult did. Now let’s
watch what Sophie, the child, did when she played with the toy.” E then played the child
clip twice on the other monitor. The end of both clips showed a picture of the model
paired with a picture of the tool for the remainder of the experiment. Video clip duration
ranged from 12 to 22 s depending on content. The two video clips shown to the same child
(one from the adult and one from the child) never differed by more than 4 s. E recapped by
saying, “Now, do you remember that Tina used this tool and Sophie used this tool [E points
to appropriate monitors and tools]? Well, now it’s your turn and you can do anything you
like.” The participant was given up to 3 min to interact with the Slotbox. There were a
number of set prompts in place if 60 s had elapsed and the child had (a) not yet touched
any part of the apparatus (“Can you pick up a tool?”), (b) picked up a tool but not made
contact with the Slotbox (“Can you play with the toy?”), or (c) moved the token to the
front of the task but not opened door (“You can open the door”). If 2 min had passed and
there was no success, the child was asked, “Can you get the toy out?” If the child had not
touched the box after 3 min or if there was no success after 4 min, the child was told
that he or she had done very well and the experiment ended. If the child was successful, E
said, “Well done, that’s a sticker for your pile. It’s your turn again. You can do
whatever you like.” E took a sticker from a pile and added it to the child’s pile and put
the token back in the Slotbox. The child was allowed up to five successes. All children
were rewarded with six stickers irrespective of success.

<hs>  Coding and analysis</hs>
  ~~~~~~~~~~~~~~~~~~~

The second author (R.A.H.) coded 100% of the sample. A research assistant, blind to the
study’s aims, coded 60 participants (43%) by watching each video from the moment the
experimenter first said, “Now it’s your turn and you can do anything you like.” Each
participant’s interaction was coded for successful retrieval of the token (yes or no) and
method of success (child demonstrated, adult demonstrated, or alternative) on each of the
five trials as well as latency to first success (from “Now it’s your turn and you can do
anything you like” to full extraction of the token). There was almost perfect agreement
(Viera & Garrett, 2005) on all nominal variables (kappa scores > .97). Latency to first
success had a moderate intraclass correlation of .54 (p < .003). For within-participant
first response and comparisons with the control group, non-parametric tests were used and
were two-tailed. Between-participants effects were analyzed using multiple regressions.

<hs>  Levels of success</hs>
  ~~~~~~~~~~~~~~~~~

Of the 140 children, 122 (87%) were successful at retrieving the token within 3 min. Of
these, 60 used the arrow tool and 54 used the rake tool (see below for the other 8),
indicating no bias toward either tool (p = .64, binomial test). Children who saw a
demonstration were significantly more likely to obtain the token than children who did not
(p < .001, Fisher’s exact test [FET]); fully 116 of 120 children from experimental
conditions were successful, whereas 6 of 20 no-demonstration children were successful.
From the no-demonstration condition, 1 child used the arrow tool paired with the adult
model for five response trials, and the other 5 children put their hand in the front
opening and pulled the token out. Thus, they did not use a tool. Only 3 (2.5%) of the
other 116 successful children in demonstration conditions initially used their hands
rather than a tool to obtain the token; thus, they were significantly less likely to use
their hands on the first trial (p < .001, FET). These 3 children also used demonstrated
tool methods in their other response trials. No children from the no-demonstration
condition spontaneously produced one of the two irrelevant actions. Because the no-
demonstration group had only 1 child who was successful with a tool, this group was
removed from subsequent analysis, as were the four unsuccessful children. The 3 children
who were successful with hands were excluded from first trial analysis. Latency to first
success (in seconds) for those who used either demonstrated method was entered into a
linear regression with the same predictor variables. Here the prediction model was
statistically significant, F(4, 108) = 7.52, p < .001, and accounted for approximately 22%
of the variance of latency to success. Table 2 shows a summary of the predictor variables.
Latency to first success was predicted by participant age and demonstration completeness.
Older children, and those who saw a more complete demonstration, were more likely to be
faster to success. Efficiency and participant sex were not significant predictors.

<hs>  Model age-based bias</hs>
  ~~~~~~~~~~~~~~~~~~~~

The 113 children who were successful with a tool were more likely to use the tool
demonstrated by the child model (n = 75, 66%) than the tool demonstrated by the adult
model (n = 38, 34%) (p < .001, binomial test) in their first trial. Of the 116 successful
children, 114 completed five trials. Across the five trials, the child method was used
more often (median = 3, interquartile range [IQR] = 1.5) than the adult method (median =
2, IQR = 2), n = 114, Wilcoxon Z = –2.53, p < .05. Five children used both methods
simultaneously at some point, all of them after they had used each of the two methods
separately.

<hs>  Irrelevant action reproduction</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Although irrelevant action demonstration from the model was a major focus of the current
study, irrelevant action reproduction of the participants was not. Thus, here we give a
concise description of children’s behavior following demonstrations of irrelevant actions.
No children from the no-irrelevant-action conditions produced an irrelevant action,
whereas 37 of 60 children (62%) who watched irrelevant actions from both models produced
an irrelevant action of some sort on their first trial. Of these, 4 used a hybrid (e.g.,
tool of the adult, action of the child), 21 performed the irrelevant actions modeled by
the child, and 12 performed those modeled by the adult, which was not a difference
(binomial p = .163).

<hs>  Efficacy and efficiency</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~

Fig. 3 shows a summary of each child’s first solution method. A logistic regression was
run with model copied (adult or child) entered as the dependent variable and demonstration
efficacy (completeness), demonstration efficiency (irrelevant actions), and participant
sex and age entered as predictor variables. A test of the full model against a constant-
only model was not statistically significant, indicating that the predictors did not
reliably distinguish between those who used the child model and those who used the adult
model, χ2(4, N = 113) = 3.25, p = 51. None of the independent variables were significant
predictors.

<hs>  Conservatism</hs>
  ~~~~~~~~~~~~

The final analysis investigated children’s conservatism to an initial solution. There were
an unanticipated 11 children who used their hands to remove the token on at least one
trial (including 3 children who did this on their first trial). These 11 children and the
4 who were initially unsuccessful were removed, leaving a total of 105 children (see Fig.
4). A logistic regression was run with method conservatism (yes or no) entered as the
dependent variable and efficacy, efficiency, model choice on first trial, and participant
sex and age entered as predictor variables. A test of the full model against a constant-
only model was statistically significant, indicating that the predictors as a set reliably
distinguished between children who copied just one model and children who copied both
models (see Table 3). Efficacy, participant sex, and first method were not significant
predictors. Age was a significant predictor, with increasing age predicting decreased
likelihood of conservatism. Efficiency was a significant predictor, with inefficient
demonstrations increasing the likelihood of conservatism. Whereas only 29 of 57 children
(51%) who saw an irrelevant action displayed both methods, 45 of 59 children (76%) who did
not see an irrelevant action showed both methods (p < .01, FET).

<h>DISCUSSION</h>
----------

We tested for a model age-based bias in differing contexts by examining children’s first
solution choice and also their conservatism in relation to this first solution over five
response trials. Our first prediction that children would socially learn from the
information provided was supported; children with no demonstration were generally
unsuccessful. Context had some effect; demonstration completeness significantly predicted
latency to success, with children in the partial condition taking longer to solve the task
than children who received more complete information. This would indicate that these
children found retrieving the token to be harder yet possible, even with limited
information within the demonstrations. We did not make a specific prediction regarding the
direction of model biases for age. Our results showed that children tended to
preferentially copy the child model both on their first response trial and over time. The
use of similar two-action reward retrieval tasks has elicited some variant biases in
previous studies; when similar-aged children were shown either an adult or a child
demonstrating relevant and irrelevant actions, they were more faithful in their copying of
the adult (McGuigan et al., 2011; Wood et al., 2012). However, a bias toward copying peer
models has been found when the context was less goal directed and more overtly playful
(Ryalls et al., 2000; Zmyj et al., 2012). We presented the Slotbox overtly as a playful
game-like activity, and children appeared correspondingly to treat it as such by copying
the child over the adult. Furthermore, the device used in Wood et al. (2012) and McGuigan
et al. (2011) was much less transparently a toy for which a child would have privileged
knowledge, whereas the Slotbox was called a toy, and given that 3- to 5-year-olds are
known to select children over adults when the domain is toys (VanderBorght & Jaswal,
2009), this labeling could have created the preference for a child model. Our second
prediction, that the model age-based bias would be most pronounced when social information
lacked evidence of efficacy and efficiency because the demonstrations would create the
most uncertainty, was not supported. Neither efficacy (demonstration completeness) nor
efficiency (irrelevant actions) affected the strength of the initial model-based bias
toward child peers. The presence of the model age-based bias, when both models gave
demonstrations, varies from Wood et al. (2015), who found that children did not
distinguish between two peers who differed in previous proficiency when two equally valid
solutions were demonstrated. One explanation for this could be that the age contrast in
the current study may be considerably more salient than the peer proficiency contrast in
Wood et al. (2015) study. For the latter, the models differed in their general levels of
proficiency, as indexed by their behavior toward a novel apparatus as well as teacher
ratings. This subtler difference between models may have diluted children’s attention to
proficiency in the context of the test task. Indeed, the peer ratings of proficiency in
Wood et al. (2015) were dominated by age, such that children rated older peers as more
proficient than younger peers irrespective of their actual proficiency. Furthermore,
previous work has shown that even though children can identify models who “know” versus
“don’t know” how to do a task, their imitation of the model is driven more by their age
than by their professed knowledge state (Wood et al., 2012). An alternative explanation
for the current finding is that the preference for matching the child model, irrespective
of demonstration content, was driven by affiliative reasons rather than learning reasons
(Uzgiris, 1981). If children copy to affiliate, then it is of no consequence which method
is more effective. Affiliative versus learning goals may explain the discrepancy between
the current study and Hu et al. (2013), who found that a bias toward copying the majority
was lost when children could see that both methods worked. This “second” function of
imitation is receiving increasing attention (Over & Carpenter, 2012; Wood et al., 2013b)
and may be an important factor in children’s model-based social learning choices. Our
third prediction, that conservatism to the initial solution would be greatest when
children are uncertain of the alternative method, was partly supported. Children’s
continued interaction with the task revealed behavior differences across conditions.
Specifically, children who viewed both models using irrelevant actions were significantly
less likely to use both methods than children who viewed both models using relevant-only
actions. One possible explanation for why demonstrated irrelevant actions discouraged use
of the alternate method is that participants may have had more uncertainty about the
quality and competence of the demonstrations offered and so continued to use their initial
previous solution and were reluctant to try the alternative method. Conversely, when there
was a lack of irrelevant actions (and potentially more information regarding success),
this led to confidence in both models and, thus, exploration beyond children’s initial
bias and personal success. The current results support the hypothesis that a copy when
uncertain bias could promote conservatism to an original method and, thus, inhibit
exploration of an alternative method, as found with Wood et al. (2013a) and Bonawitz et
al. (2011). There was an additional result that was not specifically predicted; the select
few children with no demonstration who were successful tended not to use a tool,
instead—more efficiently perhaps—using their hand. This result again highlights both the
advantage and cost of using social information; demonstration children were much more
likely to be successful but also more likely to use a tool that was actually unnecessary
(cf. Nielsen & Tomaselli, 2010). We take this as further evidence that when children have
no prior information, social information can promote high-fidelity copying of demonstrated
actions (Wood et al., 2013a) to the point of copying inefficient components (McGuigan et
al., 2007). It would be interesting to investigate what the children with social
demonstrations would have done if the tools were removed during their response; would they
have been even less likely to succeed than children with no social demonstrations because
they were reliant on the social information of using a tool for success? Children’s biases
in social learning identified in this study are likely to have wider implications for our
understanding of social traditions. In the current study, the most likely context in which
a solution was socially learned and persisted over time was when it was performed by a
child and when the information was constrained (incomplete) and inefficient. Thus,
incipient traditions in the kind of context created in our experiment may be more likely
to form when there is limited scope for confidence in the approaches seen in models and
there are biases toward learning from individuals (in this case children) with certain
characteristics. Conversely, confidence in the quality of competing socially demonstrated
solutions may promote motivation for further exploration of alternative approaches
witnessed. A combination of social learning and exploration is thought to be the bedrock
of cumulative culture; thus, seeing multiple effective solutions from multiple models may
be an influential component in humans’ cumulative cultural capacities.


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<ART>“Selfie” harm: Effects on mood and body image in young women
============================================================

Authors: Jennifer S. Mills, Sarah Musto, Lindsay Williams, Marika Tiggemann
DOI: 10.1016/j.bodyim.2018.08.007
Year: 2018  |  Pages: 86-92
ASJC codes: 3200, 3202, 3207
Keywords: Anxiety, Body image, Confidence, Retouching, Self-presentation, Selfies, Social media

--------------------------------------------------------------------------------

<h>ABSTRACT</h>
--------

“Selfies” (self-taken photos) are a common self-presentation strategy on social media. This study experimentally tested whether taking and posting selfies, with and without photo-retouching, elicits changes to mood and body image among young women. Female undergraduate students (N = 110) were randomly assigned to one of three experimental conditions: taking and uploading either an untouched selfie, taking and posting a preferred and retouched selfie to social media, or a control group. State mood and body image were measured pre- and post-manipulation. As predicted, there was a main effect of experimental condition on changes to mood and feelings of physical attractiveness. Women who took and posted selfies to social media reported feeling more anxious, less confident, and less physically attractive afterwards compared to those in the control group. Harmful effects of selfies were found even when participants could retake and retouch their selfies. This is the first experimental study showing that taking and posting selfies on social media causes adverse psychological effects for women.

--------------------------------------------------------------------------------


<h>INTRODUCTION</h>
------------

Within the past decade, social networking has become a hugely popular form of online
communication, especially among young people (Perloff, 2014). Facebook, Instagram, and
Snapchat are among some of the most widely used social media platforms available and can
be accessed via computer, smartphone, computer tablet, and through other forms of
technology (Perloff, 2014). In comparison to conventional mass media, social media are
interactive, allowing individuals to create their own personal profiles and share
information and photos with users on their social network (Stefanone, Lackaff, & Rosen,
2011). A national survey by the Pew Research Center found that in the U.S., 18- to
29-year-olds who access the Internet are the most likely of any demographic group to use a
social networking (i.e., social media) site, and that women are more likely than men to
use these sites (Duggan & Brenner, 2013). Over 95% of college students regularly maintain
and manage their social networking profiles (Perloff, 2014; Stefanone et al., 2011).
Women, in particular, have been found to upload photos to social media more frequently
than do men, and tend to spend more time updating, managing, and maintaining their
personal profiles (Stefanone et al., 2011). Emerging evidence provides insight into the
effects that social media behaviours may have on users. On one hand, social media use may
be beneficial as it allows greater connectedness with others, leading to an increased
sense of well-being (Tiggemann & Miller, 2010). On the other hand, social media use may
lead to a preoccupation and focus on physical appearance, such as engagement in
appearance-related photo activities (Cohen, Newton-John, & Slater, 2017), which could
cause appearance concerns and lowered body image and self-esteem (de Vries, Peter, Nikken,
& de Graaf, 2014). As users are frequently exposed to a variety of other profiles, they
can compare their own appearance to friends, relatives, and strangers (Haferkamp & Kramer,
2011). Hancock and Toma (2009) found that people select their own online dating profile
photos in an attempt to look as attractive as possible without being judged to be
deceptive. Cross-sectional data have revealed that for both women and men, Facebook use is
associated with greater (upward) social comparison and self-objectification, which are
both related to lower self-esteem, poorer mental health, and body image concerns (Hanna et
al., 2017).

<hs>  Social media and body image</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~

Various studies have documented widespread body and weight dissatisfaction among girls and
women, and social media has been found to be a significant catalyst for these appearance
concerns (Brown & Tiggemann, 2016; Holland & Tiggemann, 2016; Tiggemann & Miller, 2010).
Given that social media provide the opportunity for social comparison, as well as exposure
to unrealistic beauty expectations, body dissatisfaction is likely to result from frequent
use (Fardouly, Pinkus, & Vartanian, 2017; Tiggemann & Slater, 2013; Want & Saiphoo, 2017).
Social media present innumerable idealized images of thin, lean/tone, beautiful, photo-
shopped women, and the “thin ideal” and “athletic ideal” are displayed as a normal,
desirable, and attainable body type for every woman (Kim & Chock, 2015; Meier & Gray,
2014; Robinson et al., 2017). Furthermore, the Internet and social media have been found
to promote thinness, dieting behavior, and weight loss through idealized images of
“perfect” women (Perloff, 2014). Women who use social media often internalize the “thin
ideal,” causing them to strive for an unrealistic, unnatural standard of beauty and to
feel ashamed when they are unable to achieve it (Kim & Chock, 2015; Meier & Gray, 2014;
Tiggemann & Slater, 2013). Studies have found that frequent exposure to the Internet and
social networking websites results in high levels of weight dissatisfaction, drive for
thinness, and body surveillance in young women (Tiggemann & Miller, 2010; Tiggemann &
Slater, 2013), regardless of race (Howard, Heron, MacIntyre, Myers, & Everhart, 2017).
Additionally, Perloff (2014) suggests that women who have relatively higher levels of thin
ideal internalization, perfectionism, and/or low self-esteem would be especially likely to
spend time on appearance-focused online comparisons and that they probably do not use
‘self-protective’ downward appearance comparisons (i.e., comparing their appearance to
less attractive friends). These predictions are concerning, since high body
dissatisfaction among women is a primary risk factor for the development of eating
disorders and is correlated with low self-esteem and depression (Meier & Gray, 2014;
Tiggemann & Miller, 2010). Therefore, it is important for researchers to understand the
causal effects that social media and self-presentation strategies have on young women by
using experimental research methods.

<hs>  Self-presentation and impression management</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Past research on the psychological effects of social media has mainly focused on the
implications of social media use for body satisfaction in general. However, there is a
lack of empirical research that evaluates the effects of the specific self-presentation
strategies that social media users rely on. According to Toma and Hancock (2010), self-
presentation involves “adjusting and editing the self during social interactions to create
a desired impression on the audience.” The motivation to selectively self-present also
relates to impression management, whereby individuals carefully present themselves in
order to make specific impressions on their viewers (Pounders, Kowalczyk, & Stowers,
2016). As a result, social media users are driven to present the most attractive versions
of themselves to others in order to make a favorable impression (Toma & Hancock, 2010).
These photos, however, often do not portray an accurate depiction of one’s true physical
appearance (Toma & Hancock, 2010). The most common way that users selectively self-present
on social media is through the taking and uploading of “selfies” (photos taken by and of
oneself). Users tend to capture selfies from flattering angles and using bright lighting,
and may also edit their photos using colour correction, skin-retouching, and even photo-
shopping to make body parts appear thinner (Anderson, Fagan, Woodnutt, & Chamorro-
Premuzic, 2012). In this way, social media users are able to manage the impressions they
have on others by presenting only the most flattering images of themselves and minimizing
perceived flaws or imperfections (Anderson et al., 2012; Bell, Cassarly, & Dunbar, 2018;
Pounders et al., 2016). It has also been found that individuals who desire to boost their
self-esteem upload selfies more frequently, and that women of 16–25 years of age spend up
to 5 h per week taking selfies and sharing them on social media (Pounders et al., 2016).
Research on gender differences in Internet activities has found that, compared to men,
women tend to be more motivated to create a positive self-presentation on their social
media profiles, and as a result, they engage in more photo-enhancement behaviours
(Haferkamp, Eimler, Papadakis, & Kruck, 2012; Toma & Hancock, 2010). Overall, research has
suggested that the taking and retouching of selfies may be a particularly risky behaviour
in terms of its potential to negatively impact the body image and self-esteem of young
girls and women.

<hs>  The current study</hs>
  ~~~~~~~~~~~~~~~~~

In summary, previous research demonstrates that social media use is positively correlated
with appearance concern. Furthermore, the literature suggests that selfie-taking and
photo-retouching, which are very common social media behaviours, are associated with
poorer self-esteem and body image among young women. It has been suggested that editing
and uploading selfies may worsen appearance concerns (de Vries et al., 2014), but it is
not yet known whether a causal relationship exists. To fill this gap in the literature,
the current study tested the effects of selfie taking on body image and mood in women. It
was hypothesized that updating one’s social media profile with a selfie photo would result
in lowered mood and increased body concerns as compared to a control group. To answer a
secondary research question, we also tested the effects of having control over self-
presentation on social media, by retaking and retouching a selfie photo, on women’s body
image and mood. It was hypothesized that participants who were allowed to retake and
retouch their selfie would experience better mood and body image compared to women who
were not allowed to modify their selfie before posting it on social media. This is because
women typically react to seeing a photo of themselves by feeling dissatisfied with their
appearance (Mills, Shikatani, Tiggemann, & Hollitt, 2014) and photo modification allows a
person to present an idealized version of themselves to others (Tiggemann & Miller, 2010).

<hs>  Participants</hs>
  ~~~~~~~~~~~~

Participants were 113 psychology undergraduate students recruited through an online
experiment management system at York University in Toronto, Canada. Inclusion criteria
included being female, being between 16 and 29 years old (M = 19.00, SD = 1.66), and
having an active account on Facebook or Instagram. In exchange for their participation in
a single, hour-long lab session, participants received partial course credit toward their
Introduction to Psychology course. The self-reported ethnic distribution of the sample was
24.8% South Asian, 20.2% European/Caucasian, 12.8% Black/African-American, 10.1% Middle
Eastern, 9.2 Caribbean, 6.4% Pacific Islands American, 5.5% East Asian, 2.8% Latino/
Hispanic, and 8.2% other ethnic identification. Body mass index (BMI = kg/m2) scores
ranged from 15.84 to 36.23 (M = 23.71, SD = 4.03) across the sample, with the mode,
median, and mean all falling within the “normal” weight range (18.5 < BMI <24.9) (Centers
for Disease Control & Prevention, 2015). One participant who mistakenly signed up for the
study was excluded because he self-identified as male. Two participants declined to
participate after reading the informed consent form because they were uncomfortable taking
a photo of themselves for religious reasons.

        iPad

        Participants used the Internet browser, camera, and photo modification app (“You-
        Cam Now”), if applicable, installed on an iPad.

        <hss>Mood and body image</hss>

        A series of visual analogue scales (VAS) was used to measure mood and body image
        at baseline as well as after the experimental manipulation (described below). This
        commonly used set of scales was designed to assess pre-post fluctuations in
        psychological states, typically in experimental research designs (Heinberg &
        Thompson, 1995). The measure consisted of six VAS, each with a 10-centimeter
        horizontal line labeled with a specific attitude or emotional state. Participants
        are asked to place an X on the point on the line that most accurately depicts the
        degree to which they were experiencing that feeling at the moment, from Not at all
        to Very much. The mood items included anxiety, depression, and confidence. The
        body image items included feelings of fatness, physical attractiveness, and body
        size satisfaction. Rather than collapsing scores into global affect or appearance
        concerns, we separated the items so that we could examine specific affective
        changes among participants. VAS format is recommended over Likert scales for pre-
        post research designs since it reduces recall bias (i.e., participants cannot
        recall their previous response), can be completed quickly, is sensitive to
        emotional changes (Hargreaves & Tiggemann, 2003). The measure used in the current
        study is the same one used in other published studies.

        <hss>Demographics</hss>

        Age and race/ethnicity demographics were collected from each participant. Filler
        items not of interest to the study were included on the questionnaire (e.g.,
        living arrangements, year of study, university program, and media consumption).

<hs>  Procedure</hs>
  ~~~~~~~~~

Ethics approval was received from York University’s Human Participants Review Committee.
Female undergraduate students volunteered for an advertised study examining “the
relationship between personality and social media use.” Participants were tested
individually behind a partition wall from the experimenter and were asked to leave their
bags and any personal electronic devices (including phones) outside of the testing area.
Participants were randomly assigned to one of three experimental conditions prior to
arriving at the lab. Upon arrival to the lab, participants read and signed a written
informed consent form, were given a baseline VAS, and then the demographics questionnaire
with additional filler items to distract from the purpose of the study. For ethical
reasons, the informed consent form contained the information that participants may be
asked to post a selfie to their own social media profile. For the experimental task,
participants in the Untouched Selfie condition were asked to take a single photo (a
headshot) on the lab’s iPad and upload it to their preferred social media profile
(Facebook or Instagram). Participants in the Retouched Selfie condition were asked to take
one or more photos of themselves on the lab’s iPad and were told that they could use the
photo editing app installed on the iPad to retouch the photo to their satisfaction before
uploading it to their social media profile. Participants in the Control condition were
also given the lab’s iPad but were asked to read a short article from a social media news
website chosen for neutral, non-appearance related content (i.e., popular travel ideas for
university students) and to answer questions about the article. This task was chosen to
maintain the cover study of social media use and to control for using an iPad, and for the
amount of time elapsed between pre-post measures. It was intentional that Control
condition participants not engage on Facebook or Instagram (theirs or other people’s
profiles, since we could not be certain that they were not exposed to appearance-related
content, which could affect mood and/or body image). The assigned tasks in the Untouched
Selfie and Control conditions were timed (5 min each). The Retouched Selfie condition was
not timed so that participants could retake and retouch their selfie to their
satisfaction. However, time to completion was recorded by the experimenter and
participants in the Retouched Selfie condition took a similar amount of time to complete
their task (mean time to completion = 4.5 min). Instructions and set up in all three
conditions took approximately 1–2 min. As manipulation checks, Control condition
participants were asked to answer written questions about their article to ensure that
they read the article. Selfie condition participants were asked verbally by the
experimenter whether they completed the tasks as instructed. In addition, at the end of
the study the experimenter checked the photo and browser histories, and any deleted files
on the iPad to ensure that participants in all conditions adhered to the instructions and
did not open any other websites or social media profiles. All participants confirmed that
they followed the instructions and there was no evidence of non-adherence. Upon completion
of the experimental tasks, all participants completed the post-manipulation VAS.
Participants were asked to complete the scales based on how they were feeling at that
particular moment. The elapsed time between the baseline and post-manipulation VAS measure
was approximately 10 min. Furthermore, the format of the VAS scale is such that
participants cannot recall their previous answer; thus, recall bias is minimized.
Participants were then debriefed and probed as to what they believed to be the purpose of
the study. Lastly, height and weight were measured by the experimenter on a balance beam
scale.

<hs>  Data analysis</hs>
  ~~~~~~~~~~~~~

Statistical analyses were conducted using SPSS version 24. An alpha level of .05 was used
for significance testing. A power analysis was conducted using G*Power (Faul, Erdfelder,
Lang, & Buchner, 2007); an alpha of .05, medium effect size, and power estimate of .80
resulted in a recommended sample size of 110, which was obtained. Repeated measures
analysis (Time 1 – Time 2) was chosen to analyze the effects of experimental condition
instead of VAS change scores to maximize power and use within-subject error estimates. To
control for Type I error, an initial repeated measures multivariate analysis of variance
(RM-MANOVA) was performed with time (Time 1 – Time 2) and test (VAS item) as the within-
subject factors, and experimental condition (Untouched Selfie, Retouched Selfie, and
Control) as the between-subjects factor. Any significant multivariate 3-way interaction
(time × test × condition) on the combined dependent measures was followed by univariate
repeated measures ANOVAs, with time (Time 1 – Time 2) as the within-subject factor and
experimental condition as the between-subjects factor. Any significant within-subjects
contrasts (time × condition) were followed by post-hoc t-tests to examine which conditions
differed. For ease of interpretation, change scores (Time 1 – Time 2) were used only for
these post hoc t-tests to examine the direction and magnitude of change to psychological
states as a function of condition.

<hs>  Preliminary analyses</hs>
  ~~~~~~~~~~~~~~~~~~~~

Inspection of histograms, skewness, and kurtosis suggested that all of the variables were
normally distributed. There were no statistical outliers (± 3.0 SD) among the dependent
variables; therefore, no adjustments were made. Groups did not differ significantly on
baseline levels of any variable, suggesting that randomization resulted in equivalent
groups.

<hs>  Multivariate effects of experimental condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Means and standard deviations for all dependent variables of interest (pre- and post-
manipulation) as a function of the experimental condition are shown in Table 1. For ease
of interpretation, Table 1 also shows the change in participants’ self-ratings across the
psychological states. A significant 3-way (test × time × condition) multivariate effect on
the combined dependent variables was found, Hotelling’s Trace = .21, F(10, 201) = 2.14, p
=  .02, partial η2 = .10, meaning that the experimental groups differed with respect to
how mood and body image ratings changed between Time 1 and Time 2. Significant 2-way (time
× condition) interactions were found for anxiety, Hotelling’s Trace = .06, F(2, 107) =
3.32, p =  .04, partial η2 = .06, confidence, Hotelling’s Trace = .07, F(2, 107) = 3.69, p
=  .03, partial η2 = .07, and physical attractiveness, Hotelling’s Trace = .07, F(2, 107)
= 3.59, p =  .03, partial η2 = .06, meaning that the experimental groups were not equal
with respect to changes on those items from Time 1 to Time 2. Interactions were not
significant for depression, Hotelling’s Trace = .01, F(2, 107) = 0.48, p =  .62, feelings
of fatness, Hotelling’s Trace = .02, F(2, 107) = 0.97, p =  .38, or satisfaction with body
size, Hotelling’s Trace = .01, F(2, 107) = 0.75, p =  .47.

<hs>  Changes to psychological states as a function of condition</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The significant 2-way interactions reported above were followed up with t-tests to compare
changes to psychological states across experimental groups. As can be seen in Fig. 1,
participants in the Untouched Selfie condition experienced an increase in anxiety and this
was significantly greater than the Control condition t(71) = 2.35, p =  .02. The Retouched
Selfie condition also experienced an increase in anxiety but was not significantly
different from the Control condition, t(71) = 1.80, p =  .08. The Untouched and the
Retouched Selfie conditions did not differ with respect to changes in anxiety, t(71) =
0.79, p =  .43. Fig. 2 shows that participants in the Untouched Selfie condition
experienced a decrease in confidence and this was significantly greater than the Control
condition, t(71) = 2.48, p =  .01, and marginally greater than that experienced in the
Retouched Selfie conditions t(72) = 1.92, p =  .06. There was no difference in changes to
feelings of confidence between the Retouched Selfie and Control conditions, t(71) = 0.60,
p =  .55. Fig. 3 shows that participants experienced decreases in feelings of physical
attractiveness that were significantly greater than in the Control condition in both the
Untouched Selfie condition, t(71) = 2.43, p =  .02, and the Retouched Selfie condition,
t(71) = 2.32, p =  .02. These decreases were equivalent between the two selfie conditions
t(72) = 0.12, p =  .90.

<h>DISCUSSION</h>
----------

This is the first experimental study of the causal effects of posting selfies to social
media on young women. The findings generally supported our hypothesis that taking and
posting a selfie on social media would result in lowered mood and worsened self-image. We
also found that women who had the opportunity to retake and modify their selfie before
posting it to social media still experienced decreases to mood and anxiety that were
similar to the reactions of those who could not retouch their photo. Participants who took
and uploaded a selfie onto social media, without the option to retouch or take multiple
photos, felt more anxious, less confident, and less physically attractive afterward, and
these differences were significantly greater than the control condition (i.e., reading a
neutral news article online). These results all yielded medium effect sizes. These
findings are consistent with the previous suggestion that appearance concerns are
heightened when women interact with and construct their social media profiles, manifesting
in poorer body image and mood (e.g., de Vries et al., 2014). However, we did not find
significant effects of selfie-taking on all of the dependent variables of interest in the
current study; we found null effects on state feelings of fatness, satisfaction with one’s
body, and depression. We interpret these findings to suggest that the psychological states
affected by taking and posting selfies to social media are specifically related to
feelings of self-consciousness and/or fear of negative evaluation by others. This
interpretation seems likely given that participants in the study were sharing their selfie
photos on their own social media profiles and for other people they know to see. It is
interesting that feelings of physical attractiveness were negatively affected by selfie
taking and posting, but not feelings of fatness or satisfaction with one’s body size.
However, it is important to note that the current study involved taking a photo only of
one’s head and face. In other words, it may not be surprising that effects of taking a
selfie on body-related constructs were not found, since the current study looked only at
the effects of taking selfies of one’s face. If the current study had examined the effect
of taking and posting photos that showed the participant’s body the results might have
been different. Celebrities, but probably many social media users, often post body-
conscious selfies on their social media (e.g., wearing bathing suits, lingerie, or no
clothing at all). Posting selfies of one’s body (and not just the face), even when
clothed, could trigger body-specific appearance concerns but we did not capture those
effects in the current study. This is an area for future research. We had a secondary
research question related to whether being able to retake, select, and modify one’s selfie
(as is commonly done by many social media users) might, in fact, improve subsequent mood
or body image. As suggested by Kim and Chock (2015), women are motivated to present
perfected images and idealized versions of themselves on their social media profiles in
order to make a favorable impression on their viewers. Photo-retouching behaviours allow
women to present the most attractive versions of themselves and minimize perceived
imperfections (Toma & Hancock, 2010). In the current study, women in the retouched selfie
condition were able to take multiple photos, delete unwanted photos, and could retouch
their photos to their satisfaction using a photo editing application. However, we found
little evidence of any psychological benefit of being able to modify the photo women
posted to their social media. In terms of state anxiety, women who posted an untouched
selfie to social media felt significantly more anxious than those who did not post a
selfie at all. But women who were able to retouch their selfie before posting it also felt
marginally more anxious than those in the control condition and equally anxious to those
in the untouched selfie group. In other words, having the ability to retake and retouch
their selfie to their satisfaction before posting it did not mitigate women’s anxiety
significantly. This lack of difference between the effects of the two experimental selfie
tasks on anxiety was unexpected. A similar result was found regarding feelings of physical
attractiveness. Participants who could retouch their selfie felt significantly less
attractive after posting it online (as did those who were asked to post an untouched
selfie), and there was no significant difference between the retouched and untouched
selfie groups on changes to feelings of physical attractiveness. In terms of feelings of
confidence, women who could retouch their selfie did feel more confident afterward than
those in the untouched selfie group, but they felt just as confident as those who did not
post a selfie at all. In other words, posting a retouched selfie did not improve women’s
confidence, as compared to engaging in an appearance-neutral task. To explain these
findings, it could be that scrutinizing and modifying images of themselves makes women
think more about their flaws or imperfections. Retouching could activate feelings of self-
objectification. Even though self-presentation strategies like photo-editing provide a
sense of control over physical appearance (Tiggemann & Miller, 2010), they do not actually
appear to improve mood or self-image. The current study found no evidence that posting
retouched photos to social media makes women feel better than usual and found some
evidence that it makes them feel worse than usual. Although women might feel less anxious
about posting a selfie if they have the chance to retouch it and make it more flattering,
the process of taking and editing the photo still draws their attention to feeling
dissatisfied about aspects of their appearance.

<hs>  Clinical implications</hs>
  ~~~~~~~~~~~~~~~~~~~~~

These findings have clinical implications for the prevention and treatment of mental
health difficulties. Women who took a selfie and posted it to their social media profile
had increased levels of anxiety, decreased confidence, and lowered perceived physical
attractiveness compared to those who did not take a selfie. Given that women between 16–25
years of age spend up to 5 h per week taking selfies and uploading them to their personal
profiles (Pounders et al., 2016), these findings raise significant concern about social
media use and well-being. Posting selfies to one’s social media has adverse causal effects
on the self-image and mood of young women, and could make them more vulnerable to clinical
eating, mood, and/or anxiety disorders. Frequently taking selfies could be considered a
body checking behavior, such as repeated weighing and recurrent checking of one’s
reflection in mirrors (Mills et al., 2014). As a result, frequently taking and posting
selfies should be considered a risky online health-related behavior for young women in
terms of mental health, especially if they trigger weight and shape dissatisfaction. High
body dissatisfaction is the primary risk factor for the development of eating disorders
and is correlated with low self-esteem and depression (Meier & Gray, 2014; Tiggemann &
Miller, 2010). Interventions that aim to diminish or eliminate the harmful effects of
social media engagement on psychological functioning should be validated and implemented.

<hs>  Limitations and future directions</hs>
  ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

A unidirectional causal relationship between posting selfies to social media and worsened
mood and body image was demonstrated in the current study. The reverse relationship – the
effect of low mood or body dissatisfaction on posting selfies – is a future research
question of importance. There could be a bidirectional and self-perpetuating cycle between
appearance-based social media engagement and negative mood and/or body image. Because the
current sample included only young women who regularly use social media, these results may
not generalize to older women or women who do not use social media. We did not include men
since the existing literature on social media and body image has focused on women. Future
studies should include men and relevant appearance-related psychological constructs (e.g.,
drive for muscularity; Mills & D’Alfonso, 2007). For ethical reasons, participants were
informed on the consent form that they may be asked to take a photograph of themselves and
post it to social media. We attempted to minimize demand characteristics by including
filler questions between repeated measures, by using the visual analogue scale format, by
stating the purpose of the study in only vague terms, and by probing what participants
thought to be the true purpose of the study. There was no evidence that demand
characteristics were a threat to the validity of the study. Nevertheless, it is possible
that participants might have had implicit assumptions about the effects of the
experimental tasks on how they felt. We did not examine personality moderators in the
current study; future research should investigate individual differences and whether
certain types of women (e.g., those who are high on perfectionism, those who frequently
post selfies in their everyday lives) are more or less vulnerable to the adverse effects
of posting selfies to social media than others. Future research should also study the
specific modifications that participants make to their photos using retouching. We did not
include this outcome variable in the current study, but future studies could explore ways
of assessing selfie modification behaviours surreptitiously. Participants in the control
condition of the current study did not interact on social media to avoid any possible
exposure to appearance-related online content and to make the control condition entirely
appearance neutral. However, a different control task (e.g., uploading a neutral, non-
selfie photo to social media) might produce different results. Therefore, an important
next step is to dismantle what aspects of posting selfies to social media produce the
observed effects (e.g., taking selfies without posting them on social media). Finally,
future research should examine the longer term and/or cumulative effects of posting
selfies to social media using prospective, longitudinal research designs.

<h>CONCLUSIONS</h>
-----------

This is the first study to show experimentally that selfie posting on social media is
harmful in terms of young women’s mood and self-image. Being able to retouch or modify
their photo did not result in women feeling better about themselves after posting a selfie
to social media. Future research should look at the longer-term effects of posting photos
of oneself on social media, which is an increasingly common aspect of contemporary media
use.


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